9. Police Investigation of Sexual Assault Complaints: How Far Have We Come Since Jane Doe?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.010 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 it