Does ethical climate overcome the effect of supervisor narcissism on employee creativity?
Bibliographic record
Abstract
Abstract Using the tenets of learned helplessness theory, we propose and test a model suggesting how the perception of supervisor narcissism impacts acquiescent silence and employee creativity. We further suggest acquiescent silence as a mediator, and law and code ethical climate as a moderator, in the link between supervisor narcissism and creativity. We found good support for the proposed hypotheses using multi‐wave data collected from 258 employees of service‐oriented companies in North America. Results show that supervisor narcissism prompts employees to exhibit acquiescent silence, which also mediates the link between supervisor narcissism and employee creativity. The law and code ethical climate moderates the effect of supervisor narcissism on acquiescent silence and that of silence on creativity. Therefore, this study identifies a key factor, acquiescent silence, through which supervisor narcissism impedes employee creativity, and it also reveals how this process might be buffered by the law and code ethical climate. We discuss the theoretical and practical implications of our findings.
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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 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".