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Article: On the Past and Future Prospects of Quantitative History Research

TitleOn the Past and Future Prospects of Quantitative History Research
量化历史研究的过去与未来
Authors
KeywordsQuantitative research
Big data
Issue Date2016
PublisherThe Institute of Qing History, Renmin University of China (中国人民大学清史研究所). The Journal's web site is located at http://qsyj.iqh.net.cn/
Citation
The Qing History Journal = 清史研究, 2016, v. 0 n. 4, p. 1-16 How to Cite?
清史研究, 2016, v. 0 n. 4, p. 1-16 How to Cite?
AbstractFor almost six decades quantitative history research has substantially deepened our understanding of history and made historical research more of a science. Regardless the field of inquiry,the basic scientific method follows five steps. First,identify the research question and develop a testable hypothesis;Second,find or generate data through experiments or from pre-existing sources relevant to the hypothesis; Third,conduct statistical analysis and hypothesis testing,including establishing or rejecting causal relations; Fourth,interpret the test results and uncover the channels through which the causality chain runs; Finally write a research report or paper summarizing the findings and analysis. This paper argues that there is considerable room for improvement in traditional historical research,in particular from the second to the fourth step outlined herein. That is historians should emphasize the use of both large samples and robust statistical methods,rather than just relying on case studies rather than replacing it; Historians should also make use of quantitative methods to establish causality and identify channels in which the causality runs. This paper shows that quantitative methods can not only make history research more robust and efficient but also discover new knowledge about history that would not be possible using traditional approaches.
Persistent Identifierhttp://hdl.handle.net/10722/263441
ISSN

 

DC FieldValueLanguage
dc.contributor.authorChen, Z-
dc.date.accessioned2018-10-22T07:38:55Z-
dc.date.available2018-10-22T07:38:55Z-
dc.date.issued2016-
dc.identifier.citationThe Qing History Journal = 清史研究, 2016, v. 0 n. 4, p. 1-16-
dc.identifier.citation清史研究, 2016, v. 0 n. 4, p. 1-16-
dc.identifier.issn1002-8587-
dc.identifier.urihttp://hdl.handle.net/10722/263441-
dc.description.abstractFor almost six decades quantitative history research has substantially deepened our understanding of history and made historical research more of a science. Regardless the field of inquiry,the basic scientific method follows five steps. First,identify the research question and develop a testable hypothesis;Second,find or generate data through experiments or from pre-existing sources relevant to the hypothesis; Third,conduct statistical analysis and hypothesis testing,including establishing or rejecting causal relations; Fourth,interpret the test results and uncover the channels through which the causality chain runs; Finally write a research report or paper summarizing the findings and analysis. This paper argues that there is considerable room for improvement in traditional historical research,in particular from the second to the fourth step outlined herein. That is historians should emphasize the use of both large samples and robust statistical methods,rather than just relying on case studies rather than replacing it; Historians should also make use of quantitative methods to establish causality and identify channels in which the causality runs. This paper shows that quantitative methods can not only make history research more robust and efficient but also discover new knowledge about history that would not be possible using traditional approaches.-
dc.languagechi-
dc.publisherThe Institute of Qing History, Renmin University of China (中国人民大学清史研究所). The Journal's web site is located at http://qsyj.iqh.net.cn/-
dc.relation.ispartofThe Qing History Journal = 清史研究-
dc.relation.ispartof清史研究-
dc.subjectQuantitative research-
dc.subjectBig data-
dc.titleOn the Past and Future Prospects of Quantitative History Research-
dc.title量化历史研究的过去与未来-
dc.typeArticle-
dc.identifier.emailChen, Z: zchen99@hku.hk-
dc.identifier.authorityChen, Z=rp02041-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.hkuros294696-
dc.identifier.volume0-
dc.identifier.issue4-
dc.identifier.spage1-
dc.identifier.epage16-
dc.publisher.placeChina-
dc.identifier.issnl1002-8587-

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