Highlighting the Plural: Leading Amidst Romance(s)
Bibliographic record
Abstract
The current crisis makes leadership more visible and allows us to reflect on how leadership is conceived. In this essay, we consider how leadership has been represented during the first months of the COVID-19 pandemic in articles published in the business and general press. We show that, while images of heroic leadership are prevalent in this popular discourse – reminding us vividly of the romance of leadership – other elements, such as references to plural and decentred forms of leadership can be seen as also coexisting in this discourse, while not necessarily being explicitly acknowledged. Opting for a plural, relational and processual conception of leadership allows us to reveal these under-recognized elements. This leads us to propose that these elements are not specific to leadership in times of crises, but are always constitutive of leading in practice. We conclude by arguing that renewing understandings of leadership may require that we acknowledge simultaneously the inevitable presence of romance(s) in how we approach this phenomenon as well as its collective and relational accomplishment. Referring, in turn, to the central phenomenon as leading rather than as leadership may help us reach beyond the seductiveness of the romance(s) of leadership to capture its inherent relationality.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.054 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".