Reclaiming Futures considers an anti-oppressive frame to decrease disparities

The Reclaiming Futures mandate is to improve substance abuse service interventions within the juvenile justice system, and concurrently to ensure that racial disparities are avoided. But traditional efforts to reduce disparities have not been adequate to preclude these almost universal trends from reappearing in the initiative. In response, the authors have introduced anti-oppressive practice (AOP) to the initiative, beginning first with workshops at the national gatherings, and following up with webinars, discipline-specific training for judges, probation professionals, alcohol and drug treatment professionals, community members, and project directors, and finally, an in-depth course to advance the approach more deeply into the initiative. This paper begins with a review of the status of racial disparities in the United States, and shares details of the evolution of Reclaiming Futures to consider an innovative response to such disparities, namely anti-oppressive practice. We detail the ways in which AOP has been incorporated into Reclaiming Futures. The paper then discusses two key elements of our initiative: the theoretical and conceptual elements of AOP that make it a desirable approach to reducing disparities, and an introduction to the core competencies that are affiliated with AOP. We anticipate that this paper will be of interest to program administrators and service providers who are searching for practice innovations that offer a positive prognosis for reducing racial disparities.     

The Last Rogue of History: Picaresque Elements in Sasha Sokolov’s Palisandriia

This article takes a detailed look at the way in which the Habsburg Monarchy’s policy towards Serbia subtly shifted between 1881, when the Monarchy forced a secret treaty of alliance on the Serbian government, and the end of the Serbo-Bulgarian War of November 1885. Gustav von Kálnoky, the Austro-Hungarian foreign minister, inherited a policy largely shaped by his Hungarian predecessor, Count Gyula Andrássy, which relied on controlling Serbia through the person of its ruler, the wayward Milan Obrenovi?. The Austrophile and highly unpopular Milan, however, was a disastrous instrument of Austro-Hungarian control, and by the end of the Serbo-Bulgarian conflict, by which point Milan was pleading to be allowed to abdicate, Kálnoky had come to the conclusion that this “personal policy” was a failure, and that the Monarchy was better off relying on the outright coercion of Serbia. The article reconsiders some of the key stages in this development, in particular Andrássy’s memorandum of 24 November 1885, and Kálnoky’s reassessment of the value of the secret treaty of 1881, which depended solely on the guarantee of the Serbian monarch and, as a result, threatened to become worthless without his presence on the throne.     

Causality and interdependence analysis in linear econometric models with an application to fertility

This paper is an applied analysis of the causal structure of linear multi-equational econometric models. Its aim is to identify the kind of relationships linking the endogenous variables of the model, distinguishing between causal links and feedback loops. The investigation is first carried out within a deterministic framework and then moves on to show how the results may change inside a more realistic stochastic context. The causal analysis is then specifically applied to a linear simultaneous equation model explaining fertility rates. The analysis is carried out by means of a specific RATS programming code designed to show the specific nature of the relationships within the model.     

A Comparison of Hierarchical Methods for Clustering Functional Data

Functional data analysis (FDA)—the analysis of data that can be considered a set of observed continuous functions—is an increasingly common class of statistical analysis. One of the most widely used FDA methods is the cluster analysis of functional data; however, little work has been done to compare the performance of clustering methods on functional data. In this article, a simulation study compares the performance of four major hierarchical methods for clustering functional data. The simulated data varied in three ways: the nature of the signal functions (periodic, non periodic, or mixed), the amount of noise added to the signal functions, and the pattern of the true cluster sizes. The Rand index was used to compare the performance of each clustering method. As a secondary goal, clustering methods were also compared when the number of clusters has been misspecified. To illustrate the results, a real set of functional data was clustered where the true clustering structure is believed to be known. Comparing the clustering methods for the real data set confirmed the findings of the simulation. This study yields concrete suggestions to future researchers to determine the best method for clustering their functional data.     

Higher-order Bayesian Approximations for Pseudo-posterior Distributions

The theory of higher-order asymptotics provides accurate approximations to posterior distributions for a scalar parameter of interest, and to the corresponding tail area, for practical use in Bayesian analysis. The aim of this article is to extend these approximations to pseudo-posterior distributions, e.g., posterior distributions based on a pseudo-likelihood function and a suitable prior, which are proved to be particularly useful when the full likelihood is analytically or computationally infeasible. In particular, from a theoretical point of view, we derive the Laplace approximation for a pseudo-posterior distribution, and for the corresponding tail area, for a scalar parameter of interest, also in the presence of nuisance parameters. From a computational point of view, starting from these higher-order approximations, we discuss the higher-order tail area (HOTA) algorithm useful to approximate marginal posterior distributions, and related quantities. Compared to standard Markov chain Monte Carlo methods, the main advantage of the HOTA algorithm is that it gives independent samples at a negligible computational cost. The relevant computations are illustrated by two examples.     

A New Approach to Social Assistance: Latin America's Experience with Conditional Cash Transfer Programmes

Conditional cash transfers are a departure from more traditional approaches to social assistance that represents an innovative and increasingly popular channel for the delivery of social services. Conditional cash transfers provide money to poor families contingent upon certain behaviour, usually investments in human capital such as sending children to school or bringing them to health centres on a regular basis. They seek both to address traditional short-term income support objectives and promote the longer-term accumulation of human capital by serving as a demand-side complement to the supply of health and education services. Evaluation results reveal that this innovative design has been quite successful in addressing many of the failures in delivering social assistance such as poor poverty targeting, disincentive effects and limited welfare impacts. There is clear evidence of success from the first generation of programmes in Brazil, Colombia, Mexico and Nicaragua in increasing enrolment rates, improving preventive healthcare and raising household consumption. Despite this promising evidence, many questions remain unanswered about conditional cash transfer programmes, including the replicability of their success under different     

A course for clinical trial personnel in clinical study designs, randomization, allocation schedules, and interactive response systems

This continuing education course for professionals involved in all areas of clinical trials integrates concepts related to the role of randomization in the scientific process. The course includes two interactive lecture and discussion sections and a workshop practicum. The first interactive lecture introduces basic clinical trial issues and statistical principles such as bias, blinding, randomization, control groups, and the importance of formulating clear and discriminating clinical and statistical hypotheses. It then focuses on the most commonly used clinical study designs and the corresponding patient randomization schemes. The second interactive lecture focuses on the implementation of randomization of patients and drug supply through allocation and component ID schedules. The workshop practicum, conducted in small groups, enables students to apply the lecture concepts to real clinical studies. Flexibility was built into the workshop practicum materials to allow the course content to be customized to specific audiences, and the interactive lecture sessions can be stretched to cover more advanced topics according to class interest and time availability.     

Error catastrophe in mutant mitochondria

The error catastrophe theory of aging, proposed by Orgel in 1963, predicted a decrease in the fidelity of information transfer that accelerated as aging progressed, until properly functioning macromolecules could no longer be reliably made. The theory was extensively tested by comparing DNA polymerases, transfer RNAs, and proteins derived from aging versus young animals, but it did not prove to have general applicability to the process of aging. Recently, the heritable eye disorder progressive external ophthalmoplegia has been found to result from mutation of the gene encoding DNA polymerase gamma, which replicates mitochondrial DNA. The mutant form of the polymerase replicates DNA less accurately than the wild-type enzyme, providing an explanation for the accumulation of mutations in the mitochondrial DNA of patients with this disorder. The affected mitochondria appear to exhibit an age-dependent error catastrophe. It is possible that other genetic diseases might result in error catastrophes in mitochondria as well.