Systematic review of the prevention incentives of insurance and regulatory mechanisms for occupational health and safety
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to determine the strength of evidence on the effectiveness of two policy levers-the experience rating of workers' compensation insurance and the enforcement of occupational health and safety regulation-in creating incentives for firms to focus on health and safety issues. METHODS: An extensive systematic literature review was undertaken in an effort to capture both published and grey literature studies on the topic. Studies that met specific subject-matter and methods criteria underwent a quality assessment. A qualitative approach to evidence synthesis, known as "best-evidence" synthesis, was used. This method ranks the strength of evidence on a particular topic on the basis of the number, quality, and consistency of studies on the topic. RESULTS: There was moderate evidence that the degree of experience rating reduces injuries, limited to mixed evidence that inspections offer general and specific deterrence and that citations and penalties aid general deterrence, and strong evidence that actual citations and penalties reduce injuries. CONCLUSIONS: Although experience rating is a key policy lever of those providing workers' compensation insurance, there is much to be learned about its merits. Few studies have concerned the topic, and most have used crude proxy measures or exploited natural experiments. There have been many more studies on the merits of regulation enforcement, even though here too measures were often crude. Nonetheless, this synthesis indicates that general deterrence is less effective in reducing injury incidence and severity, whereas specific deterrence with regard to citations and penalties does indeed have an impact.
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.
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 | 0.013 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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