A new geography of civil war: a machine learning approach to measuring the zones of armed conflicts
| Autor: | Kyosuke Kikuta |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
021110 strategic
defence & security studies Spanish Civil War Sociology and Political Science Economy 05 social sciences Political Science and International Relations 050602 political science & public administration 0211 other engineering and technologies 02 engineering and technology 0506 political science |
| Zdroj: | Political Science Research and Methods. 10:97-115 |
| ISSN: | 2049-8489 2049-8470 |
| DOI: | 10.1017/psrm.2020.16 |
| Popis: | Where do armed conflicts occur? In applied studies, we may take ad hoc approaches to answer this question. In some regression studies, for instance, a single conflict event can cause an entire province to be classified as a conflict zone. In this paper, I fill this void of knowledge by developing a machine learning method that is less dependent on the areal-unit assumptions and can flexibly estimate conflict zones. I apply the method to a conflict event dataset and create a new dataset of conflict zones. A replication of Daskin and Pringle (2018, Nature 553, 328–332) with the new dataset indicates that the effect of civil war on mammal populations is much smaller than the original estimate. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|