Impact on alcohol‐related mortality of a rapid rise in the density of private liquor outlets in British Columbia: a local area multi‐level analysis
Bibliographic record
Abstract
AIMS: To study relationships between rates of alcohol-related deaths and (i) the density of liquor outlets and (ii) the proportion of liquor stores owned privately in British Columbia (BC) during a period of rapid increase in private stores. DESIGN: Multi-level regression analyses assessed the relationship between population rates of private liquor stores and alcohol-related mortality after adjusting for potential confounding. SETTING: The 89 local health areas of BC, Canada across a 6-year period from 2003 to 2008, for a longitudinal sample with n = 534. MEASUREMENTS: Population rates of liquor store density, alcohol-related death and socio-economic variables obtained from government sources. FINDINGS: The total number of liquor stores per 1000 residents was associated significantly and positively with population rates of alcohol-related death (P < 0.01). A conservative estimate is that rates of alcohol-related death increased by 3.25% for each 20% increase in private store density. The percentage of liquor stores in private ownership was also associated independently with local rates of alcohol-related death after controlling for overall liquor store density (P < 0.05). Alternative models confirmed significant relationships between changes in private store density and mortality over time. CONCLUSIONS: The rapidly rising densities of private liquor stores in British Columbia from 2003 to 2008 was associated with a significant local-area increase in rates of alcohol-related death.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".