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Can language relatedness be established without cognate words? This question has remained unresolved since the nineteenth century, leaving language prehistory beyond etymologically established families largely undefined. We address this problem through a theory of universal syntactic characters. We show that not only does syntax allow for comparison across distinct traditional language families, but that the probability of deeper historical relatedness between such families can be statistically tested through a dedicated algorithm which implements the concept of ‘possible languages’ suggested by a formal syntactic theory. Controversial clusters such as e.g. Altaic and Uralo-Altaic are significantly supported by our test, while other possible macro-groupings, e.g. Indo-Uralic or Basque-(Northeast) Caucasian, prove to be indistinguishable from a randomly generated distribution of language distances. These results suggest that syntactic diversity, modelled through a generative biolinguistic framework, can be used to provide a proof of historical relationship between different families irrespectively of the presence of a common lexicon from which regular sound correspondences can be determined; therefore, we argue that syntax may expand the time limits imposed by the classical comparative method.This article is part of the theme issue ‘Reconstructing prehistoric languages’.
significance testing, generative grammar, evolutionary biolinguistic, language relatedne, Linguistics, multilateral comparison, Cultural Evolution, linguistic prehistory, Humans, Speech, evolutionary biolinguistics; generative grammars; language relatedness; linguistic prehistory; multilateral comparison; significance testing, Language
significance testing, generative grammar, evolutionary biolinguistic, language relatedne, Linguistics, multilateral comparison, Cultural Evolution, linguistic prehistory, Humans, Speech, evolutionary biolinguistics; generative grammars; language relatedness; linguistic prehistory; multilateral comparison; significance testing, Language
citations 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). | 11 | |
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. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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