Lessons from across the pond: Student perspectives on the Internal Medicine clerkship experience at an Irish and Canadian medical school
Bibliographic record
Abstract
This article was migrated. The article was marked as recommended. There is an increasing number of Canadians studying medicine outside of Canada, with a large cohort studying in Ireland. Studying abroad often means different foci in medical training which may make transitioning to residency in a different system more challenging. Students often enter North American elective rotations with little knowledge of student roles and responsibilities. This paper provides insight into the differences in learning objectives and student experiences in an Internal Medicine clerkship at a medical school in Canada and Ireland. Learning objectives are similar between systems; but there is an experiential discordance. In Ireland, clerks see many different patients, gaining exposure to a breadth of topics and clinical signs, but medical student presentations rarely inform decisions around patient care. In Canada, clerks have more direct patient responsibilities, performing physical examinations, reviewing investigations, writing progress notes, and devising management plans as part of their professional development. Overall, the Irish system places emphasis on the mastery of core clinical skills and maximizing breadth of patient exposure whereas the Canadian clerkship is more focused on graduated responsibility and formulating management plans, at the expense of some breadth of exposure. Such discrepancies may not affect the quality of residents, but are important considerations for Canadians studying abroad when repatriating for electives and residencies.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.032 | 0.010 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".