Publiée 2020-09-13
Mots-clés
- underspecified Universal Grammar,
- parameter setting,
- learnability
Résumé
We propose a preliminary model of a practical parameter setting procedure that aims
at bridging the gap between descriptive and explanatory adequacy. We present a list of
questions that can successfully set 94 binary parameters in 69 languages drawn from
several different families using positive evidence only. Our proposal can be cast within a
minimalist model of the language faculty, assuming an underspecified universal gram-
mar and a rich network of implications among parameters. We argue that the workload
of parameter setting can be significantly reduced by means of two assumptions: first
by positing that only parameters with a positive value are set; second, by showing that
parameters can be set exclusively on the basis of a core subset of positive evidence, which
we call the Restricted List. We suggest that a model with these properties qualifies as a
plausible framework for language acquisition studies, and also lends itself to be applied
to closed corpora, such as those available as the sole sources for diachronic studies.
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