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Countering reactionary co-radicalization (RC-R): using multi-representational ads

Shabbir, H. ORCID: 0000-0001-7423-174X, Baines, P., Dean, D. & Braddock, K. (2023). Countering reactionary co-radicalization (RC-R): using multi-representational ads. Critical Studies on Terrorism, pp. 1-25. doi: 10.1080/17539153.2023.2295062

Abstract

This study analyses a prototypical ad for countering reactive co-radicalisation, a radicalisation process that occurs in one population segment as a response to radicalisation perceived in another population segment. We employ a multi-representational approach to develop an ad-based solution for undermining dehumanisation of perceived “others”. This “re-humanisation” process is illustrated within the context of the “Mad Mullah” stereotype, a traditional target of reactive co-radicalisation used by right-wing extremists. Using a combination of Critical Visual Theory (CVT) and Dimensional Qualitative Research (DQR), we reveal the structuration of empathy embedded within the re-humanised image of the Muslim “other” in the ad. This contributes to current understanding of attitudinal inoculation by explaining the importance of cultivating empathy in the process of re-humanising the dehumanised “other”.

Publication Type: Article
Additional Information: © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
Publisher Keywords: Reactive co-radicalisation, individuation, empathy, dehumanisation, re-humanisation, extremism, inoculation theory
Subjects: H Social Sciences > H Social Sciences (General)
Departments: Bayes Business School > Management
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