Scott examines the Metaculus Threat To Democracy Index, which uses crowdsourced forecasting to measure democratic health, discussing its advantages over traditional expert-based indices and its vulnerabilities to manipulation and selection bias. Longer summary

Scott discusses the Metaculus Threat To Democracy Index, a new approach to measuring American democratic health using crowdsourced forecasting rather than expert opinion. The index aggregates 153 questions about democratic threats (like election cancellations or ballot access) weighted by forecasters' historical accuracy. Scott analyzes its advantages—transparency, resistance to ideological bias, and ability to measure probabilities rather than binary outcomes—alongside its risks, including susceptibility to crowd attacks, bot manipulation, and question selection bias. He finds the recent data somewhat reassuring (showing no expected worsening during Trump's term) and suggests the index will become more valuable over time as question biases become less relevant. Shorter summary

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

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

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

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

A collection of interesting links spanning topics from CRISPR technology to economic studies, with Scott's commentary on each item. Longer summary

This is a links post collecting various interesting articles and studies across multiple domains. Scott shares updates on CRISPR technology, corporate governance issues, demographic claims about Bernie Sanders supporters, studies about gender bias, and various economic research. The post includes both lighter observations (like different views of the White House) and serious academic papers about genetics, intelligence, and economic development. The format is typical of SSC links posts, with brief commentary on each link and occasional humorous asides. Shorter summary

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