Substance use among older youth transitioning from foster care: Examining the protective effects of religious and spiritual capital

Among older youth transitioning from the foster care system, this longitudinal study examined the association of religious and spiritual capital to substance use in the past year at age 19. Participants consisted of African American (N = 179) and White non‐Hispanic (N = 133) older youth in foster care. Drawing from social capital theory, it was posited that religious service attendance (a proxy for religious capital) and belief in a spiritual force (a proxy for spiritual capital) would be inversely associated with substance use. Multiple logistic regression results indicated support for the first and second hypothesis for White foster youth only. Among White foster youth, more frequent religious service attendance and greater belief in a spiritual force were associated with a lower likelihood of illegal substance and polysubstance use. No association between religious or spiritual capital and substance use was found among African American foster youth. The findings underscore the importance of conducting spiritual assessments to help ensure older foster youth who have strong religious or spiritual orientations are in environments where they are accommodated and supported.     

Fathering With Multiple Partners: Links to Children's Well‐Being in Early Childhood

The claim that multiple partner fertility may pose a risk of adverse outcomes for children has not been tested. We test this argument using a sample of 4,027 resident fathers and children from the Fragile Families and Child Well‐being Survey by examining the pathways through which fathers' multipartnered fertility is associated with children's externalizing behaviors and physical health status at 36 months. Path analyses indicate that multiple partner fertility exerted both a significant direct and indirect effect through paternal depression to influence children's externalizing behaviors. Fathers' multiple partner fertility also exerted a significant indirect effect through one mediator—father involvement—to influence children's physical health. This evidence suggests that the disruptions brought about by multipartnered fertility are important for understanding child well‐being.     

MARKET STRUCTURE AND MEDIA DIVERSITY

We estimate a mixed logit model of the demand for local news service. Results provide evidence that suggest the representative consumer values more diverse news, more coverage of multicultural issues, and more information on community news, and has a distaste for advertising. Demand estimates are used to calculate the impact on consumer welfare from a marginal decrease in the number of independent television stations that lowers the amount of diversity, multiculturalism, community news, and advertising. Consumer welfare decreases, but the losses are smaller in large markets. For example, small‐market consumers lose $45 million annually while large‐market consumers lose $13 million. (JEL C9, C25, L13, L82, L96)     

Living on the margin: disabled Iranians in Belgian society

This paper explores the antecedents, experiences and consequences of marginalization as reported and dealt with by disabled Iranian immigrants in Belgium. This work extends the work of Gallie and colleagues and Siegrist demonstrating that the forces of marginalization applicable to all immigrants are particularly pertinent to disabled immigrants. The research is based on 26 in‐depth, face‐to‐face interviews, focus groups, interviews with government officials and immigration experts, ethnographic work and official government statistics. The findings detail how the combined forces of history, context and reasons for immigration; isolation, vulnerability and perceived loss of control; religion and rejection; lack of reciprocity in social exchanges; problems in obtaining jobs; and difficulties in negotiating an entry into Belgian society combine to sustain marginizalation. As a consequence, disabled immigrants in this group are generally excluded from society and discriminated against in terms of citizenship, education, jobs and general acceptance.     

Structure and process in occupational mobility

The distinction between structure and process in occupational mobility has been a dominant theme in contemporary research. While successive attempts to “solve” the structure/process dilemma have typically focused on new methodological procedures, we emphasize the conceptual issues underlying the distinction as a basis for further analysis. We introduce a simple two-stage model for the specification of mobility structure and process and use this model to evaluate current methodological “solutions” to the analysis of mobility.     

Mixture of latent trait analyzers for model-based clustering of categorical data

Model-based clustering methods for continuous data are well established and commonly used in a wide range of applications. However, model-based clustering methods for categorical data are less standard. Latent class analysis is a commonly used method for model-based clustering of binary data and/or categorical data, but due to an assumed local independence structure there may not be a correspondence between the estimated latent classes and groups in the population of interest. The mixture of latent trait analyzers model extends latent class analysis by assuming a model for the categorical response variables that depends on both a categorical latent class and a continuous latent trait variable; the discrete latent class accommodates group structure and the continuous latent trait accommodates dependence within these groups. Fitting the mixture of latent trait analyzers model is potentially difficult because the likelihood function involves an integral that cannot be evaluated analytically. We develop a variational approach for fitting the mixture of latent trait models and this provides an efficient model fitting strategy. The mixture of latent trait analyzers model is demonstrated on the analysis of data from the National Long Term Care Survey (NLTCS) and voting in the U.S. Congress. The model is shown to yield intuitive clustering results and it gives a much better fit than either latent class analysis or latent trait analysis alone.     

BIG DATA AND BIG CITIES: THE PROMISES AND LIMITATIONS OF IMPROVED MEASURES OF URBAN LIFE

New, “big data” sources allow measurement of city characteristics and outcome variables at higher collection frequencies and more granular geographic scales than ever before. However, big data will not solve large urban social science questions on its own. Big urban data has the most value for the study of cities when it allows measurement of the previously opaque, or when it can be coupled with exogenous shocks to people or place. We describe a number of new urban data sources and illustrate how they can be used to improve the study and function of cities. We first show how Google Street View images can be used to predict income in New York City, suggesting that similar imagery data can be used to map wealth and poverty in previously unmeasured areas of the developing world. We then discuss how survey techniques can be improved to better measure willingness to pay for urban amenities. Finally, we explain how Internet data is being used to improve the quality of city services. (JEL R1, C8, C18)