How to explore Scott Alexander's work and his 1500+ blog posts? This unaffiliated fan website lets you sort and search through the whole codex. Enjoy!

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5 posts found
Jun 14, 2024
acx
15 min 2,061 words 541 comments 255 likes podcast (13 min)
Scott Alexander attempts to replicate a poll claiming high rates of COVID vaccine deaths, finds much lower rates, and concludes such polls are unreliable due to bias. Longer summary
Scott Alexander attempts to replicate a poll claiming high rates of COVID vaccine-related deaths. He conducts his own survey and finds much lower rates, investigates possible reasons for the discrepancy, and concludes that such polls are unreliable due to political bias and statistical misunderstanding. Scott's survey shows 0.6% of respondents reporting a vaccine-related death in their family, compared to 8.5% in the original poll. He follows up with respondents who reported deaths, finding most cases involve elderly individuals, and the numbers are consistent with normal death rates. Shorter summary
Mar 01, 2022
acx
56 min 7,757 words 735 comments 113 likes podcast (58 min)
Scott Alexander evaluates predictions about the Russia-Ukraine war, analyzing the performance of prediction markets and individual pundits. Longer summary
Scott Alexander reviews various predictions about the Russia-Ukraine war, evaluating pundits and prediction markets on their accuracy regarding the invasion and Ukrainian resistance. He discusses the performance of Metaculus, Polymarket, Manifold Markets, and individual forecasters like Edward Luttwak, Anatoly Karlin, Richard Hanania, Dmitri Alperovich, Tyler Cowen, Samo Burja, and others. Scott notes that most failed predictions were based on political precommitments, while successful ones often aligned with biases that happened to match reality. He concludes that having a bias corresponding to the outcome is often more important than being smart when it comes to prediction success. Shorter summary
Mar 10, 2021
acx
36 min 5,025 words 653 comments 302 likes podcast (30 min)
Scott Alexander explores the concept of 'trapped priors' as a fundamental problem in rationality, explaining how it leads to persistent biases and suggesting potential solutions. Longer summary
Scott Alexander explores the concept of 'trapped priors' as a fundamental problem in rationality. He explains how the brain combines raw experience with context to produce perceptions, and how this process can lead to cognitive biases and phobias. The article discusses how trapped priors can make it difficult for people to update their beliefs, even in the face of contradictory evidence. Scott also examines how this concept applies to political biases and suggests potential ways to overcome trapped priors. Shorter summary
Oct 08, 2018
ssc
9 min 1,179 words 533 comments podcast (11 min)
Scott Alexander analyzes a survey on readers' estimated probabilities of Kavanaugh's guilt, finding significant partisan differences and no clear consensus even with probabilistic thinking. Longer summary
Scott Alexander conducted a survey asking readers to estimate the probability of Judge Kavanaugh being guilty of sexually assaulting Dr. Ford. The post analyzes the results, breaking them down by political party, gender, and background knowledge. The average probability given was 52.64%, with significant partisan differences. The survey also explored whether respondents thought the accusations were sufficient to reject Kavanaugh's nomination. Scott notes that even when encouraged to think probabilistically, people's responses still showed strong partisan biases, and there was no clear consensus even among politically neutral respondents. Shorter summary
Sep 25, 2013
ssc
4 min 552 words 79 comments
The author analyzes results of a prediction contest about American political opinions, revealing participants' inaccuracies and biases in estimating current views and changes over time. Longer summary
This post discusses the results of a prediction contest where participants estimated current American opinions on political issues and how those opinions have changed over 22 years. The author analyzes the accuracy of predictions, noting that participants were generally poor at estimating current opinions but slightly better at predicting changes. The post reveals that participants tended to overestimate how leftist Americans are and how much society has shifted left. The author also mentions that there was little difference in accuracy between reactionary and progressive participants, and names the most accurate predictors. Shorter summary