The Association Between Time Taken to Report, Lodge, and Start Wage Replacement and Return-to-Work Outcomes
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to determine if prolonged times taken to notify, file, adjudicate, and start wage replacement for workers' compensation claims are associated with poorer return-to-work (RTW) outcomes. METHODS: Using 71,607 claims lodged 2007 to 2012, logistic regression determined associations between time to claim filing, adjudication, and payment and (1) socio-demographic/economic, occupational, and injury-related factors; and (2) 52 weeks of wage replacement (WR). RESULTS: Prolonged times for all processing steps were associated with increased odds of reaching 52 weeks of WR. Prolonged times in more than one step increased the odds of a long-term claim. Being female was the only variable consistently associated with each prolonged processing time. CONCLUSIONS: The predictive ability of prolonged times in claim lodgement and processing and compensation payments demonstrate that shorter claims management and adjudication times could improve RTW outcomes.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".