JOURNAL ARTICLE

Non-referential elements in the history of Low German.

  • Published In: Evolutionary Linguistic Theory, 2024, v. 6, n. 1/2. P. 122 1 of 3

  • Database: Communication Source 2 of 3

  • Authored By: Petrova, Svetlana 3 of 3

Abstract

The paper investigates the development of the system of non-referential elements in Low German from a cross-Germanic perspective. The data is taken from the currently available reference corpora, which cover the period from the beginning of the attestation in the late 9th century to 1700. The analysis of the corpus data suggests that the equivalents of the neuter pronouns it and that act as cataphoric elements already in the earliest Low German records, and that they gradually acquire additional non-referential functions, including that of an existential expletive. This contrasts with the assumed situation in the contemporary Low German varieties which, according to traditional descriptions, lack pronominal expletives comparable to German es but rather display adverbial expletives, comparable to existential there in English and er in Dutch. Examining the distributional properties of the pronominal expletive it in the history of Low German, the paper observes that this type of expletive is prototypically present in formal written registers and likely remains outside the domain of spoken, colloquial style, which is the focus of the traditional dialectal descriptions. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Evolutionary Linguistic Theory. 2024/01, Vol. 6, Issue 1/2, p122
  • Document Type:Article
  • Subject Area:Language and Linguistics
  • Publication Date:2024
  • ISSN:2589-1588
  • DOI:10.1075/elt.00056.pet
  • Accession Number:183553763
  • Copyright Statement:Copyright of Evolutionary Linguistic Theory is the property of John Benjamins Publishing Co. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.