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Record W2784467676 · doi:10.26443/ijwpc.v5i2.179

Mindful Leadership in Interprofessional Teams

2018· article· en· W2784467676 on OpenAlexaffvenue
K De’Bell, Roberta Clark

Bibliographic record

VenueInternational Journal of Whole Person Care · 2018
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsUniversity of New BrunswickSt. Francis Xavier University
Fundersnot available
KeywordsShared leadershipPsychologyCollaborative leadershipLeadership studiesTransactional leadershipTeam leaderNeuroleadershipProcess (computing)LeadershipAppreciative inquiryLeadership stylePublic relationsKnowledge managementManagementPolitical scienceComputer scienceSocial psychologyPedagogy

Abstract

fetched live from OpenAlex

In interprofessional health teams the need for coordinating leadership and the (dynamical) need for appropriate clinical expertise to come to the fore involves a tension between the traditional role of the team leader as authority figure and the collaborative leadership which enables individual team members to emerge as leaders in their area of expertise and to relinquish this leadership as needed. Complexity analysis points to an understanding of leadership as an emergent property of the team. We discuss how a framework of mindful leadership addresses the implications of this emergent leadership model, and how Appreciative Inquiry provides a structured process for examination of team vision, values and behaviour standards.

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)0.009
metaresearch head score (Gemma)0.019
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0070.017
Scholarly communication0.0060.005
Open science0.0010.013
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.068
GPT teacher head0.361
Teacher spread0.293 · 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
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
Published2018
Admission routes2
Has abstractyes

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