In search of the pseudo-transformational leader: A person-centered approach
Bibliographic record
Abstract
Unlike truly transformational leaders who inspire and empower others to achieve a collective good, pseudo-transformational leaders (pseudo-TL) do so for their own gain. Christie et al. (2011) found preliminary support for a behavioral model proposing that pseudo-TL display the same inspirational motivation as authentic-transformational leaders (authentic-TL), but fail to display other typical transformational behaviors. In this study, we take a person-centered approach to replicate and extend Christie et al.’s (2011) research. We included leader self-interest as an attributed quality of pseudo-TL along with the transformational leadership facets. In two studies (an experimental simulation, N = 154; a survey study, N = 292), we found that while both displayed inspirational motivation, compared to authentic-TL, pseudo-TL were rated lower on intellectual stimulation, individualized consideration and idealized influence. They were perceived as more self-interested, less trustworthy, and evoked lower levels of trust. We identified five distinct profiles in Study 2, suggesting the possible need to expand the concept of pseudo-TL beyond that proposed by Christie et al. (2011).
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| 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".