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.     

The context of employment discrimination: interpreting the findings of a field experiment

Although field experiments have documented the contemporary relevance of discrimination in employment, theories developed to explain the dynamics of differential treatment cannot account for differences across organizational and institutional contexts. In this article, I address this shortcoming by presenting the main empirical findings from a multi‐method research project, in which a field experiment of ethnic discrimination in the Norwegian labour market was complemented with forty‐two in‐depth interviews with employers who were observed in the first stage of the study. While the experimental data support earlier findings in documenting that ethnic discrimination indeed takes place, the qualitative material suggests that theorizing in the field experiment literature have been too concerned with individual and intra‐psychic explanations. Discriminatory outcomes in employment processes seems to be more dependent on contextual factors such as the number of applications received, whether requirements are specified, and the degree to which recruitment procedures are formalized. I argue that different contexts of employment provide different opportunity structures for discrimination, a finding with important theoretical and methodological implications.     

Erroneous perceptions and arousal among regular and occasional video poker players

This study investigated the relationship between the level of arousal (Heart Rate) and the number of erroneous perceptions among video poker players. Twelve regular and twelve occasional gamblers participated in a gambling session conducted in a natural environment. It was hypothesised that 1) a significant positive correlation would be observed between arousal and the number of erroneous verbalizations, 2) regular players would show a higher level of arousal than occasional players, and 3) they would emit more erroneous verbalizations. Results showed that hypotheses one and three were confirmed. Theoretical and practical implications of these results for the psychology of gambling are discussed.This study was supported by a grant from Loto-Québec.     

民营企业发展中的企业家和企业家精神研究

本文回顾了国内外学者对企业家和企业家精神的研究, 讨论了转型时期民营企业家的生成和企业的行为特点, 并基于企业家理论对政府提出了相关的宏观政策建议。     

理想点法综合评价学生数学成绩

应用多目标决策———理想点法 ,建立了一个综合评价学生数学成绩的数学模型     

经济增长动因探析

一国的经济增长主要取决于技术进步、人力资本和制度创新等三个方面。技术进步是经济增长的驱动力 ,人力资本存量与质量是经济增长的关键 ,制度创新是经济增长的根源。此三者彼此密切关联、互动互进、共同推动经济增长     

Gendered Perspectives in Psychology: Immigrant Origin Youth

In this article, we contend that the field of psychology has largely failed to foreground the role of gender in its study of immigration. Here, we review studies that address gender and migration focusing on the experience of children and adolescents. We provide developmental perspectives on family relations, well‐being, identity formation, and educational outcomes, paying particular attention to the role of gender in these domains. We conclude with recommendations for future research, which include the need to consider whether, and if so, how, when, and why it makes a difference to be an immigrant, to be from a particular country, or to be female rather than male. We argue that it is important to consider socioeconomic characteristics; to consider resilience as well as pathology; and to work in interdisciplinary ways to deepen our understanding of the gendered migratory experience of immigrant origin youth.     

发展高新技术应处理好的六大关系

高新技术的成长发育离不开风险投资以及政府、市场的引导 ,离不开基础研究与人力资源的开发 ,更需要引进大量的资金及国外的先进技术 ,同时其发展也与传统产业的提升有着密不可分的关系 ,因此发展高新技术产业应在妥善处理好这些关系上下功夫