Simulation Strategies to Reduce Recidivism (Record no. 95604)

000 -LEADER
fixed length control field 04736nam a22004455i 4500
001 - CONTROL NUMBER
control field 978-1-4614-6188-3
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140220082823.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 130606s2013 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781461461883
-- 978-1-4614-6188-3
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-1-4614-6188-3
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number HV6001-7220.5
072 #7 - SUBJECT CATEGORY CODE
Subject category code JKV
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code SOC004000
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 364
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Taxman, Faye S.
Relator term editor.
245 10 - TITLE STATEMENT
Title Simulation Strategies to Reduce Recidivism
Medium [electronic resource] :
Remainder of title Risk Need Responsivity (RNR) Modeling for the Criminal Justice System /
Statement of responsibility, etc edited by Faye S. Taxman, April Pattavina.
264 #1 -
-- New York, NY :
-- Springer New York :
-- Imprint: Springer,
-- 2013.
300 ## - PHYSICAL DESCRIPTION
Extent XI, 315 p. 30 illus.
Other physical details online resource.
336 ## -
-- text
-- txt
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337 ## -
-- computer
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-- rdamedia
338 ## -
-- online resource
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347 ## -
-- text file
-- PDF
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505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introduction -- The Stages of Simulation Models in Criminal Justice -- Simulation Language, Software, and Data Needs -- Using Simulation Methods to Estimate the Cost of Policy Choices -- A Dynamic Systems Approach to Examining Sentencing Alternatives -- Assessing Correctional Treatment Outcomes with Simulation Techniques -- A Discrete-Event Simulation Model of Heroine Use and Treatment Over the Lifecourse -- Using Evidence-Based Research to Inform Model Assumptions -- Developing Synthetic Data for Criminal Justice Simulation -- The Growing Use of Simulation Techniques by Sentencing Commissions -- Creating and Sustaining Organizational Support for Simulation Use -- Maintaining Agency-Based Simulation Models -- The Benefits of Using Simulation from Criminal Justice Education.
520 ## - SUMMARY, ETC.
Summary, etc Mass incarceration, the recession, and the swinging pendulum of correctional philosophies has put increasing attention on the use of evidence-based practices and treatments to guide the future direction of our criminal justice system. The Risk-Need-Responsivity (RNR) framework has emerged as a useful set of organizing principles for treating offenders. While the literature is supportive of the RNR approach, we understand little about the system impacts of moving in this direction. Some important questions include: What would happen if we implemented RNR programming system-wide? How can we simulate such a complex strategy? What is the estimated impact on individuals, programs, and systems? Simulation modeling can be used to address these basic questions. Since the 1970’s, simulation models have been used to capture the realities of the criminal justice system.  Some early simulation projects were limited due to lack of data available to validate models, deficits in skills needed by staff to design and build models, and limited access to computing technology required to transform models into systems representations.  This timely book revisits the concept of simulation modeling for the 21st century: the wider availability of data has created more opportunity to verify and validate models; computing software has become more available and easier to use; and the capacity for visualization and communication of models shows promise for the future of simulation in criminal justice. This is an opportune time to make use of simulation models to examine the complex world of corrections and investigate the possible outcomes associated with implementing the RNR approach. Simulation Strategies to Reduce Recidivism provides a central source of information on the current state of simulation modeling in corrections. It includes an overview of the methods used to build simulation models that address questions about appropriate placement of offenders in programs and controls, as well as applications of these models. Authors use simulation tools to investigate the impact of diversion programs, to map offender movement through programs and systems, and to address other grappling issues regarding the capability to build effective recidivism reduction systems. This work will be an important resource for researchers in criminal justice and related fields, as well as those studying policy-related topics.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Social sciences.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Social policy.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Criminology.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Social Sciences.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Criminology & Criminal Justice.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Social Policy.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Pattavina, April.
Relator term editor.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9781461461876
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-1-4614-6188-3
912 ## -
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