Sally S. Simpson is a Distinguished University Professor of Criminology and Criminal Justice and Director of the Center for the Study of Business Ethics, Regulation, & Crime (C-BERC) at the University of Maryland, College Park. Her research interests include corporate crime, criminological theory, and the intersection between gender, race, class, and crime.
Simpson currently is co-editor for Regulation & Governance. In 2019-2020 she served as President of the American Society of Criminology. Honors include: 2018 Edwin H. Sutherland Award from the American Society of Criminology; ASC Fellow; Distinguished Scholar (ASC's Division on Women and Crime), Herbert Bloch Award (ASC), 2013 Gilbert Geis Lifetime Achievement Award (National White-Collar Crime Center and the National White-Collar Crime Research Consortium), and 2010 Woman of the Year by the President's Commission on Women's Issues at the University of Maryland.
Ongoing research examines medicare fraud prediction using behavioral big data and gender diversity, corporate leadership, and corporate crime.
Areas of Interest
- Corporate Crime, Gender and Crime, Measurement of White Collar Crime, Testing Criminological Theory
Degree TypePh.DDegree DetailsSociology
Degree TypeBSDegree DetailsSociology
Degree TypeMADegree DetailsSociology
Gender and Crime
With Co-Principal Investigators Julie Horney (Penn State University), Rosemary Gartner (University of Toronto), and Candace Kruttschnitt (University of Toronto), our team collected 3 years of quantitative and qualitative data from more than 800 incarcerated women in Baltimore, Toronto, and Minneapolis. This project (Women’s Experience of Violence or WEV) examines individual, situational, and community factors that are associated with violent offending and victimization. In addition, for Baltimore and Minneapolis respondents, neighborhood census data are linked to individual addresses. In addition, I have examined gender/race differences in violent crime participation; the impact of changes in arrest policies (Maryland) on intimate partner violence and victim perceptions of procedural justice on victim willingness to report future intimate partner victimizations. I typically adopt an intersectional or "doing gender" approach in my work.
My long-standing interest in corporate crime can be divided into three main themes: (1) under what conditions are companies more or less likely to violate the law; (2) manager decision-making; and (3) crime prevention and control strategies including formal legal sanctions (administrative, civil, and criminal), corporate governance and self-regulatory mechanisms. I've recently completed several funded projects including: (1) the public's willingness to pay for white-collar crime control (with Tom Loughran and Mark Cohen); (2) a report to BJS regarding the feasibility of building a comprehensive white-collar violations data system (with Peter C. Yeager; and (3) the independent and reciprocal relationships between diversity (gender, racial/ethic) in corporate governance, structural board characteristics, top management team diversity, corporate offending, and legal responses to offending (with Debra Shapiro, Christine Beckman, and Gerald Martin). These projects rely on large archival data sets, systematic review, general population surveys, vignette surveys, or information/data from regulatory agencies. I draw from rational choice/deterrence, informal social control, life-course/organizational life cycle theory, and strain theory to inform the work.
In the broader white-collar crime area, Ritu Agarwal and Gordon Gao from the CHIDS Research Center in the Smith School of Business and I received a 2019 grant from the National Institute of Justice to study physician fraud. We have created a database using behavioral big data to identify physicians likely to engage in medicare fraud (big data including information such as illegal behavior, patient complaints and malpractice, disciplinary actions, conspicuous consumption, and life stressors). Data sources include federal databases on fraud, as well as state and local court records, state medical records, and online review web sites. The project uses a retrospective matched design that includes a sample of physicians assigned to one of two groups: those who have and have not been excluded from participation in federal health care programs, such as Medicare, due to fraud, from 2015-2019.