Rise and Fall of Pseudo-Transformational Leadership: Revisiting its Relevance in Leadership Theory
Bibliographic record
Abstract
Pseudo-transformational leadership, a manipulative counterpart to authentic transformational leadership, combines self-serving motives with behaviors that outwardly emulate authenticity and inspiration. Despite its potential to reveal leadership’s darker dimensions, research on pseudo-transformational leadership has stagnated, hindered by conceptual ambiguity, measurement challenges, and overlaps with constructs like authentic and ethical leadership. This paper critically explores the construct’s theoretical evolution, its marginalization within leadership studies, and its unique emphasis on deception and ethical ambiguity. We examine its limitations alongside its contributions, proposing research avenues to refine measurement capable of detecting the deception at the core of pseudo-transformational leadership and conducting longitudinal studies to assess its organizational effects. Finally, we consider whether pseudo-transformational leadership should be revitalized as an independent construct or reframed and resituated within broader leadership theories, offering lessons for the development of novel concepts in leadership theory.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.052 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".