Project NIA Paper.pdf

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Trends in Arrests of Chicago Youth, 2009-2012

Ashley Cook, Zygmunt Czykieta, Paul Mack, Chris Skrable

UNIV 410 - Introduction to Geographic Information Systems

Client: Project NIA

General Introduction

In the last 15 years, researchers, advocates, and educators nationwide have described

the existence of a “school to prison pipeline,” wherein harsh school discipline policies coupled

with in-school law enforcement feed troubled youth into the prison system (cf. project

assignment, “Background”). In previous research, most notably the 2011 report “ARRESTING

JUSTICE: A Report About Juvenile Arrests in Chicago 2009 & 2010” (henceforth “AJ”), our client

Project NIA has asserted that these processes disproportionately impact youth in certain police

districts (7), and suggested that youth of color may have been particularly targeted by these

patterns (1). This earlier research was hampered, however, by the unavailability of defensible

population estimates for Chicago youth (including demographic information) by police district .

This made critical analysis of youth arrest data -- aggregated by police district -- difficult to do.

Project NIA’s mission is “to dramatically reduce the reliance on arrest, detention, and

incarceration for addressing youth crime and to instead promote the use of restorative and

transformative practices, a concept that relies on community-based alternatives. Through

community engagement, education, participatory action research, and capacity-building, Project

NIA facilitates the creation of community-focused responses to violence and crime” (AJ 2).

Project NIA seeks to present relevant and timely data, including data analysis, to the public in

readily interpretable ways in order to mobilize community concern and activism surrounding the

issues relating to youth arrests. Using a GIS (geographic information system) is beneficial in this

case because representing youth crimes and arrests data using maps and interactive web



applications allows the general public to more easily grasp the issues at hand.

Our group used GIS (specifically ESRI’s ArcGIS package and ArcGIS Online) to achieve

the following goals:

1. Mapping and analysis of school day crimes and arrests occurring on Chicago Public

Schools (CPS) properties, with the further goal of making this data publicly available via

an interactive web application;

2. Development of estimates of the numbers of youth by race in each Chicago Police

Department (CPD) district;

3. Using the newly available youth population estimates to create a new series of maps that

illustrate patterns of juvenile arrests by CPD district;

4. Provide preliminary critical analysis of newly revealed patterns in youth arrests in

Chicago, offering suggestions for future research.

The following sections of this paper will share the methodologies by which we achieved these

goals, as well as summaries of our results.

Crimes and Arrests on CPS Properties (Academic Year 2011-2012)

Insofar as every crime and arrest is reported as occurring in a particular location, crimes

data can easily be plotted on a map. ArcGIS allows for quite sophisticated analysis of such

“located events” by spatial location and in relation to other spatially-defined realities. For this

portion of the project, we mapped documented occurrences of crimes/arrests (available from

the City of Chicago Data Portal, or CCDP) for the most recent academic year on the geographic

footprints of active CPS schools, then analyzed the results to estimate the numbers and types of

crimes (and arrest rates) occurring on CPS campuses.

Methodology



campuses. A spatial join was used to identify the 6,460 school day crimes occurring on CPS

properties during the parameters of AY 2011-2012; a pivot-table analysis on attributes/sums of

the resulting layer yielded the information presented in Table 1.

While the aggregate information presented in Table 1 is of value for analysis (see below),

Project NIA expressed the further goal of being able to share school-specific crimes and arrests

information with the general public through a generally available, web-based interactive map. To

this end, we created a map using ESRI’s ArcGIS Online. The map overlays general

transportation, building footprints, and landmark information (“Topographic” layer, ArcGIS Online)

with four custom map layers:

a graduated polygon centroids (point) layer, which represents 2011-2012 CPS campus

school day crime and arrest statistics per 100 students in 5 classes (divided by Natural

Breaks). This layer also documents incidents of the top 10 occurring crimes (cf. Table 1)

per campus, achieved by iterative spatial joining of specific crime information, aggregated

by general crime type, to the polygons of CPS campuses;

a polygon layer representing CPS campus footprints for AY 2011-2012, including full

enrollment and demographics information for each school aggregated by campus;

two selectable polygon layers that display the outlines of the 77 Chicago Community

Areas and 23 CPD Districts, respectively.

Selection of any feature on the map opens a pop-out information window with statistics related to

that feature. This map is now available publicly at http://bit.ly/16v8zrt. A screenshot from the

map, showing a pop-out of crimes data for Sullivan HS in Rogers Park, follows as Figure 1.

http://www.google.com/url?q=http%3A%2F%2Fbit.ly%2F16v8zrt&sa=D&sntz=1&usg=AFQjCNGNVwVGF3iGN2PFoaZ0kzLqYpPygg



Figure 1: Screenshot of “Crimes on CPS Campuses, 2011-2012” (ArcGIS Online)

Aggregate Results and Preliminary Analysis

Results of the aggregation of school day crimes and arrests data for all CPS campuses

are presented in Table 1:

Table 1: School-day Crimes and Arrests on CPS Properties, AY 2011-2012

Type of Crime

Total reported

Crimes on CPS

Property*

Total reported

Arrests on CPS

Property*

Arrest rate by Crime

Type

BATTERY 2098 675 32%

THEFT 1361 112 8%

ASSAULT 1072 276 26%

NARCOTICS 566 565 100%



CRIMINAL DAMAGE 311 30 10%

PUBLIC PEACE

VIOLATION 285 187 66%

CRIMINAL TRESPASS 167 84 50%

OTHER OFFENSE 140 19 14%

WEAPONS

VIOLATION 116 62 53%

ROBBERY 83 29 35%

MOTOR VEHICLE

THEFT 64 4 6%

DECEPTIVE

PRACTICE 39 6 15%

SEX OFFENSE 38 9 24%

BURGLARY 37 6 16%

OFFENSE

INVOLVING

CHILDREN 30 3 10%

LIQUOR LAW

VIOLATION 15 14 93%

CRIM SEXUAL

ASSAULT 14 3 21%

INTIMIDATION 6 2 33%

KIDNAPPING 6 0 0%

OBSCENITY 3 3 100%

GAMBLING 3 3 100%

ARSON 2 1 50%

PUBLIC INDECENCY 1 1 100%

INTERFERENCE

WITH PUBLIC

OFFICER 1 1 100%



STALKING 1 0 0%

PROSTITUTION 1 1 100%

Grand Total 6460 2096 32%

The fourth column on Table 1 presents arrest rates per crime type based solely on the crimes

reported in column 2, i.e. for CPS school-day crimes only .

A few preliminary observations may be made based on the data in Table 1.

Simple battery: In statistics included in our group’s project introduction, Project NIA

made reference to the fact that “[n]early a third (27%) of juvenile school-based arrest

offenses is simple battery,” suggesting that “a significant number of CPS students are

probably being arrested for fighting” (Project NIA/UNIV 410, Spring 2013). That

information and statistic was drawn from CPD data documenting arrest locations coded

as occurring on CPS property (i.e. school buildings, school grounds) for calendar year

2010. When analyzed by spatial location and filtered according to school-day,

school-time parameters, the data reinforce this estimate: in 2011-2012, simple battery

accounted for 32% of school day crimes and arrests on CPS campuses.

Alcohol/drug violations: Alcohol and drug violations accounted for 9% of school day

crimes, but for 28% of CPS arrests, with near 100% arrest rates for these offenses. This

suggests that stiff drug-related penalties in schools (possibly including mandatory

arrests) are a significant contributing factor in the school-to-prison pipeline.

Other high arrest rate crimes: Leaving aside the low-incidence/high arrest rate crimes

at the bottom of Table 1, the three highest arrest rate crime types in CPS schools in

2011-2012 after drug/alcohol offenses were disturbances of the peace (66%), weapons

violations (53%), and criminal trespass (50%). While there is no way of determining from



this data the percentage of these offenses that were perpetrated by non-students

intruding illegally on CPS property during the school day, the nature of these offenses

may suggest other instances of the criminalization of otherwise typical “schoolyard” bad

behavior: i.e., disrupting classes, carrying a weapon for protection or bullying, and

sneaking into areas of the school that are normally “off limits” to students.

Each of these points may suggest an area for further research.

A final, interesting comparison may be made by comparing per capita arrest rates on

CPS campuses with general arrest rates for their surrounding CPD districts. The following two

maps (Figure 2) show general, aggregate crime and arrest rate data for school year, daytime

crimes per district (broken into quintiles), with corresponding crime and arrest rate data for CPS

campuses (symbolized as circles) shown using the same category break points for purposes of

symbolization. Thus in Figure 2, disparities in color between any given campus and its

background district indicate a corresponding difference in crime or arrest rate.

Figure 2: Comparison of Crime and Arrest Rates, CPD Districts vs. CPS Campuses



A few points immediately leap to the eye when considering Figure 2. First, it is obvious

that the vast majority of CPS schools have lower rates of incidence of both daytime crime and

arrest than their surrounding districts, even when those rates are equivalently normalized (i.e.

per 100 persons or students). This disparity is particularly pronounced in the districts with the

highest crime/arrest rates. A few key campuses in each district buck this trend with higher crime

rates than their surrounding districts, particularly in the south and south central districts (e.g. 3,

4, 5, 6, 9). In the move to arrest rates, however, many of these slightly higher crime incidence

campuses show a greater degree of disparity from their surrounding districts (see, for example,

the sudden appearance of mid-to-upper quintile campuses in the north east districts (24, 20, 19,

17). This augmented differentiation--evidencing a heightened distinction between school and

district arrest rates vs. less distinct school and district crime rates--suggests that overall arrest

rates within CPS schools may well be higher than corresponding local arrest rates at similar

hours, further evidence of a school-to-prison pipeline, at least for some “hot spot” schools.

Again, this could well be an area for further research with more refined data.

Estimation of Numbers of Youth by Race for each CPD District and Youth Arrest

Information by Race for each CPD District

In addition to supplying Project NIA with CPS youth crime and arrest point-data, our group

also provided total youth arrest data and youth demographic data aggregated to the police district

level. Eventually this data was used to make the choropleth maps used in our analysis. Unlike

our previous CPS youth arrest point-data, the aggregate youth arrest data was supplied by

Project NIA through a Freedom of Information Act request to the Chicago Police Department and

reflects arrest data throughout the entire year as opposed to school time hours during the

academic year.



The PDF documents issued by the CPD detailing youth arrest data for 2009, 2010, 2011,

and 2012 were manually inputted into a CPD district shapefile downloaded from the Chicago

Police Department website representing Chicago’s 23 police districts. The youth arrest data

reported by the CPD in 2009 and 2010 was reported across 7 different racial categories: African

American, Asian / Pacific Islander, Black Hispanic, Caucasian, White Hispanic, Other, and

Unknown. For the purposes of this project, these racial categories were consolidated into four

categories: African-American, Caucasian, Hispanic (a summation of Black and White Hispanic),

and Other (a summation of all categories not previously listed). In our map displays, we focus

on the first three categories: African-American, Caucasian, and Hispanic, which constitute a

large majority of the reported racial information. The youth arrest data CPD supplied for 2011

and 2012 was reported slightly differently as they no longer reported an “Other” category, but

added a new category of “Indian.” Again, our group consolidated these 7 categories into the

same four simply putting the new category of “Indian” in our reported “Other” category. Thus,

there is consistency in the racial category information throughout the four years.

However, there were some temporal issues dealing with how Chicago defines its police

districts. In December 2012 Chicago changed the number of its police districts from 25 to 23

and the shapefile available on the Chicago Police District website reflected these changes.

However, the youth arrest information supplied by CPD in the Freedom of Information Act for all

four years of our study is reported by Chicago’s previous 25 police districts. The police district

shapefile is missing districts 21 and 23. However, it was discovered that the Chicago Police

Department had consolidated the 21st district into the neighboring 2nd district and had also

consolidated the 23rd district into the adjacent 19th district. Keeping this in mind, when inputting

youth arrest information from the CPD FOIA request, arrest data that occurred in the 21st district

were added to the 2nd district and arrest data which had occurred in the 23rd district were added



to the 19th to reflect the department’s administrative changes.

The above steps allowed us to display Chicago youth arrests for each police district by

race, but we still needed to add youth demographic information to our analysis to examine if

racial groups were being disproportionately arrested in particular districts. Thus, we were

required to estimate how many youth of each racial type lived in Chicago’s 23 police districts.

Census block information documents titled “ Hispanic or Latino, and Not Hispanic or Latino by

Race” and “Race for the Population 18 Years and Older” were downloaded from American Fact

Finder for the 2010 Census Redistricting data in the form of Excel tables. The first table which

showed racial information by census block for the total population was subtracted by the second

table which shows racial information by census block for the adult population to create a new

data set used in our analysis of youth racial information (for youth aged 17 and under).

Once we had created a dataset of where youth live by race which matched the same

parameters as our dataset of youth arrests, we needed to aggregate the census block

demographic data to the police district level to match our youth arrests data. First, we

downloaded a shapefile of Chicago’s census blocks from the city data portal and used census

block ID numbers to do a table join relating the dataset we had created detailing where youth live

by race to the census block shapefile. Then we performed a spatial join to sum all census

blocks located within a police district together to get totals of each youth racial category by police

district. However, the U.S. Census reports race differently than the CPD. The U.S. Census

reports many different racial categories, however again for the purposes of our analysis these

categories were consolidated into four categories: African American, Caucasian, Hispanic, and

Other. The U.S. Census category of “Hispanic or Latino” was used to create our Hispanic

category, the U.S. Census category of “Population of One Race: White Alone” was used to

create our Caucasian category, the U.S. Census category of “Population of One Race: Black or



African American” was used to create our African American category, and the U.S. Census

categories of “Two or More Races” as well as various “Population of One Race” categories were

all aggregated into our “Other” category, similar to how we had aggregated race information for

youth arrests.

In this way, we were able to display youth arrest information and information regarding

where youth live concurrently by police district. This information was used to create a variety of

maps illustrating patterns of youth arrests by police district used in our analysis.

Illustration of Patterns of Juvenile Arrests by CPD District

Figure 3 aligns total estimated youth population per CPD district with averaged total youth

arrests from the period in question (2009-2012). Districts have been broken into quintiles in both

maps. Comparison of the two maps suggests that the pattern of youth arrests in CPD districts

is not a simple correlate of the youth population in each district.

Figure 3: Youth Population and Average Youth Arrests by CPD District (All Races)



Figure 4: Average Youth Arrests (2009-2012) per 100 Youth by CPD District

Figure 4 normalizes average arrest data

(2009-2012) by youth population to reveal a

clearer pattern. Per capita, youth are

generally arrested at the lowest rates in

North Side districts, at the highest rates in

West Side and Central Business/Loop

districts (i.e. those districts most

frequented by tourists), at an intermediate

rate in the South-West Side

neighborhoods, and at intermediate to



higher rates on the South Side. Comparing figure 4 with figure 3’s map of raw average arrests,

we note that while the West Side districts (11, 15) have high total arrest rates that -- when

normalized by moderate youth population -- reveal what may be “youth arrest hotspots,”

whereas the Central Business/Loop districts (1, 18) have relatively low numbers of average

arrests but high per capita rates of arrest due to low native youth population (cf. figure 3, map 1).

This may suggest that different factors need to be considered to explain youth crime in the Loop

versus in the West Side districts, e.g. the distinction between crimes of opportunity (preying on

tourists) versus more “situated” crimes related to, for example, drug or gang activity.

Preliminary Exploratory Analysis: Patterns of Youth Arrests, 2009-2012

In their FOIA request to CPD and in their project parameters for our group, Project NIA

explicitly asked that consideration be given to possible correlations between arrest rates and the

race of the youth arrested. Raw arrest numbers certainly verify the importance of this. A simple

comparison of total youth population (by main racial groups) vs. total arrests (by race) for 2012

clearly illustrates that African-American and, to a lesser extent, Hispanic youth are arrested at far

higher rates than Caucasian youth (cf. Chart 1):

Chart 1: 2012 Youth Arrests vs. Youth Population Totals by Race



Expressed in per capita rates, in 2012 African-American youth were arrested 7.6 times per 100

youth, five times more frequently than Hispanic youth (1.5 arrests per 100 youth), and TEN times

more frequently than Caucasian youth (0.7 arrests per 100 youth).

Given that Chicago remains a highly segregated city by race, this raises the question of

whether or not the apparent pattern of race-based arrests is in fact an accident of location, e.g.,

do African-American youth just happen to reside in the highest arrest-rate districts? Figure 5

divides CPD districts into quintiles to represent the highest concentrations of youth population by

race in each district.

Figure 5: Concentrations of Youth Population in CPD Districts by Race



The above figure helps to illustrate the extent of Chicago’s racial segregation which is

reflected in its police district demographics. The majority of Caucasian youth reside on the North

side (with the exception of the 22nd district on the South side which includes the predominantly

Caucasian neighborhood of Beverly). The Hispanic Youth populations are most concentrated on

the South-West side. And most concentrated of all is the distribution of African-American youth,

which are the vast majority of youth living in many districts located on the South side.

Mapping the racial breakdown of youth arrests as a percentage of total youth arrests per

district (Figure 6) shows patterns that -- overall -- roughly replicate population patterns.

Figure 6: Racial Breakdown of Youth Arrests as a percentage of TOTAL Youth Arrests (2012)



However, a district by district breakdown of percentages of specific racial populations compared

against the percentage of arrests constituted by members of that racial group reveals far more

disturbing patterns (cf. Table 2):

Table 2: Comparisons by Race between Population and Arrest Percentages by CPD District (2012)

District Percent

African-

American

Youth

African-

American

Percentage

of Youth

Arrests

Percent

Caucasian

Youth

Caucasian

Percentage

of Youth

Arrested

Percent

Hispanic

Youth

Hispanic

Percentage

of Youth

Arrested

1 32.70% 89.50% 35.10% 2.50% 9.01% 6.84%

2 81.60% 96.90% 8.25% 0.68% 3.48% 1.45%

3 94.40% 99.30% 1.10% 0.30% 2.05% 0.22%

4 59.90% 86.10% 3.28% 1.22% 35.40% 12.10%

5 95% 98.90% 0.32% 0.31% 3.95% 0.77%

6 97.10% 99.50% 0.19% 0.08% 1.51% 0.15%

7 96.70% 99.90% 0.14% 0.07% 1.92% 0.07%

8 19.90% 59.60% 9.23% 4.83% 69.40% 35.20%

9 12.80% 52.90% 6.63% 6.12% 69.50% 40.50%

10 29.50% 61.60% 0.92% 1.05% 69.10% 37.10%

11 84.80% 98.10% 0.93% 0.22% 12.90% 1.49%

12 23.30% 52% 11.30% 1.57% 59.40% 46.30%

13 25.10% 70.50% 24.50% 3.41% 36.50% 26.10%

14 10.60% 35.10% 18.90% 6.44% 66.50% 57.80%

15 93% 99.50% 0.71% 0.14% 4.93% 0.41%

16 1.10% 17.50% 55.40% 39.50% 35.10% 40.80%

17 3.48% 28% 25.80% 13.10% 57.70% 57.30%

18 21.10% 91.50% 60.10% 2.58% 7.01% 4.94%



19 11.80% 60.50% 61.70% 14.80% 16.30% 23.50%

20 12.90% 69.80% 34.80% 0% 32.20% 29.40%

22 60.50% 95% 32.40% 3.61% 5.19% 1.29%

24 20.40% 70.70% 27.20% 4.41% 32.10% 22.50%

25 15.40% 46.80% 6.07% 4% 76.50% 48.80%

As Table 2 illustrates, even in districts in which Caucasian youth arrests as a percentage

of total youth population are relatively high (like in district 16), the percentage of Caucasian youth

arrests never exceeds the percentage of Caucasian youth living within in the district. In fact, in

many cases the percentage of Caucasian youth arrests of total youth arrests within a district is

well below the percentage of Caucasian youth living within that district, as is the case in districts

such as: 1, 13, 17, 18, 19, 22, 24.

In comparison, African-American percentage of total youth arrests exceeds the

percentage of African-American youth living within the district for all 23 CPD districts. And in

some CPD districts the disparities are quite large such as in areas near the loop (districts 1, 13,

and 18), districts on the South West Side that have large Hispanic populations living there

(districts 8 and 9), and in the North Side that have large Caucasian populations (districts 19, 20,

and 24).

As Table 2 shows, the only Police Districts for which the Hispanic percentage of total

youth arrests were higher than the percentage of Hispanic youth living within a district are

districts 16 and 19, both located on the North side. Other districts had percentages of Hispanic

youth living within a district higher than Hispanic percentages of total youth arrests - though

differences are considerably less than they are for Caucasian youth - with some Hispanic

districts having roughly proportional percentages.



In conclusion, African-American youth are arrested in greater proportion than their

populations represent throughout the entire city, Hispanic youth are arrested in greater

proportions in a few districts on the North side, and Caucasian youth are arrested in smaller

proportions than their population represents throughout the entire city. This in large part reflects

the raw numbers of arrests for each racial group which can be seen in Chart 1.

But if we wish to examine where youth racial groups may be being targeted the most

relative to where they live - we can use a ratio method to explore these patterns. The following

series of maps - Figures 7,8, and 9 perform this analysis. The youth arrest numbers by race is

divided by the total youth population for that race per 100 people. These ratios highlight where

youth of a racial group are arrested the most relative to where this youth racial population group

lives.



Figure 8: Per Capita African-American Youth Arrest Rates, 2009-2012

Figure 8 shows that the highest ratios of African-American youth arrests occur in Police Districts

16, 17, 18, and 1 which are all police districts with majority Caucasians on the North side and

downtown. In 2011 and 2012, there is also a relatively high ratio of African-Americans being

arrested in district 9 - which is majority Hispanic.



Figure 9: Per Capita Hispanic Youth Arrest Rates, 2009-2012

Figure 9 shows that the highest ratios of African-American youth arrests occur in Police Districts

1, 12, 19, and 20 which, like those of the African-American ratios, are all police districts with

majority Caucasians on the North side and downtown.

These ratio maps highlight where youth are arrested at higher rates than their populations

represent. In general, it appears that African-American youth and Hispanic youth are both

arrested at higher ratios in North side neighborhoods with large Caucasian youth populations and

also near downtown. The highest ratios of Caucasian youth arrested per 100 Caucasians occur

on South side majority African-American districts and on the West side in district 15 which



contains the majority African-American neighborhood of Austin. Interestingly, Hispanic youth not

arrest ratios are not particularly high in majority African-American districts and African-American

arrest ratios are not particularly high in majority Hispanic police districts (with the exception of

district 9). Caucasian arrest ratios are highest in African-American majority districts, but are

also relatively high in Hispanic majority districts. Proportionately, youth are arrested at higher

rates in districts with demographics different than their own - but African-Americans and

Hispanics are arrested in higher ratios in Caucasian majority districts and not in each others

districts. This is potentially an area for further research with additional data.

Finally, we considered rates of change in juvenile arrest rates, city-wide, across the

period for which we had data (2009-2012). Overall arrest trends have been downward

throughout this period, as evidenced on Figure 10:

Figure 10: Rate of Change in Total Youth Arrests, 2009-2012



Given the racial dynamics that so prominently color arrest rates, we were curious to see

if each of our major races evidenced the same trend. Figure 11 compares the three races’ rates

of change in arrest rates across 2009-2012. Further refinement of these maps would allow for

more accurate comparisons by scaling the breaks on each map to match; however, it is notable

that overall arrest rates are downwardly trending for ALL races on the North (especially

northwest) side of the city. And while the Caucasian rates of arrest “top out” at a slight (0.02%)

increase in arrest rates, Hispanics and African-American rates show wider variety, with

maximum changes of 0.08% for Hispanics and 0.34% for African-American youth, replicating

general patterns evinced in earlier data (cf. Chart 1). Again, there is room for considerable

additional research regarding the factors contributing to this trend.

Figure 11: Rates of Change in Total Youth Arrests by Race, 2009-2012



Final Methodological Note

Our youth arrest data, provided in response to two FOIA requests from Project NIA to

CPD, spans four years (2009 -2012). However, all of our youth population estimates are taken

from 2010 US Census data (downloaded from American Community Factfinder). In the future, it

may be helpful to adjust youth population estimates using the American Community Survey for

each respective year - if it is to be believed that youth demographics might shift considerably

from year to year in the communities being considered.

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