Diffusive nested sampling

We introduce a general Monte Carlo method based on Nested Sampling (NS), for sampling complex probability distributions and estimating the normalising constant. The method uses one or more particles, which explore a mixture of nested probability distributions, each successive distribution occupying ∼e ⁻¹ times the enclosed prior mass of the previous distribution. While NS technically requires independent generation of particles, Markov Chain Monte Carlo (MCMC) exploration fits naturally into this technique. We illustrate the new method on a test problem and find that it can achieve four times the accuracy of classic MCMC-based Nested Sampling, for the same computational effort; equivalent to a factor of 16 speedup. An additional benefit is that more samples and a more accurate evidence value can be obtained simply by continuing the run for longer, as in standard MCMC.     

Modelling the effect of pupil mobility on school differences in educational achievement

Summary.  The recently introduced national pupil database in England allows the tracking of every child through the compulsory phases of the state education system. The data from key stage 2 for three local education authorities are studied, following cohorts of pupils through their schooling. The mobility of pupils among schools is studied in detail by using multiple-membership multilevel models that include prior achievement and other predictors and the results are compared with traditional 'value-added' approaches that ignore pupil mobility. The analysis also includes a cross-classification of junior and infant schools attended. The results suggest that some existing conclusions about schooling effects may need to be revised.     

Managing Organizational Paradoxes in Social Enterprises: Case Studies from the MENA Region

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - This study aims to examine the question around how small- and medium-scale hybrid social enterprises within the context of...     

Overcoming fieldwork challenges in urban health research in developing countries: a research note

With rapid growth in the global urban population over the next two decades, health will increasingly have an urban bias. The picture of public health is particularly complex in African cities, where rates of urbanisation, poverty and inequity are high. This paper identifies the main data collection problems encountered within a panel study in low‐income areas of Johannesburg, with special emphasis on sampling, access and partnerships. The paper will be of relevance to anyone considering research in the cities of developing countries, especially in Africa.     

Precautionary Regulation in Europe and the United States: A Quantitative Comparison

Much attention has been addressed to the question of whether Europe or the United States adopts a more precautionary stance to the regulation of potential environmental, health, and safety risks. Some commentators suggest that Europe is more risk-averse and precautionary, whereas the United States is seen as more risk-taking and optimistic about the prospects for new technology. Others suggest that the United States is more precautionary because its regulatory process is more legalistic and adversarial, while Europe is more lax and corporatist in its regulations. The flip-flop hypothesis claims that the United States was more precautionary than Europe in the 1970s and early 1980s, and that Europe has become more precautionary since then. We examine the levels and trends in regulation of environmental, health, and safety risks since 1970. Unlike previous research, which has studied only a small set of prominent cases selected nonrandomly, we develop a comprehensive list of almost 3,000 risks and code the relative stringency of regulation in Europe and the United States for each of 100 risks randomly selected from that list for each year from 1970 through 2004. Our results suggest that: (a) averaging over risks, there is no significant difference in relative precaution over the period, (b) weakly consistent with the flip-flop hypothesis, there is some evidence of a modest shift toward greater relative precaution of European regulation since about 1990, although (c) there is a diversity of trends across risks, of which the most common is no change in relative precaution (including cases where Europe and the United States are equally precautionary and where Europe or the United States has been consistently more precautionary). The overall finding is of a mixed and diverse pattern of relative transatlantic precaution over the period.     

Even More Direct Calculation of the Variance of a Maximum Penalized-Likelihood Estimator

We discuss here two examples of estimation by numerical maximization of penalized likelihood. We show that, in these examples, it is simpler not to use the EM algorithm for computation of the estimates or their standard errors. We discuss also confidence and credibility intervals based on penalized likelihood and a chi-squared approximate distribution, and compare such intervals with intervals of Wald type.

[Received July 2014. Revised September 2015.]     

THE INTELLECTUAL ORIGINS OF ‘WELFARE DEPENDENCY’

‘Welfare dependency’ has become a key term in policy debate in the United States and, more recently, Australia. In this article I explore the intellectual origins of the term, looking specifically at the writings of George Gilder and Charles Murray, two commentators whose (often polemically presented) ideas were influential within the Reagan Administration and have been at the forefront of a conservative renewal in welfare debate generally. Although others have subsequently refined some of their arguments and proposals, the authors' central claim that welfare causes dependency and thus unemployment and poverty – and that welfare reform therefore needs to focus on changing the behaviour of welfare recipients rather than providing employment opportunities – has had a lasting political impact, in Australia as much as in the US.