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Challenging generalisations: Leveraging the power of individuality in support group interactions

Published online by Cambridge University Press:  24 July 2020

Marco Pino Open the ORCID record for Marco Pino [Opens in a new window]
Marco Pino*
Affiliation:
Loughborough University, UK
*
Address for correspondence: Marco Pino Loughborough University, Communication and Media Brockington Building, Margaret Keay Rd, Loughborough, LE11 3TUUnited Kingdom of Great Britain and Northern Irelandm.pino@lboro.ac.uk
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Abstract

Explicit generalisations are statements that attribute a characteristic to all members of a social category (e.g. drug users). This article examines the tensions and negotiations that the use of generalisations prompts within support group interactions. Generalisations are practices for the cautious implementation of delicate actions. They can be used to convey perspectives on group members’ experiences by implication (without commenting on them directly), by virtue of those members belonging to the category to which a generalisation applies. At the same time, generalisations can misrepresent some individual cases within that category. Using conversation analysis, the article investigates how generalisations are deployed, challenged, and then defended in support group interactions. These analyses identify a tension between utilising the sense-making resources that category memberships afford, and the protection of its members from unwelcome generalisations. Data consist of recorded support-group meetings for people recovering from drug addiction (in Italy) and for bereaved people (in the UK). (Bereavement, conversation analysis, delicacy, drug addiction, generalisation, individuality, membership categorisation, morality, support groups)*

Type
Articles
Information
Language in Society , Volume 50 , Issue 5 , November 2021 , pp. 695 - 722
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Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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Footnotes

*

I would like to thank two anonymous reviewers for their helpful comments on this article. My gratitude also goes to Rein Sikveland for commenting on an early version of this article.

Work on the TC data was funded by the People Programme (Marie Curie Actions) of the European's Union Seventh Framework Programme (FP7/2007-2013) under REA grant agreement no 626893. The contents of this article reflect only the views of the author and not the views of the European Commission.

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