Residents as Role Models
Bibliographic record
Abstract
PURPOSE: Although researchers have investigated the value of physician role models, residents as role models have received less attention. The objectives of this study were to (1) investigate the importance of resident role models in the education and career choices of medical students, (2) examine the types of factors students judge to be most important in selecting resident role models, and (3) evaluate the specific attributes (within each factor type) that students perceive to be most important, comparing these attributes with those previously published on physician role models. METHOD: This was a cross-sectional, survey-based study, conducted in 2011, in which graduating medical students at McGill University completed a questionnaire on their perceptions of resident role models. The authors analyzed data using descriptive statistics and, for items with scalar responses, repeated measures analysis of variance. RESULTS: Of 165 possible student respondents, 151 (92%) completed the questionnaire. The findings suggest that (1) resident role models play an important role in both the education and career choice of medical students, (2) resident and attending staff role models are equally important to the education of medical students, although attending staff role models appear to be more important for students' career choices, and (3) the factors and specific attributes important in selecting resident role models align with those in previously published literature on physician role models. CONCLUSIONS: This study, suggesting that resident and attending physician role models are equally important to undergraduate education, highlights the importance of supporting residents in their status as role models.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".