Surgical residency training and international volunteerism: a national survey of residents from 2 surgical specialties
Bibliographic record
Abstract
BACKGROUND: Many low- and middle-income countries (LMICs) lack basic surgical resources, resulting in avoidable disability and mortality. Recently, residents in surgical training programs have shown increasing interest in overseas elective experiences to assist surgical programs in LMICs. The purpose of this study was to survey Canadian surgical residents about their interest in international volunteerism. METHODS: We sent a web-based survey to all general and orthopedic surgery residents enrolled in surgical training programs in Canada. The survey assessed residents' interests, attitudes and motivations, and perceived barriers and aids with respect to international volunteerism. RESULTS: In all, 361 residents completed the survey for a response rate of 38.0%. Half of the respondents indicated that the availability of an international surgery elective would have positively influenced their selection of a residency program. Excluding the 18 residents who had volunteered during residency, 63.8% of the remaining residents confirmed an interest in international volunteering with "contributing to an important cause," "teaching" and "tourism/cultural enhancement" as the leading reasons for their interest. Perceived barriers included "lack of financial support" and "lack of available organized opportunities." All (100%) respondents who had done an international elective during residency confirmed that they would pursue such work in the future. CONCLUSION: Administrators of Canadian surgical programs should be aware of strong resident interest in global health care and accordingly develop opportunities by encouraging faculty mentorships and resources for global health teaching.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".