Intentional injury and violent death after intimate partner violence. A retrospective matched-cohort study
Bibliographic record
Abstract
The incidence of intimate partner violence (IPV) varies according to IPV definitions and data collection approaches. The criminal Justice system assesses IPV through a review of the evidence gathered by the police and the court hearings. We aimed to determine the association between IPV, as identified in criminal Justice disposition records, and subsequent healthcare-identified intentional injury inflicted by others, including violent death. We conducted a retrospective population-based matched-cohort study using linked multisectoral databases. Female adult Manitoba residents identified as victims of IPV in provincial prosecution and disposition records 2004 to 2016 (n = 20,469) were matched to three non-victims (n = 61,407) of similar age, relationship status and place of residence at the date of the IPV incident. Outcomes were first healthcare use for intentional injury and violent death, assessed in Emergency Department visits, hospitalizations and Vital Statistics deaths records. Conditional Cox Regression was used to obtain Hazard Ratios (HR) with 95% confidence intervals (CI). The risk of intentional injury was 8.5 per 1000 women among non-victims of IPV and 55.8 per 1000 women among IPV victims. The Hazard Ratios associated with IPV were 3.8 (95% CI: 3.4, 4.3) for intentional injury and 4.6 (95% CI: 2.3, 9.2) for violent death, after adjustment. IPV victims experienced half the risk of subsequent intentional injury if the accused received a probation sentence. Our findings suggest that Justice involvement represents an opportunity for intersectoral collaborative prevention of subsequent intentional injury among IPV victims.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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 teacher head, 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".