14. Influences on choice of a generalist career in general surgery, general internal medicine and general pediatrics
Bibliographic record
Abstract
We performed a literature review to summarize the primary influences that encourage or discourage the pursuit of careers in General Surgery (GS), General Internal Medicine (GIM), and General Pediatrics (GP). Relevant studies were identified through a PUBMED and MEDLINE search from 1982 to 2006. All included studies were peer-reviewed and pertained to factors influencing career choice in GS, GIM, GP, and their respective subspecialties. The identified literature was analyzed based on demography, the curriculum, and the nature of the discipline, etc. Consistent factors influencing career choice were established a priori as those supported by ≥2 independent studies or reviews without contradictory findings reported to date. The top two factors favoring the choice of residency in GS are positive clerkship experiences and exposure to positive role models, whereas the top factors discouraging interest in GS are lifestyle issues and the length of residency. As for GIM, influences that favor the specialty include the female gender and preference for GIM upon entry into medical school. Factors that discourage the choice of GIM are high income expectations, the widening salary gap between generalist and specialist, negative clerkship experience and the type of patients in internal medicine. In pediatrics, the top two influences that favor GP are female gender and a predisposition for GP upon entry into medical school. A consistent factor that negatively influences career choice in GP is a favorable attitude towards research. To summarize, the main influences on the choice of a generalist career include gender, role modeling, clerkship experience, lifestyle issues, and financial compensation. Medical schools can encourage the pursuit of generalist careers by enhancing student exposure to positive role models and by providing a positive clerkship experience in GS, GIM, and GP. Kirkham JC, Widmann WD, Leddy D, Goldstein MJ, Samstein B, El-Tamer M, Harari A, Arnell TD, John R, Hardy MA. Medical student entry into general surgery increases with early exposure to surgery and to surgeons. Current Surgery 2006 (Nov-Dec); 63(6):397-400. Arora V, Wetterneck TB, Schnipper JL, Auerbach AD, Kaboli P, Wachter RM, Levinson W, Humphrey HJ, Meltzer D. Effect of the inpatient general medicine rotation on student pursuit of a generalist career. Journal of General Internal Medicine 2006 (May); 21(5):471-475. Cochran A, Melby S, Neumayer LA. An internet-based survey of factors influencing medical student selection of a general surgery career. American Journal of Surgery 2005; 189:742-746.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".