A big data project led by Stanford University's Sean Reardon aims to crack the code on our nation’s stubborn student achievement gaps by mapping race, ethnicity, poverty and academic test scores.
U.S. public schools are highly racially and economically segregated. Prior research shows that the desegregation of Southern schools beginning in the 1960s led to significant benefits for Black students. We do not know, however, whether segregation today has the same harmful effects as it did 50 years ago, nor do we have clear evidence about the mechanisms through which segregation affects achievement. We estimate the effects of current-day school segregation on racial achievement gaps using 10 years of data from all public districts in the U.S. We find that racial segregation is strongly associated with the magnitude of achievement gaps in third grade and with the rate at which gaps grow from third to eighth grade. The association of segregation with achievement gaps is completely accounted for by racial differences in school poverty (i.e., “racial economic segregation”). Racial segregation appears to be harmful because it concentrates minority students in high-poverty schools, which are, on average, less effective than lower-poverty schools. Exploratory analyses show that segregation-related between-school differences in teacher characteristics are associated with unequal learning rates, but most of the effect of racial economic segregation is unexplained by between-school differences in the set of measured teacher and school characteristics available.