Rising nationalism on the one hand and anti-racist protests on the other have called into question norms surrounding what can be considered racist. How do individuals decide whether anti- immigrant statements are “racist”? This project sought to identify determinants of agreement about what kind of speech is “racist”. Across two studies and one replication (N = 1211) from a nationally representative panel, perceivers rated how “racist” they found social media statements about immigration. The statements were drawn following the announcement of immigration policies in the United States. We introduce variance component analyses to quantify the extent to which judgments of racism are shared or idiosyncratic. We calculated the contributions of perceiver demographics and attitudes (e.g., racial category, age, gender, political leaning, attitudes toward hierarchy and race), statement attributes (e.g., aggressiveness or target of the statement), and context cues (e.g., statement popularity) to measure sources of agreement. While traditional aggregate analyses suggested that perceivers’ judgments about what constitutes racism differed on average between racial categories, the variance analyses consistently identified substantial disagreement, even within racial categories and with varied social norm cues (i.e., number of likes). Agreement occurred when perceivers shared political and racial ideology, and when the statements contained aggressive messages. Judgments of racism may not be shared within predicted social cleavages (e.g., racial categories) in this particular case, because anti-immigrant sentiment is highly politicized. Analyzing variance, as compared to only differences in means, brings new insights to the psychological study of racism, group-based beliefs, and anti-prejudice endeavors.

Human social groups exert powerful influence over their members’ behavior. We test the hypothesis that increasing individuals’ participation in their group turns the group into a source of higher motivation. We conducted a 6-week field experiment with 65 Chinese factory groups (1752 workers). Half of the groups were randomly assigned to a 20-minute participatory meeting once per week for six weeks, in which the group’s supervisor stepped aside and workers contributed ideas and personal goals in an open discussion of their work. The other half continued with status quo meetings in which supervisors spoke, workers listened, and a researcher observed. We found that participatory vs. a hierarchical structure led to a 10.6% average increase in individual treatment workers’ productivity, an increase that endured for 9 weeks after the participatory experiment ended. The brief participatory meetings also increased treatment workers’ feelings of empowerment such as job satisfaction and sense of control. We find no evidence that informational gains or new worker goals were responsible for increases in productivity; instead, evidence suggests that the increase in frequency of workers’ voicing opinions may have driven higher productivity. Participatory work structure is a popular concept but its causal impacts in real world work groups have heretofore been unidentified and research has been Western-centric. The results contribute a richer theoretical understanding of participatory group structures, and a pragmatic intervention for behavior change.

Social norms are powerful drivers of human behavior. Norms often override personal material interests and preferences. What happens when people violate norms? We conducted two randomized experiments (N = 3,499) to explore the behavioral and psychological consequences of deviating from norms. Participants played social dilemma games governed by norms of cooperation, without a mechanism for players to punish one another. Participants assigned to the treatment condition, unlike those in the control condition, were offered a monetary incentive to deviate from a strong norm of cooperation in one round of the game. Violating this norm significantly increased their propensity to violate other social norms in new settings involving new groups and new games (with no incentive to deviate). Post-treatment survey data suggest that violating norms causes people to depreciate their expectation of the costs associated with violation, but does not lead them to update their views of the self. The finding that social experience causally impacts an individual's tendency to deviate represents a new finding in the norms and deviance literature. Together, these results challenge and inform traditional views of deviance as personality or a stable individual motivation or trait.

We propose a behavioral science approach to sexual assault on college campuses. In this framework, people commit assault when aspects of the immediate situation trigger certain psychological states. No set of mental processes or situational configurations is a precise predictor of assault. Instead, the interaction between mental processes and situational configurations predicts when sexual assault is more or less likely to occur. We begin with an illustrative story to show how a behavioral science approach is relevant to sexual assault. Next, we map out a framework that suggests how behavioral theories of situations and mental processes have been or could be used to describe, predict, and develop ideas for the reduction of sexual assault. Relevant situational configurations include geographical configurations, local situational and informational cues, and situation-based power. Theories of mental processes include person perception, social norms, moral reasoning, and goals. Critically, our framework can be used to demonstrate how "good" people can commit assault, and how individuals can and will refrain from assault within institutions with a "bad" record. Compared with previous theories of sexual assault, a behavioral science framework offers unique understanding and generative methods for addressing sexual assault on college campuses.