Общественное мнение, или власть цифр
Results of public opinion polls confront us every day, being the main source of information about the society we live in.
The significance of public opinion for contemporary politics is constantly growing. However, people often wonder if the results of opinion polls can be trusted. What is the right way to read them? What is behind these numbers and what are they actually telling us? Are public opinion polls a contribution or an obstacle for the development of democracy? What are they — science, political technology, or something else? Greg Yudin’s “Public Opinion, or The Power of Numbers” answers these and other questions about the nature and operation of public opinion.
This article describes the results of sociological research on estimation of condition and development prospects of federalism in Russia, which was conducted by ZIRCON Research Group in January - May 2011. The opinion of population and elite groups of four regions about the foundations of Russian federalism development, administrative-territorial system of the Russian Federation and its principles, relations between subjects-regions and federative centre is presented. The results of the research indicate that at the moment a request for political and administrative autonomy of the subjects of the Federation is not obviously formulated by either citizens or regional elite groups. Regional identity is not a common phenomenon. The authors mark out necessary factors of federalism development: expansion of economic self-dependence of regions, existence of ethno-national or regional identity of citizens, democratization and decentralization.
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.