The Impact of Supervisor Gender on Employee Creativity and the Mediating Role of Interaction Frequency
Bibliographic record
Abstract
While it is well established that leader characteristics influence employee outcomes, little is known about whether and how leader gender influences employee creativity. Traditionally, female leaders are considered a mismatch for prototypical leadership roles, resulting in less optimal employee outcomes than male leaders. In this paper, drawing on social role and leader-member exchange theories, we argue that female supervisors may have advantages over male supervisors and may serve as a catalyst to encourage employee creativity. In the empirical analyses, we test our hypotheses using data from German, Japanese, and South Korean foreignsubsidiaries in China. Results confirm our hypotheses and contribute to creativity and innovation literature by demonstrating that female supervisors positively influence employee creativity, challenging traditional gender role stereotypes in leadership. Additionally, it highlights the mediating role of supervisor-employee interaction frequency in enhancing creative outcomes, providing important insights for organizational practices and leadership development.
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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 | 0.001 | 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 | 0.001 |
| 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".