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Early Career Citations Capture Judicial Idiosyncrasies and Predict Judgments

Published 1 Oct 2024 in cs.SI | (2410.00725v1)

Abstract: Judicial impartiality is a cornerstone of well-functioning legal systems. We assemble a dataset of 112,312 civil lawsuits in U.S. District Courts to study the effect of extraneous factors on judicial decision making. We show that cases are randomly assigned to judges and that biographical judge features are predictive of judicial decisions. We use low-dimensional representations of judges' early-career citation records as generic representations of judicial idiosyncrasies. These predict future judgments with accuracies exceeding 65% for high-confidence predictions on balanced out-of-sample test cases. For 6-8% of judges, these representations are significant predictors across all judgments. These findings indicate that a small but significant group of judges routinely relies on extraneous factors and careful vetting of judges prior to appointment may partially address this issue. Our use of low-dimensional representations of citation records may also be generalized to other jurisdictions or to study other aspects of judicial decision making.

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References (51)
  1. McKechnie, W. S. Magna Carta: A Commentary on the Great Charter of King John: with an Historical Introduction (DigiCat, 2022).
  2. Schiffman, L. H. Chapter twelve. the prohibition of judicial corruption in the dead sea scrolls, philo, josephus and talmudic law. In The Courtyards of the House of the Lord, 189–212 (Brill, 2008).
  3. Images of justice. Yale Law Journal 96, 1727 (1986).
  4. Dworkin, R. Natural law revisited. University of Florida Law Review 34, 165 (1981).
  5. Nelson, C. What is textualism. Virginia Law Review 91, 347 (2005).
  6. Sunstein, C. R. Beyond marbury: The exective’s power to say what the law is. Yale Law Journal 115, 2580 (2005).
  7. Hart, H. L. A. The Concept of Law (Oxford University Press, 1961).
  8. Fuller, L. L. The morality of law (Yale University Press, 1964).
  9. Marmor, A. No easy cases? Canadian Journal of Law & Jurisprudence 3, 61–79 (1990).
  10. Howard Jr, J. W. Courts of appeals in the federal judicial system: A study of the second, fifth, and District of Columbia circuits, vol. 647 (Princeton University Press, 2014).
  11. Posner, R. A. Some realism about judges: A reply to edwards and livermore. Duke Law Journal 59, 1177–1186 (2010).
  12. Cardozo, B. N. The growth of the law (Yale University Press, 1924).
  13. Extraneous factors in judicial decisions. Proceedings of the National Academy of Sciences 108, 6889–6892 (2011).
  14. Racial bias in bail decisions. The Quarterly Journal of Economics 133, 1885–1932 (2018).
  15. Does the judge matter? exploiting random assignment on a court of last resort to assess judge and case selection effects. Journal of Empirical Legal Studies 9, 246–290 (2012).
  16. Bhowmick, A. et al. In-group bias in the indian judiciary: Evidence from 5.5 million criminal cases. In ACM SIGCAS Conference on Computing and Sustainable Societies, 47–47 (2021).
  17. Litigation finance at trial: Model and data. SSRN Working Paper (2022).
  18. Lawlor, R. C. Information technology and the law. In Advances in Computers, vol. 3, 299–352 (Elsevier, 1962).
  19. The supreme court forecasting project: Legal and political science approaches to predicting supreme court decisionmaking. Columbia Law Review 104, 1150–1210 (2004).
  20. Using modern neural networks to predict the decisions of supreme court of the united states with state-of-the-art accuracy. In International Conference on Neural Information Processing, 475–483 (Springer, 2015).
  21. A general approach for predicting the behavior of the supreme court of the united states. PloS one 12, e0174698 (2017).
  22. Zhong, H. et al. Legal judgment prediction via topological learning. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 3540–3549 (2018).
  23. Using machine learning to predict decisions of the european court of human rights. Artificial Intelligence and Law 28, 237–266 (2020).
  24. Neural legal judgment prediction in English. In Korhonen, A., Traum, D. & Màrquez, L. (eds.) Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 4317–4323 (Association for Computational Linguistics, Florence, Italy, 2019). URL https://aclanthology.org/P19-1424.
  25. Human decisions and machine predictions. The quarterly journal of economics 133, 237–293 (2018).
  26. G’sell, F. AI judges. Global Perspectives on Law and Ethics, Cambridge University Press (2022).
  27. Pah, A. R. et al. How to build a more open justice system. Science 369, 134–136 (2020).
  28. Glöckner, A. The irrational hungry judge effect revisited: Simulations reveal that the magnitude of the effect is overestimated. Judgment and Decision making 11, 601–610 (2016).
  29. Kling, J. R. Incarceration length, employment, and earnings. American Economic Review 96, 863–876 (2006).
  30. Criminal recidivism after prison and electronic monitoring. Journal of political Economy 121, 28–73 (2013).
  31. Short-and long-term effects of imprisonment on future felony convictions and prison admissions. Proceedings of the National Academy of Sciences 114, 11103–11108 (2017).
  32. Collinson, R. et al. Eviction and Poverty in American Cities. The Quarterly Journal of Economics 139, qjad042 (2023). URL https://doi.org/10.1093/qje/qjad042. https://academic.oup.com/qje/advance-article-pdf/doi/10.1093/qje/qjad042/51667881/qjad042.pdf.
  33. The unintended impact of pretrial detention on case outcomes: Evidence from new york city arraignments. The Journal of Law and Economics 60, 529–557 (2017).
  34. The effects of pre-trial detention on conviction, future crime, and employment: Evidence from randomly assigned judges. American Economic Review 108, 201–240 (2018).
  35. The behavior of federal judges: a theoretical and empirical study of rational choice (Harvard University Press, 2012).
  36. The curious incident of the falling win rate: Individual vs system-level justification and the rule of law. UC Davis Law Review 52, 1371 (2018).
  37. Learning the parts of objects by non-negative matrix factorization. Nature 401, 788–791 (1999).
  38. Identifying latent activity behaviors and lifestyles using mobility data to describe urban dynamics. EPJ Data Science 12, 15 (2023).
  39. Metagenes and molecular pattern discovery using matrix factorization. Proceedings of the National Academy of Sciences 101, 4164–4169 (2004).
  40. Determinacy, objectivity, and authority. University of Pennsylvania Law Review 142, 549–637 (1993).
  41. Dworkin, R. Hard cases. Harvard Law Review 88, 1057 (1974).
  42. Steinman, A. N. The irrepressible myth of celotex: Reconsidering summary judgment burdens twenty years after the trilogy. Washington and Lee Law Review 63, 81 (2006).
  43. Ramadan fasting increases leniency in judges from pakistan and india. Nature Human Behaviour 7, 874–880 (2023). URL https://doi.org/10.1038/s41562-023-01547-3.
  44. Judges, juveniles, and in-group bias. The Journal of Law and Economics 60, 209–239 (2017).
  45. A test of racial bias in capital sentencing. American Economic Review 104, 3397–3433 (2014).
  46. Judicial ingroup bias in the shadow of terrorism. The Quarterly journal of economics 126, 1447–1484 (2011).
  47. Addressing information asymmetry in legal disputes through data-driven law firm rankings. arXiv preprint arXiv:2408.16863 (2024).
  48. Judge shopping. Journal of Legal Analysis 13, 341–379 (2021).
  49. Longformer: The long-document transformer. arXiv preprint arXiv:2004.05150 (2020).
  50. The control of the false discovery rate in multiple testing under dependency. Annals of statistics 29, 1165–1188 (2001).
  51. Algorithms to estimate shapley value feature attributions. Nature Machine Intelligence 5, 1–12 (2023).

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