Kansas
Article
Kansas is a recurring place in the Astral Codex Ten archive, appearing 4 times across 4 issues between April 16, 2021 and March 28, 2024. The archive places it in contexts such as “the farm in the middle of Kansas that grows your food”; “people who are hired to grow corn in Kansas”; “I believe we Kansas-tematically develop a long term plan”. It most often appears alongside Bay Area, California, China.
Metadata
- Category: Places
- Mention count: 4
- Issue count: 4
- First seen: April 16, 2021
- Last seen: March 28, 2024
Appears In
- Your Book Review: Progress And Poverty
- Why Is The Central Valley So Bad?
- Hardball Questions For The Next Debate
- Practically-A-Book Review: Rootclaim $100,000 Lab Leak Debate
Related Pages
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- Bay Area (2 shared issues)
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- California (2 shared issues)
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- China (2 shared issues)
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- Civil War (2 shared issues)
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- New York (2 shared issues)
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- San Francisco (2 shared issues)
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- Thomas Jefferson (2 shared issues)
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- “The Rent Is Too Damn High!” (1 shared issues)
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- 16th amendment (1 shared issues)
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- 1886 (1 shared issues)
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- 1897 (1 shared issues)
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- 1995 to 2000 (1 shared issues)
External Links
Source Context
Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.
Based on data from the United Kingdom National Accounts: The Blue Book 2017. Published Oct 31, 2017. Revision Period: Beginning of each time series. Date of next release: July 2018. The "privileges" in "Land and privileges" are things like taxi medallions and patents, that were worth "almost zero" according to Nate. No matter how hard you try, "there is no occupation in which labor and capital can engage which does not require the use of land." Whenever anyone does labor, the owner of some piece of land – whether it's the farm in the middle of Kansas that grows your food, the lot upon which the server farm sending you these bytes sits, or the ground that right now sits beneath your feet – is sticking their finger in the pie. George reminds us that labor and capital will have to share whatever landowners take off the top of production in rent: As Produce = Rent + Wages + Interest, Therefore, Produce - Rent = Wages + Interest So... what happens when the productivity of land goes up? Let's go back to Lot A and Lot B, both 100-util fields. Let's say they belong to different landlords, and I'm a tenant on Lot B. I improve the soil of the field I'm working on so now it's worth 110 utils. What happens? My landlord raises the rent, of course! The only way wages (the return to labor) and interest (the return to capital) can go up as productivity increases, is if land values fail to rise at the same rate. The Law of Interest George wants to find the fundamental reason capital is able to produce wealth and justly claim a fair share of production. Remember that capital is wealth devoted to getting more wealth. So if capital is wealth that begets wealth, it makes sense that if I lend it out to you, I miss out on the potential for it to grow while it's out of my hands. George says I am justly entitled to ask for more back than I originally gave you. Let's say I loan you some corn seeds for a season. Had I not leant them to you, in a season's time I could have grown my own crop of corn and been left with more seed than I started with. So in a perfectly square deal, you need to give me back what I started with and what I could have expected to gain from natural increase (less the value of the labor required to get things started). Likewise with any other article of capital – say bricks or lumber. In the time I've spent without it while it was in your possession, I could have found someone else who had a better use for it than I did and exchanged it for something of theirs that I had a better use for, leaving me with capital of greater value. George says the act of progressively exchanging things in a way that increases subjective value for all involved is analogous to the natural forces of nature that make living capital (like corn and cows) grow over time. Remember, "subjective value" is real value. In a game of Settlers of Catan, if I have two bricks and you have two lumber, neither of us can build anything. The simple act of trading one brick for one lumber means both of us are better off because each of us can now build a road. The amount of bricks and lumber in the world didn't increase, but the amount of roads (or potential roads) did, and that represents a real increase in wealth. Interest thus springs from the "reproductive" powers of capital, whether that's biological reproduction, or the more abstract reproductive force of exchanging things so that you have a more valuable distribution of capital than you started with. As for how it relates to the other two returns to production – the more powerful the "power of increase" the capital has, the greater return interest can claim compared to wages. If you're ploughing a field and I lend you a tractor which makes you ten times as productive, I can justly claim more compensation for that than if I lend you a mule that only makes you twice as productive. However, rent still holds the whip hand, so the margin of cultivation determines how much return is left over to divvy up between interest and wages. This is because the net "reproductive" value of capital goes down given rent is a general tax on overall productivity. The amount I would have gained by using the thing productively over the period of time it was out on loan (the amount I can justly charge in interest) is reduced by how much I have to pay in rent. The Law of Wages Wages, like interest, are limited by the margin of production. Within that limit there's not much to understand about how wages work except that people seek to satisfy their desires "with the least exertion," which is a fancy way of saying people don't like to get ripped off. If two bosses offer the same exact job, but one offers higher pay, I'm taking that gig. If two bosses pay the same, but one is asking for twice as much work, I'll tell that boss where he can stick it. Wages depend upon the margin of production, or upon the produce which labor can obtain at the highest point of natural productiveness open to it without the payment of rent. So with all three laws established George sums it up like so: Where land is free and labor is unassisted by capital, the whole produce will go to labor as wages. Where land is free and labor is assisted by capital, wages will consist of the whole produce, less that part necessary to induce the storing up of labor as capital. Where land is subject to ownership and rent arises, wages will be fixed by what labor could secure from the highest natural opportunities open to it without the payment of rent. Where natural opportunities are all monopolized, wages may be forced by the competition among laborers to the minimum at which laborers will consent to reproduce. This is the reason George says that wages are so high in "new countries" where there's more land available than in countries where it's been locked up for centuries. Here's how it all fits together: Though neither wages nor interest anywhere increase as material progress goes on, yet the invariable accompaniment and mark of material progress is the increase of rent – the rise of land values. And: where the value of land is highest, civilization exhibits the greatest luxury side by side with the most piteous destitution IV. Effect of Material Progress upon the Distribution of Wealth As a society undergoes material progress, the rent goes up. Why? Let's break it down. Three things contribute to material progress: Increasing population
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?)
Inline links: Carolina Demography, Okies
HALEY: Hmmmm . . . um . . . [sweating] . . . the Israeli-Palestinian conflict is one of the Maine issues facing the world today. Errgh . . . um . . . it is a source of great suffering and Missouri for the people of the Middle East. [Long pause] Idaho-ped that there would have been peace in the region, but those hopes have been dashed. [Very long pause]. I believe we Kansas-tematically develop a long term plan to bring . . .
MODERATOR: Kansas-tematically.
Okay, this one is just awful. It takes the risky gambit above - giving extreme odds to something - then doubles down on it by multiplying across twenty different stages to get a stupendously low probability of 1/5*10^25. If we believe this, it’s more likely that we win the lottery three times in a row than that we learn lab leak was true after all. Eliezer Yudkowsky calls this the Multiple Stage Fallacy. Even aside from the failure mode in the sunrise example above (where people are too reluctant to give strong probabilities), it fails because people don’t think enough about the correlations between stages. For example, maybe there’s only 1/10 odds that the Wuhan scientists would choose the suboptimal RRAR furin cleavage site. And maybe there’s only 1/20 odds that they would add a proline in front to make it PRRAR. But are these really two separate forms of weirdness, such that we can multiply them together and get 1/200? Or are scientists who do one weird thing with a furin cleavage site more likely to do another? Mightn’t they be pursuing some general strategy of testing weird furin cleavage sites? (For example, Yuri proposed that, because the scientists wanted to understand how pandemic coronaviruses originate in nature, they might deliberately pick more natural-looking features over more designed-looking ones, which would neatly explain many features seemingly inconsistent with lab leak. Is this a conspiracy theory? Rootclaim is able to successfully route around this question. If the probability of a feature happening in nature is X, then the probability of it happening in this variant of lab leak scenario is X * [chance that the scientists wanted to imitate nature). This gives it a (deserved) complexity penalty without ruling out this (non-zero and potentially important) possibility.) In any case, Peter didn’t care as much about probabilistic analysis as Saar, he didn’t make his case hinge on this slide, and he might have been kind of using it to troll Rootclaim (which definitely worked). He might not have been making any of the mistakes above. But anyone who took this slide seriously would end up dramatically miscalibrated. The Math: Big Pictures Another of Saar’s concerns with the verdict was that Peter was an extraordinary debater, to the point where it could have overwhelmed the signal from the evidence. It’s hard to watch the videos and not come away impressed. Peter seems to have a photographic memory for every detail of every study he’s ever read. He has some kind of 3D model in his brain of Wuhan, the wet market, and how all of its ventilation ducts and drains interacted with each other. Whenever someone challenged one of his points, he had a ten-slide PowerPoint presentation already made up to address that particular challenge, and would go over it with complete fluency, like he was reciting a memorized speech. I sometimes get accused of overdoing things, but I can’t imagine how many mutations it would take to make me even a fraction as competent as Peter was. Saar’s closing argument included the admission: Peter, I think everyone can agree, has much more knowledge on [COVID] origins than we do. He's invested much more time. He may be a much more talented researcher. He's much more into the details. He probably knows the best in the world on origins at this point. Once you’ve described your opponent that way in your closing argument, what’s left of your case? Saar thought a lot was left. Throughout the debate, he tried to make a point about how getting the inference right was more important than winning sub-sub-sub-debates about individual lines of evidence. Although Peter won most specific points of contention, Saar thought that if the judges could just keep their mind on the big picture, they would realize a lab leak was more likely. I’m potentially sympathetic to arguments like Saar’s. Imagine a debate about UFOs. Imaginary-Saar says “UFOs can’t be real, because it doesn’t make sense for aliens to come to Earth, circle around a few fields in Kansas, then leave without providing any other evidence of their existence.” Imaginary-Peter says “John Smith of Topeka saw a UFO at 4:52 PM on 6/12/2010, and everyone agrees he’s an honorable person who wouldn’t lie, so what’s your explanation of that?” Saar says “I don’t know, maybe he was drunk or something?” Peter says “Ha, I’ve hacked his cell phone records and geolocated him to coordinates XYZ, which is a mosque. My analysis finds that he’s there on 99.5% of Islamic holy days, which proves he’s a very religious Muslim. And religious Muslims don’t drink! Your argument is invalid!” On the one hand, imaginary-Peter is very impressive and sure did shoot down Saar’s point. On the other, imaginary-Saar never really claimed to have a great explanation for this particular UFO sighting, and his argument doesn’t depend on it. Instead of debating whether Smith could or couldn’t have been drunk, we need to zoom out and realize that the aliens explanation makes no sense. The problem was, Saar couldn’t effectively communicate what his big picture was. Neither deployed some kind of amazingly elegant prior. They both used the same kind of evidence. The only difference was that Peter’s evidence hung together, and Saar’s evidence fell apart on cross-examination. I think - not because Saar really explained it, but just reading between the lines - Saar thought the un-ignorable big picture evidence was the origin in a city with a coronavirus gain-of-function lab, and the twelve-nucleotide insertion in the furin cleavage site. To some degree, Peter just ate the loss on those questions. No matter how you slice it, it really is a weird coincidence that the epidemic started so close to Asia’s biggest coronavirus laboratory. Peter tried to deflect this - he pointed out there were other BSL-3 and BSL-4 laboratories in Beijing, Shanghai, Shenzhen, etc. But this was a rare question where he unambiguously came out looking worse - the other cities’ labs had much less coronavirus-specific research. Wuhan really was unique (aside from the other big coronavirus lab in North Carolina). Peter did better when he tried to control the damage: there are a couple hundred million people in the South Asian areas where people eat weird animals exposed to virus-infected bats, Wuhan has a population of about 12 million, so maybe 1.5% of all potential zoonotic pandemics should start in Wuhan. Peter tried to argue that Wuhan was a local trade center, so maybe we should up that to 5 - 10%. 5 - 10% coincidences aren’t that rare. Even 1.5% coincidences happen sometimes. Likewise, the furin cleavage site really does stand on a genetic map. I didn’t feel like either side did much math to quantify how weird it was. Naively, I might think of this as “30,000 bases in COVID, only one insertion, it’s in what’s obviously the most interesting place - sounds like 30,000-to-one odds against”. Against that, a virus with a boring insertion would never have become a pandemic, so maybe you need to multiply this by however much viral evolution is going on in weird caves in Laos, and then you would get the odds that at least one virus would have an insertion interesting enough to go global. Neither participant calculated this in a way that satisfied me (though see here for related discussion). Instead, Peter tried to undermine the furin argument by showing that, as surprising as the site was under a natural origin, it would be an even more surprising choice for human engineers. Saar argued it wasn’t - but because of his policy of giving adjusted-for-model-error odds, he only gave this a factor of 30 in his analysis. Since Peter gave it a higher factor of 50 in his analysis, it looked from the outside like Saar had already conceded this point, and the judges were mostly happy to go with Saar’s artificially-low estimate. The Math: Double Coincidences Saar brought up an interesting point halfway through the debate: you should rarely see high Bayes factors on both sides of an argument. That is, suppose you accept that there’s only a 1-in-10,000 chance that the pandemic starts at a wet market under lab leak. And suppose you accept there’s only a 1-in-10,000 chance that COVID’s furin cleavage site could evolve naturally. If lab leak is true, then you might find 1-in-10,000 evidence for lab leak. But it’s a freak coincidence that there was 1-in-10,000 evidence for zoonosis5. Likewise, if zoonosis is true, you might find 1-in-10,000 evidence for this true thing. But it’s a freak coincidence that there was 1-in-10,000 evidence for lab leak. Either way, you’re accepting that a 1-in-10,000 freak coincidence happened. Isn’t it more likely you’ve bungled your analysis? I was following along at home, and I definitely bungled this point; I had some high Bayes factors on both sides. I adjusted some of them downward based on Saar’s good point, but how far should we take it? Here I remember The Pyramid And The Garden: you can get very strong coincidences if you have many degrees of freedom, ie buy a lot of lottery tickets. So for example, suppose there are fifty things about a virus. You should expect at least one of those to have a one-in-fifty coincidence by pure chance. What about more than that? You might be able to get away with this by saying there are an infinite number of possible conspiracy theories, and some from that infinite set are brought into existence when a strong enough coincidence makes them plausible. For example, it’s really weird that John Adams and Thomas Jefferson both died on the 50th anniversary of the Declaration of Independence. If I wanted, I could form a conspiracy theory about a group of weird assassins obsessed with killing Founding Fathers on important dates, and then Jefferson and Adams’ deaths would be 1/10,000 evidence for that theory. But this is the Texas Sharpshooter Fallacy, which Saar warned against several times. I don’t know if “the virus started in Wuhan, which is where they’re doing this research” gets a Texas Sharpshooter penalty, or how high that penalty should be. But the furin cleavage site doesn’t - people were talking about lab leak before anyone noticed it. The Aftermath: Peter Peter seemed satisfied with the result, in an understated sort of way: It seemed like an interesting experiment in monetizing the debunking of a conspiracy theory. I think there's usually a big asymmetry where it's easy to get rich spreading bullshit (like, the top anti-vaxxers during the pandemic all made a million dollars a year on substack), but it's almost impossible to make money on debunking it. The Rootclaim challenge seemed like one rare case where the opposite was true. Beyond that, I don't know what it's good for. It does seem like there could be a positive social impact from more people understanding that the lab leak hypothesis is (almost certainly) false. The Aftermath: Saar Saar says the debate didn’t change his mind. In fact, by the end of the debate, Rootclaim released an updated analysis that placed an even higher probability on lab leak than when they started. In his blog post, he discussed the issues above, and said the judges had erred in not considering them. He respects the judges, he appreciates their efforts, he just thinks they got it wrong. Although he respected their decision, he wanted the judges to correct what he saw as mistakes in their published statements, which delayed the public verdict and which which Viewers Like You did not appreciate: I ran an early draft of this post by him. There was some miscommunication about the exact publication date, so he hasn’t had time to write up a full response, but he has some quick thoughts (and I’ll link the full response when he writes it). He says: We will provide a full response to this post soon, but the main problem with it is fairly simple: There is general agreement that the main evidence for zoonosis is HSM (Huanan Seafood Market) forming an early cluster of cases. The contention is whether it is amazing 10,000x evidence, or is it negligible. All other evidence points to a lab leak, and if HSM is shown to be weak, lab leak is a clear winner. We provided an analysis of why it is negligible that is as close to mathematical proof as such things can be. Read it here. Scott and I exchanged a few emails on this issue and Scott preferred to discuss more intuitive analyses of HSM, using rules of thumb that likely served him well in the past. While I believe I managed to mostly explain where these failed, and Scott understands HSM is far weaker evidence than he initially thought6, he still has a very strong intuitive feeling (based on years of dealing with probabilities) that this is some exceptional coincidence, and that prevents him from properly updating his posterior. At the end of the day, this cannot be settled without going through our semi-formal derivation, understanding it, and either identifying the problem with it or accepting it (and thereby accepting lab-leak to be more likely). Here is a quick summary of the mistakes made by those claiming HSM is strong evidence: The first mistake is conflating Bayes factors with conditional probabilities. 1/10000 is the supposed conditional probability p(HSM|Lab Leak), That should be divided by the conditional probability of HSM under Zoonosis. Markets were not identified as a high-risk location prior to this outbreak (This will be elaborated in the full response), and in SARS1 the spillovers were mostly at restaurants and other food handlers that deal more closely with wildlife. While it's cool to point to the raccoon dog photo, that was a result of a retrospective search (we don't know what other photos they took which in retrospect would be brought up as premonition). Unbiased data shows markets are not a likely spillover location for zoonosis. We originally estimated p(HSM|Zoonosis)<0.1. Following more research we did to answer Scott's questions, this is more likely <0.03.
Inline links: Multiple Stage Fallacy, see here, 5, The Pyramid And The Garden, Texas Sharpshooter Fallacy, blog post, 6