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.