Accomplice or Spoiler? - Assessing the Impact of Radical Flanks on Nonviolent Resistance Movements by Scrutinising their Emergence and Level of Integr

共犯还是搅局者？

• 批准号: 2562857
• 金额: --
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2562857
• 关键词: Accomplice; Spoiler; Assessing; Impact; Radical

Recent research has shown empirically that nonviolent resistance is often more effective than violent resistance. Yet, when assessing the effectiveness, the delineation and intersection between violent and nonviolent contention remain undertheorized. My project seeks to analyse this intersection systematically by investigating movement factions that employ varying (non)violent tactics. Precisely, I will scrutinise the impact of so-called 'radical flanks' on predominantly nonviolent movements, looking at their emergence, level of integration, and demise. The study will thus address the puzzle of why violence within nonviolent movements shows starkly diverging impacts, from benefitting movements, improving the prospects of reaching their goals, to backfiring on movements, undermining their mobilisation and leverage vis-à-vis the government. By employing a mixed-methods design, the project will both identify micro-level decision-making processes behind converging tactics in three 'diverse cases' (South Africa, Zambia, Kosovo) and test emerging hypotheses against large-N datasets. Qualitatively, I will engage in process-tracing through consulting varying data sources (conducting interviews, archival sources, newspaper articles), recapitulating the decision-making processes of former activists. Quantitatively, through network analysis, I will show how different factions relate to each other. Using latent space analysis, it will be measured whether the impact on the movement varies depending on the relation between 'radical flanks' and moderate factions (level of integration), suggesting successful outcomes (e.g. democratisation) when factions pursue the same goals, and failure (e.g. government repression) when factions' goals starkly diverge. Besides scholarly curiosity, this project holds policy implications, adding to the predictability of conflict dynamics and timely interventions during political crises. Increasingly seeing econometric models and machine learning tools in this research field, my micro-level insights can furthermore improve the parameters for prediction models. The proposed project contributes to the field of contentious politics and political violence within the ESRC subject of political science and international studies.

最近的研究经验表明，非暴力抵抗往往比暴力抵抗更有效。然而，在评估有效性时，暴力和非暴力争论之间的界限和交叉点仍然没有得到充分的理论化。我的项目旨在通过调查采用不同（非）暴力策略的运动派别来系统地分析这种交叉点。确切地说，我将仔细研究所谓的“激进侧翼”对主要非暴力运动的影响，研究它们的出现，整合水平和消亡。因此，这项研究将解决为什么非暴力运动中的暴力表现出明显不同的影响，从有利于运动，改善实现目标的前景，到对运动产生适得其反的影响，破坏他们的动员和维斯政府的影响力。通过采用混合方法设计，该项目将确定三个“不同案例”（南非，赞比亚，科索沃）中融合策略背后的微观决策过程，并针对大N数据集测试新出现的假设。在质量方面，我将通过咨询不同的数据来源（进行采访，档案来源，报纸文章）参与过程跟踪，概括前活动家的决策过程。通过网络分析，我将展示不同派别之间的关系。使用潜在空间分析，它将衡量运动的影响是否取决于“激进侧翼”和温和派别之间的关系（整合水平），表明成功的结果（例如民主化），当派别追求相同的目标时，失败（例如政府镇压）。除了学术好奇心，这个项目还具有政策影响，增加了冲突动态的可预测性和政治危机期间的及时干预。随着越来越多地看到计量经济学模型和机器学习工具在这个研究领域，我的微观层面的见解可以进一步改善预测模型的参数。拟议的项目有助于有争议的政治和政治暴力领域内的政治科学和国际研究ESRC主题。