Evaluating and Visualizing the Economic Impact of Commercial Districts Due to an Electric Power Network Disruption

Critical infrastructure networks enable social behavior, economic productivity, and the way of life of communities. Disruptions to these cyber–physical–social networks highlight their importance. Recent disruptions caused by natural phenomena, including Hurricanes Harvey and Irma in 2017, have particularly demonstrated the importance of functioning electric power networks. Assessing the economic impact (EI) of electricity outages after a service disruption is a challenging task, particularly when interruption costs vary by the type of electric power use (e.g., residential, commercial, industrial). In contrast with most of the literature, this work proposes an approach to spatially evaluate EIs of disruptions to particular components of the electric power network, thus enabling resilience‐based preparedness planning from economic and community perspectives. Our contribution is a mix‐method approach that combines EI evaluation, component importance analysis, and GIS visualization for decision making. We integrate geographic information systems and an economic evaluation of sporadic electric power outages to provide a tool to assist with prioritizing restoration of power in commercial areas that have the largest impact. By making use of public data describing commercial market value, gross domestic product, and electric area distribution, this article proposes a method to evaluate the EI experienced by commercial districts. A geospatial visualization is presented to observe and compare the areas that are more vulnerable in terms of EI based on the areas covered by each distribution substation. Additionally, a heat map is developed to observe the behavior of disrupted substations to determine the important component exhibiting the highest EI. The proposed resilience analytics approach is applied to analyze outages of substations in the boroughs of New York City.     

The Value of a Statistical Life for Risk‐Averse and Risk‐Seeking Individuals

This article estimates the value of a statistical life (VSL) for Chile under the hedonic wage method while accounting for individual risk preferences. Two alternative measures of risk aversion are used. First, risk aversion is directly measured using survey measures of preferences over hypothetical gambles, and second, over observed individual behaviors that may proxy for risk preferences, such as smoking status, are used. I reconcile the results with a theoretical model of economic behavior that predicts how the wage‐risk tradeoff changes as risk aversion differs across individuals. The VSL estimates range between 0.61 and 8.68 million dollars. The results using smoking behavior as a proxy for risk attitudes are consistent with previous findings. However, directly measuring risk aversion corrects the wage‐risk tradeoff estimation bias in the opposite direction. The results are robust to other observed measures of risk aversion such as drinking behavior and stock investments. Results suggest that, consistent with the literature that connects smoking behavior with labor market outcomes, smoking status could be capturing poor health productivity effect in addition to purely risk preferences.     

Beyond Neighborhoods and Crime: Expanding the Scope of Social Disorganization to Explain Occupational Deviance

This article proposes a structural explanation for the occupational deviance dimension of white collar crime. The systemic model of social disorganization theory is used as a framework for understanding organizational conditions that produce high rates of occupational deviance. The model of workplace disorganization proposed here posits parallel mechanisms can be found in communities as well as organizations. Marginalized workplaces, employee turnover, and employee heterogeneity are antecedent factors that discourage employee network formation and collective action against deviance. By refocusing on organizational factors, we offer a broader understanding of occupational deviance, one that can predict and explain the workplace conditions under which counterproductive behaviors occur.     

Interpersonal and Societal Mattering in Work: A Review and Critique

The need exists for a comprehensive literature review of the concept of mattering with regard to work. In response, this review examined a theoretical framework of societal and interpersonal mattering, mattering within the work context, and existing psychometric measures of mattering. The author analyzed the research on the current state of mattering at work, identified core frameworks and psychometric issues that have been investigated to date, and suggests the use of a more comprehensive framework for work mattering that illuminates both the relational and social aspects of the work experience. Several promising directions for future research and potential benefits of incorporating work mattering in career counseling practice emerged and are discussed.     

Stepchildren's Views About Former Step‐Relationships Following Stepfamily Dissolution

Remarriages end in divorce more often than first marriages, so many stepchildren experience multiple parental divorces and the potential loss of significant family ties. Although there is substantial research on parent–child relationships after divorce, little is known about stepparent–stepchild relationships after divorce. Therefore, the authors conducted a grounded theory study of 41 adults who had undergone a stepfamily dissolution to explore their experiences with former stepparents. Postdivorce relationships with former stepparents are a function of whether stepchildren thought of their former stepparents as kin. Postdivorce step‐relationships were based on whether the stepchild had claimed the stepparent as kin, had once claimed them as kin but disclaimed them after the divorce, or had never claimed them as family members (unclaimed stepparents). Emotional reactions to parental divorce, patterns of support or resource exchanges, and parental encouragement or discouragement for continuing step‐relationships were identified. Implications for families, practitioners, and researchers are discussed.     

“I Don’t Want to Work in Agriculture!” The Transition from Agricultural Education to the Labor Market in Rural Russia

In Russia, the shift in career incentives from agriculture‐related jobs to other sectors, even among agriculturally educated students, presents two main challenges to rural labor markets. The first relates to the shortage of agricultural employees. The second concerns difficulties in the school‐to‐work transition, characterized by long periods of unemployment. This article addresses these challenges by studying the career incentives of postsecondary agriculturally educated students, based on data from the Altai region, Siberia (N = 474). We use a logit regression to predict the probability of career transition, given the incentives. We examine whether familial background and life expectations are associated with plans to pursue a career in agriculture within a life course context. The results show that students’ career plans with respect to agriculture vary according to both sociofamilial background and views about one’s life course.     

All about ideology? Reading Piketty´s with Latin American lenses

This review essay evaluates Capital and Ideology in light of the Latin American experience. Given its history of exploitation and high levels of inequality, the region constitutes an essential case study. By considering the Latin America case, we can also benefit from the many insights coming from within the region and often overlooked by the Anglo‐Saxon (dominant) literature. The paper makes two different arguments. First, asymmetries in economic and political power are the main drivers of long‐term inequality. Following insights from structuralism, I show how the organization of the global economy has shaped domestic patterns of income distribution in many parts of the world. The dependent character of economic development together with the power of domestic elites explain Latin America's stubborn inequality; ideology has historically been more an instrument than an underlying driver. Second, we cannot understand the evolution of income distribution without considering the role of dictatorships. While Capital and Ideology explains convincingly why liberal democracies are not working, it never properly considers the risk and costs of (conservative) authoritarian regimes. In thinking about policy responses, the essay also highlights the importance of strengthening democracy, fighting dictatorships, and enhancing the influence of social movements.     

Does Remittance Outflow Stimulate or Retard Economic Growth?

This article evaluates the association between remittance outflow (RMO) and economic growth in the Gulf Cooperation Council (GCC) countries. The results of this evaluation indicate that RMO Granger creates gross domestic product (GDP) per capita in three countries, namely, Bahrain, Oman and Saudi Arabia. Similarly, the results for causality from GDP per capita to RMO are significant for four countries, namely, Bahrain, Kuwait, Qatar, and Saudi Arabia. The findings differ from those of the household consumption model, stating that higher RMO will decrease economic activity. GDP per capita is the main determinant of RMO, suggesting that economic growth promises and encourages continuous RMO and vice versa. The adverse impact of RMO can be minimized by encouraging the local population to be productive in the private sector, as local productivity will reduce the huge influx of foreign workers and provide valuable local investment opportunities to lessen the amount being remitted.     

Children’s reasoning about unequal gender‐based distributions

Children ages 7 (N = 56, M_age = 7.24, SD = 0.83), 9 (N = 55, M_age = 9.25, SD = 0.52), and 11 (N = 52, M_age = 11.60, SD = 0.79), and emerging adults (N = 50, M_age = 20.76, SD = 0.87) judged distributions of different items to boys and girls, when the items distributed varied by gender valence (related or unrelated to gender norms) and equivalency (equivalent or unequal). Distributions were judged to be acceptable most when the items were consistent with gender norms, especially for participants at ages 7 and 9, indicating that in middle childhood, children judge unequal treatment as fair when it is related to gender norms. Items were judged to be more likable when they were gendered, and likability judgments predicted more positive evaluations of the distributions, even when controlling for age.     

Application of the Hyper‐Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes

The hyper‐Poisson distribution can handle both over‐ and underdispersion, and its generalized linear model formulation allows the dispersion of the distribution to be observation‐specific and dependent on model covariates. This study's objective is to examine the potential applicability of a newly proposed generalized linear model framework for the hyper‐Poisson distribution in analyzing motor vehicle crash count data. The hyper‐Poisson generalized linear model was first fitted to intersection crash data from Toronto, characterized by overdispersion, and then to crash data from railway‐highway crossings in Korea, characterized by underdispersion. The results of this study are promising. When fitted to the Toronto data set, the goodness‐of‐fit measures indicated that the hyper‐Poisson model with a variable dispersion parameter provided a statistical fit as good as the traditional negative binomial model. The hyper‐Poisson model was also successful in handling the underdispersed data from Korea; the model performed as well as the gamma probability model and the Conway‐Maxwell‐Poisson model previously developed for the same data set. The advantages of the hyper‐Poisson model studied in this article are noteworthy. Unlike the negative binomial model, which has difficulties in handling underdispersed data, the hyper‐Poisson model can handle both over‐ and underdispersed crash data. Although not a major issue for the Conway‐Maxwell‐Poisson model, the effect of each variable on the expected mean of crashes is easily interpretable in the case of this new model.