Work-related health and safety issues must be paid for by employers, not the public
Bibliographic record
Abstract
Workplace health should be a priority for everyone. For employees, maintaining health and well-being at work is essential because we spend so much of our lives working. For employers, worker health is an important determinant of productivity. According to the Canadian Human Resources Professionals Association, the cost to Canadian businesses caused by absenteeism (absence from work due to sickness) and presenteeism (attending work despite being ill) is about $16.6 billion annually. Workplace health initiatives can play an important role in promoting healthy employee lifestyles. These initiatives can reduce absenteeism and health-care costs by more than 25 per cent. If an organization benefits from having a healthy workforce, then investing in the health of workers makes economic sense. However, not all organizations follow this approach. Some large corporations have been criticized for their health practices with Amazon having been accused of replacing burned-out employees with new ones to ensure a continuous supply of healthy employees.
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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.045 | 0.017 |
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".