Public Safety Personnel Family Resilience: A Narrative Review
Bibliographic record
Abstract
The families of public safety personnel (PSP) face demands that are unique to these occupations. Nonstandard work, trauma exposure, and dangerous work environments affect both workers and the families who support them. This narrative review aims to identify the stressors that PSP families experience and the support and resources needed to enhance family resilience. Due to a lack of research on PSP families, this review is a necessary first step to summarizing and interpreting a diverse body of research. The studies included addressed structural and emotional work-family conflict with reference to PSP sectors. A framework from the military family resiliency literature interprets the findings. Factors influencing family functioning and the availability and accessibility of resources provide clues about the type of skills and supports that PSP families rely on. Meaning-making, collaboration, a sense of coherence, and communication were identified as themes associated with intrafamilial processes. Extrafamilial themes included public perceptions, a lack of recognition for the roles families fulfill, and the need for information and education. The results suggest that the vulnerability of PSP families is variable and extrafamilial resources in the form of formal and informal supports are necessary to enhance family resiliency.
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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".