Stress experiences of women in policing: A scoping review
Bibliographic record
Abstract
Policewomen can be significantly impacted by stress, resulting in mental health challenges. Although numerous studies have explored experiences among women in policing, few have focused on the stress that can accompany these experiences and their impacts. We conducted a scoping review of stress among policewomen to explore and summarize the current breadth of research in this area and identify potential knowledge gaps and opportunities for further study. Ten databases were searched to identify relevant literature. Manual searches of reference lists and book chapters were also completed. Twenty-five peer-reviewed articles, one book chapter, one thesis, and one dissertation were included in the current review. An inductive thematic analysis was completed, and six categories relating to policewomen's workplace stress experiences and their impacts were identified. The categories included gendered institutions, gender identity and gendered roles in policing, sexual harassment and discriminatory experiences, organizational relationships between gender, career progression and promotion, policewomen and parenting, organizational change, and stressors and associated health effects for women police officers. Although the experiences were thoroughly described, their connection to stress and the effects on mental health were not. Robust research into the overall impacts of workplace stress on policewomen's mental health is needed, including exploring generative mechanisms capable of producing the stress experiences and resulting mental health challenges to develop appropriate policies, practices, and interventions.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".