Through the example of the U Street block in Washington, D.C., the noted American urbanist shows that urban “contact zones” in which people disunited by racial, ethic, confessional and class conflicts are living side by side, serve as generators of new adaptive strategies. The inexhaustible source of viability and flexibility of these communities lies in the need for survival in the conditions of “deliberate social complexity”. It is precisely this experience that enables such communities effectively to adapt to the aftermaths of natural calamities and social conflicts.
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.