Bibliographic record
Abstract
In Part 1 of this article, the legal and scientific origins of the concept of psychological safety are examined as background to, and support for, the new Canadian National Standard on Psychological Health and Safety in the Workplace (CSA Z1003/BNQ 9700). It is shown that five factors influencing psychological safety can be identified as being common to both legal and scientific perspectives: job demands and requirements of effort, job control or influence, reward, fairness, and support. This convergence of evidence from legal and scientific perspectives creates a powerful case for the development of a national standard built around these five factors. In Part 2, it is proposed that the introduction of a national standard can be expected in the long run to have positive social benefits since the health or harm that is generated in the workplace does not remain there but migrates into families, communities, and society at large in the form of either social capital or social exhaust. Consequently, psychological safety is a concept that connects the dynamics of the workplace to the health, resilience, and well-being of society at large.
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 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.010 | 0.085 |
| Scholarly communication | 0.016 | 0.016 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.010 | 0.023 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".