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Record W2150601455 · doi:10.1111/0008-4085.00067

Do stricter penalties deter drinking and driving? An empirical investigation of Canadian impaired driving laws

2001· article· en· W2150601455 on OpenAlexaffvenueabout
Anindya Sen

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2001
Typearticle
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsLegislationHumanitiesSpeed limitPoison controlPolitical scienceGeographyLawArtMedicineEnvironmental health

Abstract

fetched live from OpenAlex

In this paper I attempt to assess empirically the effects of Canadian impaired driving legislation enacted between 1976 to 1992. On average, penalties for impaired driving have limited impact on impaired driver fatalities. Instead, trends in impaired driver deaths are significantly correlated with the enactment of mandatory seatbelt legislation across provinces. Specifically, the implementation of mandatory seatbelt laws for drivers is significantly associated with a 27 per cent drop in impaired driver fatality rates. These findings suggest that more lives might be saved by focusing on initiatives aimed at enhancing vehicle safety. JEL Classification: H7, I1 Est‐ce que des punitions plus sévères découragent la conduite en état d'ébriété? Une étude empirique des lois canadiennes sur l'ivresse au volant. Ce texte tente de mesurer empiriquement les effets des lois sur l'ivresse au volant mises en place au Canada entre 1976 et 1992. En général, les punitions pour ivresse au volant ont eu un impact limité sur le nombre de décès de conducteurs en état d'ébriété. D'autre part, les tendances dans le nombre de décès de conducteurs en état d'ébriété sont reliées à la mise en place de législations obligeant le port de la ceinture de sécurité par les provinces. On peut dire que la mise en place de lois sur le port obligatoire de la ceinture de sécurité est associée à une chute de 27 pour‐cent dans le nombre de décès de conducteurs en état d'ébriété. Ces résultats suggèrent que beaucoup plus vies pourraient être épargnées en mettant l'accent sur des mesures qui amélioreraient la sécurité des véhicules.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
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
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.079
GPT teacher head0.184
Teacher spread0.105 · 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

Citations29
Published2001
Admission routes3
Has abstractyes

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