Popping back on briefly to share some insights on media consumption, spread of conspiracy theories, & epistemelogical divides.
1) We had to be the ones to insist on conversation. People are afraid of conversation right now b/c they think it will turn into a fight & they don't want that w/ people they love. Meanwhile, the epistemological divides widen.
I ask this Q: "What do you think I think & why do you think I think that?"
Answer: "You're doing your best, but you're influenced by liberal news media that doesn't report the facts fairly."
They didn't have category for ability to bypass reporters & news outlets all together. They didn't understand I can factcheck by simply going to source's socials.
That's why they think I'm unduly influenced by liberal bias. B/c they have outsourced process of drawing conclusions, they believe I have as well.
1) What do you think I think?
2) Why do you think I think that?
3) How do you square that w/ everything else you know about me?
More from Society
global health policy in 2020 has centered around NPI's (non-pharmaceutical interventions) like distancing, masks, school closures
these have been sold as a way to stop infection as though this were science.
this was never true and that fact was known and knowable.
let's look.
above is the plot of social restriction and NPI vs total death per million. there is 0 R2. this means that the variables play no role in explaining one another.
we can see this same relationship between NPI and all cause deaths.
this is devastating to the case for NPI.
clearly, correlation is not proof of causality, but a total lack of correlation IS proof that there was no material causality.
barring massive and implausible coincidence, it's essentially impossible to cause something and not correlate to it, especially 51 times.
this would seem to pose some very serious questions for those claiming that lockdowns work, those basing policy upon them, and those claiming this is the side of science.
there is no science here nor any data. this is the febrile imaginings of discredited modelers.
this has been clear and obvious from all over the world since the beginning and had been proven so clearly by may that it's hard to imagine anyone who is actually conversant with the data still believing in these responses.
everyone got the same R
these have been sold as a way to stop infection as though this were science.
this was never true and that fact was known and knowable.
let's look.
above is the plot of social restriction and NPI vs total death per million. there is 0 R2. this means that the variables play no role in explaining one another.
we can see this same relationship between NPI and all cause deaths.
this is devastating to the case for NPI.
clearly, correlation is not proof of causality, but a total lack of correlation IS proof that there was no material causality.
barring massive and implausible coincidence, it's essentially impossible to cause something and not correlate to it, especially 51 times.
this would seem to pose some very serious questions for those claiming that lockdowns work, those basing policy upon them, and those claiming this is the side of science.
there is no science here nor any data. this is the febrile imaginings of discredited modelers.
this has been clear and obvious from all over the world since the beginning and had been proven so clearly by may that it's hard to imagine anyone who is actually conversant with the data still believing in these responses.
everyone got the same R
this methodology is a little complex, so let me explain what i did.
— el gato malo (@boriquagato) May 30, 2020
a few EU countries provide real day of death data. this lets us plot meaningful curves to show rate of disease change.
what struck me is how similar all the curves were.
everyone got the same shape. pic.twitter.com/bN0hILzoSl