An examination of entrance criteria for international medical graduates (IMGs) into Canadian psychiatry residency programs
Bibliographic record
Abstract
BACKGROUND: Although international medical graduates (IMGs) are essential in health care service delivery, a gap exists in the literature about how IMGs are selected into psychiatry residency programs in Canada. The purpose of this study was to identify the relative weight or importance that Canadian program directors (PDs) of psychiatry place on certain selection criteria when matching IMGs into residency programs. METHODS: We electronically distributed a web-based questionnaire to 16 university residency program directors of psychiatry in Canada. Program Directors were asked to rate the importance of 43 selection criteria using 5-point Likert Scales. Criteria were grouped into six domains: academic criteria, extracurricular activities, supporting information, behavioural issues of concern, medical school country, and other education. Mean total values for each set of criteria were calculated and used to create rank orders within each domain. RESULTS: Eight out of 16 program directors responded. Our analysis indicated that academics and behavioral issues of concern were the most important selection criteria. CONCLUSION: Our findings provide valuable insight about the perspectives of Program Directors toward IMGs who apply for psychiatry residency programs in Canada. Further studies are needed to better understand which criteria contribute to IMGs' performances as psychiatric residents.
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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".