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Record W2092147963 · doi:10.3109/0142159x.2012.704439

Grounded theory in medical education research: AMEE Guide No. 70

2012· article· en· W2092147963 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 Teacher · 2012
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsWestern University
Fundersnot available
KeywordsGrounded theoryPerspective (graphical)Qualitative researchConstructivist grounded theoryQuality (philosophy)Key (lock)Management scienceEpistemologyComputer scienceEngineering ethicsSociologySocial scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Qualitative research in general and the grounded theory approach in particular, have become increasingly prominent in medical education research in recent years. In this Guide, we first provide a historical perspective on the origin and evolution of grounded theory. We then outline the principles underlying the grounded theory approach and the procedures for doing a grounded theory study, illustrating these elements with real examples. Next, we address key critiques of grounded theory, which continue to shape how the method is perceived and used. Finally, pitfalls and controversies in grounded theory research are examined to provide a balanced view of both the potential and the challenges of this approach. This Guide aims to assist researchers new to grounded theory to approach their studies in a disciplined and rigorous fashion, to challenge experienced researchers to reflect on their assumptions, and to arm readers of medical education research with an approach to critically appraising the quality of grounded theory studies.

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)0.019
metaresearch head score (Gemma)0.087
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.087
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0420.002

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 head0.076
GPT teacher head0.472
Teacher spread0.396 · 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