Family–school relationships in immigrant children’s well-being: the intersection of demographics and school culture in the experiences of black African immigrants in the United States

This article explores the types of family–school relationships that promote academic, socio-economic, and social and emotional well-being of black African immigrant children in the United States. The data are ethnographic, drawing on one year of participant observation and interviews at two elementary schools. The findings are also set within the context of an analysis of data from the New Immigrant Survey. The article identifies mechanisms by which relationships between black African immigrants and schools are created and argues that intersections between demographics and school culture are central, particularly as related to the possibilities for relational power, which can allow parents and school staff to transcend persistent inequalities of race and discrimination.     

An Ecological Framework for Sexual Minority Women’s Health: Factors Associated With Greater Body Mass

In recent years, many studies have focused on the body of sexual minority women, particularly emphasizing their larger size. These studies rarely offer theoretically based explanations for the increased weight, nor study the potential consequences (or lack thereof) of being heavier. This article provides a brief overview of the multitude of factors that might cause or contribute to larger size of sexual minority women, using an ecological framework that elucidates upstream social determinants of health as well as individual risk factors. This model is infused with a minority stress model, which hypothesizes excess strain resulting from the stigma associated with oppressed minority identities such as woman, lesbian, bisexual, woman of color, and others. We argue that lack of attention to the upstream social determinants of health may result in individual-level victim blaming and interventions that do not address the root causes of minority stress or increased weight.     

School (non-)attendance and ‘mobile cultures’: theoretical and empirical insights from Indigenous Australia

Aboriginal and Torres Strait Islander (Indigenous) Australians are significantly and substantially less likely to be attending school on a given day than their non-Indigenous counterparts. This has been shown to have long-term consequences for the development of the mainstream literacy and numeracy skills associated with formal schooling, as well as later school and employment outcomes. Reducing this gap is a key focus of government education policy within Australia. Hampering the design of effective policy, however, is the lack of a robust empirical and theoretical framework to explain school (non-)attendance that not only builds on existing research, but also reflects the specific circumstances and aspirations of Indigenous students and their families. This article applies mixed-methods quantitative and qualitative techniques to explore what Indigenous student (non-)attendance in Australia might tell us regarding the relationship between highly marginalised student groups and formal education systems. A robust understanding of these geographically and socio-culturally situated school (non-)attendance patterns and processes allows us to build on and contribute to human capital, critical, resistance, and other behavioural theories of formal education and draw parallels for other population sub-groups globally, especially those that display ongoing patterns of high geographic mobility. Our analysis suggests that absenteeism amongst marginalised and/or highly mobile populations, may be most usefully conceived of as a manifestation of structural incompatibilities between formal schooling systems and the life projects and circumstances of these school-aged children and their families.     

Estimators in capture–recapture studies with two sources

This paper investigates the applications of capture–recapture methods to human populations. Capture–recapture methods are commonly used in estimating the size of wildlife populations but can also be used in epidemiology and social sciences, for estimating prevalence of a particular disease or the size of the homeless population in a certain area. Here we focus on estimating the prevalence of infectious diseases. Several estimators of population size are considered: the Lincoln–Petersen estimator and its modified version, the Chapman estimator, Chao’s lower bound estimator, the Zelterman’s estimator, McKendrick’s moment estimator and the maximum likelihood estimator. In order to evaluate these estimators, they are applied to real, three-source, capture-recapture data. By conditioning on each of the sources of three source data, we have been able to compare the estimators with the true value that they are estimating. The Chapman and Chao estimators were compared in terms of their relative bias. A variance formula derived through conditioning is suggested for Chao’s estimator, and normal 95% confidence intervals are calculated for this and the Chapman estimator. We then compare the coverage of the respective confidence intervals. Furthermore, a simulation study is included to compare Chao’s and Chapman’s estimator. Results indicate that Chao’s estimator is less biased than Chapman’s estimator unless both sources are independent. Chao’s estimator has also the smaller mean squared error. Finally, the implications and limitations of the above methods are discussed, with suggestions for further development. We are grateful to the Medical Research Council for supporting this work.     

Uniform-in-bandwidth kernel estimation for censored data

We present a sharp uniform-in-bandwidth functional limit law for the increments of the Kaplan–Meier empirical process based upon right-censored random data. We apply this result to obtain limit laws for nonparametric kernel estimators of local functionals of lifetime densities, which are uniform with respect to the choices of bandwidth and kernel. These are established in the framework of convergence in probability, and we allow the bandwidth to vary within the complete range for which the estimators are consistent. We provide explicit values for the asymptotic limiting constant for the sup-norm of the estimation random error.     

Some Asymptotic Results of Kernel Density Estimators Under Random Left-Truncation and Dependent Data

Problems with truncated data arise frequently in survival analyses and reliability applications. The estimation of the density function of the lifetimes is often of interest. In this article, the estimation of density function by the kernel method is considered, when truncated data are showing some kind of dependence. We apply the strong Gaussian approximation technique to study the strong uniform consistency for kernel estimators of the density function under a truncated dependent model. We also apply the strong approximation results to study the integrated square error properties of the kernel density estimators under the truncated dependent scheme.