Sorting schools: A computational analysis of charter school identities and stratification

Abstract

Research shows that charter schools are more segregated by race and class than traditional public schools. I investigate an under-examined mechanism for this segregation: Charter schools project identities corresponding to parents’ race- and class-specific parenting styles and educational values. I use computational text analysis to detect the emphasis on inquiry-based learning in the websites of all charter schools operating in the 2015-16 school year. I then estimate mixed linear regression models to test the relationships between ideological emphasis and school- and district-level poverty and ethnicity. I thereby transcend methodological problems in scholarship on charter school identities by collecting contemporary, valid, population-wide data, as well as by blending text analysis with hypothesis testing. Findings suggest that charter school identities are both race- and class-specific, lending weight to arguments for further regulating charter school enrollments. This project contributes to literatures on school choice, educational stratification, and organizational identity.