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Recent Scientific Accomplishments McGloin’s research focuses on three primary areas: criminological theory; groups and crime (e.g., street gangs, co-offender networks, delinquent peer groups); and, policing. For example, in her 2004 paper with Travis Pratt and Jeffery Maahs in Justice Quarterly, “Rethinking the IQ-delinquency Relationship: A Longitudinal Analysis of Multiple Theoretical Models,?she investigates which theoretical mechanisms explain the relationship between IQ and delinquency/crime. The findings suggested that scholars should consider ways of integrating control and learning perspectives. Other work that has appeared in the Journal of Research in Crime and Delinquency and the International Journal of Offender Therapy and Comparative Criminology has also underscored the need for theoretical integration in criminology. With regard to her work on groups and crime, she has published on the social organization of street gangs in Newark, New Jersey, as well as gang-related homicide, in such journals as Criminology and Public Policy and the Journal of Criminal Justice. These publications are largely based on her data collection, as part of her dissertation work while at Rutgers-Newark. McGloin is currently the principal investigator (P.I.) on a grant from the State Attorney’s Office of Prince George’s County. This grant supports a process evaluation of the Prince George's County Gang Reduction Pilot Project. Funding for previous work has come from the Police Institute at Rutgers University and the United States Department of State, Bureau of Educational and Cultural Affairs. During the next few years, McGloin’s research will focus heavily on groups and anti-social behavior. She is studying the impact of delinquent peer networks on delinquency, in the context of criminological theory, using the AddHealth dataset. Her ongoing work attempts to disentangle the causal effects of peer group influence from the selection effects, that is, delinquent peer groups merely reflect the underlying delinquency of their members. McGloin exploits the fact that AddHealth collects data both on network characteristics and individual self-control. For example, the average level of anti-social behavior in a peer network (e.g. smoking cigarettes, getting drunk, skipping school) and classic network measures such as centrality and density are available in AddHealth. In addition, self-control indicators such as short-sightedness and impulsivity are measured independently in Wave I of AddHealth. Preliminary results suggest that peer group affect remain strong even after controlling for multiple measures of individual self-control. | ||||||||
Maryland Population Research Center
0124N Cole Student Activities Building (#162)
College Park, MD 20742
Phone: 301-405-6403
Fax: 301-405-5743