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Record W4392549803 · doi:10.1007/s11019-024-10198-8

Discovering clinical phronesis

2024· article· en· W4392549803 on OpenAlexafffund
J. Donald Boudreau, Hubert Wykretowicz, Elizabeth Anne Kinsella, Abraham Fuks, Michaël Saraga

Bibliographic record

VenueMedicine Health Care and Philosophy · 2024
Typearticle
Languageen
FieldMedicine
TopicClinical Reasoning and Diagnostic Skills
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersMcGill University
KeywordsPhronesisMedical lawPhilosophy of medicinePhilosophy of biologyEpistemologyPhilosophyMedicinePathologyPhilosophy of scienceAlternative medicine

Abstract

fetched live from OpenAlex

Phronesis is often described as a 'practical wisdom' adapted to the matters of everyday human life. Phronesis enables one to judge what is at stake in a situation and what means are required to bring about a good outcome. In medicine, phronesis tends to be called upon to deal with ethical issues and to offer a critique of clinical practice as a straightforward instrumental application of scientific knowledge. There is, however, a paucity of empirical studies of phronesis, including in medicine. Using a hermeneutic and phenomenological approach, this inquiry explores how phronesis is manifest in the stories of clinical practice of eleven exemplary physicians. The findings highlight five overarching themes: ethos (or character) of the physician, clinical habitus revealed in physician know-how, encountering the patient with attentiveness, modes of reasoning amidst complexity, and embodied perceptions (such as intuitions or gut feeling). The findings open a discussion about the contingent nature of clinical situations, a hermeneutic mode of clinical thinking, tacit dimensions of being and doing in clinical practice, the centrality of caring relations with patients, and the elusive quality of some aspects of practice. This study deepens understandings of the nature of phronesis within clinical settings and proposes 'Clinical phronesis' as a descriptor for its appearance and role in the daily practice of (exemplary) physicians.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.813
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.063
GPT teacher head0.444
Teacher spread0.382 · 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 designNot applicable
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

Citations14
Published2024
Admission routes2
Has abstractyes

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