Does power distance exacerbate or mitigate the effects of abusive supervision? It depends on the outcome.
Bibliographic record
Abstract
We predicted that the effects of abusive supervision are likely to be moderated by subordinate power distance orientation and that the nature of the moderating effect will depend on the outcome. Drawing upon work suggesting that high power distance orientation subordinates are more tolerant of supervisory mistreatment, we posited that high power distance orientation subordinates would be less likely to view abusive supervision as interpersonally unfair. Drawing upon social learning theory suggestions that high power distance orientation subordinates are more likely to view supervisors as role models, we posited that high power distance orientation subordinates would be more likely to pattern their own interpersonally deviant behavior after that of abusive supervisors. Across 3 samples we found support for our predicted interactions, culminating in a mediated moderation model demonstrating that social learning mediates the interaction of abusive supervision and power distance on subordinate interpersonal deviance, while ruling out alternate self-regulation impairment or displaced aggression explanations. Implications for the abusive supervision literature are discussed.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".