Geographic variation in work injuries: a multilevel analysis of individual-level data and area-level factors within Canada
Bibliographic record
Abstract
PURPOSE: This study sought to examine provincial variation in work injuries and to assess whether contextual factors are associated with geographic variation in work injuries. METHODS: Individual-level data from the 2003 and 2005 Canadian Community Health Survey was obtained for a representative sample of 89,541 Canadians aged 15 to 75 years old who reported working in the past 12 months. A multilevel regression model was conducted to identify geographic variation and contextual factors associated with the likelihood of reporting an activity limiting work injury [corrected], while adjusting for demographic and work variables. RESULTS: Provincial differences in work injuries were observed, even after controlling for other risk factors. Workers in western provinces such as Saskatchewan (adjusted odds ratio [AOR], 1.30; 95% confidence interval [CI], 1.09-1.55), Alberta (AOR, 1.31; 95% CI, 1.13-1.51), and British Columbia (AOR, 1.46; 95% CI, 1.26-1.71) had a higher risk of work injuries compared with Ontario workers. Indicators of area-level material and social deprivation were not associated with work injury risk. CONCLUSIONS: Provincial differences in work injuries suggest that broader factors acting as determinants of work injuries are operating across workplaces at a provincial level. Future research needs to identify the provincial determinants and whether similar large area-level factors are driving work injuries in other countries.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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; 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".