Social Workers’ Knowledge and Attitudes About Evidence-Based Practice: Differences Between Graduate Students,Educators, and Practitioners

Clinical Social Work Journal - The implementation of evidence-based practice (EBP) is increasingly being stressed as a responsibility of social work practitioners and social work educators....     

Axiomatizing bounded rationality: the priority heuristic

This paper presents an axiomatic framework for the priority heuristic, a model of bounded rationality in Selten’s (in: Gigerenzer and Selten (eds.) Bounded rationality: the adaptive toolbox, 2001) spirit of using empirical evidence on heuristics. The priority heuristic predicts actual human choices between risky gambles well. It implies violations of expected utility theory such as common consequence effects, common ratio effects, the fourfold pattern of risk taking and the reflection effect. We present an axiomatization of a parameterized version of the heuristic which generalizes the heuristic in order to account for individual differences and inconsistencies. The axiomatization uses semiorders (Luce, Econometrica 24:178–191, 1956), which have an intransitive indifference part and a transitive strict preference component. The axiomatization suggests new testable predictions of the priority heuristic and makes it easier for theorists to study the relation between heuristics and other axiomatic theories such as cumulative prospect theory.     

A new approach for disclosure control in the IAB establishment panel—multiple imputation for a better data access

For micro-datasets considered for release as scientific or public use files, statistical agencies have to face the dilemma of guaranteeing the confidentiality of survey respondents on the one hand and offering sufficiently detailed data on the other hand. For that reason, a variety of methods to guarantee disclosure control is discussed in the literature. In this paper, we present an application of Rubin’s (J. Off. Stat. 9, 462–468, 1993) idea to generate synthetic datasets from existing confidential survey data for public release.We use a set of variables from the 1997 wave of the German IAB Establishment Panel and evaluate the quality of the approach by comparing results from an analysis by Zwick (Ger. Econ. Rev. 6(2), 155–184, 2005) with the original data with the results we achieve for the same analysis run on the dataset after the imputation procedure. The comparison shows that valid inferences can be obtained using the synthetic datasets in this context, while confidentiality is guaranteed for the survey participants.     

Multiple imputation in practice—a case study using a complex German establishment survey

Multiple imputation is widely accepted as the method of choice to address item nonresponse in surveys. Nowadays most statistical software packages include features to multiply impute missing values in a dataset. Nevertheless, the application to real data imposes many implementation problems. To define useful imputation models for a dataset that consists of categorical and possibly skewed continuous variables, contains skip patterns and all sorts of logical constraints is a challenging task. Besides, in most applications little attention is paid to the evaluation of the underlying assumptions behind the imputation models.     

New data dissemination approaches in old Europe – synthetic datasets for a German establishment survey

Disseminating microdata to the public that provide a high level of data utility, while at the same time guaranteeing the confidentiality of the survey respondent is a difficult task. Generating multiply imputed synthetic datasets is an innovative statistical disclosure limitation technique with the potential of enabling the data disseminating agency to achieve this twofold goal. So far, the approach was successfully implemented only for a limited number of datasets in the U.S. In this paper, we present the first successful implementation outside the U.S.: the generation of partially synthetic datasets for an establishment panel survey at the German Institute for Employment Research. We describe the whole evolution of the project: from the early discussions concerning variables at risk to the final synthesis. We also present our disclosure risk evaluations and provide some first results on the data utility of the generated datasets. A variance-inflated imputation model is introduced that incorporates additional variability in the model for records that are not sufficiently protected by the standard synthesis.     

Knowledge, Embodiment, Skill and Risk: Anthropological Perspectives on Women’s Everyday Technologies in Rural Northern China

Knowledge organisation, embodiment of knowledge and knowledge representation are important issues for an anthropology of technology, which seeks to explore the ways in which people find and shape everyday solutions to social and technical challenges. This article discusses the impact of skill and of risk prevention on women’s decision-making, as well as on the domestication and appropriation of new technologies. Particular attention is paid to non-synchronicity as a retarding factor and to the obsolescence of skills as a critical moment in the transformation of socio-technical systems in twentieth century rural northern China as elsewhere.

Safe Spaces: Gay‐Straight Alliances in High Schools

In activists’ circles as in sociology, the concept “safe space” has been applied to all sorts of programs, organizations, and practices. Few studies have specified clearly what safe spaces are and how they support the people who occupy them. We examine one social location typically understood to be a safe space: gay‐straight alliance groups in high schools. Using qualitative interviews with young adults in the United States and Canada who have participated in gay‐straight alliances, we unpack this complex concept to consider some of the dimensions along which safe spaces might vary. Based on interviews with participants, we derive three interrelated dimensions of safe space: social context, membership, and activity.