Some alternative bivariate Kumaraswamy models

In this article we discuss various strategies for constructing bivariate Kumaraswamy distributions. As alternatives to the Nadarajah et al. (2011) bivariate model, four different models are introduced utilizing a conditional specification approach, a conditional survival function approach, and an Arnold–Ng bivariate beta distribution construction approach. Distributional properties for such bivariate distributions are investigated. Parameter estimation strategies for the models are discussed, as are the consequences of fitting two of the models to a particular data set involving the proportion of foggy days at two different airports in Colombia.     

‘The extreme end of a spectrum of violence’: physical abuse,hegemony and resistance in British residential care

While researching the history of traditional child care institutions – children's homes, orphanages, industrial schools and reformatories – the author was impressed by the similarities of regimen across the spectrum of traditional care. Underpinning all forms of care was a severe discipline which often became abusive. Sexual abuse was also reasonably common. There were differences but it is the similarities which are stressed in this article, which seeks reasons for the perceived sameness. Children in care came mostly from the same deprived social background, and no matter what the intentions of the carers, traditional care involved a confrontation with cherished working class values which many of the children were bound to resist. Resistance was met by severe staff reaction; hence the violent undercurrent. Copyright © 2001 John Wiley & Sons, Ltd.     

Alternative Methods for Computing the Sensitivity of Complex Surveillance Systems

Stochastic scenario trees are a new and popular method by which surveillance systems can be analyzed to demonstrate freedom from pests and disease. For multiple component systems—such as a combination of a serological survey and systematically collected observations—it can be difficult to represent the complete system in a tree because many branches are required to represent complex conditional relationships. Here we show that many of the branches of some scenario trees have identical outcomes and are therefore redundant. We demonstrate how to prune branches and derive compact representations of scenario trees using matrix algebra and Bayesian belief networks. The Bayesian network representation is particularly useful for calculation and exposition. It therefore provides a firm basis for arguing disease freedom in international forums.     

Community change for diverse democracy

This paper presents ideas about community change for diversedemocracy. It provides perspectives on change, identifies threetypes of practice, and examines some of its elements. It drawsupon secondary literature and empirical studies of practicein various communities and concludes with observations aboutfuture work in the field, with the general conclusion that democraticsocieties, especially ones whose populations are becoming morediverse, will depend in part on their ability to both recognizedifferences and also build bridges across cultural boundaries.The paper is based on the belief that strengthening the studyof these phenomena can contribute to their practice.     

The Aesthetics of Aircraft Safety Cards: Spatial Negotiations and Affective Mobilities in Diagrammatic Instructions

Instructional diagrams encountered during transit, such as the aircraft safety card, employ a range of visual elements that direct us how to move and what actions we need to undertake. However, instructions are not always easy to decipher and comprehension rates suggest that there is potential for misinterpretation. The complexity of instructions and mismatching of visual techniques give rise to an aesthetics of transit that coordinates spatial experiences and movements. Using examples from aircraft safety cards and artworks based on this format, this paper analyses how ‘transit aesthetics’ can give rise to affective experiences of spatial and mobile relationships.     

Construction of bivariate and multivariate weighted distributions via conditioning

Weighted distributions (univariate and bivariate) have received widespread attention over the last two decades because of their flexibility for analyzing skewed data. In this article, we propose an alternative method to construct a new family of bivariate and multivariate weighted distributions. For illustrative purposes, some examples of the proposed method are presented. Several structural properties of the bivariate weighted distributions including marginal distributions together with distributions of the minimum and maximum, evaluation of the reliability parameter, and verification of total positivity of order two are also presented. In addition, we provide some multivariate extensions of the proposed models. A real-life data set is used to show the applicability of these bivariate weighted distributions.