Assessment of International Medical Graduates and Their Integration into Family Practice: The Clinician Assessment for Practice Program
Bibliographic record
Abstract
The Clinician Assessment for Practice Program (CAPP), a program of the College of Physicians and Surgeons of Nova Scotia (CPSNS), assesses the readiness for family practice of international medical graduates (IMGs) who have trained and practiced abroad with no formal Canadian residency training.CAPP has three parts. Part A, a therapeutics exam and an objective structured clinical examination, assesses practice readiness. Part B is a 12-month mentorship in which the CAPP physician is in active practice under a defined license and is mentored by an established family physician. The mentor provides teaching, supervision, guidance, and regular performance assessment. Each CAPP physician negotiates an individualized continuing medical education plan. An on-site assessment of each CAPP physician's practice is conducted by an external assessor who provides feedback to the CAPP physician and his or her mentor. Multisource feedback is administered at 10 months, using questionnaires from patients and colleagues. After 12 months, all assessment data are reviewed by the CPSNS to determine whether to continue the defined license. Part C, run by the registration department (not CAPP), may last three additional years until full licensure is obtained. To date, 148 IMGs have been assessed, 35 have been deemed eligible for a defined license, and 27 have entered family practice, virtually all in small or medium-sized communities in Nova Scotia. The program has been well received by participants and their communities. The mentorship, particularly valuable in assisting IMGs to integrate into their communities, has proven to be the defining feature of CAPP.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".