I think it is Roko’s obligation to do a better job of researching and addressing counter-arguments before making a post like this one. It contains absolutely nowhere near sufficient justification for the accusations it is leveling.
viking_math
Karma: 154
“I think this is flawed. Clearly, overeating for your entire life will probably have different effects from overeating for 22 days. There are a lot of 22-day periods in a person’s life. Someone on their 30th birthday has gone through nearly 500 of them.”
This is true, but doesn’t the same critique apply to most of the hypoxia studies you cite? They’re all a few weeks or shorter (or are performed on animals) and most of them seem to have small effect sizes (a few pounds). Of course, these effects could accumulate, but they could also rebound.
“In fact, studies that simulate high altitude with hypobaria (as opposed to normobaric hypoxia) seem to show greater effects on hunger perception than studies that actually take people to high altitudes. “
This result doesn’t surprise me. I’ve spent a lot of time at altitude (5-10 thousand feet above sea level) in dry conditions, but on the ground, and never noticed food to be any less flavorful, even when coming straight from sea level. I would guess some other factor is impacting airplanes specifically (don’t airplanes aggressively filter air? that seems like it could remove some scent-related particles).
Growth rates decrease as you go back in time, plus you start to hit problems like mass loss of wealth, wealth confiscation, war, natural disaster, etc.
If you think these area issues going forward, then they apply equally well to all longtermist arguments.
(I’m not actually sure if e.g. median income is positively associated with elevation in the US, since a bunch of those people are “ski bums” working a series of seasonal jobs at ski resorts, white water rafting companies, etc. I used the word class because I think those people are still disproportionately drawing from upper-class cultures and probably have high education on average, and there are definitely a lot of rich people hanging around as well, and the latter are more likely to live closer to the resorts. Mean income is definitely higher in those areas, though.)
That’s a really neat set of data in that blog post which I will have to go over in more detail later. The effect size doesn’t seem to be that large to me, but maybe I don’t have a good intuition for birth weight; 100 g = 0.2 pounds corresponds to 4% of the low range of what is considered healthy in European babies. And that’s over a fairly wide elevation range of 3,300 feet. So I would be surprised if that could explain the very large difference in adult average BMI, but I could also be totally wrong about how fetal weight translates to adult weight. Given the limitations of “controlling for observables” I’m also still leaning towards selection effects, but the close linear relationship does cast doubt on that idea. I think it casts doubt on the pollution hypothesis too, FWIW, since there’s no way that’s cleanly linear, and it probably fits better with hypoxia but still not perfectly, since air pressure decreases sublinearly with elevation.
I have no idea, although I expect any such effect to be a very long-term thing and thus tricky to design and measure.
Long ago, when SSC had an article about the altitude/obesity thing, a friend and I looked more closely at the data. I concluded that it seems like the bulk of the effect is explainable by selection effect, since there are very few people who live above a few thousand feet elevation, and they’re probably disproportionately upper class and active. See https://slatestarcodex.com/2016/12/11/open-thread-64-5/#comment-443619 (and the original post at https://slatestarcodex.com/2016/12/05/thin-air/). I’m serious about these selection effects—the data linked in my comment includes BMI values up to 3km or 9,800 feet above sea level. I don’t think there are 10,000 Americans living at that elevation total, and they almost all live in towns that primarily exist to serve wilderness recreation.
When Scott more recently posted about this hypothesis in one of the ACX open threads, one of the SMTM authors answered some questions in the comments. The mechanism tying elevation to pollution is allegedly that elevation is a proxy for how upstream you are in the water cycle, since water will accumulate toxins from the ground or being pumped into the water as it goes. To me, this seems like an extremely loose association. The relationship will depend strongly on how many pollutants are in the local area and how quickly the water loses elevation. Also, where people get their water from may not reflect exactly where they live: Consider Dillon reservoir (https://en.wikipedia.org/wiki/Dillon_Reservoir) at 9,100 feet. This water serves people in Denver, 4,000 feet below, after a fairly direct route through a tunnel and then into the Southe Platte River. The people who live near the reservoir get their water from the Green Mountain Reservoir (https://en.wikipedia.org/wiki/Green_Mountain_Reservoir) over 1,000 feet lower. And both reservoirs are filled largely from snowmelt, with the former being surrounded by generally higher mountains. And there’s clearly a lot of other factors that are visible in the obesity map at the top of Scott’s original post other than elevation—for example, there’s clearly a large drop in obesity from Kansas to Colorado, even though the state border is in a flat area 100 miles from the Rockies. You can also see large differences between New England, the upper Midwest, and the South, despite all those places being the exact same elevation.
Given the exceedingly noisy part that pollution must play in this story, and the extreme selection effects that are required to see a clear relationship between elevation and obesity, I think the latter is a much more likely explanation of the link than pollution.
Hold on. That seems to be very wrong. The world became permanently more dangerous when smallpox, cholera, typhoid, measles, mumps, and the flu jumped to humans. That only stopped being true when vaccines were developed. I think it bodes pretty well for the outlook of COVID, if we keep vaccinating. But so far as I know, it’s definitely not the case that smallpox ever became less deadly on its own.
I’m not sure it’s any more dead than other fields of social science. Which, maybe they’re all actually zombies, but that sounds excessively strong. For example, take the effect sizes of nudges. I believe that the effect of “opt out” policies for organ donation have absolutely massive effects (see https://sparq.stanford.edu/solutions/opt-out-policies-increase-organ-donation ). So is the problem that the field is dead, or that it’s just sick with the same diseases as psychology and better work needs to be done to separate wheat from chaff? Forgetting hypotheses that turn out not to hold up, doing more replications, etc. For example, I believe hindsight bias has held up as being real, having significant effects, and being difficult to overcome.
I’ve spent a lot of time in the outdoors and I’m surprised that “ticks” occupied such a large chunk of effort/relevance. Wear long pants/shirts with long sleeves when in the woods, check yourself after you get back, and put bug spray (there are certain brands that work) on your body and clothes.
I’m curious what counts as “very high elevation” and why it’s an issue. The highest cities of any size are Santa Fe, Denver and the Front Range (including Cheyenne), and SLC. You can get some very high elevations right outside Denver, but there are no towns above 10,500′and in practice there’s very little over 8,000′ or so.More information on Austin:
Physical environment: the weather is generally nice October through April. May through September tends to be hot; it’s neither the bone dry of Colorado and the desert Southwest nor the oppressive humidity of the coast. Not ideal but not terrible. I prefer cooler weather but find it tolerable to great most of the year.
Really exciting, impactful outdoor activities like mountain climbing and backpacking are a schlep. Shorter hikes, biking, water, and outdoor sports are plentiful both in and outside the city.
Because it’s growing quickly, I would expect anywhere you find to be busier than it currently is in a few years. I’d look for an area that is currently less developed than would be ideal. Based on advertising, it seems like there’s a lot of land waiting to be developed in the towns around Austin. In my experience, commuting against traffic works very well (leaving the city in the morning and returning to it in the evening).
Getting around the city without a car is generally difficult. Mass transit is very poor, particularly if you set up anywhere outside the urban core.
Cost: Austin isn’t the Bay or NYC, but it’s not what it was 10 years ago either. We have enough space to expand that it probably won’t ever get that bad, but right now the housing market is absolutely ridiculous (if you’re making a bid on a house, you have under 24 hours to come up with 45% over asking in cash, or don’t bother, is the gist). Property taxes on residences are capped; not sure about organizations. If property tax in Austin proper is an issue, the surrounding area will likely be cheaper. There is no state income tax.
Vibe: The city used to have a very laid-back atmosphere, but has grown a lot and attracted lots of companies, particularly in tech. Now it’s more “casual but lots going on.” I can’t say I have any opinion on the general epistemic culture of any city, they all seem pretty similar to me on that front, except for the hyper-political ones, which Austin isn’t (yet, at least).
I believe crime is low to average. Getting a gun is relatively easy. The only politically motivated violence I can recall is from last summer, and that affected literally every one of the 100 largest cities in the country. Seems pretty LGBT friendly—like you would expect from any blue city. There are grumblings about tech companies driving prices up from long-time residents, but these never seem to translate into any policy issues.
The rationalist community has been going strong for ~10 years; we currently have multiple weekly in-person meetups, a remote book club, and a remote monthly movie discussion. We have expanded both in numbers and activities over the pandemic. UT Austin is also located here, with many alumni staying in the area, and we get a large number of graduates from other Texas schools like A&M and Texas Tech, and a number of tech companies have recently moved in or expanded (including Facebook, Google, and Amazon).
When I was thinking about this question earlier, I was imagining explaining my reasons to various different people (I think that imagining their response sometimes allows me to come up with counterarguments that otherwise I wouldn’t think of). One of the things I wanted to do was put a prior on a zoonotic origin in Wuhan; the proximity of its apparent origin to the WIV is the main thing that sparked the lab leak theory to begin with. I did imagine someone giving a prior of 1:1000 or less, but only because the person I was thinking of isn’t experienced in Bayesian analysis and setting priors and hadn’t explicitly done any math. I never imagined that someone active in the rationalist community would say such a thing. Wuhan is a city of 11 million people; the world population is about 7.9 billion. Saying that the prior on a zoonotic origin is anything less than 11 million / 7.9 billion = 1.4/1000 means that you think people living in Wuhan are less likely to be patient 0 than the average person in the entire world.
Think about that. People living in southern China, the same region where the closely related SARS 1 pandemic started 20 years ago, a region where people are still regularly exposed to many of the same wild animals that are known to harbor and transmit viral diseases, in a region (in the exact market, in fact) which scientists identified years ago as being somewhere that a viral pandemic is likely to start, in a major city (where a spillover event is much more likely to turn into a global pandemic), … are less likely than the average person in the world to be patient 0 for such a pandemic. There is no argument here; you just said “well this seems unlikely” and randomly chose 1/1000.
Are you unaware of this paper? https://www.sciencedirect.com/science/article/pii/S1873506120304165
Furin cleavage sites have not been observed in sarbecoviruses, the closest relatives to Covid. However, they appear frequently through other viruses that are only slightly more distantly related. FCS are observed in both Hibecovirus and Nobecovirus, which are the 2 branches of Betacoronavirus most closely related to Sarbecovirus, and they appear in the next 2 closest groups as well, Merbecovirus and Embecovirus (in fact, they seem to be nearly ubiquitous in this latter family). Going a step further out, FCS seem to be extremely common in gammacoronavirus, and it appears repeatedly in Alpha and delta coronaviruses. So not only are FCS common, they appear to have evolved naturally many separate times (since they appear in many separate sections of the tree). (Also, if the FCS is related to Covid’s infectiousness, then a p-value of 1⁄800 is wrong—a virus causing a pandemic and having an FCS would not be independent!).
You started your post by saying,
But your priors are not reasonable and your evidence is weak. This is not (good) Bayesian reasoning. There is vastly more work that should have gone into making your case before jumping to “Peter Daszak killed tens of millions of people and it’s being covered up.” There might be counter-arguments to what I’ve said above, but you don’t get to sit there and say “pay me thousands of dollars to do the research” while making posts like this.