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Unpacking the Semantics of Coronaviruses' "Referent Things”: A Corpus-Driven Systemic Functional Linguistic Analysis
Word ; 69(1):49-90, 2023.
Article in English | Scopus | ID: covidwho-2279409
ABSTRACT
The current study seeks to unpack the corpus-driven semantics of the "referent things” underlying the use of the lexical item coronaviruses in the data of The Coronavirus Corpus [Davies, Mark. 2019-. The Coronavirus Corpus. https//www.english-corpora.org/corona/]. Drawing on the Systemic Functional Linguistic (SFL) Model of the Cardiff Grammar, a concordance-bound analysis has been conducted on the item coronaviruses as expounding the structural element head (h) of its relevant nominal-group patterns in the corpus data. The Cardiff Grammar Model has systematically revealed the semantics of coronaviruses' referent things as realized by corpus-driven syntactic patterns of eleven coronaviruses-expounded nominal groups in two respects in the corpus data. First, the item coronaviruses has been empirically shown to have three dominant types of referent (i) a particularized referent has been expressed through the system of PARTICULARIZATION, (ii) a substantive referent through QUANTIFICATION (selection by quantity, selection by typicity, and selection by representation), and (iii) cultural-classification referent through the two overlapping systems of CLASSIFICATION and SELECTION (selection by quality and selection by qualification). Second, these referents demonstrated two aspects of semantic representation via participant-role (PR) conflation (i) a cultural-classification referent assumes the complementary participant roles of Identifier, Actor, and Patient;(ii) a particularized substantive referent has the sole PR of Agent. © 2023 International Linguistic Association.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Word Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Word Year: 2023 Document Type: Article