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Copyright of Canadian Journal of Criminology & Criminal Justice is the property of University of Toronto Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Facilities that draw youth from different communities are prone to become offender convergence settings and intercity crime generators. Applying network analysis to self-nominated hangouts of 5,082 delinquent youth residing in Southern California revealed specific facilities acting as regional convergence settings. A small number of magnetic locations (measured by popularity and breadth of appeal) enable the congregation and interaction of youth that would otherwise not be exposed to each other. As predicted, the sociocirculatory structure of place networks remains relatively constant over time. In-degree and betweenness centrality statistics offer a viable analytic strategy to identify facilities operating as stable regional convergence locations. Crime prevention programs invoking effective place management through ordinances may offer a way to publicly govern these private facilities. [ABSTRACT FROM PUBLISHER]

Highlights: [•] The study applies social network analysis in the context of a Ponzi scheme. [•] It draws on diffusion theory to analyze the spread through a network of investors. [•] The fraudsters were successful in convincing multiple others to spread the fraud. [•] Interpersonal ties were key in maintaining the fraud over a period of five years. [Copyright &y& Elsevier]

Rather than examining networks of individuals as prior research has done, this study systematically examines the structure and composition of co-offending among types of criminal enterprise groups. Using social network analysis, the authors show that different types of crime groups tend to have unique co-offending patterns as measured by network composition and structure. The results also support the countercurrent of criminologists who suggest that ethnically derived categories may be misleading when trying to classify criminal enterprise groups. [ABSTRACT FROM AUTHOR]

This research examines the relationship between demographic, social network, and criminal history variables, and the distance between the home and locations of individuals (associates) involved in an illicit drug production network. The authors integrate principals from environmental criminology and routine activities theories, journey to crime research, and social network analysis in order to explore the geographic and social space of criminal associates. The results show that the distance between individuals in the drug production criminal network and their associates vary systematically with network characteristics (centrality measures) but not with demographics or criminal history variables.Security Journal (2008) 21, 77–94. doi:10.1057/palgrave.sj.8350069 [ABSTRACT FROM AUTHOR]

• 5% of a global sample reported adverse drug events in the last 12 months. • Recent cryptomarket use was associated with adverse events for cocaine and LSD. • Recent cryptomarket use was associated with a drug-using network size of zero. • Those with networks >1, characteristics did not differ by recent cryptomarket use. Drug use and trading are typically social activities; however, supply through cryptomarkets can occur without any in-person social contact. People who use drugs alone may be at higher risk of experiencing harms, for example, due to lack of others who may call for emergency assistance. Alternatively, cryptomarkets may be a source of harm reduction information and drugs with better-known content and dose, potentially reducing the risk of adverse events. This study examines relationships between cryptomarket use, drug-using social networks and adverse drug events for MDMA, cocaine and LSD. A subsample of 23,053 respondents from over 70 countries was collected in the 2018 Global Drug Survey. People who reported using MDMA, cocaine or LSD were asked about using cryptomarkets to purchase these drugs; any adverse drug events requiring medical treatment (combining seeking treatment and should have sought treatment but did not); and social networks who they had used the specific drug with. All measures referred to the last 12 months, hereon referred to as 'recent'. Binary logistic regressions examined relationships between cryptomarket use, drug-using social networks, and adverse drug events, controlling for age, gender, and frequency of drug use. Adverse events from any drug type were low (5.2%) and for each drug; MDMA (3.5%); cocaine (3.3%); and LSD (3.5%). After controlling for covariates, recent cryptomarket use was associated with increased likelihood of having no drug-using network for each drug type. People who recently used cryptomarkets were more likely to report adverse cocaine (AOR = 1.70 (1.22-2.37)) and LSD (AOR = 1.58 (1.12-2.09)) events. For those reporting a network size >1, network characteristics did not differ with recent cryptomarket use; however, those reporting recent cryptomarket use were more likely to report adverse LSD events (AOR = 1.86 (0.99-3.51)). People who reported purchasing drugs from cryptomarkets more commonly reported having no drug-using network, and cryptomarket purchase was associated with reported adverse events. Our results support the notion that cryptomarket use increases drug-related harm, but further disentanglement of multiple complex mechanisms is needed in future research. [ABSTRACT FROM AUTHOR]