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Verbal borrowability and turnover rates

Bibliographic Data

ID20344767
AuthorsTimofey Arkhangelskiy (0000-0001-6195-0139, Universität Hamburg, corresponding author)
Year2020
Volume37
Issue4
Pages451-473
Publication date2020-12-10
Open AccessYes
TypeARTICLE
VenueDiachronica (JOURNAL)
Journal identifiersISSN: 0176-4225 • E-ISSN: 1569-9714
PublisherJohn Benjamins Publishing Company (PUBLISHER • NL)
DOI10.1075/dia.19032.ark
OpenAlexW3084043026
LanguageEN
Citations received1
References cited26

Conventional wisdom holds that verbs are more difficult to borrow than nouns. Recent studies have supported this claim, inferring it from the fact that synchronically almost every language studied contains a larger proportion of identifiable borrowings among nouns than among verbs. In this paper, I demonstrate that, while true, there is a logical fallacy in this inference. Using a large diachronic corpus of Russian texts, I show that verbs have lower turnover rates and, consequently, longer life expectancies than nouns, i.e., they are generally more difficult to replace. I argue that this fact alone could theoretically result in the synchronically observed disparities. The hypothesis of cross-linguistically lower verbal turnover rates, which I propose based on these findings, is difficult to verify directly on a large sample of languages. However, it makes a non-trivial prediction, which can be tested more easily. It predicts that if a contact situation lasted for a while, but ceased to exist several centuries ago, the proportion of verbs borrowed during that period and surviving to the present day may equal or exceed the proportion of such borrowings among nouns. The data found in the World Loanword Database ( Haspelmath & Tadmor 2009 ) are consistent with this prediction, thus providing evidence in favor of the hypothesis

Fallacy · Inference · Linguistics · Noun · Computer Science · History · Linguistic Variation and Morphology · Linguistics and language evolution · Linguistics, Language Diversity, and Identity · Philosophy · Psychology · Artificial Intelligence

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Citations per year0.2
Citation span2021 - 2021 (1)
Highly citedNo

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