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Exclusion in gossipy talk: Highjacking the preference structure for ingroup belonging

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journal contribution
posted on 2018-01-16, 10:49 authored by Jessica RoblesJessica Robles
This paper employs discourse analysis and draws on interdisciplinary approaches to examine how identity is constructed in conversation. The purpose of the paper is twofold: to present an argument for a particular exclusionary practice in everyday life; and to show how this practice is revealed through discourse analytic methods. Specifically, the analysis describes how extremely negative moral assessments about outgroup identity-related behaviour constitute a high-risk strategy for ingrouping with co-participants in ordinary face-to-face interactions. Demonstrating this strategy shows how discourse analysis can provide a frame through which to understand what interactional resources are available to people and therefore how we might reflect on the relationship between local exclusionary practices and broader social phenomena such as racism and sexism.

History

School

  • Social Sciences

Department

  • Communication, Media, Social and Policy Studies

Published in

Critical Approaches to Discourse Analysis across Disciplines

Citation

ROBLES, J., 2017. Exclusion in gossipy talk: Highjacking the preference structure for ingroup belonging. Critical Approaches to Discourse Analysis across Disciplines, 9(2), pp. 5–22.

Publisher

© 2017 Critical Approaches to Discourse Analysis across Disciplines

Version

  • NA (Not Applicable or Unknown)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2017-10-13

Publication date

2017

Notes

This is an Open Access Article. It is published by Critical Approaches to Discourse Analysis across Disciplines under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND). Full details of this licence are available at: http://creativecommons.org/licenses/by-nc-nd/4.0/

ISSN

1752-3079

Language

  • en