Smoothing the Transition Points in Canadian Medical Education
Bibliographic record
Abstract
In 2010, the Association of Faculties of Medicine of Canada, Collège des médecins du Québec, College of Family Physicians of Canada, and Royal College of Physicians and Surgeons of Canada launched the Future of Medical Education in Canada Postgraduate (FMEC PG) Project to examine postgraduate medical education (PGME) in Canada and make recommendations for improvement. One recommendation that emerged concerns the transitions learners experience across the undergraduate medical education-PGME-practice continuum. The FMEC PG, using a thorough process, developed projects to address these often-tumultuous transitions for the learner, aiming to provide support, tools, and standards for the learner's educational journey.With leadership by two senior academics and the Transitions Implementation Committee, three working groups helped implement these transitions projects, which addressed (1) the medical-school-to-residency transition, (2) career planning and the residency matching process, and (3) the residency-to-practice transition. Work products include the development of a learner education handover protocol and the establishment of pan-Canadian entrustable professional activities to be used nationally to help define expectations for new graduates entering residencies. A postmatch boot camp tool and a simulated night on-call tool were developed and are available to all medical schools. National standards are being promoted for career services counseling and best practices in residency selection. A practice management curriculum framework, mentorship resources, resiliency training for graduating residents, and the entry-level disciplines of residency are also being explored.Ultimately, with system-wide change and better integration of all players, transitions for Canada's learners will greatly improve.
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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 | 0.006 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".