Dallas has a high crime rate, with over 15,000 gun crimes per year. The Dallas Police Department (DPD) uses basic crime analysis methods to track crime trends over time. DPD targets crime hot spots but needs better tools to predict exact crime locations to lower the overall crime rate. This study will use narcotics arrest data from Dallas PD records to build a Geographically Weighted Regression (GWR) model to predict locations of violent crime. The model will be evaluated by comparing its predictions to actual violent crime data, with the goal of helping DPD deploy resources more efficiently and develop improved crime prevention strategies.
As per studies conducted by the University of California, it is observed that crime in any area follows the same pattern as that of earthquake aftershocks. It is difficult to predict an earthquake, but once it happens the aftershocks following it are quite predictable. Same is true for the crimes happening in a geographical area.
As per studies conducted by the University of California, it is observed that crime in any area follows the same pattern as that of earthquake aftershocks. It is difficult to predict an earthquake, but once it happens the aftershocks following it are quite predictable. Same is true for the crimes happening in a geographical area.
Predictive Policing on Gun Violence Using Open DataPredPol, Inc
This presentation is an abstract of a 2013 whitepaper published by PredPol.
PredPol delivers the same predictive accuracy for gun violence using unique mathematical methods. A study of Chicago data shows that PredPol successfully predicts 50% of gun homicides by flagging in real-time only 10.3% of city locations. Knowing where and when gun homicides are most likely to occur empowers law enforcement to use their knowledge, skills and experience to disrupt gun crime before it happens.
The study uses open government data from Chicago and predictive crime analysis.
For the full whitepaper, visit predpol.com & request information.
PredPol: How Predictive Policing WorksPredPol, Inc
PredPol’s cloud-based predictive policing software enables law enforcement agencies to better prevent crime in their communities by generating predictions on the places and times that future crimes are most likely to occur.
PredPol’s technology has been helping law enforcement agencies to dramatically reduce crime in jurisdictions of all types and sizes, across the U.S. and overseas. Over the past year, Atlanta and Los Angeles have reduced specific crimes in targeted areas at rates ranging from nearly 20% to over 40%. Smaller jurisdictions, such as Norcross, Georgia, have seen nearly a 30% reduction in burglaries and robberies; in Alhambra, California, car burglaries have dropped 20% since the software technology was deployed.
Using advanced mathematics and computer learning, PredPol’s algorithms predict many types of crime, including property crimes, drug incidents, gang activity, and gun violence as well as traffic accidents.
Only three pieces of data are used to make predictions – type of crime, place of crime, and time of crime. No personal data is utilized in making these predictions.
Crime analysts and command staff using PredPol are 100% more effective than they are with traditional hotspot mapping at predicting where and when crimes are likely to occur. That means police have twice as many opportunities to deter and reduce crime.
OECD, 2nd Task Force Meeting on Charting Illicit Trade - Jeannie CameronOECD Governance
This presentation by Jeannie Cameron was made at the 2nd Task Force Meeting on Charting Illicit Trade held on 5-7 March 2014. www.oecd.org/gov/risk/charting-illicit-trade-second-task-force-meeting.htm
Take a look at the latest crime facts and statistics from the FBI and other agencies, so you can be prepared and stay projected.
http://www.supercircuits.com/resources/blog/learn-the-facts-about-crime
Indianapolis Republican mayoral candidate Chuck Brewer is unveiling a 12-point public safety plan that has a heavy focus on attacking the illegal drug trade, increasing police intelligence and providing more social services to aid in crime prevention.
Indianapolis Republican mayoral candidate Chuck Brewer is unveiling a 12-point public safety plan that has a heavy focus on attacking the illegal drug trade, increasing police intelligence and providing more social services to aid in crime prevention.
Indy Mayoral candidate Chuck Brewer unveils his seven-point plan for economic development which includes using more data analytics, redeveloping some of the city's major corridors and "coding" academies for young people to develop their tech skills.
Predictive Policing on Gun Violence Using Open DataPredPol, Inc
This presentation is an abstract of a 2013 whitepaper published by PredPol.
PredPol delivers the same predictive accuracy for gun violence using unique mathematical methods. A study of Chicago data shows that PredPol successfully predicts 50% of gun homicides by flagging in real-time only 10.3% of city locations. Knowing where and when gun homicides are most likely to occur empowers law enforcement to use their knowledge, skills and experience to disrupt gun crime before it happens.
The study uses open government data from Chicago and predictive crime analysis.
For the full whitepaper, visit predpol.com & request information.
PredPol: How Predictive Policing WorksPredPol, Inc
PredPol’s cloud-based predictive policing software enables law enforcement agencies to better prevent crime in their communities by generating predictions on the places and times that future crimes are most likely to occur.
PredPol’s technology has been helping law enforcement agencies to dramatically reduce crime in jurisdictions of all types and sizes, across the U.S. and overseas. Over the past year, Atlanta and Los Angeles have reduced specific crimes in targeted areas at rates ranging from nearly 20% to over 40%. Smaller jurisdictions, such as Norcross, Georgia, have seen nearly a 30% reduction in burglaries and robberies; in Alhambra, California, car burglaries have dropped 20% since the software technology was deployed.
Using advanced mathematics and computer learning, PredPol’s algorithms predict many types of crime, including property crimes, drug incidents, gang activity, and gun violence as well as traffic accidents.
Only three pieces of data are used to make predictions – type of crime, place of crime, and time of crime. No personal data is utilized in making these predictions.
Crime analysts and command staff using PredPol are 100% more effective than they are with traditional hotspot mapping at predicting where and when crimes are likely to occur. That means police have twice as many opportunities to deter and reduce crime.
OECD, 2nd Task Force Meeting on Charting Illicit Trade - Jeannie CameronOECD Governance
This presentation by Jeannie Cameron was made at the 2nd Task Force Meeting on Charting Illicit Trade held on 5-7 March 2014. www.oecd.org/gov/risk/charting-illicit-trade-second-task-force-meeting.htm
Take a look at the latest crime facts and statistics from the FBI and other agencies, so you can be prepared and stay projected.
http://www.supercircuits.com/resources/blog/learn-the-facts-about-crime
Indianapolis Republican mayoral candidate Chuck Brewer is unveiling a 12-point public safety plan that has a heavy focus on attacking the illegal drug trade, increasing police intelligence and providing more social services to aid in crime prevention.
Indianapolis Republican mayoral candidate Chuck Brewer is unveiling a 12-point public safety plan that has a heavy focus on attacking the illegal drug trade, increasing police intelligence and providing more social services to aid in crime prevention.
Indy Mayoral candidate Chuck Brewer unveils his seven-point plan for economic development which includes using more data analytics, redeveloping some of the city's major corridors and "coding" academies for young people to develop their tech skills.
Student #1 I have chosen to write about the history of data anal.docxjohniemcm5zt
Student #1
I have chosen to write about the history of data analysis for the Los Angeles Police Department. While I currently reside in Colorado Springs, Colorado and work as a deputy sheriff in Denver, Colorado I grew up in the greater Los Angeles area and I know that they should have a large amount of data to draw from.
Currently the Los Angeles Police Department uses COMPSTAT to compile their data. They have a unit, known as the COMPSTAT unit, whose sole job is to compile crime statistics and analyze the data (Los Angeles Police Department, 2016) COMPSTAT is short for computer statistics. COMPSTAT was developed by Police Commissioner William Bratton in 1994 for use by the New York Police Department. According to the University of Maryland by the year 2000 over a third of police agencies with over 100 officers were utilizing some sort of COMPSTAT like program (University of Maryland, 2015). In 2002 William Bratton became the Chief of Police for the Los Angeles Police Department and brought with him the concept of COMPSTAT. During the first six years of his tenure Los Angeles saw a steady decrease in the cities crime rates thanks largely in part to COMPSTAT policing.
Mean, mode and median play a large part in analyzing criminal data. The mean is the average number. An example of this for crime data analysis would be in neighborhood C there was 14 robberies committed on Monday between 1 and 3 AM, 17 robberies on Tuesday at the same time period and 9 on Wednesday during the same time period. The mean would be 13.3 robberies per night for those 3 nights. Knowing this is high for the city the data could be used to justify extra police presence in Neighborhood C. An example of the mode would be if in the same neighborhood in the same week there were 17 robberies on both Friday and Saturday, 12 on Thursday and 11 on Sunday. The mode would be 17 and it would also be a reason to add extra police presence in the neighborhood until a significant decrease was seen in the amount of robberies taking place. Finally we come to the median. This is simply line the numbers up for the week and take the number that falls in the middle. In the case of the robberies occurring in neighborhood C the number would be 14. All of this data can be combined to show watch commanders and captain’s areas where they should be focusing their officer’s time. If there is a neighborhood that has seen only one or two robberies during the week, it is definitely not in as much need of a heavy police presence as Neighborhood C is.
Student #2
Beginning in the mid-1990’s, police in New York began to run statistical analysis of the city’s crime reports, arrests and other police activity known as COMPSTAT. Law enforcement agencies since this analysis began, has implemented their own data-driven approaches to tracking and adapting to crime trends. The LAPD is both heavily armed and thoroughly computerized. The Real-Time Analysis and Critical Response Division is its central processor..
Journal of-Criminal Justice, Vol. 7, pp. 217-241 (1979). Per.docxpriestmanmable
Journal of-Criminal Justice, Vol. 7, pp. 217-241 (1979).
Pergamon Press. Printed in U.S.A.
0047-2352’79/030217-26s2.WO
Copyright @ 1979 Pergamon Press Ltd
INFORMATION, APPREHENSION, AND DETERRENCE:
EXPLORING THE LIMITS OF POLICE PRODUCTIVITY
WESLEY G. SKOGAN
Department of Political Science and Center for Urban Affairs
Northwestern University
Evanston. Illinois 60201
GEORGE E. ANTUNES
Department of Political Science
University of Houston
Houston, Texas 77004
and
Workshop in Political Theory and Policy Analysis
Indiana University
Bloomington, Indiana 47401
ABSTRACT
The capacity of police departments to solve crimes and
apprehend offenders is low for many types of crime, particu-
larly crimes of profit. This article reviews a variety of studies
of police apprehension and hypothesizes that an important
determinant of the ability of the police to apprehend crimi-
nals is information. The complete absence of information for
many types of crime places fairly clear upper bounds on the
ability of the police to effect solutions.
To discover whether these boundaries are high or low we
analyzed data from the 1973 National Crime Panel about the
types and amount of information potentially available to po-
lice through victim reports and patrol activities. The evidence
suggests that if the police rely on information made readily
217
218 WESLEY G. SKOGAN and GEORGE E. ANTUNES
available to them, they will never do much better than they
are doing now. On the other hand, there appears to be more
information available to bystanders and passing patrols than
currently is being used, which suggests that surveillance
strategies and improved police methods for eliciting, record-
ing, and analyzing information supplied by victims and wit-
nesses might increase the probability of solving crimes and
making arrests. In light of this we review a few possibly help-
ful innovations suggested in the literature on police produc-
tivity and procedure.
Some characteristics of the crime itself, or of events surrounding the crime, that are
beyond the control of investigators, determine whether it will be cleared in most in-
stances. (Greenwood et al., 1975: 65)
There is no feasible way to solve most crimes except by securing the cooperation of
citizens to link a person to the crime. (Reiss, 1971: 105)
INTRODUCTION
A recent spate of studies of crime and the deterrent effectiveness of the criminal
justice system has raised anew a question as old as Bentham: Does raising the cost of
criminal activity signiticantly reduce the level of crime in a community? In these studies,
the cost of criminal activity has been conceptualized in two ways: as the loss of time and
opportunity attendant to apprehension (measured by the certainty of arrest or punish-
ment), and as the stigma, discomfort, and loss of opportunity that come with conviction
by the courts (measured by the severity of punishment). Indicators of the di ...
This paper investigates the degree of association between major four crimes in Sudan, including illegal drug trafficking, murder, theft, and prostitution, with indicators of institutional weakness that include surge in other four crimes: duty & customs, forgery, passport related, and firearms & ammunition crimes. These later four crimes has been considered indicators of institutional weakness because upswing in these crimes is a reflection of corruption or negligence, or incompetence of institutional performance in the country. The canonical correlation test result indicates there is a very high and significant association between the major four crimes and the indicators of institutional weakness. This finding implies institutional weakness can nurture crime surge in the country. Cluster analysis indicates the type of crimes in conflict states of Darfor region are featured in the rest of the country except in the capital state, Khartoum which represent a separate cluster on its own. Cluster analysis also indicate murder crime is connected with prostitution; and theft crime is associated with firearms & ammunition crimes; custom & duty crimes connected with passport -related and illegal drugs crimes. However, illegal drugs crime is connected with murder, theft, and prostitution crimes.
This paper focuses on finding spatial and temporal criminal hotspots. It analyses two different real-world crimes datasets for Denver, CO and Los Angeles, CA and provides a comparison between the two datasets through a statistical analysis supported by several graphs. Then, it clarifies how we conducted Apriori algorithm to produce interesting frequent patterns for criminal hotspots. In addition, the paper shows how we used Decision Tree classifier and Naïve Bayesian classifier in order to predict potential crime types. To further analyse crimes’ datasets, the paper introduces an analysis study by combining our findings of Denver crimes’ dataset with its demographics information in order to capture the factors that might affect the safety of neighborhoods. The results of this solution could be used to raise people’s awareness regarding the dangerous locations and to help agencies to predict future crimes in a specific location within
a particular time.
Combating Gun ViolenceWhat is Gun ViolenceGu.docxrobert345678
Combating Gun Violence
What is Gun Violence
Gun violence includes homicide, violent crime, attempted murder, suicide, school/mass shootings, armed robbery, etc
Gun violence is violence committed with the use of firearms, for example pistols, shotguns, assault rifles or machine guns.
Gun violence can also have a mental impact on people
The Impact of Gun Violence
Item 3
In just one year 45,222 people died from gun related injuries in the US
Firearms cause 85,000 injuries
With more than 25% of children witnessing an act of violence in their homes, schools, or community over the past year, and more than 5% witnessing a shooting, it becomes not just an issue of gun regulation, but also of addressing the impact on those who have been traumatized by such violence (Finkelhor et al., 2009).
<a href="https://www.pewresearch.org/fact-tank/2022/02/03/what-the-data-says-about-gun-deaths-in-the-u-s/ft_22-01-26_gundeaths_1/"><img src="https://www.pewresearch.org/wp-content/uploads/2022/02/FT_22.01.26_GunDeaths_1.png?w=400"></a>
Program: Pulling Levers
Pulling Levers is program that attacks the problem of gun violence head on
Pulling Levers includes problem-oriented policing strategies that follow the core principles of deterrence theory. The strategies target specific criminal behavior committed by a small number of chronic offenders, such as youth gang members or repeat violent offenders, who are vulnerable to sanctions and punishment. The Pulling Levers Program is very Promising for reducing crime.
Corsaro and colleagues (2012) found that the High Point (N.C.) Pulling Levers had a statistically significant impact on reducing violent incidents in the target areas. Targeted census blocks (treatment group) experienced a 7.9 percent decrease in violent crime
Analysis
In the US this program is currently implemented in the following cities: Oakland, Chicago, Rockford, Indianapolis, Boston, Philadelphia, Nashville and the closest being in High Point/NC
This program has been proven to work in all of these cities having an impact on gun violence and drug related crimes
So all though Pulling levers is implemented in High Point, why is it not in our big cities where crime rates are high as well?
One of the highest rated cities for crime in NC is Durham and so far they do not have a program like Pulling Levers to combat gun violence and other crime that stems from impoverished areas.
Why Durham
Durham is the 2nd most dangerous city in NC
Durham had a murder captia of 21.5 per 100,000 which is double the national average
Why Pulling Levers?
Pulling Levers has been used in multiple cities around the nation and has been successful in targeting crime
It is also a non violent way of dealing with criminals and changing their mindset so they don’t get more involved in gang life and commit more serious offenses such as homicide or drive-bys.
If the offender chooses to be compliant with law enforcement then they will get help and tr.
US POLICIES ON TWO TRANSNATIONAL CRIMES, ILLICIT DRUG .docxdickonsondorris
US POLICIES ON TWO TRANSNATIONAL CRIMES, ILLICIT DRUG
TRAFFICKING AND CYBER-LAUNDERING, WILL NOT SECURE THE
HOMELAND FROM TERRORIST THREATS
A Master Thesis
Submitted to the Faculty
of
American Public University
by
First Name Last Name
In Partial Fulfillment of the
Requirements for the Degree
of
Master of Arts
April 2012
American Public University
Charles Town, WV
1
Introduction and Purpose Statement
The threats to America that are imposed from transnational crimes are constantly changing.
The threats may originate from other nations throughout the world; but, the impacts throughout
America is surreal. The US Government fight against transnational crimes are nothing less than
intricate. US interests abroad are impacted by these threatening networks. Weapons trafficking,
intellectual property theft, cybercrime, human smuggling, trafficking in persons, and illicit drug
trafficking contribute to other crimes that evolves around these transnational crimes. The bottom
line is that the threats created by these crimes are not isolated to one specific nation or a specific
region in the world. The US Government policies that are designed to combat transnational
crimes must address both present-day threats and potential future threats.
The purpose of this paper is to explore US Government policies targeting illicit drug
trafficking and cyber-laundering while identifying vulnerabilities within the policies (if any) and
their impact on threats from terrorist organizations. Transnational crime, narcotics, and terrorism
financing are not geographical concerns. All three can be linked specifically by having potential
effect across national borders. Transnational Organized Crime (TOC) has established a
significant and increasing threat to national and international security, with dire implications for
public safety, public health, democratic institutions, and economic stability across the globe
(Finckenauer 2006, 124). The US Government have many Presidential Directives (PD) and
policies that target these areas, but are they really having an impact? Without a shadow of a
doubt, drug trafficking has resulted in funding that has supported terrorism and in some cases
such as the Madrid bombing, drugs were being utilized as the currency. The same scenario can
happen in any small or large city in America. US Government policies must be able to
compliment or supplement other Nations policies in the fight against transnational crime.
2
Because of varies religious beliefs and political views of western nations, the tasking will be
equivalent to finding a cotton ball in the field of snow.
Cybercrime is such a lucrative criminal adventure because anyone can be anyone and
anywhere in a digital environment. The utilization of electronic funding transactions
domestically and or internationally can create difficult detective efforts for an ...
Gun violence preventionpractices among local policein th.docxwhittemorelucilla
Gun violence prevention
practices among local police
in the United States
Christopher S. Koper
Department of Criminology, Law and Society, George Mason University,
Fairfax, Virginia, USA, and
Daniel J. Woods and Bruce E. Kubu
Police Executive Research Forum, Washington, District of Columbia, USA
Abstract
Purpose – The purpose of the study is to examine gun violence prevention practices among urban
police in the USA, assessing their scope, effectiveness, limitations, and impacts.
Design/methodology/approach – A national survey was conducted with police agencies serving
cities of 100,000 or more people.
Findings – Strategies used most frequently and rated as most effective include targeted efforts
focussed on high-risk places and groups, as well as multi-agency problem-solving efforts, particularly
those involving federal authorities. However, most agencies make limited use of proactive strategies to
reduce gun crime, and there are substantial gaps in the enforcement of many gun laws. Results also
suggest that gun crime is lower in places where police engage in more intensive gun-related
enforcement and prevention efforts.
Research limitations/implications – The survey focussed only on large US cities. Implementation
of the strategies could not be examined in detail, and assessments of the effectiveness of strategies
reflect the views of practitioners. There is a need for more in-depth research on gun-related
enforcement and prevention practices, their effectiveness, and the organizational and environmental
factors that facilitate or hinder them.
Practical implications – The study highlights strategies that should be given priority consideration
in policy decisions. The findings also suggest that police efforts to address gun crime can be enhanced
considerably – and that doing so may produce demonstrable reductions in gun crime. Further
examination of policy changes necessary to facilitate these efforts is warranted.
Originality/value – This study represents the first national survey of gun violence reduction efforts
by police in the USA.
Keywords Police, Firearms, Violence, Enforcement, Prevention, National, Survey, Urban,
Effectiveness, USA
Paper type Research paper
Introduction
Controlling gun crime continues to be a difficult challenge for policymakers and
practitioners in the USA. In 2010, there were nearly 10,000 murders with firearms in
the USA[1] and another 3,38,000 non-fatal violent crimes with guns (Truman, 2011).
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1363-951X.htm
Received 18 June 2012
Revised 25 September 2012
29 October 2012
Accepted 1 November 2012
Policing: An International Journal of
Police Strategies & Management
Vol. 36 No. 3, 2013
pp. 577-603
r Emerald Group Publishing Limited
1363-951X
DOI 10.1108/PIJPSM-06-2012-0052
This research was supported by funding from the Joyce Foundation and the Motorola
Foundation (the authors thank Chuck Wexler of the Polic ...
Similar to Using Narcotics Arrest Data To Predict Violent Crime (20)
Gun violence preventionpractices among local policein th.docx
Using Narcotics Arrest Data To Predict Violent Crime
1. Using Narcotics Arrest Data to Predict Violent Crime Locations in Dallas, Texas Chad Smith [email_address]
2. The crime rate is high in Dallas. More than 15,000 gun crimes per year.
3. Dallas PD uses superficial crime analysis. Percent change by week, month, & year to determine crime trends.
4. Dallas PD targets crime hot spots. DPD needs better tools to predict crime locations to lower the crime rate.
5. Routine activities increase victimization potential. Crime occurs when a motivated offender, a suitable victim, and an appropriate place intersect.
6. Social disorganization increases victimization potential. Social efficacy is a willingness to take action to achieve common goals for a neighborhood.
7. Narcotics and violent crime are related. Drugs and crime are most often related due to the Black Market Effect of prohibition.
8. Social efficacy can overcome most crime factors. Socioeconomic factors of crime are not guarantees crime.
10. The arrests will be weighted by to limit predictions to the drug market.
11. Evaluation of outcomes will be based on a NNA. When two distributions are different, the relative rankings are different.
12. Data for this research will come from Dallas PD records. The data will include arrest and offense reports for drugs and violent crime.
13. The GWR model evaluation will compare predictions to reality. The GWR model will assist in resource deployment for greater efficiency.
14. This research will extend our understanding of narcotics and violent crime. This research will lead to better crime prevention strategies for law enforcement and communities.
Editor's Notes
Abstract: The Dallas Police Department (DPD) has the goal of reducing violent crime by targeting guns, gangs, and drugs. The limited resources available to the DPD require strategic planning to maximize the effect of patrol officers. The DPD currently targets violent crime (murder, rape, robbery-individual, robbery-business and aggravated assault) by analyzing criminal offense reports. This crime model is reactive rather than a proactive, intelligence-driven policing model. The DPD needs a statistical tool to predict high crime areas prior to the offenses occurring. This research will develop a geographically weighted regression (GWR) model that utilizes drug arrest data to determine risk for violent crimes at the block-face level. The GWR tool will assist the DPD in determining where to deploy additional resources to prevent violent gun crimes. Key words: crime control, Dallas Police Department, geographic weighted regression, gun crime, narcotics trafficking Chad Smith is an undergraduate student at the University of North Texas in Denton, Texas, pursuing a Bachelors of Science in Geography. He is also a Senior Corporal of Police with the Dallas Police Department, where he has worked as a patrol officer, crime analyst and intelligence analyst. He may be reached at chad@unt.edu
During the last decade, DPD has reported a higher crime rate per capita than other large U.S. cities (Dallas Morning News 2008). Individual comparisons are often misleading and disingenuous, but they do occur (Federal Bureau of Investigation 2007). These “high crime” stories make the front page of newspapers and are featured on news casts, leading to immense public pressure to lower the crime rate (Sideman and Couzens 1974). During his inauguration speech, Mayor Tom Leppert declared his determination to get Dallas off “the list” of cities with the highest crime rate (Dallas Morning News 2007). Preventing the offenses is more important than solving existing offenses. Preventing the loss of life, injury and property damage is more critical to lowering the crime rate than finding the person responsible for a past offense.
Many major police departments use superficial crime analysis (Willis et al. 2007). While offense location is useful for deployment, crime management requires more detailed analysis of underlying causes and crime risk levels (Craglia, Haining and Wiles 2000). Crime analysis for the DPD is performed by comparing police beats and police reporting areas over various temporal units. This practice makes evaluation of police crime control efforts difficult and doesn’t account for changes in policy or the seasonality of crime.
Police officers, from beat cops to the highest executives, have shown to lack a fundamental understanding of crime hot spots and an inability to properly identify hotspots (Ratcliffe and McCullaugh 1999; Willis et al. 2007) Crime perceptions do not match reality. DPD needs a statistical tool to evaluate the spatial relationships between crime place locations at the lowest possible spatial resolution: block-face level.
Routing activity theory relates crime to everyday activities. Crime occurs at the intersection of three factors: a suitable target, a motivated offender and an appropriate place (Andersen 2000). Each factor has an intermediary that can prevent the crime from occurring. Suitable targets have capable protectors. Motivated offenders have handlers. Suitable places have place managers (Eck 1997; Mazerolle, Kadleck, and Roehl 1998). The presence of an intermediary does not prevent crime, but reduces the risk of a crime occurring.
Social disorganization is defined as “traditions of delinquency are transmitted through successive generations of the same zone in the same way language, roles, and attitudes are transmitted” (Shaw and McKay 1942). Social disorganization is manifested by several factors: residential instability, poverty, and racial/ethnic heterogeneity. Residential instability is a mobile population that does not stay in a neighborhood for long periods of time. Racial/ethnic heterogeneity can lead to social and economic isolation. It can also create feelings of insurmountable obstacles between the neighborhood and success. Poverty, while not a cause of crime, leaves a neighborhood without the resources to deal with common problems. Poverty also influences housing options, leading to concentrations of poverty (Craglia, Haining, and Wiles 2000).
The possession and sale of narcotics must occur in a location that will tolerate drug markets (McCord and Ratcliffe 2007). “ Socially disorganized areas are believed to be business-friendly environments for drug markets because they are prone to contain sufficient numbers of drug users in their population, while also lacking the resources or social efficacy to prevent the establishment of the illegal trade.” Violence related to drug trafficking may be explained by three forces (Resignatio 2000): The psychopharmacological effect is the alteration of the neurochemistry which might lead a person to commit violent acts. The economic compulsion is the crime driven by the cost of an increasingly expensive addiction. The black market effect is the violent crime associated with prohibition of narcotics and their distribution. A positive correlation between violent crime and narcotics does exist (Martinez, Rosenfeld, and Mares 2008). Drug activity was a much stronger indicator of violent crime , even more so than alcohol availability (Gorman, Zhu, and Horel 2005). Drug arrests may be an accurate indicator of drug market activity in a neighborhood (Warner and Coomer 2003).
Social efficacy is the willingness of individuals within a neighborhood to act in the pursuit of common goals. Social efficacy may prevent drug markets from emerging (McCord and Ratcliffe 2007). Individual activity, such as calling 9-1-1 or confronting offenders, is less successful in preventing crime than collective efforts (Mazerolle, Kadleck, and Roehl 1998).
Basic geographic weighted regression model. Distance between location i (arrest) and observation j (crime). Different narcotic types will be modeled with different crime types (approximately 80 combinations).
Drug market size will be estimated using a NNA, where the average distance between each arrest and all crime is calculated. The drug market size will limit the GWR, so that each drug market will be weighted according to its size. This should reduce the amount of overlap between two or more adjacent drug markets.
Fig. 1. Example A shows four random points, indicated as circles 1–4, dispersed in a study area with two crime distributions, triangles and squares. The table to the right shows the nearest neighbor distances from each random point to the nearest triangle point and the nearest square point. The distances are in arbitrary units, and the relative ranking of the random point within each crime set (triangles and squares) is shown in brackets. Where the crime points are interspersed and share the same general area of the study region it can been seen (example A) that the relative rankings of the random points is the same for both crime sets. When the two distributions are markedly different, as in example B, the relative rankings of the random points is different to the level where the change could be detected with a statistical test. Source: Ratcliffe, J. H. 2005. Detecting Spatial Movement of Intra-Region Crime Patterns Over Time. Journal of Quantitative Criminology 21: 103-123 Using a Spearman’s rank correlation, the movement of crime clusters can be detected. The data will be pre-deployment and post-deployment crimes, measured from random points.
DPD collects all of the data needed for this research. The research will utilize a rolling 365 day period. Will include seasonality of crime Will include policy changes which may affect reporting rates. The data will be analyzed at the block-face level to provide greater accuracy of risk assessment and deployment flexibility.
The GWR model will be applied to legacy data in order to predict past events. Developing the model independently of real-time police practices will allow for evaluation of the model without having to account for current deployment strategies.
DPD will be capable of determining the best deployment locations to prevent offenses. DPD can use this information to mobilize community groups, which may counteract the risk of crime for the neighborhood (Mazerolle, Kadleck, and Roehl 1998). The GWR tool will also reduce time spent by DPD selecting deployment areas, thereby saving money.