Advent of occupational health services research*
Bibliographic record
Abstract
After lagging behind health services research in general health care, research is now examining health services provided to workers suffering occupational injuries and illnesses. The National Institute for Occupational Safety and Health, the Robert Wood Johnson Foundation Workers' Compensation Health Initiative, the Agency for Health Care Policy and Research (now the Agency for Healthcare Research and Quality), and the Canadian Institute for Work and Health co-sponsored a June, 1999, conference to explore research needs in this area. Fundamental tenets for advancing occupational health services research include: adopting the goal of improving occupational health care, including better integration of preventive and curative care; creating standardized interstate occupational health care data sets that include medical, economic, and patient perspectives; better defining quality in occupational care and developing appropriate performance measures; in addition to medical costs, assessing social, economic, medical and functional outcomes of care; considering the connections between work and health, including general health services; and addressing the need to train qualified occupational health services researchers. Am. J. Ind. Med. 40:291-294, 2001. Published 2001 Wiley-Liss, Inc.
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 | 0.072 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".