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Record W2547593052 · doi:10.1111/medu.13136

Narrative inquiry: a relational research methodology for medical education

2016· article· en· W2547593052 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMedical Education · 2016
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNarrativeNarrative inquiryScholarshipContext (archaeology)Narrative criticismIdentity (music)PedagogySociologyPsychologyMedical educationMedicinePolitical scienceAestheticsLinguistics

Abstract

fetched live from OpenAlex

CONTEXT: Narrative research, an inclusive term for a range of methodologies, has rapidly become part of medical education scholarship. CONCEPTS: In this paper we identify narrative inquiry as a particular theoretical and methodological framework within narrative research and outline its characteristics. We briefly summarise how narrative research has been used in studying medical learners' identity making in medical education. USES OF NARRATIVE INQUIRY: We then turn to the uses of narrative inquiry in studying medical learners' professional identity making. With the turn to narrative inquiry, the shift is to thinking with stories instead of about stories. CONCLUSIONS: We highlight four challenges in engaging in narrative inquiry in medical education and point toward promising future research and practice possibilities.

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.

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)0.008
metaresearch head score (Gemma)0.143
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.143
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.250
GPT teacher head0.554
Teacher spread0.304 · 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