You have to be joking: Are communities loosing respect for health and safety policy, programs and systems?
Bibliographic record
Abstract
OHS management systems and professionals have done much to ensure the health and safety of workers and societies in general. However, where these systems have become complex, overbearing and authoritarian, they have stifled workers and the community’s ability to respond to unique or unanticipated occurrences of occupational and general risk. This predicament is exacerbated when the general public lose faith in an OHS culture that has “gone mad”, or become “out of control”, and where “open season” has been declared by the media on safety regulators, their systems and regulations. This may be a perceived rather than actual truth, however, perceptions drive personal attitudes and responses, and the reputation and effectiveness of OHS is at stake. Driving some contemporary attitudes towards OHS is a barrage of lampoon, satire and angry comment pervade by mischief-makers, the press and the electronic media. The profession has also looked into the mirror and revealed areas of self-doubt. This paper looks at an unfolding and worrying scenario for occupational 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 | 0.015 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.031 |
| Scholarly communication | 0.015 | 0.019 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.008 | 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".