Developing Entrepreneurship in Social Work Through International Education. Reflections on a European Intensive Programme

This paper addresses the issue of introducing training on entrepreneurial skills in social work education and illustrates the opportunities offered for doing so by international courses. It presents a critical reflection on the concept of entrepreneurship in social work based on the case of a European Intensive Programme within the Erasmus scheme. It explores the potential of using active experiential learning methods in an international environment and of creating a situation where participants are confronted with ‘real world’ problems so that they can develop entrepreneurial skills. The paper argues that experiences of this kind provide new stimuli and contribute substantially to developing an entrepreneurial mentality, by which is meant innovative and proactive attitudes as well as skills to develop the resources with which to face social problems in an adverse context.     

A Class of Multidimensional Latent Class IRT Models for Ordinal Polytomous Item Responses

We propose a class of multidimensional Item Response Theory models for polytomously-scored items with ordinal response categories. This class extends an existing class of multidimensional models for dichotomously-scored items in which the latent abilities are represented by a random vector assumed to have a discrete distribution, with support points corresponding to different latent classes in the population. In the proposed approach, we allow for different parameterizations for the conditional distribution of the response variables given the latent traits, which depend on the type of link function and the constraints imposed on the item parameters. Moreover, we suggest a strategy for model selection that is based on a series of steps consisting of selecting specific features, such as the dimension of the model (number of latent traits), the number of latent classes, and the specific parameterization. In order to illustrate the proposed approach, we analyze a dataset from a study on anxiety and depression on a sample of oncological patients.     

Some simulations and applications of forecasting long-memory time-series models

In this paper, we show some results of forecasting based on the ARFIMA(p,d,q) and ARIMA(p,d,q) models. We show, by simulation, that the technique of forecasting of the ARIMA(p,d,q) model can also be used when d is fractional, i.e., for the ARFIMA(p,d,q) model. We also conduct a simulation study to compare the two estimators of d obtained through regression methods. They are used in the hypothesis test to decide whether or not the series has long memory property and are compared on the basis of their k-step ahead forecast errors. The properties of long-memory models are also investigated using an actual set of data.     

Multilevel IRT models for the university teaching evaluation

In this paper, a generalization of the two-parameter partial credit model (2PL-PCM) and of two special cases, the partial credit model (PCM) and the rating scale model (RSM), with a hierarchical data structure will be presented. Having shown how 2PL-PCM, as with other item response theory (IRT) models, may be read in terms of a generalized linear mixed model (GLMM) with two aggregation levels, a presentation will be given of an extension to the case of measuring the latent trait of individuals aggregated in groups. The use of this Multilevel IRT model will be illustrated via reference to the evaluation of university teaching by students following the courses. The aim is to generate a ranking of teaching on the basis of student satisfaction, so as to give teachers, and those responsible for organizing study courses, a background of information that takes the opinions of the direct target group for university teaching (that is, the students) into account, in the context of improving the teaching courses available.     

The Management of Redundancies in Europe: The Case of Italy

The paper presents the findings of comparative and interdisciplinary legal and economic study on managing labour redundancies in seven EU member countries. It is structured for comparability between the systems examined. The introductory section contains an account of the evolution of the Italian labour market, with special reference to redundancy trends, of the features of the programmes for managing redundancies, of the roles of firms and the ‘external environment’ in handling workforce adjustments. The second section presents a map of policies that work to prevent labour redundancies (preventive measures) such as flexibility, training etc. Next, the instruments for handling temporary labour redundancies (retentive measures) are examined (e.g. short-time working, temporary layoffs etc.). The following section is devoted to instruments and programmes involved in the management of permanent labour redundancies (expulsive measures), e.g. collective dismissals, severance pay etc. The final section provides an overall assessment of the Italian system for managing labour redundancies, and briefly discusses the national debate on the prospects for reform, in light of the principles and policies of convergence set forth by the European Union.     

Discovering associations between players' performance indicators and matches' results in the European Soccer Leagues

The application of data mining techniques and statistical analysis to the sports field has received increasing attention in the last decade. One of the most famous sports in the world is soccer, and the present work deals with it, using data from the 2009/2010 season to the 2015/2016 season from nine European leagues extracted from the Kaggle European Soccer database. Overall performance indicators of the four roles in a soccer team (forward, midfielder, defender and goalkeeper) for home and away teams are used to investigate the relationships between them and the results of matches, and to predict the wins of the home team. The model used to answer both these demands is the Bayesian Network. This study shows that this model can be very useful for mining the relations between players'' performance indicators and for improving knowledge of the game strategies applied by coaches in different leagues. Moreover, it is shown that the ability to predict match results of the proposed Bayesian Network is roughly the same as that of the Naive Bayes model.     

Relational Resources of Individuals Living in Couple: Evidence from an Italian Survey

The need for support becomes stronger in situations of pressure, uncertainty and overload caused by unfavorable economic, demographic or social circumstances. Especially in countries—such as Italy—where an adequate welfare system is lacking, the individual’s social space can represent a resilience (anti-frailty) tool through the activation of a support network. While the literature has mainly analyzed the support that some vulnerable categories (e.g., elderly and youths) receive from their family, we focus on individuals living in Italy in the first stages of their family life, with the aim of describing their support network. We construct the potential support ego-centered (PSE) network—at partner and couple level—of individuals living in couple using data from the survey “Family and Social Subjects” carried out in Italy in 2009 by the Italian National Statistical Institute. Furthermore, we compare the network typologies detected using two alternative clustering techniques with the objective of finding the partners’ and couples’ network types and verifying whether traditional strong support received by the family persists in Italy and/or whether new kinds of support networks are emerging. Several PSE network typologies, ranging from empty to comprehensive networks, were determined with a fair match between the two procedures. Analysis revealed the importance of friends and neighbors, especially in the North of Italy, to the support of partners and couple as a whole.     

Dropout of Hospital Volunteers in Italy

Voluntary work in Charities is a constantly growing reality: in particular, in the last few years, voluntary work in hospitals has become of great importance, marking a substantial increase of commitment in social issues. However, at the same time, volunteering Charities have been plagued by the increase of the phenomenon of dropout, that is, volunteers abandoning the Charitable Association they’re working in, often after a relatively short period of activity. In this study, we attempted to verify if and how active and dropped out volunteers perceive their own activity as a source of anxiety and stress. Our data show that both active and dropped out volunteers show high levels of burnout; in fact, dropped out volunteers show higher levels of burnout, especially of emotional exhaustion, in comparison with active volunteers. Subsequently, we identified the factors potentially assuming the role of mediators or moderators in the direct relation involving the status of voluntary work activity and the levels of anxiety and burnout. Our study demonstrates that coping strategies and the relationship established with hospital workers can be considered good moderators.