Assimilation as multiracialism: The case of Singapore's Malays

The myths of meritocracy and multiracialism ‘explain’ between them both the ‘fairness’ of the Singapore system and the subordinate role of the non-Chinese minority races. They also purport to assure the minorities that they enjoy full status as members of the nation-building project and that their cultural and religious mores are embraced and protected within its framework. Using the Malay minority as its case study, and arguing from archival, oral, official government and secondary sources, this paper argues that the Singapore systems of meritocracy and multiracialism have not been concerned primarily with intercommunal tolerance since the 1970s, but are now programmes of assimilation of the racial minorities into a Chinese-dominated society.     

Divergence-based estimation and testing with misclassified data

The well-known chi-squared goodness-of-fit test for a multinomial distribution is generally biased when the observations are subject to misclassification. In Pardo and Zografos (2000) the problem was considered using a double sampling scheme and ø-divergence test statistics. A new problem appears if the null hypothesis is not simple because it is necessary to give estimators for the unknown parameters. In this paper the minimum ø-divergence estimators are considered and some of their properties are established. The proposed ø-divergence test statistics are obtained by calculating ø-divergences between probability density functions and by replacing parameters by their minimum ø-divergence estimators in the derived expressions. Asymptotic distributions of the new test statistics are also obtained. The testing procedure is illustrated with an example.     

Generalized additive models for location, scale and shape

Summary.  A general class of statistical models for a univariate response variable is presented which we call the generalized additive model for location, scale and shape (GAMLSS). The model assumes independent observations of the response variable y given the parameters, the explanatory variables and the values of the random effects. The distribution for the response variable in the GAMLSS can be selected from a very general family of distributions including highly skew or kurtotic continuous and discrete distributions. The systematic part of the model is expanded to allow modelling not only of the mean (or location) but also of the other parameters of the distribution of y , as parametric and/or additive nonparametric (smooth) functions of explanatory variables and/or random-effects terms. Maximum (penalized) likelihood estimation is used to fit the (non)parametric models. A Newton–Raphson or Fisher scoring algorithm is used to maximize the (penalized) likelihood. The additive terms in the model are fitted by using a backfitting algorithm. Censored data are easily incorporated into the framework. Five data sets from different fields of application are analysed to emphasize the generality of the GAMLSS class of models.     

Proportional reversed hazard rate model and its applications

The purpose of this paper is to study the structure and properties of the proportional reversed hazard rate model (PRHRM) in contrast to the celebrated proportional hazard model (PHM). The monotonicity of the hazard rate and the reversed hazard rate of the model is investigated. Some criteria of aging are presented and the inheritance of the aging notions (of the base distribution) by the PRHRM is studied. Characterizations of the model involving Fisher information are presented and the statistical inference of the parameters is discussed. Finally, it is shown that several members of the proportional reversed hazard rate class have been found to be useful and flexible in real data analysis.     

How Welfare Policies Affect Adolescents' School Outcomes: A Synthesis of Evidence From Experimental Studies

Using data from 8 random assignment studies and employing meta‐analytic techniques, this article provides systematic evidence that welfare and work policies targeted at low‐income parents have small adverse effects on some school outcomes among adolescents ages 12 to 18 years at follow‐up. These adverse effects were observed mostly for school performance outcomes and occurred in programs that required mothers to work or participate in employment‐related activities and those that encouraged mothers to work voluntarily. The most pronounced negative effects on school outcomes occurred for the group of adolescents who had a younger sibling, possibly because of the increased home and sibling care responsibilities they assumed as their mothers increased their employment.     

A simple procedure for the selection of significant effects

Summary.  Given a large number of test statistics, a small proportion of which represent departures from the relevant null hypothesis, a simple rule is given for choosing those statistics that are indicative of departure. It is based on fitting by moments a mixture model to the set of test statistics and then deriving an estimated likelihood ratio. Simulation suggests that the procedure has good properties when the departure from an overall null hypothesis is not too small.     

Measuring Substance Abuse Treatment Need Among Adults in Florida: A Social Indicators Approach

Determining the size and demographiccharacteristics of substance abuse populationsis extremely important for implementing publicpolicies aimed at the control of substanceabuse. Such information not only assists in theallocation of limited treatment resources bythe state, but also in the monitoring ofsubstance abuse trends over time and in theevaluation of innovative policy initiatives. Inthis study, we develop three composite measuresof treatment need. We then use these measuresto estimate treatment need for alcohol abuseand for controlled substance abuse within eachof Florida's 67 counties. This study providesan important empirical component of communityplanning, quantifying and, to a limited degree,specifying the level of need for the substanceabuse treatment of community residents. Anadditional benefit is the development of a costeffective and unobtrusive methodology fordetermining empirically when levels of need arechanging so that treatment levels can beadjusted accordingly. With proper use,policymakers can readily employ the methodologydeveloped in this study in Florida andelsewhere to make better-informed decisions inthe allocation of finite substance abusetreatment resources.     

Farming Patterns,Rural Restructuring,and Poverty: A Comparative Regional Analysis1

Abstract This study examines the contentions of two recent perspectives on rural economic organization and their implications for poverty. Building from (1) agrarian political economy and (2) the rural restructuring literatures, we present a comparative regional analysis of how farming patterns and other aspects of economic organization differentially affect poverty in rural areas. Data are based on 2,349 nonmetropolitan U.S. counties for the 1970–1980 period. Nonhired labor-dependent, family-operated farming (smaller and larger family farming) has relatively similar cross-regional effects on rural poverty. The effects of industrialized farming are more spatially variant, suggesting that this type of farming is integrated into regional political economies in different ways than are simple commodity units. However, farming patterns have only a small effect on rural poverty relative to other factors, such as the local employment structure, characteristics of the population, and geographic location. The results of this study highlight the need to move beyond the farm sector to understand both the dynamics of this sector and the socioeconomic consequences of rural restructuring. More broadly, the study underscores the importance of testing general sociological relationships under different spatial (e.g., regional) contexts.