RUcore: Rutgers University Community Repository
How are street drug dealing locations selected?
Descriptive
TitleInfo
Title
How are street drug dealing locations selected?
SubTitle
a situational analysis
Name
(type = personal)
NamePart
(type = family)
Hsu
NamePart
(type = given)
Ko-Hsin
NamePart
(type = date)
1983-
DisplayForm
Ko-Hsin Hsu
Role
RoleTerm
(authority = RULIB)
author
Name
(type = personal)
NamePart
(type = family)
Clarke
NamePart
(type = given)
Ronald V.
DisplayForm
Ronald V. Clarke
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
chair
Name
(type = personal)
NamePart
(type = family)
Braga
NamePart
(type = given)
Anthony A.
DisplayForm
Anthony A. Braga
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Miller
NamePart
(type = given)
Joel
DisplayForm
Joel Miller
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Natarajan
NamePart
(type = given)
Mangai
DisplayForm
Mangai Natarajan
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
outside member
Name
(type = corporate)
NamePart
Rutgers University
Role
RoleTerm
(authority = RULIB)
degree grantor
Name
(type = corporate)
NamePart
Graduate School - Newark
Role
RoleTerm
(authority = RULIB)
school
TypeOfResource
Text
Genre
(authority = marcgt)
theses
OriginInfo
DateCreated
(qualifier = exact)
2014
DateOther
(qualifier = exact);
(type = degree)
2014-05
Place
PlaceTerm
(type = code)
xx
Language
LanguageTerm
(authority = ISO639-2b);
(type = code)
eng
Abstract
(type = abstract)
In Newark, NJ, drug dealing is common, but it is not evenly distributed in every part of the city. Between 2007 and 2009, most drug arrests were made on less than 20% of the streets. The dissertation seeks to explain how the locations for drug dealing are related to their surrounding situational features. It is hypothesized that these features produce criminal opportunities for drug dealing activities: lack of guardianship, accessibility, and crime generators. This dissertation focuses on drug arrests at the micro-level – street segments and intersections. Police arrest records from 2007 to 2009 provided by the Newark City Police Department are analyzed. A matched case-control design is used. Applying a threshold criterion of 5 or more arrests, 104 street segments and 31 intersections having frequent dealing activity per year in 2007 to 2009 are sampled to be the cases. Controls are individually matched with the cases, taking account of their distance from the cases, street length, and the intersecting thoroughfares. The sample size is 135 pairs. Situational data of local drug dealing settings are observed using Google Street View. Inter-rater reliability is assessed to affirm the quality of the data. McNemar’s test is employed to examine the correlations between variables and the drug market. The dissertation also sets forth a conditional logistic regression model to analyze the causal relationships between variables and the drug market. Results show that drug dealing activity tends to occur on specific street segments characterized by abandoned buildings, bus stops, parking lots, vacant land, mailboxes, retail stores (near vacant lands), or the absence of a church. Drug dealing activity tends to occur on specific intersections characterized by parking lots, retail stores, and churches. The presence of a church as a crime generator to the occurrence of drug markets on intersections is one notable finding of this dissertation. The results signal that there are distinguishable situational factors affecting drug activity on streets and intersections, respectively. This dissertation demonstrates the feasibility of using Google Street View for future crime research. Policy implications are provided for making local drug markets more predictable and controllable to the police.
Subject
(authority = RUETD)
Topic
Criminal Justice
RelatedItem
(type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
(type = RULIB)
ETD
Identifier
ETD_5652
PhysicalDescription
Form
(authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
xxiv, 193 p. : ill.
Note
(type = degree)
Ph.D.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = vita)
Includes vita
Note
(type = statement of responsibility)
by Ko-Hsin Hsu
Subject
(authority = ETD-LCSH)
Topic
Drug traffic--New Jersey--Newark
Subject
(authority = ETD-LCSH)
Topic
Drugs of abuse--New Jersey--Newark
Subject
(authority = ETD-LCSH)
Topic
Streets--New Jersey--Newark
Subject
(authority = ETD-LCSH)
Topic
Selling--Drugs--New Jersey--Newark
RelatedItem
(type = host)
TitleInfo
Title
Graduate School - Newark Electronic Theses and Dissertations
Identifier
(type = local)
rucore10002600001
Location
PhysicalLocation
(authority = marcorg);
(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier
(type = doi)
doi:10.7282/T3NP22QW
Genre
(authority = ExL-Esploro)
ETD doctoral
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Rights
RightsDeclaration
(ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder
(type = personal)
Name
FamilyName
Hsu
GivenName
Ko-Hsin
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
(encoding = w3cdtf);
(qualifier = exact);
(point = start)
2014-05-01 18:55:22
AssociatedEntity
Name
Ko-Hsin Hsu
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - Newark
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical
RULTechMD
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ContentModel
ETD
OperatingSystem
(VERSION = 5.1)
windows xp
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