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The Vital Significance of Social Science in Our Daily Lives

Categories: Personal Life Social Science

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Published: Sep 12, 2023

Words: 800 | Pages: 2 | 4 min read

Understanding human behavior, shaping public policy, enhancing personal finance, addressing social issues, fostering global citizenship, enhancing critical thinking and problem-solving, informing personal values and ethics.

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Communication

What is a Social Science Essay?

[Ed. – We present this article, adapted from a chapter of Good Essay Writing: A Social Sciences Guide , as a resource for Academic Writing Month.]

There are different types of social science essay, and essays of different lengths require slightly different approaches (these will be addressed later). However, all social science essays share a basic structure which is common to many academic subject areas. At its simplest, a social science essay looks something like this:

Title | Every essay should begin with the title written out in full. In some cases this will simply be the set question or statement for discussion.

Introduction | The introduction tells the reader what the essay is about.

Main section | The main section, or ‘body’, of the essay develops the key points of the argument in a ‘logical progression’. It uses evidence from research studies (empirical evidence) and theoretical arguments to support these points.

Conclusion | The conclusion reassesses the arguments presented in the main section in order to make a final statement in answer to the question.

List of references | This lists full details of the publications referred to in the text.

What is distinctive about a social science essay?

As you are no doubt aware, essay writing is a common feature of undergraduate study in many different subjects. What, then, is distinctive about essay writing in the social sciences? There are particular features that characterize social science essays and that relate to what is called the epistemological underpinning of work in this area (that is, to ideas about what constitutes valid social scientific knowledge and where this comes from). Among the most important of these characteristics are:

• the requirement that you support arguments with evidence, particularly evidence that is the product of systematic and rigorous research;

• the use of theory to build explanations about how the social world works.

Evidence is important in social scientific writing because it is used to support or query beliefs, propositions or hypotheses about the social world. Let’s take an example. A social scientist may ask: ‘Does prison work?’ This forms an initial question, but one that is too vague to explore as it stands. (This question might be about whether prison ‘works’ for offenders, in terms of providing rehabilitation, or re-education; or it might be about whether it ‘works’ for victims of crime who may wish to see retribution – or any number of other issues.) To answer the question in mind, the social scientist will need to formulate a more specific claim, one that can be systematically and rigorously explored. Such a claim could be formulated in the following terms:

‘Imprisonment reduces the likelihood of subsequent reoffending’. This claim can now be subjected to systematic research. In other words, the social scientist will gather evidence for and against this claim, evidence that she or he will seek to interpret or evaluate. This process of evaluation will tend to support or refute the original claim, but it may be inconclusive, and/or it may generate further questions. Together, these processes of enquiry can be described as forming a ‘circuit of social scientific knowledge’. This circuit can be represented as in this figure.

Undergraduates may sometimes be asked to conduct their own small-scale research, for instance a small number of interviews, or some content analysis. However, the focus of social science study at undergraduate level, and particularly in the first two years of study, will be largely on the research of others. Generally, in preparing for writing your essays, the expectation will be that you will identify and evaluate evidence from existing research findings. However, the principle holds good: in writing social science essays you will need to find evidence for and against any claim, and you will need to evaluate that evidence.

Theory is important in social scientific writing because the theoretical orientation of the social scientist will tend to inform the types of question she or he asks, the specific claims tested, the ways in which evidence is identified and gathered, and the manner in which this evidence is interpreted and evaluated. In other words, the theoretical orientation of the social scientist is liable to impact upon the forms of knowledge she or he will produce.

Take, for example, the research question we asked above: ‘Does prison work?’ A pragmatic, policy-oriented social scientist may seek to answer this question by formulating a specific claim of the sort we identified, ‘Imprisonment reduces the likelihood of reoffending’. She or he may then gather evidence of reoffending rates among matched groups of convicted criminals, comparing those who were imprisoned with those who were given an alternative punishment such as forms of community service. Evidence that imprisonment did not produce significantly lower rates of reoffending than punishment in the community may then be interpreted as suggesting that prison does not work, or that it works only up to a point. However, another social scientist might look at the same research findings and come to a different conclusion, perhaps that the apparent failure of prison to reduce reoffending demonstrates that its primary purpose lies elsewhere. Indeed, more ‘critically’ oriented social scientists (for example, those informed by Marxism or the work of Michel Foucault) have sought to argue that the growth of prisons in the nineteenth century was part of wider social attempts to ‘discipline’, in particular, the working class.

The issue here is not whether these more ‘critical’ arguments are right or wrong but that a social scientist’s theoretical orientation will inform how she or he evaluates the available evidence. In fact, it is likely that a ‘critical’ social scientist of this sort would even have formulated a different research ‘claim’. For example, rather than seeking to test the claim, ‘Imprisonment reduces the likelihood of reoffending’, the critical social scientist might have sought to test the proposition, ‘Prisons are part of wider social strategies that aim to produce “disciplined” subjects’. The point for you to take away from this discussion is, then, that the theories we use shape the forms of social scientific knowledge we produce (see Figure 2).

There is considerable debate within the social sciences about the exact relationship between theory and evidence. To simplify somewhat, some social scientists tend to argue that evidence can be used to support or invalidate the claims investigated by research and thereby produce theoretical accounts of the social world that are more or less accurate. Other social scientists will tend to argue that our theoretical orientations (and the value judgements and taken-for-granted assumptions that they contain) shape the processes of social scientific enquiry itself, such that we can never claim to produce a straightforwardly ‘accurate’ account of the social world. Instead, they suggest that social scientific knowledge is always produced from a particular standpoint and will inevitably reflect its assumptions.

What you need to grasp is that essay writing in the social sciences is distinguished by its emphasis on: the use of researched evidence to support arguments and on theory as central to the process by which we build accounts of social worlds. Your own writing will need to engage with both elements.

Common errors in essays

Having identified what distinguishes a social science essay we can return to the more practical task of how to write one. This process is elaborated in the chapters that follow, but before getting into the details of this, we should think about what commonly goes wrong in essay writing.

Perhaps the most common mistakes in essay writing, all of which can have an impact on your marks, are:

• failure to answer the question;

• failure to write using your own words;

• poor use of social scientific skills (such as handling theory and evidence);

• poor structure;

• poor grammar, punctuation and spelling; and

• failure to observe the word limit (where this is specified).

Failing to answer the question sounds easy enough to avoid, but you might be surprised how easy it is to write a good answer to the wrong question. Most obviously, there is always the risk of misreading the question. However, it is frequently the case that questions will ‘index’ a wider debate and will want you to review and engage with this. Thus, you need to avoid the danger of understanding the question but failing to connect it to the debate and the body of literature to which the question refers. Equally, particularly on more advanced undergraduate courses, you are likely to be asked to work from an increasing range of sources. The dangers here include failing to select the most relevant material and failing to organize the material you have selected in a way that best fits the question. Therefore, make sure that you take time to read the question properly to ensure that you understand what is being asked. Next, think carefully about whether there is a debate that ‘lies behind’ the question. Then be sure to identify the material that addresses the question most fully.

Writing in your own words is crucial because this is the best way in which you can come to understand a topic, and the only way of demonstrating this understanding to your tutor. The important point to remember is that if you do plagiarize, your essay risks receiving a fail grade, and if you plagiarize repeatedly you risk further sanctions. You must therefore always put arguments in your own words except when you are quoting someone directly (in which case you must use the appropriate referencing conventions). The positive side of what might seem like a draconian rule is that you will remember better what you have put in your own words. This ensures that you will have the fullest possible understanding of your course. If there is an end-of-course exam, such an understanding will be a real asset.

Social science essays also need to demonstrate an effective use of social scientific skills. Perhaps the most obvious of these skills is the ability to deploy theory and evidence in an appropriate manner (as you saw in the previous section, this is what distinguishes social scientific essay writing). However, particularly as you move on to more advanced undergraduate courses, you should also keep in mind the need to demonstrate such things as confidence in handling social scientific concepts and vocabulary; an awareness of major debates, approaches and figures in your field; the ability to evaluate competing arguments; and an awareness of potential uncertainty, ambiguity and the limits of knowledge in your subject. These are important because they indicate your ability to work creatively with the tools of the social scientist’s trade.

An effective structure is important and pragmatic because it helps the person who marks your essay to understand what is going on. By contrast, a list of unconnected ideas and examples is likely to confuse, and will certainly fail to impress. The simplest way to avoid this is to follow the kind of essay writing conventions briefly outlined above and discussed in later chapters of this guide. Chapter 8, on the main body of the essay, is particularly relevant here, but you will also need to keep in mind the importance of a well-written introduction and conclusion to an effectively structured argument.

The ability to spell, punctuate and use grammar correctly is, generally speaking, something you are expected to have mastered prior to embarking on a degree-level course. This is really a matter of effective communication. While it is the content of your essay that will win you the most marks, you need to be able spell, punctuate and use grammar effectively in order to communicate what you have to say. Major problems in this area will inevitably hold down your marks, so if this is an issue in your work, it will be a good idea to seek further help.

Finally, observing the word limit is important – and, as you probably realize, more difficult than it sounds. The simplest advice is always to check whether there is a word limit and what this is, and then to be ruthless with yourself, focusing only on the material that is most pertinent to the question. If you find that you have written more words than is allowed, you will need to check for irrelevant discussions, examples, or even wordy sentence construction. Too few words may indicate that you haven’t provided the depth of discussion required, or that you have omitted essential points or evidence.

In the light of the above, we can identify four golden rules for effective social scientific essay writing.

Rule 1: Answer the question that is asked.

Rule 2: Write your answer in your own words.

Rule 3: Think about the content of your essay, being sure to demonstrate good social scientific skills.

Rule 4: Think about the structure of your essay, being sure to demonstrate good writing skills, and observing any word limit.

Why an essay is not a report, newspaper article or an exam answer

This section has mainly focused on what is distinctive about a social science essay, but there is something distinctive about essays in general that is worth keeping in mind. Many students come from professional backgrounds where report writing is a common form of communication. For other students a main source of information is newspapers or online websites. These are all legitimate forms of writing that serve useful purposes – but, apart from some of the content on academic websites, they just aren’t essays. There are exam conventions that make exam writing – even ‘essay style’ exams – different from essay writing.

In part, this is to do with ‘academic register’ or ‘voice’. Part of what you will develop as you become a stronger essay writer is a ‘voice’ that is your own, but that conforms to the conventions of academic practice. For social scientists, as we have noted above, this practice includes the use of evidence to support an argument and providing references that show where your ideas and evidence have come from. It also includes the ability to write with some confidence, using the vernacular – or language – of your subject area. Different forms of writing serve different purposes. The main purpose of academic writing is to develop and share knowledge and understanding. In some academic journals this can take the form of boisterous debate, with different academics fully and carefully defending, or arguing for, one position or another. For students of social science, however, there may be less at stake, but essays should nevertheless demonstrate knowledge and understanding of a particular issue or area. Conforming to some basic conventions around how to present ideas and arguments, helps us more easily to compare those ideas, just as conforming to the rules of a game makes it easier for one sports team to play against another: if one team is playing cricket and the other baseball, we will find there are similarities (both use bats, have innings, make runs), but there will also be lots of awkward differences. In the end, neither the players nor the spectators are likely to find it a very edifying experience. The following looks at other forms of serious writing that you may be familiar with, but that just aren’t cricket.

Report writing

Reports take a variety of forms, but typically involve: an up-front ‘executive summary’, a series of discussions, usually with numbered headings and subheadings. They are also likely to include ‘bullet points’ that capture an idea or argument in a succinct way. Professional reports may include evidence, arguments, recommendations and references. You may already have spotted some of the similarities with essays – and the crucial differences. Let’s begin with the similarities. Reports and essays both involve discussion, the use of evidence to support (or refute) a claim or argument, and a list of references. Both will have an introductory section, a main body and a conclusion. However, the differences are important. With the exception of very long essays (dissertations and the like), essays do not generally have numbered headings and subheadings. Nor do they have bullet points. They also don’t have executive summaries. And, with some notable exceptions (such as essays around areas of social policy perhaps), social science essays don’t usually require you to produce policy recommendations. The differences are significant, and are as much about style as they are about substance.

Journalistic writing

For many students, journalistic styles of writing are most familiar. Catchy headlines (or ‘titles’) are appealing, and newspapers’ to-the-point presentation may make for easier reading. News stories, however, follow a different set of requirements to essays – a different set of ‘golden rules’. In general, newspaper and website news articles foreground the ‘who, what, where, when and why’ of a story in the first paragraph. The most important information is despatched immediately, with the assumption that all readers will read the headline, most readers will read the first paragraph, and dwindling numbers will read the remainder of the article. Everyday newspaper articles often finish with a ‘whimper’ for this reason, and there may be no attempt to summarize findings or provide a conclusion at the end – that’s not the role of news journalists. (Though there is quite a different set of rules for ‘Op Ed’ or opinion pieces.) Student essays, by contrast, should be structured to be read from beginning to end. The introduction should serve to ‘outline’ or ‘signpost’ the main body of the essay, rather than cover everything in one fell swoop; the main body should proceed with a clear, coherent and logical argument that builds throughout; and the essay should end with a conclusion that ties the essay together.

Exam writing

Again, exam writing has similarities and differences with essay writing. Perhaps the main differences are these: under exam conditions, it is understood that you are writing at speed and that you may not communicate as effectively as in a planned essay; you will generally not be expected to provide references (though you may be expected to link clearly authors and ideas). Longer exam answers will need to include a short introduction and a conclusion, while short answers may omit these. Indeed, very short answers may not resemble essays at all as they may focus on factual knowledge or very brief points of comparison.

Peter Redman and Wendy Maples

Peter Redman is a senior lecturer in sociology at The Open University. With Stephen Frosh and Wendy Hollway, he edit the Palgrave book series, Studies in the Psychosocial and is a former editor of the journal, Psychoanalysis, Culture & Society . Academic consultant Wendy Maples is a research assistant in anthropology at the University of Sussex. Together they co-authored Good Essay Writing: A Social Sciences Guide (Sage, 2017) now in its fifth edition.

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True Crime: Insight Into The Human Fascination With The Who-Done-It
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Norman Denzin, 1941-2023: The Father of Qualitative Research

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The Critical Turkey

Essay Writing Hacks for the Social Sciences

What Should Be in a Social Science Essay? Fundamentals and Essential Techniques

This blogpost is also available as a PDF download , so it can be stored on your desktop and used as a checklist before submitting your essay.

The following is a condensed overview of the most important features of social science essay writing. Its aim is to cut through the noise, and focus on the most essential (and important) elements of essay writing. Read it carefully, and use it as a check-list once you have completed your essay.

Before we get into the details, however, be aware: The purpose of writing essays in the social and political sciences is not so much to just demonstrate your knowledge. Rather, it is about applying this knowledge, using it to make a well-informed, well-reasoned, independently-reflected argument that is based on verified (and verifiable) evidence. What should be in an essay, and how you should write it, is all informed by this purpose.

What’s in an Essay?

The main focus of an academic essay, article or book is to address a research or essay question. Therefore, make sure you have read the essay question carefully, think about what aspects of the topic you need to address, and organize the essay accordingly. Your essay should have three parts:

Introduction
Provide context to the question. Be specific (not ‘since the dawn of time, social scientists have been arguing…’, but ‘one of the key debates in the study of revolutions revolves around…’, ideally providing references to the key authors of said debate).
It is almost always a good idea to formulate an argument – an arguable statement – in relation to the essay question (e.g. if the question is ‘Evaluate Weber and Marx’s accounts of capitalism’, an argument could be ‘I am going to argue that Weber is most insightful on X, but Marx is important for Y’). This builds a nice critical element into your essay, your own take on things, going beyond merely describing what others have written.
Essay plan: Tell the reader about the points you are going to cover, and the order in which you are going to do this (e.g. ‘First, the essay looks at…, second… third…’ etc.). Think of it as a roadmap to the essay.
Define key concepts as necessary for understanding. Do not use general dictionaries, as they often contain notions that social scientists try to challenge. Use definitions from the readings, and from sociological dictionaries.
Length: Intro should be between 5 to 10%, and no more than about 10 per cent of the overall word count.
Main Part / Body
The structure of the essay body is informed by the research/essay question: What points do you need to include in order to address the question? What sub-questions are there to the big question? Concentrate on the ‘need-to-knows’ rather than the ‘nice-to-knows’ .
The order in which you arrange these points depends on what makes the most convincing line of argument. This depends on the essay question, but as a rule of thumb you want to build up your argument, from the basics to the more elaborate points, from the weaker to the stronger, from what contradicts your argument to what supports it.
The different points should be addressed in appropriate depth. Make sure you explain not just what something is, but also how it works, and use examples and illustration.
There should be a coherent thread running through the essay and connecting the various points to one another and the overall argument. Indicate these connections in strategic places with appropriate signposting. These signpostings should also help you develop your argument as you proceed.
Excellent essays often raise counter-arguments to the argument presented, and then provide arguments against those counter-arguments. Think about why and how someone might disagree about what you are saying, and how you would respond to them.
Use peer-reviewed academic sources and present evidence for the points you make, using references, reliable statistics, examples etc. Any opinion you express should be built on reliable evidence and good reasoning.
What, finally, is your answer to the question? Bring the various strings of the essay together, summarize them briefly in the context of the essay question, and round off by connecting to the bigger discussion that the essay question is part of. It is usually a good idea to have a differentiated conclusion, in which you e.g. agree with a statement to a certain extent or under specific circumstances (and explain which and why), but disagree with some other aspects of it, rather than making undifferentiated black-or-white statements. You can also contextualise your argument with your ideas from the introduction. It is normally not a good idea to introduce new material in the conclusion. You are wrapping up here, and rounding off, not starting new discussions.
Conclusion should be about, and no longer than, 10 per cent of the overall word count.

Notes on Writing Style

Find the right balance between formal and informal. Avoid being too informal and conversational on the one hand. But also don’t use overly convoluted and complicated language, as it makes your writing inaccessible, and can lead to a lack of clarity. You may at times encounter academic writing that seems deliberately obscure or overcomplicated, but those are not examples you should try to emulate.
Clarity and specificity should indeed be a top priority. Are the words you are using expressing what you want to express? Is it clear who specifically is doing what or saying what? Pay attention to this when proofreading the essay. Could someone understand this differently? Avoid ambiguities.
Key concepts should be clearly defined and used throughout the essay in the way you defined them. Choose the definitions that are most useful for your discussion.
Avoid hyperbole (don’t do ‘shocking statistics’ or ‘dire consequences’ etc.).

Notes on the Writing Process

Proofreading: When you are first writing, don’t think of it as the final product, but treat it as a first draft. Go through several drafts until you are happy with it. At a minimum, proofread the entire essay once or twice. Don’t be perfectionist when you start out, as you can always come back and improve on whatever you’ve written.
Small steps: Focussing on the small, concrete steps of your writing process rather than constantly thinking of the big task at hand will help you feel in control.
Procrastination: Feeling overwhelmed, as well as being too perfectionist, are among the leading causes for procrastination. The two previous points should therefore help you address this issue as well. Don’t be too harsh on yourself when you do procrastinate – almost everyone does it to some extent .
Over the years, keep addressing areas you want to improve on, and keep looking for information. Search online, for example ‘how to cite a book chapter in Harvard Sage’, ‘developing an argument’, ‘ using quotations ’, ‘memory techniques’, ‘how to read with speed’, ‘understanding procrastination’, or ‘ what does peer-reviewed mean ’. There is plenty of information, and some seriously good advice out there. See what works for you. Read the feedback you get on your writing, and incorporate it into your next essay.

Final Thoughts

Essay Writing skills are good skills to have in any situation (except maybe in a zombie apocalypse). They will make the studying process easier over time, and hopefully also more fun. But in a wider sense, they are general skills of critical engagement with the world around you, and will help you filter and prioritise the overload of information you are confronted with on an everyday basis. In that sense, they might actually even be helpful in a zombie apocalypse.

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1 What are the social sciences?

Learning Objectives for this Chapter

After reading this Chapter, you should be able to:

understand what the social sciences are, including some fundamental concepts and values,
understand and apply the concept of ‘phronesis’ to thinking about the purpose and value of the social sciences.

History and philosophy of the social sciences

Some of the earliest written and spoken accounts of human action, values, and the structure of society can be found in Ancient Greek, Islamic, Chinese and indigenous cultures. For example, Ibn Khaldoun , a 14th-century North African philosopher, is considered a pioneer in the field of social sciences. He wrote the book Muqaddimah , which is regarded as the first comprehensive work in the social sciences. It charts an attempt to create a universal history based on studying and explaining the economic, social, and political factors that shape society and discussed the cyclical rise and fall of civilisations. Moreover, indigenous peoples across the world have contributed in various and significant ways to the development of scientific knowledge and practices (e.g., see this recent article by Indigenous scholar, Jesse Popp – How Indigenous knowledge advances modern science and technology ). Indeed, contemporary social science has much to learn from indigenous knowledges and methodologies (e.g., Quinn 2022 ), as well as much reconciling to do in terms of its treatment of indigenous peoples the world over (see Coburn, Moreton-Robinson, Sefa Dei, and Stewart-Harawira, 2013 ).

Nevertheless, the dominant Western European narrative of the achievements of the enlightenment still tends to overlook and discredit much of this knowledge. Additionally, male thinkers have tended to dominate within the Western social sciences, while women have historically been excluded from academic institutions and their perspectives largely omitted from social science history and texts. Therefore, much of the history of the social sciences represent a predominantly white, masculine viewpoint. That is not to say that the concepts and theories developed by these male social scientists should be outright discredited. Nevertheless, in engaging with them we must understand this context; they are not the only voices, nor necessarily the most important. Indeed, it is crucial therefore that the history of the social sciences is continually re-examined through a critical lens, to identify gaps within social scientific knowledge bases and allow space for critical revisions that broaden existing concepts and theories beyond an exclusively masculine, Western-centric perspective. We seek to adopt such an approach throughout this book. However, to critique and question Western social scientific perspectives, we must first understand them.

Social sciences in the Western world

The study of the social sciences, as developed in the Western world, can be said to emerge from the Age of Enlightenment in the late 17th Century. Beginning with René Descartes (1596-1650), both the natural and social sciences developed from the concept of the rational, thinking individual. These early Enlightenment thinkers argued that human beings use reason to understand the world, rather than only referring to religion. Other thinkers around this time such as Jean-Jacques Rousseau (1712-1778), M. de Voltaire (1694-1778) and Denis Diderot (1713-1784), began to develop different methodologies to scientifically explain processes in the body, the structure of society, and the limits of human knowledge. It was during this period that the social sciences grew out of moral philosophy, which asks ‘how people ought to live’, and political philosophy, which asks ‘what form societies ought to take’. Rather than only focusing on descriptive scientific questions about ‘how things are’, the social sciences also sought answers to normative questions about ‘how things could be’. This is one of the central differences between the natural sciences and the social sciences. This era of Enlightenment marked an important turning point in history that gave way to further developments in both the natural and social sciences.

Immanuel Kant (1724-1804) is often regarded as one of the most influential philosophers for the development of the social sciences. In his work, Kant develops an epistemology that accounts for the objective validity of knowledge, due to the capacities of the human mind. In other words, how can we as individual people come to know facts about the world that are true for all of us. Social scientists, such as Émile Durkheim (1858-1917) and Max Weber (1864-1920) critically developed the work of Kant to explain social relations between individuals.

Émile Durkheim prioritised the validity of social facts over the values themselves, continuing the tradition of ‘ positivism ‘ (an ontological position that we discuss later in this Chapter). Durkheim argued that there is a distinction between social facts and individual facts. Rather than viewing the structure of the human mind as the basis for knowledge like Kant, Durkheim argued that it is society itself that forms the basis for the social experience of individuals. Social facts should therefore, “be treated as natural objects and can be classified, compared and explained according to the logic of any natural science” (Rose, 1981: 19). Durkheim developed his methodology using analogies to the natural sciences. For example, he borrowed concepts from biology to understand society as a living organism.

TRIGGER WARNING

The following section contains content which may be triggering for certain people. It focuses on the sociology of suicide, including discussion of self-harm and different forms of suicide as it exists within society.

Durkheim and Suicide

Emile Durkheim’s 1879 text ‘Suicide: a Study in Sociology’ is a foundational work for the study of social facts. Durkheim explores the phenomenon of suicide across different time periods, nationalities, religions, genders, and economic groups. Durkheim argues that the problem of suicide can not be explained through purely biological, psychological or environmental means. Suicide must, he concludes, “necessarily depend upon social causes and be in itself a collective phenomenon” (Durkheim 1897: 97). It was and continues to be a work of great impact that demonstrates that, what most would consider an individual act is actually enmeshed in social factors.

In his text, Durkheim identifies some of the different forms suicide can take within society, four of which we discuss below.

Egoistic Suicide

Egoistic suicide is caused by what Durkheim terms “excessive individuation” (Durkheim 1897: 175). A lack of integration within a particular community or society at large leads human beings to feel isolated and disconnected from others. Durkheim argues that “suicide increases with knowledge”(Durkheim 1897: 123). This is not to say that a particular human being kills themselves because of their knowledge; rather it is because of the decline of organised religion that human beings desire knowledge outside of religion. It is thus, for Durkheim the weakening organisation of religion that detaches people from their (religious) community, increasing social isolation. According to Durkheim, the capacity of religion to prevent suicide does not result from a stricter prohibition of self-harm. Religion has the power to prevent someone from committing suicide because it is a community, or a ‘society’ in Durkheim’s words. The collective values of religion increases social integration and is just one example of the importance of community in decreasing rates of suicide. Isolation of individuals, for Durkheim, is a fundamental cause of suicide: “The bond attaching man [sic] to life relaxes because that attaching him [sic] to society is itself slack” (Durkheim 1897: 173).

Altruistic Suicide

Durkheim notes another kind of suicide that stems from “insufficient individuation” (Durkheim 1897: 173). This occurs in social situations where an individual identifies so strongly with their beliefs of a group that they are willing to sacrifice themselves for what they perceive to be the greater good. Examples of altruistic suicide include suicidal sacrifice in certain cultures to honour their particular God, soldiers who go to war and die in honour of their country, or the ancient tradition of Hara-kiri in Japan. As such, Durkheim notes that some people have even refused to consider altruistic suicide a form of self-destruction, because it resembles “some categories of action which we are used to honouring with our respect and even admiration”(Durkheim 1897: 199).

Anomic Suicide

The third kind of suicide Durkheim identifies is termed anomic suicide. This type is the result of the activity of human beings “lacking regulation”, and “the consequent sufferings” that are felt from this situation (Durkheim 1897: 219). Durkheim notes the similarities between egoistic and anomic suicide, however he notes an important distinction: “In egoistic suicide it is deficient in truly collective activity, thus depriving the latter of object and meaning. In anomic suicide, society’s influence is lacking in the basically individual passions, thus leaving them without a check-rein” (Durkheim 1897: 219).

Fatalistic Suicide

There is a fourth type of suicide for Durkheim, one that has more historical meaning than current relevance. Fatalistic suicide is opposed to anomic, and is the result of “excessive regulation, that of persons with futures pitilessly blocked and passions violently choked by oppressive discipline” (Durkheim 1897: 239). These regulations occur during moments of crises, including economic and social upheaval, that destabilise the individual’s sense of meaning. It is the impact of external factors onto the individual, where meaning is thrown to the wind for the individual, that characterises fatalistic suicide.

Durkheim’s sociological study of suicide was a groundbreaking work for social sciences. His methodology, multivariate analysis, provided a way to understand numerous interrelated factors and how they relate to a particular social fact. His findings, particularly the higher suicide rates of Protestants, compared to Jewish and Catholic people, was correlated to the higher rates to individualised consciousness and the lower social control. This study, despite criticisms of the generalisations drawn from the results, has had a remarkable impact on sociology and remains a seminal text for those interested in the social sciences.

Max Weber was also influenced by the work of Kant. Unlike Durkheim, Weber “transformed the paradigm of validity and values into a sociology by giving values priority over validity” (Rose, 1981: 19). Culture is thus understood as a value that structures our understanding of the world. According to Weber, values cannot be spoken about in terms of their truth content. The separation between values and validity means that values can only be discussed in terms of faith rather than scientific reason. For Weber, only when a culture’s underpinning values are defined can facts about the social world be understood.

The philosophy of G.W.F. Hegel (1770-1831) also greatly shaped the development of the social sciences. As argued by Herbert Marcuse (1941: 251-257), Hegel instigated the shift from abstract philosophy to theories of society. According to Hegel, human beings are not restricted to the pre-existing social order and can understand and change the social world. Our natural ability to reason allows human beings to create theories about our world that are universal and true.

Karl Marx (1818-1883), often regarded as the founder of conflict theory, was deeply influenced by the philosophy of Hegel. For example, Hegel emphasises that labour and alienation are essential characteristics of human experience, and Marx applies this idea more concretely to a material analysis of society, dividing human history along the lines of the forces of production. In other words, Marx understood that labour was divided in capitalist society according to two classes that developed society through a perpetual state of conflict: the working class, or ‘ proletariat’ , and the class of ownership, or ‘ bourgeoisie’ (we talk more about Marx’s conflict theory in Chapter 3).

Overall, the social sciences have a long and complex history, influenced by many different philosophical perspectives. As alluded to earlier, however, any account of the historical beginnings of the social sciences must be understood to be embedded within dominant systems of power, including for example colonisation, patriarchy, and capitalism. Indeed, any history of the social sciences is already situated within a narrative, or ‘discourse’. Maintaining a critical lens will allow for a deeper understanding of the genesis of the social sciences, as well as the important ability to question social scientific approaches, understandings, findings, and methods. It is this disposition that we seek to cultivate throughout this book. After all, as Marx famously wrote, “The philosophers have only interpreted the world, in various ways. The point, however, is to change it.”

Defining Key Terms

Descriptive : A descriptive claim or question seeks to explain how things work, what causes them to work that way, and how things relate to one another.

Normative : A normative claim or question seeks to explain how things ought to work, why they should work a certain way, and what should change for things to work differently.

Labour : For Marx, labour is the natural capacity of human beings to work and create things. Under capitalism, labour primarily produces profits for the ruling class. (Please note, we return to the notion of labour in later chapters, and explore other understandings and definitions of this term.)

Alienation : Workers, separated from the products of their labour and replaceable in the production process, become separated or ‘alienated’ from their creative human essence. (Please also see Chapter 3 for a further explanation of the concept of alienation under Marxism.)

What are the social sciences?

Umbrella - with these words under it - Anthropology, Sociology, Criminology, DEMOGRAPHY, DEVELOPMENT STUDIES, Social work, Archaeology, Social policy, Political science, Economics, Human geography, LEGAL STUDIES.

The social sciences are a ‘broad church’, including lots of different disciplinary and sub-disciplinary areas. These include, for example, sociology, anthropology, criminology, archaeology, social policy, human geography, and many more. At their core, they apply the ‘scientific method’ to the analysis of people, societies, power, and social change.

Before we move on, let’s touch briefly on what we mean by the scientific method . At its core, the scientific method is essentially a series of steps that scientists take in order to build and test scientific knowledge. These steps include:

Observation : Scientists observe the world around them, in order to better understand it.
Question : Scientists ask ‘research questions’ about how the world works.
Hypothesis: Scientists come up with ideas or theories about how they think the world works, which they then seek to test through their research.
Experiment: In experimental research, scientists use a specific experimental design (which includes a control and experimental group) to test hypotheses. This is not always possible or desirable in the social sciences, so social scientists tend to rely on a broader array of methods to collect data that can help them test their hypotheses about the social world.
Analysis: Scientists use various different approaches to analyse the data they collect; the approach to analysis depends on the kind of data collected, and what questions are being asked of the data.
Conclusions: Scientists develop conclusions, based on the results of their analyses. They consider how these either reinforce or further develop existing knowledge and understandings, as well as what there is left to find out (the latter of which informs future research endeavours).

Over time, social scientists have developed their own ontological and epistemological leanings, which in many ways represent a departure from the typical positivist approaches of the natural sciences. While the natural sciences tend to assume there are objective ‘truths’ waiting to be discovered through, for instance, sensory experience (seeing, looking), social scientists tend to understand truth as being socially constructed. Thus, social scientists tend to adopt interpretivist and constructivist approaches to understanding the world, seeing knowledge as being co-constructed, rooted in context, and an important source/expression of power.

Consolidate your learning: ‘Introduction to the social sciences’ video

To consolidate your understanding of the social sciences, watch the following short video – Introduction to the social sciences (YouTube, 8:34) .

Flyvbjerg (2001) referred to the ‘science wars’, by which he meant the ongoing battle between the natural and social sciences. Often in public and political discourse, the natural sciences are seen as being more ‘scientific’ and a source of ‘stronger’ or ‘more objective’ knowledge than the social sciences. However, the reality is that both have equally important but different things to offer. As Flyvbjerg (2001: 3) argued:

…the social sciences are strongest where the natural sciences are weakest: just as the social sciences have not contributed much to explanatory and predictive theory, neither have the natural sciences contributed to the reflexive analysis and discussion of values and interests…

As Flyvbjerg (2001) sees it, social scientists should not try to replicate the natural sciences but should instead embrace their ability to take a different ontological and epistemological outlook, which enables deep, reflexive, and contextualised analysis about people and societies as a point of departure for values-based action . He called this ‘phronetic social science’ (which we elaborate on later in the Chapter).

Defining key terms

‘Ontology’: Ontology is the study of reality and being. When we refer to ‘ontology’, we are not just talking about people’s views of the world, but also their lived experience and actual being in the world, as well as their beliefs and claims about the nature of their existence. Some key questions are ‘what and who exists in the world?’ and ‘what are the relationships between them’?

‘Epistemology’ : Epistemology concerns the origin and nature of knowledge, including how knowledge claims are built and made. Some key questions are ‘what is knowledge?’ and ‘how is knowledge acquired’?

Positivism: Positivism is an ontology that assumes there is an objective ‘truth’ waiting to be discovered. Positivism involves, therefore, the search for a universal/generalisable ‘truth’.

Constructivism: Constructivism is an ontology that assumes that there are multiple ‘truths’ that are subjective and socially constructed. Truths are not, therefore, universal but are instead rooted in social, historical, and geographical context. These ‘truths’ are also bound up with power. For instance, those who hold power get to say what is ‘true’ and what isn’t.

In addition to the above, Argentine-Canadian philosopher Mario Bunge ‘s (2003: 285ff) glossary of key terms includes a range of ontological concepts used in the social sciences that are useful to think with:

“Definitions of Twelve Ontological Concepts

Ontology: The philosophical study of being and becoming.
Realism (ontological): The thesis that the world outside the student exists on its own.
Phenomenalism (ontological): The philosophical view that there are only phenomena (appearances to someone).
Constructivism (ontological): The view that the world is a human (individual or social) construction.
Dialectics: The ontological doctrine, due to Hegel and adopted by Marx and his followers, according to which every item is at once the unity and struggle of opposites.
Materialism: The family of naturalist ontologies according to which all existents are material.
Naturalism: The family of ontologies that assert that all existents are natural-hence none are supernatural.
Idealism. The family of ontologies according to which ideas pre-exist and dominate everything else.
Subjectivism. The family of philosophies according to which everything is in a subject’s mind (subjective idealism).
Holism: The family of doctrines according to which all things come in unanalyzable wholes.
Individualism: The view that the universe is an aggregate of separate individuals: that wholes and emergence are illusory.
Systemism (ontological): The view that everything is either a system or a component of some system.”

Source: Bunge, M. (2003). E mergence and Convergence: Qualitative Novelty and the Unity of Knowledge . University of Toronto Press. Pp. 285ff

Reflection exercise

Take a few moments to think about what you have read above. Then, write a short (~100 word) reflection explaining:

primary ways in which the natural and social sciences differ, and
some things that the social sciences offer that the natural sciences cannot.

Why study the social sciences?

In their 2019 publication, Carré asked, ‘what are the social sciences for’? In response, they propose a framework for thinking about the different approaches and contributions of social science research, which encompasses three continuums: 1) return on investment versus intrinsic value; 2) citizen (societal) relevance versus academic relevance; and 3) applied research versus basic research (see the Figure below, adapted from Carré [2019: 23]).

Image shows an adaptation of Carré's (2019: 23) framework for the social sciences

While Carré (2019) argues that social scientists move along these continuums, he also suggests that there is good justification for finding middle grounds between the extremes. For instance, while applied research will tend to focus on and find solutions for specific social issues (e.g. youth crime), ‘basic’ research tends to adopt a more high-level theoretical approach to shaping how we understand the world, which can lead to longer-term substantive change (such as changing the way we think about and understand youth crime). As Carré (2019: 22) explains: “either research is conducted to directly solve pressing social issues, or it takes a full step back from the social word, in order to reflect about it without directly meddling [and] being involved in its events and discussions.” However, both are incredibly useful for moving knowledge forward and making crucial contributions. Similarly, they can have important symbiotic relationships; applied research might be informed and guided by the knowledge created through basic research, and conversely, applied research studies might be meta-analysed (a type of combined analysis) to inform broader theoretical development that is often the purview of basic research.

A central question raised by Carré (2019) is, what should social science ‘give back’ to the society that supports it? Take a piece of paper and write down some responses to this, based on your own views and beliefs.

According to Flyvbjerg (2001), and as also covered by Schram (2012), the concept of ‘phronetic social science’ can help bring social scientists back to the central value of the social sciences, rather than seeing them try to emulate the natural sciences and their search for universal and generalisable theories and truths. Instead, phronetic social science recognises that ‘truth’ is dependent on context, is in constant flux, and is bound up with power. This is not to say that we live in a ‘post-truth’ world where anything goes, but merely that we need to interrogate how knowledge and truth are created and how societies and social structures can play a role in this. Famous sociologist, Michel Foucault (1926-1984) referred to this as a ‘politics of truth’: something we’ll continue to discuss in greater detail over coming chapters.

‘Phronetic’ social science

Phronetic social science draws on the concept of phronesis, a term coined by Aristotle (384-322 BC) to refer to practical wisdom that arises from experience. Thus, phronetic social science “is designed not to substitute for, but instead to supplement, practice wisdom and to do so in ways that can improve society” (Schram 2012: 16). In terms of improving society, phronetic social science is then also concerned with praxis, or the practical application of knowledge to the betterment of society. Finally, phronetic social science is not attached to particular methods (e.g. quantitative versus qualitative), instead being “open to relying on a diversity of data collection methods in order to best inform attempts to promote change related to the issues being studied” (Schram 2012: 20).

Schram (2012: 18-19) presents four justifications for phronetic social science as follows:

“Given the dynamic nature of human interaction in the social world, social inquiry is best practiced when it does not seek general laws of action that can be used to predict courses of action, but instead offer a critical assessment of values, norms and structures of power and dominance. Social inquiry is better when it is linked to questions of the good life, that is, to questions of what we ought to do.
While the social world is dynamic, social research is best seen as dialogical. Social inquiry is not a species of theoretical reason but of practical reason. Practical reason stays within a horizon of involvements in social life. For Flyvbjerg, this entails a context-dependent view of social inquiry that rests on the capacity for judgement. Understanding can never be grasped analytically; it is a holistic character. Understanding also has intrinsic subjective elements requiring researchers to forgo a disinterested position of detachment and enter into dialogue with those they study.
As the study of dynamic social life, dialogical social inquiry is best practiced when we give up traditional notions of objectivity and truth and put aside the fact-value distinction. Instead, we should emphasise a contextual notion of truth that is pluralistic and culture-bound, further necessitating involvement with those we study.
Dialogical social inquiry into a dynamic and changing social world provides a basis for emphasising that interpretation is itself a practice of power, one that if conducted publicly and in ways that engage the public can also challenge power and inform efforts to promote social change.”

This concept of phronetic social science is a helpful means of understanding how the social sciences differ to the natural sciences, and can add value in different ways. However, it doesn’t tell us how to do social science, or how to be social scientists. What tools, for instance, might we use to undertake the sort of dialogical social inquiry that Schram refers to above? And how might we start ‘thinking’ like social scientists? We turn to these questions in the chapter that follows.

‘Phronesis’: Described by Aristotle as ‘practical wisdom’, and juxtaposed with techn é (‘know how’ of practice) and epistem é (abstract and universal knowledge).

‘Dialogical’: Exploring the meaning of things and creating knowledge through dialogue/conversation.

‘Quantitative’ : A term used to describe research methods that typically involve measurement and counting of phenomena, regularly involving numerical data.

‘Qualitative’: A term used to describe research methods that typically involve understanding and interpretation of lived experiences (how people think, feel, act), regularly involving textual data.

Think about the concept of phronetic social science. Write a short paragraph (~30-40 words) to explain it in your own words. Then read back over the content in this chapter content to check your understanding.

Resources to support further learning

Relevant readings:

Gorton, W. ‘ The Philosophy of Social Science .’
Flyvbjerg, B. 2001. ‘The science wars: a way out.’ In. Flyvbjerg, B. Making social science matter, chapter 1. Cambridge University Press: Cambridge.
Carré, D. 2019. ‘ Social sciences, what for? On the manifold directions for social research .’ In. Valsiner, J. (Ed.) Social philosophy of science for the social sciences, pp. 13-29. Springer: Cham.
Schram, S. 2012. ‘Phronetic social science: an idea whose time has come.’ In Flyvbjerg, B., Landman, T. and Schram, S. (Eds.) Real social science: applied phronesis. Cambridge University Press: Cambridge.
Bunge, M. (2003). E mergence and Convergence: Qualitative Novelty and the Unity of Knowledge . University of Toronto Press.

Other resources:

Video: Soomo, ‘An animated introduction to social science’ (YouTube, 4:35) .
Video: ‘Introduction to the social sciences’ (YouTube, 8:34) .
Podcast: Theory and Philosophy Podcast, ‘Bent Flyvbjerg – Making Social Science Matter’ (YouTube, 44:06) . (Note, discussion of phronesis starts at 7:51)
Video: ‘Importance of social science with Professor Cary Cooper’ (YouTube, 4:13) .

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Organizing Your Social Sciences Research Paper

9. The Conclusion
Purpose of Guide
Design Flaws to Avoid
Independent and Dependent Variables
Glossary of Research Terms
Reading Research Effectively
Narrowing a Topic Idea
Broadening a Topic Idea
Extending the Timeliness of a Topic Idea
Academic Writing Style
Applying Critical Thinking
Choosing a Title
Making an Outline
Paragraph Development
Research Process Video Series
Executive Summary
The C.A.R.S. Model
Background Information
The Research Problem/Question
Theoretical Framework
Citation Tracking
Content Alert Services
Evaluating Sources
Primary Sources
Secondary Sources
Tiertiary Sources
Scholarly vs. Popular Publications
Qualitative Methods
Quantitative Methods
Insiderness
Using Non-Textual Elements
Limitations of the Study
Common Grammar Mistakes
Writing Concisely
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Footnotes or Endnotes?
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The conclusion is intended to help the reader understand why your research should matter to them after they have finished reading the paper. A conclusion is not merely a summary of the main topics covered or a re-statement of your research problem, but a synthesis of key points derived from the findings of your study and, if applicable, where you recommend new areas for future research. For most college-level research papers, two or three well-developed paragraphs is sufficient for a conclusion, although in some cases, more paragraphs may be required in describing the key findings and their significance.

Conclusions. The Writing Center. University of North Carolina; Conclusions. The Writing Lab and The OWL. Purdue University.

Importance of a Good Conclusion

A well-written conclusion provides you with important opportunities to demonstrate to the reader your understanding of the research problem. These include:

Presenting the last word on the issues you raised in your paper . Just as the introduction gives a first impression to your reader, the conclusion offers a chance to leave a lasting impression. Do this, for example, by highlighting key findings in your analysis that advance new understanding about the research problem, that are unusual or unexpected, or that have important implications applied to practice.
Summarizing your thoughts and conveying the larger significance of your study . The conclusion is an opportunity to succinctly re-emphasize your answer to the "So What?" question by placing the study within the context of how your research advances past research about the topic.
Identifying how a gap in the literature has been addressed . The conclusion can be where you describe how a previously identified gap in the literature [first identified in your literature review section] has been addressed by your research and why this contribution is significant.
Demonstrating the importance of your ideas . Don't be shy. The conclusion offers an opportunity to elaborate on the impact and significance of your findings. This is particularly important if your study approached examining the research problem from an unusual or innovative perspective.
Introducing possible new or expanded ways of thinking about the research problem . This does not refer to introducing new information [which should be avoided], but to offer new insight and creative approaches for framing or contextualizing the research problem based on the results of your study.

Bunton, David. “The Structure of PhD Conclusion Chapters.” Journal of English for Academic Purposes 4 (July 2005): 207–224; Conclusions. The Writing Center. University of North Carolina; Kretchmer, Paul. Twelve Steps to Writing an Effective Conclusion. San Francisco Edit, 2003-2008; Conclusions. The Writing Lab and The OWL. Purdue University; Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8.

Structure and Writing Style

I. General Rules

The general function of your paper's conclusion is to restate the main argument . It reminds the reader of the strengths of your main argument(s) and reiterates the most important evidence supporting those argument(s). Do this by clearly summarizing the context, background, and necessity of pursuing the research problem you investigated in relation to an issue, controversy, or a gap found in the literature. However, make sure that your conclusion is not simply a repetitive summary of the findings. This reduces the impact of the argument(s) you have developed in your paper.

When writing the conclusion to your paper, follow these general rules:

Present your conclusions in clear, concise language. Re-state the purpose of your study, then describe how your findings differ or support those of other studies and why [i.e., what were the unique, new, or crucial contributions your study made to the overall research about your topic?].
Do not simply reiterate your findings or the discussion of your results. Provide a synthesis of arguments presented in the paper to show how these converge to address the research problem and the overall objectives of your study.
Indicate opportunities for future research if you haven't already done so in the discussion section of your paper. Highlighting the need for further research provides the reader with evidence that you have an in-depth awareness of the research problem but that further investigations should take place beyond the scope of your investigation.

Consider the following points to help ensure your conclusion is presented well:

If the argument or purpose of your paper is complex, you may need to summarize the argument for your reader.
If, prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the end of your paper to describe your main points and explain their significance.
Move from a detailed to a general level of consideration that returns the topic to the context provided by the introduction or within a new context that emerges from the data [this is opposite of the introduction, which begins with general discussion of the context and ends with a detailed description of the research problem].

The conclusion also provides a place for you to persuasively and succinctly restate the research problem, given that the reader has now been presented with all the information about the topic . Depending on the discipline you are writing in, the concluding paragraph may contain your reflections on the evidence presented. However, the nature of being introspective about the research you have conducted will depend on the topic and whether your professor wants you to express your observations in this way. If asked to think introspectively about the topics, do not delve into idle speculation. Being introspective means looking within yourself as an author to try and understand an issue more deeply, not to guess at possible outcomes or make up scenarios not supported by the evidence.

II. Developing a Compelling Conclusion

Although an effective conclusion needs to be clear and succinct, it does not need to be written passively or lack a compelling narrative. Strategies to help you move beyond merely summarizing the key points of your research paper may include any of the following:

If your essay deals with a critical, contemporary problem, warn readers of the possible consequences of not attending to the problem proactively.
Recommend a specific course or courses of action that, if adopted, could address a specific problem in practice or in the development of new knowledge leading to positive change.
Cite a relevant quotation or expert opinion already noted in your paper in order to lend authority and support to the conclusion(s) you have reached [a good source would be from your literature review].
Explain the consequences of your research in a way that elicits action or demonstrates urgency in seeking change.
Restate a key statistic, fact, or visual image to emphasize the most important finding of your paper.
If your discipline encourages personal reflection, illustrate your concluding point by drawing from your own life experiences.
Return to an anecdote, an example, or a quotation that you presented in your introduction, but add further insight derived from the findings of your study; use your interpretation of results from your study to recast it in new or important ways.
Provide a "take-home" message in the form of a succinct, declarative statement that you want the reader to remember about your study.

III. Problems to Avoid

Failure to be concise Your conclusion section should be concise and to the point. Conclusions that are too lengthy often have unnecessary information in them. The conclusion is not the place for details about your methodology or results. Although you should give a summary of what was learned from your research, this summary should be relatively brief, since the emphasis in the conclusion is on the implications, evaluations, insights, and other forms of analysis that you make. Strategies for writing concisely can be found here .

Failure to comment on larger, more significant issues In the introduction, your task was to move from the general [the field of study] to the specific [the research problem]. However, in the conclusion, your task is to move from a specific discussion [your research problem] back to a general discussion framed around the implications and significance of your findings [i.e., how your research contributes new understanding or fills an important gap in the literature]. In short, the conclusion is where you should place your research within a larger context [visualize your paper as an hourglass--start with a broad introduction and review of the literature, move to the specific analysis and discussion, conclude with a broad summary of the study's implications and significance].

Failure to reveal problems and negative results Negative aspects of the research process should never be ignored. These are problems, deficiencies, or challenges encountered during your study. They should be summarized as a way of qualifying your overall conclusions. If you encountered negative or unintended results [i.e., findings that are validated outside the research context in which they were generated], you must report them in the results section and discuss their implications in the discussion section of your paper. In the conclusion, use negative results as an opportunity to explain their possible significance and/or how they may form the basis for future research.

Failure to provide a clear summary of what was learned In order to be able to discuss how your research fits within your field of study [and possibly the world at large], you need to summarize briefly and succinctly how it contributes to new knowledge or a new understanding about the research problem. This element of your conclusion may be only a few sentences long.

Failure to match the objectives of your research Often research objectives in the social and behavioral sciences change while the research is being carried out. This is not a problem unless you forget to go back and refine the original objectives in your introduction. As these changes emerge they must be documented so that they accurately reflect what you were trying to accomplish in your research [not what you thought you might accomplish when you began].

Resist the urge to apologize If you've immersed yourself in studying the research problem, you presumably should know a good deal about it [perhaps even more than your professor!]. Nevertheless, by the time you have finished writing, you may be having some doubts about what you have produced. Repress those doubts! Don't undermine your authority as a researcher by saying something like, "This is just one approach to examining this problem; there may be other, much better approaches that...." The overall tone of your conclusion should convey confidence to the reader about the study's validity and realiability.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8; Concluding Paragraphs. College Writing Center at Meramec. St. Louis Community College; Conclusions. The Writing Center. University of North Carolina; Conclusions. The Writing Lab and The OWL. Purdue University; Freedman, Leora and Jerry Plotnick. Introductions and Conclusions. The Lab Report. University College Writing Centre. University of Toronto; Leibensperger, Summer. Draft Your Conclusion. Academic Center, the University of Houston-Victoria, 2003; Make Your Last Words Count. The Writer’s Handbook. Writing Center. University of Wisconsin Madison; Miquel, Fuster-Marquez and Carmen Gregori-Signes. “Chapter Six: ‘Last but Not Least:’ Writing the Conclusion of Your Paper.” In Writing an Applied Linguistics Thesis or Dissertation: A Guide to Presenting Empirical Research . John Bitchener, editor. (Basingstoke,UK: Palgrave Macmillan, 2010), pp. 93-105; Tips for Writing a Good Conclusion. Writing@CSU. Colorado State University; Kretchmer, Paul. Twelve Steps to Writing an Effective Conclusion. San Francisco Edit, 2003-2008; Writing Conclusions. Writing Tutorial Services, Center for Innovative Teaching and Learning. Indiana University; Writing: Considering Structure and Organization. Institute for Writing Rhetoric. Dartmouth College.

Writing Tip

Don't Belabor the Obvious!

Avoid phrases like "in conclusion...," "in summary...," or "in closing...." These phrases can be useful, even welcome, in oral presentations. But readers can see by the tell-tale section heading and number of pages remaining that they are reaching the end of your paper. You'll irritate your readers if you belabor the obvious.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8.

Another Writing Tip

New Insight, Not New Information!

Don't surprise the reader with new information in your conclusion that was never referenced anywhere else in the paper. This why the conclusion rarely has citations to sources. If you have new information to present, add it to the discussion or other appropriate section of the paper. Note that, although no new information is introduced, the conclusion, along with the discussion section, is where you offer your most "original" contributions in the paper; the conclusion is where you describe the value of your research, demonstrate that you understand the material that you’ve presented, and position your findings within the larger context of scholarship on the topic, including describing how your research contributes new insights to that scholarship.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8; Conclusions. The Writing Center. University of North Carolina.

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What is Social Science?

What are the social sciences and why do they matter?

Social science is the study of people: as individuals, communities and societies; their behaviours and interactions with each other and with their built, technological and natural environments. Social science seeks to understand the evolving human systems across our increasingly complex world and how our planet can be more sustainably managed. It’s vital to our shared future.

Social science includes many different areas of study, such as how people they organise and govern themselves, and broker power and international relations; how wealth is generated, economies develop, and economic futures are modelled; how business works and what a sustainable future means; the ways in which populations are changing, and issues of unemployment, deprivation and inequality; and how these social, cultural and economic dynamics vary in different places, with different outcomes.

Did you know…

UK social sciences are ranked among the best in the world for their research.

Popular A Levels

Of the 12 most popular A level subjects, five are social sciences: business studies; economics; geography; psychology; sociology.

Around 40% (>230,000) of new undergrad students chose to study social science subjects at UK universities in 2020-2021. Social sciences are in demand.

Social science graduates are well paid. Many earn as much as STEM graduates.

Vital to business

Social science knowledge and skills from leadership and strategic planning to international liaison, sustainability, consumer growth, marketing, legal and financial management are vital to business.

In a recent survey, two thirds of the research questions the UK government sought answers to centred on social science.

Social science helps us make sense of our changing human world, inspiring us to be culturally sensitive, environmentally aware and socially responsible citizens.

Social Science Disciplines

Social science comprises 16 major disciplines and many sub-disciplines and specialisms. Find out about each and how they help us understand our contemporary human world.

Anthropology

Anthropology is the study, generally using ethnographic methods, of how different groups of people create and give meaning to their social world – ‘society’ – and how that social world places constraints on their behaviour and relationships. It is interested in what societies have in common, what differentiates them and how they change.

Business and Management

This is an interdisciplinary field including accounting, EDI, ethics, finance, HR, information systems, leadership, marketing, operations, organisational behaviour and strategy. It includes qualitative and quantitative analyses of individuals, organisations, systems, change and the role of organisations and management in society, environment and economy.

Demography, Social Statistics & Methods

Demography is the study of human populations. Demographers and social statisticians use social statistics and demographic methods to analyse the influences on population structures and dynamics, such as population growth, fertility, mortality, ageing and migration patterns. The discipline supports social policy-making at all scales that requires sound demographic analysis for decision-making.

Development Studies

Development Studies investigates global, national and local processes of change, including social, economic, political, cultural, environmental and technological. It focuses largely on contexts characterised by poverty, inequalities, environmental vulnerability and socio-political conflict and involves the critical interrogation of development theories, structures, processes, policies and practices from multiple disciplinary perspectives.

Human beings interact with the physical world and each other to produce artefacts and services that support and enhance their lives – offering usefulness and pleasure. Economics is the study of the principles, laws and dynamics that drive these economic processes; about how such wealth is created and subsequently distributed.

Education is the study of learning, teaching and human development. A well-established discipline in universities, it also has strong multi-disciplinary links for example with sociology, psychology, and philosophy. The study of education in society, including the practice and policy of early years settings, schools, colleges and teacher education, is an important aspect.

People, places and environments are central to our lives. Geographers explore the interactions between them, globally and locally. Analysing and understanding the dynamics of cultures, societies and economies, how they vary between places, and why differences and inequalities exist, inform some of the big issues facing society today.

International Relations

International Relations focuses on interactions of states and non-state actors through the tools of diplomacy, trade, and violence. Pressing questions including climate change and migration are analysed at local and global levels. Attention is paid to how gender, race, and sexuality are affected by and shape responses to these challenges.

Leisure Studies

Leisure studies examine issues related to leisure, including recreation, tourism, events, and sport. It includes studies of individuals and the relationship between leisure and wider society. It draws on scholars with backgrounds in many different social science disciplines, including economics, sociology, geography, psychology, planning, sports science, and recreation management.

Linguistics

Language is central to social interaction. Linguistics, and applied linguistics in particular, offers insights, often based on millions of words of data, into questions such as how language is used to inform, persuade and mislead – e.g. in business, healthcare and security contexts -and how we learn an additional language.

Space and place matter to us all. Planning is about creating efficient and equitable places. It is about helping to make communities that are socially inclusive, economically competitive and environmentally sustainable. Planners are at the heart of efforts to address the climate emergency, reduce regional inequalities and overcome housing shortages.

Political Studies

From democracy to dictatorship and local councils to international organisations, the study of politics examines how power is obtained, kept, lost, mobilised, divided, used and abused. It asks who gains and who loses from these processes, and why. Politics is studied in theory and practice, sometimes using scientific methods.

Psychology is the scientific study of the mind and how it influences our behaviour, from communication and memory to thought and emotion. It is both an academic discipline and a vital clinical practice, examining human behaviour, thoughts and feelings through observation, measurement, and testing.

Regional Studies

Regional Studies is interdisciplinary and concerns with the analysis of sub-national regions and regional issues. It investigates how and why regions and cities develop. It seeks to understand how economic and political processes are influenced by regional and local circumstances and vice versa.

The study of society, and the ways that social life is organised, structured, and experienced. Focusing on big issues such as inequality, poverty, crime, racism and climate change, and exploring how we make sense of, navigate and change our interpersonal and everyday lives, sociology combines the study of self and society.

Statistics underpin many other disciplines. They help us understand and quantify what is happening in society and the economy, and provide the methods and tools to help researchers of all kinds collect, analyse and interpret data.

Careers in Social Science

A wide range of well-paid and socially responsible careers are open to social science students. Some roles use skills and approaches learned in all social science disciplines. Other roles are more specific to individual subjects.

Find out more

The We Society Podcast

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Join acclaimed journalist and Academy president Will Hutton, as he invites guests from the world of social science to explore the stories behind the news and hear their solutions to society’s most pressing problems.

Listen and find out more

Making a Difference

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Environmental studies
Science, technology and society

Citizen science evolved through multiple disciplinary manifestations into a new field of study and a participatory method of enquiry. While most citizen science projects take place within problem-focused natural sciences, social sciences and humanities help understanding the human dimension and open a broad methodological spectrum for enriching scientific research with new approaches and for boosting public participation. In this paper, we use a meta-synthesis approach to explore how citizen science is practised in the so far less addressed social sciences and humanities by focusing on the role of the citizens, the goals and approaches of the projects, the tasks in which citizens are engaged and their gains across projects of diverse disciplinary background. Our findings indicate that social sciences are gaining more acknowledgment within interdisciplinary citizen science projects by addressing ‘wicked’ problems of human behaviour and agency, while humanities are in quest of a better-defined locus in citizen science. We conclude that social sciences and humanities still face considerable barriers to infiltrate citizen science; the payoffs are substantial and already rewarding for several subfields in social sciences and humanities.

Determinants of behaviour and their efficacy as targets of behavioural change interventions

Frequent disturbances enhanced the resilience of past human populations

Interviews in the social sciences

Introduction: locus of social sciences and humanities in citizen science projects.

During the last decade, an exciting trend has been recorded worldwide, with thousands of lay people from, in, and across different countries becoming engaged in citizen science (CS) projects, through various modes and channels of collecting, commenting, transcribing and analysing data. Variability in CS is high, with projects covering a vast array of topics, from bird observation to public health and bible study (Eitzel et al., 2017 ). The aspirations for supporting such activities are quite ambitious, with claims regarding the expected outcomes ranging from enabling the transition of research and policy towards sustainability (Petridis et al., 2017 ; West and Pateman, 2017 ), to participatory innovation (Hecker et al., 2018a ) up to increased scientific literacy and responsive education (Bonney et al., 2016 ; Miczajka et al., 2015 ; Wals et al., 2014 ). All these claims are continuously debated from the CS policy perspective, too (Science Europe, 2018 ).

However, CS has been predominantly pursued within the realms of the natural sciences (Crain et al., 2014 ). Activities and projects following social sciences and humanities (SSH) topics and approaches are less easily discernible in CS practice, although they may be fuelled by some genuine and challenging questions (Heiss and Matthes, 2017 ). A survey of CS projects in Europe revealed that more than 80% of current CS practice is confined to life and natural sciences and only 11% to the social sciences and humanities (Hecker et al., 2018b ). These findings point to a previous study (Heinisch, 2017 ), which demonstrates that among 1691 CS projects listed in several English-language and German-language project directories, almost 99% are contributory projects Footnote 1 . The latter study also shows that there are only a few published cases in which citizens held an active role in scientific procedures due to the method used, e.g. participatory action or collective intelligence. However, this is not in accordance to how CS was initially conceived and what stands as good CS practice, as, e.g. laid down in the ten principles proposed by the European Citizen Science Association (Robinson et al., 2018 ), all confirming that citizens should actively contribute to increasing the body of academic knowledge.

The underrepresentation of SSH may be due to several reasons. One of them is the stable and long-lasting bonds between CS and the natural sciences, with pioneer lay scientists mainly directing their interest towards the study of physical and natural phenomena by making use of positivistic methods of data collection and analysis. Such preponderant epistemological orientation in CS practice towards the natural sciences paradigm is coupled with an enduring controversy over the legitimacy of SSH and its academic status, and a growing turn of the interest among research funding schemes and institutions to more technocratic frames, goals and procedures in scientific enquiry (Heilbron et al., 2017 ). Furthermore, epistemological considerations interlink with methodological and ethical concerns when dealing with ‘sensitive’ SSH topics. They may also resonate a neoliberal drawback of academia and higher education and the transformation of universities into business-managerial enterprises with a technocratic orientation, where SSH became largely depoliticised and marginalised (Chan, 2011 ; Crawford, 2002 ; Tyfield et al., 2017 ). After all, SSH were soon categorised as junk science (as US politician Tom Coburn put it) (Geppert and Hollinshead, 2017 ). Hence, it is no surprise that for the time being SSH are underrepresented or hard to trace in CS practice.

SSH offer a long history and experience in fostering and reflecting the relationship and co-working practices between lay people and scientists, but predominantly under different terms such as participatory (action) research. Also, the translation of the term ‘science’ outside English speaking countries is broader and comprises humanities and social sciences, which in the back-translation of ‘citizen science’, a broadly used term, may cause confusion. However, SSH is assumed to provide helpful methodological (especially epistemic) contributions to the growing field of CS. For all these reasons, further exploring the role and added value of SSH in CS practice and boosting a more prominent position for them in CS practice seem quite necessary.

Then, social sciences with an emancipatory role endow citizens to contribute to research and to inform policymakers using science-based evidence (Purdam, 2014 ). This allows democratising science and increasing its responsibility towards society (Corburn, 2005 ; Irwin, 1995 ; Lakshminarayanan, 2007 ; Lidskog, 2008 ; Purdam, 2014 ; Silvertown, 2009 ; Swan, 2012 ). Given these nuances, a closer look is necessary for boosting a more prominent position for them and understand their role. Moreover, CS has a potential avenue to demonstrate the value of SSH by integrating CS as an approach.

Nevertheless, mainstream CS practice has started to expand to new research foci and explore new avenues of citizen involvement that express a more open and genuine stance towards SSH and how to make room for them in the field. This has to do both with the need to broaden the realms of CS in terms of what has been traditionally dealt by as ‘science’, and to a renewed interest in developing an enriched understanding of how to promote and sustain citizen involvement in scientific research over some socially relevant but still uncharted CS topics. It has also to do with the need to instil an emancipatory role in the citizen’s contribution to research; inform policymakers with new science-based evidence (Purdam, 2014 ); and lead to a democratisation of science and the awakening of its responsibility towards society (Corburn, 2005 ; Irwin, 1995 ; Lakshminarayanan, 2007 ; Lidskog, 2008 ; Purdam, 2014 ; Silvertown, 2009 ; Swan, 2012 ).

Our overarching research question is about the current and potential role of SSH in CS practice. Therefore, we ask how SSH could provide methodological frameworks to the growing field of CS and how the alleged added value of SSH in CS practice could be better deployed. The study reported in this paper further explicates the locus of SSH in CS projects by exposing where they meet with or differ from other fields of sciences. Our interest, therefore, focuses on what the current state of SSH in CS is, and whether there is a promising tendency towards building mutually rewarding interdisciplinary synergies for the sake of science and society. The paper begins with a description of the analytical framework that was elaborated to identify relevant areas of comparison within and across SSH as well as between SSH and natural and biomedical sciences in CS practice, based on a meta-synthesis of attentively selected publications. The findings are then presented and discussed with a view to investigating whether and how a closer bond between CS and SSH could change the way of doing research and boost citizen involvement in CS projects.

Methodological approach

Since the aim of the study was to develop a more integrated understanding of the extent and ways the SSH are represented and dealt with in current CS practice, a meta-synthesis methodology (Paterson et al., 2001 ; Zimmer, 2006 ) was adopted to identify and examine all related cases reported in the research literature. More particularly, meta-synthesis has been proposed as a qualitative method of enquiry offering the possibility to identify and integrate the contribution of different research studies to the generation of more formalised and robust knowledge (Zimmer, 2006 ). It is, therefore, a combined (analysis and interpretation) approach to individual studies developed within possibly different disciplinary fields and paradigms, diverse research foci and methodologies, aiming to prompt a more integrative understanding of the knowledge gained.

As with any other research activity, a meta-synthesis needs to be framed with an appropriate research aim or question(s) in mind (Table 1 ). This framing directed processes regarding the location and identification of relevant papers in available databases, such as the search-and-retrieve strategies to be employed. Based on the aim of our study, five research questions were formulated as follows: (1) What methodological approaches and roles of citizens are used by CS projects and activities claiming to pertain to SSH? (2) What disciplinary fields within SSH do these CS projects encompass and what do diverse interdisciplinary synergies piece together? (3) What are the SSH topics that have engrossed or attracted most of the interest in CS practice so far? (4) What purposes are defined to incorporate SSH in CS projects? (5) What are the benefits of citizen-generated data? This set of research questions and related analytical units resulted from two workshops organised in 2018 within the COST Action CA15212 ( https://cs-eu.net/ ), which already dealt with that overall question of SSH in CS. The first workshop was held at Kaunas University of Technology where 13 participants discussed the concept, methods and existing practices of CS in SSH (Butkevičienė, 2018a ). The second workshop was held at the University of Geneva where 15 participants refined their discussion into more analytical categories (Butkevičienė, 2018b ). Participants of both workshops had a different educational and professional background.

Given that the whole process of meta-synthesis involves more divergence than linearity, in order to ensure methodological quality, transparency related to steps and criteria is very important, e.g. from where and how the papers were located. In our study we opted for two of the largest databases: (a) Clarivate Analytics Core Collection (Science Citation Index Expanded, Social Science Citation Index, Arts & Humanities Citation Index, Conference Proceeding Citation Index—Science Edition & Social Science & Humanities Edition) and (b) EBSCOhost research databases. Both databases are among the most well-known and widely used and provide access to papers published since 1990. Particularly, Clarivate Analytics is one of the major indexing and abstracting databases (Lor, 2018 ), and EBSCOhost is a product of EBSCO Information Services from the largest private companies in the area. Moreover, these two databases cover a wide range of disciplines and topics, including CS. This allowed us to extend our focus not only on journals related to the topic of CS (e.g., open-access journal “Citizen Science: Theory and Practice”), but also to trace how CS topic is addressed in the light of interdisciplinarity, so in the thematically broad-scope journals. For this purpose, we chose two major well-known multidisciplinary databases.

While carrying out a focused screening of papers through these two databases and in order to avoid different connotations used under potential synonyms, a combination of two keywords only was used as subject terms/topics (e.g. citizen science AND social sciences > TS = (citizen AND science) AND TS = (natural AND sciences)). Search results were retrieved twice, in October 2018 and in January 2019. Overall, 2763 records were retrieved (Fig. 1 ). Both databases suggested mostly the same papers, although the availability of the full texts differed.

Selection procedure for the papers to be reviewed.

As the second step, and in order to effectively proceed to the papers’ selection, two authors of this paper (the first and second in order of appearance) selected solely the full texts available on-site (based on subscriptions of their universities) to avoid endless efforts to stabilise the sample. This, in turn, resulted in a sample of 1244 full-text papers. The same investigators used the manual perusal of titles, abstracts and keywords to endorse relevance for each of the papers (e.g. an explicit mention of CS, including alternative akin wording, such as ‘citizen participation’ or ‘civic science’; or a clear mention of the field of sciences, such as social, environmental, etc.). This process led to the pre-final set of papers, a necessary step before determining the final set of papers for further analysis (Kullenberg and Kasperowski, 2016 ). Overall, 344 full-text papers in English, Spanish and French were identified and submitted to a preliminary meta-synthesis (Haddaway et al., 2015 ; Zimmer, 2006 ). Even then, not all 344 papers provided enough information. Moreover, some papers were meta-analyses themselves or focused on scientific outcomes only; therefore, they served to contextualise SSH within CS, and not as raw data.

Nevertheless, the 344 papers in the actual process of meta-synthesis allowed us to develop a more in-depth view of each paper and determine a more refined list of them. To do so, we divided all papers by our expertise in the field (i.e. humanities, social, biomedical and natural sciences) and then distributed them equally among a field team along with a table containing the research questions and a list of the analytical units for the meta-synthesis (Table 1 ). Data are here named as analytical units which also served as the main inclusion criteria after the manual perusal of a full text.

Each investigator used a standard spreadsheet developed for the study, on which s/he kept detailed notes for each paper reviewed (horizontal rows) based on the analytical units (vertical columns). Each individual investigator proceeded to the meta-synthesis of multiple studies in a related field and afterwards all nine met, discussed and agreed on the consolidation of their findings (the content in the cells of all individual spreadsheets). This approach both allowed a collective generation of knowledge and ensured multiple viewpoints.

Among the most important and recurrent issues raised by all investigators was that only a few studies provided comprehensive information about analytical units (Table 1 ). Discussions led to a critical appraisal of each paper’s rigour and concluded with a refined final list of papers. In total, 62 papers were selected for being relevant and providing most of the data needed (Fig. 1 ). Out of these, 39 papers were located in the social sciences, five papers in the humanities, while two papers followed an interdisciplinary approach based on the SSH and the biomedical sciences and 16 papers on the SSH and the natural sciences. One paper ( SSP4 and BSP1 ) overlapped in two data sets, social sciences and biomedical sciences, due to the equally distributed interdisciplinary approach taken. The full texts of these 62 papers constituted the final sample of our study, based on which we conducted the meta-synthesis.

After data extraction based on the same spreadsheet as before, the findings were compared and discussed. If any of the spreadsheets did not contain enough detail on a case, the full-text paper was consulted again.

To ease the readability of data analysis, we used in-text codes for the papers reviewed by the field of sciences, namely SSP—social sciences, HP— humanities, BSP—biomedical sciences and NSP—natural sciences. All papers are also included in the list of references with an in-text code in brackets.

Limitations

Although meta-synthesis approach has some reservations (Haddaway et al., 2015 ), these can be nevertheless addressed via different techniques. For example, to minimise subjective coding biases of different investigators, we allowed for multiple disciplines to be represented in our team and resolved any disagreements via group discussion. However, our study had some built-in limitations. First, the sample of papers in some fields of sciences was very small: papers presenting interdisciplinary synergies between SSH and biomedical sciences are only two, and with humanities only five. In addition to this, CS is a contested term with different meanings for different communities (e.g. Eitzel et al., 2017 ) and may accordingly be used differently by authors, especially in the field of SSH where this term is less common. To our knowledge, there is still an ongoing work in the COST Action 15212 related to the development of an ontology for CS projects. Therefore, a greater diversity in the terms used could help us locate more papers. Hence, generalisation in these fields of sciences is rather difficult. Second, data have been collected based on two databases (Clarivate Analytics Core Collection and EBSCOhost research databases); therefore, it might be that not all papers relevant to our research questions have been traced. Furthermore, since publication strategies differ across disciplines, not all papers relevant for this study could be identified in these databases. For example, the two databases do not cover monographs, edited volumes and (online) journals which are (still) in great demand in the humanities; this makes probable that they were not listed in these databases. Nevertheless, we are aware that the citizen (social) science and citizen humanities landscape is larger than our sample. Increasing the sample by including other databases, grey literature and other online sources is an important issue for future research.

Social sciences

Methodological approaches and roles of citizens.

Though in several cases the research question(s) or hypotheses are not clearly defined, the general observation is that they are mostly demand-driven, i.e. questions were built in societal needs. Addressing societal needs is seen as a remarkable feature and highly valued in people’s everyday life (e.g. integrating traditional and local knowledge into scientific research, social perception of science and scientific spaces, or youngsters’ perception of digital technology, social design, participatory agenda-setting to fill knowledge gaps, success factors of crowdsourcing, emancipatory forms of social science research, reflective learning, learning curve of CS). One common thread surface in exploring the actual design and methodological questions related to knowledge co-creation, engaging and emancipatory form of social sciences (e.g. about the best modes of participation, trust-building).

The methods applied to the entire study are two-fold. They range from the rather conventional (literature review, (online) survey, semi-structured interviews, focus groups, content analysis) to more creative and socially innovative formats (digital storytelling, action research, participatory research, crowdsourcing, social dilemma games). Methods for citizen involvement are most often digital (e.g. mobile devices, 3D web applications, sensors, and platforms), and only sometimes personal through, e.g. gamified experiments, public talks and media advertising. Using participant observation placed the citizens in the role of researchers: ‘The volunteer observer methodology might enable and empower the citizen in the social research process and also facilitate the researching of issues where resources are limited and where populations are hard to reach’ ( SSP27 , p. 385).

Schools and educational institutions are the typical places for involvement. The role of citizens in the research cycle most often remains contributory by taking part in data collection, and there are only a few cases that citizens are involved in the whole research process. Citizens are described as simple volunteers to collect distributed data, or how to enhance decision-making processes ( SSP11 ).

Interdisciplinary synergies

CS projects in citizen social science are mostly related to interdisciplinary approaches when the issue has been analysed, taking lenses of different disciplines and integrating knowledge and methods. We identified (both as stated in the paper and assigned by the authors of this paper) 11 unique sub-fields of social and behavioural sciences (e.g. anthropology, communication, education, social and economic geography, political science, psychology, sociology, management, public policy and administration, urban studies and planning, and science and technology studies).

Regarding the fields of science, most papers ( N = 20) identify a combination of several fields of science per paper (e.g. natural sciences and social sciences; natural sciences, social sciences and humanities; applied sciences and social sciences). This shows a highly interdisciplinary nature of CS projects in social sciences.

Further analysing sub-fields of sciences, we noticed the same tendency: the major part of papers ( N = 30) combined several sub-fields of science, e.g. social geography, engineering, and humanities ( SSP1 ), information technologies, spatial sciences and social sciences ( SSP3 ), computational social science and behavioural sciences ( SSP7 ), management and natural sciences ( SSP11 ), natural sciences and social sciences ( SSP14 ), or ecology and sociology ( SSP34 ). It is important to note that some sub-fields of science are inwardly interdisciplinary. For example, nine papers identified that the research they carry out should be assigned to environmental sciences (in our classification that was assigned to the category ‘one sub-field of sciences per paper’); however, by its definition environmental sciences are already an interdisciplinary field of science. The most frequent sub-field of social sciences, mentioned in the papers, was sociology. In total, 14 papers were assigned to this sub-field of science.

The liaison of the social sciences with CS emerges through the need to learn more about different facets of societal needs. We distilled a variety of facets based on the number of CS cases described in the aims of papers analysed ( N = 39). The first facet refers to methodological solutions in CS practice, such as co-design of the study ( SSP32 ), effective ways to reach open innovation ( SSP18 ) or value and quality of data collected by citizens ( SSP25 , SSP27 , SSP28 , SSP29 ). The second facet describes managerial issues, such as risk communication ( SSP13 ), disease and another post-event management ( SSP16 , SSP17 , SSP19 ) or philanthropic marketing ( SSP33 ). The third facet relates to policy development ( SSP6 , SSP8 , SSP11 , SSP23 , SSP39 ). The fourth facet focuses on social and, where relevant, other challenges, such as ecological ( SSP4 , SSP6 , SSP14 ) and urban agriculture ( SSP26 ). The fifth facet relates to the social life of citizens, such as to monitor emotional arousal ( SSP3 ), to find out social practices in specific spaces ( SSP30 ) or examine the power of place ( SSP20 ). The sixth facet addresses the influence of technology on citizens ( SSP5 , SSP2 , SSP12 , SSP21 ). Some other facets focus on cognition, such as epistemic cultures ( SSP34 ), ethical and regulatory questions ( SSP36 , SSP38 ), reasons of cooperation ( SSP35 ) or historical development ( SSP24 ). In many projects the involvement of citizens in research contributed to the advancement of the science, so the needs of scientists too; however, there are very few CS projects that explain the benefits for citizens to be involved in research. Among these examples, we can list empowerment of active citizenship by giving citizens a voice and raising citizen awareness of a topic (e.g. post-disaster safety).

Purposes of incorporating SSH in CS projects

In some of the reviewed papers, social science theories are proposed as a frame of citizens’ involvement and the mutual benefits for participants and science. For example, the use of social-psychological theories arguing that biological and health-related findings may be related to socio-cultural-economic conditions ( SSP9 ). Critical social sciences and critical geographies serve as a critique about how commodification and neoliberalism build economic benefit around genomics and health data ( SSP16 ). Additionally, CS theory may serve as a common ground to highlight the importance of citizen involvement. For example, SSP32 takes into consideration a vast literature on how to facilitate co-creation processes. However, despite citing such theories, not all the authors seem to consider citizen participation in all the stages, adopting discourses and practices in different degrees. Like, considering that citizens should have an active role ( SSP30 ), or generalising the effects and opportunities of internet use and biodata availability for worldwide participation ( SSP3 ).

Regarding knowledge creation, epistemic analyses pointed out how citizens create narratives while addressing the learning curve of scientific topics and explaining their purpose of participating in CS projects ( SSP34 ). For example, how scientific research pays attention (and contributes) to social concerns and needs, and how co-creation and co-design processes can lead to answers to such needs ( SSP32 ); indigenous knowledge preserved through oral tradition and cultural expressions, such as a conceptual background to as a ‘broader and more multilayered understanding of the interconnection of humans’ ( SSP4 , p. 085006-1). In general terms, the conceptual frameworks drawn from the social sciences helped to provide more weight to local people’s knowledge, the expertise of the embodied experience, the situatedness and co-production of transdisciplinary knowledge ( SSP14 ) and contributed to creating an argument of trust around non-expert knowledge ( SSP12 , SSP22 ).

Benefits of citizen-generated data

The analysis of the reviewed papers revealed that citizens involved in social CS projects were asked to contribute to data collection by providing mainly personalised information but also other types of social data. Social data vary from behavioural information (e.g. personal genetic data ( SSP16 ), their own body metrics and indicators ( SSP9 ) or their bodily and emotional reactions to various states ( SSP3 ) to tracking their mobility patterns in public spaces ( SSP7 )); attitudinal and opinion-based data (e.g. their personal views towards cooperation ( SSP35 ) or how technology affects their life ( SSP5 ), their judgements regarding participation in CS projects ( SSP8 , SSP32 ) or how to promote open innovation ( SSP18 ), to expression of their political attitudes ( SSP10 ) or ecological concerns ( SSP11 )); self-reports of individual practices and lifestyle patterns (e.g. their personal nutritional and exercise habits ( SSP9 ), their points of interest in drawing some new footpaths in the area ( SSP1 ) or their channels and practices of political communication ( SSP10 ) to their modes of CS engagement and contribution ( SSP22 , SSP28 )); information about risks and hazards (e.g. shared in person ( SSP13 ) or elicited via social networks analysis ( SSP17 ), or their experience about post-disaster situations ( SSP19 )); information, ideas and personal experiences on community change trends and other social issues (e.g. migration ( SSP24 ), sustainable development ( SSP23 ) and specific urban social practices ( SSP27 ) and responses ( SSP29 )); and socio-demographic data to better understand specific situations and practices ( SSP36 , SSP37 ), or even for identifying marketing and consumer behaviour patterns ( SSP33 ).

Most of the papers reviewed ( N = 26) do not explicitly refer to whether and how they made raw data available to citizens involved. The rest of the papers reviewed mention either online data accessibility in general ( SSP3 , SSP26 ) or specify certain digital means and channels (e.g. specialised data management platforms or repositories ( SSP17 , SSP28 ), the project’s webpage ( SSP7 , SSP29 ), the project’s blog ( SSP10 ), or even via email ( SSP8 )). One paper reported that the participants had no access to the raw data, but they could receive a personalised report of the results of their own (genetic) data analysis for free ( SSP16 ). Finally, in one study ( SSP26 ) participants were not only allowed to download the raw data, but also to visualise and interact with them as they were displayed in the results charts (e.g. charts could be downloaded, emailed or shared on social media).

The situation was similar with the means employed for publicising the collected data. Most of the papers reviewed ( N = 27) do not specify whether and how they dealt with the issue at all. In a few studies there is a mention that the raw data and/or the project’s results were made publicly available and publicised through knowledge exchange ( SSP8 ) or by use of digital means ( SSP13 ). Among the most commonly used means were (open access) scientific and research papers ( SSP5 , SSP6 , SSP26 , SSP32 , SSP33 ) and the use of digital media, such as social networks and the project’s website ( SSP24 ).

Coming to what is identified by the citizens themselves as an added value from their participation in CS projects, they mentioned an acquired active scientific role instead of being the research subjects or mere informants. To get actively engaged in tasks traditionally implemented by formal scientists and professional researchers is a self-rewarding aspect of CS participation ( SSP10 ), especially when this is coupled with an acknowledgement of their contribution in academic publications ( SSP23 ). In terms of the learning gained, the citizens acknowledged increased awareness of the topic they engaged with ( SSP11 ), augmented expertise after participation in training in social science research procedures ( SSP23 ) or in any other specialised subjects (e.g. data quality ( SSP22 )), or as an outcome of the experience of participation itself ( SSP27 ). These led them to feelings of satisfaction and a sense of empowerment which were further supported by open access to the project’s data and availability of (digital) tools or more opportunities were provided for further data analysis according to their personal interests and needs ( SSP9 , SSP13 ), or even customisation of the research design and tools to develop their own new projects ( SSP1 ).

A sense of empowerment to get in personal and community action and participate in informed decision-making and policymaking, especially for disadvantaged communities, was an alternative ‘learning’ benefit for the citizens ( SSP4 ). Involvement with issues they are concerned about made their voice heard ( SSP32 ). Moreover, the knowledge gained during the CS project served as inspiration and innovation for personal life ( SSP3 ), the advancement of professional practice ( SSP6 ) or discovery about personal health and well-being ( SSP31 ). Finally, altruism-based satisfaction and the sense of serving a worthwhile goal ( SSP31 ) may be juxtaposed with more mundane or monetary benefits (e.g. money coupons were offered as a reward for participation ( SSP29 )).

The research questions and methods of the reviewed papers relate to the involvement of society when collecting, processing and analysing sources ( HP1 ), which gives researchers access to privileged information or new primary sources. Involving people may also lead to the modification of a project’s methodology, objectives, results or dissemination. This is increased in the humanities and by digital technology use as well as social networks. Therefore, these studies examined the place of crowdsourcing activities within humanities research infrastructures ( HP2 ) or reviewed the practice of public participation in three areas of digitisation (transcription, georeferencing and annotation) ( HP3 ) or analysed platforms which help to disseminate projects ( HP4 ). The findings show that these platforms usually list natural science projects which adopt a top-down approach and focus on data quantity, i.e. data collection (HP4). HP5 , however, has a clear humanities focus, i.e. historical research into CS.

The research questions related to CS are rather on a meta-level ( N = 3). For example, how to make the sciences and humanities work with and for society ( HP1 ), how platforms deepen the relationship between science and society (HP4) or CS confines to professional science, scientific practice, and education (HP5). The given examples relate to the questioning of the boundaries of professional science, distinctions between scientific practice and education.

The methods applied in the meta-studies mostly follow a qualitative approach, e.g. case studies ( HP1 ), literature reviews (HP2, HP4), content analysis (HP4), online surveys (HP2), interviews (HP2) and comparisons to create a typology of CS activities (HP3) or the study of historical documents (HP5). The methods applied to involve citizens are the use and creation of digital and analogue social networks, social media channels, media and institutions ( HP1 ). These methods served for recruitment or involvement.

The roles of citizens in the research cycle were compiling, organising, analysing and sharing sources ( HP1 ). These included data collection ( HP1 , HP4, HP5), documentation (e.g. georeferencing ( HP1 , HP3), mapping, annotation (HP3) and transcription of items ( HP1 , HP3)), or recovering sites with the help of local communities knowledgeable about protection of landscapes ( HP1 ).

The fields of science stated in the paper reviewed are history (HP1, HP5), humanities (HP2), biodiversity research and digital humanities (HP3) and natural sciences, social sciences and humanities (HP4). The additional fields of science assigned by us are history and archaeology (HP1, HP5) and other humanities (HP3). This means that they are either focused on analysing or describing CS from a humanities perspective or on combining different disciplines.

The aims in the papers reviewed differ, e.g. to analyse CS initiatives (to compare three initiatives involving civil society (HP1); to analyse relationships between crowdsourcing and humanities research infrastructures (HP2); to analyse public participation in digitisation of biodiversity research specimens (HP3); to analyse the role of volunteers in the research process (HP4)) or provide a (historical) framework for CS (to explore the networks of participants engaged in science-related activities during the 19th century (HP5)).

Meanwhile, the aim of conducting CS was explained in a few papers (e.g. HP1). There are mentions of the aim to accelerate data capture for urgent social challenges (HP3), to improve knowledge, conservation of the natural environment and ensuring that big data follow protocols to guarantee scientific validity and applicability (HP4).

The assumptions used to explain the need for CS in the research refer to the claim that citizens are also actors in the humanities (e.g. in the historiographic process) and may help to save primary historical sources. The reasons for using CS are increased coverage, access to unpublished sources scattered almost all over the world and access to local knowledge of natural resources in a specific region (HP1). Other reasons are the acceleration of the research progress by giving educators, policymakers, researchers or the public access to collections, thereby addressing data quality in CS projects (HP3).

Humanities in CS projects are not pressured to increase the quantity of data or of volunteers involved in a project. However, in some CS projects, they intend to obtain big data at low cost. Also, in the humanities, CS projects are sometimes collaborative and virtual (reaching everyone who has a computer and internet). Nevertheless, they usually follow a top-down approach, i.e. volunteers collect vast amounts of data so that professional researchers can answer research questions and enhance academic progress (HP4). The coverage and the establishment of a distributed community of citizen scientists working with professionals, thus contributing to both their own scientific education and the advancement of science (HP5), was also mentioned.

Since the papers reviewed rather analysed CS, the type of data collected by citizens was not clearly defined in a couple of reviewed papers (HP2, HP3). Citizens were asked to collect pictures, transcriptions, structured data of communities, own stories or local knowledge (HP1), environmental data (HP4) or rainfall observations (HP5). These data were used for genealogy, reciprocal exchange and communication, share and involvement of society, especially the local community (HP1), for research purposes (HP4) or in research papers (HP2). The raw data of CS projects were made available online (HP1, HP3, HP5). The data collected by users (citizens) were published on platforms (HP1) and could be used by diverse stakeholders, such as educators, policymakers, researchers and others (HP3).

Interestingly, in the rainfall research, the researcher drew some conclusions on the motivation of users, stating that the volunteers have been creating a database which can be valuable for different fields (HP5). Although the paper analyses CS in natural sciences in the 19th century and compares it with the 21st century CS, it uses methods inherent to humanities. The interplay of a few disciplines evidences a good way to enrich data and knowledge.

The added value for citizens includes a symbolic and emotional link with heritage as well as empowerment or socialisation of heritage, including identity formation and community building (HP1). This is exemplified by offline and online social networks allowing not only to collaborate, but also to create relationships and exchange knowledge between researchers and the general public. In addition, the accessibility of the methodology, the control over the data as well as the immediate publication of the work carried out and the creation of a digital contentful space were mentioned too. Citizens may benefit from participating in CS by acquiring field knowledge and skills, such as text annotation according to the Text Encoding Initiative guidelines (HP2). Furthermore, the increased public understanding of science, academic literacy (HP3, HP4, HP5) and personal development and lifelong learning (HP3, HP4, HP5) were mentioned too. Among other benefits for citizens, the reviewed papers listed items such as the personal benefit of appreciation (HP3) or contributing to science (HP5), ‘social’ rewards (e.g. through rankings, increased standing in the community or being credited and named in publications (HP2)).

Biomedical sciences

The description of methodological approaches is quite scant. Only one paper explicitly states a research question to the entire study, e.g. how groups of ‘citizen scientists’ in non-traditional settings and primarily online networks claim to be challenging conventional genomic research processes and norms ( BSP2 ). Solely qualitative approaches to the entire study are used for data analysis, such as thematic analysis and ethnography. The latter approach (ethnography) is traceable from the way how researchers describe the type of data and data collection. As the involvement of citizens is an all-the-time challenge for scientists, a snowball sampling approach was used. Citizens were asked to provide personal data about their social life, e.g. to explain spiritual and cultural aspects that affect their health and environment ( BSP1 ) and to share ‘their stated objectives, practices, and political and moral stances to institutions of expert scientific knowledge production’ ( BSP2 , p. 494). Such a role of citizens testifies their contribution to data feeding, but this is not tantamount to a partnership in data collection as the definition of CS implies.

Ties with SSH are barely noticeable. Environmental health sciences intertwine with ethnology (BSP1). This conjunction derives from the study aim, e.g. to testify ‘successful application of TEK [Traditional Ecological Knowledge] principles in federally funded research’ in order to understand the interconnectedness of environmental factors and human health (exposome and social determinants of health) ( BSP1 , p. 085006-1).

The use of SSH in CS projects is explicated through the need to learn more about different health aspects (e.g. to better understand social regulation and cultural values which are paramount to both indigenous knowledge and health (BSP1)) or to claim a more active role of lay people as potential decision-makers of their health (e.g. ‘people are no longer ‘patients’ but are instead ‘participants’ and instigators of their own health management plans’ ( BSP2 , p. 496).

The detail about what data citizens collected, what data were publicised and whether citizens had access to them is not provided. However, assumedly publishing of the reviewed papers serves this purpose to some extent. In addition to this, it is stated that citizens get the advantage of being involved in research that affects their health and the use of their personal data, e.g. ‘better informed to develop models for sustainable practice and to create lasting policies that enhance the health and quality of life’ ( BSP1 , p. 085006-6), learning ‘the ethical and legal aspects of sharing genomic information’ in terms of ownership and research conduct ( BSP2 , p. 508). These permit discovery of what other concerns citizens might have when immersing into an interaction with a scientist, and what social knowledge might be required to make their involvement safe and smooth.

Natural sciences

Most papers originally selected and read do not refer to the role and tasks of citizens at all, and subsequently do not provide a theoretical framework how to address them. Rather often, data were analysed which were collected in other contexts and projects, or mined from databases. In the papers finally reviewed as they mention SSH components, mixed-methods approaches were the most commonly applied types of methodologies. A few papers ( N = 5) had an explicitly qualitative orientation, using focus groups, individual interviews and/or participatory workshops ( NSP1 , NSP5 , NSP6 , NSP12 , NSP13 ). Some papers have combined qualitative methods with quantitative social science methods, such as surveys (NSP3, NSP6, NSP10, NSP13). Certain papers referred explicitly to quantitative natural science methodologies (e.g. experiments, modelling), but additionally used some social sciences methods to engage with the citizen scientists (e.g. online webinars, educational events, instructions of dive masters) ( NSP2 , NSP8 , NSP15, NSP16). Two papers included co-production of CS web platforms together with various CS stakeholders (NSP1, NSP7 ).

In half of the reviewed papers, citizen scientists were involved as data collectors ( N = 10). However, a few papers involved citizens in several steps of the research process, such as designing their own experiments and developing own research projects (NSP12, NSP13, NSP14 ), or collecting concerns and feelings about establishing new technologies (NSP4). In another study citizens served as observed objects when investigating how the observation of butterflies in their garden changed their behaviour patterns (NSP5).

The papers are mainly written from a natural scientist perspective with a strong focus on the epistemic scientific outcomes (e.g. NSP9 , NSP15 , NSP16). Citizens and their roles were rarely addressed beyond data collection. An interesting example is a more review-like study on civic monitoring (NSP8). The authors concluded that if both expertise from biological sciences and technology research (NSP13) and initiatives to develop integrated approaches to develop and evaluate environmental stewardship ( NSP3 , NSP14) came together, the intrinsic contradictions of human impact in citizens may turn into a more positive recognition of the role of humans.

Expertise from social sciences is involved to address the social dimension of specific projects. One example is the use of wave energy in Oregon. ‘A multidisciplinary group of social scientists’ ( NSP4 , p. 84) supports the integration of the stakes and interests of the local citizens. The other way around another project worked (NSP2): here results from a biological/environmental CS project—scuba diving—intended to inform educational programmes and research. Questionnaires to assess educational progress can be tagged as a method based in social sciences. Questionnaires are also used in other projects focusing on natural sciences (e.g. in order to understand the motivations of citizens or to improve practical or communicational challenges (NSP8)). Next to these, more evaluation-oriented methods, skills of social sciences are needed to co-create projects and enhance their social impact.

The main or most visible users of the collected data are researchers. The question arises regarding the full integration of citizens in the use of the collected data and the initiation of CS projects. Most of the papers describe top-down (initiated by researchers) CS projects (e.g. NSP3, NSP16 ), although bottom-up (community-driven) approaches were also identified (NSP14).

The reviewed papers do not always specify the availability of the raw data; therefore, it remains unclear who is the genuine owner of the data.

There are a few papers with a clear statement that raising-awareness is the main added value for citizens (e.g. ‘BugMap has proven efficient in stimulating scientific literacy and aided in raising public awareness’ ( NSP11 , p. 14)). Also, there are papers which stress the inclusion of the collected data as part of a resource management activities (e.g. NSP14).

CS projects gain impact if they reflect more carefully the role of citizens, i.e. are more aware of the social dimension of the projects situated in the realm of natural sciences. Obviously, journals become more open, ‘Insects’ does not automatically imply a social dimension but hosts a relevant paper ( NSP10 ).

When mapping fields of sciences in citizen social science projects, two main focal points regarding interdisciplinary distribution were identified. First, in most papers two or three disciplines are combined to answer the research question. The second refers to one-discipline/one-field projects; however, some disciplines are of interdisciplinary character (e.g. environmental research). Overall, just slightly more than half of the 39 papers we assigned to social sciences explicitly indicate their belongingness to social sciences. All the reviewed humanities papers, however, state that they refer to the (digital) humanities. This implies that social sciences are invisible, i.e. hidden behind other sciences in CS projects.

Nevertheless, the presence of social science theories is approached infrequently in CS. Although, some concepts related to social organisation and citizen involvement are implicated in many assumptions (e.g. the need to collaborate with diverse stakeholders ( SSP6 ), to transfer open innovation from private sector to public policies using knowledge of citizens ( SSP18 )). Most of these concepts helped to address the dichotomy between experts and laypeople, giving value to the plurality of voices and the richness of local knowledge. Social sciences help to untie those assumptions related to the organisation of citizens and their role in research projects. However, concepts that were drawn from their theory can cause several wrong assumptions about the motivations of citizens in participating in CS projects. As we saw in several studies, social sciences can provide frameworks and methodologies to address the complexities of interdisciplinary research and reduce the uncertainty around these assumptions. Social science concepts (e.g. interdisciplinary knowledge, public science, cooperative research, action research) could be helpful in facing the situatedness of knowledge creation and engage with people’s knowledge, and embodied experiences.

The ways citizens are asked to contribute to research presents a great variability and richness. Their contribution mainly comes in the form of personalised information on various behavioural, cognitive and attitudinal aspects of individual and social human agency and experience, in relation to a range of social situations, phenomena and practices. Personal information, ideas and experiences can be further coupled with socio-demographic data, so that there is richness of evidence that comes forth in a multi-faceted way.

Most of the raw data are either online accessible to the citizens or are sent to them as personalised analysis reports along with some extra tools to visualise and experiment. Publicity of the data is achieved through mainly (open access) papers, social networks and the project website. Both are recognised as important assets of a CS project that reinforce motivation for participation and cultivate a sense of connectedness with and appropriation of the project.

As to the added value of citizens’ participation in CS, active involvement in scientific practice with formal scientists and professional researchers is most common, followed by various learning benefits and a sense of empowerment to transfer this knowledge to further research and/or to their personal and communal life.

Although the reviewed papers in humanities report an underdeveloped link to CS projects, they show that CS can contribute to identity formation, community building, acquiring knowledge and skills as well as to increase academic literacy. Regarding the participants’ motivation, some of these papers assume that the motivation for people to participate voluntarily in CS includes the contribution to a greater good. Additionally, appreciation or social rewards through gaining standing in the community may also be important aspects why volunteers participate in CS. Interestingly, none of these reviewed papers mentions monetary rewards; however, the funding of such projects may have restrictions regarding establishment of prizes.

Furthermore, humanities have different approaches to CS. They use CS as a tool (e.g. crowdsourcing in the field of cultural heritage and digital humanities (Dobreva and Azzopardi, 2014 ; Oomen and Aroyo, 2011 )), as this is a common practice in CS projects. In this respect, the term ‘citizen humanities’ was introduced (e.g. Adamson, 2016 ; Dunn and Hedges, 2018 ). In addition, the humanities may facilitate the meta-analysis of CS history which also holds partly true for social sciences (e.g. social scientists are somewhat more interested in studying CS than conducting it, but social sciences are already increasingly conducting citizen social science (SSP15)).

Research clustered under ‘natural sciences’ will enhance its impact when reflecting the role of citizens in more detail. A closer link to social sciences may enrich the theoretical framework and set of methodologies to solve the wicked problems of the sustainability turn which are often linked to different interests, perceptions, or routines.

Very few reviewed papers explicitly testify that though scientists do not envisage giving access to the citizen-generated data as the primary benefit of their study, other citizens reuse these data (e.g. geospatial data), particularly when published online, for different purposes, and provide durability for data after the project end (Craglia and Shanley, 2015 ). This implies accidental (unplanned) benefits of the latter contribution to data use ( accidental contribution to CS ). Another example of accidental contribution emerges when citizens enrich the dataset without knowing how their data will be further used (e.g. user’s locations taken from his/her tweets) (Case et al., 2015 ).

The analysis of the reviewed papers does not explicitly evidence how citizen-generated data, published within a paper, was communicated to citizens to increase their benefits gained from taking part in CS. Therefore, further research is needed to explore whether and how scientists advertise their CS-related papers through online social networks. Usually, scientists are seen as isolated (Pilbeam and Denyer, 2009 ) and non-residents of online social networks (White and Le Cornu, 2011 ) (read more on typologies of users of online social networks in Tauginienė and Kalinauskaitė, 2018 ).

Finally, the claims about awareness-raising and similar outputs of CS projects are fairly well discussed. However, changes in human behaviour and cognition (particularly learning the level of pre-knowledge and post-knowledge about the topic) are not discussed (e.g. Fujitani et al., 2017 ).

Conclusions

Our research findings evidence the strong interdisciplinary character of SSH in CS projects. Quite often, social sciences are ‘married’ with environmental research or natural sciences and have a propensity towards biomedical sciences due to ‘wicked’ problems they are addressing. In this way, social sciences are less explicitly visible and recognisable within the interdisciplinary CS projects due to the general perception of science (e.g. an issue is situated in a specific field of sciences (e.g. climate change in natural sciences), but linked to values ascribed to SSH).

Though CS projects give room to harness SSH in order to gather rich data and to increase the body of interdisciplinary knowledge, we should admit that SSH are yet largely underutilised in CS. Some sub-fields of social science testify a better receptivity (e.g. psychology, management); however, some sub-fields of humanities are not yet part of CS. Therefore, social sciences seem preeminent due to their double role, doing research on CS practices and making their own projects to ‘improve’ the world (at least for the participants). Meanwhile, humanities are more neglected, so a rarity in science. Taking these points in mind, although the reflective role of SSH is discernible (e.g. via questionnaires/evaluation, ways of cooperation), this needs revisiting and strengthening the role of SSH in CS (e.g. to find out who the participants are). We do also believe that if the reflective potential and (inter/trans)-disciplinary skills of SSH is better utilised, CS will improve massively with regard to increasing sustainability if, on the one hand, SSH frameworks are applied more proactively to understand the socio-technical character of challenges, such as climate change or the loss of biodiversity, where value systems, economy, and governance system are in fact underlying factors, and, on the other hand, methodologies and skills from especially social sciences are applied to understand the motivation and learning processes of participants better to increase their self-efficiency, and the project outcomes and impacts.

Data availability

The datasets generated during the current study are available in the Zenodo repository, https://doi.org/10.5281/zenodo.3739352 .

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This publication is based upon work from COST Action CA 15212 Citizen Science to promote creativity, scientific literacy, and innovation throughout Europe supported by COST (European Cooperation in Science and Technology). We do also thank Maria Begoña Peña Lang, a researcher at the University of the Basque Country UPV/EHU (Spain), for her helpful comments on the initial research design.

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Original research article, understanding the societal impact of the social sciences and humanities: remarks on roles, challenges, and expectations.

1 Research Program Knowledge and Society, Alexander von Humboldt Institute for Internet and Society, Berlin, Germany
2 German Institute for Economic Research, Berlin, Germany
3 Research Area Research System and Science Dynamics, German Centre for Higher Education Research and Science Studies, Berlin, Germany
4 Department of Social Sciences, Humboldt University Berlin, Berlin, Germany
5 Max Planck Institute for Human Development, Berlin, Germany

Science is increasingly expected to help in solving complex societal problems in collaboration with societal stakeholders. However, it is often unclear under what conditions this can happen, i.e., what kind of challenges occur when science interacts with society and what kind of quality expectations prevail. This is particularly pertinent for Social Sciences and Humanities (SSH), which are part of the object they study and whose knowledge is always subject to provisionality. Here we discuss how SSH researchers can contribute to societal problems, what challenges might occur when they interact with societal stakeholders, and what quality expectations arise in these arrangements. We base our argumentation on the results of an online consultation among 125 experts in Germany (representatives from SSH, learned societies, stakeholders from different societal groups, and relevant intermediaries).

Introduction

Societal impact is an increasingly important evaluation paradigm in science governance. This trend can be seen in the implementation of large-scale impact agendas in various research and innovation systems over the past decade. Examples include the Research Excellence Framework in the United Kingdom, the Standard Evaluation Protocol in Netherlands, or the Excellence in Research framework in Australia ( van der Meulen and Rip, 2000 ; Geuna and Martin, 2003 ; Bornmann, 2013 ). Consequently, research is no longer assessed according to its scientific relevance alone but also according to the value it appears to generate for society. In Germany, where the present study was conducted, the societal impact of research is also at the top of the agenda of policymakers and research funders, although under a variety of terms. The German Ministry for Education and Research, for example, argues in a policy paper that a dialogue with society must become part of the logic of scientific reputation ( BMBF, 2019 ).

This gradual evolution of societal impact as an evaluation paradigm was preceded by a shift in the scholarly conception of the relationship between science and society, which can be summarized as a shift “from deficit to dialogue” ( Bucchi, 2008 ; Davies et al., 2009 ; Reincke et al., 2020 ). According to this view, science no longer provides knowledge to resolve a deficit but should develop “socially robust knowledge” together with societal stakeholders ( Nowotny et al., 2001 ). This shift in the conception of the science-society interface implies that societal impact requires interaction between scientific and societal stakeholders. As a result, evaluation frameworks increasingly focus on processes rather than outcomes, thus rely more heavily on narratives and on formative methods more than summative ones. An example of the latter is the SIAMPI approach, which focuses on ‘productive interactions’ between science and society ( Molas-Gallart and Tang, 2011 ; Spaapen and van Drooge, 2011 ).

The focus on societal impact in science governance and on interaction as a means to achieve this is particularly controversial for the social sciences and humanities (SSH), which we conceive of here as all research disciplines and subdisciplines that deal with social, societal, and cultural matters. On the one hand, from an internal scientific perspective, SSH disciplines investigate social life itself. This implies that subjects, investigators, and audiences tend to merge with one another and that value judgments might play a particularly important role ( Davies et al., 2008 ; Cassidy, 2014 ). As a result, when SSH researchers interact with societal stakeholders, questions of demarcation and boundary dissolution might arise ( Gieryn, 1983 ; Benneworth and Olmos-Peñuela, 2018 ). On the other hand, from an external perspective, evaluation exercises have rarely considered the particular epistemic conditions and specific utilization logics for SSH research ( Reale et al., 2018 ). Critics have noted the mismatch between indicators and SSH notions of quality, the lack of consideration for contributions that are critical rather than solution oriented, and the overly simple framing of societal impact as economic outputs, such as the number of patents or spin-offs ( Benneworth, 2015 ; Ochsner et al., 2017 ; Fecher and Hebing, 2021 ). Generally, established models for knowledge transfer do not do justice to the complexities of the diverse SSH disciplines and their many publics ( Davies et al., 2008 ).

Arguably, SSH research makes important societal contributions, but these are not well understood—at least not in the governance of science. We therefore recognize a need to better understand the societal impact of SSH disciplines in terms of a) the role they might play for societal challenges, b) the problems that might arise in interactive settings that involve SSH scholars and societal stakeholders, and c) the (possibly conflicting) quality expectations that are placed on their interaction. These objectives motivate our exploratory study, which consists of an online consultation with 125 experts (i.e., SSH researchers from different disciplines along with relevant societal stakeholders). Here, we report on the results of this consultation and reflect on the implications these might have for research evaluation.

Research Interest

The role of social sciences and humanities disciplines in response to societal problems.

There is some controversy about the role that SSH research can play in tackling societal problems: While some scholars argue that these fields should augment and emphasize their transformative potential ( Sörlin, 2018 ; Sigurðarson, 2020 ), others attribute a rather passive role to them, suggesting that they should create system knowledge (i.e., knowledge that increases understanding of a social issue) or orientation knowledge (i.e., knowledge that helps to determine possibilities for action) ( Becker, 2002 ; Jahn et al., 2012 ). One could furthermore argue that the public value of SSH research is not necessarily captured by their usefulness in solving problems but rather by their capacity to critically reflect on the problem itself and its potential solutions ( Olmos-Peñuela et al., 2015 ). In this regard, the societal impact of SSH research may also be counterintuitive if one expects clear-cut solutions to problems formulated in advance. Critics of an overly narrow conception of impact as research utilization have also pointed out how social science knowledge tends to be used in diverse ways, many of which are implicit ( Davies et al., 2008 ; Meagher et al., 2008 ; Stehr and Ruser, 2017 ). Weiss (1980) , for example, observes that expertise can “creep in” as conceptual knowledge that influences ideas and decisions. Compared to the natural and technical sciences, the impact of the SSH is thought to be more indirect and less visible. While utilization of SSH might be discreet, it can also be symbolic to the extent that it is used to justify political decisions that are already made ( Weiss, 1980 ; Albæk, 1995 ; Amara et al., 2004 ).

In summary, it is possible to identify quite different (often normative) perceptions of the societal role of SSH. Accordingly, the notion of socially relevant knowledge attributed to SSH disciplines varies: from more transformative and instrumental knowledge, to more indirect conceptual knowledge, to more counterintuitive critical knowledge. The different kinds of knowledge evoke quite different understandings of the role that the SSH should play in addressing societal challenges, which motivates our first research question (RQ1): What role is attributed to the SSH in addressing societal challenges?

Challenges for Collaborative Arrangements Involving the SSH and Societal Actors

In the sociology of science, the shift from deficit to dialogue is associated with concepts like “Mode 2,” “post-normal science,” or “triple helix” ( Funtowicz and Ravetz, 1992 ; Gibbons et al., 1994 ; Leydesdorff and Etzkowitz, 1998 ). These concepts all describe knowledge production as a mode of collaboration between scientific and societal stakeholders. According to a concept of transdisciplinarity, the main challenge for such collaborative arrangements is the integration of differences between actors on an epistemic, social-organizational, and communicative level ( Jahn et al., 2012 ). As already observed above, at the epistemic level, boundaries between subjects, investigators, and audiences have a tendency to become blurred in SSH research ( Davies et al., 2008 ; Cassidy, 2014 ). In collaborative arrangements that involve SSH researchers, questions of boundary work might therefore be of particular relevance ( Gieryn, 1983 ). Furthermore, within the diverse SSH disciplines, there is little consensus on research questions and suitable methods, which poses challenges to the robustness of findings ( Ochsner et al., 2017 ). Regarding the socio-organizational level, the structures that support societal exchange in universities are mostly centrally organized and focused on broad public communication ( Peters, 2013 ; Marcinkowski et al., 2014 ; Fecher and Hebing, 2021 ). Questions arise as to how adequate these might be for anticipating the complexities of science in general and of the SSH in particular. Furthermore, the focus on economic indicators as a means of measuring societal impact in the past might have led to structural discrimination against SSH disciplines in organizational efforts to promote societal engagement ( Benneworth and Olmos-Peñuela, 2018 ; Fecher and Hebing, 2021 ). Jacobson et al. (2004) suggest implementing an array of organizational measures that are believed to be more suitable for SSH disciplines, from increasing resources to fostering the skills of individual researchers. Regarding the communicative level, SSH researchers have frequently been accused of using overly specialized and obscure terms ( Alvesson et al., 2017 ; Healy, 2017 ). At the same time, because the social sciences—and to a lesser degree, the humanities—investigate social life, they must deal with the everyday observations and ad hoc assumptions of the individuals with whom they engage (cf. Cassidy, 2014 ).

Some researchers argue that a consensus on values is not the only necessary condition for facilitating cooperation between heterogeneous actors; more importantly the conditions and structures for cooperation must be created ( Star and Griesemer, 1989 ). For SSH disciplines, this might come with particular challenges that are not yet well understood. This motivates our second research question (RQ2): What hinders interaction between SSH researchers and societal stakeholders?

Quality Expectations Regarding the Interaction Process

If our aim is to grasp the collaborative settings of knowledge production, we will likely need to go beyond criteria that are either purely academic or targeted towards science communication through the media ( Secko et al., 2013 ; Rögener and Wormer, 2017 ). The term “socially robust,” meaning that knowledge should be scientifically robust and socially useful ( Nowotny et al., 2001 ), is now used frequently to describe quality in these settings. Rather than bridging a cognitive gap (as purely academic projects would do), these new modes of knowledge creation aim to bridge social gaps, i.e., they are geared towards potential users, political decision makers, and entrepreneurs ( Maasen and Lieven, 2006 ). The authors argue that in these settings, actors must develop social accountability procedures collaboratively. This undertaking produces social demands that differ from those made in disciplinary research because the researchers need to work outside the set of scientific norms that would otherwise guide their practice ( Merton, 1973 ; Mitroff, 1974 ). This creates new requirements vis-à-vis the outcome. These outcomes are not easily located on a disciplinary map but instead suit the context of application ( Gibbons et al., 1994 ). This will most likely be accompanied by processual requirements to bridge the above-mentioned gaps and to deal with the specific contexts that are addressed by these arrangements.

There are general preconceptions about how collaborative modes of knowledge production might consolidate the quality conceptions of all parties involved. Still, these often remain at an abstract level, which motivates our third research question (RQ3): What do scientific and societal stakeholders perceive as the conditions for good interaction?

Data and Methods

The study is exploratory in that it aims to better understand the societal impact of SSH disciplines by an empirical examination of the role ascribed to SSH research in addressing societal challenges, as well the quality expectations arising in collaborative processes involving SSH researchers. Our findings are based on an online consultation of SSH researchers, societal stakeholders, and intermediaries. We subsequently discussed the results of the consultation with SSH and science researchers in two workshops, where we further scrutinized their implications for assessing the societal impact of SSH.

The selection of participants in the consultation process was deliberate and targeted a) researchers from different SSH disciplines who had experience of knowledge transfer and b) societal stakeholders from politics, media, business, culture, civil society, and public administration who had experience in collaborating with SSH scholars. In order to ascertain that participants did indeed have experience of collaboration, we conducted preliminary interviews, researched specific collaboration projects, and, in the case of researchers, asked learned societies for nominations. The deliberate selection of participants was necessary in order to ensure that respondents could legitimately provide answers to the partly normative questions. Our final sample consists of 125 responses, of which 36 are SSH scholars, 71 societal stakeholders, and 18 intermediaries. Of the SSH scholars, four participants came from core humanities disciplines (philosophy, legal studies, history), four from economics, thirteen from other social sciences, and one each from pedagogy, linguistics, and design research. Twelve of the researchers did not indicate their disciplinary background. Further, our sample includes a group we describe as “intermediaries.” These are individuals that are involved in managing and enabling collaborations between SSH researchers, for example communications officers at universities or independent science communication consultants. We chose to include this group in the consultation because we assumed that they would be uniquely positioned to observe and thus reflect on the conditions of these interactions. Table 1 illustrates the final expert sample by group membership.

TABLE 1 . Sample of the online consultation by group membership.

The consultation consisted of an online survey that comprised both a close-ended section on sociodemographics and a set of mainly open-ended questions about individual experience in collaborative settings involving SSH researchers. Our analysis of the three research questions is based on five open questions in the survey ( Table 2 ). One of the questions refers to the Covid-19 pandemic ( Table 2 ; RQ1). We chose to include this because the pandemic is a complex societal challenge and is thus relevant to the subject of the study.

TABLE 2 . Research interest and survey questions.

We conducted a structuring content analysis in order to analyze the textual data. This technique corresponds to the inductive technique of qualitative content analysis ( Mayring, 2000 ) and takes into account Kuckartz’s structuring method by using an interpretative initial processing to then iteratively form consistent categories ( Kuckartz, 2014 ). Quotations in this paper are the authors’ translations from the original German responses into English.

We encouraged the experts to publish their names and responses because we consider them relevant for further research: 103 agreed to publish their responses, 68 agreed to publish their names and institutions, 27 to publish only the name of their institutions, and 30 wished to stay anonymous. The survey instrument, the anonymized MAXQDA file, as well as the full answers of those who granted permission, can be found on the project website.

This study had limitations regarding the selection of participants in the consultation: Despite every effort being made to recruit a diverse and relevant set of participants, the selection can hardly reflect the diversity of SSH researchers and its many specialized societal stakeholders. Further research is necessary to understand the manifestations of the generic categories presented here in different contexts.

From the survey responses, we first identify topics that SSH research is associated with and the role SSH research fulfills within society. Second, we present the challenges that are mentioned when SSH researchers and societal stakeholders interact. Third, we turn to quality expectations in this interaction. In each results section, we will report on the findings by referring to the number of codes ascribed to a category in brackets and use exemplary quotes where suitable.

Role of Social Sciences and Humanities Researchers

From the responses regarding the societal issues that SSH expertise is relevant for, we were able to identify 31 societal issues that span nearly every aspect of social and natural life, as well as technical innovation. Broadly, these can be assigned to the following categories: “politics” (45), “economy” (47), “culture” (6), “education” (26), “ecology” (56), “civil society” (131), “health” (34), and “technology” (42).

The answers likely relate to the respondents’ particular interests and expertise and do not represent those areas of real-world problems that the SSH contribute to. However, the issues show that the spectrum of topics ascribed to SSH disciplines goes far beyond narrow disciplinary couplings (e.g., educational research that deals with education or economics that deal with economic growth) and includes contemporary and frequently transformative topics, such as climate change, migration, or the current pandemic. The ubiquity of potential issues for SSH engagement is expressed in this quote from a journalist:

“Every topic has a societal component—from fundamental questions of democracy and politics to questions concerning nature and technology. Basically, each question that requires social action and regulation” (Media_ID103, 10).

While these issues provide some indication of the wide topical range for potential SSH engagement, the participants’ perception of the role of SSH research in addressing these societal issues might provide a more accurate picture of how that engagement might actually unfold. We coded the answers to the question of how participants assess the role of SSH research in solving societal problems accordingly. In total, we identified six distinct societal roles that are frequently referred to by the experts: explaining, reflecting, educating, signaling, foresight, and informing ( Table 3 ).

TABLE 3 . Societal functions of SSH knowledge.

We found indications that each of these six functions correspond to different types of knowledge. For example, the “explain” category relates to system knowledge needed to understand a social issue because it contains statements from participants that are geared towards contextualizing social issues without suggesting any concrete instructions for action. By the same token, the “educate” category contains knowledge used to build competence in a specific issue area. The category “foresee” relates to knowledge needed to determine possibilities for decision-making as it contains statements from participants that refer to future developments. For example, one person working in public administration describes SSH research as an “early warning system for problems that have not yet become apparent” (PublicAdmin_ID61, 9). According to this statement, SSH disciplines should assess the societal implications of social change. These include, as several respondents state, the implications of artificial intelligence on the future of work.

The “inform” category is closely linked to what is referred to as the instrumental use of SSH knowledge, i.e., it is used directly for decision-making. Both the “reflect” and the “signal” categories resonate with what might be considered critical knowledge. Statements in the “reflect” category do not refer to the provision of expertise for problem solving but to interpreting and analyzing the problem and the solution. The “signal” category includes statements that, according to the participants in the consultation, refer to issues that receive too little attention but are considered relevant to public discourse or policymaking. Accordingly, the role of SSH disciplines is to point to these problematic aspects and to act as a critical observer. In relation to the Covid-19 pandemic, for example, the participants mentioned that SSH researchers emphasized the psychological, social, and cultural consequences of pandemic control. Some experts believe SSH expertise is not given enough attention in current political strategies, others like this intermediary describe their influence as lagged but present:

“Whereas at the beginning it was mainly the virologists who were heard, in my opinion the social sciences have now made themselves heard in many respects and have pointed out numerous important aspects of economic and socio-political relevance. For example, the fact that the daycare centers and schools have not yet been closed again is not only due to the virological assessment that children are less likely to spread the virus, but also due to the indications of the problems for working parents and for the children whose educational disadvantages have been exacerbated” (Intermediary_ID110, 24).

The statements from politicians in our sample frequently referred to the “foresee” category, but other than that there were no striking quantitative variations in the distribution of codes.

With regard to the roles attributed to the SSH in solving societal problems, we identified different levels of activity, from a rather passive, contextualizing role (e.g., “explain”) to a more active, influencing role (e.g., “inform”). This leads us to conclude that the SSH provide a diverse range of problem-relevant kinds of knowledge for societal challenges. From a solution-focused point of view, SSH knowledge is partly counterintuitive because it does not necessarily aim to contribute to a solution but seeks to question the problem and its solution. Moreover, rather than producing knowledge that might itself stimulate change or even transformation, SSH disciplines are more frequently attributed the role of producing “cohesion knowledge,” that is, knowledge that helps anticipate change. In this regard, SSH research fulfils a moderating role in complex change processes by helping to establish and maintain social order, cohesion, and equality. In our view, the multiple roles attributed to SSH disciplines could amount to a moderating role that would involve taking into account the complexity of issue formation in change processes as well as attempts to tackle these. Therefore, SSH disciplines are in a position to consider overarching issues of social cohesion and equality. The capacity of SSH research to address questions of cohesion is strongly reflected in the frequency of references to issues: the terms equality or inequality are mentioned 79 times by the respondents, democracy is mentioned 32 times, and cohesion or similar terms are mentioned 28 times.

Interaction Challenges

In order to understand where difficulties arise in the interaction between SSH scholars and societal stakeholders, the participants were asked about the problems and challenges they experienced in previous interactions and—in order to assess organizational aspects—the role of universities in supporting science-society interactions. We identified four kinds of interaction challenges in the answers: 1) translational challenges that relate to different modes and logics of interaction, 2) institutional challenges that relate to the governance and organization of science, 3) epistemic challenges that relate to knowledge creation processes of SSH disciplines, and 4) uptake challenges that relate to the use of SSH expertise by different societal stakeholders. Table 4 presents these challenges and their subdimensions.

TABLE 4 . Interaction challenges.

Translational Challenges: Conflicting System Logics and Boundary Work

Translational challenges relate to different modes and logics of interaction between involved parties. The category comprises statements made by respondents that refer to semantic aspects and systemic differences between science and other social systems that hamper meaningful interaction. The statements in this category can be split into two categories: “language barriers” (27) and “conflicting system logics” (73).

Some participants perceive the language of SSH scholars to be complicated, as this journalist describes:

“As a journalist, it strikes me that social science researchers very often and unfortunately quite naturally use terms that are hardly used or understood by the general public” (Media_ID159, 13).

Differences, however, can be found in the assessment of language barriers. Some see the use of technical concepts as a necessity for describing social phenomena in a differentiated way, while others see it as unnecessarily complicated prose that is a hindrance to productive exchange. In general, references to language barriers are mostly made by participants working in the private sector or in the media.

A second challenge can be described as “conflicting system logics.” Statements in this category refer to three closely related aspects of incompatibility: 1) temporality of SSH research (i.e., SSH research takes time and cannot satisfy needs immediately), 2) conflicting notions of relevance (i.e., societal relevance of SSH is not based on immediate societal needs), and 3) self-referentiality of SSH research (i.e., SSH research refers to itself and not to what others consider social problems). The conflicting system logics resulting from these are well expressed in a quote from an SSH researcher, who on the one hand calls for SSH researchers to anticipate different societal contexts (here the media) but on the other hand reports that this can lead to conflicts among academic peers:

“Scholars should recognize that they move in a different system logic when they communicate with the media, for example. I experience a lot of criticism of the portrayal of science in the media, which I consider inappropriate. Of course, there is a decrease in length, but that is also completely okay.” (SSHscholar_ID138, 16–17)

In general, the participants often refer to different system logics, usually to explain why an exchange could not take place from their specific perspectives. In this quote, for example, a politician reports on the context of his decision making and the associated lack of time to deal with SSH research:

“Science is a different system than politics; there is a democracy proviso; being an elected official does not give me enough time to read or receive scientific literature.” (Politics_ID196, 17)

Different system logics explain the translational challenges between SSH researchers and members of other social subsystems, specifically with regards to language usage, the notions of relevance, and time and content-related use considerations. This explanation can be problematic when functional differentiation of social systems is used as a pretext for not engaging in interaction at all. It might be more fruitful to think of the interaction between societal stakeholders and scientists as one where boundaries between science and nonscience are contextually and continuously dissolved and redrawn.

Institutional Challenges: Mismatch Between Aspiration and Resources

Institutional challenges relate to the governance and organization of science. In this respect, we identified three types of challenges in the statements. These are “lack of resources” (19), “lack of organizational support” (19), and “lack of rewards” (20).

In most cases, references to lack of resources refer to limits concerning SSH researchers’ time and skills. One social scientist mentioned the need for training for research staff when explaining the latter:

“[We] are not trained to do this; we usually do basic research and teach basic science at universities—we need knowledge transfer” (SSHscholar_ID68, 15).

A second institutional challenge relates to the lack of organizational support. Respondents often refer to a decoupling of transfer infrastructures at universities and the researchers working there, or to necessary investment in transfer capacities at research organizations. The latter becomes clear in this statement made by a participant who works in public administration:

“In my opinion, scientific institutions should invest more in public relations—these positions are often sparsely staffed and funded [...]. The relevance of the job/intermediary function is recognized more and more, but this is (often) not yet reflected in the structures” (Intermediary_ID229, 13).

A third challenge in this category is the lack of rewards for societal engagement, which the participants link to the academic reputation and funding system. Another social scientist describes what she perceives as an undervaluation of engagement as follows:

“[There is a] lack of reputation for this activity as opposed to third-party funding and high-ranking publications. [Engagement] is only an “add on”” (SSHscholar_ID44, 13).

The notion of “engagement as an add-on” (i.e., not a main task) is mentioned frequently and especially by SSH scholars in the consultation. However, the participants discuss the matter of recognition with significant differentiation: One expert describes societal impact as an additional pathway for scholarly work, alongside scientific impact:

“Since publication excellence can hardly be mitigated, they could instead create funding lines that can only be used if the relevance to the SDGs is laid out clearly,” (SSHscholar_ID65, 28).

Lack of recognition for public engagement activities and a lack of resources to carry them out are not specific to SSH disciplines per se. However, they may be more pronounced here because knowledge transfer is even less rewarded and incentivized in a dominant framework focused on economic outcomes. If strengthening societal engagement is a science policy priority, the results here suggest that there is a perceived mismatch between this aspiration and the resources allocated to it.

Epistemic Challenges: The Illusion of Stable Social Sciences and Humanities Knowledge

The epistemic challenges category describes challenges that relate to the knowledge creation of SSH disciplines. It includes two subcategories, “ambiguous results” (23) and “conflicting paradigms” (9).

With respect to “ambiguous results,” statements often contain comparisons to the “hard” natural sciences, where results are perceived by some participants to be clear and unambiguous. In contrast, results from SSH disciplines are often described as vague. For example, for a respondent who works as a researcher and in the media, this is the main reason why results from the natural sciences are preferred:

“Questions and research designs are often too vague, the results too ambiguous. Therefore, journalists prefer communicating results from the natural sciences” (SSHscholar_ID142, 16).

The “conflicting paradigms” category contains statements that emphasize how different schools of thought within SSH disciplines result in different ways of understanding and assessing the same issue. A social scientist in the consultation interpreted the heterogeneity of SSH disciplines as an impediment to communication:

“Distinctive disciplinarity and families of methods in SSH disciplines prevent common problem-oriented communication” (SSHscholar_ID206, 22).

While the heterogeneity of SSH disciplines is often described as normal and indeed as an asset by the participants, some point to a problem, namely that this lack of consensus can also be perceived by the public as a lack of scientific rigor. This can lead to a loss of reputation and trust.

“One challenge is the question of how issues that are scientifically controversial can be presented to the public in such a way that the reputation of science does not suffer and, ideally, this heterogeneity can even be used productively” (SSHscholar_ID179, 13).

Of course, conflicting paradigms and ambiguous results are not purely SSH problems. However, they manifest in specific ways there. In general, SSH disciplines comprise very different approaches, research questions, and epistemological premises. Moreover, their results are often strongly dependent on context. These characteristics are echoed in our respondents’ view of the ambiguity of SSH results, which they describe as a challenge when interacting with societal stakeholders.

Uptake Challenges: Lacking Appreciation and Public Attention Dynamics

The category uptake challenges includes statements from participants that relate to the use of SSH expertise by societal stakeholders. We identified three types of uptake challenges. These are: “lacking public appreciation” (27), “public attention dynamics” (13), and the “risk of instrumentalization” (5).

Regarding “lacking appreciation,” SSH disciplines are, again, often contrasted with the natural sciences by participants. Many of them describe the natural sciences as having a comparatively higher public status, which becomes obvious in this statement from an SSH scholar:

“From my point of view, we offer many research topics that are of interest to a broader public, but we are not yet perceived and treated equally with the natural sciences” (Intermediary_ID229, 16)

This observation is backed up by a journalist who explains that while disciplines such as medicine, physics, or engineering are met with fascination, SSH disciplines are not:

“While the natural sciences and medicine are often met with widespread fascination for their subjects in society, this is often lacking in social science. Physics and technology are sexy, other disciplines are not” (Media_ID159, 16).

The “dynamics of public attention” subcategory subsumes statements that describe SSH research as being out of kilter with the public interest. In general, this refers to a perceived mismatch between the utilitarian perspective of societal stakeholders and the supply of knowledge that SSH disciplines can provide. Often, participants refer to the fast pace of social media, which SSH research cannot keep up with. Some participants even describe adverse effects when SSH researchers adapt their communication to the dynamics of publicity, which is made obvious in a quote from a humanities scholar, who explains how attention might trump relevance in public communication:

“Provocation is better “received” than factuality; “loud” colleagues are simply better seen and heard” (SSHscholar_ID67, 13).

The “risk of instrumentalization” category is rarely referenced. We list it nevertheless, because it is often mentioned in the literature and is distinct from the other listed challenges. The category subsumes statements that refer to the misuse of SSH expertise for political interests. For instance, a representative working in the economy and for an NGO states:

“Politicians must not misuse scientific findings for their own agendas and thereby partly discredit them” (Economy_ID96, 18).

Taken together, when SSH results are discussed by the public, they appear to not be appreciated in the same way as natural science results. Instead. they are made subject to attention dynamics and might be instrumentalized. This negative perception might be linked to the subtle nature and multiple ways in which SSH expertise reaches the public and political decision makers. If media attention factors determine whether SSH results are noted by the public, the scientific and societal relevance of SSH expertise might recede.

Quality Expectations

The third research question addresses quality expectations, i.e., conditions for a good exchange between societal stakeholders and SSH researchers. To this end, we asked the participants open questions about their expectations for a good exchange and about the specific conditions that might apply to SSH disciplines. From the answers, we are able to identify eight distinctive quality expectations that can be divided into three main categories. These are 1) process-related, b) outcome-related, and c) person-related quality expectations ( Table 5 ). Engagement with society, albeit an aspiration of many research organizations, seems to be difficult in current organizational structures according to our respondents.

TABLE 5 . Quality expectations.

Process-Related Quality Expectations

Process-related quality expectations refer to the interaction between SSH scholars and societal stakeholders and includes the codes “comprehensibility” (26), “pertinence” (13), “inclusivity” (26), and “form” (25).

“Comprehensibility” encompasses statements that refer to the mutual understanding between actors. Typically, these statements refer to comprehensible and clear communication of results on the part of SSH scholars and the adaptation to interlocutors. Accordingly, complex contents should be conveyed in such a way that those involved in the dialogue are able to follow and respond in an informed manner. The code “pertinence” refers to statements that suggest that knowledge should be used in a problem—and solution-oriented manner. This is illustrated by a statement made by a politician:

“For the policy sphere, I would like to see more focused exchanges that bring in key research findings” (Politics_ID237, 19).

“Inclusivity” refers to the actors involved in an interaction. We distinguished between two types of inclusivity. The first is selective inclusivity, which means that appointed experts who can contribute relevant and specific expertise should be involved. The second is universal inclusivity, which implies broader participation involving those who are possibly affected by the issue. Some participants point out that diverse expertise is needed to achieve viable results. Lastly, statements coded as “form” typically refer to the existence of an interaction format that is adequate for exchange and problem-solving.

It is impossible to meet all of these expectations of the interaction process. One SSH scholar puts it in these almost utopian terms:

“The goal should be to communicate complexity, reflexivity, and provisionality simply, clearly, understandably, and plausibly” (SSHscholar_ID205, 15).

It can be assumed that the more complex a problem is and the more diverse the parties involved in the interaction process, the more difficult it will be to arrive at some form of shared meaning. In this regard, there are expected tensions between inclusivity, pertinence, and comprehensibility, while formality might imply a strategy to meet these expectations in the best possible way.

Outcome-Related Quality Expectations

Outcome-related quality expectations refer to the results of an interaction process between SSH scholars and societal stakeholders. This category comprises the codes “transparency” (30) and “relevance” (31).

The code “transparency” indicates statements that refer to two kinds of transparency: 1) method transparency and 2) motivation transparency. In this article, we use method transparency to refer exclusively to SSH disciplines and signal the requirement of communicating uncertainties and clearly describing methods as necessary for good exchange. Motivation transparency refers to the communication of motivating factors (e.g., personal interest, dependencies, client expectations) and pertains to both SSH scholars and societal stakeholders. This is made obvious in a statement from a social science scholar:

“As part of society, scientists perceive and research socially relevant topics—politics should make the use of scientific research results transparent” (SSHscholar_ID68, 18).

“Relevance” includes statements that refer to the practical implications of the interaction process. We distinguished between individual and societal relevance. Individual relevance signifies the benefits for the individuals involved and is described by some as a motivating factor for partaking in the interaction process. Societal relevance is usually viewed in a differentiated way as referring either to benefits for individual citizens or benefits for specific groups and sectors of society. In some statements, such as the following made by a politician, societal relevance is framed as a return on societal investment in publicly financed research:

“Society makes a considerable contribution to the financial security and freedom of science, not least through public budgets. It can therefore expect science to take an interest in societal issues and to make its contribution to solving societal problems [...]” (Politics_ID234, 18).

However, achieving both transparency and relevance might be difficult, as this statement from an economics scholar shows:

“The greatest challenge in communicating social science research is often to openly acknowledge the uncertainty inherent in its findings while convincing people that they nevertheless contain important information” (SSHscholar_ID157, 16).

In this case, transparency is seen as a hindrance for relevance. Further tensions might arise when personal and societal relevance do not correspond, or when transparency (in the sense of replicability) cannot be achieved. There might also be a conflict between different quality expectations in the outcome of the interaction process.

Person-Related Quality Expectations

Person-related quality expectations refer to the individuals involved in the interaction process. They subsume the codes “empathy” (67) and “disinterestedness” (14).

“Empathy” indicates statements that refer to the mutual acknowledgement of all parties involved. Most statements in this category refer to acknowledging the position of the other parties involved in the interaction process. Typically, the social position of an individual comes with certain concessions, for example, journalists are granted reporting duties, politicians have decision-making power, and SSH scholars possess research autonomy. The reciprocal nature of the expectation of empathy is made clear in this quote from a journalist in the consultation:

“When researchers recognize that the media are their partners—in discourse, in presentation, in criticism. That means being available for media inquiries, discussing issues of relevance with a journalist, and sharing material. It also means tolerating exaggerations, even if one’s own business is differentiation” (Media_ID114, 16).

Some participants state that empathy should not be blind but informed. This is made obvious in a quote from a participant who works in public administration:

“It is important that the results of SSH disciplines can be properly assessed. Excessive claims in the social sciences, in the sense of objective truths, can easily produce disappointment and lead to a deviation, which in the worst cases can then leave the impression of arbitrariness of the decisions and actions under discussion” (PublicAdmin_ID167, 15).

The code “disinterestedness” is used for statements that emphasize that actors should not pursue their own interests but act for the benefit of society. This is often combined with the expectation that personal opinions should be separated from facts and that the conversation should be devoid of emotions and self-promotional intentions. Responding to the question of what constitutes a good collaboration between science and society, one SSH scholar states:

“In my view, a good exchange is characterized above all by the fact that it is not primarily guided and inspired by the self-promotional intentions of individual scientists or scientific organizations” (SSHscholar_ID37, 16).

There are conflicts between disinterestedness and empathy, for instance when it comes to the proclaimed necessity of leaving emotions aside. In addition, there may be potential cross-category tensions between person—and outcome-related quality expectations, for instance in relation to disinterestedness and the individual relevance described above. The same holds true for informed empathy and inclusivity. Remarkably all participants, researchers as well as societal stakeholders from different fields, name the quality expectation empathy most frequently as a condition for exchange. Reflection on ones own position seems crucial for science-society-interactions.

In this article, we used an expert consultation to examine the societal impact of SSH disciplines, i.e., the role of SSH research in addressing societal issues, as well as the resulting challenges and quality expectations. The results shed light on the conundrum of addressing societal issues while being part of the subject matter.

Social Sciences and Humanities Knowledge as Cohesion Knowledge

The societal issues that SSH disciplines relate to are broad and transcend disciplinary couplings. The quasi ubiquity of SSH impact areas resonates with recent research findings (e.g., Bastow et al., 2014 ). The roles ascribed to SSH disciplines in addressing societal problems are likewise diverse and range from more instrumental tasks, such as informing a policy decision, to more contextualizing activities, such as explaining the social implications of a problem. The latter resonates with Stehr and Ruser’s (2017) description of social scientists as “meaning producers,” i.e., their knowledge does not focus on practical choices but on processes of meaning, which may give rise to decisions. In addition, we find evidence of a more counterintuitive role for SSH disciplines in addressing societal challenges, namely critiquing the definition of a problem and the envisaged solution. This finding resonates with Burchell (2009) who proposes that, from a societal perspective, the social sciences might best be interpreted as a “critical friend” (see also Davies et al., 2008 ). Participants in the consultation describe the relevance of this critical capacity, for instance, in discussing the social, cultural, and psychological implications of the Covid-19 pandemic, which some feel have not been sufficiently considered in policy decisions.

Along with these roles, we identified different types of knowledge that SSH disciplines can provide to help resolve societal challenges. These range from overview and system knowledge, as described by Becker (2002) , to instrumental knowledge ( Fähnrich and Lü ; Stehr and Ruser, 2017 ) like the kind that is used to inform political decision-making processes. This differentiation resonates with ( Weiss, 1980 ) who suggests that the contributions of SSH research to decision-making processes are much wider than a narrow idea of knowledge utilization suggests. Moreover, “critical knowledge,” i.e., knowledge that enables us to question societal decisions, appears to be an essential contribution of SSH disciplines to societal issues. This positions SSH researchers as a critical corrective in addition to its contextualizing and co-creating capacity. At a higher level of abstraction, we observe that SSH disciplines are rarely associated with “transformative knowledge” that causes change ( Becker, 2002 ) but instead with knowledge that helps us anticipate societal transformations and to deal with change (see also Sigurðarson, 2020 ). We refer to this kind of knowledge as “cohesion knowledge.”

Continuous Boundary Work

In the scholarly debate, dialogue between representatives from both science and society is understood as a condition for “socially robust” knowledge, i.e., knowledge that is both scientifically robust and socially useful ( Nowotny et al., 2001 ). Consequently, we conceptualize interaction as a prerequisite for societal impact (see also Spaapen and van Drooge, 2011 ). This motivated us to interrogate challenges in interactive and problem-oriented settings involving SSH disciplines. The challenges we identify can be categorized as translational, institutional, epistemic, and uptake challenges, and they thus correspond roughly to the framework suggested by Jahn et al. (2012) . While many of the challenges we identified point to contingent issues, some results stand out.

When it comes to translation, reducing linguistic complexity without being accused of triviality and commonplace hypotheses is a core challenge for SSH disciplines. Some of the societal stakeholders in the consultation describe SSH disciplines as self-referential and the language used as unnecessarily complicated at times. Bridging the “social gap” ( Maasen and Lieven 2006 ) between science and society thus means that SSH scholars must adapt their language (e.g., their use of terms), although at the risk of compromising their epistemic authority. A problem-oriented interaction with societal stakeholders, however, might contribute to increased “methodological efficiency” as a form of continuous external validation ( Woolgar, 2000 ). Regarding institutional challenges, we find initial evidence for a structural disadvantage of SSH disciplines. This might be explained with reference to the fact that the established entrepreneurial heuristic of societal impact carries little significance for SSH disciplines ( Benneworth and Olmos-Peñuela, 2018 ). Epistemic challenges mostly concern the heterogeneity of SSH disciplines and their approaches, intermittently conflicting paradigms, and the dynamic object of study, i.e., society as a moving target ( Dayé, 2014 ). It follows that SSH disciplines produce knowledge that is highly context-dependent, situated, and dynamic ( Gattone, 2012 ; Fähnrich and Lüthje, 2017 ). Hence, there are serious limitations regarding the extent to which objective, stable, and context-independent knowledge can be expected from SSH disciplines ( Davies et al., 2008 ). This finding is consistent with the self-conception of many SSH disciplines as critical, reflective, and contextual. When it comes to the uptake of SSH knowledge, the consulted representatives note how SSH expertise is not always fully appreciated and may explain to a certain extent the lack of appreciation for SSH research. For example, in the consultation, SSH research is often contrasted with natural science and technical disciplines, whose results are not only perceived as more stable but often as more exciting, too. This resonates with Knudsen (2017) , who found a deficit framing for the humanities in Danish print media. Cassidy (2014) explains this lack of appreciation with the close relationship of SSH disciplines to everyday life: “Unlike most natural sciences, where the specialist training, knowledge and equipment of scientists grants them largely uncontested expertise, social scientists’ expertise is often about matters of everyday experience and common-sense knowledge” (p. 190).

Taken together, these challenges suggest a twofold implication: The calls for more resources and recognition are on the one hand contingent issues that can give impulses to the governance of science. On the other hand, our results illustrate how the position of the SSH in society is a matter of ongoing negotiations. The identified challenges show how the SSH are caught up in boundary work in their interactions with extra-academic fields ( Gieryn, 1983 ). They speak of troubles of SSH researchers to claim their authority, which is linked to epistemic dynamics, that find expression in language usage, specific temporalities and context-specific results. How the SSH position themselves towards their moving target, the society, becomes even more of a challenge in collaborative formats.

Contextual Quality Configurations

Our empirical findings indicate a three-dimensional framework for ensuring quality in collaborative arrangements involving SSH researchers and societal stakeholders. The first is process-related and describes the expectations of the exchange itself. The second is person-related and describes the expectations towards the people involved. The third is outcome-oriented and includes the expectations of the outcome. In collaborative settings, there will most likely be contradictory expectations of what entitles persons to participate, how interacting partners should behave, and what constitutes relevant knowledge (see also Kropp and Wagner, 2010 ). This leads to conflicts between different expectations of quality that are difficult to avoid, for instance between disinterestedness and empathy, but also within categories, for instance, regarding different understandings of relevance (e.g., how can scientific demands for relevance be reconciled with demands for utility?). At times, the participants in the consultation offer solutions to these conflicts between quality expectations, for instance when they say that there are conditions for participation in the interaction such as having a basic understanding of the other interaction partner. This is in line with Bromme’s (2020) concept of “informed trust,” according to which it needs not only trust in public scientific statements but also knowledge on the system of science to make an informed judgement. Our findings add a nuance to this hypothesis by suggesting that informed trust must be reciprocal, i.e., researchers participating in a dialogue must also understand the societal stakeholders they engage with.

Generally, we can safely assume that the more diverse and complex the setting for a dialogue is, the more difficult it may be to document expertise and to establish transparency. If being affected by an issue legitimizes participation in a dialogue, then it may be more difficult to enforce pertinence as a premise. If expertise legitimizes participation, there is also a risk of exceeding the level of fact. It follows that there must be legitimate reasons for trade-offs between different quality expectations. These should depend on the aim of the interaction, the individuals involved, and the chosen interaction format. It follows that quality expectations in collaborative settings should not be understood universally, unilaterally, and statically. Instead, they should be considered within their specific context, reciprocally, and dynamically. Hence, we propose that quality itself must be an object of these interactions, i.e., there should ideally be deliberation about the appropriate quality configuration for the problem at hand. This could be particularly relevant for SSH disciplines, which, as discussed above, have to engage in continuous boundary work due to their position in society. The outline of a quality framework as proposed here can be a basis for deliberating on the quality of these arrangements. That said, for particularly established forms of interaction (e.g., scientific policy advice), there may already be recognized default settings from which it is possible to extrapolate.

Our results show, that the societal impact of SSH disciplines can be counterintuitive and precisely not aimed at solving a problem. Instead, they often seek to challenge both the problem and its solution. Nor does SSH research necessarily strive for transformation but instead seeks an understanding and a moderation of social change. Therefore, the impact of the SSH is often discreet, indirect, and conceptual. Thus, the quality of the societal impact of SSH disciplines can only be understood in relation to their specific context, in the sense that it is person-, problem-, and time-dependent and must take into account different field logics as it takes place in a “space between fields” ( Williams, 2020 ). For these reasons, a rigid, purely quantitative assessment of societal impact of SSH disciplines should generally be avoided, especially with regard to how assessment shapes and stabilizes underlying values ( Espeland and Sauder, 2007 ; Williams, 2020 ).

Our results provide some arguments for so-called formative evaluations of the societal impact of SSH disciplines. Formative evaluations focus on the process (e.g., an interaction, a program, or a project) while the activities are ongoing. They are geared towards learning and goal adjustment. The SIAMPI approach ( Spaapen and van Drooge, 2011 ) as well as the Agora model ( Frederiksen et al., 2003 ; Barré, 2010 ) or Public Value Mapping ( Bozeman and Sarewitz, 2011 ) are promising examples of such formative assessment concepts. Using the concept of “productive interactions,” the SIAMPI approach focuses on the individual’s contributions to an interaction rather than reactively assessing its outputs. With its emphasis on productivity however, it cannot capture the counterintuitive contributions outlined above, which do not focus on the solution to a problem but instead question the problem.

Nonetheless, this at times counterintuitive impact of SSH disciplines may not be suitable for evaluation at all. Instead, it might imply that additional measures such as capacity building are needed to support the interaction between science and society ( Sigurðarson, 2020 ). The integration of science communication, and with it the reflection on boundaries, must become an integral part of science education. This is underlined by the trend towards public legitimation of research funds and a new social contract for science not as hasty obedience to a political desire but as a basis for an informed discussion of perspectives and implications. In that sense, it seems reasonable to reflect on and gain a more nuanced understanding of the societal impact of SSH disciplines within research communities and learned societies.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author Contributions

All authors certify that they have participated sufficiently in the work to take public responsibility for the content, including participation in the concept, design, analysis, writing, or revision of the manuscript. BF supervised, carried out the analysis, editing and data collection together with FK. All authors discussed the results and contributed to the final manuscript.

This study was carried out with funding from the German Federal Ministry of Education and Research (under grant numbers 01PW18008A and 01PW18008B BMBF).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords: impact, knowledge transfer, science-society interfaces, scientific advice, research utilization

Citation: Fecher B, Kuper F, Sokolovska N, Fenton A, Hornbostel S and Wagner GG (2021) Understanding the Societal Impact of the Social Sciences and Humanities: Remarks on Roles, Challenges, and Expectations. Front. Res. Metr. Anal. 6:696804. doi: 10.3389/frma.2021.696804

Received: 17 April 2021; Accepted: 18 June 2021; Published: 01 July 2021.

Reviewed by:

Copyright © 2021 Fecher, Kuper, Sokolovska, Fenton, Hornbostel and Wagner. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Benedikt Fecher, [email protected]

This article is part of the Research Topic

How to Play the Science Game: Insights on Scientific Teams

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A System of Social Science: Papers Relating to Adam Smith (2nd edn)

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8 The Role of the State

Published: March 1996
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Adam Smith's contribution to the field of political economy was designed to explain the working of a set of institutional arrangements that he regarded as the last of four stages of economic development, and to elucidate the ‘laws of motion’ that governed its operations. The laws of motion, once stated, were designed to show that the control of resources could be left to the market and to explain the source of their increase. This perspective led directly to the demand that the state ought not to interfere with the economy. The same sentiments appear in the Wealth of Nations , albeit expressed with even greater force. According to Lord Robbins, Smith bequeathed to his successors in the Classical School an opposition to conscious paternalism, a belief that ‘central authority was incompetent to decide on a proper distribution of resources’. This chapter also considers Smith's views on economic liberalism, constraints on the functions of the state, the organization of educational provision, justice, public works and public services, and policy reform.

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What is a Social Science Essay?
Social science essays also need to demonstrate an effective use of social scientific skills. Perhaps the most obvious of these skills is the ability to deploy theory and evidence in an appropriate manner (as you saw in the previous section, this is what distinguishes social scientific essay writing). ... that's not the role of news ...
Importance of Social Science in Our Daily Life
Social science enhances our critical thinking skills, broadens our perspectives, and enriches our interactions with the world. Whether through economics, psychology, sociology, or other disciplines, social science provides the foundation for a better understanding of ourselves and the societies we inhabit. Keep in mind: This is only a sample.
The Vital Significance of Social Science in Our Daily Lives: [Essay
Social science, far from being an abstract academic pursuit, is an integral part of our daily lives. It informs our understanding of human behavior, shapes public policies, enhances personal finance decisions, addresses societal issues, and fosters global citizenship. Moreover, it nurtures critical thinking, informs ethical values, and equips ...
What is a Social Science Essay?
In the light of the above, we can identify four golden rules for effective social scientific essay writing. Rule 1: Answer the question that is asked. Rule 2: Write your answer in your own words. Rule 3: Think about the content of your essay, being sure to demonstrate good social scientific skills.
What Should Be in a Social Science Essay? Fundamentals and Essential
This blogpost is also available as a PDF download, so it can be stored on your desktop and used as a checklist before submitting your essay.. The following is a condensed overview of the most important features of social science essay writing. Its aim is to cut through the noise, and focus on the most essential (and important) elements of essay writing.
Organizing Your Social Sciences Research Paper
In Good Essay Writing: A Social Sciences Guide. Peter Redman. 4th edition. (London: Sage, 2011), pp. 63-70; Reyes, Victoria. Demystifying the Journal Article. Inside Higher Education. Structure and Writing Style. I. Structure and Approach. The introduction is the broad beginning of the paper that answers three important questions for the reader:
PDF A Student'S Guide to Writing Social Science Essays
Give the reasons, interpret and to make plain. Illustrate: Use a figure, diagram, example or even a description to explain or clarify, thus. giving a visual impression. Justify: Support a conclusion or hypothesis by making reference to available. evidence/resources and providing a reasoned argument.
Social science
social science, any branch of academic study or science that deals with human behaviour in its social and cultural aspects. Usually included within the social sciences are cultural (or social) anthropology, sociology, psychology, political science, and economics.The discipline of historiography is regarded by many as a social science, and certain areas of historical study are almost ...
What are the social sciences?
The social sciences are made up of lots of different disciplines and sub-disciplines, which focus on different aspects of society. The social sciences are a 'broad church', including lots of different disciplinary and sub-disciplinary areas. These include, for example, sociology, anthropology, criminology, archaeology, social policy, human ...
Social Science, Philosophy of
The philosophy of social science can be described broadly as having two aims. First, it seeks to produce a rational reconstruction of social science. This entails describing the philosophical assumptions that underpin the practice of social inquiry, just as the philosophy of natural science seeks to lay bare the methodological and ontological ...
Organizing Your Social Sciences Research Paper
The conclusion is intended to help the reader understand why your research should matter to them after they have finished reading the paper. A conclusion is not merely a summary of the main topics covered or a re-statement of your research problem, but a synthesis of key points derived from the findings of your study and, if applicable, where you recommend new areas for future research.
Social & behavioural science writing
A social or behavioural science essay has to show knowledge of how evidence and theory work together. A social or behavioural science essay has to show knowledge of all the key theoretical positions relevant to the question. For example, an essay reviewing the causes of autism has to take account of theories that, respectively, emphasise ...
What is Social Science?
What are the social sciences and why do they matter? Social science is the study of people: as individuals, communities and societies; their behaviours and interactions with each other and with their built, technological and natural environments. Social science seeks to understand the evolving human systems across our increasingly complex world ...
PDF Good Essay Writing
Your essay should aim to show the role of the social sciences in understanding risks and how people live with them. In this assignment, you are asked to produce a descriptive essay that considers the role of risk in contemporary society, to consider Ulrich Beck's argument that we live in a 'risk society', and to provide relevant examples ...
philosophy of social science
Other approaches that deny that the interpretation of meaning is of fundamental import in the social sciences include systems theory and structuralism.Systems theory conceives of society as an entity each of whose various parts plays a certain role or performs a certain function in order to maintain society or to keep it in equilibrium; such roles are played by those who inhabit them, whether ...
Citizen science in the social sciences and humanities: the power of
Further analysing sub-fields of sciences, we noticed the same tendency: the major part of papers (N = 30) combined several sub-fields of science, e.g. social geography, engineering, and humanities ...
The Public Value of the Social Sciences
The social sciences are under threat from two main sources. One is external, reflected in a global university crisis that imposes the marketization of higher education on the ancient practice of scholarship. The other, internal threat is social science's withdrawal from publicly-engaged teaching and research into the protective bunker of ...
Frontiers
Role of Social Sciences and Humanities Researchers. From the responses regarding the societal issues that SSH expertise is relevant for, we were able to identify 31 societal issues that span nearly every aspect of social and natural life, as well as technical innovation. Broadly, these can be assigned to the following categories: "politics ...
Understanding Social Science Research: an Overview
Abstract. Social science research is a method to uncover social happenings in human societies. Through social research, new knowled ge is derived to help societies progress and adapt to. change ...
Relevance of the Social Sciences in the Philippines
THE SOCIAL SCIENCES HALLMARKS OF MODERNITY In this essay, I argue for the importance of the social sciences for understanding the contemporary world. We are increasingly overwhelmed by the easy availability of information, much of whose reliability is uncertain. Previously stable institutions, values, and practices are in
The Role of the State
Abstract. Adam Smith's contribution to the field of political economy was designed to explain the working of a set of institutional arrangements that he regarded as the last of four stages of economic development, and to elucidate the 'laws of motion' that governed its operations. The laws of motion, once stated, were designed to show that ...