TY - JOUR
T1 - Search for the Hidden Punishments
T2 - An Alternative Approach to Studying Alternative Sanctions
AU - Yan, Shi
N1 - Funding Information:
This project was supported by Award No. 2009-IJ-CX-0035, awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice. The opinions, findings, and conclusions or recommendations expressed in this publication are those of the author and do not necessarily reflect those of the Department of Justice. The author thanks Shawn Bushway, David McDowall, and Allison Redlich for their helpful guidance. The author also thanks David Weisburd, Sean Roche, Eric Fowler, and the three anonymous reviewers for their constructive comments. An earlier version of this manuscript was presented at the 2014 annual meeting of American Society of Criminology in San Francisco, CA.
Publisher Copyright:
© 2015, Springer Science+Business Media New York.
PY - 2017/3/1
Y1 - 2017/3/1
N2 - Objectives: Most existing studies of sentencing focus on the decision of whether or not to incarcerate a convicted individual. However, many cases do not involve incarceration, and there is a considerable amount of freedom to mete out alternative sanctions as part of a sentencing decision. This study addresses this gap in the literature by investigating the patterns of sentences among those individuals not sentenced to prison. Methods: This study used latent class analysis (LCA) to identify unobserved “classes” based on packages of sentences, which may involve both jail and non-incarceration alternative sanctions imposed on defendants not sentenced to prison. This study also demonstrates the potential use of LCA by (1) comparing and contrasting the results of LCA and the sentence severity scale approach, and (2) investigating how class membership could be explained by legal and extralegal characteristics of the cases. Results: LCA identified four latent classes among individuals who were not sentenced to prison, two of which could not be differentiated by the severity scale approach. Regression models demonstrated that legal variables were better at explaining the incarceration decision, whereas extralegal variables were better at explaining some of the margins between the classes. Conclusion: Compared with the incarceration models and severity scales, LCA revealed variations that could not be detected by either of the approaches. LCA also has the potential to be a helpful tool in future analysis of sentencing decisions utilizing large-scale, administrative datasets.
AB - Objectives: Most existing studies of sentencing focus on the decision of whether or not to incarcerate a convicted individual. However, many cases do not involve incarceration, and there is a considerable amount of freedom to mete out alternative sanctions as part of a sentencing decision. This study addresses this gap in the literature by investigating the patterns of sentences among those individuals not sentenced to prison. Methods: This study used latent class analysis (LCA) to identify unobserved “classes” based on packages of sentences, which may involve both jail and non-incarceration alternative sanctions imposed on defendants not sentenced to prison. This study also demonstrates the potential use of LCA by (1) comparing and contrasting the results of LCA and the sentence severity scale approach, and (2) investigating how class membership could be explained by legal and extralegal characteristics of the cases. Results: LCA identified four latent classes among individuals who were not sentenced to prison, two of which could not be differentiated by the severity scale approach. Regression models demonstrated that legal variables were better at explaining the incarceration decision, whereas extralegal variables were better at explaining some of the margins between the classes. Conclusion: Compared with the incarceration models and severity scales, LCA revealed variations that could not be detected by either of the approaches. LCA also has the potential to be a helpful tool in future analysis of sentencing decisions utilizing large-scale, administrative datasets.
KW - Alternative sanctions
KW - Discretion
KW - Latent class analysis
KW - Sentence severity scales
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U2 - 10.1007/s10940-015-9275-4
DO - 10.1007/s10940-015-9275-4
M3 - Article
AN - SCOPUS:84951811252
SN - 0748-4518
VL - 33
SP - 21
EP - 44
JO - Journal of Quantitative Criminology
JF - Journal of Quantitative Criminology
IS - 1
ER -