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The Collective Leadership Paradigm: Taking Stock and Moving Forward

2025· article· en· W4416005362 on OpenAlexaff
Laura Empson, Suzanne Gagnon, Sverre Spoelstra, Richard Bolden, Brigid Carroll, Ann Langley, Mary Uhl‐Bien

Bibliographic record

VenueAcademy of Management Proceedings · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEducation, Leadership, and Health Research
Canadian institutionsHEC MontréalUniversity of Manitoba
Fundersnot available
KeywordsCollective leadershipNarrativeCentralityShared leadershipPower (physics)Process (computing)Stock (firearms)Focus (optics)

Abstract

fetched live from OpenAlex

This symposium explores the evolving paradigm of collective leadership, which challenges the traditional focus on single, ‘heroic’ leaders. Grounded in relational, processual, and systemic approaches, collective leadership theorizes the centrality of collaboration, distributed agency, and shared responsibility for leadership in complex organizational contexts. Panelists will discuss five critical themes: process and complexity, objects and materiality, power and crisis, narrative and practice, and teaching and doing. These discussions aim to deepen understanding of collective leaderships theoretical foundations and practical applications, highlighting its potential to redefine leadership in diverse settings.

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 imitation

Not 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.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0080.036
Scholarly communication0.0180.034
Open science0.0030.010
Research integrity0.0090.015
Insufficient payload (model declined to judge)0.0050.002

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.

Opus teacher head0.167
GPT teacher head0.427
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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