Social Work and Disadvantage: Addressing the Roots of Stigma through Association

Abstract

This paper reports on a small-scale research study that explores the impact of climate change on rural women. Qualitative data were collected through interviews with 7 women, who came from a regional centre and were either employed by women's services or who had activist roles within the community pertaining to women's services. Outcomes of the study identified a range of areas of impact, including increased hardship for rural women, implications of household roles, and subsequent organisational responsibilities. A high level of concern, particularly for the vulnerability of women in crisis, was identified among participants. We contend that the effects of climate change are becoming increasingly relevant to the social work profession and that specific groups such as women are at risk of further disadvantage unless collective action is taken to circumvent the impact of climate change. Strategies for social work practice and policy initiatives are considered.     

Book reviews

In the long eighteenth century, the judges at the Old Bailey came to allow Jewish, Scottish, Muslim, Hindu and Chinese witnesses, but not Quakers, to swear oaths according to their own cultural practices. Although a non-Christian witness might be able to give testimony under oath, the jury still had to assess the veracity of the evidence. The increasingly adversarial mode of felony trials in the eighteenth century made the separation between who was legally able to testify and who was credible more pronounced. Barristers and prisoners raised concerns about the oaths of blacks and non-Christians as a means of impugning the truthfulness of a witness.     

Bayesian compartmental model for an infectious disease with dynamic states of infection

Population-level proportions of individuals that fall at different points in the spectrum [of disease severity], from asymptomatic infection to severe disease, are often difficult to observe, but estimating these quantities can provide information about the nature and severity of the disease in a particular population. Logistic and multinomial regression techniques are often applied to infectious disease modeling of large populations and are suited to identifying variables associated with a particular disease or disease state. However, they are less appropriate for estimating infection state prevalence over time because they do not naturally accommodate known disease dynamics like duration of time an individual is infectious, heterogeneity in the risk of acquiring infection, and patterns of seasonality. We propose a Bayesian compartmental model to estimate latent infection state prevalence over time that easily incorporates known disease dynamics. We demonstrate how and why a stochastic compartmental model is a better approach for determining infection state proportions than multinomial regression is by using a novel method for estimating Bayes factors for models with high-dimensional parameter spaces. We provide an example using visceral leishmaniasis in Brazil and present an empirically-adjusted reproductive number for the infection.     

The Social Production of Bullying: Expanding the Repertoire of Approaches to Group Dynamics

Bullying research has widely included group dynamics as contextual factors. However, explanations addressing the causes of bullying predominantly emphasise individual dysfunctions related to aggression and empathy. Analysing qualitative data from Norwegian schools, this article explores four different group dynamics that may produce bullying behaviours as well as deactivate empathy. Drawing on theories of social hierarchies and ingroups/outgroups, the article offers new approaches to understanding the ways in which the intense markings of social distinctions between positions and cliques in peer culture represent significant social driving forces in school bullying.     

Ridge estimator with correlated errors and two-stage ridge estimator under inequality restrictions

Liew (1976a Liew, C.K. (1976a). A two-stage least-squares estimation with inequality restrictions on parameters. Rev. Econ. Stat. LVIII(2):234–238.[Crossref], [Web of Science ®] , [Google Scholar]) introduced generalized inequality constrained least squares (GICLS) estimator and inequality constrained two-stage and three-stage least squares estimators by reducing primal–dual relation to problem of Dantzig and Cottle (1967 Dantzig, G.B., Cottle, R.W. (1967). Positive (semi-) definite matrices and mathematical programming. In: Abadie, J., ed. Nonlinear Programming (pp. 55–73). Amsterdam: North Holland Publishing Co. [Google Scholar]), Cottle and Dantzig (1974 Cottle, R.W., Dantzig, G.B. (1974). Complementary pivot of mathematical programming. In: Dantzig, G.B., Eaves, B.C., eds. Studies in OptimizationVol. 10. Washington: Mathematical Association of America. [Google Scholar]) and solving with Lemke (1962 Lemke, C.E. (1962). A method of solution for quadratic programs. Manage. Sci. 8(4):442–453.[Crossref], [Web of Science ®] , [Google Scholar]) algorithm. The purpose of this article is to present inequality constrained ridge regression (ICRR) estimator with correlated errors and inequality constrained two-stage and three-stage ridge regression estimators in the presence of multicollinearity. Untruncated variance–covariance matrix and mean square error are derived for the ICRR estimator with correlated errors, and its superiority over the GICLS estimator is examined via Monte Carlo simulation.