Stable variation in multidimensional competition
This addresses a theoretical issue in linguistics for researchers studying language evolution and contact, but it is incremental as it builds on existing frameworks.
The paper tackles the problem of stable variation in language change by generalizing Variational Learning to multiple-grammar systems, showing that stable variation is possible in such systems, which challenges previous limitations in the framework.
The Fundamental Theorem of Language Change (Yang, 2000) implies the impossibility of stable variation in the Variational Learning framework, but only in the special case where two, and not more, grammatical variants compete. Introducing the notion of an advantage matrix, I generalize Variational Learning to situations where the learner receives input generated by more than two grammars, and show that diachronically stable variation is an intrinsic feature of several types of such multiple-grammar systems. This invites experimentalists to take the possibility of stable variation seriously and identifies one possible place where to look for it: situations of complex language contact.