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Crime Solvability Factors

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Cover of 'Crime Solvability Factors'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Existing Research on Solvability
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    Chapter 3 Assessing Solvability Factors in Greater Manchester, England: The Case of Residential Burglaries
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    Chapter 4 Population-Level Analysis of Residential Burglaries
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    Chapter 5 Solvability Indicators for ‘First Officers’: Targeting Eyewitness Questioning at Non-residential Burglaries
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    Chapter 6 Pickpocketing on Railways
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    Chapter 7 Metal Theft Solvability and Detection
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    Chapter 8 Detecting and Combating Internet Telephony Fraud
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    Chapter 9 Targeting Factors that Predict Clearance of Non-domestic Assaults
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    Chapter 10 Solvability Factors and Investigative Strategy for Faith Hate Crime: Anti-Semitic and Islamophobic Assault, Criminal Damage and Public Order Offences in London
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    Chapter 11 Reporting, Detection and Solvability of Sex Offences on Railways
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    Chapter 12 Offender–Offence Profiling: Improving Burglary Solvability and Detection
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    Chapter 13 Boosting Offence Solvability and Detections: Solving Residential Burglaries by Predicting Single and Multiple Repeats
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    Chapter 14 Improving Offence Solvability and Detection Rates at Non-residential Burglary: Predicting Single and Multiple Repeat Incidence
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    Chapter 15 Homicide Resources, Solvability and Detection
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    Chapter 16 Investigative Activities, Resources and Burglary Detection
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    Chapter 17 The Organisation and Deployment of Patrol Resources: Cost-Effective On-Scene Arrest at Burglaries
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    Chapter 18 Resources, Solvability and Detection: A Theoretical Model
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    Chapter 19 Conclusions
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Crime Solvability Factors
Published by
Springer International Publishing, January 2019
DOI 10.1007/978-3-030-17160-5
978-3-03-017159-9, 978-3-03-017160-5

Richard Timothy Coupe, Barak Ariel, Katrin Mueller-Johnson

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 33%
Researcher 1 33%
Other 1 33%
Readers by discipline Count As %
Computer Science 1 33%
Economics, Econometrics and Finance 1 33%
Social Sciences 1 33%