When the abuse is unevenly distributed: The effects of abusive supervision variability on work attitudes and behaviors
Bibliographic record
Abstract
Summary The present study examined the consequences of a dispersion‐based conceptualization of unit‐level abusive supervision or abusive supervision variability. Abusive supervision variability was proposed to negatively affect a number of employee attitudes and behaviors through the mediating effects of interpersonal justice climate strength. The results revealed significant cross‐level effects such that abusive supervision variability was negatively related to individual perceptions of leader ethicality, organizational ethicality, leader satisfaction, and affective organizational commitment. These effects remained robust after controlling for individual‐level abusive supervision. Abusive supervision variability was also positively related to the frequency with which unit members as a whole engaged in counterproductive work behaviors. Last, the results revealed partial support for the mediating effects of interpersonal justice climate strength. In sum, the findings highlight the importance of examining abusive supervision at both the individual and unit levels of analyses. Copyright © 2012 John Wiley & Sons, Ltd.
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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 | 0.001 | 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 | 0.000 | 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) | 0.001 | 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 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".