Family medicine as a career option: how students' attitudes changed during medical school.
Bibliographic record
Abstract
OBJECTIVE: To track and describe career choice decisions of medical students as they progressed through their undergraduate training. DESIGN: Quantitative survey of each class at 5 points during their undergraduate experience. Each survey collected qualitative descriptors of students' current career choices. SETTING: Faculty of Medicine at Memorial University of Newfoundland in St John's. PARTICIPANTS: Undergraduate medical students in each year from 1999 to 2006. MAIN OUTCOME MEASURES: Number of students considering family medicine as a career option at 5 different data-collection points throughout the medical school curriculum. RESULTS: Many students considered family medicine as a career choice early in their undergraduate experience. The number of students considering family medicine dropped significantly during the second year of the curriculum. This trend was consistent across all students surveyed. Although interest in family medicine as a career rebounded later in the curriculum, it never fully recovered. CONCLUSION: A large percentage of medical students considered family medicine as a career choice when they entered medical school. The percentage dropped significantly by the end of the second year of training. Attention should be directed toward understanding how the undergraduate medical curriculum in the first 2 years can protect and cultivate interest in family medicine as a career choice.
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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 | 0.002 | 0.009 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".