The Influence of Academic Discourses on Medical Students’ Identification With the Discipline of Family Medicine
Bibliographic record
Abstract
PURPOSE: To understand the influence of academic discourses about family medicine on medical students' professional identity construction during undergraduate training. METHOD: The authors used a multiple case study research design involving international medical schools, one each from Canada, France, Spain, and the United Kingdom (UK). The authors completed the fieldwork between 2007 and 2009 by conducting 18 focus groups (with 132 students) and 67 semistructured interviews with educators and by gathering pertinent institutional documents. They carried out discursive thematic analyses of the verbatim transcripts and then performed within- and cross-case analyses. RESULTS: The most striking finding was the diverging responses between those at the UK school and those at the other schools. In the UK case, family medicine was recognized as a prestigious academic discipline; students and faculty praised the knowledge and skills of family physicians, and students more often indicated their intent to pursue family medicine. In the other cases, family medicine was not well regarded by students or faculty. This was expressed overtly or through a paradoxical academic discourse that stressed the importance of family medicine to the health care system while decrying its lack of innovative technology and the large workload-to-income ratio. Students at these schools were less likely to consider family medicine. CONCLUSIONS: These results stress the influence of academic discourses on medical students' ability to identify with the practice of family medicine. Educators must consider processes of professional identity formation during undergraduate medical training as they develop and reform medical education.
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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 | 0.020 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".