間眅埶AV

Research

Research Highlight with Dr. Martin Bouchard

January 29, 2015

Associate professor Martin Bouchard joins us to discuss the release of Advances on Illicit Networks (Routledge, 2015). Edited by Bouchard, the book is a compilation of research employing social network concepts and methods to investigate questions of criminological interest.

What key questions or ideas do you explore in the book?

It is a collective book with each author using social network concepts and methods to examine a criminological question of interest.

All chapters present original empirical studies, often in under-studied areas, like amphetamine production, illicit arms and steroid distribution and trafficking, or the division of labor within terrorist organizations. It also sheds a new light on older questions in the field like recidivism and co-offending, but taking full advantage of the most recent developments in network theories and methods.

Why do you find this topic compelling?

Social network data has had such a great impact in criminology and in other fields because it explicitly recognizes and exploits the power of something we intuitively expect to be influential in human decision-making, including criminal decision-making: our social environment.

Social network analysis provides a framework to systematically analyze the social environment of offenders or would-be offenders, but also of the agents of social control tasked with managing these populations.

The network approach is commonsensical, flexible, powerful. It combines theoretical assumptions and empirical demonstration; it is neither qualitative nor quantitative it`s both.

What are the implications of some of the research findings presented in the book?

Variations in network structures play a direct role in the ability of law enforcement agencies to detect offenders, and disrupt their activities. A network approach may make the police more efficient by reducing errors or the number of moves required to make an impact on an illegal activity.

Networks change over time, as we would expect, but the most variability occurs in the specific network participants occupying roles in the network not in the network structure per se. For control agencies having to intervene on these networks, this requires a shift in thinking about existing cultures and structures, as opposed to specific individuals and their activities at one point in time. A paper drawing from a network built from licit and illicit flow data between countries found that market infrastructure, more than traditional weapon availability indicators, act as the driving force behind changes in small arms trade relations among countries.

An important empirical implication, here and in many other chapters, is the suitability of a network approach to addressing the overlap between the legitimate and the illegal. A key strength of the network approach is to focus on ties and connections without a priori assumptions on how these should be arranged.

How do you plan to further develop this research?

Years ago I made network theory and social network analysis the main lenses through which I analyze crime. My research brings me to study activities as diverse as terrorism, online child pornography, drug trafficking, as well as illegal entities we refer to as street gangs or criminal organizations.

Social network analyses are still very much descriptive - there is a lot of work to be done to examine these phenomena using proper criminological theories, and longitudinal data. This is where I am now, and where I go next.

Any suggestions for further reading?

Some of the best work in this area is being done by Canadians.

Carlo Morsellis Inside Criminal Networks (2009) is a great introduction to this topic. Gisela Bichler and Aili Malm are editing the most recent volume of Crime Prevention Studies (2015) on the issue of disrupting illicit networks. John Scott and Peter Carringtons Sage Handbook of Social Network Analysis (2011) is also a good start, especially for readers interested in more than the criminological aspects of social networks.

Facebook
Twitter
LinkedIn
Reddit
SMS
Email
Copy