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Covering: Mutable Characteristics and Perceptions of (Masculine) Voice in the U.S. Supreme Court

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  • Chen, Daniel L.
  • Halberstam, Yosh
  • Yu, Alan

Abstract

The emphasis on “fit” as a hiring criterion has raised the spectrum of a new form of subtle discrimination (Yoshino 1998; Bertrand and Duflo 2016). Under complete markets, correlations between employee characteristics and outcomes persist only if there exists animus for the marginal employer (Becker 1957), but who is the marginal employer for mutable characteristics? Using data on 1,901 U.S. Supreme Court oral arguments between 1998 and 2012, we document that voice-based snap judgments based on lawyers’ identical introductory sentences, “Mr. Chief Justice, (and) may it please the Court?”, predict court outcomes. The connection between vocal characteristics and court outcomes is specific only to perceptions of masculinity and not other characteristics, even when judgment is based on less than three seconds of exposure to a lawyer’s speech sample. Consistent with employers irrationally favoring lawyers with masculine voices, perceived masculinity is negatively correlated with winning and the negative correlation is larger in more masculine-sounding industries. The first lawyer to speak is the main driver. Among these petitioners, males below median in masculinity are 7 percentage points more likely to win in the Supreme Court. Justices appointed by Democrats, but not Republicans, vote for lessmasculine men. Female lawyers are also coached to be more masculine and women’s perceived femininity predict court outcomes. Republicans, more than Democrats, vote for more feminine-sounding females. A de-biasing strategy is tested and shown to reduce evaluators’ tendency to perceive masculine voices as more likely to win. Perceived masculinity explains 3-10% additional variance compared to the current best prediction model of Supreme Court votes.

Suggested Citation

  • Chen, Daniel L. & Halberstam, Yosh & Yu, Alan, 2016. "Covering: Mutable Characteristics and Perceptions of (Masculine) Voice in the U.S. Supreme Court," IAST Working Papers 16-38, Institute for Advanced Study in Toulouse (IAST), revised Feb 2020.
  • Handle: RePEc:tse:iastwp:30639
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    References listed on IDEAS

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    Cited by:

    1. Jo Thori Lind & Daniel Chen, 2016. "The Political Economy Of Beliefs: Why Fiscal And Social Conservatives/Liberals Come Hand-In-Hand," 2016 Meeting Papers 606, Society for Economic Dynamics.
    2. Chen, Daniel L., 2016. "Priming Ideology: Why Presidential Elections Affect U.S. Judges," TSE Working Papers 16-681, Toulouse School of Economics (TSE), revised Aug 2016.
    3. Chen, Daniel L. & Prescott, J.J., 2016. "Implicit Egoism in Sentencing Decisions: First Letter Name Effects with Randomly Assigned Defendants," IAST Working Papers 16-56, Institute for Advanced Study in Toulouse (IAST).
    4. Carlos Berdejó & Daniel L. Chen, 2017. "Electoral Cycles among US Courts of Appeals Judges," Journal of Law and Economics, University of Chicago Press, vol. 60(3), pages 479-496.
    5. Chen, Daniel L., 2018. "Machine Learning and Rule of Law," IAST Working Papers 18-88, Institute for Advanced Study in Toulouse (IAST).
    6. Chen, Daniel L. & Sethi, Jasmin, 2016. "Insiders, Outsiders, and Involuntary Unemployment: Sexual Harrassment Exacerbates Gender Inequality," IAST Working Papers 16-44, Institute for Advanced Study in Toulouse (IAST).
    7. Chen, Daniel L., 2018. "Machine Learning and Rule of Law," TSE Working Papers 18-975, Toulouse School of Economics (TSE).
    8. Samantha Bielen & Wim Marneffe & Naci H. Mocan, 2018. "Racial Bias and In-group Bias in Judicial Decisions: Evidence from Virtual Reality Courtrooms," NBER Working Papers 25355, National Bureau of Economic Research, Inc.
    9. Chen, Daniel L., 2018. "Judicial Analytics and the Great Transformation of American Law," TSE Working Papers 18-974, Toulouse School of Economics (TSE).
    10. Chen, Daniel L. & Yeh, Susan, 2016. "Government Expropriation Increases Economic Growth and Racial Inequality: Evidence from Eminent Domain," TSE Working Papers 16-693, Toulouse School of Economics (TSE).
    11. Chen, Daniel L., 2018. "Judicial Analytics and the Great Transformation of American Law," IAST Working Papers 18-87, Institute for Advanced Study in Toulouse (IAST).
    12. Chen, Daniel L., 2018. "Attorney Voice and the U.S. Supreme Court," TSE Working Papers 18-978, Toulouse School of Economics (TSE).
    13. Chen, Daniel L., 2018. "Attorney Voice and the U.S. Supreme Court," IAST Working Papers 18-91, Institute for Advanced Study in Toulouse (IAST).

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    More about this item

    Keywords

    Identity; Phonology; Judicial Decision-Making;
    All these keywords.

    JEL classification:

    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination
    • J78 - Labor and Demographic Economics - - Labor Discrimination - - - Public Policy (including comparable worth)
    • K41 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Litigation Process

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