Testing the role of barriers in shaping segregation profiles: The importance of visualizing the local neighborhood

Abstract

“Egocentric” segregation profiles allow researchers to avoid a reliance on a priori definitions of local neighborhoods that contribute an unknown amount of error to measures of segregation. To date, however, such profiles have used distance-decay techniques that rely on “as the crow flies” measures of space. Yet we know that major roads, railroads, and other physical attributes of space mean that such techniques may introduce error into the measurement and visualization of residential segregation. Here, I use a variation on standard smoothing techniques that allows the smoothing function to vary based on a second variable of interest, in this case, the location of major roads, railroads, and nonresidential land use. Using Philadelphia as a case study due to access to detailed land-use data, I show that barriers do not affect observed values of city-level racial and ethnic dissimilarity. Visualizing the impact of barriers on local neighborhoods, however, shows that while barriers may not affect city-wide indexes of segregation, they continue to powerfully shape local experiences of the city, including protecting new immigrant ethnic enclaves, wealthy white neighborhoods, and also isolating high-poverty, predominantly black neighborhoods in different parts of the city.