Residential Segregation Across Metro St. Louis School Districts: Examining the Intersection of Two Spatial Dimensions

• In Event: Place, Geography, and Geographic Information Systems in Educational Policy and Politics

Abstract

Purpose

This study employs a geospatial approach to studying the evenness-clustering and isolation-exposure dimensions of segregation in the St. Louis, Missouri metropolitan region. In contrast to global indicators of segregation, this approach focuses on evenness and isolation dimensions at local levels in order to visualize how they interact across neighborhoods (Oka & Wong, 2014). While not traditionally a method for theory testing, GIS contributes to the validation process by displaying how these segregation constructs interact when applied in an actual geographic context. We examined separately the segregation dimension of racial evenness-clustering and its intersection with Black isolation and poverty isolation.

Framework

Spatial methodologies typically have not been incorporated in studying educational contextual factors, but these methods warrant greater use to better understand the nature of opportunity in different communities (Lubienski & Lee, 2017). Reardon and O’Sullivan (2004) theorized two interacting dimensions of segregation: evenness–clustering (Even-Clus) and isolation–exposure (Iso-Exp). To understand segregation in terms of the interaction between these dimensions, it is critical to see their interaction in a metropolitan geographic space. Values of the Even-Clus and the Iso-Exp dimensions aggregated as a global measure for a whole region only tell part of the story. The important storyline resides in the details of local neighborhood contexts. Where are the neighborhoods that are diverse and individuals are integrated? Where are the neighborhoods that lack racial evenness and groups are isolated? What type of schools and resources are located in these various Even-Clus and Iso-Exp combinations? Global segregation measures cannot answer these questions, but they can be addressed using GIS to map segregation dimensions in actual geographic space.

Data and Methods

The data are 446 St. Louis area census tracts from 5-year estimates of the 2015 American Community Survey that represent 65 area school districts. Variables at the census tract level include racial composition and families under the poverty level, as well as school fifth-grade language arts achievement data. Using geospatial mapping software the study visualized variability and relationships in the four quadrants produced by the intersection of the Even-Clus and Iso-Exp dimensions. The values of racial evenness, Black isolation, and poverty isolation located in each of these quadrants show their intersections in geographic space and provide a composite picture of how segregation operates across neighborhoods and school districts.

Results and Conclusions

An important result from the mapping approach is the ability to illustrate that in regions appearing diverse and where individuals and groups are potentially exposed to each other, there may also be neighborhoods where individuals or groups are isolated. Pockets of isolation and segregation can exist in areas considered diverse. The present results support the conceptual framework of two segregation dimensions (Even-Clus and Iso-Exp) and demonstrate how they interact in geographic space. Not surprisingly, areas of concentrated segregation also include those with the greatest poverty and economic disadvantage. The type and degree of segregation must be delineated so that isolated students adversely affected by separation from critical resources can be connected to appropriate educational and community support systems.

Authors

• Mark Hogrebe, Washington University in St. Louis

• William F. Tate, Louisiana State University