Training international medical graduate clinical fellows: the challenges and opportunities for adolescent medicine programs
Bibliographic record
Abstract
Adolescent medicine achieved accreditation status first in the United States in 1994 and then in Canada in 2008 and even if it is not an accredited subspecialty in most other Western nations, it has still become firmly established as a distinct discipline. This has not necessarily been the case in some developing countries, where even the recognition of adolescence as a unique stage of human development is not always acknowledged. The program at SickKids in Toronto has prided itself in treating its international medical graduates (IMG) clinical fellows the same as their Canadian subspecialty residents by integrating them seamlessly into the training program. Although this approach has been laudable to a great extent, it may have fallen short in formally acknowledging and addressing the challenges that the IMG trainees have had to overcome. Moving forward, faculty must be trained and supports instituted that are geared specifically towards these challenges. This must be done on a formal basis to ensure both the success of the trainees as well as the overall enrichment of the fellowship training programs.
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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 | 0.035 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".