Hearing the Sexual Assault Complaints of Women with Mental Disabilities: Consent, Capacity, and Mistaken Belief
Bibliographic record
Abstract
Women with mental disabilities experience high rates of sexual assault. The authors trace the history of the criminal law's treatment of cases involving such acts in order to evaluate whether the substantive law of sexual assault is meeting the needs of this group of women. In particular, the authors focus on the legal issues of consent, capacity, and mistaken belief. The authors situate this discussion in the context of current debates in feminist and critical disability theory, grounding the theory in scholarly research on sexual assault of women with mental disabilities. In considering the law's treatment of sexual violence against this group of women, the authors engage two key theoretical tensions: (1) the supposed dichotomy of protection and autonomy, and (2) the shift from biomedical to social models of disability. The authors conclude that the substantive law of sexual assault is inadequate to meet the needs of women with mental disabilities. The authors propose, as a partial solution, a reformed legal analysis that focuses on the accused's abuse of a relationship of power or trust, the accused's coercive behaviour, and the complainant's voluntariness. While the authors acknowledge that women with mental disabilities face certain unique challenges, they reject the creation of special legislative provisions as a solution; they assert instead the importance of recognizing the common experience of inequality that this group shares with other women.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".