Suicide fatalities in the US compared to Canada: Potential suicides averted with lower firearm ownership in the US
Bibliographic record
Abstract
INTRODUCTION AND OBJECTIVE: The United States (US) has the highest rate of firearm suicides in the world. The US and Canada are comparable countries with markedly different rates of firearm ownership, providing an opportunity to estimate suicide fatalities that could be averted in the US with a lower rate of firearm ownership. METHODS: We compared 2016 US suicide fatality rates-standardized within fourteen sex-specific age groups to reflect the ethnic composition of Canada-to 2016 Canadian suicide rates. We then calculated the number and proportion of suicides that could be averted in the US if the US had the same rates of suicide as in Canada. RESULTS: If the US had the same suicide rates as in Canada, we estimate there would be approximately 25.9% fewer US suicide fatalities, equivalent to 11,630 suicide fatalities averted each year. This decline would be driven by a 79.3% lower rate of firearm-specific suicide fatalities. The male suicide fatality rate would be 28.8% lower and equivalent to 9,992 fewer suicide fatalities each year. The female suicide fatality rate would be 16.0% lower and equivalent to 1,638 fewer suicide fatalities each year. While 36% of firearm suicide fatalities could be replaced by non-firearm suicide fatalities, 64% of firearm fatalities could be averted entirely. CONCLUSIONS: US policymakers may wish to consider policies that would reduce rates of firearm ownership, given that that about 26% of US suicide fatalities might be averted if the US had the same suicide rates as in Canada, a country with drastically lower firearm ownership rates.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".