Bias in Surgery Residency Applications Traced to a Single Section of the Dean’s Letter

Every year, thousands of medical students apply for coveted general surgery residency positions in the United States, and at the heart of each application sits a document known as the Medical Student Performance Evaluation, or MSPE. Often called the dean’s letter, this standardized narrative summary is written by medical school officials and is meant to offer residency program directors an objective, comprehensive portrait of an applicant’s strengths, clinical performance, and noteworthy characteristics. Because grades, test scores, and research output can only tell part of the story, the narrative language of the MSPE carries enormous weight in shaping how reviewers perceive a candidate. Now, a new study published in Global Surgical Education, the journal of the Association for Surgical Education, has pinpointed exactly where within this document ethnic and racial bias tends to lurk, and the answer has significant implications for how medical schools across the country write and review these letters.

The research, led by J. Christopher Polanco-Santana of Beth Israel Deaconess Medical Center and Harvard Medical School, together with Alessandra Storino of UT Southwestern Medical Center, Daniel Wong, and senior author Tara S. Kent, builds on the team’s earlier work. In a previous study published in the Journal of Surgical Education, the same group demonstrated that ethnic and racial bias existed in the MSPEs of general surgery residency applicants when measured by the differential use of two categories of descriptive language: agentic and communal terms. Agentic words, such as assertive, confident, independent, and ambitious, describe traits associated with leadership, self-direction, and achievement. Communal words, such as caring, compassionate, helpful, and warm, describe traits associated with relationships and interpersonal connection. Decades of research in social psychology and organizational behavior have shown that agentic language tends to be associated with professional success, particularly in competitive and high-status fields like surgery, while communal language, though positive, is less often linked to perceptions of leadership and excellence.

What remained unknown after that earlier study was which portion of the MSPE was responsible for the biased word use. The MSPE is not a monolithic document. It contains multiple distinct sections, including a summary or evaluation section, often referred to as the structural portion, in which the writer distills the applicant’s overall performance into a synthesis and often a comparative statement about where the student stands relative to peers. Other portions include the academic history, professional performance evaluations organized by clerkship, and the applicant’s own noteworthy characteristics. Each section is written under different circumstances and may draw on different sources of information, which means that bias could, in principle, be concentrated anywhere in the document. Identifying the specific source matters enormously, because targeted interventions, whether in writer training, template design, or automated language screening, can only be effective if they are aimed at the right section.

To answer the question, the researchers conducted a retrospective study of all MSPEs submitted by applicants to categorical general surgery residency positions at a single academic institution across two consecutive Match cycles. The final dataset comprised 1,314 evaluations drawn from 146 different medical schools, giving the analysis a broad national sampling of how these documents are written across the United States. The two application cycles were comparable at baseline, and the gender distribution of the applicant pool was nearly even, with women making up 51.6 percent of applicants. Most applicants identified as white, accounting for 52.7 percent, or Asian, accounting for 25.3 percent, while 17 percent of applicants self-identified as underrepresented in medicine, a designation that includes racial and ethnic groups whose representation in the medical profession is disproportionately low relative to their share of the general population.

The methodological core of the study was the calculation of a bias score for each distinct portion of the MSPE. Rather than treating the document as a single block of text, the researchers computed separate scores reflecting the relative frequency of agentic versus communal terms in each section. They then used multivariable regression, a statistical technique that allows researchers to assess the association between an outcome and one predictor while accounting for the influence of other variables, to test whether each section-specific bias score differed between underrepresented-in-medicine applicants and non-underrepresented applicants. This approach isolates where in the document the differential language use arises, rather than merely confirming that it exists somewhere. The use of regression also helps guard against the possibility that observed differences are explained by confounding factors such as application cycle, medical school, or applicant characteristics.

The results were striking in their specificity. Applicants who identified as underrepresented in medicine had lower median overall bias scores, at 9.09, compared with white applicants, whose median overall bias score was 13.04. The same pattern appeared in the structural or summary portion of the document, where the median bias score for underrepresented applicants was 13.33 compared with 20 for white applicants. Because higher scores reflect a greater relative use of agentic language, these numbers indicate that the MSPEs of underrepresented-in-medicine applicants were written with systematically different word choices, leaning more heavily on communal descriptors and less on agentic ones. When the researchers examined the other sections of the document, the differential word use was concentrated in the summary portion, indicating that the structural or summary section is the primary source of the biased writing.

This finding carries real weight for the residency selection process. The summary section is arguably the most consequential part of the MSPE, because it is the portion that program directors most often read closely and cite when deciding whom to invite for interviews. Survey research from the National Resident Matching Program has shown that the MSPE is among the most influential documents in residency selection, and studies of program director behavior have found that the narrative evaluation can change decisions about whether to invite an applicant at all. If the language in the summary section systematically frames underrepresented-in-medicine applicants in more communal and less agentic terms, then even well-intentioned reviewers may absorb an implicit impression that these candidates are warm and dedicated but less commanding or leader-like than their peers. Such impressions, formed in seconds during application review, can compound across thousands of programs and contribute to the persistent underrepresentation of certain racial and ethnic groups in surgery.

The study also situates itself within a broader and rapidly growing literature on bias in evaluative language across medicine. Prior work has documented racial and ethnic disparities in clinical grading during medical school, gender-based differences in the language students use to describe their own noteworthy characteristics, and agentic and communal differences in letters of recommendation for applicants to radiology, urology, and surgical training programs. Researchers have shown that implicit racial bias among health care professionals influences clinical outcomes, that implicit bias affects admissions decisions, and that word embeddings trained on large text corpora can quantify decades of shifting gender and ethnic stereotypes in language. Some studies have explored whether redacting identifiers from applications can reduce biased scoring, while others have asked whether artificial intelligence tools could help mitigate bias in recommendation writing. The new study adds a crucial layer of granularity to this literature by demonstrating that bias is not diffusely spread through evaluative documents but is concentrated in the section where writers synthesize and summarize.

Why would the summary section be particularly vulnerable? The authors’ findings are consistent with what psychologists know about how stereotypes operate. When writers compile detailed evaluations from discrete clerkship assessments, they are largely transcribing and organizing specific observations, a task that anchors them to concrete performance data. When they write the summary, however, they must distill an entire career into a general characterization, and it is precisely in this act of abstraction that implicit associations are most likely to surface. The summary is also the section most likely to include comparative statements, ranking the applicant against peers, and comparative judgments are known to be especially sensitive to stereotype-driven expectations. Whatever the underlying mechanism, the practical implication is clear: interventions aimed at reducing bias in the MSPE should focus their attention on the summary and structural portion of the document, whether through structured templates, writer training that highlights agentic and communal language, or automated screening tools applied specifically to the final synthesis before the letter is released.

The researchers caution that their data, drawn from applicants to a single academic institution over two Match cycles, reflect one program’s applicant pool, and that the underlying data, obtained through the Electronic Residency Application Service and containing protected applicant information, are not available directly from the authors. Nevertheless, the scale of the sample, spanning 146 medical schools and more than 1,300 evaluations, lends considerable weight to the conclusion. The study was approved by the Institutional Review Board at Beth Israel Deaconess Medical Center and received no specific external funding. As surgery and medicine more broadly confront the persistent gap between the diversity of the population they serve and the homogeneity of their workforce, this research offers something rare in the field: a precise anatomical map of where bias hides in one of the most important documents in a physician’s career. Fixing the summary section, the study suggests, may be the single most efficient place to start.

Subject of Research: Ethnic and racial bias in the language of medical student performance evaluations for general surgery residency applicants

Article Title: Source of ethnic/racial bias in medical school performance evaluation of general surgery residency applicants

Article References: Polanco-Santana, J. C., Storino, A., Wong, D., & Kent, T. S. (2026). Source of ethnic/racial bias in medical school performance evaluation of general surgery residency applicants. Global Surgical Education – Journal of the Association for Surgical Education, 5(1), Article 130. https://doi.org/10.1007/s44186-026-00531-5

Image Credits: AI Generated

DOI: 10.1007/s44186-026-00531-5

Keywords: MSPE, dean's letter, general surgery residency, ethnic bias, racial bias, agentic language, communal language, underrepresented in medicine, residency match, implicit bias, medical education, surgical workforce diversity