The feasibility of using crime scene behaviour to detect versatile serial offenders: an empirical test of behavioural consistency, distinctiveness, and discrimination accuracy
Purpose. To test whether geographical, temporal, and modus operandi (MO) crime scene behaviours can be used to support behavioural case linkage (BCL) with crime series that contain several different types of offence. Methods. Crime scene data relating to 749 solved commercial burglaries and robberie...
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| Format: | Electronic Article |
| Language: | English |
| Published: |
2017
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| In: |
Legal and criminological psychology
Year: 2017, Volume: 22, Issue: 1, Pages: 99-115 |
| Online Access: |
Presumably Free Access Volltext (lizenzpflichtig) Volltext (lizenzpflichtig) |
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MARC
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| 100 | 1 | |a Tonkin, Matthew |e VerfasserIn |4 aut | |
| 245 | 1 | 4 | |a The feasibility of using crime scene behaviour to detect versatile serial offenders |b an empirical test of behavioural consistency, distinctiveness, and discrimination accuracy |c Matthew Tonkin and Jessica Woodhams |
| 264 | 1 | |c 2017 | |
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| 520 | |a Purpose. To test whether geographical, temporal, and modus operandi (MO) crime scene behaviours can be used to support behavioural case linkage (BCL) with crime series that contain several different types of offence. Methods. Crime scene data relating to 749 solved commercial burglaries and robberies were extracted from the databases of the Metropolitan Police Service, London, England. From these data, 2,231 linked crime pairs (containing two crimes committed by the same offender) and 273,422 unlinked crime pairs were created (two crimes committed by different offenders). Three measures of similarity were calculated for each crime pair: (1) the kilometre distance between crimes (intercrime distance [ICD]); (2) the number of days between crimes (temporal proximity [TP]); and (3) a statistical measure of similarity in MO behaviour (Jaccard's coefficient). Statistical tests of difference, binary leave-one-out logistic regression, and receiver operating characteristic analysis were used to determine whether the three measures of similarity could be used to distinguish between linked and unlinked crime pairs, some containing only burglaries (burglary pairs), some containing only robberies (robbery pairs), and some containing both burglaries and robberies (cross-crime pairs). Results. Linked and unlinked crime pairs could be distinguished with a high level of accuracy (AUCs > .90), with the highest accuracy when combining ICD, TP, and Jaccard's coefficient. These findings were replicated with the burglary pairs, robbery pairs, and cross-crime pairs. Conclusions. Offender behaviour is sufficiently consistent and distinctive to support the use of BCL with versatile crime series, as well as with burglary crime series and robbery crime series. | ||
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