Authentic Leadership: Clashes, Convergences and Coalescences
Bibliographic record
Abstract
Contents: Foreword 1. Introduction: Authentic Leadership: Clashes, Convergences and Coalescences Donna Ladkin and Chellie Spiller PART I: GROUNDINGS: HISTORIC, CRITICAL AND SUBJECTIVE PERSPECTIVES 2. Essay: Authentic Leadership and History Owain Smolovic Jones and Keith Grint 3. Essay: Authentic Leadership Critically Reviewed Mats Alvesson and Stefan Sveningsson 4. Viewpoint: The Authentic Leader Reconsidered: Integrating the Marvellous, Mundane and Mendacious Suze Wilson 5. Cameo: A Powerful Antidote: Hannah Arendt's Concept of Uniqueness and the Discourse of Authentic Leadership Rita Gardiner 6. Viewpoint: What 'Selves' is Authentic Leadership True To? A Heideggerian Contribution Dominik Heil PART II: BEING TRUE TO THE SELF: FIGMENTS, FRAGMENTS OR FACETS 7. Essay: Laboring under False Pretences? The Emotional Labor of Authentic Leadership Caroline Clarke, Clare Kelliher and Doris Schedlitzki 8. Essay: Life Stories, Personal Ambitions and Authenticity: Can Leaders be Authentic Without Pursuing the Higher Good? Galit Eilam-Shamir and Boas Shamir 9. Essay: Authentic Leadership: Demonstrating and Encouraging Three Ways of Knowing Niki Harre PART III: MARKERS: READING THE SIGNS OF AUTHENTIC LEADERSHIP 10. Essay: Followers' Assessments of a Leader's Authenticity: What Factors Affect How Others Deem a Leader to be Authentic? Dail Fields 11. Essay: Searching for Mandela: The Saint as a Sinner Who Keeps on Trying Joanne B. Ciulla 12. Essay: Authentic Leadership and the Status Trap Steven S. Taylor 13. Viewpoint: Why Authenticity is Most Critical in the Virtual Space Ghislaine Caulat PART IV: RELATIONAL SPACES: COMING INTO AUTHENTICITY THROUGH OTHERS 14. Essay: From Authenticity to Communitas: An Ecology of Leadership Ralph Bathurst and Trudie Cain 15. Cameo: Authentic Followership in the Knowledge Economy Rob Goffee and Gareth Jones 16. Viewpoint: Responsible Investment and Authentic Leadership Rodger Spiller 17. Viewpoint: Authentic and Political Leadership: Opposite Ends of the Same Continuum? B. Parker Ellen III, Ceasar Douglas, Gerald R. Ferris and Pamela L. Perrewe PART V: AUTHENTICITY AT THE INTERSECTIONS OF IDENTITY AND INSTITUTIONS 18. Essay: Can I Really be Me? The Challenges for Women Leaders Constructing Authenticity Amanda Sinclair 19. Cameo: Developing Authentic Leadership as a Racial Minority Doyin Atewologun 20. Cameo: The Challenge for Authentic Leadership in Multi-cultural Settings Lake Wang and Kim Turnbull James 21. Cameo: Authentic Canadian Aboriginal Leadership: Living by the Circle Mark Julien, Barry Wright and Deborah McPhee 22. Viewpoint: Institutional Ethics and the Spirit of Chinese Business Leaders Yi Han PART VI: DEVELOPING AUTHENTIC LEADERS 23. Cameo: Spinning Authentic Leadership Living Stories of the Self David M. Boje, Catherine A. Helmuth and Rohny Saylors 24. Viewpoint: An Authentic Jerk. Authentic Leadership Can be Bad Leadership Lauren Zander 25. Cameo: Developing Authentic, Innovative Leaders Lotto Darso 26. Essay: So You Want to be Authentic in Your Leadership: To Whom and for What End? Helen Nicholson and Brigid Carroll Index
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.019 | 0.012 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".