The impact of policies regulating alcohol trading hours and days on specific alcohol-related harms: a systematic review
Bibliographic record
Abstract
BACKGROUND: of alcohol sales associate with changes in alcohol-related harm in both directions. However, to the best of our knowledge, no comprehensive systematic reviews had examined the effect of policies restricting time of alcohol trading on specific alcohol-related harms. OBJECTIVE: To compile existing evidence related to the impact of policies regulating alcohol trading hours/days of on specific harm outcomes such as: assault/violence, motor vehicle crashes/fatalities, injury, visits to the emergency department/hospital, murder/homicides and crime. METHODS: Systematic review of literature studying the impact of policies regulation alcohol trading times in alcohol-related harm, published between January 2000 and October 2016 in English language. RESULTS: Results support the premise that policies regulating times of alcohol trading and consumption can contribute to reduce injuries, alcohol-related hospitalisations/emergency department visits, homicides and crime. Although the impact of alcohol trading policies in assault/violence and motor vehicle crashes/fatalities is also positive, these associations seem to be more complex and require further study. CONCLUSION: Evidence suggests a potential direct effect of policies that regulate alcohol trading times in the prevention of injuries, alcohol-related hospitalisations, homicides and crime. The impact of these alcohol trading policies in assault/violence and motor vehicle crashes/fatalities is less compelling.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| 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".