At a time when resources are scarce, not every crime may be investigated as fully as is desirable. Police generally use experience to guide their case screening. This volume demonstrates a new, research-based approach, exploring innovative research on crime solvability as a factor for crime investigation and prevention. Crime solvability is the interplay between forensic science, decision-making, and prediction to determine the likelihood that a crime will be solved. This text discusses recent studies of how solvable cases may be identified, using original sets of police data. It focuses on high-volume crimes such as burglary, assault, metal theft, and cyberfraud. By targeting more cases that can be solved, police departments can manage their resources better and have the greatest effect on arrests, as well as preventing future crimes by these offenders. Topics covered include: Research into the effects of crime solvability and detection outcomes. Studies ranging from less severe, high-volume crimes to severe offences. Effects of resources on investigating and detecting crime. Theoretical resourcing-solvability model of crime detection. Detection complements preventive approaches in containing criminal activity. Chapters on incident solvability and measured use of resources in different investigative stages. Predictive approaches for improving crime solvability. Property, violent, and sexual offenses. Crime Solvability Factors: Police Resources and Crime Detection will be of interest to researchers in criminology and criminal justice, particularly with an interest in quantitative and experimental research and police studies. It will also be of interest to policymakers and police organizations.

This book explores the potential of domestic abuse data to assess the level of harm caused to victims and the amount of resources required to respond to it. Policing domestic abuse has become a major activity for the police service in England and Wales. Part of the police strategy is to gather hundreds of thousands of detailed records about victims and suspects - the single largest set of domestic abuse records available, but one that to date has largely unexplored by researchers. In this volume, Matthew Bland and Barak Ariel analyse three substantial datasets taken from police forces across the country and ask: * Can police data be used to derive meaningful insight? * How should we use these data to measure harm? * Just how much domestic abuse involves a repeat victim? * Does abuse get more serious over time? * Can serious domestic abuse be predicted before it occurs? This volume illustrates the scale of the challenge the police and other agencies face with reducing domestic abuse. A small proportion of individuals generate a majority of harm; this book argues that police records offer opportunities to identify these individuals before the harm occurs. Demonstrating that statistical techniques can be used to profile domestic abuse to target harm reduction strategies more precisely and even identify a sizable proportion of serious cases before they occur, this volume will be of interest to law enforcement officials, policing researchers, and policy makers interested in reducing the phenomenon of domestic abuse.

This volume presents a collection of essays from experienced crime analysts from around the world. It explores themes relevant to anyone embarking on, or already into a career in crime analysis. Divided into two sections, this book addresses technical issues central to the profession, from collection of data to presenting findings to reluctant audiences. It incorporates a collection of methodological case studies, demonstrating the ways analysis has made a meaningful difference to policing and security. This volume is intended for scholars who study and work with crime analysts, the global community of undergraduate and graduate students who may take one of these roles in the future, and law enforcement.

This book explores the potential of domestic abuse data to assess the level of harm caused to victims and the amount of resources required to respond to it. Policing domestic abuse has become a major activity for the police service in England and Wales. Part of the police strategy is to gather hundreds of thousands of detailed records about victims and suspects - the single largest set of domestic abuse records available, but one that to date has largely unexplored by researchers. In this volume, Matthew Bland and Barak Ariel analyse three substantial datasets taken from police forces across the country and ask: * Can police data be used to derive meaningful insight? * How should we use these data to measure harm? * Just how much domestic abuse involves a repeat victim? * Does abuse get more serious over time? * Can serious domestic abuse be predicted before it occurs? This volume illustrates the scale of the challenge the police and other agencies face with reducing domestic abuse. A small proportion of individuals generate a majority of harm; this book argues that police records offer opportunities to identify these individuals before the harm occurs. Demonstrating that statistical techniques can be used to profile domestic abuse to target harm reduction strategies more precisely and even identify a sizable proportion of serious cases before they occur, this volume will be of interest to law enforcement officials, policing researchers, and policy makers interested in reducing the phenomenon of domestic abuse.

This volume presents a collection of essays from experienced crime analysts from around the world. It explores themes relevant to anyone embarking on, or already into a career in crime analysis. Divided into two sections, this book addresses technical issues central to the profession, from collection of data to presenting findings to reluctant audiences. It incorporates a collection of methodological case studies, demonstrating the ways analysis has made a meaningful difference to policing and security. This volume is intended for scholars who study and work with crime analysts, the global community of undergraduate and graduate students who may take one of these roles in the future, and law enforcement.

At a time when resources are scarce, not every crime may be investigated as fully as is desirable. Police generally use experience to guide their case screening. This volume demonstrates a new, research-based approach, exploring innovative research on crime solvability as a factor for crime investigation and prevention. Crime solvability is the interplay between forensic science, decision-making, and prediction to determine the likelihood that a crime will be solved. This text discusses recent studies of how solvable cases may be identified, using original sets of police data. It focuses on high-volume crimes such as burglary, assault, metal theft, and cyberfraud. By targeting more cases that can be solved, police departments can manage their resources better and have the greatest effect on arrests, as well as preventing future crimes by these offenders. Topics covered include: Research into the effects of crime solvability and detection outcomes. Studies ranging from less severe, high-volume crimes to severe offences. Effects of resources on investigating and detecting crime. Theoretical resourcing-solvability model of crime detection. Detection complements preventive approaches in containing criminal activity. Chapters on incident solvability and measured use of resources in different investigative stages. Predictive approaches for improving crime solvability. Property, violent, and sexual offenses. Crime Solvability Factors: Police Resources and Crime Detection will be of interest to researchers in criminology and criminal justice, particularly with an interest in quantitative and experimental research and police studies. It will also be of interest to policymakers and police organizations.

The fourth book in The SAGE Quantitative Research Kit, this resource covers the basics of designing and conducting basic experiments, outlining the various types of experimental designs available to researchers, while providing step-by-step guidance on how to conduct your own experiment. As well as an in-depth discussion of Random Controlled Trials (RCTs), this text highlights effective alternatives to this method and includes practical steps on how to successfully adopt them. Topics include: * The advantages of randomisation * How to avoid common design pitfalls that reduce the validity of experiments * How to maintain controlled settings and pilot tests * How to conduct quasi-experiments when RCTs are not an option Practical and succintly written, this book will give you the know-how and confidence needed to succeed on your quantitative research journey.