In the Spirit of Flexner: Working Toward a Collective Vision for the Future of Medical Education in Canada
Bibliographic record
Abstract
The Association of Faculties of Medicine of Canada launched the Future of Medical Education in Canada (FMEC) Project in 2007. The FMEC Project's overarching goal was to comprehensively examine the current state of undergraduate medical education, concentrating on its alignment with current and future societal needs. Like Flexner's work, the FMEC Project used a process of reflection and renewal; unlike Flexner's work, the FMEC Project used multiple techniques to gather information, including literature reviews, key informant interviews, international visits, and a series of consultations with stakeholders and expert groups. The project's final report, The Future of Medical Education in Canada: A Collective Vision, put forth 10 recommendations that summarized priority areas for academic medicine and medical training in Canada at the start of the 21st century. The current article reviews FMEC Project recommendations in relation to the priorities set out by Flexner in 1910. In some areas, such as the scientific basis of medical education, there is striking congruence between Flexner's views and today's collective vision. In other areas, such as community-based learning, opinion appears to have shifted markedly over the past century, and concepts such as interprofessionalism may represent distinctly modern domains. While Flexnerian themes tend to center on the notion of medicine as science, present-day priorities converge on the link between academic medicine and societal needs. By looking back on Flexner's work, we can see where his vision has taken us. As well, we see more clearly the new frontiers that academic medicine will continue to explore.
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 | 0.018 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.039 | 0.025 |
| Scholarly communication | 0.024 | 0.011 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".