Examining repressive and oppressive state violence using the Ill-Treatment and Torture data

Andreas Beger and Daniel Hill
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Andreas Beger: Predictive Heuristics, Tallinn, Estonia
Daniel Hill: University of Georgia, USA

Conflict Management and Peace Science, 2019, vol. 36, issue 6, 626-644

Abstract: The literature on government violence focuses primarily on the repression of dissent. But not all state violence targets groups who oppose the government. Much of it targets criminal suspects, immigrants, and other marginalized groups who are not perceived to be challenging the government’s authority. The vast majority of findings concerning state violence comes from analyses that do not distinguish between government violence that targets acts of dissent and violence used for other purposes, which we call oppressive violence. Because of this, we have not yet established many empirical facts about the relationship between domestic institutions and violence unrelated to the repression of dissent. Though political institutions associated with democracy are known to reduce the frequency of torture and other violent abuses, it is unclear whether these effects are attributable to reductions in repressive violence, oppressive violence, or both. We argue that explanations for state violence that focus on democracy are better suited to explain repressive violence than oppressive violence. We use the Ill-Treatment and Torture data, which can be disaggregated by victim type, to explore the relationship between the torture of dissidents, criminal suspects, and members of marginalized social groups, and various conditions thought to be related to repressive and oppressive violence.

Keywords: Human rights; Will H. Moore; predictive modeling; state violence (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:sae:compsc:v:36:y:2019:i:6:p:626-644

DOI: 10.1177/0738894219882352

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