A systematic review of the factors affecting choice of surgery as a career
Bibliographic record
Abstract
BACKGROUND: Interest in surgical careers among medical students has declined over the past decade. Multiple explanations have been offered for why top students are deterred or rejected from surgical programs, though no consensus has emerged. METHODS: We conducted a review of the literature to better characterize what factors affect the pursuit of a surgical career. We searched PubMed and EMBASE and performed additional reference checks. Agency for Healthcare Research and Quality (AHRQ) and Newcastle-Ottawa Education scores were used to evaluate the included data. RESULTS: Our search identified 122 full-text, primary articles. Analysis of this evidence identified 3 core concepts that impact surgical career decision-making: gender, features of surgical education, and student "fit" in the culture of surgery. CONCLUSION: Real and perceived gender discrimination has deterred female medical students from entering surgical careers. In addition, limited exposure to surgery during medical school and differences between student and surgeon personality traits and values may deter students from entering surgical careers. We suggest that deliberate and visible effort to include women and early-career medical students in surgical settings may enhance their interest in carreers in surgery.
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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 | 0.008 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.012 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".