Personalized Recommendations Without Inducing Congestion: Mitigating Disparities in the NYC High School Match
How to recommend schools without overwhelming the best programs
A new recommendation system for NYC's high school admissions increased the share of students ranking a recommended school from 10.5% to 16.4%, and increased matches to recommended schools by 71%. The key innovation: the algorithm accounts for congestion—the problem that recommending the same popular schools to too many students backfires, making those schools harder to get into for everyone. In a real deployment, no student was rejected from a school the algorithm recommended.
NYC's high school match assigns roughly 65,000 students annually to programs. Without congestion-aware recommendations, students in underserved neighborhoods get steered toward the same few good schools, which then become so competitive that even strong applicants get rejected. This system increased matches for treatment students by 71% while keeping rejection rates unchanged, directly expanding college-track options for students with fewer nearby choices.