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.
Sun Pennsylvania State University