Proof of Lack of Fact Checking: A Farcebook Tale

The Information Wars Part VII

I rarely log into Facebook these days. I've spent nearly half this year banned from the platform for doing things like reporting on meetings I've been in with various doctors and scientists who don't fall in line with Pharmauthoritarianism. But I like to drop my articles there just to toss a life line to those who might benefit.

Two days ago, I posted my age-risk correction for Alex Berenson's article on all-cause mortality in the UK. At some point, the "fact checkers" swooped in, "reviewed the information" and proclaimed it "partly false".

I nearly ignored it and moved on, but the last part caught my eye...

Since my conclusion agreed that the vaccines were not the reason the vaccinated are dying at twice the rate of the unvaccinated, this tells me that the "fact checkers" made their pronouncement on my post...without reading my article!

It gets better…

I don't think I've had the opportunity to "See Fact-Check" before, so I almost didn't click that button-thing (yes, it turned out to be a button). In fact, I only clicked after starting to write this article and take visuals! But I'm glad that I did. The button opens up another article.

The author of the article, Dean Miller, is the Managing Editor at Lead Stories, which published the "fact-check".

In the article, he quotes a biostatistician (who likely clued him in to the phrase Simpson's paradox, so that he could type it up as if he was himself capable of doing the math to check Berenson's work against the word of the biostatistician to see who was right):

Professor Barbra Richardson, a biostatistician in the Vaccine and Infectious Disease Division of Fred Hutchinson Cancer Center in Seattle, said she saw the claim -- which she called "a huge misrepresentation" -- bouncing around on Twitter and that the problem with his analysis was obvious. In a November 23, 2021, email to Lead Stories, Richardson wrote:

... this is purely due to the fact that the age range of 10-59 is huge and younger people are less likely to be vaccinated AND less likely to die of any cause. Thus the data graphed of vaccinated consists of a much older age group than the data graphed of unvaccinated and older age = higher mortality.

It's the same phenomenon Lead Stories found in testing false claims about health statistics from Israel, which an anti-vaccine film maker similarly oversimplified in his claim COVID vaccines are not working.

In both cases, collapsing complex data into a simple chart demonstrates Simpson's Paradox, the name for a common statistical problem: a trend disappears or flips when multiple sets of data are combined, if you haven't accounted for a consequential variable that isn't captured in the data. In this case, what's not factored into the chart is the higher mortality rate of older people.

It is an interesting observation that Miller's judgment led him not just to a statistician, but a statistician working in the medical industry who might have a bias. On top of that, Barbra Richardson works in the Vaccine and Infectious Disease Division of Fred Hutchinson Cancer Center! Sure, such a bias doesn't mean she can't do the math, but if you have to reach out to a statistician in the first place, you're not a person who can check her math!

Perhaps we should call Mr. Miller "Dean of Exceptional Journalistic Ethics".

If all that isn't damning enough, Miller and Richardson make no effort to normalize the data (as I did) to show the actual relationship of all-cause mortality between the two groups. Or, if Richardson did, Miller ignored it, but I somehow doubt that Richardson would have offered up a complete analysis. I wonder why…

Do we call this...publication bias?

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Circling back to Facebook…

In summary, Facebook tagged my post as "partially false", linking to an article that states my exact reasoning...minus the actual math that demonstrates what the actual answer looks like! I can only conclude that nobody employed by or through Facebook read my article, or that the tag was placed there to bias my post and downgrade my reach and status.

If nobody read my article, then what happened?

I'm going to go out on a limb and suggest that the most likely explanation is that somebody took Berenson's graph, fed it to Facebook's censorship algorithm (what else should I call it?), and it picked up my post because it led with Berenson's graph.

I nearly edited my article when I realized it was thumbnailed with the same graph, but I'm glad I let it remain because this has been an interesting accident in exposing the censorship machinery of social media.