Gender and White Collar Crime – Implications for Corrections Research and Practice

The last couple of decades have seen a considerable increase in the number of studies that have examined the risk/need factors of individuals under correctional supervision and the validity of risk assessments that stemmed from RNR model. Empirical research has examined these factors with population...

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Bibliographic Details
Main Author: Ndrecka, Mirlinda (Author)
Format: Electronic Article
Language:English
Published: 2020
In: Criminal justice studies
Year: 2020, Volume: 33, Issue: 1, Pages: 70-78
Online Access: Volltext (lizenzpflichtig)
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Summary:The last couple of decades have seen a considerable increase in the number of studies that have examined the risk/need factors of individuals under correctional supervision and the validity of risk assessments that stemmed from RNR model. Empirical research has examined these factors with populations of different gender, ethnicity, and offense type. However, few articles to date have studied the risk/need factors of individuals that are under correctional supervision for engaging in white-collar crime. The current article discusses the empirical findings of the Benson & Harbinson (current issue), Goulette (current issue), and Ruhland & Selzer (current issue), three articles that have explored the risk/need factors of individuals involved in white-collar offenses, and gender differences in these same populations. Findings from the articles point out that individuals involved in white-collar crime display lower average risk scores than individuals engaging in common offenses. While the risk/need factors among white-collar and general offense populations appear similar, results show that individuals engaging in white-collar crime could exhibit risk/needs differently from general crime populations. Additionally, the findings from the current three articles do not seem to offer support for the gendered pathways to crime approach. The current article discusses how these empirical findings related to the RNR model of correctional supervision and offers directions for future research.
ISSN:1478-6028
DOI:10.1080/1478601X.2020.1709955