The Level of Workplace Bullying and Its Impact on Employee Loyalty: Applied Study on the Members of the Nursing Staff at Menoufia University Hospitals
Bibliographic record
Abstract
The aim of this study is to conduct an examination of how workplace bullying affects employee loyalty. The focus of the study was technical and specialist nurses employed in Egypt’s Menoufia University. The study's data was collected from 240 participants. The results from the study show that the sub-dimensions of workplace bullying and correlations with employee loyalty are moderate in the negative direction. On the other hand, it has also been concluded that the perceptions of workplace bullying sub-dimensions explain 23.8 percent of the aggregate variance in employee loyalty. The analysis of the teats results of regression coefficient regression model is conducted, it can be noted that as the levels of workplace bullying increase in the workplace, the perception of employee loyalty statistics decreases. When it comes to comparative importance predictor variables on the levels of employee loyalty shows that the leading factor is attacks on health, the second is attacks on self-expression, the third is attacks on social relations, and the last is attacks on reputation. In the study, the insignificance sub-dimension, which has the least average is the attack on the quality of professional and personal life. From the results, it can be concluded that the nursing staff at Menoufia University Hospital’s perception of their loyalty variable is at the level of medium.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".