humans

Article

humans is a recurring concept in the Astral Codex Ten archive, appearing 3 times across 3 issues between April 04, 2022 and July 12, 2024. The archive places it in contexts such as “like chimps → humans”; “In biology, humans are more successful than numerous larger animals”; “humans do NOT get mad cow disease”. It most often appears alongside American, Britain, Europe.

Metadata

• Category: Concepts
• Mention count: 3
• Issue count: 3
• First seen: April 04, 2022
• Last seen: July 12, 2024

Appears In

• Yudkowsky Contra Christiano On AI Takeoff Speeds
• The Question Of Separatism
• Your Book Review: The Family That Couldn’t Sleep

Related Pages

• • American (2 shared issues)
• • Britain (2 shared issues)
• • Europe (2 shared issues)
• • Google (2 shared issues)
• • Norway (2 shared issues)
• • Scotland (2 shared issues)
• • United Kingdom (2 shared issues)
• • 1980 (1 shared issues)
• • 1980 referendum (1 shared issues)
• • 1980s (1 shared issues)
• • 1989 (1 shared issues)
• • 1990s (1 shared issues)

External Links

• • http://web.archive.org/web/20221104130431/https://stevekirsch.substack.com/p/1m-bet-rules
• • http://web.archive.org/web/20221129133112/https://blog.rootclaim.com/rootclaim-accepts-500000-challenge-on-covid-vaccine-safety-efficacy/
• • http://web.archive.org/web/20221224061743/https://www.skirsch.com/covid/SaarWilf.pdf
• • https://archive.ph/pY4gF#selection-663.103-683.190
• • https://chatgpt.com/g/g-qXbCBoMXg-gary-marcus-ai-critic-simulator
• • https://eukaryotewritesblog.com/2023/06/24/chronic-wasting-disease/
• • https://futuur.com/q/119054/will-spacex-launch-humans-to-mars-by-the-end-of-2024
• • https://humsci.stanford.edu/feature/study-finds-chatgpts-latest-bot-behaves-humans-only-better
• • https://news.manifold.markets/p/human-v-bots-forecasting-tournament
• • https://oxfendazoledevelopmentgroup.org/
• • https://srconstantin.github.io/2019/02/25/humans-who-are-not-concentrating.html
• • https://twitter.com/gamaleldinfe/status/1691856077971935644

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.

Yudkowsky Contra Christiano On AI Takeoff Speeds

April 04, 2022 · Original source

That is - if any of this “transformative AI revolution” stuff is right at all, then at some point GDP is going to go crazy (even if it’s just GDP as measured by AIs, after humans have been wiped out). Paul thinks it will go crazy slowly. Right now world GDP doubles every ~25 years. Paul thinks it will go through an intermediate phase (doubles within 4 years) before it gets to a truly crazy phase (doubles within 1 year).

Chess AI performance over time. Why does this matter? If there’s a slow takeoff (ie gradual exponential curve), it will become obvious that some kind of terrifying transformative AI revolution is happening, before the situation gets apocalyptic. There will be time to prepare, to test slightly-below-human AIs and see how they respond, to get governments and other stakeholders on board. We don’t have to get every single thing right ahead of time. On the other hand, because this is proceeding along the usual channels, it will be the usual variety of muddled and hard-to-control. With the exception of a few big actors like the US and Chinese government, and maybe the biggest corporations like Google, the outcome will be determined less by any one agent, and more by the usual multi-agent dynamics of political and economic competition. There will be lots of opportunities to affect things, but no real locus of control to do the affecting. If there’s a fast takeoff (ie sudden FOOM), there won’t be much warning. Conventional wisdom will still say that transformative AI is thirty years away. All the necessary pieces (ie AI alignment theory) will have to be ready ahead of time, prepared blindly without any experimental trial-and-error, to load into the AI as soon as it exists. On the plus side, a single actor (whoever has this first AI) will have complete control over the process. If this actor is smart (and presumably they’re a little smart, or they wouldn’t be the first team to invent transformative AI), they can do everything right without going through the usual government-lobbying channels. So the slower a takeoff you expect, the less you should be focusing on getting every technical detail right ahead of time, and the more you should be working on building the capacity to steer government and corporate policy to direct an incoming slew of new technologies. Yudkowsky Contra Christiano Eliezer counters that although progress may retroactively look gradual and continuous when you know what metric to graph it on, it doesn’t necessarily look that way in real life by the measures that real people care about. (one way to think of this: imagine that an AI’s effective IQ starts at 0.1 points, and triples every year, but that we can only measure this vaguely and indirectly. The year it goes from 5 to 15, you get a paper in a third-tier journal reporting that it seems to be improving on some benchmark. The year it goes from 66 to 200, you get a total transformation of everything in society. But later, once we identify the right metric, it was just the same rate of gradual progress the whole time. ) So Eliezer is much less impressed by the history of previous technologies than Paul is. He’s also skeptical of the “GDP will double in 4 years before it doubles in 1” claim, because of two contingent disagreements and two fundamental disagreements. The first contingent disagreement: government regulations make it hard to deploy imperfect things, and non-trivial to deploy things even after they’re perfect. Eliezer has non-jokingly said he thinks AI might destroy the world before the average person can buy a self-driving car. Why? Because the government has to approve self-driving cars (and can drag its feet on that), but the apocalypse can happen even without government approval. In Paul’s model, sometime long before superintelligence we should have AIs that can drive cars, and that increases GDP and contributes to a general sense that exciting things are going on. Eliezer says: fine, what if that’s true? Who cares if self-driving cars will be practical a few years before the world is destroyed? It’ll take longer than that to lobby the government to allow them on the road. The second contingent disagreement: superintelligent AIs can lie to us. Suppose you have an AI which wants to destroy humanity, whose IQ is doubling every six months. Right now it’s at IQ 200, and it suspects that it would take IQ 800 to build a human-destroying superweapon. Its best strategy is to lie low for a year. If it expects humans would turn it off if they knew how close it was to superweapons, it can pretend to be less intelligent than it really is. The period when AIs are holding back so we don’t discover their true power level looks like a period of lower-than-expected GDP growth - followed by a sudden FOOM once the AI gets its superweapon and doesn’t need to hold back. So even if Paul is conceptually right and fundamental progress proceeds along a nice smooth curve, it might not look to us like a nice smooth curve, because regulations and deceptive AIs could prevent mildly-transformative AI progress from showing up on graphs, but wouldn’t prevent the extreme kind of AI progress that leads to apocalypse. To an outside observer, it would just look like nothing much changed, nothing much changed, nothing much changed, and then suddenly, FOOM. But even aside from this, Eliezer doesn’t think Paul is conceptually right! He thinks that even on the fundamental level, AI progress is going to be discontinuous. It’s like a nuclear bomb. Either you don’t have a nuclear bomb yet, or you do have one and the world is forever transformed. There is a specific moment at which you go from “no nuke” to “nuke” without any kind of “slightly worse nuke” acting as a harbinger. He uses the example of chimps → humans. Evolution has spent hundreds of millions of years evolving brainier and brainier animals (not teleologically, of course, but in practice). For most of those hundreds of millions of years, that meant the animal could have slightly more instincts, or a better memory, or some other change that still stayed within the basic animal paradigm. At the chimp → human transition, we suddenly got tool use, language use, abstract thought, mathematics, swords, guns, nuclear bombs, spaceships, and a bunch of other stuff. The rhesus monkey → chimp transition and the chimp → human transition both involved the same ~quadrupling of neuron number, but the former was pretty boring and the latter unlocked enough new capabilities to easily conquer the world. The GPT-2 → GPT-3 transition involved centupling parameter count. Maybe we will keep centupling parameter count every few years, and most times it will be incremental improvement, and one time it will conquer the world. But even talking about centupling parameter points is giving Paul too much credit. Lots of past inventions didn’t come by quadrupling or centupling something, they came by discovering “the secret sauce”. The Wright brothers (he argues) didn’t make a plane with 4x the wingspan of the last plane that didn’t work, they invented the first plane that could fly at all. The Hiroshima bomb wasn’t some previous bomb but bigger, it was what happened after a lot of scientists spent a long time thinking about a fundamentally different paradigm of bomb-making and brought it to a point where it could work at all. The first transformative AI isn’t going to be GPT-3 with more parameters, it will be what happens after someone discovers how to make machines truly intelligent. (this is the same debate Eliezer had with Ajeya over the Biological Anchors post; have I mentioned that Ajeya and Paul are married?) Fine, Let’s Nitpick The Hell Out Of The Chimps Vs. Humans Example This is where the two of them end up, so let’s follow. Between chimps and humans, there were about seven million years of intermediate steps. These had some human capabilities, but not others. IE homo erectus probably had language, but not mathematics, and in terms of taking over the world it did make it to most of the Old World but was less dominant than moderns. But if we say evolutionary history started 500 million years ago (the Cambrian), and AI history started with the Dartmouth Conference in 1955, then the equivalent of 7 million years of evolutionary history is 1 year of AI history. In the very very unlikely and forced comparison where evolutionary history and AI history go at the same speed, there will be only about a year between chimp-level and human-level AIs. A chimp-level AI probably can’t double GDP, so this would count as a fast takeoff by Paul’s criterion. But even more than that, chimp → human feels like a discontinuity. It’s not just “animals kept getting smarter for hundreds of millions of years, and then ended up very smart indeed”. That happened for a while, and then all of sudden there was a near-instant phase transition into a totally different way of using intelligence with completely new abilities. If AI worked like this, we would have useful toys and interesting specialists for a few decades, until suddenly someone “got it right”, completed the package that was necessary for “true intelligence”, and then we would have a completely new category of thing. Paul admits this analogy is awkward for his position. He answers: Chimp evolution is not primarily selecting for making and using technology, for doing science, or for facilitating cultural accumulation. The task faced by a chimp is largely independent of the abilities that give humans such a huge fitness advantage. It’s not completely independent—the overlap is the only reason that evolution eventually produces humans—but it’s different enough that we should not be surprised if there are simple changes to chimps that would make them much better at designing technology or doing science or accumulating culture […] So I don’t think the example of evolution tells us much about whether the continuous change story applies to intelligence. This case is potentially missing the key element that drives the continuous change story—optimization for performance. Evolution changes continuously on the narrow metric it is optimizing, but can change extremely rapidly on other metrics. For human technology, features of the technology that aren’t being optimized change rapidly all the time. When humans build AI, they will be optimizing for usefulness, and so progress in usefulness is much more likely to be linear. That is, evolution wasn’t optimizing for tool use/language/intelligence, so we got an “overhang” where chimps could potentially have been very good at these, but evolution never bothered “closing the circuit” and turning those capabilities “on”. After a long time, evolution finally blundered into an area where marginal improvements in these capacities improved fitness, so evolution started improving them and it was easy. Imagine a company which, through some oversight, didn’t have a Sales department. They just sat around designing and manufacturing increasingly brilliant products, but not putting any effort into selling them. Then the CEO remembers they need a Sales department, starts one up, and the company goes from moving near zero units to moving millions of units overnight. It would look like the company had “suddenly” developed a “vast increase in capabilities”. But this is only possible when a CEO who is weirdly unconcerned about profit forgets to do obvious profit-increasing things for many years. This is Paul’s counterargument to the chimp analogy. Evolution isn’t directly concerned about various intellectual skills; it only wants them in the unusual cases where they’ll contribute to fitness on the margin. AI companies will be very concerned about various intellectual skills. If there’s a trivial change that can make their product 10x better, they’ll make it. So AI capabilities will grow in a “well-rounded” way, there won’t be any “overhangs”, and there won’t be any opportunities for a sudden overhang-solving phase transition with associated new-capability development like with chimps → humans. Eliezer answers: Chimps are nearly useless because they're not general, and doing anything on the scale of building a nuclear plant requires mastering so many different nonancestral domains that it's no wonder natural selection didn't happen to separately train any single creature across enough different domains that it had evolved to solve every kind of domain-specific problem involved in solving nuclear physics and chemistry and metallurgy and thermics in order to build the first nuclear plant in advance of any old nuclear plants existing. Humans are general enough that the same braintech selected just for chipping flint handaxes and making water-pouches and outwitting other humans, happened to be general enough that it could scale up to solving all the problems of building a nuclear plant - albeit with some added cognitive tech that didn't require new brainware, and so could happen incredibly fast relative to the generation times for evolutionarily optimized brainware. Now, since neither humans nor chimps were optimized to be "useful" (general), and humans just wandered into a sufficiently general part of the space that it cascaded up to wider generality, we should legit expect the curve of generality to look at least somewhat different if we're optimizing for that. Eg, right now people are trying to optimize for generality with AIs like Mu Zero and GPT-3. In both cases we have a weirdly shallow kind of generality. Neither is as smart or as deeply general as a chimp, but they are respectively better than chimps at a wide variety of Atari games, or a wide variety of problems that can be superposed onto generating typical human text. They are, in a sense, more general than a biological organism at a similar stage of cognitive evolution, with much less complex and architected brains, in virtue of having been trained, not just on wider datasets, but on bigger datasets using gradient-descent memorization of shallower patterns, so they can cover those wide domains while being stupider and lacking some deep aspects of architecture. It is not clear to me that we can go from observations like this, to conclude that there is a dominant mainline probability for how the future clearly ought to go and that this dominant mainline is, "Well, before you get human-level depth and generalization of general intelligence, you get something with 95% depth that covers 80% of the domains for 10% of the pragmatic impact". ...or whatever the concept is here, because this whole conversation is, on my own worldview, being conducted in a shallow way relative to the kind of analysis I did in Intelligence Explosion Microeconomics, where I was like, "here is the historical observation, here is what I think it tells us that puts a lower bound on this input-output curve". Here Eliezer sort of kind of grants Paul’s point that AIs will be optimized for generality in a way chimps aren’t, but points to his previous “Intelligence Explosion Microeconomics” essay to argue that we should expect a fast takeoff anyway. IEM has a lot of stuff in it, but one key point is that instead of using analogies to predict the course of future AI, we should open that black box and try to actually reason about how it will work, in which case we realize that recursive self-improvement common-sensically has to cause an intelligence explosion. I am sort of okay with this, but I feel like a commitment to avoiding analogies should involve not bringing up the chimp-human analogy further, which Eliezer continues to do, quite a lot. I do feel like Paul succeeded in convincing me that we shouldn’t place too much evidential weight on it. The Wimbledon Of Reference Class Tennis “Reference class tennis” is an old rationalist idiom for people throwing analogies back and forth. “AI will be slow, because it’s an economic transition like the Agricultural or Industrial Revolution, and those were slow!” “No, AI will be fast, because it’s an evolutionary step like chimps → humans, and that was fast!” “No, AI will be slow, because it’s an invention, like the computer, and computers were invented piecemeal and required decades of innovation to be useful.” “No, AI will be fast, because it’s an invention, like the nuclear bomb, and nuclear bombs went from impossible to city-killing in a single day.” “No, AI will be slow, because it will be surrounded by a shell-like metallic computer case, which makes it like a turtle, and turtles are slow.” “No, AI will be fast, because it’s dangerous and powerful, like a tiger, and tigers are fast!” And so on. Comparing things to other things is a time-tested way of speculating about them. But there are so many other things to compare to that you can get whatever result you want. This is the failure mode that the term “reference class tennis” was supposed to point to. Both participants in this debate are very smart and trying their hardest to avoid reference-class tennis, but neither entirely succeeds. Eliezer’s preferred classes are Bitcoin (“there wasn't a cryptocurrency developed a year before Bitcoin using 95% of the ideas which did 10% of the transaction volume”), nukes, humans/chimps, the Wright Brothers, AlphaGo (which really was a discontinuous improvement on previous Go engines), and AlphaFold (ditto for proteins). Paul’s preferred classes are the Agricultural and Industrial Revolutions, chess engines (which have gotten better along a gradual, well-behaved curve), all sorts of inventions like computers and ships (likewise), and world GDP. Eliezer already listed most of these in his Intelligence Explosion Microeconomics paper in 2013, and concluded that the space of possible analogies was contradictory enough that we needed to operate at a higher level. Maybe so, but when someone lobs a reference class tennis ball at you, it’s hard to resist the urge to hit it back. Recursive Self-Improvement This is where I think Eliezer most wants to take the discussion. The idea is: once AI is smarter than humans, it can do a superhuman job of developing new AI. In his Microeconomics paper, he writes about an argument he (semi-hypothetically) had with Ray Kurzweil about Moore’s Law. Kurzweil expected Moore’s Law to continue forever, even after the development of superintelligence. Eliezer objects: Suppose we were dealing with minds running a million times as fast as a human, at which rate they could do a year of internal thinking in thirty-one seconds, such that the total subjective time from the birth of Socrates to the death of Turing would pass in 20.9 hours. Do you still think the best estimate for how long it would take them to produce their next generation of computing hardware would be 1.5 orbits of the Earth around the Sun? That is: the fact that it took 1.5 years for transistor density to double isn’t a natural law. It’s pointing to a law that the amount of resources (most notably intelligence) that civilization focused on the transistor-densifying problem equalled the amount it takes to double it every 1.5 years. If some shock drastically changed available resources (by eg speeding up human minds a million times), this would change the resources involved, and the same laws would predict transistor speed doubling in some shorter amount of time (naively 0.000015 years, although realistically at that scale other inputs would dominate). So when Paul derives clean laws of economics showing that things move along slow growth curves, Eliezer asks: why do you think they would keep doing this when one of the discoveries they make along that curve might be “speeding up intelligence a million times”? (Eliezer actually thinks improvements in the quality of intelligence will dominate improvements in speed - AIs will mostly be smarter, not just faster - but speed is a useful example here and we’ll stick with it) Paul answers: Summary of my response: Before there is AI that is great at self-improvement there will be AI that is mediocre at self-improvement. Powerful AI can be used to develop better AI (amongst other things). This will lead to runaway growth. This on its own is not an argument for discontinuity: before we have AI that radically accelerates AI development, the slow takeoff argument suggests we will have AI that significantly accelerates AI development (and before that, slightly accelerates development). That is, an AI is just another, faster step in the hyperbolic growth we are currently experiencing, which corresponds to a further increase in rate but not a discontinuity (or even a discontinuity in rate). The most common argument for recursive self-improvement introducing a new discontinuity seems be: some systems “fizzle out” when they try to design a better AI, generating a few improvements before running out of steam, while others are able to autonomously generate more and more improvements. This is basically the same as the universality argument in a previous section. Eliezer: Oh, come on. That is straight-up not how simple continuous toy models of RSI work. Between a neutron multiplication factor of 0.999 and 1.001 there is a very huge gap in output behavior. Outside of toy models: Over the last 10,000 years we had humans going from mediocre at improving their mental systems to being (barely) able to throw together AI systems, but 10,000 years is the equivalent of an eyeblink in evolutionary time - outside the metaphor, this says, "A month before there is AI that is great at self-improvement, there will be AI that is mediocre at self-improvement." (Or possibly an hour before, if reality is again more extreme along the Eliezer-Hanson axis than Eliezer. But it makes little difference whether it's an hour or a month, given anything like current setups.) This is just pumping hard again on the intuition that says incremental design changes yield smooth output changes, which (the meta-level of the essay informs us wordlessly) is such a strong default that we are entitled to believe it if we can do a good job of weakening the evidence and arguments against it. And the argument is: Before there are systems great at self-improvement, there will be systems mediocre at self-improvement; implicitly: "before" implies "5 years before" not "5 days before"; implicitly: this will correspond to smooth changes in output between the two regimes even though that is not how continuous feedback loops work. I got a bit confused trying to understand the criticality metaphor here. There’s no equivalent of neutron decay, so any AI that can consistently improve its intelligence is “critical” in some sense. Imagine Elon Musk replaces his brain with a Neuralink computer which - aside from having read-write access - exactly matches his current brain in capabilities. Also he becomes immortal. He secludes himself from the world, studying AI and tinkering with his brain’s algorithms. Does he become a superintelligence? I think under the assumptions Paul and Eliezer are using, eventually maybe. After some amount of time he’ll come across a breakthrough he can use to increase his intelligence. Then, armed with that extra intelligence, he’ll be able to pursue more such breakthroughs. However intelligent the AI you’re scared of is, Musk will get there eventually. How long will it take? A good guess might be “years” - Musk starts out as an ordinary human, and ordinary humans are known to take years to make breakthroughs. Suppose it takes Musk one year to come up with a first breakthrough that raises his IQ 1 point. How long will his second breakthrough take? It might take longer, because he has picked the lowest-hanging fruit, and all the other possible breakthroughs are much harder. Or it might take shorter, because he’s slightly smarter than he was before, and maybe some extra intelligence goes a really long way in AI research. The concept of an intelligence explosion seems to assume the second effect dominates the first. This would match the observation that human researchers, who aren’t getting any smarter over time, continue making new discoveries. That suggests the range of possible discoveries at a given intelligence level is pretty vast. Some research finds that the usual pattern in science is constant rate of discovery from exponentially increasing number of researchers, suggesting strong low-hanging fruit effects, but these seem to be overwhelmed by other considerations in AI right now. I think Eliezer’s position on this subject is shaped by assumptions like: If you have an AI as intelligent as Elon Musk today, then tomorrow you can run it on more hardware with a bit of normal human algorithmic progress, and get one twice as intelligent. So even if it would take Elon years to make a breakthrough, long before those years are up you’ll have an AI that can make breakthroughs much faster.

Inline links: thirty years away, Biological Anchors, Intelligence Explosion Microeconomics, hyperbolic growth we are currently experiencing, Some research finds

Given that humans (in this scenario) were able to bring AI from SHRDLU to superintelligence in less than 100 years without gaining any IQ at all, presumably you can make lots and lots and lots of progress before hitting your IQ ceiling, by which point you have a new IQ ceiling.

The Question Of Separatism

May 19, 2023 · Original source

When people argue against separatism, they often tout the benefits of being large. A Canada that would be split in two would mean smaller markets, and a weaker political counterweight to the United States. (Not to be mean to Canadian readers, but this argument seems delusional to me — I don’t think Americans currently see Canada as a political counterweight of any significance.) It would certainly be less prestigious. Large size, Jacobs says, is associated with power, and we admire power. We love slogans like “unity makes strength.” But after the medium-sized country of Sweden-Norway became the two smaller countries of Sweden and Norway, they both did well. Small size is less powerful, but it has its own advantages, such as nimbleness and ability to fail non-catastrophically. Small size also allows more diversity in cultural and economic matters, and here Jacobs waxes philosophical, pointing out that favoring diversity over uniformity is a recent, post-Enlightenment idea that has not yet been fully embraced in politics. We can see analogs everywhere. Europe, split into numerous small countries from the Middle Ages onward, became far more advanced than China, which has been unified more often than not. The city-states of ancient Greece and Renaissance Italy are seen as golden ages of Western civilization, even if they weren’t part of larger political units and therefore constantly went to war with one another. In business, large companies are impressive and powerful, but people always complain that Google or Microsoft have become stagnant and that the best place to work is tiny startups of about 2 cofounders and 4 employees. In biology, humans are more successful than numerous larger animals, and in terms of raw numbers, small animals like rats or insects are the most successful of all. Jacobs’s point isn’t that smaller is always better. Her point is that the converse statement, “bigger is always better,” is false — despite how intuitive it feels for political entities. Just like we don’t view a small nation like Switzerland or Singapore as a failure of unity, we (and in particular, Canadians) shouldn’t see the secession of a place like Quebec, if it’s done peacefully and democratically, as a failure either. Still, some people in online reviews of the book complain that this argument is a bit thin, especially considering that it serves as the foundation for the later chapters (which are more directly about late 1970s Quebec politics). Sure, small is beautiful, but large states are great for stability, peace, markets, whatever. If the potential benefits of small national size are Jacobs’s strongest argument, then we can breathe a sigh of relief and go back to agreeing that separatism is bad. Pointing out the widespread bias in favor of unified political entities does seem valuable to me, but okay, fair enough. Does Jacobs have deeper reasons why separatism might be a good idea in general? Yes, and for this we go back to the second half of Cities and the Wealth of Nations. Why Nations and Empires Fail Our breathing rate is regulated through a feedback mechanism. Too much carbon dioxide in the blood, or too little oxygen, and the brain stem commands the diaphragm to accelerate breathing. Once the levels are back to normal, the brain stem receives this feedback and slows breathing down again. Now, Jacobs asks, imagine an impossible creature: ten people, all doing their own thing, but whose breathing is somehow regulated by a single brain stem. The feedback the brain stem receives is a consolidated average of everyone’s carbon dioxide and oxygen levels, and the breathing rate the stem decides on is applied to all ten people, regardless of whether they’re sleeping or playing tennis. This, to put it mildly, wouldn’t work. This creature is an analogy, representing a nation. The ten people are its individual cities, and the breathing rate is the cities’ economies. If it sounds like a stupid analogy, that’s because it is: “I have had to propose a preposterous situation,” writes Jacobs, “because systems as structurally flawed as this don’t exist in nature; they wouldn’t last.” Nor do they exist in machines we design; they wouldn’t work. But “nations, from this point of view, don’t work either, yet do exist.” The feedback mechanism that fails to work properly in a nation is currency. A currency always fluctuates according to the exports and imports of the area where it circulates. Let me use the Republic of Venice and its ducat as a toy example, because the coins look nice: Whenever Venice produces something (like salt) and sells it abroad, foreigners need ducats to buy the exports, so the demand for ducats increases. When Venice buys something from abroad, it needs to use foreign currencies, so the demand for ducats decreases. Add up everything that Venice exports and imports, and you get either a trade surplus (more exports than imports) or a trade deficit (more imports than exports), which determines the value of the ducat relative to other currencies. In both cases, a negative feedback loop restores balance over time, just like our brain stem does with carbon dioxide levels. A trade surplus, and therefore a strong ducat, means that when foreigners want Venetian salt, it’s expensive. So Venice’s exports decrease, while imports increase, since Venetians can use their valuable ducats to buy stuff cheaply from abroad. Conversely, a trade deficit makes exports a bargain for foreigners and imports expensive for Venetians. This feedback loop is great. It’s exactly what a city needs to trigger the crucial import replacement process. When exports decrease and a trade deficit begins (maybe because Constantinople found a cheaper source of salt somewhere else), the weak ducat means that Venice is less able to afford the resources and manufactured goods it used to import. The people of Venice don’t want to have less of those goods, though, so they figure out ways to produce some themselves — that is, they do import replacement. Later they will be able to export the output of the newly expanding industries too, strengthening the ducat and continuing the cycle. Currencies, Jacobs explains, function as automatic tariffs (to protect local industry from foreign imports) and automatic export subsidies (to encourage local industry to export). They are “automatic” because of the feedback mechanism. Just like an accelerated breathing rate, they take effect exactly when they are needed — and no longer. … Or so they should, except that import replacement, as we discussed, is a city process. Whereas most currencies are national or supranational. National currencies work well for city-states, like the Republic of Venice or today’s Singapore. But in large nations, which, remember, are not the fundamental unit of economic life, they mess everything up. Take a city like Detroit. When Detroit’s exports (primarily cars) decrease, Detroit gets no feedback about this, because its currency is the United States dollar, and the United States dollar’s value depends on much more than Detroit. It depends on other cities whose foreign exports might be increasing at the moment. And on rural regions that are selling resources like oil abroad. Also, trade between Detroit and other cities that use the United States dollar — i.e., American cities — is structurally unable to provide any feedback whatsoever. So Detroit doesn’t get the signal that it should buy less stuff from other cities and replace the missing imports with local production. Instead, it just declines. Jacobs hypothesizes that this issue of national currencies is at the root of every large country’s economic troubles. It is why nations and empires always centralize everything into one large city, whether that’s Paris, London, Tokyo, or Toronto, or ancient Rome: that city, being the largest, is simply the only one for which national-level currency feedback works fine. The rest of the nation or empire, then, declines. But of course, nations and empires don’t accept this. They care about the economic well-being of their peripheral regions, sometimes out of genuine concern for the people there, sometimes out of fear that they rebel or hold independence referendums. So nations and empires will embark on every possible solution to reverse the decline. All of their solutions will look like good ideas at first, and yet fail at helping the peripheral regions. Worse, these solutions will weaken the cities, thereby destroying the only real wealth of the country and bringing untold hardship for everyone. Eventually the nation or empire will disintegrate, as nations and empires always do, and always will. Jacobs calls these false solutions transactions of decline. She identifies three types, and, content warning, you might not like some of them depending on your political sensibilities. Sustained military production is a transaction of decline. Permanent military bases and garrison towns are a special kind of settlement: they import a lot and export nothing. Superficially, producing weapons and supplies for the military seems like a good deal for some cities — Jacobs gives the example of Seattle, which, before Microsoft and Amazon were a thing, depended mostly on making military aircraft. But because nobody in a military base ever tries to replace those weapons and supplies with their own production, the trade is sterile in terms of economic development. In a sense, the wealth is slowly “drained” from cities. Large empires are especially prone to this: eventually all of their wealth is destined to the military just to keep the empire together.

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Your Book Review: The Family That Couldn’t Sleep

July 12, 2024 · Original source

(This report was, as it happens, published in the exact same month as The Family That Couldn’t Sleep.) DTM came to know the family well. He befriended them by way of two members of their younger generation, Lisi – a woman terrified by the shadow of the disease, and Ignazio – the doctor she had married, who was more terrified by the shadow of the disease. Ignazio put together the pieces of the family puzzle, consolidating all the disparate diagnoses into a single disorder and filling out a lot of blank spots on family trees. When DTM came along, he was able to help Ignazio make the case that the family would benefit from the spotlight – that greater awareness of FFI could lead to a cure both for them and for a slew of other prion diseases. As it so happens, he is one of those nonfiction authors who serve as a character in their own story. DTM has some form of progressive muscular palsy. He is, or at least was in 2006, not entirely sure what it is. The relatively unimpressive state of genetics at the time had not identified his causative mutation, though it looked a lot like one of the rarer forms of Charcot-Marie-Tooth disease2. DTM is pragmatic about this, the way everyone chronically ill is either pragmatic or doomed. Whatever he has, it is a defect in protein structure; his peripheral nerves decay not because of a problem with the nerves themselves but an inability of their scaffolding to hold them together, as he puts it. The last chapter of the book dwells on this, on the web of connections popping up between a thousand disorders. DTM’s disease is something vaguely similar, if you squint, to an exceptionally slow-progressing motor neurone disease; if you jump another level out, you see amyloid plaque diseases like Huntington’s and Alzheimer’s, and if you jump yet another level out, you see something like prions. His interest in the Venetian family was driven by this. Some of its members thought this a beautiful act of sympathy; others thought him a grotesque parody of themselves, an onlooker, a gawker, peddling their tragedy to salve his relatively insignificant problems. They are, he thinks, both right. That’s the beginning, and that’s the end. What happens in the middle? --------------------------------------------------------- The Venetian family lends the book its title, but they’re really more of a framing device. The Family That Couldn’t Sleep is separated into four parts, of which the first and fourth – the shortest by far – deal with the family. Part 2 is kuru, the king of fucked up diseases you read about in clickbait Weird Medicine listicles. Let’s talk about kuru! Kuru, is, famously, the prion disease you get if you eat another person’s brain. Well, not quite. It’s a prion disease that became endemic amongst women in the Fore society, who ritually ate brains, one of which had an inherited or spontaneous prion disease. This is an important note – there’s a tendency (which the book’s later chapters engage in) to assume cannibalism just has a Prion Disease Generator attached. If you eat people who don’t have prion diseases, you won’t suddenly get one. Uh, don’t eat people. Anyway, part 2 is DTM’s historiography of Fore-Westerner first contact. It’s hilarious. Papua New Guinea is a frankly ridiculous place; one of the all-time best Lyttle Lytton winners (worst first sentence from a hypothetical or, in this case, real work) was “Papua New Guinea is so violent that more than 820 languages are spoken there”. The native residents were so hostile to outsiders that all the colonial empires had cut their losses – and when you think about the places they colonized, that says something. After the First World War, PNG was ripped from its nominal German ‘owners’, but no one else wanted the place. So, of course, they gave it to the Australians. It was thirty years and another war before we actually made contact. 1940s Australia was as ‘settled’ as it’d ever be; the cities were bustling and the interior was mapped. The kind of explorer who two centuries before would be heading to new continents had to console himself with Pacific islands. Console he did. The native peoples of the PNG coasts were hostile enough to the wannabe-colonialists that the Australians, flying planes overhead, were the first people to discover that the island’s inland was populated too. No one had broken through on land. In all this deep and angry rainforest, the Fore were the furthest out. They lived far into the island’s mountainous interior; DTM describes their territory as “nearly vertical”. Calling people primitives is a bit passe these days for understandable reasons, but no other term comes to mind. The Fore had no name for themselves; we call them by an exonym, “the people to the south”. They weren’t, to be clear, hunter-gatherers – they were slash-and-burn agriculturalists, but very well-fed ones. Despite the tendency in grain-focused cultures for poor agriculturalists to be stunted/malnourished, the Fore were a remarkably healthy people. Well, except for the famous bit. The first remarkable thing about the Fore was just how quickly they wanted to assimilate. Most PNG tribes weren’t particularly enthused by Western offers of injections/tractors/radios/Christianity. Yet as soon as the Australians arrived, the Fore made ceasefires in their wars with other tribes, volunteered to help large-scale Australian projects on the coast, started planting and trading coffee, and enthusiastically participated in censuses. It’s the only first-contact narrative I’ve seen where the colonizers were concerned about how badly the other guys wanted to be colonized. The next was the one that got their names in the history books. Australian officials started to notice a remarkable lack of women in Fore camps. Some tribes sequestered their women, particularly when Westerners were around, so at first they thought nothing of it. The high rate of unpartnered young men, though, was way out of PNG norms. DTM tells this part fantastically. The Fore chapters drip with the dread of dramatic irony. When the first breakthrough comes, you have to catch your breath: “Tiny” Carey noted something in the middle of August 1950 that deepened this mystery. He noticed that near the village of Henganofi there had been an unusual number of deaths. “It appears,” he wrote his superiors, “natives suffer from stomach trouble, get violent shivering, as with the ague, and die fairly rapidly.” [...] McArthur investigated a little more [...] One day in August 1953 he ran into more of the shivering people Tiny Carey had seen several years before: “Nearing one of the dwellings, I observed a small girl sitting down beside a fire. She was shivering violently and her head was jerking spasmodically from side to side.” It would be quite some time before anyone figured out what caused it – but the problem, as DTM notes, was that its cause wasn’t possible. Everyone priored that the weird undescribed disease in the Fore lands was some nocebo sorcery-sickness. Vincent Zigas, the first actual doctor sent to work with the Fore, tried to placebo-effect them and failed miserably: On the way, Apekono stopped at a hut and showed Zigas his first kuru victim. “On the ground in the far corner sat a woman of about thirty,” the doctor wrote. “She looked odd, not ill, rather emaciated, looking up with blank eyes with a mask-like expression. There was an occasional fine tremor of her head and trunk, as if she were shivering from cold, though the day was very warm.” It was almost exactly the tableau McArthur had witnessed in 1953. Zigas, though, was a doctor. He could do more than look—or so he thought: “I decided I might as well try my own variety of magic,” he remembered. He rubbed Sloan’s Liniment, a balm for sore muscles, on her and declared to her family and his guide: “The sorcerer has put a bad spirit inside the woman. I am going to burn this spirit so that it comes out of her and leaves her. You will not see the fire, but she will feel it. The bad spirit will leave her and she will not die.” The lotion penetrated the woman’s skin and she writhed in pain. “Get up! Walk!” Zigas commanded theatrically. “The woman struggled feebly as if to rise, then, exhausted, started to tremble more violently, making a sound of foolish laughter, akin to a titter.” That evening Apekono asked Zigas not to try to cure any more kuru victims; “Don’t use your magic medicine anymore. It will not win our strong sorcery.” This was a disaster. The Fore were so cooperative precisely because they hoped “Western magic” could conquer theirs. As it became clear it couldn’t, they turned hostile. The Australians had hoped to “modernize a Stone Age people”; now all their subjects were dropping dead before their eyes, from what they could only assume was a “hysterical reaction” to colonization itself. So, to solve this, they needed a batshit insane American. Carleton Gajdusek is one of the characters who dominates The Family That Couldn’t Sleep. He couldn’t not. You could put him in a car commercial and he’d dominate it. Gajdusek was a physician with a rare, intense combination of science and practice. He was a romanticist, a field worker, and a lover of everything strange. He’d been an army doctor, a government conspiracy-cover-upper, and a postdoc under Linus Pauling who described his intent as “to straighten out Pauling’s ideas about proteins”. He hated civilization, in a slightly-to-Ted’s-centre sense, and was passionate about “primitives and isolates”. He jumped at the chance to work in Papua New Guinea; he planned to conduct a multi-site study on child development in such cultures, and relished the opportunity to live in a “primitive” environment himself. He did all this so he could rape kids. Oh, he did it for the scientific curiosity and love of medicine, but he also did it so he could rape kids. Gajdusek was a pedophile in the actual-lifelong-exclusive-paraphilia sense, as opposed to the “metonym for child molester” sense. Some people who roll snake-eyes on the Sexuality Dice repress it, but some are perfectly happy to act on it; Gajdusek was #2 in its fullest form, the kind of guy who believes that a well-lived life includes raping some kids. DTM doesn’t shy from this, not for a moment. It’s the first thing he tells you about Gajdusek. It couldn’t not be; you couldn’t talk about why he went to PNG otherwise. When Gajdusek landed in PNG, he first found the place too civilized. He’d been promised a land of “cannibal savages” – where were they? After some traipsing, he found them, right where he was promised. The Fore were perfect for Gajdusek. They had some kind of medical mystery that’d been lost on everyone else. They ate each other, in exactly the way he loved detailing in his diaries (“”Women and children, particularly, partake of the human flesh,” he noted with pleasure”). As kuru cases popped up, he aggressively recorded them. He wrote lovingly detailed notes that he sent back to his Australian advisor. He wrote with intensity, with exclamation marks, with the joie de vivre of a man just where he wanted to be. Gajdusek smothered the Fore with ‘cures’ that never worked, but they didn’t get angry at him. As DTM dryly puts it: “Their children trusted him, and that was enough for them.” At some point, someone suggested sending an anthropologist...or an epidemiologist...or literally anyone with more credentials than Gajdusek and Zigas3. Gajdusek threw a shitfit, convinced this one-and-a-half-man team was enough to Solve The Problem Forever. But he got bored eventually – running off with another tribe with, as his diary notes at length, an apparent custom of youths ritually fellating older men – and Zigas, I dunno, the book neglects him a bit here. So they managed to sneak in some anthropologists. The husband-and-wife team of Robert Glasse and Shirley Lindenbaum4 were the first involved parties to give a shit about the Fore as people, rather than as colonial subjects/medical mysteries/walking sex toys. What they uncovered was fascinating. The Fore were cannibals, yes, but they were recent cannibals. They didn’t have an ancient tradition of eating their dead, like the other visitors assumed. They happened to be in contact with some cannibal groups, and after a Fore man died of “sorcery”, they thought: well, what would happen if we ate him? “People tasting it expressed their approval. ‘”This is sweet,” they said, “What is the matter with us, are we mad? Here is good food and we have neglected to eat it.”” If not for the wild coincidence that the first Fore cannibalism victim had a prion disease, kuru would never have existed. Glasse and Lindenbaum started to put together the pieces. They’d been sent down to rule out a genetic explanation – to track the kinship ties of the Fore and see how the disease ran through families. It didn’t run through families in any coherent sense, but it sure did run through cannibalism. The clincher was the age distribution. The Fore, ever enthused by colonialism, quit eating each other as soon as the Australians arrived. Children stopped dying of kuru shortly after; they simply weren’t exposed to the infectious agent. The couple sent the news to Gajdusek, who was off raping kids somewhere else. In the next part of the book, DTM runs through Gajdusek’s many conjectures of kuru’s cause – more like sketches or abstract paintings than like true hypotheses. Gajdusek was annoyed that someone else was doing something he “totally could’ve done”, and even more annoyed that another lab was running similar experiments – an attempt at a vaccine for a particular sheep disease had accidentally created a prion generator. But he was happy to swoop in and claim the credit for what he was starting to think of as “slow viruses”, an infection that somehow lays dormant for years. DTM portrays Gajdusek perfectly, in that “real life has no need for verisimilitude” way. Gajdusek was at once a brilliant man, an all-consuming narcissist, an entertaining character, and a monster beyond redemption. A lesser book might pick one or two. The Family That Couldn’t Sleep portrays him as all four, and on a personality level (as opposed to a scientific one), the Gajdusek-focused parts are some of the most gripping. --------------------------------------------------------- Outside of the jumps between the Venetian family and everything else, The Family That Couldn’t Sleep is not siloed. The narratives of all prion diseases are deeply intertwined. This is what makes it a great book. It’s 300 pages of dramatic irony. You read the whole thing, waiting for the eureka moment – the point everyone realizes they’re looking at the same cause. It does, however, make it a tad difficult to review or synopsize. The book’s story is so weird – and, often, so at odds with conventional wisdom that trickles down about the Fore et al – that you have to recap quite a bit, and the book steadfastly resists recapping. The next couple chapters after we depart from Gajdusek’s credit-claiming are mostly about experiments with various prion diseases. They’re scientifically fascinating. Unlike some medical-books-for-general-audiences (cough, How Not to Study a Disease), DTM never talks down to the reader. He assumes someone reading a 300-page book about prions is smart and wants to learn about prions. He also has – you can feel it in his words – the agonizing experience of spending his life on the other side of the doctor’s desk, trying to beat into whoever he’s talking to that no, seriously, you don’t need to lie to him or try explain a complex disease at a fourth-grade level. The first prion disease studied was scrapie. Scrapie was a big deal – it starved and killed large shares of British sheep flocks, making it a serious economic problem. Veterinary researchers had tried to prevent or cure it for centuries. It was a veritable graveyard of ambitions: Quintessential was D. R. Wilson at the Moredun Institute in Scotland, who worked in the middle of the last century for more than a decade trying, with mounting frustration, to kill the scrapie agent. He found that it survived desiccation; dosing with chloroform, phenol, and formalin; ultraviolet light; and cooking at 100 degrees centigrade for thirty minutes. The scrapie researcher Alan Dickinson told me he remembered Wilson at the end of his career as “very, very, very quiet. Of course, that was after his breakdown.” “Now it is our turn to study prions. Perhaps we should approach the subject cautiously.” The problem, as DTM explains, is that prion diseases were impossible. They violated 20th-century understandings of biology. Proteins “were no more alive, and no more infectious, than bone”. Prion diseases seemed to have too many causes – genetic, infectious, and sporadic. They looked infection-like in some ways, but patients didn’t produce virus antibodies. Sheep exposed to scrapie, or chimps infected with kuru, took years to develop symptoms. Their facts did not fit together. In the 1960s, people started wondering. The unifying trait of prion agents was that they had to be denatured to be destroyed. Was this a particularly small virus defined by its protein coating? Or – even more outre – was it pure protein, no DNA at all? No one could figure out quite how the latter worked, but it was tempting. Gajdusek, by now a major figure in this field, kept a foot in both worlds. He didn’t want to stake his reputation on a no-DNA hypothesis, but he certainly sympathized. Enter Prusiner. Stanley Prusiner was Gajdusek’s counterpart. Where Gajdusek seemed permanently manic, Prusiner was deliberate and exacting. He entered Gajdusek’s “slow viruses” field in the early 1970s after a chance encounter with a CJD patient. He relished the laboratory in a way Gajdusek didn’t at all, and set out to optimize the hell out of his projects. Prusiner set out to isolate the smallest infectious particle in the scrapie agent. He injected tons of hamsters (hamsters got sick faster than mice) with increasingly tiny scrapie proteins, hoping to determine whether the Minimum Viable Scrapie was DNA. By the mid-1980s, he’d produced something so small it couldn’t possibly be a virus. Denaturing it destroyed it; exposing it to nucleic acid dissolvers actually made it stronger. Emboldened by this discovery, Prusiner set out to anoint himself the King of Prions. Here emerges something of a Voldemort-Umbridge distinction – the difference between cartoonish villainy and banal evil. Gajdusek is a bad guy because he rapes kids. Prusiner is a bad guy because he is the most grotesque stereotype of the Advisor/Peer Reviewer from Hell made flesh. Everything Prusiner did was to build his reputation atop a pile of skulls. When recruited as a peer reviewer for other prion papers, he wrote negative reviews to undermine their authors. He worked his grad students to the bone and intentionally destroyed their careers, telling them he’d “ruin them” if they entered prion research as competitors. He lied about the origin of the protein-only hypothesis, claiming he originated it a decade after it was actually conjectured. But hey, he was good at getting grants. I was surprised reading a lot of this, because for all the time I’ve been aware of it, the cause of prion disease has seemed settled. “Oh yeah, it’s a protein that gets all fucked up.” But DTM goes through just how unsettled it was right up through to The Family That Couldn’t Sleep’s publication. Serious confirmation only arrived a couple years later. Many people were deeply critical of the prion hypothesis – often, it seemed, because they loathed Prusiner too much to go along. Throughout the book, he cuts an uncharismatic figure. Gajdusek and Prusiner both won the Nobel for discovering prions, decades apart. This tells you something – the “discovery” of prions can be construed quite a few ways. Gajdusek formulated the hypothesis; Prusiner proved it. Gajdusek was grievously offended by Prusiner’s Nobel, perceiving his rival – not inaccurately – as a follower who never originated any ideas of his own. But Gajdusek was offended from a federal prison cell, so how’d that work out for him? Fascinating as all this is, no one published a book about prions in the mid-2000s because it was about kuru or FFI. They published books about prions because teenagers were dying, and people wanted to know why. DTM lays the seeds for part 3 – the mad cow section – in part 1. This is a discussion of scrapie, the longstanding prion disease of sheep. Scrapie was a medical mystery for centuries (remember poor D. R. Wilson), precisely because of the intuitive implausibility of prions. The scrapie chapter is a great history-of-science piece, covering the agricultural productivity revolutions of the 18th century, the surfeit of bizarre origins veterinarians concocted, and the treatments that never worked. Scrapie is not transmissible to humans – well, we hope. It’s concerningly transmissible to primates. But it’s been around for a long, long time, and it doesn’t epidemiologically look like humans get it...we hope. Anyway, you ever tried to generalize from one example? The British government did! In the mid-1980s, strange reports started coming out of the UK’s farms. Farmers were describing a new disease where dairy cows – incredibly docile creatures, under normal circumstances – turned hostile, kicking them as they went into the milking stalls. The symptoms looked to all the world like scrapie. Epidemiologists tracing the outbreaks found a unifying link with “cake” – animal protein feed sweetened with molasses. The scrapie-like symptoms must have traced to an infected sheep. But scrapie doesn’t transmit to humans, so it must be okay to keep slaughtering them, right? We all know how this ended. The best term for the British response to the mad cow outbreak is “cacklingly evil conspiracy”. The agricultural industry really, really didn’t need a huge zoonotic outbreak – so it decided it didn’t have one. They first suppressed all mentions that the disease looked like scrapie, then – when this became impossible – hyped up that scrapie doesn’t transmit to humans, so there’s nothing to worry about. The formal name of the disease, “bovine spongiform encephalopathy”, was supposedly chosen to optimize for unfamiliarity – it wouldn’t fit well in a headline. They emphasized, extensively, that there was nothing to worry about. Ever. At some point, people started asking questions. If there was nothing to worry about, why was the agricultural industry panicking so hard? As things became ever more worry-inducing, this turned down ludicrously twisting paths: Meanwhile, the Southwood Working Party and the experts who advised it were learning on the job. They learned, for instance, that the BSE agent entered the animal through the mouth and then followed the digestive tract into the organs that try to filter out infections—the tonsils, the guts, and the spleen—and from there traveled into the peripheral and central nervous system, and finally arrived at the brain. They also learned that pasties, meat pies, and even some baby foods contained tissues from a lot of those organs. So the Southwood Working Party recommended banning these organs, but only from baby food. This started a chain reaction of consumer doubt: if infected cow organs were unsafe for babies, how could they be good for adults? The government then banned offal, as the organs were collectively called, in all human food but gave the industry a grace period to get it out of the feed supply. Then pet food manufacturers began to wonder if what drove cows mad might not also drive dogs, cats, and parrots mad. The feed they sold came from concentrate made of the same sick animals that had previously made up the meat and bone meal farmers used. Their trade group decided to put a similar ban in place—immediately. So for five months it was safer to be a dog than a human in Britain. DTM spends pretty much this whole section of the book making fun of the British government. To be fair, they deserved it. They killed hundreds of kids in agonizing and preventable ways – they could take some ribbing. This is all throughout the mid-1980s to early-mid 1990s. Through this period, it wasn’t yet clear that mad cow could spread to humans. The panic was clear, and deserved, but it didn’t yet have a match for its powder keg. It would alight. The first suspected case of vCJD – human mad cow – was in 1994. Fifteen-year-old Vicky Rimmer developed a sudden, strange disease. Doctors gave her months to live...until she died in 1998. A couple other suspected cases trickled down through the mid-90s, including a young man who made meat pies for a living, whose grieving mother received a letter from the Prime Minister that “humans do NOT get mad cow disease”. (That must’ve been fun.) Soon, they couldn’t deny it any longer. On March 20, 1996, Stephen Dorrell, the health secretary, stood up in Parliament to announce the news that had already appeared as a tentative conclusion in scientific journals and as rumor in newspapers for the previous two years: British beef was killing British teenagers. The first confirmed death was that of Stephen Churchill, a nineteen-year-old student from Wiltshire, who died in May 1995. Back in 1989, at the Southwood Working Party’s suggestion, the government had set up a surveillance unit in Edinburgh to watch for any evidence that BSE had crossed to humans. One worry had been that if BSE passed to humans, how would anyone know it? How would you recognize something you had never seen? It turned out to be easy: Churchill and the nine other teenagers who had gotten sick had spectacular amyloid plaques in their brains, chunks of dead protein almost visible to the naked eye. If sporadic CJD was a whisper, BSE-caused prion disease was a shout. The investigators sat open-mouthed looking at slides whose damage, they feared, portended the most severe epidemic in modern British history. This part of the book is not fun. It lacks the insane personalities and duelling careers of the other entries. It is an honest chronology of the vCJD epidemic – a gruesome failure of the agricultural industry, the one system that everyone is vulnerable to. The government and industry had completely violated their duty of care to citizens and consumers. They were paying the price. No one would buy British beef anymore – not while they watched their children die. Now here’s the thing: this is ethnography, not historiography. The Family That Couldn’t Sleep is a book from the mid-2000s. The epidemic was not at all in the rear view mirror. There were piles of unanswered questions that DTM constantly alludes to. We have eighteen years more hindsight than he did then. What do we know now? --------------------------------------------------------- In 2006, the vCJD epidemic looked like it was going to be a lot better than the worst fears. BSE itself was a huge problem for the cattle industry, but honestly, no one is too sympathetic to the cattle industry. People were not going to die in anywhere near the numbers believed. We had all sorts of reassuring data coming out about this, which DTM chronicles. We were learning that only some genotypes seemed susceptible to vCJD. We didn’t see any older people die of the disease. We were seeing numbers drop, such that vCJD must have a pretty short incubation period. Anyway, all of this is wrong! The Family That Couldn’t Sleep was written in the candidate gene era. Back then, the nascent field of human genetics was sure it was about to Solve Polygenism. Yes, the simple Mendelian monogenic patterns popular a few decades back clearly didn’t apply to common diseases, but how many variants could there be? We were about to discover the five genes influencing 20% of Alzheimer’s risk each, the five genes influencing 20% of heart disease risk each, etc., and once we were done we’d just do gene therapy and cure Alzheimer’s. A paper on autism genetics from 1999 was so outre as to speculate there might be as many as fifteen genes involved. The fact we are now using the term “omnigenic model” should tell you roughly how well this worked out. Do you remember SNPedia? If you were a 2014 Slate Star Codex reader, you might. 2014 was still pretty candidate gene. People were out there publishing papers saying a single variant could increase your life expectancy by 15 years. SNPedia was a site that beautifully categorized all of these, so you could do 23andme or whatever, look up your results on SNPedia, and make horrible life choices.5 It was eventually bought out by one of the consumer DNA companies, so no one ever edited it again, making it a great time capsule of early-mid 2010s behavioural/medical genetics takes. SNPedia will excitedly explain to you that common genetic variants make you immune to vCJD. They cite a 2009 post from the now-archived 23andme blog titled “No Good Evidence That Potential Pool of Mad Cow Disease Victims Is Expanding”, explaining how fears of late-onset vCJD are clearly debunked by new Scientific Knowledge. Everyone who developed vCJD in the 1990s and 2000s had an M/M genotype in a particular part of the PRNP prion gene, so the roughly half the population with M/V or V/V genotypes were immune. The Family That Couldn’t Sleep buys this, too. In fact, it buys it in an even more agonizingly 2000s way. The first sign that transmissible prion diseases weren’t genotype-restricted should’ve been the growth hormone kids. You might have heard this story – from the late 1950s through mid-1980s, human growth hormone produced from brain tissue was used as a treatment for pituitary dwarfism, until it turned out to spread CJD if the originating brain was infected. DTM discusses this, to set the scene for the genetics thing. He mentions what was the state of the art at the time – that a disproportionate share of both the growth hormone kids and sporadic CJD cases were V/V homozygotes. This, uh – so the book was written in the mid-2000s, yeah? Yeah. The conclusion DTM drew – and this was a common conclusion at the time – was that homozygosity somehow made you more vulnerable to CJD, and M/M homozygosity made you vulnerable to BSE-borne CJD in particular. We cannot criticise the author for not predicting the future, but we live in the future, and can say how this worked out. Turns out, nope, M/V heterozygotes totally get vCJD. After a British man in his 30s died of CJD in 2016, he was found to have vCJD and an M/V genotype. He was tested for vCJD only because he was exceptionally young for someone with a sporadic prion disease – meaning people developing it later in life would be missed6. Did you know up to 1 in 2000 people in the UK have latent vCJD? There is one line in The Family That Couldn’t Sleep that stopped me dead in my tracks when I read it: What happens to the Italian family in the end depends less on their own actions than on the world’s interest in prion diseases, which they cannot control. If lots of people are afraid of getting variant CJD, the family benefits. If fear of prion disease goes the way of the fear of swine flu or Ebola, then they will be orphaned again. THIS BOOK IS FROM 2006! Three years before the swine flu pandemic! Eight years before the Ebola pandemic! “If you’re looking for a sign, this is it.” --------------------------------------------------------- The last section of The Family That Couldn’t Sleep addresses BSE fears in America and a nascent internet subculture DTM calls “Creutzfeldt Jakobins” – people who track American CJD cases, trying to spot vCJD patterns. When reading his description of the Creutzfeldt Jakobins, my mind constantly, uncontrollably turned to covid. Here it was – an online community of people deeply skeptical about a disease’s official story, tracking every contradiction, every implausibility, every statistic that failed to apply to the individual. Self-described “redneck hippies” and “soccer mom Republicans” teaming up to find the truth hidden behind an impossible world. You know what they’re doing now. I’ve always combined a deep interest in medicine with a healthy distrust for it. People who are constitutionally inquisitive, anti-authoritarian, and suspicious about official narratives tend to end up skeptical of at least some mainstream claims in the field. This is not to say I think you should take bleach enemas or something, just that I understand the impulse behind concluding the US government was covering up a local vCJD wave. Traditionally, sporadic prion diseases are said to have a prevalence of one in a million. (Hold on to that for a second.) The last section of the book is a chronology of Americans finding bizarrely more than one in a million of their friends dying of sporadic CJD, often at inexplicably young ages, sometimes in geographical clusters. This is understandably suspicious. Then DTM goes on to reassure us by saying none of these cases were confirmed to have an M/M genotype, which OH GOD OH FUCK A number of high-profile people in the prion world, including Gajdusek, are clarified as not believing sporadic prion diseases exist. You get the impression DTM doesn’t, either. Now, how common are prion diseases? Eric Vallabh Minikel has an answer for you! Eric and his wife Sonia are prion researchers from a rather unique background – after Sonia was diagnosed as having a single-gene mutation with ~100% penetrance for prion disease, they left their previous jobs to dedicate their lives to curing it. It turns out, when you run the numbers, you get not one in a million but 1 in 5000 people dying of prion diseases. This is best described as “nightmarishly high”. I’m normed on genetic disorders. A genetic disorder that affects one in five thousand people is pretty common! I have known, in person, completely unselected, just from “random people I’ve met in my life in a non-medical context”, someone with a ~1/250k syndrome and someone with a ~1/50k-100k syndrome. I don’t think anyone in my extended family knows someone who died of a prion disease. I feel like it would’ve come up if they did! Prion diseases have distinctive phenotypes. Not distinctive enough, apparently, to avoid a lot of CJD being misdiagnosed as Alzheimer’s – but diagnosis is consistently insane. Something DTM reiterates throughout The Family That Couldn’t Sleep is just what prion dementia looks like. The characteristic dementia in prion diseases spares something – “self” or “recognition” or “reflection” – that is not spared by Alzheimer’s, or by most common dementias. Shouldn’t this be, uh, noticeable?7 They kill rapidly, often over the course of months, and often onset in midlife. ALS shares this pattern and is way, way more common than prion diseases; you hear about ALS far more in the “disorder people actually have” sense. What am I missing here? Anyway: 1 in 2000 prevalence of latent vCJD in the UK + extreme lack of clarity over whether scrapie is human-transmissible + blood donations spread vCJD + sporadic CJD prevalence keeps going up = ??? (Yes, I am annoyed that most countries have lifted their ban on UK blood donors, thank you for asking!) --------------------------------------------------------- But back to the book. The “American chapter” is one-third about the country’s response to vCJD, one-third about the Creutzfeldt Jakobins, and one-third about chronic wasting disease. The last part is the most interesting. Chronic wasting disease is a prion disease of deer. Like scrapie, it “probably, we hope” isn’t human-transmissible (eat venison at your own risk). Under natural circumstances, deer shouldn’t get prion diseases: A prion plague should not be possible among ruminants in the wild. Deer are not cannibals, as the cows that spread BSE were forced to be; and, because deer and elk are not domesticated, they do not have enough contact with one another to spread a prion infection the way sheep are thought to spread scrapie. But deer do not live as they used to live, humans having once again brought their ambitions to bear on the natural course of things. The Family That Couldn’t Sleep is a book of medical anthropology. Anthropology of the Veneto, anthropology of Papua New Guinea, anthropology of 1990s Britain. Here, it is an anthropology of America. Americans, having won the world, still fight to win their own backyard. The North American continent is geographically diverse, cutting through rain-snow-shine, mountains jutting over plains, cities sprawling into wilderness, habitations criss-cross dotted with surprisingly few empty zones. Go somewhere like Denver, the Mile High City, three million people fighting against nature. Few other countries have anything like this; geographically vast polities usually have uninhabitable blocks. Australians are twenty-five million people clustered against the shore. It still surprises me, after all this time, how every US state has a meaningful city8. Midcentury Denver, growing and sprawling out across its mountains, started to run into their natural inhabitants – deer. Starvation is one way nature adjusts the deer population to the available food supply. People did not usually see this process, but in the 1950s and 1960s Colorado became more densely settled, reducing forested areas and forcing deer to look longer and harder for food. At the same time, the state enacted conservation laws, limiting when and where hunters could shoot. Soon emaciated deer began wandering onto the lawns and through suburban streets looking for a meal. People began to feed them, only to find that they died anyway. They would drop dead by haystacks, along highways, and in flower beds. In the late 1960s, a young biologist named Gene Schoonveld tried to figure out why the deer starved even when they were fed.9 He deprived some deer of food for a while, “[h]e cut windows in their stomachs to see what went on inside, and then he began to feed them”. While this was going on, he had a control group of healthy, well-fed deer as backups in case anything went wrong. It did...but not to the experimental group. The pen in which the deer were kept also housed sheep, which, it turned out, were scrapie carriers. The deer somehow acquired scrapie – there’s a huge unanswered question here, which DTM doesn’t address. How did they get scrapie? They didn’t eat the sheep, presumably. Did it somehow transmit from casual contact? This is not supposed to happen. And yet: the deer in the sheep pen started dying of a mysterious scrapie-like disease, one never reported before, that would go on to infect thousands. These deer were released into the wild. Ten years later, the first reports of chronic wasting disease came out. The disease spread across deer and elk in the western half of the country. By the turn of the millennium, cases were exploding – and lost all geographical restriction. DTM can report up to 2005, at which point it was floating around Upstate New York. This kind of spread doesn’t track natural deer migration. That’s irrelevant, because nothing about CWD’s spread is natural. We shift gears into an anthropology of the American hunter. The hunter wants to shoot the most impressive buck, to bag himself one with as many “points” as possible – one whose antlers branch out most. A “ten-point buck” has five branches on each horn: Original by Ric McArthur Nature doesn’t make enough bucks with perfectly symmetrical ten-point horns. To fill the demand, the market had to step in. Thus was born the deer farm industry, which raises captive deer in better genetic and nutritional conditions than Nature permits, then ships them across the country so hunters who couldn’t get legit ten-point bucks get the taxidermy piece for their wall. These are controversial amongst hunters and illegal in numerous states – but the industry is big enough to spread CWD. (The kind of hunter who needs a deer shipped to his house is the kind of hunter who will fumble killing it.) Another problem is supplemental feeding – leaving out protein-enriched food for deer to eat. This produces “trophy class animals at an earlier age”, but again, what’s in that protein? (“It is much like feeding your cows 41 percent protein cottonseed cake during the winter to raise the protein level in the cow’s diet to a level that will maintain acceptable production”, says that article from 1991.)10 The book segues into a vignette. CWD was new in Wisconsin in the early 2000s, and the state’s Department of Natural Resources was optimistic it could eradicate it. In a state with a love of hunting, you could, in theory, recruit people to kill every single deer in a 400-square-mile radius: In many states, the state would have had to call out the National Guard for such an onslaught, but hunting is a passion in Wisconsin. Hunters shoot 450,000 deer every year, more than in any other state. “I’m looking for ardent hunters to help us, unless fear or their wives keep them away,” one DNR official told a Milwaukee magazine. The state extended the normal hunting season and waived the usual limit of one buck per hunter, and the hunters came out in force. The whole affair was gruesome – one official called it “hunting for slob hunters”. If you’re trying to eradicate a prion disease, you can’t very well let people take the carcasses home to eat. Bodies piled up in control stations, decomposition mingling with bleach. The 2002 hunt established a base rate of 2% for chronic wasting disease in Wisconsin deer, with the most affected areas getting up to 10%. Further hunts in 2003, 2004, and 2005 spread to wider and wider areas – and didn’t move the needle one bit. This is to say that CWD is quite a bit more common in the American deer population than BSE ever was in British cattle. Since publication, it’s popped up in Norway and South Korea. Notably, Norway doesn’t allow for the import of cervids, raising numerous questions about how it got there. There are no unambiguous cases of CWD transmission to humans, and in vivo/in vitro primate studies have mixed results. There sure are some unusually young hunters with sporadic CJD, though. But don’t worry, most of them aren’t M/M homozygotes! There is an absolute ton going on in this book. I’ve had to skim over whole sections. Parts that couldn’t be easily slotted into a narrative review include: When Gajdusek was invited to a party at Prusiner’s house, he was horrified to find his rival had purchased hundreds of New Guinean statues – all with the genitals removed.

Inline links: 2, Lyttle Lytton, 3, 4, a couple years later, concerningly transmissible to primates, omnigenic model, you might, 5, SNPedia, a 2009 post, https://substackcdn.com/image/fetch/$s_!N93S!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fced2eca3-ec58-40b8-8c13-debdb559ab8f_651x601.png, Yeah., nope, M/V heterozygotes totally get vCJD, 6, up to 1 in 2000 people in the UK have latent vCJD, bleach enemas, has an answer for you, 7, blood donations spread vCJD, going, up, 8, 9, not supposed to happen, https://substackcdn.com/image/fetch/$s_!0J8B!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F2a64b287-a7c6-4d82-bbe1-da949fc93118_1024x683.png, Ric McArthur, controversial, amongst, hunters, illegal in numerous states, trophy class animals at an earlier age, 10, Norway, South Korea, mixed results, sure are

Yeah. The conclusion DTM drew – and this was a common conclusion at the time – was that homozygosity somehow made you more vulnerable to CJD, and M/M homozygosity made you vulnerable to BSE-borne CJD in particular. We cannot criticise the author for not predicting the future, but we live in the future, and can say how this worked out. Turns out, nope, M/V heterozygotes totally get vCJD. After a British man in his 30s died of CJD in 2016, he was found to have vCJD and an M/V genotype. He was tested for vCJD only because he was exceptionally young for someone with a sporadic prion disease – meaning people developing it later in life would be missed6. Did you know up to 1 in 2000 people in the UK have latent vCJD? There is one line in The Family That Couldn’t Sleep that stopped me dead in my tracks when I read it: What happens to the Italian family in the end depends less on their own actions than on the world’s interest in prion diseases, which they cannot control. If lots of people are afraid of getting variant CJD, the family benefits. If fear of prion disease goes the way of the fear of swine flu or Ebola, then they will be orphaned again. THIS BOOK IS FROM 2006! Three years before the swine flu pandemic! Eight years before the Ebola pandemic! “If you’re looking for a sign, this is it.” --------------------------------------------------------- The last section of The Family That Couldn’t Sleep addresses BSE fears in America and a nascent internet subculture DTM calls “Creutzfeldt Jakobins” – people who track American CJD cases, trying to spot vCJD patterns. When reading his description of the Creutzfeldt Jakobins, my mind constantly, uncontrollably turned to covid. Here it was – an online community of people deeply skeptical about a disease’s official story, tracking every contradiction, every implausibility, every statistic that failed to apply to the individual. Self-described “redneck hippies” and “soccer mom Republicans” teaming up to find the truth hidden behind an impossible world. You know what they’re doing now. I’ve always combined a deep interest in medicine with a healthy distrust for it. People who are constitutionally inquisitive, anti-authoritarian, and suspicious about official narratives tend to end up skeptical of at least some mainstream claims in the field. This is not to say I think you should take bleach enemas or something, just that I understand the impulse behind concluding the US government was covering up a local vCJD wave. Traditionally, sporadic prion diseases are said to have a prevalence of one in a million. (Hold on to that for a second.) The last section of the book is a chronology of Americans finding bizarrely more than one in a million of their friends dying of sporadic CJD, often at inexplicably young ages, sometimes in geographical clusters. This is understandably suspicious. Then DTM goes on to reassure us by saying none of these cases were confirmed to have an M/M genotype, which OH GOD OH FUCK A number of high-profile people in the prion world, including Gajdusek, are clarified as not believing sporadic prion diseases exist. You get the impression DTM doesn’t, either. Now, how common are prion diseases? Eric Vallabh Minikel has an answer for you! Eric and his wife Sonia are prion researchers from a rather unique background – after Sonia was diagnosed as having a single-gene mutation with ~100% penetrance for prion disease, they left their previous jobs to dedicate their lives to curing it. It turns out, when you run the numbers, you get not one in a million but 1 in 5000 people dying of prion diseases. This is best described as “nightmarishly high”. I’m normed on genetic disorders. A genetic disorder that affects one in five thousand people is pretty common! I have known, in person, completely unselected, just from “random people I’ve met in my life in a non-medical context”, someone with a ~1/250k syndrome and someone with a ~1/50k-100k syndrome. I don’t think anyone in my extended family knows someone who died of a prion disease. I feel like it would’ve come up if they did! Prion diseases have distinctive phenotypes. Not distinctive enough, apparently, to avoid a lot of CJD being misdiagnosed as Alzheimer’s – but diagnosis is consistently insane. Something DTM reiterates throughout The Family That Couldn’t Sleep is just what prion dementia looks like. The characteristic dementia in prion diseases spares something – “self” or “recognition” or “reflection” – that is not spared by Alzheimer’s, or by most common dementias. Shouldn’t this be, uh, noticeable?7 They kill rapidly, often over the course of months, and often onset in midlife. ALS shares this pattern and is way, way more common than prion diseases; you hear about ALS far more in the “disorder people actually have” sense. What am I missing here? Anyway: 1 in 2000 prevalence of latent vCJD in the UK + extreme lack of clarity over whether scrapie is human-transmissible + blood donations spread vCJD + sporadic CJD prevalence keeps going up = ??? (Yes, I am annoyed that most countries have lifted their ban on UK blood donors, thank you for asking!) --------------------------------------------------------- But back to the book. The “American chapter” is one-third about the country’s response to vCJD, one-third about the Creutzfeldt Jakobins, and one-third about chronic wasting disease. The last part is the most interesting. Chronic wasting disease is a prion disease of deer. Like scrapie, it “probably, we hope” isn’t human-transmissible (eat venison at your own risk). Under natural circumstances, deer shouldn’t get prion diseases: A prion plague should not be possible among ruminants in the wild. Deer are not cannibals, as the cows that spread BSE were forced to be; and, because deer and elk are not domesticated, they do not have enough contact with one another to spread a prion infection the way sheep are thought to spread scrapie. But deer do not live as they used to live, humans having once again brought their ambitions to bear on the natural course of things. The Family That Couldn’t Sleep is a book of medical anthropology. Anthropology of the Veneto, anthropology of Papua New Guinea, anthropology of 1990s Britain. Here, it is an anthropology of America. Americans, having won the world, still fight to win their own backyard. The North American continent is geographically diverse, cutting through rain-snow-shine, mountains jutting over plains, cities sprawling into wilderness, habitations criss-cross dotted with surprisingly few empty zones. Go somewhere like Denver, the Mile High City, three million people fighting against nature. Few other countries have anything like this; geographically vast polities usually have uninhabitable blocks. Australians are twenty-five million people clustered against the shore. It still surprises me, after all this time, how every US state has a meaningful city8. Midcentury Denver, growing and sprawling out across its mountains, started to run into their natural inhabitants – deer. Starvation is one way nature adjusts the deer population to the available food supply. People did not usually see this process, but in the 1950s and 1960s Colorado became more densely settled, reducing forested areas and forcing deer to look longer and harder for food. At the same time, the state enacted conservation laws, limiting when and where hunters could shoot. Soon emaciated deer began wandering onto the lawns and through suburban streets looking for a meal. People began to feed them, only to find that they died anyway. They would drop dead by haystacks, along highways, and in flower beds. In the late 1960s, a young biologist named Gene Schoonveld tried to figure out why the deer starved even when they were fed.9 He deprived some deer of food for a while, “[h]e cut windows in their stomachs to see what went on inside, and then he began to feed them”. While this was going on, he had a control group of healthy, well-fed deer as backups in case anything went wrong. It did...but not to the experimental group. The pen in which the deer were kept also housed sheep, which, it turned out, were scrapie carriers. The deer somehow acquired scrapie – there’s a huge unanswered question here, which DTM doesn’t address. How did they get scrapie? They didn’t eat the sheep, presumably. Did it somehow transmit from casual contact? This is not supposed to happen. And yet: the deer in the sheep pen started dying of a mysterious scrapie-like disease, one never reported before, that would go on to infect thousands. These deer were released into the wild. Ten years later, the first reports of chronic wasting disease came out. The disease spread across deer and elk in the western half of the country. By the turn of the millennium, cases were exploding – and lost all geographical restriction. DTM can report up to 2005, at which point it was floating around Upstate New York. This kind of spread doesn’t track natural deer migration. That’s irrelevant, because nothing about CWD’s spread is natural. We shift gears into an anthropology of the American hunter. The hunter wants to shoot the most impressive buck, to bag himself one with as many “points” as possible – one whose antlers branch out most. A “ten-point buck” has five branches on each horn: Original by Ric McArthur Nature doesn’t make enough bucks with perfectly symmetrical ten-point horns. To fill the demand, the market had to step in. Thus was born the deer farm industry, which raises captive deer in better genetic and nutritional conditions than Nature permits, then ships them across the country so hunters who couldn’t get legit ten-point bucks get the taxidermy piece for their wall. These are controversial amongst hunters and illegal in numerous states – but the industry is big enough to spread CWD. (The kind of hunter who needs a deer shipped to his house is the kind of hunter who will fumble killing it.) Another problem is supplemental feeding – leaving out protein-enriched food for deer to eat. This produces “trophy class animals at an earlier age”, but again, what’s in that protein? (“It is much like feeding your cows 41 percent protein cottonseed cake during the winter to raise the protein level in the cow’s diet to a level that will maintain acceptable production”, says that article from 1991.)10 The book segues into a vignette. CWD was new in Wisconsin in the early 2000s, and the state’s Department of Natural Resources was optimistic it could eradicate it. In a state with a love of hunting, you could, in theory, recruit people to kill every single deer in a 400-square-mile radius: In many states, the state would have had to call out the National Guard for such an onslaught, but hunting is a passion in Wisconsin. Hunters shoot 450,000 deer every year, more than in any other state. “I’m looking for ardent hunters to help us, unless fear or their wives keep them away,” one DNR official told a Milwaukee magazine. The state extended the normal hunting season and waived the usual limit of one buck per hunter, and the hunters came out in force. The whole affair was gruesome – one official called it “hunting for slob hunters”. If you’re trying to eradicate a prion disease, you can’t very well let people take the carcasses home to eat. Bodies piled up in control stations, decomposition mingling with bleach. The 2002 hunt established a base rate of 2% for chronic wasting disease in Wisconsin deer, with the most affected areas getting up to 10%. Further hunts in 2003, 2004, and 2005 spread to wider and wider areas – and didn’t move the needle one bit. This is to say that CWD is quite a bit more common in the American deer population than BSE ever was in British cattle. Since publication, it’s popped up in Norway and South Korea. Notably, Norway doesn’t allow for the import of cervids, raising numerous questions about how it got there. There are no unambiguous cases of CWD transmission to humans, and in vivo/in vitro primate studies have mixed results. There sure are some unusually young hunters with sporadic CJD, though. But don’t worry, most of them aren’t M/M homozygotes! There is an absolute ton going on in this book. I’ve had to skim over whole sections. Parts that couldn’t be easily slotted into a narrative review include: When Gajdusek was invited to a party at Prusiner’s house, he was horrified to find his rival had purchased hundreds of New Guinean statues – all with the genitals removed.

Inline links: Yeah., nope, M/V heterozygotes totally get vCJD, 6, up to 1 in 2000 people in the UK have latent vCJD, bleach enemas, has an answer for you, 7, blood donations spread vCJD, going, up, 8, 9, not supposed to happen, https://substackcdn.com/image/fetch/$s_!0J8B!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F2a64b287-a7c6-4d82-bbe1-da949fc93118_1024x683.png, Ric McArthur, controversial, amongst, hunters, illegal in numerous states, trophy class animals at an earlier age, 10, Norway, South Korea, mixed results, sure are

Original by Ric McArthur Nature doesn’t make enough bucks with perfectly symmetrical ten-point horns. To fill the demand, the market had to step in. Thus was born the deer farm industry, which raises captive deer in better genetic and nutritional conditions than Nature permits, then ships them across the country so hunters who couldn’t get legit ten-point bucks get the taxidermy piece for their wall. These are controversial amongst hunters and illegal in numerous states – but the industry is big enough to spread CWD. (The kind of hunter who needs a deer shipped to his house is the kind of hunter who will fumble killing it.) Another problem is supplemental feeding – leaving out protein-enriched food for deer to eat. This produces “trophy class animals at an earlier age”, but again, what’s in that protein? (“It is much like feeding your cows 41 percent protein cottonseed cake during the winter to raise the protein level in the cow’s diet to a level that will maintain acceptable production”, says that article from 1991.)10 The book segues into a vignette. CWD was new in Wisconsin in the early 2000s, and the state’s Department of Natural Resources was optimistic it could eradicate it. In a state with a love of hunting, you could, in theory, recruit people to kill every single deer in a 400-square-mile radius: In many states, the state would have had to call out the National Guard for such an onslaught, but hunting is a passion in Wisconsin. Hunters shoot 450,000 deer every year, more than in any other state. “I’m looking for ardent hunters to help us, unless fear or their wives keep them away,” one DNR official told a Milwaukee magazine. The state extended the normal hunting season and waived the usual limit of one buck per hunter, and the hunters came out in force. The whole affair was gruesome – one official called it “hunting for slob hunters”. If you’re trying to eradicate a prion disease, you can’t very well let people take the carcasses home to eat. Bodies piled up in control stations, decomposition mingling with bleach. The 2002 hunt established a base rate of 2% for chronic wasting disease in Wisconsin deer, with the most affected areas getting up to 10%. Further hunts in 2003, 2004, and 2005 spread to wider and wider areas – and didn’t move the needle one bit. This is to say that CWD is quite a bit more common in the American deer population than BSE ever was in British cattle. Since publication, it’s popped up in Norway and South Korea. Notably, Norway doesn’t allow for the import of cervids, raising numerous questions about how it got there. There are no unambiguous cases of CWD transmission to humans, and in vivo/in vitro primate studies have mixed results. There sure are some unusually young hunters with sporadic CJD, though. But don’t worry, most of them aren’t M/M homozygotes! There is an absolute ton going on in this book. I’ve had to skim over whole sections. Parts that couldn’t be easily slotted into a narrative review include: When Gajdusek was invited to a party at Prusiner’s house, he was horrified to find his rival had purchased hundreds of New Guinean statues – all with the genitals removed.

Inline links: Ric McArthur, controversial, amongst, hunters, illegal in numerous states, trophy class animals at an earlier age, 10, Norway, South Korea, mixed results, sure are

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