How Latinos Are Transforming the United States: Research, Theory, and Policy

The United States is entering a new era, a period marked by some important demographic changes in the composition of the population, most especially significant increases in the Latino and Latino immigrant segments of society. These population shifts require corresponding interpersonal, organizational, and structural changes. The present issue bridges research and theory across disciplines and includes studies incorporating a variety of methodologies to examine these important areas. These articles begin to fill some of the voids where a systematic and robust corpus of knowledge is lacking. The contributions address topics ranging from issues of identity and interpersonal relations to pressing matters of educational significance to general approaches to navigating the cultural transitions that mark fluid transnational adaptations. Finally, each contribution delineates the policy implications resulting from the processes and literatures that are examined.     

The Politics of Hope and Despair: The Effect of Presidential Election Outcomes on Suicide Rates*

Objectives. This article examines the effect of election outcomes on suicide rates by combining the theory of social integration developed by Durkheim with the models of rational choice used in economics. Methods. Theory predicts that states with a greater percentage of residents who supported the losing candidate would tend to exhibit a relative increase in suicide rates. However, being around others who also supported the losing candidate may indicate a greater degree of social integration at the local level, thereby lowering relative suicide rates. We therefore use fixed‐effects regression of state suicide rates from 1981 to 2005 on state election outcomes during presidential elections to determine which effect is stronger. Results. We find that the local effect of social integration is dominant. The suicide rate when a state supports the losing candidate will tend to be lower than if the state had supported the winning candidate—4.6 percent lower for males and 5.3 percent lower for females. Conclusion. Social integration works at many levels; it not only affects suicide risk directly, but can mediate other shocks that influence suicide risk.     

A cyclical view of the relationship between corporate governance and strategic management

The vast majority of research on the relationship between corporate governance and strategic management focuses on the impact of corporate governance on strategic management. In this article we propose a cyclical model, highlighting that strategic decisions can also affect corporate governance through shaping firm ownership structure. We discuss the impacts of strategic decisions on firm ownership structure and corporate governance in the contexts of publicly traded firms, private firms, and the privatization of state-owned enterprises. We hope that our cyclical model can promote researchers to develop a more complete view about the relationships between strategic management, ownership structure, and corporate governance.     

Dose‐Response Models Incorporating Aerosol Size Dependency for Francisella tularensis

The effect of bioaerosol size was incorporated into predictive dose‐response models for the effects of inhaled aerosols of Francisella tularensis (the causative agent of tularemia) on rhesus monkeys and guinea pigs with bioaerosol diameters ranging between 1.0 and 24 μm. Aerosol‐size‐dependent models were formulated as modification of the exponential and β‐Poisson dose‐response models and model parameters were estimated using maximum likelihood methods and multiple data sets of quantal dose‐response data for which aerosol sizes of inhaled doses were known. Analysis of F. tularensis dose‐response data was best fit by an exponential dose‐response model with a power function including the particle diameter size substituting for the rate parameter k scaling the applied dose. There were differences in the pathogen's aerosol‐size‐dependence equation and models that better represent the observed dose‐response results than the estimate derived from applying the model developed by the International Commission on Radiological Protection (ICRP, 1994) that relies on differential regional lung deposition for human particle exposure.     

A Comparative Pharmacokinetic Estimate of Mercury in U.S. Infants Following Yearly Exposures to Inactivated Influenza Vaccines Containing Thimerosal

The use of thimerosal preservative in childhood vaccines has been largely eliminated over the past decade in the United States because vaccines have been reformulated in single‐dose vials that do not require preservative. An exception is the inactivated influenza vaccines, which are formulated in both multidose vials requiring preservative and preservative‐free single‐dose vials. As part of an ongoing evaluation by USFDA of the safety of biologics throughout their lifecycle, the infant body burden of mercury following scheduled exposures to thimerosal preservative in inactivated influenza vaccines in the United States was estimated and compared to the infant body burden of mercury following daily exposures to dietary methylmercury at the reference dose established by the USEPA. Body burdens were estimated using kinetic parameters derived from experiments conducted in infant monkeys that were exposed episodically to thimerosal or MeHg at identical doses. We found that the body burden of mercury (AUC) in infants (including low birth weight) over the first 4.5 years of life following yearly exposures to thimerosal was two orders of magnitude lower than that estimated for exposures to the lowest regulatory threshold for MeHg over the same time period. In addition, peak body burdens of mercury following episodic exposures to thimerosal in this worst‐case analysis did not exceed the corresponding safe body burden of mercury from methylmercury at any time, even for low‐birth‐weight infants. Our pharmacokinetic analysis supports the acknowledged safety of thimerosal when used as a preservative at current levels in certain multidose infant vaccines in the United States.     

Perceptions of Randomized Security Schedules

Security of infrastructure is a major concern. Traditional security schedules are unable to provide omnipresent coverage; consequently, adversaries can exploit predictable vulnerabilities to their advantage. Randomized security schedules, which randomly deploy security measures, overcome these limitations, but public perceptions of such schedules have not been examined. In this experiment, participants were asked to make a choice between attending a venue that employed a traditional (i.e., search everyone) or a random (i.e., a probability of being searched) security schedule. The absolute probability of detecting contraband was manipulated (i.e., 1/10, 1/4, 1/2) but equivalent between the two schedule types. In general, participants were indifferent to either security schedule, regardless of the probability of detection. The randomized schedule was deemed more convenient, but the traditional schedule was considered fairer and safer. There were no differences between traditional and random schedule in terms of perceived effectiveness or deterrence. Policy implications for the implementation and utilization of randomized schedules are discussed.     

Model Uncertainty and Bayesian Model Averaged Benchmark Dose Estimation for Continuous Data

The benchmark dose (BMD) approach has gained acceptance as a valuable risk assessment tool, but risk assessors still face significant challenges associated with selecting an appropriate BMD/BMDL estimate from the results of a set of acceptable dose‐response models. Current approaches do not explicitly address model uncertainty, and there is an existing need to more fully inform health risk assessors in this regard. In this study, a Bayesian model averaging (BMA) BMD estimation method taking model uncertainty into account is proposed as an alternative to current BMD estimation approaches for continuous data. Using the “hybrid” method proposed by Crump, two strategies of BMA, including both “maximum likelihood estimation based” and “Markov Chain Monte Carlo based” methods, are first applied as a demonstration to calculate model averaged BMD estimates from real continuous dose‐response data. The outcomes from the example data sets examined suggest that the BMA BMD estimates have higher reliability than the estimates from the individual models with highest posterior weight in terms of higher BMDL and smaller 90th percentile intervals. In addition, a simulation study is performed to evaluate the accuracy of the BMA BMD estimator. The results from the simulation study recommend that the BMA BMD estimates have smaller bias than the BMDs selected using other criteria. To further validate the BMA method, some technical issues, including the selection of models and the use of bootstrap methods for BMDL derivation, need further investigation over a more extensive, representative set of dose‐response data.     

State of the Art in Risk Analysis of Workforce Criticality Influencing Disaster Preparedness for Interdependent Systems

The objective of this article is to discuss a needed paradigm shift in disaster risk analysis to emphasize the role of the workforce in managing the recovery of interdependent infrastructure and economic systems. Much of the work that has been done on disaster risk analysis has focused primarily on preparedness and recovery strategies for disrupted infrastructure systems. The reliability of systems such as transportation, electric power, and telecommunications is crucial in sustaining business processes, supply chains, and regional livelihoods, as well as ensuring the availability of vital services in the aftermath of disasters. There has been a growing momentum in recognizing workforce criticality in the aftermath of disasters; nevertheless, significant gaps still remain in modeling, assessing, and managing workforce disruptions and their associated ripple effects to other interdependent systems. The workforce plays a pivotal role in ensuring that a disrupted region continues to function and subsequently recover from the adverse effects of disasters. With this in mind, this article presents a review of recent studies that have underscored the criticality of workforce sectors in formulating synergistic preparedness and recovery policies for interdependent infrastructure and regional economic systems.     

Anti-N-methyl-D-aspartate receptor antibody encephalitis: An important cause of encephalitis in young adults. A report of two cases

Encephalitis is a clinical syndrome which can include altered mental status, motor and sensory deficits, altered behavior including personality changes, speech and movement disorders and seizures. While the overall incidence of encephalitis is not known, it is common enough that most pediatric and adolescent medicine physicians will have seen at least one case. Peak times of risk include the newborn period and middle-to-late adolescence.¹ Dalmau J, Tüzün E, Wu HY, et al. Paraneoplastic anti-N-methyl-D-aspartate receptor encephalitis associated with ovarian teratoma. Ann Neurol. 2007 Jan;61(1):25–36. doi:10.1002/ana.21050. PMID: 17262855.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar] It is important for clinicians to have a working knowledge of the broad range of encephalitis etiologies: viral, post-viral, toxic, auto-immune, and paraneoplastic. We discuss two cases of encephalitis in young adult women with ovarian teratoma and production of anti-N-methyl-D-aspartate receptor (NMDAR) antibodies.