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NCJ Number: 78323 Add to Shopping cart Find in a Library
Title: Comparison of Sentencing Strategies Between States
Journal: Evaluation Review  Volume:5  Issue:3  Dated:(June 1981)  Pages:307-324
Author(s): S J Deutsch; C J Malmborg
Date Published: 1981
Page Count: 18
Sponsoring Agency: National Institute of Justice (NIJ)
Washington, DC 20531
US Dept of Justice NIJ Pub
Washington, DC 20531
Grant Number: 78-NI-AX-0003; 78-NI-AX-0040
Type: Report (Study/Research)
Format: Article
Language: English
Country: United States of America
Annotation: A dynamic descriptive model which is intended to assist public officials in setting sentencing policies is presented and applied to data from three States, with emphasis on applications to Missouri and Texas.
Abstract: The model provides a dynamic description of the crime rate in a given time period by using a multiplicative combination of three independently derived factors: the average rate at which individual offenders commit crime, the proportion of the criminal population which is free at any given time, and the proportion of the population choosing to engage in crime at a given time. The proportion who commit crimes is viewed as a function of the probability of imprisonment for a convicted offender and the average sentence length. The model can be used to determine the sentencing strategy which will have the greatest effectiveness in controlling crime. The model can also separate the incapacitative and deterrent effects of a sentencing policy. Application of the model to data from Missouri, Texas, and Georgia supports the hypothesis that career criminals tend to commit crimes in a nonseasonal fashion and that the seasonality in crime data results from the effects of marginal and transient elements within the total criminal population. Findings also forecast that crime rates will rise in the three States over the next two decades as a result of an increasing level of deviance within a fairly fixed criminal population size. The model also implies that Texas and Missouri should be able to partially offset the expected increase in crime through adjustment of imprisonment policy. Tables, an appendix discussing methodological background, and a list of 33 references are provided.
Index Term(s): Crime Rate; Deterrence effectiveness; Geographical sentencing variation; Mathematical modeling; Missouri; Models; Prediction; Texas; Time series
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