RATE

When studying crime, if a researcher wishes to compare the amount of crime over time or between communities of different sizes, it is not adequate to do a gross count of the amount of crime because the population bases may be different.

To get around the problems involved with this, criminologists calculate crime rates (or incarceration rates, conviction rates, recidivism rates). This is done by dividing the amount of crime by the population size and multiplying by 100,000. This produces a rate per 100,000, but occasionally it is useful to calculate a rate per million or some other figure.

Rate is synonym of rhythm or frequency, such as heart rate or sample rate. In statistics, a unit rate is a rate that is simplified so that it has a denominator of 1. 

The Effect of State Sentencing Policies on Incarceration Rates - Jon Sorensen, Don Stemen, State Sentencing and Corrections Program, Vera Institute of Justice

This article explores the relationship between sentencing policies and the state incarceration rate, prison admission rate, and average sentence length in the late 1990s. Presumptive sentencing guidelines represent the only policy consistently related to incarceration and admission rates, whereas three strikes laws may increase the rate of admission to prison among those arrested for drug offenses. Determinate sentencing, mandatory sentencing, and truth-in-sentencing laws have no effect on rates of incarceration or admission. Crime rates, the percentage of the population that is Black, and citizen ideology have the greatest influence on the rates of incarceration and admission across states. The apparently limited effects of sentencing policies on incarceration or admission rates should give pause to state policy makers seeking to quickly alter prison populations through the adoption of such policies without considering other factors that independently influence prison populations in their states. - Crime & Delinquency, Vol. 48, No. 3, 456-475 (2002)

Variation in Incarceration Rates Across the Fifty States, Pritchard, Anita - Paper examines variation in incarceration rates across the fifty states. As expected, states' crime rates and the ideological identification of their leaders and citizens have the greatest effect upon incarceration rates

Why are Immigrants' Incarceration Rates so Low? Evidence on Selective Immigration, Deterrence, and Deportation - Kristin F. Butcher, Federal Reserve Bank of Chicago
Anne Morrison Piehl, Rutgers University - National Bureau of Economic Research (NBER)
Abstract: Much of the concern about immigration adversely affecting crime derives from the fact that immigrants tend to have characteristics in common with native born populations that are disproportionately incarcerated. This perception of a link between immigration and crime led to legislation in the 1990s increasing punishments toward criminal aliens. Despite the widespread perception of a link between immigration and crime, immigrants have much lower institutionalization (incarceration) rates than the native born. More recently arrived immigrants have the lowest comparative incarceration rates, and this difference increased from 1980 to 2000.
We present a model of immigrant self-selection that suggests why, despite poor labor market outcomes, immigrants may have better incarceration outcomes than the native-born. We examine whether the improvement in immigrants' relative incarceration rates over the last three decades is linked to increased deportation, immigrant self-selection, or deterrence. Our evidence suggests that deportation and deterrence of immigrants' crime commission from the threat of deportation are not driving the results. Rather, immigrants appear to be self-selected to have low criminal propensities and this has increased over time.

Patterns and Predictors of County-Level Incarceration Rates Over Time - Schupp, Paul. and Rivera, Craig - Annual meeting of the AMERICAN SOCIETY OF CRIMINOLOGY.
Abstract: This research relies on the semi-parametric group-based method of modeling developmental trajectories, developed by Nagin and colleagues (e.g., Nagin, 1999), to model trajectories of incarceration rates for New York counties in recent decades. Most previous research has relied on state- and federal-level data to map imprisonment rates over time (e.g., the imprisonment rate in the U.S. has increased dramatically for the past thirty years), but this makes the assumption that there is one underlying pattern of growth determining this trend. The current analysis will examine that assumption at the county level by identifying distinct groups of counties that display within-group homogeneity of incarceration patterns of over time, and by modeling a separate trajectory for each group. Despite the fact that the overall trend in New York is one of increasing incarceration rates, this method will allow us to identify whether or not there are actually a variety of patterns displayed across counties. For example, some counties may actually be decreasing or staying the same over time, while others are increasing. The current study will also examine political, economic, and demographic predictors of the different patterns of incarceration that are identified.

Convictions Versus Conviction Rates: The Prosecutor's Choice
J. Mark Ramseyer, Harvard Law School, Eric Bennett Rasmusen, Indiana University Bloomington
Manu Raghav, Washington and Lee University; Indiana University Bloomington
Harvard Law and Economics Discussion Paper No. 611
Abstract: It is natural to suppose that a prosecutor's conviction rate - the ratio of convictions to cases prosecuted - is a sign of his competence. Prosecutors, however, choose which cases to prosecute. If they prosecute only the strongest cases, they will have high conviction rates. Any system which pays attention to conviction rates, as opposed to the number of convictions, is liable to abuse. As a prosecutor's budget increases, he allocates it between prosecuting more cases and putting more effort into existing cases. Either can be socially desirable, depending on particular circumstances. We model the tradeoffs theoretically in two models, one of a benevolent social planner and one of a prosecutor rewarded directly for his conviction rate as well as caring about convictions and personal goals. We also look at anecdotal evidence from Japan and detailed U.S. data drawn from county-level crime statistics and a survey of all state prosecutors by district. We find that prosecution rates vary little with budget, but conviction rates do increase, and that the conviction rate declines in the number of cases prosecuted and with the crime rate of a district.

Analysis of Recidivism Rates Based on Risk and Needs Assessments, Foster, Michelle
Paper presented at the annual meeting of the Midwest Political Science Association.
Abstract: The focus of this work is on analyzing recidivism rates for offenders who have received risk and needs assessments. This study uses secondary data obtained from ICPSR and collected by the Los Angeles Probation Department from April 1997 to December 1997 for offenders placed on probation. The reoffending rates over there time periods are examined. The results of the logistic regression analysis are that offenders who have a drug abuse problem are more likely to offend at 12 months and 18 month timeframes rather than initially at 6 months. These results suggest a greater need for treatment services the longer an offender is probation instead of a shorter time period for treatment.

Recidivism Among Youth Released From The Youth Leadership Academy To The City Challenge Intensive Aftercare Program - by Bruce Frederick and Dina Roy
The present study examined recidivism among 323 male juvenile delinquents from New York City who were released from the Sergeant Henry Johnson Youth Leadership Academy (YLA) to the City Challenge Intensive Aftercare Program (CCh) from May 1992 through June 1999. The primary purpose of the study was to determine whether efforts to improve the design and implementation of the YLA/CCh sequence had been accompanied by reductions in post-release recidivism.
Methods
Analyses of changes in recidivism rates controlled for changes in the distribution of youth characteristics and circumstances, including age, race, length of residential stay, time at risk, 2 measures of academic achievement, 4 measures of prior record, 4 measures of youth attitudes and behavior, 4 measures of youth's home environment, 5 measures of local crime and arrest rates, and 6 measures of local population and housing characteristics. These measures were combined in multivariate statistical models to produce scores reflecting the a priori risk of recidivism for each individual.
Findings
After controlling for changes in a priori risk, the study found no reduction in overall recidivism, as measured by post-release arrests for any criminal offenses. The study did find a statistically significant reduction between the second and third phases for certain measures of violent recidivism. The effects were strongest for short-term recidivism, that is, for rearrests for violent crimes within the first 6 months following release. During the second phase, the observed rate of violent recidivism within six months at risk had been more than double the rate expected on the basis of average a priori risk, but it dropped to levels slightly below a priori risk during the third and fourth phases. Despite this relative reduction, though, the absolute level of violent recidivism for the fourth phase was still high-17% within 6 months and 31% within 12 months.
Conclusion
Patterns in the detailed findings suggest that the relative reduction in violent recidivism was probably not due to changes in the characteristics and circumstances of participants, changes in pre-arrest revocation rates, changes in local arrest rates, or improvements in the YLA component. Among the most salient explanations, the most plausible is that the reduction was due primarily to improvements in the City Challenge Intensive Aftercare Program.

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