A Content Analysis of Web-Based Heat Stress Materials Published by Occupational Health and Safety Ministries, Associations, and Agencies in Canada
Bibliographic record
Abstract
An ever-increasing number of workplaces are becoming heat-exposed due to rising temperature extremes. However, a comprehensive review of Canadian safety materials available to support workplaces in managing this critical hazard has not previously been conducted. We undertook a review and a content analysis of heat stress materials on safety-based ministry, association, and agency websites in Canada (n = 155) to identify content related to heat stress (n = 595). Each document was qualitatively analyzed using NVivo. The most dominant components identified were heat stress control measures (n = 492, 83%), training and education (n = 414, 70%), workplaces and workers at risk (n = 361, 61%), exposure limits and monitoring practices (n = 344, 58%), and emergency response and reporting (n = 249, 42%). However, the content within these programming components was highly variable. While we found that organizations across Canada provide heat stress content, there was evidence of inconsistencies and considerable gaps in the availability of material and the strategies presented to control the critical risk posed by heat.
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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 | 0.010 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.048 | 0.070 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".