Not Just about Posttraumatic Stress Disorder: A Call for Military-Centric Social Work

Most warriors do not get PTSD but can still be affected by war. The “military gestalt,” defined as the complex myriad of “all things military” including the functions, processes, and human elements related to combat, is seriously impacted by the warrior-in-combat construct that is reflective of the person-in-environment construct. Thus, it suggests that problems within the gestalt can be understood and addressed from a military-centric social work perspective and approach. The situation is so insidious that it requires a call to action from all disciplines but, most important, for the social work profession to take the lead.     

Inference in hybrid Bayesian networks using dynamic discretization

We consider approximate inference in hybrid Bayesian Networks (BNs) and present a new iterative algorithm that efficiently combines dynamic discretization with robust propagation algorithms on junction trees. Our approach offers a significant extension to Bayesian Network theory and practice by offering a flexible way of modeling continuous nodes in BNs conditioned on complex configurations of evidence and intermixed with discrete nodes as both parents and children of continuous nodes. Our algorithm is implemented in a commercial Bayesian Network software package, AgenaRisk, which allows model construction and testing to be carried out easily. The results from the empirical trials clearly show how our software can deal effectively with different type of hybrid models containing elements of expert judgment as well as statistical inference. In particular, we show how the rapid convergence of the algorithm towards zones of high probability density, make robust inference analysis possible even in situations where, due to the lack of information in both prior and data, robust sampling becomes unfeasible.     

Heterosexuals' attitudes toward hate crimes and hate speech against gays and lesbians: old-fashioned and modern heterosexism

Modern racism and sexism have been studied to examine the different ways that prejudice can be expressed; yet, little attention has been given to modern heterosexism. This study examined the extent to which modern heterosexism and old-fashioned heterosexism predict acceptance of hate crimes against gays and lesbians and perceptions of hate speech. Male (n = 74) and female (n = 95) heterosexual college students completed a survey consisting of scales that assessed modern and old-fashioned heterosexism, acceptance of violence against gays and lesbians, attitudes toward the harm of hate speech and its offensiveness, and the importance of freedom of speech. Results indicated strong negative relations between both modern and old-fashioned heterosexism and the perceived harm of hate speech. When old-fashioned heterosexism,modern heterosexism, and the importance of freedom of speech were combined to predict hate crime and hate speech attitudes, only old-fashioned heterosexism predicted acceptance of hate crimes. All three predictors contributed to the perception of the harm of hate speech. Gender differences in the role of the importance of freedom of speech in predicting attitudes toward hate crimes and hate speech are noted.     

Evaluating and Visualizing the Economic Impact of Commercial Districts Due to an Electric Power Network Disruption

Critical infrastructure networks enable social behavior, economic productivity, and the way of life of communities. Disruptions to these cyber–physical–social networks highlight their importance. Recent disruptions caused by natural phenomena, including Hurricanes Harvey and Irma in 2017, have particularly demonstrated the importance of functioning electric power networks. Assessing the economic impact (EI) of electricity outages after a service disruption is a challenging task, particularly when interruption costs vary by the type of electric power use (e.g., residential, commercial, industrial). In contrast with most of the literature, this work proposes an approach to spatially evaluate EIs of disruptions to particular components of the electric power network, thus enabling resilience‐based preparedness planning from economic and community perspectives. Our contribution is a mix‐method approach that combines EI evaluation, component importance analysis, and GIS visualization for decision making. We integrate geographic information systems and an economic evaluation of sporadic electric power outages to provide a tool to assist with prioritizing restoration of power in commercial areas that have the largest impact. By making use of public data describing commercial market value, gross domestic product, and electric area distribution, this article proposes a method to evaluate the EI experienced by commercial districts. A geospatial visualization is presented to observe and compare the areas that are more vulnerable in terms of EI based on the areas covered by each distribution substation. Additionally, a heat map is developed to observe the behavior of disrupted substations to determine the important component exhibiting the highest EI. The proposed resilience analytics approach is applied to analyze outages of substations in the boroughs of New York City.     

Information and Efficiency in Tender Offers

We analyze tender offers where privately informed shareholders are uncertain about the raider's ability to improve firm value. The raider suffers a “lemons problem” in that, for any price offered, only shareholders who are relatively pessimistic about the value of the firm tender their shares. Consequently, the raider finds it too costly to induce shareholders to tender when their information is positive. In the limit as the number of shareholders gets arbitrarily large, when private benefits are relatively low, the tender offer is unsuccessful if the takeover has the potential to create value. The takeover market is therefore inefficient. In contrast, when private benefits of control are high, the tender offer allocates the firm to any value‐increasing raider, but may also allow inefficient takeovers to occur. Unlike the case where all information is symmetric, shareholders cannot always extract the entire surplus from the acquisition.     

Stochastic Measures of Network Resilience: Applications to Waterway Commodity Flows

Given the ubiquitous nature of infrastructure networks in today's society, there is a global need to understand, quantify, and plan for the resilience of these networks to disruptions. This work defines network resilience along dimensions of reliability, vulnerability, survivability, and recoverability, and quantifies network resilience as a function of component and network performance. The treatment of vulnerability and recoverability as random variables leads to stochastic measures of resilience, including time to total system restoration, time to full system service resilience, and time to a specific α% resilience. Ultimately, a means to optimize network resilience strategies is discussed, primarily through an adaption of the Copeland Score for nonparametric stochastic ranking. The measures of resilience and optimization techniques are applied to inland waterway networks, an important mode in the larger multimodal transportation network upon which we rely for the flow of commodities. We provide a case study analyzing and planning for the resilience of commodity flows along the Mississippi River Navigation System to illustrate the usefulness of the proposed metrics.     

The Relevance of Organizational Structure to NGOs’ Approaches to the Policy Process

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - NGOs are recognized as active participants in the policy process. There is general agreement that they are agenda setters...