Northern Kentucky University
When Stereotypes Collide: Evaluations of People with Multiple Group Memberships
Institution
Northern Kentucky University
Faculty Advisor/ Mentor
Douglas Krull
Abstract
People can be categorized in many ways based on race, gender, career, and other variables, making it important to understand how stereotypes about multiple categories are integrated to form judgments about individuals who belong to those categories. The objective of this study was to investigate how observers combine information about multiple stereotypes in making judgments about personality traits. Participants read a description of a female individual who was described as “a student at a local university” and were randomly assigned to either receive or not receive additional information that the individual was a member of two groups: sorority members and engineering majors. Participants were asked to rate the target person on several personality traits. Composite indices were created for traits related to stereotypes about sorority members and engineering majors, and were used as dependent measures in two 2 (sorority member or not stated) by 2 (engineering major or not stated) between-subjects ANOVAs. For the engineering index, participants used an additive model to combine group stereotypes - engineering majors were rated higher than nonengineering majors and sorority members were rated somewhat lower than nonsorority members; no interaction was found between the two categories. For the sorority index, a different pattern of results was observed. Sorority members were rated higher than non-sorority members and engineering majors were rated lower than non-engineering majors. There was a significant interaction between sorority and engineering category membership such that engineering major information was only used when the target was not a sorority member. Thus the two stereotypes were applied hierarchically, with sorority membership used over engineering major membership.
When Stereotypes Collide: Evaluations of People with Multiple Group Memberships
People can be categorized in many ways based on race, gender, career, and other variables, making it important to understand how stereotypes about multiple categories are integrated to form judgments about individuals who belong to those categories. The objective of this study was to investigate how observers combine information about multiple stereotypes in making judgments about personality traits. Participants read a description of a female individual who was described as “a student at a local university” and were randomly assigned to either receive or not receive additional information that the individual was a member of two groups: sorority members and engineering majors. Participants were asked to rate the target person on several personality traits. Composite indices were created for traits related to stereotypes about sorority members and engineering majors, and were used as dependent measures in two 2 (sorority member or not stated) by 2 (engineering major or not stated) between-subjects ANOVAs. For the engineering index, participants used an additive model to combine group stereotypes - engineering majors were rated higher than nonengineering majors and sorority members were rated somewhat lower than nonsorority members; no interaction was found between the two categories. For the sorority index, a different pattern of results was observed. Sorority members were rated higher than non-sorority members and engineering majors were rated lower than non-engineering majors. There was a significant interaction between sorority and engineering category membership such that engineering major information was only used when the target was not a sorority member. Thus the two stereotypes were applied hierarchically, with sorority membership used over engineering major membership.