The value of leaders we trust and leaders who make us stronger: Exploring the distinct contributions of different components of identity leadership to group member outcomes
Bibliographic record
Abstract
This study investigates the critical role of social identity in leadership, specifically examining identity leadership (IL) and the unique contributions of its four subdimensions: identity prototypicality, identity advancement, identity entrepreneurship, and identity impresarioship. To date, research has largely focused on the global construct of identity leadership and shown that in organizational contexts, it is a predictor of a range of outcomes, including group members’ burnout and organizational citizenship. However, the distinct roles of the four subdimensions remain little understood. Extending earlier findings, we address this gap by testing the hypothesis that the four subdimensions are differentially implicated in two key mechanisms that underlie the relationship between IL and group outcomes: (a) trust in the leader and (b) team identification. The present study explores this proposition by using structural equation modeling with latent factors to test a mediation model in 2020–2021 data from the Global Identity Leadership Development project (GILD; N = 7,855). As hypothesized, we found that identity prototypicality and identity advancement predominantly predicted greater trust in the leader, whereas identity entrepreneurship primarily predicted greater team identification. Contrary to our hypothesis, identity impresarioship showed a negative relation with trust. In turn, both trust in the leader and team identification were positively associated with organizational citizenship behavior (OCB), and negatively with burnout. We conclude by reflecting on the implications of these findings for both the theory and practice of leadership.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| 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".