Attorney Voice and the U.S. Supreme Court

Computational Analysis of Law, Santa Fe Institute Press, ed. M. Livermore and D. Rockmore, Forthcoming

18 Pages Posted: 17 Dec 2018 Last revised: 10 Jan 2019

See all articles by Daniel L. Chen

Daniel L. Chen

Directeur de Recherche, Centre National de la Recherche Scientifique, Toulouse School of Economics, Institute for Advanced Study in Toulouse, University of Toulouse Capitole, Toulouse, France

Yosh Halberstam

University of Toronto

Manoj Kumar

Independent

Alan Yu

University of Chicago

Date Written: January 6, 2019

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.

Keywords: Supreme Court, voices

Suggested Citation

Chen, Daniel L. and Halberstam, Yosh and Kumar, Manoj and Yu, Alan, Attorney Voice and the U.S. Supreme Court (January 6, 2019). Computational Analysis of Law, Santa Fe Institute Press, ed. M. Livermore and D. Rockmore, Forthcoming. Available at SSRN: https://ssrn.com/abstract=3241596

Daniel L. Chen (Contact Author)

Directeur de Recherche, Centre National de la Recherche Scientifique, Toulouse School of Economics, Institute for Advanced Study in Toulouse, University of Toulouse Capitole, Toulouse, France ( email )

21 allée de Brienne
31015 Toulouse cedex 6 France
Toulouse, 31015
France

Yosh Halberstam

University of Toronto ( email )

Department of Economics
150 St George St.
Toronto, Ontario M5S 3G7
Canada

Manoj Kumar

Independent

No Address Available

Alan Yu

University of Chicago ( email )

1101 East 58th Street
Chicago, IL 60637
United States

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