Jia Miao & Xiaogang Wu 
Understanding Inequality in China [PDF ebook] 
The Contribution of the Chinese General Social Survey

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This edited volume provides an overview of inequality and stratification in contemporary China. A rare and timely resource, it presents key research on the topic published in Chinese Sociological Review from 2011 to 2023, using one or multiple waves of Chinese General Social Survey (CGSS) data, reflecting the advancement of the field over the past decade. The CGSS, launched in 2003 and modelled after the US General Social Survey, is an annual or biennial cross-sectional survey of a nationally representative sample of the population from all provinces except for Tibet. Certain waves of CGSS data (e.g., 2003 and 2008) contain detailed retrospective information about education and job history, which can be analysed to address various issues related to educational stratification and career mobility in both the pre-reform and reform eras. At the junction of the 20th anniversary of the CGSS (2003-2023), this volume draws on CGSS data to uncover dynamic and evolving inequality in China by examining topics such as education stratification, income inequality, career and intergeneration mobility, and how they are shaped by the socialist/post-socialist institutional structure such as the household registration (hukou) system, the work unit (danwei) system. This collection significantly advances the understanding of Chinese social stratification, extending far beyond scholars’ initial interests in the social consequences of the market transition. This volume invites social scientists to think more deeply about how politics and economics interplay with other social and demographic trends in shaping the pattern of inequality and provides a rich source and foundation for understanding inequality dynamics in contemporary China.

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Lingua Inglese ● Formato PDF ● Pagine 380 ● ISBN 9781040254967 ● Editore Jia Miao & Xiaogang Wu ● Casa editrice Taylor & Francis ● Pubblicato 2024 ● Scaricabile 3 volte ● Moneta EUR ● ID 9978544 ● Protezione dalla copia Adobe DRM
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