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Generic language (e.g., “Birds fly”) conveys generalizations about categories and is essential for learning beyond our direct experience. The meaning of generic language is notoriously hard to specify, however (e.g., penguins don’t fly). Tessler and Goodman (2019) proposed a model for generics that is mathematically equivalent to Bayesian belief-updating based on a single pedagogical example, suggesting a deep connection be- tween learning from experience and learning from language. Relatedly, Csibra and Shamsudheen (2015) argue that generics are inherently pedagogical, understood by infants as referring to a member of a kind. In two experiments with adults, we quantify the exchange-rate between generics and observations by relating their belief-updating capacity, varying both the number of observations and whether they are presented pedagogically or incidentally. We find generics convey stronger generalizations than single pedagogical observations (Expt. 1), even when the property is explicitly demarcated (Expt. 2). We suggest revisions to the vague quantifier model of generics that would allow it to accommodate this intriguing exchange-rate.
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When generic language does not promote psychological essentialism.
Generic language (e.g., “Women are nurturing”; “Women do not like math”) is prominent in child-directed speech, and has been shown to promote essentialist beliefs about the relevant kind, supporting stereotyping and prejudice. Here we investigate a theoretically-motivated intervention to break the link between generics and essentialist assumptions. In a study with 223 3-8-year-old children who learned about novel social groups from generic language, we demonstrate that a structural construal of generics (attributing the category-property association to stable external constraints) mitigates essentialist assumptions about social categories. We discuss practical applications for reducing stereotype endorsement, and theoretical implications regarding the meaning of generic language and the development of social kind representations.
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- Award ID(s):
- 1948630
- PAR ID:
- 10273799
- Editor(s):
- Denison, Stephanie; Mack, Michael; Xu, Yang; Armstrong, Blair C.
- Date Published:
- Journal Name:
- Proceedings of the 42nd Annual Conference of the Cognitive Science Society
- Page Range / eLocation ID:
- 688-694
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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