Managing ‘American Islam’

Focusing on the case of Islam in post-9/11 United States, this article highlights the particularity of how US secularism is enacted by the state. In much sociological theory, the United States has been understood to be a neutral and non-interfering state with regard to religion, thereby fostering a pluralist religious context of free consumer choice. Some Muslim reformists have argued that this context makes the US highly fertile ground upon which to reform Islam and to improve women's status in Islam. This article argues that, in the context of the US-led ‘war on terror’, the government has drawn on and amplified this discourse in the service of producing a representation of the US as tolerant, while also seeking to promote a concept of ‘true’ Islam and produce patriotic Muslim citizens. At the center of this discourse are contested portrayals of Muslim women as symbolic of a modern and liberated Islam that is uniquely ‘American’ and opposed to other presumably oppressive Islams. While this context may in fact promote the reform of Islam, it does so with state involvement rather than as a result of state neutrality.     

Technology Import and Industrial Employment: Evidence from Developing Countries

Abstract. This paper based on panel data across countries examines the possible effect of the imported technology on labour absorption in the industrial sector, after controlling for real wage rate and GDP per capita. Findings tend to suggest a negative relationship between the two. Technical efficiency index derived on the basis of the stochastic frontier function framework is also negatively affected by the import of technology. Without enhancing the knowledge relating to the mechanisms of exploiting the new technology acquired from abroad, a mere increase in import of technology would mean rising unutilized capacity. And this could be due to the poor skill base of the available human capital. Investment in human capital in terms of skill formation, up‐gradation, and training on the one hand and technological advancement to suit the internal labour market conditions are the two important policy conclusions for reviving the role of industry as the engine of pro‐poor growth.     

Assessment of hospital services and patient reactions

This paper deals with the study of assessment of hospital services and patient reactions carried out amongst 473 respondents, both in-door (3 wards) and out-door patients in M.L.B. Medical College Hospital, Jhansi (Uttar Pradesh). The patients were from three wards medical, surgical and gynaecological wards and consisted of 373 discharged and 100 out-door patients.     

Estimating the parameters of the linear compartment model

In this paper we consider the linear compartment model and consider the estimation procedures of the different parameters. We discuss a method to obtain the initial estimators, which can be used for any iterative procedures to obtain the least-squares estimators. Four different types of confidence intervals have been discussed and they have been compared by computer simulations. We propose different methods to estimate the number of components of the linear compartment model. One data set has been used to see how the different methods work in practice.     

The Politics of ‘Social Accountability’ in England and Germany: Democratic Control and Moral Imperatives

This article investigates how politicians in England and Germany approach social accountability during the introduction of markets in the national health care systems. It analyses the discourse among members of parliament during the law making process of the 2012 NHS Health Care Act in England and the 2011 Act for Financing of Statutory Health Insurance in Germany. Generally, the new social accountability reform agenda is attractive to policy makers as it foregrounds public engagement and bottom-up participation (Peters 2001). Social accountability refers to institutional practices that favour participatory and horizontal mechanisms that depart from traditional hierarchical Principal-Agent forms.     

WARRANTY COST ESTIMATION: A GOAL PROGRAMMING APPROACH

This paper proposes a goal programming approach to the warranty cost estimation problem. Past research on this topic has mostly dealt with a single objective—the minimization of the warranty reserve cost or the maximization of profit. A more realistic approach to warranty cost problems could, however, involve several goals, some of which might be conflicting to others. In this paper, three goals are prioritized. The goals considered are minimization of warranty reserve cost per unit, offering a minimum level of warranty time based on an allowable proportion of failures within the warranty period, and capturing a minimum specified market share of the product. An example is illustrated using the proposed formulation, and goal achievements are discussed.     

CONSEQUENCES OF OFFSHORING TO DEVELOPING NATIONS: LABOR-MARKET OUTCOMES,WELFARE, AND CORRECTIVE INTERVENTIONS

Our parsimonious two-country (developed country and developing country) model of offshoring provides nuanced results. These include cases where wages monotonically improve, as well as where wages exhibit an inverted-U relationship with offshoring cost reductions. We identify conditions under which these relationships hold. Since global welfare always rises with improvements in offshoring technology, we find that there is a role for a minimum wage (alternatively, wage tax) in the developing country. We derive such a policy's optimal level. There is also the possibility of a developed country optimal offshoring tax for extracting terms-of-trade benefits. We, finally, analyze the two-country Nash equilibrium in policies. (JEL F11, F13, F16, F66, O19, O24)     

Bayesian hierarchical model for protein identifications

In proteomics, identification of proteins from complex mixtures of proteins extracted from biological samples is an important problem. Among the experimental technologies, mass spectrometry (MS) is the most popular one. Protein identification from MS data typically relies on a ‘two-step’ procedure of identifying the peptide first followed by the separate protein identification procedure next. In this setup, the interdependence of peptides and proteins is neglected resulting in relatively inaccurate protein identification. In this article, we propose a Markov chain Monte Carlo based Bayesian hierarchical model, a first of its kind in protein identification, which integrates the two steps and performs joint analysis of proteins and peptides using posterior probabilities. We remove the assumption of independence of proteins by using clustering group priors to the proteins based on the assumption that proteins sharing the same biological pathway are likely to be present or absent together and are correlated. The complete conditionals of the proposed joint model being tractable, we propose and implement a Gibbs sampling scheme for full posterior inference that provides the estimation and statistical uncertainties of all relevant parameters. The model has better operational characteristics compared to two existing ‘one-step’ procedures on a range of simulation settings as well as on two well-studied datasets.