Leading Question: The Romance Lives On: Contemporary Issues Surrounding the Romance of Leadership
Bibliographic record
Abstract
With the passing of James R. Meindl in 2004, the leadership community lost a preeminent scholar, leader, and very dear mentor and friend.In the current paper we explore key elements of Jim"s legacy, with a particular focus on continuing research streams and ongoing questions regarding the romance of leadership.In addition, in recognition of the increased attention to follower-centered approaches to leadership that Jim helped inspire, we offer a number of challenges to leadership researchers that in our view have yet to be met.We begin by briefly reviewing Jim"s romance of leadership perspective and a selection of his seminal empirical work before exploring how the romance of leadership and his emphasis on followers and followers" perceptions has been enacted in a multitude of ways and new research streams.For example, Meindl, Ehrlich, and Dukerich"s (1985) paper alone has been cited over 160 times in other scientific articles.In addition, research streams referring to Meindl"s work have emerged in at least 11 different countries (e.g., USA, Canada, the Netherlands, Australia, Israel) and the romance of leadership perspective has been utilized across 16 different disciplines (most notably in management, psychology, and public administration).The current paper concentrates on the impact the romance of leadership approach has had on leadership research in the past 20 years, giving rise to a number of ongoing questions and challenges that remain open to future research to address.According to the romance of leadership view, people tend to overuse and glorify leadership as a causal category, due primarily to a psychological need to make sense of complex organizational phenomena.In addition, empirical research has demonstrated that this tendency is strongest for more extreme situations, such as very high or low levels of organizational performance.Meindl et al."s (1985) empirical work confirmed that people
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.018 | 0.058 |
| Scholarly communication | 0.021 | 0.021 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.015 |
| Insufficient payload (model declined to judge) | 0.006 | 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".