We created a repository to share the STATA code that processes the original CMGPD data from the Excel spreadsheets produced by our coders and turns it into the working file that is the basis of our analysis and the public release available at ICPSR. This is intended to help users of the data better understand the process by which it went from the spreadsheets transcribed by the coders to the datasets available at ICPSR. The code for linking individuals to their kin may be of particular interest.
Volume 3 of Big Data and the Study of Chinese History 大数据与中国历史研究，第三辑, edited by Fu Haiyan 付海晏 of the Central China Normal University School of History and Culture 华中师范大学历史文化学院 and published by the Social Sciences Academic Press (China) 社会科学文献出版社, contains a number of chapters related to Lee-Campbell Group Projects, or by members of the Lee-Campbell Group.
Here is a link to the complete Chinese language text of the State views and Local Views paper at Weixin: https://mp.weixin.qq.com/s/wGfMhYIogXHlVGwosIp5_Q
Here is an announcement of the volume at the web page of the Chinese Academy of Social Sciences Institute of Modern History web page. The book should be available for order online in the coming weeks.
Chapters by Lee-Campbell Group members include the following:
An introduction by Bijia Chen to the process of constructing the CGED-Q, its current status, and its future prospects:
A Chinese translation of a paper by Cameron Campbell and James Lee comparing the recording of families in genealogies and household registers in Qing Liaoning that originally appeared in History and Computing. It shows that there were biases in genealogies beyond what has been recognized in earlier literature:
从国家和地方的角度看人口记录和行为 (康文林 李中清 翻:谌畅)
Essays by James Lee, Yuxue Ren, and Liang Chen on big data and quantitative history:
Two papers by Lee-Campbell Group PhD students Yang Li and Xue Qin:
The volume also includes a paper by an MA Student in the Central China Normal University program in Historical Big Data, Cai Xiaoying, that uses the publicly released CGED-Q Jinshenlu 1900-1912 Public Release, and is based on a paper that she originally wrote for the Historical Big Data class that Cameron Campbell taught in Wuhan in 2019:
At the 2020 Chinese Digital Humanities Annual Meeting (中国数字人文年会), the China Multi Generational Panel Dataset 中国多世代人口数据库 CMGPD was awarded the inaugural “最佳题材奖” Prize. This is the 14th prize or similar recognition awarded to Lee-Campbell group research projects and our first for something other than a book or article. See Publications and Prizes for a complete list.
On December 13, 2019, the Lee-Campbell Group held a dinner in Beijing in honor of Xiao Xing, who retired in 2018 after working with us for 20 years.
Xiao Xing was the first coder we engaged in mainland China in 1998 after we decided to move our data entry there. She helped enter material for many of our databases, including but not limited to the CMGPD-LN, CMGPD-SC and more recently the CGED-Q. She also helped with the training of new coders. Her feedback also played a role in the specification of protocols for data entry.
It has been a tremendous pleasure to work with Xiao Xing for two decades. We are grateful for all of her contributions and wish her the best in her retirement.
The paper “Interethnic marriage in Northeast China, 1866-1913” co-authored by current Lee-Campbell group PhD student Bijia Chen, Lee-Campbell group PhD graduate Dong Hao (now an Assistant Professor at Peking University) and Cameron Campbell that was published this year in Demographic Research has been named Editor’s Choice by the journal’s editorial board as one of the best papers published in volume 38. The paper examines patterns of intermarriage between Han and Manchu in a frontier population in northeast China from the mid-19th century to the beginning of the 20th century. It finds that intermarriage between the two groups was not uncommon and also increased over time. The chances of intermarriage depended on village and family context as well as individual socioeconomic and demographic characteristics. The article is available Open Access here:
The complete list of Editor’s Choice papers is available here: