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Attorney voice and the U.S. supreme Court

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  • Daniel L. Chen

    (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

Using data from 1946–2014, we show that audio features of lawyers' introductory statements improve the performance of the best prediction models of Supreme Court outcomes. We infer voice attributes using a 15-year sample of human-labeled Supreme Court advocate voices. Audio features improved prediction of case outcomes by 1.1 percentage points. Lawyer traits receive approximately half the weight of the most important feature from the models without audio features.

Suggested Citation

  • Daniel L. Chen, 2024. "Attorney voice and the U.S. supreme Court," Working Papers hal-04533829, HAL.
    • Handle: RePEc:hal:wpaper:hal-04533829
    Note: View the original document on HAL open archive server: https://hal.science/hal-04533829
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