On the Edge: The Art of Risking Everything
by Nate Silver · 12 Aug 2024 · 848pp · 227,015 words
the Noise: Why So Many Predictions Fail—But Some Don’t PENGUIN PRESS An imprint of Penguin Random House LLC penguinrandomhouse.com Copyright © 2024 by Nate Silver Penguin Random House supports copyright. Copyright fuels creativity, encourages diverse voices, promotes free speech, and creates a vibrant culture. Thank you for buying an authorized
…
page: courtesy of xkcd library of congress cataloging-in-publication data Names: Silver, Nate, 1978– author. Title: On the edge: the art of risking everything / Nate Silver. Description: New York: Penguin Press, 2024. | Includes bibliographical references and index. Identifiers: LCCN 2024011711 (print) | LCCN 2024011712 (ebook) | ISBN 9781594204128 (hardcover) | ISBN 9780593491638 (ebook) Subjects
…
percent). Trump won, of course, by sweeping several Rust Belt swing states. The reaction of many people in the political world to this forecast was: “Nate Silver is a fucking idiot.” But from my standpoint—and from the standpoint of people in the River, the landscape of skilled gamblers and like-minded
…
guy who only plays aces and kings—but I’m gradually aging into that demographic. And if my opponents know me as “statistician and author Nate Silver,” but don’t know my poker-playing background, they’ll usually assume my play is tight and conservative. People tend to read “statistician” as “calculating
…
. That reputation may be changing, though, because one of the poker hands I’m best known for is a bluff. Entitled “America’s Top Statistician Nate Silver Runs Epic Bluff in $10,000 Poker Tournament” on the PokerGO YouTube channel, the clip of that bluff has gotten tens of thousands of views
…
Gambler”: You’ve got to know when to Hold’em, know when to fold ’em Know when to walk away and know when to raise —Nate Silver, On the Edge As Doyle Brunson figured out fifty years ago, no-limit Texas Hold’em is a game of aggression. Modern poker solvers confirm
…
pseudonymous AI personality who was later outed[*6] by Forbes magazine. But roon told me that he first created his Twitter account to be a Nate Silver reply guy, “with the express intention of trolling your replies” about my election forecasts. (The internet works in mysterious ways.) A person like roon, with
…
worth your while. But I’m still going to claw out every inch of EV that I can if we meet at the poker table. —Nate Silver, Las Vegas, Nevada, April 10, 2024 Glossary: How to Speak Riverian This is a reasonably complete list of technical terms used in On the Edge
…
. GO TO NOTE REFERENCE IN TEXT estimate of Trump’s chances: Matthew Yglesias, “Why I Think Nate Silver’s Model Underrates Clinton’s Odds,” Vox, November 7, 2016, vox.com/policy-and-politics/2016/11/7/13550068/nate-silver-forecast-wrong. GO TO NOTE REFERENCE IN TEXT less than 1 percent: Josh Katz, “Who
…
: What We Know,” Time, December 14, 2022, time.com/6241262/sam-bankman-fried-political-donations. GO TO NOTE REFERENCE IN TEXT the Village’s claims: Nate Silver, “Twitter, Elon and the Indigo Blob,” Silver Bulletin (blog), October 1, 2023, natesilver.net/p/twitter-elon-and-the-indigo-blob. GO TO NOTE REFERENCE
…
TEXT aren’t any insurmountable barriers: See for instance the responses in this Twitter thread, which drew replies from various people with expertise in robotics. Nate Silver (@NateSilver538), “Weird question for my book. Given current tech, could a robot physically play in a poker game? It would need to e.g.:—Handle
…
1, 2020, quoteinvestigator.com/2020/03/01/underestimate. GO TO NOTE REFERENCE IN TEXT poker hands I’m best known for: “America’s Top Statistician Nate Silver Runs Epic Bluff in $10,000 Poker Tournament,” PokerGO, 2022, youtube.com/watch?v=9cVrlVzoh48. GO TO NOTE REFERENCE IN TEXT 1 million in chips
…
National?,” Analytics Blog (blog), Data Golf, April 8, 2019, datagolf.ca/does-experience-matter-at-augusta. GO TO NOTE REFERENCE IN TEXT the NBA playoffs: Nate Silver, “Why the Warriors and Cavs Are Still Big Favorites,” FiveThirtyEight, October 13, 2017, fivethirtyeight.com/features/why-the-warriors-and-cavs-are-still-big-favorites
…
REFERENCE IN TEXT goalie Ken Dryden: Coates, The Hour Between Dog and Wolf, 78. GO TO NOTE REFERENCE IN TEXT national news coverage: Ryan Glasspiegel, “Nate Silver Made Brutal All-in Call at WSOP: ‘F—King Poker,’ ” New York Post, July 13, 2023, nypost.com/2023/07/13
…
/nate-silver-made-brutal-all-in-call-at-wsop-f-king-poker. GO TO NOTE REFERENCE IN TEXT playing to survive: This was not the exact phrasing,
…
CCAdj),” FRED, Federal Reserve Bank of St. Louis, January 1, 1946), fred.stlouisfed.org/series/CP. GO TO NOTE REFERENCE IN TEXT fast food delivery: Nate Silver, “The McDonald’s Theory of Why Everyone Thinks the Economy Sucks,” Silver Bulletin (blog), October 1, 2023, natesilver.net/p/the-mcdonalds-theory-of-why
…
TO NOTE REFERENCE IN TEXT sworn to secrecy: Chamath Palihapitiya et al., “#AIS: FiveThirtyEight’s Nate Silver on How Gamblers Think,” All-In with Chamath, Jason, Sacks & Friedberg, 2022, podcasts.apple.com/ie/podcast/ais-fivethirtyeights-nate-silver-on-how-gamblers-think/id1502871393?i=1000564483582. GO TO NOTE REFERENCE IN TEXT aggressive compensation deal
…
3:1 in Air War,” Wesleyan Media Project, November 3, 2016, mediaproject.wesleyan.edu/nov-2016. GO TO NOTE REFERENCE IN TEXT Clinton email scandal: Nate Silver, “The Real Story of 2016,” FiveThirtyEight, January 19, 2017, fivethirtyeight.com/features/the-real-story-of-2016. GO TO NOTE REFERENCE IN TEXT amid sometimes
…
, 2022, sec. News, theguardian.com/news/2022/jul/10/uber-files-leak-reveals-global-lobbying-campaign. GO TO NOTE REFERENCE IN TEXT a political cudgel: Nate Silver, “Twitter, Elon and the Indigo Blob,” Silver Bulletin (blog), October 1, 2023, natesilver.net/p/twitter-elon-and-the-indigo-blob. GO TO NOTE REFERENCE
…
York Times, April 8, 2023, nytimes.com/2022/04/08/business/hiring-without-college-degree.html. GO TO NOTE REFERENCE IN TEXT congressional hearing featuring: Nate Silver, “Why Liberalism and Leftism Are Increasingly at Odds,” Silver Bulletin (blog), December 12, 2023, natesilver.net/p/why-liberalism-and-leftism-are-increasingly. GO TO
…
, June 23, 2023, cointelegraph.com/news/sequoia-partner-says-investing-ftx-was-right-move. GO TO NOTE REFERENCE IN TEXT told me that: Email to Nate Silver, January 8, 2024. GO TO NOTE REFERENCE IN TEXT by SBF nemesis: David Marsanic, “CZ and SBF Twitter Fight Reveals How They Became Rivals,” DailyCoin
…
an xkcd cartoon: Randall Munroe, “Duty Calls,” xkcd, xkcd.com/386. GO TO NOTE REFERENCE IN TEXT most popular stories: As of December 21, 2023; Nate Silver, “Fine, I’ll Run a Regression Analysis. But It Won’t Make You Happy,” Silver Bulletin (blog), October 1, 2023, natesilver.net/p/fine-ill
…
. Technology, nytimes.com/2023/03/31/technology/sam-altman-open-ai-chatgpt.html. GO TO NOTE REFERENCE IN TEXT that Altman knew: Per email to Nate Silver, January 19, 2024. GO TO NOTE REFERENCE IN TEXT taking a shot: Sam Altman (@sama), “i’ve been stopping myself from sending my EA tweetstorm
…
-model-works-and-how-it-fueled-the-tumult-around-ceo-sam-altmans-short-lived-ouster-218340. GO TO NOTE REFERENCE IN TEXT like fast food: Nate Silver, “The McDonald’s Theory of Why Everyone Thinks the Economy Sucks,” Silver Bulletin (blog), October 1, 2023, natesilver.net/p/the-mcdonalds-theory-of-why
…
S. Wood, The Radicalism of the American Revolution, Kindle ed. (New York: Vintage Books, 1993), 5. GO TO NOTE REFERENCE IN TEXT rule of law: Nate Silver, “Why Liberalism and Leftism Are Increasingly at Odds,” Silver Bulletin (blog), December 12, 2023, natesilver.net/p/why-liberalism-and-leftism-are-increasingly. GO TO
…
-highs.aspx. GO TO NOTE REFERENCE IN TEXT large language models: ChatGPT, Claude, and Google Bard. GO TO NOTE REFERENCE IN TEXT my Twitter followers: Nate Silver (@NateSilver588), “The most important inventions of the decade of the 1900s vs the decade of the 2000s. Pretty good evidence for secular stagnation,” Twitter, x
…
E F G H I J K L M N O P Q R S T U V W X Y Z About the Author Nate Silver is the founder of FiveThirtyEight and the New York Times bestselling author of The Signal and the Noise. He writes the Substack "Silver Bulletin." What
The Signal and the Noise: Why So Many Predictions Fail-But Some Don't
by Nate Silver · 31 Aug 2012 · 829pp · 186,976 words
Ltd, Registered Offices: 80 Strand, London WC2R 0RL, England First published in 2012 by The Penguin Press, a member of Penguin Group (USA) Inc. Copyright © Nate Silver, 2012 All rights reserved Illustration credits Figure 4-2: Courtesy of Dr. Tim Parker, University of Oxford Figure 7-1: From “1918 Influenza: The Mother
…
, University of Pennsylvania LIBRARY OF CONGRESS CATALOGING IN PUBLICATION DATA Silver, Nate. The signal and the noise : why most predictions fail but some don’t / Nate Silver. p. cm. Includes bibliographical references and index. ISBN 978-1-101-59595-4 1. Forecasting. 2. Forecasting—Methodology. 3. Forecasting—History. 4. Bayesian statistical decision
…
will start by buying the first beer for anybody on this list, and the first three for anybody who should have been, but isn’t. —Nate Silver Brooklyn, NY NOTES INTRODUCTION 1. The Industrial Revolution is variously described as starting anywhere from the mid-eighteenth to the early nineteenth centuries. I choose
…
: The Data Deluge Makes the Scientific Method Obsolete,” Wired magazine, June 23, 2008. http://www.wired.com/science/discoveries/magazine/16-07/pb_theory. 38. Nate Silver, “Models Based on ‘Fundamentals’ Have Failed at Predicting Presidential Elections,” FiveThirtyEight, New York Times, March 26, 2012. http://fivethirtyeight.blogs.nytimes.com/2012/03/26
…
passed, later statistical analyses suggested that members of Congress who had voted for the bailout were more likely to lose their seats. See for example: Nate Silver, “Health Care and Bailout Votes May Have Hurt Democrats,” FiveThirtyEight, New York Times, November 16, 2011. http://fivethirtyeight.blogs.nytimes.com/2010/11/16/health
…
/pricehistory/PriceHistory_GetData.cfm. 3. The McLaughlin Group transcript, Federal News Service; taped November 7, 2008. http://www.mclaughlin.com/transcript.htm?id=688. 4. Nate Silver, “Debunking the Bradley Effect,” Newsweek, October 20, 2008. http://www.thedailybeast.com/newsweek/2008/10/20/debunking-the-bradley-effect.html. 5. Academic studies of
…
of their votes. 25. “Election Results: House Big Board,” New York Times, November 2, 2010. http://elections.nytimes.com/2010/results/house/big-board. 26. Nate Silver, “A Warning on the Accuracy of Primary Polls,” FiveThirtyEight, New York Times, March 1, 2012. http://fivethirtyeight.blogs.nytimes.com/2012/03/01/a-warning
…
-on-the-accuracy-of-primary-polls/. 27. Nate Silver, “Bill Buckner Strikes Again,” FiveThirtyEight, New York Times; September 29, 2011. http://fivethirtyeight.blogs.nytimes.com/2011/09/29/bill-buckner-strikes-again/. 28. Otherwise
…
, you should have assigned the congressman a 100 percent chance of victory instead. 29. Matthew Dickinson, “Nate Silver Is Not a Political Scientist,” in Presidential Power: A Nonpartisan Analysis of Presidential Power, Blogs Dot Middlebury, November 1, 2010. http://blogs.middlebury.edu/presidentialpower
…
/2010/11/01/nate-silver-is-not-a-political-scientist/. 30. Sam Wang, “A Weakness in FiveThirtyEight.com,” Princeton Election Consortium, August 8, 2008. http://election.princeton.edu/2008/08
…
Polls So Predictable?” British Journal of Political Science 23, no. 4 (October 1993). http://www.rochester.edu/College/faculty/mperess/ada2007/Gelman_King.pdf. 35. Nate Silver, “Models Based on ‘Fundamentals’ Have Failed at Predicting Presidential Elections,” FiveThirtyEight, New York Times, March 26, 2012. 36. Between 1998 and 2008, the average poll
…
Harper, Online Etymology Dictionary. http://www.etymonline.com/index.php?term=objective. CHAPTER 3: ALL I CARE ABOUT IS W’S AND L’S 1. Nate Silver in Jonah Keri, et al., Baseball Between the Numbers: Why Everything You Know About the Game Is Wrong (New York: Basic Books, 2006). 2. Danny
…
Knobler, “The Opposite of a ‘Tools Guy,’ Pedroia’s Simply a Winner,” CBSSports.com, November 18, 2008. http://www.cbssports.com/mlb/story/11116048. 3. Nate Silver, “Lies, Damned Lies: PECOTA Takes on Prospects, Wrap-up,” BaseballProspectus.com, March 8, 2006. http://www.baseballprospectus.com/article.php?articleid=4841. 4. Law is
…
. Alan Schwarz, “The Great Debate,” Baseball America, January. 7, 2005. http://www.baseballamerica.com/today/features/050107debate.html. 20. Per interview with Billy Beane. 21. Nate Silver, “What Tim Geithner Can Learn from Baseball,” Esquire, March 11, 2009. http://www.esquire.com/features/data/mlb-player-salaries-0409. 22. As a result
…
methodology. The methods I describe herein apply to the 2003–2009 version of PECOTA specifically. 23. Nate Silver, “PECOTA Takes on the Field,” Baseball Prospectus, January 16, 2004. http://www.baseballprospectus.com/article.php?articleid=2515. 24. Nate Silver, “Lies, Damned Lies: Projection Reflection,” Baseball Prospectus, October 11, 2006. http://www.baseballprospectus.com/article
…
. 48. 2008 New Hampshire Democratic Primary polls via RealClearPolitics.com. http://www.realclearpolitics.com/epolls/2008/president/nh/new_hampshire_democratic_primary-194.html. 49. Nate Silver, “Rasmussen Polls Were Biased and Inaccurate; Quinnipiac, SurveyUSA Performed Strongly,” FiveThirtyEight, New York Times, November 4, 2010. http://fivethirtyeight.blogs.nytimes.com/2010/11/04
…
on the river, he would essentially be doing so as a bluff since he wouldn’t expect us to call with a weaker hand. 6. Nate Silver, “Sanity Check: 88 Hand” twoplustwo.com; May 14, 2012. http://forumserver.twoplustwo.com/56/medium-stakes-pl-nl/sanity-check-88-hand-1199549/. 7. G4mblers
…
-uigea-487/. 26. Branon Adams, “The Poker Economy,” Bluff Magazine, November, 2006. http://www.bluffmagazine.com/magazine/The-Poker-Economy-Brandon-Adams-584.htm. 27. Nate Silver, “After ‘Black Friday,’ American Poker Faces Cloudy Future,” FiveThirtyEight, New York Times, April 20, 2011. http://fivethirtyeight.blogs.nytimes.com/2011/04/20/after-black
…
. 18. “Super Tuesday 2012 on Intrade;” Intrade.com, March 8, 2012. http://www.intrade.com/v4/reports/historic/2012-03-07-super-tuesday-2012/. 19. Nate Silver, “Intrade Betting Is Suspicious,” FiveThirtyEight, September 24, 2008. http://www.fivethirtyeight.com/2008/09/intrade-betting-is-suspcious.html. 20
…
. Nate Silver, “Evidence of Irrationality at Intrade,” “Live Coverage: Alabama and Mississippi Primaries;” FiveThirtyEight, New York Times, March 13, 2012. http://fivethirtyeight.blogs.nytimes.com/2012/03/
…
. 30. “FAQ: Copenhagen Conference 2009;” CBCNews.ca, December 8, 2009. http://www.cbc.ca/news/world/story/2009/12/01/f-copenhagen-summit.html. 31. Nate Silver, “Despite Protests, Some Reason for Optimism in Copenhagen,” FiveThirtyEight.com, December 9, 2009. http://www.fivethirtyeight.com/2009/12/despite-protests-some-reasons-for.html
…
Security Theater,” Schneier on Security, November 13, 2009. http://www.schneier.com/blog/archives/2009/11/beyond_security.html. 76. Ibid., Kindle location 1035. 77. Nate Silver, “Crunching the Risk Numbers,” Wall Street Journal, January 8, 2010. http://Online.wsj.com/article/SB10001424052748703481004574646963713065116.html. 78. Russian Authorities: Terrorist Bombing at Moscow Airport
The Plague Year: America in the Time of Covid
by Lawrence Wright · 7 Jun 2021 · 391pp · 112,312 words
, 2020. widest margin: Alec Tyson and Shiva Maniam, “Behind Trump’s victory: Divisions by race, gender, education,” Pew Research Center, Nov. 9, 2016. “unbreakable lead”: Nate Silver, “The Comey Letter Probably Cost Clinton The Election,” FiveThirtyEight, May 3, 2016. opioid epidemic: Dean Reynolds, “Overdoses now leading cause of death of Americans under
The Rationalist's Guide to the Galaxy: Superintelligent AI and the Geeks Who Are Trying to Save Humanity's Future
by Tom Chivers · 12 Jun 2019 · 289pp · 92,714 words
this is to make lots of predictions and see how many come in. This method became particularly famous around the 2012 US presidential election, when Nate Silver, editor-in-chief of the website FiveThirtyEight.com, correctly predicted which way all 50 states would end up voting. He did it using exactly these
How I Built This: The Unexpected Paths to Success From the World's Most Inspiring Entrepreneurs
by Guy Raz · 14 Sep 2020 · 361pp · 107,461 words
customers. 13 Get Attention, Part 2: Engineering Word of Mouth In 2012, amidst an explosion of social networking platforms, smartphones, and big data, the statistician Nate Silver published a book titled The Signal and the Noise, about the difficulty of developing accurate predictions. Up until that point, “signal-to-noise ratio” was
Outnumbered: From Facebook and Google to Fake News and Filter-Bubbles – the Algorithms That Control Our Lives
by David Sumpter · 18 Jun 2018 · 276pp · 81,153 words
4: One Hundred Dimensions of You Chapter 5: Cambridge Hyperbolytica Chapter 6: Impossibly Unbiased Chapter 7: The Data Alchemists PART 2: INFLUENCING US Chapter 8: Nate Silver vs the Rest of Us Chapter 9: We ‘Also Liked’ the Internet Chapter 10: The Popularity Contest Chapter 11: Bubbling Up Chapter 12: Football Matters
…
achieved amazing results in a short time. It is people like Julia who can prevent us from being outnumbered. PART TWO Influencing Us CHAPTER EIGHT Nate Silver vs the Rest of Us Refresh, refresh, refresh. As voting for the 2016 US presidential election started, the political prediction website FiveThirtyEight received tens of
…
elections have become more and more common. There has been a shift from newspapers reporting opinion polls to online political sites, like FiveThirtyEight run by Nate Silver, and The Upshot at the New York Times, making probabilistic predictions of outcomes. As we have seen, algorithms work in terms of probabilities and not
…
predictions to binary: ‘yes’ or ‘no’, ‘Brexit’ or ‘remain’ and ‘Trump’ or ‘Clinton’. Our lazy minds like certainty. After the 2012 US presidential election, when Nate Silver’s model predicted all US states correctly, he was declared a genius in blogs and across social media. He was ‘the man who called it
…
in both their own model (the newspaper’s Upshot model had given Clinton a 91 per cent chance of winning) and the approach taken by Nate Silver and FiveThirtyEight. The newspaper was blaming statisticians for its own inability to account for uncertainty. For Silver, this was just one example of how the
…
at how FiveThirtyEight had evolved over the past 10 years, was that the site provides a powerful case study of the limits of mathematical models. Nate Silver had been propelled to a position of authority. He had accumulated financial resources (FiveThirtyEight is owned by ESPN) that had allowed him to build sophisticated
…
the maths and he understood the relationship between data and the real world. If anyone could create a good model of an election, it was Nate Silver. When it came to analysing our behaviour, the algorithms we have looked at up to now were, at best, on a par with humans. Julia
…
with music recommendations as good as those of our friends. I wondered whether the same limitations applied to the FiveThirtyEight model? Given the resources at Nate Silver’s disposal, FiveThirtyEight was the undisputed heavyweight champion of algorithmic prediction. I wanted to find out whether a human contender could take it on. Could
…
probability of victory for Trump.7 This compared with 28 per cent estimated by FiveThirtyEight. Unlike Carl Diggler, who called it 100 per cent Clinton, Nate Silver and the superforecasters hedged their bets, and rightly so. The superforecasters didn’t provide individual predictions for different US states, which made it difficult to
…
.4). This can be partly explained by PredictIt users exploiting FiveThirtyEight. Indeed, on the superforecasters’ forum discussions, the single most frequent source for information was Nate Silver’s website. However, the whole point of a prediction market is that it brings together different pieces of information, weighing them in proportion to their
…
done a bit of betting on football (purely for scientific research reasons, of course). There is an urban legend of the mathematical genius, maybe the Nate Silver of gambling, who has worked out the formula for beating the bookies. If only, the legend goes, you can find the tips that this person
…
a game. I thought it was fun to compare models to markets, to see which won. But I was falling into the same trap as Nate Silver. I was forgetting that the outcome of the US presidential election was crucial to the lives of so many people. Mona told me that the
…
at those two numbers for Clinton and Trump, and they are concluding that Clinton is going to win.’ We are outnumbered by statistical experts like Nate Silver because we believe that they have a better answer than we do. They don’t. They might be better than chimpanzees with darts and they
…
learning. Monika Scholz at the University of Chicago has recently created a model of how the worm uses probabilistic inference, similar to that used in Nate Silver’s model of election polls in Chapter 8, to decide when to move.11 The worm ‘polls’ its local environment to measure how much food
…
other words, a simple model accounting for age and priors is (for the Broward County data set) as accurate as the COMPAS model. Chapter 8 : Nate Silver vs the Rest of Us 1 www.yougov.co.uk/news/2017/06/09/the-day-after 2 www.nytimes.com/2016/11/01/us
Strength in Numbers: How Polls Work and Why We Need Them
by G. Elliott Morris · 11 Jul 2022 · 252pp · 71,176 words
poll of the 2014 Kansas Senate race from its website shortly after it was released. At the time, political blogger Harry Enten and FiveThirtyEight’s Nate Silver wondered whether the firm did so because they “got cold feet” when CNN and Fox News published polls with which Rasmussen’s was far out
…
. The forecasters have to bring in their own analysis to create such predictions. One reason for Pollster’s mixed success was the incredible popularity of Nate Silver, a rival polling aggregator and election forecaster. Silver not only took the polls and averaged them together, but he created probabilistic models to answer the
…
day job—running sports statistics for a company called Baseball Prospectus—and switched to election forecasting and political blogging full-time. SOME MODELS ARE USEFUL Nate Silver’s 2008 election forecasting model was the first of its kind to make its way into political journalism. His embrace of probabilistic statistics and sophisticated
…
investigation into her use of a private email server eleven days before the election—a move that may have sunk her candidacy.10 In comparison, Nate Silver’s forecast gave Trump a 29% chance of winning in 2016—higher than Jackson’s 2% or the New York Times’s 15%. The nearly
…
on the 2016 election, but it did not work as well in reality as we had hoped. Our forecasts were only slightly less biased than Nate Silver’s in red states, and we missed a surprising number of Trump’s voters in Florida and the Midwest, since the polls there were most
…
research, they will be drowned out by the significant volume of less accurate polls, making the output of the aggregate worse than its inputs. WHEN NATE SILVER STARTED FIVETHIRTYEIGHT.COM in 2008, the conventional wisdom surrounding polling aggregation was that it was nearly a sure bet on the outcome. We know now
…
in a face-to-face survey. In 2000, no major public poll was conducted online. By 2020, well over half of the surveys collected by Nate Silver’s staff at FiveThirtyEight, by then a major media outlet, were conducted over the internet. The motivation for switching methods is clear. The last twenty
…
misses in the history of polling. It nearly gave the Literary Digest a run for its money. But the aggregates in Wisconsin were also off; Nate Silver’s model had Biden up by eight points, when he only won by 0.6. So while cherry-picking by focusing on outliers like the
…
the polls go wrong, rather than providing pinpoint predictions of the election. The expectations of hyper-accuracy, largely caused by the media’s misunderstanding of Nate Silver’s successful forecasts in 2008 and 2012, as well as his championing of correct forecasts in binary terms, but to which I have contributed as
…
Premier Liberal Pollster,” New Republic, September 12, 2012, https://newrepublic.com/article/114682/ppp-polling-methodology-opaque-flawed#footnote-114682-$2 26. Harry Enten and Nate Silver, “Why Did a Rasmussen Reports Poll Disappear?,” FiveThirtyEight, October 24, 2014, https://fivethirtyeight.com/features/why-did-a-rasmussen-reports-poll-disappear/. 27. G. Elliott
…
Franklin, interview with the author, February 3, 2021. 5. Mark Blumenthal, interview with the author, February 3, 2021. 6. Blumenthal, interview, February 3, 2021. 7. Nate Silver, “General Election Projections, Beta Version,” Daily Kos, February 26, 2008, https://www.dailykos.com/stories/2008/2/26/464643/-General-Election-Projections-Beta-Version. 8
…
. Nate Silver (@natesilver538), “Today is the 10-year anniversary of http://FiveThirtyEight.com! Can’t believe I’ve been doing this for a decade now. Thanks to
…
Horse Race,” Slate, August 24, 2016, https://slate.com/news-and-politics/2016/08/there-is-no-clinton-trump-horce-race.html. 2. Ryan Grim, “Nate Silver Is Unskewing Polls—All of Them—in Trump’s Direction,” Huffington Post, November 5, 2016, https://www.huffpost.com/entry
…
/nate-silver-election-forecast_n_581e1c33e4b0d9ce6fbc6f7f. 3. Nolan McCaskill, “Trump Tells Wisconsin: Victory Was a Surprise,” Politico, December 13, 2016, https://slate.com/news-and-politics/2016/
Deep Work: Rules for Focused Success in a Distracted World
by Cal Newport · 5 Jan 2016
from one of the paper’s Pulitzer Prize–winning columnists; it was instead a blog run by a baseball stats geek turned election forecaster named Nate Silver. Less than a year later, ESPN and ABC News lured Silver away from the Times (which tried to retain him by promising a staff of
…
these groups in turn to better understand why they’re suddenly so valuable. The High-Skilled Workers Brynjolfsson and McAfee call the group personified by Nate Silver the “high-skilled” workers. Advances such as robotics and voice recognition are automating many low-skilled positions, but as these economists emphasize, “other technologies like
…
machines will thrive. Tyler Cowen summarizes this reality more bluntly: “The key question will be: are you good at working with intelligent machines or not?” Nate Silver, of course, with his comfort in feeding data into large databases, then siphoning it out into his mysterious Monte Carlo simulations, is the epitome of
…
, however, are consumer products, not serious tools: Most of the intelligent machines driving the Great Restructuring are significantly more complex to understand and master. Consider Nate Silver, our earlier example of someone who thrives by working well with complicated technology. If we dive deeper into his methodology, we discover that generating data
…
is a tricky question, one of many that you must understand and master to tease reasonable results out of real-world databases. Sticking with our Nate Silver case study, consider the other technology he relies on: Stata. This is a powerful tool, and definitely not something you can learn intuitively after some
…
and produce unambiguously valuable and concrete results. This ability to produce also applies to those looking to master intelligent machines. It wasn’t enough for Nate Silver to learn how to manipulate large data sets and run statistical analyses; he needed to then show that he could use this skill to tease
…
Up the Wrong Tree. September 18, 2013. http://www.bakadesuyo.com/2013/09/stay-focused/. Chapter 1 Information about Nate Silver’s election traffic on the New York Times website: Tracy, Marc. “Nate Silver Is a One-Man Traffic Machine for the Times.” New Republic, November 6, 2012. http://www.newrepublic.com/article/109714
…
/nate-silvers-fivethirtyeight-blog-drawing-massive-traffic-new-york-times. Information about Nate Silver’s ESPN/ABC News deal: Allen, Mike. “How ESPN and
…
ABC Landed Nate Silver.” Politico, July 22, 2013. http://www.politico.com/blogs/media/2013/07/how-espn
…
-and-abc-landed-nate-silver-168888.html. Examples of concerns regarding Silver’s methodology: Davis, Sean M
…
. “Is Nate Silver’s Value at Risk?” Daily Caller, November 1, 2012. http
…
://dailycaller.com/2012/11/01/is-nate-silvers-value-at-risk/. Marcus, Gary, and Ernest Davis. “What Nate Silver Gets Wrong.” The New Yorker, January 25, 2013. http://www.newyorker.com/online
…
/blogs/books/2013/01/what-nate-silver-gets-wrong.html. Information about David Heinemeier Hansson comes from the following
…
/speaking of Jaron Lanier. How to Become a Winner in the New Economy Details on Nate Silver’s tools: • Hickey, Walter. “How to Become Nate Silver in 9 Simple Steps.” Business Insider, November 14, 2012. http://www.businessinsider.com/how-nate-silver-and-fivethityeight-works-2012-11. • Silver, Nate. “IAmA Blogger for FiveThirtyEight at The New
Thinking in Bets
by Annie Duke · 6 Feb 2018 · 288pp · 81,253 words
see it coming was wrong. The same thing happened after Donald Trump won the presidency. There was a huge outcry about the polls being wrong. Nate Silver, the founder of FiveThirtyEight.com, drew a lot of that criticism. But he never said Clinton was a sure thing. Based on his aggregation and
…
entire tournament. I know viscerally how likely 60–40 and 70–30 favorites are to lose (and, of course, the opposite). When people complained that Nate Silver did his job poorly because he had Clinton favored, I thought, “Those people haven’t gotten all their chips in a pot with a pair
…
the possibilities, then take a stab at the probabilities. To start, we imagine the range of potential futures. This is also known as scenario planning. Nate Silver, who compiles and interprets data from the perspective of getting the best strategic use of it, frequently takes a scenario-planning approach. Instead of using
…
70%, according to FiveThirtyEight.com. When Donald Trump won, pollsters got the Pete Carroll treatment, maybe no one more than Nate Silver, founder of FiveThirtyEight.com and a thoughtful analyzer of polling data. (“Nate Silver was wrong.” “The pollsters missed it.” “Just like Brexit, the bookies blew it.” Etc.) The press spun this as
…
? Mistaking Odds for Wrong When the Underdog Wins,” Huffington Post, September 21, 2016, http://www.huffingtonpost.com/annie-duke/even-dershowitz-mistaking_b_12120592.html. Nate Silver and his website, FiveThirtyEight.com, bore the brunt of the criticism for pollsters and forecasters after the 2016 presidential election. Silver’s site updated, in
…
the election and had (depending on the date) the probability of a Clinton victory at approximately 60%–70%. If you Google (without the quotation marks) “Nate Silver got it wrong election,” 465,000 results come up. Politico’s November 9 headline was “How Did Everyone Get It So Wrong?,” http://www.politico
…
. Gizmodo.com jumped on Silver even before the election, in a November 4 article by Matt Novak titled “Nate Silver’s Very Very Wrong Predictions About Donald Trump Are Terrifying,” http://paleofuture.gizmodo.com/nate-silvers-very-very-wrong-predictions-about-donald-t-1788583912, including the declaration, “Silver has no f**king idea.” CHAPTER
…
Amazing Invasion,” TheDailyBeast.com, June 5, 2014, and, of course, Symonds’s book, Neptune: Allied Invasion of Europe and the D-Day Landings. Also, see Nate Silver, “14 Versions of Trump’s Presidency, from #MAGA to Impeachment,” FiveThirtyEight.com, February 3, 2017. Backcasting: working backward from a positive future: For stories describing
The Internet of Us: Knowing More and Understanding Less in the Age of Big Data
by Michael P. Lynch · 21 Mar 2016 · 230pp · 61,702 words
crowd has the same information and training as the relevant experts, it is not clear that they have wisdom to impart. As Leonhardt’s colleague Nate Silver noted during the final run-up to the 2012 election, such markets may contain more or less sophisticated participants, and the more sophisticated the average
…
individuals’ commitments. 8. Surowiecki, The Wisdom of Crowds, xii. 9. David Leonhardt, “When the Crowd Isn’t Wise,” New York Times, July 7, 2012. 10. Nate Silver, “The Virtues and Vices of Election Prediction Markets,” New York Times, October 24, 2012. 11. I was helped to see these points in discussions with
Simple Rules: How to Thrive in a Complex World
by Donald Sull and Kathleen M. Eisenhardt · 20 Apr 2015 · 294pp · 82,438 words
Trumpocalypse: Restoring American Democracy
by David Frum · 25 May 2020 · 319pp · 75,257 words
Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
by Eric Siegel · 19 Feb 2013 · 502pp · 107,657 words
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are
by Seth Stephens-Davidowitz · 8 May 2017 · 337pp · 86,320 words
Merchants of Truth: The Business of News and the Fight for Facts
by Jill Abramson · 5 Feb 2019 · 788pp · 223,004 words
Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World
by Bruce Schneier · 2 Mar 2015 · 598pp · 134,339 words
Fluke: Chance, Chaos, and Why Everything We Do Matters
by Brian Klaas · 23 Jan 2024 · 250pp · 96,870 words
The Age of Extraction: How Tech Platforms Conquered the Economy and Threaten Our Future Prosperity
by Tim Wu · 4 Nov 2025 · 246pp · 65,143 words
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
by Pedro Domingos · 21 Sep 2015 · 396pp · 117,149 words
Superforecasting: The Art and Science of Prediction
by Philip Tetlock and Dan Gardner · 14 Sep 2015 · 317pp · 100,414 words
Dataclysm: Who We Are (When We Think No One's Looking)
by Christian Rudder · 8 Sep 2014 · 366pp · 76,476 words
Radical Uncertainty: Decision-Making for an Unknowable Future
by Mervyn King and John Kay · 5 Mar 2020 · 807pp · 154,435 words
Shape: The Hidden Geometry of Information, Biology, Strategy, Democracy, and Everything Else
by Jordan Ellenberg · 14 May 2021 · 665pp · 159,350 words
The Art of Statistics: Learning From Data
by David Spiegelhalter · 14 Oct 2019 · 442pp · 94,734 words
Why We're Polarized
by Ezra Klein · 28 Jan 2020 · 412pp · 96,251 words
The Hype Machine: How Social Media Disrupts Our Elections, Our Economy, and Our Health--And How We Must Adapt
by Sinan Aral · 14 Sep 2020 · 475pp · 134,707 words
Hate Inc.: Why Today’s Media Makes Us Despise One Another
by Matt Taibbi · 7 Oct 2019 · 357pp · 99,456 words
Enlightenment Now: The Case for Reason, Science, Humanism, and Progress
by Steven Pinker · 13 Feb 2018 · 1,034pp · 241,773 words
Big Data: A Revolution That Will Transform How We Live, Work, and Think
by Viktor Mayer-Schonberger and Kenneth Cukier · 5 Mar 2013 · 304pp · 82,395 words
Future Crimes: Everything Is Connected, Everyone Is Vulnerable and What We Can Do About It
by Marc Goodman · 24 Feb 2015 · 677pp · 206,548 words
The Joys of Compounding: The Passionate Pursuit of Lifelong Learning, Revised and Updated
by Gautam Baid · 1 Jun 2020 · 1,239pp · 163,625 words
The Great Reset: How the Post-Crash Economy Will Change the Way We Live and Work
by Richard Florida · 22 Apr 2010 · 265pp · 74,941 words
Devil's Bargain: Steve Bannon, Donald Trump, and the Storming of the Presidency
by Joshua Green · 17 Jul 2017 · 296pp · 78,112 words
Misbehaving: The Making of Behavioral Economics
by Richard H. Thaler · 10 May 2015 · 500pp · 145,005 words
Data Wrangling With Python: Tips and Tools to Make Your Life Easier
by Jacqueline Kazil · 4 Feb 2016
The New Class War: Saving Democracy From the Metropolitan Elite
by Michael Lind · 20 Feb 2020
Twilight of the Elites: America After Meritocracy
by Chris Hayes · 11 Jun 2012 · 285pp · 86,174 words
The Revolt of the Public and the Crisis of Authority in the New Millennium
by Martin Gurri · 13 Nov 2018 · 379pp · 99,340 words
The Art of Statistics: How to Learn From Data
by David Spiegelhalter · 2 Sep 2019 · 404pp · 92,713 words
The Vanishing Neighbor: The Transformation of American Community
by Marc J. Dunkelman · 3 Aug 2014 · 327pp · 88,121 words
The Coming of Neo-Feudalism: A Warning to the Global Middle Class
by Joel Kotkin · 11 May 2020 · 393pp · 91,257 words
Doing Good Better: How Effective Altruism Can Help You Make a Difference
by William MacAskill · 27 Jul 2015 · 293pp · 81,183 words
Army of None: Autonomous Weapons and the Future of War
by Paul Scharre · 23 Apr 2018 · 590pp · 152,595 words
The Hacker and the State: Cyber Attacks and the New Normal of Geopolitics
by Ben Buchanan · 25 Feb 2020 · 443pp · 116,832 words
In Covid's Wake: How Our Politics Failed Us
by Stephen Macedo and Frances Lee · 10 Mar 2025 · 393pp · 146,371 words
The Meritocracy Trap: How America's Foundational Myth Feeds Inequality, Dismantles the Middle Class, and Devours the Elite
by Daniel Markovits · 14 Sep 2019 · 976pp · 235,576 words
Artificial Unintelligence: How Computers Misunderstand the World
by Meredith Broussard · 19 Apr 2018 · 245pp · 83,272 words
What Algorithms Want: Imagination in the Age of Computing
by Ed Finn · 10 Mar 2017 · 285pp · 86,853 words
The Behavioral Investor
by Daniel Crosby · 15 Feb 2018 · 249pp · 77,342 words
Pivot: The Only Move That Matters Is Your Next One
by Jenny Blake · 14 Jul 2016 · 292pp · 76,185 words
Whiteshift: Populism, Immigration and the Future of White Majorities
by Eric Kaufmann · 24 Oct 2018 · 691pp · 203,236 words
Robot Rules: Regulating Artificial Intelligence
by Jacob Turner · 29 Oct 2018 · 688pp · 147,571 words
The Ones We've Been Waiting For: How a New Generation of Leaders Will Transform America
by Charlotte Alter · 18 Feb 2020 · 504pp · 129,087 words
The Biggest Bluff: How I Learned to Pay Attention, Master Myself, and Win
by Maria Konnikova · 22 Jun 2020 · 377pp · 117,339 words
The Myth of Artificial Intelligence: Why Computers Can't Think the Way We Do
by Erik J. Larson · 5 Apr 2021
Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins
by Garry Kasparov · 1 May 2017 · 331pp · 104,366 words
Coders: The Making of a New Tribe and the Remaking of the World
by Clive Thompson · 26 Mar 2019 · 499pp · 144,278 words
Occupy
by Noam Chomsky · 2 Jan 1994 · 75pp · 22,220 words
Prediction Machines: The Simple Economics of Artificial Intelligence
by Ajay Agrawal, Joshua Gans and Avi Goldfarb · 16 Apr 2018 · 345pp · 75,660 words
Invisible Women
by Caroline Criado Perez · 12 Mar 2019 · 480pp · 119,407 words
Warnings
by Richard A. Clarke · 10 Apr 2017 · 428pp · 121,717 words
The Patient Will See You Now: The Future of Medicine Is in Your Hands
by Eric Topol · 6 Jan 2015 · 588pp · 131,025 words
Stuffocation
by James Wallman · 6 Dec 2013 · 296pp · 82,501 words
Uncharted: How to Map the Future
by Margaret Heffernan · 20 Feb 2020 · 335pp · 97,468 words
The Theft of a Decade: How the Baby Boomers Stole the Millennials' Economic Future
by Joseph C. Sternberg · 13 May 2019 · 336pp · 95,773 words
Whiplash: How to Survive Our Faster Future
by Joi Ito and Jeff Howe · 6 Dec 2016 · 254pp · 76,064 words
Artificial Whiteness
by Yarden Katz
More Everything Forever: AI Overlords, Space Empires, and Silicon Valley's Crusade to Control the Fate of Humanity
by Adam Becker · 14 Jun 2025 · 381pp · 119,533 words
How to Read Numbers: A Guide to Statistics in the News (And Knowing When to Trust Them)
by Tom Chivers and David Chivers · 18 Mar 2021 · 172pp · 51,837 words
Zero to One: Notes on Startups, or How to Build the Future
by Peter Thiel and Blake Masters · 15 Sep 2014 · 185pp · 43,609 words
Everydata: The Misinformation Hidden in the Little Data You Consume Every Day
by John H. Johnson · 27 Apr 2016 · 250pp · 64,011 words
Why Women Have Better Sex Under Socialism: And Other Arguments for Economic Independence
by Kristen R. Ghodsee · 20 Nov 2018 · 211pp · 57,759 words
The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant From Two Centuries of Controversy
by Sharon Bertsch McGrayne · 16 May 2011 · 561pp · 120,899 words
Bulletproof Problem Solving
by Charles Conn and Robert McLean · 6 Mar 2019
The New Urban Crisis: How Our Cities Are Increasing Inequality, Deepening Segregation, and Failing the Middle Class?and What We Can Do About It
by Richard Florida · 9 May 2016 · 356pp · 91,157 words
The Formula: How Algorithms Solve All Our Problems-And Create More
by Luke Dormehl · 4 Nov 2014 · 268pp · 75,850 words
Dark Money: The Hidden History of the Billionaires Behind the Rise of the Radical Right
by Jane Mayer · 19 Jan 2016 · 558pp · 168,179 words
The End of Power: From Boardrooms to Battlefields and Churches to States, Why Being in Charge Isn’t What It Used to Be
by Moises Naim · 5 Mar 2013 · 474pp · 120,801 words
How Democracies Die
by Steven Levitsky and Daniel Ziblatt · 16 Jan 2018 · 340pp · 81,110 words
Spies, Lies, and Algorithms: The History and Future of American Intelligence
by Amy B. Zegart · 6 Nov 2021
Escape From Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do About It
by Erica Thompson · 6 Dec 2022 · 250pp · 79,360 words
Cogs and Monsters: What Economics Is, and What It Should Be
by Diane Coyle · 11 Oct 2021 · 305pp · 75,697 words
Not Working: Where Have All the Good Jobs Gone?
by David G. Blanchflower · 12 Apr 2021 · 566pp · 160,453 words
Data Science for Business: What You Need to Know About Data Mining and Data-Analytic Thinking
by Foster Provost and Tom Fawcett · 30 Jun 2013 · 660pp · 141,595 words
Four Battlegrounds
by Paul Scharre · 18 Jan 2023
Mexico City Street Food: A Travel Guide for the Curious Eater. How to Safely Enjoy the Delicious Foods From the Street Vendors of Mexico City.
by Ron Upshaw · 24 Nov 2015 · 37pp · 10,904 words
The Age of Entitlement: America Since the Sixties
by Christopher Caldwell · 21 Jan 2020 · 450pp · 113,173 words
We Need New Stories: Challenging the Toxic Myths Behind Our Age of Discontent
by Nesrine Malik · 4 Sep 2019
Covid by Numbers
by David Spiegelhalter and Anthony Masters · 28 Oct 2021
Uncontrolled Spread: Why COVID-19 Crushed Us and How We Can Defeat the Next Pandemic
by Scott Gottlieb · 20 Sep 2021
The Dying Citizen: How Progressive Elites, Tribalism, and Globalization Are Destroying the Idea of America
by Victor Davis Hanson · 15 Nov 2021 · 458pp · 132,912 words
Can It Happen Here?: Authoritarianism in America
by Cass R. Sunstein · 6 Mar 2018 · 434pp · 117,327 words
Street Smart: The Rise of Cities and the Fall of Cars
by Samuel I. Schwartz · 17 Aug 2015 · 340pp · 92,904 words
Future Perfect: The Case for Progress in a Networked Age
by Steven Johnson · 14 Jul 2012 · 184pp · 53,625 words
Machine Learning for Hackers
by Drew Conway and John Myles White · 10 Feb 2012 · 451pp · 103,606 words
Winner-Take-All Politics: How Washington Made the Rich Richer-And Turned Its Back on the Middle Class
by Paul Pierson and Jacob S. Hacker · 14 Sep 2010 · 602pp · 120,848 words
Doing Data Science: Straight Talk From the Frontline
by Cathy O'Neil and Rachel Schutt · 8 Oct 2013 · 523pp · 112,185 words
A Hacker's Mind: How the Powerful Bend Society's Rules, and How to Bend Them Back
by Bruce Schneier · 7 Feb 2023 · 306pp · 82,909 words
The Wires of War: Technology and the Global Struggle for Power
by Jacob Helberg · 11 Oct 2021 · 521pp · 118,183 words
The Tyranny of Merit: What’s Become of the Common Good?
by Michael J. Sandel · 9 Sep 2020 · 493pp · 98,982 words
The New Class Conflict
by Joel Kotkin · 31 Aug 2014 · 362pp · 83,464 words
The Internet Is Not the Answer
by Andrew Keen · 5 Jan 2015 · 361pp · 81,068 words
Going Infinite: The Rise and Fall of a New Tycoon
by Michael Lewis · 2 Oct 2023 · 263pp · 92,618 words
Ten Lessons for a Post-Pandemic World
by Fareed Zakaria · 5 Oct 2020 · 289pp · 86,165 words
Team of Teams: New Rules of Engagement for a Complex World
by General Stanley McChrystal, Tantum Collins, David Silverman and Chris Fussell · 11 May 2015 · 409pp · 105,551 words
Designing Social Interfaces
by Christian Crumlish and Erin Malone · 30 Sep 2009 · 518pp · 49,555 words
The Elements of Choice: Why the Way We Decide Matters
by Eric J. Johnson · 12 Oct 2021 · 362pp · 103,087 words
Searches: Selfhood in the Digital Age
by Vauhini Vara · 8 Apr 2025 · 301pp · 105,209 words
Carjacked: The Culture of the Automobile and Its Effect on Our Lives
by Catherine Lutz and Anne Lutz Fernandez · 5 Jan 2010 · 269pp · 104,430 words
Liars and Outliers: How Security Holds Society Together
by Bruce Schneier · 14 Feb 2012 · 503pp · 131,064 words
No Is Not Enough: Resisting Trump’s Shock Politics and Winning the World We Need
by Naomi Klein · 12 Jun 2017 · 357pp · 94,852 words
The Impossible Climb: Alex Honnold, El Capitan, and the Climbing Life
by Mark Synnott · 5 Mar 2019 · 389pp · 131,688 words
The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies
by Erik Brynjolfsson and Andrew McAfee · 20 Jan 2014 · 339pp · 88,732 words
How to Run a Government: So That Citizens Benefit and Taxpayers Don't Go Crazy
by Michael Barber · 12 Mar 2015 · 350pp · 109,379 words
The Undoing Project: A Friendship That Changed Our Minds
by Michael Lewis · 6 Dec 2016 · 336pp · 113,519 words
Stress Test: Reflections on Financial Crises
by Timothy F. Geithner · 11 May 2014 · 593pp · 189,857 words
Hit Makers: The Science of Popularity in an Age of Distraction
by Derek Thompson · 7 Feb 2017 · 416pp · 108,370 words
The Attention Merchants: The Epic Scramble to Get Inside Our Heads
by Tim Wu · 14 May 2016 · 515pp · 143,055 words
The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences
by Rob Kitchin · 25 Aug 2014
Good to Go: What the Athlete in All of Us Can Learn From the Strange Science of Recovery
by Christie Aschwanden · 5 Feb 2019 · 324pp · 92,535 words
America's Bitter Pill: Money, Politics, Backroom Deals, and the Fight to Fix Our Broken Healthcare System
by Steven Brill · 5 Jan 2015 · 554pp · 167,247 words