Senior research project looks at multiple characteristics often not discussed in the conversation around educational achievement in Chicago public schools. This project explored factors, often considered secondary, to variables that impact/influence success of a student in Chicago.

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Educational and financial disparities in Chicago
neighborhoods
Mia Harris, Wake Forest University, April 2017
Chicago has a strong history of racial segregation, since the
Great Migration in the first half of the 20th century, political
and physical boundaries divide the city and continues to do
so. For this project, I looked at the economic, social, and
educational disparities that exist throughout Chicago at the
neighborhood level. A city nick-named “melting-pot,” has
undergone systematic isolation of cultures to the point
where neighborhoods are named after the majority
ethnicities that occupy them (Little Italy, Greek-town,
China-town, etc.) Explanations for socio-economic
disparities are often placing blame on the work ethic and/or
lack of education of the community of interest. The
following maps are to contradict this explanation and to
provide an alternative perspective; in doing so, change the
approach in Urban development planning ultimately
increasing the level of operational and sustainability
growth.
Introduction
Methods
Results
Chicago has undergone countless urban development projects
over the past decade. Often times leading to gentrification
which has consistently forced many community members to
relocate because of rising property taxes, rent, and X. After
comparing high school graduation rates, per capital income,
and transportation accessibility between Englewood and
Uptown neighborhoods it is possible that the focus of Urban
development projects are misdirected. Extending research
further would look at quality of education funding and
supplemental assistance to targeted under-resourced
neighborhoods. The current solution to shrinking socio-
economic disparities in Chicago relies heavily on the influx of
new affluent residents. This project brings a different
perspective to urban planning and ultimately a new way to
approach urban development projects.
Conclusion
Results
Austin
South Deering
Ashburn
Englewood
Roseland
New City
O'Hare
Hegewisch
Dunning
Beverly
Little Village
Riverdale
Chatham
Norwood Park
Portage Park
Clearing
Humboldt Park
Uptown
Irving Park
Garfield Ridge
Lake View
West Lawn
West Pullman
Morgan Park
Belmont Cragin
South Shore
Garfield Park
North Park
South Chicago
West Ridge
Grand Crossing
Loop
Gage Park
Avondale
Douglas
North Lawndale
West Town
Logan Square
West Loop
Lower West Side
Little Italy, UIC
Albany Park
Woodlawn
Galewood
East SidePullman
Chicago Lawn
Auburn Gresham
Brighton Park
Bridgeport
Lincoln Park
Lincoln Square
Jefferson Park
North Center
Mount Greenwood
Washington Heights
Sauganash,Forest Glen
Hyde Park
Archer Heights
Edgewater
Hermosa
River North
Kenwood
Calumet Heights
Avalon Park
Grand Boulevard
Bucktown
Montclare
Mckinley Park
West Elsdon Washington Park
United Center
Wicker Park
Near South Side
Rogers Park
Oakland
Old Town
Burnside
Jackson Park
Fuller Park
Edison Park
Streeterville
Armour Square
Chinatown
Museum Campus
Grant Park
Andersonville
Gold Coast
Ukrainian Village
East Village
Wrigleyville
Sheffield & DePaul
Boystown
Millenium Park
Printers Row
Greektown
Streeterville
The collection of data was obtained
from multiple sources and was
condensed based on FID numbers. In
cases when an FID number was
unavailable or did not match up with
multiple data sets (occurring most
often when referencing census block
data), the census block information
was crossed referenced with its
respective neighborhood and then that
name to its corresponding FID
number. Fortunately, only one
shapefile was required to project the
data and as such this project there was
no need to change/alter the reference
system.
To compare the relationship between
the variables represented in the maps
two neighborhoods were used as
models, Englewood (on the south side
of Chicago) and Uptown (on the north
side of Chicago). Both communities
have populations greater than 30,000
and are a fair representation of racial
disparities based off of demographic
data gathered from the 2010 census.
¯
Legend
Grocery Stores/Population
Grocery Stores/Population
< -1.5 Std. Dev.
-1.5 - -0.50 Std. Dev.
-0.50 - 0.50 Std. Dev.
0.50 - 1.5 Std. Dev.
1.5 - 2.3 Std. Dev.
Per capita Income
Per capita Income
0.0
0.010 - 20000
21000 - 29000
30000 - 43000
44000 - 72000
Food and economic disparities within Chicago neighborhoods
Age demographic of Chicago neighborhoods
Education accessibility within Chicago neighborhoods
Legend
Chicago Public Schools
CTA_RailLines
Percentage of population without a high school diploma
16 - 23
24 - 32
33 - 38
39 - 41
42 - 50
0 4 8 12 162
Miles
0 4 8 12 162
Miles
0 4 8 12 162
Miles
¯
¯
Age demographic of Chicago
neighborhoods:
This map overlays the percentage of people
18> and <65(shown in red) and the
location of Chicago Public Schools (CPS)
throughout the city. The black bold line
running through the map is the city’s
public train line
Age and economic disparities
within Chicago neighborhoods:
This map overlays two variables,
the per capita income (displayed in
orange) and the ratio of groceries
stores to the neighborhood’s
population as a standard deviation
(displayed in blue). The magnitude
of overlap represents ease of access
to food and a higher economic
class.
Education accessibility within
Chicago neighborhoods:
This map details the percentage
of people who have not
obtained their high school
diploma and the locations of
public/private schools within
the city. The data doesn’t
consider persons which have
obtained their GED. The
likelihood that a neighborhood
block has a lower high school
graduation rate and lacks an
adequate number of public or
private schools is slim.
However this relationship in
characteristic of many
neighborhoods in Chicago
Englewood Uptown City
Populations 30,654 56,362 2,722,000
Area (Square
miles)
3.089 2.351
234
Per capita
Income
$11888 $35787
$33437
# of Public
Schools
32 7
660
# of Private
Schools
7 7
404
Age: 18<, and
65<
43.4% 22.2%
33.4%
No high school
diploma
29.4% 13.6% 18.9%
Uninsured 20.6% 20.3% 18.5%
This set of data is based on a city-wide survey conducted by the Chicago Department of
Health in 2012 and census data from 2010.
Chicago Data Portal, Data.Goc, Census.gov, Epidemiology and Public
Health Informatics, Chicago Department of Public Health, and
Censusreporter.org