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Laparoscopic Endoscopic Surgical Science Lexico-grammatical Cohesion in English as a Global Lingua Franca: A Corpus-based Systemic Functional Analysis [ALRJournal]
ALRJournal. 2018; 2(2): 22-32 | DOI: 10.14744/alrj.2018.22931

Lexico-grammatical Cohesion in English as a Global Lingua Franca: A Corpus-based Systemic Functional Analysis

Amin Mohammad Mostajeran Gourtani, Reza Ghaffarsamar, Ramin Akbari
ELT Department, Tarbiat Modares University, Tehran, Iran

This corpus-based study is an attempt to illuminate two lexicogrammatical features of ELF represented by the texts in the “about” section of sixty universities around the globe. Drawing on the Kachruvian three-circle model, a corpus was collected from the websites of twenty universities in the inner circle, twenty in the outer circle and twenty in the expanding circle. The corpus was then analysed around the clause for the types of Reference and the types of Conjunction, two of the four main ways of creating cohesion in Halliday’s Systemic Functional Grammar. The frequency count of the seven devices in the system of Reference reveals that all the three circles use the system of Reference in similar ways, although some differences can be identified. The results also show similarities between the ways the system of conjunction is used. However, the main aim of the study was to describe varieties of English alongside each other rather than find statistically significant differences between them. One major implication of this study is that this line of research has a huge potential for clarifying the linguistic features and explaining English as a global lingua franca as an independent variety.

Keywords: ELF, Corpus, Systemic Functional Grammar, System of Reference, System of Conjunction, Cohesion

Amin Mohammad Mostajeran Gourtani, Reza Ghaffarsamar, Ramin Akbari. Lexico-grammatical Cohesion in English as a Global Lingua Franca: A Corpus-based Systemic Functional Analysis. ALRJournal. 2018; 2(2): 22-32

Corresponding Author: Amin Mohammad Mostajeran Gourtani, Iran
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