My thesis examines the impact of academic screening policies on racial segregation and application patterns in New York City middle schools. Using an event study model and panel data from 2018–2023, I find that removing academic screens during the pandemic led to a statistically significant reduction in schools’ Segregation Index for Black, Hispanic, and Other (BHO) students and for Asian and White (AW) students—specifically, a 1 to 1.4 percentage point decrease in the absolute percent difference between each school's racial composition and that of its district. This reduction in segregation was primarily driven by changes in White student representation, resulting in a significant decrease in the Segregation Index across both previously screened and unscreened schools. This pattern demonstrates the system-wide spillover effects of eliminating screened admissions. With the selective reintroduction of academic screens in 2023, the Segregation Index for screened schools increased, particularly affecting Asian and Hispanic students. However, this policy shift did not result in a return of White students to these schools. Using a dynamic panel data model and estimating applicant demographics, I study the long-term impact of removing academic screens on the Segregation Index. I find that both White and Asian populations exhibit persistent changes in segregation: past shifts in their representation are predictive of continued future changes. This trend reflects greater mobility among these groups and lends support to the “White flight” hypothesis, where White families respond to demographic shifts by seeking other schooling options. Finally, changes in segregation and homophily preferences among students had minimal and inconclusive effects on applicant demographics, highlighting the limited impact of demand-side reforms and spillover effects arising from evolving school demographics.