It is a nervous tick. A "tell," as gamblers say.
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Apologies for straying off the CoVid main thread; I would just like to leave this here. It's, imho, the best summary of the current geopolitical situation that one could make in such a short allotted time.
https://twitter.com/RnaudBertrand/st...66227847888896
IPB
What they need to hear is “doing NLP will make you better at your job.” Citing outliers is counterproductive, because it engages the competitive spirit which deranged them. Everything from college admissions to Instagram has told them that if an outcome isn’t good enough to put on their resume (or reels), then they shouldn’t bother.
Forum Conversation: Norman Fenton
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Suppose that at a given time there is data available suggesting that, in the general population, one in a thousand asymptomatic people were likely to have the virus. Such data was never confirmed of course, the infection rate varied over time, but I will use it to explain the Bayesian reasoning.
If I take a PCR test and it’s positive but I’m not feeling ill, I would want to know if I really have the virus. In other words, if I am one — of the one-in-a-thousand people — who is asymptomatic but carrying the virus, I’d want to know the accuracy of the test. There weren’t any reliable studies about the reliability of the PCR test, but the public was assured these tests were very accurate. Let’s suppose there was only a one-in-a-hundred chance that someone who doesn't have the virus will test positive — a 1% false positive rate. Then conversely, if I don't have the virus, there's a 99% chance of a negative test. With this information most people assumed if you tested positive you almost certainly had COVID. But that is not the case.
Think about a group of 10,000 asymptomatic people getting tested. Because we are assuming one-in-a-thousand asymptomatic people have the virus, that means about 10 of the 10,000 really have the virus. Let’s also assume these genuinely infected people test positive. Then we are left with just under 10,000 people — 9990, who do not have the virus. But a PCR test with only a 1%false positive rate still means that about 100 of these people would falsely test positive. So in total there are 110 people testing positive of whom we know only 10 will actually become ill from the virus. So, the actual probability that you've got the virus if you test positive is closer to 10%. This means that with reasonable assumptions about the underlying infection rate and test accuracy, the PCR test used as a standard for life-impacting decisions and mandates, had a 99% inaccuracy rate for asymptomatic people testing positive.
Red meat is not a health risk. New study slams shoddy research - Big Think
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The IHME scientists had been observing the shoddy nature of health science for decades. Each year, hundreds of frankly lazy studies are published that simply attempt to find an observational link between some action — eating a food for example — and a health outcome, like death or disease. In the end, owing to sloppy methods, varying subject populations, and inconsistent statistical measures, everything, especially different foods, seems to be both associated and not associated with cancer. How is the lay public supposed to interpret this mess?
Also, I think the de facto assumption is that the genetic line of the best of us are going to evolve into aliens with big heads and pencil-thin bodies, representing relative usage. Like Spieldberg’s benign and magnanimous aliens in “A.I.”. (If that’s the cost of having spacecraft like theirs, I am tempted.)
Sounds like both parties backed FTX when it was brought up in congress:
"You're An Absolute Fraud": CME CEO Terry Duffy Recalls First Meeting Sam Bankman-Fried In March 2022 | ZeroHedge
I believed in Shaken Baby Syndrome until science showed I was wrong | Waney Squier | TEDxWandsworth - YouTubeQuote:
For decades, the medical community has viewed the symptoms and diagnosis of Shaken Baby Syndrome as an incontrovertible truth. Waney Squier spent many of these years offering expert testimony in court cases before new evidence convinced her to change her perspective. In this important talk, Waney explains her reasons for speaking out, argues a new case for Shaken Baby Syndrome and discusses the challenges she faced when she questioned the conventional way of thinking. Dr Waney Squier is a Consultant Neuropathologist to the Oxford Radcliffe Hospitals and Honorary Clinical lecturer at University of Oxford.
Her specialism is in the pathology of the developing brain in the foetus and neonate. Other areas of interest are developmental causes of epilepsy and muscle pathology.
Dr Squier has carried out extensive research into the nature and timing of brain damage due to intrauterine and perinatal insults. As a result of this research, Dr Squier has published widely in peer-reviewed journals, edited a book on developmental brain damage, and acted as a prosecution and defence expert witness in cases of unexpected infant death.
However, her court testimonies were shrouded in controversy after she began to question the research evidence and in 2001 changed her mind about the causes for ‘shaken baby’ cases.