The status of women police officers: An \ninternational review
Bibliographic record
Abstract
This paper reports on a survey of English-language police department websites, annual reports and \nother reports in order to identify key aspects of the status of women police internationally. Findings are \nreported for England and Wales, Scotland, Northern Ireland, Eire, the United States, Canada, Australia \n(eight departments), New Zealand, South Africa, Ghana, Nigeria, India, Pakistan, Hong Kong, Papua New \nGuinea, and Fiji. Data on the proportion of female officers were available from 18 of 23 locations, with a \nrange between 5.1% and 28.8%. Recruit numbers were available for six locations, and ranged between \n26.6% and 37.0%. Limited data on rank and deployment indicated overall improvements. Available \nlonger-term trend data suggested that growth in female officers was slowing or levelling out. Overall, the \nstudy showed an urgent need to improve gender-based statistics in order to better inform strategies aimed \nat maximising the participation of women in policing. \n� 2013 Elsevier Ltd. All rights reserved. \nKeywords: Women police; Female police; Gender equity; Equal employment opportunity; Affirm
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 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 | 0.001 | 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) | 0.005 | 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 teacher head, 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".