Icosian Reflections

…a tendency to systematize and a keen sense

that we live in a broken world.

IN  WHICH Ross Rheingans-Yoo—a sometime economist, trader, artist, expat, poet, EA, and programmer—writes on things of int­erest.

Reading Feed (last update: August 6)

A collection of things that I was glad I read. Views expressed by linked authors are chosen because I think they’re interesting, not because I think they’re correct, unless indicated otherwise.


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Blog: Marginal Revolution | PredictIt seems to be closing?


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Blog: Marginal Revolution | How many times are we going to make this kind of mistake? — I am old enough to remember the claims that we had a strategic national stockpile of poxvirus vaccines large enough to vaccinate every American. Now: "The shortage of vaccines to combat a fast-growing monkeypox outbreak was caused in part because the Department of Health and Human Services failed early on to ask that bulk stocks of the vaccine it already owned be bottled for distribution, according to multiple administration officials familiar with the matter."

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January 16 Links: Technologies, Games, and Play

Yes, the Friday linkwrap is, in fact, going out on Friday. We're living in the future!

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The Harvard Political Review reports that a Chicago nonprofit is scraping Twitter to pass on complaints about food poisoning in restaurants to the Chicago Department of Public Health:

Foodborne Chicago depends on human judgment in addition to computerized predictions. First, the algorithm "surfaces tweets that are related to foodborne illnesses." Next, "a human classifier goes through those complaints that the machine classifies, [...determining] what is really about food poisoning and what may be other noise." The Foodborne team then tweets back at the likely cases, providing a link for users to file an official complaint. In short, computers deal with the massive quantity of Twitter data, and humans ensure the quality of the result. According to its website, between its launch on March 23, 2013 and November 10, 2014, the Foodborne algorithm flagged 3,594 tweets as potential food poisoning cases. Of these tweets, human coders have identified 419,

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