Peer Mentorship for International Medical Students in the United States
Bibliographic record
Abstract
To the Editor: International students in U.S. medical schools face unique challenges. After enrolling in medical school, international students must strategically prepare for matching into residency programs that sponsor visas while engaging with meaningful extracurricular opportunities within the restrictions set forth by their student visas. As citizens of Nicaragua and Canada, respectively, who have encountered difficulties when finding answers to questions specific to our international status in undergraduate and postgraduate medical training, we suggest medical schools facilitate peer mentorship initiatives intended for international medical students. An important reason for this difficulty is the low number of enrolled international medical students in the United States. For example, of the 2020–2021 matriculating students to allopathic medical schools in the United States, only 131 out of 22,329 matriculants had a legal residence abroad. 1 In turn, medical schools may be relatively limited in providing nuanced, experience-based career guidance and support to their international students. Navigating the limited and different visa options for postgraduate training—in addition to identifying residency programs that even consider international applicants—can be challenging. This compounds the many challenges medical students face in general, including the uncertainty of matching to a residency program and the impact of the COVID-19 pandemic on each application cycle, setting up international medical students for a more complex journey in medical education than their U.S. peers. Given the few international U.S. medical graduates, and the limitations in career counseling for this population, there is a need for well-informed mentorship and guidance. Peer mentorship initiatives that connect international medical students with each other remain largely underused by medical schools. Although medical schools often offer peer mentorship programs in which more senior students provide academic advice and support to newer students, this approach is insufficient for international students who require guidance in the context of their specific situation. Instead, medical schools should proactively connect international medical students to each other across class years and, just as importantly, to their international alumni. Individuals who have navigated the many barriers present for international medical students in the United States are more likely to provide focused, experience-based support. Facilitating these relationships early in medical school may result in other benefits, including involvement with scholarship and research activities. Ultimately, international medical students in the United States have left their home countries and families to serve the U.S. people. Medical schools that admit international students should place value in using every possible tool to propel them to a successful career in medicine. Acknowledgments: The authors would like to thank the deans of the Warren Alpert Medical School of Brown University for supporting their medical training in the United States.
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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 | 0.005 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".