I have loathed Tim Walz since the covid panic. He embraced hersterical models, and used the excuse they were The Science to grab power.
Briefly, in May 2020, as you’ll see below, panic models predicted 25,000 (!) covid first wave deaths by July 2020 in Minnesota. I predicted about 800. My model, a simple extrapolation, was correct. The official The Science model stunk it up.
Walz said: “Modeling was never meant to provide a number. It was meant to show trend and direction, that if you social distance you buy more time.”
No. This is circular. The model was told to say social distancing would save lives. You cannot therefore say “The model shows us social distancing saves lives”, and conclude the model proves social distancing. All models only say what they are told to say. I made mine say “Do what previous epidemics did.”
Social distancing was pure hokum from the beginning. It was entirely made up. There was never any evidence for it. It was from a high-school girl’s science project. I kid you not (we document this in Price of Panic). Her science dad helped her turn it into a paper. And then it became gospel. But it was always made up.
Walz wanted control. So he used a BS excuse to grab power. Remember that. Below is my 13 May 2020 article on this, and the link to official data so you can compare model outputs is next. (I stripped off a joke about another hersterian, Eric Fing-Ding, or whatever, a person best forgotten.)
Check this site to confirm their models sucked yellow grease, whereas mine was pretty.
The original post, Models Only Say What They’re Told To Say, ran on 13 May 2020 (before I had Substack). I think this is the first time I used the phrase in a title. I later wrote a peer-reviewed (so you can’t argue with it) paper on the subject.
ORIGINAL POST
Here are the Minnesota daily deaths, with our naive model overlaid—-which are you free to ignore. As of Tuesday night, about 9 PM, there are 614 total reported deaths in Minnesota. Our naive model predicts 800 in total, assuming no second, third, fourth, fifth, and more waves.
You can see—forget our model—-that deaths if deaths are on the way down, they at least aren’t increasing, just as you’d expect in any typical outbreak. Weather is slowly improving in Minnesota, as it sometimes does.
Here’s what the article says: “An updated model from the University of Minnesota and state’s health department is predicting that COVID-19 cases will peak in late-July with 25,000 deaths possible — if the stay-at-home order is extended until the end of May.”
Twenty-five thousand more deaths even if the stay-at-home “order”—memorize the word—is obeyed. Even if.
In Scenario 5 [one of several model scenarios], the stay-at-home order is extended for all until the end of May. With that happening, the model predicts that the COVID-19 peak will happen on July 27, with the top intensive care units (ICU) demand being 4,000 and 25,000 possible deaths.
Another estimate, Scenario 4, predicts that if the stay-at-home order is extended by a month into mid-July, the peak would occur on July 13 with 3,700 as the top ICU demand and 22,000 possible deaths.
All right. Here’s what the great leader of that state said about models.
In previous briefings, Gov. Tim Walz has asked Minnesotans not to focus on specific numbers, but rather focus on when the peaks might occur.
“Modeling was never meant to provide a number,” Governor Walz said on Wednesday. “It was meant to show trend and direction, that if you social distance you buy more time.”
No!
Social distance working is an INPUT to the damned models. You can’t point to model output and say, “See? The model says social distancing works!”
No shit, you *&&^^&)**!
I have seen this mistake made so many times in this crisis that I am well on my way to a stroke.
The models reported on—just like Ferguson’s and everybody else’s—are built saying social distancing reduces death. This fact is an integral part of them. It’s not a “discovery” of the models, it is a condition in them. The models had to say social distancing worked because they started with the premise social distancing worked.
You cannot “discover” social distancing worked via any model. You had to have built in that possibility in the first place. You knew in advance that it worked because that’s what you told the model.
You cannot run the model, wait for the output, run to your boss and say “Look at this, chief! The latest model says social distancing works!” If your boss had any sense he would slap you and say, “Didn’t you write that code? And didn’t the code say somewhere that social distancing worked?” If there was any justice, you’d join the ranks of everybody else fired because of the panic and be forced to stand at the end of the bread line.
I don’t know how else to say this. I am obviously failing to make the point. I admit to being unable to make it so that it sticks.
Why doesn’t it stick? All I can figure is that the Deadly Sin of Reification strikes when people think about models, even their own. Excuse me: computer models.
A scientist creates a model, or a civilian looks at a model created by some smart person, and, somehow, the model takes on a life of its own. It becomes and replaces reality, this model, at least in part.
Since the model is now “reality”, we can look at it like we do Reality and pretend to come to an understanding of how the world works. The model’s workings take the place of Reality’s workings.
This is all wrong. Yes, a model can be so complex that if you push lever A, the “unexpected” result X is churned out. X is only “unexpected” because of limited intelligence of the model writer. Further, X can only come out because the model was built with that possibility. This must be so. If it wasn’t, then X would never come out!
Models do help simplify Reality. They do aid in thinking about how things work, what causes what. They clarify thought. But they never, not ever, say what they are not told to say. Not ever. Never.
(No, not even when you build in “randomness”. Every piece of every model does only what it is told, and nothing more.)
Learning what to tell models what outputs to make (given what inputs) is the real point of modeling; for that is when we can make skillful predictions. That is when we have a grasp of cause, or at least of correlation.
Yet I insist that you can never get out of a model what you do not put in. That means whoever built the models predicting insane numbers of dead bodies in Minnesota unless the stay-at-home “order” was obeyed knew what the outcome had to be in advance. In the sense they knew social distancing would lead to predictions of lower deaths. Even stronger, they must have been advocates for this position.
That, or they have no idea how models work. This means the modelers are incompetent or that they are true believers. Their only possible hope of proving competence is if Minnesotans start keeling over at magnificent rates.
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