Classifying people into groups—like race and ethnicity—is common in public policy and clinical medicine, but inconsistent definitions can make these classifications unreliable for predicting outcomes and making decisions. A recent working paper by Charles Manski, John Mullahy, and Atheendar Venkataramani explores the challenges of using data from different classification schemes, particularly when data are limited.