Mapping a Decade of Authentic Leadership Research: A Structural Topic Modeling Approach
Bibliographic record
Abstract
Authentic leadership, characterized by self-awareness, relational transparency, and ethical behavior, has emerged as a vital construct in leadership studies, addressing the complexities of volatile business environments. However, conceptual overlap with other leadership styles and limited cross-cultural applicability pose challenges to its theoretical and practical advancement. This study employs Structural Topic Modeling (STM) to analyze 99 peer-reviewed articles published between 2013 and 2023, uncovering key thematic patterns and evolutionary trends in authentic leadership research. Our findings reveal 20 topics central to defining authentic leadership, emphasizing its core dimensions while identifying emerging elements such as emotional intelligence, adaptability, and resilience. Additionally, 15 topics trace the theoretical evolution of authentic leadership across three phases: definitional clarity (2013–2015), contextual expansion (2016–2019), and dynamic integration (2020–2023). These phases highlight its progression from a static construct to a relational and context-sensitive model, integrating cultural adaptability and ethical decision-making. This study advances the understanding of authentic leadership as a dynamic and relational process shaped by organizational and cultural contexts. By validating its foundational dimensions and identifying new components, it offers theoretical clarity and practical insights for navigating complex and diverse leadership challenges.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".