This journal issue has also been published in eletronic format

Annoucement

This journal issue has also been published in eletronic format     

CHANGE IN SPOUSE AGE DIFFERENCE AT MARRIAGE: A CHALLENGE TO TRADITIONAL FAMILY AND SEX ROLES?

We speculate that four broad societal changes (postponement of marriage by large numbers of women, dispersion of divorce throughout the life cycle, more equitable distribution of power between men and women, and wide swings in fertility) should eventually affect male-female age difference at marriage—i.e., the age-mating gradient. Examination of age difference at marriage from 1930–1980 in a central Florida county shows a trend toward increasing percentages of women marrying men younger than themselves. Data on all marriages for 1985 for this same county ( N = 7,021) indicates a continuation of this trend. Previous investigation of the age-mating gradient disclosed that age at marriage and marriage parity are related to the percentage of marriages in which the age-mating gradient is "followed.' Using the proportion marrying mates older or younger by three or more years as a conservative measure of the violation of the age-mating gradient, we find that the persons most likely to deviate from the traditional age-mating gradient were men ages 24–29, women over 30, and those persons who were marrying for the second, third, or later time. Some suggested explanations for these patterns are offered.     

Vyāghranomics in space and time: Estimating habitat threats for Bengal,Indochinese, Malayan and Sumatran tigers

The wild tiger population in tropical Asia has dropped from about 100,000 to 3500 in the last century, and the need to conserve tiger habitats poses a challenge for the Global Tiger Recovery Program. This paper develops and uses a high-resolution monthly forest clearing database for 74 tiger habitat areas in ten countries to investigate habitat threats for Bengal, Indochinese, Malayan and Sumatran tigers. The econometric model links forest habitat loss and forest clearing to profitability calculations that are affected by market expectations, environmental conditions and evolving patterns of settlement, among others. It uses new spatial panel estimation methods that allow for temporal and spatial autocorrelation. The econometric results emphasize the role of short-run market variables, including the exchange rate, real interest rate and prices of agricultural products in forest clearing, with considerable variation in the estimated timing for response and impact elasticities across countries. The results highlight a critical message for the conservation policy community: Changes in world agricultural-product markets and national financial policies have significant, measurable effects on tropical forest clearing, with variable time lags and degrees of responsiveness across countries. Measuring these effects and pinpointing areas at risk can provide valuable guidance for policymakers, conservation managers, and donor institutions.     

The Learning Square: Four Domains that Impact on Strategy

In the search for strategic competitive advantage, the importance of learning and knowledge is increasingly recognized. In this paper, we identify four domains synthesized from the literature – multi-dimensional goals, using tacit knowledge, continual learning, and shared vision – that impact upon and provide a framework for developing strategy. Three themes are drawn from learning organization literature linking to a fourth from strategy literature. These domains are brought together in a holistic model proposed for use by managers in evaluating and developing strategy –'The Learning Square'.     

Positively Impacting Maternal Stress and Parental Adjustment through Community-Based Relationship Education (RE)

Relationship education (RE) is a brief, strength-based psychoeducational intervention for couples that demonstrates strong outcomes to decrease individual and couple stress. The current study examined changes in relationship and family adjustment for expectant mothers following RE intervention. Participants included 91 pregnant women (64.8% racial or ethnic minorities) who participated in a community-based RE program. In examination of pre and post-intervention relationship assessment scale and parental stress and coping inventory results, RE intervention contributed to increased relationship satisfaction, and reduced parental distress, as well as to improved social support and family-based support scores among participants. In addition, relationship stress is a major contributor to stress during pregnancy that adds vulnerability for the health of low-income and ethnic minority expectant mothers and their children. Findings indicate the effectiveness of RE to significantly reduce stress for expectant mothers. Therefore, the use of RE as a low-cost and accessible intervention to combat stress provides positive implications for this vulnerable population.     

Understanding paid peer support in mental health

This study aimed to explore, articulate and expand on existing concepts of recovery and paid peer support within consumer-operated mental health organizations. Focus groups and interviews were conducted with 32 participants to identify elements of paid peer support work in two organizations in Queensland, Australia. Participants included peer-supported consumers, paid peer support workers, managers and other key stakeholders. Through a grounded theory analysis, eight categories of paid peer support were identified. For the most part, the categories aligned well with evidence in the literature. However, two of these categories, issues of power and the ‘dark side’ of peer support, have been relatively unexplored and understated in previous studies. These findings provide an expanded understanding of the role of paid peer support as part of the recovery process in mental health service delivery. The effective use of paid peer support workers can be enhanced through attention to the issues identified.     

Bayesian Hierarchical Structure for Quantifying Population Variability to Inform Probabilistic Health Risk Assessments

Human variability is a very important factor considered in human health risk assessment for protecting sensitive populations from chemical exposure. Traditionally, to account for this variability, an interhuman uncertainty factor is applied to lower the exposure limit. However, using a fixed uncertainty factor rather than probabilistically accounting for human variability can hardly support probabilistic risk assessment advocated by a number of researchers; new methods are needed to probabilistically quantify human population variability. We propose a Bayesian hierarchical model to quantify variability among different populations. This approach jointly characterizes the distribution of risk at background exposure and the sensitivity of response to exposure, which are commonly represented by model parameters. We demonstrate, through both an application to real data and a simulation study, that using the proposed hierarchical structure adequately characterizes variability across different populations.     

Integrating Stakeholder Mapping and Risk Scenarios to Improve Resilience of Cyber‐Physical‐Social Networks

The future of energy mobility involves networks of users, operators, organizations, vehicles, charging stations, communications, materials, transportation corridors, points of service, and so on. The integration of smart grids with plug‐in electric vehicle technologies has societal and commercial advantages that include improving grid stability, minimizing dependence on nonrenewable fuels, reducing vehicle emissions, and reducing the cost of electric vehicle ownership. However, ineffective or delayed participation of particular groups of stakeholders could disrupt industry plans and delay the desired outcomes. This article develops a framework to address enterprise resilience for two modes of disruptions—the first being the influence of scenarios on priorities and the second being the influence of multiple groups of stakeholders on priorities. The innovation of this study is to obtain the advantages of integrating two recent approaches: scenario‐based preferences modeling and stakeholder mapping. Public agencies, grid operators, plug‐in electric vehicle owners, and vehicle manufacturers are the four groups of stakeholders that are considered in this framework, along with the influence of four scenarios on priorities.