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Integration is a fundamental mandate of schooling in democratic and differentiated societies. This chapter analyzes the consequences generated by an increase in number of students without Italian citizenship in Italian schools, and the development of multiethnic classrooms. When non-Italian pupils comprise >25–50% of the pupils in classrooms, it’s worth questioning: Are these classrooms segregated? Which factors affect school integration and for whom? The chapter presents the results of the first survey on classrooms with a “high density” of students with an immigrant background carried out in Italy. This study is based on a sample of 1,040 students enrolled in lower secondary education in Lombardy. We use statistical indicators related to two dimensions of integration: (a) the institutional dimension (school access and achievement), and (b) the relational dimension (well-being and absence of conflicts among peers). Data analysis included indexes and a correlation matrix between indexes, regression analysis, and cluster analysis. Results demonstrate a positive correlation between the rate of non-native students in the classroom and low degree of integration, but also the complexity of factors at stake such as gender imbalance and the high concentration of students whose families have a low Socio-Economic Status (SES), independently from citizenship. These results enabled us to de-construct the concept of school integration, identifying a plurality of integrative factors and providing suggestions for intervention.

The continued flow of immigrants in various countries, including Finland, has made it necessary to assess their level of integration for both academic and policy reasons. Despite the proliferation of multiple immigration integration indices, none of them are irreproachable. The indicators of integration levels are context-dependent. The index should also be both standardized to facilitate cross-comparative research and flexible to be relevant across multiple contexts. The choice of the unit of analysis also alters the definition of integration.

The main purpose of this study is to identify the indicators of immigration integration levels at the individual level in the Finnish context. Thereafter, a combined index identifying six types of integration measures – psychological, linguistic, economic, political, social and navigational – based on the Immigration Policy Lab (IPL) Integration Index, is administered to foreigners in Finland (N = 86). The sample consists of young (20–40), highly educated individuals, from 36 different countries who have migrated to Finland predominantly for family and study purposes.

The results show that immigrants who have stayed longer in Finland and are highly educated display higher levels of integration. Immigrants who are naturalized citizens display higher levels of integration across all dimensions. IPL Integration Index performs in the expected direction and can be applied across Finland in a larger random sample, after slight modifications, to increase generalizability. The study further suggests that Finnish immigration integration schemes focus excessively on macrolevel policies aiming at linguistic, economic and navigational integration of new immigrants at the cost of individual psychosocial integration of well-established immigrants.

The paper examines the degree of interlocking directorships across the major Eurozone economies. It uses the major stock market indices in France, Germany, Italy, the Netherlands, and Belgium to identify the top of the corporate elite in each country. For the period of 2005–2008, it studies transnational links between European companies. The paper draws attention to a number of features of these interlocks. Firstly transnational interlocks remain relatively low but secondly they do vary considerably. An important issue here is the degree of bilateral integration which is occurring between some countries within the Eurozone, for example France and Belgium, and the degree to which other countries, most notably, Italy are increasingly disconnected, whilst the two most powerful economies, France and Germany, are very weakly connected. This variability reflects a series of structural divides between big business in the Eurozone that makes it difficult for this corporate elites to be cohesive at the European level.

Economic and financial integration (hereafter, economic integration) among economies has been a fertile area of research. Yet, what we argue is that economic integration needs new thoughts to adequately model the recent challenges to the global economy by developing a new index/measure of economic integration. The new index will not only shed invaluable insights into the drivers of economic integration between Australia and the Middle East but will also help craft economic, trade, and commercial policies to achieve the desired type of integration with Australia's trading partners. Our analysis is undertaken on a cross section of 140 countries for the year 2011, to understand the causes and indicators of integration. Our model combines changes in real GDP, per capita GDP, percentage of educational expense, and gender inequality as causal factors to explain integration as a latent variable. We use three indicators of integration: (1) a standard measure of economic integration, (2) exports and imports as a percentage of GDP, (3) flows of foreign direct investment. We then explore the linkages between these indicators, or manifestations of integration, and a number of its possible causes. In terms of the new index we rank 140 nations and note that Australia is ranked among the top 20 nations in terms of integration with the global economy. Except Israel and Oman, Australia's trade partners in the Middle East have little integration with the global economy. In a similar vein, we also find that Australia's northern neighbors – especially Indonesia, Malaysia, Thailand, Cambodia, Myanmar, Sri Lanka, India – are yet to get well-integrated with the global economy. As a result, we argue, Australia can lead these countries from Southeast Asia and the Middle East to form closer ties with the global economy via Australia and, by doing so, Australia can create unprecedented economic and social benefit.

This chapter measures financial integration in 10 industries over 4 different periods. We use two robust measures of integration: (i) the Pukthuanthong and Roll (2009)’s multi-factor R-square and (ii) the Volosovych (2011)’s integration index. Both measures, based on PCA, indicate that the difference between the level of integration over the period 2009–2012 (“Post-Lehman” era) and the level of integration over the period 1994–1998 (“Post-Liberalizations” era) is relatively high. In addition, the level of financial integration across international equity markets decreased during the late 1990s. This suggests that de jure integration does not necessarily improve de facto integration. Overall, our findings give rise to a “diversification benefits-insurance benefits trade-off.”

This article axiomatically derives a class of numerical indices of integration (equality) in the distribution of different types of workers across occupations. The associated segregation (inequality) indices parallel one form of multidimensional generalized Gini inequality indices. A comparison is made with the other Gini-related segregation indices. A numerical illustration of the family of indices is also provided using US occupational data.