<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Probabilistic Thinking on Stephanie Rebecca</title><link>https://stephanierebecca.com/categories/probabilistic-thinking/</link><description>Recent content in Probabilistic Thinking on Stephanie Rebecca</description><generator>Hugo</generator><language>en-gb</language><lastBuildDate>Fri, 08 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://stephanierebecca.com/categories/probabilistic-thinking/index.xml" rel="self" type="application/rss+xml"/><item><title>Superforcasting</title><link>https://stephanierebecca.com/books/superforcasting/</link><pubDate>Fri, 08 May 2026 00:00:00 +0000</pubDate><guid>https://stephanierebecca.com/books/superforcasting/</guid><description>&lt;p&gt;In 2011, IARPA, the research arm of the US intelligence community, launched a massive competition to identify cutting-edge methods to forecast geopolitical events. Four years, 500 questions, and over a million forecasts later, the Good Judgment Project (GJP) led by Philip Tetlock and Barbara Mellers at the University of Pennsylvania emerged as the undisputed victor in the tournament.&lt;/p&gt;
&lt;p&gt;GJP’s forecasts were so accurate that they even outperformed those of intelligence analysts with access to classified data. One of the biggest discoveries of GJP were the Superforecasters: GJP research found compelling evidence that some people are exceptionally skilled at assigning realistic probabilities to possible outcomes even on topics outside their primary subject-matter training.&lt;/p&gt;</description></item></channel></rss>