5 resultados para Political Science, Public Administration|Education, Higher


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This paper analyses the effects of public funding of higher education on the welfare of the different agents. It takes into account the hierarchical nature of the educational system and also the fact that parents always have the possibility to complement basic public education with private expenditures in individual tutoring. It is obtained that although public funding implies a larger access to higher education it is always the case that some of the agents that gain access lose in welfare terms. Moreover, it is shown that the marginal agent to access university would always prefer a pure private funding system. Thus, when studying the effects of public funding of higher education, we can not identify gaining access to University with an increase in welfare. Finally, I consider a funding system where only those that send their o¤spring to university support the funding of higher education.

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The present article is based on the MA thesis of Hou Bowen (Ph.D candidate) and on the presentation made at the ISA World Congress of Sociology held in Yokohama (Japan) on July 2014 at the Session on “Assessing Technologies: Global Patterns of Trust and Distrust” of RC23-Sociology of Science and Technology.

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This paper appears in International Journal of Information and Communication Technology Education edited by Lawrence A. Tomei (Ed.) Copyright 2007, IGI Global, www.igi-global.com. Posted by permission of the publisher. URL:http://www.idea-group.com/journals/details.asp?id=4287.

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This chapter appears in Encyclopaedia of Distance Learning 2nd Edition edit by Rogers, P.; Berg, Gary; Boettecher, Judith V.; Howard, Caroline; Justice, Lorraine; Schenk, Karen D.. Copyright 2009, IGI Global, www.igi-global.com. Posted by permission of the publisher. URL: http://www.igi-global.com/reference/ details.asp?ID=9703&v=tableOfContents

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Spatial analysis and social network analysis typically take into consideration social processes in specific contexts of geographical or network space. The research in political science increasingly strives to model heterogeneity and spatial dependence. To better understand and geographically model the relationship between “non-political” events, streaming data from social networks, and political climate was the primary objective of the current study. Geographic information systems (GIS) are useful tools in the organization and analysis of streaming data from social networks. In this study, geographical and statistical analysis were combined in order to define the temporal and spatial nature of the data eminating from the popular social network Twitter during the 2014 FIFA World Cup. The study spans the entire globe because Twitter’s geotagging function, the fundamental data that makes this study possible, is not limited to a geographic area. By examining the public reactions to an inherenlty non-political event, this study serves to illuminate broader questions about social behavior and spatial dependence. From a practical perspective, the analyses demonstrate how the discussion of political topics fluсtuate according to football matches. Tableau and Rapidminer, in addition to a set basic statistical methods, were applied to find patterns in the social behavior in space and time in different geographic regions. It was found some insight into the relationship between an ostensibly non-political event – the World Cup - and public opinion transmitted by social media. The methodology could serve as a prototype for future studies and guide policy makers in governmental and non-governmental organizations in gauging the public opinion in certain geographic locations.