Examining the predictive validity of the Ontario Domentic Assault Risk Assessment (ODARA) in police departments and pretrial service agencies in the United States
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
Intimate partner violence (IPV) is a pattern of coercive and controlling behaviors that includes emotional, verbal and psychological abuse, sexual coercion and assault, and other forms of physical violence. Without intervention, IPV tends to escalate in frequency and severity over time and, in extreme cases, intimate partner violence can lead to homicide. The need to determine and treat the most serious cases of IPV has brought about a proliferation of statistical assessments and standardized decision-making tools. One such tool is the ODARA, which has performed very well in tests of predictive validity in Ontario, Canada, and may be appropriate for implementation in the U.S. criminal justice system. However, no tests of the predictive validity of the ODARA have been conducted in the U.S.The current research will provide an empirical base for implementation of the ODARA (or a modified version of the ODARA) in the U.S. criminal justice context as well as recommendations for implementation within police departments and pretrial services. The specific aims of the study are as follows: (1) To examine the predictive validity (at 1, 3, and 5 year follow-up) of the ODARA as used by police in a single county (Saco) and in 2 additional counties in the state of Maine, (2) To examine the predictive validity (at 1, 3, and 5 year follow-up) of the ODARA as used by pretrial services in 2 Counties (Denver, CO and Travis County, TX). The inclusion of multiple sites (with geographic and demographic diversity) and larger sample sizes will also assist with providing justification for generalization.
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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 | 0.018 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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