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        Forensic Genetics in the Governance of Crime

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        Author(s)
        Machado, Helena
        Granja, Rafaela
        Collection
        European Research Council (ERC); EU collection
        Language
        English
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        Abstract
        This open access book uses a critical sociological perspective to explore contemporary ways of reformulating the governance of crime through genetics. Through the lens of scientific knowledge and genetic technology, Machado and Granja offer a unique perspective on current trends in crime governance. They explore the place and role of genetics in criminal justice systems, and show how classical and contemporary social theory can help address challenges posed by social processes and interactions generated by the uses, meanings, and expectations attributed to genetics in the governance of crime. Cutting-edge methods and research techniques are also integrated to address crucial aspects of this social reality. Finally, the authors examine new challenges emerging from recent paradigm shifts within forensic genetics, moving away from the construction of evidence as presented in court to the production of intelligence guiding criminal investigations.
        URI
        http://library.oapen.org/handle/20.500.12657/23264
        Keywords
        Social sciences; Technology—Sociological aspects; Criminology
        DOI
        10.1007/978-981-15-2429-5
        Publisher
        Springer Nature
        Publisher website
        https://www.springernature.com/gp/products/books
        Publication date and place
        Singapore, 2020
        Grantor
        • H2020 European Research Council
        Classification
        Sociology
        Crime and criminology
        Pages
        114
        Rights
        https://creativecommons.org/licenses/by/4.0
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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