HO

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.

Gun crime is a problem in some areas in the UK and many other countries. The police have ways of detecting criminals carrying guns, but this usually involves surveillance over a period of time together with targeted stop and search. There is no affordable detector available that is capable of remotely sensing whether a person is likely to be carrying a gun or not. The police do have scanners and portals that can be installed at key locations such as airports and major event venues to detect people carrying even small metal objects, or portals that use harmless microwaves, THz waves or very low level x-rays to form images of concealed guns on a person. THz and microwaves can form clear body images by penetrating clothing, but moral and technical issues arise from the technology, particularly intrusion into privacy. Also, these are not easily deployable, however, and are still at the research stage in many cases. What is really required is a portable device capable of remotely and discretely detecting whether suspects are carrying weapons and this proposed project aims to commence the development of such a device. During its development, the research will aim to first identify what sort of electromagnetic radiation best penetrates clothing over a range of atmospheric conditions. Microwaves are a form of electromagnetic radiation, but other forms exist such as light, infra-red, Tera-Hertz and millimetre waves and they all differ in their ability to penetrate fabrics. It is also possible to use ultrasound to detect metal objects concealed under clothing and we also propose to investigate this. Some of these forms of electromagnetic radiation get absorbed by the body, whereas others are reflected back depending on the precise wavelength. We will be looking for reflections off the surfaces of the gun in a similar manner to radar detecting the bright echoes from ships and aircraft, whilst filtering out the lower level reflections from the human body. Guns are not the only objects that could be concealed about a person that could give these bright reflections at a remote sensing site. Mobile phones, leather wallets, pens and portable music players could also give detectable signals. We aim to use features unique to a gun, such as gun barrels and other cavities to identify unique signatures in the reflected signals. For example, the gun barrel acts as a resonant cavity rather like air blown over a musical wind instrument, and we aim to detect these resonances remotely. During the second phase of the investigation, we will utilise a mix of the most effective bands in the electromagnetic spectrum, whether that be radio frequencies, microwaves or some other part of the spectrum, together with ultrasound, to develop a sensor that is effective at detecting guns remotely and is deployable by the police. It is possible that different guns will produce different responses from the sensor, but we will use pattern recognition techniques similar to those used in the automatic recognition of number plates or handwriting (i.e. neural networks ) to learn to recognise these particular responses. The research will be undertaken by a consortium of Universities, namely Manchester Metropolitan University, Manchester University, University of Huddersfield and Queen Mary London who will each investigate different aspects of the problem.

Current cargo screening systems are sub-optimal because they are based on historic layouts, for instance luggage will go through fixed tiered systems: First all luggage will go through detector A, if it fails to pass, then it will go through detector B and if it fails again through detector C. Moreover, we do not understand the performance of current systems as no baseline performance data is available, i.e. it is unclear whether current systems perform better than random or not. Thus even if an improvement was proposed, it would be difficult to measure its impact if any.We are proposing to design a plug and play software tool (cargo screening system simulator) that will map the right technology to the right commodity / threat combination and thus* Identify gaps in a current sensor system set-up / what new technology do we need?* Allow for proper evaluation of new sensor technology / is it value for money?* Optimise given resources / get highest throughput / detection for fixed resources.Additionally, as the project is interested in the whole system and allows for the evaluation of new technologies, it is an enabling project for all other sandpit projects. We will be able to evaluate new sensor technologies proposed in specific scenarios to establish practical cost / benefits. To achieve this, we propose to run a follow on network alongside the project.

Gun crime is a problem in some areas in the UK and many other countries. The police have ways of detecting criminals carrying guns, but this usually involves surveillance over a period of time together with targeted stop and search. There is no affordable detector available that is capable of remotely sensing whether a person is likely to be carrying a gun or not. The police do have scanners and portals that can be installed at key locations such as airports and major event venues to detect people carrying even small metal objects, or portals that use harmless microwaves, THz waves or very low level x-rays to form images of concealed guns on a person. THz and microwaves can form clear body images by penetrating clothing, but moral and technical issues arise from the technology, particularly intrusion into privacy. Also, these are not easily deployable, however, and are still at the research stage in many cases. What is really required is a portable device capable of remotely and discretely detecting whether suspects are carrying weapons and this proposed project aims to commence the development of such a device. During its development, the research will aim to first identify what sort of electromagnetic radiation best penetrates clothing over a range of atmospheric conditions. Microwaves are a form of electromagnetic radiation, but other forms exist such as light, infra-red, Tera-Hertz and millimetre waves and they all differ in their ability to penetrate fabrics. It is also possible to use ultrasound to detect metal objects concealed under clothing and we also propose to investigate this. Some of these forms of electromagnetic radiation get absorbed by the body, whereas others are reflected back depending on the precise wavelength. We will be looking for reflections off the surfaces of the gun in a similar manner to radar detecting the bright echoes from ships and aircraft, whilst filtering out the lower level reflections from the human body. Guns are not the only objects that could be concealed about a person that could give these bright reflections at a remote sensing site. Mobile phones, leather wallets, pens and portable music players could also give detectable signals. We aim to use features unique to a gun, such as gun barrels and other cavities to identify unique signatures in the reflected signals. For example, the gun barrel acts as a resonant cavity rather like air blown over a musical wind instrument, and we aim to detect these resonances remotely. During the second phase of the investigation, we will utilise a mix of the most effective bands in the electromagnetic spectrum, whether that be radio frequencies, microwaves or some other part of the spectrum, together with ultrasound, to develop a sensor that is effective at detecting guns remotely and is deployable by the police. It is possible that different guns will produce different responses from the sensor, but we will use pattern recognition techniques similar to those used in the automatic recognition of number plates or handwriting (i.e. neural networks ) to learn to recognise these particular responses. The research will be undertaken by a consortium of Universities, namely Manchester Metropolitan University, Manchester University, University of Huddersfield and Queen Mary London who will each investigate different aspects of the problem.