Why the internet keeps ranking women by their origin

Comparing women by nationality and scoring them from 1 to 10 is a recurring pattern online. Behind it lies more stereotype than real observation.

English · Original discussion in Spanish · Published

Why the internet keeps ranking women by their origin
Ranking women by their origin: the online aesthetic bias

Sorting women by nationality and rating them — from the idealized Asian woman to the girl next door — is a pattern that resurfaces online every so often. What's new is not the idea itself but the vocabulary: a jargon of its own that mixes fascination and contempt and turns attractiveness into a hierarchical scale based on passports. Beneath the joke lies an old mechanism. Classifying the other by their origin before anything else.

From imported ideal to barely passing grade

The recurring archetype — with actress Tang Wei as the reference — clashes with the reality of those who live there. Someone living about 80 km from Shanghai sums it up without drama: the same face that is elevated to a beauty standard here barely passes in her own country. Idealization works better the farther away its object is. When the distance shrinks, the myth deflates.

Aesthetic trends know no borders

The supposed exoticism doesn't hold up either. The tattoo craze, cosmetic procedures, and imported beauty standards spread just as fast in Asia as in Europe: what is sold as a cultural trait is usually a global trend. And the generalizations — that they all smile the same way, that they all look identical — say more about the prejudice of those making them than about a group of over a billion people.

Where the reasoning falls apart

Ranking by nationality doesn't withstand serious analysis, but it keeps working as clickbait. As soon as it is asked for a measurable criterion — a figure, an objective fact — it runs out of steam on its own. The rest is bar-talk conversation.

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Summary of a discussion on Burbuja.info - Foro de economía, actualidad y política., translated from Spanish and reviewed before publication. Read the full discussion (32 replies).

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