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The Effect of Professional Identity on Comprehensiveness in Strategic Decision Making: Physician Executives in the Canadian Health Care Context

2012· article· en· W2417059228 on OpenAlexaffabout
Shazia Karmali

Bibliographic record

VenueAdvances in health care management · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsUniversity of Victoria
FundersUniversity of New South Wales
KeywordsConstruct (python library)ConceptualizationSocializationContext (archaeology)Identity (music)Health careValue (mathematics)Public relationsPsychologyBusinessPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

PURPOSE: This paper explores differences in decision-making approaches between physician executives and nonphysician executives in a managerial setting. DESIGN/METHODOLOGY/APPROACH: Fredrickson and Mitchell's (1984) conceptualization of the construct of comprehensiveness in strategic decision making is the central construct of this paper. Theories of professional identity, socialization, and institutional/dominant logics are applied to illustrate their impact on strategic decision-making approaches of physician and nonphysician executives. FINDINGS: This paper proposes that high-status professionals, specifically physicians, occupying senior management roles are likely to approach decision making in a way that is consistent with their professional identity, and by extension, that departments led by physician executives are less likely to exhibit comprehensiveness in strategic decision-making processes than departments led by nonphysician executives. ORIGINALITY/VALUE: This paper provides conceptual evidence that physicians and nonphysicians approach management differently, and introduces the utility of comprehensiveness as a construct for strategic decision making in the context of health care management.

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 score0.457
Threshold uncertainty score0.995

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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.329
Teacher spread0.314 · 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

Citations3
Published2012
Admission routes2
Has abstractyes

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