Outshined by Creative Stars: A Dual-Pathway Model of Leader Reactions to Employees’ Reputation for Creativity
Bibliographic record
Abstract
Establishing a reputation for creativity can endow employees with considerable social advantages as others look to them as a source of assistance, inspiration, and guidance. Yet, as leaders often expect access to certain privileges and advantages based on their hierarchical positions, such employees may signal a discrepancy with leaders’ own expected superiority. Drawing from the social functional view of emotions, we provide a novel extension to the creativity literature by developing and testing a dual-path model of leaders’ emotional and behavioral reactions to their employees’ reputation for creativity. Results from a survey study of 257 leader–employee dyads at a large Chinese automobile company supported our predictions that the presence of an employee reputed for their creativity fostered leaders’ feelings of envy and motivated corresponding remedial actions. Specifically, we found that, conditional on leaders’ beliefs in their own ability to be creative (i.e., creative self-efficacy), employee reputation for creativity either triggered leaders’ dysfunctional resistance toward the employee via leaders’ malicious envy, or led to leaders’ creativity help-seeking from the employee via leaders’ benign envy. We discuss how our results contribute to the extant literature.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".