Getting away “Scott” (but not Susan) free: The effects of safety‐specific abusive supervision and supervisor gender on follower attributions and safety outcomes
Bibliographic record
Abstract
Summary While most research emphasizes the harmful effects of abusive supervision, we argue that certain contextual factors—specifically hazardous work environments and supervisor gender—may lead abusive supervision to be perceived as driven by performance promotion intentions as opposed to injury initiation intentions. We introduce the concept of Safety‐Specific Abusive Supervision (SSAS), which we define as the extent to which a supervisor's active response to safety incidents is perceived by employees as abusive. Drawing from event system theory and research on attributions of abusive supervision, we theorize that when supervisors engage in SSAS, employees are more likely to attribute their behavior to performance promotion rather than injury initiation, perceiving the supervisors' actions as a means to keep them safe rather than to cause harm. We predict that performance promotion attributions mediate the relationship between SSAS and safety performance outcomes, namely safety voice and perceived supervisor safety commitment. However, consistent with role congruity theory, we hypothesize that this relationship is only true for male supervisors and not for female supervisors. Across three studies (two experimental studies and one field study), we largely find support for our hypotheses.
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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 | 0.001 | 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) | 0.000 | 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".