Identification and alignment of interested actors around civil wars using the text of UN General Assembly speeches

使用联合国大会演讲文本识别和协调围绕内战感兴趣的参与者

• 批准号: 2004212
• 负责人: Zuhaib Mahmood
• 金额: $ 13.8万
• 依托单位: Mahmood, Zuhaib Sheikh
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2004212&HistoricalAwards=false
• 关键词: Identification; alignment; interested; actors; around

This award was provided as part of NSF's Social, Behavioral and Economic Sciences Postdoctoral Research Fellowships (SPRF) program and SBE's Security and Preparedness program. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Dr. Kyle Beardsley at Duke University, this postdoctoral fellowship award supports an early career scientist investigating the internationalization of civil conflicts, using United Nations (UN) General Assembly speeches to help identify politically interested countries and to measure their alignment around a given conflict. The project advances both the study of diplomacy at the United Nations and the study of third-party involvement in civil wars. Additionally, by focusing on the content of UN speeches as a predictor of risk, it provides a scalable framework for creating longer-term tracking and finer-grained forecasts as geopolitical interests develop, change, and evolve. Finally, it helps build enhanced infrastructure for future scholastic collaboration on data collection and forecasting, as well as for providing future generations of researchers with hands-on training in a large-scale research program.Civil wars often escalate to envelop an entire region or, in some cases, the entire world. This process of internationalization involves both an assessment of whether countries actually have a political interest in the ongoing conflict, and also whether other countries have similar or conflicting interests. This project zooms into these two questions by setting out to both identify interested countries, and measure the alignment of interests across these parties, using the text of UN General Assembly speeches as a data source for both (in conjunction with other measures from the literature). Funding for this project supports three primary tasks. The first task leverages machine learning methods to match the content of individual UN General Assembly Speeches (from 1984-2014) to the discussion of a given civil war. The second task models the risk of whether an individual country has an identifiable political interest in this civil war, drawing on the content of the classified UN General Assembly speeches and also drawing on a systematic review of prior literature on the topic. Finally, given this political interest, the third task measures the alignment of interested countries to determine whether they are likely to cooperate or conflict surrounding that conflict. Output from this study are relevant for both scholars and policymakers, with implications for understanding diplomacy at the United Nations, and for modeling the intricate link between civil wars, inter-state conflict, and international institutions like the UN. It facilitates progress in both the scholarly understanding of conflict processes, and in the efficient allocation of national security resources following the outbreak of a politically relevant conflict with the potential for internationalization.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项是NSF的社会，行为和经济科学博士后研究奖学金（SPRF）计划和SBE的安全和准备计划的一部分。SPRF计划的目标是为学术界，工业或私营部门和政府的科学事业准备有前途的早期职业博士级科学家。SPRF的奖励包括在知名科学家的赞助下进行两年的培训，并鼓励博士后研究员进行独立研究。NSF致力于促进来自科学界各部门的科学家，包括来自代表性不足的群体的科学家参与其研究计划和活动;博士后期间被认为是实现这一目标的专业发展的重要水平。每个博士后研究员必须解决推进各自学科领域的重要科学问题。在杜克大学的凯尔比尔兹利博士的赞助下，这个博士后奖学金支持一个早期的职业科学家调查国内冲突的国际化，利用联合国（UN）大会演讲，以帮助确定政治上感兴趣的国家，并衡量他们围绕特定冲突的结盟。该项目推动了联合国外交研究和第三方参与内战的研究。此外，通过关注联合国演讲的内容作为风险预测器，它提供了一个可扩展的框架，随着地缘政治利益的发展，变化和演变，可以创建长期跟踪和更细粒度的预测。最后，它有助于为未来的数据收集和预测学术合作建立更好的基础设施，并为未来几代研究人员提供大规模研究项目的实践培训。这一国际化进程既涉及评估各国在当前冲突中是否实际具有政治利益，也涉及评估其他国家是否具有类似或冲突的利益。该项目通过确定感兴趣的国家并衡量这些各方的利益一致性来放大这两个问题，使用联合国大会发言的文本作为两者的数据来源（结合文献中的其他措施）。该项目的资金支持三项主要任务。第一项任务利用机器学习方法将单个联合国大会演讲（1984年至2014年）的内容与特定内战的讨论进行匹配。第二项任务是根据联合国大会机密发言的内容，并对有关这一主题的先前文献进行系统审查，对单个国家是否在这场内战中具有可识别的政治利益的风险进行建模。最后，考虑到这种政治利益，第三项任务衡量有关国家的结盟情况，以确定它们是否可能围绕这一冲突进行合作或冲突。这项研究的成果对学者和政策制定者都有意义，对理解联合国的外交有影响，对模拟内战、国家间冲突和联合国等国际机构之间的复杂联系也有影响。它促进了对冲突过程的学术理解的进步，以及在爆发具有国际化潜力的政治相关冲突后有效分配国家安全资源的进步。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。