Silence and proactivity in managing supervisor ostracism: implications for creativity
Bibliographic record
Abstract
Purpose Anchored in a social control theory framework, this study aims to investigate the mediating effect of defensive silence in the relationship between employees' perception of supervisor ostracism and their creative performance, as well as the buffering role of proactivity in this process. Design/methodology/approach The hypotheses were tested using three-wave survey data collected from employees in North American organizations. Findings The authors found that an important reason for supervisor ostracism adversely affecting employee creativity is their observance of defensive silence. This mechanism, in turn, is less prominent among employees who show agency and change-oriented behavior (i.e. proactivity). Practical implications For practitioners, this study identifies defensive silence as a key mechanism through which supervisor ostracism hinders employee creativity. Further, this process is less likely to escalate when their proactivity makes them less vulnerable to experience such social exclusion. Originality/value This study establishes a more complete understanding of the connection between supervisor ostracism and employee creativity, with particular attention to mediating mechanism of defensive silence and the moderating role of proactivity in this relationship.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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 source (direct Gemma or distilled Codex), 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".