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Premium Crime scene actions and offender characteristics in arsons
Häkkänen Helinä,
Puolakka Pia,
Santtila Pekka
Publication year2004
Publication title
legal and criminological psychology
Resource typeJournals
PublisherBlackwell Publishing Ltd
Purpose. Crime scene actions displayed by offenders in arsons were analysed in relation to offender characteristics and self‐reported motives. Methods. Data were drawn from an official police database and consisted of a random sample of arsons occurring in Finland between 1990 and 2001 ( N = 189). The structure of dichotomous variables derived through a content analysis of crime scene actions and offender characteristics was analysed using non‐metric multidimensional scaling (MDS) analyses. Results. The analyses revealed four separate crime scene action types, with thematic emphasis on either expressive or instrumental motivation and the target being either a person or object. The MDS solution for offender characteristics suggested four types of offenders: Self‐destructive, Serial, Criminal, and Adolescent. In order to analyse the associations between action and characteristics themes, each case was assigned to one of the action and characteristic themes or a hybrid based on the frequency of variables present from each theme. Several statistically significant associations between the action and characteristic themes were found. Self‐reported motives were also analysed in relation to the themes. Conclusions. The results support the thematic classification of arsonists presented in Canter and Fritzon (1998). The results are discussed with regard to earlier research and deducing offender characteristics based on crime scene actions.
Subject(s)action (physics) , artificial intelligence , chemistry , chromatography , computer science , crime prevention , crime scene , criminology , data mining , environmental health , mathematics , medicine , multidimensional scaling , object (grammar) , operating system , physics , poison control , psychology , qualitative research , quantum mechanics , relation (database) , sample (material) , social psychology , social science , sociology , statistics , thematic analysis , theme (computing)
SCImago Journal Rank0.65

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