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Cited by 1,998

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Stance and engagement: a model of interaction in academic discourse

Hyland, Ken·2005·Discourse Studies

Abstract

A great deal of research has now established that written texts embody interactions between writers and readers. A range of linguistic features have been identified as contributing to the writer's projection of a stance to the material referenced by the text, and, to a lesser extent, the strategies employed to presuppose the active role of an addressee. As yet, however, there is no overall typology of the resources writers employ to express their positions and connect with readers. Based on an analysis of 240 published research articles from eight disciplines and insider informant interviews, I attempt to address this gap and consolidate much of my earlier work to offer a framework for analysing the linguistic resources of intersubjective positioning. Attending to both stance and engagement, the model provides a comprehensive and integrated way of examining the means by which interaction is achieved in academic argument and how the discoursal preferences of disciplinary communities construct both writers and readers.

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Metadata

Authors
Hyland, K.
Venue
Discourse Studies
Published
2005-05
Volume
7
Issue
2
Pages
173-192
ISSN
  • 1461-4456 (ISSN-L)
  • 1461-7080
OpenAlex
W1987274994
Cited by
1,998
References
5
FWCI
201.85
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Stance and engagement: a model of interaction in academic discourse. https://app.cochat.ai/papers/10.1177/1461445605050365
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Hyland, K. (2005). Stance and engagement: a model of interaction in academic discourse. Discourse Studies. https://doi.org/10.1177/1461445605050365

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.