Mexico is a recurring place in the Astral Codex Ten archive, appearing 39 times across 39 issues between April 14, 2021 and April 01, 2026. The archive places it in contexts such as "list of Best Practice Peer Countries including: Mexico"; ""Mexico tried, but was screwed over by geography and racial inequality""; "Chapingo, Mexico". It most often appears alongside India, United States, Canada.
- Article page
- Mexico
- Mention count
- 39
- Issue count
- 39
- First seen
- April 14, 2021
- Last seen
- April 01, 2026
- https://astralcodexten.substack.com/p/dictator-book-club-xi-jinping
- https://forum.effectivealtruism.org/posts/KkPo9cpLThWyd7yju/save-the-date-eagx-latam
- https://www.astralcodexten.com/p/dictator-book-club-xi-jinping
- https://www.astralcodexten.com/p/secrets-of-the-great-families
- https://www.metaculus.com/questions/10634/xi-jinping-re-elected-in-2022/
- https://www.neonarrative.us/p/an-interview-with-scott-alexander
- https://x.com/AppSpartacus
- Prospectus On Próspera
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Australia, Austria, Belgium, Canada, Chile, Denmark, Dubai, Estonia, Finland, France, Germany, Iceland, Ireland, Hong Kong, Israel, Italy, Japan, South Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Spain, Sweden, Singapore, Switzerland, United Kingdom, and United States of America
Other countries tried the Standard Model but couldn't quite get it to work. Mexico tried, but was screwed over by geography and racial inequality. Mexico's industrial heartland is in the center of the country, in the mountains near Mexico City, and there wasn't a great way to get products to the coast where they could be traded with Europe. Also, its racial caste system made the elites nervous about educating the (mostly mestizo) masses, so they were never able to really get the education prong worked out (the US had the same issue with blacks, but blacks are only 12% of Americans, and mestizos are ~80% of Mexicans). The independent countries of western South America had similar problems. Russia tried this a little, but also had crappy geography and serfdom. Other countries were mostly European colonies at this point; their colonial masters did a pretty good job with Prong 1 (especially building railroads), but absolutely banned Prong 2 and were generally weak on the others.
And how does globalization fit into this picture? New parts of existing countries are able to develop relatively quickly - for example, when the US took California from Mexico, it eventually converged to US (not Mexican) standards of living. If a New California were to rise out of the Pacific Ocean just west of the regular one, and Americans were to colonize it, I would expect it to also converge to normal US standards of living eventually. Why? In 2021, New California has nothing, and (eg) India has much more than nothing. How come we are more certain that New California will soon get First World living standards than that India will? If the answer is something like “because American companies can expand to New California and trade with other Americans without tariffs”, doesn’t that mean that if India invites US companies in, lowers tariffs, and has good institutions - then they too can quickly converge to US standards of living? But isn’t that the opposite of GED:VSI’s thesis? I’m not saying they’re wrong - I assume development economists know what they’re talking about - but it confuses me and this book didn’t give me a great answer.
In college, Borlaug first studies forestry, then gets seduced by plant biologist Elvin Charles Stakman’s personal crusade against stem rust, a fungus that blights wheat crops and, at the time, critically endangered the global wheat supply. After a brief stint as an industry research scientist at DuPont, in the 1940s Borlaug ends up as the unlikely candidate to lead a nascent rust study in Chapingo, Mexico. Borlaug is sent by his superiors essentially to sell the Mexican farmers on the more productive (but still rust-susceptible) American wheat strains. Instead, he takes the underfunded and under-resourced Chapingo project into an unexpected direction: after seeing that rust and variability in growing conditions would hamper any attempt to increase wheat crop yields in Mexico, he begins a series of years-long Mendelian cross-breeding pilots in four different locations of Mexico to find a prodigious, hardy wheat strain that is not only immune to rust, but can survive and thrive virtually no matter the location or growing conditions.
Despite lack of experience, no knowledge of the molecular mechanisms of genetics (which were yet to be discovered), skepticism from his superiors, suspicion from the Mexican farmers, and even Vogt’s attempt to shut the program down, Borlaug perseveres. After years of painstakingly cross-breeding hundreds of wheat strains from all around the world by hand, he finally stumbles on his miracle wheat, which sextuples the yield of the previous wheat cultivars in Mexico and turns the country into a wheat exporter virtually overnight. With Borlaug’s "package" of new wheat (and later, rice), modern synthetic fertilizer, and state-of-the-art agricultural science, a global famine – threatening not just Mexico, but the billions of people worldwide experiencing the post-WWII population boom – is averted, and farmers around the world can now feed orders of magnitude more people with less effort. For this, he wins the Nobel prize and timeless love and admira– ...haha, just kidding. He does win a Nobel prize, but I think it’s safe to say that while some highly educated folks in some niche fields know what the Green Revolution is, outside of a few unassuming places in the Midwest, nobody is going to run into a statue of this guy in their town square.
If you look around, you’ll see lots of other COVID-like problems out there that are quietly but inexorably claiming lives and dragging down average utility worldwide – poverty, homelessness, economic stagnation – that Wizards haven’t found good solutions for. I don’t think it’s from a lack of trying; I think we may have hit a carrying capacity limit on our ability to deal with complexity. Systems in the modern world are complex. No, really complex. No, even more complex than that. Consider all of the different systems that interacted to form the giant clusterfuck that is the COVID-19 pandemic response: local politics, global politics, scientific knowledge production, scientific knowledge dissemination, the media, social media, business, regulations, logistics chains. Each of these contain multitudes of factors that no single human on earth, not even the Normanest of Borlaugs, could keep straight in his or her head and "fix" with a single quick hack like a better strain of wheat. And these complex systems aren’t just statically complex – they seem to be getting more complex over time in their interactions with each other. In the 1960s, Borlaug’s new wheat strain was used by virtually all Mexican farmers a year after it was released commercially; if it had been created today, it probably would have sat on a shelf for a decade while various global FDA-like agencies dickered over whether it was safe or not and anti-GMO groups launched a thousand frankenwheat memes; you’d definitely never be able to buy it at Whole Foods.
Mexico declared bankruptcy in 1982; by the time the smoke cleared, average Mexican wages had fallen 40%. The rest of Latin America did little better. Communists suggested that the inevitable fall of capitalism was finally at hand.
Harvey comes across a little better when talking about debt crises in Mexico, Latin America, and beyond. My understanding here is something like: the Volcker Shock caused a sharp increase in the price of the US dollar. Latin American countries had taken out a lot of dollar-denominated debt, which (as the dollar rose) suddenly became much bigger. They had been prepared to pay off their old debts, but not their new, much-bigger debts, so they had to cut deals with their creditors. These were mostly American banks, and the American government was backing them. The banks and government, negotiating partly through the IMF, weren’t really willing to compromise and demanded quite a lot of the money back. But also, as a condition for what compromises they did make, they demanded these countries neoliberalize. The banks/US/IMF said this was so that they could break their addiction to debt and overspending, have functional economies, and be able to pay off what they owed eventually. Obviously Harvey isn’t buying it, and says it was a plot for the American rich to enhance their power, plus crushing all fair and decent systems that might have provided an alternative to the dystopia they were planning at home.
What the Mexico case demonstrated, however, was a key difference between liberal and neoliberal practice: under the former, lenders take the losses that arise from bad investment decisions, while under the latter the borrowers are forced by state and international powers to take on board the cost of debt repayment no matter what the consequences for the livelihood and well-being of the local population. If this required the surrender of assets toforeign companies at fire-sale prices, then so be it. This, it turnsout, is not consistent with neoliberal theory. One effect, as Duménil and Lévy show, was to permit US owners of capital to extract high rates of return from the rest of the world during the 1980s and 1990s (Figures 1.8 and 1.9). The restoration of power to an economic elite or upper class in the US and elsewhere in the advanced capitalist countries drew heavily on surpluses extracted from the rest of the world through international flows and structural adjustment practices.
In 1940s Texas, basically every type of election fraud was real: Dead people voting, county bosses writing down whatever numbers they wanted, Mexicans being hired to cross the border and vote, etc. By buying tens of thousands of votes, LBJ was almost able to close the gap between him and Coke Stevenson. That wasn't enough, so six days after the election, Luis Salas "found" 200 more votes for LBJ, giving him a margin of victory of 0.01%.
Why do I trust Caro? He's the kind of biographer who searches Mexico to find Luis Salas:
We didn’t just get tremendous economic growth though – we got “magical” results, but they were based on a one-time confluence of factors that “overwhelmed the normal rule that lots of twenty-and thirty-somethings make for an expensive-capital environment.” What were these one-time accelerants? He identifies the peace dividend – cuts in military spending that allowed capital to be put to more productive uses – as one such change, along with the emergent dominance of the US dollar, particularly boosted by Russian demand thanks to the collapse of their currency, and a later boost in demand thanks to the East Asian financial crisis. With the Europeans’ decision to eliminate national currencies (agreed upon in a 1992 treaty, with the Euro to be introduced in 1999), they became relatively unattractive, and the Euro itself (an “unprecedented experiment in pan-government planning”) was too risky. Many holders of European currencies switched to the US dollar, such that between 1994 and 2002 (“when the euro finally got some traction and the surge dialed back”) there was a $2 trillion increase in the money supply. Zeihan also points to a collapse in commodities prices influenced by the elimination of Russian demand, but continued Russian production of oil and other commodities, followed by a collapse in demand thanks to the East Asian financial crisis. This story of capital coming to the West (“allowing consumption-driven growth not simply to soar, but to explode”) is one of chance world events. However, the story of capital coming from the Boomer cohort is one of demographics. By the 2000s, they’re the mature workers of Zeihan’s four stages described above – and as the bulge in the demographic pyramid, they started flooding the world with capital. Accordingly, “The cost of credit plummeted to levels never before experienced.” Zeihan suggests that developed-world demographics are the cause of booms in places that haven’t been well-developed, from Southern Europe to Brazil, Russia, and India. But he says it’s quickly coming to an end; Boomer savings into stocks and bonds will be moving to low-risk instruments and then turning into withdrawals rather than savings, and the cohort behind them is too small to replace all of that capital. And it’s a worldwide phenomenon: In every single developed country there is currently an American-style population inversion between the about-to-retire and the about-to-be-mature-workers age groups. Japan’s Boomers bulge is a decade older than the American equivalent, while Spain’s is roughly fifteen years younger. Everyone else falls somewhere in between. It dictates a period of chronically low growth and high credit costs, just not on precisely the same time frame. The undeveloped world is that way because it can’t self-fund, so without foreign capital, their growth will come to an end. In sum, the 1990-2005 period of high growth and easy capital was a historical anomaly; “the post-Cold War financial flight was a once-in-a-generation event” and the demographic bulge that coincided with it won’t come around again for decades, if ever. 4 2: America’s incredible advantages As noted above, Zeihan really likes America’s position in the world. He likes its demographics (relative to other developed countries) and loves its geography. Taking the population question first, in America, “the demographic inversion is only a temporary development.” America is younger than the rest of the developed world, as it urbanized later and its enormous size made having kids easier despite that urbanization (i.e., the suburbs exist). This makes the demographic crunch a single-generation issue, as the Millennials are a huge cohort. And even if they weren’t, America assimilates immigrants more easily than other places – Zeihan attributes this to it being a “settler society” – which can help with demographic problems. The rest of the developed world doesn’t have similar cohorts following their massive Boomer and Gen-X analogues. Accordingly: While the American financial world will be past its period of maximum stress by 2030, for the rest of the world 2030 will simply be another year of an ever-deepening imbalance between retirees and taxpayers, with smaller and smaller generations coming up the ranks generating less and less growth. For the developed world beyond the United States—and even large portions of the developing world—chronic capital poverty and permanent recession will be the new normal from which there is no return. Together with America’s Millennial-led growth and abundant energy (there’s a chapter explaining how shale is a done deal that, as of the mid-2014 writing, already made America the world’s largest energy producer 5), by 2030 Zeihan sees it as practically the only country with an economy worth noting. Anyone who is familiar with American geography should see the argument that’s coming about that aspect of Zeihan’s model. Isn’t the Mississippi River a pretty big deal? And those oceans on the east and west coasts seem like nice borders. Indeed, while he gives us many reasons why there was always going to be an American superpower, geography is central to his story. He has lots to say about America’s internal river systems, farmland, and other geographic features. What mountain barriers exist are apparently better than in other countries in terms of allowing internal transport; the Rockies have major passes, several of which have large cities within them, and the easiest pass in the Appalachians featured America’s first National Road, 130 miles of buried logs that linked two rivers, and thus the east coast with the best farmland in the world. As we saw with his exposition on the Nile, Zeihan puts a lot of emphasis on the value of river systems. He argues that America’s waterway network alone should be sufficient for “global dominance.” The numbers he provides in support of this point are impressive. For example, “the Mississippi is only one of twelve major navigable American rivers. Collectively, all of America’s temperate-zone rivers are 14,650 miles long. China and Germany each have about 2,000 miles, France about 1,000. The entirety of the Arab world has but 120.” He praises US barrier islands that mitigate oceanic destruction and effectively create another river system, as well as the fact that the river system is an actual network. All of this gives America more internal waterways than the rest of the world combined. Thus, we get cheap transportation for “Nebraska corn or Tennessee whiskey or Texas oil or New Jersey steel or Georgia peaches or Michigan cars,” enabling savings that “can be used for whatever Americans (or their government) want, from iPhones to aircraft carrier battle groups.” America doesn’t have to spend on artificial infrastructure, like German roads and rails, but when it does, the competition from the rivers keeps transport costs low. Cheap internal transportation has other benefits. “It’s a recipe for small government and high levels of entrepreneurship,” as small government keeps taxes low, leaving people with plenty of capital. Some people may think of the American consumer with disdain, but it isn’t a new phenomenon. Zeihan points out that America has been the world’s largest consumer market “since shortly after the Civil War.” His observation about a robust food supply forming the base of any civilization bodes well for America, which apparently has the largest connected stretch of quality farmland in the world (the Midwest), the value of which is exponentially increased by the fact that it overlaps with so many of these amazing river systems. It isn’t just the Midwest that he gushes over. California’s Central Valley and the Sacramento River, and Washington and Oregon’s farmland with the Columbia and Snake Rivers get praise. The only major farmland more than 150 miles from a navigable waterway is some of the Great Plains near the Rockies. ***** Zeihan provides a reminder that national security is actually a thing, and that at its most basic level, it’s about protection against invasions. It was something of a shock reading about America’s land borders in that context. “As Santa Anna discovered during the Texas Independence War, there is no good staging location in (contemporary) Mexican territory that could strike at American lands.” And, “Canada’s border with the United States is much longer, more varied, and even more successful at keeping the two countries separated,” thanks to mountains and thick forests over much of it. The mid-continent lands are much more connected, but Zeihan frames these Canadian areas as basically American; they’re physically separated from Canada’s core eastern provinces, so trade with them is weaker than with the closer American states. Then there are the oceans. As much as Zeihan loves deserts for protection, he loves oceans more (particularly in a post-World War II world; more on that below). We get a story about the War of 1812 nearly splitting America into three when the British attacked Baltimore. America learned about “strategic vulnerability and sea approaches,” as the attack “on Baltimore—indeed, the entire war effort—would have been impossible without launching grounds in Canada and the Caribbean.” American foreign policy since then can be understood with respect to this lesson. Zeihan cites it as inspiration for America’s steps to make its ocean borders truly impenetrable, such as working to sever Canada from Britain, and the imperial-era acquisitions of Alaska, Hawaii, Midway, Puerto Rico, and de facto control of Cuba (preventing enemies from cutting off Mississippi River-based trade from the rest of the world). There’s more to Zeihan’s being awestruck by America than his analysis of its balance of transport advantages. He argues that America has been the world leader for agriculture, technology, finance, and industry since the Civil War, and runs through a litany of reasons for its preeminence: America is like a continent-sized island (because of its effective land borders), which is always going to be a more natural naval power than a more landlocked country.
MEXICO CITY, MEXICO (RSVP) Contact: Fornicad Cigarros, fagarrido[at]gmail[dot]com Time: 4:00 PM, Saturday, September 11 Location: Bosque de Chapultepec by the Canadian Totem Coordinates: https://w3w.co/spoiled.given.waving
I think the main difference is that there isn't a 3rd country at the USA-Mexico border and USA is the target country for immigrants anyway. Hungary is just one of a several countries on a route from Middle East to Western Europe, so if they make their wall slighly more inconvenient than the neighboring countries that's enough to sway the torrent of immigrants another way.
…A North American equivalent would be if there had been an agreement between Canada, US and Mexico that refugees could be returned to the country of “first entry” – which would usually be Mexico. For obvious reasons, Mexico would not have been happy with such an agreement (and EU countries bordering on non-EU countries, including bordering on the Mediterranean, have also tried – so far unsuccessfully- to change the Dublin agreement).
Click to expand. # is how many people were in the smallest relevant group (eg if there were 20 people in placebo and 10 in ivermectin, it was 10). Dose is ivermectin dose x number of days. Tested w/ is what drugs were given alongside ivermectin; compare is what drugs were in the “placebo” group (I excluded some very common things like paracetamol). %-PCR7 is what percent of patients had a negative PCR test (indicating recovery) after 7 days (though if 7 wasn’t available, I accepted anything from 6-12); the (I) and (P) are ivermectin and placebo groups. R is the ratio - green if statistically significant, red otherwise. DaysPCR is how many days it took to get a negative PCR test. Days to -sym are how many days it took symptoms to resolve. -outc is some serious negative outcome in the study, either clinical worsening, hospitalization, or death. I was inconsistent which one I chose, trying to pick whichever I thought struck a balance between high sample size and severity. Since this was almost never significant, I made it blue if it favored ivermectin and orange if it favored placebo (which it never did; there is no orange). Lowest p is the lowest p-value in the study for one of the headline results. 1o+ is whether the primary outcome was positive or not. I made this very quickly and unprincipledly and I am sure there are a lot of errors; please forgive me. Of studies that included any of the endpoints I recorded, ivermectin had a statistically significant effect on the endpoint 13 times, and failed to reach significance 8 times. Of studies that named a specific primary endpoint, 9 found ivermectin affected it significantly, and 12 found it didn’t. But that’s still pretty good. And “doesn’t affect to a statistically significant degree” doesn’t mean it doesn’t work. It might just mean your study is too small for a real and important effect to achieve statistical significance. That’s why people do meta-analyses to combine studies. And the ivmmeta people say they did that and it was really impressive. All of this is still basically what things would look like if ivermectin worked. But of course we can’t give every study one vote. We’ve got to actually look at these and see which ones are good and which ones are bad. So, God help us, let’s go over all thirty of the ivermectin studies in this top panel of ivmmeta.com. (if you get bored of this, scroll down to the section called “The Analysis”) The Studies Elgazzar et al: This one isn’t on the table above, but we can’t start talking about the others until we get it out of the way. 600 Egyptian patients were randomized into six groups, including three that got ivermectin. The ivermectin groups did substantially better: for example, 2 vs. 20 deaths in ivermectin group 3 vs. non-ivermectin group 4. There were various other equally impressive outcomes. Unfortunately, it’s all false. Some epidemiologists and reporters were able to obtain the raw data (it was password-protected, but the password was “1234”), and it was pretty bizarre. Some patients appeared to have died before the trial started; others were arranged in groups of four such that it seemed like the authors had just copy-pasted the same four patients again and again. Probably either the study never happened, or at least the data were heavily edited afterwards. You can read more here. A lot of the apparent benefit of ivermectin in meta-analyses disappeared after taking out this paper (though remember, this isn’t even on the table at the top of the post, so it doesn’t directly affect that). Since the Elgazzar debacle, a group of researchers including Gideon Meyerowitz-Katz, Kyle Sheldrake, James Heathers, Nick Brown, Jack Lawrence, etc, have been trying to double-check as many other ivermectin studies as possible. At least three others - Samaha, Carvallo, and Niaee - have similar problems and have been retracted. Those studies were all removed before I screenshotted the table above, and they’re not on there. But everybody is pretty paranoid right now and looking for fraud a lot harder than they might be in normal situations. Moving on: Chowdury et al: Bangladeshi RCT. 60 patients in Group A got low-dose ivermectin plus the antibiotic doxycycline, 56 in Group B got hydroxychloroquine (another weird COVID treatment which most scientists think doesn’t work) plus the antibiotic azithromycin. No declared primary outcome. Ivermectin group got to negative PCR a little faster than the other (5.9 vs. 7 days) but it wasn’t statistically significant (p = 0.2). A couple of other non-statistically-significant things happened too. 2 controls were hospitalized, 0 ivermectin patients were. This is a boring study that got boring results, so nobody has felt the need to assassinate it, but if they did, it would probably focus on both groups getting various medications besides ivermectin. None of these other medications are believed to work, so I don’t really care about this, but you could tell a story where actually doxycycline works great at addressing associated bacterial pneumonias, or where HCQ causes lots of side effects and that makes the ivermectin group look good in comparison, or whatever. Espitia-Hernandez et al: Mexican trial which is probably not an RCT - all it says is that “patients were voluntarily allocated”. 28 ended up taking a cocktail of low-dose ivermectin, vitamin D, and azithromycin; 7 were controls. On day ten, everyone (!) in the experimental group was PCR negative; everyone (!) in the control group was still positive. Also, symptoms in the experimental group lasted an average of three days; in the control group, more like 10. These results make ivermectin look amazingly super-good, probably better than any other drug for any other disease, except maybe stuff like vitamins for treatment of vitamin deficiency. Any issues? We don’t know how patients were allocated, but they discuss patient characteristics and they don’t look different enough to produce this big an effect size. The experimental group got a lot of things other than ivermectin, but I would be equally surprised if vitamin D or azithromycin cured COVID this effectively. It deviated from its preregistration in basically every way possible, but you shouldn’t be able to get “every experimental patient tested negative when zero control patients did” by garden-of-forking-paths alone! But this has to be false, right? Even the other pro-ivermectin studies don’t show effects nearly this big. In all other studies combined, ivermectin patients took an average of 8 days to recover; in Espitia-Hernandez, they took 3. Also, it’s pretty weird that the entire control group had positive PCRs on day 10 - in most other studies, a majority of people had negative PCRs by day 7 or so, regardless of whether they were control or placebo. Everything about this is so shoddy that I can easily believe something went wrong here. I don’t have a great understanding of this one but I don’t trust it at all. Luckily it is small and non-randomized so it will be easy to ignore going forward. I’m not saying this is related, but I’m not saying it *isn’t* related either. Carvallo et al: This one has all the disadvantages of Espitia-Hernandez, plus it’s completely unreadable. It’s hard to figure out how many patients there were, whether it was an RCT or not, etc. It looks like maybe there were 42 experimentals and 14 controls, and the controls were about 10x more likely to die than the experimentals. Seems pretty bad. On the other hand, another Carvallo paper was retracted because of fraud: apparently the hospital where the study supposedly took place said it never happened there. I can’t tell if this is a different version of that study, a pilot study for that study, or a different study by the same guy. Anyway, it’s too confusing to interpret, shows implausible results, and is by a known fraudster, so I feel okay about ignoring this one. Mahmud et al: RCT from Bangladesh. 200 patients received ivermectin plus doxycycline, 200 received placebo. Everything was written up very nicely in real English, by people who were clearly not on 34 lbs of meth at the time. They designated a primary outcome, “number of days required for clinical recovery”, and found a statistically significant difference at p < 0.001: Okay, fine, they misspelled “recovery” once. But they spelled it right the other time! That puts it in the top 50% for ivermectin papers! The fraud-hunters have examined this paper closely and are unable to find any signs of fraud. @PubPeer on the Mahmud trial of ivermectin in covid patients.\n\nI have now reviewed the individual patient data master sheet.\n\nI did not find any irregularities and the summary data matches the published data.\n\n","username":"K_Sheldrick","name":"Kyle Sheldrick","profile_image_url":"","date":"Sat Jul 17 11:06:25 +0000 2021","photos":[],"quoted_tweet":{},"reply_count":0,"retweet_count":2,"like_count":12,"impression_count":0,"expanded_url":{"url":"https://pubpeer.com/publications/E1D65711EF28D14517731BEACB89C8#2","title":"PubPeer - Ivermectin in combination with doxycycline for treating COVI...","description":"There are comments on PubPeer for publication: Ivermectin in combination with doxycycline for treating COVID-19 symptoms: a randomized trial (2021)","domain":"pubpeer.com"},"video_url":null,"belowTheFold":true}" data-component-name="Twitter2ToDOM"> I think this paper is legitimate and that its findings need to be seriously considered. Serious consideration doesn’t always meant they’re true - sometimes if we have strong evidence otherwise we can dismiss things without understanding why. And there’s always the chance it was a fluke, right? Can something have a p-value less than 0.001 and still be a fluke? Szenta Fonseca et al: This is a chart review from Brazil. Researchers looked at various people who had been treated for COVID in an insurance company database, saw whether they got ivermectin or not, and saw whether the people who got it did better or worse. About a hundred people got it, and a few hundred others didn’t. The people who got it did not do any better than anyone else, and you’ll notice this is one of the rare red boxes on the table above. But we shouldn’t take this study seriously. Nobody took any effort to avoid selection bias, so it’s very possible that sicker people were given more medication (including ivermectin), which unfairly handicaps the ivermectin group. Also, it’s hard to tell from the paper who was on how much of what, and the discussion of ivermectin seems like kind of an afterthought after discussing lots of other meds in much more depth. This is another one I feel comfortable ignoring. Cadegiani et al: A crazy person decided to put his patients on every weird medication he could think of, and 585 subjects ended up on a combination of ivermectin, hydroxychloroquine, azithromycin, and nitazoxanide, with dutasteride and spironolactone "optionally offered" and vitamin D, vitamin C, zinc, apixaban, rivaraxoban, enoxaparin, and glucocorticoids "added according to clinical judgment". There was no control group, but the author helpfully designated some random patients in his area as a sort-of-control, and then synthetically generated a second control group based on “a precise estimative based on a thorough and structured review of articles indexed in PubMed and MEDLINE and statements by official government agencies and specific medical societies”. Patients in the experimental group were twice as likely to recover (p < 0.0001), had negative PCR after 14 vs. 21 days, and had 0 vs. 27 hospitalizations. Speaking of low p-values, some people did fraud-detection tests on another of Cadegiani’s COVID-19 studies and got values like p < 8.24E-11 in favor of it being fraudulent. And, uh, he’s also studied whether ultra-high-dose antiandrogens treated COVID, and found that they did, cutting mortality by 92% . But the trial is under suspicion, with a BMJ article calling it “[the worst] violations of medical ethics and human rights in Brazil’s history” and “an ethical cesspit of violations”. [update 2022: this section originally contained more accusations against Cadegiani. Alexandros Marinos does a deeper dive with information not available at the time I wrote this, and finds some of them were overstated or false by implication] Anyway, let’s not base anything important on the results of this study, mmkay? A defiant Flavio Cadegiani. Imagine a guy who looks like this telling you to take ultra-high-dose antiandrogens. Ahmed et al: And we’re back in Bangladesh. 72 hospital patients were randomized to one of three arms: ivermectin only, ivermectin + doxycycline, and placebo. Primary endpoint was time to negative PCR, which was 9.7 days for ivermectin only and 12.7 days for placebo (p = 0.03). Other endpoints including duration of hospitalization (9.6 days ivermectin vs. 9.7 days placebo, not significant). This looks pretty good for ivermectin and does not have any signs of fraud or methodological problems. If I wanted to pick at it anyway, I would point out that the ivermectin + doxycycline group didn’t really differ from placebo, and that if you average out both ivermectin groups (with and without doxycycline) it looks like the difference would not be significant. I had previously committed to considering only ivermectin alone in trials that had multiple ivermectin groups, so I’m not going to do this. I can’t find any evidence this trial was preregistered so I don’t know whether they waited to see what would come out positive and then made that their primary endpoint, but virological clearance is a pretty normal primary endpoint and this isn’t that suspicious. It’s impossible to find any useful commentary on this study because Elgazzar (the guy who ran the most famous fraudulent ivermectin study) had the first name Ahmed, everyone is talking about Elgazzar all the time, and this overwhelms Google whenever I try to search for Ahmed et al. For now I’ll just keep this as a mildly positive and mildly plausible virological clearance result, in the context of no effect on hospitalization length or most symptoms. Chaccour et al: 24 patients in Spain were randomized to receive either medium-dose ivermectin or placebo. The primary outcome was percent of patients with negative PCR at day 7; secondary outcomes were viral load and symptoms. The primary endpoint ended up being kind of a wash - everyone still PCR positive by day 7 so it was impossible to compare groups. Ivermectin trended toward lower viral load but never reached significance. Weirdly, ivermectin did seem to help symptoms, but only anosmia and cough towards the end (p = 0.03), which you would usually think of as lingering post-COVID problems. The paper says: Given these findings, consideration could be given to alternative mechanisms of action different from a direct antiviral effect. One alternative explanation might be a positive allosteric modulation of the nicotinic acetylcholine receptor caused by ivermectin and leading to a downregulation of the ACE-2 receptor and viral entry into the cells of the respiratory epithelium and olfactory bulb. Another mechanism through which ivermectin might influence the reversal of anosmia is by inhibiting the activation of pro-inflammatory pathways in the olfactory epithelium. Inflammation of the olfactory mucosa is thought to play a key role in the development of anosmia in SARS-CoV-2 infection This seems kind of hedge-y. If you’re wondering where things went from there, Dr. Chaccour is now a passionate anti-ivermectin activist: @Finneganporter in @BusinessInsider \n\nThe roots of #ivermectin mania: How South America incubated a fake-medicine craze that took the US by storm\n\n","username":"carlos_chaccour","name":"Dr. Carlos Chaccour ??????","profile_image_url":"","date":"Sun Nov 07 18:40:28 +0000 2021","photos":[],"quoted_tweet":{},"reply_count":0,"retweet_count":2,"like_count":9,"impression_count":0,"expanded_url":{"url":"https://www.businessinsider.in/international/news/the-roots-of-ivermectin-mania-how-south-america-incubated-a-fake-medicine-craze-that-took-the-us-by-storm/articleshow/87554081.cms","image":"https://bucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com/public/images/88d08e70-c9e2-46d4-a5df-96807b6c3a13_2000x1000.jpeg","title":"The roots of ivermectin mania: How South America incubated a fake-medicine craze that took the US by storm","description":"The popularity of unproven anti-parasitic drug ivermectin as a COVID-19 treatment is surging. Its use has roots in South America, where it was hyped by populist","domain":"businessinsider.in"},"video_url":null,"belowTheFold":true}" data-component-name="Twitter2ToDOM"> So I guess he must think of this trial as basically negative, although realistically it’s 24 people and we shouldn’t put too much weight on it either way. Ghauri et al: Pakistan, 95 patients. Nonrandom; the study compared patients who happened to be given ivermectin (along with hydroxychloroquine and azithromycin) vs. patients who were just given the latter two drugs. There’s some evidence this produced systematic differences between the two groups - for example, patients in the control group were 3x more likely to have had diarrhea (this makes sense; diarrhea is a potential ivermectin side effect, so you probably wouldn’t give it to people already struggling with this problem). Also, the control group was twice as likely to be getting corticosteroids, maybe a marker for illness severity. Primary outcome was what percent of both groups had a fever: on day 7 it was 21% of ivermectin patients vs. 65% of controls, p < 0.001. No other outcomes were reported. I don’t hate this study, but I think the nonrandom assignment (and observed systematic differences) is a pretty fatal flaw. I can’t find anyone else talking about this one. At least no one seems to be saying anything bad. Babaloba et al: Be warned: if I have to refer to this one in real-life conversation, I will expand out the “et al” and call it “Babalola & Alakoloko”, because that’s really fun to say. This was a Nigerian RCT comparing 21 patients on low-dose ivermectin, 21 patients on high-dose ivermectin, and 20 patients on a combination of lopinavir and ritonavir, a combination antiviral which later studies found not to work for COVID and which might as well be considered a placebo. Primary outcome, as usual, was days until a negative PCR test. High dose ivermectin was 4.65 days, low dose was 6 days, control was 9.15, p = 0.035. Figure 2 is apparently a photograph of the computer screen where they did this calculation. Gideon Meyerowitz-Katz, part of the team that detects fraud in ivermectin papers, is not a fan of this one: He doesn’t say there what means, but elsewhere he tweets this figure: It’s always a bad sign when your study features in an image with “NUMEROUS IMPOSSIBLE NUMBERS” in red at the top. I think his point is that if you have 21 people, it’s impossible to have 50% of them have headache, because that would be 10.5. If 10 people have a headache, it would be 47.6%; if 11, 52%. So something is clearly wrong here. Seems like a relatively minor mistake, and Meyerowitz-Katz stops short of calling fraud, but it’s not a good look. I’m going to be slightly uncomfortable with this study without rejecting it entirely, and move on. Ravakirti et al: Here we’re in Eastern India - not exactly Bangladesh again, but a stone’s throw away from it. In this RCT patients were randomized into an ivermectin group (57) and a placebo group (58). Primary outcome was negative PCR on day 6, because doing it on day 7 like everyone else would be too easy. As with several other groups, this was a bad move; too few people had it to make a good comparison; it was 13% of intervention vs. 18% of placebo, p = 0.3. Secondary outcomes were also pretty boring, except for the most important: 4 people in the placebo group died, compared to 0 in ivermectin (p = 0.045). On the one hand, this is one outcome of many, reaching the barest significance threshold. Another fluke? Still, there are no real problems with this study, and nobody has anything to say against it. Let’s add this one to the scale as another very small and noisy piece of real evidence in ivermectin’s favor. Bukhari et al: Now we’re in Pakistan. 50 patients were randomized to low-dose ivermectin, another 50 got standard of care including vitamin D. There was no placebo, but primary outcome was number of days to reach negative PCR, which it seems hard for placebo to affect much, so I don’t care. 5 controls and 9 ivermectin patients left the hospital against medical advice and could not be followed up, which is bad but not necessarily study-ruining. They never measured their supposed primary outcome of “days to reach negative PCR” directly, but they did measure how many people had negative PCR on various days, and ivermectin had a clear advantage - for example, on day 7, it was 37/50 for IVR and only 20/50 for control. Even if we assume all the lost-to-followup patients had maximally bad-for-the-hypothesis results, that’s still a positive finding. Nobody else has much to say about this one, certainly no accusations that they’ve found anything suspicious. Keep. Mohan et al: India. RCT. 40 patients got low-dose ivermectin, 40 high-dose ivermectin, and 45 placebo. Primary outcomes were time to negative PCR, and viral load on day 5. In the results, they seem to have reinterpreted “time to negative PCR” as the subtly different “percent with negative PCR on some specific day”. High-dose ivermectin did best (47.5% negative on day 5) and placebo worst (31% negative), but it was insignificant (p = 0.3). There was no difference in viral load. All groups took about the same amount of time for symptoms to resolve. More placebo patients had failed to recover by the end of the study (6) than ivermectin patients (2), but this didn’t reach statistical significance (p = 0.4). Overall a well-done, boring, negative study, although ivermectin proponents will correctly point out that, like basically every other study we have looked at, the trend was in favor of ivermectin and this could potentially end up looking impressive in a meta-analysis. Biber et al: This is an RCT from Israel. 47 patients got ivermectin and 42 placebo. Primary endpoint was viral load on day 6. I am having trouble finding out what happened with this; as far as I can tell it was a negative result and they buried it in favor of more interesting things. In a "multivariable logistic regression model, the adjusted odds ratio of negative SARS-CoV-2 RT-PCR negative test" favored ivermectin over placebo (p = 0.03 for day 6, p = 0.01 for day 8), but this seems like the kind of thing you do when your primary outcome is boring and you’re angry. Gideon Meyerowitz-Katz is not a fan: He notes that the study excluded people with high viral load, but the preregistration didn’t say they would do that. Looking more closely, he finds they did that because, if you included these people, the study got no positive results. So probably they did the study, found no positive results, re-ran it with various subsets of patients until they did get a positive result, and then claimed to have “excluded” patients who weren’t in the subset that worked. I’m going to toss this one. Elalfy et al: What even is this? Where am I? As best I can tell, this is some kind of Egyptian trial. It might or might not be an RCT; it says stuff like “Patients were self-allocated to the treatment groups; the first 3 days of the week for the intervention arm while the other 3 days for symptomatic treatment”. Were they self-allocated in the sense that they got to choose? Doesn’t that mean it’s not random? Aren’t there seven days in a week? These are among the many questions that Elalfy et al do not answer for us. The control group (which they seem to think can also be called “the white group”) took zinc, paracetamol, and maybe azithromycin. The intervention group took zinc, nitazoxanide, ribavirin, and ivermectin. There were very large demographic differences between the groups of the sort which make the study unusable, which they mention and then ignore. From there, they follow this normal and totally comprehensible flowchart: There is no primary outcome assigned, but viral clearance rates on day seven were 58% in the yellow group compared to 0% in the white group, which I guess is a strong positive result. This table… …looks very impressive, in terms of the experimental group doing better than the control, except that they don’t specify whether it was before the trial or after it, and at least one online commentator thinks it might have been before, in which case it’s only impressive how thoroughly they failed to randomize their groups. Overall I don’t feel bad throwing this study out. I hope it one day succeeds in returning to its home planet. Lopez-Medina et al: Colombian RCT. 200 patients took ivermectin, another 200 took placebo. They originally worried the placebo might taste different than real ivermectin, then solved this by replacing it with a different placebo, which is a pretty high level of conscientiousness. Primary outcome was originally percent of patients whose symptoms worsened by two points, as rated on a complicated symptom scale when a researcher asked them over the phone. Halfway through the study, they realized nobody was worsening that much, so they changed the primary outcome to time until symptoms got better, as measured by the scale. In the ivermectin group, symptoms improved that much after 10 days; in the placebo group, after 12, p = 0.53. By the end of the study, symptoms had improved in 82% of ivermectin users and 79% of controls, also insignificant. 4 patients in the ivermectin group needed to be hospitalized compared to 6 in the placebo group, again insignificant. This study is bigger than most of the other RCTs, and more polished in terms of how many spelling errors, photographs of computer screens, etc, it contains. It was published in JAMA, one of the most prestigious US medical journals, as opposed to the crappy nth-tier journals most of the others have been in. When people say things like “sure, a lot of small studies show good results for ivermectin, but the bigger and more professional trials don’t”, this is one of the two big professional trials they’re talking about. Ivermectin proponents make some good arguments against it. In order to get as big as it did, Lopez-Medina had to compromise on rigor. Its outcome is how people self-score their symptoms on a hokey scale in a phone interview, instead of viral load or PCR results or anything like that. Still, this is basically what we want, right? In the end, we want people to feel better and less sick, not to get good scores on PCR tests. Also, it changed its primary outcome halfway through; isn’t that bad? I think maybe not; the reason we want a preregistered primary outcome is so that you don’t change halfway through to whatever outcome shows the results you want. The researchers in this study did a good job explaining why they changed their outcome, the change makes sense, and their original outcome would also have shown ivermectin not working (albeit less accurately and effectively). I don’t know of any evidence that they knew (or suspected) final results when switching to this new outcome, and it seems like the most reasonable new outcome to switch to. Finally, their original placebo tasted different from ivermectin (though they switched halfway through). This is one of the few studies where I actually care about placebo, because people are self-rating their symptoms. But realistically most of these people don’t know what ivermectin is supposed to taste like. Also, they did a re-analysis and found there was no difference between the people who got the old placebo and the new one. I’m making a big deal of this because ivmmeta.com - the really impressive meta-analysis site I’ve been going off of - puts a special warning letter underneath their discussion of this study, urging us not to trust it. They don’t do this for any of the other ones we’ve addressed so far - not the one by the guy whose other studies were all frauds, not the one where 50% of 21 people had headaches, not the unrandomized one where the groups were completely different before the experiment started, not even the one by the guy accused of crimes against humanity. Only this one. This makes me a lot less charitable to ivmmeta than I would otherwise be; I think it’s hard to choose this particular warning letter strategy out of well-intentioned commitment to truth. They just really don’t like this big study that shows ivermectin doesn’t work. Also, the warning itself irritates me, and includes paragraphs like: RCTs have a fundamental bias against finding an effect for interventions that are widely available — patients that believe they need treatment are more likely to decline participation and take the intervention [Yeh], i.e., RCTs are more likely to enroll low-risk participants that do not need treatment to recover (this does not apply to the typical pharmaceutical trial of a new drug that is otherwise unavailable). This trial was run in a community where ivermectin was available OTC and very widely known and used. Nobody else worries about this, and there are a million biases that non-randomized studies have that would be super-relevant when discussing those, but somehow when they’re pro-ivermectin the site forgets to be this thorough. I think a better pro-ivermectin response to this study is to point out that all the trends support ivermectin. Symptoms took 10 days to resolve in the ivermectin group vs. 12 in placebo; 4 ivermectin patients were hospitalized vs. 6 placebo patients, etc. Just say that this was an unusually noisy trial because of the self-report methodology, and you’re confident that these small differences will add up to significance when you put them into a meta-analysis. Roy et al: We’re back in East India, and back to non-randomized trials. 56 patients were retrospectively examined; some had been given ivermectin + doxycycline, others hydroxychloroquine, other azithromycin, and others symptomatic treatment only. We don’t get any meaningful information about how this worked, but we are told that they did not differ in “clinical well-being reporting onset timing”. Whatever. Chahla et al: The first of many Argentine trials. 110 patients received medium-dose ivermectin; 144 were kept as a control (no placebo). This was “cluster randomized”, which means they randomize different health centers to either give the experimental drug or not. This is worse than regular randomization, because there could be differences between these health centers (eg one might have better doctors who otherwise give better treatment, one might be in the poor part of town and have sicker patients, etc). They checked to see if there were any differences between the groups, and it sure looks like there were (the experimental group had twice as many obese people as the controls), but as per them, these differences were not statistically significant. Note that if this did make a difference, it would presumably make ivermectin look worse, not better. The primary outcome was given as “increase discharge from outpatient care with COVID-19 mild disease”. This favored the treatment; only 2/110 patients in the ivermectin group failed to be discharged, compared to 20 patients in the control group. But, uh, these were at different medical centers. Can’t different medical centers just have different discharge policies? One discharges you as soon as you seem to be getting better, the other waits to really make sure? This is an utterly crap endpoint to do a cluster randomized controlled trial on. If you’re going to do cRCT, which is never a great idea, you should be using some extremely objective endpoint that doctors and clinic administrators can’t possibly affect, like viral load according to some third-party laboratory, using the same third-party laboratory for both clinics. This is such a bad idea that I can’t help worrying I’m missing or misunderstanding something. If not, this is dumb and bad and should be ignored. Mourya et al: We’re back in India. This is a nonrandomized study comparing 50 patients given ivermectin to 50 patients given hydroxychloroquine. No primary outcome was named, but they focus on PCR negativity. Only 6% of patients in the hydroxychloroquine group were negative, compared to 90% of patients in the ivermectin group! On what day did they do the test? Uh, kind of random, and they admit that “in [the hydroxychloroquine group], mean time difference from the date of initiation of treatment and second test was significantly longer (7.24±2.75 days) as compared to 5.22±1.21 days in [the ivermectin group] (p=0.021).” Since they assessed these groups at different times, we shouldn’t draw any conclusions from them getting different results. Except that as far as I can tell this should handicap ivermectin, making it especially impressive that it did better. But also, the ivermectin group was made mostly of people who had been asymptomatic at the beginning (70%), and the hydroxychloroquine group had almost no asymptomatic cases (8%) . They were giving the ivermectin to healthy people and the hydroxychloroquine to sick people! They admit deep in the discussion that this “may be a confounding factor”. So basically they got totally different groups of people, tested them at totally different times, and the two sets of test results differed. So what? So this is why normal people do RCTs instead of whatever the heck this is, that’s what. Loue et al: …this one isn’t going to be an RCT either. Loue tells a story about a cluster of COVID cases at the French nursing home where he works. He asked people if they wanted to try ivermectin; 10 did and 15 didn’t. 1 ivermectin patient died, compared to 5 non-ivermectin patients. The non-ivermectin group looked a bit sicker than the ivermectin group in the inevitable Table 1, though it’s hard to tell. One interesting possible confounder (not mentioned, but I’m imagining it) is that demented patients probably couldn’t consent to ivermectin and ended up in the control group. This is another case of “I’m not going to trust anything that isn’t an RCT”. Merino et al: Another (sigh) non-RCT. Mexico City tried a public health program where if you called a hotline and said you had COVID, they sent you an emergency kit with various useful supplies. One of those supplies was ivermectin tablets. 18,074 people got the kit (and presumably some appreciable fraction took the ivermectin, though there’s no way to prove that). Their control group is people from before they started giving out the kits, people from after they stopped giving out the kits, and people who didn’t want the kits. There are differences in who got COVID early in the epidemic vs. later, and in people who did opt for medical kits vs. didn’t. To correct these, the researchers tried to adjust for confounders, something which - as I keep trying to hammer home again and again - never works. They found that using the kit led to a 75% or so reduction in hospitalization, though they were unable to separate out the ivermectin from the other things in the kit (paracetamol and aspirin), or from the placebo effect of having a kit and feeling like you had already gotten some treatment (if I understand right, the decision to go to the hospital was left entirely to the patient). I think this study is a moderate point in favor of giving people kits in order to prevent hospital overcrowding, but I’m not willing to accept that it tells us much about ivermectin in particular. Faisal et al: This one was published in The Professional Medical Journal (mispelled as “Profesional Medical Journal” in its URL), so you know it’s going to be good! It describes itself as “a cross-sectional study”, but later says it “randomized patients into two groups”, which would make it an RCT - I think they might just be using the term “cross-sectional” different from the standard American usage. A hospital in Pakistan got 50 patients on ivermectin + azithromycin, and another 50 on azithromycin alone. Primary outcome was not mentioned, and the data were presented confusingly, but a typical result is that only 4% of the ivermectin group had symptoms lasting more than 10 days, whereas 16% of the control group did, p < 0.01. They do a really weird thing where they compare how long it took symptoms to resolve between IVM and control groups within each bin. That is, if I’m understanding correctly, they ask “of the people who took between 3-5 days for symptoms to resolve, did they resolve faster for IVM or control?”. This is an utterly bizarre analysis to perform, although it doesn’t affect the fact that their other results still seem to favor ivermectin. Maybe I’m confused about what’s going on here. I’ve mostly been letting people off easy on no placebo, but I as far as I can tell (not very far) this paper seems to be going off whether patients reported continuing to have symptoms to the hospital doing the study, and I think that is potentially susceptible to placebo effects. Additionally, there’s no preregistration, and even though they talk a lot about doing PCR tests they don’t present the results. This is by no means the worst study here but I still think it’s pretty low quality and I don’t trust it. Aref et al: This one is published in the International Journal Of Nanomedicine, even though I’m pretty sure that isn’t a real thing. In this case the “nanomedicine” is a new nasal spray version of ivermectin which is so confusing I cannot for the life of me figure out what dose they are giving these patients. This Egyptian study gives 57 patients intranasal ivermectin plus hydroxychloroquine, azithromycin, oseltamavir, and some vitamins; another 57 patients get all that stuff except the ivermectin. Primary outcome is not stated, but they look at various symptoms, all of which look better in the ivermectin group: 95% of ivermectin patients got negative PCRs at some time point, compared to 75% of controls, p = 0.004. I am pretty suspicious of this study, not least because it comes from Egypt which has an awful reputation for fake studies, and it returns extreme results that I wouldn’t expect even if ivermectin was actually a wonder drug. But I cannot find any particular thing wrong with it, nor did anyone else I looked at, so I will grudgingly let it stand. Krolewiecki et al: Another Argentine study. This one is a real RCT. 30 patients received ivermectin, 15 were the control group (no placebo, again). Primary outcome was difference in viral load on day 5. The trend favored ivermectin but it was not statistically significant, although they were able to make it statistically significant if they looked at a subset of higher-IVM-plasma-concentration patients. They did not find any difference in clinical outcomes. A pro-ivermectin person could point out that in the subgroup with the highest ivermectin concentrations, the drug seemed to work. A skeptic could point out that this is exactly the kind of subgroup slicing that you are not supposed to do without pre-registering it, which I don’t think this team did. I agree with the skeptic. Vallejos et al: Another Argentine study. It’s big (250 people in each arm). It’s an RCT. It tries to define a primary outcome (“Primary outcome: the trial ended when the last patient who was included achieved the end of study visit”), but that’s not what “primary outcome” means, and they don’t offer an alternative. Other outcomes: no difference in PCR on days 3 or 12. Hospitalization is nonsignificantly better in the ivermectin group (14 vs. 21, p = 0.2), but death is nonsigificantly better in the placebo group (3 vs. 4, p = 0.7). This isn’t even the kind of nonsignificant that might contribute to an exciting meta-analysis later. This is just a pure null result. I cannot find any problem with this study, and neither can anyone else I checked. This is the biggest RCT we’ve seen so far, so we should take it seriously. TOGETHER Trial: Speaking of big RCTs… This one hasn’t been published yet. There’s a video of a talk about it, but I am not going to watch it, because it is a video, so I am getting information secondhand from eg here. Apparently, it compares 677 people (!) randomized to ivermectin to 678 people randomized to placebo. 86 ivermectin patients ended up in the hospital compared to 95 placebo patients, p-value not significant. This was a really big professional trial done by bigshot researchers from a major Canadian university, and the medical establishment is taking it much more seriously than any of these others. When it comes out, it will probably get published in a top journal. When discussing Lopez-Medina, I wrote: When people say things like “sure, a lot of small studies show good results for ivermectin, but the bigger and more professional trials don’t”, this is one of the two big professional trials they’re talking about. This is the other one. Not coincidentally, it’s also the other trial that ivmmeta.com has a warning letter underneath telling you to disregard. Their main concern is that instead of truly randomizing patients to ivermectin vs. placebo, they did a time-dependent randomization that meant during some weeks more patients were getting one or the other. This is a problem because the trial takes place in Brazil, where different variants were more common at different times. Here’s their image: On the one hand, I have immense contempt for ivmmeta for letting all those other awful studies pass and then pulling out all the stops to try to nitpick this one. I have no idea if their proposed randomization failure really happened. And no doubt the reason they’re even able to investigate this is that this study is really careful and transparent - most of them don’t tell you anything about their randomization method. I would be shocked if other studies don’t have all these problems and worse. On the other hand, the point isn’t to be fair, it’s to be right. And this is a potential confounder. Not a huge one. But a potential one. I guess all we can do is try to bound the damage. Even if the confounding is 100% real and bad, there’s no way to make this study consistent with the crazy super-pro-ivermectin results of studies like Espitia-Hernandez and Aref. And even if we deny any confounding, we see the same slight pro-ivermectin trend - 86 hospitalizations vs. 95 - that we’ve seen in so many other studies. Nothing is going to make me believe that this isn’t in the top 33% of studies we’ve been looking at, so let’s add it as grist for the meta-analysis (though maybe not quite as much grist as its vast size indicates) and move on, angrily. Buonfrate et al: An Italian RCT. Patients were randomized into low-dose ivermectin (32), placebo (29), or high-dose ivermectin (32). Primary outcome was viral load on day 7. There was no significant difference (average of 2 in ivermectin groups, 2.2 in placebo group). They admit that they failed to reach the planned sample size, but did a calculation to show that even if they had, the trial could not have returned a positive result. Clinically, an average of 2 patients were hospitalized in each of the ivermectin arms, compared to 0 in the placebo arm - which bucks our previously-very-constant pro-ivermectin trend. Mayer et al: Not an RCT. Patients in an Argentine province were offered the opportunity to try ivermectin; 3266 said yes and become the experimental group, 17966 said no and became the control group. There were many obvious differences between the groups, but they all seemed to handicap ivermectin. There was a nonsignificant trend toward less hospitalization and significantly less mortality (1.5% vs. 2.1%, p = 0.03). While looking into this study, I learned the term “immortal time bias”. This means a period in between selection for the study and the beginning of study recording where patient outcomes are not counted. I think the problem here is that if you signed up for the system on Day X, and if you got sick before they could give you ivermectin, you were in the control group. See this Twitter thread, I have not confirmed everything he says. This only hardens my resolve to stay away from non-RCTs. Borody et al: Our last paper! …is it a paper? I can’t find it published anywhere. It mostly seems to be on news sites. Doesn’t look peer-reviewed. And it starts with “Note that views expressed in this opinion article are the writer’s personal views”. Whatever. 600 Australians were treated with ivermectin, doxycycline, and zinc. The article compares this to an “equivalent control group” made of “contemporary infected subjects in Australia obtained from published Covid Tracking Data”; this is not how you control group, @#!% you. Then it gets excited about the fact that most patients had better symptoms at the end of the ten-day study period than the beginning (untreated COVID resolves in about ten days). Why are these people wasting my time with this? Let’s move on. The Analysis If we remove all fraudulent and methodologically unsound studies from the table above, we end up with this: Gideon Meyerowitz-Katz, who investigated many of the studies above for fraud, tried a similar exercise. I learned about his halfway through, couldn’t help seeing it briefly, but tried to avoid remembering it or using it when generating mine (also, I did take the result of his fraud investigations into account), so they should be considered not quite independent efforts. His looks like this: He nixed Chowdhury, Babaloba, Ghauri, Faisal, and Aref, but kept Szenta Fonseca, Biber (?), and Mayer. There was correlation of 0.45, which I guess is okay. I asked him about his decision-making, and he listed a combination of serious statistical errors and small red flags adding up. I was pretty uncomfortable with most of these studies myself, so I will err on the side of severity, and remove all studies that either I or Meyerowitz-Katz disliked. We end up with the following short list: We’ve gone from 29 studies to 11, getting rid of 18 along the way. For the record, we eliminated 2/19 for fraud, 1/19 for severe preregistration violations, 10 for methodological problems, and 6 because Meyerowitz-Katz was suspicious of them. …but honestly this table still looks pretty good for ivermectin, doesn’t it? Still lots of big green boxes. Meyerowitz-Katz accuses ivmmeta of cherry-picking what statistic to use for their forest plot. That is, if a study measures ten outcomes, they sometimes take the most pro-ivermectin outcome. Ivmmeta.com counters that they used a consistent and reasonable (if complicated) process for choosing their outcome of focus, that being: If studies report multiple kinds of effects then the most serious outcome is used in calculations for that study. For example, if effects for mortality and cases are both reported, the effect for mortality is used, this may be different to the effect that a study focused on. If symptomatic results are reported at multiple times, we used the latest time, for example if mortality results are provided at 14 days and 28 days, the results at 28 days are used. Mortality alone is preferred over combined outcomes. Outcomes with zero events in both arms were not used (the next most serious outcome is used — no studies were excluded). For example, in low-risk populations with no mortality, a reduction in mortality with treatment is not possible, however a reduction in hospitalization, for example, is still valuable. Clinical outcome is considered more important than PCR testing status. When basically all patients recover in both treatment and control groups, preference for viral clearance and recovery is given to results mid-recovery where available (after most or all patients have recovered there is no room for an effective treatment to do better). If only individual symptom data is available, the most serious symptom has priority, for example difficulty breathing or low SpO2 is more important than cough. I’m having trouble judging this, partly because Meyerowitz-Katz says ivmmeta has corrected some earlier mistakes, and partly because there really is some reasonable debate over how to judge studies with lots of complicated endpoints. By this point I had completely forgotten what ivmmeta did, so I independently coded all 11 remaining studies following something in between my best understanding of their procedure and what I considered common sense. The only exception was that when the most severe outcome was measured in something other than patients (ie average number of virus copies per patient), I defaulted to one that was measured in patients instead, to keep everything with the same denominator. My results mostly matched ivmmeta’s, with one or two exceptions that I think are within the scope of argument or related to my minor deviations from their protocol. Placebo vs. ivermectin groups sometimes differed in size, which I’ve adjusted for and rounded off. Probably I’m forgetting some reason I can’t just do simple summary statistics to this, but whatever. It is p = 0.15, not significant. This is maybe unfair, because there aren’t a lot of deaths in the sample, so by focusing on death rather than more common outcomes we’re pointlessly throwing away sample size. What happens if I unprincipledly pick whatever I think the most reasonable outcome to use from each study is? I’ve chosen “most reasonable” as a balance between “is the most severe” and “has a lot of data points”: Now it’s p = 0.04, seemingly significant, but I had to make some unprincipled decisions to get there. I don’t think I specifically replaced negative findings with positive ones, but I can’t prove that even to myself, let alone to you. [UPDATE 5/31/22: A reader writes in to tell me that the t-test I used above is overly simplistic. A Dersimonian-Laird test is more appropriate for meta-analysis, and would have given 0.03 and 0.005 on the first and second analysis, where I got 0.15 and 0.04. This significantly strengthens the apparent benefit of ivermectin from ‘debatable’ to ‘clear’. I discuss some reasons below why I am not convinced by this apparent benefit.] (how come I’m finding a bunch of things on the edge of significance, but the original ivmmeta site found a lot of extremely significant things? Because they combined ratios, such that “one death in placebo, zero in ivermectin” looked like a nigh-infinite benefit for ivermectin, whereas I’m combining raw numbers. Possibly my way is statistically illegitimate for some reason, but I’m just trying to get a rough estimate of how convinced to be) So we are stuck somewhere between “nonsignificant trend in favor” and “maybe-significant trend in favor, after throwing out some best practices”. This is normally where I would compare my results to those of other meta-analyses made by real professionals. But when I look at them, they all include studies later found to be fake, like Elgazzar, and unsurprisingly come up with wildly positive conclusions. There are about six in this category. One of them later revised their results to exclude Elgazzar and still found strong efficacy for ivermectin, but they still included Niaee and some other dubious studies. The only meta-analysis that doesn’t make these mistakes is Popp (a Cochrane review), which is from before Elgazzar was found to be fraudulent, but coincidentally excludes it for other reasons. It also excludes a lot of good studies like Mahmud and Ravakirti because they give patients other things like HCQ and azithromycin - I chose to include them, because I don’t think they either work or have especially bad side effects, so they’re basically placebo - but Cochrane is always harsh like this. They end up with a point estimate where ivermectin cuts mortality by 40% - but say the confidence intervals are too wide to draw any conclusion. I think this basically agrees with my analyses above - the trends really are in ivermectin’s favor, but once you eliminate all the questionable studies there are too few studies left to have enough statistical power to reach significance. Except that everyone is still focusing on deaths and hospitalizations just because they’re flashy. Mahmud et al, which everyone agrees is a great study, found that ivermectin decreased days until clinical recovery, p = 0.003? So what do you do? This is one of the toughest questions in medicine. It comes up again and again. You have some drug. You read some studies. Again and again, more people are surviving (or avoiding complications) when they get the drug. It’s a pattern strong enough to common-sensically notice. But there isn’t an undeniable, unbreachable fortress of evidence. The drug is really safe and doesn’t have a lot of side effects. So do you give it to your patients? Do you take it yourself? Here this question is especially tough, because, uh, if you say anything in favor of ivermectin you will be cast out of civilization and thrown into the circle of social hell reserved for Klan members and 1/6 insurrectionists. All the health officials in the world will shout “horse dewormer!” at you and compare you to Josef Mengele. But good doctors aren’t supposed to care about such things. Your only goal is to save your patient. Nothing else matters. I am telling you that Mahmud et al is a good study and it got p = 0.003 in favor of ivermectin. You can take the blue pill, and stay a decent respectable member of society. Or you can take the horse dewormer pill, and see where you end up. In a second, I’ll tell you my answer. But you won’t always have me to answer questions like this, and it might be morally edifying to observe your thought process in situations like this. So take a second, and meet me on the other side of the next section heading. … … … … … The Synthesis Hopefully you learned something interesting about yourself there. But my answer is: worms! As several doctors and researchers have pointed out (h/t especially Avi Bitterman and David Boulware), the most impressive studies come from places that are teeming with worms. Mahmud from Bangladesh, Ravakirti from East India, Lopez-Medina from Colombia, etc. Here’s the prevalence of roundworm infections by country (source). But alongside roundworms, there are threadworms, hookworms, blood flukes, liver flukes, nematodes, trematodes, all sorts of worms. Add them all up and somewhere between half and a quarter of people in the developing world have at least one parasitic worm in their body. Being full of worms may impact your ability to fight coronavirus. Gluchowska et al write: Helminth [ie worm] infections are among the most common infectious diseases. Bradbury et al. highlight the possible negative interactions between helminth infection and COVID-19 severity in helminth-endemic regions and note that alterations in the gut microbiome associated with helminth infection appear to have systemic immunomodulatory effects. It has also been proposed that helminth co-infection may increase the morbidity and mortality of COVID-19, because the immune system cannot efficiently respond to the virus; in addition, vaccines will be less effective for these patients, but treatment and prevention of helminth infections might reduce the negative effect of COVID-19. During millennia of parasite-host coevolution helminths evolved mechanisms suppressing the host immune responses, which may mitigate vaccine efficacy and increase severity of other infectious diseases. Treatment of worm infections might reduce the negative effect of COVID-19! And ivermectin is a deworming drug! You can see where this is going… The most relevant species of worm here is the roundworm Strongyloides stercoralis. Among the commonest treatments for COVID-19 is corticosteroids, a type of immunosuppresant drug. The types of immune responses it suppresses do more harm than good in coronavirus, so turning them off limits collateral damage and makes patients better on net. But these are also the types of immune responses that control Strongyloides. If you turn them off even very briefly, the worms multiply out of control, you get what’s called “Strongyloides hyperinfection”, and pretty often you die. According to the WHO: The current COVID-19 pandemic serves to highlight the risk of using systemic corticosteroids and, to a lesser extent, other immunosuppressive therapy, in populations with significant risk of underlying strongyloidiasis. Cases of strongyloidiasis hyperinfection in the setting of corticosteroid use as COVID-19 therapy have been described and draw attention to the necessity of addressing the risk of iatrogenic strongyloidiasis hyperinfection syndrome in infected individuals prior to corticosteroid administration. Although this has gained importance in the midst of a pandemic where corticosteroids are one of few therapies shown to improve mortality, its relevance is much broader given that corticosteroids and other immunosuppressive therapies have become increasingly common in treatment of chronic diseases (e.g. asthma or certain rheumatologic conditions). So you need to “address the risk” of strongyloides infection during COVID treatment in roundworm-endemic areas. And how might you address this, WHO? Treatment of chronic strongyloidiasis with ivermectin 200 µg/kg per day orally x 1-2 days is considered safe with potential contraindications including possible Loa loa infection (endemic in West and Central Africa), pregnancy, and weight <15kg. Given ivermectin’s safety profile, the United States has utilized presumptive treatment with ivermectin for strongyloidiasis in refugees resettling from endemic areas, and both Canada and the European Centre for Disease Prevention and Control have issued guidance on presumptive treatment to avoid hyperinfection in at risk populations. Screening and treatment, or where not available, addition of ivermectin to mass drug administration programs should be studied and considered. This is serious and common enough that, if you’re not going to screen for it, it might be worth “add[ing] ivermectin to mass drug administration programs” in affected areas! Dr. Avi Bitterman carries the hypothesis to the finish line: First two images are with all relevant studies; second two are a sensitivity analysis that removes some of the most dubious. The good ivermectin trials in areas with low Strongyloides prevalence, like Vallejos in Argentina, are mostly negative. The good ivermectin trials in areas with high Strongyloides prevalence, like Mahmud in Bangladesh, are mostly positive. Worms can’t explain the viral positivity outcomes (ie PCR), but Dr. Bitterman suggests that once you remove low quality trials and worm-related results, the rest looks like simple publication bias: This is still just a possibility. Maybe I’m over-focusing too hard on a couple positive results and this will all turn out to be nothing. Or who knows, maybe ivermectin does work against COVID a little - although it would have to be very little, fading to not at all in temperate worm-free countries. But this theory feels right to me. It feels right to me because it’s the most troll-ish possible solution. Everybody was wrong! The people who called it a miracle drug against COVID were wrong. The people who dismissed all the studies because they F@#king Love Science were wrong. Ivmmeta.com was wrong. Gideon Meyerowitz-Katz was…well, he was right, actually, I got the worm-related meta-analysis graphic above from his Twitter timeline. Still, an excellent troll. Also, the best part is that I ignorantly asked, in my description of Mahmud et al above: And it was! It was a fluke! A literal, physical, fluke! For my whole life, God has been placing terrible puns in my path to irritate me, and this would be the worst one ever! So it has to be true! The Scientific Takeaway About ten years ago, when the replication crisis started, we learned a certain set of tools for examining studies. Check for selection bias. Distrust “adjusting for confounders”. Check for p-hacking and forking paths. Make teams preregister their analyses. Do forest plots to find publication bias. Stop accepting p-values of 0.049. Wait for replications. Trust reviews and meta-analyses, instead of individual small studies. These were good tools. Having them was infinitely better than not having them. But even in 2014, I was writing about how many bad studies seemed to slip through the cracks even when we pushed this toolbox to its limits. We needed new tools. I think the methods that Meyerowitz-Katz, Sheldrake, Heathers, Brown, Lawrence and others brought to the limelight this year are some of the new tools we were waiting for. Part of this new toolset is to check for fraud. About 10 - 15% of the seemingly-good studies on ivermectin ended up extremely suspicious for fraud. Elgazzar, Carvallo, Niaee, Cadegiani, Samaha. There are ways to check for this even when you don’t have the raw data. Like: The Carlisle-Stouffer-Fisher method: Check some large group of comparisons, usually the Table 1 of an RCT where they compare the demographic characteristics of the control and experimental groups, for reasonable p-values. Real data will have p-values all over the map; one in every ten comparisons will have a p-value of 0.1 or less. Fakers seem bad at this and usually give everything a nice safe p-value like 0.8 or 0.9.
…looks very impressive, in terms of the experimental group doing better than the control, except that they don’t specify whether it was before the trial or after it, and at least one online commentator thinks it might have been before, in which case it’s only impressive how thoroughly they failed to randomize their groups. Overall I don’t feel bad throwing this study out. I hope it one day succeeds in returning to its home planet. Lopez-Medina et al: Colombian RCT. 200 patients took ivermectin, another 200 took placebo. They originally worried the placebo might taste different than real ivermectin, then solved this by replacing it with a different placebo, which is a pretty high level of conscientiousness. Primary outcome was originally percent of patients whose symptoms worsened by two points, as rated on a complicated symptom scale when a researcher asked them over the phone. Halfway through the study, they realized nobody was worsening that much, so they changed the primary outcome to time until symptoms got better, as measured by the scale. In the ivermectin group, symptoms improved that much after 10 days; in the placebo group, after 12, p = 0.53. By the end of the study, symptoms had improved in 82% of ivermectin users and 79% of controls, also insignificant. 4 patients in the ivermectin group needed to be hospitalized compared to 6 in the placebo group, again insignificant. This study is bigger than most of the other RCTs, and more polished in terms of how many spelling errors, photographs of computer screens, etc, it contains. It was published in JAMA, one of the most prestigious US medical journals, as opposed to the crappy nth-tier journals most of the others have been in. When people say things like “sure, a lot of small studies show good results for ivermectin, but the bigger and more professional trials don’t”, this is one of the two big professional trials they’re talking about. Ivermectin proponents make some good arguments against it. In order to get as big as it did, Lopez-Medina had to compromise on rigor. Its outcome is how people self-score their symptoms on a hokey scale in a phone interview, instead of viral load or PCR results or anything like that. Still, this is basically what we want, right? In the end, we want people to feel better and less sick, not to get good scores on PCR tests. Also, it changed its primary outcome halfway through; isn’t that bad? I think maybe not; the reason we want a preregistered primary outcome is so that you don’t change halfway through to whatever outcome shows the results you want. The researchers in this study did a good job explaining why they changed their outcome, the change makes sense, and their original outcome would also have shown ivermectin not working (albeit less accurately and effectively). I don’t know of any evidence that they knew (or suspected) final results when switching to this new outcome, and it seems like the most reasonable new outcome to switch to. Finally, their original placebo tasted different from ivermectin (though they switched halfway through). This is one of the few studies where I actually care about placebo, because people are self-rating their symptoms. But realistically most of these people don’t know what ivermectin is supposed to taste like. Also, they did a re-analysis and found there was no difference between the people who got the old placebo and the new one. I’m making a big deal of this because ivmmeta.com - the really impressive meta-analysis site I’ve been going off of - puts a special warning letter underneath their discussion of this study, urging us not to trust it. They don’t do this for any of the other ones we’ve addressed so far - not the one by the guy whose other studies were all frauds, not the one where 50% of 21 people had headaches, not the unrandomized one where the groups were completely different before the experiment started, not even the one by the guy accused of crimes against humanity. Only this one. This makes me a lot less charitable to ivmmeta than I would otherwise be; I think it’s hard to choose this particular warning letter strategy out of well-intentioned commitment to truth. They just really don’t like this big study that shows ivermectin doesn’t work. Also, the warning itself irritates me, and includes paragraphs like: RCTs have a fundamental bias against finding an effect for interventions that are widely available — patients that believe they need treatment are more likely to decline participation and take the intervention [Yeh], i.e., RCTs are more likely to enroll low-risk participants that do not need treatment to recover (this does not apply to the typical pharmaceutical trial of a new drug that is otherwise unavailable). This trial was run in a community where ivermectin was available OTC and very widely known and used. Nobody else worries about this, and there are a million biases that non-randomized studies have that would be super-relevant when discussing those, but somehow when they’re pro-ivermectin the site forgets to be this thorough. I think a better pro-ivermectin response to this study is to point out that all the trends support ivermectin. Symptoms took 10 days to resolve in the ivermectin group vs. 12 in placebo; 4 ivermectin patients were hospitalized vs. 6 placebo patients, etc. Just say that this was an unusually noisy trial because of the self-report methodology, and you’re confident that these small differences will add up to significance when you put them into a meta-analysis. Roy et al: We’re back in East India, and back to non-randomized trials. 56 patients were retrospectively examined; some had been given ivermectin + doxycycline, others hydroxychloroquine, other azithromycin, and others symptomatic treatment only. We don’t get any meaningful information about how this worked, but we are told that they did not differ in “clinical well-being reporting onset timing”. Whatever. Chahla et al: The first of many Argentine trials. 110 patients received medium-dose ivermectin; 144 were kept as a control (no placebo). This was “cluster randomized”, which means they randomize different health centers to either give the experimental drug or not. This is worse than regular randomization, because there could be differences between these health centers (eg one might have better doctors who otherwise give better treatment, one might be in the poor part of town and have sicker patients, etc). They checked to see if there were any differences between the groups, and it sure looks like there were (the experimental group had twice as many obese people as the controls), but as per them, these differences were not statistically significant. Note that if this did make a difference, it would presumably make ivermectin look worse, not better. The primary outcome was given as “increase discharge from outpatient care with COVID-19 mild disease”. This favored the treatment; only 2/110 patients in the ivermectin group failed to be discharged, compared to 20 patients in the control group. But, uh, these were at different medical centers. Can’t different medical centers just have different discharge policies? One discharges you as soon as you seem to be getting better, the other waits to really make sure? This is an utterly crap endpoint to do a cluster randomized controlled trial on. If you’re going to do cRCT, which is never a great idea, you should be using some extremely objective endpoint that doctors and clinic administrators can’t possibly affect, like viral load according to some third-party laboratory, using the same third-party laboratory for both clinics. This is such a bad idea that I can’t help worrying I’m missing or misunderstanding something. If not, this is dumb and bad and should be ignored. Mourya et al: We’re back in India. This is a nonrandomized study comparing 50 patients given ivermectin to 50 patients given hydroxychloroquine. No primary outcome was named, but they focus on PCR negativity. Only 6% of patients in the hydroxychloroquine group were negative, compared to 90% of patients in the ivermectin group! On what day did they do the test? Uh, kind of random, and they admit that “in [the hydroxychloroquine group], mean time difference from the date of initiation of treatment and second test was significantly longer (7.24±2.75 days) as compared to 5.22±1.21 days in [the ivermectin group] (p=0.021).” Since they assessed these groups at different times, we shouldn’t draw any conclusions from them getting different results. Except that as far as I can tell this should handicap ivermectin, making it especially impressive that it did better. But also, the ivermectin group was made mostly of people who had been asymptomatic at the beginning (70%), and the hydroxychloroquine group had almost no asymptomatic cases (8%) . They were giving the ivermectin to healthy people and the hydroxychloroquine to sick people! They admit deep in the discussion that this “may be a confounding factor”. So basically they got totally different groups of people, tested them at totally different times, and the two sets of test results differed. So what? So this is why normal people do RCTs instead of whatever the heck this is, that’s what. Loue et al: …this one isn’t going to be an RCT either. Loue tells a story about a cluster of COVID cases at the French nursing home where he works. He asked people if they wanted to try ivermectin; 10 did and 15 didn’t. 1 ivermectin patient died, compared to 5 non-ivermectin patients. The non-ivermectin group looked a bit sicker than the ivermectin group in the inevitable Table 1, though it’s hard to tell. One interesting possible confounder (not mentioned, but I’m imagining it) is that demented patients probably couldn’t consent to ivermectin and ended up in the control group. This is another case of “I’m not going to trust anything that isn’t an RCT”. Merino et al: Another (sigh) non-RCT. Mexico City tried a public health program where if you called a hotline and said you had COVID, they sent you an emergency kit with various useful supplies. One of those supplies was ivermectin tablets. 18,074 people got the kit (and presumably some appreciable fraction took the ivermectin, though there’s no way to prove that). Their control group is people from before they started giving out the kits, people from after they stopped giving out the kits, and people who didn’t want the kits. There are differences in who got COVID early in the epidemic vs. later, and in people who did opt for medical kits vs. didn’t. To correct these, the researchers tried to adjust for confounders, something which - as I keep trying to hammer home again and again - never works. They found that using the kit led to a 75% or so reduction in hospitalization, though they were unable to separate out the ivermectin from the other things in the kit (paracetamol and aspirin), or from the placebo effect of having a kit and feeling like you had already gotten some treatment (if I understand right, the decision to go to the hospital was left entirely to the patient). I think this study is a moderate point in favor of giving people kits in order to prevent hospital overcrowding, but I’m not willing to accept that it tells us much about ivermectin in particular. Faisal et al: This one was published in The Professional Medical Journal (mispelled as “Profesional Medical Journal” in its URL), so you know it’s going to be good! It describes itself as “a cross-sectional study”, but later says it “randomized patients into two groups”, which would make it an RCT - I think they might just be using the term “cross-sectional” different from the standard American usage. A hospital in Pakistan got 50 patients on ivermectin + azithromycin, and another 50 on azithromycin alone. Primary outcome was not mentioned, and the data were presented confusingly, but a typical result is that only 4% of the ivermectin group had symptoms lasting more than 10 days, whereas 16% of the control group did, p < 0.01. They do a really weird thing where they compare how long it took symptoms to resolve between IVM and control groups within each bin. That is, if I’m understanding correctly, they ask “of the people who took between 3-5 days for symptoms to resolve, did they resolve faster for IVM or control?”. This is an utterly bizarre analysis to perform, although it doesn’t affect the fact that their other results still seem to favor ivermectin. Maybe I’m confused about what’s going on here. I’ve mostly been letting people off easy on no placebo, but I as far as I can tell (not very far) this paper seems to be going off whether patients reported continuing to have symptoms to the hospital doing the study, and I think that is potentially susceptible to placebo effects. Additionally, there’s no preregistration, and even though they talk a lot about doing PCR tests they don’t present the results. This is by no means the worst study here but I still think it’s pretty low quality and I don’t trust it. Aref et al: This one is published in the International Journal Of Nanomedicine, even though I’m pretty sure that isn’t a real thing. In this case the “nanomedicine” is a new nasal spray version of ivermectin which is so confusing I cannot for the life of me figure out what dose they are giving these patients. This Egyptian study gives 57 patients intranasal ivermectin plus hydroxychloroquine, azithromycin, oseltamavir, and some vitamins; another 57 patients get all that stuff except the ivermectin. Primary outcome is not stated, but they look at various symptoms, all of which look better in the ivermectin group: 95% of ivermectin patients got negative PCRs at some time point, compared to 75% of controls, p = 0.004. I am pretty suspicious of this study, not least because it comes from Egypt which has an awful reputation for fake studies, and it returns extreme results that I wouldn’t expect even if ivermectin was actually a wonder drug. But I cannot find any particular thing wrong with it, nor did anyone else I looked at, so I will grudgingly let it stand. Krolewiecki et al: Another Argentine study. This one is a real RCT. 30 patients received ivermectin, 15 were the control group (no placebo, again). Primary outcome was difference in viral load on day 5. The trend favored ivermectin but it was not statistically significant, although they were able to make it statistically significant if they looked at a subset of higher-IVM-plasma-concentration patients. They did not find any difference in clinical outcomes. A pro-ivermectin person could point out that in the subgroup with the highest ivermectin concentrations, the drug seemed to work. A skeptic could point out that this is exactly the kind of subgroup slicing that you are not supposed to do without pre-registering it, which I don’t think this team did. I agree with the skeptic. Vallejos et al: Another Argentine study. It’s big (250 people in each arm). It’s an RCT. It tries to define a primary outcome (“Primary outcome: the trial ended when the last patient who was included achieved the end of study visit”), but that’s not what “primary outcome” means, and they don’t offer an alternative. Other outcomes: no difference in PCR on days 3 or 12. Hospitalization is nonsignificantly better in the ivermectin group (14 vs. 21, p = 0.2), but death is nonsigificantly better in the placebo group (3 vs. 4, p = 0.7). This isn’t even the kind of nonsignificant that might contribute to an exciting meta-analysis later. This is just a pure null result. I cannot find any problem with this study, and neither can anyone else I checked. This is the biggest RCT we’ve seen so far, so we should take it seriously. TOGETHER Trial: Speaking of big RCTs… This one hasn’t been published yet. There’s a video of a talk about it, but I am not going to watch it, because it is a video, so I am getting information secondhand from eg here. Apparently, it compares 677 people (!) randomized to ivermectin to 678 people randomized to placebo. 86 ivermectin patients ended up in the hospital compared to 95 placebo patients, p-value not significant. This was a really big professional trial done by bigshot researchers from a major Canadian university, and the medical establishment is taking it much more seriously than any of these others. When it comes out, it will probably get published in a top journal. When discussing Lopez-Medina, I wrote: When people say things like “sure, a lot of small studies show good results for ivermectin, but the bigger and more professional trials don’t”, this is one of the two big professional trials they’re talking about. This is the other one. Not coincidentally, it’s also the other trial that ivmmeta.com has a warning letter underneath telling you to disregard. Their main concern is that instead of truly randomizing patients to ivermectin vs. placebo, they did a time-dependent randomization that meant during some weeks more patients were getting one or the other. This is a problem because the trial takes place in Brazil, where different variants were more common at different times. Here’s their image: On the one hand, I have immense contempt for ivmmeta for letting all those other awful studies pass and then pulling out all the stops to try to nitpick this one. I have no idea if their proposed randomization failure really happened. And no doubt the reason they’re even able to investigate this is that this study is really careful and transparent - most of them don’t tell you anything about their randomization method. I would be shocked if other studies don’t have all these problems and worse. On the other hand, the point isn’t to be fair, it’s to be right. And this is a potential confounder. Not a huge one. But a potential one. I guess all we can do is try to bound the damage. Even if the confounding is 100% real and bad, there’s no way to make this study consistent with the crazy super-pro-ivermectin results of studies like Espitia-Hernandez and Aref. And even if we deny any confounding, we see the same slight pro-ivermectin trend - 86 hospitalizations vs. 95 - that we’ve seen in so many other studies. Nothing is going to make me believe that this isn’t in the top 33% of studies we’ve been looking at, so let’s add it as grist for the meta-analysis (though maybe not quite as much grist as its vast size indicates) and move on, angrily. Buonfrate et al: An Italian RCT. Patients were randomized into low-dose ivermectin (32), placebo (29), or high-dose ivermectin (32). Primary outcome was viral load on day 7. There was no significant difference (average of 2 in ivermectin groups, 2.2 in placebo group). They admit that they failed to reach the planned sample size, but did a calculation to show that even if they had, the trial could not have returned a positive result. Clinically, an average of 2 patients were hospitalized in each of the ivermectin arms, compared to 0 in the placebo arm - which bucks our previously-very-constant pro-ivermectin trend. Mayer et al: Not an RCT. Patients in an Argentine province were offered the opportunity to try ivermectin; 3266 said yes and become the experimental group, 17966 said no and became the control group. There were many obvious differences between the groups, but they all seemed to handicap ivermectin. There was a nonsignificant trend toward less hospitalization and significantly less mortality (1.5% vs. 2.1%, p = 0.03). While looking into this study, I learned the term “immortal time bias”. This means a period in between selection for the study and the beginning of study recording where patient outcomes are not counted. I think the problem here is that if you signed up for the system on Day X, and if you got sick before they could give you ivermectin, you were in the control group. See this Twitter thread, I have not confirmed everything he says. This only hardens my resolve to stay away from non-RCTs. Borody et al: Our last paper! …is it a paper? I can’t find it published anywhere. It mostly seems to be on news sites. Doesn’t look peer-reviewed. And it starts with “Note that views expressed in this opinion article are the writer’s personal views”. Whatever. 600 Australians were treated with ivermectin, doxycycline, and zinc. The article compares this to an “equivalent control group” made of “contemporary infected subjects in Australia obtained from published Covid Tracking Data”; this is not how you control group, @#!% you. Then it gets excited about the fact that most patients had better symptoms at the end of the ten-day study period than the beginning (untreated COVID resolves in about ten days). Why are these people wasting my time with this? Let’s move on. The Analysis If we remove all fraudulent and methodologically unsound studies from the table above, we end up with this: Gideon Meyerowitz-Katz, who investigated many of the studies above for fraud, tried a similar exercise. I learned about his halfway through, couldn’t help seeing it briefly, but tried to avoid remembering it or using it when generating mine (also, I did take the result of his fraud investigations into account), so they should be considered not quite independent efforts. His looks like this: He nixed Chowdhury, Babaloba, Ghauri, Faisal, and Aref, but kept Szenta Fonseca, Biber (?), and Mayer. There was correlation of 0.45, which I guess is okay. I asked him about his decision-making, and he listed a combination of serious statistical errors and small red flags adding up. I was pretty uncomfortable with most of these studies myself, so I will err on the side of severity, and remove all studies that either I or Meyerowitz-Katz disliked. We end up with the following short list: We’ve gone from 29 studies to 11, getting rid of 18 along the way. For the record, we eliminated 2/19 for fraud, 1/19 for severe preregistration violations, 10 for methodological problems, and 6 because Meyerowitz-Katz was suspicious of them. …but honestly this table still looks pretty good for ivermectin, doesn’t it? Still lots of big green boxes. Meyerowitz-Katz accuses ivmmeta of cherry-picking what statistic to use for their forest plot. That is, if a study measures ten outcomes, they sometimes take the most pro-ivermectin outcome. Ivmmeta.com counters that they used a consistent and reasonable (if complicated) process for choosing their outcome of focus, that being: If studies report multiple kinds of effects then the most serious outcome is used in calculations for that study. For example, if effects for mortality and cases are both reported, the effect for mortality is used, this may be different to the effect that a study focused on. If symptomatic results are reported at multiple times, we used the latest time, for example if mortality results are provided at 14 days and 28 days, the results at 28 days are used. Mortality alone is preferred over combined outcomes. Outcomes with zero events in both arms were not used (the next most serious outcome is used — no studies were excluded). For example, in low-risk populations with no mortality, a reduction in mortality with treatment is not possible, however a reduction in hospitalization, for example, is still valuable. Clinical outcome is considered more important than PCR testing status. When basically all patients recover in both treatment and control groups, preference for viral clearance and recovery is given to results mid-recovery where available (after most or all patients have recovered there is no room for an effective treatment to do better). If only individual symptom data is available, the most serious symptom has priority, for example difficulty breathing or low SpO2 is more important than cough. I’m having trouble judging this, partly because Meyerowitz-Katz says ivmmeta has corrected some earlier mistakes, and partly because there really is some reasonable debate over how to judge studies with lots of complicated endpoints. By this point I had completely forgotten what ivmmeta did, so I independently coded all 11 remaining studies following something in between my best understanding of their procedure and what I considered common sense. The only exception was that when the most severe outcome was measured in something other than patients (ie average number of virus copies per patient), I defaulted to one that was measured in patients instead, to keep everything with the same denominator. My results mostly matched ivmmeta’s, with one or two exceptions that I think are within the scope of argument or related to my minor deviations from their protocol. Placebo vs. ivermectin groups sometimes differed in size, which I’ve adjusted for and rounded off. Probably I’m forgetting some reason I can’t just do simple summary statistics to this, but whatever. It is p = 0.15, not significant. This is maybe unfair, because there aren’t a lot of deaths in the sample, so by focusing on death rather than more common outcomes we’re pointlessly throwing away sample size. What happens if I unprincipledly pick whatever I think the most reasonable outcome to use from each study is? I’ve chosen “most reasonable” as a balance between “is the most severe” and “has a lot of data points”: Now it’s p = 0.04, seemingly significant, but I had to make some unprincipled decisions to get there. I don’t think I specifically replaced negative findings with positive ones, but I can’t prove that even to myself, let alone to you. [UPDATE 5/31/22: A reader writes in to tell me that the t-test I used above is overly simplistic. A Dersimonian-Laird test is more appropriate for meta-analysis, and would have given 0.03 and 0.005 on the first and second analysis, where I got 0.15 and 0.04. This significantly strengthens the apparent benefit of ivermectin from ‘debatable’ to ‘clear’. I discuss some reasons below why I am not convinced by this apparent benefit.] (how come I’m finding a bunch of things on the edge of significance, but the original ivmmeta site found a lot of extremely significant things? Because they combined ratios, such that “one death in placebo, zero in ivermectin” looked like a nigh-infinite benefit for ivermectin, whereas I’m combining raw numbers. Possibly my way is statistically illegitimate for some reason, but I’m just trying to get a rough estimate of how convinced to be) So we are stuck somewhere between “nonsignificant trend in favor” and “maybe-significant trend in favor, after throwing out some best practices”. This is normally where I would compare my results to those of other meta-analyses made by real professionals. But when I look at them, they all include studies later found to be fake, like Elgazzar, and unsurprisingly come up with wildly positive conclusions. There are about six in this category. One of them later revised their results to exclude Elgazzar and still found strong efficacy for ivermectin, but they still included Niaee and some other dubious studies. The only meta-analysis that doesn’t make these mistakes is Popp (a Cochrane review), which is from before Elgazzar was found to be fraudulent, but coincidentally excludes it for other reasons. It also excludes a lot of good studies like Mahmud and Ravakirti because they give patients other things like HCQ and azithromycin - I chose to include them, because I don’t think they either work or have especially bad side effects, so they’re basically placebo - but Cochrane is always harsh like this. They end up with a point estimate where ivermectin cuts mortality by 40% - but say the confidence intervals are too wide to draw any conclusion. I think this basically agrees with my analyses above - the trends really are in ivermectin’s favor, but once you eliminate all the questionable studies there are too few studies left to have enough statistical power to reach significance. Except that everyone is still focusing on deaths and hospitalizations just because they’re flashy. Mahmud et al, which everyone agrees is a great study, found that ivermectin decreased days until clinical recovery, p = 0.003? So what do you do? This is one of the toughest questions in medicine. It comes up again and again. You have some drug. You read some studies. Again and again, more people are surviving (or avoiding complications) when they get the drug. It’s a pattern strong enough to common-sensically notice. But there isn’t an undeniable, unbreachable fortress of evidence. The drug is really safe and doesn’t have a lot of side effects. So do you give it to your patients? Do you take it yourself? Here this question is especially tough, because, uh, if you say anything in favor of ivermectin you will be cast out of civilization and thrown into the circle of social hell reserved for Klan members and 1/6 insurrectionists. All the health officials in the world will shout “horse dewormer!” at you and compare you to Josef Mengele. But good doctors aren’t supposed to care about such things. Your only goal is to save your patient. Nothing else matters. I am telling you that Mahmud et al is a good study and it got p = 0.003 in favor of ivermectin. You can take the blue pill, and stay a decent respectable member of society. Or you can take the horse dewormer pill, and see where you end up. In a second, I’ll tell you my answer. But you won’t always have me to answer questions like this, and it might be morally edifying to observe your thought process in situations like this. So take a second, and meet me on the other side of the next section heading. … … … … … The Synthesis Hopefully you learned something interesting about yourself there. But my answer is: worms! As several doctors and researchers have pointed out (h/t especially Avi Bitterman and David Boulware), the most impressive studies come from places that are teeming with worms. Mahmud from Bangladesh, Ravakirti from East India, Lopez-Medina from Colombia, etc. Here’s the prevalence of roundworm infections by country (source). But alongside roundworms, there are threadworms, hookworms, blood flukes, liver flukes, nematodes, trematodes, all sorts of worms. Add them all up and somewhere between half and a quarter of people in the developing world have at least one parasitic worm in their body. Being full of worms may impact your ability to fight coronavirus. Gluchowska et al write: Helminth [ie worm] infections are among the most common infectious diseases. Bradbury et al. highlight the possible negative interactions between helminth infection and COVID-19 severity in helminth-endemic regions and note that alterations in the gut microbiome associated with helminth infection appear to have systemic immunomodulatory effects. It has also been proposed that helminth co-infection may increase the morbidity and mortality of COVID-19, because the immune system cannot efficiently respond to the virus; in addition, vaccines will be less effective for these patients, but treatment and prevention of helminth infections might reduce the negative effect of COVID-19. During millennia of parasite-host coevolution helminths evolved mechanisms suppressing the host immune responses, which may mitigate vaccine efficacy and increase severity of other infectious diseases. Treatment of worm infections might reduce the negative effect of COVID-19! And ivermectin is a deworming drug! You can see where this is going… The most relevant species of worm here is the roundworm Strongyloides stercoralis. Among the commonest treatments for COVID-19 is corticosteroids, a type of immunosuppresant drug. The types of immune responses it suppresses do more harm than good in coronavirus, so turning them off limits collateral damage and makes patients better on net. But these are also the types of immune responses that control Strongyloides. If you turn them off even very briefly, the worms multiply out of control, you get what’s called “Strongyloides hyperinfection”, and pretty often you die. According to the WHO: The current COVID-19 pandemic serves to highlight the risk of using systemic corticosteroids and, to a lesser extent, other immunosuppressive therapy, in populations with significant risk of underlying strongyloidiasis. Cases of strongyloidiasis hyperinfection in the setting of corticosteroid use as COVID-19 therapy have been described and draw attention to the necessity of addressing the risk of iatrogenic strongyloidiasis hyperinfection syndrome in infected individuals prior to corticosteroid administration. Although this has gained importance in the midst of a pandemic where corticosteroids are one of few therapies shown to improve mortality, its relevance is much broader given that corticosteroids and other immunosuppressive therapies have become increasingly common in treatment of chronic diseases (e.g. asthma or certain rheumatologic conditions). So you need to “address the risk” of strongyloides infection during COVID treatment in roundworm-endemic areas. And how might you address this, WHO? Treatment of chronic strongyloidiasis with ivermectin 200 µg/kg per day orally x 1-2 days is considered safe with potential contraindications including possible Loa loa infection (endemic in West and Central Africa), pregnancy, and weight <15kg. Given ivermectin’s safety profile, the United States has utilized presumptive treatment with ivermectin for strongyloidiasis in refugees resettling from endemic areas, and both Canada and the European Centre for Disease Prevention and Control have issued guidance on presumptive treatment to avoid hyperinfection in at risk populations. Screening and treatment, or where not available, addition of ivermectin to mass drug administration programs should be studied and considered. This is serious and common enough that, if you’re not going to screen for it, it might be worth “add[ing] ivermectin to mass drug administration programs” in affected areas! Dr. Avi Bitterman carries the hypothesis to the finish line: First two images are with all relevant studies; second two are a sensitivity analysis that removes some of the most dubious. The good ivermectin trials in areas with low Strongyloides prevalence, like Vallejos in Argentina, are mostly negative. The good ivermectin trials in areas with high Strongyloides prevalence, like Mahmud in Bangladesh, are mostly positive. Worms can’t explain the viral positivity outcomes (ie PCR), but Dr. Bitterman suggests that once you remove low quality trials and worm-related results, the rest looks like simple publication bias: This is still just a possibility. Maybe I’m over-focusing too hard on a couple positive results and this will all turn out to be nothing. Or who knows, maybe ivermectin does work against COVID a little - although it would have to be very little, fading to not at all in temperate worm-free countries. But this theory feels right to me. It feels right to me because it’s the most troll-ish possible solution. Everybody was wrong! The people who called it a miracle drug against COVID were wrong. The people who dismissed all the studies because they F@#king Love Science were wrong. Ivmmeta.com was wrong. Gideon Meyerowitz-Katz was…well, he was right, actually, I got the worm-related meta-analysis graphic above from his Twitter timeline. Still, an excellent troll. Also, the best part is that I ignorantly asked, in my description of Mahmud et al above: And it was! It was a fluke! A literal, physical, fluke! For my whole life, God has been placing terrible puns in my path to irritate me, and this would be the worst one ever! So it has to be true! The Scientific Takeaway About ten years ago, when the replication crisis started, we learned a certain set of tools for examining studies. Check for selection bias. Distrust “adjusting for confounders”. Check for p-hacking and forking paths. Make teams preregister their analyses. Do forest plots to find publication bias. Stop accepting p-values of 0.049. Wait for replications. Trust reviews and meta-analyses, instead of individual small studies. These were good tools. Having them was infinitely better than not having them. But even in 2014, I was writing about how many bad studies seemed to slip through the cracks even when we pushed this toolbox to its limits. We needed new tools. I think the methods that Meyerowitz-Katz, Sheldrake, Heathers, Brown, Lawrence and others brought to the limelight this year are some of the new tools we were waiting for. Part of this new toolset is to check for fraud. About 10 - 15% of the seemingly-good studies on ivermectin ended up extremely suspicious for fraud. Elgazzar, Carvallo, Niaee, Cadegiani, Samaha. There are ways to check for this even when you don’t have the raw data. Like: The Carlisle-Stouffer-Fisher method: Check some large group of comparisons, usually the Table 1 of an RCT where they compare the demographic characteristics of the control and experimental groups, for reasonable p-values. Real data will have p-values all over the map; one in every ten comparisons will have a p-value of 0.1 or less. Fakers seem bad at this and usually give everything a nice safe p-value like 0.8 or 0.9.
Source. Real data would follow something like a bell curve. This is going to require a social norm of always sharing data. Even better, journals should require the raw data before they publish anything, and should make it available on their website. People are going to fight hard against this, partly because it’s annoying and partly because of (imho exaggerated) patient privacy related concerns. Somebody’s going to try make some kind of gated thing where you have to prove you have a PhD and a “legitimate cause” before you can access the data, and that person should be fought tooth and nail (some of the “data detectives” who figured out the ivermectin study didn’t have advanced degrees). I want a world where “I did a study, but I can’t show you the data” should be taken as seriously as “I determined P = NP, but I can’t show you the proof.” The second reason I think this, aside from checking for fraud, is checking for mistakes. I have no proof this was involved in ivermectin in particular. But I’ve been surprised how often it comes up when I talk to scientists. Someone in their field got a shocking result, everyone looked over the study really hard and couldn’t find any methodological problems, there’s no evidence of fraud, so do you accept it? A lot of times instead I hear people say “I assume they made a coding error”. I believe them, because I have made a bunch of stupid errors. Sometimes you make the errors for me - an early draft of this post of mine stated that there was an strong positive effect of assortative mating on autism, but when I double-checked it was entirely due to some idiot who filled out the survey and claimed to have 99999 autistic children. In this very essay, I almost said that a set of ivermectin studies showed a positive result because I was reading the number for whether two lists were correlated rather than whether a paired-samples t-test on the lists was significant. I think lots of studies make these kinds of errors. But even if it’s only 1%, these will make up much more than 1% of published studies, and much more than 1% of important ground-breaking published studies, because correct studies can only prove true things, but false studies can prove arbitrarily interesting hypotheses (did you know there was an increase in the suicide rate on days that Donald Trump tweeted?!?) and those are the ones that will get published and become famous. So if the lesson of the original replication crisis was “read the methodology” and “read the preregistration document”, this year’s lesson is “read the raw data”. Which is a bit more of an ask. Especially since most studies don’t make it available. The Sociological Takeaway I’ve been thinking about this one a lot too. Ivermectin supporters were really wrong. I enjoy the idea of a cosmic joke where ivermectin sort of works in some senses in some areas. But the things people were claiming - that ivermectin has a 100% success rate, that you don’t need to take the vaccine because you can just take ivermectin instead, etc - have been untenable not just since the big negative trials came out this summer, but even by the standards of the early positive trials. Mahmud et al was big and positive and exciting, but it showed that ivermectin patients recovered in about 7 days on average instead of 9. I think the conventional wisdom - that the most extreme ivermectin supporters were mostly gullible rubes who were bamboozled by pseudoscience - was basically accurate. Mainstream medicine has reacted with slogans like “believe Science”. I don’t know if those kinds of slogans ever help, but they’re especially unhelpful here. A quick look at ivermectin supporters shows their problem is they believed Science too much. @jonno_bosch I work in hospitality so I need things to return to normal ASAP. I am using Ivermectin as a prophylactic. Hugely influenced by Carvallo trail and Chala trail which showed huge protection","username":"Bannisterious","name":"Andrew Bannister","profile_image_url":"","date":"Fri Feb 12 16:21:14 +0000 2021","photos":[],"quoted_tweet":{},"reply_count":0,"retweet_count":0,"like_count":0,"impression_count":0,"expanded_url":{},"video_url":null,"belowTheFold":true}" data-component-name="Twitter2ToDOM"> @mtskullcrusher @HereComeTheJud @therealjosexy @joeycadre @PeegeRiley @dcwickedestcity @blaireerskine Read Raad. Or Mahmud. Or ICON study from Florida. Or Mexico City hospitalizations study. Or Niaee. Or...\n\nOr just type \"ivermectin covid\" in Google Scholar and read.","username":"fatlas6","name":"fatlas","profile_image_url":"","date":"Thu Sep 02 21:34:59 +0000 2021","photos":[],"quoted_tweet":{},"reply_count":0,"retweet_count":0,"like_count":1,"impression_count":0,"expanded_url":{},"video_url":null,"belowTheFold":true}" data-component-name="Twitter2ToDOM"> They have a very reasonable-sounding belief, which is that if dozens of studies all say a drug works really well, then it probably works really well. When they see dozens of studies saying a drug works really well, and the elites saying “no don’t take it!”, their extremely natural conclusion is that it works really well but the elites are covering it up. Sometimes these people even have a specific theory for why elites are covering up ivermectin, like that pharma companies want you to use more expensive patented drugs instead. This theory is extremely plausible. Pharma companies are always trying to convince people to use expensive patented drugs instead of equally good generic alternatives. Ivermectin believers probably heard about this from the many, many good articles by responsible news outlets, discussing the many, many times pharma companies have tried to trick people into using more expensive patented medications. Like this ACSH article about Nexium. Or my article on esketamine. Given that dozens of studies said a drug worked, and elites continued to deny it worked, and there are well-known times where elites lie about drugs in order to make money, it was an incredibly reasonable inference that this was one of those times. If you have a lot of experience with pharma, you know who lies and who doesn’t, and you know what lies they’re willing to tell and which ones they shrink back from. As far as I know, no reputable scientist has ever come out and said ‘esketamine definitely works better than regular ketamine’. The regulatory system just heavily implied it. I claim that with ivermectin, even the people who don’t usually lie were saying it was ineffective, and they were saying it more directly and decisively than liars usually do. But most people can’t translate Pharma → English fluently enough to know where the space of “things people routinely lie about and nobody worries about it too much” ends. So they incredibly reasonably assume anything could be a lie. And if you don’t know which statements about pharmaceuticals are lies, “the one that has dozens of studies contradicting it” is a pretty good heuristic! If you tell these people to “believe Science”, you will just worsen the problem where they trust dozens of scientific studies done by scientists using the scientific method over the pronouncements of the CDC or whoever. So “believe experts”? That would have been better advice in this case. But the experts have beclowned themselves again and again throughout this pandemic, from the first stirrings of “anyone who worries about coronavirus reaching the US is dog-whistling anti-Chinese racism”, to the Surgeon-General tweeting “Don’t wear a face mask”, to government campaigns focusing entirely on hand-washing (HEPA filters? What are those?) Not only would a recommendation to trust experts be misleading, I don’t even think you could make it work. People would notice how often the experts were wrong, and your public awareness campaign would come to naught. But also: one of the data detectives who exposed some fraudulent ivermectin papers was a medical student, which puts him somewhere between pond scum and hookworms on the Medical Establishment Totem Pole. Some of the people whose studies he helped sink were distinguished Professors of Medicine and heads of Health Institutes. If anyone interprets “trust experts” as “mere medical students must not publicly challenge heads of Health Institutes”, then we’ve accidentally thrown the fundamental principle of science out with the bathwater. But Pierre Kory, spiritual leader of the Ivermectin Jihad, is a distinguished critical care doctor. What heuristic tells us “Medical students should be allowed to publicly challenge heads of Health Institutes” but not “Distinguished critical care doctors should be allowed to publicly challenge the CDC”? Then what about “believe statisticians”? I’ve never heard anyone propose this before, but re-centering the mystique of scientific-expertise in study-analyzers and study-aggregators rather than object-level scientists is…one way you could go, I guess. Statisticians admittedly sort of failed us here: the first several meta-analyses said ivermectin worked. But the statistical process - the idea that studies are raw materials, but it takes skill to turn them into the finished good of scientific knowledge - sort of comes out looking good. If we need to summarize our takeaway in a slogan of exactly two words, one of which is “trust”, you could do worse than this one. (am I secretly suggesting that we make rationality higher status? Maybe, although rationalists did no better here during the early phase of “looks promising so far” than anyone else, and it was researchers digging into the nitty-gritty of the data who really solved this.) Or maybe this is the wrong level on which to think about this. Maybe there isn’t and can’t be a simple heuristic you can teach everyone in school or via a PR campaign which will lead to them having making good health decisions in an adversarial information environment, without having any negative effects anywhere else. But you also don’t want people to make bad health decisions. So what do you do? The Political Takeaway All of this is complicated by the impression many people (including me) have, that ivermectin boosterism and vaccine denialism are closely linked. The ivermectin evidence is complicated. There’s room for doubt. I can maybe see room for doubt on some marginal vaccine-related issues like how seriously to take the occasional reports of myocarditis in teens. But the basic issue - that the vaccine works really well and is incredibly safe for adults - seems beyond question. Yet people keep questioning it. I think it’s important to address ivermectin support on its own terms - as a potentially plausible scientific theory in a debris field of confusing evidence, which should be debated to the usual standards of scientific debate. I’ve tried to do that above. But this picture wouldn’t be complete without acknowledging the overlap with vaccine denial - a segment of people who are completely crazy and wrong and who happen to have fixated on this mildly interesting question as opposed to some other one with even less evidence. I’ve been trying to figure out a model where ivermectin support and vaccine denialism both make visceral sense to me, and here’s what I’ve got: Imagine that in 2025, an alien invasion fleet reaches Earth. But it got hit by a supernova on the way, the spaceships are partly disabled, and they’re only able to conquer some out-of-the-way place - let’s say Australia. There’s a few cycles of conflict and cease-fire, a few cities get nuked, and finally we settle into an uneasy peace. Over the next few years, humanity grudgingly admits the invaders into the world community. They get a seat in the United Nations. We sort of cooperate with them on projects that are important to both sides, like stopping climate change. We still hate them, but only at the level of ordinary international rivalries, like USA/USSR. In 2035, the aliens announce that a quantum memetic plague from the Andromeda Sector has reached Earth. Billions of people will die unless we let them put an immunity-granting cybernetic implant in all humans’ brain. The aliens admit we haven’t always been friends, and honestly they would still like to conquer us someday. But this plague is an ancient enemy of all sentient beings, they dealt with it on their homeworld eons ago, and they want to help us out here. Humans apparently don’t have the ability to detect quantum memetic plagues, but mortality rates for over-65s do seem weirdly high this year, something like 10x worse than a normal flu season. Do you let the aliens put an implant in your brain, or not? If it helps, the aliens look like this. Surely anyone with a brain that size must know what they’re talking about, right? (source) Fine, you don’t have to decide immediately. The brain implants aren’t even ready yet. Some human scientists suggest wearing face masks in the interim. The aliens say no, that will never work, that’s not how you deal with quantum memetic plagues, if you do anything other than wait for the brain implants you’re anti-science idiots who are wasting precious time and will kill millions of people. Human nations try face masks anyway…and they clearly and conspicuously work. The aliens say whatever, we’re still the advanced spacefaring civilization here, maybe it works for humans but that’s not the point, the point is you’ve got to let us put implants in your brains. Some human scientists suggest reopening vital services. The aliens say no, millions will die, this is “mass human sacrifice”, humans apparently must care nothing about their families’ lives. The humans try reopening anyway, and…it goes kind of okay? Maybe the death rate goes up 10% to 20% or so, hard to say? The aliens say whatever, maybe their calculations were off by a few orders of magnitude, the point is, you have to let us put implants in your brain or you’ll all die. Then some human scientists suggest vaccinating against the plague. The aliens say this is idiotic, vaccines originally come from cowpox, even the word “vaccine” comes from Latin vaccus meaning “cow”, are you saying you want cow medicine instead of actual brain implants which alien Science has proven will work? They make lots of cartoons displaying humans who want vaccines as having cow heads, or rolling around in cow poop. Meanwhile, the first few dozen studies show vaccines work great. Many top human leaders, including war heroes from the struggle against the aliens, get vaccines and are seen going out in public, looking healthy and happy. The aliens say that human science is hopelessly flawed because of complicated statistical concepts that inferior life forms like us don’t even have words for. You need to ignore all the studies and meta-analyses showing that vaccines definitely work, and let the aliens give you brain implants instead. So do you let the aliens put an implant in your brain, or not? Obviously you think long and hard before doing this. And obviously this is an extended metaphor for vaccine denialism. So what’s the difference between the metaphor (where you’re presumably anti-implant) and the real world (where you’re presumably pro-vaccine?) For me, it’s a combination of: The aliens are hostile, so I don’t trust them no matter how smart they are
PLAYA DEL CARMEN, MEXICO Contact: Drew (andrew.d.cutler@gmail.com) Date: April 13 Time: 6:00 PM Coordinates: https://plus.codes/76GJJWPH+WQ Location: Tohuka Park, in the main pavilion
MEXICO CITY Contact: Francisco (fagarrido@gmail.com) Date: May 7 Time: 4:00 PM Coordinates: https://plus.codes/76F2CRH5+J2 Location: Cafe Toscano Notes: Please RSVP at fagarrido@gmail.com. The place is not very large, so if there is too much interest I may change the location.
Daniel is part-Italian and part-Mexican. He’s a navy vet, CEO of an “independent production company”, CFO of a private cryptocurrency investment firm, and a mixed martial arts instructor. He tried running for Congress a few years ago, but lost.
PROUD OF MY MEXICAN ANCESTRY FROM MICHOACAN/ GUANAJUATO
Spanish: Orgulloso de mi ascendencia Mexicana y mis padres inmigrantes. Necesitamos a "MANDO" para deveras ayudar a nuestra comunidad Latina. Mis abuelos piscaban fresas y naranjas cuando llegaron a California, ahora por su esfuerzo y la ayuda de Dios soy un Candidato Catolico pidiendo su voto.
Though President Polk wanted the land owned by Mexico, he did not simply threaten to invade unless the Mexican government handed it over”.
His legal justification for the war looked back to 1821, when Mexico secured its independence from Spain. The years following independence brought deep instability. Mexico went through thirty-five administrations in thirty-four years. U.S. citizens conducting business there were subject to illegal confiscations of property and physical assaults by government officials and made numerous claims against Mexico for compensation. U.S. diplomats collected these complaints and presented them to the Mexican government. (Chapter 2)
Under a succession of Presidents, the US threatened Mexico with war if redress wasn't provided. We went to arbitration in 1839 with a panel of 2 Mexicans, 2 Americans, and the representative of the King of Prussia.
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
V. So why is the Central Valley so bad? It’s an agricultural region, but lots of places are agricultural. It got lots of immigrants, but no more than many other places. It’s polluted - but so was LA, and LA rebounded. This is just a weak guess, but I think it starts with their crops. The Midwest grows mostly corn and wheat. The Central Valley is more fruits, vegetables, and nuts. Corn and wheat are easier to harvest, so middle-class farmers can own the farm and buy a mechanical harvester or something. Fruits, vegetables, and nuts benefit from intensive manual picking, so farm owners hire outside labor. According to Carolina Demography: There are about 3 million farmworkers in the United States: about two million are family farmworkers and another one million are hired farmworkers…nationally, about three-fourths of hired farmworkers are foreign-born; most (69%) were born in Mexico; 6% were born in Central America; and 1% were born in another country. Given that these are mostly Mexican immigrants, we’re probably not talking about people who are hired to grow corn in Kansas. I think plausibly the majority of US hired farmworkers live in California’s Central Valley. This makes it a sort of plantation agriculture system, which naturally tends towards landowners taking all the gains and workers ending up as an underclass. In the mid-20th century, the local plantation underclass was made of Okies (cf. The Grapes of Wrath). In the later 20th century, many immigrants moved in, lowering wages. Although immigrants don’t usually lower wages, this is because there are usually lots of industries for people to branch out into, but the Central Valley only has agriculture. Also, agribusinesses were becoming better at mechanizing their operations. Although technology doesn’t usually lower wages, again, this requires lots of diverse industries, and the Central Valley only had agriculture. All of this corresponds to the 1975-1985 period on the graphs where wages were going down. But it sounded from some of the testimonials above like the Central Valley didn’t become truly miserable until the late 90s. I’m not sure why this is. It could be the immigrants switching from being migrant laborers to raising families, and those families were impacted by poverty and inequality in a way the original migrants weren’t. It could be worsening drug problems as new drugs get invented and go down in price. (I’m not sure if NIMBYism and rising house prices also played a part. House prices do seem to have risen, a lot, but I was under the impression that building things in the Central Valley was easy and most of a house’s price there is construction rather than land. I’m not sure why house prices would have gone up so much since 1990 if this were true, though.) Other things that the articles I read emphasized: There’s a severe drought in the Central Valley right now. This is probably partly climate change, partly bad luck, and partly California diverting water to hydrate growing coastal cities. This has made everything worse (but then why isn’t that reflected in worsening economic statistics?)
I looked for photos of the Central Valley to illustrate this article, but none of them were quite as I remember it. This one from Sacramento Bee is the closest I could find. But imagine it through a layer of haze, and also you can’t see well because you are in the process of dying from heatstroke. Of large Central Valley cities, Sacramento has a median income of $33,565 (but it’s the state capital, which inflates it with politicians and lobbyists), Fresno of $25,738, and Bakersfield of $30,144. Compare to Mississippi, where the state capital of Jackson has $23,714, and numbers 2 and 3 cities Gulfport and Southhaven have $25,074 and $34,237. Overall Missisippi comes out worse here, and none of these seem horrible compared to eg Phoenix with $31,821. Given these numbers (from Google), urban salaries in the Central Valley don’t seem so bad. But when instead I look directly at this list of 280 US metropolitan areas by per capita income, numbers are much lower. Bakersfield at $15,760 is 260th/280, Fresno is 267th, and only Sacramento does okay at 22nd. Mississippi cities come in at 146, 202, and 251. Maybe the difference is because Google’s data is city proper and the list is metro area? Still, it seems fair to say that the Central Valley is at least somewhat in the same league as Mississippi, even though exactly who outscores whom is inconsistent. III. What do the people who live in the Valley think went wrong? What The Hell Is Wrong With California’s Central Valley?, starting around 9:30, interviews a local conservative realtor (most people in the Valley are conservative; I haven’t found a liberal equivalent). He says that the farms in the Central Valley used to be manned by migrant workers, who would come from Mexico, work for a season, then go back to Mexico and live off their earnings for the rest of the year. Later, policies shifted to welcoming them and granting them citizenship, so many of them came over and brought their families. But around the same time there was a drought, the farm industry crashed, the remaining farms mechanized, all the immigrants were left without work, they got on welfare, and they weren’t able to get off of it. He doesn’t say exactly when this happened, but he says times were good when he was a child, and he looks like he’s in his 30s or 40s. So if he’s 35 and things started going bad when he was 10, that would mean he thinks things started going bad around 1995 to 2000. Here’s a story in the LA Times from 1999, which talks about how things are starting to get bad. It admits that Californians like to poke fun at the Central Valley, but it seems to be just that - poking fun - and not freaking out about poverty and dysfunction the way articles about the Valley do now. But it ends by saying that things are getting worse: To be honest, living in the Central Valley takes some getting used to, especially if you’re from the coast. It’s an acquired taste. Oppressive heat in summer. Depressing tule fog in winter. Sure, fall and spring are OK. But where aren’t they? First-rate culture is scarce. The state capital doesn’t even have a symphony. One of the attractions--it’s almost a local joke--is the ability to get away, particularly from Sacramento. It’s 90 minutes to San Francisco in one direction, or skiing in another; two hours-plus to the ocean or Tahoe […] Still, earthquakes aren’t a menace to most people. And it doesn’t take long before you begin to appreciate certain benefits--indeed, to understand that some Central Valley burgs, especially the capital, are among California’s best kept secrets. Or, at least, they have been. Continuing: When I moved here nearly 40 years ago--the first of three times--summer skies were blue and the stars bright. Fishing was easy in the rivers and pheasant hunting was 10 minutes from town--in fact, where I now live. All this good life, however, has been changing. Sacramento is now the sixth smoggiest area in the country. A gloomy, beige pall greets motorists as they descend from the Sierra. Even worse is the San Joaquin Valley, from Stockton to Bakersfield. It’s rated the nation’s fourth smoggiest region […] And this brings us to the root problem: a population explosion, fed notably by commuters spilling over the Grapevine from L.A. into Bakersfield, and from the Bay Area into the northern San Joaquin Valley, turning farms into houses and freeways into parking lots. In Sacramento, high-tech industry is generating jobs and sprawl. Up and down the valley, people without job skills are having babies and going on welfare. Many are immigrants from Mexico and Southeast Asia. “The population is growing at a faster pace than the economy,” notes Dan Whitehurst, a former Fresno mayor who is running again. “Livability is becoming more of an issue. But the biggest issue still is jobs.” That’s because, aside from Sacramento, the Central Valley has not cashed in on California’s economic boom. Unemployment in the San Joaquin Valley is roughly double the state average. It’s smoggy. Traffic’s getting worse. Farms are disappearing. There aren’t enough jobs. And, says pollster Mark Baldassare, people are “myopic” about their plight. It finishes: “We have a huge problem. ‘No way L.A.’ has been our slogan. But if we build nonstop houses, we’ll be worse than L.A. because we’ll have destroyed our [farm] economic base. . . . There’s no regional leadership. More state officials need to decide this area matters and poke their heads up out of the fog.” The fog and the smog. If not, one day there’ll be no getting used to the place. This is a weird article. It seems to confirm that things used to be better - nobody would call the Central Valley “the good life” now. But its concerns are smog, sprawl, and decreasing share of agriculture. These seem like the problems of somewhere that’s growing - local NIMBYs complaining that too many people want to move in. Today the problem is more that everyone in the Central Valley wants to leave. The piece sort of touches on poverty - “people without job skills are having babies and going on welfare” and “the population is growing at a faster pace than the economy” - but it’s still a weird emphasis, and one that makes me think of this as supporting the “problems were starting in the 90s” view. But by 2012, things were clearly very bad - here’s an article about how Census Shows Central Valley Areas Among Poorest In Nation. It says: Experts say the poverty problem in the nation’s agricultural powerhouse is deeply ingrained. The most important barrier is the valley’s lack of economic diversity. There are simply too few good nonagricultural jobs around and jobs in agriculture tend to be low-wage ones — except for those who run agribusinesses. “It’s a pretty ag-heavy region, so the inequality of wages and the opportunity to earn better wages is really skewed,” said Caroline Farrell, executive director of the Delano-based Center on Race, Poverty & the Environment. “If you own a farm, you’re apt to earn more wealth, while if you’re a farmworker, don’t earn very much.” The valley has not been able to bring or retain many new companies partly because it lacks a qualified workforce, said Atonio Avalos, associate professor of economics at Fresno State University. “We have an issue of skills mismatch,” Avalos said. “Companies may be offering jobs, but the skills of people in the valley are not ones they are looking for.” Students who want to get a college degree face many barriers, he said, and public funding for education is being slashed. Those who do graduate leave to find jobs elsewhere. The valley also doesn’t offer attractive amenities and has serious problems such as air pollution that have gone unaddressed. “If you’re a doctor or engineer, there are other places where you can make good money and live in better conditions,” Avalos said. “Many people don’t come here or leave because of the high incidence of asthma and other respiratory problems.” This sounds like things were already pretty bad in 2012, maybe bad enough that they must have been getting worse for longer than 10 or 15 years, I don’t know. IV. What do the data say? Here are some economic time series. I couldn’t find any good long-term ones; the least bad one comes from this unsourced report: Here it looks like things got worse from 1975 - 1985, and then depending on county there was a slower-to-imperceptible decline thereafter. FRED only has data since 1989, but agrees that things haven’t gotten worse since then. Here’s unemployment: Is this just because people got discouraged (or on welfare) and stopped seeking employment, and so stopped showing up in the statistics? Here’s a graph of Total Employed Persons: In 1990, 303,000 people were employed out of a population of 354,000. In 2022, 430,000 people were employed out of a population of 542,000. So labor participation rate went from 86% to 79%. But national labor force participation decreased by about the same amount during that time, so I don’t think we should overemphasize that. And here are some other graphs I found useful: Fresno housing prices: Racial demographics: Source: Wikipedia. Central Valley cities like Fresno and Bakersfield aren’t really more Hispanic than other parts of California or Arizona, so if immigration or racial issues played a part it must have been more complicated than just numbers. Number of immigrants in California over time: Factors of productivity in agriculture: V. So why is the Central Valley so bad? It’s an agricultural region, but lots of places are agricultural. It got lots of immigrants, but no more than many other places. It’s polluted - but so was LA, and LA rebounded. This is just a weak guess, but I think it starts with their crops. The Midwest grows mostly corn and wheat. The Central Valley is more fruits, vegetables, and nuts. Corn and wheat are easier to harvest, so middle-class farmers can own the farm and buy a mechanical harvester or something. Fruits, vegetables, and nuts benefit from intensive manual picking, so farm owners hire outside labor. According to Carolina Demography: There are about 3 million farmworkers in the United States: about two million are family farmworkers and another one million are hired farmworkers…nationally, about three-fourths of hired farmworkers are foreign-born; most (69%) were born in Mexico; 6% were born in Central America; and 1% were born in another country. Given that these are mostly Mexican immigrants, we’re probably not talking about people who are hired to grow corn in Kansas. I think plausibly the majority of US hired farmworkers live in California’s Central Valley. This makes it a sort of plantation agriculture system, which naturally tends towards landowners taking all the gains and workers ending up as an underclass. In the mid-20th century, the local plantation underclass was made of Okies (cf. The Grapes of Wrath). In the later 20th century, many immigrants moved in, lowering wages. Although immigrants don’t usually lower wages, this is because there are usually lots of industries for people to branch out into, but the Central Valley only has agriculture. Also, agribusinesses were becoming better at mechanizing their operations. Although technology doesn’t usually lower wages, again, this requires lots of diverse industries, and the Central Valley only had agriculture. All of this corresponds to the 1975-1985 period on the graphs where wages were going down. But it sounded from some of the testimonials above like the Central Valley didn’t become truly miserable until the late 90s. I’m not sure why this is. It could be the immigrants switching from being migrant laborers to raising families, and those families were impacted by poverty and inequality in a way the original migrants weren’t. It could be worsening drug problems as new drugs get invented and go down in price. (I’m not sure if NIMBYism and rising house prices also played a part. House prices do seem to have risen, a lot, but I was under the impression that building things in the Central Valley was easy and most of a house’s price there is construction rather than land. I’m not sure why house prices would have gone up so much since 1990 if this were true, though.) Other things that the articles I read emphasized: There’s a severe drought in the Central Valley right now. This is probably partly climate change, partly bad luck, and partly California diverting water to hydrate growing coastal cities. This has made everything worse (but then why isn’t that reflected in worsening economic statistics?)
Possibly, what seems like poverty that is "humbling and a little scary" to rich coastal front-rowers, is a relatively pleasant middle class lifestyle to a Mexican immigrant earning 10x the median household of his home country?
(though see here for some discussion of the Mexico comparison)
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.
MEXICO CITY, MEXICO Contact: Francisco Garrido Contact Info: fagarrido[at]gmail[dot]com Time: Saturday, April 29th, 4:00 PM Location: Don Asado, Av. Homero 428, Polanco Coordinates: https://plus.codes/76F2CRQ7+26 Event Link: https://www.lesswrong.com/events/M7Rqk3rdtirpvvkaL/acx-cdmx-meetups-everywhere-2
An oversized jobs force creates a region workers abandon. When workers leave to work in distant cities, they improve their own situation, but their region of origin stagnates. This is true even if the workers send remittances, as in her main example, the town of Napizaro in rural Mexico. Most men from Napizaro work hundreds of kilometers north, in the factories of the dynamic city of Los Angeles. Even though they send back a lot of money to their families in Napizaro, Napizaro is never able to develop, because it imports everything it consumes and doesn’t replace those imports.
2: All the ancients, from Darius the Great to Augustus Caesar, agreed that the Nisean horse was the most majestic horse breed, the horse of kings. The Chinese fought a war (the War of Heavenly Horses) just to get access to a breeding stock. Then they sort of ambiguously went extinct during the Middle Ages. But here’s a modern Iranian horse enthusiast talking about which breeds might be its descendants. 3: Remember when the global community banned whaling, but some countries (eg Japan) continued doing it under the facade of “research”? With octopus factory farms under increasing scrutiny, UNAM university in Mexico is operating a “farm disguised as a research center”. 4: Genuinely new (to me) optical illusion: what is this guy is doing with his hands? Here’s a slow motion version that shows how it’s done. And some people in the replies were speculating this only works because of his dark skin, but here’s a white person doing the exact same thing (wait for it). 5: Shingles vaccine probably reduces incidence of dementia, suggesting that VZV (virus behind shingles and chickenpox) is a contributor. Further discussion here that I’m still trying to make sense of. 6: This deserves to go down in history alongside the wittiest Socratic comebacks in the Platonic dialogues: 7: Matt Lakeman: Notes On Nigeria. Great introduction to modern Nigerian history. Read it for the visceral understanding of the “resource curse” and why poor countries stay poor, but also: A savant is basically someone who has innate mental challenges but is extremely competent in a particular narrow domain. Some savants become obsessed with trains and become great engineers. Some become obsessed with computers and build software wonders. One of Abacha’s predecessors said of him: “He might not be bright upstairs, but he knows how to overthrow governments.” Kenyon elaborates: “It was as if Abacha was an idiot savant. Dull, even gormless, he filled his days with cowboy movies and sleeping off the previous night’s indulgences in alcohol and prostitutes. But he was possessed of a prodigious flair when it came to coups.” 8: Related to my previous subscribers-only post on the psychology of fantasy: Balioc’s Taxonomy Of What Magic Is Doing In Fantasy Books. See also Eliezer’s commentary. 9: New study on the timing of human mutations confirms Greg Cochran’s 2012 post about how after leaving Africa, modern humans were limited to “Arabia and surrounding regions” for ~30,000 - 50,000 years, racking up various new mutations and becoming adapted to life outside Africa (kabbalistically equivalent to the 40 years spent wandering in Sinai?). Most mutations in “fat storage, neural development, skin physiology, and cilia function”. 10: Iron Economist on Twitter: “Desalinization was one of the big technological success stories of the 2010s”. 11: Matt Bruenig argues against the Success Sequence, whose proponents (including Bryan Caplan) describe it as: 97% of Millennials who follow what has been called the “success sequence”—that is, who get at least a high school degree, work, and then marry before having any children, in that order—are not poor by the time they reach their prime young adult years (ages 28-34). Bruenig’s argument is mostly a lot of annoying “well maybe it’s just your cultural bias that makes you care about this”, but in the middle of this it mentions some genuinely strong points, especially that the research doesn’t measure “sequence”, but rather “current status”. So if you graduated, got a job, got married, and had children, but then lost your job, your would be counted as “not following the sequence” (same if you get divorced). Also, disabled and old people and their caretakers are excluded from the analysis, which in one sense is fair (your conclusion can be “abled young adults can avoid poverty through this method”) but in another sense risks reducing all of this to the more trivial-seeming statement “if you’re young, healthy, abled, married, don’t have to support anyone else, and have a full-time job, you’re probably not poor”. But the authors (channeled by Caplan) disagree: Some critics of the success sequence have argued that marriage does not matter once education and work status are controlled. The regression results indicate that after controlling for a range of background factors, the order of marriage and parenthood in Millennials’ lives is significantly associated with their financial well-being in the prime of young adulthood. Simply put, compared with the path of having a baby first, marrying before children more than doubles young adults’ odds of being in the middle or top income. Meanwhile, putting marriage first reduces the odds of young adults being in poverty by 60% (vs. having a baby first). The main thing I would want to look at here is how much of this is causal vs. just class selection: upper-class people are more likely to marry, less likely to divorce, and more likely to wait before having children. Has anyone followed some pre-selected group of equal class people (eg the population of some low-income school district) and seen how their own success varies with sequence compliance? 12: I’ve previously linked claims that vat-grown meat, freed from the tyranny of having to grow inside animals, will include tiger steaks, lion burgers, and the like. Once again global capitalism outpaces my wildest fantasies and offers burgers with woolly mammoth protein (so far just the myoglobin, not the meat). 13: The people who believed there was lots of gender bias in STEM academia, and the people who believed there wasn’t finally did an adversarial collaboration (a study co-conducted by two groups of scientists with conflicting theories, keeping each other honest). The results: Contrary to the omnipresent claims of sexism in these domains appearing in top journals and the media, our findings show that tenure-track women are at parity with tenure-track men in three domains (grant funding, journal acceptances, and recommendation letters) and are advantaged over men in a fourth domain (hiring). For teaching ratings and salaries, we found evidence of bias against women; although gender gaps in salary were much smaller than often claimed, they were nevertheless concerning. For ten years lots of important people told us again and again that discrimination against women in STEM was a massive problem. People who questioned its extent were accused of misogyny and sometimes fired, I got harassed and insulted for pointing out reasons the standard arguments didn’t seem to hold true. Millions of dollars were spent investigating and responding to the problem. And now I expect this pretty strong evidence that women were actually advantaged in hiring and had parity in most other things (the salary is probably just the usual negotiation issue) to produce no publicity, no apologies, and no soul-searching from the people leading the current round of anti-academia and anti-STEM inquisitions. Sorry, yes I am bitter, it just bothers me how much the people claiming that it’s urgently important that nobody is ever allowed to suggest they are wrong have a consistent track record of being totally and inexcusably wrong. 14: In my response to Sam Kriss, I speculated on what would happen if someone rewrote the MCU to sound like ancient myths. Thanks to the many people who reminded me of Star Wars as Icelandic saga and Star Wars as Irish epic. And Sam has a response . 15: @AISafetyMemes on Twitter is exactly what you’d expect from the name. I especially like the fire dogs: More here: 16: More AI links from this month: Can’t even list all the new people who have come out as AI x-risk believers, but you can just read the CAIS statement. The top signatures are Geoff Hinton, Yoshua Bengio, Demis Hassabis, Sam Altman, and Dario Amodei; aside from the usual suspects, they also have Bruce Schneier (computer security expert) , Dawn Song (computer scientist and security expert), Andy Clark (professor of cognitive philosophy, wrote Surfing Uncertainty), Eliezer Yudkowsky (he didn't sign the last one because he disagreed with specifics, but he's here), and a former US Assistant Secretary of Defense for Nuclear, Chemical, and Biological Defense.
PLAYA DEL CARMEN, MEXICO Contact: Andrew Contact Info: andrew[dot]d[dot]cutler[at]gmail[dot]com Time: Monday, September 25th, 7:00 PM Location: Aloft Hotel Rooftop Lounge, Calle 34, Avenida 10, Playa Del Carmen, Mexico Coordinates: https://plus.codes/76GJJWPJ+3J Notes: Please RSVP via email
VANCOUVER, BRITISH COLUMBIA, CANADA Contact: Michael Contact Info: maswiebe[at]gmail[dot]com Time: Thursday, September 28th, 7:00 PM Location: East Van Brewing Company, upstairs Coordinates: https://plus.codes/84XR7WGH+PH Mexico MEXICO CITY, MEXICO Contact: Francisco Contact Info: fagarrido[at]gmail[dot]com Time: Saturday, October 14th, 4:00 PM Location: Cafebrería El Péndulo, Av Nuevo León 115, Hipódromo, Cuauhtémoc, 06100 Ciudad de México, CDMX Coordinates: https://plus.codes/76F2CR6G+6R Notes: Please RSVP on LW, so that I can let you know of any potential change of plans.
MEXICO CITY, MEXICO Contact: Francisco Contact Info: fagarrido[at]gmail[dot]com Time: Saturday, October 14th, 4:00 PM Location: Cafebrería El Péndulo, Av Nuevo León 115, Hipódromo, Cuauhtémoc, 06100 Ciudad de México, CDMX Coordinates: https://plus.codes/76F2CR6G+6R Notes: Please RSVP on LW, so that I can let you know of any potential change of plans.
Even if correct, it is much less interesting and useful than it appears. Epistemic status: I have a decade-old PhD in economics (not in the field of economic growth) and a handful of peer-reviewed papers in moderately-ranked journals. I'm not claiming to make any original technical points, or to give a comprehensive evaluation of the economic growth literature. My criticisms are largely straight from the authors' own mouths. 1. What is this book about? Why is it not very good? Acemoglu and Robinson (AR) argue that countries are rich or poor because of their political institutions, not culture, geography or policy ignorance. I'll do this as much as possible in AR’s own words. Why Nations Fail was written during the Arab Spring, so the preface begins with Egypt. Some stress that Egypt’s poverty is determined primarily by its geography, by the fact that the country is mostly a desert and lacks adequate rainfall, and that its soils and climate do not allow productive agriculture1. Others instead point to cultural attributes ... Egyptians, they argue, lack the same sort of work ethic and cultural traits that have allowed others to prosper, and instead have accepted Islamic beliefs that are inconsistent with economic success. A third approach, the one dominant among economists and policy pundits, is based on the notion that the rulers of Egypt simply don’t know what is needed to make their country prosperous, and have followed incorrect policies and strategies in the past. Unsurprisingly, those other economists and policy pundits turn out to be wrong and the authors turn out to be right. In this book we’ll argue that the Egyptians in Tahrir Square, not most academics and commentators, have the right idea. In fact, Egypt is poor precisely because it has been ruled by a narrow elite that have organized society for their own benefit at the expense of the vast mass of people. And the Egyptian lesson turns out to be general. Whether it is North Korea, Sierra Leone, or Zimbabwe, we’ll show that poor countries are poor for the same reason that Egypt is poor. Countries such as Great Britain and the United States became rich because their citizens overthrew the elites who controlled power and created a society where political rights were much more broadly distributed, where the government was accountable and responsive to citizens, and where the great mass of people could take advantage of economic opportunities. What are “institutions” anyway? (The economic and political kind, not the prison and mental hospital kind.) Basically, AR mean politics. The word "institutions" occurs over 1000 times in Why Nations Fail2. I'll just focus on how AR use it without worrying about the dictionary, different schools of economics, or other social sciences. They begin with what institutions do rather than what they are. Nogales, Arizona, is in the United States. Its inhabitants have access to the economic institutions of the United States, which enable them to choose their occupations freely, acquire schooling and skills, and encourage their employers to invest in the best technology, which leads to higher wages for them. They also have access to political institutions that allow them to take part in the democratic process, to elect their representatives, and replace them if they misbehave. The word is used dozens more times before ARattempt a more general definition. Each society functions with a set of economic and political rules created and enforced by the state and the citizens collectively. Economic institutions shape economic incentives: the incentives to become educated, to save and invest, to innovate and adopt new technologies, and so on. It is the political process that determines what economic institutions people live under, and it is the political institutions that determine how this process works. So while economic and political institutions can be separated, it is the political institutions that matter in the long run. The good kind of institutions that lead to economic growth are "inclusive", as opposed to "extractive". To be inclusive, economic institutions must feature secure private property, an unbiased system of law, and a provision of public services that provides a level playing field in which people can exchange and contract; it also must permit the entry of new businesses and allow people to choose their careers. ... such rights must exist for the majority of people in society. Political pluralism is necessary, but not sufficient without a strong centralised state. ... political institutions that distribute power broadly in society and subject it to constraints are pluralistic. ... the key to understanding why South Korea and the United States have inclusive economic institutions is not just their pluralistic political institutions but also their sufficiently centralized and powerful states. A telling contrast is with the East African nation of Somalia. I am still a bit hazy as to the relative importance of de jure written rules versus the de facto struggle for power. AR are somewhat circular: Politics is the process by which a society chooses the rules that will govern it. Politics surrounds institutions ... When there is conflict over institutions, what happens depends on which people or group wins out in the game of politics ... The political institutions of a society are a key determinant of the outcome of this game. They are the rules that govern incentives in politics. But overall, you could just say ‘politics’ and not be too far off. AR do this themselves occasionally. South Korea ended up with very different economic institutions than the North because different people with different interests and objectives made the decisions about how to structure society. In other words, South Korea had different politics. AR's academic reputation is based on statistical analysis, but Why Nations Fail tries to do narrative history, IMHO not very well. When Jeffrey Sachs reviewed the book, he complained: They never define their key variables with precision, present any quantitative data or classifications based on those definitions, or offer even a single table, figure, or regression line to demonstrate the relationships that they contend underpin all economic history. Instead, they present a stream of assertions and anecdotes about the inclusive or extractive nature of this or that institution. AR replied baldly: Sachs ... argues that we provide no evidence. Right, we do not in the book. But that’s because a book for a general audience is not the right forum for presenting academic research, and we spent many years of our lives precisely on writing academic papers providing exactly the sort of evidence. ... So yes, we don’t provide the econometric evidence in the book, which isn’t of course the right place to do it, but econometric evidence is abundantly loud in the way it speaks on these topics. So, don't expect Why Nations Fail to be an accessible explanation of AR's academic work, which is what I was hoping for when I first read it. What do they spend over 500 pages on then? Well, after the preface, there's fifteen chapters of, as Sachs says, "assertions and anecdotes". Not just about "the inclusive or extractive nature of this or that institution", to be fair, but how institutions can change at "critical junctures" such as the Black Death or colonisation, and why it can be in elites’ interests to block economic innovation if it threatens their power, so that growth under extractive institutions is unlikely to be sustained. These chapters are not particularly good – I found them poorly organised and repetitive – but not particularly bad, if you are willing to accept the underlying premise that institutions are the main determinant of economic growth. Cumulatively they have an effect similar to the Old Testament, if you are willing to accept the underlying premise that the fortunes of the nation of Israel are determined by the LORD. Only the second chapter, ‘Theories that Don't Work’, makes a sustained argument against alternative theories. Geography is disposed of by noting the stark differences at the US-Mexican, North-South Korean and East-West German borders, and the reversal of fortune by which the present day US and Canada only became richer than Mexico, Central and South America following European colonisation. Culture is hand-waved away with the assertion that institutions determine the any relevant cultural behaviours, not the other way around, referring to the same border examples, the rapid catch up of Catholic Europe despite Weber's Protestant Ethic, the malign influence of the European and Ottoman empires on Africa, the range of outcomes within the former British Empire, and the more European population of Argentina and Uruguay versus the US and Canada, or of Columbia versus Ecuador and Peru. Not a bad list of anecdotes, but one could equally well point to the cross-border success of Ashkenazi Jews, overseas Chinese, or Baltic and Volga Germans. Ignorance is simply dismissed with the assertion that "if ignorance were the problem, well-meaning leaders would quickly learn what types of policies increased their citizens’ incomes and welfare, and would gravitate toward those policies." Various good and bad policy changes are explained as the result of political pressures rather than improved knowledge. The implication seems to be that good policies are so obvious they don’t require expert knowledge or advice, or that the experts never get it wrong. This appears most implausible in the debate over socialism and economic planning. Writing off the entire Communist experience as simply another elite trying to preserve its power feels inadequate, especially considering that some distinguished bourgeois economists thought central planning was a plausible road to riches until quite late in the day. Genetics or race is not mentioned, but would presumably attract the same counterexamples as geography and culture. Another theory AR do not discuss is crude exploitation: while colonial empires are excoriated, it is for setting up persistent extractive political institutions rather than for a direct theft of resources. The prosperity of white-owned South African farms next to poverty-stricken Bantustans is explained by the better quality of the institutions available to whites under apartheid, not relative population densities and land quality. For the rest of the book, I'll just list a few nitpicks to signal I read the whole thing and know a bit of history, but feel free to skip this – the real evidence for AR's thesis is in their academic papers, and I'll discuss those in the next section. I think AR overrate the importance of the Glorious Revolution, to the point of claiming it "created the rule of law" – after all, Parliament had already deposed and executed a king, then brought back the king’s son on their own terms after a decade of republican government. No less a luminary than Edmund Burke asserted "The Revolution was made to preserve our ancient indisputable laws and liberties, and that ancient constitution of government which is our only security for law and liberty." Also, strong signs of British economic uniqueness – the abnormal growth of London and reliance on coal as a fuel – predated 1688.
1: Since we posted Meetups Everywhere on Friday, we’ve added in proposed meetups for Eindhoven, Netherlands and Mérida, Mexico.
Zone based reforms are a hack around the public choice challenges of nation-state reforms. Bob Haywood, former director of the World Economic Processing Zones Association, makes the case that zones address Doug North's "natural state" of oligarchy preventing liberalization because export zones don't immediately threaten the rent-seeking structures. In his experience, usually zones were adovcated by the peripheral elites - not the core elites, but the son-in-law, cousin, younger brothers, etc. who had access to elites but were not currently benefiting from rent-seeking themselves. Without zone solutions, however irregular their success, most nations tend to be stuck in the "natural state" of oligarchic rent-seeking. Haywood makes the case that zones led to broader economic liberalization in Mexico, China, Mauritius, Ireland, and elsewhere. If the benefits of zone-based reforms includes broader economic liberalization then the returns are much greater.
TAMARINDO Contact: Timeless Contact Info: pvspam-acxorganiser[at]hacklab[dot]net Time: Sunday, April 7th, 1:00 PM Location: El Mercadito Food Court Coordinates: https://plus.codes/762P75X5+QMR Notes: Feel free to bring kids/dogs. I will wear a nerdy t-shirt and stay close to Asian Fusion Sushi section of the court. Mexico MÉRIDA, MEXICO Contact: Silvia Fernández Contact Info: silviafidelina[at]hotmail[dot]com Time: Saturday, April 20th, 6:00 PM Location: Centro de Estudios e Investigaciones Sociales y Culturales Efrain Calderon, calle 38 No. 453 por 35 y 37 Barrio Obrero: Jesús Carranza, Mérida, Mexico Coordinates: https://plus.codes/76GGX9JV+W6 Group Link: https://www.facebook.com/groups/lesswrongmerida Notes: Favor de reservar por mail
MÉRIDA, MEXICO Contact: Silvia Fernández Contact Info: silviafidelina[at]hotmail[dot]com Time: Saturday, April 20th, 6:00 PM Location: Centro de Estudios e Investigaciones Sociales y Culturales Efrain Calderon, calle 38 No. 453 por 35 y 37 Barrio Obrero: Jesús Carranza, Mérida, Mexico Coordinates: https://plus.codes/76GGX9JV+W6 Group Link: https://www.facebook.com/groups/lesswrongmerida Notes: Favor de reservar por mail
MEXICO CITY, MEXICO Contact: Francisco Contact Info: fagarrido[at]gmail[dot]com Time: Saturday, April 13th, 5:00 PM Location: Cafebreria El Pendulo Coordinates: https://plus.codes/76F2CR6G+6R Group Link: https://www.lesswrong.com/groups/uzTxYaFupgz9ZnCT5
This is what he looks like. According to Wikipedia, the context for this picture is: “Noam Chomsky speaks about humanity's prospects for survival” Since around 1957, Chomsky has dominated linguistics. And this matters because he is kind of a contrarian with weird ideas. Is language for communicating? No, it’s mainly for thinking: (What Kind of Creatures Are We? Ch. 1, pg. 15-16) It is, indeed, virtual dogma that the function of language is communication. ... there is by now quite significant evidence that it is simply false. Doubtless language is sometimes used for communication, as is style of dress, facial expression and stance, and much else. But fundamental properties of language design indicate that a rich tradition is correct in regarding language as essentially an instrument of thought, even if we do not go as far as Humboldt in identifying the two. Should linguists care about the interaction between culture and language? No, that’s essentially stamp-collecting: (Language and Responsibility, Ch. 2, pg. 56-57) Again, a discipline is defined in terms of its object and its results. Sociology is the study of society. As to its results, it seems that there are few things one can say about that, at least at a fairly general level. One finds observations, intuitions, impressions, some valid generalizations perhaps. All very valuable, no doubt, but not at the level of explanatory principles. … Sociolinguistics is, I suppose, a discipline that seeks to apply principles of sociology to the study of language; but I suspect that it can draw little from sociology, and I wonder whether it is likely to contribute much to it. … You can also collect butterflies and make many observations. If you like butterflies, that’s fine; but such work must not be confounded with research, which is concerned to discover explanatory principles of some depth and fails if it has not done so. Did the human capacity for language evolve gradually? No, it suddenly appeared around 50,000 years ago after a freak gene mutation: (Language and Mind, third edition, pg, 183-184) An elementary fact about the language faculty is that it is a system of discrete infinity, rare in the organic world. Any such system is based on a primitive operation that takes objects already constructed, and constructs from them a new object: in the simplest case, the set containing them. Call that operation Merge. Either Merge or some equivalent is a minimal requirement. With Merge available, we instantly have an unbounded system of hierarchically structured expressions. The simplest account of the “Great Leap Forward” in the evolution of humans would be that the brain was rewired, perhaps by some slight mutation, to provide the operation Merge … There are speculations about the evolution of language that postulate a far more complex process … A more parsimonious speculation is that they did not, and that the Great Leap was effectively instantaneous, in a single individual, who was instantly endowed with intellectual capacities far superior to those of others, transmitted to offspring and coming to predominate. At best a reasonable guess, as are all speculations about such matters, but about the simplest one imaginable, and not inconsistent with anything known or plausibly surmised. It is hard to see what account of human evolution would not assume at least this much, in one or another form. I think all of these positions are kind of insane for reasons that we will discuss later. (Side note: Chomsky’s proposal is essentially the hard takeoff theory of human intelligence.) Most consequential of all, perhaps, are the ways Chomsky has influenced (i) what linguists mainly study, and (ii) how they go about studying it. Naively, since language involves many different components—including sound production and comprehension, intonation, gestures, and context, among many others—linguists might want to study all of these. While they do study all of these, Chomsky and his followers view grammar as by far the most important component of humans’ ability to understand and produce language, and accordingly make it their central focus. Roughly speaking, grammar refers to the set of language-specific rules that determine whether a sentence is well-formed. It goes beyond specifying word order (or ‘surface structure’, in Chomskyan terminology) since one needs to know more than just where words are placed in order to modify or extend a given sentence. Consider a pair of sentences Chomsky uses to illustrate this point in Aspects of the Theory of Syntax (pg. 22), his most cited work: (1a) I expected John to be examined by a specialist. (2a) I persuaded John to be examined by a specialist. The words “expected” and “persuaded” appear in the same location in each sentence, but imply different ‘latent’ grammatical structures, or ‘deep structures’. One way to show this is to observe that a particular way of rearranging the words produces a sentence with the same meaning in the first case (1a = 1b), and a different meaning in the second (2a != 2b): (1b) I expected a specialist to examine John. (2b) I persuaded a specialist to examine John. In particular, the target of persuasion is “John” in the case of (2a), and “the specialist” in the case of (2b). A full Chomskyan treatment of sentences like this would involve hierarchical tree diagrams, which permit a precise description of deep structure. You may have encountered the famous sentence: “Colorless green ideas sleep furiously.” It first appeared in Chomsky’s 1957 book Syntactic Structures, and the point is that even nonsense sentences can be grammatically well-formed, and that speakers can quickly assess the grammatical correctness of even nonsense sentences that they’ve never seen before. To Chomsky, this is one of the most important facts to be explained about language. A naive response to Chomsky’s preoccupation with grammar is: doesn’t real language involve a lot of non-grammatical stuff, like stuttering and slips of the tongue and midstream changes of mind? Of course it does, and Chomsky acknowledges this. To address this point, Chomsky has to move the goalposts in two important ways. First, he famously distinguishes competence from performance, and identifies the former as the subject of any serious theory of language: (Aspects of the Theory of Syntax, Ch. 1, pg. 4) The problem for the linguist, as well as for the child learning the language, is to determine from the data of performance the underlying system of rules that has been mastered by the speaker-hearer and that he puts to use in actual performance. Hence, in the technical sense, linguistic theory is mentalistic, since it is concerned with discovering a mental reality underlying actual behavior. Observed use of language or hypothesized dispositions to respond, habits, and so on, may provide evidence as to the nature of this mental reality, but surely cannot constitute the actual subject matter of linguistics, if this is to be a serious discipline. Moreover, he claims that grammar captures most of what we should mean when we talk about speakers’ linguistic competence: (Aspects of the Theory of Syntax, Ch. 1, pg. 24) A grammar can be regarded as a theory of a language; it is descriptively adequate to the extent that it correctly describes the intrinsic competence of the idealized native speaker. Another way Chomsky moves the goalposts is by distinguishing E-languages, like English and Spanish and Japanese, from I-languages, which only exist inside human minds. He claims that serious linguistics should be primarily interested in the latter. In a semi-technical book summarizing Chomsky’s theory of language, Cook and Newson write: (Chomsky’s Universal Grammar: An Introduction, pg. 13) E-language linguistics … aims to collect samples of language and then describe their properties. … I-language linguistics, however, is concerned with what a speaker knows about language and where this knowledge comes from; it treats language as an internal property of the human mind rather than something external … Not only should linguistics primarily be interested in studying I-languages, but to try and study E-languages at all may be a fool’s errand: (Chomsky’s Universal Grammar: An Introduction, pg. 13) Chomsky claims that the history of generative linguistics shows a shift from an E-language to an I-language approach; ‘the shift of focus from the dubious concept of E-language to the significant notion of I-language was a crucial step in early generative grammar’ (Chomsky, 1991b, pg. 10). … Indeed Chomsky is extremely dismissive of E-language approaches: ‘E-language, if it exists at all, is derivative, remote from mechanisms and of no particular empirical significance, perhaps none at all’ (Chomsky, 1991b, pg. 10).1 I Am Not A Linguist (IANAL), but this redefinition of the primary concern of linguistics seems crazy to me. Is studying a language like English as it is actually used really of no particular empirical significance? And this doesn’t seem to be a one-time hyperbole, but a representative claim. Cook and Newson continue: (Chomsky’s Universal Grammar: An Introduction, pg. 14) The opposition between these two approaches in linguistics has been long and acrimonious, neither side conceding the other’s reality. … The E-linguist despises the I-linguist for not looking at the ‘real’ facts; the I-linguist derides the E-linguist for looking at trivia. The I-language versus E-language distinction is as much a difference of research methods and of admissible evidence as it is of long-term goals. So much for what linguists ought to study. How should they study it? The previous quote gives us a clue. Especially in the era before Chomsky (BC), linguists were more interested in description. Linguists were, at least in one view, people who could be dropped anywhere in the world, and emerge with a tentative grammar of the local language six months later. (A notion like this is mentioned early in this video.) Linguists catalog the myriad of strange details about human languages, like the fact that some languages don’t appear to have words for relative directions, or “thank you”, or “yes” and “no”. After Chomsky's domination of the field (AD), there were a lot more theorists. While you could study language by going out into the field and collecting data, this was viewed as not the only, and maybe not even the most important, way to work. Diagrams of sentences proliferated. Chomsky, arguably the most influential linguist of the past hundred years, has never done fieldwork. In summary, to Chomsky and many of the linguists working in his tradition, the scientifically interesting component of language is grammar competence, and real linguistic data only indirectly reflects it. All of this matters because the dominance of Chomskyan linguistics has had downstream effects in adjacent fields like artificial intelligence (AI), evolutionary biology, and neuroscience. Chomsky has long been an opponent of the statistical learning tradition of language modeling, essentially claiming that it does not provide insight about what humans know about languages, and that engineering success probably can’t be achieved without explicitly incorporating important mathematical facts about the underlying structure of language. Chomsky’s ideas have motivated researchers to look for a “language gene” and “language areas” of the brain. Arguably, no one has yet found either—but more on that later. How Chomsky attained this stranglehold on linguistics is an interesting sociological question, but not our main concern in the present work2. The intent here is not to pooh-pooh Chomsky, either; brilliant and hard-working people are often wrong on important questions. Consider that his academic career began in the early 1950s—over 70 years ago!—when our understanding of language, anthropology, biology, neuroscience, and artificial intelligence, among many other things, was substantially more rudimentary. Where are we going with this? All of this is context for understanding the ideas of a certain bomb-throwing terrorist blight on the face of linguistics: Daniel Everett. How Language Began is a book he wrote about, well, what language is and how it began. Everett is the anti-Chomsky. II. THE MISSIONARY We all love classic boy-meets-girl stories. Here’s one: boy meets girl at a rock concert, they fall in love, the boy converts to Christianity for the girl, then the boy and girl move to the Amazon jungle to dedicate the rest of their lives to saving the souls of an isolated hunter-gatherer tribe. Daniel Everett is the boy in this story. The woman he married, Keren Graham, is the daughter of Christian missionaries and had formative experiences living in the Amazon jungle among the Sateré-Mawé people. At seventeen, Everett became a born-again Christian; at eighteen, he and Keren married; and over the next few years, they started a family and prepared to become full-fledged missionaries like Keren’s parents. First, Everett studied “Bible and Foreign Missions” at the Moody Bible Institute in Chicago. After finishing his degree in 1975, the natural next step was to train more specifically to follow in the footsteps of Keren’s parents. In 1976, he and his wife enrolled in the Summer Institute of Linguistics (SIL) to learn translation techniques and more viscerally prepare for life in the jungle: They were sent to Chiapas, Mexico, where Keren stayed in a hut in the jungle with the couple’s children—by this time, there were three—while Everett underwent grueling field training. He endured fifty-mile hikes and survived for several days deep in the jungle with only matches, water, a rope, a machete, and a flashlight. Everett apparently had a gift for language-learning. This led SIL to invite Everett and his wife to work with the Pirahã people (pronounced pee-da-HAN), whose unusual language had thwarted all previous attempts to learn it. In 1977, Everett’s family moved to Brazil, and in December they met the Pirahã for the first time. As an SIL-affiliated missionary, Everett’s explicit goals were to (i) translate the Bible into Pirahã, and (ii) convert as many Pirahã as possible to Christianity. But Everett’s first encounter with the Pirahã was cut short for political reasons: (Don’t Sleep There Are Snakes, Ch. 1, pg. 13-14) In December of 1977 the Brazilian government ordered all missionaries to leave Indian reservations. … Leaving the village under these forced circumstances made me wonder whether I’d ever be able to return. The Summer Institute of Linguistics was concerned too and wanted to find a way around the government’s prohibition against missionaries. So SIL asked me to apply to the graduate linguistics program at the State University of Campinas (UNICAMP), in the state of São Paulo, Brazil. It was hoped that UNICAMP would be able to secure government authorization for me to visit the Pirahãs for a prolonged period, in spite of the general ban against missionaries. … My work at UNICAMP paid off as SIL hoped it would. Everett became a linguist proper sort of by accident, mostly as an excuse to continue his missionary work. But he ended up developing a passion for it. In 1980, he completed Aspects of the Phonology of Pirahã, his master’s thesis. He continued on to get a PhD in linguistics, also from UNICAMP, and in 1983 finished The Pirahã Language and Theory of Syntax, his dissertation. He continued studying the Pirahã and working as an academic linguist after that. In all, Everett spent around ten years of his life living with the Pirahã, spread out over some thirty-odd years. As he notes in Don’t Sleep, There Are Snakes: (Prologue, pg. xvii-xviii) I went to the Pirahãs when I was twenty-six years old. Now I am old enough to receive senior discounts. I gave them my youth. I have contracted malaria many times. I remember several occasions on which the Pirahãs or others threatened my life. I have carried more heavy boxes, bags, and barrels on my back through the jungle than I care to remember. But my grandchildren all know the Pirahãs. My children are who they are in part because of the Pirahãs. And I can look at some of those old men (old like me) who once threatened to kill me and recognize some of the dearest friends I have ever had—men who would now risk their lives for me. Everett interviewing some Pirahã people. (source) Everett did eventually learn their language, and it’s worth taking a step back to appreciate just how hard that task was. No Pirahã spoke Portuguese, apart from some isolated phrases they used for bartering. They didn’t speak any other language at all—just Pirahã. How do you learn another group’s language when you have no languages in common? The technical term is monolingual fieldwork. But this is just a fancy label for some combination of pointing at things, listening, crude imitation, and obsessively transcribing whatever you hear. For years. It doesn’t help that the Pirahã language seems genuinely hard to learn in a few different senses. First, it is probably conventionally difficult for Westerners to learn since it is a tonal language (two tones: high and low) with a small number of phonemes (building block sounds) and a few unusual sounds3. Second, there is no written language. Third, the language has a variety of ‘channels of discourse’, or ways of talking specialized for one or another cultural context. One of these is ‘whistle speech’; Pirahãs can communicate purely in whistles. This feature appears to be extremely useful during hunting trips: (Don’t Sleep, There Are Snakes, Ch. 11, pg. 187-188) My first intense contact with whistle speech came one day when the Pirahãs had given me permission to go hunting with them. After we’d been walking for about an hour, they decided that they weren’t seeing any game because I, with my clunking canteens and machete and congenital clumsiness, was making too much noise. “You stay here and we will be back for you later.” Xaikáibaí said gently but firmly. … As I tried to make the best of my solitary confinement, I heard the men whistling to one another. They were saying, “I’ll go over there; you go that way,” and other such hunting talk. But clearly they were communicating. It was fascinating because it sounded so different from anything I had heard before. The whistle carried long and clear in the jungle. I could immediately see the importance and usefulness of this channel, which I guessed would also be much less likely to scare away game than the lower frequencies of the men’s normal voices. Fourth, important aspects of the language reflect core tenets of Pirahã culture in ways that one might not a priori expect. Everett writes extensively about the ‘immediacy of experience principle’ of Pirahã culture, which he summarizes as the idea that: (Don’t Sleep, There Are Snakes, Ch. 7, pg. 132) Declarative Pirahã utterances contain only assertions related directly to the moment of speech, either experienced by the speaker or witnessed by someone alive during the lifetime of the speaker. One way the language reflects this is that the speaker must specify how they know something by affixing an appropriate suffix to verbs: (Don’t Sleep, There Are Snakes, Ch. 12, pg. 196) Perhaps the most interesting suffixes, however (though these are not unique to Pirahã), are what linguists call evidentials, elements that represent the speaker’s evaluation of his or her knowledge of what he or she is saying. There are three of these in Pirahã: hearsay, observation, and deduction. To see what these do, let’s use an English example. If I ask you, “Did Joe go fishing?” you could answer, “Yes, at least I heard that he did,” or “Yes, I know because I saw him leave,” or “Yes, at least I suppose he did because his boat is gone.” The difference between English and Pirahã is that what English does with a sentence, Pirahã does with a verbal suffix. Everett also convincingly links this cultural principle to the lack of Pirahã number words and creation myths. On the latter topic, Everett recalls the following exchange: (Don’t Sleep, There Are Snakes, Ch. 7, pg. 134) I sat with Kóhoi once and he asked me, after hearing about my god, “What else does your god do?” And I answered, “Well, he made the stars, and he made the earth.” Then I asked, “What do the Pirahãs say?” He answered, “Well, the Pirahãs say that these things were not made.” And all of this is to say nothing of the manifold perils of the jungle: malaria, typhoid fever, dysentery, dangerous snakes, insects, morally gray river traders, and periodic downpours. If Indiana Jones braved these conditions for years, we would consider his stories rousing adventures. Everett did this while also learning one of the most unusual languages in the world. People on the bank of the Maici river. (source) By the way, he did eventually sort of achieve his goal of translating the Bible. Armed with a solid knowledge of Pirahã, he was able to translate the New Testament’s Gospel of Mark. Since the Pirahã have no written language, he provided them with a recorded version, but did not get the reaction he expected: (Don’t Sleep, There Are Snakes, Ch. 17, pg. 267-268) When we returned to the village, I recorded Mark’s gospel in my own voice for the Pirahãs to listen to. I then brought in a wind-up tape recorder to play the recording, and I taught the Pirahãs how to use it, which, surprisingly enough, some of the children did. Keren and I left the village and returned a few weeks later. The people were still listening to the gospel, with children cranking the recorder. I was initially quite excited about this, until it became clear that the only part of the book that they paid attention to was the beheading of John the Baptist. “Wow, they cut off his head. Play that again!” One reaction to hearing the gospel caught Everett even more off-guard: (Don’t Sleep, There Are Snakes, Ch. 17, pg. 269) "The women are afraid of Jesus. We do not want him." "Why not?" I asked, wondering what had triggered this declaration. "Because last night he came to our village and tried to have sex with our women. He chased them around the village, trying to stick his large penis into them." Kaaxaóoi proceeded to show me with his two hands held far apart how long Jesus's penis was—a good three feet. But the Pirahã had an even more serious objection to Jesus: (Don’t Sleep, There Are Snakes, Ch. 17, pg. 265-266) Part of the difficulty of my task began to become clear to me. I communicated more or less correctly to the Pirahãs about my Christian beliefs. The men listening to me understood that there was a man named Hisó, Jesus, and that he wanted others to do what he told them. "The Pirahã men then asked, "Hey Dan, what does Jesus look like? Is he dark like us or light like you?" I said, "Well, I have never actually seen him. He lived a long time ago. But I do have his words." "Well, Dan, how do you have his words if you have never heard him or seen him?" They then made it clear that if I had not actually seen this guy (and not in any metaphorical sense, but literally), they weren't interested in any stories I had to tell about him. Period. This is because, as I now knew, the Pirahãs believe only what they see. Sometimes they also believe in things that someone else has told them, so long as that person has personally witnessed what he or she is reporting. In the end, Everett never converted a single Pirahã. But he did even worse than converting zero people—he lost his own faith after coming to believe that the Pirahã had a good point. After keeping this to himself for many years, he revealed his loss of faith to his family, which led to a divorce and his children breaking contact with him for a number of years afterward. But Everett losing his faith in the God of Abraham was only the beginning. Most importantly for us, he also lost his faith in the God of Linguistics—Noam Chomsky. III. THE WAR In 2005, Everett’s paper “Cultural constraints on grammar and cognition in Pirahã: Another look at the design features of human language” was published in the journal Cultural Anthropology. An outsider might expect an article like this, which made a technical observation about the apparent lack of a property called ‘recursion’ in the Pirahã language, to receive an ‘oh, neat’ sort of response. Languages can be pretty different from one another, after all. Mandarin lacks plurals. Spanish sentences can omit an explicit subject. This is one of those kinds of things. But the article ignited a firestorm of controversy that follows Everett to this day. Praise for Everett and his work on recursion in Pirahã: He became a pure charlatan, although he used to be a good descriptive linguist. That is why, as far as I know, all the serious linguists who work on Brazilian languages ignore him. Noam Chomsky, MIT professor and linguist
He makes it as far south as Acapulco in Mexico before crashing into a donkey that had wandered into the road.
What to say about Infinite Jest? It remains Wallace’s masterpiece, widely considered the greatest novel of Generation X. It takes place in a near future where the US, Canada and Mexico have been merged into a single state. Each year is corporately branded, with most of the action taking place in “The Year of the Depend Adult Undergarment.” It’s set in three locales: a drug rehabilitation center, an elite tennis academy, and a Quebecois terrorist cell.3 The novel clocks in at over a thousand pages, two hundred of which are footnotes. It includes sentences of absurd length, with some descending into multi-page molecular descriptions of various drugs. The book pulls the kind of stunts that shouldn’t work, but in Infinite Jest they do, because the book is that good, the characters that deep, the subject matter that prescient. Infinite Jest is often considered the “first internet novel,” predicting in particular its addictive allure.
55: The “fastest growing new religion in the world” is the cult of Santa Muerte (St. Death) in Mexico, with perhaps 29 million followers since going public in 2001. I find it hard to determine its appeal - the entire content of the religion seems to be “if you give sacrifices to an idol of a female skeleton, she will grant your prayers”. It’s not just that this is boring - it’s that it’s absolutely typical replacement-level paganism, and I’d always thought that Christianity beat paganism because it was inherently more attractive. Yet the Mexican youth are turning away from the stodgy boring Catholic Church en masse to worship Santa Muerte. Why?
From “Genesis and pathogenesis of the 1918 pandemic H1N1 influenza A virus”, linked above. You may recognize the lead author - Michael Worobey has also been a leading voice on the zoonotic side of the COVID origins debate. The recent history of the flu, as far as I can tell, is: 1918: An H1N1 flu (“Spanish flu”) jumped from birds to humans in America and killed 50 million people worldwide. This replaced all older strains, so most seasonal flus during this era were H1N1. 1957: An H2N2 flu (“Asian flu”) crossed from birds to humans in China, and killed about 2 million people worldwide. It replaced the H1N1 strain, so most seasonal flus during this era were H2N2. 1968: An H3N2 flu (“Hong Kong flu”) crossed from pigs (?) to humans in Hong Kong, and killed another 2 million people worldwide. It replaced the H2N2 strain, so most seasonal flus during this era were H3N2. 1977: An H1N1 flu (“Russian flu”) leaked from a biology lab (?) in Russia (it might have been a strain from the 1940s, which the Russians were trying to make a vaccine for). It didn’t kill that many people, but it stuck around, and from then on, seasonal flus could be either H3N2 or H1N1. 2009: An H1N1 flu (“Mexican flu” until the PC police stepped in; afterwards “swine flu”) took some horrible circuitous route between birds and pigs and back again, crossed over into humans in Mexico, and killed 200,000 people. It outcompeted older strains of H1N1, but couldn’t crowd out H3N2, so seasonal flus are still either H3N2 or H1N1. …which brings us to the present, hopefully illuminating why “new flu strain crosses over from animals into humans” is such an “uh oh” moment. The Bird Flu Technically, all pandemic flus start as bird flus. Influenza A evolved in birds. Sometimes it spreads to other animals, including pigs, cattle, and humans. The most common way for a bird flu to spread to humans is to “reassort” (not exactly virus sex, but close enough, and the real version is less memorable) with a human flu virus (ie one that has already crossed over to humans). The resulting virus has all of the human flu virus’ human adaptations, but borrows enough new antigens from the bird virus to evade the immune system. Pigs can be infected by both human and bird viruses, so they are a common place for this reassortment to take place. If reassortment is sort of like viral sex, pigs are sort of like Tinder. When a bird flu and human flu reassort in pigs, the resulting disease is called a swine flu. At least the 2009 flu pandemic was a swine flu, and a minority opinion thinks the 1918 pandemic was too. There aren’t major epidemiological differences between direct-from-bird flus and swine flus. H5N1 was first noticed in birds - specifically, a flock of chickens in Scotland in 1959 - after which it disappeared for forty years. In 1996, it showed up in geese in China, then gradually increased its market share among birds worldwide. In 2022, it was found in minks; apparently it had learned to infect mammals. By early 2024, it was seen in cows. Now it’s in cow herds in 16 states, and one of them (California) has declared a state of emergency. And in October, H5N1 was found in pigs for the first time. It’s not uncommon for humans to catch an animal disease. This doesn’t mean the disease has “crossed over” to humans. If the virus isn’t suited to human-to-human transmission, it simply dies off (either before or after killing its human host). Thus, chicken farmers have been reporting scattered H5N1 cases since 1997; now that the virus has spread to cattle, cow farmers have started reporting the same. A Metaculus comment on this topic introduced me to the phrase “biocomputational surface”. Every viral replication that takes place in a human gives the virus one more chance to develop the set of mutations that makes it human-transmissible and start the next pandemic. Or, more likely, every viral replication that takes place in a human who has both the H5N1 bird flu and a normal human flu - or in a pig which has both viruses - gives the virus one extra chance to reassort in a way that produces a bird-antigen-fortified human-adapted flu virus. This doesn’t mean H5N1 will definitely become human-transmissible soon. Many viruses hang out on the borders of transmissibility for decades. Some, for unclear reasons, never cross over at all. But all of this is compatible with the virus becoming transmissible soon. So: What Is The Chance Of A Pandemic? The prediction markets on this topic ask a question about “10,000 cases in the United States”. Does this necessarily mean “pandemic”? Might it be possible to get to 10,000 cases just from the scattered chicken and cow farmers, with no human-to-human transmission? Despite many chicken and cow infections this year, there have only been 60 - 70 recorded human cases. Unless there is a phase change in screening methods, it seems hard for this number to increase to 10,000 off farmers alone. I think it’s fair to treat this question as operationalizing “what is the chance of a pandemic”? By this definition, Manifold estimates a 40% chance of an H5N1 pandemic in 2025. Metaculus estimates a 5% chance. You can see below whether that’s changed since I wrote this essay: 5% versus 40% is a big difference! Who do we trust? I trust Metaculus. Metaculus has beaten Manifold in both of the two head-to-head comparisons that I know of (Jeremiah Johnson’s and mine). Manifold’s number swings by a factor of two from week to week; Metaculus has been steady. But also, Metaculus hosts a CDC-sponsored respiratory disease forecasting tournament which has enriched them in epidemiological expertise. And if you look at the quality of comments on both sites, it’s pretty obvious where the people with more intellectual chops are hanging out. The Manifold comments are mostly single sentences, or occasionally just links to an article about new cases. The Metaculus comments look more like this one by dimaklenchin: Despite the panic propaganda, H5N1 is unlikely to be "just a single mutation away from switching host preference": 1) It normally takes a lot more than a single mutation to switch hosts. E.g., there are at least five different reasons why SIV (monkey equivalent of HIV) is not infectious to humans. Heck, a variant of SIV that bears HIV's receptor-recognizing surface protein (SHIV) is still not infectious to humans. HIV most certainly evolved from SIV but, almost as certainly, it took a very long time to get there. Not that all viruses are the same and things can't turn out differently with flu, but I don't subscribe to the idea that a mere change of receptor specificity (something that can take 1-2 mutations) will be sufficient. 2) We have data. Lots of human infections with other varieties of bird flu in the past - all those viruses ultimately went nowhere. Why would H5N1 be radically different? E.g., the "Canadian teen", despite what sounds like a prolonged exposure, failed to infect anyone around him. Since I am at 18% for the h-2-h H5N1 detection in 2025, I am arbitrarily going ~ an order of magnitude lower than that for something as unprecedented as 10K human infections. Maybe should be much lower but hedging for the time being and will allow another couple months of observations. And Sergio: I'm currently at 20% on the question of reported human-to-human transmission of highly pathogenic avian influenza H5N1 globally before 2026. However, this question is only about the US, and is more general about all subtypes of H5. But H5N1 very strongly appears to be the most important subtype to consider in this time period. And, given the current situation in the US with H5N1 human cases derived from exposure to poultry or cattle (with cattle(mammals) being more worrisome), h2h transmission seems quite more likely to arise in North America than elsewhere before 2026. Conditioning on h2h transmission in the US (and also trying to consider, with lower probability, a start in Canada), I want to estimate the chances that it becomes sustained and out of control (in which case, if it starts in Canada, I largely expect it to spread to the US). The (6) past events of probable h2h transmission of avian H5(N1), none of which were sustained, could serve as a base rate, although I'm a bit wary of giving much weight to this precedent, since the last event was quite a while ago (2007), and also because reporting and testing standards may have improved considerably since then (so perhaps they might not have been classified as h2h transmission events if they had occurred more recently). The current situation in the US, and events such as the Canadian teen who got sick with H5N1, do suggest a higher background level of risk than normal (which would be reduced if a vaccine for cattle is licensed soon), but I'm wary of overupdating. Conditioned on sustained h2h transmission, reaching over 10k cases in a few months seems likely, although perhaps very strong monitoring and surveillance could contain the situation in time (at the very least to moderate the growth rate). Trying to combine all these factors somewhat haphazardly, I'm currently at 3.5% for this question. That’s before 2026. What about longer-term? Manifold gives a ~50% chance before 2030; Metaculus uses a more complicated method but it says about 25% chance before 2030. H5N1 may cross to humans, but it could take a while. Superforecaster Juan Cambeiro at The Institute For Progress estimated a 4% chance of a “worse than COVID” H5N1 pandemic in “the next year”, but their estimate was made in 2023, without the benefit of the Metaculus estimates or most of our current knowledge. This feels high now - Metaculus says 5% total for H5N1 pandemic, and most pandemic flus are not worse than COVID. IFP also seem to be expecting a case fatality rate greater than 10%, which I find unlikely for the reasons mentioned above. I trust their estimate less than Metaculus’ current ones. I conclude that the most plausible estimate for the chance of an H5N1 pandemic in the next year is 5%. Interestingly, 5% is about the base rate for pandemic flus per year: five in the past century = one per twenty years = 5% chance per year. Isn’t it surprising that we’re still at the base rate when we can see a dangerous-looking flu virus spreading through the types of animals that have caused pandemic flus in the past? Part of the answer is that we’re not - in addition to the 5% chance of H5N1, we have to add the chance of some other pandemic flu. This probably isn’t 5% on its own; scientists monitor flu strains closely, and they haven’t found any others which are giving off as many red flags as H5N1. Still, something could always come out of left field. Maybe we should add a 2.5% chance of some other strain, for a total of 7.5% chance of a flu pandemic (ie beyond normal seasonal flu) next year. But still, isn’t it surprising that we’re so close to the base rate? One way to think about this: the base rate represents how concerned we should be if there was no epidemiological monitoring at all. In that case, we would estimate a probability distribution across different epidemiological landscapes, most of which contain some concerning-looking flu strains. Since we are doing the epidemiological monitoring, we can collapse that distribution into a single picture: one flu strain, H5N1, is in fact pretty concerning, and other strains mostly aren’t. This is enough to move our prior from 5% to 7.5%, but no more. The forecasters I talked to raised one other point of uncertainty: does the flu work more like a dice roll, or like a bus? Dice rolls are uncorrelated with their predecessors; even if it’s been a hundred rolls since you last rolled a 6, your chance this time is still 1/6. But buses come at fixed intervals; if the buses are hourly, and you haven’t seen a bus in the past 59 minutes, then your chance of seeing a bus in the next minute is very high. It’s been 16 years since the last flu pandemic; these pandemics come (on average) every 20 years. I don’t think anyone has a good sense of how to think about this. But it was 40 years between the Spanish and Hong Kong flus, so the twenty year number is at best a rule of thumb. The 5% number feels very low to me (and, apparently, to the average Manifold forecaster). Isn’t H5N1 spreading to cows and pigs and all sorts of other mammals? Isn’t it in the news all the time? I trust Metaculus a lot, but I agree that this is a surprising update, and I’m taking it on faith rather than feeling it in my bones. What Would The Fatality Rate Be For An H5N1 Pandemic? There are four basic stories you could tell about likely H5N1 mortality. First, maybe mortality would be 50%. The argument here is that official statistics report this mortality rate in the chicken farmers who have been infected with H5N1 so far. Several news sources and even some scientists have raised the specter of a pandemic version of H5N1 pandemic with this same death rate, which could kill a quarter to a third of the world population. THIS IS EXTREMELY FAKE. The official statistics only report fatality rate in the infections we know about. Bird flu is rare, there’s no mass testing, and we only learn that somebody had it if they’re in a hospital and the doctors are worried enough to test for rare conditions. Of Americans who got bird flu in the past year, 0 out of 61 have died. Probably this is mostly because America upped its detection game and is now finding milder cases; we also can’t rule out the virus mutating to become less virulent. Metaculus estimates the current true mortality rate as 1.25%. …but leaves a wide 90% confidence interval, from 0.5% to 7%. Second, maybe mortality would be somewhere around 1.25%. The argument here is that Metaculus uses this as its central estimate of US mortality. But Sentinel discusses some reasons to be skeptical of broad inferences from the US numbers: Scientists have been puzzled by the apparently low H5N1 case fatality rate in humans in the US. They offer a number of hypotheses: “The way in which the virus is being transmitted — along with the amount of virus exposure — is limiting the severity of disease.”
. . . undermine the Communist regime by offering an easier exit than flight to Miami or Mexico, and help rehabilitate America’s image, given Guantanamo’s current association with the War on Terror’s excesses. With effective governance and a welcoming environment, a Guantanamo Bay site would powerfully demonstrate that the American model of capitalism can thrive anywhere.
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.
Same state curriculum, same worksheets, same pace. The school philosophy was “no acceleration—just go deep.” We knew this was the philosophy going in. The pitch was that instead of accelerating through the state curriculum the teachers would take their time with the kids and allow them to fully explore and master the content of each grade. When we asked for examples of what that meant in practice we were told things like: “Instead of reading more advanced vocabulary, the students will learn to read out loud and use emotion and character impressions. They will learn how to vary the timing of their reading like where and when to pause to create emotion in the listener”. That sounded reasonable! It sounded like more learning, but just different learning than what the state had mandated. In practice that was not what happened. In practice “deep” just meant “un‑measured.” Smart kids + small classes ≠ accountability. The kids had time to do music, lego building, theatre and Friday ski trips because they were all really bright. They didn’t need 6+ hours a day to learn the limited math required by the state, and since the school did not feel the need to advance faster than the state, there was no pressure to push learning at all – on anything really. There was no overall school curriculum. Every teacher did their own thing. While one first grade class had weekly spelling bees, the teacher in the other classroom did not believe in learning spelling at all. But it didn’t matter. The metrics they measured the kids on in both classes advanced “enough” that no one was concerned. Most time wasn’t spent on math or language anyway. Beyond the brochure activities like skiing and theater and the four hours of foreign language per week they split between Spanish and Mandarin (which was really a great opportunity for the kids who already spoke Spanish and Mandarin to have their egos flattered. I did not see any learning in either language class. I don’t see how you can teach a language a couple of hours a week to a group of 18 kids with skill levels from zero to fluency and expect to have any impact), a lot of time was spent on DEI. DEI was pitched as helping kids handle the emotions that often come from being sensitive gifted children (they called it “Synapse”). In practice my oldest daughter got four years of learning about the basic ideas of Martin Luther King Junior and Rosa Parks, a rough understanding that some people are non-binary, and a great deal of anxiety every time I left the water running while I was brushing my teeth. The talent drain In Spring 2024 the “intermediate-school” head resigned, as did the 40+ year veteran science teacher we had been looking forward to our daughter having, the beloved tech teacher who had built a her own proprietary “learn to type” software, plus half the lower‑school faculty. Our oldest was going to be entering fourth grade; her incoming roster read like a rebuilding year for a professional sports team. It was possible we could get her into a middle school that would feed into a top tier high school, but those did not start until 5th grade. Our best option looked like “suck it up and accept whatever we had for at least a year”. One option was to do something radical. We considered taking a GAP year and traveling the world with an organization called “Boundless” but decided the timing wasn’t right. Earlier in the year we had started exploring moving to the charter city of Prospera. There is a Montessori school there that seemed like it might be alright. And we could surround the kids with an interesting group of people (and live on the beach!). But by the spring we had ruled it out. There did not seem to be many families as part of the community and we were not comfortable with the risk profile based on what was happening with the conflict between Honduras and their charter cities. Then I stumbled across Alpha: Two‑hour mornings, life‑skills afternoons, claims of 2x learning. Marketing copy is cheap; still, the promise was different enough to warrant due diligence. The initial plan was to fly some of the kids to Austin for an Alpha summer camp for a week in June – just to try it out. But once we started exploring more my wife asked me: “Could we actually move to Austin and try it for a year? Based on what is happening at the kids' school, this might be the year to try it.” So over eight weeks we flew to Austin five times – conversations with admissions and school heads, real estate searches, kids doing shadow‑days. Every parent we spoke to was very impressed with the school. Their kids really were advancing at 2x+ speed – and no one believed it was just a “selection effect”. And every guide I spoke to was extremely impressive themselves. They reminded me of the staff you run into when visiting Disney World. They all seemed “full faced” and fully-engaged. When I asked the head of admissions how they found such good staff he told me their compensation was fully transparent. “Associate Guides” were paid $60,000/year (vs the $40,000 average for Austin teachers), “Full Guides” made $100,000 and the five “Head Guides” in the school each made $150,000. They were able to both poach the best teachers from other schools, but also bring exceptional people into teaching that would not have considered it otherwise. It also let them have very high expectations for teachers once they were hired. We pulled the trigger in July. New house. Admissions letter signed. Moving truck (plus car-mover) scheduled for October. Worst case, it would be a one‑year sabbatical from stagnation. The hypothesis I carried south Elite private school attendance buys you smaller classes, brighter kids, and fancier field trips – not academic acceleration. If Alpha was real, we’d see that differential, measurable impact by Christmas – that was when we would need to decide if we would cut bait and re-apply to schools back home (and sign the kids up for more IQ-tests. The school would not accept old ones). That prior—show me velocity, not polish—is the lens through which the rest of this review should be read. Part Two: A History of Alpha Note: This is my best attempt at piecing together the history of the school based on conversations with co‑founder MacKenzie Price, high school head Chris Locke, Alpha staff, and Alpha parents; All dates are estimates and I am SURE I have gotten some details wrong. I will come back after the fact in the comments and make corrections as I hear from the people involved with corrections. 2013 – 2017 | Garage‑School to “Alpha” MacKenzie Price, then a mortgage broker in Austin, wasn’t impressed by the city’s gifted programs. She invited a small number of neighbourhood kids (including her two) into a makeshift microschool that ran two intense, teacher‑led academic “sprints” each morning, then “life‑skills” projects after lunch. Joe Liemandt — Founder of Trinity Technology, ESW Capital billionaire and family friend (MacKenzie’s husband worked for him) — kept his own children in conventional private school until he saw the qualitative improvement in the life skills of MacKenzie’s kids. He decided he wanted his kids to join MacKenzie’s but he wanted to take the project to the next level. Sometime around 2014-2017 he joined MacKenzie as a co-founder and started writing checks. Alpha recruited more students and guides and the operation jumped from location-to-location looking for a larger permanent home. 2017 – 2020 | K-8 Expansion and 2-hour focus Alpha grew to roughly 90 students from K‑8 and stabilized. Morning “core blocks” were still teacher‑driven (20‑minute bursts, 5‑minute breaks, rinse, repeat), but focused on students engaged in exercises with rapid feedback (not lectures). Afternoon workshops covered “life skills” like how to give and receive feedback or public speaking. I have not seen academic data from this time period, but when I spoke to Chris Locke, head of Alpha’s high school (which launched around 2020), he told me the kids coming into his 9th grade program were “fine,” academically – it was their life skills, confidence, and ability to engage with adults and their peers were exceptional. At this stage no AI, no dashboard, no 2x learning, no portal — just better ratios and focused pacing and the result was well balanced kids who were enjoying their education experience (even if they were unexceptional academically). 2020 – 2022 | Platform Era Begins Somewhere along the way Liemandt hired a small engineering team to stitch together edtech learning tools. Many schools use tools like iXL, Beast Academy and Amira. Those tools fit in well with the 2-hour structured approach Alpha was using. The “platform” Liemandt’s team built was meant as a tool to free up guide time so that students could be more self-directed. The dev team stitched together the preferred off‑the‑shelf apps behind a single login, and built out tracking and dashboards so guides (and students) could easily see how they were progressing. This also gave the curriculum team (there was a curriculum team now) data to understand where students were spending their time, what tools were working, and which weren’t as effective. The Alpha Portal was born. Not only did it increase efficiency, it provided data to iterate with. Chris Locke saw the curve change incrementally: each new cohort of ninth‑graders under the new tech-enabled learning platform came in a little stronger academically. The “life skills” were now being matched by the “academic skills”. 2022 | Expansion and Iteration By having access to Alpha kids post-graduation in the high school, Locke could send feedback back to the elementary school.The kids coming out of the new program were now killing it academically on Math, Language, and Science, but they were still weak on things like History and Geography. He fed that type of information back to the curriculum designers, who iterated and improved the program. Soon, in addition to the core platform that directed students to third-party tools, the tech team was building proprietary “Alpha” tools themselves. The flagship of the in-house tools was “AlphaReads”. AlphaReads requires students to read progressively more complicated passages, followed by answering reading comprehension questions. In addition to helping the kids improve reading skills, Alpha uses it to push types of content. Instead of classes in history, geography, economics and political science, some of the reading passages will cover that material (in addition to learning how to read and understand Shakespeare and Proust). The success of the 2-hour learning platform was giving the Alpha founders confidence. Liemandt in particular wanted to see if the program had legs beyond the elite group of students being educated in Austin. Alpha’s first external test in August 2022 in Brownsville, TX – a small community on the Mexico border with less than half the per capita income of Austin. SpaceX had recently launched Starbase in Brownsville in 2014 and the employees there were not happy with the existing school options. Someone at SpaceX approached Alpha and asked if they could launch a new campus for their employees. It is unclear if any money changed hands, but when Alpha launched their Brownsville campus (available to SpaceX employees and any other locals who are interested) tuition was only $10,000 (vs $40,000 at the main Austin campus); incoming students trailed national academic standards by over a year. But after nine months on the Alpha program the first cohort of students had caught up and surpassed the national average, and they kept accelerating, achieving an average learning velocity of ~2× the national average (see section four for what that means). Brownsville was Alpha’s attempt to show that their model wasn’t just rich‑kid selection effects. Spring 2024 | Field Pilots & Ukraine Trip Alpha tuition is high for the Austin area ($40,000 vs average private school ~$10,000-$15,000), but unlike most private schools tuition is all-inclusive. There are no extra fees for computers or field trips. There are no silent auctions or appeals for donations. This “no extra fees” allows the school to do some pretty ridiculous things. In the first half of 2024 Alpha sent a group of students to Poland to help launch a 2-hour learning pilot among Ukrainian refugees. Students did not pay to go on the trip. But students also did not have a “right” to go on the trip. They had to earn it. In addition to being on top of academic and non-academic expectations, students who wanted to participate had to learn basic Ukrainian so they could interact with the students in Poland they were meant to be helping. By not linking the opportunity to payment, the school could instead link it to behavior and achievement. This year a group of kids who learned to sail during the school year are going on a sailing trip through the Caribbean – for no additional fees to the parents. I also heard that around this time Alpha began testing the 2-hour learning platform at a facility for juvenile delinquents in Florida. I heard that from one individual who was not directly involved and I have not found any written documentation on it, so unclear if it worked, it was a one off, or if it even happened. But it fits into the pattern of Alpha at this stage: “We know this program works for a specific type of kid. Let’s find out how broadly it is applicable. Can it work for everyone? Is it the solution for learning and education for the world?” Fall 2024 | “Pick‑Your‑Afternoon” Specialist Schools MacKenzie told me that there was consensus among the current parents of Alpha that the 2-hour learning program was exceptional and was making a huge difference with their kids. Their kids were all learning at breathtaking speed in a very condensed period of time. But there was NOT consensus about what the kids should be doing in the other 22-hours of the day. Some parents wanted to utilize the platform’s capabilities to go even faster. Some wanted their kids to just chill out and enjoy the rest of their day – let kids be kids. Others wanted their kids to use the freed up time to do sports, or study music. It was clear to her that “learn more faster in a short period of time” was a universal desire. But beyond that it was unclear what the “right” solution for the rest of her program was. You can make the morning ultra-personalized, but if the goal of the afternoon is socialization that you are missing in the morning, you need to have some sort of alignment on how to spend that afternoon. That challenge led to Alpha’s 2024 expansion into specialty schools. Three micro‑campuses opened August 2024: GT School (Georgetown, TX) — Alpha’s “Gifted and Talented” School. Higher admissions bar; higher academic expectations; Afternoon programming focused on excelling in “academic competitions” like chess, go, debate, public speaking, robotics, programming and Quiz Bowl.
He made two copies, and gave each one to a priest. One of these priests brought a copy to a convent in Cuzco, where it sat in the library. The other priest kept his copy, and the original remained with Valdez. In 1835, a relative of Valdez’s wrote an article in a Cuzco periodical where he made reference to the fact that copies of Ollantay yet existed. This article came to the attention of a certain Johann Moritz Rugendas, a German artist who had recently been booted out of Mexico for trying to overthrow the government there and was presently touring South America.
Maximillian Seunik, $50K, for Screwworm Free Future. The screwworm is a nasty flesh-eating parasite that infests cattle and occasionally humans. It was laboriously eliminated from the US in the 1960s, from Mexico and Central America in the 90s, and finally fought to a standstill along the defensible chokepoint of the Panama isthmus in 2006. Since then, the US has regularly dropped sterile male screwworms over Panama; these distract the females and prevent them from advancing back north. During COVID, the parasite breached the barrier; it’s now back as far as Mexico, and likely to re-enter the US soon. SFF wants to encourage the development and testing of genetic biocontrol approaches, alongside other technology, to rapidly suppress screwworm populations. If these techniques work in screwworms, they could later be applied to mosquitoes, ticks, and other pests.
The OECD also produces consumer confidence surveys and the US is pretty middle of the pack compared to other advanced countries for the last three years - US, Australia, western europe, UK, japan, are all in the -1 to -1.5 z score range historically. China is the worst, around -2 z scores. Interestingly, Mexico is one of the few places with high consumer confidence right now.
This makes it tempting for US right-wingers to center their discussion of immigration around stories, narratives, and images from Europe. No-go zones, grooming gangs, rape statistics, sharia law, and asylum seekers are all parts of the European experience with limited relevance to an America where most immigrants are Mexican, Central American, or Indian.
My “favorite” example, spotted during the 2016 election, was a response to some #BuildTheWall types saying that illegal immigration through the southern border was near record highs. Some data journalist got good statistics and proved that the number of Mexicans illegally entering the country was actually quite low. When I looked into it further, I found that this was true - illegal immigration had shifted from Mexicans to Hondurans/Guatemalans/Salvadoreans etc entering through Mexico. If you counted those, illegal immigration through the southern border was near record highs.
On the other hand, it’s a problem if malicious streetlight fallacy can never be challenged, because perpetrators can always defend themselves by appealing to some hypothetical group of people who think Mexican immigration is worse than Central American immigration and are lying to convince people that it’s Mexican immigrants specifically.
Some kids never guessed. They thought it was dishonest. I had trouble understanding them, but when I think back on it, I had limits too. I would guess on multiple choice questions, but never the short answer section. “Who invented the cotton gin?” For any “who invented” question in US History, there’s a 10% chance it’s Thomas Edison. Still, I never put down his name. “Who negotiated the purchase of southern Arizona from Mexico?” The most common name in the United States has long been “John Smith”, applying to 1/10,000 individuals. An 0.01% chance of getting a question right is better than zero, right? If I’d guessed “John Smith” for every short answer question I didn’t know, I might have gotten ~1 extra point in my school career, with no downside.
Contact: Brent Contact Info: brent[.]komer[@]gmail[.]com Time: Thursday, May 21st, 7:00 PM Location: We’ll be meeting in the Waterloo Public Library Main Branch Auditorium (35 Albert St, Waterloo). This is next to the children’s books area, on the ground floor. Coordinates: https://plus.codes/86MXFF8G+94G Group Link: https://www.lesswrong.com/groups/NiM9cQJ5qXqhdmP5p Notes: If possible, please RSVP on LW and/or Discord so I know how much food to get. https://www.lesswrong.com/events/T3Avhaw6TXuz5gnyw/acx-meetups-everywhere-spring-2026 Mexico MEXICO CITY Contact: Eddie Contact Info: acxcdmx[@]gmail[.]com Time: Saturday, May 16th, 4:00 PM Location: Feel free to join us at Cafebrería El Péndulo, Condesa, for coffee, drinks, and rationalist-related conversation. Coordinates: https://plus.codes/76F2CR6G+6R Group Link: https://www.lesswrong.com/groups/uzTxYaFupgz9ZnCT5
Contact: AGG Contact Info: signoregalilei[@]gmail[.]com Time: Saturday, May 2nd, 2:00 PM Location: Lackawanna Station (1 Lackawanna Plaza, Montclair, NJ 07042) - inside the converted station building, across from “Burgers, Donuts, Potatoes”. I will have the appropriate sign. Coordinates: https://plus.codes/87G7RQ6P+FRP Notes: The lot is paid but some nearby street parking is free. Also, one of the Inkhaven-trained notable bloggers will be there! New Mexico ALBUQUERQUE Contact: Mary Contact Info: geofishtree[@]gmail[.]com Time: Saturday, April 11th, 2:00 PM Location: Boxing Bear Brewing Co. Bridges on Tramway Taproom, 12501 Candelaria Rd NE, Albuquerque, NM 87112. I will be at one of the picnic tables outside around the corner (not under the shelter) with an ACX meetup sign. Coordinates: https://plus.codes/857M4G82+HPJ Notes: Although this is a brewery, it’s child friendly and has plenty of non-alcoholic drink options, and outside food is allowed. I will have some food to share.