Previous civil war analyses have approached conflict as a single category with limited exceptions, and this thesis project assesses whether differentiating conflicts by their type and intensity using a local-level geo-referenced analytical approach produces differing results for sub-groups of conflicts. The conflicts are divided into 1) governmental hostilities, where the aim of the armed non-state group is to capture the state, and 2) territorial hostilities, where the aim of the armed non-state group is to capture increased autonomy or secession for a territorial claim. The conflicts are also differentiated by intensity into 1) low-intensity conflicts, with fewer than 1000 battle-related deaths per year, and 2) civil wars, with 1000 or more battle-related deaths per year. The results demonstrate that conflicts with differing insurgent goals and intensities of battle are correlated with markedly different factors. There are three factors – local population density, change in local rainfall, and statewide GDP growth – that are significant to both governmental and territorial hostilities but have opposite signs for the two sets. Only one variable – Polity IV scores – showed a consistently significant correlation for governmental and territorial hostilities. There are no factors that are significant to both low-intensity conflict and higher-intensity civil war. These findings suggest that approaching all conflicts as a single class, particularly at the local level, may not reveal significant differences in factors correlated with conflict. Modeling of local conflict will require differentiation of conflicts into salient sub-groups. For policymakers and practitioners, this research suggests that there is not a one-size-fits-all approach for conflict prevention but that strategies need to be targeted to specific types of conflict.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:543672 |
Date | January 2011 |
Creators | Haring-Smith, Whitney |
Contributors | Duch, Raymond |
Publisher | University of Oxford |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://ora.ox.ac.uk/objects/uuid:05603826-f731-4817-a6a7-965e8056b62f |
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