Assessing Schools’ Academic Performance Using a Belief Structure

A lot of attention has been given to education as it is the most practical way of improving social mobility. In order to be progressive and resilient, there has to be an overall transformation of society as evidenced in the annual budget allocations which has educational implications to it. Therefore, schools will come to term that they are under the watching eyes of interested parties who want them to perform academically. Thus, this will lead the stakeholders of education to make assessment and comparison between schools. However, the process of assessing schools is not an easy task as it involves many attributes. The problem of aggregating a large number of attributes will be a challenge if we use the traditional Multi Criteria Decision Making (MCDM) method. Hence, in this paper an innovative approach called Evidential Reasoning (ER) will be used to assess school performance in a multilevel or hierarchical setting which involved indirect measurement of quality by using standardized examination results, rather than directly measuring the quality of the processes unfolding within the schools. The approach is different from most conventional decision making modeling methods in that it employs a belief structure to represent an assessment as a distribution. By using this method, we are able to assess and rank the schools involved by giving an appropriate weight and merit point for each attribute and grade, respectively. For easy comprehension of the method, a numerical example was given on how to utilize the proposed method in order to obtain a single performance figure for school ranking purposes. Finally, by comparing the school ranking reveals that there is little similarity with the normal practice currently adopted.     

Estimation of the distribution function under hybrid ranked set sampling

Recently, a hybrid ranked set sampling (HRSS) scheme has been proposed in the literature. The HRSS scheme encompasses several existing ranked set sampling (RSS) schemes, and it is a cost-effective alternative to the classical RSS and double RSS schemes. In this paper, we propose an improved estimator for estimating the cumulative distribution function (CDF) using HRSS. It is shown, both theoretically and numerically, that the CDF estimator under HRSS scheme is unbiased and its variance is always less than the variance of the CDF estimator with simple random sampling (SRS). An unbiased estimator of the variance of CDF estimator using HRSS is also derived. Using Monte Carlo simulations, we also study the performances of the proposed and existing CDF estimators under both perfect and imperfect rankings. It turns out that the proposed CDF estimator is by far a superior alternative to the existing CDF estimators with SRS, RSS and L-RSS schemes. For a practical application, a real data set is considered on the bilirubin level of babies in neonatal intensive care.     

NeoLiberalism and the Challenges of Managing Labour Migration in Urban Malaysia

Labour migration into Malaysia has increased rapidly in recent decades and this has affected Malaysia's government policy in managing migrants’ movement. Interestingly, Malaysia has attracted a high degree of unskilled labour, accompanied by unabated rise of undocumented migrant workers. Mitigating undocumented migration is the main aim of Malaysia's labour migration policy and therefore the focus of Malaysian government. This has impacted on how enforcement agencies work out strategies. These agencies are the forefront of Malaysia's labour migration policy but they faced a number of challenges, such as documentation, finance and manpower capability, and political intervention, which impede their ability to optimize their capabilities in enforcing the Malaysian government labour migration policy. Resolving these challenges and moving towards a long‐term labour migration policy will benefit the Malaysian state, its citizens and the labour migrants.     

A Decade of Sub-national Pro-poor Growth in Pakistan

The literature on subjective well-being has highlighted the negative effects associated with the restrictions and inequality imposed by the hukou system on China’s rural population. However, quantifying the cost of holding a rural hukou has generally been challenging because it can reflect unobserved individual characteristics related to educational and occupational choices. Thanks to RUMiC, a new longitudinal database on China, this limitation can be overcome by exploiting exogenous changes in hukou status due to land expropriation. The results support that receiving an urban hukou substantially enhances subjective well-being within the household, especially for males. The results complement a growing literature on subjective well-being focusing on China.     

Convention on the Elimination of Discrimination Against Women and the Prospect of Development of Muslim Personal Law in Singapore

This paper examines Singapore's partial reservations to Articles 2 and 16 of the United Nations Convention on the Elimination of Discrimination against Women (CEDAW). It contends that the reservations justified on the basis of protecting the rights of the Muslim minority community to practice its personal law has unwittingly impeded the potential of reviewing and addressing significant gaps and limitations in the ways in which the laws are conceived and administered. More pertinently, the policy reinforces the dominance of traditionalism in the thinking of dominant stakeholders of the law. Taking the standpoint that the values of equality and non-discrimination on the basis of gender espoused by CEDAW are compatible with the objectives of Muslim law, this paper maintains that ratifying the relevant Articles of CEDAW will strengthen the process of the development of the Muslim personal law and address essentialist presumptions of the law. This perspective departs from the dominant discourse on the Muslim law and CEDAW which is framed in terms of conflict and polarity between the law and human rights, religious law and women's rights, and universal values versus cultural relativism.     

A clustering approach to detect multiple outliers in linear functional relationship model for circular data

Outlier detection has been used extensively in data analysis to detect anomalous observation in data. It has important applications such as in fraud detection and robust analysis, among others. In this paper, we propose a method in detecting multiple outliers in linear functional relationship model for circular variables. Using the residual values of the Caires and Wyatt model, we applied the hierarchical clustering approach. With the use of a tree diagram, we illustrate the detection of outliers graphically. A Monte Carlo simulation study is done to verify the accuracy of the proposed method. Low probability of masking and swamping effects indicate the validity of the proposed approach. Also, the illustrations to two sets of real data are given to show its practical applicability.     

Politics,Not Economic Interests: Determinants of Migration Policies in the European Union1

In this article we examine the determinants of European Union (EU) migration policies. We look at the passage of six pieces of migration and immigrant integration legislation in the fifth European Parliament (1999–2004). Based on the sixty‐one roll‐call votes on these bills we create a “migration score” for each Member of the European Parliament. We then use regression analysis to investigate the determinants of these scores. We find that the strongest determinants of policy outcomes on migration issues in this arena are the left‐right preferences of EU legislators. These are stronger predictors than the economic preferences of national parties’ constituents or the economic interests or political preferences of the member states.     

The Impact of Social Capital on Household Well-being in Pakistan

Social Indicators Research - The main purpose is to check the impact of social capital on households’ objective well-being in the context of a developing country like Pakistan. The primary...