Networking Enforced – Comparing Social Services' Collaborative Rationales across Different Welfare Regimes

Collaboration and networking are ubiquitous, versatile features of social service provision in most Western countries. However, it is an open question whether networking means and entails the same across countries. Comparing regulatory frameworks in three jurisdictions representing distinctive ‘worlds of welfare services’ – Germany, Norway and Quebec – this article aims at eliciting the normative rationales that underpin and inform local service networks in child welfare and protection (CWP) systems. In Norway, where services are little diversified and largely insular, networking appears as a way of opening up for greater organizational plurality, within and beyond the public sector realm. In Germany in contrast, where services are highly pluralized and fragmented, networks are seen as an instrument for streamlining complexity. As for Quebec – an intermediate case in some respects – networking is envisioned as a catalyst for aligning two co‐existing service streams and mitigating the child protection–family support divide. Interestingly, in all three places, networking is now being enforced through similar highly formalized, top‐down regulatory provisions, even though the intended directions of change differ markedly. This has implications for CWP policy as well as research on networks at large.     

Voting paradoxes and referenda

In representational democracies the referenda constitute an additional way for the voters to express their opinions. At the same time they are accompanied by problems of agenda manipulation and interpretation of results. In this context various voting paradoxes and their interrelationships are of considerable interest. In this article particular attention is paid to opinion aggregation paradoxes in referendum institutions. The limits and interrelationships of paradoxes are discussed. Some ways of avoiding paradoxical situations are also outlined. Received: 11 September 1995 / Accepted: 7 January 1997     

On the geometry of multivariate L 1 objective functions

Summary: Two multivariate L ₁ objective functions, namely the k–variate extensions of the classical mean deviation and mean difference, are considered. The duality between the original data vectors and the hyperplanes going through the origin and k – 1 data points is discussed and, consequently, different interesting representations and interpretations of the multivariate mean deviation are introduced. A similar duality is found between the lift data vectors and the hyperplanes going through k data points leading to different representations of the multivariate mean difference. The objective functions are also shown to have interpretations in terms of the centers of facets of the data based zonotopes and lift zonotopes. Moreover, interchanging the roles of the data vectors and the data hyperplanes yields nonparametric measures of (angular) distances between the data vectors as well as between the hyperplanes. Finally, multivariate sign and rank based tests and estimates in the one–sample and several–samples multivariate cases are discussed to illustrate the theory.*The authors wish to thank the referees for valuable comments and suggestions. The research was partially supported by the Academy of Finland.     

One-sample location tests for multilevel data

In this paper, we consider testing the location parameter with multilevel (or hierarchical) data. A general family of weighted test statistics is introduced. This family includes extensions to the case of multilevel data of familiar procedures like the t, the sign and the Wilcoxon signed-rank tests. Under mild assumptions, the test statistics have a null limiting normal distribution which facilitates their use. An investigation of the relative merits of selected members of the family of tests is achieved theoretically by deriving their asymptotic relative efficiency (ARE) and empirically via a simulation study. It is shown that the performance of a test depends on the clusters configurations and on the intracluster correlations. Explicit formulas for optimal weights and a discussion of the impact of omitting a level are provided for 2 and 3-level data. It is shown that using appropriate weights can greatly improve the performance of the tests. Finally, the use of the new tests is illustrated with a real data example.     

A weighted spatial median for clustered data

A weighted spatial median is proposed for the multivariate one-sample location problem with clustered data. Its limiting distribution is derived under mild conditions (no moment assumptions) and it is shown to be multivariate normal. Asymptotic as well as finite sample efficiencies and breakdown properties are considered, and the theoretical results are supplied with illustrative examples. It turns out that there is a potential for meaningful gains in estimation efficiency: the weighted spatial median has superior efficiency to the unweighted spatial median particularly when the cluster sizes are widely disparate and in the presence of strong intracluster correlation. The unweighted spatial median for clustered data was considered earlier by Nevalainen et al. (Can J Statist, in press, 2007). The proposed weighted estimators provide companion estimates to the weighted affine invariant sign test proposed recently by Larocque et al. (Biometrika, in press, 2007). An affine equivariant weighted spatial median is discussed in parallel.     

A Comparison of Some Distance-Based Choice Rules in Ranking Environments

We discuss the relationships between positional rules (such as plurality and approval voting as well as the Borda count), Dodgsons, Kemenys and Litvaks methods of reaching consensus. The discrepancies between methods are seen as results of different intuitive conceptions of consensus goal states and ways of measuring distances therefrom. Saaris geometric methodology is resorted to in the analysis of the consensus reaching methods.     

What Makes Performance-Related Pay Schemes Work? Finnish Evidence

We analyze how features of performance-related pay (PRP) schemes affect their perceived motivational effects using a Finnish survey for upper white-collar employees from 1999. The results show that the following features are important for a successful PRP scheme: (i) the employees have to feel they are able to affect the outcomes; (ii) the organizational level of the performance measurement should be close to the employee: individual and team level performance measurement increase the probability that the scheme is perceived to be motivating; (iii) employees should be familiar with the performance measures; (iv) the level of payments should be high enough and rewards frequent enough. Levels below the median do not generate positive effects; (v) employees should participate in the design of the PRP scheme.     

A Simple Model of Secure Public Communication

Public communication is secure if a hostile third-party cannot decode the messages exchanged by the communicating parties. In Nash equilibrium, communication by computationally unbounded players cannot be secure. We assume complexity averse players, and show that a simple, secure, and costless communication protocol becomes available as the marginal complexity cost tends to zero.      

Affine Invariant Multivariate Sign and Rank Tests and Corresponding Estimates: a Review

The paper reviews recent contributions to the statistical inference methods, tests and estimates, based on the generalized median of Oja. Multivariate analogues of sign and rank concepts, affine invariant one-sample and two-sample sign tests and rank tests, affine equivariant median and Hodges–Lehmann-type estimates are reviewed and discussed. Some comparisons are made to other generalizations. The theory is illustrated by two examples.