This is beyond outrageous behavior by @dartmouth's @GeiselMed school.

Without warning students, they used activity logs from Canvas, an online course management system not intended for forensic use, to dragnet for cheating on exams.

The problem is...

nytimes.com/2021/05/09/tec…
...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. Image
No, dean Compton, that you accused 17 students of cheating based on a system you knew was generating false positives indicates that you lack the empathy and compassion to fulfill your job duties.

Even if dismissed, such accusations are devastating, and all the more so for URMs.
I have a heck of a lot more to say, but you (and anyone else interested) might start by reading about the problems even with software that has been designed for forensic use. Jumping in mid-thread:

Imagine initiating a life-altering medical procedure based on readout from an evaluative instrument that was never designed for individual diagnosis, and which has unknown sensitivity and specificity—that would be medical malpractice.

That's what you just did, @GeiselMed.
I'm still reeling from the notion that exonerating many false accused people proves that they system is working.

How can anyone be that fucking stupid? Image

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More from @CT_Bergstrom

31 May
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.
Read 9 tweets
31 May
Online exam proctoring software is bullshit.

Instructors, don't use it.

Students, if you're been forced to use Proctorio or other academic spyware, consider contacting the dean of students or dean of undergraduate education at your college.

newyorker.com/tech/annals-of…
The article above is so horrifying that it's hard to know what to pick out to highlight.

By no means the worst part of the article, but if your clients don't know how to use the bullshit software you pushed on them and cause active harm, that's on you, not on them.
Early in the pandemic I wrote a long thread about the harms these kinds of programs cause.

It's a bit tl;dr, but I'd encourage instructors and students to explore the problems with academic spyware in more detail:

Read 4 tweets
24 May
This is your weekly reminder that "up to" means something different than "at least".

BMPCs were sampled 7-8 months after infection and remained present at that time. This sets a lower bound, not an upper bound, on persistence.
Here's a simple cheat sheet.
Indeed this very paper sampled a subset of the patients again at 11 months, and found the BMPC levels stable in almost all of them, providing direct evidence of persistence beyond 7 months.
Read 4 tweets
22 May
No, this paper doesn't show that COVID antibodies are lost within a year.

The title could certainly be better, because it does provide a misleading impression if you don't read any further.

medrxiv.org/content/10.110… Image
If you look at the text, though, you'll see that the "up to" is not meant to set 12 months as an upper bound to persistence; it's the period of observation. Image
Most importantly, let's the look at the data they present. Antibody titers are substantial after 12 months, and there is some suggestion that they may be stabilizing. Image
Read 5 tweets
20 May
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".

Compare:

"Storm clouds mean rain."

and

"The symbol ♂ means male".

(Here I loosely follow my paper with @KevinZollman et al sciencedirect.com/science/articl…)
"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.
Read 23 tweets
19 May
Changing denominators are a bear.

This is a comparison of reservation occupancy at the places open and taking reservations currently, to their pre-pandemic occupancies.

It doesn’t tell anything like the whole story. The places that went out of business are not counted.
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.
Read 4 tweets

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