Making sense of grounded theory in medical education
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.
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.
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 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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 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 it