Cultural transition of international medical graduate residents into family practice in Canada
Bibliographic record
Abstract
OBJECTIVE: To identify the perceived strengths that international medical graduate (IMG) family medicine residents possess and the challenges they are perceived to encounter in integrating into Canadian family practice. METHODS: This was a qualitative, exploratory study employing focus groups and interviews with 27 participants - 10 family physicians, 13 health care professionals, and 4 family medicine residents. Focus group/interview questions addressed the strengths that IMGs possess and the challenges they face in becoming culturally competent within the Canadian medico-cultural context. Qualitative data were audiotaped, transcribed, and analyzed thematically. RESULTS: Participants identified that IMG residents brought multiple strengths to Canadian practice including strong clinical knowledge and experience, high education level, the richness of varied cultural perspectives, and positive personal strengths. At the same time, IMG residents appeared to experience challenges in the areas of: (1) communication skills (language nuances, unfamiliar accents, speech volume/tone, eye contact, directness of communication); (2) clinical practice (uncommon diagnoses, lack of familiarity with care of the opposite sex and mental health conditions); (3) learning challenges (limited knowledge of Canada's health care system, patient-centered care and ethical principles, unfamiliarity with self-directed learning, unease with receiving feedback); (4) cultural differences (gender roles, gender equality, personal space, boundary issues; and (5) personal struggles. CONCLUSIONS: Residency programs must recognize the challenges that can occur during the cultural transition to Canadian family practice and incorporate medico-cultural education into the curriculum. IMG residents also need to be aware of cultural differences and be open to different perspectives and new learning.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".