Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction

Damage models for natural hazards are used for decision making on reducing and transferring risk. The damage estimates from these models depend on many variables and their complex sometimes nonlinear relationships with the damage. In recent years, data‐driven modeling techniques have been used to capture those relationships. The available data to build such models are often limited. Therefore, in practice it is usually necessary to transfer models to a different context. In this article, we show that this implies the samples used to build the model are often not fully representative for the situation where they need to be applied on, which leads to a “sample selection bias.” In this article, we enhance data‐driven damage models by applying methods, not previously applied to damage modeling, to correct for this bias before the machine learning (ML) models are trained. We demonstrate this with case studies on flooding in Europe, and typhoon wind damage in the Philippines. Two sample selection bias correction methods from the ML literature are applied and one of these methods is also adjusted to our problem. These three methods are combined with stochastic generation of synthetic damage data. We demonstrate that for both case studies, the sample selection bias correction techniques reduce model errors, especially for the mean bias error this reduction can be larger than 30%. The novel combination with stochastic data generation seems to enhance these techniques. This shows that sample selection bias correction methods are beneficial for damage model transfer.     

Learning from a lot: Empirical Bayes for high‐dimensional model‐based prediction

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, stored in public repositories. We review applications of a variety of empirical Bayes methods to several well‐known model‐based prediction methods, including penalized regression, linear discriminant analysis, and Bayesian models with sparse or dense priors. We discuss “formal” empirical Bayes methods that maximize the marginal likelihood but also more informal approaches based on other data summaries. We contrast empirical Bayes to cross‐validation and full Bayes and discuss hybrid approaches. To study the relation between the quality of an empirical Bayes estimator and p, the number of variables, we consider a simple empirical Bayes estimator in a linear model setting. We argue that empirical Bayes is particularly useful when the prior contains multiple parameters, which model a priori information on variables termed “co‐data”. In particular, we present two novel examples that allow for co‐data: first, a Bayesian spike‐and‐slab setting that facilitates inclusion of multiple co‐data sources and types and, second, a hybrid empirical Bayes–full Bayes ridge regression approach for estimation of the posterior predictive interval.     

Klassen messen

The article investigates whether Austrian sociological research empirically addressed social class conceptions between 1945 and 1990. Contrary to the German reception, we find that, indeed, during the whole period scientific publications analyzed social relations and social change from a class perspective with an empirical approach. We embed this research in its historical context in order to work out the implicit explanations given concerning the existence of social inequalities. Moreover, we work out if post-World War II Austrian class analysis did link its work to the Austro-Marxist tradition that flourished between the two World Wars. The empirical focus of the article lies on scientific publications with an empirical approach to social classes and social change.     

A Grounded Theory of Sexual Minority Women and Transgender Individuals’ Social Justice Activism

Psychosocial benefits of activism include increased empowerment, social connectedness, and resilience. Yet sexual minority women (SMW) and transgender individuals with multiple oppressed statuses and identities are especially prone to oppression-based experiences, even within minority activist communities. This study sought to develop an empirical model to explain the diverse meanings of social justice activism situated in SMW and transgender individuals’ social identities, values, and experiences of oppression and privilege. Using a grounded theory design, 20 SMW and transgender individuals participated in initial, follow-up, and feedback interviews. The most frequent demographic identities were queer or bisexual, White, middle-class women with advanced degrees. The results indicated that social justice activism was intensely relational, replete with multiple benefits, yet rife with experiences of oppression from within and outside of activist communities. The empirically derived model shows the complexity of SMW and transgender individuals’ experiences, meanings, and benefits of social justice activism.     

The Welfare State as Safety Net in Migration Preferences: Empirical Evidence from an Experiment Among Dutch Master Students

Population Research and Policy Review - The welfare state can be perceived as a safety net which helps individuals adjust to situations of risk or transition. Starting from this idea of the welfare...     

Inequality Assessment by Probabilistic Development Indices

Social Indicators Research - This paper analyses the Human Development Index (HDI) time series from 2010 to 2017. An alternative index is studied, which combines the same components of the HDI by...     

Frustration in Infancy: Implications for Emotion Regulation,Physiological Processes,and Temperament

A study sample of 162 six‐month‐old children was selected from a larger sample of 346 infants on the basis of parents' report of their infants' temperament and a laboratory assessment of temperament. Infants were classified as easily frustrated and less easily frustrated and compared on a number of emotion regulation, physiology, and temperament measures. Results indicated that male and female infants were equally likely to be classified as frustrated and less easily frustrated; however, male infants were less able to regulate physiologically. Easily frustrated infants used different emotion regulation strategies and were observed to be less attentive and more active than less easily frustrated infants when observed in the laboratory. These infants were also characterized by their parents as more active, less attentive, and more distressed to novelty. Infants classified as easily frustrated were more reactive physiologically and less able to regulate physiological reactivity than their less easily frustrated counterparts. It is hypothesized that this cluster of characteristics may constitute a unique temperamental type that may have implications for other types of behavioral functioning. Limitations of the study are that observations are based on a single brief assessment of the infant, modest effect sizes were found, and the study is cross‐sectional.     

Best Practice Options: Yugoslavia

Several Cooperative Efforts to Manage Emigration (CEME) members visited the Federal Republic of Yugoslavia (FRY) in early June 2001 to examine the new Government's approach to migration issues. We found that both the Federal Government and the Serb Republic are faced with three principal issues related to immigration and refugees that require substantial cooperation with North American and European countries that are donors of international aid, as well as recipients of Yugoslav migrants and third country nationals transiting the FRY.
First, they are faced with migration issues that the international community considers priorities, including demilitarizing border management; combating human smuggling and trafficking; and drafting and implementing an aliens law, which includes asylum policies and procedures consistent with international standards.
Second, they need to plan for the return or integration of 350,000 refugees from Croatia and Bosnia, and another 150,000 internally displaced Yugoslavs from Kosovo, primarily by offering dual citizenship in the FRY, and Croatia and Bosnia so refugees can integrate in the FRY, but retain rights and privileges according to Croatians or Bosnians.
Third, it is important to build bridges to Yugoslavs abroad in order to attract remittances and the return of the professionals needed to rebuild the FRY.