Experiences of Intimate Partner Violence Victims With Police and the Justice System in Canada
Bibliographic record
Abstract
Legal responses to intimate partner violence (IPV) can determine whether and how those exposed to IPV seek help. Understanding the victim's perspective is essential to developing policy and practice standards, as well as informing professionals working in policing and the justice system. In this survey study, we utilized a subset of 2,831 people who reported experiencing IPV to examine (a) rates of reporting to the police; (b) experiences with, and perceived helpfulness of, police; (c) rates of involvement with the criminal and family law systems, including protection orders; and (d) experiences with, and perceived helpfulness of, the justice system. Data were analyzed using descriptive statistics for closed-ended survey questions and content analysis of text responses. More than 35% of victims reported a violent incident to the police, and perceptions of helpfulness were mixed. Fewer victims were involved with the criminal and family law systems, and their satisfaction also varied. Text responses provided insight into possible reasons for the variability found in experiences, for example, the proposed role of victim and system expectations, and respondents' perception that getting help depends on "being lucky" with the officials encountered.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.017 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".