An Integrated Risk Assessment Model of Township‐Scaled Land Subsidence Based on an Evidential Reasoning Algorithm and Fuzzy Set Theory

Land subsidence risk assessment (LSRA) is a multi‐attribute decision analysis (MADA) problem and is often characterized by both quantitative and qualitative attributes with various types of uncertainty. Therefore, the problem needs to be modeled and analyzed using methods that can handle uncertainty. In this article, we propose an integrated assessment model based on the evidential reasoning (ER) algorithm and fuzzy set theory. The assessment model is structured as a hierarchical framework that regards land subsidence risk as a composite of two key factors: hazard and vulnerability. These factors can be described by a set of basic indicators defined by assessment grades with attributes for transforming both numerical data and subjective judgments into a belief structure. The factor‐level attributes of hazard and vulnerability are combined using the ER algorithm, which is based on the information from a belief structure calculated by the Dempster‐Shafer (D‐S) theory, and a distributed fuzzy belief structure calculated by fuzzy set theory. The results from the combined algorithms yield distributed assessment grade matrices. The application of the model to the Xixi‐Chengnan area, China, illustrates its usefulness and validity for LSRA. The model utilizes a combination of all types of evidence, including all assessment information—quantitative or qualitative, complete or incomplete, and precise or imprecise—to provide assessment grades that define risk assessment on the basis of hazard and vulnerability. The results will enable risk managers to apply different risk prevention measures and mitigation planning based on the calculated risk states.     

The Box–Cox Transformation and Non‐Iterative Estimation Methods for Ordinal Log‐Linear Models

Recently Beh and Farver investigated and evaluated three non‐iterative procedures for estimating the linear‐by‐linear parameter of an ordinal log‐linear model. The study demonstrated that these non‐iterative techniques provide estimates that are, for most types of contingency tables, statistically indistinguishable from estimates from Newton's unidimensional algorithm. Here we show how two of these techniques are related using the Box–Cox transformation. We also show that by using this transformation, accurate non‐iterative estimates are achievable even when a contingency table contains sampling zeros.     

Restoring sanity through comic relief: Parody television viewers and political outlook

Parody news programs regale viewers with satirical, witty, and humorous exposés of the political world and news coverage, but they have also been criticized for creating cynicism and political disengagement. This study found that parody news viewers are self-efficacious and more politically active than viewers of CNN, Fox News, MSNBC, or broadcast television news. Moreover, reliance on parody news shows does not lead to political polarization or government distrust.     

State Immigration Policies: The Role of State Compacts and Interest Groups on Immigration Legislation

US states are active in enacting immigration policies, which vary widely and have substantial impact on the lives of immigrants. Our understanding of what produces these divergent state laws remains limited. Qualitative research demonstrates the importance of a 2010 immigration compact, supported by a powerful religious organization, in shaping immigration policies in Utah, and the Utah Compact was held up as a model for other states. But is the experience of Utah applicable across other states? We test the effects of compacts and interest groups on immigration policy adoption across all 50 states between 2005 and 2013. Our findings suggest that compacts are actually associated with more restrictive immigration policy. Although states with compacts are more likely to pass inclusive immigration laws, these are counterbalanced by higher numbers of exclusive laws. Both religious and non‐religious interests groups are associated with policy, but they do not explain the effects of compacts.     

Does Hearing About Cancer Influence Stimulus Control? An Exploratory Study of Verbal Modulation of Stimulus Generalization

The Analysis of Verbal Behavior - Participants first became familiar with an image showing moderate symptoms of the skin cancer melanoma. In a generalization test, they indicated whether images...     

Exit or Voice? The Recent Drivers of Kosovar Out‐migration

A remarkable out‐migration from Kosovo occurred after the winter 2014/15, raising urgent questions about its underlying drivers and implications for both Kosovo and the destination countries. This article aims at providing a better understanding of key migration triggers and some particularities of the phenomenon. We link our empirically found migration drivers to Hirschman's ( 1970 ) famous exit, voice or loyalty scheme by asking in how far the exit must be understood as the explicit alternative to voicing dissatisfaction with the current situation in the country. According to our results, the recent Kosovar out‐migration is a clear response to weak governance and thus goes beyond the widespread ‘migration‐cum‐remittances’ livelihood practice. In this sense it could be interpreted as a revolt against the political system. With view to policy implications for destination countries, we point at legal travel and migration opportunities as the better solution to channel both voice and exit.     

Social identity and alcohol in young adolescence: the perceived difference between youthful and adult drinking

This paper examines the evolving social identities of young adolescents in regard to alcohol and drinking culture in Norway. Detailed analysis of 29 focus group interviews and 32 individual interviews with 12–13-year-olds reveal a thorough negative attitude towards alcohol, especially when enjoyed by young people. Young adolescents found young people to be too irresponsible and immature to drink, while adults were portrayed as capable of enjoying alcohol without losing control or experiencing other negative effects. Through symbolic boundary work, they distanced themselves from adolescents who drank. The young adolescents rejected the idea that drinking alcohol was a sign of maturity; instead, they exhibited maturity by distancing themselves from drunk adolescents. We discuss how these findings reflect the participants’ socio-cognitive development, and how symbolic boundaries are often drawn against those closest in social distance. We conclude that boundaries between ‘adolescents’ and ‘adults’ are fundamental when understanding emerging adolescent social identities, especially when it comes to drinking and drinking culture.     

Conditional covariance penalties for mixed models

The prediction error for mixed models can have a conditional or a marginal perspective depending on the research focus. We introduce a novel conditional version of the optimism theorem for mixed models linking the conditional prediction error to covariance penalties for mixed models. Different possibilities for estimating these conditional covariance penalties are introduced. These are bootstrap methods, cross-validation, and a direct approach called Steinian. The behavior of the different estimation techniques is assessed in a simulation study for the binomial-, the t-, and the gamma distribution and for different kinds of prediction error. Furthermore, the impact of the estimation techniques on the prediction error is discussed based on an application to undernutrition in Zambia.     

Building a Human Health Risk Assessment Ontology (RsO): A Proposed Framework

Over the last decade the health and environmental research communities have made significant progress in collecting and improving access to genomic, toxicology, exposure, health, and disease data useful to health risk assessment. One of the barriers to applying these growing volumes of information in fields such as risk assessment is the lack of informatics tools to organize, curate, and evaluate thousands of journal publications and hundreds of databases to provide new insights on relationships among exposure, hazard, and disease burden. Many fields are developing ontologies as a way of organizing and analyzing large amounts of complex information from multiple scientific disciplines. Ontologies include a vocabulary of terms and concepts with defined logical relationships to each other. Building from the recently published exposure ontology and other relevant health and environmental ontologies, this article proposes an ontology for health risk assessment (RsO) that provides a structural framework for organizing risk assessment information and methods. The RsO is anchored by eight major concepts that were either identified by exploratory curations of the risk literature or the exposure‐ontology working group as key for describing the risk assessment domain. These concepts are: (1) stressor, (2) receptor, (3) outcome, (4) exposure event, (5) dose‐response approach, (6) dose‐response metric, (7) uncertainty, and (8) measure of risk. We illustrate the utility of these concepts for the RsO with example curations of published risk assessments for ionizing radiation, arsenic in drinking water, and persistent pollutants in salmon.