Contribution à des ouvrages

Attorney Voice and the U.S. Supreme Court

Daniel L. Chen, Yosh Halberstam, Manoj Kumar et Alan Yu

Résumé

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.

Remplace

Daniel L. Chen, « Attorney Voice and the U.S. Supreme Court », IAST Working Paper, n° 18-91, décembre 2018.

Voir aussi

Publié dans

Law as Data: Computation, Text, and the Future of Legal Analysis, 2019sous la direction de Michael Livermore et Daniel Rockmore, Santa Fe Institute Press, 2019