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Record W4293078333 · doi:10.5744/rhm.2022.50015

The Politics of Standardized Patienthood

2022· article· en· W4293078333 on OpenAlexaff
Sara V. Press

Bibliographic record

VenueRhetoric of Health & Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIndigenousRhetorical questionTRACE (psycholinguistics)PoliticsRepresentation (politics)Health carePersonality psychologyReciprocalPsychologyMedicinePedagogySociologyMedical educationPolitical scienceLinguisticsSocial psychologyLaw

Abstract

fetched live from OpenAlex

Abstract: Standardized Patient Programs (SPPs) enlist actors to roleplay the symptoms of various diseases and disorders, and to embody a range of personalities. These simulations are used to help improve the communicative practices and professional competencies of future healthcare workers. Focusing on the use of these programs for medical students and doctors, this article establishes a kairology of the SPP to better understand the shifting terrains of patient representation. A kairological account focuses on “historical moments as rhetorical opportunities” (Segal, 2005, p. 23) and, in the case of medicine, illustrates how “changes in [medical] practice are importantly reciprocal with changes in the terms of practice” (Segal, 2005, p. 22). I trace the SPP through various linguistic iterations to reveal how the shifting language of simulated patienthood reflects different orientations towards medical pedagogy and patient populations at significant junctures in time. I conclude my kairology with an examination of the Indigenous Simulated Patient Program, a 2011 pilot program that has the potential to better represent and serve Indigenous peoples in medical pedagogy and practice.

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)0.001
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: Empirical
Teacher disagreement score0.527
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.028
GPT teacher head0.359
Teacher spread0.331 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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