Choosing a career in surgery: factors that influence Canadian medical students' interest in pursuing a surgical career.
Bibliographic record
Abstract
BACKGROUND: Interest in both general surgery and surgical subspecialties has been declining among Canadian medical students. Studies have shown that a student's desire to practise surgery is largely determined before entry into medical school. As part of a larger study of students' career preferences throughout medical school, we sought to identify the level of interest in surgical careers and the factors that influence a student's interest in pursuing a surgical career. METHODS: We surveyed students from 18 different classes at Canadian medical schools at the commencement of their studies between 2001 and 2004. We asked the students to list their top career choices and the degree to which a series of variables influenced their choices. We also collected demographic data. We performed a factor analysis on the variables. RESULTS: Of 2420 surveys distributed, 2168 (89.6%) were completed. A total of 21.0% of respondents named a surgical specialty as their first choice of career. We found that male students were more likely to express interest in a surgical specialty than female students, who were more likely to express interest in either family medicine or a medical specialty. Compared with students interested in a career in family medicine, those interested in a surgical or medical specialty were younger, more likely to be single and more likely to be influenced by prestige when making their career choices. Students interested in a career in surgery were less influenced by medical lifestyle and a varied scope of practice, less likely to demonstrate a social orientation and more likely to be hospital-oriented than students interested in either family medicine or a medical specialty. Male students interested in a career in surgery were more hospital-oriented and less likely to demonstrate a social orientation than female students interested in surgical careers. CONCLUSION: We identified 5 factors and a number of demographic variables associated with a student's interest in a surgical career.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".