Toward a Unified Understanding of Casualty Distributions in Human Conflict

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 power-law 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 for why observed casualty distributions may follow approximate power laws and how and why they may deviate from a power law. In particular, it provides a unified mechanistic interpretation of the origin of deviations from a power law in terms of dynamical processes within the conflict. Taken together, our findings strengthen the notion that a unified framework can be used to understand and quantitatively describe human conflict.