Places: Y

Cities, neighborhoods, regions, and other geographic anchors. This section collects the Y slice of the category index.

Reference Index

Use the title to open the reference entry. Use the caret to expand a compact inline dossier with source context, issue trail, related pages, and outbound links.

Yemen

Yemen is a recurring place in the Astral Codex Ten archive, appearing 6 times across 6 issues between January 21, 2021 and October 01, 2024. The archive places it in contexts such as "isn't there still a war in Yemen?"; "civil wars continued in Nigeria, South Sudan, Yemen, Syria, Iraq, Afghanistan, Pakistan, Somalia, and Ukraine"; "and not, say, Yemen ?". It most often appears alongside Russia, Ukraine, Syria.

Article page
Yemen
Mention count
6
Issue count
6
First seen
January 21, 2021
Last seen
October 01, 2024
January 21, 2021 · Original source
With all due respect to these reporters, and with complete admission of my own bias, I reject this entire way of looking at things. If someone wants to report that I'm a 30-something psychiatrist who lives in Oakland, California, that's fine, I've had it in my About page for years. If some reporter wants to investigate and confirm, I have some suggestions for how they could use their time better - isn't there still a war in Yemen? - but I'm not going to complain too loudly. But I don't think whatever claim the public has on me includes a right to know my name if I don't want them to. I don't think the public needs to know the name of the cops who write cop blogs, or the deadnames of trans people, or the dating lives of sexy cyborgs. I'm not even sure the public needs to know the name of Satoshi Nakamoto. If he isn't harming anyone, let him have his anonymity! I would rather we get whatever pathologies come from people being able to invent Bitcoin scot-free, than get whatever pathologies come from anyone being allowed to dox anyone else if they can argue that person is "influential". Most people don't start out trying to be influential. They just have a Tumblr or a LiveJournal or something, and a few people read it, and then a few more people read it, and bam! - they're influential! If influence takes away your protection, then none of us are safe - not the random grad student with a Twitter account making fun of bad science, not the teenager with a sex Tumblr, not the aspiring fashionista with an Instagram. I've read lots of interesting discussion on how much power tech oligarchs should or shouldn't be allowed to have. But this is the first time I've seen someone suggest their powers should include a magic privacy-destroying gaze, where just by looking at someone they can transform them into a different kind of citizen with fewer rights. Is Paul Graham some weird kind of basilisk, such that anyone he stares at too long turns into fair game?
July 01, 2022 · Original source
The US keeps starting or engaging in wars, like in Libya, Afghanistan, and Iraq. I will briefly summarize the 3 major sections of the book and how they tackle the first five claims. Section 1: The Old World Order This section refutes the claim that outlawry of war wasn't actually a significant change for anyone at the time. To do so, it covers the history of the international laws of war as described by Hugo Grotius in a set of books titled The Law of War and Peace, including how he came to write it, what the laws were, and how they were used and understood. In this section, H&S work to fully immerse us in the laws of war before the Peace Pact, and the ways that people understood war as a result. I’ve already included a number of things about this up above, so I’ll just put in a few interesting notes here, and if you want more persuasion that people viewed war differently, I’d suggest you pick up the book. There is lots of historical evidence that attitudes toward war before the Peace Pact were not like attitudes toward war today, that people - lawyers, diplomats, sovereigns, and citizens - believed it to be normal and legal, and frequently justified. Conquest in response to debts or offenses was one of the primary motivators of war in the period ruled by the Old World Order (generally, from some time before 1625 when Grotius wrote the rules down to 1928, when the Peace Pact was signed), though H&S also document some of the weirder ones, like a King who declared that they had the right to wage war against another because the other King stole his wife. But because Grotius had declared that no one outside the belligerents could determine whose side was just without violating neutrality, the reasons for war were largely whatever Monarchs could get away, which ran the gamut. Perhaps because it was fashionable, perhaps to convince their citizenry of their rightness, Monarchs paid handsomely for famous thinkers to write manifestos explaining why they were going to war, and other Monarchs and the citizenry generally accepted these reasons. It would be like if Putin had called up Google co-founder Sergey Brin and asked him to write out why Russia had the right to conquer Ukraine, and then everyone else shrugged and decided, sure, that sounds reasonable. Heads of state enlisted esteemed writers and scholars as well as experienced lawyers to draft [war manifestos]. The English military and political leader Oliver Cromwell commissioned John Milton, the great epic poet, to write A Manifesto of the Lord Protector of the Commonwealth in 1655 when he ordered the invasion of the Spanish possessions in the Caribbean. In 1703, the Holy Roman Emperor Leopold I employed Gottfried Leibniz, the rationalist philosopher, co-inventor of calculus, and a trained lawyer, to compose the Manifesto for the Defense of the Rights of Charles III, which defended the empire’s involvement in the War of the Spanish Succession. Commodore Perry arrived in Japan in 1853 and returned for real the next year. Because they were so confused about how the laws of war were supposed to work, Japan proceeded to send Nishi Amane to the Netherlands to study the Law of War and Peace, and twenty years later, in 1875, Japan conquered Korea. Their logic for doing so was that they were afraid Europe or China would get there first. The world recognized their conquest at the time, though after WWII they were made to give it up. Korea was alluring prey for aggressive Western nations. As Nishi Amane [the scholar who brought the Grotian rules to Japan] would later explain, defending one’s borders “is like riding in a third-class train; at first there is adequate space but as more passengers enter there is no place for them to sit. The logic of necessity requires the people to plant both feet firmly and expand their elbows into any opening that may occur for, unless this is done, others will close the opening. (Chapter 6) Section 2: The Transformation Period Recall our list of counterclaims, #s 2 and 3. 2. Outlawry wasn't taken seriously at the time by the signatories - that it was just feel-good propaganda. 3. World War II proves that it failed, so it wasn't important. This section tells the story of how the Peace Pact came into existence, including how influential it was on the thinkers of the time. Throughout the 1930s and 40s, thinkers and diplomats attempted to turn the Peace Pact into practice, and then, when World War II demonstrated that they needed significantly more teeth to make the Peace Pact real, created the United Nations and other international institutions dedicated to supporting the Pact’s goals. At the time, they viewed World War II as a sign that they hadn’t gotten the right combination of institutions to make the Peace Pact succeed, not that it wasn’t important. This was a classic situation of needing More Dakka and they did, indeed, keep adding more until it worked. In an account composed more than a decade later, Jackson recounted that this view of the Pact was shared by the president and his inner circle. The Peace Pact, he reported, “left no vestige of legal right for [a state] to resort to a war of aggression. From the beginning, Roosevelt, Hull, Welles, Stimson and I had been in agreement that Hitler’s war . . . was an illegal one, and that other powers were under no obligation to remain indifferent. (Chapter 11) There is some counter-evidence in support of #2, from the side of the Japanese at least. Japan, for example, did not think that it had renounced the rules of the Old World Order on August 27, 1928. Its signing of the “No-War Pact,” as the Paris Peace Pact was known in Japan, was regarded as a diplomatic gesture, a noble proclamation affirming the aspiration of all civilized nations to seek peace. Indeed, Japanese officials considered it a sign of how far their nation had come that it was included among the fifteen countries at the grand ceremony in Paris. (Chapter 7) But at least on the Allies side, they had intended it seriously, and as World War II went on, that intention redoubled. Sumner Welles, Undersecretary of State during World War II, was assigned by Roosevelt to create a plan for peace after the war. What he and James Shotwell authored was effectively an outline of the United Nations, and they put the Peace Pact at the very center of it. Shotwell was far from subtle about his effort to treat the Pact as a starting point. He placed the Pact at the start of his preliminary draft. Article 1 repeated the Pact verbatim. Article 2 provided that “[t]he United Nations, in order to strengthen and safeguard the peace of nations as set forth in the General Pact for the Renunciation of war, agree to cooperate in the establishment of the necessary instrumentalities for its effective maintenance.” What followed was an outline of nearly every essential institutional component of the modern-day United Nations. Ten days later he circulated a more detailed draft, now entitled “Provisional Outline of International Organization.” (Chapter 8) It wasn't just the United Nations. NATO was built off of the Atlantic Charter, and it was also designed to reinforce the Peace Pact. This is why it's reasonably accurate to describe it as a defensive alliance. The [first draft of the Atlantic Charter] was a remarkable document. It began by restating the principles of the Stimson Doctrine—there would be no conquest; the two countries would “seek no aggrandizement, territorial or other.” Moreover, there would be “no territorial changes that do not accord with the freely expressed wishes of the peoples concerned.” The Charter looked ahead to a time “after the final destruction of the Nazi tyranny”—a remarkable statement for a neutral in the war—and declared the two states’ “hope to see established a peace which will afford to all nations the means of dwelling in safety within their own boundaries. (Chapter 8) This section brings to bear quotes from leaders at the time showing how important they considered the outlawry of war, how they viewed it as changing the world, but also how unprepared they were for how to react to countries choosing to ignore the Pact. Most importantly, they show how the Allies were strongly motivated to fight World War II specifically to preserve and expand the Pact, to make the world safe for peace. Unfortunately, then, as now, Russia/the Soviet Union did not quite live up to the ideals that the Allies generally advocated for. The Soviet Union took territory after World War II, the only one of the Allies to do so. The only ally to gain any significant territory after the war was the Soviet Union. More than twenty million of the nation’s citizens had died in the course of the war, and Stalin insisted on several territorial gains as the price of peace—many, but not all, of them in areas previously contested. … These concessions to Stalin were seen by the other Allied powers as regrettable deviations from accepted law, not precedents to be followed in the future. (Chapter 13) To be fair, we are talking about Josef Stalin, here. Who’s surprised? Section 3: The New World Order Recall our list of counterclaims, #s 4 and 5. 4. The world isn't more peaceful post outlawry. 5. Any increase in peace since World War II is due to democracies, nuclear weapons, or other reasons, and not the Peace Pact. H&S walk through the best academic evidence we have of whether the world is more peaceful today than it was in the period from 1816 (when our data collection starts being decent) to the Peace Pact. They then spend some time discussing why the evidence better supports the Peace Pact than other causes. In particular, H&S highlight that only since the Peace Pact have countries been denied territorial gains from their conquests. There's a lot of detail in there. Here's just a taste of it. A loose team of political scientists has assembled comprehensive data to help them study war. The resulting project, with the intentionally clinical name “Correlates of War,” hosts datasets on everything from “militarized interstate disputes” to “world religion data” to “bilateral trade.” Most relevant here, it includes extensive data on “territorial change”—a record of every single territorial exchange between states from 1816 to 2014, totaling over eight hundred entries. What do our 254 cases of territorial change tell us? They tell us something that is at once striking and surprising: Conquest, once common, has nearly disappeared. Even more unexpected, the switch point is that now familiar year when the world came together to outlaw war, 1928. From the time the data start in 1816 until the Peace Pact opened for signature in 1928, there was, on average, approximately one conquest every ten months (1.21 conquests per year). Put another way, the average state during this period had a 1.33 percent chance of being the victim of conquest in any given year. Those may seem like pretty good odds. They are not: A state with a 1.33 percent annual chance of conquest can expect to lose territory in a conquest once in an ordinary human lifetime. After 1948, the chance an average state would suffer a conquest fell from once in a lifetime to once or twice a millennium. (Chapter 13) The US wars in Afghanistan, Iraq, and Libya One disappointment I have is that H&S do not spend much time discussing the US wars of the last two decades. The book was published in 2017, so there’s really no excuse for this. Even counting them, their claim that wars since the Peace Pact have been fewer and less world-changing than before the Peace Pact still holds up, but since they don’t directly discuss the most notable wars of the last two decades, they leave a significant hole in their argument. I can imagine defenses that they would make, but they should have made them. They mostly refer to these conflicts either as not a conquest (since the US isn’t officially running those places now) or as a side effect of the Peace Pact in allowing failed states (See Addendum 1 for more on that) More recently, the United States invaded Iraq in 2003, toppled Sadaam Hussein, and installed the Coalition Provisional Authority to govern the country. But what’s most notable about these “nonconquests” is how ineffective and unstable they usually are. Exerting influence indirectly is inefficient and expensive. (Chapter 13) And in 2015 alone, high-fatality civil wars continued in Nigeria, South Sudan, Yemen, Syria, Iraq, Afghanistan, Pakistan, Somalia, and Ukraine. Why, if war has been outlawed, is there still so much conflict? The answer is that these conflicts are not prohibited by the Pact. Indeed, they are the predictable consequences of it … the prohibition on the use of force by one state against the territory of another has allowed two sources of conflict to simmer… within [states]. (Chapter 15) The broader intellectual history of war Reading The Internationalists led me to want to read a broader intellectual history of war. H&S include some comments that hint at it, for example describing the Principle of Distinction and other agreements made about how to behave during war. Fortunately for the civilians of Europe, the biblical model of war was finally repudiated. By the middle of the eighteenth century, European armies had come to recognize a “Principle of Distinction,” the doctrine central to modern humanitarian law, which distinguishes between soldiers and civilians and protects the latter from the former. The Principle of Distinction was the first curtailment of Grotius’s blanket immunity for those waging war. In the next century, it was followed by a flood of new legal regulations placing stricter controls on a soldier’s license to kill. International treaties protected the wounded and medical personnel (First Geneva Convention, 1864) prohibited the use of fragmenting, explosive, and incendiary small arms ammunition (St. Petersburg Declaration, 1874) banned explosives from balloons, asphyxiating gas, and dum-dum bullets (First Hague Convention, 1899) and proscribed pillage, the execution of surrendering soldiers and prisoners of war, and forcing civilians to swear an allegiance to a foreign power (Second Hague Convention, 1907). (Chapter 3) But the history of this and other pre-Peace Pact intellectual history of war is thin within the text, as the point H&S are chasing is specific to the Peace Pact's relevance in history, not the broader history of war. Some of my favorite books are books that tie together aspects of history across wide gulfs, which The Internationalists succeeds at. It’s rare and delightful to see how a piratical ship capture by the Dutch in the 16th century ties together with the opening of Japan, the US battles with Mexico, and finally, the creation of the United Nations. H&S’s perspective is that the Peace Pact marks a turning point, and one that should not be forgotten. It’s also clear that it marks a capstone on a long history of small changes that are also, themselves, interesting battles in the long-running war to make the world less intolerable. In the end, they identify four key changes in the intellectual landscape, with Lauterpacht’s fingers in nearly all of them. Neutrality no longer requires impartiality. States can help those they view as victims.
July 22, 2022 · Original source
For that matter, why are we up in arms about Ukraine and not, say, Yemen? There are clear reasons why - they just have nothing to do with democracy, sovereignty, war crimes, or human rights. I don't mean to say that nobody cares about those things. We all do, at least in a vague and abstract way. But that collective concern only becomes acute when the spectacle brings it into focus. The spectacle's gaze roves and lingers according to its whims. Without that constant reminder to care, awareness dissipates.
February 20, 2023 · Original source
I grade 1, 3, 4, 5, and 7 as true, and 2 and 6 as false. I don’t think my country predictions were especially good or bad, except that Russia and the UK have indeed been having a hard time. The Middle East as a whole did not get worse. Lebanon did have an economic collapse but has stayed relatively politically stable; the Arabian Peninsula is doing pretty well with a cease-fire still hanging on in Yemen.
September 13, 2024 · Original source
It is not possible to understand al-Qaeda's strategy without understanding its fixation on fulfilling the prophecies. Creating the preconditions for the arrival of the Mahdi also explained the group's later establishment of affiliates in Yemen, Syria, Iraq and the Maghreb, which along with Afghanistan are the lands of the Five Armies of Jihad prophesied to fight in the epic battles.
October 01, 2024 · Original source
The IMF says Argentina’s economy this year is among the worst in the world, exceeded only by places like Sudan and Yemen in the midst of civil wars. Even Ukraine and Russia are doing better! (also, what’s happening in Estonia?) According to classical economics, this kind of “shock therapy” is supposed to be temporarily bad, but long-run good. So although it probably doesn’t feel this way to Argentines, things are potentially still going according to plan. But economics doesn’t have a clear prediction for how bad things will get, or how long it will take before they are good again, and I haven’t seen any analysis of whether the current recession is consistent with predictions or whether people should start worrying.
Yugoslavia

Yugoslavia is a recurring place in the Astral Codex Ten archive, appearing 4 times across 4 issues between November 04, 2021 and February 22, 2023. The archive places it in contexts such as "the ceded land going primarily to ... Yugoslavia"; "Somalia and Yugoslavia are some of the least strategically important states in the 1990s"; "invading ... Yugoslavia". It most often appears alongside China, Congress, Europe.

Article page
Yugoslavia
Mention count
4
Issue count
4
First seen
November 04, 2021
Last seen
February 22, 2023
November 04, 2021 · Original source
But in their own minds, they are proud steppe nomads. And they keep the language of the steppe nomads alive, a strange non-Indo-European language with lots of SZ's and ZS's. In their own mind, they are an orphan people, Asiatic horselords surrounded on all sides by hostile Europeans who are probably snickering behind their back at their uncouth ways and unpronounceable letter combinations. Sometimes this contempt turned violent; Hungary has been conquered and occupied by Ottomans, Austrians, and Russians. The worst insult was the 1920 Treaty of Trianon, when the victorious Allied Powers stripped away 2/3s of Hungarian territory in retaliation for its WWI loss, the ceded land going primarily to Slovakia, Romania, and Yugoslavia. Hungarians have never forgotten this humiliation, but through the long Soviet occupation there wasn't much to do but let it fester.
June 24, 2022 · Original source
Yugoslavia Humanitarian Intervention (1995, 1999): UNSC sanctioned NATO’s intervention against ethnic Serbs’ massacre of ethnic Bosnians in Srebrenica and Sarajevo in 1995, but not the so-called “illegal but legitimate” 1999 bombing of Kosovo to stop the Serbs’ ethnic cleansing of Bosnians as NATO would have been vetoed by Russia and China.
The bombing of Librya (2011): a newly passed UNSC resolution allowed NATO to enforce a no-fly zone against al-Gadhaffi’s government “to protect civilians”, but did not sanction the no-fly zone intended for regime change, nor the subsequent airstrike that led to the capture and killling of al-Gadhaffi by rebels Indeed, the idea of some wars being “illegal” seems odd enough, but the fact that no country on earth violates the most fundamental tenets of international norms so flagrantly and often as the United States means that IR theorists cannot insist on the grand strategy of maintaining “rules based international order”. Hanania also dismisses other popular explanations of American grand strategy, in particular Chomsky’s argument that America’s interventions are a matter of great power competition and/or a struggle for resources. Somalia and Yugoslavia are some of the least strategically important states in the 1990s; the war in Iraq did not in any way increase American power but rather empowered Iran; and the removal of al-Gadhaffi made it clear to Kim Jong Un that any leader willing to dismantle their WMD program and ally themselves with the US in the war on terror were destined to be killed. As for intervention in oil-rich states, the US was not even willing or able to ensure American corporations benefited as Libya was already selling its oil on the open market (al-Gadhaffi’s removal only hurt production), and the largest Iraqi oil contracts under US occupation went to China and Russia (even if they went to the US, the costs of war ~$3 trillion was far from recoverable). It’s surprising how the longest-running meme of American invasion for oil is misplaced cynicism; US foreign policy elites aren’t even competent enough to secure oil for American exploitation. An additional evidence against American grand strategy is the pattern of troop deployments abroad: Practically unchanged throughout 1951, 1986, and 2019. It’s difficult to see what threat the US is protecting against in the United Kingdom, Italy, and Germany. The rise of China has not lead to increase in troop deployment in Japan or South Korea; the wars in the Greater Middle East has not resulted in the influx of the bulk of troops from the former Axis powers; the fall of the Soviet Union has not seen any withdrawal as promised to Gorbachev but rather expansion of troops right up to the border of the Russian Federation. Once again, Hanania clearly shows that status quo bias has been disguised as grand strategy. IR theorists have long debated what strategy the US should adopt when responding to potential challengers: realists are pessimistic in viewing great powers to be destined for war; liberal internationalists are optimistic in trusting the pacifying effects of trade and enlightened self interests. Either way, they assume states make rational decisions to attain long-term objectives, but the two ideologically hostile states of the Soviet Union and China show that presidents are too worried about short-term political prospects to stop American business and technology from engaging with and empowering rivals. If there is no grand strategy against the most powerful geopolitical rivals, it’s unlikely any exists for lesser adversaries. 4. The Atrocity Of American Sanctions Sanctions were introduced by the Trading with the Enemy Act of 1917, and the International Emergency Economic Powers Act (IEEPA) in 1977 gave the president the right to sign an executive order to declare a national emergency to prohibit any transaction between anyone under the jurisdiction of the United States and the foreign country or its nationals. This means most sanctions are decided on and applied within the executive branch with little input from Congress or the broader public. The three main concentrated interests do not oppose sanctions (the only exception being the unprecedented lobbying campaign from American businesses to open up trade with China). The national security bureaucracy doesn’t stand to gain or lose from trading with foreign states, nor do government contractors (most rogue states' economies are miniscule compared to China’s). Foreign governments that are candidates for sanctions also can’t oppose them — Kim Jong Un cannot fund Washington think tanks; Israel and Saudi Arabia can fund a maximum pressure campaign against Iran as even meetings with Iranian state officials bring accusations of illegality. In theory, sanctions work by: Hurting the economy
July 01, 2022 · Original source
The Axis powers stood for the Old World Order. Germany, Japan, and Italy had each rejected the principles of the Peace Pact—Japan by invading Manchuria and continuing into China, French Indochina, British Malaya, Indonesia, and Singapore; Italy by invading Ethiopia, Greece, Yugoslavia, and North Africa; and Germany by seeking to gain control of nearly all of Europe. Each had a reason to resent the Allies and their efforts to outlaw war. The Axis powers had largely missed out on the colonial land grab. Japan only began to participate in international affairs in the 1860s, and it was more than a generation before it was prepared to project military force outside its own borders, too late to successfully participate in the empire-building scramble. Both Germany and Italy finally achieved unification in the same year—1871. They joined the land grab soon after, but were never as successful as France, Spain, Portugal, Britain, and the Netherlands, which built extensive empires. Without the authority to wage war and conquer new territory, the Axis powers saw little possibility of ever achieving equality. (Chapter 8)
February 22, 2023 · Original source
She reminded me that yesterday she was unusually grumpy, so much so that she had apologized to me for it and tried to come up with explanations - and then later yesterday she had her period. Meanwhile, Bures’ counterargument is - what? That it sounds kind of sexist to accuse female hormones of making women overly emotional? Hasn’t he ever heard of stereotype accuracy? That people asked their doctors to be treated for it more often after they knew it was considered a medical condition, and was treatable? That seems to have a much simpler explanation! That there are no biomarkers? There are inconsistent biomarkers that work sometimes but not other times, just like for schizophrenia, epilepsy, cancer, and half the other conditions in medicine. That these conditions don’t occur in most cultures? From here: A World Health Organization (WHO) study on menstruation (1981) surveyed 5,322 women from Egypt, India, Indonesia, Jamaica, Korea, Mexico, Pakistan, Philippines, United Kingdom and Yugoslavia. . . The majority of women in all cultures report some premenstrual physical discomfort in addition to negative mood changes, however fewer women report mood change than physical change. The main cross-cultural difference was in the prevalence of specific symptoms. Immigrants to the United States report more PMDD the longer they’re here? True (source), but it’s a matter of degree, and seems more true of the PMDD diagnosis than specific symptoms. The diagnosis requires impairment, which is subjective. I imagine an immigrant from a culture where mental disorders are unthinkable - something that only happens to a few psychos in asylums - and where you work 12-hour days in sweatshops. Someone asks her “hey, has this mental disorder ever prevented you from working?”, and she says no, because obviously you grit your teeth and work through the symptoms. And I imagine an American seeing the same question and saying “Yeah, I did decide I had to take a couple of sick days because of that.” I’m not saying this definitely happened, just that it’s a possibility. Meanwhile, this entire area of study is a mess. The “PMDD is culture-bound” hypothesis was originally invented by feminist scholars trying to argue that the diagnosis was a sexist attempt to pathologize women as overemotional and untrustworthy (this is also where Bures got his “it’s just hysteria by a different name” idea). See for example here and here, the second of which says that “the feminist argument is that if women are angry/distressed, it is for good reason, not due to pathology”. Bures somehow swallowed and repeated this, and then some feminists on Vox wrote an article attacking him as a “male writer” who was denying women’s lived experiences of PMS and stereotyping them as stupid and gullible. Neither side has an argument beyond “I can think of a reason it would be sexist for people to disagree with me” and neither side will acknowledge that the other side is also feminists basing their argument entirely on how it would be sexist to disagree with them. Everything in every area of social science has been like this for at least the past twenty years. But also, this highlights the difficulties with declaring something culture-bound. How do you know if something’s culture-bound, vs. people don’t notice it or mention it if they don’t have a name for it? How do you know if something’s culture-bound vs. some cultures consider it too embarrassing or taboo to think about? How do you know if something’s culture-bound, vs. people will go to doctors about it if they think doctors can treat it, and otherwise they won’t? I’ll discuss these questions more later, but I want to finish Bures’ argument. He gestures at a few other possible candidates for culture-bound mental disorders, including repetitive strain injury and chronic pain. But he quickly moves on to a long section that tries to establish the reality of “voodoo death”, ie the thing where if you believe you are going to die hard enough, you actually die. I think most arguments for voodoo death are pretty bad, and I didn’t find Bures’ convincing. But bonus points for referencing a study claiming that chronically stressed people only die at higher rates if they believe chronic stress is bad for them, and if not then they don’t (this is not really how I interpret the abstract, but I haven’t looked closely) Is it weird to stay on the crazy train long enough to agree that cultural effects are strong enough to make you think witches are stealing your penis, and then get off it once people start talking about voodoo death? I think no - these are very different situations. Believing in koro can make you hallucinate that your penis is shrunken or gone, but no belief, however strong, can (directly) remove your penis itself. Culture → beliefs is fine; culture → reality is a step I’m not willing to take. V. Since I rejected Bures’ PMDD example, I want to digress to what I think is a stronger argument: anorexia, which Ethan Watters discusses in his book Crazy Like Us. Anorexia was mostly unknown in the West, until becoming “trendy” in the mid-1800s. During that period, doctors reported high prevalence of anorexia among “hysterics”, but the fad ended after about ten or twenty years, and it went back to being basically unknown. In 1983, famous singer Karen Carpenter died of anorexia, thrusting it back into the national news, and suddenly lots of people (in the West) were anorexic again. Meanwhile, foreign doctors who trained in the West went back to their home countries, searched far and wide for it, and found almost nothing. The few cases they did see didn’t resemble the typical Western version at all - for example, one Hong Kong psychiatrist was able to find a woman who refused to eat out of grief when a boyfriend left her, but she didn’t think she was fat, or feel any cultural pressure to be thinner. The absence of anorexia abroad was especially surprising since anorexics tend to end up in the hospital with extremely noticeable malnutrition that doesn’t really mimic anything else. It’s not really possible to hide severe anorexia the way you can hide severe depression. In 1994, Hong Kong got its own Karen Carpenter - a young girl died of anorexia, setting off a national panic and many public awareness campaigns. Near-instantly, anorexia rates shot up to the same level as the West, with the appropriate number of people presenting to hospital ERs with severe malnutrition. This story raises a lot of questions. For example: where did the first anorexics (Karen Carpenter, the girl in Hong Kong) come from? Why anorexia and not something else? And how come knowing about anorexia makes it spread so quickly? VI. Past this point I’m using this review to discuss my own thoughts, not Bures’ or Watters’. “Culture-bound” is less all-or-nothing than you’d think. Look hard enough, and you’ll find people having “culture-bound syndromes” from cultures they’ve never heard of. Ntouros et al in Thessaloniki describe “koro-like symptoms in two Greek men”. One, a paranoid schizophrenic: . . . reported for the first time a sensation that his penis retracts into the abdomen and a fear that it will subsequently be lost. This would be accompanied by anxiety and sadness pertaining only to the loss itself. He would then proceed to search manually for his penis and masturbate. No pleasure was gained by masturbation, but the anxiety would be lifted. Romero et al describe a case of koro in "an intellectually disabled Caucasian patient" in Spain. They write that "although it is widely regarded as an epidemic in South-east Asia, there are some isolated cases in other cultures as well." Wilson and Agin describe a 29 year old white male from New York, "not exposed to the Chinese culture”, who went to the doctor with a five month history of worrying that his genitals were retracting into his body: Sometimes, he would manually reaffirm the presence of his genitals. Occasionally he would, in private, remove his garments and visually confirm the presence of his genitals. On one occasion, while taking the train home from work, he experienced an acute exacerbation of these symptoms. His pain increased from 3/10 to 10/10, and he felt as if his genitals had fully retracted within his belly. Upon reaching his hometown, he immediately went to the local hospital emergency room where examinations for inguinal hernia, urinary tract infection, proctitis, prostatitis, and testicular disorders proved negative. He improved significantly on the anti-anxiety medication desipramine. Chowdhury surveys the evidence on koro and divides the condition into two types: culture-bound and non-culture-bound. The culture-bound type usually goes in large epidemics, hundreds to thousands of people, in koro-believing parts of Africa and Asia; the victims were usually previously psychologically normal. The non-culture-bound type hits a few scattered individuals, is not contagious, and can happen anywhere - Greece, Spain, America. Some patients are psychologically normal, but there are a disproportionate number of schizophrenics, drug users, brain damage victims, and other previously-mentally-ill people. Other culture-bound illnesses seem to be like this too. Running amok has been big in Malaysia for 300 years. The Columbine shooters seem to have been autocthonous American cases, equivalent to that one New Yorker who got koro - before their fame inscribed amok onto the US collective consciousness the same way Karen Carpenter’s inscribed anorexia. Japan’s jikoshu-kyofu affects occasional victims in the US under the name olfactory reference syndrome. Watters admits there were a tiny handful of unusual anorexia cases in Hong Kong before Westernization. And even that Indian there’s-a-lizard-in-my-skin condition differs only in species from delusional parasitosis. Delusional parasitosis - the false belief that you are infested with parasites and can feel them crawling in your skin - is actually an especially interesting case. Two groups are disproportionately represented among patients: menopausal women and cocaine addicts. Relatedly, two biological conditions that can sometimes cause weird skin sensations that feel like crawling insects are . . . menopause and cocaine use. So there’s no mystery here. But, also represented among delusional parasitosis patients are the roommates and family members of these people. The index case hallucinates insects for a well-understood biological reason; their close contacts hallucinate insects through social contagion. So a unified theory of these conditions might be: Some people have the condition for a normal biological or psychiatric reason. For example, someone might believe a lizard is crawling under their skin because they use cocaine, which causes hallucinatory crawling sensations. Or someone might believe their penis is missing because they’re schizophrenic, which makes them naturally hallucination-prone.
Yunnan

Yunnan is a recurring place in the Astral Codex Ten archive, appearing 4 times across 4 issues between June 17, 2021 and April 09, 2024. The archive places it in contexts such as "The plague probably existed in say Yunnan, China"; "Yunnan province and Laos, which are more than a thousand kilometers away from Wuhan"; "even further than Yunnan". It most often appears alongside China, BANAL-52, COVID-19.

Article page
Yunnan
Mention count
4
Issue count
4
First seen
June 17, 2021
Last seen
April 09, 2024
June 17, 2021 · Original source
Mongol caravans introduced the plague to rats and then spread the plague rats across the world. The plague probably existed in say Yunnan, China where the locals had developed a complex set of myths and traditions to say, not eat rats. When the Mongols came they trapped the rats, got the plague and spread it in China. China’s population decreased from around 123 million in 1200 to around 65 million in 1331. Then the Mongols brought the rats to Europe 1346.
July 30, 2022 · Original source
Photograph of the famous Latané and Darley experiment, cerca 1968. So, what could those participants have been thinking? Maybe something like: Hmm, why’s the room filling up with smoke? Is this a problem? *looks around the room* Well nobody else seems to care, so I guess not. Looking back at the early stages of the COVID-19 pandemic, I think maybe this is why so many of us didn’t think twice about the location of the initial outbreak. Hmm, is it kinda suspicious that this virus broke out near a major virology institute that works on bat coronaviruses? Should we maybe look into that? *looks around* Well nobody else seems to think so, so I guess not. I can’t speak for everyone else, but this was at least my mindset. I had vaguely heard something about how there was a virology research institute close to where the pandemic broke out, and that some conspiracy theorists were claiming it was the source of the virus. I looked around and noticed that nobody was really taking this idea seriously, so I figured I didn’t need to take it seriously either. Also, I was thinking something like: Eh, probably every major city has labs and research institutes doing this kind of research. And I’ll bet they purposely built the virology institute close to where these viruses occur in nature, to give them easy access for sampling. Well, it turns out both of these things are wrong. The type of research conducted at the Wuhan Institute of Virology (WIV) is pretty rare and specialized. It includes things like creation of chimeric coronaviruses [1, 2], infecting humanized mice with bat coronaviruses, and other types of gain of function research, which Chan and Ridley devote a chapter to. The WIV is one of only a few institutions in the world doing this type of research. It’s not the case, as I had assumed, that every major university has a couple labs doing similar work. So it does seem like a pretty remarkable coincidence that the outbreak happened in Wuhan. But maybe they purposely built the Wuhan Institute of Virology close to where these viruses are found in nature? Well, this also turns out to be wrong. The areas where viruses most similar to SARS-CoV-2 are found in nature are Yunnan province and Laos, which are more than a thousand kilometers away from Wuhan. The authors put this distance in perspective by noting that it’s more than the distance between Orlando and NYC. Image source: https://www.bloomberg.com/news/features/2020-12-30/china-is-making-it-harder-to-solve-the-mystery-of-how-covid-began If SARS-CoV-2 originated in an animal somewhere around the Yunnan / Laos area, how did it make it all the way to Wuhan without leaving a trail along the way? 4. The story of RaTG13 Although I enjoyed the book, I do have one pretty major criticism. The authors repeatedly make the claim that a virus called RaTG13, which was being studied at the WIV before the pandemic, is the closest known genetic match to SARS-CoV-2. But this claim is outdated and no longer correct. In September 2021 researchers identified a virus called BANAL-52 in Laos that’s a 96.8% match to SARS-CoV-2, closer than RaTG13’s 96.2% match. (Important note: a 96.8% match is still a long way off in genomic space, and does not imply that this is the same virus as SARS-CoV-2, or even necessarily a progenitor.) At first I thought maybe the authors didn’t mention BANAL-52 because it was discovered after the book was published, but this isn’t the case – Viral was published November 16, 2021, nearly two months after the discovery of BANAL-52 was published. Although I’m writing an overall-positive review here, I don’t want to go easy on the book where serious criticism is warranted. It’s completely unacceptable that BANAL-52 wasn’t mentioned. Even if it would have been inconvenient from a publishing standpoint, the authors should have rewritten the RaTG13 chapter, or at least included an addendum about the discovery of BANAL-52. With that being said, I think the story of RaTG13 is still interesting and important, so I’ll give a quick summary here. At the start of the pandemic in 2020, SARS-CoV-2 was quickly sequenced, and the full genome sequence was published by Dr. Shi Zhengli’s team at the WIV. In this paper, they also briefly mentioned that the genome was a 96.2% match with another bat coronavirus called RaTG13 – the closest known match at the time. Oddly, the mention of RaTG13 did not include any reference, footnote, or link to any previously published sequence. Although the WIV didn’t provide details on this mysterious RaTG13 virus, a group of internet volunteers, including both amateurs as well as professional scientists working in their free time, began to investigate. This loose collection of open-source researchers, called DRASTIC, uncovered a medical thesis describing an outbreak of a mysterious disease in 2012. Six men who had been working in a bat-infested mine in Mojiang County, China, fell ill and were admitted to a hospital with symptoms including dry coughs, shortness of breath, fevers, muscle aches, headaches, and fatigue. Three of the men eventually died of this mysterious illness. In the years following this incident, teams of researchers (including a team led by Dr. Shi Zhengli of the WIV) were sent to investigate the cause of this illness and collect samples from the Mojiang mine. This sampling led to the discovery of a novel SARS-like coronavirus in 2013, and a part of its genomic sequence was published under the name BtCoV/4991 in 2016. The DRASTIC researchers discovered that RaTG13 was genetically identical to the BtCoV/4991 sequence from the Mojiang mine – it was the same virus, and had just been renamed for some reason, without any public record of the change. They also discovered that at least eight other closely related coronaviruses were also sampled from this mine and brought to the WIV. Although unhelpful throughout the investigation, the WIV eventually verified these facts when pressed on them, and an addendum was added to the original paper confirming DRASTIC’s account of the origin of RaTG13. So what should we make of this? Well, as I mentioned before, RaTG13 is no longer the closest known genetic match to SARS-CoV-2, so maybe the whole story is less important as it pertains to the origin of the pandemic. But the discovery of BANAL-52 doesn’t really resolve things either [2]. Laos is very far away from Wuhan (actually even further than Yunnan), so we’re left with the same question as before – how did SARS-CoV-2 make it all the way to Wuhan from such a distant natural reservoir without leaving a trail along the way? 5. Lack of institutional transparency and competence A lot of the book is devoted to criticizing the Chinese government’s lack of transparency during the pandemic. Some brief examples: In the early days of the initial outbreak in Wuhan, hundreds of people were investigated and punished for the crime of “spreading rumors”. This included whistleblowing doctors who attempted to warn others [3] about the spread of the disease and its human-to-human transmission, which was being denied by the Chinese government at the time.
Image source: https://www.bloomberg.com/news/features/2020-12-30/china-is-making-it-harder-to-solve-the-mystery-of-how-covid-began If SARS-CoV-2 originated in an animal somewhere around the Yunnan / Laos area, how did it make it all the way to Wuhan without leaving a trail along the way? 4. The story of RaTG13 Although I enjoyed the book, I do have one pretty major criticism. The authors repeatedly make the claim that a virus called RaTG13, which was being studied at the WIV before the pandemic, is the closest known genetic match to SARS-CoV-2. But this claim is outdated and no longer correct. In September 2021 researchers identified a virus called BANAL-52 in Laos that’s a 96.8% match to SARS-CoV-2, closer than RaTG13’s 96.2% match. (Important note: a 96.8% match is still a long way off in genomic space, and does not imply that this is the same virus as SARS-CoV-2, or even necessarily a progenitor.) At first I thought maybe the authors didn’t mention BANAL-52 because it was discovered after the book was published, but this isn’t the case – Viral was published November 16, 2021, nearly two months after the discovery of BANAL-52 was published. Although I’m writing an overall-positive review here, I don’t want to go easy on the book where serious criticism is warranted. It’s completely unacceptable that BANAL-52 wasn’t mentioned. Even if it would have been inconvenient from a publishing standpoint, the authors should have rewritten the RaTG13 chapter, or at least included an addendum about the discovery of BANAL-52. With that being said, I think the story of RaTG13 is still interesting and important, so I’ll give a quick summary here. At the start of the pandemic in 2020, SARS-CoV-2 was quickly sequenced, and the full genome sequence was published by Dr. Shi Zhengli’s team at the WIV. In this paper, they also briefly mentioned that the genome was a 96.2% match with another bat coronavirus called RaTG13 – the closest known match at the time. Oddly, the mention of RaTG13 did not include any reference, footnote, or link to any previously published sequence. Although the WIV didn’t provide details on this mysterious RaTG13 virus, a group of internet volunteers, including both amateurs as well as professional scientists working in their free time, began to investigate. This loose collection of open-source researchers, called DRASTIC, uncovered a medical thesis describing an outbreak of a mysterious disease in 2012. Six men who had been working in a bat-infested mine in Mojiang County, China, fell ill and were admitted to a hospital with symptoms including dry coughs, shortness of breath, fevers, muscle aches, headaches, and fatigue. Three of the men eventually died of this mysterious illness. In the years following this incident, teams of researchers (including a team led by Dr. Shi Zhengli of the WIV) were sent to investigate the cause of this illness and collect samples from the Mojiang mine. This sampling led to the discovery of a novel SARS-like coronavirus in 2013, and a part of its genomic sequence was published under the name BtCoV/4991 in 2016. The DRASTIC researchers discovered that RaTG13 was genetically identical to the BtCoV/4991 sequence from the Mojiang mine – it was the same virus, and had just been renamed for some reason, without any public record of the change. They also discovered that at least eight other closely related coronaviruses were also sampled from this mine and brought to the WIV. Although unhelpful throughout the investigation, the WIV eventually verified these facts when pressed on them, and an addendum was added to the original paper confirming DRASTIC’s account of the origin of RaTG13. So what should we make of this? Well, as I mentioned before, RaTG13 is no longer the closest known genetic match to SARS-CoV-2, so maybe the whole story is less important as it pertains to the origin of the pandemic. But the discovery of BANAL-52 doesn’t really resolve things either [2]. Laos is very far away from Wuhan (actually even further than Yunnan), so we’re left with the same question as before – how did SARS-CoV-2 make it all the way to Wuhan from such a distant natural reservoir without leaving a trail along the way? 5. Lack of institutional transparency and competence A lot of the book is devoted to criticizing the Chinese government’s lack of transparency during the pandemic. Some brief examples: In the early days of the initial outbreak in Wuhan, hundreds of people were investigated and punished for the crime of “spreading rumors”. This included whistleblowing doctors who attempted to warn others [3] about the spread of the disease and its human-to-human transmission, which was being denied by the Chinese government at the time.
March 28, 2024 · Original source
Lineage A (left) was used by the Minoan Cretans, but has never been deciphered. Lineage B (right) was used by the Mycaeneans for lists of palace goods. This matches Saar’s story above. The lab leaked to somewhere else in Wuhan, not the wet market. The virus spread undetected in the population for a while. During this time, it mutated to Lineage B. Then one of the people with Lineage B went to the wet market and started a superspreader event. The authorities sampled the patients, found Lineage B, then started looking elsewhere. Later they detected some of the earlier Lineage A cases. The market is unlikely to be the origin of the pandemic, because the original Lineage A strain wasn’t found there. Peter: Although Lineage A is evolutionarily older, Lineage B started spreading in humans first. We know this because Lineage B is more common. Throughout the early pandemic, until the D614G variant drove all other strains extinct, a consistent 2/3 of the cases were B, compared to 1/3 A. Both strains spread at the same rate, so the best explanation is that B started earlier than A. Since COVID doubles every 3-4 days, probably Lineage B started 3-4 days earlier than Lineage A, which explains why it’s always been twice as many cases. But also, Lineage B also has more internal genetic diversity than Lineage A. In general, older viruses have more genetic diversity (the “molecular clock”). This is further evidence that B started spreading first. Pekar 2022 and Pipes 2021 do analyses with known parameters for spread rate and diversity, and find 90%+ odds that Lineage B was the first one in humans. Why did the older strain start spreading later? Probably the virus crossed from bats into raccoon-dogs on some raccoon-dog farm out in the country. It spread in the raccoon-dogs for a while, racking up mutations, including the (less mutated) Lineage A strain and the (slightly more mutated) Lineage B strain. Then several raccoon-dogs were taken to Wuhan for sale, including one with Lineage A and another with Lineage B. The one with Lineage B passed its virus to humans earlier. Then 3-4 days later, the Lineage A one passed its virus to humans. Lineage A was first found in a Wuhan neighborhood right next to the wet market (closer to the wet market than 97% of Wuhan’s population). Again, it would be a bizarre coincidence if a lab leak pandemic was first detected at a wet market. But it would be an even more bizarre coincidence if a lab leak pandemic separated into two strains, and both were first detected at a wet market! Although no known wet market cases were Lineage A, a positive Lineage A environmental sample was found at the wet market, and everyone agrees most cases went undetected. So maybe the Lineage B raccoon-dog spread its virus to a vendor, and that sub-strain mostly stayed in the market. But the Lineage A raccoon-dog spread its virus to a customer, who went back to his house nearby, and that strain spread in the neighborhoods next to the market. This is the only story that explains the evolutionary precedence of A, the greater spread and older molecular clock of B, and the fact that both strains were first found very close to the wet market. Yuri/Saar: Lineage B could be more common and diverse because it got the advantage of a super-spreader event in the wet market. There are a few scattered cases of intermediates between A and B, and a few other scattered cases of lineages that seem even more ancestral (ie closer to the bat virus) than either. This doesn’t make sense in a double spillover hypothesis. But it does make sense if the lineages separated in human transmission somewhere between the lab and the first super-spreader event at the wet market. Peter: Again, the wet market wasn’t a super-spreader event. COVID spread in the wet market at exactly its normal spread rate, doubling about once every 3.5 days. Stop calling the wet market a super-spreader event. The scattered cases of “intermediates” are sequencing errors. They were all found by the same computer software, which “autofills” unsequenced bases in a genome to the most plausible guess. Because Lineage B was already in the software, depending on which part of a Lineage A virus you sequenced, you might get one half or the other autofilled as Lineage B, which looked like an “intermediate”. We know this because all the supposed “intermediates” were partial cases sequenced by this particular software. We can confirm this by noting that there are too many intermediates! That is, where Lineage A is (T/C) and Lineage B is (C/T), the software found both (T/T) “intermediates” and (C/C) “intermediates”. But obviously there can only be one real intermediate form, and we have to dismiss one or the other. But in fact we can dismiss both, because they were both caused by the same software bug. The scattered “progenitor” cases - those closer to the ancestral bat virus than either A or B - are reversions, ie cases where a new mutation in the virus happened to hit an already-mutated base and shift it back towards the ancestral virus. We know this because all of these “progenitors” were scattered cases found months after the pandemic started, often in entirely different countries from Wuhan. If these were real progenitor viruses, they would have either fizzled out or exploded into a substantial portion of all cases, not be found one time in one guy in Malaysia. Given the number of mutations the virus developed over the course of the pandemic, it’s inevitable that some of them would be mutations that bring it closer to the original bat virus, and in fact we find the number of “progenitors” found very nicely matches the number of progenitor-appearing viruses we would expect by chance. And in many cases, we know the “progenitors” are newer than the original lineages, because they also have some of the later mutations that Lineage A or B picked up along the way, alongside their apparent ancestral-bat-virus-like mutations. Session 2: Viral Genetics Yuri: Two years before COVID, scientists at the Wuhan Institute of Virology, together with colleagues at the University of North Carolina, sent in a grant proposal for the DEFUSE program. This program, intended to locate and better understand potential future pandemic viruses, involved going into bat caves and collecting new coronaviruses. Once they had them, they would do gain-of-function: specifically, they would add a furin cleavage site to make them more infectious and see what happened. (quick interlude: COVID’s spike protein has two sections: one binds to human cells through the ACE2 receptor, the other helps fuse with the cell after binding. In order to avoid the immune system, it hides both of these into one spike. But when it reaches a cell, it needs to separate them again. It takes advantage of a human respiratory enzyme, furin, to do the separation - this also ensures that it only infects its primary target, human respiratory cells. The part of COVID that lets it get separated by furin is called the “furin cleavage site”. COVID’s bat-virus ancestors were gastrointestinal viruses; the addition of a furin cleavage site was what made them respiratory viruses.) We’ve found two close relatives of COVID: bat viruses called RATG-13 and BANAL-52. In particular, COVID looks more or less like BANAL-52 plus a furin cleavage site. There are 1500 sarbecoviruses, members of the family of viruses that includes SARS and SARS2/COVID. None of them except COVID have furin cleavage sites. BANAL-52, COVID’s closest ancestor, doesn’t even have anything resembling one that could mutate into a functional furin cleavage site like COVID’s. Instead, COVID - which mostly just resembles BANAL-52 with a few scattered single-point mutations - has twelve completely new nucleotides in a row - a fully formed furin cleavage site that came out of nowhere. There is nowhere else in the genome that COVID differs from BANAL-52 in such a profound way. It’s just BANAL-52 plus a little bit of random mutation plus a fully-formed furin cleavage site that came out of nowhere. Further, the furin cleavage site is weird. It uses the protein arginine twice. But instead of the nucleotides coding for arginine in the usual viral way, both times it uses the codons CGG - the way that higher animals code for arginine. This works fine - it’s just not how viruses do it. So the obvious conclusion is that WIV, which said in 2018 that it was going to find viruses and add furin cleavage sites to them, found a close relative of BANAL-52 and added a furin cleavage site. Since they were humans, and most familiar with the human way of encoding arginine, they added it as CGG both times. COVID seemed surprisingly optimized for infecting humans. Of fifty animals it was tested in, including the usual coronavirus intermediate hosts (pangolins, raccoon-dogs, etc), it was best at infecting human cells. Further, a virus that enters a new species will usually show a burst of mutations as it “figures out” the best way to adapt to that species’ unique biology. But COVID has had a pretty constant mutation rate in humans, from the beginning of the pandemic to the end. That suggests it was already adapted to humans. This could be because the lab screened for viruses with existing adaptations, because they passed it through humanized mice in the lab, or because it adapted in the hundreds of undetected cases that happened between the lab and detection in the wet market. Usually, research with potentially dangerous coronaviruses is done in BSL-3 or 4, ie high to very-high security. But WIV was irresponsibly doing it in BSL-2, ie medium security. The researchers weren’t even required to wear masks. In general, about 1/500 labs will leak any given pathogen they’re working on (?!). But because WIV was researching such an infectious virus in such an irresponsible way, the odds of a leak were much higher. The most likely explanation for all these facts is that WIV went ahead and did the gain-of-function research they said they were going to do (the particular DEFUSE grant proposal we know about got rejected, but it proves that Wuhan wanted to do this, and they could easily have gotten funding somewhere else, or done it out of their regular budget). They found a close relative of BANAL-52 and added a furin cleavage site as a simple twelve-nucleotide insertion, using the human method of encoding arginine that their genetic engineers were familiar with. Then it leaked, spread for a while in the general Wuhan population, and eventually made it to the wet market where it got detected. Peter: As mentioned earlier, the DEFUSE grant was rejected. Further, the grant said that the Wuhan Institute of Virology was responsible for finding the viruses, and the University of North Carolina would do all the gain-of-function research. This was a reasonable division of labor, since UNC was actually good at gain-of-function research, and WIV mostly wasn’t. They had done a few very simple gain-of-function projects before, but weren’t really set up for this particular proposal and were happy to leave it for their American colleagues. Even if WIV did try to create COVID, they couldn’t have. As Yuri said, COVID looks like BANAL-52 plus a furin cleavage site. But WIV didn’t have BANAL-52. It wasn’t discovered until after the COVID pandemic started, when scientists scoured the area for potential COVID relatives. WIV had a more distant COVID relative, RATG-13. But you can’t create COVID from RATG-13; they’re too different. You would need BANAL-52, or some as-yet-undiscovered extremely close relative. WIV had neither. Are we sure they had neither? Yes. Remember, WIV’s whole job was looking for new coronaviruses. They published lists of which ones they had found pretty regularly. They published their last list in mid-2019, just a few months before the pandemic. Although lab leak proponents claimed these lists showed weird discrepancies, this was just their inability to keep names consistent, and all the lists showed basically the same viruses (plus a few extra on the later ones, as they kept discovering more). The lists didn’t include BANAL-52 or any other suitable COVID relatives - only RATG-13, which isn’t close enough to work. Could they have been keeping their discovery of BANAL-52 secret? No. Pre-pandemic, there was nothing interesting about it; our understanding of virology wasn’t good enough to point this out as a potential pandemic candidate. WIV did its gain-of-function research openly and proudly (before the pandemic, gain-of-function wasn’t as unpopular as it is now) so it’s not like they wanted to keep it secret because they might gain-of-function it later. Their lists very clearly showed they had no virus they could create COVID from, and they had no reason to hide it if they did. COVID’s furin cleavage site is admittedly unusual. But it’s unusual in a way that looks natural rather than man-made. Labs don’t usually add furin cleavage sites through nucleotide insertions (they usually mutate what’s already there). On the other hand, viruses get weird insertions of 12+ nucleotides in nature. For example, HKU1 is another emergent Chinese coronavirus that caused a small outbreak of pneumonia in 2004. It had a 15 nucleotide insertion right next to its furin cleavage site. Later strains of COVID got further 12 - 15 nucleotide insertions. Plenty of flus have 12 to 15 nucleotide insertions compared to other earlier flu strains. Sometimes insertions happen because of a mistake in viral replication. Other times the virus gets confused between its own RNA and its host’s, and splices a bit of the host RNA into the virus. This would neatly explain why the insertion used the unusual coding CGG for arginine, which is common in animals but rare in viruses. On the other hand, it’s not that rare in viruses - COVID uses CGG for arginine about 3% of the time. And human engineers don’t necessarily use it any more than that - Peter was able to find one example of humans adding arginine to a virus, and 0 out of the 5 arginines added were CGG. COVID’s furin cleavage site is a mess. When humans are inserting furin cleavage sites into viruses for gain-of-function, the standard practice is RRKR, a very nice and simple furin cleavage site which works well. COVID uses PRRAR, a bizarre furin cleavage site which no human has ever used before, and which virologists expected to work poorly. They later found that an adjacent part of COVID’s genome twisted the protein in an unusual way that allowed PRRAR to be a viable furin cleavage site, but this discovery took a lot of computer power, and was only made after COVID became important. The Wuhan virologists supposedly doing gain-of-function research on COVID shouldn’t have known this would work. Why didn’t they just use the standard RRKR site, which would have worked better? Everyone thinks it works better! Even the virus eventually decided it worked better - sometime during the course of the pandemic, it mutated away from its weird PRRAR furin cleavage site towards a more normal form. Further, COVID’s furin cleavage site was inserted via what seems to be a frameshift mutation - it wasn’t a clean insertion of the amino acids that formed the site, it was an insertion of a sequence which changed the context of the surrounding nucleotides into the amino acids that formed the site. This is a pointless too-clever-by-half “flourish” that there would be no reason for a human engineer to do. But it’s exactly the kind of weird thing that happens in the random chance of evolution. COVID is hard to culture. If you culture it in most standard media or animals, it will quickly develop characteristic mutations. But the original Wuhan strains didn’t have these mutations. The only ways to culture it without mutations are in human airway cells, or (apparently) in live raccoon-dogs. Getting human airway cells requires a donor (ie someone who donates their body to science), and Wuhan had never done this before (it was one of the technologies only used at the superior North Carolina site). As for raccoon-dogs, it sure does seems suspicious that the virus is already suited to them. The claim that COVID is uniquely adapted to humans is false. The paper that claimed that defined how well COVID was adapted to different animals by those animals’ difference (on the relevant cell receptors) from humans. So in its methodology, humans came out #1 by default. If you don’t do that, COVID is better-adapted to many other animals. It’s not necessarily true that viruses see a burst of mutations when they enter a new host. COVID spread to deer and mink, and in neither case was there a burst of mutations. COVID has a pretty simple job of infecting respiratory cells and is already very good at it, regardless of species. In Yuri’s model, Wuhan Institute of Virology picked up a discarded grant and decided to do the gain-of-function half allotted to a different university, despite their relative inexperience. They skipped over all the SARS-like viruses they were supposed to work on, and all the standard gain-of-function model backbones, in favor of BANAL-52, a virus which would not be discovered for another two years, but which they somehow had samples of, which they had for some reason decided to keep secret despite its total lack of interestingness. Then they would have had to eschew all usual gain-of-function practices in favor of inserting a weird furin cleavage site that shouldn’t have worked according to the theory they had at the time, via a frameshift mutation. Then they would have had to culture it, a technique beyond their limited capabilities. Then it would have had to leak, and magically show up again in front of the raccoon-dog stall at a wet market. Yuri: WIV wouldn’t have needed to keep BANAL-52 “secret” in some kind of sinister way. Plenty of researchers have backlogs of work they haven’t published yet. Probably they a found BANAL relative in one of their normal sampling trips, did some preliminary studies on it, and planned to publish it later once they cleaned up their data. Everyone works like this. The part of DEFUSE saying that they would only work on viruses that were 95% similar to SARS is unclear and might mean something else. It looks more like they say they’ll start with those viruses, but also do some work on novel viruses. BANAL-52 could have been one of the novel viruses. The furin cleavage site is weird, but the researchers might have done that on purpose, to make the virus easier to keep track of, or to test different furin cleavage sites. Depending on the exact BANAL-52 relative they used, it might not even be a frameshift; there’s a particular way to spell serine that would make the insertion more natural. The claims that COVID can’t be cultured in normal media are based on speculative original research by Peter and might not hold up. Peter: WIV did most of its virus-gathering in a trip to a Yunnan cave between 2010 and 2015. All those viruses have long since been processed and added to the database. There’s no sign that they made more trips to Yunnan caves, and no reason for them to keep that secret. So the idea that they might just have some new viruses they didn’t publish doesn’t hold up. But suppose they did make more trips. Given the amount of time between the DEFUSE proposal and COVID, if they kept to their normal virus-collection rate, they would have gotten about thirty new viruses. What’s the chance that one of those was BANAL-52? There are thousands of bat viruses, and BANAL-52 is so rare that it wasn’t found until well after the pandemic started and people were looking for it very hard. So the chance that one of their 30 would be BANAL-52 is low. Also, they said in DEFUSE that they planned to go back to the same Yunnan cave. But BANAL-52 was found far away from that cave, so unless it ranged over a wide area, they probably couldn’t have found it even if they got very lucky. Session 3: Closing Arguments This third debate was supposed to be about “inference”, ie how much Bayesian evidence was provided by each of the facts given so far, and how to fit them into the Rootclaim probabilistic model. I’m going to relegate my summary of the more probabilistic half to the next section of this post, and just include the closing arguments here. Saar: Peter’s case hinges on the idea that it’s very improbable that a lab leak pandemic would first show up at a wet market. But this isn’t necessarily improbable. The Huanan Seafood Market had several factors that made it a likely location for a superspreader event. It was busy, with over 10,000 visitors a day. Many of the people there (eg the 1,000 vendors) came back daily, letting them reinfect each other. It had poor ventilation, especially in the high-positivity area near the raccoon-dog stall. It had cold wet surfaces on which the virus could survive for long periods. It was indoors, which prevented UV light from killing the virus. Given a small amount of sporadic COVID going around Wuhan, it’s not surprising for the first place it started spreading en masse to be a wet market. In fact, we have several examples of this. When China was COVID Zero, there would occasionally be small outbreaks that the authorities would have to contain. Most of these were at wet markets. For example, the big COVID outbreak in Beijing started at Xinfadi Market, their local seafood market. This couldn’t be an animal spillover, because there were no raccoon-dogs or other weird wildlife there. So it must be that wet markets are natural places for superspreader events. There are several other examples, which make up about half of the total outbreaks in Zero COVID era China, plus others in Singapore and Thailand. Since COVID clusters concentrate in wet markets even when there is no animal spillover, we should accept this as a property of the virus, and not attribute any significance to the fact that this happened in Wuhan too. Peter: About 1/10,000 citizens of Wuhan was a wet market vendor. So there’s a 1/10,000 chance that the first known COVID case should be a wet market vendor by chance alone. Weibo lists the most popular places for people to check in to their network on their phones, and the wet market was the 1600th most popular place in Wuhan, meaning that if you weight locations by busy-ness, there’s a less than 1/1600 chance that the first cases would be in the wet market. Yes, the wet market is indoors, has mediocre ventilation, has repeat visitors, etc. So do thousands of other places in Wuhan, like schools, hospitals, workplaces, places of worship. The wet market isn’t special in any way. And again, it wasn’t a superspreader event! COVID spread at the same rate in the wet market as it does everywhere else: doubling once per 3.5 days. It doesn’t matter what kinds of arguments you can come up with for why the wet market should have been the perfect superspreader event location, we can look at it and see that it wasn’t. It’s an environment that spreads COVID at exactly the normal rate. Zero COVID era Chinese outbreaks were concentrated in wet markets because they received infected animal products. We know why there was an outbreak in the Xinfadi Market in Beijing: it was because the seafood stall got frozen fish from some non-Zero-COVID country, the fish had COVID particles on it, and the vendor got infected and spread it to everyone else. Something like this is true for the other Chinese wet market based outbreaks we know about it. So this makes the opposite point you think it does: wet markets start outbreaks because there are infected goods being sold there. Then the virus spreads through the wet market at a completely normal rate. Saar: The Weibo list of 1600 places bigger than the wet market is likely inaccurate, because it's based on check-in data and people don't check in to seafood markets. Most of those 1600 places aren't amenable to superspread. The 70 markets supposedly bigger than Huanan are irrelevant, because they're supermarkets, open air markets, etc. Huanan is the largest seafood market in central China, and a more likely place for the first cluster of cases to be noticed. Markets weren't a common spillover location in SARS1, so the zoonosis hypothesis hasn't "called" this event in a way that should give them a high Bayes factor. And there’s still plenty of evidence for isolated (though not super-spreading) pre-market cases. A British expatriate in Wuhan, Connor Reed, says he got sick in November, three weeks before the first wet market case. Later the hospital tested his samples and said it was COVID. Another paper reports 90 cases before the first wet market one. Peter: Connor Reed was lying. The case wasn’t reported in any peer-reviewed paper. It was reported in the tabloid The Daily Mail, months after it supposedly happened. He also told the Mail that his cat died of coronavirus too, which is rare-to-impossible. Also, to get a positive hospital test, he would have had to go to the hospital, but he was 25 years old and almost no 25-year-olds go to the hospital for coronavirus. His only evidence that it was COVID was that two months later, the hospital supposedly “notified” him that it was. The hospital never informed anyone else of this extremely surprising fact which would be the biggest scientific story of the year if true. So probably he was lying. Incidentally, he died of a drug overdose shortly after giving the Mail that story; while not all drug addicts are liars, given all the other implausibilities in his story, this certainly doesn’t make him seem more credible. And in any case, he claimed he got his case at a market “like in the media” The other 90 cases are also fake. A lab leak guy found a paper that mentioned 90 more cases than other papers, and made up a conspiracy theory where the author was trying to secretly communicate that there had been 90 secret cases before any of the confirmed cases, even though there was nothing about this in the text of the paper. But actually that paper just counted cases differently than other papers, and they were referring to normal cases after the pandemic officially started. Again, I’ll come back to the discussion about inference later, but for now, here’s a table of both sides’ reasoning. This exact presentation comparing both analyses is mine3, but you can see Saar’s version here, and Peter’s starting at 45:33 of this video. Slightly made up; the two sides didn’t express their probabilities in the same way and I had to make editorial decisions to match them. Note that these aren't entirely comparable because Peter is being laxer about out-of-model probability than Saar. Although Saar's final odds here are 533-to-1, this just the central estimate. Rootclaim’s real final probability is 94% lab leak. You can see their analysis here. And The Winner Is . . . … … … … … Peter and the zoonosis hypothesis. This was a decisive victory. There were two judges, who each gave separate verdicts (or were allowed to declare a draw). Both judges decided in favor of Peter. You can see the judges’ own summary of their reasoning here (Will, Eric) Manifold agreed with the judges. There was a prediction market on who would win. It started out 70-30 in favor of lab leak. As the videos came out, zoonosis started doing better and better. I don’t want to take the exact final numbers too seriously, since I think some of the later price increases involved hints from the participants’ behavior. But it’s clear which way viewers thought the wind was blowing4. Around the same time, the Good Judgment Project - Philip Tetlock’s group studying superforecasters - put out a report on the lab leak hypothesis. After studying it in depth, his forecasters ended up 75-25 in favor of zoonosis. The Rootclaim debate was one of ten sources they said they found especially interesting. And also around the same time, and unrelated to any of this, the Global Catastrophic Risks Institute surveyed experts (“168 virologists, infectious disease epidemiologists, and other scientists from 47 countries”) and found the same thing (though see here for some potential problems with the survey): For what it’s worth, I was close to 50-50 before the debate, and now I’m 90-10 in favor of zoonosis. III. The Math And The Aftermath The third debate session was about “inference”, how to put evidence together. I put this part off until after disclosing the winner, because I wanted to talk about some of these issues at more length. The Math: Judges Both judges included a probabilistic analysis in their written decision. Here’s the same table as above, expanded to add the judges: I shoehorned the judges’ factors into the categories I already had; some of them were actually subtly different from Peter’s, Saar’s, and each other’s. The “priors” category is especially a mess here. We’ll go over these later, but I get the impression that they both thought of probabilistic analyses as an afterthought. For example, Judge Eric wrote 30,000 words about which considerations moved him, and only then includes the analysis, saying: I am not convinced that this Bayesian calculation is even an appropriate way to estimate the relative posterior probability of Z and LL; it just seemed fair that after criticizing Rootclaim’s calculations at length I should make an attempt at it myself. Judge Will’s decision ran to 10,000 words. He said he independently tried both reasoning it out intuitively, and running the Bayesian analysis, and was relieved when these two methods returned the same result. He said: I am skeptical that the Bayesian decision making/evaluation methods are any more "objective" than [intuitive reasoning]. I think they maximize legibility, not objectivity, and tend to hide the intuitive/heuristic portion in the data inclusion step and values, where it’s harder to see . . . I am not skilled in the Bayesian method, and I am sure I made significant mistakes. More time and practice would improve and refine my estimates. At the fundamental rules of the universe level, Bayesian analysis must be the best way to evaluate evidence. However, I am unsure that it’s a good strategy for a human given our cognitive limitations, and doubly unsure it’s truly being used (in the dispassionate sense) where the outcome is social desirability/fame/Twitter likes. I’m focusing on this because Saar’s opinion is that the debate went wrong (for his side) because he didn’t realize the judges were going to use Bayesian math, they did the math wrong (because Saar hadn’t done enough work explaining how to do it right), and so they got the wrong answer. I want to discuss the math errors he thinks the judges made, but this discussion would be incomplete without mentioning that the judges themselves say the numbers were only a supplement for their intuitive reasoning. That having been said, let’s look deeper into some of Saar’s concerns. The Math: Extreme Odds Saar complained that Peter’s odds were too extreme. For example, Peter said there was only a 1/10,000 chance that a lab leak pandemic would first show up at a wet market. Peter’s argument went something like: obviously a zoonotic pandemic would start at a site selling weird animals. But a lab leak pandemic - if it didn’t start at the lab - could show up anywhere. 1/10,000 Wuhan citizens work at the wet market. So if a lab leak was going to show up somewhere random, the wet market was a 1/10,000 chance. Saar had specific arguments against this, but he also had a more general argument: you should rarely see odds like 1/10,000 outside of well-understood domains. In his blog post, he gave this example: A prosecutor shows the court a statistical analysis of which DNA markers matched the defendant and their prevalence, arriving at a 1E-9 probability they would all match a random person, implying a Bayes factor near 1E9 for guilty. But if we try to estimate p(DNA|~guilty) by truly assuming innocence, it is immediately evident how ridiculous it is to claim only 1 out of a billion innocent suspects will have a DNA match to the crime scene. There are obviously far better explanations like a lab mistake, framing, an object of the suspect being brought by someone to the scene, etc. So the real p(wet market|lab leak) isn’t the 1/10,000 chance a pandemic arising in a random place hits the wet market, but the (higher?) probability that there’s something wrong with Peter’s argument. Then Saar tried to show specific things that might be wrong with Peter’s argument. I didn’t find his specific examples convincing. But maybe the question shouldn’t be whether I agreed with him. It should be whether I’m so confident he’s wrong that I would give it 10,000-to-1 odds. This makes total sense, it’s absolutely true, and I want to be really, really careful with it. If you take this kind of reasoning too far, you can convince yourself that the sun won’t rise tomorrow morning. All you have to do is propose 100 different reasons the sunrise might not happen. For example: The sun might go nova.
April 09, 2024 · Original source
1. Xiao et al (2021) - https://www.nature.com/articles/s41598-021-91470-2%E2%80%8B%E2%80%8B%E2%80%8B , which includes a co-author of Worobey et al (2022), a leading zoonosis paper states in table 1 that the raccoon dogs were wild caught in Hubei, not farmed as you assert in the piece. This alone rules out raccoon dogs as plausible hosts for two independently sufficient reasons. Firstly, there is unanimity in the literature that the bat ancestral virus to SARS-CoV-2 is in southern Yunnan or South East Asia. Everyone agrees with this, including Shi Zhengli. If a species was wild caught in Hubei, then there would be no explanation of how it acquired the ancestral bat virus, given that Hubei is 1000 miles from southern Yunnan.
This alone isn’t fatal to lab leak. It’s perfectly possible for the lab to leak (let’s say) November 5th, the virus spreads a bit, and then a month later someone goes to the wet market, coughs on a vendor, and starts the officially recognized pandemic. But if that were true, you’d expect (let’s say) 30 cases by early December. Let’s say the wet market vendor was exactly Case # 30. She infected the other wet market vendors, starting a pandemic with an obvious center at the wet market and lots of infected wet market vendors and patrons. What about Case # 29? If they were (let’s say) a barista, how come they didn’t infect people at their coffee shop? How come there wasn’t a second obvious cluster radiating out from a coffee shop, lots of coffee-shop-linked cases, etc? How come there weren’t 30 equally-sized clusters? In order to avoid this, you either need to claim that the wet market was a perfect superspreader location, or that the pattern with lots of cases in the wet market and few-to-none anywhere else was a result of ascertainment bias. Saar made both those arguments during the debate, but I thought Peter rebutted them effectively. 1.4: COVID in Brazilian wastewater Nicholas Halden (blog) writes: What should we make of this study, which found the presence of covid in Brazilian wastewater in late 2019? Consider the doubling times. The study says that scientists working in late 2020 found COVID in samples of Brazilian wastewater from November 27, 2019. This was long before the first detected case of transmission in Brazil on March 13, 2020. Between November 27, 2019 and March 13, 2020 is about 16 weeks, so 32 COVID doubling times. 32 doubling times with no lockdown is enough time for COVID to infect every single person in Brazil. If COVID had infected everyone in Brazil before the first recognized case, we would have noticed. (again, COVID doubling time isn’t exactly invariably 3.5 days, but here we’re talking about numbers big enough that the exact details don’t matter very much) So if COVID was in Brazil on November 27, it must have fizzled out instead of going pandemic. How likely is that? If one person had COVID, it’s not too unlikely - not all COVID cases transmit it forward. If (let’s say) twenty people had COVID, it’s very unlikely - at that point, the law of large numbers takes over; in a freak coincidence, every single patient would have to fail to infect anyone else. So almost certainly fewer than 20 people in Brazil had COVID in November 27. So which is more likely - that somehow 20 people had COVID long before the virus was officially detected, and on a totally different continent, yet somehow a scientist looking through wastewater found the water from exactly those people and managed to detect the virus? Or that there was a sampling error, which happens all the time in these kinds of things? Peter wrote a blog post on some of these issues. He found that there were positive tests from wastewater samples as early as March 2019, which doesn’t fit anyone’s timeline, including lab leakers’. And most of these positives (including the Brazilian sample) contained later strains of the virus with mutations it picked up late in 2020. So these were almost certainly false positives from contamination. 1.5: Biorealism’s 16 arguments Biorealism has a list of sixteen arguments, which he liked so much that he posted it three times in the ACX comments, twice on Less Wrong, twice on Manifold, and about a dozen times on Twitter under multiple account names. Some posts were slightly different from others, but a typical version is: Importantly, Miller incorrectly claimed the N501Y mutation would result from passage in hACE2 mice (mixed them up with BALB/c mice). The major papers Miller relied on have been seriously challenged since the debate. See Stoyan and Chiu (2024), Weissman (2024), Bloom (2023) and Lv et al (2024). Overall the circumstantial evidence makes lab v plausible: Peter admitted getting this wrong during the debate. I think this very minor point about mice mutations was approximately his only mistake in 15 hours of debating, and he admitted it as soon as he noticed. Biorealism somehow heard about this (obviously not through watching the debate, as we’ll see in a moment), then left about 20-30 comments starting with it, under various accounts, on various platforms, as if it somehow discredited Peter. This is making me somewhat less charitable to him and his 16 arguments than I would be otherwise. 1. Chinese researchers Botao & Lei Xiao observed lab origin was likely given the nearest known relatives to SARS-CoV-2 were far from Wuhan. Wuhan Institute of Virology (WIV) sampled SARS-related bat coronaviruses where the nearest relatives are found in Yunnan, Laos and Vietnam ~1500km away. They refuse to share their records. The ancestral viruses of SARS were found equally far from where SARS spilled over into humans, so we know it’s possible (and likely) for viruses to travel that far. 2. Patrick Berche, DG at Institut Pasteur in Lille 2014-18, notes you would expect secondary outbreaks if it arose via the live animal trade. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10234839/ There are constant outbreaks of weird coronaviruses in animal handlers. See eg this paper, which estimates about 60,000 of these per year. None of these ever go anywhere, because the farmers are in rural areas that aren’t dense enough to sustain a high R0, and the epidemic fizzles out after a single digit number of cases. Any early outbreaks of COVID would have vanished into this long and mostly unnoticed list. 3. Molecular data: Only sarbecovirus with a furin cleavage site. Well adapted to human ACE2 cells. Low genetic diversity indicating a lack of prior circulation (Berche 2023). Restriction site SARS-CoV-2 BsaI/BsmBI restriction map falls neatly within the ideal range for a reverse genetics system and used previously at WIV and UNC. Ngram analysis of the codon usage per Professor Louis Nemzer https://twitter.com/BiophysicsFL/status/1667232580255490053?t=IJgitS5cw364ioclzVWxaA&s=19 The SARS2 backbone is very low in CG and CpG. While the 12-nt insert that gives it the FCS is extremely high in both. Almost as if it was some kind of chimera of a consensus sequence and a codon-optimized polybasic cleavage site? https://twitter.com/BiophysicsFL/status/1752800486837678377?t=EpIRgyybJVaPgeMP5xdstA&s=19 https://www.biorxiv.org/content/10.1101/2022.10.18.512756v1 https://link.springer.com/article/10.1007/s10311-021-01211-0?fbclid=IwAR1HMUMtLIAFOFppVasQDeoIAYrVhP8j4YoPO4wnaTOUiKLsllZl_oKryOw Most of this was discussed extensively in the second session of the debate, which I recommend. The CGG-CGG arginine codon usage is particularly unusual but used in synthetic biology. I asked a synthetic biologist about this. He said: » “Nope. I would literally never do this if I was designing a small insert (maybe I wouldn't notice if it happened by chance with ~1 in 25 odds in a naive codon optimization algorithm as part of a larger sequence). High GC% is bad. Tandem repeat is worse. Several other perfectly fine arginine codons. And I wouldn't engineer a viral genome using human codon usage. An engineer would not do it.” 4. DEFUSE full proposal: virus 20% different from SARS1, consensus seq assembled with 6 segments, without disrupting coding seq, BsmBI order, FCS. SARS2: 20% different than SARS1, 6 evenly spaced fragments w BsmBI and BsaI restriction sites, FCS. Jesse Bloom, Jack Nunberg, Robert Townley, Alexandre Hassanin have observed this workflow could have lead to SARS-CoV-2. Work often begins before funding sought or goes ahead anyway. Re: 4 - Also scattered across second section of debate, also not going to retread 5. Market cases were all lineage B. Lv et al (2024) indicates there was a single point of emergence and A came before B. So market cases not the primary cases. See also Bloom (2021), Kumar et al (2022). Peter Ben Embarek said there were likely already thousands of cases in Wuhan in December 2019.https://t.co/50kFV9zSb6 https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/34398234/ https://academic.oup.com/bioinformatics/article/38/10/2719/6553661 There was a Lineage A sample in the market, lab leak proponents just try to ignore/dismiss/conspiracize it away. The first two known Lineage A cases were very close to the market. Lv (is this even a real name? It sounds like Roman numeral? But I guess that’s what you expect in a country ruled by someone named Xi) found some weird COVID variants in Shanghai that might or might not mean anything; you can see some discussion of the implications here, but I don’t think they’re strong evidence either way. If A was first, it means some really weird stuff coincidences have to happen to give us the spread rates and genetic clock data we get, but they’re not necessarily weirder in the zoonosis hypothesis than the lab leak one. The claim that there were “thousands of cases in Wuhan in December 2019” is very easy to disprove by doubling rate arguments like the one above, by the blood bank study mentioned above, by the WHO’s failed case search, and by many other lines of argument. 6. Evidence for lineage A in the market is based on a low quality sample according to Liu et. al. (2023). I really think lab leakers need to decide whether they think China is a sinister actor trying to cover up the truth, or whether they should trust every offhand comment by Chinese government officials as gospel. Dr. Liu doesn’t explain in what sense he thinks the Lineage A sample is “low-quality”, and the Western scientists who I asked about this said they didn’t understand this complaint and that the sample was fine. A Western team re-analyzing the same sample describes it as “conclusively contain[ing] Lineage A.” I think most lab leakers have switched from trying to deny the genetics to claiming that this was “contamination”, which also doesn’t make sense (the sample is genetically very early). Note that aside from this sample, the first two Lineage A cases discovered were both very close to the wet market. 7. Bloom (2023) shows market samples do not support market origin. There is also no evidence of transmission in the claimed susceptible animals elsewhere. https://academic.oup.com/ve/advance-article/doi/10.1093/ve/vead089/7504441 Discussed extensively in my article as well as the first section of the debate. 8. Lineage A and B only two mutations apart. François Ballox, Bloom and Virginie Courtier-Orgogozo note this is unlikely to reflect two separate animal spillovers as opposed to incomplete case ascertainment of human to human transmission (Bloom 2021). Discussed extensively in my article as well as the first section of the debate. 9. Sampling bias. George Gao, Chinese CDC head at the time, acknowledged to the BBC stating they may have focused too much on and around the market and missed cases on the other side of the city. David Bahry outlines the documented bias. Michael Weissman has shown this mathematically. https://journals.asm.org/doi/10.1128/mbio.00313-23 https://academic.oup.com/jrsssa/advance-article-abstract/doi/10.1093/jrsssa/qnae021/7632556 Re: Dr. Gao, see above comment about Chinese officials. See the section Ascertainment Bias below for why I disagree with this specific claim, which also addresses the Michael Weissman argument. 10. Spatial statistics experts show the Worobey claim the market was the early epicentre was flawed. https://academic.oup.com/jrsssa/advance-article-abstract/doi/10.1093/jrsssa/qnad139/7557954 Re: 10 - See Confirmation Of The Centrality Of The Huanan Market Among Early COVID-19 Cases, a response to the paper you cite: The centrality of Wuhan's Huanan market in maps of December 2019 COVID-19 case residential locations, established by Worobey et al. (2022a), has recently been challenged by Stoyan and Chiu (2024, SC2024). SC2024 proposed a statistical test based on the premise that the measure of central tendency (hereafter, "centre") of a sample of case locations must coincide with the exact point from which local transmission began. Here we show that this premise is erroneous. SC2024 put forward two alternative centres (centroid and mode) to the centre-point which was used by Worobey et al. for some analyses, and proposed a bootstrapping method, based on their premise, to test whether a particular location is consistent with it being the point source of transmission. We show that SC2024's concerns about the use of centre-points are inconsequential, and that use of centroids for these data is inadvisable. The mode is an appropriate, even optimal, choice as centre; however, contrary to SC2024's results, we demonstrate that with proper implementation of their methods, the mode falls at the entrance of a parking lot at the market itself, and the 95% confidence region around the mode includes the market. Thus, the market cannot be rejected as central even by SC2024's overly stringent statistical test. I think this response is pretty strong. In one analysis, they show that even though the other paper’s methodology is worse than theirs, if you apply it correctly (instead of inappropriately excluding various cases like the paper’s authors did), the center of all early cases in Hubei province lands on the wet market parking lot. In another analysis, they show that the other paper’s recommended tests wouldn’t have correctly pointed to the offending water pump in the famous John Snow cholera outbreak, but theirs would have. Still, I think it’s useful to supplement fancy statistics with normal common sense, so I recommend just looking at the map of early cases: …and deciding whether you think the assumptions behind a specific statistical test are likely to debunk the idea that cases are centered around the wet market. 11. Wuhan used as a control for a 2015 serological study on SARS-related bat coronaviruses due to its urban location. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6178078/ I don’t know why this point is supposed to matter. If you mean that Wuhan isn’t directly exposed to bats, nobody ever said it was. The zoonotic theory is that wildlife carted in from other areas of China started the pandemic in the wet market. 12. Superspreader events also seen at wet markets in Beijing and Singapore (Xinfadi and Jurong). This was discussed very extensively in the debates, both in section 1 and section 3. Wet markets weren’t “superspreader locations” - in fact, the disease spread no more quickly there than anywhere else. They were the first place in those cities that the pandemic started, due to contaminated animal products. If anything, this supports zoonosis. See also my discussion with Saar on this point below. 13. WIV refuse to share their records with NIH who terminated subaward in 2022. Wider suspension over biosafety concerns. https://www.bloomberg.com/news/articles/2023-07-18/us-suspends-wuhan-institute-funds-over-covid-stonewalling Although WIV has not been especially forthcoming, some of their databases were leaked in various ways and showed that they did not have any viruses capable of transforming into COVID. 14. PLA involvement at WIV and MERS research prior to SARS-COV-2. MERS features several similarities with SARS-CoV-2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7022351/ I can’t even tell what conspiracy theory you’re trying to propose with this one; if you spell it out I can try to explain why it might be false. 15. SARS1 leaked several times and SARS-COV-2 has leaked from a BSL-3 lab in Taiwan. Agreed that SARS leaked several times. It also spilled over from animals several times. During the debate, a lab leak rate of once per lab per 500 years was proposed (everyone agreed to steelman this by 10x for WIV numbers); I would be interested to know whether anything about the study of SARS challenges that number. 16. Unpublished infectious clone identified from Wuhan contradicting arguments such reverse genetics systems would be published. https://www.biorxiv.org/content/10.1101/2023.02.12.528210v1.full I asked some scientists about this paper and here’s what they told me. Wuhan University sequenced some rice. In the middle of the sequence, there’s an unexpected sequence from a common coronavirus, HKU4. The most likely explanation is that someone else in Wuhan was working on the coronavirus and there was cross-contamination. Plausibly this is Wuhan Institute of Virology, who is known to work with coronaviruses. This is cool detective work, but it’s not clear what it’s supposed to prove. I think some lab leakers are using it to prove that WIV can do reverse genetics, but they admitted this already in a published paper so that’s not too helpful. I think others are using it to prove WIV had “secret viruses” in their catalogue, but the rice virus wasn’t secret, it was HKU4, which is common and which WIV has already published papers about. 1.6: DrJayChou’s 7 Arguments Once again, I cannot stress enough how much better a take you might have on this debate if you watch it. “The first known case predates the market outbreak by a month” - this is not the consensus position. I cannot say for sure what Dr. Chou means by this, but I suspect he’s referring to one of the many claims to this effect that Peter effectively debunked during the debate (Connor Reed, Mr. Chen, the 92 cases, Brazil, etc).
I’m not a virologist, but I question how this comparison works. Surely HKU1 got its insert on some specific day. If you take the virus the day before, and then the other virus the day after, there will be no differences except the insert, and it will look just like COVID (ie an insert without many other mutations). The fact that the COVID comparison has few mutations, and the HKU1 insert has many mutations, just shows that whatever older virus we chose to compare HKU1 to is more distant from HKU1 than BANAL-52 (or whatever) is from COVID. Or am I missing something here? [The evidence that China tried to cover up zoonosis from the start] is untrue. They clearly said from the start this is a zoonotic spillover at HSM, and at least part of the government went to immense efforts to identify the animal, close farms, etc. (and of course couldn’t find any infected animal). Only in late 2020 did they start suspecting an import from cold-chain products after having multiple outbreaks that seem related to cold-chain products. From a Vox article from March 2023: From the start, the Chinese government interfered with efforts by both Chinese and international experts to study the pandemic, including its origins. Reporting by the AP found that even as WHO officials were publicly praising China’s cooperation, behind the scenes they were complaining about lack of access and a refusal to share data. Within months of the beginning of the pandemic, the Chinese government imposed restrictions on academic research into the origins of the novel coronavirus … China’s intransigence wasn’t unusual — countries are rarely eager to confirm that they’re the source of a deadly disease — but it went beyond the norm. International investigators weren’t permitted to see the market until more than a year after the pandemic began and a WHO-affiliated team was allowed a highly choreographed and controlled visit. The resulting report that came out of the Wuhan visit, which dismissed the possibility of a lab origin, pointed the finger at some kind of zoonotic spillover while concluding that it was unlikely that the spread started at the market, which surprised many experts. It also found that it was “possible” that the virus had been introduced via contaminated frozen food products from abroad. While few experts took that possibility seriously, it fit a narrative the Chinese government had been pushing, against nearly all evidence, that the pandemic had in fact not originated in China. “China just doesn’t want to look bad,” Filippa Lentzos, a biosecurity expert at King’s College London, told Science last August. “They need to maintain an image of control and competence. And that is what goes through everything they do.” […] it seems clear that with more cooperation, scientists could have been looking at raccoon dogs a year or more ago. “The big issue right now is that this data exists and that it is not readily available to the international community,” Maria Van Kerkhove, the WHO’s Covid-19 technical lead, told reporters on Friday. “This is first and foremost absolutely critical, not to mention that it should have been made available years earlier, but that data needs to be made accessible to individuals who can access it, who can analyze it and who can discuss it with each other.” The irony is that by making it so difficult to properly investigate a zoonotic origin of Covid, the Chinese government has created a vacuum that has been filled by claims on all sides, including the much more damning accusation that the pandemic was the result of a lab error at the Wuhan Institute of Virology. For what it’s worth, my timeline of Chinese denials and coverups looks like this: December: COVID doesn't exist, it's all lies Early January: Fine, it exists, but it’s just some wet market thing that can't spread from person to person Late January: Fine, it can spread from person to person, but we’ve got it under control now. February: Fine, it’s out of control, but you would not believe how great our response was. We're basically heroes. March: COVID was a US bioweapon, or possibly came from Italy. April: Chinese people are banned from researching the origins of COVID without government permission. 2: Comments Arguing Against Lab Leak 2.1: Is the pandemic starting near WIV reverse correlation? randomstringofcharacters wrote: Isn't [the pandemic starting near the lab] a reverse correlation issue? The lab is situated there because it's an area where coronaviruses were found in the past. Many people had this question, but Wuhan Institute of Virology was founded in 1956, didn’t originally focus on coronaviruses, and isn’t in a coronavirus hot spot. Most of WIV’s coronavirus samples come from Yunnan, about a thousand miles away. COVID’s closest relatives were found in Laos, almost two thousand miles away. During the debate, both Saar and Peter calculated the odds of a natural pandemic arising in Wuhan by dividing the population of Wuhan by the total urban population of East Asia (Saar) or South China (Peter). Saar got 1.5%, Peter got 3% (he later said this could be as high as 10% because it was a central hub in the wildlife trade). This isn’t an Official Position and I don’t think anyone else shares it, but during the debate Peter pointed out a few times that there are plenty of disease-ridden bats in Hubei (the province Wuhan is in), and that it’s not impossible that a bat virus currently known only in Laos could be active in Hubei. Still, this is the minority viewpoint and most scientists just think it involved something about the wildlife trade. 3: Other Points That Came Up 3.1: Apology to Peter re: extreme odds quiet_NaN wrote: Hot take: Peter clearly failed to convince anyone. The lab leak odds, in log10 (i.e. orders of magnitude are): Peter -20.7 Saar 2.7 Eric -3.1 Will -2.5 Scott -1.2 Daniel -1.4 One of these numbers is clearly an outlier. Scott mentions it and calls it "trolling", I would argue that it is debating in bad faith. 2e-21 is a ratio which is just silly. For one thing, the gain of function at WiV pathway is not the only pathway towards a lab leak. The WIV could also have released a naturally occurring coronavirus at the wet market. At 2e-21 odds, we would probably have to consider the possibility that the WIV built a time machine and went back in time to infect the wet market. I might have screwed up here - or at least I should have emphasized the “trolling” part. Peter complained about my presentation of his extreme-odds slide, saying: This is basically accurate. During the debate, Saar gave lots of different numbers. I don’t want to say exactly what the different numbers meant, because in earlier drafts of my post, Saar said I misunderstood them. My impression were that some of his numbers were conservative, others were central, others were extreme, others were adjusted-for-out-of-model-error, others were not-adjusted, etc. In an early draft of the post, I gave higher numbers for Saar. Saar asked me to replace them with the numbers I ended up using. I decided to agree, because I wanted to represent Saar fairly with the numbers he most centrally believed, but also because these were closest to the numbers on his Rootclaim site so it wasn’t like he was making them up just to fool me. Peter didn’t argue quite as hard, and also he didn’t have anything like the Rootclaim site, so I just took his first set of numbers. Trying to piece things together, I think a reasonable summary would be: During the debate, Saar mentioned 700-million-to-one odds in favor of lab leak, not because he thought this was plausible, but just as a discussion of where the situation would end up if you didn’t adjust for human fallibility.
Yale

Yale is a recurring place in the Astral Codex Ten archive, appearing 2 times across 2 issues between March 27, 2022 and June 18, 2025. The archive places it in contexts such as "Yale: 4/22–4/23"; "former Yale grad". It most often appears alongside Baltimore, California, Metaculus.

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Yale
Mention count
2
Issue count
2
First seen
March 27, 2022
Last seen
June 18, 2025
March 27, 2022 · Original source
Metaculus currently has him at 40% to win the primary and 29% to win the general. I’m closer to 60/45. Although he’s getting support from some big funders, campaign finance privileges small-to-medium-sized donations from ordinary people. If you want to support him, you can see a list of possible options here - including donations. You can donate max $2900 for the primary, plus another $2900 for the general that will be refunded if he doesn’t make it. If you do donate, it would be extra helpful if the money came in before a key reporting deadline March 31. 3: Every year in autumn I hold a big Meetups Everywhere event, and every time people tell me I should do it more often than once a year. So this time we’ll hold a mini-Meetups-Everywhere this April. It won’t be any different from your usual meetup schedule except that it’ll be the Schelling time for everyone who only wants to come once every few months to come. If you’re a meetups organizer (or want to become one), please fill in this form with the date of a meetup April 11th or later. Next Sunday I’ll put the results on the Open Thread for people to see. 4: Speaking of meetups, the rationalist/EA establishment is trying to promote local meetups. If you’re a local ACX/LW meetups organizer, you’re potentially invited to attend an all-expenses paid retreat in California in July with our meetups czar Mingyuan. Please read more here, then fill in this form to get on her radar. 5: And speaking of Mingyuan, she is going to inspect - sorry, enjoy the hospitality of - the East Coast meetup groups. She’ll be in DC: 4/11–4/13 Baltimore: 4/14 Philadelphia: 4/15–4/16 NYC: 4/17–4/21 Yale: 4/22–4/23 Northampton: 4/24–4/25 Boston: 4/26–5/1. The local groups have already taken care of having meetups at the right time, but she’s looking for people who could host her and drive her between cities . Email meetupsmingyuan@gmail.com if you can help. 6: Last week I tried to figure out the needs of community members in Russia and Ukraine. There are some great resources on the thread, but issues that still need solving: Seven Ukrainian refugees looking for remote work
June 18, 2025 · Original source
Since 2022, Alice has undertaken qualitative research in nine world regions: Mexico, Costa Rica, Brazil, Morocco, Italy, Spain, Britain, US, Poland, Turkey, India, Uzbekistan, South Korea and Hong Kong. Through this globally comparative analysis, she analyses the drivers and obstacles to gender equality. Gender interventions will be more impactful if they target locally binding constraints - in the Middle East, North Africa and South Asia, this is "the honour-income trade-off" (whereby male honour depends on female seclusion, and women tend to remain at home. Meanwhile, Latin America and the Caribbean face a different obstacle: pervasive violence elevates femicides. Over the past few years, she's held visiting appointments at Stanford, Chicago, and Yale, while providing policy advice to the World Bank, and sharing insights with a public audience via Substack (www.ggd.world). In April 2025, she gave a TedTalk on romantic love as an under-rated driver of gender equality.
Minnesota and Virginia also have legislation to enable cities to implement land value taxes. We are monitoring these efforts. There are a few other cities we are operating in. We have helped another organization prepare for a meeting in Tennessee by doing impact analysis of land value taxes in the city. We have presented to city officials in the City of South Bend who have expressed support for land value taxes. Finally, we are in conversation with a State Senator in Colorado who is a champion of land value taxes. Meanwhile, we have soft launched and developed the OpenAVMKit, which uses a unified schema to do assessment accuracy reports and automated valuation methods for any property tax data given. Valuation of land is the key binding constraint to successful implementation of land value taxes. We plan to be the leaders in this space with strong benchmarking capabilities and a repo that can enable the open-source community to make the best automated valuation methods. Along with these efforts, we have expanded the movement. We have posted to the Progress and Poverty Substack growing the subscriber base to around 5,000 subscribers. We have spoken to over 25 local advocates interested in working on land value taxes in their local communities. Yet, there is a long way to go. We need to start earning income through technical assistance contracts as our grant funding expires. We need to continue pushing for a state to implement, and we need to be prepared to tell the success story for when they do. 65: EN’s Work On Bacteriophage Therapy Our project is aimed at pioneering phage therapy in Nigeria, where limited resources/infrastructure have historically held back research in this field. Starting from the ground up, we are establishing the foundational systems needed to support a robust phage research ecosystem. So far, we’ve isolated 34 bacteriophages targeting Pseudomonas aeruginosa, an essential step toward building a comprehensive phage bank. This began with collecting a wide range of clinical Pseudomonas isolates, which we are now characterizing alongside the phages through genome sequencing and phenotypic assays including studies on phage stability across pH, temperature, and salinity ranges. Our long-term goal is to develop a phage-based hydrogel for treating diabetic wounds. On the regulatory front, we have secured approval from the Attorney General to register our nonprofit organization, the Centre for Phage Biology and Therapeutics. Additionally, we’re expanding into vaccine development; following a research stay in Prof. Roderick's lab at the University of Waterloo, we have initiated the design of a phage-based universal Salmonella vaccine aimed at covering all major serotypes—an urgent need underscored by Africa’s reliance on external vaccine sources during the COVID-19 pandemic. I have signed an MTA agreement with Roderick to use his phage-based vaccine platform patents to enable us to design vaccines against any common disease affecting us. This is only the beginning, but we are proud to be laying the scientific and institutional groundwork for homegrown phage innovation in Africa. Emergent Ventures funded EN before we did and deserves a lot of credit here also. 66: Create An Artificial Kidney For an implantable artificial kidney, the first essential component is a hemofilter designed to emulate the glomerulus. Critical requirements for this hemofilter include high permeability (to maximize flow for a given area), selectivity (specifically, the retention of albumin), and robust blood compatibility (ensuring sustained function over time). Our initial strategy focused on using negative surface charge to reduce fouling. I began by testing polyelectrolyte (PE) coatings on 24nm pore membranes featuring a negative terminal charge, similar to the glomerular barrier. These initial static tests, assessing platelet adsorption in whole blood, yielded positive outcomes for some polyelectrolytes, indicating potentially desirable blood compatibility. However, static test setups are not truly representative of dynamic in-vitro conditions and don't provide data on key parameters like permeability, fouling progression, or changes in membrane selectivity. To address these limitations, I designed and built a blood filtration setup. This system sustains human whole blood in circulation for 20 minutes, allowing us to analyze all the aforementioned parameters, as well as platelet activation markers. This has resulted in a fairly high-throughput system for evaluating any surface coating. I'm pleased to report this setup has been accepted for presentation at this year's European Society for Artificial Organs (ESAIO) conference. I am also currently working on a full manuscript, as I believe this system offers a viable way to partially replace animal experiments in our early-stage research, requiring only 1.2ml of human blood per run. Working with a PhD student (hired to support both this research and work on membrane substrates), we have continued testing these PE coatings, alongside PEG coatings, on our membranes. Here, we're finding that optimization of the coating layer is crucial. With the current PE coatings, we observe a permeability drop of about an order of magnitude compared to the base membrane, making them unsuitable for an implantable device in their present form. This is likely due to the specific nature of the initial PE layer, which we can modify. We also suspect there may be ingress of PE into the pores, meaning we're not achieving just a surface coating (our goal), but rather a very thick coating, which would explain the flux loss. Optimizing the coating process to control penetration depth is now a primary focus of my ongoing work. I am currently aiming for a flux of 20ul/min (as this is cap introduced by the protein gel layer anyway) but for it to be at this 'steady state' permeability without drop in permeability. I am also imaging the membranes after contact with SEM to see if there is indeed any platelet adsorption etc. Tugrul has the dubious honor of maybe being "the only person to climb a 4000m peak with severe kidney failure". To raise money and awareness for his artificial kidney project, he is running Climb Against Time, where he will climb 41 mountains over 4000m (13000 ft) this summer. He is looking for donors and climbing partners. 67: Add Tardigrade Genes To Human Cells The goal of this one was to make hybrid cells that are more resilient for research and certain medical applications. They report: The grant was to synthesize vectors for the expression of humanized tardigrade proteins that can be targeted to different areas of the cell. All the vectors were designed, generated, and transposed into human cells. The proteins all localize successfully (e.g. they match the designed target), with one exception (we are still working on validating it). We've done some stress testing with the trangenic cells, but haven't reached firm conclusions yet. We've further generated some multigene designs but have not yet transposed them into cells, but should shortly. We're hoping to submit a manuscript on the first round later this year. 68: Teach Forecasting To EU Policy-Makers The original project didn't work out, but our grantee (who still prefers to remain anonymous) is now working with an EU think tank pursuing the same agenda, and has been teaching forecasting workshops to policy-makers for the past two months. 69: Platform For Single-Cell Imaging They ended up unable to accept this grant and returned the money. 70: Open Source Polygenic Predictor For EA/IQ They have an update here. They think they have a predictor that can explain 12% of variance in intelligence, and they’re working on validating it and creating an easy-to-use website. 71: Improve Flu Vaccines The grant mainly funded agent based modelling to demonstrate the benefit of pre-existing immunity to pandemic influenza if and when a future pandemic occurs (academic publication will result). The original proposal was to attempt to influence the WHO influenza strain selection process. After attending WHO meetings and a global influenza conference, I believe this is not feasible. Stakeholder feedback was the potential short term negative effect on vaccine hesitancy is believed to outweigh the less tangible future benefit. Given the conservative nature of decision makers, pandemic vaccines are likely to remain research only. There are still green shoots of research into pandemic preparedness/prevention that I am continuing to work on. I'm working under the "Australians for Pandemic Prevention" brand of Good Ancestors, another group that ACX funded in 2024. 72: Scenario Analysis For Developing World Agricultural Programs In addition to the research and analysis funded by the grant, I’ve learned to code with LLMs and have built an MVP of the project. The app is being considered for further development by staff at a large international organization. 73: Further C’s Political Career C’s political career is going well, but he continues to think it wouldn’t be strategic to give more information publicly at this time. Lessons Learned I'm most impressed with our lobbying/advocacy organizations. In particular, Good Ancestors has gotten the Australian government to sign onto an international AI safety declaration, partner with various x-risk-related organizations, and (possibly) extend charity tax deductions to some EA causes that previously didn't have it - I think this on its own goes a substantial way to paying back the cost of all ACX Grants. Coalition to Modify NOTA has a kidney donation bill in front of Congress that the (very illiquid) prediction markets give a 45% chance of passing; if it works, it could save thousands of lives. The Georgists are partly responsible for bills making land value taxes slightly easier to implement in a handful of states. Good Science Project seems to have significantly improved science. Are lobbying organizations a better bet than other types of nonprofit (within the constraints of ACX Grants)? I'm not sure. It could just be that lobbyists are (naturally) better at playing themselves up and sounding successful than (for example) scientists, or that politicians are good at people-pleasing and make people feel heard and encouraged in a way that might not change overall policy later. Also, I recently talked to some grantmakers who funded a lobbying organization that superficially seems excellent, but they expressed concern it was net negative (!) by taking away oxygen and spotlight from potentially more effective orgs. So I am encouraged but wary. Animal welfare organizations were another standout success. Again, I don't know how to think about this - while I think our grantees were exceptional, there's also an issue where the scale of animal welfare challenges is so great, and work on them so neglected, that lots of organizations can save a million chickens here, or a million fish there, without particularly making a splash. On the one hand, this is exactly what effective altruism should be doing - exploring grants that are very high in linear utility even if they don't feel satisfying. On the other, they're unsatisfying - and also hard to assess retroactively. How many chickens should a good animal welfare grant save? Any realistic number will both be overwhelmingly large in absolute terms and far too small in relative terms. I'm most ambivalent about our science grants. Many of them say they are successful and can point to published papers which explain the science they did. But it's hard to judge whether anything useful has changed based on the science getting done. I know it's important to fund basic research and not just last-mile technology startups, but it's hard for a mini-grants program like this one to evaluate these kinds of abstract interventions. One disappointing result was that grants to legibly-credentialled people operating in high-status ways usually did better than betting on small scrappy startups (whether companies or nonprofits). For example, Innovate Animal Ag was in many ways overdetermined as a grantee - former Yale grad and Google engineer founder, profiled in NYT, already funded by Open Philanthropy - and they in fact did amazing work. On the other hand, there were a lot of promising ACX community members with interesting ideas who were going to turn them into startups any day now, but who ended up kind of floundering (although this also describes Manifold, one of our standout successes). One thing I still don't understand is that Innovate Animal Ag seemed to genuinely need more funding despite being legibly great and high status - does this screen off a theoretical objection that they don't provide ACX Grants with as much counterfactual impact? Am I really just mad that it would be boring to give too many grants to obviously-good things that even moron could spot as promising? Someone (I think it might be Paul Graham) once said that they were always surprised how quickly destined-to-be-successful startup founders responded to emails - sometimes within a single-digit number of minutes regardless of time of day. I used to think of this as mysterious - some sort of psychological trait? Working with these grants has made me think of it as just a straightforward fact of life: some people operate an order of magnitude faster than others. The Manifold team created something like five different novel institutions in the amount of time it's taken some other grantees to figure out a business plan; I particularly remember one time when I needed something, sent out a request to talk about it with two or three different teams, and the Manifold team had fully created the thing and were pestering me to launch a trial version before some of the other people had even gotten back to me. I take no pleasure in reporting this - I sometimes take a week or two to answer emails, and all of the predictions about my personality that this implies would be correct - but it's increasingly something that I look for and respect. A lot of the most successful grants succeeded quickly, or at least were quick to get on a promising track. Since everything takes ten times longer than people expect, only someone who moves ten times faster than people expect can get things done in a reasonable amount of time. In almost every case where I thought to myself “this is a cool idea, but I don’t know how it’s going to really pay off, as opposed to reaching a cool intermediate accomplishment and then stagnating”, this was a correct criticism, and I should have taken it more seriously. But I can’t rule out that these were good in vague and hard-to-measure ways that I should take more seriously. This one is really self-serving, but in general when people were good communicators (or even bloggers) and wowed me with the writing-composition of their application, they turned out to be a good bet. And when people were hard to understand and annoying to communicate with, even if their ideas seemed good, they were less likely to pan out. Overall Thoughts The total cost of ACX Grants, both rounds, was about $3 million. Do these outcomes represent a successful use of that amount of money? Very naively, startups originating from ACX Grants have about $50 million in value1. If ACX Grants is equivalent to a pre-seed funder, and pre-seed funders usually get ~5%, then if we were VCs we would have a portfolio worth $2.5 million. About 1/5 of ACX Grants were attempting to be market-valued startups, so if we assume the charitable portion did about as well as the startup portion, then the charity portion is “worth” $10 million. There’s some reason to expect this is too high, since much of the startup value came from one successful outlier. But there’s another reason to expect this is too low, since we were aiming at charity rather than market cap, and any actual market cap that our grantees got was an unexpected side effect. I’m treating this as a sanity check rather than as a real number. It’s harder to produce Inside View estimates, because so many of the projects either produce vague deliverables (eg a white paper that might guide future action) or intermediate results only (eg getting a government to pass AI safety regulations is good, but can’t be considered an end result unless those regulations prevent the AI apocalypse). Because we tend towards incubating charities and funding research (rather than last-mile causes like buying bednets), achieved measurable deliverables are thin on the ground. But here are things that ACX grantees have already accomplished: Improved the living/slaughter conditions of 30 million fish.
Yellow River

Yellow River is a recurring place in the Astral Codex Ten archive, appearing 2 times across 2 issues between May 21, 2021 and August 19, 2022. The archive places it in contexts such as "the Yellow is not navigable"; "When the Yellow River burst its dikes in 1587"; "after drunkenly falling into the Yellow River during a fishing expedition". It most often appears alongside China, Egypt, Europe.

Article page
Yellow River
Mention count
2
Issue count
2
First seen
May 21, 2021
Last seen
August 19, 2022
May 21, 2021 · Original source
Its geographic disadvantages are apparently numerous. China lacks much in the way of navigable rivers (“the Yellow is not navigable—in part due to its heavy engineering”) and frequent, heavy flooding and droughts on the North China Plain require strong irrigation efforts. The stunted trade that follows from these features – and the mass labor that it takes to make agriculture here work – has traditionally kept China from accumulating capital, much less industrializing. The Yangtze River in central China could provide that capital (Zeihan calls it “China’s sole navigable river”), but it’s seasonal and shallow and mountainous. It contributes to a “fractured nature” of central China that “complicate[s] northern China’s always vexing problem of internal disunity.”
August 19, 2022 · Original source
Shen had more mixed success in handling practical matters outside the realm of the literary bureaucracy. When the Yellow River burst its dikes in 1587, Shen did well overseeing the mitigation and rebuilding efforts, exerting his political influence to ensure that the best qualified people were chosen to lead the operation. On the other hand, also in 1587, Shen judged that a disagreement between a governor and a district director in China's northeastern province was a matter of no significance (like everything else that year) and ignored their dispute. This was a mistake. The governor and district director held opposite views on how to deal with a certain troublesome border chieftain named Nurhaci.
He took a great interest in the military, riding with his troops and even engaging in combat against the Mongols. But he left no heir when he died, after drunkenly falling into the Yellow River during a fishing expedition.
Yucatan

Yucatan is a recurring place in the Astral Codex Ten archive, appearing 2 times across 2 issues between August 25, 2023 and December 04, 2024. The archive places it in contexts such as "MERIDA, YUCATAN, MEXICO"; "I might as well have been talking about numerology in the Yucatan". It most often appears alongside Berlin, Chicago, France.

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Yucatan
Mention count
2
Issue count
2
First seen
August 25, 2023
Last seen
December 04, 2024
August 25, 2023 · Original source
MERIDA, YUCATAN, MEXICO Contact: Silvia Contact Info: silviafidelina[at]hotmail[dot]com Time: Thursday, October 21st, 10:00 AM Location: Centro de Estudios e Investigaciones Sociales y Culturales "Efraín Calderón Lara", calle 38 453 Jesús Carranza, 97109, Mérida, Yucatán, México. Coordinates: https://plus.codes/76GGX9JV+V6C Group Link: https://www.facebook.com/groups/lesswrongmerida/ Notes: Please RSVP on LessWrong so I know how much food to get. The languages of the meeting will be Spanish (preferred) and English (rescue tool).
December 04, 2024 · Original source
In 1970, Lapidus’ work was selected as the subject of an Architectural League of New York show and panel discussion entitled “Morris Lapidus: Architecture Of Joy”. Ordinarily this was an honor. In Lapidus’ case it was hard to say what it was. I was asked to be on the panel - probably, as I look back on it, with the hope that I might offer a “pop” perspective (This word, “pop”, had already come to be one of the curses of my life). The evening took on an uneasy, rather camp atmosphere - uneasy, because Lapidus himself had turned up in the audience. His work was being regarded not so much as architecture as a pop phenomenon, like Dick Tracy or the Busby Berkeley movies. I kept trying to put in my two cents’ worth about the general question of portraying American power, wealth, and exuberance in architectural form. I might as well have been talking about numerology in the Yucatan. The initial camp rush had passed, and the assembled architects began to give Lapidus’ work a predictable going-over. At the end, Lapidus himself stood up and said that the Soviets had once asked him to come to Russia and design some public housing and that they had been highly pleased with the results. Then he sat down. Nobody could quite figure it out, unless he was making a desperate claim of redeeming social significance . . . that might make him less radioactive.
Yuma

Yuma is a recurring place in the Astral Codex Ten archive, appearing 2 times across 2 issues between May 24, 2022 and October 13, 2022. The archive places it in contexts such as "built a 200-mile electric train from San Diego to Yuma"; ""It's not as hot as Yuma or Phoenix or [list of other too-hot cities]."". It most often appears alongside America, California, Los Angeles.

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Yuma
Mention count
2
Issue count
2
First seen
May 24, 2022
Last seen
October 13, 2022
May 24, 2022 · Original source
With the same money, built a 200-mile electric train from San Diego to Yuma [in Arizona], along the border [with Mexico], UNDERGROUND. Place a light rail system above ground. Now, you have cut off any possible illegal drug and human trafficking across the border, both above and below ground. And, you have a basic infrastructure to develop the 200+ miles of undeveloped land, to build new cities and millions of new homes, thus solving the housing crisis! A Double WIN-WIN, a secure border, and room to grow. IT'S THAT SIMPLE!
October 13, 2022 · Original source
Weather: It's not as hot as Yuma or Phoenix or [list of other too-hot cities]. It's still too hot.
Yaba

Yaba is a recurring place in the Astral Codex Ten archive, appearing 1 times across 1 issues between April 10, 2022 and April 10, 2022. The archive places it in contexts such as "University of Lagos, Yaba, Lagos". It most often appears alongside 1022 High St. Blue House w/red porches, 11:11 Cafe, 1548 NE 15th Ave.

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Yaba
Mention count
1
Issue count
1
First seen
April 10, 2022
Last seen
April 10, 2022
April 10, 2022 · Original source
LAGOS, NIGERIA Contact: Damola (social@damolamorenikeji.com) Date: May 4 Time: 12:12 PM Coordinates: https://plus.codes/6FR5G97X+62 Location: Alvan Ikoku Gardens, 1 Alvan Ikoku Road, University of Lagos, Yaba, Lagos. (We’ll be sitting close to the second tree).
Yadavagiri

Yadavagiri is a recurring place in the Astral Codex Ten archive, appearing 1 times across 1 issues between March 25, 2025 and March 25, 2025. The archive places it in contexts such as "Location: ... Cheluvamba Park on KRS Road in Yadavagiri". It most often appears alongside 10 E Main Street, Fairborn 45324, 11841 Wagner Street, Culver City, 13 Mile road.

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Yadavagiri
Mention count
1
Issue count
1
First seen
March 25, 2025
Last seen
March 25, 2025
March 25, 2025 · Original source
Contact: Chetan Contact Info: witnwisdumb[a t]gmail[period]com Time: Saturday, April 19th, 5:00 PM Location: I'll be at the gazebo at the centre of Cheluvamba Park on KRS Road in Yadavagiri. I will be wearing a white shirt, and standing next to an A4-sized sign with "ACX MEETUP" on it. Coordinates: https://plus.codes/7J4R8JCP+FW Notes: Please RSVP via email.
Yan

Yan is a recurring place in the Astral Codex Ten archive, appearing 1 times across 1 issues between September 01, 2023 and September 01, 2023. The archive places it in contexts such as "the Liege of Zheng overcame Duan at Yan". It most often appears alongside 536 BC, ACX, Ai Jiang.

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Yan
Mention count
1
Issue count
1
First seen
September 01, 2023
Last seen
September 01, 2023
September 01, 2023 · Original source
In summer, in the fifth month, the Liege of Zheng overcame Duan at Yan.
Yangtze River

Yangtze River is a recurring place in the Astral Codex Ten archive, appearing 1 times across 1 issues between May 21, 2021 and May 21, 2021. The archive places it in contexts such as "The Yangtze River in central China could provide that capital". It most often appears alongside 1992 treaty, ACX, Africa.

Reference entry
Yangtze River
Mention count
1
Issue count
1
First seen
May 21, 2021
Last seen
May 21, 2021
May 21, 2021 · Original source
Its geographic disadvantages are apparently numerous. China lacks much in the way of navigable rivers (“the Yellow is not navigable—in part due to its heavy engineering”) and frequent, heavy flooding and droughts on the North China Plain require strong irrigation efforts. The stunted trade that follows from these features – and the mass labor that it takes to make agriculture here work – has traditionally kept China from accumulating capital, much less industrializing. The Yangtze River in central China could provide that capital (Zeihan calls it “China’s sole navigable river”), but it’s seasonal and shallow and mountainous. It contributes to a “fractured nature” of central China that “complicate[s] northern China’s always vexing problem of internal disunity.”
Yangtze Valley

Yangtze Valley is a recurring place in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 17, 2021 and June 17, 2021. The archive places it in contexts such as "ecological conditions of the Yangtze Valley and regions farther south". It most often appears alongside Africa, antelope, August Hirsch.

Reference entry
Yangtze Valley
Mention count
1
Issue count
1
First seen
June 17, 2021
Last seen
June 17, 2021
June 17, 2021 · Original source
Yellow River Basin The Han Dynasty never made it very far south towards the Yangtze. Political and military obstacles were relatively unimportant, and the climate and land meant longer and more productive growing seasons for agriculture. The Yangtze also has more predictable and manageable flood plains. Yangtze Valley is prettier too. Why not extend civilization southward? In McNeill’s words “for in moving southward and into better farming regions, Chinese pioneers were also climbing a rather steep disease gradient!” The climatic gradient is steep, like New England to Florida, in a shorter geographic distance. For a Chinese peasant, the mutually tolerable accommodation with the state and with the microparasites of the Yellow River Valley was maintainable. But more microparasitic intensity made the balance unmaintainable. The Han Dynasty and Confucianism really only worked at a certain latitude. By the way, guess which major Chinese city is on the Yangtze? (You can look back at the map.) In contrast to the Ganges Valley in India, with a civilization and farming starting around 600 BC but remained unstable and never consolidated. The Ganges Valley is hugely productive agriculturally but also warmer and wetter than China’s southern Yangtze Valley. “Classical Indian civilization thus took form under climatic and (presumed) disease conditions that the early Chinese found too much to bear.” It took a long time for China to populate the Yangtze River basin- biological accommodation to a microparasitic climate will take a long time. By that time, around 1200 AD, there is also evidence the Sung Dynasty was a less powerful and less demanding macroparasite. “To achieve such a mass population [100 million by A.D.1200] two things were needed: a suitable microparasistic accommodation to the ecological conditions of the Yangtze Valley and regions farther south, and a regulated macroparasitism that left enough of their product with the Chinese peasants so that they could sustain a substantial rate of natural increase over several generations.” Epistemic Status: A convincing narrative with zero evidence McNeill explicitly and regularly reminds the reader that this overarching thesis has little to no evidence. But it does have lots of examples. It’s the same problem that most overarching histories of humanity face: lack of documentation. Except this time it’s lack of documentation 10,000 years ago of something we discovered existed 300 years ago and is invisible without a microscope. In some way, though, this complete lack of documentation makes his case stronger- the invisible forces are stronger than the visible ones. We all kind of knew the narrative that the Spanish decimated the Aztecs and Mayans with help of smallpox. I just never extended that logic towards humanity’s escape from Africa, the march of civilizations into the countryside, and what type of social structures worked best at certain ‘disease gradient’ latitudes. The documentation of the conquistadors was almost adequate to infer disease as a massive influence. But earlier medical records and writings lack such detail. When McNeill contrasts this force of microparasitism balancing with and against the adequately vague force of macroparasitism, it’s hard not to nod your head and agree. McNeill provides as much detail and admits lack of detail as possible. The book is about on fifth footnotes. But the most convincing arguments for his narrative is the sum of parts that make up the narrative. I’m going to just list a few more examples that fit his framework because they are all interesting and also paint a more convincing picture of the importance microparasitism played in human history. The way that Europeans decimated Native Americans with smallpox blankets has been a key driver in ancient civilization expansion. The moment the city folk come in contact with tribes, smaller towns, anyone in the countryside they also bring the city folk diseases. This makes civilization expansion fundamentally easier.
Yekaterinburg

Yekaterinburg is a recurring place in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 04, 2023 and August 04, 2023. The archive places it in contexts such as "When the candidate tried to hold a campaign event in Yekaterinburg, the largest city in the Urals". It most often appears alongside Alexander Alexandrov, Berlin, City of Leningrad.

Reference entry
Yekaterinburg
Mention count
1
Issue count
1
First seen
August 04, 2023
Last seen
August 04, 2023
August 04, 2023 · Original source
During the campaign, opposition candidates constantly encountered refusals to print their campaign material, air their commercials, or even rent them space for campaign events. Yana Dubeykovskaya, who managed the campaign of nationalist-leftist economist Sergei Glayev, told me that it took days to find a printing plant willing to accept Glazyev’s money. When the candidate tried to hold a campaign event in Yekaterinburg, the largest city in the Urals, the police suddenly kicked everyone out of the building, claiming there was a bomb threat. In Nizhny Novgorod, Russia’s third-largest city, electricity was turned off when Glazyev was getting ready to speak - and every subsequent campaign event in that city was held outdoors, since no one was willing to rent the pariah candidate.
Yellow River Valley

Yellow River Valley is a recurring place in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 17, 2021 and June 17, 2021. The archive places it in contexts such as "Around 600 BC extensive farming started in the Yellow River Valley". It most often appears alongside Africa, antelope, August Hirsch.

Reference entry
Yellow River Valley
Mention count
1
Issue count
1
First seen
June 17, 2021
Last seen
June 17, 2021
June 17, 2021 · Original source
Around 600 BC extensive farming started in the Yellow River Valley. It took enormous collective engineering effort to build canals, irrigation systems, and flood controls to turn the vast flood plain into a productive carpet of rice paddies. Chronic warfare ended around 200 BC with consolidation of power in the Han Dynasty. This introduced a double layer of macroparasitism: private landowners and the Emperor both demanded taxes be paid. This was still better than tumultuous chronic warfare. This coincided with another powerful factor in the macroparasistic balance: Confucianism. The ideals propagated “a culture among imperial officials and private landowners internalized an ethic that strenuously restrained arbitrary or innovative use of power.”
This system seemed to work. “A remarkably stable and long-lasting balance was achieved within Chinese society between peasant farmers and the two social classes most directly parasitic upon them. This balance survived, with some important elaborations but not real structural breaks, until the twentieth century. The system flourished throughout the Yellow River Valley, and eventually beyond.
Yellow River Basin The Han Dynasty never made it very far south towards the Yangtze. Political and military obstacles were relatively unimportant, and the climate and land meant longer and more productive growing seasons for agriculture. The Yangtze also has more predictable and manageable flood plains. Yangtze Valley is prettier too. Why not extend civilization southward? In McNeill’s words “for in moving southward and into better farming regions, Chinese pioneers were also climbing a rather steep disease gradient!” The climatic gradient is steep, like New England to Florida, in a shorter geographic distance. For a Chinese peasant, the mutually tolerable accommodation with the state and with the microparasites of the Yellow River Valley was maintainable. But more microparasitic intensity made the balance unmaintainable. The Han Dynasty and Confucianism really only worked at a certain latitude. By the way, guess which major Chinese city is on the Yangtze? (You can look back at the map.) In contrast to the Ganges Valley in India, with a civilization and farming starting around 600 BC but remained unstable and never consolidated. The Ganges Valley is hugely productive agriculturally but also warmer and wetter than China’s southern Yangtze Valley. “Classical Indian civilization thus took form under climatic and (presumed) disease conditions that the early Chinese found too much to bear.” It took a long time for China to populate the Yangtze River basin- biological accommodation to a microparasitic climate will take a long time. By that time, around 1200 AD, there is also evidence the Sung Dynasty was a less powerful and less demanding macroparasite. “To achieve such a mass population [100 million by A.D.1200] two things were needed: a suitable microparasistic accommodation to the ecological conditions of the Yangtze Valley and regions farther south, and a regulated macroparasitism that left enough of their product with the Chinese peasants so that they could sustain a substantial rate of natural increase over several generations.” Epistemic Status: A convincing narrative with zero evidence McNeill explicitly and regularly reminds the reader that this overarching thesis has little to no evidence. But it does have lots of examples. It’s the same problem that most overarching histories of humanity face: lack of documentation. Except this time it’s lack of documentation 10,000 years ago of something we discovered existed 300 years ago and is invisible without a microscope. In some way, though, this complete lack of documentation makes his case stronger- the invisible forces are stronger than the visible ones. We all kind of knew the narrative that the Spanish decimated the Aztecs and Mayans with help of smallpox. I just never extended that logic towards humanity’s escape from Africa, the march of civilizations into the countryside, and what type of social structures worked best at certain ‘disease gradient’ latitudes. The documentation of the conquistadors was almost adequate to infer disease as a massive influence. But earlier medical records and writings lack such detail. When McNeill contrasts this force of microparasitism balancing with and against the adequately vague force of macroparasitism, it’s hard not to nod your head and agree. McNeill provides as much detail and admits lack of detail as possible. The book is about on fifth footnotes. But the most convincing arguments for his narrative is the sum of parts that make up the narrative. I’m going to just list a few more examples that fit his framework because they are all interesting and also paint a more convincing picture of the importance microparasitism played in human history. The way that Europeans decimated Native Americans with smallpox blankets has been a key driver in ancient civilization expansion. The moment the city folk come in contact with tribes, smaller towns, anyone in the countryside they also bring the city folk diseases. This makes civilization expansion fundamentally easier.
Yi

Yi is a recurring place in the Astral Codex Ten archive, appearing 1 times across 1 issues between September 01, 2023 and September 01, 2023. The archive places it in contexts such as "a conquered Yi, or 'barbarian', state". It most often appears alongside 536 BC, ACX, Ai Jiang.

Reference entry
Yi
Mention count
1
Issue count
1
First seen
September 01, 2023
Last seen
September 01, 2023
September 01, 2023 · Original source
No direct inline source block was recovered for this mention.
Yokohama

Yokohama is a recurring place in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 21, 2024 and June 21, 2024. The archive places it in contexts such as "he goes to Yokohama and begins speaking to some of the merchants". It most often appears alongside Abenomics, An Encouragement of Learning, An Outline of a Theory of Civilization.

Reference entry
Yokohama
Mention count
1
Issue count
1
First seen
June 21, 2024
Last seen
June 21, 2024
June 21, 2024 · Original source
Having become one of the best students in Osaka, Fukuzawa is invited by a leading advocate of Dutch culture to open a school in Edo. His timing is very good. Soon after his arrival the Ansei Treaties are signed, which open up more of Japan’s ports to foreign ships. Excited to communicate with real foreigners, he goes to Yokohama and begins speaking to some of the merchants in residence there. Only he is saddened to realize that communication is impossible. Nobody speaks Dutch.
Yorktown

Yorktown is a recurring place in the Astral Codex Ten archive, appearing 1 times across 1 issues between April 19, 2021 and April 19, 2021. The archive places it in contexts such as "125 at Yorktown in 2005". It most often appears alongside #Resistance, 1/2019 government shut down, 538.

Reference entry
Yorktown
Mention count
1
Issue count
1
First seen
April 19, 2021
Last seen
April 19, 2021
April 19, 2021 · Original source
Needless to say, none of that happened. White supremacist activity in the United States never went beyond normal levels. After Charlottesville, the media tried to convince everyone that this was the promised spike in white supremacist activity, but it wasn't: there had been a bunch of white supremacist rallies larger than the Charlottesville protest throughout the Clinton, Bush, and Obama presidencies - the media just hadn't signal-boosted them as hard. 500 Nazis rallied at Lake Tahoe in 1996; 125 at Yorktown in 2005; 2000 in Budapest in 2009. Charlottesville's couple hundred were kind of par for the course - and all of these numbers are around the same number of people who eg attend Satanist rallies. After Charlottesville there were no further large white supremacist rallies, with an attempted Charlottesville II attracting about 20-30 people.
Yosemite

Yosemite is a recurring place in the Astral Codex Ten archive, appearing 1 times across 1 issues between October 13, 2022 and October 13, 2022. The archive places it in contexts such as "you can reach SF, Monterey, Yosemite, or Tahoe for a day trip". It most often appears alongside 1996 Illegal Immigration Reform and Immigrant Responsibility Act, 21st Century Salon, ACX.

Reference entry
Yosemite
Mention count
1
Issue count
1
First seen
October 13, 2022
Last seen
October 13, 2022
October 13, 2022 · Original source
Also, your categorization of the region as being a strategic location by which you can escape is spot on. People would talk about how great it is that you can reach SF, Monterey, Yosemite, or Tahoe for a day trip quite frequently.
Ypsilanti

Ypsilanti is a recurring place in the Astral Codex Ten archive, appearing 1 times across 1 issues between November 11, 2022 and November 11, 2022. The archive places it in contexts such as "last week in a mental hospital in Ypsilanti some schizophrenic’s thalamus". It most often appears alongside Aella, astral projection, Bayes.

Reference entry
Ypsilanti
Mention count
1
Issue count
1
First seen
November 11, 2022
Last seen
November 11, 2022
November 11, 2022 · Original source
What do we mean when we say that a certain perception (let’s say of Jesus) is a “hallucination”? We don’t mean anything about the experience the little homunculus in your neocortex is having. We mean that this particular pattern of nerve impulses from the thalamus - which is the same either way - doesn’t correspond to a referent in the external world. Maybe in 30 AD, St. Peter’s thalamus sent his neocortex the packet 3a09e1508ff7, which corresponded to some particular image of Jesus, and this wasn’t a hallucination because Jesus was standing right in front of him. And maybe last week in a mental hospital in Ypsilanti some schizophrenic’s thalamus sent his neocortex that exact same packet, 3a09e1508ff7, which corresponds to the exact same perception of a vision of Jesus, but in that case it was a hallucination, because Jesus wasn’t there.
Yuc.

Yuc. is a recurring place in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 26, 2022 and August 26, 2022. The archive places it in contexts such as "Location: Parque Gardenia, C. 65-A, Residencial Floresta, 97309 Mérida, Yuc". It most often appears alongside 't Heem, 10/40 Coffee, 11841 Wagner St., Culver City.

Reference entry
Yuc.
Mention count
1
Issue count
1
First seen
August 26, 2022
Last seen
August 26, 2022
August 26, 2022 · Original source
SÃO PAULO, BRAZIL Contact: [Update on 2025-02-03: Removed at organizers’s request] Time: Saturday, September 10, 2:00 PM Location: Ibirapuera Park in Praca do Porquinho. I will be wearing a white t-shirt, be very tall and have a sign. Coordinates: 588MC85Q+6X Event link(s): LessWrong BOGOTÁ, COLOMBIA Contact: Dan P, shorty[dot]george[dot]productions[at]gmail[dot]com Time: Sunday, September 18, 4:00 PM Location: Illy Cafe, Kr 15 with Park Virrey. Sign will say ACX Coordinates: 67P7MWFW+3F7 Event link(s): LessWrong MEDELLÍN, COLOMBIA Contact: HP, hp-med-acx[at]proton[dot]me Time: Sunday, September 18, 5:00 PM Location: Hija Mia Nomada Coordinates: 67R66C7G+8V Event link(s): LessWrong MÉRIDA, MEXICO Contact: Mati Roy, mathieu[dot]roy[dot]37[at]gmail[dot]com, Facebook Time: Sunday, August 28, 5:00 PM Location: Parque Gardenia, C. 65-A, Residencial Floresta, 97309 Mérida, Yuc. Coordinates: 76HG2C7X+8F Event link(s): LessWrong, Facebook event Group info: Facebook group Notes: Please let me know if you'll be coming. MEXICO CITY, MEXICO Contact: Calcifer, fagarrido[at]gmail[dot]com, Discord: Francisco (Mexico City)#0227 Time: Saturday, September 10, 4:00 PM Location: Comedor de los Milagros. I'll be wearing a green shirt and will carry a 'ACX/CDMX Meetup' sign. Coordinates: 76F2CR6P+37 Event link(s): LessWrong Group info: We are a rather new group. We've been meeting sporadically since April, and we recently settled on a formal twice-per-month frequency. We have a WhatsApp group which we use mostly for coordination purposes. Send me an email if you want in. Notes: If possible, RSVP on Less Wrong to get a sense of how many people to expect. Feel free to come if you haven't RSVP'd, though! PUNTA DEL ESTE, URUGUAY Contact: Manuel, acx[at]maraoz[dot]com Time: Saturday, September 24, 5:00 PM Location: Borneo Coffee, patio del fondo. Ruta 10, 20001 La Barra, Departamento de Maldonado, Uruguay Coordinates: 48Q734PQ+58 Event link(s): LessWrong
Yunnan province

Yunnan province is a recurring place in the Astral Codex Ten archive, appearing 1 times across 1 issues between July 30, 2022 and July 30, 2022. The archive places it in contexts such as "The areas where viruses most similar to SARS-CoV-2 are found in nature are Yunnan province and Laos". It most often appears alongside 1950s influenza strain, 1977 influenza pandemic, 1992 scientific investigation.

Reference entry
Yunnan province
Mention count
1
Issue count
1
First seen
July 30, 2022
Last seen
July 30, 2022
July 30, 2022 · Original source
Photograph of the famous Latané and Darley experiment, cerca 1968. So, what could those participants have been thinking? Maybe something like: Hmm, why’s the room filling up with smoke? Is this a problem? *looks around the room* Well nobody else seems to care, so I guess not. Looking back at the early stages of the COVID-19 pandemic, I think maybe this is why so many of us didn’t think twice about the location of the initial outbreak. Hmm, is it kinda suspicious that this virus broke out near a major virology institute that works on bat coronaviruses? Should we maybe look into that? *looks around* Well nobody else seems to think so, so I guess not. I can’t speak for everyone else, but this was at least my mindset. I had vaguely heard something about how there was a virology research institute close to where the pandemic broke out, and that some conspiracy theorists were claiming it was the source of the virus. I looked around and noticed that nobody was really taking this idea seriously, so I figured I didn’t need to take it seriously either. Also, I was thinking something like: Eh, probably every major city has labs and research institutes doing this kind of research. And I’ll bet they purposely built the virology institute close to where these viruses occur in nature, to give them easy access for sampling. Well, it turns out both of these things are wrong. The type of research conducted at the Wuhan Institute of Virology (WIV) is pretty rare and specialized. It includes things like creation of chimeric coronaviruses [1, 2], infecting humanized mice with bat coronaviruses, and other types of gain of function research, which Chan and Ridley devote a chapter to. The WIV is one of only a few institutions in the world doing this type of research. It’s not the case, as I had assumed, that every major university has a couple labs doing similar work. So it does seem like a pretty remarkable coincidence that the outbreak happened in Wuhan. But maybe they purposely built the Wuhan Institute of Virology close to where these viruses are found in nature? Well, this also turns out to be wrong. The areas where viruses most similar to SARS-CoV-2 are found in nature are Yunnan province and Laos, which are more than a thousand kilometers away from Wuhan. The authors put this distance in perspective by noting that it’s more than the distance between Orlando and NYC. Image source: https://www.bloomberg.com/news/features/2020-12-30/china-is-making-it-harder-to-solve-the-mystery-of-how-covid-began If SARS-CoV-2 originated in an animal somewhere around the Yunnan / Laos area, how did it make it all the way to Wuhan without leaving a trail along the way? 4. The story of RaTG13 Although I enjoyed the book, I do have one pretty major criticism. The authors repeatedly make the claim that a virus called RaTG13, which was being studied at the WIV before the pandemic, is the closest known genetic match to SARS-CoV-2. But this claim is outdated and no longer correct. In September 2021 researchers identified a virus called BANAL-52 in Laos that’s a 96.8% match to SARS-CoV-2, closer than RaTG13’s 96.2% match. (Important note: a 96.8% match is still a long way off in genomic space, and does not imply that this is the same virus as SARS-CoV-2, or even necessarily a progenitor.) At first I thought maybe the authors didn’t mention BANAL-52 because it was discovered after the book was published, but this isn’t the case – Viral was published November 16, 2021, nearly two months after the discovery of BANAL-52 was published. Although I’m writing an overall-positive review here, I don’t want to go easy on the book where serious criticism is warranted. It’s completely unacceptable that BANAL-52 wasn’t mentioned. Even if it would have been inconvenient from a publishing standpoint, the authors should have rewritten the RaTG13 chapter, or at least included an addendum about the discovery of BANAL-52. With that being said, I think the story of RaTG13 is still interesting and important, so I’ll give a quick summary here. At the start of the pandemic in 2020, SARS-CoV-2 was quickly sequenced, and the full genome sequence was published by Dr. Shi Zhengli’s team at the WIV. In this paper, they also briefly mentioned that the genome was a 96.2% match with another bat coronavirus called RaTG13 – the closest known match at the time. Oddly, the mention of RaTG13 did not include any reference, footnote, or link to any previously published sequence. Although the WIV didn’t provide details on this mysterious RaTG13 virus, a group of internet volunteers, including both amateurs as well as professional scientists working in their free time, began to investigate. This loose collection of open-source researchers, called DRASTIC, uncovered a medical thesis describing an outbreak of a mysterious disease in 2012. Six men who had been working in a bat-infested mine in Mojiang County, China, fell ill and were admitted to a hospital with symptoms including dry coughs, shortness of breath, fevers, muscle aches, headaches, and fatigue. Three of the men eventually died of this mysterious illness. In the years following this incident, teams of researchers (including a team led by Dr. Shi Zhengli of the WIV) were sent to investigate the cause of this illness and collect samples from the Mojiang mine. This sampling led to the discovery of a novel SARS-like coronavirus in 2013, and a part of its genomic sequence was published under the name BtCoV/4991 in 2016. The DRASTIC researchers discovered that RaTG13 was genetically identical to the BtCoV/4991 sequence from the Mojiang mine – it was the same virus, and had just been renamed for some reason, without any public record of the change. They also discovered that at least eight other closely related coronaviruses were also sampled from this mine and brought to the WIV. Although unhelpful throughout the investigation, the WIV eventually verified these facts when pressed on them, and an addendum was added to the original paper confirming DRASTIC’s account of the origin of RaTG13. So what should we make of this? Well, as I mentioned before, RaTG13 is no longer the closest known genetic match to SARS-CoV-2, so maybe the whole story is less important as it pertains to the origin of the pandemic. But the discovery of BANAL-52 doesn’t really resolve things either [2]. Laos is very far away from Wuhan (actually even further than Yunnan), so we’re left with the same question as before – how did SARS-CoV-2 make it all the way to Wuhan from such a distant natural reservoir without leaving a trail along the way? 5. Lack of institutional transparency and competence A lot of the book is devoted to criticizing the Chinese government’s lack of transparency during the pandemic. Some brief examples: In the early days of the initial outbreak in Wuhan, hundreds of people were investigated and punished for the crime of “spreading rumors”. This included whistleblowing doctors who attempted to warn others [3] about the spread of the disease and its human-to-human transmission, which was being denied by the Chinese government at the time.
Image source: https://www.bloomberg.com/news/features/2020-12-30/china-is-making-it-harder-to-solve-the-mystery-of-how-covid-began If SARS-CoV-2 originated in an animal somewhere around the Yunnan / Laos area, how did it make it all the way to Wuhan without leaving a trail along the way? 4. The story of RaTG13 Although I enjoyed the book, I do have one pretty major criticism. The authors repeatedly make the claim that a virus called RaTG13, which was being studied at the WIV before the pandemic, is the closest known genetic match to SARS-CoV-2. But this claim is outdated and no longer correct. In September 2021 researchers identified a virus called BANAL-52 in Laos that’s a 96.8% match to SARS-CoV-2, closer than RaTG13’s 96.2% match. (Important note: a 96.8% match is still a long way off in genomic space, and does not imply that this is the same virus as SARS-CoV-2, or even necessarily a progenitor.) At first I thought maybe the authors didn’t mention BANAL-52 because it was discovered after the book was published, but this isn’t the case – Viral was published November 16, 2021, nearly two months after the discovery of BANAL-52 was published. Although I’m writing an overall-positive review here, I don’t want to go easy on the book where serious criticism is warranted. It’s completely unacceptable that BANAL-52 wasn’t mentioned. Even if it would have been inconvenient from a publishing standpoint, the authors should have rewritten the RaTG13 chapter, or at least included an addendum about the discovery of BANAL-52. With that being said, I think the story of RaTG13 is still interesting and important, so I’ll give a quick summary here. At the start of the pandemic in 2020, SARS-CoV-2 was quickly sequenced, and the full genome sequence was published by Dr. Shi Zhengli’s team at the WIV. In this paper, they also briefly mentioned that the genome was a 96.2% match with another bat coronavirus called RaTG13 – the closest known match at the time. Oddly, the mention of RaTG13 did not include any reference, footnote, or link to any previously published sequence. Although the WIV didn’t provide details on this mysterious RaTG13 virus, a group of internet volunteers, including both amateurs as well as professional scientists working in their free time, began to investigate. This loose collection of open-source researchers, called DRASTIC, uncovered a medical thesis describing an outbreak of a mysterious disease in 2012. Six men who had been working in a bat-infested mine in Mojiang County, China, fell ill and were admitted to a hospital with symptoms including dry coughs, shortness of breath, fevers, muscle aches, headaches, and fatigue. Three of the men eventually died of this mysterious illness. In the years following this incident, teams of researchers (including a team led by Dr. Shi Zhengli of the WIV) were sent to investigate the cause of this illness and collect samples from the Mojiang mine. This sampling led to the discovery of a novel SARS-like coronavirus in 2013, and a part of its genomic sequence was published under the name BtCoV/4991 in 2016. The DRASTIC researchers discovered that RaTG13 was genetically identical to the BtCoV/4991 sequence from the Mojiang mine – it was the same virus, and had just been renamed for some reason, without any public record of the change. They also discovered that at least eight other closely related coronaviruses were also sampled from this mine and brought to the WIV. Although unhelpful throughout the investigation, the WIV eventually verified these facts when pressed on them, and an addendum was added to the original paper confirming DRASTIC’s account of the origin of RaTG13. So what should we make of this? Well, as I mentioned before, RaTG13 is no longer the closest known genetic match to SARS-CoV-2, so maybe the whole story is less important as it pertains to the origin of the pandemic. But the discovery of BANAL-52 doesn’t really resolve things either [2]. Laos is very far away from Wuhan (actually even further than Yunnan), so we’re left with the same question as before – how did SARS-CoV-2 make it all the way to Wuhan from such a distant natural reservoir without leaving a trail along the way? 5. Lack of institutional transparency and competence A lot of the book is devoted to criticizing the Chinese government’s lack of transparency during the pandemic. Some brief examples: In the early days of the initial outbreak in Wuhan, hundreds of people were investigated and punished for the crime of “spreading rumors”. This included whistleblowing doctors who attempted to warn others [3] about the spread of the disease and its human-to-human transmission, which was being denied by the Chinese government at the time.