Statistical typology methods silently bake in exhaustive, mutually exclusive category rules.

Evidence

Hierarchical clustering techniques are prototypically designed to sequentially partition a set of N cases into K mutually exclusive clusters [a typology] based on the joint information contained in the J outcome variables. … The K classes are exhaustive and mutually exclusive such that each individual in the population has membership in exactly one of the K latent classes” (Masyn 2013, 552). — Gary Goertz, Social Science Concepts and Measurement, 1335

Categorization

• DEFINE: Clarifies that mutual exclusivity and exhaustiveness are axioms of hierarchical clustering and latent class analysis, not findings about the world.