Bibliographic record
Abstract
Purpose The purpose of this paper is to establish a critical synthesis of the dynamics of narcissistic leadership in organizations. Moreover, this paper offers suggestions for research aimed at providing greater insight into this form of leadership. Design/methodology/approach The paper comprises a review of the latest scientific research in the field of narcissistic leadership. In strictly methodological terms, this synthesis can thus be classified as a literature review. Findings The paper presents details of four factors that can trigger manifestations of narcissistic leadership: idiosyncratic, cultural, environmental and structural factors. Research limitations/implications Based on a comprehensive review of the literature, this paper proposes an analysis of the dominant characteristics and dynamics of narcissistic leadership, essentially from the point of view of a pathological narcissism of the overt (grandiose) type. It would be interesting to extend the exploration to another form of narcissistic leadership – namely, covert (vulnerable) leadership. Practical implications Through its exploration of the nature and limits of narcissistic leadership, this paper proposes avenues of research that could have interesting managerial applications. Originality/value To the author's knowledge, this is the first synthesis to propose an integrated research model that incorporates the antecedents, components and consequences of narcissistic leadership in organizations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".