Clientelism and Informal Networks of Regional Elites in Russia:
Network Analysis of the Case of Sverdlovsk Oblast
Melnikov K.V.,
Institute of Philosophy and Law, Ural Branch of the Russian Academy of Sciences, Ekaterinburg, Russia, melnikovrezh@gmail.com
elibrary_id: 913396 | ORCID: 0000-0001-7200-659X | RESEARCHER_ID: AAB-7492-2020
DOI: 10.17976/jpps/2021.06.12
Melnikov K.V. Clientelism and Informal Networks of Regional Elites in Russia: Network Analysis of the Case of Sverdlovsk Oblast. – Polis. Political Studies. 2021. No. 6. https://doi.org/10.17976/jpps/2021.06.12
Studying informal aspects of politics in Russia and post-Soviet states more broadly has become an influential research trend. The concepts of clientelism and informal networks often serve as a theoretical framework for such an analysis. Despite obvious connotations, students of informal networks only rarely take advantage of methodological tools provided by Social Network Analysis (SNA). They not only allow scholars to visualize a network and to calculate its basic statistic characteristics, but also puts forth more rigorous requirements for the operationalization of the informal network, thereby making it a logically conceptualized category and not just a metaphor, as it is often presented in the literature. By using SNA tools, the presented paper studies informal networks of administrative elites of the Sverdlovsk Oblast. Having experienced a relatively rapid economy recovery following the collapse of the USSR, the region’s success in bargaining with federal elites over the advancement of its legal status in the 1990s and long-term into the office of its first governor brought forth explanations that emphasize the power of elite networks in this region. This article aims to test these assumptions quantitatively. To that end, we analyzed informal networks of the heads of the executive agencies and provided three temporal snapshots. These correspond to the terms of the two governors that held the office: Eduard Rossel and Alexandr Misharin. The informal networks were based on biographical data, which we collected and recorded into the database. This database consists of 665 rows, which contain information on the career paths of 78 officials. After identifying the intersections of the career paths of these individuals prior to them occupying elite positions, we built networks based on them. We have analyzed the structures of these networks, their density, the presence of communities, and centrality measures, which allowed us to see how different the patterns of the networks can be depending on the strategies of their leaders.
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