LessWrong developer, rationalist since the Overcoming Bias days. Connoisseur of jargon.
jimrandomh(Jim Babcock)
Karma: 17,374
I think the combination of the Rationality and Practical tags gets pretty close to what you want, but to get all the way there you also would add the Motivations tag. Ie
Epistemic Rationality = Rationality & !Practical & !Motivations
Instrumental Rationality = Practical | MotivationsI think the real reason we didn’t make Epistemic & Instrumental core tags was because when we tried tagging sample posts, too large a fraction of posts hit corner cases and failed to be well classified by the distinction.
It seems fairly normal to me for an emotionally charged movement to attract people for whom it’s difficult to tell whether they’re not-too-bright fanatics or agents provocateur.
This is a very good observation, and seems like a pretty big problem for such movements.
https://www.medrxiv.org/content/10.1101/2020.05.23.20111559v2
This paper (from June 27) collects studies published after this post, does meta-analysis, and corrects for some methodological problems like false negative rates, and gives a central estimate of the household secondary attack rate of 30%.
LessWrong developer here. Here’s an overview of what all those domains are. The code is open source, so you should be able to verify these, with some effort.
Algolia (algolia.net, algolianet.com) is a service we use for site search (what you get when you click the magnifying glass icon on the top-bar). They have a mirror of all searchable data (ie non-draft posts and comments, tag pages, user bios); they receive a copy of searches that are performed through the site search box, which they can associate with IP addresses but not with usernames.
Cloudflare is a CDN that is hosting components of MathJax, the Javascript library that renders LaTeX in posts and comments, and some libraries we use for integrating MathJax with the comment/post editors. The CDN URLs were defaults that came with libraries we’re using; we could probably move them to our own domain with a little effort. JsDelivr is hosting some things that similarly came with library defaults, as parts of MathJax3 and Algolia.
Cloudinary is an image-hosting CDN that we use for images in some posts and images that are part of the site UI.
dropbox.com and dropboxusercontent.com are hosting images that were used in posts, presumably because they were visible in the Recent Discussion section when you loaded the front page. Currently, when users insert images into posts, depending how they do it and which editor they’re using, it may point to the original domain of the image. Also, for authors we have set up automatic crossposting for, the crossposts will use the original image URLs. We will hopefully switch this to always upload those images to Cloudinary and host them there instead, partially for privacy reasons but mostly to prevent link rot in archives of old posts.
dl.drop is not a valid domain name; it’s either a broken image link in some post that was in Recent Discussion, or a typo in this post.
The Google domains are from Google Analytics, Google Tag Manager, Google Fonts, and ReCaptcha. Google Analytics and Google Tag Manager measure site traffic and aggregate usage patterns.
intercom.io is for the chat icon in the bottom-right corner, used for messaging the admins about the site.
lr-ingest.io is LogRocket. We (the devs) use it to see how the site is being used; we can watch anonymized replays of sessions (anonymized in that the username in the corner is edited out). As policy, we don’t read people’s direct messages or unpublished drafts, or deanonymize votes, though in principle we have the capability to (both with this tool or with direct database access).
TypeKit, aka Adobe Fonts, is a font library and font hosting service. We could probably consolidate this with one of the other CDNs being used, but font-hosting involves some user-agent-string based compatibility polyfills, which would be somewhat annoying to reproduce ourselves.
Twitter is an unusually angry place. One reason is that the length limit makes people favor punchiness over tact. A less well-known reason is that in addition to notifying you when people like your own tweets, it gives a lot of notifications for people liking replies to you. So if someone replies to disagree, you will get a slow drip of reminders, which will make you feel indignant.
LessWrong is a relatively calm place, because we do the opposite: under default settings, we batch upvote/karma-change notifications together to only one notification per day, to avoid encouraging obsessive-refresh spirals.
Despite the justness of their cause, the protests are bad. They will kill at least thousands, possibly as many as hundreds of thousands, through COVID-19 spread. Many more will be crippled. The deaths will be disproportionately among dark-skinned people, because of the association between disease severity and vitamin D deficiency.
Up to this point, R was about 1; not good enough to win, but good enough that one more upgrade in public health strategy would do it. I wasn’t optimistic, but I held out hope that my home city, Berkeley, might become a green zone.
Masks help, and being outdoors helps. They do not help nearly enough.
George Floyd was murdered on May 25. Most protesters protest on weekends; the first weekend after that was May 30-31. Due to ~5-day incubation plus reporting delays, we don’t yet know how many were infected during that first weekend of protests; we’ll get that number over the next 72 hours or so.
We are now in the second weekend of protests, meaning that anyone who got infected at the first protest is now close to peak infectivity. People who protested last weekend will be superspreaders this weekend; the jump in cases we see over the next 72 hours will be about *the square root* of the number of cases that the protests will generate.
Here’s the COVID-19 case count dashboard for Alameda County and for Berkeley. I predict a 72 hours from now, Berkeley’s case-count will be 170 (50% CI 125-200; 90% CI 115-500).
(Crossposted on Facebook; abridgeposted on Twitter.)
If I sometimes write down a 6-nines confidence number because I’m sleepy, then this affects your posterior probability after hearing that I wrote down a 6-nines confidence number, but doesn’t reduce the validity of 6-nines confidence numbers that I write down when I’m alert. The 6-nines confidence number is inside an argument, while your posterior is outside the argument.
Six nines of reliability sounds like a lot, and it’s more than is usually achieved in criminal cases, but it’s hardly insurmountable. You just need to be confident enough that, given one million similar cases, you would make only one mistake. A combination of recorded video and DNA evidence, with reasonably good validation of the video chain of custody and of the DNA evidence-processing lab’s procedures, would probably clear this bar.
As a diabetic, I have a few things (insulin infusion canula, continuous glucose monitor) that attach to skin with adhesive. In principle, you could use medical tape around the edges of a normal mask, and it would improve the seal. I think the reason people don’t do this is because it’s a lot of effort to put on (effort which could be spent improving the fit in other ways), and it’s physically painful to take off. This limits its usefulness to the range where an imperfectly-fitted N95 isn’t good enough, but a positive-pressure suite isn’t necessary; I’m not sure situations in that range are at all common.
Thanks; I have fixed the link.
Responding to this news article which is responding to Bornstein et al on the subject of diabetes as a complication of COVID-19 infection.
The paper is primarily about management of COVID19 in patients with existing diabetes, rather than the risk of new-onset diabetes as a result of COVID infection, so it’s on shakier ground than you might expect given the news article. The relevant arguments given are: (1) pancreatic beta cells express ACE2 in a mouse model, (2) SARS1 was known to directly damage pancreatic beta cells, and (3) Italian physicians anecdotally report a high rate of DKA in new-onset COVID19 patients (no percentage or citation).
This is strong enough to convince me that this is a thing that happens, for at least a non-negligible (but not necessarily large) subset of the patients who are admitted to ICU.
Some background for people less familiar with diabetes. Pancreatic beta cells produce insulin, which is a hormone that signals to the rest of the body that they should eat the sugar that’s in the blood. Under normal circumstances, this keeps blood sugar within a narrow range (70-110mg/dL). However, if the pancreas is damaged or if the pancreatic-function-to-body-size ratio is too low, it can’t produce enough insulin, so blood sugar rises higher than it’s supposed to. Very high blood sugar is toxic to pancreatic beta cells themselves, causing a feedback loop which leads to a state called diabetic ketoacidosis (DKA), which is reliably fatal if left untreated.
For SARS1, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7088164/ says:
Twenty of the 39 followed-up patients were diabetic during hospitalization. After 3 years, only two of these patients had diabetes.
Unfortunately the paper didn’t say how many of those patients had gotten as far as DKA, as opposed to developing diabetes short of DKA in a hospital setting and having it treated promptly. I haven’t verified this yet, but my prior belief was that anyone who enters DKA is probably going to be diabetic forever.
This is all separate from the question of whether there’s a lasting risk of diabetes in patients who were not hospitalized, or who survived their hospitalization without obvious blood sugar complications. This is a hard question; it seems plausible, but we don’t yet have empirical evidence either way. My guess is probably some increased risk, but not a very large one, and decreasing over time.
I have a suspicion that some of these seizures are not actually being done by the federal government, but actually are straightforward robberies where the thieves lie about their identity.
Yes, I think That Alien Message should have the AI Alignment tag. (In general, if older posts don’t have tags, it mostly means no one has considered yet whether the tag should be applied.)
These are adorable.
If she does decide to post to LessWrong, the reception will probably be better if it’s an Open Thread comment or in the Shortform section, than if it’s a top-level post.
This is definitely an improvement over the US CDC and Shenzhen papers, but I still have reservations about it. The first issue is that it’s based on calling people and asking about symptoms, not based on testing. So it doesn’t count asymptomatic people, nor people with mild symptoms who don’t disclose them. The second issue is that their numbers imply an average household size of 6.4, which implies a definition of “household” which is somehow not as expected.
They track contacts of the first 30 identified cases of COVID-19 in South Korea, and find 119 household contacts, of which 9 are infected. Table 2 describes every transmission they found, and whether it was a household transmission. Of the first 30 cases, 8 of them got it by household transmission from someone else who was also one of the first 30 cases, so that’s 22 distinct households.
(30 people + (119 contacts − 8 already counted)) / 22 households = 141⁄22 = 6.4 people per household.
Genetic engineering is ruled out, but gain-of-function research isn’t.
First, a clarification: whether SARS-CoV-2 was laboratory-constructed or manipulated is a separate question from whether it escaped from a lab. The main reason a lab would be working with SARS-like coronavirus is to test drugs against it in preparation for a possible future outbreak from a zoonotic source; those experiments would involve culturing it, but not manipulating it.
But also: If it had been the subject of gain-of-function research, this probably wouldn’t be detectable. The example I’m most familiar with, the controversial 2012 US A/H5N1 gain of function study, used a method which would not have left any genetic evidence of manipulation.
That’s overstating it. They’re the only BSL-4 lab. Whether BSL-3 labs were allowed to deal with this class of virus, is something that someone should research.
I agree that this is technically correct, but the prior for “escaped specifically from a lab in Wuhan” is also probably ~100 times lower than the prior for “escaped from any biolab in China”
I don’t think this is true. The Wuhan Institute of Virology is the only biolab in China with a BSL-4 certification, and therefore is probably the only biolab in China which could legally have been studying this class of virus. While the BSL-3 Chinese Institute of Virology in Beijing studied SARS in the past and had laboratory escapes, I expect all of that research to have been shut down or moved, given the history, and I expect a review of Chinese publications will not find any studies involving live virus testing outside of WIV. While the existence of one or two more labs in China studying SARS would not be super surprising, the existence of 100 would be extremely surprising, and would be a major scandal in itself.
One hypothesis is that the excess mysterious deaths are happening in people who “recovered” from COVID-19, who were then finished off by a comorbidity or other health problem.
Another possibility is that these are deaths from malnutrition. We do have reports of extremely large increases in unemployment and long lines at food banks. First-world malnutrition deaths are pretty much never recorded as such, so this seems pretty likely to me.