We are able to unify various disparate claims and results in the literature, that stand in the way of a unified description and understanding of human conflict. First, we provide a reconciliation of the numerically different exponent values for fatality distributions across entire wars and within single wars. Second, we explain how ignoring the details of how conflict datasets are compiled, can generate falsely negative evaluations from power-law distribution fitting. Third, we explain how a generative theory of human conflict is able to provide a quantitative explanation of how most observed casualty distributions follow approximate power-laws and how and why they deviate from it. In particular, it provides a unified mechanistic interpretation of the origin of these power-law deviations in terms of dynamical processes within the conflict. Combined, our findings strengthen the notion that a unified framework can be used to understand and quantitatively describe human conflict.
{"title":"Toward a Unified Understanding of Casualty Distributions in Human Conflict","authors":"M. Spagat, Stijn van Weezel, M. Zheng, N. Johnson","doi":"10.2139/ssrn.3481393","DOIUrl":"https://doi.org/10.2139/ssrn.3481393","url":null,"abstract":"We are able to unify various disparate claims and results in the literature, that stand in the way of a unified description and understanding of human conflict. First, we provide a reconciliation of the numerically different exponent values for fatality distributions across entire wars and within single wars. Second, we explain how ignoring the details of how conflict datasets are compiled, can generate falsely negative evaluations from power-law distribution fitting. Third, we explain how a generative theory of human conflict is able to provide a quantitative explanation of how most observed casualty distributions follow approximate power-laws and how and why they deviate from it. In particular, it provides a unified mechanistic interpretation of the origin of these power-law deviations in terms of dynamical processes within the conflict. Combined, our findings strengthen the notion that a unified framework can be used to understand and quantitatively describe human conflict.","PeriodicalId":375906,"journal":{"name":"PSN: Other Effects of Conflict (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115784766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Over 90 percent of the world’s states currently select their national leaders through multi-party elections. However, in Africa the quality of elections still varies widely, ranging from elections plagued by violence and fraud to elections that are relatively “free and fair”. The literature on election fraud and integrity has identified several factors explaining cross-national variation in overall levels of election integrity. Much less is known about trade offs between different strategies of electoral manipulation and the differences between incumbent and opposition actors’ strategies. Existing research suggest that incumbents engage more in vote buying while opposition engage more in election violence. We theorize that choices for specific types of manipulation are driven by available resources and cost considerations for both incumbents and opposition actors, and are mutually responsive. We also suggest that costs of manipulative strategies are shaped by the level of democratization. We test our hypotheses on time-series- cross-section data for 285 African elections from 1986 to 2012. We find that democratization initially leads to increases in vote buying as “cheap” forms of electoral manipulation available to incumbents such as intimidation and manipulating electoral administration become less viable.
{"title":"Vote Buying is a Good Sign: Alternate Tactics of Fraud in Africa 1986-2012","authors":"Carolien van Ham, S. Lindberg","doi":"10.2139/ssrn.2613854","DOIUrl":"https://doi.org/10.2139/ssrn.2613854","url":null,"abstract":"Over 90 percent of the world’s states currently select their national leaders through multi-party elections. However, in Africa the quality of elections still varies widely, ranging from elections plagued by violence and fraud to elections that are relatively “free and fair”. The literature on election fraud and integrity has identified several factors explaining cross-national variation in overall levels of election integrity. Much less is known about trade offs between different strategies of electoral manipulation and the differences between incumbent and opposition actors’ strategies. Existing research suggest that incumbents engage more in vote buying while opposition engage more in election violence. We theorize that choices for specific types of manipulation are driven by available resources and cost considerations for both incumbents and opposition actors, and are mutually responsive. We also suggest that costs of manipulative strategies are shaped by the level of democratization. We test our hypotheses on time-series- cross-section data for 285 African elections from 1986 to 2012. We find that democratization initially leads to increases in vote buying as “cheap” forms of electoral manipulation available to incumbents such as intimidation and manipulating electoral administration become less viable.","PeriodicalId":375906,"journal":{"name":"PSN: Other Effects of Conflict (Topic)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123201381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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