An exploratory survey assessing the determinants of heat stress and heat strain in the Canadian mining industry from the worker’s perspective
Bibliographic record
Abstract
With mines extending deeper and rising surface temperatures, workers are exposed to hotter environments. This study aimed to characterize heat stress and strain in the Canadian mining industry and evaluate the utility of the Heat Strain Score Index (HSSI), combined with additional self-reported adverse health outcomes. An exploratory web-based survey was conducted among workers (n = 119) in the Canadian mining industry. The survey included 74 questions on workers’ risk perception, strategies for heat stress management, and the HSSI—a validated tool to classify workplace heat stress based on various workplace factors and indicators of heat strain. Most workers reported that heat stress is an occupational hazard associated with their duties and tasks (89%). Based on the HSSI, 22% of respondents were classified as high risk, 42% at moderate risk, and 36% at low risk for heat stress and heat strain. Those with higher HSSI scores self-reported more heat-related adverse signs and symptoms with a higher prevalence of self-reported heat-related illness (p < 0.01). Despite workers reporting various self-initiated practices (e.g., drinking water) and management-enforced heat mitigation practices (e.g., rest breaks), many workers reported still having experienced signs or symptoms of heat stress (86%) and heat-related illnesses (37%). The study found elevated heat stress and strain levels among a sample of workers in the Canadian mining industry despite workers employing various heat-mitigating strategies. Heat stress management programs considering mining-specific factors and challenges are needed to safeguard worker health and safety.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".