An ecological study of regional variation in work injuries among young workers
Bibliographic record
Abstract
BACKGROUND: The investigation of geographic variation in occupational injuries has received little attention. Young workers 15 to 24 years are of particular concern because they consistently show elevated occupational injury rates compared to older workers. The present study sought to: (a) to describe the geographic variation of work injuries; (b) to determine whether geographic variation remained after controlling for relevant demographic and job characteristics; (c) to identify the region-level factors that correlate with the geographic variation. METHODS: Using workers compensation claims and census data, we estimated claim rates per 100 full-time equivalents for 15 to 24 year olds in 46 regions in Ontario. A total of 21 region-level indicators were derived primarily from Census and Labour Force Survey data to reflect social and material deprivation of the region as well as demographic and employment characteristics of youth living in those areas. RESULTS: Descriptive findings showed substantial geographic variation in young worker injury rates, even after controlling for several job and demographic variables. Region-level characteristics such as greater residential stability were associated with low work injury rates. Also, regions with the lowest claim rates tended to have proportionally fewer cuts and burns than high-claim-rate regions. CONCLUSION: The finding of substantial geographic variation in youth claim rates even after controlling for demographic and job factors can aid in targeting prevention resource. The association between region-level indicators such as residential stability and youth work injury suggests that work injury prevention strategies can be integrated with other local economic development measures. The findings partially support the notion that work safety measures may be unevenly distributed with respect to regional socio-economic factors.
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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 | 0.018 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".