Big Data for the Study of Qing Officialdom: The China Government Employee Database-Qing (CGED-Q)

Chen, Bijia; Campbell, Cameron Dougall; Ren, Yuxue; Lee, James

doi:10.1017/jch.2020.15

Cited by 15 publications

(13 citation statements)

References 4 publications

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“…32 See Chen et al (2020) for an English language introduction and Ren et al (2016) for a Chinese language introduction to the project, sample of results, and complete list of the collaborators, students, and coders who contributed to the CGED-Q. 33…”

Section: Phase 3 -The Expansion 2009-presentmentioning

confidence: 99%

“…Analysis of the CGED-Q has already yielded insights into Qing officialdom and the careers of officials not available from traditional approaches to the study of the Qing civil service which emphasize case studies of individuals or offices, or specific time periods. Ren et al (2016), Chen (2019) and Chen et al (2020) show that the central government, especially its upper reaches, were dominated by Manchu and other bannermen right up to the end of the Qing. Only a relatively small share of Han who qualified by their civil service examination performance served in the central government largely confined to the Hanlin Academy and related offices.…”

Section: Chinamentioning

confidence: 99%

“…Outside the central government, however, officials were predominantly Han, and included more holders of purchased degrees than holders of exam degrees. Median career length was just under seven years, except for bannermen and holders of gongsheng exam degrees, whose medium career length was three years (Chen et al, 2020). The abolition of the examination system in 1905 had little effect on the holders of exam degrees who were already officials, or on holders of exam degrees who awaited appointment.…”

Section: Chinamentioning

confidence: 99%

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Historical Chinese Microdata. 40 Years of Dataset Construction by the Lee-Campbell Research Group

Campbell¹,

Lee²

2020

hlcs

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The Lee-Campbell Group has spent forty years constructing and analysing individual-level datasets based largely on Chinese archival materials to produce a scholarship of discovery. Initially, we constructed datasets for the study of Chinese demographic behaviour, households, kin networks, and socioeconomic attainment. More recently, we have turned to the construction and analysis of datasets on civil and military officials and other educational and professional elites, especially their social origins and their careers. As of July 2020, the datasets include nominative information on the behaviour and life outcomes of approximately two million individuals. This article is a retrospective on the construction of these datasets and a summary of their findings. This is the first time we have presented all our projects together and discussed them and the results of our analysis as a single integrated whole. We begin by summarizing the contents, organization, and notable features of each dataset and provide an integrated history of our data construction, starting in 1979 up to the present. We then summarize the most important results from our research on demographic behaviour, family, and household organization, and more recently inequality and stratification. We conclude with a reflection on the importance of data discovery, flexibility, interaction and collaboration to the success of our efforts.

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Section: Phase 3 -The Expansion 2009-presentmentioning

confidence: 99%

Section: Chinamentioning

confidence: 99%

Section: Chinamentioning

confidence: 99%

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Historical Chinese Microdata. 40 Years of Dataset Construction by the Lee-Campbell Research Group

Campbell¹,

Lee²

2020

hlcs

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“…One such newly-constructed quantitative historical dataset is the CGED-Q (China Government Employee Database-Qing) [3], [4]. It records the career trajectories of over 340,000 government officials in the bureaucracy of Qing China from 1760 to 1912.…”

Section: Introductionmentioning

confidence: 99%

Interactive Visual Exploration of Longitudinal Historical Career Mobility Data

Wang

Liang

Shu

et al. 2022

IEEE Trans. Visual. Comput. Graphics

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The increased availability of quantitative historical datasets has provided new research opportunities for multiple disciplines in social science. In this paper, we work closely with the constructors of a new dataset, CGED-Q (China Government Employee Database-Qing), that records the career trajectories of over 340,000 government officials in the Qing bureaucracy in China from 1760 to 1912. We use these data to study career mobility from a historical perspective and understand social mobility and inequality. However, existing statistical approaches are inadequate for analyzing career mobility in this historical dataset with its fine-grained attributes and long time span, since they are mostly hypothesis-driven and require substantial effort. We propose CareerLens, an interactive visual analytics system for assisting experts in exploring, understanding, and reasoning from historical career data. With CareerLens, experts examine mobility patterns in three levels-of-detail, namely, the macro-level providing a summary of overall mobility, the meso-level extracting latent group mobility patterns, and the micro-level revealing social relationships of individuals. We demonstrate the effectiveness and usability of CareerLens through two case studies and receive encouraging feedback from follow-up interviews with domain experts.

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“…We arrived at the approach we describe here iteratively, building on experience analyzing career histories in the CGED-Q JSL in a series of publications on appointment, promotion, and exit of Qing officials (Campbell, 2020;Chen, Campbell, & Lee, 2018;Hu, Chen, & Campbell, 2020;Hu, Hu, Chen, & Campbell, 2021;Xue & Campbell, 2022), a visualization platform (Wang et al, 2021), an introduction to the CGED-Q JSL (Chen, Campbell, Ren, & Lee, 2020) and a dissertation (Chen, 2019). Each analysis brought to light issues with the sources, the transcription process, and linkage procedures that had not arisen previously and required adjustments.…”

Section: Introductionmentioning

confidence: 99%

Nominative Linkage of Records of Officials in the China Government Employee Dataset-Qing (CGED-Q)

Campbell

Chen

2022

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We introduce our approach to the nominative linkage of records of Qing officials who were included in the China Government Employee Datasets-Qing (CGED-Q) Jinshenlu (JSL) and Examination Records (ER). We constructed these datasets by transcription of quarterly rosters of civil and military officials produced by the government and by commercial presses, and records of examination degree holders. We assess each of the primary attributes available in the original sources in terms of their usefulness for disambiguation, focusing on their diversity and potential for inconsistent recording. For officials who were not affiliated with the Eight Banners, these primary attributes include surname, given name, and province and county of origin. For the small subset of officials who were affiliated with the Bannermen, we assess the available data separately. We also assess secondary attributes available in the data that may be useful for adjudicating candidate matches. We then describe the approach that we developed that addresses the issues we identified with the primary and secondary attributes. The issues we have identified and the approach that we have developed will be of interest to researchers engaged in similar efforts to construct and link datasets based on elite males in historical China.

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Big Data for the Study of Qing Officialdom: The China Government Employee Database-Qing (CGED-Q)

Cited by 15 publications

References 4 publications

Historical Chinese Microdata. 40 Years of Dataset Construction by the Lee-Campbell Research Group

Historical Chinese Microdata. 40 Years of Dataset Construction by the Lee-Campbell Research Group

Interactive Visual Exploration of Longitudinal Historical Career Mobility Data

Nominative Linkage of Records of Officials in the China Government Employee Dataset-Qing (CGED-Q)

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