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Redeemed Compared to Whom? Comparing the Distributional Properties of Arrest Risk Across Convicted and General Populations
Abstract
Research Summary:
By using data on provisional employees with and without criminal records, we find that existing standards of a “reasonable amount of [arrest] risk” (derived from “time to redemption” research) for an employer to incur in hiring individuals with criminal histories prove too onerous for many employees without records to meet, let alone those
with records. We then propose an alternative method of assessing arrest risk across these populations—benchmarking—and provide several alternative standards, illustrating that they (a) clear a demonstrable majority of employees without records and a sizable
minority of those with a criminal history and (b) do not increase the risk incurred by employers over and above the level they already accept among employees without records.
Policy Implications:
Our findings suggest that the almost singular importance placed on “time since last” policies when conducting criminal background checks is ill-placed as the risk of arrest across populations of employees with and without criminal histories overlaps more than the results of extant research would imply. Although future research needs to be conducted to ascertain whether our findings generalize to other employment contexts, current background check practices would be better served if they were to adopt an approach that chooses a specific threshold for comparison, which should align with an easily communicated and face-valid cost function. Furthermore, the selected standard should (a) hold all individuals to the same standard and (b) be one that a demonstrable majority of individuals without criminal records can meet.
Criminal background checks are increasingly being incorporated into hiring decisions by employers. Although originally uncompromising—almost anyone with a criminal record could be denied employment—court rulings and policy changes have forced criminal background checks to become more nuanced. One motivation for allowing more individuals with criminal records to work is to decrease recidivism and encourage desistance. In this article, we estimate the causal impact of receiving a clearance to work on subsequent arrests for individuals with criminal records who have been provisionally hired to work in certain nonlicensed health-care jobs in New York State (N = 6,648). We employ an instrumental variable approach based on a substantive understanding of the state-mandated criminal background check process. We examine age-graded effects within this group of motivated individuals and differential effects by sex in the rapidly growing health-care industry, which is typically dominated by women. Our estimated local average treatment effect indicates a 2.2-percentage-point decrease in the likelihood of a subsequent arrest in 1 year and a 4.2-percentage-point decrease over 3 years. We find meaningful variations by sex; men are 8.4 percentage points less likely to be arrested over the 3-year period when cleared compared with a 2.4-percentage-point (and nonsignificant) effect for women. Older women in particular are driving the nonsignificant results for women.
Two conflicting definitions of desistance exist in the criminology literature. The first definition is instantaneous desistance in which an offender simply chooses to end a criminal career instantaneously moving to a zero rate of offending (). The second definition views desistance as a process by which the offending rate declines steadily over time to zero or to a point close to zero (; ; ). In this article, we capitalize on the underlying assumptions of several parametric survival distributions to gain a better understanding of which of these models best describes actual patterns of desistance. All models are examined using 18 years of follow‐up data on a cohort of felony convicts in Essex County, NJ. Our analysis leads us to three conclusions. First, some people have already desisted at the beginning of the follow‐up period, which is consistent with the notion of “instantaneous desistance.” Second, a three‐parameter model that allows for a turning point in the risk of recidivism followed by a long period of decline fits the data best. This conclusion suggests that for those offenders active at the start of the study period, the risk of recidivism is declining over time. However, we also find that a simpler two‐group model fits the data almost as well and gains superiority in the later years of follow‐up. This last point is particularly relevant as it suggests that the observed gradual decline in the hazard over time is a result of a compositional effect rather than of a pattern of individually declining hazards.
It is well accepted that criminal records impose collateral consequences on offenders. Such records affect access to public housing, student financial aid, welfare benefits, and voting rights. An axiom of these policies is that individuals with criminal records—even old criminal records—exhibit significantly higher risk of future criminal conduct than do individuals without criminal records. In this article, the authors use police contact data from the 1942 Racine birth cohort study to determine whether individuals whose last criminal record occurred many years ago exhibit a higher risk of acquiring future criminal records than do individuals with no criminal record at all. Findings suggest that there is little to no distinguishable difference between these groups.
In sentencing research, significant negative coefficients on age research have been interpreted as evidence that actors in the criminal justice system discriminate against younger people. This interpretation is incomplete. Criminal sentencing laws generally specify punishment in terms of the number of past events in a defendant’s criminal history. Doing so inadvertently makes age a meaningful variable because older people have had more time to accumulate criminal history events. Therefore, two people of different ages with the same criminal history are not in fact equal. This is true for pure retributivists, as the fact that the younger offender has been committing crimes at a higher rate of offending may make the younger offender more culpable, and is also true for those with some utilitarian aims for sentencing. Simulation results illustrate the stakes. To a certain extent, the interests of low-rate older offenders are opposed to those of high-rate younger offenders.
This paper discusses the concerns associated with the introduction of, and increased reliance on, actuarial risk tools in sentencing in order to: (1) stimulate cross-disciplinary dialog and research about the impact of incorporating actuarial risk logic into sentencing processes and (2) identify questions requiring further empirical examination. In this article, I recognize that actuarial risk logic offers managerial and organizational benefits, but I also demonstrate that the application of actuarial risk when sentencing offenders is not without important consequences. First, I provide a brief outline of the emergence, logic, and entrenchment of probabilistic reasoning within criminal justice decision-making, and the more recent extension and application of actuarial risk logic to sentencing. Then, I use the following themes to define the limits of using risk sciences in sentencing: (1) the logical structure of risk; (2) the slippage between risk prediction and individual causation; (3) current methodological limits of risk science; (4) the potential for gender and race discrimination; (5) the legal relevance and transparency of risk-based sentencing; and (6) the jurisprudential and organizational impact of various risk technologies. Importantly, the nature and severity of these complications will vary by, and within, the jurisdiction (or sentencing regime) because current sentencing practices are influenced by local jurisdictional needs and sentencing laws.
The essence of benchmarking is the process of identifying the highest standards of excellence for products, services, or processes, and then making the improvements necessary to reach those standards – commonly called “best practices”. Various companies have adopted benchmarking and customized the methodology to suit their needs. A five-step benchmarking model is suggested in this paper as a model to be used when undertaking a benchmarking study. Two case studies are enumerated and a comparison presented.
Objective:
Although the individual placement and support (IPS) approach has demonstrated superior competitive employment outcomes for people with severe mental illness, practitioners report that job obtainment for people with criminal convictions is particularly challenging. The current study examined employer hiring decisions and attitudes regarding job applicants with felonies. The main purpose of the study was to identify the percentage of employers who had knowingly hired applicants with felonies, and if the hiring patterns differed by employer type.
Method:
Twelve employment specialists from nine states interviewed 128 employers about their past hiring practices. Two IPS trainers coordinated the project with the specialists.
Results:
Survey findings did not support common assumptions held by employment specialists about employer attitudes. Sixty-three percent of employers surveyed said that they had knowingly hired at least one person with a felony conviction. Further, few businesses had written policies that would prohibit the hiring of people with felony convictions.
Conclusions and implications for practice:
Employers' reported reasons for having hired individuals with felony convictions provide a framework to help jobseekers improve their prospects for favorable hiring decisions. Employers suggested that relationships with employment specialists can also facilitate the hiring of applicants with felonies.
In this paper, we analyze employer demand for ex-offenders. We use data from a recent survey of employers to analyze not only employer preferences for offenders, but also the extent to which they check criminal backgrounds in the presence of very imperfect information about the job applicants whom they consider. We investigate the firm and job characteristics that correlate with these measures of employer demand. We also consider the extent to which such demand changed during the 1990's, in response to tighter labor market conditions, using data from surveys administered at different points in time. Finally, we consider the quantities of demand for ex-offenders relative to their supply, based on a variety of estimates of total stocks and annual flows of offenders back to the civilian population.
This paper estimates the effect of employment denial based on a criminal background check on recidivism outcomes for individuals with convictions who are provisionally hired in the New York State healthcare industry. Using institutional knowledge about the New York State Department of Health's screening process, I build structural assumptions on potential outcomes for different subsamples in my data, which partially identifies the Average Treatment Effects. I find a 0–2.2 percentage-point increase in the likelihood of subsequent arrests caused by employment denial, with substantial heterogeneity across the sample. Specifically, I find that the a priori highest risk individuals are most likely to be impacted by a loss of employment opportunity based on their criminal background. Policy implications of these results are discussed.
The past decade has seen the development and overall acceptance of the concept of Integrated Flood Risk Management. This approach strives to balance positive and negative effects of riverine floods and combines it with risk management concepts. In practice, this has led to a diversification of flood management practices that go beyond traditional structural flood protection measures towards non-structural measures. These include giving more space for rivers, backwards-location of dykes, re-naturalization of flood plains and a suite of improved information systems including improved flood forecasting services, promoting flood risk awareness and self-help capabilities.The paper describes in some detail the process of benchmarking to support effective planning, implementation and monitoring of integrated flood risk management activities that require a set of quantifiable measures, against which progress in flood risk management can be referenced. The case of the extreme Elbe River floods in 2002 and 2013 triggered the development and implementation of the Elbe Flood Protection - Action Plan that in large parts has been implemented. The paper shows the basic concepts of the Elbe Flood Protection Plan and its actions and puts these in the context of a benchmarking framework. The paper concludes that although elements of a benchmarking concept are outlined in the Action Plan, the establishment of benchmarking practices as a tool in flood risk management is in its infancy. The development of a consistent benchmarking procedure would have the potential to further improve the effectiveness of Integrated Flood Risk Management practices in national and international river basins.
In this study, we examine race, sex, and self-reported arrest histories (excluding arrests for minor traffic violations) from the 1997 National Longitudinal Survey of Youth (NLSY; N = 7,335) for the period 1997 through 2008 covering cumulative arrest histories through ages 18 and 23. The analysis produces three key findings: (1) males have higher cumulative prevalence of arrest than females; and (2) there are important race differences in the probability of arrest for males but not for females. Assuming the missing cases are missing at random, about 30% of black males have experienced at least one arrest by age 18 (vs. about 22% for white males); by age 23 about 49% of black males have been arrested (vs. about 38% for white males). Earlier research using the NLSY showed that the risk of arrest by age 23 was 30%, with nonresponse bounds [25.3%, 41.4%]. This study indicates that the risk of arrest is not evenly distributed across the population. Future research should focus on the identification and management of collateral risks that often accompany arrest experiences.
Objectives Prior theoretical scholarship makes strong assumptions about the invariance of the age-crime relationship by sex. However, scant research has evaluated this assumption. This paper asks whether the age-crime curve from age 12–30 is invariant by sex using a contemporary, nationally representative sample of youth, the National Longitudinal Survey of Youth 1997 cohort (NLSY97). Methods To address the limitations of the existing empirical literature, a novel localized modeling approach is used that does not require a priori assumptions about the shape of the age-crime curve. With a non-parametric method—B-spline regression, the study models self-report criminal behavior and arrest by sex using age as the independent variable, and its cubic spline terms to accommodate different slopes for different phases of the curve. Results The study shows that males and females have parallel age-crime curves when modeled with self-report criminal behavior variety score but they have unique age-crime in the frequency of self-report arrest. Group-based trajectory analysis is then used to provide a deeper understanding of heterogeneity underlying the average trends. The onset patterns by sex are quite similar but the post-peak analyses using the early onset sample reveal different patterns of desistance for arrest by sex. Conclusions The study found evidence of relatively early and faster desistance of arrest among females but little difference exists for the variety of criminal behaviors. Implications and future directions are discussed.
Purpose
– The purpose of this paper is to examine current approaches to interpretation of student evaluation data and present an innovative approach to developing benchmark targets for the effective and efficient use of these data.
Design/methodology/approach
– This article discusses traditional approaches to gathering and using student feedback across the tertiary sector. The limitations of the customary use of the statistical mean as a quality measure of performance are presented and examined. An alternative method of interpreting student evaluation data is proposed and examples given.
Findings
– The traditional use of the statistical mean to interpret student evaluation data has limitations. Focusing on data at the macro level provides subject teaching staff and managers with a clearer indication of student satisfaction. The use of a percentage satisfied and percentage dissatisfied metric to classify and rank subjects is presented as an efficient alternative to the traditional approach, while recognising the value of the statistical mean to interpret data at the micro level.
Originality/value
– In light of the important role student feedback plays in determining university ranking, prioritising staff development and its potential function as an academic performance indicator, the effective interpretation of student evaluation data is critical. As economic factors become increasingly important to higher education providers, the role of evaluation data obtained from students will continue to gain traction. The identification of methods to fully capitalise on the value of these data, such as the one proposed in this article, is therefore crucial.
In an age of widespread background checks, we ask how managers in different organizational contexts navigate legal ambiguity in assessing applicants' criminal history information, based on interview data obtained in a recent field experiment. The study builds on institutional analyses of the social sources of workplace legality to describe how employers consider applicants with criminal histories. We find that some organizations set explicit standards to guide hiring decisions, providing concrete policies on how to treat applicants with records. Where such procedural mandates are lacking, however, hiring managers turn to a micro-rational decision process to evaluate potential risk and liability. These individualized approaches create inconsistencies in how the law is interpreted and applied across organizations, as evidenced by actual hiring behavior in the field experiment.
Statistically based risk assessment devices are widely used in criminal justice settings. Their promise remains largely unfulfilled, however, because assumptions and premises requisite to their development and application are routinely ignored and/or violated. This article provides a brief review of the most salient of these assumptions and premises, addressing the base rate and selection ratios, methods of combining predictor variables and the nature of criterion variables chosen, cross-validation, replicability, and generalizability. The article also discusses decision makers’ choices to add or delete items from the instruments and suggests recommendations for policy makers to consider when adopting risk assessments. Suggestions for improved practice, practical and methodological, are made.
Many legal barriers exist that prevent ex-offenders from obtaining lawful employment, a principle means for reintegration. This article explores the scope and utility of these laws, which aim ostensibly to reduce the prospective employee’s likelihood of engaging in workplace crime. Irrelevance of the provisions to the effective assessment of job applicants’ risks of offending, shortcomings of criminal background checks, lack of empirical evidence linking ex-offenders to workplace crime, and the availability of viable alternatives underscore the need to scale back these significant obstacles to ex-offender reentry. The article concludes with recommendations for reasonable uses of risk assessment in employment screening laws.
Previous methodological research has shown that hidden heterogeneity in hazard rate regression models-in the form of systematic differences between sample members in the risk or hazard of making a transition due to unobserved variables not accounted for by the measured covariates-can produce biased parameter estimates and erroneous inferences. However, few empirical applications of hazard regression do more than pay lip service to the complications of hidden heterogeneity. In part, this is due to the relative inaccessibility of the mathematical apparatus of continuous-time hazard regression methodology with flexible nonparametric specifications on the hidden heterogeneity This article presents new methods for incorporating nonparametric specifications of hidden heterogeneity into hazard regressions by developing discrete-time Poisson rate/complementary log-log hazard regression models with nonparametric hidden heterogeneity that are analogous to the continuous-rime models of Heckman and Singer: Maximum-likelihood estimators and associated hypothesis tests are described. An empirical application to data on criminal careers, which illustrates the utility of models that explicitly incorporate hidden heterogeneity, is presented.
Research Summary
This research explores the issue of old prior records and their ability to predict future offending. In particular, we are interested in the question of whether, after a given period of time, the risk of recidivism for a person who has been arrested in the distant past is ever indistinguishable from that of a population of persons with no prior arrests. Two well‐documented empirical facts guide our investigation: (1) Individuals who have offended in the past are relatively more likely to offend in the future, and (2) the risk of recidivism declines as the time since the last criminal act increases. We find that immediately after an arrest, the knowledge of this prior record does significantly differentiate this population from a population of nonoffenders. However, these differences weaken dramatically and quickly over time so that the risk of new offenses among those who last offended six or seven years ago begins to approximate (but not match) the risk of new offenses among persons with no criminal record.
Policy Implications
Individuals with official records of past offending behavior encounter a barrier when they try to obtain employment, even if a person's most recent offense occurred in the distant past. There are many reasons for such obstacles, but they are at least partially premised on the concern that individuals with arrest records—even from the distant past—are more likely to offend in the future than persons with no criminal history. Our analysis questions the logic of such practices and suggests that after a given period of remaining crime free, it may be prudent to wash away the brand of “offender” and open up more legitimate opportunities to this population.
Age is one of the most robust correlates of criminal behavior. Yet, explanations for this relationship are varied and conflicting. Developmental theories point to a multitude of sociological, psychological, and biological changes that occur during adolescence and adulthood. One prominent criminological perspective outlined by Gottfredson and Hirschi claims that age has a direct effect on crime, inexplicable from sociological and psychological variables. Despite the attention this claim has received, few direct empirical tests of it have been conducted. We use data from Pathways to Desistance, a longitudinal study of over 1,300 serious youthful offenders (85.8 % male, 40.1 % African-American, 34.3 % Hispanic, 21.0 % White), to test this claim. On average, youths were 16.5 years old at the initial interview and were followed for 7 years. We use multilevel longitudinal models to assess the extent to which the direct effects of age are reduced to statistical and substantive non-significance when constructs from a wide range of developmental and criminological theories are controlled. Unlike previous studies, we are able to control for changes across numerous realms emphasized within differing theoretical perspectives including social control (e.g., employment and marriage), procedural justice (e.g., perceptions of the legitimacy and fairness of the legal system), learning (e.g., gang membership and exposure to antisocial peers), strain (e.g., victimization and relationship breakup), psychosocial maturity (e.g., impulse control, self-regulation and moral disengagement), and rational choice (e.g., costs and rewards of crime). Assessed separately, these perspectives explain anywhere from 3 % (procedural justice) to 49 % (social learning) of the age-crime relationship. Together, changes in these constructs explain 69 % of the drop in crime from ages 15 to 25. We conclude that the relationship between age and crime in adolescence and early adulthood is largely explainable, though not entirely, attributable to multiple co-occurring developmental changes.
Criminal record checks are being used increasingly by decision makers to predict future unwanted behaviors. A central question these decision makers face is how much time it takes before offenders can be considered “redeemed” and resemble nonoffenders in terms of the probability of offending. Building on a small literature addressing this topic for youthful, first-time offenders, the current article asks whether this period differs across the age of last conviction and the total number of prior convictions. Using long-term longitudinal data on a Dutch conviction cohort, we find that young novice offenders are redeemed after approximately 10 years of remaining crime free. For older offenders, the redemption period is considerably shorter. Offenders with extensive criminal histories, however, either never resemble their nonconvicted counterparts or only do so after a crime-free period of more than 20 years. Practical and theoretical implications of these findings are discussed.
Our goal is to build bridges between theoretical criminology, the study of criminal careers, and policy-relevant research. Insights from the criminal career and propensity positions lead us to seek (1) a comprehensive means of incorporating theoretical variables in research on criminal careers, (2) statistical models that yield meaningful projections relevant to public policy issues, and (3) methods for comparing findings for different measures of offending. We present a conceptual framework accomplishing this by applying the general linear model to the study of crime and criminal careers. This framework differentiates the elements of (1) a curvilinear function linking the scale of the linear model and the scale of the measure of offending, (2) a probabilistic relationship between a latent tendency to offend and the measure of offending, (3) a probability distribution of individual differences on the latent dimension, and (4) relationships among repeated observations for the same individual. We describe numerous versions of the general linear model that do not require special statistical expertise and are appropriate for the full range of measures of offending. We conclude by addressing strategies for comparing results across measures.
Criminal background checks have now become ubiquitous because of advances in information technology and growing concerns about employer liability. Also, a large number of individual criminal records have accumulated and have been computerized in state repositories and commercial databases. As a result, many ex-offenders seeking employment could be haunted by a stale record. Recidivism probability declines with time “clean,” so some point in time is reached when a person with a criminal record, who remained free of further contact with the criminal justice system, is of no greater risk than a counterpart of the same age—an indication of redemption from the mark of crime. Very little information exists on this measure of time until redemption and on how its value varies with the crime type and the offender's age at the time of the earlier event. Using data from a state criminal-history repository, we estimate the declining hazard of rearrest with time clean. We first estimate a point of redemption as the time when the hazard intersects the age–crime curve, which represents the arrest risk for the general population of the same age. We also estimate another similar redemption point when the declining hazard comes “sufficiently close” to the hazard of those who have never been arrested. We estimate both measures of redemption as a function of the age and the crime type of the earlier arrest. These findings aid in the development of guidelines for the users of background checking and in developing regulations to enhance employment opportunities for ex-offenders.
The statistical procedures typically used for forecasting in criminal justice settings rest on symmetric loss functions. For
quantitative response variables, overestimates are treated the same as underestimates. For categorical response variables,
it does not matter in which class a case is inaccurately placed. In many criminal justice settings, symmetric costs are not
responsive to the needs of stakeholders. It can follow that the forecasts are not responsive either. In this paper, we consider
asymmetric loss functions that can lead to forecasting procedures far more sensitive to the real consequences of forecasting
errors. Theoretical points are illustrated with examples using criminal justice data of the kind that might be used for “predictive
policing.”
KeywordsForecasting–Loss functions–Asymmetric loss–Predictive policing
By articulating a general theory of crime and related behavior, the authors present a new and comprehensive statement of what the criminological enterprise should be about. They argue that prevalent academic criminologyâwhether sociological, psychological, biological, or economicâhas been unable to provide believable explanations of criminal behavior. The long-discarded classical tradition in criminology was based on choice and free will, and saw crime as the natural consequence of unrestrained human tendencies to seek pleasure and to avoid pain. It concerned itself with the nature of crime and paid little attention to the criminal. The scientific, or disciplinary, tradition is based on causation and determinism, and has dominated twentieth-century criminology. It concerns itself with the nature of the criminal and pays little attention to the crime itself. Though the two traditions are considered incompatible, this book brings classical and modern criminology together by requiring that their conceptions be consistent with each other and with the results of research. The authors explore the essential nature of crime, finding that scientific and popular conceptions of crime are misleading, and they assess the truth of disciplinary claims about crime, concluding that such claims are contrary to the nature of crime and, interestingly enough, to the data produced by the disciplines themselves. They then put forward their own theory of crime, which asserts that the essential element of criminality is the absence of self-control. Persons with high self-control consider the long-term consequences of their behavior; those with low self-control do not. Such control is learned, usually early in life, and once learned, is highly resistant to change. In the remainder of the book, the authors apply their theory to the persistent problems of criminology. Why are men, adolescents, and minorities more likely than their counterparts to commit criminal acts? What is the role of the school in the causation of delinquincy? To what extent could crime be reduced by providing meaningful work? Why do some societies have much lower crime rates than others? Does white-collar crime require its own theory? Is there such a thing as organized crime? In all cases, the theory forces fundamental reconsideration of the conventional wisdom of academians and crimina justic practitioners. The authors conclude by exploring the implications of the theory for the future study and control of crime.
From random security checks at airports to the use of risk assessment in sentencing, actuarial methods are being used more than ever to determine whom law enforcement officials target and punish. And with the exception of racial profiling on our highways and streets, most people favor these methods because they believe theyâre a more cost-effective way to fight crime. In Against Prediction, Bernard E. Harcourt challenges this growing reliance on actuarial methods. These prediction tools, he demonstrates, may in fact increase the overall amount of crime in society, depending on the relative responsiveness of the profiled populations to heightened security. They may also aggravate the difficulties that minorities already have obtaining work, education, and a better quality of lifeâthus perpetuating the pattern of criminal behavior. Ultimately, Harcourt shows how the perceived success of actuarial methods has begun to distort our very conception of just punishment and to obscure alternate visions of social order. In place of the actuarial, he proposes instead a turn to randomization in punishment and policing. The presumption, Harcourt concludes, should be against prediction.
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