Geographical Aspects of Activities of Nongovernmental Organizations and Civic Initiatives in Czechia - Local and Regional Level in the Case of Liberec Region
Abstract
This dissertation thesis is trying to find and apply a political-geographical approach to the study of political activities of the civil society. From theoretical viewpoint, It stresses an importance of an active role of a citizen as an actor in liberal democracy, in a complex society, but also a conflictful character or forms of a part of CS, which, by its public control, finally contributes to strengthening and maintaining of democracy.
It also admits a possible risk of conflict with representative democracy. The issue is studied also empirically on the example of local and regional level in the Liberec Region, where impacts of a hierarchical level, a distance from the centre, the territory resettled after the WWII and other possible geographical influencing factors.
As the data source about the organisations and activities of the civil society the thesis uses namely these three items: (i) data from the Register of Economical Subjects about subjects associating their members as to enforcing common interests (the CZ-NACE ""94*"" category); (ii) media data obtained by own research from servers Deník.cz and iDNES.cz using Google Advanced Search, according to selected keywords. From 2857 newspaper articles automatically researched from years 2010-2014 there were selected, based on criteria defined in advance, 381 relevant articles.
On this basis, an analysis of protest and other events was processed; (iii) The thesis also studies successfulness of traditional associations and other groups excepting classical political parties in municipal elections 2010 and 2014. Regarding the data from all the sources, on the one hand, geographical aspects of other phenomena are analyzed, using a basic cartographic projection and aggregate table outputs.
On the other hand, as to outline influences of possible geographical factors and spatial patterns, methods of multivariate linear regression and local spatial autocorrelation (LISA) are employed.