Choosing family medicine. What influences medical students?
Bibliographic record
Abstract
OBJECTIVE: To explore factors that influence senior medical students to pursue careers in family medicine. DESIGN: Qualitative study using semistructured interviews. SETTING: University of Western Ontario (UWO) in London. PARTICIPANTS: Eleven of 29 graduating UWO medical students matched to Canadian family medicine residency programs beginning in July 2001. METHOD: Eleven semistructured interviews were conducted with a maximum variation sample of medical students. Interviews were transcribed and reviewed independently, and a constant comparative approach was used by the team to analyze the data. MAIN FINDINGS: Family physician mentors were an important influence on participants' decisions to pursue careers in family medicine. Participants followed one of three pathways to selecting family medicine: from an early decision to pursue family medicine, from initial uncertainty about career choice, or from an early decision to specialize and a change of mind. CONCLUSION: The perception of a wide scope of practice attracts candidates to family medicine. Having more family medicine role models early in medical school might encourage more medical students to select careers in family medicine.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".