Cohort profile: workers’ compensation in a changing Australian labour market: the return to work (RTW) study
Bibliographic record
Abstract
PURPOSE: Workers' compensation claims for older workers and workers who have suffered psychological injury are increasing as a proportion of total claims in many jurisdictions. In the Australian state of Victoria, claims from both these groups are associated with higher than average wage replacement and healthcare expenditures. This cohort profile describes a longitudinal study which aims to investigate differences in the return to work (RTW) process for older workers compared with younger workers and claimants with musculoskeletal injuries compared with those with psychological injuries. PARTICIPANTS: This prospective cohort study involved interviewing workers' compensation claimants at three time points. The cohort was restricted to psychological and musculoskeletal claims. Only claimants aged 18 and over were recruited, with no upper age limit. A total of 869 claimants completed the baseline interview, representing 36% of the eligible claimant population. Ninety-one per cent of participants agreed at baseline to have their survey responses linked to administrative workers' compensation data. Of the 869 claimants who participated at baseline, 632 (73%) took part in the 6-month follow-up interview, and 572 (66%) participated in the 12-month follow-up interview. FINDINGS TO DATE: Information on different aspects of the RTW process and important factors that may impact the RTW process was collected at the three survey periods. At baseline, participants and non-participants did not differ by injury type or age group, but were more likely to be female and from the healthcare and social assistance industry. The probability of non-participation at follow-up interviews showed younger age was a statistically significant predictor of non-participation. FUTURE PLANS: Analysis of the longitudinal cohort will identify important factors in the RTW process and explore differences across age and injury type groups. Ongoing linkage to administrative workers' compensation data will provide information on wage replacement and healthcare service use into the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".