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Understanding the space-time patterns of the victim-offender crime overlap SSS5

  • School: School of Social Sciences
  • Study mode(s): Full-time / Part-time
  • Starting: 2022
  • Funding: UK student / EU student (non-UK) / International student (non-EU) / Fully-funded


NTU's Fully-funded PhD Studentship Scheme 2022

Project ID: SSS5

A small but growing body of evidence has identified that people who are victims (or targets) of crime, are also offenders for other crimes, and vice versa. This is known as the victim-offender overlap. A range of theoretical perspectives may support this – for example individual perspective such as routine activities and lifestyle theory, and neighbourhood-based theories such as social disorganisation and collective efficacy. However, studies to date have predominantly focussed on violence, and identified victim-offender overlaps as ratios or proportions of all offending and victimisation. However, we know little about the nature of this offending. Where and when do these offences and victimisations occur; how proximate are they in time and space; are the offender and victim previously known to each other; and to what extent does this overlap influence repeat offending and or repeat victimisation. Further questions include: do offenders and victims commit/experience similar crime types such as violence - or are these patterns evident over a wider set of crime offences such as volume crime including theft from person or even antisocial behaviour; and does the offender-victim overlap tend to occur close to people’s homes, or in similar activity spaces such as the night-time economy or transport interchanges - or is this dispersed across urban spaces. A key area for investigation is to examine the extent to which this ‘overlap’ influences crime hot spots.

You may work closely with local police forces (we have established links with several police forces including Nottinghamshire) to examine this using at least one local police force area. This analysis will also be supported using Ministry of Justice ADR UK (Administrative Data Research UK) Data First datasets to seek (a) to explore whether the local patterns identified are replicated on a national scale - to consider the wider applicability of the findings – and (b) to identify sentencing outcomes that may interrupt the victim-offender nexus. You should have skills in data science or geo-computation, and ideally experience in using GIS, R or Python. You should also have a strong background in quantitative methods and/or spatial-statistical analysis.

The successful PhD candidate will join the Quantitative and Spatial Criminology (QSC) research group at Nottingham Trent University. QSC research identifies the individual, household and area characteristics that shape crime victimisation. The research knowledge QSC has generated directly informs crime reduction policy and initiatives.

School strategic research priority

This aligns with the aims of the Quantitative and Spatial Criminology (QSC) group in the Centre for Crime and Offending Prevention and Engagement (COPE).

It also aligns with the University thematic priority – Safety and Security of Citizens and Society.

Entry qualifications

For the eligibility criteria, visit our studentship application page.

How to apply

For guidance and to make an application, please visit our studentship application page. The application deadline is Friday 14 January 2022.

Fees and funding

This is part of NTU's 2022 fully-funded PhD Studentship Scheme.

Guidance and support

Download our full applicant guidance notes for more information.

Still need help?

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