Community-managed water supplies in Africa: sustainable or dispensable?

Over the past two decades, community management has become theprevalent model for management of rural water supplies throughoutsub-Saharan Africa. Despite its widespread popularity amongdonors and implementing agencies, low water supply sustainabilitylevels throughout the sub-continent indicate that it is notthe panacea it is often presented to be. There is a strong needto distinguish between ‘community participation’which is a prerequisite for sustainability and ‘communitymanagement’ which is not. If community management systemsare to be sustainable, they require ongoing support from anoverseeing institution to provide encouragement and motivation,monitoring, participatory planning, capacity building, and specialisttechnical assistance. If such support is not available, alternativessuch as household water supplies and private sector servicedelivery should be considered.     

Public Management at the Ballot Box: Performance Information and Electoral Support for Incumbent English Local Governments

Publishing performance information about local public services,an increasing trend in many Organisation for Economic Co-operationand Development countries, matters politically because it hasan effect on incumbent local governments' electoral support.Voters are able to use performance information to punish orreward incumbents in the elections that follow their publication,which may fill a gap in the chain of accountability betweenvoters and governments. We model the introduction of publishedComprehensive Performance Assessments of local authorities inEngland, which make summary information about performance availableto voters, as a "shock" to the relationship between voters andincumbents. Controlling for an unpublicized measure of performancechange over time, change in the local tax level, change in localeconomic conditions, and whether the local incumbent is theparty of the incumbent government at the national level, wefind negativity bias. Incumbents in local authorities in the"poor" performance category experience a substantial reductionin aggregate vote share at the election following publication,but there is no similarly sized reward for those in the highestperformance category.     

Correcting missing-data bias in historical demography

Studies on population history are often based on incomplete records of life histories. For instance, in studies using data obtained from family reconstitution, the date of death is right censored (by migration) and the censoring time is never observed. Several methods for the correction of mortality estimates are proposed in the literature, most of which first estimate the number of individuals at risk and then use standard techniques to estimate mortality. Other methods are based on statistical models. In this paper all methods are reviewed, and their merits are compared by applying them to simulated and to seventeenth-century data from the English parish of Reigate. An ad hoc method proposed by Ruggles performs reasonably well. Methods based on statistical models, provided they are sufficiently realistic, give comparable accuracy and allow the estimation of several other quantities of interest, such as the distribution of migration times.     

Changes in HIV/AIDS knowledge and testing behavior in Africa: how much and for whom?

Demographic and Health Survey data from nine African countries make it clear that HIV/AIDS prevention knowledge has been increasing. Still, in many cases, fewer than half of adult respondents can identify specific prevention behaviors. Knowledge is lowest in rural areas and among women. HIV testing generally remains rare but is highly variable across countries, likely reflecting differences in the supply of testing services. In most cases, schooling and wealth impacts on prevention knowledge have either been stable or have increased; hence, in the majority of contexts, initial disparities in knowledge by education and wealth levels have persisted or widened.

Penalized Pseudolikelihood Inference in Spatial Interaction Models with Covariates

Given spatially located observed random variables ( x , z = {( x _i , z _i )} _i , we propose a new method for non-parametric estimation of the potential functions of a Markov random field p ( x | z ), based on a roughness penalty approach. The new estimator maximizes the penalized log-pseudolikelihood function and is a natural cubic spline. The calculations involved do not rely on Monte Carlo simulation. We suggest the use of B-splines to stabilize the numerical procedure. An application in Bayesian image reconstruction is described.     

Importance of interpolation when constructing double-bootstrap confidence intervals

We show that, in the context of double-bootstrap confidence intervals, linear interpolation at the second level of the double bootstrap can reduce the simulation error component of coverage error by an order of magnitude. Intervals that are indistinguishable in terms of coverage error with theoretical, infinite simulation, double-bootstrap confidence intervals may be obtained at substantially less computational expense than by using the standard Monte Carlo approximation method. The intervals retain the simplicity of uniform bootstrap sampling and require no special analysis or computational techniques. Interpolation at the first level of the double bootstrap is shown to have a relatively minor effect on the simulation error.     

Learning from a lot: Empirical Bayes for high‐dimensional model‐based prediction

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, stored in public repositories. We review applications of a variety of empirical Bayes methods to several well‐known model‐based prediction methods, including penalized regression, linear discriminant analysis, and Bayesian models with sparse or dense priors. We discuss “formal” empirical Bayes methods that maximize the marginal likelihood but also more informal approaches based on other data summaries. We contrast empirical Bayes to cross‐validation and full Bayes and discuss hybrid approaches. To study the relation between the quality of an empirical Bayes estimator and p, the number of variables, we consider a simple empirical Bayes estimator in a linear model setting. We argue that empirical Bayes is particularly useful when the prior contains multiple parameters, which model a priori information on variables termed “co‐data”. In particular, we present two novel examples that allow for co‐data: first, a Bayesian spike‐and‐slab setting that facilitates inclusion of multiple co‐data sources and types and, second, a hybrid empirical Bayes–full Bayes ridge regression approach for estimation of the posterior predictive interval.     

We are not in control—embrace uncertainty and trust in what emerges. Peter Senge on the legacy and future of Change Management

Gruppe. Interaktion. Organisation. Zeitschrift für Angewandte Organisationspsychologie (GIO) - Peter Senge is a senior lecturer at the MIT Sloan School of Management and founder of...     

Finding common ground: how superdiversity is unsettling social work education

For social work education in the Netherlands, the rapid transition towards superdiversity means that its capacity to adapt to this new reality and to adjust to diverse students’ backgrounds is fiercely challenged. The key aim of this article is to discuss how social work educators are dealing with the unsettling challenges of increasing diversity, based on the research outcomes of an explorative study amongst Turkish–Dutch and Moroccan–Dutch female professionals. Two different groups of educators were asked to comment on the outcomes of this study. One of the dilemmas for educators is to determine what can be considered supportive and inclusive and as reducing inequality in education. The authors used two key theoretical concepts, ‘superdiversity’ and ‘the capability approach’. These theoretical perspectives were used to deconstruct the rather massive concepts of diversity and social justice, by emphasising contextual approaches. Both perspectives stress the urgent need to involve students as ‘active agents of change’, by building a social work community to stimulate and facilitate an on-going dialogue. To successfully fulfil a pivotal role in the upward mobility or emancipation of ethnic minority students, social work education needs to be adjusted to accommodate diverse student groups.