Effect of the discipline of formal faculty advisors on medical student experience and career interest.
Bibliographic record
Abstract
OBJECTIVE: To examine whether the discipline (family medicine vs other specialty) of formally assigned faculty advisors affected medical student experience and career interest. DESIGN: Survey. SETTING: University of Calgary in Alberta. PARTICIPANTS: A total of 104 medical students from the graduating class of 2011. MAIN OUTCOME MEASURES: Number of times medical students met with their advisors, topics of discussions, interest in family medicine, and overall medical school experience. For binary categorical variables, χ2 tests of significance were computed, and t tests were used for count and Likert-scale variables. RESULTS: Overall, 89 (86%) surveys were returned. Significant differences were noted when the discipline of the faculty advisor (family medicine vs Royal College specialty) was considered. Family medicine faculty advisors met with their students more often (P = .03) and were more likely to have a beneficial effect on the medical school experience (P = .005). Having a relationship with a family medicine faculty advisor significantly increased family medicine career interest (P = .01), although a faculty advisor in any other discipline did not erode family medicine interest. The discipline of the faculty advisor had no statistically significant influence on a student's intended selection of family medicine in the Canadian Resident Matching Service match. CONCLUSION: Family medicine faculty advisors appear particularly active in their role as mentors and appear beneficial to the medical student experience. Career interest in family medicine was enhanced by being paired with a family medicine advisor and not eroded by an advisor from another specialty.
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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 | 0.004 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".