P197 Does being an immigrant affect work disability duration for injured workers in canada?
Bibliographic record
Abstract
Objective To investigate whether disability durations differ by immigration status for injured workers with a workers’ compensation claim. Method A cohort of injured workers with an accepted workers’ compensation claim from 1995 to 2012 was derived from workers’ compensation claim records and linked to Citizenship and Immigration Canada Permanent Residents data. Injured workers were identified as recent immigrants (less than10 years in Canada), established immigrants (10 years or more in Canada), and Canadian-born workers. Disability duration was derived from claim data that indicated the number of disability days paid in the first year after injury. Differences in disability duration by immigration status were examined at different points across the disability duration distribution at the 25th, 50th and 75th percentiles, using quantile regression. Models were stratified by age and sex, and where appropriate, adjusted for age, sex, and occupation. Results Both recent and established immigrants had longer work disability durations than Canadian-born workers, at all points of the distribution (Recent: 25th % 0.5 days, 0.4–0.6; 50th %, 1.8 days, CI: 1.6–2; 75th %, 3.9 days, CI: 3.1–4.7; Established: 25th % 0.9 days, 0.8–1; 50th% 3; CI: 2.8–3.3; 75th % 6.6 days, 5.6–7.5). For younger immigrants, the effect was greater (Recent: 75th „%, 7 days, CI: 6–7.9; Established: 12 days, CI: 9.2–14.8) than at older ages (Recent: 1.3 days, CI: −0.2–2.5; Established: 6 days, CI: 5–7.3). The effect was different for immigrant women (Recent: 75th%, −1.5 days; CI: −3.1–0.01; Established: 6.4 days; CI: 4.8–8.1) than immigrant men (Recent: 75th%, 5.8 days, CI: 4.9–6.8; Established: 6.4 days; CI: 5.2–7.6) in sex-stratified models. Conclusion Immigrants, especially established immigrants, have longer disability durations than Canadian-born workers, following a work injury. Results show that immigrants may face barriers after work injury, which persist even for established immigrants. Future research may need to focus on interventions to reduce this inequality.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".