Workplace bullying as an organizational problem: Spotlight on people management practices.
Bibliographic record
Abstract
Though workplace bullying is conceptualized as an organizational problem, there remains a gap in understanding the contexts in which bullying manifests-knowledge vital for addressing bullying in practice. In three studies, we leverage the rich content contained within workplace bullying complaint records to explore this issue then, based on our discoveries, investigate people management practices linked to bullying. First, through content analysis of 342 official complaints lodged with a state health and safety regulator (over 5,500 pages), we discovered that the risk of bullying primarily arises from ineffective people management in 11 different contexts (e.g., managing underperformance, coordinating working hours, and entitlements). Next, we developed a behaviorally anchored rating scale to measure people management practices within a refined set of nine risk contexts. Effective and ineffective behavioral indicators were identified through content analysis of the complaints data and data from 44 critical incident interviews with subject matter experts; indicators were then sorted and rated by two independent samples to form a risk audit tool. Finally, data from a multilevel multisource study of 145 clinical healthcare staff nested in 25 hospital wards showed that the effectiveness of people management practices predicts concurrent exposure to workplace bullying at individual level beyond established organizational antecedents, and at the team level beyond leading indicator psychosocial safety climate. Overall, our findings highlight where the greatest risk of bullying lies within organizational systems and identifies effective ways of managing people within those contexts to reduce the risk, opening new avenues for bullying intervention research and practice. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".