Listening to the Street?; The Response of Post-Soviet Non-Democratic Regimes to Popular Protests

Lead Research Organisation: King's College London
Department Name: King’s Russia Institute


It is hypothesised that, to maintain the stability of contemporary authoritarian regimes, repression alone is insufficient and responsiveness to popular opinion necessary. It is further hypothesised that street protests are a mechanism of government responsiveness. Protests are, all other things equal, less likely to escalate into revolutionary events when met by concessions. The governments of Georgia, Kazakhstan, Kyrgyzstan, and Uzbekistan will be used as case studies to assess these hypotheses.
As well as introducing methodological innovations, this thesis represents a shift in focus from the existing literature on contemporary authoritarianism, challenging several prevailing assumptions.
Research Questions
How do non-democratic regimes respond to street protests?
What impact does this have on the course of protests and longer-term regime stability?
What determines differences in outcomes and responses?
This thesis aims to contribute primarily to the literature on the internal dynamics of contemporary authoritarianism, building on the work of Hale (2005) and Levitsky and Way (2002), who analysed the role of protests in such regimes. The approach of this thesis differs from those dominant in the literature. Firstly, existing studies tend to focus on the relationship between regime and opposition elites, rather than investigating protestors as actors with agency. The potential causal effects of protests as an independent variable are therefore neglected.
Secondly, the literature focuses on democratisation. The focus is therefore on regime, rather than policy, change. Results that fall short of systemic change are neglected. This thesis analyses the role of street protests in routine politics.
Thirdly, there is an assumption that regimes subvert and manipulate public opinion, rather than attempting to respond to it. There has been little investigation into whether this holds in all cases.
Method and Sources
Primarily, a qualitative case study approach will be adopted, taking as cases the governments of Shevardnadze (Georgia, 1992-2003), Nazarbaev (Kazakhstan, 1990- present), Akaev, (Kyrgyzstan, 1990-2005), Bakiev (Kyrgyzstan, 2005-2010), Karimov (Uzbekistan, 1990-2016), and Mirziyoyev (Uzbekistan, 2016- present). All are authoritarian regimes defined by patronal presidentialism (Hale, 2005). However, they differ in levels of economic development, resource wealth, coercive capacity, and repressiveness, both between cases and within cases over time.
The cases also differ in levels of stability. Kyrgyzstan and Georgia have experienced regime change preceded by popular mobilisations, whilst Uzbekistan and Kazakhstan have generally maintained stability.
For each case, protest incidents will be identified using a keyword search of the LexisNexis and GDELT news aggregators. Protest event analysis (PEA) will be carried out on each incident. Key variables will be identified and coded, allowing for some quantitative analysis.
Correlations between the occurrence of street protests and regime decisions that align with popular preferences will be investigated, as well as correlations between particular government responses and broader regime stability. Causal mechanisms will then be suggested.
News data will be supplemented with statistical data, Russian language local media outlets that are not included in the LexisNexis database, social media posts, and author conducted interviews, where possible. Triangulation with these data sources, as well as the use of a very wide range of news sources, will mitigate the weaknesses associated with news data.
Whilst following a core approach typical of social movement research, this methodology introduces an innovation in the use of news aggregators. PEAs typically use a small number of news outlets, searched manually. News aggregators allow thousands of local, regional, and international to be searched, mitigating selection bias, and reducing the resources required.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
ES/P000703/1 30/09/2017 29/09/2027
2103522 Studentship ES/P000703/1 30/09/2018 21/08/2022 Katherine Crofts-Gibbons