Correlating Post-disaster Support Network Density with Reciprocal Support Relation Satisfaction: An Elderly Cohort Within One Year of the 2011 Japan Disasters

While there has been much empirical investigation into how social support networks improve mental health in post-disaster communities, network density—the extent members within a network are acquainted—remains under-researched. This study examines correlations between support network density and support reciprocity satisfaction in an elderly sample (N = 221), and the influence on post-disaster depression and trauma symptomology in a fishing community south of the Fukushima nuclear plant within 1 year of the March 11, 2011 Japan earthquake. The Brief Inventory of Social Support Exchange Network (BISSEN) taps support network density, support source by relational category, tangible and emotional type, and providing or receiving direction of social support. Density measurement convergent validity was established from questionnaire responses. After confirming network density construct and criteria validity, and extracting components reciprocal support relationship satisfaction, correlation between these two variables was moderate at r = 0.34. However, reciprocity satisfaction moderately explained mental health variance, but results were not significant for density nor interaction between predictors. These results question the assumption that support network density and support reciprocity can be validly incorporated into a construct of “social capital” necessarily promoting mental health.     

Bayesian Inventory Management with Potential Change‐Points in Demand

We consider the inventory management problem of a firm reacting to potential change points in demand, which we define as known epochs at which the demand distribution may (or may not) abruptly change. Motivating examples include global news events (e.g., the 9/11 terrorist attacks), local events (e.g., the opening of a nearby attraction), or internal events (e.g., a product redesign). In the periods following such a potential change point in demand, a manager is torn between using a possibly obsolete demand model estimated from a long data history and using a model estimated from a short, recent history. We formulate a Bayesian inventory problem just after a potential change point. We pursue heuristic policies coupled with cost lower bounds, including a new lower bounding approach to non‐perishable Bayesian inventory problems that relaxes the dependence between physical demand and demand signals and that can be applied for a broad set of belief and demand distributions. Our numerical studies reveal small gaps between the costs implied by our heuristic solutions and our lower bounds. We also provide analytical and numerical sensitivity results suggesting that a manager worried about downside profit risk should err on the side of underestimating demand at a potential change point.     

Improving Catastrophe Modeling for Business Interruption Insurance Needs

While catastrophe (CAT) modeling of property damage is well developed, modeling of business interruption (BI) lags far behind. One reason is the crude nature of functional relationships in CAT models that translate property damage into BI. Another is that estimating BI losses is more complicated because it depends greatly on public and private decisions during recovery with respect to resilience tactics that dampen losses by using remaining resources more efficiently to maintain business function and to recover more quickly. This article proposes a framework for improving hazard loss estimation for BI insurance needs. Improved data collection that allows for analysis at the level of individual facilities within a company can improve matching the facilities with the effectiveness of individual forms of resilience, such as accessing inventories, relocating operations, and accelerating repair, and can therefore improve estimation accuracy. We then illustrate the difference this can make in a case study example of losses from a hurricane.     

Workplace occupation and the possibilities of popular power in Chile and Argentina, 1972–6

ABSTRACT

The recent wave of occupations has had a transformative effect on radical politics, but, to date, many have been restricted in their social and spatial expansion. Reflecting on these challenges, this article examines workplace occupation in the coordinadoras interfabriles in Argentina (1975–6) and the cordones industriales in Chile (1972–3) to understand how they overcame barriers to such expansion. Starting from debates in critical geography and social movement studies on space and occupations, I unpack the possibilities for popular power that emerged in this period by using approaches from critical labour studies and autonomist Marxism. First, I outline the generative role of the workplace in producing these possibilities in a context of wider social change. Second, I demonstrate how the capacity for expansion lay in the simultaneous capacity to disrupt and reconstruct social relations derived from solidarities that exceeded the existing physical space of occupation.     

BAYESIAN BETA REGRESSION: APPLICATIONS TO HOUSEHOLD EXPENDITURE DATA AND GENETIC DISTANCE BETWEEN FOOT-AND-MOUTH DISEASE VIRUSES

There is considerable interest in understanding how factors such as time and geographic distance between isolates might influence the evolutionary direction of foot‐and‐mouth disease. Genetic differences between viruses can be measured as the proportion of nucleotides that differ for a given sequence or gene. We present a Bayesian hierarchical regression model for the statistical analysis of continuous data with sample space restricted to the interval (0, 1). The data are modelled using beta distributions with means that depend on covariates through a link function. We discuss methodology for: (i) the incorporation of informative prior information into an analysis; (ii) fitting the model using Markov chain Monte Carlo sampling; (iii) model selection using Bayes factors; and (iv) semiparametric beta regression using penalized splines. The model was applied to two different datasets.     

EVALUATING PDAS FOR DATA COLLECTION IN FAMILY RESEARCH WITH NON-PROFESSIONAL COUPLES

Repeated measures designs such as daily diary methods provide flexibility for examinations of fluid phenomena. The focus of this paper is to evaluate the effectiveness of Personal Digital Assistants (PDAs) as data collection tools with an end of the day (EOD) diary design and a non-professional sample. Participants reported the PDA was easy to use, convenient and enhanced the privacy of their responses. The PDAs minimized data entry errors and increased the data validity because responses were time stamped. Given the overall positive nature of participant reactions and the additional data PDAs make available to the researcher, the technology is recommended for further use in collecting data with non-professionals or in other couple or family research.     

Systematic review of primary prevention human papillomavirus interventions targeting college students

ABSTRACT. Objectives: The purpose of this research was to systematically analyze human papillomavirus (HPV) interventions targeting college students. Methods: Completed interventions targeting general HPV prevention, HPV vaccine uptake, or antecedents of HPV vaccination uptake that used any quantitative design, published from January 2000 to January 2014 in the English language, were reviewed. Results: Twelve interventions met the criteria. Ten interventions produced 1 or more significant outcomes on primary or secondary variables of interest. Conclusions: Efficacy of interventions can be enhanced through tailoring materials and pretesting by sex, operationalizing theories, incorporating process evaluations, employing HPV vaccine uptake outcome measures, and utilizing Web-based delivery of programs.     

Fear of acquaintance versus stranger rape as a "master status": towards refinement of the "shadow of sexual assault"

Using a sample of 1010 women from a southeastern state university, we explore whether associations between fear of sexual assault and other crime-specific fears vary based on presumed victim-offender relationship. More specifically, we assess the extent to which fear of stranger- and acquaintance-perpetrated sexual assaults differ in the extent to which they are correlated with fear of other crime victimizations. Multivariate logistic regression analysis revealed that both fear of stranger-perpetrated sexual assault and fear of acquaintance-perpetrated sexual assault were positively associated with nearly all other crime-specific fears under examination. However, associations were particularly strong between fear of sexual assault by a stranger and fear of other stranger-perpetrated crimes. Findings have significant implications for how academic institutions should comprehensively address direct and indirect negative influences of violence against college women.     

Exploring How an Elementary Teacher Plans and Implements Social Studies Inquiry

Social studies continues to be marginalized in elementary grades, yet the C3 Framework and its Inquiry Arc offer possibilities for high-quality elementary social studies instruction. However, the C3 Framework requires that teachers possess an adequate understanding of how to implement inquiry within the various social studies disciplines, which we argue is an aspect of the pedagogical content knowledge necessary for effective elementary social studies instruction. This single-case study follows an elementary teacher through her use of the C3 Framework, Inquiry Arc, and a related curriculum approach called the Inquiry Design Model as she conceptualized, planned, and implemented inquiries in her fifth-grade classroom. By incorporating this new knowledge into her existing understanding of social studies pedagogy, as well as her knowledge of her students and specific educational context, the teacher was able to successfully navigate some of the challenges associated with implementing social studies inquiry in elementary classrooms.