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

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.