A numerical study of scientific consensus formation: a case study of Copernican revolution

We investigate the cognitive mechanisms behind scientific consensus formation, focusing on how internal cognitive frameworks guide the model selection of the best among competing ones. By understanding these mechanisms, we aim to enhance our comprehension of cognitive processes in scientific consensus building and support scientific development. Using historical transitions in planetary motion models—Ptolemaic, Copernican, and Kepler—as a case study of Kuhn’s revolutionary period, we numerically analyze the model selection criteria that scientists may have used. We discuss the factors that could explain the transition from one scientific model to another, using predictive accuracy and the degree of freedom. Using Simple Additive Weighting (SAW) in Multi-Criteria Decision Making (MCDM), the historical change could be explained by two types of predictive accuracies, qualitative and quantitative, and the degree of freedom.