{"title":"用机器学习方法研究德国战略文化","authors":"Jonathan Tappe, Fredrik Doeser","doi":"10.1080/13523260.2021.1992150","DOIUrl":null,"url":null,"abstract":"ABSTRACT This article introduces supervised machine learning to the study of German strategic culture, analyzing both how German strategic culture has changed and the impact of strategic culture on Germany's military engagement between 1990 and 2017. In contrast with previous qualitative research on strategic culture, supervised machine learning can yield measurable and empirical insights into strategic culture and its effects at any given point in time over a very long period, based on the reproduction of human coding of a very extensive set of security policy documents. The article shows that German strategic culture has changed slowly and in a nonlinear way after the Cold War, and that strategic culture, when controlling for confounding variables and the temporal order, has a measurable impact on Germany's military engagement. The article demonstrates the analytical value of machine learning for future studies of strategic culture.","PeriodicalId":46729,"journal":{"name":"Contemporary Security Policy","volume":"42 1","pages":"450 - 474"},"PeriodicalIF":4.0000,"publicationDate":"2021-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A machine learning approach to the study of German strategic culture\",\"authors\":\"Jonathan Tappe, Fredrik Doeser\",\"doi\":\"10.1080/13523260.2021.1992150\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT This article introduces supervised machine learning to the study of German strategic culture, analyzing both how German strategic culture has changed and the impact of strategic culture on Germany's military engagement between 1990 and 2017. In contrast with previous qualitative research on strategic culture, supervised machine learning can yield measurable and empirical insights into strategic culture and its effects at any given point in time over a very long period, based on the reproduction of human coding of a very extensive set of security policy documents. The article shows that German strategic culture has changed slowly and in a nonlinear way after the Cold War, and that strategic culture, when controlling for confounding variables and the temporal order, has a measurable impact on Germany's military engagement. The article demonstrates the analytical value of machine learning for future studies of strategic culture.\",\"PeriodicalId\":46729,\"journal\":{\"name\":\"Contemporary Security Policy\",\"volume\":\"42 1\",\"pages\":\"450 - 474\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2021-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Contemporary Security Policy\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1080/13523260.2021.1992150\",\"RegionNum\":1,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INTERNATIONAL RELATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Contemporary Security Policy","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1080/13523260.2021.1992150","RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INTERNATIONAL RELATIONS","Score":null,"Total":0}
A machine learning approach to the study of German strategic culture
ABSTRACT This article introduces supervised machine learning to the study of German strategic culture, analyzing both how German strategic culture has changed and the impact of strategic culture on Germany's military engagement between 1990 and 2017. In contrast with previous qualitative research on strategic culture, supervised machine learning can yield measurable and empirical insights into strategic culture and its effects at any given point in time over a very long period, based on the reproduction of human coding of a very extensive set of security policy documents. The article shows that German strategic culture has changed slowly and in a nonlinear way after the Cold War, and that strategic culture, when controlling for confounding variables and the temporal order, has a measurable impact on Germany's military engagement. The article demonstrates the analytical value of machine learning for future studies of strategic culture.
期刊介绍：
One of the oldest peer-reviewed journals in international conflict and security, Contemporary Security Policy promotes theoretically-based research on policy problems of armed conflict, intervention and conflict resolution. Since it first appeared in 1980, CSP has established its unique place as a meeting ground for research at the nexus of theory and policy.
Spanning the gap between academic and policy approaches, CSP offers policy analysts a place to pursue fundamental issues, and academic writers a venue for addressing policy. Major fields of concern include:
War and armed conflict
Peacekeeping
Conflict resolution
Arms control and disarmament
Defense policy
Strategic culture
International institutions.
CSP is committed to a broad range of intellectual perspectives. Articles promote new analytical approaches, iconoclastic interpretations and previously overlooked perspectives. Its pages encourage novel contributions and outlooks, not particular methodologies or policy goals. Its geographical scope is worldwide and includes security challenges in Europe, Africa, the Middle-East and Asia. Authors are encouraged to examine established priorities in innovative ways and to apply traditional methods to new problems.
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