Kimberly L. Barrett & Lyndsay N. Boggess, Ph.D. Friday, November 16, 2012 American Society of Criminology- 2012 Annual Meeting Chicago, IL.

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Presentation transcript:

Kimberly L. Barrett & Lyndsay N. Boggess, Ph.D. Friday, November 16, 2012 American Society of Criminology Annual Meeting Chicago, IL

Introduction Link in the literature between school environment & student performance (Gottfredson et al., 2005) School’s distance to Environmental Harms of special concern Does location of environmental hazards in Buffalo perpetuate school segregation and concentrated disadvantage?

Literature Review & Background Human Ecology vs. Race and Political Economy Function of the market (Been, 1994) or race and SES interact (Bullard, 1994) Schools and Proxy to Environmental Hazards Children extra sensitive to toxins (Landrigan et al., 2010) School Segregation, Environmental Hazards, and Buffalo 6 th most segregated city in the nation Love Canal, Bethlehem Steel, Allied Chemical

The Current Study Differentiates from prior environmental justice work by: Being the first to focus on schools in Buffalo, NY Studying years Hypothesizes: H1: Schools with Low SES significantly closer to hazards H2: School high in minority enrollment significantly closer to hazards H3: Over time, schools close to hazards will become significantly segregated and have lower SES Race and Political Economy Theory

Data Two Sources: Environmental Protection Agency (EPA) (n = 72) Envirofacts Database New York State Department of Education (n = 50) Obtained for Buffalo Public Schools, from DOE School Report Cards: NYSTART Database Only schools with complete data for ten years included (4 schools dropped: initial n = 54)

Measures Environmental Hazard Toxic Release Inventory (TRI) (n = 28) Facilities that use, manufacture, treat, transport or release and one of over 650 identified toxins Resource Conservation Recovery Act (RCRA) (n = 12) Facilities that generate, treat, transport, store, or dispose of hazardous waste Used RCRAs that “require corrective action”- in need of clean up response or program Comprehensive Environmental Response Compensation and Liability Act (CERCLA) (n = 32) Identify sites where mismanagement of waste occurs or has occurred

Measures School Segregation Race of students at each school and for district obtained for District Totals 2000: 56.8% Black; 29.5% White; 10.9% Hispanic District Totals 2010: 56% Black; 23% White; 15% Hispanic Socioeconomic Status (SES) % of students eligible for free lunch at each school for Used as proxy for SES District Total 2000: 66.5% of district eligible for free lunch District Total 2010: 70% of district eligible for free lunch

Method Use GIS to map schools and hazards # of meters to nearest hazard # hazards within 1 mile of school Obtain segregation score for each school and district as a whole (Stretesky & Lynch, 2002; Darden & Kamel, 2000) -1 = All white school & 1 = All minority Test H1 and H2 using Bivariate Correlations for years 2000 and 2010 H3 tested using OLS regression for each year

Results Location of Environmental Hazards and Public Schools in Buffalo Red = Hazard Blue = School

Results District Wide Segregation Scores for

Results H1: Schools with Low SES significantly closer to hazards H2: School high in minority enrollment significantly closer to hazards In 2000: only Hispanic Segregation marginally significant with # of meters to hazard, in opposite direction r =.247, p =.083) Similar results found for 2001, 2002, and 2003 only Hispanic score: r=.243,.258,.239, p <.10, respectively In 2010, neither minority composition or SES emerged as significantly related to proxy to hazard

Results H3: Over time, schools close to hazards will become significantly segregated and have lower SES Controlling for SES, as meters to hazard increase, segregation score increases (b = 1.5, p <.05) After controlling for SES and prior year’s segregation score, coefficient for meters to hazard drops below significance in 2001, 2002, and 2003

Results Additional Correlations Performed to Examine Percent Change in School Segregation Score & SES In 2001 & 2006: % change in Hispanic segregation score marginally significantly related to distance to hazard in meters in hypothesized direction In 2001 & 2006: % change in SES significantly related to distance to hazard in meters For 2004 & 2005: % change in Black segregation score significantly related to # of hazards < 1 mile, in opposite direction than hypothesized

Discussion Support for first and second hypothesis not found in this study Marginally significant in few cases, and contingent on year While Buffalo public schools appear to become increasingly segregated, this study does not find evidence that this is driven by proxy to environmental hazards Observations do not appear to support either the Human Ecology or Race and Political Economy perspective In fact, many of the significant relationships that emerge do so in opposite than hypothesized directions

Conclusions Findings unpredicted but not unprecedented: Krieg, 2005: No relationship between TRI sites & Black residents using zip codes in Buffalo Downey, 2005: Minority segregated communities less proximate to TRI sites than white communities in Detroit Paradox observed in “Rust Belt” Cities? Downey suggests: Socially Desirable “good”(employment) spatially tied to socially undesirable “bad” (pollution) segregation acts as a protective factor The group that monopolizes on the “good” over-exposed to the “bad”

Conclusions Implications: Buffalo must confront its segregation problem in schools & communities More environmental hazards in the city of Buffalo than schools Recommended that clean up endeavors should continue Future Studies: Continue examining environmental justice in other “Rust Belt” cities Continued theorizing about proxy to environmental hazards, race, and SES

Thank you!