Miniature artificial language learning as a complement to typological data

Maryia Fedzechkina, Elissa L. Newport, T. Florian Jaeger

Research output: Chapter in Book/Report/Conference proceedingChapter

7 Scopus citations

Abstract

As observed by linguist Joseph Greenberg (Greenberg 1963), languages across the world seem to share properties at all levels of linguistic organization. Some of these patterns are regularities in the crosslinguistic distribution of elements that hold across languages (non-implicational universals1). For example, sentential subjects almost always precede objects in declarative sentences (Greenberg 1963). Others, the so-called implicational universals, describe correlations between elements that vary together across languages: If a language has property A, then it most likely has property B. An example of such an implicational universal is the well-documented correlation between constituent order freedom and the presence of case-marking (Blake 2001; Sapir 1921): Languages with flexible constituent order often use morphological means, such as case, to mark grammatical function assignment (e.g., German, Japanese, and Russian), whereas languages with fixed constituent order typically lack case morphology (e.g., English and Mandarin).

Original languageEnglish (US)
Title of host publicationThe Usage-Based Study of Language Learning and Multilingualism
PublisherGeorgetown University Press
Pages211-232
Number of pages22
ISBN (Electronic)9781626163256
ISBN (Print)9781626163249
StatePublished - Jan 1 2016
Externally publishedYes

ASJC Scopus subject areas

  • Arts and Humanities(all)
  • Social Sciences(all)

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  • Cite this

    Fedzechkina, M., Newport, E. L., & Florian Jaeger, T. (2016). Miniature artificial language learning as a complement to typological data. In The Usage-Based Study of Language Learning and Multilingualism (pp. 211-232). Georgetown University Press.