8 Comments

Matthew, this kind of situation is one in which I struggle fatally.

I’m that rare kind of person who has TWO ‘ordinary’ school certificates in maths.

I didn’t enter the ‘ordinary’ exam twice.

I took the ‘ordinary’ exams aged 16yo & got an A grade,

At 18yo, I entered the ‘advanced’ exams & failed so badly that they awarded me only an ‘ordinary’ pass.

In other words, I’ve a good basic competence but quickly run out of competence and complexity increases.

Paradoxically I seem to get better at understanding, using & explaining complex systems problems, such as are common in biology, which often involve numerous poorly defined subsystems interacting with each other.

But on numeric problems such as are outlined here, I’d be in the easily-fooled group (providing there were no clues arising from the complex systems biology involvement, which wouldn’t give me clarity, but would signal that I didn’t understand it & would not accept it).

It’s my paradox 😎

It’s very important work you’re done here. I simply wasn’t aware how readily a bad actor can fool very many people, and similarly how easy it is that an incompetent yet honest person ends up misleading themselves as well as others.

Cheers!

Mike

Ps: thankfully there are honest competent & vigilant people around.

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Aug 3, 2021Liked by Mathew Crawford

Matthew - that is brilliant analysis for the Simpson paradox and opened my eyes to the manipulation of statistical data, in this case incorrectly aggregating the data from 1000 people from Hospital 2 classified as 500 ADV and 500 no ADV to Hospital 1 and Hospital 2 respectively and I didn’t quite see it at 1st read through and had to re-read it. To understand this manipulation you really need to be on top of your statistical and mathematical professional game and thanks for sharing this information as it has enlightened me to the fact. I‘ve seen statistical data being incorrectly manipulated in the past using incorrect proportionalities ie using incorrectly attributed denominators to yield the result the author was biased to report and it was in a respected medical journal site. It’s good to know you that you are critically reviewing of all these papers especially the WHO aggregation of data from many hospitals conducting HCQ trials.

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Jul 28, 2021Liked by Mathew Crawford

Thank you Mathew!

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Unfortunately, this has been going on in the scientific community for many, many decades. The more political the scientific subject, the higher the probability of scientific deceit. I've been fighting this personally, at great professional harm, for four decades. I am quite convinced that we (humans) are LONG past rectifying it.

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In a world of Lysenkos, be a Zelenko. Lest we forget, Dr. Zelenko was the one who boldly pioneered the use of HCQ from the get-go. May he rest in peace.

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“The generation of random numbers is too important to be left to chance.” –Robert Coveyou, not Covey

https://www.atomicheritage.org/profile/robert-coveyou

I make it a habit to try verify quotes, especially good ones that I’m unfamiliar with, like that one, regardless of the reliability of the source. (So many keep turning out to be erroneous in one way or another.) So I offer the above correction in the interest of fine tuning, and will welcome any feedback as to the accuracy of my source.

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Thanks Matthew. It is slow for me to comprehend this type of thing and I’ll have to reread it, but for now I get the gist of it.

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Bravo! IOW, RCTs (euphemism for blinded) are susceptible to "ballot harvesting". Secrecy doesn't work, or is at least highly problematic.

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