A satirical collection of fictional saint stories about rationalists taking rationalist principles to extreme lengths, written in the style of religious hagiography.

Scott Alexander praises Polymarket's election success but argues their Trump odds were mispriced, explaining why Trump's win doesn't significantly validate their numbers over other forecasters.

Scott Alexander discusses recent developments in prediction markets and forecasting, including Metaculus' milestone, PredictIt's legal issues, and various prediction market topics.

Scott Alexander examines the use of absurdity arguments, reflecting on his critique of Neom and offering strategies to balance absurdity heuristics with careful reasoning.

Scott Alexander evaluates his 2021 predictions, analyzing his performance across various confidence levels and comparing his results to other forecasters and prediction markets.

Scott Alexander evaluates his 2020 predictions, finding he was generally overconfident, and discusses the implications for his prediction-making process.

Scott Alexander reviews and analyzes his 2019 predictions, finding he was generally well-calibrated but slightly underconfident across all confidence levels.

Scott Alexander evaluates his 2018 predictions, analyzing his accuracy and discussing factors that affected his performance.

Scott Alexander evaluates his 2017 predictions, analyzing his accuracy and calibration across different confidence levels.

Scott Alexander evaluates his 2016 predictions, finding good overall calibration with slight underconfidence at 70% probability, consistent with previous years.

Scott Alexander evaluates the accuracy of his 2015 predictions, finding overall good calibration and considering it a successful year.

Scott Alexander discusses the problem of overconfidence in probability estimates, arguing that extreme certainty is rarely justified, especially for complex future predictions.

Scott Alexander explores the possibility of a 'General Factor of Correctness' and its implications for rationality and decision-making across various fields.

Scott Alexander makes belated predictions for 2015, covering world events and personal life with varying confidence levels.

Scott presents the results of the 2014 Less Wrong survey covering demographics, beliefs, community participation, and various psychological measures from 1503 respondents.

Scott Alexander evaluates his 2014 predictions, finding himself well-calibrated across various confidence levels, and jokingly declares himself trustworthy on all matters.

Scott Alexander presents comprehensive results from the 2013 Less Wrong community survey, covering demographics, beliefs, and behavioral patterns of 1636 respondents.

Scott presents comprehensive results from the 2012 Less Wrong Survey of 1195 respondents, covering demographics, beliefs, IQ measures, and a concerning calibration test showing poor performance at avoiding overconfidence bias.

Scott Alexander presents comprehensive results from the 2011 Less Wrong survey of 1090 respondents, covering demographics, beliefs, probability estimates on various topics, and a calibration test that shows the community performs better than average but has some calibration issues.

Scott discusses how people's subjective self-assessments are often miscalibrated, using his own exam experiences and research on physical attractiveness and likeability to argue for replacing internal feelings with objective external measurements.

Scott asks whether there's an accepted method for measuring calibration separately from domain knowledge, noting that common scoring rules conflate the two.

Scott describes six techniques for translating vague probability feelings into accurate numerical estimates, explaining the strengths and weaknesses of each method.

Scott calculates that on exams penalizing wrong answers at half the reward for correct ones, guessing always has positive expected value, but none of his intelligent classmates would accept this logic despite clear explanations.