Automated Classification of Modes of Moral Reasoning in Judicial Decisions

Résumé

What modes of moral reasoning do judges employ? We construct a linear SVM classifier for moral reasoning mode trained on applied ethics articles written by consequentialists and deontologists. The model can classify a paragraph of text in held out data with over 90 percent accuracy. We then apply this classifier to a corpus of circuit court opinions. We show that the use of consequentialist reasoning has increased over time. We report rankings of relative use of reasoning modes by legal topic, by judge, and by judge law school.

Remplacé par

Nischal Mainali, Liam Meier, Elliott Ash et Daniel L. Chen, « Automated Classification of Modes of Moral Reasoning in Judicial Decisions », dans Computational Legal Studies: The Promise and Challenge of Data-Driven Research, sous la direction de Ryan Whalen, 2020.

Référence

Elliott Ash, Daniel L. Chen, Nischal Mainali et Liam Meier, « Automated Classification of Modes of Moral Reasoning in Judicial Decisions », IAST Working Paper, n° 18-92, décembre 2018.