Disconnected Geography: A Spatial Analysis of Disconnected Youth in the United States

Since the Great Recession, US policy and advocacy groups have sought to better understand its effect on a group of especially vulnerable young adults who are not enrolled in school or training programs and not participating in the labor market, so called ‘disconnected youth.’ This article distinguishes between disconnected youth and unemployed youth and examines the spatial clustering of these two groups across counties in the US. The focus is to ascertain whether there are differences in underlying contextual factors among groups of counties that are mutually exclusive and spatially disparate (non-adjacent), comprising two types of spatial clusters – high rates of disconnected youth and high rates of unemployed youth. Using restricted, household-level census data inside the Census Research Data Center (RDC) under special permission by the US Census Bureau, we were able to define these two groups using detailed household questionnaires that are not available to researchers outside the RDC. The geospatial patterns in the two types of clusters suggest that places with high concentrations of disconnected youth are distinctly different in terms of underlying characteristics from places with high concentrations of unemployed youth. These differences include, among other things, arrests for synthetic drug production, enclaves of poor in rural areas, persistent poverty in areas, educational attainment in the populace, children in poverty, persons without health insurance, the social capital index, and elders who receive disability benefits. This article provides some preliminary evidence regarding the social forces underlying the two types of observed geospatial clusters and discusses how they differ.     

Population growth,changing agricultural practices,and environmental degradation in Zaire

This paper examines linkages between the demographic changes taking place in Zaire, particularly overall population growth and rapid urbanization, changes in agricultural practices, and related environmental degradation. Pressures to feed Zaire's rapidly increasing urban population, which fall on a rural population that has been growing relatively slowly in recent years, as well as population growth and increased population density in certain areas of the country, have resulted in changes in agricultural practices that are described in the paper. These changes in turn are leading to declining soil fertility, deforestation, and degradation of the natural resource base. Given present technology and the state of Zaire's economy, the changes in agricultural practices that have emerged in response to population growth, increased population density, and growth in demand for food production do not appear to be sustainable in the long run.     

Estimating likelihoods for spatio-temporal models using importance sampling

This paper describes how importance sampling can be applied to estimate likelihoods for spatio-temporal stochastic models of epidemics in plant populations, where observations consist of the set of diseased individuals at two or more distinct times. Likelihood computation is problematic because of the inherent lack of independence of the status of individuals in the population whenever disease transmission is distance-dependent. The methods of this paper overcome this by partitioning the population into a number of sectors and then attempting to take account of this dependence within each sector, while neglecting that between-sectors. Application to both simulated and real epidemic data sets show that the techniques perform well in comparison with existing approaches. Moreover, the results confirm the validity of likelihood estimates obtained elsewhere using Markov chain Monte Carlo methods.     

Depression and childhood illness

Childhood depression as a component of the impact of childhood illness or developmental impairment on the latency age child is studied in relation to three diagnostic groups: children with asthma, cancer, and psychiatric diagnoses of behavioral disorders. The study revealed a range of coping styles to deal with the anxiety, loss and feelings induced by the specific crises. The special dimensions of stress and coping adaptations affected the child's developing self concept, the separation individuation process and the child-parent relationships. Depressive symptoms were variously present within and between the three groups of children.This study was funded, in part, by grants from the University of Michigan Medical School and the Horace Rackham Graduate School of the University of Michigan.     

Adult Problem Solving: Contributor to Parenting and Child Outcomes in Divorced Families

This cross-sectional study extends child outcome models by focusing on factors in the adult social domain as contributors to parenting. The sample included 138 divorced mothers, their focal sons, and their support confidants assessed approximately 5 years after marital separation. The multimethod latent variable analysis tested a hypothesized progression stating observed confidant support would enhance problem solving outcomes achieved by mothers and confidants. Resolving parenting and personal issues for the mother was expected to benefit parenting practices (i.e., monitoring, discipline, and mother/child problem solving), which in turn would predict a macro level measure of child antisocial behavior. Analysis of the simplex model supported the progression. The final model explained 36% of the variance in antisocial behavior, 15% of the variance in parenting, and 53% of the variance in problem solving outcome. Dyads with cohabiting partners scored higher on problem solving outcomes than did dyads with friends or family members. The model is discussed in the context of social interactional and social learning theory.