Bibliographic record
Abstract
Workplace violence against women is a widespread phenomenon affecting various service sectors across the globe. Although libraries are traditionally regarded as calm and quiet spaces, incidents of workplace violence, particularly against women have increasingly come to light. This study aims to explore the nature, causes, and preventive strategies related to workplace violence against women in library settings, both locally and globally. Using a systematic review methodology, 27 research papers were selected from diverse geographic contexts, including Sweden, the United Kingdom, Canada, the United States, India, Africa, Nigeria, and Sri Lanka. The analysis explored the different forms of violence experienced by women in libraries, identified those responsible for the incidents, highlighted the specific areas within library premises where such occurrences are most common, examined the underlying causes, and reviewed suggested strategies for prevention. The findings revealed that verbal abuse is the most prevalent form of violence in libraries, typically occurring in public areas and perpetrated by users. In contrast, incidents of physical, psychological, and sexual harassment tend to take place in more isolated parts of the library, often involving staff members or known individuals. Such acts of violence have significant consequences, leading to psychological distress among female library staff and a decrease in job satisfaction and motivation. To mitigate workplace violence, several strategies are recommended, including the installation of security systems such as CCTV cameras, the deployment of trained security personnel, and the introduction of volunteer reader programs to monitor and deter inappropriate behavior. The study underscores the urgent need for institutional policies and proactive measures to ensure the safety and well-being of women working in library environments.
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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 | 0.011 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".