The Bayesian model of X&T is important in providing insight into how people might reason about samples of data that exemplify categories.
it relies on having complete, built-in knowledge about the taxonomic hierarchy, including both the detailed composition of categories and the values for between-object similarities, drawn from adult similarity judgments.