Cross sectional analysis of student-led surgical societies in fostering medical student interest in Canada
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to examine how surgery interest groups (SIGs) across Canada function and influence medical students' interest in surgical careers. METHODS: Two unique surveys were distributed using a cross sectional design. The first was sent to SIG executives and the second to SIG members enrolled at a Canadian medical school in the 2016/17 academic year. The prior focused on the types of events hosted, SIG structure/ supports, and barriers/ plans for improvement. The second questionnaire focused on student experience, involvement, and suggestions for improvement. RESULTS: SIG executives became involved in SIG through classmates and colleagues (8/17, 47%). Their roles focused on organizing events (17/17, 100%), facilitating student contact with resident/surgeons (17/17, 100%), and organizing funding (13/17, 76%). Surgical skills events were among the most successful and well received by students (15/17, 88%). Major barriers faced by SIG executives during their tenure included time conflicts with other interest groups (13/17, 76%), lack of funding (8/17, 47%), and difficulty booking spaces for events (8,17, 47%). SIGs were found to facilitate improvement in basic surgical skills (μ = 3.89/5 ± 0.70) in a comfortable environment (μ = 4.02/5, ±0.6), but were not helpful with final block examinations (μ = 2.98/5, ±0.80). Members indicated that more skills sessions, panel discussion and shadowing opportunities would be beneficial additions. Overall, members felt that SIGs increased their interest in surgical careers (μ = 3.50/5, ±0.79). CONCLUSION: Canadian SIGs not only play a critical role in early exposure, but may provide a foundation to contribute to student success in surgery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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 teacher head, 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".