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Record W2012579539 · doi:10.1002/jls.20120

The anatomy of interprofessional leadership: An investigation of leadership behaviors in team‐based health care

2009· article· en· W2012579539 on OpenAlexaff
June Anonson, Linda Ferguson, Mary B. MacDonald, B. Lee Murray, Susan Fowler‐Kerry, Jill Bally

Bibliographic record

VenueJournal of Leadership Studies · 2009
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsHealth careTeamworkPsychologyContext (archaeology)Interprofessional educationMedical educationShared leadershipLeadership developmentNursingMedicineLeadership stylePublic relationsManagementPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

Abstract Increasing specialization among health care professions has heightened the need for proficient interprofessional teamwork. Within the team context for practice, leadership becomes a competency expected of all practitioners who must recognize the necessity of situational leadership dependent on patient needs and the professional competencies to meet those needs. Although this need for leadership within interprofessional practice is recognized, the behavioral components of that leadership competency have not been delineated. In this article, the authors report on a study to identify the behavioral components of interprofessional practice and highlight the indicators of leadership competency in interprofessional patient‐centered care. This qualitative study involved in‐depth interviews with 24 participants from nine professions engaged in collaborative team care of clients or patients in a variety of community and acute‐based health care facilities. Interprofessional competencies were explored using grounded theory, with coding of participants' responses. In this article, the authors have highlighted leadership in interprofessional practice, and discussed the behavioral indicators of leadership that could be used in preparation of students, faculty, and practitioners for interprofessional practice, as well as in evaluation of that practice for purposes of professional growth.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.243
GPT teacher head0.507
Teacher spread0.264 · 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 designQualitative
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

Citations21
Published2009
Admission routes1
Has abstractyes

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