The Perfect Victim: Computational Analysis of Judicial Attitudes towards Victims of Sexual Violence

TL;DR

This paper presents computational models and a curated dataset to analyze judicial attitudes towards victims of sexual violence, focusing on credibility assessments and the influence of rape myths in Israeli court cases.

Contribution

It introduces an ontology, a manually annotated dataset, and a model for extracting judicial attitudes from court statements in Hebrew sexual assault cases.

Findings

Developed an ontology for judicial credibility assessment

Created a dataset of 855 annotated verdicts from 1990-2021

Built a model to classify judicial attitudes towards victims

Abstract

We develop computational models to analyze court statements in order to assess judicial attitudes toward victims of sexual violence in the Israeli court system. The study examines the resonance of "rape myths" in the criminal justice system's response to sex crimes, in particular in judicial assessment of victim's credibility. We begin by formulating an ontology for evaluating judicial attitudes toward victim's credibility, with eight ordinal labels and binary categorizations. Second, we curate a manually annotated dataset for judicial assessments of victim's credibility in the Hebrew language, as well as a model that can extract credibility labels from court cases. The dataset consists of 855 verdict decision documents in sexual assault cases from 1990-2021, annotated with the help of legal experts and trained law students. The model uses a combined approach of syntactic and latent structures to find sentences that convey the judge's attitude towards the victim and classify them according to the credibility label set. Our ontology, data, and models will be made available upon request, in the hope they spur future progress in this judicial important task.