Alcohol Sales and Risk of Serious Assault
Bibliographic record
Abstract
BACKGROUND: Alcohol is a contributing cause of unintentional injuries, such as motor vehicle crashes. Prior research on the association between alcohol use and violent injury was limited to survey-based data, and the inclusion of cases from a single trauma centre, without adequate controls. Beyond these limitations was the inability of prior researchers to comprehensively capture most alcohol sales. In Ontario, most alcohol is sold through retail outlets run by the provincial government, and hospitals are financed under a provincial health care system. We assessed the risk of being hospitalized due to assault in association with retail alcohol sales across Ontario. METHODS AND FINDINGS: We performed a population-based case-crossover analysis of all persons aged 13 years and older hospitalized for assault in Ontario from 1 April 2002 to 1 December 2004. On the day prior to each assault case's hospitalization, the volume of alcohol sold at the store in closest proximity to the victim's home was compared to the volume of alcohol sold at the same store 7 d earlier. Conditional logistic regression analysis was used to determine the associated relative risk (RR) of assault per 1,000 l higher daily sales of alcohol. Of the 3,212 persons admitted to hospital for assault, nearly 25% were between the ages of 13 and 20 y, and 83% were male. A total of 1,150 assaults (36%) involved the use of a sharp or blunt weapon, and 1,532 (48%) arose during an unarmed brawl or fight. For every 1,000 l more of alcohol sold per store per day, the relative risk of being hospitalized for assault was 1.13 (95% confidence interval [CI] 1.02-1.26). The risk was accentuated for males (1.18, 95% CI 1.05-1.33), youth aged 13 to 20 y (1.21, 95% CI 0.99-1.46), and those in urban areas (1.19, 95% CI 1.06-1.35). CONCLUSIONS: The risk of being a victim of serious assault increases with alcohol sales, especially among young urban men. Akin to reducing the risk of driving while impaired, consideration should be given to novel methods of preventing alcohol-related violence.
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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 | 0.001 | 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 | 0.000 | 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".