Institutional fragmentation and coordination initiatives in western European welfare states

As a result of recent welfare state transformations, and most notably the reorientation of welfare states towards activation, the internal fragmentation of social security systems has emerged as a key policy problem in many western European countries. The types of response that have been adopted, however, vary substantially across countries, ranging from the encouragement of inter-agency collaboration to the outright merger of agencies. The purpose of this exploratory article is twofold. First, by proposing the concept of coordination initiatives, it tries to develop a better conceptualization of the cross-national diversity in responses to the fragmentation problem. Second, starting from existing theories of welfare state development and policy change, it presents first hypotheses accounting for the variation observed in coordination initiatives.

Federalism and Welfare to Work in Switzerland: The Development of Active Social Policies in a Fragmented Welfare State

This article is concerned with the impact that federal structures have on the development of welfare to work or activation policies. More precisely, it argues that the incentives and the risks associated with a division of responsibilities among different jurisdictions may constitute an obstacle to broad reforms that promote labor market participation of nonworking benefit recipients. This argument is illustrated with a case study discussing policy responses to a massive rise in caseloads among social assistance recipients in Switzerland. We conclude that the lack of a fundamental reform was the consequence of the incentives provided by the federal structure of the program. These incentives have both encouraged cost shifting among jurisdictions and discouraged involvement of federal level policy makers in a bigger reform.

Implementing statistical learning methods through Bayesian networks (Part 2): bayesian evaluations for results of black toner analyses in forensic document examination

This paper presents and discusses the use of Bayesian procedures - introduced through the use of Bayesian networks in Part I of this series of papers - for 'learning' probabilities from data. The discussion will relate to a set of real data on characteristics of black toners commonly used in printing and copying devices. Particular attention is drawn to the incorporation of the proposed procedures as an integral part in probabilistic inference schemes (notably in the form of Bayesian networks) that are intended to address uncertainties related to particular propositions of interest (e.g., whether or not a sample originates from a particular source). The conceptual tenets of the proposed methodologies are presented along with aspects of their practical implementation using currently available Bayesian network software.