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Since the 1970s, important struggles were won to improve the ‘publicness’ of gender-based violence (GBV) in Norway. Since 2000, the Ministry of Justice has coordinated policy work to combat GBV for the Norwegian government. In 2010, a Shelter Act made the provision of domestic violence shelters by local governments mandatory. This article turns to the question of how a public responsibility for GBV was established, and how dedicated public policy, legislation, funding, and services were subsequently realised. This article identifies the crucial actors, factors, and conditions that have had the greatest influence on agenda-setting, policy development and decision making in the policy cycle. Analysis is based on 22 interviews, policy analysis and previous Norwegian studies that have theorised about the success, how it came about, and the decisive factors in achieving change. Participants of this study were academics, activists, specialist service providers, politicians, lawyers, survivor-advocates, and political advisors. In exploring campaigning for change with participants, the study uncovered fault lines within gender equality and violence scholarship and public policy in Norway that may help explain why GBV is still commonplace. The article offers future directions for policy and research that reflect on these discursive exclusions and normative assumptions.

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Scientific research ethics are challenged today by the risk of misusing research results that could adversely affect or harm both individuals and their environment. In the ethics literature, such risks have been linked to the possibility of research results falling into the wrong hands, that is, for criminal or terrorist purposes. However, crime data misuse can also affect policy makers’ decisions and lead to discrimination, stigmatization, harassment and intimidation of citizens. From a two-fold perspective, this chapter examines the potential misuse of crime data caused by policy decisions: (1) outlining the ethical scope of potential misuses in European security research; and (2) proposing recommendations to minimize this risk based on a ‘Mutual Distrust Model’ between researchers and policy makers.

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This chapter explores the potential for administrative data to improve police policy and decision making by focusing on how to incorporate a critical reflection into the analysis and interpretation of administrative data by understanding its construction. To do this, we focus on Police Recorded Crime as the key source of administrative data in policing in England and Wales. We then evaluate where policing is currently in terms of understanding the need for and having the skills to undertake this critical reflection, based on work undertaken with 60 police analysts from the North of England in 2018/19 as part of the N8 Policing Research Partnership. Finally, we look to the future and raise the issue of the place of the police analysts in the policing institution, considering what they currently contribute and what they could contribute to police policy and decision making.

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With the rise of evidence-informed approaches to criminal justice, new models of data-driven decision making and the emergence of predictive analytics and other new tools for understanding and employing crime data, the field of crime research has grown substantially over the past decade. The fuel that drives that growth is data. In this edited collection, we present a comprehensive volume of chapters from some of the leading crime scientists from around the world. Researchers, crime analysts and others working with crime data from across four continents and seven countries provide rich discussions of some of the strengths, perils and opportunities provided by the range of data sources, tools, techniques and topics now available. Aimed at a diverse audience – including students, academic researchers, police practitioners, crime analysts and public policy makers – our goal in this book is to make crime data and analysis accessible and interesting. This book will thus appeal to readers who are interested in learning more about the varieties of data types and sources that can and is informing contemporary criminal justice research.

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Social network analysis (SNA) is an approach concerned with analysing networks of relations and interactions among a defined set of actors. In recent years, SNA has become known as a useful tool for analysing a wide range of criminal networks, including networks of serious financial crime. However, using SNA in the study of crime is hindered by the aim of actors involved in these to conceal their interactions, making data collection complicated. These complications stem from issues with data availability, validity and reliability. To tackle these issues, we first introduce a framework for thinking about six aspects of network data collection: nodes, ties, attributes, levels, dynamics and context. In the light of this framework, we subsequently review three types of data sources usable for analysing financial crime networks in the context of the United Kingdom. These data sources are documents accompanying Deferred Prosecution Agreements, enforcement case files and commercial transaction data. We illustrate the contents of each of these data sources together with their potential for extracting network data and the types of conclusions that can be drawn through analysing them. These data sources share common problems in being of a secondary non-scientific nature and being prone to contain missing information. In conclusion, we illustrate further uses of SNA and possible extensions of the introduced data sources to other types of criminal networks and jurisdictions beyond the United Kingdom.

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Crime research has grown substantially over the past decade, with a rise in evidence-informed approaches to criminal justice, statistics-driven decision-making and predictive analytics. The fuel that has driven this growth is data – and one of its most pressing challenges is the lack of research on the use and interpretation of data sources.

This accessible, engaging book closes that gap for researchers, practitioners and students. International researchers and crime analysts discuss the strengths, perils and opportunities of the data sources and tools now available and their best use in informing sound public policy and criminal justice practice.

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With the rise of evidence-informed approaches to criminal justice, new models of data-driven decision making and the emergence of predictive analytics and other new tools for understanding and employing crime data, the field of crime research has grown substantially over the past decade. The fuel that drives that growth is data. In this edited collection, we present a comprehensive volume of chapters from some of the leading crime scientists from around the world. Researchers, crime analysts and others working with crime data from across four continents and seven countries provide rich discussions of some of the strengths, perils and opportunities provided by the range of data sources, tools, techniques and topics now available. Aimed at a diverse audience – including students, academic researchers, police practitioners, crime analysts and public policy makers – our goal in this book is to make crime data and analysis accessible and interesting. This book will thus appeal to readers who are interested in learning more about the varieties of data types and sources that can and is informing contemporary criminal justice research.

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With the rise of evidence-informed approaches to criminal justice, new models of data-driven decision making and the emergence of predictive analytics and other new tools for understanding and employing crime data, the field of crime research has grown substantially over the past decade. The fuel that drives that growth is data. In this edited collection, we present a comprehensive volume of chapters from some of the leading crime scientists from around the world. Researchers, crime analysts and others working with crime data from across four continents and seven countries provide rich discussions of some of the strengths, perils and opportunities provided by the range of data sources, tools, techniques and topics now available. Aimed at a diverse audience – including students, academic researchers, police practitioners, crime analysts and public policy makers – our goal in this book is to make crime data and analysis accessible and interesting. This book will thus appeal to readers who are interested in learning more about the varieties of data types and sources that can and is informing contemporary criminal justice research.

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Prisons are concerned with safety. One key piece of information is how much violence takes place in prison. This is important from a micro perspective – will this new inmate be at risk of victimization? And from a macro one too – are more resources needed in a prison to reduce the potential for violence? Yet our knowledge about the ‘dark figure’ of prison violence is limited by the nature of the act and our ability to research it. We use a mixed-methods project in the Penitentiary Unit 4 (Uruguay) that combines: official records of prison incidents; survey data in a convenience sample of inmates (n=209); qualitative interviews with inmates, prison staff and key informants (n=33); and non-participant unstructured and structured observation. Our findings show that in two months only 12 violent incidents were officially recorded, compared to 82 incidents recorded in our observations. Of the total inmates that answered our survey (42 per cent of the module), 60 per cent were victimized but only 22 per cent of victims reported to authorities. Reasons for not reporting were not wanting to break prison codes, fear of retaliation, lack of trust in the prison system and the perception of lack of punishment. Under-reporting was also associated with institutional conditions related to lack of resources, irrelevance of reporting in guard role, lack of trust in the importance of reporting, poor knowledge of how to report and ‘naturalization’ of violence. We finish by discussing the limitations of our study, and making suggestions for estimation of dark figure and policy implications.

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