This is the weekly visible open thread. In fact, it’s the two hundredth open thread! For historical reference, you can find Open Thread 1 here. Post about whatever you want. Also:
1: Thanks to the 600 (!) of you who sent in ACX grants applications. I’d complained earlier that there weren’t many good ones, but I was being impatient - now I have the opposite problem, way too many good ones to fund or evaluate easily. I’ll be sending out emails to those of you who offered to help fund or judge applications in a few days to a week, after I’ve come up with a strategy. Probably results will be announced towards the end of the window I committed to on the original post, so around Christmas time. Please bear with me during the inevitable snafus in trying to set this process up.
2: Commenters brought up even more examples of interesting families last week. For example, neuroscientist Oliver Sacks, Yes, Minister co-creator Jonathan Lynn, Israeli deputy PM Abba Eban, and econ Nobelist Robert Aumann are all cousins. Steve Jobs is the biological brother (adopted and raised apart) of award-winning novelist Mona Simpson, and their cousins (raised apart in Syria, never met) are famous pianist Malek Jandali and journalist Bassma Al-Jandaly. Paleogenetics founder Svante Paabo is the illegitimate son (raised apart) of Nobel-winning biochemist Sune Bergstrom. Add him alongside Bobby Fisher to the pile of illegitimate children raised apart from their talented parents who still become talented, I guess.
Staying on the subject of nature vs. nurture: Albert Einstein had two grandchildren who lived to adulthood: one biological, and one adopted. His biological grandchild Bernhard Einstein was an engineer who worked on laser technology for the Swiss Army and “obtained four U.S. patents related to light amplification”. His adopted grandchild Evelyn Einstein “worked briefly as an animal control officer, as a cult deprogrammer, and as a Berkeley, California, reserve police officer”
3: Comment of the week is Gwern on whether we should consider China “successful”:"
This was a big thing with the USSR too: they'd bury us in economic productivity with their stakhanovite New Soviet Men freed from the waste of capitalism (cf. that _Conquest of Bread_ review incidentally). Then it was with Japan, they'd surpass us with their unique Japan Inc. fusion of pseudo-democracy in which one party was always elected and worked hand-in-glove with the zaibatsus (or maybe South Korea, or another Asian Tiger). Then it was China... http://web.archive.org/web/20090302203414/http://web.mit.edu/krugman/www/myth.html You'll note all the countries in question are still below (sometimes vastly) US per capita.
The conclusion is more "the Industrial Revolution is a helluva drug", and can make any regime look good and get high on its own ideological supply about how it has restarted history and inaugurated the Caliphate or China Dream or Japan as #1 or whatever.
Noahpinion had a pretty similar point a few months ago, but it’s always good to get more reminders.
4: Dr. Bitterman, one of the researchers who came up with the ivermectin-effects-are-from-worms hypothesis, is defending his idea from some of the concerns you guys brought up in the comments. For example, in response to a comment that hyperinfection syndrome is rare, he writes:
This is simply not true. I've pointed out exactly why this isn't true in the past to you as well and yet you continue to repeat it. I'm not sure why. Anyway, this is just pure ignorance of the relative risk scale and just how few deaths can radically shift that reported scale. The entire difference of mortality effect is only 39 people among a control group of 1984 patients. Assuming a 15.5% prevalence (average prevalence by parasitologic methods of the trials driving the favorable effect), and even assuming a only 5% chance of getting disseminated strongyloids infection due to either immunosuppression (since less half of the patients in the only paper reporting semi-reporting prevalence Rzztmass likes to cite were immunosupprsssed from steroids) or eosinopenia associated with COVID (which happens even without steroids), that already explains ~15.5 deaths, which is already ~40% of the mortality benefit. That absolutely makes a dent. And even then I suspect this is a low estimate. Bottom line: you continue to not appreciate how small number absolute patient event differences can translate into large differences on a relative risk scale.
See the full comment there, and his other Reddit comments, for more. See also his Twitter. He also points out that the serological prevalence numbers I cited in one of my responses might not be accurate, since those include people with previous cases.
5: Alexandros Marinos, whose pro-ivermectin views I argued against in the same comments post, has finally started a Substack and written up those views at length. Among his interesting findings are that keeping all of the studies mentioned on ivmmeta, removing the ones I think are bad, removing the ones ivmmeta itself thinks are bad, and removing the ones that leading anti-ivermectin researcher Gideon Meyerowitz-Katz thinks are bad - all give about the same relative risk result (by ivmmeta’s methodology), somewhere around 0.3 or 0.4 (Marinos thinks that my and ivmmeta’s exclusions are similar around 0.3, and GMK’s exclusions are different around 0.4, but this seems like splitting hairs to me, since all three are overwhelmingly positive by these standards). I think this is an interesting finding about how (at least when critiquing ivmmeta) it’s probably not worth arguing over which studies to include or not, so much as about the overall methodology for how we interpret the studies remaining.
In terms of the more polemical points, I might or might not write a longer response later. Right now the point I think is most important is that Marinos sort of grants that many of the substances with many positive studies probably don’t work - but says ivermectin is different because it has more studies and stronger effects than the others. I think the stronger effects are a bit exaggerated - the graphic that Marinos presents shows it’s pretty similar to melatonin, anti-androgens, and a bunch of other things - but I will grant that it has significantly more studies.
But as I’ve tried to point out elsewhere, adding more studies can only address problems within your model, not problems outside your model. Suppose that some parapsychologist has done twenty studies, all of which prove psychic phenomena exist (and there are many such parapsychologists!) Does it help if she works for another year or two, and we get forty such studies? How about another decade, and we get two hundred such studies? Who cares?! We already know that this parapsychologist, using whatever methodology she uses, is able to consistently get positive results. It’s not like all twenty of her studies went badly just by coincidence! So either you should believe in psychic phenomena, or you should believe that this genre of study is bad (ie an outside-of-model problem) and we need some independent researcher or some better methodology to try replicating it.
When I see fifty studies mostly showing that ivermectin works, you have successfully convinced me that, if you did a thousand more studies of approximately this quality, they would also show that ivermectin works. But then who cares how many studies anti-androgens have relative to ivermectin?
I realize this looks bad - aren’t we supposed to use “replications” and “number of studies” as a proxy for truth? But this is why I point out that there are dozens of studies showing psychic phenomena are real, and hundreds of studies showing the same for homeopathy. I don’t think anyone has a great idea where to go from here (“larger and more professional studies” is a good guess, but people will understandably worry that just means the establishment wants to never have to admit it’s wrong and wants only establishment studies that it can bias to count). But “just do the same bad studies more and more times” sure isn’t the answer.
6: In the highlights to the comments on my Paxlovid post, I posted some people’s explanations for why the FDA’s behavior wasn’t so bad. Dan Elton still thinks it’s bad and has written a post on why he rejects the explanations.
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