Alexander M. Holsinger

Bio: Alexander M. Holsinger is an academic researcher from University of Missouri–Kansas City. The author has contributed to research in topics: Predictive validity & Risk assessment. The author has an hindex of 18, co-authored 33 publications receiving 1665 citations. Previous affiliations of Alexander M. Holsinger include University of Missouri.

Trademarks, Press Releases, and Policy: Will Rigorous Research Get in the Way?

Abstract: Rigorous research has taken a back seat to trademarks, press releases and the policy that follows. This article revisits some recent research that was used to develop policy and support movements to change pretrial release processes. The original research, was originally delivered with cautions and numerous limitations that seemed to be ignored. This paper follows up on those limitations and suggests that additional research be conducted prior to making sweeping changes in policy and practice.

“Two Perspectives” on Teaching Crime Films

Abstract: Due to the media, many students enter undergraduate Criminal Justice programs with biased and/or entertainment-based perceptions about justice generally, and the Criminal Justice system in particular. As a result, many instructors may be compelled to do regular “myth busting” in order to instill a more realistic understanding of Criminal Justice. However, these “myths” hold potential as learning tools in a specific course that confronts and deconstructs them head on. The current paper is about the use of popular media (specifically produced films) as the primary focus of a Criminal Justice course. While such courses tend to be very popular with students, and are potentially very useful in a comprehensive curriculum, there are many considerations when implementing them effectively. Using both student and faculty perspectives, we present the major concerns that need to be considered and addressed when implementing courses that focus solely on Criminal Justice within the popular media.

The Recent Past and Near Future of Risk and/or Need Assessment

Abstract: The history of risk assessment in criminal justice has been written on several occasions (Andrews & Bonta, 2003; Clements, 1996; Hollin, 2002). Here we assess progress since Andrews, Bonta, and Hoge’s (1990; Andrews, Zinger, et al., 1990) statement of the human service principles of risk-needresponsivity (RNR) and professional discretion. In those articles, the corrections-based terms of risk and need were transformed into principles addressing the major clinical issues of who receives treatment (higher risk cases), what intermediate targets are set (reduce criminogenic needs), and what treatment strategies are employed (match strategies to the learning styles and motivation of cases: the principles of general and specific responsivity). General responsivity asserts the general power of behavioral, social learning, and cognitive-behavioral strategies. Specific responsivity suggests matching of service with personality, motivation, and ability and with demographics such as age, gender, and ethnicity. Nonadherence is possible for stated reasons under the principle of professional discretion. Expanded sets of principles now include consideration of case strengths, setting of multiple criminogenic needs as targets, community-based, staff relationship and structuring skills, and a management focus on integrity through the selection, training, and clinical supervision of staff and organizational supports (Andrews, 2001). The review is conducted in the context of the advent of the fourth generation of offender assessment. Bonta (1996) earlier described three generations of risk assessment. The first generation (1G) consisted mainly of unstructured professional judgments of the probability of offending behavior. A

Associations of parenting dimensions and styles with externalizing problems of children and adolescents: An updated meta-analysis.

Abstract: The present meta-analysis integrates research from 1,435 studies on associations of parenting dimensions and styles with externalizing symptoms in children and adolescents. Parental warmth, behavioral control, autonomy granting, and an authoritative parenting style showed very small to small negative concurrent and longitudinal associations with externalizing problems. In contrast, harsh control, psychological control, authoritarian, permissive, and neglectful parenting were associated with higher levels of externalizing problems. The strongest associations were observed for harsh control and psychological control. Parental warmth, behavioral control, harsh control, psychological control, autonomy granting, authoritative, and permissive parenting predicted change in externalizing problems over time, with associations of externalizing problems with warmth, behavioral control, harsh control, psychological control, and authoritative parenting being bidirectional. Moderating effects of sampling, child's age, form of externalizing problems, rater of parenting and externalizing problems, quality of measures, and publication status were identified. Implications for future research and practice are discussed. (PsycINFO Database Record

The Measure and Mismeasure of Fairness: A Critical Review of Fair Machine Learning.

Abstract: The nascent field of fair machine learning aims to ensure that decisions guided by algorithms are equitable. Over the last several years, three formal definitions of fairness have gained prominence: (1) anti-classification, meaning that protected attributes---like race, gender, and their proxies---are not explicitly used to make decisions; (2) classification parity, meaning that common measures of predictive performance (e.g., false positive and false negative rates) are equal across groups defined by the protected attributes; and (3) calibration, meaning that conditional on risk estimates, outcomes are independent of protected attributes. Here we show that all three of these fairness definitions suffer from significant statistical limitations. Requiring anti-classification or classification parity can, perversely, harm the very groups they were designed to protect; and calibration, though generally desirable, provides little guarantee that decisions are equitable. In contrast to these formal fairness criteria, we argue that it is often preferable to treat similarly risky people similarly, based on the most statistically accurate estimates of risk that one can produce. Such a strategy, while not universally applicable, often aligns well with policy objectives; notably, this strategy will typically violate both anti-classification and classification parity. In practice, it requires significant effort to construct suitable risk estimates. One must carefully define and measure the targets of prediction to avoid retrenching biases in the data. But, importantly, one cannot generally address these difficulties by requiring that algorithms satisfy popular mathematical formalizations of fairness. By highlighting these challenges in the foundation of fair machine learning, we hope to help researchers and practitioners productively advance the area.

The Effectiveness of Correctional Rehabilitation: A Review of Systematic Reviews

Abstract: The effects of correctional interventions on recidivism have important public safety implications when offenders are released from probation or prison. Hundreds of studies have been conducted on those effects, some investigating punitive approaches and some investigating rehabilitation treatments. Systematic reviews (meta-analyses) of those studies, while varying greatly in coverage and technique, display remarkable consistency in their overall findings. Supervision and sanctions, at best, show modest mean reductions in recidivism and, in some instances, have the opposite effect and increase reoffense rates. The mean recidivism effects found in studies of rehabilitation treatment, by comparison, are consistently positive and relatively large. There is, however, considerable variability in those effects associated with the type of treatment, how well it is implemented, and the nature of the offenders to whom it is applied. The specific sources of that variability have not been well explored, but some princ...