Nieto Tibaquira, Alberto;
(2023)
Studying Accomplice Selection and Criminal Specialisation
Through Networks.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
Understanding cooperation between offenders is essential for understanding criminality. It occurs across a broad range of criminal behaviours - it can be seen between a pair of shoplifters or in complex transnational criminal organisations - and can have significant implications for whether and how crimes are committed. Crime researchers have studied different aspects of co-offending - the term used to describe instances where multiple individuals collaborate to commit a crime - across a range of settings. In particular, some theories have been proposed to understand why people decide to co-offend and how they select their accomplices. Having a better understanding of how offenders go about selecting accomplices can support Law Enforcement Agencies (LEAs) in identifying ways to reduce crime by, for example, preventing motivated offenders from finding suitable partners. There have been limited attempts to refine or falsify existing theories by examining data on a large scale. This thesis endeavours to address this gap by adopting a network approach, whereby co-offending behaviours are examined through the analysis of connections between offenders. Employing a network approach can unveil concealed patterns and structures that may not be readily apparent when studying co-offenders or criminal events in isolation. This approach possesses the capability to capture intricate relationships, reveal obscured patterns, and employ network science concepts, rendering it a valuable instrument in advancing the understanding of criminal collaboration. In particular, it employs a range of analytical strategies to explore a number of aspects of the accomplice selection process. By examining networks modelling the interactions between offenders and criminal events, it investigates the extent to which offenders procure accomplices from their former associates. It also examines the evolution of co-offending networks (i.e., networks connecting co-offenders) to identify the underlying mechanisms that might explain how new co-offending relationships are created. Additionally, this thesis explores the criminal specialisation of adult co-offending groups, an issue that has not been fully addressed in the literature. The studies included in this thesis were completed using a unique dataset of information on adult offenders (N=274,689) linked to criminal investigations (N=286,591) in Bogotá, Colombia. The data provided by the Attorney General's Office (AGO) was not restricted to a specific set of offences; hence, it comprises all possible crime types that were investigated and prosecuted in this city between 2005 and 2018. The records contain details of arrestees, defendants on trial, and convicted defendants. While the use of arrest records and court files in co-offending studies is commonplace, it is infrequent to find both sources of information combined in one comprehensive data set. The results suggest that co-offending networks, like other social networks, exhibit some degree of triadic closure. Given the connections A-B (i.e., A co-offends with B) and A-C, it is likely to see a connection of the sort B-C. This finding suggests that associates might be crucial in procuring new accomplices for their former accomplices. Moreover, this thesis shows how the evolution of co-offending networks can be studied by integrating multiple mechanisms that describe how social networks grow. Specifically, it shows that popular offenders (i.e., those with numerous connections to other offenders) might not explain how co-offending networks evolve. It also shows that some offenders do not limit co-offending relationships to single events, as previous studies have shown. On the contrary, re-using accomplices was favoured over finding new partners (e.g., events of the sort A→B - or `A co-offends with B' - are followed by similar events A→B). The results also support the hypothesis that offenders change roles throughout their criminal careers. They go from followers to recruiters (or vice versa), allowing co-offending networks to grow by reciprocating co-offending relationships (e.g., events similar to A→B are followed by instances of the sort B→A). This thesis also shows that criminal specialisation is a characteristic observed among co-offending groups. Nearly half of those groups that re-offended exhibited traits of becoming specialists in particular types of crimes, such as those affecting private property. The thesis contributes to the literature on co-offending by examining the behaviours exhibited by co-offending networks, challenging findings from previous studies, and providing inputs for disrupting co-offending relationships. It also contributes to networked criminology - an emerging field that combines network science and crime-related theories - by showing how networks can be used to study accomplice selection and identify co-offending groups. Several methodological issues are also discussed in this thesis, including why co-offending studies need to use bipartite networks to gain a better understanding of criminal collaboration, the advantages of using null models for assessing the statistical significance of network statistics, and how co-offending network evolution can be analysed as the result of discrete choices made by co-offenders.
Type: | Thesis (Doctoral) |
---|---|
Qualification: | Ph.D |
Title: | Studying Accomplice Selection and Criminal Specialisation Through Networks |
Open access status: | An open access version is available from UCL Discovery |
Language: | English |
Additional information: | Copyright © The Author 2022. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10184561 |
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