1 00:00:00,080 --> 00:00:03,320 Speaker 1: Welcome to today's edition of the Clay Travis and Buck 2 00:00:03,360 --> 00:00:07,920 Speaker 1: Sexton Show podcast. Welcome back. In appreciate all of you 3 00:00:07,960 --> 00:00:11,320 Speaker 1: hanging out with us. We roll through the Thursday edition 4 00:00:11,440 --> 00:00:16,159 Speaker 1: of the program. We were talking with you about the 5 00:00:16,200 --> 00:00:21,360 Speaker 1: craziness coming out of the NHL over their the NHL 6 00:00:21,440 --> 00:00:25,840 Speaker 1: media really and their insanity as it pertains to a 7 00:00:25,880 --> 00:00:29,240 Speaker 1: guy who decided not to wear a Pride jersey. Encourage 8 00:00:29,280 --> 00:00:31,040 Speaker 1: you to go check that out. Download the podcast. You 9 00:00:31,040 --> 00:00:33,640 Speaker 1: can hear all of our conversations every single day. Search 10 00:00:33,640 --> 00:00:36,840 Speaker 1: out Clay Travis, search out Buck Sexton. Lots of original 11 00:00:37,400 --> 00:00:41,760 Speaker 1: non airing on the radio content coming to the podcast feed. 12 00:00:42,159 --> 00:00:45,000 Speaker 1: You're gonna love it. We joined now by our buddy 13 00:00:45,040 --> 00:00:50,920 Speaker 1: Alex Barrenson for the latest on the COVID shot data 14 00:00:51,120 --> 00:00:56,360 Speaker 1: and Alex yesterday on your sub stack very alarming data 15 00:00:56,480 --> 00:01:00,000 Speaker 1: that is coming out. We've moved from I think everybody 16 00:00:59,800 --> 00:01:05,080 Speaker 1: basically acknowledges, generally speaking that the COVID shot does not 17 00:01:05,319 --> 00:01:08,120 Speaker 1: do anywhere near what it was promised to do and 18 00:01:08,200 --> 00:01:13,760 Speaker 1: at best has some small prophylactic value for a relatively 19 00:01:13,800 --> 00:01:16,560 Speaker 1: short period of time three or four months after a 20 00:01:16,600 --> 00:01:20,960 Speaker 1: shot is given. Now it's moving from it doesn't do 21 00:01:21,200 --> 00:01:25,280 Speaker 1: very much the story. Alex too, there may be actual 22 00:01:25,440 --> 00:01:27,920 Speaker 1: harm done by these shots. What can you tell us 23 00:01:27,959 --> 00:01:31,399 Speaker 1: about the latest data? Is that an accurate trajectory of 24 00:01:31,440 --> 00:01:35,720 Speaker 1: how you would assess the narrative surrounding these shots. Well, 25 00:01:35,880 --> 00:01:38,039 Speaker 1: I mean I would say that the people who've defended 26 00:01:38,080 --> 00:01:42,319 Speaker 1: them would still insist that they that they reduced severe 27 00:01:42,360 --> 00:01:45,560 Speaker 1: disease and death. I mean, that's the claim that that no, 28 00:01:45,720 --> 00:01:49,080 Speaker 1: they don't stop in faction, No they don't sup tradmission. Yeah, 29 00:01:49,160 --> 00:01:51,520 Speaker 1: you might even be at somewhat higher risk of being 30 00:01:51,520 --> 00:01:53,720 Speaker 1: infected if you've gotten a bunch of boosters in the 31 00:01:53,800 --> 00:01:57,080 Speaker 1: in the omicron era, but they do stop severe disease 32 00:01:57,120 --> 00:01:58,920 Speaker 1: and death, and you know, and to and to make 33 00:01:58,960 --> 00:02:03,000 Speaker 1: that case, they rely on a bunch of data that Um, 34 00:02:03,040 --> 00:02:06,400 Speaker 1: that's that that that I could go through and sort 35 00:02:06,440 --> 00:02:10,280 Speaker 1: of explain why it's problematic, But but that would take 36 00:02:10,280 --> 00:02:13,120 Speaker 1: the whole segment. So instead, let let me let me 37 00:02:13,160 --> 00:02:16,480 Speaker 1: talk about sort of why I'm more concerned right now 38 00:02:16,520 --> 00:02:18,880 Speaker 1: than I you know, and I think I talking to 39 00:02:18,919 --> 00:02:21,200 Speaker 1: you now for almost two years. You hear when I 40 00:02:21,240 --> 00:02:23,840 Speaker 1: think things are you know, getting better. You hear when 41 00:02:23,840 --> 00:02:25,760 Speaker 1: I think things are getting worse. I certainly a few 42 00:02:25,760 --> 00:02:28,359 Speaker 1: months ago thought I really thought we were we were 43 00:02:28,480 --> 00:02:32,359 Speaker 1: probably coming out of this um and uh, and now 44 00:02:32,400 --> 00:02:35,360 Speaker 1: I'm much more concerned than I was. And the reason is, uh, 45 00:02:35,760 --> 00:02:39,040 Speaker 1: it's twofold. It's when you look at some of the 46 00:02:39,440 --> 00:02:42,880 Speaker 1: all cosmotality in others. Then one number that truly can't 47 00:02:42,919 --> 00:02:45,840 Speaker 1: be faked is how many people are dying. Right if 48 00:02:45,880 --> 00:02:48,200 Speaker 1: you're in the United States or you're in Europe, you're 49 00:02:48,200 --> 00:02:50,240 Speaker 1: really almost anywhere in the world with a with a 50 00:02:50,320 --> 00:02:54,240 Speaker 1: functioning government, they count births and they count death okay, 51 00:02:54,400 --> 00:02:57,720 Speaker 1: and those numbers, um, you know, some places report them 52 00:02:57,720 --> 00:02:59,960 Speaker 1: more quickly than others. The US actually doesn't do that 53 00:03:00,080 --> 00:03:03,440 Speaker 1: good a job of reporting quickly. But in places that 54 00:03:04,440 --> 00:03:07,200 Speaker 1: for most of last year, in places that used the 55 00:03:07,240 --> 00:03:10,320 Speaker 1: advanced vaccines, especially the mr Anda vaccines which are their 56 00:03:10,360 --> 00:03:14,519 Speaker 1: fires are in Materna vaccines, excess deaths have been running 57 00:03:14,520 --> 00:03:18,919 Speaker 1: hot okay, non COVID mostly, And that's not what anybody 58 00:03:18,960 --> 00:03:21,800 Speaker 1: expected when this whole thing began. They thought, Hey, there's 59 00:03:21,800 --> 00:03:23,240 Speaker 1: going to be a bunch of old six people who 60 00:03:23,280 --> 00:03:24,839 Speaker 1: died from COVID, and then for a couple of years, 61 00:03:24,840 --> 00:03:28,360 Speaker 1: we're probably gonna actually pretty low deaths because the people 62 00:03:28,360 --> 00:03:31,000 Speaker 1: who died from COVID were very sick and likely to 63 00:03:31,080 --> 00:03:34,040 Speaker 1: die in the next six months to two years anyway, 64 00:03:34,520 --> 00:03:36,360 Speaker 1: And that's not what's happened. We've had a lot of 65 00:03:36,360 --> 00:03:39,120 Speaker 1: extra deaths, and in the last couple of weeks actually 66 00:03:39,640 --> 00:03:42,720 Speaker 1: the numbers have gone way up again, to the point 67 00:03:42,720 --> 00:03:45,520 Speaker 1: in Europe where they're as bad as they were really 68 00:03:45,520 --> 00:03:50,120 Speaker 1: at any time in the COVID era. And remember when Italy, 69 00:03:50,720 --> 00:03:53,480 Speaker 1: when a few countries in Europe had bad excess deaths 70 00:03:53,920 --> 00:03:56,480 Speaker 1: in March twenty twenty, we shut the world down. It 71 00:03:56,600 --> 00:03:58,960 Speaker 1: was a really big deal. And now this is just 72 00:03:59,000 --> 00:04:02,880 Speaker 1: sort of happening and we're basically the media is ignoring it. Okay, 73 00:04:02,880 --> 00:04:05,160 Speaker 1: but the numbers are real. You can find them yourself 74 00:04:05,200 --> 00:04:07,800 Speaker 1: if you know where to look. They're publicly reported, and 75 00:04:07,920 --> 00:04:11,720 Speaker 1: they're bad, and no one has a good explanation for that. Well, Alex, 76 00:04:11,760 --> 00:04:13,840 Speaker 1: that's the next thing I wanted to ask you is 77 00:04:14,280 --> 00:04:16,599 Speaker 1: do do you have a theory or a set of 78 00:04:16,640 --> 00:04:19,520 Speaker 1: theories as to what is going on that's producing this 79 00:04:20,160 --> 00:04:24,680 Speaker 1: very obviously troubling data. Yeah. So so okay, I mean, 80 00:04:24,720 --> 00:04:27,440 Speaker 1: so you can say, well, this is delayed medical care, 81 00:04:27,560 --> 00:04:30,120 Speaker 1: but that doesn't make any sense at this point. You know, 82 00:04:30,120 --> 00:04:32,760 Speaker 1: we're sort of two years out from the lockdowns, like that, 83 00:04:33,040 --> 00:04:35,040 Speaker 1: why now, why would this be happening now? Or you 84 00:04:35,040 --> 00:04:37,240 Speaker 1: can say, well, this is long COVID, except when you 85 00:04:37,279 --> 00:04:39,679 Speaker 1: actually trying to find a mechanism that makes any sense 86 00:04:39,720 --> 00:04:43,080 Speaker 1: for long COVID, you can't find one. And there's data showing, 87 00:04:43,120 --> 00:04:45,080 Speaker 1: for example, that when you have mild COVID, A very 88 00:04:45,080 --> 00:04:46,840 Speaker 1: big study that came out a few weeks ago out 89 00:04:46,839 --> 00:04:48,960 Speaker 1: of Israel. They looked at a lot of people who've 90 00:04:48,960 --> 00:04:51,120 Speaker 1: had mild COVID and compared them to a lot of 91 00:04:51,160 --> 00:04:53,840 Speaker 1: people who didn't and guess what in the next year, 92 00:04:54,320 --> 00:04:56,720 Speaker 1: the people who had COVID but not a severe case 93 00:04:57,000 --> 00:04:59,839 Speaker 1: and the people who didn't have COVID had basically exactly 94 00:05:00,000 --> 00:05:02,840 Speaker 1: the same number of possiblizations over the next twelve months. Okay, 95 00:05:03,200 --> 00:05:06,719 Speaker 1: so so long COVID. I mean, it does not really 96 00:05:06,760 --> 00:05:08,800 Speaker 1: make sense to me as an explanation. So what do 97 00:05:08,880 --> 00:05:11,839 Speaker 1: we know. We know that we vaccinated an enormous number 98 00:05:11,880 --> 00:05:14,320 Speaker 1: of people with these vaccines that we didn't have long 99 00:05:14,400 --> 00:05:16,800 Speaker 1: term safety data on. And now we get to the 100 00:05:16,839 --> 00:05:19,200 Speaker 1: second part of this, why this is concerning We are 101 00:05:19,240 --> 00:05:23,760 Speaker 1: now finding out that these vaccines seem to cause immune 102 00:05:23,800 --> 00:05:26,919 Speaker 1: system changes that we're not predicted, that we didn't expect. 103 00:05:26,960 --> 00:05:29,520 Speaker 1: And there's two very good papers, both of which came 104 00:05:29,520 --> 00:05:33,040 Speaker 1: out of Germany in the last month, showing that after 105 00:05:33,080 --> 00:05:37,520 Speaker 1: you get the mRNA is, your immune system essentially stopped 106 00:05:37,720 --> 00:05:45,279 Speaker 1: really trying to fight part of the COVID, part of 107 00:05:45,320 --> 00:05:50,719 Speaker 1: the coronavirus. Okay, I'm simplifying and exaggerating, but you make 108 00:05:50,760 --> 00:05:54,599 Speaker 1: antibodies to the coronavirus, and over time you start to 109 00:05:54,640 --> 00:05:57,120 Speaker 1: make more and more of a kind of antibody that 110 00:05:57,360 --> 00:06:01,080 Speaker 1: isn't very good at fighting the coronavirus. And the theory is, 111 00:06:01,160 --> 00:06:04,119 Speaker 1: although I don't think we know why yet for sure, 112 00:06:04,720 --> 00:06:08,240 Speaker 1: the theory is because the vaccines are so good at 113 00:06:08,240 --> 00:06:12,000 Speaker 1: getting your immune system redded up early on, it eventually 114 00:06:12,080 --> 00:06:15,120 Speaker 1: has to downregulate. It's like it's like it's like if 115 00:06:15,160 --> 00:06:18,120 Speaker 1: you flood the engine, you know eventually you're going to 116 00:06:18,200 --> 00:06:20,560 Speaker 1: burn it out, and so you have to lay off. 117 00:06:20,720 --> 00:06:24,840 Speaker 1: And that seems to be a problem that was not anticipated, 118 00:06:24,880 --> 00:06:27,080 Speaker 1: at least not by the company. And then there's this 119 00:06:27,120 --> 00:06:28,520 Speaker 1: paper and this is why you know, that's why you 120 00:06:28,560 --> 00:06:30,440 Speaker 1: guys asked me on today a paper that came out 121 00:06:30,440 --> 00:06:35,559 Speaker 1: of China just a few weeks ago showing that when 122 00:06:35,600 --> 00:06:40,200 Speaker 1: people had went not people when they gave mice repeated 123 00:06:40,279 --> 00:06:45,000 Speaker 1: injections of a version of a COVID vaccine after the 124 00:06:45,040 --> 00:06:49,320 Speaker 1: fourth shot, but in the fifth and six shots, essentially 125 00:06:49,360 --> 00:06:52,520 Speaker 1: their immune systems collapsed against COVID. Now people are gonna 126 00:06:52,520 --> 00:06:55,320 Speaker 1: say it's mice, it's true. They're gonna say this is 127 00:06:55,320 --> 00:06:58,040 Speaker 1: not the COVID vaccine we get in the United States. 128 00:06:58,040 --> 00:07:00,920 Speaker 1: It's not the mRNA. That's true. They're gonna say it's 129 00:07:00,920 --> 00:07:04,040 Speaker 1: a fifth shot and a sixth shot. That's true. So 130 00:07:04,200 --> 00:07:06,839 Speaker 1: I'm not saying that this proves that this is happening 131 00:07:06,880 --> 00:07:09,240 Speaker 1: in the United States. What I'm saying is, against this 132 00:07:09,400 --> 00:07:14,240 Speaker 1: backdrop of this big problem with excess mortality and the 133 00:07:14,240 --> 00:07:17,560 Speaker 1: fact that COVID hasn't gone away, we're getting more and 134 00:07:17,640 --> 00:07:20,560 Speaker 1: more evidence that these vaccines on a cellular level are 135 00:07:20,640 --> 00:07:23,600 Speaker 1: doing stuff that we didn't expect and that we probably 136 00:07:23,640 --> 00:07:26,720 Speaker 1: don't want. How scared would you be if you'd gotten 137 00:07:26,760 --> 00:07:30,160 Speaker 1: five or six COVID shots? Oh, I mean, if I'd 138 00:07:30,160 --> 00:07:33,000 Speaker 1: gotten five or six, I'd be nervous at this point. 139 00:07:33,200 --> 00:07:35,240 Speaker 1: I don't think that's a good idea. I think the 140 00:07:35,280 --> 00:07:38,760 Speaker 1: booster campaign should essentially be halted at this point because, 141 00:07:39,000 --> 00:07:42,320 Speaker 1: and here's the thing, there's no upside. Okay, at best, 142 00:07:42,360 --> 00:07:45,280 Speaker 1: you're getting some extra antibodies that last a matter of 143 00:07:45,280 --> 00:07:48,640 Speaker 1: weeks and don't work very well against omicrons. So why 144 00:07:48,640 --> 00:07:52,120 Speaker 1: are we doing this to ourselves? The core that we 145 00:07:52,200 --> 00:07:55,200 Speaker 1: don't want to have happen is we know the antibody's 146 00:07:55,360 --> 00:07:57,680 Speaker 1: switch is happening. Okay, we know this, and we know 147 00:07:57,800 --> 00:08:00,440 Speaker 1: also that the anybody sift the vaccines produced don't work 148 00:08:00,480 --> 00:08:03,520 Speaker 1: that way. Later, you still have T cells, Okay, you 149 00:08:03,520 --> 00:08:07,840 Speaker 1: still have this back line of defense that if your 150 00:08:07,840 --> 00:08:11,120 Speaker 1: cells get infected, the T cells go and attack those 151 00:08:11,120 --> 00:08:15,480 Speaker 1: cells and prevent the virus from you know, replicating out 152 00:08:15,480 --> 00:08:18,880 Speaker 1: of control. Okay, you have to have T cells, right, 153 00:08:19,320 --> 00:08:21,240 Speaker 1: And what we don't want to do is follow a 154 00:08:21,320 --> 00:08:24,320 Speaker 1: course of action that causes those to burn out. And 155 00:08:24,440 --> 00:08:27,880 Speaker 1: that should be where the focus of the public health 156 00:08:27,920 --> 00:08:30,280 Speaker 1: and the vaccine coming. We should be talking about this 157 00:08:30,360 --> 00:08:33,320 Speaker 1: openly and figuring out if that's a list right now. 158 00:08:33,400 --> 00:08:36,120 Speaker 1: I don't think that's too much an ask for Alex. 159 00:08:36,280 --> 00:08:38,559 Speaker 1: And we're speaking to Alex Barrenson. You can all subscribe 160 00:08:38,600 --> 00:08:43,360 Speaker 1: to his sub stack Alex Is there is there any 161 00:08:44,440 --> 00:08:50,440 Speaker 1: historical precedent for this kind of of taking a shot 162 00:08:50,480 --> 00:08:54,959 Speaker 1: again and again and again to create an immune system 163 00:08:55,040 --> 00:08:59,439 Speaker 1: boost like this that has ended up working out very 164 00:08:59,480 --> 00:09:02,120 Speaker 1: well with a high level of efficacy. I mean, is 165 00:09:02,160 --> 00:09:06,240 Speaker 1: this totally uncharted territory? Totally uncharted? I mean, you can 166 00:09:06,240 --> 00:09:08,679 Speaker 1: compare it to the flu vaccine, and that's not really 167 00:09:08,720 --> 00:09:10,520 Speaker 1: a great comparison for the people who want to do 168 00:09:10,559 --> 00:09:13,559 Speaker 1: this right. I mean, people people have been pressed to 169 00:09:13,600 --> 00:09:16,280 Speaker 1: get the flu vaccine aggressively. For the last twenty years. 170 00:09:16,320 --> 00:09:17,920 Speaker 1: We give out a lot more flu shots than we 171 00:09:18,000 --> 00:09:19,640 Speaker 1: used to. I shouldn't even call a vaccine. Really, they 172 00:09:19,640 --> 00:09:22,600 Speaker 1: don't even call a vaccine. It doesn't work very well, 173 00:09:22,800 --> 00:09:25,800 Speaker 1: and the number of flu deaths in the last thirty 174 00:09:25,880 --> 00:09:30,160 Speaker 1: or forty years has actually increased dramatically. So the flu 175 00:09:30,280 --> 00:09:33,400 Speaker 1: vaccine doesn't work very well. Okay, but at least we 176 00:09:33,520 --> 00:09:36,840 Speaker 1: know how the flu vaccine works. Okay, it's a pretty 177 00:09:36,920 --> 00:09:41,600 Speaker 1: straightforward vaccine. The covid vaccine we're now learning doesn't work 178 00:09:41,760 --> 00:09:46,120 Speaker 1: very well either, except it has all these other issues 179 00:09:46,160 --> 00:09:49,440 Speaker 1: that we didn't anticipate, and it works in a completely 180 00:09:49,480 --> 00:09:51,640 Speaker 1: different way than the flu vaccine. So no, there is 181 00:09:51,679 --> 00:09:54,920 Speaker 1: no precedent for what we've done in the last two years. Alex. 182 00:09:55,000 --> 00:09:58,160 Speaker 1: What's scary about this is the I would say risk 183 00:09:58,320 --> 00:10:03,760 Speaker 1: profile of the COVID shots continue to get worse, and 184 00:10:03,880 --> 00:10:08,960 Speaker 1: the risk reward obviously continues to get worse. How much 185 00:10:09,040 --> 00:10:12,760 Speaker 1: worse can it get? And and as a tie in 186 00:10:12,840 --> 00:10:17,319 Speaker 1: with that, is there good data on all cause mortality 187 00:10:17,360 --> 00:10:20,760 Speaker 1: from countries that did not give a lot of COVID shots. 188 00:10:20,760 --> 00:10:23,120 Speaker 1: Those tend I would imagine to be more Third world 189 00:10:23,160 --> 00:10:26,040 Speaker 1: countries in a generality, and maybe their data is not 190 00:10:26,160 --> 00:10:30,360 Speaker 1: as reliable. But in let's say, poor African countries, does 191 00:10:30,400 --> 00:10:33,120 Speaker 1: there seem to be also a higher rate of death 192 00:10:33,440 --> 00:10:36,640 Speaker 1: in those countries like we would see in England or 193 00:10:36,720 --> 00:10:40,400 Speaker 1: Israel or the United States? Great, great question, And I've 194 00:10:40,400 --> 00:10:42,440 Speaker 1: been trying to find that data and I have not 195 00:10:42,559 --> 00:10:44,560 Speaker 1: been able to find it for exactly the reason you 196 00:10:44,600 --> 00:10:48,120 Speaker 1: say these are they're poor countries and they report this 197 00:10:48,160 --> 00:10:50,840 Speaker 1: stuff flow when they report it at all. That China 198 00:10:50,840 --> 00:10:53,640 Speaker 1: would actually be a really good um place to it, 199 00:10:53,679 --> 00:10:57,320 Speaker 1: because China, you know, has a pretty modern economy anyway, 200 00:10:57,480 --> 00:10:59,600 Speaker 1: and uh and probably collect us to put as we know, 201 00:10:59,640 --> 00:11:02,680 Speaker 1: we can't really trust the Chinese data on a national 202 00:11:02,760 --> 00:11:05,640 Speaker 1: level that much. So there is some I will say 203 00:11:05,720 --> 00:11:10,199 Speaker 1: Eastern Europe, there are some countries that are reporting relatively 204 00:11:10,400 --> 00:11:14,320 Speaker 1: low deaths in the last you know, the last or 205 00:11:14,480 --> 00:11:17,079 Speaker 1: nine months or so. The country like Bulgaria, So those 206 00:11:17,080 --> 00:11:20,120 Speaker 1: countries have bad COVID waves worse than Western Europe to 207 00:11:19,960 --> 00:11:22,120 Speaker 1: be to be frank with you, they didn't use a 208 00:11:22,120 --> 00:11:25,440 Speaker 1: lot of the MR and A vaccines but seems less 209 00:11:25,440 --> 00:11:27,839 Speaker 1: so that so that is, that's the one place I 210 00:11:27,880 --> 00:11:29,760 Speaker 1: can point to and say, this is sort of what 211 00:11:29,800 --> 00:11:32,040 Speaker 1: I would expect to see if it's the vaccines that 212 00:11:32,080 --> 00:11:33,839 Speaker 1: are causing the problem. But if you're asking in a 213 00:11:33,880 --> 00:11:36,840 Speaker 1: worldwide basis, I've been trying to find that data and 214 00:11:36,880 --> 00:11:39,079 Speaker 1: I have not been able to find it yet. Alice, 215 00:11:39,120 --> 00:11:45,480 Speaker 1: when you see people sharing stories news stories about young 216 00:11:45,720 --> 00:11:49,080 Speaker 1: athletic individuals, some professional athletes, some are high school athletes, 217 00:11:49,160 --> 00:11:53,200 Speaker 1: whatever the case may be, at heart trouble, how much 218 00:11:53,200 --> 00:11:56,400 Speaker 1: of this do you think is in any way tied 219 00:11:56,440 --> 00:11:59,199 Speaker 1: to the vaccine based on the data right now versus 220 00:11:59,320 --> 00:12:02,320 Speaker 1: now everyone and every time they see somebody who's younger, 221 00:12:02,600 --> 00:12:05,360 Speaker 1: who's an athlete and has any hard issue, there is 222 00:12:05,400 --> 00:12:09,560 Speaker 1: this there's a jump to conclusion that happens. I think 223 00:12:09,559 --> 00:12:11,120 Speaker 1: it's a lot of the latter. I mean, I think 224 00:12:11,120 --> 00:12:13,880 Speaker 1: we just don't know in any individual case. I mean, 225 00:12:14,280 --> 00:12:17,840 Speaker 1: you can look, there are certain cases, very very rare, 226 00:12:17,880 --> 00:12:19,320 Speaker 1: and I don't think that you know, we're not talking 227 00:12:19,360 --> 00:12:22,080 Speaker 1: about themar Hamlet here. We're talking about, you know, like 228 00:12:22,120 --> 00:12:25,679 Speaker 1: a handful of cases where people have gotten vaccine, they've 229 00:12:25,720 --> 00:12:29,240 Speaker 1: gone to the you know, er with myocarditis, they've died. 230 00:12:29,679 --> 00:12:32,319 Speaker 1: Autopsies have been done and they've showed that that myocarditis 231 00:12:32,480 --> 00:12:35,840 Speaker 1: was conclusively linked to the vaccine, but based on sort 232 00:12:35,840 --> 00:12:39,280 Speaker 1: of like the profile of the inflammatory response and other things. 233 00:12:39,600 --> 00:12:42,560 Speaker 1: But that is not what's happening in the big cases. 234 00:12:42,600 --> 00:12:45,000 Speaker 1: And look, I've been criticized, you know, and I know 235 00:12:45,200 --> 00:12:47,719 Speaker 1: I know you have too, for um, you know, for 236 00:12:47,960 --> 00:12:52,040 Speaker 1: for occasionally pointing these cases out and saying what happens here? 237 00:12:52,400 --> 00:12:55,760 Speaker 1: But what I think is happening the bigger question is, Look, 238 00:12:56,040 --> 00:12:58,080 Speaker 1: I can find you a story from the last couple 239 00:12:58,080 --> 00:13:01,560 Speaker 1: of days showing that hospitals in England have been overrun. Okay, 240 00:13:01,640 --> 00:13:04,240 Speaker 1: I can point you to government data release this morning 241 00:13:04,320 --> 00:13:08,040 Speaker 1: from Scotland that Scotland had more death last week than 242 00:13:08,280 --> 00:13:10,120 Speaker 1: I think in the last twenty years. You have to 243 00:13:10,200 --> 00:13:13,080 Speaker 1: go back to two thousand to find when they had 244 00:13:13,120 --> 00:13:15,559 Speaker 1: more than two thousand deaths in a week. Okay, so 245 00:13:15,679 --> 00:13:19,440 Speaker 1: people are aware broadly that the vaccines didn't work. It's promised, 246 00:13:19,440 --> 00:13:21,960 Speaker 1: and they're starting to be aware that there's something going 247 00:13:21,960 --> 00:13:25,400 Speaker 1: on with excess death and it is the refusal of 248 00:13:25,480 --> 00:13:28,720 Speaker 1: government health authorities to deal with this in an honest 249 00:13:28,760 --> 00:13:32,720 Speaker 1: way that's causing the conspiracy theories. All right, let's pretend 250 00:13:33,120 --> 00:13:35,559 Speaker 1: last question for you, Alex. Let's pretend President Ron de 251 00:13:35,640 --> 00:13:38,160 Speaker 1: Santis was in office right now and he was willing 252 00:13:38,200 --> 00:13:41,040 Speaker 1: to look at this data as he has been in Florida. 253 00:13:41,240 --> 00:13:44,640 Speaker 1: What should the government do? Let's pretend Joe Biden suddenly 254 00:13:44,960 --> 00:13:48,760 Speaker 1: got Jesus and brought you in and said, hey, you're right, 255 00:13:49,000 --> 00:13:52,480 Speaker 1: COVID is a disaster. These shots. What should the government 256 00:13:52,520 --> 00:13:55,920 Speaker 1: do in an ideal world right now? Right now? We 257 00:13:56,000 --> 00:13:58,679 Speaker 1: got to find out the impact of this IgG for 258 00:13:58,800 --> 00:14:01,920 Speaker 1: a class switch? Is this anybody class switch? We need 259 00:14:01,960 --> 00:14:04,240 Speaker 1: to figure out, you know who this is happening to 260 00:14:04,320 --> 00:14:07,160 Speaker 1: the most and sort of try to look perspectively at 261 00:14:07,160 --> 00:14:09,840 Speaker 1: whether or not they're getting sicker. We need to look 262 00:14:09,840 --> 00:14:13,640 Speaker 1: at the various causes of all cause mortality. You know 263 00:14:13,679 --> 00:14:16,920 Speaker 1: what's driving the extra mortality in the US and elsewhere, 264 00:14:16,960 --> 00:14:19,160 Speaker 1: and try to find out, you know, are people who 265 00:14:19,240 --> 00:14:22,000 Speaker 1: got four shots more likely to be in this group. 266 00:14:22,040 --> 00:14:25,760 Speaker 1: There's a lot of really complicated epidemiology and there's complicated 267 00:14:25,840 --> 00:14:29,360 Speaker 1: basic cellular work that needs to happen. But there we 268 00:14:29,400 --> 00:14:31,560 Speaker 1: can get some answers to this. And in the meantime, 269 00:14:31,560 --> 00:14:34,000 Speaker 1: what I would say is, you know, if Ronnes Sayors 270 00:14:34,000 --> 00:14:35,720 Speaker 1: are in charge, I bet you we'd be suspending the 271 00:14:35,720 --> 00:14:38,720 Speaker 1: booster campaigns. And that would be a good thing right now, 272 00:14:38,760 --> 00:14:42,200 Speaker 1: because again, you know what Bucks said, there's no there's 273 00:14:42,240 --> 00:14:44,720 Speaker 1: no good, there's no reward here, there's only risk of 274 00:14:44,880 --> 00:14:48,400 Speaker 1: doing this at this point. Thank you, Alex. We're going 275 00:14:48,440 --> 00:14:50,960 Speaker 1: to keep updated, tell people to check out the sub 276 00:14:51,000 --> 00:14:53,840 Speaker 1: stack as always, and we appreciate your time. Thanks for 277 00:14:53,880 --> 00:14:57,040 Speaker 1: having me. Guys, it's Alex Berenson and that is alarming. 278 00:14:57,040 --> 00:14:58,600 Speaker 1: We'll discuss break it down a little bit more for 279 00:14:58,640 --> 00:15:01,040 Speaker 1: you in the meantime. Hillsdale Call it's bringing their teaching 280 00:15:01,080 --> 00:15:04,880 Speaker 1: to you. They're offering dozens of free online video courses 281 00:15:04,880 --> 00:15:07,800 Speaker 1: that make learning fun. You can watch one or more 282 00:15:07,920 --> 00:15:10,400 Speaker 1: on a topic that fascinates you. For example, do you 283 00:15:10,480 --> 00:15:13,239 Speaker 1: know Hillsdale has a lot of admiration for the Constitution. 284 00:15:13,280 --> 00:15:16,520 Speaker 1: That's pretty important, and they have Constitution one oh one. 285 00:15:16,640 --> 00:15:19,040 Speaker 1: It's one of their most popular courses. 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Pick one of more than thirty free Hillsdale courses. 293 00:15:44,080 --> 00:15:47,080 Speaker 1: Learn something new, become a more educated American in twenty 294 00:15:47,120 --> 00:15:50,920 Speaker 1: twenty three to Clay and Buck four Hillsdale dot com. 295 00:15:51,200 --> 00:15:54,280 Speaker 1: Start your free course today Clay and Buck four Hillsdale 296 00:15:54,320 --> 00:15:59,560 Speaker 1: dot Com. Clay Travis and Buck Sexton chuck up a 297 00:15:59,640 --> 00:16:03,280 Speaker 1: win for Team Reality. Welcome back to Clay an Buck. 298 00:16:03,320 --> 00:16:06,840 Speaker 1: You know one thing that I can say was was 299 00:16:06,880 --> 00:16:11,000 Speaker 1: a bit of happy news on the COVID front. Did 300 00:16:11,040 --> 00:16:17,480 Speaker 1: you see Clay that Jacinda Arderne Yes, the Tyrant of 301 00:16:17,600 --> 00:16:22,040 Speaker 1: New Zealand, has put out as a little video saying 302 00:16:22,080 --> 00:16:24,720 Speaker 1: that she will not be running again. I know New 303 00:16:24,800 --> 00:16:26,800 Speaker 1: Zealand is on the other side of the world, it 304 00:16:26,880 --> 00:16:30,120 Speaker 1: is a small country with a small population, etc. All 305 00:16:30,200 --> 00:16:34,440 Speaker 1: of that said, she was among the worst leaders in 306 00:16:34,480 --> 00:16:37,400 Speaker 1: the entire world on this issue, and I would like 307 00:16:37,480 --> 00:16:41,720 Speaker 1: to think that the Kiwis decided they had had enough 308 00:16:41,920 --> 00:16:45,200 Speaker 1: of her crazy town. I don't know. I would like 309 00:16:45,280 --> 00:16:49,880 Speaker 1: to think that the challenges buck Most of the craziest 310 00:16:49,960 --> 00:16:54,640 Speaker 1: COVID politicians still have their jobs. Gavin Newsom still governor, 311 00:16:54,840 --> 00:16:59,840 Speaker 1: Gretchen Whitmer's still governor. Andrew Cuomo's not governor, but that's 312 00:17:00,040 --> 00:17:02,920 Speaker 1: only because he got caught in a sexual harassment scandal 313 00:17:02,960 --> 00:17:04,880 Speaker 1: and they decided to go ahead and ax him out. 314 00:17:05,920 --> 00:17:09,159 Speaker 1: Who is someone who got everything wrong on COVID, that 315 00:17:09,400 --> 00:17:13,280 Speaker 1: is in the political realm that actually paid consequences. No 316 00:17:13,320 --> 00:17:15,359 Speaker 1: one really that I can think of, that lost their 317 00:17:15,480 --> 00:17:18,639 Speaker 1: job because they got everything wrong on COVID, Which is 318 00:17:18,680 --> 00:17:23,600 Speaker 1: why I'm so disappointed in many ways and ultimately believe 319 00:17:23,720 --> 00:17:28,200 Speaker 1: that really twenty twenty four, if there were truth and 320 00:17:28,359 --> 00:17:31,680 Speaker 1: justice to me, should be Roun de Santis against Gavin 321 00:17:31,800 --> 00:17:35,280 Speaker 1: Newsom with a knockdown, drag out throw down on who 322 00:17:35,359 --> 00:17:38,199 Speaker 1: was the better governor responding to COVID, because that's the 323 00:17:38,200 --> 00:17:40,679 Speaker 1: most important decision that any of these politicians have had 324 00:17:40,720 --> 00:17:42,560 Speaker 1: to make in their lives, and many of them got 325 00:17:42,600 --> 00:17:46,760 Speaker 1: everything wrong, like Gavin Newsom. Nothing easy about owning your 326 00:17:46,760 --> 00:17:49,359 Speaker 1: own small business these days. I'm sure many of you 327 00:17:49,359 --> 00:17:51,399 Speaker 1: could use a break. If your business has five or 328 00:17:51,440 --> 00:17:54,680 Speaker 1: more employees, made it through COVID, you could be eligible 329 00:17:54,720 --> 00:17:56,920 Speaker 1: to receive a payroll tax rebate of up to twenty 330 00:17:56,960 --> 00:18:00,680 Speaker 1: six thousand dollars per employee, not alone, no payback, It's 331 00:18:00,680 --> 00:18:02,679 Speaker 1: a refund of your taxes. How do you get your 332 00:18:02,680 --> 00:18:06,160 Speaker 1: business this refund money? Go get refunds dot Com their 333 00:18:06,200 --> 00:18:10,120 Speaker 1: tax attorneys specialists little known payroll tax refund program. 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Don't miss out go to get 343 00:18:38,520 --> 00:18:41,920 Speaker 1: refunds dot com, No risk, high reward, Get refunds dot 344 00:18:41,960 --> 00:18:47,400 Speaker 1: Com and buck Sexton on the front Lines Welcome back 345 00:18:47,400 --> 00:18:51,639 Speaker 1: in Clay Travis buck Sexton Show producer Ali looked it up. 346 00:18:51,680 --> 00:18:53,440 Speaker 1: You heard Alex Barrenson at the top of the hour 347 00:18:53,560 --> 00:18:57,080 Speaker 1: talking about the dangers of the COVID shot. We had 348 00:18:57,160 --> 00:18:59,600 Speaker 1: him on right after what's considered to be a very 349 00:18:59,640 --> 00:19:04,640 Speaker 1: controversial perspective, which was that the COVID shots neither stopped 350 00:19:04,680 --> 00:19:08,840 Speaker 1: nor prevented the spread of COVID And I think based 351 00:19:08,920 --> 00:19:11,280 Speaker 1: on what you heard from Alex Berenson at the top 352 00:19:11,320 --> 00:19:16,159 Speaker 1: of this hour, the conversation is going to similarly shift 353 00:19:16,320 --> 00:19:19,720 Speaker 1: over the next several months and even into twenty twenty 354 00:19:19,720 --> 00:19:23,800 Speaker 1: four from Hey, the COVID shots they may have a 355 00:19:23,840 --> 00:19:27,040 Speaker 1: small protective effect, they'll keep you from dying. There still 356 00:19:27,119 --> 00:19:31,520 Speaker 1: is that argument out there to actually, they are doing 357 00:19:31,600 --> 00:19:34,720 Speaker 1: direct harm to people who got them, and the more 358 00:19:34,840 --> 00:19:38,600 Speaker 1: of them you got, the more harm you are potentially facing. Well, 359 00:19:38,800 --> 00:19:41,920 Speaker 1: wouldn't that be true if you just approach this from 360 00:19:41,920 --> 00:19:48,520 Speaker 1: a perspective of basic logic. Every pharmaceutical, every drug, everything 361 00:19:49,440 --> 00:19:52,919 Speaker 1: in excess or taken too many times has risks. You 362 00:19:52,960 --> 00:19:56,320 Speaker 1: can actually die from drinking too much water too fast, right, 363 00:19:56,320 --> 00:19:58,560 Speaker 1: I mean to take it to a true extreme, but 364 00:19:58,960 --> 00:20:01,960 Speaker 1: you know, whether it's thailand all or an antibiotic or 365 00:20:02,000 --> 00:20:04,720 Speaker 1: you name it, at some point you're taking too much 366 00:20:04,760 --> 00:20:08,800 Speaker 1: of it. We don't have any long term data on 367 00:20:09,040 --> 00:20:11,000 Speaker 1: what too much of it is. With a drug that 368 00:20:11,040 --> 00:20:13,280 Speaker 1: they came up with that was based on a brand 369 00:20:13,280 --> 00:20:16,159 Speaker 1: new technology. You know a lot of things in the 370 00:20:16,600 --> 00:20:19,960 Speaker 1: pharmaceutical world. It'll be a new delivery mechanism. You know, 371 00:20:20,000 --> 00:20:23,080 Speaker 1: instead of something that you inject, it's something that you 372 00:20:23,200 --> 00:20:25,080 Speaker 1: taken a pill, instead of something you taken a pill. 373 00:20:25,080 --> 00:20:27,040 Speaker 1: It's something you know, you rub on your skin, whatever. 374 00:20:27,840 --> 00:20:30,760 Speaker 1: This is brand new technology. There were no long term 375 00:20:30,840 --> 00:20:32,760 Speaker 1: studies on it, and now we're getting to the point 376 00:20:32,800 --> 00:20:36,040 Speaker 1: where their answer is we'll just keep taking more doses 377 00:20:36,080 --> 00:20:38,879 Speaker 1: of it. And I think I can't say based on 378 00:20:38,960 --> 00:20:42,480 Speaker 1: that alone, there's some terrible thing that's happened. Question was 379 00:20:42,560 --> 00:20:45,159 Speaker 1: so good, buck, which like, hey, give me a positive 380 00:20:45,200 --> 00:20:49,520 Speaker 1: story associated with needing to get four shots for something? Yeah? Right, 381 00:20:50,280 --> 00:20:52,399 Speaker 1: I mean, I think it's just it's really tough, and 382 00:20:52,600 --> 00:20:56,159 Speaker 1: that's why the buck the question of hey, if you 383 00:20:56,280 --> 00:21:01,080 Speaker 1: got the measles vaccine and you still got measle, take 384 00:21:01,119 --> 00:21:03,639 Speaker 1: it outside of COVID because it's so politicized. But if 385 00:21:03,720 --> 00:21:06,800 Speaker 1: you got the measles vaccine and you still got measles, 386 00:21:06,840 --> 00:21:10,000 Speaker 1: you'd be like, Man, this measles vaccine doesn't seem like 387 00:21:10,040 --> 00:21:12,200 Speaker 1: it did what it was supposed to. And they tried 388 00:21:12,240 --> 00:21:14,719 Speaker 1: to make they change the definition of vaccine first of all, 389 00:21:14,720 --> 00:21:15,720 Speaker 1: which is why I think you have to call it 390 00:21:15,760 --> 00:21:18,440 Speaker 1: the COVID shot. But they tried to be like they 391 00:21:18,720 --> 00:21:21,119 Speaker 1: lied to us so much. Buck, That's what's so frustrating 392 00:21:21,119 --> 00:21:24,720 Speaker 1: about this is they told us things that we knew 393 00:21:24,720 --> 00:21:28,000 Speaker 1: to be untrue based on our life experience, that we 394 00:21:28,000 --> 00:21:31,120 Speaker 1: were the ones who were misunderstanding. I also think that 395 00:21:31,240 --> 00:21:35,840 Speaker 1: when you understand the mentality of the Fauciites and those 396 00:21:36,440 --> 00:21:39,640 Speaker 1: people that were really pushing all this stuff, their belief 397 00:21:39,840 --> 00:21:43,119 Speaker 1: was that if the lie was in service of the cause, 398 00:21:43,160 --> 00:21:45,600 Speaker 1: it wasn't really a lie, or it wasn't really a problem. 399 00:21:45,960 --> 00:21:49,760 Speaker 1: So if they had to exaggerate how effective things were 400 00:21:49,960 --> 00:21:52,760 Speaker 1: to get us to take the vaccine, or if they 401 00:21:52,760 --> 00:21:55,960 Speaker 1: had to exaggerate how effective masks were, I think it 402 00:21:56,000 --> 00:21:58,040 Speaker 1: was the Atlantic in the summer of twenty twenty had 403 00:21:58,080 --> 00:22:00,440 Speaker 1: some peace where if we just all massed up properly, 404 00:22:00,880 --> 00:22:03,520 Speaker 1: you know, COVID debts would drop sixty percent or seven 405 00:22:03,520 --> 00:22:06,639 Speaker 1: basically in COVID was their argument like if everybody just 406 00:22:06,680 --> 00:22:09,680 Speaker 1: wore their masks, which is just lunacy. Yes, And what's 407 00:22:09,680 --> 00:22:11,399 Speaker 1: amazing is that, you know, Clay, you and I are 408 00:22:11,400 --> 00:22:14,840 Speaker 1: both guys who derive a lot of enjoyment when it 409 00:22:14,840 --> 00:22:18,760 Speaker 1: comes to reading history and all the stuff about masks 410 00:22:18,760 --> 00:22:22,960 Speaker 1: and masking we went through during the Spanish influenza. There 411 00:22:23,080 --> 00:22:25,560 Speaker 1: was a lot of back and forth. There were societies 412 00:22:25,560 --> 00:22:28,239 Speaker 1: of you know, the proper masking technique, and there were 413 00:22:28,280 --> 00:22:30,520 Speaker 1: some cities where there were huge fights over this issue. 414 00:22:30,760 --> 00:22:33,719 Speaker 1: It didn't do a damn thing. Okay, we ran through this, 415 00:22:33,800 --> 00:22:36,960 Speaker 1: didn't do anything. Then, it didn't do anything this time around. 416 00:22:37,600 --> 00:22:40,520 Speaker 1: And I think for anybody who wants to say, well, 417 00:22:40,600 --> 00:22:44,119 Speaker 1: we're past this, we're done, they haven't admitted they were wrong. 418 00:22:44,480 --> 00:22:47,400 Speaker 1: They still have the usage of emergency powers that they 419 00:22:47,400 --> 00:22:50,800 Speaker 1: can accelerate or enhance at any point in time if 420 00:22:50,800 --> 00:22:54,040 Speaker 1: they decide to. And I think that they view it 421 00:22:54,080 --> 00:22:58,240 Speaker 1: as really a test run for similar you know, oh, 422 00:22:58,280 --> 00:23:02,440 Speaker 1: it's an emergency do whatever we say conditioning going forward. 423 00:23:02,520 --> 00:23:04,920 Speaker 1: So this is about a lot more that even just 424 00:23:05,520 --> 00:23:07,880 Speaker 1: how how well did the shots work or not work. 425 00:23:07,960 --> 00:23:09,879 Speaker 1: This is about what kind of a society do we 426 00:23:09,920 --> 00:23:14,119 Speaker 1: live in. We got a test run of totalitarianism in America, 427 00:23:14,160 --> 00:23:18,679 Speaker 1: and honestly, it transform my sense of what a lot 428 00:23:18,720 --> 00:23:21,119 Speaker 1: of Americans will put up with and what they'll just 429 00:23:21,240 --> 00:23:25,160 Speaker 1: accept and go along with. It was appalling because people 430 00:23:25,200 --> 00:23:28,760 Speaker 1: weren't even just scared. They then turned into the enforcers 431 00:23:28,840 --> 00:23:31,239 Speaker 1: of the lunacy. Right, that's a whole. It's one thing. 432 00:23:31,240 --> 00:23:34,119 Speaker 1: If you want to go around wrapping your face in 433 00:23:34,240 --> 00:23:36,479 Speaker 1: saran wrap and oh I don't want to touch anything 434 00:23:36,560 --> 00:23:38,800 Speaker 1: and stay away from people. I mean, that's sad and 435 00:23:38,920 --> 00:23:42,359 Speaker 1: it's it's a mental illness on parade, But you know, 436 00:23:42,440 --> 00:23:44,560 Speaker 1: that's that's one thing. But the people that were going 437 00:23:44,560 --> 00:23:46,480 Speaker 1: around yelling at everybody else that they had to do 438 00:23:46,520 --> 00:23:48,399 Speaker 1: the same thing, and they wanted people to be arrested 439 00:23:48,400 --> 00:23:51,840 Speaker 1: who wouldn't do the same stuff. That was frightening and 440 00:23:51,920 --> 00:23:54,199 Speaker 1: it was happening in this country. And those people are 441 00:23:54,200 --> 00:23:57,880 Speaker 1: still out there and they think they're heroes. Albert Borla 442 00:23:58,160 --> 00:24:02,000 Speaker 1: is not surprisingly at the War Old Economic Forum in Davos. 443 00:24:02,600 --> 00:24:05,840 Speaker 1: There's a group called Rebel News. I'm not actually that 444 00:24:06,040 --> 00:24:09,119 Speaker 1: familiar with them. You may or may not be a Canadian. 445 00:24:09,760 --> 00:24:13,119 Speaker 1: It's kind of like the successor to Sun TV or 446 00:24:13,160 --> 00:24:16,320 Speaker 1: Sun News. Rather if anybody remembers that. Okay, So they 447 00:24:16,359 --> 00:24:21,160 Speaker 1: are following Albert Borla, the CEO of Visor, as he 448 00:24:21,280 --> 00:24:24,680 Speaker 1: is walking in the streets, trying to ask him questions. 449 00:24:24,720 --> 00:24:27,760 Speaker 1: Of course, Borla won't talk to anybody who will actually 450 00:24:27,760 --> 00:24:33,560 Speaker 1: share facts about how destructive and fraudulent his COVID shot is. 451 00:24:34,160 --> 00:24:37,720 Speaker 1: But I derived a great pleasure from all of this. 452 00:24:38,200 --> 00:24:42,000 Speaker 1: Listen to their questions as they are walking alongside Albert 453 00:24:42,040 --> 00:24:46,440 Speaker 1: Borla in Davos, calling out to his face the failure 454 00:24:46,640 --> 00:24:49,840 Speaker 1: of his of his COVID shot, that they made billions 455 00:24:49,840 --> 00:24:52,679 Speaker 1: of dollars off of ad Visor support. La, can I 456 00:24:52,720 --> 00:24:55,639 Speaker 1: ask you when did you know that the vaccines didn't 457 00:24:55,640 --> 00:24:58,760 Speaker 1: stop transmission? How long did you know that without saying 458 00:24:58,760 --> 00:25:01,640 Speaker 1: it publicly? Thank you very much. I mean, we now 459 00:25:01,720 --> 00:25:05,360 Speaker 1: know that the vaccines didn't stop transmission, but why did 460 00:25:05,400 --> 00:25:08,800 Speaker 1: you keep it secret? I won't have a nice day 461 00:25:09,080 --> 00:25:11,480 Speaker 1: until I know the answer. Is it time to apologize 462 00:25:11,480 --> 00:25:13,879 Speaker 1: to the world, sir, to give refunds back to the 463 00:25:13,880 --> 00:25:16,280 Speaker 1: countries that bought all their money into your vaccine that 464 00:25:16,359 --> 00:25:19,360 Speaker 1: doesn't work to your ineffective vaccine. Are you're not ashamed 465 00:25:19,400 --> 00:25:20,880 Speaker 1: of what you've done in the last couple of years, 466 00:25:20,960 --> 00:25:24,479 Speaker 1: gepany apologies to the public? Sir? What about the sudden deaths? 467 00:25:24,680 --> 00:25:27,040 Speaker 1: What do you have to say about young men dropping 468 00:25:27,080 --> 00:25:30,320 Speaker 1: dead of heart attacks every day? Are you used to 469 00:25:30,359 --> 00:25:33,439 Speaker 1: only sympathetic media so you don't know how to answer 470 00:25:33,440 --> 00:25:38,119 Speaker 1: any questions? Sam on you, sir, Shame on you. I 471 00:25:38,280 --> 00:25:40,080 Speaker 1: loved it. It's so great. If you haven't, if you 472 00:25:40,080 --> 00:25:41,719 Speaker 1: want to watch that video and you're as angry as 473 00:25:41,720 --> 00:25:44,480 Speaker 1: Buck and I have been. I found it somewhat cathartic 474 00:25:44,520 --> 00:25:46,600 Speaker 1: to watch him be confronted face to face with all 475 00:25:46,640 --> 00:25:49,919 Speaker 1: the wise that he spread, and you look at all 476 00:25:49,920 --> 00:25:53,880 Speaker 1: the people that made so much money off of this. Yes, 477 00:25:54,440 --> 00:25:58,840 Speaker 1: it's pretty remarkable in retrospect when you consider that they 478 00:25:58,840 --> 00:26:03,600 Speaker 1: were absolved any legal responsibility for whatever this thing does, 479 00:26:04,600 --> 00:26:06,639 Speaker 1: and that this was all pushed forward and pushed on 480 00:26:06,760 --> 00:26:09,840 Speaker 1: us with a force of government that had to be 481 00:26:09,920 --> 00:26:13,320 Speaker 1: stopped by the Supreme Court. I think there's not enough 482 00:26:13,359 --> 00:26:17,360 Speaker 1: time spent thinking about how Joe Biden tried to use 483 00:26:17,560 --> 00:26:21,240 Speaker 1: OSHA to force effectively everybody. I mean, I think, what 484 00:26:21,359 --> 00:26:23,040 Speaker 1: was it if you had one hundred or more employees 485 00:26:23,040 --> 00:26:25,560 Speaker 1: in your company and they were going to expand it 486 00:26:25,640 --> 00:26:28,359 Speaker 1: beyond that too, But they were going to use an 487 00:26:28,359 --> 00:26:31,800 Speaker 1: OSHA regulation to make everybody get an experimental vaccine. That 488 00:26:32,680 --> 00:26:34,920 Speaker 1: does anyone really think this works very well? I mean, 489 00:26:34,960 --> 00:26:36,960 Speaker 1: that's at this point. I would love to see the 490 00:26:37,080 --> 00:26:39,600 Speaker 1: data that shows that it works so well. When as 491 00:26:39,640 --> 00:26:43,359 Speaker 1: we know there it went from you won't get the shot, 492 00:26:43,400 --> 00:26:47,399 Speaker 1: I remember the argument from last summer summer twenty twenty one. 493 00:26:47,480 --> 00:26:51,320 Speaker 1: Rather it went from it's incredibly rare for you to 494 00:26:51,400 --> 00:26:54,000 Speaker 1: die from COVID if you get the COVID shot to 495 00:26:54,960 --> 00:26:57,320 Speaker 1: actually a lot of people die from COVID who get 496 00:26:57,320 --> 00:26:59,640 Speaker 1: the COVID shot, and would initially say it was rare. 497 00:26:59,640 --> 00:27:02,000 Speaker 1: Bucky said, President of the United States, a lot of 498 00:27:02,280 --> 00:27:04,200 Speaker 1: if you get the COVID shot, you will not die 499 00:27:04,200 --> 00:27:07,200 Speaker 1: of COVID. Yeah, I think that that is what he said. 500 00:27:07,760 --> 00:27:10,119 Speaker 1: They initially said. I mean, there's a clip of Biden 501 00:27:10,160 --> 00:27:13,199 Speaker 1: directly saying that in the summer of twenty one, and 502 00:27:13,960 --> 00:27:15,840 Speaker 1: of course initially they sold it and a lot of 503 00:27:15,840 --> 00:27:17,679 Speaker 1: you out there listening may have bought into what they 504 00:27:17,720 --> 00:27:21,119 Speaker 1: sold you, which was you will neither get nor transmit 505 00:27:21,200 --> 00:27:23,760 Speaker 1: the virus. Remember there's Rachel Maddow sitting on there and saying, 506 00:27:24,080 --> 00:27:26,280 Speaker 1: so it stops with you if you get the shot. 507 00:27:26,359 --> 00:27:29,240 Speaker 1: We now know, I mean they sold that. That's why 508 00:27:29,359 --> 00:27:31,879 Speaker 1: if you take it outside of the COVID shot discussion 509 00:27:31,880 --> 00:27:35,200 Speaker 1: and just say we were sold a product, doesn't matter 510 00:27:35,200 --> 00:27:38,879 Speaker 1: what that product was based on a fraudulent incentive, right 511 00:27:38,920 --> 00:27:41,480 Speaker 1: if they told you, hey, if you buy a Rolls Royce, 512 00:27:41,920 --> 00:27:46,280 Speaker 1: you'll never have to buy gas again for your car. Well, 513 00:27:46,320 --> 00:27:47,720 Speaker 1: and then you bought the Rolls Royce and the like, 514 00:27:47,760 --> 00:27:49,399 Speaker 1: Actually it has a gas tank, I'm gonna have to 515 00:27:49,440 --> 00:27:51,240 Speaker 1: fill it up with gas. Like I don't never have 516 00:27:51,280 --> 00:27:53,280 Speaker 1: to pay for gas again for the rest of my life. 517 00:27:53,600 --> 00:27:55,840 Speaker 1: That would be a fraudulent incentive for you to buy 518 00:27:55,880 --> 00:27:59,320 Speaker 1: that car any other car. They sold these shots based 519 00:27:59,320 --> 00:28:02,520 Speaker 1: on fraud juelant arguments, which is why. And guess what, 520 00:28:02,920 --> 00:28:06,280 Speaker 1: these companies all made billions of dollars, tens of billions 521 00:28:06,280 --> 00:28:10,280 Speaker 1: of dollars off our taxpayer money for shots that did 522 00:28:10,320 --> 00:28:12,600 Speaker 1: not work that our government mandated, which is why I've 523 00:28:12,600 --> 00:28:13,800 Speaker 1: been asking for a while and I don't know that 524 00:28:13,840 --> 00:28:16,560 Speaker 1: there are very many examples of this. How many times 525 00:28:16,560 --> 00:28:20,920 Speaker 1: in history has the government mandated that you buy something 526 00:28:21,440 --> 00:28:26,000 Speaker 1: basically from a specific operator, right Fizer, Maderna, and that 527 00:28:26,080 --> 00:28:30,200 Speaker 1: they're for profit and you must do it. It's kind 528 00:28:30,200 --> 00:28:32,239 Speaker 1: of unheard of. It's a great business model, right if 529 00:28:32,280 --> 00:28:35,040 Speaker 1: your government could come out and say, hey, you have 530 00:28:35,119 --> 00:28:37,200 Speaker 1: to go buy this product. If the government came out 531 00:28:37,280 --> 00:28:39,960 Speaker 1: obviously said hey, everybody has to listen to Clay and Buck, 532 00:28:40,040 --> 00:28:41,280 Speaker 1: You and I would make a lot of money. It 533 00:28:41,280 --> 00:28:43,440 Speaker 1: would be not a good idea for the government to 534 00:28:43,480 --> 00:28:45,840 Speaker 1: do that. Well, I mean I it would be a 535 00:28:45,880 --> 00:28:49,040 Speaker 1: good idea for the world. But yes, technically the government 536 00:28:49,040 --> 00:28:54,200 Speaker 1: shouldn't do that. But under the Obamacare jurisprudence, they could 537 00:28:54,280 --> 00:28:58,600 Speaker 1: mandate that we all Otherwise you face a tax, right, 538 00:28:58,600 --> 00:29:01,960 Speaker 1: you face some tax if you will get the vaccine. 539 00:29:02,000 --> 00:29:04,840 Speaker 1: You have to buy the vaccine and take the vaccine 540 00:29:05,160 --> 00:29:07,960 Speaker 1: or else will tax you. Right. So this is why 541 00:29:08,040 --> 00:29:10,600 Speaker 1: regulating inactivity with such a big deal. This is why 542 00:29:10,640 --> 00:29:13,080 Speaker 1: John Roberts is a huge coward. But that's something we'll 543 00:29:13,080 --> 00:29:15,560 Speaker 1: talk about another time. A lot of us are online 544 00:29:15,600 --> 00:29:18,600 Speaker 1: every day, whether it's sending emails, buying something off the Internet, 545 00:29:18,640 --> 00:29:21,000 Speaker 1: browsing social media. The list goes on and on. The 546 00:29:21,040 --> 00:29:24,240 Speaker 1: point is your personal information is all over the place 547 00:29:24,480 --> 00:29:27,800 Speaker 1: in today's technological age. We are all vulnerable, but you 548 00:29:27,840 --> 00:29:31,520 Speaker 1: can add a layer of protection with LifeLock. LifeLock systems 549 00:29:31,600 --> 00:29:33,800 Speaker 1: monitor the web looking for evidence that your info is 550 00:29:33,840 --> 00:29:37,120 Speaker 1: in the wrong hands. Cyber hackers are more sophisticated than ever, 551 00:29:37,200 --> 00:29:39,560 Speaker 1: so it's worth the investment in peace of mind knowing 552 00:29:39,600 --> 00:29:43,280 Speaker 1: you've got a digital bodyguard. They're the undisputed number one 553 00:29:43,360 --> 00:29:46,440 Speaker 1: online identity theft protection source. I've relied on them for 554 00:29:46,600 --> 00:29:48,880 Speaker 1: years now. No one can prevent all identity theft or 555 00:29:48,920 --> 00:29:51,960 Speaker 1: monitor all transactions at all businesses, but it's easy to 556 00:29:52,000 --> 00:29:55,160 Speaker 1: help protect yourself with LifeLock. Sign up today and protect 557 00:29:55,200 --> 00:29:58,600 Speaker 1: yourself joy now. Save up at twenty five percent off 558 00:29:58,600 --> 00:30:01,640 Speaker 1: your first year with promo code Buck. Call one eight 559 00:30:01,680 --> 00:30:04,440 Speaker 1: hundred LifeLock, or go to LifeLock dot com and use 560 00:30:04,480 --> 00:30:07,360 Speaker 1: promo code b U c K for twenty five percent off. 561 00:30:08,840 --> 00:30:12,160 Speaker 1: Don't miss a minute of playing Buck and get behind 562 00:30:12,200 --> 00:30:16,400 Speaker 1: the scene access to special content for members only. Subscribe 563 00:30:16,480 --> 00:30:19,280 Speaker 1: to C and B twenty four to seven. Welcome back 564 00:30:19,280 --> 00:30:21,960 Speaker 1: into Clay and Buck eight hundred two eight two two 565 00:30:22,040 --> 00:30:24,160 Speaker 1: eight eight two on the phone lines if you would 566 00:30:24,160 --> 00:30:28,560 Speaker 1: like to chat with us, we have do we Well, 567 00:30:28,600 --> 00:30:30,600 Speaker 1: I'll check in a second and see exactly who's up 568 00:30:31,080 --> 00:30:37,200 Speaker 1: on the lines here. But Clay Alec Baldwin is now 569 00:30:37,240 --> 00:30:43,480 Speaker 1: facing two counts of involuntary manslaughter, and the armorer as 570 00:30:43,520 --> 00:30:48,520 Speaker 1: well from that the movie set Rust was the film 571 00:30:48,560 --> 00:30:55,760 Speaker 1: that they were making, also faces involuntary manslaughter charges. One 572 00:30:55,920 --> 00:30:58,080 Speaker 1: is the first question I have is do you think 573 00:30:58,120 --> 00:31:04,120 Speaker 1: that this is fair the right decision from the prosecutor 574 00:31:04,120 --> 00:31:06,640 Speaker 1: in this case? And also do we ever find out 575 00:31:06,840 --> 00:31:10,120 Speaker 1: how did live ammunition get on the set of a movie? 576 00:31:10,240 --> 00:31:12,960 Speaker 1: Because that is what happened. I'm presuming that that's why 577 00:31:13,000 --> 00:31:19,640 Speaker 1: the armorer is being charged too, And I don't know 578 00:31:19,680 --> 00:31:24,720 Speaker 1: the specific statutes under which he's being charged, but involuntary 579 00:31:25,240 --> 00:31:30,160 Speaker 1: manslaughter sounds like probably the right charge, right. There's also 580 00:31:30,600 --> 00:31:35,960 Speaker 1: oftentimes like a basically negligent homicide, where you are engaging 581 00:31:35,960 --> 00:31:39,800 Speaker 1: in a negligent act that could lead to negative consequences, 582 00:31:39,840 --> 00:31:42,640 Speaker 1: but you don't intend for this to happen. I don't 583 00:31:42,640 --> 00:31:46,000 Speaker 1: think there's any suggestion that Alec Baldwin intended for this 584 00:31:46,040 --> 00:31:49,880 Speaker 1: to be the result, and I imagine his defense, and 585 00:31:49,920 --> 00:31:52,200 Speaker 1: again it's without seeing the statute written in front of 586 00:31:52,200 --> 00:31:55,520 Speaker 1: me right now, will be that whoever the other person 587 00:31:55,640 --> 00:31:59,680 Speaker 1: is who's charged, gave him a loaded handgun and there 588 00:31:59,720 --> 00:32:02,800 Speaker 1: was no reason whatsoever why he would expect that he 589 00:32:02,800 --> 00:32:06,400 Speaker 1: would have a loaded handgun on the set, and that 590 00:32:06,400 --> 00:32:08,200 Speaker 1: that will be his defense. I think I said that 591 00:32:08,280 --> 00:32:11,960 Speaker 1: saw that he faces eighteen months in prison if he's convicted. 592 00:32:13,040 --> 00:32:15,120 Speaker 1: I don't think he'll serve any prison time over thet you. 593 00:32:15,800 --> 00:32:17,680 Speaker 1: I would be surprised. I think this is New Mexico, 594 00:32:17,840 --> 00:32:21,240 Speaker 1: right if I'm not mistaken, And the reason why I say, 595 00:32:21,400 --> 00:32:24,520 Speaker 1: somebody might say, well, why does this matter where it's located. 596 00:32:24,960 --> 00:32:29,200 Speaker 1: I would think a New Mexico jury would be less 597 00:32:29,240 --> 00:32:32,560 Speaker 1: impressed by Alec Baldwin than in New York or LA 598 00:32:32,720 --> 00:32:35,320 Speaker 1: jury would be where a lot of movies obviously you're filmed. 599 00:32:35,640 --> 00:32:38,520 Speaker 1: This is not a big city locale, and so they 600 00:32:38,560 --> 00:32:43,080 Speaker 1: may have more experience on this jury around firearms and 601 00:32:43,320 --> 00:32:45,840 Speaker 1: probably ask the question that I think most people are 602 00:32:45,840 --> 00:32:49,239 Speaker 1: contemplating here, which is what you asked, how did there 603 00:32:49,240 --> 00:32:52,080 Speaker 1: ever end up a loaded handgun in his possession in 604 00:32:52,120 --> 00:32:54,360 Speaker 1: the first place? Where this incident was able to occur. 605 00:32:55,280 --> 00:32:58,360 Speaker 1: I would say one part of his defense is likely 606 00:32:58,400 --> 00:33:01,560 Speaker 1: to be that there's an armorer on set who's in 607 00:33:01,640 --> 00:33:04,760 Speaker 1: charge of these weapons and is supposed to be the 608 00:33:05,400 --> 00:33:09,640 Speaker 1: safety personnel, obviously, so that this kind of you know, 609 00:33:09,880 --> 00:33:12,000 Speaker 1: everyone agreed it was a tragic accident, right, there's no 610 00:33:12,160 --> 00:33:14,840 Speaker 1: question about that, obviously, Alec Baldwin, this is just a 611 00:33:14,960 --> 00:33:19,520 Speaker 1: it was a terrible situation. There was not any dispute 612 00:33:19,520 --> 00:33:23,520 Speaker 1: about the facts that this was accidental. But he'll probably 613 00:33:23,920 --> 00:33:28,200 Speaker 1: claim his defense. Attorneys against this will claim because I 614 00:33:28,640 --> 00:33:31,160 Speaker 1: doubt he'll I don't know, maybe he'll please. You'll have 615 00:33:31,160 --> 00:33:33,560 Speaker 1: to see what they're offering him. He's only facing eighteen 616 00:33:33,600 --> 00:33:36,280 Speaker 1: months though, right, so are you going to take a 617 00:33:36,280 --> 00:33:39,520 Speaker 1: plea bargain or are you going to see you roll 618 00:33:39,560 --> 00:33:42,000 Speaker 1: your dice? Roll the dice with the jury. I think 619 00:33:42,040 --> 00:33:45,840 Speaker 1: it's likely Clay that he'll say this is it's not 620 00:33:46,000 --> 00:33:49,840 Speaker 1: reasonable to expect him as the actor to know the 621 00:33:49,920 --> 00:33:53,320 Speaker 1: difference even with what is a live round versus what 622 00:33:53,520 --> 00:33:56,240 Speaker 1: is a blank that will be used on a movie set, 623 00:33:56,240 --> 00:33:58,000 Speaker 1: and that's why they have an armor who's paid to 624 00:33:58,040 --> 00:34:01,960 Speaker 1: do this? But to your point of New Mexico, anybody 625 00:34:02,000 --> 00:34:06,160 Speaker 1: who has any understanding of firearms, comes out of gun 626 00:34:06,200 --> 00:34:09,040 Speaker 1: culture and understands what it is to go to range 627 00:34:09,080 --> 00:34:13,080 Speaker 1: and to be engaged in live fire. Knows that every 628 00:34:13,160 --> 00:34:15,360 Speaker 1: round that comes out of that weapon you are responsible for. 629 00:34:15,960 --> 00:34:18,440 Speaker 1: So don't I don't know how that shakes out in 630 00:34:18,440 --> 00:34:21,320 Speaker 1: front of a jury in New Mexico because I didn't 631 00:34:21,320 --> 00:34:23,200 Speaker 1: know there was a real bullet in there. May not, 632 00:34:23,719 --> 00:34:26,239 Speaker 1: may not sway them. Well, remember he also did an 633 00:34:26,239 --> 00:34:28,480 Speaker 1: interview where he claimed he never pulled the trigger and 634 00:34:28,480 --> 00:34:33,080 Speaker 1: that the gun discharged without his I mean, that's clearly 635 00:34:33,080 --> 00:34:35,200 Speaker 1: a lie, but that is going to be Now this 636 00:34:35,239 --> 00:34:37,759 Speaker 1: is why you don't do interviews that's going to be 637 00:34:38,280 --> 00:34:40,719 Speaker 1: used in the court of law because you know that 638 00:34:40,840 --> 00:34:42,560 Speaker 1: the fact that he pulled the trigger will be a 639 00:34:42,600 --> 00:34:44,000 Speaker 1: big part of this case. By the way, we got 640 00:34:44,040 --> 00:34:48,120 Speaker 1: an interesting callbuck Pat Gomez, who was a former Major 641 00:34:48,160 --> 00:34:51,680 Speaker 1: League Baseball pitcher calling in. We were talking earlier about 642 00:34:51,920 --> 00:34:56,440 Speaker 1: the requirement of sometimes embracing LGBTQ. He played with the 643 00:34:56,880 --> 00:35:01,080 Speaker 1: San Francisco Giants. Pat, we appreciate you list. What story 644 00:35:01,080 --> 00:35:04,080 Speaker 1: did you want to share with us? A guy's big 645 00:35:04,120 --> 00:35:07,560 Speaker 1: fan of the show, Hey um In ninety five we 646 00:35:07,560 --> 00:35:10,080 Speaker 1: were told it we were going to be pre games 647 00:35:10,239 --> 00:35:12,239 Speaker 1: during the national anthem, We're going to be standing with 648 00:35:12,280 --> 00:35:15,239 Speaker 1: some actors and so on and so forth, and that's 649 00:35:15,320 --> 00:35:18,560 Speaker 1: kind of how it was pitched. And then the actors 650 00:35:18,560 --> 00:35:22,520 Speaker 1: came into the dugout and it was men dressed as nuns, 651 00:35:22,920 --> 00:35:25,680 Speaker 1: and it was the cast from I think it's called 652 00:35:25,719 --> 00:35:29,600 Speaker 1: Beach Blanket, Babylon. I didn't know anything about it or 653 00:35:29,640 --> 00:35:33,320 Speaker 1: what it was, but there was all kinds of flesh exposed. 654 00:35:33,320 --> 00:35:36,880 Speaker 1: We'll leave it at that. And I looked at Dusty Pakard, 655 00:35:36,880 --> 00:35:38,960 Speaker 1: I'm I'm not standing out there with that. I mean, 656 00:35:39,000 --> 00:35:42,719 Speaker 1: it was literally completely disparaging to the Catholic Church or 657 00:35:42,719 --> 00:35:44,560 Speaker 1: anybody who grew up in the Catholic face. What was 658 00:35:44,600 --> 00:35:49,760 Speaker 1: the response when you said that, Oh, we got completely vilified. 659 00:35:49,760 --> 00:35:51,680 Speaker 1: Oh come on man, it's it's a couple of minutes 660 00:35:51,680 --> 00:35:53,040 Speaker 1: like how bad could it be? And this and that 661 00:35:53,080 --> 00:35:55,560 Speaker 1: and the other thing. And I'm like, I'm not. I mean, 662 00:35:55,600 --> 00:35:58,640 Speaker 1: there was whole parts of their outfits that we're missing. Yeah, 663 00:35:58,680 --> 00:36:00,480 Speaker 1: and I'm like, we'll have no idea what this is, 664 00:36:00,520 --> 00:36:02,600 Speaker 1: but I am not standing out there with that. And 665 00:36:03,680 --> 00:36:06,080 Speaker 1: the next day not I mean, after the game, we 666 00:36:06,080 --> 00:36:08,400 Speaker 1: were just vilified by the press, the Census of Chronicle, 667 00:36:08,440 --> 00:36:11,960 Speaker 1: of the Examiner, and then the USA to Day picked 668 00:36:12,000 --> 00:36:15,400 Speaker 1: up the story, and so in regards to the hockey 669 00:36:15,400 --> 00:36:19,480 Speaker 1: player who's having to deal with the onslaught of social media, 670 00:36:19,719 --> 00:36:21,719 Speaker 1: we didn't have social media back in that day, and 671 00:36:21,760 --> 00:36:24,120 Speaker 1: we were still getting pretty vilified to the press. Thank 672 00:36:24,120 --> 00:36:26,719 Speaker 1: you for the call. Hundreds of people I bet buck 673 00:36:26,800 --> 00:36:28,919 Speaker 1: agree with this player, almost none of them were able 674 00:36:29,080 --> 00:36:30,120 Speaker 1: or willing to do what he did.