The conflict trajectory in the cases of Madagascar features highly unstable dynamics composed of various shifts (and no shift) of conflict stages. With nine main successive episodes of conflict spanning a long period of time (the colonial period to 2016), dynamics of escalation, de-escalation and stability (where the level of conflict remains the same) are building up the cycles of peace/conflict processes in this country. The present manuscript studies conflict recurrence in Madagascar and mainly argues that peace is multi-leveled throughout the cycles. Starting from that viewpoint, the concept of conflict transformation is used in explaining the ebbs and flows at play constructing the conflict trajectory. An innovative as well as original conceptual and methodological approach to the study of conflicts, weaving together Qualitative Comparative Analysis (QCA) and in-depth narrative analysis was applied. Reactive and non-reactive methods were used to collect the data, which, after being tested with fsQCA, Tosmana and R software, were examined by conducting conflict analysis, semiotics, public policy studies and critical discourse analysis. The Units of analysis in the research design allowing the study of the dynamics of conflict recurrence in Madagascar were the structural factors and parts of the mechanism pertaining to :a) conflict dimensions (cultural, socio-demographic and economic, political and global external), b) repertoires of action the conflicting parties used throughout the shifts (or no shift) of conflict stages, c) their framings of the conflicts, d) the boundary construction of the self/the other and e) the accommodation policies as well as f) the metanarratives and local narratives. On the whole peace and conflict processes in Madagascar.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:754854 |
Date | January 2018 |
Creators | Razakamaharavo, Velomahanina Tahinjanahary |
Contributors | Azmanova, Albena ; Guichaoua, Yvan ; Féron, Élise |
Publisher | University of Kent |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | https://kar.kent.ac.uk/69072/ |
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