This paper explores how women’s roles and participation in resistance to Czechoslovak communism from 1968 to the Velvet Revolution serve as a base for Czech feminist thought. By examining three generations of participants through a gendered, Beauvoirian lens, the emergence of feminism can be easily charted through changing perceived gender roles and increased attention to gender issues. After the events of the Prague Spring, women from different groups of the Czechoslovak underground risked their own safety to exercise free speech and expression. Women’s struggles for greater liberties were framed by traditional gender barriers, supposed communist equality, and Western influence. To understand the experiences of female dissidents as a base for Czech feminist thought, one must examine the nature and progression of various underground communities and women’s roles within them. Since 1968, an increased emphasis on women’s freedoms and liberties has helped create a unique, local sense of femininity and feminism., Megan R. Martin., and Obsahuje bibliografii
This article focuses on methods for measuring corruption, first describing three generations of corruption indicators and then comparing them qualitatively and quantitatively. Corruption is a clandestine activity that is extremely difficult to measure; there are no official statistics on the number of corruption cases. For this reason, corruption can only be measured indirectly, by various proxies, and it is extremely hard to state whether these indicators are reliable and indeed measure the corruption phenomena in a given country. A large number of different indicators have been developed over the years that try to capture and quantify corruption. Some authors measure perceptions of corruption, others try to use “hard data” to explore the level of corruption in a country, and even others combine different measurements, weight them, and then publish composite indicators to capture the overall level of corruption in a country. This article aims to evaluate the quality of the different indicators using quantitative and qualitative methods. Possible uses and value of each individual indicator are discussed in terms of quality and practical considerations. First-generation indicators combine expert evaluations, surveys, and other data on corruption. The article focuses on the two best-known and most frequently used indicators - the Control of Corruption measurement by the World Bank and the Corruption Perception Index by Transparency International. Second-generation indicators are based on opinion surveys that ask respondents about their perceptions of and own experience with corruption. There are two types of such surveys, one focusing on the public and the other one on businesses. The second-generation indicators include surveys such as Eurobarometer, World Values Survey (WVS), European Social Survey (ESS), Global Corruption Barometer (GCB), WB BEEPS, or International Social Survey Programme (ISSP). Finally, the author presents a correlation analysis of different indicators over time and across countries, indicating whether and how strongly these three generations correlate with one another. The article concludes with a discussion on whether the three generations of indicators measure the same type of corruption and whether they can be used interchangeably. As for results, it seems that there are statistically significant associations between different types of indicators; however, this significance is, in most cases, not high enough to allow for interchangeability. Therefore, it is of utmost importance to carefully select the type of indicator used for scientific research, as results and conclusions might differ significantly depending on the indicator used., Kristýna Bašná., and Obsahuje bibliografické odkazy
The goal of this article is to inform social scientists, especially those of a quantitative orientation, about the basic characteristics of Big Data and to present the opportunities and limitations of using such data in social research. The paper informs about three basic types of Big Data as they are distinguished in contemporary methodological literature, namely administrative data, transaction data and social network data, and exemplifies how they can be utilized by quantitative social research. According to many, questionnaire-based sample survey as the dominant method of quantitative social research has found itself in a crisis, especially as response rates have decreased in most developed countries and public confidence in opinion polling has declined. The author presents the characteristics and specifics of Big Data compared to survey research - a method whose primary distinguishing characteristic is the capacity to quantify individual behaviour, social action and attitudes at the level of populations. In this context, the article draws attention to the differences between Big Data and survey data typically presented in scholarly literature, namely that datasets are not representative of known populations, the values of observed variables are systematically biased, there is a limited number of variables in Big Data sets, there is uncertainty about the meaning of observed values, and social environment has direct influence on the behaviours captured by Big Data. Attention is also paid to such characteristics of Big Data that pose an obstacle to smooth integration of this type of data in the social scientific mainstream. First, the collection, processing and analysis of Big Data is extremely demanding in terms of programming skills, something social scientists typically do not have. Second, the availability of Big Data is limited as they are normally possessed by private corporations, some of which (Facebook, Google) have undoubtedly come to form data oligopolies - and their management is mostly unwilling to share their data with traditional academics. Based on the above-mentioned specifics, differences and limitations, it is argued that Big Data currently do not have the potential of becoming a full-fledged source of social science data and replacing sample surveys as the dominant research method. Finally, the article draws attention to the specifics of different types of Big Data as they are primarily generated for purposes other than social research and result from specific situations framed by existing social relations - and it is from this perspective that Big Data should be viewed by social researchers., Johana Chylíková., and Obsahuje bibliografické odkazy