Relationship between health services outcomes and social and economic outcomes in workplace injury and disease: Data sources and methods*
Bibliographic record
Abstract
BACKGROUND: Understanding the mediating role of health care in mitigating social, economic and occupational role disability is a complex task. METHODS: No single method of research will be successful in addressing all elements of this NORA research priority area. In this paper, we argue that research methods are needed which have the following components: (1) the detailed measurement of therapeutic intervention and the impacts of this intervention on clinical and functional health status using study designs which rule out competing explanations, (2) a longitudinal follow-up component which measures social, economic, and occupational role function following the conclusion of therapy, and (3) a commitment to execute studies across multiple settings to observe the variations in health care and in social and occupational role function that arise as a result of differences in labor market factors and employer and government policies. CONCLUSIONS: More comprehensive portraits of the longitudinal trajectory of individual workers, social, economic and occupational role function following an occupational injury or illness will have significance for a large number of policy sectors.
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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 | 0.062 | 0.144 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.015 | 0.025 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".