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→Inequality within sexes
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== Inequality within sexes == | == Inequality within sexes == | ||
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A study analyzing GINI coefficients in human [[relationship|relationships]] found that “single men have a higher Gini coefficient (.536) than single women (.470). Thus, female sexual partners are more unequally distributed among single men than male sexual partners are among single women”<ref>https://contexts.org/blog/who-has-how-many-sexual-partners/</ref>. Famous sexologist [[Kristin Spitznogle]] says this is proof that [[Bateman's Principle]] now applies to humans.<ref>https://resett.no/2018/06/29/menn-i-ufrivillig-solibati/</ref> A separate study of Tinder found that Tinder's GINI coefficient between the genders was on scale with the income inequality of third-world countries (see chart below).<ref>https://medium.com/@worstonlinedater/tinder-experiments-ii-guys-unless-you-are-really-hot-you-are-probably-better-off-not-wasting-your-2ddf370a6e9a</ref> | A study analyzing GINI coefficients in human [[relationship|relationships]] found that “single men have a higher Gini coefficient (.536) than single women (.470). Thus, female sexual partners are more unequally distributed among single men than male sexual partners are among single women”<ref>https://contexts.org/blog/who-has-how-many-sexual-partners/</ref>. Famous sexologist [[Kristin Spitznogle]] says this is proof that [[Bateman's Principle]] now applies to humans.<ref>https://resett.no/2018/06/29/menn-i-ufrivillig-solibati/</ref> A separate study of Tinder found that Tinder's GINI coefficient between the genders was on scale with the income inequality of third-world countries (see chart below).<ref>https://medium.com/@worstonlinedater/tinder-experiments-ii-guys-unless-you-are-really-hot-you-are-probably-better-off-not-wasting-your-2ddf370a6e9a</ref> | ||
A data scientist for Hinge reported on the Gini coefficients he had found in his company’s abundant data, treating “likes” as the equivalent of income. He reported that heterosexual females faced a Gini coefficient of 0.324, while heterosexual males faced a much higher Gini coefficient of 0.542. While the situation for women is something like an economy with some poor, some middle class, and some millionaires, the situation for men is closer to a world with a small number of super-billionaires surrounded by huge masses who possess almost nothing. According to the Hinge analyst: | A data scientist for Hinge reported on the Gini coefficients he had found in his company’s abundant data, treating “likes” as the equivalent of income. He reported that heterosexual females faced a Gini coefficient of 0.324, while heterosexual males faced a much higher Gini coefficient of 0.542. While the situation for women is something like an economy with some poor, some middle class, and some millionaires, the situation for men is closer to a world with a small number of super-billionaires surrounded by huge masses who possess almost nothing. According to the Hinge analyst: | ||