Православная церковь при новом патриархе
The chapter focuses on one of the ways to communicate with the sacred popular among contemporary Russian Orthodox believers – written appealing to the saints (letters and notes). Although not happy at all about this habit, the Church managers allow to publish these letters in the parish newspapers and web-sites and in other church mass-media. Analysis of publications of the letters addressed to Saint Xenia of Petersburg proves that the Church publishes them as a part of its advertising campaign targeted on those people who prefer irregular religiosity (pilgrimages, letters to the saint, etc) to traditional regular parish life. The chapter develops Peter Berger’s metaphor of religious market.
In this book the author explores the social, economic and legal status of the Russian lower clergy (priests, deacons and sacristans), its role in the parish life and the institutional history of the Russian parish in the 16-17th centuries. The institution of proprietary or private churches (German Eigenkirchenwesen) is analysed and compared with the analogous phenomena in Byzantium and Western and Central Europe. Special attention is given to state legislation and policy, which influenced the status of the lower clergy, and the formation of the clerical estate (dukhovnoe soslovie). Various sources have been examined: the tsar’s immunity charters, cadastres, private contracts, letters, literary works, materials from the archives of the bishop’s chancelleries etc.
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.