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NCJ Number: 99708 Find in a Library
Title: Model-Based US Prison Population Projections
Author(s): A I Barnett; T F Rich
Corporate Author: Public Systems Evaluation, Inc
United States of America
Date Published: 1985
Page Count: 32
Sponsoring Agency: Public Systems Evaluation, Inc
Cambridge, MA 02139
Format: Document
Language: English
Country: United States of America
Annotation: This paper explains the modeling techniques used to produce the conclusion that overcrowding in State prisons is not a short-term problem.
Abstract: The doubling of the prison population between 1974 and 1984 led to concern about the need for long-range forecasting and for planning to avoid temporary solutions that might quickly become outmoded. Under a grant from the National Institute of Justice, this study used a computer-based mathematical model to project male prison populations for eight States: Arizona, California, Florida, Illinois, Massachusetts, North Carolina, Pennsylvania, and Utah. The forecasts went through the year 2020. The model used Census Bureau projections, data from the eight States on their current imprisonment policies, and existing criminological theory on the behavior of individual offenders. Concepts of probability from operations research also formed the basis for part of the analysis. Forecasts were made assuming either the maintenance of the status quo in terms of sentencing policy or four possible policy changes. The model showed that prison populations might stop growing by the end of this decade (1989). This would represent a temporary deviation from an upward trend rather than a meaningful trend in itself. However, individual States may show substantial variations from the overall pattern. The growth in prison populations is likely regardless of whether sentencing policies are changed, although increases in average prison terms will place substantial pressures on prison populations. Figures, notes, and a discussion of limitations of forecasts are included.
Index Term(s): Future trends; Mathematical modeling; Prison population prediction; Sentencing reform
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