Stronger together: Understanding when and why group ethical voice inhibits group abusive supervision
Bibliographic record
Abstract
Summary In this research, we integrate social impact theory (SIT) and social cognitive theory (SCT) to examine how group ethical voice, as a form of social influence, reduces group abusive supervision. Drawing on SIT, we hypothesize that the strength of this relationship is contingent on the group's power, size, and social distance from the group leader (i.e., interaction frequency). Results from data collected over two time periods from 521 employees in 98 work groups (Study 1) reveal that group ethical voice reduces group abusive supervision, controlling for general group voice and group performance. Furthermore, we found that the relationship between group ethical voice and group abusive supervision was strongest when the group is larger, powerful, and interacts frequently with the group leader. These findings are replicated in Study 2, a time‐lagged study of employees across three time periods. Study 2 also shows that the interactive effects of group ethical voice, group power, and social distance (but not group size) on abusive supervision are mediated by leader reflective moral attentiveness. Specifically, in powerful and socially proximal groups, group ethical voice reduces abusive supervision by fostering greater reflective moral attentiveness in group leaders.
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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 | 0.003 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".