A Suburban School Typology

• In Event: Exploring Suburban School Inequality

Abstract

Objectives
Racial change is happening in suburbia. Although suburbia is commonly thought of as a monolith and defined broadly as part of a metropolitan area that is not a central city, suburbia is no longer easy to define. Suburban racial change, like the development of suburbs themselves, is happening in very different ways and at very different speeds. We need a new way of thinking about suburbs and suburban school districts. This paper aims to understand the different ways that suburban districts are changing and proposes a typology of suburban districts.
Theoretical Perspectives
While much policy and discussion still delineates a city-suburban binary, suburb actually encompasses substantial diversity in terms of population characteristics, economic base, and housing stock. Myron Orfield (2002) argued that rather than a single “suburban” category, there exist instead a typology of suburban communities that have dramatically different tax bases and populations. A similar categorization scheme using demographic and voting data has divided the entire country by both congressional districts and counties into a dozen categories (Badger, 2011).
Data sources
This paper explores differences between suburban districts by examining the suburban school districts in the largest twenty-five U.S. metropolitan areas, which enroll one-quarter of all students. This paper uses the CCD’s Public School Universe; here, I use data from 1990–91, 1999–2000, and 2006–07.
Modes of analysis
Several dimensions of segregation are analyzed within and across districts in metropolitan areas for student enrollment by race/ethnicity and poverty status: (1) the index of dissimilarity, to measure the evenness of the population’s distribution; and (2) the percentage of students in intensely segregated schools, to measure concentration (Massey & Denton, 1988). This paper also used cluster analysis to group the 2,364 suburban districts into six distinct clusters. Using the K-means clustering procedure to cluster large numbers of observations (e.g., suburban school districts) into distinct groups, this analysis created clusters using relative metropolitan indicators of racial and economic characteristics of the district enrollment, size of enrollment, and racial change (Orfield, 2002).
Findings
District-level segregation between suburban districts is high between certain racial pairs, and as the number of Latino students in suburbia has grown, so too has their segregation from white students. While Latinos are present to a larger extent in growing districts, whites are more likely to leave districts at a higher rate at even small percentages of Latino students (Frankenberg, 2010).
The cluster analysis reveals considerably variety among suburban districts and distinct student patterns (table 1). Given the continuing suburbanization amid racial and economic change, this cluster analysis illustrates the differentiation between suburban districts and the diversity of suburban district types. There are notable patterns of school-level characteristics and segregation in these six types of suburban districts as well (table 2).
Significance
As the growing diversification of suburbia occurs (Farrell, 2008), understanding whether and how the suburban enrollment may be replicating patterns of segregation on a larger geographic scale has important implications for both the opportunities and challenges suburban districts face in providing high-quality educational opportunities for all students.

Author

• Erica Frankenberg, The Pennsylvania State University