The Effect of Professional Identity on Comprehensiveness in Strategic Decision Making: Physician Executives in the Canadian Health Care Context
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".