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.     

Behavioral economics and the value of a statistical life

Journal of Risk and Uncertainty - There are many possible connections between the value of statistical life (VSL) and behavioral economics. A list of topics includes endowment effects, risk...     

Data-driven Kriging models based on FANOVA-decomposition

Kriging models have been widely used in computer experiments for the analysis of time-consuming computer codes. Based on kernels, they are flexible and can be tuned to many situations. In this paper, we construct kernels that reproduce the computer code complexity by mimicking its interaction structure. While the standard tensor-product kernel implicitly assumes that all interactions are active, the new kernels are suited for a general interaction structure, and will take advantage of the absence of interaction between some inputs. The methodology is twofold. First, the interaction structure is estimated from the data, using a first initial standard Kriging model, and represented by a so-called FANOVA graph. New FANOVA-based sensitivity indices are introduced to detect active interactions. Then this graph is used to derive the form of the kernel, and the corresponding Kriging model is estimated by maximum likelihood. The performance of the overall procedure is illustrated by several 3-dimensional and 6-dimensional simulated and real examples. A substantial improvement is observed when the computer code has a relatively high level of complexity.     

Dublin’s Seventeenth Century Parishes and the Quality of Life

Social Indicators Research - The registers of Dublin’s parishes in the seventeenth century provide access to aspects of civic and religious life. In the registers are records of burials,...     

ARE WORKERS WILLING TO PAY TO JOIN A BETTER TEAM?

Using data from the Major League Baseball free‐agent market, this study is the first to show that the productivity expected of the team a worker will join produces a significant, negative compensating wage differential. The younger workers in the sample drive this result, trading 25% of their wages to join teams with an expected productivity one standard deviation higher. This investment can be recouped if a reasonable increase in human capital occurs. These results are robust to contract length‐wage simultaneity and indicate that investment in human capital motivates the observed tradeoff, suggesting a new pathway through which human capital accumulation can affect wages. Reliable measures of workers' own past productivity and the productivity expected of a worker's future team provide key advantages to identifying these effects. (JEL J31, J24, M54)     

Demographic change and shifting views about marine resources and the coastal environment in Downeast Maine

Connections to the sea often define the character of coastal towns. However, as migrants arrive and economic diversification occurs, views about the use of marine resources and the ocean environment can change. Using survey data from Maine, we examined whether shifting demographics affect public perceptions of marine resource uses and coastal environmental concerns. We tested resource use and environmental items against a common set of demographic, background, and place-related variables. Results indicate that the level of education and the county of residence predict Mainers?? views about different marine resource uses and ocean-related environmental issues. Political party affiliation strongly influences environmental concern but not views about the use of marine resources. Migration history, on the other hand, has little effect. Understanding community contexts as well as individual background and ideological orientations will be critical as managers attempt to balance alternative uses of marine resources and resolve coastal environmental problems.