Alcohol Availability Across Neighborhoods in Ontario Following Alcohol Sales Deregulation, 2013–2017
Bibliographic record
Abstract
Objectives. To examine the association between neighborhood socioeconomic status (SES) and alcohol availability before and after deregulation in 2015 of the alcohol market in Ontario, Canada. Methods. We quantified alcohol access by number of alcohol outlets and hours of retail for all 19 964 neighborhoods in Ontario. We used mixed effects regression models to examine the associations between alcohol access and a validated SES index between 2013 and 2017. Results. Following deregulation, the number of alcohol outlets in Ontario increased by 15.0%. Low neighborhood SES was positively associated with increased alcohol access: lower-SES neighborhoods had more alcohol outlets within 1000 meters and were closer to the nearest alcohol outlets. Outlets located in low-SES neighborhoods kept longer hours of operation. Conclusions. We observed a substantial increase in alcohol access in Ontario following deregulation. Access to alcohol was greatest in low-SES neighborhoods and may contribute to established inequities in alcohol harms. Public Health Implications. Placing limits on number of alcohol outlets and the hours of operation in low-SES neighborhoods offers an opportunity to reduce alcohol-related health inequities.
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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 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".