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.     

Reintegration upon return: insights from Ecuadorian returnees from Spain

Using the ECM2 survey data on Ecuadorian migrants returning from Spain, we investigate the determinants of reintegration upon return. We study how the migration experience, but also the before‐ and after‐migration characteristics, correlate with migrants’ outcomes upon return. We adopt a broad conception of reintegration, considering jointly labour market‐related outcomes that proxy for structural reintegration and subjective indicators that provide insights on sociocultural reintegration. The determinants of these two types of outcomes appear to be different: reintegration indeed encompasses multiple dimensions which cannot be captured by a single indicator. Our results suggest that return assistance programmes’ efficiency in helping reintegration could be improved by (I) targeting, ex‐ante, returnees who plan to launch their own business, and, ex‐post, the most vulnerable workers (women, older returnees, unemployed), and (ii) facilitating the labour market integration of foreign‐educated returnees. They also call for further research to better understand the consequences of these programmes.     

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.     

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.     

Research Note—A Pilot Cyber Counseling Course in a Graduate Social Work Program

Cyber counseling is a new and growing medium for offering mental health services to children and youth. However, there is a lack of identification of the core competencies required to provide effective online counseling. A school of social work, in partnership with a national service agency providing online counseling to children and youth, developed and offered a 13-week course to participating MSW social work students and agency staff. The development of online counseling competencies was assessed through individual interviews with participants and a content analysis of online posts. Participants scored well in areas of assessment and intervention. Challenges were identified in relationship building within an online environment.