Canadian Public Safety Personnel and Occupational Stressors: How PSP Interpret Stressors on Duty
Bibliographic record
Abstract
Canadian public safety personnel (e.g., correctional workers, firefighters) experience potential stressors as a function of their occupation. Occupational stressors can include organizational (e.g., job context) and operational (e.g., job content) elements. Operational stressors (e.g., exposures to potentially psychologically traumatic events) may be inevitable, but opportunities may exist to mitigate other occupational stressors for public safety personnel. Research exploring the diverse forms of stress among public safety personnel remains sparse. In our current qualitative study we provide insights into how public safety personnel interpret occupational stressors. We use a semi-grounded thematic approach to analyze what public safety personnel reported when asked to further comment on occupational stress or their work experiences in two open-ended comment fields of an online survey. We provide a more comprehensive understanding of how public safety personnel experience occupational stress and the stressors that are unique to their occupations. Beyond known operational stressors, our respondents (n = 1238; n = 828) reported substantial difficulties with organizational (interpersonal work relationship dynamics; workload distribution, resources, and administrative obligations) and operational (vigilance, work location, interacting with the public) stressors. Some operational stressors are inevitable, but other occupational stressors can be mitigated to better support our public safety personnel.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.020 | 0.009 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".