Gender differences in policing: signs of progress?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose This exploratory study aims to compare job demands, work outcomes, social and coping resources and indicators of psychological and physical health of male and female police officers in Norway. Design/methodology/approach Data were collected using anonymously completed questionnaires. Findings Many demographic differences were present in that male officers were older, worked more hours and overtime hours, were more likely to work continuous shiftwork, worked in smaller forces and were less educated. Few differences were found on job demands but male officers experienced more violence and threat, and female officers more harassment and discrimination. The two groups were generally similar on work satisfactions, social and coping resources and psychological and physical health. Research limitations/implications All data were collected using questionnaires raising the possibility of common method variance. It is also not clear extent to what these findings generalize to police officers in other countries. Practical implications While few differences were found between male and female police officers, the fact that females reported more harassment and discrimination suggests that police forces need to continue to address these gender issues. Originality/value While other studies of police officers have suggested widespread gender differences, few appeared here.
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.
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) | 0.001 | 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 it