Transformational Leadership and Incivility: A Multilevel and Longitudinal Test
Bibliographic record
Abstract
This research examines group-level perceptions of transformational leadership (TFL) as negative longitudinal predictors of witnessing person-related (e.g., insults/affronts) and work-related (e.g., negation/intentional work overload) acts of incivility at work. Witnessing workplace incivility was also postulated to negatively predict employee need satisfaction. Data were collected among production employees in different Canadian plants of a major manufacturing company ( N = 344) who worked for 42 different managers ( M group size = 9.76). Two waves of data collection occurred 1 year apart. Results from multilevel analyses showed that workgroups where managers were perceived to engage in more frequent TFL behaviors reported reduced levels of person- and work-related incivility 1 year later. However, group-level incivility did not predict change in group-level need satisfaction 1 year later. At the individual level, results showed that witnessing higher levels of person-related incivility than one’s colleagues predicted reduced satisfaction of the need for relatedness 1 year later. These longitudinal findings build upon previous literature by identifying TFL as a potential managerial strategy to reduce incivility in workgroups over time. They also show that mere exposure to workplace misbehavior still affects employees’ adjustment, suggesting that every effort to reduce deviance in workplaces is worthwhile.
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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 | 0.000 | 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 | 0.002 |
| 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".