Applying to Plastic Surgery Residency: Factors Associated with Medical Student Career Choice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Applications to plastic surgery residency increased 34 percent from 2002 to 2005, despite decreasing applications to other surgical subspecialties. During this period, medical education, reimbursement, work hours, and media coverage have changed. METHODS: To determine factors responsible for rising applications to plastic surgery residencies, medical student applicants to plastic surgery residencies for 2005 were surveyed. Applicants recorded exposure to plastic surgery during medical school and graded the influence of personality, lifestyle, income potential, and media coverage on their decision to choose plastic surgery training. To further study the effects of plastic surgery exposure on career choice, the percentage of graduating students applying to plastic surgery residency was compared between medical schools with and without plastic surgery training programs. RESULTS: Medical schools that provided greater exposure to plastic surgery and schools with plastic surgery training programs had a higher percentage of graduates applying to plastic surgery residency (p < 0.001). Applicants rated compatibility with the personality of plastic surgeons as a significant factor in their career choice. Lifestyle and income potential were moderately important, whereas media coverage minimally affected career decision. Applicants typically decided on a plastic surgical career during the third year of medical school. CONCLUSIONS: Medical student exposure to plastic surgery is the most influential factor in a student's decision to pursue a career in plastic surgery. To continue the increasing applicant trend toward plastic surgery, plastic surgeon engagement of medical students should be emphasized, ideally before the third year of medical school.
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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 | 0.002 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it