Altitude and early child growth in 47 countries

Population and Environment - The relationship between altitude of residence and child linear growth is studied using data for 630,499 children below age 5 years born between 1992 and 2016,...     

Women on boards of nonprofits: What difference do they make?

In this article, the authors explore the impact of women on nonprofit boards. From a sociological perspective, they look at the actual proportion of women on boards and, from a more psychological perspective, at the sex of the chief executive officers in order to examine the impact of these variables on board effectiveness, structure, and process. The study results, based on data from a cross section of Canadian nonprofits, indicate that as the percentage of women on a board increases, the dynamics of the board are significantly affected.     

Paradigm shifts,feminist phase theory,and the missing variable in women's studies curriculum transformation projects

Feminist phase theory describes the process of integrating women's studies scholarship as a series of identifiable stages, for both individuals and disciplines. Literature on the revolutionary and paradigm-shift potential of women's studies scholarship suggests important disciplinary differences in its construction, adoption, and diffusion. We reformulate feminist phase theory in paradigm shift terms, then operationalize and contrast two versions of it. Our analysis and review indicate that the missing variable in women's studies transformation projects is the participants' discipline. Data from our integration project show faculty in interpretive disciplines scoring higher on degree of integration of women's studies scholarship but not changing as a result of the project itself, while those in positivist disciplines do change but have lower absolute scores. These findings indicate a need for different integration strategies based on discipline. Empirical support for one sequential ordering in feminist phase theory argues for the importance and centrality of women-focused scholarship.An earlier version was presented at the 84th annual meeting of the American Sociological Association, San Francisco, California, August 1989.     

Exploring the Meaning of Rural Through Cognitive Maps1

Rural often is viewed as a setting for study rather than an object of study. Often a priori definitions of rural are used; these definitions may bear little resemblance to residents' understanding of the concept. A cognitive mapping experiment to explore the meaning of rural is undertaken in this paper. Results indicate that urban residents could readily identify rural areas on a blank map of Pennsylvania. Their responses to the question varied, however, with some respondents indicating urban areas or writing images on the map. A discussion of these thought processes and implications from these varying responses are presented. Then, the cognitive maps are compared to three commonly accepted definitions of rural. Population density was found to best approximate the areas that urban residents perceived as rural. The paper concludes by discussing policy implications of the findings.     

Bayesian compartmental model for an infectious disease with dynamic states of infection

Population-level proportions of individuals that fall at different points in the spectrum [of disease severity], from asymptomatic infection to severe disease, are often difficult to observe, but estimating these quantities can provide information about the nature and severity of the disease in a particular population. Logistic and multinomial regression techniques are often applied to infectious disease modeling of large populations and are suited to identifying variables associated with a particular disease or disease state. However, they are less appropriate for estimating infection state prevalence over time because they do not naturally accommodate known disease dynamics like duration of time an individual is infectious, heterogeneity in the risk of acquiring infection, and patterns of seasonality. We propose a Bayesian compartmental model to estimate latent infection state prevalence over time that easily incorporates known disease dynamics. We demonstrate how and why a stochastic compartmental model is a better approach for determining infection state proportions than multinomial regression is by using a novel method for estimating Bayes factors for models with high-dimensional parameter spaces. We provide an example using visceral leishmaniasis in Brazil and present an empirically-adjusted reproductive number for the infection.     

“I Want to Feel Like a Full Man”: Conceptualizing Gay,Bisexual, and Heterosexual Men’s Sexual Difficulties

Current understandings of sexual difficulties originate from a model that is based on the study of heterosexual men and women. Most research has focused on sexual difficulties experienced by heterosexual men incapable of engaging in vaginal penetration. To better understand men’s perceptions and experiences of sexual difficulties, seven focus groups and 29 individual interviews were conducted with gay (n = 22), bisexual (n = 5), and heterosexual (n = 25) men. In addition, the extent to which difficulties reported by gay and bisexual men differ from heterosexual men was explored. Data were analyzed using thematic analysis applying an inductive approach. Two intercorrelated conceptualizations were identified: penis function (themes: medicalization, masculine identity, psychological consequences, coping mechanisms) and pain (themes: penile pain, pain during receptive anal sex). For the most part, gay, bisexual, and heterosexual men reported similar sexual difficulties; differences were evident regarding alternative masculinity, penis size competition, and pain during receptive anal sex. The results of this study demonstrate the complexity of men’s sexual difficulties and the important role of sociocultural, interpersonal, and psychological factors. Limitations and suggested directions for future research are outlined.     

A Resilience-Based Approach to Risk Assessments—Building Resilient Organizations under Arctic Conditions

Reliability and higher levels of safety are thought to be achieved by using systematic approaches to managing risks. The assessment of risks has produced a range of different approaches to assessing these uncertainties, presenting models for how risks affect individuals or organizations. Contemporary risk assessment tools based on this approach have proven difficult for practitioners to use as tools for tactical and operational decision making. This article presents an alternative to these assessments by utilizing a resilience perspective, arguing that complex systems are inclined to variety and uncertainty regarding the results they produce and are therefore prone to systemic failures. A continuous improvement approach is a source of reliability when managing complex systems and is necessary to manage varieties and uncertainties. For an organization to understand how risk events occur, it is necessary to define what is believed to be the equilibrium of the system in time and space. By applying a resilience engineering (RE) perspective to risk assessment, it is possible to manage this complexity by assessing the ability to respond, monitor, learn, and anticipate risks, and in so doing to move away from the flawed frequency and consequences approach. Using a research station network in the Arctic as an example illustrates how an RE approach qualifies assessments by bridging risk assessments with value-creation processes. The article concludes by arguing that a resilience-based risk assessment can improve on current practice, including for organizations located outside the Arctic region.