Geographic Trends of International Medical Graduate Residents and Faculty in US Plastic Surgery Training Programs
Bibliographic record
Abstract
BACKGROUND: Of the academic plastic surgeons in the United States, 13.6% are international medical graduates (IMGs). The objective of this study was to identify the countries from which IMGs obtained their medical degrees and the states they matched in. We sought to establish a correlation between IMG faculty and residents in plastic surgery programs. METHODS: Plastic surgery program Web sites were reviewed. The primary outcome of interest was the country IMG residents had obtained their medical degrees from. Secondary outcomes of interest were program state location, IMG resident postgraduate year, and programs' number of IMG faculty. RESULTS: One hundred one programs were screened. A total of 39 states were represented; there were 1262 current residents, of which 92 (7.3%) were IMGs. International medical graduate residents received their medical degrees from 46 different countries. The most common countries were England (n = 6 [6.5%]) for IMG residents and Canada (24.5%) for IMG faculty. The most common region represented for residents was South America (n = 44 [47.8%]). The highest proportions of IMGs per total state plastic surgery residents were found in West Virginia (33.3%) and Minnesota (25%); 13.5% and 15.6% of program directors and program chairs were IMGs, respectively. There was a statistically significant difference between the proportion of IMG residents in programs that had an IMG program director versus programs with no IMG program director (P = 0.016). No such statistically significant difference was found between the proportion of IMG residents in given programs with IMG chairs (P = 0.55). There were significantly more IMG faculty in programs with IMG chairs (P = 0.001). The number of IMG faculty was positively correlated to the number of IMG residents in a given program (P = 0.0001, r = 0.39). CONCLUSION: International medical graduate residents constitute a small but appreciable portion of current plastic surgery residents; the majority have earned their degrees from the South America region. International medical graduate plastic surgery residents are more likely to be recruited to programs that have an IMG program director and a higher number of IMG faculty. International medical graduate faculty have a strong representation in academic plastic surgery, as evidenced by the percentage of IMG program directors and chairs. Programs with IMG chairs had a greater number of IMG faculty.
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 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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.000 | 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".