Neighborhoods and neighborhood change are often at least implicitly understood in relation to processes taking place at scales both smaller than and larger than the neighborhood itself. Until recently our capacity to represent these multi-scalar processes with quantitative measures has been limited. Recent work on “segregation profiles” by Reardon and collaborators (Reardon et al., 2008, 2009) expands our capacity to explore the relationship between population measures and scale. With the methodological tools now available, we need a conceptual shift in how we view population measures in order to bring our theories and measures of neighborhoods into alignment. I argue that segregation can be beneficially viewed as multi-scalar; not a value calculable at some ‘correct’ scale, but a continuous function with respect to scale. This shift requires new ways of thinking about and analyzing segregation with respect to scale that engage with the complexity of the multi-scalar measure. Using block level data for eight neighborhoods in Seattle, Washington I explore the implications of a multi-scalar segregation measure for understanding neighborhoods and neighborhood change from 1990 to 2010.

Although the trend toward greater ethnoracial diversity in the United States has been documented at a variety of geographic scales, most research tracks diversity one scale at a time. Our study bridges scales, asking how the diversity and segregation patterns of metropolitan areas are influenced by shifts in the racial/ethnic composition of their constituent places. Drawing on 1980–2010 decennial census data, we use a new visual tool to compare the distributions of place diversity for 50 U.S. metro areas over three decades. We also undertake a decomposition analysis of segregation within these areas to evaluate hypotheses about the roles of different types of places in ethnoracial change. The decomposition indicates that although principal cities continue to shape the overall diversity of metro areas, their relative impact has declined since 1980. Inner suburbs have experienced substantial increases in diversity during the same period. Places with large white majorities now contribute more to overall metropolitan diversity than in the past. In contrast, majority black and majority Hispanic places contribute less to metropolitan diversity than in the past. The complexity of the patterns we observe is underscored through an inspection of two featured metropolises: Chicago and Dallas.

This article explores the effects of mixed-race household formation on trends in neighborhood-scale racial segregation. Census data show that these effects are nontrivial in relation to the magnitude of decadal changes in residential segregation. An agent-based model illustrates the potential long-run impacts of rising numbers of mixed-race households on measures of neighborhood-scale segregation. It reveals that high rates of mixed-race household formation will reduce residential segregation considerably. This occurs even when preferences for own-group neighbors are high enough to maintain racial separation in residential space in a Schelling-type model. We uncover a disturbing trend, however; levels of neighborhood-scale segregation of single-race households can remain persistently high even while a growing number of mixed-race households drives down the overall rate of residential segregation. Thus, the article’s main conclusion is that parsing neighborhood segregation levels by household type—single versus mixed race—is essential to interpret correctly trends in the spatial separation of racial groups, especially when the fraction of households that are mixed race is dynamic. More broadly, the article illustrates the importance of household-scale processes for urban outcomes and joins debates in geography about interscalar relationships.

U.S. financial services are bifurcated into a traditional banking sector that serves wealthier individuals and a less regulated alternative financial services sector (payday lenders, check cashers, etc.) catering to lower income individuals. What determines the spatial distribution of fringe banks? First, at the county level, fringe banks do not fill a spatial void in traditional services. Second, whether fringe providers disproportionately locate in counties with more minorities depends on the service and the minority population. Finally, pawnshop prevalence is shaped by restrictions on interest and fees, but the location of payday lenders and check cashers is not sensitive to such regulation.