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In academic research writing, the way in which an author engages with and positions him/herself in relation to other voices in the discourse, e.g. with the literature and the putative reader, is an integral part of the social practice of communicating research. Understanding how this engagement is realized may have important implications for academic literacy programs, particularly in the development of academic writing skills. In this paper, I investigate engagement in written medical research discourse, by applying the systemic-functional framework of APPRAISAL, a model of evaluative language, to a corpus of English-language medical research articles. Specifically, I present how the corpus has been compiled and annotated according to part of the ENGAGEMENT system, a subsystem of APPRAISAL dealing with writer/speaker resources for intersubjective positioning. These engagement resources include what are generally dealt with under the headings of modality, hedging, and attribution, among others, but they are interpreted here in terms of their dialogic functionality; that is, the role they play in construing for the text a background of different voices (the literature, the putative reader) and different value positions. For instance, a modal Finite such as may not only signals a speaker’s/writer’s degree of certainty or level of commitment, but, from a dialogic perspective, it also ‘entertains’ or allows for the possibility of alternative positions or viewpoints in the discourse. (Consider, for example, Reducing LDL cholesterol may reduce the development of vascular disease.) In this paper, I present the different types of engagement features and their interrelations as identified in the corpus, the probabilities of these features being selected, the frequencies of their occurrence, their distributions across the texts, and some of their typical realizations. The findings show that there is considerable variation in the types of engagement resources used as well as in their distributions, both across and within different sections of the medical research article.
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Stored only when both papers are in the corpus — 60 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.