Mapping Indexed Violent Crime
Mapping Indexed Violent Crime in Salinas, CA
Gregory Giovannoli
Social and Behavioral Science
Capstone Project
California State University Monterey Bay
Capstone Advisor: Dr. George Baldwin
Capstone Facilitator: Dr. Rebecca Bales
Capstone Third Committee Member: Dr. Yong Lao
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Mapping Indexed Violent Crime
Abstract
This is a descriptive study that uses Geographic Information System to answer three questions
about crime in Salinas California: 1) Does more indexed violent crime occur in the first two
concentric zones of the city of Salinas, CA? 2) Are the gang territory boundaries in areas of
Salinas with higher poverty levels? 3) Does more violent crimes happen within gang territory
boundary lines? Concentric Zone Theory, Interactional Theory and Conflict Theory are the
theories providing the theoretical framework to answer the three research questions. I
hypothesize the data models created in this study provide conclusive evidence that Concentric
Zone is an effective model to use when studying crime within a city, while theories like
Interactional Theory and Conflict Theory can be used as ways to describe the societal impacts on
crime.
Keywords: Geographic Information System, indexed violent crime , Concentric Zone,
Interactional Theory
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Mapping Indexed Violent Crime
Introduction
This capstone project is a descriptive study of gang hotspots and indexed violent
crime in Salinas, CA. A hotspot is defined as an area in which something happens with a high
occurrence. For the purpose of this research paper, the “something” will be gang involvement in
a given area. This research paper is a compilation of demographic data of Salinas, CA and maps
of that data as a geographic information system. It will also compare indexed violent crime and
gang hotspots. While Interactional Theory and Concentric Zone Theory will be used for midlevel analysis, Conflict Theory is the macro theory applied to the interpretation of the maps.
Conflict theory centers around the idea that society is divided into groups with competing values
and interests. There are conflicts like rich versus poor, corporations versus labor, whites versus
minorities, etc. “In many cases, competing interest groups are not equal in power and resources,
and consequently one group is dominant and the other is subordinate” (Bohm, 2001, p.110). One
major advancement conflict theorists brought to criminological theories is the awareness of the
role power plays in society.
This study has three research questions: 1) Does more indexed violent crimes get
reported within the first two concentric zones of the city of Salinas? 2) Are these areas of gang
territories boundaries in areas with higher poverty levels than the rest of Salinas? 3) Does more
of the violent crime happen within the gang territory boundaries? A multi-layered Geographic
Information System was produced and analyzed to help answer these three questions.
These data maps and information produced by the results of this capstone research
project could help the city of Salinas, CA on a variety of levels: 1) civic, this project could go a
long way in helping community leaders, city planners and emergency services, establish a
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method for allocation of services, types of funding, potential redevelopment and revitalization
projects. City officials and leaders could benefit because these maps could dispel mis-truths and
assumptions attributed to the entire city, when in reality, only particular parts of the city have a
problem, like Weisburd, et all, found in the results of his 16 year study, “1% of street
segments… associated with 23% of crime in the city during the study period”. 2) police, we
already know that most major cities report having some sort of gang problem. With Salinas
Police Chief acknowledging April 30, 2015 that the under-manned Salinas Police Department
was going to be restructured to accommodate the lack of patrol officers, this project would help
precincts determine where to focus the energy of the force that are available. A program initiated
in Memphis, Tennessee, as an example, where “the system ostensibly helps law enforcement
better target its scarce resources” (Mayer-Schonberger, Cukier, p.158). Who say, “Since its
inception in 2006, major property crimes and violent offenses have fallen by a quarter”.
Literature Review
This literature review will be detailing prior findings and contributions to the following
topics: 1) gangs, 2) gang theory and conflict theory, 3) the uniform crime report, 4) crime
mapping, 5) democratizing of data.
Gangs
This section reviews one of the major problems in researching gangs. There is no
universal definition, so depending on the background and field of research of the researcher the
definition varies. The psychologist will focus more on the self, while the sociologist would be
focused on the group dynamics. Even those involved in law and government have troubles,
Spergel (1995) writes, “Definitions in different states and communities determine, in part,
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whether we have a large, small or even no problem…”(Spergel, 1995, p.17). Here, Klein (1995)
cites Gil Geis’s etymology of the word “gang” that says, “the early English usage of gang was a
going, walking or a journey” (Klein, 1995, p.22). While general information resources like
Oxforddictionaries.com simply states gangs as, “An organized group of criminals”. Another
source for general knowledge, Wikipedia goes into a bit more detail,
A gang is a group of recurrently associating individuals or close friends or family
with identifiable leadership and internal organization, identifying with or claiming
control over territory in a community, and engaging either individually
or collectively in violent or other forms of illegal behavior.
We use these common reference definitions as points of reference to understand how the general
public views the societal problems we study. One of the more simply stated, but most thorough
definitions the researcher found is this one from Klein, and Maxson, (2006): “A street gang is
any durable, street-oriented youth group whose involvement in illegal activity is part of its
groups identity” (Klein & Maxon, 2006, p.4)
Because of the inclusion of law enforcement agencies in the research, it’s appropriate to
determine how local and federal agencies define gangs. Ebensen, Tibbetts, and Gaines (2004)
give The National Youth Gang Survey’s definition of gang:
A group of youth in your jurisdiction that you or other responsible
persons in your agency or community are willing to identify or
classify as a gang. DO NOT include motorcycle gangs, hate or
ideology groups, prison gangs or other exclusively adult gangs
(Ebensen, et al, 2004, p.95).
Gang Theory and Conflict Theory
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The following section reviews the literature on theories of gangs. There are many social
theories out there to try and describe why individuals become involved with the gang subculture
and the violence and criminality that accompanies it. In this paper the researcher will focus on
Conflict theories, but there are Integrated theories, Marxist theories, Social Structural theories
and Social Process theories. According to Robinson (2004):
Social Structural theories include anomie and strain theories,
social disorganization and ecological theories, and cultural
deviance or subcultural theories. Social Process theories
include social learning theories and social control theories
and labeling theories…(Robinson, 2004, p.222).
Some of the theories from some of the earliest work in sociology and psychology hold
truths that apply all these years later. In Criminological Theories Understanding Crime in
America, Anderson, and Laronistine (2002) write that, “Quetelet’s contribution to crime is well
documented. He argued that social forces influence the occasion of crime (Quetelet, 1831)”
(Anderson & Laronistine, 2002, p.103).
The Marxist criminologist views criminality as inequalities and instabilities within
society. “Marx believed that with the inherent inequities built into Capitalism, class struggles
between the “haves” and the “have nots” are inevitable” (Anderson,and Laronistine, 2002,
p.224). Essentially, they believe that the system is set up for certain segments of society to
succeed or to fail. “In The Social Reality of Crime (1970), Quinney argues that criminal
definitions are generally formulated by those with power and influence” (Anderson &
Laronistine, 2002, p.226).
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The macro theory used by the researcher in this paper is Conflict Theory. This theoretical
approach centers around the idea that society is divided into groups with competing values and
interests. There are conflicts like rich vs poor, corporations versus labor, whites versus
minorities, etc. “In many cases, competing interest groups are not equal in power and resources,
and consequently one group is dominant and the other is subordinate” (Bohm, 2001, p.110). One
major advancement conflict theorists brought to criminological theories is the awareness of the
role power plays in society. The Conflict theory had its origins out of Marxist criminological
theory but differentiates itself with one key element, conflict theorists do not desire the end of
capitalism like Marxist theorists.
There has been a multitude of contributors to the theory. Thorsten Sellin focused on the
conflict of behavioral norms among different subcultures. George Vold revolved around the
groups conflicts of interests. Ralf Dahrendorf described it as the norms that are created by
authority or the people with institutionalized control. Austin T. Turk adds the “distinction
between cultural norms, which relate to the verbal formulation of values, and social norms,
which concern actual behaviour”(Jones, 2013, p.185). Richard Quinney’s adaptation to conflict
theory was arguing “whatever the physical reality may be, it was the social reality that mattered:
the processes by which a collective meaning of crime came to be established and
maintained”(Jones, 2013, p.186).
A theory used for mid level analysis was the Concentric Zone Theory. This theory was
established by Park and Burgess of the Chicago School in the early part of the 1920’s. The
concept of the concentric zones is that rings band out from the center zone, known as the central
business district. The next ring is the factory zone, followed by the zone in transition. The last
three are the working class zone, residential and commuter zones. The original study determined
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that most of the deviant behavior was occurring between the central business district and the
zone in transition. Then lessened as you got out from the center of the city.
A second theory used for mid-level analysis was the Interactional Theory. This theory
was developed by Terrence P. Thornberry in 1987 as a cross between Social Control Theory and
Social Learning Theory. Its basic premise is that gang membership results when there is a
reciprocal relationship between individual or peer group and social structure.
The Uniform Crime Report
The Uniform Crime Report (UCR) is “an annual compilation of data on U.S. crimes and
arrests based upon information provided to the Federal Bureau of Investigation (FBI) by local
law enforcement agencies” (Blumstein & Wallman, 2000, p.3). This research project will use the
UCR program because it is data collected by agencies as crimes are cleared by police. The
Uniform Crime Report defines violent crime as “murder and nonnegligent manslaughter, forcible
rape, robbery, and aggravated assault. (http://www.fbi.gov/about-us/cjis/ucr/crime-in-theu.s/2011/crime-in-the-u.s.-2011/violent-crime/violent-crime). One major drawback of the UCR
is that its singular incident reporting,. If multiple offences occur, only the more serious gets
recorded in the FBI statistics. For this research,the UCR seems more reliable than the National
Crime Victimization Survey (NCVS), another crime data collection tool. The NCVS is collected
data from respondents to telephone surveys by the Department of Justice. One major reason to
reject the use of the NCVS for this research is the absence of murder statistics.Another reason is
it could be a less viable source because data statistics are based on the victim’s volunteering the
information to authorities.
Murder and nonnegligent manslaughter, forcible rape, robbery, and aggravated assault
make up the four components of indexed violent crime. “Violent crimes are defined in the UCR
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Program as those offenses which involve force or threat of force” (http://www.fbi.gov/aboutus/cjis/ucr/crime-in-the-u.s/2011/crime-in-the-u.s.-2011/violent-crime/violent-crime).
Crime Mapping
Now that gangs and crime are defined, the next section is crime mapping, crime analysis
and the Uniform Crime Report. To fully understand crime mapping and analysis there are a
number of concepts to discuss. Two key terms found in the title, crime mapping and hotspot,
need to be defined
The idea of mapping crime has been around for centuries. But gone are the wall maps of
yesteryear, hanging in the detective's office with colored push pins, each color identifying a
particular crime, jabbed into approximate locations of crimes. The idea of crime mapping is now
a science. Today, “crime mapping is the process of using a geographic information system to
conduct spatial analysis of crime and disorder problems as well as other police related issues”
(Santos, 2013, p.5). There are many programs available to perform these spatial analysis and a
common misconception is that GIS is one of the programs. In actuality “A GIS is best defined as
a system which uses spatial database to provide answers to queries of a geographic nature, the
generic GIS that can be viewed as a number of specialized spatial routines laid over a standard
relational database management system”(Huxhold, 1991, p.28).
Santos describes what the analysis is and how it might be used:
“crime analysis is the systematic study of crime and disorder
problems as well as other police-related issues- including socio
demographic, spatial, and temporal factors- to assist the police in
criminal apprehension, crime and disorder reduction, crime
prevention and evaluation” (Santos, 2013, p.5).
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While the capabilities of GIS can prove to be an excellent tool, there are some inherent
dangers. The main one being that the information in the data sets that support the maps, are
geocoded data. If the data is put into the database incorrectly, your maps will be flawed. Vann
and Garson explain, “Because GIS maps are developed from layers of information, the final
product is only as good as the data in the composite layers” (Vann, & Garson, 2001, p. 478).
Democratization of Data
The idea of the democratization of data is not brand new. In the 1970’s and 1980’s a
social movement group, pushing for community reinvestment, were able to take data, that was
made available by the Home Mortgage Disclosure Act and analyze bank lending patterns to
reveal racial biases in how banks were lending. Today, a third party company “AirSage crunches
15 billion geo-loco records daily from the travels of millions of cellphone subscribers to create
real-time traffic reports in over 100 cities across America” (Mayer-Schonberger & Cukier, 2013,
p.90). The idea of big data is only getting bigger. “According to IBM, ninety percent of the
world’s data has been generated in the past two years” (Joh, 2014, p.39). Big data is defined as
mass volumes of data created digitally in real time. It is so voluminous in fact, Wang & Yuan
write:
“as of 2003 humans have created a total of 5EB data, while in the
year 2011, the amount of data that had been copied and produced
is exceeded 1.8ZB. It is expected that by 2020 will reach 35.2ZB,
which needs 37.6 billion hard drives of 1TB capacity to
store”(Wang & Yuan, 2014, p.55).
Just to try to put those numbers in perspective, a song that is downloaded onto an iPhone
takes roughly 4MB of storage space. A gigabyte equals 1,024MB or roughly 250 downloaded
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songs. One Terabyte equals 1,024GB or 1,073,741,824MB or roughly 250,000 downloaded
songs. Now multiply those 250,000 downloaded songs by the 37.6 billion 1TB hard drives, that’s
a lot of downloaded songs. The data is being collected and stored, and then reused or mined.
Companies are now gaining perspective on the importance of this data to their business. Big
retail corporations like Amazon online, and Target or Walmart use this big data to monitor
shopping habits and use those habits to offer coupons for items we purchase or like items we
purchase. It gives these chains the ability to stock the right products in their stores. One study of
data by Walmart showed an increase in particular non-perishable foodstuffs in the southsoutheast region, when a hurricane is forecasted. Another bright spot to big data, Big data and
data mining is creating a job market. A story written by Anne Fisher on Fortune.com, “statistics
is the fastest growing STEM major in the US” the article continues, “the number of
undergraduates majoring in statistics has nearly doubled in the past four years”
In the world of public policy big data provides necessary data for cities and
municipalities to improve or justify not improving. It also allows the community organizations to
gain access to the knowledge required to force a change, but at a huge disadvantage. For the
most part, the community organizations lack the same skill at turning the data into knowledge
and thus turning that knowledge into effective policy. Sawicki and Craig explain
“we are interested in a particular type of community:
organizations serving resource poor communities… such
community groups are not technologically sophisticated.
Professional planners and policy makers know how to turn
data into information, information into knowledge, and
knowledge into policy… too often the data they
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Mapping Indexed Violent Crime
(community groups) need are available only from media
that require substantial technical skills to read, then more
skills to manipulate that data into something
meaningful”.(Sawicki, & Craig, 1996, p.513).
They go onto describe a “provider” that these communities can use to take these data sets
that these community groups need to effectively mine the data useful for their needs. The hope
would be that these intermediaries would help the community organizations become more active
and informed participants in the policy making process.
One major development in the community organization becoming armed with big data
and ready to make change happened in the 1970’s and 1980’s. During the 1970’s people in
certain neighborhoods were being rejected for loans and mortgages based on the neighborhoods
which they lived. A community reinvestment movement group wanted to explore what was
going on. They analyzed “the banks lending patterns systematically for geographic and racial
bias”(Dreier, 2003, p.345), what it revealed was damning to the banks. They were in fact,
disallowing loans to a very targeted community of people. The community organization had the
ability to take the data and turn it into information and a new public policy. In 1975, the Home
Mortgage Disclosure Act was created to make the way banks loan transparent, for all to see.
Methodology
This capstone research project is a descriptive study of gang hotspots and indexed violent
crime in Salinas, CA. The data researched in this project are both qualitative and quantitative in
nature. The output raster data map is qualitative data. The quantitative data is the information
used within the data tables of the output raster maps. The data tables are city demographic data
and is census tract data from the 2010 census. The census data file was provided by Dr.
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Bhupendra Patel, Senior Transportation Modeler at The Association of Monterey Bay
Governments (AMBAG). It is also available at factfinder2.census.gov. The crime data was
acquired from an SBS senior who works as an intern with the mapping department and received
the data first hand from the city of Salinas.
Maps had to be created and analyzed to respond to the three research questions: 1) Do
more indexed violent crimes get reported within the first two concentric zones of the city of
Salinas? 2) Are the areas of gang territory boundaries in areas with higher poverty levels than the
rest of Salinas? 3) Do more of the violent crimes happen within the gang territory boundaries?
Concentric Zone Theory was used to interpret whether or or not more indexed violent
crime gets reported within the first two concentric zones of Salinas. Both Interactional Theory
and Conflict Theory were used to interpret whether gang territory boundaries are in higher
poverty areas than the rest of Salinas. The map was analyzed to interpret whether or not more
violent crimes happen within the gang boundaries.
The computer software used to create the maps for this project were ArcGis and
ArcCatalog. ArcCatalog is the part of the program that allowed the researcher to mine the crime
data and make it more usable. ArcGis is the map making tool in the software. The map that was
created was a multi-layered raster map and included the following layers: 1) regional city
boundary layer, provided by AMBAG, 2) Roads layer, provided by AMBAG, 3) Census Block
information layer, provided by AMBAG, 4) Salinas Points of Interest layer, provided by ESRI,
5) Gang territory map, provided by Google, 6) Geocoding Results layers, created by researcher,
7) City Limit_Census Intersects, created by researcher, 8) Buffer Layers, created by researcher 9)
tiger lines shapefile for geocode, provided by AMBAG, 9) Sumary_Output tables, created by
researcher.
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Mapping Indexed Violent Crime
Chart graphs, included in the Appendix, show the four violent crimes, in Salinas, CA
between the years 2008-2012. Table 1 shows Homicide, Table 2, Forcible Rape, Table 3,
Robbery, and Table 4 Assault. The source for the violent crime statistics were found
http://www.salinaspd.com/sites/default/files/crime_stats_history_1993-2012.pdf . The objective
of hot spot analysis is to identify areas showing to have tendencies of crime events. Since each
occurrence of crime would be geocoded with an x- y- coordinate value, Point Density would be
an effective method for me to use in my hot spot analysis. Point density is used to calculate the
density of occurrences within each cell on the output raster. When dealing in a cluster, repeat
location can become an issue. The main issue being that a point can only represent one
occurrence. This would jeopardize the integrity of the output raster. One way to avoid this is by
using graduated dots. Then a size can be assigned, so the dot corresponds to a quantity of crimes
in a legend. If individual points of crime were removed from the raster map it could still show
risks of crime with a choropleth map. This map would use color gradients to effectively show the
increased risk of crime as you move through a neighborhood. More in-depth analysis of the
output rasters could include creating a buffer. A buffer is a preset “zone” around a particular
point on the map. For example, including a half mile buffer around 24-hour convenience stores.
If there were more occurrences within the given buffer, someone could make a case to close such
24-hour convenience stores and have an analytical basis to make such a case.
Data and Analysis
The Concentric Zone Theory proved to be an effective way to analyze crime in Salinas
Ca. The buffer layer created to indicate the two mile ring did have more indexed violent crime
than the rest of the city. The numbers indicate that 862 of the 1121 geocoded results of reported
indexed violent crimes for 2009 occurred within the two mile boundary created by the
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researcher. Of those 862 indexed violent crimes, only 183 were a single incident address points.
For the year 2010, 690 of 950 geocoded results occurred within the two mile concentric zone.
With a single event address occurring 255 times of those 690. In 2011, of the 889 total crimes in
Salinas, 652 of them were in the two mile concentric ring. 251 of those crimes were at single
incident address points. There were 839 total indexed violent crimes in 2012. Of those, 605
occurred in the two mile concentric ring. 222 of the crimes within the ring were at single incident
address points. In 2013, 600 of the 833 crimes occurred within the two mile concentric ring. Of
those, 238 were single incident address points.
Interactional Theory and Conflict Theory were good ways to interpret the
demographic data findings from the map. They are both used to explain the societal factors that
could lead to incidents of crime. Based on Thornberry’s premise of Social Structure in his
Interactional Theory (1987), the ArcGis map can identify “class differences in family disruption,
poverty, and residential community” (Jang, 6). This map would be very important because
according to Thornberry, (1987):
“The manner in which the social class of origin affects the
interactional variables and the behavioral trajectories can be
demonstrated by comparing the life expectancies of children from
lower- and middle-class families”(p.887).
The three societal, demographic factors the mapped in the study were: 1) the lowest income
levels, 2) households with the highest density, 5 or more people and 3) housing units by renter.
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The city data in graphs 1-4 was collected from the Salinas Police Department statistics
link on their homepage. The information there was the quantity of crimes broken down by month
as well as by type. Totals were taken for each year by type and inserted into the graphs. The data
in those graphs show that much of the violent crime occurrences in the county of Monterey,
occur within the city boundaries of Salinas.
Graph 1
Source: http://www.salinaspd.com/sites/default/files/crime_stats_history_1993-2012.pdf .
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Graph 2
Source: http://www.salinaspd.com/sites/default/files/crime_stats_history_1993-2012.pdf .
G
raph
3
Sour
ce:
http:/
/ww
w.sal
inasp
d.co
m/sit
es/default/files/crime_stats_history_1993-2012.pdf .
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Graph 4
Source: http://www.salinaspd.com/sites/default/files/crime_stats_history_1993-2012.pdf.
Results & Conclusions
My hypothesis for the Concentric Zone Theory was supported, much more of the indexed
violent crime occurred within the concentric buffer. Nearly 75% in all the years studied was
located in the area of that circle. The numbers indicate that 862 of the 1121 geocoded results of
reported indexed violent crimes for 2009 occurred within the two mile boundary created by the
researcher. Of those 862 indexed violent crimes, only 183 were a single incident address points.
For the year 2010, 690 of 950 geocoded results occurred within the two mile concentric zone.
With a single event address occurring 255 times of those 690. In 2011, of the 889 total crimes in
Salinas, 652 of them were in the two mile concentric ring. 251 of those crimes were at single
incident address points. There were 839 total indexed violent crimes in 2012. Of those, 605
occurred in the two mile concentric ring. 222 of the crimes within the ring were at single incident
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Mapping Indexed Violent Crime
address points. In 2013, 600 of the 833 crimes occurred within the two mile concentric ring. Of
those, 238 were single incident address points.
Interactional Theory and Conflict Theory were good ways to interpret the demographic
data findings from the map. They are both used to explain the societal factors that could lead to
incidents of crime. Based on Thornberry’s premise of Social Structure in his Interactional Theory
(1987), the ArcGis map can identify “class differences in family disruption, poverty, and
residential community” (Jang, 6). This map would be very important because according to
Thornberry, (1987):
“The manner in which the social class of origin affects the
interactional variables and the behavioral trajectories can be
demonstrated by comparing the life expectancies of children from
lower- and middle-class families”(p.887).
The three societal, demographic factors the mapped in the study were: 1) the lowest income
levels, 2) households with the highest density, 5 or more people and 3) housing units by renter.
Recommendations
If I could do the project again,the first thing I would do differently is run my 2 mile buffer or
concentric zone off of the actual downtown business district. The way I did it for this project
may have skewed the crimes within the concentric zone and included way too many. The other
thing I would look into changing was the distance of the rings. Nowhere in the literature was the
distance explained. In a city boundary of just about 6 miles across, having a 4 mile wide circle
again, may lead to inaccuracies in the results. My future recommendations would be to make the
data models using different variables or remove demographic analysis altogether. I would
emphasize physical attributes of areas of the city as risks for gang territory boundaries. One
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possible scenario would be is there a correlation to areas with broken or missing street lamps and
crime. Then map crimes by type in those areas and interpret the findings.