O7A.2 Gender, immigration status, and work disability for acute injuries
Bibliographic record
Abstract
Background The nature of work is changing rapidly with precarious work emerging as an occupational health issue. Both immigration status and gender are associated with precarious work and health inequalities. This paper investigated the modifying effect of gender on the relationship between immigration status and work disability duration for acute injuries in the Canadian context. Methods Workers in the Canadian jurisdiction of British Columbia with a workers’ compensation claim from 1995 to 2012 were linked to immigration data (n=8 83 830 claims), and categorized as recent (<10 years, 6.7%) or established immigrants (10+years, 4.0%), versus Canadian-born (89.3%). Work disability days one-year post-injury were modeled using quantile regression, adjusted for confounders and stratified by gender (29.6% women). The analyses was restricted to fractures (n=55 324 claims, 19.4% women), a ‘visible’ injury with a prescribed treatment trajectory within a public health care system. Results Disability duration for a work-related fracture was significantly longer for immigrant workers compared to Canadian–born workers regardless of immigration timing or gender, across the disability distribution: 7 to 10 days longer at the 25th percentile [e.g. recent immigrant women 10.4 [95% CI 5.6, 15.2] and men 8.9 days [6.8, 10.9]]; 12 to 15 days longer at the 50th percentile [e.g. recent immigrant women 15.3 [8.0, 22.7] and men 15.6 [12.5, 18.8]]; and 22 to 26 days longer at the 75th percentile [e.g. established immigrant women 22.5 [9.4, 35.8] and men 21.9 [13.4–30.3]]. Discussion Longer disabilities durations for fractures suggest that health inequalities and work vulnerabilities for immigrant workers are not readily explained by subjective injury characteristics or variability in clinical treatment guidelines. The current findings informed two research initiatives to investigate precarious employment on worker health, and to identity policy levers to mitigate inequalities.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.055 | 0.004 |
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".