MétaCan
Menu
Back to cohort
Record W1998615389 · doi:10.1136/ip.2007.017095

Zero blood alcohol concentration limits for drivers under 21: lessons from Canada

2008· review· en· W1998615389 on OpenAlexaffabout
Erika Chamberlain, R Solomon

Bibliographic record

VenueInjury Prevention · 2008
Typereview
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsWestern University
Fundersnot available
KeywordsBlood alcoholPoison controlForensic engineeringAlcoholEngineeringHuman factors and ergonomicsInjury preventionZero (linguistics)Occupational safety and healthSuicide preventionMedical emergencyEnvironmental scienceEnvironmental healthMedicineChemistry

Abstract

fetched live from OpenAlex

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.044
GPT teacher head0.304
Teacher spread0.260 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations16
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueInjury PreventionSame topicTraffic and Road SafetyFrench-language works237,207