1. Equality data as immoral race politics: A case study of liberal, colour‐blind, and antiracialist opposition to equality data in Sweden.
- Author
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Wikström, Peter and Hübinette, Tobias
- Subjects
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PREVENTION of racism , *ETHICS , *PRACTICAL politics , *CRITICISM , *ATTITUDE (Psychology) , *GROUP identity , *RACIAL inequality , *GOVERNMENT policy , *POLICY sciences - Abstract
This study concerns discursive mobilisations of race and racism in the Swedish debate on equality data, in the case of a controversial statement made by a Swedish Green Party MP. In March 2019, female Muslim MP Leila Ali Elmi argued publicly for introducing equality data in Sweden, in opposition to prevailing colour‐blind and antiracialist norms. Her statement was controversially formulated in terms of 'registering' people 'by race', leading to forceful criticism in the mainstream press and on social media, particularly on Twitter. In a material representing this criticism, we analyse discourse participants' argumentative strategies, focusing on mobilisations of race and racism as acts of subject positioning, performative of a moral identity. Participants positioned themselves as morally righteous, liberal antiracists by virtue of their own antiracialism (Goldberg, 2009, The threat of race. Wiley‐Blackwell, Hoboken, NJ) and colour‐blindness (Bonilla‐Silva, 2010, Racism without racists. Rowman & Littlefield, Lanham, MA), while constructing equality data as a racist practice, and as a threat to a liberal order. They also constructed advocates of equality data, and specifically Ali Elmi herself, as being irrational race ideologues, to be morally condemned for espousing a return to racial thinking comparable to that of German Nazism or scientific racism. The findings point to the exceptional status and character of what we call a colour‐blind antiracialism in Sweden, and further show how far 'liberal arguments for illiberal ends' can go in reinforcing a moral status quo and counteracting antiracist reform. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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