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Or explain why the NYT does use the chosen name of other people, like musicians' stage names.
Brand new account, reposting old arguments? Not suspicious at all.
Stoyan and Chiu (2024)
"Just because the market was the epicenter doesn't mean the pandemic started there," while technically true, is fairly meaningless. If the center were at the lab every lab leak proponent would be shouting at the top of their lungs this conclusively proves the lab leak theory. Debating one particular statistical analysis doesn't disprove the very elementary technique of "look at the data, it's obvious" aka https://xkcd.com/2400/.
The multiple spillover theory might be wrong. But then again, so might all of the analyses that Roko cited in his initial post, including the paper about genetic engineering, the Richard Ebright tweet, the RTK estimates, etc. The point of that part was to show that it's very easy to generate high Bayes factors if you highball favorable pieces of information, ignore unfavorable ones, make convenient assumptions, and multiply numbers together.
https://michaelweissman.substack.com/p/an-inconvenient-probability
This analysis is obviously heavily biased. No Bayes factor at all for the cases being at the market? Again, no LL supporter would seriously say the BF would be one if the cases were clustered near the WIV. This is the exact same sort of highly motivated reasoning that Rootclaim applied, and neither of the judges bought it, for the same reason. The CGG analysis is just wrong, etc.
They're not equally unlikely. You haven't provided any actual evidence for this claim.
Also, why on Earth would we just take the ratio of distances or areas as the probability factor? That's not how pandemics work.
ICUs were overwhelmed because Covid spread so much. Its hospitalization rate is a few percent and its fatality rate is 1% or so. This is in contrast to diseases like SARS 1 (9.5% fatality rate) or MERS (34% fatality rate). Sure, it's not mild compared to seasonal flu, but it is much more mild than the obvious things you would compare it to.
The second thing would be surprising as if the virus can so often jump to humans from animals it will happen closer to its origin in Laos.
Spillover events probably did happen elsewhere, but not all spillover events lead to a pandemic, and covid is usually so mild that it's not surprising we can't find any such cases. (I also don't know if some final important mutation didn't happen until much closer to the actual pandemic start).
Alternative explanation is following: as the market is one of the most crowded place in the city
This is discussed in the Rootclaim debate. There are many different types of places which served as superspreader events early on, the evidence we have shows the growth rate in the market as the same outside of it, and overall growth didn't seem to slow down when they closed the market.
If we assume that a worker of WIH was infected at work, this will be completely unspectacular until he started infecting other people. Such person can commute all around the city including to CDC near wet market.
This is also addressed. It would be a fantastic coincidence--much stronger than the one you posited at the start of this thread--if the only place they brought the disease was one of only a handful of other places in the city that a pandemic could actually start. Like, if all the early cases clustered around the WIV, and I said that a HSM worker could have brought it to the lab, would anyone take that seriously?
This, by the way, is exactly the kind of thing that annoys me and which is one of the main issues I made this thread to address. If you make enough favorable assumptions, you can make any hypothesis look good. This is clearly not the best explanation for the available evidence. Merely because you have successfully epicycled your way into a version of the theory which is not obviously impossible doesn't mean anyone has any reason to think it is even remotely likely. Your arguments aren't even consistent, as you seem surprised that there were no spillovers between Wuhan and Laos, but then don't seem at all skeptical of the idea that a sick person would commute all over the city and only bring it to 1 place.
I mean, I could point out that the first non-Wuhan case was in Beijing on December 17th (I think, going off memory here) and that someone could have gotten sick in a different city, and then just hopped on a train and immediately went to the HSM, and the WIV isn't relevant at all. Is this story convincing? Is there any evidence to support it? Does it feel like I am engaging in truth-seeking, or just throwing shit at a wall and seeing what sticks so I can prop up my pet theory?
What would the disjunctive fallacy be? Failing to account for the fact that P(A or B) >= P(A) and P(B)?
At one point Miller gave a likelihood against LL by a factor of 1e20 or 1e25, I think during the second debate, on genetic evidence. I don't think he intended this number to be an actual Bayes factor, but rather to show how easy it is to get a big BF by multiplying many small numbers together (see also https://arbital.com/p/multiple_stage_fallacy/).
I would like to see what Roko has to say about my post, so now I'm very curious how this works. Is this saying that you get rate-limited if you have at least 7 people downvoting you in the past 20 comments, regardless of how many people upvote you or how many times those 7 people vote? Also, does this count both overall and agreement karma?
What facility? WIV and HSM are at least 6 miles apart as the crow flies, with a big river between that forces anyone traveling from one to the other to go even further than that.
To override this we need some mental equlibristics (I think of meme here but I don't want to be rude)
No, you just need stronger evidence. 1/20 isn't that strong, especially for a complex situation with a high number of possible parameters to check.
To make sure I understand your point... the "Bayes Factors" I give like 1/ 1 million aren't meant to be taken literally. Rather they're to show how easy it is to get a high BF in this case, if you do a very quick analysis that doesn't account for details. I don't expect this post, on its own, to convince anyone of the zoonotic origin hypothesis.
I would describe that as dismissing counter-evidence out of hand; it's trivially easy to answer the question as stated, even if you don't believe that particular story. In any event, this seems like arguing over semantics. I think that accusing someone of a being responsible for several million deaths requires quite strong evidence, and that a pretty key component of presenting strong evidence is seriously addressing counter-arguments and counter-evidence. None of Roko's posts do that.
[It seems to me like you're arguing he's making procedural errors instead of just combing to the wrong conclusion / using the wrong numbers, and so I'm focusing on that as the more important point.
Sure. For example, he's making the exact procedural error you describe in your footnote, by failing to consider how likely the genetic evidence is under the lab leak hypothesis, or if any other cities would look suspicious as the starting location of a pandemic, etc. He's failing to apply consistent levels of skepticism to sources. But the biggest issue, in my mind, is still just not giving the question the level of consideration it requires. (I'm drafting an actual post so more detailed object-level arguments can go there when I'm done).
This is what numbers are for. Is "1000-1" a lot? Is it tremendous? Who cares about fuzzy words when the number 1000 is right there. (I happen to think 1000-1 is a lot but is not tremendous.)
I'm not sure what the point of arguing about the definition of "tremendous" is. If I had written "a lot" instead of "a tremendous amount" would anything substantial change?
I don't think that's counts as tremendous certainty.
"Brute Force Manufactured consensus is hiding the Crime of the Century (emphasis mine). Although the post contains the statement "I believe" it doesn't really express any other reservations, qualifiers, or uncertainty. It doesn't present or consider any evidence for the alternatives.
this is really not a tremendous amount either.
It certainly seems like it's supposed to a lot:
For the love of Bayes! How many times do you have to rerun history for a naturally occurring virus to randomly appear outside the lab that's studying it at the exact time they are studying it?
If it's not a lot of evidence, then taking this post at face value, what would one conclude is the probability that covid came from a lab? edit: And if it's not a lot of evidence, is it ok to accuse someone of mass murder with that amount of evidence?
I think we should treat them as being roughly equally terrible.
Well I think this is pretty wild, but that's beside the point, as this isn't what the post actually says:
prosecute what I believe is the crime of the century: a group of scientists who I believe committed the equivalent of a modern holocaust (either deliberately or accidentally) are going to get away with it. For those who are not aware, the death toll of Covid-19 is estimated at between 19 million and 35 million.
It would also be very strange for the post to have a bunch of content which is clearly supposed to be evidence that Covid was, in fact, a lab leak, and not just evidence that Peter Daszak tried to bury evidence if the point is simply that hiding evidence is bad.
What the social consensus is and why it exists are not relevant to the point I was making. This post is accusing specific individuals of mass murder, claiming they are responsible for millions of deaths. If you just want to say that you don't believe the expert consensus, that's one thing, but that just leaves you in a state of uncertainty. This post expresses a tremendous amount of certainty, and the mere fact that debate was stifled cannot possibly demonstrate that the stifled side is actually correct.
I think it's plausible--perhaps even likely--that the FBI, Secret Service, and various other agencies may have messed up the investigation in to the JFK assassination as well as acted or even colluded with each other to hide their own incompetence at protecting the president and during the aforementioned initial investigation. But this doesn't mean they were the ones who assassinated him!
There is a large amount of material that is publicly available to be analyzed that might weigh on the question of Covid's origins, as well as many arguments one could make. The Rootclaim debate covers much of it, but I'm sure not all. These data could be evaluated. Roko has not done that; the arguments and evidence here and in their other threads is extremely weak compared to the level of confidence that is expressed, or the level of confidence that would be required to level these accusations. Roko has clearly spent a lot of time making this post, his other 2 posts, various comments, and obnoxious comments on the Manifold thread about who would win the rootclaim debate, and has apparently done at least some research to support his claims. But when it's pointed out that his grasp of the facts is lacking, his response is to say "pay me $200 an hour." This is such obviously motivated reasoning that it is frankly an embarrassment for this post to have over 200 net upvotes.
I think the right strategy is to assume guilt in the presence of a coverup, because then someone who is genuinely uncertain as to whether or not they caused the issue is incentivized to cooperate with investigations instead of obstruct them.
This might have strategic usefulness, but that doesn't mean it's accurate. There are reasons why this video exists, one of which is because people don't always behave rationally in situations like this.
That is, even if further investigation shows that COVID did not originate from WIV, I still think it's a colossal crime to have dismissed the possibility of a lab leak and have fudged the evidence (or, at the very least, conflicted the investigations).
It was terrible, and likely backfired, but that isn't "the crime of the century" being referenced, that would be the millions of dead people.
This is the kind of thing you do before you make a big post accusing someone of "the crime of the century." I don't know how you even thought this was remotely reasonable. This is basically just Pascal's mugging, except that the worst you can do is harm the reputation of the community... "pay me or I might make really bad posts."
Ok. I don't think that Roko necessarily thought of the situation that way; rather, I thought if it as a way to contextualize what a 1:1000 probability of a natural bat coronavirus pandemic starting in Wuhan meant.
Your first comment seemed to take the position that the OP's number was not merely different from yours, but indefensible, and you gave a lower bound for a defensible prior that was 1.4x higher than the number you were complaining about.
Are you claiming the timing argument is so weak that no reasonable person could possibly estimate its Bayes factor as >1.4? I don't feel like you've come close to justifying a claim like that.
Roko gave a fairly high-level argument that didn't dive too much into the details. I don't believe it is possible for such an argument to reasonably give a probability of "at most 1/1000" that we see what he described with no lab leak. The location and type of disease make a great deal of sense for zoonosis and the timing factor is quite complicated--simply putting a uniform distribution over 80 years is not remotely valid.
It might be possible, with detailed argument and actual data, to come to the conclusion that the level of evidence from these factors gives a Bayes Factor of 1000 or more in favor of lab leak. I don't think it's likely, but it is at least complicated enough that I won't say for sure it's impossible.
I have no idea! What's your 90% CI for how long it would take them, and what evidence are you relying on for that?
I don't know. What I do know is that many relevant experts are skeptical that Covid could have been "created" in a lab, or if possible, think that it would have taken a very long time, and this does not seem to have changed from this old reddit post: https://www.reddit.com/r/science/comments/gk6y95/covid19_did_not_come_from_the_wuhan_institute_of/fqpc7c8/ to the recent Rootclaim debate. It would be theoretically possible that the WIV figured a bunch of things out that no one else knew, and kept them secret, but this of course has to be argued for and put a probability on before you can use it to generate any Bayes Factor at all. It's the responsibility of the person saying that the timing provides strong evidence to demonstrate that.
I previously thought you were claiming "the unconditional probability of a naturally-occurring pandemic to be a bat coronavirus is ~1". This claim differs from that in several ways. Thank you for clarifying!
Making the probability conditional on location of origin: Absolutely fair, we already accounted for the improbability of the location. I missed this.
Sorry for not being clearer on this. I can't remember if I emphasized this above, but I don't think the pieces of evidence that Roko mentions in this post are independent, so A) actually analyzing them is kind of hard, and B) you can't just multiply the numbers together.
What's your probability if we change that to "are currently performing gain-of-function research on it"?
I have no idea, probably pretty low. But that's because we don't actually know that the WIV is performing "gain of function research" or how closely related the viruses it worked on were to Covid. The closest viruses that we know the WIV had samples of are still thousands of mutations away. The only evidence in the post for what research might have been happening is the rejected grant proposal from 2018; it's not actually clear if WIV did GOF research. See e.g. https://www.factcheck.org/2021/05/the-wuhan-lab-and-the-gain-of-function-disagreement/
(Arguably some genetic features of the virus lean toward lab leak, but this is highly debatable and would require substantial analysis to put any sort of number on; Roko barely mentions them, and I discussed the one thing that he does mention above).
The other thing to keep in mind, which I haven't brought up yet, is that Wuhan is not the only place one could generate a similar lab-leak hypothesis for. Although it is home to one of only 2 BSL-4 labs in China (as far we know, at any rate), virology labs are spread across China, and over the course of the last several years, many of them have been asserted to potentially be related to the lab leak as well. One you start speculating that labs might be doing things that they haven't made public, then you can consider the possibility that any lab anywhere might be involved. WIV might be one of the stronger coincidences, but it's certainly not the only one. Doubly so when we have to speculate on what research they might have done and what viruses they might have had, as I mentioned above; if you can assert that the WIV could have been doing things that we don't know about, well, you could say the same of any lab. And when evaluating evidence this way, you have to not only consider the exact set of facts you got, but all of the situations that you would evaluate similarly (sort of like how a p-value gives the probability of a result at least as extreme as the one you saw under the null). So while something like P(bat coronavirus starts in Wuhan) is at least some level of odd coincidence, a statement like
For the love of Bayes! How many times do you have to rerun history for a naturally occurring virus to randomly appear outside the lab that's studying it at the exact time they are studying it?
taken literally, the probability might actually be close to one! I haven't done a thorough review of what every virology lab in China and Southeast Asia is doing, but this is obviously a very large factor that is not considered at all when generating the "1:1000 against" claim.
This is a period of about 2 years out of the entire 1920-2020 hundred-year window. Now, we could probably discount that hundred year window down to say an equivalent of 40 years as people have become more mobile and more numerous in China over the past 100 years, on average.
I did see this, but didn't find it convincing. China has become substantially more urban, more interconnected, more populous, and more connected to the outside world even over the past 10 or 20 years. A claim like this requires substantially more thorough analysis. And, again, is it reasonable to start researching and make COVID in the ~2 year time window given? Like suppose covid started 1 month after this moratorium was lifted, would we just say the probability is 2/1920?
You appear to have more knowledge of virology than I do, but this is far too implausible for me to believe it merely because you declared it. I've heard of many plagues that were not bat coronaviruses. Your prior on the next naturally-occurring pandemic being a bat coronavirus cannot plausibly be ~100% unless you know some hitherto-unmentioned information that would be very startling to me.
I think that whatever the next pandemic out of Southern or Central China or Southeast Asia is, the WIV (or some other lab in the region) is extremely likely to have a sample of a related virus and studied it. Sars-Cov-2, as the name might imply, is closely related to the Sars-Cov-1 1 pandemic of 20 years ago; as far as I know, the original reservoir animal of neither virus has been conclusively identified, although bats are the most obvious candidate.
Scientists have been identifying this region, specifically wet markets, as a likely source of viral pandemics, particularly from bat coronaviruses, for years. This is the exact region of the world they come from. I'm not an expert on virology, but the exact market in Wuhan where the first cases all cluster was identified as a likely place for a pandemic to start in 2014: https://www.nytimes.com/2022/03/23/health/wuhan-pandemic-edward-holmes.html
I'm somewhat surprised that you're so skeptical of this; I don't think anyone was ever in doubt that bat coronaviruses spilling into humans in Southeast Asia this part of China has been considered a likely problem for a long time.
"What kind of disease" has Bayes Factor 1. It's exactly the kind of disease that has caused pandemics in the same region of the world within the past 20 years, and which comes from the kind of wild animal trade that has been known to be happening in Wuhan for years. I discussed this in the very next paragraph.
The timing is given by such a weak argument that I did ignore it, yes. WIV has been studying bat coronaviruses for years, and probably will continue to do so for years, and the only thing to tie it so closely in time is a rejected grant proposal that emphasized having the actual work done at UNC.
Actually, I think timing is actually evidence against the relevance of the grant proposal. I don't think they could have done anything like creating Covid (which, based on everything I've heard, would have required vastly new and different techniques from what existed in 2018, and which is several thousand mutations away from the nearest known natural virus) in a year and a half.
... and we're supposed to believe that this is a coincidence? For the love of Bayes! How many times do you have to rerun history for a naturally occurring virus to randomly appear outside the lab that's studying it at the exact time they are studying it? I think it's at least 1000:1 against.
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,
Ordinary people who haven't spent years of their lives thinking about rationality and epistemology don't form beliefs by impartially tallying up evidence like a Bayesian reasoner.
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.
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.
"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).