Key Questions

1. How can a “neighborhood-centered” rather than “variable-centered” approach to analyses help to answer questions about how access to and enrollment in school-based pre-k may have varied by neighborhood characteristics?


Understanding the characteristics of neighborhoods is important for informing policy decisions about how to most equitably and efficiently allocate services, supports, and resources, but determining how to characterize neighborhoods is not a straightforward task.

This brief describes a data-driven method for characterizing neighborhoods in Chicago that leveraged publicly available census data and allowed researchers to consider many neighborhood characteristics simultaneously resulting in a set of five neighborhood groupings.

Key Insights

  • This “neighborhood-centered” (as opposed to a “variable-centered”) method resulted in a parsimonious set of five neighborhoods groupings in Chicago that focused researchers’ attention on the characteristics of neighborhood residents rather than the geographic locale of individual neighborhoods.
  • The five groupings are relatively easy to describe and are easily understood by those familiar with Chicago. It is important to note that they reflect Chicago’s longstanding residential segregation patterns and racial and economic inequities.
  • These neighborhood groupings allowed a more fine-grained look at sections of the city than is possible with the 77 community areas that are typically used, making variation within community areas more visible.
  • This work provides just one example of how these methods can be useful to cities, school districts, and policy makers across the country. Future work can apply a similar approach for different objectives, including conducting research studies, making policy decisions, and providing services or resources.