The power of benevolence: The joint effects of contrasting leader values on follower‐focused leadership and its outcomes
Bibliographic record
Abstract
Summary The most frequent approach to studying leader attributes has been to demonstrate links between separate dispositions (e.g., traits and values) and leader behavior. Yet, both in the field of personality overall and the field of personal values in particular, there is a growing understanding that to more realistically capture the effects of personality, one needs to study the joint effects of personality dimensions, rather than their separate ones. In the present studies, we demonstrate how a combination of values predicts leaders' follower‐focused behavior and its outcomes. Specifically, we demonstrate that the combination of leaders' power and benevolence values predicts leaders' follower‐focused leadership and follower outcomes. In Study 1, the interaction between 75 school leaders' power and benevolence predicted followers' reports ( N = 293) of their leaders' follower‐focused leadership, such that the relationship between power values and follower‐focused leadership was positive and significant only among leaders high on benevolence values. We replicated this effect in Study 2 with data collected in two points in time, from 76 principals and 494 of their subordinates. We also demonstrated the indirect effect of principals' values, through their follower‐focused leadership, on teachers' satisfaction and nurturing behavior.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".