Citation in APA format: Paluck, E. L., & Shah, A. K. (2025). Field research: Five approaches to theoretical development in the field. In D. T. Gilbert, S. T. Fiske, E. J. Finkel, & W. B. Mendes (Eds.), The handbook of social psychology (6th ed.). Situational Press. https://doi.org/10.70400/MHNP3692

Field Research: Five Approaches to Theoretical Development in the Field

Elizabeth Levy Paluck, Princeton University

Anuj K. Shah, Princeton University

Social psychologists are radicals; deeply so, almost by habit. Because to understand how people think and behave in the world, they often turn to laboratory experiments. Each one of those laboratory experiments is a radical act. It is an assertion that one can take some feature of a complex world, simulate it in the lab, and examine it with precision. And with a series of these radical acts, psychologists hope they might develop and test laws about human behavior in the world.

This chapter, we warn you, will be much less radical. It will discuss how to develop and test theories about people thinking and behaving in the world by running studies in the place where that thinking and behaving normally happens: the world.  

There is a long tradition of social psychologists doing fieldwork (going back to Campbell, Cook, & Day, 1979; Lewin, 1939; 1951), but field research isn’t as dominant a method as laboratory or online experimentation (see Miller & Laurin, 2025; Wilson, Westgate, & Aronson, 2025). Indeed, psychologists have sometimes cast field research as the “end game” in the process of theoretical development. The psychology laboratory is seen as a spare, precise environment—the behavioral version of a physics laboratory, where scientists control various dimensions of the research and only allow the variables of interest to move. This vision of laboratory research is contrasted with a wider, and wilder, “field” or “real world”, where distractions and confounds blur the precision of findings.1  

By this account, field research is less useful for theory development. Rather, it is something to attempt after a theory has been fully developed in the laboratory. This is one reason why field research is often labeled as “applied research”, implying that a fully fleshed-out and tested theory is applied to a problem or challenge presented by the real world.  

And so in social psychology, researchers have a habit of treating the lab as the site of theory development, whereas the field is for application. But in this chapter we highlight several notable times that psychologists broke with that habit, and we consider how this kind of field research can help develop social psychological theory. 

From the start of the discipline, social psychologists have consistently demonstrated how theory can be developed in the field. Social psychologists like Kurt Lewin and Donald Campbell located much of their important theoretical work in field settings, and many psychologists followed this tradition (see Miller & Laurin, 2025).  Robert Cialdini, whose field experiments on persuasion and influence built some of psychology’s most influential theories of social norms and behavioral change, introduced the concept of “full cycle research” (Cialdini, 1980; Mortensen & Cialdini, 2010). Full cycle research is a scientific process in which a powerful and interesting phenomenon is identified in its natural environment, and subsequent tests of the phenomenon move back and forth between the laboratory and the field, depending on when the researcher wants to investigate theoretical underpinnings and mediators (in the laboratory) or to assess the impact of the phenomenon and its theoretical conditions in the world (field).  

This chapter, and all the research that it describes, has benefited greatly from the full cycle approach. Much of the research in the sections below can be described as full cycle. But instead of describing the complementarities of laboratory and field studies (see Wilson et al., 2025, for a longer discussion of laboratory work), this chapter will focus entirely on how field research on its own can be used to develop theory.  

Previous reviews of field research have covered different field research techniques, such as interviews, ambulatory measures, and randomized rollout designs (e.g., Reis & Gosling, 2010, Paluck & Cialdini, 2014). These are enormously useful in helping researchers figure out how to rigorously test hypotheses or answer questions. But here, we focus on an important step that comes before designing a study: Thinking through the kinds of questions one might try to answer with field research. The subsequent sections detail different orientations towards the field, which vary on two dimensions of theoretical development: Questions about psychological phenomena (e.g., behaviors, emotions, and thoughts) and questions about the real-world context of those phenomena. Conveniently, this typology creates a classic social psychological 2x2 bracket.  

Specifically, some field studies begin from a relatively well-defined psychological phenomenon, meaning that the theory has already been developed, but it could use refinement or extensions. Field research is useful for theory at this stage because it can test its conditions, boundaries, decay of its predicted effects over time, or its strength relative to other theories. For example, theories of social norms’ influence on behavior are well-established, but there remain questions about how long effects persist (e.g., Allcott & Rogers, 2014) or who shapes the emergence of new norms (Paluck & Shepherd, 2012). Other field studies start from a psychology that is relatively undefined and seek to discover or elaborate a theory based on initial intuitions. These studies start from an observation of a phenomenon, like a pattern of behavior or some fingerprint of a distinct mental process, and then collect evidence to build a hypothesis regarding the psychology of that behavior or mental pattern. For example, psychologists have sought to understand the psychology of choices made among people living in poverty (Mani, Mullainathan, Shafir, & Zhao, 2013), or of transgender youth (Fast & Olson, 2018). 

A second dimension of theoretical development involves questions about the real-world context. Some field studies take place in relatively well-defined contexts, meaning that the researcher knows a great deal about the behavioral or psychological patterns evident in that context, and has chosen that specific context to study those patterns and to understand them better. These contexts could include a political campaign (Kalla & Broockman, 2020) or a youth intervention that is explicitly designed by social scientists and their practitioner collaborators (Heller, Shah, Guryan, Ludwig, Mullainathan, & Pollack, 2017).  Other field studies are in relatively undefined contexts, meaning that researchers have fewer observations about behavioral patterns or psychological processes of that context. These contexts might include a collection of neighborhoods where researchers are trying different approaches to enrolling residents in an energy program (Yoeli, Hoffman, Rand, & Nowak, 2013), or various departments in a factory where researchers are trying different meeting structures for employees (Wu & Paluck, 2020). In relatively undefined contexts, one context might substitute for another equally well in the study of a psychological phenomenon. Part of an investigation includes whether the researcher can reliably observe the psychological phenomena in that particular context and whether the context does in fact matter.  

Table 1 shows how these two dimensions of psychological inquiry can interact. On the top, the table invites readers to consider the psychological phenomena of interest. Does the reader already have a well-defined theory about the psychologies under consideration—how they relate to each other, and to behavior? This is a well-defined psychology. Or perhaps readers are interested in psychological phenomena like behaviors, emotions, or thoughts but don’t yet have a fully-developed theory of the extent to which they are interdependent, or of how they relate to the context or what behaviors they predict. This is an undefined psychology. On one side, the table invites readers to consider what they know about the field context of interest. Maybe they have many observations about the context that make it a perfect place for a study (i.e., the context is well-defined); maybe they don’t have as many observations of the context and how psychological phenomena play out there (i.e., the context is undefined). 

Readers can put a particular project into one of these quadrants after they understand their inputs, in terms of their chosen psychology and context under study. Each quadrant describes the goal of a study with a combination of a relatively well- or un-defined context or psychology, and what kind of theoretical development to expect. For example, in the undefined context + undefined psychology context, researchers are “Scouting.” Researchers would run this study because they’re unsure of what context they should simulate in the lab. The theoretical development researchers could expect is a sharpened focus on which behaviors and mental processes need more exploration. Or take the defined context + defined psychology quadrant, which we label “Refining.” Researchers would run this study because the context and the psychological phenomena seem like a match for one another, sometimes because there are previous studies of the psychology in this context, or maybe because the researcher believes that the psychological theory holds the key for “solving” a problem or psychological challenge that is well-observed in that context. In this quadrant, researchers could expect to refine their theory of the context and the psychology as a result, perhaps by identifying heterogeneous conditions of their prediction, or by identifying the rate of decay of the phenomenon.  

This typology is meant to orient social psychologists to the kind of field research they want to plan, and what kind of theoretical progress they might expect from the research. Potentially, one project could serve various purposes, and the quadrants could help clarify which purpose fits the project. For example, a researcher might know that they want to work with a well-defined psychology, but might not know where they want to locate their field study. Should they find a relatively well-understood context, so that the goal of the project becomes theoretical refining (e.g., identifying the longevity of the effect, or heterogeneity of the effect on different groups of people)? Or should they locate the study in a relatively understudied context, in which case the goal of the project would be to “Prototype”, meaning that the goal is to understand whether this theory extends to this new context and whether you might learn something about its theoretical predictions when the ideas are prototyped in new conditions. In sum, the quadrants do not offer a rigid typology and should not constrain where researchers go, theoretically or physically, with field research. The quadrants can be used to clarify the goals of a project that has already been planned, or to identify goals for new field research where the context or the theoretical motivation is still under development.  

The rest of this chapter describes recent field research that falls in each of the cells of this 2x2 and articulates the types of theoretical progress each type of study has made. The studies highlighted in each cell are exemplary in their design, in their creativity, or the innovation of their methods, although no one study is perfect in every dimension. While they vary greatly in the contextual and psychological phenomena of interest, the country where they are located, and the methods they use for inference, one commonality is that they are all identified as field research. What do we mean by field research? We define field research as relatively more naturalistic and allow for a continuum-based (rather than dichotomous) conceptualization. When assessing the degree to which studies qualify as field studies, we consider the naturalism of four aspects of the study: (1) participants, (2) the intervention and its target, (3) the obtrusiveness of intervention delivery, and (4) the assessed response to the intervention (Paluck & Cialdini 2014). 

After reviewing examples of each of these four types of theoretical development, we propose a fifth type of field research, which pursues a type of psychology that does not aspire to universalism. We call this type of theory development an “undefined interaction”, because in this case it is the interaction itself that is relatively undefined, as opposed to the relative definition of the psychology or of the context. This kind of research has previously been called an “afforded psychology” (Steele & Sherman, 1999), in which researchers study a psychological phenomenon that arises from a very specific context. We label this type of research “Situating” research. The purpose of the research is not to generalize to other contexts, but to make predictions about the psychological phenomena in the same context. For example, using qualitative interviews with women at a homeless shelter in New York City, Steele and Sherman (1999) focus on how a particular type of self-reliance emerges for women on government assistance because they cannot be economically dependent on anyone else. Research of this type can still make meta-scientific progress by using methods that can inform questions from other contexts (or other interactions between context and psychology). For example, recent developments in computational and algorithmic approaches to social psychology can yield both specific insights within a context, as well as generalizable methods for understanding other contexts.  

Table 1: Types of Field Research, as Defined by the Theoretical Development That Is Possible When the Research Begins from a More Defined Vs. Undefined Psychology and Context

PROTOTYPING: DEFINED PSYCHOLOGY, UNDEFINED CONTEXT 

Field studies that take a well-defined psychology into a less-defined context, a theoretical project we call prototyping, may be the most common type of field research in psychology. In a prototyping field study, there is ample laboratory or survey evidence behind the psychological theory, and so researchers decide to study the theory in “real-world conditions.” Designers call this type of activity prototyping when they turn an idea into a material object in the world. Prototyping is the attempt to find out more about the idea by road-testing it in naturalistic conditions. For psychologists, taking a well-understood theory into the world usually means choosing a context that is not as “well-defined” as the psychological theory, in that the context has not been extensively studied in the past, and there is not much theory that describes the problems or specifics of the context.  

In these studies, the researcher often knows relatively little about how the psychological phenomenon functions in the real world, or about which contextual features may support or detract from that phenomenon. The researcher may wish to scale the size of the phenomenon by measuring its strength in the presence of real-world distractions, or by comparing it to other psychological phenomena that can be simultaneously measured in the world. The researcher may also want to assess contextual conditions under which the phenomenon is strengthened or diminished.   

It is not uncommon to hear feedback like “But we already knew that!” when these kinds of field studies show an effect of the phenomenon in a real-world context. Similarly, audience members might label the study as an “application” of what is known. However, field researchers and cultural psychologists have pointed out that the psychological laboratory is one particular context, or culture, and that the translation from this culture to any others needs to be assessed to ensure that the phenomenon is not particular to the laboratory (e.g., Adams & Stocks, 2008).² From this perspective, a theory with only laboratory evidence raises the question: do we have an existence proof of this phenomenon in any real-world setting? Moreover, laboratory study effect sizes are regularly larger than field study effect sizes (e.g., Paluck et al., 2021)—Is there evidence that we can find the effect in the field at all, or will it be swamped by competing influences in the field? Finally, a field study can ask with what features of the field does this phenomenon interact and modify the theory accordingly.  

One study that we consider a prototyping study is a field experiment by Yoeli et al. (2013). The authors tested a hypothesis that springs from psychological theory regarding the role of reciprocity in generating group cooperation. Specifically, they tested the predictions of observability, that individuals will sacrifice some of their private resources for the common good because the group is observable to one another over time—they can see one another, and they can see cooperation when it happens in the group. As Yoeli et al. point out, this condition of cooperation for public goods has been tested with theoretical modeling, computer simulations, and with small fictional groups in the laboratory, but “...there has been little evidence of observability’s power to promote large-scale cooperation in real-world settings” (p. 10424). Specifically, when people’s actions can be observed by others, does this boost participation in cooperative efforts that benefit the collective?  

In their field experiment, the research team collaborated with a utility company that was offering a program designed to prevent blackouts during high-demand periods like heat waves by cycling some machines off and on. Those high-demand periods also drive up energy costs and harm the environment. Encouraging people to sign up to voluntarily have their air conditioning and other appliances turned down was the best policy tool available to the company and could additionally save over one hundred billion dollars.  

The researchers pitted their theoretical test of observability against a separate incentive intervention favored by the energy company executives, who believed that people would be most likely to sign up for the program when they were offered a payment of $25. The team sent letters to residents of 15 homeowners associations in California, asking them to sign up for the program. The letters were randomly assigned to offer $25 or nothing for signing up. To test their observability hypothesis, the team randomly assigned the sign-up sheets for the program, which were posted in communal neighborhood mailbox areas, to require a name and unit number to register (observability condition) or to require an anonymous code from the invitation letter (control condition).  

The research team found that residents were three times as likely to participate in the environmental program when they were observable to their community, i.e., asked to sign the sheet with their name and unit number as opposed to anonymously. The observability condition was also nearly seven times more effective than paying residents $25 to sign up (the authors calculated that the price would have had to rise to an infeasible $174 to achieve the equivalent encouragement effect as the observable sign-up sheet). Interestingly, contextual variation in the study revealed more lessons about the power of observability on participation in public goods. The treatment effect was larger in apartment buildings, where people know each other and see each other relatively more compared to row houses and individual homes where residents are more anonymous to one another. The effects were also larger for residents who own their homes vs. rent, presumably because owners are more invested in and thus know more and care more about the community and their standing in the community.  

This study exemplifies several excellent field research methods. One additional treatment was critical to the theoretical progress made. Specifically, the authors randomized whether the program invitation letter specified that the program was not a public good, i.e., it would not benefit the community as a whole. This condition did not lead to behavior change, supporting the authors’ claim that the psychology of observability is about public goods behaviors specifically.  

The study’s theoretical gains are clear. The authors demonstrated that observability is a powerful predictor of cooperation, especially under certain circumstances that enhance observability. These conditions carry lessons about when the theory will be most useful in which contexts. Specifically, variation in a real-world context can shed light on the conditions, perhaps even the mechanisms, of the theory (e.g., comparing communal apartments to isolated individual homes). The theoretical comparison with incentives teaches us about the relative strengths of group psychology vs. individual reward.  

Another paper that exemplifies this type of field study combines two previously separate phenomena from well-understood psychological theory and asks if their combined effect will be meaningful when implemented as part of a real-world campaign (i.e. when implemented “at scale”). Kalla and Broockman (2020) tested “lab-based strategies…to reduce individuals’ resistance to persuasion” (p. 410) within the context of political canvassing in the US. Political canvassing is a much-studied context for encouraging individuals to vote (e.g., Green & Gerber, 2019), but it is not as well-understood as a context for trying to change minds (e.g., about social and political topics like immigration, abortion, or human rights). In this context, canvassing means that representatives from an organization that takes a particular stand on an issue, for example granting citizenship to immigrants who were brought to the U.S. as children, knock on doors to try to talk with and persuade community members of their policy stance.  

Prior canvassing campaigns have used rhetorical argumentation, in which canvassers counter or debate residents’ opposing perspectives. Instead of argumentation, Kalla & Broockman opted for psychological techniques developed in the laboratory that bolster the self-image of the target of persuasion. Specifically, they highlighted a technique they label “high-quality listening”, and another called narrative persuasion. These two techniques, which involve reserving judgment, being curious (listening), and sharing stories instead of arguments (narratives), have been separately tested but never previously combined in the laboratory. Not only have these techniques not been combined in the laboratory, but psychologists don’t know what the combination of narratives and high-quality listening looks like in real-world conversations and particularly in canvassing, which is why this is an “undefined” context for field research.  

The researchers tested whether these psychological processes are effective for changing attitudes among community residents who answer their doors across three field experiments. The suite of studies shows how field experiments can build evidence just like laboratory experiments, by “varying the presence of a particular strategy across multiple treatment conditions in multiple experiments” (p. 411). The three experiments varied the topic of the canvassing efforts (prejudice against immigrants and transgender individuals), the modality of the interaction (canvassing face-to-face vs. by phone), and the source of the narratives about immigration or transgender people (canvasser vs. a third party). The experiments took place across 7 regions in the U.S. and were carried out in collaboration with community-based organizations that hired canvassers to initiate the conversations. 

The method started with mail-based recruitment of registered voters from their seven regions (a total N for the paper of 217,600 voters) for a series of online surveys. Using the list of people who agreed to be surveyed online, the researchers randomly assigned survey respondents to the full intervention (with the non-judgmental listening and exchange of narratives), to an abbreviated intervention (without the narrative exchange), or to a placebo condition (a one-minute conversation unrelated to the topic, which demonstrated they could contact the voter in the household).  

Individuals who were reached by the canvassers were then re-contacted by the online survey 4 days, 30 days, and 3-6 months following the conversation. The survey (ostensibly unrelated to the canvas experience) measured support for inclusionary government policies for and prejudice toward immigrants or transgender people (depending on the topic of the canvassing).  

The results from the set of experiments are impressive. The canvassing conversations that used the non-judgmental exchange of narratives (vs. not using them) reduced prejudice toward unauthorized immigrants and toward transgender people for up to 4.5 months, even among self-identified Republican partisans during a time when the leader of the Republican party, Donald Trump, was expressing hostility toward the groups. The sizes of the effects are modest, but most impressive is their persistence and their emergence from conversations with canvassers who had never conducted these types of conversations before the experiment. The effects were found only when the high-quality listening and exchange of narratives was present, but it emerged face-to-face and over the phone, as well as when canvassers used a recorded narrative. 

Methodologically, the authors offer a template for conducting real-world research at scale, with highly unobtrusive measurement that is disconnected from the intervention (see Broockman, Kalla, & Sekhon, 2017 for a treatment of this methodology). The theoretical progress made by this paper demonstrates how field research can build new theory by combining, and not just translating, theories from the laboratory. The project also shows the importance of a varied field implementation–demonstrating that effects are robust to varied contextual conditions like topic, communication modality, and geography. 

The studies in this quadrant discussed so far primarily ask: Does a well-defined psychological construct matter in a real-world context? Yet other work in this quadrant asks a different question: What are the mechanisms underlying well-defined psychological phenomena? Usually, the lab is best suited for refining our understanding of mechanism. But for some phenomena—especially social phenomena—mechanisms are best studied in in the field. 

For instance, there are limits to how much laboratory studies can tell us about how people perceive and transmit collective norms. Previous research highlights the importance of social referents—the behaviors of salient individuals often shapes people’s perceptions of what is acceptable (e.g., Cialdini, Reno, & Kallgren, 1990; Sherif & Sherif, 1964). But less is known about how social referents affect the transmission of norms through social networks. To examine this mechanism, you have to study a large network of people. You have to study it outside of the lab. 

Paluck and Shepherd (2012) accomplished this by examining how high schoolers perceive and transmit norms of harassment and bullying. This context was not essential to answering the theoretical questions about mechanism, nor was it well-understood for the purposes of answering theoretical questions about the mechanisms of norm development and transmission. Yet given the importance of this context, the study makes both substantial practical and theoretical contributions.  

Using surveys, the authors mapped out the social networks for all students in a school. This included measuring how much time students spent with each other, as well as the nature of their interactions. Of particular interest was the interactions students chose (in contrast to interactions that might arise from institutional channels like sharing a class). By mapping these social networks, the authors identified social referents who were widely known and those who were leaders of smaller cliques. These social referents were then randomly-assigned to either a control group or a treatment group that attended a program to counteract harassment and bullying in the school.  

All students in the school were repeatedly surveyed on a range of measures regarding harassment (perceptions of prescriptive and descriptive norms; personal beliefs and experiences). The authors also collected behavioral measures of harassment, as well as support for an anti-harassment initiative. 

The authors found that social referents in the anti-harassment condition significantly reduced the likelihood that their peers saw harassment as normal or desirable behavior. Moreover, the intervention reduced harassment behavior and increased anti-harassment actions. In addition to the practical importance of these findings, the extensive data collection made it possible to examine the mechanism behind social referents’ influence. The authors found that institutionally facilitated interactions (e.g., sharing a class) have little impact on harassment behaviors. Critically, the main channel through which social referents shape norms is personally-motivated interactions. 

It would have been nearly impossible to use laboratory studies to identify this mechanism underlying a well-known social phenomenon—it required turning to the field. And in addition to this theoretical contribution, there are important practical implications. In fact, a subsequent study (Paluck, Shepherd, & Aronow, 2016) showed how scaling up this intervention (to over 20,000 students) led to a school-wide reduction in student conflict.  

In sum, research that takes a well-defined psychological phenomenon or process into a less well-defined field context can make theoretical progress in several ways. The foregoing examples show that these kinds of studies can calibrate expectations for the scale of the theory’s real-world impact or its impact relative to other psychological phenomena in the world, and they can highlight theoretically defined real-world conditions that magnify or detract from the psychology. In this way, this approach can build theories of context, which are surprisingly rare in a field like social psychology that pays close attention to the immediate context of behavioral and psychological expression. Specifically, tests of well-understood psychological phenomena in new field contexts help characterize the type of situation that is theoretically relevant (e.g., the relevance of living arrangements to social observability). Finally, these study examples show that field research of this type can be a site of new combinations of theoretical insights.  

INTERPRETING: UNDEFINED PSYCHOLOGY, DEFINED CONTEXT 

The Interpreting quadrant describes the opposite asymmetry taken up in the Prototyping quadrant: a category of studies in which the research takes place in a well-defined context but tests a relatively undefined psychology. Here, researchers aim to develop theory about the psychology of a particular type of context. The context might include a place that features a certain pattern of behavior or psychological phenomena. The researcher seeks to build theory by exploring the site of these patterns in their natural context, and to characterize those patterns according to psychological theories that exist, or by inventing a new theory, or by expanding existing theories so that they can help describe and predict in that context. The researcher recognizes: here is a well-defined social problem, or an established behavioral pattern–what psychology is at play?  

Heller, Shah, Guryan, Mullainathan, and Pollack (2017) took up this kind of challenge by studying the Becoming a Man (BAM) anti-violence program for underserved adolescent boys living in Chicago. In this setting, they observed longstanding and stable rates of high school dropout and violence among adolescent boys. They also observed a program, BAM, that was reputed to reduce dropout and violence. The program featured facilitators who worked with the boys in groups and led them through many experiential and group talk exercises that helped them to revisit or consider for the first time the thoughts and behaviors that can lead to violence in their everyday situations.  

Their study evaluated the impact of BAM because it was thought to be successful, and because it addressed many of the psychological constructs of interest associated with violent behavior in adolescents. Thus, the job of the researchers was not just to evaluate “Does this intervention change behavior or not?”, but also to open the hood of the program’s engine and understand what psychological theory could tell us about why it worked.  Many psychologists conduct research this way—looking for promising interventions in the world that seem to have a compelling sway over the participants and recognizing good psychological ideas in the intervention. They study the interventions to deepen understanding of those psychological processes. In this case—what theories provide insight into why young people might act violently or disengage from school? The best way to do it would be to study an attempt to change this behavior.  

First, the researchers worked to measure the causal impact of the program. Heller et al. randomized participation in the program across three different contexts: twice in disadvantaged neighborhood public high schools in Chicago, and a third time in a juvenile temporary detention center not far from those schools. Each of these studies lasted one to two years, in which boys were randomly assigned to be in the program (or not). The researchers collected behavioral data to measure outcomes including arrests, violent crime arrests, and readmission rates to the detention center. Strikingly, these measures show that following program participation, arrests of the participants were reduced by 28%-35%, violent-crime arrests by 45%-50%, readmission rates at the juvenile temporary detention center by 21%, and high school graduation rates increased for participants. The importance of these outcomes, combined with the relatively low cost of the interventions, means that these programs are cost-effective, saving $5 to $30 for every $1 spent. This is why the study is categorized as a well-defined context: the experiment evaluating its impact generates many observations about the behavior in that context. Moreover, it comes on the heels of a great deal of qualitative observation by the program designers, observations that were of great use to the social scientists. 

The deep theoretical progress made by this project comes from sorting through the psychological explanations for why the program worked. At the outset, the psychology of the study was less-defined. There are many theories about the channels through which young people could become more successful at school and less violent, including grit, conscientiousness, adult support and role modeling, and self-control. The researchers eliminated some of these candidates for explanation by collecting additional data—for example, using a survey of all students in the public school system (including students who participated in the program). However, survey measures of various explanations for the program’s success, like grit and the presence of role models showed no difference between boys who participated and those who did not.  

In the case of this work, the researchers arrived at the critical mechanism of the program’s success through a qualitative analysis of the program’s curriculum and interviews with the program facilitators. They noted that those exercises and the program facilitators “recognize that these youth live in distressed neighborhoods where being aggressive or even fighting may, unfortunately, sometimes be necessary to avoid developing a reputation as someone who is an easy victim” (p. 5). In essence, the program recognized that boys needed to develop certain aggressive reflexes, which are adaptive for their neighborhoods but highly maladaptive in a school setting or an interaction with police. The psychology of automaticity became the researchers’ candidate for understanding how the program worked. They hypothesized that BAM programs “...improve youth outcomes in substantial part because they help youth slow down in high-stakes settings, examine their automatic assumptions about what situation they are in, and ask whether the situation could be construed differently. That is, the programs help youth have a greater sense of occasion” (p. 6). 

The researchers found evidence for this hypothesis using laboratory experiments (featuring behavioral games like a modified dictator game) fielded in the high schools where the program takes place. Qualitative evidence from discussions with the intervention providers highlighted how automaticity might also explain another phenomenon: Some youth are too passive in the context of their neighborhood because they overgeneralize an automatic response of not fighting back. In these cases, slowing down and recognizing their automatic response may help them see when a more assertive response is warranted. In this way, reducing automaticity helps youth become better calibrated to their situation.  

The paper also expanded on how psychologists had been theorizing about automaticity. Rarely, if ever, was automaticity used to theorize about notions of “code-switching” from one context to the other. Before this work, “thinking fast and slow” did not describe a suite of theories that were regularly applied to behavioral problems like violence or delinquency, or theories about situational code-switching. 

Field research is often more likely to include non-WEIRD (non-Western, Educated, Industrialized, Rich, Democratic) populations, and the skills needed for studying populations from other societies or from the researchers’ society who do not share the researchers’ geography, race, or class, etc. (see also Giner-Sorolla, 2025; Harris, 2025). In this study, the researchers prioritized listening to the facilitators, whose job is to listen to the participating boys. It is not surprising that in attending to experts on the community and to locally grown solutions like the BAM program, researchers arrive at newer and often less “abnormal” explanations for negative behaviors. The authors’ characterization of the boys’ violence and school dropout is not that those behaviors are caused by an extreme or wrongheaded reason. They characterized the behaviors as part of the boys’ canny adaptation to their violent and stressful environment. This highlights an important strategy that many field researchers use, which is to stay close to the field, use qualitative evidence, and talk to the experts in the context.  

Work such as this also highlights a further difference in orientation between field research and lab research. In some traditions, lab paradigms are designed with a “correct” response in mind and psychological theories are developed to explain “biases” or “errors” in participants’ responses. The errors are not always essential to the theory, but they can become part of a narrative about how people are predictably irrational, pursue maladaptive strategies, or are “strangers to themselves.” The complexities of the field make it more difficult to know what the “correct” response is. Theories that emerge from the field might therefore place more emphasis on explaining behavior in the context, without an emphasis on whether the behavior is a bias or error. 

As another example, Fast and Olson (2018) used field research to explore a context with a frequently observed behavioral pattern: child development in the United States, and specifically the emerging pattern of gender transitions among younger children (3-5 years old). The authors reported that although it is still rare, it is increasingly common for parents to allow their children to live as the gender they feel themselves to be (one that does not accord with their natal sex) by using pronouns connected to that gender but no other medical or hormonal intervention.  

What is the psychology at play for preschool children who socially transition? Here, the researchers have found a behavioral pattern that demands psychological explanation. Fast and Olson asked whether transgender children, defined as “those who express a gender identity that is ‘opposite’ their natal sex,” differ from “gender-typical” peers on basic gender development milestones. Developing conceptions and practices of gender is central to child development since gender is a) the primary mode of social categorization for both children and adults and b) the earliest personal identity. Thus, developmental theory needs to account for how this new context of transgender childhoods might modify our understanding of the emergence of gender knowledge, beliefs, and behaviors.  

For example, a previous theory by Kohlberg (1966) argued that a conceptualization of gender as constant or stable allows for greater organization and motivation of strong same-gender preferences and behaviors that we observe in children. For children who may not think of gender as constant or stable (because they have “changed” genders over the course of their short lives), showing that they are comparable in terms of their gendered preferences and behaviors would trouble this theory and change our understanding of “normal” gender development. In other words, the achievement of gender constancy might not play “…a causal role, so much as it is a developmentally cooccurring phenomenon” (Fast & Olson, 2018, p. 623)  

Because transgender children in preschool are relatively rare, the research team traveled extensively to recruit their sample of three to five-year-old children who were: transgender and gender nonconforming, siblings of transgender and gender nonconforming children, and cisgender children from the same communities matched to the transgender and gender nonconforming children along various sociodemographic dimensions. “Over the course of 9 months (March 2015 to November 2015), the researchers flew and drove throughout the United States to meet with families from 17 U.S. states…at a series of conferences and camps for gender diverse children, at support group meetings for families with transgender children, at our research laboratory (for area families), or at families’ own homes to recruit this sample of transgender children and siblings” (Fast & Olson, 2018, p. 624). Once recruited, the researchers asked the children to complete a series of tasks to measure (a) gender constancy understanding, (b) gender preferences, (c) gendered behavior (stereotypicality of the child’s current outfit), (d) explicit gender identity, (e) perceived similarity to boys and girls, and (f) gender stereotyping. 

The findings of this research did alter fundamental theories of childhood gender development. The gender preferences, beliefs, behavior, and expressed identity of socially transitioned children did not differ from their siblings or matched cisgender peers in their communities. The only way in which transgender and gender nonconforming children stood apart from the controls was in their perceptions of gender constancy—they were more likely to believe (from their own experience) that gender can change over time.  

This finding flies in the face of the foundational contention by Kohlberg (1966) that a belief in gender constancy is necessary for other gendered development in terms of beliefs, preferences, and behavior. These data suggest that the development of perceptions of gender constancy co-occurs with these other changes but are not necessary for subsequent gender development. The authors suggested that the field should “…consider an amendment to this cognitive theory of gender development, such that children’s sense of gender stability from the current moment into the future (with the removed assumption that gender is necessarily consistent with a child’s sex at birth) is what motivates or contributes to especially strong gendered preferences and behavior, rather than the belief that past gender must be stable” (Fast & Olson, 2018, p. 633). 

Paluck (2009) offers another example of research in this quadrant that can simultaneously challenge core theoretical notions and have practical importance. This work examined the effect of a radio intervention on prejudice reduction and conflict resolution in Rwanda. In many ways, the context was well-defined. There was a rich understanding of the role that mass media played in the Rwandan genocide and ethnic violence. However, the psychology was less well-defined. Despite prior research on how media campaigns could reduce prejudice, there was little theoretical consensus. Some theories argued that such campaigns need to focus on changing personal beliefs. Others asserted that media campaigns should shift perceptions of social norms. Still others pointed towards the importance of developing empathy or fostering group discussions. Critically, most of these theories were studied separately (and rarely outside of the lab). Paluck considered the role that all these factors play in reducing prejudice in the field. 

The study randomly assigned communities to either listen to a radio soap opera focused on reconciliation (treatment) or a soap opera about health (control). The reconciliation soap opera portrayed tensions between two ethnic groups (and community members who band together despite the ethnic tensions), paralleling the conflict between Tutsis and Hutus. Paluck (2009) evaluated the program on a few dimensions. First, surveys and focus groups measured (a) personal beliefs about mass violence and trauma and (b) perceptions of descriptive and prescriptive norms regarding intergroup conflict, community trust, and disagreement. Moreover, community members were asked to engage in group deliberations while solving a problem. This provided an opportunity for (c) behavioral observations of the number of different perspectives that were debated and the number of positive comments made about group cooperation. 

Indeed, the intervention increased the number of perspectives shared and the positive sentiment regarding group cooperation. Yet, these positive behavioral effects were not the result of changes in personal beliefs. Rather, the intervention shifted perceptions of community norms. These findings have a striking implication for both theory and practice: prejudice reduction might depend less on changing personal beliefs and more on changing perceptions of norms.  

The extensive qualitative work conducted as part of this project also hints at an important element of the process for reducing prejudice through media campaigns. Qualitative and survey measures suggested that the emotional reactions prompted by the soap opera might have been essential for having listeners connect the program’s messages to their lives. And the fact that community members listened in groups (rather than as individuals) may have fostered discussions that further supported drawing these connections. Though not the central focus of the study, these insights enrich our understanding of how to best deliver a prejudice reduction intervention. 

Research that explores a less well-known psychology in a well-defined context is perhaps the type of field research where it is easiest to appreciate the theoretical gains, which we characterize as “interpretation.” Here, the field is used as a place of exploration and theory development because the researchers have found a behavioral problem that demands psychological explanation. Many psychological ideas might apply, or it’s not immediately apparent which ideas apply. What might be less immediately appreciated is that this type of field research also contributes to theories of context and situation. For example, from Heller et al. (2017) we are left with a greater appreciation for situations in which violence may be more likely to occur because they promote fast thinking or because the situation is not well-distinguished between school and home (street). Or as in the case of Fast and Olson (2018), we may observe aspects of the familial or community context that support healthy nonconforming gender development—e.g., parents supporting the gender identity of their children. And in Paluck (2009), we see that phenomena that are often treated as peripheral to the intervention (e.g., the emotional reactions it causes) can actually be essential elements of its delivery. Thus, while psychologists are often trained to control for or remove these peripheral elements in the lab, in turning to the field, we must recognize when the noisiness of the world is an essential ingredient in the process of psychological change.  

REFINING: DEFINED PSYCHOLOGY, DEFINED CONTEXT 

The Refining quadrant describes a type of field research that investigates a hypothesized match between a relatively well-known psychology and a relatively well-defined context. Here, the researcher has a fuller theory of the psychological construct and wants to make progress by investigating whether the psychology functions as one would predict in a particular context where the behavioral or psychological problem is well-described. This is why the psychology and the context are in expectation a “match” for one another. The researcher can refine the theory by going beyond “Is this true that the psychology and the context match” to asking, “Does the phenomenon decay over time”, “For whom is this phenomenon not true”, and the like. 

A series of field experiments kicked off by the collaboration of Gerber, Green, and Latimer (2008) with elections campaign consultant Mark Grebner exemplifies this type of field research. The social scientists who published the paper have over many years developed theory about the context of political campaigns that attempt to get out the vote (Green & Gerber, 2019). Grebner, a campaign consultant, noticed that community members targeted by his campaigns believed in voting as a shared American value, and knew the dates of elections, but in post-election surveys often lied that they had voted when they had in fact neglected to vote (which is of course indicated by public record). In Grebner’s words, voting was a “private act, rather than a public one, and it was safe to routinely misreport voting not only to researchers but to friends and family” (Green & Gerber, 2023).  

Grebner’s observations inspired him to create social pressure campaigns that encouraged voters to live up to their shared values of voting. This idea parallels a well-defined psychology of social norms stretching back to Cialdini and further back to Milgram and Asch. This theory predicts that social pressure will motivate behavior when a person is made aware that they are violating a norm, and that others are aware of their violation. As hypothesized by Gerber, Green, and Larimer: “Social pressure is thought to be amplified if a person’s compliance with social norms is disclosed to others.” (2008, p. 165). But would it work to raise the vote? Their first field experiment exploring this hypothesis returned a resounding yes. But in that study and in the replications that followed, their field research would also uncover quite a bit more about the psychology of social pressure and the context of voting as well.  

In this foundational social pressure field experiment (Gerber, Green, & Larimer, 2008), the researchers randomly assigned four different “mailers,” or postcards to be delivered to registered voters in a Michigan primary election (a kind of election that is typically low salience to voters). All mailers pressured voters to vote, but only one used social pressure. The first mailer asked voters to “do your civic duty”, a second added that the recipient was being watched as part of an academic study, and the third “self” mailer included information about whether each person in the house had voted in the previous elections and indicated that the sender would follow up about whether they voted in the present election. The fourth “social pressure” mailer added information about the recipient’s neighbors’ voting record and a message that it would follow up about the person’s turnout as well as their neighbors’ turnout. The dependent measure of the study was behavior: voting in the election. In total, 80,000 households were randomized into one of these four conditions or into a no-contact control group.   

The social pressure mailer increased the probability of voting in the election by more than 8 percentage points. This was a major discovery that attracted the attention of campaigns and academics alike, as a practical and a theoretical matter. In the context of politics, this was an Asch and Milgram-sized effect. Note that typically mailers do not raise voter turnout, and their effects were previously capped at 1 percentage point. Even the “self” mailer that reminded voters of their own record, and that it was public, had a large effect—between 4 and 5 percentage points.  

In the many replications of this field experiment that followed, much was learned about voting, norms and social pressure, and their interaction. For one, voters do not like the social pressure mailer. Green and Gerber describe it as “lightning in a bottle”:   

… we would warn readers against using this tactic. Social pressure mail is like lightning in a bottle, an interesting but dangerous curio. It is interesting because it reminds us that mail is indeed capable of producing big [get out the vote] effects and that, in some cases, the message does matter. But it is dangerous because many people who receive this mail become irritated at the prospect of a campaign snooping on them and scolding them in front of their neighbors. Survey research shows that the public takes a dim view of social pressure mail, and one campaign found that roughly one in every 200 recipients lodges a complaint by e-mail or phone.  If you send out thousands of mailers, you will quickly be inundated with complaints, not to mention calls from journalists eager to investigate accusations of voter intimidation (Green & Gerber, 2023, p. 76).  

This hard-won observation shows another way this kind of field research can refine your theory. It can teach you about the preferences and dynamics in the context that may push back against the psychology, even when it is effective at changing the behavior. 

Replications of the original experiment have subsequently found that “softer” versions of the pressure mailer, leaving out the explicit comparisons with neighbors, do not provoke the same outrage. Across many follow-up studies, they increase turnout by an average of 16%. However, they don’t work as strongly in high-salience elections, and interestingly they are more variably effective when campaigns use phone or text to send them out. They seem to not have an effect when coupled with partisan appeals (e.g., “It is important for Democrats to vote!”) 

Some of these softer variations have also led to discoveries. One scholar's idea was to subtly make people aware that their voting record was public, through gratitude: “We realize voting takes time and effort, and we just wanted to say, “thank you.” …We appreciate the fact that you made it a priority to cast a ballot in the last midterm election in November 2006” (Panagopuolos, 2013). The mailer increased turnout that was approximately two-thirds as large as the original “self” social pressure mailer—still a success. However, it turned out in later experiments that when placebo mailers used only gratitude and no mention of the public record, these mailers were also effective at raising turnout. An additional finding about voters–not a carrot or a stick, but rather honey–a kind thank you–was also appreciated and behaviorally motivating.  

Green and Gerber (2023) predict that effects like these likely decay somewhat over time (“if everyone starts thanking voters, recipients will quickly become inured to these expressions of gratitude” p. 173). However, social pressure mailers continue to be used in places like Michigan, and there does not appear to be a declining return. 

A field experiment testing a different kind of social norm influence over behavior did examine the rate of decay over time. Allcott and Rogers (2014) sought to use the well-understood psychology of social norm information for changing behavior pioneered by Bob Cialdini—social psychology’s distinguished “full cycle” psychologist. Cialdini uncovered principles of normative informational influence by running field studies in which he and colleagues provided information about the behavior of relevant others to set a norm where none previously existed. For example, in a hotel room when a placard in the bathroom encourages guests to re-use their towels, guests’ towel re-usage is higher if the placard doesn’t simply encourage but informs them that previous guests in the room have re-used the towels. A previously invisible norm is made clear, and individuals are persuaded to reuse the towels.  

Allcott and Rogers’ high-powered field experiments took this social norm insight into another context of energy savings: people’s home electricity use. The researchers worked with a company, OPower, that was carefully tracking home energy use for hundreds of thousands of customers, which makes this a more defined context of study. Allcott and Rogers report that 234,000 individuals in the Midwest and Western regions of the US were randomized to receive a comparison of their energy usage to their efficient neighbors. Like Cialdini, they found that the normative information significantly reduces energy usage.  

Because the researchers studied repeated messaging, they were able to detect something rare in psychological research—a decay of effects. The households continued to respond to reports even after two years, and if reports were discontinued, households continued to use less energy, but this effect decayed at a rate of 10-20% per year.  

Over time, research in this quadrant arguably follows a more systematic path than in other quadrants. Because both the context and psychology are well-defined, the outstanding questions in an area might be clearer, and subsequent research builds more directly on prior work, thus refining the underlying theory. Often, this approach plays out over several papers.  

More recently, “megastudies” simultaneously compare many well-defined psychologies in contexts where they are expected to matter, using the same population and evaluating outcomes using the same measures for the same duration of time. A good example is Milkman et al. (2021), a study that tested different interventions for increasing physical exercise among members of a chain fitness center. All 54 separate treatments were delivered to a total of 61,293 gym patrons digitally (by phone) over the course of four weeks. Each patron received a unique treatment or a placebo condition (receiving points on Amazon.com for enrolling in the study). The treatments were designed by 30 scientists from 15 universities, all of whom focused on theories of interest to them that they predicted would meaningfully increase patrons’ exercising frequency at the gym.  

The psychological phenomena tested across the megastudy have been well-defined in laboratory studies and even in other field contexts. And the context of gym attendance has also been the subject of considerable research. The robust foundation for both the theoretical and contextual aspects of this work makes it possible to simultaneously compare interventions that could reasonably be expected to have a practical impact. 

Of the 54 separate treatments, nearly half (45%) increased gym visits significantly, ranging from a 9 to 27% increase. However, only 8% of the total interventions had an effect that was significant after four weeks. The top-performing interventions shared a common theme of higher incentives or of social norms that portrayed exercise in the US as common and growing in popularity. All 24 treatments that increased exercise in comparison to the placebo included some element of planning, reminders, and social or monetary incentives to exercise.   

In addition to helping calibrate theories of behavior change to one another in a particular context, megastudy field research encourages meta-theorizing about what we know about our theories vs. what we think we know. An important part of this study’s methodology was that before revealing any results of the study, researchers asked outside judges (expert academics and practitioners as well as laypeople) to forecast which interventions would be most effective. The most striking finding of this exercise was not that the judges failed to predict which theoretically driven interventions would be most successful. It was that every prediction about the size of each intervention’s impact was substantially larger than its actual impact on exercise behavior. Thus, these mega-field studies help calibrate expectations for how laboratory-grown theories might function in the world.  

Note that the field research in the Refining quadrant is one where studies can make progress on theories of both psychology and context, not just “solve” a contextual problem with theory. The studies described in this category address a behavior change challenge to learn more about theory. But other qualifying studies might fail to do so and still teach us something about psychology, the context, or both. For example, going back to the context of voting, one campaign field experiment tested the “door in the face” hypothesis—the classic hypothesis that an initial large request will make people more likely to accept the terms of a smaller request that immediately follows. McCabe and Michelson (2015) tried this strategy in the context of getting out the vote, by calling voters and first asking them to volunteer for an 8-hour shift as a get-out-the-vote person on Election Day. Short of that (only 1 person out of 543 total agreed to the shift), they asked, would you vote? This appeal did not work compared to simply asking people to vote. They surmise that requests that are too large are construed as illegitimate and that turning down these requests does not leave people feeling obligated to accept a smaller request (Schwarzwald, Raz & Zvibel, 1979).  

SCOUTING: UNDEFINED PSYCHOLOGY AND UNDEFINED CONTEXT 

The Scouting quadrant starts its psychological theory development in the field rather than in the lab and moves across field settings rather than back and forth between the lab and the field. The context is not well-defined, and so the psychology is thought to be possible in the contexts where it is tested. The researcher seeks to develop a psychological theory in the field, and not in just one field context but a few, to be sure it is not a psychology particular to one place. For this reason, we think of this quadrant as a scouting exercise, when researchers seek to develop theory in a few different field contexts. The exercise is one of pure theory development, while investigating its breadth.  

One study that exemplifies the approach of developing theory in two different field sites is Mani et al. (2013). The research team derived their research question from the consistent correlation between poverty and “counterproductive behavior.” This correlation can be found in many countries around the world (they cite data from North America, Europe, and from global meta-analyses), and includes behaviors like not engaging in preventative health care, not taking prescribed medicine as instructed, showing up to appointments late or not at all, not being as productive on the job, and parenting children with less attention. While there is much known about the lives of people living in poverty, much less is known about which aspects of those people’s mental lives can explain these behaviors, or which contexts would be most useful for that investigation. That is why this study could be considered as starting from an undefined psychology and a relatively undefined context. The research team sought to define a psychological theory that focuses on poverty’s effects on mental processes and to test it across two different contexts. 

Their hypothesis is not unique to contexts of poverty—it is specific to the mental processes required when the human cognitive system is under strain. “Because our hypothesis is about how monetary concerns tax the cognitive system, we define poverty broadly as the gap between one’s needs and the resources available to fulfill them. Because this is based on subjective needs, it encompasses low-income individuals both in the developing and the developed world as well as those experiencing sharp transitory income shocks” (Mani et al., 2013, p. 976). Specifically, the team proposed that poverty impedes cognitive function, likely through attentional capture in which poverty “captures attention, triggers intrusive thoughts, and reduces cognitive resources” (p. 980), which can account for the behavioral choices that otherwise look like preferences, traits, or pure products of the environment.  

To test these ideas, they went to two different field sites: a New Jersey shopping mall, and a sugarcane-growing farm region in India. The New Jersey site is a place to recruit non-students from a variety of income brackets—the data collection is closer to a laboratory study on the continuum from controlled to naturalistic methods. They presented participants recruited at the mall with hypothetical financial scenarios in which they are surprised with a bill, and they are randomly assigned to view a hard or an easy bill to pay (e.g., a car mechanic bill is $1500 vs. $150). While thinking about how they might solve the problem, participants take cognitive tasks: e.g., Raven’s Progressive Matrices and a spatial compatibility task. In line with the team’s predictions, relatively richer and poorer participants performed similarly on the cognitive tasks in the financially easy condition ($150), but participants who were relatively poorer performed significantly worse than the richer when the higher bill was weighing on their mind ($1500). 

The team then moved their data collection to Tamil Nadu, India, with 464 farmers who earn at least 60% of their income from harvesting sugarcane. The farmers completed the same cognitive tasks before and after their harvest. Because sugarcane farmers receive their income annually, at harvest time, this means that those two measurements were taken at very different points in their cycle of poverty—poor before harvest and rich after. Now in a within-subjects analysis, the team found that the farmers show more diminished cognitive performance when relatively poor, just before their harvest, than when they are rich just after selling their crop. Overall, the size of these cognitive effects of financial worries is comparable to losing 13 IQ points, or operating without any sleep for one night.  

This study was able to explore and test a hypothesized psychological process that was not thought to be defined by a context or a particular population. If the authors had anchored their theoretical tests to one context, the ultimate theoretical lesson might resemble some other contextual accounts of poverty, for example about how the financial system in the US is predatory for low-income individuals, or how the social and economic system overall leaves very little “slack” or room for mistakes among people with low resources (e.g., Barr, 2012). Instead, this kind of field study roams from context to context, attempting to find a common psychological process connecting the people in these different places, who share similar pressures on their mental processes.  

Wu and Paluck (2020) sought a similar kind of theoretical development, by fielding the same experimental intervention in two very different real-world workplaces, one in China and the other in the U.S. The question they sought to test was a longstanding theoretical concern of social and political philosophers—Are attitudes toward authority shaped over time by contexts like the workplace? Can those attitudes be changed by social and workplace experiences, but over the shorter term?  

Wu and Paluck specifically wondered if reshaping some workplace interactions could reshape generalized attitudes toward authority–not just toward a workplace boss but more generally toward authority in the family and politics. Work by one of the founders of social psychology, Kurt Lewin (1947), proposed the idea that these kinds of attitudes toward authority might change if working groups can become their own “cultural islands” away from the mainstream political culture. However, he did not rigorously test the possibility of the creation of a cultural island, although he watched and described the evolution of participatory groups in factories.  

The authors pick up where Lewin left off, in a factory setting in China. They note previous work on this question has focused on workplaces in the United States and Europe, which are far less authoritarian and hierarchical than China. China is thus “...a particularly interesting site for testing the hypothesis that groups can become “cultural islands” when the broader environment does not support the group practices. However, the question is not particularly Chinese or American–it is a broader question about political cultural socialization and development that is thought to happen across many contexts.  

Thus, Wu and Paluck put together relatively less well-defined questions about the psychology of groups and attitudes toward authorities with questions about the context of this attitudinal development and change. Their experiments randomly assigned work groups one time per week for six weeks to a 20-minute participatory meeting during which the supervisor was silent and workers led a discussion of their problems, ideas, and goals regarding their work (vs. a status quo weekly meeting). In China, the intervention took place in a textile factory, and in the US, it took place in a university’s departmental staff meetings.  

The authors found that treatment workers in China reported less deference to generalized authority and lower belief in the just nature of the world, compared with workers who were not empowered to lead their work meetings. The size of these shifts is roughly one standard deviation on the survey measurement scale, and they were observed one month (2 weeks, in Study 2) after participatory meetings had ended. The size is more impressive considering that the attitudes are generalized attitudes toward authority and justice and that they were affected by relatively brief if immersive experiences with a more egalitarian local power structure.  

The authors observed similar findings in a conceptual replication of the field experiment in the US, where workplace and societal contexts are much less hierarchical and authoritarian. In both studies, one of the most plausible mechanisms of change seems to be the regular opportunity to voice one’s opinion in a group. Thus, even if workers start from very different levels of average opportunities for empowerment, it seems that the experience of speaking up in a group can drive the attitudinal change toward authority and justice. Across both studies, support workers who were lower-positioned in the organizational hierarchy were given a regular opportunity to voice their opinions, which was the common factor between these two drastically different settings.  

Thus, field research that seeks to develop theory across different field contexts has the ambition of building theories that start their life with claims to more universalistic (or at least, cross-cultural) processes.  

Moreover, for work that falls in the Scouting quadrant, field research can be an essential first step. In some cases, this is because it is nearly impossible to simulate the real-world context in the lab. For example, Wu and Paluck’s (2020) investigations of workplace culture necessitate situating their studies among groups of people in organizations. Even the cleverest experimentalist would find it difficult to recreate the most important aspects of a workplace. Part of the challenge is that we do not know which features of the context are the most important to simulate in the lab. In laboratory studies, we often try to create psychological realism, or the experience of psychological processes from everyday life (Aronson, Wilson, & Ackert, 1994). But, before we can create realism in the lab, we need a better understanding of the psychology in the context. Sometimes intuitions about the psychology and observations about the world are sufficient to create this realism. In other cases, more rigorous field research is necessary. For example, without Mani et al.’s (2013) studies with sugarcane farmers in India, it would have been difficult to understand the link between poverty, resource scarcity, and cognitive bandwidth. However, once that link was clear, it became possible to simulate the psychology and context in laboratory studies for further theoretical development (e.g., Shah et al., 2015).  That is, field research necessarily has the psychological realism that facilitates theory development—realism that we either cannot recreate in the lab or do not yet know how to recreate until we conduct field research. 

SITUATING: FIELD RESEARCH THAT INVESTIGATES AN UNDEFINED INTERACTION OF PSYCHOLOGY AND CONTEXT 

The Situating quadrant of field research investigates the unknown interaction of a particular psychology and a particular context. This research can foster theoretical development in at least two ways. First, some research might have highly particular goals—to generate insights specific to the psychology and context, but which do not necessarily generalize (e.g., a psychological “affordance”, Steele & Sherman, 1999). Second, some research may use a particular psychology and context to develop methods or ways of approaching questions that demonstrate a new, generalizable way of doing science. The latter type of research may or may not care about the answers of the study itself but aim to make a meta-scientific contribution.  We describe two recent studies that do just this: one that cares both about the answer to the study’s hypothesis and about generalizing the methods of the study, and the other that uses the process of the study to demonstrate a new method for doing social science.  

Both studies feature “big data” and computational analysis of high-dimensional data containing millions of data points involving text or imagery. This is no accident since a great deal of methodological and meta-scientific progress is currently being made within studies using algorithmic and computational methods (see Kosinski, 2025). Social psychologists are at present immersed in the project of how best to use high-dimensional data captured from field settings: “...data on human behavior is exploding: second-by-second price and volume data in asset markets, high-frequency cellphone data on location and usage, CCTV camera and bodycam footage, news stories, the entire text of corporate filings and so on. The kind of information researchers once relied on for inspiration is now machine readable: what was once solely mental data is increasingly becoming actual data” (Ludwig & Mullainathan, 2022, p. 1). These methodological innovations may make it more feasible to develop theory about the interactions of psychology and context because to develop such theories, researchers may need large data sets of observations pairing that psychology and context over time (which may not have been available or analyzable before).  

Our first example of such a study is Voigt et al. (2017). This study asks:  Do police show different levels of respect to Black and White community members?  Here, many previous studies reveal that Black community members report being treated with less respect than they would want or expect. Police officers’ lack of respect toward Black people is anticipated, and in this context explicitly. However, it has not been well-documented by previous social science, which has relied on recollections or observations where the researcher changes the scene by their very presence.  “Despite the formative role officer respect plays in establishing or eroding police legitimacy, it has been impossible to measure how police officers communicate with the public, let alone gauge racial disparities in officer respect” (Voigt et al., 2017, p. 6524).  

The research team examined data collected by body cameras during routine traffic stops— “common, everyday interactions between the police and the communities they serve,” which account for more than 25% of the times in which the public encounters police. The footage, from which they analyzed audio, comes from 245 different Oakland Police Department officers, resulting in 183 hours of footage transcribed into text. 

First, the authors asked human raters to read a randomly selected sample of police language directed toward community members. Police officers’ language was judged to be similarly formal when directed toward Black and White drivers. However, officers’ language was significantly less respectful when directed toward Black drivers.  To test whether these patterns emerged across a large swath of police interactions, the authors then built a computational model of respect and formality, based on the human rater data. After testing its reliability, the team applied it to the entire dataset of “utterances” from police officers (N = 36,738). The model confirmed that the disparities in respectfulness are present across these utterances: White community members are 57% more likely to hear an officer say one of the most respectful utterances, whereas Black community members were 61% more likely to hear an officer say one of the least respectful utterances in the dataset. 

The paper does not develop a generalizable theory of respect, nor does it offer a broad theory on police discrimination. But it does show how police officers communicate respect through language, and how there are disparities in officers’ use respectful language. Work at this interaction of psychology and context offers important policy lessons, highlighting opportunities for training police to use more standardized language in encounters with the community, and for pointing out the current “respect gap” as a driver of police de-legitimization in the community. Moreover, beyond this context, the paper makes a point about the use of big data in this field. “Computational, large-scale analyses of language give us a way to examine and improve police-community interaction that we have never had before” (p. 6525). The authors note that linguistic computational methods are powerful enough to scale to a very large number of interactions while also remaining sensitive enough to draw out the interpersonal subtleties that make a difference to the success of interactions, socially and psychologically.  

A second example of a study aimed at the intersection of a particular psychology and context is Ludwig and Mullainathan (2022), who investigated bail decisions made by judges—decisions about whether to release those accused of a crime from jail before their trial. Whom do the judges detain and whom do they release, and what can we divine about how they make their decision, from observing a dataset of their decisions over time? The authors added to this dataset the mugshots of the accused, which the judges view as part of their decision process. A great deal of psychology predicts that the judges will be biased by the mugshots (Todorov & Oh, 2021)—but in what ways?  

The authors built a deep learning model that uses the millions of high-dimensional data from the mugshots and marries it with the judges’ decisions, to predict what features of the mugshots can predict whether the accused were sent back to jail or not. In a fascinating twist, the algorithm successfully predicts judges’ decisions better than humans do when they view a sample of mugshots—but the algorithm does not identify a factor that is recognizable from the psychological theoretical literature on bias from faces. That is, the algorithm predicts judges’ decisions over and above factors like race, gender, and skin tone. It is time for hypothesis generation: What is the judge’s decision process, and what is the algorithm’s? Psychologists are used to prying open the “black box” of the human mind, but much less used to prying open the black box of an algorithm. What is it using to accurately predict judge decisions and how can we figure it out in a principled way? 

The authors built a communication procedure between humans and the algorithm so that people can better see the patterns that the algorithm sees. Specifically, they built a model so that the algorithm produced a composite (morphed) face that exemplified a mugshot with a high and a mugshot with a low probability of prediction of a judge deciding for bail. Human judges were shown many of these faces, to see whether they could spot thematic differences between faces with a high vs. low probability of predicted bail. And indeed, humans were able to do this. Human participants comparing pictures side by side named two features that the algorithm detected: well-groomed faces and heavy-faced faces (wider, puffier, rounder faces). Well-groomed and heavy-faced faces are more likely to be released, even controlling for demographic features and known facial features from psychology. Those who were in the top quartile of well-groomedness and heavy-facedness were a quarter to almost a third percent more likely to be released over the base rate, which is a larger difference than the rate comparing those arrested for violent vs. non-violent crimes.  Participants using this procedure seemed to be able to guess the algorithm’s predictions. They saw facial features that explain the algorithm’s (correct) predictions.  

For a researcher interested in the specific interaction between the psychology of facial features and judges’ bail decisions, this paper offers some theoretical insight. But of course, that is not the actual point of this paper or its main contribution. The authors note, “…our results are specific, our approach is general. … Our framework provides a way to produce novel interpretable hypotheses from high-dimensional data such as these, a way to marry the predictive power of machine learning with human intuition.” What the authors accomplish here is a more formalized method for hypothesis generation. Rather than relying on human intuition to make sense of high-dimensional patterns, humans can collaborate with algorithms to see whether predictions made by these deep learning models are sensible, recognizable by humans, and capable of being captured by language and not just deep learning models. “Ultimately…this is not a paper about well-groomed or heavy-faced defendants, nor are its implications limited to faces or judges. It is about a procedure that can be applied wherever there is rich data with which to predict behavior” (Ludwig & Mullainathan, 2022, p. 6). And so, while Voigt et al. (2017) make a substantive and methodological contribution, Ludwig & Mullainathan (2022) demonstrate how research on the interaction of psychology and context can make meta-scientific contributions.  

GENERAL DISCUSSION 

Social psychology’s radical habit of simulating the world in the laboratory is essential for developing theory. The discipline’s unique focus on understanding how the mind interfaces with the world sometimes demands a lab experiment’s abstraction and precision. Yet to develop social psychological theory more fully, the world cannot just be the inspiration for experiments, it must also be the site of them.  

Naturally, stepping outside of a habit (or developing a new one) can be disorienting. Our hope is that this chapter makes it easier to start navigating the kinds of theoretical questions one might ask and answer using field research. The typology and examples presented here are just a few templates of what such work can look like. But this is not meant to be exhaustive or rigid. It is a starting point to inspire researchers to use the field (perhaps alongside the lab) to develop social psychological theory. 

The examples above also highlight how field research can shift what constitutes theory in the first place. Social psychology often seeks out domain-general truths about the world and atomic principles of the mind. The research described in this chapter highlights how theories about contexts in the world can also make strong contributions to social psychology (see also Kelley et al., 2003).  Indeed, the typology described previously rejects the notion that field research is merely applied research. Rarely can we easily apply psychological principles to engineer interventions in the world. Instead, we must sharpen theories and fill in their gaps, whether by figuring out how to translate them into different contexts or by mapping out their boundaries in the world.  

There is, of course, a whole Handbook surrounding this chapter. It has chapters on history and methods and theories. All these chapters share the goal of describing how people think and behave in the world. As readers traverse these other chapters, we encourage them to develop the habit of asking, "What would we gain by studying this in the world? 

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ENDNOTES

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