What Determines Efficacy? The Roles of Codes and Guidance Materials in Occupational Safety and Health Regulation
Bibliographic record
Abstract
Codes of practice and guidance material fulfil important roles, especially (but not exclusively) under the occupational safety and health regimes of countries that have adopted the ‘Robens model’ of legislation, such as Australia, New Zealand and the UK. In these countries, codes provide greater certainty about what constitutes compliance, while guidance material provides broader advice. Despite the centrality of these mechanisms to the success of occupational safety and health regulation, they have been subjected to very little empirical scrutiny. The principal aim of this paper is to review the key characteristics that determine the efficacy of occupational safety and health codes of practice and guidance materials and, in so doing, to fill some gaps in the knowledge base about them. The empirical component was drawn from interviews and questionnaires in Australia, Canada (in particular British Columbia), Denmark, Finland, the Netherlands, New Zealand and the UK.
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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 | 0.145 | 0.368 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.031 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".