A systematic literature review of the effectiveness of occupational health and safety regulatory enforcement
Bibliographic record
Abstract
BACKGROUND: We aimed to determine the strength of evidence on the effectiveness of legislative and regulatory policy levers in creating incentives for organizations to improve occupational health and safety processes and outcomes. METHODS: A systematic review was undertaken to assess the strength of evidence on the effectiveness of specific policy levers using a "best-evidence" synthesis approach. RESULTS: A structured literature search identified 11,947 citations from 13 peer-reviewed literature databases. Forty-three studies were retained for synthesis. Strong evidence was identified for three out of nine clusters. CONCLUSIONS: There is strong evidence that several OHS policy levers are effective in terms of reducing injuries and/or increasing compliance with legislation. This study adds to the evidence on OHS regulatory effectiveness from an earlier review. In addition to new evidence supporting previous study findings, it included new categories of evidence-compliance as an outcome, nature of enforcement, awareness campaigns, and smoke-free workplace legislation. Am. J. Ind. Med. 59:919-933, 2016. © 2016 Wiley Periodicals, Inc.
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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 | 0.026 | 0.114 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.019 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".