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Record W4220824417 · doi:10.33423/jabe.v24i1.5044

Exploratory Study of Polyvagal Theory and Underlying Stress and Trauma That Influence Major Leadership Approaches

2022· article· en· W4220824417 on OpenAlexvenueno aff

Bibliographic record

VenueJournal of Applied Business and Economics · 2022
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsTransformational leadershipTransactional leadershipServant leadershipPsychologyLeadership studiesCognitionExploratory researchManagement scienceLeadership styleSocial psychologySociologySocial scienceEconomicsNeuroscience

Abstract

fetched live from OpenAlex

Leadership approaches have evolved to incorporate rational and non-rational processes. Traditional leadership research focused on internal and external organizational influences, but this paper underscores the need for adopting modern-day approaches for investigating leadership outcomes. Neuroscience can illuminate different cognitive effects that influence leadership. The research paper highlights the importance of attitudes towards leadership due to the complexity of modern organizational influences. The main forces highlighted are polyvagal theory, underlying stress, and trauma. A literature review provides a description of the fundamental neural and cognitive drivers of leadership. The paper also explains the findings of research studies demonstrating the correlation between neurocognitive processes and three leadership approaches: transactional, transformational and servant leadership. The discussion section elaborates these findings to determine whether insights can be applied in typical organizational settings. Lastly, the conclusion section summarizes the main deductions and explains limitations and recommendations for future exploratory investigations on rational and non-rational leadership choices. Overall, the paper attempts to justify why non-rational drivers carry equal weight as the rational influences.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.211
GPT teacher head0.297
Teacher spread0.086 · 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 designObservational
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

Citations2
Published2022
Admission routes1
Has abstractyes

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