扩大冲突事件数据集的覆盖范围:三个概念验证

IF 1.2 Q3 POLITICAL SCIENCE
Andrew Shaver, Hannah Kazis-Taylor, Claudia Loomis, Mia Bartschi, Paul Patterson, Adrian Vera, Kevin Abad, Saher Alqarwani, Clay Bell, Sebastian Bock, Kieran Cabezas, Heidi Felix, Jennifer Gonzalez, Christopher Hoeft, Aileen Ibarra Martinez, Kai Keltner, Jessica Moroyoqui, Kieko Paman, Ethan Ramirez, Priscilla Reis, Juan Jose Rodriguez, Jazmin Santos-Perez, Katha Komal Sikka, Arjan Singh, Cassidy Tao, Richard Tirado, Aishvari Trivedi, Lillian Xu, Margaret You, Meriam Eskander
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引用次数: 0

摘要

摘要 许多有关政治暴力/社会动乱的当代研究都依赖于主要来自主要国际/国家新闻报道的冲突事件数据集。然而,大量研究发现,这些数据中存在系统性的 "遗漏 "模式,从而对由此得出的统计结果提出了质疑。在本项目中,我们探讨了额外数据收集的三个具体机会,以帮助恢复被系统性排除的事件,并有可能帮助解决由此产生的偏差。我们发现,所有这三种方法都会产生额外的、往往与基于新闻的数据集所报道的内容存在系统性差异的材料,我们对这些方法的优点和缺点进行了反思。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Expanding the Coverage of Conflict Event Datasets: Three Proofs of Concept
ABSTRACT Many contemporary studies on political violence/social unrest rely on conflict event datasets derived primarily from major international/national news reports. Yet, a large body of research identifies systematic patterns of ‘missingness’ in these data, calling into question statistical results drawn from them. In this project, we explore three specific opportunities for additional data collection to help recover systematically excluded events and to potentially assist in addressing resulting bias. We find that all three approaches result in additional and often systematically different material than that reported in news-based datasets, and we reflect on the advantages and drawbacks of these approaches.
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来源期刊
Civil Wars
Civil Wars POLITICAL SCIENCE-
CiteScore
2.70
自引率
18.20%
发文量
23
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