The AAS is a useful tool for researchers to assess hostile and benevolent ageism. This measure serves as an important first step in designing interventions to reduce the harmful effects of both hostile and benevolent ageism.
Individuals can be simultaneously categorized into multiple social groups (e.g., racial, gender, age), and stereotypes about one social group may conflict with another. Two such conflicting stereotype sets are those associated with older adults (e.g., frail, kind) and with Black people (e.g., violent, hostile). Recent research shows that young adult perceivers evaluate elderly Black men more positively than young Black men, suggesting that components of the elderly stereotype moderate the influence of conflicting Black stereotypes (Kang & Chasteen, 2009). The current research begins to examine whether this pattern of perceiving multiply-categorizable individuals is maintained among older adults or altered, perhaps due to aging-related cognitive and motivational changes. In three studies using different targets and evaluative tasks, both young and older participants showed evidence of an interplay between Black and elderly stereotypes, such that they perceived elderly Black targets more positively than young Black targets. A similar pattern was observed when assessing emotion change (Study 1), making ratings of warmth and power in the past, present, and future (Study 2), and when directly comparing young and old Black and White targets on traits related to warmth and power (Study 3). The absence of age differences suggests that evaluation of multiply-categorizable targets follows comparable underlying patterns of stereotype activation and inhibition in younger and older adults.
Despite the increasing popularity of video games and the diversity of people who play, prejudice remains common in online gaming. In the current study, we use structural equation modeling to test the role of social norms, individual differences, and gamer identification as predictors of how likely someone is to report engaging in prejudiced behavior while playing online video games. We also test the relative importance of these predictors to assess how likely people are to confront prejudice when it occurs in online video games. Participants (N = 384) completed a series of questionnaires to assess their attitudes and perceptions of online gaming norms, as well as to report their own prejudiced and confrontation behavior in video games. We found that both social norms and individual differences are significant predictors of behavior in online gaming. The more normative people report prejudice to be, the more they report making prejudiced comments. Similarly, the more normative confrontation of prejudice is reported to be, the more likely people are to report confronting prejudice. The more people endorsed generally prejudiced attitudes, the more likely they were to report making prejudiced remakes in online gaming and the less likely they were to report confronting prejudiced remarks. These results provide a foundation to inform interventions to reduce prejudice in gaming and indicate that both individual differences and norms are important to consider when designing interventions.
Due to their awareness of multiraciality and their perceptions of race categories as fluid, multiracial individuals may be unique in how they racially categorize multiracial faces. Yet race categorization research has largely overlooked how multiracial individuals categorize other mixed-race people. We therefore asked Asian, White, and multiracial individuals to categorize Asian-White faces using an open-ended response format, which more closely mirrors real-world race categorizations than forced-choice response formats. Our results showed that perceivers from all three racial groups tended to categorize Asian-White faces as monoracial Asian, White, or Hispanic. However, multiracial perceivers categorized the Asian-White faces as multiracial more often than monoracial perceivers did. Our findings suggest that multiracial individuals may approach racial categorization differently from either monoracial majority or minority group members. Furthermore, our results illustrate possible difficulties multiracial people may face when trying to identify other multiracial in-group members.
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