Alex Berenson and James Suriowiecki Fail the Clown Veracity Test

Clowns of the Plandemonium, Part 1

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Alex and James are very serious intellectuals. They have pictures and claims to back that up.

Alex, a Yale graduate, previously spent time trying to make his fortune writing spy novels, found fame being the journalist with the ability to get invited on network television to say, "Public health measures too much. Dumb." At least partially, this was due to the fact that most people who could get invited on network televisions would have lost their jobs for stating the obvious. Jobs that pay more than writing spy novels that most of us know about only if we read his Wikipedia page. 

I never paid all that much attention to Alex Berenson. I suppose I was slightly tickled that a mainstreamer pushed back against some small fraction of plandemonium, but he didn't say or point out much of anything that I wasn't getting from friend circles. But I was appreciative that he turned me on to Substack, which turned out to be the best source of news and analysis during the plandemonium, a certain amount of thin Kirchian-noise and Robert Malone's long-winded, self-lionizing articles notwithstanding.

I did once have to correct Alex's work when he stumbled over a Simpson's paradox, which might be most easily described as a data illusion that sometimes occurs in top line data due to the weights of subgroups that comprise the data.

https://roundingtheearth.substack.com/p/uk-data-shows-no-all-cause-mortality

I was polite about it, and after a brief email exchange with Alex, he showed no interest in discussing data with me, and I settled into ignoring his articles since there are better sources of analysis put together by more curious people interested in learning about their errors and misunderstandings.

Notice that Alex links his readers to not me, but to Steve Kirsch and Bret Weinstein. I suspect that this is a form of directing traffic within an approved clown bubble. Neither of those guys do any serious data analysis or share my arguments. In particular, they're both overcommitted to the "escape variant" hypothesis pushed by former Gates-sphere employee Geert VandenBossche whose analysis of the Omicron hypothesis seemed primarily to be inaudible barks and growls.

Earlier this week, it was pointed out to me that Alex was discussing the military health data (from DMED).

Here is the publication linked by Berenson.

Alex got a little ratioed, but not nearly so much as he deserved. Relating the downward trend in military hospitalizations over the past…decade…to [lack of problems with] vaccination rather than the more obvious variables of [absence of] war and bringing troops home to safety seems like a rookie mistake in the world of variable analysis. But that's journalism, I guess.

At some point, you'd think a journalist making all these errors would want to couple with a competent data mind to accomplish more serious investigation, if that were the goal.

I commented to share one of my more important observations from studying the DMED data:

I shared this chart in the next tweet:

I created this chart using two DMED queries to produce the rate/ratio, and it may be the single most important chart produced during the plandemonium because it clearly shows "COVID" getting worse both after the vaccine rollout, and heading into the August 2021 mandates. Were it not for the fact that heavy hitters in the Medical Freedom Movement (MFM) actively isolated and ignored me after sinking hundreds of pro bono hours into an honest analysis [that didn't fit the shock narrative sold in mockumentaries like Died Suddenly], this chart would likely be a top line item in every debate over the vaccines. Think about that (and send it to your skeptical friends).

You won't believe what happened next! Alex ignored the conversation.

He tweeted a sort of non-response, later, but I'll come back to that.

I did however get responses from a rando anon calling himself "the Real Truther" and also NYT best-selling author James Surowiecki, who made similar [and incorrect] claims about the broader data.

I shared with James the international correlations graph I produced in late 2021 showing that more vaccination correlated with more [COVID] disease and death among all the world's nations.

The argument James is making goes like this, "What appears to be vaccine harms that resulted in a relative severity spike among young people only is actually the result of variant X."

Blaming all bad things on the variant of the day (or "variant of concern" henceforth VoC) is a great way to sweep vaccine-associated harms under the rug. It's also starkly scientifically illiterate. The scientific approach is to test which variable might be the cause by viewing all available data before making a best subjective judgment as to which variable resulted in the dose response.

But the VoC is a concocted variable. Such variables have a history in pseudoscience. A little over a decade ago, Cornell University parapsychology researcher Daryl Bem published claims (Bem, 2011) that his series of experiments demonstrated precognition, a sort of psychic ability. Under one of my pseudonyms, I gladly took part online in dismantling the nonsense. One of those experiments involved subjecting participants to pornography, to see if that spurred the ability to "see into the future," or something like that. Stephen Colbert was happy to give it some attention and oddly favorable laughs,

New Scientist‘s initial story about the paper was among the most widely read articles we published online last year. Bem ended up a minor celebrity, being interviewed on Comedy Central TV’s The Colbert Report – where host Stephen Colbert homed in on experiments into “time-travelling porn”, in which volunteers seemed to anticipate the position where erotic images would appear on a computer screen.

Frivolity aside, confirmation of Bem’s findings would turn established ideas about time, cause and effect on their head. “We openly admit that the reported findings conflict with our own beliefs about causality and that we find them extremely puzzling,” the Journal of Personality and Social Psychology‘s editors said in an accompanying comment.

Suspiciously, the paper, which challenges notions of causality, was accepted on its face value, and without replication, to a serious journal, which then did not want to publish failed replication efforts.

One of the [very] many problems with the paper, if I recall what I read all those years ago, is that Bem first ran the experiment testing precognitive stimulus to pornography, and the result was confirmation of the null hypothesis. Then he ran the experiment again. And again. And again. Voila, p-value achieved!

What Bem did was to "jack up the severity of the porn" repeatedly until a desirable p-value was achieved. But this presupposes the impact of the variable. The p-value should not have been judged from only the final trial series against a standard distribution, and a p-value that viewed all the trials together, and on a curve that assumes variable impact, should also have been included in the analysis—as the primary p-value. But there are infinitely many p-values that can be computed for any experiment, and most of them are entirely meaningless.

That Bem's work took up the real time and resources of productive people should be viewed as something like criminal.

This brings us back to the VoC argument. The VoC is a variable assumed to have an impact as "severity" increases, though nobody ever bothers to qualify or quantify the variable.

There are many ways to model the supposed impact of COVID-19, but the most obvious one is the case fatality rate (CFR). And why CFR was most certainly overestimated at the outset of the declared-pandemic when only the sickest were tested for COVID. However, you can notice that the only upward bump in CFR was during vaccine rollout. This is part of how I estimated vaccine mortality the first time in early August 2021. That's another analysis that is weirdly underpromoted in the MFM—particularly given that it perfectly predicted the German health insurer data, and is consistent with Denis Rancourt's analysis (and others).

Of course, this doesn't settle the question of whether a VoC caused the CFR bump, though the "porn variant" proposition seems…tenuous. Should we also test whether the colors of sweaters sold each season correlates with mortality data? Find enough variables, and some are going to be associated with exceptional p-values, just by chance. And that's why singular p-values without associated mechanisms or prior testing histories are stupidly meaningless.

What makes the VoC porn variant less than compelling is the lack of associated mechanism or prior history. The argument James makes is simply, "It was [must have been] more virulent." Okay, so what gene caused that? And how? Or better yet, can we identify a single infectious disease that suddenly became more harmful only to young people, but nobody else?

The expected response, not that James made it, is something like, "Escape variants bad," but since the child vaccine schedule includes several thousand vaccines (did I count that correctly?), we should have other examples to point to. I've asked for those examples numerous times over the past couple of years, but nobody has yet delivered one. I can only conclude that the VoC porn variant argument is as nonsensical as it sounds.

The only other data that I've seen that might support the "VoC porn variant did in the library with the candlestick" hypothesis is the clearly refuted Society of Actuaries analysis, which is consistent with the DMED hospitalization chart, if nothing else:

But the breakdown of COVID vs. non-COVID deaths in young people shows that the majority of the excess among young people was non-COVID deaths! That's even after we ignore the nonsense of PCR-positivity as confirmation of COVID. These deaths were [sadly] at least partially the result of an increase in opioid fatalities and suicides.

There is no evidence that young, healthy people were ever at serious risk of death or hospitalization from COVID, and the "VoC porn variant" hypothesis pushed by James and others is probably just irresponsible noise.

"But Mathew, it's not irresponsible to hypothesize."

True. But it is irresponsible to promote ignoring a highly plausible variable (vaccine injury) in favor of a variable that stands out as just as ahistorical as "sweater dye-color trend analysis on mortality subgroups." And understand that in my mild sparring with James, I shared with him a small sample of the thousands of graphs my wife and I have produced. This includes some of the healthy user bias (health/wealth/education bias) correlations I previously published. I goaded him a bit to see if I could provoke an honest meeting of the minds.

But understand that I invited James and Alex to a simple conversation of the data, so that we could talk it through. I'm open to being wrong, but I have a mountain of data of differing granularities, and I'd like to be able to hear how these guys justify their arguments against the broader set of data. This is how serious data analysis is usually done—among curious minds batting around models and interpretations. Neither of them showed up.

While we sparred a bit, I made it clear that my strong preference was to have a calm, civil conversation as I did with Stuart Buck, who disagreed with the notion that hydroxychloroquine was effective in preventing or treating COVID (whether or not x-percent of those cases were really other respiratory illness). But if they tried to pull a Debunk the Funk, and BS the conversation, I would have been happy to posterize them.

Here is the broadcast of my talking alone through some of the data. Sorry about the audio switch. I was juggling inputs to multiple platforms, so you may have to adjust volume after ten minutes or so.

https://rumble.com/v47d4an-why-berenson-and-surowiecki-trip-over-data-illusions-of-vaccine-effectivene.html

Over a thousand people were in and out of the Twitter space that ran all day, but spent several hours devoted to the conversation about the data that neither Alex nor James were willing to attend, in addition to the thousand or so people who have watched the Rumble video. Much thanks to WogPoG for hosting. Neither Alex nor James were willing to talk about the data, or defend their opinions. This is another failed Gorski Challenge. In their honor, I'm devoting a portion of the Big Picture Plandemonium graph (perpetually under construction) to them and their ilk.

https://embed.kumu.io/65414d83f8e8e125e045e4ab3e40204e