Power and physician leadership
Bibliographic record
Abstract
Power and leadership are intimately related. While physician leadership is widely discussed in healthcare, power has received less attention. Formal organisational leadership by physicians is increasingly common even though the evidence for the effectiveness of physician leadership is still evolving. There is an expectation of leadership by all physicians for resource stewardship. The impact of power on interprofessional education and practice needs further study. Power also shapes the profession’s attempts to address physician and learner well-being with its implications for patient care. Unfortunately, the profession is not exempt from inappropriate use of power. These observations led the authors to explore the concept and impact of power in physician leadership. Drawing from a range of conceptualisations including structuralist (French and Raven), feminist (Allen) and poststructuralist (Foucault) conceptualisations of power, we explore how power is acquired and exercised in healthcare systems and enacted in leadership praxis by individual physician leaders (PL). Judicious use of power will benefit from consideration and application of a range of concepts including liminality, power mediation, power distance, inter-related use of power bases, intergroup and shared leadership, inclusive leadership, empowerment, transformational leadership and discourse for meaning-making. Avoiding abuse of power requires moral courage, and those who seek to become accountable leaders may benefit from adaptive reflection. Reframing ‘followers’ as ‘constituents or citizens’ is one way to interrupt discourses and narratives that reinforce traditional power imbalances. Applying these concepts can enhance creativity, cocreation and citizenship-strengthening commitment to improved healthcare. PLs can contribute greatly in this regard to further transform healthcare.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.023 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".