Learning from generic language

Generic language (e.g., "Birds have hollow bones") conveys generalizations about categories and is a fundamental and ubiquitous mechanism of learning about the world. How exactly learning from generics occurs, however, is unclear: Generics exhibit so much flexibility in how they are interpreted that a formal, quantitative theory of how generic language updates beliefs has not only never been developed or tested, but the very notion has often been explicitly dismissed. Here, we explore a hypothesis implicit in the work of Tessler and Goodman (2019) that generics update beliefs via an uncertain threshold, like a vague quantifier: A category-property generic ("Ks F") means that the property F is expected to be relatively widespread in the category K, where the threshold for being relatively widespread is a priori uncertain and resolved by consulting one's prior knowledge of the property. We compare this model to a family of alternatives with the same background knowledge but where generics have a fixed, context-invariant threshold meaning. We additionally formalize a novel quantitative model of an explicitly conceptual-based approach to generics, which does not involve any thresholds, where generics would act as a direct connection to conceptual structures. Across three experiments in which we both measure and manipulate prior beliefs, we find the uncertain threshold approach to generics to be the best explanation of participants' highly context-sensitive interpretations of novel generic statements. The sufficiency of this rational model of generic interpretation suggests that generics are an effective medium for faithful transmission of knowledge between interlocutors, arguing against proposals that generic language interpretation is biased in a fundamental way. This work adds to the growing enterprise of formal, quantitative studies of human understanding of generic language. (PsycInfo Database Record (c) 2026 APA, all rights reserved).