Abusive Supervision and Retaliation: A Self-Control Framework
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There are conflicting perspectives on whether subordinates will or will not aggress against an abusive supervisor. To address this paradox we develop a self-control model of retaliatory behavior, wherein subordinates' self-control capacity and motivation to self-control influence emotional and retaliatory reactions to provocations by enabling individuals to override their hostile impulses. In Study 1, we demonstrate that self-control capacity, motivation to self-control (supervisor coercive power), and abusive supervision interact in such a way that the strongest association between abusive supervision and supervisor-directed aggression occurs when subordinates are low in self-control capacity and perceive their supervisor to be low in coercive power. In Study 2, we extend this finding, testing a moderated mediation model, wherein hostility toward a supervisor represents the hostile impulse resulting in retaliatory behavior, mediating the relation between abusive supervision and supervisor-directed aggression. Results from Study 2 indicate that self-control capacity allows individuals to regulate the hostile feelings experienced following abusive supervision, while self-control capacity and supervisor coercive power jointly moderate the tendency to act on one's hostile feelings toward an abusive supervisor. We discuss implications for retaliatory behaviors at work.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.002 |
| 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 it