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Record W2336843782 · doi:10.1177/1077800415617207

Educating Critical Qualitative Health Researchers in the Land of the Randomized Controlled Trial

2015· article· en· W2336843782 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

VenueQualitative Inquiry · 2015
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsQualitative researchPositivismSociologyEngineering ethicsSocial sciencePublic relationsEpistemologyPolitical science

Abstract

fetched live from OpenAlex

Drawing on long experience as a sociologist in the health academy, I explore the challenges of practicing and teaching critical qualitative research in an environment dominated by very different scientific reasoning. I account for the transgressive positioning of qualitative research in the health sciences in terms of the role of social theory in interpretive research, rising interest in qualitative approaches among health professionals, research and educational doctrines that impede “value-added” analysis, and the ascendance of applied, post-positivist forms of qualitative research. Strategies for producing critical qualitative researchers who can both survive and thrive in the health arena include creation of institutional authority, prioritization of methodological depth over breadth, teaching pragmatic but non-compromising survival skills, and forging supportive communities of practice. I describe how one particular academic organization is engaging with these strategies and reflect on future prospects for educating critical qualitative researchers in the field of health.

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)0.190
metaresearch head score (Gemma)0.274
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1900.274
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.935
GPT teacher head0.809
Teacher spread0.126 · 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