Ewa Rumińska-Zimny přednáší genderová studia na Polské akademii věd a je prezidentkou Mezinárodního fóra pro ženy v akademii a obchodu na Varšavské vysoké škole ekonomické. Akademickou práci spojuje s prací pro Organizaci spojených národů. Autorsky a editorsky se podílela na přípravě řady zpráv OSN, například Zpráv o lidském rozvoji, a v Evropské hospodářské komisi OSN v Ženevě spolupracovala na hodnocení závazků přijatých na Konferenci OSN o ženách v Pekingu. Odborně se zabývá procesy tranzice ve východní a střední Evropě, feministickou ekonomií a genderovou rovností. Je členkou Mezinárodní asociace feministických ekonomů a ekonomek (IAFFE) a spoluzakladatelkou GEM-Europe, který je součástí globální vědecké sítě Gender a makroekonomika., Dr. Ewa Rumińska-Zimny is a lecturer in Gender Studies at the Polish Academy of Science and the President of the International Forum of Women in Academia and Business at the Warsaw School of Economics. She combined academic work with work for the United Nations. Her work included writing and coordination of UN reports, e.g., Human Development Reports, analyses of the transition process in Eastern and Central Europe and reviews of progress in gender equality within the framework of the Beijing process at the UN Economic Commission for Europe in Geneva. She is a member of the International Association of Feminist Economists (IAFFE) and the initiator of GEM Europe, a part of the global network of researchers on Gender and Macroeconomics., Ewa Rumińska-Zimny, Zuzana Uhde, Alena Křížková., and Obsahuje seznam literatury
The paper presents to Czech social scientists an introductory review of the concept of equivalence and the method of blockmodeling in social network analysis (SNA). After introducing the central concepts of SNA such as node and tie, along with their basic metrics such as centrality and cohesion, I present the concepts of role and position. These are treated by SNA as clusters of nodes with similar ties, something I juxtapose to algorithms to identify cohesive subgroups of nodes. Subsequently, I define and compare the two most frequently applied types of equivalence - structural, which is strict but broadly applicable, and regular, which is more liberal but has limited uses. Structural equivalence builds on a strict definition of similarity of ties, treating as equivalent only such nodes that have the same ties to the same other nodes. Regular equivalence works with looser criteria and better corresponds with both the theoretical and the intuitive notions of role; this, however, is outweighed by the absence of a unique regular-equivalent solution within a network and by the difficulty to process networks with undirected ties. Regular-equivalent nodes are such that have ties to other mutually equivalent nodes. I present examples to demonstrate the differences between both definitions. In the following section, I discuss measurement of similarity between the different nodes’ profiles of ties (e.g., correlation and Euclidean distance) and possible uses of the standard statistical methods of cluster analysis and multidimensional scaling to detect equivalent classes of nodes within networks. After pointing to the weaknesses of these techniques in network data analysis, I present blockmodeling as a method designed specifically to identify roles and positions within networks. Ischematize the blockmodeling procedure and present its basic terms before comparing classic inductive blockmodeling, which is primarily fit for the purposes of exploration and network reduction, with deductive generalized blockmodeling, which is applicable in testing hypotheses about basic structural characteristics of a network. I bring attention to the strengths and weaknesses of both approaches. Relatedly, I present an application of blockmodeling especially for the purposes of simplified network representation, comparing structural patterns across networks, and testing structural theories. In the following section, I demonstrate specific blockmodeling algorithms based on both structural equivalence (CONCOR and Tabu Search optimization) and regular equivalence (REGE and Tabu Search optimization). Then I verify the adequacy of their resulting assignment of positions to nodes using eta coefficient, Q modularity and correlation of the ideal blocked and the empirical adjacency matrices. In the concluding section, I demonstrate the entire blockmodeling procedure on an empirical case of a small network with undirected ties using the UCINET software tool, including interpretation of results. Finally, I reflect the contemporary position of blockmodeling among leading research approaches in SNA, referring to other empirically oriented studies that demonstrate the broad applicability and utility of position analysis., Tomáš Diviák., and Obsahuje použitou literaturu a poznámky
This article deals with empirical research on poverty in Czechoslovakia from the interwar period to the present in terms of three distinct phases. First, between 1918 and 1948, considerable attention was devoted to poverty, but research possibilities modest, so that a complex mapping of the problem was not feasible. Second, during the 1948 to 1989 period, the communist regime allowed "examinations" of poverty for the purpose of depicting pre-war capitalist Czechoslovakia as an impoverished, class-divided society. A similar approach was applied to studies of Western countries during the Cold War period. Research on poverty within the socialist regime was not allowed, even after the rehabilitation of sociology as a social science. Detailed analysis of household surveys was either forbidden or the results were embargoed; only simple cross-tabulations were ever published. Third, after 1989, the opportunities for undertaking research on poverty increased dramatically due to stimulus in both the national and international arenas. Important projects were fielded leading to many studies and published articles. Statistical surveys were used to map poverty primarily in terms of income; while sociological, ethnographic and anthropological approaches were used to examine key groups affected by poverty in Czech society. Within the literature there has been to date no synthesis of the study of the nature and origins of poverty in the Czech Republic., Jiří Večerník., and Obsahuje bibliografii a bibliografické odkazy
The European Union Statistics on Income and Living Conditions (EU-SILC) set of surveys are an important source of comparative statistical data. EU-SILC provides data on income, living conditions, poverty and social exclusion, material deprivation: topics of growing interest to scholars in Europe and elsewhere. EU-SILC surveys are fielded in 29 European countries and coordinated by Eurostat. Although the survey is harmonised, the individual level microdata consists of many dissimilarities across participating countries because of different national conditions, methods of data collection and/or data processing. The aim of this article is to discuss the opportunities and limitations of EU-SILC datasets. In addition to discussing the development, methodology and basic pitfalls of EU-SILC, this article focuses on (a) income variables, (b) differences in income among countries and (c) impact of income differentials on data comparability. The main problems of income data may be summarised as follows. 1) Some countries use registers to report income variables while others obtain this information from interviews, and this difference lowers their comparability. 2) The incidence of negative or zero values makes the construction of poverty and inequality measures difficult. 3) There are national differences in the net-to-gross income conversion procedure. This study shows using a four country analysis that the net-to-gross conversion procedure overestimates gross wages in two countries and underestimates it in two others. Notwithstanding these methodological issues, EU-SILC is an important resource for the comparative study of income., Martina Mysíková., and Obsahuje bibliografii a bibliografické odkazy
The article defends the possibility of using evolutionary schemes in historical sciences, as models for interpreting cultural-historical changes. It points out the possibilities for maintaining certain space within master narratives for explaining the theories of partial developmental processes. The demographic data could, then, be used as hypothetical indicators of the processes of cultural-historical change., Jan Horský., and Obsahuje bibliografii