Gender Insights on Team-Oriented Leadership: Findings from the GLOBE Project
Bibliographic record
Abstract
This study examines gender differences in Team-Oriented Leadership (TOL) attributes, utilizing the Global Leadership and Organizational Behavior Effectiveness (GLOBE) framework. With a focus on five subdimensions Collaborative Orientation, Team Integrator, Diplomatic, Malevolent (reversed), and Administrative Competence the research investigates whether female managers exhibit stronger alignment with TOL attributes compared to male managers. A quantitative, non-experimental, causal-comparative design was employed, using data from 287 U.S.-based managers across various industries. The results revealed that women scored significantly higher in the Collaborative Orientation and Team Integrator subdimensions, reinforcing the "feminine leadership advantage" and their aptitude for fostering team cohesion and shared purpose. While no gender differences were found in the Diplomatic or Administrative Competence subdimensions, the universal disfavor of malevolent traits was observed. Limitations include the exclusive use of U.S. GLOBE data, which may skew findings toward American cultural norms. This study contributes to the growing body of literature on gender and leadership by highlighting the value of inclusive and collaborative leadership styles and providing actionable insights for leadership development programs and organizational practices.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".