Journal of Contemporary Criminal Justice

This introduction to the JCCJ special issue on illicit networks seeks to accomplish three objectives. First, we offer a brief explanation of the network paradigm and its importance to criminology; our purpose is to convince readers of the utility of social network analysis (SNA). Second, we summarize the benefits of working groups with the aim of providing readers with the context from which they can understand why these informal collectives are critical to the advancement of science. And finally, the remainder of the article introduces the research assembled for this special issue.

On-officer videos, or body cameras, can provide objective accounts of interactions among police officers and the public. Police leadership tends to view this emerging technology as an avenue for resolving citizen complaints and prosecuting offenses where victims and witnesses are reluctant to testify. However, getting endorsement from patrol officers is difficult. These incongruent cognitive frames are a cultural barrier to the utilization of innovative technologies. Understanding the mechanisms that lead to the deconstruction of these barriers is essential for the integration of technology into organizations. Using affiliation data collected from a large police department in Southwestern United States over a 4-month period, we find that interactions with other officers provide a conduit for facilitating cognitive frames that increase camera legitimacy.

Social network analysis (SNA) conducted on criminal networks can identify key players and shed light on important patterns of connectivity. This information can be used to develop interventions to dismantle or disrupt criminal networks. Drawing upon the network capital construct, this study demonstrates that integrating centrality measures (such as degree or betweenness centrality) with other individual attributes related to functional roles and access to tangible and intangible resources will enhance efforts to identify critical actors. Using a drug trafficking network that operated in Australia in the 1990s, we identify actors who are key to the network by virtue of their position in the network, their attributes, and combinations of these factors. Implications for law enforcement practice are discussed.

Focusing on business leaders in control of Fortune 500 companies, this study examines corporate interlock among CEOs with security exchange commission (SEC) violations and CEOs without. Using affiliation networks built from publicly available information, we analyzed rates of participation (outdegree centrality), organizational influence (indegree centrality), and brokerage (betweenness centrality). The findings suggest that a single, integrated network exists. However, within these interlocking directorates, subsets of executives exhibit substantial cohesion suggesting the presence of distinct social circles. Only a few organizations and individuals were found to link the subset of offending CEOs to their law-abiding counterparts. Moreover, SEC violators were more socially isolated, thereby increasing the influence of weak ties to active executives playing a controlling role within the network.

Illicit markets capitalize on the vulnerabilities of trade systems. When these weaknesses involve mechanisms common to several aspects of transnational commerce, the effect of illicit behavior, and conversely of anti-crime policy, can be magnified. This study introduces a script-network method to estimate the impact of targeting illicit behavior within the context of an entire market system. Using the high-value art and antiquities market as a case study, we anticipate the effects of two anti-crime policy directives—movement control and monitoring financial transactions. In addition to advancing a new method, two original metrics are presented—one measures the complexity of sectors in a trade system (complexity) and the other anticipates the incentive to work around crime control efforts (transformity). In consideration of these system characteristics, our results suggest that maximum decoupling of illicit\legal trade is more likely with the introduction of safeguards targeting central trade functions that are associated with valuing and gifting objects. Network-oriented research could help the prevailing market reduction approach (MRA) to be more effective in reducing transnational illicit trade because network analytics are specially crafted for dealing with the statistical challenges that are inherent to studying transnational illicit market systems.

Little is known about homicide co-offending networks at the individual gang member level. Of particular interest is whether and to what degree gang members who are selected to participate in murder are different from those who are not. The current study constructed the co-offense network of 18 participants from the Incarcerated Serious and Violent Young Offender Study who were identified as members of a prominent gang within British Columbia, Canada, referred to as the BC Gang. This gang started to form not long before seven offenders together committed a homicide that was orchestrated by the founder and leader of the BC Gang. After this offense, some of these seven offenders became the most central actors within a large network of co-offenders (n = 137) that was measured at four time periods over a 20-year period. Over this period, a second murder, like the first, was orchestrated by the leader of the BC Gang, offering a rare glimpse into the co-offending recruitment decisions made by a high ranking gang member for two separate homicides. Although only 25% of the 137 co-offenders are BC gang members (n = 35), 100% of the offenders selected for a homicide were members of this gang (n = 13). The network contained 8 separate components at the final measurement period, but all 13 homicide offenders were connected to the same network component of 48 individuals.

This article examines age homophily among co-offenders, using data on approximately 440,000 co-offenses recorded by police in Canada during 2006 to 2009. Log-linear models for social mobility tables are applied to an 86-by-86 table of frequencies of co-offending among year-of-age groups for individuals from 3 to 88 years old. The results indicate strong age homophily for co-offenders of all ages, but decreasing with age. There is further structuration into four age groups: children (3-11 years), youth (12-17 years), young adults (18-45 years), and older adults (46-88 years). The “Fagin” hypothesis that offenders below the age of criminal responsibility are particularly attractive as co-offenders for older offenders is disconfirmed.

Previous studies indicate the importance of similarities between street gang members in terms of ethnicity for mapping the patterns of co-offending relationships within gangs. Individual members are more likely to co-offend with other members who are from the same ethnicity. Past studies, however, do not appropriately account for the fact that correlation between attributes of co-offending gang members may be driven by alternative mechanisms. Most importantly, the presence of clustering in networks can dramatically affect the assessment and make us believe that homophily—the deliberate choice to co-offend with others from the same ethnic group—is important while in fact it is not. In this article, we recreate the internal structure of a London-based street gang with exponential random graph (ERG) models. Our results refine the role of ethnicity for co-offending within gangs. While homophily is still prevalent, the effect diminishes when triad closure—the tendency for two individuals to offend with each other when they also offend with a common third person—is considered. Furthermore, we extend existing ERG specifications and investigate the interaction between ethnic homophily and triad closure. Findings indicate that ethnic homophily is even stronger when it is embedded in co-offending triads.