Differences in Drowning Rates between Rural and Non-Rural Residents of Ontario, Canada
Bibliographic record
Abstract
The objective of our study was to determine if rural residence was associated with an increased risk of drowning in Ontario, Canada. We conducted a retrospective cohort study of all unintentional drowning deaths in Ontario Canada from 2004 to 2008. Age-adjusted mortality rates for males and females living in rural and non-rural areas were calculated using direct standardization, with non-rural residents as the reference population. We identified a total of 564 unintentional drowning deaths. The majority (89%) of fatal drowning victims were male, and 75% percent of victims were from non-rural area. Excluding bathtub drowning deaths, the age-adjusted drowning mortality rate was significantly higher for both males (rate ratio 2.8; 95% CI, 2.3- 3.4) and females (rate ratio 2.8; 95% CI 1.5- 5.0) from rural compared to non-rural areas. In Ontario, rural residence was associated with an increased risk of unintentional drowning.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".