Social work and macro-economic neoliberalism: beyond the social justice rhetoric

Macro-economic policy shapes and structures social welfare policy, services, and their implementation. As a result, the commoditisation of social welfare services and the use of markets as well as private sector management philosophies and tools have colonised and fashioned the design, provision and implementation of social welfare policy and structures. The impact has been far reaching, from limiting social welfare responses of elected democratic government to shaping the profession in a range of intended and unintended directions. Written from a UK perspective, this paper proposes a discussion of the impact of macro-economic neoliberal policies in the field of social welfare and explores the implications for social work practice. The paper also promotes a debate within the profession regarding the importance of macro-economic analysis and possible responses, as well as suggesting a way forward within European and, more broadly, international practice contexts.     

Using WhatsApp for a homeless count

The study analyses how the use of instant messaging (WhatsApp) alongside other ICT tools is adequate to complement the count of homeless people in an area. In particular, it describes the methodology used in order to organize the first official count of homeless people in Girona (Catalonia, Spain). Given that this is the first count of individuals experiencing homelessness in the city, it is difficult to say that it is an improvement, but it could be suggested that the app might make the future counts more efficient. Both professional and volunteers and homeless people used WhatsApp to send information. A total of 283 homeless people were detected. Results show that the usage of this application optimized the results of the count. 36.1% of the data were obtained online. Homeless people, who were reluctant to contact directly with the professional team, used WhatsApp to communicate with them, adding up to 19.4% of the data obtained. Results show how communication between homeless people and health and mental health services can be potentially improved with this type of application.     

Living Environment Preferences of the Inhabitants of Istanbul: A Modified Hierarchical Information Integration Model

This paper presents a two-stage research to model the different priorities and expectations about living environment preferences of the inhabitants of Istanbul, Turkey's largest metropolitan with a population of 10 million. In the first stage, a modified hierarchical information integration approach was used to estimate the utilities of different attributes for each individual sampled from the inhabitants of Istanbul. This is a decompositional approach and involves measuring individual preferences. In this study, not only aggregate results are reported but also a segmentation study is carried out to explore the heterogeneity in respondents' preferences. Identification of such segments would help planner offer different planning options to groups with different preferences. Thus, the second stage of this study consists of identifying distinct groups of inhabitants with different preference structures by using cluster analysis. The resulting information is believed to be more useful especially to understand diverging demands of inhabitants of Istanbul.     

The genetic heterogeneity of deer mouse populations ( Peromyscus maniculatus ) in an insular landscape

A survey of the genetic variability in deer mouse populations was performed using specimens collected from six different islands on a lake covering approximately 50 km². Random amplified polymorphic DNA (RAPD) was used to measure the extent of the genetic differences in this insular system. An analysis of molecular variance (AMOVA) revealed that populations are clearly separated at this microgeographic scale (F _st = 0.13863; P < 0.001). The homogeneity of molecular variance test (HOMOVA) indicated that within-population levels vary greatly (B _p = 0.76831; P < 0.001). The within-population molecular variance was found to be mainly correlated with the accessibility of the islands, computed as the inverse of the geographic distance separating an island from the lakeshore (r = 0.916; P < 0.003). Received: March 5, 1999 / Accepted: July 16, 1999     

Individual gendered attitudes toward immigrants. Empirical evidence from French surveys

This article explores gendered attitudes towards immigrants and argues there are three gendered effects on intolerance: the gender gap that induces different levels of intolerance for men and women; gendered sensitivity, meaning men and women react differently to contact or competition with immigrants; the relative sex ratio related to the demographic gender changes in the environment due to immigrants. These hypotheses are tested using the French WVS data and three different intolerance measurements: soft and hard intolerance and relative empathy. The results highlight that the simple gender gap, already observed in the literature, can be partly accounted for by both gendered sensitivity and the relative sex ratio. More broadly, the findings confirm the hypothesis of gendered attitudes towards immigrants defined by three dimensions.     

A Short History of the Sociology of Corruption: the Demise of Counter-Intuitivity and the Rise of Numerical Comparisons

This article examines the history of the sociology of corruption. It is shown that from the 1950s until the early 1970s, the sociological discourse on corruption was dominated by a functionalist approach that tried to offer a counter-intuitive perspective on deviant behavior in arguing that corruption has positive functions for political and economic development. Because of a political reading of this discourse, its ambiguous terminology and some difficulties in methodology, it was largely abandoned in sociology. However, this not only led to a change in paradigmatic orientations in the sociology of corruption, but also to a general decline in interest for the phenomenon in sociology. This gap was filled by economic models of corruption that could bypass some terminological difficulties in defining corruption and, building on this, also enabled a largely quantitative approach in numerically comparing, correlating and ranking corruption. The effect was a consensus on the mostly negative effects of corruption on development, a proliferation of the transparency ideal and the disability of sociology to offer an alternative perspective on evaluating the effects of corruption.     

Metropolis–Hastings algorithms with adaptive proposals

Different strategies have been proposed to improve mixing and convergence properties of Markov Chain Monte Carlo algorithms. These are mainly concerned with customizing the proposal density in the Metropolis–Hastings algorithm to the specific target density and require a detailed exploratory analysis of the stationary distribution and/or some preliminary experiments to determine an efficient proposal. Various Metropolis–Hastings algorithms have been suggested that make use of previously sampled states in defining an adaptive proposal density. Here we propose a general class of adaptive Metropolis–Hastings algorithms based on Metropolis–Hastings-within-Gibbs sampling. For the case of a one-dimensional target distribution, we present two novel algorithms using mixtures of triangular and trapezoidal densities. These can also be seen as improved versions of the all-purpose adaptive rejection Metropolis sampling (ARMS) algorithm to sample from non-logconcave univariate densities. Using various different examples, we demonstrate their properties and efficiencies and point out their advantages over ARMS and other adaptive alternatives such as the Normal Kernel Coupler.     

Influence measures based on confidence ellipsoids in general linear regression model with correlated regressors

In this paper, we investigated the Andrews–Pregibon (AP), COVRATIO and Cook–Weisberg (CW) statistics to determine the influential observations on the confidence ellipsoids in linear regression model with correlated errors and correlated regressors. A real example and a Monte Carlo simulation study are given to detect the effects of autocorrelation coefficient and ridge parameter on the AP, COVRATIO and CW statistics.     

Nonparametric prediction of spatial multivariate data

This paper investigates a nonparametric spatial predictor of a stationary multidimensional spatial process observed over a rectangular domain. The proposed predictor depends on two kernels in order to control both the distance between observations and that between spatial locations. The uniform almost complete consistency and the asymptotic normality of the kernel predictor are obtained when the sample considered is an alpha-mixing sequence. Numerical studies were carried out in order to illustrate the behaviour of our methodology both for simulated data and for an environmental data set.