Moving Accreditation Forward With Accreditation Scholarship
Bibliographic record
Abstract
ABSTRACT: Accreditation in medical education serves to create and sustain a culture of excellence in medical education endeavors. Accreditors in undergraduate medical education, graduate medical education, and continuing professional development spaces on the medical education continuum need to enhance collaboration across international boundaries to develop and implement best practices in medical education accreditation. One opportunity that exists to achieve this is the emerging field of accreditation research, and more broadly, accreditation scholarship. In this commentary, the authors, both professional members of Canadian accreditation committee secretariats (the Committee on the Accreditation of Canadian Medical Schools and the Committee on the Accreditation of Continuing Medical Education), highlight accreditation scholarship as tool to support medical education accreditation improvement, growth, and innovation.
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 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 | 0.104 | 0.246 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.020 | 0.051 |
| Scholarly communication | 0.035 | 0.030 |
| Open science | 0.007 | 0.017 |
| Research integrity | 0.043 | 0.048 |
| Insufficient payload (model declined to judge) | 0.009 | 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; a candidate call from one source (direct Gemma or distilled Codex), 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".