METRICS: a pattern language of scholarship 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
This article was migrated. The article was marked as recommended. Scholarly activity in health professions education has been growing steadily but despite the broad interest, quite what is considered to be scholarly activity in medical education has remained vague. Boyer's classes of scholarly activity ( Boyer 1990) and Glassick et al.'s criteria required of an artefact to render it scholarly ( Glassick et al. 1997) have been widely discussed. While the Glassick model has helped to define to what scholarly activity should be, we have found the Boyer model of what kinds of activity count as scholarship is lacking. We have developed the METRICS model of scholarly activity in medical education that maps more directly to scholarly activities. Metascholarship - activities that reflect on the nature of scholarshipEvaluation - activities that measure value or axiologyTranslation - activities that move findings or practices from one domain to anotherResearch - activities that focus on theory generation or testing (experimental, descriptive or explanatory)Innovation - activities that focus on creating new ideas, objects and practicesConceptual - activities that explore or develop new models, concepts, and paradigmsSynthesis - activities that focus on the integration of existing knowledge and practice Having built the METRICS model and tested it extensively in our own practice, we now seek to engage others in its use and appraisal.
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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 | 0.041 |
| 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 | 0.000 |
| 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 it