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

arXiv: https://arxiv.org/abs/2305.05302 · HTML: https://mlsanity.com/paper/2305.05302/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 11 of its 41 references that are in the map.
- First posted on arXiv 9 May 2023.

## Builds on (most cited first, 11 of 11)

- [Large-Scale Multi-Label Text Classification on EU Legislation](https://mlsanity.com/paper/1906.02192/) (2019)
- [Trankit: A Light-Weight Transformer-based Toolkit for Multilingual Natural Language Processing](https://mlsanity.com/paper/2101.03289/) (2021)
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- [Identification of Rhetorical Roles of Sentences in Indian Legal Judgments](https://mlsanity.com/paper/1911.05405/) (2019)
- [Syntactic Search by Example](https://mlsanity.com/paper/2006.03010/) (2020)
- [Empirical Study of Deep Learning for Text Classification in Legal Document Review](https://mlsanity.com/paper/1904.01723/) (2019)
- [pyBART: Evidence-based Syntactic Transformations for IE](https://mlsanity.com/paper/2005.01306/) (2020)
- [Legal and Political Stance Detection of SCOTUS Language](https://mlsanity.com/paper/2211.11724/) (2022)
- [Legal Document Classification: An Application to Law Area Prediction of Petitions to Public Prosecution Service](https://mlsanity.com/paper/2010.12533/) (2020)
- [Automated Extraction of Sentencing Decisions from Court Cases in the Hebrew Language](https://mlsanity.com/paper/2110.12383/) (2021)
- [Sexism in the Judiciary](https://mlsanity.com/paper/2106.15103/) (2021)

## Abstract (arXiv)

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.