Organizational Perspectives on How to Successfully Integrate Health Promotion Activities into Occupational Health and Safety
Bibliographic record
Abstract
OBJECTIVE: There is increasing recognition of the value of integrating efforts to promote worker health with existing occupational health and safety activities. This paper aimed to identify facilitators, barriers and recommendations for implementing integrated worker health approaches. METHODS: Thirteen stakeholders from different job sectors participated in a workshop that targeted key issues underlying integrated worker health approaches in their own and other organizations. Included were participants from human resources, occupational health and safety, government, and unions. Thematic analysis and an online ranking exercise identified recommendation priorities and contributed to a conceptual framework. RESULTS: Participants highlighted the importance of planning phases in addition to implementation and evaluation. Themes highlighted organizational priorities, leadership buy-in, external pressures, training, program promotion and evaluation metrics. CONCLUSIONS: Findings provide practical directions for integrating worker health promotion and safety and implementation steps.
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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 | 0.052 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".