School Segregation, Charter Schools, and Access to Quality Education

ABSTRACT:

Race, class, neighborhood, and school quality are all highly interrelated in the U.S. educational system. In the last decade a new factor has come into play, the option of attending a charter school. We offer a comprehensive analysis of the disparities among public schools attended by white, black, Hispanic, Asian, and Native American children in 2010–2011, including all districts in which charter schools existed. We compare schools in terms of poverty concentration, racial composition, and standardized test scores, and we also examine how attending a charter or non-charter school affects these differences. Black and Hispanic (and to a lesser extent Native American and Asian) students attend elementary and high schools with higher rates of poverty than white students. Especially for whites and Asians, attending a charter school means lower exposure to poverty. Children’s own race and the poverty and charter status of their schools affect the test scores and racial isolation of schools that children attend in complex combinations. Most intriguing, attending a charter school means attending a better-performing school in high-poverty areas but a lower performing school in low-poverty areas. Yet even in the best case the positive effect of attending a charter school only slightly offsets the disadvantages of black and Hispanic students.

Notes

A complication in using these scores is that in many cases NCES reported a score range (sometimes a range as large as 15 or 20 percentage points) rather than a specific score. For each reported range we determined the average score among schools in the nation with reported specific scores in that range. A control variable for the original range for each school is not statistically significant and does not change the results of the models. There are other ways to assess relative ranking within a state. We then use the imputed precise scores to calculate a percentile within each state. Compared to percentiles, the alternative of using z-scores (standardizing by the mean and standard deviation within the state) would tend to reduce differences between schools with similar scores near the middle of the distribution and accentuate the high or low values at either tail. It is likely that our approach is therefore somewhat conservative in measuring the disparities across groups, since whites/Asians and other groups tend to lie at opposite ends of the distribution. One disadvantage of using z-scores is that school test scores are not normally distributed. For example, for fourth-grade reading in Texas, the state with the largest sample of elementary schools, scores have a significant negative skew. However, choice of statistic is unlikely to have much effect on the results: the correlation between z-scores and percentiles in this case is .935.

Additional information

Notes on contributors

John R. Logan

John Logan is a Professor of Sociology at Brown University and Director of the initiative on Spatial Structures in the Social Sciences. He continues to conduct national-level studies of trends in school segregation and educational inequalities. Data from these studies for the period 1970–2010 are available to view and download on his webpage: http://www.s4.brown.edu/usschools3/DataMain.aspx

Julia Burdick-Will

Julia Burdick-Will is an Assistant Professor in the Department of Sociology and the School of Education at Johns Hopkins University. Following her PhD from the University of Chicago, she was a Postdoctoral Research Associate at Brown University’s Spatial Structures in Social Sciences Initiative. Her current projects focus on the impact of violent crime in neighborhoods and schools on student achievement and the relationship between neighborhood disadvantage and patterns of high school attendance and school choice.