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This file provides the data on relations as extracted from the Biographical Dictionary of Republican China (BDRC) with CoreNLP. This is the raw output before any form of processing and cleaning.
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\r\n", "page": "The ERC-funded ENEP-CHINA project proposes a step-change in the study of modern China reliant upon scalable data-rich history. It will deliver precise historical information at an unprecedented scale from heretofore untapped sources – as well as reshaping the analysis of existing sources – to create a new dimension in the study of the transformation of elites in modern China. It will deploy an array of cutting-edge digital methods— including data mining, sampling, and analysis within an integrated virtual research environment. To establish the validity of this approach, the project focuses on the three urban areas (Shanghai, Beijing/Tianjin, Canton/Hong Kong) that had the most profound impact on the course of modern Chinese history. The project will challenge the China-centered and group-based approach dominant in the historical literature of the past two decades. The project envisions elites in urban China as actors whose status, position, and practices were shaped by the power configurations that developed over time and whose actions through institutions and informal/formal networks in turn were a determining factor in redrawing social and political boundaries. The project will place the emphasis on the networks through which information, capital, and individuals circulated. It will investigate the transnationalization of elites as a process that overstepped the limits of institutions and nation states. The key issue that the project will address is breaking through existing limits of access to historical information that is embedded in complex sources and its transformation into refined, re-usable and sustainable data for contemporary and future study of modern China.
\r\n\r\nThis project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 788476).
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