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Definition of research

 (Entry 1 of 2)

Definition of research  (Entry 2 of 2)

transitive verb

intransitive verb

• disquisition
• examination
• exploration
• inquisition
• investigation
• delve (into)
• inquire (into)
• investigate
• look (into)

Examples of research in a Sentence

These examples are programmatically compiled from various online sources to illustrate current usage of the word 'research.' Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Send us feedback about these examples.

Word History

Middle French recerche , from recercher to go about seeking, from Old French recerchier , from re- + cerchier, sercher to search — more at search

1577, in the meaning defined at sense 3

1588, in the meaning defined at transitive sense 1

Phrases Containing research

• marketing research
• market research
• operations research
• oppo research

research and development

• research park
• translational research

Dictionary Entries Near research

Cite this entry.

“Research.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/research. Accessed 4 Jun. 2024.

Kids Definition

Kids definition of research.

Kids Definition of research  (Entry 2 of 2)

More from Merriam-Webster on research

Nglish: Translation of research for Spanish Speakers

Britannica English: Translation of research for Arabic Speakers

Britannica.com: Encyclopedia article about research

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Research Basics

• What Is Research?
• Types of Research
• Secondary Research | Literature Review
• Developing Your Topic
• Primary vs. Secondary Sources
• Evaluating Sources
• Responsible Conduct of Research
• More Information

A good working definition of research might be:

Research is the deliberate, purposeful, and systematic gathering of data, information, facts, and/or opinions for the advancement of personal, societal, or overall human knowledge.

Based on this definition, we all do research all the time. Most of this research is casual research. Asking friends what they think of different restaurants, looking up reviews of various products online, learning more about celebrities; these are all research.

Formal research includes the type of research most people think of when they hear the term “research”: scientists in white coats working in a fully equipped laboratory. But formal research is a much broader category that just this. Most people will never do laboratory research after graduating from college, but almost everybody will have to do some sort of formal research at some point in their careers.

So What Do We Mean By “Formal Research?”

Casual research is inward facing: it’s done to satisfy our own curiosity or meet our own needs, whether that’s choosing a reliable car or figuring out what to watch on TV. Formal research is outward facing. While it may satisfy our own curiosity, it’s primarily intended to be shared in order to achieve some purpose. That purpose could be anything: finding a cure for cancer, securing funding for a new business, improving some process at your workplace, proving the latest theory in quantum physics, or even just getting a good grade in your Humanities 200 class.

What sets formal research apart from casual research is the documentation of where you gathered your information from. This is done in the form of “citations” and “bibliographies.” Citing sources is covered in the section "Citing Your Sources."

Formal research also follows certain common patterns depending on what the research is trying to show or prove. These are covered in the section “Types of Research.”

• Next: Types of Research >>
• Last Updated: May 21, 2024 9:38 AM
• URL: https://guides.library.iit.edu/research_basics

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Home Market Research

What is Research: Definition, Methods, Types & Examples

The search for knowledge is closely linked to the object of study; that is, to the reconstruction of the facts that will provide an explanation to an observed event and that at first sight can be considered as a problem. It is very human to seek answers and satisfy our curiosity. Let’s talk about research.

Content Index

What is Research?

What are the characteristics of research.

• Comparative analysis chart

Qualitative methods

Quantitative methods, 8 tips for conducting accurate research.

Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, “research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.”

Inductive methods analyze an observed event, while deductive methods verify the observed event. Inductive approaches are associated with qualitative research , and deductive methods are more commonly associated with quantitative analysis .

Research is conducted with a purpose to:

• Identify potential and new customers
• Understand existing customers
• Set pragmatic goals
• Develop productive market strategies
• Address business challenges
• Put together a business expansion plan
• Identify new business opportunities
• Good research follows a systematic approach to capture accurate data. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.
• The analysis is based on logical reasoning and involves both inductive and deductive methods.
• Real-time data and knowledge is derived from actual observations in natural settings.
• There is an in-depth analysis of all data collected so that there are no anomalies associated with it.
• It creates a path for generating new questions. Existing data helps create more research opportunities.
• It is analytical and uses all the available data so that there is no ambiguity in inference.
• Accuracy is one of the most critical aspects of research. The information must be accurate and correct. For example, laboratories provide a controlled environment to collect data. Accuracy is measured in the instruments used, the calibrations of instruments or tools, and the experiment’s final result.

What is the purpose of research?

There are three main purposes:

• Exploratory: As the name suggests, researchers conduct exploratory studies to explore a group of questions. The answers and analytics may not offer a conclusion to the perceived problem. It is undertaken to handle new problem areas that haven’t been explored before. This exploratory data analysis process lays the foundation for more conclusive data collection and analysis.

LEARN ABOUT: Descriptive Analysis

• Descriptive: It focuses on expanding knowledge on current issues through a process of data collection. Descriptive research describe the behavior of a sample population. Only one variable is required to conduct the study. The three primary purposes of descriptive studies are describing, explaining, and validating the findings. For example, a study conducted to know if top-level management leaders in the 21st century possess the moral right to receive a considerable sum of money from the company profit.

LEARN ABOUT: Best Data Collection Tools

• Explanatory: Causal research or explanatory research is conducted to understand the impact of specific changes in existing standard procedures. Running experiments is the most popular form. For example, a study that is conducted to understand the effect of rebranding on customer loyalty.

Here is a comparative analysis chart for a better understanding:

It begins by asking the right questions and choosing an appropriate method to investigate the problem. After collecting answers to your questions, you can analyze the findings or observations to draw reasonable conclusions.

When it comes to customers and market studies, the more thorough your questions, the better the analysis. You get essential insights into brand perception and product needs by thoroughly collecting customer data through surveys and questionnaires . You can use this data to make smart decisions about your marketing strategies to position your business effectively.

To make sense of your study and get insights faster, it helps to use a research repository as a single source of truth in your organization and manage your research data in one centralized data repository .

Types of research methods and Examples

Research methods are broadly classified as Qualitative and Quantitative .

Both methods have distinctive properties and data collection methods .

Qualitative research is a method that collects data using conversational methods, usually open-ended questions . The responses collected are essentially non-numerical. This method helps a researcher understand what participants think and why they think in a particular way.

Types of qualitative methods include:

• One-to-one Interview
• Focus Groups
• Ethnographic studies
• Text Analysis

Quantitative methods deal with numbers and measurable forms . It uses a systematic way of investigating events or data. It answers questions to justify relationships with measurable variables to either explain, predict, or control a phenomenon.

Types of quantitative methods include:

• Survey research
• Descriptive research
• Correlational research

LEARN MORE: Descriptive Research vs Correlational Research

Remember, it is only valuable and useful when it is valid, accurate, and reliable. Incorrect results can lead to customer churn and a decrease in sales.

It is essential to ensure that your data is:

• Valid – founded, logical, rigorous, and impartial.
• Accurate – free of errors and including required details.
• Reliable – other people who investigate in the same way can produce similar results.
• Timely – current and collected within an appropriate time frame.
• Complete – includes all the data you need to support your business decisions.

Gather insights

• Identify the main trends and issues, opportunities, and problems you observe. Write a sentence describing each one.
• Keep track of the frequency with which each of the main findings appears.
• Make a list of your findings from the most common to the least common.
• Evaluate a list of the strengths, weaknesses, opportunities, and threats identified in a SWOT analysis .
• Prepare conclusions and recommendations about your study.
• Act on your strategies
• Look for gaps in the information, and consider doing additional inquiry if necessary
• Plan to review the results and consider efficient methods to analyze and interpret results.

Review your goals before making any conclusions about your study. Remember how the process you have completed and the data you have gathered help answer your questions. Ask yourself if what your analysis revealed facilitates the identification of your conclusions and recommendations.

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• Cambridge Dictionary +Plus

Meaning of research – Learner’s Dictionary

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• There is the potential for some really interesting research.
• She has done research into how children acquire language .
• The appeal raised over £2 million for AIDS research.
• This report echoes some of the earlier research I've read .
• The government has committed thousands of pounds to the research.

(Definition of research from the Cambridge Learner's Dictionary © Cambridge University Press)

Translations of research

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Word of the Day

the ability to move freely or be easily moved

Keeping up appearances (Talking about how things seem)

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Definition of 'research'

research in British English

Research in american english, examples of 'research' in a sentence research, cobuild collocations research, trends of research.

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Browse alphabetically research

• resealable bag
• research a book
• research a product
• research a source
• All ENGLISH words that begin with 'R'

Related terms of research

• do research
• aid research
• cite research
• fund research
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Definition of research noun from the Oxford Advanced American Dictionary

• formulate/advance a theory/hypothesis
• build/construct/create/develop a simple/theoretical/mathematical model
• develop/establish/provide/use a theoretical/conceptual framework/an algorithm
• advance/argue/develop the thesis that…
• explore an idea/a concept/a hypothesis
• make a prediction/an inference
• base a prediction/your calculations on something
• investigate/evaluate/accept/challenge/reject a theory/hypothesis/model
• design an experiment/a questionnaire/a study/a test
• do research/an experiment/an analysis
• make observations/calculations
• take/record measurements
• carry out/conduct/perform an experiment/a test/a longitudinal study/observations/clinical trials
• run an experiment/a simulation/clinical trials
• repeat an experiment/a test/an analysis
• replicate a study/the results/the findings
• observe/study/examine/investigate/assess a pattern/a process/a behavior
• fund/support the research/project/study
• seek/provide/get/secure funding for research
• collect/gather/extract data/information
• yield data/evidence/similar findings/the same results
• analyze/examine the data/soil samples/a specimen
• consider/compare/interpret the results/findings
• fit the data/model
• confirm/support/verify a prediction/a hypothesis/the results/the findings
• prove a conjecture/hypothesis/theorem
• draw/make/reach the same conclusions
• read/review the records/literature
• describe/report an experiment/a study
• present/publish/summarize the results/findings
• present/publish/read/review/cite a paper in a scientific journal

Take your English to the next level

The Oxford Learner’s Thesaurus explains the difference between groups of similar words. Try it for free as part of the Oxford Advanced Learner’s Dictionary app

Research is an original and systematic investigation undertaken to increase existing knowledge and understanding of the unknown to establish facts and principles.

Let’s understand research:

What is Research?

Research is a voyage of discovery of new knowledge. It comprises creating ideas and generating new knowledge that leads to new and improved insights and the development of new materials, devices, products, and processes.

It should have the potential to produce sufficiently relevant results to increase and synthesize existing knowledge or correct and integrate previous knowledge.

Good reflective research produces theories and hypotheses and benefits any intellectual attempt to analyze facts and phenomena.

Where did the word Research Come from?

The word ‘research’ perhaps originates from the old French word “recerchier” which meant to ‘ search again.’ It implicitly assumes that the earlier search was not exhaustive and complete; hence, a repeated search is called for.

In practice, ‘research’ refers to a scientific process of generating an unexplored horizon of knowledge, aiming at discovering or establishing facts, solving a problem, and reaching a decision. Keeping the above points in view, we arrive at the following definition of research:

Research Definition

Research is a scientific approach to answering a research question, solving a research problem, or generating new knowledge through a systematic and orderly collection, organization, and analysis of data to make research findings useful in decision-making.

When do we call research scientific? Any research endeavor is said to be scientific if

• It is based on empirical and measurable evidence subject to specific principles of reasoning;
• It consists of systematic observations, measurement, and experimentation;
• It relies on the application of scientific methods and harnessing of curiosity;
• It provides scientific information and theories for the explanation of nature;
• It makes practical applications possible, and
• It ensures adequate analysis of data employing rigorous statistical techniques.

The chief characteristic that distinguishes the scientific method from other methods of acquiring knowledge is that scientists seek to let reality speak for itself, supporting a theory when a theory’s predictions are confirmed and challenging a theory when its predictions prove false.

Scientific research has multidimensional functions, characteristics, and objectives.

Keeping these issues in view, we assert that research in any field or discipline:

• Attempts to solve a research problem;
• Involves gathering new data from primary or first-hand sources or using existing data for a new purpose;
• is based upon observable experiences or empirical evidence;
• Demands accurate observation and description;
• Employs carefully designed procedures and rigorous analysis;
• attempts to find an objective, unbiased solution to the problem and takes great pains to validate the methods employed;
• is a deliberate and unhurried activity that is directional but often refines the problem or questions as the research progresses.

Characteristics of Research

Keeping this in mind that research in any field of inquiry is undertaken to provide information to support decision-making in its respective area, we summarize some desirable characteristics of research:

• The research should focus on priority problems.
• The research should be systematic. It emphasizes that a researcher should employ a structured procedure.
• The research should be logical. Without manipulating ideas logically, the scientific researcher cannot make much progress in any investigation.
• The research should be reductive. This means that one researcher’s findings should be made available to other researchers to prevent them from repeating the same research.
• The research should be replicable. This asserts that there should be scope to confirm previous research findings in a new environment and different settings with a new group of subjects or at a different point in time.
• The research should be generative. This is one of the valuable characteristics of research because answering one question leads to generating many other new questions.
• The research should be action-oriented. In other words, it should be aimed at solving to implement its findings.
• The research should follow an integrated multidisciplinary approach, i.e., research approaches from more than one discipline are needed.
• The research should be participatory, involving all parties concerned (from policymakers down to community members) at all stages of the study.
• The research must be relatively simple, timely, and time-bound, employing a comparatively simple design.
• The research must be as much cost-effective as possible.
• The research results should be presented in formats most useful for administrators, decision-makers, business managers, or community members.

3 Basic Operations of Research

Scientific research in any field of inquiry involves three basic operations:

• Data collection;
• Data analysis;
• Report writing .

• Data collection refers to observing, measuring, and recording data or information.
• Data analysis, on the other hand, refers to arranging and organizing the collected data so that we may be able to find out what their significance is and generalize about them.
• Report writing is the ultimate step of the study . Its purpose is to convey the information contained in it to the readers or audience.

If you note down, for example, the reading habit of newspapers of a group of residents in a community, that would be your data collection.

If you then divide these residents into three categories, ‘regular,’ ‘occasional,’ and ‘never,’ you have performed a simple data analysis. Your findings may now be presented in a report form.

A reader of your report knows what percentage of the community people never read any newspaper and so on.

Here are some examples that demonstrate what research is:

• A farmer is planting two varieties of jute side by side to compare yields;
• A sociologist examines the causes and consequences of divorce;
• An economist is looking at the interdependence of inflation and foreign direct investment;
• A physician is experimenting with the effects of multiple uses of disposable insulin syringes in a hospital;
• A business enterprise is examining the effects of advertisement of their products on the volume of sales;
• An economist is doing a cost-benefit analysis of reducing the sales tax on essential commodities;
• The Bangladesh Bank is closely observing and monitoring the performance of nationalized and private banks;
• Based on some prior information, Bank Management plans to open new counters for female customers.
• Supermarket Management is assessing the satisfaction level of the customers with their products.

The above examples are all researching whether the instrument is an electronic microscope, hospital records, a microcomputer, a questionnaire, or a checklist.

Research Motivation – What makes one motivated to do research?

A person may be motivated to undertake research activities because

• He might have genuine interest and curiosity in the existing body of knowledge and understanding of the problem;
• He is looking for answers to questions that have remained unanswered so far and trying to unfold the truth;
• The existing tools and techniques are accessible to him, and others may need modification and change to suit the current needs.

One might research ensuring.

• Better livelihood;
• Better career development;
• Higher position, prestige, and dignity in society;
• Academic achievement leading to higher degrees;
• Self-gratification.

At the individual level, the results of the research are used by many:

• A villager is drinking water from an arsenic-free tube well;
• A rural woman is giving more green vegetables to her child than before;
• A cigarette smoker is actively considering quitting smoking;
• An old man is jogging for cardiovascular fitness;
• A sociologist is using newly suggested tools and techniques in poverty measurement.

The above activities are all outcomes of the research.

All involved in the above processes will benefit from the research results. There is hardly any action in everyday life that does not depend upon previous research.

Research in any field of inquiry provides us with the knowledge and skills to solve problems and meet the challenges of a fast-paced decision-making environment.

9 Qualities of Research

Good research generates dependable data. It is conducted by professionals and can be used reliably for decision-making. It is thus of crucial importance that research should be made acceptable to the audience for which research should possess some desirable qualities in terms of.

9 qualities of research are;

Purpose clearly defined

Research process detailed, research design planner, ethical issues considered, limitations revealed, adequate analysis ensured, findings unambiguously presented, conclusions and recommendations justified..

We enumerate below a few qualities that good research should possess.

Good research must have its purposes clearly and unambiguously defined.

The problem involved or the decision to be made should be sharply delineated as clearly as possible to demonstrate the credibility of the research.

The research procedures should be described in sufficient detail to permit other researchers to repeat the research later.

Failure to do so makes it difficult or impossible to estimate the validity and reliability of the results. This weakens the confidence of the readers.

Any recommendations from such research justifiably get little attention from the policymakers and implementation.

The procedural design of the research should be carefully planned to yield results that are as objective as possible.

In doing so, care must be taken so that the sample’s representativeness is ensured, relevant literature has been thoroughly searched, experimental controls, whenever necessary, have been followed, and the personal bias in selecting and recording data has been minimized.

A research design should always safeguard against causing mental and physical harm not only to the participants but also those who belong to their organizations.

Careful consideration must also be given to research situations when there is a possibility for exploitation, invasion of privacy, and loss of dignity of all those involved in the study.

The researcher should report with complete honesty and frankness any flaws in procedural design; he followed and provided estimates of their effects on the findings.

This enhances the readers’ confidence and makes the report acceptable to the audience. One can legitimately question the value of research where no limitations are reported.

Adequate analysis reveals the significance of the data and helps the researcher to check the reliability and validity of his estimates.

Data should, therefore, be analyzed with proper statistical rigor to assist the researcher in reaching firm conclusions.

When statistical methods have been employed, the probability of error should be estimated, and criteria of statistical significance applied.

The presentation of the results should be comprehensive, easily understood by the readers, and organized so that the readers can readily locate the critical and central findings.

Proper research always specifies the conditions under which the research conclusions seem valid.

Therefore, it is important that any conclusions drawn and recommendations made should be solely based on the findings of the study.

No inferences or generalizations should be made beyond the data. If this were not followed, the objectivity of the research would tend to decrease, resulting in confidence in the findings.

The researcher’s experiences were reflected.

The research report should contain information about the qualifications of the researchers .

If the researcher is experienced, has a good reputation in research, and is a person of integrity, his report is likely to be highly valued. The policymakers feel confident in implementing the recommendations made in such reports.

4 Goals of Research

The primary goal or purpose of research in any field of inquiry; is to add to what is known about the phenomenon under investigation by applying scientific methods. Though each research has its own specific goals, we may enumerate the following 4 broad goals of scientific research:

Exploration and Explorative Research

Description and descriptive research, causal explanation and causal research, prediction and predictive research.

The link between the 4 goals of research and the questions raised in reaching these goals.

Let’s try to understand the 4 goals of the research.

Exploration is finding out about some previously unexamined phenomenon. In other words, an explorative study structures and identifies new problems.

The explorative study aims to gain familiarity with a phenomenon or gain new insights into it.

Exploration is particularly useful when researchers lack a clear idea of the problems they meet during their study.

Through exploration, researchers attempt to

• Develop concepts more clearly;
• Establish priorities among several alternatives;
• Develop operational definitions of variables;
• Formulate research hypotheses and sharpen research objectives;
• Improve the methodology and modify (if needed) the research design .

Exploration is achieved through what we call exploratory research.

The end of an explorative study comes when the researchers are convinced that they have established the major dimensions of the research task.

Many research activities consist of gathering information on some topic of interest. The description refers to these data-based information-gathering activities. Descriptive studies portray precisely the characteristics of a particular individual, situation, or group.

Here, we attempt to describe situations and events through studies, which we refer to as descriptive research.

Such research is undertaken when much is known about the problem under investigation.

Descriptive studies try to discover answers to the questions of who, what, when, where, and sometimes how.

Such research studies may involve the collection of data and the creation of distribution of the number of times the researcher observes a single event or characteristic, known as a research variable.

A descriptive study may also involve the interaction of two or more variables and attempts to observe if there is any relationship between the variables under investigation .

Research that examines such a relationship is sometimes called a correlational study. It is correlational because it attempts to relate (i.e., co-relate) two or more variables.

A descriptive study may be feasible to answer the questions of the following types:

• What are the characteristics of the people who are involved in city crime? Are they young? Middle-aged? Poor? Muslim? Educated?
• Who are the potential buyers of the new product? Men or women? Urban people or rural people?
• Are rural women more likely to marry earlier than their urban counterparts?
• Does previous experience help an employee to get a higher initial salary?

Although the data description in descriptive research is factual, accurate, and systematic, the research cannot describe what caused a situation.

Thus, descriptive research cannot be used to create a causal relationship where one variable affects another.

In other words, descriptive research can be said to have a low requirement for internal validity. In sum, descriptive research deals with everything that can be counted and studied.

But there are always restrictions on that. All research must impact the lives of the people around us.

For example, finding the most frequent disease that affects the people of a community falls under descriptive research.

But the research readers will have the hunch to know why this has happened and what to do to prevent that disease so that more people will live healthy lives.

It dictates that we need a causal explanation of the situation under reference and a causal study vis-a-vis causal research .

Explanation reveals why and how something happens.

An explanatory study goes beyond description and attempts to establish a cause-and-effect relationship between variables. It explains the reason for the phenomenon that the descriptive study observed.

Thus, if a researcher finds that communities with larger family sizes have higher child deaths or that smoking correlates with lung cancer, he is performing a descriptive study.

If he explains why it is so and tries to establish a cause-and-effect relationship, he is performing explanatory or causal research . The researcher uses theories or at-least hypotheses to account for the factors that caused a certain phenomenon.

Look at the following examples that fit causal studies:

• Why are people involved in crime? Can we explain this as a consequence of the present job market crisis or lack of parental care?
• Will the buyers be motivated to purchase the new product in a new container ? Can an attractive advertisement motivate them to buy a new product?
• Why has the share market shown the steepest-ever fall in stock prices? Is it because of the IMF’s warnings and prescriptions on the commercial banks’ exposure to the stock market or because of an abundant increase in the supply of new shares?

Prediction seeks to answer when and in what situations will occur if we can provide a plausible explanation for the event in question.

However, the precise nature of the relationship between explanation and prediction has been a subject of debate.

One view is that explanation and prediction are the same phenomena, except that prediction precedes the event while the explanation takes place after the event has occurred.

Another view is that explanation and prediction are fundamentally different processes.

We need not be concerned with this debate here but can simply state that in addition to being able to explain an event after it has occurred, we would also be able to predict when it will occur.

Research Approaches

There are two main approaches to doing research.

The first is the basic approach, which mostly pertains to academic research. Many people view this as pure research or fundamental research.

The research implemented through the second approach is variously known as applied research, action research, operations research, or contract research.

Also, the third category of research, evaluative research, is important in many applications. All these approaches have different purposes influencing the nature of the respective research.

Lastly, precautions in research are required for thorough research.

So, 4 research approaches are;

• Basic Research .
• Applied Research .
• Evaluative Research .
• Precautions in Research.

Areas of Research

The most important fields or areas of research, among others, are;

• Social Research .
• Health Research .
• Population Research .
• Business Research .
• Marketing Research .
• Agricultural Research .
• Biomedical Research.
• Clinical Research .
• Outcomes Research.
• Internet Research.
• Archival Research.
• Empirical Research.
• Legal Research .
• Education Research .
• Engineering Research .
• Historical Research.

Check out our article describing all 16 areas of research .

Precautions in Research

Whether a researcher is doing applied or basic research or research of any other form, he or she must take necessary precautions to ensure that the research he or she is doing is relevant, timely, efficient, accurate, and ethical .

The research is considered relevant if it anticipates the kinds of information that decision-makers, scientists, or policymakers will require.

Timely research is completed in time to influence decisions.

• Research is efficient when it is of the best quality for the minimum expenditure and the study is appropriate to the research context.
• Research is considered accurate or valid when the interpretation can account for both consistencies and inconsistencies in the data.
• Research is ethical when it can promote trust, exercise care, ensure standards, and protect the rights of the participants in the research process.

What is the definition of research?

What are the characteristics of good research, what are the three basic operations involved in scientific research, what are the four broad goals of scientific research, what distinguishes the scientific method from other methods of acquiring knowledge, what is the origin of the word ‘research’, how is “research methodology” defined, how does research methodology ensure the appropriateness of a research method.

After discussing the research definition and knowing the characteristics, goals, and approaches, it’s time to delve into the research fundamentals. For a comprehensive understanding, refer to our detailed research and methodology concepts guide .

Research should be relevant, timely, efficient, accurate, and ethical. It should anticipate the information required by decision-makers, be completed in time to influence decisions, be of the best quality for the minimum expenditure, and protect the rights of participants in the research process.

The two main approaches to research are the basic approach, often viewed as pure or fundamental research, and the applied approach, which includes action research, operations research, and contract research.

What Is Research, and Why Do People Do It?

• Open Access
• First Online: 03 December 2022

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• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
• Anne K Morris 6 &
• Charles Hohensee 6  

Part of the book series: Research in Mathematics Education ((RME))

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Abstractspiepr Abs1

Every day people do research as they gather information to learn about something of interest. In the scientific world, however, research means something different than simply gathering information. Scientific research is characterized by its careful planning and observing, by its relentless efforts to understand and explain, and by its commitment to learn from everyone else seriously engaged in research. We call this kind of research scientific inquiry and define it as “formulating, testing, and revising hypotheses.” By “hypotheses” we do not mean the hypotheses you encounter in statistics courses. We mean predictions about what you expect to find and rationales for why you made these predictions. Throughout this and the remaining chapters we make clear that the process of scientific inquiry applies to all kinds of research studies and data, both qualitative and quantitative.

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Part I. What Is Research?

Have you ever studied something carefully because you wanted to know more about it? Maybe you wanted to know more about your grandmother’s life when she was younger so you asked her to tell you stories from her childhood, or maybe you wanted to know more about a fertilizer you were about to use in your garden so you read the ingredients on the package and looked them up online. According to the dictionary definition, you were doing research.

Recall your high school assignments asking you to “research” a topic. The assignment likely included consulting a variety of sources that discussed the topic, perhaps including some “original” sources. Often, the teacher referred to your product as a “research paper.”

Were you conducting research when you interviewed your grandmother or wrote high school papers reviewing a particular topic? Our view is that you were engaged in part of the research process, but only a small part. In this book, we reserve the word “research” for what it means in the scientific world, that is, for scientific research or, more pointedly, for scientific inquiry .

Exercise 1.1

Before you read any further, write a definition of what you think scientific inquiry is. Keep it short—Two to three sentences. You will periodically update this definition as you read this chapter and the remainder of the book.

This book is about scientific inquiry—what it is and how to do it. For starters, scientific inquiry is a process, a particular way of finding out about something that involves a number of phases. Each phase of the process constitutes one aspect of scientific inquiry. You are doing scientific inquiry as you engage in each phase, but you have not done scientific inquiry until you complete the full process. Each phase is necessary but not sufficient.

In this chapter, we set the stage by defining scientific inquiry—describing what it is and what it is not—and by discussing what it is good for and why people do it. The remaining chapters build directly on the ideas presented in this chapter.

A first thing to know is that scientific inquiry is not all or nothing. “Scientificness” is a continuum. Inquiries can be more scientific or less scientific. What makes an inquiry more scientific? You might be surprised there is no universally agreed upon answer to this question. None of the descriptors we know of are sufficient by themselves to define scientific inquiry. But all of them give you a way of thinking about some aspects of the process of scientific inquiry. Each one gives you different insights.

Exercise 1.2

As you read about each descriptor below, think about what would make an inquiry more or less scientific. If you think a descriptor is important, use it to revise your definition of scientific inquiry.

Creating an Image of Scientific Inquiry

We will present three descriptors of scientific inquiry. Each provides a different perspective and emphasizes a different aspect of scientific inquiry. We will draw on all three descriptors to compose our definition of scientific inquiry.

Descriptor 1. Experience Carefully Planned in Advance

Sir Ronald Fisher, often called the father of modern statistical design, once referred to research as “experience carefully planned in advance” (1935, p. 8). He said that humans are always learning from experience, from interacting with the world around them. Usually, this learning is haphazard rather than the result of a deliberate process carried out over an extended period of time. Research, Fisher said, was learning from experience, but experience carefully planned in advance.

This phrase can be fully appreciated by looking at each word. The fact that scientific inquiry is based on experience means that it is based on interacting with the world. These interactions could be thought of as the stuff of scientific inquiry. In addition, it is not just any experience that counts. The experience must be carefully planned . The interactions with the world must be conducted with an explicit, describable purpose, and steps must be taken to make the intended learning as likely as possible. This planning is an integral part of scientific inquiry; it is not just a preparation phase. It is one of the things that distinguishes scientific inquiry from many everyday learning experiences. Finally, these steps must be taken beforehand and the purpose of the inquiry must be articulated in advance of the experience. Clearly, scientific inquiry does not happen by accident, by just stumbling into something. Stumbling into something unexpected and interesting can happen while engaged in scientific inquiry, but learning does not depend on it and serendipity does not make the inquiry scientific.

Descriptor 2. Observing Something and Trying to Explain Why It Is the Way It Is

When we were writing this chapter and googled “scientific inquiry,” the first entry was: “Scientific inquiry refers to the diverse ways in which scientists study the natural world and propose explanations based on the evidence derived from their work.” The emphasis is on studying, or observing, and then explaining . This descriptor takes the image of scientific inquiry beyond carefully planned experience and includes explaining what was experienced.

According to the Merriam-Webster dictionary, “explain” means “(a) to make known, (b) to make plain or understandable, (c) to give the reason or cause of, and (d) to show the logical development or relations of” (Merriam-Webster, n.d. ). We will use all these definitions. Taken together, they suggest that to explain an observation means to understand it by finding reasons (or causes) for why it is as it is. In this sense of scientific inquiry, the following are synonyms: explaining why, understanding why, and reasoning about causes and effects. Our image of scientific inquiry now includes planning, observing, and explaining why.

We need to add a final note about this descriptor. We have phrased it in a way that suggests “observing something” means you are observing something in real time—observing the way things are or the way things are changing. This is often true. But, observing could mean observing data that already have been collected, maybe by someone else making the original observations (e.g., secondary analysis of NAEP data or analysis of existing video recordings of classroom instruction). We will address secondary analyses more fully in Chap. 4 . For now, what is important is that the process requires explaining why the data look like they do.

We must note that for us, the term “data” is not limited to numerical or quantitative data such as test scores. Data can also take many nonquantitative forms, including written survey responses, interview transcripts, journal entries, video recordings of students, teachers, and classrooms, text messages, and so forth.

Exercise 1.3

What are the implications of the statement that just “observing” is not enough to count as scientific inquiry? Does this mean that a detailed description of a phenomenon is not scientific inquiry?

Find sources that define research in education that differ with our position, that say description alone, without explanation, counts as scientific research. Identify the precise points where the opinions differ. What are the best arguments for each of the positions? Which do you prefer? Why?

Descriptor 3. Updating Everyone’s Thinking in Response to More and Better Information

This descriptor focuses on a third aspect of scientific inquiry: updating and advancing the field’s understanding of phenomena that are investigated. This descriptor foregrounds a powerful characteristic of scientific inquiry: the reliability (or trustworthiness) of what is learned and the ultimate inevitability of this learning to advance human understanding of phenomena. Humans might choose not to learn from scientific inquiry, but history suggests that scientific inquiry always has the potential to advance understanding and that, eventually, humans take advantage of these new understandings.

Before exploring these bold claims a bit further, note that this descriptor uses “information” in the same way the previous two descriptors used “experience” and “observations.” These are the stuff of scientific inquiry and we will use them often, sometimes interchangeably. Frequently, we will use the term “data” to stand for all these terms.

An overriding goal of scientific inquiry is for everyone to learn from what one scientist does. Much of this book is about the methods you need to use so others have faith in what you report and can learn the same things you learned. This aspect of scientific inquiry has many implications.

One implication is that scientific inquiry is not a private practice. It is a public practice available for others to see and learn from. Notice how different this is from everyday learning. When you happen to learn something from your everyday experience, often only you gain from the experience. The fact that research is a public practice means it is also a social one. It is best conducted by interacting with others along the way: soliciting feedback at each phase, taking opportunities to present work-in-progress, and benefitting from the advice of others.

A second implication is that you, as the researcher, must be committed to sharing what you are doing and what you are learning in an open and transparent way. This allows all phases of your work to be scrutinized and critiqued. This is what gives your work credibility. The reliability or trustworthiness of your findings depends on your colleagues recognizing that you have used all appropriate methods to maximize the chances that your claims are justified by the data.

A third implication of viewing scientific inquiry as a collective enterprise is the reverse of the second—you must be committed to receiving comments from others. You must treat your colleagues as fair and honest critics even though it might sometimes feel otherwise. You must appreciate their job, which is to remain skeptical while scrutinizing what you have done in considerable detail. To provide the best help to you, they must remain skeptical about your conclusions (when, for example, the data are difficult for them to interpret) until you offer a convincing logical argument based on the information you share. A rather harsh but good-to-remember statement of the role of your friendly critics was voiced by Karl Popper, a well-known twentieth century philosopher of science: “. . . if you are interested in the problem which I tried to solve by my tentative assertion, you may help me by criticizing it as severely as you can” (Popper, 1968, p. 27).

A final implication of this third descriptor is that, as someone engaged in scientific inquiry, you have no choice but to update your thinking when the data support a different conclusion. This applies to your own data as well as to those of others. When data clearly point to a specific claim, even one that is quite different than you expected, you must reconsider your position. If the outcome is replicated multiple times, you need to adjust your thinking accordingly. Scientific inquiry does not let you pick and choose which data to believe; it mandates that everyone update their thinking when the data warrant an update.

Doing Scientific Inquiry

We define scientific inquiry in an operational sense—what does it mean to do scientific inquiry? What kind of process would satisfy all three descriptors: carefully planning an experience in advance; observing and trying to explain what you see; and, contributing to updating everyone’s thinking about an important phenomenon?

We define scientific inquiry as formulating , testing , and revising hypotheses about phenomena of interest.

Of course, we are not the only ones who define it in this way. The definition for the scientific method posted by the editors of Britannica is: “a researcher develops a hypothesis, tests it through various means, and then modifies the hypothesis on the basis of the outcome of the tests and experiments” (Britannica, n.d. ).

Notice how defining scientific inquiry this way satisfies each of the descriptors. “Carefully planning an experience in advance” is exactly what happens when formulating a hypothesis about a phenomenon of interest and thinking about how to test it. “ Observing a phenomenon” occurs when testing a hypothesis, and “ explaining ” what is found is required when revising a hypothesis based on the data. Finally, “updating everyone’s thinking” comes from comparing publicly the original with the revised hypothesis.

Doing scientific inquiry, as we have defined it, underscores the value of accumulating knowledge rather than generating random bits of knowledge. Formulating, testing, and revising hypotheses is an ongoing process, with each revised hypothesis begging for another test, whether by the same researcher or by new researchers. The editors of Britannica signaled this cyclic process by adding the following phrase to their definition of the scientific method: “The modified hypothesis is then retested, further modified, and tested again.” Scientific inquiry creates a process that encourages each study to build on the studies that have gone before. Through collective engagement in this process of building study on top of study, the scientific community works together to update its thinking.

Before exploring more fully the meaning of “formulating, testing, and revising hypotheses,” we need to acknowledge that this is not the only way researchers define research. Some researchers prefer a less formal definition, one that includes more serendipity, less planning, less explanation. You might have come across more open definitions such as “research is finding out about something.” We prefer the tighter hypothesis formulation, testing, and revision definition because we believe it provides a single, coherent map for conducting research that addresses many of the thorny problems educational researchers encounter. We believe it is the most useful orientation toward research and the most helpful to learn as a beginning researcher.

A final clarification of our definition is that it applies equally to qualitative and quantitative research. This is a familiar distinction in education that has generated much discussion. You might think our definition favors quantitative methods over qualitative methods because the language of hypothesis formulation and testing is often associated with quantitative methods. In fact, we do not favor one method over another. In Chap. 4 , we will illustrate how our definition fits research using a range of quantitative and qualitative methods.

Exercise 1.4

Look for ways to extend what the field knows in an area that has already received attention by other researchers. Specifically, you can search for a program of research carried out by more experienced researchers that has some revised hypotheses that remain untested. Identify a revised hypothesis that you might like to test.

Unpacking the Terms Formulating, Testing, and Revising Hypotheses

To get a full sense of the definition of scientific inquiry we will use throughout this book, it is helpful to spend a little time with each of the key terms.

We first want to make clear that we use the term “hypothesis” as it is defined in most dictionaries and as it used in many scientific fields rather than as it is usually defined in educational statistics courses. By “hypothesis,” we do not mean a null hypothesis that is accepted or rejected by statistical analysis. Rather, we use “hypothesis” in the sense conveyed by the following definitions: “An idea or explanation for something that is based on known facts but has not yet been proved” (Cambridge University Press, n.d. ), and “An unproved theory, proposition, or supposition, tentatively accepted to explain certain facts and to provide a basis for further investigation or argument” (Agnes & Guralnik, 2008 ).

We distinguish two parts to “hypotheses.” Hypotheses consist of predictions and rationales . Predictions are statements about what you expect to find when you inquire about something. Rationales are explanations for why you made the predictions you did, why you believe your predictions are correct. So, for us “formulating hypotheses” means making explicit predictions and developing rationales for the predictions.

“Testing hypotheses” means making observations that allow you to assess in what ways your predictions were correct and in what ways they were incorrect. In education research, it is rarely useful to think of your predictions as either right or wrong. Because of the complexity of most issues you will investigate, most predictions will be right in some ways and wrong in others.

By studying the observations you make (data you collect) to test your hypotheses, you can revise your hypotheses to better align with the observations. This means revising your predictions plus revising your rationales to justify your adjusted predictions. Even though you might not run another test, formulating revised hypotheses is an essential part of conducting a research study. Comparing your original and revised hypotheses informs everyone of what you learned by conducting your study. In addition, a revised hypothesis sets the stage for you or someone else to extend your study and accumulate more knowledge of the phenomenon.

We should note that not everyone makes a clear distinction between predictions and rationales as two aspects of hypotheses. In fact, common, non-scientific uses of the word “hypothesis” may limit it to only a prediction or only an explanation (or rationale). We choose to explicitly include both prediction and rationale in our definition of hypothesis, not because we assert this should be the universal definition, but because we want to foreground the importance of both parts acting in concert. Using “hypothesis” to represent both prediction and rationale could hide the two aspects, but we make them explicit because they provide different kinds of information. It is usually easier to make predictions than develop rationales because predictions can be guesses, hunches, or gut feelings about which you have little confidence. Developing a compelling rationale requires careful thought plus reading what other researchers have found plus talking with your colleagues. Often, while you are developing your rationale you will find good reasons to change your predictions. Developing good rationales is the engine that drives scientific inquiry. Rationales are essentially descriptions of how much you know about the phenomenon you are studying. Throughout this guide, we will elaborate on how developing good rationales drives scientific inquiry. For now, we simply note that it can sharpen your predictions and help you to interpret your data as you test your hypotheses.

Hypotheses in education research take a variety of forms or types. This is because there are a variety of phenomena that can be investigated. Investigating educational phenomena is sometimes best done using qualitative methods, sometimes using quantitative methods, and most often using mixed methods (e.g., Hay, 2016 ; Weis et al. 2019a ; Weisner, 2005 ). This means that, given our definition, hypotheses are equally applicable to qualitative and quantitative investigations.

Hypotheses take different forms when they are used to investigate different kinds of phenomena. Two very different activities in education could be labeled conducting experiments and descriptions. In an experiment, a hypothesis makes a prediction about anticipated changes, say the changes that occur when a treatment or intervention is applied. You might investigate how students’ thinking changes during a particular kind of instruction.

A second type of hypothesis, relevant for descriptive research, makes a prediction about what you will find when you investigate and describe the nature of a situation. The goal is to understand a situation as it exists rather than to understand a change from one situation to another. In this case, your prediction is what you expect to observe. Your rationale is the set of reasons for making this prediction; it is your current explanation for why the situation will look like it does.

You will probably read, if you have not already, that some researchers say you do not need a prediction to conduct a descriptive study. We will discuss this point of view in Chap. 2 . For now, we simply claim that scientific inquiry, as we have defined it, applies to all kinds of research studies. Descriptive studies, like others, not only benefit from formulating, testing, and revising hypotheses, but also need hypothesis formulating, testing, and revising.

One reason we define research as formulating, testing, and revising hypotheses is that if you think of research in this way you are less likely to go wrong. It is a useful guide for the entire process, as we will describe in detail in the chapters ahead. For example, as you build the rationale for your predictions, you are constructing the theoretical framework for your study (Chap. 3 ). As you work out the methods you will use to test your hypothesis, every decision you make will be based on asking, “Will this help me formulate or test or revise my hypothesis?” (Chap. 4 ). As you interpret the results of testing your predictions, you will compare them to what you predicted and examine the differences, focusing on how you must revise your hypotheses (Chap. 5 ). By anchoring the process to formulating, testing, and revising hypotheses, you will make smart decisions that yield a coherent and well-designed study.

Exercise 1.5

Compare the concept of formulating, testing, and revising hypotheses with the descriptions of scientific inquiry contained in Scientific Research in Education (NRC, 2002 ). How are they similar or different?

Exercise 1.6

Provide an example to illustrate and emphasize the differences between everyday learning/thinking and scientific inquiry.

Learning from Doing Scientific Inquiry

We noted earlier that a measure of what you have learned by conducting a research study is found in the differences between your original hypothesis and your revised hypothesis based on the data you collected to test your hypothesis. We will elaborate this statement in later chapters, but we preview our argument here.

Even before collecting data, scientific inquiry requires cycles of making a prediction, developing a rationale, refining your predictions, reading and studying more to strengthen your rationale, refining your predictions again, and so forth. And, even if you have run through several such cycles, you still will likely find that when you test your prediction you will be partly right and partly wrong. The results will support some parts of your predictions but not others, or the results will “kind of” support your predictions. A critical part of scientific inquiry is making sense of your results by interpreting them against your predictions. Carefully describing what aspects of your data supported your predictions, what aspects did not, and what data fell outside of any predictions is not an easy task, but you cannot learn from your study without doing this analysis.

Analyzing the matches and mismatches between your predictions and your data allows you to formulate different rationales that would have accounted for more of the data. The best revised rationale is the one that accounts for the most data. Once you have revised your rationales, you can think about the predictions they best justify or explain. It is by comparing your original rationales to your new rationales that you can sort out what you learned from your study.

Suppose your study was an experiment. Maybe you were investigating the effects of a new instructional intervention on students’ learning. Your original rationale was your explanation for why the intervention would change the learning outcomes in a particular way. Your revised rationale explained why the changes that you observed occurred like they did and why your revised predictions are better. Maybe your original rationale focused on the potential of the activities if they were implemented in ideal ways and your revised rationale included the factors that are likely to affect how teachers implement them. By comparing the before and after rationales, you are describing what you learned—what you can explain now that you could not before. Another way of saying this is that you are describing how much more you understand now than before you conducted your study.

Revised predictions based on carefully planned and collected data usually exhibit some of the following features compared with the originals: more precision, more completeness, and broader scope. Revised rationales have more explanatory power and become more complete, more aligned with the new predictions, sharper, and overall more convincing.

Part II. Why Do Educators Do Research?

Doing scientific inquiry is a lot of work. Each phase of the process takes time, and you will often cycle back to improve earlier phases as you engage in later phases. Because of the significant effort required, you should make sure your study is worth it. So, from the beginning, you should think about the purpose of your study. Why do you want to do it? And, because research is a social practice, you should also think about whether the results of your study are likely to be important and significant to the education community.

If you are doing research in the way we have described—as scientific inquiry—then one purpose of your study is to understand , not just to describe or evaluate or report. As we noted earlier, when you formulate hypotheses, you are developing rationales that explain why things might be like they are. In our view, trying to understand and explain is what separates research from other kinds of activities, like evaluating or describing.

One reason understanding is so important is that it allows researchers to see how or why something works like it does. When you see how something works, you are better able to predict how it might work in other contexts, under other conditions. And, because conditions, or contextual factors, matter a lot in education, gaining insights into applying your findings to other contexts increases the contributions of your work and its importance to the broader education community.

Consequently, the purposes of research studies in education often include the more specific aim of identifying and understanding the conditions under which the phenomena being studied work like the observations suggest. A classic example of this kind of study in mathematics education was reported by William Brownell and Harold Moser in 1949 . They were trying to establish which method of subtracting whole numbers could be taught most effectively—the regrouping method or the equal additions method. However, they realized that effectiveness might depend on the conditions under which the methods were taught—“meaningfully” versus “mechanically.” So, they designed a study that crossed the two instructional approaches with the two different methods (regrouping and equal additions). Among other results, they found that these conditions did matter. The regrouping method was more effective under the meaningful condition than the mechanical condition, but the same was not true for the equal additions algorithm.

What do education researchers want to understand? In our view, the ultimate goal of education is to offer all students the best possible learning opportunities. So, we believe the ultimate purpose of scientific inquiry in education is to develop understanding that supports the improvement of learning opportunities for all students. We say “ultimate” because there are lots of issues that must be understood to improve learning opportunities for all students. Hypotheses about many aspects of education are connected, ultimately, to students’ learning. For example, formulating and testing a hypothesis that preservice teachers need to engage in particular kinds of activities in their coursework in order to teach particular topics well is, ultimately, connected to improving students’ learning opportunities. So is hypothesizing that school districts often devote relatively few resources to instructional leadership training or hypothesizing that positioning mathematics as a tool students can use to combat social injustice can help students see the relevance of mathematics to their lives.

We do not exclude the importance of research on educational issues more removed from improving students’ learning opportunities, but we do think the argument for their importance will be more difficult to make. If there is no way to imagine a connection between your hypothesis and improving learning opportunities for students, even a distant connection, we recommend you reconsider whether it is an important hypothesis within the education community.

Notice that we said the ultimate goal of education is to offer all students the best possible learning opportunities. For too long, educators have been satisfied with a goal of offering rich learning opportunities for lots of students, sometimes even for just the majority of students, but not necessarily for all students. Evaluations of success often are based on outcomes that show high averages. In other words, if many students have learned something, or even a smaller number have learned a lot, educators may have been satisfied. The problem is that there is usually a pattern in the groups of students who receive lower quality opportunities—students of color and students who live in poor areas, urban and rural. This is not acceptable. Consequently, we emphasize the premise that the purpose of education research is to offer rich learning opportunities to all students.

One way to make sure you will be able to convince others of the importance of your study is to consider investigating some aspect of teachers’ shared instructional problems. Historically, researchers in education have set their own research agendas, regardless of the problems teachers are facing in schools. It is increasingly recognized that teachers have had trouble applying to their own classrooms what researchers find. To address this problem, a researcher could partner with a teacher—better yet, a small group of teachers—and talk with them about instructional problems they all share. These discussions can create a rich pool of problems researchers can consider. If researchers pursued one of these problems (preferably alongside teachers), the connection to improving learning opportunities for all students could be direct and immediate. “Grounding a research question in instructional problems that are experienced across multiple teachers’ classrooms helps to ensure that the answer to the question will be of sufficient scope to be relevant and significant beyond the local context” (Cai et al., 2019b , p. 115).

As a beginning researcher, determining the relevance and importance of a research problem is especially challenging. We recommend talking with advisors, other experienced researchers, and peers to test the educational importance of possible research problems and topics of study. You will also learn much more about the issue of research importance when you read Chap. 5 .

Exercise 1.7

Identify a problem in education that is closely connected to improving learning opportunities and a problem that has a less close connection. For each problem, write a brief argument (like a logical sequence of if-then statements) that connects the problem to all students’ learning opportunities.

Part III. Conducting Research as a Practice of Failing Productively

Scientific inquiry involves formulating hypotheses about phenomena that are not fully understood—by you or anyone else. Even if you are able to inform your hypotheses with lots of knowledge that has already been accumulated, you are likely to find that your prediction is not entirely accurate. This is normal. Remember, scientific inquiry is a process of constantly updating your thinking. More and better information means revising your thinking, again, and again, and again. Because you never fully understand a complicated phenomenon and your hypotheses never produce completely accurate predictions, it is easy to believe you are somehow failing.

The trick is to fail upward, to fail to predict accurately in ways that inform your next hypothesis so you can make a better prediction. Some of the best-known researchers in education have been open and honest about the many times their predictions were wrong and, based on the results of their studies and those of others, they continuously updated their thinking and changed their hypotheses.

A striking example of publicly revising (actually reversing) hypotheses due to incorrect predictions is found in the work of Lee J. Cronbach, one of the most distinguished educational psychologists of the twentieth century. In 1955, Cronbach delivered his presidential address to the American Psychological Association. Titling it “Two Disciplines of Scientific Psychology,” Cronbach proposed a rapprochement between two research approaches—correlational studies that focused on individual differences and experimental studies that focused on instructional treatments controlling for individual differences. (We will examine different research approaches in Chap. 4 ). If these approaches could be brought together, reasoned Cronbach ( 1957 ), researchers could find interactions between individual characteristics and treatments (aptitude-treatment interactions or ATIs), fitting the best treatments to different individuals.

In 1975, after years of research by many researchers looking for ATIs, Cronbach acknowledged the evidence for simple, useful ATIs had not been found. Even when trying to find interactions between a few variables that could provide instructional guidance, the analysis, said Cronbach, creates “a hall of mirrors that extends to infinity, tormenting even the boldest investigators and defeating even ambitious designs” (Cronbach, 1975 , p. 119).

As he was reflecting back on his work, Cronbach ( 1986 ) recommended moving away from documenting instructional effects through statistical inference (an approach he had championed for much of his career) and toward approaches that probe the reasons for these effects, approaches that provide a “full account of events in a time, place, and context” (Cronbach, 1986 , p. 104). This is a remarkable change in hypotheses, a change based on data and made fully transparent. Cronbach understood the value of failing productively.

Closer to home, in a less dramatic example, one of us began a line of scientific inquiry into how to prepare elementary preservice teachers to teach early algebra. Teaching early algebra meant engaging elementary students in early forms of algebraic reasoning. Such reasoning should help them transition from arithmetic to algebra. To begin this line of inquiry, a set of activities for preservice teachers were developed. Even though the activities were based on well-supported hypotheses, they largely failed to engage preservice teachers as predicted because of unanticipated challenges the preservice teachers faced. To capitalize on this failure, follow-up studies were conducted, first to better understand elementary preservice teachers’ challenges with preparing to teach early algebra, and then to better support preservice teachers in navigating these challenges. In this example, the initial failure was a necessary step in the researchers’ scientific inquiry and furthered the researchers’ understanding of this issue.

We present another example of failing productively in Chap. 2 . That example emerges from recounting the history of a well-known research program in mathematics education.

Making mistakes is an inherent part of doing scientific research. Conducting a study is rarely a smooth path from beginning to end. We recommend that you keep the following things in mind as you begin a career of conducting research in education.

First, do not get discouraged when you make mistakes; do not fall into the trap of feeling like you are not capable of doing research because you make too many errors.

Second, learn from your mistakes. Do not ignore your mistakes or treat them as errors that you simply need to forget and move past. Mistakes are rich sites for learning—in research just as in other fields of study.

Third, by reflecting on your mistakes, you can learn to make better mistakes, mistakes that inform you about a productive next step. You will not be able to eliminate your mistakes, but you can set a goal of making better and better mistakes.

Exercise 1.8

How does scientific inquiry differ from everyday learning in giving you the tools to fail upward? You may find helpful perspectives on this question in other resources on science and scientific inquiry (e.g., Failure: Why Science is So Successful by Firestein, 2015).

Exercise 1.9

Use what you have learned in this chapter to write a new definition of scientific inquiry. Compare this definition with the one you wrote before reading this chapter. If you are reading this book as part of a course, compare your definition with your colleagues’ definitions. Develop a consensus definition with everyone in the course.

Part IV. Preview of Chap. 2

Now that you have a good idea of what research is, at least of what we believe research is, the next step is to think about how to actually begin doing research. This means how to begin formulating, testing, and revising hypotheses. As for all phases of scientific inquiry, there are lots of things to think about. Because it is critical to start well, we devote Chap. 2 to getting started with formulating hypotheses.

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Hiebert, J., Cai, J., Hwang, S., Morris, A.K., Hohensee, C. (2023). What Is Research, and Why Do People Do It?. In: Doing Research: A New Researcher’s Guide. Research in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-19078-0_1

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What is Research? – Purpose of Research

• By DiscoverPhDs
• September 10, 2020

The purpose of research is to enhance society by advancing knowledge through the development of scientific theories, concepts and ideas. A research purpose is met through forming hypotheses, collecting data, analysing results, forming conclusions, implementing findings into real-life applications and forming new research questions.

What is Research

Simply put, research is the process of discovering new knowledge. This knowledge can be either the development of new concepts or the advancement of existing knowledge and theories, leading to a new understanding that was not previously known.

As a more formal definition of research, the following has been extracted from the Code of Federal Regulations :

While research can be carried out by anyone and in any field, most research is usually done to broaden knowledge in the physical, biological, and social worlds. This can range from learning why certain materials behave the way they do, to asking why certain people are more resilient than others when faced with the same challenges.

The use of ‘systematic investigation’ in the formal definition represents how research is normally conducted – a hypothesis is formed, appropriate research methods are designed, data is collected and analysed, and research results are summarised into one or more ‘research conclusions’. These research conclusions are then shared with the rest of the scientific community to add to the existing knowledge and serve as evidence to form additional questions that can be investigated. It is this cyclical process that enables scientific research to make continuous progress over the years; the true purpose of research.

What is the Purpose of Research

From weather forecasts to the discovery of antibiotics, researchers are constantly trying to find new ways to understand the world and how things work – with the ultimate goal of improving our lives.

The purpose of research is therefore to find out what is known, what is not and what we can develop further. In this way, scientists can develop new theories, ideas and products that shape our society and our everyday lives.

Although research can take many forms, there are three main purposes of research:

• Exploratory: Exploratory research is the first research to be conducted around a problem that has not yet been clearly defined. Exploration research therefore aims to gain a better understanding of the exact nature of the problem and not to provide a conclusive answer to the problem itself. This enables us to conduct more in-depth research later on.
• Descriptive: Descriptive research expands knowledge of a research problem or phenomenon by describing it according to its characteristics and population. Descriptive research focuses on the ‘how’ and ‘what’, but not on the ‘why’.
• Explanatory: Explanatory research, also referred to as casual research, is conducted to determine how variables interact, i.e. to identify cause-and-effect relationships. Explanatory research deals with the ‘why’ of research questions and is therefore often based on experiments.

Characteristics of Research

There are 8 core characteristics that all research projects should have. These are:

• Empirical  – based on proven scientific methods derived from real-life observations and experiments.
• Logical  – follows sequential procedures based on valid principles.
• Cyclic  – research begins with a question and ends with a question, i.e. research should lead to a new line of questioning.
• Controlled  – vigorous measures put into place to keep all variables constant, except those under investigation.
• Hypothesis-based  – the research design generates data that sufficiently meets the research objectives and can prove or disprove the hypothesis. It makes the research study repeatable and gives credibility to the results.
• Analytical  – data is generated, recorded and analysed using proven techniques to ensure high accuracy and repeatability while minimising potential errors and anomalies.
• Objective  – sound judgement is used by the researcher to ensure that the research findings are valid.
• Statistical treatment  – statistical treatment is used to transform the available data into something more meaningful from which knowledge can be gained.

Finding a PhD has never been this easy – search for a PhD by keyword, location or academic area of interest.

Types of Research

Research can be divided into two main types: basic research (also known as pure research) and applied research.

Basic Research

Basic research, also known as pure research, is an original investigation into the reasons behind a process, phenomenon or particular event. It focuses on generating knowledge around existing basic principles.

Basic research is generally considered ‘non-commercial research’ because it does not focus on solving practical problems, and has no immediate benefit or ways it can be applied.

While basic research may not have direct applications, it usually provides new insights that can later be used in applied research.

Applied Research

Applied research investigates well-known theories and principles in order to enhance knowledge around a practical aim. Because of this, applied research focuses on solving real-life problems by deriving knowledge which has an immediate application.

Methods of Research

Research methods for data collection fall into one of two categories: inductive methods or deductive methods.

Inductive research methods focus on the analysis of an observation and are usually associated with qualitative research. Deductive research methods focus on the verification of an observation and are typically associated with quantitative research.

Qualitative Research

Qualitative research is a method that enables non-numerical data collection through open-ended methods such as interviews, case studies and focus groups .

It enables researchers to collect data on personal experiences, feelings or behaviours, as well as the reasons behind them. Because of this, qualitative research is often used in fields such as social science, psychology and philosophy and other areas where it is useful to know the connection between what has occurred and why it has occurred.

Quantitative Research

Quantitative research is a method that collects and analyses numerical data through statistical analysis.

It allows us to quantify variables, uncover relationships, and make generalisations across a larger population. As a result, quantitative research is often used in the natural and physical sciences such as engineering, biology, chemistry, physics, computer science, finance, and medical research, etc.

What does Research Involve?

Research often follows a systematic approach known as a Scientific Method, which is carried out using an hourglass model.

A research project first starts with a problem statement, or rather, the research purpose for engaging in the study. This can take the form of the ‘ scope of the study ’ or ‘ aims and objectives ’ of your research topic.

Subsequently, a literature review is carried out and a hypothesis is formed. The researcher then creates a research methodology and collects the data.

The data is then analysed using various statistical methods and the null hypothesis is either accepted or rejected.

In both cases, the study and its conclusion are officially written up as a report or research paper, and the researcher may also recommend lines of further questioning. The report or research paper is then shared with the wider research community, and the cycle begins all over again.

Although these steps outline the overall research process, keep in mind that research projects are highly dynamic and are therefore considered an iterative process with continued refinements and not a series of fixed stages.

Do you need to have published papers to do a PhD? The simple answer is no but it could benefit your application if you can.

Scientific misconduct can be described as a deviation from the accepted standards of scientific research, study and publication ethics.

Thinking about applying to a PhD? Then don’t miss out on these 4 tips on how to best prepare your application.

Join thousands of other students and stay up to date with the latest PhD programmes, funding opportunities and advice.

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Julia is entering the third year of a combined master’s and PhD program at Stanford University. Her research explores how to give robots the sense of touch to make them more useful for tasks such as dexterous manipulation.

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What is Research?

Research is a process of systematic inquiry that entails collection of data; documentation of critical information; and analysis and interpretation of that data/information, in accordance with suitable methodologies set by specific professional fields and academic disciplines.

Research is conducted to...

• Evaluate the validity of a hypothesis or an interpretive framework.
• To assemble a body of substantive knowledge and findings for sharing them in appropriate manners.
• To help generate questions for further inquiries.

If you would like further examples of specific ways different schools at Hampshire think about research, see: School Definitions of Research » What is "research" that needs to be reviewed and approved by the Institutional Review Board at Hampshire before proceeding?  Research should be reviewed by the IRB only when human subjects are involved, and the term research should be considered under a more narrow definition. Specifically, when the researcher is conducting research as outlined above AND has direct interaction with participants or data linked to personal identifiers , it should always fall under the purview of the IRB. Even if you have not directly collected the data yourself, as the researcher, your research may fall under the purview of the IRB. In reviewing such research, the IRB is concerned with the methodology of data collection in the "field" (e.g. collection, experimentation, interview, participant observation, etc.) and the use of the data.  The broader validity of the hypotheses or research questions, and the quality of inferences that may result (unless, of course, the research methodologies severely compromise the data collection and data usage directly), is not something they will be evaluating.

What if I am using information that is already available?

If you are doing research that is limited to secondary analysis of data, records, or specimens that are either publicly available, de-identified, or otherwise impossible to be linked to personal identities, you may still need IRB approval to do your project. Sometimes a data use agreement between the researcher and the data custodian may still be required to verify that the researcher will not have access to identifying codes.  This "de-linking" of data from personal identifiers  allows the IRB to make this determination. Regardless, you should submit an IRB proposal so the IRB can determine whether your project needs IRB review, and if so, the type of review required. For specifics of what research should be reviewed by the IRB and the category of review required, see the flow chart and examples provided .

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Ibram X. Kendi Faces a Reckoning of His Own

In 2020, the author of “How to Be an Antiracist” galvanized Americans with his ideas. The past four years have tested them — and him.

Ibram X. Kendi, the founding director of the Boston University Center for Antiracist Research. Credit... Wayne Lawrence for The New York Times

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By Rachel Poser

Rachel Poser is an editor for the magazine. She spoke to Kendi over a period of several months and visited him at his research center in Boston.

• June 4, 2024 Updated 4:49 p.m. ET

Ibram X. Kendi has a notebook that prompts him, on every other page, to write down “Things to be grateful for.” There are many things he might put under that heading. First and foremost, his wife and two daughters, and his health, having made it through Stage 4 colon cancer in his 30s — a diagnosis with a 12 percent survival rate. Tenure at Boston University, where Martin Luther King Jr. earned his doctorate in theology. A National Book Award, and a MacArthur “genius” grant for “transforming how many people understand, discuss and attempt to redress America’s longstanding racial challenges.” Then there were the millions of people who bought “How to Be an Antiracist,” the first of five of his books to take the No. 1 spot on the New York Times best-seller list. But he was particularly grateful to the readers who wrote to him to say his work changed them for the better.

Listen to this article, read by January LaVoy

These days, he could use the reminder. Four years have gone by since George Floyd was murdered on the pavement near Cup Foods in Minneapolis, sparking the racial “reckoning” that made Kendi a household name. Many people, Kendi among them, believe that reckoning is long over. State legislatures have pushed through harsh antiprotest measures . Conservative-led campaigns against teaching Black history and against diversity, equity and inclusion programs are underway. Last June, the Supreme Court struck down affirmative action in college admissions. And Donald Trump is once again the Republican nominee for president, promising to root out “the radical-left thugs that live like vermin within the confines of our country.”

Kendi has become a prime target of this backlash. Books of his have been banned from schools in some districts, and his name is a kind of profanity among conservatives who believe racism is mostly a problem of the past. Though legions of readers continue to celebrate Kendi as a courageous and groundbreaking thinker, for many others he has become a symbol of everything that’s wrong in racial discourse today. Even many allies in the fight for racial justice dismiss his brand of antiracism as unworkable, wrongheaded or counterproductive. “The vast majority of my critics,” Kendi told me last year, “either haven’t read my work or willfully misrepresent it.”

Criticism of Kendi only grew in September, when he made the “painful decision” to lay off more than half the staff of the research center he runs at Boston University. The Center for Antiracist Research, which Kendi founded during the 2020 protests to tackle “seemingly intractable problems of racial inequity and injustice,” raised an enormous sum of $55 million, and the news of its downsizing led to a storm of questions. False rumors began circulating that Kendi had stolen funds, and the university announced it would investigate after former employees accused him of mismanagement and secrecy.

The controversy quickly ballooned into a national news story, fueled in large part by right-wing media, which was all too happy to speculate about “missing funds” and condemn Kendi — and the broader racial-justice movement — as a fraud. On Fox News, the conservative activist Christopher Rufo told the host John Roberts that the center’s “failure” was “poetic justice.” “This is a symbol of where we have come since 2020 and why that movement is really floundering today,” he said. In early October, a podcast affiliated with the Manhattan Institute, the conservative think tank where Rufo works, jubilantly released an episode titled “The End of Ibram X. Kendi?”

‘I don’t know of anybody more ill suited for fame than Ibram Kendi.’

In December, I met Kendi at the Center for Antiracist Research, which was by then mostly empty, though I caught signs of its former life: Space heaters sat idly under desks, and Post-it notes lingered around the edges of unplugged monitors. On the frame of one cleared-out cubicle, a sticker in the shape of Earth read “Be the change.” Kendi welcomed me into his office in a pink shirt and a periwinkle blazer with a handkerchief tucked neatly in its pocket. He was calm on the surface, but he seemed to me, as he often did during the conversations we’d had since the layoffs, to be holding himself taut, like a tensile substance under enormous strain. The furor over the center, he said, was a measure of how desperate many people were to damage his reputation: “If this had happened at another center, it would either not have been a story or a one-day story.”

In “How to Be an Antiracist,” his best-known book, Kendi challenges readers to evaluate themselves by their racial impact, by whether their actions advance or impede the cause of racial equality. “There is no neutrality in the racial struggle,” he writes. “The question for each of us is: What side of history will we stand on?” This question evinces Kendi’s confidence that ideas and policies can be dependably sorted into one of two categories: racist or antiracist.

Kendi is a vegan, a tall man with a gentle, serious nature. “He’ll laugh at a joke — he’ll never crack one,” Kellie Carter Jackson, the chair of the Africana studies department at Wellesley and someone who has known Kendi for years, told me. He considers himself an “introvert and loner” who was chased down by the spotlight and is now caught in its glare. “I don’t know of anybody more ill suited for fame than Ibram Kendi,” said Stefan Bradley, a longtime friend and professor of Black studies at Amherst. There is a corniness to Kendi that’s endearing, like his use of the gratitude notebook — a thick, pastel-colored pad with gold spiral binding — or the fact that his phone email signature is “Sent from Typoville aka my iPhone.” Though he is always soft-spoken, volume sometimes seems to be a gauge of how comfortable he feels. The first time I met him in person, he greeted me so quietly that I worried my recorder wouldn’t pick up his voice.

Kendi had hired a pair of crisis-P.R. consultants to help him manage the fallout from the layoffs, a controversy that he believed had fed into dangerous, racist stories about Black leaders, and about him in particular. In the fun-house mirror of conservative media, Kendi has long loomed as an antiwhite extremist trying to get rich by sowing racial division. Kendi told me he received regular threats; he allowed me to come to the center only on the condition that I not reveal its location. “When it comes to the white supremacists who are the greatest domestic terrorist threat of our time, I am one of their chief enemies,” he told me.

Boston University had recently released the results of its audit, which found “no issues” with how the center’s finances were handled. The center’s problem, Kendi told me, was more banal: Most of its money was in its endowment or restricted to specific uses, and after the high of 2020, donations had crashed. “At our current rate, we were going to run out in two years,” he said. “That was what ultimately led us to feel like we needed to make a major change.” The center’s new model would fund nine-month academic fellowships rather than a large full-time staff. Though inquiries into the center’s grant-management practices and workplace culture were continuing, Kendi was confident that they would absolve him, too. In the media, he’d dismissed the complaints about his leadership as “unfair,” “unfounded,” “vague,” “meanspirited” and an attempt to “settle old scores.”

In the fall, when I began talking to former employees and faculty — most of whom asked for anonymity because they remain at Boston University or signed severance agreements that included nondisparagement language — it was clear that many of them felt caught in a bind. They could already see that the story of the center’s dysfunction was being used to undermine the racial-justice movement, but they were frustrated to watch Kendi play down the problems and cast their concerns as spiteful or even racist. They felt that what they experienced at the center was now playing out in public: Kendi’s tendency to see their constructive feedback as hostile. “He doesn’t trust anybody,” one person told me. “He doesn’t let anyone in.”

To Kendi, attacks from those who claim to be allies, like attacks from political enemies, are to be expected. In his books, Kendi argues that history is not an arc bending toward justice but a war of “dueling” forces — racist and antiracist — that each escalate their response when the other advances. In the years since 2020, he believes, the country has entered a predictable period of retrenchment, when the force of racism is ascendant and the racial progress of the last several decades is under threat. To defend antiracism, to defend himself, he would simply have to fight harder.

Not so long ago, Kendi thought he saw a new world coming into being. “We are living in the midst of an antiracist revolution,” he wrote in September 2020 in an Atlantic cover story headlined, “Is This the Beginning of the End for American Racism?” Nearly 20 percent of Americans were saying that “race relations” was the most urgent problem facing the nation — more than at any point since 1968 — and many of them were turning to Kendi to figure out what to do about it. They were buying his memoir and manifesto, “How to Be an Antiracist,” much of which he wrote while undergoing chemotherapy. “This was perhaps the last thing he was going to write,” Chris Jackson, Kendi’s editor, told me. “There was no cynicism in the writing of it.” (Jackson was the editor of a 2021 book based on The 1619 Project, which originated in this magazine in 2019 ; Kendi contributed a chapter to that book.)

Kendi confesses in the introduction that he “used to be racist most of the time.” The year 1994, when he turned 12, marked three decades since the United States outlawed discrimination on the basis of race. Then why, Kendi wondered as an adolescent, were so many Black people out of work, impoverished or incarcerated? The problem, he concluded, must be Black people themselves. Not Black people like his parents, God-loving professionals who had saved enough to buy a home in Jamaica, Queens, and who never let their two sons forget the importance of education and hard work. But they were the exception. In high school, Kendi competed in an oratory contest in which he gave voice to many of the anti-Black stereotypes circulating in the ’90s — that Black youths were violent, unstudious, unmotivated. “They think it’s OK to be the most feared in our society,” he proclaimed. “They think it’s OK not to think!” Kendi also turned these ideas on himself, believing that he was a “subpar student” because of his race.

Kendi’s mind began to change when he arrived on the campus of Florida A&M, one of the largest historically Black universities in the country, in the fall of 2000 to study sports journalism. “I had never seen so many Black people together with positive motives,” he wrote at the time. Kendi was disengaged for most of high school, as concerned with his clothes as his grades. His friends at the university teased him for joining a modeling troupe and preening before parties, particularly because once he got to them he was too shy to talk to anyone. “He would come out, and you could smell the cologne from down the hall,” Grady Tripp, Kendi’s housemate, told me. But experimenting with his style, for Kendi, was part of trying on new ideas. For a while, he wore honey-colored contact lenses that turned his irises an off-putting shade of orange; he got rid of them once he decided they were a rejection of blackness, like Malcolm X’s straightening his hair with lye.

Over long hours spent reading alone in the library, Kendi found his way to some unlikely conclusions. In “How to Be an Antiracist,” he describes bursting into his housemate’s room to declare that he had “figured white people out.” “They are aliens,” he said. Kendi had gone searching for answers in conspiracy theories and Nation of Islam theology that cast whites as a “devil race” bred by an evil Black scientist to conquer the planet. “Europeans are simply a different breed of human,” he wrote in a column for the student newspaper in 2003. They are “socialized to be aggressive” and have used “the AIDS virus and cloning” to dominate the world’s peoples. Recently, the column has circulated on right-wing social media as evidence of Kendi’s antiwhite extremism, which frustrates him because it’s in his own memoir as an example of just how lost he had become.

Kendi went on to earn a Ph.D. in African American studies from Temple University. The founder of his department was Molefi Kete Asante, an Afrocentrist who has called on the descendants of enslaved people to embrace traditional African dress, languages and religions. Kendi eventually changed his middle name to Xolani, meaning “peace” in Zulu; at their wedding, he and his wife, Sadiqa, adopted the last name Kendi, meaning “loved one” in Meru. Kendi has called Asante “profoundly antiracist,” but Kendi remained an idiosyncratic thinker who did not consider himself a part of just one scholarly tradition; he knew early on that he wanted to write for the public. In a 2019 interview, when asked about his intellectual lineage, Kendi named W.E.B. Du Bois, Ida B. Wells and Malcolm X.

Kendi became part of a cohort of Black writers, among them Nikole Hannah-Jones and Ta-Nehisi Coates, who, through the sunset of the Obama presidency and the red dawn of the MAGA movement, argued that anti-Blackness remains a major force shaping American politics. They helped popularize the longstanding idea that racism in the United States is systemic — that the country’s laws and institutions perpetuate Black disadvantage despite a pledge of equal treatment. The Civil Rights Act of 1964 ended de jure white supremacy, but President Lyndon B. Johnson, who signed it into law, acknowledged that it wouldn’t uproot a racial caste system grown over centuries.

“The next and the more profound stage of the battle for civil rights,” he said, would be to achieve “not just equality as a right and a theory but equality as a fact.” Kendi and others wrote bracingly about the failure of that promise. Far from economic redress, Black Americans were met with continued discrimination in every realm of life, while being told the country was now “colorblind.” Kendi and others argued that remedying the impact of hundreds of years of subjugation would require policies that recognize, rather than ignore, that legacy, such as affirmative action and reparations.

‘The vast majority of my critics either haven’t read my work or willfully misrepresent it.’

Far too many Americans, Kendi felt, still thought of racism as conscious prejudice, so conversations got stuck in cul-de-sacs of denial, in which people protested that they were “not racist” because they harbored no anti-Black animus. To convey this, he landed on the binary that would become his most famous and perhaps most controversial idea. “There is no such thing as a not-racist idea” or a “race-neutral policy,” he wrote in “How to Be an Antiracist,” published in 2019. “The opposite of ‘racist’ isn’t ‘not racist.’ It is ‘antiracist.’”

Black activists have long used the word “antiracist” to describe active resistance to white supremacy, but “How to Be an Antiracist” catapulted the term into the American lexicon, in much the same way that Sheryl Sandberg turned “Lean In” into a mantra. After George Floyd’s death, the book sold out on Amazon, which was “unheard-of,” Kendi said. Media coverage of Kendi in those days made him sound nearly superhuman. In a GQ profile, for example, the novelist ZZ Packer describes Kendi as a “preternaturally wise” Buddha-like figure, “the antiracist guru of our time” with a “Jedi-like prowess for recognizing and neutralizing the racism pervading our society.”

During the summer of 2020, Kendi sometimes appeared onstage or onscreen alongside Robin DiAngelo, the educator whose book “White Fragility” was also a No. 1 best seller. Kendi and DiAngelo write less about the workings of systemic racism than the ideas and psychological defenses that cause people to deny their complicity in it. They share a belief in what Kendi calls “individual transformation for societal transformation.” When Kendi took over Selena Gomez’s Instagram, for example, he urged her 180 million followers to “1. Acknowledge your racism,” “2. Confess your racist ideas” and “3. Define racism and antiracism.” Then they would be ready for Steps 4 and 5, identifying and working to change racist policies.

Kendi and DiAngelo’s talk of confession — antiracism as a kind of conversion experience — inspired many people and disturbed others. By focusing so much on personal growth, critics said, they made it easy for self-help to take the place of organizing, for a conflict over the policing of Black communities, and by extension their material conditions, to become a fight not over policy but over etiquette — which words to use, whether to say “Black Lives Matter” or “All Lives Matter.” Many allies felt that Kendi and DiAngelo were merely helping white people alleviate their guilt.

They also questioned Kendi’s willingness to turn his philosophy into a brand. Following the success of “How to Be an Antiracist,” he released a deck of “antiracist” conversation-starter cards, an “antiracist” journal with prompts for self-reflection and a children’s book, “Antiracist Baby.” Christine Platt, an author and advocate who worked with Kendi at American University, recently co-wrote a novel that features a Kendi-like figure — a “soft-spoken” author named Dr. Braxton Walsh Jr., whose book “Woke Yet?” becomes a viral phenomenon. “White folks post about it on social media all the time,” rants De’Andrea, one of the main characters. “Wake up and get your copy today! Only nineteen ninety-nine plus shipping and handling.”

Those who thought of him as a self-help guru, Kendi felt, simply hadn’t read his work. Like most scholars of race, Kendi believes that Blackness is a fiction born of colonial powers’ self-interest, not just ignorance or hate, meaning that combating racism today requires upending the economic and political structures that propagate it. But Kendi doesn’t like the term “systemic racism” because it turns racism into a “hidden and unknowable” force for which there’s no one to blame, so he prefers to talk about “racist policies.”

In The Atlantic, he warned against the country going down a path of symbolic change where “monuments to racism are dismantled, but Americans shrink from the awesome task of reshaping the country with antiracist policies,” like Medicare for All, need-based school funding and reparations. Changing policy was exactly what he aimed to do at Boston University. During the protests, in the summer of 2020, the university named Kendi the Andrew W. Mellon professor of the humanities, a chair previously held by the Nobel Peace Prize winner Elie Wiesel, and announced the creation of a center on campus to put his ideas into action. Donations came pouring in, led by an anonymous $25 million gift and a $10 million gift from the Twitter founder Jack Dorsey, which the provost said would give Kendi “the resources to launch the center like a rocket ship.”

Kendi started the center from his home in Boston, while Sadiqa, a pediatric E.R. doctor, came and went from the hospital in full protective gear. Kendi ran a research center as part of his old job at American University, but he felt unable to make a meaningful impact because the resources were modest and he was diagnosed with cancer just four months after its founding. Now, granted tens of millions of dollars to enact his most ambitious ideas, Kendi was determined to create an organization that could be a real engine of progress. “We’ve got to build an infrastructure to match what the right has created,” he later told a co-worker. “We’ve got to build something equally powerful.”

Kendi’s two centers were part of a wave of racial-justice spaces being founded at universities, like the Thurgood Marshall Civil Rights Center at Howard or the Ida B. Wells Just Data Lab at Princeton, that pledged to work in partnership with activists and community groups to achieve social change. Kendi envisioned an organization that supported people of color in campaigning for policies that would concretely improve their lives.

To reflect that mission, he designed a structure with four “pillars” or offices: Research, Policy, Narrative and Advocacy. He recruited data scientists, policy analysts, organizers and educators and brought in faculty members working on race from across the university. They set up a model-legislation unit, which would draft sample bills and public-comment notes; an amicus-brief practice, which would target court cases in which race was being overlooked as an issue; and a grant process to fund research on racism by interdisciplinary teams elsewhere at the university, among other programs. Kendi also struck up a partnership with The Boston Globe to revive The Emancipator, a storied abolitionist newspaper. “It was a really exciting time,” he told me.

That summer, however, Kendi found himself on the defensive beyond Boston as Republican book-banning campaigns revved up. On Fox News, Tucker Carlson denounced “How to Be an Antiracist” as “poisonous,” plucking out Kendi’s summary of the case for race-conscious policymaking, which sounded particularly maladroit when taken out of context: “ The only remedy to racist discrimination is antiracist discrimination ,” Carlson read in mock disbelief. “In other words, his book against racism promotes racism.” This was around the same time that Rufo, the conservative activist, started to position Kendi as a leading proponent of critical race theory, a school of thought, Rufo told The New Yorker, that he discovered by hunting through the footnotes of “How to Be an Antiracist.”

Critical race theorists were a group of legal scholars in the 1970s and ’80s who documented ways that the American legal framework of racial equality was nevertheless producing unequal treatment. They elaborated the idea of systemic racism and the critique of “colorblindness” that inform much of the writing of Kendi’s cohort. Rufo wrote on Twitter that his goal was to change the meaning of the term “critical race theory” — to “turn it toxic” by putting “all of the various cultural insanities under that brand category.” In his attacks on Kendi, Rufo also amplified the left’s critique of Kendi’s corporate-friendliness, caricaturing Kendi as a grifter out to enrich himself by raking in speaking fees. The number of threatening messages Kendi received began to rise. “I don’t feel safe anywhere,” Kendi later told a colleague. “I’m constantly looking over my shoulder.”

By the time the academic year began, in the fall of 2021, Kendi decided to take extraordinary measures. Before the center began in-person work that September, Kendi sent the staff an email about “security protocols,” instructing them to conceal the location of the center even from other Boston University faculty members and students. “It is critical to not share the address of the center with anyone or bring anyone to the center,” Kendi wrote. The email included a mock script to be used in the event of an inquiry about the center’s location, which ended abruptly with, “I gotta go.”

Though such precautions felt necessary to Kendi, they were met with incredulity and frustration by some employees who were starting to question his leadership. Problems emerged within the first six months, according to more than a dozen staff and faculty members I interviewed. Some told me they had gone to the center because they considered Kendi a visionary; others had reservations about or flat-out disagreements with his work but believed he had brought much-needed attention to issues they cared about. They would be able to find common ground, they thought. They were ready for some chaos as they tried to spin up a new organization remotely, but they quickly ran into difficulty as they tried to execute some of Kendi’s plans.

Kendi emphasizes in his books that policies alone are the cause of racial disparities today. In “Stamped From the Beginning,” his 2016 history of anti-Black ideas from the 15th century to the Obama presidency — which won the National Book Award and was recently made into a Netflix documentary that made the Oscar shortlist — Kendi writes that blaming Black people for their own oppression, by implying that Black people or Black culture are inferior or pathological, was one of the oldest cons in America. He had witnessed it again during the early days of the pandemic, when the numbers suggested that Black people were dying from Covid faster than every racial group save Native Americans. Some pundits speculated about the “soul food” diet or posited that Black communities weren’t taking the virus seriously, even though a Pew survey found that Black respondents were most likely to view the coronavirus as a major threat.

Kendi wanted the center to build “the nation’s largest online collection” of racial data to track disparities like this one and do analytical work to understand each policy responsible. In the case of Covid, for example, Black Americans are disproportionately likely to work in low-income essential jobs, to live in crowded conditions and to lack access to high-quality insurance or medical care. The center might research these conditions and propose targeted interventions, like changes to Medicaid coverage, or more transformative measures, like a universal basic income. One faculty member involved told me that she was “initially incredibly enthusiastic” about the idea. “It seemed like an opportunity to do rigorous, well-funded social-science research that would be aimed at real policy change on issues that I cared about,” she told me.

Like Kendi, his staff believed that historical oppression and ongoing discrimination explained why Black Americans fared comparatively poorly on so many measures of well-being, from education to wealth to longevity, and that centuries of injustice demanded a sweeping policy response to remedy. But understanding that past and present racism is the underlying cause of Black disadvantage is different from the work of assessing its role in any single policy, let alone figuring out how to change the policy to eliminate it. That takes careful analysis. “You have to have specificity,” the faculty member said, “or you can’t measure.”

Kendi pushed back at staff members who argued that the center should constrain its focus. There were plenty of academic centers and researchers that tracked data on racial disparities in one policy area or another, he said; he wanted to convene that pre-existing data, bringing it together in one place for easy access by the public. In a 2022 meeting, when the team tried to get a better sense of his vision, Kendi told them that he wanted a guy at a barbershop or a bar to be able to “pull up the numbers.” To many employees with data or policy backgrounds, what Kendi wanted didn’t seem feasible; at worst, they thought, it risked simply replicating others’ work or creating a mess of sloppily merged data, connected to too many policies for their small team to track rigorously. In the midst of the pandemic, the center struggled to hire a director of research who might have been able to mediate the dispute.

In November, a confidential complaint was filed with the university administration raising concerns about Kendi’s leadership. The anonymous employee told a university compliance officer that Kendi ran the center with “hypercontrol” and created an environment of “silence and secrecy” that was causing low morale and high turnover, claiming that “when Dr. Kendi is questioned, the narrative becomes that the employee must be the one with the ‘problem.’” The employee warned the university that the situation “is potentially going to blow up.”

One of Kendi’s refrains is that being antiracist demands self-criticism. “If I share an idea that people don’t understand, I’m to blame,” he told an interviewer in 2019. “I’m always to blame.” Kendi told me that his most productive conversations with critics of his ideas often happened in private, including one with a prominent Black thinker who inspired him to make a change in the revised edition of “How to Be an Antiracist.” “This person talked about how the goal should not just be equity,” Kendi said. “The goal should not be the same percentage of Black people being killed by police as white people. The goal should be no one being killed by police.” But some Black scholars, as the right-wing backlash strengthened, debated whether to make their criticisms in public. The philosopher Charles Mills, after listening to a graduate-student presentation about Kendi and DiAngelo at a conference in 2021, asked the presenter: “Are their views now sufficiently influential, or perhaps sufficiently harmful, that we should make them a part of the target?”

Kendi was frustrated to be constantly lumped in with DiAngelo, whose ideas diverge from his in important ways. DiAngelo considers “white identity” to be “inherently racist,” while Kendi argues that anyone, including Black people, can be racist or antiracist. That puts him at odds with an understanding — common in the academy and the racial-justice movement — that Black people can’t be racist because racism is a system of power relations, and that Black people as a group don’t have the structural means to enforce their prejudice; this notion is often phrased as a formula, that racism is “prejudice plus power.”

Kendi thinks of “racist” not as a pejorative but as a simple word of description. His reigning metaphor is the sticker. Racist and antiracist are “peelable name tags,” Kendi writes; they describe not who we are but who we are being in any particular moment. He says he opposes the censoriousness that has become the sharp edge of identity politics, because he doesn’t regard shame as a useful social tool. But he has no intention of taking the moral sting out of “racist” completely. “I wouldn’t say that a person is not being condemned when they’re being called a racist,” he told Ezra Klein in a 2019 interview.

Rather than replacing one definition of racism with another, Kendi is really joining two senses into one. For much of the 20th century, the white mainstream considered racism a personal moral issue, while Black civil rights activists, among others, argued that it’s also structural and systemic. In his definition, Kendi aims to connect the individual to the system. A “racist,” he writes, is “one who is expressing an idea of racial hierarchy, or through actions or inaction is supporting a policy that leads to racial inequity or injustice.”

Kendi’s focus on outcomes is not new. For decades, civil rights activists have brought lawsuits based on the legal theory of “disparate impact,” which holds that unequal outcomes prove that certain practices (by, for example, an employer or a landlord) are racially discriminatory, without evidence of malicious intent. Kendi’s definition urges us to perform this sort of disparate-impact analysis all the time. In Politico in 2020, Kendi proposed the creation of a federal agency that would clear every new policy — local, state or federal — to ensure that it wouldn’t increase racial disparities. But as his team at the center knew well, policies can have complicated effects. Let’s say that a local environmental policy would improve the air quality in Black neighborhoods near factories but would also lead to hundreds of lost jobs and worsen the area’s racial wealth gap. Should it be cleared? Is such a policy racist or antiracist?

The question is made even trickier by the fact that the racial impact of many policies might not become clear until years later. The legacy of desegregation, for example, shows that even a profoundly antiracist policy can be turned against itself in its implementation. This is what the term “systemic racism” captures that can be lost in Kendi’s translation of “racist policies.”

In “Stamped From the Beginning,” Kendi writes that “racist policy is the cause of racial disparities in this country and the world at large.” Mary Pattillo, a sociologist at Northwestern, told me that Kendi’s focus on race didn’t fully capture the complexity of social life — the roles of class, culture, religion, community. “No one variable alone explains anything ,” she said. But she thought there was value in simplifying. She understood Kendi not as an official making policy but as a thought leader making a “defensible, succinct provocation.” “We live in a country whose ideology is very individualistic, so the standard response to any failure is individual blame,” she said. “Those of us who do recognize the importance of policies, laws and so on have to always push so hard against that that we have to make statements like the one that Kendi is making.”

I came to think, after months of talking to Kendi, that this was the key to understanding him — to remember that he is trying to push so hard against that . To shove back the anti-Black stereotypes he documented in “Stamped From the Beginning,” the racist ideas that poisoned his own mind and sense of self-worth. His aim, at every turn, is to blame the policies that create unequal conditions and not the people enduring them. But Kendi is so consumed by combating the racist notion of Black inferiority that some of what he says in response is overstated, circular or uncareful, creating an easy target for his critics and discomfiting his allies. Conservatives were far from the only ones alarmed, for example, by his proposal for a constitutional amendment to appoint a panel of racism “experts” with the power to discipline public officials for “racist ideas.” (Kendi told me he modeled this proposal on European countries like Germany, where the bar for hate speech is much lower.)

Some of Kendi’s ideas are softer than they appear at first. Kendi told me that people who believe that his binary applies to “everything” are misreading him. Though he writes that “there is no such thing as a not-racist idea, only racist ideas and antiracist ideas,” he says he never meant that sentence to apply to the whole universe of ideas, only to ideas about race. When I asked him whether the environmental policy above would be racist or antiracist based on his definition, he qualified that “policies can be like people, both racist and antiracist,” and went on: “By improving the air quality in Black neighborhoods near factories, the policy is being antiracist. By exacerbating the area’s racial wealth gap, the policy is being racist.” Many of his critics might find this a more reasonable position, but it also leads to a question about how useful or powerful a dichotomy it is in the end.

Kendi wanted to remain open to criticism, but so much of what he encountered was racist mockery, lies, professional jealousy, misreadings and threats. “I have thought many times about exiting my vocation as a scholar who studies racism,” he wrote in the revised edition of “How to Be an Antiracist.” “After the experience of the last three years, it does not feel safe for me to be publicly self-reflective or self-critical. It feels dangerous for me to be vulnerable.” Though he commits to doing so anyway, the onslaught brought on by celebrity seemed to cause Kendi’s introversion to harden into distrust. “Fame can be defeating and depleting,” Stefan Bradley, Kendi’s friend, told me. “Every word he puts into the atmosphere will be chopped up a hundred different ways, and that takes a toll on somebody’s mental health.” Bradley continued: “I think that if he were a lesser spirit, he would have been destroyed.”

That Kendi felt under siege became clear to Yanique Redwood when she started her job at the Center for Antiracist Research. Redwood had met Kendi once, in 2017, and she remembered him as soft-spoken but burning with big, exciting ideas. In the fall of 2021, when she interviewed to be the center’s executive director, Kendi told her he felt as though he was failing. Fund-raising while also running the center was too much for one person, and he wanted Redwood, a Caribbean American health and racial-equity researcher who had spent nearly a decade running a small foundation, to take over internal operations. Redwood was prepared to find some disorder, but the state of the center’s finances was a mess unlike any she had ever seen. “Nothing was in place,” she said. “It was unbelievable that an institution like that, with so much spotlight on it, just did not have systems. I understood why I was being brought in.”

Before starting, she conducted a round of entry interviews with faculty and staff members, and by her 27th and last conversation, she was exhausted from absorbing their frustration. “There’s something really wrong here,” she told Kendi. Much of the staff was relieved when Redwood was hired. There had been widespread confusion as employees were asked to do “damage control” by performing jobs for which they weren’t hired, or even qualified. “Everyone was overwhelmed,” Redwood told me. “There were too many promises being made to funders. Products were being promised that could never be delivered.”

Redwood designed a process to help get researchers going on pilot projects tracking disparities relating to felony murder, the health and social safety net, reparations and student-debt forgiveness. She wanted to share some takeaways from her round of entry interviews with the staff, in a tactful and encouraging way, to start the work of repairing the center’s culture, but Kendi worried that whatever she wrote might leak. A reporter from a conservative media outlet was reaching out to former employees, asking about problems at the center. “This media storm was coming,” Redwood told me. “It was brewing.”

Employees said Kendi’s fear of leaks slowed the work and created confusion and unease. The first time Rachael DeCruz, the head of the Advocacy office, asked Kendi about the center’s finances to help her budget, in 2021, he reacted “bizarrely,” she told me. “Why do you need that information?” he asked. (Kendi denies that this conversation took place. DeCruz says that after asking repeatedly, she received the information about six months later.) The threat of outside scrutiny exacerbated what employees described as Kendi’s tendency to withhold information to avoid interpersonal conflict. “He doesn’t understand people, how to nurture them, how to make them want to do their best work,” Redwood told me. “It’s not his strength, not even a little bit.”

During her entry interviews, Redwood asked each employee what the organization’s values were, and many of them responded by saying something along the lines of “I’ve been wondering that myself.” She encouraged Kendi to hold a retreat to talk through the mission as a group. Kendi was hesitant because he found work retreats “uncomfortable” — “sitting in a room with a large group of people all day long is exhausting for me,” he told me — but he committed to holding one anyway and solicited staff comments on a document he wrote laying out his theory of social change and the center’s role in it. “I was happy to receive all this great feedback,” he wrote to Redwood. “I think the changes will make the document much stronger and clearer.”

On a spring day in 2022, the staff met at a conference center a half-hour’s drive from campus. The day’s agenda, though couched in the gentle jargon of nonprofits, contained hints of the mood: The organizers on staff had scheduled time for an acknowledgment of the center’s growing pains, for a “healing justice moment” and for a period of “wicked questions” when concerns or challenges could be raised. At the start of the day, Naima Wong, an outside facilitator, encouraged the staff not to hold back. “We’re here to really get into this,” she said.

Late in the afternoon, when it was time to wrap up, the group assembled at tables arranged in a circle. Saida Grundy, a sociologist, was seated across from Kendi. She had never been on board with Kendi’s understanding of racism, subscribing instead to the “power plus prejudice” view. Grundy had forwarded Kendi’s email about security to colleagues with the note “The paranoia is INSANE.” “Ibram is so lily-livered he probably jumps when the biscuit tin pops,” she told me. Grundy was the one who, back in November, had made the anonymous complaint, in which some charges carried a hint of paranoia of her own, like the idea that Kendi “despises academia” and had “gotten satisfaction out of pulling academics out of their own research.” She had accused the center of being an exploitative workplace and, after having conflict with her supervisor, had already mostly stepped back from her role. Grundy had told the compliance office that the center might explode, and now she was ready to blow it up herself.

Her voice raised, Grundy laid out an indictment of the document Kendi wrote. “This is a mile wide and an inch deep,” she said. She argued that the center needed to be more specific about its goals; “fighting racism” was such a broad mission that it felt cynically strategic, allowing the center to take in money for all sorts of projects. “If there is a grant for antiracism on Jupiter, great,” she said. “We do extraterrestrial antiracism.” Grundy, unlike most of the staff, thought the center should become a resource for university faculty members and students; her parents were Black student activists in the 1970s, and she believed that real change starts where you are. “If you lined up 99 Black students at B.U.,” she said, “99 will tell you the center’s made no difference to their experience.”

When she finished speaking, the room was silent. Several people were crying. Dawna Johnson, the center’s financial director at the time, called it an “explosion.” “People didn’t know what to say after that,” she said. “It just left you so unhappy and uptight.” Kendi, his face inscrutable behind a Covid mask, said nothing, and the facilitator wrapped up the session. “Scholars who study the experience of Black leaders find that the No.1 racist challenge Black leaders face is contested authority, even from other Black leaders and staff,” he wrote to me later. I asked him what he remembered from that day. “It’s almost like trying to remember a day in which you were really happy, but then something horrible happened at the end,” he told me. “It’s hard to remember anything else other than that horrible thing.”

Grundy had admittedly come in hot, many staff members agreed, but it didn’t seem to matter how they couched their concerns. Employees continued to push to make sure that the center’s research projects were both rigorous and responsive to community needs, but the issues they raised in response to Kendi’s “theory of change” document never seemed to get fully resolved. “He’s communicating one thing,” one person said. “Behind the curtain, he’s behaving a very different kind of way.” Redwood and several others said that if someone was too persistent about a concern, Kendi would slow or stop his communication with that person. “If someone disagrees or someone is being vocal, you can’t just get rid of them,” she wanted to tell him. “Like, this is how you breed distrust.”

Redwood ultimately decided that Kendi wasn’t interested in building consensus around a shared mission. “Only he had the ideas,” she said. “We were there to execute on his ideas.” Redwood resigned in October 2022.

In a memo to The Times, Kendi disputed many of the staff’s recollections of his leadership. “This is not me, and anyone close to me, who has worked with me for a long time, knows that I’m open to constructive criticism as a writer and a thinker and a leader,” he wrote. Many progressive advocacy groups, Kendi pointed out, have been torn apart by internal clashes in recent years, conflicts that he said were driven by employees who “care more about performing their radicalism” than working to “improve the lives of everyday people.” “Former employees constantly deauthorized me as the director of the center — not because they were against hierarchy — but to assume authority for themselves,” he wrote.

Even before Redwood’s departure, Kendi told me, he realized the center was in financial trouble. He was far from the only nonprofit leader caught short as funding for racial-justice work collapsed after 2020. Funders that doused organizations with cash in the wake of George Floyd’s murder proved unwilling or unable to sustain their commitment, and layoffs were taking place across the sector, even at large nonprofits like the Chan-Zuckerberg Initiative. The center had gone from raising $40 million in 2020 to a fraction of that — $420,000 — the next year.

In June 2023, after he went on parental leave, Kendi approached university leaders with the idea of switching to a fellowship model, which could adjust its number of awards to fluctuations in fund-raising. He told the staff only that he would be announcing some major changes when he returned from leave. Dawna Johnson, who succeeded Redwood as executive director, was left to manage a staff frustrated by being kept in the dark. “I think the staff thought I knew more than I actually did, as far as what the future of the center was,” she told me. “He’s like, Just don’t spend money, essentially, which is kind of difficult in an organization that needs to move forward.” (Kendi denies that he said anything like this to Johnson, who remains in her role today.)

Kendi spent the next three months taking care of his newborn daughter, Imara, and his wife, who was diagnosed with Stage 4 breast cancer while pregnant. In his absence, at another staff retreat, four employees stood up and spoke in turn about the problems at the center. Much of the staff had just learned that the center agreed to partner with the D.E.I. arm of the consulting company Deloitte, which does work for the police and prisons, on designing an antiracism training for corporate workplaces. “Why wasn’t this shared with the broader staff sooner, as a potential high-risk partnership that could impact the relationships we are forging with movement leaders?” one person said. “Why are we contemplating this partnership that arguably goes against our values?”

Kendi, who identifies as a police and prison abolitionist, suggested that donations from corporations could be seen as a “form of reparations,” and he stressed to me that the Deloitte agreement “allowed us to control the products from design to delivery.” He once again dismissed the critics at the retreat as “performative radicals” of the sort that have been “causing all kinds of havoc in Black-led social justice organizations for years, claiming that they are against hierarchy when they really are against being directed by a Black person.” He thought they were being hypocritical in objecting to the Deloitte partnership because they “do not object to personally having profiles on social media corporations that platform copaganda, or buying goods from retailers employing incarcerated labor in their supply chains, or using technology from corporations providing carceral states with technologies of surveillance.”

When I asked the employees about this, one of them called Kendi’s comments about hypocrisy a “deflection tactic.” She stressed that the staff was not making a demand but asking for an open dialogue — or at least a clearly articulated rationale — about decisions that affected them. His response fit a clear pattern, they thought, of believing that employees were trying to undermine him when they really just cared about the work. “I understand he’s coming from a place of trauma,” another told me. “He’s criticized unfairly and through a racist lens constantly. I do understand it. But then to distort that into an inability to receive feedback that’s going to ensure the success and usefulness of the center — that’s where it becomes a problem.”

In September, Kendi fired 19 of the center’s 36 employees in a series of Zoom meetings. Many told me they could understand the layoffs given the financial climate, but to change the model from an ambitious organization that had pledged to drive social change to one that handed out academic fellowships felt like a betrayal of the mission. The abruptness of the decision forced the staff to scramble to find other homes for projects, including a research program supporting Boston-area organizers on a campaign to challenge family policing in schools, for which they were in the midst of sensitive interviews with affected parents and caregivers. Breaking promises they’d made to grass-roots partners was what bothered her team most, said DeCruz, the head of the Advocacy office, because equitable and sustained relationships between communities and advocates build a strong network — a movement aligned on its goals. Pulling out damaged those relationships.

Though some staff members told me they appreciated Kendi — “My life forever, forever changed because I worked for someone who pushed me to envision what’s possible,” one said — many others had become darkly cynical about him. The most vocal among them was Grundy, who took to Twitter calling Kendi a “grifter” and fueling the rumor that he might have stolen funds. Redwood tried to have empathy. She imagined what it must be like to be constantly attacked — to have your intelligence insulted, your motives questioned. “I wonder if some of the secrecy and paranoid behavior came about as a result of that,” she told me. “I have no idea, and I had to just eventually stop trying to figure it out and just move on, because I couldn’t understand how the person I met when he was at American, when I sat down with him for lunch, the person who appeared to be so humble, so committed — and I still think he is committed — could be the person that I worked for. It is not something that I have ever been able to understand.”

Several people stressed to me that Kendi’s weaknesses as a leader were not as important as the larger forces that surrounded his leadership — the opportunism of white-led institutions, the boom and bust of trend-chasing nonprofit funding, the commodification of Black thought and activism. I asked Boston University to comment on a complaint I heard from the staff, that its administration had failed to provide adequate oversight. “Boston University provided significant financial and administrative support to Dr. Kendi and the center. Dr. Kendi did not always accept the support,” a spokesperson wrote. “In hindsight, and with the fuller knowledge of the organizational problems that arose, the university should have done more to insist on additional oversight.”

The spokesperson also said that the decision to end the center’s projects was Kendi’s choice. “Several different models were discussed with Dr. Kendi, including bringing many of the projects to completion over the next two years and lessening the impact on staff,” he wrote. “However, Dr. Kendi’s preference was to terminate the ongoing projects and ask the funders to repurpose the funds for his new endeavor.” (In a written response, Kendi accused the interim university administration of trying to undermine the center’s work. “The center has faced more oversight and scrutiny than every other center at B.U. from the Office of Research and this interim B.U. administration,” he wrote. “I’m disappointed that this interim B.U. administration is giving The Times a version of events that doesn’t reconcile with the facts.”)

The last time I saw Kendi in person was in January, when he came to New York to promote his newest book, a young readers’ adaptation of Zora Neale Hurston’s “Barracoon,” based on her 1927 interviews with Cudjo Lewis, one of the last survivors of the Middle Passage from Africa. That night, Kendi was doing an event at an independent bookstore in Brooklyn Heights, where the streets were salt-streaked after a light snowstorm and white string lights glowed on a tree outside. One of the three personal-security officers he brought with him — bearded Black men in black peacoats and dress pants, fitted with earpieces — was checking bags at the door.

Kendi was standing by a wall of books in a teal blazer, his pocket square in place. For a while, he said, he stopped doing many public events because of his security concerns, but he realized it had contributed to his feeling alienated and embattled. “Not doing live book signings prevented me from engaging with the people who were reading and appreciating my work,” he told me later. Going on tour again had “helped tremendously,” he said. But he didn’t want to be away from home long while Sadiqa was in treatment. “It’s incredibly difficult to witness someone you care about deeply facing so much pain and loss,” he said. “I’d much rather just be the one facing that pain.”

Boston University had cleared him and the center of grant mismanagement, but he was still waiting for Korn Ferry, the management consulting firm hired by the administration, to finish its culture inquiry, and he continued to attribute any dysfunction at the center to the hardships of the pandemic and employees who repeatedly contested his leadership. He was coordinating with the university on the center’s next phase, he said, but the work that felt most meaningful to him at the moment was “getting back to my roots as a writer.” He was at work on his next big project, a contemporary political history.

Kendi has spun out 13 books since “How to Be an Antiracist” in 2019, 10 of which are adaptations of his or others’ work for children. Since becoming a father, he told me, it has become even more important to him to reach young readers — particularly Black kids like him who may have internalized racist ideas about themselves. Earlier that day, Kendi spoke to 250 kids at a middle school elsewhere in Brooklyn, taking questions from a panel of seventh and eighth graders. “Barracoon” was the latest in a series of books he was adapting by Hurston, the Harlem Renaissance ethnographer he has called the “greatest antiracist novelist of the interwar era.” “I wanted it to read like a grandparent sharing their difficult life story with care and love to their grandchild,” Kendi wrote on Instagram.

During the talk, Kendi told the audience that there are some Black people who, from the way they maneuver in the world, you can tell are spiritual maroons. “This is the person who truly is living and navigating from the standpoint of a freedom,” he said. “They’re unafraid or not worried at all about the white gaze. They’re operating and navigating the world based on their own destiny, based on what they want.” Hurston, who traveled throughout the South, Jamaica and Haiti collecting folklore from the descendants of slaves, was one of those people, Kendi said.

Listening to him, I wondered how often he felt like one of them, too. I got the impression that Kendi spent a lot of time in his head, in that defensive pose, anticipating or parrying attacks from his critics. When I asked him later where he and Sadiqa had gone on vacation over the New Year holiday, he declined even to name the country for fear that “bad-faith people” would try to figure out where they had stayed and how much their hotel room cost. I told him it seemed as though he devoted a lot of thought to how something he said or did could be used against him by the least generous person on the internet. “I certainly don’t want to provide fodder for it,” he told me.

Kendi is right that there’s a mess of misinformation about what he believes. He has become a cipher for the unfinished national conversation about the post-George Floyd moment — the outrage and wild hope of the protests, the reactionary anger, the disillusionment. In tying together racism’s two senses — the personal and the systemic — Kendi has helped many more Americans understand that they are responsible not only for the ideas in their heads but also for the impact they have on the world. But this gap between intention and action, so core to his thinking, is where all the hard work takes place, DeCruz told me. That’s where organizing and movement-building happens, where you practice the kind of world you want to live in. “Having a shared language is important,” she said, but “it’s just the first step.”

Read by January LaVoy

Narration produced by Emma Kehlbeck and Krish Seenivasan

Engineered by David Mason

Rachel Poser is a story editor for the magazine. She has previously written about whiteness in classical studies, sting operations and the charms of paleoart. Wayne Lawrence is a visual artist in Brooklyn and Detroit whose work is focused on community and purpose. His work is in the permanent collection of the Smithsonian’s National Museum of African American History and Culture.

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4 surprising ways to find happiness, according to studies

In an ageing world, social connections are crucial. Image:  Unsplash/Melanie Stander

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• There are ‘hacks’ to happiness, a university study has found.
• Having a sense of meaning is more important than pleasure, another study found.
• Social connections that prevent loneliness are crucial for happiness in our ageing world, according to a World Economic Forum initiative.

We all want to be happy, but achieving happiness can feel far from straightforward.

Could science help us?

Yes, according to studies. One research programme found that there are seven ‘hacks’ to being happy, another discovered that purpose is more important than pleasure, while a third revealed that spending time among birdlife is the answer.

As the World Happiness Report 2024 reveals the countries with the happiest citizens , here are four facts about happiness which may surprise you.

Have you read?

A generation adrift: why young people are less happy and what we can do about it, charted: the happiest countries in the world, why wellbeing and happiness hold the key to a healthy ageing society in japan, 1. hack your way to happiness.

There are seven “happiness hacks” , according to a study by the University of Bristol, in the UK.

The Science of Happiness programme questioned 228 psychology undergraduates who had taken a positive psychology course.

Immediately after taking the course, the students reported a 10-15% improvement in their wellbeing, while researchers found that, by continuing to practise the activities they had been taught, more than half the group maintained their positive outlook one to two years afterwards .

Dr Bruce Hood, senior author of the study, has identified seven “happiness hacks”. In case you want to try them out for yourself, they are:

• Performing acts of kindness
• Increasing social connections, including initiating conversations with people you don’t know
• Savouring experiences
• Deliberately drawing attention to the positive events and aspects of the day
• Practising feeling grateful, and endeavouring to thank people
• Being physically active
• Exploring mindfulness and other meditation techniques.

One in four people will experience mental illness in their lives, costing the global economy an estimated $6 trillion by 2030.

Mental ill-health is the leading cause of disability and poor life outcomes in young people aged 10–24 years, contributing up to 45% of the overall burden of disease in this age-group. Yet globally, young people have the worst access to youth mental health care within the lifespan and across all the stages of illness (particularly during the early stages).

In response, the Forum has launched a global dialogue series to discuss the ideas, tools and architecture in which public and private stakeholders can build an ecosystem for health promotion and disease management on mental health.

One of the current key priorities is to support global efforts toward mental health outcomes - promoting key recommendations toward achieving the global targets on mental health, such as the WHO Knowledge-Action-Portal and the Countdown Global Mental Health

Read more about the work of our Platform for Shaping the Future of Health and Healthcare , and contact us to get involved.

2. Purpose rather than pleasure is the key to happiness

When it comes to being happy, having a sense of meaning in life is more important than pleasure , according to a study by the ESCP Business School.

The research investigated how pleasure, meaning and spirituality affected life satisfaction levels in 2,615 people spread across six continents and representing different cultural contexts.

And they discovered that meaning is a stronger predictor of life satisfaction than pleasure and spirituality.

The study’s authors, writing in a World Economic Forum piece, said the findings could be valuable for bosses looking for new ways to enhance staff wellbeing. Managers “could benefit from widening their focus on pleasure-based benefits such as financial rewards, to include giving employees a sense of meaning , by volunteering their time, for example,” they said.

3. Just seeing or hearing birds can make you happier

Achieving happiness, or at least an improvement in your sense of well-being, doesn’t have to be complicated, it turns out.

A King’s College London study discovered “ significant positive associations between seeing or hearing birds and mental wellbeing ”.

Using an app, more than 1,200 people from around the world “were prompted at random intervals to record how they were feeling, including whether they were happy or stressed , whether they could see trees, and whether they could see or hear birds,” reports The Guardian.

And it turns out that everyday encounters with birdlife can be linked to “time-lasting improvements in mental well-being”. What’s more, say the study’s authors, “these improvements were evident not only in healthy people but also in those with a diagnosis of depression, the most common mental illness across the world”.

4. Good relationships make us happy – and live longer

Harvard University researchers have spent 85 years trying to scientifically prove what makes us happy. And they think they’ve found the answer – being sociable.

The study focused on 724 participants, from adolescence to old age. Regardless of material wealth, physical health or job status, what was striking over the course of the project was that people with strong, supportive relationships were found to be happier , healthier and live longer than those without.

The study also found that “social fitness” – the ability to build and maintain strong relationships – was more important to a long and happy life than genes, social class, or IQ.

“Personal connection creates mental and emotional stimulation, which are automatic mood boosters ,” said the project’s director, Dr Waldinger, “while isolation is a mood buster.”

Isolation is one of the challenges facing our ageing population. To that end, the Forum has developed six ‘longevity economy’ principles .

Principle five is to ‘ Design systems and environments for social connection and purpose ’. “Social connection is integral to healthy longevity,” says the report. “Socially isolated older adults have a higher risk of poor health and earlier death. Intentional design of systems and environments for social connection can mitigate these impacts,” it says.

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License and Republishing

World Economic Forum articles may be republished in accordance with the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License, and in accordance with our Terms of Use.

The views expressed in this article are those of the author alone and not the World Economic Forum.

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The state of AI in early 2024: Gen AI adoption spikes and starts to generate value

If 2023 was the year the world discovered generative AI (gen AI) , 2024 is the year organizations truly began using—and deriving business value from—this new technology. In the latest McKinsey Global Survey  on AI, 65 percent of respondents report that their organizations are regularly using gen AI, nearly double the percentage from our previous survey just ten months ago. Respondents’ expectations for gen AI’s impact remain as high as they were last year , with three-quarters predicting that gen AI will lead to significant or disruptive change in their industries in the years ahead.

About the authors

This article is a collaborative effort by Alex Singla , Alexander Sukharevsky , Lareina Yee , and Michael Chui , with Bryce Hall , representing views from QuantumBlack, AI by McKinsey, and McKinsey Digital.

Organizations are already seeing material benefits from gen AI use, reporting both cost decreases and revenue jumps in the business units deploying the technology. The survey also provides insights into the kinds of risks presented by gen AI—most notably, inaccuracy—as well as the emerging practices of top performers to mitigate those challenges and capture value.

AI adoption surges

Interest in generative AI has also brightened the spotlight on a broader set of AI capabilities. For the past six years, AI adoption by respondents’ organizations has hovered at about 50 percent. This year, the survey finds that adoption has jumped to 72 percent (Exhibit 1). And the interest is truly global in scope. Our 2023 survey found that AI adoption did not reach 66 percent in any region; however, this year more than two-thirds of respondents in nearly every region say their organizations are using AI. 1 Organizations based in Central and South America are the exception, with 58 percent of respondents working for organizations based in Central and South America reporting AI adoption. Looking by industry, the biggest increase in adoption can be found in professional services. 2 Includes respondents working for organizations focused on human resources, legal services, management consulting, market research, R&D, tax preparation, and training.

Also, responses suggest that companies are now using AI in more parts of the business. Half of respondents say their organizations have adopted AI in two or more business functions, up from less than a third of respondents in 2023 (Exhibit 2).

Gen AI adoption is most common in the functions where it can create the most value

Most respondents now report that their organizations—and they as individuals—are using gen AI. Sixty-five percent of respondents say their organizations are regularly using gen AI in at least one business function, up from one-third last year. The average organization using gen AI is doing so in two functions, most often in marketing and sales and in product and service development—two functions in which previous research  determined that gen AI adoption could generate the most value 3 “ The economic potential of generative AI: The next productivity frontier ,” McKinsey, June 14, 2023. —as well as in IT (Exhibit 3). The biggest increase from 2023 is found in marketing and sales, where reported adoption has more than doubled. Yet across functions, only two use cases, both within marketing and sales, are reported by 15 percent or more of respondents.

Gen AI also is weaving its way into respondents’ personal lives. Compared with 2023, respondents are much more likely to be using gen AI at work and even more likely to be using gen AI both at work and in their personal lives (Exhibit 4). The survey finds upticks in gen AI use across all regions, with the largest increases in Asia–Pacific and Greater China. Respondents at the highest seniority levels, meanwhile, show larger jumps in the use of gen Al tools for work and outside of work compared with their midlevel-management peers. Looking at specific industries, respondents working in energy and materials and in professional services report the largest increase in gen AI use.

Investments in gen AI and analytical AI are beginning to create value

The latest survey also shows how different industries are budgeting for gen AI. Responses suggest that, in many industries, organizations are about equally as likely to be investing more than 5 percent of their digital budgets in gen AI as they are in nongenerative, analytical-AI solutions (Exhibit 5). Yet in most industries, larger shares of respondents report that their organizations spend more than 20 percent on analytical AI than on gen AI. Looking ahead, most respondents—67 percent—expect their organizations to invest more in AI over the next three years.

Where are those investments paying off? For the first time, our latest survey explored the value created by gen AI use by business function. The function in which the largest share of respondents report seeing cost decreases is human resources. Respondents most commonly report meaningful revenue increases (of more than 5 percent) in supply chain and inventory management (Exhibit 6). For analytical AI, respondents most often report seeing cost benefits in service operations—in line with what we found last year —as well as meaningful revenue increases from AI use in marketing and sales.

Inaccuracy: The most recognized and experienced risk of gen AI use

As businesses begin to see the benefits of gen AI, they’re also recognizing the diverse risks associated with the technology. These can range from data management risks such as data privacy, bias, or intellectual property (IP) infringement to model management risks, which tend to focus on inaccurate output or lack of explainability. A third big risk category is security and incorrect use.

Respondents to the latest survey are more likely than they were last year to say their organizations consider inaccuracy and IP infringement to be relevant to their use of gen AI, and about half continue to view cybersecurity as a risk (Exhibit 7).

Conversely, respondents are less likely than they were last year to say their organizations consider workforce and labor displacement to be relevant risks and are not increasing efforts to mitigate them.

In fact, inaccuracy— which can affect use cases across the gen AI value chain , ranging from customer journeys and summarization to coding and creative content—is the only risk that respondents are significantly more likely than last year to say their organizations are actively working to mitigate.

Some organizations have already experienced negative consequences from the use of gen AI, with 44 percent of respondents saying their organizations have experienced at least one consequence (Exhibit 8). Respondents most often report inaccuracy as a risk that has affected their organizations, followed by cybersecurity and explainability.

Our previous research has found that there are several elements of governance that can help in scaling gen AI use responsibly, yet few respondents report having these risk-related practices in place. 4 “ Implementing generative AI with speed and safety ,” McKinsey Quarterly , March 13, 2024. For example, just 18 percent say their organizations have an enterprise-wide council or board with the authority to make decisions involving responsible AI governance, and only one-third say gen AI risk awareness and risk mitigation controls are required skill sets for technical talent.

Bringing gen AI capabilities to bear

The latest survey also sought to understand how, and how quickly, organizations are deploying these new gen AI tools. We have found three archetypes for implementing gen AI solutions : takers use off-the-shelf, publicly available solutions; shapers customize those tools with proprietary data and systems; and makers develop their own foundation models from scratch. 5 “ Technology’s generational moment with generative AI: A CIO and CTO guide ,” McKinsey, July 11, 2023. Across most industries, the survey results suggest that organizations are finding off-the-shelf offerings applicable to their business needs—though many are pursuing opportunities to customize models or even develop their own (Exhibit 9). About half of reported gen AI uses within respondents’ business functions are utilizing off-the-shelf, publicly available models or tools, with little or no customization. Respondents in energy and materials, technology, and media and telecommunications are more likely to report significant customization or tuning of publicly available models or developing their own proprietary models to address specific business needs.

Respondents most often report that their organizations required one to four months from the start of a project to put gen AI into production, though the time it takes varies by business function (Exhibit 10). It also depends upon the approach for acquiring those capabilities. Not surprisingly, reported uses of highly customized or proprietary models are 1.5 times more likely than off-the-shelf, publicly available models to take five months or more to implement.

Gen AI high performers are excelling despite facing challenges

Gen AI is a new technology, and organizations are still early in the journey of pursuing its opportunities and scaling it across functions. So it’s little surprise that only a small subset of respondents (46 out of 876) report that a meaningful share of their organizations’ EBIT can be attributed to their deployment of gen AI. Still, these gen AI leaders are worth examining closely. These, after all, are the early movers, who already attribute more than 10 percent of their organizations’ EBIT to their use of gen AI. Forty-two percent of these high performers say more than 20 percent of their EBIT is attributable to their use of nongenerative, analytical AI, and they span industries and regions—though most are at organizations with less than $1 billion in annual revenue. The AI-related practices at these organizations can offer guidance to those looking to create value from gen AI adoption at their own organizations.

To start, gen AI high performers are using gen AI in more business functions—an average of three functions, while others average two. They, like other organizations, are most likely to use gen AI in marketing and sales and product or service development, but they’re much more likely than others to use gen AI solutions in risk, legal, and compliance; in strategy and corporate finance; and in supply chain and inventory management. They’re more than three times as likely as others to be using gen AI in activities ranging from processing of accounting documents and risk assessment to R&D testing and pricing and promotions. While, overall, about half of reported gen AI applications within business functions are utilizing publicly available models or tools, gen AI high performers are less likely to use those off-the-shelf options than to either implement significantly customized versions of those tools or to develop their own proprietary foundation models.

What else are these high performers doing differently? For one thing, they are paying more attention to gen-AI-related risks. Perhaps because they are further along on their journeys, they are more likely than others to say their organizations have experienced every negative consequence from gen AI we asked about, from cybersecurity and personal privacy to explainability and IP infringement. Given that, they are more likely than others to report that their organizations consider those risks, as well as regulatory compliance, environmental impacts, and political stability, to be relevant to their gen AI use, and they say they take steps to mitigate more risks than others do.

Gen AI high performers are also much more likely to say their organizations follow a set of risk-related best practices (Exhibit 11). For example, they are nearly twice as likely as others to involve the legal function and embed risk reviews early on in the development of gen AI solutions—that is, to “ shift left .” They’re also much more likely than others to employ a wide range of other best practices, from strategy-related practices to those related to scaling.

In addition to experiencing the risks of gen AI adoption, high performers have encountered other challenges that can serve as warnings to others (Exhibit 12). Seventy percent say they have experienced difficulties with data, including defining processes for data governance, developing the ability to quickly integrate data into AI models, and an insufficient amount of training data, highlighting the essential role that data play in capturing value. High performers are also more likely than others to report experiencing challenges with their operating models, such as implementing agile ways of working and effective sprint performance management.

About the research

The online survey was in the field from February 22 to March 5, 2024, and garnered responses from 1,363 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of those respondents, 981 said their organizations had adopted AI in at least one business function, and 878 said their organizations were regularly using gen AI in at least one function. To adjust for differences in response rates, the data are weighted by the contribution of each respondent’s nation to global GDP.

Alex Singla and Alexander Sukharevsky  are global coleaders of QuantumBlack, AI by McKinsey, and senior partners in McKinsey’s Chicago and London offices, respectively; Lareina Yee  is a senior partner in the Bay Area office, where Michael Chui , a McKinsey Global Institute partner, is a partner; and Bryce Hall  is an associate partner in the Washington, DC, office.

They wish to thank Kaitlin Noe, Larry Kanter, Mallika Jhamb, and Shinjini Srivastava for their contributions to this work.

This article was edited by Heather Hanselman, a senior editor in McKinsey’s Atlanta office.

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How Trump's definition of a 'real' American has grabbed his audience—what our research shows about why

D onald Trump has recently doubled down on his derogatory depictions of undocumented migrants in his bid to win the 2024 presidential election. In an interview with Time magazine , published on April 30 2024, Trump referred to migrants as "criminals," who "come in and they steal our jobs, and steal our wealth, and they steal our country." Trump was especially disparaging towards migrants from China, who he said are a "major force that's forming in our country." In short, according to Trump, undocumented migration is "an invasion of our country."

Trump's recent anti-migrant rhetoric is particularly inflammatory, but it is not new. It has been Trump's calling card since he entered the political fray. For example, in his first speech announcing his candidacy for the 2016 presidency, Trump infamously referred to Mexicans migrants saying, they are "bringing drugs, they are bringing crime and they are rapists" . Why does Trump use this kind of negative rhetoric to refer to migrants? Because it works as an electoral strategy. It has been especially successful in cultivating support from Trump's core voting base: white, working-class Americans.

A recent aggregate analysis of leading polls shows Trump 13.7 percentage points ahead of Biden among white voters . This electoral advantage is even greater among white Americans without college degrees, among whom 60% prefer Trump . So, while many observers have noted Trump's recent gains with black and Hispanic voters as a key dynamic to watch in the 2024 election, his support remains firmly rooted in white America.

How has a billionaire from New York City managed to cultivate such strong support among working-class Americans? This has been a question many have asked since Trump's win in 2016. In response, most have pointed to his populist style and his ability to tap into the grievances of those who fear a perceived growth in "woke" politics, or who see themselves as left behind by globalization. Our take is slightly different.

Our in-depth research on Trump's 2016 and 2020 campaigns shows that Trump's support stems from his ability to tap into an "ethno-nationalist" tradition of American identity in his campaign rhetoric. This tradition of American identity is based on a set of criteria (including being white, Christian, native-born, and English-speaking) to define who is a "real" American, and who is not. Trump uses this vision of American identity to garner support from white Americans by campaigning on the idea that he will defend them from the threat posed by people who are not perceived as real Americans—particularly the ostensible threat posed by undocumented migrants.

Trump's shifting support

How does our argument that Trump's support is based on an ethno-nationalist ideology that speaks to white Americans square with the fact he has recently been growing his support among people of color—the so-called racial realignment in US politics ?

While seemingly paradoxical, Trump's messaging could also explain why he is gaining support from some Latino and Hispanic Americans. As others have shown, Trump's support among people of color is not proof that race doesn't matter in America—quite the opposite. People of color who support Trump tend to have conservative views on race and migration. . Trump's recent doubling down on anti-migrant messaging picks up and reinforces these views. He is speaking to both his white voting base and a minority of people of color who hold conservative views about migration and racial problems in the US. This helps understand how he is cultivating support from ethnic minorities because of—not in spite of—his messaging.

Interestingly, even though ethno-nationalism is central to Trump's campaign rhetoric, he tends to avoid explicitly referring to it. Presumably this tactic reflects a desire to continue to build his support among people of color as well as white Americans, while also avoiding charges of outright racism. For example, he rarely defends white Americans directly, although there are indications that he is increasingly willing to do so)—for example, at a rally in Arizona in 2022, he claimed that "white people" were being "denigrated" and discriminated against when they tried to seek "life-saving therapeutics."

Instead, Trump tends to heavily rely upon thinly veiled speech codes known as "dog whistles" to implicitly refer to them. This is what he is doing when he says he is standing up for the "silent majority" and "forgotten men and women" , or when he claims he will protect "suburban housewives" from the threat of illegal migrants . The examples of Trump invoking these messages are countless now—we all know what he says, how he says it, and who he is taking about.

But why is Trump's use of this type of rhetoric so effective at winning support? In short, it is because it is not new. There is a long tradition of ethno-nationalism in American politics, as we discuss in our recent book . The idea at the heart of the founding documents of the US, such as the Bill of Rights—which outlines how all Americans should have equal rights regardless of their ethnic, racial, or religious backgrounds—has long been countered by the idea that America is first and foremost a white, Christian nation.

This alternative conception of America has periodically gained force among white Americans during times of heightened anxiety over their perceived loss of status, for example in relation to the emancipation of formerly enslaved black Americans or—as we are seeing today—in response to migration. Trump draws directly on this long tradition, while also adapting it so that it resonates with contemporary anxieties. Trump may be the most successful defender of this tradition of American identity in recent memory, but he is not the first.

But, as much as Trump's campaign strategy has been remarkably effective in building his base, it is also inherently limiting. This is because many Americans—including many white Americans—reject this tradition of American identity in favor of a more inclusive one which is more closely aligned with the founding documents. This tradition underpinned Biden's 2020 campaign . This is the "soul of the nation" Biden says he is trying to save.

Seen from this perspective—in which the two presumed candidates are drawing on diametrically opposed visions of American national identity—it is not surprising that Trump has not been able to meaningfully increase his support. And here Trump is faced with a puzzle as he ramps up his 2024 campaign: the very ideology that has enabled him to make a powerful connection with his base is just as powerfully repellent to many other Americans.

This article is republished from The Conversation under a Creative Commons license. Read the original article .

Provided by The Conversation

Trump Is a Convicted Felon. Does That Actually Mean Anything?

He cannot serve on a jury. bu law experts explain what rights the former president may or may not see restricted and how that could affect a trump presidency.

In a historic ruling, a New York jury found former President Donald J. Trump guilty on 34 counts of falsifying business records, marking the first criminal conviction of a US president. The legal repercussions are still to be determined, but two BU School of Law experts don’t expect much to stick. Photo by Jabin Botsford/The Washington Post via AP

Alene Bouranova

When a New York jury found former President Donald J. Trump guilty of 34 counts of falsifying business records in the first degree, it was historic for a number of reasons. The guilty verdicts represent the first-ever criminal conviction of a former president, and they make Trump the second person to campaign for president as a convicted felon. (The first was Eugene V. Debs, the Socialist Party candidate who famously ran for president from a jail cell in the 1920 election.) Trump’s sentencing is expected in early July.

Trump is currently the front-runner as the Republican candidate for the presidency. No law exists that bars a felon from running for president. But will the reality of having a criminal record complicate Trump’s bid for the Oval Office?

BU Today spoke to two criminal law experts from the School of Law, Shira Diner , a lecturer and instructor in LAW’s Defender Clinic , and Angelo Petrigh , a clinical associate professor and fellow Defender Clinic instructor, about what a felony conviction means for the former president and probable Republican presidential candidate. 

The bottom line? It likely doesn’t mean much, Diner and Petrigh, both longtime public defenders, say. 

“A lot of the negative consequences of getting a felony [conviction] really aren’t going to apply to Trump because of his wealth and status,” Petrigh says.

Normally, a felony conviction is a big deal, he says. It can prevent individuals from receiving government assistance like public housing and can impact job and loan applications. But, “none of those things are going to affect Donald Trump, because his wealth isolates him from those consequences,” Petrigh says. Even Trump’s right to vote will likely not be impacted, he notes: Florida, where Trump is a resident, prevents felons from voting. However, if an individual wasn’t convicted in Florida, the state defers to the law in the state where the individual was convicted. New York allows non-incarcerated felons to vote. Florida Governor Ron DeSantis, a Republican, has said he would allow Trump to vote.

If there will be any complication from his conviction, it will come from the punishment. The judge’s sentencing will ultimately determine his fate. On the severe end, his conviction could translate to up to four years in prison. On the lighter end, it could mean no jail time and being put on probation. 

In the case of the latter, the judge would impose a set of conditions on Trump. “A major feature of probation is that instead of sending someone to prison, you rehabilitate them,” Diner explains. “The way to do that, theoretically, is to set very specific restrictions on what someone can’t do, or what they must do, and a judge has a ton of discretion in setting those conditions.”

What those conditions could be—and whether they would have any bearing on the election—remains to be seen, Diner says. Read more about potential consequences of Trump’s conviction below.

These interviews have been condensed and edited for clarity.

With Shira Diner and Angelo Petrigh

Bu today: so, what are some of the consequences of being convicted of a felony.

Shira Diner: Donald Trump is in a different position from many people convicted of crimes, because he has resources. For people who don’t have resources, being convicted of a felony can mean losing government assistance—like SNAP benefits or FAFSA help, depending on the type of conviction—and housing benefits, and can have real implications for people in applying for jobs. A felony conviction can have consequences for professional licenses, such a broker’s or a medical license. There are also implications for someone who isn’t a US citizen and is convicted of a felony, and for those in armed forces service.  These are not immediate problems for Trump. But once you’re convicted of a felony, that is a stigma you have to carry around forever. Felons can’t serve on juries. And states are allowed to set restrictions on felons voting. The law in Florida, where Trump is a resident, states that convicted felons are not allowed to vote. [However, because his conviction was in New York, it is likely that Trump would still be allowed to vote.]

BU Today: Is there any chance Trump could go to jail?

Angelo Petrigh: It’s not without precedent that somebody convicted of a nonviolent felony for the first time could get a jail sentence, so it’s certainly not impossible. But I would be very surprised if that happened here given the facts of the case: it’s not only a nonviolent offense, but it’s not the sort of circumstances where someone was defrauded of money. And then there’s obviously the fact that he’s not just a wealthy man, but a former president who’s running for president again. I can’t imagine a judge would want to have to justify a partial sentence. It’s already been a set of historic circumstances to have a former president indicted and then convicted. To deviate from what the sentencing expectation is—which I think is probation—would mean really sticking your neck out as a judge.

BU Today: What do you think probation for Trump could look like?

Diner: The judge can be as creative as they want. In theory, probation could absolutely have an impact on Trump’s ability to campaign. Conditions of probation that restrict travel have been upheld as constitutional, as long as they are somehow related to the probation goals. The judge could also say that Trump could be restricted from engaging in certain monetary transactions, which I’ve seen happen when people are convicted of financial crimes like insider trading. I don’t think the judge would set a condition that he can’t talk to the press or can’t continue campaigning, but who knows? Regardless, probation becomes a very intrusive way of policing people even when they’re not in custody. There’s a very limited expectation of privacy when you’re on probation.  Petrigh: Probation comes with a lot of conditions, both automatic conditions and those that are discretionary for a probation officer. In theory, you could be subject to travel restrictions. You’ll be prevented from owning a firearm, and potentially prevented from associating with certain people convicted of felonies. But I imagine probation for Trump would include exceptions and not prevent him from leaving the state to go on the campaign trail, or associating with members of his staff who have felonies—which is an overwhelming majority at this point. The other aspect I’ve seen come up is that Trump can go on Truth Social and get nine million people to say that his probation officer is a fascist. No probation officer is going to go out of their way to enact any sort of meaningful interference with Trump running his campaign, because of the stakes.

BU Today: If Trump gets elected to the presidency, could probation continue into the White House?

Petrigh: I think the probation sentence would basically be terminated if he was elected. Social media has been abuzz about things like, can he command the army when he can’t possess a firearm? I don’t think those things have any realistic possibility. It just becomes too much of a headache. I don’t think being the commander-in-chief will ever be restrained by something like a state probation sentence for an unrelated offense. That comes with constitutional issues: even if New York tried to enforce probation conditions, I feel like federal courts would enjoin any sort of enforcement that limits his ability to carry out the duties that he was elected to do.

BU Today: If nothing else, this case puts a huge spotlight on our criminal justice system. What do you hope this case brings attention to?

Diner: Being convicted of a felony happens all the time, with much more severe implications for others. The implications of not being able to get Section 8 housing if you have a conviction are really significant. So are the ramifications in terms of employment. As I said earlier, there’s a huge stigma attached to being a convicted felon. It just sets up barrier after barrier and makes your life significantly harder, often in a really unfair way.  If I were to try and send a message, what I hope people take from this is the difference in treatment between people with means and people without. The best example I can think of is: Trump walked out of that courtroom, on his own. I tried [and failed] to think about a client of mine who was convicted of a felony at trial and got to walk out of the courtroom after. Even if they weren’t being held on bail pending a trial, they’re almost always taken into custody at that point and have to surrender their passport.  Petrigh: Calling Trump a felon as a dirty word doesn’t serve anyone’s purposes. It’s only going to be used to stigmatize my clients [often convicted felons without means] further. The reality is, if you think Trump was a bad person because of what he did, it’s because of what he did. It’s not because of this scarlet letter that we’ve imposed on people in society. I’d like to destigmatize convictions. Obviously a conviction like this matters. I just don’t want us to escalate the fact that Trump has been convicted into anything that adds to the problem of how much we penalize poor people with convictions, and how much status they lose. These are people that could become members of society again, but we prevent that by placing stigmas on them.

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Alene Bouranova is a Pacific Northwest native and a BU alum (COM’16). After earning a BS in journalism, she spent four years at Boston magazine writing, copyediting, and managing production for all publications. These days, she covers campus happenings, current events, and more for BU Today . Fun fact: she’s still using her Terrier card from 2013. When she’s not writing about campus, she’s trying to lose her Terrier card so BU will give her a new one. She lives in Cambridge with her plants. Profile

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• Patient Care & Health Information
• Diseases & Conditions
• Neurofibromatosis type 1

Neurofibromatosis type 1 (NF1) is a genetic condition that causes changes in skin pigment and tumors on nerve tissue. Skin changes include flat, light brown spots and freckles in the armpits and groin. Tumors can grow anywhere in the nervous system, including the brain, spinal cord and nerves. NF1 is rare. About 1 in 2,500 is affected by NF1.

The tumors often are not cancerous, known as benign tumors. But sometimes they can become cancerous. Symptoms often are mild. But complications can occur and may include trouble with learning, heart and blood vessel conditions, vision loss, and pain.

Treatment focuses on supporting healthy growth and development in children and early management of complications. If NF1 causes large tumors or tumors that press on a nerve, surgery can reduce symptoms. A newer medicine is available to treat tumors in children, and other new treatments are being developed.

Neurofibromatosis type 1 (NF1) usually is diagnosed during childhood. Symptoms are seen at birth or shortly afterward and almost always by age 10. Symptoms tend to be mild to moderate, but they can vary from person to person.

Symptoms include:

• Flat, light brown spots on the skin, known as cafe au lait spots. These harmless spots are common in many people. But having more than six cafe au lait spots suggests NF1. They often are present at birth or appear during the first years of life. After childhood, new spots stop appearing.
• Freckling in the armpits or groin area. Freckling often appears by ages 3 to 5. Freckles are smaller than cafe au lait spots and tend to occur in clusters in skin folds.
• Tiny bumps on the iris of the eye, known as Lisch nodules. These nodules can't easily be seen and don't affect vision.
• Soft, pea-sized bumps on or under the skin called neurofibromas. These benign tumors usually grow in or under the skin but can also grow inside the body. A growth that involves many nerves is called a plexiform neurofibroma. Plexiform neurofibromas, when located on the face, can cause disfigurement. Neurofibromas may increase in number with age.
• Bone changes. Changes in bone development and low bone mineral density can cause bones to form in an irregular way. People with NF1 may have a curved spine, known as scoliosis, or a bowed lower leg.
• Tumor on the nerve that connects the eye to the brain, called an optic pathway glioma. This tumor usually appears by age 3. The tumor rarely appears in late childhood and among teenagers, and almost never in adults.
• Learning disabilities. It's common for children with NF1 to have some trouble with learning. Often there is a specific learning disability, such as trouble with reading or math. Attention-deficit/hyperactivity disorder (ADHD) and speech delay also are common.
• Larger than average head size. Children with NF1 tend to have a larger than average head size due to increased brain volume.
• Short stature. Children who have NF1 often are below average in height.

When to see a doctor

See a healthcare professional if your child has symptoms of neurofibromatosis type 1. The tumors are often not cancerous and are slow growing, but complications can be managed. If your child has a plexiform neurofibroma, a medicine is available to treat it.

Neurofibromatosis type 1 is caused by an altered gene that either is passed down by a parent or occurs at conception.

The NF1 gene is located on chromosome 17. This gene produces a protein called neurofibromin that helps regulate cell growth. When the gene is altered, it causes a loss of neurofibromin. This allows cells to grow without control.

Risk factors

Autosomal dominant inheritance pattern

In an autosomal dominant disorder, the changed gene is a dominant gene. It's located on one of the nonsex chromosomes, called autosomes. Only one changed gene is needed for someone to be affected by this type of condition. A person with an autosomal dominant condition — in this example, the father — has a 50% chance of having an affected child with one changed gene and a 50% chance of having an unaffected child.

The biggest risk factor for neurofibromatosis type 1 (NF1) is a family history. For about half of people who have NF1, the disease was passed down from a parent. People who have NF1 and whose relatives aren't affected are likely to have a new change to a gene.

NF1 has an autosomal dominant inheritance pattern. This means that any child of a parent who is affected by the disease has a 50% chance of having the altered gene.

Complications

Complications of neurofibromatosis type 1 (NF1) vary, even within the same family. Generally, complications occur when tumors affect nerve tissue or press on internal organs.

Complications of NF1 include:

• Neurological symptoms. Trouble with learning and thinking are the most common neurological symptoms associated with NF1. Less common complications include epilepsy and the buildup of excess fluid in the brain.
• Concerns with appearance. Visible signs of NF1 can include widespread cafe au lait spots, many neurofibromas in the facial area or large neurofibromas. In some people this can cause anxiety and emotional distress, even if they're not medically serious.
• Skeletal symptoms. Some children have bones that didn't form as usual. This can cause bowing of the legs and fractures that sometimes don't heal. NF1 can cause curvature of the spine, known as scoliosis, that may need bracing or surgery. NF1 also is associated with lower bone mineral density, which increases the risk of weak bones, known as osteoporosis.
• Changes in vision. Sometimes a tumor called an optic pathway glioma develops on the optic nerve. When this happens, it can affect vision.
• Increase in symptoms during times of hormonal change. Hormonal changes associated with puberty or pregnancy might cause an increase in neurofibromas. Most people who have NF1 have healthy pregnancies but will likely need monitoring by an obstetrician who is familiar with NF1.
• Cardiovascular symptoms. People who have NF1 have an increased risk of high blood pressure and may develop blood vessel conditions.
• Trouble breathing. Rarely, plexiform neurofibromas can put pressure on the airway.
• Cancer. Some people who have NF1 develop cancerous tumors. These usually arise from neurofibromas under the skin or from plexiform neurofibromas. People who have NF1 also have a higher risk of other forms of cancer. They include breast cancer, leukemia, colorectal cancer, brain tumors and some types of soft tissue cancer. Screening for breast cancer should begin earlier, at age 30, for women with NF1 compared to the general population.
• Benign adrenal gland tumor, known as a pheochromocytoma. This noncancerous tumor produces hormones that raise your blood pressure. Surgery often is needed to remove it.

Neurofibromatosis type 1 care at Mayo Clinic

• Ferri FF. Neurofibromatosis. In: Ferri's Clinical Advisor 2024. Elsevier; 2024. https://www.clinicalkey.com. Accessed Feb. 21, 2024.
• Neurofibromatosis. National Institute of Neurological Disorders and Stroke. https://www.ninds.nih.gov/Disorders/Patient-Caregiver-Education/Fact-Sheets/Neurofibromatosis-Fact-Sheet. Accessed Feb. 21, 2024.
• Korf BR, et al. Neurofibromatosis type 1 (NF1): Pathogenesis, clinical features, and diagnosis. https://www.uptodate.com/contents/search. Accessed Feb. 21, 2024.
• Saleh M, et al. Neurofibromatosis type 1 system-based manifestations and treatments: A review. Neurological Sciences. 2023; doi:10.1007/s10072-023-06680-5.
• Neurofibromatosis. American Association of Neurological Surgeons. https://www.aans.org/en/Patients/Neurosurgical-Conditions-and-Treatments/Neurofibromatosis. Accessed Feb. 21, 2024.
• Neurofibromatosis. Merck Manual Professional Version. https://www.merckmanuals.com/professional/pediatrics/neurocutaneous-syndromes/neurofibromatosis. Accessed Feb. 21, 2024.
• Jankovic J, et al., eds. Neurocutaneous syndromes. In: Bradley and Daroff's Neurology in Clinical Practice. 8th ed. Elsevier; 2022. https://www.clinicalkey.com. Accessed Feb. 21, 2024.
• Armstrong AE, et al. Treatment decisions and the use of the MEK inhibitors for children with neurofibromatosis type 1-related plexiform neurofibromas. BMC Cancer. 2023; doi:10.1186/s12885-023-10996-y.
• Zitelli BJ, et al., eds. Neurology. In: Zitelli and Davis' Atlas of Pediatric Physical Diagnoses. 8th ed. Elsevier; 2023. https://www.clinicalkey.com. Accessed Feb. 21, 2024.
• Kellerman RD, et al. Neurofibromatosis (type 1). In: Conn's Current Therapy 2024. Elsevier; 2024. https://www.clinicalkey.com. Accessed Feb. 21, 2024.
• Babovic-Vuksanovic D (expert opinion). Mayo Clinic. March 26, 2024.
• Tamura R. Current understanding of neurofibromatosis type 1, 2 and schwannomatosis. International Journal of Molecular Sciences. 2021; doi:10.3390/ijms22115850.
• Legius E, et al. Revised diagnostic criteria for neurofibromatosis type 1 and Legius syndrome: An international consensus recommendation. Genetics in Medicine. 2021; doi:10.1038/s41436-021-01170-5.
• Find a doctor. Children's Tumor Foundation. https://www.ctf.org/understanding-nf/find-a-doctor/. Accessed Feb. 26, 2024.
• Ami TR. Allscripts EPSi. Mayo Clinic. April 18, 2024.

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