My Faults My Own

…willing to sacrifice something we don't have

for something we won't have, so somebody will someday.

IN WHICH Ross Rheingans-Yoo—an artist, economist, poet, trader, ex-pat, EA, and programmer—oc­cas­ion­al­ly writes on things of int­erest.

Reading Feed (last update: December 15)

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 | A social credit system for scientists? — Chinese scientists, that is, and fraudsters at that. What, would you rather be soft on fraud?


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Blog: JeffTK | Taking a Safety Report

Comic: xkcd | arXiv — "...invaluable projects which, if they didn't exist, we would dismiss as obviously ridiculous and unworkable."


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Blog: Thing of Things | Scrupulosity Sequence #3: Load-Bearing Things

Blog: JeffTK | Not losing things — "I almost never lose things, especially important things like my keys, laptop, or ear warmers. Here's an attempt to write up the system I use, in case it's useful to others..."


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Blog: Tyler

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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, roughly 12 percent, as

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