...a system like Canvas can generate activity even when a user is not at the keyboard, so long as one is still logged in.
More generally, Canvas activity logs were never designed to be used for forensic analysis and cannot be trusted for such purposes.
In one of the stupidest quotes I've ever read from a university administrator, @GeiselMed dean Duane Compton admits that these data generated numerous false positives—and has the gall to suggest that this means the system is working.
It's interesting to look back on the things that I got wrong over the course of the COVID pandemic, and to understand why.
I think I got a fair bit right as well—perhaps most notably in being the first to point out the problems in the IHME model...
...and in arguing early-on about the futility of a natural herd immunity strategy.
But let's look at what I got wrong, roughly in order, and why. In almost every case my mistake was in anchoring too strongly on influenza.
1. Early on I was skeptical that R0 was >3 instead of <2.
This was anchoring on flu directly, and also in looking at the epidemic curve. You can't tell from the epidemic curve whether you have higher R0 and longer generation interval, or lower R0 and shorter generation interval.
In light of the recent paper claiming to provide "initial evidence for bullshit ability as an honest signal of intelligence", I think it's useful to talk a bit about what a signal is, as compared to cue.
Let's start with Grice's distinction between natural and non-natural meaning, in his 1957 paper entitled simply "Meaning".
"Storm clouds mean rain" involves what Grice calls natural meaning.
This is a naturally arising correlation that an observer can use to learn about unobserved features or predict future happenings. No intent is involved; storms clouds don't form to tell us about impending rain.
This matters because (1) with fewer open restaurants, we expect an increased demand on the remaining venues, and (2) there is a selection effect here in that being included in the sample is correlated with having done well during the pandemic (instead of going out of business).
Maybe more importantly, the same article looks at overall traffic including walk-ins, as opposed to just reservations.
This has not recovered even given the caveats above.
Imagine a colleague came to you with a purported explanation for fighting ability among territorial vertebrates.
“Over the eons,” he claims, “the ability to kick ass has been selected because it is an honest signal of the ability to kick ass.”
I hope it would be transparent to you that an honest signalling story is unnecessary here. The ability to kick is ass is selected because one can then kick the asses of those whose asses need kicking, and no signaling is needed.
(To explain a bit more, the people ranking BBQ joints in Seattle are not the same people ranking them in Brownsville, TX. These data tell us that Seattlites are nice when they rank things and/or have low standards for BBQ, not that we are a contender on the national stage.)
I now really want to see the rankings for best pizza, using the same absurd metric.
Before anyone panics, note (1) the selection bias arising because this is exampled picked out of the various outbreak case reports as being "worrisome", (2) the small sample size, and (3) these numbers still give you a point estimate of 84% effectiveness against infection.
In a bit more detail: As small case clusters arise and are reported worldwide, we expect to see a distribution of effectiveness estimates. Some will have more vaccinated cases by chance, some fewer. The smaller the clusters, the wider the distribution.
Singling out a small cluster that yields a low effectiveness estimate for some variant of concern—and ignoring all the other data on that variant of concern everywhere else in the world—is reckless, and, odds are, misleading.
“`Nobody said you can do that, holding up their bones for the camera. That’s not how we process our dead. This is beyond words. The anthropology professor is holding the bones of a 14-year-old girl whose mother is still alive and grieving,' Michael Africa Jr said."
Since people are still on about that headline: my problem with it is that it suggests the lazy "arcana" narrative about a piece of obscure math that turned out to be useful, whereas the article does a nice job of explaining Bayes's rule as a foundational piece of probability.
The real key to me is to whom the word "obscure" is intended to refer. No one would refer to the mRNA in an mRNA vaccine as "an obscure alternative form of genetic material", even though most readers (pre-2021) would not know the term.
Yes, because it's common knowledge that a multiple murderer fleeing the cops and likely facing the death penalty in Texas will take every possible precaution to avoid injuring members of the general public.
Citizens in Wisconsin this afternoon should feel similarly secure in the knowledge that their mass shooter on the loose is not a threat either.
Thirteen year old boy: threat.
Handcuffed detainee: threat.
Unarmed 90 pound grandmother: threat.
Former police marksman accused of child sex abuse, on the lam after murdering three: no risk to the general community.
2. For 20 years now, commercial publishers have been aggressively attacking preprint culture as risky and unreliable, while claiming that only formal publication can provide a trusted, authenticated version of record (VOR).
3. Industry mouthpiece @scholarlykitchn has been banging away at this theme since its inception. Just this week, we read that:
1. Thread: Proactive testing in a partially vaccinated population.
I will start with a disclosure. The work described was done in collaboration with @Color Health and I was paid as a consultant for my efforts. I have no financial stake in COVID tests, treatments, or vaccines.
2. Large-scale proactive testing has been an important COVID control measure, because it identifies those who are presymptomatic, asymptomatic, or paucisymptomatic and allows them to self-isolate.
As vaccination becomes widespread, two questions arise:
3. First, at what level of vaccine coverage is proactive testing no longer necessary?
Second, as we transition to this point, what are best practices for tapering off testing efforts?