A Heart to Learn and Care? Teachers' responses toward special needs children in mainstream schools in Hong Kong

This article examines the problems associated with introducing integrated education into Hong Kong's mainstream schooling system. The research objectives were to examine the experience of teachers in teaching children with special needs in mainstream schools; to examine the attitude of mainstream teachers towards integrated education, and explore whether the differences in perception of difficulties and attitudes are attributable to types of disability and availability of resources. This was achieved through a research strategy utilising a questionnaire survey combined with individual and group interviews. The results demonstrate that there is a clear hierarchy of preference amongst teachers in relation to special needs children. Students with a learning disability and/or behavioural problems pose more challenges to teachers than those with a physical difficulty. Teachers that had both types of special needs children in a class experience more problems in maintaining classroom discipline, have a greater workload and struggle to manage the disparate academic standards amongst students. Teachers in schools with extra funding provisions, teachers trained to teach special needs children, additional counselling resources and specialist support expressed more accepting attitudes towards children with special needs and their admission into mainstream schools. Resource classes did not exert a positive effect on acceptance. More than 70% of questionnaire respondents were supportive of two positive value statements 'realisation of equal opportunities' and 'a good chance for students to interact'. At the same time teachers tended to agree with the statements 'integration was a burden to the schools and teachers' (over 60%) and 'a painful struggle for special students' (48%). Although there is a general normative acceptance of inclusion, the statistical pattern suggests that teachers' attitudes are not static or based solely on ideology.     

Optimising the queuing system for an ear, nose and throat outpatient clinic

Several authors have considered the problem of the efficient running of hospital outpatient clinics. The first solution was probably by Welch & Bailey (1952). More recent authors include Fetter & Thompson (1966), Vissers (1979), Stafford & Aggarwal (1979). The Ear, Nose and Throat outpatient clinic presents a special case due to the complex queuing structure involved, which is described in the next section. A simulation of this special clinic was undertaken, any useful theoretical results being impossible to obtain.     

Improvement over bayes prediction in small samples in the presence of model uncertainty

In an online prediction context, the authors introduce a new class of mongrel criteria that allow for the weighing of candidate models and the combination of their predictions based both on model‐based and empirical measures of their performance. They present simulation results which show that model averaging using the mongrel‐derived weights leads, in small samples, to predictions that are more accurate than that obtained by Bayesian weight updating, provided that none of the candidate models is too distant from the data generator.     

The Informal ‘Guanxi’ Institutional Culture of the Malaysian Housing Development Industry

There has been limited understanding of the relationship between private developers and the housing delivery mechanism in Malaysia. This paper seeks to bridge the research gap by analysing the social relationships and informal institutions embedded in the Malaysian housing development industry. Empirical data were collected for Kuala Lumpur and Johor to compare and contrast developers’ views and their working relationships with government departments. Informed by various arguments that ‘guanxi’ can reduce transaction costs and supplement/complement the formal legal regime, this paper examines the ways developers are engaged in such transaction cost reduction activities. Policy and theoretical implications of the informal cultural practice in the housing development industry are then drawn out.     

Empirical investigation of alternate cumulative capability models: a multi-method approach

Quality (Q), delivery (D), flexibility (F) and cost (C) may reinforce each other to form specific models of cumulative capability. Previous empirical studies reveal two dominant models of cumulative capabilities (Q–D–F–C and Q–D–C–F) without testing whether other models could better fit their data. The present study fulfils this gap and conducts a comparative analysis by testing various models of cumulative capabilities based on a survey of 368 Thai manufacturing plants, and concludes that Q–D–C–F is the best-fit model and further extends the models to reveal ‘simultaneous’ cumulative capability. The contributions are threefold. First, multiple methods are applied to robustly search for the best-fit model. Second, direct and indirect links between capabilities are revealed to add insights into the cumulative reinforcement patterns among capabilities. Third, we show that the widely accepted sand-cone model (Q–D–F–C) and competitive progression theory are not necessarily the dominant approaches for explaining cumulative capability patterns of manufacturers, especially from an emerging country. The results are also significant for practitioners as they understand how capabilities such as quality and delivery can simultaneously improve the next sequential capability.     

Properties of the bridge sampler with a focus on splitting the MCMC sample

Computation of normalizing constants is a fundamental mathematical problem in various disciplines, particularly in Bayesian model selection problems. A sampling-based technique known as bridge sampling (Meng and Wong in Stat Sin 6(4):831–860, 1996) has been found to produce accurate estimates of normalizing constants and is shown to possess good asymptotic properties. For small to moderate sample sizes (as in situations with limited computational resources), we demonstrate that the (optimal) bridge sampler produces biased estimates. Specifically, when one density (we denote as $$p_2$$) is constructed to be close to the target density (we denote as $$p_1$$) using method of moments, our simulation-based results indicate that the correlation-induced bias through the moment-matching procedure is non-negligible. More crucially, the bias amplifies as the dimensionality of the problem increases. Thus, a series of theoretical as well as empirical investigations is carried out to identify the nature and origin of the bias. We then examine the effect of sample size allocation on the accuracy of bridge sampling estimates and discovered that one possibility of reducing both the bias and standard error with a small increase in computational effort is by drawing extra samples from the moment-matched density $$p_2$$ (which we assume easy to sample from), provided that the evaluation of $$p_1$$ is not too expensive. We proceed to show how the simple adaptive approach we termed “splitting” manages to alleviate the correlation-induced bias at the expense of a higher standard error, irrespective of the dimensionality involved. We also slightly modified the strategy suggested by Wang et al. (Warp bridge sampling: the next generation, Preprint, 2019. arXiv:1609.07690) to address the issue of the increase in standard error due to splitting, which is later generalized to further improve the efficiency. We conclude the paper by offering our insights of the application of a combination of these adaptive methods to improve the accuracy of bridge sampling estimates in Bayesian applications (where posterior samples are typically expensive to generate) based on the preceding investigations, with an application to a practical example.     

Estimating the impact of the Global Financial Crisis on poverty and deprivation

Although the Australian economy has avoided going into recession since the onset of the global financial crisis, relatively little is known about the social impact of the crisis. Survey and anecdotal evidence presented by a number of community sector NGOs suggest that the demand for emergency relief and other services rose in the aftermath of the crisis. This article reports results derived from two national surveys on poverty and social disadvantage that were conducted in 2006 and 2010 – prior to and after the crisis struck. The survey data allow income‐based poverty rates to be estimated as well as the extent and nature of deprivation, where deprivation is defined as being unable to afford items that a majority regards as essential: things that no‐one in Australia should have to go without. Poverty and deprivation are not alternative indicators but can be combined into a multi‐dimensional measure of consistent poverty. The paper examines how conventional (income) poverty, deprivation and consistent poverty changed between 2006 and 2010, and analyses the sensitivity of the results to alternative definitions. The findings provide the first comprehensive evidence on how the profile of social disadvantage in Australia changed in the period that spans the financial crisis.