In this last chapter, we raise what typically is an opening question: What is the purpose of research? Of course, what is meant by purpose here goes well beyond the aims, objectives, research questions, and hypotheses in any given study (Doody & Bailey, Reference Doody and Bailey2016). These are all generally made explicit (see Chapter 4). What is less explicit is the reason we engage in research; what is research for? For some, this interrogation could sound trivial: Through research, we gain knowledge about ourselves and the world (discovering Truth). If this knowledge is valid, then research is a worthy achievement in and of itself. But what exactly counts as valid knowledge, and how do we judge it so? The positivist view, dominant in many areas of the human and social sciences (even if not always convergent with the thinking of early positivists; Bailey & Eastman, Reference Bailey and Eastman1994), is that research’s true purpose is to reveal what is the case and do so by organizing the messiness of life-as-we-find-it and abstracting, from it, a transcendental and universal Truth. To this end, positivist research tries to rise above the changing realm of human needs, values, and biases. In contrast, constructionist research prefers to dwell within the messiness of human life and anchors all knowledge to human contingencies (Holstein & Gubrium, Reference Holstein and Gubrium2013). This implies a plurality of truths, potentially as many as there are perspectives in and on the world.

Pragmatism avoids the pitfalls of considering research either as the discovery of objective Truth or the multiplicity of subjectivities. Research is not merely an exercise of knowing the world (or one’s version of it) but one of world-making and future-building (Gergen, Reference Gergen2015; Power et al., Reference Power, Zittoun and Akkerman2023). This does not mean that every piece of research gets to change the world, yet doing research means engaging in human, most often collaborative, activity that transforms the present given an anticipated future. This future not only includes the acquisition of new knowledge, it considers its impact, use, and renewal. When we understand research as an activity, we acknowledge its material, social, cultural, and political embeddedness. The perspectives enacted and coconstructed during the research process are not the God’s eye view of positivism nor the relativism of constructionists. For pragmatism, perspectives are bound to positions in the world and actively construct the world (i.e., change it) through dialogue, interaction, and position exchange, all of which are possibility-expanding processes. In this chapter, we develop the implications of our final pragmatist proposition that social research should aim to expand human possibility.

We will argue, with Dewey (Reference Dewey1929), that research depends on and should foster human imagination, agency, and possibility. These creative elements permeate the research cycle, from epistemology to data analysis. In this chapter, we will trace the role of possibility in human research, from human interests through methodology and into the overall aims of social research.

9.1 Human Interests

A pragmatist discussion of research purposes starts from human interests. Human interests refer to people’s needs and wants. People’s actions in the world are initiated by their interests and aim to satisfy their interests. Social research, as an activity, is motivated by the interests of researchers, funders, and governments. From a positivist standpoint, the connection between human interests and research is problematic because it undermines assumptions about impartiality, objectivity, and absolute certainty. From a constructionist standpoint, this is further evidence of research serving vested or idiosyncratic interests. Between the Scylla of naïve realism and the Charybdis of extreme relativism, pragmatists turn the problem of human interests into a guiding light for social research.

From a pragmatist standpoint, truth that is independent of human interests (if it could exist) would be meaningless and uninteresting. Any truth that is not “for us,” that serves no human purpose and contributes nothing to our future, is simply inconceivable. In James’s words:

The beating heart of knowledge is at the intersection with human interests. It is these interests that make knowledge important, interesting, and useful. There is no “useful” without a guiding interest. Instead of suppressing human interests, pragmatism builds them into knowledge production to such an extent that they become the criteria for evaluating knowledge. Does the knowledge work? Does it fulfil the goal? Does it satisfy the interest that fueled the research project? In this way, the problem of human interests is transformed into the solution to both naïve realism and extreme relativism. The question is not “is this true” but, instead, whether this enables us to act more effectively (Rorty, Reference Rorty1999). The knowledge that enables us to land on the moon, run the Internet, and handle a pandemic is true in so far as it works. Equally, anti-vaccine beliefs are false in so far as they will not serve the human interest of avoiding infection – although it might serve other interests (de Saint Laurent et al., Reference de Saint Laurent, Murphy, Hegarty and Greene2021b).

Habermas (Reference Habermas1968) analyzed the human interests underlying the production of knowledge. In a radical move, criticizing the focus on creating reliable knowledge (as knowledge independent of human activity), Habermas proceeded to classify knowledge in terms of the interests that it addresses. Thus, he marks an important shift in focus from “how do we know this knowledge is accurate?” to “what interests are being served by this knowledge?” His theory identifies three basic human interests.

Technocratic interests are served by knowledge that predicts, guides interventions, and, in general, acts upon the world, including other people. For example, big data can be aggregated to create predictive models, based on vast numbers of correlations, without any clear theory (Coveney et al., Reference Coveney, Dougherty and Highfield2016), and these models can serve technocratic interests (including surveillance; Andrejevic, Reference Andrejevic and Pimple2014). Technocratic interests do not require understanding, merely prediction and control. In the social sciences, technocratic interests often entail one group (e.g., companies, governments, health services) creating knowledge to predict the behavior of another group (e.g., consumers, citizens, patients) and sometimes to change it for personal advantage (increasingly with advanced computational techniques; Hunter, Reference Hunter2018). Many popular theories in social science serve technocratic interests (e.g., nudge theory; Thaler & Sunstein, Reference Thaler and Sunstein2009), even when the outcomes are intended to benefit society.

Hermeneutic interests are served by knowledge that provides understanding, makes phenomena explicable, and, in short, tells a good story. This interest seeks insight into the world, history, and the human condition (Brockmeier & Meretoja, Reference Brockmeier and Meretoja2014; Martin & Sugarman, Reference Martin and Sugarman2001). From a hermeneutic standpoint, purely predictive models (e.g., based on big data) will be unsatisfying and uninsightful because they cannot explain the “why” of human activity (Coveney et al., Reference Coveney, Dougherty and Highfield2016; Wise & Shaffer, Reference Wise and Shaffer2015) or help us to make sense of the future (Jäger, Reference Jäger2016). Pure prediction fails because it bypasses interpretation – data are considered to contain, within themselves, the “finding” or “result” the researcher is looking for when, in reality, any act of research should be an act of making new meaning. Knowledge answering to hermeneutic interests does not need to predict or control anything; it only aims to explain in human terms, such as through narrative and metaphor (see Chapter 3; Bruner, Reference Bruner1990).

Emancipatory interests are served by knowledge that enables people to act, especially upon themselves (rather than other people). Emancipatory research leads to personal transformation and/or the transformation of one’s world. Habermas (Reference Habermas1968) argued that emancipatory knowledge entails reflective reason grasping itself as interested and attempting to transcend its own limitations. He gave the example of psychoanalysis, which provided people with concepts that could be used to liberate themselves from their unconscious tendencies (Madison, Reference Madison2005). Another example is what Paolo Freire (Reference Freire1970) referred to as conscientization, namely, the liberating act of coming to terms with one’s (sometimes oppressed) position in the world and striving toward a better, more equal, and just future. From an emancipatory standpoint, a big data predictive model could be emancipatory if it was put in the hands of people who used it to better predict and thus master their own behavior. Any knowledge can be emancipatory if it liberates people from their biases, habits, or societal condition (Mantelero, Reference Mantelero2018; Montiel & Uyheng, Reference Montiel and Uyheng2022).

Habermas emphasized the emancipatory interest, which he saw as arising in the reflective act of reason grasping itself and thus transcending the very interests it started from. He believed that the emancipatory interest, driven by critical reflection, can produce nonideological knowledge (Habermas, Reference Habermas1989). This might sound like an overly optimistic aim for research, given the cultural, historical, and political dimensions of scientific knowledge. The emancipatory interest should not be considered an end state but a means for developing studies that consider the hopes, needs, and life contexts of those involved in the research. It is research that foregrounds awareness, critical thought, and ethical concerns. Last but not least, it is research that produces knowledge for the sake of people rather than for the sake of knowledge itself. This does not mean that technocratic or hermeneutical interests are not valuable. Indeed, in trying to build something efficiently, we might need to increase control or be ready to predict the outcomes of our actions. At the same time, emancipatory interests should allow for a hermeneutic analysis of the situation before trying to implement change. The overarching point is that researchers should be aware of, and critically reflect on, the main interests that guide their research.

From a methodological standpoint, there is no one-to-one correspondence between the human interests being pursued and the methods used (Bauer & Gaskell, Reference Bauer and Gaskell2000). Although technocratic interests gravitate toward quantitative methods, so that the insights scale to larger groups, qualitative methods can also be employed for this purpose. For example, during the colonial era, qualitative anthropological studies were used for intelligence gathering on subjugated populations (Gosden, Reference Gosden, Meskell and Preucel2004). Today, qualitative studies could be employed to understand what people like or do not like about e-cigarettes (Pokhrel et al., Reference Pokhrel, Herzog, Muranaka and Fagan2015) and thus better target advertising. Equally, although hermeneutic and emancipatory interests gravitate toward qualitative methods, quantitative methods can be used (e.g., quantitative changes in how people use language; Moretti, Reference Moretti2013) and provide emancipatory insights (e.g., documenting inequality and social immobility; Breen & Jonsson, Reference Breen and Jonsson2005).

To some extent, the human interest underpinning a particular research project is revealed by the topic and declared aim of the study. For instance, research questions (see Chapter 4) that aim to measure, examine associations, or establish cause and effect typically follow a control and prediction logic specific to technocratic interests. But these might be secondary outcomes of the study itself, with the researcher primarily motivated to understand a set of events (hermeneutical) or give voice to participants rarely represented in research (empowering). Conversely, questions oriented toward uncovering human experience, a key aim in qualitative studies, may be only superficially hermeneutical if they are motivated by a desire to better predict how people will behave in a given context (technocratic).

The picture becomes even more complex when we consider mixing methods because different human interests can be served by various subcomponents or substages of the research, regardless of whether there is an overall interest that guides the entire investigation. This reflects the synergistic quality of mixing methods (see Chapter 6) and can lead, for example, to technocratic and hermeneutic concerns being subordinated to emancipatory aims or the other way around (for a discussion of paradigmatic perspectives in this type of research, see Shannon-Baker, Reference Shannon-Baker2016). Such potentially entangled interests should prompt mixed methods researchers to be extra reflective about their topic and methodological choices (Cain et al., Reference Cain, MacDonald, Coker, Velasco and West2019; Feilzer, Reference Feilzer2010). Using mixed methods, especially in a recursive manner (i.e., quantifying and qualitizing the same raw data; Chapter 7), can stimulate this reflection because the raw data usually reflect the interest of the people being studied (e.g., their words verbatim) while the highly transformed data increasingly reflect the interests of the researchers (e.g., codified or quantified using the researchers’ chosen constructs). Thus moving between these data transformations ensures that these interests are forced into contact. Moreover, such recursive transformations mean that the interests embedded in the raw data cannot be completely forgotten, but they remain salient and evident throughout the analysis process. A pragmatist standpoint does not prescribe which interest to pursue but it does demand reflexivity about the interests at stake.

9.2 Hierarchies of Knowledge and Interests

A question that students of research methodology sometimes ask is: Which is the best method to use? Teachers are quick to point out, in line with pragmatist views, that this question is incomplete without specifying “best for what.” And yet the positivist tradition does imply a hierarchy of methods, knowledge, and human interests. While the social sciences use a wide array of methods (e.g., randomized control trials, narrative analysis, experiments, experience sampling, and computational text analysis), they are not all considered equal. Some methods are viewed as intrinsically “better” than others. This approach proposes “hierarchies of evidence” that rank methods in terms of their rigor, reliability, and validity (Elamin & Montori, Reference Elamin, Montori and Burneo2012; Evans, Reference Evans2003). Usually, meta-analyses and systematic reviews are at the top of the hierarchy, closely followed by randomized control trials. Further down are descriptive studies with decreasing sample sizes and case studies at the bottom. While these hierarchies have been criticized for devaluing qualitative research and overvaluing quantitative methods (e.g., Creswell et al., Reference Creswell, Hanson, Clark Plano and Morales2007), a pragmatist lens provides additional insight into why these hierarchies are problematic.

From a pragmatist standpoint, different research methods are suited not only for different problems but also for different interests. For example, randomized control trials often serve a technocratic interest in determining precisely which specified intervention (e.g., a medicine, vaccine, or nudge) is effective in producing a predetermined outcome for a specific population (Birnie et al., Reference Birnie, Chambers and Taddio2015; Wilson et al., Reference Wilson, Just, Swigert and Wansink2017). This method effectively answers questions such as: Should medicine X be approved by regulators? Is medicine X more effective than medicine Y for condition Z? Does having chocolate near the checkout counter increase chocolate purchases? Are people more likely to agree to organ donation if they have to opt out compared to opting in? Randomized control trials are particularly effective in the social context of “evidence-based policy” because they adjudicate between interventions. They aid policymakers in deciding which medicine, intervention, or policy is likely to have the desired outcome (Sanderson, Reference Sanderson2002). But there is more to human life than evidence-based policy (for a critique, see Greenhalgh & Russell, Reference Greenhalgh and Russell2009).

Many valuable bodies of knowledge have developed without randomized control trials (Cornish & Gillespie, Reference Cornish and Gillespie2009). Theories of self-presentation (Goffman, Reference Goffman1959) and language use (Schegloff, Reference Schegloff2007) are insightful, revealing the incredible subtlety of human interaction. Their validity hinges upon good description and astute interpretation. A randomized trial in these domains would add little because the aim is hermeneutic understanding. Feminism does not rely upon experimental trials, yet it contributes to society by answering to an emancipatory interest (Fahy, Reference Fahy1997). Heuristics for living with mental illness (e.g., using headphones to block out hearing voices, reminder technologies for dementia; Gillespie et al., Reference Gillespie, Best and O’Neill2012; Shergill et al., Reference Shergill, Murray and McGuire1998) are also emancipatory. They are documented and circulated as potential resources, and it makes little sense to experiment to determine which is “best” because some work fully for some people but not for others. Similarly, we do not use experiments to determine which carpentry tool or mnemonic heuristic is “best” and remove the rest. The diversity of tools and heuristics is valuable; it is the fertile soil for future developments and a resource we can use for adapting to unforeseen contexts.

A pragmatist approach recognizes the diversity of human interests and values the diversity of methodological tools. However, it is critical of universal hierarchies (of evidence, knowledge, or interests). It asks the questions: Why have randomized control trials been conceptualized as superior to research focusing on the tactics of daily living and cultural critique? What purposes does this hierarchy serve? What do these hierarchies imply about the relation between research, methods, and human existence?

The hierarchy of evidence idea reveals that there is a hierarchy of human interests; it suggests that contemporary science is in the service of technocratic interests, not hermeneutic, and much less emancipatory interests. Positivism, grounded in the technocratic interests of prediction and control (Merchant, Reference Merchant2015), is widespread and assumes that predictive tools like experiments define what science is (Hendrick, Reference Hendrick and Hendrick1977). Hermeneutic traditions, often associated with qualitative and constructionist approaches, had a resurgence during the heyday of postmodernism, in the late 1980s and 1990s (with earlier roots in the more materialist approach of Berger & Luckmann, Reference Berger and Luckmann1966), but have come under considerable criticism recently in the wake of post-truth scholarship (D’Ancona, Reference D’Ancona2017; McIntyre, Reference McIntyre2018). Emancipatory research, while far from dominant, has been growing, fueled by Marxist, feminist, and postcolonial, and decolonial critiques (Sandoval, Reference Sandoval2013). Nevertheless, these emancipatory approaches struggle against the hierarchies of knowledge that enshrine the positivist interests of prediction and control.

Health psychologists have filled many library shelves with technocratic research, for example, on whether attitudes predict smoking, exercise, taking medication, ethical consumption, and so on. This research shows that despite well-intentioned attitudes, behavioral follow-through is more challenging (e.g., De Leeuw et al., Reference De Leeuw, Engels, Vermulst and Scholte2008). The neglected emancipatory questions that need to be asked are: What heuristics do people use to change their behavior? How can health psychologists create empowering heuristics to enable people to follow through on their attitudes? How can people be supported to design their lives so that their behavior can be consistent with their attitudes? And, more structurally, how can we collectively design societies to support human health and wellbeing? For example, might the societal structures of consumerism be fueling the growing epidemic of perfectionism (with the associated tendencies toward anxiety, self-harm, and suicide) among young people (Curran, Reference Curran2023)? These health-related questions do not depend on control and prediction or on understanding lived experience. What motivates (or demotivates) actions in this area reflects people’s networks of participation and the agency they derive from them (see Campbell & Jovchelovitch, Reference Campbell and Jovchelovitch2000).

Similarly, social psychologists have spent much effort examining the technocratic conditions for creating persuasive messages (e.g., Bergkvist & Zhou, Reference Bergkvist and Zhou2019; Chaiken, Reference Chaiken1979). Obviously, this research is beneficial to commercial and political interests. The neglected emancipatory questions include: What discursive tactics do people use to resist peer pressure and speak up? What heuristics and tactics could be created that might support people in critically evaluating and resisting persuasive advertisements? What knowledge might enable employees, politicians, and even regulators to speak up about problems? And, more structurally, what are the social and societal conditions that empower people to speak up about problems and voice concerns? What are the societal and organizational supports that enable people to listen to and act upon concerns raised? Again, these are uncommon research questions because they address a nonprioritized set of emancipatory human interests. They also challenge a long-standing negative bias when it comes to social psychological research that is extensively invested in the study of the loss of agency (e.g., conformity and obedience, the bystander effect, crowds and deindividuation, the automatic nature of stereotypes) rather than how individuals, groups, and societies gain agency, including as part of the research process (e.g., Christens, Reference Christens2019; Trott, Reference Trott2019).

In summary, the research questions we ask reveal the interests we serve. There is an infinity of research questions – no question is self-evident. All research questions entail a choice. We can choose to ask different questions. Instead of asking primarily “does X predict Y?” and “how can we make people do Z?” emancipatory questions ask “what do people want to do?” “what are their problems of living?” “what would enrich their lives?” and “how can we enable people to do what they want to do?” The point is not to replace technocratic questions and interests altogether but to realize that many other valid research questions and interests exist.

A pragmatist approach does not advocate for hermeneutic or emancipatory interests over technocratic interests; this would uphold an inverted hierarchy but a hierarchy nonetheless. Pragmatism only insists that diverse human interests are at the heart of knowledge production. And, with this realization, we are forced to address the challenge at the center of all science: Choosing one question out of an infinity of possible questions entails prioritizing one interest over others. This challenge cannot be addressed within science (i.e., science cannot tell us which questions to ask; see Chapter 4). There is no “True” interest or research question we should pursue. The choice of a research question is an ethical choice. Our choice reveals what we want to do, whom we want to empower, and what type of society we want to create.

9.3 Empowering Human Activity

Pragmatism accepts the contingency and uncertainty of knowledge (Dewey, Reference Dewey1929; Rorty, Reference Rorty1989). The only facts we have belong to the past; the future is an expectation that will become a fact, whether surprising or expected (Miller, Reference Miller2010). Knowledge is our attempt to generalize past experience into useful expectations (Peirce, Reference Peirce1955). Knowledge is our attempt to guide human action into a fundamentally uncertain future. However, this fundamental uncertainty does not mean that we should give up on knowing or become skeptical of it. Useful knowledge can reduce future surprises and make the future more, rather than less, expected, even if never entirely predictable. In this sense, there is a close affinity between pragmatism and recent propositions that all life (from cells to humans to societies) aims at surprise reduction and, thus, at maximizing expectation (Friston, Reference Friston2010; Friston et al., Reference Friston, Thornton and Clark2012). From a pragmatist standpoint, studying human action means engaging with the future-making and world-building potentialities of individuals and societies. It implies research that is sensitive to uncertainty, contingency, and surprise. We live in irreversible time (Valsiner, Reference Valsiner2014), in a world made and remade through differences (Glӑveanu & Gillespie, Reference Glӑveanu, Gillespie, Glӑveanu, Gillespie and Valsiner2014), material engagement (Malafouris, Reference Malafouris2019), and dialogues with alterity (Marková, Reference Marková2016).

Human beings are actively constructing the future, both for themselves and others. Reducing surprise is not merely a cognitive act. We build shelters, check the weather forecast, and put on sun cream to avoid the surprise of sunburn (see also the role of anticipation; Poli, Reference Poli2017). That is to say, the future we encounter does not merely happen, it is also something that we contribute to making (Thompson & Byrne, Reference Thompson and Byrne2022; Wenzel, Reference Wenzel2022). We are not passive in the face of the future – we use knowledge to prepare ourselves for various eventualities. This is not to say that we are always in control of the future we create; even our unintended actions contribute to the future we encounter (Gillon, Reference Gillon2001; Merton, Reference Merton1936; Tenner, Reference Tenner1996). We are often in the predicament of being responsible for a future that we did not intend to make. But, again, the lack of certainty, the disjunction between expectation and the reality of our future situation, should not lead us to abdicate responsibility. We can create knowledge that enables us to understand the consequences of our actions better and thus be more responsible (Baldwin, Reference Baldwin1979; van der Duin, Reference van der Duin2019). Our knowledge is necessarily imperfect, but it is better than nothing, and it is incrementally improving (including through scientific research and the Popperian principle of falsification; Popper, Reference Popper1969). Creating useful knowledge – the pragmatist marker for truth – entails not only making the future less surprising but also enhancing human coordination, empowering human action, and creating ideas, situations, and resources that bring out the best in humanity.

The pragmatist emphasis on the relation between action, knowledge, and responsibility invites a reflection on morality. From a pragmatist standpoint, to the extent that knowledge is consequential it is also moral (Brinkmann, Reference Brinkmann2010). Knowledge is necessarily moral because changing the possibilities for action changes the status quo (Mach et al., Reference Mach, Lemos and Meadow2020). If knowledge makes a difference for human life, then it is not merely a matter of Truth, it is also a matter of what future we want to create (i.e., the “Truth” of climate change, medical error, and famine are determined by human choices). This leads to the idea that we can evaluate knowledge not in terms of whether it is True but in terms of whether it enriches our collective future (de Saint Laurent et al., Reference de Saint Laurent, Obradović and Carriere2018). Thus, the discussion of human interests in this chapter goes beyond choosing between questions or methods; it fundamentally concerns the kinds of futures we envision, cultivate, and enact through doing social research. Is it the causal and orderly world of technocratic interests, focused on control and efficiency? Or are we cultivating intersubjectivity and lived experience, such that the future is built on understanding oneself and others? Or, yet, are we supporting agentic action in which participation is empowered for the construction of inclusive, just, and equitable futures?

As researchers, we hold additional responsibility for the world we live in and the world we bring into being through knowledge production (Glerup et al., Reference Glerup, Davies and Horst2017; Leonelli, Reference Leonelli2016). Even the smallest decisions we take in a research process contribute to this future in the making, whether we are aware of it or not, whether this is the future we intend or not. Gergen (Reference Gergen2015) argued against a mirroring view of knowledge and for a more active future-making paradigm. Instead of observing reality to report on it “as is,” he proposed we see research as a value-based exploration of what could be. The question is, then, what exactly do we want this world to be like? Science is a methodology that can make the world more predictable (technocratic interests), understandable (hermeneutic interests), and actionable (empowerment interests). But science cannot tell us what we should try to predict, understand, or act upon. Science is a method that cannot be used to determine the goals it should be directed toward. Deciding what to do with science is a decision that lies outside of science, in ethics, common sense (Marková, Reference Marková2016), or public deliberation (Christiano, Reference Christiano, Bohman and Rehg1997). Science can help us achieve goals, but there is no scientific determination of which goals we should pursue; that is a choice and, thus, a moral decision.

9.4 Methodologies of the Possible

We have argued for a pragmatist approach to key methodological issues such as epistemology, theory, questions, data, analysis, and ethics. It is important to emphasize that pragmatism, at heart, entertains any approach to these issues that makes a contribution. Pragmatism is inherently pluralistic (deVries et al., Reference deVries, Jackman, Aikin and Talisse2017; Melles, Reference Melles2008). It does not take a fundamentalist stance on any of these issues; the only thing it will not relinquish is the focus on the consequences. Pragmatism not only evaluates knowledge in terms of its consequences but it also conceptualizes methodology as a way to make new knowledge that opens up new (and hopefully desirable) consequences. This pluralistic approach to methodology opens new possibilities for research.

Possibilities come out of differences and dialogues of perspective (Glӑveanu, Reference Glӑveanu2020a; Glӑveanu & Gillespie, Reference Glӑveanu, Gillespie, Glӑveanu, Gillespie and Valsiner2014). We are all positioned in the world in material, social, cultural, and historical ways, and we develop perspectives on self, others, and society from the different positions we occupy (Gillespie, Reference Gillespie2012; Martin & Gillespie, Reference Martin, Gillespie, Martin and Bickhard2013, Reference Martin, Gillespie and Glaveanu2020). Equally, researchers are positioned in a material sense when conducting a study – from the tools used to the way in which bodies, roles, and places are engaged during an investigation – where they acquire different knowledge and identities based on the projects they work on and the institutions they belong to, each one with its own rights, responsibilities, and power relations. Importantly, researchers also occupy symbolic positions from which they enact symbolic perspectives on the problem at hand. These perspectives can be understood in general terms (e.g., theory, epistemology, and human interests) or specific ones (e.g., the way key constructs are defined, variables measured, and conclusions drawn). This is where methods emerge as both enablers and constrainers of possibility. When adopting a specific method, the researcher commits, at least to some extent, to its premises, approach, and worldview (Christ, Reference Christ2013; Kuhn, Reference Kuhn1962; Marková, Reference Marková1982; Mulej, Reference Mulej2007). Each method is a perspective that highlights specific qualities of the data, context, or findings and brings them to the fore. At the same time, it works to obscure other qualities and insights that would have become apparent to a researcher using a different method. Some possibilities are gained, some are lost (see Chapter 7 for the gains and losses of transforming data into excerpts, categories, and numbers). No method encapsulates the Truth; each method is incomplete but each can also be useful.

Possibility expands when a person, or a researcher, takes distance from and steps outside a singular perspective (Gillespie, Reference Gillespie, Valsiner and Rosa2007b, Reference Gillespie, Valsiner and Rosa2018). New possibilities arise in the space between perspectives or methodological approaches. This does not mean abandoning any particular perspective or method altogether. It is the capacity to relate the space of possibilities (and constraints) specific to one data type, method, or approach with alternatives that is crucial. Going back to pragmatist theory, it is an act of repositioning and, more specifically, exchanging positions (Gillespie, Reference Gillespie2012; Gillespie & Martin, Reference Gillespie and Martin2014) that holds the key to understanding the dynamics of the possible. In practical terms, this means moving between physical, social, and symbolic positions in ways that enrich one’s perspective and understanding of the situation. Each movement can potentially leverage new insight into the problem at hand. For example, in the game of hide and seek, mastering the two positions (hiding, seeking) and their associated perspectives and being able to even hold them simultaneously (i.e., hiding with the view of the seeker in mind, and the other way around) is crucial for a player’s success. And children learn to play hide and seek by alternating between doing hiding and doing seeking (Gillespie, Reference Gillespie2006b). Agency and creativity within the game come not from taking the role and the associated perspective of either the hider or the seeker but from integrating both.

In methodological terms, this means that new spaces of possibilities open not only when we use multiple methods in the same research project – the metaphorical equivalent of occupying multiple positions – but especially when we can seamlessly move between these methods and the perspectives they offer. Multi-resolution research (Chapter 7) is meant to achieve precisely this aim. Within it, while distinct analytical steps can still be differentiated, what matters more is the repositioning offered by zooming in and out of the same dataset, the simultaneity of grasping overall patterns (zooming out) and individual detail (zooming in). The recursiveness vis-à-vis the data, reminding of position exchange, is a feature embedded in multi-resolution research. It scaffolds possibility-enabling processes within research by fostering repositioning via position exchange (e.g., moving between qualitative and quantitative positions in relation to the same raw data) and dialogues of perspective (e.g., showcasing potential tensions between raw and transformed data). At the same time, multi-resolution research is not a specific form of analysis. Thus, it is less prescriptive than most other methods, and in the spirit of pragmatism, it allows researchers the freedom to choose between specific analytical tools regarding their data, problem, and question. This increased agency evokes empowerment as a human interest when applied to the choice of methodology. Whether the exact topics under investigation help or empower people depends, of course, on each project. However, by offering the opportunity to retrieve the particular within the general (and the general in the particular), multi-resolution research makes it easier to recover participant voices, stories, and experiences and let them support, nuance, and often contradict the overall pattern, thus increasing the chances of discovering surprise and having our expectations disrupted.

An overarching theme running through each chapter of this book is the idea that differences (between theories, questions, methods, and research traditions) can expand the possibilities for research. Whether discussing epistemology, theory, data, or analysis, the emphasis falls on how diverse perspectives can be brought together and how this dialogue of difference can enable creative synergies. Pragmatism is inherently pluralistic, and while such pluralism can make some researchers recoil with the fear that “anything goes,” pragmatism cuts through with a clear-headed focus on consequences.

Chapter 1 outlined seven propositions for a pragmatist approach to methodology in social research – each developed further in the subsequent chapters. This pragmatist approach starts with action and its consequences. From the start, what is specific for human action is that it can have multiple motivations and be guided by various interests and concerns (see also Boesch, Reference Boesch1991). Research is no exception, and any viewpoint, datum, or analysis is welcomed if it can contribute to the problem at hand; there is no fundamentalism beyond the commitment to being useful and making a contribution. However, to fully appreciate the consequences of knowledge necessarily requires engaging with the perspectives of multiple stakeholders (e.g., research colleagues, participants, ethics committees, and institutions). Human possibility is expanded not by being trapped in one perspective but by evaluating the consequences of knowledge from a diversity of standpoints.

Chapter 2 developed the epistemological proposition that truth is in its consequences. Historically, the debate has been between, on the one hand, realist and positivist views and, on the other hand, constructionist, relativist, and postmodern views (Jovchelovitch, Reference Jovchelovitch2019). Pragmatism emerges, historically and methodologically, as a third epistemology that avoids the pitfalls of a transcendental Truth and hopelessly subjective and fragmented truths. Pragmatism focuses on the future rather than only the present or past; it focuses on the world as it becomes, and not only the world as it is or was. Simplistically, positivism is an epistemology anchored in the past; it emphasizes underlying causes as the push from the past. It uses the metaphor of the universe as a mechanical clock set in motion by initial conditions. Constructionism is an epistemology anchored in the present. It risks trapping researchers in an eternal present of subjective experience without being able to say anything confidently about the past or the future. Pragmatism is an epistemology anchored in the future; it takes ideas and expectations from the past, acts in the present, and evaluates everything by the consequences in the future.

Chapter 3 developed the proposition that theories are tools for action. The idea is that theories crystallize past experiences into guides or maps to the future, which can be more or less useful. From a pragmatist standpoint, we use theories to make the world more predictable, hospitable, and actionable. Theories are lenses through which we make sense of ongoing events and the data derived from them; theories lean into the future (Davis, Reference Davis2021). This pragmatist realization is empowering because it enables researchers to take advantage of moving between the bricolage of theoretical positions to acquire more tools to act on their data. From a pragmatist standpoint, theories are rarely competing alternatives (e.g., to be tested between) and are more often akin to a collection of tools, with each tool being useful in certain cases. Instead of separating theory from data collection and analysis, as is common, pragmatism sees the value of theory throughout the research process. Placing the researcher at a meta-level and, as such, developing theories about one’s own theoretical tools and constructs can be empowering by creating a much-needed space for choice and deliberation about theories and methods.

Chapter 4 developed the proposition that research is as much about creating questions as answering questions. To this end, we outlined a typology of research questions and conceptualized these questions as bridges between theories and research practice. If theories are tools, then research questions connect these tools to the particularities of the problem at hand. Following the pragmatist principle of plurality, in this typology, quantitative and qualitative lines of questioning are not only intrinsically diverse but they can and do often complement each other, supporting theoretical development and empowering researchers to create new questions (Fetters & Molina-Azorin, Reference Fetters and Molina-Azorin2017b). What is possibility-enabling at this level is the capacity to mix and match research questions, aware of the different human interests and theoretical commitments they embody. This is empowering for researchers to the extent to which they can then innovate at the level of method and pragmatically adapt their analytical procedures to the new questions being created. Creating new questions entails being open to surprise and being sensitive to disruptive data. We argued that one way to search for such disruptions is to move back and forth between theories, methods, and modes of analysis. Tensions revealed by such movement are the seeds of possibility – new theories, questions, and paths of action.

Chapter 5 developed the idea of data as a process. In contrast to static classifications of “types” of data, we examined different “states” of data. The idea is that raw data can be transformed into different types of data, and thus they can be continuously restructured into multiple types. Data emerged, thus, as a process rather than a fixed state, very much in line with the pragmatist emphasis on repositioning in order to develop new perspectives. And, indeed, working with data has different affordances depending on where these data are in their transformation (Hogan, Reference Hogan, Bertino and Matei2015). Most of all, the reversibility of data transformations reflects the principle of position exchange and, as such, has the potential to expand researcher agency. But, of course, there are also powerful constraints on data collection, including data accessibility, that can hinder possibilities in this area. Data have been described as the new oil, and thus companies increasingly want exclusive access to the data they collect. Often researchers are locked out under the guise of protecting personal data. This undermines the possibility of researchers scrutinizing how these data, concealed within the corporate vaults, are (and could be) used.

Chapter 6 developed the proposition that qualitative and quantitative methods are synergistic. Mixed methods research is a clear example of “methodologies of the possible” because of the creative synergies that can be produced. The literature on mixing methods is vast and continuously expanding (Molina-Azorin & Fetters, Reference Molina-Azorin and Fetters2022), and, at its core, it offers researchers an expanded horizon of possibilities regarding topics under study, methodological procedures, and the depth and usefulness of research findings. Often driven by a pragmatist type of logic, even if only implicitly, mixed methods cut across old divides, especially the one between qualitative and quantitative data and analyses. Although mixed methods research often fails to yield synergies, when it does, the results can be dramatic, with each method reinforcing, enriching, and even challenging the other. The key theoretical issue for mixed methods research is the integration challenge (Fetters & Freshwater, Reference Fetters and Freshwater2015a), namely, the challenge of specifying how mixing methods can yield outcomes that are more than the sum of the parts. We showed how a pragmatist approach can contribute to this debate, by showing how qualitative and quantitative research have different purposes and how these purposes can be combined in synergistic and empowering ways.

Chapter 7 developed the idea of analyzing big qualitative data both qualitatively and quantitatively. The key insight here is that big qualitative datasets do not have a fixed data type; they can be converted into both qualitative (e.g., excerpts) and quantitative (e.g., numeric) forms. Recursively repositioning vis-à-vis the raw data can improve rigor, spur theoretical development, and expand the possibilities for analysis. Zooming in and out of the same body of data provides more legitimacy to the findings while, at the same time, increasing the possibility of abductive insights (Mitchell, Reference Mitchell2018). This intrinsic creativity of multi-resolution research, in terms of its outcomes, resonates with the agency of researchers applying this new methodology. This is because, besides some general guidelines, multi-resolution research does not overconstrain the types of analyses (quantitative or qualitative) that can be applied to the data. At the same time, working with data at different stages of structuration allows for the kind of repositioning that is fundamental for agency and possibility. This opens the ethical question of whether the new possibilities experienced by researchers are translated into expanded fields of opportunities for participants or other stakeholders.

Chapter 8 elaborated on the pragmatist proposal that social research creates both power and responsibility. A pragmatist approach to ethics moves away from universal principles toward contextual moral deliberation. This view reveals the deep connections between pragmatism and democracy as a sociocultural practice (Brinkmann, Reference Brinkmann2013; Caspary, Reference Caspary2000). From this standpoint, the emphasis is placed on dialogue and participation rather than preestablished and decontextualized moral laws, something that is also at the heart of emancipatory human interests (i.e., being able to understand and value marginal perspectives and local knowledge, and measure them against their consequences for individuals, groups, and society). Conducting social research requires engagement with issues of participation, deliberation, and responsibility. If we bring futures into existence through our research and methods, we hold responsibility for how these futures affect others, not only in the short term. Ethics is, thus, not a one-time concern, typically at the start of the research process, but an ongoing practice of reflection on the present in the horizon of multiple possible futures.

Finally, we get to the uniting proposition of this chapter, that social research should aim to expand human possibility. Pragmatism views science as a means to create useful knowledge. What counts as useful, however, is determined by the guiding research interests (e.g., technocratic, hermeneutic, or emancipatory). No scientific method can determine which interest social researchers “should” pursue; it is a choice. Our choice, along with the early American pragmatists, is unashamedly emancipatory: social research should be used to increase people’s capacity to act, to improve lives, to make the future more predictable and desirable, and to be reflective about who is using which knowledge to do what to whom.

9.5 Conclusion

In this final chapter, we argued that social scientists are not mere servants of Truth, they are social, cultural, and political actors making choices, following human interests, and advancing toward their preferred futures (Voros, Reference Voros2003). Research is never the neutral pursuit of Truth, regardless of how much realists and positivists would want it to be. But neither is it the mere cataloging of subjectivities and social conventions, as it is sometimes portrayed by constructionists. From a pragmatist standpoint, research is an activity animated by human interests that is part of the activities of today that will shape the lives of tomorrow (McNamee, Reference McNamee1988; Schratz & Walker, Reference Schratz and Walker2005).

Given that “knowledge is power” (Mead, Reference Mead and Moore1936, pp. 350–351), we should also evaluate it in terms of the interests advanced or hindered by it. Is the research producing effective, insightful, or emancipatory knowledge? Pragmatism invites us to reflect on this question but does not determine what interests we should pursue. For some, this might be a glaring hole at the heart of classical pragmatism. In trying to avoid hierarchies and dichotomies, pragmatism also avoids prescribing courses of action and considers each human interest potentially useful, depending on what we might want to achieve with it. How should we decide which interest to follow? Are all of them equally valid? What if the interest motivating the research leads to the domination of others or environmental destruction? Where do we draw the line? Faced with the multiple global challenges of today, it seems irresponsible not to take a stand on this issue.

The early positivists, such as Comte (Reference Comte and Martineau1858), recognized these issues. Comte saw the transformative potential of social science for society but argued that it needed to be given direction by a secular religion that itself was outside science. The pragmatists, in contrast, put their faith in democracy (Addams, Reference Addams2002). This link between democracy and science is odd for many realists, but, from the standpoint of pragmatism, which sees no clear separation between values and knowledge, it is essential (Brinkmann, Reference Brinkmann2013; Putnam, Reference Putnam1995). Social science needs steering in terms of what questions to ask, what interests to enhance, and how to evaluate the consequences of the knowledge produced. It is only through deep democracy, permeating the public sphere and institutions, that the interests of the many can be addressed and the most broadly beneficial consequences of knowledge can be achieved.

In this book, we have developed pragmatism into a possibility-expanding approach to methodology. The pragmatist insight is to use consequences to bypass relativism and reconceptualize all knowledge as moral. This approach is grounded in notions of difference, plurality, and dialogue. The strength of this approach lies in the value of considering traditional topics such as epistemology, research questions, data, analyses, and human interests as intrinsically plural. There is no universally better question to ask or method to use; creativity and agency are embedded in the myriad of choices researchers have to make along the research process (see also Wegener et al., Reference Wegener, Meier and Maslo2018). Mixing methods, an eminently pragmatist exercise, is especially amenable to reflection, deliberation, and discovering new synergies and possibilities.

A pragmatist approach to refining our methodologies of the possible can help social researchers to seize the emerging potentials created by the exponential increase in new forms of data and, in particular, big qualitative data (see Chapter 5). Besides the opportunities and challenges associated with using this mainly – for now – public resource, there are a few methods out there that can use these data to reach useful and meaningful conclusions. Moreover, any single method, in isolation, risks giving us only a partial picture when it comes to this kind of data (think, for instance, about the advantages and disadvantages of natural language processing vs. discourse analysis). Possibilities abound when it comes to creatively devising new tools for research, and this book advanced one such idea in the form of multi-resolution research (Chapter 7). Such methodologies have the potential to create more valid and robust findings that are useful because they are simultaneously connected to particulars while also leveraging vast quantities of data.

Although we were not born into a universe with the simple certainties often craved (Dewey, Reference Dewey1929), we have the potential and the responsibility to improve the world we find ourselves in. What is often sought “behind” human experience needs to be created through human experience. Certainties, agency, and social justice are made, not found. Pragmatism entails a project of world-making (Gergen, Reference Gergen2015; Power et al., Reference Power, Zittoun and Akkerman2023). It eschews grand plans and simple narratives in favor of concrete incremental improvements to the human condition (Dewey, Reference Dewey1910a). A pragmatist approach to research methodology starts from where we are, with the world as we find it, and aims to improve upon it. As James eloquently wrote, the world is “unfinished, growing in all sorts of places, especially in the places where thinking beings are at work” (Reference James1907, p. 116). To support this collective project, the role of research is not simply to describe the world as it is but to help imagine the world as it could be.