<scp>The Effects of Occupational Injuries After Returns to Work: Work Absences and Losses of On‐the‐Job Productivity</scp>
Why this work is in the frame
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Bibliographic record
Abstract
Abstract We extend the research on postinjury employment by estimating productivity losses for workers with permanent partial disabilities (PPDs) in the first three years after injury. Our method distinguishes between productivity losses attributed to spells of work absence versus reduced earnings during spells of employment. The method is applied to data for 800 Ontario workers with PPDs. The results document large productivity losses persisting at least three years after injury, with different loss patterns for workers returning to stable versus unstable employment. Human capital investments or job accommodations can reduce productivity losses, but the significant determinants of losses differ for the stable versus unstable employment groups.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it