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.     

Integrating Operational and Organizational Aspects in Interdependent Infrastructure Network Recovery

Managing risk in infrastructure systems implies dealing with interdependent physical networks and their relationships with the natural and societal contexts. Computational tools are often used to support operational decisions aimed at improving resilience, whereas economics‐related tools tend to be used to address broader societal and policy issues in infrastructure management. We propose an optimization‐based framework for infrastructure resilience analysis that incorporates organizational and socioeconomic aspects into operational problems, allowing to understand relationships between decisions at the policy level (e.g., regulation) and the technical level (e.g., optimal infrastructure restoration). We focus on three issues that arise when integrating such levels. First, optimal restoration strategies driven by financial and operational factors evolve differently compared to those driven by socioeconomic and humanitarian factors. Second, regulatory aspects have a significant impact on recovery dynamics (e.g., effective recovery is most challenging in societies with weak institutions and regulation, where individual interests may compromise societal well‐being). And third, the decision space (i.e., available actions) in postdisaster phases is strongly determined by predisaster decisions (e.g., resource allocation). The proposed optimization framework addresses these issues by using: (1) parametric analyses to test the influence of operational and socioeconomic factors on optimization outcomes, (2) regulatory constraints to model and assess the cost and benefit (for a variety of actors) of enforcing specific policy‐related conditions for the recovery process, and (3) sensitivity analyses to capture the effect of predisaster decisions on recovery. We illustrate our methodology with an example regarding the recovery of interdependent water, power, and gas networks in Shelby County, TN (USA), with exposure to natural hazards.     

Cross‐Sectional Psychological and Demographic Associations of Zika Knowledge and Conspiracy Beliefs Before and After Local Zika Transmission

Perceptions of infectious diseases are important predictors of whether people engage in disease‐specific preventive behaviors. Having accurate beliefs about a given infectious disease has been found to be a necessary condition for engaging in appropriate preventive behaviors during an infectious disease outbreak, while endorsing conspiracy beliefs can inhibit preventive behaviors. Despite their seemingly opposing natures, knowledge and conspiracy beliefs may share some of the same psychological motivations, including a relationship with perceived risk and self‐efficacy (i.e., control). The 2015–2016 Zika epidemic provided an opportunity to explore this. The current research provides some exploratory tests of this topic derived from two studies with similar measures, but different primary outcomes: one study that included knowledge of Zika as a key outcome and one that included conspiracy beliefs about Zika as a key outcome. Both studies involved cross‐sectional data collections that occurred during the same two periods of the Zika outbreak: one data collection prior to the first cases of local Zika transmission in the United States (March–May 2016) and one just after the first cases of local transmission (July–August). Using ordinal logistic and linear regression analyses of data from two time points in both studies, the authors show an increase in relationship strength between greater perceived risk and self‐efficacy with both increased knowledge and increased conspiracy beliefs after local Zika transmission in the United States. Although these results highlight that similar psychological motivations may lead to Zika knowledge and conspiracy beliefs, there was a divergence in demographic association.     

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...     

Journey towards independent living: a grounded theory investigation of leaving the care of Girls & Boys Town,South Africa

The journey out of care and towards independent living is a challenge for many care-leavers. There has been little research into the social processes involved in this care-leaving journey. This paper presents the results of a grounded theory investigation into the care-leaving journeys of nine young men who had, several years previously, been in the care of Girls & Boys Town in South Africa. Working from a resilience perspective, with an ecological emphasis, four central social processes emerged that together explain the care-leaving experiences of the participants. These processes are striving for authentic belonging; networking people for goal attainment; contextualised responsiveness and building hopeful and tenacious self-confidence. These four processes are located within contextual boundaries and at the social environmental interface. The paper presents these processes in detail, drawing on selected narratives of the participants and integrated with additional theory. It is hoped that this paper may contribute to theory building concerning care-leaving processes and enhance youth care practices for youth in care and leaving care.     

Hidden Resources and Barriers in Career Learning Assessment With Adolescents Vulnerable to Discrimination

The authors maintain that the social learning theory of career development and counseling has not been applied to diverse populations. To address this gap in the literature, the authors conducted a qualitative analysis of interviews with 21 middle school students in a low‐income, culturally diverse, inner‐city public school. Four themes emerged, reflecting the influence of discrimination on participants' career learning: contextual barriers and resources for learning, and psychological barriers and resources for learning. The authors provide a conceptual framework for assessing resources and barriers and a rationale for why these aspects often remain hidden or unexamined in career assessment with clients who are vulnerable to discrimination.     

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.     

The African Evaluation Guidelines: 2002. A checklist to assist in planning evaluations, negotiating clear contracts, reviewing progress and ensuring adequate completion of an evaluation

A review of the US ‘program evaluation standards’ (PES), undertaken in a series of workshops and meetings of networks of evaluators in Africa, resulted in modifications to those standards. The result was presented to a plenary session of the Inaugural Conference of the African Evaluation Association in September 1999, attended by over 300 evaluators from 35 countries. The AfrEA Conference decided that a systematic effort should be made to produce a list of African evaluation guidelines, similar to the PES, and that this checklist should be reviewed by national evaluation associations and networks in Africa and field tested in several countries. Ten national and regional networks and associations suggested modifications to the text and endorsed the final version of the guidelines.