SCM-based Fairness and Faithful Explainability for Legal Document Classification
Transformer models such as LegalBERT are increasingly used in legal decision support, raising concerns about both fairness and the transparency of model explanations. These properties are usually evaluated separately, leaving open whether a debiasing intervention that changes fairness also changes how faithfully explanations reflect model reasoning. This study investigates that relationship on the ECtHR alleged-violations corpus from LexGLUE. It compares a LegalBERT baseline with a fairness-regularized variant that penalizes stereotypical warmth and competence representations during fine-tuning. The evaluation covers predictive performance, demographic fairness, and SHAP explanation faith...
| Authors | Yasmina El Kacemi, Seyed Sahand Mohammadi Ziabari, Ali Mohammed Mansoor Alsahag |
|---|---|
| Primary category | cs.CL |
| Published | 3 September 2026 |
| Last updated at source | 3 September 2026 |
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