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Life Histories and Social Change in Contemporary China, 1996 (M889V1)

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Mendeley Data2024-03-27 更新2024-06-29 收录
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https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/33PMXL
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资源简介:
As part of the project "Life Histories and Social Change in Contemporary China," a national probability sample survey was conducted in the People's Republic of China during June-October 1996. Interviews were completed for 3,087 urban residents and 3,003 rural residents, using an identical questionnaire. These data may be regarded either as two separate samples or as a single sample stratified by urban vs. rural residence. As part of the fieldwork operation for the rural survey, a survey of 383 village leaders was also carried out, using the same questionnaire. The project was initiated in 1994 by Donald J. Treiman and Ivan Szelenyi, at UCLA, and Andrew Walder, then at Harvard and now at Stanford University and the Hong Kong University of Science and Technology, in cooperation with staff of the Department of Sociology, People's University, Beijing, a group with extensive experience carrying out sample surveys in China. Funding was obtained by Treiman, Szelenyi, and Walder from the U.S. National Science Foundation, the Luce Foundation, the Ford Foundation–Beijing, and the University of California Pacific Rim Research Program. This was a cooperative project, between the U.S. and Chinese sides. In a series of some 10 meetings the sample design for the surveys was developed and the questionnaire was hammered into final form, drawing upon the expertise of the participants plus the results of two, relatively small, pretests. At several points in its development, the questionnaire was translated from English to Chinese by members of the People’s University team and from Chinese to English by Prof. Walder and several Chinese-speaking UCLA graduate students.
创建时间:
2023-06-28
搜集汇总
数据集介绍
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背景与挑战
背景概述
该数据集是1996年在中国进行的一项全国概率抽样调查,旨在研究当代生活史和社会变化,覆盖了3,087名城市居民和3,003名农村居民,并包括383名村领导的附加调查。数据按城乡分层设计,采用相同问卷,由中美合作团队完成,资金来自多个美国基金会,适用于社会科学的比较研究。
以上内容由遇见数据集搜集并总结生成
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