The importance of co-convictions in the prediction of dangerous recidivism:blackmail and kidnapping as a demonstration study

Co-convictions are court convictions made at the same time as a more serious conviction. Their importance has been little recognized. We investigate their value using data on two separate serious crimes. Taking official conviction careers in England and Wales (1979-2001) for blackmail (n = 5774) and kidnapping offenders (n = 7291), we considered how much information on co-convictions is normally overlooked, and how knowledge of co-convictions contributes to predicting serious recidivism. We identified that co-convictions were pervasive, with 54 per cent of convictions for blackmail and 77 per cent for kidnapping having co-convictions. Co-convictions provided extra explanatory power in predicting the risk of a subsequent sexual or violent offence for both blackmail and kidnapping. For blackmail, most types of co-conviction were associated with a significantly raised relative risk, whereas for kidnapping, only co-convictions which were not acquisitive, sexual or violent had a significantly raised relative risk. We concluded that co-convictions are a useful measure of short-term specialization and are important when predicting serious recidivism

Criminal Lifestyle Specialization:Female Offending in England and Wales

In criminal careers research, specialization has usually been defined through prespecifying spheres of criminal activity (violent/nonviolent or sexual, violent, burglary, theft, etc.) and then determining the amounts of criminal activity lying within these spheres over a certain time period. However, there is increasing recognition that some offenders work in well-defined domains of offending, which cut across these groups. Thus, some offenders might be involved in both burglary and theft, but unwilling to engage in violent activity, whereas others might also be involved in violence. The authors propose an alternative approach to specialization using latent transition analysis. This approach seeks to identify such domains of activity, which would represent criminal lifestyles. Offenders staying within a domain over time can be defined as lifestyle specialized; those moving between domains are lifestyle versatile. The criminal lifestyles themselves can represent different degrees of diversity. The concept is assessed on England and Wales birth cohort data on female court convictions and comparisons are made with traditional measures of specialization. The authors identify that some females engage in one criminal lifestyle and move to non-offending, others will progress to more diverse lifestyles as they age. Late starters will also tend to engage in diverse patterns of offending

The importance of centralities in dark network value chains

This paper introduces three novel centrality measures based on the nodes’ role in the operation of a joint task, i.e., their position in a criminal network value chain. For this, we consider networks where nodes have attributes describing their "capabilities" or "colors", i.e., the possible roles they may play in a value chain. A value chain here is understood as a series of tasks to be performed in a specific order, each requiring a specific capability. The first centrality notion measures how many value chain instances a given node participates in. The other two assess the costs of replacing a node in the value chain in case the given node is no longer available to perform the task. The first of them considers the direct distance (shortest path length) between the node in question and its nearest replacement, while the second evaluates the actual replacement process, assuming that preceding and following nodes in the network should each be able to find and contact the replacement. In this report, we demonstrate the properties of the new centrality measures using a few toy examples and compare them to classic centralities, such as betweenness, closeness and degree centrality. We also apply the new measures to randomly colored empirical networks. We find that the newly introduced centralities differ sufficiently from the classic measures, pointing towards different aspects of the network. Our results also pinpoint the difference between having a replacement node in the network and being able to find one. This is the reason why "introduction distance" often has a noticeable correlation with betweenness. Our studies show that projecting value chains over networks may significantly alter the nodes’ perceived importance. These insights might have important implications for the way law enforcement or intelligence agencies look at the effectiveness of dark network disruption strategies over time