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Mapping Educational Opportunity Zones: A Geospatial Analysis of Neighborhood Block Groups

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Abstract

The author uses geospatial analysis to examine the “educational opportunity spaces” of two adjacent urban neighborhoods in Pittsburgh, Pennsylvania. Organizing insights are gathered from Bronfenbrenner’s (1979) ecological perspectives on human development, which posit that students are significantly impacted by multiple environmental systems—including their immediate family and school surroundings and several other mutually affective layers of systems. The author suggests that while school and district-based reform initiatives targeting “within school factors” clearly have direct and significant relevance on student performance, neighborhood and community factors are also worthy of consideration. Based on analyses of multiple block-level data, several recommendations are made toward the further integration of school and community-based practice.

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Notes

  1. Drawing from Hopson et al. (2007), Kincheloe (2004), and Noblit and Pink (2007), I recognize “urban” as a complex and multifaceted term that includes both widely disseminated aspects of the term (high density areas, economic disparity, diversity of residents, and shortages of resources, etc.) as well as those that are often overlooked (cultural richness, resilience, perseverance, and intersectionality).

  2. Roosevelt resigned in the fall of 2010 in order to assume a leadership position in another state. Linda Lane, one of Roosevelt’s top assistants, was named his successor, ensuring that PPS would continue following a similar path.

  3. PPS students have options to attend schools other than those in their local neighborhoods, but most students enrolled in the schools noted here are from the Homewood and/or Squirrel Hill areas.

  4. According to the US Census Bureau, “Block groups generally contain between 600 and 3,000 people, with an optimum size of 1,500 people” (http://www.census.gov). Homewood has 13 block groups and Squirrel Hill has 21 block groups.

  5. It is also important to note here my focus upon public data. These highly impactful variables urgently beckon our attention, but do not reveal deeper family and neighborhood narratives about local assets and challenges (such as, for example, the works of Rogoff et al. (2001), Rogoff (2003) and Gutierrez and Rogoff (2003)). Both types of data are essential, but, in the interest of space, this paper focuses mostly on the former.

  6. According to the 2008 At Schools Report to the Community, attendance percentages were determined by dividing average daily student attendance by enrollment and the student stability rate represents the total number of students enrolled for the entire year divided by the total enrollment for the year. The higher the number, the more stable the student population.

  7. I used the crime related offenses of youth under age 17 because: (a) I wanted to provide a snapshot of youth crime amid the other adult-inclusive crime indicators that I mapped, and (b) it was not feasible to map the multiple hundreds of crime incidences in a clear visual manner.

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  1. University of Wisconsin-Madison, Madison, WI, USA

    Peter M. Miller

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Miller, P.M. Mapping Educational Opportunity Zones: A Geospatial Analysis of Neighborhood Block Groups. Urban Rev 44, 189–218 (2012). https://doi.org/10.1007/s11256-011-0189-7

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