Workplace Bullying as a Predictor of Organizational Commitment: Unveiling the Mediating Role of Mobbing
Bibliographic record
Abstract
The current research aimed to study the relationship between workplace bullying, mobbing and organizational commitment in employees. The study used quantitative correlational research design to examine the relationship between mobbing, workplace bullying, and organizational commitment. Non-probability purposive sampling strategy was used to recruit the sample of N = 150 from national and multinational company employees of Lahore. Workplace Bullying Scale EAPA-T, Luxembourg Workplace Mobbing Scale and TCM Employee Commitment Survey were used for data collection purpose. Pearson Product Moment Correlation Analysis was run to investigate the relationship among workplace bullying, mobbing and organizational commitment. Test of mean differences was used to identify the effect of multiple groups of a demographic variable on the dependent variable. Multiple Hierarchical Regression Analysis was used to find out the mediating role of mobbing in relationship between workplace bullying and organizational commitment. Results indicated that there was a negative correlation of workplace bullying and mobbing with organizational commitment. Workplace bullying negatively predicted organizational commitment. There was a partial mediation of mobbing between workplace bullying and organizational commitment. There were no gender differences in these three variables. This study provides an insight that organizational commitment can be increased by handling workplace bullying and mobbing.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".