Predictors of Reporting Workplace Violence to an Employer According to Sex: A Cross-Sectional Study
Bibliographic record
Abstract
Reporting workplace violence to the employer is essential in order to take the necessary measures to help workers face the consequences of violence and to prevent future situations of violence. Nevertheless, there is a lack of knowledge regarding predictors of reporting workplace violence according to sex. This study aims to assess sex differences in reporting workplace violence to the employer and in predictors of reporting among a sample of 900 workers who were victims of serious workplace violence in the province of Quebec (Canada). Sociodemographic characteristics, history of victimization, perpetrator's characteristics, psychological consequences, and attitudes toward violence and reporting were considered. Results indicated that, although men were more often victims of serious violence (p = .0001), women reported more violence to their employer (p = .009). Being a victim of physical violence was positively associated with reporting, whereas being attacked by a coworker was negatively associated with reporting for both sexes. Certain predictors were specific to men (R2 = .194, p < .0001), with lower income and normalization of violence being negatively associated with reporting. Specifically for women (R2 = .308, p < .0001), being a victim of verbal violence was negatively associated with reporting, whereas working in the healthcare sector was positively associated with reporting. Results are discussed and specific recommendations are made.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 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".