The appreciation of the collaboration agreements used to prevent intrafamilial homicides
Bibliographic record
Abstract
Purpose The purpose of this paper is to improve the understanding of how collaboration agreements function and their benefits for the environments where they are implemented. The goal of these initiatives is to bring together in partnerships the actors concerned by domestic violence and coordinate their actions to ensure the safety of persons at risk of intrafamilial homicides through an effective collaboration structure. Design/methodology/approach The synthesis data originates from four research projects research work with the partners of four studied agreements: A-GIR (Arrimage-Groupe d’Intervention Rapide [Rapid Intervention Unit]) in Laval, Alerte-Lanaudière [Lanaudière Alert] in the Lanaudière region, P.H.A.R.E. (Prévention des homicides intrafamiliaux par des Actions Rapides et Engagées [Domestic Homicide Prevention through Rapid and Committed Action]) in South Western Montérégie and the Rabaska Protocol in Abitibi-Témiscamingue. Findings Overall, the interveners agree on the positive impacts resulting from the relationships between the partners, the development of a common expertise and the collective responsibility acting to prevent intrafamilial homicides, while highlighting the challenges met and the essential conditions for the success of these collaboration initiatives. Research limitations/implications Findings are drawn from participants in a particular locale – i.e. French–Canada, and may not entirely apply to other regions and cultures. Additional research should be conducted with similar methodology in other regions of Canada and elsewhere. Practical implications The findings should help in the further development of best practices for IPH prevention and therefore protect potential victims from lethal assaults of domestic violence. Originality/value Few studies have been conducted on how stakeholders involved in IPH prevention actually work together in collaborative efforts, and none, as far as we know, specifically on drawing up formal agreements.
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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 | 0.006 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".