dedication - usc spatial sciences...
TRANSCRIPT
TITLE:
SUBTITLE
by
Your Full Name
A Thesis Presented to theFACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIAIn Partial Fulfillment of the
Requirements for the DegreeMASTER OF SCIENCE
(GEOGRAPHIC INFORMATION SCIENCE AND TECHNOLOGY)
Month YEAR
Copyright YEAR Your Full Name (spelled as above)
DEDICATION
I dedicate this document to my parents for their constant support, and to Tommy Trojan, who has
inspired me throughout this process.
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ACKNOWLEDGMENTS
I will be forever grateful to my mentor, Professor Smith. Thank you also to my family and
friends, without whom I could not have made it this far.
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TABLE OF CONTENTS
DEDICATION ii
ACKNOWLEDGMENTS iii
LIST OF TABLES iii
LIST OF FIGURES iv
LIST OF ABBREVIATIONS v
ABSTRACT vi
CHAPTER 1: INTRODUCTION 1
1.1 Subchapter 1
1.1.1 Second Level Subchapter 2
CHAPTER 2: BACKGROUND AND LITERATURE REVIEW 4
2.1 Subchapter 4
2.1.1 Second Level Subchapter 5
2.1.1.1 Third Level Subchapter 5
CHAPTER 3: METHODOLOGY 7
3.1 Subchapter 7
3.2 Second Level Subchapter 8
CHAPTER 4: RESULTS 12
4.1 Subchapter 12
4.2 Subchapter 13
CHAPTER 5: DISCUSSION AND CONCLUSIONS 15
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5.1 Subchapter 15
5.2 Subchapter 15
REFERENCES 16
APPENDIX A: TITLE 17
APPENDIX B: TITLE 18
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LIST OF TABLES
Table 1 List of Participating Schools (USC, 2013) 5
Table 2 Armed-Conflicts by Territory, 2008-2012: Normalized by Population 8
Table 3 Variables Referenced in the Analysis of Comparative Changes 11
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LIST OF FIGURES
Figure 1 Ozro W. Childs 3
Figure 2 2008 Armed-conflicts Heat Map 7
Figure 3 Methodological Comparative Diagram 9
Figure 4 Comparing Changes by Territory 10
Figure 5 2008-2012 Abductions in Central Africa 12
Figure 6 Map of Administrative Boundaries in Central Africa 13
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LIST OF ABBREVIATIONS
AAG Association of American Geographers
GIST Geographic Information Science and Technology
JEP Joint Educational Project
SSI Spatial Sciences Institute
USC University of Southern California
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ABSTRACT
The Traveler tradition began in 1961 with Traveler the First. From 1961 to 1988, the equestrian
mascots were selected, trained and ridden by Richard Saukko. After his death, the Saukko family
continued the tradition of raising the famous Trojan horses until 2003, when equestrian manager
Joanne Asman took over.
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CHAPTER 1: INTRODUCTION
Los Angeles was a rough-and-tumble frontier town in the early 1870s, when a group of public-
spirited citizens led by Judge Robert Maclay Widney first dreamed of establishing a university in
the region. It took nearly a decade for this vision to become a reality, but in 1879 Widney
formed a board of trustees and secured a donation of 308 lots of land from three prominent
members of the community – Ozro W. Childs, a Protestant horticulturist; former California
governor John G. Downey, an Irish-Catholic pharmacist and businessman; and Isaias W.
Hellman, a German-Jewish banker and philanthropist. The gift provided land for a campus as
well as a source of endowment, the seeds of financial support for the nascent institution.
When the University of Southern California (USC) first opened its doors to 53 students
and 10 teachers in 1880, the “city” still lacked paved streets, electric lights, telephones and a
reliable fire alarm system. Today, USC is home to more than 33,000 students and nearly 3,200
full-time faculty, and is located in the heart of one of the biggest metropolises in the world.
1.1 Subchapter
More than anyone else, real estate promoter, attorney and Judge Robert Maclay Widney was
responsible for setting into motion the events that led to the founding of USC.
A poor Ohio farm boy, Widney left home at 16, arriving in Northern California in 1857.
After working at odd jobs, he entered the University of the Pacific, and upon graduation, taught
mathematics and geology there while studying law on the side. He was admitted to the California
and Nevada bars in 1867 and decided to settle in Los Angeles. He soon found that legal advice
was less marketable than real estate in the little town, however, so he diversified, selling land to
newcomers, settling land claims and boundary disputes, and publishing a monthly newsletter,
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Los Angeles Real Estate Advertiser. Using land he accepted in lieu of fees, he developed such
towns as Pacoima, San Fernando, Ontario, Victorville and Long Beach. In 1871, Widney
intervened as violent anti-Chinese rioting stormed through town, drawing his pistol and plunging
into the mob to escort several immigrants to safety. In December of that year, he was appointed a
U.S. district judge.
Widney was instrumental in a number of advances in Southern California. He helped
bring the Southern Pacific Railroad to Los Angeles, establish the city’s first horse-drawn trolley
and organize the first chamber of commerce. He also helped form the Los Angeles County Bar
Association and incorporate the city’s first light and power company.
When the University of Southern California was founded, largely through his
perseverance, he was elected the first president of its board of directors and was one of the
original trustees of the endowment fund. Widney died in 1929, at the age of 93.
1.1.1 Second Level Subchapter
The three men who made the original gift of land to establish the University of Southern
California were as diverse as nineteenth-century Los Angeles. They came from three different
countries and practiced three different religions, but the civic-mindedness they shared helped
direct the course of their young city for decades to come.
Ozro W. Childs was born in Vermont in 1824 and, after paying his own way to gain an
education, became a schoolteacher. A lifelong battle with asthma, however, prompted him to
move to Ohio, where he hoped to find a more congenial climate.
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Figure 1 Ozro W. ChildsPhotograph by Tommy Trojan
There he learned tinsmithing, a trade that provided a livelihood when the Gold Rush
lured him to Northern California in 1850. Although he prospered, he soon opted for the milder
climate of Los Angeles, where, as pictured in Figure 1, he spent most of his adult life. He and a
partner opened a tin shop, and then switched to selling groceries and other provisions — the first
of a series of successful ventures. In 1857, he turned to horticulture and founded yet another
profitable business, a nursery importing and selling exotic trees and plants. A few years later, the
city hired him to construct an irrigation ditch, or zanja, for the city. Instead of money, he took
land as his payment. The parcel he received was bounded by Main, Figueroa, 6th and 12th
streets. When he put the property on the market, his wife named some of the streets after the
three Christian graces: Faith Street (which became Flower), Hope Street and Charity (which
became Grand Avenue). A fourth street, called Calle de los Chapules in recognition of its large
population of grasshoppers, became Figueroa. In 1884, he opened a new theater on Main Street,
known as Childs’ Opera House.
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CHAPTER 2: BACKGROUND AND LITERATURE REVIEW
Founded in 1972, the Joint Educational Project (JEP) is one of the oldest and largest service-
learning programs in the country, offering students at the University of Southern California the
unique opportunity to combine academic coursework with experiences in the community
surrounding the campus. Each year, some 2,000 students from over several courses receive
academic credit for their participation in JEP. In addition, about 400 students serve as non-credit
volunteers and share their time and special talents with their neighbors. JEP is also home to the
Trojan Health Volunteers, a program designed to serve pre-meds and health educators, and USC
ReadersPlus, an America Reads / America Counts work-study affiliate.
2.1 Subchapter
Imagine an urban university that contributes to the well-being of its community while offering
students an opportunity to learn about issues of poverty, immigration, education, inequality and
other contemporary concerns. It is this vision that Dr. Barbara Seaver Gardner, of the University
of Southern California, had in 1972 when she created the Joint Educational Project (JEP). Today
JEP is recognized as one of the oldest and best organized service-learning program in the country
(USC 2013).
Through the years, over 70,000 USC students have contributed over a million hours of
service to the surrounding community. At the same time, these students have carried away a
better understanding of an academic discipline and have had an opportunity to work and learn
with people of other cultures.
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JEP stands as a monument to the notion that universities and their communities can work
together toward goals that are mutually beneficial. As seen in Table 1, there is a long history and
many hours of learning support through the JEP program at the USC neighborhood schools.
Table 1 List of Participating Schools (USC, 2013)
School Years in JEP Program Total Student Number
Jefferson Elementary 35 50,000
32nd Street School 40 75,000
Manual Arts High School 25 20,000
Bravo Medical Magnet 15 15,000Source: Data adapted from USC (2013)
2.1.1 Second Level Subchapter
In 1974, long before mentoring was a political agenda for presidents and governors, JEP students
were working one-on-one with neighborhood children through our PALS program. JEP received
its first mentoring grant in 1989. Two years before the Los Angeles Police Department began
their D.A.R.E. program, JEP launched its Choices Drug Education program with support from
the Walter S. Johnson Foundation.
2.1.1.1 Third Level Subchapter
In 1991, JEP converted an adult literacy program designed by a USC undergraduate to a program
for young readers. Literacy will be ever more important in the world of big data. As USC’s
Dornsife College Dean, Steven Kay explains:
The roar of ‘Big Data’ is driving this change. There are dizzying amounts of consumer records, music, satellite imagery, and of course, Facebook content, that have to be stored, retrieved and understood in their proper context. This stored information is growing by 23 percent a year and shows no signs of retreating. The mountain of data we now face will be but 1 percent of that in 2020. What does this mean? This sea of data influences how we contribute to society as academics.
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It shifts how we acquire and share knowledge. It changes how we teach our students to be leaders. It shapes how we inspire a passion for discovery deep within their being (Kay 2012, 4).
The JEP program will no doubt adapt its literacy education to take account of the evolving
requirements for adult literacy in the era of big data. The focus on big data also points to an
increasingly important role for USC’s Spatial Sciences Institute (SSI) and its graduate program
in Geographic Information Science and Technology (GIST).
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CHAPTER 3: METHODOLOGY
This chapter will review LRA-active areas, discuss the data sources being used to capture
metrics of violence, and it will provide a conceptual framework for conducting a descriptive
analysis of change in the rates of violence given the introduction of radios over time.
3.1 Subchapter
Clustering methods were explored to show where armed-conflicts are concentrated and whether
there is evidence of heavy clustering. In a heavily clustered environment, there is the potential to
identify predictor variables that can be used to explain the highs and lows of the data. Six kernel
density maps were created to produce rasterized surfaces indicating concentrations of LRA
activity. Figure 2 reflects the kernel density of armed-conflicts in 2008.
Figure 2 2008 Armed-conflicts Heat Map
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With conflict data spatially joined with the “Territories” feature class, Modelbuilder was
used to generate 15 new territory feature classes as show in Table 2.
Table 2 Armed-Conflicts by Territory, 2008-2012: Normalized by Population
Country Territory Name 2008 2009 2010 2011 2012SSD Raja 0.00 0.04 0.00 0.07 0.00 Wau 0.00 0.00 0.01 0.00 0.00 Nahr Yew 0.01 0.01 0.00 0.00 0.00 Meridi 0.05 0.02 0.05 0.00 0.00 Mundri 0.00 0.02 0.00 0.00 0.00 Tombura 0.05 0.16 0.25 0.16 0.02 Yambio 0.02 0.02 0.10 0.10 0.00DRC Ango 0.00 4.15 3.69 2.54 1.84 Bambesa 0.00 0.00 0.00 0.06 0.00 Bondo 0.00 0.00 0.05 0.00 0.16 Poko 0.00 0.42 0.21 0.00 0.00 Dungu 1.39 3.08 8.64 5.02 4.34 Faradje 0.20 0.44 0.36 0.96 0.80 Niangara 0.07 1.22 1.86 0.36 0.43 Watsa 0.00 0.06 0.03 0.06 0.00CAR Djemah 0.00 2.18 0.00 0.00 0.00 Obo 0.08 1.05 0.31 0.39 0.14 Zémio 0.00 0.12 1.19 0.65 0.71 Yalinga 0.00 0.00 0.77 0.00 0.58 Bakouma 0.00 0.00 0.10 0.19 0.29 Bangassou 0.00 0.02 0.03 0.02 0.05 Rafaï 0.00 0.14 3.08 0.43 1.22 Birao 0.00 0.00 0.10 0.00 0.00
3.2 Second Level Subchapter
The process of calculating the annual rates of change by territory is illustrated in Figure 3.
Included in this figure are the additional steps taken to compare changes between the sample
group of territories and the control group as represented by the analysis.
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Figure 3 Methodological Comparative Diagram
After the rate changes were coded to each feature class, the territories were divided into
two groups: the first group is the sample (n), which is composed of territories in which HF radios
are located. The second group is the control (m), which is composed of territories without HF
radios. HF radios were aggregated by territory and each territory was coded as either having or
not having one or more HF radios. The mean rate of change for the control group was then
subtracted from the mean rate of change for the sample group. Figure 4 is a conceptualization of
this method, illustrating comparative changes between a sample group and a control group.
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Figure 4 Comparing Changes by Territory
The comparative changes between the two groups are calculated using Equation 1, which
is based on the Difference-in-Differences statistical method (Abadie 2005):
m
zrr
n
zrrxx
n
territoryibiiyy
n
territoryiaiiyy 11
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Resulting values indicate how the rate of violence in territories with HF radios changed in
comparison to territories without HF radios. The detailed flowchart for this approach is included
in Figure 16. Due to the low n, the significance at local scale of the true Difference-in-
Differences statistical analysis could not be established or validated. Therefore, the numerical
results derived from this method are shown in chapter four and described qualitatively focusing
on a comparative description of the results.
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Next, feature classes for the same category of violence were joined from one year to the
next using a table join and a common ObjectID (Territory_Name); Armed-conflicts_2008 was
joined with Armed-conflicts_2009, and Armed-conflicts_2009 was joined with Armed-
conflicts_2010, etc. Table 3 below shows the variables used to calculate rate changes by year.
Table 3 Variables Referenced in the Analysis of Comparative Changes
Variable Description Assumptions Limitations
i Territory The territory sustained at least one armed-conflict for each year-to-year interval.
Territories vary widely in area and population.
r Rate of change Rate of each assumes each territory's population is static through each year-to-year transition.
The rate of change is calculated for armed-conflict, civilian murders, and abductions. It does not consider other forms of looting or harassment.
y Year Annual interval provides a summary of violence over the course of a year.
Interval does not account for spikes or drops in violence that can occur weekly or monthly.
n Number of territories in sample group
All HF radios locations are known.
Territories are not weighted by how many radios they contain.
m Number of territories in control group
Territories in control group are not affected by HF radios in adjacent territories.
Some territories in the control group very seldom experience violence compared to territories in the sample group.
za Indicator = 1 if HF radios are present, 0 if not
If an HF radio is present in a territory, it is being used.
Does not account for how long a radio has been present.
zb Indicator = 0 if HF radios are present, 1 if not
If an HF radio is present in a territory, it is being used
Does not account for how long a radio has been present.
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CHAPTER 4: RESULTS
This chapter documents the spatial distribution of violence and demonstrates change over time
for each category of violence. Results of the distribution of violence are shown by countries and
by territories.
4.1 Subchapter
A summary of the raw number of armed-conflicts occurring from 2008 to 2012 is shown in
Figure 18. The year 2008 marks the lowest levels of LRA attacks in the five-year span; only 55
attacks occurred during this period. However, violence increased significantly in 2009 and again
in 2010 with attacks becoming increasingly prevalent in the DRC.
Figure 5 2008-2012 Abductions in Central Africa
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2008 2009 2010 2011 20120
50
100
150
200
250
300
CAR DRC SSD
Year
Num
ber
of P
eopl
e
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4.2 Subchapter
In 2008, the baseline rates of civilian abductions (Figure 6) had a pattern similar to the rates of
armed-conflicts and civilian murders. The mean rate of abductions across the area of operations
was 4.06 abductions per 1,000 people. The highest rates were in Dungu and Faradje measuring
15.26 and 7.60 respectively making the two territories again the most dangerous in 2008.
Figure 6 Map of Administrative Boundaries in Central Africa
While the overall number of armed-conflicts steadily declined after peaking in 2010, the
number of civilian-murders declined even more substantially. Although LRA killed 49 civilians
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in 2012, this is 96 percent fewer civilian than they killed in 2010 and over 99 percent fewer than
in 2009.
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CHAPTER 5: DISCUSSION AND CONCLUSIONS
Chapter Five discusses the impact of the findings, their contribution to existing research on
conflict geographies, and their relevance to ongoing discussions regarding the development of
counter-insurgency efforts in Central Africa. Shortcomings of the data are discussed, and several
recommendations for future geographic studies in insurgency-violence are made.
5.1 Subchapter
Results in this work suggest that the LRA’s area of operations has fluctuated over time in an
apparent reaction to external influences. Since the number of attacks and casualties peaked in
2010, there has been a steady decline in violence committed by the group with the year 2012
marking the lowest levels of violence in the years observed. In 2012, there were a total of 49
civilian murders. This is a 92.7 percent reduction in murders since 2010 when MONUSCO first
adopted Security Council Resolution 1925. This represents a 74.8 percent reduction in CAR, a
97.3 percent reduction in the DRC, and a 100 percent reduction in South Sudan.
5.2 Subchapter
The diminishing of LRA attacks around Dungu suggests that MONUSCO’s forward base of
operations have been influential there as an anti-insurgency organization. This work does not
suggest that the same counter-insurgency efforts would be successful against other paramilitary
organizations in Africa, but the contrary observations suggest that the LRA area of operations
has reacted to the tailored counter-insurgency strategies targeting the organization’s structure,
priorities, ethnic and ideological foundations.
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REFERENCES
Abadie, A. 2005. Semiparametric difference-in-differences estimators. The Review of
Economic Studies 72: 1-18.
Andreas, P. 2002. Transnational crime and economics globalization. In Transnational
organized crime and international security. ed. M. Berdal and M.
Serrano, 37-52. Boulder, CO: Lynne Rienner Publishers, Inc.
Arquilla, J., D. Ronfeldt, and M. Zanini, 1999. Networks, netwar, and information-age
Terrorism. In Strategic appraisal. ed. Z. Khalilzad and J. White, 24-48. Santa Monica,
CA: Rand.
BBC. 2014. DRCongo: Key facts. BBC News. 19 January 2014.
http://news.bbc.co.uk/2/shared/spl/hi/guides/456900/456977/html (last accessed 23
February 2014).
Kay, S. 2012. Dean Steve Kay’s installation remarks. USC Dornsife College. 2 November 2012.
http://dornsife.usc.edu/dean-steve-kay-installation-remarks (last accessed 7 July 2013).
Trojan, R.O. 2011. Trojan living. Los Angeles, CA: University of Southern California Press.
Trojan, T. 2008. The history of the University of Southern California. Los Angeles: University
of Southern California Press, 2008.
USC (University of Southern California). 2013. The vision of USC’s Joint Educational Project
(JEP). USC Dornsife College. http://dornsife.usc.edu/jep-vision (last accessed 7 July
2013).
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APPENDIX A: TITLE
1. Data Collection Reports are gathered from a variety of sources: • HF radio towers in DRC and CAR o Civilians report activity to HF radio tower operators o Over 30 HF radio operators call the Dungu hub twice daily to report armed-group activity o Activity is entered into a spreadsheet and then sent to data coders • UN & NGO reports • News & media outlets • Civil society contacts in local communities • Field research conducted by Resolve and Invisible Children staff
2. Database Entry Database entry: • Reports are divided between a team of coders from both Invisible Children and
Resolve. Coders determine if the source is reliable or unreliable (see section 4.2B of the codebook). Before an incident is reported, the coder reads through other incidents to check for duplicates.
Verification ratings: • After an incident is categorized, each incident is given a verification rating (see
section 4.2A of the codebook). • If a coder determines that an incident was potentially committed by the LRA, the
incident is rated on the LRA Actor Verification Scale (see section 4.2C of the codebook).3. Data Review • A second data coder reviews each incident to catch human errors and duplicate
reports (see section 4.1E). • IC and Resolve staff with field experience review sensitive incidents immediately and
review all incidents every three months. Should these staff members feel an incident was misreported, the incident is corrected. External LRA and regional experts are consulted as necessary.
4. Data Mapping & Sharing • After an incident is entered and approved to be mapped, it appears on the LRA Crisis Tracker website.
• Data is regularly sent to UN agencies and humanitarian practitioners for comparison and collaboration.
5. Data Revamp • As the database grows and policies are updated to reflect best practices, data coders revisit and “revamp” the data when needed.
6. Data Analysis & Reporting • Crisis Tracker staff analyze data for trends and patterns in LRA activity.
• Specific areas and provinces are also analyzed for increases or decreases in the
number and type of attack.
• After analysis has been completed and reviewed, it is reported in various Crisis Tracker reports that can be found on the LRA Crisis Tracker website.
Source: Invisible Children. 2012. The LRA crisis tracker.
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APPENDIX B: TITLE
Country Territory 2008 2009 2010 2011 2012SSD Raja 0 2 0 4 0 Wau 0 0 1 0 0 Nahr Yei 3 2 0 0 0 Meridi 4 2 4 0 0 Mundri 0 2 0 0 0 Tombura 3 9 14 9 1 Yambio 3 3 15 15 0DRC Ango 0 36 32 22 16 Bambesa 0 0 0 1 0 Bondo 0 0 1 0 3 Poko 0 4 2 0 0 Dungu 33 73 205 119 103 Faradje 5 11 9 24 20 Niangara 1 17 26 5 6 Watsa 0 2 1 2 0CAR Djemah 0 4 0 0 0 Obo 3 38 11 14 5 Zémio 0 2 20 11 12 Yalinga 0 0 4 0 3 Bakouma 0 0 2 4 6 Bangassou 0 1 2 1 3 Rafaï 0 2 43 6 17 Birao 0 0 5 0 0 Ouanda Djallé 0 0 2 0 0
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