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Familiarity and Race Bias: Evidence from a Television Competition (and the Case for More Women Judges?)

Author

Listed:
  • Chong Bruno Z.

    (Bethesda-Chevy Chase HS, Bethesda, MD 20814, USA)

  • Chong Marco Z.

    (Bethesda-Chevy Chase HS, Bethesda, MD 20814, USA)

Abstract

While social interaction is claimed to help reduce racial bias, the evidence is mixed. We argue that not only interaction, but familiarity among agents may help reduce race bias. We use new data from MasterChef, a nationally syndicated television competition that cover 10 years. We find that familiarity does not help reduce race bias. When judges are all Caucasian they appear to favor Caucasian contestants and set back minority contestants in the final placements. Interestingly, we find an analogous finding with minority judges. Female judges are the only ones who show no bias.

Suggested Citation

  • Chong Bruno Z. & Chong Marco Z., 2022. "Familiarity and Race Bias: Evidence from a Television Competition (and the Case for More Women Judges?)," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 22(2), pages 389-398, April.
    • Handle: RePEc:bpj:bejeap:v:22:y:2022:i:2:p:389-398:n:6
    DOI: 10.1515/bejeap-2022-0058
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    More about this item

    Keywords

    race bias; television; competition; judges; females; minorities;
    All these keywords.

    JEL classification:

    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
    • J79 - Labor and Demographic Economics - - Labor Discrimination - - - Other
    • Z19 - Other Special Topics - - Cultural Economics - - - Other

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