The Effects of Race and Gender When Predicting Intimate Partner Violence Recidivism in Police Reports Using the Ontario Domestic Assault Risk Assessment
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
Despite a growth in risk assessment for intimate partner violence (IPV), validation research has focused on men’s violence against women leading to a dearth of research among other genders and racialized populations. We examined validity of an IPV risk assessment tool in 448 Black and White men and women identified as IPV perpetrators by a United States urban police service. The Ontario Domestic Assault Risk Assessment (ODARA) predicted new police reports of IPV in a fixed 2-year follow up (baserate = 33%, AUC = 0.59). Predictive effects were mostly small, with few significant differences between groups. Further research should examine the benefits and potential harms of IPV risk assessment to individuals who identify within minority race and gender groups.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it