Exploring the effects of PSP careers on families
Bibliographic record
Abstract
Public safety personnel (PSP), as a nature of their jobs, are exposed to occupational stressors, including operational factors (i.e., potentially psychologically traumatic events) and organizational factors (i.e., shift work). There is increasing knowledge of how these occupational stressors affect the health and well-being of the PSP; however, there is less known about how these can affect family relationships as well as the health and well-being of family members. The current chapter explores family-related challenges from the perspectives of PSPs from a range of professions within a Canadian context. Responses to an open-ended question from a national survey of PSP were analyzed, resulting in two main themes: (1) the effects of organizational occupational stressors on PSP families and (2) the effects of operational occupational stressors on PSP families. The themes highlight the impact of occupational stressors on PSP family relationships as well as their families as a whole. The available results further support systems theories that acknowledge the bidirectionality within families, creating a mechanism enabling work–family conflict and spillover to manifest. The current chapter provides an important next step to inform future work to better understand the experiences and the consequences of PSP careers on the health and well-being of PSP and their families in Canada.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".