Neighborhood Socioeconomic Status and Homicides Among Children in Urban Canada
Bibliographic record
Abstract
OBJECTIVE: We sought to determine the influence of neighborhood income on homicides among children living in urban Canada. METHODS: Homicides among children <15 years of age living in any of Canada's census metropolitan areas in 1996, 1997, or 1998 were identified on the basis of vital statistics death registration data, by using International Classification of Diseases, Ninth Revision codes. Deaths were assigned to census tracts through postal codes, and the tracts were then assigned to neighborhood income quintiles on the basis of the proportions of the population below the Statistics Canada low-income cutoff values. Census population counts and intercensal population interpolations were used to estimate person-years at risk for rate calculations. Interquintile rate ratios and 95% confidence intervals were calculated. Poisson regression was used to model the effects of neighborhood income quintiles on homicide rates, after adjustment for age. RESULTS: During the 3-year study period, there were 87 homicides among children <15 years of age in Canada's census metropolitan areas (0.82 cases per 100,000; not statistically different according to gender). The age-adjusted relative risks for the lowest versus highest neighborhood income quintiles were 2.95 for all children <15 years of age and 3.39 for children <5 years of age. CONCLUSION: Effective child homicide-prevention strategies should be focused on children <5 years of age living in low-income areas.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".