Natural language, unlike animal communication systems, provides a rich combinatorial system that encodes meaning structurally, allowing a finite set of words to express an unbounded number of thoughts. My research investigates how children acquire the logical representations that underlie language, and how they acquire abstract, uniquely human, concepts. A guiding hypothesis of this work is that many important conceptual changes in human development do not require the creation of entirely novel representations, but instead emerge from the representational resources provided by natural language.

Dr. Barner’s work in linguistics has focused on the problem of computational economy in structure/process tradeoffs between lexical and syntactic levels of representation, beginning with work on lexicalist vs. non-lexicalist accounts of noun-verb flexibility (Barner & Bale, 2002, 2005), extending to work on the mass-count distinction (Barner & Snedeker, 2005; Bale & Barner, 2009). Current work is focused on how children acquire logical connectives and quantifiers, their acquisition of singular, dual, and plural morphology, and grammatical accounts of pragmatic inference (e.g., implicature, inter alia).

Dr. Barner’s recent work also focuses on the origin of human mathematical knowledge, and argues that significant aspects of this competence derive from representations made available by natural language. This competence includes two central components, including (1) an innate semantic space that furnishes the content of the singular, dual, trial systems and children's initial meanings for "one", "two", and "three", and (2) a recursive syntactic capacity that children use to derive the morphological rules of counting, the successor function, and from this the intuition that numbers are infinite (Barner, 2017, in press). Dr. Barner uses empirical methods from language acquisition, investigation of languages including English, French, Cantonese, Slovenian, Hindi, Gujarati, and Japanese, and begins with the assumption that language is a domain-specific mental system optimized for composing semantically interpretable representations.

Additional case studies include gradable adjectives, one-to-one correspondence, color, time, and moral development.

CV here.

Research (click HERE for publications)

  • Mass / count distinction and acquisition

  • Counting

  • Language, thought, and object perception

  • Time words

  • Color words

  • Quantifier acquisition & counting

  • Pragmatic inference

  • Gradable adjectives and measurement

  • Singular / plural morphology

  • Numerical estimation and non-linguistic representation

  • Non-linguistic mathematical computation and the "mental abacus"

  • Moral development

  • Classifier languages and individuation