Making sense of grounded theory in medical education
Bibliographic record
Abstract
BACKGROUND: Grounded theory is a research methodology designed to develop, through collection and analysis of data that is primarily (but not exclusively) qualitative, a well-integrated set of concepts that provide a theoretical explanation of a social phenomenon. OBJECTIVE: This paper aims to provide an introduction to key features of grounded theory methodology within the context of medical education research. OVERVIEW: In this paper we include a discussion of the origins of grounded theory, a description of key methodological processes, a comment on pitfalls encountered commonly in the application of grounded theory research, and a summary of the strengths of grounded theory methodology with illustrations from the medical education domain. DISCUSSION: The significant strengths of grounded theory that have resulted in its enduring prominence in qualitative research include its clearly articulated analytical process and its emphasis on the generation of pragmatic theory that is grounded in the data of experience. When applied properly and thoughtfully, grounded theory can address research questions of significant relevance to the domain of medical education.
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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 | 0.222 | 0.185 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.006 | 0.065 |
| Scholarly communication | 0.024 | 0.019 |
| Open science | 0.008 | 0.016 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".