Do stricter penalties deter drinking and driving? An empirical investigation of Canadian impaired driving laws
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".