Abstract Accident Analysis and Prevention 37 (2005) 549–556 Road safety impact of extended drinking hours in Ontario
Bibliographic record
Abstract
establishments from 1 to 2 a.m. The purpose of this study was to evaluate the road safety impact of extended drinking hours in Ontario. Method: A quasi-experimental design using interrupted time series with a nonequivalent no-intervention control group was used to assess changes. The analyzed data sets are total and alcohol-related, monthly, traffic fatalities for Ontario, for the 11–12 p.m., 12–1 a.m., 1–2 a.m. and 2–3 a.m. time windows, for Sunday through Wednesday nights and for Thursday through Saturday nights, for 4 years pre- and 3 years post-policy change, compared to neighbouring regions of New York and Michigan. Results: The blood alcohol concentration positive driver fatality trends reflected downward trends for Sunday–Wednesday 12–2 a.m. and Thursday–Saturday 1–2 a.m. for Ontario and downward trends for Thursday–Saturday 12–1 a.m. and 2–3 a.m. for New York and Michigan after the extended drinking hour policy change. Ontario total fatality data showed similar trends to the Ontario blood alcohol positive trends. Conclusions: The multiple datasets converge in suggesting little impact on BAC positive fatalities with extension of the closing hours. These observations are consistent with other studies of small changes in alcohol 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".