Substance or Semantics? The Consequences of Definitional Ambiguity for White-collar Research

Abstract

Objectives: To determine whether different conceptions (Populist, Patrician) and operationalizations of “white-collar crime” produce different substantive conclusions, using the applied case of sentencing in federal criminal court. Method: Federal Justice Statistics Program data are used to identify white-collar and comparable crimes referred for prosecution in 2009 to 2011 that were also sentenced through 2013. Five different operational strategies are used to identify “white-collar crime” and are employed in separate hurdle regressions jointly capturing incarceration and sentence length. Differences in model coefficients and case composition are discussed across definitions. Results: There are differences in the relationship between “white-collar crime” and incarceration both between and within Populist and Patrician conceptions. These differences are most pronounced at the in/out decision but are also present for sentence length. Conclusions: Contradictory findings from past research are largely able to be replicated within a single sample simply by changing the conception and operationalization of white-collar crime used. This demonstrates that debating what is “truly” white-collar crime is not just an exercise in semantics—it is a conceptual and methodological choice that can have dramatic consequences on what (we think) we know about the treatment of white-collar crime in the criminal justice system.

Perceptions of White-Collar Crime Seriousness: Unpacking and Translating Attitudes into Policy Preferences

“…Removing the scenarios involving data theft caused the coefficient for Black respondents to become significant at p < .05, one-tailed (consistent with our hypothesis). Altogether, this speaks to the challenges of using the label “white-collar crime” to refer to what are ultimately incredibly varied behaviors (Galvin, 2020; Rorie et al, 2017). However, it is also possible that, as with the label “white-collar crime,” the hypothesized relationship between race and perceived crime seriousness (and support for crime reduction policies) is overly simplistic.…”

Technology, White-Collar Cybercrime, and White-Collar Crime: An Analysis of Utah’s White-Collar Crime Registry Data

“…Despite these scholarly pursuits, research on the overlap between white-collar crime and cybercrime is notable for its absence. The failure to identify the connections between white-collar crime and cybercrime likely stems from different empirical foci of researchers, resistance to interdisciplinary pursuits, conceptual ambiguity regarding the way scholars define white-collar crime and cybercrime, ambiguity between the way that professionals and researchers define the concepts, the minimal attention given to systems theory in criminology and criminal justice, and jurisdictional issues governing the two types of crimes (Boden & Borrego, 2011; Cross, 2020; Galvin, 2020; Leahey & Barringer, 2020; Payne, 2016a, 2016; Payne et al, 2019; Walker, 2007). At the same time, the advancement in technology has made certain types of crimes – white-collar and cybercrime alike – easier to commit.…”

“…The subsequent categorization of occupational and corporate offending, offered by Clinard and his colleagues (Clinard et al, 2017) addressed concerns that the broader concept was too vague. Still, criminologists debate whether definitions of white-collar crime should focus on the offender or the offense (Galvin, 2020; Pontell, 2016; Shover & Cullen, 2008). Shover and Cullen (2008) distinguish between the populist approach (which focuses on the offender’s role and their power) and the patrician approach (which focuses on the offense).…”

Stacking punishment: The imposition of consecutive sentences in Pennsylvania

“…Probation tails are almost exclusively serviced by county probation agencies. Unlike the overwhelming share of federal supervised release, these individuals make up a small share of overall probation caseloads and may not receive dedicated reentry programming 4 204 Pa. Code §303.5 5 "Multiple counts of conviction" is occasionally included as binary control variable in the federal data (Johnson et al, 2008;Steffensmeier and Demuth, 2001) or, more rarely, the number of counts (Galvin, 2020;Kautt, 2002). However, many studies do not include any such control (e.g., Engen et al, 2003;Mustard, 2001).…”

“…55“Multiple counts of conviction” is occasionally included as binary control variable in the federal data (Johnson et al., 2008; Steffensmeier and Demuth, 2001) or, more rarely, the number of counts (Galvin, 2020; Kautt, 2002). However, many studies do not include any such control (e.g., Engen et al., 2003; Mustard, 2001).…”