Paige Colton
11-11-11
Assignment 6: Initial Project Description and Data Documentation
1. Description
For this project I am going to make a map of neighborhoods with major nonprofits and
churches, a series of maps that show demographic change in Boston over time, and hopefully
some series of maps which shows school enrollment, openings and closings, and potentially
racial breakdown as well. I hope to answer the question of how Boston has changed racially
(and potentially how income distributions have changed as well) over the past 50 years. In
addition, I would like to answer the question of how the school system has changed over the
same time period.
2. Annotated Examples
It was actually surprisingly difficult to find GIS research related to my topic (schools,
desegregation, and racial demographic analysis), so I apologize if some of the papers listed here
are not entirely relevant. I did learn something for each that I think helps me better understand
interesting avenues of analysis that can be done using the data I will be using.
Sohoni, D. and S. Saporito. 2009. Mapping School Segregation: Using GIS to Explore Racial
Segregation between Schools and Their Corresponding Attendance Areas. American Journal
of Education 115(4), 569-600.
By using GIS data, Sohoni et al. found that there is greater segregation in public schools than in
the neighborhoods they draw from, and that public, charter, and magnet schools increase this
segregation. The paper describes their process of finding school district polygons (by either
using shape files provided by the school districts or by tracing paper maps), georeferencing
them to TIGER data, and overlaying these areas on top of Census block level data. In this case
they look at the Census data to determine what the racial distribution of a school would be if
every student in its catchment area attended this school, compared with the racial breakdown
in the enrollment data for the schools. This paper provided me with two good school data
sources: the Common Core of Data (CCD) and the Private School Universe Survey, from the U.S.
Department of Education’s National Center for Educational Statistics. While the data doesn’t
go farther back than the 90s, it does have information on racial breakdowns by grade for all
schools.
Crowder, Kyle, and Scott South. 2008. Spatial Dynamics of White Flight: The Effects of Local
and Extralocal Racial Conditions on Neighborhood Out-Migration. American Sociological
Review 73.5 (2008): 792-812.
This paper is looking at the theory of “White flight” to determine if characteristics of areas
surrounding a neighborhood play a role in White out-migration. Crowder et al. uses
neighborhood-level Census data and individual-level data from the Panel Study of Income
Dynamics. It is interesting because they are able to track the residences participants of the
Panel Study of Income Dynamics to determine where they moved. They find that increasing
diversity in surrounding neighborhoods increases white out-migration, but high levels of
diversity in surrounding neighborhoods decreases out-migration (suggesting that this large
diversity provides less choice in where to migrate). While this doesn’t exactly relate to my
topic, it provides a possible way to explain the demographic change in Boston overtime and
contributes to my understanding of “white-flight,” which occurred during the desegregation
process.
Logan, J., Zhang, W. and H. Xu. 2010. Applying Spatial Thinking in Social Science
Research. GeoJournal 75.1: 15-27.
This paper discusses the implications of spatial analysis when doing social science research. In
particular, the authors have a section on looking at residential segregation. They discuss how
the size of segregated neighborhood matters when determining the level of segregation in an
area and also how spatial analysis can help define a neighborhood beyond simply using political
boundaries.
Hough, G. C. and R. Proehl. 2001. School Enrollment, GIS and Census 2000. Paper presented
at the ESRI Education Conference, San Diego, 2001. Population Research Center, Portland
State University.
This paper describes the possibilities with using Census 2000 data to analyze school enrollment.
The purpose is to describe how to administrators and school districts how to use Census data to
determine policy. It also describes a case study completed to determine reasons for declining
enrollment in Portland Public Schools. They used the Census data combined with birth rates to
determine that decreasing birth rates and a decreasing number of women of child bearing age
led to declining enrollment. This paper shows the relatively simple analysis that can be done
using Census data to look at education. It is not extremely detailed, unfortunately, and only
hints at more interesting research that could be done.
Nancy Hudspeth. 2003. Gentrification and Decline in Chicago: Defining Neighborhood Change
with Census Data. College of Urban Planning and Public Affairs, Great Cities Institute
University of Illinois at Chicago.
<http://www.uic.edu/cuppa/voorheesctr/Gentrification%20Index%20Site/Main%20Neighborhood%2
0Change%20Revised.htm>.
This paper is part of a project called “Interpreting Neighborhood Change in Chicago” conducted
by the Nathalie P. Voorhees Center for Neighborhood and Community Improvement at the
University of Illinois. Hudspeth is examining a number of variables using Census data in an index
in order to determine patterns of gentrification in Chicago over the past 40 years. In relation to
my project, she notices what she calls “significant shifts in race and ethnicity.”
3. Conceptual description of process
For the NGO map, I am working with Donna to narrow down the organizations into a more
reasonably sized list and then will map these points over Census block data (potentially showing
population densities or racial breakdowns?).
For the demographic change maps, I will be using dot densities to map different racial
categories per decade. I could potentially compare demographic statistics between the time
periods to have more numerical data, though I’m sure there is more that could be done to
compare these quantitatively.
For the school maps, I will be finding data on school location change over time (hopefully),
on enrollment and racial breakdown, and school zones. I think looking at change over time
would be a good way to view this data. Mapping percent white per school using different sized
dots would be one way to display this data. Looking at income levels of students would also be
potentially useful (maybe looking at the free lunch programs like we discussed).
4. Data layers
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NGO map:
o NGOs: Reference USA
o Census 2010 SF1
Demographic change map:
o Census Geolytics and Census 2010 data, short-form and long
Schools map
o MassGIS schools data set
o Common Core of from the Dept. of Education
o Private School Universe Survey from the Dept. of Education
o Data from the Boston Public School system (I will need to contact them to ask for
data, especially historical data)