Author: Cameron Campbell
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CGED-Q Research Seminar and Training Workshop at Central China Normal University, July 28-August 3, 2024
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…
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New paper on the organizational demography of Qing officialdom in 社會科學研究
A paper by Cameron Campbell and Shuaiqi GAO on the organizational demography of Qing officialdom has been published in 社會科學研究. You can read it in its entirety in a post at the journal’s official account. You can download the PDF at the entry for the paper at the journal’s website. The English version is available…
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Workshop on Chinese Historical Databases: Sources, Methods, Prospects held at HKUST, January 11-12, 2024
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…
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First in-person Lee-Campbell Group meeting since 2019 held 4 December 2023
The Lee-Campbell Group met in person at HKUST on December 4, 2023. This was our first in-person meeting of nearly all of the affiliates of the group since before 2020. Group members discussed their ongoing projects and their plans for future work. 15 participants attended in person, and another 3 joined online.
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New publication using process mining to study the careers of Qing officials in the CGED-Q JSL
Adam Burke at the Queensland University of Technology lead-authored a paper “State Snapshot Process Discovery on Career Paths of Qing Dynasty Civil Servants” that introduces a new process mining technique he calls ‘state snapshot process discovery’ and illustrates it by application to our CGED-Q JSL data on the careers of jinshi officials. Cameron Campbell is…
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Training guide for using R to analyze the CGED-Q JSL public releases
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…
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New 大数据与中国历史 Chinese translation of Cameron Campbell’s and James Lee’s 40 year career retrospective is now available
The 4th edition of the annual 大数据与中国历史 (Big Data and Chinese History), edited by Fu Haiyan at Central China Normal University, is out now from 社会科学文献出版社 (Social Science Documents Publishing House). It includes a Chinese translation of my and James Lee’s career retrospective, summarizing our work over the last four decades constructing and analyzing historical…
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English version of forthcoming paper on the organizational demography of the Qing civil service
社會科學研究 (Social Science Research) published by the Sichuan Academy of Social Science has accepted our paper “The Organizational Demography of the Qing Civil Service, 1830-1911” and tentatively scheduled it for publication in 2024. In the meantime, they have given permission for us to share the original English language version: The Organizational Demography of the Qing…
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Tutorial for using R to analyze the CGED-Q JSL Public Releases
Chen Jun, my MA student at Central China Normal University, has shared slides and sample code he produced to help anyone planning to use R to analyze the CGED-Q JSL public releases. The materials are all in Chinese. They introduce how to import the public data into R, create and transform variables, process strings to…
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New paper by others using CMGPD-LN
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…