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The development of the causative construction in Persian child language*

Published online by Cambridge University Press:  03 March 2015

NEILOUFAR FAMILY  and
SHANLEY E. M. ALLEN
NEILOUFAR FAMILY*
Affiliation:
University of Kaiserslautern
SHANLEY E. M. ALLEN
Affiliation:
University of Kaiserslautern
*
Address for correspondence: Neiloufar Family, University of Kaiserslautern – Faculty of Social Sciences, Kaiserslautern, Germany. e-mail: [email protected]
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Abstract

The acquisition of systematic patterns and exceptions in different languages can be readily examined using the causative construction. Persian allows four types of causative structures, including one productive multiword structure (i.e. the light verb construction). In this study, we examine the development of all four structures in Persian child speech between the ages of 1;11 and 6;7, in correspondence with their caregivers’ speech. We define developmental stages based on dendrograms derived from variability clustering (Gries & Stoll, 2009). These stages are further substantiated by qualitative data, including overgeneralization errors and alternating structures. We find that Persian-speaking children learn to exploit two (i.e. lexical and light verb construction causatives) of the four constructions. They go from relying on lexical causatives to forming progressively constrained templates for the more complex light verb construction. This first study of the development of Persian causatives supports a usage-based account of verb-by-verb learning in child language development.

Type
Articles
Information
Journal of Child Language , Volume 42 , Issue 6 , November 2015 , pp. 1337 - 1378
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Copyright
Copyright © Cambridge University Press 2015 

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Footnotes

[*]

This research was made possible through support by the ANR (Agence Nationale de la Recherche) project COLAJE (Paris, France) and the Institute for Cognitive Science Studies (Tehran, Iran). We would also like to thank Stefan Gries for providing the tools for the statistical analyses used in this paper and Laleh Ghadakpour for cross-checking the data coding in the corpus.

References

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