Language and unintentional injury mortality in Quebec, Canada
Bibliographic record
Abstract
Language-based differences in unintentional injury are poorly understood, despite the importance of language as a determinant of health. This study assessed inequalities in unintentional injury mortality between Francophones and Anglophones of Quebec, Canada. We calculated age-standardised rates of death by period, region, residential deprivation and cause of injury, and estimated rate ratios for Francophones relative to Anglophones. Francophones had higher unintentional injury mortality rates than Anglophones. Inequalities decreased over time for men, but rates remained 50% higher for Francophones at the end of the study period. Rates were stable for women, but were 30% higher for Francophones compared with Anglophones. Inequalities were larger at age 15-44 years, in urban areas, and for MVCs. Better understanding of risk factors for MVCs may benefit injury prevention in Quebec. Language-based differences in injury mortality warrant attention in other multilingual populations, especially across different demographic, temporal, regional and cause-of-injury groups.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".