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International audience ; [The 250 million immigrants as the United Nations countdown to the mid-2010s under three geographic fields. The first concerns the sustainability of migratory couples, the second concerns the migratory field intracontinental and the third is due to a globalization of migration flows.] ; Les 250 millions d'immigrants que décompte l'ONU au milieu des années 2010 re-lèvent de trois champs géographiques. Le premier tient à la pérennité de couples migra-toires, le deuxième concerne des champs migratoires intracontinentaux et le troisième s'explique par une mondialisation des flux migratoires.

International audience [The 250 million immigrants as the United Nations countdown to the mid-2010s under three geographic fields. The first concerns the sustainability of migratory couples, the second concerns the migratory field intracontinental and the third is due to a globalization of migration flows.] ; Les 250 millions d'immigrants que décompte l'ONU au milieu des années 2010 re-lèvent de trois champs géographiques. Le premier tient à la pérennité de couples migra-toires, le deuxième concerne des champs migratoires intracontinentaux et le troisième s'explique par une mondialisation des flux migratoires.

International audience ; [The 250 million immigrants as the United Nations countdown to the mid-2010s under three geographic fields. The first concerns the sustainability of migratory couples, the second concerns the migratory field intracontinental and the third is due to a globalization of migration flows.] ; Les 250 millions d'immigrants que décompte l'ONU au milieu des années 2010 re-lèvent de trois champs géographiques. Le premier tient à la pérennité de couples migra-toires, le deuxième concerne des champs migratoires intracontinentaux et le troisième s'explique par une mondialisation des flux migratoires.

In this article, we incorporate the study of diasporas into international relations (IR) theory by focusing on diasporas as independent actors who actively influence their homeland (kin-state) foreign policies. We argue that diasporic influences can best be understood by situating them in the 'theoretical space' shared by constructivism and liberalism; two approaches that acknowledge the impact of identity and domestic politics on international behavior. We also maintain that the exploration of diasporic activities can enrich both constructivism and liberalism. First, diasporas' identity-based motivations should be an integral part of the constructivist effort to explain the formation of national identities. Second, diasporic activities and influences in their homelands expand the meaning of the term 'domestic politics' to include not only politics inside the state but also inside the people For the liberal approach, this is a "new fact" in the Lakatosian sense of the word. We theorize that the extent of diasporic influence on homeland foreign policy is determined by three components that make up the 'balance of power' between homelands and diasporas. We then test this theory by delving into the interaction between the newly established state of Armenia and its powerful diaspora, and by comparing this case with examples taken from the relations between Israel and diaspora Jews.

Some of the most important phenomena in international conflict are coded as "rare events": binary dependent variables with dozens to thousands of times fewer events, such as wars and coups, than "nonevents." Unfortunately, rare events data are difficult to explain and predict, a problem stemming from at least two sources. First, and most important, the data-collection strategies used in international conflict studies are grossly inefficient. The fear of collecting data with too few events has led to data collections with huge numbers of observations but relatively few, and poorly measured, explanatory variables. As it turns out, more efficient sampling designs exist for making valid inferences, such as sampling all available events (wars, for example) and a tiny fraction of nonevents (peace). This enables scholars to save as much as 99 percent of their (nonfixed) data-collection costs or to collect much more meaningful explanatory variables. Second, logistic regression, and other commonly used statistical procedures, can underestimate the probability of rare events. We introduce some corrections that outperform existing methods and change the estimates of absolute and relative risks by as much as some estimated effects reported in the literature. We also provide easy-to-use methods and software that link these two results, enabling both types of corrections to work simultaneously.