Reflective practice and social responsibility in family medicine
Bibliographic record
Abstract
Objective To explore the perceived effect of an elective international health rotation on family medicine resident learning. Design Qualitative, collaborative study based on semistructured interviews. Setting Quebec. Participants A sample of 12 family medicine residents and 9 rotation supervisors (N = 21). Methods Semistructured interviews of residents and rotation supervisors. Main findings Residents and supervisors alike reported that their technical skills and relationship skills had benefited. All increased their knowledge of tropical pathologies and learned to expand their clinical examinations. They benefited from having very rich interactions in other care settings, working with vulnerable populations. The rotations had their greatest effect on relationship skills (communication, empathy, etc) and the ability to work with vulnerable patients. All of the participants were exposed to local therapies and local interpretations of disease symptoms and pathogenesis. Conclusion The findings of this study will have a considerable effect on pedagogy. The residents’ experiences of their international health rotations and what they learned in terms of medical skills and pedagogic approaches in working with patients are described. Using a collaborative approach with the rotation supervisors, the data were triangulated and the benefits of an international rotation on academic training were more accurately defined. The findings can now be used to enrich academic programs in social and preventive medicine and more adequately prepare future family physicians for work in various social and cultural settings.
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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 | 0.040 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.054 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".