Zero blood alcohol concentration limits for drivers under 21: lessons from Canada
Bibliographic record
Abstract
Graduated licensing programs (GLPs) that include zero or low blood alcohol concentration (BAC) restrictions have proven to be a popular and effective measure for improving traffic safety among young people. However, a major drawback of such programs, at least in Canada, is that the BAC restriction is lifted on completion of the GLP, which typically occurs around the age of 18 or 19. This corresponds to the legal drinking age in Canada, a time when alcohol consumption and rates of binge drinking increase. It is not surprising, then, that 18-20 year-old drivers are dramatically overrepresented in alcohol-related deaths and injuries. One way to address this problem is to raise the legal drinking age, as has occurred in the United States. In jurisdictions, like Canada, that are unlikely to raise the legal drinking age, other measures are necessary to separate drinking from driving among 18-20 year-olds. This article recommends that the zero BAC restrictions be extended beyond the completion of the GLP, until drivers reach the age of 21. The scientific evidence for such a measure is reviewed, and the growing government support for enacting such BAC limits in Canada is described.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".