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  • Potts_Semino_Corpora_final

    Rights statement: Copyright © 2017. Edinburgh University Press.

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Healthcare professionals’ online use of violence metaphors for care at the end of life in the US: a corpus-based comparison with the UK

Research output: Contribution to Journal/MagazineJournal articlepeer-review

<mark>Journal publication date</mark>04/2017
Issue number1
Number of pages30
Pages (from-to)55-84
Publication StatusPublished
<mark>Original language</mark>English


The use of Violence metaphors in healthcare has long been criticised as detrimental to patients. Recent work (Demmen et al., 2015; Semino et al., 2015) has combined qualitative analysis with corpus-based quantitative methods to analyse the frequency and variety of Violence metaphors in the language of UK-based patients, family carers, and healthcare professionals talking about cancer and/or end-of-life care. A new, 250,324-word corpus of US health professionals’ online discourse has been collected to add a contrastive, cross-cultural element to the study of metaphors in end-of-life care. In this work, we move towards a replicable method for comparing frequency and type of Violence metaphors in UK and US contexts by making use of both search-and-recall and key semantic tag analysis in the corpus query tool Wmatrix. First, we discuss the most overused and underused semantic domains in the US corpus as compared with the pre-existing UK corpus of online healthcare professional discourse. Second, we show that there are no notable frequency differences in the occurrence of Violence metaphors in the two corpora, but we point out some differences in the topics that these metaphors are used to discuss. Third, we introduce a novel framework for analysing agency in Violence metaphors and apply it to the US corpus. This reveals the variety of relationships, concerns and challenges that these metaphors can express. Throughout, we relate our findings to the different US and UK cultural and institutional contexts, and reflect on the methodological implications of our approach for corpus-based metaphor analysis.

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Copyright © 2017. Edinburgh University Press.