Can the offence behaviours of stranger rapists discriminate between UK and non-UK nationals

Published date11 February 2019
Date11 February 2019
AuthorLouise Almond,Michelle McManus,Gemma Curtis
Subject MatterHealth & social care,Criminology & forensic psychology,Aggression, conflict & peace,Sociology,Gender studies,Gender violence,Political sociology, policy & social change,Social conflicts,War/peace
Can the offence behaviours of stranger
rapists discriminate between UK and
non-UK nationals
Louise Almond, Michelle McManus and Gemma Curtis
Purpose Currently, no research is available for behavioura l investigative advisorsto provide
justifications to infer from the crime scene that an offender is a UK or non-UK national. The paper aims to
discuss these issues.
Design/methodology/approach Data were obtained from National Crime Agency and consisted of 651
stranger rapes, 434 UK nationals and 217 non-UK nationals. All cases were coded for 70 offence behaviour
variables. χ
analyses were conducted to identify significant associations between offence behaviours and
offender nationality. Significant associations were then entered into a logistic regression analysis to assess
their combined predictive ability of offender nationality.
Findings Analyses revealed 11 offence behaviours with significant associations to offender nationality:
confidence, darkness, offender kisses victim, victim performs sex acts, requests sex acts, apologises,
destroys forensics, block entry/exit, weapon firearm, vaginal penetration hands/fist/digital, and violence:
minimal. From this, seven variables held predictive ability within the logistic regression, with five predicting the
non-UK grouping and two the UK grouping.
Research limitations/implications Future research should test the distinctions between UK and non-UK
national stranger rapists and explore the impact of length of residency.
Practical implications Results indicated that on the wh ole UK and non-UK stranger rapis ts display
similar behaviours, bu t there were some distinct behaviours w ithin stranger rape crime scenes, parti cularly
the use of firearms. The ability to use crime scene behaviours to narrow suspect pools by criminal
conviction is only useful when police have access to full criminal histories. Unfortunately, the ability to
access and search non-UK databases is not always possible. Therefore, this study may be the first step for
BIAs to utilise in identi fying the likely offender nationality, be fore using further models that narrow down t o
criminal history.
Originality/value This is the first study to examine whether it is possible to differentiate stranger rapists
nationality using their offence behaviours.
Keywords UK, Rape, Nationality, Sexual offences, Offence behaviours, Offender profiling
Paper type Research paper
Due to the increasing prevalence of rape, the number of people it affects and the heterogeneity
of offenders, rape is widely researched in the forensic field. Since 2014, the reported number of
sexual offences has risen by 41 per cent (Office for National Statistics, 2015) with around
16 per cent of serious sexual assaults committed by a stranger in 2013/2014. Stranger rapes
are difficult to solv e due to a multitude of f actors, includin g: investigator s working under time
pressures, limited resources (Hakkanen et al., 2004), a lack of physical evidence to help
generate investi gative inferences a nd a reliance on victim ac counts (Corovic et al., 2012).
Forensic research has, therefore, increasingly focussed on generating inferences between
crime scene behaviours and characteristics of the offender to aid this difficult investigative
process (Mokros and Alison, 2002).
Received 27 April 2018
Revised 3 July 2018
Accepted 3 July 2018
Louise Almond is Senior
Lecturer at the University of
Liverpool, Liverpool, UK.
Michelle McManus is Senior
Lecturer at the University
of Central Lancashire,
Preston, UK.
Gemma Curtis is based at the
University of Liverpool,
Liverpool, UK.
DOI 10.1108/JACPR-04-2018-0357 VOL. 11 NO. 1 2019, pp.67-76, © Emerald Publishing Limited, ISSN 1759-6599
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