MétaCan
Menu
Back to cohort
Record W7098341219

Abstract Accident Analysis and Prevention 37 (2005) 549–556 Road safety impact of extended drinking hours in Ontario

2003· article· en· W7098341219 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsThursdayBlood alcoholOccupational safety and healthCase fatality ratePoison controlAccident analysisInjury preventionTraffic accident
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.580
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.027
GPT teacher head0.354
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2003
Admission routes1
Has abstractyes

Explore more

Same topicEducation and Islamic StudiesFrench-language works237,207