Determinants of choosing a career in surgery
Bibliographic record
Abstract
INTRODUCTION: Student choice is an important determinant of the specialty mix of practicing physicians in Canada. Understanding student characteristics at medical school entry that are associated with a student choosing a residency in surgery can assist surgical educators in supporting medical students interested in surgery and in serving health human resources needs. METHODS: From 2002 to 2004, data was collected from entering students in 15 classes at eight of 16 Canadian medical schools. Surveys included questions on career choice, attitudes to practice, and socio-demographics. Students were followed prospectively with survey data linked to their residency choice. Multiple logistic regression analysis was used to identify entry characteristics that predicted a student's ultimate choice of a surgical career. RESULTS: Eight entry variables predicted whether a student named surgery (including obstetrics) as their top residency choice: having surgery as their top career choice, having a relative or friend in a surgical career, having undertaken volunteer work with sports teams, an interest in narrow scope of practice, greater interest in medical the social patient problems, an interest in urgent care, and younger age were identified as predictors of a surgical career choice. DISCUSSION: Surgical educators may wish to attend to the factors that we found that predicted students selecting a surgical residency as their top career choice at medical school exit in order to foster and support students interested in the surgical disciplines during medical school. In addition, these factors could be used to identify students interested in a surgical career at medical school entry.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".