The Verifiability Principle: A Framework for Studying Judgment Accuracy, Accurately

The study of judgment accuracy is common in the behavioral sciences, however there is no agreed upon method for how to quantify accuracy in estimation or forecasting studies. In this paper, I review past theories of judgment accuracy to provide a comprehensive framework that researchers can use in their studies to increase internal validity and decrease noise, what I call the verifiability principle. I develop axioms applicable to all studies of accuracy across the behavioral sciences, such as stereotype accuracy, forecasting accuracy, etc. Using this principle and associated axioms, I clarify which items are essential to the study of accuracy, and which are non-essential, but serve as noise reducing techniques.