This article is based in part on a master's thesis submitted to Columbia University by Sheri R. Levy. We extend special appreciation to Chi-yue Chiu and Ying-yi Hong for their contribution to. Experiment 3. We are grateful to E. Tory Higgins and Jeffrey W. Sherman for their helpful comments on an earlier draft of this article. We also thank
How do people respond to information that counters a stereotype? Do they approach it or avoid it? Four experiments showed that attention to stereotype-consistent vs. -inconsistent information depends on people's implicit theories about human traits. Those holding an entity theory (the belief that traits are fixed) consistently displayed greater attention to (Experiments 1 and 4) and recognition of (Experiments 2 and 3) consistent information, whereas those holding an incremental (dynamic) theory tended to display greater attention to (Experiment 1) and recognition of (Experiment 3) inconsistent information. This was true whether implicit theories were measured as chronic structures (Experiments 1, 2, and 4) or were experimentally manipulated (Experiment 3). Thus, different a priori assumptions about human traits and behavior lead to processing that supports versus limits stereotype maintenance.
Four studies demonstrate the importance of self-regulatory mechanisms for understanding risk-seeking behavior under loss. Findings suggest that risk seeking becomes a motivational necessity under 3 conditions: (a) when an individual is in a state of loss; (b) when the individual is in a prevention-focused regulatory state (E. T. Higgins, 1997); and (c) when the risky option alone offers the possibility of eliminating loss. In situations involving loss, prevention motivation but not promotion motivation (whether measured or manipulated) was uniquely associated with behaviors that served the motivation to maintain the status quo. When the risky option offered the sole possibility of returning to the status quo, prevention motivation predicted increased risk seeking. However, when a more conservative option was available that also offered the possibility to return to the status quo, prevention motivation predicted risk aversion. When neither option offered the possibility to return to the status quo, prevention motivation was not associated with risky choice. The authors discuss the benefits of complementing existing accounts of risky decision making under loss with regulatory focus motivational mechanisms.
Two experiments assessed target-based determinants of social categorization. In Experiment 1 , participants judged targets' race and sex separately. Consistent with the prediction that targets would be categorized on dimensions perceived to be non-normative, black male targets' race was judged more quickly and sex more slowly than for white male targets. Judgments of black females' race and sex were both inhibited, suggesting that these targets were subtyped. In Experiment 2, participants judged targets' race and sex simultaneously. Also consistent with predictions, black female targets were judged more quickly, and black male and white female targets more slowly, than white male targets. These data provide additional evidence that targets are categorized based on non-normative informa tion. The automaticity of race and sex categorization is discussed, and possible revisions of current models of impression formation are considered.How do we categorize others? When we encounter another person for the first time, a tremendous amount of readily observable feature infor mation is available. This feature information, of course, provides cues about the groups to which the person belongs. Based on the feature This research is based in part on a doctoral dissertation submitted to
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.