Reliability of professional judgments in forensic child sexual abuse evaluations: unsettled or unsettling science?

In the absence of photographic or DNA evidence, a credible eyewitness, or perpetrator confession, forensic evaluators in cases of alleged child sexual abuse must rely on psychosocial or "soft" evidence, often requiring substantial professional judgment for case determination. This article offers a three-part rebuttal to Herman's (2009 ) argument that forensic decisions based on psychosocial evidence are fundamentally unreliable and that this conclusion represents settled science. The article also discusses the potentially adverse consequences of Herman's proposed reforms to forensic practice on child protection and prosecution efforts.     

Family structure and child outcomes: a high definition, wide angle “snapshot”

Using data from the National Survey of America??s Families (NSAF), this research investigates the relationships between a highly defined set of family structures and a broad set of child outcomes at a particular point in time in a child??s life. A detailed classification of family structures is constructed that clarifies key differences among various types of diverse families, and facilitates equivalencies testing and pairwise comparisons across nontraditional family structures. The NSAF contains a large number of observations for less common, but growing, family structures such as single-father families, grandparent-headed households and cohabiters, which makes such detailed analyses feasible and allows further stratification by child age, gender and race. The data also contains information on child behavioral, educational and physical health outcomes, as well as extensive household characteristics, economic resources and parental behaviors and inputs. Results suggest that differences across nontraditional family structures are particularly prominent for child health outcomes and that the gender of the resident parent is empirically important, more so than the presence of a cohabiting or married step-parent. Children in single father families have lesser access to health care yet enjoy better health outcomes than those in other families, even after controlling for economic resources (and inputs). In contrast, few differences are found between grandparent-headed families and other non-parent families. While we explore alternative explanations for these results, our cross-sectional data and complex set of family structure variables preclude isolating causal relationships; instead, our analyses yield empirically important distinctions that point to promising avenues for future research.     

Development in youth enterprises

Business enterprises run by youth can create jobs and teach the principles of free enterprise but also convey skills that can be used by employees in large companies, as well as political activists and entrepreneurs. Research is needed to test the efficacy of this approach and identify its key components.     

How moral disengagement facilitates the detention of refugee children and families

Refugee children and families are a vulnerable demographic with the propensity to disrupt entrenched disparaging perceptions about immigrants. This project investigates how institutionalised moral disengagement practices [Bandura, Albert. 2002. “Selective Moral Disengagement in the Exercise of Moral Agency.” Journal of Moral Education 31: 101–119] at family detention centres facilitate the apprehension and confinement of children and families seeking asylum. Interviews with former volunteers and an analysis of news reports describing conditions at these centres reveal that moral disengagement plays a pivotal role in rationalising detention, while also enabling restrictive immigration policies and mass deportations. This occurs through the criminalisation of immigrants, suppressing details about residential conditions, and a quota capacity model. Findings are contextualised with regard to recent immigration legislations.     

Gender egalitarianism,perceived economic insecurity,and fertility intentions in Spain: A qualitative analysis

Economic uncertainty contributes to low fertility in many European countries. On the other hand, greater gender equality may positively influence fertility. This paper examines how these two forces interact in Spain. We use in-depth interviews to analyse fertility decision-making among young and highly educated partnered adults living in urban areas. Highly gender-egalitarian interviewees are less likely to perceive economic insecurity as an obstacle to proceeding to a next birth than less egalitarian interviewees. But there is not necessarily a difference in these two groups’ overall fertility intentions, as highly egalitarian interviewees’ greater valuation of stable employment for both partners requires institutional and policy support for dual-earner couples’ childrearing. When we look only at interviewees who express economic insecurity, somewhat higher fertility intentions are expressed by those holding less gender-egalitarian attitudes. Our results underline the complexity of the interrelationships between economic insecurity, gender egalitarianism, and fertility intentions.     

Improving the detection of unusual observations in high‐dimensional settings

Multivariate control charts are used to monitor stochastic processes for changes and unusual observations. Hotelling's T² statistic is calculated for each new observation and an out‐of‐control signal is issued if it goes beyond the control limits. However, this classical approach becomes unreliable as the number of variables p approaches the number of observations n, and impossible when p exceeds n. In this paper, we devise an improvement to the monitoring procedure in high‐dimensional settings. We regularise the covariance matrix to estimate the baseline parameter and incorporate a leave‐one‐out re‐sampling approach to estimate the empirical distribution of future observations. An extensive simulation study demonstrates that the new method outperforms the classical Hotelling T² approach in power, and maintains appropriate false positive rates. We demonstrate the utility of the method using a set of quality control samples collected to monitor a gas chromatography–mass spectrometry apparatus over a period of 67 days.     

Improving the Efficacy of Administrative Data for Evaluation of Holistic Defense

A college of social work developed a partnership with a state commission on indigent defense to examine existing data-collection procedures, potential case outcomes, and practical implications of implementing holistic defense programs. The holistic defense model responds to the complex challenges of justice-system-involved defendants by providing social services in public defense offices. Using chi-square and logistic regression analyses of administrative data for a sample of 15,994 public defendants from a single judicial circuit, this research study examined case outcomes before and after implementation of a holistic defense program. Results were mixed regarding effectiveness of holistic defense in mitigating the effect of justice involvement for indigent defendants. Implementation of holistic defense was associated with a decrease in case dismissals. However, defendants receiving holistic representation were less likely to be indicted than defendants prior to program implementation. Once indicted, there were no changes in levels of diversions, and more defendants were held on bond, convicted as guilty, and incarcerated. After program implementation, fewer defendants were sentenced to alternatives to incarceration; more defendants were sentenced to time served, avoiding further incarcerative penalty. These findings suggested the need for further research to determine whether holistic defense practices are producing desired legal and social service outcomes.     

THE USE OF AGGREGATE DATA TO ESTIMATE GOMPERTZ‐TYPE OLD‐AGE MORTALITY IN HETEROGENEOUS POPULATIONS

We consider two related aspects of the study of old‐age mortality. One is the estimation of a parameterized hazard function from grouped data, and the other is its possible deceleration at extreme old age owing to heterogeneity described by a mixture of distinct sub‐populations. The first is treated by half of a logistic transform, which is known to be free of discretization bias at older ages, and also preserves the increasing slope of the log hazard in the Gompertz case. It is assumed that data are available in the form published by official statistical agencies, that is, as aggregated frequencies in discrete time. Local polynomial modelling and weighted least squares are applied to cause‐of‐death mortality counts. The second, related, problem is to discover what conditions are necessary for population mortality to exhibit deceleration for a mixture of Gompertz sub‐populations. The general problem remains open but, in the case of three groups, we demonstrate that heterogeneity may be such that it is possible for a population to show decelerating mortality and then return to a Gompertz‐like increase at a later age. This implies that there are situations, depending on the extent of heterogeneity, in which there is at least one age interval in which the hazard function decreases before increasing again.     

Empirical Prediction Intervals for County Population Forecasts

Population forecasts entail a significant amount of uncertainty, especially for long-range horizons and for places with small or rapidly changing populations. This uncertainty can be dealt with by presenting a range of projections or by developing statistical prediction intervals. The latter can be based on models that incorporate the stochastic nature of the forecasting process, on empirical analyses of past forecast errors, or on a combination of the two. In this article, we develop and test prediction intervals based on empirical analyses of past forecast errors for counties in the United States. Using decennial census data from 1900 to 2000, we apply trend extrapolation techniques to develop a set of county population forecasts; calculate forecast errors by comparing forecasts to subsequent census counts; and use the distribution of errors to construct empirical prediction intervals. We find that empirically-based prediction intervals provide reasonably accurate predictions of the precision of population forecasts, but provide little guidance regarding their tendency to be too high or too low. We believe the construction of empirically-based prediction intervals will help users of small-area population forecasts measure and evaluate the uncertainty inherent in population forecasts and plan more effectively for the future.