Educating Critical Qualitative Health Researchers in the Land of the Randomized Controlled Trial
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.561 | 0.614 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.009 | 0.044 |
| Scholarly communication | 0.019 | 0.019 |
| Open science | 0.006 | 0.015 |
| Research integrity | 0.012 | 0.025 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".