Collaborative Research: Cooperation in Multi-Dyadic Civil Conflicts

合作研究：多元民事冲突中的合作

• 批准号: 2215024
• 负责人: Alyssa Prorok
• 金额: $ 27.3万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2215024&HistoricalAwards=false
• 关键词: Collaborative; Research; Cooperation; Multi; Dyadic

Civil conflicts impose significant human, economic, and political costs on the countries involved and the broader regions affected. This is particularly true when conflicts involve multiple rebel groups (i.e., multi-dyadic conflicts). This project advances knowledge of multi-dyadic civil conflict dynamics and resolution by evaluating how government-rebel cooperation shapes opportunities for conflict resolution and violence reduction. It contributes to ongoing debates among policymakers and scholars about the dynamics of war and the nature and sustainability of post-conflict peace, speaking to fundamental questions of national security and the prosperity and welfare of countries currently embroiled in civil conflicts around the world. The project provides novel cross-country data compatible with leading civil war datasets, providing a valuable tool to advance cutting-edge research on civil conflict. Moreover, The project also provides training and mentorship opportunities for undergraduate and graduate students. Understanding the dynamics of cooperation between adversaries will improve evaluation and forecasting of (in)stability. The PIs integrative approach to cooperation provides insights into when cooperation signals meaningful shifts in conflict dynamics and prospects for long-term peace.The project involves three central aims: (1) to create a comprehensive dataset on cooperation between combatants in multi-dyadic civil wars, (2) to assess the impact of past cooperation on future cooperation and conflict resolution, and (3) to evaluate the impact of past cooperation on future conflict. To achieve aim 1, the PIs create the Cooperation in Civil War: Multi-Dyadic Conflicts Dataset (CCW-MC). CCW-MC covers 12 countries that have experienced the most complex civil conflicts in the post-cold war period. These novel data will capture the full evolution of dyadic cooperation from initial requests to final implementation. Using these data, the PIs test novel theoretical expectations (aims 2 and 3) about how the legacies of past cooperative attempts, both within a government-rebel group dyad and gleaned from observing other dyads in the country, influence subsequent cooperative and conflictual outcomes. Using network analysis, the PIs examine the influence of other active rebel groups on this evolution of cooperation and conflict. By engaging with the multi-dyadic context of these civil wars, the project explicitly takes each dyad's context into consideration when theorizing about and evaluating the role of cooperation. This project addresses a critical gap by examining the evolution of cooperation within and across government-rebel group dyads in multi-dyadic civil conflicts. It will provide novel insights into how cooperation diffuses across dyads, how past attempts at cooperation influence subsequent cooperative efforts, and how cooperation of one form influences subsequent cooperation of another form. The project advances research on conflict management and settlement by treating cooperation as an iterative process that reveals unique information about combatant credibility that cannot be revealed on the battlefield.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.

民间冲突对所涉及的国家和更广泛的地区施加了重大的人类，经济和政治成本。当冲突涉及多个叛军群体（即多野蛮冲突）时，尤其如此。该项目通过评估政府re贝尔合作如何塑造解决冲突和减少暴力的机会来提高多义义民间冲突动力和解决方案的知识。它促进了政策制定者和学者之间关于战争动态以及冲突后和平的性质和可持续性的持续辩论，对目前卷入世界各地民间冲突的国家的基本问题以及国家安全的基本问题以及对国家安全的基本问题进行了交流。该项目提供了与领先的内战数据集兼容的新型越野数据，从而提供了一种有价值的工具来推动对民间冲突的尖端研究。此外，该项目还为本科生和研究生提供培训和指导机会。了解对手之间的合作动态将改善（以）稳定性的评估和预测。 PIS综合合作方法提供了有关何时合作信号在冲突动态和长期和平的前景中有意义的转变的见解。该项目涉及三个核心目的：（1）创建一个全面的数据集，该数据集关于战斗人员之间的合作数据集，（2）评估对未来和冲突的合作的影响，以评估对未来和冲突的影响的影响，以评估对未来和冲突的影响（3）。为了达到目标1，PI在内战中创建了合作：多野战冲突数据集（CCW-MC）。 CCW-MC涵盖了12个国家，这些国家在冷战后期遇到了最复杂的民用冲突。这些新颖的数据将捕获二元合作从初始请求到最终实施的全部演变。使用这些数据，PIS测试了新的理论期望（目标2和3），介绍了过去的合作企图的遗产，无论是在政府 - 雷贝尔集团二元组中以及观察到该国其他二元组而收集的，都会影响随后的合作和冲突成果。使用网络分析，PIS检查了其他活跃叛军群体对这种合作和冲突演变的影响。通过与这些内战的多野际背景接触，该项目明确地考虑了每个二元组在理论化和评估合作作用时考虑的。该项目通过研究多野战民间冲突中政府 - 雷贝尔集团内部和整个雷贝尔集团内部的合作演变来解决一个关键的差距。它将提供有关合作如何扩散二元组，过去的合作尝试如何影响随后的合作努力以及一种形式的合作如何影响另一种形式的随后合作的新颖见解。该项目通过将合作视为一个迭代过程，揭示了有关战斗人员信誉的独特信息，从而在冲突管理和解决方案上进行了进步。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的审查标准来评估的，并被视为值得通过评估。