Social insurance and children: The relationship between Social Security,economic well-being,and family context among child recipients

The relationship between social insurance, which provides families protection against certain risks, and child economic security is understudied. Using the 2004 Survey of Income and Program Participation (SIPP) matched to Social Security Administration benefit records, this article investigates the economic welfare effects of the child component of the US Social Security program. We examine how the poverty rate of child beneficiaries would change, absent Social Security income, and how heavily the family incomes of these children rely on it, by family characteristics. Our findings reveal that Social Security plays an important role in mitigating economic insecurity among children deprived of a wage-earning parent through disability, death, or retirement. Family structure, earnings, and employment status are identified as key factors moderating the effect of Social Security on child recipients’ financial circumstance.     

Testing for bioequivalence of highly variable drugs from TR‐RT crossover designs with heterogeneous residual variances

Traditional bioavailability studies assess average bioequivalence (ABE) between the test (T) and reference (R) products under the crossover design with TR and RT sequences. With highly variable (HV) drugs whose intrasubject coefficient of variation in pharmacokinetic measures is 30% or greater, assertion of ABE becomes difficult due to the large sample sizes needed to achieve adequate power. In 2011, the FDA adopted a more relaxed, yet complex, ABE criterion and supplied a procedure to assess this criterion exclusively under TRR‐RTR‐RRT and TRTR‐RTRT designs. However, designs with more than 2 periods are not always feasible. This present work investigates how to evaluate HV drugs under TR‐RT designs. A mixed model with heterogeneous residual variances is used to fit data from TR‐RT designs. Under the assumption of zero subject‐by‐formulation interaction, this basic model is comparable to the FDA‐recommended model for TRR‐RTR‐RRT and TRTR‐RTRT designs, suggesting the conceptual plausibility of our approach. To overcome the distributional dependency among summary statistics of model parameters, we develop statistical tests via the generalized pivotal quantity (GPQ). A real‐world data example is given to illustrate the utility of the resulting procedures. Our simulation study identifies a GPQ‐based testing procedure that evaluates HV drugs under practical TR‐RT designs with desirable type I error rate and reasonable power. In comparison to the FDA's approach, this GPQ‐based procedure gives similar performance when the product's intersubject standard deviation is low (≤0.4) and is most useful when practical considerations restrict the crossover design to 2 periods.     

Bayesian credible intervals for response surface optima

In response surface methodology, one is usually interested in estimating the optimal conditions based on a small number of experimental runs which are designed to optimally sample the experimental space. Typically, regression models are constructed from the experimental data and interrogated in order to provide a point estimate of the independent variable settings predicted to optimize the response. Unfortunately, these point estimates are rarely accompanied with uncertainty intervals. Though classical frequentist confidence intervals can be constructed for unconstrained quadratic models, higher order, constrained or nonlinear models are often encountered in practice. Existing techniques for constructing uncertainty estimates in such situations have not been implemented widely, due in part to the need to set adjustable parameters or because of limited or difficult applicability to constrained or nonlinear problems. To address these limitations a Bayesian method of determining credible intervals for response surface optima was developed. The approach shows good coverage probabilities on two test problems, is straightforward to implement and is readily applicable to the kind of constrained and/or nonlinear problems that frequently appear in practice.     

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.     

Public Sociology on Twitter: a Space for Public Pedagogy?

Research has examined various elements of Twitter; however, no scholarship has explored how sociologists currently use the platform. This empirically driven paper explores how individuals that self-identify as sociologists on Twitter use the popular micro-blogging social media site. A total of 152,977 tweets from Twitter profiles of 130 sociologists were collected and examined using qualitative media analysis. The potential use of Twitter allows the sociologist to become both the generator and interlocutor of dialogue with publics. We frame our data analysis and discussion around the core theme of expertise - namely, the role that expertise plays in the use of Twitter by sociologists. Our findings indicate that when sociologists used Twitter as sociologists (i.e., drawing upon their stated research expertise) little direct engagement with publics occurred. Thus, while sociologists appear to be using Twitter as a space for public sociology, the use of this interactive platform is mostly limited to the generation of content, a finding consistent with Burawoy’s traditional form of public sociology. Suggestions for future research are noted.     

Becoming a Race-Conscious Social Studies Teacher: The Influence of Personal and Professional Experiences

In this interpretive case study the researchers examined the beliefs of 13 self-identifying race-conscious secondary social studies teachers from diverse racial or ethnic, gender, and school-context backgrounds. The researchers found that the teachers' beliefs and views of practice were generally aligned with the main assertions of critical race theory. The teachers described their personal and professional experiences as a major influence on their race-conscious beliefs and views of practice. Moreover, teachers in diverse contexts described having to learn how to navigate the different racial experiences of the students in their classrooms, while teachers in racially segregated contexts (predominately White, Black, or Latino) emphasized the importance of teaching their students about others. Finally, despite the teachers' regular integration of race-related issues into their required and elective courses, they expressed a desire to have more opportunities to teach about race.     

REPEATED LOBBYING BY COMMERCIAL LOBBYISTS AND SPECIAL INTERESTS

Developing a lobbying model of repeated agency, we explain previously unexplained features of the real‐world lobbying industry. Lobbying is divided between direct representation by special interests to policymakers, and indirect representation where special interests employ professional intermediaries called commercial lobbyists to lobby policymakers on their behalf. Our analytical structure allows us to explain several trends in lobbying. For example, using the observation that in the United States over the last 20 years, policymakers have spent an increasing amount of their time fundraising as opposed to legislating, we are able to explain why the share of commercial lobbyist activity in total lobbying has risen dramatically and now constitutes over 60% of the total. The key scarce resource in our analysis is policymakers' time. Policymakers allocate this resource via implicit repeated agency contracts that are used to incent special interests and commercial lobbyists to provide a mix of financial contributions and information on policy proposals. These implicit agency contracts solve both an information problem in the presence of unverifiable policy information and a contracting problem in the absence of legal enforcement. These repeated relationships, that are often described using the pejorative term “cronyism” in the popular press, may in certain circumstances be welfare improving. (JEL D72, D82, H1, P16)     

Emerging issues in urban ecology: implications for research,social justice,human health,and well-being

Urbanization affects landscape structure and the overall human condition in numerous ways. Green spaces include vegetated land cover (e.g., urban forests, trees, riparian zones, parks) which play a distinctive role in urban ecology. This article reviews emergent literature on the linkages between urban green spaces, social justice, and human health. We explore this subject in the context of landscape structure, ecosystem services, and distributional equity as it relates to various health outcomes. Finally, we conclude by identifying gaps in the scholarship and potential areas of future research.