What separates Ptolemy’s survey from simple jingoism, however, is his attempt to ascribe the ethnic differences he perceived to a set of rational principles. On this account, the Tetrabiblos is one of the earliest examples of what’s sometimes called anthropological ethnology. And unlike the blood-based racial theories which became especially pernicious in America and Europe in the 19th and 20th centuries, Ptolemy’s ethnology is entirely geographical. This makes the Tetrabiblos rightfully the great-grandfather of what’s surely the most famous modern work of geographic anthropology, Jared Diamond’s best-selling Guns, Germs, and Steel. But let’s not be coy here. What really makes Ptolemy’s whirlwind world tour so entertaining is all the sex—or, rather, how candidly Ptolemy discusses the sexual habits of the peoples he describes. [...]
Ptolemy’s assertion that acceptance of homosexuality decreases along a line running from London to Riyadh agrees pretty well with what I imagine is the current conventional wisdom on the matter. Could he be on to something? To add a quantitative veneer to this question, we can use that favorite tool of data analysts everywhere: a linear regression. [...]
It’s no secret, for instance, that northwestern Europe historically, and even quite recently, was not especially welcoming toward homosexuals. Indeed, when the great Victorian explorer Richard Burton developed his own theory of geographically-influenced sexuality, the Middle East was explicitly included, and England excluded, from his map of what he termed the “Sotadic Zone”—a region where homosexuality was supposedly natural, accepted, and common. Were Figure 2 to be redrawn with data from 150 years ago, it’s altogether likely that the best-fit regression line would have entirely the opposite slope. Yet a correlation that shifts from one moment to the next undermines any argument that there’s a fixed principle at work. Instead, perhaps the only constant uniting Ptolemy’s and Burton’s theories is that each imagined the sexual mores of faraway lands to be radically different from what he knew back home, and each projected his disgust or desire accordingly. That’s hardly the story you would get if the only information you had was the cold and context-free data of Figure 2. Trying to figure out which story, if any, is hiding in your data is challenging expressly because there are usually multiple stories which can be crafted, and deciding which one to emphasize rarely has anything to do with the data itself.
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