MétaCan
Menu
Back to cohort
Record W4416594492 · doi:10.3390/admsci15120461

The Neurobiology of Effective Leadership: Integrating Polyvagal Theory with the Coaching Leadership Style

2025· article· en· W4416594492 on OpenAlexaff
Orla Colgate, Mark Colgate

Bibliographic record

VenueAdministrative Sciences · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsOperationalizationCoachingInterpersonal communicationMechanism (biology)Leadership styleTransactional leadershipDirectiveShared leadershipStyle (visual arts)

Abstract

fetched live from OpenAlex

The contemporary volatile business environment demands a shift from directive oversight to developmental leadership, given the complexity and rapid technological advancement characterizing modern workplaces. The Coaching Leadership Style (CLS) has emerged as a critical approach, linking extensively to enhanced employee engagement, performance, innovation, and psychological safety. However, the mechanisms by which coaching behaviors create these outcomes, especially the foundational element of safety, remain under-specified. Existing leadership research often lacks a replicable, mechanistic, and neurobiologically grounded model. This conceptual paper bridges this gap by integrating leadership science with interpersonal neurobiology. We propose Polyvagal Theory (PVT), a framework explaining the neurophysiology of safety and connection, as the missing mechanism that explains the effectiveness of CLS. We argue that the relational cues of a coaching leader (e.g., vocal prosody, attuned listening) are non-consciously detected via neuroception, shaping an employee’s autonomic state. We propose that these cues create physiological safety, which is the biological prerequisite that enables the interpersonal risk-taking and voice behaviors that constitute psychological safety. We then operationalize this synthesis by embedding PVT principles within the established 5E Coaching Model (Engage, Explore, Explain, Execute, Evaluate), offering a practical, state-aware framework for leaders. This paper contributes a testable, micro-to-macro pathway from leader autonomic co-regulation to team-level high-performance outcomes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.876
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.057
GPT teacher head0.298
Teacher spread0.241 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAdministrative SciencesSame topicJob Satisfaction and Organizational BehaviorFrench-language works237,207