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. 2016 Aug 16;113(33):9244-9.
doi: 10.1073/pnas.1601341113. Epub 2016 Aug 1.

Cross-linguistic patterns in the acquisition of quantifiers

Affiliations

Cross-linguistic patterns in the acquisition of quantifiers

Napoleon Katsos et al. Proc Natl Acad Sci U S A. .

Abstract

Learners of most languages are faced with the task of acquiring words to talk about number and quantity. Much is known about the order of acquisition of number words as well as the cognitive and perceptual systems and cultural practices that shape it. Substantially less is known about the acquisition of quantifiers. Here, we consider the extent to which systems and practices that support number word acquisition can be applied to quantifier acquisition and conclude that the two domains are largely distinct in this respect. Consequently, we hypothesize that the acquisition of quantifiers is constrained by a set of factors related to each quantifier's specific meaning. We investigate competence with the expressions for "all," "none," "some," "some…not," and "most" in 31 languages, representing 11 language types, by testing 768 5-y-old children and 536 adults. We found a cross-linguistically similar order of acquisition of quantifiers, explicable in terms of four factors relating to their meaning and use. In addition, exploratory analyses reveal that language- and learner-specific factors, such as negative concord and gender, are significant predictors of variation.

Keywords: language acquisition; pragmatics; quantifiers; semantics; universals.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. S1.
Fig. S1.
N = 768. Percentages based on correct responses to true and false conditions for the English-equivalent expressions for “all,” “none,” “some,” “some…not,” and “most,” excluding underinformative conditions for “some,” “some…not,” and “most.” Languages are classified following the work in ref. . Table S7 shows the English-equivalent expressions in our sample.
Fig. S2.
Fig. S2.
Children (n = 768) and adults (n = 536). Percentages for the average of “some,” “some…not,” and “most” are presented in A, for “some” in B, for “some…not” in C, and for “most” in D. Languages are classified following the work in ref. . Table S7 shows the English-equivalent expressions in our sample.

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