Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.746332
Title: Developing mathematical models of complex social processes : radicalisation and criminality development
Author: Pepys, R. C.
ISNI:       0000 0004 7231 1529
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2016
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Abstract:
The purpose of this thesis is to examine the use to which mathematical modelling techniques can be put in answering hard questions in social science. The specific area that this thesis focuses on is the development of an individual's propensity for crime or terrorism, with the primary research question answered being: are the process by which an individual develops the propensity to commit crime and the radicalisation process indistinguishable? The answer to this question may assist policy makers and practitioners in the fields of counter-terrorism and crime prevention develop more effective interventions, but it is a difficult question to answer using techniques rooted in social science alone, as crime and terrorism are the outcomes of complex social processes that form part of large socio-ecological systems. The thesis answers this question through the use of mathematical modelling. A model is developed based on the Individual Vulnerability, Exposure and Emergence (IVEE) theoretical framework for radicalisation. This model is realised as a computer simulation imitating the process by which an individual develops the propensity to commit an act of crime or terrorism, and is parameterised using data from secondary sources. The behaviour of the simulation is then explored to determine whether, with sufficient data, it could potentially be of practical use to practitioners: for example, the simulation is used to explore whether crime prevention interventions might also be effective for countering radicalisation, or vice versa. It is concluded that while the simulations developed in this thesis are still theoretical, the models themselves have the potential for further development, and the methodology could be applied to a range of alternative fields.
Supervisor: Bouhana, N. ; Bowles, R. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.746332  DOI: Not available
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