<p>SaudiMEDs and CanMEDs frameworks: similarities and differences</p>
Bibliographic record
Abstract
Background: The SaudiMEDs framework was founded and adopted by the Saudi Deans’ Committee in 2011 to ensure that Saudi medical graduates learned core competencies. Meanwhile, CanMEDs was established by the Canadian Royal College of Physicians and Surgeons in 1996 and aimed to establish the abilities and skills of all aspects of medical practice, as well as to ensure the acquisition of basic knowledge related to medical education. The main purpose of this study was to explore the similarities and differences between both frameworks. Methods: In March and April 2017, 15 researchers conducted an extensive review of both the SaudiMEDs and CanMEDs frameworks using a semi-quantitative evaluation with color codes to determine the following: the exact similarities in both frameworks, the close similarities, and the unique differences. Results: According to the coloring system, most of the frameworks were similar. For example, Leadership, Communication and Professionalism were almost identical in both frameworks. There was some degree of similarity between both frameworks in “Collaborator”. Furthermore, the SaudiMEDs framework had a unique input which involved the most essential skills that undergraduate medical students must acquire. Conclusion: SaudiMEDs has great potential to improve the quality of Saudi medical graduates in a manner that fits our current and future needs. CanMEDs focuses mainly on outcomes and processes, while SaudiMEDs focuses more on outcomes. SaudiMEDs was not created to provide a copy-and-paste curriculum. The ultimate goal was to create an outcome-based curriculum that ensures the quality of Saudi medical school graduates. Keywords: SaudiMEDs, CanMEDs, framework, competency-based education, Saudi Arabia
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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 | 0.028 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".