Sally S. Simpson is a Distinguished University Professor (Emerita) of Criminology and Criminal Justice and Former 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 is Vice Chair of the NAS Committee on Law and Justice; past co-editor of the journal Regulation & Governance (2020-2023).  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
CV: vita August 2022.pdf619.42 KB

Degrees

  • Degree Type
    Ph.D
    Degree Details
    Sociology
  • Degree Type
    BS
    Degree Details
    Sociology
  • Degree Type
    MA
    Degree Details
    Sociology

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.

Corporate Crime

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 recently completed a project funded by the National Institute of Justice to study physician fraud.  We 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.

 

Current Students

Related Students (Listed by Student on Student's Profile)

  • Isabella Castillo
  • Alexandra Smith
Sally Simpson
2165C LeFrak Hall
Department of Criminology and Criminal Justice