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Automated Classification of Modes of Moral Reasoning in Judicial Decisions

Author

Listed:
  • Nischal Mainali

    (NYU - New York University [New York] - NYU - NYU System)

  • Liam Meier

    (NYU - New York University [New York] - NYU - NYU System)

  • Elliott Ash

    (University of Warwick [Coventry])

  • 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, CNRS - Centre National de la Recherche Scientifique)

Abstract

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.

Suggested Citation

  • Nischal Mainali & Liam Meier & Elliott Ash & Daniel L. Chen, 2023. "Automated Classification of Modes of Moral Reasoning in Judicial Decisions," Working Papers hal-04163443, HAL.
    • Handle: RePEc:hal:wpaper:hal-04163443
    DOI: 10.2139/ssrn.3205286
    Note: View the original document on HAL open archive server: https://hal.science/hal-04163443
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