Learning to see hate crimes : a framework for understanding and clarifying ambiguities in bias crime classification

Abstract

Recent empirical research has identified ambiguity in bias crime reporting as a source of confusion and frustration in law enforcement agencies and as a source of error in the national hate crime statistics. The authors develop a framework for understanding and clarifying these ambiguities based on John Dewey's conception of intension and extension and their own application of mathematical set theory to the issue. The authors discuss the implications of their model for helping law enforcement officials see bias crimes for varied purposes, including prevention, statistical reporting, and criminal prosecution.