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Hello and welcome back to Rounding the Earth.

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And today I have the pleasure to introduce my friend, author, physician, engineer, Dr.

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Madaba Setti, who has been with Children's Health Defense and recently started a substack

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known as an insult to intuition.

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And he has gone on a kind of an interesting adventure today that we'll talk about.

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Welcome Dr. Setti, how are you?

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Hi Matthew.

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Yeah, I'm well.

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Good to see you.

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Always great to talk to you.

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So recently you went on, you called it Into the Belly of the Beast, and I'm sure that

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there are going to be a lot of people who want to know what the krill smells like.

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So, tell, you know, where was this adventure that you went on?

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It was the World Vaccine Congress, the 23rd meeting of them, and it was in Washington,

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D.C., April 3rd through the 7th.

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And my trip down there was funded by Children's Health Defense, and I went with another physician,

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pediatrician, Elizabeth Mumper.

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And we were sent down there just to smell around, like you said, what does the krill

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smell like down there?

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And it turned out to be a very, very interesting interaction because honestly, three years

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into this, nobody has been able to like look face to face with one of the movers and shakers

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on the inside and ask them a direct question.

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That hasn't happened.

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And suddenly we found ourselves in that opportunity and, you know, the responses were quite stunning.

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So while you're there, do people know that you're, in a sense, I don't want to say the

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opposition but not part of the inside, you know, asking these questions?

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Well, sadly, no.

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I don't have that kind of, you know, online personality or presence.

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I mean, people didn't know who I was for sure.

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And you know, that was an asset.

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And probably why I was sent down instead of someone like Merrill Nass or, you know, other

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physicians, physician colleagues that I know.

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So it was an opportunity to, you know, I don't want to call it infiltration, but it was in

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a way.

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It is a great way to understand.

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One of the ways I felt like I learned the most in life, and I realized this when I moved

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to Manhattan and right around the time I turned 21 years old, I got into the habit of maybe

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once a week, just sitting down at the bar of a restaurant to eat and just, you know,

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being willing to listen to anybody's story.

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You know, it's like you hear things that you would never otherwise hear.

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You're not adversarial.

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If you're just listening, if you're not judging.

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And suddenly you find out, you know, what something really looks like that you would

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have had no idea about that you may never have discovered.

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So what is the people, you know, talked about as they walked around this convention?

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It was, first of all, we have to understand who was there.

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There weren't a lot of physicians in clinical practice at the time.

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You know, there were physicians who became researchers, but mainly it was, you know,

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tech people, people who worked for the vaccine industry and their offshoots.

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There were all sorts of displays, exhibitions by, you know, companies who profited or earned

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their money from, you know, like vaccine trials.

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Like there was companies that recruited patients.

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There were companies that were, you know, making new technology like needles that would

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be absorbed.

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So you could, you know, tell your participants it wouldn't be a whole lot of injections.

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It was just like this tiny little thing and then it would dissolve.

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So all sorts of industries that branch off of the vaccine and big pharma industry.

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So these were tech people.

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And there were a lot of scientists, you know, like basic bench scientists there.

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So you know, to answer your question, what was it like, first of all, you walk in there

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and you realize that these people are pretty well funded.

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You know what I mean?

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This conference center probably cost several hundred thousand dollars a day and people

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were well-heeled.

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Not unexpectedly.

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This is what we were expecting, right?

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And it took a while to get comfortable because we realized, like this is, you know, what's

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really interesting is to be inside an area where you're pretty certain that 99% of the

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people there completely disagree with one of the biggest issues that you have.

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And you know, how do you open your mouth?

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Like what's the first thing you say to these people, right?

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Because you know where they stand.

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So that's what the people were like.

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But as the week progressed, I had more and more interactions with not necessarily the

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presenters but people in the audience.

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And you know, to just lay it out there, they are open to the idea that they could be wrong.

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And every single time I ask a question, and we can talk about that later, you know, people

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would come up to me afterwards and say, wow, that was a really good question.

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Why didn't they answer it?

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You know?

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So it's hopeful.

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Yeah.

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Pardon.

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It's good to hear that the number of people who are open-minded seems to be substantial,

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especially at an event like that, right?

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You wouldn't necessarily expect as much open-mindedness.

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But then again, I guess I don't know who the audience is, you know, who the crowd is.

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Is this is that media people in the audience?

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Is it is there partially like a sales job going on with this conference?

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What you know, who is there?

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Well beyond the people who are running the exhibits and the scientists, there were some

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media people there.

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You know, I wrote this piece on my sub stack just a few days ago and it got a lot of play

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and people have reached out to me saying that they tried to get in as a media person, but

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they were rejected.

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So there was undoubtedly media people there.

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And in fact, in one of the plenary sessions, there were spokespeople from MSNBC and the

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Scientific American and another, the Washington Post.

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These were like reporters that were on stage and talking about how difficult it was to

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get the story right.

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So there were obviously media people there, but it was like walking into you've probably

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been at a conference like this, a scientific meeting or a conference put on by an industry

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where everybody is, you know, looking to network as opposed to, you know, tell us what the

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latest trial data shows.

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That's not what they were there for.

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However, you know, the thing is, is that at each one of these round tables or presentations,

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there was an opportunity to ask questions and I took every opportunity to steer the

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discussion in a certain direction.

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And the entire symposium opened on a Tuesday.

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There was 3,100 people there and Gregory Poland, who maybe your viewers know is the head of

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vaccine research at the Mayo Clinic, chaired the opening and closing plenary sessions.

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And he's a very interesting character.

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He happens to be a pastor and the tone of, and he was sermonizing, honestly.

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I mean, like it was actually like walking into a place of worship retrospectively when

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I look at it because he was laying down, you know, what the tenets of the philosophy are,

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which were number one, millions of people have died of COVID.

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No, that's actually number one.

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The vaccines have saved millions and millions of lives.

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I'm not, I mean, these are actual statements that he made.

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The regulatory agencies like the FDA and the CDC have done a stellar job in making sure

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that these products made it to the public as soon as possible.

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And the biggest challenge we have now is the vaccine hesitant.

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And you know, he just dropped it all there.

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Like, okay.

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Right.

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So it's just a past all debate and just, you know, conclusion and push conclusions and

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repeat them.

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It feels like a tactic for mind control, essentially, like brainwashing.

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I've started actually calling this governance by aggressive nonsensical guruism.

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Government by nonsensical guruism.

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Yeah.

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Aggressive nonsensical guruism.

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Yeah.

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And I think that it has been shown to work effectively.

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I think that it is a technique that was studied and practiced over a period of years.

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I think that that is part of what, you know, all of this is and that there are probably

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people who have a sense of it, but just wouldn't know that that type of planning of messaging

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went on even.

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I agree.

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So one of the things that you mentioned is in your articles that there are calls for

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public private partnership.

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And I hear this messaging, right?

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I haven't looked too deeply into it myself.

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I've been focused on other things.

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But tell us what that sounded like or what does that represent?

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How do people explain public private partnership?

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Well, obviously in this forum, it was considered to be an amazing breakthrough.

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We're finally cooperating and this will allow us to move at a greater pace with their objectives.

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And to look at it more clearly, I would have to say if this was truly a free society, like

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a true democracy with a free press that held tyranny in check, that would be reasonable.

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What a good idea.

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But we don't have that, right?

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I mean, we all know that that's not what's going on.

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And so this to me is just a euphemism for fascism.

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That's one way of looking at it.

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When you have that sort of partnership, you have government controlling industry and you

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have communism, you have industry controlling government and you have fascism.

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And both are totalitarian in the end.

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So they were hinting at that, but obviously people in attendance didn't see it that way

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at all.

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Yeah.

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Yeah.

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I guess I described fascism slightly differently.

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I don't know if it's necessarily the corporations have control of government, but I think public

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private partnership actually really does kind of strike at fascism better than any other

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phrase that I've heard.

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But when you say public and private, those words like individually, they sound so good,

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but it's not like chocolate and peanut butter.

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It's these things that aren't supposed to mix, almost by definition, they're not supposed

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to mix.

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But I've worried that there's something else going on, which is that the Department of

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Defense has been so intertwined with the pharmaceutical industry during the past three years.

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I'm going to say three years plus, because I think that there was a lot of work going

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on ahead of time.

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In fact, we know there was.

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But both industries, I think needed a dance partner.

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There's an article that I had found, I put it in multiple of my own articles, my sub

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stack over the past two years, but it showed that the rate of the return on investment

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of R&D in the pharmaceutical industry was hitting zero in 2020.

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That was the trajectory of ROI in the pharmaceutical industry.

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And I'm not sure what all reasons go into that.

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It may just be you get certain low hanging fruit.

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It may be that the more things have a treatment for them, the more you have to spend large

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amounts of money for illnesses that don't have many patients, perhaps.

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And of course, there's all the things that have gone on in the healthcare industry that

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just make it more expensive, insurance and malpractice suits and all those sorts of things.

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And I would say the pressure on doctors too.

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I think that medical school and residency is kind of its own mess, but jumping past

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that.

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The pharmaceutical industry really did look like it was in long-term trouble in a lot

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of ways.

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I find that astounding.

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I'm interested to know more about that.

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I would have never thought that that kind of industry was in, I don't want to say dire

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straights, but on a trajectory to zero.

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And it may be that the globalization hit certain parts of that industry also.

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When 90 something percent of antibiotic production gets shifted to China, for instance, it's

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hard to know exactly what effect those sorts of moves have.

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I don't know exactly how the industry is organized.

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So what does that do to Merck?

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What does that do to Pfizer?

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Don't know exactly, but there are a lot of factors involved.

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Generally profit goes hand in hand with new technology.

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New technology is the primary driver of localized profits on a time scale.

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On top of that, you have the DOD, and we've had sort of like decades of, let's call it

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domestic peace in the sense that we haven't really felt threatened.

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We don't have easy borders to invade.

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We have two giant oceans on our east and west and Canada to our north.

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And whatever people say on the news about migrants coming from the south being an invasion,

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it's not as if we fear an actual army coming over.

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It's a different kind of local problem or job struggle or competition or something.

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But it's not quite the same thing, but the DOD wants more and more money every year.

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And so if you have these two industries that both sort of have a need to have either a

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problem to solve or a villain to go after, right?

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I mean, DOD would rather have something like an invisible enemy than to actually go confront

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face to face Russia in a war or something like that.

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Nobody wants to open up nuclear cans.

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There's a lot of reasons why the DOD would be real happy with an invisible enemy.

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And so you have this possibility of a dance partner.

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I think people aren't stepping back and questioning that skeptically, but that's a place where

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fascism could grow even if it was not intended to be that way.

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You know what I mean?

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Well, I agree with everything you're saying, and you're opening up another incredible conversation

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to have about this.

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Obviously, the best friend to a military industrial complex person would be an enemy.

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The best friends to the pharmaceutical industry would be disease.

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And the best friends to a central banker would be the need for debt.

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I mean, let's be real here.

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That's kind of what's going on, right?

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I think we all should sort of understand.

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If we don't know it with 100% certainty, that's what I put my money on.

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And Matthew, I know that you're very, very reluctant to ever claim certainty.

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But that's what's going on.

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That's the way I'm living my life.

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That's the way I see it completely.

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And I don't know where to go from here.

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We could talk about a lot of different things.

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Yeah.

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And just to be clear, I do live as if I believe something with certainty, even when I put

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a probability on it.

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And you're right.

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I try not to claim certainty very often.

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Well, it's smart.

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It's smart not to claim certainty, honestly.

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I mean, one of the big struggles we have right now is our need for certainty.

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If both sides would just admit that they can't be sure, then we can actually have a conversation.

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And that's part of why it was interesting to go into this particular symposium to see

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how sure these people were about not only what they believed in, but about their whole

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lifeline of earnings, what they did for their careers.

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And they're not sure.

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I mean, the people on the stages were, but everyone else in the audience, I think they

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know.

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And I had a very interesting conversation with someone who approached one of our people

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on the ground who was handing out flyers outside of the symposium.

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And this person came up to one of our chapter members in Virginia who was handing out flyers

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and said, thank you for what you're doing.

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And by the way, half the people in there are not vaccinated.

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And I was able to track this person down and they were willing to have a conversation with

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me off the record.

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And I said, really?

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Is that really true?

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People in there didn't get the jab.

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And this person said, well, I was exaggerating.

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But there was a minority that was able to evade the vaccination campaign.

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But she said there was a...

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Is she talking about the press or the scientists and technology?

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They were an MD, PhD working for the industry.

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And what they said was that most of their colleagues realized that when they got the

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jab that they were going to be part of an experiment.

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And they were the guinea pigs, but they went along.

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And this person's position on it was that they were very certain that safety has not

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been demonstrated by their standards.

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They didn't go into all of the damage and the number of casualties that have arisen

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from this vaccine campaign.

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But when it comes to safety, they knew very well that these things have not been proven

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safe, which I thought was very enlightening.

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At some point, I stopped keeping track.

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Before my Substack really took off, when I had 800, 900 readers, I would watch each few

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names every day come in.

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And I would notice a lot of names with doctor at the front on their email address or this

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or that.

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So I just took the time every now and then to just Google who's this person, who's this

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person.

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So I was just curious, what sort of an audience am I getting?

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And one of the things that I realized was, oh, fully half of my first 900 or so readers

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were either physicians or professional scientists.

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That's encouraging.

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And it did feel encouraging.

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In fact, a lot of the feedback that I got seemed to be confirmed.

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I saw statistics at some point that showed that of each educational status, didn't finish

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high school, finished high school, got a bachelor's degree, got an advanced degree, PhDs are the

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most vaccine-hesitant class.

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The most vaccinated, though, are just the step below them, the people with bachelor's

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degrees.

295
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That's right.

296
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I went to college, and I can think through this problem, but wait.

297
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The PhDs are exactly the opposite.

298
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So what does that tell us?

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And I think it tells me that those are people who are most headfirst confronting these industries.

300
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They know how the sausage is made.

301
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They're more likely to think things through.

302
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And I think also they're more likely to keep their professional life and their private

303
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choices perhaps separate enough.

304
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They know the politics and the landscape.

305
00:22:12,600 --> 00:22:17,600
I don't know, and of course, you don't have to say anything, but I've had approximately

306
00:22:17,600 --> 00:22:24,860
eight conversations with people who either they or their child got a fake vaccine card.

307
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And half of those people were PhDs.

308
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That makes sense to me.

309
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It could be more than just knowing how the sausage is made.

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I would suggest that it has some bearing on what we just talked about with uncertainty.

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I would suggest that PhDs know the difference between believing and knowing.

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And the ones that don't have the higher education, I'm just generalizing, they've been believing

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their whole lives.

314
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One thing that I talk about a lot was in terms of knowing versus believing, which is I think

315
00:23:05,120 --> 00:23:11,200
a very important aspect of what's happening in our planet right now, is about a decade

316
00:23:11,200 --> 00:23:15,480
ago the National Science Foundation surveyed the American public.

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And one of the questions they asked was, do you think the sun goes around the earth or

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do you think the earth goes around the sun?

319
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And of course, embarrassingly, one out of four people in this country got it wrong.

320
00:23:25,400 --> 00:23:27,760
They think the sun goes around the earth.

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And the rest of us are like, oh my gosh, how could you not know this fact that we've established

322
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500 years ago?

323
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But if you ask the other 75%, how do they know?

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How do you know?

325
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And I would suggest that most people don't know.

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They believe.

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They just happen to believe the right things.

328
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But when it comes right down to it, it doesn't matter if it's 2023 or the year 1023, you

329
00:23:51,680 --> 00:23:54,920
can't go outside and look up at the sky and know what's going on.

330
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It is very, very difficult to tell.

331
00:23:57,360 --> 00:24:03,440
But the point here is once you understand how we've come to knowing that, now you actually

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00:24:03,440 --> 00:24:05,440
know you don't believe.

333
00:24:05,440 --> 00:24:10,080
And that's something that may be reserved for the people who really do serious investigation

334
00:24:10,080 --> 00:24:15,920
to things and realize that there is always uncertainty, especially with science, which

335
00:24:15,920 --> 00:24:23,240
makes this whole mandated vaccine thing even more egregious because we are violating some

336
00:24:23,240 --> 00:24:29,960
major, major standards of ethical medical practice when we cannot inform patients what

337
00:24:29,960 --> 00:24:31,680
is in the jab.

338
00:24:31,680 --> 00:24:33,220
There is no ingredient list.

339
00:24:33,220 --> 00:24:36,400
How can you possibly inform someone?

340
00:24:36,400 --> 00:24:42,240
So yeah, that's an interesting statistic about that.

341
00:24:42,240 --> 00:24:43,240
Yeah.

342
00:24:43,240 --> 00:24:49,040
In fact, that whole thing of not knowing why you know something, right, when you think

343
00:24:49,040 --> 00:24:52,760
you know something and not knowing why you know it, that's a lot of the reason I named

344
00:24:52,760 --> 00:24:57,560
this program and my substack, Routing the Earth, right?

345
00:24:57,560 --> 00:25:02,720
Because the fact that a flat earth movement could exist, which I personally think is probably

346
00:25:02,720 --> 00:25:07,440
some sort of like an intelligence study operation.

347
00:25:07,440 --> 00:25:08,440
Oh, absolutely.

348
00:25:08,440 --> 00:25:09,440
Right?

349
00:25:09,440 --> 00:25:15,360
And my gut feeling is we've seen several versions of it during this, you know, pandemonium.

350
00:25:15,360 --> 00:25:21,120
I personally think that the no virus people are something like that.

351
00:25:21,120 --> 00:25:26,760
In fact, I've met a person who admitted to me that in 2020 she organized those people

352
00:25:26,760 --> 00:25:29,520
in meetings to get on message together.

353
00:25:29,520 --> 00:25:37,520
And I know a close friend of hers that I have pretty good reason to believe is herself an

354
00:25:37,520 --> 00:25:38,520
agent.

355
00:25:38,520 --> 00:25:44,520
So, you know, when I see this, I think, you know, we're constantly being studied, but

356
00:25:44,520 --> 00:25:51,440
now we're being studied for massive event controls of memetic behavior.

357
00:25:51,440 --> 00:25:52,440
Right?

358
00:25:52,440 --> 00:26:02,240
And I'm curious like to know, you know, how much, you know, how much of that memetic behavior

359
00:26:02,240 --> 00:26:08,680
and how much of that sort of belief control is actually targeted at the people at the

360
00:26:08,680 --> 00:26:13,400
vaccine conference, like the people doing the technology who are involved in the science.

361
00:26:13,400 --> 00:26:14,400
Right?

362
00:26:14,400 --> 00:26:21,440
Like if you were to focus your, if you were to focus a lot of time and energy running

363
00:26:21,440 --> 00:26:27,480
something like psychological operations, would those be the people to target just constantly

364
00:26:27,480 --> 00:26:33,400
blast and making them, making them think that any question that they asked was sort of crazy?

365
00:26:33,400 --> 00:26:35,920
No, 100% Matthew.

366
00:26:35,920 --> 00:26:41,200
I, you know, that was my conclusion was that this, this kind of sermonizing was not meant

367
00:26:41,200 --> 00:26:42,840
for the vaccine hesitant.

368
00:26:42,840 --> 00:26:47,320
It was meant for the people there to make sure that they were in line and they weren't

369
00:26:47,320 --> 00:26:55,320
questioning what was going on primarily because, you know, you know, Gregory Poland, which

370
00:26:55,320 --> 00:26:58,920
is an interesting, let's go back to the first plenary session, for example, because Gregory

371
00:26:58,920 --> 00:27:05,160
Poland, this might be a good time to flash up who he is.

372
00:27:05,160 --> 00:27:12,280
He was the guy, he was the pastor and the head of vaccine research at the Mayo Clinic.

373
00:27:12,280 --> 00:27:18,880
But interestingly, a year ago, he came forward as being vaccine injured.

374
00:27:18,880 --> 00:27:29,600
And as he was talking about how amazingly safe and effective these vaccines were, I

375
00:27:29,600 --> 00:27:32,240
was under the impression that he had recovered.

376
00:27:32,240 --> 00:27:40,840
And what happened to him was after a second dose of an mRNA vaccine, he developed tinnitus

377
00:27:40,840 --> 00:27:45,960
and he described it at the time as extraordinarily bothersome.

378
00:27:45,960 --> 00:27:48,680
That's what he said a year ago.

379
00:27:48,680 --> 00:27:56,200
And he pulled together a couple of scientists, like a researcher and I think an ENT specialist

380
00:27:56,200 --> 00:28:02,560
to talk about, you know, what needs to be done and how certain they could be that this

381
00:28:02,560 --> 00:28:04,440
was a causative reaction.

382
00:28:04,440 --> 00:28:09,120
And to my understanding, he understood that it was absolutely from the vaccine.

383
00:28:09,120 --> 00:28:13,360
Nevertheless, he decided to get a booster.

384
00:28:13,360 --> 00:28:16,480
At the time it was the monovalent booster.

385
00:28:16,480 --> 00:28:24,200
And what he said was for 24 hours, the tinnitus, tinnitus, by the way, is ringing in ears.

386
00:28:24,200 --> 00:28:25,200
Yeah.

387
00:28:25,200 --> 00:28:30,640
I've actually been suffering from it lately for the first time in my life.

388
00:28:30,640 --> 00:28:33,880
So I know a little bit about this now.

389
00:28:33,880 --> 00:28:42,040
So yeah, it can be, you know, barely detected in your experience or it can be, as he says,

390
00:28:42,040 --> 00:28:43,120
extraordinarily bothersome.

391
00:28:43,120 --> 00:28:49,280
So in any case, he got the booster and it went away for 24 hours and then it returned

392
00:28:49,280 --> 00:28:51,760
at a higher pitch.

393
00:28:51,760 --> 00:28:56,120
And so it became a little less bothersome, is what he said.

394
00:28:56,120 --> 00:29:02,960
Anyway, at the end of the entire symposium, I approached him to, you know, see what was

395
00:29:02,960 --> 00:29:05,600
going on with him, whether or not he recovered.

396
00:29:05,600 --> 00:29:12,120
And he said, no, it's still it's disrupted his life, which, you know, which points to

397
00:29:12,120 --> 00:29:16,960
the hypocrisy of his initial statements.

398
00:29:16,960 --> 00:29:21,880
When he opened up the symposium, this is someone who is vaccine injured, telling everyone that

399
00:29:21,880 --> 00:29:26,000
this is the best thing since sliced bread.

400
00:29:26,000 --> 00:29:30,080
So that's where that's how it started.

401
00:29:30,080 --> 00:29:38,640
And anyway, in this particular session on stage was Peter Marks, who is the head of

402
00:29:38,640 --> 00:29:44,520
CBER at the FDA sits on the Verpack, a big voice in this.

403
00:29:44,520 --> 00:29:49,040
And he made some really interesting statements.

404
00:29:49,040 --> 00:29:57,800
And the first thing he said was that he has he's no longer interested.

405
00:29:57,800 --> 00:30:00,040
I wish I could quote him directly.

406
00:30:00,040 --> 00:30:08,320
I'm no longer interested in arguing with someone who believes that vaccines aren't safe.

407
00:30:08,320 --> 00:30:15,360
Now, you know, what to make of this, this is someone who's supposed to be on the regulatory

408
00:30:15,360 --> 00:30:17,600
board, right, to make sure they're safe.

409
00:30:17,600 --> 00:30:21,120
And he doesn't want to hear an argument from someone who has an opposing opinion.

410
00:30:21,120 --> 00:30:25,360
So I found that to be very disquieting, to say the least.

411
00:30:25,360 --> 00:30:30,760
Moreover, and here, let's be very clear, maybe he's sort of signaling to the crowd that,

412
00:30:30,760 --> 00:30:34,600
look, even I, Peter Marks, know that these things are safe.

413
00:30:34,600 --> 00:30:35,800
Let's be real.

414
00:30:35,800 --> 00:30:43,400
The other thing he mentioned was that he's given up on the idea of a sterilizing vaccine.

415
00:30:43,400 --> 00:30:47,200
He's like, that's it may be possible in the future, but against COVID, no way.

416
00:30:47,200 --> 00:30:49,200
He's not expecting that ever to happen.

417
00:30:49,200 --> 00:30:53,080
And by sterilizing, I'm talking about preventing infection and transmission.

418
00:30:53,080 --> 00:30:54,280
Right.

419
00:30:54,280 --> 00:30:59,720
And what he's saying is that all we need is something that can prevent symptoms or mitigate

420
00:30:59,720 --> 00:31:03,760
them, you know, essentially in medical therapy at this point.

421
00:31:03,760 --> 00:31:12,320
And he was flanked by someone from Moderna and J&J.

422
00:31:12,320 --> 00:31:18,360
And he was saying, look, what we want to do is be able to identify the strain that we

423
00:31:18,360 --> 00:31:21,760
want to target in June and deploy it in September.

424
00:31:21,760 --> 00:31:26,320
And this can be possible as long as manufacturing capacity is ready to go.

425
00:31:26,320 --> 00:31:31,680
And sure enough, the people in the industry nodded their head.

426
00:31:31,680 --> 00:31:34,120
Yeah, we're ready to go, Peter.

427
00:31:34,120 --> 00:31:36,600
Just tell us what to do and we're going to make it happen.

428
00:31:36,600 --> 00:31:44,200
And the point here is that 100-day turnaround leaves no room for actual testing on any scale

429
00:31:44,200 --> 00:31:47,040
whatsoever.

430
00:31:47,040 --> 00:31:57,340
We're basically looking to forgo all of the safety testing on human beings with the assumption

431
00:31:57,340 --> 00:32:00,820
that they've already tested the mRNA platform.

432
00:32:00,820 --> 00:32:02,080
It's been proven safe.

433
00:32:02,080 --> 00:32:06,480
And so all we need to do now is just, you know, give us the genetic sequence and we

434
00:32:06,480 --> 00:32:11,280
are going to throw them in vials and deploy them.

435
00:32:11,280 --> 00:32:15,560
You know, that reminds me, I think one of the reasons why I was skeptical of the vaccines

436
00:32:15,560 --> 00:32:21,920
from the start, aside from the fact that I caught on to the hydroxychloroquine story

437
00:32:21,920 --> 00:32:27,360
and I don't know if it was the very end of February onward, I started following Dr. Didier

438
00:32:27,360 --> 00:32:33,960
Riehl's work in France and kept track of from there, you know, all of the hydroxychloroquine

439
00:32:33,960 --> 00:32:39,680
statistics that I could find, that I could see just clear shenanigans going on around

440
00:32:39,680 --> 00:32:42,080
that topic.

441
00:32:42,080 --> 00:32:46,680
Aside from that, there were like two, three, for two, three years before the pandemic,

442
00:32:46,680 --> 00:32:50,760
I was hearing a disturbing amount of discussion about from scientists.

443
00:32:50,760 --> 00:32:54,880
Like I would go to, you know, conferences, weren't even necessarily like science conferences.

444
00:32:54,880 --> 00:33:02,560
I was at a cryptocurrency conference here in Dallas and I was in a discussion with a

445
00:33:02,560 --> 00:33:08,160
computer scientist and just for whatever reason, he steers the conversation into, you know,

446
00:33:08,160 --> 00:33:13,760
about how we need to learn how to become more competitive with China again and that, you

447
00:33:13,760 --> 00:33:20,160
know, we're going to have to, I can't remember the way that he put it, but we're going to

448
00:33:20,160 --> 00:33:26,320
have to like roll up our sleeves and do what they do and experiment on our own people.

449
00:33:26,320 --> 00:33:30,480
And I was just like, like, like, wow, where did that come from?

450
00:33:30,480 --> 00:33:34,680
Or you know, like, you know, can you say that so easily?

451
00:33:34,680 --> 00:33:41,720
You know, like it, but it confused and concerned me that I heard this not once, but numerous

452
00:33:41,720 --> 00:33:45,040
times in the three or four years, uh, leaving up to the pandemic.

453
00:33:45,040 --> 00:33:49,960
And I thought about that and I thought, you know, is somebody putting out messaging and

454
00:33:49,960 --> 00:33:54,360
giving people on message and just telling people, go around and make this part of your

455
00:33:54,360 --> 00:33:58,600
shtick just, you know, cocktail conversations, just throw it out there.

456
00:33:58,600 --> 00:34:02,200
You know, we're not going to be competitive with China if we don't experiment on our own

457
00:34:02,200 --> 00:34:03,200
people.

458
00:34:03,200 --> 00:34:04,800
Now that's a really good point, Matthew.

459
00:34:04,800 --> 00:34:07,640
I think you're onto something for sure.

460
00:34:07,640 --> 00:34:13,000
And these kinds of get togethers are where you would experiment with that, right?

461
00:34:13,000 --> 00:34:17,680
Because you're in a group of people that are more or less aligned and you are steering

462
00:34:17,680 --> 00:34:19,960
it towards that.

463
00:34:19,960 --> 00:34:21,440
And that's clearly what happened here too.

464
00:34:21,440 --> 00:34:26,720
I mean, over and over again, like we need public private partnerships and the stuff

465
00:34:26,720 --> 00:34:33,160
is safe and we need, we need to go after the vaccine hesitant, you know, as, as, as, as

466
00:34:33,160 --> 00:34:37,720
as, uh, urgently as possible.

467
00:34:37,720 --> 00:34:44,040
And um, you know, nothing like what you just mentioned there at the, at the crypto conference

468
00:34:44,040 --> 00:34:47,400
about experimentation, but I understand what you're saying completely.

469
00:34:47,400 --> 00:34:51,600
You know, you, you make that part of the, um, of the narrative and suddenly it gets

470
00:34:51,600 --> 00:34:53,440
accepted without question.

471
00:34:53,440 --> 00:34:59,240
Um, if enough people believe it, you know, yeah, I also met a man, um, uh, Brian Bishop,

472
00:34:59,240 --> 00:35:04,440
uh, in January at, uh, at a dinner that I held in Austin, Texas.

473
00:35:04,440 --> 00:35:11,120
And he claimed to have helped fund one of the mRNA vaccines secretly, uh, using Bitcoin.

474
00:35:11,120 --> 00:35:13,840
And I know that he is a wealthy individual.

475
00:35:13,840 --> 00:35:23,040
He helped, um, uh, he co-founded a bank and, uh, uh, he was one of the, on the board of

476
00:35:23,040 --> 00:35:27,280
ledger X when it was sold to FTX, I believe or call correctly.

477
00:35:27,280 --> 00:35:32,140
So, you know, obviously a very wealthy individual had been around Bitcoin for, you know, sounded

478
00:35:32,140 --> 00:35:33,140
like a decade.

479
00:35:33,140 --> 00:35:40,800
Um, but, you know, he, he was himself like a DIY, you know, genetic experimentalist.

480
00:35:40,800 --> 00:35:47,080
He was, uh, he, he was giving pitches a few years ago on developing designer babies.

481
00:35:47,080 --> 00:35:53,200
And you know, like literally doing this from like, like he built a home lab.

482
00:35:53,200 --> 00:35:59,560
He was also funding, he was literally funding a Ukrainian bio lab to do his, his work.

483
00:35:59,560 --> 00:36:03,960
It was, it was very, very, you know, interesting conversation that I, you know, unfortunately

484
00:36:03,960 --> 00:36:07,480
it was only six minutes because I would have, you know, I had, uh, many other guests to

485
00:36:07,480 --> 00:36:10,840
talk to and it would have been interesting to hear.

486
00:36:10,840 --> 00:36:16,680
Um, but yeah, there's so much that is weird about all of this.

487
00:36:16,680 --> 00:36:22,680
Um, you know, it, it, it, it's hard to know, you know, how long the planning took place,

488
00:36:22,680 --> 00:36:27,840
but, um, since you brought it up, just because you mentioned Peter Marks and talking about,

489
00:36:27,840 --> 00:36:31,680
you know, whether or not sterile immunity is something that they're going to work toward.

490
00:36:31,680 --> 00:36:34,320
I feel almost obliged to pull up this graph.

491
00:36:34,320 --> 00:36:40,480
Uh, when I was working on the military health database, I took the, um, hospitalizations,

492
00:36:40,480 --> 00:36:45,760
uh, each, each query has hospitalizations and it has ambulatory reports.

493
00:36:45,760 --> 00:36:50,400
And so I divided one by the other to get hospitalizations per case.

494
00:36:50,400 --> 00:36:54,240
And they were going up through the, the mandates in August.

495
00:36:54,240 --> 00:36:56,600
That's when the military mandates were.

496
00:36:56,600 --> 00:37:02,600
And so the cases were getting more severe as they vaccinated, not less severe.

497
00:37:02,600 --> 00:37:11,880
Um, you know, this, this, uh, this, uh, jives well with, uh, some of the work that, um,

498
00:37:11,880 --> 00:37:15,240
you know, a guy down the street here, John Baudewin, have you looked at his work with

499
00:37:15,240 --> 00:37:16,240
the Massachusetts?

500
00:37:16,240 --> 00:37:17,760
Oh yeah, I know, I know John pretty well.

501
00:37:17,760 --> 00:37:18,760
Yeah.

502
00:37:18,760 --> 00:37:19,760
Yeah.

503
00:37:19,760 --> 00:37:20,760
Oh, has he?

504
00:37:20,760 --> 00:37:21,760
Oh, good.

505
00:37:21,760 --> 00:37:22,760
Yeah.

506
00:37:22,760 --> 00:37:23,760
Oh, that's right.

507
00:37:23,760 --> 00:37:24,760
Yes.

508
00:37:24,760 --> 00:37:25,760
That's right.

509
00:37:25,760 --> 00:37:26,760
Um, I'm sorry.

510
00:37:26,760 --> 00:37:27,760
Yeah.

511
00:37:27,760 --> 00:37:29,760
You know, I mean, look, uh, you know, the evidence is pretty clear what's really going on here.

512
00:37:29,760 --> 00:37:36,360
Um, but let me tell you about this, the next anecdote, which is very interesting because,

513
00:37:36,360 --> 00:37:47,480
um, I sat in, in a, in a round table discussion and the topic was, um, how do we, uh, how do

514
00:37:47,480 --> 00:37:48,960
we deal with vaccine hesitancy?

515
00:37:48,960 --> 00:37:56,280
And like immediately I saw exactly, you know, what the mission was for the next three days,

516
00:37:56,280 --> 00:38:01,440
because they're making that a priority, um, to dealing with that.

517
00:38:01,440 --> 00:38:08,120
And um, before the discussion actually started, a woman sat next to me and I find out that,

518
00:38:08,120 --> 00:38:18,520
uh, she is, um, Jennifer Margaret Harry's and Harry's is the, um, the chief executive

519
00:38:18,520 --> 00:38:21,120
of the UK HSA.

520
00:38:21,120 --> 00:38:25,320
It's the United Kingdom health security agency.

521
00:38:25,320 --> 00:38:31,240
And um, as your audience probably knows, they put out a lot of data and I said, oh my gosh,

522
00:38:31,240 --> 00:38:32,240
you're with the UK HSA.

523
00:38:32,240 --> 00:38:33,240
That's awesome.

524
00:38:33,240 --> 00:38:38,920
I, I've been following your, your data for two years because we have crap data in this

525
00:38:38,920 --> 00:38:44,720
country and you're one of the few sources of like legitimate data out there.

526
00:38:44,720 --> 00:38:45,960
And thank you very much for your work.

527
00:38:45,960 --> 00:38:48,520
And she was, you know, she smiled and was very happy.

528
00:38:48,520 --> 00:38:50,040
Your energy was really good.

529
00:38:50,040 --> 00:38:58,440
And then I said, um, you know, I was very pleased that you reported on the, um, the

530
00:38:58,440 --> 00:39:05,560
increased incidents of COVID-19 in the vaccinated population in September, 2021 and you had

531
00:39:05,560 --> 00:39:07,360
age stratified it.

532
00:39:07,360 --> 00:39:13,680
And um, you know, it wasn't an aberration in data because those numbers continue to

533
00:39:13,680 --> 00:39:14,680
grow.

534
00:39:14,680 --> 00:39:20,160
There's negative efficacy, um, in all age groups within three or four months.

535
00:39:20,160 --> 00:39:22,440
And um, then you stopped reporting.

536
00:39:22,440 --> 00:39:23,440
Why?

537
00:39:23,440 --> 00:39:27,720
And she looked at me and you know, her whole like, everything changed.

538
00:39:27,720 --> 00:39:28,720
I'm not aware of that.

539
00:39:28,720 --> 00:39:29,720
I'm like, what?

540
00:39:29,720 --> 00:39:31,760
How could you not be aware of that?

541
00:39:31,760 --> 00:39:35,880
You took over the entire agency in I think April of 2021.

542
00:39:35,880 --> 00:39:37,440
This report came out in September.

543
00:39:37,440 --> 00:39:41,360
I mean, clearly you had something to do with, you know, stopping that right there.

544
00:39:41,360 --> 00:39:47,120
And you know, I don't know if you've looked at, at those reports, but they tried to, um,

545
00:39:47,120 --> 00:39:51,400
explain a way why this was happening with just, just bullshit arguments.

546
00:39:51,400 --> 00:39:55,080
Anyway, um, she clearly didn't want to talk about that anymore.

547
00:39:55,080 --> 00:40:01,080
And so then I asked her, um, about, oh my gosh, where did it go next?

548
00:40:01,080 --> 00:40:07,200
Oh, I said, um, uh, so what about, um, uh, test Lori?

549
00:40:07,200 --> 00:40:15,480
Um, you know, and, and, you know, she seemed like a very reasonable, um, doctor and researcher,

550
00:40:15,480 --> 00:40:20,320
you know, she's the head of the evidence-based, uh, uh, medicine consultancy in England.

551
00:40:20,320 --> 00:40:27,080
And she wrote this open letter to the UK, um, uh, MHRA, uh, which is the equivalent

552
00:40:27,080 --> 00:40:32,720
of the FDA in England in an open letter saying, look, we gotta, we gotta stop the vaccines

553
00:40:32,720 --> 00:40:37,880
in the United Kingdom because the yellow card, the yellow card being the, uh, vaccine adverse

554
00:40:37,880 --> 00:40:41,920
event reporting system of the UK was clearly showing a danger signal.

555
00:40:41,920 --> 00:40:42,920
Right.

556
00:40:42,920 --> 00:40:49,320
Um, and then she looked at me and she was like, you know, um, there are a lot of physicians

557
00:40:49,320 --> 00:40:55,480
in my country, uh, that are gaining a lot of fame for their extreme positions.

558
00:40:55,480 --> 00:41:00,440
In fact, right now there's, there's a cardiologist that's doing the same thing.

559
00:41:00,440 --> 00:41:05,320
And I said, you mean, uh, Dr. Malhotra, is that who you're talking about?

560
00:41:05,320 --> 00:41:07,040
And she said, Oh, you know who that is?

561
00:41:07,040 --> 00:41:08,040
I'm like, yeah.

562
00:41:08,040 --> 00:41:11,040
I mean, wasn't he famous before COVID?

563
00:41:11,040 --> 00:41:13,040
One of the more famous cardiologists in the world.

564
00:41:13,040 --> 00:41:14,040
Yeah.

565
00:41:14,040 --> 00:41:16,800
I mean, like he's gaining fame from, from this.

566
00:41:16,800 --> 00:41:20,160
I mean, he was pretty, he was pretty well known before, right?

567
00:41:20,160 --> 00:41:25,880
Anyway, so, um, I had another interaction with her later on, but that's when the thing

568
00:41:25,880 --> 00:41:26,880
started.

569
00:41:26,880 --> 00:41:28,880
It's like, okay, who has any suggestions?

570
00:41:28,880 --> 00:41:30,000
And no one was saying anything.

571
00:41:30,000 --> 00:41:32,400
So I'm like, okay, I'll go first.

572
00:41:32,400 --> 00:41:36,760
And um, you know, I said, look, you guys, let's be real.

573
00:41:36,760 --> 00:41:38,480
Like, here's the thing, right?

574
00:41:38,480 --> 00:41:43,800
It's, it's, I'm not going there as a protester and trying to put it in their face, engage

575
00:41:43,800 --> 00:41:50,000
the con the conversation so that people can see the hypocrisy and the uncertainty in what

576
00:41:50,000 --> 00:41:51,160
they're doing.

577
00:41:51,160 --> 00:41:56,560
So I said, um, look, the, you know, you've already talked to people who you wanted to

578
00:41:56,560 --> 00:42:03,840
talk into getting it with, um, you know, uh, gift cards to target and, uh, limiting their

579
00:42:03,840 --> 00:42:05,040
travel restrictions, right?

580
00:42:05,040 --> 00:42:08,720
The people who are resistant right now, they don't give a shit about that.

581
00:42:08,720 --> 00:42:13,280
You know, they're listening to people who are qualified to speak on this topic, who

582
00:42:13,280 --> 00:42:15,680
have very, very good points.

583
00:42:15,680 --> 00:42:18,800
Why don't we bring in their spokespeople?

584
00:42:18,800 --> 00:42:26,520
Oh, and by the way, in the last session, you know, who, who they believe is the, the, the

585
00:42:26,520 --> 00:42:33,280
biggest, um, heretic, it's not Peter McCullough or Robert Malone.

586
00:42:33,280 --> 00:42:39,200
They kept citing, um, Wakefield as, you know, he's the one that's pushing this.

587
00:42:39,200 --> 00:42:43,080
It's like, dude, that guy is, you know, I mean, he's done amazing work, you know, I

588
00:42:43,080 --> 00:42:45,240
hope we've all seen the movie vaxed.

589
00:42:45,240 --> 00:42:49,080
Um, and that whole issue, I'm not coming down one side or the other.

590
00:42:49,080 --> 00:42:51,880
I'm just saying that that's been out there for like years.

591
00:42:51,880 --> 00:42:57,080
We're talking about a whole new like birth of, of resistant people who know what they're

592
00:42:57,080 --> 00:42:58,080
talking about.

593
00:42:58,080 --> 00:42:59,080
Anyway, um, yeah.

594
00:42:59,080 --> 00:43:04,360
So I said, why don't we bring on some, you know, some of their spokespeople and dismantle

595
00:43:04,360 --> 00:43:07,320
their arguments in a public forum, right?

596
00:43:07,320 --> 00:43:13,600
Um, and immediately, uh, another person got up and said, no, that would be, um, that's

597
00:43:13,600 --> 00:43:14,600
a terrible idea.

598
00:43:14,600 --> 00:43:19,880
And my research, if you give them equal footing, the public will think that, uh, they have

599
00:43:19,880 --> 00:43:20,880
a point.

600
00:43:20,880 --> 00:43:23,640
So we should never ever let them speak.

601
00:43:23,640 --> 00:43:28,280
And that woman, um, who I encountered several times over the next few days, her name is

602
00:43:28,280 --> 00:43:36,040
Katie Atwell and she is a behavioral scientist from the university of, uh, Western Australia.

603
00:43:36,040 --> 00:43:40,520
And I didn't know who she was at the time, but I got to know more about her, uh, as the

604
00:43:40,520 --> 00:43:44,960
week progressed because every time that I would somehow we would always end up in the

605
00:43:44,960 --> 00:43:47,100
same panel discussions.

606
00:43:47,100 --> 00:43:50,360
And every time I'd, I'd suggest this, she would immediately jump in and say, no, that's

607
00:43:50,360 --> 00:43:52,240
a bad idea.

608
00:43:52,240 --> 00:43:57,400
Um, but what ha here's, what's interesting is that what afterwards people would come

609
00:43:57,400 --> 00:43:59,000
up to me and say, God, that was a really good idea.

610
00:43:59,000 --> 00:44:00,000
Why don't we do that?

611
00:44:00,000 --> 00:44:01,000
And I said, I know.

612
00:44:01,000 --> 00:44:02,400
And, you know, we should do that.

613
00:44:02,400 --> 00:44:03,400
Let's see what happens.

614
00:44:03,400 --> 00:44:04,400
Right.

615
00:44:04,400 --> 00:44:07,600
And, um, in query is the basis of science.

616
00:44:07,600 --> 00:44:08,600
Yes.

617
00:44:08,600 --> 00:44:09,600
Too bad.

618
00:44:09,600 --> 00:44:10,600
We're not doing any science.

619
00:44:10,600 --> 00:44:16,520
Um, there was another person there and this is a, another person that you may want to

620
00:44:16,520 --> 00:44:19,120
bring up her whose name is Christopher Graves.

621
00:44:19,120 --> 00:44:28,000
This guy, um, is, uh, you know, sided with at well, and he claims to have done this amazing

622
00:44:28,000 --> 00:44:36,880
research that goes into how do you, uh, target messaging based on a person's, um, biases

623
00:44:36,880 --> 00:44:37,880
and predilections.

624
00:44:37,880 --> 00:44:45,840
And, you know, these, uh, you know, he basically categorizes people in, in, um, I think 16

625
00:44:45,840 --> 00:44:52,520
different ways based, you know, hyper religiosity, uh, anti authoritarianism, you know, these

626
00:44:52,520 --> 00:44:54,520
kinds of classifications.

627
00:44:54,520 --> 00:45:00,320
And then, uh, they also, it was a study of 3000 vaccine hesitant people.

628
00:45:00,320 --> 00:45:05,800
And then once he's done that, then they ask specific questions like, what is your issue

629
00:45:05,800 --> 00:45:07,240
with the vaccine exactly?

630
00:45:07,240 --> 00:45:13,520
Is it because, um, you think that you don't know what's in them, you don't trust the government,

631
00:45:13,520 --> 00:45:15,480
you know, like all of these questions.

632
00:45:15,480 --> 00:45:21,440
And then they come up with a, uh, targeted messaging, like for this kind of person who

633
00:45:21,440 --> 00:45:25,400
believes that this is the kind of message you want to give to them.

634
00:45:25,400 --> 00:45:30,080
And the point here is, uh, so Matthew, can you bring up that, that, um, PDF file?

635
00:45:30,080 --> 00:45:31,080
Can you do that?

636
00:45:31,080 --> 00:45:33,600
Cause it's really, really interesting.

637
00:45:33,600 --> 00:45:42,600
Um, this study, uh, was funded by Merck of all people, obviously.

638
00:45:42,600 --> 00:45:51,600
And the reality here is, is that they are pathologizing the vaccine hesitant, you know,

639
00:45:51,600 --> 00:45:56,440
like it must be some sort of cognitive, yeah, that's Sam Christopher Graves, you know, and

640
00:45:56,440 --> 00:45:57,440
here it is.

641
00:45:57,440 --> 00:46:04,360
Um, of course he's WEF, but more importantly, he, I think it says he's had a long, a life

642
00:46:04,360 --> 00:46:07,040
member of, uh, the CFR.

643
00:46:07,040 --> 00:46:15,120
So this is someone who's been involved in all of this stuff for decades and he, um,

644
00:46:15,120 --> 00:46:17,160
was very affable.

645
00:46:17,160 --> 00:46:23,840
And we spoke for about 30 minutes after this particular presentation and, um, he was telling

646
00:46:23,840 --> 00:46:27,480
me about the research and, um, he sent me this PDF file.

647
00:46:27,480 --> 00:46:33,840
I don't know if you can put it up of a large poster that, um, summarizes the research

648
00:46:33,840 --> 00:46:35,720
he was paid to do by Merck.

649
00:46:35,720 --> 00:46:40,560
I guess I don't know where that PDF is.

650
00:46:40,560 --> 00:46:45,280
Um, if it was in your email to me, I guess I missed it.

651
00:46:45,280 --> 00:46:46,280
Okay.

652
00:46:46,280 --> 00:46:48,800
It was an attachment because it was a PDF, so it doesn't really matter.

653
00:46:48,800 --> 00:46:56,840
The point is, is that it was, it was a very, very, um, uh, uh, I would say sophisticated

654
00:46:56,840 --> 00:46:57,840
analysis.

655
00:46:57,840 --> 00:47:04,400
And the point number one here is that we have to understand that they're approaching us

656
00:47:04,400 --> 00:47:07,120
with very sophisticated messaging.

657
00:47:07,120 --> 00:47:11,040
You know, that's how they're, you know, they are saying like, this is, this is the problem.

658
00:47:11,040 --> 00:47:18,360
We have to be very targeted with how we approach and, and engage with the vaccine hesitant.

659
00:47:18,360 --> 00:47:22,440
And we need to take a lesson from that, you know, which is like, we have to like consolidate

660
00:47:22,440 --> 00:47:27,040
around, uh, you know, a clear message.

661
00:47:27,040 --> 00:47:35,560
And, and as you pointed out before the, the, the no virus, um, group, look, I, you know,

662
00:47:35,560 --> 00:47:39,720
far for me to say, for sure, I know what's going on, but you know, for someone to say,

663
00:47:39,720 --> 00:47:46,800
uh, there is no virus that defeats the purpose or at least my purpose, which is to keep this

664
00:47:46,800 --> 00:47:55,280
technology away from children and to, you know, and everybody else and restore, um,

665
00:47:55,280 --> 00:47:56,320
health freedom.

666
00:47:56,320 --> 00:47:59,040
And so it's a, it's a detractor.

667
00:47:59,040 --> 00:48:06,120
Um, but the point here is that these guys have a tremendous amount of resources and

668
00:48:06,120 --> 00:48:07,240
this is what they're doing.

669
00:48:07,240 --> 00:48:15,240
They're pathologizing our position and they want to make this, um, a, uh, a disease, you

670
00:48:15,240 --> 00:48:20,600
know, disease of the mind of psychology of cognition and, um, and treat it that way.

671
00:48:20,600 --> 00:48:21,960
Yes, there it is.

672
00:48:21,960 --> 00:48:28,600
I mean, it's, it's a, it's a really, really interesting look, 51.9% of the people he's

673
00:48:28,600 --> 00:48:38,520
surveyed, um, believe have lost confidence in, um, in vaccines throughout the pandemic.

674
00:48:38,520 --> 00:48:45,320
Um, and if you look at the numbers there, it's hard to see, but there are a lot of people

675
00:48:45,320 --> 00:48:53,520
independent of their ethnicity that feel like their confidence in the industry, um,

676
00:48:53,520 --> 00:48:55,320
is down a lot.

677
00:48:55,320 --> 00:48:56,320
Right.

678
00:48:56,320 --> 00:49:05,280
I, I think that they over gambled on, um, using ash conformity to, to create conformity

679
00:49:05,280 --> 00:49:09,360
because the way that that study worked, and this is how, why I think that you can bring

680
00:49:09,360 --> 00:49:13,120
in somebody like Christopher graves, who goes through like psych profiling to figure out

681
00:49:13,120 --> 00:49:15,360
how it is to apply this to people.

682
00:49:15,360 --> 00:49:19,160
Um, there were a number of versions of the ash conformity experiment, but after the original

683
00:49:19,160 --> 00:49:25,440
experiment, uh, you know, uh, ash had his, um, you know, researchers survey every single

684
00:49:25,440 --> 00:49:29,480
person to find out why did you go with the wrong answer?

685
00:49:29,480 --> 00:49:30,480
Right.

686
00:49:30,480 --> 00:49:32,560
And, and there were different answers given, right?

687
00:49:32,560 --> 00:49:37,840
Some people said, uh, they were going along to avoid social punishment in so many words.

688
00:49:37,840 --> 00:49:41,920
Some people were going along to accrue social acceptance.

689
00:49:41,920 --> 00:49:44,960
So, you know, positive reinforcement, negative reinforcement.

690
00:49:44,960 --> 00:49:49,840
And then there was a third crowd and this is, you know, interesting concerning.

691
00:49:49,840 --> 00:49:51,640
Um, but there was a third crowd.

692
00:49:51,640 --> 00:49:56,280
It was not a majority or anything, you know, as a minority crowd, but, um, there was actual,

693
00:49:56,280 --> 00:50:00,440
uh, distortion of perception, right?

694
00:50:00,440 --> 00:50:05,760
Other people saying this line is longer than that line or, or, or this line matches, uh,

695
00:50:05,760 --> 00:50:09,960
you know, the one that they were supposed to match it to, um, other people literally,

696
00:50:09,960 --> 00:50:16,040
you know, whatever it was, they were disoriented by the actions of these other people.

697
00:50:16,040 --> 00:50:21,560
I didn't know that now versions of the ash conformity experiment have involved, uh, confidants

698
00:50:21,560 --> 00:50:28,840
who were, you know, you put a confidant in a white coat and suddenly conformity goes

699
00:50:28,840 --> 00:50:29,840
up.

700
00:50:29,840 --> 00:50:30,840
Yeah.

701
00:50:30,840 --> 00:50:31,840
It goes up substantially.

702
00:50:31,840 --> 00:50:32,840
Right.

703
00:50:32,840 --> 00:50:37,920
And, and my bet is that, uh, the types of people who play these games have studied further

704
00:50:37,920 --> 00:50:42,600
versions of these conformity studies and they know what to do.

705
00:50:42,600 --> 00:50:47,680
But, uh, I think that they, that they, and this is something I actually, I told my wife

706
00:50:47,680 --> 00:50:51,960
this back in 2020, when I first started thinking that this was all an ash conformity experiment,

707
00:50:51,960 --> 00:50:58,480
I said, what's going to happen is people are going to lose trust in the icon that you were

708
00:50:58,480 --> 00:50:59,480
using.

709
00:50:59,480 --> 00:51:00,480
Right.

710
00:51:00,480 --> 00:51:05,340
Because that's the only thing that they can do is blame it on the confidant.

711
00:51:05,340 --> 00:51:09,520
So what's happening is these are parasocial relationships that are being used.

712
00:51:09,520 --> 00:51:10,520
Right.

713
00:51:10,520 --> 00:51:14,520
You put up a Trump, you put up a Fauci and you know how it is that people relate to these

714
00:51:14,520 --> 00:51:15,520
two figures.

715
00:51:15,520 --> 00:51:16,520
Right.

716
00:51:16,520 --> 00:51:20,800
Um, you know, instead of, um, I think of them as like Dunbar slots, you know, you have your

717
00:51:20,800 --> 00:51:25,880
Dunbar number, your 150 people that you, that you know, or do you know this concept?

718
00:51:25,880 --> 00:51:26,880
No.

719
00:51:26,880 --> 00:51:31,360
Um, you know, Robin Dunbar, uh, I guess he was a anthropologist or sociologist.

720
00:51:31,360 --> 00:51:35,200
He said, um, you know, it seems to be the large of the primate brain.

721
00:51:35,200 --> 00:51:41,120
The larger the group that they hang out in, you know, um, eight cotton monkeys, 60 baboons,

722
00:51:41,120 --> 00:51:46,280
you know, 150 to 300 humans, 150 became known as Dunbar's number.

723
00:51:46,280 --> 00:51:51,040
And I think that it was not just the number, like in terms of our brains can hold, uh,

724
00:51:51,040 --> 00:51:56,240
capacity for 150 social relationships where you truly know people, you know, their, their

725
00:51:56,240 --> 00:52:01,800
movements you, you would, you couldn't really be deceived by them very easily, very often.

726
00:52:01,800 --> 00:52:05,520
Um, at least the vast majority of those relationships, right.

727
00:52:05,520 --> 00:52:08,840
And there wouldn't be much attempt to, because you're all in it together.

728
00:52:08,840 --> 00:52:09,840
You really are.

729
00:52:09,840 --> 00:52:10,840
You're a tribe.

730
00:52:10,840 --> 00:52:11,840
Right.

731
00:52:11,840 --> 00:52:18,160
I think that, um, that a lot of modern, uh, propaganda has focused around taking over

732
00:52:18,160 --> 00:52:22,280
not just a member of the tribe, but like a specific slot, right.

733
00:52:22,280 --> 00:52:29,160
TV comes in and people see Biden, Trump, Reagan, whoever, and you know, Clinton, and they think

734
00:52:29,160 --> 00:52:34,000
chief or they might even think chief of the other tribe, right.

735
00:52:34,000 --> 00:52:37,640
Like those are the people that we have to watch for, you know, if they come in our territory,

736
00:52:37,640 --> 00:52:38,920
we make war, right.

737
00:52:38,920 --> 00:52:45,840
So, uh, and I think that probably there is sort of, um, there's probably a handful of

738
00:52:45,840 --> 00:52:48,320
slots that are designated.

739
00:52:48,320 --> 00:52:51,380
They have a specific utility in your brain.

740
00:52:51,380 --> 00:52:56,160
Family member might be one, but you know, medicine man, you know, um, the scientist,

741
00:52:56,160 --> 00:53:00,720
uh, you know, that, that person in the group that, that sort of has the most curiosity

742
00:53:00,720 --> 00:53:05,880
and figures things out or something, you know, the engineer, if you showed, if you show people

743
00:53:05,880 --> 00:53:13,360
images on TV of that, and they don't have that relationship close to them enough that,

744
00:53:13,360 --> 00:53:18,520
you know, that it can't be replaced easily, you know, Neil deGrasse Tyson, you know, Anthony

745
00:53:18,520 --> 00:53:22,400
Fauci these become in people's heads, archetypes.

746
00:53:22,400 --> 00:53:23,720
Yes.

747
00:53:23,720 --> 00:53:28,760
And suddenly these archetypes get used as the confidants and the, it is Ash conformity

748
00:53:28,760 --> 00:53:29,760
experiments.

749
00:53:29,760 --> 00:53:35,000
And the only thing, the only possible way people can, can, uh, you know, rationalize

750
00:53:35,000 --> 00:53:41,080
is to give up the archetype, either give up the archetype entirely or give up the person

751
00:53:41,080 --> 00:53:45,920
as a representation of, you know, and, and who knows, like we, we may not know which

752
00:53:45,920 --> 00:53:47,160
of those things is going to happen.

753
00:53:47,160 --> 00:53:51,500
And that's actually its own sort of concerning facet of the whole experience, right.

754
00:53:51,500 --> 00:53:53,400
Are people going to reject science?

755
00:53:53,400 --> 00:53:56,280
Will we see a mass rejection of science?

756
00:53:56,280 --> 00:53:58,640
You know, are, are people going to be discerning enough?

757
00:53:58,640 --> 00:54:02,640
I think the answer is no, but I, are people going to be discerning enough to distinguish

758
00:54:02,640 --> 00:54:09,080
between science and the institutions that have been created to make science into an

759
00:54:09,080 --> 00:54:10,080
industry?

760
00:54:10,080 --> 00:54:13,280
Yeah, that's a really, yeah.

761
00:54:13,280 --> 00:54:20,680
So Matthew, do you think that, um, that these archetypes, uh, have been created?

762
00:54:20,680 --> 00:54:27,360
In other words, um, do you think that someone like Neil deGrasse Tyson, um, has been a project

763
00:54:27,360 --> 00:54:28,800
of, you know, Mr.

764
00:54:28,800 --> 00:54:33,960
I've actually wondered, uh, you know, almost a decade ago, I actually said something like

765
00:54:33,960 --> 00:54:39,200
this on my Facebook and, uh, you know, I had some people snap back at me over it, but,

766
00:54:39,200 --> 00:54:45,160
um, you know, I said, like, this guy almost looks like a cartoon, like he's a caricature

767
00:54:45,160 --> 00:54:50,600
of what he is, you know, it, it almost feels like this is like yet another type of, uh,

768
00:54:50,600 --> 00:54:51,600
intelligence operation.

769
00:54:51,600 --> 00:54:52,600
Yeah.

770
00:54:52,600 --> 00:54:54,320
I think the odds are pretty high.

771
00:54:54,320 --> 00:54:59,360
And when I say high, I mean, you know, in my mind, I'd put, you know, wide interval

772
00:54:59,360 --> 00:55:02,320
20 to 90%, but I'd call that high.

773
00:55:02,320 --> 00:55:05,080
You know, anything above one is probably high.

774
00:55:05,080 --> 00:55:06,080
Right.

775
00:55:06,080 --> 00:55:07,080
Yeah.

776
00:55:07,080 --> 00:55:08,400
I, I would agree with you.

777
00:55:08,400 --> 00:55:10,400
I, you know, anything is possible.

778
00:55:10,400 --> 00:55:15,040
And given what was, you know, divulged in just this, these few days in terms of like

779
00:55:15,040 --> 00:55:20,640
how, how, how much money they're willing to spend in looking at this more closely, I wouldn't

780
00:55:20,640 --> 00:55:24,600
be surprised at all, um, that this is all been engineered.

781
00:55:24,600 --> 00:55:30,600
And, and there was another, there was another, um, small group session, um, where this guy

782
00:55:30,600 --> 00:55:38,000
from Hopkins, uh, whose name is something Solomon Salmon, he presented the stuff that

783
00:55:38,000 --> 00:55:44,440
they're doing and, um, he created a website and a whole platform called let's talk shots.

784
00:55:44,440 --> 00:55:51,040
And, um, like you pointed out there, uh, some people need to hear the message from their

785
00:55:51,040 --> 00:55:52,320
pastor.

786
00:55:52,320 --> 00:55:54,840
Some people need to hear it from the doctor.

787
00:55:54,840 --> 00:56:01,320
Some people need to hear it, uh, from a doctor who is of the same cultural background.

788
00:56:01,320 --> 00:56:04,600
Um, and that's what they're doing.

789
00:56:04,600 --> 00:56:11,640
You know, they're, they're not, you know, they're not, um, compromising on, uh, or,

790
00:56:11,640 --> 00:56:13,000
or cutting any corners.

791
00:56:13,000 --> 00:56:15,000
They're after everybody.

792
00:56:15,000 --> 00:56:20,880
And you know, even when I said, look, they admit that there's a problem because, you

793
00:56:20,880 --> 00:56:21,880
know, what is it?

794
00:56:21,880 --> 00:56:26,920
79% of people have gotten one shot in this country and 60 have got the primary series,

795
00:56:26,920 --> 00:56:30,720
but only 15% have taken the biovalent booster.

796
00:56:30,720 --> 00:56:34,880
And um, and all they say is like, oh, you know, the reason why is that the perceived

797
00:56:34,880 --> 00:56:41,400
threat is much lower and that's why they're not waiting in line and the right, right.

798
00:56:41,400 --> 00:56:45,480
I mean, I hope we all understand that the pathogenicity of this, whatever strains are

799
00:56:45,480 --> 00:56:49,040
out there right now is much different than it was three years ago, but nowhere did they

800
00:56:49,040 --> 00:56:54,920
ever acknowledge the fact that, um, people don't trust anyone anymore.

801
00:56:54,920 --> 00:56:59,000
Um, it, and that there are injuries in any case.

802
00:56:59,000 --> 00:57:02,640
So going back to graves here, this is what I wanted to say is that I'm talking to him

803
00:57:02,640 --> 00:57:07,560
outside of the, um, outside the hall about his research and he's telling me all of these

804
00:57:07,560 --> 00:57:09,640
things about what they're doing.

805
00:57:09,640 --> 00:57:17,320
And I said, so how would you, um, how would you talk to a position who went back to the

806
00:57:17,320 --> 00:57:23,040
trial data and saw that there were more mortality in the, in the, in the therapy groups in the

807
00:57:23,040 --> 00:57:26,480
placebo group, right?

808
00:57:26,480 --> 00:57:28,280
What's the proper messaging for that person?

809
00:57:28,280 --> 00:57:33,960
And he's like, oh, those are the, uh, like the cognitive fixated people.

810
00:57:33,960 --> 00:57:37,680
Those are the ones that have a problem with uncertainty.

811
00:57:37,680 --> 00:57:39,680
You know, they won't move.

812
00:57:39,680 --> 00:57:40,680
Okay.

813
00:57:40,680 --> 00:57:45,120
I'm like, okay, that's the problem.

814
00:57:45,120 --> 00:57:46,120
I see.

815
00:57:46,120 --> 00:57:49,640
Um, so, you know, and I said, have you, have you looked at the data?

816
00:57:49,640 --> 00:57:51,760
And he said, no, no, I haven't looked at the data.

817
00:57:51,760 --> 00:57:53,840
You know, it was almost like, who cares about the data?

818
00:57:53,840 --> 00:57:56,120
You know, that's not my problem, right?

819
00:57:56,120 --> 00:58:00,520
He's looking to pathologize without even understanding whether or not those people are making accurate

820
00:58:00,520 --> 00:58:01,520
observations.

821
00:58:01,520 --> 00:58:02,520
Yes.

822
00:58:02,520 --> 00:58:03,520
That's amazing.

823
00:58:03,520 --> 00:58:05,320
That, that's really amazing.

824
00:58:05,320 --> 00:58:07,880
That's where you know, it's somebody's job.

825
00:58:07,880 --> 00:58:10,880
They're told to hunt for a pathology.

826
00:58:10,880 --> 00:58:11,880
Yep.

827
00:58:11,880 --> 00:58:12,880
Yes.

828
00:58:12,880 --> 00:58:13,880
That's, that's what they're doing.

829
00:58:13,880 --> 00:58:17,800
Um, and the same thing, the same thing occurred in the next.

830
00:58:17,800 --> 00:58:23,520
So I don't really expect someone like Christopher Graves to have looked at the data, but I had

831
00:58:23,520 --> 00:58:30,920
nearly the same conversation with an epidemiologist from, um, oh boy, she was also from Hopkins.

832
00:58:30,920 --> 00:58:35,440
And again, it was another session with this woman, Katie Atwell, who, you know, shot down

833
00:58:35,440 --> 00:58:37,560
my, my idea immediately.

834
00:58:37,560 --> 00:58:42,440
Um, but then this other person came up to me afterwards and once again, I was encouraged

835
00:58:42,440 --> 00:58:47,440
because she was like, you know, Dr. Setti, I think your questions were really good and,

836
00:58:47,440 --> 00:58:54,360
um, we need to work more on education of our physicians so that they understand, um, what's

837
00:58:54,360 --> 00:58:55,760
really going on, right?

838
00:58:55,760 --> 00:58:57,200
Um, that's the way through.

839
00:58:57,200 --> 00:59:00,160
We need education, education, education.

840
00:59:00,160 --> 00:59:03,480
You know, something that you're into.

841
00:59:03,480 --> 00:59:08,800
And um, yeah, that's Katie Atwell at the, so this other person whose name escapes me

842
00:59:08,800 --> 00:59:13,040
right now, but she had an extensive background in Africa.

843
00:59:13,040 --> 00:59:20,560
Anyway, she comes up to me and says, yeah, we need to, um, we need to look at, uh, educating

844
00:59:20,560 --> 00:59:25,840
our, our, uh, uh, our, uh, primary care physicians.

845
00:59:25,840 --> 00:59:33,640
And so I said, um, look, the, um, the, the, the people in my community, um, they come

846
00:59:33,640 --> 00:59:35,960
to me and I, and I quoted the same thing.

847
00:59:35,960 --> 00:59:41,280
It's like all cause mortality, six month interim results from Pfizer, a grader in the therapy

848
00:59:41,280 --> 00:59:42,280
group.

849
00:59:42,280 --> 00:59:45,440
They come to me and I don't know what to say to that.

850
00:59:45,440 --> 00:59:46,600
What do you think?

851
00:59:46,600 --> 00:59:50,120
And she looks at me and she goes, is that, is that a new study that just came out?

852
00:59:50,120 --> 00:59:53,600
And I said, this is your original trial results.

853
00:59:53,600 --> 00:59:54,600
Like you don't know that.

854
00:59:54,600 --> 00:59:59,080
How is that even possible that you don't even understand that?

855
00:59:59,080 --> 01:00:02,880
And, and, and to her credit, she was like, well, I didn't know I'm, I'll look into it.

856
01:00:02,880 --> 01:00:10,260
So the point here is that there are clearly people at the very, very top that, that know

857
01:00:10,260 --> 01:00:13,240
what they're pushing is not good.

858
01:00:13,240 --> 01:00:17,600
But then you have all of these, you know, middle people, you know, these academics who

859
01:00:17,600 --> 01:00:23,280
just, you know, are stuck in herd mentality and group think who just listened to it and

860
01:00:23,280 --> 01:00:25,920
assume that they've got it right.

861
01:00:25,920 --> 01:00:31,160
And I could understand how that was happening because, you know, one of the, one of the,

862
01:00:31,160 --> 01:00:38,400
the big things that I observed was people there are unwilling to second guess their

863
01:00:38,400 --> 01:00:43,000
position because they've got all the trophies, they've got all the toys, they've got all

864
01:00:43,000 --> 01:00:44,000
the money.

865
01:00:44,000 --> 01:00:50,240
Like why would the world be rewarding them, you know, so bountifully if they had it wrong?

866
01:00:50,240 --> 01:00:51,240
Right.

867
01:00:51,240 --> 01:00:59,320
So their education was more about being mimetic than about, you know, learning how to find

868
01:00:59,320 --> 01:01:04,000
all the answers themselves, because there's so much information, you know, whether you're

869
01:01:04,000 --> 01:01:09,360
a physician or a scientist, the amount, the, the information pool, I guess people say things

870
01:01:09,360 --> 01:01:13,680
like information doubles every year and a half or I don't know, it's probably like 17

871
01:01:13,680 --> 01:01:14,680
days at this point, right.

872
01:01:14,680 --> 01:01:17,240
It's something it's all insane, right.

873
01:01:17,240 --> 01:01:26,280
I mean, you know, when I went to school, it, college classes were already looking tedious

874
01:01:26,280 --> 01:01:31,320
to me just on the level of, you know, gosh, I have to go through this much information

875
01:01:31,320 --> 01:01:37,840
and I have no idea what I'm even going to learn in terms of processes or procedures.

876
01:01:37,840 --> 01:01:42,020
And because of that, I didn't like a lot of the college classes, but I, you know, I could,

877
01:01:42,020 --> 01:01:48,720
I could see the, the pre-med students, you know, working, you know, 80 hours a week and,

878
01:01:48,720 --> 01:01:50,640
you know, memorizing stuff on note cards.

879
01:01:50,640 --> 01:01:55,840
I just thought, I just thought, you know, like this is like, it just feels like the

880
01:01:55,840 --> 01:02:00,720
wrong thing, but I assumed that medical school and beyond that it got better from there.

881
01:02:00,720 --> 01:02:04,400
And then of course I've had so many friends go to medical school that I know that's not,

882
01:02:04,400 --> 01:02:12,240
that's not true, that it's just, it's constant pressure and that, you know, people release

883
01:02:12,240 --> 01:02:17,520
that pressure by beginning to look around and behaving like the flock around them.

884
01:02:17,520 --> 01:02:22,840
Because they assume that there are at least some members of the flock who are putting

885
01:02:22,840 --> 01:02:26,480
in all of the work to figure out how it all works.

886
01:02:26,480 --> 01:02:28,000
Correct.

887
01:02:28,000 --> 01:02:33,560
And they don't know that they could all be led along, you know, you see it a few people

888
01:02:33,560 --> 01:02:38,160
with, I don't know, an ash conformity experiment or, you know, a little bit of pressure and

889
01:02:38,160 --> 01:02:43,080
control and suddenly you have the flock moving in one direction together.

890
01:02:43,080 --> 01:02:48,280
Or it could be entirely natural or natural process of incentives.

891
01:02:48,280 --> 01:02:51,960
You know, the incentives are all wrong and they've all been poisoned for so many years

892
01:02:51,960 --> 01:02:55,120
intentionally or otherwise.

893
01:02:55,120 --> 01:02:59,800
And you know, I do think that there is a certain amount of intent to it because when you have

894
01:02:59,800 --> 01:03:02,800
industries that, well, we know Rockefeller's history.

895
01:03:02,800 --> 01:03:08,680
I mean, he, you know, he was very clearly poisoning, you know, putting money in all

896
01:03:08,680 --> 01:03:12,320
the medical schools saying no strings attached and then coming back later and saying, oh,

897
01:03:12,320 --> 01:03:15,800
but we'd like a board member just to make sure that it's spent well, right?

898
01:03:15,800 --> 01:03:21,240
Come back a second time and up the stakes a little bit each time knowing that they may

899
01:03:21,240 --> 01:03:26,080
have, you know, these people who didn't have nice salaries probably misspent a little of

900
01:03:26,080 --> 01:03:28,880
that money.

901
01:03:28,880 --> 01:03:37,320
So it, you know, the momentary behavior and not, not letting people relax and think creatively

902
01:03:37,320 --> 01:03:43,440
while climbing up this ladder where they may even be building debt to get there.

903
01:03:43,440 --> 01:03:44,760
It's a trap.

904
01:03:44,760 --> 01:03:46,160
It's a terrible trap.

905
01:03:46,160 --> 01:03:47,640
It is.

906
01:03:47,640 --> 01:03:48,640
Absolutely.

907
01:03:48,640 --> 01:03:53,040
And, yeah, you said it really well and explained it.

908
01:03:53,040 --> 01:03:56,480
You know, my personal experience in medical school was much different than most of my

909
01:03:56,480 --> 01:03:57,720
colleagues.

910
01:03:57,720 --> 01:04:05,880
You know, I had a background outside of medicine first and, and it became very clear to me

911
01:04:05,880 --> 01:04:14,280
that there was a lot of what you just described there happening right there in medical education.

912
01:04:14,280 --> 01:04:19,560
And you know, most of my classmates were six or seven years younger than I was, and they

913
01:04:19,560 --> 01:04:26,880
had never been out there, you know, doing like real, you know, computational stuff.

914
01:04:26,880 --> 01:04:34,720
And the idea that they could actually critique the methodology of a study was preposterous.

915
01:04:34,720 --> 01:04:35,880
They can't.

916
01:04:35,880 --> 01:04:42,780
And look, I'm not trying to just slam all physicians of being, you know, victims of

917
01:04:42,780 --> 01:04:45,000
groupthink.

918
01:04:45,000 --> 01:04:51,680
Doctors are much better at challenging ideas coming from their own specialty, reading literature

919
01:04:51,680 --> 01:04:57,440
that has to do with their own field and pushing back when they feel like, you know, my own

920
01:04:57,440 --> 01:04:59,060
experience is different.

921
01:04:59,060 --> 01:05:01,600
So I don't really believe the study.

922
01:05:01,600 --> 01:05:05,640
But when it comes to like the pandemic, for example, like, you know, as an anesthesiologist,

923
01:05:05,640 --> 01:05:06,640
I never listened to the CDC.

924
01:05:06,640 --> 01:05:10,360
I didn't even know, you know, really what the CDC was, to be honest with you, until

925
01:05:10,360 --> 01:05:11,800
this happened.

926
01:05:11,800 --> 01:05:18,680
And suddenly, you know, a huge swath of physicians, the vast majority who don't deal with infectious

927
01:05:18,680 --> 01:05:23,880
diseases and epidemiology, what are they going to do when the CDC says that this is what

928
01:05:23,880 --> 01:05:24,880
the science is?

929
01:05:24,880 --> 01:05:27,440
They're not going to be able to push back on it.

930
01:05:27,440 --> 01:05:29,360
And I'm not trying to make excuses for physicians.

931
01:05:29,360 --> 01:05:36,120
I know there's a lot of anger on our side, you know, that want to criminalize every single

932
01:05:36,120 --> 01:05:39,520
physician or the entire field.

933
01:05:39,520 --> 01:05:45,760
But I think it's more important to understand that these people are just misinformed.

934
01:05:45,760 --> 01:05:48,800
At least that's been my experience.

935
01:05:48,800 --> 01:05:50,940
And this should be hopeful to us, right?

936
01:05:50,940 --> 01:05:55,560
Because you're not going to talk a psychopath into doing the right thing, but you can teach

937
01:05:55,560 --> 01:05:57,680
someone who is misinformed.

938
01:05:57,680 --> 01:06:03,720
And you know, ultimately, the collision of truth and this fake narrative, I think is

939
01:06:03,720 --> 01:06:07,360
going to occur in physicians' offices, you know.

940
01:06:07,360 --> 01:06:13,240
And we have to be smarter about how we use those five or six minutes when you have a

941
01:06:13,240 --> 01:06:19,160
doctor who is trained to listen to you, you know, answer your questions.

942
01:06:19,160 --> 01:06:21,760
We have to ask the right questions, you know.

943
01:06:21,760 --> 01:06:24,600
We don't want to lecture to your doctors, say, oh, you don't know what you're doing

944
01:06:24,600 --> 01:06:26,960
and I would never get that shot and all this stuff.

945
01:06:26,960 --> 01:06:32,800
But like ask them, like, have you read the study or, you know, please tell me, you know,

946
01:06:32,800 --> 01:06:37,880
why if they're so safe, why can't I sue the vaccine manufacturer?

947
01:06:37,880 --> 01:06:39,400
Like what's a good reason for that?

948
01:06:39,400 --> 01:06:42,360
I mean, these are basic questions.

949
01:06:42,360 --> 01:06:47,080
And we have to understand that you're not going to convert a physician in one conversation,

950
01:06:47,080 --> 01:06:48,080
right?

951
01:06:48,080 --> 01:06:54,840
You just want to push the door open a little bit so it remains cracked so that the next

952
01:06:54,840 --> 01:06:59,480
person that comes in who asks the next question will push it open a little more.

953
01:06:59,480 --> 01:07:02,080
This is going to, you know, sadly, you know.

954
01:07:02,080 --> 01:07:04,880
And are there bridges that can be unburned, right?

955
01:07:04,880 --> 01:07:09,600
Like people say you can't unburn a bridge, but sometimes the burning is an illusion,

956
01:07:09,600 --> 01:07:11,240
right?

957
01:07:11,240 --> 01:07:17,960
If there is a lot of, you know, controlled, you know, Christopher Graves psychological,

958
01:07:17,960 --> 01:07:23,200
you know, experimentation types of nudge units, all of that, maybe there are bridges that

959
01:07:23,200 --> 01:07:25,280
aren't truly burned.

960
01:07:25,280 --> 01:07:34,080
And maybe what you can do is invite, you know, have an amnesty party, you know, call it patient

961
01:07:34,080 --> 01:07:38,320
physician jubilee or something like that.

962
01:07:38,320 --> 01:07:44,040
And you know, oh, goodness, I'm forgetting the doctor's name, but the one who made the

963
01:07:44,040 --> 01:07:45,040
apology.

964
01:07:45,040 --> 01:07:47,040
Oh, in the Atlantic?

965
01:07:47,040 --> 01:07:50,320
No, no, no, no, no, no.

966
01:07:50,320 --> 01:07:51,640
That was Emily Oster.

967
01:07:51,640 --> 01:07:52,640
That was an economist.

968
01:07:52,640 --> 01:07:57,120
I'm thinking there was a doctor and I've written about both these stories and I've compared

969
01:07:57,120 --> 01:07:58,840
the apologies, right?

970
01:07:58,840 --> 01:08:00,600
Like to me, to me, that's important, right?

971
01:08:00,600 --> 01:08:05,760
If somebody says I'm sorry, like that's not nearly as meaningful to me as what I see in

972
01:08:05,760 --> 01:08:09,440
their demeanor, character actions, right?

973
01:08:09,440 --> 01:08:15,440
Like those are the things that make the apology worth something, right?

974
01:08:15,440 --> 01:08:23,600
But there was a doctor, he's an RTE reader, you know, there was something going on in

975
01:08:23,600 --> 01:08:26,700
Florida, I think, and there were panels that were up.

976
01:08:26,700 --> 01:08:27,920
Maybe Lapidot was there.

977
01:08:27,920 --> 01:08:30,040
I think Dr. Malone was there.

978
01:08:30,040 --> 01:08:33,160
My friend David Weissman was on one of the TVs in the background, was one of those with

979
01:08:33,160 --> 01:08:38,720
all the TVs going, all kinds of people, but they showed the doctor and the doctor said,

980
01:08:38,720 --> 01:08:41,400
look, I'm sorry.

981
01:08:41,400 --> 01:08:46,760
I just want to say that because a lot of the things that I thought were true, I've determined

982
01:08:46,760 --> 01:08:47,760
now are wrong.

983
01:08:47,760 --> 01:08:51,560
And I can't remember exactly what he was referring to, whether it was public health measures,

984
01:08:51,560 --> 01:08:58,240
like masking and quarantining and all this stuff, or if it was more specific to the medicines.

985
01:08:58,240 --> 01:09:02,000
But one way or another, I felt like, oh, that's great.

986
01:09:02,000 --> 01:09:03,000
That was awesome.

987
01:09:03,000 --> 01:09:09,160
So it felt like this is somebody who crossed lines in a sense, and I don't even want to

988
01:09:09,160 --> 01:09:14,720
think of it as lines, just said, you know what, I'm questioning things and I'm sorry

989
01:09:14,720 --> 01:09:20,760
that I wasn't before, but my conclusions have steered since I started questioning.

990
01:09:20,760 --> 01:09:32,360
To have something like, could we do something like a date, like July 31st, 2023, physician-patient

991
01:09:32,360 --> 01:09:41,720
jubilee or something like that, and invite physicians to question anything between now

992
01:09:41,720 --> 01:09:47,160
and then, and then to sit down with their patients, almost like a town hall meeting,

993
01:09:47,160 --> 01:09:49,300
because this is that serious, right?

994
01:09:49,300 --> 01:09:56,760
This is that serious because people are talking about loss of trust of the public health system,

995
01:09:56,760 --> 01:09:59,720
of their doctors, things like that.

996
01:09:59,720 --> 01:10:10,040
I personally changed doctors myself, to a lot of people who did.

997
01:10:10,040 --> 01:10:11,360
Where do we go from here?

998
01:10:11,360 --> 01:10:14,400
Like you said, there are more and more people.

999
01:10:14,400 --> 01:10:16,560
It's not just lower perceived threat.

1000
01:10:16,560 --> 01:10:17,560
Absolutely.

1001
01:10:17,560 --> 01:10:18,560
You're right.

1002
01:10:18,560 --> 01:10:23,280
I hear discussions all the time.

1003
01:10:23,280 --> 01:10:27,920
Well, look, let's talk about all the positive things that are happening right now.

1004
01:10:27,920 --> 01:10:32,800
First of all, we have to understand that they're going to lose by attrition.

1005
01:10:32,800 --> 01:10:33,800
It's inevitable.

1006
01:10:33,800 --> 01:10:42,360
There's like how many people are out there saying, well, I resisted the vaccine for three

1007
01:10:42,360 --> 01:10:43,720
years, but now you've converted me.

1008
01:10:43,720 --> 01:10:46,160
I'm going to go get jabbed.

1009
01:10:46,160 --> 01:10:47,160
That's not going to happen.

1010
01:10:47,160 --> 01:10:49,160
Everyone's going to come over to our side eventually.

1011
01:10:49,160 --> 01:10:53,800
We have to be able to hasten it in a way so that we can still remain friends, honestly.

1012
01:10:53,800 --> 01:10:57,360
That's really an important part of this.

1013
01:10:57,360 --> 01:11:06,040
We talked about forums and get togethers.

1014
01:11:06,040 --> 01:11:09,080
A lot of this is going to happen, hopefully.

1015
01:11:09,080 --> 01:11:11,200
We have Bobby Kennedy running for president.

1016
01:11:11,200 --> 01:11:14,880
This is going to put this issue right up there.

1017
01:11:14,880 --> 01:11:19,920
Obviously lots of media is not going to cover it, but there are going to be town halls about

1018
01:11:19,920 --> 01:11:21,860
this.

1019
01:11:21,860 --> 01:11:24,880
Those things are going to happen.

1020
01:11:24,880 --> 01:11:26,560
Obviously he can't do it all himself.

1021
01:11:26,560 --> 01:11:30,600
All of us have to be representatives of that position that are willing to speak up in those

1022
01:11:30,600 --> 01:11:31,600
kinds of formats.

1023
01:11:31,600 --> 01:11:32,600
Just the other day-

1024
01:11:32,600 --> 01:11:35,400
And it refers to our own positions.

1025
01:11:35,400 --> 01:11:40,080
They don't have to all be the same, but just so long as we're getting back to questioning

1026
01:11:40,080 --> 01:11:48,280
medicine and science and thinking and not just following the flock.

1027
01:11:48,280 --> 01:11:56,540
Just the other day I was in one of the facilities I work at and they had just removed the requirement

1028
01:11:56,540 --> 01:12:05,200
for people to be COVID-19 tested before coming in for an elective procedure.

1029
01:12:05,200 --> 01:12:09,800
I asked a group of three nurses that didn't have anything to do and I said, what do you

1030
01:12:09,800 --> 01:12:10,800
think about this?

1031
01:12:10,800 --> 01:12:12,480
Do you feel safe that we're not testing anymore?

1032
01:12:12,480 --> 01:12:14,720
They're like, no, I think we're done.

1033
01:12:14,720 --> 01:12:17,840
I don't really believe in the testing.

1034
01:12:17,840 --> 01:12:19,920
We're still wearing masks.

1035
01:12:19,920 --> 01:12:24,120
You walk around the hospital, it doesn't matter if they're with patients or not, you have

1036
01:12:24,120 --> 01:12:26,400
to wear a mask.

1037
01:12:26,400 --> 01:12:28,640
And I said, so what do you think about this mask thing?

1038
01:12:28,640 --> 01:12:30,280
Do you think we can take off our masks now?

1039
01:12:30,280 --> 01:12:31,880
Do you guys feel safe?

1040
01:12:31,880 --> 01:12:36,960
And they said, yeah, I wish we would drop the masks.

1041
01:12:36,960 --> 01:12:41,080
And then I said, so what do you think about getting a booster?

1042
01:12:41,080 --> 01:12:42,960
Are you still behind that?

1043
01:12:42,960 --> 01:12:50,040
And they're like, I don't really know about that because I've heard that one of my friends

1044
01:12:50,040 --> 01:12:53,760
had a really bad reaction and I didn't feel good afterwards.

1045
01:12:53,760 --> 01:13:01,880
And then I said, do you understand that there's probably, I don't know, what is it now, 1.5

1046
01:13:01,880 --> 01:13:06,800
million reports and VAERS and 37,000 deaths?

1047
01:13:06,800 --> 01:13:10,560
And the three of them just looked up and said, what's VAERS?

1048
01:13:10,560 --> 01:13:14,040
And I said, well, it's the Vaccine Adverse Event Reporting System.

1049
01:13:14,040 --> 01:13:18,640
And immediately, without even prompting, one of them goes up to a computer and looks it

1050
01:13:18,640 --> 01:13:22,120
up and they start looking at the reports and they're like, oh my God, you guys, come here,

1051
01:13:22,120 --> 01:13:23,200
look at this.

1052
01:13:23,200 --> 01:13:31,880
And as soon as they saw it, like on the internet, which means it's true, suddenly it just confirmed

1053
01:13:31,880 --> 01:13:33,720
all of these suspicions that they had had.

1054
01:13:33,720 --> 01:13:37,440
It's like, oh my God, that person was actually, it was a vaccine injury.

1055
01:13:37,440 --> 01:13:39,320
I can't believe this is what's going on.

1056
01:13:39,320 --> 01:13:42,920
So I'm just saying that the tide is turning.

1057
01:13:42,920 --> 01:13:48,560
And my experience at this Congress confirmed that.

1058
01:13:48,560 --> 01:13:50,480
People were coming up to me and saying, yeah, that's a good point.

1059
01:13:50,480 --> 01:13:52,840
And we don't know enough about this.

1060
01:13:52,840 --> 01:14:01,120
And the very, very last question of the symposium is with Gregory Poland moderating.

1061
01:14:01,120 --> 01:14:09,480
They were talking about, oh, markers for vaccine durability.

1062
01:14:09,480 --> 01:14:13,080
They have identified the problem is like people don't want to get another shot every three

1063
01:14:13,080 --> 01:14:14,080
months.

1064
01:14:14,080 --> 01:14:15,080
How can we make these vaccines?

1065
01:14:15,080 --> 01:14:19,360
Or at least how do we have a marker for whether or not it's going to last for more than a

1066
01:14:19,360 --> 01:14:20,840
few months?

1067
01:14:20,840 --> 01:14:25,200
And there's some basic science that was being thrown around and ideas.

1068
01:14:25,200 --> 01:14:31,640
And then one of the presenters said, we found something very interesting in the early days

1069
01:14:31,640 --> 01:14:35,000
of the pandemic in 2020 before the vaccine.

1070
01:14:35,000 --> 01:14:40,720
Young infants who got COVID, we followed them for two or three years.

1071
01:14:40,720 --> 01:14:43,600
They still have remarkably robust immunity.

1072
01:14:43,600 --> 01:14:47,640
Infants, maybe there's a clue.

1073
01:14:47,640 --> 01:14:51,920
Maybe there's a clue in there that could help us figure out a marker for this.

1074
01:14:51,920 --> 01:14:57,960
And my colleague, Elizabeth Mumper, saw the opportunity and said, OK, look.

1075
01:14:57,960 --> 01:15:01,680
And she asked the very last question of the entire week.

1076
01:15:01,680 --> 01:15:11,800
And she said, can you please explain to me why I should be advocating a six-month-old

1077
01:15:11,800 --> 01:15:14,400
getting the vaccine?

1078
01:15:14,400 --> 01:15:20,760
If you are now telling me that if they get COVID, they're going to be protected, your

1079
01:15:20,760 --> 01:15:22,520
vaccines don't work.

1080
01:15:22,520 --> 01:15:29,120
We have no idea what the long-term effects of lipid nanoparticles are in these babies.

1081
01:15:29,120 --> 01:15:34,840
And the survivability is 99.9997%.

1082
01:15:34,840 --> 01:15:35,840
Convince me.

1083
01:15:35,840 --> 01:15:38,080
I mean, that's exactly what she said.

1084
01:15:38,080 --> 01:15:41,120
And then the presenter said, I don't know.

1085
01:15:41,120 --> 01:15:43,280
I don't have an answer to that.

1086
01:15:43,280 --> 01:15:47,480
And then she said, anybody else up there want to tackle the question?

1087
01:15:47,480 --> 01:15:52,640
And then someone said, oh, well, you know, so, doctor, look, you've got this misconception

1088
01:15:52,640 --> 01:15:56,960
that it's better to get COVID than the vaccine.

1089
01:15:56,960 --> 01:16:01,240
And you don't know what the long-term side effects of COVID are.

1090
01:16:01,240 --> 01:16:04,200
And then Poland ended the conversation right there.

1091
01:16:04,200 --> 01:16:07,640
And it's like, holy cow, you missed the whole point.

1092
01:16:07,640 --> 01:16:10,520
We know that natural immunity is good.

1093
01:16:10,520 --> 01:16:11,960
The vaccine wanes.

1094
01:16:11,960 --> 01:16:13,600
The survivability is excellent.

1095
01:16:13,600 --> 01:16:18,040
And we have no idea about the long-term effects of the vaccine.

1096
01:16:18,040 --> 01:16:22,120
Yet your counterargument is, well, we don't know what the long-term effects of COVID are

1097
01:16:22,120 --> 01:16:23,120
either.

1098
01:16:23,120 --> 01:16:26,600
How does that justify inoculating babies?

1099
01:16:26,600 --> 01:16:30,160
And once again, people came up to her and said, wow, that's a really good question.

1100
01:16:30,160 --> 01:16:32,160
I don't think he answered the question.

1101
01:16:32,160 --> 01:16:34,440
And we're like, yeah, he didn't.

1102
01:16:34,440 --> 01:16:38,000
And people should stop and think also, wait a minute.

1103
01:16:38,000 --> 01:16:43,400
One of these forms of immunity lasts for one, two decades.

1104
01:16:43,400 --> 01:16:49,200
We know that the people who had the original SARS had immunity like 17 years later.

1105
01:16:49,200 --> 01:16:50,200
Right?

1106
01:16:50,200 --> 01:16:51,200
They probably still do.

1107
01:16:51,200 --> 01:16:52,200
Right?

1108
01:16:52,200 --> 01:16:54,200
It's probably 20 years on.

1109
01:16:54,200 --> 01:16:57,880
Why is it that a vaccination seems to wane after four months?

1110
01:16:57,880 --> 01:17:01,480
When people start asking that question, I think that's when they're going to understand

1111
01:17:01,480 --> 01:17:04,880
the whole 14 days miscategorization.

1112
01:17:04,880 --> 01:17:08,240
Then they're going to realize that there was never any efficacy.

1113
01:17:08,240 --> 01:17:09,240
Right.

1114
01:17:09,240 --> 01:17:10,400
That's my opinion.

1115
01:17:10,400 --> 01:17:11,680
That's my strong belief.

1116
01:17:11,680 --> 01:17:16,800
I think that it's right there in the numbers that if you flip those people to the vaccinated

1117
01:17:16,800 --> 01:17:22,520
pool, then suddenly you have zero or probably negative efficacy from the start.

1118
01:17:22,520 --> 01:17:24,360
It's not waning efficacy.

1119
01:17:24,360 --> 01:17:25,520
It's waning bias.

1120
01:17:25,520 --> 01:17:26,520
It's waning miscategorization.

1121
01:17:26,520 --> 01:17:29,520
I think you're right, Matthew.

1122
01:17:29,520 --> 01:17:30,520
Absolutely.

1123
01:17:30,520 --> 01:17:33,960
I've read a lot of your stack articles on that.

1124
01:17:33,960 --> 01:17:37,160
I see exactly what you're saying.

1125
01:17:37,160 --> 01:17:40,920
But again, you have to start someplace with these people.

1126
01:17:40,920 --> 01:17:46,120
You start off saying that there is no efficacy, healthy user bias and all this stuff.

1127
01:17:46,120 --> 01:17:47,780
They're not going to hear it.

1128
01:17:47,780 --> 01:17:52,080
Start someplace where they feel confident and you lead them another place with those

1129
01:17:52,080 --> 01:17:53,080
kinds of things.

1130
01:17:53,080 --> 01:17:54,080
Here's something interesting.

1131
01:17:54,080 --> 01:18:01,000
I know we've got to wind down soon, but I went to another presentation by a researcher

1132
01:18:01,000 --> 01:18:07,520
who was talking about lipid nanoparticles and delivery systems of these medicines.

1133
01:18:07,520 --> 01:18:18,240
She was saying that what they found was the design of the LNP is very important because

1134
01:18:18,240 --> 01:18:24,160
you can make it... What's the word she used?

1135
01:18:24,160 --> 01:18:27,120
You can make it so that it acts as an adjuvant.

1136
01:18:27,120 --> 01:18:30,560
It incites an inflammatory response.

1137
01:18:30,560 --> 01:18:35,840
The point here is that that's the kind of LNP you want when you're delivering a vaccine.

1138
01:18:35,840 --> 01:18:40,280
That is not what you want when you're delivering a chemotherapeutic agent because you don't

1139
01:18:40,280 --> 01:18:41,280
want the inflammation.

1140
01:18:41,280 --> 01:18:45,760
You just want the drug to get there.

1141
01:18:45,760 --> 01:18:48,760
Anyway, here's the thing.

1142
01:18:48,760 --> 01:18:50,920
She gives a presentation and I talked to her.

1143
01:18:50,920 --> 01:18:56,480
I said, look, do you have any information about how you can modulate the LNP so that

1144
01:18:56,480 --> 01:18:59,760
you can direct where it ends up in the body?

1145
01:18:59,760 --> 01:19:04,640
She said, oh, it always gets taken up by your lymphatic tissues through the spleen and liver.

1146
01:19:04,640 --> 01:19:05,640
That's where it goes.

1147
01:19:05,640 --> 01:19:07,520
I said, well, what about the brain?

1148
01:19:07,520 --> 01:19:08,920
Does it go there?

1149
01:19:08,920 --> 01:19:10,600
She said, yes, that's true.

1150
01:19:10,600 --> 01:19:11,600
It does go there.

1151
01:19:11,600 --> 01:19:19,520
I said, can you make sure that doesn't happen?

1152
01:19:19,520 --> 01:19:20,520
What do you know about that?

1153
01:19:20,520 --> 01:19:26,840
She said, well, we have no idea, but that's a really important topic of our research.

1154
01:19:26,840 --> 01:19:28,600
That's put it all together for me.

1155
01:19:28,600 --> 01:19:38,320
You know, clearly the LNPs that were used in these formulations were immunogenic or

1156
01:19:38,320 --> 01:19:39,320
inflammatory.

1157
01:19:39,320 --> 01:19:41,600
Of course, they did that.

1158
01:19:41,600 --> 01:19:43,300
That's how they get the response.

1159
01:19:43,300 --> 01:19:49,240
We know that it goes to the brain and we've got scores, if not thousands of neurologic

1160
01:19:49,240 --> 01:19:51,800
... She wasn't going to say it if you didn't

1161
01:19:51,800 --> 01:19:52,800
bring it up.

1162
01:19:52,800 --> 01:19:53,800
No, she didn't say that at all.

1163
01:19:53,800 --> 01:19:56,040
Yeah, I had to bring it up.

1164
01:19:56,040 --> 01:20:01,560
It was one of those presentations where she... 20 minutes long, 30 slides full of data.

1165
01:20:01,560 --> 01:20:05,160
I don't even know what she's saying, but when she talked about that, I was like, okay, that's

1166
01:20:05,160 --> 01:20:07,920
my question.

1167
01:20:07,920 --> 01:20:09,640
Here we have it.

1168
01:20:09,640 --> 01:20:12,360
You have the mechanism of inflammation.

1169
01:20:12,360 --> 01:20:14,960
You know that it goes across the blood brain barrier.

1170
01:20:14,960 --> 01:20:25,480
You have the chairman of the entire symposium with some sort of neurologic issue with the

1171
01:20:25,480 --> 01:20:29,120
acoustic nerve or whatever is causing the stuff.

1172
01:20:29,120 --> 01:20:32,000
How much more do you need, honestly?

1173
01:20:32,000 --> 01:20:35,880
You have to ask the probing questions, but this was just a big show, honestly.

1174
01:20:35,880 --> 01:20:43,240
It was like, you know, it was a mind game, but most of the people there didn't know about

1175
01:20:43,240 --> 01:20:48,160
all of these things, but they're open to hearing it.

1176
01:20:48,160 --> 01:20:49,160
Interesting.

1177
01:20:49,160 --> 01:20:57,160
I'm going to think on this a little bit because I'm so glad to hear your report on all of

1178
01:20:57,160 --> 01:21:04,160
this because it's an update for me as to how it is we might move forward, possibly how

1179
01:21:04,160 --> 01:21:07,480
I might be able to make my time more valuable also.

1180
01:21:07,480 --> 01:21:17,200
But gosh, when I hear this, I think this is something that should go on with every event,

1181
01:21:17,200 --> 01:21:18,200
perhaps.

1182
01:21:18,200 --> 01:21:26,160
I mean, and you had mentioned an idea to me, and maybe we'll talk about it after the show.

1183
01:21:26,160 --> 01:21:27,880
Maybe revisit or discuss that idea.

1184
01:21:27,880 --> 01:21:32,320
I think I have a better sense of your intention with that.

1185
01:21:32,320 --> 01:21:34,560
I have a better sense of what you brought up.

1186
01:21:34,560 --> 01:21:37,440
But any other thoughts?

1187
01:21:37,440 --> 01:21:41,120
Gosh, you know, where does this leave us?

1188
01:21:41,120 --> 01:21:44,440
Actually, you know, maybe I want to do this.

1189
01:21:44,440 --> 01:21:51,960
When I brought up the idea of something like a doctor-patient jubilee, I do want to say

1190
01:21:51,960 --> 01:21:53,200
this.

1191
01:21:53,200 --> 01:22:00,240
I think that there are different degrees of probably criminal activity that have taken

1192
01:22:00,240 --> 01:22:02,680
place.

1193
01:22:02,680 --> 01:22:10,960
But I think that we have to be as discerning as possible as to where we place the blame,

1194
01:22:10,960 --> 01:22:19,000
especially if the amount of pressure that was put on physicians, you know, there were

1195
01:22:19,000 --> 01:22:25,000
some who seemed almost gleeful about the entire process and procedure, but some who probably

1196
01:22:25,000 --> 01:22:27,600
just went along to get along, right?

1197
01:22:27,600 --> 01:22:30,960
I think that we're going to have to be discerning in our judgment.

1198
01:22:30,960 --> 01:22:37,680
But there are times when I think the game theory suggests that you find a way to walk

1199
01:22:37,680 --> 01:22:45,160
away from the situation by, I don't know, separating the way that you deal with one

1200
01:22:45,160 --> 01:22:46,640
group of people from the other.

1201
01:22:46,640 --> 01:22:51,480
There are certain people that should probably be held to account, if possible, under all

1202
01:22:51,480 --> 01:22:53,680
circumstances.

1203
01:22:53,680 --> 01:23:00,520
But there are people who just want to be Americans, you know, who just want to participate in

1204
01:23:00,520 --> 01:23:01,520
their noble profession.

1205
01:23:01,520 --> 01:23:05,360
And, you know, there was a substack this morning.

1206
01:23:05,360 --> 01:23:11,480
I can't remember who wrote it, but who said, look, the doctors are traumatized.

1207
01:23:11,480 --> 01:23:12,480
That was mine.

1208
01:23:12,480 --> 01:23:13,480
I think it was.

1209
01:23:13,480 --> 01:23:14,480
Oh, that was you.

1210
01:23:14,480 --> 01:23:15,480
Okay.

1211
01:23:15,480 --> 01:23:16,480
Okay.

1212
01:23:16,480 --> 01:23:20,640
And I maybe I was catching up on your articles.

1213
01:23:20,640 --> 01:23:27,120
But yeah, I think, yeah, really good subsexties, by the way.

1214
01:23:27,120 --> 01:23:34,000
Yeah, I think that you hit the nail on the head, though, with that observation.

1215
01:23:34,000 --> 01:23:39,280
You know, we have to consider that this is something that is so unique, that was done

1216
01:23:39,280 --> 01:23:42,520
to all of us at once.

1217
01:23:42,520 --> 01:23:49,640
And find a way to let those who, you know, those people who want to untangle, like I

1218
01:23:49,640 --> 01:23:55,840
said, if we pick the date, like July 31st, and said, who's willing to come to the room

1219
01:23:55,840 --> 01:24:00,880
and have a conversation, if not tell us you're on our side?

1220
01:24:00,880 --> 01:24:01,880
Right?

1221
01:24:01,880 --> 01:24:05,080
Like, either one of those is a step of good faith.

1222
01:24:05,080 --> 01:24:06,800
Yes, the very least.

1223
01:24:06,800 --> 01:24:07,800
Right?

1224
01:24:07,800 --> 01:24:12,040
Those are the people that I think, you know, you can embrace again.

1225
01:24:12,040 --> 01:24:13,040
Yeah.

1226
01:24:13,040 --> 01:24:14,040
Wow.

1227
01:24:14,040 --> 01:24:18,680
Yeah, I I'm encouraged.

1228
01:24:18,680 --> 01:24:19,800
I like what you're saying here.

1229
01:24:19,800 --> 01:24:26,320
So you're suggesting that we spread the spread the word and about and I'm throwing it out

1230
01:24:26,320 --> 01:24:27,320
there.

1231
01:24:27,320 --> 01:24:30,720
You know, it was just an idea that sprang into my head because we were talking, you know?

1232
01:24:30,720 --> 01:24:35,480
Yeah, I think none of us none of us know what to think.

1233
01:24:35,480 --> 01:24:36,480
Right.

1234
01:24:36,480 --> 01:24:38,440
I mean, it's been so crazy.

1235
01:24:38,440 --> 01:24:40,880
Well, look, you brought up two really good points.

1236
01:24:40,880 --> 01:24:46,160
The first is those guys who are managing the narrative, you know, the pro vaccine narrative,

1237
01:24:46,160 --> 01:24:48,040
they don't want dialogue.

1238
01:24:48,040 --> 01:24:51,480
So the idea of dialogue is automatically good.

1239
01:24:51,480 --> 01:24:52,480
Right.

1240
01:24:52,480 --> 01:24:54,840
We have to assume that that's that's probably going to work and they know it's going to

1241
01:24:54,840 --> 01:24:55,840
work.

1242
01:24:55,840 --> 01:24:57,640
That's why they don't want that.

1243
01:24:57,640 --> 01:25:02,320
And the other point you made that I want to chime in on slips my mind now.

1244
01:25:02,320 --> 01:25:06,640
Well, I should have went with that one first.

1245
01:25:06,640 --> 01:25:12,720
Oh, well, what did you just say?

1246
01:25:12,720 --> 01:25:19,040
Well, we can we can pick it back up.

1247
01:25:19,040 --> 01:25:20,040
Right.

1248
01:25:20,040 --> 01:25:21,040
We're talking.

1249
01:25:21,040 --> 01:25:23,040
So so all good.

1250
01:25:23,040 --> 01:25:26,480
Well, thanks for coming and sharing this experience with us.

1251
01:25:26,480 --> 01:25:35,440
I think that's this is so uniquely valuable and probably go ahead.

1252
01:25:35,440 --> 01:25:47,000
I think that when we our prize is to punish the wrongdoers, we lose a lot of momentum

1253
01:25:47,000 --> 01:25:52,840
and ability to actually change things because, you know, eventually, hopefully people will

1254
01:25:52,840 --> 01:25:55,320
be brought to task, the ones who deserve to be punished.

1255
01:25:55,320 --> 01:25:57,040
But we have to stop this.

1256
01:25:57,040 --> 01:26:02,680
And you know, that's the first goal is to like stop doing this as opposed to we need

1257
01:26:02,680 --> 01:26:03,920
to punish the people who are doing this.

1258
01:26:03,920 --> 01:26:05,720
We have to stop it first.

1259
01:26:05,720 --> 01:26:07,680
And that should be our priority.

1260
01:26:07,680 --> 01:26:14,280
Once we stop it and and cease the damage, then we can start picking up the pieces and

1261
01:26:14,280 --> 01:26:21,440
find out, you know, who who are really the malevolent ones behind this.

1262
01:26:21,440 --> 01:26:24,280
And you know, look, I'm not into punishing people.

1263
01:26:24,280 --> 01:26:26,560
I that's somewhat somebody else can do that.

1264
01:26:26,560 --> 01:26:29,160
I'm not saying that they don't deserve some sort of retribution.

1265
01:26:29,160 --> 01:26:31,200
But you know, that's not my interest.

1266
01:26:31,200 --> 01:26:35,160
My interest is to stop this.

1267
01:26:35,160 --> 01:26:38,680
First Yeah, first and foremost.

1268
01:26:38,680 --> 01:26:39,680
Yeah.

1269
01:26:39,680 --> 01:26:45,080
And and, you know, to a large extent, the system is is the people in many ways.

1270
01:26:45,080 --> 01:26:48,560
And if you know, if we make the system better, we make people better.

1271
01:26:48,560 --> 01:26:54,760
You know, not not exactly, but in a sense, you know, the incentives determine it at least

1272
01:26:54,760 --> 01:26:58,040
the flow of the outcome precisely.

1273
01:26:58,040 --> 01:27:01,720
So well, thanks so much for joining us, Madaba.

1274
01:27:01,720 --> 01:27:08,160
And it's always a pleasure to speak with you and learn something every time I'm looking

1275
01:27:08,160 --> 01:27:13,400
at any questions from the audience before we cut down.

1276
01:27:13,400 --> 01:27:15,720
We still got we've got a few dozen watchers here.

1277
01:27:15,720 --> 01:27:18,480
We have a few dozen in the different channels.

1278
01:27:18,480 --> 01:27:19,480
What's that?

1279
01:27:19,480 --> 01:27:20,480
Is it a few dozen?

1280
01:27:20,480 --> 01:27:21,480
That's good.

1281
01:27:21,480 --> 01:27:25,640
Well, we'll go ahead and cut here.

1282
01:27:25,640 --> 01:27:27,040
Thanks so much for joining us.

1283
01:27:27,040 --> 01:27:34,760
And everybody go check out Madaba's substack is fairly new.

1284
01:27:34,760 --> 01:27:37,000
And it's called an insult to intuition.

1285
01:27:37,000 --> 01:27:39,240
Go check that out.

1286
01:27:39,240 --> 01:27:41,680
You've got to look through this from the belly of the beast article.

1287
01:27:41,680 --> 01:27:46,400
I mean, this is we've talked about a lot of it here, but he's got a lot of more information

1288
01:27:46,400 --> 01:27:47,400
there.

1289
01:27:47,400 --> 01:27:49,760
So thanks, everybody.

1290
01:27:49,760 --> 01:27:51,560
And we will see you again soon.

1291
01:27:51,560 --> 01:27:52,560
We'll see you tomorrow.

1292
01:27:52,560 --> 01:28:18,400
Liam and I are going to be hosting JJ Cooey, and we hope you join us in.

1293
01:28:18,400 --> 01:28:24,080
Bye.