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					                                              CRIMINAL JUSTICE GRADUATE
                                                STUDENT SYMPOSIUM 2008
                                                   “SPATIAL CRIMINOLOGY”

                                      MONDAY, May 19, 2008

8:00 am – 9:00 am                                             Registration

9:00 am – 9:30 am                                  Welcome and Opening Remarks

                            Racial And Ethnic Change And The Spatial Dynamics Of Crime In Los Angeles
9:40 am – 10:20 am                                      Lyndsay Boggess
                                                  University of California, Irvine

                          The Buyers, The Sellers, And The Spatio-Temporal Dimensions Of Drug Markets In
                                                            Camden, NJ
10:20 am – 11:00 am                                      Travis Taniguchi
                                                         Temple University

11:00 am – 11:20 am                                          Coffee Break

                         The Triad Of Social Disorganization,                Mining ProDES: Spatial Data Mining
                        Incivilities And Territorial Functioning                    Juvenile Recidivism
11:20 am - 12:00 pm               Sean Robert Christie                                 Joseph Jupin
                           Northeastern University, Boston                           Temple University

                                                                      Investigating Routine Activity Dynamics By
                      Analyzing Recovery Sites Of Stolen Vehicles
                                                                                  Simulation Methods
12:00 pm - 12:40 pm                 Shuryo Fujita
                                                                                  Charlotte Gerritsen
                              Rutgers University, Newark
                                                                             Vrije Universiteit Amsterdam

12:40 pm – 1:40 pm                                           Lunch Break

                                  Guardianship In Action: Developing A New Tool For Measurement
1:40 pm – 2:20 pm                                         Danielle Reynald
                                  Netherlands Institute for the Study of Crime & Law Enforcement

                            Awareness Paths And Activity Nodes: Investigating The Relationship Between
                                Public Awareness Spaces And The Distribution Of Criminal Activity
2:20 pm – 3:00 pm                                       Kathryn Wuschke
                                                Simon Fraser University, Canada

3:00 pm – 3:30 pm                                            Coffee Break

                                          The Future Of Spatial Criminology – A Discussion
                           Henk Elffers (Netherlands Institute for the Study of Crime & Law Enforcement)
3:30 pm – 4:10 pm                             Bryan Kinney (Simon Fraser University)
                                                 Ralph Taylor (Temple University)
                                              Michael Townsley (Griffith University)

4.10 pm – 5.00 pm                        Criminal Justice Dept lab open for internet access
                                   TUESDAY, May 20, 2008

8:30 am – 9:30 am                      Criminal Justice Dept lab open for internet access

                      Buffers And Inverse Distances: Measuring The Proximity Effects Of Criminogenic Land
                                                     Uses On Fear And Crime
9:30 am - 10:10 am                                       Eric S. McCord
                                                       Temple University

                                         Social Disorganization In A Military Community
10:10 am - 10:50 am                                       Meghan Peel
                                                 Northeastern University, Boston

10:50 am – 11:10 am                                      Coffee Break

                       Social Disorganization, Collective Efficacy, And The Distribution Of Registered Sex
                                                  Offenders In Chicago, Illinois
11:10 am – 11:50 am                                       Kelly M. Socia
                                                    SUNY, University at Albany

                      The 3am Nightclub Lockout: A Time-Based Crime Prevention Initiative In A Beachside
                                                     Entertainment District
11:50 am – 12:30 pm                                   Dominique Murray
                                            Griffith University, Brisbane, Australia

                       Are Hotels And Boardwalks Crime Generators In New Jersey’s Resort Communities?
12:30 pm – 1:10 pm                                   Andrew Lemieux
                                                 Rutgers University, Newark

1.10 pm – 1.15pm                                       Conference close

Racial And Ethnic Change And The Spatial Dynamics Of Crime In Los Angeles 
Lyndsay N. Boggess 
University of California, Irvine 
      This project examines the relationship between changes in the racial and ethnic composition of
neighborhoods and changes in crime. Neighborhood level research in the Chicago-school tradition acknowledges
the importance of social structural characteristics of communities on local crime rates. That is, racial and ethnic
heterogeneity, poverty, and residential instability positively influence crime. But much current neighborhood
effects research overlooks the embeddedness of a neighborhood within a wider social environment, deviating from
Park, Burgess, and colleagues’ original notion of a dynamic interrelated social system. By treating each
neighborhood as independent, this research ignores the importance of the broader social context on crime rates.
      Spatial analysis in Criminology has been used as an effective tool to measure the diffusion of violence across
neighborhoods (e.g. Cohen and Tita, 1999; Morenoff and Sampson, 1997). That is, the rate of violence in one
neighborhood affects violence in proximate communities through a process of diffusion or contagion. Loftin (1986)
argues that the spread of violence across neighborhood boundaries is analogous to the transmission of a contagious
      Recent work by Anselin (2003) and Morenoff (2003), however, examines the influence of space through
spatial externalities rather than through a process of diffusion. These models use reduced form equations in order
to account for the endogenous Wy in traditional spatial regression analysis and to account for spatial multiplier
effects. Spatial externality models then, measure outcomes in which the spatial effects operate directly through
observed X variables. Following Anselin and Morenoff’s work, this project examines the impact of spatial
externalities related to racial and ethnic change on change in crime in the focal neighborhood.
      I use crime and Census data for the City of Los Angeles in 1990 and 2000 at the census tract level. Over the
past two decades, Los Angeles has undergone significant change in the geographic distribution of race and
ethnicity. The turnover caused by residential flux disrupts the way communities operate and the population shifts
can obscure norms and decrease the ability of residents to monitor behavior. Increases in crime are tied to race
and ethnicity in particular, either through heterogeneity or the concentration and segregation of minority
residents. It is likely that racial and ethnic transition not only affects crime in the tract in which it is occurring,
but in the surrounding areas as well.
      My dependent variable of interest is the change in crime between 1990 and 2000, which I model as a function
of change between 1990 and 2000 in structural characteristics of the focal tract and of the wider social
environment surrounding the tract. I am primarily interested in how change in racial and ethnic composition
impacts changes in crime, particularly violent crime, while controlling for changes in social characteristics related
to social disorganization theory (such as poverty, population density, and residential mobility). Therefore, I will
define racial and ethnic change in two different ways. First, I will analyze the relationship using the change in
racial/ethnic heterogeneity between 1990 and 2000 as an indicator of racial/ethnic change. Recently, however,
Sampson has argued that heterogeneity is a static measure, and that the ten year difference will be minimal.
Therefore, I will also analyze an alternative model, using “residential churning” as my indicator of neighborhood
change; this is a dynamic measure that accounts for the process of change in a neighborhood (Hipp, Tita, and
Boggess, in progress; Pastor, Sadd, and Hipp, 2001).
The Buyers, The Sellers, And The Spatio­Temporal Dimensions Of Drug Markets In 
Camden, NJ 
Travis Taniguchi 
Temple University 

     This presentation provides an in-depth look into drug markets located in Camden, NJ. In order for a drug
market to be successful buyers and sellers must come together in space and time in the absence of a capable
guardian. The analysis of drug markets is therefore approached from a routine activities perspective as suggested
by Eck (1995). To fully describe the drug markets a number of data sources are utilized. These included police
crime records collected by the Camden Police Department and criminal intelligence data gathered by the Office of
Intelligence Services in the Camden County Prosecutors office.
      Based on information provided by the Office of Intelligence Services it was possible to identify the location of
open-air, gang controlled, drug dealing locations. These locations were classified into three types (non-gang, non-
drug dealing corner; gang-drug dealing corner; drug corner with multiple gangs). Thiessen polygons defined the
sphere of influence of each corner, and areally weighted census data to match the polygons was used to control
for community demographic fabric. Negative binomial regressions of property and violent crime (2005 and 2006
combined) showed that crime counts were higher around gang-drug corners compared to non-gang, non-drug
corners, and even higher if multiple gangs were linked to the drug corner. The pattern persisted after controlling
for community fabric and nearby crime. Further, both violent and property crime counts were higher in less stable
locales. At least when gang set space is defined on the basis of known open-air drug market locations, it appears
these spaces, especially when control is disputed, link to more crime.
      Buyers are another critical component of successful drug markets. During 2007 Camden law enforcement
agencies performed a number of reverse buy operations where undercover police officers act as drug sellers. These
operations allow for intelligence gathering of the people buying drugs within the City of Camden. Analysis of these
data demonstrates that a substantial quantity of drug buyers home addresses located outside the City of Camden
yet still within the State of New Jersey.
      Finally, buyers and sellers must come together in space and time for a drug transaction to occur. This
indicates that drug arrests (serving as a proxy for underlying drug sales transactions) will have both a temporal and
spatial extent. This relationship is explored with kernel density estimations analyzing the spatio-temporal point
pattern of drug arrests. Additional contrast is made by comparing spatio-temporal pattern of drug arrests with
violent crime incidents.

The Triad Of Social Disorganization, Incivilities And Territorial Functioning 
Sean Robert Christie 
Northeastern University, Boston 
      Criminologists have become increasingly aware of the ‘place’ in crime. This awareness of the spatial aspect
of crime is not new and has a long history. Historical research has focused on the macro while recent interest in
the spatial patterning of crime has focused on different levels of aggregation. The focus on lower levels of
aggregation improves on this historical research by moving the focus of research to the crime event. This study
examines the propositions of theories that focus on the micro and the meso: Territorial Functioning and Incivilities
      Territorial functioning is claimed to effect disorder either indirectly or directly (Taylor, 1988). Incivilities
theorists claim that incivilities are indicative of underlying social problems (Taylor,2001). Incivilities therefore are
seen as indicators of “social disorganization, collective efficacy and social capital” (Taylor, 2001; p7). Within the
research on social disorganization Meithe and Meier (1994) claim there are four consistent indicators of social
disorganization. These indicators consist of socio-economic status, population mobility, ethnic heterogeneity and
broken homes. The current study attempted to investigate the link between social disorganization measures,
incivilities, and territorial functioning.
      The study was conducted in Revere, a city located on the north border of Boston, Massachusetts. The study
area within Revere, known locally as Revere Beach, consists of six census block groups. These block groups in turn
contain approximately 60 street blocks and 1,000 properties.
      As recommended by Sampson (2002) and colleagues, who suggested that research on spatial patterns of crime
should explore alternative sources of data, the data collection was heavily supplemented with qualitative
systematic social observations (SSOs) of the area conducted over several months. To guide the SSOs, Perkins,
Meeks and Taylor’s (1992) “Block Environmental Inventory (BEI)” was modified and employed. The modified BEI
was used to evaluate all properties in the study area. Some SSO’s led to better knowledge of the issues of the area
through interaction with residents. Further SSO’s highlighted threats to the validity of the BEI measurements, such
as garbage collection patterns. Finally, the data collected using the modified BEI as well as US Census Bureau data
at the block group level were empirically analyzed.
      The presentation of this study will focus on the process and evolution of the research and will present a
mixture of qualitative and quantitative findings. Qualitative observations include a mixture of resident statements,
researcher observations, and patterns of territorial functioning. The presentation will conclude with a discussion of
the limitations of data as well as future directions intended for this study, including alternative data sources and
crime data. This research was conducted to fulfill the requirements of a Master’s thesis.

Analyzing Recovery Sites Of Stolen Vehicles 
Shuryo Fujita 
Rutgers University, Newark 
      The uneven distribution of crime over space and time has been a matter of concern for environmental
criminologists. For example, auto theft is generally concentrated in three ways; places, times and vehicles. Once
those concentrations of auto theft have been identified, crime analysts and police may focus on such areas to
maximize their prevention efforts.
      Meanwhile, auto theft has another dimension -- recovery of the stolen vehicle -- that has received little
attention in crime analysis. Just as property marking that tries to disrupt the illicit market in stolen vehicles has
proven to reduce auto theft, so too might an approach that focuses on the recovery place play an important role in
preventing auto theft. That is, focusing on the place where many stolen vehicles have been dumped might reduce
the crime because if there was nowhere to dispose of or abandon a stolen car, the car might no longer be an
attractive object for stealing, but rather expose thieves to a risk of being apprehended.
      While presenting the spatial and temporal patterns of auto theft in Newark, NJ, this paper explores the
nature of the recovery locations of stolen vehicles. Specifically, it focuses on the spatial distribution of recovered
vehicles that have been stripped of its parts, and explores how the spatial distribution of the recovery locations
might differ by the degree or severity of stripping (e.g., low level of stripping includes removing of A/C, battery
and headlight, while moderate level includes removing of tire/wheel, body parts and seats, and high level includes
removing of engine, transmission and radiator).
      This study hypothesizes that the spatial distribution of the recovery locations of the stolen vehicles whose
parts are taken tend to be more patterned, compared to those whose parts are not taken. That is because thieves
pay particular attention to the dump location, where they can park the stolen car and remove its parts without
disturbance, while opportunistic thieves who steal cars for fun or as a mean of transportation pay less attention to
the dump sites, disposing the stolen car as if they are parking their own.
      Data collected from the Newark Police Department contains detailed information on recoveries as well as
auto thefts that occurred in the city between 2005 and 2007. After mapping theft and recovery locations, kernel
density estimation is used to detect both auto theft and auto recovery hotspots. The clusters for auto recovery
are disaggregated by the severity of stripping to compare the differences in distribution patterns among them.
Also, the distances between theft and recovery locations were calculated to see how the average distance differs
by the severity of stripping. In addition, this paper introduces visual representations of crime information using
basic graphs and charts.

Mining ProDES: Spatial Data Mining Juvenile Recidivism 
Joseph Jupin 
Temple University 
       This paper describes the methods and findings of spatial data mining techniques and data fusion that have
been applied to ProDES, a ten-year collection of case-based data pertaining to Philadelphia juvenile delinquency,
and other data sets. Our hypothesis is that the inclusion of spatial data will provide input from the environment
and allow us to build better descriptive and predictive models. It is a difficult task to build accurate predictive
mathematical models based on human data. Many natural phenomena, such as protein disorders and cancer, have
strong underlying processes that can be exploited to make certain predictions based on case-level data. Human
behavior tends to have an underlying random process that can foil these models. Preliminary tests were performed
on a subset of ProDES to find only point level attributes that were directly related to recidivism. It was consistent
in all models that each individual attribute was very weak in its ability to model or predict recidivism.
       Data, including the U.S. Census, PHMC (Philadelphia Health Management Corp.), Philadelphia Police arrests,
and Philadelphia Probation and Parole, have been fused with ProDES to identify spatial factors that may promote
or deter juvenile recidivism. We have applied clustering techniques that include both spatial and point level data
to generate subgroups of kids and applied traditional data mining techniques to these subgroups. We have also
used these data to build predictive models to compare the predictability of the underlying processes of the
subgroups against that of the entire set. Lastly, we have applied sensitivity analysis using neural networks to
identify the individual attributes that most significantly affect the accuracy of these models. These attributes are
the point and spatial factors that affect the likelihood of recidivism.
       It is our hope that the results of this research can be used to help government authorities better allocate
scarce resources and decrease the likelihood of juvenile recidivism. We also hope to provide information and
possibly a new and innovative risk assessment to tool to aid judicial and criminal justice authorities in the
treatment of juvenile delinquents.

Investigating Routine Activity Dynamics By Simulation Methods 
Charlotte Gerritsen 
Vrije Universiteit Amsterdam 
      The Routine Activity Theory by Cohen and Felson states that a crime will occur when a motivated offender
meets a suitable target without a capable guardian being present. This theory is already well established since a
number of years. However, both criminals and guardians may adapt their movements based on their observations.
Criminals will select targets based on personal preferences, while guardians will follow criminals. The dynamical
interaction of many of such agents may easily defy our analytical capabilities. Simulation methods may then be
called for. We will present a simple simulation model in which targets have fixed positions in geographical space.
Offenders move around, looking for suitable targets, while guardians move around trying to prevent the offenders
from assaulting their target.
      In order to build this simulation model we have used the modeling language LEADSTO. This is a modeling
language based on simple causal relationships (of the format α     β, pronounced “α leads to β”). The language is
based on first order predicate logic and allows the modeler to use both quantitative aspects (for example, the
number of times that a certain house has been broken into) as qualitative aspects (e.g., the decision to break into
a house) in an intuitive manner. Moreover, a piece of software has been implemented that visualizes the results of
the simulation in the form of a 2D-animation.
      We’ll discuss under what circumstances we may derive useful insights from analyzing simulation results in
general. Furthermore, we investigate, by running simulations and performing statistical analyses, how various
policies of guardians such as random patrolling and hot spot policing, interact with various target distributions over
space, and with various strategies of offenders such as preferring the most valuable targets versus selecting those
targets for which guardian density in the past has been low (reputation building).

     We finish with outlining how we can set up a program of incrementally more complex models, and how
environmental criminology may learn from studying simulation results in this context, discussing both opportunities
provided by the method as well as restrictions inherent to it.

Guardianship In Action: Developing A New Tool For Measurement 
Danielle Reynald 
Netherlands Institute for the Study of Crime & Law Enforcement 
      This study presents a new and reliable observational tool for measuring guardianship in action, based on a
four-stage-model of the intensity of guardianship. This model is based on the premise that a more robust, dynamic
measure of the intensity of guardianship at place ought to measure: - 1) invisibility, 2) the availability of potential
guardians, 3) the capability of available guardians, and 4) the action taken by available, capable guardians. Based
on this classification, this paper will present a new way of measuring these four stages through direct observation.
In doing so, the current study will seek to construct an even more direct measure of guardianship at place than
those previously constructed, by observing, not only the potential for guardianship, but also guardianship in action
in real-time. It shall be argued that guardianship in action can be observed, in the first instance, by having
outsiders observe whether a household is occupied or not. In addition to occupancy, we suggest that a direct
measure of the actively available guardianship at a place needs to encompass the second stage of guardianship–
actual surveillance or monitoring. The final stage of guardianship that will be measured is whether or not
available, capable guardians intervene when necessary.
      The reliability of this new measurement instrument will be examined using inter-rater reliability testing.
Once this test of reliability is passed, the concurrent validity of the new measurement tool will be tested by
examining the correlation between our new measure of guardianship and indicators for related environmental
variables, including territoriality, natural surveillance, image, social interaction among neighbors and activity
level. This paper will then investigate the extent to which the stages of guardianship we have outlined in our
model are valid. To conclude the investigation, we will then test the extent to which our new measure of
guardianship intensity can explain the variance in crime at the property level. Accordingly, the present study aims
to answer the following questions:-
     o Can we reliably and validly measure guardianship in action at the property level via direct observation?
     o What are the environmental correlates of guardianship intensity?
             o   To what extent do defensible space, routine activity and social climate variables determine the
                 intensity of active guardianship at place?
    o    Does guardianship intensity affect the amount of crime experienced at the property level?

      Testing of our new measurement instrument revealed that guardianship intensity at the property level can be
reliably and validly measured through direct observation, and is enhanced by the physical and social environment.
The results reinforce the thesis that guardianship intensity is the product of a two-fold action process that involves
both the physical potential to carry out supervision of people and places, as well as the acts of monitoring and
intervention when necessary. The predictive validity of our instrument was also confirmed, as results showed that
crime levels drop significantly as guardianship intensifies.

Awareness Paths And Activity Nodes: Investigating The Relationship Between 
Public Awareness Spaces And The Distribution Of Criminal Activity 
Kathryn Wuschke 
Simon Fraser University, Canada 
      Criminal activity is unevenly distributed across the urban landscape, simultaneously constrained and
supported by both the built environment and the routine activities of the population. The spatial representation
and analysis of crime patterns has been dominated in recent years by areal-based choropleth analyses, aggregating
crime to predetermined neighborhoods or census areas in order to correspond with publicly available socio-
economic and demographic information. While valuable additions to the field of crime analysis, these techniques
are limited by their units of aggregation, challenged by both the modifiable area unit problem (MAUP), and the
ecological fallacy. Several novel exceptions have been introduced and refined in recent years; however, few
techniques have been developed that encourage the representation and investigation of crime patterns in relation
to their immediate environmental backcloth. This research addresses this gap by introducing and testing a
methodology to analyze criminal occurrences based on their spatial relationship to the urban road network, and to
key urban activity nodes.
      Using major urban transportation corridors as a base map, rule-based and topological selection models were
created to identify the proportion of crime occurrences falling within set distances of these arteries. In early
stages of this research, buffers were created around arterial roadways using Geographic Information Systems, in
order to create a catchment corridor, within which crime patterns could be analyzed. Later iterations
incorporated the topological connectivity of the road networks, identifying all crime occurrences falling on road
segments connected within two turns of a major transportation artery. Commercial districts and important activity
nodes were then added to the urban environmental backcloth, and further relational analyses determined the
proportions and types of crimes that cluster along these activity nodes and transportation paths. Results indicate
that a significant and disproportionate amount of crime is spatially clustered into these highly accessible locations.


Buffers And Inverse Distances: Measuring The Proximity Effects Of Criminogenic 
Land Uses On Fear And Crime 
Eric S. McCord 
Temple University 
      A significant body of research has demonstrated that crime is not random in space and time. A considerably
smaller and more recent body of literature has shown that crime clusters in areas of high opportunity, and that
certain categories of land uses and public facilities are often identified as being located within these areas of
crime clustering. Environmental criminology’s theories provides a nexus to explain relationships between land uses
and crime clusters, but researchers are often limited in their ability to make inferences about the criminogenic
effects of land uses and crime, because standard methodologies rarely allow the inclusion of neighborhood
demographic controls. The goal of this paper is to present a series of studies by the author aimed at further
developing methodologies that can specifically measure the criminogenic effects found at and around theorized
criminogenic land uses.
      The paper examines three techniques for specifically evaluating the proximity effects of criminogenic land
uses with case studies in Philadelphia. Each method was developed by researchers working with the author to
answer questions concerning proximity effects, while also controlling for neighborhood structure, and in one multi-
level study, individual factors. The first method and study uses the variance of total percentage of land area of
identified criminogenic opportunity buffers overlaid on census block groups, to predict the location and size of
street drug markets. The second study utilizes summed inverse-distance scores between respondent’s homes and
theorized land use crime generators to evaluate individual fear of crime, while controlling for individual and
neighborhood factors. The third method was developed specifically to more precisely evaluate proximity effects of
criminogenic land uses. A summed value for all crime events falling within a selected bandwidth (buffer radius)
using an inverse-distance weighting scheme. This method allows proximity effects to be compared across crime
types and study areas, includes a simple statistical significance test, and minimizes negative effects associated
with selecting too large a buffer radius. A case study of street robberies and subway stations in Philadelphia is
used as an example.
Social Disorganization in a Military Community 
Meghan Peel 
Northeastern University, Boston 
      The relationship between land uses and crime has been demonstrated in prior research (Brantingham and
Brantingham, 1993; Brower, 1996; Miller, 1981; Kurtz, Koons, and Taylor, 1998; Sampson and Raudenbush, 1999;
McCord et al., 2007). Land uses that are frequently the subject of ecological theories typically relate to residential
or non-residential classifications (McCord et al, 2007; Brantingham and Brantingham, 1981). This research proposes
consideration of a different land use – military bases. Military bases introduce a unique population to communities.
This population is typically younger, of lower socioeconomic status, and more mobile than the surrounding
community. Additionally, land use barriers (Brantingham and Brantingham, 1993) introduced by the military bases
have the potential to change the way crime is arranged in the built environment. Examples of land use barriers
may include the gates and fences surrounding the base. Social barriers may also be introduced by the military
base, especially in isolated communities. Frequent deployments of military service members further exacerbate
the problems introduced by these physical and social barriers by creating significant and regular population
change. This research explored how the presence of indicators of social disorganization (Shaw and McKay, 1969)
and concentrated disadvantage that are associated with military bases related to the distribution of potentially
criminogenic land uses and the spatial arrangement of crime in surrounding areas.
      Using geographically weighted regression analysis, the results showed that there is a significant relationship
between indicators of social disorganization and crime in military communities. Further, the presence of a military
base may alter the land use distribution of a community. In this site, the military base relates to an unusual
distribution of potentially criminogenic features in two clusters: one near the central business district and another
in the area proximate to the military base. This unusual distribution has the potential to alter the distribution of
crime in the community as well as the distribution of socially disorganized areas. This research faced several
limitations, including limitations to the data available and limitations to generalizability due to the use of a single
study site. Potential policies implicated by this research include adjustments to the zoning policies in military
communities; adjustments to policing practices including resource allocation to areas more prone to crime during
periods of increased criminal activity; and partnerships between military personnel, military law enforcement,
civilian law enforcement, and the civilian community in military communities. Future research should consider the
use of multiple sites, explore the impact of military deployments and mobility on the delinquency of military
dependent children, consider the impact of ambient population change (especially that resulting from military
deployments) on crime patterns, and explore how the routine activities of military personnel and their dependents
affect criminal victimization and offending.

Social Disorganization, Collective Efficacy, And The Distribution Of Registered Sex 
Offenders In Chicago, Illinois 
Kelly M. Socia  
SUNY, University at Albany 
      In response to several high-profile child abduction and murder cases, there has been much federal and state
legislation since the early 1990s regulating convicted sex offenders who have been released back into the
community after serving their sentences. Federal laws require sex offenders to register with law enforcement
agencies upon their release from correctional facilities, oblige law enforcement agencies to make information
about the presence of registered sex offenders known to their communities, and create a national internet sex
offender registry containing offenders’ names, addresses, descriptions, and photographs. Additionally, many
jurisdictions have enacted residency restrictions prohibiting sex offenders from living within certain distances of
areas with high concentrations of children.
      The laws regulating sex offenders are explicitly spatial. They were developed under assumptions that sexual
predators choose victims within a certain geographical proximity of the offenders’ homes, that neighborhood
residents can and will monitor the activities of other community members, and that the police are better
equipped to prevent and solve sex crimes knowing the current residences of convicted offenders. However, the
spatial dynamics of sex offenders’ behaviors and the physical contexts in which they live are not well documented;
therefore, we do not know whether the assumptions underlying these laws are tenable. Additionally, the few
studies that have examined residency characteristics of sex offenders have lacked measurement of, and control
for, spatial autocorrelation. It is possible that conclusions based on the spatial characteristics of sex offenders
would change were such controls included in the analytical model.
      This study examines sex offender residences within the context of existing criminological literature on crime
and communities. Relationships among neighborhood levels of social disorganization and collective efficacy are
examined against the spatial distribution of registered sex offenders using sex offender registrations, census data,
and survey data for the city of Chicago.
      In short, this study examines whether sex offenders are more likely to live in socially disorganized
neighborhoods than not, and the implications of neighborhood context for reintegration, reoffending, and formal
and informal social control. The spatial patterns of sex offender residences in Chicago and the types of
neighborhoods in which they live are explored, in particular how conclusions might change by including controls for
spatial autocorrelation.

The 3am Nightclub Lockout: A Time­Based Crime Prevention Initiative In A 
Beachside Entertainment District 
Dominique Murray 
Griffith University, Brisbane, Australia 
      Crime in and around bars and nightclubs in Australia is a frequent and complicated problem, often facilitated
by alcohol, testosterone, bar management practices, and the escapist atmosphere that nightclubs offer. The
impact of crimes and particularly violence in this setting has widespread effects on police and public health
resources as well as justice administration. Previous work in the field of situational crime prevention in bars,
focuses heavily on place-based cues in the physical and social environment.
      The reputation of Surfers Paradise, known for its beach and party atmosphere, is vital to the Gold Coast’s
regional economy, being one of Australia’s most popular domestic and international tourist destinations. On 1 April
2004, the Gold Coast introduced the ‘3am lockout’, a new regulation affecting the trading practices of late night
licensed venues, with an aim to reduce ‘club-hopping,’ anti-social behavior (particularly street violence), and to
promote general safety. The regulation permits bars and clubs to trade until a later time, but forbids patrons from
entering premises after 3am. Police data for Surfers Paradise have been collected over a three year period, from
July 2003 to June 2006, allowing an evaluation of the 3am lockout intervention. Using a pre-post design, we
investigated whether violence decreased as a result of the new Liquor Act regulation. As the intervention was
primarily time based, issues of temporal and spatial displacement need to be considered.
      Results were mixed. The short term impact of the lockout was negative with an increase in overall crimes
rates in the evaluated time period of July to September 2004. Violent crimes played a substantial role in this
increase. However, these immediate results diminished over time, showing a considerable decrease in recorded
violent crime when compared with recorded crime figures for the same months in 2005. We hypothesize that a
high police presence at the time of the lockout introduction contributed to the initial effects. Whilst the early
hours of the morning have always been peak times for violence in and around nightclubs, the lockout resulted in a
degree of temporal variation in crime patterns. With respect to spatial patterns, changes in hot spot locations can
also be explained by the high turnover of club ownership as well as changes to styles of the clubs and the patrons
these styles attract.
      This study faced a number of significant challenges including poor quality secondary data which in turn
impacted on the temporal and spatial analysis. While the inevitable inaccuracies of recorded crime data address
information was present, this had a non-trivial impact on efforts to gauge spatial and temporal displacement.
Various methods have been used to increase the number of incidents that have been geocoded, including mapping
crimes to intersections and allocating crimes with only street names as addresses to measured points along the

Are Hotels And Boardwalks Crime Generators In New Jersey’s Resort 
Andrew Lemieux 
Rutgers University, Newark 
      The crime rates of resort communities are of great interest to the tourism industry and vacationing public.
The New Jersey Uniform Crime Report provides information on fifty municipalities along the shore. Analysis of this
information has found a unique pattern of crime in New Jersey’s shore communities. Of 50 municipalities, 14
account for more than 79% of all violent crime and 71% of all non-violent crime. Using a routine activity approach,
this paper argues crime is a function of resident and visitor populations. Visitor populations are often neglected in
crime rate calculations and criminological theory. The literature shows many examples of visitors becoming
involved in crime as victims and offenders. Hotels and boardwalks attract visitors to specific communities along
the shore. The purpose of this study is to determine if they generate crime.

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