MétaCan
Menu
Back to cohort
Record W1996143496 · doi:10.1080/00207594.2010.526121

Canadian and Spanish youths’ risk perceptions of drinking and driving, and riding with a drunk driver

2010· article· en· W1996143496 on OpenAlexaffabout
Mandeep K. Dhami, David R. Mandel, Rocío García‐Retamero

Bibliographic record

VenueInternational Journal of Psychology · 2010
Typearticle
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsUniversity of TorontoDefence Research and Development Canada
Fundersnot available
KeywordsDrunk drivingDriving under the influencePsychologyDrunk driversPerceptionSuicide preventionInjury preventionHuman factors and ergonomicsPoison controlSocial psychologyApplied psychologyEnvironmental healthMedicine

Abstract

fetched live from OpenAlex

The present research compared Canadian and Spanish youths' perceptions of the potential benefits and drawbacks of driving under the influence of alcohol (DUI) and riding with a drunk driver (RDD). Eighty (41 female) Canadian and 87 (71 female) Spanish undergraduates completed a survey asking about their past and forecasted engagement in DUI and RDD, and their perceptions of the benefits and drawbacks of DUI and RDD. A sizeable proportion of both samples reported DUI and RDD in the past year. Past risk takers forecasted significantly greater chances of engaging in these behaviors in the following year compared to those who had not engaged in DUI and RDD. Both samples provided significantly more drawbacks than benefits of DUI and RDD. Whereas the benefits of both behaviors tended to refer to personal effects (e.g., save money, arrive faster) that occurred before, during, or after driving, the drawbacks referred to a range of outcomes (e.g., accident, kill/injure, penal sanction) that mostly occurred during driving. Although Canada and Spain differ in important respects (e.g., potential penalty for DUI), there were similarities in the two samples' perceptions of DUI and RDD. Young people are aware of the costs of these risky behaviors but nevertheless engage in them. These findings can inform theories of the co-occurrence of risky driving behaviors, and the development of prevention programs that focus on perceived outcomes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.004
GPT teacher head0.236
Teacher spread0.232 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations13
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of PsychologySame topicTraffic and Road SafetyFrench-language works237,207