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Race‐based shifting standards of SES: Potential moderators and implications.

  • Published In: European Journal of Social Psychology, 2023, v. 53, n. 5. P. 906 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Weeks, Matthew; Robinson, Jessica; Stansberry, Jacob; Connor, Paul 3 of 3

Abstract

We report three studies investigating race‐based shifts in interpersonal judgments of SES, investigating potential racism‐related correlates and implications for social judgments. Study 1 examined differences in these race‐based shifts based on respondent race and SES, as well as social dominance orientation, while Study 2 investigated differences based on explicit racial prejudice and motivations to control prejudiced responses. While replicating the shifting standards effect, we observed no relation between either the demographic or prejudice measures and the shifting standards effect. Study 3 used individual differences in the tendency to make these race‐based shifts to predict discriminatory judgments in monetary expectations. Overall, the results supported individual tendencies to make race‐based shifts in judgments of another's SES, and suggest this shift is largely independent of several prominent racial prejudice constructs and predicts potentially discriminatory behaviour. The results are discussed in their implications for interracial and interclass interactions and discriminatory judgments. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:European Journal of Social Psychology. 2023/08, Vol. 53, Issue 5, p906
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2023
  • ISSN:0046-2772
  • DOI:10.1002/ejsp.2943
  • Accession Number:169783470
  • Copyright Statement:Copyright of European Journal of Social Psychology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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