At its core my research examines the way our choices about geographic boundaries shape the outcomes we are able to observe. I examine neighborhoods, school catchment areas, electoral districts, metropolitan areas, and labor markets with a focus on how these units of observation reflect the distribution of populations in space. My work focuses in particular on patterns of clustering and dispersal by race and income as these two characteristics can tell us a lot about inequality in economic, education, health, and political outcomes.
Some key applications of my current research are:
- How school districts change catchment areas to influence racial diversity within schools
- How changing the scale of congressional districts can influence the degree to which constituents get 'good' representation
- How uncertainty in the underlying data influences the designation of places as rural or metropolitan
- How effectively can we interpolate historical Census data into present day administrative units.
Previously my work has also focused on patterns of segregation and diversity at multiple scales, on clustering of economic activity, and on competitiveness among cities and across transportation networks.