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.     

A new generalized Weibull distribution in income economic inequality curves

Researchers have been developing various extensions and modified forms of the Weibull distribution to enhance its capability for modeling and fitting different data sets. In this note, we investigate the potential usefulness of the new modification to the standard Weibull distribution called odd Weibull distribution in income economic inequality studies. Some mathematical and statistical properties of this model are proposed. We obtain explicit expressions for the first incomplete moment, quantile function, Lorenz and Zenga curves and related inequality indices. In addition to the well-known stochastic order based on Lorenz curve, the stochastic order based on Zenga curve is considered. Since the new generalized Weibull distribution seems to be suitable to model wealth, financial, actuarial and especially income distributions, these findings are fundamental in the understanding of how parameter values are related to inequality. Also, the estimation of parameters by maximum likelihood and moment methods is discussed. Finally, this distribution has been fitted to United States and Austrian income data sets and has been found to fit remarkably well in compare with the other widely used income models.     

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.     

Enterprising? Disabled? The status and potential for disabled people’s microenterprise in South Korea

This article explores the position, potential and scope for self-employment and microenterprise for disabled South Koreans. The chronic barriers experienced in disabled people gaining paid work suggest that self-employment and enterprise might offer a good alternative to paid work. The self-determined nature of running a microenterprise has been shown to connect with disabled people who may not conform to standardised notions of body and brain that underpin many mainstream work contexts. Despite this promise, several barriers continue to beset disabled people’s access to micro-enterprise activity; barriers ranging from Confucian precepts, to employment protections that are geared largely towards paid employment and to the lack of training, finance and business support for disabled people starting up and sustaining microenterprise in Korea. The extension of legal protections, meaningful start-up subsidies, better business support and bridges between paid work and microenterprise are all seen as important policy correctives that would better support disabled people.     

Marxist sociology and humanist sociology: Diversity, intersections, and convergence

Marxist sociology is at the intersection of Marxism and sociology; while humanist sociology is at the intersection of humanist thought and sociology. Both see sociological theory as a living, evolving activity, and both take a critical stance toward the workings of capitalism. The main difference between them is that Marxist sociology is a body of thought tied to a movement, whereas humanist sociology is a movement tied to a body of thought. Professor of Sociology, Purdue University Calumet. He is past chair of the Section on Marxist Sociology, has been a member of the AHS for twenty years, and is co-author of Crisis and Change: Basic Questions of Marxist Sociology.