Rates of serious violent crime in England and Wales have been increasing since 2014. Although these offences account for only around 1% of total crime, they cause disproportionate harm to individuals and society as a whole. Because of this, tackling serious violence is a UK Government and police priority. It is increasingly recognised that violence is preventable and that the most effective ways to prevent violent crime are not directly related to the policing or criminal justice systems. New strategies aimed at reducing violence seek to tackle upstream risk factors, thus preventing the development of offending behaviour among young people. However, there is currently little evidence regarding what types of intervention are effective. A total of £200 million has been granted to the Youth Endowment Fund (YEF) over the next 10 years to support early interventions; evaluation of these interventions is an integral part of the programme. In order to generate high quality evidence, rigorous evaluation of interventions is crucial. There are two key issues that will impact on the quality of such evaluations. Firstly, there is a need for valid, reliable data sources - that measure outcomes prior to and after the intervention has been implemented. Ideally, the data would include both short-term and long-term outcomes. Secondly, it is important to have a well-matched comparison group. Without this, it is difficult to draw any clear conclusions about the effect of the intervention because any changes in rates of offending could arise as a result of other factors (i.e. may not be due to the intervention itself). With this in mind, the Ministry of Justice (MoJ) and Department for Education (DfE) are linking key national datasets, bringing together data from the criminal justice system, including police, prison, and court records, with data from the education system, such as school attainment, absence and exclusions. The linked dataset will contain around 15 years' of data on around 20 million individuals and will have the potential to form a resource to allow robust evaluation of YEF and other interventions. This study has two main elements. In the first stage we will evaluate and document the quality and scope of the MoJ-DfE linked dataset. In the second stage we will investigate the feasibility of using the linked dataset to generate matched control groups for the purpose of evaluating interventions aimed at reducing offending rates in young people; we will compare two different statistical approaches to doing this. Our findings will inform the future development and use of the dataset.

Spouses constitute the largest category of migrant settlement in the UK (40% in 2009). In Britain, as elsewhere in Europe, concern is increasingly expressed over the implications of marriage migration for integration. In some ethnic minority groups, significant numbers of children and grandchildren of former migrants to the UK continue to marry partners from their ancestral homelands. Such marriages are presented as particularly problematic. A 'first generation' of spouses in every generation is thought to inhibit processes of individual and group integration, impeding socio-economic participation and cultural change for both parties in the marriage. New immigration restrictions likely to impact particularly on such groups have thus been justified on the grounds of promoting integration. The evidence base to underpin this concern is, however, surprisingly limited. The principle aim of this project is to enhance understanding of the relationships between marriage-related migration and these complex processes of integration, providing much needed new grounding for both policy and academic debates. Discussion of integration is also characterized by differing and often partial understandings of the concept, which is contested and politicized. In this project, we adopt a multi-level conceptualization of integration as: 1. Referring to processes of migrant and host society interaction: a. Spanning several domains (structural, social, cultural, civic, political and identity). These may be separate or interacting. b. A two-way process affected by both the actions and attributes of migrants, but also by factors in the receiving society which may facilitate or impede integration. 2. Part of discourses of national belonging, which may themselves be perceived as exclusionary. Indicators used to measure integration in quantitative research may also however be used as indicators of related concepts of ethnic inequality and cultural difference, complicating assessments of the integration impact of transnational marriages. In order to disentangle the effects of transnational marriage from those related to ethnic minority membership, we need not just survey research, but the more complex information provided by qualitative methods. This project will focus on the two largest UK populations involved in this genre of marriage migration: Pakistani Muslims and Indian Sikhs. To reflect the diversity of these populations and localities in which they are settled, research will focus on two geographical areas with differing characteristics: West Yorkshire and Bristol. In the first stage of the project, we will analyse available quantitative data to create a background picture of the associations between transnational marriage and various indicators of integration. We will then carry out semi-structured interviews with 64 couples to generate a new body of qualitative data with which to explore processes underlying associations identified in the quantitative data, and identify new avenues for enquiry. In order to bring the role of transnational marriage in these processes to the fore, participants will be sampled through pairs of siblings with contrasting marriage choices, i.e. where one sibling's marriage is transnational, and one took place within the ethnic population in the UK. Together, these two stages of research will allow us to develop nuanced understandings of the relationships between marriage migration and processes of integration in these significant populations. The comparisons between regions, and between ethnic groups will allow us to identify impacts particular to certain contexts, and those which are common in all, and so may also have relevance for other migrant spouses and their partners. These improvements in understandings are necessary not only for scholarship in this area, but also to inform service provision and assist in developing more targeted policy interventions.

Homicide is undoubtedly the most serious form of violence, resulting in substantial and widespread social, financial, and economic harm. Not only does it result in the physical loss of life, but also in problems for surviving families and friends, the neighbourhoods and communities where the crime was committed, and broader society. The most serious form of violence, homicide, declined in England and Wales between the early 2000s and 2014, after which the homicide rate rose again. Much work remains to be done to the drivers of homicide trends; a significant challenge to societies globally, but especially so in England and Wales where research remains in its infancy. This project aims to examine and to better understand the patterns in rising and falling homicide rates in England and Wales over a period of four decades (1977-2019). We will do this by directing special attention to the following individual and aggregate level characteristics, including: (i) the demographic characteristics of victims/offenders involved in homicides (e.g. age, sex, and social background); (ii) the circumstantial characteristics of homicide incidents (e.g. location, weapon use, alcohol use); (iii) the (aggregate-level) characteristics relating to lifestyle patterns/routine activities; (iv) the wider socio-economic conditions, cultural values; and (v) the role played by public perceptions and social attitudes in responding to homicide trends. In particular, we will (a) disaggregate and compare distinct homicide subtypes to scrutinize and better understand changes in homicide trends, using more comprehensive typologies based on offender-victim relationships and the motives/circumstances of the homicide; and (b) compare lethal violence trends with trends in non-lethal violence by dissecting violence subtypes to allow for a more accurate examination of changes in violent crimes, and to assess similarities and differences in patterns of lethal and non-lethal violence in England and Wales. Investigating the role these factors play in facilitating trends in homicide over time is critical for advancing our theoretical and empirical knowledge in this area, enabling guided policy efforts to further help reduce homicide and to potentially help mitigate further spikes. To achieve the project's aims, we will draw on highly reliable, robust, large-scale datasets, including the Homicide Index (HI, 1977-2019), the British Crime Survey/Crime Survey for England and Wales (BCS/CSEW, 1981-2019), and the British Social Attitudes Survey (BSA, 1983-2019). Data from the HI will allow for an extensive exploration of long-term patterns in homicide trends and will enable further refinement of disaggregating different subtypes of homicides; the two other sources will allow us to relate variables on lifestyle/routine activities at aggregate level, public perception/attitudes, and socioeconomic factors in a representative population sample. To analyse the data, multivariate trend analysis will be used to identify significant influencing factors driving changes in homicide trends. Lastly, one report will be produced, and four articles will be published in peer-reviewed international journals. The project will be conducted by an interdisciplinary team of experienced researchers with (a) a background in criminology, sociology, social policy and economics, (b) an interest in homicide, violence and crime in general; and in processes of change, both at the individual level, and the societal level; (c) expertise in quantitative research methods, with particular experience in social statistics, and working with large-scale and sensitive datasets; and (d) a track record of undertaking a multitude of successful ESRC-projects using secondary data analyses to inform theory, practice, and policy. This will ensure that the project is performed successfully and efficiently with the highest quality standard.

This project will develop an operationally and technically viable approach to cargo threat investigation. The main aim of the project is to provide a real-time dynamic passive profiling technique to assist Border Control Agencies and has the potential to improve hit rates; i.e. to improve targeting the people that carry contraband and hence ensure less is entering the UK.To be specific, the real-time dynamic passive profiling technique will be based on the modelling of facial expressions, eye movement and pupil changes in both the visual and thermal domains and link these to malicious intent and physiological processes (such as blood flow, eye movement patterns, and pupil dilation). To facilitate this process, one of the initial aspects of the project will be the collection, analysis and development of the dataset used to model the baseline of facial imagery behaviour of the general population against which physiological behaviours in people with malicious intent would need to be detected. Both the baseline and the dynamic profiling will be based on the response to a series of questions. The developed techniques will be evaluated in operational trails at border control points. The multi-modal facial analysis will provide additional information to the current profiling and the developed techniques will have a wider remit into other domains. It is envisioned that this will be easily integrated into the current process.There are three main challenges:a) to determine the facial/eye features, in combination with psychological profiling, to provide robust baselines that can be linked to malicious intent,b) to develop and combine the various dynamic real-time facial models (visual expression, thermal, eye movement) related to intent, andc) to evaluate the developed system within different environments, ranging from airport to port based border control points.

Terrorist risks and threats are increasingly identified and countered through new forms of data analytics made possible by rapid advances in machine learning (ML) and artificial intelligence (AI). Private actors, including social media platforms, airlines and financial institutions, now actively collaborate with states and international organisations (IOs) to implement ambitious data-led security projects to support global counterterrorism efforts. The UN Security Council (UNSC) has called on all states to intensify the exchange of information about suspected terrorists by building watchlists and sharing biometric data, using ML to predictively identify 'future terrorists' in advance. Social media platforms are using AI to detect extremist content online and regulate global data flows on an unprecedented scale. Passenger data from the aviation industry is analysed to identify suspicious 'patterns of behaviour' and control the movements of risky travellers. Financial data is mined by banks to spot suspicious transactions and terrorist 'associations'. These changes are all putting new and far-reaching global information infrastructure projects into motion. Yet the implications of these shifts for how international law is practiced, global security threats known and powerful actors held accountable remain uncertain. The data infrastructures underlying global governance have been largely neglected in legal scholarship. And whilst potential problems that AI poses (discrimination and privacy violations) are becoming clearer, solutions remain elusive - especially in the security domain, where secrecy is key and the inner workings of algorithms are 'black-boxed' even more than usual. Regulatory theorists argue that we urgently need to 'expand our frame of rights discourse to encompass our socio-technical architecture' to respond to the accountability challenges of AI (Yeung 2019). Data infrastructures, in other words, might provide the basis for reimagining how information and rights could be reconnected in our digital present. This project rethinks global security law from the 'infrastructure space' it is creating, focusing on (i) countering terrorism online and (ii) controlling the movements of 'risky' individuals. My hypothesis is that the most far-reaching changes to global security governance are not being written in the language of international law, or created through the formal powers of states and IOs, but built through new socio-technical infrastructures and the expertise they are enabling. Data infrastructures are critical for understanding how rights might be extended through AI. I develop the concept of 'infra-legalities' (or, the regulatory effects of data infrastructures) to analyse these shifts and develop a new approach for studying international law and regulation in the age of algorithmic global governance. Infrastructure is usually disregarded as an invisible substrate on which powerful actors act. It is rarely seen as something through which knowledge and governance can be created and shaped. Drawing from Science and Technology Studies, computer science and security studies, this project performs what Bowker and Star (1999) call an 'infrastructural inversion' by mapping the seemingly mundane governance work of data infrastructures in this domain. By 'following the data' - and tracing the socio-technical relations, norms, knowledge practices and power asymmetries that security infrastructures are enacting - a different method of studying global governance can emerge. States, IOs and tech platforms are all calling for the ethical development of AI. Different regulatory approaches are proposed with no consensus on how to mitigate the adverse effects of AI whilst embracing its vast potentialities. Studying the infra-legalities of global security law opens space for addressing these challenges and shaping current policy debates on security, trust and accountability in the age of AI and automation.