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Record W2283447352 · doi:10.1136/medhum-2015-010731

I and Thou: learning the ‘human’ side of medicine

2016· article· en· W2283447352 on OpenAlexaff
Atara Messinger, Benjamin Chin‐Yee

Bibliographic record

VenueMedical Humanities · 2016
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsThouPerspective (graphical)HumanismNarrativeEpistemologySociologyMedical humanitiesNarrative medicinePsychologyPhilosophyMedicineLinguisticsMedical educationComputer science

Abstract

fetched live from OpenAlex

This essay is a reflection on the doctor-patient relationship from the perspective of two medical students, which draws on the ideas of 20th-century philosopher Martin Buber. Although Buber never wrote about medicine directly, his 'philosophy of dialogue' raises fundamental questions about how human beings relate to one another, and can thus offer valuable insights into the nature of the clinical encounter. We argue that Buber's basic word pairs, 'I-You' and 'I-It', provide a useful heuristic for understanding different modes of caring for patients, which we illustrate using examples of illness narratives from two literary works: Tolstoy's Ivan Ilych and Margaret Edson's Wit Our essay demonstrates how the humanities in general and philosophy in particular can inform a more humanistic practice for healthcare trainees and practicing clinicians alike.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0080.062
Scholarly communication0.0090.010
Open science0.0010.008
Research integrity0.0050.011
Insufficient payload (model declined to judge)0.0030.001

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 head0.043
GPT teacher head0.323
Teacher spread0.280 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations8
Published2016
Admission routes1
Has abstractyes

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