Running head THE ROLE OF QUESTIONS IN SOLVING CRIMES 1The Ro.docx

Running head: THE ROLE OF QUESTIONS IN SOLVING
CRIMES 1
The Role of Questions in Solving Crimes6
The Role of Questions in Solving Crimes
Michael D Sheppard
Prof. Jon Hager
11 March 2020
The Role of Questions in Solving Crimes
Introduction
It appears like something out of a horror movie when you get to
your car and see your tires slashed. It is not only scary but also
inconvenient because it is costly to replace tires, especially
when it is all four. Most people wonder what to do when they
find their tires slashed. However, this crime is an easy way of
acquiring revenge or random vandalism without leaving much
evidence. Therefore, the questions below will assist you in
determining what to do after someone has slashed your tires.
1. Why do people slash tires?
Slashing tires is a way of obtaining revenge without leaving
much evidence. However, most people would consider it
cowardice because the individuals doing it are angry at the
victim but do not dare to face them. The theory of social
deviance can also be used to explain this act of vandalism. Tire
slashing is considered a deviant behavior because these people
are inept at life and only want to violate social norms. They are
incapable of doing anything meaningful with their lives, and so

they destroy things to make their presence felt. The more
psychological evaluation should be done to determine why
people slash tires.
2. How can you tell if someone slashed your tires with a knife?
There are numerous varieties of knives, but the most commonly
used to slash tires are the lock blade pocket knives and the chef
knife. Arguably, these two types of knives are not double-
edged. Therefore, they leave diamond-shaped holes, which leave
the puncture in an acute-triangle.
3. How can you determine if the tire has been intentionally
damaged or it is an ordinary blowout?
Tires that have been blown out are ragged and uneven. If the
tire has been messed with, it is easy to see the even cut marks.
Forensically, the pocketknives leave distinctive marks that can
be proven. The knives are standard and leave a deliberate
incident. Individuals can find out more about this question by
contacting an experienced tire retailer. If the technician
believes the tire has been tampered with, then you should file a
police report.
4. What should you do when your car tires are slashed?
Most people assume slashing tires is just another inept criminal
damaging their property and end up fixing them. However, you
should talk to your neighbors to determine if it's a common
occurrence and if they have seen the culprit. Often, the
individuals who do this are people you know. Even if you
recognize the individual, the police cannot deal with the issue
without evidence of the crime. Therefore, search for camera
footage around your area or catch them in the act.
5. How serious of a crime is it to slash tires?
Slashing people's tires is a simple crime of destruction of
property. Most people found guilty of this misdemeanor
vandalism only have to pay fines and then released on probation
(Jones, 2019).
6. Can you face jail time for slashing tires?
The amount of jail time relies on the value of the damaged
vehicle. In some countries, the punishment for the destruction

of tires worth over $1000 is about five years in prison. If the
tires are less than that value, the accused can face up to a year
in jail. New answers to this question can be obtained by
contacting criminal defense attorneys (Banner, 2019).
7. Is it a crime to pay someone to slash other individuals' tires
for you?
I believe it is a crime, but details will differ depending on the
law systems. In the United States, for instance, a contract
formulated that includes an illegal activity is not enforceable
(Gambardello, 2019). For example, when someone slashes tires
on your behalf, and you refuse to pay them, there is no legal
recourse that can hold you to the agreement. Nonetheless, when
you pay them for their service, it will incriminate you.
8. Can you file a claim after your tires are slashed?
If your car is intentionally damaged by slashing the tires, you
must file a personal injury claim to cover the damage. The best
way to do so is to initially register a police report within 24
hours and then contact a professional injury attorney to assess
the damage (Gambardello, 2019). You can take pictures and
video footage of the vandalism for additional evidence.
9. Why do criminals only slash three tires?
Criminals only slash three tires because the insurance
companies are forced to pay when all four are cut (Gambardello,
2019). When only three are slashed, the owners have to pay out
of their own pockets. Most victims are not familiar with this
information. Therefore, they must conduct sufficient research
within their states before contacting their insurance provider.
10. How can you prevent individuals from slashing your tires?
It is not easy to prevent others from slashing your tires, mostly
because you park it outside or reside in a criminal-infested
neighborhood. To prevent your tires from being cut in the
future, find a secure and well-lit parking space. Secondly, you
can install security cameras and motion sensors lighting around
the house. Lastly, you can establish a neighborhood crime
watch.
Conclusion

There are many reasons why individuals break the law. Some of
the reasons include the opportunity, being in the right place at
the right time, jealousy, or it can be just plain ole’ boredom.
Regardless of the reason, there are a few crime theories as to
why offences still occur. Byrne and Hummer, 2016 suggest four
different types of crime theories, which are classically,
biologically, psychologically, and sociologically based.
Classically based criminologist is when an individual makes a
conscious choice in committing crime based on the cost and
benefits of the individual(s) (Byrne & Hummer, 2016).
Biologically based criminologists is when inherited traits
increase the occurrences of committing a crime because other
family members committed crimes (Byrne & Hummer. For
example, if the individual(s) saw family member slashing tires
out of anger, they may do it as well out of anger.
Psychologically based criminologists explain criminal behavior
as a negative circumstance(s) in the individual’s youth that
brought on a criminal thinking mindset. For example, if the
individual(s) feels like there is no one in their corners, as an
adolescent, they then may show out to attain attention and
associate bad behavior with getting attention and will continue
it as an adult. The last theory is sociologically based
criminologists. Within this theory level, individuals feel
conflicted to doing criminal activities because of factors that
they feel constricted them from succeeding in life and look
towards violence and criminal activities as a last resort and only
result of succeeding in life Byrne &Hummer, 2016).
References
Banner, G. (2019, May 24). Arrest made in Gravenhurst tire
slashing of 9 vehicles parked near bar.
https://lopes.idm.oclc.org/login?url=https://search.ebscohost.co
m/login.aspx?direct=true&db=edsgin&AN=edsgcl.586606424&s
ite=eds-live&scope=site
Byrne, J., & Hummer, D. (2016). An Examination of the Impact
of Criminological Theory on Community Corrections Practice.

In www.USCourts.gov. Retrieve from
https://pdfs.semanticscholar.org/bc5e/1f37118c587f88253e8efb
784459ae6e4ede.pdf
Gambardello, J. (2019). Police seek trio in tire slashing spree in
West philadelphia. Philadelphia: Tribune Content Agency.
m/login.aspx?direct=true&db=nfh&AN=2W6731577171&site=e
ds-live&scope=site
Jones, R. (2019, November 8). Crooks ruin 'more than 50 cars'
in tyre slashing spree.
m/login.aspx?direct=true&db=edsgin&AN=edsgcl.605092394&s
ite=eds-live&scope=site
1190 Assignment Specifications
1190.16
35 Points Possible
Content Criteria
CURRENT INFORMATION ABOUT A FIELD I AM
PURSUING
1) Which professional organization monitors entry into and
current practice in the field you are pursuing?
2) When and where are the organization’s nation meetings
generally held?
3) Does your profession’s organization maintain ethical polices
for best practice of your field?
4) Is there a student branch/division of your profession’s
organization?

5) Search for information about the profession’s current
practices in our library’s card catalog.
6) Using paper-copy information: evaluate your sources – which
are academic, which are from current professional organizations
7) Do a web search for the profession’s current practice
information.
8) Do a web search for how to cite Internet sources in the
format determined by the Modern Language Association (MLA).
9) Remember to cite your resources in the correct reference
form. You will need citations for each of the resources that you
used, both paper and Internet sources. (The book and your
internet research will help)
10) Submit your research in paragraph format as 1190.16.
Editing Criteria
1. Identify 2 correlative conjunctions in your submitted research
by underlining them.
2. Identify 2 subordinating conjunctions in your submitted
research by identifying them with underline andbold.
3. Identify 2 complex sentences in your submitted research in
bold.
4. Identify 4 acronyms/abbreviations in your submitted research
and correctly punctuate them.
5. Fragments, run-ons, and comma splices are edited into
submission.
6. The writer has eliminated the use of the second person “you”
in the writing of your essay and written up the research using

third person.
7. Overall, there are fewer than five editing errors.
Submission Criteria
1. The length of the essay is a minimum of 1 page, single-
spaced when printed in 12 point New Times Roman Font. No
spaces between the paragraphs or unnecessary spacing around
the title. I may scan and reprint the essays if there is any doubt
about the length of the essay. If an essay is less than the
prescribed length, the grade will be shortened. Short essays
lead to short grades.
2. The completed essay should have less than five editing
errors.
3. The editing features are identified with underline and bold as
requested.
4. The references for information which you took from web
sources and hard copy has been identified both in the body of
your essay and in the Work Cited
5. At the end of the essay, after the page minimum, the
following questions are to be answered:
a) What influenced you to select this topic?
b) What assistance did you have in creating the essay?
c) What assistance did you have in editing the essay?
d) Do you state that the above answers are true?
e) Are you aware that the consequence for dishonesty is a
failing grade?

Journal of Digital Forensics, Security and Law, Vol. 8(1)
73
TECHNOLOGY CORNER
VISUALISING FORENSIC DATA: EVIDENCE
(PART 1)
Damian Schofield
State University of New York
Department of Computer Science
[email protected]
+1 (410) 504 3178
Ken Fowle
Edith Cowan University
School of Computer and Security Science
[email protected]
+61 (8) 9370 6013

Keywords: Visualisation, Visualization, Evidence,
Reconstruction, Digital
Forensics, Computer Graphics, Forensic Animation, Guidelines.
ABSTRACT
Visualisation is becoming increasingly important for
understanding information,
such as investigative data (for example: computing, medical and
crime scene
evidence) and analysis (for example: network capability
assessment, data file
reconstruction and planning scenarios). Investigative data
visualisation is used
to reconstruct a scene or item and is used to assist the viewer
(who may well be
a member of the general public with little or no understanding
of the subject
matter) to understand what is being presented. Analysis
visualisations, on the
other hand, are usually developed to review data, information
and assess
competing scenario hypotheses for those who usually have an
understanding of
the subject matter.

Visualisation represents information that has been digitally
recorded (for
example: pictures, video and sound), hand written and/or spoken
data, to show
what may have, could have, did happen or is believed to have
happened. That is
why visualising data is an important development in the
analysis and
investigation realms, as visualisation explores the accuracies,
inconsistencies
and discrepancies of the collected data and information.
This paper introduces some of the various graphical techniques
and technology
used to display digital information in a courtroom. The
advantages and
disadvantages involved in the implementation of this technology
are also
mailto:[email protected]
mailto:[email protected]
74

discussed. This paper is part one of a two part series that aims
to describe the use
of, and provide guidelines for, the use of graphical displays in
courtrooms.
1. INTRODUCTION
At the end of the 18th Century William Playfair, a Scottish
inventor, introduced
the line graph, bar chart and pie chart into statistics. He
demonstrated how much
could be learned if one plotted data graphically and looked for
suggestive
patterns to provide evidence for pursuing research. However,
due to the novelty
of the graphical forms, Playfair had to include extensive
directions for the viewer
informing them how to read the data visualised from the graphs
and charts he
created (Tufte 1997). Today these graphs (and many other more
complex
graphical representations) are a vital and everyday part of
communication in
science and technology, business, education and the mass media
(Cleveland &
McGill, 1984).

Scientists and scholars have always used graphical techniques
to describe,
represent, and create knowledge. Traditionally, these techniques
have focused
on the communication of quantitative data and information
(e.g., graphs and
charts) although a variety of methods have also emerged to
communicate more
qualitative information including behavioral maps, and
perspective renderings
(Ramasubramanian and McNeil, 2004).
The human visual system has the ability to interpret and
comprehend pictures,
video, and charts much faster than reading a description of the
same material.
The human brain performs some processing early in the chain of
processing
visual input; this process starts in the eyes. Hence, images are
interpreted much
faster than textual descriptions as the brain processes the visual
input much
earlier than textual input. This results in the human visual
system’s ability to

examine graphics in parallel, whereas humans can only process
text serially
(Teerlink and Erbacher, 2006).
A visualisation is an image, diagram, graphic or animation
representing data that
is intended to give a better understanding of that data. There are
many different
visualisation areas, differing mostly by the domain of the
visualised information.
Examples include: mathematical & scientific visualisations
(results from
equations and formulas); product visualisation and three-
dimensional design
(images, photos or computer aided design software) and medical
imaging
(information and images from medical machines such as
magnetic resonance
imaging scanners).
Visualisation, in its broadest sense, is a communicative process
that relies on
encoded meanings that can be transferred from creators and
organizers of
information to users and receivers of the same information
(Shannon, 1948).

Edward Tuft (1997) proposes that visualisation is as much an
art as a science,
where the processes of arranging data and information in order
to achieve
75
representation, communication, and explanation are consistent
regardless of the
nature of substantive content or the technologies used to display
the information.
Marty (2008) stated:
“It is not just the expedited browsing capabilities that
visualization has to offer, but often a visual representation—in
contrast to a textual representation”
2. VISUAL EVIDENCE
In a modern courtroom, the presentation of forensic evidence by
an expert
witness can bring about the need for arduous descriptions by
lawyers and experts

to get across the specific details of complicated scientific,
spatial and temporal
data. Within the realms of forensic science, the use of new
technologies in order
to gather, analyse and present evidence is of the utmost
importance in the modern
world. Better collection and analysis of evidence from a wide
range of digital
media can be achieved by the use of data from the devices of
perpetrators,
victims and witnesses involved in incidents. The devices which
may provide
additional evidence include mobile phones, PDAs, tablets,
digital cameras,
computers and closed-circuit TV. Recent terrorist event have
highlighted these
new forms of evidence as mobile phone images and video are
collected from
members of the public who were at the scene of an incident
(Schofield, 2007).
Digital visual evidence presentation systems (including digital
displays,
computer-generated graphical presentations and three-dimension
simulations)

have already been used in many jurisdictions. As courtrooms
transform into
multi-media, cinematic display environments, this has enormous
implications
for the legal processes taking place with them. One must ask
whether the
decisions made in these visual courtrooms are affected by the
manner in which
the evidence is presented, and in truth, no one really knows the
answer to this
important question.
Gerald Lefcourt (2003), a criminal defence lawyer in New York,
has made the
following comments about members of the public who attend
court:
“These are people who by and large have grown up on
television … The day of the lawyers droning on is really gone. I
think that jurors today, particularly the young ones, expect
quickness and things they can see.”
Forensic visualisation methods for two specific areas
(investigation and

presentation) have a common thread; that is, that data
visualisation is still
relatively new within the forensic and evidential thematic area.
There is further
research required to establish an accepted framework of what
visual is suitable
and acceptable for investigation and presentation in relation to
the target
audience.
76
3. WHY VISUALISE DATA
There is a famous expression that “a picture paints a thousand
words” but this
epigram is only true if the viewer has some understanding of
what is being
presented and why it is being presented. The inability of the
general public to
understand William Playfair’s first graphs and charts is a prime
example of this

problem (Tufte 1997). Consider the image shown below (Figure
1) and its
potential ability to confuse a viewer unfamiliar with the
information types being
visualised.
Figure 1 Visual Representation of Computer Network Traffic
(Wand n.d.)
The image above shows computer network traffic in a graphical
format, the data
is captured from a live network interface, visualising the flow
of network data
between hosts, providing (at a glance) information about
network usage. To a
person trained in computer network traffic analysis the image
has meaning and
provides displays information but to a layperson it will require
the provision of
a detailed explanation. How information and data is viewed,
interpreted and
understood depends on what is presented, to whom it is
presented and why it is
being presented. Visualisations are only effective when the right

kind of pictorial
representation is chosen and can be manipulated to show useful
information
(Lowman, 2010).
Many forensic disciplines are facing an ever-growing amount of
data and
information that needs to be analysed, processed, and
communicated. Those who
77
have to look at, browse, or understand the data (judges, lawyers,
jurors, etc.)
need ways to display relevant information graphically to assist
in understanding
the data, analysing it, and remembering parts of it.
The ability of a computer to create synthetic copies of an event
or issue (whether
as a static image, a plan or schematic, a computer animation or
a virtual reality
simulation) provides the opportunity to enhance the viewer’s

current
understanding. These visualisations allow users to learn,
question and interact
within the computer-generated environment and it provides the
opportunity to
make mistakes, revisit and review, without necessarily putting
themselves at risk
(Fowle and Schofield, 2011).
4. INVESTIGATION VISUALISATION
Analysis of digital data storage is often a key area in modern
crime scene
investigation, so much so in fact, that the computer is
sometimes now considered
as a separate crime scene. The computer may hold evidence in
the form of
documents, e-mail records, web history and caches, login dates
and times of
access, and illegal files, to name but a few. The digital evidence
process has
become so focused around this area, that disk analysis has
become known, by
some authors as ‘forensic computing’ (Schofield and Mason,
2012).

Today’s digital forensic investigator has “hundreds of specific
and unique
application software packages and hardware devices that could
qualify as cyber
forensic tools…hundreds of utilities available for the same
task” (Marcella and
Menendez, 2007). The basic requirement for a computer
forensics tool is to
convert specific files into a human readable format for analysis
by a forensic
investigator.
This analysis can be difficult and time-consuming and often
involves trawling
through large amounts of text-based data. Efficient and
effective visual
interfaces and visualisations can vastly improve the time it
takes to analyse data.
These graphical tools can help users gain an overview of data,
spot patterns and
anomalies, and so reduce errors and tedium (Lowman and
Ferguson 2011).
In the case of a digital forensic investigation, an investigator
may need to
examine the network traffic on a defendant’s computer. The

investigators would
begin by investigating network traffic log files taken from the
computer in
question. Marty (2008) reports that instead of showing a jury a
log file that
describes how a digital event occurred, a picture or visual
representation of the
log records should be used (such as the one shown in Figure 1).
At one glance,
a picture such as this is potentially capable of communicating
the content of this
log. So long as viewers are made aware of the context and
content of the image,
most viewers can process this information in a fraction of time
that it would take
them to read the original log (Fielder, 2003).
78
In the area of forensic surveying, the use of visuals to
reconstruct the crime scene

from all the collected and recorded information (whether it be
text, photographs,
sketches, or survey information) is invaluable. The crime scene
will not be
available in its initial condition forever; evidence is often
transitory and
ephemeral. Evidence and information needs to be recorded
before crime scene
officers collect and remove any items of interest (thereby
changing the original
condition of the crime scene).
The court is usually provided with some form of visual
representation of the
crime scene. Traditionally, a hand created drawing (or map)
based on the use of
traditional drafting techniques is represented as a two-
dimensional (2D)
diagram, such as the one shown in Figure 2. In the past this may
have been
crudely drawn or plotted to varying degrees of accuracy.
Figure 2 Hand Drawn Crime Scene Plan
(Courtesy of Mr. G. Schofield, Toronto Police)

Over the past few decades, the widespread introduction and
acceptance of
computer technology has meant that courts have become used to
seeing maps
and plans rendered digitally. The technology used to create
these two-
dimensional displays varies, from simple freeware drafting
programs to complex
mechanical engineering based drafting tools such as Autocad’s
Mechanical
Desktop©. Often investigators use drafting technology that is
tied to their scene-
measuring instrument; for example, many police surveyors draft
plans using
software that download data from their electronic theodolites.
Currently, investigators are starting to see the use of three-
dimensional laser
scanning technology for scene measurement and capture. These
devices provide
79

a combination of laser scanning surveying and digital
photography. The
technology is capable of capturing all physical aspects of a
scene in true three
dimensions (in the x, y and z planes) for accurate interrogation
and analysis.
Figure 3 depicts an image of three-dimensional (3D) laser scan
data; the black
spot (void) is where the scanner was placed to capture the crime
scene. The three-
dimensional model represents a quantitative, objective database
of
measurements, which different operators and investigators can
share for
subsequent analysis.
Figure 3 A Three-Dimensional Laser Scan
(Courtesy of Mr. M. Haag, Albuquerque Police)
5. ANIMATING EVIDENCE
Computer-generated graphical evidence in the US has primarily
been used in
civil cases. One of the first major uses of forensic animation

took place in the
federal civil case for the Delta flight 191 crash. In August 1985
the Delta airplane
with 163 people aboard was caught in a wind vortex and crashed
while
attempting to land at Dallas-Fort Worth Airport, a mile from the
runway. In the
subsequent litigation the US Government offered a 55-minute
computer-
generated presentation, including forensic animations to the
court to explain
details pertaining to each item of evidence (Marcotte, 1989).
There is an extensive precedent concerning the use of a range of
computer-
generated evidence in the United States, but very little in
comparison in many
80
other jurisdictions. Consequently, judges in other jurisdictions
may look to the

US for guidance in considering issues of admissibility. This has
been particularly
true for the introduction of computer-generated animations and
virtual
simulations in courtrooms in the UK and Australia. The legal
precedents for the
admissibility of this technology into courtrooms have been
extensively discussed
in other publications (Galves, 2000; Girvan, 2001; Schofield,
2007; Schofield
and Mason, 2012).
Presenting data related to road traffic accidents in the
courtroom (such as the
example in Figure 4) provides is a prime example of the need to
relate spatial
and temporal data, for which the use of virtual environment
technology has been
extensively adopted (Schofield, et al., 2001). In such cases, a
computer-
generated forensic reconstruction is built using a three-
dimensional virtual
environment of a scene created from actual measurements,
which are usually
taken by the police or investigators at the time of the incident.

Figure 4 An Image from a Forensic Animation of a Road Traffic
Accident
Dynamic vehicle movements are often then simulated using
scientific
calculations based on those measurements and the experience of
the
reconstruction engineer. This computer model can then be
rendered to create a
series of images and animations, which describe the scene or
incident. These
virtual environments, when viewed in court, must support and
corroborate
existing evidence to be admissible as substantive evidence in
any courtroom
(Noond and Schofield, 2002).
81

In this example, the images in Figure 5 show a pathology
reconstruction used in
a murder case to investigate the nature of a stabbing incident. In
this case the
autopsy report described the injuries sustained by a 30-year-old
male who had
received a number of blunt force injuries to the face and chest,
and a stab wound
to the back measuring 3.4 cm in length. The autopsy reported
that the cause of
death was attributed to the extensive internal bleeding caused
by the stab wound
which pierced the heart. It was also concluded that a large
amount of force would
be necessary to cause the incision to the eleventh thoracic
vertebra and that the
bruising to the victim’s body suggested some degree of violent
struggle prior to
the fatal injury (March, et al., 2004; Noond, et al., 2002).
Figure 5 An Image from a Forensic Animation based on
Autopsy Information
The left-hand image (Figure 5) shows the angle of the blade as
it entered the

body, cutting through the vertebra. The right hand image
(Figure 5) shows a
hypothetical body dynamic produced to illustrate the position of
the victim so
82
that the damage to the internal organs matches up with the angle
of the knife
entry (March, et al., 2004).
Unlike the environment surrounding a road traffic accident or
crime scene
reconstruction, where exact, surveyed measurements are usually
available,
pathology or medical visualisations are often based on
descriptive post-mortem
findings or approximate measurements. The use of generic
anatomical computer
models allows the recreation of dynamic events in which
wounding or damage
to a human body occurs. Such a reconstruction is, by its very
nature, often

dependent on the knowledge, expertise and opinion of medical
experts. Hence,
in many of these cases the advice of the expert is seen as crucial
in creating a
graphical representation that accurately matches the medical
opinion. However,
the potential inaccuracies involved mean that these
reconstructions must be
viewed cautiously, and the uncertainty associated with the exact
position of
virtual objects must be explained to the viewer (Schofield and
Mason, 2012).
Stephenson v. Honda Motors Ltd. of America (Cal. Super. Case
No. 81067, 25th
June 1992) is generally accepted to be the first case to admit
evidence using a
computer game engine (real-time simulator). The attorney
convinced a
California Superior Court of the need to use the visual
component of a virtual
reality simulation to help a jury understand the nature of the
terrain over which
an accident victim chose to drive her Honda motorcycle (Dunn,
2001). Honda

argued that the terrain was obviously too treacherous for the
safe operation of a
motorcycle, and that, while two-dimensional photographs and
videos would help
provide the jury with some idea of what the terrain was like, a
three-dimensional,
interactive simulator was much more realistic. In allowing the
evidence, the
court determined that the three-dimensional simulation was
more informative,
relevant, and probative.
Since this initial success, the sporadic worldwide application of
such computer
game based, real-time technology in courtroom situations has
(in most cases)
offered a unique platform for the collection, interrogation,
analysis and
presentation of complex forensic data across a wide spectrum of
crime-scene and
accident scenarios. Three-dimensional reconstructions of
incidents have allowed
the user to interactively visualise views from multiple relevant
positions within

the virtual environment, something that can be beneficial within
the dynamic,
adversarial environment of the courtroom.
The USA has a larger precedent for the admissibility of such
technology into
courtrooms (Schofield and Mason, 2012). All of the above
information has been
collected, extracted and produced by qualified people and/or
experts in their
respective field. They understand the visuals they create and use
and understand
what it is being shown. These visuals are often used as
explanatory tools for
juries and non-experts. However, the general public are rarely
presented with
these visuals without extensive expert explanation, as there is a
possibility that
83
they may not understand the raw visualisation, misconstrue the
data presented,

or may infer a biased view from them.
6. ADVANTAGES AND DISADVANTAGES OF THE USE OF
THE TECHNOLOGY
By their very nature, any discussion of the issues involved in
the presentation of
the whole range of digital evidence is likely to be basic and
generic relating to
broad generalisations about the use of this technology across
diverse courtroom
application areas. Many of the issues raised in the previous
section affect the
admissibility of the reconstructions as courtroom evidence in
the various global
jurisdictions. Consideration of these issues is crucial if such
technology is to be
successfully used. As Wheate (2006) stated:
“It is difficult to determine how well twelve untrained,
underpaid and usually inconvenienced strangers comprehend
and utilise the evidence they hear in court, especially in cases
where the evidence is provided by highly trained experts such

as forensic scientists.”
It is possible to summarise a list of advantages and
disadvantages of the use of
this technology.
Advantages of using the technology include:
– Three-dimensional reconstructions
have the
ability to improve the comprehension, and the memory
retention, of
complex spatial and temporal data and evidence.
– Reconstruction technology can improve the
speed with
which complex information can be imparted to a courtroom
audience,
and therefore may shorten the length of a case. They may rarely,
on
occasion, be responsible for extra points of confusion and cause
an
increase in case length.
– According to research conducted in the USA
(Lederer
and Solomon, 1997) people are twice as likely to be persuaded
when
arguments are supported by visual aids.

– People’s attention is drawn to moving
objects. They
rank top on the hierarchy of methods to draw attention which
spans from
actions, through objects, pictures, diagrams, written word, to
spoken
word (Schofield, 2006). This increased attention should lead to
the triers
of fact (usually a judge and jury) studying the evidence more
intently.
84
Disadvantages of using the technology include:
– Visual displays when used can introduce levels of
prejudice,
if one side has such evidence and the other does not.
– Graphics-based reconstruction technology is
potentially prone to
allowing bias into the presentation, whether that is conscious
bias (a

form of evidence tampering) or subconscious bias. In an attempt
to
reduce this, all computer-generated graphical evidence must be
backed
up with a comprehensive audit trail, and the expert witness
presenting
such evidence must be able to substantiate the accuracy of the
reconstruction, both in terms of the original data used to
reconstruct the
incident, and the accuracy of the reconstruction (Schofield and
Mason,
2012).
– this is an issue of the
‘persuasiveness’
of the technology. It is possible that when a subject is shown a
‘realistic’
computer-generated reconstruction of an event they may feel
mesmerised, or believe that they are seeing the actual event
happen.
Jurors may hence adopt a ‘seeing is believing’ attitude, as has
been
shown to sometimes be the case with television viewing
(Fielder, 2003;
Schofield, 2007; Speisel and Feigenson, 2009). There is

therefore a
potential reduction in their level of critical appraisal of the
reconstructed
evidence.
It does not make sense to use technology just for the sake of
using something
new. However, as many lawyers and expert witnesses continue
to push towards
the dynamic presentations of video, text, documents and other
forms of evidence,
it seems likely that these complex data visualisations and
forensic virtual models
will become a more pervasive and effective alternative to the
sketches, drawings
and photographs traditionally used to portray demonstrative
evidence in the
courtroom (Bailenson, 2006; Galves, 2000; Girvan, 2001;
O’Flaherty, 1996;
Schofield, 2011).
It could be said that when visualising data, a person must have
the knowledge of
the data they are visualising, but they must also have knowledge
of how to apply

the visualising techniques for their audience. Marty (2008)
supports this
reasoning: he reports that most people who are trying to
visualise data have
knowledge of the data itself and what it means, even if they do
not necessarily
understand the visualisation. The viewer tends to visualise only
the information
collected or generated by a specific solution.
The use of advanced visualization tools (specifically three-
dimensional
computer models) allows for the recreation of an incident
illustrating the
chronological sequence of events. However, such a
reconstruction is, by its very
nature, often dependent on the knowledge, expertise and opinion
of the experts.
These must be viewed cautiously and the uncertainty associated
with each item’s
85

position and action within the reconstruction must be explained
by the person
presenting the visual to the audience.
It should be noted that during both investigation and courtroom
presentation
there should be some concern that the investigator/reviewer will
be focused on
the visual images rather than the data source. This is of
importance since visual
evidence has the potential to be particularly misleading and it is
possible that
people may focus only on the elements that have a high degree
of visual appeal.
In all these situations, new visualisation techniques and
products may be used
inappropriately or used to deflect the viewer’s focus away from
key evidential
issues.
In summary, the main benefit of the use of these reconstructions
in the courtroom
is their ability to persuade a jury. In terms of admissibility in
courtrooms around
the world, this persuasive nature may also bring about a variety

of objections to
their use.
7. CONCLUSIONS
Our culture is dominated with images whose value may be
simultaneously over-
determined and indeterminate, whose layers of significance can
only be teased
apart with difficulty. Different academic disciplines (including
critical theory,
psychology, education, media studies, art history, and
semiotics) help explain
how audiences interpret visual imagery. The continuing digital
revolution has
had an enormous impact on the way forensic evidence is
collected, analysed,
interpreted and presented and has even led to the defining of
new types of digital
evidence (for example, digital imagery and video, hard drives
and digital storage
devices). Much of this digital media will end up needing to be
admitted into
courtrooms as evidence. In most jurisdictions around the world
technology can

be slow to become legally accepted. It is fair to say that, in
general, legislation
for the admissibility of digital media usually lags behind the
technological
development (Schofield and Mason, 2012). In a very real and
practical sense,
the analysis of courtroom imagery and its interpretation by
jurors and other
courtroom participants)is only just beginning (Speisel and
Feigenson, 2009).
This paper has highlighted thematic areas where novel
technologies may bring
improvement to the forensic process. It underlines the fact that,
recently, three-
dimensional forensic reconstruction techniques are being
increasing used (along
with other multimedia technologies) to present forensic
evidence in the
courtroom. The technologies have been targeted in this area due
to their success
in communicating highly complex, technical, spatial and
temporal evidential
information to the general public.
Forensic science technology advances rapidly, and the public,

who regularly
watch high-technology crime scene investigation on television,
expect to see
their TV experience duplicated in the real courtroom
environment. The public
86
expects professional visual representations illustrating complex
forensic
evidence, polished digital media displays demonstrating the
location of spatially
distributed evidence and dynamic animated graphics showing
event
chronologies.
Modern systems for creating visualisations have evolved to the
extent that non-
experts can create meaningful representations of their data.
However, the process
is still not easy enough, mainly because the visual effects of
processing, realising

and rendering data are not well-understood by the user, and the
mechanisms used
to create visualisations can be a largely ad hoc process
(Rogowitz and Treinish,
2006).
Commercial media companies often magically appear offering
‘professional
graphics’, ‘forensic animation’ and ‘crime scene reconstruction’
services similar
to those seen on the televised forensic/crime shows. In countries
all around the
world, many lawyers and expert witnesses now use, and have to
confront in an
adversarial manner, computer-generated animations, three-
dimensional virtual
reconstructions, real time interactive environments and
graphical computer
simulations (Schofield, 2007). However, there is little research
being undertaken
to consider the impact this technology is having in the
courtroom, in particular
how it is affecting the decisions being made (Schofield, 2011).
This concludes part one of this two part investigation into the
use of digital

displays in the courtroom. Part two of this paper will analyse
and discuss specific
problems in relation to the use of this technology in the
courtroom.
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Field Manual for
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2007, Bangkok, Thailand.
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Accident scenarios:

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Schofield, D., & Mason, S. (ed). (2012). Using Graphical
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Nexis.
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Australian Journal
of Forensic Sciences, 38(2): 75.
BIOGRAPHICAL DETAILS
Dr. Schofield (PhD) is currently Director of Human Computer
Interaction
(Associate Professor) at the State University of New York
(SUNY) Oswego,
USA, and an Adjunct Associate Professor of Digital Forensics
in the School of
Computer and Security Science at Edith Cowan University,
Perth, Australia.
89
Previous to this position he held the title of Associate Professor
of Computer
Games and Digital Media, in the School of Creative Media at
RMIT University

in Melbourne, Australia. In his earlier career he was one of the
managers of the
internationally renowned Mixed Reality Lab (MRL) at the
University of
Nottingham in the UK.
Dr. Schofield has also been on the management board of both
the Visual
Learning Lab (a UK HEFCE centre of excellence) and the
Learning Sciences
Research Institute (UK). Dr. Schofield also remains a director
and major
shareholder of Aims
Solution
s Ltd., a UK based company providing computer
graphics visualisation services and virtual reality based
simulation training
products to a wide range of public and private sector
organisations.

Dr. Schofield has been involved in developing crime scene
reconstructions using
computer games/graphics technology for over 15 years. His
research is
specifically concerned with representation and understanding of
visual
information in the courtroom environment. The reconstructions
he and his team
create cover a wide range of forensic visualisation from
computational fluid
dynamics models to blood spatter patterns at crime scenes, from
road traffic
accident reconstruction to post-mortem pathology visualisation.
Dr. Schofield is
regularly used as an expert witness in courts all over the world
and has worked
on many high profile cases.

Dr. Schofield has been involved in forensic casework in the UK,
Australia, the
USA and Malaysia. A few years ago, he was responsible for the
facial
reconstruction of an Egyptian mummy for a documentary called
Nefertiti
Reserected on the Discovery Channel. For the last six years he
has also been
working on a major facial biometric project for the FBI (Federal
Bureau of
Investigation) in the USA.
Ken Fowle (PhD) is currently the Head of School (Associate
Professor),
Computer and Security Science, at Edith Cowan University
(ECU), Western
Australian and an Adjunct Associate Professor at the University

of Western
Australia, Centre of Forensic Science (CFS). Prior to moving
over to academia,
Dr Fowle was employed by the Department of Mines and
Petroleum in the
Investigation Branch.
Dr Fowle’s interest in visualisation and accident reconstruct
started back in
1996, when seconded to the departments Mine Safety Branch to
assist with
developing computer applications for mining accident and
incidents. This
interest was further enhanced in 1999 when he was seconded to
Central Tafe to
establish a research and development group specifically for
developing

computer graphics for the resource sectors of Western Australia.
During his time
at Central Tafe, Dr Fowle undertook a PhD with the University
of Nottingham’s
AIM’s research group.
90
In 2003 Dr Fowle returned to the Department of Mines and
Petroleum where he
continued his research into visualisation and won funding from
the WA
Government, to continue research in the use of 3D environments
for accident

reconstruction. This research interest continues at ECU with
collaboration with
the WA Police Service, London Metropolitan Police,
Northumbria University,
State University of New York and local and national research
groups such as
IVEC, CFS and ECU’s Security Research Institute.
Dr Fowle is past president of the Australian and New Zealand
Forensic Science
Society and is still an active committee member, is a member of
the International
Association for Forensic Survey and Metrology, American
Society for Industrial
Security, Australian Computer Society and the Australian Law
Enforcement
Forensic Surveying Working Group.

Reproduced with permission of the copyright owner. Further
reproduction prohibited without
permission.

Journal of Quantitative Criminology, Vol. 15, No. 2, 1999
Using National Incident-Based Reporting System
Data for Strategic Crime Analysis
Donald Faggiani,1,2 and Colleen McLaughlin1,3
The utility of the National Incident-Based Reporting System
(NIBRS) for stra-
tegic crime analysis has yet to be explored. The NIBRS
represents an advance-
ment over existing reporting systems and possesses considerable
utility to
frontline law enforcement with respect to strategic crime
analysis. This paper
discusses the utility of the NIBRS for identifying local and
regional trends in
narcotics related offenses. As an example, we selected four
localities from the
1997 Virginia NIBRS data to examine trends in the
saleydistribution and pos-
session of narcotics. Our analysis shows that the NIBRS
provides significantly
more incident-related detail than has heretofore been available
for strategic crime

analysis at the regional or state level. Moreover, the NIBRS
provides neighbor-
ing communities the opportunity to compare information on
emerging crime
patterns and criminal enterprises which extend beyond local
boundaries. Finally,
enhancing local reporting compliance by highlighting the
strategic utility of the
data to local law enforcement will ultimately ensure the quality
of the data set,
which can then be employed by larger entities as well as
criminal justice research-
ers for policy development and planning.
KEY WORDS: NIBRS; crime strategy; narcotics enforcement;
drugs; crime
analysis.
1. INTRODUCTION
The utility of crime analysis techniques for identifying patterns
of crime
over time and location is well documented. Maltz et al. (1991)
note that
‘‘information is the lifeblood of the police’’ (p. 12). While

information may
be the lifeblood of the police, a well-designed incident-based
data system
provides the infrastructure that maintains the information for
analyzing
emerging or ongoing crime problems. A primary objective of
the FBI’s
1Virginia Statistical Analysis Center, Department of Criminal
Justice Services, 805 East Broad
Street, Richmond, Virginia 23219.
2To whom correspondence should be addressed. e-mail:
[email protected]
3Departments of Surgery and Emergency Medicine, Medical
College of Virginia, Virginia
Commonwealth University, P.O. 980454, Richmond, Virginia
23298-0454.
181
0748-4518y99y0600-
Corporation

Faggiani and McLaughlin182
National Incident-Based Reporting System (NIBRS) is to serve
as a basic
foundation for a crime analysis information system. The intent
is to provide
a crime information tool with standardized data elements that
has utility at
the local law enforcement level for tactical crime analysis.
Unfortunately, the NIBRS has not achieved immediate and
widespread
acceptance. In part this may due to misunderstandings
surrounding the uses
of NIBRS data by local and state law enforcement officials. A
Joint Docu-
ment of the Bureau of Justice Statistics (BJS) and the Federal
Bureau of
Investigation (FBI) outlines seven impediments to the
implementation of
NIBRS (BJS, 1997). Second on the list of impediments, just
below funding,
is uncertainty of benefits. Through a series of national focus
groups, the

FBI and BJS study found that the participants of these groups
felt that the
NIBRS was useful only for macro-level analysis and had no
practical utility
for local law enforcement. Analysis of the NIBRS system,
however, reveals
that it possesses significant and immediate utility for local
agencies.
The NIBRS data system is designed to provide basic,
standardized
incident-level information that is consistent across law
enforcement jurisdic-
tions. The resulting data set represents an invaluable asset to
local law
enforcement, as well as other governmental organizations and
criminology
researchers. The specific aim of the current paper is to provide
an example
of how NIBRS data can be useful for strategic crime analysis
and criminal
investigative analysis at the local and regional levels.
The analysis focuses on identifying local and regional trends in
the

saleydistribution and possession of narcotics. Narcotics-related
offenses
have been selected for the present study for three reasons. First,
narcotics-
related offenses affect most communities: large and small,
urban and rural.
Second, the NIBRS permits the opportunity to analyze specific
types of
narcotics-related offenses (e.g., possession and
sellingydistribution), which
significantly enhances the potential utility of the NIBRS data to
local law
enforcement. Finally, narcotics-related offenders have the
ability to be rela-
tively mobile in their criminal activity. With some geographic
constraints,
drug users and sellers may conduct their transactions in a wide
variety of
locations of varying levels of convenience and risk to either
party, irrespec-
tive of established community boundaries. Drug-selling and
illegal drug
markets also have the potential to be ‘‘franchised,’’ moved,
established, and
reestablished. Dealers may bring their product to the user or

may elect to
sell in their home community. While user prevalence and
preference may
impact the establishment and location of illegal drug markets, it
is also
likely that local tolerance of drug crimes and local law
enforcement practices
may impact these decisions as well. Therefore, data pertaining
to patterns
and trends for narcotics-related offending across localities
would be
especially useful in developing law enforcement tactics and
strategies.
Using the NIBRS for Strategic Crime Analysis 183
2. VIRGINIA NIBRS DATA
Virginia is still in the developmental stages of establishing the
NIBRS.
The data for the current analysis were provided by the Virginia
State Police
(VSP) and include 133 (48.9%) certified NIBRS agencies out of

272 total
agencies in Virginia. As with most U.S. localities reporting
NIBRS data in
1997, the Virginia localities are heavily skewed toward rural
and small
agencies. The VSP certifies local law enforcement agencies for
NIBRS com-
pliance, which then submit their NIBRS data on a monthly
basis. The VSP
check the reliability of the local reporting prior to submitting
the data to
the FBI’s Uniform Crime Reporting Section. The data for this
analysis are
the same data the VSP submits to the FBI.
For the current project the data were structured to allow for
multiple
unit analysis within one file. The data include all incidents in
which a nar-
cotics-related offense was charged, even if the narcotics-related
offense was
not the most serious offense in the incident.4 For example, in an
incident
involving a motor vehicle theft and a narcotics possession
offense, the motor

vehicle theft would be reported as the most serious offense in
the incident.
Further selections were made to limit the analysis to all
narcotics (except
marijuana) offenses where the type of drug was known. In
addition, we
limited the analysis to criminal acts of sellydistribute and
possess. The link-
ages between the various NIBRS segments provide detail on
drug type,
criminal act (sellydistribute or possess); and drug quantity
(including how
the quantity is measured), as well as other offenses that might
be involved
in the incident such as weapon offenses or theft. To minimize
problems with
compliance and sampling frames, only agencies certified to
report NIBRS
data on or before January 1, 1997, and reporting data for all 12
months of
1997 were selected. In all, 57 local agencies met these criteria.
To provide
focus for our discussion we selected four localities, three of
which appear
to have emerging or ongoing problems with narcotics offenses.

It is important to emphasize that the Virginia localities
represented in
the present study are skewed heavily toward rural and small
agencies. This
can have a significant impact on the ability to generalize the
outcomes of
any analysis to larger populations. Moreover, although actual
data are used,
differences in sampling frames and levels of compliance
significantly limit
the ability to draw firm conclusions from the results. As such,
any results
drawn from this analysis must be viewed as preliminary. The
intent was to
examine the use of the NIBRS for strategic crime analysis, not
draw statisti-
cal inferences from the data. In light of these caveats, the names
of the
communities represented in this study have not been provided in
an effort
4Seriousness of the offense is based upon the FBI’s UCR
offense hierarchical rule as specified
in the Uniform Crime Reporting Handbook (1991).

to prevent the misinterpretation of these preliminary results or
embarrass-
ment to the locality.
3. TACTICAL CRIME ANALYSIS
Crime analysis techniques which help investigators identify
patterns of
crime over time and location are extremely useful. Tactical
crime analysis
can provide investigators extensive detail on offenses occurring
in specific
areas at specific times. At the local agency level tactical
planning can be
enhanced significantly through effective utilization of NIBRS
data. Com-
parison of incident and arrest rates for specific patterns of
offending has the
potential to reveal emerging patterns or trends. Moreover, the
use of the

NIBRS for surveillance purposes affords the opportunity for
routine moni-
toring of local conditions. Any departure from established
‘‘baseline’’ con-
ditions might serve as an effective early warning system for
local law
enforcement. Consequently, the ability to monitor and anticipate
local and
regional changes in patterns of offending provides local law
enforcement
the opportunity to engage in proactive prevention strategies
rather than the
reactive strategies often required. Analysis of arrest rates also
provides the
opportunity to compare and contrast local law enforcement
strategies
between communities, a strategy that can be useful to
multijurisdictional or
regional drug task forces. Patterns of offending open to
‘‘franchising’’ in
rural communities may be effectively monitored and, perhaps,
anticipated
through NIBRS data.
Comparison of incident to arrest rates may provide insight into

factors
including local tolerance for certain patterns of offending. For
example,
high arrest rates for narcotics-related offenses may suggest an
emerging drug
problem. On the other hand, high arrest rates may indicate a low
tolerance
for substance use in the community. This information coupled
with street-
level intelligence may yield insight into the relative
attractiveness of a com-
munity to criminal enterprise. Communities with high levels of
known nar-
cotics activity but low overall arrest rates may indicate a degree
of tolerance
for certain patterns of offending. Differences in aggressiveness
of law
enforcement may make certain communities particularly
attractive to
offenders. Communities not responding to patterns of offending
with
aggressive sanctions may appear as open territory to offenders.
NIBRS data provide the ability to analyze specific types of
offending

not previously possible with the aggregate data provided
through UCR
reports. For example, distinguishing narcotics possession from
saleydistri-
bution offenses (possible with the NIBRS) significantly
enhances surveil-
lance. Differences in the rates of these types of offenses may
have very
different implications for the community. High rates of
possession offenses
compared to saleydistribution offenses may indicate differential
disposition
of cases or community tolerance. On the other hand, it may
suggest local
interest in a certain drug or an increased preference for a
particular pattern
of substance use. In response to changes in demand, local users
may estab-
lish a distribution network to meet their needs. The community
also may

become attractive to larger distributors from outside the area.
Therefore,
increases in possession offenses may foretell the creation of
new drug mar-
kets or precede the establishment of an illegal distribution
network, either
from within or outside the community.
Conversely, high rates of selling with respect to possession
offenses may
reflect local discretion, suggesting harsh sanctions or ‘‘zero
tolerance’’ for
drugs in the community. These findings also may indicate that
this com-
munity serves as a local distribution center for the surrounding
localities. A
large increase in saleydistribution incidents may suggest the
targeting of a
community by drug sellers or the attempt to create a new
market. Knowl-
edge of offender characteristics may enhance the ability to track
and moni-
tor these individuals, suggest the source of the drugs (e.g., high
school
students), or indicate the involvement of outside criminal

enterprises. Analy-
sis of the relative quantities seized would provide local analysts
the oppor-
tunity to answer many of these questions while plotting and
anticipating
local trends.
Analysis of local data in conjunction with data from
surrounding com-
munities provides localities the opportunity to analyze trends
and patterns
that extend beyond their jurisdiction. Offenders and criminal
enterprises are
not constrained by the same jurisdictional lines that constrain
law enforce-
ment. Therefore techniques that permit the expansion of
criminal intelli-
gence beyond jurisdictional lines may be critical to the effective
identification, monitoring, and apprehension of these
individuals and
groups. In addition, relative differences in criminal activity will
provide
localities the opportunity to compare their crime rates. Lower
rates may
suggest effective law enforcement techniques that could be

shared with
neighboring communities. Communities with higher rates could
examine
what makes their community attractive to this pattern of
offending. Again,
the identification of outside criminal elements could cause a
locality to
examine what makes their community attractive to outside
criminal
elements.
4. ANNOTATED EXAMPLE
As an illustration of how NIBRS data might be used to evaluate
local
trends in narcotics-related offenses, offense data from four
communities
within the Commonwealth of Virginia have been compiled.
Analysis of
Table I. SaleyDistribution and Possession of Narcotics by

Locality
Possession Sale
incidents Possession incidents Sale
Community Populationa (% total) rateb (% total) ratec Total
A 17,890 18 100.6 34 190.1 52
(35%) (65%)
B 88,300 37 41.9 2 2.3 39
(95%) (5%)
C 22,800 39 140.4 94 416.7 133
(29.3%) (70.7%)
D 34,000 294 850.0 151 423.5 445
(66.1%) (33.9%)
aPopulation data are 1997 estimates provided by the Weldon
Cooper Center for Public Service,
University of Virginia.
bSale and possession rates are per 100,000 population.

these data reveals areas where additional qualitative intelligence
on local
criminal activity is not only useful, but essential in the analysis
of these
incident-based data.
Table I shows the 1997 narcotics5 sale and possession rates for
four
localities in Virginia. The offender is the unit of analysis and
the data
include all offenders identified in all incidents in which a
narcotics sale andy
or possession offense was charged. The narcotics offense may
not have been
the most serious offense or the only offense and the offender
may or may
not have been arrested. Review of the narcotics offenses in
Table I revealed
large differences in incidents rates between communities. For
example, com-
parison of the per capita rates for communities A and B
suggested a large
difference in narcotics-related offenses. Further analysis of the
data, possible
with NIBRS, revealed qualitative differences in the type of

offending. In
community A, the preponderance of incidents was for the
saleydistribution
of narcotics, while the majority of incidents in community B
were for pos-
session offenses.
The differences in incident rates may be interpreted in at least
two
ways. As described above, an increased incident rate for
narcotics-related
offenses may be suggestive of an established or emerging drug
problem in
the community. Conversely, an increased rate may indicate
aggressive polic-
ing or diminished community tolerance for substance use andyor
drug sell-
ing in the community. Knowledge of the data at the community
level would
provide further insight into the meaning behind the numbers.
5For the purposes of this analysis we operationalize narcotics as
crack cocaine, powder cocaine,
heroin, and all other illegal hallucinogens, stimulants, and
designer drugs. Marijuana and

other cannabinoids (e.g., hashish) are not included.
Table II. Drug Type by Activity and Locality
Activity
Sell, distribute,
Community Type of drug manufacture Possession Total
C Crack cocaine
Number 43 14 57
(% total) (45.7%) (35.9%) (42.9%)
Cocaine
Number 50 13 63
(% total) (53.2%) (33.3%) (47.4%)
Heroin
Number 2 2
(% total) (5.1%) (1.5%)

Othera
Number 1 10 11
(% total) (1.1%) (25.7%) (8.2%)
D Crack cocaine
Number 144 291 435
(% total) (95.4%) (99.0%) (97.8%)
Cocaine
Number 2 2
(% total) (0.7%) (0.4%)
Heroin
Number 7 1 8
(% total) (4.6%) (0.3%) (1.8%)
Othera
Number
(% total)
aIncludes hallucinogens, stimulants, and designer drugs.
Localities C and D both appear to have very high overall

offender rates
for narcotics offenses. However, locality C reported an
extraordinarily high
per capita rate for saleydistribution incidents (416.7) and a
much lower rate
for possession incidents (140.4). Locality D, on the other hand,
has a very
high total rate but the pattern of sale (423.5) vs possession
(850.0) is
opposite that of agency C.
Analysis of the NIBRS data for agencies C and D provides
further
insight into the problems in these communities. Table II
provides a break-
down on the drug types involved in the incidents for these two
localities. As
in Table I, in Table II the offender is the unit of analysis. Table
II shows
that narcotics-related offenses in locality D are almost
exclusively crack
cocaine-related offenses. Locality C, on the other hand, shows a
different
pattern. Narcotics-related offenses are almost evenly split
between powder

cocaine and crack cocaine. Other narcotics offenses represent
only a small
overall percentage of the offenders in both localities. However,
this is one
area that should be followed closely, as many of the larger
cities in the
United States are beginning to report increases in their heroin
markets.
Although relatively small, the number of offenders charged with
the sale or
distribution of heroin in locality D may be an indication of a
small but
possibly emerging heroin distribution market. On the other
hand, locality
C does not appear, at least in 1997, to have a problem with the
sale or
distribution of heroin.
Unlike the standard UCR program, NIBRS provides detailed
infor-

mation on the incident. Traditional research on narcotics
offenses at the
community level has been limited to the FBI’s UCR summary
level data.
Detailed information on narcotics sale and distribution
generally has come
from extensive research efforts such as Goldstein (1985), where
specific
information is gathered for limited areas within large cities.
NIBRS offers
crime analysts and researchers the opportunity to expand their
knowledge
of drug offenses as well for a wide range of other offenses.
Additional analysis using UCR6 data for these two communities
shows
that locality D experienced significant increases in violent
crime beginning
in the late 1980’s. By 1994 the locality’s violent crime rate
began to decline.
Locality C had a low violent crime rate throughout the 1980’s.
Around 1990
the crime rate in community C began to increase. By 1997 the
violent crime
rate in community C was 171% higher than the 1987 level. The

nexus
between violent crime and drugs has been explored elsewhere
(e.g.,
Goldstein et al., 1992). The intent here is to provide a context
for the differ-
ences between the sale and possession rates reported by
agencies C and D.
Locality D had an emerging drug and violence problem in the
late
1980s. However, the 1997 NIBRS data for this community
reports an over-
all clearance rate7 of 76% for incidents involving a narcotics
offense that
are known to the police. The numbers reported for 1997 would
be consistent
with a community that is coming to grips with a serious
problem. Overall
the community appears less tolerant of both drugs and violence
and it may
be paying off with higher arrest rates for drug offenses and an
overall lower
violent crime rate.
UCR data show that community C has had an ongoing problem

with
narcotics-related arrests dating back to the mid-1980s, while
their violent
crime rate was relatively low throughout the 1980s. Around
1991, however,
community C began to show a steady increase in reported
violent crime that
6It is not our intent to conduct a comparison between the UCR
summary data and NIBRS
data. UCR data are used to provide background for the analysis.
7For the purposes of this discussion, a clearance is any incident
involving a narcotics offense
in which there was at least one arrest.
has continued through 1997. Relative to the clearance rate for
locality D,
locality C’s 1997 narcotics-related incident clearance rate is
low. The ques-
tion becomes are the low arrest rate and high rates for sale of

narcotics a
sign of an emerging or ongoing problem. The pattern of
increasing violent
crime and low arrest rates for sale of narcotics may indicate that
the com-
munity has become the target for expansion by outside drug
dealers.
The intent of the above scenario is to provide an example of
how the
NIBRS would be useful for tactical crime analysis. The
knowledge of crime
patterns and trends that can be extracted from a NIBRS data
system can
prove beneficial to all law enforcement agencies. However, the
NIBRS can
provide information only on patterns of criminal activity. The
NIBRS can
provide a great deal more information on each of the narcotics
incidents in
this analysis. For example, 41% of the crack cocaine arrests in
community
D were at a residence, compared to 57% of the arrests in
community C. It
is also possible to determine the time of day and day of the

week when the
offenses occurred. Additional analysis on the part of local law
enforcement
will be necessary to answer the questions and find solutions.
The key is
that the NIBRS provides an opportunity for strategic crime
analysis that
heretofore was unavailable.
In summary, effective utilization of NIBRS data can enhance
signifi-
cantly tactical crime analysis and planning at the local level.
Analysis of
specific patterns of offending, and comparison and contrast of
incident and
arrest rates within as well as across jurisdictions, affords the
opportunity to
effectively monitor and anticipate local and regional trends.
This approach
permits the evaluation of local law enforcement strategies and
provides the
opportunity to initiate proactive crime prevention strategies.
5. CRIMINAL INVESTIGATIVE ANALYSIS

Block’s (1993) research on homicides has shown that the risk of
becom-
ing a victim and the risk of being an offender can vary by
demographic
groups, location, time, and type of homicide. The NIBRS offers
the oppor-
tunity to identify the victim, offender, and interaction risk
levels for all
offenses reported to the FBI.
One of the primary advantages of NIBRS is that each incident
can be
analyzed independently, and interactions between hierarchical
units within
the data set can be analyzed with linkages between the different
units. For
example, these linkages allow the victim to be linked to the
offenders and
the offenders to the offenses. The ability to establish these
linkages between
victim, offender, and offense is critical to analyzing criminal
events and
behavior within the context of larger trends. This becomes
important when
defining profiles of victim or offender types, and when

examining victim–
offender relationships. This feature can be used to identify
particularly vul-
nerable segments of the community, establish victim risk, and
track serial
crime. Again, the ability to cross jurisdictional boundaries with
this
approach may enhance the ability to track offenders and analyze
crimes not
constrained by the same boundaries imposed on law
enforcement.
6. SUMMARY AND CONCLUSIONS
The NIBRS represents an exciting opportunity for researchers
and
practitioners to interact through the use of a common tool. The
wealth of
detail available in the NIBRS will permit scientists and
practitioners to

interact and exchange information through a common medium.
The struc-
ture provided by a common NIBRS data system also transcends
the needs
of the local agency, permitting neighboring communities the
opportunity
to compare like information on emerging crime patterns and on
criminal
enterprises which extend beyond local boundaries. Access to
data from
neighboring communities would permit agencies to cross
jurisdictional lines
with respect to intelligence without requiring complicated
interagency agree-
ments for collaboration. Data from neighboring communities
could then be
used to follow, as well as anticipate, trends. The NIBRS will
also be an
important tool for providing policy-relevant information across
jurisdic-
tions and across levels of government, giving police
administrators as well
as state planners the ability to develop or redirect policies.
Promoting local
participation by highlighting the strategic utility of the data to

local law
enforcement will ultimately enhance the quality of the data,
which can then
be employed by larger entities (e.g., counties, states and
multijurisdictional
task forces) for policy development and planning.
Unfortunately, as the BJSyFBI report (1997) indicates, state and
local
officials envision limited utility of the NIBRS data for local law
enforce-
ment. However, accurate data collection from this same group is
essential to
effective implementation of the NIBRS system. In light of this
discrepancy,
perhaps the true challenge to NIBRS lies in promoting the
collaboration
and alliance with local law enforcement or the provision of
incentives for
accurate and complete compliance with the data collection
requirements.
These incentives may be limited to a description of the tactical
crime
analysis functions embedded within the data set or may extend

to include
the availability of analysis programs andyor technical assistance
for front-
line users. The NIBRS represents a huge advancement over
existing
reporting systems and possesses considerable utility to frontline
law enforce-
ment with respect to tactical crime analysis. A brief description
of the
advantages of the NIBRS and their relation to tactical crime
analysis may
be sufficient to effect compliant data collection. Development
of a user-
friendly interface which could be utilized by an investigator in
the field to
access NIBRS data would facilitate the development of local
crime preven-
tion strategies and may also be useful in case investigations.
These potential
benefits are well within the realm of NIBRS capabilities and

would be par-
ticularly useful to smaller jurisdictions that lack crime analysis
capabilities.
The availability of technical support from those familiar with
and using
the NIBRS database would further enhance the ability of a
community to
utilize the data effectively. The opportunity to utilize a common
data set
and interact with the individuals who have firsthand knowledge
of the
crimes and trends included in the data may be an invaluable
resource for
researchers and analysts using NIBRS data for research
purposes. Regard-
less of the form, however, the provision of incentives may
represent the
difference between the type of data set resulting from
mandatory com-
pliance or an ‘‘enhanced’’ compliance where the data are
collected and
meticulously maintained by the frontline user who has a vested
interest in
the success of the product.

REFERENCES
Block, C. R. (1993). Organizing a dataset to support analysis of
multiple units: Victim, incident
and offender risk. In Block, C. R., and Block, R. L. (eds.),
Questions and Answers in
Lethal and Non-lethal Violence, National Institute of Justice,
Washington, DC, pp. 209–
212.
Bureau of Justice Statistics (1997). Implementing the National
Incident-Based Reporting System:
A Project Status Report, Government Printing Office,
Washington, DC.
Federal Bureau of Investigation (1991). Uniform Crime
Reporting Handbook, FBI, Washington,
DC.
Goldstein, P. J. (1985). The drugsyviolence nexus: A tripartite
conceptual framework. J. Drug
Issues 15: 493–506.
Goldstein, P. J., Brownstein, H. H., and Ryan, P. J. (1992).

Drug-related homicide in New
York: 1984 and 1988. Crime Delinq. 38(4): 459–476.
Maltz, M. D., Gordon, A. C., and Friedman, W. (1991).
Mapping Crime in Its Community
Setting: Event Geography Analysis, Springer-Verlag, New
York.
Copyright of Journal of Quantitative Criminology is the
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posted to a listserv without the copyright
holder's express written permission. However, users may print,
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263

Journal of Contemporary
Criminal Justice
Volume 24 Number 3
August 2008 263-273
© 2008 Sage Publications
10.1177/1043986208318225
http://ccj.sagepub.com
hosted at
http://online.sagepub.com
Risk Assessment in Organized
Crime
Developing a Market and Product-Based
Model to Determine Threat Levels
Jay S. Albanese
Virginia Commonwealth University, Richmond
The risk posed by organized crime is a central concern of
governments around the world.
The infiltration and control of legal and illegal markets and

products is a major concern
in nearly every country. New agencies and initiatives are under
way in the United
Kingdom, Canada, New Zealand, Belgium, and elsewhere, with
the specific purpose to
better predict and detect organized crime activity. This article
proposes a model to assess
the risk of organized crime. It employs a different unit of
analysis from most current
models, focusing on illicit markets rather than groups, and it
offers a practical alterna-
tive for determining the presence of organized crime in areas
that may or may not have
a history of organized crime involvement.
Keywords: organized crime; risk assessment; prediction; illicit
markets; threat assess-
ment; criminal markets
Definition of Organized Crime
It is important to be clear about what we mean by organized
crime. Too often, dis-
cussions of organized crime lack focus because it is not clear
what precisely is being

talked about. Definitions of organized crime have been offered
by a wide variety of
authors and researchers over the years, and an analysis of those
definitions is presented
in Table 1. It can be seen from Table 1 that authors have
identified 11 different char-
acteristics of organized crime in their definitions. When these
are broken down,
however, it is seen that 5 characteristics are most typical:
organized continuing hier-
archy, rational profit through crime, use of force or threat,
corruption of public officials
for immunity, and public demand for services. There seems to
be less consensus
about whether organized crime holds a monopoly over particular
markets, has
restricted membership, is nonideological, specializes in certain
activities, has a code
of secrecy, or engages in extensive planning of its activities.
A definition based on the consensus of these authors (see Table
1) would read,
“Organized crime is a continuing criminal enterprise that
rationally works to profit
from illicit activities that are often in great public demand. Its

continuing existence is
maintained through the use of force, threats, monopoly control,
and/or the corruption
264 Journal of Contemporary Criminal Justice
of public officials” (Albanese, 2007, p. 4). The precise size of
the enterprise or group
is not important to the definition; two persons are the minimum
required to engage
in a criminal conspiracy, so any group of two or larger suffices.
Organized crime can be described either by the activities it
engages in or by the
groups involved. Continuing criminal conspiracies that
constitute organized crime
require insiders and outsiders to connect suppliers with
customers and also to protect
the enterprise from law enforcement. Therefore, organized
crime groups need to obtain
the product (e.g., drugs, stolen property) and make it easily
available to customers
(e.g., movement from source to destination) while obtaining

some “insurance” when
members are caught or convicted (e.g., the need for corruption
of public officials to
protect the enterprise from disruption). All successful organized
crime groups require
these elements to survive and make a profit.
The Risk of Organized Crime
Determining the risk of organized crime requires specific local
assessments rather
than global judgments. To say that organized crime is a problem
in the United States,
for example, is too broad a statement to be useful because it
overlooks the huge vari-
ations within the country (i.e., some locations have no
organized crime problem,
whereas other locations within the country have serious
organized crime problems).
Global assessments of organized crime abound: “Transnational
organized crime
continues to grow in the absence of a comprehensive, integrated
global counter strat-
egy. . . . There are more slaves in the world now than at the
highest point of the African

slave trade” (World Federation of United Nations Associations,
2007). More than $1
trillion is paid each year in political bribes (World Bank
Institute, 2007). Global
Table 1
Definitions of Organized Crime in the Literature
Characteristic Number of Authors
Organized hierarchy continuing 16
Rational profit through crime 13
Use of force or threat 12
Corruption of public officials to maintain immunity 11
Public demand for services 7
Monopoly over particular market 6
Restricted membership 4
Nonideological 4
Specialization 3
Code of secrecy 3
Source: Albanese (2007).

assessments like these are useful in drawing attention to the
problem, but they are
not useful in assessing the risk or threat in a particular location.
To accomplish this,
more precise information at the local level is required.
Most risk or threat assessments in organized crime have focused
on groups. These
assessments are often carried by law enforcement agencies to
determine which
groups are at highest risk or pose the greatest threat. The
methods used to determine
risk involve identifying the universe of known crime groups in
the country and then
ranking them by their attributes and potential seriousness.
Sample attributes used in
these assessments include violence, corruption, infiltration,
sophistication, discipline,
insulation, stability, and group cohesiveness (Royal Canadian
Mounted Police, 2006;
Serious Organized Crime Agency, 2007).
In a similar way, the Federal Bureau of Investigation’s
Organized Crime Section
at FBI Headquarters is divided into three units, which are

focused on Italian American
organized crime, Eurasian/Middle Eastern Organized Crime, and
Asian and African
criminal enterprises (Federal Bureau of Investigation, 2008).
This illustrates a primary
focus on crime groups as a focal point for attention to organized
crime. Table 2 is
excerpted from a Canadian threat assessment. It illustrates that
threat assessment is
carried out by law enforcement agencies to target individuals
and groups determined
to pose the highest risk. This selection of “groups” as the
criterion to be predicted is
based on the premise that law enforcement agencies place
apprehension of criminals
as the central part of their mission. Experience shows, however,
that apprehension of
organized crime figures usually does not eliminate the group—
which recruits new
members or promotes existing members after a successful
prosecution (Organized
Contraband Smuggling, 2000; President’s Commission on
Organized Crime, 1987).
The expectation that prosecution of individuals involved in
organized crime groups

will affect the operation of the group and also affect the illegal
market for the illicit
products in question is problematic. Successful prosecutions of
organized crime
figures affect groups for only a short period because the
customer demand for the
illegal products or services is not diminished by a prosecution,
so existing or new
groups continue to exploit these illicit markets.
High-Risk Activities Versus High-Risk Groups
A focus on organized crime activities rather than groups is
useful for purposes of
assessment and analysis to produce an objective basis for
investigative priorities and
targets. Three categories of organized crime can be identified:
provision of illicit
services, provision of illicit goods, and infiltration of legitimate
business (Albanese,
2007). Provision of illicit services involves money, sex, and
gambling outside legit-
imate avenues (i.e., loan-sharking, prostitution and
pornography, and illegal gambling).
Provision of illicit goods includes drug trafficking or the

buying, selling, or distribution
Albanese / Risk Assessment in Organized Crime 265
of stolen property. Infiltration of legitimate business involves
coercive use of legal busi-
nesses to exploit them for profit or use them for money
laundering.
This three-part typology of organized crime can be subdivided
further into specific
offenses of concern to law enforcement agencies and the general
public. Summarized
in Table 3, it can be seen that the provision of illicit services
entails the offenses of
commercialized sex (prostitution or pornography), illegal
gambling, human trafficking,
and subcontracting to others (to provide services such as illicit
dumping of waste,
trafficking in human organs or protected animal species, or
murder for hire). The
provision of illicit goods includes the offenses of drug
trafficking, property theft

(e.g., automobiles, clothing, art), and counterfeiting (e.g.,
identity documents, software,
DVDs, CDs, weapons). The infiltration of business involves
extortion of business
owners, racketeering (ongoing criminal enterprises which
“front” for illegal activity),
money laundering, and fraud (e.g., investment fraud, Internet
phishing, and smuggling
of goods).
Table 3 suggests that much of organized crime can be grouped
into 1 of 10 dif-
ferent categories of offenses. Of course, manifestations of these
criminal behaviors
can change over time, but the underlying conduct is remarkably
stable. Consider
Table 4, which compares “traditional” with “modern” forms of
organized crime
Table 2
Findings From 2006 Canada/U.S. Organized Crime Threat
Assessment

Asian organized crime groups are distinguished by a high level
of criminal entrepreneurship. They use
both personal relationships and specific business and
technological skills to maximize profit.
Asian organized crime is active throughout Canada and the
United States, from major metropolitan
areas and their suburbs to isolated rural communities.
During the past decade, preexisting underground economies of
the former Soviet Union and its satellite
states have transformed into fully realized transnational
organized crime syndicates.
Increasingly, Russian organized crime is characterized by fluid,
cellular-type structures. Senior
members/associates of Russian criminal groups appear to
recognize and accept the hegemony of a
single criminal authority who plays an important role in dispute
resolution, decision making, and the
administration of criminal funds.
Italian organized crime/La Cosa Nostra is the most mature form
of organized crime in both Canada and
the United States. Its ability to form alliances with and co-opt

other organized crime groups gives it
global influence.
In both Canada and the United States, Italian organized
crime/La Cosa Nostra is distinguished by its
strict, vertically integrated, hierarchical structure. The resulting
discipline and efficiency permit these
groups to focus resources and maximize profit.
African criminal enterprises are engaged in a variety of low- to
mid-level criminal activities that include
a number of financial fraud schemes.
Albanian criminal groups are engaged in a range of cross-border
criminal activity, including drug smug
gling and money laundering.
Source: Royal Canadian Mounted Police. “Strategic Priority:
Organized Crime 2006 Canada/US Organized
Crime Threat Assessment” http://www.rcmp-
grc.gc.ca/organizedcrime/octa_e.htm Royal Canadian Mounted
Police, 2007. Reproduced with the permission of the Minister of
Public Works and Government Services, 2008.

activity. It can be seen that the modern forms are simply newer
versions of older kinds
of criminal conduct that have changed due to opportunity,
technology, and likelihood
of apprehension. Therefore, the number of underlying organized
crime activities does
not appear to change significantly over time, although the
specific manifestations of
those crimes shift to account for broader social changes.
When we think of risk assessment, the fundamental question to
be answered is
“risk of what?” Tables 3 and 4 illustrate that we can identify in
specific terms the
particular organized crime risks we wish to target. This is a
departure from most risk
prediction and assessment efforts to date, which focus on crime
groups rather than
the products or markets that constitute the focus of organized
crime activity.
There has not been much effort to explain organized crime’s
choices of particular
criminal activities. Why is drug trafficking chosen over

cigarette trafficking, or human
trafficking engaged in versus trafficking in endangered species?
One approach to this
question focuses on routine activities or situational crime
prevention. This perspective
concentrates on criminal settings (environments conducive to
organized crime activ-
ity) rather than on the motivations of individuals or groups of
people. Because much
organized crime activity depends on transactions in public and
semipublic places
(e.g., selling drugs, stolen property), better surveillance and
control of these settings
would reduce the opportunity for small-time organized crimes,
which would affect
Table 3
Specific Offenses That Constitute Organized Crime
Provision of Illicit Services Provision of Illicit Goods
Infiltration of Business
Commercialized sex activity Drug trafficking Extortion and

racketeering
Illegal gambling Stolen property Money laundering
Human trafficking Counterfeiting (identity documents, Fraud
(investment fraud,
Subcontracted services: dumping, software, DVDs, CDs,
weapons) phishing, smuggling)
trafficking in protected species,
human organs, murder for hire
Table 4
Shifts in Organized Crime Activity Over Time
Original Activity Modern Version
Local numbers and lottery gambling Internet gambling at
international sites
Heroin, cocaine trafficking Synthetic drugs (less vulnerable to
supply problems)
Street prostitution Internet prostitution and trafficking in human
beings
Extortion of local businesses for protection Extortion of
corporations, kidnappings
Loan-sharking Money laundering, precious stones, commodities
Fencing stolen property Theft of intellectual property

larger organized crime operations, according to this view
(Felson, 2006). The routine
activities approach has not been systematically applied to
organized crime, however,
so it is not clear whether a focus on criminal settings, and the
exclusion of individual
motivation, would effectively prevent large-scale organized
crime activity.
Risk Assessment in Criminal Justice Settings
Risk assessment is not easy, because criminal conduct remains a
relatively rare
event. The less common an event, the harder it is to forecast or
predict effectively.
Therefore, it is easier to predict automobile accidents than it is
to predict incidents
of organized crime. In the biological sciences, where many
well-known diseases are
in fact rare, it is difficult to predict diseases such as prostate
cancer or breast cancer
in an individual patient. However, it is possible to determine

broader risk levels
among groups by scrutinizing common factors among known
victims of the disease
and comparing them with nonvictims. It is this basic strategy of
science that helped
to identify factors such as cigarette smoking, obesity, and lack
of exercise to increase
risk for a number of serious diseases. Indeed, it has been found
that in general, people
themselves are not at high risk; it is their activities that place
them at high risk
(Kravitz, 2007; Ortega, Ruiz, & Sjostrom, 2007).
In criminology, the approach should be similar. We cannot
predict very well who
will become a criminal or which precise offense or victim will
be chosen in a given
case. However, a close examination of known cases of
offenders, crimes, and victims
can be compared with nonoffenders, crime-free activities, and
nonvictims to assess
their comparative risk levels. Therefore, the purpose of risk
assessment and prediction
in criminal justice is the same as it is in natural science: to
determine comparative

risk levels of different activities so that resources can be
focused on those activities
that pose the highest risk. A great deal of useful research has
been produced that
shows the utility of risk levels to determine intensity of
probation supervision, the
factors important in determining parole release guidelines, and
sentencing guidelines
in criminal justice (Davies & Dedel, 2006; Kleiman, Ostrom, &
Cheesman, 2007;
Langton, 2006; Sims & Jones, 1997).
Research in criminal justice risk assessment has been consistent
in that very few
variables account for most of the risk; the addition of more
factors does not add to
predictive efficiency. Although our ability to predict the
behavior of individuals is
poor, our ability to distinguish risk levels among and within
groups is much better
(Farrington & Tarling, 1985; Gottfredson & Tonry, 1988). Here,
we wish to assess
comparative risk levels of criminal activities and illicit markets.
The assumption is
that if we properly assess and rank these illicit markets and

activities, our targeting
of these activities will lead us, in turn, to the high-risk people
(organized crime groups)
involved in them. Another way to illustrate this is presented in
Figure 1.
Figure 1 compares traditional approaches to organized crime
risk assessment with
a different approach. Historically, the focus of risk assessment
has been to gather
information on offenders to locate and interdict high-risk
individuals and groups
involved in organized crime. The long-term goal for the
prosecution of these individ-
uals is to have an impact on the illicit activities involved. The
alternative approach,
proposed here (following the large, curved arrows in Figure 1),
looks to assessment
of high risk in specific products and markets, knowing that
these markets will attract
the offenders that law enforcement seeks. The difference in the

two approaches is
that the traditional approach focuses on high-risk offenders
(with impacts on illicit
markets and activities a secondary concern), whereas the
alternative approach focuses
on identification of high-risk products and markets (knowing
that targeting these will
have a more substantial impact and also yield the offenders
involved). Put another
way, if you correctly identify the high-risk products and
markets, you will know where
to look for the offenders. This is an important distinction
because even markets with
no prior history of organized crime can be identified through
this process, providing
information for investigators beyond what might be obtained
from targeting assess-
ments to those individuals and groups with known ties to
organized crime.
Modeling the Illicit Markets
Changing the criterion of risk assessment from identifying high-
risk individuals
and groups to high-risk illicit markets requires an understanding

of important mar-
ket variables. Prior work on illicit markets and organized crime
makes it clear that
supply, demand, regulators, and competition are crucial
variables to measure to
determine markets at risk (Albanese, 2001; Edwards & Gill,
2002; Reuter, 1985;
Risk of
organized crime
involvement in
specific
products
and markets
Impact
High-risk
markets
will attract

offenders
Historical
law enforcement
focus:
Gather information to
locate offenders
A different focus and approach
Traditional
approach
Locate/interdict
high-risk
individuals
and groups
Figure 1
Risk Assessment Focus on Activities Versus Individuals

Smith, 1980; Vander Beken, 2004; Wilkins & Casswell, 2003).
Figure 2 illustrates how
these risk factors might interact to increase the risk of
organized crime involvement
for a particular product or market.
Figure 2 illustrates that organized crime groups operate
enterprises with the goals
of survival and making a profit, while controlling the pressures
they face from sup-
pliers (sources), customers (demand), regulators (law, police),
and competitors (other
legal and illegal businesses and products). In each category, it
can be seen that spe-
cific indicators (variables) can be developed to measure the
comparative nature of
supply (availability, ease of movement), demand (the level of
demand and whether it
is elastic or inelastic), competition from other groups and
products (profitability,
history of organized crime in that market, and impact of harms
produced), and regu-
lators (ease of entry into the illicit market or product—existing
regulations and any

special skills needed, the capacity and effectiveness of law
enforcement in that juris-
diction, and government corruption levels). If indicators for
each of these variables
are developed (and applied to different illicit products), it is
possible to assess the
comparative risk of organized crime involvement for different
types of products and
illicit markets (a listing of specific product markets is shown in
Table 3).
There is a need to measure these variables for each product
periodically to assess
changes in risk over time. It is likely that the true value of such
a risk assessment
effort will be to assess changes in the comparative risk of
organized crime involve-
ment in different products and markets over time. A one-time
effort to assess risk
would be limited in its utility because it cannot assess the
direction of the risk (is it
Regulators

•Ease of entry into
market (regulation/skills)
•Law enforcement
capability
•Government corruption
level
Competition
•History of Organized
crime in market
•Profitability
•Harm
Supply
•Objective availability
of product or service
•Ease of movement/sale
Customers
•Current demand

for product
•Elastic/inelastic
nature of demand
Organized crime
as enterprise
Goal: survive
and make profit
Figure 2
A Model of Organized Crime Operation in Illicit Markets
on its way up or down?), and periodic assessments are needed to
assess the impact
of efforts and initiatives against organized crime.
Summarized in another way, Figure 2 offers a 10-factor model
for risk assessment.
The types of variables include supply indicators ([a] objective
availability of product
or service, [b] ease of movement/sale), regulation indicators

([c] ease of entry into
market by its regulation and the skills needed, [d] law
enforcement capability and
competence, [e] level of local government corruption),
competition indicators
([f] history of organized crime in the market, [g] profitability,
[h] harm), demand indi-
cators ([i] current customer demand for product, [j] nature of
the demand—whether
elastic or inelastic). Using multiple indicators or measures for
each of the variables
(and for each product) would yield a reliable, comparative
assessment of risk.
The indicators in the risk assessment model can be combined
into an index for ease
of use in practice. The index would be based on the perceptions
and experiences of
those who might have knowledge of illicit products. Much in
the same way that the
Transparency International (2005) corruption surveys rely
heavily on perceptions of
business activities, analogous surveys at the local level could be
conducted to deter-
mine the circumstances surrounding the supply, demand,

regulation, and competition
for various illicit products in specific jurisdictions. For
example, local citizen, business,
police, and perhaps offender surveys could be used to help
measure perceptions of
supply, demand, regulation, and competition for particular
illicit products. An analysis
of known, closed cases could be added to this information to
look for evidence of the
10 indicators (noted above) in actual criminal cases. Police
training and performance
can be comparatively assessed to determine its capability and
competence. Similarly,
an assessment of local or national legislation and regulations
can be carried out to
determine the extent to which they advance organized crime
activity by unwittingly
enlarging or shifting illegal markets for various products or
services. Preliminary work
on the impact of legislation on organized crime has begun in the
European Union
(Morgan & Clarke, 2006; Savona, 2006; Vander Beken &
Balcaen, 2006).
The Future of Risk Assessment in Organized Crime

The preceding discussion illustrates that it is possible to
develop a model and com-
posite measures for each of the 10 indicators noted above to
produce an index of risk
of organized crime involvement in different illegal products and
markets. The poten-
tial utility of such a risk assessment index for screening, and
targeting of law enforce-
ment and prevention efforts, should not be underestimated. A
10-factor risk model
does not oversimplify the situation. Consider the UN Gender-
Related Development
Index, which is an indicator of the standard of living in a
country, measuring inequal-
ities between men and women in health, life expectancy, and
income. The Gender-
Related Development Index is composed of only three
indicators (Somers, 2007). In a
similar way, the Transparency International Corruption
Perceptions Index uses only six

survey sources for most nations included (Beets, 2005;
Transparency International,
2007). Therefore, a risk assessment model does not need to
contain a large number of
variables to be useful in practice in distinguishing risk levels.
Unlike most contemporary efforts to assess risk of organized
crime, the model
proposed here focuses on assessment of products/markets at
highest risk (rather than
on offenders or groups). Correct identification of these product
markets will lead
police to the organized crime groups they are looking for.
Targeting only the crime
groups themselves fails to anticipate future changes in
organized crime involvement
in new and different products and locations.
To enhance the utility of the risk assessment approach proposed
here, several
important aspects cannot be ignored. First, specific locations
must be the basis for
analysis due to variations in supply, demand, regulation, and
competition among

localities and regions. Second, different products/activities will
have different risks,
so separate risk assessments must be carried out for each
product/activity—to produce
a comparative risk (threat) for each activity in a given location
(Table 3 provides a
list of these organized crimes/activities). Third, risk assessment
in organized crime
must be connected to allocation of resources so that government
resources can be
targeted systematically at those criminal activities found to be
the highest risk. Fourth,
there must be periodic application of risk assessment to
different products and loca-
tions to help assess the impact of intervention efforts over time.
Systematic risk assess-
ment in organized crime holds great promise as a practical
screening device and
investigative tool to target illicit markets, activities, and
government resources in
responding to the threats identified.
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/CMSY10
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/CMTI10

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/CopperplateGothicBT-Heavy
/CopperplateGothicBT-Roman
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/Courier-BoldOblique
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/Delphin-IIA
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/Delta-MediumItalic
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/DINMittelschrift-Alternate
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/DomCasual-Bold
/Dom-CasualBT
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/ErasITCbyBT-Bold
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/ErasITCbyBT-Demi
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/EUFB10

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/FranklinGothicITCbyBT-DemiItal
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/FranklinGothic-Medium
/FranklinGothic-MediumItal
/FranklinGothic-Roman
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/Freeform721BT-BoldItalic
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/FreestyleScript
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/FrizQuadrataITCbyBT-Bold
/FrizQuadrataITCbyBT-Roman

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/Frutiger-BoldCn
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/Frutiger-Cn
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/Futura-HeavyOblique
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/Futura-LightOblique
/Futura-Oblique
/Futura-Thin
/Galliard-Black
/Galliard-BlackItalic

/Galliard-Bold
/Galliard-BoldItalic
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/GalliardITCbyBT-Bold
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/Galliard-Roman
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/GaramondBE-MediumCn
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/GaramondBE-MediumExpert

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/GaramondBE-MediumItalicExpert
/GaramondBE-MediumItalicOsF
/GaramondBE-MediumSC
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/GaramondBE-RegularExpert
/GaramondBE-RegularSC
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/Garamond-BoldCondensedItalic
/Garamond-BoldItalic
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/Garamond-BookCondensed
/Garamond-BookCondensedItalic
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/Garamond-Halbfett
/Garamond-HandtooledBold
/Garamond-HandtooledBoldItalic
/GaramondITCbyBT-Bold
/GaramondITCbyBT-BoldCondensed
/GaramondITCbyBT-BoldCondItalic
/GaramondITCbyBT-BoldItalic
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/GaramondITCbyBT-BoldNarrowItal

/GaramondITCbyBT-Book
/GaramondITCbyBT-BookCondensed
/GaramondITCbyBT-BookCondItalic
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/GaramondITCbyBT-Light
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/GaramondITCbyBT-LightCondItalic
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/GaramondITCbyBT-Ultra
/GaramondITCbyBT-UltraCondensed
/GaramondITCbyBT-UltraCondItalic
/GaramondITCbyBT-UltraItalic
/Garamond-Kursiv
/Garamond-KursivHalbfett
/Garamond-Light
/Garamond-LightCondensed
/Garamond-LightCondensedItalic
/Garamond-LightItalic
/GaramondNo4CyrTCY-Ligh
/GaramondNo4CyrTCY-LighItal
/GaramondThree

/GaramondThree-Bold
/GaramondThree-BoldItalic
/GaramondThree-BoldItalicOsF
/GaramondThree-BoldSC
/GaramondThree-Italic
/GaramondThree-ItalicOsF
/GaramondThree-SC
/GaramondThreeSMSIISpl-Italic
/GaramondThreeSMSitalicSpl-Italic
/GaramondThreeSMSspl
/GaramondThreespl
/GaramondThreeSpl-Bold
/GaramondThreeSpl-Italic
/Garamond-Ultra
/Garamond-UltraCondensed
/Garamond-UltraCondensedItalic
/Garamond-UltraItalic
/GarthGraphic
/GarthGraphic-Black
/GarthGraphic-Bold
/GarthGraphic-BoldCondensed
/GarthGraphic-BoldItalic
/GarthGraphic-Condensed
/GarthGraphic-ExtraBold
/GarthGraphic-Italic

/Geometric231BT-HeavyC
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/GeometricSlab712BT-ExtraBoldA
/GeometricSlab712BT-LightA
/GeometricSlab712BT-LightItalicA
/GeometricSlab712BT-MediumA
/GeometricSlab712BT-MediumItalA
/Giddyup
/Giddyup-Thangs
/GillSans
/GillSans-Bold
/GillSans-BoldCondensed
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/GillSans-BoldItalic
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/GillSans-Italic
/GillSans-Light
/GillSans-LightItalic
/GillSans-LightShadowed
/GillSans-Shadowed
/GillSans-UltraBold
/GillSans-UltraBoldCondensed
/Gill-Special

/Giovanni-Bold
/Giovanni-BoldItalic
/Giovanni-Book
/Giovanni-BookItalic
/Glypha
/Glypha-Bold
/Glypha-BoldOblique
/Glypha-Oblique
/Gothic-Thirteen
/Goudy
/Goudy-Bold
/Goudy-BoldItalic
/GoudyCatalogueBT-Regular
/Goudy-ExtraBold
/GoudyHandtooledBT-Regular
/GoudyHeavyfaceBT-Regular
/GoudyHeavyfaceBT-RegularCond
/Goudy-Italic
/GoudyOldStyleBT-Bold
/GoudyOldStyleBT-BoldItalic
/GoudyOldStyleBT-ExtraBold
/GoudyOldStyleBT-Italic
/GoudyOldStyleBT-Roman
/GoudySans-Black
/GoudySans-BlackItalic

/GoudySans-Bold
/GoudySans-BoldItalic
/GoudySans-Book
/GoudySans-BookItalic
/GoudySansITCbyBT-Black
/GoudySansITCbyBT-BlackItalic
/GoudySansITCbyBT-Bold
/GoudySansITCbyBT-BoldItalic
/GoudySansITCbyBT-Light
/GoudySansITCbyBT-LightItalic
/GoudySansITCbyBT-Medium
/GoudySansITCbyBT-MediumItalic
/GoudySans-Medium
/GoudySans-MediumItalic
/Granjon
/Granjon-Bold
/Granjon-BoldOsF
/Granjon-Italic
/Granjon-ItalicOsF
/Granjon-SC
/GreymantleMVB-Ornaments
/Helvetica
/Helvetica-Black
/Helvetica-BlackOblique
/Helvetica-Black-SemiBold

/Helvetica-Bold
/Helvetica-BoldOblique
/Helvetica-Compressed
/Helvetica-Condensed
/Helvetica-Condensed-Black
/Helvetica-Condensed-BlackObl
/Helvetica-Condensed-Bold
/Helvetica-Condensed-BoldObl
/Helvetica-Condensed-Light
/Helvetica-Condensed-Light-Light
/Helvetica-Condensed-LightObl
/Helvetica-Condensed-Oblique
/Helvetica-Condensed-Thin
/Helvetica-ExtraCompressed
/Helvetica-Fraction
/Helvetica-FractionBold
/HelveticaInserat-Roman
/HelveticaInserat-Roman-SemiBold
/Helvetica-Light
/Helvetica-LightOblique
/Helvetica-Narrow
/Helvetica-Narrow-Bold
/Helvetica-Narrow-BoldOblique
/Helvetica-Narrow-Oblique
/HelveticaNeue-Black

/HelveticaNeue-BlackCond
/HelveticaNeue-BlackCondObl
/HelveticaNeue-BlackExt
/HelveticaNeue-BlackExtObl
/HelveticaNeue-BlackItalic
/HelveticaNeue-Bold
/HelveticaNeue-BoldCond
/HelveticaNeue-BoldCondObl
/HelveticaNeue-BoldExt
/HelveticaNeue-BoldExtObl
/HelveticaNeue-BoldItalic
/HelveticaNeue-Condensed
/HelveticaNeue-CondensedObl
/HelveticaNeue-ExtBlackCond
/HelveticaNeue-ExtBlackCondObl
/HelveticaNeue-Extended
/HelveticaNeue-ExtendedObl
/HelveticaNeue-Heavy
/HelveticaNeue-HeavyCond
/HelveticaNeue-HeavyCondObl
/HelveticaNeue-HeavyExt
/HelveticaNeue-HeavyExtObl
/HelveticaNeue-HeavyItalic
/HelveticaNeue-Italic
/HelveticaNeue-Light

/HelveticaNeue-LightCond
/HelveticaNeue-LightCondObl
/HelveticaNeue-LightExt
/HelveticaNeue-LightExtObl
/HelveticaNeue-LightItalic
/HelveticaNeueLTStd-Md
/HelveticaNeueLTStd-MdIt
/HelveticaNeue-Medium
/HelveticaNeue-MediumCond
/HelveticaNeue-MediumCondObl
/HelveticaNeue-MediumExt
/HelveticaNeue-MediumExtObl
/HelveticaNeue-MediumItalic
/HelveticaNeue-Roman
/HelveticaNeue-Thin
/HelveticaNeue-ThinCond
/HelveticaNeue-ThinCondObl
/HelveticaNeue-ThinItalic
/HelveticaNeue-UltraLigCond
/HelveticaNeue-UltraLigCondObl
/HelveticaNeue-UltraLigExt
/HelveticaNeue-UltraLigExtObl
/HelveticaNeue-UltraLight
/HelveticaNeue-UltraLightItal
/Helvetica-Oblique

/Helvetica-UltraCompressed
/HelvExtCompressed
/HelvLight
/HelvUltCompressed
/Humanist521BT-Bold
/Humanist521BT-BoldCondensed
/Humanist521BT-BoldItalic
/Humanist521BT-ExtraBold
/Humanist521BT-Italic
/Humanist521BT-Light
/Humanist521BT-LightItalic
/Humanist521BT-Roman
/Humanist521BT-RomanCondensed
/Humanist521BT-UltraBold
/Humanist521BT-XtraBoldCondensed
/Humanist531BT-BlackA
/Humanist531BT-BoldA
/Humanist531BT-RomanA
/Humanist531BT-UltraBlackA
/Humanist777BT-BlackB
/Humanist777BT-BlackCondensedB
/Humanist777BT-BlackItalicB
/Humanist777BT-BoldB
/Humanist777BT-BoldCondensedB
/Humanist777BT-BoldItalicB

/Humanist777BT-ExtraBlackB
/Humanist777BT-ExtraBlackCondB
/Humanist777BT-ItalicB
/Humanist777BT-LightB
/Humanist777BT-LightCondensedB
/Humanist777BT-LightItalicB
/Humanist777BT-RomanB
/Humanist777BT-RomanCondensedB
/Humanist970BT-BoldC
/Humanist970BT-RomanC
/HumanistSlabserif712BT-Black
/HumanistSlabserif712BT-Bold
/HumanistSlabserif712BT-Italic
/HumanistSlabserif712BT-Roman
/ICMEX10
/ICMMI8
/ICMSY8
/ICMTT8
/Iglesia-Light
/ILASY8
/ILCMSS8
/ILCMSSB8
/ILCMSSI8
/Imago-Book
/Imago-BookItalic

/Imago-ExtraBold
/Imago-ExtraBoldItalic
/Imago-Light
/Imago-LightItalic
/Imago-Medium
/Imago-MediumItalic
/Industria-Inline
/Industria-InlineA
/Industria-Solid
/Industria-SolidA
/Insignia
/Insignia-A
/IPAExtras
/IPAHighLow
/IPAKiel
/IPAKielSeven
/IPAsans
/ITCGaramondMM
/ITCGaramondMM-It
/JAKEOpti-Regular
/JansonText-Bold
/JansonText-BoldItalic
/JansonText-Italic
/JansonText-Roman
/JansonText-RomanSC

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/JoannaMT-Bold
/JoannaMT-BoldItalic
/JoannaMT-Italic
/Juniper
/KabelITCbyBT-Book
/KabelITCbyBT-Demi
/KabelITCbyBT-Medium
/KabelITCbyBT-Ultra
/Kaufmann
/Kaufmann-Bold
/KeplMM-Or2
/KisBT-Italic
/KisBT-Roman
/KlangMT
/Kuenstler480BT-Black
/Kuenstler480BT-Bold
/Kuenstler480BT-BoldItalic
/Kuenstler480BT-Italic
/Kuenstler480BT-Roman
/KunstlerschreibschD-Bold
/KunstlerschreibschD-Medi
/Lapidary333BT-Black
/Lapidary333BT-Bold
/Lapidary333BT-BoldItalic

/Lapidary333BT-Italic
/Lapidary333BT-Roman
/LASY10
/LASY5
/LASY6
/LASY7
/LASY8
/LASY9
/LASYB10
/LatinMT-Condensed
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/LCIRCLEW10
/LCMSS8
/LCMSSB8
/LCMSSI8
/LDecorationPi-One
/LDecorationPi-Two
/Leawood-Black
/Leawood-BlackItalic
/Leawood-Bold
/Leawood-BoldItalic
/Leawood-Book
/Leawood-BookItalic
/Leawood-Medium
/Leawood-MediumItalic

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/LegacySans-BoldItalic
/LegacySans-Book
/LegacySans-BookItalic
/LegacySans-Medium
/LegacySans-MediumItalic
/LegacySans-Ultra
/LegacySerif-Bold
/LegacySerif-BoldItalic
/LegacySerif-Book
/LegacySerif-BookItalic
/LegacySerif-Medium
/LegacySerif-MediumItalic
/LegacySerif-Ultra
/LetterGothic
/LetterGothic-Bold
/LetterGothic-BoldSlanted
/LetterGothic-Slanted
/Life-Bold
/Life-Italic
/Life-Roman
/LINE10
/LINEW10
/Linotext
/Lithos-Black

/LithosBold
/Lithos-Bold
/Lithos-Regular
/LOGO10
/LOGO8
/LOGO9
/LOGOBF10
/LOGOSL10
/LOMD-Normal
/LubalinGraph-Book
/LubalinGraph-BookOblique
/LubalinGraph-Demi
/LubalinGraph-DemiOblique
/LucidaHandwritingItalic
/LucidaMath-Symbol
/LucidaSansTypewriter
/LucidaSansTypewriter-Bd
/LucidaSansTypewriter-BdObl
/LucidaSansTypewriter-Obl
/LucidaTypewriter
/LucidaTypewriter-Bold
/LucidaTypewriter-BoldObl
/LucidaTypewriter-Obl
/LydianBT-Bold
/LydianBT-BoldItalic

/LydianBT-Italic
/LydianBT-Roman
/LydianCursiveBT-Regular
/Machine
/Machine-Bold
/Marigold
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/MathematicalPi-Four
/MathematicalPi-One
/MathematicalPi-Six
/MathematicalPi-Three
/MathematicalPi-Two
/MatrixScriptBold
/MatrixScriptBoldLin
/MatrixScriptBook
/MatrixScriptBookLin
/MatrixScriptRegular
/MatrixScriptRegularLin
/Melior
/Melior-Bold
/Melior-BoldItalic
/Melior-Italic
/MercuriusCT-Black
/MercuriusCT-BlackItalic
/MercuriusCT-Light

/MercuriusCT-LightItalic
/MercuriusCT-Medium
/MercuriusCT-MediumItalic
/MercuriusMT-BoldScript
/Meridien-Bold
/Meridien-BoldItalic
/Meridien-Italic
/Meridien-Medium
/Meridien-MediumItalic
/Meridien-Roman
/Minion-Black
/Minion-Bold
/Minion-BoldCondensed
/Minion-BoldCondensedItalic
/Minion-BoldItalic
/Minion-Condensed
/Minion-CondensedItalic
/Minion-DisplayItalic
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/MinionExp-Italic
/MinionExp-Semibold
/MinionExp-SemiboldItalic
/Minion-Italic
/Minion-Ornaments
/Minion-Regular

/Minion-Semibold
/Minion-SemiboldItalic
/MonaLisa-Recut
/MrsEavesAllPetiteCaps
/MrsEavesAllSmallCaps
/MrsEavesBold
/MrsEavesFractions
/MrsEavesItalic
/MrsEavesPetiteCaps
/MrsEavesRoman
/MrsEavesRomanLining
/MrsEavesSmallCaps
/MSAM10
/MSAM10A
/MSAM5
/MSAM6
/MSAM7
/MSAM8
/MSAM9
/MSBM10
/MSBM10A
/MSBM5
/MSBM6
/MSBM7
/MSBM8

/MSBM9
/MTEX
/MTEXB
/MTEXH
/MTGU
/MTGUB
/MTMI
/MTMIB
/MTMIH
/MTMS
/MTMSB
/MTMUB
/MTMUH
/MTSY
/MTSYB
/MTSYH
/MTSYN
/MusicalSymbols-Normal
/Myriad-Bold
/Myriad-BoldItalic
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/SVE
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60061006c0069007400650074002e0020005000440046002d0064
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/ENU (Use these settings for creating PDF files for
submission to The Sheridan Press. These settings configured for
Acrobat v6.0 08/06/03.)
>>
>> setdistillerparams
<<
/HWResolution [2400 2400]
/PageSize [612.000 792.000]
>> setpagedevice

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Running head THE ROLE OF QUESTIONS IN SOLVING CRIMES 1The Ro.docx