Abstract
Research on discriminating behavior against ethnic minorities in everyday situations is still a rather under-researched field, since most prior research on ethnic discrimination focuses on housing markets, job markets, criminal justice, institutions or discourses. This article contributes toward filling the research-gap on everyday discrimination by bringing together prior research from sociology and social-psychology, including threat and competition theories from integration research, social identity theory, particularism-universalism theory and experimental findings on fairness norms. It conceptually advances the field by combining them into an integrated interdisciplinary approach that can examine discriminating behavior in everyday situations. This approach studies the dynamics of ingroup-outgroup relationships, fairness norms and threat in regard to negative behavior toward others (e.g., a neighbor). In particular, it focusses on the dynamics under which negative behavior is more likely toward an ethnic outgroup-person than an ingroup-person (i.e., discriminating behavior). To scrutinize the expectations derived within this framework, a factorial survey experiment was designed, implemented and analyzed (by means of multilevel mixed-effects linear regressions and average marginal effects). The survey experiment presents a hypothetical scenario between two neighbors in order to measure the effects and dynamics of ingroup-outgroup relationships, fairness norms and threat on behavior. While no significant outgroup-effect can be found in the general analysis of the main effects, more in-depth analyses show an interplay of situational cues: Outgroup-discriminating behavior becomes significantly more likely when the “actor” has low general fairness norms and/or when threat-level in a situation is low. These results foreground the importance of interdisciplinary in-depth analyses of dynamics for understanding the conditions under which discriminating behavior takes place in everyday situations—and for deriving measures that can reduce discrimination.