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Omicron Variant Post #1: We’re F***ed, It’s Never Over

It is pronounced identically to the adjective "new".

Omicron Variant Post #1: We’re F***ed, It’s Never Over

I give the WHO kudos for picking omicron instead of nu. (Actually, I'm pretty shocked that they did something this common-sensical, and notice that I am surprised.) I spent Friday morning (= Thursday evening, US time) talking out loud with colleagues about the new nu variant and after like two attempts to clarify what the f--- I actually meant, multiple people independently joked that it was so bad we should just skip nu and go to omicron.

If you've only ever discussed it in text, you're underestimating how bad it is to use "nu" as an adjective in verbal conversation.

Omicron Variant Post #1: We’re F***ed, It’s Never Over

Both were sent to the hospital but it is unclear whether this was part of a standard procedure or if they were ill enough to need to go.

Testing positive was sufficient to get them sent to the hospital, and they had mandatory PCR testing every ~3 days; this is no evidence about their symptoms.

(I recently went through HK arrival quarantine -- in the same hotel, no less -- and researched the operating procedure runbook out of personal interest.)

Covid 11/18: Paxlovid Remains Illegal

I think I was unclear. I meant that if you did correctly estimate the number of cases, you'd need mamy times that many courses of medicine "in the system" to make sure that no one worried about running out in their part of the system, so that no one started hoarding where they were. I estimated that about ten times as many cases as you natively needed would about do it.

If our standard is non-scarcity for prophylactic prescription for close contacts, then 10x the expected number of close contacts in your "part of the system"...

(To be clear, this is just a statement about hoarding/availability dynamics, not about when "things should go back to normal".)

A Bayesian Aggregation Paradox

Right, I agree that for the update aggregation is better than (but still lossy). And the thing that affects is the weighting in the average -- so if then the s don't matter! (which is a possible answer to your question of "how much aggregation/disaggregation can you do?")

But yeah if is very different from then I don't think there's any way around it, because the effective could be one or the other depending on what the are.

A Bayesian Aggregation Paradox

The framing of this issue that makes the most sense to me is " is a function of ".

When I look at it this way, I disagree with the claim (in "Mennen's ABC example") that "[Bayesian updating] is not invariant when we aggregate outcomes" -- I think it's clearer to say the Bayesian updating is not well-defined when we aggregate outcomes.

Additionally, in "Interpreting Bayesian Networks", the framing seems to make it clearer that the problem is that you used  for  -- but they're not the same thing! In essence, you're taking the sum where you should be taking the average...

With this focus on (mis)calculating , the issue seems to me more like "a common error in applying Bayesian updates", rather than a fundamental paradox in Bayesian updating itself. I agree with the takeaway "be careful when grouping together outcomes of a variable" -- because grouping exposes one to committing this error -- but I'm not sure I'm seeing the thing that makes you describe it as unintuitive?

Covid 11/18: Paxlovid Remains Illegal

I would guess that having that many courses of Paxlovid "in the system" would be about an order of magnitude too low for true non-scarcity. (See: how many vaccine doses needed to be in the system before you could assume that there was going to be adequate supply anywhere you might try to look?)

Sci-Hub sued in India

What's the breakdown of fields by whether they have a pre-print server or not? (Which of the ones most important to human progress are in the good state?)

I'm most familiar with economics, where there's no server, but there's a universally-journal-respected right to publish the pre-print on your personal site, which ends up in the "it's free if you Google for it" equilibrium in practice.

Sci-Hub sued in India

Yeah, that all checks out from my publishing experiences with them. (I've co-authored one paper for an Elsevier journal and have another out for review with them.)

As I say in my reply to Viliam's comment nephew to yours: I'm confused by the OP's choice to present the profit margin figure so prominently in "Why does Sci-Hub exist?", not discuss the true objections about net-negative spending, and then choose comment guidelines that say "Aim to explain, not persuade". The margin is striking and persuasive, but (assuming they agree with your model of the world) it isn't the biggest issue with Elsevier!

I have no particular love in my heart for Elsevier here, but I do care about the common standards of how post-writers argue their claims on LessWrong. If the biggest problem here is actually how the other 63% gets spent, but focusing on that makes a less persuasive case to readers, then I'd at least hope that the author would tag it with something like "Actually, this 37% isn't my real problem with Elsevier; it's just the thing that I thought would be easiest to understand."

(I think your reply actually does an excellent job of this -- it lays out a single detailed example, tagged with the evidence you're basing it on, then you lay out the rest of your objections to Elsevier, tagged with an epistemic status.)

Sci-Hub sued in India

I see; that helps to make sense of the 37% figure, thanks!

Given that explanation, though, I'm confused by the OP's choice to present the 37% number in the segment "Why does Sci-Hub exist?". Given that the number as presented isn't their true objection, it feels like a fact being presented to persuade, rather than to inform. Given that the first comment guideline (in the set they chose to apply) is "Aim to explain, not persuade", I don't understand this choice?

(Again, I don't have any problem with the content of the post; I just wanted to register confusion about the choice of presentation.)

I'm similarly confused about choices in the form of your reply -- I would strongly expect that CEO salary explains less than 1% of the £1.6 billion figure, so I'm surprised that you would cite it first as an explanation of why the headline costs were not necessary expenses.

Similarly "I also find it implausible that it really costs billions a year to... keep a website, and coordinate by e-mail all the scientists that work for you for free." After the CEO line I was kind of on edge about being persuaded by emotionally-laden claims, so I checked Wikipedia for the number of employees at the company (8,100). Making the conservative assumption that they get paid $30k/yr, and estimating that they cost 175% of that fully loaded, that alone is £320 million, 20% of the cited costs. Maybe some of those 8,100 are in unnecessary divisions like bribery or suing Sci-Hub? (Again, as far as I'm concerned, they can all be fired out of a catapult as a lesson to the other publishers.)

One thing that I think could explain these choices is if you and the OP felt that it was justified to deploy arguments-as-soldiers in defense of Sci-Hub / against Elsevier, because the cause was just and the value of drawing additional allies to the side was worth it. Would you endorse that claim? Or am I off-base about what is happening here?

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