Alcohol retail privatisation in Canadian provinces between 2012 and 2017. Is decision making oriented to harm reduction?
Bibliographic record
Abstract
INTRODUCTION: Policy changes may contribute to increased alcohol-related risks to populations. These include privatisation of alcohol retailing, which influences density of alcohol outlets, location of outlets, hours of sale and prevention of alcohol sales to minors or intoxicated customers. Meta-analyses, reviews and original research indicate enhanced access to alcohol is associated with elevated risk of and actual harm. We assess the 10 Canadian provinces on two alcohol policy domains-type of alcohol control system and physical availability of alcohol-in order to track changes over time, and document shifting changes in alcohol policy. METHODS: Our information was based on government documents and websites, archival statistics and key informant interviews. Policy domains were selected and weighted for their degree of effectiveness and population reach based on systematic reviews and epidemiological evidence. Government representatives were asked to validate all the information for their jurisdiction. RESULTS: The province-specific reports based on the 2012 results showed that 9 of 10 provinces had mixed retail systems-a combination of government-run and privately owned alcohol outlets. Recommendations in each provincial report were to not increase privatisation. However, by 2017 the percentage of off-premise private outlets had increased in four of these nine provinces, with new private outlet systems introduced in several. DISCUSSION AND CONCLUSIONS: Decision-making protocols are oriented to commercial interests and perceived consumer convenience. If public health and safety considerations are not meaningfully included in decision-making protocols on alcohol policy, then it will be challenging to curtail or reduce harms.
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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".