Global System Theory and ‘Market-friendly’ Religion

This article explores some implications of the interplay of neoliberal economic policy and religion for Leslie Sklair's global system theory (GST), and some implications of Sklair's theory for the study of contemporary religion. We first suggest that Sklair needlessly restricted his theory's scope by analyzing culture in terms of consumerist ideologies without systematic consideration of religious doctrines and practices. Second, based on studies of ‘market Islam’ and our own research on neo-Pentecostal Christianity in Guatemala, we argue that Sklair's notion of a transnational capitalist class is needed for an adequate understanding of the rapid growth of these religious movements. We conclude that GST can benefit from consideration of contemporary religious change, while the study of contemporary religion has perhaps even more to gain from theorizing the influence of transnational elites.     

On Decomposition and Aggregation Error in Estimation: Some Basic Principles and Examples

A common strategy in estimation is to decompose the quantity being estimated into several factors, estimate a value for each factor, and then reaggregate these values to obtain an overall estimate. Until now, the extent of decomposition to use has been considered largely a matter of judgment. However, both the extent of decomposition and the manner in which the results are reaggregated can have a significant effect on the resulting estimate. This paper discusses factors affecting the optimum level of decomposition, and presents examples showing that the use of nonoptimal decomposition strategies can lead to significant inaccuracies.     

On designing new optimal synthetic Tukey’s control charts

Tukey’s control chart is generally used for monitoring the processes where the measurement process physically damages the product. It is based on single observation and robust to outliers. In this paper, two optimal synthetic Tukey’s control charts are proposed by integrating the conforming run length chart with the Tukey’s control chart and its modification. The performance comparison of the proposed charts with the existing Tukey’s control charts is made by using out-of-control average run length and extra quadratic loss as performance metrics. The proposed charts offer better protection against the process shifts as compare to the existing Tukey’s control charts when the underlying process distribution is symmetric or asymmetric. Simulation studies also establish the supremacy of the proposed control charts over the existing Tukey’s control charts. In the end, an illustrative example based on a real data set of the combined cycle power plant is provided for practical implementation.     

Is this what depression looks like? Visual narratives of depression on social media

Humans are inherent storytellers that in turn shapes our identity. The tendency to talk about health and illness is called ‘illness narratives.’ Most research on illness narratives is generated from diaries, interviews, and surveys. However, text is not the only means of expression. An alternative is to produce images of illness, known as ‘visual illness narratives.’ Depression is a common and serious illness, which can lead to serious health hazards. Despite the increased use of images on social media, little research has been done on visual narratives of depression. The current study examines such illness narratives elicited through images on Tumblr. Fourteen patients with moderately severe depression (Mean age = 27), mostly female (N = 12) were recruited from a counselling centre. Participants were presented with 72 depression-related images from Tumblr in a semi-structured interview. Participants sorted the images into three piles, based on personal relevance, and then talked in detail about each image. Inductive thematic analysis identified six themes providing rich insights into participants’ depressive states, dysfunctional thoughts, suicidal ideation, lifestyle changes, help-seeking, and social struggles. The study offers insights to improve care for depressed individuals using visuals of depression on social media.     

Variable selection in gamma regression models via artificial bee colony algorithm

Variable selection is an important task in regression analysis. Performance of the statistical model highly depends on the determination of the subset of predictors. There are several methods to select most relevant variables to construct a good model. However in practice, the dependent variable may have positive continuous values and not normally distributed. In such situations, gamma distribution is more suitable than normal for building a regression model. This paper introduces an heuristic approach to perform variable selection using artificial bee colony optimization for gamma regression models. We evaluated the proposed method against with classical selection methods such as backward and stepwise. Both simulation studies and real data set examples proved the accuracy of our selection procedure.     

An Arab perspective on social media: How banks in Kuwait use instagram for public relations

This study examines the public relations functions of eight Kuwaiti banks listed in the Kuwait Stock Exchange Market (KSEM) that post on their Instagram accounts. It also uses market-size, organization, and individual level predictors to model Instagram postings. A content analysis of 1502 posts revealed the banks use Instagram for promotion, information dissemination, community building, and interactive engagement, in that order of prominence. The findings suggest banks operate at the confluence of visual communication through Instagram and integration of religious symbolism to serve a public relations function predicated on image and influence. In doing so, the banks tap into the wellspring of social media use by target publics by navigating a balance between obedience to Allah and meeting bank business objectives. The resulting tension between sacred and secular highlights Arab cultural values and suggests Instagram fosters individualism, which challenges Arab emphasis on collectivism and fractures the notion online platforms can effectively build meaningful relationships that characterize Arab culture. The study posits Instagram is more effective in an Arab context at image building than relationship building, threading the importance of visual communication through social media across Arab culture and global public relations practices.     

Addressing the effect of parameter estimation on phase II monitoring of multivariate multiple linear profiles via a new cluster-based approach

Abstract

Profile monitoring is applied when the quality of a product or a process can be determined by the relationship between a response variable and one or more independent variables. In most Phase II monitoring approaches, it is assumed that the process parameters are known. However, it is obvious that this assumption is not valid in many real-world applications. In fact, the process parameters should be estimated based on the in-control Phase I samples. In this study, the effect of parameter estimation on the performance of four Phase II control charts for monitoring multivariate multiple linear profiles is evaluated. In addition, since the accuracy of the parameter estimation has a significant impact on the performance of Phase II control charts, a new cluster-based approach is developed to address this effect. Moreover, we evaluate and compare the performance of the proposed approach with a previous approach in terms of two metrics, average of average run length and its standard deviation, which are used for considering practitioner-to-practitioner variability. In this approach, it is not necessary to know the distribution of the chart statistic. Therefore, in addition to ease of use, the proposed approach can be applied to other type of profiles. The superior performance of the proposed method compared to the competing one is shown in terms of all metrics. Based on the results obtained, our method yields less bias with small-variance Phase I estimates compared to the competing approach.     

Disaster cosmologies in comparative perspective: Islam,climate change and the 2010 floods in Pakistan's Southern Punjab

As humanity enters a new era of climate‐induced unpredictability, research into the role of religion in shaping perceptions of, and responses to disaster will become increasingly important. This is particularly true of South Asia, which contains dense populations certain to be adversely affected by climate change. This contribution explores the way religion shapes and mediates responses to disaster in Pakistan. Where previous work in this field has focused on extremists and militants, mine considers currents of lived Islam that take explicit stances on questions of natural resource development. Drawing upon extensive primary data, I identify two distinct disaster cosmologies permeating state and society. First, I consider the official Islam of experts and policymakers, whose approach to development is derived from, but arguably surpasses the modernism of British and American colonial and Cold War paradigms in its dogmatic, faith‐based belief in the imperative of mastering and exploiting nature. The second is an altogether contrasting formation embedded in a political protest movement representing a marginalized constituency, the Siraiki speaking population of Southern Punjab, which mobilized flood affectees in the aftermath of the 2010 floods around issues of social and environmental justice.     

Distribution of linear functions from ordered bivariate log-normal distribution

In this work we consider the problem of finding the distribution of linear functions of the minimum and the maximum of the bivariate log-normal distribution. We derive the distribution function, density function and moments of these statistics. This work will provide a generalization of the minimum and the maximum cases.