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Machine learning for criminology and crime research : at the crossroads / Gian Maria Campedelli. (Record no. 20454)

000 -LEADER
fixed length control field 02771nam a22002057a 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781003217732
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 364.072
Item number C193 2022
100 ## - MAIN ENTRY--AUTHOR NAME
Personal name Campedelli, Gian Maria, author.
245 ## - TITLE STATEMENT
Title Machine learning for criminology and crime research : at the crossroads / Gian Maria Campedelli.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication New York :
Name of publisher Routledge, Taylor & Francis Group,
Year of publication ©2022.
300 ## - PHYSICAL DESCRIPTION
Number of Pages 1 online resource, xviii, 159 pages :
Other physical details Illustrations.
490 ## - SERIES STATEMENT
Series statement (Routledge advances in criminology)
500 ## - GENERAL NOTE
General note Includes bibliographical references and index.
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note Print version: Campedelli, Gian Maria. Machine learning for criminology and criminal research First Edition. London ; New York : Routledge, Taylor & Francis Group, 2022 9781032109190 (DLC) 2021059992
520 ## - SUMMARY, ETC.
Summary, etc Machine Learning for Criminology and Crime Research reviews the roots of the intersection between machine learning, Artificial Intelligence, and research on crime, examines the current state of the art in this area of scholarly inquiry, and discusses future perspectives that may emerge from this relationship. As machine learning and Artificial Intelligence (AI) approaches become increasingly pervasive, it is critical for criminology and crime research to reflect on the ways in which these paradigms could reshape the study of crime. In response, this book seeks to stimulate this discussion. The opening part is framed through a historical lens, with the first chapter dedicated to the origins of the relationship between AI and research on crime, refuting the "novelty narrative" that often surrounds this debate. The second presents a compact overview of the history of AI, further providing a non-technical primer on machine learning. The following chapter reviews some of the most important trends in computational criminology and quantitatively characterizing publication patterns at the intersection of AI and criminology, through a network science approach. The book also looks to the future, proposing two goals and four pathways to increase the positive societal impact of algorithmic systems in research on crime. The final chapter provides a survey of the methods emerging from the integration of machine learning and causal inference, showcasing their promise for answering a range of critical questions. With its transdisciplinary approach, Machine Learning for Criminology and Crime Research is important reading for scholars and students in criminology, criminal justice, sociology and economics, as well as Artificial Intelligence, data sciences and statistics, and computer science"-- Provided by publisher.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Criminology--Research.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Artificial intelligence--Research.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Machine learning--Statistical methods.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Electronic Books
Holdings
Source of acquisition Permanent Location Date acquired Collection code Koha item type Lost status Shelving location Withdrawn status Current Location Full call number
DonationCagayan State University - Carig Library2025-05-17E-BooksElectronic Books E-Resource Section Cagayan State University - Carig Library364.072 C193 2022

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