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.     

Constructing Trustworthy Historical Narratives: Criteria,Principles and Techniques

Organizational scholars increasingly recognize the value of employing historical research. Yet the fields of history and organization studies struggle to reconcile. In this paper, the authors contend that a closer connection between these two fields is possible if organizational historians bring their role in the construction of historical narratives to the fore and open up their research decisions for discussion. They provide guidelines to support this endeavor, drawing on four criteria that are prevalent within interpretive organization studies for developing the trustworthiness of research: credibility; confirmability; dependability; and transferability. In contrast to the traditional use of trustworthiness criteria to evaluate the quality of research, the authors advance the criteria to encourage historians to generate more transparent narratives. Such transparency allows others to comprehend and comment on the construction of narratives, thereby building trust and understanding. Each criterion is converted into a set of guiding principles to enhance the trustworthiness of historical research, pairing each principle with a practical technique gleaned from a range of disciplines within the social sciences to provide practical guidance.     

Has Opposition to Immigration Increased in the United States after the Economic Crisis? An Experimental Approach

We employ two population‐level experiments to accurately measure opposition to immigration before and after the economic crisis of 2008. Our design explicitly addresses social desirability bias, which is the tendency to give responses that are seen favorably by others and can lead to substantial underreporting of opposition to immigration. We find that overt opposition to immigration, expressed as support for a closed border, increases slightly after the crisis. However, once we account for social desirability bias, no significant increase remains. We conclude that the observed increase in anti‐immigration sentiment in the post‐crisis United States is attributable to greater expression of opposition rather than any underlying change in attitudes.     

A new long-term survival model with dispersion induced by discrete frailty

Lifetime Data Analysis - Frailty models are generally used to model heterogeneity between the individuals. The distribution of the frailty variable is often assumed to be continuous. However, there...     

Predicting the Risk of Biological Invasions Using Environmental Similarity and Transport Network Connectedness

Understanding the risk of biological invasions associated with particular transport pathways and source regions is critical for implementing effective biosecurity management. This may require both a model for physical connectedness between regions, and a measure of environmental similarity, so as to quantify the potential for a species to be transported from a given region and to survive at a destination region. We present an analysis of integrated biosecurity risk into Australia, based on flights and shipping data from each global geopolitical region, and an adaptation of the “range bagging” method to determine environmental matching between regions. Here, we describe global patterns of environmental matching and highlight those regions with many physical connections. We classify patterns of global invasion risk (high to low) into Australian states and territories. We validate our analysis by comparison with global presence data for 844 phytophagous insect pest species, and produce a list of high‐risk species not previously known to be present in Australia. We determined that, of the insect pest species used for validation, the species most likely to be present in Australia were those also present in geopolitical regions with high transport connectivity to Australia, and those regions that were geographically close, and had similar environments.     

Exploring Social and Geographical Trajectories of Latin Americans in Sweden

Close to 20 percent of the Swedish population are of immigrant origin; one in eight is foreign‐born. About 45 percent of all immigrants originate from outside Europe and most of these have entered the country as refugees or relatives of refugees. Issues connected to immigration, including the number of immigrants, settlement patterns and level of social integration of ethnic minorities, have been much discussed in Sweden in recent decades. This paper focuses on the integration of Latin American immigrants in Sweden. It compares the level of integration – measured as educational achievement, labour market participation, income and housing – experienced by first and second generation migrants. I use register information allowing me to include all 1^st and 2^nd generation Latin Americans that have lived in Sweden between 1990 and 2006 (in total 127,000 individuals). Data are longitudinal, which means that individuals can be followed over time. I make use of the longitudinal material in order to study changes in residential patterns and in attempts to explain educational and employment outcomes for second generation Latin Americans. The general conclusion of the paper is that in terms of integration, LAC immigrants have an intermediate position compared to other immigrant categories; they are often better off than people from Africa and the Middle East but clearly below the level experienced by some other migrants, especially those from Western Europe. This cannot be explained by level of education. The average level of education is high for first generation immigrants from LA countries. For many people, the level of labour market participation and income increase over time but one important result of this analysis is that second generation Latin Americans seem to do less well in Sweden compared to many other second generation migrants.     

Aging in the Era of Regenerative Medicine: Analysis of Aging‐Related Representations among Canadian Researchers

Explicitly aimed at understanding and controlling molecular and cellular processes at the root of senescence and biological aging, regenerative medicine aspires to artificially reproduce the biological processes that enable the body to regenerate itself. This no longer involves conserving the body's state of balance by combating disease, as in clinical medicine, but rather fighting degeneration itself. From stem cell research to gene therapy to the production of replacement tissues, regenerative medicine perfectly corresponds to the logic of biomedicalization specific to postmodern society. Based on a series of 18 interviews conducted with Canadian researchers and clinicians in the field of regenerative medicine, this article seeks to understand representations of the aging body among researchers in this field. Seen from a strictly negative angle, aging is assimilated by researchers to an inevitable catastrophe that nevertheless must be combated. More closely observing the theoretical model of regenerative biology and the types of treatments developed, it can be observed, however, that this medicine of the future does not target the elderly, but rather promises youth the ability to regenerate themselves to avoid aging.