The curious case of case study research
Bibliographic record
Abstract
The conceptualisation of 'good' medical education research as hypothesis testing to identify universal truths that are generalisable across contexts has been challenged. Joining this conversation, the field of health professions education research is complex and contextual and there are ways of examining and reporting locally based activities and innovations, which can be of general value. This position leads to a focus on case study research (CSR), inquiry bound in time and place that generates thick descriptions and close interpretations to reach explanations. CSR has grown in sophistication in recent years and can inform practice and advance the science of medical and health professions education. The authors evaluated the current state of the science of CSR in the medical education literature by identifying and reviewing 160 papers. Most articles presented as 'case studies' were not in fact CSR. Moreover, most articles failed to go beyond a 'we did this' account. The authors explore definitions of CSR, and they examine dominant CSR methodologists, Yin, Stake and Merriam, and their respective approaches to CSR. They then set out some of the basic tenets of CSR (case definition, methods of data collection and analysis) and consider the logics of CSR (its structures, purposes, assumptions and symbols). CSR challenges are considered next (such as emic and etic perspectives; ethical complexities; generalisability; quality; and reporting and reflexivity). The authors conclude that context is a mechanism, which needs to be understood, and rigorous CSR provides the structures and criticality to do so, opening up new areas of understanding and inquiry.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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; a candidate call from one teacher head, not a consensus.
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".