The Perfect Victim: Computational Analysis of Judicial Attitudes towards Victims of Sexual Violence
This addresses the problem of understanding judicial bias in sexual assault cases for legal researchers and policymakers, though it appears incremental as it applies existing computational methods to a new domain.
The researchers developed computational models to analyze judicial attitudes toward sexual violence victims in Israeli courts, creating an ontology and dataset of 855 verdict documents (1990-2021) and a model that extracts credibility labels from court cases.
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.