Department of Criminology and Criminal Justice
Jean McGloin is currently an Associate Professor of Criminology and Criminal Justice at the University of Maryland. She received her Ph.D. in Criminal Justice from Rutgers University in 2004, where her dissertation focused on street gangs in Newark, New Jersey. Dr. McGloin's research interests include peer influence, co-offending, and offending specialization.
- Co-offending, peer influence, offending specialization
Jean McGloin’s primary research focus is on groups and crime, which is reflected in several research programs. First, she has an ongoing research program focused on peer influence processes. This program has focused on developing new theoretical explanations of peer influence, the role of peer network structure in shaping delinquency, and the extent to which individual characteristics (e.g., immigrant status, gender) condition peer influence. She is currently working on papers addressing the extent to which the larger social context of schoolmates' delinquency affects the strength of the peer group's influence on delinquency. This research program typically uses the AddHealth data to investigate these questions, which provides ample information on adolescents' social networks, though not exclusively.
Second, she conducts research on co-offending, including why offenders decide to commit crime with accomplices, under what conditions they will instigate group crime rather than follow others, and how co-offending networks can shape and influence the criminal career. As part of this stream of research, she is currently working on a project that involves data collection from prisoners, focusing on the perceived benefits and risks of co-offending and particular criminal accomplices.
Finally, she is working on a research project with her colleague Kiminori Nakamura that focuses on social networks and the re-entry process among parolees. This project is collecting information on social networks, which include both criminal and prosocial connections. They are interested in the extent to which social networks at different stages of life help to explain and predict recidivism.