Developing a National Collaborative Approach to Prevent Domestic Homicides: Domestic Homicide Review Committees
Bibliographic record
Abstract
Canadian perspectives on domestic homicide review and prevention were discussed at a 2010 national think-tank held in London, Ontario. The think-tank brought together practitioners, researchers, and government officials from 10 provinces and two territories to share regional experiences with domestic homicide reviews, to identify benefits and challenges of conducting reviews for domestic homicide prevention, and to outline promising practices that have been or may be implemented to address challenges. Think-tank members discussed both the differences and similarities of death review processes within individual provinces/territories and emerging issues and concerns around domestic violence death reviews. The final outcome of the think-tank was the identification of next steps in domestic homicide death review and prevention through various recommendations that support the future framework for research and practice in this area.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.244 | 0.232 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.013 | 0.007 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.007 | 0.016 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".