MétaCan
Menu
Back to cohort
Record W2575125221 · doi:10.1080/15389588.2016.1149169

Self-reported driving under the influence of alcohol and cannabis among Ontario students: Associations with graduated licensing, risk taking, and substance abuse

2017· article· en· W2575125221 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueTraffic Injury Prevention · 2017
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of TorontoThe King's UniversityCentre for Addiction and Mental HealthNipissing University
FundersCanadian Institutes of Health Research
KeywordsCannabisPoison controlInjury preventionOccupational safety and healthSuicide preventionDriving under the influenceHuman factors and ergonomicsMedicineAlcohol abusePsychologyEnvironmental healthMedical emergencyPsychiatryEngineeringClinical psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: This article describes the patterns of self-reported driving under the influence of alcohol (DUIA) and driving under the influence of cannabis (DUIC) among licensed Ontario students in 2009 and examines their associations with graduated licensing, risk taking, and substance use problems for understanding DUIA and DUIC behaviors. Ontario's graduated licensing system requires new drivers to hold a G1 license for a minimum of 8 months and a G2 license for a minimum of 12 months before a full and unrestricted G license can be obtained. Among other restrictions, G1 drivers must maintain a 0 blood alcohol content (BAC), have an experienced driver in the passenger seat, not drive on any high-speed expressways, and not drive between the hours of midnight and 5 a.m. A G2 license is more similar to a G license, with fewer restrictions. METHOD: This study analyzed data from the 2009 Ontario Student Drug Use and Health Survey (OSDUHS). The OSDUHS is a biennial population-based survey of students (grades 7 to 12) in Ontario, Canada. RESULTS: The results showed that 16.3% of licensed students in Ontario reported DUIC and 11.5% reported DUIA during the past year. After controlling for the effect of age, type of license emerged as a robust predictor for both DUIA and DUIC behavior, because students with a G2 and full license were significantly more likely to report DUIA and DUIC than drivers with a G1 license. Multivariate analyses suggested that risk-seeking behaviors were more important for understanding DUIA behavior than for DUIC behavior. Elevated problem indicators for alcohol and for cannabis were associated with DUIA and DUIC, respectively. CONCLUSIONS: Though much attention has been paid to drinking and driving among adolescents, this research shows that more Ontario students now report driving after cannabis use than after drinking alcohol. The results identify important correlates of both behaviors that may be useful for prevention purposes.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.997

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 studies0.0010.000
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 head0.019
GPT teacher head0.321
Teacher spread0.302 · 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