What is “shared” in shared decision‐making? Philosophical perspectives, epistemic justice, and implications for health professions education
Bibliographic record
Abstract
BACKGROUND: Drawing from the philosophical work of Hans-Georg Gadamer and the perspectives of theorists Mikhail Bakhtin and Kenneth Burke, the aim of this paper is to critically reflect on the meaning of the word "shared." METHOD: The authors draw on the concept of epistemic justice, which they argue permeates the clinical encounter, to discuss how various forms of, and claims to, knowledge may influence the attainement of shared decision-making in health care contexts. The specific objectives are twofold: first, the authors draw key concepts from key Gadamerian, Burkean, and Bakhtinian philosophical perspectives to consider shared decision-making in relation to two types of epistemic injustice: testimonial and hermeneutic epistemic injustice. Second, building on philosopher Paulo Freire's critical pedagogy, the authors emphasize that major changes in educational structures and systems are required to promote the critical reflexivity required to address issues of epistemic justice, in the broader pursuit of authentic shared decision-making. RESULTS: They propose three main areas of focus for helath professions education: (a) changes in content (moving from a focus on biomedical knowledge to more content on social sciences) and methods of teaching (more dialogue and the creation of moments of dissonance); (b) a re-examination of teachers' role in promoting epistemic justice; and (c) inclusion of patients as partners. CONCLUSIONS: Without major transformation in what, how, and with whom we teach, future clinicians may be unprepared to enact shared decision-making in a manner that does justice to the various ways of knowing.
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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 | 0.082 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.016 | 0.201 |
| Scholarly communication | 0.025 | 0.029 |
| Open science | 0.004 | 0.021 |
| Research integrity | 0.009 | 0.015 |
| 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".