18. The future of Canadian residency education: The core competency project
Bibliographic record
Abstract
The Core Competency Project (CCP) is an initiative to reexamine fundamental recurring issues in Canadian medical education, including: (1) premature career decision making by medical students, (2) barriers to changing career disciplines by residents and practicing physicians, (3) lack of clarity on the role of “generalism” in medical training, and (4) the optimal structure and function of the PGME system. The CCP is a collaborative national endeavour of The Royal College of Physicians and Surgeons of Canada and the College of Family Physicians of Canada. From 2005 to 2007, the CCP employed four primary methods, including: (1) a systematic review of relevant literature, (2) a series of commentary papers by leaders in medicine and medical education, (3) a series of focus groups across Canada involving medical students, residents, and practicing physicians, and (4) a national survey of stakeholders. This was supplemented by consultations with key groups in the medical profession. We describe the findings of these studies and the implications for medical education policy in Canada and around the world. The CCP is an unprecedented national medical education policy initiative.
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 | 0.017 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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; 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".