Perceptions of workplace health: building community partnerships
Bibliographic record
Abstract
Purpose Workplace health promotion initiatives are an effective way to reach adults, and provide safe and healthy working environments that support individual health. The purpose of this project was to: learn how organizations/businesses define workplace health; assess employer support and commitment for workplace health initiatives; assess facilitators and barriers to workplace wellness/health; and understand workplace needs around evaluation and outcome measures. Design/methodology/approach A community partnership, Wellness Initiatives Network (WIN), was established to provide a forum for organizations in Atlantic Canada to share knowledge and experience on workplace health. Focus groups were conducted with businesses/organizations in the four Atlantic Provinces. Tape‐recorded transcriptions were analyzed using thematic analysis. Findings Ingredients for successful workplace health initiatives include onsite programs, the provision of incentives and recognition for employees, and the need to build awareness, understanding and commitment among managers who can help to create a supportive culture, which supports employee health. Measuring outcomes related to workplace health is critical. Practical implications Workplace health promotion should encompass a comprehensive approach that acknowledges the important roles of personal, social and environmental factors. Originality/value There is both interest and readiness to implement workplace health in Atlantic Canada. Workplace health is a responsibility of all – individual employees, employers and workplaces, and government. All stakeholders must be involved to help employees, workplaces and the health system cope with an aging population and concomitant increasing stresses at work and home. Engaging leaders is a critical step in building an integrated, comprehensive and sustainable approach to workplace health.
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.
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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".