Explaining the Varieties of Volunteering in Europe: A Capability Approach

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - Volunteer rates vary greatly across Europe despite the voluntary sector’s common history and tradition. This...     

Samiul Hasan (ed.): Human Security and Philanthropy: Islamic Perspectives and Muslim Majority Country Practices

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations -     

Social choice theory and the “Centre de Mathématique Sociale”: some historical notes

In this paper we describe some research directions in social choice and aggregation theory taken at the “Centre de Mathématique Sociale” since the fifties. We begin by presenting some institutional aspects concerning this center. Then we sketch a thematic history by considering the following questions about the “effet Condorcet” (“voting paradox”): What is it? How is it overcome? Why does it occur? These questions were adressed in Guilbaud's paper (Guilbaud GTh (1952) Les théories de l'intérêt général et le problème logique de l'agrégation, (Theories of the general interest and the logical problem of aggregation) which will mark the beginning of our inquiry. The conclusion outlines some more recent research developments linked to these questions.     

Heideggerian existentialism and social work practice with death and survivor bereavement

Heideggerian existentialism has not been applied on a widespread basis to the Generalist Social Work Practice Model. This paper explores the relationship between social work practice with bereavement issues and Heideggerian existentialism. Applications of Heideggerian existentialism in the social work profession with clients and families experiencing bereavement are examined. Conceptual applications also address future utilization of Heideggerian existentialism.     

On discrimination procedure with mixtures of continuous and categorical variables

A discrimination procedure, based on the location model is described and suggested for use in situation where the discriminating variables are mixtures of continuous and binary variables. Some procedures that have been previously employed, in a similar situation, like Fisher's linear discriminant function and the logistic regression were compared with this method using error rate (ER). Optimal ERs for these procedures are reported using real and simulated data for the case of varying sample size and number of continuous and binary variables and were used as a measure for assessing the performance of the various procedures. The suggested procedure performed considerably better in the cases considered and never did produce a result that is poor when compared with other procedures. Hence, the suggested procedure might be considered for such situations.     

Inversion of the Renewal Density with Dead-time

Stationary renewal point processes are defined by the probability distribution of the distances between successive points (lifetimes) that are independent and identically distributed random variables. For some applications it is also interesting to define the properties of a renewal process by using the renewal density. There are well-known expressions of this density in terms of the probability density of the lifetimes. It is more difficult to solve the inverse problem consisting in the determination of the density of the lifetimes in terms of the renewal density. Theoretical expressions between their Laplace transforms are available but the inversion of these transforms is often very difficult to obtain in closed form. We show that this is possible for renewal processes presenting a dead-time property characterized by the fact that the renewal density is zero in an interval including the origin. We present the principle of a recursive method allowing the solution of this problem and we apply this method to the case of some processes with input dead-time. Computer simulations on Poisson and Erlang (2) processes show quite good agreement between theoretical calculations and experimental measurements on simulated data.