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 --> 00:00:06,800 Speaker 1: Sexton Show podcast. Welcome back in Clay Travis and Buck 3 00:00:06,840 --> 00:00:09,799 Speaker 1: Sexton Show. Our two everybody eight hundred two eight two 4 00:00:09,960 --> 00:00:13,520 Speaker 1: two eight eight two on those phone lines. If you're 5 00:00:13,560 --> 00:00:17,640 Speaker 1: seeing anything really interesting in your state on the airwaves. 6 00:00:18,880 --> 00:00:23,520 Speaker 1: When it comes to advertisements for these for the upcoming election, 7 00:00:23,760 --> 00:00:26,920 Speaker 1: comes to political ads, let us know what you're seeing. 8 00:00:27,000 --> 00:00:29,120 Speaker 1: We're trying to read the tea leaves here get a 9 00:00:29,160 --> 00:00:32,120 Speaker 1: sense for where the momentum is. Clay has gone deep 10 00:00:32,159 --> 00:00:35,120 Speaker 1: into the betting odds. We're looking at the polling and 11 00:00:35,920 --> 00:00:38,400 Speaker 1: if things continue on this trajectory, it's gonna it's gonna 12 00:00:38,440 --> 00:00:42,639 Speaker 1: be good, I think for Republicans clearly. And we are 13 00:00:42,680 --> 00:00:46,319 Speaker 1: planning an election Clay and Buck election party that we're 14 00:00:46,320 --> 00:00:48,879 Speaker 1: gonna be having in Clay's home state of Tennessee. We're 15 00:00:48,920 --> 00:00:52,520 Speaker 1: gonna we're celebrating. We called our shot to be clear 16 00:00:53,320 --> 00:00:55,320 Speaker 1: like six months ago. We're like, it's gonna be a 17 00:00:55,360 --> 00:00:58,920 Speaker 1: good year for Republicans. And so we've put our money 18 00:00:59,480 --> 00:01:02,279 Speaker 1: and our beer pong where our mouths are and are 19 00:01:02,280 --> 00:01:05,880 Speaker 1: going to be throwing an election party in Nashville coming 20 00:01:05,959 --> 00:01:08,039 Speaker 1: up here, which Hopefully it doesn't end up like Hillary 21 00:01:08,040 --> 00:01:12,320 Speaker 1: Clinton's twenty sixteen presidential election party. One of my biggest 22 00:01:12,360 --> 00:01:17,399 Speaker 1: regrets to this day in politics is I was I 23 00:01:17,480 --> 00:01:19,520 Speaker 1: was in the flat Iron District, where I was living 24 00:01:19,520 --> 00:01:22,160 Speaker 1: at the time, named for the flat Iron Building, which 25 00:01:22,240 --> 00:01:23,920 Speaker 1: kind of looks like a flat Iron which was originally 26 00:01:23,959 --> 00:01:26,920 Speaker 1: supposed to be an uptown version of Wall Street and 27 00:01:27,000 --> 00:01:29,920 Speaker 1: build a financial center right near what is now Madison 28 00:01:29,920 --> 00:01:34,280 Speaker 1: Square Park, very famous iconic building, the flat Iron Building 29 00:01:34,280 --> 00:01:36,399 Speaker 1: in New York. I lived a couple blocks from it, 30 00:01:36,800 --> 00:01:41,120 Speaker 1: and when the Trump victory happened, I was so busy 31 00:01:41,840 --> 00:01:44,520 Speaker 1: calling and texting all of my friends and saying, oh 32 00:01:44,600 --> 00:01:47,440 Speaker 1: my god, this is amazing, and look what's like. I 33 00:01:47,480 --> 00:01:49,520 Speaker 1: can't believe he did it. And because I look, I 34 00:01:49,640 --> 00:01:51,760 Speaker 1: voted for him. But I didn't think the first time around. 35 00:01:51,760 --> 00:01:54,640 Speaker 1: I thought I was just you know, voting for it 36 00:01:54,680 --> 00:01:56,640 Speaker 1: was you know, because the ninety seven percent of year times. 37 00:01:56,640 --> 00:01:59,440 Speaker 1: Obviously all of our political perception about polling changed after that. 38 00:01:59,480 --> 00:02:03,320 Speaker 1: But Clay, I bring it up because the Hillary victory 39 00:02:03,440 --> 00:02:07,880 Speaker 1: party was like a fifteen minute walk to my west 40 00:02:08,440 --> 00:02:12,760 Speaker 1: and I wish I had gone, just to see what 41 00:02:12,960 --> 00:02:18,200 Speaker 1: that mausoleum of Hillary's hopes and dreams looked like at 42 00:02:18,240 --> 00:02:20,400 Speaker 1: that time. I wish I could have gone to just 43 00:02:20,520 --> 00:02:25,480 Speaker 1: go see all of the Apparently there were just tears everywhere. 44 00:02:25,680 --> 00:02:27,440 Speaker 1: And you know, look, if you're an adult, you shouldn't 45 00:02:27,480 --> 00:02:30,120 Speaker 1: cry after presidential election. Sorry, So I had no sympathy 46 00:02:30,120 --> 00:02:32,320 Speaker 1: on that one. I wish I had gone to check 47 00:02:32,360 --> 00:02:34,320 Speaker 1: it out because it would have been instructive about what 48 00:02:34,320 --> 00:02:38,000 Speaker 1: we're dealing with. Oh, I mean, we're gonna have a 49 00:02:38,200 --> 00:02:43,120 Speaker 1: really fun night, because I am convinced the more I 50 00:02:43,240 --> 00:02:47,520 Speaker 1: look at this, at this data. I predicted in January, 51 00:02:48,160 --> 00:02:50,799 Speaker 1: Buck I got two things wrong. I said, the Packers 52 00:02:50,840 --> 00:02:53,680 Speaker 1: who win the Super Bowl. Sorry, Packers fans, this is 53 00:02:53,720 --> 00:02:55,919 Speaker 1: my New Year's prediction. You did win the Super Bowl. 54 00:02:56,639 --> 00:03:03,160 Speaker 1: The oh Man, the Rams beat the Bengals. I wasn't 55 00:03:03,160 --> 00:03:05,760 Speaker 1: expecting to get quizzed on the Super Bowl. Here. Rams 56 00:03:05,760 --> 00:03:07,639 Speaker 1: beat the Bengals of the Super Bowl this past year. 57 00:03:07,840 --> 00:03:11,560 Speaker 1: So I got that wrong. Our boy, Aaron Rodgers, mister 58 00:03:11,680 --> 00:03:14,359 Speaker 1: anti COVID shot, was not able to get the Packers 59 00:03:14,360 --> 00:03:17,280 Speaker 1: across the finish line. There. I predicted Georgio would win 60 00:03:17,320 --> 00:03:21,040 Speaker 1: the National Championship. Got that right. But I said three 61 00:03:21,280 --> 00:03:25,399 Speaker 1: plus three on the Senate and plus twenty five on 62 00:03:25,560 --> 00:03:29,480 Speaker 1: the House, and I feel pretty good still about those. 63 00:03:29,560 --> 00:03:31,959 Speaker 1: Now people would say plus three on the Senate, you're 64 00:03:32,000 --> 00:03:37,440 Speaker 1: being aggressive. I think if Republicans win a couple of 65 00:03:37,520 --> 00:03:40,720 Speaker 1: close races, there will be a tide that will carry. 66 00:03:41,120 --> 00:03:44,680 Speaker 1: And so it wouldn't stun me if we won in Nevada, Georgia, 67 00:03:44,760 --> 00:03:48,880 Speaker 1: and let's say Arizona, Like that wouldn't be shocking to 68 00:03:48,960 --> 00:03:50,720 Speaker 1: me if all three of those because I think, and 69 00:03:50,840 --> 00:03:52,680 Speaker 1: let me give you my theory here, Buck, I think 70 00:03:52,720 --> 00:03:55,880 Speaker 1: Carrie Lake is going to win the governorship in Arizona, 71 00:03:55,920 --> 00:03:58,920 Speaker 1: and I think she may win comfortably. Brian Kemp is 72 00:03:58,960 --> 00:04:02,840 Speaker 1: going to, I believe, win comfortably in Georgia. I just 73 00:04:02,880 --> 00:04:05,520 Speaker 1: don't know how many in Lombardo I think is gonna win. 74 00:04:05,520 --> 00:04:08,600 Speaker 1: In Nevada, I don't know how many split tickets we're 75 00:04:08,640 --> 00:04:12,080 Speaker 1: gonna really see. And so it wouldn't surprise me if 76 00:04:12,160 --> 00:04:18,600 Speaker 1: we got all three of those states as the Nevada 77 00:04:19,080 --> 00:04:22,680 Speaker 1: Lombardo right, isn't he the governor's candidate? Oh? Sorry, yes, yes, 78 00:04:23,000 --> 00:04:25,920 Speaker 1: So I think all three of those governors are gonna win. 79 00:04:26,400 --> 00:04:29,719 Speaker 1: And if all three governors win, if Lake, Lombardo and 80 00:04:30,160 --> 00:04:34,120 Speaker 1: uh uh, and uh and kemp Win. I just I 81 00:04:34,400 --> 00:04:36,800 Speaker 1: don't buy in necessarily to this idea that we're going 82 00:04:36,880 --> 00:04:39,320 Speaker 1: to see a ton of split tickets. I just don't. 83 00:04:39,360 --> 00:04:43,159 Speaker 1: I think herschel Walker, I think that that Blake Masters 84 00:04:43,279 --> 00:04:48,040 Speaker 1: and Adam Laxall all three may win alongside of the governors. 85 00:04:48,080 --> 00:04:51,960 Speaker 1: There's definitely some shifting going on in the political narrative 86 00:04:52,040 --> 00:04:54,960 Speaker 1: right now, and you're seeing it in these races, but 87 00:04:55,040 --> 00:04:59,760 Speaker 1: also at a broader level. I think the Democrat January six, 88 00:05:00,360 --> 00:05:06,919 Speaker 1: blm anti Trump obsession is crashing against the rocks of reality. 89 00:05:06,960 --> 00:05:12,240 Speaker 1: And one example of this comes via Tulsi Gabbert, who 90 00:05:12,520 --> 00:05:15,400 Speaker 1: many of us are familiar with because she has she looks. 91 00:05:15,400 --> 00:05:17,640 Speaker 1: She's on Tucker's show on a regular basis, and I 92 00:05:17,680 --> 00:05:21,159 Speaker 1: always have to say this, don't you know. She will 93 00:05:21,240 --> 00:05:24,760 Speaker 1: disappoint conservatives on some things. She's not going to agree. 94 00:05:24,800 --> 00:05:28,360 Speaker 1: She's not a conservative. So just understand that this doesn't mean, 95 00:05:28,600 --> 00:05:32,640 Speaker 1: oh great, she's on our team. But she's a person 96 00:05:32,800 --> 00:05:36,640 Speaker 1: who served her country, who is ethical, who comes across 97 00:05:36,800 --> 00:05:40,800 Speaker 1: as kind and open minded toward the other side. And 98 00:05:40,839 --> 00:05:44,920 Speaker 1: it's it is not possible to be those things and 99 00:05:45,000 --> 00:05:49,000 Speaker 1: be a mainstream Democrat today. To be a mainstream Democrat 100 00:05:49,080 --> 00:05:53,560 Speaker 1: today is to despise people on the right, to despise 101 00:05:53,640 --> 00:05:57,280 Speaker 1: conservatives personally and person to person, to think they should 102 00:05:57,320 --> 00:05:59,480 Speaker 1: be kicked off of social media, to think they should 103 00:05:59,520 --> 00:06:02,400 Speaker 1: be fired from their jobs for not announcing their pronouns 104 00:06:02,440 --> 00:06:04,679 Speaker 1: in their email signatures. They think they should be fired 105 00:06:04,720 --> 00:06:07,520 Speaker 1: from their jobs for not getting a shot. That's what 106 00:06:07,560 --> 00:06:11,160 Speaker 1: it means to be a Democrat. Tulsi Gabbard breaks from that, 107 00:06:11,720 --> 00:06:14,640 Speaker 1: and she has officially broken now from the Democrat Party. 108 00:06:15,080 --> 00:06:18,720 Speaker 1: And she was pulling no punches in this one. I 109 00:06:18,760 --> 00:06:22,560 Speaker 1: can no longer remain in today's Democratic Party that's under 110 00:06:22,600 --> 00:06:26,520 Speaker 1: the complete control of an elitist cabal of war mongers, 111 00:06:26,920 --> 00:06:30,440 Speaker 1: who were driven by cowardly wokeness, who divide us by 112 00:06:30,560 --> 00:06:35,720 Speaker 1: racializing every issue and stoking anti white racism, who actively 113 00:06:35,720 --> 00:06:39,200 Speaker 1: work to undermine our god given freedoms that are enshrined 114 00:06:39,200 --> 00:06:43,120 Speaker 1: in our constitution, who are hostile to people of faith 115 00:06:43,320 --> 00:06:47,680 Speaker 1: and spirituality, who demonize the police but protect criminals at 116 00:06:47,680 --> 00:06:51,560 Speaker 1: the expense of law abiding Americans, who believe in open borders, 117 00:06:51,600 --> 00:06:55,080 Speaker 1: who weaponize the national security state to go after their 118 00:06:55,120 --> 00:06:59,600 Speaker 1: political opponents, and above all, who are dragging us ever 119 00:06:59,640 --> 00:07:02,800 Speaker 1: close search to nuclear war. Clay, can I just say 120 00:07:02,839 --> 00:07:05,880 Speaker 1: everything she said and I want your take on it, 121 00:07:06,040 --> 00:07:08,279 Speaker 1: because we haven't talked about this before we played it now. 122 00:07:08,640 --> 00:07:12,600 Speaker 1: Everything she said is powerful because it is true. And 123 00:07:12,640 --> 00:07:14,760 Speaker 1: the thing that stuck out to me the most is 124 00:07:14,760 --> 00:07:18,000 Speaker 1: that she calls out the anti white racism of the 125 00:07:18,040 --> 00:07:22,880 Speaker 1: Democrat Party. Now she has mixed heritage, she has her 126 00:07:23,280 --> 00:07:27,400 Speaker 1: father is Samoan, so she has maybe a little more 127 00:07:27,440 --> 00:07:29,840 Speaker 1: you know, there's a little more leeway to speak about 128 00:07:29,840 --> 00:07:32,120 Speaker 1: some of these issues, even you know, on the left. 129 00:07:33,320 --> 00:07:36,840 Speaker 1: The Democrat Party does have an anti white, anti white 130 00:07:36,880 --> 00:07:39,240 Speaker 1: racism at the heart of many of its policies, and 131 00:07:39,280 --> 00:07:43,640 Speaker 1: many white Democrats use this actually to attack their opponents. 132 00:07:43,680 --> 00:07:45,880 Speaker 1: That may seem strange, but you understand the strategy. It 133 00:07:45,960 --> 00:07:48,880 Speaker 1: actually all holds up. I thought it was a brave 134 00:07:48,920 --> 00:07:52,480 Speaker 1: statement she made. I think she's right in everything that 135 00:07:52,560 --> 00:07:55,880 Speaker 1: she said, and I agree with everything that we that 136 00:07:56,000 --> 00:07:59,520 Speaker 1: she said in that clip, and really, to me, the 137 00:07:59,600 --> 00:08:05,320 Speaker 1: Democrat at party at its base now is about identity politics, 138 00:08:05,640 --> 00:08:10,600 Speaker 1: which in a woke context is white people are responsible 139 00:08:10,680 --> 00:08:15,560 Speaker 1: for everything bad and are awful human beings. And really, 140 00:08:16,360 --> 00:08:19,120 Speaker 1: I would argue the people destroying our country right now 141 00:08:19,200 --> 00:08:23,600 Speaker 1: are the woke white community that should be our top 142 00:08:23,720 --> 00:08:28,240 Speaker 1: opponents in the Republican Party because when you actually talk 143 00:08:28,640 --> 00:08:35,320 Speaker 1: to Hispanic, Asian and Black voters, they reject many of 144 00:08:35,360 --> 00:08:38,359 Speaker 1: the things that are being argued by the woke white community. 145 00:08:38,679 --> 00:08:45,160 Speaker 1: The BLM movement was put in its high echelon mostly 146 00:08:45,200 --> 00:08:49,280 Speaker 1: by woke white people who live very often in very 147 00:08:49,280 --> 00:08:53,160 Speaker 1: wealthy communities and don't have to worry about needing police protection. 148 00:08:53,559 --> 00:08:55,800 Speaker 1: You know the I saw the other day where Stacy 149 00:08:55,840 --> 00:08:59,800 Speaker 1: Abrams had spent one point two million dollars on her 150 00:08:59,840 --> 00:09:04,840 Speaker 1: own private security. Many of these Democrats that are arguing 151 00:09:04,960 --> 00:09:08,439 Speaker 1: in favor of woke white policies, because let's be honest, 152 00:09:08,480 --> 00:09:11,600 Speaker 1: that's what they are, are protected by their own security. 153 00:09:12,000 --> 00:09:17,480 Speaker 1: And to me, it's woke politics, identity politics, and cancel culture. 154 00:09:17,840 --> 00:09:21,520 Speaker 1: Those are the foundational elements of what the Democrats support. Now, 155 00:09:21,600 --> 00:09:25,160 Speaker 1: if you say something they don't like, they don't argue 156 00:09:25,160 --> 00:09:27,640 Speaker 1: with your opinion, what do they do buck They go 157 00:09:27,800 --> 00:09:30,800 Speaker 1: right to you don't have the right to have your 158 00:09:30,840 --> 00:09:34,640 Speaker 1: opinion because they want to silence you. They want to 159 00:09:34,640 --> 00:09:36,480 Speaker 1: take Alex Barnson, who we're going to talk to in 160 00:09:36,520 --> 00:09:41,559 Speaker 1: twenty minutes, doctor Joseph Latipo from the Surgeon General of Florida. 161 00:09:41,800 --> 00:09:45,520 Speaker 1: Science is about argument. Science is about debate. That's what 162 00:09:45,600 --> 00:09:49,440 Speaker 1: the scientific method is. What Democrats have tried to do 163 00:09:49,960 --> 00:09:52,960 Speaker 1: is through their levers of power, both in the federal 164 00:09:53,000 --> 00:09:55,640 Speaker 1: government and in the state government, and their connections with 165 00:09:55,720 --> 00:09:58,560 Speaker 1: the big tech communities, they've tried to shut down anybody 166 00:09:58,559 --> 00:10:01,040 Speaker 1: who puts out anything they disagree. There's something I always 167 00:10:01,080 --> 00:10:03,520 Speaker 1: like to remind people of on that big tech issue, because, 168 00:10:04,040 --> 00:10:06,800 Speaker 1: as you said, they shut down. Joseph Ladipo, the Surgeon 169 00:10:06,880 --> 00:10:10,200 Speaker 1: General Florida, shares a study that's a real study, a 170 00:10:10,240 --> 00:10:14,120 Speaker 1: real scientific study that says, look, the risk of myocarditis, 171 00:10:14,240 --> 00:10:17,680 Speaker 1: which is a hard inflammation. It's a serious problem. Anything 172 00:10:17,720 --> 00:10:19,880 Speaker 1: that inflames your heart you want to be you're concerned about, 173 00:10:20,559 --> 00:10:23,920 Speaker 1: can cause scarring. By the way in the cardiac tissue. 174 00:10:24,240 --> 00:10:27,360 Speaker 1: The long you might not know the complications for a 175 00:10:27,400 --> 00:10:30,240 Speaker 1: long time afterwards, even if it feels like even if 176 00:10:30,240 --> 00:10:32,920 Speaker 1: it heals in the shorter term. The fact that they 177 00:10:32,920 --> 00:10:37,080 Speaker 1: would shut that down is appalling but not surprising anymore. 178 00:10:37,280 --> 00:10:40,240 Speaker 1: And I would just note for everybody big tech and 179 00:10:40,280 --> 00:10:44,000 Speaker 1: the Democrat apparatus that has harnessed it for partisan purposes, 180 00:10:44,559 --> 00:10:48,400 Speaker 1: lied to get where it is for many years, whether 181 00:10:48,440 --> 00:10:52,839 Speaker 1: it's Facebook or Twitter, they said, we have no politics, 182 00:10:53,160 --> 00:10:56,400 Speaker 1: use our platform. They said, this is about free speech 183 00:10:56,679 --> 00:11:01,040 Speaker 1: and freedom of information transferring. It's a transfer on the internet. 184 00:11:01,440 --> 00:11:04,520 Speaker 1: We don't do the partisan game. You can trust us, 185 00:11:05,240 --> 00:11:08,440 Speaker 1: don't be evil. Remember Google's slogo. Yeah. And then finally, 186 00:11:08,480 --> 00:11:12,120 Speaker 1: when they became the sole players in these spaces, when 187 00:11:12,120 --> 00:11:16,480 Speaker 1: they became effectively digital monopolists, what do they do crush 188 00:11:16,559 --> 00:11:20,840 Speaker 1: the opposition like in stalinist fashion, You say what we 189 00:11:20,960 --> 00:11:23,880 Speaker 1: want you to on the core issues, on the most 190 00:11:23,880 --> 00:11:28,120 Speaker 1: important debates, or you're gone. What Joseph Latipos shared Buck 191 00:11:28,520 --> 00:11:32,319 Speaker 1: was data that suggests that if you are young and healthy, 192 00:11:32,760 --> 00:11:35,320 Speaker 1: or your kids are young and healthy, they shouldn't get 193 00:11:35,360 --> 00:11:38,240 Speaker 1: the COVID shot because the risk reward balance isn't there 194 00:11:38,280 --> 00:11:40,920 Speaker 1: for them. And they are trying to shut him down 195 00:11:40,920 --> 00:11:42,280 Speaker 1: from being able to say this. This is the guy 196 00:11:42,280 --> 00:11:45,320 Speaker 1: who's a surgeon general Florida and Buck. The analogy that 197 00:11:45,400 --> 00:11:47,720 Speaker 1: I would make that I think everybody out there will understand, 198 00:11:47,720 --> 00:11:49,520 Speaker 1: and I've I've been kind of hammering this home for 199 00:11:49,559 --> 00:11:53,760 Speaker 1: a while is China has built a great wall of 200 00:11:53,800 --> 00:11:56,440 Speaker 1: the Chinese Internet where For instance, if you were to 201 00:11:56,480 --> 00:11:58,319 Speaker 1: go in China right now and you try to search 202 00:11:58,320 --> 00:12:01,320 Speaker 1: out timm And Square, you can't even find it. If 203 00:12:01,320 --> 00:12:05,000 Speaker 1: you put the date into the search engines in China, 204 00:12:05,080 --> 00:12:09,040 Speaker 1: they won't return any evidence that Tianamen Square ever occurred. 205 00:12:09,080 --> 00:12:12,800 Speaker 1: Back in I believe nineteen eighty nine the democracy protests 206 00:12:13,480 --> 00:12:18,160 Speaker 1: and seeking democracy, and most Americans I think would say, okay, well, 207 00:12:18,160 --> 00:12:22,840 Speaker 1: that's wrong. The federal government, the large state government should 208 00:12:22,880 --> 00:12:26,640 Speaker 1: not be restricting what people can find on the Internet. Well, 209 00:12:26,840 --> 00:12:29,120 Speaker 1: we're not doing that because it would be a violation 210 00:12:29,120 --> 00:12:33,480 Speaker 1: of the First Amendment. But our government is in agreement. 211 00:12:33,520 --> 00:12:37,440 Speaker 1: The Joe Biden administration is in constant contact with big 212 00:12:37,480 --> 00:12:41,640 Speaker 1: tech companies, and the big tech companies are censoring at 213 00:12:41,679 --> 00:12:45,280 Speaker 1: the behest of the government. So we have created effectively 214 00:12:45,679 --> 00:12:50,200 Speaker 1: our own government censorship. The differences the government does it 215 00:12:50,280 --> 00:12:53,240 Speaker 1: in China, our big tech companies do it in America, 216 00:12:53,400 --> 00:12:55,640 Speaker 1: and it's flat out wrong. We'll talk about that with 217 00:12:55,679 --> 00:12:58,959 Speaker 1: Alex Barrinson, who we believe is dealing with his own 218 00:12:59,440 --> 00:13:02,920 Speaker 1: additional banning after he won and beat back the first banning. 219 00:13:02,960 --> 00:13:06,360 Speaker 1: We'll discuss that more with him coming up shortly. But 220 00:13:06,440 --> 00:13:09,840 Speaker 1: in the meantime. You know, look, so many of you 221 00:13:09,960 --> 00:13:12,840 Speaker 1: right now are worried about being able to take care 222 00:13:12,880 --> 00:13:15,559 Speaker 1: of your family going forward, as we likely or headed 223 00:13:15,559 --> 00:13:19,960 Speaker 1: into a recession and maybe continued major issues with supply 224 00:13:20,080 --> 00:13:23,600 Speaker 1: chain shortages. Why don't you take care of your family 225 00:13:23,679 --> 00:13:26,480 Speaker 1: right now and do what we've done. Get a three 226 00:13:26,600 --> 00:13:29,560 Speaker 1: month food kit from our friends at my Patriots supply 227 00:13:30,400 --> 00:13:34,240 Speaker 1: three months of all of the food that you could 228 00:13:34,280 --> 00:13:37,680 Speaker 1: need per person for your family to be taken care 229 00:13:37,720 --> 00:13:41,560 Speaker 1: of in case true chaos happens in this country, which 230 00:13:41,600 --> 00:13:45,720 Speaker 1: frankly doesn't feel that far from the truth. Right now, 231 00:13:45,800 --> 00:13:50,200 Speaker 1: I've got three boys, a wife, My parents are the kids. 232 00:13:50,280 --> 00:13:53,360 Speaker 1: Right now at the beach. We have gotten our own 233 00:13:53,559 --> 00:13:57,880 Speaker 1: three month food supply just in case something crazy happens, 234 00:13:57,920 --> 00:14:01,520 Speaker 1: basically insurance for my family. I'm the head of the household, 235 00:14:01,600 --> 00:14:03,360 Speaker 1: or at least like to think that I'm the head 236 00:14:03,400 --> 00:14:05,920 Speaker 1: of the household, even though my wife makes virtually every 237 00:14:05,960 --> 00:14:08,240 Speaker 1: decision inside of the house. But I said, we got 238 00:14:08,240 --> 00:14:10,360 Speaker 1: to do this. I said, I want three months to 239 00:14:10,400 --> 00:14:13,000 Speaker 1: take care of all of us. You can save twenty 240 00:14:13,040 --> 00:14:15,280 Speaker 1: percent right now, plus you get free shipping when you 241 00:14:15,320 --> 00:14:19,240 Speaker 1: go to our special website Prepare with Clay and Buck 242 00:14:19,440 --> 00:14:22,920 Speaker 1: dot com. That's yourself, your family, give them all the 243 00:14:23,000 --> 00:14:26,640 Speaker 1: peace of mind which comes from being self reliant. Today. 244 00:14:27,080 --> 00:14:30,320 Speaker 1: That's prepare with Clay and Buck dot com one more time. 245 00:14:30,760 --> 00:14:35,600 Speaker 1: Prepare with Clay and Buck dot com. Welcome back in 246 00:14:35,760 --> 00:14:37,840 Speaker 1: Klay Trevis buck Sexton show. Going to be joined by 247 00:14:37,880 --> 00:14:39,680 Speaker 1: Alex Barden sent at the bottom of the hour in 248 00:14:39,760 --> 00:14:44,600 Speaker 1: a few minutes. Buck, this you're gonna appreciate. MSNBC is 249 00:14:44,640 --> 00:14:46,960 Speaker 1: bad when they talk politics, they get a lot of 250 00:14:47,000 --> 00:14:49,680 Speaker 1: things wrong. They have, frankly, a lot of people who 251 00:14:49,680 --> 00:14:53,160 Speaker 1: aren't very smart at work there. But they have someone 252 00:14:53,240 --> 00:14:58,360 Speaker 1: named Tiffany Cross who evidently tried to make this story. 253 00:14:58,400 --> 00:14:59,960 Speaker 1: You may have heard about it, like two talk about 254 00:15:00,040 --> 00:15:02,920 Speaker 1: Loah Is, the quarterback from Miami Dolphins had a health 255 00:15:02,960 --> 00:15:06,600 Speaker 1: related concussion issue and it's turned into a big discussion 256 00:15:06,680 --> 00:15:11,840 Speaker 1: point about when quarterbacks should be allowed to play with 257 00:15:12,040 --> 00:15:16,600 Speaker 1: health potential issues in the NFL and not Okay, so Tuah. 258 00:15:16,880 --> 00:15:23,240 Speaker 1: So the background here is Samoan uh Samoan faith. Samoan 259 00:15:23,520 --> 00:15:30,080 Speaker 1: ethnicity overwhelmingly is the biggest percentage of NFL players, right 260 00:15:30,120 --> 00:15:33,640 Speaker 1: like So American Samoa. They turn out the Samoans in 261 00:15:33,720 --> 00:15:38,280 Speaker 1: general massive amounts of NFL players. Tuah is Samoan, his 262 00:15:38,480 --> 00:15:44,640 Speaker 1: coach is of mixed race, but is counted as a 263 00:15:45,120 --> 00:15:49,600 Speaker 1: black head coach for purposes of the NFL's ridiculous identity politics. 264 00:15:50,000 --> 00:15:54,680 Speaker 1: So this MSNBC analyst goes on and says, the reason 265 00:15:54,760 --> 00:15:57,880 Speaker 1: Tah is being treated the way he is is because 266 00:15:57,920 --> 00:16:01,200 Speaker 1: he's a black quarterback with a white head coach. She 267 00:16:01,280 --> 00:16:04,840 Speaker 1: got both things wrong. Listen, just for the folks outside 268 00:16:04,840 --> 00:16:06,720 Speaker 1: of us who don't follow the sport as closely as 269 00:16:06,720 --> 00:16:08,720 Speaker 1: you and I do. Of course, I gotta say, the 270 00:16:08,800 --> 00:16:11,280 Speaker 1: optics just look bad to see all these black men 271 00:16:11,360 --> 00:16:13,880 Speaker 1: crashing into each other with a bunch of white owners, 272 00:16:13,960 --> 00:16:16,880 Speaker 1: white coaches, and the complete disregard of black bodies and 273 00:16:16,960 --> 00:16:19,440 Speaker 1: black life. I mean, it just represents a larger issue, 274 00:16:19,760 --> 00:16:21,760 Speaker 1: and I think that's the problem. And with the NFL 275 00:16:21,880 --> 00:16:24,240 Speaker 1: ratings through the roof, you know, I just wonder what 276 00:16:24,320 --> 00:16:28,040 Speaker 1: incentive do they have to just be better? Okay? So 277 00:16:28,360 --> 00:16:31,800 Speaker 1: I mean, like, I love that she said a lot 278 00:16:31,840 --> 00:16:33,560 Speaker 1: of people don't know the sport as well as you 279 00:16:33,680 --> 00:16:37,440 Speaker 1: and I do. But again, Tua is Samoan and his 280 00:16:37,560 --> 00:16:41,600 Speaker 1: coach is black, and so the race of the players 281 00:16:41,680 --> 00:16:43,960 Speaker 1: doesn't have a lot to do with the owners wanting 282 00:16:43,960 --> 00:16:45,840 Speaker 1: their players to get back on the field. And now 283 00:16:45,880 --> 00:16:49,440 Speaker 1: we're supposed to believe, and we've heard versions of this before, 284 00:16:50,240 --> 00:16:57,320 Speaker 1: that adults who are paid millions of dollars creating multi 285 00:16:57,440 --> 00:17:02,160 Speaker 1: generational wealth. Yes, to play a kids game that people 286 00:17:02,200 --> 00:17:05,240 Speaker 1: play for fun, that people play to you know, get 287 00:17:05,240 --> 00:17:08,040 Speaker 1: out there and enjoy themselves. And to play a game 288 00:17:08,080 --> 00:17:10,720 Speaker 1: that many of our listeners in high school had the 289 00:17:10,760 --> 00:17:13,320 Speaker 1: most fun in their lives was playing high school football 290 00:17:13,359 --> 00:17:15,520 Speaker 1: from an athletics protect, that is common. I mean, it's 291 00:17:15,560 --> 00:17:18,439 Speaker 1: like it's like, you know, being a kid getting paid 292 00:17:18,480 --> 00:17:21,119 Speaker 1: to eat ice cream Sundays or something. It's like a 293 00:17:21,240 --> 00:17:23,359 Speaker 1: thing that people love. I mean, I know, yes, you 294 00:17:23,440 --> 00:17:25,840 Speaker 1: gotta work hard and all this stuff, but everybody, everybody 295 00:17:25,880 --> 00:17:27,639 Speaker 1: works hard. The guys showing up every day at the 296 00:17:27,640 --> 00:17:30,399 Speaker 1: post office works hard. He doesn't make eight million dollars 297 00:17:30,400 --> 00:17:32,679 Speaker 1: a year. So we're supposed to believe this is this 298 00:17:32,840 --> 00:17:35,920 Speaker 1: is racism now. I mean, at some point it's so 299 00:17:35,960 --> 00:17:38,239 Speaker 1: stupid you just kind of wonder, like, what do they 300 00:17:38,240 --> 00:17:40,960 Speaker 1: think people are going to think? Well, this is the 301 00:17:41,680 --> 00:17:43,840 Speaker 1: Tulsi Gabbert thing. I think it ties in. This is 302 00:17:43,880 --> 00:17:48,520 Speaker 1: the talking points now, of the Democrat Party. Everything is racist. 303 00:17:48,800 --> 00:17:52,920 Speaker 1: Everybody is racist, even if you are making millions of dollars. 304 00:17:52,960 --> 00:17:55,160 Speaker 1: Remember Colin Kaepernick tried to say this was the equivalent 305 00:17:55,200 --> 00:17:57,520 Speaker 1: of the modern day slave trade. I mean he actually 306 00:17:57,560 --> 00:18:00,720 Speaker 1: said that the Netflix documentary Business Owner on a scale 307 00:18:00,760 --> 00:18:03,200 Speaker 1: one to ten, ten being the toughest. How hard is 308 00:18:03,200 --> 00:18:05,840 Speaker 1: it to manage your staff these days? I bet it's 309 00:18:05,880 --> 00:18:09,120 Speaker 1: a ten because keeping up with changing regulations, HR compliance, 310 00:18:09,320 --> 00:18:13,400 Speaker 1: hiring and retaining top talent, handling payroll, the list goes on. 311 00:18:13,760 --> 00:18:15,679 Speaker 1: There's just a limit to what you can do to 312 00:18:15,760 --> 00:18:19,040 Speaker 1: keep employees engaged while running your business smoothly. That's why 313 00:18:19,080 --> 00:18:22,800 Speaker 1: there's inspirity. They put thirty plus years of HR experience 314 00:18:22,840 --> 00:18:25,439 Speaker 1: to work to help you develop a people strategy that 315 00:18:25,480 --> 00:18:29,399 Speaker 1: supports your business strategy, focusing on the health of your organization. 316 00:18:29,840 --> 00:18:33,280 Speaker 1: What if your HR strategy included access to better benefits 317 00:18:33,280 --> 00:18:35,920 Speaker 1: to help you keep the employees you have and attract 318 00:18:35,920 --> 00:18:38,520 Speaker 1: new ones. What if it also offered training for your 319 00:18:38,560 --> 00:18:41,639 Speaker 1: employees to increase their skills so they become more productive. 320 00:18:41,800 --> 00:18:44,000 Speaker 1: There's always going to be challenges in business, no matter 321 00:18:44,040 --> 00:18:48,240 Speaker 1: where they come from. Inspirities ready, nothing seems impossible inspirity. 322 00:18:48,440 --> 00:18:54,720 Speaker 1: Hr that makes a difference. Ask people sometimes who are 323 00:18:54,720 --> 00:18:58,360 Speaker 1: still hemming and hawing about this. If this vaccine, if 324 00:18:58,359 --> 00:19:01,800 Speaker 1: it had been known to years ago or so that 325 00:19:01,920 --> 00:19:06,600 Speaker 1: this vaccine would increase cardiac deaths in young men by 326 00:19:06,680 --> 00:19:10,880 Speaker 1: eighty four percent, would they have approved it. The obvious 327 00:19:11,000 --> 00:19:14,280 Speaker 1: answer is no, you would never give something to someone 328 00:19:14,359 --> 00:19:16,560 Speaker 1: who was young and healthy and increase their risk of 329 00:19:16,720 --> 00:19:19,679 Speaker 1: dying from sudden cardiac death by eighty four percent. But 330 00:19:19,840 --> 00:19:22,920 Speaker 1: people are often their responses, well, you know, I don't know. 331 00:19:23,119 --> 00:19:27,240 Speaker 1: COVID's pretty bad. Yes, COVID can be terrible, but we 332 00:19:27,320 --> 00:19:33,440 Speaker 1: don't give people medications that kill them. That was doctor 333 00:19:33,560 --> 00:19:39,200 Speaker 1: Joseph Latipo, trying at Harvard Medical School, the surgeon General 334 00:19:39,320 --> 00:19:43,399 Speaker 1: for the state of Florida, pointing out something that is 335 00:19:44,920 --> 00:19:47,320 Speaker 1: I think stunning to hear, even if you've been someone 336 00:19:47,359 --> 00:19:50,239 Speaker 1: as we have here on this show, who has been 337 00:19:50,280 --> 00:19:52,960 Speaker 1: willing to show skepticism and ask questions, even in the 338 00:19:53,040 --> 00:19:57,679 Speaker 1: face of the overwhelming efforts of the vaccine matrix to 339 00:19:57,720 --> 00:20:01,920 Speaker 1: push this on everybody, right, even with social media clamping down, 340 00:20:02,280 --> 00:20:04,320 Speaker 1: Thank Heavens, Clay, you know we have this, We have 341 00:20:04,480 --> 00:20:08,119 Speaker 1: this radio platform to be able to reach people. Not 342 00:20:08,200 --> 00:20:11,800 Speaker 1: a word that we say here on radio is censored. 343 00:20:12,760 --> 00:20:16,320 Speaker 1: I mean, they're FCC regular. We can't start dropping, yes, 344 00:20:16,440 --> 00:20:18,880 Speaker 1: certain you know, verbal bombs on the air. That's nothing 345 00:20:18,920 --> 00:20:21,679 Speaker 1: to do with content though, that's just a word choice issue. 346 00:20:22,680 --> 00:20:24,760 Speaker 1: But we've been talking about this for a long time 347 00:20:24,840 --> 00:20:27,960 Speaker 1: and I think what we see here with Latipo and 348 00:20:28,400 --> 00:20:34,000 Speaker 1: the situation of the vaccines, they're going to try to 349 00:20:34,080 --> 00:20:38,000 Speaker 1: suppress this with everything that they have. They're gonna try 350 00:20:38,000 --> 00:20:40,199 Speaker 1: to say that this is not the case, this is 351 00:20:40,240 --> 00:20:42,840 Speaker 1: not true. We have Alex barren said has promised with 352 00:20:42,880 --> 00:20:46,639 Speaker 1: us now, author of Pandemia, his sub stack something you 353 00:20:46,640 --> 00:20:50,199 Speaker 1: should all check out and subscribe to. Mister Barrenson. We 354 00:20:50,280 --> 00:20:52,159 Speaker 1: want to talk to you about your Twitter fight, but actually, 355 00:20:52,160 --> 00:20:56,480 Speaker 1: first can you just respond? Doctor Latipo is a serious 356 00:20:56,520 --> 00:20:59,399 Speaker 1: guy who's been right about a lot when it comes 357 00:20:59,400 --> 00:21:03,000 Speaker 1: to COVID the pandemic. And they took this all, They've 358 00:21:03,000 --> 00:21:07,119 Speaker 1: taken this study off of Twitter. What's going on here? Well? Yeah, so, 359 00:21:07,160 --> 00:21:10,280 Speaker 1: I mean Twitter, it's it's it's weird. What's happening Twitter 360 00:21:10,359 --> 00:21:12,680 Speaker 1: right now? Right? Twitter is about to get purchased by 361 00:21:12,800 --> 00:21:14,560 Speaker 1: Elon Musk, And I think, you know, I think at 362 00:21:14,560 --> 00:21:16,359 Speaker 1: this point, the odds are pretty good the deal is 363 00:21:16,400 --> 00:21:19,000 Speaker 1: going to go through, right, you know, Elon it's one day. 364 00:21:19,040 --> 00:21:21,160 Speaker 1: I don't think he can walk away again, and they haven't, 365 00:21:21,240 --> 00:21:23,600 Speaker 1: you know, they have an agreement. They've you know, uh, 366 00:21:24,359 --> 00:21:27,000 Speaker 1: they he's got the money. It's going to happen. So 367 00:21:27,600 --> 00:21:29,960 Speaker 1: um So Twitter is having this sort of fit at 368 00:21:30,000 --> 00:21:32,720 Speaker 1: the end of it's like last days. You know, it's 369 00:21:32,760 --> 00:21:34,840 Speaker 1: like it's like the Russian armies on the outskirts of 370 00:21:34,880 --> 00:21:37,320 Speaker 1: Berlin and like, and they're in their bunker, you know, 371 00:21:37,400 --> 00:21:39,679 Speaker 1: trying to do one last round up or something. So 372 00:21:39,680 --> 00:21:43,080 Speaker 1: so they've been you know, they've they've they've been barring people, 373 00:21:43,440 --> 00:21:46,639 Speaker 1: banning people, suspending people. Me, they've tried to give a 374 00:21:46,680 --> 00:21:50,000 Speaker 1: strike to now under the terms of now I have 375 00:21:50,119 --> 00:21:53,160 Speaker 1: ways to uh to to you know, to fight them 376 00:21:53,160 --> 00:21:56,639 Speaker 1: over this. But frankly, at this point it doesn't matter 377 00:21:56,720 --> 00:21:59,320 Speaker 1: that much to me right now, because if Elon, I mean, 378 00:21:59,320 --> 00:22:01,360 Speaker 1: if the deal fall through, then I guess I will 379 00:22:01,400 --> 00:22:05,080 Speaker 1: have to start to uh to pursue my remedies to 380 00:22:05,280 --> 00:22:08,960 Speaker 1: you know, prevent them from from suspending me. Yeah. But Alex, 381 00:22:09,280 --> 00:22:11,440 Speaker 1: now right, we also want to ask you though about 382 00:22:11,440 --> 00:22:14,560 Speaker 1: the substance of what doctor Latipo said, there, yes, yes, 383 00:22:14,800 --> 00:22:16,679 Speaker 1: so no, what he said is only right. So I 384 00:22:16,720 --> 00:22:19,280 Speaker 1: mean this is but let's look, there's a number of 385 00:22:19,400 --> 00:22:23,600 Speaker 1: countries that have already stopped recommending the vaccine for people 386 00:22:23,680 --> 00:22:27,920 Speaker 1: under fifty basically further boosters in the case of Norway, 387 00:22:27,920 --> 00:22:32,640 Speaker 1: people under sixty five unless they're really ill, um chronically ill, 388 00:22:32,960 --> 00:22:34,680 Speaker 1: or in the case of Norway, or in the second 389 00:22:34,760 --> 00:22:36,720 Speaker 1: or third trimesters of privacy, which is a little weird, 390 00:22:36,760 --> 00:22:39,880 Speaker 1: but that's what the Norwegians say. So country, not not 391 00:22:39,960 --> 00:22:44,160 Speaker 1: just not just you know, Rondstantus, but other countries health 392 00:22:44,160 --> 00:22:47,160 Speaker 1: authorities are looking at this and now saying no more 393 00:22:47,160 --> 00:22:50,200 Speaker 1: boosters for helping people, you know, healthy adults under the 394 00:22:50,240 --> 00:22:54,640 Speaker 1: age of fifty thirty in some cases teenagers for some countries. 395 00:22:54,640 --> 00:22:58,080 Speaker 1: So so the tide is rolling out. And that study 396 00:22:58,280 --> 00:23:01,960 Speaker 1: is a good study. Okay, it's observational, but the design 397 00:23:02,080 --> 00:23:04,879 Speaker 1: is a good one, and he didn't overreach. He said, 398 00:23:05,240 --> 00:23:08,400 Speaker 1: based on what I see in this data, I don't 399 00:23:08,440 --> 00:23:12,400 Speaker 1: recommend that men eighteen to thirty nine get more mRNA 400 00:23:12,520 --> 00:23:14,920 Speaker 1: shots because they have a double the risk of cardiac 401 00:23:15,000 --> 00:23:18,840 Speaker 1: death following the shot, and the four weas following shots 402 00:23:19,240 --> 00:23:21,840 Speaker 1: that's a that's a I mean, that's a pretty solid 403 00:23:21,880 --> 00:23:25,000 Speaker 1: finding and there's tons of other data about miacarditis that 404 00:23:25,160 --> 00:23:29,240 Speaker 1: back it up. So little is I mean, I've spoken 405 00:23:29,280 --> 00:23:33,160 Speaker 1: to him. He's a he's a smart guy. He doesn't overreach. 406 00:23:34,320 --> 00:23:37,960 Speaker 1: And I think it's a little bit terrifying now that Florida, 407 00:23:38,000 --> 00:23:40,399 Speaker 1: which has a database, you know, of twenty million people, 408 00:23:40,640 --> 00:23:42,520 Speaker 1: it's going to start to look at their database. So 409 00:23:42,560 --> 00:23:45,400 Speaker 1: it's not just going to be foreign countries that are 410 00:23:45,400 --> 00:23:47,840 Speaker 1: going to say, hey, our data is showing problems with 411 00:23:47,880 --> 00:23:51,400 Speaker 1: the vaccine. It's gonna be a big US date too. 412 00:23:51,560 --> 00:23:54,119 Speaker 1: So so that's what they're doing that. And it's not 413 00:23:54,160 --> 00:23:57,199 Speaker 1: just Twitter, right, it's whenever Twitter banns something. The you know, 414 00:23:57,240 --> 00:24:00,240 Speaker 1: the media is suppressing this, they're ignoring it, they don't 415 00:24:00,280 --> 00:24:03,280 Speaker 1: cover it. But the vaccines, as we talked about the 416 00:24:03,359 --> 00:24:05,880 Speaker 1: last couple of times, you know, they're gone. No one's 417 00:24:05,920 --> 00:24:10,679 Speaker 1: taking them anyway. So Alex, what is the long range 418 00:24:10,800 --> 00:24:14,280 Speaker 1: impact for people who got the COVID shot? Right? That's 419 00:24:14,359 --> 00:24:16,520 Speaker 1: at this point what I'm concerned about because a lot 420 00:24:16,560 --> 00:24:20,000 Speaker 1: of people trusted the quote unquote experts and they went 421 00:24:20,040 --> 00:24:22,119 Speaker 1: out and they got their first couple of shots, they 422 00:24:22,119 --> 00:24:25,320 Speaker 1: may have even gotten a booster. What is the data 423 00:24:25,400 --> 00:24:29,600 Speaker 1: reflecting for them going forward that there's about twenty percent 424 00:24:29,640 --> 00:24:31,800 Speaker 1: of us that basically said, hey, we're never going to 425 00:24:31,880 --> 00:24:33,679 Speaker 1: get it. I'm in that group. I think you're in 426 00:24:33,680 --> 00:24:36,399 Speaker 1: that group. Certainly hopefully a lot of kids are in 427 00:24:36,440 --> 00:24:39,760 Speaker 1: that group, younger kids. But what's the data reflecting for 428 00:24:39,880 --> 00:24:42,240 Speaker 1: like my parents who went and got the first couple 429 00:24:42,280 --> 00:24:48,000 Speaker 1: of shots and people like them. So the honor thinss 430 00:24:48,040 --> 00:24:50,359 Speaker 1: we do not really know. And there's a couple of reasons. 431 00:24:50,359 --> 00:24:53,000 Speaker 1: First of all, something has happened which has never happened 432 00:24:53,040 --> 00:24:55,760 Speaker 1: with any other you know, certain mass vaccination, which is 433 00:24:56,119 --> 00:24:58,560 Speaker 1: there seemed to be side effects that are that are 434 00:24:58,600 --> 00:25:02,479 Speaker 1: occurring months or you know, or even a year after 435 00:25:02,520 --> 00:25:05,840 Speaker 1: the vaccination, which the idea was, we don't need to 436 00:25:05,880 --> 00:25:08,080 Speaker 1: follow these for very long because you know, it's just 437 00:25:08,160 --> 00:25:11,000 Speaker 1: one or two doses of something, and you know, every 438 00:25:11,040 --> 00:25:15,360 Speaker 1: other vaccine, you know, within forty two days, we'll see 439 00:25:15,359 --> 00:25:17,680 Speaker 1: the side effects if there are. The problem is, the 440 00:25:17,760 --> 00:25:20,840 Speaker 1: mRNA vaccines don't work like other vaccines, and there is 441 00:25:20,880 --> 00:25:25,879 Speaker 1: evidence that in some people, the mRNA stays in your 442 00:25:25,920 --> 00:25:29,240 Speaker 1: body for much longer than they expected, and it continues 443 00:25:29,280 --> 00:25:31,640 Speaker 1: to actually to cause your body to produce by protein 444 00:25:31,760 --> 00:25:34,679 Speaker 1: for much longer than anyone expected. So that's you know, 445 00:25:34,760 --> 00:25:37,240 Speaker 1: that's one problem. Another problem is is there you know, 446 00:25:37,359 --> 00:25:39,800 Speaker 1: is there something but the fact that this is modified 447 00:25:40,000 --> 00:25:43,920 Speaker 1: mRNA that doesn't look like natural mRNA that's causing some 448 00:25:44,000 --> 00:25:47,679 Speaker 1: kind of autoimmune issues And we don't know the answers 449 00:25:47,680 --> 00:25:49,800 Speaker 1: to that. And the other reason we don't know the 450 00:25:49,840 --> 00:25:53,040 Speaker 1: answers is that the scientists who should be looking at 451 00:25:53,040 --> 00:25:55,760 Speaker 1: this and should be forcing the companies to look at this, 452 00:25:56,119 --> 00:25:58,280 Speaker 1: are not really doing so, so that data is kind 453 00:25:58,280 --> 00:26:00,040 Speaker 1: of coming out in dribs and drafts. Here's why I 454 00:26:00,040 --> 00:26:03,639 Speaker 1: can tell you with certainty, most countries that used a 455 00:26:03,640 --> 00:26:07,960 Speaker 1: lot of mr ANDA have above normal excess deaths in 456 00:26:08,040 --> 00:26:10,160 Speaker 1: twenty twenty two. That's what I was going to ask. 457 00:26:10,160 --> 00:26:11,600 Speaker 1: That's what I was going to ask you so for 458 00:26:11,760 --> 00:26:13,800 Speaker 1: to storry to cut you off there, but for our 459 00:26:13,840 --> 00:26:17,639 Speaker 1: audience out there, explain what that excess death data is 460 00:26:17,680 --> 00:26:22,160 Speaker 1: showing you as it pertains to twenty twenty two. Sure, so, 461 00:26:22,160 --> 00:26:25,480 Speaker 1: so if you're you know, it's a very basic homography. 462 00:26:25,800 --> 00:26:29,720 Speaker 1: You know, countries know how old their populations are, and 463 00:26:29,800 --> 00:26:32,960 Speaker 1: you can you can make very good estimates of happening. 464 00:26:35,440 --> 00:26:37,560 Speaker 1: You can make very good estimates of how many people 465 00:26:37,600 --> 00:26:40,840 Speaker 1: are going to die, uh, you know, every year in 466 00:26:42,040 --> 00:26:46,960 Speaker 1: various stages, okay, And so in Australia, for example, excess 467 00:26:47,040 --> 00:26:51,320 Speaker 1: deaths are running almost twenty percent above or death overall 468 00:26:51,400 --> 00:26:54,320 Speaker 1: deaths or twenty percent higher, almost ringers an higher than 469 00:26:54,359 --> 00:26:57,399 Speaker 1: they should be in twenty twenty two. And Australia you 470 00:26:57,440 --> 00:27:00,720 Speaker 1: can't say, oh, that long COVID, or that's because their 471 00:27:00,720 --> 00:27:03,320 Speaker 1: hospitals were overwhelmed, or any of the other excuses that 472 00:27:03,320 --> 00:27:06,359 Speaker 1: would be needed. Because Australia had almost no COVID in 473 00:27:06,400 --> 00:27:09,160 Speaker 1: twenty twenty and twenty twenty one. They locked down really hard, 474 00:27:09,440 --> 00:27:12,760 Speaker 1: they didn't let anybody in and so they had very 475 00:27:12,760 --> 00:27:15,919 Speaker 1: little COVID. So something is producing that now they've had 476 00:27:15,920 --> 00:27:18,240 Speaker 1: a lot of COVID this year, okay, And some of 477 00:27:18,240 --> 00:27:21,880 Speaker 1: those deaths are COVID related. But even when you factor 478 00:27:21,880 --> 00:27:24,560 Speaker 1: out all the death the things that they're attributing to 479 00:27:24,560 --> 00:27:29,280 Speaker 1: COVID using a pretty liberal standard, there's still about ten 480 00:27:29,440 --> 00:27:33,439 Speaker 1: or twelve percent access other deaths and we don't know 481 00:27:33,480 --> 00:27:38,160 Speaker 1: what's causing that. To me, considering that the vaccine were 482 00:27:38,200 --> 00:27:41,560 Speaker 1: given to almost everyone in especially in Australia, I mean, 483 00:27:41,600 --> 00:27:44,560 Speaker 1: but also in Europe the rates were very high. A 484 00:27:44,720 --> 00:27:48,280 Speaker 1: natural place to look would be vaccine, but people don't 485 00:27:48,320 --> 00:27:50,360 Speaker 1: want to do it, they're afraid to do it, so 486 00:27:50,400 --> 00:27:53,399 Speaker 1: we don't We don't know that it's vaccine caused, and 487 00:27:53,440 --> 00:27:56,000 Speaker 1: we don't know even if it is, how long it 488 00:27:56,040 --> 00:27:58,840 Speaker 1: will last. And to be clear, this is not like people. 489 00:27:59,240 --> 00:28:01,399 Speaker 1: You know, it's not like the death redoubled or anything 490 00:28:01,440 --> 00:28:05,439 Speaker 1: like that. It's it's a ten percent, uh, non COVID increase, 491 00:28:05,480 --> 00:28:08,280 Speaker 1: a close to twenty percent overall increase. So that's a 492 00:28:08,440 --> 00:28:12,119 Speaker 1: that's a big number, but it isn't It isn't like apocalyptic. 493 00:28:12,400 --> 00:28:15,960 Speaker 1: So we just don't know. Alex, just one more quickly 494 00:28:15,960 --> 00:28:19,400 Speaker 1: for you. When someone says now online or you see 495 00:28:19,440 --> 00:28:22,440 Speaker 1: them on TV, say well, we know that the shots 496 00:28:22,560 --> 00:28:27,640 Speaker 1: prevent severe hospitalization and death, where are we on that? So, 497 00:28:27,880 --> 00:28:30,879 Speaker 1: I mean, that's just totally wrong, you know, in Australia again, 498 00:28:31,240 --> 00:28:33,760 Speaker 1: and they're gonna come back to them because their data 499 00:28:33,880 --> 00:28:38,200 Speaker 1: is cleanly, you know, they it's it's presented cleanly. In Australia. 500 00:28:38,240 --> 00:28:41,920 Speaker 1: For example, in New South Wales that's the biggest state 501 00:28:41,960 --> 00:28:44,760 Speaker 1: in Australia, it's about a third of the whole country's population. 502 00:28:45,240 --> 00:28:47,640 Speaker 1: In the most recent week for which they release data, 503 00:28:47,800 --> 00:28:50,400 Speaker 1: I believe it, it's seventy five COVID deaths and four 504 00:28:50,440 --> 00:28:55,200 Speaker 1: of those were in unvaccinated people. So so I mean, now, look, 505 00:28:55,280 --> 00:28:58,400 Speaker 1: they're they're gonna say, yeah, we've vaccinated almost everybody, and 506 00:28:58,440 --> 00:29:01,880 Speaker 1: so that's why you know, almost everybody who vaccinated who 507 00:29:01,960 --> 00:29:04,800 Speaker 1: died is vaccinated. Okay, fine, but don't tell me that 508 00:29:04,880 --> 00:29:07,960 Speaker 1: the vaccines are doing anything or you know, or anything 509 00:29:08,040 --> 00:29:11,800 Speaker 1: much to prevent disease and death right now, because why 510 00:29:11,840 --> 00:29:14,440 Speaker 1: would ninety five percent of the death be occurring and 511 00:29:14,520 --> 00:29:18,160 Speaker 1: vaccinated people to stat with the case seems pretty obvious, 512 00:29:18,160 --> 00:29:20,320 Speaker 1: but they don't want to admit it, folks. Alex Berenson 513 00:29:20,440 --> 00:29:25,880 Speaker 1: go check out his sub stack. And but you know 514 00:29:25,920 --> 00:29:28,000 Speaker 1: you can't follow me. Well you can't follow me on Twitter, 515 00:29:28,040 --> 00:29:30,400 Speaker 1: but I can't sweep right now because it's the last 516 00:29:30,480 --> 00:29:32,920 Speaker 1: days of the Twitter empire. Yeah, well, have you on it. 517 00:29:32,920 --> 00:29:36,360 Speaker 1: Maybe we'll have a little celebration finally has it and 518 00:29:36,400 --> 00:29:39,240 Speaker 1: we can throw a little Barrenson freedom party on Twitter. 519 00:29:39,280 --> 00:29:41,080 Speaker 1: It'd be fun. So thanks for being with us, Alex. 520 00:29:41,640 --> 00:29:45,840 Speaker 1: Thank thanks guys. There are some things in life that 521 00:29:46,280 --> 00:29:48,520 Speaker 1: you know for sure, Folks, your health is in your 522 00:29:48,520 --> 00:29:50,040 Speaker 1: own hands. That much is clear. Look where we're just 523 00:29:50,080 --> 00:29:52,720 Speaker 1: talking to Alex about. And if you're going to listen 524 00:29:52,760 --> 00:29:56,200 Speaker 1: to the establishment, if you're gonna listen to the apparatus, 525 00:29:56,760 --> 00:29:59,560 Speaker 1: they're gonna tell you to eat a lot of soy, 526 00:30:00,040 --> 00:30:02,840 Speaker 1: watch a lot of CNN. You know your chest will 527 00:30:02,880 --> 00:30:04,960 Speaker 1: go concave. If you're a guy, you're gonna start to 528 00:30:05,040 --> 00:30:07,280 Speaker 1: hunch over and just be like, I don't have any energy. 529 00:30:07,600 --> 00:30:09,720 Speaker 1: I feel like Brian Stelter walking around out there. You 530 00:30:09,720 --> 00:30:12,800 Speaker 1: don't want that. You want ample testosterone for your day 531 00:30:12,800 --> 00:30:13,800 Speaker 1: to day. You don't want to be one of these 532 00:30:13,880 --> 00:30:16,680 Speaker 1: democrats that can't get after it in life, doesn't have 533 00:30:16,680 --> 00:30:18,880 Speaker 1: the energy and drive to get it done. This is 534 00:30:18,880 --> 00:30:20,600 Speaker 1: why you need to try Chalk, friends, If you want 535 00:30:20,640 --> 00:30:24,320 Speaker 1: a little boost, little additional umph in your day, Chalk 536 00:30:24,400 --> 00:30:28,920 Speaker 1: Supplements delivered just that. 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Use my name 546 00:30:57,080 --> 00:30:59,520 Speaker 1: Buck when you sign on and get thirty five percent 547 00:30:59,560 --> 00:31:04,000 Speaker 1: off for life. The website is spelled choq dot com. 548 00:31:04,080 --> 00:31:06,800 Speaker 1: That's chalk dot com. Remember make sure you use my 549 00:31:06,880 --> 00:31:10,280 Speaker 1: code Buck. You get thirty five percent off. Get fired up, 550 00:31:10,400 --> 00:31:16,520 Speaker 1: Get after it, Try Chalk. Welcome back in Clay Travis 551 00:31:16,560 --> 00:31:20,440 Speaker 1: buck Sexton show Buck. My mom wanted to send a word. 552 00:31:20,480 --> 00:31:22,800 Speaker 1: We were talking about this earlier. She is, in fact 553 00:31:22,960 --> 00:31:26,920 Speaker 1: listening to the show on the beach right now, watching 554 00:31:27,360 --> 00:31:33,000 Speaker 1: our grandkids, her grandkids, my kids. We've got several different 555 00:31:33,000 --> 00:31:34,800 Speaker 1: people who want to weigh in on a variety of 556 00:31:34,800 --> 00:31:37,200 Speaker 1: different subjects, giving you a little bit of a roadmap 557 00:31:37,240 --> 00:31:39,960 Speaker 1: of where we're heading. The third hour gonna lay out 558 00:31:40,040 --> 00:31:44,800 Speaker 1: four weeks out from the mid terms. John Fetterman disaster candidate. 559 00:31:45,000 --> 00:31:47,040 Speaker 1: We'll talk about hershel what we think is going to 560 00:31:47,160 --> 00:31:50,600 Speaker 1: go on there, Optimism in many states where it would 561 00:31:50,680 --> 00:31:55,360 Speaker 1: be not traditional necessarily to be optimistic about the chances 562 00:31:55,440 --> 00:31:58,960 Speaker 1: of Republicans being elected. We'll talk about all that, but 563 00:31:59,240 --> 00:32:01,960 Speaker 1: a lot of people went away in in the wake 564 00:32:02,280 --> 00:32:07,320 Speaker 1: of what Alex Barrinson was talking about. There's a lot 565 00:32:07,320 --> 00:32:10,520 Speaker 1: of people telling stories, Buck, as you well know, about 566 00:32:10,600 --> 00:32:13,600 Speaker 1: what the COVID shot has done to them. Let's take 567 00:32:13,600 --> 00:32:16,760 Speaker 1: a couple of these calls. Richard in South Carolina. Richard, 568 00:32:16,800 --> 00:32:19,920 Speaker 1: thanks for listening what you got for us. I'm one 569 00:32:19,920 --> 00:32:22,600 Speaker 1: of the people that the vaccine nearly killed within days, 570 00:32:23,360 --> 00:32:25,800 Speaker 1: and I've been waiting for someone to start the conversation 571 00:32:25,840 --> 00:32:28,720 Speaker 1: about this. That was in the last week of April 572 00:32:28,800 --> 00:32:33,480 Speaker 1: of twenty one, and nobody's interested. I emailed Glenn Beck, 573 00:32:33,560 --> 00:32:37,680 Speaker 1: I emailed Sean Hannity, nothing, my congressional representative, my two 574 00:32:37,720 --> 00:32:42,000 Speaker 1: South Carolina Senators, Lindsey Graham and Tim Scott, Governor McMaster. 575 00:32:42,320 --> 00:32:44,760 Speaker 1: So tell us, tell us what happened. So you took 576 00:32:44,800 --> 00:32:47,760 Speaker 1: the shot in April of twenty twenty one, one shot, 577 00:32:47,800 --> 00:32:51,240 Speaker 1: two shot? What happened to you? Two shots within the 578 00:32:51,280 --> 00:32:55,000 Speaker 1: second day or so. I assist on both my eyeballs 579 00:32:55,200 --> 00:33:00,360 Speaker 1: the kind of consistent with tuberculosis my elbows like I 580 00:33:00,400 --> 00:33:04,200 Speaker 1: had tennis balls underneath the skin my hips. I was 581 00:33:04,280 --> 00:33:06,200 Speaker 1: unable to walk for the better part of a year. 582 00:33:06,440 --> 00:33:09,440 Speaker 1: I'm sixteen months into it and I'm finally getting some 583 00:33:09,480 --> 00:33:13,360 Speaker 1: sort of experimental treatment that I mean, I'm able to 584 00:33:13,400 --> 00:33:16,920 Speaker 1: walk a little bit now. But basically what it amounts 585 00:33:16,920 --> 00:33:20,400 Speaker 1: to is none of these pinheads thought that the people 586 00:33:20,440 --> 00:33:22,280 Speaker 1: that are going to suffer from this, their lives are 587 00:33:22,320 --> 00:33:25,640 Speaker 1: destroyed forever. So you did this. Were you forced to 588 00:33:25,680 --> 00:33:27,720 Speaker 1: get it for to stay to work like or you 589 00:33:27,760 --> 00:33:30,120 Speaker 1: just listened to everybody who said, hey, you should go 590 00:33:30,160 --> 00:33:34,360 Speaker 1: get the COVID shot. The politicians and fauci all said 591 00:33:34,440 --> 00:33:37,280 Speaker 1: that they're safe, they're effective. Turns out there neither of those. 592 00:33:38,760 --> 00:33:40,680 Speaker 1: First of all, we're so sorry Richard that you're going 593 00:33:40,720 --> 00:33:43,680 Speaker 1: through this. And you know, people were forced to take 594 00:33:43,720 --> 00:33:46,960 Speaker 1: these shots in many places around the country. But even 595 00:33:46,960 --> 00:33:49,160 Speaker 1: if you weren't necessarily forced as a matter of keeping 596 00:33:49,200 --> 00:33:52,520 Speaker 1: your job or of state regulations and Bide administration tried 597 00:33:52,560 --> 00:33:55,680 Speaker 1: to force it federally. The whole medical establishment. I mean, 598 00:33:55,680 --> 00:33:58,400 Speaker 1: I'm still furious, Clay, and thank you Richard for calling 599 00:33:58,440 --> 00:34:02,040 Speaker 1: in medical establishment got this. Very few voices spoke out 600 00:34:02,080 --> 00:34:04,440 Speaker 1: against it. I'm angry every time I go into a 601 00:34:04,480 --> 00:34:06,840 Speaker 1: doctor's officers, excuse me, sir, can you put on a mask? 602 00:34:06,880 --> 00:34:09,200 Speaker 1: I'm going why why am I putting on a mask? 603 00:34:09,360 --> 00:34:11,640 Speaker 1: So I can go into work, and go into church, 604 00:34:11,840 --> 00:34:14,360 Speaker 1: and go into restaurants and go without a mask on. 605 00:34:14,480 --> 00:34:16,960 Speaker 1: But here I have to wear a mask? What sense 606 00:34:17,120 --> 00:34:20,440 Speaker 1: does that make? Yeah? Look, Buck, I wish that I didn't, 607 00:34:20,600 --> 00:34:22,400 Speaker 1: and I understand the people who are like live and 608 00:34:22,480 --> 00:34:25,680 Speaker 1: Let live. Every time I see somebody with a mask on, 609 00:34:26,239 --> 00:34:31,799 Speaker 1: I instinctively think I despise you. Well, this is why 610 00:34:32,280 --> 00:34:34,520 Speaker 1: I told you the story of a characton. It was hilarious. 611 00:34:34,680 --> 00:34:36,759 Speaker 1: When someone's like, aren't you Buck, sex, then she's wearing 612 00:34:36,760 --> 00:34:38,440 Speaker 1: a ninety five mask, I'm like, nah, I don't know. 613 00:34:38,440 --> 00:34:40,560 Speaker 1: I don't know who that is. Don't trust it. But 614 00:34:40,640 --> 00:34:43,799 Speaker 1: I just I the reason why I understand the Live 615 00:34:43,840 --> 00:34:47,920 Speaker 1: and Let live people. But we've lived through two years 616 00:34:48,080 --> 00:34:52,120 Speaker 1: of the mask people demanding that everybody else wear a mask. 617 00:34:52,400 --> 00:34:55,480 Speaker 1: So when I still see someone walking around and god forbid, 618 00:34:55,520 --> 00:34:58,239 Speaker 1: I feel awful for the kids when their parents are 619 00:34:58,239 --> 00:35:03,520 Speaker 1: making them wear masks, and I think, yeah, it's child abuse. 620 00:35:03,600 --> 00:35:07,840 Speaker 1: I mean, it's what it is. Um Ned in Glenwood Springs, Colorado, 621 00:35:11,239 --> 00:35:16,200 Speaker 1: to show my experience. I took the we got one minute, NED, 622 00:35:16,200 --> 00:35:19,080 Speaker 1: just so you know, go ahead. I took the first 623 00:35:19,120 --> 00:35:23,919 Speaker 1: Johnson and Johnson COVID shot June twenty third last year. 624 00:35:24,480 --> 00:35:28,680 Speaker 1: It took about five months and I started having major problems. 625 00:35:29,680 --> 00:35:34,680 Speaker 1: Took three neurologists, multiple doctors. I've been diagnosed with chronic 626 00:35:34,719 --> 00:35:41,840 Speaker 1: inflammatory demyelinating polyneuropathy. My immune system was destroying the milan, 627 00:35:42,040 --> 00:35:46,279 Speaker 1: which is the fat insulating protective layer on my nerves. 628 00:35:46,560 --> 00:35:52,600 Speaker 1: Every three weeks. Now I get an immunoglobulin infusion to 629 00:35:52,719 --> 00:35:56,359 Speaker 1: the tune of almost ten thousand bucks. Now I can 630 00:35:56,440 --> 00:36:02,319 Speaker 1: walk at least, but it totally who barred me completely? 631 00:36:02,680 --> 00:36:08,160 Speaker 1: I'm disabled now. I'm sixty years old, and please excuse 632 00:36:08,239 --> 00:36:12,239 Speaker 1: my language. I am not happy, NED. We appreciate calling it. 633 00:36:12,360 --> 00:36:15,680 Speaker 1: We're so sorry about what you're going through. Clay. A 634 00:36:15,719 --> 00:36:17,840 Speaker 1: lot of these stories all across that we could do 635 00:36:17,880 --> 00:36:19,919 Speaker 1: a whole show just taking calls from people that feel 636 00:36:19,960 --> 00:36:23,480 Speaker 1: they got really severely injured by the vaccine. There's no doubt, 637 00:36:23,520 --> 00:36:26,440 Speaker 1: and that's why the fact that you can't sue is 638 00:36:26,480 --> 00:36:31,480 Speaker 1: so indefensible, and also why we need major hearings and 639 00:36:31,600 --> 00:36:36,239 Speaker 1: investigations into these shots Visor, Maderna, Johnson and Johnson What 640 00:36:36,280 --> 00:36:39,279 Speaker 1: did they do? What did these companies know and when 641 00:36:39,320 --> 00:36:40,919 Speaker 1: did they know it? And we need it now