Activity Badge Wednesday Winners

Congratulations to forecasters from the past several weeks who won profile badges on SciCast.org during Activity Badge Wednesday. Learn more about the special.

Profile Badge Winners

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July 23, 2014

laughinghyena13, jcurtis, kelli.thompson, supportcaring, mwwebb@uams.edu, parkerrc, Kaspar Snashall won a Helium badge

Tender won a Neon badge

Apeear, Phoenix won an Argon badge

Recycler, Recurring, hippolyta won a Krypton badge

July 30, 2014

thucthuc, DustLover1104, ronald.redfern, mrmark, Jaydady, jimpencelol, jameswillwin1, Awsomeboy360, sferrrl, Bill Humphrey, iknwnbob, melrrorfd, sciamazon, kmcwilliams, richhuah, bdjzn won a Helium badge

Phoenix won a Neon badge

hippolyta, peaigr won an Argon badge

dvasya won a Krypton badge

August 6, 2014

spambot2113, 123bilbobibo, jkim3, DaBagBoy, Kz556 won a Helium badge

Recycler won an Argon badge

Robert, sflicht won a Radon badge

August 13, 2014

banneradman, ejrowi, ejonahor, maria, journeymenc, brigadier won a Helium badge

pressurization won a Neon badge

Robert won a Xenon badge

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3 thoughts on “Activity Badge Wednesday Winners

    1. ctwardy

      Based on comments it seems that ~5 of our top forecasters use models at least sometimes, and a couple have even started automating forecasts from their models. It’s wise to include models when you can. But in weather forecasting, chess, and many other areas, the top systems are hybrids where humans adjust the model forecasts for local context or “broken leg” scenarios the model can’t see.

      In Expert Political Judgment the humans only explained half the variance of relatively simple trend models. But in Tetlock’s Good Judgment Project, the humans have gotten very good, partly by using models, but partly by finding skilled, well-calibrated forecasters, and giving them enough feedback and support to get even better.

      Hopefully some of our forecasters can reply on how they mix models, careful thought, intuition, and outrage to make their forecasts.

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    2. kominek

      I’m one of the forecasters using models. I don’t have exact counts, but I expect I have models (formal, written down things/programs I could give another person so they get the same number I do) for fewer than a quarter of the questions I trade on. The rest are just my opinion (expert or not, depending on the question).

      There are quite a few questions dealing with technological development, mathematical breakthroughs, and the business decisions of tech companies. None of those really seem amenable enough to modelling to make it worth the effort to try.

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