Exploring sexual harassment in a police department in Taiwan
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 The purpose of this paper is to investigate the conceptual and empirical issues related to sexual harassment (SH) in a police department in Taiwan. Design/methodology/approach Survey data were collected. Through the analysis, the paper proposes that SH can be better divided into two subcategories: quid pro quo and hostile work environment harassment. Multivariate analysis is used to explore the sources of SH. Findings It was found that both types of SH can be better explained by work environment variables than by demographic variables, but the specific sources differ. Hostile work environment harassment is predicted by the extent to which female officers perceive or experience that deployment and transfer practices are influenced by their gender. Quid pro quo harassment is related to job barriers and dodging from work. Research limitations/implications The two scales used in this research have captured the core of SH, but they might not fully depict the nature of SH in the police department in Taiwan. The sample was limited to the largest police department in Taiwan and it may not represent the entire police in Taiwan. Practical implications If hostile work environment and quid pro quo harassments are related to different organizational factors, it is useful for policy makers in the police to differentiate these two different types of SH and develop differential prevention and response measures. Originality/value This paper highlights the need to differentiate quid pro quo and hostile work environment harassments. It fills a gap in the literature by providing the baseline information on the prevalence of SH in one police department in Taiwan and by examining sources of SH in a profession dominated by males.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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