Internal Migration of Ethno‐national Minorities: The Case of Arabs in Israel

Recent scholarship emphasizes differences among ethnic groups' internal migration patterns. Yet, with few exceptions, research has focused on the Anglo‐American world, neglecting experiences from other regions. This paper is part of a larger research project that studies mobility among the Arab minority in Israel and its driving forces. In this paper we examine patterns of internal migration by analysing the propensity to migrate as well as migrants' individual and social characteristics. First, we survey the theoretical backdrop that is suggested by recent geographic literature on internal migration among ethnic and racial minorities, including native groups. Second, we contextualize the group studied, providing necessary background information on the political, socio‐economic and demographic conditions of Arabs in Israel. We briefly discuss attributes that are – or have been – potential hindering factors to Arab mobility in the Jewish state. Finally, we analyse 1995 national census data at the micro scale and provide a basis for future explanations of the phenomenon. We conclude by outlying some future directions in the study of internal migration of minorities in Israel.     

An adaptive allocation sampling design for which the conventional stratified estimator is an appropriate estimator

Adaptive allocations in stratified sampling design are suitable for studying Biological and Environmental populations. Biologists tend to use the conventional stratified estimator for an adaptive allocation sampling design in spite of its adaptive nature. In this paper, we have introduced an adaptive allocation sampling design for which the conventional stratified estimator has some desired statistical properties. We conduct a simulation study on a real population. The results show that the conventional stratified estimator for the introduced adaptive allocation sampling design is more efficient than other available estimators.     

Bayesian classification with multivariate autoregressive sources that might have different orders

The main objective of this paper is to develop an exact Bayesian technique that can be used to assign a multivariate time series realization to one of several autoregressive sources, with unknown coefficients and precision, that might have different orders. The foundation of the proposed technique is to develop the posterior mass function of a classification vector, in an easy form, using the conditional likelihood function. A multivariate time series realization is assigned to the multivariate autoregressive source with the largest posterior probability. A simulation study, with uniform prior mass function, is carried out to demonstrate the performance of the proposed technique and to test its adequacy in handling the multivariate classification problems. The analysis of the numerical results supports the adequacy of the proposed technique in solving the classification problems with multivariate autoregressive sources.     

Improved attribute acceptance sampling plans based on maxima nomination sampling

This paper demonstrates the use of maxima nomination sampling (MNS) technique in design and evaluation of single AQL, LTPD, and EQL acceptance sampling plans for attributes. We exploit the effect of sample size and acceptance number on the performance of our proposed MNS plans using operating characteristic (OC) curve. Among other results, we show that MNS acceptance sampling plans with smaller sample size and bigger acceptance number perform better than commonly used acceptance sampling plans for attributes based on simple random sampling (SRS) technique. Indeed, MNS acceptance sampling plans result in OC curves which, compared to their SRS counterparts, are much closer to the ideal OC curve. A computer program is designed which can be used to specify the optimum MNS acceptance sampling plan and to show, visually, how the shape of the OC curve changes when parameters of the acceptance sampling plan vary. Theoretical results and numerical evaluations are given.     

Estimation of the means of the bivariate normal using moving extreme ranked set sampling with concomitant variable

The estimation of the means of the bivariate normal distribution, based on a sample obtained using a modification of the moving extreme ranked set sampling technique (MERSS) is considered. The modification involves using a concomitant random variable. Nonparametric-type methods as well as the maximum likelihood estimation are considered. The estimators obtained are compared to their counterparts based on simple random sampling (SRS). It appears that the suggested estimators are more efficient. Also, MERSS with concomitant variable is easier to use in practice than the usual ranked set sampling (RSS) with concomitant variable. The issue of robustness of the procedure is addressed. Real trees data set is used for illustration.     

Media, Racism and Islamophobia: The Representation of Islam and Muslims in the Media

This article examines the representation of Islam and Muslims in the British press. It suggests that British Muslims are portrayed as an 'alien other' within the media. It suggests that this misrepresenatation can be linked to the development of a 'racism', namely, Islamphobia that has its roots in cultural representations of the 'other'. In order to develop this arguement, the article provies a summary/overview of how ethnic minorities have been represented in the British press and argues that the treatment of British Muslims and Islam follows these themes of 'deviance' and 'un-Britishness'.     

Being Middle Eastern American: Identity Negotiation in the Context of the War on Terror

Using in‐depth interviews with naturalized U.S. citizens and immigrants as well as autoethnographic data, the author examines the stigma management strategies Middle Eastern Americans deploy, particularly in the aftermath of the September 11th terrorist attacks. He applies the concepts of interpretive practice and accounting to narratives of disrupted encounters in which Middle Eastern Americans were prompted to explain their identities, and classifies the stigma management strategies this group utilizes into five types of accounting: humorous, educational, defiant, cowering, and passing. This article evaluates the strengths and drawbacks of each accounting type for combating stigma and discusses how these findings inform existing scholarship on the social construction of deviant identities and their management in everyday life.     

Compressed Natural Gas Bus Safety: A Quantitative Risk Assessment

This study assesses the fire safety risks associated with compressed natural gas (CNG) vehicle systems, comprising primarily a typical school bus and supporting fuel infrastructure. The study determines the sensitivity of the results to variations in component failure rates and consequences of fire events. The components and subsystems that contribute most to fire safety risk are determined. Finally, the results are compared to fire risks of the present generation of diesel-fueled school buses. Direct computation of the safety risks associated with diesel-powered vehicles is possible because these are mature technologies for which historical performance data are available. Because of limited experience, fatal accident data for CNG bus fleets are minimal. Therefore, this study uses the probabilistic risk assessment (PRA) approach to model and predict fire safety risk of CNG buses. Generic failure data, engineering judgments, and assumptions are used in this study. This study predicts the mean fire fatality risk for typical CNG buses as approximately 0.23 fatalities per 100-million miles for all people involved, including bus passengers. The study estimates mean values of 0.16 fatalities per 100-million miles for bus passengers only. Based on historical data, diesel school bus mean fire fatality risk is 0.091 and 0.0007 per 100-million miles for all people and bus passengers, respectively. One can therefore conclude that CNG buses are more prone to fire fatality risk by 2.5 times that of diesel buses, with the bus passengers being more at risk by over two orders of magnitude. The study estimates a mean fire risk frequency of 2.2 x 10(-5) fatalities/bus per year. The 5% and 95% uncertainty bounds are 9.1 x 10(-6) and 4.0 x 10(-5), respectively. The risk result was found to be affected most by failure rates of pressure relief valves, CNG cylinders, and fuel piping.