hypothesis on language

Sapir–Whorf hypothesis (Linguistic Relativity Hypothesis)

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There are about seven thousand languages heard around the world – they all have different sounds, vocabularies, and structures. As you know, language plays a significant role in our lives.

But one intriguing question is – can it actually affect how we think?

It is widely thought that reality and how one perceives the world is expressed in spoken words and are precisely the same as reality.

That is, perception and expression are understood to be synonymous, and it is assumed that speech is based on thoughts. This idea believes that what one says depends on how the world is encoded and decoded in the mind.

However, many believe the opposite.

In that, what one perceives is dependent on the spoken word. Basically, that thought depends on language, not the other way around.

What Is The Sapir-Whorf Hypothesis?

Twentieth-century linguists Edward Sapir and Benjamin Lee Whorf are known for this very principle and its popularization. Their joint theory, known as the Sapir-Whorf Hypothesis or, more commonly, the Theory of Linguistic Relativity, holds great significance in all scopes of communication theories.

The Sapir-Whorf hypothesis states that the grammatical and verbal structure of a person’s language influences how they perceive the world. It emphasizes that language either determines or influences one’s thoughts.

The Sapir-Whorf hypothesis states that people experience the world based on the structure of their language, and that linguistic categories shape and limit cognitive processes. It proposes that differences in language affect thought, perception, and behavior, so speakers of different languages think and act differently.

For example, different words mean various things in other languages. Not every word in all languages has an exact one-to-one translation in a foreign language.

Because of these small but crucial differences, using the wrong word within a particular language can have significant consequences.

The Sapir-Whorf hypothesis is sometimes called “linguistic relativity” or the “principle of linguistic relativity.” So while they have slightly different names, they refer to the same basic proposal about the relationship between language and thought.

How Language Influences Culture

Culture is defined by the values, norms, and beliefs of a society. Our culture can be considered a lens through which we undergo the world and develop a shared meaning of what occurs around us.

The language that we create and use is in response to the cultural and societal needs that arose. In other words, there is an apparent relationship between how we talk and how we perceive the world.

One crucial question that many intellectuals have asked is how our society’s language influences its culture.

Linguist and anthropologist Edward Sapir and his then-student Benjamin Whorf were interested in answering this question.

Together, they created the Sapir-Whorf hypothesis, which states that our thought processes predominantly determine how we look at the world.

Our language restricts our thought processes – our language shapes our reality. Simply, the language that we use shapes the way we think and how we see the world.

Since the Sapir-Whorf hypothesis theorizes that our language use shapes our perspective of the world, people who speak different languages have different views of the world.

In the 1920s, Benjamin Whorf was a Yale University graduate student studying with linguist Edward Sapir, who was considered the father of American linguistic anthropology.

Sapir was responsible for documenting and recording the cultures and languages of many Native American tribes disappearing at an alarming rate. He and his predecessors were well aware of the close relationship between language and culture.

Anthropologists like Sapir need to learn the language of the culture they are studying to understand the worldview of its speakers truly. Whorf believed that the opposite is also true, that language affects culture by influencing how its speakers think.

His hypothesis proposed that the words and structures of a language influence how its speaker behaves and feels about the world and, ultimately, the culture itself.

Simply put, Whorf believed that you see the world differently from another person who speaks another language due to the specific language you speak.

Human beings do not live in the matter-of-fact world alone, nor solitary in the world of social action as traditionally understood, but are very much at the pardon of the certain language which has become the medium of communication and expression for their society.

To a large extent, the real world is unconsciously built on habits in regard to the language of the group. We hear and see and otherwise experience broadly as we do because the language habits of our community predispose choices of interpretation.

Studies & Examples

The lexicon, or vocabulary, is the inventory of the articles a culture speaks about and has classified to understand the world around them and deal with it effectively.

For example, our modern life is dictated for many by the need to travel by some vehicle – cars, buses, trucks, SUVs, trains, etc. We, therefore, have thousands of words to talk about and mention, including types of models, vehicles, parts, or brands.

The most influential aspects of each culture are similarly reflected in the dictionary of its language. Among the societies living on the islands in the Pacific, fish have significant economic and cultural importance.

Therefore, this is reflected in the rich vocabulary that describes all aspects of the fish and the environments that islanders depend on for survival.

For example, there are over 1,000 fish species in Palau, and Palauan fishers knew, even long before biologists existed, details about the anatomy, behavior, growth patterns, and habitat of most of them – far more than modern biologists know today.

Whorf’s studies at Yale involved working with many Native American languages, including Hopi. He discovered that the Hopi language is quite different from English in many ways, especially regarding time.

Western cultures and languages view times as a flowing river that carries us continuously through the present, away from the past, and to the future.

Our grammar and system of verbs reflect this concept with particular tenses for past, present, and future.

We perceive this concept of time as universal in that all humans see it in the same way.

Although a speaker of Hopi has very different ideas, their language’s structure both reflects and shapes the way they think about time. Seemingly, the Hopi language has no present, past, or future tense; instead, they divide the world into manifested and unmanifest domains.

The manifested domain consists of the physical universe, including the present, the immediate past, and the future; the unmanifest domain consists of the remote past and the future and the world of dreams, thoughts, desires, and life forces.

Also, there are no words for minutes, minutes, or days of the week. Native Hopi speakers often had great difficulty adapting to life in the English-speaking world when it came to being on time for their job or other affairs.

It is due to the simple fact that this was not how they had been conditioned to behave concerning time in their Hopi world, which followed the phases of the moon and the movements of the sun.

Today, it is widely believed that some aspects of perception are affected by language.

One big problem with the original Sapir-Whorf hypothesis derives from the idea that if a person’s language has no word for a specific concept, then that person would not understand that concept.

Honestly, the idea that a mother tongue can restrict one’s understanding has been largely unaccepted. For example, in German, there is a term that means to take pleasure in another person’s unhappiness.

While there is no translatable equivalent in English, it just would not be accurate to say that English speakers have never experienced or would not be able to comprehend this emotion.

Just because there is no word for this in the English language does not mean English speakers are less equipped to feel or experience the meaning of the word.

Not to mention a “chicken and egg” problem with the theory.

Of course, languages are human creations, very much tools we invented and honed to suit our needs. Merely showing that speakers of diverse languages think differently does not tell us whether it is the language that shapes belief or the other way around.

Supporting Evidence

On the other hand, there is hard evidence that the language-associated habits we acquire play a role in how we view the world. And indeed, this is especially true for languages that attach genders to inanimate objects.

There was a study done that looked at how German and Spanish speakers view different things based on their given gender association in each respective language.

The results demonstrated that in describing things that are referred to as masculine in Spanish, speakers of the language marked them as having more male characteristics like “strong” and “long.” Similarly, these same items, which use feminine phrasings in German, were noted by German speakers as effeminate, like “beautiful” and “elegant.”

The findings imply that speakers of each language have developed preconceived notions of something being feminine or masculine, not due to the objects” characteristics or appearances but because of how they are categorized in their native language.

It is important to remember that the Theory of Linguistic Relativity (Sapir-Whorf Hypothesis) also successfully achieves openness. The theory is shown as a window where we view the cognitive process, not as an absolute.

It is set forth to look at a phenomenon differently than one usually would. Furthermore, the Sapir-Whorf Hypothesis is very simple and logically sound. Understandably, one’s atmosphere and culture will affect decoding.

Likewise, in studies done by the authors of the theory, many Native American tribes do not have a word for particular things because they do not exist in their lives. The logical simplism of this idea of relativism provides parsimony.

Truly, the Sapir-Whorf Hypothesis makes sense. It can be utilized in describing great numerous misunderstandings in everyday life. When a Pennsylvanian says “yuns,” it does not make any sense to a Californian, but when examined, it is just another word for “you all.”

The Linguistic Relativity Theory addresses this and suggests that it is all relative. This concept of relativity passes outside dialect boundaries and delves into the world of language – from different countries and, consequently, from mind to mind.

Is language reality honestly because of thought, or is it thought which occurs because of language? The Sapir-Whorf Hypothesis very transparently presents a view of reality being expressed in language and thus forming in thought.

The principles rehashed in it show a reasonable and even simple idea of how one perceives the world, but the question is still arguable: thought then language or language then thought?

Modern Relevance

Regardless of its age, the Sapir-Whorf hypothesis, or the Linguistic Relativity Theory, has continued to force itself into linguistic conversations, even including pop culture.

The idea was just recently revisited in the movie “Arrival,” – a science fiction film that engagingly explores the ways in which an alien language can affect and alter human thinking.

And even if some of the most drastic claims of the theory have been debunked or argued against, the idea has continued its relevance, and that does say something about its importance.

Hypotheses, thoughts, and intellectual musings do not need to be totally accurate to remain in the public eye as long as they make us think and question the world – and the Sapir-Whorf Hypothesis does precisely that.

The theory does not only make us question linguistic theory and our own language but also our very existence and how our perceptions might shape what exists in this world.

There are generalities that we can expect every person to encounter in their day-to-day life – in relationships, love, work, sadness, and so on. But thinking about the more granular disparities experienced by those in diverse circumstances, linguistic or otherwise, helps us realize that there is more to the story than ours.

And beautifully, at the same time, the Sapir-Whorf Hypothesis reiterates the fact that we are more alike than we are different, regardless of the language we speak.

Isn’t it just amazing that linguistic diversity just reveals to us how ingenious and flexible the human mind is – human minds have invented not one cognitive universe but, indeed, seven thousand!

Kay, P., & Kempton, W. (1984). What is the Sapir‐Whorf hypothesis?. American anthropologist, 86(1), 65-79.

Whorf, B. L. (1952). Language, mind, and reality. ETC: A review of general semantics, 167-188.

Whorf, B. L. (1997). The relation of habitual thought and behavior to language. In Sociolinguistics (pp. 443-463). Palgrave, London.

Whorf, B. L. (2012). Language, thought, and reality: Selected writings of Benjamin Lee Whorf. MIT press.

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The Sapir-Whorf Hypothesis: How Language Influences How We Express Ourselves

Rachael is a New York-based writer and freelance writer for Verywell Mind, where she leverages her decades of personal experience with and research on mental illness—particularly ADHD and depression—to help readers better understand how their mind works and how to manage their mental health.

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What to Know About the Sapir-Whorf Hypothesis

Real-world examples of linguistic relativity, linguistic relativity in psychology.

The Sapir-Whorf Hypothesis, also known as linguistic relativity, refers to the idea that the language a person speaks can influence their worldview, thought, and even how they experience and understand the world.

While more extreme versions of the hypothesis have largely been discredited, a growing body of research has demonstrated that language can meaningfully shape how we understand the world around us and even ourselves.

Keep reading to learn more about linguistic relativity, including some real-world examples of how it shapes thoughts, emotions, and behavior.  

The hypothesis is named after anthropologist and linguist Edward Sapir and his student, Benjamin Lee Whorf. While the hypothesis is named after them both, the two never actually formally co-authored a coherent hypothesis together.

This Hypothesis Aims to Figure Out How Language and Culture Are Connected

Sapir was interested in charting the difference in language and cultural worldviews, including how language and culture influence each other. Whorf took this work on how language and culture shape each other a step further to explore how different languages might shape thought and behavior.

Since then, the concept has evolved into multiple variations, some more credible than others.

Linguistic Determinism Is an Extreme Version of the Hypothesis

Linguistic determinism, for example, is a more extreme version suggesting that a person’s perception and thought are limited to the language they speak. An early example of linguistic determinism comes from Whorf himself who argued that the Hopi people in Arizona don’t conjugate verbs into past, present, and future tenses as English speakers do and that their words for units of time (like “day” or “hour”) were verbs rather than nouns.

From this, he concluded that the Hopi don’t view time as a physical object that can be counted out in minutes and hours the way English speakers do. Instead, Whorf argued, the Hopi view time as a formless process.

This was then taken by others to mean that the Hopi don’t have any concept of time—an extreme view that has since been repeatedly disproven.

There is some evidence for a more nuanced version of linguistic relativity, which suggests that the structure and vocabulary of the language you speak can influence how you understand the world around you. To understand this better, it helps to look at real-world examples of the effects language can have on thought and behavior.

Different Languages Express Colors Differently

Color is one of the most common examples of linguistic relativity. Most known languages have somewhere between two and twelve color terms, and the way colors are categorized varies widely. In English, for example, there are distinct categories for blue and green .

Blue and Green

But in Korean, there is one word that encompasses both. This doesn’t mean Korean speakers can’t see blue, it just means blue is understood as a variant of green rather than a distinct color category all its own.

In Russian, meanwhile, the colors that English speakers would lump under the umbrella term of “blue” are further subdivided into two distinct color categories, “siniy” and “goluboy.” They roughly correspond to light blue and dark blue in English. But to Russian speakers, they are as distinct as orange and brown .

In one study comparing English and Russian speakers, participants were shown a color square and then asked to choose which of the two color squares below it was the closest in shade to the first square.

The test specifically focused on varying shades of blue ranging from “siniy” to “goluboy.” Russian speakers were not only faster at selecting the matching color square but were more accurate in their selections.

The Way Location Is Expressed Varies Across Languages

This same variation occurs in other areas of language. For example, in Guugu Ymithirr, a language spoken by Aboriginal Australians, spatial orientation is always described in absolute terms of cardinal directions. While an English speaker would say the laptop is “in front of” you, a Guugu Ymithirr speaker would say it was north, south, west, or east of you.

As a result, Aboriginal Australians have to be constantly attuned to cardinal directions because their language requires it (just as Russian speakers develop a more instinctive ability to discern between shades of what English speakers call blue because their language requires it).

So when you ask a Guugu Ymithirr speaker to tell you which way south is, they can point in the right direction without a moment’s hesitation. Meanwhile, most English speakers would struggle to accurately identify South without the help of a compass or taking a moment to recall grade school lessons about how to find it.

The concept of these cardinal directions exists in English, but English speakers aren’t required to think about or use them on a daily basis so it’s not as intuitive or ingrained in how they orient themselves in space.

Just as with other aspects of thought and perception, the vocabulary and grammatical structure we have for thinking about or talking about what we feel doesn’t create our feelings, but it does shape how we understand them and, to an extent, how we experience them.

Words Help Us Put a Name to Our Emotions

For example, the ability to detect displeasure from a person’s face is universal. But in a language that has the words “angry” and “sad,” you can further distinguish what kind of displeasure you observe in their facial expression. This doesn’t mean humans never experienced anger or sadness before words for them emerged. But they may have struggled to understand or explain the subtle differences between different dimensions of displeasure.

In one study of English speakers, toddlers were shown a picture of a person with an angry facial expression. Then, they were given a set of pictures of people displaying different expressions including happy, sad, surprised, scared, disgusted, or angry. Researchers asked them to put all the pictures that matched the first angry face picture into a box.

The two-year-olds in the experiment tended to place all faces except happy faces into the box. But four-year-olds were more selective, often leaving out sad or fearful faces as well as happy faces. This suggests that as our vocabulary for talking about emotions expands, so does our ability to understand and distinguish those emotions.

But some research suggests the influence is not limited to just developing a wider vocabulary for categorizing emotions. Language may “also help constitute emotion by cohering sensations into specific perceptions of ‘anger,’ ‘disgust,’ ‘fear,’ etc.,” said Dr. Harold Hong, a board-certified psychiatrist at New Waters Recovery in North Carolina.

As our vocabulary for talking about emotions expands, so does our ability to understand and distinguish those emotions.

Words for emotions, like words for colors, are an attempt to categorize a spectrum of sensations into a handful of distinct categories. And, like color, there’s no objective or hard rule on where the boundaries between emotions should be which can lead to variation across languages in how emotions are categorized.

Emotions Are Categorized Differently in Different Languages

Just as different languages categorize color a little differently, researchers have also found differences in how emotions are categorized. In German, for example, there’s an emotion called “gemütlichkeit.”

While it’s usually translated as “cozy” or “ friendly ” in English, there really isn’t a direct translation. It refers to a particular kind of peace and sense of belonging that a person feels when surrounded by the people they love or feel connected to in a place they feel comfortable and free to be who they are.

Harold Hong, MD, Psychiatrist

The lack of a word for an emotion in a language does not mean that its speakers don't experience that emotion.

You may have felt gemütlichkeit when staying up with your friends to joke and play games at a sleepover. You may feel it when you visit home for the holidays and spend your time eating, laughing, and reminiscing with your family in the house you grew up in.

In Japanese, the word “amae” is just as difficult to translate into English. Usually, it’s translated as "spoiled child" or "presumed indulgence," as in making a request and assuming it will be indulged. But both of those have strong negative connotations in English and amae is a positive emotion .

Instead of being spoiled or coddled, it’s referring to that particular kind of trust and assurance that comes with being nurtured by someone and knowing that you can ask for what you want without worrying whether the other person might feel resentful or burdened by your request.

You might have felt amae when your car broke down and you immediately called your mom to pick you up, without having to worry for even a second whether or not she would drop everything to help you.

Regardless of which languages you speak, though, you’re capable of feeling both of these emotions. “The lack of a word for an emotion in a language does not mean that its speakers don't experience that emotion,” Dr. Hong explained.

What This Means For You

“While having the words to describe emotions can help us better understand and regulate them, it is possible to experience and express those emotions without specific labels for them.” Without the words for these feelings, you can still feel them but you just might not be able to identify them as readily or clearly as someone who does have those words. 

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By Rachael Green Rachael is a New York-based writer and freelance writer for Verywell Mind, where she leverages her decades of personal experience with and research on mental illness—particularly ADHD and depression—to help readers better understand how their mind works and how to manage their mental health.

Modern Theories of Language

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Embodied language processing ; Emergentist approaches to language ; Sociocultural theories of language ; Usage-based linguistics

Modern theories of language represent efforts to account for the evolution, acquisition, and processing of language within an integrated framework. Such efforts acknowledge the relationship of language to sensorimotor experience, social interaction, and general cognitive constraints on information processing.

Introduction

The study of language is a diverse field that engages the applied interests of educators and speech pathologists as well as the academic interests of researchers working in wide range of disciplines including linguistics, speech and hearing sciences, psychology, biology, computer science, philosophy, sociology, and anthropology. Scholars in these different disciplines invariably conceptualize language in different ways, viewing it, e.g., as a biological attribute, a cultural trait, a set of communication skills, or a...

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April 25, 2024

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Elizabeth Bates and the Search for the Roots of Human Language

In the 1970s a young psychologist challenged a popular theory of how we acquire language, launching a fierce debate that continues to this day

By Samia Bouzid , Katie Hafner & The Lost Women of Science Initiative

Keren Mevorach ( illustration ); Courtesy of George Carnevale ( photograph )

“We were each put on Earth to torment the other,” says cognitive scientist Steven Pinker in reference to Elizabeth Bates, a psychologist who challenged a prevailing theory about how humans acquire language. Bates believed that language emerges from interactions between our brain and our environments and that we do not have an innate language capacity. To many, that sounds like an innocuous statement. But in making these claims starting in the 1970s, Bates challenged formidable linguists such as Noam Chomsky and, later, Pinker, placing herself at the center of a heated debate that remains unresolved half a century later.

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Katie Hafner : In the 1970s, a psychology Ph.D., fresh out of grad school, decided to take on one of the biggest names in linguistics, Noam Chomsky. Her name was Elizabeth Bates, and over the decades she would become one of the most vocal opponents of “nativism,” which was Chomsky’s widely supported theory of language. And the debate that followed would change how many of us think about language and our brains.

Samia Bouzid brings us this story.

Samia Bouzid: In 1972, a group of linguists was hunkered down at a seaside villa in Croatia. They'd come together to hash out some ideas about how we humans acquire language.

One day, while the group was in the middle of their morning research session, a tanned young woman walked up the beach to the villa, carrying a backpack and a sleeping bag. She introduced herself as Liz Bates, and told the astonished researchers that she was there to join them.

Liz Bates was a grad student studying human development at the University of Chicago. She'd heard that this group would be convening, and she’d already planned a summer trip to Italy, so she thought, why not hop across the Adriatic Sea and drop in on them?

She wouldn't be any trouble, Liz assured the group, adding that she would just sleep on the terrace in her sleeping bag.

Little did they know, she was about to cause some trouble– at least, for linguists and psychologists–by upsetting the apple cart on one of their most well-regarded theories. Or at least, trying her very best to.

Katie Hafner: This is Lost Women of Science. I'm Katie Hafner. And today I’m joined by Samia Bouzid who brings us the story of Elizabeth Bates.

Katie Hafner: Hey Samia.

Samia Bouzid : Hi Katie.

Katie Hafner : So today we’re talking about Elizabeth Bates. Andby the way, that story, which of course, I had never heard, is quite amazing. So just to recap, this was Liz in the early 1970s, she's this audacious grad student crashing this meeting in Croatia, says, oh I'll just sleep on the porch in my sleeping bag. So what happened next?

Samia Bouzid: So she leaves Croatia behind, heads off to Italy as planned, and then in 1976 she publishes a book. She’s just 29 years old, she's just gotten her Ph.D., and this is her first book. It's all about how children learn language.

And the reception was mixed, to say the least. Some reviews were positive, some not so much. One critic said she had a weak grasp of theory, and that she made “sloppy” category mistakes, either because of laziness, or an inability to write clearly, or just some basic misunderstanding.

Katie Hafner: Oh wow, that is harsh.

Samia Bouzid : Yes. And look, it is totally possible that the book really wasn’t perfect. I mean, this was her first book. But it’s also possible that the book just rubbed some people the wrong way. Because Liz was arguing that our basic language abilities are not innate. And that was controversial.

At that time, linguists widely believed that humans are hardwired for language and that we're born with specific language skills that are encoded in our genes.

It all started…with Noam Chomsky.

Noam Chomsky: In a certain sense, I think we might even go on to say that language isn't even learned–at least if by learning, we mean any process that has those characteristics that are generally associated with learning.

Samia Bouzid: This was an interview he did on a BBC show called Men of Ideas in 1978.

Katie Hafner : And Chomsky, we should point out, was the man of ideas.

Samia Bouzid: Yeah, he was a total superstar. I mean today a lot of people today know Noam Chomsky as a political activist, but he’s also one of the biggest names in linguistics. And in the 1950s, he revolutionized the way we think about language.

Before he came along, most linguists thought of language as a type of behavior that you learn…. not something that’s genetically hardwired. So the idea was that children learn to speak by mimicking the people around them, and through the feedback they get as they practice speaking.

But that didn’t sit right with Chomsky. He recognized that speaking a language involves a lot more than just parroting sounds. Like when people speak, they don’t just pull from a bank of phrases, they’re putting words together in entirely new ways.

Katie Hafner: I get that—so it’s like, you can learn to say “dog” and you can learn to say “potato,” but how can you learn to say “Hey look at that potato-shaped dog with the tuberous snout?” Right?

Samia Bouzid: Exactly. Exactly. And Chomsky also pointed out that every child with normal cognitive abilities naturally develops language, without any kind of instruction–and they do it quickly. So he took that to mean that humans have a language instinct–in other words, we don’t really learn language.

Noam Chomsky: It seems to me that if we want a reasonable metaphor, we should talk about growth. Language seems to me to grow in the mind, rather in the way that familiar physical systems of the body grow.

Katie Hafner : What does he mean by that? I mean people obviously do learn languages.

Samia Bouzid: Right. you weren’t born speaking English, you had to learn it. And, you know, Swedish kids have to learn Swedish words, and Brazilian kids have to learn Portuguese ones. Chomsky wasn’t denying all that, but he proposed that the basic circuitry our brains use for language is innate, and that thanks to this circuitry, there are some universal features that underlie every language. This was what he called this universal grammar.

Katie Hafner: So you have this innate language ability…but you also learn language. So how would that work?

Samia Bouzid : So the theory has evolved a lot over the decades. But there’s a switch box analogy that I found kind of useful as a way of wrapping my head around the premise. And I should be clear: It doesn’t reflect how nativists think of the brain today, but it was popular back in the ‘80s, when Liz was deep in this debate, and I think it’s a useful way of grasping how something like this could work.

Imagine you have a language machine in your brain. And then there are a set of switches that get flicked on or off depending on the specific language you’re learning. So, if you’re learning French, you’ll flick on a switch that means all nouns have to have a gender. And if you’re learning English, you’ll turn that switch off.

But whether you speak French or English or Icelandic or Cantonese, if you pull back all the layers, the basic machinery is the same. At least that’s what Chomsky believed.

Again, the theory’s evolved since then, and people aren’t talking about switch boxes anymore. But that idea, that there’s this part that’s innate, and then these parameters that change depending on what language you’re learning, that still holds. So that’s the basic idea and one of the things that Chomsky and other nativists have historically pointed to as evidence is the fact that humans are the only animals that have what they considered to be language. So as far as they’re concerned, there must be something innate in us that makes language possible.

Katie Hafner: So he thinks animals don't have language? I mean, my dog, Newman, he has language. He understands many things. Like his best friend Carmelo, I say Carmelo, and he runs to the door to look for Carmelo. That's language.

Samia Bouzid : Well, I know what you mean, but, but no, actually a lot of people don’t think what animals have really counts as language. So this is a very big and old debate. We’re definitely not going to settle it today. But I think what we can say for sure is that animals don’t seem to be able to fully grasp the kind of language we humans have. Because if you think about it, no one has ever been able to teach another species to use language like we do. And for the record, psychologists have absolutely tried:

Researcher: “Can you say what this is?”

Chimp : Cup.

Samia Bouzid: Katie, did you catch that sound at the end?

Katie Hafner: Uhh… sounded like a whisper.

Samia Bouzid : Hang on, let me play it again…

Chimp : Cup

Samia Bouzid : It’s a little hard to hear. But that was a chimp named Vicky saying the word “cup.” She’s also wearing a dress. But the point is, even though animals like Vicky learned some words, by the 1970s, animals are not talking. Language is seen by most people as a uniquely human thing, and the question is just why. For Chomsky, the answer was because we evolved that way. His theory was broadly known as nativism, and it was really popular.

Mike Tomasello: Everybody learned Chomsky. In graduate school, I learned Chomsky and it had a certain intuitive appeal to it, that there are these universal features of language.

Samia Bouzid: Mike Tomasello is a professor of psychology and neuroscience at Duke, who worked with Liz Bates for many years. When he was doing his PhD in the 1970s, Chomsky's ideas were king. And it didn't hurt that Chomsky himself was a sort of superstar in other ways.

Mike Tomasello: Chomsky was the one faculty professor in America who really stood up against the war in Vietnam. So he was a hero to people regardless of the linguistics.

Samia Bouzid: His reputation helped elevate his ideas, and those ideas stuck. By the early 1970s, Chomsky's theory that language is innate was widely accepted. But Elizabeth Bates wasn’t accepting it.

Samia Bouzid: Liz came to linguistics through psychology. As a Ph.D. student at the University of Chicago, she had studied human development. In particular, how children develop language. And she wasn't satisfied with Chomsky’s theory.

She had trouble accepting the idea that our ability to use language was just there, pre-programmed.

[toddler babbling]

Samia Bouzid: Liz started out by studying young children when she was in grad school, observing how they interacted with their environment and learned language.

And what she saw–in her own research and in her colleagues’ research–didn’t seem to match Chomsky’s theory.

Katie Hafner : Interesting… So, the way kids learn language can tell you whether it’s innate?

Samia Bouzid : Debatable. But some psychologists would argue it at least gives you some really important clues. So to give you an idea of what I’m talking about, Liz and her colleagues studied kids who were raised in different language environments, like Italian and English and German. And they noticed some intriguing differences. For instance, here’s an example from one of Liz’s own grad students. His name is Fred Dick, and he's now a professor of cognitive neuroscience at University College London.

Fred Dick: So in English, the order of words is really important. So like if the dog comes before bite, he is very likely to be doing the biting.

Samia Bouzid: But word order is more flexible in a language like Italian. You can rearrange some words without changing the meaning. So English-speaking kids tend to master word order before Italian kids do because they need to. It seemed like in each language, the timing of when kids master these grammatical concepts depended on how crucial it was for their particular language.

To Liz, that suggested that kids weren't just flicking on a switch and activating some pre-programmed ability, instead they seemed to be building out a new ability as they interacted with their environment or the people around them.

Katie Hafner : Right, like they’re custom building their language skills as they go… I can see that. I speak German and the structure is so different from English. It’s hard to wrap my head around the idea that there’s one universal language framework underneath all of these very different languages.

Samia Bouzid : Mhm. Yeah, and I will say, nativists have worked really hard to explain what unifies every language out there. But for Liz, seeing how kids kind of build different languages from the ground up just seemed like more evidence against universal grammar. She talked about this a little bit in this educational video we found from 2001.

Liz Bates: The more we learn about human languages, the more diversity we see. To give you two examples at opposite extremes, if you have a language like Chinese, there are absolutely no endings on words of the sort we're used to in English, like dog - dogs, walk - walked. Uh, the way you would say the equivalent of “already ate dinner” in Chinese would be something that's loosely translatable as “eat finish.”

Samia Bouzid: And on the opposite end, you have languages like Greenlandic Inuit.

Liz Bates: where you have a sentence that could be one word with 17 inflections. Uh, prefixes, suffixes, and they ripped apart the word in the middle and stick stuff in the middle too. Infixes. So you have this extraordinary extreme from this very, very analytic and, and austere system to this very synthetic and stuffing as much as you can onto the word system. And human babies have to come into the world prepared to learn any of those.

Samia Bouzid: By the way, that wasn't to say that there was nothing special about our human brains. And Liz said as much in an interview on NPR in 1999.

Interviewer : Uh, Liz, is, is language innate? Are we born with brains hardwired to learn language?

Liz Bates: There's gotta be a reason why human beings are the only brains on the planet that acquire language. Your dog doesn't acquire language because he's got a dog brain.

Samia Bouzid : Okay, so Liz was in the camp that other animals do not have language. Like I said, we’re going to steer clear of that whole debate today and just acknowledge for now that at least no dog has mastered Japanese like a human has.

Katie Hafner: My dog has!

Samia Bouzid: Oh yeah?

Katie Hafner: Just Japanese.

Liz Bates : But, uh, the question is, what is it about that brain that makes it the only one on the planet that can acquire language? Uh, the easiest answer, which is also probably wrong, is it's because we have a language organ that no other species has.

Katie Hafner: So mean!

Samia Bouzid : Yes, definitely a dig at Chomsky there. But here’s the thing, Katie, if Liz was right, then that leaves us with a puzzle right? Because if human brains are the only ones capable of at least human-style language, but we don’t have a unique language organ…then what is it?What gives us the ability to speak?

Liz Bates: Well, sometimes I use the analogy of a giraffe's neck, you know, if you, uh, look at the giraffe's neck, it's very striking, it's clearly adapted for reaching up there in the trees, and they get the, they're the only ones that can get up there and get those leaves, right? But it's not a special organ in the sense that it's something new that no other species has. It has the same number of bones your neck has.

Samia Bouzid: In other words, Giraffes don’t have a specially evolved totally unique reaching organ. They have a neck. Just a much longer one. And in the same way, if there was something special about the human brain, Liz thought maybe it was just that it was so big. It didn’t have to have specially evolved language circuits. Maybe it just has a lot more circuitry than other animals, so it could learn much more complicated kinds of communication.

Here’s Fred Dick again.

Fred Dick: Liz's whole approach from the beginning of her career was really to think of language as being the product of our interaction with the world, and of many small tweaks over evolution that were not specific to language, but that really helped language along.

Samia Bouzid: But in the 1970s, Liz’s conclusions pitted her directly against Chomsky, and most other linguists at the time. And going against the grain like that made most people nervous. Liz’s close collaborator, Brian MacWhinney, remembers how people reacted during one presentation he did with Liz in Paris.

Brian MacWhinney: They just would have nothing of it because it wasn't Chomskian, and so no one would defend us, you know, everyone would say it's wrong, but then, in the back afterwards, they said, well, you know, we kind of agree, but we didn't want to say it.

Samia Bouzid: In some ways, Liz was protected from all this. Mike Tomasello told me that psychologists working in psychology departments, like him and Liz, were under less pressure to conform. The debate was mostly playing out among linguists. But he said that people working in linguistics departments really had a lot to lose.

Mike Tomasello: Their jobs were at stake. Or even if they had an established job in a linguistics department, their students weren't going to get jobs if they went against the grain too much.

Samia Bouzid: But as far as Liz was concerned, her data simply didn't support nativism. And she wasn’t the only one having her doubts. Brian MacWhinney and Mike Tomasello were some of her only supporters, and little by little, a group of researchers started to coalesce around this theory, which became known as “connectionism,” or “emergentism.”

Emergentism is actually a concept that extends way beyond linguistics. Very generally speaking, it’s the idea that simple interactions can give rise to complex systems. And those complex systems are much more than just a sum of their parts. Which I know sounds really abstract, but this kind of thing, emergent phenomena, are actually really common all over the universe. So if you think about a beehive, there’s no architect bee with a whole beehive blueprint in its brain, but as bees interact with each other, the beehive structure just naturally emerges. So along these same lines, Liz and other emergentists believed that there was no blueprint for language in our genes, but that language emerges as simpler mechanisms in the brain interact with the environment.

But not everyone was convinced. Actually, most people weren’t. And this wasn't just any old academic question. It was one people felt really strongly about... And I wasn’t sure why. I mean I think it’s a fascinating question, but I didn’t quite get why it was so heated and so personal—why people were afraid to speak up or admit what they really thought. And I’m still not positive, but in talking to people, there was one theme that came up a few times.

Mike Tomasello: I think a lot of people intuitively believe that the thing that distinguishes humans most clearly from other creatures is language.

Fred Dick: I think there is an element of feeling like humans are special. And this is our most special specialness, is language. And so I think there's a kind of level of commitment to the theoretical debates that gets a little religious at times.

Samia Bouzid: It’s kind of like if our language abilities aren't written into our genes, or hardwired into our brains, then what sets us apart from other animals? You know? What makes us human?

For Liz, having an innate language instinct wasn’t it. And so far we’ve heard a lot from her side of the debate, but after the break, we’ll hear from the other side. And the view is pretty different.

Katie Hafner : Okay, Samia, so before the break, we learned that there were two camps—nativists, like Chomsky, and a smaller group of emergentists, like Liz. And this debate was about to get surprisingly intense.

Samia Bouzid: Yes, it did. And it worked out to basically East Coast vs. West Coast. So Chomsky was at MIT, and nativists kind of coalesced there, meanwhile, Liz was on the West Coast at UC San Diego, which was the home base of the emergentists.

And the two sides went at it. Fred Dick was there for some of those years:

Fred Dick: People were not very nice. The attacks were not just kind of intellectual. They were quite demeaning at times. And, uh, there was a bit of a pile on mentality I think.

Samia Bouzid : And this is something I've really wanted to understand more, because I had spoken to a number of Liz’s colleagues and friends, and you know I came away with this impression that she was this tireless scientist who was on a quest to figure out the truth. But obviously there’s a whole other side to this story—the nativists. And based on everything I was hearing, there’s no doubt to me that they saw things pretty differently. So I wanted to know what they thought of all of this, and of Liz.

Katie Hafner: I mean, who were these other, who were the other people? I mean, we know about Chomsky.

Samia Bouzid: Yeah, so I didn't manage to get a hold of Noam Chomsky, although I did reach out to him.

Katie Hafner: And he is, for the record, 95 years old, as I understand it, and still going strong. But, uh….

Samia Bouzid: Yes, so that's fine. He has better things to do than answer my emails. But I actually did get a hold of one of the key players from the other side, Steven Pinker.

Katie Hafner: Oh, Steven Pinker, I've met him, nice guy.

Samia Bouzid: Yeah, and for anyone who doesn't know him, Steven Pinker is a cognitive psychologist at Harvard, and he's written a ton of popular books about language and how the mind works and human nature. And I knew that he'd been around when these debates were going on, so I thought that he'd have an interesting perspective.

So we emailed him, and he wrote back right away and agreed to talk to me about Liz. But in that first email, he was kind of like, wait a second, Liz Bates, a Lost Woman of Science?

Steven Pinker : Everyone knew about Liz Bates. Everyone had an opinion on Liz Bates. She was a highly polarizing figure.

Samia Bouzid: And compared to her supporters, let’s just say Steven Pinker had a pretty different experience of Liz.

Steven Pinker : I think that she and I had probably symmetrical feelings about the other. That is, each one respected the other. Each one knew that it’s important that the other one pressed their case, but probably didn't like each other that much, although at the same time with some mixed with some almost like a situation comedy, a kind of barbs and affection and sparring and respect.

Samia Bouzid: In other words….

Steven Pinker: We were each put on earth to torment the other.

Samia Bouzid: So, as we mentioned, these debates got passionate. But as far as Steven Pinker could tell, Elizabeth Bates could hold her own.

Steven Pinker : There were a number of people in the general Chomskian universe who were kind of bullies, and dogmatic, and she could out-bully the bullies. For her, science was war, and the object was to discredit, humiliate, obliterate your opponents. Now, you know, I say that with some caution because I know that there is, of course, a tendency to forgive that in men and to use it as a criticism of women, but I think anyone who knew her would say that she was fiercer than the fiercest men.

Katie Hafner : He doesn't mince words when it comes to this.

Samia Bouzid: No, but I think it really reflects the intensity of what was going on back then. And by the way, this went on for decades. On the one side, the nativists weren't budging. They were like, you just can't explain the uniqueness and complexity of language without some innate structure.

And if you look at the human brain, there are certain areas that are usually dedicated to language, like the left temporal cortex. If you have a stroke that damages that part of your brain, chances are you're going to have trouble understanding people when they speak to you. And Liz didn't deny any of that.

Liz Bates: Under normal conditions, in the absence of lesions, left temporal cortex, in a domain general way, is a detail cruncher. It wins the contract for language use. It wins.

Samia Bouzid: That's Liz talking about this during a lecture around the 1990s. But she'd also been studying kids with brain injuries herself. And she saw that kids could have really severe damage to the so-called language region of their brain, and they could still talk.

Liz Bates: Children with holes in their heads that you could put your fist through, exactly where the lesions cause aphasia in adults, do fine.

Katie Hafner : That's pretty incredible. It's, it's hard to imagine.

Samia Bouzid: Yeah, and Fred Dick told me this story that Liz told him about something that happened at one of her talks. Apparently, a girl who was missing most of the left hemisphere of her brain showed up at this talk and asked a perfectly coherent question. And the emergentist felt like, that pretty much settled things, like there couldn't be a specific part of the brain hardwired for language if language still existed even without that part of the brain.

Katie Hafner: But let me guess. That was not the end of things, right?

Samia Bouzid: Nope. Obviously, nativists recognized that sometimes the brain kind of reorganized itself, but as far as they were concerned, that didn't really contradict the core idea that language mechanisms were somehow innate.

Katie Hafner: So where did this end?

Samia Bouzid: It didn't. So each side just dug their heels in, and eventually some of them felt like they weren't even having a debate anymore. They were just talking past each other.

Katie Hafner: Like a presidential debate.

Samia Bouzid: Yeah, exactly.

Katie Hafner: So what was this like for Liz? It sounds like kind of a downer.

Samia Bouzid: Yeah, but you know what, as intense as that debate was, everyone I talked to made it absolutely clear that Liz loved what she did. I mean, work was her whole life, and not because it was some chore or something, it was just because she couldn't get enough of it. And this wasn't just when she was a young, recent grad trying to hustle her way into the field or anything. This went on for her whole career.

In 1981, she got married to a physicist named George Carnevale, and in 1983, they had a daughter, Julia. And true to form, Liz had Julia visiting the lab before she was even a year old.

Liz Bates: Okay, here's Julia at ten and a half months. Brought some of her favorite toys to see if she'll show off.

Katie Hafner: Oh, I love that. So what were they doing with Julia in the lab?

Samia Bouzid: Oh, that time, they were just there for fun. But Liz and George actually did make a little study out of Julia. They kept this incredible written record of Julia’s development called “Julianotes,” And they just wrote down things that they noticed about her while she was a baby.

Katie Hafner: Like what?

Samia Bouzid: Mostly pretty ordinary things, but some of them are kind of hilarious. Here, I'll read you one of them. Liz wrote, “My first impression, other than amazement at her alertness, was amazement at her incompetence.”

Katie Hafner: Oh man, I'm trying to think, what would it be like to have Liz as a mother, but in any event, I'd say high standards.

Samia Bouzid: Yeah[laughs] So this was their life. In the 1980s and ‘90s, Liz and George were both busy academics, but judging from what everyone told me, they also had really full social lives.

At this point they had homes in both San Diego and Rome, that was where Liz did a lot of her cross-linguistic research, comparing English- and Italian-speaking kids. But no matter where they were, their home was always just full of people. Liz’s colleagues, her friends. I mean, her colleagues were her friends. And it’s just, it sounds like she really drew people in.

Katie Hafner: All right, but here's the real question. Did she manage to change people's minds about nativism?

Samia Bouzid: Well she did gain some traction, because emergentism started out as this really pretty unpopular theory, and eventually it became a well established alternative to nativism. But she never really won the debate. It's actually still not settled.

But that’s okay. This intellectual, academic debate–this was really just one piece of her career. She was doing work that had a lot of real tangible impacts too.

Like, she was coming up with techniques for measuring children's language skills, and that had a real impact because it made it easier to spot possible language disorders early on. And one of her biggest discoveries was showing just how plastic the brain is when it comes to language. How young children can recover from really serious brain injuries and go on to speak as well as anyone else.

Katie Hafner: Like that child with the hole in her head.

Samia Bouzid: Yep, exactly. So Liz’s work reached pretty far and wide. And she also pushed people to look past their own narrow fields.

Mike Tomasello: What I loved about her was that she had this, a little bit of a revolutionary streak, always wanting to think about the bigger picture and what it means for the bigger picture.

Samia Bouzid: Liz didn't think that you could understand the brain just by studying the brain. She was absolutely interested in how our brains are wired, but she was also interested in context, and the way things changed over time. Whether that was over a lifetime, over our evolutionary history, she was interested in how every crumb of knowledge and experience we gain from our environment literally changes us by reshaping our brains.

Mike Tomasello: She always had this dynamic, historical, evolutionary, developmental perspective, and a big-ideas-theoretical person. And that's what made her so interesting.

Katie Hafner: So where did all of this lead to for her?

Samia Bouzid: Well, it all ended much sooner than Liz would have liked. While she was in Italy in 2002, she was diagnosed with pancreatic cancer, and told she only had months left to live. But there was so much she still wanted to do, so even then, she didn’t stop working. And, you know, her family knew how much she loved her work, but even for them this was a little bit shocking. I talked to her daughter Julia Carnevale, and she told me a little bit about it. Julia was a teenager back then.

Julia Carnevale: When she was sick at the end, I remember you know my dad and I kind of thought maybe she'd want to, I don't know, like do something else, travel who knows, but she was just: "Nope, I'm going to my lab."

Katie Hafner: You know, what she says rings familiar to me. There are several women we've profiled where this has happened. They get sick and they're like, nope, I gotta keep working to the end. Just gotta keep going, as if they've just run out of time.

Samia Bouzid: That was one thing Julia said, that she just wanted to squeeze out every little drop that she could out of her life and her career. And so even when she couldn't be in her lab herself, she still found a way to keep doing her work.

Fred Dick was one of the people working with her back then.

Fred Dick: When she was sick with pancreatic cancer her last year, I would go and visit her in the chemo suite as she was getting chemo, and we would write papers.

Julia Carnevale: She was just driven by the sheer excitement of discovery, and it was just so pure. I think you know, you know she she had a lot of friends she had a lot of like scientific enemies is my memory, like a lot of, she maybe rubbed some people the wrong way because she was just so passionate, and you can see that, right, and people get in their corners and I'm sure she did too, but um I do remember just like, you know, this woman really kind of like loved – loved this, you know, and that's I really stood out and continues to stand out to me.

Samia Bouzid: After scrambling to do all this work, in April 2003, in the last months of her life, Liz and her colleagues debuted a brand-new neuroimaging technique. And then, in December of that same year, she died.

Katie Hafner: Boy, she really did not waste a second of her life. So what were things like after, after she was gone?

Samia Bouzid: Well, the debate didn't disappear or anything like that. Plenty of people still challenged Chomsky's idea of a language instinct. But from what I gather, the kind of sparring that was happening in the ‘70s and ‘80s stopped happening. So that's not going on anymore. But that fundamental question of how we acquire language, that's still there. And it's gotten a little more interesting recently, ever since large language models like ChatGPT came into the picture.

Katie Hafner: Right. So, what do the linguists make of this?

Samia Bouzid: Well, some see it as evidence in favor of emergentism. Here's Fred Dick.

Fred Dick: The advent of deep learning and the advent of ChatGPT has shown that indeed if you just give a machine enough information and not give it a sort of special purpose language learning device you can actually pick up the structure of language and use it productively.

Samia Bouzid: That’s because ChatGPT doesn’t have any built-in rules telling it how to conjugate verbs or order sentences. It doesn’t have any programming dictating how languages should be structured. But it still learned to use grammar properly. Which suggests that you don’t necessarily need any pre-existing structure to learn a language.

But Steven Pinker doesn’t think that that’s entirely relevant to the question of how humans got language.

Steven Pinker: You know, on the one hand, I often said, if one of those models could actually speak the way a grown-up human could speak, making fine grammatical distinctions, understanding completely novel content, then I would be willing to concede that models without any particular pre-programming for language could be a model of what the child does.

On the other hand, we do have to take into account that the reason these models do so well is that they've been trained on the entire world wide web, and that would take 30,000 years.

Samia Bouzid: In other words, this shows it’s possible to learn language without a special language box in the brain, but Steven Pinker isn’t convinced that this is actually how humans do it. And so, the debate goes on.

Katie Hafner : So all of this makes me think, I mean, we, we look at a lot of women who did something amazing, discovered something, invented something, and yet Elizabeth Bates, I mean, she spent much of her life fighting a fight she didn't win. So what does that imply about her, her legacy?

Samia Bouzid: Well, I think that even though this debate kicked off Liz's career and motivated so much of her research, it's not by any means her only scientific legacy. Liz's work seeded all sorts of new research in all the fields she worked in. She trained so many grad students who are still carrying on the work that she started. I think what’s sort of striking is that, based on what I heard from some of her former colleagues, given all that, given that her impact is being felt in all these fields, Liz herself is not as well known anymore as you might expect.

Virginia Volterra was Liz’s colleague and one of her closest friends from Rome. And here’s how she sees it.

Virginia Volterra: In Italy, she was very, very well known. When she gave a talk, she had hundreds of people coming. And, now, it seems that she is almost, not completely, but disappearing.

Katie Hafner: And why do you think that is?

Samia Bouzid: Well, some of her colleagues had some ideas about that. Virginia Volterra thinks the main reason is just that she was gone too soon.

Virginia Volterra: She died very early in some way. I am learning that, that if you live, if you can survive, you have more chance to be remembered.

Samia Bouzid: As for Brian MacWhinney, he thinks that in a way, her disappearance is partly because she was such a pioneer.

Brian MacWhinney: If you're too much ahead of your time, that can be a curse.

Samia Bouzid: But whether or not people know Liz’s name today, or whether they know her name well and remember her as a thorn in their side, Liz mattered.

Steven Pinker: A lot of people really couldn’t stand her.

Samia Bouzid: Steven Pinker again.

Steven Pinker: But I think everyone respected her because she was really smart. And she was absolutely necessary to that intellectual ecosystem. So when I would write something, I would have to think, hmm, how would she try to demolish this? And you know I gotta say, that's the kind of thing that makes you a better, a sharper and a better thinker. You don't get a free pass.

Samia Bouzid: Liz had the courage to challenge the status quo and stand up to ideas she disagreed with, no matter who they were coming from.

And regardless of who got what right in the end, that kind of challenge and debate is what it takes to push science forward.

Katie Hafner : This episode was hosted by me, Katie Hafner.

Samia Bouzid : And me, Samia Bouzid.

Katie Hafner: Samia wrote, produced, and sound-designed this episode with help from our senior producer, Elah Feder. Lizzie Younan composes all of our music. And, we had fact-checking help from Lexi Atiya.

Samia Bouzid : I want to thank George Carnevale, Liz’s husband, who shared his memories of Liz, along with the recordings of her voice that you heard in this piece.

I’d also like to thank Ian Roberts, who took the time to speak with us and helped us better understand the nativist perspective.

Katie Hafner : Thanks also to Jeff Delviscio at our publishing partner, Scientific American. And to my co-executive producer Amy Scharf, as well as our senior managing producer, Deborah Unger. The episode art was created by Keren Mevorach.

Lost Women of Science is funded in part by the Alfred P. Sloan Foundation and the Anne Wojcicki Foundation. We're distributed by PRX.

Samia Bouzid : You can get show notes and an episode transcript at lostwomenofscience.org

Katie Hafner : And while you’re there, do not forget to hit that donate button. See you next week!

HOST: Katie Hafner

GUESTS: Fred Dick , Professor of Neuroimaging and Director of BUCNI, University College London

Brian MacWhinney , Professor of Psychology and Modern Languages, Carnegie Mellon University

Steven Pinker , Johnstone Family Professor of Psychology, Harvard University

Mike Tomasello , Professor of Psychology and Neuroscience, Duke University

Virginia Volterra , formerly Director of the Institute of Cognitive Sciences and Technologies in Rome

Julia Carnevale , Physician-Scientist at the University of California, San Francisco

PRODUCER: Samia Bouzid

SENIOR PRODUCER: Elah Feder

Art Design: Keren Mevorach; Photo: courtesy of George Carnevale

FURTHER READING/LISTENING:

Language and context: the acquisition of pragmatics , by Elizabeth Bates, Academic Press (1976)

Noam Chomsky interviewed on the BBC’s Men of Ideas (1978)

Tribute to Elizabeth Bates , obituary by Virginia Volterra (Cortex, 2004)

Beyond nature-nurture: essays in honor of Elizabeth Bates , edited by Michael Tomasello and Dan Isaac Slobin, Lawrence Erlbaum Associates (2005)

The Language instinct , by Steven Pinker, Harper Perennial Modern Classics (1994/2007)

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What is sapir-whorf hypothesis in behavioral science.

The Sapir-Whorf Hypothesis, also known as the linguistic relativity hypothesis, is a theory in linguistics and cognitive science that posits that the structure of a language influences the way its speakers perceive and think about the world. This hypothesis is named after its proponents, American linguists Edward Sapir and Benjamin Lee Whorf, who independently formulated and expanded upon the idea in the early 20th century.

The Sapir-Whorf Hypothesis is commonly divided into two versions:

• Strong version (linguistic determinism): This version asserts that language determines thought, meaning that the way people think is entirely shaped by their language. According to this perspective, speakers of different languages perceive and conceptualize the world in fundamentally different ways due to the unique structures and vocabulary of their languages.
• Weak version (linguistic relativity): This version proposes that language influences, but does not determine, thought. It suggests that while the structure of a language can affect the way its speakers perceive and think about the world, other cognitive factors and experiences also play a significant role in shaping their thoughts and perceptions.

The Sapir-Whorf Hypothesis has generated extensive debate and research, with empirical evidence supporting both its strong and weak versions to varying degrees. Some studies have demonstrated that language can indeed influence cognitive processes such as color perception, spatial reasoning, and time perception. However, other research has challenged the hypothesis, arguing that universal cognitive processes exist independently of language.

Despite the ongoing debate, the Sapir-Whorf Hypothesis has contributed to our understanding of the relationship between language, culture, and cognition. Its implications extend across various disciplines, including anthropology, psychology, sociology, and education, by informing the development of:

• Cross-cultural communication: Recognizing the influence of language on thought can help improve communication and understanding between speakers of different languages and cultural backgrounds.
• Language teaching and learning: The Sapir-Whorf Hypothesis highlights the importance of considering cultural and cognitive factors in language education, as language learning involves not only acquiring new vocabulary and grammar but also adapting to new ways of thinking and perceiving the world.
• Cognitive development research: Investigating the relationship between language and thought can provide insights into cognitive development and the role of linguistic factors in shaping cognitive abilities.

While the Sapir-Whorf Hypothesis remains a subject of debate and investigation, it has significantly impacted our understanding of the complex interplay between language, thought, and culture.

Related Behavioral Science Terms

Belief perseverance, crystallized intelligence, extraneous variable, representative sample, factor analysis, egocentrism, stimulus generalization, reciprocal determinism, divergent thinking, convergent thinking, social environment, decision making, related articles.

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Five Theories on the Origins of Language

• An Introduction to Punctuation
• Ph.D., Rhetoric and English, University of Georgia
• M.A., Modern English and American Literature, University of Leicester
• B.A., English, State University of New York

What was the first language ? How did language begin—where and when? Until recently, a sensible linguist would likely respond to such questions with a shrug and a sigh. As Bernard Campbell states flatly in "Humankind Emerging" (Allyn & Bacon, 2005), "We simply do not know, and never will, how or when language began."

It's hard to imagine a cultural phenomenon that's more important than the development of language. And yet no human attribute offers less conclusive evidence regarding its origins. The mystery, says Christine Kenneally in her book "The First Word," lies in the nature of the spoken word:

"For all its power to wound and seduce, speech is our most ephemeral creation; it is little more than air. It exits the body as a series of puffs and dissipates quickly into the atmosphere. ... there are no verbs preserved in amber, no ossified nouns, and no prehistorical shrieks forever spread-eagled in the lava that took them by surprise."

The absence of such evidence certainly hasn't discouraged speculation about the origins of language. Over the centuries, many theories have been put forward—and just about all of them have been challenged, discounted, and often ridiculed. Each theory accounts for only a small part of what we know about language.

Here, identified by their disparaging nicknames , are five of the oldest and most common theories of how language began .

The Bow-Wow Theory

According to this theory, language began when our ancestors started imitating the natural sounds around them. The first speech was onomatopoeic —marked by echoic words such as moo, meow, splash, cuckoo, and bang . 

What's wrong with this theory?

Relatively few words are onomatopoeic, and these words vary from one language to another. For instance, a dog's bark is heard as au au in Brazil, ham ham in Albania, and wang, wang in China. In addition, many onomatopoeic words are of recent origin, and not all are derived from natural sounds.

The Ding-Dong Theory

This theory, favored by Plato and Pythagoras, maintains that speech arose in response to the essential qualities of objects in the environment. The original sounds people made were supposedly in harmony with the world around them.

Apart from some rare instances of sound symbolism , there is no persuasive evidence, in any language, of an innate connection between sound and meaning.

The La-La Theory

The Danish linguist Otto Jespersen suggested that language may have developed from sounds associated with love, play, and (especially) song.

As David Crystal notes in "How Language Works" (Penguin, 2005), this theory still fails to account for "... the gap between the emotional and the rational aspects of speech expression... ."

The Pooh-Pooh Theory

This theory holds that speech began with interjections —spontaneous cries of pain ("Ouch!"), surprise ("Oh!"), and other emotions ("Yabba dabba do!").

No language contains very many interjections, and, Crystal points out, "the clicks, intakes of breath, and other noises which are used in this way bear little relationship to the vowels and consonants found in phonology ."

The Yo-He-Ho Theory

According to this theory, language evolved from the grunts, groans, and snorts evoked by heavy physical labor.

 Though this notion may account for some of the rhythmic features of the language, it doesn't go very far in explaining where words come from.

As Peter Farb says in "Word Play: What Happens When People Talk" (Vintage, 1993): "All these speculations have serious flaws, and none can withstand the close scrutiny of present knowledge about the structure of language and about the evolution of our species."

But does this mean that all questions about the origin of language are unanswerable? Not necessarily. Over the past 20 years, scholars from such diverse fields as genetics, anthropology, and cognitive science have been engaged, as Kenneally says, in "a cross-discipline, multidimensional treasure hunt" to find out how language began. It is, she says, "the hardest problem in science today."

As William James remarked, "Language is the most imperfect and expensive means yet discovered for communicating thought."

• Where Did Language Come From? (Theories)
• 10 Animal Sounds in Japanese Words
• Displacement in Language
• Holophrase in Language Acquisition
• The Sapir-Whorf Hypothesis Linguistic Theory
• What Is an Echo Word?
• Universal Grammar (UG)
• Transformational Grammar (TG) Definition and Examples
• Pragmatics Gives Context to Language
• What Is Psycholinguistics?
• Generative Grammar: Definition and Examples
• Indo-European (IE)
• The Theory of Poverty of the Stimulus in Language Development
• Definition and Examples of Speakers in Language Studies
• Descriptive Grammar
• The Origin of Our Solar System

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A critical period for second language acquisition: Evidence from 2/3 million English speakers

Joshua k. hartshorne.

a Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Building 46, 77 Massachusetts Avenue, MIT, Cambridge, MA 02139, United States

b Department of Psychology, Boston College, McGuinn Hall 527, Chestnut Hill, MA 02467, United States

Joshua B. Tenenbaum

Steven pinker.

c Department of Psychology, Harvard University, William James Hall 970, 33 Kirkland St., Cambridge, MA 02138, United States

Associated Data

Children learn language more easily than adults, though when and why this ability declines have been obscure for both empirical reasons (underpowered studies) and conceptual reasons (measuring the ultimate attainment of learners who started at different ages cannot by itself reveal changes in underlying learning ability). We address both limitations with a dataset of unprecedented size (669,498 native and non-native English speakers) and a computational model that estimates the trajectory of underlying learning ability by disentangling current age, age at first exposure, and years of experience. This allows us to provide the first direct estimate of how grammar-learning ability changes with age, finding that it is preserved almost to the crux of adulthood (17.4 years old) and then declines steadily. This finding held not only for “difficult” syntactic phenomena but also for “easy” syntactic phenomena that are normally mastered early in acquisition. The results support the existence of a sharply-defined critical period for language acquisition, but the age of offset is much later than previously speculated. The size of the dataset also provides novel insight into several other outstanding questions in language acquisition.

1. Introduction

People who learned a second language in childhood are difficult to distinguish from native speakers, whereas those who began in adulthood are often saddled with an accent and conspicuous grammatical errors. This fact has influenced many areas of science, including theories about the plasticity of the young brain, the role of neural maturation in learning, and the modularity of linguistic abilities ( Johnson & Newport, 1989 ; Lenneberg, 1967 ; Morgan-Short & Ullman, 2012 ; Newport, 1988 ; Pinker, 1994 ). It has also affected policy, driving debates about early childhood stimulation, bilingual education, and foreign language instruction ( Bruer, 1999 ).

However, neither the nature nor the causes of this “critical period” for second language acquisition are well understood. (Here, we use the term “critical period” as a theory-neutral descriptor of diminished achievement by adult learners, whatever its cause.) There is little consensus as to whether children’s advantage comes from superior neural plasticity, an earlier start that gives them additional years of learning, limitations in cognitive processing that prevent them from being distracted by irrelevant information, a lack of interference from a well-learned first language, a greater willingness to experiment and make errors, a greater desire to conform to their peers, or a greater likelihood of learning through immersion in a community of native speakers ( Birdsong, 2017 ; Birdsong & Molis, 2001 ; Hakuta, Bialystok, & Wiley, 2003 ; Hernandez, Li, & MacWhinney, 2005 ; Johnson & Newport, 1989 ; Newport, 1990 ; Pinker, 1994 ). We do not even know how long the critical period lasts, whether learning ability declines gradually or precipitously once it is over, or whether the ability continues to decline throughout adulthood or instead reaches a floor ( Birdsong & Molis, 2001 ; Guion, Flege, Liu, & Yeni-Komshian, 2000 ; Hakuta et al., 2003 ; Jia, Aaronson, & Wu, 2002 ; Johnson & Newport, 1989 ; McDonald, 2000 ; Sebastián-Gallés, Echeverría, & Bosch, 2005 ; Vanhove, 2013 ).

1.1. Learning ability vs. ultimate attainment

As noted by Patkowski (1980) , researchers interested in critical periods focus on two interrelated yet distinct questions:

• How does learning ability change with age?
• How proficient can someone be if they began learning at a particular age?

The questions are different because language acquisition is not instantaneous. For example, an older learner who (hypothetically) acquired language at a slower rate could, in theory, still attain perfect proficiency if he or she persisted at the learning long enough.

The question of ultimate attainment (2) captures the most public attention because it directly applies to people’s lives, but the question of learning ability (1) is more theoretically central. Does learning ability decline gradually from birth ( Guion et al., 2000 ; Hernandez et al., 2005 ), whether from neural maturation, interference from the first language, or other causes ( Fig. 1A )? Alternatively, is there an initial period of high ability, followed by a continuous decline ( Fig. 1B ), or a decline that reaches a floor ( Fig. 1C ) ( Johnson & Newport, 1989 )? Or does ability remain relatively constant ( Fig. 1D ), with adults failing to learn for some other reason such as less time and interest ( Hakuta et al., 2003 ; Hernandez et al., 2005 )?

(A–D) Schematic depictions of four theories of how language learning ability might change with age. (E–H) Schematic depictions of four theories of how ultimate attainment might vary with age of first exposure to the language. Note: While the curves hypothesized for learning ability and ultimate attainment resemble one another, there is little systematic relationship between the two; see the main text.

Unfortunately, learning ability is a hidden variable that is difficult to measure directly. Studies that compare children and adults exposed to comparable material in the lab or during the initial months of an immersion program show that adults perform better, not worse, than children ( Huang, 2015 ; Krashen, Long, & Scarcella, 1979 ; Snow & Hoefnagel-Höhle, 1978 ), perhaps because they deploy conscious strategies and transfer what they know about their first language. Thus, studies that are confined to the initial stages of learning cannot easily measure whatever it is that gives children their long-term advantage. (Note that strictly speaking, these studies measure learning rate , not learning ability . While these are conceptually distinct, in practice they are difficult to disentangle, and the distinction has played little role in the literature. In the present paper, we will use the terms interchangeably.)

Thus, although the question of learning ability (1) is more theoretically central, empirical studies have largely probed the more tractable question of how ultimate attainment changes as a function of age of first exposure (2). Here, too, there are a number of theoretically interesting possibilities ( Fig. 1E–H ). The hope has been that identifying the shape of the ultimate attainment curve might tell us something about the shape of the learning ability curve (cf. Birdsong, 2006 ; Hakuta et al., 2003 ; Johnson & Newport, 1989 ). Unfortunately, this turns out not to be the case. Despite the similarities between the two sets of hypothesized curves (e.g., compare Fig. 1A and E ), they bear little relationship to one another: The same ultimate attainment curve (e.g., Fig. 1E ) is consistent with many different learning ability curves ( Fig. 1A–D ).

Here is why learning ability curves ( Fig. 1A–D ) and ultimate attainment curves ( Fig. 1E–H ) should not be conflated: If, hypothetically, learning ability plummeted at age 15 but it took 10 years of experience to master a language completely, then ultimate attainment would decline starting at an age of exposure of 5 (since someone who began at 6 years old would learn at peak capacity for only 9 of the 10 years required, someone who began at 7 years old would learn for only 8 of those years, and so on). It would be erroneous, in that case, to conclude that a decline in ultimate attainment starting at age 5 implied that children’s learning ability declines starting at age 5. Conversely, showing that people who began learning at a certain age reached native-like proficiency merely indicates that they learned fast enough, not that they learned as fast as a native speaker, just as the fact that two runners both finished a race indicates only that they both started early enough and ran fast enough, not that they ran at the exact same speed.

As a result, it is impossible to directly infer developmental changes in underlying ability (the theoretical construct of interest) from age-related changes in ultimate attainment (the empirically available measurements). Fig. 2 shows that two very distinct ability curves, one with a steady decline from infancy (2A), the other with a sudden drop in late adolescence (2B), can give rise to indistinguishable ultimate attainment curves. (The curves are generated by our ELSD model, described below, but the point is model-independent.) Conversely, a rapid drop in ultimate attainment beginning at age 10 could be explained by a continuous decline in learning ability beginning in infancy ( Fig. 2C ) or by a discontinuous drop in learning rate at 15 years old ( Fig. 2D ). Moreover, quantitative differences in the magnitude of a hypothetical decline in underlying learning ability (which are not specified in existing theories) can give rise to qualitative differences in the empirically measured ultimate attainment curves, such as a gentle decline versus a sudden drop-off: compare Fig. 2A with 2C , and Fig. 2B with 2D .

Simulation results showing how the mapping between hypothetical changes in underlying learning rate (the left graph in each pair) and empirically measured changes in ultimate attainment is many-to-many. These quantitative predictions were derived from the ELSD model, described below, but the basic point is model-independent.

1.2. The present study

As we have seen, to understand how language-learning ability changes with age, we must disentangle it from age of exposure, years of experience, and age at testing. Unfortunately, this challenge is insuperable with any study that fails to use sufficiently large samples and ranges, because any imprecision in measuring the effects of amount of exposure on attainment, the effects of age of first exposure on attainment, or both, will render the results ambiguous or even uninterpretable.

Moreover, an underlying ability curve can be ascertained only if the measure of language attainment is sufficiently sensitive: If learners hit an artificial ceiling, any gains from an earlier age of exposure or a greater amount of exposure will be concealed. Indeed, the concept of native proficiency entails extreme levels of accuracy. An error rate that would be considered excellent in other academic or psychological settings, such as 0.75%, represents a conspicuous immaturity in the context of language. For example, over-regularizations of irregular verbs, such as runned and breaked , are among the most frequently noted errors in preschoolers’ speech ( Pinker, 1999 ), despite occurring in only 0.75% of utterances (and on 2.5% of past-marked irregular verbs; Marcus et al., 1992 ).

These basic mathematical facts raise a significant practical problem: Detecting an error that occurs as little as 0.75% of the time requires a lot of data: A preschooler has to produce 92 utterances to have a better than even chance of producing an over-regularization. Thus, to detect even “conspicuous” errors, such as childhood over-regularization, we need to test many subjects on many items.

Below, we describe a study of syntax that attempts to meet these challenges using novel experimental and analytical techniques. To foreshadow, the age at which syntax-learning ability begins to decline is much later than usually suspected, and it takes both native and non-native speakers longer to reach their ultimate level of attainment than has been previously assumed. While both findings are unexpected, we show that the apparent inconsistencies with prior findings can be explained by the much higher precision afforded by our methods. Indeed, the findings below should not be surprising in retrospect. More importantly, these findings appear robust and emerge in a variety of different analyses.

2.1. Overview

Initial power calculations suggested that several hundred thousand subjects of diverse ages and linguistic backgrounds would be required to disentangle age of first exposure, age at testing, and years of exposure (we return to issues of power in the discussion, below). The standard undergraduate subject pools are not nearly large or diverse enough to achieve this, nor are crowdsourcing platforms like Amazon Mechanical Turk ( Stewart et al., 2015 ). Inspired partly by Josh Katz’s Dialect Quiz for the New York Times , we developed an Internet quiz we hoped would be sufficiently appealing as to attract large numbers of participants. In order to go viral, the quiz needed to be entertaining and intrinsically motivating while also quick to complete, since Internet volunteers rarely spend more than 10 min on a quiz. At the same time, to yield useful data the quiz had to include a robust, comprehensive measure of syntactic knowledge without an artificial ceiling, as well as elicit demographic data about age and linguistic background. Below, we describe how we addressed these desiderata. Procedures were approved by the Committee on the Use of Humans as Experimental Subjects at Massachusetts Institute of Technology.

2.2. Procedure

Potential subjects were invited to take a grammar quiz ( www.gameswithwords.org/WhichEnglish ), the results of which would allow a computer algorithm to guess their native language and their dialect of English. After providing informed consent, subjects provided basic demographic details (age, gender, education, learning disability) and indicated whether they had taken the quiz before. They then completed the quiz and were presented with the algorithm’s top three guesses of their native language and their dialect, which was based on the Euclidean distance between the vector of the subject’s responses and the vector of mean responses for each language and dialect. Participants found this aspect of the quiz highly engaging, and the quiz was widely shared on social media. For instance, it was shared more than 300,000 times on Facebook.

After seeing the guesses, subjects were invited to help us improve the algorithm by filling out a demographic questionnaire. (Although early answers were used to tune the algorithm, the algorithm’s accuracy quickly plateaued and was not tuned further.) This included all the countries they had lived in for at least 6 months, and all the languages they spoke from birth. 1 Participants who listed multiple countries were asked to indicate their current country. For some countries (such as the USA), additional localizing information was collected. Participants who did not report speaking English from birth were asked at what age they began learning English, how many years they had lived in an English-speaking country, and whether any immediate family members were native speakers of English. Approximately 80% of subjects who completed the syntax questions also completed this demographic questionnaire. The data reported here come from those subjects.

2.3. Participants

All participants gave informed consent. 680,333 participants completed the experiment, excluding repeats. We further excluded participants who gave inconsistent or implausible responses to the demographic questions (listing a current age less than the age of first exposure to English; listing a current age that is less than the number of years spent in an English-speaking country; reporting college attendance and a current age of less than 16, or reporting graduate school attendance and a current age of less than 19), resulting in 669,800 participants. Finally, based on the histogram of ages, we excluded participants younger than 7 and older than 89 as implausible. Note: a number of participants ages 7–10 reported in the comments that their parents helped by reading the quiz to them, adding credibility to those data. The resulting number of participants for the analyses was 669,498.

The sample was demographically diverse ( Fig. 3 ). Thirty-eight languages were represented by at least 1000 native speakers, not counting individuals who had multiple native languages. The most common native languages other than English were Finnish (N = 39,962), Turkish (N = 36,239), German (N = 24,995), Russian (N = 22,834), and Hungarian (N = 22,108).

(A) Current country of residence of participants (excluding participants with multiple residences). (B) Histogram of participants by age of first exposure to English. (C) Native languages of the bilinguals (excluding English). (D) Histogram of participants by current age.

Analyses focused on three subject groups. Monolinguals (N = 246,497) grew up speaking English only; their age of first exposure was coded as 0. Immersion learners (N = 45,067) were either simultaneous bilinguals who grew up learning English simultaneously with another language (age of first exposure = 0), or later learners who learned English primarily in an English-speaking setting (defined as spending at least 90% of their life since age of first exposure in an English-speaking country). Non-immersion learners (N = 266,701) had spent at most 10% of post-exposure life in an English-speaking country and no more than 1 year in total. 2 Subjects with intermediate amounts of immersion (N = 122,068) were not analyzed further.

2.4. Materials

We took a shotgun approach to assessing syntax, using as diverse a set of items as we could fit into a short quiz, addressing such phenomena as passivization, clefting, agreement, relative clauses, preposition use, verb syntactic subcategorization, pronoun gender and case, modals, determiners, subject-dropping, aspect, sequence of tenses, and wh- movement. This broad approach has two advantages. First, it provides a more comprehensive assessment of syntactic phenomena than many prior studies, which focused on a smaller number of phenomena ( Flege, Yeni-Komshian, & Liu, 1999 ; Johnson & Newport, 1989 ; Mayberry & Lock, 2003 ). Second, this diversity provides some robustness to transfer from the first language. That is, while native speakers of some languages may find certain phenomena easier to master than others (e.g., Spanish-speakers may find tense reasonably natural while Mandarin-speakers may find word-order restrictions intuitive), the diversity of items should help wash out these differences (see also discussion below).

2.4.1. Item selection

Items were subjected to several rounds of pilot testing to select a suffficient number of critical items that were diagnostic of proficiency (neither too easy nor too hard) and that represented a wide range of grammatical phenomena, while requiring less than 10 min to complete. These included phenomena known to present difficulties for children, such as passives and clefts, and for non-native speakers, such as tenses and articles. We focused particularly on items known to be difficult for speakers of a variety of first languages: in particular, Arabic, French, German, Hindi, Japanese, Korean, Mandarin, Russian, Spanish, or Vietnamese. Based on previous experiments on gameswithwords.org, we expected these to be among the most common native languages.

In addition to the critical items, we included items designed to distinguish among English dialects drawn from websites describing “Irishisms,” “Canadianisms”, and so on. These items were not used for assessing language proficiency and were not used in the data analyses below, but were important for recruiting subjects (see above). Several rounds of pilot-testing reduced this set to the smallest number of items that could reliably distinguish major English dialects.

As in most previous studies, we solicited grammaticality judgments (e.g., “Is the following grammatical: Who whom kissed ?”). In order to shorten the test and improve the subject experience, where possible we grouped multiple grammaticality judgments into a single multiple-choice question. Because the grammaticality judgment task is time-consuming and unsuitable for probing certain grammatical phenomena, we also included items that required matching a sentence to a picture (e.g., to probe topicalization and the application of linking rules). Several rounds of piloting were used to construct a test that involved items of a range of difficulty.

The final set of 132 items is provided in the Supplementary Materials . Of these, 95 were critical items, defined as items for which the same response was selected by at least 70% of the native English speaking adults 18–70 years old in our full dataset in each of thirteen broadly-defined English dialects (Standard American, African American Vernacular English, Canadian, English, Scottish, Irish, North Irish, Welsh, South African, Australian, New Zealand, Indian, and Singaporean). (For obvious reasons, the exact number of critical items was not known until after the data was collected.) All analyses below are restricted to this set.

Many prior studies classify items according to the syntactic phenomenon they test. While this is straightforward for certain types of tests, such as our sentence-picture matching items, the accuracy of these categorizations for grammaticality judgments is unclear. For instance, in judging a sentence to be grammatical, subjects can hardly be expected to know which syntactic rule the experimenter deliberately did not violate. Likewise, ungrammatical sentences may implicate different rules depending on what the intended message was: I eats dinner could involve an agreement error on the verb or a failure of pronoun selection. Thus, the syntactic violation that catches the subject’s eye may not be the one the experimenter had in mind. Because our goal was merely to have a diverse set of items, an exact count of syntactic phenomena is less important than demonstrating diversity. Thus, we have bypassed these theoretically thorny issues by avoiding categorization and simply providing the entire stimulus set in the Supplementary Materials . As a result, readers can judge for themselves whether the items are sufficiently diverse.

2.4.2. Test reliability

Reliability for the critical items was high across the entire dataset (Chronbach’s alpha = 0.86). Because monolingual subjects were close to ceiling, reliability is expected to be lower for that subset. Reliability is a measure of covariation, and the monolinguals exhibited very little variation (the majority missed fewer than 3 items), exactly as one would expect for a valid test. However, reliability for monolinguals was still well above chance (0.66), indicating that what few errors they made were not randomly distributed (as would be expected from mere sloppiness) nor concentrated on a few “bad” items (in which case, there would be little variance). Thus, our test was sensitive to differences in grammatical knowledge even for monolinguals who were close to ceiling. It is difficult to compare these numbers to prior studies, since most did not report reliability (but see DeKeyser, 2000 ; DeKeyser, Alfi-Shabtay, & Ravid, 2010 ; Granena & Long, 2013 ).

2.4.3. Data

The resulting dataset is available at http://osf.io/pyb8s .

3.1. Learning rate

We focus first on the difficult but theoretically important question of the underlying learning rate. We defer the traditional question of level of ultimate attainment to a later section. Note that all analyses are conducted in terms of log-odds (the log-transformed odds of a correct answer, using the empirical logit method to avoid division by zero) rather than percent correct. Although prior work on critical periods has tended to use percent correct, this is problematic. Specifically, percentage points are not all of equal value, being more meaningful closer to 0% or 100% than when near 50% ( Jaeger, 2008 ). That is, the difference between 95% and 96% is “larger” than the difference between 55% and 56%. Thus, the use of percentages artificially imposes ceiling effects, inflating both Type I and Type II error rates, particularly for interactions. Similarly, graphing results in terms of percentage correct distorts the results (particularly the shapes of curves), and so we have graphed in terms of log odds. For reference, we have included percent correct on the right-hand side of many of the graphs.

Fig. 4 plots the level of performance against current age in separate curves for participants with different ranges of age of first exposure. It simultaneously reveals the effects of age of first exposure (the differences among the curves) and total years of exposure (the left-to-right position along each curve). Immersion learners—who were less numerous than the other groups—were aggregated into three-year bins for age of exposure, except for the simultaneous bilinguals (age of exposure = 0), who constituted their own bin. Curves were smoothed with a five-year floating window (analyses on non-smoothed data are discussed in the next subsection), and each of the estimated performance curves (described below) was restricted to consecutive ages for which there were at least ten participants in the five-year window, leaving 244,840 monolinguals, 44,412 immersion learners, and 257,998 non-immersion learners.

(A and B) Performance curves for monolinguals and immersion learners (A) and non-immersion learners (B) under 70 years old, smoothed with five-year floating windows. (C and D) Corresponding curves for the best-fitting model. (E) Learning rate for the best-fitting model (black), with examples of the many hypotheses for how learning rate changes with age that were considered in model fitting (grey). For additional detail, see Fig. 7 , S3, and S6 .

In order to estimate how underlying learning ability changes with age, we used a novel computational model to disentangle current age, age of first exposure, and amount of experience. Specifically, we modeled syntax acquisition as a simple exponential learning process:

where g is grammatical proficiency, t is current age, t e is age of first exposure, r is the learning rate, and E is an experience discount factor, modeled separately for simultaneous bilinguals, immigrants, and non-immersion learners, reflecting the fact that they may receive less English input than monolinguals. We modeled a possible developmental change in the learning rate r as a piecewise function in which r is constant from birth to age t c , whereupon it declines according to a sigmoid with shape parameters α and δ (α controls the steepness of the sigmoid, and δ moves its center left or right):

The piecewise structure of this Exponential Learning with Sigmoidal Decay (ELSD) model, and the fact that sigmoid functions can accommodate both flat and steep declines, allows it to capture a very wide range of developmental trajectories, including all of those discussed in the literature. Learning rate may be initially high or low, begin declining at any point in the lifespan (or not at all), decline rapidly or gradually, decline continuously or discontinuously, etc. Examples of the many possibilities encompassed by the model include the different curves shown in Figs. 2 and S2 , as well as the gray lines in Fig. 4E .

The model was fitted simultaneously to the performance curves for monolinguals, immersion learners, and non-immersion learners (cf. Fig. 4A and B ). Parameters were fit with Differential Evolution ( Mullen, Aridia, Gil, Windover, & Cline, 2011 ) and compared using Monte Carlo split-half cross-validated R 2 , which avoids over-fitting. The best-fitting model (R 2 = 0.89) involved a rate change beginning at 17.4 years ( Fig. 4E ). The fit was significantly better than the best fit for alternative models in which learning rate did not change (R 2 = 0.66) or changed according to a step function with no further decline in the learning rate after the initial drop (R 2 = 0.70). Details on these and related models can be found in the supplementary materials .

3.2. Interim discussion

Though the ELSD model is necessarily simplified, the good fit between model and data, and the poorer fit by reasonable alternatives, offers good support for the existence of a critical period for language acquisition, and suggests that our estimate of when the learning rate declines (17.4 years old) is likely to be reasonably accurate.

This age is much later than what is usually found for the offset of the critical period for native-like ultimate attainment of syntax. However, as discussed in the Introduction, because language acquisition takes time, there is no reason to suppose that the last age at which native-like ultimate attainment can be achieved is the same as the age at which underlying ability declines (see also Patkowski, 1980 ). Instead, the relationship between ultimate attainment and critical periods is complex, depending also on how long it takes to learn a language. The ELSD model disentangles these factors. In order to better understand the results of the above analyses, we look at these issues in turn.

3.3. The duration of learning

Little is known about how long it takes learners to reach asymptotic performance. On the one hand, developmentalists have observed that by 3–5 years of age, most children show above-chance sensitivity to many syntactic phenomena ( Crain & Thornton, 2011 ; Pinker, 1994 ). Indeed, our youngest native speakers (~7 years old) were already scoring very well on our quiz ( Fig. 5B ).

(A) Histogram of cutoffs used for minimum years of experience to asymptotic learning in previous studies of syntax ( Abrahamsson, 2012 ; Birdsong & Molis, 2001 ; DeKeyser, 2000 ; DeKeyser et al., 2010 ; Flege et al., 1999 ; Granena & Long, 2013 ; Jia et al., 2002 ; Johnson & Newport, 1989 , 1991 ; Mayberry & Lock, 2003 ; Mayberry, Lock, & Kazmi, 2002 ; McDonald, 2000 ; Weber-Fox & Neville, 1996 ). Papers with multiple studies are included only once, except for McDonald (2000) , which used different cutoffs in two different studies. (B) Accuracy for monolinguals (N = 246,497) and simultaneous bilinguals (N = 30,397). Shadowed area represents ± 1 SE. This highlights information also available in Fig. 4A .

While certainly an important fact about acquisition, this is the wrong standard for research into critical periods. The question has never been “why do non-native speakers not match the competency level of preschooler?” Many of them do. In fact, in our dataset, even non-native immersion learners who began learning in their late 20 s eventually surpassed the youngest native speakers in our dataset ( Fig. 4A ).

Instead, the puzzle driving this entire research domain is why later learners do not reach the same proficiency level of mature native speakers. That is a much higher standard. Many other aspects of syntax continue to develop in the school-age years ( Berman, 2004 , 2007 ; Nippold, 2007 ), and prior studies have not been able to determine the age at which syntactic development concludes. Even for those aspects of syntax that preschoolers are sensitive to, they are rarely at ceiling, and they typically do worse than college-age adults, whether assessed through comprehension, elicited production, or spontaneous production (e.g., Kidd & Bavin, 2002 ; Kidd & Lum, 2008 ; Marcus et al., 1992 ; Messenger, Branigan, McLean, & Sorace, 2012 ; Rowland & Pine, 2000 ). However, while we know that performance continues to improve into the school ages, the literature has little to say about when children attain adult levels of accuracy. Moreover, the common practice of comparing children to college-aged adults necessarily renders undetectable any post-college development.

Even less is known about how long non-native speakers continue to improve on the target language. While a few studies found limited continued improvement for immersion learners after the first five years ( Johnson & Newport, 1989 ; Patkowski, 1980 ), these studies had minimal power to detect continued improvement (see below). Specifically, looking at samples of non-native learners who were selected to have at least three years ( Johnson & Newport, 1989 ) or five years ( Patkowski, 1980 ) of experience, these authors found that while age of first exposure predicted performance, length of experience did not. In contrast, analysis of US Census data suggests that learning continues for decades ( Stevens, 1999 ), though the validity of this self-report data is uncertain. Analysis of foreign language education suggests learning in that context may continue for a couple of decades, though this may merely reflect the slower pace of non-immersion learning ( Huang, 2015 ).

This empirical uncertainty is reflected directly in the ultimate attainment literature. Ultimate attainment analyses require restricting analysis to those subjects who have been learning the target language long enough to have reached asymptote (e.g., Johnson & Newport, 1989 ). In the absence of any clear evidence, researchers have chosen a diverse set of cut-offs, ranging anywhere from three ( Birdsong & Molis, 2001 ; McDonald, 2000 ) to fifteen years ( Abrahamsson, 2012 ) ( Fig. 5A ).

Inspection of Fig. 5B suggests that native speakers did not reach asymptote until around 30 years old, though most of the learning takes place in the first 10–20 years. The results for later learners shown in Fig. 4 similarly suggest a protracted period of learning (for detailed results, see Figs. S21 and S22 in the Supplementary Materials , and surrounding discussion). Note that the increases in performance after the first 15–20 years are modest, which accords with the fact that they are not routinely noticed.

While this prolonged learning trajectory was not anticipated in the language learning literature, it joins mounting evidence that many cognitive abilities continue to develop through adolescence and even adulthood, including working memory, face recognition, magnitude estimation, and various measures of crystalized intelligence ( Germine, Duchaine, & Nakayama, 2011 ; Halberda, Ly, Wilmer, Naiman, & Germine, 2012 ; Hartshorne & Germine, 2015 ).

Thus, even native speakers—who are able to make full use of the critical period—take a very long time to reach mature, native-like proficiency. By implication, someone who started relatively late in the critical period—that is, someone who had limited time to learn at the high rate the critical period provides—would simply run out of time. In order to follow up on this issue and test this implication, we turn to analysis of ultimate attainment.

3.4. Ultimate attainment

Based on the results above, we expect that the last age of first exposure at which native-like attainment is still within reach is likely well prior to 17. Below, we first estimate this age from our own data and then compare that against previous estimates.

Following the usual practice, we first restrict the analysis to those subjects who have been learning English long enough to have reached asymptote (e.g., Johnson & Newport, 1989 ). As described in the previous section, there is no consensus as to how long “long enough” is (see Fig. 5A ). This stems from the fact that, prior to our own study, there was little data to constrain hypotheses (see previous section). Inspection of Figs. 4 and ​ and5 5 suggests 30 years old as a reasonable cutoff.

Thus, to estimate the age at which mastery of a second language is no longer attainable, we analyzed ultimate attainment curves by focusing on the 11,371 immersion learners and 29,708 non-immersion learners who had at least 30 years of experience (ensuring asymptotic learning) and who were at most 70 years old (avoiding age-related decline) ( Fig. 6 ). We fitted these curves using multivariate adaptive regression splines ( Friedman, 1991 ; Milborrow, 2014 ). Immersion learners showed only a minimal decline in ultimate attainment until an age of first exposure of 12 years ( B = −0.009; 0.01 SDs/year), after which the decline became significantly steeper ( B = −0.06; 0.07 SDs/year). Non-immersion learners showed similar results: From 4 years to 9 years, proficiency showed no decline (in fact it increased slightly; B = 0.01; 0.01 SDs/year), followed by a steep decline ( B = −0.06; 0.07 SDs/year). Two other methods of estimating changes in slope provided similar results (see Supplementary Materials ).

Ultimate attainment for monolinguals, immersion learners, and non-immersion learners, smoothed with a three-year floating window. Shadowed areas represent ± 1 SE. Attainment for monolinguals was significantly higher than that of simultaneous bilinguals (immersion learners with exposure age = 0) ( p < .01).

While these analyses employ the standard method of analyzing subjects who have (presumably) already reached ultimate attainment, the density of our data allows a more direct analysis. Fig. 7 re-plots the data in Fig. 4 against years of experience, aligning the curves for the learners who began at different ages at the onset of learning. Inspection reveals that the learning trajectories for immersion learners who began in the first decade of life (the orange curves) are almost indistinguishable ( Fig. 7A ). We see a similar trend for the non-immersion learners ( Fig. 7B ).

Accuracy as a function of years of experience, by age of first exposure for immersion learners (A) and non-immersion learners (B). Color scheme is same as in Fig. 4 . Red: monolinguals. Orange: AoFE < 11. Green: 10 < AoFE < 21. Blue: AoFE > 20. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

We confirmed these observations with permutation analysis. Specifically, we calculated the average difference between each performance curve and the performance curve for the youngest learners of that type (the simultaneous bilinguals for immersion learners, the learners with an age of first exposure of 4 years for the non-immersion learners). A positive score indicated that the performance curve was, on average, below the curve for the earliest learners. We then constructed an empirical distribution by randomly permuting the age of exposure across participants at a given number of years of experience. The curves were again smoothed with five-year floating windows and the difference scores were again calculated. This was repeated 1000 times. The percentage of cases in this distribution in which the difference score for a given performance curve is larger than the actual difference score for that performance curve serves as a one-tailed p -value (all comparisons reported as significant are also significant as two-tailed tests). These analyses revealed that the performance curves for immersion learners with average exposure ages of 2, 5, and 8 years were not significantly different from those of simultaneous bilinguals (exposure age = 0; p s > 0.31), while the curves for later learners were significantly lower ( p s < 0.01). Similarly, non-immersion learners with ages of exposure of 5–11 years were indistinguishable from our earliest non-immersion learners (4 years; ps > 0.31), whereas later learners learned significantly more slowly ( p s < 0.01).

3.4.1. Comparison with previous ultimate attainment results

Both traditional ultimate attainment analyses and permutation analyses indicated that learners must start by 10–12 years of age to reach native-level proficiency. Those who begin later literally run out of time before the sharp drop in learning rate at around 17–18 years of age. For non-immersion learners, the ceiling was lower but the overall story was the same: little difference between learners who start within the first decade of life, with a ceiling that noticeably drops for later learners. These findings are consistent with the protracted trajectory of learning that we observe in our data (see previous section).

However, our results for immersion learners diverge from those of some previous studies (there are no similar studies of non-immersion learners). For instance, Johnson and Newport’s (1989) study of immersion learners found no correlation between ultimate attainment and age of first exposure after an onset age of 16, whereas we see a strong relationship (for review, see Qureshi, 2016 ). In principle, this could be due to differences in subject population or the types of grammar rules tested. Indeed, researchers frequently argue that such differences have large effects on ultimate attainment, based on the fact that studies of different populations or stimuli have produced different results ( Abrahamsson, 2012 ; Birdsong & Molis, 2001 ; DeKeyser, 2000 ; DeKeyser et al., 2010 ; Flege et al., 1999 ; Granena & Long, 2013 ; Hakuta et al., 2003 ; Jia et al., 2002 ; Johnson & Newport, 1989 ; Vanhove, 2013 ; Weber-Fox & Neville, 1996 ).

However, a recent analysis by Vanhove (2013) raised questions about whether these differences are statistically meaningful. Whereas most prior studies had between 50 and 250 subjects, Vanhove demonstrates that precisely measuring how ultimate attainment changes as a function of age of first exposure requires thousands. Only one previous dataset, based on US Census data, reaches sufficient sample size ( Hakuta et al., 2003 ; Stevens, 1999 ). However, this study was based on a self-report of proficiency on a four-point scale, which is unlikely to have much precision. Thus, differences across findings in the literature could reflect nothing more than random noise.

Thus, in order to better understand whether the differences in our findings and those of prior studies are meaningful, we need to consider the precision of these findings. We estimated precision using bootstrapping, simulating running many different studies by resampling with replacement from our own data ( Efron & Tibshirani, 1993 ). The results of each simulation will be slightly different, and so the range of results across simulations simulates the variability we would expect from statistical noise alone. Crucially, we can simulate running studies with different sample sizes. Thus, we can ask whether Johnson and Newport’s (1989) findings are within what we might have found had we used our own methods but tested the same number of subjects (N = 69).

For our simulations, we considered two different sample sizes: N = 69, the size of the classic Johnson and Newport (1989) study, and N = 275, larger than the largest prior study, with the exception of the aforementioned Census studies. For comparison, we also simulated studies with N = 11,371, the number of subjects in our own ultimate attainment results described in the previous section.

We focused on three different analyses that have been reported in a number of prior studies ( Bialystok & Miller, 1999 ; Birdsong & Molis, 2001 ; DeKeyser, 2000 ; DeKeyser et al., 2010 ; Flege et al., 1999 ; Johnson & Newport, 1989 ; Weber-Fox & Neville, 1996 ). First, we considered Johnson and Newport’s finding that the correlation between age of first exposure and ultimate attainment is much stronger before an exposure age of 16 ( r = −0.87) than after ( r = −0.16). This finding has proved controversial, with subsequent studies finding much weaker effects or no effect at all ( Bialystok & Miller, 1999 ; Birdsong & Molis, 2001 ; DeKeyser, 2000 ; Johnson & Newport, 1989 ). All these prior findings are well within what one would expect for N = 69 ( Fig. 8 , upper left). As power increased, the variability in the estimates dropped dramatically, with more highly-powered studies being increasingly unlikely to find any substantial difference in the correlations before and after 16 years old.

We conducted 2500 simulated experiments of monolingual and immersion learners with each of three sample sizes: N = 69 (equivalent to Johnson & Newport, 1989 ), N = 275 (larger than the largest prior lab-based study), and N = 11,371 (equivalent to the present study). Three analyses were considered. Left: Correlation between age of first exposure and ultimate attainment prior to 16 years old minus after 16 years old. Middle: First subgroup of subjects to be significantly worse than monolinguals in a t -test (note: the top graph uses the same age bins as Johnson & Newport, 1989 ). Right: age of first exposure at which performance begins to decline more rapidly, if any. Blue: estimates from Bialystok and Miller (1999) , Birdsong and Molis (2001) , DeKeyser (2000) , DeKeyser et al. (2010) , Flege et al. (1999) , Johnson and Newport (1989) , and Weber-Fox and Neville (1996) . While many other papers addressed similar issues, these papers provide the closest analog to Johnson & Newport in that they used a broad-spectrum test of syntax, defined the onset of learning as the age at immigration, and (crucially) report comparable statistics. Red: estimates from current study. Full details available in Supplementary Materials . (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Second, Johnson and Newport also reported that individuals who began learning English at 8–10 years old failed to reach monolingual-like ultimate attainment, whereas individuals who began earlier did, suggesting that the “optimal period” for language-learning is 0–7 years old. Once again, there has been considerable variability in subsequent studies, and our own study finds that even simultaneous bilinguals do not quite reach monolingual levels. Vanhove (2013) suggested, based on power calculations, that accurately estimating the end of the optimal period requires thousands of subjects. Although a small study can detect very large effects, the differences between learners who began just within the optimal period and those who began just after are relatively small ( Fig. 6 ) and thus undetectable with a low-power study. Our simulations confirm this analysis ( Fig. 8 , middle column): in our simulation of Johnson & Newport ( Fig. 8 , middle column, top), the 95% confidence interval contained almost the entire range. Even with 275 subjects, a wide range of findings would be expected. However, simulations based on our full sample show no variability at all, with learners who began at 1 year of age performing reliably worse than monolinguals ( Fig. 8 , middle column, bottom).

Third, whereas the previous analysis of the optimal period followed Johnson and Newport’s method of using t-tests to compare native speakers to groups of later-learners, subsequent researchers have used instead curve estimation—typically segmented regression with breakpoint estimation—which is argued to be more precise and less prone to false positives ( Birdsong & Molis, 2001 ; Vanhove, 2013 ; but see DeKeyser et al., 2010 ). If there is an optimal period, the slope of the ultimate attainment curve should initially be close to 0, followed by a point where it becomes significantly more negative. By this standard of evidence, most studies have failed to find any evidence of an optimal period ( Birdsong & Molis, 2001 ; Flege et al., 1999 ; Vanhove, 2013 ). Our simulations suggest these prior findings were false negatives due to low power: Like the majority of prior studies, low-power simulations elicited largely null results, whereas high-power simulations suggested an optimal period ending in early or middle childhood ( Fig. 8 , right).

3.4.2. Interim discussion

Two sets of analyses of our data suggest that learners who begin as late as 10–12 years old reach similar levels of ultimate attainment as native bilinguals. After that age, we find a continuous decline in attainment as a function of age of first exposure, with no evidence that this relationship ceases after a particular age (cf. Johnson & Newport, 1989 ; Pulvermüller & Schumann, 1994 ). These findings are consistent with our results for learning rate. Interestingly, these findings held not only for immersion but also non-immersion learners, a population that has not been much studied in this regard.

Our findings do contrast with the conclusions of some prior studies of ultimate attainment in immersion learners. However, as our simulations show, these conclusions were probably overfit to point estimates. That is, conclusions depended on the most probable estimate (the optimal period ends at 8 years of age), ignoring the error bars, which in some cases were likely so large as to encompass the entire possible range ( Fig. 8 ). In contrast, our larger sample size allows for fairly precise estimates ( Fig. 8 ). These simulations support Vanhove’s (2013) contention that thousands of subjects are required to provide reliable conclusions about ultimate attainment. Note that we cannot conclude that differences in stimuli or population do not matter for ultimate attainment, only that studying such effects requires very large datasets. We return to this issue in the General Discussion.

4. General discussion

Taken together, the analyses above all point to a grammar-learning ability that is preserved throughout childhood and declines rapidly in late adolescence. This model provided a better fit to the data than did a wide range of alternatives, including models with declines that were earlier or later, faster or slower, sharper or smoother.

In addition to providing the first empirical estimate of how language-learning ability changes with age, we addressed two related issues. First, we found that native and non-native learners both require around 30 years to reach asymptotic performance, at least in immersion settings. While this question has not been previously addressed, these findings are compatible with what is known about the initial period of learning.

Second, we found that ultimate attainment—that is, the level of asymptotic performance—is fairly consistent for learners who begin prior to 10–12 years of age. We found no evidence that the ultimate attainment curve reaches a floor at around puberty, as has been previously proposed ( Johnson & Newport, 1989 ). While these results differed from the conclusions of some prior studies, our simulations showed that the prior findings were in fact too noisy to provide precise estimates. 3 To provide reliable results about ultimate attainment, a study should have in excess of 10,000 subjects (see also Vanhove, 2013 ). This suggests that the results of those prior studies, all but one of which has fewer than 250 subjects, largely reflect statistical noise. The remaining study had many subjects but uncertain validity (see discussion above).

This set of results is internally consistent, adding credibility to the whole. However, our conclusions—like any conclusions—are only as good as the data supporting them. Below, we address a number of possible concerns. These include both methodological concerns about the data and how they were collected but also more theoretical concerns, like the possibility that results differ across subsets of subjects or items. We then conclude by discussing the implications of our results, should they prove valid and robust.

4.1. Potential concerns and complications

4.1.1. familiarity with the testing procedure.

One possible concern is that differences across subjects were due to age-related differences in familiarity with the Internet. Prior comparisons of Internet-based and offine datasets have found little support for this concern ( Hartshorne & Germine, 2015 ). Similarly, some of the differences between children and adults could conceivably be due to general test-taking ability. In order to better understand interactions between subject age and test method, if any, it would be ideal to gather data from a variety of tests in a variety of modalities.

Crucially, however, most of our analyses did not depend on the current age of the subject but on their age at first exposure, which should weaken any effects of current age. Moreover, we can compare the learning trajectories of learners who started at different ages (see Figs. 4 and ​ and7 7 but especially Figs. S21–S22 in the Supplementary Materials ). If older subjects are substantially better at taking our test, this should appear as more rapid early learning. As inspection of the figures indicates, any such effect is inconsistent and small.

4.1.2. Test modality

Our use of a written comprehension test was dictated by our methodology. Comprehension studies can be scored automatically (which is crucial when there are over half a million subjects), and written tests do not require high-quality audio equipment or sound booths. Nonetheless, one might ask how these choices affected our results.

Certainly, differences between production and comprehension and between written and oral modalities can affect comparisons between native and non-native speakers ( Bialystok & Miller, 1999 ). Listening places high demands on speed and memory (one can re-read but not rehear), and the speech must be analyzed by non-native acoustic phonetics and phonology, which we do not test here. Written tests require literacy. Production allows one to strategically avoid difficult and imperfectly learned words and constructions.

Whether any of these factors affect estimates of a critical period depends on whether they interact with the variables that define critical period effects, namely age at first exposure, current age, and years of experience. While the necessary studies are not currently feasible, this is likely to change as technology improves. (For instance, we are exploring the use of machine learning to characterize the nativeness of a written text.)

Importantly, none of these considerations would make the study of critical periods in written comprehension uninteresting or uninformative, merely complex. Results from any modality must reflect underlying grammatical ability at least to some degree, and reading comprehension is important in its own right, given the importance of reading in many modern societies. (In fact, for many non-native speakers, this may be their primary use for the non-native language.)

4.1.3. Item selection and quiz difficulty

Another potential worry is that our results may depend on smallish differences among subjects who are already near the ceiling (for relevant discussion, see: Abrahamsson & Hyltenstam, 2009 ; Birdsong, 2006 ). Mitigating this concern is that, as we argued in the Introduction, the ceiling is where all the action is. What is remarkable about language is that we are (nearly) all extremely good at it, including adult learners. For reference, we noted that over-regularizations of irregular verbs, which are among the most salient errors in the speech of preschoolers, occur in only 0.75% of their utterances. On a continuum of linguistic ability that includes apes and machines at one end, preschoolers and reasonably diligent late learners are clustered at the other end, near native-speaking adults. Indeed, the question in the critical period literature has never been why adults are incapable of learning a new language—obviously they are—but why adult learners so rarely (if ever) achieve native-like mastery. Likewise, asking whether adult learners can master basic syntax may be theoretically interesting but distracts from the original motivation for this literature: adult learners rarely, if ever, achieve the same level of mastery as those who started in childhood. In order to study that phenomenon, the relevant yardstick is the asymptotic performance of native speakers.

Still, we can ask whether our results hold for both items mastered early in typical development and for items mastered only in adolescence or adulthood. We found no evidence of such a difference: In the best-fitting models of learning, the learning rate began to slow at approximately the same time for the 47 items that are mastered by the youngest monolingual English-speakers in the sample (ages 7–8) as for the 48 items that are mastered only by the older ones: 17.3 years old and 18.2 years old, respectively. Moreover, if there were substantial interactions between item and age of first exposure, we would expect to see substantial differences in terms of which items were more or less difficult for early and late learners. However, item difficulty was strongly correlated across learners regardless of age of first exposure (for details of these analyses, see Supplementary Materials , “Item Effects”).

We might similarly ask whether results vary based on the type of syntactic construction tested. Prior analyses of ultimate attainment have provided conflicting results, likely due to the power issues discussed above ( Coppieters, 1987 ; Flege et al., 1999 ; Johnson & Newport, 1989 , 1991 ; McDonald, 2000 ; Weber-Fox & Neville, 1996 ) and the theoretical issues raised below. Our just-discussed analyses of item difficulty provide some initial evidence against substantial differences across syntactic phenomena. More precise analyses would involve the direct comparison of different types of constructions. Unfortunately, our quiz was designed to cover a wide range of phenomena, and thus we have few items of any given type, making it difficult to distinguish differences between items and differences between item types . In any case, such analyses raise thorny theoretical questions: different theories of syntactic processing categorize phenomena differently, and any given sentence involves many different phenomena. Thus, classifying items by syntactic phenomena is far from trivial and may not even be the right approach. Progress on this question will require a significant amount of further research. 4 If it turns out that different aspects of syntax do indeed have different critical periods, the conclusions presented here would need to be revised. Design of follow-up studies may be informed by comparing items in our dataset, which is available at http://osf.io/pyb8s .

4.1.4. The effect of the first language

Our results are unlikely to be specific to any one language or language family: Participants listed more than 6000 native languages or combinations of them. The best-represented language families among immersion and non-immersion learners were Uralic (N = 54,664), Slavic (N = 41,640), West Germanic (N = 38,385), Romance (N = 40,476), Turkic (N = 29,816), and Chinese (N = 15,161). The remaining 29% of participants either had multiple native languages or had native languages belonging to a different family. Thus, no language contributed more than a small fraction of the immersion or non- immersion learners ( Fig. 3C ). However, this leaves the possibility that our results reflect an epiphenomenal average of very different trajectories for very different types of learners ( Bialystok & Miller, 1999 ; McDonald, 2000 ).

It is uncontroversial that speakers of different native languages make characteristic mistakes when speaking English ( Schachter, 1990 , among others); indeed, the algorithm we used as part of our recruitment strategy depended on this fact (see Section 2.2). However, that is logically distinct from the question as to whether critical periods differ across native languages. Ideally, we would compare the results of our model for speakers of different native languages. However, our samples of individual languages are too small. Specifically, because our data are unevenly distributed across ages and learner conditions, we risk over-fitting certain conditions (such as monolinguals) at the expense of others. As described in the Method, we circumvented this issue by averaging across subjects in each bin prior to running the model. This is not applied easily to subsets of the data: too many bins have few or no subjects. In any case, we lack a computationally tractable method for comparing model fits for different datasets. Thus, we must leave this for future research.

We can, however, address a related question. It could be that speakers of different native languages learn English more or less quickly and to a greater or lesser degree. At best, this would add noise to our analyses. At worst, to the extent that native language is confounded with other variables of interest in our sample (e.g., age of first exposure), it could have distorted our results. Anecdotally, many people perceive that speakers of certain languages are better or worse at English, though it is hard to know how much this is confounded with accent (which likely has a critical period distinct from that of syntax), cultural variation in age at first exposure, and differences in the types of exposure (e.g., songs, movies, tourism, coursework) and instructional methods. For instance, in our dataset, speakers of Chinese and Western Germanic languages tended to start learning English in immersion settings earlier than speakers of Turkic or Uralic languages (5.2 and 5.9 years old vs. 13.4 and 14.8 years old, respectively). More systematically, some studies have suggested different patterns of ultimate attainment for speakers of different native languages ( Bialystok & Miller, 1999 ), though caution is warranted given the extremely low power for such studies (see Fig. 8 and surrounding discussion).

We considered the effect of native language on three different metrics of learning success: the level of ultimate attainment (how well the most advanced learners do), the age at the end of the optimal period (the last age to start learning in order to reach native-like performance), and the shape of the learning curve (performance as a function of years of experience). In keeping with our earlier analyses, ultimate attainment was defined as the average performance for subjects no older than 70 years old and with at least 30 years of experience with English. To increase power, we grouped subjects into Uralic, Slavic, West Germanic, Romance, and Chinese language groups (no other language group had nearly as many speakers at similarly wide ranges of years of experience and ages of first exposure). For each measurement, we assessed the level of evidence that speakers of one language group differed from the others using Bayes Factor model comparison with the BIC approximation ( Wagenmakers, 2007 ). Details for all analyses are provided in the Supplementary Materials , under “Item Effects.”

By looking at ultimate attainment, we can assess whether speakers of different languages have greater or lesser success in learning English, equating for years of experience. In fact, the differences across language groups were small (see Fig. S14 ) and generally not reliable. In most cases, analyses favored the null hypothesis (no difference between the target language and the other languages), and differences across language groups were inconsistent: among learners who began at age 0, the best-performing language group was Romance, for learners beginning at 1–5 years old, it was West Germanic, and for learners who began at 6–10 years old, it was Chinese. Likewise, analysis indicated that the length of the optimal period does not vary across language groups. We found slightly more evidence for differences in learning curves. In particular, simultaneous English-Chinese speakers could be distinguished from the rest, whereas simultaneous bilinguals who spoke Romance or West Germanic languages both matched the overall pattern. However, the actual differences are subtle and seem to reflect slightly faster initial learning by the Chinese speakers ( Fig. S18 ). Most other comparisons were not possible due to insufficiently many subjects (see Supplementary Materials ).

Thus, although speakers of different languages make different mistakes, we find only limited evidence of differences in learning once learning context (immersion vs. non-immersion), years of experience, and age at first exposure are taken into account. That said, power analyses suggest that we only had sufficient subjects to detect relatively large effects, meaning that we cannot rule out more subtle differences (see Supplementary Materials , under “Item Effects”). These power analyses should, however, provide guidance on sample sizes for future research along these lines.

Whatever these analyses say about language-learning in general, they do not provide any evidence that our findings were heavily confounded by differences across the native languages in our sample.

4.2. Implications

The analyses above suggest that our findings are reasonably robust, particularly in comparison to those of previous studies. While this inspires confidence, it should also suggest caution: future work that successfully addresses the limitations of the present study may similarly prompt significant revisions in what we believe to be true. Science is the process of becoming less wrong, and while hopefully the revisions are smaller and smaller after each step, there is no way of knowing that this is the case in advance. Thus, confirmation and extension of the present results is crucial, particularly given the novelty of our questions, methods, models, and results.

Nonetheless, we believe it is useful to consider the implications of the present findings, on the presumption that they prove to be (reasonably) robust:

4.2.1. The nature of the critical period for second language acquisition

On the assumption that the present results apply broadly to syntax acquisition by diverse learners, they have profound theoretical implications. Most importantly, they clarify the shape of the well-attested critical period for second-language acquisition: a plateau followed by a continuous decline. The end of the plateau period must be due to changes in late adolescence rather than childhood, whether they are biological, social, or environmental. Thus the critical period cannot be attributed to neuronal death or syntactic pruning in the first few years of life, nor to hormonal changes surrounding adrenarche or puberty ( Johnson & Newport, 1989 ; Lenneberg, 1967 ; Pinker, 1994 ). Also casting doubt on the effect of hormones is our finding that girls do not show a decline in learning ability before boys do, despite their earlier age of puberty (see Supplementary Materials ). Likewise, the critical period cannot be explained by documented developmental changes in working memory, episodic memory, reasoning ability, processing speed, or social cognition ( Hakuta et al., 2003 ; Hartshorne & Germine, 2015 ; Klindt, Devaine, & Daunizeau, 2017 ; Morgan-Short & Ullman, 2012 ; Newport, 1988 ), to the diminished likelihood that adolescent and adult immigrants will be immersed in an environment of native speakers and identify with the new culture, 5 or to gradually accumulating interference from a first language ( Hernandez et al., 2005 ; Jia et al., 2002 ; Sebastián-Gallés et al., 2005 ).

In short, these data are inconsistent with any hypothesis that places the decline in childhood—which is to say, every prior specific hypothesis that we know of. What, then, could explain the critical period? There are a number of possibilities. For instance, it remains possible that the critical period is an epiphenomenon of culture: the age we identified (17–18 years old) coincides with a number of social changes, any of which could diminish one’s ability, opportunity, or willingness to learn a new language. In many cultures, this age marks the transition to the workforce or to professional education, which may diminish opportunities to learn. Note that causality (if any) could run the other direction: cultures may have chosen this age for certain transitions because of age-dependent changes in neural plasticity. Further traction on these issues could come from cross-cultural comparison, or comparison of individuals within a culture who are on different educational tracks.

Alternatively, the critical period could reflect interference from the first language, so long as this interference is non-linear rather than gradually accumulating. While it has generally been assumed that interference from the first language would be proportional to the amount of first language learned—something inconsistent with our data—we cannot rule out the possibility of non-linear interference. Neural network models, which are capable of showing interference from a first language ( Hernandez et al., 2005 ), can exhibit surprising nonlinearities ( Haykin, 1999 ; Hernandez et al., 2005 ). It remains to be seen whether they can successfully model the nonlinearities we actually observed.

Finally, the end of the critical period might reflect late-emerging neural maturation processes that compromise the circuitry responsible for successful language acquisition (whether specific to language or not). While language acquisition researchers often focus on neural development in the childhood years, the brain undergoes significant changes through adolescence and early adulthood ( Blakemore & Mills, 2014 ; Mills, Lalonde, CLasen, Giedd, & Blakemore, 2014 ; Pinto, Hornby, Jones, & Murphy, 2010 ; Shafee, Buckner, & Fischl, 2015 ; Tamnes et al., 2010 ). While continued develoment of the prefrontal cortex is perhaps the most familiar, changes occur throughout the brain and along multiple dimensions. Drawing on these and other findings, some researchers have suggested that adolescence may involve a number of different biologically-driven critical periods ( Crews, He, & Hodge, 2007 ; Fuhrmann, Knoll, & Blakemore, 2015 ; see also Ghitza & Gelman, 2014 ).

Little is certain about the relationship between neural maturation and behavioral maturation, other than the likelihood it is complex. Current evidence suggests that critical periods in perception involve a complex interplay of neurochemical and epigenetic promoters and brakes for both synaptic pruning and outgrowth ( Werker & Hensch, 2015 ). Given this complexity, and the relative sparseness of the data on neural maturation, it is hard to say whether any of the identified neural maturation processes might correspond to the changes in syntax acquisition that we observed.

Nor can we do much more than speculate as to whether these maturational process (if any) are specific to structures subserving language acquisition. It is notable that language-learning ability is, out of every cognitive ability whose developmental trajectory has been characterized behaviorally, the only one that is stable through childhood and declines sharply in late adolescence ( Hartshorne & Germine, 2015 ). This observation is consistent with the possibility of language-specific maturation. However, the developmental trajectories of some cognitive abilities, such as procedural memory, have not been well characterized ( Fuhrmann et al., 2015 ; Hartshorne & Germine, 2015 ). Moreover, cognitive testing has largely focused on simple abilities that can be measured in a single, short session (e.g., working memory). In contrast, syntax acquisition takes place over much longer intervals and involves learning a complex, interlocking system. Thus, progress on this question will require characterization of a broader range of cognitive abilities, as well as acquisition of other complex systems (e.g., music or chess).

In attempting to gain traction on these issues, there are additional complexities, which future studies should seek to clarify. The duration of the critical period may differ for other aspects of language, like phonology and vocabulary. Moreover, we cannot be certain that syntax learning ability is a unitary construct rather than the combination of multiple factors potentially operating on distinct timelines and affecting different aspects of syntax differently. Second, the exact timing of the critical period may be obfuscated by older learners deploying conscious learning strategies, absorbing explicit instruction, or transferring knowledge from the first language. Some purchase on these issues may come from additional studies, potentially using different methods (e.g., online processing, production, ERP, or longitudinal studies), should obtaining sufficiently many subjects become feasible. Finally, because our dataset consists of people’s performance in a second language, it does not directly address the question of how age affects the learning of a first language. It is possible that exposure to linguistic input delays the atrophy of language learning circuitry, in which case the decline in learning ability we have documented would represent the prolongation of a critical period that terminates sooner in people who have been deprived of all language input ( Curtiss, 1994 ; de Villiers, 2007 ; Mayberry, 1993 ; Newport, 1990 ). Because delayed first-language acquisition is fortunately rare, it would be impossible to achieve a sample size similar to the one here, but our results could be used to guide smaller, targeted studies.

Crucially, the investigation of these issues—all of which have long been of interest but difficult to address—can now be guided by the finding that the ability to learn the grammar of a new language, though indeed compromised in adults compared to children, is largely or entirely preserved up to the cusp of adulthood.

4.2.2. Additional implications

The dataset bears on many issues beyond those discussed in detail above. For instance, the data contain a rich source of information about dialect variation and L1 transfer effects. We briefly mention a few other issues. First, prior work has indicated that simultaneous bilinguals do not reach the same level of proficiency in phonology as individuals with a single first language ( Sebastián-Gallés et al., 2005 ). We extend this finding to syntax, where it is apparent throughout the lifespan Fig. 5B ). ( This finding is consistent with some earlier work suggesting that a sufficiently sensitive test can distinguish even highly proficient bilinguals from monolinguals ( Abrahamsson & Hyltenstam, 2008 , 2009 ). 6 Our model captures this difference as one of exposure, estimating that simultaneous bilinguals receive only 63% as much English input as monolinguals (see Fig. S6 ). Though parsimonious, this is not the only possible explanation; alternatives include the effects of suppression of the non-target language and influences of each language on the other ( Birdsong & Gertken, 2013 ).

Similarly, there are a number of interesting demographic effects. We confirm prior findings of a main effect of education on ultimate attainment, with post-secondary education resulting in higher accuracy (see Supplementary Materials , “Education Differences”) ( Birdsong, 2014 ; Hakuta et al., 2003 ). We likewise find a main effect for gender, with higher accuracy by females (see Supplementary Materials , “Gender Differences”). In neither case do these main effects appear to interact with age at first exposure, and so they are unlikely to be relevant for critical periods. However, they likely have implications for other aspects of language learning.

We have made the data available ( http://osf.io/pyb8s ) in the hopes they will be prove informative for investigation of these and other questions.

Supplementary Material

Supplemental, acknowledgments.

We are indebted to David Barner, David Birdsong, Kenji Hakuta, Elissa Newport, Laura-Ann Petitto, and Michael Ullman for comments, to Tanya Ivonchyk and Brandon Benson for help with developing the quiz, and to the hundreds of thousands of volunteers who participated in the study. This research was supported by an NIH NRSA award to JKH (5F32HD072748) and the Center for Minds, Brains, & Machines (NSF STC CCF-1231216).

Appendix A. Supplementary material

Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.cognition.2018.04.007 .

1 The first several thousand participants were asked to list their “native languages.” Based on participant feedback, this was adjusted to “native languages (learned from birth).”

2 A small proportion of the non-immersion learners (2.7%) reported ages of first exposure between 1 and 3 years. These learners scored quite poorly (the ultimate attainment of those with ages of exposure of 1 year was as poor as those with ages of exposure in their 20 s) and exhibited noisy performance curves that, unlike those of all other learners, failed to show any improvement with age ( Fig. S1 ). While this might be a genuine and surprising finding, it more likely reffects the idiosyncratic histories or questionnaire responses of these learners. Unlike the later non-immersion learners, many of whom cited school instruction as their initial source of their exposure, the early non-immersion learners gave little indication about the nature of their first exposure, and it is possible that they had little formal instruction and had learned primarily through television and movies (frequently cited by non-immersion learners as significant sources of English input). Given this uncertainty, we excluded these participants from the main analyses.

3 We also noted a number of limitations and confounds in prior studies, such as how ultimate attainment was defined, which would have biased results. However, detailed investigation shows that the resulting biases and imprecisions were likely swamped by the effect of low power (see Supplementary Materials , “Effect of Analysis Decisions”).

4 We note a further difficulty. All research in this domain has treated items as fixed effects, averaging across them. This simplifies calculation, but at a cost: such statistical analyses do not directly assess the question of whether the results generalize beyond the items used ( Baayen, Davidson, & Bates, 2008 ; Clark, 1973 ). This problem is mitigated somewhat when using a large and representative set of items—as we do—but is particularly problematic when looking at smaller samples of items. The standard solution currently is to use mixed effects modeling ( Baayen et al., 2008 ). However, mixed effects modeling requires significant computational power. We have so far been unable to identify a tractable method of applying mixed effects modeling to a dataset the size of the present one.

5 Note that while critical period researchers widely assume that there are age-related effects on cultural identification among immigrant groups, this may not in fact be the case ( Chudek, Cheung, & Heine, 2015 ).

6 This finding also has practical consequences for research. Many researchers have argued that if later learners can reach monolingual levels of performance, that would be evidence against critical periods (and conversely, the failure of later learners to match monolinguals would be evidence for critical periods) (e.g., Abrahamsson & Hyltenstam, 2009 ). This standard, in conjunction with our results, leads to the unlikely conclusion that the critical period for syntax closes prior to birth. For additional discussion, see Birdsong and Gertken (2013) .

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• Beelinguapp

Stephen Krashen’s Five Hypotheses of Second Language Acquisition

Unsplash Monica Melton

Interested in learning more about linguistics and linguists ? Read this way.

What is linguistics? Linguistics is the scientific study of language that involves the analysis of language rules, language meaning, and language context. In other words, linguistics is the study of how a language is formed and how it works.

A person who studies linguistics is called a linguist . A linguist doesn't necessarily have to learn different languages because they’re more interested in learning the structures of languages. Noam Chomsky and Dr. Stephen Krashen are two of the world’s most famous linguists.

Dr. Stephen D. Krashen facilitated research in second-language acquisition , bilingual education, and in reading. He believes that language acquisition requires “meaningful interaction with the target language.”

Dr. Krashen also theorized that there are 5 hypotheses to second language acquisition , which have been very influential in the field of second language research and teaching

Let’s take a look at these hypotheses. Who knows, maybe you’ve applied one or all of them in your language learning journey!

1. Acquisition-Learning Hypothesis

The Acquisition-Learning Hypothesis states that there is a distinction between language acquisition and language learning. In language acquisition, the student acquires language unconsciously . This is similar to when a child picks up their first language. On the other hand, language learning happens when the student is consciously discovering and learning the rules and grammatical structures of the language.

2. Monitor Hypothesis

Monitor Hypothesis states that the learner is consciously learning the grammar rules and functions of a language rather than its meaning. This theory focuses more on the correctness of the language . To use the Monitor Hypothesis properly, three standards must be met:

• The acquirer must know the rules of the language.
• The acquirer must concentrate on the exact form of the language.
• The acquirer must set aside some time to review and apply the language rules in a conversation. Although this is a tricky one, because in regular conversations there’s hardly enough time to ensure correctness of the language.

3. Natural Order Hypothesis

Natural Order Hypothesis is based on the finding that language learners learn grammatical structures in a fixed and universal way . There is a sense of predictability to this kind of learning, which is similar to how a speaker learns their first language.

4. Input Hypothesis

Input Hypothesis places more emphasis on the acquisition of the second language. This theory is more concerned about how the language is acquired rather than learned.

Moreover, the Input Hypothesis states that the learner naturally develops language as soon as the student receives interesting and fun information .

5. Affective Filter Hypothesis

In Affective Filter, language acquisition can be affected by emotional factors. If the affective filter is higher, then the student is less likely to learn the language. Therefore, the learning environment for the student must be positive and stress-free so that the student is open for input.

Language acquisition is a subconscious process. Usually, language acquirers are aware that they’re using the language for communication but are unaware that they are acquiring the language.

Language acquirers also are unaware of the rules of the language they are acquiring. Instead, language acquirers feel a sense of correctness, when the sentence sounds and feels right. Strange right? But it is also quite fascinating.

Acquiring a language is a tedious process. It can seem more like a chore, a game of should I learn today or should I just do something else? Sigh

But Dr. Krashen’s language acquisition theories might be onto something, don’t you think? Learning a language should be fun and in some way it should happen naturally. Try to engage in meaningful interactions like reading exciting stories and relevant news articles, even talking with friends and family in a different language. Indulge in interesting and easy to understand language activities, and by then you might already have slowly started acquiring your target language!

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Philosophy of Linguistics

Philosophy of linguistics is the philosophy of science as applied to linguistics. This differentiates it sharply from the philosophy of language, traditionally concerned with matters of meaning and reference.

As with the philosophy of other special sciences, there are general topics relating to matters like methodology and explanation (e.g., the status of statistical explanations in psychology and sociology, or the physics-chemistry relation in philosophy of chemistry), and more specific philosophical issues that come up in the special science at issue (simultaneity for philosophy of physics; individuation of species and ecosystems for the philosophy of biology). General topics of the first type in the philosophy of linguistics include:

• What the subject matter is,
• What the theoretical goals are,
• What form theories should take, and
• What counts as data.

Specific topics include issues in language learnability, language change, the competence-performance distinction, and the expressive power of linguistic theories.

There are also topics that fall on the borderline between philosophy of language and philosophy of linguistics: of “linguistic relativity” (see the supplement on the linguistic relativity hypothesis in the Summer 2015 archived version of the entry on relativism ), language vs. idiolect , speech acts (including the distinction between locutionary, illocutionary, and perlocutionary acts), the language of thought, implicature, and the semantics of mental states (see the entries on analysis , semantic compositionality , mental representation , pragmatics , and defaults in semantics and pragmatics ). In these cases it is often the kind of answer given and not the inherent nature of the topic itself that determines the classification. Topics that we consider to be more in the philosophy of language than the philosophy of linguistics include intensional contexts, direct reference, and empty names (see the entries on propositional attitude reports , intensional logic , rigid designators , reference , and descriptions ).

This entry does not aim to provide a general introduction to linguistics for philosophers; readers seeking that should consult a suitable textbook such as Akmajian et al. (2010) or Napoli (1996). For a general history of Western linguistic thought, including recent theoretical linguistics, see Seuren (1998). Newmeyer (1986) is useful additional reading for post-1950 American linguistics. Tomalin (2006) traces the philosophical, scientific, and linguistic antecedents of Chomsky’s magnum opus (1955/1956; published 1975), and Scholz and Pullum (2007) provide a critical review. Articles that have focused on the philosophical implications of generative linguistics include Ludlow (2011) and Rey (2020). For recent articles on the philosophy of linguistics more generally, Itkonen (2013) discusses various aspects of the field from its early Greek beginnings, Pullum (2019) details debates that have engaged philosophers from 1945 to 2015, and Nefdt (2019a) discusses connections with contemporary issues in the philosophy of science.

1.1 The Externalists

1.2 the emergentists, 1.3 the essentialists, 1.4 comparing the three approaches, 2.1 competence and performance, 2.2 ‘i-language’ and ‘e-language’, 2.3 the faculty of language in narrow and broad senses, 2.4 linguistic ontology, 2.5 components of linguistic theories, 3.1 acrimony over linguistic intuitions, 3.2 grammaticality and acceptability judgments, 3.3 assessing degrees of acceptability, 3.4 informal and experimental elicitation, 3.5 what informal methods actually are, 3.6 corpus data, 4.1 linguistic nativism, 4.2 language learnability, 5.1 phylogenetic emergence, 5.2 historical evolution, other internet resources, related entries.

• Supplement on Whorfianism

1. Three Approaches to Linguistic Theorizing: Externalism, Emergentism, and Essentialism

The issues we discuss have been debated with vigor and sometimes venom. Some of the people involved have had famous exchanges in the linguistics journals, in the popular press, and in public forums. To understand the sharp disagreements between advocates of the approaches it may be useful to have a sketch of the dramatis personae before us, even if it is undeniably an oversimplification.

We see three tendencies or foci, divided by what they take to be the subject matter, the approach they advocate for studying it, and what they count as an explanation. We characterize them roughly in Table 1.

Table 1. Three Approaches to the Study of Language

A broad and varied range of distinct research projects can be pursued within any of these approaches; one advocate may be more motivated by some parts of the overall project than others are. So the tendencies should not be taken as sharply honed, well-developed research programs or theories. Rather, they provide background biases for the development of specific research programs—biases which sometimes develop into ideological stances or polemical programs or lead to the branching off of new specialisms with separate journals. In the judgment of Phillips (2010), “Dialog between adherents of different approaches is alarmingly rare.”

The names we have given these approaches are just mnemonic tags, not descriptions. The Externalists, for example, might well have been called ‘structural descriptivists’ instead, since they tend to be especially concerned to develop models that can be used to predict the structure of natural language expressions. The Externalists have long been referred to by Essentialists as ‘empiricists’ (and sometimes Externalists apply that term to themselves), though this is misleading (see Scholz and Pullum 2006: 60–63): the ‘empiricist’ tag comes with an accusation of denying the role of learning biases in language acquisition (see Matthews 1984, Laurence and Margolis 2001), but that is no part of the Externalists’ creed (see e.g. Elman 1993, Lappin and Shieber 2007).

Emergentists are also sometimes referred to by Essentialists as ‘empiricists’, but they either use the Emergentist label for themselves (Bates et al. 1998, O’Grady 2008, MacWhinney 2005) or call themselves ‘usage-based’ linguists (Barlow and Kemmer 2002, Tomasello 2003) or ‘construction grammarians’ (Goldberg 1995, Croft 2001). Newmeyer (1991), like Tomasello, refers to the Essentialists as ‘formalists’, because of their tendency to employ abstractions, and to use tools from mathematics and logic.

Despite these terminological inconsistencies, we can look at what typical members of each approach would say about their vision of linguistic science, and what they say about the alternatives. Many of the central differences between these approaches depend on what proponents consider to be the main project of linguistic theorizing, and what they count as a satisfying explanation.

Many researchers—perhaps most—mix elements from each of the three approaches. For example, if Emergentists are to explain the syntactic structure of expressions by appeal to facts about the nature of the use of symbols in human communication, then they will presuppose a great deal of Externalist work in describing linguistic patterns, and those Externalists who work on computational parsing systems frequently use (at least as a starting point) rule systems and ‘structural’ patterns worked out by Essentialists. Certainly, there are no logical impediments for a researcher with one tendency from simultaneously pursuing another; these approaches are only general centers of emphasis.

If one assumes, with the Externalists, that the main goal of a linguistic theory is to develop accurate models of the structural properties of the speech sounds, words, phrases, and other linguistic items, then the clearly privileged information will include corpora (written and oral)—bodies of attested and recorded language use (suitably idealized). The goal is to describe how this public record exhibits certain (perhaps non-phenomenal) patterns that are projectable.

American structural linguistics of the 1920s to 1950s championed the development of techniques for using corpora as a basis for developing structural descriptions of natural languages, although such work was really not practically possible until the wide-spread availability of cheap, powerful, and fast computers. André Martinet (1960: 1) notes that one of the basic assumptions of structuralist approaches to linguistics is that “nothing may be called ‘linguistic’ that is not manifest or manifested one way or another between the mouth of the speaker and the ears of the listener”. He is, however, quick to point out that “this assumption does not entail that linguists should restrict their field of research to the audible part of the communication process—speech can only be interpreted as such, and not as so much noise, because it stands for something else that is not speech.”

American structuralists—Leonard Bloomfield in particular—were attacked, sometimes legitimately and sometimes illegitimately, by certain factions in the Essentialist tradition. For example, it was perhaps justifiable to criticize Bloomfield for adopting a nominalist ontology as popularized by the logical empiricists. But he was later attacked by Essentialists for holding anti-mentalist views about linguistics, when it is arguable that his actual view was that the science of linguistics should not commit itself to any particular psychological theory. (He had earlier been an enthusiast for the mentalist and introspectionist psychology of Wilhelm Wundt; see Bloomfield 1914.)

Externalism continues to thrive within computational linguistics, where the American structuralist vison of studying language through automatic analysis of corpora has enjoyed a recrudescence, and very large, computationally searchable corpora are being used to test hypotheses about the structure of languages (see Sampson 2001, chapter 1, for discussion).

Emergentists aim to explain the capacity for language in terms of non-linguistic human capacities: thinking, communicating, and interacting. Edward Sapir expressed a characteristic Emergentist theme when he wrote:

Language is primarily a cultural or social product and must be understood as such… It is peculiarly important that linguists, who are often accused, and accused justly, of failure to look beyond the pretty patterns of their subject matter, should become aware of what their science may mean for the interpretation of human conduct in general. (Sapir 1929: 214)

The “pretty patterns” derided here are characteristic of structuralist analyses. Sociolinguistics, which is much closer in spirit to Sapir’s project, studies the influence of social and linguistic structure on each other. One particularly influential study, Labov (1966), examines the influence of social class on language variation. Other sociolinguists examine the relation between status within a group on linguistic innovation (Eckert 1989). This interest in variation within languages is characteristic of Emergentist approaches to the study of language.

Another kind of Emergentist, like Tomasello (2003), will stress the role of theory of mind and the capacity to use symbols to change conspecifics’ mental states as uniquely human preadaptations for language acquisition, use, and invention. MacWhinney (2005) aims to explain linguistic phenomena (such as phrase structure and constraints on long distance dependencies) in terms of the way conversation facilitates accurate information-tracking and perspective-switching.

Functionalist research programs generally fall within the broad tendency to approach the study of language as an Emergentist. According to one proponent:

The functionalist view of language [is] as a system of communicative social interaction… Syntax is not radically arbitrary, in this view, but rather is relatively motivated by semantic, pragmatic, and cognitive concerns. (Van Valin 1991, quoted in Newmeyer 1991: 4; emphasis in original)

And according to Russ Tomlin, a linguist who takes a functionalist approach:

Syntax is not autonomous from semantics or pragmatics…the rejection of autonomy derives from the observation that the use of particular grammatical forms is strongly linked, even deterministically linked, to the presence of particular semantic or pragmatic functions in discourse. (Tomlin 1990, quoted by Newmeyer (1991): 4)

The idea that linguistic form is autonomous, and more specifically that syntactic form (rather than, say, phonological form) is autonomous, is a characteristic theme of the Essentialists. And the claims of Van Valin and Tomlin to the effect that syntax is not independent of semantics and pragmatics might tempt some to think that Emergentism and Essentialism are logically incompatible. But this would be a mistake, since there are a large number of nonequivalent autonomy of form theses.

Even in the context of trying to explain what the autonomy thesis is, Newmeyer (1991: 3) talks about five formulations of the thesis, each of which can be found in some Essentialists’ writings, without (apparently) realizing that they are non-equivalent. One is the relatively strong claim that the central properties of linguistic form must not be defined with essential reference to “concepts outside the system”, which suggests that no primitives in linguistics could be defined in psychological or biological terms. Another takes autonomy of form to be a normative claim: that linguistic concepts ought not to be defined or characterized in terms of non-linguistic concepts. The third and fourth versions are ontological: one denies that central linguistic concepts should be ontologically reduced to non-linguistic ones, and the other denies that they can be. And in the fifth version the autonomy of syntax is taken to deny that syntactic patterning can be explained in terms of meaning or discourse functions.

For each of these versions of autonomy, there are Essentialists who agree with it. Probably the paradigmatic Essentialist agrees with them all. But Emergentists need not disagree with them all. Paradigmatic functionalists like Tomlin, Van Valin and MacWhinney could in principle hold that the explanation of syntactic form, for example, will ultimately be in terms of discourse functions and semantics, but still accept that syntactic categories cannot be reduced to non-linguistic ones.

If Leonard Bloomfield is the intellectual ancestor of Externalism, and Sapir the father of Emergentism, then Noam Chomsky is the intellectual ancestor of Essentialism. The researcher with predominantly Essentialist inclinations aims to identify the intrinsic properties of language that make it what it is. For a huge majority of practitioners of this approach—researchers in the tradition of generative grammar associated with Chomsky—this means postulating universals of human linguistic structure, unlearned but tacitly known, that permit and assist children to acquire human languages. This generative Essentialism has a preference for finding surprising characteristics of languages that cannot be inferred from the data of usage, and are not predictable from human cognition or the requirements of communication.

Rather than being impressed with language variation, as are Emergentists and many Externalists, the generative Essentialists are extremely impressed with the idea that very young children of almost any intelligence level, and just about any social upbringing, acquire language to the same high degree of mastery. From this it is inferred that there must be unlearned features shared by all languages that somehow assist in language acquisition.

A large number of contemporary Essentialists who follow Chomsky’s teaching on this matter claim that semantics and pragmatics are not a central part of the study of language. In Chomsky’s view, “it is possible that natural language has only syntax and pragmatics” (Chomsky 1995: 26); that is, only “internalist computations and performance systems that access them”; semantic theories are merely “part of an interface level” or “a form of syntax” (Chomsky 1992: 223).

Thus, while Bloomfield understood it to be a sensible practical decision to assign semantics to some field other than linguistics because of the underdeveloped state of semantic research, Chomsky appears to think that semantics as standardly understood is not part of the essence of the language faculty at all. (In broad outline, this exclusion of semantics from linguistics comports with Sapir’s view that form is linguistic but content is cultural.)

Although Chomsky is an Essentialist in his approach to the study of language, excluding semantics as a central part of linguistic theory clearly does not follow from linguistic Essentialism (Katz 1980 provides a detailed discussion of Chomsky’s views on semantics). Today there are many Essentialists who do hold that semantics is a component of a full linguistic theory.

For example, many linguists today are interested in the syntax-semantics interface—the relationship between the surface syntactic structure of sentences and their semantic interpretation. This area of interest is generally quite alien to philosophers who are primarily concerned with semantics only, and it falls outside of Chomsky’s syntactocentric purview as well. Linguists who work in the kind of semantics initiated by Montague (1974) certainly focus on the essential features of language (most of their findings appear to be of universal import rather than limited to the semantic rules of specific languages). Useful works to consult to get a sense of the modern style of investigation of the syntax-semantics interface would include Partee (1975), Jacobson (1996), Szabolcsi (1997), Chierchia (1998), Steedman (2000).

The discussion so far has been at a rather high level of abstraction. It may be useful to contrast the three tendencies by looking at how they each would analyze a particular linguistic phenomenon. We have selected the syntax of double-object clauses like Hand the guard your pass (also called ditransitive clauses), in which the verb is immediately followed by a sequence of two noun phrases, the first typically denoting a recipient and the second something transferred. For many such clauses there is an alternative way of expressing roughly the same thing: for Hand the guard your pass there is the alternative Hand your pass to the guard , in which the verb is followed by a single object noun phrase and the recipient is expressed after that by a preposition phrase with to . We will call these recipient-PP clauses.

1.4.1 A typical Essentialist analysis

Larson (1988) offers a generative Essentialist approach to the syntax of double-object clauses. In order to provide even a rough outline of his proposals, it will be very useful to be able to use tree diagrams of syntactic structure. A tree is a mathematical object consisting of a set of points called nodes between which certain relations hold. The nodes correspond to syntactic units; left-right order on the page corresponds to temporal order of utterance between them; and upward connecting lines represent the relation ‘is an immediate subpart of’. Nodes are labeled to show categories of phrases and words, such as noun phrase (NP); preposition phrase (PP); and verb phrase (VP). When the internal structure of some subpart of a tree is basically unimportant to the topic under discussion, it is customary to mask that part with an empty triangle. Consider a simple example: an active transitive clause like (Ai) and its passive equivalent (Aii).

A tree structure for (Ai) is shown in (T1).

In analyses of the sort Larson exemplifies, the structure of an expression is given by a derivation , which consists of a sequence of successively modified trees. Larson calls the earliest ones underlying structures. The last (and least abstract) in the derivation is the surface structure, which captures properties relevant to the way the expression is written and pronounced. The underlying structures are posited in order to better identify syntactic generalizations. They are related to surface structures by a series of operations called transformations (which generative Essentialists typically regard as mentally real operations of the human language faculty).

One of the fundamental operations that a transformation can effect is movement , which involves shifting a part of the syntactic structure of a tree to another location within it. For example, it is often claimed that passive clauses have very much the same kinds of underlying structures as the synonymous active clauses, and thus a passive clause like (Aii) would have an underlying structure much like (T1). A movement transformation would shift the guard toward the end of the clause (and add by ), and another would shift my pass into the position before the verb. In other words, passive clauses look much more like their active counterparts in underlying structure.

In a similar way, Larson proposes that a double-object clause like (B.ii) has the same underlying structure as (B.i).

Moreover, he proposes that the transformational operation of deriving the surface structure of (B.ii) from the underlying structure of (B.i) is essentially the same as the one that derives the surface structure of (A.ii) from the underlying structure of (A.i).

Larson adopts many assumptions from Chomsky (1981) and subsequent work. One is that all NPs have to be assigned Case in the course of a derivation. (Case is an abstract syntactic property, only indirectly related to the morphological case forms displayed by nominative, accusative, and genitive pronouns. Objective Case is assumed to be assigned to any NP in direct object position, e.g., my pass in (T1), and Nominative Case is assigned to an NP in the subject position of a tensed clause, e.g., the guard in (T1).)

He also makes two specific assumptions about the derivation of passive clauses. First, Case assignment to the position immediately after the verb is “suppressed”, which entails that the NP there will not get Case unless it moves to some other position. (The subject position is the obvious one, because there it will receive Nominative Case.) Second, there is an unusual assignment of semantic role to NPs: instead of the subject NP being identified as the agent of the action the clause describes, that role is assigned to an adjunct at the end of the VP (the by -phrase in (A.ii); an adjunct is a constituent with an optional modifying role in its clause rather than a grammatically obligatory one like subject or object).

Larson proposes that both of these points about passive clauses have analogs in the structure of double-object VPs. First, Case assignment to the position immediately after the verb is suppressed; and since Larson takes the preposition to to be the marker of Case, this means in effect that to disappears. This entails that the NP after to will not get Case unless it moves to some other position. Second, there is an unusual assignment of semantic role to NPs: instead of the direct object NP being identified as the entity affected by the action the clause describes, that role is assigned to an adjunct at the end of the VP.

Larson makes some innovative assumptions about VPs. First, he proposes that in the underlying structure of a double-object clause the direct object precedes the verb , the tree diagram being (T2).

This does not match the surface order of words ( showed my pass to the guard ), but it is not intended to: it is an underlying structure. A transformation will move the verb to the left of my pass to produce the surface order seen in (B.i).

Second, he assumes that there are two nodes labeled VP in a double-object clause, and two more labeled V′, though there is only one word of the verb (V) category. (Only the smaller VP and V′ are shown in the partial structure (T2).)

What is important here is that (T2) is the basis for the double-object surface structure as well. To produce that, the preposition to is erased and an additional NP position (for my pass ) is attached to the V′, thus:

The additional NP is assigned the affected-entity semantic role. The other NP ( the guard ) does not yet have Case; but Larson assumes that it moves into the NP position before the verb. The result is shown in (T4), where ‘ e ’ marks the empty string left where some words have been moved away:

Larson assumes that in this position the guard can receive Case. What remains is for the verb to move into a higher V position further to its left, to obtain the surface order:

The complete sequence of transformations is taken to give a deep theoretical explanation of many properties of (B.i) and (B.ii), including such things as what could be substituted for the two NPs, and the fact there is at least rough truth-conditional equivalence between the two clauses.

The reader with no previous experience of generative linguistics will have many questions about the foregoing sketch (e.g., whether it is really necessary to have the guard after showed in (T3), then the opposite order in (T4), and finally the same order again in (T5)). We cannot hope to answer such questions here; Larson’s paper is extremely rich in further assumptions, links to the previous literature, and additional classes of data that he aims to explain. But the foregoing should suffice to convey some of the flavor of the analysis.

The key point to note is that Essentialists seek underlying symmetries and parallels whose operation is not manifest in the data of language use. For Essentialists, there is positive explanatory virtue in hypothesizing abstract structures that are very far from being inferrable from performance; and the posited operations on those structures are justified in terms of elegance and formal parallelism with other analyses, not through observation of language use in communicative situations.

1.4.2 A typical Emergentist analysis

Many Emergentists are favorably disposed toward the kind of construction grammar expounded in Goldberg (1995). We will use her work as an exemplar of the Emergentist approach. The first thing to note is that Goldberg does not take double-object clauses like (B.ii) to be derived alternants of recipient-PP structures like (B.i), the way Larson does. So she is not looking for a regular syntactic operation that can relate their derivations; indeed, she does not posit derivations at all. She is interested in explaining correlations between syntactic, semantic, and pragmatic aspects of clauses; for example, she asks this question:

How are the semantics of independent constructions related such that the classes of verbs associated with one overlap with the classes of verbs associated with another? (Goldberg 1995: 89)

Thus she aims to explain why some verbs occur in both the double-object and recipient-PP kinds of expression and some do not.

The fundamental notion in Goldberg’s linguistic theory is that of a construction . A construction can be defined very roughly as a way of structurally composing words or phrases—a sort of template—for expressing a certain class of meanings. Like Emergentists in general, Goldberg regards linguistic theory as continuous with a certain part of general cognitive psychological theory; linguistics emerges from this more general theory, and linguistic matters are rarely fully separate from cognitive matters. So a construction for Goldberg has a mental reality: it corresponds to a generalized concept or scenario expressible in a language, annotated with a guide to the linguistic structure of the expression.

Many words will be trivial examples of constructions: a single concept paired with a way of pronouncing and some details about grammatical restrictions (category, inflectional class, etc.); but constructions can be much more abstract and internally complex. The double-object construction, which Goldberg calls the Ditransitive Construction, is a moderately abstract and complex one; she diagrams it thus (p. 50):

This expresses a set of constraints on how to use English to communicate the idea of a particular kind of scenario. The scenario involves a ternary relation CAUSE-RECEIVE holding between an agent ( agt ), a recipient ( rec ), and a patient ( pat ). PRED is a variable that is filled by the meaning of a particular verb when it is employed in this construction.

The solid vertical lines downward from agt and pat indicate that for any verb integrated into this construction it is required that its subject NP should express the agent participant, and the direct object (OBJ 2 ) should express the patient participant. The dashed vertical line downward from rec signals that the first object (OBJ) may express the recipient but it does not have to—the necessity of there being a recipient is a property of the construction itself, and not every verb demands that it be made explicit who the recipient is. But if there are two objects, the first is obligatorily associated with the recipient role: We sent the builder a carpenter can only express a claim about the sending of a carpenter over to the builder, never the sending of the builder over to where a carpenter is.

When a particular verb is used in this construction, it may have obligatory accompanying NPs denoting what Goldberg calls “profiled participants” so that the match between the participant roles ( agt , rec , pat ) is one-to-one, as with the verb hand . When this verb is used, the agent (‘hander’), recipient (‘handee’), and item transferred (‘handed’) must all be made explicit. Goldberg gives the following diagram of the “composite structure” that results when hand is used in the construction:

Because of this requirement of explicit presence, Hand him your pass is grammatical, but * Hand him is not, and neither is * Hand your pass . The verb send , on the other hand, illustrates the optional syntactic expression of the recipient role: we can say Send a text message , which is understood to involve some recipient but does not make the recipient explicit.

The R notation relates to the fact that particular verbs may express either an instance of causing someone to receive something, as with hand , or a means of causing someone to receive something, as with kick : what Joe kicked Bill the ball means is that Joe caused Bill to receive the ball by means of a kicking action.

Goldberg’s discussion covers many subtle ways in which the scenario communicated affects whether the use of a construction is grammatical and appropriate. For example, there is something odd about ? Joe kicked Bill the ball he was trying to kick to Sam : the Ditransitive Construction seems best suited to cases of volitional transfer (rather than transfer as an unexpected side effect of a blunder). However, an exception is provided by a class of cases in which the transfer is not of a physical object but is only metaphorical: That guy gives me the creeps does not imply any volitional transfer of a physical object.

Metaphorical cases are distinguished from physical transfers in other ways as well. Goldberg notes sentences like The music lent the event a festive air , where the music is subject of the verb lend despite the fact that music cannot literally lend anything to anyone.

Goldberg discusses many topics such as metaphorical extension, shading, metonymy, cutting, role merging, and also presents various general principles linking meanings and constructions. One of these principles, the No Synonymy Principle, says that no two syntactically distinct constructions can be both semantically and pragmatically synonymous. It might seem that if any two sentences are synonymous, pairs like this are:

Yet the two constructions cannot be fully synonymous, both semantically and pragmatically, if the No Synonymy Principle is correct. And to support the principle, Goldberg notes purported contrasts such as this:

There is a causation-as-transfer metaphor here, and it seems to be compatible with the double object construction but not with the recipient-PP. So (in Goldberg’s view) the two are not fully synonymous.

It is no part of our aim here to provide a full account of the content of Goldberg’s discussion of double-object clauses. But what we want to highlight is that the focus is not on finding abstract elements or operations of a purely syntactic nature that are candidates for being essential properties of language per se. The focus for Emergentists is nearly always on the ways in which meaning is conveyed, the scenarios that particular constructions are used to communicate, and the aspects of language that connect up with psychological topics like cognition, perception, and conceptualization.

1.4.3 A typical Externalist analysis

One kind of work that is representative of the Externalist tendency is nicely illustrated by Bresnan et al. (2007) and Bresnan and Ford (2010). Bresnan and her colleagues defend the use of corpora—bodies of attested written and spoken texts. One of their findings is that a number of types of expressions that linguists have often taken to be ungrammatical do in fact turn up in actual use. Essentialists and Emergentists alike have often, purely on the basis of intuition, asserted that sentences like John gave Mary a kiss are grammatical but sentences like John gave a kiss to Mary are no, as we see above with Goldberg’s (D)(ii). Bresnan and her colleagues find numerous occurrences of the latter sort on the World Wide Web, and conclude that they are not ungrammatical or even unacceptable, but merely dispreferred.

Bresnan and colleagues used a three-million-word collection of recorded and transcribed spontaneous telephone conversations known as the Switchboard corpus to study the double-object and recipient-PP constructions. They first annotated the utterances with indications of a number of factors that they thought might influence the choice between the double-object and recipient-PP constructions:

• Discourse accessibility of NPs: does a particular NP refer to something already mentioned, or to something new to the discourse?
• Relative lengths of NPs: what is the difference in number of words between the recipient NP and the transferred-item NP?
• Definiteness: are the recipient and transferred-item NPs definite like the bishop or indefinite like some members
• Animacy: do the recipient and transferred-item NPs denote animate beings or inanimate things?
• Pronominality: are the recipient and transferred-item NPs pronouns?
• Number: are the recipient and transferred-item NPs singular or plural?
• person: are the recipient and transferred-item NPs first-person or second-person pronouns, or third person?

They also coded the verb meanings by assigning them to half a dozen semantic categories:

• Abstract senses ( give it some thought );
• Transfer of possession ( give him an armband );
• Future transfer of possession ( I owe you a dollar );
• Prevention of possession ( They denied me my rights );
• Communication verb sense ( tell me your name ).

They then constructed a statistical model of the corpus: a mathematical formula expressing, for each combination of the factors listed above, the ratio of the probabilities of the double object and the recipient-PP. (To be precise, they used the natural logarithm of the ratio of p to 1 − p , where p is the probability of a double-object or recipient-PP in the corpus being of the double-object form.) They then used logistic regression to predict the probability of fit to the data.

To determine how well the model generalized to unseen data, they divided the data randomly 100 times into a training set and a testing set, fit the model parameters on each training set, and scored its predictions on the unseen testing set. The average percent of correct predictions on unseen data was 92%. All components of the model except number of the recipient NP made a statistically significant difference—almost all at the 0.001 level.

What this means is that knowing only the presence or absence of the sort of factors listed above they were reliably able to predict whether double-object or recipient-PP structures would be used in a given context, with a 92% score accuracy rate.

The implication is that the two kinds of structure are not interchangeable: they are reliably differentiated by the presence of other factors in the texts in which they occur.

They then took the model they had generated for the telephone speech data and applied it to a corpus of written material: the Wall Street Journal corpus (WSJ), a collection of 1987–9 newspaper copy, only roughly edited. The main relevant difference with written language is that the language producer has more opportunity to reflect thoughtfully on how they are going to phrase things. It was reasonable to think that a model based on speech data might not transfer well. But instead the model had 93.5% accuracy. The authors conclude is that “the model for spoken English transfers beautifully to written”. The main difference between the corpora was found to be a slightly higher probability of the recipient-PP structure in written English.

In a very thorough subsequent study, Bresnan and Ford (2010) show that the results also correlate with native speakers’ metalinguistic judgments of naturalness for sentence structures, and with lexical decision latencies (speed of deciding whether the words in a text were genuine English words or not), and with a sentence completion task (choosing the most natural of a list of possible completions of a partial sentence). The results of these experiments confirmed that their model predicted participants’ performance.

Among the things to note about this work is that it was all done on directly recorded performance data: transcripts of people speaking to each other spontaneously on the phone in the case of the Switchboard corpus, stories as written by newspaper journalists in the case of WSJ, measured responses of volunteer subjects in a laboratory in the case of the psycholinguistic experiments of Bresnan and Ford (2010). The focus is on identifying the factors in linguistic performance that permit accurate prediction of future performance, and the methods of investigation have a replicability and checkability that is familiar in the natural sciences.

However, we should make it clear that the work is not some kind of close-to-the-ground collecting and classifying of instances. The models that Bresnan and her colleagues develop are sophisticated mathematical abstractions, very far removed from the records of utterance tokens. They claim that these models “allow linguistic theory to solve more difficult problems than it has in the past, and to build convergent projects with psychology, computer science, and allied fields of cognitive science” (Bresnan et al. 2007: 69).

1.4.4 Conclusion

It is important to see that the contrast we have drawn here is not just between three pieces of work that chose to look at different aspects of the phenomena associated with double-object sentences. It is true that Larson focuses more on details of tree structure, Goldberg more on subtle differences in meaning, and Bresnan et al. on frequencies of occurrence. But that is not what we are pointing to. What we want to stress is that we are illustrating three different broad approaches to language that regard different facts as likely to be relevant, and make different assumptions about what needs to be accounted for, and what might count as an explanation.

Larson looks at contrasts between different kinds of clause with different meanings and see evidence of abstract operations affecting subtle details of tree structure, and parallelism between derivational operations formerly thought distinct.

Goldberg looks at the same facts and sees evidence not for anything to do with derivations but for the reality of specific constructions—roughly, packets of syntactic, semantic, and pragmatic information tied together by constraints.

Bresnan and her colleagues see evidence that readily observable facts about speaker behavior and frequency of word sequences correlate closely with certain lexical, syntactic, and semantic properties of words.

Nothing precludes defenders of any of the three approaches from paying attention to any of the phenomena that the other approaches attend to. There is ample opportunity for linguists to mix aspects of the three approaches in particular projects. But in broad outline there are three different tendencies exhibited here, with stereotypical views and assumptions roughly as we laid them out in Table 1.

2. The Subject Matter of Linguistic Theories

The complex and multi-faceted character of linguistic phenomena means that the discipline of linguistics has a whole complex of distinguishable subject matters associated with different research questions. Among the possible topics for investigation are these:

• the capacity of humans to acquire, use, and invent languages;
• the abstract structural patterns (phonetic, morphological, syntactic, or semantic) found in a particular language under some idealization;
• systematic structural manifestations of the use of some particular language;
• the changes in a language or among languages across time;
• the psychological functioning of individuals who have successfully acquired particular languages;
• the psychological processes underlying speech or linguistically mediated thinking in humans;
• the evolutionary origin of (i), and/or (ii).

There is no reason for all of the discipline of linguistics to converge on a single subject matter, or to think that the entire field of linguistics cannot have a diverse range of subject matters. To give a few examples:

• The influential Swiss linguist Ferdinand de Saussure (1916) distinguished between langue , a socially shared set of abstract conventions (compare with (ii)) and parole , the particular choices made by a speaker deploying a language (compare (iii)).
• The anthropological linguist Edward Sapir (1921, 1929) thought that human beings have a seemingly species-universal capacity to acquire and use languages (compare (i)), but his own interest was limited to the systematic structural features of particular languages (compare (ii)) and the psychological reality of linguistic units such as the phoneme (an aspect of (vi)), and the psychological effects of language and thought (an aspect of (v)).
• Bloomfield (1933) showed a strong interest in historical linguistic change (compare (iv)), distinguishing that sharply (much as Saussure did) from synchronic description of language structure ((ii) again) and language use (compare (iii)), arguing that the study of (iv) presupposed (vi).
• Bloomfield famously eschewed all dualistic mentalistic approaches to the study of language, but since he rejected them on materialist ontological grounds, his rejection of mentalism was not clearly a rejection of (vi) or (vii): his attempt to cast linguistics in terms of stimulus-response psychology indicates that he was sympathetic to the Weissian psychology of his time and accepted that linguistics might have psychological subject matter.
• Zellig Harris, on the other hand, showed little interest in the psychology of language, concentrating on mathematical techniques for tackling (ii).

Most saliently of all, Harris’s student Chomsky reacted strongly against indifference toward the mind, and insisted that the principal subject matter of linguistics was, and had to be, a narrow psychological version of (i), and an individual, non-social, and internalized conception of (ii).

In the course of advancing his view, Chomsky introduced a number of novel pairs of terms into the linguistics literature: competence vs. performance (Chomsky 1965); ‘I-language’ vs. ‘E-language’ (Chomsky 1986); the faculty of language in the narrow sense vs. the and faculty of language in the broad sense (the ‘FLN’ and ‘FLB’ of Hauser et al. 2002). Because Chomsky’s terminological innovations have been adopted so widely in linguistics, the focus of sections 2.1–2.3 will be to examine the use of these expressions as they were introduced into the linguistics literature and consider their relation to (i)–(vii).

Essentialists invariably distinguish between what Chomsky (1965) called competence and performance . Competence is what knowing a language confers: a tacit grasp of the structural properties of all the sentences of a language. Performance involves actual real-time use, and may diverge radically from the underlying competence, for at least two reasons: (a) an attempt to produce an utterance may be perturbed by non-linguistic factors like being distracted or interrupted, changing plans or losing attention, being drunk or having a brain injury; or (b) certain capacity limits of the mechanisms of perception or production may be overstepped.

Emergentists tend to feel that the competence/performance distinction sidelines language use too much. Bybee and McClelland put it this way:

One common view is that language has an essential and unique inner structure that conforms to a universal ideal, and what people say is a potentially imperfect reflection of this inner essence, muddied by performance factors. According to an opposing view…language use has a major impact on language structure. The experience that users have with language shapes cognitive representations, which are built up through the application of general principles of human cognition to linguistic input. The structure that appears to underlie language use reflects the operation of these principles as they shape how individual speakers and hearers represent form and meaning and adapt these forms and meanings as they speak. (Bybee and McClelland 2005: 382)

And Externalists are often concerned to describe and explain not only language structure, but also the workings of processing mechanisms and the etiology of performance errors.

However, every linguist accepts that some idealization away from the speech phenomena is necessary. Emergentists and Externalists are almost always happy to idealize away from sporadic speech errors. What they are not so keen to do is to idealize away from limitations on linguistic processing and the short-term memory on which it relies. Acceptance of a thoroughgoing competence/performance distinction thus tends to be a hallmark of Essentialist approaches, which take the nature of language to be entirely independent of other human cognitive processes (though of course capable of connecting to them).

The Essentialists’ practice of idealizing away from even psycholinguistically relevant factors like limits on memory and processing plays a significant role in various important debates within linguistics. Perhaps the most salient and famous is the issue of whether English is a finite-state language.

The claim that English is not accepted by any finite-state automaton can only be supported by showing that every grammar for English has center- embedding to an unbounded depth (see Levelt 2008: 20–23 for an exposition and proof of the relevant theorem, originally from Chomsky 1959). But even depth-3 center-embedding of clauses (a clause interrupting a clause that itself interrupts a clause) is in practice extraordinarily hard to process. Hardly anyone can readily understand even semantically plausible sentences like Vehicles that engineers who car companies trust build crash every day . And such sentences virtually never occur, even in writing. Karlsson (2007) undertakes an extensive examination of available textual material, and concludes that depth-3 center-embeddings are vanishingly rare, and no genuine depth-4 center-embedding has ever occurred at all in naturally composed text. He proposes that there is no reason to regard center-embedding as grammatical beyond depth 3 (and for spoken language, depth 2). Karlsson is proposing a grammar that stays close to what performance data can confirm; the standard Essentialist view is that we should project massively from what is observed, and say that depth- n center-embedding is fully grammatical for all n .

Chomsky (1986) introduced into the linguistics literature two technical notions of a language: ‘E-Language’ and ‘I-Language’. He deprecates the former as either undeserving of study or as a fictional entity, and promotes the latter as the only scientifically respectable object of study for a serious linguistics.

2.2.1 ‘E-language’

Chomsky’s notion ‘E-language’ is supposed to suggest by its initial ‘E’ both ‘extensional’ (concerned with which sentences happen to satisfy a definition of a language rather than with what the definition says) and ‘external’ (external to the mind, that is, non-mental). The dismissal of E-language as an object of study is aimed at critics of Essentialism—many but not all of those critics falling within our categories of Externalists and Emergentists.

Extensional . First, there is an attempt to impugn the extensional notion of a language that is found in two radically different strands of Externalist work. Some Externalist investigations are grounded in the details of attested utterances (as collected in corpora), external to human minds. Others, with mathematical or computational interests, sometimes idealize languages as extensionally definable objects (typically infinite sets of strings) with a certain structure, independently of whatever device might be employed to characterize them. A set of strings of words either is or is not regular (finite-state), either is or is not recursive (decidable), etc., independently of forms of grammar statement. Chomsky (1986) basically dismissed both corpus-based work and mathematical linguistics simply on the grounds that they employ an extensional conception of language that is, a conception that removes the object of study from having an essential connection with the mental.

External . Second, a distinct meaning based on ‘external’ was folded into the neologism ‘E-language’ to suggest criticism of any view that conceives of a natural language as a public, intersubjectively accessible system used by a community of people (often millions of them spread across different countries). Here, the objection is that languages as thus conceived have no clear criteria of individuation in terms of necessary and sufficient conditions. On this conception, the subject matter of interest is a historico-geographical entity that changes as it is transmitted over generations, or over mountain ranges. Famously, for example, there is a gradual valley-to-valley change in the language spoken between southeastern France and northwestern Italy such that each valley’s speakers can understand the next. But the far northwesterners clearly speak French and the far southeasterners clearly speak Italian. It is the politically defined geographical border, not the intrinsic properties of the dialects, that would encourage viewing this continuum as two different languages.

Perhaps the most famous quotation by any linguist is standardly attributed to Max Weinreich (1945): ‘A shprakh iz a dialekt mit an armey un flot’ (‘A language is a dialect with an army and navy’; he actually credits the remark to an unnamed student). The implication is that E-languages are defined in terms of non-linguistic, non-essential properties. Essentialists object that a scientific linguistics cannot tolerate individuating French and Italian in a way that is subject to historical contingencies of wars and treaties (after all, the borders could have coincided with a different hill or valley had some battle had a different outcome).

Considerations of intelligibility fare no better. Mutual intelligibility between languages is not a transitive relation, and sometimes the intelligibility relation is not even symmetric (smaller, more isolated, or less prestigious groups often understand the dialects of larger, more central, or higher-prestige groups when the converse does not hold). So these sociological facts cannot individuate languages either.

Chomsky therefore concludes that languages cannot be defined or individuated extensionally or mind-externally, and hence the only scientifically interesting conception of a ‘language’ is the ‘I-language’ view (see for example Chomsky 1986: 25; 1992; 1995 and elsewhere). Chomsky says of E-languages that “all scientific approaches have simply abandoned these elements of what is called ‘language’ in common usage” (Chomsky 1988, 37); and “we can define E-language in one way or another or not at all, since the concept appears to play no role in the theory of language” (Chomsky 1986: 26; in saying that it appears to play no role in the theory of language, here he means that it plays no role in the theory he favours).

This conclusion may be bewildering to non-linguists as well as non-Essentialists. It is at odds with what a broad range of philosophers have tacitly assumed or explicitly claimed about language or languages: ‘[A language] is a practice in which people engage…it is constituted by rules which it is part of social custom to follow’ (Dummett 1986: 473–473); ‘Language is a set of rules existing at the level of common knowledge’ and these rules are ‘norms which govern intentional social behavior’ (Itkonen 1978: 122), and so on. Generally speaking, those philosophers influenced by Wittgenstein also take the view that a language is a social-historical entity. But the opposite view has become a part of the conceptual underpinning of linguistics for many Essentialists.

Failing to have precise individuation conditions is surely not a sufficient reason to deny that an entity can be studied scientifically. ‘Language’ as a count noun in the extensional and socio-historical sense is vague, but this need not be any greater obstacle to theorizing about them than is the vagueness of other terms for historical entities without clear individuation conditions, like ‘species’ and ‘individual organism’ in biology.

At least some Emergentist linguists, and perhaps some Externalists, would be content to say that languages are collections of social conventions, publicly shared, and some philosophers would agree (see Millikan 2003, for example, and Chomsky 2003 for a reply). Lewis (1969) explicitly defends the view that language can be understood in terms of public communications, functioning to solve coordination problems within a group (although he acknowledges that the coordination could be between different temporal stages of one individual, so language use by an isolated person is also intelligible; see the appendix “Lewis’s Theory of Languages as Conventions” in the entry on idiolects , for further discussion of Lewis). What Chomsky calls E-languages, then, would be perfectly amenable to linguistic or philosophical study. Santana (2016) makes a similar argument in terms of scientific idealization. He argues that since all sciences idealize their targets, Chomsky needs to do more to show why idealizations concerning E-languages are illicit (see also Stainton 2014).

2.2.2 ‘I-language’

Chomsky (1986) introduced the neologism ‘I-language’ in part to disambiguate the word ‘grammar’. In earlier generative Essentialist literature, ‘grammar’ was (deliberately) ambiguous between (i) the linguist’s generative theory and (ii) what a speaker knows when they know a language. ‘I-language’ can be regarded as a replacement for Bever’s term ‘psychogrammar’ (see also George 1989): it denotes a mental or psychological entity (not a grammarian’s description of a language as externally manifested).

I-language is first discussed under the sub-heading of ‘internalized language’ to denote linguistic knowledge. Later discussion in Chomsky 1986 and 1995 makes it clear that the ‘I’ of ‘I-language’ is supposed to suggest at least three English words: ‘individual’, ‘internal’, and ‘intensional’. And Chomsky emphasizes that the neologism also implies a kind of realism about speakers’ knowledge of language.

Individual . A language is claimed to be strictly a property of individual human beings—not groups. The contrast is between the idiolect of a single individual, and a dialect or language of a geographical, social, historical, or political group. I-languages are properties of the minds of individuals who know them.

Internal . As generative Essentialists see it, your I-language is a state of your mind/brain. Meaning is internal—indeed, on Chomsky’s conception, an I-language

is a strictly internalist, individualist approach to language, analogous in this respect to studies of the visual system. If the cognitive system of Jones’s language faculty is in state L, we will say that Jones has the I-language L. (Chomsky 1995: 13)

And he clarifies the sense in which an I-language is internal by appealing to an analogy with the way the study of vision is internal:

The same considerations apply to the study of visual perception along lines pioneered by David Marr, which has been much discussed in this connection. This work is mostly concerned with operations carried out by the retina; loosely put, the mapping of retinal images to the visual cortex. Marr’s famous three levels of analysis—computational, algorithmic, and implementation—have to do with ways of construing such mappings. Again, the theory applies to a brain in a vat exactly as it does to a person seeing an object in motion. (Chomsky 1995: 52)

Thus, while the speaker’s I-language may be involved in performing operations over representations of distal stimuli—representations of other speaker’s utterances—I-languages can and should be studied in isolation from their external environments.

Although Chomsky sometimes refers to this narrow individuation of I-languages as ‘individual’, he clearly claims that I-languages are individuated in isolation from both speech communities and other aspects of the broadly conceived natural environment:

Suppose Jones is a member of some ordinary community, and J is indistinguishable from him except that his total experience derives from some virtual reality design; or let J be Jones’s Twin in a Twin-Earth scenario. They have had indistinguishable experiences and will behave the same way (in so far as behavior is predictable at all); they have the same internal states. Suppose that J replaces Jones in the community, unknown to anyone except the observing scientist. Unaware of any change, everyone will act as before, treating J as Jones; J too will continue as before. The scientist seeking the best theory of all of this will construct a narrow individualist account of Jones, J, and others in the community. The account omits nothing… (Chomsky 1995: 53–54)

This passage can also be seen as suggesting a radically intensionalist conception of language.

Intensional . The way in which I-languages are ‘intensional’ for Chomsky needs a little explication. The concept of intension is familiar in logic and semantics, where ‘intensional’ contrasts with ‘extensional’. The extension of a predicate like blue is simply the set of all blue objects; the intension is the function that picks out in a given world the blue objects contained therein. In a similar way, the extension of a set can be distinguished from an intensional description of the set in terms of a function: the set of integer squares is {1, 4, 9, 16, 25, 36, …}, and the intension could be given in terms of the one-place function f such that f ( n ) = n × n . One difference between the two accounts of squaring is that the intensional one could be applied to a different domain (any domain on which the ‘×’ operation is defined: on the rationals rather than the integers, for example, the extension of the identically defined function is a different and larger set containing infinitely many fractions).

In an analogous way, a language can be identified with the set of all and only its expressions (regardless of what sort of object an expression is: a word sequence, a tree structure, a complete derivation, or whatever), which is the extensional view; but it can also be identified intensionally by means of a recipe or formal specification of some kind—what linguists call a grammar. Ludlow (2011) considers the first I (individual) to be the weakest link and thus the most expendable. He argues in its stead for a concept of a “Ψ-language” which allows for the possibility of the I-language relating to external objects either constitutively or otherwise.

In natural language semantics, an intensional context is one where substitution of co-extensional terms fails to preserve truth value ( Scott is Scott is true, and Scott is the author of Waverley is true, but the truth of George knows that Scott is Scott doesn’t guarantee the truth of George knows that Scott is the author of Waverly , so knows that establishes an intensional context).

Chomsky claims that the truth of an I-language attribution is not preserved by substituting terms that have the same extension. That is, even when two human beings do not differ at all on what expressions are grammatical, it may be false to say that they have the same I-language. Where H is a human being and L is a language (in the informal sense) and R is the relation of knowing (or having, or using) that holds between a human being and a language, Chomsky holds, in effect, that R establishes an intensional context in statements of the theory:

[F]or H to know L is for H to have a certain I-language. The statements of the grammar are statements of the theory of mind about the I-language, hence structures of the brain formulated at a certain level of abstraction from mechanisms. These structures are specific things in the world, with their properties… The I-language L may be the one used by a speaker but not the I-language L′ even if the two generate the same class of expressions (or other formal objects) … L′ may not even be a possible human I-language, one attainable by the language faculty. (Chomsky 1986: 23)

The idea is that two individuals can know (or have, or use) different I-languages that generate exactly the same strings of words, and even give them exactly the same structures. This situation forms the basis of Quine’s (1972) infamous critique of the psychological reality of generative grammars (see Johnson 2015 for a solution in terms of invariance of ‘behaviorally equivalent grammar formalisms, to use Quine’s terminology, see also Nefdt 2021 for a similar resolution in terms of structural realism in the philosophy of science).

The generative Essentialist conception of an I-language is antithetical to Emergentist research programs. If the fundamental explanandum of scientific linguistics is how actual linguistic communication takes place, one must start by looking at both internal (psychological) and external (public) practices and conventions in virtue of which it occurs, and consider the effect of historical and geographic contingencies on the relevant underlying processes. That would not rule out ‘I-language’ as part of the explanans; but some Emergentists seem to be fictionalists about I-languages, in an analogous sense to the way that Chomsky is a fictionalist about E-languages. Emergentists do not see a child as learning a generative grammar, but as learning how to use a symbolic system for propositional communication. On this view grammars are mere artifacts that are developed by linguists to codify aspects of the relevant systems, and positing an I-language amounts to projecting the linguist’s codification illegitimately onto human minds (see, for example, Tomasello 2003).

The I-language concept brushes aside certain phenomena of interest to the Externalists, who hold that the forms of actually attested expressions (sentences, phrases, syllables, and systems of such units) are of interest for linguistics. For example, computational linguistics (work on speech recognition, machine translation, and natural language interfaces to databases) must rely on a conception of language as public and extensional; so must any work on the utterances of young children, or the effects of word frequency on vowel reduction, or misunderstandings caused by road sign wordings. At the very least, it might be said on behalf of this strain of Externalism (along the lines of Soames 1984) that linguistics will need careful work on languages as intersubjectively accessible systems before hypotheses about the I-language that purportedly produces them can be investigated.

It is a highly biased claim that the E-language concept “appears to play no role in the theory of language” (Chomsky 1986: 26). Indeed, the terminological contrast seems to have been invented not to clarify a distinction between concepts but to nudge linguistic research in a particular direction.

In Hauser et al. (2002) (henceforth HCF) a further pair of contrasting terms is introduced. They draw a distinction quite separate from the competence/performance and ‘I-language’/‘E-language’ distinctions: the “language faculty in the narrow sense” (FLN) is distinguished from the “language faculty in the broad sense” (FLB). According to HCF, FLB “excludes other organism-internal systems that are necessary but not sufficient for language (e.g., memory, respiration, digestion, circulation, etc.)” but includes whatever is involved in language, and FLN is some limited part of FLB (p. 1571) This is all fairly vague, but it is clear that FLN and FLB are both internal rather than external, and individual rather than social.

The FLN/FLB distinction apparently aims to address the uniqueness of one component of the human capacity for language rather than (say) the content of human grammars. HCF say (p. 1573) that “Only FLN is uniquely human”; they “hypothesize that most, if not all, of FLB is based on mechanisms shared with nonhuman animals”; and they say:

[T]he computations underlying FLN may be quite limited. In fact, we propose in this hypothesis that FLN comprises only the core computational mechanisms of recursion as they appear in narrow syntax and the mappings to the interfaces. (ibid.)

The components of FLB that HCF hypothesize are not part of FLN are the “sensory-motor” and “conceptual-intentional” systems. The study of the conceptual-intentional system includes investigations of things like the theory of mind; referential vocal signals; whether imitation is goal directed; and the field of pragmatics. The study of the sensory motor system, by contrast, includes “vocal tract length and formant dispersion in birds and primates”; learning of songs by songbirds; analyses of vocal dialects in whales and spontaneous imitation of artificially created sounds in dolphins; “primate vocal production, including the role of mandibular oscillations”; and “[c]ross-modal perception and sign language in humans versus unimodal communication in animals”.

It is presented as an empirical hypothesis that a core property of the FLN is “recursion”:

All approaches agree that a core property of FLN is recursion, attributed to narrow syntax…FLN takes a finite set of elements and yields a potentially infinite array of discrete expressions. This capacity of FLN yields discrete infinity (a property that also characterizes the natural numbers). (HCF, p. 1571)

HCF leave open exactly what the FLN includes in addition to recursion. It is not ruled out that the FLN incorporates substantive universals as well as the formal property of “recursion”. But whatever “recursion” is in this context, it is apparently not domain-specific in the sense of earlier discussions by generative Essentialists, because it is not unique to human natural language or defined over specifically linguistic inputs and outputs: it is the basis for humans’ grasp of the formal and arguably non-natural language of arithmetic (counting, and the successor function), and perhaps also navigation and social relations. It might be more appropriate to say that HCF identify recursion as a cognitive universal, not a linguistic one. And in that case it is difficult to see how the so-called ‘language faculty’ deserves that name: it is more like a faculty for cognition and communication.

This abandonment of linguistic domain-specificity contrasts very sharply with the picture that was such a prominent characteristic of the earlier work on linguistic nativism, popularized in different ways by Fodor (1983), Barkow et al. (1992), and Pinker (1994). And yet the HCF discussion of FLN seems to incline to the view that human language capacities have a unique human (though not uniquely linguistic) essence.

The FLN/FLB distinction provides earlier generative Essentialism with an answer (at least in part) to the question of what the singularity of the human language faculty consists in, and it does so in a way that subsumes many of the empirical discoveries of paleoanthropology, primatology, and ethnography that have been part of highly influential in Emergentist approaches as well as neo-Darwinian Essentialist approaches. A neo-Darwinian Essentialist like Pinker will accept that the language faculty involves recursion, but also will also hold (with Emergentists) that human language capacities originated, via natural selection, for the purpose of linguistic communication.

Thus, over the years, those Essentialists who follow Chomsky closely have changed the term they use for their core subject matter from ‘linguistic competence’ to ‘I-language’ to ‘FLN’, and the concepts expressed by these terms are all slightly different. In particular, what they are counterposed to differs in each case.

The challenge for the generative Essentialist adopting the FLN/FLB distinction as characterized by HCF is to identify empirical data that can support the hypothesis that the FLN “yields discrete infinity”. That will mean answering the question: discrete infinity of what? HCF write that FLN “takes a finite set of elements and yields a potentially infinite array of discrete expressions” (p. 1571), which makes it clear that there must be a recursive procedure in the mathematical sense, perhaps putting atomic elements such as words together to make internally complex elements like sentences (“array” should probably be understood as a misnomer for ‘set’). But then they say, somewhat mystifyingly:

Each of these discrete expressions is then passed to the sensory-motor and conceptual-intentional systems, which process and elaborate this information in the use of language. Each expression is, in this sense, a pairing of sound and meaning. (HCF, p. 1571)

But the sensory-motor and conceptual-intentional systems are concrete parts of the organism: muscles and nerves and articulatory organs and perceptual channels and neuronal activity. How can each one of a “potentially infinite array” be “passed to” such concrete systems without it taking a potentially infinite amount of time? HCF may mean that for any one of the expressions that FLN defines as well-formed (by generating it) there is a possibility of its being used as the basis for a pairing of sound and meaning. This would be closer to the classical generative Essentialist view that the grammar generates an infinite set of structural descriptions; but it is not what HCF say.

At root, HCF is a polemical work intended to identify the view it promotes as valuable and all other approaches to linguistics as otiose.

In the varieties of modern linguistics that concern us here, the term “language” is used quite differently to refer to an internal component of the mind/brain (sometimes called internal language or I-language).… However, this biologically and individually grounded usage still leaves much open to interpretation (and misunderstanding). For example, a neuroscientist might ask: What components of the human nervous system are recruited in the use of language in its broadest sense? Because any aspect of cognition appears to be, at least in principle, accessible to language, the broadest answer to this question is, probably, “most of it.” Even aspects of emotion or cognition not readily verbalized may be influenced by linguistically based thought processes. Thus, this conception is too broad to be of much use. (HCF, p. 1570)

It is hard to see this as anything other than a claim that approaches to linguistics focusing on anything that could fall under the label ‘E-language’ are to be dismissed as useless.

Some Externalists and Emergentists actually reject the idea that the human capacity for language yields “a potentially infinite array of expressions”. It is often pointed out by empirically inclined computational linguists that in practice there will only ever be a finite number of sentences to be dealt with (though the people saying this may underestimate the sheer vastness of the finite set involved). And naturally, for those who do not believe there are generative grammars in speakers’ heads at all, it holds a fortiori that speakers do not have grammars in their heads generating infinite languages (see Nefdt 2019c for a scientific modeling perspective on the infinity postulate). Externalists and Emergentists tend to hold that the “discrete infinity” that HCF posits is more plausibly a property of the generative Essentialists’ model of linguistic competence, I-language, or FLN, than a part of the human mind/brain. This does not mean that non-Essentialists deny that actual language use is creative, or (of course) that they think there is a longest sentence of English. But they may reject the link between linguistic productivity or creativity and the mathematical notion of recursion (see Pullum and Scholz 2010).

HCF’s remarks about how FLN “yields” or “generates” a specific “array” assume that languages are clearly and sharply individuated by their generators. They appear to be committed to the view that there is a fact of the matter about exactly which generator is in a given speaker’s head. Emergentists tend not to individuate languages in this way, and may reject generative grammars entirely as inappropriately or unacceptably ‘formalist’. They are content with the notion that the common-sense concept of a language is vague, and it is not the job of linguistic theory to explain what a language is, any more than it is the job of physicists to explain what material is, or of biologists to explain what life is. Emergentists, in particular, are interested not so much in identifying generators, or individuating languages, but in exploring the component capacities that facilitate linguistic communication, and finding out how they interact.

Similarly, Externalists are interested in the linguistic structure of expressions, but have little use for the idea of a discrete infinity of them, a view that is not, and cannot be empirically supported, unless one thinks of simplicity and elegance of theory as empirical matters. They focus on the outward manifestations of language, not on a set of expressions regarded as a whole language—at least not in any way that would give a language a definite cardinality. Zellig Harris, an archetypal Externalist, is explicit that the reason for not regarding the set of utterances as finite concerns the elegance of the resulting grammar: “If we were to insist on a finite language, we would have to include in our grammar several highly arbitrary and numerical conditions” (Harris 1957: 208). Infinitude, on his view is an unimportant side consequence of setting up a sentence-generating grammar in an uncluttered and maximally elegant way, not a discovered property of languages (see Pullum and Scholz 2010 for further discussion).

Not all Essentialists agree that linguistics studies aspects of what is in the mind or aspects of what is human. There are some who do not see language as either mental or human, and certainly do not regard linguists as working on a problem within cognitive psychology or neurophysiology. The debate on the ontology of language has seen three major options emerging in the literature. Besides the mentalism of Chomskyan linguistics, Katz (1981), Katz and Postal (1991) and Postal (2003) proffered a platonistic alternative and finally nominalism was proposed by Devitt (2006).

However, the Katzian trichotomy is no longer a useful characterisation of the state-of-the-art in linguistic ontology. For one thing, Katzian-style linguistic Platonism has very few if any extant adherents. One reason for this situation is that linguistic platonists attempt to restage the debate on the foundations and metaphysics of natural language within the philosophy of mathematics (see Katz 1996). But even if this move was legitimate, it would only have opened up a range of possibilities including nominalism (Field 1980; Azzouni 2004), structuralism (Hellman 1989; Shapiro 2007; Nefdt 2016), and forms of mentalism in the guise of intuitionism. For instance, while Richard Montague is often attributed with the view that linguistics can be viewed as a branch of mathematics, it is unclear whether or not he endorsed a platonistic ontology. Devitt (2006: 26) describes the possibility of a ‘methodological platonism’ in the following manner:

It is often convenient to talk of objects posited by these theories as if they were types not tokens, as if they were Platonic objects, but this need be nothing more than a manner of speaking: when the chips are down the objects are part of the spatiotemporal physical world.

Devitt’s nominalism or ‘linguistic conception’ was not around at the time of the original Katzian tripartite analysis. He argues that linguistics is an empirical science which studies languages as they are spoken by linguistic communities and viewing sentences as ‘idealised tokens’. Devitt’s ‘linguistic view’ (as opposed to the ’psychological view’ or Chomskyan mentalism) claims that grammars map onto behavioural output of language production, of which speakers are generally ignorant.

Katz took nominalism to have been refuted by Chomsky in his critiques of American structuralists in the 1960s. But, in Katz’s opinion, Chomsky had failed to notice that conceptualism was infected with many of the same faults as nominalism, because it too localized language spatiotemporally (in contingently existing, finite, human brains). Since contemporary Minimalist theories share in the earlier ontological commitment, Katz’ argument would presumably extent to them. Through an argument by elimination, Katz concluded that only platonism remained, and must be the correct view to adopt. But this is a false trichotomy and besides predating Devitt’s more philosophically grounded nominalism, it also fails to take linguistic pluralism into account.

Recent adherents of pluralism are Stainton (2014) and Santana (2016). Santana (2016) argues in favour of a pluralistic ontology for natural language based on all of the major foundational approaches, including sociolinguistic ontology. His approach is thoroughly naturalistic in asking the ontological question through the lens of “what sort of roles the concept of language plays in linguistic theory and practice” (Santana, 2016: 501).

The first thing Santana does is to separate the discussion into two related questions, one scientific and the other metascientific or ‘descriptive’ and ‘normative’ in his terms. He claims that “[l]anguage, the scientific concept, is thus descriptively whatever it is that linguists take as their primary object of study, and normatively whatever it is they should be studying” (Santana, 2016: 501). Eventually he advocates a union of various ontologies based on the ineliminable status of each perspective (in that way the oppose of Katz’ eliminative strategy).

Stainton (2014) similarly proposes a pluralistic ontology but with a more intersectional approach. His additional argument relates to how all of the views are indeed compatible. This argument is a response to an immediate objection along the lines of Postal (2003, 2009) as to the incompatibility of the various ontologies associated with mentalism, Platonism, physicalism and public language views. Stainton begins the pluralist apology in this way.

There is an obvious rebuttal on behalf of pluralism, namely that “the linguistic” is a complex phenomenon with parts that belong to distinct ontological categories. This shouldn’t surprise, since even “the mathematical” is like this: Two wholly physical dogs plus two other wholly physical dogs yields four dogs; there certainly is the mental operation of multiplying 26 by 84, the mental state of thinking about the square root of 7, and so on. (2014: 5)

His main argument against incompatibility, and in favour of intersection, is that the former rests on an equivocation of the terms ‘mental’, ‘abstract’ and even ‘physical’. Once the equivocation is cleared up, it is argued, hybrid ontological objects are licensed. The argument goes that appreciating the nuanced physical and mental and what he calls ‘abstractish’ nature of natural language will dissolve worries about ontological inconsistency and open the door for intersection. Consider some other members of this category of objects.

Indeed, our world is replete with such hybrid objects: psychocultural kinds (e.g. dining room tables, footwear, bonfires, people, sport fishing [...]; intellectual artifacts (college diplomas, drivers’ licenses, the Canadian dollar [...]; and institutions (MIT’s Department of Linguistics and Philosophy, Disneyworld [...] (Stainton, 2014: 6).

Despite the decline in interest in the ontology of language itself, philosophers have recently embraced a subset of this debate in the philosophy of linguistic objects with a special focus on words. There is a recent debate in philosophy on the philosophy of what Rey (2006, 2020) calls ‘Standard Linguistic Entities’ (SLEs) or tokens of word, sentence, morpheme, and phonemes types. Rey then defines a position called ’physical tokenism’ or PT as the assumption that SLEs can be identified with physical (acoustic) spatio-temporal phenomena. He doesn’t think that SLEs share the same kind of existence as his trusty Honda. In fact he thinks that they are ‘intentional inexistents’ (borrowed from Brentano, see the SEP entry on ‘Brentano’s Theory of Judgement, see also the section entitled ‘Intentional Inexistence’ in the entry on Intentionality ) or purely intentional uses of the term ‘represents’ which denote fictions of a particular sort. Linguistic theory according to him is only committed to the intentional contents of things like nouns, verbs, verb phrases etc. where “an (intentional) content is whatever we understand x to be when we use the idiom ‘represent(ation of) x’ but there is no real x” (2006: 242).

There has been some theoretical work on the nature of entities like phrases and words in linguistics. For example, Ross (2010) argues that the concept of parts of speech is fuzzy. Similarly, Szabó (2015) rejects the idea that parts of speech should be identified by distributional analysis as is common in syntax. Instead he offers a semantic approach based on predicate logic where the aim is to model the major lexical categories directly in terms of open class constants. This, he claims, results in a reduction of the gap between grammar and logic. So, for instance, nouns become not types corresponding to distributionally defined syntactic objects but rather open lexical constants used for reference such that the semantic clause only needs to involve a universal quantifier and a variable specified in terms of reference. Verbs, on the other hand, are constants which purport to predicate (for more details, see Szabó 2015 and Nefdt 2020). For Haspelmath (2011) a central problem is the concept of wordhood. He identifies ten morphosyntactic criteria for words as the best possible candidates over seemingly inferior semantic or phonological options. He shows all of them to be wanting, with the result among other things being that “the notion of lexical integrity is not well supported and should not be appealed to in explaining grammatical phenomena” (Haspelmath, 2011: 33). The very notion of wordhood, although intuitive and central, is unclear upon further scrutiny. Yet, in linguistics there is continual hope for a resolution, that there is something more than essential inexistence at stake. Haspelmath thinks this is a vain hope, and attributes it to the influence of orthography on the thought of linguist researchers.

Philosophers have been traditionally interested in the metaphysics of SLEs with a special focus on the ontological status of words. Interestingly, this literature showcases variations on the foundational debates on the ontology of language. As Miller (2020) notes:

Words play various roles in our lives. Some insult, some inspire, and words are central to communication. The aim of an ontology of words is to determine what entities, if any, can play those roles and possess (or instantiate) these properties. (2)

However the positions advocated are somewhat more nuanced than the original Katzian trichotomy suggests. They usually start with the problem of word individuation expressed in the following manner:

Think of the following line: A rose is a rose is a rose. How many words are there in this line? If we were to count words themselves, not their instances, the answer is three: rose, is, and a. If we were to count the concrete instances we see on a piece of paper, the answer is eight. The line, however, can be taken as an abstract type; a sequence of shapes. (Irmak, 2019: 1140)

Further complications are introduced by reference to words like “color” and “colour”. Here the idea is that the phonological profile of a word is a guide to its identity. But this fails in other cases.

Now take the name MOHAMMED. Since Arabic does not notate vowels, the name has been transcribed in a wide variety of ways in English, and some of such transcriptions present important discrepancies: For example, “Mohammad” and “Mehmood.” Even if we know that they originated from the same source, the difference between the two forms is considerable, and intuitions about their being variants of the same name are less clear. What is the point up to which differences in spelling are consistent with word identity? (Gasparri, 2021: 594)

Word individuation goes beyond this initial characterisation and it is not always clear how the many accounts deal with the more complex questions directly in their metaphysical pursuits. For instance, issues not usually mentioned in the literature, but which seem equally important are related to whether pitch in ‘They poured pitch all over the parking lot’ and ‘The players swarmed the pitch after they won the game’ are different words. What about words within different syntactic categories, such as ‘watch’ (time-telling device) and ‘watch’ (observe)? Are “ain’t” and “isn’t” and “aren’t” different words? What about simple cases of inflectional morphology such as like ‘toy’ and ‘toys’?

According to Nefdt (2019b), the identity of a word is tied to its role in the sentence structure. In which case, “ain’t” and “isn’t” come out as the same word (at least in the singular use) but ‘watch’ (noun) and ‘watch’ (verb) do not. However, counterintuitively, his account might license the identity of words like ‘truck’ and ‘lorry’.

There are two strong but separate traditions which can both lay claim to being the ‘received position’. Within linguistics, the idea of a word as a LEXEME or mental dictionary entry is commonplace (with stipulations for senses, irregular forms, and selectional criteria). Most introductory textbooks assume something of this sort. In the philosophical literature, on the other hand, a mild or methodological version of platonism is often presupposed. This view has it that words can be separated into types and tokens, where the former lack specific spatiotemporal features and the latter instantiate these forms somehow.

The latter intuition seems to characterize most views on the ontology of words. Bromberger (1989) defines what he calls “the Platonic Relationship Principle” or the principle that allows us to ‘impute properties to types after observing and judging some of their tokens’ (Bromberger 1989, 62). While Bromberger (1989, 2011) represents the pinnacle of the classical philosophy of linguistics approach to these questions. In a more metaphysical mode, David Kaplan (1990, 2011) constructs a thoroughly physicalist proposal in which words are modelled in terms of a stages and continuants:

I propose a quite different model according to which utterances and inscriptions are stages of words, which are the continuants made up of these interpersonal stages along with some more mysterious intrapersonal stages. (Kaplan 1990: 98)

For him, what individuates words is the intention of the user (see Cappelen (1999) for an objection to intentional accounts tout court). Unfortunately, fascinating as Kaplan’s proposal is, it does not attempt to reflect on linguistic theory directly. In fact, one major criticism of his view, courtesy of Hawthorne and Lepore (2011), is that it fails to account for uninstantiated word-types whose existence is guaranteed by derivational morphology, whether or not they’ve been tokened or baptized in the real world. Other notable accounts are Wetzel’s (2009) Platonism (see the SEP entry on abstract objects ) and Szabó’s (1999) representational/nominalist view.

The philosophy of words has recently seen a resurgence in interest among philosophers, especially on the ontological issues. Miller (2021), for example, attempts to apply a bundle theory to the task of word individuation and identification. Irmak (2019) suggests that words are abstract artifacts (similarly to Katz and Wetzel) but insists that they are more akin to musical scores or works of fiction which have temporal components (“temporal abstracta” as he calls it). Mallory (2020) advocates the position that words are not really objects in the ordinary sense. However, he opts for an action-theoretic approach in which tokens provide instructions for the performance of action-types where our normal understanding of ‘word’ is to be identified with those types. His view is overtly naturalistic and focuses on the concept of words which is drawn from contemporary linguistic theory. Similarly, Nefdt (2019b) proffers a mathematical structuralist interpretation of SLEs in which the definition of words is continuous with the ontology of phrases and sentences. Here he follows Jackendoff (2018) who uses model-theoretic (Pullum 2013) or constraint-based grammar formalisms to argue for a continuum between words and linguistic rules. In other words, these latter two authors reject the idea that words are somehow sui generis entities in need of discontinuous explanation. Gasparri (2020) suggests pluralism is a more solid foundation for the ontology of words. He evaluates both “bundlistic” views such as Miller’s and causal-historical accounts such as Irmak’s before offering an alternative “view that there is a plurality of epistemically virtuous ways of thinking about the nature of words” (608).

These are of course complex issues and they offer a lens through which to appreciate the erstwhile debate on the ontology of language but with a contemporary and more focused flavor. Not all of the authors who work on the philosophy of words consider the role of linguistic theory to be central. Hence their work might be related but it does not quite qualify as the philosophy of linguistics, where this is viewed as a subfield of the philosophy of science. By contrast, we have focused on the authors who directly engage with linguistic theory in their accounts of the ontology of SLEs. There is also no clear mapping between the various ontological accounts mentioned here and the characterizations of linguistic theorizing in terms of Externalism, Emergentism and Essentialism. No particular metaphysical view unifies any of our three groupings. For example, not all Externalists incline toward nominalism; numerous Emergentists as well as most Essentialists take linguistics to be about mental phenomena; and our Essentialists include Katz’s platonism alongside the Chomskyan ‘I-language’ advocates and pluralists embrace aspects of all of the above.

Linguists’ conception of the components of the study of language contrast with philosophers’ conceptions (even those of philosophers of language) in at least three ways. First, linguists are often intensely interested in small details of linguistic form in their own right. Second, linguists take an interest in whole topic areas like the internal structure of phrases, the physics of pronunciation, morphological features such as conjugation classes, lexical information about particular words, and so on—topics in which there is typically little philosophical payoff. And third, linguists are concerned with relations between the different subsystems of languages: the exact way the syntax meshes with the semantics, the relationship between phonological and syntactic facts, and so on.

With regard to form, philosophers broadly follow Morris (1938), a foundational work in semiotics, and to some extent Peirce (see SEP entry: Peirce, semiotics), in thinking of the theory of language as having three main components:

• syntax , which treats of the form of signs;
• semantics , which deals with the relations of signs to their denotations; and
• pragmatics , which concerns the contextualized use of interpreted signs.

Linguists, by contrast, following both Sapir (1921) and Bloomfield (1933), treat the syntactic component in a more detailed way than Morris or Peirce, and distinguish between at least three kinds of linguistic form: the form of speech sounds (phonology), the form of words (morphology), and the form of sentences. (If syntax is about the form of expressions in general, then each of these would be an element of Morris’s syntax.)

Emergentists in general deny that there is a distinction between semantics and pragmatics—a position that is familiar enough in philosophy: Quine (1987: 211), for instance, holds that “the separation between semantics and pragmatics is a pernicious error.” And generally speaking, those theorists who, like the later Wittgenstein, focus on meaning as use will deny that one can separate semantics from pragmatics. Emergentists such as Paul Hopper & Sandra Thompson agree:

[W]hat is called semantics and what is called pragmatics are an integrated whole. (Hopper and Thompson 1993: 372)

Some Essentialists—notably Chomsky—also deny that semantics can be separated from pragmatics, but unlike the Emergentists (who think that semantics-pragmatics is a starting point for linguistic theory), Chomsky (as we noted briefly in section 1.3) denies that semantics and pragmatics can have any role in linguistics:

It seems that other cognitive systems—in particular, our system of beliefs concerning things in the world and their behavior—play an essential part in our judgments of meaning and reference, in an extremely intricate manner, and it is not at all clear that much will remain if we try to separate the purely linguistic components of what in informal usage or even in technical discussion we call ‘the meaning of [a] linguistic expression.’ (Chomsky 1979; 142)

Regarding the theoretical account of the relation between words or phrases and what speakers take them to refer to, Chomsky says, “I think such theories should be regarded as a variety of syntax” (Chomsky 1992: 223).

Not every Essentialist agrees with Chomsky on this point. Many believe that every theory should incorporate a linguistic component that yields meanings, in much the same way that many philosophers of language believe there to be such a separate component. Often, although not always, this component amounts to a truth-theoretic account of the values of syntactically-characterized sentences. This typically involves a translation of the natural language sentence into some representation that is “intermediate” between natural language and a truth-theory—perhaps an augmented version of first-order logic, or perhaps a higher-order intensional language. The Essentialists who study semantics in such ways usually agree with Chomsky in seeing little role for pragmatics within linguistic theory. But their separation of semantics from pragmatics allows them to accord semantics a legitimacy within linguistics itself, and not just in psychology or sociology.

Such Essentialists, as well as the Emergentists, differ in important ways from classical philosophical logic in their attitudes towards “the syntactic-semantic interface”, however. Philosophers of language and logic who are not also heavily influenced by linguistics tend to move directly—perhaps by means of a “semantic intuition” or perhaps from an intuitive understanding of the truth conditions involved—from a natural language sentence to its “deep, logical” representation. For example, they may move directly from (EX1) to (LF1):

And from there perhaps to a model-theoretic description of its truth-conditions. A linguist, on the other hand, would aim to describe how (EX1) and (LF1) are related. From the point of view of a semantically-inclined Essentialist, the question is: how should the syntactic component of linguistic theory be written so that the semantic value (or, “logical form representation”) can be assigned? From some Emergentist points of view, the question is: how can the semantic properties and communicative function of an expression explain its syntactic properties?

Matters are perhaps less clear with the Externalists—at least with those who identify semantic value with distribution in terms of neighboring words (there is a tradition stemming from the structuralists of equating synonymy with the possibility of substitution in all contexts without affecting acceptability).

Matters are in general quite a bit more subtle and tricky than (EX1) might suggest. Philosophers have taken the natural language sentence (EX2) to have two logical forms, (LF2a) and (LF2b):

But for the linguist interested in the syntax-semantics interface, there needs to be some explanation of how (LF2a) and (LF2b) are associated with (EX2). It could be a way in which rules can derive (LF2a) and (LF2b) from the syntactic representation of (EX2), as some semantically-inclined Essentialists would propose, or a way to explain the syntactic properties of (EX2) from facts about the meanings represented by (LF2a) and (LF2b), as some Emergentists might want. But that they should be connected up in some way is something that linguists would typically count as non-negotiable.

3. Linguistic Methodology and Data

The strengths and limitations of different data gathering methods began to play an important role in linguistics in the early to mid-20th century. Voegelin and Harris (1951: 323) discuss several methods that had been used to distinguish Amerindian languages and dialects:

• Informal elicitation : asking an informant for a metalinguistic judgment on an expression. [E.g., “Is this sentence grammatical?” “Do these two sentences mean the same thing?”]
• Corpus collection : gathering a body of naturally occurring utterances.
• Controlled experimentation : testing informants in some way that directly gauges their linguistic capacities.

They note that the anthropological linguists Boas and Sapir (who we take to be proto-Emergentists) used the ‘ask the informant’ method of informal elicitation, addressing questions “to the informant’s perception rather than to the data directly” (1951: 324). Bloomfield (the proto-Externalist), on the other hand, worked on Amerindian languages mostly by collecting corpora, with occasional use of monolingual elicitation.

The preferred method of Essentialists today is informal elicitation, including elicitation from oneself. Although the techniques for gathering data about speakers and their language use have changed dramatically over the past 60 or more years, the general strategies have not: data is still gathered by elicitation of metalinguistic judgments, collection of corpus material, or direct psychological testing of speakers’ reactions and behaviors. Different linguists will have different preferences among these techniques, but it is important to understand that data could be gathered in any of the three ways by advocates of any tendency. Essentialists, Emergentists, and Externalists differ as much on how data is interpreted and used as on their views of how it should be gathered.

A wide range of methodological issues about data collection have been raised in linguistics. Since gathering data by direct objective experimental testing of informants is a familiar practice throughout the social, psychological, medical, and biological sciences, we will say little about it here, focusing instead on these five issues about data:

• Disputes over the use of linguistic intuitions as linguistic data;
• Differences between grammaticality and acceptability judgments;
• Differences between scales for measuring acceptability judgments;
• Debates about the reliability of informal judgment elicitation methods; and
• Issues concerning the relevance and reliability of corpus evidence.

The debate in linguistics over the use of linguistic intuitions (elicited metalinguistic judgments) as data, and how that data should be collected has resulted in enduring, rancorous, often ideologically tinged disputes over the past 45 years. The disputes are remarkable, if only for their fairly consistent venomous tone.

At their most extreme, many Emergentists and some Externalists cast the debate in terms of whether linguistic intuitions should ever count as evidence for linguistic theorizing. And many Essentialists cast it in terms of whether anything but linguistic intuitions are ever really needed to support linguistic theorizing.

The debate focuses on the Essentialists’ notion of a mental grammar, since linguistic intuitions are generally understood to be a consequence of tacit knowledge of language. Emergentists who deny that speakers have innate domain-specific grammars (competence, I-languages, or FLN) have raised a diverse range of objections to the use of reports of intuitions as linguistic data – though Devitt (2006) offers an account of linguistic intuitions that does not base them on inferred tacit knowledge of competence grammars. The following passages are representative Emergentist critiques of ‘intuitions’ (elicited judgments):

Generative linguists typically respond to calls for evidence for the reality of their theoretical constructs by claiming that no evidence is needed over and above the theory’s ability to account for patterns of grammaticality judgments elicited from native speakers. This response is unsatisfactory on two accounts. First, such judgments are inherently unreliable because of their unavoidable meta-cognitive overtones… Second, the outcome of a judgment (or the analysis of an elicited utterance) is invariably brought to bear on some distinction between variants of the current generative theory, never on its foundational assumptions. (Edelman and Christiansen 2003: 60) The data that are actually used toward this end in Generative Grammar analyses are almost always disembodied sentences that analysts have made up ad hoc, … rather than utterances produced by real people in real discourse situations… In diametric opposition to these methodological assumptions and choices, cognitive-functional linguists take as their object of study all aspects of natural language understanding and use… They (especially the more functionally oriented analysts) take as an important part of their data not disembodied sentences derived from introspection, but rather utterances or other longer sequences from naturally occurring discourse. (Tomasello 1998: xiii) [T]he journals are full of papers containing highly questionable data, as readers can verify simply by perusing the examples in nearly any syntax article about a familiar language. (Wasow and Arnold 2005: 1484)

It is a common Emergentist objection that linguistic intuitions (taken to be reports of elicited judgments of the acceptability of expressions not their grammaticality) are bad data points because not only are they not usage data, i.e., they are metalinguistic, but also because they are linguists’ judgments about invented example sentences. On neither count would they be clear and direct evidence of language use and human communicative capacities—the subject matter of linguistics on the Emergentist view. A further objection is to their use by theorists to the exclusion of all other kinds of evidence. For example,

[Formal linguistics] continues to insist that its method for gathering data is not only appropriate, but is superior to others. Occasionally a syntactician will acknowledge that no one type of data is privileged, but the actual behavior of people in the field belies this concession. Take a look at any recent article on formal syntax and see whether anything other than the theorist’s judgments constitute the data on which the arguments are based. (Ferreira 2005: 372)

“Formal” is Emergentist shorthand for referring to generative linguistics. And it should be noted that the practice by Essentialists of collapsing various kinds of acceptability judgments under the single label ‘intuitions’ masks important differences. In principle there might be significant differences between the judgments of (i) linguists with a stake in what the evidence shows; (ii) linguists with experience in syntactic theory but no stake in the issue at hand; (iii) non-linguist native speakers who have been tutored in how to provide the kinds of judgments the linguist is interested in; and (iv) linguistically naïve native speakers.

Many Emergentists object to all four kinds of reports of intuitions on the grounds that they are not direct evidence language use. For example, a common objection is based on the view that

[T]he primary object of study is the language people actually produce and understand. Language in use is the best evidence we have for determining the nature and specific organization of linguistic systems. Thus, an ideal usage-based analysis is one that emerges from observation of such bodies of usage data, called corpora.… Because the linguistic system is so closely tied to usage, it follows that theories of language should be grounded in an observation of data from actual uses of language. (Barlow and Kemmer 2002, Introduction)

But collections of linguists’ reports of their own judgments are also criticized by Emergentists as “arm-chair data collection,” or “data collection by introspection”. All parties tend to call this kind of data collection “informal”—though they all rely on either formally or informally elicited judgments to some degree.

On the other side, Essentialists tend to deny that usage data is adequate evidence by itself:

More than five decades of research in generative linguistics have shown that the standard generative methodology of hypothesis formation and empirical verification via judgment elicitation can lead to a veritable goldmine of linguistic discovery and explanation. In many cases it has yielded good, replicable results, ones that could not as easily have been obtained by using other data-gathering methods, such as corpus-based research…[C]onsider the fact that parasitic gap constructions…are exceedingly rare in corpora…. [T]hese distributional phenomena would have been entirely impossible to distill via any non-introspective, non-elicitation based data gathering method. Corpus data simply cannot yield such a detailed picture of what is licit and, more crucially, what is not licit for a particular construction in a particular linguistic environment. (den Dikken et al. 2007: 336)

And Essentialists often seem to deny that they are guilty of what the Emergentist claims they are guilty of. For example, Chomsky appears to be claiming that acceptability judgments are performance data, i.e. evidence of use:

Acceptability is a concept that belongs to the study of performance, whereas grammaticalness belongs to the study of competence… Like acceptability, grammaticalness is, no doubt, a matter of degree…but the scales of grammaticalness and acceptability do not coincide. Grammaticalness is only one of many factors that interact to determine acceptability. (Chomsky 1965: 11)

Chomsky means to deny that acceptability judgments are direct evidence of linguistic competence . But it does not follow from this that elicited acceptability judgments are direct evidence of language use.

And as for the charge of “arm-chair” collection methods, some Essentialists claim to have shown that such methods are as good as more controlled experimental methods. For example, Sprouse and Almeida report:

[W]e empirically assess this claim by formally testing all 469 (unique, US-English) data points from a popular syntax textbook (Adger 2003) using 440 naïve participants, two judgment tasks (magnitude estimation and yes–no), and three different types of statistical analyses (standard frequentist tests, linear mixed effects models, and Bayes factor analysis). The results suggest that the maximum discrepancy between traditional methods and formal experimental methods is 2%. This suggests that … the minimum replication rate of these 469 data points is 98%. (Spouse and Almeida 2012, p. 609, abstract)

This can be read as defending either Essentialists’ consulting of their own intuitions simpliciter, or their self-consultation of intuitions on uncontroversial textbook cases only. The former is much more controversial than the later.

One might also wonder whether an error rate of 2% really is appropriate for the primary data presented in an elementary textbook. If a geography textbook misidentified 2–3% of the rivers of the continental United States, or gave incorrect locations for them, or incorrectly reported their lengths, it would forfeit our trust. Analogous claims could be made about any elementary textbook in other fields: an elementary English literature textbook that misidentified the authors of 2% of the books discussed, or their years of publication, etc.

Finally, both parties of the debate engage in ad hominem attacks on their opponents. Here is one example of a classic ad hominem or tu quoque attack on Emergentists in defense of constructed examples by Essentialists:

[The charge made concerning “armchair data collection”] implies that there is something intrinsic to generative grammar that invites partisans of that framework to construct syntactic theories on the evidence of a single person’s judgments. Nothing could be farther from the truth. The great bulk of publications in cognitive and functional linguistics follow the same practice. Of course, rhetorically many of the latter decry the use of linguists’ own intuitions as data. For example, in … an important collections [sic] of papers in cognitive-functional linguistics, … only two contributors to the volume … present segments of natural discourse, neither filling even a page of text. All of the other contributors employ examples constructed by the linguists themselves. It is quite difficult to find any work in cognitive linguistics (and functional linguists are only slightly better) that uses multiple informants. It seems almost disingenuous … to fault generativists for what (for better or worse) is standard practice in the field, regardless of theoretical allegiance. (Newmeyer 2007: 395)

Clearly, the mere fact that some Emergentists may in practice have made use of invented examples in testing their theories does not tell against any cogent general objections they may have offered to such practice. What is needed is a decision on the methodological point, not just a cry of “You did it too!”.

Given the intolerance of each other’s views, and the crosstalk present in these debates, it is tempting to think that Emergentism and Essentialism are fundamentally incompatible on what counts as linguistic data, since their differences are based on their different views of the subject matter of linguistics, and what the phenomena and goals of linguistic theorizing are. There is no doubt that the opposing sides think that their respective views are incompatible. But this conclusion may well be too hasty. In what follows, we try to point to a way that the dispute could be ameliorated, if not adjudicated.

Essentialists who accept the competence/performance distinction of Chomsky (1965) traditionally emphasize elicited acceptability judgment data (although they need not reject data that is gathered using other methods). But as Cowart notes:

In this view, which exploits the distinction between competence and performance, the act of expressing a judgment of acceptability is a kind of linguistic performance. The grammar that a [generative Essentialist] linguistic theory posits in the head of a speaker does not exercise exhaustive control of judgments… While forming a sentence judgment, a speaker draws on a variety of cognitive resources… The resulting [acceptability] judgments could pattern quite differently than the grammaticality values we might like them to reflect. (Cowart 1997: 7)

The grammaticality of an expression, on the standard generative Essentialist view, is the status conferred on it by the competence state of an ideal speaker. But competence can never be exercised or used without potentially interfering performance factors like memory being exercised as well. This means that judgments about grammaticality are never really directly available to the linguist through informant judgments: they have to be inferred from judgments of acceptability (along with any other relevant evidence). Nevertheless, Essentialists do take acceptability judgments to provide fairly good evidence concerning the character of linguistic competence. In fact the use of informally gathered acceptability judgment data is a hallmark of post-1965 Essentialist practice.

It would be a mistake, however, to suppose that only Essentialists make use of such judgments. Many contemporary Externalists and Emergentists who reject the competence/performance distinction still use informally gathered acceptability judgments in linguistic theorizing, though perhaps not in theory testing. Emergentists tend to interpret experimentally gathered judgment data as performance data reflecting the interactions between learned features of communication systems and general learning mechanisms as deployed in communication. And Externalists use judgment data for corpus cleaning (see below).

It should be noted that sociolinguists and anthropological linguists (and we regard them as tending toward Emergentist views) often informally elicit informant judgments not only about acceptability but also about social and regional style and variation, and meaning. They may ask informants questions like, “Who would typically say that?”, or “What does X mean in context XYZ?”, or “If you can say WXY, can you say WXZ?” (see Labov 1996: 77).

A generative grammar gives a finite specification of a set of expressions. A psychogrammar, to the extent that it corresponds to a generative grammar, might be thought to equip a speaker to know (at least in principle) absolutely whether a string is in the language. However, elicited metalinguistic judgments are uncontroversially a matter of degree. A question arises concerning the scale on which these degrees of acceptability should be measured.

Linguists have implicitly worked with a scale of roughly half a dozen levels and types of acceptability, annotating them with prefixed symbols. The most familiar is the asterisk, originally used simply to mark strings of words as ungrammatical, i.e., as not belonging to the language at all. Other prefixed marks have gradually become current:

But other annotations have been used to indicate a gradation in the extent to which some sentences are unacceptable. No scientifically validated or explicitly agreed meanings have been associated with these marks, but a tradition has slowly grown up of assigning prefixes such as those in Table 2 to signify degrees of unacceptability:

Table 2: Prefixes used to mark levels of acceptability

Such markings are often used in a way that suggests an ordinal scale , i.e. a partial ordering that is silent on anything other than equivalence in acceptability or ranking in degree of unacceptability.

By contrast, Bard et al. (1996: 39) point out, it is possible to use interval scales , which additionally measure distance between ordinal positions. Interval scales of acceptability would measure relative distances between strings—how much more or less acceptable one is than another. Magnitude estimation is a method developed in psychophysics to measure subjects’ judgments of physical stimuli on an interval scale. Bard et al. (1996) adapted these methods to linguistic acceptability judgments, arguing that interval scales of measurement are required for testing theoretical claims that rely on subtle judgments of comparative acceptability. An ordinal scale of acceptability can represent one expression as being less acceptable than another, but cannot support quantitative questions about how much less. Many generative Essentialist theorists had been suggesting that violation of different universal principles led to different degrees of unacceptability. According to Bard et al. (34–35), because there may be “disproportion between the fineness of judgments people can make and the symbol set available for recording them” it will not suffice to use some fixed scale such as this one:

? < ?? < ?* < * < **

indicating absolute degrees of unacceptability. Degrees of relative unacceptability must be measured. This is done by asking the informant how much less acceptable one string is than another.

Magnitude estimation can be used with both informal and experimental methods of data collection. And data that is measured using interval scales can be subjected to much more mathematically sophisticated tests and analyses than data measured solely by an ordinal scale, provided that quantitative data are available.

It should be noted that the value of applying magnitude estimation to the judgment of acceptability has been directly challenged in two recent papers. Weskott and Fanselow (2011) and Sprouse (2011) both present critiques of Bard et al. (1996). Weskott and Fanselow compared magnitude estimation data to standard judgments on binary and 7-point scales, and claim that magnitude estimation does not yield more information than other judgment tasks, and moreover can produce spurious variance. And Sprouse, on the basis of recent formalizations of magnitude estimation in the psychophysics literature, presents experimental evidence that participants cannot make ratio judgments of acceptability (for example, a judgment that one sentence is precisely half as acceptable as another), which suggests that the magnitude estimation task probably provides the same interval-level data as other judgment tasks.

Part of the dispute over the reliability of informal methods of acceptability judgment elicitation and collection is between different groups of Essentialists. Experimentally trained psycholinguists advocate using and adapting various experimental methods that have been developed in the cognitive and behavioral sciences to collect acceptability judgments. And while the debate is often cast in terms of which method is absolutely better, a more appropriate question might be when one method is to be preferred to the others. Those inclined toward less experimentally controlled methods point out that there are many clear and uncontroversial acceptability judgments that do not need to be shown to be reliable. Advocates of experimental methods point out that many purportedly clear, uncontroversial judgments have turned out to be unreliable, and led to false empirical generalizations about languages. Both seem to be right in different cases.

Chomsky has frequently stated his view that the experimental data-gathering techniques developed in the behavioral sciences are neither used nor needed in linguistic theorizing. For example:

The gathering of data is informal; there has been little use of experimental approaches (outside of phonetics) or of complex techniques of data collection and data analysis of a sort that can easily be devised, and that are widely used in the behavioral sciences. The arguments in favor of this informal procedure seem to me quite compelling; basically, they turn on the realization that for the theoretical problems that seem most critical today, it is not at all difficult to obtain a mass of crucial data without use of such techniques. Consequently, linguistic work, at what I believe to be its best, lacks many of the features of the behavioral sciences. (Chomsky 1969: 56)

He also expressed the opinion that using experimental behavioral data collection methods in linguistics “would be a waste of time and energy” (1969: 81).

Although many Emergentists—the intellectual heirs of Sapir—would accept ‘ask-the-informant’ data, we might expect them to tend to accept experimental data-gathering methods that have been developed in the social sciences. There is little doubt that strict followers of the methodology preferred by Bloomfield in his later career would disapprove of ‘ask the informant’ methods. Charles Hockett remarked:

A language, as a set of habits, is a fragile thing, subject to minor modification in the slightest breeze of circumstance; this, indeed, is its great source of power. But this is also why the transformationalists (like the rest of us!), using themselves as informants, have such a hard time deciding whether certain candidates for sentencehood are really ‘in their dialect’ or not; and it is why Bloomfield, in his field work, would never elicit paradigms, for fear he would induce his informant to say something under the artificial conditions of talking with an outsider that he would never have said in his own everyday surroundings. (Hockett 1968: 89–90, fn. 31)

We might expect Bloomfield, having abandoned his earlier Wundtian psychological leanings, to be suspicious of any method that could be cast as introspective. And we might expect many contemporary Externalists to prefer more experimentally controlled methods too. (We shall see below that to some extent they do.)

Derwing (1973) was one early critic of Chomsky’s view (1969) that experimentally controlled data collection is useless; but it was nearly 25 years before systematic research into possible confounding variables in acceptability judgment data started being conducted on any significant scale. In the same year that Bard et al. (1996) appeared, Carson Schütze (1996) published a monograph with the following goal statement:

I aim to demonstrate…that grammaticality judgments and other sorts of linguistic intuition, while indispensable forms of data for linguistic theory, require new ways of being collected and used. A great deal is known about the instability and unreliability of judgments, but rather than propose that they be abandoned, I endeavor to explain the source of their shiftiness and how it can be minimized. (1996: 1)

In a similar vein, Wayne Cowart stated that he wanted to “describe a family of practical methods that yield demonstrably reliable data on patterns of sentence acceptability.” He observes that the stability and reliability of acceptability judgment collection is

complicated by the fact that there seems to be no consensus on how to gather judgments apart from a widespread tolerance for informal methods in which the linguist consults her own intuitions and those of the first handy informant (what we might call the “Hey, Sally” method). (Cowart 1997: 2)

Schütze also expresses the importance of using experimental methods developed in cognitive science:

[M]y claim is that none of the variables that confound metalinguistic data are peculiar to judgments about language. Rather they can be shown to operate in some other domain in a similar way. (This is quite similar to Valian’s (1982) claim that the data of more traditional psychological experiments have all the same problems that judgment data have.) (Schütze 1996: 14)

The above can be read as sympathetic to the Essentialist preference for elicited judgments.

Among the findings of Schütze and Cowart about informal judgment collection methods are these:

• There is really no agreement in linguistics on what counts as an informal method (though note that Sprouse and Almeida 2012 are much more comfortable with the informal method of consulting one's own intuitions of grammaticality).
• The collection of acceptability judgment data is just as vulnerable to the influence of extraneous variables as are other kinds of psychological data.
• Judgment samples can be biased in informal judgment collection.
• Experimenter bias is often not controlled for in informal judgment collection.
• Judgment materials are often not carefully prepared to present a relevant, well-ordered, contrasting set of minimal pairs.
• The instability of one-off speaker judgments can be controlled for by gathering judgments from a given speaker across time.

Although Schütze (1996) and Cowart (1997) are both critical of traditional Essentialist informal elicitation methods, their primary concern is to show how the claims of Essentialist linguistics can be made less vulnerable to legitimate complaints about informal data collection methods. Broadly speaking, they are friends of Essentialism. Critics of Essentialism have raised similar concerns in less friendly terms, but it is important to note that the debate over the reliability of informal methods is a debate within Essentialist linguistics as well.

Informal methods of acceptability judgment data have often been described as excessively casual. Ferreira described the informal method this way:

An example sentence that is predicted to be ungrammatical is contrasted with some other sentence that is supposed to be similar in all relevant ways; these two sentences constitute a “minimal pair”. The author of the article provides the judgment that the sentence hypothesized to be bad is in fact ungrammatical, as indicated by the star annotating the example. But there are serious problems with this methodology. The example that is tested could have idiosyncratic properties due to its unique lexical content. Occasionally a second or third minimal pair is provided, but no attempt is made to consider the range of relevant extraneous variables that must be accounted for and held constant to make sure there isn’t some correlated property that is responsible for the contrast in judgments. Even worse, the “subject” who provides the data is not a naïve informant, but is in fact the theorist himself or herself, and that person has a stake in whether the sentence is judged grammatical or ungrammatical. That is, the person’s theory would be falsified if the prediction were wrong, and this is a potential source of bias. (Ferreira 2005: 372)

(It would be appropriate to read ‘grammatical’ and ‘grammaticality’ in Ferreira’s text as meaning ‘acceptable’ and ‘acceptability’.)

This critical characterization exemplifies the kind of method that Schütze and Cowart aimed to improve on. More recently, Gibson and Fedorenko describe the traditional informal method this way:

As has often been noted in recent years (Cowart, 1997; Edelman & Christiansen, 2003; Featherston, 2007; Ferreira, 2005; Gibson & Fedorenko, 2010a; Marantz, 2005; Myers, 2009; Schütze, 1996; Wasow & Arnold, 2005), the results obtained using this method are not necessarily generalisable because of (a) the small number of experimental participants (typically one); (b) the small number of experimental stimuli (typically one); (c) cognitive biases on the part of the researcher and participants; and (d) the effect of the preceding context (e.g., other constructions the researcher may have been recently considering). (Gibson and Fedorenko, 2013)

While some Essentialists have acknowledged these problems with the reliability of informal methods, others have, in effect, denied their relevance. For example, Colin Phillips (2010) argues that “there is little evidence for the frequent claim that sloppy data-collection practices have harmed the development of linguistic theories”. He admits that not all is epistemologically well in syntactic theory, but adds, “I just don’t think that the problems will be solved by a few rating surveys.” He concludes:

I do not think that we should be fooled into thinking that informal judgment gathering is the root of the problem or that more formalized judgment collection will solve the problems. (Phillips 2010: 61)

To suggest that informal methods are as fully reliable as controlled experimental ones would be a serious charge, implying that researchers like Bard, Robinson, Sorace, Cowart, Schütze, Gibson, Fedorenko, and others have been wasting their time. But Phillips actually seems to be making a different claim. He suggests first that informally gathered data has not actually harmed linguistics, and second that linguists are in danger of being “fooled” by critics who invent stories about unreliable data having harmed linguistics.

The harm that Phillips claims has not occurred relates to the charge that “mainstream linguistics” (he means the current generative Essentialist framework called ‘Minimalism’) is “irrelevant” to broader interests in the cognitive sciences, and has lost “the initiative in language study”. Of course, Phillips is right in a sense: one cannot insure that experimental judgment collection methods will address every way in which Minimalist theorizing is irrelevant to particular endeavors (language description, language teaching, natural language processing, or broader questions in cognitive psychological research). But this claim does not bear on what Schütze (1996) and Cowart (1997) show about the unreliability of informal methods.

Phillips does not fully accept the view of Chomsky (1969) that experimental methods are useless for data gathering (he says, “I do not mean to argue that comprehensive data gathering studies of acceptability are worthless”). But his defense of informal methods of data collection rests on whether these methods have damaged Essentialist theory testing:

The critiques I have read present no evidence of the supposed damage that informal intuitions have caused, and among those who do provide specific examples it is rare to provide clear evidence of the supposed damage that informal intuitions have caused… What I am specifically questioning is whether informal (and occasionally careless) gathering of acceptability judgments has actually held back progress in linguistics, and whether more careful gathering of acceptability judgments will provide the key to future progress.

Either Phillips is fronting the surprising opinion that generative theorizing has never been led down the wrong track by demonstrably unreliable data, or he is changing the subject. And unless clear criteria are established for what counts as “damage” and “holding back,” Phillips is not offering any testable hypothesis about data collection methodology. For example, Phillips discounts the observation of Schütze (1996) that conflicting judgments of relative unacceptability of violations of two linguistic universals held back the development of Government and Binding (GB), on the grounds that two sets of conflicting judgments and their analyses “are now largely forgotten, supplanted by theories that have little to say about such examples.” But the fact that the proposed universals are discarded principles of UG is irrelevant to the effect that unreliable data once had on the (now largely abandoned) GB theory. A methodological concern cannot be dismissed on the basis of a move to a new theory that abandons the old theory but not its methods!

More recently, Bresnan (2007) claims that many theoretical claims have arguably been supported by unreliable informally gathered syntactic acceptability judgments. She observes:

Erroneous generalizations based on linguistic intuitions about isolated, constructed examples occur throughout all parts of the grammar. They often seriously underestimate the space of grammatical possibility (Taylor 1994, 1996, Bresnan & Nikitina 2003, Fellbaum 2005, Lødrup 2006, among others), reflect relative frequency instead of categorical grammaticality (Labov 1996, Lapata 1999, Manning 2003), overlook complex constraint interactions (Green 1971, Gries 2003) and processing effects (Arnon et al. 2005a, b), and fail to address the problems of investigator bias (Labov 1975, Naro 1980, Chambers 2003: 34) and social intervention (Labov 1996, Milroy 2001, Cornips & Poletto 2005). (Bresnan 2007: 301)

Her discussion supports the view that various highly abstract theoretical hypotheses have been defended through the use of generalizations based on unreliable data.

The debate over the harm that the acceptance of informally collected data has had on theory testing is somewhat difficult to understand for Essentialist, Externalist, and Emergentist researchers who have been trained in the methods of the cognitive and behavioral sciences. Why try to support one’s theories of universal grammar, or of the grammars of particular languages, by using questionably reliable data?

One clue might be found in Culicover and Jackendoff (2010), who write:

[T]heoreticians’ subjective judgments are essential in formulating linguistic theories. It would cripple linguistic investigation if it were required that all judgments of ambiguity and grammaticality be subject to statistically rigorous experiments on naive subjects. (Culicover and Jackendoff 2010)

The worry is that use of experimental methods is so resource consumptive that it would impede the formulation of linguistic theories. But this changes the subject from the importance of using reliable data as evidence in theory testing to using only experimentally gathered data in theory formulation . We are not aware of anyone who has ever suggested that at the stage of hypothesis development or theory formulation the linguist should eschew intuition. Certainly Bard et al., Schütze, Cowart, Gibson & Fedorenko, and Ferreira say no such thing. The relevant issue concerns what data should be used to test theories, which is a very different matter.

We noted earlier that there are clear and uncontroversial acceptability judgments, and that these judgments are reliable data. The difficulty lies in distinguishing the clear, uncontroversial, and reliable data from what only appears to be clear, uncontroversial, and reliable to a research community at a time. William Labov, the founder of modern quantitative sociolinguistics, who takes an Emergentist approach, proposed a set of working methodological principles in Labov (1975) for adjudicating when experimental methods should be employed.

The Consensus Principle : If there is no reason to think otherwise, assume that the judgments of any native speaker are characteristic of all speakers. The Experimenter Principle : If there is any disagreement on introspective judgments, the judgments of those who are familiar with the theoretical issues may not be counted as evidence. The Clear Case Principle : Disputed judgments should be shown to include at least one consistent pattern in the speech community or be abandoned. If differing judgments are said to represent different dialects, enough investigation of each dialect should be carried out to show that each judgment is a clear case in that dialect. (Labov 1975, quoted in Schütze 1996: 200)

If we accept that ‘introspective judgments’ are acceptability judgments, then Labov’s rules of thumb are guides for when to deploy experimental methods, although they no doubt need refinement. However, it seems vastly more likely that careful development of such methodological rules of thumb can serve to improve the reliability of linguistic data and adjudicate these methodological disputes that seem largely independent of any particular approach to linguistics.

In linguistics, the goal of collecting corpus data is to identify and organize a representative sample of a written and/or spoken variety from which characteristics of the entire variety or genre can be induced. Concordances of word usage in linguistic context have long been used to aid in the translation and interpretation of literary and sacred texts of particular authors (e.g. Plato, Aristotle, Aquinas) and of particular texts (e.g. the Torah, the rest of the Old Testament, the Gospels, the Epistles). Formal textual criticism, the identification of antecedently existing oral traditions that were later redacted into Biblical texts, and author identification (e.g. figuring out which of the Epistles were written by Paul and which were probably not) began to develop in the late 19th century.

The development of computational methods for collecting, analyzing, and searching corpora have seen rapid development as computer memory has become less expensive and search and analysis programs have become faster. The first computer searchable corpus of American English, the Brown Corpus, developed in the 1960s, contained just over one million word tokens. The British National Corpus (BNC) is a balanced corpus containing over 100 million words—a hundredfold size increase—of which 90% is written prose published from 1991 to 1994 and 10% is spoken English. Between 2005 and 2007, billion-word corpora were released for British English (ukWaC), German (deWaC), and Italian (itWaC)—a thousand times bigger than the Brown corpus. And the entire World Wide Web probably holds about a thousand times as much as that—around a trillion words. Thus corpus linguistics has gone from megabytes of data (∼ 10 3 kB) to terabytes of data (∼ 10 9 kB) in fifty years.

Just as a central issue concerning acceptability judgment data concerns its reliability as evidence for empirical generalizations about languages or idiolects, a central question concerning the collection of corpus data concerns whether or not it is representative of the language variety it purports to represent. Some linguists make the criterion of representativeness definitional: they call a collection of samples of language use a corpus only if it has been carefully balanced between different genres (conversation, informal writing, journalism, literature, etc.), regional varieties, or whatever.

But corpora are of many different kinds. Some are just very large compilations of text from individual sources such as newspapers of record or the World Wide Web—compilations large enough for the diversity in the source to act as a surrogate for representativeness. For example, a billion words of a newspaper, despite coming from a single source, will include not only journalists’ news reports and prepared editorials but also quoted speech, political rhetoric, humor columns, light features, theater and film reviews, readers’ letters, fiction items, and so on, and will thus provide examples of a much wider variety of styles than one might have thought.

Corpora are cleaned up through automatic or manual removal of such elements as numerical tables, typographical slips, spelling mistakes, markup tags, accidental repetitions ( the the ), larger-scale duplications (e.g., copies on mirror sites), boilerplate text ( Opinions expressed in this email do not necessarily reflect …), and so on (see Baroni et al. 2009 for a fuller discussion of corpus cleaning).

The entire web itself can be used as a corpus to some degree, despite its constantly changing content, its multilinguality, its many tables and images, and its total lack of quality control; but when it is, the outputs of searches are nearly always cleaned by disregarding unwanted results. For example, Google searches are blind to punctuation, capitalization, and sentence boundaries, so search results for to be will unfortunately include irrelevant cases, such as where a sentence like Do you want to? happens to be followed by a sentence like Be careful .

Corpora can be annotated in ways that permit certain kinds of analysis and grammar testing. One basic kind of annotation is part-of-speech tagging, in which each word is labeled with its syntactic category. Another is lemmatization, which classifies the different morphologically inflected forms of a word as belonging together ( goes , gone , going , and went belong with go , for example). A more thoroughgoing kind of annotation involves adding markup that encodes trees representing their structure; an example like That road leads to the freeway might be marked up as a Clause within which the first two words make up a Noun Phrase (NP), the last four constitute a Verb Phrase (VP), and so on, giving a structural analysis represented thus:

Such a diagram is isomorphic to (and the one shown was computed directly from) a labeled bracketing like this:

(.Clause. (.NP. (.D. ‘that’ ) (.N. ‘road’ ) ) (.VP. (.V. ‘leads’ ) (.PP. (.P. ‘to’ ) (.NP. (.D. ‘the’ ) (.N. ‘freeway’ ) ) ) ) )

and this in turn could be represented in a markup language like XML as:

A corpus annotated with tree structure is known as a treebank . Clearly, such a corpus is not a raw record of attested utterances at all; it is a combination of a collection of attested utterances together with a systematic attempt at analysing their structure. Whether the analysis is added manually or semi-automatically, it is ultimately based on native speaker judgments. (Treebanks are often developed by graduate student annotators tutored by computational linguists; naturally, consistency between annotators is an issue that needs regular attention. See Artstein and Poesio, 2008, for discussion of the methodological issues.).

One of the purposes of a treebank is to permit the further investigation of a language and the checking of further linguistic hypotheses by searching a large database of previously established analyses. It can also be used to test grammars, natural language processing systems, or machine learning programs.

Going beyond syntactic parse trees, it is possible to annotate corpora further, with information of a semantic and pragmatic nature. There is ongoing computational linguistic research aimed at discovering whether, for example, semantic annotation that is semi-automatically added might suffice for recognition of whether a product review is positive or negative (what computational linguists call ‘sentiment analysis’).

Notice, then, that using corpus data does not mean abandoning or escaping from the use of intuitions about acceptability or grammatical structure: the results of a corpus search are generally filtered through the judgments of an investigator who decides which pieces of corpus data are to be taken at face value and which are just bad hits or irrelevant noise.

Difficult methodological issues arise in connection with the collection, annotation, and use of corpus data. For example, there is the issue of extremely rare expression tokens. Are they accurately recorded tokens of expression types that turn up only in consequence of sporadic errors and should be dismissed as irrelevant unless the topic of interest is performance errors? Are they due to errors in the compilation of the corpus itself, corresponding to neither accepted usage nor sporadic speech errors? Or are they perfectly grammatical but (for some extraneous reason) very rare, at least in that particular corpus?

Many questions arise about what kind of corpus is best suited to the research questions under consideration, as well as what kind of annotation is most appropriate. For example, as Ferreira (2005: 375) points out, some large corpora, insofar as they have not been cleaned of speech errors, provide relevant data for studying the distribution of speech disfluencies. In addition, probabilistic information about the relation between a particular verb and its arguments has been used to show that “verb-argument preferences [are] an essential part of the process of sentence interpretation” (Roland and Jurafsky 2002: 325): acceptability judgments on individual expressions do not provide information about the distribution of a verb and its arguments in various kinds of speech and writing. Studying conveyed meaning in context and identification of speech acts will require a kind of data that decontextualized acceptability judgments do not provide but semantically annotated corpora might.

Many Essentialists have been skeptical of the reliability of uncleaned, unanalyzed corpus data as evidence to support linguistic theorizing, because it is assumed to be replete with strings that any native speaker would judge unacceptable. And many Emergentists and Externalists, as well as some Essentialists, have charged that informally gathered acceptability judgments can be highly unreliable too. Both worries are apposite; but the former does not hold for adequately cleaned and analyzed corpora, and the latter does not hold for judgment data that has been gathered using appropriately controlled methods. In certain contested cases of acceptability, it will of course be important to use both corpus and controlled elicitation methods to cross-compare.

Notice that we have not in any way suggested that our three broad approaches to linguistics should differ in the kinds of data they use for theory testing: Essentialists are not limited to informal elicitation; nor are Emergentists and Externalists denied access to it. In matters of methodology, at least, there is in principle an open market—even if many linguists seem to think otherwise.

4. Language Acquisition

The three approaches to linguistic theorizing have at least something to say about how languages are acquired, or could in principle be acquired. Language acquisition has had a much higher profile since generative Essentialist work of the 1970s and 1980s gave it a central place on the agenda for linguistic theory.

Research into language acquisition falls squarely within the psychology of language; see the entry on language and innateness . In this section we do not aim to deal in detail with any of the voluminous literature on psychological or computational experiments bearing on language acquisition, or with any of the empirical study of language acquisition by developmental linguists, or the ‘stimulus poverty’ argument for the existence of innate knowledge about linguistic structure (Pullum and Scholz 2002). Our goals are merely to define the issue of linguistic nativism , set it in context, and draw morals for our three approaches from some of the mathematical work on inductive language learning.

The reader with prior acquaintance with the literature of linguistics will notice that we have not made reference to any partitioning of linguists into two camps called ‘empiricists’ and ‘rationalists’ (see e.g. Matthews 1984, Cowie 1999). We draw a different distinction relating to the psychological and biological prerequisites for first language acquisition. It divides nearly all Emergentists and Externalists from most Essentialists. It has often been confused with the classical empiricist/rationalist issue.

General nativists maintain that the prerequisites for language acquisition are just general cognitive abilities and resources. Linguistic nativists , by contrast, claim that human infants have access to at least some specifically linguistic information that is not learned from linguistic experience. Table 3 briefly sketches the differences between the two views.

Table 3: General and linguistic nativism contrasted

There does not really seem to be anyone who is a complete non-nativist: nobody really thinks that a creature with no unlearned capacities at all could acquire a language. That was the point of the much-quoted remark by Quine (1972: 95–96) about how “the behaviorist is knowingly and cheerfully up to his neck in innate mechanisms of learning-readiness”. Geoffrey Sampson (2001, 2005) is about as extreme an opponent of linguistic nativism as one can find, but even he would not take the failure of language acquisition in his cat to be unrelated to the cognitive and physical capabilities of cats.

The issue on which empirical research can and should be done is whether some of the unlearned prerequisites that humans enjoy have specifically linguistic content. For a philosophically-oriented discussion of the matter, see chapters 4–6 of Stainton (2006). For extensive debate about “the argument from poverty of the stimulus”, see Pullum and Scholz (2002) together with the six critiques published in the same issue of The Linguistic Review and the responses to those critiques by Scholz and Pullum (2002).

Linguists have given considerable attention to considerations of in-principle learnability —not so much the course of language acquisition as tracked empirically (the work of developmental psycholinguists) but the question of how languages of the human sort could possibly be learned by any kind of learner. The topic was placed squarely on the agenda by Chomsky (1965); and a hugely influential mathematical linguistics paper by Gold (1967)has dominated much of the subsequent discussion.

4.2.1 The Gold paradigm

Gold began by considering a reformulation of the standard philosophical problem of induction. The trouble with the question ‘Which hypothesis is correct given the totality of the data?’ is of course the one that Hume saw: if the domain is unbounded, no finite amount of data can answer the question. Any finite body of evidence will be consistent with arbitrarily many hypotheses that are not consistent with each other. But Gold proposed replacing the question with a very different one: Which tentative hypothesis is the one to pick , given the data provided so far, assuming a finite number of wrong guesses can be forgiven?

Gold assumed that the hypotheses, in the case of language learning, were generative grammars (or alternatively parsers; he proves results concerning both, but for brevity we follow most of the literature and neglect the very similar results on parsers). The learner’s task is conceived of as responding to an unending input data stream (ultimately complete, in that every expression eventually turns up) by enunciating a sequence of guesses at grammars.

Although Gold talks in developmental psycholinguistic terms about language learners learning grammars by trial and error, his extremely abstract proofs actually make no reference to the linguistic content of languages or grammars at all. The set of all finite grammars formulable in any given metalanguage is computably enumerable, so grammars can be systematically numbered. Inputs—grammatical expressions from the target language—can also be numerically encoded. We end up being concerned simply with the existence or non-existence of certain functions from natural number sequences to natural numbers.

A successful learner is one who uses a procedure that is guaranteed to eventually hit on a correct grammar. For single languages, this is trivial: if the target language is L and it is generated by a grammar G , then the procedure “Always guess G ” does the job, and every language is learnable. What makes the problem interesting is applying it to classes of grammars. A successful learner for a class C is one who uses a procedure that is guaranteed to succeed no matter what grammar from C is the target and no matter what the data stream is like (as long as it is complete and contains no ungrammatical examples).

Gold’s work has interesting similarities with earlier philosophical work on inductive learning by Hilary Putnam (1963; it is not clear whether Gold was aware of this paper). Putnam gave an informal proof of a sort of incompleteness theorem for inductive regularity-learning devices: no matter what algorithm is used in a machine for inducing regularities from experience, and thus becoming able to predict events, there will always be some possible environmental regularities that will defeat it. (As a simple example, imagine an environment giving an unbroken sequence of presentations all having some property a . If there is a positive integer n such that after n presentations the machine will predict that presentation number n + 1 will also have property a , then the machine will be defeated by an environment consisting of n presentations of a followed by one with the incompatible property b —the future need not always resemble the past. But if on the other hand there is no such n , then an environment consisting of an unending sequence of a presentations will defeat it.)

Gold’s theorems are founded on certain specific idealizing assumptions about the language learning situation, some of which are intuitively very generous to the learner. The main ones are these:

• Pre-set grammar class . A class of grammars from among which to select is fixed ab initio, and the learner’s strategy can be one that only works for that class.
• Pre-set vocabulary . A finite universal vocabulary of elements V is fixed ab initio, and the learner can rely on not encountering any other elements (though the learner does not know which subset of V is used in the target language).
• Unending input . The input (the evidence presented to the learner) goes on forever—though it may contain arbitrary repetitions, and a successful learner will always reach a point where no future evidence will cause a change of guess.
• Exhaustive evidence . Ultimately every expression in the language will appear in the evidence presented to the learner.
• No noise . Every input example is a grammatical expression of the target language.
• No ordering restrictions . Any expression may appear at any point in the input data stream.
• No memory limit . The learner can remember every expression ever presented.
• No time limit . Learning must be achieved after some finite time, but no fixed bound is set in advance.
• Generative grammar target . What is ultimately learned is a generative grammar.
• No statistics . Frequency of particular expressions in the input plays no role in the learning process.

The most celebrated of the theorems Gold proved (using some reasoning remarkably similar to that of Putnam 1963) showed that a language learner could be similarly hostage to malign environments. Imagine a learner being exposed to an endless and ultimately exhaustive sequence of presented expressions from some target language—Gold calls such a sequence a ‘text’. Suppose the learner does not know in advance whether the language is infinite, or is one of the infinitely many finite languages over the vocabulary V . Gold reasons roughly thus:

• There must be some n such that an environment consisting of a sequence of n presented expressions all taken from a certain finite language L 1 (possibly with many repetitions) will cause the learner to guess the target language is L 1 . (If there is not, then we already know how to baffle the learner: the learner will be unable to learn L 1 from any text.)
• But if there is such an n , then the learner will be baffled by any infinite target language that is a superset of them all: a text consisting of n presentations of expressions from L 1 followed by n presentations of a slightly larger finite language L 2 , and so on forever (there is no largest finite language, and ex hypothesi the learner will keep trying them all).

Leaping too soon to the conclusion that the target language is infinite will be disastrous, because there will be no way to retrench: no presented examples from a finite language L k will ever conflict with the hypothesis that the target is some infinite superset of L k .

The relevance of all this to the philosophy of linguistics is that the theorem just sketched has been interpreted by many linguists, psycholinguists, and philosophers as showing that humans could not learn languages by inductive inference based on examples of language use, because all of the well-known families of languages defined by different types of generative grammar have the crucial property of allowing grammars for every finite language and for at least some infinite supersets of them. But Gold’s paper has often been over-interpreted. A few examples of the resultant mistakes follow.

It’s not about underdetermination . Gold’s negative results are sometimes wrongly taken to be an unsurprising reflection of the underdetermination of theories by finite bodies of evidence (Hauser et al. 2002 seem to make this erroneous equation on p. 1577; so do Fodor and Crowther 2002, implicitly—see Scholz and Pullum 2002, 204–206). But the failure of text-identifiability for certain classes of languages is different from underdetermination in a very important way, because there are infinite classes of infinite languages that are identifiable from text. The first chapter of Jain et al. (1999) discusses an illustrative example (basically, it is the class containing, for all n > 0, the set of all strings with length greater than n ). There are infinitely many others. For example, Shinohara (1990) showed that for any positive integer n the class of all languages generated by a context-sensitive grammar with not more than n rules is learnable from text.

It’s not about stimulus poverty . It has also sometimes been assumed that Gold is giving some kind of argument from poverty of the stimulus (there are signs of this in Cowie 1999, 194ff; Hauser et al. 2002, 1577; and Prinz 2002, 210). This is very clearly a mistake (as both Laurence and Margolis 2001 and Matthews 2007 note): in Gold’s text-learning scenario there is no stimulus poverty at all. Every expression in the language eventually turns up in the learner’s input.

It’s not all bad news . It is sometimes forgotten that Gold established a number of optimistic results as well as the pessimistic one about learning from text. Given what he called an ‘informant’ environment rather than a text environment, we see strikingly different results. An informant environment is an infinite sequence of presentations sorted into two lists, positive instances (expressions belonging to the target language) and negative instances (not in the language). Almost all major language-theoretic classes are identifiable in the limit from an informant environment (up to and including the class of all languages with a primitive recursive characteristic function, which comes close to covering any language that could conceivably be of linguistic interest), and all computably enumerable languages become learnable if texts are allowed to be sequenced in particular ways (see the results in Gold 1967 on ‘anomalous text’).

Gold did not give a necessary condition for a class to be identifiable in the limit from text, but Angluin (1980) later provided one (in a result almost but not quite obtained by Wexler and Hamburger 1973). Angluin showed that a class C is text-identifiable iff every language L in C has a finite “telltale” subset T such that if T is also proper subset of some other language in C , that other language is not a proper subset of L . This condition precludes guessing too large a language. Once all the members of the telltale subset for L have been received as input, the learner can safely make L the current conjecture. The language to be identified must be either L or (if subsequent inputs include new sentences not in L ) some larger language, but it can’t be a proper subset of L .

Johnson (2004) provides a useful review of several other misconceptions about Gold’s work; e.g., the notion that it might be the absence of semantics from the input that makes identification from text impossible (this is not the case).

4.2.2 Gold’s paradox

Some generative Essentialists see a kind of paradox in Gold’s results—a reductio on one or more of the assumptions he makes about in-principle learnability. To put it very crudely, learning generative grammars from presented grammatical examples seems to have been proved impossible, yet children do learn their first languages, which for generative Essentialists means they internalize generative psychogrammars, and it is claimed to be an empirical fact that they get almost no explicit evidence about what is not in the language (Brown and Hanlon 1970 is invariably cited to support this). Contradiction. Gold himself suggested three escape routes from the apparent paradox:

• Assume tighter limits on the pre-set grammar class. Perhaps, for example, learners have an ‘innate’ grasp of some definition of the pre-set grammar class that guarantees its learnability. (For example, identifiability in the limit from text could be guaranteed by ensuring that the class of candidate languages does not contain both (a) some infinite set of finite languages and (b) some infinite language that is the union of all of them.)
• Assume learners get systematic information about what is not in the language (perhaps indirectly, in ways not yet recognized), so that the environment is of the informant type rather than the text type.
• Assume some helpful feature is present in learning environments. The ‘no order restrictions’ assumption might be false: there could be regularities in the order of expressions in texts that can support inferences about what is ungrammatical.

All three of these paths have been subsequently explored. Path (1) appealed to generative Essentialists. Chomsky (1981) suggested an extreme restriction: that universal grammar permitted only finitely many grammars. This claim (for which Chomsky had little basis: see Pullum 1983) would immediately guarantee that not all finite languages are humanly learnable (there are infinitely many finite languages, so for most of them there would be no permissible grammar). Osherson and Weinstein (1984) even proved that under three fairly plausible assumptions about the conditions on learning, finiteness of the class of languages is necessary—that is, a class must be finite if it is to be identifiable from text. However, they also proved that this is not sufficient: there are very small finite classes of languages that are not identifiable from text, so it is logically possible for text-identification to be impossible even given only a finite number of languages (grammars). These two results show that Chomsky’s approach cannot be the whole answer.

Path (2) proposes investigation of children’s input with an eye to finding covert sources of negative evidence. Various psycholinguists have pursued this idea; see the entry on language and innateness in this encyclopedia, and (to cite one example) the results of Chouinard and Clark (2003) on hitherto unnoticed sources of negative evidence in the infant’s linguistic environment, such as parental corrections.

Path (3) suggests investigating the nature of children’s linguistic environments more generally. Making evidence available to the learner in some fixed order can certainly alter the picture quite radically (Gold proved that if some primitive-recursive generator controls the text it can in effect encode the identity of the target language so that all computably enumerable languages become identifiable from text). It is possible in principle that limitations on texts (or on learners’ uptake) might have positive rather than negative effects on learnability (see Newport 1988; Elman 1993; Rohde and Plaut 1999; and the entry on language and innateness ).

4.2.3 The claimed link to ‘rationalism’ versus ‘empiricism’

Gold’s suggested strategy of restricting the pre-set class of grammars has been interpreted by some as a defense of rationalist rather than empiricist theories of language acquisition. For example, Wexler and Culicover state:

Empiricist theory allows for a class of sensory or peripheral processing mechanisms by means of which the organism receives data. In addition, the organism possesses some set of inductive principles or learning mechanisms…Rationalist theory also assumes that a learner has sensory mechanisms and inductive principles. But rationalist theory assumes that in addition the learner possesses a rich set of principles concerning the general nature of the ability that is to be learned. (Wexler and Culicover 1980: 5)

Wexler and Culicover claim that ‘empiricist’ learning mechanisms are both weak and general: not only are they ‘not related to the learning of any particular subject matter or cognitive ability’ but they are not ‘limited to any particular species’. It is of course not surprising that empiricist learning fails if it is defined in a way that precludes drawing a distinction between the cognitive abilities of humans and fruit flies.

Equating Gold’s idea of restricting the class of grammars with the idea of a ‘rationalist’ knowledge acquisition theory, Wexler and Culicover try to draw out the consequences of Gold’s paradigm for the Essentialist linguistic theory of Chomsky (1965). They show how a very tightly restricted class of transformational grammars could be regarded as text-identifiable under extremely strong assumptions (e.g., that all languages have the same innately known deep structures).

Matthews (1984) follows Wexler and Culicover’s lead and draws a more philosophically oriented moral:

The significance of Gold’s result becomes apparent if one considers that (i) empiricists assume that there are no constraints on the class of possible languages (besides perhaps that natural languages be recursively enumerable), and (ii) the learner employs a maximally powerful learning strategy—there are no strategies that could accomplish what that assumed by Gold cannot. These two facts, given Gold’s unsolvability result for text data, effectively dispose of the empiricist claim that there exists a ‘discovery procedure’. (1989: 60)

The actual relation of Gold’s results to the empiricism/rationalism controversy seems to us rather different. Gold’s paradigm looks a lot more like a formalization of so-called ‘rationalism’. The fixed class of candidate hypotheses (grammars) corresponds to what is given by universal grammar—the innate definition of the essential properties of language. What Gold actually shows, therefore, is not “the plausibility of rationalism” but rather the inadequacy of a huge range of rationalist theories: under a wide range of different choices of universal grammar, language acquisition appears to remain impossible.

Moreover, Matthews ignores (as most linguists have) the existence of large and interesting classes of languages that are text-identifiable.

Gold’s result, like Putnam’s earlier one, does show that a certain kind of trial-and-error inductive learning is insufficient to permit learning of arbitrary environmental regularities. There has to be some kind of initial bias in the learning procedure or in the data. But ‘empiricism’, the supposed opponent of ‘rationalism’, is not to be equated with a denial of the existence of learning biases. No one doubts that humans have inductive biases. To quote Quine again, “Innate biases and dispositions are the cornerstone of behaviorism, and have been studied by behaviorists” (1972: 95–96). As Lappin and Shieber (2007) stress, there cannot be such a thing as a learning procedure (or processing mechanism) with no biases at all.

The biases posited in Emergentist theories of language acquisition are found, at least in part, in the non-linguistic social and cognitive bases of human communication. And the biases of Externalist approaches to language acquisition are to be found in the distributional and stochastic structure of the learning input and the multitude of mechanisms that process that input and their interactions. All contemporary approaches to language acquistion have acknowledged Gold’s results, but those results do not by themselves vindicate any one of our three approaches to the study of language.

Gold’s explicit equation of acquiring a language with identifying a generative grammar that exactly generates it naturally makes his work seem relevant to generative Essentialists (though even for them, his results do not provide anything like a sufficient reason for adopting the linguistic nativist position). But another key assumption, that nothing about the statistical structure of the input plays a role in the acquisition process, is being questioned by increasing numbers of Externalists, many of whom have used Bayesian modeling to show that the absence of positive evidence can function as a powerful source of (indirect) negative evidence: learning can be driven by what is not found as well as by what is (see e.g. Foraker et al. (2009)).

Most Emergentists simply reject the assumption that what is learned is a generative grammar. They see the acquisition task as a matter of learning the details of an array of constructions (roughly, meaning-bearing ways of structurally composing words or phrases) and how to use them to communicate. How such learning is accomplished needs a great deal of further study, but Gold’s paper did not show it to be impossible.

5. Language Evolution

Over the past three decades a large amount of work has been done on topics to which the term ‘language evolution’ is attached, but there are in fact four distinct such topics:

• the phylogenetic emergence of non-human communication capacities, systems, and behaviors in various animals;
• the phylogenetic emergence of uniquely human communication capacities, systems, and behaviors;
• the phylogenetic emergence, unique in humans, of the capacity (or capacities) to develop , acquire , and use language;
• the course of historical evolution through intergenerational changes in particular languages as they are acquired and used by humans.

Emergentists tend to regard any of the topics (a)–(d) as potentially relevant to the study of language evolution. Essentialists tend to focus solely on (c). Some Essentialists even deny that (a) and (b) have any relevance to the study of (c); for example:

There is nothing useful to be said about behavior or thought at the level of abstraction at which animal and human communication fall together… [H]uman language, it appears, is based on entirely different principles. This, I think, is an important point, often overlooked by those who approach language as a natural, biological phenomenon; in particular, it seems rather pointless, for these reasons, to speculate about the evolution of human language from simpler systems… (Chomsky 1968: 62)

Other generative Essentialists, like Pinker and Bloom (1990) and Pinker and Jackendoff (2005), seem open to the view that even the most elemental aspects of topic (b) can be directly relevant to the study of (c). This division among Essentialists reflects a division among their views about the role of adaptive explanations in the emergence of (b) and especially (c). For example:

We know very little about what happens when 10 10 neurons are crammed into something the size of a basketball, with further conditions imposed by the specific manner in which this system developed over time. It would be a serious error to suppose that all properties, or the interesting properties of the structures that evolved, can be ‘explained’ in terms of ‘natural selection’. (Chomsky 1975:59, quoted by Newmeyer 1998 and Jackendoff 2002)

The view expressed here that all (or even most) interesting properties of the language faculty are not adaptations conflicts with the basic explanatory strategy of evolutionary psychology found in the neo-Darwinian Essentialist views of Pinker and Bloom. Piattelli-Palmarini (1989), following Chomsky, adopts a fairly standard Bauplan critique of adaptationism. On this view the language faculty did not originate as an adaptation, but more plausibly “may have originally arisen for some purely architectural or structural reason (perhaps overall brain size, or the sheer duplication of pre-existing modules), or as a by product of the evolutionary pressures” (p. 19), i.e., it is a kind of Gouldian spandrel.

More recently, some Essentialist-leaning authors have rejected the view that no analogies and homologies between animal and human communication are relevant to the study of language. For example, in the context of commenting on Hauser et al. (2002), Tecumseh Fitch (2010) claims that “Although Language, writ large, is unique to our species (many probably most) of the mechanisms involved in language have analogues or homologues in other animals.” However, the view that the investigation of animal communication can shed light on human language is still firmly rejected by some. For example, Bickerton (2007: 512) asserts that “nothing resembling human language could have developed from prior animal call systems.”

Bickerton fronts the following simple argument for his view:

If any adaptation is unique to a species, the selective pressure that drove it must also be unique to that species; otherwise the adaptation would have appeared elsewhere, at least in rudimentary form. (2007: 514)

Thus, the mere fact that language is unique to humans is sufficient to rule out monkey and primate call systems as preadapations for language. But, contra Bickerton, a neo-Darwinian like Jackendoff (2002) appeals to the work of Dunbar (1998), Power (1998), Worden (1998) to provide a selectionist story which assumes that cooperation in hunting, defense (Pinker and Bloom 1990), and “ ‘social grooming’ or deception” are selective forces that operated on human ancestors to drive increases in expressive power that distinguishes non-human communication and human linguistic capacities and systems. Bickerton (2014), however, combines aspects of Essentialism, Emergentism, and Externalism by taking equal parts of Minimalism, primatology, and cultural evolution into a more holistic account. He specifically tailors a niche construction theory to explain the emergence of displaced, discrete symbolization in a particular kind of primate, namely human beings. He thus allows for (a) and (b) to figure in an explanation of (c). This is somewhat of a departure from his earlier positions.

Within the general Essentialist camp, language evolution has taken center stage since the inception of the Minimalist Program. An explanation of the evolution of language now became one of the main theoretical driving forces behind linguistic theory and explanation. Again, the focus seems to have stayed largely on (c). Berwick and Chomsky explicitly state:

At some time in the very recent past, apparently sometime before 80,000 years ago, if we can judge from associated symbolic proxies, individuals in a small group of hominids in East Africa underwent a minor biological change that provided the operation Merge-an operation that takes human concepts as computational atoms and yields structured expressions that, systematically interpreted by the conceptual system, provide a rich language of thought. (2016: 87)

Such theories rely heavily on the possibility of the evolution of language being explained in terms of saltation or random mutation. This postulate has come under significant scrutiny (see Steedman 2017). Saltation views, however, rely on one of the core assumptions mentioned in the quote above, i.e. that language evolved circa 100 000 years old. This central claim has recently been challenged by Everett (2017) who cites paleontological evidence from the alleged nautical abilities of Homo Erectus to dismantle this timeline. If true, this would mean that language evolved around two million years ago and random mutation need not be the only viable explanation as many in the Essentialist framework assume (see Progovac 2015 for a particular gradualist account).

While generative Essentialists debate among themselves about the plausibility of adaptive explanations for the emergence of essential features of a modular language capacity, Emergentists are perhaps best characterized as seeking broad evolutionary explanations of the features of languages (topic (c)) and communicative capacities (topics (b) and (c)) conceived in non-essentialist, non-modular ways. And as theorists who are committed to exploring non-modular views of linguistic capacities (topic (c)), the differences and similarities between (a) and (b) are potentially relevant to (c).

Primatologists like Cheney and Seyfarth, psychologists like Tomasello, anthropologists like Terrence Deacon, and linguists like Phillip Lieberman share an interest in investigating the communicative, anatomical, and cognitive characteristics of non-human animals to identify biological differences between humans, and monkeys and primates. In the following paragraph we discuss Cheney and Seyfarth (2005) as an example, but we could easily have chosen any of a number of other theorists.

Cheney and Seyfarth (2005) emphasize that non-human primates have a small, stimulus specific repertoire of vocal productions that are not “entirely involuntary,” and this contrasts with their “almost openended ability to learn novel sound-meaning pairs” (p. 149). They also emphasize that vocalizations in monkeys and apes are used to communicate information about the vocalizer, not to provide information intended to “rectify false beliefs in others or instruct others” (p. 150). Non-human primate communication consists in the mainly involuntary broadcasting of the vocalizer’s current affective state. Moreover, although Cheney and Seyfarth recognize that the vervet monkey’s celebrated call system (Cheney and Seyfarth 1990) is “functionally referential” in context, their calls have no explicit meaning since they lack “any propositional structure”. From this they conclude:

The communication of non-human animals lacks three features that are abundantly present in the utterances of young children: a rudimentary ability to attribute mental states different from their own to others, the ability to generate new words, and lexical syntax. (2005: 151)

By ‘lexical syntax’ Cheney and Seyfarth mean a kind of semantic compositionality of characteristic vocalizations. If a vocalization (call) were to have lexical syntax, the semantic significance of the whole would depend on the relation of the structure of parts of the call to the structure of what they signify. The absence of ‘lexical syntax’ in call systems suggests that it is illegitimate to think of them as having anything like semantic structure at all.

Despite the rudimentary character of animal communication systems when compared with human languages, Cheney and Seyfarth argue that monkeys and apes exhibit at least five characteristics that are pre-adaptations for human communication:

• their vocalizations are representational;
• they have competitive/cooperative relations in which alliances, friendships, and rivalries that “create selective pressures for the kind of complex, abstract conceptual abilities that are likely to have proceeded the earlier linguistic communication”;
• because of (ii), their representations of social relations between individuals and themselves are hierarchally structured;
• certain monkeys, e.g. baboons, have open-ended, rule-governed systems of social knowledge;
• their knowledge is propositional.

It is, of course, controversial to claim that monkeys have rule-governed propositional social knowledge systems as claimed in (iv) and (v). For instance, Tomasello’s (2008) ‘Cooperative Communication’ approach makes a case for primate intentional systems not based on their vocalizations but on their gestural systems. Therein he claims that “great ape gestural communication shares with human linguistic communication foundational aspects of its manner of functioning, namely, the intentional and flexible use of learned communicative signals” (2008: 21).

But Emergentists, Externalists, and Essentialists could all, in principle, agree that there are both unique characteristics of human communicative capacities and characteristics of such capacities that are shared with non-humans. For example, by the age of one, human infants can use direction of gaze and focus of attention to infer the referent of a speaker’s utterance (Baldwin and Moses 1994). By contrast, this sort of social referencing capacity in monkeys and apes is rudimentary. This suggests that a major component of humans’ capacity to infer a specific referent is lacking in non-humans.

Disagreements between the approaches might be due to the perceived significance of non-human communicative capacities and their relation to uniquely human ones.

We mentioned earlier that both early 20th-century linguistics monographs and contemporary introductory textbooks include discussions of historical linguistics, i.e., that branch that studies the history and prehistory of changes in particular languages, how they are related to each other, and how and why they change. Again, this topic is distinct from the emergence of language in hominoid species and concerns mostly the linguistic changes that have occurred over a much shorter period within languages.

The last decade has seen two kinds of innovations related to studying changes in particular languages. One, which we will call ‘linguistic phylogeny’, concerns the application of stochastic phylogenetic methods to investigate prehistoric population and language dispersion (Gray and Jordan 2000, Gray 2005, Atkinson and Gray 2006, Gray et al. 2009). These methods answer questions about how members of a family of languages are related to each other and dispersed throughout a geographic area. The second, which we will call the effects of transmission, examines how interpreted artificial languages (sets of signifier/signified pairs) change under a range of transmission conditions (Kirby et al. 2008, Kirby 2001, Hurford 2000), thus providing evidence about how the process of transmission affects the characteristics, especially the structure, of the transmitted interpreted system.

5.2.1 Linguistic phylogeny

Russell Gray and his colleagues have taken powerful phylogenetic methods that were developed by biologists to investigate molecular evolution, and applied them to linguistic data in order to answer questions about the evolution of language families. For example, Gray and Jordan (2000) used a parsimony analysis of a large language data set to adjudicate between competing hypotheses about the speed of the spread of Austronesian languages through the Pacific. More recently, Greenhill et al. (2010) used a NeighbourNet analysis to evaluate the relative rates of change in the typological and lexical features of Austronesian and Indo-European. These results bear on hypotheses about the relative stability of language types over lexical features of those languages, and how far back in time that stability extends. If there were highly conserved typological and lexical features, then it might be possible to identify relationships between languages that date beyond the 8000 (plus or minus 2000) year limit that is imposed by lexical instability.

5.2.2 Effects of transmission

The computational and laboratory experiments of Kirby and his collaborators have shown that under certain conditions of iterated learning, any given set of signifier/signified pairs in which the mapping is initially arbitrary will change to exhibit a very general kind of compositional structure. Iterated learning has been studied in both computational and laboratory experiments by means of diffusion chains, i.e., sequences of learners. A primary characteristic of such sequences of transmission is that what is transmitted from learner to learner will change in an iterated learning environment, in a way that depends on the conditions of transmission.

The children’s game called ‘Telephone’ in the USA (‘Chinese Whispers’ in the UK), provides an example of diffusion chains under which what is transmitted is not stable. In a diffusion chain learning situation what a chain member has actually learned from an earlier member of the chain is presented as the input to the next learner, and what that learner has actually learned provides the input to the following learner. In cases where the initial learning task is very simple: i.e., where what is transmitted is both simple, completely transmitted, and the transmission channel is not noisy, what is transmitted is stable over iterated transmissions even in cases when the participants are young children and chimpanzees (Horner et al. 2006). That is, there is little change in what is transmitted over iterated transmissions. However, in cases where what is transmitted is only partially presented, very complex, or the channel is noisy, then there is a decrease in the fidelity of what is transmitted across iterations just like there is in the children’s game of Telephone.

What Kirby and colleagues show is that when the initial input to a diffusion chain is a reasonably complex set of arbitrary signal/signifier pairs, e.g. one in which 27 complex signals of 6 letters are randomly assigned to 27 objects varying on dimensions of color, kind of motion, and shape, what is transmitted becomes more and more compositional over iterated transmission. Here, ‘compositional’ is being used to refer to the high degree to which sub-strings of the signals come to be systematically paired with specific phenomenal sub-features of what is signified. The transmission conditions in these experiments were free of noise, and for each iteration of the learning task only half of the possible 27 signifier/signified pairs were presented to participants. Under this kind of transmission bottleneck a high degree of sign/signified structure emerged.

A plausible interpretation of these results is that the developing structure of the collection of signs is a consequence of the repeated forced inference by participants from 14 signs and signifieds in the training set to the entire set of 27 pairs. A moral could be that iterated forced prediction of the sign/signified pairs in the entire set, on the basis of exposure to only about half of them, induced the development of a systematic, compositional structure over the course of transmission. It is reasonable to conjecture that this resulting structure reflects effects of human memory, not a domain-specific language module—although further work would be required to rule out many other competing hypotheses.

Thus Kirby and his colleagues focus on something very different from the prerequisites for language emergence. Linguistic nativists have been interested in how primates like us could have become capable of acquiring systems with the structural properties of natural languages. Kirby and his colleagues (while not denying that human cognitive evolution is of interest) are studying how languages evolve to be capable of being acquired by primates like us .

5.2.3 Trends in the Philosophy of Language Evolution

Lastly, language evolution has amassed a great deal of interdisciplinary work in recent times. This has allowed philosophers to directly contribute to this emerging field. The trends in the philosophical work have only loosely followed the Externalist, Emergentist and Essentialist divisions we advocate here. Most philosophical work has largely been focused on Emergentist conceptions within the evolution of linguistic meaning specifically.

Bar-On (2013) distinguishes between Gricean and Post-Gricean approaches to the evolution of language. The former requires an attribution of Gricean speaker meaning to our languageless ancestors which in turn seems to assume intentional actions govern by rationality (‘nonnatural meaning’). This task is as fraught as explaining the evolution of language itself. She thus proposes the latter, specifically a Post-Gricean (Orrigi and Sperber 2000) approach which takes expressive communication (found widely in non-human animal species) as a basis for the emergence of linguistic meaning between signalers and receivers. She states:

Expressive communication, I will argue, exhibits features that foreshadow significant aspects of linguistic communication. In its domain, we can identify legitimate natural precursors of meaningful linguistic communication. (For present purposes, by ‘legitimate natural precursors’, I mean behavioral interactions that at least: a. can be found in the natural world; b. go beyond Tomasello’s mere ‘communicative displays’; c. do not depend on crediting the relevant creatures with language-like propositional thought or post-Gricean communicative intentions, and; d. exhibit features that foreshadow important semantic and pragmatic features of linguistic communication so in that sense are proto-semantic and proto-pragmatic.) (2013: 354)

Recent work in Evolutionary Game Theory has also lent credence to the emergence of signaling systems involving non-intentional states. Taking Lewis (1969) as a spring-board, Skyrms (2010) investigates the structure of signaling behavior beyond the existence of mutual conventions. His framework starts from the most basic non-trivial cases and gradually introduces complexity (such as deception and the introduction of new signals etc.). Skyrms’ account views propositional or semantic content as a special case of informational content thereby reintroducing information theory as a tool to philosophers of language and linguistics interested in the emergence of linguistic communication and/or semantic meaning.

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How to cite this entry . Preview the PDF version of this entry at the Friends of the SEP Society . Look up topics and thinkers related to this entry at the Internet Philosophy Ontology Project (InPhO). Enhanced bibliography for this entry at PhilPapers , with links to its database.

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analysis | assertion | compositionality | defaults in semantics and pragmatics | descriptions | empiricism: logical | idiolects | innate/acquired distinction | innateness: and language | language of thought hypothesis | linguistics: computational | logic: intensional | mental representation | pragmatics | propositional attitude reports | reference | relativism | rigid designators

Acknowledgments

The authors are very grateful to the two SEP referees, Tom Wasow and William Starr, who provided careful reviews of our drafts; to Bonnie Webber and Zoltan Galsi for insightful comments and advice; and to Dean Mellow for some helpful corrections. BCS was the lead author of this article throughout the lengthy period of its preparation, and worked on it in collaboration with FJP and GKP until the post-refereeing revision was submitted at the end of April 2011. She died two weeks later, on May 14. FJP and GKP oversaw the few final corrections that were made when the HTML version was first published in September 2011.

Copyright © 2024 by Barbara C. Scholz Francis Jeffry Pelletier < francisp @ ualberta . ca > Geoffrey K. Pullum < pullum @ gmail . com > Ryan Nefdt < ryan . nefdt @ uct . ac . za >

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11.10: Theories of Language Development

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• Paris, Ricardo, Raymond, & Johnson
• College of the Canyons via College of the Canyons

Humans, especially children, have an amazing ability to learn language. Within the first year of life, children will have learned many of the necessary concepts to have functional language, although it will still take years for their capabilities to develop fully. As we just explained, some people learn two or more languages fluently and are bilingual or multilingual. Here is a recap of the theorists and theories that have been proposed to explain the development of language, and related brain structures, in children.

Skinner: Operant Conditioning

B. F. Skinner believed that children learn language through operant conditioning ; in other words, children receive “rewards” for using language in a functional manner. For example, a child learns to say the word “drink” when she is thirsty; she receives something to drink, which reinforces her use of the word for getting a drink, and thus she will continue to do so. This follows the four-term contingency that Skinner believed was the basis of language development—motivating operations, discriminative stimuli, response, and reinforcing stimuli. Skinner also suggested that children learn language through imitation of others, prompting, and shaping.

Chomsky: Language Acquisition Device

Noam Chomsky’s work discusses the biological basis for language and claims that children have innate abilities to learn language. Chomsky terms this innate ability the “ language acquisition device .” He believes children instinctively learn language without any formal instruction. He also believes children have a natural need to use language, and that in the absence of formal language children will develop a system of communication to meet their needs. He has observed that all children make the same type of language errors, regardless of the language they are taught. Chomsky also believes in the existence of a “universal grammar,” which posits that there are certain grammatical rules all human languages share. However, his research does not identify areas of the brain or a genetic basis that enables humans’ innate ability for language.

Piaget: Assimilation and Accommodation

Jean Piaget’s theory of language development suggests that children use both assimilation and accommodation to learn language. Assimilation is the process of changing one’s environment to place information into an already-existing schema (or idea). Accommodation is the process of changing one’s schema to adapt to the new environment. Piaget believed children need to first develop mentally before language acquisition can occur. According to him, children first create mental structures within the mind (schemas) and from these schemas, language development happens.

Vygotsky: Zone of Proximal Development

Lev Vygotsky’s theory of language development focused on social learning and the zone of proximal development (ZPD) . The ZPD is a level of development obtained when children engage in social interactions with others; it is the distance between a child’s potential to learn and the actual learning that takes place. Vygotsky’s theory also demonstrated that Piaget underestimated the importance of social interactions in the development of language. Piaget’s and Vygotsky’s theories are often compared with each other, and both have been used successfully in the field of education.