Analyzing Radicalization and Terrorism: A Situational Action Theory

Although the years since 9/11 have seen an significant increase in the contribution of criminologists to the study of terrorist events, efforts to apply major criminological theories to the understanding of the development of terrorist criminality and individual involvement in terrorist action have lagged. In this chapter, we apply a recently formulated theory of moral action and crime causation, Situational Action Theory, to the explanation of terrorism and radicalization. The case is made that explanations of terrorism and radicalisation should be mechanism-based and integrate all levels of analysis. Situational Action Theory is introduced and examples of its application to the study of terrorism and radicalization are provided. The priorities of a SAT-driven, systematic research agenda are outlined

Unpacking the relationships between impulsivity, neighborhood disadvantage, and adolescent violence : an application of a neighborhood-based group decomposition

The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007–2013)/ERC Grant Agreement no. 615159 (ERC Consolidator Grant DEPRIVEDHOODS, Socio-spatial inequality, deprived neighbourhoods, and neighbourhood effects); and from the Marie Curie programme under the European Union’s Seventh Framework Programme (FP/2007–2013)/Career Integration Grant no. PCIG10-GA-2011-303728 (CIG Grant NBHCHOICE, Neighbourhood choice, neighbourhood sorting, and neighbourhood effects).Scholars have become increasingly interested in how social environments condition the relationships between individual risk-factors and adolescent behavior. An appreciable portion of this literature is concerned with the relationship between impulsivity and delinquency across neighborhood settings. The present article builds upon this growing body of research by considering the more nuanced pathways through which neighborhood disadvantage shapes the development of impulsivity and provides a situational context for impulsive tendencies to manifest in violent and aggressive behaviors. Using a sample of 12,935 adolescent from the National Longitudinal Study of Adolescent to Adult Health (Add Health) (mean age = 15.3, 51% female; 20% Black, 17% Hispanic), we demonstrate the extent to which variation in the association between impulsivity and delinquency across neighborhoods can be attributed to (1) differences in mean-levels of impulsivity and violence and (2) differences in coefficients across neighborhoods. The results of a series of multivariate regression models indicate that impulsivity is positively associated with self-reported violence, and that this relationship is strongest among youth living in disadvantaged neighborhoods. The moderating effect of neighborhood disadvantage can be attributed primarily to the stronger effect of impulsivity on violence in these areas, while differences in average levels of violence and impulsivity account for a smaller, yet nontrivial portion of the observed relationship. These results indicate that the differential effect of impulsivity on violence can be attributed to both developmental processes that lead to the greater concentration of violent and impulsive adolescents in economically deprived neighborhoods as well as the greater likelihood of impulsive adolescents engaging in violence when they reside in economically disadvantaged communities.Publisher PDFPeer reviewe

Unveiling relationships between crime and property in England and Wales via density scale-adjusted metrics and network tools

Scale-adjusted metrics (SAMs) are a significant achievement of the urban scaling hypothesis. SAMs remove the inherent biases of per capita measures computed in the absence of isometric allometries. However, this approach is limited to urban areas, while a large portion of the world’s population still lives outside cities and rural areas dominate land use worldwide. Here, we extend the concept of SAMs to population density scale-adjusted metrics (DSAMs) to reveal relationships among different types of crime and property metrics. Our approach allows all human environments to be considered, avoids problems in the definition of urban areas, and accounts for the heterogeneity of population distributions within urban regions. By combining DSAMs, cross-correlation, and complex network analysis, we find that crime and property types have intricate and hierarchically organized relationships leading to some striking conclusions. Drugs and burglary had uncorrelated DSAMs and, to the extent property transaction values are indicators of affluence, twelve out of fourteen crime metrics showed no evidence of specifically targeting affluence. Burglary and robbery were the most connected in our network analysis and the modular structures suggest an alternative to "zero-tolerance" policies by unveiling the crime and/or property types most likely to affect each other

Beyond crime statistics: the construction and application of a criminogenity monitor in Amsterdam

Criminologists have devoted a great deal of attention to risk factors - also called criminogenic factors - leading to criminal offending. This paper presents a criminogenity monitor which includes 19 risk factors that underlie crime. These factors do not themselves cause criminal behaviour; rather, they must be seen as signals that crimes may be committed. After discussing how the criminogenity monitor was constructed, we apply the risk factors we examined to the situation in Amsterdam, capital city of the Netherlands. The monitor is intended to function particularly as an instrument to rationalise policy-makers' work in targeting and preventing symptoms of crime at three geographical levels: the entire city, its boroughs and its neighbourhoods. © 2012 The Author(s)