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Opacity in Tundra Nenets

Authors: Kavitskaya, Darya; Staroverov, Peter;

Opacity in Tundra Nenets

Abstract

The analysis of opaque relations presents a problem to classic Optimality Theory (Prince and Smolensky 1993, McCarthy and Prince 1993), inherently a surface-oriented theory. Many different proposals have been made to integrate the analysis of opacity into OT. In this paper, we address the problem of opacity in Tundra Nenets (TN), a Uralic (Samoyedic) language spoken in Arctic Russia and Northern Siberia.TN has a complex system of alternations, many of which interact opaquely, and provides a good test case for the current theories of opacity. In this paper, we are concerned with the categorical metrical vowel deletion that represents a case of self-counterfeeding opacity, and its interaction with vowel deletion in final syllables. We show that among OT approaches to opacity, there are some that cannot handle metrical vowel deletion in TN in principle (Targeted Constraints, OT-CC), some that can but are undesirable on theoretical grounds (Local Constraint Conjunction, in particular, self-conjunction), and the full analysis of the data still requires combining two different theories (Stratal OT and Comparative Markedness).

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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