Русский национализм как проблема российской общественности. Попытка философской проблематизации
This book emanates from the research project ‘Nation-building, nationalism and the new “other” in today’s Russia’ (NEORUSS) funded by the Research Council of Norway under the Russia and the High North/Arctic (NORRUSS) programme, project number 220599. It is a sequel to The New Russian Nationalism: Imperialism, Ethnicity and Authoritarianism, 2000–15 (2016), edited by Pål Kolstø and Helge Blakkisrud, likewise published by Edinburgh University Press. Since our research project commenced, major events have taken place that affect Russian nationalism, in particular the annexation of Crimea and the war in Eastern Ukraine. The first volume was well underway when these momentous developments unfolded and we were able to refl ect on them only to a limited degree. In this second volume, with more distance to these events, we are better able to incorporate the effects of the Ukrainian crisis on Russian nationalism.
The article provides a comparison of two intellectual accounts of experiences in the First World War – From the Letters of an Artillery Ensign (1918) by the Russian philosopher and writer Fjodor Stepun and The Storm of Steel (1920) by the German essayist Ernst Jünger. The aim of this article is to reveal similarities and differences between “optics” of Jünger and Stepun who are reporting one and the same event but deal with two different images of the Great War.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.