The idea that theory should be practical is both obvious and surprising. It is obvious because the avowed aim of science is to create knowledge to empower human activity (Bacon, Reference Bacon1620). However, theory is often associated with abstruse terms and obscure concerns (Tourish, Reference Tourish2020). Kurt Lewin’s (Reference Lewin1943, p. 118) maxim that “there is nothing as practical as a good theory” has gone from being cited about ten times a year in the 1990s to nearly fifty times a year recently (McCain, Reference McCain2015). This upsurge betrays the challenge of creating robust and insightful theories in social science that are also useful.

Developing useful knowledge is challenging because theory that is too practical is quickly criticized for being unsurprising, lacking intellectual depth, and merely repackaging common sense. While it is easy to do something useful (e.g., help someone, cook a meal), it is much more challenging to create helpful knowledge. Creating useful knowledge entails synthesizing prior experience and applying it to an unknown future. It means going beyond what is already done, opening the future up to more purposive human action, and, in short, expanding human agency. In this sense, useful knowledge aims to empower human action, to make the consequences of human action expected, and to avoid unwanted surprises.

We propose that pragmatism, especially as developed by the early American pragmatists (Charles Sanders Peirce, John Dewey, Jane Addams, William James, and George Herbert Mead), provides a helpful way to think about methodology in social research. It provides timely conceptions of epistemology, theory, research questions, and data that can address our current concerns. It can help us make useful knowledge that is neither naïvely realist nor impotently critical, and it can help us address the current challenges and opportunities of both big and small data.

There is an irony in the consequences of pragmatism. As an approach, it is avowedly against abstraction and abstruse theory. It argues for starting and ending with the problems of living. But the consequences of pragmatism have been mainly theoretical and philosophical rather than practical. Despite pragmatism contributing to diverse domains (Allemang et al., Reference Allemang, Sitter and Dimitropoulos2022; Ansell & Boin, Reference Ansell and Boin2019; Craig, Reference Craig2007; Kaushik & Walsh, Reference Kaushik and Walsh2019; Kelly & Cordeiro, Reference Kelly and Cordeiro2020) and being foundational to mixed methods research (Morgan, Reference Morgan2014a), there have been few systematic attempts to translate the philosophy of pragmatism into a consistent methodology. This book aims to bridge this gap in pragmatist scholarship by outlining the consequences of pragmatism for social research.

From a pragmatist standpoint, knowledge should be effective, insightful, and emancipatory in its consequences. We have written this book not to contribute to pragmatist philosophy but to develop pragmatism’s fruitful consequences for social research methodology. Traditionally, methods in the social sciences have been caught between realist (often quantitative) and relativist (often qualitative) tendencies. We use pragmatism to chart a course between these extremes and to produce knowledge that is both useful and critical. To this end, the book provides an end-to-end pragmatist approach to knowledge creation, spanning epistemology, theory, question creation, and the nature of data, methods of analysis, and ethics.

We are social and cultural psychologists focused on studying human activity in context, enabled by both knowledge and technology. Indeed, we use this basic orientation to understand social research activity as also being enabled by knowledge (e.g., theories, epistemology, research questions) and technology (e.g., questionnaires, interview techniques, and computational algorithms). While many of our examples pertain to social and cultural psychology, the ideas presented are broader and, we believe, have applicability across the human sciences. Specifically, this book aims to contribute to three broad debates.

1) Rehabilitating the value of useful knowledge. The so-called paradigm wars in social science have had consequences beyond academia, providing resources for “post-truth” politics. The paradigm wars related to debates between realism and relativism (often termed “constructionism”), focusing on the extent to which scientific knowledge is true versus being a human construction (Bryman, Reference Bryman, Alasuutari, Brannen and Bickman2008). Unhelpful oppositions were created: science versus critique, realism versus relativism, and objectivity versus subjectivity. Nuanced arguments on both the realist side (Hacking, Reference Hacking1999) and the constructionist side (Berger & Luckmann, Reference Berger and Luckmann1967) were oversimplified. Extreme and unrepresentative positions emerged on both sides. On the realist side, qualitative analysis was shunned as unscientific, and on the constructionist side, quantitative analysis was resisted as naïve, uncritical, or even oppressive. Nevertheless, despite being uncommon positions, these extremes undermined science within the public domain (Onwuegbuzie & Leech, Reference Onwuegbuzie and Leech2005) and sowed seeds of doubt that enabled inconvenient facts to be dismissed and “alternative facts” to thrive (Cooke, Reference Cooke2017, p. 211).

A pragmatist approach to social research acknowledges the stubborn resistance of facts and also the subjectivity and contextuality inherent in all knowledge. We argue that this approach can provide both the basis for creating common ground around effective knowledge while also avoiding science as an ideology beyond critical questioning.

2) Mixing methods. The paradigm wars drove an unhelpful wedge between qualitative and quantitative methods that had previously worked synergistically (Morgan, Reference Morgan2007). It was argued that qualitative and quantitative methods pertained to fundamentally different, incommensurable, epistemological frameworks (Filstead, Reference Filstead, Cook and Reichardt1979) and were “competing paradigms” (Guba & Lincoln, Reference Guba and Lincoln1994, p. 105). While separating qualitative methods from quantitative methods enabled qualitative methods to mature independent of a quantitative framing, it had the unfortunate consequence of undermining mixed methods research. Indeed, it even became seen as potentially philosophically naïve to try and combine them (Denzin, Reference Denzin2012).

A pragmatist approach argues that qualitative and quantitative methods can be combined and, moreover, that they should be combined. Quantitative methods provide breadth, and qualitative methods provide depth. If both add value, why choose one over the other? The choice is false: It is more rigorous to have both breadth and depth. Together, they can make social science more robust, insightful, and emancipatory. Moreover, we will argue that mixed methods research is necessary for addressing the challenges and harnessing the potential of big qualitative data.

3) The challenge and potential of big qualitative data. Qualitative research in psychology and related disciplines is at a crossroads. On the one hand, the field has substantially increased in terms of its thematic reach – the number of studies, journals, and textbooks. However, we are living through a qualitative data explosion, with an exponential growth of digitally recorded but unstructured text, image, audio, and video data. While these data are often termed “big data,” they are also “qualitative data.” Thus, somewhat ironically, at the extreme end of quantification (i.e., big data) is qualitative data (i.e., digital text, image, video). To tackle the challenges of these data, and to make the most of the opportunities they offer for social research, we need to integrate data science (i.e., quantitative and computational) techniques with qualitative research techniques (Bazeley, Reference Bazeley2017; Chang et al., Reference Chang, DeJonckheere and Vydiswaran2021).

A pragmatist approach suggests a novel way of mixing big data and qualitative research techniques. We will argue not only for mixing qualitative and quantitative methods side by side but also for what we call multi-resolution research, where the same data are analyzed both qualitatively (to zoom in on details) and quantitatively (to zoom out on patterns). Such analysis is possible only by reconceptualizing raw data as affording a bidirectional transformation into both qualitative and quantitative forms. Such bidirectional transformations enable a continual moving back and forth between qualitative and quantitative facets of the same dataset.

Overall, we argue that a pragmatist approach to methodology can address the challenge of creating useful knowledge, enhance the rigor and creativity of research, foster deeply integrated qualitative and quantitative methods, and avoid overly simplistic oppositions between realism and relativism. Pragmatism’s guiding insight is to consider the consequences of knowledge. This enables a realist-type analysis of the effectiveness of knowledge combined with a constructionist-type critique of who benefits from that effectiveness. The chapters in the book step through pragmatism (Chapter 1), epistemology (Chapter 2), theory (Chapter 3), research questions (Chapter 4), data collection and curation (Chapter 5), mixed methods research (Chapter 6), multi-resolution research (Chapter 7), ethics (Chapter 8), and the role of social research in enhancing human possibility (Chapter 9). The aim is to propose pragmatism as a coherent, flexible, and robust framework for creating useful knowledge that can enhance society.

Finally, in preparing this book, and in the many years of discussion that led to this book, we would like to acknowledge the intellectual support of our colleagues, including Flora Cornish, Kevin Corti, Ioana Literat, Mark Noort, Tom Reader, and Tania Zittoun. This book has been supported financially by two grants from the Swiss National Science Foundation (51NF40-205605 via “nccr – on the move” and P400PS-180686).