Is Retail Alcohol Deregulation Correlated with More Crime and Traffic Injuries? Evidence from Canadian Provinces
Bibliographic record
Abstract
Data across six Canadian provinces from 1993 to 2011 are employed to estimate the effects of differences in retail alcohol distribution systems on trends in per capita violent and property crime rates and fatality and injury rates from motor vehicle accidents. OLS estimates of dummy variables representing the presence of a more deregulated retail distribution system are either statistically insignificant or significant and negative with respect to different types of crime and traffic-related injuries. These results are robust to the inclusion of different covariates and province/year fixed effects. Estimates from multivariate regression models also reveal that per capita alcohol sales are not higher in provinces with deregulated retail access. Finally, data from the Canadian Community Health Surveys do not reveal any consistent differences between regulated and deregulated provinces in binge drinking among teens and young adults. In summary, provinces with more deregulated retail access to alcohol do not experience worse outcomes than jurisdictions with more controlled availability.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".