Evolving Optimum Classification Policies in the Implementation of Truth-in-Sentencing: A Dynamic Model to Predict Bed-Type Mix, Final Report

• NCJ Number: 197353
• Author(s): Lorraine T. Fowler; Meesim C. Lee; Deanne R. Williams; Shawn M. Larrymore; Lisa S. Woodard; Deborah J. Castaldi; Farhat L. Ayers; Hector H. Guerrero; David Murray
• Date Published: May 2000
• Length: 105 pages
• Grant Number(s): 98-CE-VX-0025
• Sponsoring Agency: National Institute of Justice (NIJ)
• Corporate Author: South Carolina Dept of Corrections
• Sale Source: South Carolina Dept of Corrections; NCJRS Photocopy Services
• Publication Format: Document
• Publication Type: Report (Technical Assistance)
• Language: English
• Country: United States of America
• Note: Dataset may be archived by the NIJ Data Resources Program at the National Archive of Criminal Justice Data. Glossary of terms added to original report after acceptance. Page numbering of glossary is not consistent with original document.

Annotation

This final report details the results of preparing a software package to enable prison administrators to integrate inmate classification with bed type space and demand.

Abstract

This article seeks to integrate truth-in-sentencing, sentencing guidelines, and prison classification systems into a unified system that can appropriately predict and control for bed space mix among inmates. When entering a correctional institution, the authors explain that inmates are classified, and based upon this classification, are assigned a type of bed that corresponds to their classification. Classifications involve the level and type of security required by the inmate. In order to facilitate an integrated system for classifying inmates, the researchers created a software tool that enables prison administrators to integrate inmate classifications with bed space demand. This software allows prison administrators to develop cost efficient and cost effective classification systems. In order to develop this software, the authors studied various dynamic factors affecting the level and type of security bed space needed by the prison system. The researchers focused on analyzing the dynamics of classification, sentencing structure, and inmate behavior. Their mission was to incorporate all these factors into a software package that would aid administrators in their system of classification and bed assignment. The researchers analyzed the South Carolina inmate data and found that institutional behavior among truth-in-sentencing inmates was worse than that for non-truth-in-sentencing inmates who committed similar crimes and were admitted during the same period. The authors explain that the research was not conducted to recommend classification policy changes, but rather to provide a suitable tool for assessing the impact of classifications on bed type demand. Bibliography, appendix, figures