This visualisation looks at ten scientific discoveries where a woman was under-credited in favour of a man. Its central question: does the recognition bias correct itself over time? The data answer no.
The pairs are organised in two tiers.
Tier 1, documented Matilda effect (8 pairs). The woman's under-crediting is documented by at least one academic or encyclopaedic source: Rossiter (1993) on the Matilda effect, Sayre (1975) on Rosalind Franklin, INSERM report (2014) on the Gautier-Lejeune case.
Tier 2, observable under-crediting (2 pairs). The woman contributed significantly to the same discovery or research programme, but her contribution is markedly less recognised, without specific scholarly documentation framing it as a Matilda effect.
Three cases initially considered were set aside. Nettie Stevens: an outlier peak in 2016 pulled the average up across the whole period, even though the man had dominated year after year from 2017 onward. Marietta Blau: annual volumes were too low, between three and nine thousand page views per year. Leona Woods: her extreme ratio relative to Enrico Fermi was partly explained by Fermi's enormous public fame (an emblematic figure of the twentieth century, Nobel laureate, Manhattan Project), which made the case hardly comparable to the rest of the corpus.
Institutional recognition. Number of Wikipedia language editions. Source: Wikidata, February 2026.
Contemporary attention. English-language Wikipedia page views, July 2015 to December 2025. Source: Wikimedia Pageviews API.
F/M ratio. The simple ratio of the woman's average annual page views to the man's, in each pair. A ratio above 1 means the woman is viewed more than her male colleague.
A note on the choice of comparison men. The F/M ratio jointly measures the woman's under-crediting and the man's renown. This entanglement is intrinsic to the question asked: invisibility is measured in the gap, not in any isolated quantity. All selected pairs share a documented scientific co-signature and a documented or observable attribution dispute. The Leona Woods case was set aside precisely because Fermi's public fame dominated to the point of making the case hardly comparable to the rest of the corpus.
This is a piece of communication, not a research paper. The visualisation does not claim to establish a causal link between visibility and recognition, which would be trivial.
What it does show is less obvious: across ten documented cases of scientific under-crediting, the bias inherited from the twentieth century does not correct itself on its own. Today, the women who have not been the subject of a specific public act of visibility remain as little known as they were twenty years ago.
The causal effect of showing female role models on perceptions has been established in other contexts, in particular by the randomised study of Breda, Grenet, Monnet & Van Effenterre (The Economic Journal, 2023).
Lauriane Mouysset
Research Director at CNRS
CNRS Bronze Medal (2024)
Ambassador for Femmes & Sciences
lauriane-mouysset.fr
© 2025 Lauriane Mouysset · CC BY-NC 4.0