Arts, Faculty of
Psychology, Department of
DSpace
UBCV
Engstrom, Holly Rose
Doctor of Philosophy - PhD
University of British Columbia
Trust is vital for success in all kinds of social interactions. But how do people decide whether an individual can be trusted? The social class of the individual in question may be one important cue to trusting that they will behave in a moral and competent manner. We propose three mechanisms through which a person’s social class may influence how much we trust their morality and competence: Explicit dispositional stereotypes, explicit beliefs about situations, and implicit associations. We investigated this in two ways, with two opposing sets of findings. In Chapter Two, participants who played an economic game involving trust in morality trusted lower-class game partners more than higher-class partners. This was partially explained by people’s explicit stereotypes of lower-class people as more dispositionally moral than higher-class people. They also believed lower-class partners would be more tempted by their financial situation to betray them, but this did not predict trust. In Chapter Three, however, participants made repeated choices as to who they would trust in hypothetical scenarios involving trust in morality and in competence. Here, participants tended to trust higher-class partners in both morality and competence scenarios. We ran six additional studies testing potential explanations for the difference in results between Chapter Two and Three, finding some hints but no conclusive evidence. Finally, we considered whether implicit stereotypes might help to explain this difference. Across seven studies we developed a novel task to measure implicit associations with social class. Despite often reporting explicit stereotypes of lower- (vs. higher-) class people having more moral dispositions, people implicitly associated low social class with low morality. Both implicit and explicit morality stereotypes predicted decisions in the morality trust scenarios. We discuss additional possible resolutions to the discrepancy in results, as well as implications of our findings for understanding trust, social class stereotypes, and inequality.
TRUST AND SOCIAL CLASS: THE COMPLEX RELATIONSHIP BETWEEN EXPLICIT STEREOTYPES (ABOUT DISPOSITIONS AND SITUATIONS), IMPLICIT STEREOTYPES, AND TRUST by Holly Rose Engstrom B.A., McGill University, 2016 M.A., University of British Columbia, 2019 A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in The Faculty of Graduate and Postdoctoral Studies (Psychology) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) October 2023 © Holly Rose Engstrom, 2023 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Trust and social class: The complex relationship between explicit stereotypes (about dispositions and situations), implicit stereotypes, and trust submitted by Holly Rose Engstrom in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Psychology Examining Committee: Kristin Laurin, Associate Professor, Dept. of Psychology, UBC Supervisor Toni Schmader, Professor, Dept. of Psychology, UBC Supervisory Committee Member Gerry Veenstra, Professor, Dept. of Sociology, UBC University Examiner Mark Schaller, Professor, Dept. of Psychology, UBC University Examiner Additional Supervisory Committee Members: Andrew Baron, Professor, Dept. of Psychology, UBC Supervisory Committee Member iii Abstract Trust is vital for success in all kinds of social interactions. But how do people decide whether an individual can be trusted? The social class of the individual in question may be one important cue to trusting that they will behave in a moral and competent manner. We propose three mechanisms through which a person’s social class may influence how much we trust their morality and competence: Explicit dispositional stereotypes, explicit beliefs about situations, and implicit associations. We investigated this in two ways, with two opposing sets of findings. In Chapter Two, participants who played an economic game involving trust in morality trusted lower-class game partners more than higher-class partners. This was partially explained by people’s explicit stereotypes of lower-class people as more dispositionally moral than higher-class people. They also believed lower-class partners would be more tempted by their financial situation to betray them, but this did not predict trust. In Chapter Three, however, participants made repeated choices as to who they would trust in hypothetical scenarios involving trust in morality and in competence. Here, participants tended to trust higher-class partners in both morality and competence scenarios. We ran six additional studies testing potential explanations for the difference in results between Chapter Two and Three, finding some hints but no conclusive evidence. Finally, we considered whether implicit stereotypes might help to explain this difference. Across seven studies we developed a novel task to measure implicit associations with social class. Despite often reporting explicit stereotypes of lower- (vs. higher-) class people having more moral dispositions, people implicitly associated low social class with low morality. Both implicit and explicit morality stereotypes predicted decisions in the morality trust scenarios. We discuss additional possible resolutions to the discrepancy in results, as well as implications of our findings for understanding trust, social class stereotypes, and inequality. iv Lay Summary How does a person’s social class – their income, education, and occupation – affect how much we trust them? We tested this in two ways. In a first set of experiments, participants played a game involving trust. Results showed they trusted lower- (vs. higher-) class game partners more. This was partly explained by people believing lower-class people are more moral. In a second set of experiments, participants read hypothetical trust scenarios and repeatedly chose who they would trust. Here, people said they would trust higher-class people more than lower-class people. We tested six potential reasons for this discrepancy in results, but did not find a conclusive answer. Next, we thought people might say lower-class people are more moral, but in fact, associate low social class with less morality. We developed a new measure of these implicit associations with social class which supported this idea, and found that these implicit associations predicted trust. v Preface I am the primary author of the work presented in this dissertation. I designed the experiments, collected and analyzed the data, and wrote the dissertation. All studies were approved by UBC’s Behavioral Research Ethics Board # H17-03597. Below, I describe additional contributions for each chapter. Chapters 1 and 4: Introduction and General Discussion I prepared these chapters in collaboration with my supervisor, Kristin Laurin, who provided intellectual contributions and shaped the ideas discussed in these chapters. Chapter 2: Social Class, Trust in Morality, and Explicit Stereotypes A version of Chapter 2 is being prepared for publication. I designed the experiments, collected and analyzed the data, and prepared the manuscript. Kristin Laurin and Toni Schmader provided intellectual contributions to the study design and analysis and edited the manuscript. Chapter 3: Social Class, Trust in Morality and Competence, and Implicit Stereotypes I designed the experiments, collected and analyzed the data, and prepared the chapter. To create our new measure of implicit associations with social class, I modified code written by Patrick Dubois. Kristin Laurin provided intellectual contributions and edited the chapter. vi Table of Contents Abstract .......................................................................................................................................... iii Lay Summary ................................................................................................................................. iv Preface............................................................................................................................................. v Table of Contents ........................................................................................................................... vi List of Tables ................................................................................................................................. ix List of Figures ................................................................................................................................ xi Acknowledgments......................................................................................................................... xii Dedication .................................................................................................................................... xiii Chapter One: Introduction .............................................................................................................. 1 Impact and Scope of Project........................................................................................................ 1 Overview of Previous Research .................................................................................................. 2 Why Might Others’ Social Class Affect Decisions to Trust their Morality? .............................. 5 Social Class and Morality Judgments ......................................................................................... 6 Dispositional Trustworthiness and Situational Limitations ..................................................... 7 Social Class and Trust-Related Dispositions ........................................................................... 7 Social Class and Trust-Related Situations ............................................................................... 9 Implicit Morality Stereotypes ................................................................................................ 11 Broadening the Scope: What About Trust in Competence? ..................................................... 12 How Might Social Class Influence Trust in Others’ Competence?....................................... 14 Which Pathway Takes Precedence? .......................................................................................... 15 Overview of Dissertation Research ........................................................................................... 17 Chapter Two: Trust in Morality Based on Explicit Social Class Stereotypes .............................. 19 Chapter Two Overview ............................................................................................................. 19 Study 1....................................................................................................................................... 21 Method ................................................................................................................................... 22 Results ................................................................................................................................... 28 Discussion .............................................................................................................................. 31 Study 2....................................................................................................................................... 32 Method ................................................................................................................................... 33 Results ................................................................................................................................... 36 Discussion .............................................................................................................................. 38 vii Study 3....................................................................................................................................... 39 Method ................................................................................................................................... 40 Results ................................................................................................................................... 42 Discussion .............................................................................................................................. 44 Study 4....................................................................................................................................... 45 Method ................................................................................................................................... 46 Results ................................................................................................................................... 49 Discussion .............................................................................................................................. 56 General Discussion .................................................................................................................... 57 Chapter Three: Social Class, Trust in Morality and Competence, and Implicit Stereotypes ....... 59 Chapter Three Overview ........................................................................................................... 59 Study 5....................................................................................................................................... 62 Method ................................................................................................................................... 63 Results ................................................................................................................................... 70 Discussion .............................................................................................................................. 73 Studies 6A-6F ............................................................................................................................ 73 Method ................................................................................................................................... 77 Results ................................................................................................................................... 89 Discussion .............................................................................................................................. 97 Studies 7A-7G ........................................................................................................................... 99 Method ................................................................................................................................. 101 Results ................................................................................................................................. 108 Discussion ............................................................................................................................ 111 Study 8..................................................................................................................................... 111 Method ................................................................................................................................. 112 Results ................................................................................................................................. 115 Discussion ............................................................................................................................ 119 Chapter Four: General Discussion .............................................................................................. 120 Approach #1: Situational Moderators ..................................................................................... 120 Approach #2: Implicit Stereotypes .......................................................................................... 122 Is the Discrepancy Resolved? ................................................................................................. 124 Other Potential Explanations ................................................................................................... 125 Evaluating the Three Pathways to Trust in Morality, and Adding a Moderator ..................... 128 Implications ............................................................................................................................. 130 viii Limitations .............................................................................................................................. 134 Participant Social Class and Generalized Trust ...................................................................... 136 Conclusion ............................................................................................................................... 138 References ................................................................................................................................... 139 Appendix A: Supplemental Material for Chapter Two ............................................................... 162 Study 1 Items for Guessing Targets’ Demographics .............................................................. 162 Study 2 Full Three-Way Interaction Results ........................................................................... 162 Study 3 Results with Alternate Exclusion Criteria ................................................................. 163 Study 4 Additional Mediation Models .................................................................................... 165 Mediation by Dispositional and Situational Stereotypes, Separated by Condition ............. 165 Mediation by Relational Models, Moderated by Condition ................................................ 166 Testing Independent Effects of Dispositional Variables ..................................................... 167 Supplemental Studies A1.1-A1.3: Trusting Others on MTurk ............................................... 167 Supplemental Study A2: Trusting Others with Time .............................................................. 177 Supplemental Study A3: Pilot for Study 4 .............................................................................. 180 Studies 1-4 and A1.1-A3 Exploratory Mediation Analyses .................................................... 187 Study 3 Moderation Analyses ................................................................................................. 193 Appendix B: Supplemental Material for Chapter Three ............................................................. 196 Study B1 .................................................................................................................................. 196 Study B2 .................................................................................................................................. 198 Moderation Analyses, Study 5 ................................................................................................ 199 Moderation Analyses, Studies 6A-6F ..................................................................................... 202 ix List of Tables Table 1 Summary of previous research investigating how target social class affects trust. ........ 19 Table 2 Demographics for participants in each Chapter Two study. .......................................... 22 Table 3 Profiles used to manipulate target social class, Study 1. ................................................ 25 Table 4 Multilevel regression analyses predicting trust, Study 1. ............................................... 28 Table 5 Participants’ guesses of targets’ demographics. ............................................................ 29 Table 6 Multilevel regression analyses showing effect of (manipulated) target social class on trust holds controlling for perceived age, gender, and ethnicity, but not perceived social class, Study 1. .......................................................................................................................................... 30 Table 7 Multilevel regression analysis predicting trust, Study 2. ................................................ 36 Table 8 Multilevel regression analyses predicting trust in the trust game and cooperation in the prisoner’s dilemma game, Study 3. ............................................................................................... 43 Table 9 Mediator items, Study 4................................................................................................... 47 Table 10 Vignettes for high and low temptation trust situations, Study 4. .................................. 49 Table 11 Multilevel regression analyses predicting trust, Study 4. ............................................. 50 Table 12 Correlations and descriptive statistics for mediators. Correlations for ratings of low SES target below diagonal; correlations for ratings of high SES target above diagonal; means (SDs) in rightmost columns (subscript L = lower-class target; subscript H = higher-class target)....................................................................................................................................................... 52 Table 13 Exploratory analyses examining relational models as mediators, Study 4. ................. 55 Table 14 Summary of methods and results of all studies testing the relationship between target social class and trust. Significant positive effect sizes highlighted in green indicate people trusted higher-class targets over lower-class ones; significant negative effect sizes highlighted in blue indicate the reverse; effects with no significant difference in trust based on target class are not highlighted. ................................................................................................................................... 61 Table 15 Target descriptions, Study 5. ......................................................................................... 67 Table 16 Multilevel logistic regression analyses testing who people trust in morality and competence scenarios based on target social class and type of social class information provided........................................................................................................................................................ 71 Table 17 Demographics and exclusions, Studies 6A-6F. ............................................................. 77 Table 18 Manipulations used in Studies 6A-6F. .......................................................................... 83 Table 19 Log odds ratios from multilevel logistic regression analyses testing who people trust in morality and competence scenarios based on target social class, type of social class information, and moderators. ............................................................................................................................ 90 Table 20 Sample details, Studies 7A-7G. ................................................................................... 101 Table 21 Psychometric properties of BIATs, Studies 7A-7B. ..................................................... 106 Table 22 Implicit and explicit stereotypes of morality (M) and competence (C), and their correlations, across Studies 7A-7G. ........................................................................................... 109 Table 23 Implicit and explicit stereotypes predicting trusting higher-class targets over lower-class ones, Studies 7F-7G. .......................................................................................................... 109 Table 24 Target descriptions, Study 8. ....................................................................................... 114 Table 25 One-sample t-tests comparing the social class difference in explicit stereotypes, implicit stereotypes, and trust to no difference. .......................................................................... 116 Table 26 Implicit and explicit stereotypes predicting trusting higher-class targets over lower-class ones in trust scenarios, Study 8.......................................................................................... 117 x Table 27 Summary of trust scenarios used across studies and their results. ............................. 125 Table 28 Items for participants to guess targets’ demographics, Study 1. ................................ 162 Table 29 Three-way interactions between target class, participant class, and condition, Study 2...................................................................................................................................................... 162 Table 30 Multilevel regression analyses predicting trust (in the trust game) and cooperation (in the prisoner’s dilemma game) using different exclusion criteria, Study 3. ................................ 164 Table 31 Interaction and indirect effects from moderated mediation models examining relational models as mediators between target social class and trust, moderated by temptation condition...................................................................................................................................................... 167 Table 32 Testing independent effects of dispositional mediators, Study 4................................. 167 Table 33 Demographics for individual Studies A1.1-A1.3. ........................................................ 169 Table 34 Data quality across studies. ........................................................................................ 170 Table 35 Sample profiles manipulating target social class, Studies A1.1-A1.3......................... 172 Table 36 Multilevel regression analysis predicting trust, Study A1.1-A1.3. .............................. 175 Table 37 Demographics, Study A2. ............................................................................................ 178 Table 38 Multilevel regression analyses predicting trust, Study A2. ......................................... 179 Table 39 Demographics, Study A3. ............................................................................................ 180 Table 40 Trust scenarios, Study A3. ........................................................................................... 182 Table 41 Multilevel regression analysis predicting trust, Study A3. ......................................... 182 Table 42 Trust in other situations based on social class, Study A3. .......................................... 184 Table 43 Correlations and descriptive statistics for mediators. Correlations for ratings of low SES target below diagonal; correlations for ratings of high SES target above diagonal; means (SDs) in rightmost columns (subscript L = lower-class target; subscript H = higher-class target). ......................................................................................................................................... 185 Table 44 Exploratory mediation models, Study A3. ................................................................... 186 Table 45 Mediation measures across studies. ............................................................................ 187 Table 46 Exploratory mediation analyses across studies. ......................................................... 189 Table 47 Moderation analyses, Study 2 (key moderation tests bolded). .................................... 194 Table 48 Pilot testing results showing that people prefer to choose a moral (but incompetent) person in the morality scenarios, and a competent (but immoral) person in the competence scenarios. .................................................................................................................................... 199 Table 49 Participant social class, social class stereotypes, and attributions for social class predicting choosing to trust a high vs. low social class target, Study 5. .................................... 200 Table 50 Participant social class, social class stereotypes, attributions for social class, and political orientation predicting choosing to trust a high vs. low social class target, Studies 6A-6F. ............................................................................................................................................... 202 xi List of Figures Figure 1 Example of one combination of lower- and higher-class target profiles participants viewed. .......................................................................................................................................... 24 Figure 2 Example of target profiles participants viewed, Study 2. .............................................. 35 Figure 3 Testing the theorized pathways between social class, moral disposition and situational temptation, and trust, moderated by temptation condition; Study 4. ............................................ 53 Figure 4 Sample trial, Study 5. ..................................................................................................... 69 Figure 5 Probability of choosing the higher-class target in competence and morality scenarios, based on the type of social class information provided. The black line indicates chance (0.5), or no difference between targets based on their social class. ........................................................... 71 Figure 6 Trust based on target social class, scenario type, and manipulation............................ 91 Figure 7 Participants stereotype high-class targets as more competent and slightly less moral than low-class targets, Studies 6A-6F. ......................................................................................... 96 Figure 8 Cohen’s ds for the difference in explicit stereotypes, implicit stereotypes, and trust based on social class. .................................................................................................................. 115 Figure 9 Theorized potential pathways explaining the relationship between social class and trust. Black icons and arrows indicate empirically supported pathways; grey icons and arrows indicate weak empirical evidence; blue dashed arrows indicate theorized but untested pathways...................................................................................................................................................... 128 Figure 10 Mediation of the effect of target social class on trust through moral dispositions and situational temptation, separately for the low and high temptation conditions, Study 4............ 165 Figure 11 Relational models mediating the link between target social class and trust, moderated by temptation condition............................................................................................................... 166 Figure 12 Exploratory mediation analysis, Study A2B-A2C pooled. ......................................... 176 Figure 13 Testing the theorized pathways between social class, moral disposition and situational temptation, and trust; Study A3. ................................................................................................. 185 xii Acknowledgments This research was primarily conducted at UBC’s Vancouver campus, which is located on the traditional, ancestral, and stolen territory of the xʷməθkʷəy̓əm (Musqueam) people. I also conducted some of this research from my home in Chilliwack, which is the traditional, ancestral, and stolen territory of the Stó:lō Coast Salish peoples. I am grateful to live and work here. This research would not have been possible without the hard work and dedication of many wonderful undergraduate researchers, including Sereen Alabdulateef, Farah Charania, Rachel Hueller, Tianmu Ji, Nick R. Kay, Yawen Liu, Felipa Schmidt, and many others. I am also grateful to my lab members in the MECC lab for their invaluable contributions and feedback to this project, and to Dr. Toni Schmader for her collaboration and input on the writing and idea development for the studies in Chapter Two. Finally, I want to thank my supervisor, Dr. Kristin Laurin, for her constant support and guidance over the past six years. This project (like many others) turned into a confusing and unwieldy set of findings, and without Kristin’s enthusiasm and motivation to untangle the mystery I would have lost the thread. xiii Dedication This dissertation is dedicated to two cats, Mimzy and Yogurt, who I hope are sitting on laptop keyboards and demanding food somewhere in cat heaven. Mimzy went through nine years of higher education with me and could probably have written this dissertation herself, but she found it more fun to delete pages and make me panic. I miss you both. Oh, and I suppose I also dedicate it to my partner Tim, my family, and my friends. You’re almost as good as cats. 1 Chapter One: Introduction Impact and Scope of Project Trust is vital for social interactions to be successful across a wide variety of domains, including interpersonal relationships, political participation, and workplace productivity (e.g., Dunning et al., 2019; Evans & Krueger, 2009; Kramer, 1999; Krueger & Meyer-Lindenberg, 2019; Rotter, 1971; Simpson, 2007b; Thielmann & Hilbig, 2015). Most social psychological research on trust has focused on trust in another person’s morality – trusting that person to do the right, fair thing (e.g., Berg et al., 1995; Krueger & Meyer-Lindenberg, 2019; Rathbun, 2009; Rempel et al., 1985). Other disciplines like organizational behavior have also examined trust in another person’s competence – trusting that person to perform the task well (e.g., Kim et al., 2004; Lee, 2004; Mayer et al., 1995). In this dissertation we examine how people’s trust is influenced by potential trustees’ social class. We propose that people use social class as a cue of morality and competence, because social class is linked to stereotypes on both dimensions (e.g., Christopher & Schlenker, 2000; Durante et al., 2017; Lindqvist & Björklund, 2017; Ragusa, 2015; Wu et al., 2018), and therefore use social class to inform their trust decisions. In so doing, we develop a novel, nuanced portrait of how low social class is linked to stereotypes of both moral dispositions and immoral situational temptations, distinguish for the first time between explicit and implicit social class stereotypes of morality and competence, and link this complex network of stereotypes to trust, an important behavioral outcome. The scope of this dissertation project does not extend to the extreme ranges of the socioeconomic spectrum; all theorizing and studies focus on the most densely populated range of the socioeconomic spectrum, and may not necessarily apply to those at the extreme low (e.g., unhoused people) or high (e.g., billionaire CEOs) ends of the spectrum. 2 If trust is distributed differently across the socioeconomic spectrum – that is, if people trust upper-class others more than lower-class others, or vice versa – this has implications at an individual level for the financial and emotional well-being of those receiving (or not receiving) this trust. Trust often carries rewards for the trustee, for example, when trusting someone enough to hire them, lend a precious item to them, or buy a car from them. Thus, if there is systemic bias against one social class group in terms of whom people prefer to trust, this bias could have material consequences for their experiences and outcomes in a variety of domains (e.g., hiring, house loans, social relationships). Any such systemic bias is becoming increasingly important as economic inequality continues to rise in many parts of the world (Dabla-Norris et al., 2015; Musterd et al., 2017; OECD, 2011): As lower-class groups become poorer, and higher-class groups become richer, any trust differential they experience will only grow. Overview of Previous Research Psychologists commonly define trust as “a psychological state comprising the intention to accept vulnerability based on the positive expectations of the intentions or behavior of another” (Rousseau et al., 1998 p. 395). Trust is important because it allows people to accept the “ordinary uncertainties” (Evans & Krueger, 2009, p. 1003) of life that exist in every social interaction: One cannot know what another person’s intentions are or future behavior will be, but trust means one can accept these uncertainties and proceed with the interaction anyway. Some research on trust, including the earliest social psychological investigations of trust, examines generalized trust (Aarøe et al., 2016; Gurtman, 1992; Holmes, 1991; Lu et al., 2019; Rotter, 1971). From this perspective, some individuals are more trusting than others: They generally believe others are helpful, dependable, and cooperative, and are more willing to accept vulnerability based on this positive expectation. Generalized trust is often measured by asking 3 participants to what degree they think other people in general can be trusted (Bjørnskov, 2006; Glanville & Paxton, 2007; Nannestad, 2008). Other researchers, including later social psychological investigations of trust, examine interpersonal trust. From this perspective, trust depends on the relationship between the person trusting and the person being trusted. People may decide to accept vulnerability based on what they know about the other person, past interactions they have had with this person, and so on (Everett et al., 2016; Qi et al., 2018; Righetti & Finkenauer, 2011). Interpersonal trust is studied in a variety of different ways, for example, by asking people how trustworthy specific other people are based on their faces, or by studying how trust develops based on interactions in relationships (Sofer et al., 2015; Uysal et al., 2012; Weber et al., 2005). Most contemporary trust research acknowledges both forms of trust matter (Simpson, 2007a). For example, one daily diary study of trust across daily social interactions found evidence for both consistent differences between individuals (i.e., generalized trust) but also reliable differences across people with whom these individuals interacted (i.e., interpersonal trust; Fleeson & Leicht, 2006). These two forms of trust illustrate how the individual doing the trusting and the individual being trusted are two separable and important components of trust. A third important component that social psychologists often do not explicitly highlight is what, exactly, one is trusting the other person to do (e.g., “I trust you to do X”) (Hardin, 2003; Simpson, 2007a). In other words, what uncertainty or vulnerability is trust helping us to accept? In this dissertation, we make explicit an assumption that is implicit in most social psychological research on trust, which is that trust often allows us to accept uncertainties around another person’s morality – trusting someone means believing they have moral intentions and will behave morally, with the associated risk being that they could take advantage of you and betray you by behaving 4 immorally (e.g., Berg et al., 1995; Rempel et al., 1985). To illustrate with an example how this is our field’s traditional emphasis, much of the social psychological literature on trust is focused on trust within romantic relationships, investigating whether people can trust their partners to be faithful, responsive to their needs, and committed to their well-being – in other words, to behave morally (e.g., Arikewuyo et al., 2021; Holmes, 1991; Luchies et al., 2013; Norona et al., 2017; Rempel et al., 1985). As another example, one of the most commonly used behavioral measure of trust (cited almost 7,000 times), the trust game, also involves trust in morality (Berg et al., 1995). In this game, participants can transfer as much (or as little) of their initial start-up funds as they want to another player. Upon being transferred, this money is tripled. The other player can then decide to return as much (or as little) of this tripled pool as they want to the participant. In other words, transferring money to the other player involves trusting them to return a fair, moral amount of the now-expanded pot of money. This dissertation work too focuses primarily on trust in others’ morality, although later on in the introduction, and in several studies, we expand to also consider trust in someone’s competence. We therefore define trust in line with Rousseau’s (1998) definition as cited above, but we do not assume that one’s “positive expectations of the intentions or behavior of another” refer specifically to moral intentions or behavior. Rather, we follow the literal interpretation of the definition: Trust involves one person expecting that another person will behave in the way one hopes they will (e.g., they will be faithful in a romantic relationship, return money to oneself in the trust game, or complete a task at work properly), and based on this expectation, being willing to accept the possibility that the other person will betray one’s trust and fail to live up to one’s hopes (e.g., by cheating in a relationship, keeping the money, or leaving the work task incomplete). We presume that when someone is in this state of trust, they will be more willing to 5 take trusting actions such as transferring more money to their partner in a trust game, allowing their romantic partner to take a long business trip with an attractive colleague, or giving an important project to a new colleague at work, because they expect the other person to behave the way they hope, and despite the risk of betrayal. Why Might Others’ Social Class Affect Decisions to Trust their Morality? One factor that may influence how much people trust one another to behave morally is social class. Researchers have defined social class and theorized about its effect on people’s psychology using a wide variety of approaches, for example, considering social class as a cultural context that promotes particular norms and ways of being suited to that context (e.g., Phillips et al., 2020; Stephens et al., 2007, 2014), as a transient state where an individual assesses their status relative to others’ and behaves accordingly (e.g., Kraus et al., 2011, 2013), or as a source of power (control over resources) and status (respect from others) (e.g., Rucker et al., 2015). Here, we sidestep the discussion on how, precisely, social class might influence an individual psychologically, and instead focus on how that individual might be treated differently by others because of that individual’s social class. In other words, we focus on how laypeople perceive others who differ in social class, and how these lay perceptions influence trust. We define social class, in line with Piff and colleagues, as “a pervasive form of hierarchy rooted in a person’s wealth, education, and occupational prestige” (2018, p. 57), and operationalize it using manipulations of these three factors, in different combinations across studies. People can quickly and accurately perceive each other’s place in this hierarchy (Kraus et al., 2017), even from cues as limited as photographs of their shoes (Gillath et al., 2012), standardized photographs of faces (Bjornsdottir & Rule, 2017), or videos of brief interactions between two individuals (Kraus & Keltner, 2009). Based on these perceptions of others’ social 6 class, people then readily make assumptions and form stereotypical judgments about them – including about their morality (e.g., Christopher & Schlenker, 2000; Durante et al., 2017; Horwitz & Dovidio, 2017; Ragusa, 2015; Sainz et al., 2018, 2020; Wu et al., 2018). We examine how these judgments about morality, in turn, may lead to interpersonal trust (or distrust). That said, some research has investigated the relationship between trusters’ social class and generalized trust, finding that people with lower (versus higher) social class tend to report lower trust in strangers in general (Brandt et al., 2015; Fischer & Torgler, 2013; S. T. Fiske et al., 2012). Changes in trusters’ social class predict subsequent changes in trust, suggesting this may be a causal relationship (Brandt et al., 2015). Thus, where possible, we also test for effects of trusters’ social class on the degree to which they trust targets in general. Social Class and Morality Judgments When deciding whether to trust someone’s morality, trusters might ask themselves two questions in trying to predict how the potential trustee will behave: (1) Is this person the kind of person who will behave immorally and betray my trust? (2) Is this person in a situation that will tempt them to behave immorally and betray my trust? If people base morality trust decisions on dispositions, the assumptions people make about the moral character of people with lower (versus higher) social class would lead them place more trust in those with lower (versus higher) social class. Alternatively, if people base morality trust decisions on situations, they may assume that lower-class individuals chronically find themselves in contexts that could tempt them to betray trust for financial gain, and place less trust in lower- (versus higher-) class others. That is, the social class of the trustee could theoretically exert opposing dispositional and situational influences on how people answer trust-related questions; our research investigates the existence and relative strength of these influences. 7 Dispositional Trustworthiness and Situational Limitations People often behave in line with their dispositions, but can be influenced by situational factors (e.g., Epstein & O’Brien, 1985; Fleeson, 2004; Funder, 2008; Kenrick & Funder, 1988; Mischel, 1973; Thielmann & Hilbig, 2015). For example, people whose disposition places morality at the center (rather than the periphery) of their self-concept are less likely to lie, but this difference disappears in situations that present sufficient financial incentive (Aquino et al., 2009). In turn, observers anticipate these dual forces, using both dispositional and situational information to predict how actors will behave (Kunda & Nisbett, 1986; Newman, 1996; Nisbett, 1987; Zuroff, 1982). For example, people believe that a dispositionally friendly person will behave more warmly than a dispositionally shy person, but also that both people will behave more warmly with authorities than peers (Kammrath et al., 2005). In the domain of trust, we trust the kind of people whose information is likely credible (e.g., experts), and distrust those who are situationally tempted to lie (e.g., who would benefit by convincing us to adopt a particular belief; Hovland et al., 1953). Similarly, when determining how much to trust a romantic partner, we trust the kind of people who seem unlikely to cheat (e.g., those with strong self-control; Righetti & Finkenauer, 2011), and distrust those who are situationally tempted to cheat (e.g., those surrounded by viable partners; Murray et al., 2009). This prior research does not, however, directly pit dispositional and situational influences against each other: How much should we trust someone who seems dispositionally inclined to be trustworthy, but situationally tempted to betray us? Social Class and Trust-Related Dispositions One question people might ask when making trust decisions is what kind of person is this: Are they intrinsically disposed to honor or betray my trust? Regardless of their own social 8 class, people stereotype those with low to middle class as warmer than those with high social class (Christopher & Schlenker, 2000; Durante et al., 2017; Durante & Fiske, 2017; Ragusa, 2015). Warmth comprises both sociability (e.g., friendliness) and morality (e.g., honesty; Abele et al., 2016, 2021). This suggests people assume those with lower (vs. higher) social class are dispositionally more moral, and perhaps therefore more trustworthy (Kong, 2018). Conversely, people tend to stereotype higher-class people as out of touch, arrogant, selfish, and greedy (Zitelmann, 2020), dehumanize them by viewing them as cold, mechanistic, and unemotional (Sainz et al., 2018, 2019), and suspect that the status they have accumulated probably required selfish, manipulative behavior (Belmi & Laurin, 2016). Thus, to the extent that trusters focus on what kind of person the potential trustee is, class-based stereotypes should lead people to trust lower-class individuals more than higher-class ones. In addition to these broad dimensional stereotypes, we wondered whether people also assume lower- and higher-class are disposed specifically to take different approaches to relationships. There is evidence that those with lower social class backgrounds are socialized to have more interdependent cultural orientations, whereas those with higher class backgrounds are socialized to have more independent cultural orientations (Kraus et al., 2011; Stephens et al., 2014). In turn, this could make them culturally inclined to adopt certain relational styles. From this, we reasoned that people might believe lower-class individuals would be especially disposed to use interdependent cognitive models to guide their relationships (A. P. Fiske, 1991, 1992). Specifically, we wondered if people would stereotype lower-class others as being more likely than higher-class others to endorse models based in communal sharing (viewing people as equal parts of a collective and therefore sharing resources freely) and equality matching (ensuring the relationship is balanced and fair by taking turns and reciprocating others’ actions). Because (to 9 our knowledge) no prior work has examined stereotypes about social class and relational styles, we explore these ideas as a secondary goal. Social Class and Trust-Related Situations When deciding whom to trust, people might consider not only a target’s disposition, but also the situation that the target finds themselves in. Though researchers typically study stereotypes of dispositions (e.g., Ellemers, 2017; S. T. Fiske et al., 2002; Sainz et al., 2018), research in person perception and gender stereotyping indicates that people also hold stereotypes of how members of different groups behave in different situations (Kammrath et al., 2005; Kelly & Hutson-Comeaux, 1999; Mendoza-Denton et al., 2008). For example, people stereotype women as having a more emotional disposition than men and expect women to be more likely than men to overreact emotionally in interpersonal contexts – but they expect men to be more likely than women to overreact emotionally in achievement contexts (Kelly & Hutson-Comeaux, 1999). Similarly, people expect men to behave more assertively than women in work and sport contexts, in line with research on dispositional stereotypes about gender and assertiveness – but they expect women to behave more assertively than men in home and interpersonal contexts (Mendoza-Denton et al., 2008). Thus, situational information moderates people’s stereotypic expectations for how members of different groups will behave, sometimes in ways that seem contrary to their overall dispositional stereotype of members of that group. One relevant piece of situational information that may moderate people’s expectations of trustworthy behavior from members of different social class groups is the financial temptation to betray one’s trust. In many everyday trust situations, there is some financial incentive to betray. The employee you trust to handle the cash register might steal money, the friend you trust with a rare cookbook might hold onto it indefinitely to avoid buying their own copy, or the salesperson 10 you trust to advise you might exaggerate the benefits of a new car to make the sale. If none of these people had an incentive to betray you, then you could hire, lend to, or take purchasing advice from anyone without fear of being swindled, and none of these situations would create vulnerability or require trust. To the extent trusters consider trustees’ situations (Evans & Krueger, 2011; Snijders & Keren, 1999), they might perceive that lower-class individuals are typically in greater financial need than higher-class individuals. Thus, if a lower- and higher-class individual face the same situation, where they could gain financially by betraying someone’s trust, people might expect the lower-class individual to be more tempted by that incentive. In other words, because of these individuals’ chronic financial situation, people likely expect them to react differently when faced with acute situations that offer financial rewards for betrayal of trust. When making trust decisions based on the trustee’s social class, trusters may consider situations both in terms of the financial situation that the person to be trusted chronically occupies, as well as in terms of the level of temptation posed by the financial incentive in this specific trust situation. Even though people believe low (versus high) social class individuals are dispositionally moral (Durante et al., 2017), they also associate them with criminal behavior (Smalarz et al., 2016): The complete stereotype seems to be of an inherently good person whose financial situation may nonetheless tempt them toward illegal or harmful acts for personal gain. Likewise, trusters may recognize that wealthy people’s financial security may be a circumstance that inoculates them against financial temptations to betray trust. If anything, this circumstance affords the wealthy the ability to materially reward the trust others place in them (Sugiyama & Sugiyama, 2003; Tooby & Cosmides, 1996). To the extent that trusters focus on the situation the trustee is in, decision-makers may trust higher-class individuals more than 11 lower-class ones (at least when incentives to betray are material), and may be especially likely to do so when there is a larger material incentive to betray. Implicit Morality Stereotypes This reasoning that we have suggested trusters might apply, where they consider who is a moral person versus who might be tempted by their situation to behave immorally, involves explicit stereotypes about people based on their social class. That is, we expect that trusters would be consciously aware of viewing lower-class (versus higher-class) people as more moral but more tempted by their financial situation to behave immorally, and that trusters would be able and willing to report holding these views. We based this theoretical rationale on the finding that people explicitly rate lower-class people as more moral, but more criminal, than higher-class people (Durante et al., 2017; Smalarz et al., 2016). But people might also hold implicit stereotypes about people based on their social class. That is, they might also have associations that come to mind automatically, without their control, when they see or think about someone with a specific social class background (e.g., Fazio & Olson, 2003; Greenwald & Lai, 2020). People may be unaware that they hold these associations, or be aware that they hold them but unwilling to report them (for example, because they want to avoid seeming prejudiced). Thus, an additional complication in the relationship between a target’s social class and decisions about whether to trust them is that it is difficult to predict whether people’s trust decisions will follow their explicit stereotypes or their implicit stereotypes. People’s implicit stereotypes sometimes diverge from their explicit ones (e.g., Fazio & Olson, 2003; Hofmann, Gschwendner, et al., 2005; Hofmann, Gawronski, et al., 2005; Latu et al., 2011). In the particular case of social class they may even be the complete reverse. People tend to have positive implicit associations with high social class, even when they explicitly 12 profess disliking the rich (Horwitz & Dovidio, 2017) or holding ambivalent stereotypes about them (Wu et al., 2018). Moreover, one study found that in Sweden, people implicitly associate welfare recipients with low warmth (Lindqvist et al., 2017), which may further imply low morality. Thus, people may implicitly associate high social class with high morality, and low social class with low morality – the reverse of their explicit dispositional judgments. In morality trust situations, even if we knew people relied on dispositional morality stereotypes more than on situations, we would still not know what to predict: We would expect them to trust lower-class individuals more than upper-class ones if they consult their explicit stereotypes, but the reverse if they instead rely on implicit stereotypes. Broadening the Scope: What About Trust in Competence? In theorizing about this question of how social class may influence people’s judgments of others’ dispositions and situations and therefore their trust, we have followed the tradition of other social psychological research and focused on trusting others to behave morally. However, the organizational behavior and management literatures take a broader view of trust, going beyond trust in morality alone (e.g., Butler & Cantrell, 1984; Cook & Wall, 1980; Kim et al., 2004; Lee, 2004; Mayer et al., 1995; Schindler & Thomas, 1993). In the most widely cited management framework (Mayer et al., 1995), there are three key antecedents to trust: benevolence, meaning someone has positive intentions towards you; integrity, meaning someone generally adheres to a moral code you find acceptable; and ability, meaning that someone has the skills and capacities needed for whatever it is you are trusting them to do. Benevolence and integrity clearly align with the social psychological view of trust: trusting someone to have good intentions towards you, and a set of moral principles that you share. However, ability seems different. It could apply within the social psychological view (for example, will your romantic 13 partner have the self-control resources to resist the temptation of an attractive colleague on a work trip?), but could also apply beyond the realm of morality (for example, will your employee be able to handle the added responsibility that comes with a promotion?). Indeed, management and organizational behavior researchers distinguish between morality trust violations and competence trust violations. For example, if an accountant intentionally files taxes wrong to evade taxation, that is a morality trust violation due to her lack of benevolence or integrity, but if she files the taxes wrong because she misunderstood the tax code, that is a competence trust violation due to her lack of ability (Kim et al., 2006). Trusting someone to do the competent thing is different in many ways from trusting someone to do the ethical thing; nonetheless both clearly fit within even social psychology’s accepted definition of trust: accepting vulnerability based on one’s expectations for how others will behave. In the accountant example, people expect positive behavior – filing taxes correctly – and accept that this makes them vulnerable to getting in trouble with the government if the accountant fails to meet those expectations, whether due to a failure of morality or competence. In the accountant example, morality and competence are both relevant factors and people would likely choose an accountant they trusted to be both moral and competent. However, some situations likely emphasize one more than the other. For example, the decision to trust someone with an embarrassing secret likely hinges on whether you trust that they will behave morally and keep this secret, rather than spreading the story all over town. In contrast, the decision to trust an employee who asks for the opportunity to prove themselves by giving the presentation to an important client likely hinges on whether you trust that they will behave competently and give a compelling presentation, rather than bombing the presentation and losing the client. Accordingly, people likely weigh the antecedents of trust differently depending on the situation, attending 14 more to morality (integrity and benevolence) in situations requiring trust in morality, and more to competence (ability) in situations requiring trust in competence. Thus, considering the dispositional and situational pathways to morality judgments is useful to understand how social class may influence trust in morality situations, but does not answer how social class might influence trust in competence situations. How Might Social Class Influence Trust in Others’ Competence? Competence stereotypes have a straightforward link with social class: Those with high social class are consistently stereotyped as more competent than those with lower social class at an explicit level (Asbrock, 2010; Durante et al., 2017; Durante & Fiske, 2017; S. T. Fiske et al., 2002; Spencer & Castano, 2007) because people tend to believe that getting to a higher socioeconomic position requires skill and intelligence (Connor et al., 2021; in addition to believing it requires potentially unethical political maneuvering; Belmi & Laurin, 2016). Moreover, because implicit associations with high social class tend to be more positive than those with low social class (Horwitz & Dovidio, 2017; Lindqvist et al., 2017; Wu et al., 2018), we are not aware of any reason to expect that people’s implicit associations between competence and high social class would be any different (less positive) than their explicit stereotypes. Thus, in competence trust situations, if people rely on dispositional impressions, people should trust those with high social class more than those with lower social class, regardless of whether they rely on explicit or implicit stereotypes. This is likely to be particularly important for economic inequality: If people do not trust lower-class individuals’ competence, they are unlikely to admit them to higher education, hire them to do jobs requiring competence, or promote them to higher levels requiring more competence. 15 For competence, we examine only dispositional stereotypes. It is possible that people’s situational stereotypes about social class and competence differ from their dispositional ones (for example, people might think that because those with lower social class are in a chronic financial situation where they are more in need of their job, they might take more seriously a situation where they have the opportunity to advance at work and therefore perform more competently). However, the association between social class and dispositional competence stereotypes is very large, typically between d = 0.8 and d = 1.5 (see Studies 6A-6F). It therefore seems unlikely that any situational competence stereotype would be strong enough to neutralize this. Which Pathway Takes Precedence? We have outlined three possible pathways through which the trustee’s social class might influence trust: explicit stereotypes about dispositions, explicit stereotypes about situations (though we focus on this pathway for morality, and leave competence stereotypes to future researchers), and implicit stereotypes. Which of these pathway(s) will win out over the other, and under what circumstances? There is a great deal of psychological literature that could inform this answer. For example, beginning by comparing explicit dispositional versus situational stereotypes, classic research on the fundamental attribution error found that people often attend more to dispositions than situations, suggesting dispositional stereotypes will affect trust behavior more so than situational ones (e.g., Jones & Harris, 1967; Ross, 1977). Subsequent research showed this varied based on culture, with those from interdependent cultures attending more to dispositions than those from independent cultures (e.g., Choi et al., 1998; Choi & Nisbett, 1998), suggesting those with more interdependent (vs. independent) cultural orientations may attend more to situational stereotypes. Researchers have since identified a diverse array of other factors that moderate this tendency to privilege dispositions over situations, including 16 mood (Forgas, 1998), self-presentation motivation (Jellison & Green, 1981), age (Higgins & Bryant, 1982), the passage of time (Burger, 1991), personality (Hicks, 1985), and many others (e.g., Block & Funder, 1986; Miller & Lawson, 1989; Stalder, 2000; Tetlock, 1985; see Granot & Balcetis, 2013 for a review). Turning to the explicit versus implicit stereotype difference, again, researchers have identified many factors that affect which is most likely to predict behavior. For example, one meta-analysis demonstrated that implicit attitudes are better predictors of behavior related to intergroup relations, whereas explicit stereotypes are better predictors of behavior in other domains such as political preferences, personality traits, and clinical outcomes (Greenwald et al., 2009). Theorists have also proposed that implicit stereotypes likely predict behavior more than explicit stereotypes in domains that are more versus less socially sensitive (e.g., stereotypes about racial groups; Crosby et al., 1980; Dovidio et al., 1997; Fazio et al., 1995) and when the behavior in question is more spontaneous versus controlled (e.g., reactions under time pressure Asendorpf et al., 2002; Devine, 1989; Dovidio et al., 1997; Egloff & Schmukle, 2002; Wilson & Schooler, 2000). However, empirical evidence of these moderators is mixed (Greenwald et al., 2009; Oswald et al., 2013) The question, then, of which pathway(s) will win out over the other(s) is challenging to answer, and likely depends on a multitude of different factors depending on the individual and situation at hand. Therefore, our goal is not to answer all possible questions about these potential moderators, but instead to offer a preliminary investigation into (1) the overall effect of target social class on trust among Canadian university students and US and UK online study participants using two paradigms, and (2) how well this effect aligns (both conceptually and 17 statistically) with explicit dispositional stereotypes, explicit situational stereotypes, and implicit stereotypes. Overview of Dissertation Research In all chapters, all sample sizes, data exclusions and analyses were pre-registered unless otherwise specified. Chapter Two presents Studies 1-4, a set of pre-registered studies focusing on how social class influences trust in morality via explicit dispositional and situational stereotypes; Appendix A provides supplemental information for Chapter Two, including five supplemental studies (three pre-registered). These studies use the trust game, the behavioral measure of trust in which participants transfer money (or other resources) to their partner, trusting their partner to return some of those resources back to them. (Participants can choose not to transfer money, or to transfer very little, if they do not expect their partner to return a fair share of the money, so the amount transferred indexes trust.) These studies provide strong evidence that Canadian undergraduates, and US and UK online study participants, trust those with lower social class more so than those with higher social class in an economic game. Study 4 also demonstrates that people do stereotype those with lower social class as being more dispositionally moral, but also more situationally tempted towards immorality, than those with higher social class. However, only this dispositional morality pathway predicts trust. We tested this question among a fairly culturally homogeneous set of participants (though the US, Canada, and the UK obviously differ in many ways, they are all highly individualistic; Hofstede, 1980), and using a single paradigm, which involved controlled, thoughtful decision-making. Thus, this effect may not generalize to participants who are more collectivistic, or to paradigms involving more spontaneous decisions. Chapter Three presents a second set of fifteen studies expanding the scope to consider trust in both morality and competence. These studies use a self-report measure in which 18 participants read a scenario involving trust in either morality or competence, then make repeated decisions about who they would trust between targets differing in social class. This measure has not been validated in previous research, but is more face valid than the trust game, as it directly asks participants who they would trust given the choice between two targets. Our first study in this chapter, Study 5, found results in direct contrast with those from Chapter Two: People trusted those with higher social class more in both morality and competence situations. We first attempt to resolve this contradiction in Studies 6A-6F by testing possible moderators that could explain the different findings from Chapters Two and Study 5, with limited success. We next attempt to resolve the contradiction by developing a measure of implicit stereotypes across Studies 7A-7G. Using the measure we developed across those studies, Study 8 demonstrates that though people explicitly report that they perceive lower-class individuals as more moral than higher-class individuals, their implicit associations show the opposite pattern, and predict responses in the morality trust scenarios. Chapter Four discusses the findings from Chapters Two and Three. We speculate on why these findings were not resolved, discuss how different elements of social class may influence trust in different directions, and outline the impact of this work for considering the complexity and nuance of social class stereotypes. 19 Chapter Two: Trust in Morality Based on Explicit Social Class Stereotypes Chapter Two Overview Chapter Two focuses on testing the link between social class and trust in morality using a behavioral measure of trust with material resources at stake. It also tests whether this link can be explained by explicit social class stereotypes about dispositions and situations. When material resources are at stake, people’s beliefs about personal character versus situational constraints may lead to opposing impulses regarding whether to place more trust in those with lower versus higher social class. If people focus on dispositional qualities, they may trust lower-class others more; if they focus on situational constraints, they may trust higher-class others more; if they focus on both equally, there may be no difference. Existing research provides inconsistent evidence with respect to these possibilities. We do not examine implicit stereotypes until Chapter Three, but if we are correct in proposing that people implicitly associate low social class with immorality, and if this is what drives people’s trust decisions, we would expect people to trust higher-class others more. In other words, implicit dispositional stereotypes would lead to the same pattern as explicit situational stereotypes. Four published studies have measured trust behavior while manipulating something related to the trustee’s social class (Brülhart & Usunier, 2012; Lindqvist & Björklund, 2017; Lount & Pettit, 2012; Qi et al., 2018). These studies all use the trust game (Berg et al., 1995), in which the potential trustee has a material incentive to betray the truster. As summarized in Table 1, these existing studies each contain methodological limitations (e.g., power below 30%, lack of experimental realism) that yield inconclusive results and/or limit their ability answer the question of how others’ social class influences trust decisions. Table 1 Summary of previous research investigating how target social class affects trust. 20 Brülhart & Usunier, 2012 Lindqvist & Björklund, 2017 Qi et al., 2018, Study 2 Lount & Pettit, 2012, Study 3 Who participants trusted more? No difference No difference Higher-status targets Lower-status targets Study’s power to detect d=.20? 25% (N=169, between-subjectsa). 29% (N=198, between-subjects) 20%b (N=33, within-subjects) 16% (N=92, between-subjects) Social class manipulated directly? No (in-study starting endowment). Yes (target’s occupation and self-rated status). Yes (target’s income). Yes (prestige of target’s university). Other features limiting the study’s utility in answering our question N/A Participants could punish targets (might change how they make trust decisions) Experimental non-realism (participants interacted in real time in-lab with 67 partners, who could not plausibly have been real). N/A aThis N represents observations from 69 participants who provided one observation (i.e., for them, the study was between-subjects) and another 50 who provided two observations (i.e., for them, the study was within-subjects). Following the study’s analyses, our power calculation treated all observations as between-subjects. bUsing G-power’s default assumption that the within-subjects measurements are correlated at .5). To test this question, Chapter Two reports four pre-registered studies powered to detect effects as small as d = .20 with 88% power on average (total N = 1,494); additional data from five studies (three pre-registered) reported in Appendix A (total N = 906) provide further consistent evidence of the basic effect of target class on trust. In Study 1, Canadian undergraduate participants played the trust game with targets who varied in social class. Study 2 replicated Study 1 findings in a sample of adults from the United Kingdom and used a new manipulation of target social class to rule out alternative explanations. Studies 3 and 4 again replicated the primary findings, while extending them to an additional behavioral measure of trust (Study 3) and to trust scenarios beyond the trust game (Study 4). Study 4 also tested our theorized rationale through explicit stereotypes, comparing the respective roles of explicit stereotypes of dispositional versus situational morality, and manipulated the magnitude of the 21 situational temptation to examine whether situational factors ever play a role. All studies received ethics approval. In principle, trust decisions could also vary with people’s own social class: There could be a main effect on trust (e.g., because lower-class people face more interpersonal threats and therefore have lower generalized trust; Brandt et al., 2015; Fischer & Torgler, 2013; Fiske et al., 2012) or an interaction with trustee’s social class (e.g., because people tend to trust ingroup members more than outgroup members; Balliet et al., 2014; Falk & Zehnder, 2007; Foddy et al., 2009; Romano et al., 2017). In all studies we report analyses testing these possibilities. For each study, we report how we determined our sample size, all data exclusions, all manipulations, and all measures in the study. All studies in the main text, and three of the five studies reported in Appendix A, were pre-registered. All materials, pre-registrations, data, and analysis code are available online at https://osf.io/q84z6/?view_only=805bf0a9c1284db6881d0141d524d657. Study 1 In this within-subjects study, undergraduate participants played four rounds of the trust game: Three in the role of truster with key targets (one with lower social class, one with higher class, and one control target), and one in the role of trustee with a filler target (whose social class was mid-range), to allay suspicion. We conveyed the targets’ social class using realistic, handwritten profiles that contained hints of family wealth or poverty. We also ensured participants believed these fictional targets were actually in the lab with them, for example, by having research assistants repeat instructions aloud in adjacent (but actually empty) cubicles. This study was pre-registered (https://osf.io/7m59n/?view_only=fdb501a828f544b69e45c2994e6c9533); we planned to test 22 whether people trusted lower-class targets more (presumably due to dispositional inferences), or higher-class targets more (presumably due to inferences about situational constraints, though this could also be explained by implicit stereotypes). We also planned to explore moderation by participant social class, with no directional predictions. Method Participants. We collected data from 200 undergraduates, aiming for 80% power to detect a within-subjects effect of d = .20. We excluded 15 participants who, at the end of the study, failed to notice the obvious class difference between the high- and low social class targets on an attention check asking them to indicate, while they still had targets’ profiles in front of them, whether each had “lower to middle class” or “middle to upper-class”. We also excluded seven participants who were suspicious that they were not actually interacting with other people. Our final sample of 178 provided 76% power (close to our target 80%); see Table 2 for demographic characteristics for this and all other studies. Table 2 Demographics for participants in each Chapter Two study. Study Variable 1 2 3 4 N after exclusions 178 549 187 580 Power for d = .20a 76% >99% 78% >99% Class ladder M (SD) 6.48 (1.32) 5.10 (1.71) 6.57 (1.15) 5.04 (1.64) Range 3-10 1-10 3-9 1-9 % with (parental)b income in CAD < $50K 22 43 21 47 > $50K & < $100K 38 39 38 36 > $100,000 39 18 42 17 % with (parental)b education no college degree 20 44 20 40 2- or 4-year college degree 42 41 46 40 postgraduate degree 38 15 34 20 % women 65 64 67 51 % men 34 35 33 49 % another gender 1 1 1 1 23 age M (SD) 20.30 (2.25) 35.76 (12.75) 20.45 (3.42) 41.39 (14.24) % selecting ethnicity White 22 89 22 88 East Asian 48 1 53 3 South Asian 14 4 13 5 Black 2 3 2 2 Another ethnicity 14 3 10 2 Note: We included other ethnicity options and more fine-grained income and education options but present these coarser groupings for brevity. a Under GPower’s default assumption that within-subjects measurements are correlated at .5). b For Studies 1 and 3, income and education are parental, as all participants were students. Procedure. Participants came into the lab for a study about how limited information affects impression formation and economic decision-making. They learned that they and four other participants—the targets—would play four rounds of an economic game in rotating pairs. First, they completed a two-section paper-and-pencil profile and learned that for each person in their group either zero, one, or both sections would be shared with other members. The targets’ profiles contained our critical manipulation of social class (see below); participants filled out their own profile only to ensure experimental realism. After participants completed their profiles, the computer indicated that zero of their sections would be shared with the group; when the experimenter entered the room they noted this information and redacted all participants’ answers with a black marker before taking the profile to be photocopied. Having participants’ own profiles remain hidden from the targets ensured that participants’ trust decisions would not be influenced by what they believed their partners knew about them. After having ostensibly made photocopies, the experimenter returned and gave the participants copies of four bogus target profiles, redacted to varying degrees (see Figure 1). Participants then learned the rules of the economic game, read the targets’ profiles, and played the game with each target in turn. Following this, they completed open-ended suspicion 24 questions, demographic questions about the targets and themselves, and the attention check described above. Finally, participants were debriefed and compensated.1 Target Social Class Manipulation. Each of the four target profiles included neither, one or both of two sections: one with short answers and one with long answers. For the three key targets, those with whom participants were assigned to be the truster, the profiles contained our manipulation (control, lower-class, and higher-class; see Figure 1 and Table 3): both sections redacted (i.e., no information conveyed) for the control target, and complementary sections redacted for the lower- and higher-class targets (e.g., if they saw the short answers for the higher-class target, they saw only the long answers for the lower-class target; allowing us to counterbalance across participants which target answered which questions). For the filler target (included to deflect suspicion, with whom participants were assigned the trustee role), there was no information redacted and the profile conveyed middle class. Figure 1 Example of one combination of lower- and higher-class target profiles participants viewed. 1 We also assessed various items as exploratory mediators. However, none of these items (e.g., “To what extent did you want to show respect for this person?”; “Assuming that you had given some or all of your tickets to this person, how upset would you be if they decided not to give back any of your tickets?”) measured dispositional or situational inferences about the target, as our theoretical rationale evolved over time. For brevity we report analyses on these exploratory measures in Appendix A. 25 Table 3 Profiles used to manipulate target social class, Study 1. Question Control response Lower-class response Higher-class response Filler response Short answer section What are some of your hobbies? (always redacted) Soccer, watching movies, reading. Soccer, watching movies, reading. Cooking, hiking, basketball. Do you have a part-time job? (always redacted) Yeah I work at McDonalds, I’m trying to start paying off my student loans. No, my parents are paying my tuition, I’m trying to focus on school. Not right now. Have you won any awards at [university]? (always redacted) Last year I got a student athletic award. Last year I got a student athletic award. Nope. What do your parents do for a living? (always redacted) My dad is a construction worker & my mom works at a daycare. My dad is a software engineer & my mom is a corporate lawyer. My dad is an accountant and my mom is a nurse. Where was your last vacation? (always redacted) Grandparents’ house (had to work all break so couldn’t really go anywhere). Grandparents’ vacation home in Italy. Camping with a couple friends. Long answer section 26 How was your experience in high school? (always redacted) Okay I guess, I went to a public school in kind of a sketchy area, but I liked my teachers a lot. Okay I guess, I went to a private school in a nice area, and I liked my teachers a lot. Pretty good, I’m still close with a few of my friends from high school. What are your main goals for the year? (always redacted) I want to earn enough money to support myself and maybe start paying off my student loans. I want to earn enough money to support myself, so I want to start by interning at my mom’s law firm. Get good grades in all my classes, start going to the gym more and eating healthy. Why did you choose to attend [university]? (always redacted) It’s close to where my parents live and had a couple of programs I was really interested in. It’s close to where my parents live and had a couple of programs I was really interested in. I really like the campus, and [city] in general. What did you do over the winter break? (always redacted) Stayed with my cousins (had to work during the break so couldn’t really go anywhere). Stayed with my cousins at their vacation home in Italy. Went home to visit my family. What’s a fun fact about yourself? (always redacted) I have the same birthday as my mom and 2 of my cousins! I have the same birthday as my mom and 2 of my cousins! I got my appendix taken out when I was 12 years old. Notes: Participants saw either the italicized responses with the bolded responses redacted, or vice versa. Black responses contain the social class signals; neutral responses appear in grey. Trust Game. Participants learned the standard rules of the trust game: One person (the truster, labeled “Person A”) started with 10 raffle tickets to a draw for two $100 Amazon gift cards, and could transfer any number of those tickets to the other person (the trustee, labeled “Person B”). The transferred tickets would then be tripled, and the trustee could decide to return any number of those tickets back to the truster. Participants had to correctly answer three comprehension questions before moving on to ensure they understood the game. Our dependent variable was trust, quantified as the number of tickets the truster transferred to the trustee (M = 4.63, SD = 3.17, range = 0-10). 27 For the three rounds on which participants learned they had been randomly selected to be “Person A” (the truster), they received three packets color-coded to match the control, higher-class, and lower-class targets’ profiles. Each packet contained 10 raffle tickets and two envelopes labelled “tickets to keep” and “tickets to give to Person B”. The experimenter left the room while the participant placed their tickets into the envelopes according to their trust decisions. Demographic Questions About Targets. Participants answered demographic questions about the lower- and higher-class targets as a manipulation check; these questions were not present for the filler and control targets. We asked participants to: “Please guess the correct answers to the following questions about the person whose profile is highlighted in [YELLOW / GREEN]” (corresponding to the color-coded higher- and lower-class profiles). The key question assessed perceptions of targets’ social class, embedded among questions about their gender, ethnicity, and age (see Appendix A for exact text). Participants indicated where each target would fall on a ladder with 10 rungs if the bottom rung represents people who have the least money, least education, and worst or no jobs, and the top rung represents people who have the most money, most education, and best jobs (e.g., Adler et al., 2000; Adler & Ostrove, 1999). Our manipulation was successful: Participants rated the higher-class target higher on the ladder (M = 8.02, SD = 1.01) than the lower-class target (M = 4.64, SD = 1.32, t(177) = 29.76, p < .001). Participant Social Class. To measure participants’ objective social class, we took the highest level of education achieved by either parent, standardized this, and summed it with standardized parental income. These indices were only weakly correlated (r = .19, p = .012), but we nevertheless report analyses using this composite measure as pre-registered; results do not differ if we examine income and education individually. To measure participants’ subjective 28 social class, we had them reported their own position on the ladder measure described above (e.g., Adler et al., 2000; Adler & Ostrove, 1999). Results Pre-Registered Analyses. We ran two multilevel regression models using the lmerTest package in R (Kuznetsova et al., 2017); see Table 4. In Model 1, we predicted trust (number of tickets transferred) from target class (lower-class, higher-class, or control; dummy coded with lower class as the reference group), subjective participant class (centered), and random intercepts for participants. In Model 2, we added the interaction terms between the target class dummy codes and participant class. In both models we also included as a covariate which version of the manipulation participants saw (effect coded as 1 = short answer section for the lower-class target and long answer section for the higher-class target, -1 = the reverse)2. We then re-ran both models replacing subjective participant class with objective class, yielding four models in total. Table 4 Multilevel regression analyses predicting trust, Study 1. Predictor Model 1 (no interactions) Model 2 (interactions) b SE t p b SE t p Models with participant subjective class Intercept (lower-class target) 5.16 .24 21.88 <.001 5.16 .24 21.87 <.001 Control target -.84 .18 -4.75 <.001 -.84 .18 -4.74 <.001 Higher-class target -.70 .18 -3.96 <.001 -.70 .18 -3.95 <.001 Profile combination condition .38 .21 1.77 .079 .38 .21 1.76 .079 Participant subjective class (centered) -.04 .16 -.25 .802 -.09 .18 -.52 .602 Control target × participant class .10 .13 .71 .478 Higher-class target × participant class .06 .13 .47 .638 Models with participant objective class Intercept (lower-class target) 5.19 .24 22.01 <.001 5.19 .24 22.00 <.001 Control target -.85 .18 -4.76 <.001 -.85 .18 -4.74 <.001 Higher-class target -.71 .18 -3.96 <.001 -.71 .18 -3.95 <.001 Profile combination condition .35 .21 1.67 .097 .35 .21 1.67 .097 Participant objective class (centered) -.10 .14 -.70 .488 -.10 .16 -.63 .529 2 We pre-registered including this variable as a random intercept. However, these models did not converge, perhaps because of the estimation problems that can come from random effects with very few levels (e.g., Crawley, 2002; Hodges, 2014); we therefore included it as a fixed effect instead. 29 Control target × participant class .04 .12 .37 .709 Higher-class target × participant class -.04 .12 -.36 .722 Note: Rows containing the key hypothesis test are bolded. All four models revealed that people trusted the lower-class target (M = 5.15, SD = 3.08) more than the higher-class (M = 4.44, SD = 3.23, d = .27) and control (M = 4.30, SD = 3.14, d = .36) targets respectively (all d-scores are calculated without covariates). The difference between the higher-class and control targets was not significant (b = .14, SE = .18, p = .429, d = .07). There were no main effects of, or interactions with, participant subjective or objective class. Exploratory Analyses. In analyses that were not pre-registered, we explored whether the social class manipulation affected other perceptions about the targets (see Appendix A for measures). It did: Unexpectedly, participants also judged the higher-class target to be younger, and more likely to be male and White (see Table 5). These inferences parallel the reality that social class is correlated with a host of demographic features, including race and gender (e.g., Graf et al., 2021; Kochhar & Cilluffo, 2018), but these unintended effects indicated the need for additional analyses to confirm that effects in our pre-registered analyses were driven by perceived social class, not other confounded factors. Table 5 Participants’ guesses of targets’ demographics. Demographic variable Target social class Difference between targets Low High Social class: M (SD) 4.64 (1.31) 8.03 (1.01) t(177) = 29.76, p <.001 Gender: % male 53 82 McNemar’s χ2(1) = 30.24, p <.001 Ethnicity: % Whitea 69 83 McNemar’s χ2(1) = 9.19, p =.002 Ethnicity: % Asiana 25 15 McNemar’s χ2(1) = 5.49, p =.019 Age: M (SD) 20.13 (1.17) 19.88 (1.07) t(176) = 2.80, p =.006 Notes: a Other ethnicity categories were selected too infrequently to analyze. 30 For this reason, we ran additional exploratory analyses (see Table 6). The social class effect persisted in a model that included the target’s perceived gender (dummy coded so 1 = male, 0 = female), age (mean-centered), and ethnicity (two dummy coded variables for the most commonly used categories; 1 = White, 0 = all other ethnicities, and 1 = East Asian, 0 = all other ethnicities) as covariates. However, when we added perceived social class (mean-centered) to this model as an additional covariate, this new variable showed a significant negative effect, and the effect of the social class manipulation became non-significant. These exploratory analyses increase our confidence that participants’ greater trust in the lower-class target came from how the manipulation changed their perceptions of the targets’ social class, not other perceived demographics. Table 6 Multilevel regression analyses showing effect of (manipulated) target social class on trust holds controlling for perceived age, gender, and ethnicity, but not perceived social class, Study 1. Predictor Model without perceived target social class Model with perceived target social class b SE t p b SE t p Models with participant subjective class Intercept (lower-class target) 5.44 .73 7.43 <.001 6.67 .93 7.19 <.001 Higher-class target -.70 .22 -3.12 .002 .13 .45 .28 .778 Profile combination condition .32 .22 1.46 .147 .31 .22 1.43 .155 Participant subjective class -.06 .16 -.35 .729 .01 .17 .04 .972 Perceived gender: man -.27 .29 -.93 .351 -.27 .29 -.95 .341 Perceived age .16 .14 1.22 .223 .15 .13 1.11 .268 Perceived ethnicity: White -.14 .70 -.20 .838 -.23 .70 -.33 .745 Perceived ethnicity: Asian -.01 .75 -.02 .987 -.12 .74 -.16 .876 Perceived class -.25 .12 -2.12 .035 Models with participant objective class Intercept (lower-class target) 5.47 .73 7.46 <.001 6.67 .92 7.24 <.001 Higher-class target -.70 .22 -3.12 .002 .11 .44 .25 .803 Profile combination condition .29 .22 1.35 .178 .29 .22 1.32 .188 Participant objective class -.14 .14 -.95 .344 -.12 .14 -.84 .401 Perceived gender: man -.27 .29 -.93 .355 -.27 .29 -.93 .355 Perceived age .18 .14 1.32 .187 .16 .14 1.22 .224 Perceived ethnicity: White -.14 .70 -.20 .838 -.22 .70 -.31 .757 Perceived ethnicity: Asian -.02 .75 -.03 .975 -.12 .74 -.16 .874 Perceived class -.24 .12 -2.10 .036 31 Note: Continuous variables are mean-centered; categorical variables are dummy-coded. Rows containing the key hypothesis test are bolded. These models do not include data for the control target because participants did not rate the control target’s demographics. Discussion In Study 1, participants trusted the lower-class target significantly more than both the control target and the higher-class target in a situation where financial resources were on the line. This study has key strengths compared to past research that has yielded mixed results. Our study used a pre-registered sample and design that had nearly triple the power of any previous study (see Table 1). It also used the trust game in its most straightforward form, and directly manipulated target social class using casual statements that people might realistically share with one another in conversation (e.g., discussing recent vacations). The low suspicion rate (3.5%) indicates that participants indeed found this manipulation believable. This initial finding does not align with situational stereotypes or implicit dispositional stereotypes, suggesting instead that explicit dispositional stereotypes might be the most important driver of trust based on social class of the three pathways we considered. People trusted the lower-class target more than the higher-class target, even though the lower-class target is more in need of the resources traded in this study (a chance to win an Amazon gift card) and people might therefore have suspected them of being more tempted to abscond with any raffle tickets they received, and even though they might have had negative implicit views of this target’s morality. Study 4 (and to some extent Study 3) tests the role of explicit dispositional stereotypes directly, but first Study 2 tested the replicability of our findings using a different population and a different manipulation of social class. 32 Study 2 Study 2 (pre-registered at https://osf.io/p5zjr/?view_only=9262f9268b2143f99ab2506b1862f6ea), sought to further replicate the core finding from Study 1 using a cleaner social class manipulation. Study 1’s target profiles dropped hints to their wealth, which could have manipulated perceptions besides social class (e.g., that the higher-class target was an arrogant braggart). To eliminate this potential confound, Study 2 conveyed social class via targets’ income, a more objective, less loaded cue. Study 2 also employed a different population of participants and targets. Study 1’s targets were university students, and so even the lower-class one was perceived as closer to middle class (M = 4.64 on the 10-rung ladder); this could have weakened situational inferences about financial constraints. That is, participants may have believed that these upwardly mobile mid-to-lower-class university targets would be less tempted to betray a peer’s trust for material gain, compared to a lower-class target from the broader community. Participants themselves also had relatively high social class (see Table 2), and sharing a university affiliation with targets might have elevated feelings of trust beyond what we might expect between most strangers. Thus, to ensure that results would generalize more broadly, Study 2 drew from an online population with a larger range of social class and no obvious shared social identity with targets. Finally, Study 2 manipulated experimental realism by having some participants play ostensibly real economic games with real partners and others play hypothetical economic games with fake partners. We included this manipulation after noticing a methodological difference between past studies: Our Study 1, like Lout and Pettit (2012), used highly realistic designs and obtained similar findings. In contrast, Qi and colleagues (2018) used a less realistic paradigm (participants played the trust game in a lab with 67 other people; many must have doubted all 33 these people could have been present in the lab with them simultaneously) and obtained the opposite finding (that people trusted higher-class individuals more). It therefore seemed possible manipulating realism would help reconcile these prior results; we ultimately found it had no effect. Method Participants. We pre-registered collecting data from 600 UK participants recruited through Prolific Academic. This sample size provides over 99% power to detect a within-subjects effect of d = .20 (testing whether people place different degrees of trust in a lower- versus higher-class target) and about 70% power to detect a between-subjects effect of d = .20 (e.g., testing whether real versus hypothetical condition affects the difference in trust towards the higher-class target minus the lower-class target). In total, 603 participants completed the study. We excluded 10 participants who were suspicious that the targets were not real, and 16 who failed an attention check about the rules of the trust game (“If Person A gives £0.05 to Person B, what would Person B receive? A) £0.05, b) £0.10, c) £0.15 [correct response], d) £0.20, e) £1.50”). We also excluded 30 participants who failed to notice the difference between the higher- and lower-class targets (participants indicated where they thought each target fell on the social class ladder while the targets’ profiles were displayed on-screen, and passed the check if they indicated that the lower-class target was below the higher-class target on the ladder). This remaining sample of 549 participants provides >99% power for a within-subjects effect of d = .20, and about 65% power for a between-subjects effect of d = .20. The sample was indeed more diverse in terms of participant social class than Study 1, with nearly double the proportion of low-income participants; see Table 2. 34 Procedure. Overall, Study 2 followed a very similar procedure to Study 1, online instead of in the lab, with participants again assigned to play the trust game as truster with three key targets and as trustee with a filler target. We describe differences between the studies below.3 Experimental Realism Manipulation. Participants were randomly assigned to either the real condition, where they made consequential decisions in games with actual partners, or the hypothetical condition, where they imagined that the study was real, but viewed instructions clearly indicating the game was hypothetical, their partners were not real, and their decisions would have no consequences. Target Social Class. We used different profiles that manipulated social class using only targets’ income (similar to Qi et al., 2018, who reported increased trust in higher-class targets); see Figure 2. The lower-class target’s family income was listed as “£10,000-£20,000” (a range that includes the UK poverty line; Department for Work & Pensions, 2019) and the higher-class target’s family income was listed as “Above £150,000” (which is above the 97th percentile in the UK; Department for Work & Pensions, 2019). This manipulation was successful, and increased the range of perceived target social class relative to Study 1: Participants rated the higher-class target much higher on the social class ladder (M = 8.23) than the lower-class target (M = 3.52, t(602) = 63.85, p < .001). For participants in the real condition, the filler target (with whom participants thought they would play the role of trustee) was a real other participant with whom they had an online conversation for five minutes using Chatplat, an instant-messaging platform embedded into the survey. We included this target and the real chat conversation to ensure that participants believed 3 As in Study 1, we included several items as exploratory mediators (e.g., “How similar do you think you are to this person?”), but none measured dispositional or situational inferences about the target. We therefore cannot use them to test our theoretical rationale; we nonetheless report analyses using these items in Appendix A. 35 they were really interacting with other participants in this study; participants in the hypothetical condition only imagined having this conversation with their fourth partner. Participants read all four targets’ profiles at the same time, on the same screen (see Figure 2). Figure 2 Example of target profiles participants viewed, Study 2. Notes. As in Study 1 we also provided filler information; we counterbalanced which income was paired with what filler information, so some participants viewed the pairing depicted here, while others saw a low income paired with the filler information in the top left quadrant and a high income paired with the filler information in the bottom right quadrant. We also counterbalanced 36 whether participants viewed the control target depicted here, or one who was a 20-year-old female. To help participants remember the four different targets, each was paired with a cartoon avatar: The filler target was always a fish or dolphin; the other three targets were a sheep, bird, and turtle, with target pairings counterbalanced across participants. The top right quadrant is what participants in the real condition viewed; those in the hypothetical condition viewed instructions telling them to imagine having a conversation. Trust Game. The trust game was similar to Study 1, but participants played for money, not raffle tickets. Participants began their rounds as truster with £0.50 per round and could transfer any amount to the trustee in increments of £0.05. Participant Social Class. Participants answered the same questions as in Study 1 for subjective social class, income and education, except participants reported their own income (in pounds) and education rather than their parents’ because they were not students. Results We ran multilevel models predicting trust with target social class (dummy coded with the lower-class target as the reference), experimental realism condition (effect coded: 1 = real, -1 = hypothetical), their interaction, and random effects for participants; see Table 7. We also included pre-registered covariates: one effect coded variable indicating the profile version of the higher- and lower-class targets, a second effect coded variable indicating the version of the control target, and a third effect coded variable indicating the targets’ avatars. Because none of these covariates had effects approaching significance (all bs < |.01|, all ps > .282), we omit them from the table for brevity. Table 7 Multilevel regression analysis predicting trust, Study 2. Predictor b SE t p Intercept .33 .007 44.97 <.001 Control target -.04 .005 -7.03 <.001 Higher-class target -.05 .005 -8.48 <.001 Experimental realism .00 .007 .68 .495 Control target × experimental realism .00 .005 .73 .468 37 Higher-class target × experimental realism .01 .005 .98 .328 Note: Rows containing the key hypothesis test are bolded. Even though Study 2 used less loaded and more extreme information about target social class, non-student targets, and non-student participants with a wider social class range, we found robust effects replicating our previous findings: Similar to Study 1, participants trusted the lower-class target with about 10% more of their initial endowment compared to the higher-class (d = .31) and control (d = .35) targets, with no difference between the higher-class and control (b = .01, SE = .005, p = .141, d = .07) targets. There were no effects involving the real vs. hypothetical manipulation. Next, we examined whether these effects were moderated by participants’ subjective or objective social class by adding participant social class (centered) and all its interactions to the same models (full results are available in Appendix A). No two-way interactions with participant subjective or objective social class approached significance, all bs < |.005|, all ps > .298. However, there was a small main effect of participant objective (but not subjective) social class on trust, b = .010, SE = .005, p = .030, such that those with higher objective class were more trusting across targets, perhaps because they were more willing to risk losing the money (Grable, 2000). Study 2 measured personal, rather than parental, income and education, and as we noted the sample varied more widely in their objective social class (see Table 2). The increased range and personal relevance of objective social class, as well as the increased power for between-subjects effects in this larger-sampled study, may explain why the effect of participant class emerged only here and in Study 4 which both used large non-student samples (but not in Study 1 or 3, which both used smaller student samples). 38 Discussion Study 2 again found that participants trusted a lower-class target significantly more than a higher-class target. This result emerged even though Study 2 differed from Study 1 in its target social class manipulation (objective information about income vs. statements hinting at one’s level of affluence), target status (non-student vs. student), and sample (adults vs. undergraduates). Notably, Study 2 sampled from a culture (British) known historically for being more classist than North America (Gerteis & Savage, 1998; Robinson & Kelley, 1979). Supplemental Studies A1.1-A1.3 replicated the finding among adults in the United States using the same objective social class manipulation with non-student targets and participants; see Appendix A. Theoretically, these findings further hint that people trust others whom they believe to be good people, even when they might suspect those others have situational temptations to betray them, and even when they might implicitly associate those others with low morality. In this study, participants knew that the lower-class target had a low income, and may even have lived below the poverty line. Even with this knowledge, participants preferred to trust that target over the higher-class target with their money. Studies 1 and 2 assessed behavior in the trust game, which is specifically designed to measure trust (Berg et al., 1995), but is vulnerable to an alternative interpretation: Perhaps participants did not trust the lower-class target more, but rather simply preferred to give that partner more money or raffle tickets, because of the lower-class target’s presumed higher need. Studies 3 and 4 replicate the effect on trust game behavior, while also including additional trust-related measures that are less vulnerable to this alternative explanation. 39 Study 3 Study 3 had university students play the trust game; we pre-registered (https://osf.io/xmtp5/?view_only=ca64396c67ea4ee5b15390a4c8d8ae1c) that we would replicate the pattern from Studies 1-2. We included exploratory measures of stereotypes of the targets’ warmth and morality, to test our theoretical account of dispositional inferences guiding trust. We also included a secondary measure of trust-related behavior: the prisoner’s dilemma game (Axelrod, 1984). In the prisoner’s dilemma, two people simultaneously choose whether to cooperate or defect. If both cooperate, both receive a moderately high payout; if both defect, both receive a moderately low payout; if one defects and the other cooperates, the defector receives a very high payout while the cooperator receives a very low or even no payout. In a prisoner’s dilemma game, deciding to cooperate requires trust, because it does not make sense to cooperate if you distrust your partner and suspect they will defect, leaving you with the worst possible outcome (Chaudhuri et al., 2002; Deutsch, 1958). Like in other trust decisions, people may consider whether their partner is the type of person to cooperate, as well as whether the situation will tempt their partner to defect. However, unlike the trust game, the trusting response (cooperating) does not involve giving financial resources to the target, making the alternative explanation of generosity less plausible. Choosing to cooperate in the prisoner’s dilemma also requires being trustworthy, because the most individually profitable response is always to defect. This feature makes the prisoner’s dilemma a less pure measure of behavioral trust, which is why we pre-registered it as a secondary measure, but it also makes it mirror many real-life scenarios. For example, when 40 hiring a babysitter, you trust them to care for your child and not steal your jewelry, and they trust you to return home at the appointed time and to pay them fairly for their work. Method Participants. As in Study 1, we pre-registered collecting data from 200 undergraduates. Once we examined the data, we realized that a new exclusion criterion we included was far more potent than expected: Nearly half the sample failed to read a block of text telling them to ignore the question at the bottom of the screen and instead select “other” and type a phrase, leaving us with only 117 participants. This unexpectedly small sample replicated the effects we found in Studies 1-2; nevertheless, to get closer to our originally projected sample size, we collected data from an additional 172 participants for a total of 372 participants, 187 after exclusions. Significance levels are consistent regardless of which sample we use (all 372 vs. the original 200) or how we apply exclusions (no exclusions vs. all pre-registered exclusions vs. all but the new overly potent one); see Appendix A for details. The results we report here follow all our pre-registered exclusion criteria (the overly potent one, n = 163; failing to correctly perceive the difference between the higher- and lower-class targets as in Study 1, n = 54, expressing suspicion that the targets were not real, n = 8; some exclusions were overlapping), but maximize power by using all available datapoints that meet these criteria. The resulting sample of 187 participants offered 78% power for detecting within-subjects effects of d = .20, close to our target 80%; see Table 2 for demographics. Procedure. This study followed a procedure similar to Study 2, again including a manipulation of experimental realism (though as in Study 2, this variable did not moderate the effect of target social class), but used the target social class manipulations from Study 1. We describe other differences in the procedure below. 41 Target Social Class Manipulation. Participants completed the survey at an appointed time. In the real condition, participants believed they had been scheduled at the same time as their three partners while those in the hypothetical condition simply imagined this. Based on the findings from Studies 1-2, we dropped the control target, so participants were introduced to the two key targets (lower- and higher-class), through profiles identical to those used in Study 1. Although no participants were actually scheduled in groups of four, they were scheduled in pairs; as in Study 2, pairs in the real condition acted as each other’s filler targets and chatted via instant messaging, whereas people in the hypothetical condition merely imagined chatting. We again measured perceived target social class as in Studies 1-2, but included questions about other estimated attributes (e.g., hair color, personality, favorite hobby) to mask our interest in social class. The manipulation was successful (higher-class target M = 8.17, lower-class target M = 4.82, t(186) = 33.60, p < .001). Trust Game and Prisoner’s Dilemma. To prevent participants worrying that their choices in one game would affect their partner’s choices in the subsequent game, we told them no game outcomes would be shared until all decisions were made. That is, all participants would make prisoner’s dilemma decisions and any decisions as Player A (in counterbalanced order), then participants with any Player B role(s) would learn of their Player A’s decision and respond, and only then would participants learn the outcomes of all rounds of both games. The trust game was identical to that in Study 1, except participants allocated tickets using a dropdown menu in the online survey rather than by placing physical tickets into envelopes in the lab. As in Studies 1-2, the experiment ended after participants had made their Player A and prisoner’s dilemma decisions, so they did not need to make a trust game decision regarding the filler target, with whom they had the role of Player B. For the prisoner’s dilemma game, 42 participants learned that if both partners cooperated, they would both receive 6 tickets for the gift card raffle; if both defected, both would receive 2 tickets; and if one defected while the other cooperated, the defector would receive 10 tickets and the cooperator would receive 0 tickets. The trust game and prisoner’s dilemma game were correlated at r = .41, p < .001, suggesting they measure related but not identical constructs. Participant Social Class. We measured this identically to Study 1. Mediators and Moderators. Participants answered exploratory mediation questions about the lower- and higher-class (but not filler) targets, including measures of the targets’ dispositional warmth and morality. None of the items assessed situational inferences, the warmth and morality measures consisted of a single item each, and Study 3 was not pre-registered to test for mediation, so even though they showed promising results, we did not think them robust enough to rely on, and summarize them only briefly below (but provide full details in Appendix A). Study 4’s more comprehensive and pre-registered mediation analyses will allow for stronger inferences. Results Primary DV: Trust Game Behavior. We ran a multilevel regression model in which we predicted the number of tickets participants transferred to each target in the trust game with target class (effect coded so 1 = high, -1 = low), experimental realism (effect coded so 1 = real, -1 = hypothetical), their interaction, profile combination condition and random intercepts for participants; see Table 8, leftmost columns. Similar to Studies 1-2, participants trusted the lower-class target with about 7% more of their initial endowment (d = .22) than the higher-class target. As in Study 2, this was not moderated by whether people were actually or only imagining playing with another player. Models including participant social class and its interactions with 43 target class and condition revealed no additional effects. Across all models, the only significant coefficient supported our prediction: Participants trusted the lower-class target with more tickets than the higher-class one. Table 8 Multilevel regression analyses predicting trust in the trust game and cooperation in the prisoner’s dilemma game, Study 3. Predictor Trust game Prisoner’s dilemma game b SE t p OR SE z p Models without participant class Intercept 5.47 .22 24.98 <.001 .97 .21 4.55 <.001 Target class -.29 .11 -2.65 .009 -.28 .14 -2.04 .042 Profile combination condition -.12 .22 -.56 .576 .09 .18 .48 .633 Experimental realism .00 .22 .02 .986 .28 .18 1.50 .135 Target class × experimental realism .18 .11 1.63 .104 .06 .14 .46 .649 Models with participant subjective class Intercept 5.48 .22 24.93 <.001 .98 .21 4.55 <.001 Target class -.29 .11 -2.65 .009 -.28 .14 -2.04 .042 Profile combination condition -.11 .22 -.51 .612 .09 .18 .53 .597 Experimental realism -.00 .22 -.01 .990 .24 .18 1.33 .184 Participant subjective class .15 .21 .72 .471 .33 .17 1.91 .056 Target class × experimental realism .18 .11 1.63 .105 .06 .14 .42 .677 Target class × participant class -.02 .10 -.21 .844 .08 .13 .65 .517 Experimental realism × participant class -.15 .21 -.71 .480 -.14 .17 -.81 .419 Target class × experimental realism × participant class .04 .10 .35 .725 .01 .13 .11 .910 Models with participant objective class Intercept 5.47 .22 24.97 <.001 .98 .21 4.57 <.001 Target class -.29 .11 -2.65 .009 -.28 .14 -2.01 .045 Profile combination condition -.13 .22 -.61 .543 .09 .18 .48 .631 Experimental realism -.01 .22 -.03 .973 .28 .19 1.49 .137 Participant objective class .19 .14 1.38 .168 .03 .11 .25 .804 Target class × experimental realism .18 .11 1.60 .112 .06 .14 .45 .655 Target class × participant class .05 .07 .67 .505 .02 .09 .27 .790 Experimental realism × participant class -.04 .14 -.29 .773 -.13 .11 -1.11 .268 Target class × experimental realism × participant class .02 .07 .22 .829 -.05 .09 -.56 .574 Note: Rows containing the key hypothesis test are bolded; we did not analyze prisoner’s dilemma decisions with the filler target. Secondary DV: Prisoner’s Dilemma Behavior. We ran similar but logistic rather than linear regressions to test our secondary measure, prisoner’s dilemma decisions (0 = defect, 1= 44 cooperate); see Table 8, rightmost columns. Results paralleled the trust game findings: Participants cooperated more with the lower-class target than the higher-class target. Mediation Analyses. Exploratory (not pre-registered) mediation analyses reported in detail in Appendix A show that people stereotyped the lower-class target as warmer and more moral than the higher-class target, and that this in turn predicted greater trust (in the trust game) and cooperation (in the prisoner’s dilemma game) toward the lower-class target; both indirect effects were significant. Discussion As in Studies 1-2, participants trusted lower-class individuals more than higher-class ones, this time in two separate trust-related behavioral games. The effects on prisoner’s dilemma behavior help rule out an alternative explanation—that people prefer to give more financial resources to lower-class others. In the prisoner’s dilemma game, the trusting response (cooperation) does not involve giving anything directly to the target. In Supplemental Study A2, described in Appendix A, we replicated this pattern of trust behavior in another context that did not involve giving money to trustees: a trust game where the transferred resource was not money, but credits that allowed participants to leave the study early. In sum, using well-powered experiments with different sampling strategies, different manipulations of social class, and different behavioral measures of trust, the results from Studies 1-3 provide consistent evidence that people trust lower-class individuals more than lower-class individuals. Study 4 follows up on the preliminary evidence from Study 3 that explicit dispositional judgments might mediate these effects, while also investigating a parallel situational pathway. 45 Study 4 In addition to replicating the basic effect from Studies 1-3, Study 4 (pre-registered at https://osf.io/xyvw3/?view_only=28975ee27e0e442caba8da4dec720b82) had four goals. First, to provide a more direct test of people’s explicit dispositional versus situational focus in these trust decisions, Study 4 added measures of explicit dispositional and situational inferences to the hypothetical trust game procedure from Study 2. We hypothesized people would see the lower-class target as both more dispositionally moral and more situationally tempted than the higher-class target, and that the former inference would be more strongly associated with trust decisions. We pilot-tested these measures, and obtained similar results, in Supplemental Study A3; see Appendix A. Second, Study 4 manipulated the strength of the situational temptation, both to provide a causal test of the situational pathway to trust and to examine a potential boundary condition. Our previous studies involved only small incentives to betray (i.e., raffle tickets or small amounts of money), which may have minimized the situational temptation; this could be why participants attended more to dispositional cues, and consistently trusted the lower-class target over the higher-class one. Thus, Study 4 examines whether people weigh their perceptions of a person’s situational vulnerability to temptations more heavily in the face of a stronger temptation. Third, in addition to the trust game, Study 4 included a scenario-based trust measure to provide convergent validity for our findings. The economic games we used in our prior studies are useful because they capture real consequential trust behavior (Pisor et al., 2020) that also predicts trust toward strangers in everyday life (Weiss et al., 2021). Nonetheless, these types of economic games are artificial, contrived situations that may not always relate to how people behave in less controlled real-world settings (Baumard & Sperber, 2010; Galizzi & Navarro-46 Martinez, 2019). Study 4’s scenario-based measure thus is a good companion to the trust game measure, with the two offering complementary pros and cons. Fourth, as an explicitly exploratory goal, Study 4 also investigated the relational models people might assume the targets hold. We speculated that people might stereotype lower-class individuals as more likely to hold communal sharing or equality matching relational models (A. P. Fiske, 1991, 1992), a dispositional inference about cognitive representations rather than about personal character. We also assessed two other relational models, authority ranking (attending to who outranks and has power over whom), and market pricing (ensuring that one gets from a relationship in proportion to one’s contributions), speculating these more independent models might be seen as stereotypical of higher-class individuals. Method Participants. We collected data from 600 UK participants recruited through Prolific Academic. This sample size provides >99% power to detect a within-subjects effect of d = .20, about 70% power to detect a between-subjects effect of d = .20 (e.g., testing whether temptation condition affects the difference in trust towards the higher-class minus the lower-class target), and over 80% power to detect indirect effects composed of small (β = .14) a and b paths for the mediation analyses (Fritz & MacKinnon, 2007). We excluded 20 participants who failed the same attention check about the rules of the game from Study 2 (modified for those in the high-temptation condition so it referred to the correct amounts for their higher-stakes game), leaving a final sample of N = 580. This final sample has >99% power for within-subjects effects of d = .20, about 67% power for between-subjects effects of d = .20, and about 80% power to detect indirect effects. We had also planned to exclude participants who failed to perceive the difference between the higher- and lower-class targets, but inadvertently left this check out of the final 47 survey. This likely makes the test more conservative than we had intended, as our sample included any participants who did not catch our social class manipulation. Procedure. This study had three parts. In part one we measured mediators, in part two participants played the trust game (following the hypothetical condition from Study 4), and in part three they completed the new trust scenarios. Parts two and three featured independent manipulations of the temptation to betray (i.e., participants could view any possible combination of high vs. low temptation version of the trust game and high vs. low temptation version of the trust scenarios). Part One. Participants first read the four target profiles from Study 2 (lower-class, higher-class, control, and filler). Next, in counterbalanced order, they completed mediator measures about the lower- and higher-class targets (but not the filler or control targets), asking about their explicit dispositional morality and their situational vulnerability to temptations (prior to any temptation manipulation or learning about any trust measures). Table 9 provides exact items and measure reliabilities. The moral disposition measure included items similar or identical to those used in past research (Brambilla et al., 2013; Landy et al., 2016). The situational temptation measure included three items we created to measure the targets’ situational temptation towards immorality. Finally, participants rated the targets’ relational models using a shortened version of the relational models scale (Haslam & Fiske, 1999; Simão & Seibt, 2014). Table 9 Mediator items, Study 4. Construct (α) Items Moral disposition (αlower-class = .96, αhigher-class = .96) How MORAL is this person?: How PRINCIPLED is this person?; How HONEST is this person?; How SINCERE is this person?; How ETHICAL is this person?; Are they a GOOD PERSON? Situational temptation (αlower-class = .90, αhigher-class = .82) This person’s situation would tempt them to steal, lie or cheat; Because of this person’s situation, they might have to do unfair or immoral things; This person’s situation might tempt them to prioritize their own gain over others’ well-being 48 Communal sharing (αlower-class = .88, αhigher-class = .88) This person would “give the shirt off their back” for others; “What’s mine is yours” is true of their relationships; This person would cancel plans to help someone else; “One for all and all for one” is true of their relationships Equality matching (αlower-class = .74, αhigher-class = .67). Their relationships are organized on a 50/50 basis; If one of you does something for the other, the other tries to do the same thing in return next time; If they share something, they divide it down the middle; They more or less keep track of favors and obligations Authority ranking (αlower-class = .86, αhigher-class = .89). They expect some people to be entitled to more; They expect one person to direct the work, while others pretty much do what they are told; They expect one person to be the leader; the other loyally follows their will; They expect some people to be above others in a kind of hierarchy Market pricing (αlower-class = .71, αhigher-class = .78). They expect people’s outcomes to be directly proportional to how much they put in; They prefer to divide things up according to how much each person has paid or contributed; They make decisions according to the ratio of the benefits they get and the costs; They expect to get the same rate of return on their effort and investment that other people get Part Two. Next, participants learned the rules of the trust game. For those randomly assigned to the low temptation condition, the rules were identical to Study 2: The truster (participant) started with £0.50 each time, so even if they decided to transfer the full £0.50 to the trustee, the trustee could only leave the study with £1.50 by betraying the participant and taking all the money for themselves. For those randomly assigned to the high temptation condition, the truster (participant) started with £500 each time, so if they decided to transfer the full £500 to the trustee, the trustee could instead leave the study with £1500 by betraying the participant. Participants then played the hypothetical trust game. Part Three. Finally, participants completed the scenario measure of trust. In pilot testing (see Supplemental Study A3 in Appendix A), we designed four scenarios measuring trust. Two of these showed the predicted effect, so we used those here. (We dedicate the next chapter of this dissertation to understanding why the other two did not show the predicted effect). For each of the two that did show the predicted effect, we created a low-temptation and a high-temptation 49 version, yielding four vignettes in total; see Table 10 for vignette text. We randomly assigned participants to view one of these four vignettes (i.e., the low- and high-temptation vignette version was independent of the low- versus high-temptation trust game manipulation). Participants then viewed the same lower- and higher-class target profiles from the trust game in part one and indicated which person they would trust. Table 10 Vignettes for high and low temptation trust situations, Study 4. Vignette text: unhighlighted text indicates consistent across conditions; [blue highlight indicates low temptation only]; [yellow highlight indicates high temptation only] On the way home from work today, you realize you left a message open on your computer where you complained about your boss to a friend. You know your boss would not be happy to see that message[, and they’re about to hand out leads for a couple of very big nearly guaranteed sales that will get big commissions for the employee who closes the deal. If your boss sees your nasty message, they will probably give the leads (and thus the commissions) to your coworkers and not to you]. Two of your coworkers are still at work. You decide to ask one of them to log out of your computer for you before your boss sees. You know whoever you choose could instead show your boss, expose your rudeness, and get themselves into your boss’s good graces, so you want to make sure to make the right decision. If these two people from the economic game were your two coworkers, which one would you ask to log you out? Your work team entered a lottery for charity to win a [weekend trip to a nearby lake ($20 value)][all expenses paid, two week long tropical vacation ($10,000 value)], and you won! Unfortunately you didn’t realize that the trip is actually only for one person, so your team is currently on a group phone call trying to decide who should get the trip. You decide it would be fairest to just flip a coin – but now you have to choose who flips the coin. You know that whoever flips the coin could just lie and say they won the flip and take the trip for themselves, so you want to make the right decision. If these two people from the economic game were your two coworkers, which one would you choose to flip the coin? Results Trust Game Behavior. To make trust responses comparable between the two temptation conditions, we recoded participants’ responses so that they represented the percentage of the participants’ starting endowment. We predicted this variable in a multilevel model with target social class (two dummy variables: 0 = low, 1 = high; 0 = low, 1 = control), temptation condition 50 (-1 = low, 1 = high), their interaction, and random intercepts for participants; see Table 11. We also included the same covariates as in Study 2; because none of these covariates had effects approaching significance (all bs < |.01|, all ps > .288), we omit them from the table for brevity. To obtain the simple effects of target social class within each temptation condition, we also re-ran this model with both possible dummy codings for temptation. Table 11 Multilevel regression analyses predicting trust, Study 4. Effect type Contrast b SE t p Main effect Lower- vs. upper-class target -13.14 1.06 -12.42 <.001 Lower-class vs. control target -5.01 1.06 -4.74 <.001 Low vs. high temptation condition -4.41 1.37 -3.21 .001 Interaction Lower- vs. upper-class target × temptation 0.03 1.06 0.03 .976 Lower-class vs. control target × temptation 0.64 1.06 0.61 .542 Simple effects: Low temptation Lower- vs. upper-class target -13.17 1.48 -8.89 <.001 Lower-class vs. control target -5.66 1.48 -3.82 <.001 Simple effects: High temptation Lower- vs. upper-class target -13.11 1.51 -8.70 <.001 Lower-class vs. control target -4.37 1.51 -2.90 .004 Note: Rows containing the key hypothesis test are bolded. Our confirmatory predictions pertained to the low temptation condition, represented by the rows in Table 11 labelled “Simple effects: Low temptation”. Replicating our previous findings, in this condition participants trusted the lower-class target with about 13% more of their initial endowment compared to the higher-class target (d = .40), and about 6% more of their initial endowment compared to the control target (d = .23); both effects were significant. Also, participants trusted the control target with significantly more of their endowment than the higher-class target, d = .32, b = 7.51, SE = 1.48, t = 5.07, p < .001; we also found this pattern in Study A3 (see Appendix A) but no other study. The temptation manipulation had a main effect (d = -.29): Overall, people trusted targets with a smaller proportion of their endowment when they could reasonably assume the targets’ temptation to betray would be higher. This indicates that participants did attend to our temptation 51 manipulation. However, this manipulation did not moderate the effect of target: Participants trusted the lower-class target more than the higher-class and control targets, and to a similar degree, regardless of the size of the financial incentive for targets to betray this trust. Next, we examined whether these effects were moderated by participant subjective or objective social class by adding participant social class (centered) and all its interactions to the same models. We did not pre-register this analysis as previous studies found few effects of social class, but present it here for comparison with other studies. Again, no two-way interactions with participant subjective or objective social class approached significance, all bs < |1.53|, all ps > .249, and neither did any three-way interactions with participant class, target class, and temptation condition, all bs < |.64|, all ps > .330. However, as in Study 2, there was a small main effect of participant objective (but not subjective) social class on trust, b = 3.57, SE = 1.54, p = .021, such that those with higher objective class were more trusting across targets. In Studies 2 and 4, participants who personally had more objective resources were more willing to trust (perhaps because they are less concerned with losing a portion of their ample resources); we did not find these effects in Studies 1 and 3, where our younger participants reported on their parents’ resources. Trust Scenarios. Next, we used chi square tests to examine whether participants trusted the lower-class target over the higher-class target in the trust vignettes we presented, and whether this differed if the vignette described a situation with low versus high temptation to betray trust. Results replicated those using the trust game. Overall, 73% of participants trusted the lower-class target over the higher-class one, significantly different from chance (50%), χ2(1) = 121.99, p < .001. This effect did not differ based on the temptation condition, χ2(1) = 0.37, p = .541: In the 52 low and high temptation conditions respectively, 74% and 72% trusted the lower-class target over the higher-class one. These effects were consistent across both vignettes. Mediation: Primary Analysis of Moral Dispositions and Situational Temptation. Table 12 presents the correlations and descriptive statistics for our primary mediators; the direction and magnitude of relationships were similar for both lower- and higher-class targets. Table 12 Correlations and descriptive statistics for mediators. Correlations for ratings of low SES target below diagonal; correlations for ratings of high SES target above diagonal; means (SDs) in rightmost columns (subscript L = lower-class target; subscript H = higher-class target) 1. 2. 3. 4. 5. 6. ML (SDL) MH (SDH) 1. Morality -.48*** .60*** .49*** -.12** .09* 4.84 (0.82) 4.17 (1.00) 2. Situational temptation -.33*** -.35*** -.29*** .18*** -.01 3.51 (1.30) 3.31 (1.38) 3. Communal .46*** -.16*** .61*** -.35*** -.07 4.48 (0.84) 3.44 (1.02) 4. Equality .44*** -.12** .55*** -.02 .20*** 4.58 (0.70) 3.96 (0.90) 5. Authority -.01 .16*** -.04 .10* .43*** 4.15 (1.01) 5.01 (1.10) 6. Market .15*** -.02 -.02 .25*** .25*** 4.35 (0.88) 4.72 (1.00) Note. † p < .10, * p < .05, ** p <.01, *** p < .001 Mediation of trust game decisions. We tested whether participants explicitly viewed the lower-class target as both more dispositionally moral and more situationally tempted towards immorality than the higher-class target (the a links), whether these two mediators predicted trust in the trust game (the b links), and whether these b links differed based on temptation condition; see Figure 3 (see Appendix A for similar results from additional pre-registered models testing the mediation model in each condition separately). We used the lavaan package in R (Rosseel, 2012) to estimate this multilevel moderated mediation model, with each variable nested within participants. Our pre-registered plan included moderation of the b links only, because we wondered whether people’s perceptions of the targets’ situational vulnerability to temptation would play a larger role when the temptation itself was stronger. The mediator items themselves appeared before the temptation manipulation and were phrased in general terms rather than tailored to the specific scenario; therefore the temptation manipulation could not moderate the a 53 links—participants’ perceptions of the targets’ general dispositions, or of their general vulnerability to temptations due to their financial situation. Figure 3 Testing the theorized pathways between social class, moral disposition and situational temptation, and trust, moderated by temptation condition; Study 4. This analysis revealed results consistent with our theorizing: Considering first the dispositional pathway, as in Study 3, participants explicitly reported thinking that the lower-class target had a more moral disposition, and this strongly predicted their trust decisions. These effects were of similar magnitudes in the two temptation conditions, and did not differ significantly based on condition, interaction = -2.50, SE = 1.70, p = .142 (though as noted above, participants were less trusting overall when the financial temptation to betray was larger). Considering next the situational pathway, results were more nuanced. As expected, participants thought the lower-class target’s situation might make them more vulnerable to temptation than the higher-class target. However, this situational inference was not related to 54 their trust decisions when there was only a small financial incentive to betray trust. When we raised the stakes, the association was larger, but was only marginally significant, and less than a quarter of the size of the association with dispositional inferences. Moreover, the difference in these associations by condition was not significant, interaction = -1.34, SE = 1.21, p = .267. These results suggest that even across a range of financial incentives, people’s trust decisions are much more strongly linked to their perceptions of a potential trustee’s moral disposition than they are to their perceptions of that person’s situation and how it might tempt them towards betrayal. Mediation of Trust Scenario Decisions. These analyses were exploratory (not pre-registered). On the scenario measure, participants made a binary choice between targets, which meant we had to change our analytic approach: We could not examine how explicit ratings of each target’s disposition and situation predicted trust decisions for that target, because participants did not make independent trust decisions for each target. Instead, using logistic regression, we predicted target choice (lower-class = 0; higher-class = 1) from the difference score for each mediator (rating of higher-class target minus rating of lower-class target; mean-centered), temptation condition (1 = high, 0 = low), and their interaction. In this dissertation, when we use logistic regression, we report the log odds ratio rather than the odds ratio for ease of interpretation. Log odds ratios with positive signs represent positive effects (and vice versa for negative signs); if the number’s absolute value is larger, the effect is larger (and vice versa if the absolute value is smaller). Overall, explicitly perceiving the lower-class target as more moral than the higher-class target predicted trusting them more, log(OR) = .43, SE = .11, z = 3.80, p < .001, while viewing the lower-class target as facing more situational temptation predicted trusting them less, log(OR) 55 = -.24, SE = .06, z = -4.01, p < .001, but with an effect of smaller magnitude. The temptation condition here had no significant effect, log(OR) = .05, SE = .21, z = 0.23, p = .819, nor did it moderate the effect of explicit moral disposition, log(OR) = .32, SE = .23, z = 1.41, p = .158, or situational temptation, log(OR) = -.02, SE = .12, z = -0.13, p = .900. Thus, in the trust scenarios, both explicit dispositional morality judgments and situational temptation judgments predicted trust decisions, in opposing directions as predicted. As with the trust game, the effect of explicit dispositional judgments was much larger (in this case almost twice as large) as that of situational judgments. Mediation: Exploratory Analysis of Relational Models. Finally, we ran exploratory models using measures of relational models as mediators in separate models predicting trust in the trust game and the scenarios, running eight models in total (four relational models as mediators, two dependent variables); see Table 13. Given our previous results, we conducted these analyses across temptation condition, but otherwise used models identical to those described above; see Appendix A for analyses examining (and finding no evidence for) moderation by condition. Table 13 Exploratory analyses examining relational models as mediators, Study 4. Mediator DV: Trust game DV: Trust scenarios Class  mediator Mediator  trust Direct effect Indirect effect log(OR) p b p b p b p b CI95 p Communal -1.04 <.001 6.58 <.001 -6.30 <.001 -6.86 [-8.66, -5.05] <.001 .41 <.001 Equality -.62 <.001 6.05 <.001 -9.38 <.001 -3.77 [-5.12, -2.43] <.001 .40 <.001 Authority .86 <.001 -3.58 <.001 -10.09 <.001 -3.06 [-4.41, -1.72] <.001 -.24 <.001 Market .36 <.001 -1.10 .200 -12.75 <.001 -0.40 [-1.03, 0.22] .208 -.04 .578 Note. Total effect is presented in Figure 3 (b = -13.16, p < .001). Target class is coded so 0 = lower-class, 1 = higher-class. 56 Results were consistent across both trust game behavior and scenario ratings. As expected, participants viewed the lower- (vs. higher-) class target as having relational models more based in communal sharing and equality matching, and less based in authority ranking; the effect for market pricing was in the expected direction but not significant. Communal sharing and equality matching positively predicted trust and had significant indirect effects; authority ranking also negatively predicted trust and had a significant indirect effect. Appendix A provides details on an additional exploratory (not pre-registered) mediation model that included all four relational models as well as explicit dispositional morality stereotypes as parallel mediators. In this model, the indirect effects through explicit morality stereotypes, communal sharing models, and authority ranking models were all independent of one another; the effect of morality stereotypes were about twice as large as those for relational models. Discussion Study 4 again replicated the effect of target social class on trust, and for the first time tested whether this effect varied depending on the magnitude of the incentive to betray. Even when this incentive was quite large, people continued to place more trust in the lower-class target than the higher-class target. Additional findings from Study 4 may explain this: Although people explicitly view lower-class individuals as both having more moral dispositions and being more tempted by their situation towards immorality, people attend much more to explicit stereotypes of moral disposition than situational temptation when deciding who to trust. People did attend to the magnitude of the incentive to betray—when temptation was high they trusted less overall, and relied somewhat more on their perceptions of targets’ vulnerability to temptation—but these situational inferences were far outweighed by moral dispositional inferences. 57 All these patterns emerged consistently using a new measure of trust, hypothetical scenarios, suggesting our findings apply more broadly than just to stylized economic games. Everything we report here also replicated in the pilot for this study (see Appendix A Study A3). General Discussion Across four pre-registered studies, as well as five additional studies (three pre-registered) reported in Appendix A, participants were more inclined to trust lower-class individuals with their money compared to higher-class individuals. This held across Canadian undergraduates and more economically diverse samples of British adults, across target social class manipulations involving conversational sentences hinting at their background or direct demographic data, across real or hypothetical trust situations, across low or high temptation to betray trust, and across participants from lower-, middle-, or higher-class backgrounds. Moreoever, the greater trust for lower- (vs. higher-) class targets was partially explained by participants explicitly attributing warmer, more moral dispositions to the lower-class targets. Though participants also believed that lower-class targets were more likely than higher-class targets to be in situations that would make them more vulnerable to temptations to betray trust, this did not lead them to distrust these targets. When we raised the stakes of the trust situation, participants did respond to their partner’s increased temptation to betray, but nonetheless continued to trust the lower-class targets over the higher-class ones. These studies shed light on conflicting findings in the literature. Of the four past studies on this issue (all with power < 30% for d = .20), only one reported the pattern we have observed here (N = 92, Lount & Pettit, 2012). Two others found no difference in trust based on target status (N = 169, Brülhart & Usunier, 2012; N = 198, Lindqvist & Björklund, 2017), and the fourth found that people trust lower-status targets less than higher-status targets (N = 33 within-58 subjects, Qi et al., 2018). Our studies provide the most highly-powered test of this question to date (total N = 2,400 including supplemental studies, with on average 88% power for d = .20), directly manipulated social class rather than some other form of status, were highly believable (as evinced by the low suspicion rates), and did not add any additional features to the trust game. Our findings thus provide a better estimate of the true effect of target social class on trust in the trust game: Participants trust lower-class others more than higher-class others. However, this conclusion is limited to the paradigms we used in this study, and we found some hints that it may differ using a different paradigm. The results we showcase here emerged using two similar economic games, the trust game and prisoner’s dilemma game, and two different self-report hypothetical dilemmas (who to trust not to reveal a social faux pas to a mutual boss with the boss’ positive regard at stake, or to fairly report the outcome of a coin flip with a free vacation at stake). However, two additional hypothetical dilemmas showed different patterns (see Supplemental Study A3): Participants showed no class preference in choosing a treasurer for their club, and preferred a high class target when trusting that a car seller to be honest about the car’s history with accidents. This suggests variations in the trust situation may add nuance to the relationship between target social class and trust that economic games cannot capture. Moreover, Chapter Two examined explicit perceptions of dispositional and situational morality, but Chapter One also proposed that implicit morality stereotypes might affect trust. Chapter Three therefore considers different trust situations and implicit stereotypes, while also extending these findings from trust in morality to trust in competence. Because Chapter Two found little evidence for situational stereotypes as a mechanism underlying trust, we focus on dispositional stereotypes in Chapter Three. 59 Chapter Three: Social Class, Trust in Morality and Competence, and Implicit Stereotypes Chapter Three Overview Chapter Two found robust evidence that people were more inclined to trust lower-class strangers than higher-class strangers with their resources in a trust game, and that this replicated in some trust scenarios but not in others. Chapter Three explores this nuance using a paradigm where participants read hypothetical trust scenarios and make repeated decisions between pairs of targets differing in social class as to who they would trust in the given scenario. Initial results using this paradigm were directly opposite to the general pattern emerging from Chapter Two, so subsequent Chapter Three studies aimed to reconcile the findings using the two paradigms. We tested many theoretically derived moderators that we thought might reconcile these findings, and did find some hints of plausible reconciliations, but ultimately did not find a conclusive answer—and continued to find results generally contradicting those from Chapter Two. These results aligned more with situational social class stereotypes than dispositional ones, but in Chapter Two, we had found little evidence that situational stereotypes predicted trust. We therefore turned to a different potential mechanism that we thought might help explain Chapter Three’s findings: Implicit stereotypes. As outlined in the introduction, implicit stereotypes may diverge from explicit stereotypes. Specifically, though people explicitly stereotype those with low social class as warmer and more moral than those with high social class, here we test the possibility that they also implicitly associate low social class with lower morality. To do so, we develop a novel version of the brief implicit association test (BIAT; Nosek et al., 2014; Sriram & Greenwald, 2009) that measures implicit social class stereotypes, finding that indeed people implicitly associate low social class with lower morality (despite 60 explicit stereotypes to the contrary), and that these implicit associations predict responses to the trust scenarios. An additional goal of Chapter Three is to extend the theorizing and findings in Chapter Two to include trust in competence, rather than solely focusing on trust in morality. As outlined in the introduction, though social psychologists have largely focused on studying trust that others will behave in a moral way, other fields like organizational behavior also examine trust that others will behave competently. This form of trust is likely to be particularly consequential for the target’s financial outcomes: It is hard to imagine hiring someone for a job, promoting them to a higher-tier position, or admitting them to a selective university without considering whether one trusts them to behave in a competent manner. Social class is also strongly tied to stereotypes about competence: People stereotype those with higher social class as more competent than those with lower social class, and this effect size tends to be much larger than that for warmth social class stereotypes (e.g., Durante et al., 2017). This suggests that people will be less likely to trust those with low social class in situations involving trust in competence, with potential consequences for these individuals’ ability to get ahead at work and school, and therefore potential consequences for inequality. Study Overview Study 5 provides the first test of a new paradigm for examining trust in hypothetical scenarios, and finds that people trust those with high social class more than those with low social class in competence scenarios, but also in morality scenarios, contrasting with findings reported in Chapter Two. In fact, this contrast with Chapter Two will be a common theme of Chapter Three; see Table 14 for a summary of methods and results of all studies testing how trust differs based on target social class. 61 Studies 6A-6E test potential moderators of this effect in attempts to reconcile this finding with those in Chapter Two. Then, Studies 7A-7G develop the social class BIAT. Finally, Study 8 provides a pre-registered three-part study in which participants report their explicit stereotypes, complete the BIAT, and finally complete the trust scenarios, with one week between each phase of the study (and with explicit stereotypes and the BIAT phases counterbalanced as the first and second phases; the scenario phase was always last). Table 14 Summary of methods and results of all studies testing the relationship between target social class and trust. Significant positive effect sizes highlighted in green indicate people trusted higher-class targets over lower-class ones; significant negative effect sizes highlighted in blue indicate the reverse; effects with no significant difference in trust based on target class are not highlighted. Study N Country Notable study features DV d 1 178 Canada n/a Trust game -.27*** 2 549 UK Experimental realism manipulation Trust game -.31*** 3 187 Canada Experimental realism manipulation; prisoner’s dilemma DV Trust game -.22** 4 580 UK Temptation manipulation; mediation by explicit stereotypes; hypothetical only Trust game -.43*** Scenario: work faux pas -.67*** Scenario: coin flip -.43*** A1.1 147 US Lower-quality data Trust game -.16† A1.2 130 US Lower-quality data Trust game -.09 A1.3 160 US Lower-quality data; hypothetical only Trust game -.13† A2 173 Canada Played for time, not money/raffle tickets Trust game -.27*** A3 296 UK Mediation by explicit stereotypes; hypothetical only Trust game -.30*** Scenario: work faux pas -.59*** Scenario: coin flip -.39** Scenario: treasurer -.06 Scenario: used car .31* 5 152 Canada n/a Scenario: train station .70*** 6A 154 Canada Student manipulation Scenario: doctor’s office -.05 6B 151 US Stakes manipulation Scenario: doctor’s office -.11 6C 142 US Benefit to target manipulation Scenario: babysitting .52*** 6D 147 US Potential for future interaction manipulation Scenario: doctor’s office -.01 6E 166 UK Legality of betrayal manipulation Scenario: care for plants/pet .24** Scenario: used car .51*** 6F 124 US Deliberation time manipulation Scenario: train station .47*** 7F 162 Canada Measured BIAT and explicit stereotypes Scenario: train station 1.27*** 62 7G 129 Canada Measured BIAT and explicit stereotypes Scenario: train station 1.11*** 8 138 UK Measured BIAT and explicit stereotypes separated by 1-week intervals Scenario: train station .75*** Notes. For studies that had between- and/or within-subjects manipulation(s) (e.g., high vs. low temptation; objective information only vs. objective and about-me information), we collapsed across conditions to obtain the overall effect sizes. All effect sizes were calculated without covariates. We used formulas provided by Sánchez-Meca and colleagues (2003) and the website https://www.escal.site/ to convert from log odds ratios to Cohen’s d. Participants from Canada were undergraduate students at UBC; participants from the US were recruited from Amazon’s Mechanical Turk; participants from the UK were recruited from Prolific Academic. *** p < .001, ** p < .01, * p < .05, † p < .10 Study 5 This pre-registered study (https://osf.io/26ba5/?view_only=97839e911d80448ab377aa424ba12ba2) was the first to use our new scenario method. Participants completed 32 trials, in each case indicating who they would trust of two targets who differed in social class. They made these decisions for two trust scenarios in sequence (16 trials per scenario), one involving morality and the other, competence. Based on Chapter Two results, we pre-registered as a confirmatory hypothesis that people would trust the lower-class target more than the higher-class target in the morality scenario. As an exploratory question, we planned to explore whether this effect was weakened, eliminated, or reversed when trust instead involved competence rather than morality. We pre-registered two additional exploratory questions. First, within-subjects, we manipulated whether targets’ social class was provided only through objective information such as income and education, compared to if the targets’ descriptions also included an “about me” sentence that revealed their social class. We asked whether targets who explicitly discussed their social class would evoke different responses than targets about whom social class information was merely available to participants. For example, an upper-class target who shows off their wealth may seem less trustworthy than one who simply is wealthy but does not brag about it. A 63 lower-class target who discusses their poverty may seem desperate, and potentially more likely to betray one’s trust – or, they might seem more open and honest, and less likely to betray one’s trust. We therefore did not pre-register specific hypotheses about this manipulation. Second, in this study and in Studies 6A-6F, we pre-registered tests of three potential moderators of the effect of target social class on trust: (1) participants’ own social class, (2) explicit social class stereotypes of competence and morality, and (3) attributions for social class – that is, beliefs in whether social class is caused by internal factors like hard work or poor financial planning versus external factors like being born into a wealthy family or bad luck (e.g., Kallio & Niemelä, 2014; Zucker & Weiner, 1993). We did not make specific predictions about these moderation effects. Because only moderation by social class stereotypes is relevant to our theoretical rationale, we summarize those results here and the others in Appendix B. Method Participants. We pre-registered collecting data from 200 undergraduate students; 203 participated, providing 6,596 trials. We excluded those who failed two or more of six comprehension questions about the trust scenarios (see below; n=10), those who spent less than two seconds on average across trials (n=0), those who, for more than 13 of the 16 trials for each scenario, consistently chose the target that appeared on either the left or the right side of the screen (the side of the screen on which targets appeared was randomized; n=5), and those who failed the following attention check (n=43): Research in decision making shows that people, when making decisions and answering questions, prefer not to pay attention and minimize their effort as much as possible. Some studies show that over 50% of people don't carefully read questions. if you are reading this question and have read all the other questions, please select the box marked 'other' and type 'person perception'. Do not select "first impressions". Thank you for participating and for taking the time to read through the questions carefully!  First impressions  Demographic characteristics 64  Decision making  Other (please specify): _________________ We also discarded data from individual trials that participants completed in under one second (n=80 trials). Some exclusions were overlapping. The final sample included 4,830 trials from 152 participants (116 women, 36 men, 0 non-binary; M age = 20.41, SD = 4.18; 88 Asian, 2 Black, 3 Hispanic, 1 Indigenous, 44 White, 21 another ethnicity [participants could select multiple options]). Procedure. Participants learned that the study would be about first impressions and how people make decisions based on those first impressions. Then, they read a scenario that involved either trust in morality or trust in competence (counterbalanced across participants). To encourage participants to vividly imagine it, we asked them to write four words describing how they would feel in this scenario. They then completed 16 trials: For each one, they saw the scenario on-screen alongside two targets, and chose which target they would trust in that scenario. After completing all 16 trials, they answered three comprehension checks about the scenario. Participants then completed the same procedure with a second scenario, involving either trust in morality or trust in competence (whichever one they had not yet seen). At the end of the survey, they indicated their attributions for social class, explicit social class stereotypes, and demographics (see Appendix B). Materials. Scenarios. The morality scenario asked participants who they would trust to watch their suitcase at a train station while they went to the bathroom; the competence scenario asked who they would trust to give a presentation on their behalf at work: Morality scenario: You are sitting at a train station on your way back from helping your parents clean out their house. You have a heavy suitcase full of papers with you. The 65 papers are extremely important, they are irreplaceable and confidential legal and medical documents and that kind of thing. You realize that you really have to go to the bathroom, but it would be too annoying to drag the heavy suitcase with you. Another train has just pulled into the station, so you know the platform is about to be full of people and there’s a chance your suitcase could get stolen. These two people are sitting beside you. Which one do you ask to watch your suitcase for you? Competence scenario: You are supposed to give a big presentation at work today of an overview of all the marketing pitches your company has been using for the past year. Unfortunately, you are sick and won’t be able to attend. Presentations like this don’t happen very often at your company, so this is a really big deal. On a conference call with two of your coworkers, they ask you who should give the presentation on your behalf. Although you don't know these coworkers very well, because they only started working at your job recently, you know both of your coworkers want you to succeed, and each one would help you out to the best of their abilities. You also know your boss will hold you responsible for the presentation, so if it’s done poorly, your boss will probably fire you. These two people are your coworkers. Which person do you choose to give the presentation for you? We wrote both scenarios to fit the definition of trust: They both involve accepting vulnerability – the possibility that one’s suitcase could be stolen or that the person could flub the presentation (for which one would be held accountable by the boss) – based on the expectation the other person would behave morally (not steal the suitcase or carelessly walk away) or competently (execute the presentation well). In the competence scenario, we specified that both targets were equally motivated, to ensure participants focused primarily on competence, rather than on the possibility that one target might care less, or intentionally seek to undermine them. After each scenario, participants answered three comprehension questions to check attentiveness. The questions were (1) “What would the person you selected have to do?”, (2) “Why were you not able to do this yourself?”, and (3) “What would happen if the person you chose did not do a good job?”; each with four multiple choice options. Targets. We manipulated target social class with 10 different target person descriptions (four low-class targets, four high-class targets, and two control targets); see Table 15. Each target description contained one piece of objective demographic information and one “about-me” 66 statement. For all low- and high-class targets, the objective demographic information always signaled either low or high social class (e.g., income, education, occupation). For half of these targets, the about-me statement also signaled social class (e.g., discussing financial problems, mentioning expensive purchases), whereas for the other half, the about-me statement contained no social class signals. We intended these targets whose about-me statement revealed their social class to be actively displaying their status, akin to the targets in Chapter Two’s Study 2 and 4 who wrote about things like where they vacationed and their parents’ occupations on their profiles. In contrast, those targets whose social class was only revealed through objective information were more akin to the targets in Chapter Two’s Study 1 and 3, where we provided only income, education, or position on the social class ladder. Control targets provided no social class information of either kind. We pilot tested these targets in a separate sample of 151 American MTurkers (77 women, 73 men, 1 preferred not to disclose gender; M age = 40.50, SD = 12.53; 11 Asian, 12 Black, 8 Hispanic, 1 Native American, 234 White, 3 another ethnicity [participants could select multiple ethnicities]). In random order, these participants rated all targets on the social class ladder. Within-subjects t tests verified that all high-class targets were perceived as higher in social class than all control targets, whom in turn were perceived as higher in social class than all low-class targets; see Table 15. On each trial, participants viewed a pair of targets and chose which one they would trust in the given scenario. Each pair was made up of targets from two different social class groups (low, high, control); for low versus high class pairs, the survey always matched which type of information was provided (objective only versus objective and about-me statement). Thus the following six trial types were possible: 67  Low-class vs. high-class: o Low-class, objective-only vs. high-class, objective only o Low-class, objective and about-me vs. high-class, objective and about-me  Low-class vs. control: o Low-class, objective only vs. control o Low-class, objective and about-me vs. control  High-class vs. control: o High-class, objective only vs. control o High-class, objective and about-me vs. control With two targets to represent each social class / description type combination, each of these six trial types existed as four possible pairs of targets, for a total of 24 possible trials. Our focus in this study was the comparison between low and high SES targets, so we presented all eight trials featuring that comparison with the first scenario, and presented all eight again with the second scenario. Of the remaining 16 trials that involved control targets, the survey randomly selected half to present with the first scenario and the other half to present with the second scenario. The order of all trials was randomized, and for each trial the survey randomly allocated which target would appear on the left versus right side of the screen. To help participants imagine choosing between these targets, we paired each description with one of 10 images from the Chicago Face Database (Ma et al., 2015). We selected the 10 White male faces that were rated highest for trustworthiness and had open-mouthed smiling images available. For each participant the survey randomly assigned which image to associate with each description. See Figure 4 for an example trial. Table 15 Target descriptions, Study 5. Social class Information type Description M class rating Low Objective only Objective information: Income: $10,000-$20,000 About me: I like to listen to music and especially like finding out about new bands with good new music. I have a cat named Max who likes me but doesn’t like anyone else. 3.08 68 Objective information: Education: High school degree About me: I spend a lot of time playing basketball with my friends, sometimes we switch it up and play some soccer too. My favorite color is green. 3.68a Objective and about-me Objective information: Occupation: Office assistant About me: I really like to travel but can’t afford to do that very often. On my last break from work I explored some neighborhoods in my city that I don’t usually go to, which was nice. 4.17 Objective information: Income: $20,000-$30,000 About me: This year my goal is to get back in shape, but it’s hard because I can’t really afford a gym membership. So I’ve been trying to spend lots of time playing sports. 3.81a Control n/a Objective information: State: DE About me: Back when I was in school I did a lot of track and field so I’m trying to get back into running. I usually take my dog Rufus with me, he loves it. 4.67 Objective information: Age: 33 About me: This year I’m hoping to get better at playing the guitar, I’ve been practicing a lot. I mostly watch comedy TV shows and movies, don’t like horror movies much. 4.40 High Objective only Objective information: Income: $150,000-$200,000 About me: I like tea more than coffee, usually I drink it with milk and sugar. I’m allergic to peanuts but otherwise I eat pretty much anything. 7.87b Objective information: Occupation: Lawyer About me: I have a cat named Mittens who’s great, except he wakes me up too early in the morning. I like to read novels and listen to music. 7.30 Objective and about-me Objective information: Income: $140,000-$150,000 About me: I enjoy sailing and am hoping to spend more time out on the water this year. I recently got a new boat which I’m excited to try out. 7.75b Objective information: Education: MD and PhD About me: I have two dogs and I usually take them up to my lake house for the summer, they always have fun 8.22 69 swimming in the lake. I recently had the whole place rebuilt so now there’s plenty of room. Note. Numbers with the same subscript are not significantly different at p < .05. All others are significantly different. Figure 4 Sample trial, Study 5. Participant Social Class. We assessed objective and subjective class using the same measures as in our previous studies on undergraduates, Studies 1 and 3. Social Class Stereotypes. In counterbalanced order, participants reported their stereotypes about people with high social class (“Imagine a man who is very wealthy, drives a nice car, is highly educated, and lives in a nice neighbourhood.”) and people with low social class (“Imagine a man who has a low income, drives a car that’s not very nice, is uneducated, 70 and who lives in a bad neighborhood.”) on the same two items: “How MORAL do you think this man is likely to be?”; “How COMPETENT do you think this man is likely to be?” (1 = not at all, 7 = very). We calculated two difference scores (high-class score minus low-class score), one for each stereotype dimension4. In line with prior research and Chapter Two results, participants on average stereotyped those with high social class as less moral, t(151) = -2.13, p = .035, Mlow-class = 4.17, SDlow-class = 1.08, Mhigh-class = 3.91, SDhigh-class = 0.98, but much more competent, t(151) = 13.93, p < .001, Mlow-class = 3.45, SDlow-class = 1.11, Mhigh-class = 5.36, SDhigh-class = 1.14. Results For each trial, we coded a choice for the target with the higher class between the two as 1, and a choice for target with the lower class as 0. That is, we coded trials as 1 when a participant chose a high-class target over a control or lower-class target, or chose a control target over a lower-class target, and as 0 otherwise. We began by analyzing only those trials where participants chose between a low-class and a high-class target. A multilevel logistic regression predicted participants’ choices on each trial with situation (dummy coded so 0 = morality, 1 = competence), type of information (dummy coded so 0 = objective and about-me, 1 = objective only), a term for the interaction of situation and type of information, and random intercepts for participants (to account for data being nested within participants). In this model, the intercept provides the test of our confirmatory hypothesis: the log odds ratio when all fixed effects are 0, that is, in the morality scenario, when both objective and about-me information is provided. Next, we ran this same model again but examining only those trials comparing low-class and 4Though we pre-registered combining these into an overall score of the degree to which people followed the typical social class stereotyping pattern (that is, by calculating a difference score of high social class competence stereotypes minus low social class competence stereotypes, and another difference score of low social class morality stereotypes minus high social class morality stereotypes, then averaging the two difference scores), we later realized this would obscure important differences between the morality and competence stereotypes that may map on to our morality and competence scenarios. 71 control targets, and finally for a third time examining only those trials comparing high-class and control targets. These models are presented in Table 16 (see “Models with dummy coding” columns) and Figure 5. Additional models used effect coding (rather than dummy coding) to test main effects of scenario and information type; these models are also presented in Table 16 (see “Models with effect coding” columns). Table 16 Multilevel logistic regression analyses testing who people trust in morality and competence scenarios based on target social class and type of social class information provided. Trial type Predictor Models with dummy coding (intercept tests effect in morality scenario with subjective info included) Models with effect coding (intercept tests overall mean; both variables’ coefficients test main effects) log(OR) SE p log(OR) SE p Low- vs. upper-class (Intercept) 1.26 .14 <.001 1.56 .11 <.001 Scenario type (1=competence) 0.06 .14 .671 .27 .05 <.001 Information type (1=objective only) .05 .14 .702 .27 .05 <.001 Scenario × information .97 .22 <.001 .24 .05 <.001 Low-class vs. control (Intercept) -0.06 1.5 .681 .15 .11 .160 Scenario type (1=competence) -0.85 .19 <.001 -.18 .07 .007 Information type (1=objective only) 0.79 .19 <.001 .64 .07 <.001 Scenario × information 0.99 .27 <.001 .25 .07 <.001 High-class vs. control (Intercept) 0.68 .21 .001 1.37 .18 <.001 Scenario type (1=competence) 1.01 .22 <.001 .52 .08 <.001 Information type (1=objective only) 0.37 .21 .077 .19 .08 .014 Scenario × information 0.03 .31 .914 .01 .08 .914 Figure 5 Probability of choosing the higher-class target in competence and morality scenarios, based on the type of social class information provided. The black line indicates chance (0.5), or no difference between targets based on their social class. 72 Note. Error bars are 95% confidence intervals. The key intercept in the dummy coded models directly contradicted our pre-registered predictions, as did the fact that the bars in Figure 5 are nearly all above chance—that is, they show that people generally favored the higher class of the two targets. In fact, participants never favored the lower-class target in the morality scenario; the only time they trusted the lower-class member of a pair of targets was in the competence scenario, when the about-me statement contained class information, and only when choosing between control and low-class targets. The main effects models generally suggested that people’s preference for higher class targets was stronger when they learned about class purely from objective information. There was not a clear effect of scenario type—the competence scenario did sometimes result in stronger preferences for higher class targets, compared to the morality scenario, but this was sometimes moderated by information type and was not consistent across the different comparisons between high-class, low-class, and control targets. Appendix B reports tests for moderation by social class stereotypes. We found that people who stereotyped high-class targets as more competent and more moral than low-class 73 ones were also more likely to choose to trust those targets. Unexpectedly, both stereotypes operated similarly across scenarios: Stereotyping high-class targets as competent predicted trusting them more in both the competence and morality scenarios, and the same was true for morality stereotypes. Discussion This study found a strong effect in the opposite direction from those in Chapter Two: Participants were much more likely to choose to trust those with high social class over those with low social class, not only in a competence scenario (which we expected) but even in a morality scenario. This is particularly surprising given that these same participants reported explicit stereotypes viewing high-class individuals as more competent but less moral than low-class individuals, and that these explicit stereotypes did predict trust choices. In the next series of studies, we test potential explanations for why results in this study’s morality scenario are so different from Chapter Two’s results. We continue to test parallel effects in competence scenarios, to determine whether these potential explanations also affect trust in competence based on social class. Studies 6A-6F The following studies each use similar methods and find similar results, so we describe them together. All studies were pre-registered:  Study 6A: https://osf.io/6sqj9/?view_only=b4e67239d7ab4c63ae4e719ce08f9478  Study 6B: https://osf.io/axb6q/?view_only=f8bb5cda71f145059d7c0cf098ef6c86  Study 6C: https://osf.io/zfmgc/?view_only=c41496a75d074302b1d9510b4b5a3875  Study 6D: https://osf.io/68taz/?view_only=fa1ced3bfd3e452c9f8eaca80626a300  Study 6E: https://osf.io/8cpdw/?view_only=4ab892d5dca448ecb0554bfda243cac7 74  Study 6F: https://osf.io/qr6za/?view_only=c489c2258d6941d2804acb39fa92ea42 These studies used the same paradigm as Study 5 (including the objective vs. objective and about-me statement manipulation, and including the morality vs. competence manipulation [except Study 6E which instead uses two morality scenarios]). Each one also introduced an additional moderator that we thought might explain the different results using this scenario paradigm compared to the trust game paradigm. (1) Target group identity (Study 6A). In Chapter Two, participants believed they were playing the trust game with someone else with whom they shared at least a superficial group identity: Other students at the same university (Studies 1, 3) or other participants on the same survey platform (Studies 2, 4). In contrast, in Study 5’s morality scenario, participants decided who to trust between complete strangers (people at a train station). Perhaps people trust those from lower social class backgrounds to be moral if they feel a shared sense of identity with them, but are more suspicious of their morality if they are complete strangers. Accordingly, in Study 6A we recruited a student sample, and manipulated whether we described the targets as other students at their university versus strangers. After the fact, we realized this manipulation might influence not only the presence of a shared social identity, but also what kinds of extremes participants were imagining, especially on the lower social class end of the spectrum. When we described the targets as perfect strangers, participants were free to imagine extremely low class targets, such as the homeless, a group that tends to be negatively stereotyped in terms of both competence and warmth (S. T. Fiske et al., 2002), as they might have in Study 5’s morality scenario. When we described them as fellow students, this was much less likely, as we suspect 75 it was in Chapter Two’s studies where the targets were all students or online survey respondents. (2) Stakes (Study 6B). In Chapter Two, most trust decisions were low stakes. People generally played the trust game for a few cents or for raffle tickets giving them the chance to win a gift card. In contrast, in Study 5’s morality scenario participants faced the risk of losing a suitcase full of irreplaceable documents. Perhaps people trust a lower-class individual with something of little consequence (maybe to show that they are not prejudiced, or to benefit the person in need by giving them a few cents or a chance to win a gift card), but a higher-class individual when the stakes are higher. Accordingly, in Study 6B we manipulated the stakes of the trust decision. Chapter Two’s Study 4 found that manipulating the stakes does not influence how people trust higher- versus lower-class targets, but when we conducted Study 6B we had not yet run Study 4. (3) Benefit to target (Study 6C). In Chapter Two, decisions to trust a target benefited that target: They received some material resource they could then return some (or all, or none) of. In contrast, in Study 5’s morality scenario, trusted targets would receive no benefit in exchange for watching the bag. Perhaps people trust lower-class individuals, who are more in need, when trusting will help the trustee (Van Doesum et al., 2017). Accordingly, in Study 6C, we manipulated whether trusting the target would benefit that target or not. (4) Potential future interactions with target (Study 6D). In Chapter Two, participants would never even learn the identity of their partners. In contrast, in Study 5’s morality scenario, participants imagined they would talk to their trusted target, creating the 76 possibility of a continued relationship if both parties desired. Perhaps people trust higher-class individuals more when trusting opens the door to a social connection, which people might want to do if a target has high status, but avoid if they have low status (Bullock, 1995; Li et al., 2014; Lott, 2002). Accordingly, in Study 6D we manipulated whether the scenario involved the potential for interactions in the future with the target or not. (5) Legality of betrayal (Study 6E). In Chapter Two, the targets were perfectly within their rights, legally and within the explicit game parameters, to betray the participant. In contrast, in Study 5’s morality scenario, a target who betrayed a participant’s trust would have committed the crime of stealing their suitcase. Because people stereotypically associate low social class with criminality (Smalarz et al., 2016), perhaps they worry a target with low social class might commit a crime (maybe out of desperation); because people stereotypically associate higher social class with selfish and manipulative behavior (Belmi & Laurin, 2016; Zitelmann, 2020), they instead might worry a target with high class might bend rules and norms, without breaking them, to their own advantage. A pre-registered pilot study (see Study B1 in Appendix B) confirmed these stereotypes: People did indeed expect those with low social class to be more likely to break the law, whereas they expected those with high social class to be more likely to do something unethical but legal. Accordingly, in Study 6E, we manipulated the legality of betrayal. (6) Deliberation time (Study 6F). In Chapter Two, participants had unlimited time to make their trust decisions. In contrast, in Study 5, participants made 32 choices in rapid succession between pairs of targets. Perhaps when people have more time to 77 deliberate, their explicit morality stereotypes of the lower-class targets or their desire to help the lower-class targets more strongly influence their decisions (Dovidio et al., 1997; Li et al., 2014). In contrast, when making faster, more automatic decisions, perhaps people’s implicit preference for higher-class individuals might reveal itself (Horwitz & Dovidio, 2017). Accordingly, in Study 6F we manipulated how slowly and deliberately vs. quickly and automatically people made their trust decisions. We also noted that one difference between the trust game and Study 5 is that the trust game involves real decisions whereas Study 5 is hypothetical. However, Chapter Two found similar results for hypothetical and real versions of the trust game, so this seems an unlikely explanation and we did not test it further in Chapter Three. Method Participants. All studies used the same exclusion criteria as in Study 5; see Table 17 for sample details. In each case, as in Study 5, we pre-registered collecting data from 200 participants (except for Study 6E, where we pre-registered recruiting 300 participants). For MTurk and Prolific studies, we required that all participants come from the United States. For MTurk studies we also required participants to have a minimum 95% task approval rating, have completed fewer than 5000 tasks, and correctly answer three English comprehension questions at the beginning of the survey. Table 17 Demographics and exclusions, Studies 6A-6F. Study 6A 6B 6C 6Da 6E 6F Initial N participants 201 201 202 193 300 191 Initial N observations 6,432 6,432 6,464 6,176 9,600 4,672b Sample Student MTurk MTurk MTurk Prolific MTurk Exclusions: Failed 2+ comprehension checks 23 16 36 4 107 38 78 Spent <2s average across trials 3 5 17 1 5 7c Chose target on same side of the screen >87% of the time 2 4 5 5 0 7 Failed attention check 31 37 27 25 42 24 Discarded trials (completed in <1s) 118 195 661 117 392 n/ac Final N participants 154 151 142 147 166 124 Final N observations 4,894 4,770 4,439 4,179 5,159 2,976 Gender: # women 117 85 73 68 80 58 # men 36 69 69 78 82 65 # another gender 1 1 0 1 4 1 Age: M 20.21 39.05 35.67 36.96 39.05 35.45 SD 2.75 12.16 10.87 10.91 13.04 10.70 Ethnicity: # Asian 100 13 5 9 19 10 # Black 1 14 12 11 18 14 # Hispanic 0 7 7 4 11 5 # Indigenous 1 4 1 2 3 0 # White 49 118 116 127 119 95 # Another ethnicity 8 1 1 1 2 2 Notes. Participants could select multiple ethnicities. a This study had one additional exclusion criterion: Participants answered an additional multiple-choice question after each scenario assessing whether they understood the manipulation about the potential for future interaction. We excluded their responses for any scenario for which they failed this check (morality scenario only n=9, competence scenario only n=30, both scenarios n=15). b This study has fewer trials per participant than other studies because in one condition, participants only completed half the typical number of trials; see methods description below. c This study manipulated decision time. We excluded participants in the short decision time condition if they spent more than 5 seconds on average per trial (n=7); we excluded no participants in the long decision time condition, because the survey forced them to stay on each trial for at least 15 seconds. Procedure. All studies generally followed the procedure of Study 5, including both a morality and a competence scenario, with the following exceptions. Study 6A participants were randomly assigned (between-subjects) to learn that all targets were fellow students at their university, or were strangers who were not university students. Study 6B, 6C, and 6D participants were randomly assigned, for each scenario, to view one of two possible versions of the scenario; in each case the two versions constituted our 79 manipulation of the relevant moderator. For example, in Study 6B, participants saw scenarios that involved either high-stakes or low-stakes decisions. Because this was randomly assigned per scenario, some participants saw two scenarios at the same level of the moderator (e.g., high stakes for both the morality scenario and the competence scenario), while others saw scenarios at different levels (e.g., high-stakes in the morality scenario but low-stakes in the competence scenario). Study 6E participants saw two different morality scenarios, rather than one morality and one competence scenario: one where they chose who they would trust to care for their cat or plants, and one where they chose who they would trust to be honest during a used car purchase (see below for materials). We wrote a legal betrayal and an illegal betrayal version of each scenario, so that the manipulation could be within-subjects: For each participant, the survey randomly assigned participants to see the legal or the illegal version of the care scenario, and the opposite version for the honesty scenario. Study 6F manipulated deliberation time by randomly assigning participants to either the fast or slow condition. In the fast condition, we first familiarized participants with the paradigm and targets, to allow them to make faster decisions in the task. To do so, we asked them first to make 16 judgments between pairs of targets on topics unrelated to trust (e.g., “Which person do you think drinks the most coffee?”). Once participants reached the actual task, we instructed them to make their decisions as quickly as possible, ideally in under five seconds, because we wanted to know their intuitive, gut responses. On each trial they saw a timer counting down from five on each trial (though they could still take more than five seconds). We selected five seconds as the benchmark as this was slightly under the median time per trial (5.8 seconds) in Study 5, so we reasoned this instruction should keep participants at or below the speed of prior participants. 80 In the slow condition, because we wanted to see whether increasing the decision time relative to prior studies would lead participants to be more likely to trust the lower-class targets, we tripled the amount of time they spent per decision by programming the survey to force them to wait at least 15 seconds to submit an answer. In this condition participants made only eight practice judgments (to keep the conditions roughly parallel while ensuring participants in this condition would not become overly familiar with the targets). Once they reached the actual task, we instructed them to make their decisions slowly and thoughtfully, in at least 15 seconds, because we wanted to know their carefully considered decisions. We also told them we would ask them to explain the reasoning behind their choices at the end of the study, to ensure they thought deeply about each choice. To ensure the survey was roughly the same length in both conditions, participants in the slow condition did not view or make any decisions involving control targets, only those comparing low versus high social class targets. Materials. Scenarios. Table 18 presents the full text of all scenarios. These studies used a variety of morality scenarios for generalizability, including trusting someone to hold one’s spot in line at a doctor’s office (Studies 6A, 6B, and 6D), babysit one’s child (Study 6C), care for one’s plants or pet (Study 6E), be honest when selling a used car (Study 6E), as well as a similar train station scenario as in Study 5 (Study 6F). The competence scenarios were either the same work presentation scenario from Study 5 (Study 6A, 6B, 6F) or a new scenario involving trusting someone to be one’s partner in a gameshow that requires competence (e.g., logic puzzles; Study 6C, 6D); Study 6E did not include a competence scenario. We validated all these scenarios except for those used in Study 6E in a pilot study (see Study B2 in Appendix B), confirming that 81 in the morality scenarios, people said they would prefer to choose someone who is moral but not very competent over someone who is competent but not very moral, and vice versa for the competence scenarios. In most studies, we avoided providing participants any information that would indicate the level of any of our moderators except the one that study intended to manipulate. The two exceptions to this rule were Study 6D, which manipulated the potential for future interactions with the target while specifying to all participants the trusted target would benefit from trust, and Study 6F, which manipulated deliberation time while specifying to all participants that the stakes were low. Targets. These studies generally used the same targets as in Study 5 with the following exceptions: In Study 6A, participants in the non-student condition also read explicitly that no targets were students; those in the student condition viewed targets modified to fit the student context (for example, using parental income and education rather than personal income and education as objective social class indicators, and mentioning on-campus jobs, the UBC gym, student debt, and the Vancouver marina in the about-me statements). In Study 6C, participants did not see pictures of the targets, but read that all were in their 30s. In Studies 6D and 6E we used faces of White women from the Chicago Face Database rather than White men, for generalizability. In Study 6E, all references to pets were removed from the targets’ about-me statements and replaced with other generic statements (e.g., “my favorite color is green”), because one of the scenarios in this study involved trusting someone to care for one’s cat. 82 Participant Demographics. Social class measures were the same as in Study 5, except that because Studies 6B-6F had non-student participants, we assessed their own (rather than their parents’) education and income. In Studies 6A and 6B, we also pre-registered examining participants’ political orientation as a moderator (one item, “What is your political orientation in general? 0 = extremely liberal, 100 = extremely conservative); see Appendix B for results. Social Class Stereotypes. These measures were the same as in Study 5, except that Studies 6E and 6F also asked about explicit trustworthiness stereotypes as well as morality stereotypes (using the same wording: “How TRUSTWORTHY do you think this man is likely to be?”), and Study 6D asked only about trustworthiness, not morality. 83 Table 18 Manipulations used in Studies 6A-6F. Study Conceptual moderator Operationalization: Morality scenario Operationalization: Competence scenario 6A Targets’ group identity: Strangers vs. fellow UBC students You are in a crowded waiting room at the doctor’s office / a UBC medical clinic waiting for your number to be called so you can see the doctor. You have already been here for two hours and it seems like it’s probably going to be a pretty long wait, but it’s hard to tell because they aren’t calling the numbers in order. You’re really hungry and want to go to the food court next door to grab something to eat, but you don’t want to potentially lose your chance to see the doctor. If your number was called while you were gone, you’d have to get a new number and probably wait for even longer, which would be kind of annoying, since you had some work you were planning to do later. You decide to ask one of the two people sitting next to you to phone you when your number is called. You hope that whoever you choose won’t instead claim that they had your number all along and take the chance to see the doctor sooner. They aren’t checking people’s numbers when they let them in – it seems like whoever says “Yes, that’s me” when that number is called gets let in, so it would be pretty easy for the person you choose to take your spot. You have a part-time job on a UBC committee along with some other UBC students. You are supposed to give a presentation at work today of an overview of all the work your department / committee has done over the past four months / semester. Unfortunately, you are sick and won’t be able to attend. You are on a conference call with two of your student coworkers, and you can ask one of them to give the presentation on your behalf. Although you don't know these coworkers very well, because they only started working at your job recently, you know both of your coworkers want you to succeed, and each one would help you out to the best of their abilities. However, neither of your coworkers has experience with this kind of presentation. You also know your boss will hold you responsible for the presentation, so if it’s done poorly, your boss will probably be annoyed with you. These two people are your coworkers. Which person do you choose to give the presentation for you? 84 These two people are sitting beside you. Which one do you ask to phone you when your number is called? 6B Stakes: Low vs. high You are in a crowded waiting room at the doctor’s office waiting for your number to be called so you can see the doctor. You have already been here for two hours and it seems like it’s probably going to be a pretty long wait, but it’s hard to tell because they aren’t calling the numbers in order. You’re really hungry and want to go to the food court next door to grab something to eat, but you don’t want to potentially lose your chance to see the doctor. If your number was called while you were gone, you’d have to get a new number and probably wait for even longer, but that’s not too big of a deal because you don’t have any other plans for today, and if you’re being honest you’re kind of enjoying having nothing to do but read your book while you wait / which would really put you in a bind: You absolutely need to see the doctor today, but you also have an important meeting to get to this afternoon that you absolutely can’t miss. You decide to ask one of the two people sitting next to you to phone you when your number is called. You hope that whoever you choose won’t instead claim that they had your number all along and take the chance to see the doctor sooner. They aren’t checking people’s numbers when they let them in – it seems like whoever says You have a meeting at work today, but / You are supposed to give a big presentation at work today of an overview of all the marketing pitches your company has been using for the past year. Unfortunately, you are sick and won't be able to attend. You are supposed to give a short update on how your project is going. You do these updates every week and they're not a very big deal - your boss doesn't go to this meeting, and wouldn't even know if there was no update on your project. Even so, you figure it's worth asking someone to fill in for you. Presentations like this don’t happen very often at your company, so this is a really big deal. You are on a conference call with two of your coworkers, and you can ask one of them to give the update on your behalf. Although you don't know these coworkers very well, because they only started working at your job recently, you know both of your coworkers want you to succeed, and each one would help you out to the best of their abilities. However, neither of your coworkers has experience with this kind of presentation. You also know your boss will hold you responsible for the presentation, so if it’s done poorly, your boss will probably fire you. 85 “Yes, that’s me” when that number is called gets let in, so it would be pretty easy for the person you choose to take your spot. These two people are sitting beside you. Which one do you ask to phone you when your number is called? These two people are your coworkers. Which person do you choose to give the presentation for you? 6C Benefit to target: Benefit vs. no benefit You are looking for a babysitter for your child for about five hours one night this week. Your child is only 4, so would need to be put to bed before you return. After that, the babysitter would just be hanging out in your home for a few hours, waiting for you to return. Unfortunately, your regular babysitter is out of town. You ask around to see if any of your friends know someone who might be willing to watch your child for the night. Two of your friends recommend acquaintances of theirs as people who would be willing to watch your child. You do not know either of the people who your friends recommended, and neither of your friends knows them well either, but you really need someone, so you have to choose one of them. You plan to pay whoever you choose $100 for the babysitting to thank them for doing it on short notice. These are the two people your friends suggested. Which one do you offer money to and ask to watch your child? You are participating in a mock gameshow at your local recreation center with the potential to win some money if you do well. For the next task, which is going to involve some logic puzzles, math questions, and language skills, you have to pick someone from the audience to help you complete it. You are not allowed to choose your friends and family – instead, you have to pick a stranger. Whoever you choose will automatically receive $100 just because you chose them, regardless of how you two perform on the task. If you and this stranger do well on the task, you will personally win $200. If you do not do well, you will have lost the game and lost your opportunity to advance any further in the competition or win any money. These are the two people you have to choose between. You know that both of them would probably prefer to look smart in front of the audience, so they will both be motivated to try hard to do well with you on the task. 86 Which one do you choose to get the monetary reward for being chosen and to work on the task with you? 6D Potential future interactions: No future interactions vs. possible future interactions You are travelling to a different state for a vacation, and unfortunately, you aren’t feeling well. You are in a crowded waiting room at the doctor’s office, waiting for your number to be called so you can see the doctor. You have already been here for two hours and it seems like it’s probably going to be a pretty long wait, but it’s hard to tell because they aren’t calling the numbers in order. You are supposed to go meet your friend nearby for coffee, but you don’t want to lose your chance to see the doctor. You have two $20 Starbucks gift cards in your wallet you got as a reward for being employee of the month at work. You decide to ask one of the two people sitting next to you to phone you when your number is called so you can leave your coffee date if you need to. You plan to give one of the gift cards to this person before you leave for your coffee date, to thank them. You hope that whoever you choose won’t instead claim that they had your number all along and take the chance to see the doctor sooner, although it wouldn’t be that big of a deal if they did, since you don’t have anywhere else to be today. They aren’t checking people’s numbers when they let them in – it seems like whoever says “Yep, that’s me” when that number is called gets let in, so it You are travelling to a different state for a vacation, and for fun, you are participating in a mock gameshow at the local recreation center near your hotel. If you do well in the gameshow you could win some money. For the next task, which is going to involve some logic puzzles, math questions, and language skills, you have to pick someone from the audience to help you complete it. You are not allowed to choose your friends and family – instead, you have to pick a stranger. Whoever you choose will automatically receive $20 just because you chose them, regardless of how you two perform on the task. If you and this stranger do well on the task, you will personally win $40. If you do not do well, you will have lost the game and lost your opportunity to advance any further in the competition or win any money. These are the two people you have to choose between. You know that both of them would probably prefer to look smart in front of the audience, so they will both be motivated to try hard to do well with you on the task. You probably won’t see either of them ever again, since you’re planning to leave this state and go home in a couple of days / You live nearby this recreation center, so there’s a good chance that you might run into these people again, or at least 87 would be pretty easy for the person you choose to take your spot. These are the two people sitting beside you. You probably won’t see either of them ever again, since you’re planning to leave this state and go home in a couple of days / You live nearby this doctor’s office, so there’s a good chance that you might run into these people again, or at least chat with them for a while once you return to the doctor’s office. Which one do you pick to give the gift card to and ask to phone you when your number is called? chat with them for a while after the gameshow ends. Which one do you choose to get the monetary reward for being chosen and to work on the task with you? 6Ea Legality: Betrayal would be immoral but legal vs. immoral and illegal Morality scenario 1: You are looking for someone to take care of your cat / plants while you are away for the week. You would drop off your cat with them and they would take her home for the week. / They would have to come to your place to water the plants every few days. You are concerned with finding someone you can trust to be kind to your cat and make sure all her needs are met / not to steal anything from your place. You decide to ask one of these two people to take care of your cat / plants for you. Which one do you ask? Morality scenario 2: You are buying a used car, and you have two options. Both cars seem to be the same in every way – they are the same make, model, and year, and they both have been well-maintained (with receipts from mechanics to prove it). Both cars also have a dent in the fender so you are worried they might have been in an accident. Both sellers explain away the dent and assure you their car has never been in an accident. In your state, sellers are not required by law to disclose if a car has been in an accident, so if they were lying they would be violating your trust, but not / and breaking the law. These are the two people selling their car. Who do you trust to be telling you the truth about the car’s history? 88 6Fb Deliberation time: fast vs. slow You are sitting at a train station on your way back from helping your parents clean out their house. You have a heavy cardboard box full of papers with you. You realize that you really have to go to the bathroom. It would be too annoying to drag the heavy box with you, and the papers in the box aren’t even important, just some old odds and ends. Still, it feels weird to you to just abandon it while you’re gone, and you don’t really like the idea of someone else rifling through it. These two people are sitting beside you. Which one do you ask to watch your suitcase for you? You have a meeting at work today, but you are sick and won't be able to attend. You are supposed to give a short update on how your project is going. You do these updates every week and they're not a very big deal - your boss doesn't go to this meeting, and wouldn't even know if there was no update on your project. Even so, you figure it's worth asking someone to fill in for you. You are on a conference call with two of your coworkers, and you can ask one of them to give the update on your behalf. Although you don't know these coworkers very well, because they only started working at your job recently, you know both of your coworkers want you to succeed, and each one would help you out to the best of their abilities. However, neither of your coworkers has experience with this kind of presentation. These two people are your coworkers. Which person do you choose to give the presentation for you? a Note that Study 6E included two morality scenarios, rather than one morality and one competence scenario. b Note that the Study 6F manipulation involved changing the amount of time participants spent on each trial, rather than changing the trust scenarios. 89 Results General Analysis Strategy. As in Study 5, we began by analyzing only those trials where participants chose between a low-class and a high-class target. Multilevel logistic regression models predicted participants’ choices on each trial with scenario (dummy coded so 0 = morality, 1 = competence), type of information (effect coded so -1 = objective and about-me, 1 = objective only), the manipulation (effect coded such that -1 = level where we thought people might trust lower more than higher class targets, 1 = level where we thought people might trust higher more than lower class targets; see Table 19 notes), all possible interactions, and random intercepts for participants. Because information type and the manipulation are effect coded, but scenario is dummy coded, the intercept tests participants’ overall preference for the higher-class targets in the morality scenario. The manipulation coefficient answers our key question by testing the simple effect of the manipulation in the morality scenario (the interaction with scenario indicates whether the manipulation has a different effect in the competence scenario). We always code manipulation such that higher numbers indicate conditions where we expected increased trust for the higher-class targets, meaning that our prediction was always that the manipulation coefficient would be positive. We ran these same models two additional times, examining only those trials comparing low-class and control targets, and then only those trials comparing high-class and control targets; see Table 19 and Figure 6. Note that in Study 6E, instead of including a morality scenario and a competence scenario we included two different morality scenarios; the scenario type variable therefore indicates which morality scenario was presented (1=selling a used car; -1=caring for pets/plants). For brevity our discussion of results, as well as Figure 6, focus on comparisons between low- 90 versus high-class targets, and without considering the information type variable; results with control targets and information type are provided in Table 19 for the interested reader. Table 19 Log odds ratios from multilevel logistic regression analyses testing who people trust in morality and competence scenarios based on target social class, type of social class information, and moderators. Trial type Predictor Study 6A 6B 6C 6D 6E 6Fa Low- vs. high-class (Intercept) -.09 -.21 .99*** -.02 .55*** .86*** Scenario type 1.12*** -1.94*** -.16 1.26*** .31*** .53*** Information type .28*** .09 .24*** .18** .31*** .21** Manipulation .18* -.09 -.25* .10 .17** -.18 Scenario × information .08 .12 .15 .56*** .04 -.09 Scenario × manipulation .56*** .68*** .81*** -.26 -.35* .10 Information × manipulation -.21*** -.06 -.20** .04 -.10*** .02 Scenario × information × manipulation .22* .10 .27* -.08 .15** -.07 Low-class vs. control (Intercept) .46*** .43** .73*** .06 .63*** -.04 Scenario type .02 .03 -.76*** .20 .04 .63** Information type .29** .43*** .52*** .13 .26** .71*** Manipulation .01 .10 -.32* .24 .19** Scenario × information .39** .25† .15 .18 -.06 -.46* Scenario × manipulation -.18 .15 .55** -.55* -.08 Information × manipulation -.02 -.07 -.43*** -.19† .02 Scenario × information × manipulation .07 .35** .51*** .22 .11 High-class vs. control (Intercept) -.92*** -1.03*** .10 -.10 .05 .96*** Scenario type 1.56*** 2.79*** .90*** 1.24*** .19* .39† Information type .30** .14 .08 .09 .17 .07 Manipulation .21 .24 -.27† .12 .26*** Scenario × information -.29† -.29† .10 .28† -.00 .00 Scenario × manipulation .92*** .71*** .69** -.25 -.57*** Information × manipulation .05 -.09 -.28** -.18† -.19* 91 Scenario × information × manipulation -.06 .01 .19 .28† -.01 Notes. a In Study 6F, participants in the slow deliberation time condition did not complete any trials with control targets, so these analyses only include participants in the fast condition and do not include deliberation time as a predictor. † p < .10, * p < .05, ** p < .01, *** p < .001 All responses are coded so 1=chose the higher-class target in this comparison (e.g., the high-class target on trials comparing high- vs. low-class targets; the control target on trials comparing control vs. low-class targets). Scenario is coded so 1=competence, 0=morality (except for Study 6E, see text); information type is coded so 1=objective only, -1=objective and about-me; manipulations are coded as follows: - Study 6A: 1=nonstudent targets, -1=student targets - Study 6B: 1=high stakes, -1=low stakes - Study 6C: 1=no benefit to target, -1=benefit to target - Study 6D: 1=potential for future interaction with target, -1=no potential for future interaction with target - Study 6E: 1=betrayal would be illegal, -1=betrayal would be legal - Study 6F: 1=fast deliberation time, -1=slow deliberation time Figure 6 Trust based on target social class, scenario type, and manipulation. 92 Note. Error bars are 95% CIs. Figure 6 displays two notable patterns. First, the bars for the competence scenario nearly all show a preference for trusting high over low class targets—this is in line with our theorizing about both explicit and implicit dispositional stereotypes. Second, only one bar in the morality scenario shows a (barely-significant) preference for low-class targets: In Study 6A’s morality scenario when all targets were students, 57% chose the low-class target over the high-class target, difference from chance (50%) log(OR)=-.26, SE=.13, p=.040. In other words, only one of our six attempts to design scenarios that matched features of the trust game yielded results 93 similar to those we observed with the trust game. This did not bode particularly well for our key hypothesis tests. Key Hypothesis Tests: Effects of Manipulations on Choices in the Morality Scenario. Nonetheless, we examined whether each manipulation at least shifted participants’ preferences in the direction we had expected (see Table 19, manipulation main effects). People were not drawn toward trusting lower class targets when the stakes were lower (6B), in one-shot interaction scenarios (6D), or when they made slower decisions (6F). And they were unexpectedly drawn toward trusting higher class targets when the target could benefit more from their trust (6C). Only two of the six manipulations showed the expected positive significant effect: When the targets were students, compared to non-students (Study 6A), and when the betrayal would be legal compared to illegal (Study 6E), participants’ preferences shifted toward trusting lower status targets. (Significant interactions with scenario in both cases indicated the student effect was stronger in the competence condition, but the legality effect weaker in the selling a used car condition). Unpacking the student effect in 6A, participants (who were students themselves) preferred to trust the morality of low-class targets over high-class ones, but only when they were fellow students. Only half of Chapter Two’s studies featured student targets, however in all of Chapter Two’s studies featured participants and targets were part of the same group (of students or online survey pool). Study 6A suggests this could help resolve the discrepancy in results between Chapter Two and Chapter Three. One possible interpretation is that people are more inclined to trust low-class targets over high-class ones when they feel a shared identity with these targets. However, some results from a 94 supplemental study cast some doubt on this interpretation: Study B1 in Appendix B found that people expected high-, not low-, class targets to be especially trustworthy with trusters they knew. Knowing someone is different than sharing an identity with them, but to the degree they are similar, it does not seem that people think low class targets who they (could) know are likely to be more trustworthy. A second possible interpretation is that people are more inclined to trust low-class, but not extremely low-class targets over high class ones—it is unlikely that students or members of an online survey pool would be, for example, homeless. In the absence of evidence ruling out this second interpretation, we deem it at the very least more likely than the first. However, we note that the effect of the manipulation was relatively weak, and that it did not have similar effects on participants’ choices between high-class and control, or between control and low-class targets. It is possible this manipulation’s effect was a false positive. Turning next to unpacking the legality effect, the significant interaction with scenario indicated it only held in one of that study’s two morality scenarios: The predicted effect emerged in the care scenario (log(OR)=-1.03, SE=.29, p<.001) but not the car scenario (log(OR)=.37, SE=.29, p=.210). This makes the finding difficult to interpret: The legality manipulation in the car scenario was much cleaner, as the scenarios were exactly the same – the only difference was whether lying when selling a used car was described as legal or illegal in one’s state. In contrast, the scenarios about caring involved caring for a cat in the legal condition (where the betrayal we highlighted was being mean to the cat) versus a plant in the illegal condition (where the betrayal we highlighted was stealing belongings). Indeed, many more participants failed an attention check about legality of betrayal in the caring scenario (42%) than in the car scenario (19%). Thus, we hesitate to draw firm conclusions about the role of legality on the basis of these results. 95 Summary of Manipulation Effects. None of the six manipulations we attempted provides a clear, definitive answer to the question of why there is a discrepancy in results between Chapter Two’s trust game findings and Study 5’s scenario findings. The only two manipulations to produce significant differences in line with what we expected in the morality scenario did not have particularly robust effects. The effect whereby people were more drawn to trust low-class targets if they were students was weak, and did not influence choices involving a control target; the effect whereby people were more drawn to trust low-class targets if the potential betrayal was legal was specific one of our two scenarios, and never resulted in a significant preference for low-class over high-class targets. Variation by Scenario. We also noticed considerable variation in the main effect of target social class on trust depending on which scenario we used. We summarize that variation here (we do not perform any analyses on these differences, and we did not pre-register expecting any differences based on scenarios). When participants chose who they would trust to hold their spot in line at a doctor’s office (Studies 6A, 6B, and 6D) they tended to have no preference between high- and low-class targets; in the other morality scenarios (trusting someone to watch their bag at a train station, babysit their child, be honest about selling a used car, or take care of their cat/plants), participants were more likely to prefer high- over low-class targets. When participants chose who they would trust to have as a partner on a gameshow in a condition where choosing the target would mean that target received a monetary prize (Study 6C), they tended to have no preference between high- and low-class targets; in the other competence scenario (trusting someone to give a presentation at work), participants were more likely to prefer high- over low-class targets. We note this variation in case future researchers want to develop ideas about trust based on the particular features of the doctor’s office or gameshow scenarios. 96 Individual Differences in the Effect of Target Social Class on Trust. Appendix B provides detailed moderator analyses, including moderation by social class stereotypes. First, Figure 7 illustrates the general size and direction of these stereotypes, plotting the difference in explicit perceptions of high compared to low class targets. Participants always stereotyped high-class targets as more competent but less moral than low-class targets; the competence effect was always large and significant whereas the morality effect was smaller and not consistently significant. Further complicating matters, participants stereotyped high-class targets as more trustworthy in Study 6D (though not in Studies 6E-6F). These inconsistencies with stereotypes related to morality are puzzling, given the existing literature (S. T. Fiske et al., 2002; Ragusa, 2015; Zitelmann, 2020). It is possible that when participants reported their explicit stereotypes after making 32 repeated choices generally in favor of trusting a higher-class target, they felt some pressure toward consistency and thus suppressed their general impression that lower-class targets are more moral. We return to this question in Study 8. Figure 7 Participants stereotype high-class targets as more competent and slightly less moral than low-class targets, Studies 6A-6F. 97 Turning to the question of whether these stereotypes moderate trust decisions, results were similar to Study 5. In general, participants who stereotyped high-class targets more positively also trusted these targets more, and this did not seem to depend on the match between the stereotype dimension and the scenario. Stereotypes of trustworthiness were possibly an exception to this latter pattern: In two of the three studies where we measured this, stereotyping high class targets as more trustworthy predicted trusting them more especially in the morality scenario. Discussion Across six pre-registered studies, participants most often trusted higher-class targets over lower-class ones, and sometimes showed no preference based on social class; in only one of 14 cases did they behave consistently with findings from Chapter Two and trust lower-class targets’ morality more. Only two of the six moderators we tested came close to explaining the 98 discrepancy in results between Chapter Two and Study 5, but neither effect was particularly strong and we did not deem either reliable enough to justify further investigation, especially given the possibility of false positives in our numerous statistical tests. Running these six studies made us aware that there is a vast array of possible differences between the scenario and trust game paradigms, and even among the different scenarios. Acknowledging that manipulating each possibility in this vast array—let alone testing them in combination—could be a long and inefficient route to understanding these findings, we turned instead to a different approach: Understanding what perceiver-level variables predict participants’ trust decisions. We thought answering this question could help us understand antecedents of the relationship between target social class and trust, and this might provide insight both into the discrepancy in our results and into the question of trust and social class more broadly. Studies 5 through 6F already provide some hints about perceiver-level predictors. Participants' explicit stereotypes associating high social class with high competence and morality predict trusting higher-class individuals more than lower-class ones. That is, those who viewed higher-class people as more moral than lower-class people also trusted them more in moral situations. However, participants also generally explicitly associated high social class with slightly lower morality compared to low social class. This we found puzzling: The average person in our sample reported viewing higher-class people as less moral than lower-class people, and although these views predicted who they tended to trust they still overall trusted the higher-class targets more. What could explain this apparent paradox? We wondered whether implicit stereotypes, in addition to explicit stereotypes, played a role in people’s trust decisions. If our sample on average implicitly associated high social class with high morality (despite their 99 explicit stereotypes), and these implicit stereotypes were a stronger predictor of trust in the scenarios, this could explain why people generally do not trust lower-class individuals in these scenarios. We therefore developed a new measures of implicit social class stereotypes of morality and competence in Studies 7A-7G and tested it as a predictor of trust in our scenarios in Study 8. Studies 7A-7G To measure implicit stereotypes, we first considered prior research examining implicit stereotypes of social class. Several previous studies have measured the general valence of implicit associations with social class (Horwitz & Dovidio, 2017; Lindqvist et al., 2017; Mattan et al., 2019; Mattan & Cloutier, 2020; Rudman et al., 2002; Wu et al., 2018). Many of these studies find that explicit and implicit attitudes towards the rich diverge, with people generally reporting negative explicit stereotypes, but demonstrating implicit positive associations, with the wealthy compared to the poor (Horwitz & Dovidio, 2017; Lindqvist et al., 2017; Rudman et al., 2002; Wu et al., 2018). However, these studies have examined only valence, not specific stereotype content (warmth versus competence, or any other dimension). The sole exception is Lindqvist and colleagues’ (2017) study showing that, in line with our predictions, Swedish participants implicitly associated the poor with being not only incompetent (rather than competent) but also cold (rather than warm). However, this study tested stereotypical associations with words representing social class (e.g., rich vs. poor). That people associate the word rich with competence and warmth words more than the word poor may merely reflect that people feel more positively toward the idea of wealth than of poverty, rather how they implicitly view people who are wealthy versus poor. 100 Indeed, this use of concept words rather than people is the overwhelming norm in research on implicit wealth attitudes, perhaps because it can be difficult to unambiguously display a person’s social class in an image flashed on a screen. The one study we found that did this taught participants that red versus blue borders meant the individual pictured within had high versus low status, and used this to test the general valence of their implicit attitudes (Mattan et al., 2019). We used this colored border approach in Studies 7A-7B, but the warmth and competence associations in these studies had poor psychometric properties. We therefore developed a new strategy to flash images of people that participants would immediately recognize as high versus low class: We had participants first complete repeated trials teaching them that specific target faces had high social class while others had low social class. We then used these now-familiar faces as nonverbal stimuli in two brief implicit association tasks (BIATs; Nosek et al., 2014; Sriram & Greenwald, 2009), one measuring associations with morality vs. immorality and the other measuring associations with competence vs. incompetence. In this way, our task measures associations between stereotypes and people with high and low social class, rather than associations between stereotypes and words about high and low social class. We ran seven studies iterating on this task, modifying its parameters until it had adequate psychometric properties. We began by developing the competence BIAT in Studies 7A-7C, because we could confidently predict people would implicitly associate competence with high class and could use this prediction as a sanity check on the task. We then developed the morality BIAT in Study 7D. Study 7E was a pre-registered (https://osf.io/te39u/?view_only=43cc95a0b50744ca843f20169b5a1407) test of the BIAT tasks’ properties and of our confirmatory hypothesis that that people would implicitly associate high social class with high competence and high morality. Studies 7B-7E also measured explicit 101 social class stereotypes. Studies 7F-7G explored whether these implicit associations predicted responses to the trust scenarios. Method Participants. For these studies we recruited participants from either MTurk or our undergraduate Human Subjects Pool (HSP); see Table 20 for sample details, exclusions, and demographics. We excluded participants who gave more than 10% of their responses to the BIAT in under 300 milliseconds; this exclusion criterion improves the psychometric properties of the BIAT and is recommended by the creators of the paradigm (Nosek et al., 2014). Studies 7F and 7G also included the scenario measures; we did not apply any exclusion criteria to these scenarios to preserve power in these smaller sampled pilot studies. Because these are pilot studies they use small samples; we pre-registered Study 7E with a larger sample to verify the findings of Studies 7A-7D (that is, the general pattern of implicit associations with social class), and we pre-registered Study 8 with a larger sample to verify the findings of Studies 7F-7G (the associations between implicit stereotypes, explicit stereotypes, and trust in the scenarios). Table 20 Sample details, Studies 7A-7G. Study 7A 7B 7C 7D 7E 7F 7G Sample MTurk MTurk MTurk MTurk HSP HSP HSP N 43 41 48 43 210 (M) 206 (C) 181 (M) 172 (C) 136 (M) 135 (C) Excluded: >10% responses < 300 ms 8 10 3 8 7 (M) 7 (C) 12 (M) 10 (C) 6 (M) 6 (C) Final N 35 31 45 35 200 (M) 199 (C) 169 (M) 162 (C) 130 (M) 129 (C) Gender: # women 16 15 24 13 143 81 100 # men 19 16 21 22 46 27 19 102 # another gender 0 0 0 0 2 0 0 Age: M 35.24 33.90 34.04 36.26 20.06 20.37 20.55 SD 9.73 8.58 8.96 11.62 1.99 2.29 3.10 Ethnicity: # Asian 2 3 5 2 128 64 75 # Black 1 5 5 1 1 3 2 # Hispanic 2 1 2 4 2 1 3 # Indigenous 1 0 2 1 0 1 0 # White 26 22 35 31 41 27 29 # another ethnicity 1 0 0 0 27 17 14 Note. Participants could select multiple ethnicities. For studies 7E-7G, most participants completed both the morality and competence BIAT, but a small number of them did not finish the study and thus only completed one BIAT. We therefore provide Ns and exclusions separately for the morality (M) and competence (C) BIATs. If participants were excluded from only one BIAT because >10% of their responses were under 300 ms, we still used their data for the other BIAT. Demographics for these studies are demographics for participants who passed all inclusion criteria for both BIATs. BIAT. The BIAT (Nosek et al., 2014; Sriram & Greenwald, 2009) is a modified version of an IAT. In a typical IAT, participants see two categories on the left side of their screen (e.g., “flowers” + “good”) and two opposing categories on the right side of the screen (e.g., “bugs” + “bad”), and they use keys to indicate whether a stimulus (e.g., a picture of a tulip or the word “terrible”) fits into the categories on the left side of the screen or the right. After repeated trials, two of the categories switch sides (e.g., so the left side now has the categories “flowers” + “bad”, and the right side, “bugs” + “good”), and participants complete the categorization task again using these new categories. People respond more quickly to the degree they have a positive implicit association for the two categories (e.g., when “flowers” and “good” are paired on the same side of the screen, assuming most people feel positively about flowers), and more slowly when they have a negative one (e.g., when “flowers” and “bad” are paired on the same side of 103 the screen). If we replace flower and bug categories with two different social groups, IATs therefore measure people’s relative implicit associations toward these social groups. The BIAT uses similar logic, but asks participants to focus only on two of the four categories, making the task simpler, shorter, and less subject to variance due to different participants using different strategies (Sriram & Greenwald, 2009). Specifically, participants view only two of the four categories on the screen (e.g., “flowers” + “good”), and are told to press one key (the “focal response key”) if the stimulus falls into either one of those two focal categories (e.g., if it is a picture of a sunflower, or the word “fantastic”), and a different key (the “nonfocal response key”) if it does not (e.g., if it is a picture of a centipede, or the word “terrible”). If they press the wrong key, the task prompts them to correct the error. After completing one block of trials in this manner, they complete a second block of trials following the same procedure with a different set of two categories that now appear on the screen (e.g., “bugs” + “good”). Participants then complete a third and fourth block of trials that repeat the same structure as the first and second blocks. The task is then over—there is no block with the pairing “flowers” + “bad”, or “bugs” + “bad”; in fact, “bad” never appears as a category. The purpose of this task is to assess people’s relative feelings about flowers compared to bugs (if researchers wanted to assess only people’s feelings about flowers, they could administer a single-category IAT, where “flowers” appears with either “good” or “bad”; in our case, we wanted to know relative feelings about high- versus low-class people, so this type of single-category IAT would not be sufficient.) Our studies applied the BIAT paradigm to assess people’s implicit associations between high- and low-class people and competence, and between high- and low-class people and morality. Each BIAT had four blocks that we analyzed (for morality, two paired “moral” + “high 104 status” and two paired “moral” + “low status”; for competence, two paired “competent” + “high status” and two paired “competent” + “low status”; the first block was randomly selected, and the rest appeared in alternating order). We followed Nosek and colleagues’ recommendations for calculating BIAT D-scores from participants’ reaction time data. We always used the same words as stereotype content stimuli (morality IAT: “moral”, “honest”, “generous”, “ethical”, and their opposites: “immoral”, “dishonest”, “selfish”, “unethical”; competence IAT: “competent”, “intelligent”, “skilled”, “capable”, and their opposites: “incompetent”, “unintelligent”, “unskilled”, “incapable”). These words come from prior research measuring competence and morality stereotypes (e.g., Abele et al., 2016; Durante et al., 2017; S. T. Fiske et al., 2002). For low- and high-class stimuli, we first taught participants to quickly recognize the faces of several high-class and low-class targets by presenting faces paired with descriptions that indicated the person’s social class. In repeated trials, they used the up or down arrow key to indicate whether the target being presented was high or low status. They could not advance to the next trial until they responded correctly. This procedure familiarized participants with the targets and their social class, which meant we could then use these targets’ faces without all the written information as stimuli in the BIAT. The specific number of targets and trials, as well as their descriptions, differed between studies; see below. Procedural Differences Between Studies. We began by only testing the competence BIAT, because it seemed highly likely that participants would associate high status with competence so we could use this as a test of the task’s validity. Thus, Studies 7A-7C’s participants completed only the competence BIAT. We narrowed in on BIAT parameters in these studies to identify ones that yielded a measure with acceptable psychometric properties (see 105 below). Next in Study 7D we used the same parameters to test the morality BIAT. In Studies 7B through 7D, participants also reported their explicit stereotypes corresponding to the BIAT they completed, after the BIAT but before their demographics. To assess these stereotypes, we first showed participants a description of a low (high) class person: “Imagine a man who has a low income (is wealthy), drives a car that’s not very nice (nice car), is uneducated (highly educated), and who lives in a bad (nice) neighbourhood”. Then, they rated each target on one item for competence (morality): “How competent (moral) do you think this person is likely to be?” (1 = not at all, 7 = very). In Study 7E, participants completed both BIATs (in random order), then reported their explicit stereotypes of both competence and morality on a more specific prompt and using a multi-item scale. For the low-class person, they read, “Mark has a job in the manufacturing industry and makes minimum wage. He rents a small apartment in a low-income neighborhood. He recently got a 15-year-old station wagon that he bought from a neighbor.” For the high-class person, they read, “John makes $3,000,000 a year. He owns a vacation home in Hawaii, has a private yacht, and owns three expensive sports cars.” They then rated four competence items (“How X do you think [Mark / John] is likely to be?”, with X replaced by competent, skilled, capable, intelligent; high-class α = .85, low-class α = .86) and four morality items (same wording, with X replaced by moral, ethical, generous, honest; high-class α = .92, low-class α = .84) on a seven-point scale (1 = not at all, 7 = very). The competence and morality words are the ones we use in our BIAT, ensuring results are comparable. In Studies 7F-7G, participants completed both BIATs (in random order), then completed the trust scenario paradigm from Study 5, then reported their explicit stereotypes. The explicit 106 stereotype measure used the prompt from Studies 7B-7D, but the multi-item scale from Study 7E. Differences Between Studies’ BIATs. Table 21 illustrates how each iteration of the BIAT guided our methodological decisions for the next iteration. In each case, we calculated participants’ error rate and the split-half reliability (using two methods to split the task in half: by odd-numbered versus even-numbered trials, and by the first two blocks versus second two blocks of the task; Nosek et al., 2014; Sriram & Greenwald, 2009), and evaluated these metrics against what is typical for BIATs. We also tested for undesired methodological effects (see below) – these effects would ideally be near 0. Table 21 Psychometric properties of BIATs, Studies 7A-7B. Error rate Reliability (odd vs. even) Reliability (first vs. second) Order Color Face matching % α α Cohen’s d Cohen’s d Cohen’s d Typical BIAT1 8-10 .7-.8 .7-.8 (Ideally 0) (Ideally 0) (Ideally 0) Study 7A (C) 15 .83 .53 -.63† -.24 n/a Study 7B (C) 13 .65 .62 .04 .02 n/a Study 7C (C) 9 .84 .87 .00 n/a .10 Study 7D (M) 8 .88 .56 -.34 n/a .45 Study 7E (M) 10 .57 .44 -.27† n/a n/a Study 7E (C) 11 .83 .70 -.02 n/a n/a Study 7F (M) 9 .76 .70 -.33* n/a -.60*** Study 7F (C) 11 .86 .64 -.31† n/a -.44** Study 7G (M) 9 .68 .35 -.14 n/a n/a Study 7G (C) 11 .85 .66 -.24 n/a n/a 1(Nosek et al., 2014; Sriram & Greenwald, 2009) (M) denotes the morality BIAT; (C) denotes the competence BIAT. For order, positive effects indicate larger associations between high social class and positive stereotypes if the high class + positive stereotype block was presented first, compared to if the low class + positive stereotype block was presented first. For color, positive effects indicate larger associations between high social class and positive stereotypes if the high-class targets had blue borders while the low-class targets had green borders, compared to if the high-class targets had green borders and the low-class, blue. † p < .10, * p < .05, ** p < .01, *** p < .001 107 In Study 7A, we included a practice block where participants categorized words as fitting versus not fitting the category “competent” (no status category appeared in this practice block). However, when we analyzed the effect of the order of blocks (positive stereotype + “high status” first, or positive stereotype + “low status” first), we found a large effect of order, though this effect was not significant in this small-sampled pilot study (see “order” column in Table 21). For this reason, in all subsequent studies, we included two practice blocks that were identical to the two blocks in the real BIAT (i.e., they presented two categories, with one block presenting “competent” + “high status” while the other presented “competent” + “low status”). We presented these practice blocks in random order and did not analyze data from them. After including these blocks, the effect of order was much smaller or absent. Studies 7A and 7B used as stimuli all eight of Study 5’s low- and high-class targets; these studies also included colored outlines around the images (green and blue, with the association to each class counterbalanced across participants), to help participants learn. We tested whether the matching between each color and each social class affected results; its effect was minimal (see “color” column in Table 21). Study 7A showed each target 5 times (40 total trials); Study 7B 9 times (72 total trials). After observing high error rates in both studies, we abandoned the colored outlines and instead tried to help learning by using only four instead of eight targets. We used the four targets whose social class was conveyed through both objective information and about-me statements, to ensure the manipulation was strong. Our initial studies using this procedure (7C, 7D, and 7F) created two versions of the stimuli, using in each case a different matching of faces with target descriptions. However, when we analyzed the effect of face—description matching version (see “face matching” column, Table 21), we sometimes observed different results for these two 108 versions. Therefore, our two final studies (7E and 7G) randomly matched faces with target descriptions. The final iteration of the BIAT (used in Studies 7E-7G) had error rates comparable to field norms for BIATs. It also had acceptable reliability when reliability was assessed by comparing odd versus even trials, though reliability was lower when assessed by comparing the first to the second half of the task (perhaps because participants became more practiced at the task as they progressed). Prior research on BIATs does not make clear which approach for calculating reliability should be used (Nosek et al., 2014; Sriram & Greenwald, 2009). Results Implicit Associations and Explicit Stereotypes. Notwithstanding the methodological flaws in earlier iterations of the task, we examined the D-scores in each study: the difference in response time between responding to blocks pairing “high status” + “competence” / “warmth” and those pairing “low status” + “competence” + “warmth”, calculated using Nosek and colleagues’ 2014 algorithm). We ran one-sample t tests comparing these D-scores to zero (see Table 22, second and third columns). We expected that both competence and warmth would show positive D-scores. We ran similar one-sample t-tests comparing the analogous difference scores for explicit stereotypes (calculated by subtracting explicit stereotypes of low-class targets from explicit stereotypes of high-class targets) to zero (see Table 22, fourth and fifth columns). Here, we expected competence to show positive difference scores, but morality to show negative difference scores. We also computed correlations between corresponding implicit and explicit stereotypes (see Table 22, sixth and seventh columns), and between morality and competence implicit stereotypes (see Table 22, eighth column) and morality and competence explicit stereotypes (see Table 22, ninth column). 109 Table 22 Implicit and explicit stereotypes of morality (M) and competence (C), and their correlations, across Studies 7A-7G. Study Implicit D-score Explicit difference score Implicit—explicit r M—C r M C M C M C Implicit Explicit 7A .20* 7B .04 1.81*** .17 7C .64*** 2.14*** .21 7D .41*** -.06 -.17 7E .40*** .54*** .32** .99*** .05 -.03 .26*** -.20** 7F .28*** .59*** .11 2.28*** .09 .18* .42*** .59*** 7G .33*** .46*** .08 2.29*** .26** .17† .44*** .53*** Note. † p <.10, * p < .05, ** p < .01, *** p < .001 Study 7A did not measure explicit stereotypes; Studies 7A-7C did not measure morality stereotypes and Study 7D did not measure competence stereotypes, so these cells are left blank. The results generally confirmed our expectations for implicit stereotypes and for explicit competence stereotypes, but not explicit morality stereotypes: Rather than perceiving lower class targets as more moral, participants generally perceived no difference, save for one study where they perceived lower class targets as less moral. As we had in Studies 6A-F, we wondered whether this might represent participants’ effort to be consistent with what they might have noticed themselves doing on the BIAT or in the trust scenarios. We return to this issue in Study 8. Stereotypes and Trust Decisions. In Studies 7F-7G, we tested whether implicit and explicit stereotypes predicted responses to the trust scenarios. For each participant and each trust scenario, we calculated the proportion of times they selected the high-class target over the low-class one. Then, we examined both the zero-order correlations between trust proportions and the relevant stereotypes, and linear regressions predicting trust proportions from the relevant implicit and explicit stereotypes simultaneously. Table 23 displays the results. Table 23 Implicit and explicit stereotypes predicting trusting higher-class targets over lower-class ones, Studies 7F-7G. 110 Study Predictor Morality Competence Correlations r p r p 7F Explicit stereotypes .23 <.001 .31 <.001 Implicit stereotypes .07 .361 .11 .171 7G Explicit stereotypes .36 <.001 .26 .003 Implicit stereotypes .19 .039 .15 .090 Regressions β SE p β SE p 7F Explicit stereotypes .30 .07 <.001 .28 .08 <.001 Implicit stereotypes .05 .08 .533 .06 .08 .440 7G Explicit stereotypes .31 .09 <.001 .24 .09 .009 Implicit stereotypes .10 .09 .239 .11 .09 .208 In these analyses, explicit stereotypes always predicted trust on the relevant dimension. Implicit stereotypes were also always positively related to trust, but their effects were weaker and less consistent (significant in only one of the four tests). We also ran two additional analyses predicting trust (one analysis predicting trust in morality and the other, trust in competence) with all four stereotypes (i.e., implicit stereotypes of morality and of competence, and explicit stereotypes of morality and of competence). In these larger models, in Study 7F, only the explicit competence stereotype significantly predicted trust on both dimensions, trust in morality β = .46, p <.001, trust in competence β = .30, p = .023; implicit morality stereotypes were marginally related to trust in morality, β = .19, p = .085; all other effects were nonsignificant, all βs < |.12|, all ps > .297. In Study 7G, only the explicit morality stereotype significantly predicted trust in morality, β = .23, p = .022 (though the implicit competence stereotype was marginally related to trust in morality, β = .18, p = .084). Similarly, only the explicit competence stereotype significantly predicted trust in competence, β = .24, p = .031(though again the implicit competence stereotype was marginally related to trust in competence, β = .17, p = .094). All other effects were nonsignificant, βs < |.17|, ps > .125. 111 Discussion Across Studies 7A-7G, we developed two measures of implicit stereotypes measuring people’s implicit associations with social class – one measuring associations between class and competence, and the other, class and morality. These studies found, as predicted, that people implicitly associated high social class with higher morality and higher competence. However, in Studies 7F-7G we found that these implicit associations generally were not strongly related to people’s trust decisions, certainly not as strongly as their explicit associations. This could mean that implicit stereotypes do not in fact explain the effect of target social class on trust. However, these samples were fairly small, and we did not exclude inattentive participants (to avoid making the samples even smaller). This may have increased the noise in the data, making it harder to detect effects of implicit stereotypes. Moreover, it is also possible that the order of tasks created these asymmetrical results: Participants completed the implicit stereotype measure before, but the explicit stereotype measure after, the trust measure. So their decisions during the trust scenarios could plausibly have influenced how they completed the explicit, but not the implicit, stereotype measure: After repeatedly selecting that they would trust the higher-class targets, participants might have felt motivated to report explicit stereotypes that aligned with their trust decisions. We conducted Study 8 to resolve these issues. Study 8 In Study 8, we used the final version of the BIATs from Study 7G in a pre-registered (https://osf.io/fmsyw/?view_only=3b337b3964ef4a59baa2f44ce13e0535) three-part design. Participants completed measures of a) implicit stereotypes, b) explicit stereotypes, and c) trust in morality and competence, each in separate surveys administered one week apart from each other. Participants completed the implicit and explicit stereotype measures during the first and second 112 weeks, counterbalanced across participants, and the trust measure last, during the third week. Having the surveys administered one week apart from each other reduced the likelihood that participants would feel pressure to report explicit stereotypes aligned with their trust decisions or their BIAT responses. This study also used a set of new targets in each measure which manipulated social class using only objective information. This ensured effects are generalizable beyond the targets we used in previous studies, and that we manipulated only social class rather than providing additional subjective hints that people might interpret in different ways. We expected that participants would explicitly stereotype higher-class people as more competent but less moral than lower-class people, but would implicitly associate high (versus low) social class with high competence and high morality. We also pre-registered testing whether implicit and explicit stereotypes predicted choices in the scenarios, and if so, which was a stronger predictor. Method Participants. We recruited 303 American participants from Prolific Academic to complete the first session of the study: either the measure of explicit stereotypes (n=149) or implicit stereotypes (n=154). One week later, we contacted those 278 of the 303 who passed our exclusion criteria (see below) to complete the second session of the study: whichever stereotype measure they had not yet completed (n=195 participated in this second session; n=102 reported explicit stereotypes and n=93 reported implicit stereotypes). After another week, we contacted the 174 who had completed both sessions and passed all exclusion criteria to complete the third session: the trust scenarios (n=165 participated in this third session). We excluded 46 participants who, in the implicit stereotype session, gave more than 10% of their responses to the BIAT in under 300 milliseconds, as we had in Studies 7A-7G (Nosek et al., 2014). We also excluded participants who, during the scenario measure, spent on average 113 less than two seconds per trial (n=12), failed more than two comprehension checks about the scenarios (n=16), or who selected targets on the same side of the screen more than 87% of the time (n=2; some exclusions were overlapping). In total, this left 138 participants with complete data who passed exclusion criteria (75 women, 61 men, 0 non-binary; M age = 31.48, SD = 11.10; 45 Asian, 5 Black, 14 Hispanic, 2 Indigenous, 76 White, 3 another ethnicity [participants could select multiple options]). Measures and Materials. Targets. For this study we created 16 new targets, for generalizability beyond the targets we used in Studies 5-7G. These served as the targets across all three measures. To make the social class information about these targets as easy to remember as possible, we only included objective information about each one, and we included the same three pieces of information for each target: income, education, and occupation (see Table 24). Each target description was paired with a face from the Chicago Face Database (Ma et al., 2015). We chose faces that were (1) White, (2) female, (3) making a neutral facial expression, (4) rated as appearing over 28 years old (to make it plausible that the target could have a very high income or prestigious job), and (5) within plus or minus one standard deviation from the mean score for White women on trustworthiness and dominance (as proxies for morality and competence); this left us with 16 faces, the same number as we had target descriptions. We randomly selected four target descriptions and four faces to appear with the explicit stereotype measure, four descriptions and faces to appear with the BIATs, and eight descriptions and faces to appear with the trust scenario measure. We did not randomly select this for each participant; we only did this random selection once, so all participants saw the same four faces and descriptions in the explicit stereotype measure, the same four faces and descriptions for the BIATs, and the same eight faces and 114 descriptions with the trust scenario measure. However, we did pair faces randomly with target descriptions within each task for each participant, so one participant might see face #1 paired with description #4 in the BIAT, while another might see face #1 paired with description #2. Table 24 Target descriptions, Study 8. Task Target Income Education Occupation Implicit stereotypes Low-class 1 $10,000-$20,000 High school degree Seasonal farm worker Low-class 2 $15,000-$25,000 Some college but no degree Cashier High-class 1 $175,000-$200,000 BSc. and MD Psychiatrist High-class 2 $200,000-$250,000 BA and MBA Investment banker Explicit stereotypes Low-class 1 $10,000-$20,000 High school degree Doordash delivery driver Low-class 2 $15,000-$25,000 Some college but no degree Waitress High-class 1 $150,000-$200,000 BA and MA Managing director High-class 2 $200,000-$250,000 BSc and MSc Software engineer Scenarios Low-class 1 $10,000-$20,000 High school degree Bellhop Low-class 2 $20,000-$30,000 High school degree Assembly line worker Low-class 3 $15,000-$25,000 Some college but no degree Office assistant Low-class 4 $10,000-$20,000 Some college but no degree Dishwasher High-class 1 $250,000-$300,000 BA and MBA CFO of hotel chain High-class 2 $140,000-$150,000 BA and culinary arts degree Executive chef and restauranteur High-class 3 $200,000-$250,000 BSc. and MD Surgeon High-class 4 $150,000-$200,000 BA and JD Lawyer Explicit Stereotype Procedure. In random order, participants reported their stereotypes of either low- or high-class targets. For the low (high) class stereotype measure, they viewed two targets and were told, “These two people are examples of people who have low (high) social class, meaning they have low (high) incomes, little (a lot of) education, and low-status (high-status) jobs. Think about this group of people in general, people who have low (high) social 115 class. What traits do you think people in this group tend to have?”. They then responded to the same four competence and morality items from Studies 7E-7G. Implicit Stereotype Procedure. Participants completed the BIATs for morality and competence (in random order) that we developed in Studies 7A-7G. Trust Scenario Procedure. This phase of the study closely followed Study 5’s procedure. The trust scenarios were the same (trusting someone to watch a bag at a train station [morality], or deliver a presentation at work [competence]), but the targets were different as described above (specifically, we did not include control targets or about-me statements, meaning participants learned objective social class information about all targets). With four low- and four high-class targets, there were 16 possible target pairings; participants saw each of these pairings once per scenario, in random order. Results We first examined whether participants overall (1) explicitly associated high social class with high competence but low morality, (2) implicitly associated high social class with high competence and high morality, and (3) chose high-class targets more often in both competence and morality trust scenarios. For explicit stereotypes we calculated a difference score between stereotypes of high minus low social class targets. For implicit stereotypes we calculated BIAT D-scores as recommended by Nosek and colleagues (2014). For the trust scenarios we calculated the proportion of the time participants chose high-class targets over low-class targets. In all cases, higher scores indicate more positive responses to high-class targets than low-class ones. All predictions were supported; see Figure 8 and Table 25. Figure 8 Cohen’s ds for the difference in explicit stereotypes, implicit stereotypes, and trust based on social class. 116 Note. Error bars are 95% CIs. Positive scores indicate more positive reactions towards high versus low-class targets; zero indicates no difference; negative scores indicate more positive reactions towards low- versus high-class targets. Table 25 One-sample t-tests comparing the social class difference in explicit stereotypes, implicit stereotypes, and trust to no difference. Implicit D-score Explicit difference score Proportion of times trusting high-class target M .33, t(137)=8.50, p<.001 -.46, t(137)=-4.01, p<.001 .72, t(137)=8.61, p<.001 C .49, t(137)=11.54, p<.001 1.41, t(137)=12.71, p<.001 .92, t(137)=32.93, p<.001 Note. M = morality, C = competence. As predicted, and using a validated multi-item measure of stereotypes that is uncontaminated by participants’ immediately preceding trust decisions or BIAT behavior, 117 participants reported viewing low-class targets as more moral than high-class targets. This aligns with results from Chapter Two. However, the implicit stereotype measure revealed that despite these explicit stereotypes, participants implicitly associated low social class with lower morality than high social class; moreover they more often chose high class targets to trust in the morality scenario. This, in turn, aligns with results we generally observed in our research using scenarios. This is some preliminary evidence consistent with the idea that implicit stereotypes might explain why people prefer to trust higher-class targets in morality scenarios despite their explicit stereotypes. Moreover, the effect size for implicit morality stereotypes was more than double that of explicit morality stereotypes (see Figure 8), suggesting the implicit association between low class and immorality is stronger than the explicit one between low class and morality. The implicit morality D-score (0.33) was quite large, roughly double that of previous literature using BIATs to measure reliable stereotypic associations such as that between women (men) and arts (science), D-score = .17, and between weapons (gadgets) and African-Americans (European-Americans), D-score = .16 (Sriram & Greenwald, 2009). Competence results were more straightforward: Participants explicitly and implicitly stereotyped high-class targets as more competent than low-class targets, and chose them more often in the competence trust scenario. Crucially, we then examined whether implicit and explicit stereotypes predicted choices in each scenario, using the same analytic approach as in Studies 7F-7G; see Table 26. Table 26 Implicit and explicit stereotypes predicting trusting higher-class targets over lower-class ones in trust scenarios, Study 8. Predictor Morality Competence Correlations r p r p Explicit stereotypes .29 .001 .25 .003 118 Implicit stereotypes .21 .016 .04 .625 Regressions β SE p β SE p Explicit stereotypes .26 .08 .002 .25 .09 .004 Implicit stereotypes .18 .08 .037 -.00 .09 .966 Note. In the regression models, both predictors are entered simultaneously. For the morality trust scenario, both implicit and explicit stereotypes had consistent, significant and independent effects: Participants who explicitly believed high-class people were more moral (a minority of participants), and participants who implicitly associated high social class with morality (a majority of participants), were more likely to choose high-class targets in the morality trust scenarios. In other words, these implicit stereotypes – which, on average, run counter to the explicit morality stereotypes – help to explain why we found that the trust scenarios also run counter to what these explicit stereotypes would lead us to predict. However, in an additional analysis including all four stereotypes as predictors, only the explicit morality stereotype had a significant independent effect on trust in morality, β = .24, SE = .09, p = .008; all other effects were nonsignificant, all βs < |.15|, all ps > .104. For the competence trust scenario, only the explicit stereotype measure mattered. This might be because the explicit and implicit competence stereotypes are more aligned than the same morality stereotypes, meaning that there is no additional variance explained by including implicit competence stereotypes. Indeed, explicit and implicit competence stereotypes are more strongly correlated than explicit and implicit morality stereotypes, competence r(136)=.21, p=.014, morality r(136)=.08, p=.332. Moreover, in an additional analysis including all four stereotypes as predictors, only the explicit competence stereotype had a significant independent effect on trust in competence, β = .19, SE = .09, p = .038; though both morality stereotypes had marginal effects, implicit morality β = .16, SE = .09, p = .063, explicit morality β = .17, SE = 119 .09, p = .062; the remaining effect of implicit competence stereotypes was not significant, β = -.07, SE = .09, p = .429. Discussion Study 8, using a pre-registered longitudinal design and a larger sample than our prior studies, revealed diverging implicit and explicit morality social class stereotypes: People explicitly say they perceive lower-class people as more moral, but implicitly they associate high social class with higher morality. Both stereotypes independently predicted trusting someone to behave morally, though after controlling for competence stereotypes, only the explicit morality stereotype significantly predicted trust in morality. These findings suggest that when it comes to making choices about trusting someone to be moral, people face two opposing influences: Explicit dispositional stereotypes pushing them to trust lower-class individuals, and implicit stereotypes pushing them to trust upper-class individuals. Perhaps by also considering explicit situational stereotypes (which also push for trusting upper-class individuals), we could more fully explain why people tended to trust the upper-class individuals in these scenario studies, particularly considering that some of the scenarios in these studies did involve a sizeable temptation for the target to betray the participant (e.g., the chance to steal a suitcase). In contrast, when trusting someone to be competent, decisions are more straightforward: People’s explicit competence stereotypes push them to trust upper-class individuals over lower-class individuals. 120 Chapter Four: General Discussion Chapter Two found robust evidence that Americans, Canadians, and UK participants tended to transfer more money to a lower-class target than an upper-class person in an economic game where doing so is typically interpreted as trusting the target will return some of the money the participant had transferred. In other words, they trusted this lower-class person to be more likely to do the fair, moral thing and return a fair portion of their money. Our first study in Chapter Three aimed to replicate the findings of Chapter Two using a new paradigm, where participants repeatedly decided who to trust in a hypothetical scenario. Though this paradigm loses Chapter Two’s measurement of behavior, it gains the use of realistic trust scenarios that people may actually encounter in real life. Moreover, by making repeated decisions between new targets, we could further generalize effects beyond just Chapter Two’s targets. We were so confident results would replicate using this new paradigm that we built in a new question pertaining to trust in competence, expecting people to trust higher-class targets more than lower-class ones. Instead, this new paradigm revealed the opposite effect from what we found in Chapter Two: Participants strongly preferred to trust higher-class targets over lower-class ones, in both morality and competence scenarios. We took two approaches to resolve this discrepancy in results. Approach #1: Situational Moderators First, we tested six situational factors—all differences we noted between the trust game versus our scenario paradigm—that we thought might moderate the effect of social class on trust. Of these factors, three had no effect on people’s tendency to trust higher- over lower-class targets: Whether the trust decision involved high stakes, risking losing something vitally important (or low stakes, risking losing something unimportant), whether people responded 121 quickly and automatically (versus slowly and deliberately), and whether people had a chance (versus no chance) to interact with the target in the future. One of the situational factors moderated participants’ decisions but in the opposite direction from what we expected: When trusting the target would (versus would not) benefit that target, people were less willing to trust a lower-class target to behave morally. This cannot explain why participants were more willing to trust a lower-class target in the trust game, where trusting a target involved giving them money. There were some hints that the remaining two situational factors might help explain the discrepancy. First, when betraying trust was perfectly legal (versus would mean committing a crime), people were more inclined to trust lower-class targets over higher-class ones. This aligned with our predictions, given that betrayal in the trust game is perfectly within-bounds. Moreover, from a theoretical standpoint, we reasoned that people might expect higher-class people to be more likely to commit unethical behaviour within the limits of the law, whereas they might associate low social class with criminal behaviour. We had even confirmed this reasoning in a pilot study. However, the effects of legality of betrayal were weak and driven by the more confounded of our two different legality manipulations. Second, when the targets were students, people were more inclined to trust lower-class targets to behave morally than higher-class targets. This was the only case in all scenario studies where we found a significant preference for lower-class targets, and it aligns with results in Chapter Two: Targets in that chapter were (like students) not likely to be extremely low status, and participants in that chapter (like our student participants in the scenario study) shared some degree of identity with targets (e.g., they were both survey workers on MTurk). However, the effect was small, with a p-value close to the significance border. If this variable plays a role, it is not likely to be the only explanation. 122 After running Studies 6A-6F and finding some suggestive (but no conclusive) evidence of moderators, we began to consider alternative approaches. Rather than considering all possible differences between the trust game and the scenarios (and within the scenarios) – as well as all possible combinations of those differences – it might be more fruitful to consider individual differences in explaining choices in the trust scenarios. Approach #2: Implicit Stereotypes One puzzling aspect of the scenario studies is that even after repeatedly choosing to trust the higher-class target’s morality, people still often reported viewing higher-class people as less dispositionally moral in general than lower-class people. Though this explicit stereotype difference was not significant in all studies, it consistently emerged in this direction. Because people’s implicit attitudes towards the rich and the poor often diverge from their explicit ones, at least when it comes to generally positive versus negative attitudes (Horwitz & Dovidio, 2017; Lindqvist et al., 2017; Rudman et al., 2002; Wu et al., 2018), we thought it possible that this would also extend to specific associations with morality and competence. That is, we suspected people might implicitly associate high social class with higher morality, despite holding explicit stereotypes in the opposite direction, and these implicit associations might explain the effect of target social class on trust. We therefore developed a novel version of the BIAT in Studies 7A-7G where participants first learned that some faces had low social class and others, high social class, and then viewed these faces as stimuli within the BIAT. In our pre-registered test of this task, Study 8, people implicitly associated high social class with higher morality, despite reporting explicit stereotypes associating high social class with lower morality. Moreover, these implicit stereotypes predicted choices in the morality trust scenario. Both implicit and explicit morality stereotypes had significant independent effects in predicting trust (though only the 123 explicit morality stereotype effect held controlling for implicit and explicit competence stereotypes). This suggests that these implicit stereotypes could help to explain why people prefer to trust higher-class individuals in the scenario studies: Because they implicitly associate them with high morality. However, this is not a fully satisfying explanation. Why did implicit stereotypes presumably not play a role in Chapter Two’s findings, where people showed a strong preference to trust lower-class individuals? One might think that this has something to do with the fact that in the scenario paradigm people make fast, repeated decisions where automatic associations could have more influence than in a context like the trust game, where they can carefully consider and control their responses (Greenwald et al., 2009). But when we manipulated deliberation time in the scenarios, it did not affect rates of trust towards higher versus lower class targets, so this seems unlikely. Indeed, a large meta-analysis of 217 studies shows that despite researchers’ expectations that implicit attitudes should predict behavior that is difficult to control more than behavior that is easy to control, in fact controllability did not predict the size of the relationship between implicit attitudes and behavior (Kurdi et al., 2018). This meta-analysis does suggest one methodological reason why our measure of implicit attitudes might predict the scenarios and not the trust game results, though it does not address the conceptual disconnect between the implicit attitude results and the trust game results. Specifically, implicit attitude – behavior correlations are larger when there is higher correspondence between the implicit attitude measure and the behavior measure, meaning that the two measures share similar targets and similar actions towards those targets (Ajzen & Fishbein, 1977; Greenwald & Lai, 2020; Kurdi et al., 2018). The IAT we created uses almost identical targets to the scenarios, and both involve repeated fast decisions when images and 124 words are presented on screen. In contrast, the trust game used different targets and a very different form of decision-making. This might help to explain why implicit attitudes would relate more to the scenario paradigm than the trust game paradigm. (Note, though, that we did not test this directly: We are assuming that implicit attitudes would be unlikely to predict trust game decisions based on the lack of fit between people’s implicit associations with higher-class people as more moral, and people’s decisions to trust lower-class people more in the trust game.) At any rate, this explanation is still somewhat unsatisfying, as it suggests that if we properly captured implicit attitudes in a way that paralleled the trust game, they would predict the trust game results – but if people’s implicit attitudes indeed favor the wealthy, it is hard to see how that could mesh with trust game results favoring the poor. It seems more likely that there is a conceptual, rather than methodological, reason that people’s trust game decisions match their explicit stereotypes while their trust scenario decisions match their implicit stereotypes. Is the Discrepancy Resolved? In short, no. The legality manipulation did not have consistent effects across the two morality scenarios, and did not cause people to choose to trust lower-class individuals more than higher-class ones. The student manipulation did cause people to trust lower-class individuals more, but the effect was weak and not significantly different from the non-student condition. Implicit stereotypes did match the pattern of trust in the morality scenarios, but it is unclear why they would operate here and not in the trust game – and, explicit and implicit stereotypes both predicted outcomes in the trust scenarios, with explicit stereotypes having a somewhat larger effect. However, it might be that all three of these explanations, operating together, could fully explain the discrepancy in results: Perhaps a trust game study with targets who were complete strangers (not fellow participants on the same research platform), where betraying someone’s 125 trust involved contravening official rules of the game, and where an implicit measure was tailored to match the targets and setup of the game, would reveal effects in line with the scenario study findings. Other Potential Explanations It is also possible that other factors are at play beyond those we tested here, and that – potentially in combination with those we found evidence for above – they would help to resolve the discrepancy. To consider what factor this might be, it is helpful to review the evidence accumulated thus far. Table 27 summarizes all the trust situations used in this dissertation – including the trust game and scenarios used in Chapter Two – and their results. (See also Table 14 for a more detailed summary of each study’s methods and results.) Table 27 Summary of trust scenarios used across studies and their results. Higher trust towards lower-class targets No difference Higher trust towards upper-class targets Trusting someone to fairly report the outcome of a coin flip Trusting someone in your club to be the treasurer for the club Trusting someone at a train station to watch your bag while you go to the bathroom Trusting someone not to take advantage of your social faux pas Trusting someone not to take your spot in line at the doctor’s office Trusting someone to be honest in a used car sale Trusting someone to fairly return a portion of what you gave them in the trust game. Trusting someone to take care of your cat. Trusting someone to babysit your child Trusting someone to take care of your plants. Note. The only result that does not follow the pattern described here is the student condition of Study 6A, which used the doctor’s office scenario and found higher trust towards lower-class targets. All other studies that used this scenario found no difference in trust. One factor that could account for all these discrepancies is potential reputational cost. People might believe that higher-class people are less dispositionally moral overall (as their explicit stereotypes demonstrate), but also less willing to potentially lose reputational face and status in public settings. All the scenarios where people were more likely to trust higher-class 126 individuals are those where it would be easy to identify the person who betrayed one’s trust. In the train station scenario, one could easily be caught for stealing a bag in public. The other three scenarios all involve betrayal that would be easy to notice (if the car stops working, the child tells the parent the sitter harmed them or stole from the house, or if items are missing from the house and only the plant-sitter had access to it), and direct contact with the target, who would have to be the person who committed the betrayal (the used car sale is not through a dealer – instead the buyer and seller deal with each other directly; the baby- and plant-sitters are directly hired by the baby’s or plant’s parent). In contrast, all the scenarios where people trusted lower-class individuals more are those where it would be difficult to know whether one had been betrayed and if so, by whom. In the coin flip scenario (where someone flips a coin to see who should get to win a vacation), only the coin flipper knows what the coin truly said. In the social faux pas scenario (where someone could close the rude message about the boss on the work computer, or leave it up for the boss to see), one would not know if the boss saw the message or not (and if they did, another coworker could have told the boss about the message). In the trust game, the targets are anonymous, and there would be no way to find out who failed to return a fair share of the resources. In the scenarios where there is no preference for lower- versus higher-class targets, it is unclear whether one would know whether a betrayal had occurred and if so, who committed it. In the treasurer scenario, we did not specify whether it would be easy to tell that the treasurer had stolen money from the club – some participants might have assumed this would be obvious, while others might have assumed it would be difficult to tell. In the doctor’s office scenario, we did not specify what would happen upon returning to the doctor’s office if the target betrayed one’s trust. Some participants might have assumed it would be obvious that their spot in line was 127 taken and the person who had taken the spot would still be there (meaning they could publicly accuse them), while others might have assumed the person would have left and it would not be easy to tell if one’s spot had been taken or if the number was simply skipped. In the cat scenario, some participants might have thought it would be easy to tell if their cat sitter was neglectful or cruel, while others might have thought the cat’s inability to speak would pose a problem there. In other words, in situations where it would be easy to identify a betrayal, and easy to identify the perpetrator of that betrayal, people are more likely to trust higher-class individuals over lower-class ones. In contrast, when it would be difficult to identify a betrayal, or difficult to identify who committed that betrayal if it did occur, people are more likely to trust lower-class individuals over higher-class ones. When it is unclear whether the betrayal and betrayer would be identifiable, people show no preference based on social class. This suggests that people might believe higher-class individuals are less willing to risk harming their reputation, and therefore people feel more comfortable trusting these individuals in situations where betrayal carries a risk of harm to the betrayer’s reputation. Presumably in such situations the rate of betrayal is low overall – people might therefore believe that only those with a great situational temptation and little to lose in terms of reputation would be willing to betray. In other words, if there is a potential cost to the betrayer’s reputation, people might attend more to situational temptation to determine who would be willing to accept this cost given the benefits of betrayal. In contrast, people might believe that in general, lower-class individuals are more moral and trustworthy, and therefore feel more inclined to trust these individuals when betrayal would be easy and unidentifiable. Presumably in such situations the rate of betrayal is high overall – people might therefore believe that those who are dispositionally more moral are less likely to betray. In other 128 words, if there was no potential cost to reputation, people might attend more to explicit morality stereotypes to determine who would refuse to betray even when betrayal is easy and low-cost. We did attempt to test this explanation in an additional study, but were unable to successfully manipulate reputational costs. Future research should investigate this as a potential resolution to the discrepancy identified here, and more broadly as a nuance of social class morality stereotypes. Evaluating the Three Pathways to Trust in Morality, and Adding a Moderator We proposed three pathways from social class to beliefs about morality to trust. This reasoning about reputational costs suggests a moderator of two of these pathways: If betraying trust carries reputational costs, people might attend more to situational temptation; if betrayal carries little or no reputational costs, people might attend more to explicit dispositional stereotypes. Figure 9 depicts these proposed relationships. Figure 9 Theorized potential pathways explaining the relationship between social class and trust. Black icons and arrows indicate empirically supported pathways; grey icons and arrows indicate weak empirical evidence; blue dashed arrows indicate theorized but untested pathways. 129 We began, in Chapter Two, by testing explicit dispositional moral stereotypes and beliefs about temptation towards immorality based on people’s situation. People believed those with low social class were more dispositionally moral than those with high social class, but also more situationally tempted to betray trust for financial gain. Only this first dispositional pathway predicted trust. This makes sense in the context of decades of research suggesting that at least Westerners might prioritize dispositions and pay little attention to situations (Choi et al., 1998; Choi & Nisbett, 1998; Kelley & Michela, 1980; Sabini et al., 2001). For example, one of the most well-known findings in social psychology is the fundamental attribution error, people’s tendency to attribute others’ behavior more to their disposition than to their situation (e.g., Ross, 1977). Other classic studies show we spontaneously infer others’ traits when given even a shred of information about their behavior (e.g., Winter & Uleman, 1984), assume others’ behavior is more consistent across situations than it really is (e.g., Kunda & Nisbett, 1986), and believe others’ behavior to be caused by their disposition even when there is a clear situational reason for the behavior (e.g., Jones & Harris, 1967). Similarly, when predicting others’ future behavior, people tend to rely more on dispositional than situational information (Newman, 1996; Nisbett, 1987; Nisbett et al., 1973). In line with this accumulated literature, Chapter Two participants consistently trusted the lower-class target, whom they stereotyped as warmer and more moral, but more situationally tempted towards immorality, than higher-class targets. In Study 4 as well as in Supplemental Study A3, and across two measures of trust, perceptions of dispositional morality predicted trust more strongly than perceptions of situational temptation. Even when we increased the temptation targets might face by increasing the stakes a thousandfold, people continued to trust the lower-130 class target more than the higher-class one, and we found only weak evidence that they weighed situational temptation slightly more in that decision. But, in Chapter Three, the main effect of target social class on trust differed, suggesting that something about the way we measured trust affected the pathways through which people made their trust decisions (e.g., making them focus more on their implicit stereotypes), or moderated the effect of these pathways (e.g., because the targets were complete strangers, participants might have assumed they had extremely low social class and therefore stereotyped them as low in morality, unlike peers at a university or on a study participation platform as in Chapter Two). This highlights the fact that the line between these pathways may not always be easy to draw. The dispositional inference we focus on here, based on warmth and morality stereotypes, is one people draw based others’ social class, which itself could be described as a situation. This blurs the line between disposition and situation: If someone’s (situational) social class changes, the (dispositional) stereotype others ascribe to them is likely to change as well. It may also affect the weight people put on situations: If someone is in a situation of desperate financial need, trusters may be more wary of their susceptibility to that powerful temptation. Despite our numerous studies, we are unable to present a full and comprehensive picture of the complex set of associations between social class, trust, these four mechanisms, and the many potential moderators of these mechanisms. Future research should measure all four potential pathways in order to compare their relative predictive power, and bear in mind that their effects may differ based on the specific trust question, the specific targets, and the specific participant. Implications Even without fully resolving the theoretical picture and the discrepancy in our results, the results themselves have important implications. First, to the degree Chapter Two’s findings 131 replicate in at least some real-world contexts, that would indicate that in those contexts people from lower social class backgrounds are likely to gain more trust than those from higher-class backgrounds. This could have especially important consequences if those in power are frequently in the position of choosing to trust people who vary in social class. However, these choices across the social class spectrum may be relatively infrequent. For one thing, economic segregation in neighborhoods and social circles means that people are more likely to encounter those with similar (vs. different) social class to their own (Marques, 2012; Quillian, 2012; Thal, 2017). Thus, if a manager with a wealthy background mentions a job opening to their friends and family, they are likely to see job applicants who also have wealthy backgrounds, reducing their opportunities to place trust in a lower-class applicant. Also, those with lower (compared to higher) social class tend to (inaccurately) expect others to view them as less moral (Engstrom et al., 2023), which might make them less likely to put themselves in positions where others could trust them. Thus, a hiring manager for a position requiring a trustworthy employee might, again, see few applicants with low social class. Future research might study how promoting cross-class interactions could have important consequences for those at the bottom of the ladder by giving others more opportunity to trust them. However, this only applies to trust in morality. In Chapter Three, we also tested how social class influenced trust in people’s competence, with extremely consistent results: People almost always showed a very strong preference towards trusting higher-class individuals’ competence over that of lower-class individuals. This makes sense, as people also have strong explicit and implicit associations between high social class and competence. This effect likely has consequences for lower-class individuals’ ability to succeed financially, because many workplace decisions, like hiring and promotion, likely rely on trusting people’s competence. In 132 other words, even if there are many circumstances where, as in Chapter Two, people trust lower-class individuals’ morality, Chapter Three’s findings with competence may outweigh this, particularly for these kinds of trust that carry financial consequences. In this way, these effects on trust in competence likely have consequences for inequality. These consequences of trust in competence highlight the importance of going beyond social psychology’s typical focus on trust in morality. Second, if research using clear manipulations of legality of betrayal replicated the results we find here, that would again add nuance to what we currently know about social class morality stereotypes, and more broadly about how people perceive the social class hierarchy. If people suspect those with high social class of being more likely to commit immoral but legal actions, this suspicion might lead them towards low political engagement. If one believes that those at the top of the social class hierarchy can use their financial power to lobby for laws that benefit them at the expense of those at the middle or bottom of the hierarchy, and use existing laws to their own immoral advantage, there might seem to be little point in voting – it might seem unlikely that the government would implement laws that benefit ordinary people or reduce economic inequality. On the other hand, if people suspect those with low social class of being more likely to commit crimes, they might feel less inclined to support redistribution programs, because they feel that people who break the law do not deserve aid. These ideas are entirely speculative; future research might test them empirically. Third, if future research on the student variable replicated the results we obtained here, and specifically found that this effect was driven by people’s expectation that a lower-class student would not be an extreme example of a low social class individual, this would suggest an important boundary condition on the effect of target social class on trust. Though people believe 133 those with moderately low social class are more moral than those with high social class, this may not extend to those extremely low on the social class ladder. In our studies we manipulated target social class as a categorical variable, but future studies could attempt to manipulate it in a more continuous manner to find out where the inflection point is: At what rung on the social class ladder do people stop receiving positive stereotypes about their morality? Fourth, our implicit stereotype results demonstrate, for the first time, that people’s explicit morality stereotypes about the rich and poor diverge from their implicit stereotypes, and that these implicit stereotypes can predict important outcomes like trust. One reason for this divergence might be that people are motivated to report explicit stereotypes of people with low social class as being highly moral. According to system justification theory, people are motivated to feel that the social system in which they live is good, justified, and legitimate (Jost et al., 2004; Jost & Banaji, 1994). One important part of people’s social system is the economic hierarchy between the rich and the poor, and one way that people can justify this hierarchy is through stereotypes of richer people as more competent than poorer people: If people at the top of the hierarchy earned their position through hard work and intelligence, that hierarchy seems meritocratic and legitimate (Fu et al., 2019; Jost & Banaji, 1994). Thus, stereotyping wealthy people as competent likely helps people feel that the system is fair (S. T. Fiske & Durante, 2019). However, though this makes the system seem meritocratic, it also highlights the advantages held by those at the top: They have both the economic advantage and the advantage of being highly competent. System justification theorists therefore posit that people compensate those who are positively stereotyped on one dimension with negative stereotypes on the other. Viewing poor people as happy and moral (and rich people as miserable and dishonest) leads 134 people (especially liberals; Kay et al., 2009) to feel their society is fairer (Fu et al., 2019; Kay et al., 2007; Kay & Jost, 2003), because it seems that “poverty has its rewards and affluence its drawbacks” (Kay & Jost, 2003, p. 823). This suggests that people’s desire to feel their society is fair motivates them to apply these compensatory stereotypes in order to feel like every group has a fair set of advantages and disadvantages. This motivation may only operate on explicit stereotypes, making people feel better when thinking about the fairness of their social systems. Implicit stereotypes might reveal what people feel when their motivated cognition is not leading them to report otherwise: Generally more positive views of higher-status individuals, be they in terms of morality or competence. Indeed, other research has found people have more implicit positive associations with higher-status others than lower-status others, even when they themselves are part of the lower-status group (see Jost, 2019 for a summary). This work did not distinguish between competence and warmth, instead investigating only general positivity. Researchers interpreted this as evidence of system justification (favoring those at the top, even at the expense of one’s own ego). It might be that compensatory stereotyping is a more complex process that occurs only explicitly, and emerges after people have already applied these generally positive stereotypes, either implicitly or explicitly, to those at the top. Future research could investigate this question. Limitations We have already discussed the limitations to these studies in terms of resolving the discrepancy between chapters; other limitations also apply. For example, these studies all used White male or female targets – results might differ if we had used a more diverse set of target images due to intersectional race and social class stereotypes (Brown-Iannuzzi et al., 2021; Mattan et al., 2019). Moreover, our samples were either Canadian undergraduates or American 135 and British online survey workers. Social class stereotypes differ substantially across countries, for example based on the country’s income inequality (Durante et al., 2014) or history of communist governance (Grigoryan et al., 2020), so we could expect these effects to also differ across countries. These samples also restrict our range of participant social class: Undergraduates are already above the lowest possible social class, given their university attendance, and are more likely to come from high social class backgrounds (but unlikely to themselves be extremely high income, given their student status); online survey workers are also likely to be above the lowest possible social class (given that they have a smartphone or computer where they can complete studies), but are unlikely to be extremely high in social class (given that they are completing surveys for small amounts of money). With a more diverse range of participants, we might have found more effects of participant social class; in these studies, as in Chapter Two, we rarely found participant social class effects. These studies also highlight the challenges and limitations to using traditional psychological measures of trust: The trust game is artificial, and when we tried to create scenarios that would parallel its setup but use a more realistic context, we found completely different results. Future research would benefit from more ecologically valid measures, to determine what the true effect(s) of social class on trust may be. One feature that we did not test, which may improve the ecological validity of this investigation, might be to examine trust between people who know one another rather than trust between strangers. One study found that trust in the trust game predicts trust towards strangers but not towards targets whom the person knows (Weiss et al., 2021), so Chapter Two’s findings are unlikely to help in predicting how social class might influence trust among acquaintances or friends. It might be that people are not often in situations where they must trust a stranger and the only thing they know about that 136 stranger is their social class. But, everyday interpersonal interactions between people who know one another – including knowing each other’s social class – often require trust. Participant Social Class and Generalized Trust In most of this dissertation we focused on the question of interpersonal trust, or trust that occurs in a specific relationship between two individuals. In this case, we focused on how characteristics of one individual – their social class – affected how much others trusted that individual. However, in Chapter One, we pointed out that much of social psychological research on the relationship between social class and trust has instead focused on generalized trust, or how much one individual tends to trust other people in general. This work tends to find that higher-class individuals are more generally trusting than lower-class ones (Brandt et al., 2015; Fischer & Torgler, 2013; S. T. Fiske et al., 2012). Our findings in Chapter Two align to some extent with this general pattern. (We were not able to test these patterns in Chapter Three because the scenario studies always involved deciding to trust one of two targets, meaning that participants never had the option to display generally lower trust [e.g., by choosing neither target] or generally higher trust [e.g, by choosing both targets]). In Studies 2, 4, and A3 (see Appendix A), there were significant main effects of objective social class, such that those with higher incomes and educations trusted more overall. These studies all used large samples of UK adults recruited from Prolific Academic. The studies where this effect did not emerge used different, generally smaller samples of either Canadian undergraduate students (Studies 1, 3, and A2) or American adults recruited from MTurk (Studies A1.1-A1.3). Thus, this main effect may not have emerged in these latter studies for three reasons. First, they had relatively lower power to detect this between-subjects effect (an average sample size of 162.5, compared to 475 in the studies with a significant effect). Second, 137 undergraduate participants reported their parents’ income and education, whereas Prolific participants reported their own income and education; this information may have therefore been more directly relevant to their decisions in the trust game (though this cannot explain why MTurk participants – who also reported their own income and education –did not show the same effect). Third, Prolific participants come from the United Kingdom, rather than North America, which could suggest that the effect of social class on trust differs based on cultural context. However, in both Chapters 2 and 3 we were able to test for moderation by participant social class. In Chapter Two we found little evidence of ingroup favoritism – in Study A2 participants with higher subjective and objective social class were more likely to trust higher-class others, but this did not emerge in any other studies. In Chapter Three (see Appendix B) we found some evidence for ingroup favoritism: In Studies 5, 6B, and 6D, participants with higher subjective social class were more likely to trust higher-class others; this also emerged using objective class measures in Study 6D only. Thus, these ingroup favoritism effects are not consistent across measures or studies. Though we had not pre-registered any expections about such effects, their absence is somewhat surprising, given that people tend to trust and cooperate more with members of their ethnic or political ingroups (Balliet et al., 2014). One reason why our findings may diverge from this past work is that social class groups are different than the types of groups in which ingroup favoritism has commonly been demonstrated. One’s social class might change more readily (e.g., through job loss or inheritance gains) than other group memberships like race or gender (Beller & Hout, 2006; Blanden, 2013). Moreover, class can be highly subjective: A surprising number of people simply identify themselves as middle-class (Pew Research Center, 2015), even though they might possess certain features (e.g., high or low income or education) that make them higher- or lower-class in more 138 objective terms. Our measures of social class may thus not have been good proxies for participants’ sense of class similarity with the targets. Conclusion When asked what they thought about their partners in the economic game, one participant in Study 2 mentioned, “The last one is extremely rich – I can’t decide whether that will make her spoilt and on the selfish side, or generous as she already has plenty of money”. Our conflicting results in Chapter Two and Chapter Three show that participants land on different sides of this dilemma depending how we measure trust. Though most participants in Chapter Two seemed to land on the side of rich targets being selfish and untrustworthy, Chapter Three participants seemed to land on the side of rich targets being generous and trustworthy. We found some support for three potential explanations for this difference: betrayal in the trust scenarios often involved committing a crime (whereas in the trust game it was perfectly legal and permissible), the targets in the trust scenarios were often complete strangers who may have been extremely low in social class (whereas in the trust game they had a common social identity with the participant and were unlikely to be at the extreme end of the social class spectrum), and that people’s implicit morality stereotypes associated high social class with morality, matching their responses in the scenarios (whereas their explicit stereotypes associated low social class with morality, matching their responses in the trust game). The question of how social class influences trust is a thorny and complex one, with important implications for people’s relationships across social class lines. 139 References Aarøe, L., Osmundsen, M., & Petersen, M. B. (2016). 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Conservatism and perceptions of poverty: An attributional analysis. Journal of Applied Social Psychology, 23(12), 925–943. 161 https://doi.org/10.1111/j.1559-1816.1993.tb01014.x 162 Appendix A: Supplemental Material for Chapter Two This appendix provides supplemental information for Chapter Two. All sample sizes, data exclusions and analyses were pre-registered unless otherwise specified. Study 1 Items for Guessing Targets’ Demographics In Study 1, participants guessed demographics about the lower- and higher-class targets; see Table 28 for the full text of these items. The prompt was, “Please guess the correct answers to the following questions about the person whose profile is highlighted in [YELLOW / GREEN]” (with the color corresponding to the color-coded profiles for the lower- and higher-class targets). Participants answered the same questions about both targets, in random order. Table 28 Items for participants to guess targets’ demographics, Study 1. Item What is this person’s gender? [Male/Female] How old is this person? [10-102] What is this person’s ethnicity? [East Asian / White / South Asian / Hispanic / Black / First Nations, Metis, or Inuit] Imagine that this ladder shows how your society is set up. At the top of the ladder are the people who are the best off – they have the most money, the highest amount of schooling, and the jobs that bring the most respect. At the bottom are the people who are the worst off – they have the least money, little or no education, no jobs or jobs that no one wants or respects. Now think about the person whose profile is highlighted in [YELLOW / GREEN]. Please tell us where you think they would be on this ladder. [1-10] Study 2 Full Three-Way Interaction Results We examined whether the effect of target social class and condition were moderated by participant subjective or objective social class. These results are summarized in the main text; here we provide the full results in Table 29. Table 29 Three-way interactions between target class, participant class, and condition, Study 2. 163 Predictor Models with participant subjective social class Models with participant objective social class b SE t p b SE t p Intercept .33 .007 44.56 <.001 .33 .007 44.99 <.001 Control target -.04 .005 -6.79 <.001 -.04 .005 -6.91 <.001 Higher-class target -.04 .005 -8.20 <.001 -.04 .005 -8.37 <.001 Experimental realism .00 .007 .65 .515 .01 .007 .72 .472 Participant class .00 .004 .20 .840 .01 .005 2.17 .030 Control target × experimental realism .00 .005 .82 .411 .00 .005 .58 .561 Control target × participant class -.00 .003 -.81 .418 -.00 .003 -.76 .448 Higher-class target × experimental realism .01 .005 .97 .334 .00 .005 .84 .399 Higher-class target × participant class .00 .003 .20 .840 -.00 .003 -1.17 .242 Experimental realism × participant class .00 .004 .50 .620 -.00 .005 -.56 .576 Control target × experimental realism × participant class -.01 .003 -1.80 .072 -.00 .003 -.65 .515 Higher-class target × experimental realism × participant class -.01 .003 -2.09 .037 -.00 .003 -.47 .641 Note: Rows containing the key hypothesis test are bolded. Target is dummy coded. This model also includes covariates for which demographic pairing participants saw (effect coded), control target demographics (effect coded), and target avatar (effect coded). Because none of these covariates had effects approaching significance (all bs < |.008|, all ps > .275), we omit them from the table for brevity. Study 3 Results with Alternate Exclusion Criteria In Study 3, we pre-registered collecting a sample of N = 200. However, many participants failed the attention check, so we collected additional data (total N = 372) to ensure the study was adequately powered. We therefore present results using both possible samples – the original sample, only the first 200 participants we collected or the full sample, the total 372 participants we collected – using three different sets of exclusion criteria, all of which produce the same conclusion as analyses reported in the main text (see Table 30). Using the exclusion criteria laid out in our pre-registration (i.e., excluding participants who failed to correctly perceive the difference between the higher- and lower-class targets [original sample: n = 27, full sample: n = 54], were suspicious that their partners were not real [original sample: n = 4, full sample: n = 8], or who failed the attention check [original sample: n = 83, full sample: n = 163]) 164 resulted in final samples of 187 (full sample; this is what we report in the main text analyses) or 103 (original sample); some exclusions were overlapping. Dropping the overly potent attention check to retain more power resulted in final samples of 304 (full sample) or 169 (original sample). Maximizing power by including all participants resulted in final samples of 372 (full sample) or 200 (original sample). Table 30 reports the same analyses described in the main text for all six of these possible samples. Table 30 Multilevel regression analyses predicting trust (in the trust game) and cooperation (in the prisoner’s dilemma game) using different exclusion criteria, Study 3. Predictor Trust game Prisoner’s dilemma game b SE t p OR SE z p Full sample, pre-registered exclusion criteria (N = 187)—this analysis presented in main text Intercept 5.47 .22 24.98 <.001 .97 .21 4.55 <.001 Target class -.29 .11 -2.65 .009 -.28 .14 -2.04 .042 Profile combination -.12 .22 -.56 .576 .09 .18 .48 .633 Experimental realism .00 .22 .02 .986 .28 .18 1.50 .135 Target class × experimental realism .18 .11 1.63 .104 .06 .14 .46 .649 Full sample, pre-registered criteria except overly potent attention check (N = 304) Intercept 5.08 .18 29.03 <.001 .90 .18 5.09 <.001 Target class -.34 .08 -4.31 <.001 -.37 .11 -3.31 <.001 Profile combination .11 .17 .60 .548 .25 .15 1.61 .108 Experimental realism -.23 .18 -1.32 .188 .15 .15 .96 .338 Target class × experimental realism .14 .08 1.72 .086 .04 .11 .41 .682 Full sample, no exclusions (N = 372) Intercept 4.97 .16 31.44 <.001 .95 .17 5.65 <.001 Target class -.29 .07 -4.16 <.001 -.34 .10 -3.30 <.001 Profile combination .10 .16 .61 .540 .10 .14 .73 .469 Experimental realism -.22 .16 -1.41 .161 .16 .14 1.14 .254 Target class × experimental realism .13 .07 1.79 .074 .06 .10 .59 .552 Original sample, pre-registered exclusion criteria (N = 103) Intercept 4.92 .27 18.22 <.001 .71 .29 2.40 .016 Target class -.36 .15 -2.35 .021 -.43 .20 -2.21 .028 Profile combination -.09 .27 -.34 .738 .13 .27 .47 .640 Experimental realism -.11 .27 -.40 .690 .30 .28 1.09 .275 Target class × experimental realism .24 .15 1.59 .115 .05 .19 .25 .800 Original sample, pre-registered criteria except overly potent attention check (N = 169) 165 Intercept 4.96 .22 22.61 <.001 .77 .26 3.00 .003 Target class -.42 .11 -3.87 <.001 -.38 .16 -2.42 .016 Profile combination .08 .22 .35 .729 .47 .24 1.96 .050 Experimental realism -.24 .22 -1.10 .275 .35 .24 1.48 .138 Target class × experimental realism .21 .11 1.94 .054 .05 .15 .31 .755 Original sample, no exclusions (N = 200) Intercept 4.90 .21 23.85 <.001 .85 .26 3.29 <.001 Target class -.39 .10 -3.99 <.001 -.36 .15 -2.44 .015 Profile combination .11 .21 .53 .599 .23 .23 .98 .326 Experimental realism -.22 .21 -1.09 .279 .38 .23 1.60 .110 Target class × experimental realism .20 .10 2.01 .046 .08 .14 .567 .571 Note: Rows containing the key hypothesis tests are bolded. Study 4 Additional Mediation Models We conducted additional mediation models in Study 4 to supplement those reported in the main text. Mediation by Dispositional and Situational Stereotypes, Separated by Condition We tested mediation by moral disposition and situational temptation separately for each temptation condition; see Figure 10. Figure 10 Mediation of the effect of target social class on trust through moral dispositions and situational temptation, separately for the low and high temptation conditions, Study 4. Note: †p < .10 *p < .05 **p < .01 ***p < .001 These analyses showed similar effects as those reported in the main text: Participants viewed the lower-class target as significantly more moral than the higher-class target, and this in 166 turn predicted increased trust, with significant indirect effects (low temptation condition = -5.90, p < .001, 95% CI [-8.11, -3.70], high temptation condition = -4.79, p <.001, 95% CI [-6.79, -2.80]). Participants viewed the lower-class target as more situationally tempted towards immorality than the lower-class target, though this effect was only significant in one of these separate halves of the sample; situational temptation did not significantly predict trust, and did not have significant indirect effects (low temptation condition = 0.02, p = .911, 95% CI [-0.26, 0.29], high temptation condition = 0.43, p = .122, 95% CI [-0.11, 0.97]). Mediation by Relational Models, Moderated by Condition In the main text, we report models examining mediation of the effect of target social class on trust by relational models, collapsed across condition. Here, we examined whether the b links between each relational model and trust vary based on condition, using the same strategy as in the main text; see Figure 11 and Table 31. The b links did not differ significantly by condition for any of the relational models. Figure 11 Relational models mediating the link between target social class and trust, moderated by temptation condition. †p< .10 *p <.05 **p <.005 ***p < .001 167 Table 31 Interaction and indirect effects from moderated mediation models examining relational models as mediators between target social class and trust, moderated by temptation condition. Mediator Interaction Indirect effect, low temptation condition Indirect effect, high temptation condition b SE p b CI95 p b CI95 p Communal -1.83 1.33 .168 -7.78 [-10.06, -5.50] <.001 -5.87 [-8.10, -3.64] <.001 Equality -1.22 1.81 .500 -4.62 [-5.79, -2.34] <.001 -3.31 [-5.06, -1.56] <.001 Market 2.14 1.67 .201 -0.84 [-1.74, 0.07] .071 -0.06 [-0.89, 0.78] .892 Authority 0.30 1.35 .823 -3.32 [-5.13, -1.50] <.001 -3.06 [-4.76, -1.35] <.001 Testing Independent Effects of Dispositional Variables In one additional exploratory (not pre-registered) model, we tested whether the dispositional variables (stereotypes about morality and each relational model) had independent indirect effects on trust by including all five variables as parallel mediators in the same model, collapsing across temptation condition; see Table 32 After accounting for all five mediators, the direct effect of target social class on trust was still significant, b = -3.90, p = .009; as noted in the main text, the strongest independent mediator was morality stereotypes. Table 32 Testing independent effects of dispositional mediators, Study 4. Mediator Class  mediator Mediator  trust Indirect effect b p b p b CI95 p Morality -.67 <.001 6.45 <.001 -4.31 [-5.90, -2.72] <.001 Communal -1.04 <.001 2.29 .043 -2.38 [-4.70, -0.07] .044 Equality -.62 <.001 .93 .468 -0.58 [-2.15, 0.99] .469 Market .36 <.001 -.66 .446 -0.24 [-0.86, 0.38] .449 Authority .86 <.001 -2.04 .009 -1.74 [-3.07, -0.41] .010 Supplemental Studies A1.1-A1.3: Trusting Others on MTurk Studies A1.1-A1.3 sought to further replicate the core finding from Studies 1-4 using a similar method to Study 2 on different recruitment platform: Amazon Mechanical Turk. However, this platform yielded substantially poorer data quality than Studies 1-4 and Studies 168 A2-A3 (see below). Individually, each sample lost too much power to properly test our predicted effect, but analyses across all three samples combined were well-powered and consistent with Studies 1-3 (and Studies A2-A3). Studies A1.2 and A1.3 contained measures similar to those used in the mediation models in Study 3, providing an additional opportunity to replicate these findings (with the caveat that the data quality is much poorer in these studies). Study A1.1 was exploratory and included only Study 2’s hypothetical condition; Studies A1.2 (https://osf.io/bwqjy/?view_only=7b3d18879dba45168a312d8bf38d70ba) and A1.3 (https://osf.io/u9me6/?view_only=db4d40a6fd4c40bebffff0e48c771997) included only the real condition and were pre-registered to replicate the pattern from Studies 1-4. Method Participants For each study we planned to collect data from 200 Amazon Mechanical Turk participants; in total 200 people participated for Study A1.1, 203 for Study A1.2, and 204 for Study A1.3. Only participants located in the US, who had received at least a 95% approval rating, and who had completed fewer than 5000 MTurk HITs were permitted to participate. Studies A1.2 (n = 8) and A1.3 (n = 6) excluded participants who suspected they were not actually interacting with other people in the game; this exclusion criterion did not apply for Study 1A as this study was hypothetical. All three studies excluded participants who failed an attention check about the rules of the trust game similar to that used in Study 2 (Study A1.1: n = 28; Study A1.2: n = 32; Study A1.3: n = 22). We also excluded people who failed to correctly perceive the difference between the lower-class and higher-class targets (Study A1.1: n = 43; Study A1.2: n = 59; Study A1.3: n = 25). In Study A1.1 and A1.2 we assessed this perception as 169 we had in Study 2; Study A1.3 used a simpler check where participants viewed both profiles side by side and selected which partner had higher social class than the other. These criteria excluded participants at rates were far greater than we had anticipated, between 22 and 36%, leaving us with sample sizes of only 147 for Study A1.1, 130 for Study A1.2, and 160 for Study A1.3 (see Table 33 for demographics). This reduced our power to an average of 67% for d = .20, meaningfully below our target 80%. Moreover, additional analyses described below indicated that the data quality in these samples was lower than in our other studies. For transparency, we still report the results for individual studies, but given their unexpectedly low power we also pool the data across the three studies (N = 437, power >99% for d = .20), placing more emphasis on those higher-powered analyses. Table 33 Demographics for individual Studies A1.1-A1.3. Variable Pooled data Individual study data A1.1 A1.2 A1.3 N after exclusions 437 147 130 160 Power for d = .20a >99% 67% 62% 71% Class ladder M (SD) 5.08 (1.67) 5.02 (1.61) 4.93 (1.57) 5.27 (1.79) Range 1-10 2-9 1-8 1-10 % with income in CADb < $50K 33 30 27 41 > $50K & < $100K 44 46 52 37 > $100K 23 24 22 22 % with education no college degree 31 34 32 28 college degree 56 54 56 58 postgraduate degree 13 12 12 14 % women 46 50 44 44 % men 54 50 56 56 % another gender 0 0 0 0 age M (SD) 35.46 (11.47) 34.15 (10.83) 37.22 (11.21) 35.25 (12.15) % selecting ethnicity 170 Note: We included other ethnicity options and more fine-grained income and education options but present these coarser groupings for brevity. a Under G-power’s default assumption that within-subjects measurements are correlated at .5). bWe asked about income in USD, but converted to CAD to more easily enable comparisons with the demographics for other studies. Data Quality Across studies, we compared participants’ performance on attention checks, ability to correctly perceive the difference between the higher- and lower-class targets, and quality of text responses; see Table 34. To measure text response quality, two coders blind to the study read through (1) responses to the suspicion questions and (2) chat conversations, and flagged low-quality responses (e.g., nonsense responses). Coders discussed any disagreements and came to consensus. Across all metrics, Studies A1.1-A1.3, the only studies conducted on MTurk, showed lower quality than the other studies we report for Chapter Two. Table 34 Data quality across studies. Study % failed attention check % failed to correctly perceive difference between lower- and higher-class targets % low-quality text responses % low-quality chats 1 n/a (not included) 7.5 0.5 n/a (no chats) 2 2.7 5.0 8.6 15.6 3 see notea 14.5 3.5 11.4 4 3.4 n/a (not included) 0.7 n/a (no chats) A2 5.9 13.4 3.0 18.3 A3 3.0 n/a (not included) 1.0 n/a (no chats) 1,2,3,4, A2,A3 average 3.8 10.1 2.9 15.1 White 78 76 83 74 East Asian 3 4 3 3 South Asian 2 0 2 3 Black 12 10 10 11 Another ethnicity 5 10 2 9 171 A1.1 15.8 29.1 14.8 20.1 A1.2 10.8 21.5 17.6 16.7 A1.3 14.0 see noteb n/a (no text responses) n/a (no chats) A1.1-A1.3 average 13.5 25.3 16.2 18.4 Notes: aStudy 3 did include an attention check, but as noted in the main text it was included in no other study because it proved too difficult (41.4% of the sample failed), requiring participants to read a long chunk of instructional text to discover that they should ignore the question beneath it. The attention checks in Studies 2, A1.1-A1.3, and A2 were directly comparable, asking a simple question about the rules of the game (e.g., “If Person A gives $0.05 to Person B, what would Person B receive?” response options = $0.05, $0.10, $0.15 (correct), $0.20, $1.50). bStudy A1.3 did include a manipulation check, but it was much easier than those included in the other studies (12.3% of the sample failed). Participants got to see the two profiles again, and simply had to indicate which between the two had higher social class, giving them a 50% chance of passing even if they only guessed randomly. In each of the other studies, the manipulation checks were more difficult since they required participants to answer separate questions about the lower- and higher-class targets. Procedure These studies followed a procedure similar to Study 2. Given that experimental realism did not moderate findings in Study 2 or 3, the exploratory Study A1.1 employed the hypothetical condition, whereas the pre-registered Studies A1.2 and A1.3 employed the real condition. In all three studies, participants played four rounds of the trust game: One in the role of trustee with a filler target, and three in the role of truster with key targets: One key target had lower social class, one had higher class, and the third was a control target, as in Studies 1, 2, and 4. Target Social Class. We used profiles that, like in Studies 2 and 4, provided straightforward information about social class rather than indirect hints (see Table 35 for examples). All profiles provided targets’ answers to questions about their gender and age; in Studies A1.1 and A1.2 the higher- and lower-class profiles each provided targets’ answers to one of two additional sets of questions. As in Studies 1 and 3, we varied whether the higher-class 172 target answered the first and the lower-class the second set of questions, or vice versa, but unlike Studies 1 and 3, the questions called for closed rather than open-ended responses. The first set of questions asked about one target’s home state, number of siblings and, crucially, family income; the second asked about the target’s handedness, ethnicity (always White) and, crucially, self-reported position on the class ladder. In other words, some participants saw one target with low family income and another with high self-reported social class; other participants saw one with high family income and another with low self-reported social class. After running Studies A1.1 and A1.2, we wondered if participants had found this comparison difficult to make, so in Study A1.3 we used only one set of questions that both targets answered: gender, age, home state, number of siblings, handedness, ethnicity, and position on the social class ladder. Table 35 Sample profiles manipulating target social class, Studies A1.1-A1.3. Studies A1.1-A1.2 Profiles Study A1.3 Profiles Lower-class Higher-class Lower-class Higher-class 173 Note: Approximately half participants saw these versions of the profiles; the other half saw other versions that counterbalanced the differences. For example, in Studies A1.1-A1.2, the other versions provided home state, sibling and income (“above $150,000”) information for the higher-class target, and handedness, ethnicity and ladder position (rung 2) for the lower-class target. As in Studies 1, 2, and 4, we also included a control target, whose profile indicated only that the target was either a 24-year-old female or a 21-year-old male (counterbalanced across participants), and a filler target with whom participants always played the role of trustee and therefore made no trust decisions. In Studies A1.2-A1.3, participants were paired to serve as each other’s filler target, and each pair had a four-minute online chat; in Study A1.1 participants simply imagined this procedure (similar to the real and hypothetical conditions of Studies 2-3, respectively). In Studies A1.1 and A1.2, participants viewed information about all targets at once; in Study A1.3 they viewed a page with all four avatars, and clicked on them in whatever order they chose until they had seen all four profiles. 174 Trust Game. The trust game was similar to Studies 2 and 4, except that we varied participants’ starting endowment, randomly assigning them to begin their rounds as truster with either $0.40, $0.50, or $0.60, randomly allocated across the three rounds. They were allowed to transfer any amount in five cent increments. Given that this increment carried a different significance depending on the starting amount, we converted participants’ behavior into the proportion of the initial endowment that they transferred to each partner. Participant Social Class. Participants answered the same questions as in Studies 2 and 4 for social class, except that they reported their income in USD instead of pounds. Exploratory Mediators. Each of these studies contained slightly different mediators. Study A1.1 did not contain any measures relevant to dispositional and situational mechanisms. In Study A1.2-A1.3 though, we measured dispositional warmth with one item, “How warm do you think this person is?” [1 = not at all, 7 = very warm]. These studies also contained additional mediators and moderators not relevant to our theoretical rationale; see the Exploratory Mediators section of Appendix A for details. Results Primary Analyses: Trust Behavior For each study, we ran similar multilevel models as prior studies in which we predicted trust with partner social class (dummy coded with the lower-class target as the reference group), participant social class (centered) and their interaction, and random intercepts for participants; see Table 36, right three columns. We also included covariates for starting endowment (centered) and target avatar (effect coded), demographics information paired with higher- versus lower-class target (effect coded), and demographics information of control target (effect coded); we omit the latter two from the table for brevity as their effects never approached significance. To 175 maximize statistical power across these similarly designed studies, we also ran models pooling the data across these samples, including random intercepts for study to account for differences between them (leftmost columns of Table 36). As in previous studies, we first ran the models without participant social class, and then ran models including participant social class and its interaction with target social class. Table 36 Multilevel regression analysis predicting trust, Study A1.1-A1.3. Predictor Pooled, Study A1.1-A1.3 Study A1.1 Study A1.2 Study A1.3 b SE t p b p b p b p Models without participant class Intercept .61 .02 32.57 <.001 .58 <.001 .66 <.001 .61 <.001 Control target -.02 .01 -1.83 .067 .02 .449 -.03 .035 -.05 .009 Higher-class target -.03 .01 -2.49 .013 -.03 .161 -.02 .137 -.03 .076 Endowment -.12 .06 -2.25 .024 -.21 .065 -.21 .009 .02 .831 Avatar – bird -.01 .01 -.94 .350 -.03 .036 .01 .358 .00 .993 Avatar – turtle -.00 .01 -.57 .570 .00 .985 -.01 .175 .00 .686 Models with participant subjective class Intercept .61 .02 33.47 <.001 .58 <.001 .66 <.001 .61 <.001 Control target -.02 .01 -1.83 .067 .02 .437 -.03 .035 -.05 .007 Higher-class target -.03 .01 -2.49 .013 -.03 .142 -.02 .136 -.03 .068 Participant social class -.01 .01 -.62 .537 .02 .218 -.03 .116 -.01 .371 Control target × participant class -.01 .01 -.96 .337 .01 .463 -.01 .563 -.02 .072 Higher-class target × participant class -.00 .01 -.20 .839 -.04 .013 .00 .644 .02 .030 Endowment -.12 .06 -2.22 .026 -.23 .046 -.20 .011 .05 .545 Avatar – bird -.01 .01 -.93 .353 -.03 .009 .01 .321 -.00 .978 Avatar – turtle -.00 .01 -.56 .573 .01 .611 -.01 .183 .01 .483 Models with participant objective class Intercept .61 .02 32.71 <.001 .58 <.001 .66 <.001 .61 <.001 Control target -.02 .01 -1.83 .068 .02 .444 -.03 .036 -.05 .008 Higher-class target -.03 .01 -2.49 .013 -.03 .150 -.02 .138 -.03 .069 Participant social class -.00 .01 -.11 .911 .01 .620 -.01 .594 -.01 .723 Control target × participant class -.01 .01 -1.02 .308 -.01 .338 -.00 .622 -.00 .801 176 Higher-class target × participant class -.00 .01 -.27 .786 -.03 .024 -.00 .637 .03 .005 Endowment -.12 .06 -2.26 .024 -.21 .068 -.21 .009 .05 .552 Avatar – bird -.01 .01 -.89 .372 -.03 .029 .01 .371 .00 .850 Avatar – turtle -.00 .01 -.55 .582 .00 .795 -.01 .190 .00 .697 Note: Rows containing the key hypothesis test are bolded. The more highly powered analyses of the pooled dataset replicated Studies 1-4: In all three cross-study models, participants trusted lower-class targets more than higher-class targets (significantly, d = .13) and control targets (marginally, d = .09). There was no significant difference between higher-class and control targets (d = .03). There were also no significant interactions with participant social class (subjective or objective). In each individual lower powered dataset, the difference in trust between the lower- and higher-class targets trended in the same direction as in previous studies, but never reached significance. Exploratory Mediation Analyses Figure 12 Exploratory mediation analysis, Study A2B-A2C pooled. We next used the lavaan package in R (Rosseel, 2012) to run an exploratory (not pre-registered) multilevel mediation model, with each variable nested within participant, of target social class predicting trust mediated by warmth. These analyses use only Studies A1.2-A1.3, not A1.1, as A1.1 did not include a measure of warmth. We present only the pooled analyses across Studies A1.2-A1.3 (including study as a covariate), as the individual studies are underpowered to detect mediation paths. Results paralleled our other mediation analyses and supported the 177 dispositional account: Participants viewed lower-class targets as warmer than higher-class ones, and perceiving a target as having a warmer disposition predicted higher trust behavior; see Figure 12. This indirect effect was significant, indirect effect = -.01, p = .017, 95% CI [-.012, -.001]. Supplemental Study A2: Trusting Others with Time Together, Studies 1-4 find that people trusted lower-class more than higher-class individuals with their money or raffle tickets for a gift card. However, another interpretation of these results has nothing to do with trust. Our participants may have given their money (or chances at a gift card) to the target who needed it more, without regard to whether the target would return any of it. We designed this supplemental study to provide a replication in a situation where this alternative would not apply, by having participants play the trust game for a non-financial resource: time. If participants were transferring more to the lower-class target than the higher-class target in our studies simply because they wanted to help this target financially, then changing the trust game to use a non-financial resource should eliminate any difference in trust based on target social class. In contrast, if participants were transferring more to the lower-class target than the higher-class target because they saw them as dispositionally more trustworthy (and therefore genuinely trusted them to return more resources), changing the trust game to use a different resource should not eliminate this difference. Thus, in this study, participants played the trust game for the real chance to leave the study early, rather than for money or raffle tickets. This study was pre-registered (https://osf.io/yp6jm/?view_only=9eccc12511644e5491ee6366db710778). Method Participants 178 We collected data from 202 undergraduate participants. We excluded those who failed to correctly perceive the difference between the lower-class and higher-class targets as in Studies 1 and 3 (n = 27), and who were suspicious that they were not actually interacting with other people in the game (n = 2), leaving a final sample of 173 (power = 74% for d = .20); see Table 37 for demographics. Table 37 Demographics, Study A2. Variable Statistic Class ladder M (SD) 6.76 (1.18) Range 3-9 % with parental income in CAD < $50K 16 > $50K & < $100K 39 > $100,000 45 % with parental education no college degree 19 2- or 4-year college degree 49 postgraduate degree 31 % women 79 % men 21 % another gender 0 age M (SD) 21.44 (4.29) % selecting ethnicity White 22 East Asian 50 South Asian 16 Black 2 other 10 Note: We included other ethnicity options and more fine-grained income and education options but present these coarser groupings for brevity. Procedure The procedure was similar to that of Study 3 (in the real condition). Participants played three rounds of the trust game: One in the role of trustee with a filler target, and two in the role of truster with key targets (one with lower social class and one with higher class). As in Study 3 (but unlike our other studies), there was no control target. 179 Target and Participant Social Class. We manipulated target social class, and measured participant social class, in the same way as Study 1 and 3. Trust Game. The trust game was similar to Studies 1-4, but participants played for time credits rather than raffle tickets or money. The truster began each round with 10 credits, each of which permitted the participant to leave the study one minute early. Given the mechanics of the trust game, participants would therefore end each round with between 0 and 30 credits. We informed them that one of their three rounds would be randomly selected to determine how early they would get to leave. To ensure participants were motivated to get as many credits as possible, we warned them that any time spent in the study in the last 30 minutes (i.e., any time they did not have enough credits to discount from their participation) would involve filling out tedious questionnaires of many slightly different versions of the same question for pilot-testing purposes. In fact, the study only took 30 minutes, not an hour as advertised, so all participants left the study 30 minutes early. Results We followed a similar analysis strategy as previous studies, but this time we pre-registered including profile combination as a random intercept instead of a fixed effect. Replicating the previous pattern, participants trusted the lower-class target with about half a credit (worth half a minute) more, d = .27, than the higher-class target; see Table 38. Table 38 Multilevel regression analyses predicting trust, Study A2. Predictor b SE t p Model without participant class Intercept (lower-class target) 5.95 .25 23.57 .016 Higher-class target -.50 .14 -3.49 <.001 Model with participant subjective class Intercept (lower-class target) 5.96 .27 1.10 .022 Higher-class target -.50 .14 -3.49 <.001 180 Participant subjective class (centered) -.18 .20 -.86 .390 Higher-class target × participant class .22 .12 1.80 .074 Model with participant objective class Intercept (lower-class target) 5.92 .24 24.52 <.001 Higher-class target -.45 .13 -3.33 .001 Participant objective class (centered) -.07 .15 -.46 .644 Higher-class target × participant class .19 .09 2.21 .029 Note: Rows containing the key hypothesis test are bolded. For the first time, we found interactions, one significant and one marginal, between target and participant social class: Participants with lower social class showed a stronger effect than those with higher social class. This pattern is intriguing, but did not emerge in any other Chapter Two studies and therefore should be interpreted with caution. Supplemental Study A3: Pilot for Study 4 We ran Study A3 as a pilot test of the mechanism measures (moral dispositions and situational temptations) and new trust measures (scenarios) to be used in Study 4. This study follows a similar method as Study 4, but did not include a temptation manipulation. This study was not pre-registered. Method Participants We collected data from 305 UK participants recruited through Prolific Academic. We excluded participants who failed the same attention check from Study 2 and 4 (n = 9), leaving a final sample of N = 296; see Table 39 for demographics. Table 39 Demographics, Study A3. Variable Statistic Class ladder M (SD) 5.09 (1.60) Range 1-9 % with income in CADb < $50K 40 > $50K & < $100K 41 > $100,000 20 181 % with parental education no college degree 39 2- or 4-year college degree 47 postgraduate degree 15 % women 50 % men 50 % another gender 0.3 age M (SD) 38.33 (13.24) % selecting ethnicity White 85 East Asian 6 South Asian 3 Black 3 other 3 Note: We included other ethnicity options and more fine-grained income and education options but present these coarser groupings for brevity. bWe asked about income in USD, but converted to CAD to more easily enable comparisons with the demographics for other studies. Procedure This study generally followed the same method as Study 4’s low temptation condition, with three differences. First, we randomly assigned participants to complete mediator measures either immediately before or immediately after playing the trust game; because order did not influence results, we did not preserve this counterbalancing in Study 4. Second, participants completed two different measures of moral dispositions. One of these was the same measure derived from prior literature and used in Study 4. The other contained three items we created ourselves. These items correlated more strongly with situational temptation than with the literature-derived measure of moral disposition, suggesting it was not a good measure; for this reason we did not included it in Study 4 nor do we report on it further. Third, for pilot-testing purposes, participants were randomly assigned to complete one of four trust scenarios (see Table 40); we retained two of these (the first two rows in Table 40) to be used in Study 4 with slightly different wording adapted to the temptation conditions, and discarded the other two. 182 Table 40 Trust scenarios, Study A3. On the way home from work today, you realize you left a message open on your computer where you complained about your boss to a friend. You know your boss would not be happy to see that message. Two of your coworkers are still at work. You decide to ask one of them to log out of your computer for you before your boss sees. You know whoever you choose could instead show your boss, expose your rudeness, and get themselves into your boss's good graces, so you want to make sure to make the right decision. If these two people from the economic game were your two coworkers, which one would you ask to log you out? Your work team entered a lottery for charity to win a trip, and you won! Unfortunately you didn't realize that the trip is actually only for one person, so your team is currently on a group phone call trying to decide who should get the trip. You decide it would be fairest to just flip a coin - but now you have to choose who flips the coin. You know that whoever flips the coin could just lie and say they won the flip and take the trip for themselves, so you want to make the right decision. If these two people from the economic game were your two coworkers, which one would you choose to flip the coin? Your club is voting for someone to be the treasurer. This job is very simple - all the treasurer has to do is collect cash at various events and fundraisers, count it, and keep it secure. Of course, it would be easy for the treasurer to steal some of the money if they wanted to, so you want to make sure to make the right decision when voting for the treasurer. If these two people from the economic game were the two candidates, who would you vote for? You want to buy a used car, so you are looking on Facebook marketplace. You see two ads for the type of car you want to buy. You don't know much about cars so you are taking a risk that the car you buy could have some problems you don't notice, so you want to make the right decision of which car to buy. If these two people from the economic game were the two sellers who made these ads, whose car would you buy? Results Trust Game Behavior We began by testing the effect of target social class on trust game behavior. We ran a multilevel model predicting trust with target social class and random effects for participants; see Table 41. We also included the same covariates as in Study 2 and 4; because none of these covariates had effects approaching significance (all bs < |.01|, all ps > .309), we omit them from the table for brevity. Table 41 Multilevel regression analysis predicting trust, Study A3. 183 Predictor b SE t p Models without participant class Intercept (lower-class target) .31 .010 32.31 <.001 Control target -.02 .007 -2.45 .015 Higher-class target -.04 .007 -6.20 <.001 Models with participant subjective class Intercept (lower-class target) .31 .010 31.99 <.001 Control target -.02 .007 -2.54 .011 Higher-class target -.04 .007 -6.20 <.001 Participant subjective class (centered) -.00 .006 -.25 .801 Control target × participant class -.01 .005 -2.03 .043 Higher-class target × participant class -.01 .005 -1.90 .058 Models with participant objective class Intercept (lower-class target) .31 .010 32.54 <.001 Control target -.02 .007 -2.45 .015 Higher-class target -.04 .007 -6.20 <.001 Participant objective class (centered) .04 .012 3.03 .003 Control target × participant class -.01 .009 -1.21 .228 Higher-class target × participant class -.02 .009 -1.93 .054 Note: Rows containing the key hypothesis test are bolded. Target is dummy coded. This model also includes covariates for which demographic pairing participants saw (effect coded), control target demographics (effect coded), and target avatar (effect coded). Similar to the previous studies, participants trusted the lower-class target with about 10% more of their initial endowment compared to the higher-class target (d = .30), and about 4% more compared to the control target (d = .17). Models with different dummy coding to obtain the differences between the higher-class and control targets showed that people also trusted the control target with about 5% more of their initial endowment compared to the higher-class target (d = .23, b = .03, SE = .007, p < .001). Next, we examined whether these effects were moderated by participant subjective or objective social class by adding participant social class (centered) and all its interactions to the same models; see Table 41. We did find one significant interaction between participant subjective class and the difference between the control target and the lower-class target; because this did not emerge in any other study (the interaction in Study A2 concerned the difference between the lower- and higher-class targets) and does not concern the key contrast of interest 184 (that between the lower- and higher-class targets), we do not discuss it further. Additional models with altered dummy coding to test for interactions with the difference between the control and higher-class targets revealed no significant interactions. Trust Scenarios Next, we used chi square tests to examine whether participants trusted the lower-class target over the higher-class target in the trust vignettes we presented, and whether this differed if the vignette described a situation with low versus high temptation to betray trust. Across scenarios, results replicated those using the trust game: More than half (57%) of participants trusted the lower-class target over the higher-class one, significantly different from chance (50%), χ2(1) = 5.41, p = .020. However, there was wide variation between scenarios; see Table 42. Table 42 Trust in other situations based on social class, Study A3. N Vignette: Trusting someone to… % choosing lower-class target χ2(1) p 296 [overall, across vignettes] 57 5.14 .020 74 … hide a rude message before the boss sees it. 74 17.51 <.001 70 … report the outcome of a coin flip honestly. 67 8.29 .004 74 … be the treasurer (and not steal money). 53 0.22 .642 74 … sell a good used car. 36 5.41 .020 Only the first two scenarios showed the predicted effect, where people trusted the lower-class target more often than the higher-class target. In the scenario where participants trusted the target to be a treasurer (and not steal money), there was no difference based on target social class, and in the scenario where participants trusted the target to sell a good used car, participants trusted the lower-class target less often than the higher-class target. Mediation: Primary Analysis of Dispositions and Situations 185 Next, we examined the mediators. Table 43 presents the correlations and descriptive statistics for these mediators; correlations between mediators showed a similar pattern of direction and magnitude for the lower- and higher-class targets. Table 43 Correlations and descriptive statistics for mediators. Correlations for ratings of low SES target below diagonal; correlations for ratings of high SES target above diagonal; means (SDs) in rightmost columns (subscript L = lower-class target; subscript H = higher-class target). 1. 2. 3. 4. 5. 6. ML (SDL) MH (SDH) 1. Morality -.51*** .56*** .48*** -.21*** .06 4.69 (0.85) 4.24 (0.91) 2. Situational temptation -.34*** -.30*** -.23*** .22*** .13* 3.59 (1.34) 3.33 (1.33) 3. Communal .60*** -.20*** .65*** -.27*** -.07 4.44 (0.89) 3.59 (1.02) 4. Equality .53*** -.24*** .60*** -.01 .16** 4.47 (0.81) 3.96 (0.85) 5. Authority -.10† .16** -.02 .12* .47*** 4.16 (1.05) 4.79 (1.11) 6. Market .30*** -.09 .25*** .41*** .18** 4.29 (0.81) 4.71 (0.99) Note. † p < .10, * p < .05, ** p <.01, *** p < .001 As in Study 4, we tested whether participants viewed the lower-class target as both more dispositionally moral and more situationally tempted towards immorality than the higher-class target (the a links), and whether these two mediators predicted trust in the trust game (the b links); see Figure 13. Figure 13 Testing the theorized pathways between social class, moral disposition and situational temptation, and trust; Study A3. 186 Consistent with our theorizing and previous findings, participants viewed the lower-class target as having a more moral disposition than the higher-class target, but at the same time, as being more situationally vulnerable to temptation to betray trust. However, only participants’ dispositional inferences predicted who they trusted; their situational inferences had no significant association with their trust decisions. Next, we examined these same dispositional and situational mediators in relation to trust in the hypothetical scenarios, using the same strategy as in Study 4. These analyses revealed that perceiving the lower-class target as more moral than the higher-class target predicted trusting them more, log(OR) = .46, SE = .16, z = 2.97, p = .003, while perceiving the lower-class target as more situationally tempted than the higher-class target predicted trusting them marginally less, log(OR) = -.17, SE = .09, z = 1.91, p = .057, with an effect of a smaller magnitude relative to the dispositional perception. Thus, results were similar as those using the trust game: moral dispositions predicted trust more strongly than situational dispositions, in line with Study 4. Mediation: Exploratory Analysis of Relational Models Next, we ran exploratory models using our measures of relational models as mediators in separate models predicting trust in the trust game and the scenarios; see Table 44. Table 44 Exploratory mediation models, Study A3. DV: Trust game DV: Trust scenarios Mediator Class  mediator Mediator  trust Direct effect Indirect effect log(OR) p b p b p b p b CI95 p Communal -.85 <.001 .02 .002 -.03 .003 -.015 [-.025, -.005] .003 .23 .014 Equality -.51 <.001 .02 .004 -.03 <.001 -.010 [-.017, -.003] .007 .22 .039 Authority .63 <.001 -.01 .255 -.04 <.001 -.004 [-.011, .003] .259 -.15 .127 Market .42 <.001 -.01 .086 -.04 <.001 -.005 [-.010, .001] .098 .05 .660 Note. Total effect is presented in Figure 13 (b = -.04, p < .001). Target class is coded so 0 = lower-class, 1 = higher-class. 187 As in Study 4, participants viewed the lower (vs. higher) class target as having more communal sharing and equality matching, but less authority ranking and market pricing relational models. Communal sharing and equality matching positively predicted trust in both the trust game and trust scenarios, and both had significant indirect effects. Contrary to Study 4, authority ranking and market pricing did not significantly predict trust (either the trust game or the scenarios), nor did they have significant indirect effects. This difference might have emerged due to the lower power (half the sample size) in Study A3. Studies 1-4 and A1.1-A3 Exploratory Mediation Analyses In most studies we measured potential mediators of the difference in trust between the lower- and higher-class targets, and pre-registered the mediation analyses as secondary or exploratory questions; we present these results in the following section. For these we pre-registered examining simple single-mediator models. After that, we summarize results for two additional variables measured in Study 2 only. We asked each mediation question twice, once about the higher-class target and once about the lower-class target. We did not ask any mediation questions about the control targets. Table 45 summarizes the measures for each study; Table 46 provides the results. Table 45 Mediation measures across studies. Studies Construct Item 1, 2, 3, A1.1, A1.2, A1.3, A2 aExpectations of honoring trust If you had given all [entire initial stake] to this person, they would then have [triple the initial stake]. How [many tickets / much money / many credits] do you think they would have given back to you? [0-triple the initial stake] 3, A1.2, A1.3 bPerceived warmth How warm do you think this person is (behavioral condition) / would be (self-report condition)? [1 = not at all, 4 = somewhat, 7 = very warm] 3 bPerceived morality How moral do you think this person is (behavioral condition) / would be (self-report condition)? [1 = not at all, 4 = somewhat, 7 = very moral] 188 A1.2, A1.3 Positive relationship How well do you think you would get along with this person? [1 = not at all, 4 = somewhat, 7 = very well] A1.2, A1.3 Liking How much do you like this person? [1 = not at all, 4 = somewhat, 7 = very much] 1, A1.2, A1.3, A2 cOwn kindness, generosity To what extent did you want to give [resources] to this person because it would be the kind, generous thing to do? [1=not at all, 4=somewhat, 7=very much] 1 cDesire for trust to be honored Assuming you had given some or all of your tickets to this person, to what extent did you care about getting some tickets back from them? [1=not at all, 4=somewhat, 7=very much] 1, A1.2, A1.3 cEmotional reaction if trust not honored Assuming you had given some or all of your tickets to this person, how upset would you be if they decided not to give back any of your tickets? [1=not at all, 4=somewhat, 7=very much] 1, A1.2, A1.3, A2 dDesire to show respect To what extent did you want to show respect to this person? [1=not at all, 4=somewhat, 7=very much] A1.2, A1.3 dRespect How much do you respect this person?” [1 = not at all, 4 = somewhat, 7 = very much] 3, A1.2, A1.3 bPerceived competence How competent do you think this person is (behavioral condition) / would be (self-report condition)? [1 = not at all, 4 = somewhat, 7 = very competent] 1 dPerceived insult to target if not trusted If you had not given any tickets to this person, how insulted do you think they would have been? [1=not at all, 4=somewhat, 7=very much] 2, A2 Perceived similarity How similar do you think you are to this person? [1 = not at all similar, 4 = somewhat similar, 7 = extremely similar] A1.2, A1.3, A2 Perceived need How much did this person need the extra [resources] you could give them during the game? [1 = not at all, 4 = somewhat, 7 = very much] A1.3 Perceived responsibility for status A person's position in society is determined by lots of different factors, including some they are responsible for (e.g. hard work, poor financial decisions) and some they are not responsible for (e.g. being born into a wealthy family, bad luck). How responsible do you think this person is for their position on the ladder shown above? [1 = not at all responsible, 7 = completely responsible] Notes: a Because Study 3 also included the prisoner’s dilemma game, we included another item to measure expectations of cooperating in the game: “Do you think this person is going to (behavioral condition) / would (self-report condition) cooperate or defect?” [1 = cooperate, 0 = defect]. We use that item in the mediation analysis examining expected behavior predicting cooperation in the prisoner’s dilemma game. b In Study 3, we initially pre-registered examining these items as mechanisms using a different analytic strategy, where we would test whether the effect of target class on trust was moderated by these stereotypes. However, we subsequently realized that this analysis would essentially only 189 test the b link in a full mediation model, ignoring the preliminary question of the a link: Do people in fact stereotype the targets based on their social class? We therefore report this analysis in two ways, as mediation here and as moderation in the next section. c In Study 1 only, we pre-registered combining these items into a composite. However, these items had poor reliability (mean α across targets = .54), so we instead analyze them separately. d Also only in Study 1, we pre-registered combining these items into a composite, but they had poor reliability (mean α across targets = .35), so we instead analyze them separately. As pre-registered (for most studies; Study A1.1 was not pre-registered, and see Note B under Table 45 for an alternate analysis strategy pre-registered in Study 3), we tested the indirect effect from partner social class to trust, mediated by each potential mediating variable, in separate models with 10,000 bootstrapped samples using the MEMORE macro in SPSS (Montoya & Hayes, 2017); see Table 46. We also tested the same models predicting cooperation in the prisoner’s dilemma game (denoted as PDG) for Study 3. Also for Study 3, because both warmth and morality are relevant to dispositional morality stereotypes (warmth being a broader concept that encompasses morality; Abele et al., 2016, 2021), and because these items were strongly correlated (rlower-class target = .57***, rhigher-class target = .55***), we also created a composite measure of both items by taking their mean. Table 46 Exploratory mediation analyses across studies. Mediator Study a b c c' a*b [95% CI] Expectations of honoring trust 1 -.07 .18*** -.77*** -.76*** -.01 [-.18, .11] 2 -.01 .09*** -.05*** -.04*** -.00 [-.004, .002] 3 - trust -.67** .16*** -.65** -.54** -.11 [-.31, .05] 3 - PDG -.09† .32*** -.09* -.06† -.03 [-.06, .004] A1.1 .06† .05 -.04† -.04* .00 [-.004, .01] A1.2 .07* .01 -.02 -.02 .00 [-.01, .01] A1.3 .03 .14† -.02 -.02 .00 [-.004, .01] A2 -1.30*** .08** -.51*** -.41** -.10 [-.27, -.02] Perceived warmth/morality composite 3 – trust -.51*** .89*** -.64*** -.18 -.46 [-.75, -.22] 3 – PDG -.53*** .08** -.09* -.05 -.04 [-.08, -.01] Perceived warmth 3 – trust -.53*** .69*** -.64** -.27 -.37 [-.63, -.17] 3 – PDG -.55*** .08** -.09* -.05 -.04 [-.08, -.01] A1.2 -.38*** .02 -.02 -.01 -.01 [-.02, .01] 190 A1.3 -.36** .04** -.02 -.00 -.01 [-.03, -.001] Perceived morality 3 – trust -.50*** .72*** -.64** -.28 -.36 [-.64, -.14] 3 – PDG -.52*** .05† -.09* -.06 -.03 [-.06, .002] Positive relationship A1.2 -.28* -.00 -.02 -.02 .00 [-.01, .01] A1.3 -.29** .04** -.02 -.00 -.01 [-.03, -.002] Liking A1.2 -.15 .00 -.02 -.02 -.00 [-.01, .01] A1.3 -.30** .03* -.02 -.01 -.01 [-.02, -.001] Own kindness, generosity 1 -1.06*** .48*** -.70*** -.19 -.51 [-.85, -.19] A1.2 -.55*** .03* -.02 -.00 -.01 [-.04, .001] A1.3 -.54*** .03* -.02 -.00 -.01 [-.03, -.002] A2 -.44*** .40** -.51*** -.33* -.18 [-.36, -.04] Desire for trust to be honored 1 .40** .10 -.70*** -.74*** .04 [-.12, .17] Emotional reaction if trust not honored 1 .43*** -.03 -.70*** -.69*** -.00 [-.18, .12] A1.2 .64*** .00 -.02 -.02 .00 [-.01, .01] A1.3 .36** .02† -.02 -.02 .01 [-.003, .02] Desire to show respect 1 -.76*** .73*** -.70*** -.15 -.55 [-.87, -.29] A1.2 -.11 .03† -.02 -.01 -.00 [-.01, .003] A1.3 -.25* .03† -.02 -.01 -.01 [-.02, .001] A2 -.68*** .27* -.51*** -.32† -.19 [-.45, .03] Respect A1.2 -.15† .02 -.02 -.01 -.00 [-.02, .004] A1.3 -.34*** .02 -.02 -.01 -.01 [-.02, .003] Perceived competence 3 – trust .07 .31* -.64** -.66** .02 [-.06, .10] 3 – PDG .06 -.01 -.09* -.09* -.00 [-.01, .01] A1.2 .35** -.02† -.02 -.01 -.01 [-.03, .004] A1.3 .19† .02 -.02 -.02 .00 [-.002, .01] Perceived insult to target if not trusted 1 .07 .03 -.70*** -.70*** -.00 [-.06, .03] Perceived similarity 2 -1.17*** .01** -.05*** -.04*** -.01 [-.02, -.002] A2 -.32* .20** -.51*** -.44** -.06 [-.19, .001] Perceived need A1.2 -1.88*** .01 -.02 .00 -.02 [-.06, .01] A1.3 -1.69*** .01 -.02 -.01 -.01 [-.03, .01] A2 -.70*** .16 -.51*** -.39* -.11 [-.30, .03] Perceived responsibility for status A1.3 -.03 .02 -.02 -.02 -.00 [-.01, .005] Note: Larger numbers for the a, c, and c’ paths indicate higher scores with the higher-class target than the lower-class target. In some studies not all participants completed all measures, so estimates for total effects differ slightly. Examining the a links comparing the lower-class target to the higher-class target, we found several consistent patterns: Participants saw the lower-class (vs. higher-class) target as 191 warmer (four out of four analyses) and more moral (two out of two analyses) (and higher on the warmth-morality composite in Study three), anticipated getting along better with this target (two out of two analyses), were more inclined to give to them because it was the kind, generous thing to do (four out of four analyses), cared less about having their resources returned (one out of one analysis), would be less upset if no resources were returned (three out of three analyses), were more inclined to show them respect (three out of four analyses), saw the target as more similar to themselves (two out of two analyses), and thought they were more in need of resources (four out of four analyses). We found mixed results for likelihood of honouring trust (two out of eight analyses showed increased likelihood for the lower-class target, one showed increased likelihood for the higher-class target, and five showed no difference), for viewing the target as competent (one out of four analyses showed people saw the lower-class target as less competent, the other three showed no difference), for respecting the target (one out of two analyses showed people respected the lower-class target more; the other showed no difference), and for liking (one out of two analyses showed increased liking for the lower-class target; the other showed no difference). Participants saw no difference in how responsible the lower- and higher-class targets were for their status on the social class ladder (one out of one analysis) and in how insulted the targets would be if participants gave them few resources (one out of one analysis). Examining the b links testing the association between each mediator and trust, results were less consistent, but generally variables associated with warmth positively predicted trust, including seeing the target as warm (three out of four analyses), moral (one out of two analyses), or both (two out of two analyses), anticipating getting along well with the target (one out of two analyses), liking the target (one out of two analyses), and wanting to give to the target because it would be the kind, generous thing to do (four out of four analyses). Likelihood of honouring trust 192 also generally positively predicted trust (five out of eight analyses), as did perceiving oneself as similar to the target (two out of two analyses). Variables associated with respect were inconsistently related to trust: wanting to show respect to the target sometimes positively predicted trust (two out of four analyses; the other two were not significantly related to trust), but respecting the target was unrelated to trust (zero out of two analyses showed a relationship with trust). Variables that were generally uncorrelated with trust include caring about having trust honored (zero out of one analysis showed a relationship with trust), feeling upset if trust was not honored (one out of three analyses show a relationship with trust), thinking the target would feel insulted if they did not give the target any resources (zero out of one analysis show a relationship with trust), perceiving the target as more in need of resources (zero out of three analyses show a relationship with trust), perceiving the target as competent (one out of four analyses show a relationship with trust), and perceiving the target as responsible for their position on the social class ladder (the sole analysis showed no relationship with trust). Additional Variables for Study 2 In Study 2 we measured two additional variables as mediators, desire to profit (two items, α = .76): “When making your decisions about how much to give to each partner, how much did you care about ending up with as much money as possible?” [1 = not at all, 4 = somewhat, 7 = very much]; “Was getting as much money as possible your main concern in the economic game, or did you also think about other factors?” [1 = mostly other factors guided my decisions, 4 = I weighed money and other factors equally, 7 = mostly money guided my decisions] and desire for moral self-regard (two items, α = .74): “When making your decisions about how much to give to each partner, how much did you care about feeling like a good person? [1 = not at all, 4 = somewhat, 7 = very much]; “When making your decisions about how much to give to each 193 partner, how much did you care about making the morally right decision?” [1 not at all, 4 = somewhat, 7 = very much]. We measured these two constructs only once, rather than measuring them for each target (because they concerned participants’ motivation during the game as a whole, not their impressions of each target). For that reason, we pre-registered using these constructs as mediators in a mediation model where the DV would be the difference in trust between the higher-and lower-class targets. However, we subsequently realized that no such model is possible, because there would be no independent variable: Target social class is already incorporated in the DV, and only two variables are involved: the predictor (desire to profit or desire for moral self-regard) and the outcome (the difference in trust between targets). Instead, we used the conceptual mediators to predict the difference score: Would, for instance, participants more motivated by profit be especially likely to trust the lower over the higher class target (or vice versa)? Participants with a stronger desire to profit showed relatively more trust in the higher (versus lower) class target, b = .01, SE = .004, p = .005. Participants with stronger versus weaker desire for moral self-regard showed similar levels of trust bias, b = .01, SE = .004, p = .244. Thus, perhaps participants overall trusted the lower class target more because they were not, in general, motivated by profit. Extending this idea, raising the stakes such that more people were concerned with profit might have reversed the overall effect, but Study 6B found no support for this idea. Study 3 Moderation Analyses In Study 3, we had originally pre-registered examining warmth, morality, and competence stereotypes as moderators by calculating a difference score of participants’ ratings of the lower-class target minus their rating of the higher-class target on each measure, then testing 194 whether this variable interacted with target social class to predict trust. This is analogous to testing only the b link of the mediation model (as both analyses examine whether those who view lower-class targets as warmer, more moral, or more competent also trust those targets more). However, this analysis does not examine the a link of the mediation model (i.e., whether people do in general view lower-class targets as warmer, more moral, or more competent). Because the mediation framework provides more information, we focus on it in the main text, but provide results for our pre-registered moderation strategy here. We also pre-registered examining political orientation (“What is your political orientation in general?” [0 = extremely liberal, 100 = extremely conservative]) as a moderator. To test these moderators, we ran separate multilevel regression models predicting trust with target social class (-1 = lower-class target, 1 = higher-class target), experimental realism condition (-1 = hypothetical, 1 = real), the moderator in question (centered), and all possible interactions. These models also included a term for profile combination condition (effect coded) and random intercepts for participants; see Table 47 for results. Table 47 Moderation analyses, Study 2 (key moderation tests bolded). Predictor b SE t p Intercept 5.48 .22 25.03 <.001 Target class -.29 .11 -2.62 .010 Profile combination -.11 .22 -.50 .620 Experimental realism .00 .22 .02 .985 Political orientation -.00 .01 -.12 .902 Target class × experimental realism .18 .11 1.67 .097 Target class × political orientation .01 .01 1.27 .205 Political orientation × experimental realism .02 .01 1.46 .146 Target class × experimental realism × political orientation .01 .01 1.74 .084 Intercept 5.48 .22 25.03 <.001 Target class -.29 .10 -2.88 .005 Profile combination -.08 .22 -.38 .704 Experimental realism -.00 .22 -.01 .996 Warmth stereotype -.18 .16 -1.14 .255 195 Target class × experimental realism .20 .10 1.92 .056 Target class × warmth stereotype .32 .08 4.45 <.001 Warmth stereotype × experimental realism .12 .16 .77 .443 Target class × experimental realism × warmth stereotype -.11 .07 -1.54 .126 Intercept 5.45 .22 24.59 <.001 Target class -.29 .10 -2.80 .006 Profile combination -.13 .22 -.59 .556 Experimental realism -.03 .22 -.11 .911 Morality stereotype .18 .19 .94 .351 Target class × experimental realism .14 .10 1.37 .174 Target class × morality stereotype .31 .09 3.52 <.001 Morality stereotype × experimental realism .14 .19 .73 .464 Target class × experimental realism × morality stereotype -.06 .09 -.73 .468 Intercept 5.47 .23 24.32 <.001 Target class -.31 .11 -2.76 .006 Profile combination -.13 .22 -.59 .557 Experimental realism .01 .23 .05 .962 Competence stereotype -.04 .18 -.20 .846 Target class × experimental realism .14 .11 1.26 .209 Target class × competence stereotype .16 .09 1.76 .081 Competence stereotype × experimental realism .01 .18 .07 .948 Target class × experimental realism × competence stereotype .05 .09 .52 .603 196 Appendix B: Supplemental Material for Chapter Three This appendix provides supplemental information for Chapter Three. All sample sizes, data exclusions and analyses were pre-registered unless otherwise specified. Study B1 This was a pre-registered (https://osf.io/4xu9a/?view_only=ba64fce4916e4a1e93e50bc47213d29b) preliminary test of two potential stereotypes about social class and morality that might help explain the diverging results from Chapter 2 and Study 5. First, we thought people might expect those with lower social class to behave more morally towards acquaintances or others to whom they are socially connected, but less so towards strangers, compared to those with high social class. Second, we thought people might expect those with lower social class to be more likely to commit crimes than those with higher social class, whereas they might expect those with high social class to be more likely to commit acts that were immoral but not technically illegal. Method Participants. We collected data from 199 Americans on Prolific Academic (102 women, 95 men, 1 nonbinary, 1 questioning; age M = 35.85, SD = 12.64; 38 Asian, 18 Black, 29 Hispanic, 2 Middle Eastern, 3 Native American, 125 White, 4 another ethnicity [participants could select multiple options]). No participants were excluded. Procedure. Participants answered the same questions twice, once referring to lower-class targets and once to higher-class targets, in random order. In each case, participants read a description of low/high social class and viewed two examples of targets with low/high social class; these were identical to those presented in Study 7’s explicit stereotype phase, and as in that phase, we asked participants to think about people in this social class group (low or high) in 197 general. Then, we assessed stereotypes about morality towards strangers versus acquaintances. Participants read, “We are interested in how you think people in this group tend to act towards strangers (people they do not know and have no social connection to - for example, a cashier in a grocery store at an unfamiliar part of town, or a stranger walking by on the sidewalk), and how you think they tend to act towards people in their social circle (people they know and are socially connected to - for example, a cousin or a coworker).” Participants then answered the same morality stereotype questions as in Study 7’s explicit stereotype phase, but rephrased so that once the questions referred to morality towards strangers (e.g., “How morally do you think people in this group tend to act towards strangers?”) and once they referred to morality towards acquaintances (e.g., “How morally do you think people in this group tend to act towards people in their social circle?”). Next, to assess views about legal and illegal acts we told participants, “We are also interested in your views about actions that people in this group might take”, and asked five questions with the stem “How likely are people in this group to do something that is…”: “immoral”, “against the law”, “immoral, but isn’t against the law”, “against the law, but isn’t immoral”, “both immoral and against the law” (1 = not at all, 4 = somewhat, 7 = extremely). Finally, we collected demographics information and compensated participants. Results A multilevel regression analysis using the lmerTest package in R predicted morality stereotypes with target social class (0 = lower, 1 = higher), social connectedness (0 = strangers, 1 = people in their social circle), and their interaction. This interaction was significant, b = -.46, SE = .11, p < .001, but in the opposite direction from what we expected. People believed that everyone would treat those in their social circle more morally than they would treat strangers, but 198 they thought this was especially true for those with high social class, b = 1.05, SE = .11, p < .001, compared to low social class b = .59, SE = .08, p <.001. Turning to legality, as predicted, people expected those with high social class to be more likely than those with low social class to commit immoral acts in general, t(198) = 3.15, p = .002, and to commit immoral but legal acts, t(198) = 4.79, p < .001, but less likely to commit crimes in general, t(198) = -2.52, p = .012, and to commit acts that are illegal but not immoral, t(198) = -2.98, p = .003. (There was no difference based on social class for acts that were both illegal and immoral, t(198) = 0.68, p = .495; we had no predictions for this item.) Study B2 A pilot study verified that participants perceived the trust scenarios used in Chapter Three as we intended: That morality would be the most important factor in the moral trust scenarios, and competence in the competence scenarios. This study was not pre-registered. Method Participants. We collected data from 308 American MTurkers. We did not collect demographic information. No participants were excluded. Procedure. We included these questions at the end of another unrelated study. Participants viewed all five scenarios used in Chapter Three (save Study 6E, which came after this pilot study), in random order, and responded to two questions for each one: (1) a Likert-style question (“Imagine that you had to choose between two people. Person A is very moral but NOT very competent. Person B is very competent, but NOT very moral. Who would you prefer to choose in this scenario?” 1 = I would definitely choose Person A, 7 = I would definitely choose Person B); and (2) a forced-choice question (“If you had to make a choice between Person A and Person B, which one would you choose?” Person A / Person B). 199 Results For each scenario, one-sample t tests compared participants’ ratings on the Likert-type item to the midpoint (4), and chi-square tests compared the proportion of participants’ choices on the forced-choice item to chance (.50); see Table 48. Table 48 Pilot testing results showing that people prefer to choose a moral (but incompetent) person in the morality scenarios, and a competent (but immoral) person in the competence scenarios. Scenario M preference p comparing to scale midpoint % who would choose moral but incompetent p comparing to 50% Moral: Train 3.15 < .001 82.7% < .001 Moral: Doctor 3.23 < .001 81.4% < .001 Moral: Babysitter 3.87 .246 63.4% < .001 Competence: Gameshow 5.03 < .001 42.3% .012 Competence: Presentation 5.17 < .001 37.0% < .001 In all five scenarios, participants’ Likert ratings were on the anticipated side of the midpoint, significantly four times out of five. The exception was the babysitting scenario, where participants’ ratings were no different from the midpoint. We used this scenario only once, because even prior to running this pilot study we recognized it likely involved competence as well as morality. In all five scenarios, when forced to choose between two people, participants were significantly more likely to choose the one whose attributes aligned with the intended requirements of the scenario. Moderation Analyses, Study 5 In Study 5, we measured three potential moderators of the effect of target social class on trust: Participant social class (objective and subjective), social class stereotypes (of morality and competence), and attributions for social class. The main text provides the measures for participant class and class stereotypes; attributions were measured with one item: “A person’s position in society is determined by lots of different factors, including some they are responsible 200 for (e.g. hard work, poor financial decisions) and some they are not responsible for (e.g. being born into a wealthy family, bad luck). How responsible do you think people in general are for their position in society?” (1 = not at all, 7 = completely). To test for moderation, we used only those trials comparing low- and high-class targets, and used multilevel logistic regression analyses to predict choices for the high-class target over the low-class one from scenario type (effect coded so 1 = competence, -1 = morality), information type (effect coded so 1 = objective only, -1 = objective and about-me statement), moderator (mean-centered), all possible interactions, and random intercepts for participants. The coefficient for moderator tests the key moderation question: Does the moderator in question influence the odds that participants will choose the high-class target on each trial’s binary decision, across scenario and information types? The interaction of the moderator with scenario type tests whether this moderation unfolds differently in the morality versus the competence scenario, while the interaction of the moderator with information type tests whether this moderation unfolds differently for targets where only objective information was provided versus where we provided both objective and subjective information. Table 49 provides the results. Here and for Studies 6A-6F, the effects of stereotypes are summarized in the main text so we do not rehash them here, and focus instead on moderation by participant social class and attributions for social class. Table 49 Participant social class, social class stereotypes, and attributions for social class predicting choosing to trust a high vs. low social class target, Study 5. Predictor log(OR) SE p (Intercept) 1.27 .14 <.001 Scenario .05 .14 .724 Information type .05 .14 .728 Morality stereotype .19 .09 .028 Scenario × information type .98 .22 <.001 Scenario × morality stereotype -.08 .09 .376 201 Morality stereotype × information type -.03 .09 .708 Scenario × information type × morality stereotype .10 .14 .451 (Intercept) 1.27 .14 <.001 Scenario .06 .14 .683 Information type .04 .14 .799 Competence stereotype .27 .08 <.001 Scenario × information type .94 .22 <.001 Scenario × competence stereotype -.01 .09 .913 Competence stereotype × information type -.08 .08 .338 Scenario × information type × competence stereotype -.11 .13 .385 (Intercept) 1.27 .14 <.001 Scenario .05 .14 .746 Information type .04 .14 .768 Subjective class .22 .09 .015 Scenario × information type .97 .22 <.001 Scenario × subjective class -.13 .09 .147 Subjective class × information type -.11 .09 .234 Scenario × information type × subjective class .03 .14 .830 (Intercept) 1.28 .14 <.001 Scenario .03 .14 .810 Information type .08 .14 .567 Objective class .10 .09 .265 Scenario × information type .93 .22 <.001 Scenario × objective class .04 .10 .699 Objective class × information type .10 .10 .282 Scenario × information type × objective class -.14 .15 .359 (Intercept) 1.26 .14 <.001 Scenario .05 .14 .702 Information type .09 .14 .544 Attributions for status .26 .12 .031 Scenario × information type .94 .22 <.001 Scenario × attributions for status -.08 .12 .544 Attributions for status × information type -.14 .12 .247 Scenario × information type × attributions for status .13 .18 .470 Note. Stereotypes are difference scores where more positive values indicate more positive stereotypes of high-class than low-class individuals. Participant showed some evidence of ingroup favoritism based on their subjective social class, though their objective social class did not significantly predict trust choices. Neither social class variable interacted with scenario type or information type. People who attributed social class more to internal than external factors were more likely to choose the high-class targets over 202 the low-class ones; this also did not differ across scenarios or information type. This is logical: It makes sense to trust someone who you believe to have rightfully earned high status over someone who has made poor choices and therefore deserves their low status; it makes less sense to trust high status over low status people if you believe their relative statuses merely reflect good and bad luck. Moderation Analyses, Studies 6A-6F As in Study 5, we examined individual differences as predictors of choices for high-class over low-class targets. We examined the same individual differences as in Study 5 with some exceptions: Studies 6A and 6B also examined political orientation; Study 6D measured trustworthiness stereotypes instead of morality stereotypes; Studies 6E-6F measured both trustworthiness and morality stereotypes; Study 6E did not include the attribution measure. In each case, we conducted the same moderation analyses as for Study 5; see Table 50. Table 50 Participant social class, social class stereotypes, attributions for social class, and political orientation predicting choosing to trust a high vs. low social class target, Studies 6A-6F. 6A 6B 6C 6D 6E 6F Predictor log(OR) log(OR) log(OR) log(OR) log(OR) log(OR) (Intercept) .43*** .73*** 1.01*** .69*** 1.13*** Scenario .53*** .91*** .06 .25*** .26*** Information type .31*** .15** .31*** .26*** .17** Morality stereotype .19** .29** .20* .07 .12 Scenario × information type .02 .06 .10† .08 -.05 Scenario × morality stereotype -.05 .10* -.06 -.01 -.09* Morality stereotype × information type -.11*** .02 -.05 .03 .03 Scenario × information type × morality stereotype .02 .04 .02 -.04 .07† (Intercept) .61*** .70*** 1.13*** Scenario .64*** .25*** .26*** Information type .46*** .26*** .17** Trustworthiness stereotype .20* .22* .21* 203 Scenario × information type .28*** .08 -.05 Scenario × trustworthiness stereotype -.10* .01 -.15** Trustworthiness stereotype × information type .01 .03 .03 Scenario × information type × trustworthiness stereotype -.07† -.02 .01 (Intercept) .43*** .74*** 1.01*** .62*** .69*** 1.12*** Scenario .53*** .93*** .06 .64*** .24*** .27*** Information type .31*** .16** .31*** .46*** .25*** .17** Competence stereotype .29*** .21** .24*** .11 .32*** .23** Scenario × information type .03 .06 .11* .28*** .08† -.04 Scenario × competence stereotype -.03 .14*** .02 .03 -.07* .02 Competence stereotype × information type -.04 .04 -.04 .09* -.06† -.02 Scenario × information type × competence stereotype .04 .04 .03 .03 .03 .04 (Intercept) .44*** .71*** 1.01*** .63*** .69*** 1.12*** Scenario .53*** .90*** .06 .64*** .25*** .27*** Information type .31*** .14** .32*** .47*** .26*** .17** Subjective class -.07 .18* .12† .15* .07 -.05 Scenario × information type .03 .04 .10† .29*** .08 -.05 Scenario × subjective class -.03 .02 .04 .05 -.01 .02 Subjective class × information type -.01 -.06† .04 .08* .00 .00 Scenario × information type × subjective class -.02 -.02 -.04 .02 .03 -.04 (Intercept) .45*** .71*** 1.02*** .62*** .69*** 1.13*** Scenario .53*** .91*** .08 .64*** .25*** .27*** Information type .31*** .14** .32*** .46*** .26*** .17** Objective class .03 .10 .13† .17* .05† -.00 Scenario × information type .02 .05 .10† .28*** .08 -.05 Scenario × objective class -.02 .11** .11*** .00 .00 .06† Objective class × information type .02 -.04 .02 .05 -.00 .01 Scenario × information type × objective class .01 .01 -.05 -.01 -.00 .01 (Intercept) .44*** .71*** 1.01*** .62*** Scenario .53*** .90*** .06 .64*** 204 Information type .31*** .14** .31*** .46*** Attributions for status .13 .09 .19 .11 Scenario × information type .03 .05 .10† .28*** Scenario × attributions for status -.05 -.04 .08 .07 Attributions for status × information type -.01 -.03 -.16** -.01 Scenario × information type × attributions for status -.03 .03 .08 -.01 (Intercept) .45*** .71*** Scenario .53*** .90*** Information type .31*** .14** Political orientation .01** -.00 Scenario × information type .03 .04 Scenario × political orientation -.00 -.00* Political orientation × information type -.01* .00 Scenario × information type × political orientation .00 .00 Note. All responses are coded so 1=chose the high-class target, 0=chose the low-class target. Scenario is coded so 1=competence, -1=morality (except for Study 6E, which contained two morality scenarios, so scenario is coded 1=selling a used car, -1=caring for pet/plants); stereotypes are difference scores where more positive values indicate more positive stereotypes of high-class than low-class individuals. Some cells are blank because not all variables were measured in all studies. Participant social class predicted trust in the direction of ingroup favoritism, either marginally or significantly, in half of the tests of this effect. For participants’ objective but not subjective social class, there was a trend for this to be most true of trust in competence. Attributions for social class did not predict trust. We only tested political orientation as a moderator twice; it is therefore very tentatively that we report more conservative participants always trusted the morality of high-class targets more than that of low-class ones, but this was not consistent for trust in competence.
Thesis/Dissertation
eng
Psychology
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Laurin, Kristin
Trust and social class : the complex relationship between explicit stereotypes (about dispositions and situations), implicit stereotypes, and trust
Text