0465 Gender, age, and the changing burden of work-related disability in canada and australia
Bibliographic record
Abstract
Objectives This research investigates the changing burden of work-related disability in Canada and Australia and how this varies by gender and age. The secondary objective is to demonstrate a means of comparing work disability data internationally. Methods Workers’ compensation data from Canada and Australia were used to analyse the relative disability burden of workers injured between 2004 and 2010. The two measures used were the number of claims with compensated time-loss and the corresponding time-loss years accrued, indexed to 2004. Gender and age-stratified analyses were conducted using descriptive statistics. Results Male workers had more claims and cumulative time-loss in both countries. They also had steeper reductions in claim volumes and cumulative time-loss over time, indicating a narrowing in overall gender differences. Age-stratified analysis showed that differences between men and women were smaller among younger workers compared to older workers. In Canada, the proportion of claims attributable to females grew at the same rate as the proportion of time loss until 2007–08 when a gap emerged. In Australia, the proportion of claims and time loss attributable to females grew closer over time. Conclusions While the volume of claims and cumulative time-loss has decreased in Canada and Australia, and the largest proportion is attributable to workers who are male and aged 35–54, a growing proportion is attributable to female and older workers. These changes have been driven by demographic factors (growth of females in the workforce, ageing workforce) and structural factors (economic recession and policy changes), particularly in Canada.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".