6. Words That Match: Linguistic Analysis of Plastic Surgery Residency Personal Statements to Predict Match and Identify Bias
Malka Korenblit, David Le, Celia Ernstrom, Skyler Palmer, Mark Greyson, David W. Mathes, David Khechoyan, Jason Yu, Katie Egan · 2026
Read 6. Words That Match: Linguistic Analysis of Plastic Surgery Residency Personal Statements to Predict Match and Identify Bias by Malka Korenblit, David Le, Celia Ernstrom, Skyler Palmer, Mark Greyson, David W. Mathes, David Khechoyan, Jason Yu, Katie Egan (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13268037.txt.
Description
Malka Korenblit and co-authors analyze in 2026 the personal statements of 298 applicants to one plastic surgery residency program, hunting for language patterns tied to matching and to bias. Statements were scored by word-analysis software for tone, reasoning style, and self-presentation, then compared with outcomes and applicant backgrounds. Of the group, about six in ten matched into a program.
Matched applicants wrote with more analytical thinking and richer vocabulary, and they addressed the reader far less often. Statement length itself did not matter. Language patterns differed by race even after accounting for grades and scores: Asian applicants wrote more analytically, while Black and Hispanic applicants used less positive and certain language. The authors warn that uniform standards can still favor majority writing styles.
Catalog record
| CREATOR | Malka Korenblit, David Le, Celia Ernstrom, Skyler Palmer, Mark Greyson, David W. Mathes, David Khechoyan, Jason Yu, Katie Egan |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 3 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |