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Prosodically-conditioned variability in children's production of French determiners*

Published online by Cambridge University Press:  03 January 2008

KATHERINE DEMUTH*
Affiliation:
Brown University and University of Hawai‘i at Mānoa
ANNIE TREMBLAY
Affiliation:
Brown University and University of Hawai‘i at Mānoa
*
Address for correspondence: Department of Cognitive & Linguistic Sciences, Brown University, Box 1978, Providence, RI 02912. e-mail: Katherine_Demuth@brown.edu.
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Abstract

Researchers have long noted that children's grammatical morphemes are variably produced, raising questions about when and how grammatical competence is acquired. This study examined the spontaneous production of determiners by two French-speaking children aged 1 ; 5–2 ; 5. It found that determiners were produced earlier with monosyllabic words, and later with disyllabic and trisyllabic words. This suggests that French-speaking children's early determiners are prosodically licensed as part of a binary foot, with determiners appearing more consistently only once prosodic representations become more complex. This study therefore provides support for the notion that grammatical morphemes first appear in prosodically licensed contexts, suggesting that some of the early variability in morphological production is systematic and predictable.

Information

Type
Research Article
Copyright
Copyright © Cambridge University Press 2008
Figure 0

TABLE 1. Participants' ages and MLUs (Mean Lengths of Utterance)

Figure 1

TABLE 2. French determiners and target phonemic forms (C=consonant; V=vowel)

Figure 2

TABLE 3. Total number (percent) of determiners produced in obligatory contexts

Figure 3

TABLE 4. Tim's number (percent) of determiners produced by type

Figure 4

TABLE 5. Marie's number (percent) of determiners produced by type

Figure 5

TABLE 6. Tim's number (percent) of truncated nouns

Figure 6

TABLE 7. Marie's number (percent) of truncated nouns

Figure 7

TABLE 8. Tim's number (percent) of determiner use with different non-truncated target word-shapes

Figure 8

TABLE 9. Marie's number (percent) of determiner use with different non-truncated target word-shapes