@article{ref1,
title="Means to an end: pro-government militias as a predictive indicator of strategic mass killing",
journal="Conflict management and peace science",
year="2017",
author="Koren, Ore",
volume="34",
number="5",
pages="461-484",
abstract="Forecasting models of state-led mass killing are limited in their use of structural indicators, despite a large body of research that emphasizes the importance of agency and security repertoires in conditioning political violence. I seek to overcome these limitations by developing a theoretical and statistical framework that highlights the advantages of using pro-government militias (PGMs) as a predictive indicator in forecasting models of state-led mass killing. I argue that PGMs can lower the potential costs associated with mass killing for a regime faced with an internal threat, and might hence &quot;tip the balance&quot; in its favor. In estimating a series of statistical models and their receiver-operator characteristic curves to evaluate this hypothesis globally for the years 1981-2007, focusing on 270 internal threat episodes, I find robust support for my expectations: including PGM indicators in state-led mass killing models significantly improves their predictive strength. Moreover, these results hold even when coefficient estimates produced by in-sample data are used to predict state-led mass killing in cross-validation and out-of-sample data for the years 2008-2013. This study hence provides an introductory demonstration of the potential advantages of including security repertoires, in addition to structural factors, in forecasting models.<p /> <p>Language: en</p>",
language="en",
issn="0738-8942",
doi="10.1177/0738894215600385",
url="http://dx.doi.org/10.1177/0738894215600385"
}