Kimberly L. Barrett & Lyndsay N. Boggess, Ph.D.
Friday, November 16, 2012
American Society of Criminology- 2012 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
 6th 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 2000-2010
 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 2000-2010
 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
2000-2010
 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 2000-2010
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!