Discrete emotions linking abusive supervision to employee intention and behavior
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Drawing on appraisal theories of discrete emotions, we propose and test a model in which abusive supervision directed toward oneself and toward work unit peers (coworker abusive supervision) are interactively related to generalized feelings of shame, anger, and fear. These discrete emotions, in turn, tend to precipitate distinct responses that do not directly target the supervisor. We tested our hypotheses with a three‐wave, time‐lagged survey of 285 full‐time workers from 55 work units. Consistent with our theorizing, supervisory abuse was associated with stronger feelings of shame while at work when the abusive supervision reported by one's coworkers was lower (vs. higher), whereas abuse had a stronger association with anger when coworkers also perceived relatively high levels of abuse. The distinct action tendencies associated with shame and anger are related to employees engaging in less voice behavior and more interpersonal deviance, respectively, and fear is related to higher turnover intentions. We discuss the study's implications for theory development concerning abusive supervision.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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 it