Italy: the ‘illegality factory’? Theory and practice of refugees’ reception in Sicily

ABSTRACT

The recent surge of migrants crossing the Mediterranean in search of protection has presented a major challenge for the whole European Union. What has been labelled as a ‘refugee crisis’ is first and foremost a crisis of international politics and the result of inadequate response mechanisms at local level. This paper focuses on the case of Sicily, the second main area of arrival, after Greece, when migration to the Mediterranean reached its peak. With a long history of immigration, since 2015 the Italian island has seen the implementation of a new approach based on ‘hotspots’: designated areas for the separation of those deemed as economic migrants from ‘genuine asylum seekers’. In the view of some, this has made Italy into a model of migration management, as opposed to the chaotic situation of the Greek islands. The hotspot approach, however, has been also criticised for being engrained on practices that many deem unlawful, actively producing discrimination and condemning many migrants to an illegal status on the Italian soil. Informed by findings from an international research project (EVI-MED), this paper examines this complex scenario, exploring the social, legal and human implications of the refugees’ reception system in Italy.     

The power of (extended) monitoring in robust clustering

We complement the work of Cerioli, Riani, Atkinson and Corbellini by discussing monitoring in the context of robust clustering. This implies extending the approach to clustering, and possibly monitoring more than one parameter simultaneously. The cases of trimming and snipping are discussed separately, and special attention is given to recently proposed methods like double clustering, reweighting in robust clustering, and fuzzy regression clustering.     

The Recent Crisis Impact on the Economies of Some Countries of Central and Eastern Europe

Wealth of nations is nowadays something complex depending on democratic processes and debt accumulation. In Europe the EURO introduction provoked even more complexity, as there is no common government to steer the fiscal process, a situation without precedence. New solutions are therefore looked for, based on different schools of thought in order to tackle the problem. The analytical part analyzes the economic behaviour of four recently less studied countries. A comparison between them is based on time series of Real GDP Growth, Consumer Price Inflation, Government Balance.     

Prognostic assessment of repeatedly measured time-dependent biomarkers,with application to dilated cardiomyopathy

We propose new time-dependent sensitivity, specificity, ROC curves and net reclassification indices that can take into account biomarkers or scores that are repeatedly measured at different time-points. Inference proceeds through inverse probability weighting and resampling. The newly proposed measures exploit the information contained in biomarkers measured at different visits, rather than using only the measurements at the first visits. The contribution is illustrated via simulations and an original application on patients affected by dilated cardiomiopathy. The aim is to evaluate if repeated binary measurements of right ventricular dysfunction bring additive prognostic information on mortality/urgent heart transplant. It is shown that taking into account the trajectory of the new biomarker improves risk classification, while the first measurement alone might not be sufficiently informative. The methods are implemented in an R package (longROC), freely available on CRAN.     

Modelling work history patterns in the Italian labour market

We focus on work histories of new entrants in 1998 in the Italian labour market. For workers in the private sector, we define a standard and three non-standard history patterns. We profile the workers through a mixed-effect multinomial logit model and show that certain features may be associated with the probability of belonging to one or the other category. Furthermore, we show that there are differential effects on wages associated with non-standard patterns. A closer look at best performing non-standard workers shows that even for them an early contractual stabilization may not always be expected.     

Volunteer Motivation and Organizational Climate: Factors that Promote Satisfaction and Sustained Volunteerism in NPOs

Keeping volunteers committed and engaged is one of the toughest challenges for NPOs. The aim of the present study is to investigate the individual and organizational factors that promote volunteer satisfaction and, vice versa, foster intentions to quit. Two hundred forty-seven volunteers operating in four different NPOs were asked to fill in a self-report questionnaire that aimed to explore their motivations to volunteer, their degree of satisfaction and their perception of the organizational climate in the NPO they worked with, in addition to providing details of the activities which they were involved in. Results showed that the organizational climate mediates the relationship between autonomous motivation and satisfaction, as well as that between external motivation and intentions to leave an organization.     

Snipping for robust k-means clustering under component-wise contamination

We introduce the concept of snipping, complementing that of trimming, in robust cluster analysis. An observation is snipped when some of its dimensions are discarded, but the remaining are used for clustering and estimation. Snipped k-means is performed through a probabilistic optimization algorithm which is guaranteed to converge to the global optimum. We show global robustness properties of our snipped k-means procedure. Simulations and a real data application to optical recognition of handwritten digits are used to illustrate and compare the approach.     

Joint analysis of occurrence and time to stability after entrance into the Italian labour market: an approach based on a Bayesian cure model with structured stochastic search variable selection

Precarious employment is a serious social problem, especially in those countries, such as Italy, where there are limited benefits from social security. We investigate this phenomenon by analysing the initial part of the career of employees starting with unstable contracts for a panel of Italian workers. Our aim is to estimate the probability of getting a stable job and to detect factors influencing both this probability and the duration of precariousness. To answer these questions, we use an ad hoc mixture cure rate model in a Bayesian framework.