What's in a Taxon?

Abstract

Whether taxometrics yields inferential knowledge to something latent is partly but not wholly a semantic question. Although the single variables are manifest indicator scores of individuals, the statistics computed from them via postulates of the formalism are not mere data summaries and will be incorrect or meaningless if the structural conjectures are false. The unidirectional derivability from postulates to data relations supplies the taxonic inferences' surplus meaning that constitutes conventional psychometric meaning of latency (e.g., latent class analysis). Surplus meaning beyond the purely mathematical may be provided by interpretive text attributing unobserved attributes or causal origin to taxon members.