9. Police Investigation of Sexual Assault Complaints: How Far Have We Come Since Jane Doe?
Bibliographic record
Abstract
This chapter turns to the “unfounding” problem condemned by Jane Doe’s judge in her legal victory in 1998. Teresa DuBois revisits the Jane Doe Social Audit mentioned in the first chapter of this book, “The Victories of Jane Doe.” The audit represented an effort by activists to pressure police to respond to the legal judgment against them by reforming their investigatory practices and discarding biased assumptions in their assessments of the credibility of women’s reports of sexual assault. Teresa reviews successive audit reports from Toronto and studies beyond that show not only that police continue to unfound sexual assault reports at higher rates than any other crime, but also that “rape myths” seem to be operative in police assessments of whom to believe. Two investigative techniques used by police to assess women’s credibility, both premised on women as “hard to be believed,” may play a role in sexual assault being “wrongfully” unfounded. Teresa joins Fran Odette in calling for data collection as the basis for policy-making and legal strategy
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".