Chen Jun has created a R Markdown file that provides a tutorial for using R to analyze the CGED-Q, including executable code. The tutorial has been uploaded to the Lee-Campbell Group dataspaces at Harvard and HKUST, along with PDF of the output.
He has also produced updated Powerpoints showing how to use R to analyze the CGED-Q JSL.
We have updated the CGED-Q JSL User Guide 中国历史官员量化数据库-缙绅录用户指南 to reflect the 1760-1798 data that we released last year. Chen Jun and Bijia Chen were mostly responsible for this update, though we had feedback from others. We have included new data on the variables, new information about the sources, and various other edits. The new version is available for download at the Harvard Dataverse and the HKUST Dataspace:
In conjunction with the next public release of data from the CGED-Q JSL, there will be a research conference and training workshop at Central China Normal University July 28-August 3 in conjunction with the next public release of data from the China Government Employee Dataset-Qing (CGED_Q) Jinshenlu. The conference will be July 29 and July 30. Papers that make use of Jinshenlu and related sources are welcome. The training workshop will be July 31-August 2.
Here is the announcement of the research conference in Chinese:
Cameron Campbell organized a meeting on Chinese Historical Databases: Sources, Methods, Prospects on January 11 and 12, 2024 at the Hong Kong University of Science and Technology.
The meeting is one in a series of activities intended to promote the development of research infrastructure for studying China’s past organized under the auspices of and with support from the RGC Areas of Excellence Project Quantitative History of China (Chen Zhiwu PI). Staff from the HKUST School of Humanities and Social Sciences, including Lee-Campbell Group RA Shengbin Wei, provided logistical support.
The meeting brought together historians and social scientists constructing databases suited for the quantitative analysis of Chinese history. Participants from Hong Kong, mainland China, and Europe introduced their databases. These included projects that were already complete, others were in progress, and some were in the planning stages. Presentations and discussion focused not only on the content of the databases and prospects for analysis, but nuts and bolts issues related to the construction, preservation, documentation and dissemination of the databases. Several presentations covered techniques being used to automate the creation of databases, including OCR, tokenization, entity recognition, and record linkage.
Lee-Campbell Group members including Cameron Campbell, Dong Hao, Gao Shuaqi, Chen Jun, Wu Yibei, James Lee, Hou Yueran and Matt Noellert made presentations introducing their databases.
In addition to the presenters, other faculty and students attended as observers.
The meeting concluded with the development of plans for training workshops for historians to help them learn how to construct databases and make use of existing ones.
Chen Jun has created a training guide (in Chinese) to help anyone who would like to learn how to use R to analyze the CGED-Q JSL Public Releases. The PDF file is available for download here.
Chen Jun has produced other resources including slides and sample code for R, and they and the training guide are all available at this page.
We were pleased to learn that Yu Bai, Yanjun Li, and Pak Hong Lam had just published a paper “Quantity-quality trade-off in Northeast China during the Qing dynasty” in the Journal of Population Economics using the public release of the CMGPD-LN! We hope their paper along with other recent publications by others using the dataset will inspire others to use it.
We are pleased to report that the China Government Employee-Qing (CGED-Q) Jinshenlu (JSL) dataset was one of four to receive the Best Project Award (最佳项目奖 ) at the China Digital Humanities 2022 Annual Meeting held at Renmin University on November 26 and 27.
For more information about the award, please see the final report of the CDH 2022 meeting.
For more information about the CGED-Q JSL, please see the project page at the Lee-Campbell Group Website.
