L'effet des lois en matière de contrôle des armes à feu sur les homicides au Canada, 1974–2004
Bibliographic record
Abstract
Bills C-51 (1977), C-17 (1991), and C-68 (1995) were enacted into law by the Government of Canada with a view to tightening controls on firearms in order to prevent homicides related to their use. The effectiveness of these laws has fuelled several debates on the political scene. Given the many limitations of assessments conducted to this day, the credibility of their results is often questioned. Using a multiple-time-series design, the purpose of this article is to assess the impact of the three most recent Canadian gun control laws, all the while overcoming the limitations identified in the scientific literature. Our results show that the enactment of Bills C-51 and C-68 was followed by a significant drop in the number of homicides committed with a firearm, a decrease of 5% to 10%, depending on the province. This reduction was most noticeable in the case of homicides committed with a shotgun or a hunting rifle. No tactical displacement was observed. Finally, results suggest that the effectiveness of these laws is due to the reduced access and availability of firearms rather than to the severity of sentences provided in the legislation.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".