The Science Virus, Part I: Orwellian Science
The Science Wars Part II
“The more the media peddled fear, the more the people lost the ability to believe in one another. For every new ill that befell them, the media created an explanation, and the explanation always had a face and a name. The people came to fear even their closest neighbors. At the level of the individual, the community, and the nation, people sought signs of others’ ill intentions; and everywhere they looked, they found them, for this is what looking does.” -Bernard Beckett
How do you characterize something that is unhealthy and spreads between hosts?
What happens when corrupt science goes viral? What is the impact of a fraudulent, or ill-considered result cited and re-cited in an expanding tree of scientific literature?
We're talking about Viral Absurdities—just not the cute or funny type. Can we rebuild our collective immune system?
Orwellian Science During the Pandemic
"Everything other than working was forbidden: walking in the streets, having fun, singing, dancing, getting together, everything was forbidden…" -George Orwell, 1984
Yesterday, a friend of mine who recently started work at Children's Health Defense sent out this message in a group chat:
Friends, I am collecting examples of published studies where the data presented does not match the author’s conclusions. I have a hunch that the academics that are doing the research know that the censorship net gets triggered by conclusive statements in the discussion. Please share your comments or examples with me at [redacted]@childrenshealthdefense.org.
What my friend is asking for is not likely a small pool of scientific studies. I've documented far too many of them, myself, and have more fodder, still. And the studies with oppositely stated conclusions might be categorized as just a subset of "Orwellian Science" science during the pandemic. Frustratingly, such research can infect future bodies of research, not to mention the public consciousness. It might even be appropriate to wonder if this kind of "false reality generation" has been scaffolding for a Matrix that we've long been living in that doesn't even need silicon chips and neural interfaces to operate. Why go to the trouble to build a neural plugin when Prussianesque obedience schooling and television do most of the work, already?
Crowdsourcing and Documenting
Let's crowdsource this one. I know my medical and science peeps got it going on.
For those of you who do not yet see the importance of the Campfire Wiki, now is the time to understand it a little better. This is the wedge we're driving between the real world and the Matrix. And if we do not document it, then not enough people will understand it or believe it. After all, beliefs, including mine and yours, are fundamentally driven by prior biases. It takes deliberate effort to change that. Not everyone has the time to read thousands of scientific papers and learn how to read them in order to understand the problem. But if we lay it out for them, they might.
Even our most brilliant leaders in this battle, like Dr. Peter McCullough, do not have the time to know everything (that would be asking far too much). I saw this during his Joe Rogan interview when he talked about the propagation of understanding of the hydroxychloroquine story during the early days of the pandemic without knowledge of what appears to look like a broad conspiracy of silence in media never to talk about hydroxychloroquine prior to Trump's discussion of the drug on March 19, 2020. That organized silence set up the Asch conformity experiment in which Trump plays the role of anti-confidant for many.
The reason I could write that story is that after months of gathering hundreds of pages of stories, evidence, and citations, I recognized the elements of the story upon organizing all of what I had documented. Seeing all the articles in the early timeline together, I thought to check Google results in the appropriate date range and BOOM: the bigger picture became obvious.
What happens when we have dozens of stories like that? The bigger picture will become clearer to a greater proportion of the public, and it may even help with lawsuits. And if you were not listening to the disaster that were today's oral arguments in front of the Supreme Court, you need to know that they need all the help they can get. Not every legal team is as resourceful as Robert F. Kennedy's, but more to the point—no person or even group of several dozen people is enough to put all the arguments and data together.
Yes, you can be that help. The way that you do so is to email OperationUpliftTeam@gmail.com and participate. There are numerous projects going on there at any one time that range from data analysis, article writing, wiki building (vaccine manufacturer Monica Hughes has been with us for months now, Joomi Kim works on some of the wiki pages, and I saw Jessica Rose edit the wiki the other day), media production, and work on technological solutions [to an array of problems]. Other great minds are currently introducing themselves to these projects, but there are a tremendous number of bright and motivated people like you doing the work, whether or not you know their names.
Why sit on all those articles and papers shared in your email circle when you could participate in documenting them in an organized way? It takes a little longer per source, but if spending twice the time on a source means wikifying it into the big picture perspective for potentially millions of people, that's a gigantic win. And if you don't know how to document in the wiki, there are dozens of team members in our chat channels who can personally guide you.
I'm also calling on the other Stackers to participate, now. We need you. If nothing else, you can appropriately insert your articles as citations into related articles so that the bigger picture comes together for all of us. If that isn't the best and most natural form of advertisement for your work, I don't know what could be.
It's time to win the battle Orwell warned us about. The ScienceTM has gone too far.
Hi, Matt! You asked for examples of studies in which the data doesn't match the conclusions.
Well, there's none larger than the Women's Health Initiative. A multi-year billion-dollar study to try to prove that the low-fat diet reduces heart disease. Tim Noakes drills down in detail into exactly how the authors deliberately manipulated and misrepresented the data, or simply ignored it, to publish conclusions that were in direct contradiction to their actual clinical data.
Paper: https://openheart.bmj.com/content/8/2/e001680
Video: https://www.youtube.com/watch?v=n-wjEnsEXI0
(where I first saw this)
The video presentation is beautifully done and you hear more about the back story -- especially that he knows and has worked with some of these people.
This is off topic but.., In my world of criminal law here's what happens: Decision based on precedent X, which is based upon earlier case Y. All cases now follow X. But dig back and go the precedent case Y and find that it relied upon case A. Go to Case A and it didn't actually say what Y says. Bu no matter, X confirms the predetermined decision the court wanted to make. And lo and behold, that is the law.