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Record W2761399101 · doi:10.1097/acm.0000000000001957

Beyond “Dr. Feel-Good”: A Role for the Humanities in Medical Education

2017· article· en· W2761399101 on OpenAlexaff
Arno K. Kumagai

Bibliographic record

VenueAcademic Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsThe Wilson CentreWomen's College Hospital
Fundersnot available
KeywordsMedical humanitiesThe artsExcellenceCompassionWitnessHumanitiesCurriculumPsychologyAestheticsPedagogySociologyMedical educationMedicineEpistemologyPolitical scienceArtVisual artsPhilosophyLaw

Abstract

fetched live from OpenAlex

Although educators embrace the values that are nominally included in the idea of "the art and science of medicine," the arts and humanities have remained at the edges of medical education. One reason for this exile is the overwhelming emphasis in the curriculum on biomedical science over the social sciences and humanities. Other causes are self-inflicted-a frequent lack of theoretical rigor in the design of educational offerings and, more important, no clear answer to the question of how the humanities can make better physicians. A common justification for including the arts and humanities in medical education-that spending time with literature, music, and the visual arts contributes to student and faculty reflection and well-being-is compelling; however, it risks further marginalizing the field as a soft, feel-good supplement to training.In this Invited Commentary, the author proposes several unique ways in which the arts and humanities contribute to the development of physicians who practice with excellence, compassion, and justice.These ways include disrupting taken-for-granted beliefs and assumptions; introducing a pause in perceiving, thinking, and acting; encouraging engagement with complexity and ambiguity; seeing past the surface to historical and societal influences and causes; and encouraging an awareness of the multiple, unique voices and perspectives of patients. Ultimately, the humanities prompt awareness of the space in which physicians care for human beings in their moments of greatest need and bear witness to fundamental changes in their patients and in themselves.

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)0.002
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.395
Teacher spread0.348 · 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.

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

Citations55
Published2017
Admission routes1
Has abstractyes

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