Occupational stress and the laws in selected jurisdictions
Bibliographic record
Abstract
In the contemporary modern and globalised world, it is common for the majority of employers to draw a great attention to the productivity of the workforce rather than the employees working capability and physical and mental conditions. Businesses and industries have always been striving towards maximising profit and minimising the cost. As a result, employees of uncountable organisations suffer from the alarming occupational stress in catching up with the respective schedule of productions, shipments and services. The question arises here is that whether there should be some regulatory measures to relief the occupational stress of the workforce? Accordingly, this article examines the laws relating to the occupational safety and health in selected jurisdictions, namely, Malaysia, Australia, Canada, the United Kingdom and New Zealand in order to evaluate whether these laws protect workers’ mental health. It is found that the existing legislations on occupational health and safety in the selected jurisdictions do not explicitly address on the emotional and mental health of employees. Therefore, authors propose that a specific legislation is warranted to regulate occupational stress closely and carefully in order to provide better work-life balance to the workforce.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".