Joint ICOH-WOPS & APA-PFAW global roundtable perspectives: exploring national policy approaches for psychological health at work through the ‘National Policy Index’ lens
Bibliographic record
Abstract
Worker psychological health is a significant global imperative that requires national policy action and stakeholder engagement. While national policy is a critical lever for improving worker psychological health, some countries are more progressive than others in relation to policy development and/or implementation. At the Joint Congress of the International Commission on Occupational Health, Scientific Committee on Work Organization and Psychosocial Factors and the Asia Pacific Academy for Psychosocial Factors at Work in Tokyo (September 2023), a Global Roundtable was held that to initiate international dialogue and knowledge exchange about national policy approaches for work-related psychological health. The Global Roundtable involved experts from diverse regions alongside an engaged audience of congress attendees and facilitators. Qualitative data were analysed against the five components of the National Policy Index tool comprising, policy priority, specific laws, nation-wide initiatives, sector-oriented initiatives, national survey and/or studies. Analysis revealed that while work-related psychological health is a policy priority across many countries, at the same time, there are global gaps in both legislation specificity and active regulation across different countries. For future policy development across countries, it will be beneficial to continue and deepen international discourse and for countries to share their approaches with others.
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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 | 0.048 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.023 | 0.016 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.014 | 0.013 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".