Stream.Transcripts/twitch/1947878197 (2023-10-10) - Denis Rancourt PhD -- 10 Oct 2023/1947878197 (2023-10-10) - Denis Rancourt PhD -- 10 Oct 2023 -- Gigaohm Biological High Resistance Low Noise Information Brief.vtt

WEBVTT

00:00.000 --> 00:05.520
All right, hopefully this sound check will be better.

00:05.520 --> 00:10.740
We are back with Denny Rancourt from Canada talking about the Lancet paper from September

00:10.740 --> 00:17.760
of 2022, which has basically been lampooned by giving it the Nobel Prize as a backing.

00:17.760 --> 00:24.620
And so now drawing attention to its analysis, Denny has decided to take it upon himself

00:24.620 --> 00:27.760
to see what this analysis really means in real terms.

00:27.760 --> 00:31.000
And so he was just giving us an introduction and we were out of sync.

00:31.000 --> 00:34.040
Still out of sync, it says, well, whatever, we're going to keep going because I'm recording

00:34.040 --> 00:35.040
fine.

00:35.040 --> 00:37.640
So go ahead, Denny, take it away.

00:37.640 --> 00:38.640
Okay.

00:38.640 --> 00:45.680
Well, so as I was saying, the Nobel Prize is a political propaganda instrument.

00:45.680 --> 00:49.000
And that's the general rule.

00:49.000 --> 00:57.480
And when it was announced for some aspects of the developments in the lab that led to

00:57.480 --> 01:04.640
the, I guess, the development of the vaccine that was then injected into billions of times

01:04.640 --> 01:12.080
into people's arms, when that Nobel Prize was awarded, everyone, virtually everyone in

01:12.080 --> 01:20.400
the mainstream sort of sounding echo chamber was saying that this vaccine had saved millions

01:20.400 --> 01:24.160
of lives and tens of millions of lives.

01:24.160 --> 01:30.520
So you had the New York Times saying that blasting it was all front page news and everyone

01:30.520 --> 01:36.560
who would mention it in these leading media like the New York Times, the Washington Post

01:36.560 --> 01:37.560
and so on.

01:37.560 --> 01:38.560
I made a list of them.

01:38.560 --> 01:42.080
I actually cited them in my article there.

01:42.080 --> 01:45.120
They would all talk about these millions of lives that were saved.

01:45.120 --> 01:52.160
And I thought, this is crazy how, you know, there has never been a clinical trial that

01:52.160 --> 01:57.680
has shown or demonstrated or even suggested, I would argue even suggested that you could

01:57.680 --> 02:04.280
reasonably take to suggest that this vaccine had ever saved a life and could save lives

02:04.280 --> 02:08.640
because mortality was not an end point in these trials.

02:08.640 --> 02:13.100
So this was completely outside of science.

02:13.100 --> 02:15.280
This was coming from somewhere else.

02:15.280 --> 02:19.120
And when you look at what the somewhere else was, where was this coming from?

02:19.120 --> 02:23.560
Where were they getting this number of a million or 10 million lives saved?

02:23.560 --> 02:29.600
Well, it turns out that science news, science is a leading science journal and they have

02:29.600 --> 02:36.400
a news section and science news talked about the Nobel and referred to the scientific paper

02:36.400 --> 02:41.360
that had calculated this tens of millions of lives saved.

02:41.360 --> 02:44.760
And that was the paper that you mentioned.

02:44.760 --> 02:51.400
And so they made that link and we went in and looked at this paper.

02:51.400 --> 02:56.200
And it turns out that the paper is just, well, first of all, the research is funded by Gates

02:56.200 --> 02:59.200
and the World Health Organization, et cetera.

02:59.200 --> 03:00.520
That's clear.

03:00.520 --> 03:03.660
And the paper is a modeling paper.

03:03.660 --> 03:10.720
And I would argue that these people, this is not, this is the opposite of good science,

03:10.720 --> 03:17.200
okay, because they did not check to see if their theoretical calculation or prediction

03:17.200 --> 03:23.040
or, you know, counter view as they call it, they didn't check to see if it actually stuck

03:23.040 --> 03:29.640
with something that was reasonable and realistic and could actually happen in the real world.

03:29.640 --> 03:31.120
They didn't make that verification.

03:31.120 --> 03:33.680
They just came up with a number and then reported it.

03:33.680 --> 03:37.320
So I thought that this is really nasty stuff.

03:37.320 --> 03:41.720
And so we looked in detail at how they had done it and what they did exactly.

03:41.720 --> 03:45.000
And we thought, my God, this is complete fabrication.

03:45.000 --> 03:46.000
It's garbage.

03:46.000 --> 03:47.000
Now, let me be clear.

03:47.000 --> 03:52.720
I don't mean that the actual mathematical calculations in the paper are incorrect.

03:52.720 --> 04:00.160
And I don't mean that the principle of how they try to calculate this is incorrect.

04:00.160 --> 04:06.400
What I mean is that they are making assumptions about what to input into that model that are

04:06.400 --> 04:07.400
just wild.

04:07.400 --> 04:11.000
Like, why would you believe that these inputs are valid?

04:11.000 --> 04:16.400
And also, if you do believe that they're valid because Pharma is telling you that they're

04:16.400 --> 04:22.600
valid and so on, then when you calculate the consequence of those assumptions and you

04:22.600 --> 04:26.840
get ridiculous numbers, why don't you question yourself?

04:26.840 --> 04:29.860
You have to go back and say, well, what the heck was that?

04:29.860 --> 04:31.160
How is this possible?

04:31.160 --> 04:37.680
I'm doing a proper calculation with known science and I'm doing it mathematically correctly.

04:37.680 --> 04:41.960
I'm not making, you know, there are no bugs in my program and not making any errors.

04:41.960 --> 04:46.680
And I input what Pharma claims is the efficacy of these vaccines.

04:46.680 --> 04:55.840
And I input what according to testing of people and so on would have been the prevalence

04:55.840 --> 05:00.840
of people who are susceptible to being infected at various times during the pandemic.

05:00.840 --> 05:02.920
I input all of that.

05:02.920 --> 05:08.520
And I end up with a number of people that would have been saved by this huge vaccine rollout

05:08.520 --> 05:13.960
that was actually done in the real society that is just a ridiculous number, tens of

05:13.960 --> 05:16.160
millions of people that would have been saved.

05:16.160 --> 05:23.000
So what we wanted to do in our paper is we wanted to show graphically, if this was true,

05:23.000 --> 05:24.000
what would it mean?

05:24.000 --> 05:25.080
What would it look like?

05:25.080 --> 05:30.520
In terms of hard data, when you're looking at all cost mortality itself as a function

05:30.520 --> 05:36.440
of time in any given country, in terms of hard data, what they're saying, what would

05:36.440 --> 05:38.160
it look like?

05:38.160 --> 05:43.760
And so we made a bunch of graphs to illustrate what it would look like if you actually believed

05:43.760 --> 05:50.080
in their calculation and you just put it on the graph of what that would mean in terms

05:50.080 --> 05:51.840
of all cost mortality.

05:51.840 --> 05:54.240
This is the kind of thing that you get.

05:54.240 --> 05:59.040
Now we started in the paper, we did, in fact, we did 95 countries.

05:59.040 --> 06:01.800
So we did this calculation for 95 countries.

06:01.800 --> 06:06.760
You see, the original authors, Watson et al, predicted for many, many countries, more

06:06.760 --> 06:13.000
than 95, in each case, how many lives would have been saved in each of those countries.

06:13.000 --> 06:20.440
We had data for 95 countries, so we applied their method and their number to see what

06:20.440 --> 06:22.400
it would give on these graphs.

06:22.400 --> 06:27.160
And so we started with the United States because it's a very large jurisdiction that

06:27.200 --> 06:31.280
there's good data and it was spectacular what happened in the United States.

06:31.280 --> 06:36.120
So when I show a graph like the one you're showing now, the top panel is actual all

06:36.120 --> 06:40.160
cost mortality where you have the Y scale starting at zero.

06:40.160 --> 06:47.360
So you actually see the number of deaths starting at zero by week in the USA for the whole country,

06:47.360 --> 06:48.960
all ages.

06:48.960 --> 06:53.400
And you see that as soon as the pandemic is announced, there's a faint vertical line there,

06:53.400 --> 06:59.360
you get a peak that surges up in the United States like that, which was due to people

06:59.360 --> 07:03.120
being killed in hospitals by very aggressive protocols and things like that.

07:03.120 --> 07:10.320
But the point is, the high peaks in mortality are unprecedented in recent history.

07:10.320 --> 07:16.080
So you get the usual gradual seasonal variations before, but then during the COVID period,

07:16.080 --> 07:18.840
you get this huge structure and a lot of peaks.

07:18.840 --> 07:24.400
And some of those peaks are directly related to increases in vaccination and so on.

07:24.400 --> 07:28.920
And so you can see the cumulative vaccination curve there on the same graph.

07:28.920 --> 07:30.840
We put it there for comparison.

07:30.840 --> 07:37.680
And what they're saying amounts to the red line that we put on the graph there.

07:37.680 --> 07:42.360
So in other words, the all cost mortality, if what they're saying is true,

07:42.360 --> 07:46.600
would have not been the blue line, which is the actual measured value,

07:46.600 --> 07:50.560
but would have been this red line if what they're saying is true.

07:50.560 --> 07:56.240
So the mortality by week would have risen to that kind of level in the United States,

07:56.240 --> 07:57.600
which is a huge level.

07:57.600 --> 08:02.520
You already have huge, huge peaks during the COVID period,

08:02.520 --> 08:07.720
but they're talking about going way beyond that to these very high levels, you see.

08:07.720 --> 08:14.560
And you can represent the same thing for the United States as an excess all cost mortality.

08:14.600 --> 08:21.120
So where you take out the regular seasonal pattern and you just see in terms of an excess,

08:21.120 --> 08:27.040
compared to the historic trend recently in the last five years, what these peaks would look like.

08:27.040 --> 08:30.360
And so you get just the excess compared to the seasonal trend.

08:30.360 --> 08:33.000
You see all that structured during the COVID period.

08:33.000 --> 08:37.600
And you see this much higher mortality that they say would have occurred

08:37.600 --> 08:43.440
if we didn't have these wonderful vaccines to bring it down to those levels there, you see.

08:43.440 --> 08:47.200
But I mean, then we really averted a disaster.

08:47.200 --> 08:50.760
Yes. Yeah, that's the point is that we averted.

08:50.760 --> 08:54.840
I mean, if we hadn't rolled out these vaccines like we did there,

08:54.840 --> 09:01.840
oh my God, it would have been so much worse than the horrible calamity that it was in the US, you see.

09:01.840 --> 09:06.320
But this illustration, we started with the US because it's such a big jurisdiction.

09:06.320 --> 09:07.360
There's good data.

09:07.360 --> 09:10.800
But when you do this for other countries, it's even more striking.

09:10.800 --> 09:13.840
It's just unbelievable.

09:13.840 --> 09:19.720
So maybe we could show just a few more countries to show you how ridiculous what they're proposing is.

09:19.720 --> 09:24.360
Because if you move just to Canada, which is the next one, for example,

09:24.360 --> 09:30.320
the all cost mortality excesses during the COVID period in Canada are much smaller than in the US.

09:30.320 --> 09:34.280
That's because you didn't have New York City anywhere in Canada.

09:34.280 --> 09:35.160
That's right.

09:35.160 --> 09:40.440
And the virus didn't cross the border into Canada hardly at all.

09:40.680 --> 09:43.120
It didn't dare to cross the border.

09:43.120 --> 09:47.520
And so you had this very low mortality in Canada comparatively.

09:47.520 --> 09:52.120
And what they're saying is that those are the deaths that would have occurred if we hadn't vaccinated.

09:52.120 --> 09:54.280
So you have to wrap your head around this.

09:54.280 --> 10:00.360
What they're seeing in Canada, if you look at all cost mortality, it's basically a flat line.

10:00.360 --> 10:06.360
And they're saying if we hadn't vaccinated right when we started vaccinating,

10:06.360 --> 10:09.400
there would have been this huge mega surge in all cost mortality.

10:09.400 --> 10:11.640
And that's what we saved you from.

10:11.640 --> 10:18.720
So they have to argue that excess all cost mortality and all cost mortality itself

10:18.720 --> 10:23.320
would have had to surge precisely when they started vaccinating.

10:23.320 --> 10:25.240
And we saved you from that.

10:25.240 --> 10:30.840
So you have to believe them that mortality,

10:30.840 --> 10:39.760
they rolled out the vaccines at just the right time to avert this incredible disaster.

10:39.760 --> 10:45.320
You see, and if you believe that, you know, I've got a bridge I want to sell you.

10:45.320 --> 10:47.760
You know, I mean, this is crazy, right?

10:47.760 --> 10:52.920
And it's so stunning when you look at Canada like that.

10:52.920 --> 10:55.520
And it's even more striking in other countries.

10:55.520 --> 10:59.840
If you go down to a few more examples, we did, for example, we did all of Europe.

10:59.840 --> 11:01.560
We added a bunch of countries in Europe.

11:01.560 --> 11:06.640
We see we see essentially the same thing in Europe as if you were looking at the entire United States.

11:06.640 --> 11:13.680
I mean, what is compelling about these graphs is the is the cumulative vaccination in the gray line.

11:13.680 --> 11:20.160
Yes, so that you know where these these these presumed save deaths have to occur.

11:20.160 --> 11:23.680
You can't save anybody before the vaccine rollout.

11:23.720 --> 11:33.920
And so it's extraordinary because you are really claiming it's like they're they're claiming that

11:33.920 --> 11:42.200
the the evolution of the natural spread of a virulent pathogen would have been such

11:42.200 --> 11:46.080
that at that time there would have been these huge peaks in mortality.

11:46.080 --> 11:52.320
And thank God we got the vaccines out in time because we hit it right at the right moment to bring it down.

11:52.360 --> 11:56.080
And look at look at the the country you're looking at now, Singapore.

11:56.080 --> 11:59.920
I mean, it's as flat a line as you can have.

11:59.920 --> 12:07.640
And they're claiming that it would have been this incredible through the roof thing just unbelievable.

12:07.640 --> 12:11.600
And they brought it right back down to the to the flat line, you see.

12:11.600 --> 12:14.880
So these these things are really incredible, these vaccines.

12:14.880 --> 12:24.800
Now, the other thing too is that they always the the result is you always bring it back to what normally you were seeing before.

12:24.800 --> 12:30.800
So not something lower and not something halfway in between, you see.

12:30.800 --> 12:39.840
The vaccines have had a perfect effect of bringing back the mortality right down to the observed mortality,

12:39.840 --> 12:43.920
which is pretty much the same as it has been historically.

12:43.960 --> 12:49.760
Except for these additional peaks like in the U.S. and Europe that occur in the COVID period.

12:49.760 --> 12:56.600
But you want us to believe a couple of pretty extraordinary things.

12:56.600 --> 13:03.280
You want us to believe that the natural evolution of this thing more than a year into the pandemic

13:03.280 --> 13:06.880
is such that there would have been this huge surge in mortality.

13:06.880 --> 13:10.920
I mean, huge unprecedented in the history of the world as we know it.

13:10.920 --> 13:22.480
OK, and that you saved humanity from that and brought the mortality down to precisely not halfway, not a third of the way,

13:22.480 --> 13:29.960
but precisely down to basically what we've been seeing during the COVID period or historically before in some in some nations.

13:29.960 --> 13:32.040
That's what they want us to believe.

13:32.040 --> 13:35.720
That's where the 14 million saved lives comes from.

13:35.760 --> 13:41.800
So when you when you plot what those 14 million saved lives look like on these graphs,

13:41.800 --> 13:45.480
that's the kind of thing that they're actually proposing.

13:45.480 --> 13:50.320
So when you put it in terms of all cause mortality, which is a hard number like that,

13:50.320 --> 13:57.400
you realize that what they're telling us to believe is absolutely absurd.

13:57.400 --> 13:59.080
Complete nonsense.

13:59.080 --> 14:02.080
There's there's there's never been any phenomenon like this.

14:02.080 --> 14:04.080
There's never been that kind of mortality.

14:04.080 --> 14:14.240
There's never been you know, waiting, having waves of a pandemic, supposedly a pandemic.

14:14.240 --> 14:25.680
And then after a couple of waves of it, all of a sudden the next resurgence of it is 10 times more intense in terms of causing mortality

14:25.680 --> 14:31.800
than the first waves of it were right at the time when you happen to be rolling out a vaccine.

14:31.840 --> 14:34.360
This is what they want us to believe.

14:34.360 --> 14:44.600
And the other striking feature of what we saw is that in fact, if you look closely in detail at the all cause mortality itself,

14:44.600 --> 14:46.400
you see the opposite of what they're saying.

14:46.400 --> 14:50.120
You see that it increases when you roll out the vaccine.

14:50.120 --> 14:58.160
So on the finer scale of actually looking at the data itself, we showed in the paper that you see these these these increases

14:58.160 --> 15:05.960
and not just regular increases and a higher kind of level, but also peaks when they roll out the the the boosters and so on.

15:05.960 --> 15:09.360
You get peaks and you know, I've written papers about that and so on.

15:09.360 --> 15:14.880
So we've actually calculated how many deaths are caused by the injections in other papers.

15:14.880 --> 15:20.040
But in this paper, we just wanted to show just how insane what they were proposing is.

15:20.040 --> 15:26.120
And so this this means, Jay, that they didn't have a reality check in their mind.

15:26.120 --> 15:29.800
They didn't bother to think, does this make any sense?

15:29.800 --> 15:35.880
Are we proposing something that is realistic, that that is believable in the real world?

15:35.880 --> 15:39.240
What does it look like in terms of the actual mortality that would have occurred?

15:39.240 --> 15:43.000
You know, they did they never question themselves in that regard.

15:43.000 --> 15:47.440
So it's it's crazy for that reason.

15:47.440 --> 15:55.920
And so we concluded in the paper, hey, we concluded, hey, how did this get through peer review?

15:55.920 --> 16:03.520
How did how did editors and reviewers and the authors themselves misguide them to this degree,

16:03.520 --> 16:08.640
misguide themselves to this degree or not see or not bother to think about what this meant?

16:08.640 --> 16:12.880
You know, it's funny, they even have in their paper, they even have a graph like that.

16:12.880 --> 16:20.640
Yes, they have deaths averted by vaccines direct in light blue and then deaths averted by vaccines

16:20.640 --> 16:22.320
indirect in green.

16:22.320 --> 16:25.160
Well, how would you indirectly avert death?

16:25.160 --> 16:28.320
Yeah, they're a mission or infection at all.

16:28.320 --> 16:29.400
Yeah, that's right.

16:29.400 --> 16:36.280
They're looking at two different mechanisms of that's infection, which the vaccine prevented you from.

16:36.280 --> 16:41.240
So there's one that you were where you die from getting sick from the infection.

16:41.240 --> 16:45.120
And there's one where there's more deaths because there were more infections.

16:45.120 --> 16:49.720
So the transmission, if you like, they have a transmission component in there as well.

16:49.760 --> 16:55.960
And so basically, their calculation is in two steps.

16:55.960 --> 17:04.760
They have to have a scenario for how the spread, how the pandemic would have evolved in time.

17:04.760 --> 17:09.880
So that has to involve spread, their model of spread.

17:09.880 --> 17:16.000
And then they have this idea of how many of those people who get infected would likely get very sick and die.

17:16.040 --> 17:22.600
And then they have to fold in that they were vaccinated and there's a certain

17:22.600 --> 17:25.360
efficacy for that vaccine against being very sick.

17:25.360 --> 17:26.960
So they would have been saved.

17:26.960 --> 17:32.840
And so they have to fold all that in to calculate how many people would have been saved.

17:32.840 --> 17:39.120
So there's a certain degree of preventing spread of the vaccine, if you like.

17:39.120 --> 17:43.120
So they fold that in to prevent the spread part, you see.

17:43.120 --> 17:46.360
And so this is what they're doing.

17:46.360 --> 18:01.240
And even in that part of their work, you can easily be very critical because one of the things they do to predict spread is they take the reproduction number, the R number,

18:01.240 --> 18:07.880
to be what you get from a first look at number of cases versus time.

18:07.960 --> 18:14.160
And then they keep that R number throughout, which is kind of crazy, OK?

18:14.160 --> 18:31.000
So they apply a method that gives them a virus, if you like, that spreads much more and is more virulent at that time later on.

18:31.000 --> 18:37.000
That's in the end what they have to have because they have to have a lot of presumed deaths

18:37.000 --> 18:38.960
that you have to save people from.

18:38.960 --> 18:49.080
So they were not very critical of their own approach when it came to predicting the degree to which this thing would spread in the future.

18:49.080 --> 18:56.640
In the future, you see, they have to do all of this to get these huge numbers, OK?

18:56.640 --> 18:59.800
So it's just bad, bad science.

18:59.840 --> 19:10.080
And I mean, it puts in doubt the whole publication process at this top journal.

19:10.080 --> 19:16.560
And every time a paper like this gets published, you have to wonder, what were the reviewers thinking?

19:16.560 --> 19:18.040
Who were these reviewers?

19:18.040 --> 19:28.120
How could they be so blind and incompetent and unquestioning of what some authors are doing that is completely novel and completely fabricated?

19:28.120 --> 19:29.760
How could they be so unquestioning?

19:29.760 --> 19:31.240
Are they not able to see it?

19:31.240 --> 19:33.440
Are they incompetent?

19:33.440 --> 19:36.680
And on the other hand, what about the editors?

19:36.680 --> 19:39.240
How did the editors pick these reviewers?

19:39.240 --> 19:46.600
Did the editors go with only the reviewers that thought it was OK and ignore the reviewers that were critical of it?

19:46.600 --> 19:51.560
What were the editors doing to get this thing through?

19:51.560 --> 19:57.600
And the editors, are they themselves scientifically illiterate to be able to do this?

19:57.920 --> 20:02.520
To do a theoretical calculation and never, Feynman is a great physicist.

20:02.520 --> 20:06.160
And he would always bring us back to the common sense.

20:06.160 --> 20:10.000
Does this make any kind of freaking sense, right?

20:10.000 --> 20:14.320
And you have to do that constantly when you're doing theoretical projections.

20:14.320 --> 20:23.520
You have to ask yourself, wait a minute, would the radius of the Earth need to be 10 times what it is for this to be true?

20:23.600 --> 20:28.760
In that case, maybe I should rethink about what I just did here.

20:28.760 --> 20:31.960
And so that's what you have to...

20:31.960 --> 20:33.680
That's how scientists have to behave.

20:33.680 --> 20:40.800
They have to be critical of their own ideas, not just rub their hands because they get something that gates will like.

20:40.800 --> 20:44.400
And therefore, let's go with it because we know the editors will accept it.

20:44.400 --> 20:46.800
So that's my critique of that paper.

20:46.800 --> 20:52.360
But then there's another level of critique, which is once that paper is published,

20:52.360 --> 20:56.640
what the Nobel Prize Committee people who selected this prize,

20:56.640 --> 21:04.040
they were obviously affected by this paper and this idea that millions of lives were saved.

21:04.040 --> 21:06.880
Are these people scientifically illiterate?

21:06.880 --> 21:15.200
Are they not able to question themselves and say there's a claim out there that millions of lives were saved?

21:15.200 --> 21:17.280
What's it based on?

21:17.280 --> 21:21.000
We need to examine this and we need to do some fact checking

21:21.000 --> 21:25.760
because after all, we are the Nobel Committee that's going to give the prize in medicine.

21:25.760 --> 21:29.520
So let's give this a good, thorough look at.

21:29.520 --> 21:31.120
No, no, they didn't do that.

21:31.120 --> 21:34.520
In their press release, they talked about millions of lives saved.

21:34.520 --> 21:40.120
And essentially, that means this is one of the reasons that this is a valid Nobel Prize, right?

21:40.120 --> 21:46.880
So the Nobel Prize Committee itself had to be clueless, had to be unscientific,

21:46.880 --> 21:53.960
had to be unquestioning, had to look for something, a prize they wanted to give

21:53.960 --> 21:58.560
and not bother thinking for themselves about whether or not this made any sense.

21:58.560 --> 22:03.600
And then they repeated this millions of lives saved thing, which is nonsense.

22:03.600 --> 22:06.600
And so the Nobel Prize Committee was at fault.

22:06.600 --> 22:15.200
All the leading media were at fault, you know, the trend leading media, they were all at fault.

22:15.240 --> 22:18.320
The reviewers were at fault, the editors published it were at fault,

22:18.320 --> 22:22.520
and the authors of the article were at fault.

22:22.520 --> 22:28.880
It's a complete meltdown of the whole establishment of science when you have this kind of crap

22:28.880 --> 22:36.080
being produced, submitted, accepted, and then talked about uncritically,

22:36.080 --> 22:42.360
and then media who affect public opinion just repeating this stuff.

22:42.360 --> 22:47.920
And as though it were some big truth about the world, that millions of lives were saved.

22:47.920 --> 22:51.920
Complete nonsense.

22:51.920 --> 22:54.120
That's what I wanted to tell you about.

22:54.120 --> 22:55.120
I think it's beautiful.

22:55.120 --> 23:00.720
I think the thing that gets me is trying to get this to the way my neighbors can understand it.

23:00.720 --> 23:07.400
Yesterday, I kind of struck gold with saying that what they've told you in 2020

23:07.400 --> 23:10.640
is that there's a new cause of death on the planet.

23:10.680 --> 23:17.320
It wasn't there before and is there now that contributes more death than there would be.

23:17.320 --> 23:19.640
And we don't see that in the math.

23:19.640 --> 23:24.480
There's no new cause of death that we can see as a signal.

23:24.480 --> 23:29.400
And except for these these protocols and stuff, but that's not a new cause of death.

23:29.400 --> 23:37.360
And so my question is, in your many years, analyzing all of these countries,

23:37.360 --> 23:44.160
does the United States really stand out as a country that has a number of geographic anomalies

23:44.160 --> 23:48.760
in all cause mortality that aren't present in other places?

23:48.760 --> 23:50.040
Are we just a big country?

23:50.040 --> 23:52.480
And that's the way it is?

23:52.480 --> 24:00.160
Oh, well, we're preparing now our next paper, which will be pretty much about the entire world.

24:00.160 --> 24:02.760
We've got a lot of countries on every continent,

24:02.760 --> 24:07.160
and we'll be explaining the systematics of what happened in the world.

24:07.160 --> 24:13.280
In our next paper, but the USA was was very similar to Europe taken as a whole.

24:13.280 --> 24:16.240
As I showed in this latest paper, we saw some graphs to that effect.

24:16.240 --> 24:22.400
OK, but when you go country to country in Europe or even state to state within the United States,

24:22.400 --> 24:28.760
you get jurisdictions that are nothing like the average for the entire United States

24:28.760 --> 24:34.360
or the average for all of Europe, OK, where you have much less, much less mortality

24:34.360 --> 24:41.160
and you have no excess mortality in places where just a neighboring state might have a huge peak in mortality.

24:41.160 --> 24:46.000
You see, so it's it's incredibly heterogeneous, the mortality.

24:46.000 --> 24:52.560
And there are there on every continent, there are countries that virtually nothing happened

24:52.560 --> 24:55.200
until they rolled out the vaccine.

24:55.200 --> 24:58.400
So you can directly see in the all cause mortality.

24:58.400 --> 25:03.680
And this is true to some degree of certain states, it's largely true for Canada.

25:03.680 --> 25:11.560
And it's it's very clearly true for a lot of countries, unambiguously true that you you cannot detect

25:11.560 --> 25:14.840
and excess mortality until they roll out the vaccines.

25:14.840 --> 25:21.120
Then you get a surge in all calls in in additional all cause mortality above the historic trend.

25:21.120 --> 25:26.200
And then when they roll out these particularly dangerous boosters, you get an extra peak,

25:26.200 --> 25:29.480
especially among the elderly every time they roll one out.

25:29.480 --> 25:31.480
So you see all that.

25:31.520 --> 25:36.240
So in other words, the mortality becomes much more uniform in its behavior

25:36.240 --> 25:39.520
when they start rolling out the vaccines in twenty twenty one,

25:39.520 --> 25:43.320
because then you've got kind of a uniform cause of death, if you like.

25:43.320 --> 25:47.480
And they're not being as aggressive with all the protocols and the lockdowns

25:47.480 --> 25:52.640
and the the political actions and so on against people and they open up the economy.

25:52.640 --> 25:53.960
So they normalize things.

25:53.960 --> 25:59.600
So the causes of death that were very prevalent and very heterogeneous

25:59.640 --> 26:05.560
in before they were vaccinating are kind of are dissipated or gone.

26:05.560 --> 26:12.160
And then in during the rollouts, the main cause of death, the extra cause of death is the vaccines themselves.

26:12.160 --> 26:19.720
And so you get a much more regular behavior when you're looking at the world, you see that heterogeneity pretty much disappears.

26:19.720 --> 26:22.920
Basically, you have deaths where you rolled out vaccines.

26:22.920 --> 26:28.520
So, for example, in India, their vaccine, their initial vaccine rollout was three months late.

26:28.920 --> 26:36.560
Well, they didn't have any excess mortality until they actually rolled out that late vaccine and then it surges up.

26:36.560 --> 26:41.480
So it really follows the vaccines.

26:43.440 --> 26:48.080
And the most important point from from our studies up till now,

26:48.080 --> 26:55.880
one of the most important points is that the risk of dying per injection increases exponentially with age.

26:55.920 --> 26:59.600
So it gets very, very high as you get very elderly.

27:01.040 --> 27:05.800
And so this is a vaccine that is particularly toxic for the elderly.

27:06.320 --> 27:11.120
And that and that is in complete opposition to the idea that we should

27:12.640 --> 27:16.120
particularly give it to the elderly to protect them, right?

27:17.240 --> 27:20.840
Preferentially give it to them, make sure they get every booster and everything.

27:21.280 --> 27:29.440
That's that's a nasty, nasty thing in terms of the very real risk of dying that we have quantified.

27:30.240 --> 27:38.160
If you know, it's, I think, one of these things that you can chalk up to the TV common sense.

27:38.160 --> 27:42.920
Remember, they said, well, masks do some, they must do something so you might as well wear them.

27:43.480 --> 27:47.760
And these shots, if they're going to help somebody, we want to help the most vulnerable

27:48.200 --> 27:51.800
without thinking that the shots themselves could be too dangerous for them.

27:52.880 --> 27:55.440
Yes, it's horrible.

27:55.440 --> 28:00.840
And, you know, it's it's scientifically, it makes no sense that they would not think

28:01.200 --> 28:07.040
of the increased toxicity of the vaccines for the elderly, because there's a lot of toxic

28:07.440 --> 28:11.680
ecology out there. It's an entire field of research where they study, you know,

28:11.680 --> 28:17.200
poisonings and overdoses, and they they do animal studies where they inject a certain

28:17.760 --> 28:24.560
known quantity, a constant quantity of a dangerous substance into the animal to see if they'll die

28:24.560 --> 28:30.720
or not and how sick they get and so on. And all of those studies show that the older the animal is,

28:30.720 --> 28:35.760
including humans, the more likely their chance of dying from from that exposure.

28:36.320 --> 28:42.480
And so this is extremely well known, and it locks in with the idea that your your immune system

28:43.920 --> 28:49.440
deteriorates quite a lot as you get older and is more fragile in the sense that if you change an

28:49.440 --> 28:56.000
elderly person's nutrition, if they go to a home and they're what they eat is completely different

28:56.000 --> 29:02.160
than the gut biome changes and that has a dramatic effect on the immune system and on their general

29:02.160 --> 29:08.720
health and so on. So these fragilities are much higher for elderly people than they are for younger

29:08.720 --> 29:16.720
adults and children. So this is this is not new. This is this is extremely well known. It's it's just

29:18.080 --> 29:24.640
criminally irresponsible to have developed a policy that we need to absolutely prioritize the elderly

29:24.640 --> 29:32.640
for this injection without ever doing a trial to see is to see if as a function of age, there is a

29:32.640 --> 29:38.400
higher risk of adverse effects. No trial was specifically designed to answer that question

29:38.960 --> 29:45.680
to my knowledge. And so this is this is criminally irresponsible, especially now that we

29:45.680 --> 29:50.160
know from the all cause mortality that it's a huge effect. It's a huge effect.

29:51.120 --> 29:58.160
And you went in Canada, you guys went pretty hardcore. I mean, I'm like full on and the people

29:58.160 --> 30:05.360
that bought into it bought into it big time, right? I mean, this is yeah. Yeah, yeah, yeah. It's a very

30:05.360 --> 30:14.960
high vaccination rate, very aligned unipolar propaganda, intense control of the major media.

30:15.520 --> 30:23.280
Um, crazy. Yeah, it's it's heartbreaking, really. And and I don't know where it's going to go, but

30:23.280 --> 30:29.280
it's I think it's going to get pretty hairy in America. I don't know how this is all going to

30:29.840 --> 30:38.480
pan out because the it is really a a schism of of Grand Canyon proportions now. It's really like some

30:38.480 --> 30:45.600
of us think there are Martians and some of us don't. It's it's it's that bad. Right. Well,

30:46.640 --> 30:52.240
it's good that a lot of people well, you can't not have a lot of people being aware because an

30:52.240 --> 31:00.640
awful lot of people were harmed by the by the injections. And it's easy to think that your

31:00.640 --> 31:06.640
parent or grandparent died of natural causes in the home after even though they had been vaccinated

31:06.640 --> 31:11.040
recently, it's easy to think that and you want to protect yourself because you allowed it. So

31:11.040 --> 31:16.000
it's easy to think that. But a lot of elderly people would have died directly as a result of

31:16.000 --> 31:22.640
being inject injected. So that's harder to see. But there's a lot of young adults and children

31:22.640 --> 31:28.880
and so on who have been harmed significantly, not not the huge numbers that you have among the elderly,

31:28.880 --> 31:35.920
but still a lot. And that you you really notice it. And it's not just deaths. It's it's a

31:35.920 --> 31:44.160
permanent disability, heart conditions, you name it. So this ends up creating a a group of

31:44.160 --> 31:50.560
aware people who really feel that the government did them wrong. I mean, it's the basis for

31:51.520 --> 31:57.280
the opposition against childhood vaccinations is that, you know, the a lot of parents have

31:57.280 --> 32:04.480
had their children permanently harmed by these injections. And they understand and they have

32:04.480 --> 32:10.080
come to believe from personal experience from observing their child that this is real. And

32:10.080 --> 32:15.760
this was nasty. And it should never happen to anyone. And that is the basis for things like

32:15.760 --> 32:24.160
Children's Health Defense and and the Canadian equivalent of it and so on. So it's a movement

32:24.160 --> 32:30.160
when you it movements are based on people being abused seriously by the government or by powerful

32:30.160 --> 32:36.880
forces. And that creates a desire to want to defend yourself. And that's that's the basis of

32:36.880 --> 32:41.760
movements. So I think there is, for a long time, there will be a movement of that type.

32:42.640 --> 32:48.000
I don't think very many people move in the opposite direction. The only one that I know of is a guy

32:48.000 --> 32:55.520
by the name of Dan Wilson, debunk the funk is his name on YouTube. And he claims to have been

32:55.920 --> 33:02.560
a conspiracy theorist, and now come back to the good side and believes in in vaccines and everything.

33:04.960 --> 33:10.240
Yeah, I don't I don't know what to say other than if if we can get your paper

33:11.760 --> 33:15.840
onto the defender, we're going to do it again, because I think this is really one of these.

33:15.840 --> 33:21.760
It is really absurd, but it's it's it was sort of a ball that somebody had to hit out of the

33:21.840 --> 33:28.480
park, because you can't make these kinds of claims and and not have them not have them lampooned.

33:28.480 --> 33:36.560
I mean, it's really, it's shocking, really, it really is shocking, if you think about it, that

33:37.280 --> 33:42.640
people still haven't been able to get their head around the idea that they what they told us versus

33:42.640 --> 33:49.440
what actually happened. Jay, Jay, Jake, here's an injection that they're going to force on

33:50.400 --> 33:55.280
billions of people. They're basically going to force you to take this, they're going to

33:55.280 --> 33:59.840
coerce you in every possible way, you can lose your job and so on and so on, make you feel guilty

33:59.840 --> 34:04.560
if you're not protecting the people around you and all this thing, they're going to completely

34:04.560 --> 34:10.000
coerce you to take this to accept that the that the state is going to inject this substance into

34:10.000 --> 34:18.240
your body. And it turns out that substance has no benefit for you whatsoever that can be detected

34:18.320 --> 34:25.360
by hard numbers. And not only that, it has a definite risk of making you either very disabled

34:25.360 --> 34:34.240
or dead. Okay, that's the situation. And then, after you've basically completed this huge military

34:34.240 --> 34:38.960
style campaign where you've injected everyone and you've done these and it's had all these horrible

34:38.960 --> 34:46.880
consequences, then you give the Nobel Prize to someone who was who whose fundamental work was

34:47.600 --> 34:54.880
part of presumably what have developed this vaccine. And then you have everyone scream up

34:54.880 --> 35:00.240
and down the Nobel Committee and everybody saying, this is so wonderful because it's saved millions

35:00.240 --> 35:09.360
of lives. It's saved millions of lives. The same substance that poisoned us, and that is this

35:09.360 --> 35:15.600
horrendous product that should never been injected into people's bodies, is now something that we're

35:15.600 --> 35:21.920
going to celebrate. It's going to be an achievement of human science of the science created by humans.

35:21.920 --> 35:27.040
It's going to go into all the textbooks, we're going to teach it at school, and it has saved

35:27.040 --> 35:32.560
millions of lives. This is this is the mantra that we're going to hear over and over again.

35:32.560 --> 35:40.800
And that mantra is based on what it's based on nothing. There is no scientific basis for saying

35:40.800 --> 35:48.000
that whatsoever. No clinical trials have ever demonstrated that. And it's based on a garbage

35:48.000 --> 35:55.440
simulation funded by the industry for God's sakes, where the authors didn't even double check if their

35:55.440 --> 36:03.040
results made any kind of freaking sense. This is this is the absurdity that we're now experiencing.

36:03.040 --> 36:08.800
So of course, I have to scream it on every rooftop. Of course, I have to write a paper where I

36:09.520 --> 36:16.000
calmly explain this is how you do this calculation. This is what it looks like if you actually

36:16.000 --> 36:21.360
project what it means in terms of real deaths. These are what the grass looks like. This is

36:21.360 --> 36:28.160
what they're claiming, folks. This is what they're claiming. And and try to try to explain to people

36:28.160 --> 36:36.000
that it's just insane to think that this this pathogen would have started being

36:36.000 --> 36:41.680
10 or 20 times more violent right at the time when they happen to roll out the vaccines. You

36:41.680 --> 36:47.840
have to believe that. I mean, this is all just there's layers and layers of insane here. And

36:47.840 --> 36:52.720
every time they make a statement, the reg flags should go up. If you're a thinking scientist,

36:52.720 --> 36:59.680
you should be saying, what? Where's that coming from? How can you even say that? You know, you

36:59.680 --> 37:05.600
should you should be ridiculed in your department. There's you know, when you go to coffee at the

37:05.600 --> 37:11.440
staff meeting, they should snicker at you and say, you actually wrote this paper. Did you see what

37:11.440 --> 37:16.160
it look? I'm looking at figure three here. Does this make any kind of sense? You know, they should

37:16.160 --> 37:24.480
be ridiculed. And normally, in a society that is healthy, that has democracy, that has professional

37:24.480 --> 37:31.360
independence, they would be ridiculed. But we are at such an advanced state of people just want to

37:31.360 --> 37:38.160
protect their careers. We're into totalitarianism. We're into, you know, a society that doesn't have

37:38.160 --> 37:42.320
independent thinkers. And it's not you're not rewarded in any way. If you're an independent

37:42.320 --> 37:49.040
thinker, you're you're in fact, you're penalized for it severely. And so that's the society that

37:49.040 --> 37:54.560
we have now. So scientists can't even ridicule each other. I mean, there used to be, when I was a

37:54.560 --> 38:00.000
staff member at the university, we would have fights because we would we would make fun of each

38:00.000 --> 38:06.080
other's work and and question each other's work and people get really insulted. That was healthy.

38:06.080 --> 38:10.800
That was a good thing. Because you would go back and think, eh, maybe he's right, you know, I better

38:10.800 --> 38:15.120
I better not I better think twice before I say that again at the next conference, you know,

38:16.080 --> 38:22.800
none of that happens now. Everyone's aligned with vaccines are wonderful and, you know, pharma is

38:22.800 --> 38:28.800
saving lives and, you know, all of this stuff, including the scientists and academics. Where are

38:28.800 --> 38:36.160
the critics? Where are they? Yeah, I would I would go so far as to say that I would follow up on what

38:36.160 --> 38:42.640
you just said is that when I first started in academic science, I remember that the old men

38:42.640 --> 38:49.200
and women in the back of the of the room would often just be creeps and say, why should I even

38:49.200 --> 38:54.240
care about this? I just sat in here for 45 minutes and I don't know why I should care about this.

38:54.800 --> 39:03.040
And nobody would ever critique science on that level anymore. And I saw it very clearly because

39:03.040 --> 39:08.640
this Drew Weisman guy has been going around talking about his technology for the last 14

39:08.640 --> 39:14.640
months. You can go and see all of these lectures that led up to the Nobel Prize. And if you listen

39:14.640 --> 39:22.160
to his discussions of immunology and his discussions of how these things work for him, it's really as

39:22.160 --> 39:29.600
simple as previous vaccines used to give us some antibodies. And my mRNA gives us 50 times more.

39:29.600 --> 39:35.920
So it has to be better. And it's the that's the end of the story. Yes. And it's extraordinary

39:36.480 --> 39:42.080
how you have this roomful of people that doesn't go, isn't that a little bit too simple? Isn't that

39:42.080 --> 39:48.240
assuming, you know, a lot? Assuming layers and layers of things. Yes, seriously, layers and layers

39:48.240 --> 39:55.680
of things. Yes. So it's, it's, it's crazy. It's crazy that the establishment will pick on a bogus

39:55.680 --> 40:03.600
argument like that and amplify it and not mention anything else. And that becomes the supposedly

40:03.760 --> 40:11.120
educated view of the subject. It's insane. It's like, you know, the biggest arguments I've had about

40:11.120 --> 40:16.240
against I've had with people who believed in masks and believed in the COVID measures and the

40:16.240 --> 40:22.480
distancing, the biggest arguments I've had were with very educated people, engineers and people

40:22.480 --> 40:27.840
like that, who had just read everything and listened to everything. And because they understood

40:27.840 --> 40:33.920
the arguments that were being made, they thought that they understood what was going on. In other

40:33.920 --> 40:38.240
words, they didn't think to themselves, okay, I understand that, but is there more to it?

40:38.240 --> 40:41.680
Is there stuff that, is there questions I should be asking? Is there, you know, is there more to

40:41.680 --> 40:46.800
this than what I'm being explained in this cartoon and what's being told to me and these

40:46.800 --> 40:50.720
scientific papers that are written? What about, what about this other thing? What about this other

40:50.720 --> 40:56.480
fact? And is that part of it true? They didn't do that. No, they pleased themselves intellectually

40:56.480 --> 41:01.680
by understanding what was being presented to them. They could repeat it because they understood it,

41:01.680 --> 41:07.840
and therefore they became experts in this, and they would argue with you on that basis, you see.

41:08.480 --> 41:12.160
Knowing that there were plenty of people on Facebook and TV to back them up,

41:12.720 --> 41:16.480
that they could point to and say, but these people all agree with me. So it's this.

41:16.480 --> 41:22.480
And scientists as well, who written all these papers that is based on. So these are the people

41:22.560 --> 41:26.080
that you have to argue with. They're, they're people who have tunnel vision,

41:26.880 --> 41:32.560
and who reinforce their tunnel vision by the fact that they can understand technical arguments.

41:33.600 --> 41:39.040
You see, so it's very, it's very, it's a, it's a, it's a crazy world out there.

41:39.600 --> 41:44.720
It definitely is. And then you have the other extreme of people who understand things very

41:44.720 --> 41:52.160
clearly, who are typically working class or from different professions, and their response to my

41:52.160 --> 41:59.120
detailed proofs that this is all garbage is, well, that's obvious. I could have told you that.

41:59.120 --> 42:03.200
I knew that right away because of this and because of that. And they're often quite right.

42:03.200 --> 42:09.040
They've got the big picture, you know. And so I'm kind of working between those two extremes

42:09.040 --> 42:14.640
where I'm trying to help the people who already know to know that there are really rigorous

42:14.640 --> 42:21.280
arguments that you can rely on, and to stab the people in the eye that think they already know

42:21.280 --> 42:25.120
by pointing out that they're making these fundamental errors. So I'm kind of working in

42:25.120 --> 42:33.840
the middle there in our work, you know. Yep. I think this is all, it's all work that has to be

42:33.840 --> 42:40.560
done very slowly because even, even myself, I know that before the pandemic, I didn't know

42:40.560 --> 42:44.800
how many people died every year in America. I didn't know how many people died every week.

42:45.440 --> 42:50.160
And so when these numbers came out, I really had to work very hard to find any context for them

42:50.160 --> 42:56.160
because as this, this picture that I just had up there a second ago of the elanset paper,

42:56.160 --> 43:02.240
it starts from zero. And then there's just a bunch of COVID people. And so you don't have

43:02.240 --> 43:08.480
an idea of the context of how those numbers are being generated and how many of them overlap with

43:08.480 --> 43:16.480
expected deaths. And so most people won't ask themselves those questions. Right. Because they're

43:16.480 --> 43:22.400
so pleased that they understood the graph that's being presented to them that, you know, that suffices

43:22.400 --> 43:28.400
for them. They're not, they're not, they're not questioning. Yeah. Well, I mean, it's just, it's

43:28.400 --> 43:35.200
crazy. I think that people, you know, get, get as far as maybe they hear 5,000 people died of COVID

43:35.200 --> 43:41.280
this week in America. And they might get as far as to divide by 50 states and try to think of

43:41.280 --> 43:44.800
how many people in that, but they don't, they don't ever get to the stage where they're like,

43:44.800 --> 43:52.480
oh, wait, they expected between 50 and 60,000 to die this week. Oh, and now that puts 5,000

43:52.480 --> 43:56.640
into context. Now, how many of those actually died of a respiratory disease? You know, and it's

43:56.640 --> 44:03.840
none. So now you have a real problem. Or, you know, it's all, all pneumonia, but it is a real,

44:05.200 --> 44:11.200
it's something that honestly, I don't think Danny, we could have seen until maybe 2022 though.

44:11.920 --> 44:19.600
And 2023 now, hindsight is clearer because they were holding back deaths in 2020. They were holding

44:19.600 --> 44:25.120
back. Right. I heard that. They were reporting them. And so even what, what Jessica sees now is

44:25.120 --> 44:29.520
clear. I don't, I don't completely agree. I, I, I know that it's true that they were, it took them

44:29.520 --> 44:34.880
a while to, to get all the deaths into their records and they were updating and it was, there

44:34.880 --> 44:42.160
was some significant adjustments as they were updating, but the actual initial peak that surged

44:42.160 --> 44:48.640
in certain hotspots right away, that was clear from the beginning. It was clear that, and it was

44:48.640 --> 44:54.560
clear given the heterogeneity of that, you know, spatially, that it was only happening in hotspots

44:54.560 --> 45:01.600
and, and that this couldn't be a spreading, a spreading viral respiratory disease. The fact

45:01.680 --> 45:08.400
that it was happening synchronously around the world, that you could see it right away in Italy,

45:09.200 --> 45:16.080
Stockholm, New York and Madrid and so on, that it was synchronous with the political announcement

45:16.080 --> 45:22.480
of the, of the pandemic. I don't care about the details of it. Maybe the numbers aren't quite

45:22.480 --> 45:28.080
right because they haven't tabulated everything yet. A synchronous incredible surge in mortality

45:28.080 --> 45:35.760
that occurs when you announce a pandemic is impossible to be from a spreading viral respiratory

45:35.760 --> 45:44.480
disease. And I said that in June of 2020 and it has held true throughout all of my work. Okay.

45:44.480 --> 45:50.480
And so even though there were these difficulties in terms of tabulating, you could tell things

45:50.480 --> 45:58.400
right away. And I did, I did, I saw those things right away. Do you, there were hotspots though,

45:58.400 --> 46:04.880
hotspots of death or? Yes, that's what I mean. Yeah. Yeah. That's what I mean. I mean, I mean,

46:04.880 --> 46:12.960
all cause mortality. Yeah. And then when the data became more clear, you could see that, okay, now

46:12.960 --> 46:17.840
that, now that we've got really good statistics, there are in those states where I thought,

46:17.840 --> 46:23.520
at first, you're not seeing any kind of a surge, anything like New York State and Vermont and so

46:23.520 --> 46:29.440
on. Okay, there's a little blip there and it's statistically significant, you know, but overall

46:29.440 --> 46:37.440
the picture was exactly what you were seeing at the beginning within almost weeks, you could see it.

46:38.560 --> 46:45.360
And so thinking epidemiologists could know right away that this story was bogus.

46:46.000 --> 46:52.560
But most of the mainstream, most of the mainstream media was using like a nationwide average. And so

46:52.560 --> 46:57.440
these few hotspots were sufficient to, to blab about spread, right? I mean,

46:58.960 --> 47:03.920
no, well, that, that doesn't demonstrate spread. No, but that's what they, they kind of just said

47:03.920 --> 47:09.840
that then the United States, there are new, they don't say a lot of things and you're supposed to

47:09.840 --> 47:15.120
presume that the, that the, that the notion of spread and the virus and everything is, is the

47:15.120 --> 47:19.200
correct notion, right? That's, they play that game all the time. But I mean, there were super

47:19.200 --> 47:23.440
spread. I mean, you can't, you can't question that. There were super spreader events. I mean,

47:23.440 --> 47:29.120
so spreading definitely happens. Right, right, right. There was a lot of crazy stuff. But you

47:29.120 --> 47:34.320
know, when you read the old epidemiology literature of a hundred years ago and so on, these people

47:34.320 --> 47:44.240
were common sense, clever scientists. They, they would have immediately said they're talking garbage.

47:44.240 --> 47:49.920
This shouldn't even be allowed to be told to the public. This is, this really is misinformation.

47:49.920 --> 47:55.360
And please, you know, please talk to the experts, the real experts. They would have just, they would

47:55.360 --> 48:00.400
have just said, no, this is crazy. I'm, you know, I'm coming out of the grave here. I'm one of the

48:00.400 --> 48:06.080
founders of epidemiology. And I want to tell you, this is garbage. You know,

48:08.400 --> 48:13.680
but they don't do that anymore. I mean, epidemiology has been hijacked in a way. And the people that

48:13.680 --> 48:20.640
are, it doesn't, as far as I could see, it's almost non-existent now. The people used to try to

48:20.640 --> 48:28.400
understand disease on large scale from the large scale observations and really try to infer what

48:28.400 --> 48:34.000
could be happening. And there was a lot of that kind of very fundamental work. And it just doesn't

48:34.000 --> 48:41.840
exist anymore. You're only allowed to look at whether people die according to their race. And

48:41.840 --> 48:49.200
whether, you know, poor, more poor people die. And if there's a correlation to your financial

48:49.200 --> 48:52.720
status and things like that, there's certain things that are allowed that you can look at.

48:52.800 --> 48:58.320
We think fundamentally about the nature of death and disease and so on.

48:59.760 --> 49:03.920
Has this had much of an impact on you since you've been speaking out and getting your word out a

49:03.920 --> 49:07.840
little bit? Has it had any negative impacts for you? Are you pretty independent and okay?

49:09.280 --> 49:12.080
Oh, you mean negative impacts on my person and my family?

49:12.080 --> 49:13.280
Yeah, if I can ask, yeah.

49:13.920 --> 49:19.200
Oh, yeah. No, no, no. This has not to, I'm not conscious of it if it has.

49:19.760 --> 49:28.160
You know, this has been very positive for me because I've always been this way. I've always

49:28.160 --> 49:33.200
challenged the dominant views in any scientific field that I've entered. So I'm a fighter,

49:33.200 --> 49:38.400
I love doing this kind of thing. And I've done it all the time. I did it for more than a decade on

49:38.400 --> 49:45.040
the cold global warming stuff. And I could go through a history of all the areas of science

49:45.040 --> 49:49.840
that I worked in where I challenged the dominant paradigms. So this is what I do.

49:50.640 --> 49:58.720
And so, but this, the beauty of this time around is that the public was really involved in the

49:58.720 --> 50:05.360
discussion. So the things that I would normally have almost no public to hear me, except maybe on

50:05.360 --> 50:10.320
global warming and things, I gave some lectures and things like that. But all of a sudden,

50:10.320 --> 50:15.680
on social media, everyone wanted to hear about it. Everyone wanted to understand

50:16.480 --> 50:21.600
my scientific arguments. And I never, I never really encountered that on that scale, you know.

50:22.240 --> 50:28.880
So that was very, a very positive experience to see that there are all these people out there,

50:28.880 --> 50:33.840
even though the majority were maybe not of that group, even though the mainstream media didn't

50:33.840 --> 50:38.880
didn't do their job and were out of it, and the government was really misbehaving,

50:38.960 --> 50:43.440
nonetheless, there are all these people out there who are really thinking independently

50:43.440 --> 50:50.000
and who are starved to hear these arguments and these new perspectives and so on. And that was

50:50.000 --> 50:57.120
very refreshing, I have to say. Yeah, I really enjoyed that. I mean, when I would talk about

50:58.000 --> 51:03.040
global warming, I've done a lot of work on that and did a lot of physics calculations to demonstrate

51:03.040 --> 51:08.800
the magnitude of the effect and everything. And when I would talk about that, even among, even

51:08.800 --> 51:14.240
in a general kind of audience, like in a big auditorium or something, most people were very

51:14.240 --> 51:18.480
critical of what I was trying to say. They didn't really try to understand or really get it. They

51:18.480 --> 51:25.760
were just like, yeah, I guess I misread the title of this talk, this guy's a nut, you know. It was

51:25.760 --> 51:35.680
that kind of a response. But nowadays, it's the opposite. People will travel from far to hear

51:35.680 --> 51:41.600
you, and they don't have to travel when it's on the internet, obviously, but no, it was great.

51:41.600 --> 51:50.240
So I had never been in rallies where everybody, a huge public rally live in person, where people

51:50.240 --> 51:56.000
are interested to hear my views of my technical and scientific views about something. And they're

51:56.000 --> 52:01.120
like sitting on the edge of their seats listening to it, and then wanting to talk to me afterwards

52:01.120 --> 52:08.720
about science. I think I'd never seen that before. So that was a very positive experience for me.

52:09.520 --> 52:20.720
Now, in terms of my, you know, I am financially secure, independent, established life, married,

52:20.720 --> 52:28.960
all that kind of thing. So nothing, none of that has changed. So I didn't suffer a loss of employment

52:28.960 --> 52:36.480
or difficulties with family members or anything like that. A lot of my close family, my siblings,

52:36.560 --> 52:42.400
they completely agree that they're on the side of, you know, thinking that the masks and the

52:42.400 --> 52:49.440
vaccines are pretty crazy. So there were no big, there were no big battles on that front.

52:51.440 --> 52:57.280
I really think it would be important for you, if you have the time, maybe to come back and

52:57.280 --> 53:03.920
meet Jessica Hockett on this stream, because she has done so much work specifically on New York,

53:03.920 --> 53:10.080
and it would be interesting to talk to her because she sees like a 600% increase in mortality for

53:10.080 --> 53:15.840
like four weeks in New York, and that's all that ever happens there. She's still trying to figure

53:15.840 --> 53:22.720
that out. Well, I would have to look at the data and look at what she's doing and how she's starting

53:22.720 --> 53:32.080
to interpret it to really have a good discussion with her. I can already see lots of pitfalls and

53:32.080 --> 53:37.280
caveats when you try to do what she's trying to do. So I can foresee a lot of problems, you know,

53:38.320 --> 53:43.840
but I haven't had time to really look into detail at what she's doing. But I mean, it's great that

53:43.840 --> 53:49.440
she's digging into the data and representing it in different ways and trying to find out more

53:49.440 --> 53:54.960
information as well. It's great that she's doing all of that because New York was a very special

53:54.960 --> 54:05.200
place and in many ways, the state of New York, but also the major centers, hospitals, and so on,

54:05.200 --> 54:12.400
and how they were behaving. So it was a pretty special events there that were occurring, yes.

54:14.000 --> 54:18.640
Extraordinary, I don't know what to say. So your next paper is coming out of all

54:18.640 --> 54:23.840
countries in the world or many countries in the world? Yeah, we're hoping to get it out within

54:23.840 --> 54:29.680
a month or two. But I have to say, I'm going to a conference in Romania, an international conference

54:30.320 --> 54:35.040
on COVID, and we're going to speak at the parliaments. That's going to be a lot of fun.

54:35.840 --> 54:40.720
And we've got our plane tickets and two of my co-authors are going to be there as well.

54:42.720 --> 54:48.480
Yeah, it's going to be great. So that's taking up some of my time preparing that and they're going

54:48.560 --> 54:54.240
to publish a conference book about it and so on. That might slow me down a bit, but

54:56.000 --> 54:58.720
yeah, within a month or two, we should have that big paper out.

54:59.440 --> 55:03.360
A few months ago when I talked to you, one of the things that you were interested in

55:04.080 --> 55:10.560
understanding a little bit better was the library of genome sequences of the virus and

55:10.560 --> 55:14.960
all that business. Have you been able to spin your wheels in that at all?

55:15.680 --> 55:24.400
It's on my to-do list to figure out how PCR works in some detail. I mean, I have a bit of

55:24.400 --> 55:32.080
experience with wet chemistry and I know how you can fool yourself as a chemist easily.

55:32.720 --> 55:38.960
And I've read some of the background and I've read the inventors' criticisms of the technique

55:38.960 --> 55:45.840
and so on. So I know there are a lot of potential places where you can fool yourself easily.

55:45.840 --> 55:51.680
I've so often seen fields where people think that they are able to do something with a certain

55:51.680 --> 55:57.280
precision, but in fact, their accuracy is way off if you distinguish between precision and

55:57.280 --> 56:02.880
accuracy, right? So it's just so easy to fool yourself when you're using this kind of technology.

56:03.440 --> 56:07.440
And I suspect that a lot of that is happening. I suspect that

56:07.440 --> 56:11.600
there's a lot of things that they claim you can do that you can't really do.

56:11.600 --> 56:15.040
I don't know if you'd agree with me, but that's my feeling right now.

56:16.320 --> 56:21.280
I'm sure there's a lot of things you can do with some certainty in a robust way, but there's a lot

56:21.280 --> 56:27.120
of other things you can't do. And this has all been pushed by pharma, the whole development of the

56:28.080 --> 56:34.080
human genome sequencing, that whole project, all the funding. It's all a pharma project to

56:34.800 --> 56:40.960
legitimize more and more sophisticated drugs that supposedly you can target to the people that

56:40.960 --> 56:45.760
won't have bad reactions to them, and it will be beneficial to them if you know their genome,

56:45.760 --> 56:52.480
you know, this kind of stuff. This is the driving force behind this stuff. And let's face it,

56:52.480 --> 56:58.000
there was a Nobel Prize given for PCR, maybe not an accident from a political perspective,

56:58.000 --> 57:03.360
you know, as much as I appreciate the inventor and how brilliant he is and how critical he's

57:03.360 --> 57:09.840
been of things like AIDS and so on. Nonetheless, it was one of those things, you know. So,

57:10.480 --> 57:17.360
yeah, it's something I want to get into. I've got a list of about three or four really major

57:17.360 --> 57:23.680
research projects that I want to get into once I've done the emergency work around mortality.

57:24.640 --> 57:30.240
Very good. Yeah. I'm not letting it out of the bag what some of our

57:31.200 --> 57:36.720
next research is because it's going to be very, it's going to be breakthrough stuff.

57:38.000 --> 57:42.400
But I'm not, I don't want to let it out of the bag. I don't want to talk about it before it's

57:42.400 --> 57:48.080
time. Okay, well, very good. Then you save it up and we'll just, we'll wait and we'll hear

57:48.080 --> 57:53.600
it when it comes. And good luck on your travels. Thank you for joining me. It's been

57:54.080 --> 58:02.320
not surprising, also insightful again to have you here. And it's just, I don't know, it's lucky

58:02.320 --> 58:06.480
that we've got you. I don't know, somebody needed to do this work. You seem to be one of the only

58:06.480 --> 58:11.840
people who's doing it. So it's really, everybody's happy. Thanks for having me, Jay. I love your

58:11.840 --> 58:18.640
venue. I love the way you think. Thanks for having me. Yep. Have a good evening. Thanks. Bye.

58:18.640 --> 58:26.960
Bye. I don't know what the timing is like here. If the timing is really bad, then I'm just going

58:26.960 --> 58:33.280
to edit it and I'll fix it and maybe I'll stream it again. But I'll also put it on Vimeo and I'll

58:33.280 --> 58:38.800
put it on the website. I apologize. You know, I do think that they're starting to mess with me. So

58:38.800 --> 58:43.680
we're going to have to pull some different maneuvers, but I've got a bunch of tricks up my sleeve

58:43.680 --> 58:49.440
yet. So don't worry. We've got a whole YouTube channel that we haven't touched and is just waiting

58:49.440 --> 58:54.240
for us to pull the trigger on. And we have a rumble channel that we're not really filling yet. So

58:54.240 --> 59:01.440
there's a lot of places, a lot of space, a lot of, you know, artillery at our disposal yet. So just

59:01.440 --> 59:07.120
stay calm. Don't panic. I apologize again for the alignment of the video, but don't worry. I'm

59:07.120 --> 59:13.120
always recording here at home base. And so I can rerun it and either put it back on Twitch

59:13.120 --> 59:18.640
or at least have a good video up on rumble and a good video up on my website. So thanks very much

59:18.640 --> 59:25.200
for coming. Looks like the Nobel Prize is based on a little bit of Hoopie Hoopie. A little bit of

59:25.200 --> 59:33.200
hocus pocus. And it's not like we didn't know that, of course. Make sure that you realize that these

59:33.200 --> 59:40.960
people are interested in eliminating the control group by any means necessary. So stop

59:40.960 --> 59:49.840
transfections in humans. Please stop transfections in humans. Say hi to the Broken Science Initiative

59:49.840 --> 59:55.760
for me by going there and making a comment about how badass you go and biological is.

59:56.400 --> 01:00:02.160
And that Greg Glassman should be on this show. Go over there and make a comment. Thanks very much

01:00:02.160 --> 01:00:08.240
for joining me. See you guys again soon. Probably tomorrow because you know we do it every day.

01:00:41.920 --> 01:00:57.280
I'm just really excited. I just want you everybody to know if you're still listening that

01:00:59.040 --> 01:01:03.120
that Halloween is the night. Halloween is the night. You've got to be around

01:01:04.000 --> 01:01:09.760
Halloween like Halloween is going to be big on YouTube for JC on a bike. Just don't forget,

01:01:09.760 --> 01:01:15.600
okay? I told you. I told you.