O-483 Geographic variation in work disability duration in 5 Canadian workers’ compensation jurisdictions
Bibliographic record
Abstract
Introduction Prior research has focused on individual or employer-level factors that influence work disability duration. A smaller number of studies identified differences in work disability duration by province or state and the urban-rural spectrum. Variations may also occur across smaller units of geography due to place-based factors, such as labour market characteristics and healthcare access, that play an important role in work disability duration. Objectives The purpose of this study is to describe geographic variation in work disability duration within five work disability jurisdictions in Canada and examine if variation differs by injury type and jurisdiction. Methods Using Canadian workers’ compensation data, we examined variability in disability days by calculating the coefficient of variations (CVs) across standardized units of geography in cohorts of workers with low back, shoulder and knee injuries. Results Preliminary results suggest shoulder injuries had the longest disability duration with a mean of 50.10 days (SD 67.94), followed by knee injuries with a mean of 44.77 days (SD 62.03). Low back injuries had the shortest duration with a mean of 27.31 days (SD 45.49). There were different patterns of regional variation within jurisdictions. In three jurisdictions, British Columbia, Manitoba and Ontario, higher CV values were observed for shoulder injuries (10.98, 12.03 and 15.65 respectively) and lower CVs observed for knee injuries (6.34, 9.77, 14.19 respectively). In contrast, in Alberta and Saskatchewan CVs were lower for shoulder injuries (4.47 and 4.92 respectively) and higher for low back injuries in Alberta (CV=8.27) and knee injuries in Saskatchewan (CV=13.49). Conclusion Findings suggest that variation across regions differs by jurisdiction and injury cohorts. This variation may reflect differences in approaches to treatment for specific injuries across jurisdictions. Further analysis will examine the association between work disability duration and workers’ compensation healthcare utilization and spending in these cohorts.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".