Evidentiality in science from specialization to popularization: A case study of COVID-19 texts

Abstract

Abstract Since the beginning of the COVID-19 pandemic outbreak, medical texts on the pandemic have enjoyed wide popularity, and one of the key issues has always been the accuracy and dependability of the information they contain. The use of evidentiality, a linguistic system which functions to indicate the source and credibility of information, is thus worth exploring in COVID-19 texts. Adopting a synthesized framework within the overall model of systemic functional linguistics, this paper sets out to investigate the lexicogrammar and semantics of evidentiality on the basis of data collected in the form of both specialized and popular texts on COVID-19. Evidentiality in these texts is explored along four dimensions: (i) evidential taxonomy, where specialized texts favor reporting, while popular texts favor belief and inferring; (ii) information source, where specialized texts highlight the voices of authorship, original research, and patients, whereas popular texts highlight the voices of scientists, institutions, countries, and laypeople; (iii) modalization, where specialized texts typically indicate a higher degree of modal responsibility than their popular counterparts; and (iv) engagement, where specialized texts favor dialogic expansion and popular texts favor contraction. It is hoped that these findings will shed light on linguistic variation according to different contextual configurations, as well as clarifying rhetorical conventions in discourse communities of science.