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Modeling the Protest-Repression Nexus

Ch. 1. P. 1–11.
Akhremenko A. S., Petrov A.

Over the last 30 years, numerous studies have shown that repression can de-crease, increase, or have some kind of a nonlinear or mixed impact on the intensity of protest. This problem is usually referred to as the “protest-repression nexus” or the “punishment puzzle”, and it is still not resolved. The mathematical and computational model that we present in this paper is intended to shed new light on the causes of puzzling contradictions in empirical results.
Building upon micro-level approach to political participation, we demonstrate that the reaction of protesters to repression can be dramatically different under the virtually same conditions. We show that an increase in repression levels leads to a more pronounced division between two possible outcomes of a contentious political event: successful protest and failed protest. The model highlights the importance of the intensity of the government’s repressive reaction to protests. The more disproportionate (“nervous”) this reaction is, the less stable the situation
becomes. The latter means that the protest will either be suppressed or become extremely massive, but it is unlikely to remain moderate. Both findings are qualitatively similar and emphasize our general finding: the suppression of protest makes its further course less predictable. Methodological contribution of the paper is that our model allows for accounting both fueling and stifling effects of repression on participation within the same model
specification 

Language: English
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Keywords: математическая модельrepressionрепрессиидинамическая модельformal modeldynamical modelprotestпротествычислительная модельcomputational model

In book

Proceedings of the Conference on Modeling and Analysis of Complex Systems and Processes 2020 (MACSPro 2020)
Vol. 2795. , CEUR Workshop Proceedings, 2020.
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