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Memeing scientific racism: the digital reframing of racialist ideologies

Published online by Cambridge University Press:  17 June 2026

Sarah Rodriguez-Louette*
Affiliation:
CREW, Universite Sorbonne Nouvelle, Paris, France

Abstract

Content of image described in text.

This article examines how racialised memes circulating on X revive scientific racism, demonstrating that hybrid formats reconfigure biological essentialisation within contemporary digital culture. Using a corpus of 68 viral items and 4 case studies, our analysis applies Shifman’s content–form–stance model, informed by cognitive psychology. We show that these memes adopt common scientific conventions while relying on visual polarisation, whereby rapid perceptual contrasts stand in for arguments. Familiar templates, reinforced by selective algorithmic amplification, create a sense of perceptual legitimacy through fast categorisation and pre-attentive processing. We also trace how these cognitive shortcuts provide the basis for a regime of racialisation tailored to digitally immersed male audiences, producing gendered behavioural stereotypes and disappearance anxieties. A further pattern is the recoding of older racial hierarchies into neutral-sounding language of competence, allowing these ideas to travel across racialist, masculinist, techno-elitist, and anti-DEI (Diversity, Equity, Inclusion) communities. In this environment, memes work as micro-infrastructures of classification that align claims to objectivity with affect and platform incentives, making inequality appear natural and necessary. We conclude that effective critique must meet these images on their own terrain, with a pedagogy of the gaze that teaches publics how to recognise and challenge persuasion in meme-driven spaces.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2026. Published by Cambridge University Press.
Figure 0

Table 1. Thematic distribution of the corpus (n = 68) and average engagement metrics across themes. Average likes and views are calculated across all memes assigned to each thematic category1 long description.

Figure 1

Figure 1. Schematic reconstruction of a meme juxtaposing Black and White female profiles. Digital alterations accentuate contrast while preserving only general compositional features.

Figure 2

Figure 2. Schematic reconstruction of a meme using the ‘smuggie’ character to ridicule progressive positions.

Figure 3

Figure 3. Schematic reconstruction of a meme combining a world map with stylised demographic icons.

Figure 4

Figure 4. Schematic reconstruction of a meme contrasting the technological history of the United States with a stereotyped image of an earthen dwelling used to symbolise Africa.

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