The impact of interest: how do family medicine interest groups influence medical students?
Bibliographic record
Abstract
OBJECTIVE: To describe the knowledge of, and experience with, the Interest Group in Family Medicine (IgFM) at the University of Toronto, among undergraduate medical students; to explore the effects of the IgFM on undergraduate medical students; and to help determine future directions for the IgFM and other family medicine interest groups in Canada. DESIGN: Qualitative descriptive design and focus groups. SETTING: The Faculty of Medicine at the University of Toronto in Ontario. PARTICIPANTS: A total of 45 students in the undergraduate medical school program at the University of Toronto participated in this study. Approximately equal numbers of students from each year were represented in the sample. METHOD: Focus groups were conducted to determine students' knowledge of, experiences with, and perspectives on the IgFM. The focus groups were audiotaped and transcribed verbatim. Transcripts were coded and analyzed for themes using qualitative content analysis. Data were collected until saturation of emerging themes was reached. MAIN FINDINGS: The students were generally knowledgeable about the IgFM and many had attended IgFM events. The IgFM had different effects on students depending on their level of interest in family medicine (FM). For those already interested in FM, the IgFM helped to maintain and support that interest. For students still undecided about their career choices, the IgFM helped to support continued interest in FM by dispelling negative myths about the discipline, providing positive peer influences, and supplying information about careers in FM. For students not interested in FM, the IgFM provided helpful information about the discipline. Students also had many useful suggestions regarding the future direction of the IgFM. CONCLUSION: The IgFM has been successful in increasing medical student exposure to FM and in supporting students' interest in this discipline. Information from this study also provides strategies for future direction to the IgFM and other family medicine interest groups in Canada and the United States.
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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 | 0.009 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".