Strengthening Safety Compliance in Nuclear Power Operations: A Role‐Based Approach

Safety compliance is of paramount importance in guaranteeing the safe running of nuclear power plants. However, it depends mostly on procedures that do not always involve the safest outcomes. This article introduces an empirical model based on the organizational role theory to analyze the influence of legitimate sources of expectations (procedures formalization and leadership) on workers’ compliance behaviors. The sample was composed of 495 employees from two Spanish nuclear power plants. Structural equation analysis showed that, in spite of some problematic effects of proceduralization (such as role conflict and role ambiguity), procedure formalization along with an empowering leadership style lead to safety compliance by clarifying a worker's role in safety. Implications of these findings for safety research are outlined, as well as their practical implications.     

Conservation Management of EU Priority Habitats after Collapse of Traditional Pastoralism: Navigating Socioecological Transitions in Mountain Rangeland

Agricultural abandonment is a major driver of change in rural landscapes. Assumed to provide beneficial results to the environment and the conservation of biota, rural abandonment triggers landscape and biotic homogenization and loss of valuable species and habitats. This article focuses on the ecological effects and conservation challenges of shifts in extensive grazing regimes on marginal pastureland of Mediterranean mountains. We conceptualize a navigated socioecological transition toward conservation‐oriented management after the collapse of historical land systems. The article provides examples from the LIFE+ project “Higro,” developed in mountainous protected areas in Portugal, of how management for conservation could sustain disturbance‐dependent habitats. We argue that actively and regularly managing large habitat areas should be envisaged as a short‐term approach to limit the immediate effects of rural abandonment. A gradual integration of conservation targets with other activities in changing rural economies is necessary to foster long‐term conservation of species and habitats, building on the link between conservation‐oriented habitat management and ecosystem services in rural landscapes. Conservation goals should run alongside recovery of social systems and innovation applied to traditional sources of income. This parallel development would contribute to building up social‐ecological resilience by maintaining a diversity of social and ecological capital in rural areas.     

Comparing the performance of normality tests with ROC analysis and confidence intervals

There are several statistical hypothesis tests available for assessing normality assumptions, which is an a priori requirement for most parametric statistical procedures. The usual method for comparing the performances of normality tests is to use Monte Carlo simulations to obtain point estimates for the corresponding powers. The aim of this work is to improve the assessment of 9 normality hypothesis tests. For that purpose, random samples were drawn from several symmetric and asymmetric nonnormal distributions and Monte Carlo simulations were carried out to compute confidence intervals for the power achieved, for each distribution, by two of the most usual normality tests, Kolmogorov–Smirnov with Lilliefors correction and Shapiro–Wilk. In addition, the specificity was computed for each test, again resorting to Monte Carlo simulations, taking samples from standard normal distributions. The analysis was then additionally extended to the Anderson–Darling, Cramer-Von Mises, Pearson chi-square Shapiro–Francia, Jarque–Bera, D'Agostino and uncorrected Kolmogorov–Smirnov tests by determining confidence intervals for the areas under the receiver operating characteristic curves. Simulations were performed to this end, wherein for each sample from a nonnormal distribution an equal-sized sample was taken from a normal distribution. The Shapiro–Wilk test was seen to have the best global performance overall, though in some circumstances the Shapiro–Francia or the D'Agostino tests offered better results. The differences between the tests were not as clear for smaller sample sizes. Also to be noted, the SW and KS tests performed generally quite poorly in distinguishing between samples drawn from normal distributions and t Student distributions.     

LATIN AMERICAN IMMIGRATION TO SPAIN

On the whole, Latin American migration currently represents the highest percentage of migration into the Spanish state. This situation results from a series of factors, combined in both the points of origin and destination, and relating to the economic policies of the emitting and receiving countries within the framework of globalization. However, despite the way in which the phenomenon is portrayed by politicians and the media, this predominance is not due exclusively to the historical and cultural ties between Latin America and Spain, but rather to the implementation of a complex series of legal measures which contribute to the constant renewal of national collectives at the service of the labour markets in search of the desired ‘flexibility’ based on ethnic and gender segmentation of migrant workers.     

A land of the ‘fair go’? Intergenerational earnings elasticity in Australia

This paper contributes to the existing literature on income mobility by developing and applying a two‐stage panel regression model and assessing the effects of using different levels of occupational (dis)aggregation and different earnings measures on the magnitude of father–son earnings elasticities in Australia. We find that the overall intergenerational earnings elasticity in Australia between 2001 and 2013 ranges from 0.11 to 0.30. Our preferred estimates lie between 0.24 and 0.28. Elasticity estimates vary depending on the level of occupational (dis)aggregation and earnings measure used: they are highest when two‐digit level occupations and hourly earnings are used, and lowest when four‐digit level occupations and annual earnings are used. We read these findings as indicating that elasticity estimates are sensitive to the use of different data and methods, and researchers should be careful when undertaking cross‐study, cross‐temporal or cross‐national comparisons.     

Pickup Basketball in the Production of Black Community

Recent studies on basketball employ Elijah Anderson’s decent-street dichotomy. In these works, institutional basketball is “decent” and unifying, whereas pickup basketball is “street” and atomizing. Based on ethnographic research in New York City’s pickup basketball scene, this article argues that such an approach obscures many of the ways in which pickup basketball actually strengthens Black community. The article shows that through practice, contests, competitions, and its embeddedness in everyday life pickup basketball directly produces Black community by bringing together diverse people. Pickup basketball also indirectly produces community by: 1) articulating, enacting, and disseminating essential communal values; and 2) serving as a collective depot for information and support. In rejecting the institutional basketball-pickup basketball as decent-street binary, the article attempts to reorient the very understanding of pickup basketball and its place in the urban Black community.     

Deviance Residuals for an Angular Response

This paper discusses deviance residual approximations in von Mises regression models. By using a relationship between the von Mises and the wrapped normal distributions, the paper shows that the deviance component of the von Mises distribution is approximately a linear function of the standard normal distribution. Two standardized forms are proposed for the deviance residual, and a simulation study is performed to compare the approximation of the proposed residuals to the standard normal distribution. An illustrative example is given.     

Regularized estimation for highly multivariate log Gaussian Cox processes

Statistical inference for highly multivariate point pattern data is challenging due to complex models with large numbers of parameters. In this paper, we develop numerically stable and efficient parameter estimation and model selection algorithms for a class of multivariate log Gaussian Cox processes. The methodology is applied to a highly multivariate point pattern data set from tropical rain forest ecology.