Uralic typology in the light of a new comprehensive dataset

Norvik, Miina; Jing, Yingqi; Dunn, Michael; Forkel, Robert; Honkola, Terhi; Klumpp, Gerson; Kowalik, Richard G A; Metslang, Helle; Pajusalu, Karl; Piha, Minerva; Saar, Eva; Saarinen, Sirkka; Vesakoski, Outi

doi:10.1075/jul.00002.nor

Cited by 3 publications

(1 citation statement)

References 38 publications

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“…The borrowing profiles provide a coarser, zoomed-out overview of contact history, but if necessary a more detailed picture can usually be obtained by using the existing information about the contact situations, supplemented with other, non-basic semantic domains, and taking into account the wider context of historical events. In all, studies on linguistic contacts with vocabulary can be considered a start-ing point, and, in order to gain a fuller picture on contact history, more studies are needed on borrowing in the domains of morphology and syntax (Norvik et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

Loanwords in Basic Vocabulary as an Indicator of Borrowing Profiles

de Heer,

Blokland,

Dunn

et al. 2024

J. Lang. Contact

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Loanwords carry information on linguistic interactions, and can also reveal (pre-)historical population contacts. The contact history of a particular language family is an essential component of historical linguistics, but it is also illuminating for integrative studies of the human past. However, data availability and the time-consuming nature of etymology mean that comprehensive research on loanword layers exists for relatively few languages, forcing us to rely on limited material for others. This paper compares the loanword layers in the basic and total vocabulary of six well-studied Uralic languages, assessing how accurately the borrowing profile in basic vocabulary reflects the full profile of a language. We define “borrowing profile” as the known contact history of a language reflected by its loanword layers. We demonstrate that the loanword layers in basic vocabulary provide an adequate cross-section of the full borrowing profile, although basic vocabulary manifests prehistoric contacts more strongly than more recent contacts.

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Section: Discussionmentioning

confidence: 99%

Loanwords in Basic Vocabulary as an Indicator of Borrowing Profiles

de Heer,

Blokland,

Dunn

et al. 2024

J. Lang. Contact

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Modelling admixture across language levels to evaluate deep history claims

Hübler

Greenhill

2022

Journal of Language Evolution

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The so-called ‘Altaic’ languages have been subject of debate for over 200 years. An array of different data sets have been used to investigate the genealogical relationships between them, but the controversy persists. The new data with a high potential for such cases in historical linguistics are structural features, which are sometimes declared to be prone to borrowing and discarded from the very beginning and at other times considered to have an especially precise historical signal reaching further back in time than other types of linguistic data. We investigate the performance of typological features across different domains of language by using an admixture model from genetics. As implemented in the software STRUCTURE, this model allows us to account for both a genealogical and an areal signal in the data. Our analysis shows that morphological features have the strongest genealogical signal and syntactic features diffuse most easily. When using only morphological structural data, the model is able to correctly identify three language families: Turkic, Mongolic, and Tungusic, whereas Japonic and Koreanic languages are assigned the same ancestry.

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Best practices for spatial language data harmonization, sharing and map creation—A case study of Uralic

et al. 2022

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Despite remarkable progress in digital linguistics, extensive databases of geographical language distributions are missing. This hampers both studies on language spatiality and public outreach of language diversity. We present best practices for creating and sharing digital spatial language data by collecting and harmonizing Uralic language distributions as case study. Language distribution studies have utilized various methodologies, and the results are often available as printed maps or written descriptions. In order to analyze language spatiality, the information must be digitized into geospatial data, which contains location, time and other parameters. When compiled and harmonized, this data can be used to study changes in languages’ distribution, and combined with, for example, population and environmental data. We also utilized the knowledge of language experts to adjust previous and new information of language distributions into state-of-the-art maps. The extensive database, including the distribution datasets and detailed map visualizations of the Uralic languages are introduced alongside this article, and they are freely available.

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Uralic typology in the light of a new comprehensive dataset

Cited by 3 publications

References 38 publications

Loanwords in Basic Vocabulary as an Indicator of Borrowing Profiles

Loanwords in Basic Vocabulary as an Indicator of Borrowing Profiles

Modelling admixture across language levels to evaluate deep history claims

Best practices for spatial language data harmonization, sharing and map creation—A case study of Uralic

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