Evidence map›Paper›PMID 42445127›Full record

ArticleEvolutionary human sciences2026

Memeing scientific racism: the digital reframing of racialist ideologies.

Sarah Rodriguez-Louette

Abstract read
In one paragraph

Article in Evolutionary human sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Sarah Rodriguez-LouetteCREW, Universite Sorbonne Nouvelle, Paris, France.ORCID https://orcid.org/0009-0009-1071-8271

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

memesracialismscientific racismsocial mediastrategies

Identifiers

PMID42445127
PMCPMC13358990

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.