A population-based study of homicide deaths in Ontario, Canada using linked death records
Bibliographic record
Abstract
BACKGROUND: Homicide - a lethal expression of violence - has garnered little attention from public health researchers and health policy makers, despite the fact that homicides are a cause of preventable and premature death. Identifying populations at risk and the upstream determinants of homicide are important for addressing inequalities that hinder population health. This population-based study investigates the public health significance of homicides in Ontario, Canada, over the period of 1999-2012. We quantified the relative burden of homicides by comparing the socioeconomic gradient in homicides with the leading causes of death, cardiovascular disease (CVD) and neoplasm, and estimated the potential years of life lost (PYLL) due to homicide. METHODS: We linked vital statistics from the Office of the Registrar General Deaths register (ORG-D) with Census and administrative data for all Ontario residents. We extracted all homicide, neoplasm, and cardiovascular deaths from 1999 to 2012, using International Classification of Diseases codes. For socioeconomic status (SES), we used two dimensions of the Ontario Marginalization Index (ON-Marg): material deprivation and residential instability. Trends were summarized across deprivation indices using age-specific rates, rate ratios, and PYLL. RESULTS: Young males, 15-29 years old, were the main victims of homicide with a rate of 3.85 [IC 95%: 3.56; 4.13] per 100,000 population and experienced an upward trend over the study period. The socioeconomic neighbourhood gradient was substantial and higher than the gradient for both cardiovascular and neoplasms. Finally, the PYLL due to homicide were 63,512 and 24,066 years for males and females, respectively. CONCLUSIONS: Homicides are an important cause of death among young males, and populations living in disadvantaged neighbourhoods. Our findings raise concerns about the burden of homicides in the Canadian population and the importance of addressing social determinants to address these premature deaths.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".