1 00:00:01,360 --> 00:00:04,120 Speaker 1: You're in the freedom Hunt. This is the Buck Sexton 2 00:00:04,200 --> 00:00:07,520 Speaker 1: Show podcast. Get more from Buck by following him on 3 00:00:07,600 --> 00:00:11,440 Speaker 1: social media at buck Sexton on Facebook, Twitter, and Instagram. 4 00:00:11,720 --> 00:00:16,320 Speaker 1: Welcome my friends to the Buck Sexton Show. Joe Biden 5 00:00:16,480 --> 00:00:19,680 Speaker 1: taking a victory lap yesterday because the Electoral College has 6 00:00:19,680 --> 00:00:23,720 Speaker 1: certified his win and we have to take stock of 7 00:00:23,800 --> 00:00:28,600 Speaker 1: where we are right now in response to this, and 8 00:00:28,680 --> 00:00:30,720 Speaker 1: I think that everyone needs to understand there's going to 9 00:00:30,800 --> 00:00:34,159 Speaker 1: be a lot of frustration here. There's going to be 10 00:00:34,200 --> 00:00:38,800 Speaker 1: a lot of agitation because, yes, we know there was fraud. 11 00:00:38,920 --> 00:00:42,519 Speaker 1: Yes we know that the Democrats stack the deck in 12 00:00:42,600 --> 00:00:47,120 Speaker 1: their favor with the elimination of anti fraud safeguards using 13 00:00:47,159 --> 00:00:52,320 Speaker 1: COVID nineteen as an excuse. But the process is continuing 14 00:00:52,400 --> 00:00:57,560 Speaker 1: on and with each passing week now it's favoring Joe Biden. 15 00:00:57,800 --> 00:01:02,480 Speaker 1: That's just an objective reality that we're dealing with. Is 16 00:01:02,520 --> 00:01:07,320 Speaker 1: there the possibility that there will be some last minute case, 17 00:01:07,680 --> 00:01:09,560 Speaker 1: that something will come up that we'll be able to 18 00:01:09,640 --> 00:01:18,200 Speaker 1: finally prove definitively that there was systematic and intentional fraud, 19 00:01:18,400 --> 00:01:21,960 Speaker 1: the kind of proof that even a weak will, even 20 00:01:22,000 --> 00:01:25,480 Speaker 1: a cowardly judge would have to say for fear of 21 00:01:25,880 --> 00:01:29,600 Speaker 1: shaming his profession or her profession, would have to say, yes, 22 00:01:29,640 --> 00:01:33,280 Speaker 1: you're correct, this is fraud. We cannot certify the results 23 00:01:33,280 --> 00:01:36,399 Speaker 1: in these states. Yes, it is possible. Is it likely? 24 00:01:37,520 --> 00:01:40,399 Speaker 1: I think you all know the answer to that. Joe 25 00:01:40,440 --> 00:01:45,080 Speaker 1: Biden now is feeling like he is inevitable that this 26 00:01:45,160 --> 00:01:48,760 Speaker 1: is over, this is done with. We can continue, you 27 00:01:48,800 --> 00:01:50,560 Speaker 1: know that old you can walk and chew gum. At 28 00:01:50,560 --> 00:01:53,440 Speaker 1: the same time, we can continue to look for that fraud. 29 00:01:55,080 --> 00:02:00,880 Speaker 1: We can dive into the Antrim County autopsy report from 30 00:02:00,880 --> 00:02:04,800 Speaker 1: the voting machines, right the deep dive that they did. 31 00:02:04,840 --> 00:02:08,760 Speaker 1: I read it last night. I'm curious to see what's 32 00:02:08,800 --> 00:02:10,960 Speaker 1: going to be done with it. I'm sure the DOJ 33 00:02:11,919 --> 00:02:13,720 Speaker 1: is aware of it. I'm sure that this is being 34 00:02:13,919 --> 00:02:17,160 Speaker 1: looked at. Now. Being looked at is not the same 35 00:02:17,200 --> 00:02:20,360 Speaker 1: thing as action taken on. But I believe that there 36 00:02:20,360 --> 00:02:21,960 Speaker 1: are people who are going to read this thing and 37 00:02:22,560 --> 00:02:25,080 Speaker 1: take a look at whether or not it changes the 38 00:02:26,280 --> 00:02:30,560 Speaker 1: certification in a place like Michigan. But we have to 39 00:02:30,600 --> 00:02:33,600 Speaker 1: look at that and also understand that Joe Biden is 40 00:02:33,720 --> 00:02:37,360 Speaker 1: preparing for his administration at this point, and this is 41 00:02:37,440 --> 00:02:41,360 Speaker 1: likely what we are going to face, and I understand 42 00:02:41,400 --> 00:02:43,400 Speaker 1: there's going to be heat that I get for this. 43 00:02:43,560 --> 00:02:46,000 Speaker 1: I understand that people don't want to hear this, but 44 00:02:46,080 --> 00:02:50,440 Speaker 1: I always tell you that I will speak the truth 45 00:02:50,520 --> 00:02:53,000 Speaker 1: to you as I see it, and I believe that 46 00:02:53,080 --> 00:02:56,840 Speaker 1: this is the objective truth right now. It is a future, 47 00:02:57,960 --> 00:03:00,360 Speaker 1: It is an issue of the future. It is a 48 00:03:00,560 --> 00:03:03,600 Speaker 1: prediction in a sense. Right the future has not happened yet, 49 00:03:04,120 --> 00:03:06,440 Speaker 1: to borrow from the Terminator films, the future is not 50 00:03:06,520 --> 00:03:10,760 Speaker 1: yet set. But we need to understand what the reality 51 00:03:11,320 --> 00:03:15,919 Speaker 1: of the numbers tells us right now and prepare accordingly, 52 00:03:16,800 --> 00:03:21,200 Speaker 1: including making sure that we focus on the race right 53 00:03:21,240 --> 00:03:25,320 Speaker 1: ahead of us here in Georgia, because a Biden administration 54 00:03:25,480 --> 00:03:29,000 Speaker 1: with the House and the Senate in Democrat control is 55 00:03:29,040 --> 00:03:34,040 Speaker 1: a very different thing than a Biden administration with divided Congress. 56 00:03:34,760 --> 00:03:37,200 Speaker 1: With a divided Congress, they're going to have to prop 57 00:03:37,320 --> 00:03:43,320 Speaker 1: up this really buffoonish, clownish and yes, corrupt fellow and 58 00:03:43,400 --> 00:03:47,040 Speaker 1: spend a tremendous amount of time and energy and resources 59 00:03:47,280 --> 00:03:49,360 Speaker 1: just to make sure the American people don't see for 60 00:03:49,400 --> 00:03:54,880 Speaker 1: themselves this is the clown that we've elected. Really this guy. Now, 61 00:03:54,880 --> 00:03:56,040 Speaker 1: I know a lot of you would say you didn't 62 00:03:56,040 --> 00:03:58,960 Speaker 1: elect him, but if he becomes president, then he is 63 00:03:59,000 --> 00:04:02,880 Speaker 1: technically the guy. And so we look at this now 64 00:04:02,880 --> 00:04:04,960 Speaker 1: and we say, what could we do in preparation, what 65 00:04:05,000 --> 00:04:07,440 Speaker 1: could we do to get ready for this? Well, I 66 00:04:07,440 --> 00:04:10,000 Speaker 1: can tell you this much. A lot of what they 67 00:04:10,040 --> 00:04:15,040 Speaker 1: were saying about Trump will be true or would be 68 00:04:15,080 --> 00:04:18,400 Speaker 1: true about a Biden administration. A lot of it would 69 00:04:18,400 --> 00:04:22,520 Speaker 1: be accurate. For example, when they talked about state media 70 00:04:22,720 --> 00:04:24,640 Speaker 1: under Trump, they would say this, They really would only 71 00:04:24,680 --> 00:04:27,680 Speaker 1: say this as a knock on Fox News. And I 72 00:04:27,800 --> 00:04:32,159 Speaker 1: was consistent in pointing out that state media would indicate 73 00:04:32,200 --> 00:04:36,280 Speaker 1: that there's only really one acceptable media point of view. 74 00:04:37,200 --> 00:04:40,240 Speaker 1: I mean true state media. Some places have a government, 75 00:04:40,880 --> 00:04:44,480 Speaker 1: a kind of quasi government or government Oregon, but usually 76 00:04:44,520 --> 00:04:48,400 Speaker 1: if there's an actual state media apparatus, the opposition is 77 00:04:48,400 --> 00:04:52,960 Speaker 1: at a minimum tiny, right, the opposition is small. In 78 00:04:53,000 --> 00:04:55,200 Speaker 1: this country, we had the opposite. We had ninety five 79 00:04:55,400 --> 00:05:01,880 Speaker 1: percent of journos out there, and of them anti the administration, 80 00:05:02,240 --> 00:05:05,880 Speaker 1: and they advanced their careers despite what they said, Despite 81 00:05:05,920 --> 00:05:07,839 Speaker 1: what Jim Acosta would pretend when you go to the 82 00:05:07,839 --> 00:05:11,400 Speaker 1: White House, you know they were not doing the journalistic 83 00:05:11,400 --> 00:05:14,960 Speaker 1: equivalent of storming the beaches of normandy, they were advancing 84 00:05:14,960 --> 00:05:18,120 Speaker 1: their careers, they were becoming more famous, they were fattening 85 00:05:18,160 --> 00:05:23,760 Speaker 1: their paychecks. So in no way, whatsoever, in no way 86 00:05:23,800 --> 00:05:26,479 Speaker 1: do we see this now and have any reason to 87 00:05:26,520 --> 00:05:31,200 Speaker 1: believe that Joe Biden will be anything other than absolutely 88 00:05:31,200 --> 00:05:36,080 Speaker 1: coddled and propped up and assisted by the media. That's 89 00:05:36,120 --> 00:05:39,120 Speaker 1: what's going to happen. And you're going to hear a 90 00:05:39,200 --> 00:05:44,440 Speaker 1: lot of empty rhetoric from Biden himself but also from 91 00:05:44,480 --> 00:05:47,040 Speaker 1: the people around him, because this is going to be 92 00:05:47,279 --> 00:05:50,920 Speaker 1: the most incredible emperor has no closed situation you've ever seen. 93 00:05:51,760 --> 00:05:55,440 Speaker 1: The emperor is too old, he's incompetent, and he's corrupt. 94 00:05:56,080 --> 00:05:57,960 Speaker 1: But they're going to tell you that this is great. 95 00:05:58,440 --> 00:06:00,960 Speaker 1: There's going to be this amazing restaurant ration of America 96 00:06:01,000 --> 00:06:03,560 Speaker 1: that happens. You know that's a fraud. You know that's 97 00:06:03,600 --> 00:06:08,400 Speaker 1: not true. The amount of lies that you are likely 98 00:06:08,440 --> 00:06:11,159 Speaker 1: to be told in the next ninety days alone will 99 00:06:11,200 --> 00:06:14,919 Speaker 1: surpass anything you've ever seen before. Because now the media 100 00:06:14,960 --> 00:06:19,479 Speaker 1: doesn't even really pretend there's no objectivity. They picked a team, 101 00:06:19,960 --> 00:06:21,880 Speaker 1: He's their team. This is what they're going to do. 102 00:06:23,040 --> 00:06:26,280 Speaker 1: And here's what Biden was saying yesterday on the one hand, 103 00:06:26,360 --> 00:06:29,880 Speaker 1: calling for unity, calling to bring us all together, and 104 00:06:29,960 --> 00:06:37,040 Speaker 1: then trashing Trump play eighteen. By his own standards, these 105 00:06:37,120 --> 00:06:41,200 Speaker 1: numbers represent it a clear victory then, and I respectfully 106 00:06:41,240 --> 00:06:44,239 Speaker 1: suggest they do so now. If anyone didn't know before, 107 00:06:44,400 --> 00:06:47,240 Speaker 1: they know now. What beats deep in the hearts of 108 00:06:47,279 --> 00:06:52,200 Speaker 1: the American people is this democracy, the right to be heard, 109 00:06:52,920 --> 00:06:56,800 Speaker 1: to have your vote counted, to choose leaders of this nation, 110 00:06:57,560 --> 00:07:03,160 Speaker 1: to govern ourselves in America. Politicians don't take power. People 111 00:07:03,320 --> 00:07:07,000 Speaker 1: grant power to them. The flame of democracy was lit 112 00:07:07,000 --> 00:07:09,560 Speaker 1: in this nation a long time ago, and we now 113 00:07:09,600 --> 00:07:13,680 Speaker 1: know nothing, not even a pandemic or an abusive power, 114 00:07:14,120 --> 00:07:17,600 Speaker 1: can extinguish that flame. An abusive power. What was the 115 00:07:17,600 --> 00:07:22,280 Speaker 1: abusive power again? Bringing lawsuits, something that they did endlessly 116 00:07:22,320 --> 00:07:24,600 Speaker 1: and in bad faith against Trump to slow him down. 117 00:07:25,080 --> 00:07:28,000 Speaker 1: But now the courts are bad. Understand that we are 118 00:07:28,040 --> 00:07:32,400 Speaker 1: not only going into a post journalism area with the Democrats, 119 00:07:32,800 --> 00:07:37,440 Speaker 1: we're also going into a post principle era. Whatever they 120 00:07:37,440 --> 00:07:40,280 Speaker 1: don't like, whatever stands in their way, they'll just discard. 121 00:07:41,040 --> 00:07:43,720 Speaker 1: They don't have to make any show of really caring 122 00:07:43,720 --> 00:07:46,800 Speaker 1: what you think anymore. This is about the raw exercise 123 00:07:46,880 --> 00:07:49,800 Speaker 1: of political power. They think they will have achieved it 124 00:07:49,840 --> 00:07:52,560 Speaker 1: through this, and look at what they did to get here. 125 00:07:52,960 --> 00:07:55,960 Speaker 1: Biden's talking about democracy and how beautiful a thing it 126 00:07:56,040 --> 00:07:58,400 Speaker 1: is now because he likes the outcome for him as 127 00:07:58,440 --> 00:08:01,600 Speaker 1: it stands so far. The rest of us stand around saying, 128 00:08:02,360 --> 00:08:04,960 Speaker 1: you guys changed the rules in an election year by 129 00:08:05,040 --> 00:08:11,040 Speaker 1: hyperventilating about and exaggerating about the threat of COVID nineteen 130 00:08:11,440 --> 00:08:14,640 Speaker 1: only as it pertains of course, to voting in person, 131 00:08:15,200 --> 00:08:18,800 Speaker 1: not to having blm rallies in the streets, not to 132 00:08:18,880 --> 00:08:23,480 Speaker 1: any number of other activities that are Democrat approved, but 133 00:08:23,680 --> 00:08:28,520 Speaker 1: voting no that required enormous shifts in the actual mail 134 00:08:28,600 --> 00:08:33,280 Speaker 1: in balloting process and transforming the process in the year 135 00:08:33,320 --> 00:08:36,200 Speaker 1: of the election and using it to the absolute maximum advantage. 136 00:08:36,200 --> 00:08:39,000 Speaker 1: And I do at some level blame Republicans, who are 137 00:08:39,040 --> 00:08:42,319 Speaker 1: supposed to be the ones on guard against this blocking this. 138 00:08:42,720 --> 00:08:46,920 Speaker 1: I blame them for not doing more in advance, for 139 00:08:47,080 --> 00:08:51,079 Speaker 1: not seeing this train coming down the tracks. Why do 140 00:08:51,120 --> 00:08:54,959 Speaker 1: you think Pelosi and the other Libs we're going all 141 00:08:55,000 --> 00:08:58,040 Speaker 1: out with the crazy post office conspiracy over the summer. 142 00:08:59,280 --> 00:09:02,720 Speaker 1: So that's something that now we have to learn from. 143 00:09:02,760 --> 00:09:05,760 Speaker 1: I hope going forward, no matter what or what we 144 00:09:05,800 --> 00:09:07,960 Speaker 1: end up finding out here about the fraud. I will 145 00:09:07,960 --> 00:09:12,400 Speaker 1: continue to look at every allegation, every bit of evidence 146 00:09:12,440 --> 00:09:15,960 Speaker 1: that is presented here by the Trump legal team, by 147 00:09:16,120 --> 00:09:20,400 Speaker 1: anyone who comes forward and has proof of fraud. We 148 00:09:20,559 --> 00:09:24,360 Speaker 1: owe that to the country. But we also need to 149 00:09:24,440 --> 00:09:28,000 Speaker 1: be ready for what is coming now. And you are 150 00:09:28,040 --> 00:09:32,679 Speaker 1: going to see an administration that has the full and 151 00:09:33,000 --> 00:09:37,800 Speaker 1: open partisan backing of the social media companies, the entirety 152 00:09:37,880 --> 00:09:42,640 Speaker 1: of the journalistic media apparatus in its pocket, big government 153 00:09:43,000 --> 00:09:48,560 Speaker 1: and big business working hand in glove, not shedding any 154 00:09:48,600 --> 00:09:53,439 Speaker 1: tears for the destruction, the wanton, reckless destruction of small 155 00:09:53,480 --> 00:09:59,080 Speaker 1: businesses across the country as a result of these preposterous lockdowns. 156 00:10:00,640 --> 00:10:02,640 Speaker 1: You're not gonna see any any tears over that. They 157 00:10:02,679 --> 00:10:07,440 Speaker 1: like this advantage that they have. The eradication of small 158 00:10:07,440 --> 00:10:10,360 Speaker 1: business is something that Democrats aren't particularly upset about either. 159 00:10:10,960 --> 00:10:13,840 Speaker 1: Every business that's independently owned and operated is a little 160 00:10:13,880 --> 00:10:19,400 Speaker 1: bit of a pushback against central planning. So they prefer 161 00:10:20,440 --> 00:10:25,160 Speaker 1: that they just have Amazon and Google and these megacorporations 162 00:10:25,520 --> 00:10:28,120 Speaker 1: calling all the shots and making sure they go in 163 00:10:28,160 --> 00:10:31,400 Speaker 1: favor of the Democrats. And we're gonna be up against 164 00:10:31,400 --> 00:10:36,679 Speaker 1: an administration that has already shown us again, assuming that 165 00:10:36,720 --> 00:10:39,480 Speaker 1: this pathway continues, but we have to deal with the 166 00:10:39,520 --> 00:10:41,840 Speaker 1: path that is before us. We're going to have an 167 00:10:41,840 --> 00:10:47,360 Speaker 1: administration that is already compromised by China, our chief geopolitical rival. 168 00:10:47,679 --> 00:10:51,720 Speaker 1: They lied about Russia collusion with Trump and pretended that 169 00:10:51,800 --> 00:10:54,400 Speaker 1: Russia was a much greater threat than it was. But 170 00:10:54,559 --> 00:10:58,120 Speaker 1: in fact what they were saying about about Russia is 171 00:10:58,240 --> 00:11:03,360 Speaker 1: true of China. It has infiltrated our government apparatus, it 172 00:11:03,400 --> 00:11:07,480 Speaker 1: has been stealing our most sensitive information and secrets for years, 173 00:11:08,600 --> 00:11:12,240 Speaker 1: and it has compromised the would be first family very 174 00:11:12,280 --> 00:11:16,320 Speaker 1: directly and very obviously. So this is going to be 175 00:11:16,400 --> 00:11:20,160 Speaker 1: an enormous challenge. I hope that no matter what, President 176 00:11:20,200 --> 00:11:26,120 Speaker 1: Trump and all of his chief advisors and supporters will 177 00:11:26,120 --> 00:11:31,160 Speaker 1: come together and face this as one. But this is 178 00:11:31,160 --> 00:11:33,480 Speaker 1: where we are, the electoral College. It is now President 179 00:11:33,640 --> 00:11:36,800 Speaker 1: elect Biden as of now. I understand that you're going 180 00:11:36,840 --> 00:11:41,080 Speaker 1: to tell me it's a fraud, and I share your sentiment, 181 00:11:41,160 --> 00:11:45,720 Speaker 1: I share your outrage. But this is where we are now. 182 00:11:46,320 --> 00:11:48,840 Speaker 1: I've been saying, we trust the process. The process is 183 00:11:48,880 --> 00:11:51,960 Speaker 1: not over, but we are taking stock of this today. 184 00:11:52,160 --> 00:11:54,520 Speaker 1: We have our work cut out for us. Friends, We 185 00:11:54,600 --> 00:11:58,480 Speaker 1: have a Georgia election to win. We have judges that 186 00:11:58,520 --> 00:12:01,640 Speaker 1: should be getting at last minute here pushed through as 187 00:12:01,679 --> 00:12:03,800 Speaker 1: many federal judges as possible. I don't know what the 188 00:12:03,840 --> 00:12:07,480 Speaker 1: heck is going on with the Republicans thinking that they 189 00:12:07,720 --> 00:12:12,760 Speaker 1: can take it easy, and we have to start to 190 00:12:12,800 --> 00:12:18,000 Speaker 1: make the argument against what will be a bid administration 191 00:12:18,400 --> 00:12:22,520 Speaker 1: that has a lot of support from very powerful people. 192 00:12:23,200 --> 00:12:25,160 Speaker 1: And you will be told that what you know is 193 00:12:25,200 --> 00:12:28,439 Speaker 1: not true and what you know is and so you 194 00:12:28,559 --> 00:12:32,280 Speaker 1: got to relearn that part of it. Get ready for this. Friends, 195 00:12:32,880 --> 00:12:36,680 Speaker 1: we are in this together. We will eventually win. It's 196 00:12:36,679 --> 00:12:39,840 Speaker 1: just a question of when. Thanks for listening to The 197 00:12:39,920 --> 00:12:43,760 Speaker 1: Buck Sexton Show podcast. Get the latest news and information 198 00:12:43,840 --> 00:12:49,440 Speaker 1: from Buck by heading to Bucksexton dot com. Four years ago, 199 00:12:49,480 --> 00:12:50,959 Speaker 1: when I was a city and Vice president of the 200 00:12:51,000 --> 00:12:55,240 Speaker 1: United States, it was my responsibility to announce the tally 201 00:12:55,320 --> 00:12:58,800 Speaker 1: the Electric College votes the Joint Session of Congress and 202 00:12:59,000 --> 00:13:02,360 Speaker 1: voted to elect Don't Trump. I did my job, and 203 00:13:02,480 --> 00:13:05,200 Speaker 1: I'm pleased but not surprised. But the number of my 204 00:13:05,280 --> 00:13:09,040 Speaker 1: former Republican colleagues in the Senate who have acknowledged already 205 00:13:09,280 --> 00:13:13,040 Speaker 1: the results of the Electoral College, I thank them, and 206 00:13:13,200 --> 00:13:15,240 Speaker 1: I'm convinced we can work together for the good of 207 00:13:15,320 --> 00:13:18,840 Speaker 1: the nation on many subjects. That's the duty go to 208 00:13:18,880 --> 00:13:23,080 Speaker 1: the people, to our constitution, to our history. You know, 209 00:13:23,120 --> 00:13:27,040 Speaker 1: in this battle for the soul of America, democracy prevailed. 210 00:13:27,240 --> 00:13:31,480 Speaker 1: We the people voted, faith in our institutions held. The 211 00:13:31,559 --> 00:13:35,439 Speaker 1: integrity of our elections remains intact. And now it's time 212 00:13:35,600 --> 00:13:38,160 Speaker 1: to turn the page, as you've done throughout our history, 213 00:13:38,240 --> 00:13:41,520 Speaker 1: to unite to heal. Yeah, he sounds like he's in 214 00:13:41,559 --> 00:13:43,959 Speaker 1: great shape, doesn't he. Everything's gonna be just fine. It's 215 00:13:43,960 --> 00:13:46,680 Speaker 1: gonna be a great present. It's gonna be a great presidency, folks, 216 00:13:46,679 --> 00:13:49,840 Speaker 1: all all eighteen months or so of it, before he 217 00:13:49,880 --> 00:13:52,960 Speaker 1: decides he's had enough. Although you know, I will say 218 00:13:53,000 --> 00:13:55,080 Speaker 1: a lot of us underestimated. You know, I don't think 219 00:13:55,080 --> 00:14:00,360 Speaker 1: it's fair to say I underestimated Joe Biden. I underestimated 220 00:14:00,720 --> 00:14:05,840 Speaker 1: the Democrat willingness to put forward a clownish buffoon, but 221 00:14:06,280 --> 00:14:10,120 Speaker 1: to create a package of a Biden administration that they 222 00:14:10,120 --> 00:14:13,240 Speaker 1: were able to sell to enough people that they thought 223 00:14:13,240 --> 00:14:16,400 Speaker 1: this was gonna be much better. Look, the Trump't arrangement 224 00:14:16,520 --> 00:14:19,160 Speaker 1: syndrome that they spread all of the media, spread all 225 00:14:19,200 --> 00:14:23,120 Speaker 1: across the country. It certainly had an effect. I mean, 226 00:14:23,120 --> 00:14:25,160 Speaker 1: there were a lot a lot of people. The fact 227 00:14:25,200 --> 00:14:29,080 Speaker 1: that Joe Biden, let's say Joe Biden cheated just theoretically 228 00:14:29,120 --> 00:14:30,400 Speaker 1: though I don't want to anyone to fact check me 229 00:14:30,400 --> 00:14:32,560 Speaker 1: on this, but let's say Joe Biden had had his 230 00:14:32,640 --> 00:14:35,080 Speaker 1: team add a half a million votes to the tally. 231 00:14:35,680 --> 00:14:39,160 Speaker 1: The fact that this guy still got the eighty million 232 00:14:39,240 --> 00:14:44,400 Speaker 1: votes roughly that he is mind blowing, this clown, this 233 00:14:44,440 --> 00:14:47,840 Speaker 1: guy whose son is getting spare keys made for him 234 00:14:47,880 --> 00:14:50,440 Speaker 1: to open up the office where they're gonna be peddling 235 00:14:50,480 --> 00:14:53,960 Speaker 1: influence to the Chinese Communist Party when he's not, you know, 236 00:14:54,080 --> 00:14:57,120 Speaker 1: getting strippers knocked up and pretending he's not the dad 237 00:14:57,200 --> 00:14:59,840 Speaker 1: and doing all kinds of you know, I mean, come, 238 00:15:00,360 --> 00:15:04,840 Speaker 1: this guy, it's gonna be president. Maybe maybe I know 239 00:15:04,920 --> 00:15:07,600 Speaker 1: it's not until he's sworn in. I mean, folks, I 240 00:15:07,600 --> 00:15:10,160 Speaker 1: just want to know what will be the At what 241 00:15:10,320 --> 00:15:13,280 Speaker 1: point do you think that it's no longer an issue 242 00:15:13,280 --> 00:15:16,080 Speaker 1: of having a backbone for the fight to call in there? 243 00:15:16,720 --> 00:15:19,360 Speaker 1: Do we wait? I will ask some folks this because 244 00:15:19,360 --> 00:15:21,560 Speaker 1: I know today just by me saying, I'm trying to 245 00:15:21,560 --> 00:15:24,320 Speaker 1: take stock of where we are and be honest about this. 246 00:15:25,200 --> 00:15:26,640 Speaker 1: I know people are gonna email me and say that, 247 00:15:26,680 --> 00:15:28,160 Speaker 1: you know, I don't have enough stomach for the fight, 248 00:15:28,240 --> 00:15:30,920 Speaker 1: or something like that, and I just want to respond 249 00:15:30,920 --> 00:15:34,200 Speaker 1: to them what I've been saying. Fight every step of 250 00:15:34,200 --> 00:15:36,960 Speaker 1: the way. But at some point, you know, at some point, 251 00:15:36,960 --> 00:15:40,320 Speaker 1: we're the team that's staying behind on the field, at 252 00:15:40,400 --> 00:15:43,560 Speaker 1: least for this particular game, when the other team is left, 253 00:15:43,680 --> 00:15:46,000 Speaker 1: they're waving a trophy in the air, and the stands 254 00:15:46,000 --> 00:15:48,960 Speaker 1: have emptied out, and the lights, you know, the field 255 00:15:49,040 --> 00:15:52,760 Speaker 1: lights are getting turned off. It is it the inauguration day? 256 00:15:53,920 --> 00:15:56,080 Speaker 1: Do I think that there's going to be an opportunity 257 00:15:56,120 --> 00:16:01,000 Speaker 1: perhaps to bring action against Joe Biden and against some 258 00:16:01,080 --> 00:16:03,160 Speaker 1: of the other some of the Democrats who are involved 259 00:16:03,160 --> 00:16:05,920 Speaker 1: in Russia collusion, for example, based on the Durham probe. 260 00:16:06,280 --> 00:16:08,760 Speaker 1: I think it's possible. I wouldn't say it's likely at all. 261 00:16:09,560 --> 00:16:11,440 Speaker 1: I always tell you no one can predict the future. 262 00:16:11,520 --> 00:16:14,240 Speaker 1: Obviously not a lot of US conservatives can. I really 263 00:16:14,280 --> 00:16:17,600 Speaker 1: believed in my heart that Trump was gonna win, and yeah, 264 00:16:17,640 --> 00:16:19,720 Speaker 1: I think that if only legal ballots were countered, I 265 00:16:19,720 --> 00:16:22,280 Speaker 1: think that Trump did win. But I can't change this. 266 00:16:23,120 --> 00:16:25,720 Speaker 1: You can't change this. I mean, I wish that I 267 00:16:25,760 --> 00:16:28,560 Speaker 1: had the resources and the ability to go out there 268 00:16:28,600 --> 00:16:31,000 Speaker 1: and find all this fraud and piece it all together. 269 00:16:32,000 --> 00:16:34,240 Speaker 1: I'm willing to tell you though, the people that are 270 00:16:34,320 --> 00:16:37,000 Speaker 1: claiming that, don't worry. It's still in the bag. There's 271 00:16:37,000 --> 00:16:40,120 Speaker 1: the plan release the crack in. They're not being honest 272 00:16:40,120 --> 00:16:44,840 Speaker 1: with you. They're not being straight with you. The best, 273 00:16:44,920 --> 00:16:49,520 Speaker 1: the biggest earliest Trump supporters that I know, people that 274 00:16:49,520 --> 00:16:51,960 Speaker 1: I won't name because I've talked to them in confidence, 275 00:16:52,000 --> 00:16:54,520 Speaker 1: but the ones that I know, they'll say offline, yeah, look, 276 00:16:54,560 --> 00:16:56,320 Speaker 1: this is not it's not looking good. But we fight 277 00:16:56,400 --> 00:16:58,960 Speaker 1: this to the end. That's where I am. I'm telling you, 278 00:16:59,040 --> 00:17:03,040 Speaker 1: let's let's deal with what's ahead of us. Continue to 279 00:17:03,760 --> 00:17:09,720 Speaker 1: push see where this Antrim County audit, the forensic electronic 280 00:17:09,760 --> 00:17:15,200 Speaker 1: audit really goes, and understand that there's a lot. There's 281 00:17:15,240 --> 00:17:18,159 Speaker 1: a lot that we have here that we have to 282 00:17:18,240 --> 00:17:23,439 Speaker 1: focus on. And I am very concerned about the trajectory 283 00:17:23,480 --> 00:17:28,000 Speaker 1: of the US versus China under a possible Biden administration now, 284 00:17:29,080 --> 00:17:32,560 Speaker 1: but you know is this is something that we have 285 00:17:32,680 --> 00:17:36,040 Speaker 1: to regain our focus here pretty quickly because they're gonna 286 00:17:36,040 --> 00:17:38,760 Speaker 1: want to hit the ground running. We are weeks away 287 00:17:39,320 --> 00:17:42,200 Speaker 1: from an inauguration that the media is going to treat 288 00:17:42,240 --> 00:17:45,280 Speaker 1: as a total reset. And remember, our freedoms are under 289 00:17:45,320 --> 00:17:49,080 Speaker 1: assault because of COVID and ways that are unimaginable. We 290 00:17:49,200 --> 00:17:53,199 Speaker 1: have an enormous challenge ahead of us with the Chinese 291 00:17:53,240 --> 00:17:57,080 Speaker 1: Communist Party, and we've got a buffoon in Joe Biden 292 00:17:57,119 --> 00:17:59,120 Speaker 1: who's going to be the one calling the shots. If 293 00:17:59,160 --> 00:18:03,640 Speaker 1: this trend can continues, you're in the freedom hunt. This 294 00:18:03,760 --> 00:18:07,400 Speaker 1: is the Buck Sexton Show podcast from More Bucked. Head 295 00:18:07,440 --> 00:18:11,159 Speaker 1: to Bucksexton dot com and remember to subscribe to the podcast. 296 00:18:12,760 --> 00:18:17,000 Speaker 1: I mentioned the Michigan voting machine audit. I was going 297 00:18:17,080 --> 00:18:20,000 Speaker 1: to say that the President of the United States, Donald Trump, 298 00:18:20,080 --> 00:18:22,520 Speaker 1: was sharing this earlier today. This is what he thinks 299 00:18:22,600 --> 00:18:25,479 Speaker 1: is going on here, and we should at least follow 300 00:18:25,480 --> 00:18:29,120 Speaker 1: what the actual commander in chief is saying about all 301 00:18:29,119 --> 00:18:32,120 Speaker 1: of this. He wrote on Twitter at quote sixty eight 302 00:18:32,160 --> 00:18:35,320 Speaker 1: percent ararated Michigan voting machines should be by law a 303 00:18:35,400 --> 00:18:38,919 Speaker 1: tiny percentage of one percent? Did the Michigan Secretary of 304 00:18:38,960 --> 00:18:44,640 Speaker 1: State break the law? Stay tuned? And then tremendous problems 305 00:18:44,680 --> 00:18:47,880 Speaker 1: being found with voting machines. They are so far off 306 00:18:47,920 --> 00:18:51,399 Speaker 1: it is ridiculous able to take a landslide victory and 307 00:18:51,440 --> 00:18:54,280 Speaker 1: reduce it to a tight loss. This is not what 308 00:18:54,320 --> 00:18:59,080 Speaker 1: the usay is all about. Law enforcement shielding machines do 309 00:18:59,280 --> 00:19:03,760 Speaker 1: not tamper a crime. Much more to come? Okay, well 310 00:19:03,840 --> 00:19:05,760 Speaker 1: let's see what the much more to come is. As 311 00:19:05,840 --> 00:19:09,280 Speaker 1: as I've been telling you all along, I want more information, 312 00:19:09,320 --> 00:19:13,720 Speaker 1: I want more data, more evidence. There's no there is 313 00:19:13,760 --> 00:19:16,720 Speaker 1: no part of me that is saying, oh if we 314 00:19:16,760 --> 00:19:18,480 Speaker 1: find out right and think of there's almost like a 315 00:19:18,560 --> 00:19:22,479 Speaker 1: murder investigation, all right, you can you can know that 316 00:19:22,520 --> 00:19:25,239 Speaker 1: someone did the murder. You could know that someone did 317 00:19:25,280 --> 00:19:28,800 Speaker 1: the murder as a law enforcement person. But you can't 318 00:19:28,880 --> 00:19:32,440 Speaker 1: hold them while you're gathering all the evidence if you 319 00:19:32,600 --> 00:19:35,000 Speaker 1: if you have not yet you know, charged them with 320 00:19:35,040 --> 00:19:37,400 Speaker 1: the crime, right, you can't just hold them. You're like, well, 321 00:19:37,400 --> 00:19:40,040 Speaker 1: we think it's you, but we don't have the evidence 322 00:19:40,119 --> 00:19:42,760 Speaker 1: yet to go and get an arrest warrant, and we 323 00:19:42,960 --> 00:19:45,920 Speaker 1: don't have that, so we're just gonna hold you until 324 00:19:45,960 --> 00:19:48,080 Speaker 1: we find all of it. No, you got to release 325 00:19:48,119 --> 00:19:50,600 Speaker 1: the person, even if you know, even if you know 326 00:19:50,680 --> 00:19:53,280 Speaker 1: that they're probably guilty, but you don't have the proof yet. 327 00:19:53,960 --> 00:19:55,960 Speaker 1: You got to release them. That doesn't mean, though, you 328 00:19:56,000 --> 00:19:59,880 Speaker 1: can't come back to it later. So let's see, let's 329 00:20:00,000 --> 00:20:02,679 Speaker 1: see what we're able to pull together here. I've been 330 00:20:02,720 --> 00:20:06,560 Speaker 1: hearing from people who are not just the Trump legal team, 331 00:20:06,600 --> 00:20:10,000 Speaker 1: but are independently trying to assess and pull together all 332 00:20:10,040 --> 00:20:13,479 Speaker 1: the data. You know. Remember, it's one thing to show 333 00:20:14,440 --> 00:20:19,480 Speaker 1: that it's almost impossible statistically for Trump to have lost 334 00:20:19,480 --> 00:20:23,440 Speaker 1: in some of these places, but almost impossible without proof 335 00:20:23,520 --> 00:20:27,000 Speaker 1: of the intentional fraud. Is not going to be enough 336 00:20:27,040 --> 00:20:29,960 Speaker 1: to get a judge to say that there was cheating here. 337 00:20:30,840 --> 00:20:32,520 Speaker 1: And that's not the same thing as saying there was 338 00:20:32,600 --> 00:20:35,240 Speaker 1: no cheating, right, So this is what I'm trying to 339 00:20:35,960 --> 00:20:38,880 Speaker 1: I'm talking about the process and the system and trying 340 00:20:38,920 --> 00:20:42,879 Speaker 1: to make us all understand what's really happening, what's unfolding 341 00:20:42,920 --> 00:20:48,840 Speaker 1: before us right now. And it's infuriating, but it is 342 00:20:49,400 --> 00:20:52,600 Speaker 1: what it is. So Trump is saying that they found 343 00:20:52,640 --> 00:20:56,560 Speaker 1: these problems. We'll see what ends up happening. And as 344 00:20:56,600 --> 00:20:59,240 Speaker 1: I've also told you, affidavits not going to be enough, 345 00:21:00,119 --> 00:21:01,560 Speaker 1: not going to be enough. You and I can sit 346 00:21:01,640 --> 00:21:05,000 Speaker 1: here and have a conversation about how affidavits are these are. 347 00:21:05,240 --> 00:21:07,480 Speaker 1: Do I believe them? Yes? I do. Do I think 348 00:21:07,520 --> 00:21:11,000 Speaker 1: that these people are telling the truth. Yeah, But is 349 00:21:11,040 --> 00:21:14,480 Speaker 1: a judge going to say, well, this person saw a 350 00:21:14,600 --> 00:21:19,879 Speaker 1: thousand ballots that it's inexplicable how they all went for Biden. 351 00:21:20,840 --> 00:21:24,639 Speaker 1: But I'm going to invalidate then the hundred thousand ballots 352 00:21:24,640 --> 00:21:28,240 Speaker 1: that were counted that day at that election site. They're 353 00:21:28,280 --> 00:21:30,720 Speaker 1: not going to do that. The judge is not going 354 00:21:30,760 --> 00:21:33,720 Speaker 1: to do that. So, as I've been telling you, the 355 00:21:35,160 --> 00:21:39,000 Speaker 1: the affidavits are not enough. And look, I know if 356 00:21:39,040 --> 00:21:40,560 Speaker 1: I'm wrong about any of this, I'll come back and 357 00:21:40,600 --> 00:21:42,440 Speaker 1: I'll tell you that I'm wrong. I will tell you 358 00:21:42,480 --> 00:21:44,520 Speaker 1: there are people out there right now who are just 359 00:21:44,560 --> 00:21:47,479 Speaker 1: squabbling from the from the scraps or for the scraps 360 00:21:47,480 --> 00:21:51,040 Speaker 1: from the Trump train, and it's really just about them. 361 00:21:51,080 --> 00:21:54,440 Speaker 1: They don't there's no interest in then being honest with 362 00:21:54,480 --> 00:21:56,159 Speaker 1: people because they don't want they don't want to shoot 363 00:21:56,160 --> 00:21:59,399 Speaker 1: the messenger phenomenon to happen right now, you know. But 364 00:21:59,480 --> 00:22:03,800 Speaker 1: the Electoral College met yesterday and it is now, it 365 00:22:03,920 --> 00:22:06,640 Speaker 1: is now President elect Joe Biden. That's that's where we are. 366 00:22:07,920 --> 00:22:11,440 Speaker 1: And I spit out the words too, but I appreciate 367 00:22:11,520 --> 00:22:13,280 Speaker 1: that those of you who are joining me here understand 368 00:22:13,320 --> 00:22:16,600 Speaker 1: that we gotta face this. We gotta face it. We 369 00:22:16,640 --> 00:22:18,680 Speaker 1: can't hide from it, can't run from it. This is 370 00:22:18,720 --> 00:22:23,240 Speaker 1: what we're dealing with. And you also have the resignation 371 00:22:23,560 --> 00:22:28,600 Speaker 1: of Attorney General bar that occurred yesterday. And let me 372 00:22:28,640 --> 00:22:32,159 Speaker 1: say this, I have been a big proponent of the 373 00:22:32,160 --> 00:22:34,840 Speaker 1: Attorney General. I think that he's an excellent legal mind. 374 00:22:34,880 --> 00:22:37,320 Speaker 1: I think he's a good and ethical man, and I 375 00:22:37,400 --> 00:22:39,840 Speaker 1: understand there's a lot of frustration right now about both 376 00:22:39,840 --> 00:22:42,080 Speaker 1: the Durham probe and the election. A few things here. One, 377 00:22:43,320 --> 00:22:47,560 Speaker 1: he appointed Durham. Durham's a guy running that probe, and 378 00:22:47,960 --> 00:22:50,240 Speaker 1: you know, I don't there's no way for the Attorney 379 00:22:50,280 --> 00:22:52,679 Speaker 1: General that I'm aware of, to say you need to 380 00:22:52,680 --> 00:22:57,280 Speaker 1: speed this thing up. That could be considered undue interference, 381 00:22:57,320 --> 00:23:00,800 Speaker 1: that could be considered politicization. So he handed this off 382 00:23:00,840 --> 00:23:04,080 Speaker 1: to somebody who's supposed to be a very dogged and 383 00:23:04,200 --> 00:23:06,960 Speaker 1: thorough prosecutor. Well, I think a lot of people are 384 00:23:06,960 --> 00:23:11,600 Speaker 1: finding that its prosecutors are just lawyers. They're just lawyers. 385 00:23:11,359 --> 00:23:15,720 Speaker 1: There's not some you know, factory of superheroes somewhere that's 386 00:23:15,800 --> 00:23:18,880 Speaker 1: churning out great folks will then all become prosecutors, right, 387 00:23:18,880 --> 00:23:22,440 Speaker 1: there's bad prosecutors, good prosecutors, and so the Durham probe 388 00:23:23,160 --> 00:23:25,920 Speaker 1: is frustrating. But I also never really believe that they 389 00:23:25,960 --> 00:23:29,840 Speaker 1: would that they would hold to full account members of 390 00:23:29,880 --> 00:23:32,840 Speaker 1: the deep state. They're too powerful. There's there's too many 391 00:23:32,880 --> 00:23:38,960 Speaker 1: connections here among them. And then you have the frustration 392 00:23:39,240 --> 00:23:43,600 Speaker 1: over bar and the election, and I just he's not 393 00:23:43,640 --> 00:23:46,320 Speaker 1: a judge. And I know this is not maybe a 394 00:23:46,359 --> 00:23:48,760 Speaker 1: popular thing to say right now, but he's not a judge. 395 00:23:49,359 --> 00:23:52,600 Speaker 1: What is he supposed to do here? People who say 396 00:23:52,840 --> 00:23:56,720 Speaker 1: that the DOJ is not looking at these allegations, I 397 00:23:56,880 --> 00:23:59,840 Speaker 1: have it. I have it on very good authority that 398 00:24:00,160 --> 00:24:04,119 Speaker 1: they are looking at these allegations and they are presenting 399 00:24:04,560 --> 00:24:07,879 Speaker 1: they are presenting this information up the chain, and that 400 00:24:09,119 --> 00:24:12,879 Speaker 1: it's exactly what I've been saying. The Democrats removed the 401 00:24:13,000 --> 00:24:17,639 Speaker 1: safeguards to be able to prove the fraud so we 402 00:24:17,640 --> 00:24:19,920 Speaker 1: can keep running around. I understand there's this frustration people 403 00:24:19,920 --> 00:24:21,760 Speaker 1: are It's like they're banging on the wall here saying, 404 00:24:21,800 --> 00:24:24,359 Speaker 1: but there was fraud. I'm saying, I know, but you 405 00:24:24,480 --> 00:24:28,400 Speaker 1: have to be able to prove it or judges will 406 00:24:28,520 --> 00:24:31,160 Speaker 1: not do anything about it. This is where we are. 407 00:24:31,480 --> 00:24:35,520 Speaker 1: You know, if you had a burglary and and somebody 408 00:24:35,560 --> 00:24:38,919 Speaker 1: and somebody pulled all of the alarms and the and 409 00:24:38,960 --> 00:24:41,280 Speaker 1: the video cameras out of the room, and all of 410 00:24:41,320 --> 00:24:44,119 Speaker 1: a sudden, the you know, the diamond necklace is gone. 411 00:24:44,480 --> 00:24:46,480 Speaker 1: You can talk about how it was stolen, but if 412 00:24:46,520 --> 00:24:49,479 Speaker 1: you can't show any proof, no one's going to prison. 413 00:24:49,680 --> 00:24:52,400 Speaker 1: That's what I'm trying to tell you. And other people 414 00:24:52,440 --> 00:24:54,080 Speaker 1: aren't going to tell you that now, they're gonna say, Oh, 415 00:24:54,080 --> 00:24:55,960 Speaker 1: the kracking is just waiting on the sign the no, 416 00:24:56,119 --> 00:25:01,159 Speaker 1: it's not, it's not. I'm every bit as frustrated as 417 00:25:01,200 --> 00:25:03,119 Speaker 1: you are. I think the four years of a Trump 418 00:25:03,119 --> 00:25:06,639 Speaker 1: presidency was going to be four more years, was going 419 00:25:06,720 --> 00:25:08,560 Speaker 1: to be fantastic for us. We're gonna have a great 420 00:25:08,600 --> 00:25:14,199 Speaker 1: twenty twenty one booming economy. Maybe maybe we still get it. 421 00:25:14,240 --> 00:25:20,600 Speaker 1: But it's not looking good, not looking good at all. Now. A. G. 422 00:25:20,800 --> 00:25:24,440 Speaker 1: Barr resigned. This the last thing that the President said 423 00:25:24,440 --> 00:25:26,600 Speaker 1: about him. I think should be remembered here because there 424 00:25:26,600 --> 00:25:28,680 Speaker 1: are a lot of people that are trashing the attorney general. 425 00:25:29,119 --> 00:25:31,240 Speaker 1: And I think there are people who worked in the 426 00:25:31,240 --> 00:25:34,879 Speaker 1: Trump administration at a very senior level. I think there 427 00:25:35,160 --> 00:25:39,320 Speaker 1: are people who were completely incompetent, bad at their jobs 428 00:25:39,920 --> 00:25:42,800 Speaker 1: and deserve to be fired. I think James Comey obviously 429 00:25:42,840 --> 00:25:46,800 Speaker 1: deserved to be fired and sent to prison. But here's 430 00:25:46,800 --> 00:25:49,600 Speaker 1: what Donald Trump wrote yesterday about the Attorney general. Just 431 00:25:49,640 --> 00:25:51,640 Speaker 1: had a very nice meeting with Attorney General Bill Barr 432 00:25:51,640 --> 00:25:54,080 Speaker 1: at the White House. Our relationship has been a very 433 00:25:54,119 --> 00:25:57,160 Speaker 1: good one. He's done an outstanding job. As per letter, 434 00:25:57,160 --> 00:25:59,080 Speaker 1: Bill will be leaving just before Christmas to spend the 435 00:25:59,080 --> 00:26:02,480 Speaker 1: holidays with his family. So there's the President saying, look 436 00:26:02,520 --> 00:26:04,680 Speaker 1: I like this guy, and he's stepping down, and that's fine. 437 00:26:05,560 --> 00:26:08,679 Speaker 1: So let's not you know, he's not some deep state stuge. 438 00:26:08,800 --> 00:26:10,840 Speaker 1: He's not the enemy of the people or any of 439 00:26:10,840 --> 00:26:14,639 Speaker 1: this stuff. He probably just realized he's in an unwinnable situation. 440 00:26:16,000 --> 00:26:19,160 Speaker 1: He's just gonna get blamed for things by people who 441 00:26:19,560 --> 00:26:22,280 Speaker 1: understand that there was fraud in this election. But he 442 00:26:22,320 --> 00:26:24,280 Speaker 1: has not. You know, the Attorney General has not been 443 00:26:24,280 --> 00:26:26,919 Speaker 1: able to find enough of it, nor have they been 444 00:26:26,920 --> 00:26:28,879 Speaker 1: able to present evidence in a federal court of it 445 00:26:28,920 --> 00:26:31,480 Speaker 1: to change the result. So he's in a losing position 446 00:26:31,920 --> 00:26:34,000 Speaker 1: and he doesn't and he just figures, okay, look, have 447 00:26:34,119 --> 00:26:38,879 Speaker 1: someone else do this. I get it. It's a thankless, 448 00:26:38,880 --> 00:26:42,000 Speaker 1: a thankless role right now. And I just want to 449 00:26:42,000 --> 00:26:44,440 Speaker 1: everyone to be very clear. The president sent him. This 450 00:26:44,520 --> 00:26:48,080 Speaker 1: is like being you know, honorably discharged. President said nice 451 00:26:48,080 --> 00:26:49,640 Speaker 1: things about him on the way out. The president doesn't 452 00:26:49,640 --> 00:26:53,520 Speaker 1: always do that, as you know. So this is the 453 00:26:53,560 --> 00:26:55,680 Speaker 1: Attorney General saying, all right, I've done what I can. 454 00:26:55,840 --> 00:26:57,879 Speaker 1: Maybe there's somebody better who can step up and do this. 455 00:26:58,160 --> 00:27:00,320 Speaker 1: I'm gonna go home with my family for Christmas. That's 456 00:27:00,320 --> 00:27:02,600 Speaker 1: all it is. And I think the Attorney General did 457 00:27:02,600 --> 00:27:04,760 Speaker 1: a solid job. You freed, of course, disagree with me 458 00:27:04,800 --> 00:27:06,679 Speaker 1: on that, but I think that overall the Attorney General 459 00:27:07,119 --> 00:27:09,480 Speaker 1: was an ethical guy. And for those of you who 460 00:27:09,520 --> 00:27:10,800 Speaker 1: were going to really get mad at me, let me 461 00:27:10,840 --> 00:27:15,040 Speaker 1: just say Bill Barr was considered a stooge and a 462 00:27:15,119 --> 00:27:18,560 Speaker 1: hatchetman by the media of Trump until five minutes ago. 463 00:27:19,440 --> 00:27:23,920 Speaker 1: So something happened here. And it's not that the Attorney 464 00:27:23,960 --> 00:27:27,880 Speaker 1: General all of a sudden became some deep state operative, right, 465 00:27:27,880 --> 00:27:31,320 Speaker 1: That's not what happened. What happened is we've got a 466 00:27:31,400 --> 00:27:34,920 Speaker 1: very frustrating election result, and there's a lot of blame 467 00:27:34,960 --> 00:27:37,640 Speaker 1: going around right now, and including the people that don't 468 00:27:37,680 --> 00:27:41,399 Speaker 1: deserve it. You're in the freedom Hunt. This is the 469 00:27:41,480 --> 00:27:45,280 Speaker 1: Buck Sexton Show podcast. Get more from Buck by following 470 00:27:45,359 --> 00:27:48,760 Speaker 1: him on social media at buck Sexton on Facebook, Twitter, 471 00:27:48,800 --> 00:27:51,199 Speaker 1: and Instagram. Let me ask you, Governor. There was an 472 00:27:51,240 --> 00:27:54,280 Speaker 1: allegation made over the weekend on Twitter by a former 473 00:27:54,440 --> 00:27:57,840 Speaker 1: aid of yours who said that accused you of sexual 474 00:27:57,840 --> 00:28:00,360 Speaker 1: harassments that had happened over a period of year. I 475 00:28:00,400 --> 00:28:03,280 Speaker 1: wanted to get your reaction to that. Yeah, I heard 476 00:28:03,680 --> 00:28:09,800 Speaker 1: about the tweet, uh, and what it's said about comments 477 00:28:10,640 --> 00:28:17,120 Speaker 1: that I had made And it's not true, zach. Uh. Look, 478 00:28:17,160 --> 00:28:21,320 Speaker 1: I fought for and I believe a woman has the 479 00:28:21,400 --> 00:28:26,080 Speaker 1: right to come forward and express her opinion and express 480 00:28:26,160 --> 00:28:31,040 Speaker 1: issues and concerns that she has. But it's uh, it's 481 00:28:31,080 --> 00:28:33,680 Speaker 1: just not true. So he's calling her a liar. Can 482 00:28:33,760 --> 00:28:35,760 Speaker 1: we can we just all agree that that's what he 483 00:28:35,880 --> 00:28:39,680 Speaker 1: is saying, that she is a liar. And I would 484 00:28:39,680 --> 00:28:41,480 Speaker 1: just prefer it if he would come out and say 485 00:28:41,520 --> 00:28:46,160 Speaker 1: that instead of playing this game where you have him 486 00:28:46,160 --> 00:28:50,240 Speaker 1: say I I fought for a right to come forward 487 00:28:50,960 --> 00:28:55,080 Speaker 1: and you know, to say to things. But turns out 488 00:28:55,240 --> 00:28:58,720 Speaker 1: thought she's a big liar. Look, I don't think she's 489 00:28:58,760 --> 00:29:01,360 Speaker 1: lying at all, and it's I know that you could 490 00:29:01,360 --> 00:29:03,520 Speaker 1: say to me, oh, but Buck, that's because he's a 491 00:29:03,520 --> 00:29:05,200 Speaker 1: Democrat and you don't like him, and you think that 492 00:29:05,240 --> 00:29:07,600 Speaker 1: he's you know, King Cuomo and a maniac. I don't 493 00:29:07,600 --> 00:29:09,120 Speaker 1: like him, and I do think he's a maniac. And 494 00:29:09,160 --> 00:29:13,120 Speaker 1: it's terrifying that he might be a an attorney general 495 00:29:13,600 --> 00:29:16,120 Speaker 1: under a bid administration that's already been talked about. That 496 00:29:16,120 --> 00:29:20,320 Speaker 1: I find that deeply concerning. But I also am willing 497 00:29:20,320 --> 00:29:22,280 Speaker 1: to give you my honest assessment of these things. I 498 00:29:22,320 --> 00:29:25,440 Speaker 1: don't always think that these allegations, even there against Democrats 499 00:29:25,440 --> 00:29:28,520 Speaker 1: are true. They do tend to be true more often 500 00:29:28,600 --> 00:29:31,880 Speaker 1: against high profile Democrats than they are against high profile Republicans. 501 00:29:31,880 --> 00:29:35,720 Speaker 1: I'm gonna say that there you have noticed this, but 502 00:29:35,800 --> 00:29:39,120 Speaker 1: it's it's not an absolute. But Cuomo is a jerk. 503 00:29:39,880 --> 00:29:43,120 Speaker 1: And Cuomo is a guy who you can just tell. 504 00:29:43,280 --> 00:29:44,920 Speaker 1: You can tell that he thinks that he can get 505 00:29:44,920 --> 00:29:47,480 Speaker 1: away with stuff. He's known as a bully, he's known 506 00:29:47,480 --> 00:29:51,120 Speaker 1: as being vindictive. It's not a nice guy. So you 507 00:29:51,160 --> 00:29:55,240 Speaker 1: know when they accuse Kavanaugh, who is like, you know, 508 00:29:55,720 --> 00:29:58,560 Speaker 1: Ned Flanders went to Harvard Law School or something, or 509 00:29:58,640 --> 00:30:01,080 Speaker 1: Yale Law School. I forget which one. And it is 510 00:30:01,080 --> 00:30:05,080 Speaker 1: like this legal legal supermind who is coaching you know, 511 00:30:05,320 --> 00:30:08,280 Speaker 1: girls basketball on the weekend. Everybody loves him. They accuse 512 00:30:08,440 --> 00:30:11,960 Speaker 1: him of being a serial gang rapist, one of the ugliest, 513 00:30:12,000 --> 00:30:18,840 Speaker 1: most underhanded and disgraceful episodes in American politics in my lifetime. 514 00:30:19,280 --> 00:30:22,280 Speaker 1: And no intelligent person could really believe that those things 515 00:30:22,320 --> 00:30:24,719 Speaker 1: were true, but they wanted to believe it because they 516 00:30:24,760 --> 00:30:26,560 Speaker 1: wanted to stop him from being on the Supreme Court. 517 00:30:26,800 --> 00:30:29,200 Speaker 1: Look what we're seeing the Supreme Court. Even when you 518 00:30:29,240 --> 00:30:32,720 Speaker 1: put constitutionalists on the left. And I'm gonna say this, 519 00:30:32,760 --> 00:30:34,800 Speaker 1: and it's annoying, but you gotta know the truth. When 520 00:30:34,840 --> 00:30:37,440 Speaker 1: the left gets one of their judges on, they've got 521 00:30:37,520 --> 00:30:41,480 Speaker 1: somebody who plays for their team. When the right gets 522 00:30:41,520 --> 00:30:44,200 Speaker 1: one of their judges on, they've got somebody who adheres 523 00:30:44,280 --> 00:30:49,800 Speaker 1: to the constitution. You can see this the left, the 524 00:30:49,880 --> 00:30:54,040 Speaker 1: left does not disappoint their side. They get what they want. 525 00:30:54,080 --> 00:30:57,000 Speaker 1: That's what an activist judge means. That's their mandate, give 526 00:30:57,120 --> 00:31:00,520 Speaker 1: us what we want. Right, create a living constitution where 527 00:31:00,520 --> 00:31:03,239 Speaker 1: you just decide that you think this is better, and 528 00:31:03,280 --> 00:31:06,200 Speaker 1: the progressive should get their way. For the on the right, 529 00:31:06,480 --> 00:31:10,240 Speaker 1: constitutionalist judges they say, look, I don't like this policy 530 00:31:10,400 --> 00:31:12,400 Speaker 1: or I don't think this is a good idea, but 531 00:31:12,560 --> 00:31:15,200 Speaker 1: it is constitutional, so I can't do anything about it. 532 00:31:15,960 --> 00:31:18,120 Speaker 1: You just think of all think of big cases. That's 533 00:31:18,120 --> 00:31:22,320 Speaker 1: what keeps happening. But bring it back to Cuomo. So 534 00:31:22,360 --> 00:31:26,120 Speaker 1: they'll say that boy scout Cavanaugh is a bad guy, 535 00:31:26,480 --> 00:31:28,280 Speaker 1: and you know he's a rapist and all this stuff, 536 00:31:28,280 --> 00:31:31,400 Speaker 1: and it's just absurd and I'm never letting that go. That, 537 00:31:31,600 --> 00:31:36,160 Speaker 1: in some ways was almost as radicalizing and perhaps it 538 00:31:36,280 --> 00:31:39,280 Speaker 1: was as radicalizing a moment for many conservatives as the 539 00:31:39,400 --> 00:31:45,400 Speaker 1: Russia collusion lies about Trump, because it was so obviously 540 00:31:45,440 --> 00:31:50,080 Speaker 1: false and so vicious, and I'm never gonna forget it, 541 00:31:50,200 --> 00:31:53,440 Speaker 1: never gonna forgive it either. But then you have Cuomo. 542 00:31:53,600 --> 00:31:57,160 Speaker 1: Here's a guy who is a jerk and everyone knows it, 543 00:31:57,640 --> 00:32:00,640 Speaker 1: and he's powermad and I believe there was actually a 544 00:32:00,680 --> 00:32:03,160 Speaker 1: domestic disturbance at his house once when he was married, 545 00:32:03,160 --> 00:32:04,720 Speaker 1: and the police showed up, and that everyone had to 546 00:32:04,720 --> 00:32:07,600 Speaker 1: pretend it didn't happen. He shut down the Morelin Commission 547 00:32:07,640 --> 00:32:10,560 Speaker 1: in a corruption of him, just essentially by intimidating and 548 00:32:10,600 --> 00:32:15,120 Speaker 1: you know, scaring everybody is a bad guy. He's just 549 00:32:15,280 --> 00:32:23,360 Speaker 1: a bad guy, and now he's being accused of things that. Remember, 550 00:32:23,520 --> 00:32:25,840 Speaker 1: she didn't go overboard. She wasn't saying, oh, you know, 551 00:32:25,880 --> 00:32:27,920 Speaker 1: he drugged me and all this other stuff. I mean, 552 00:32:27,960 --> 00:32:29,600 Speaker 1: I mean, not that couldn't happen, but that would be 553 00:32:29,680 --> 00:32:31,720 Speaker 1: a bit of that would be a pretty extreme allegation. 554 00:32:32,040 --> 00:32:35,440 Speaker 1: She says that he said, you know, sexist comments and 555 00:32:35,520 --> 00:32:37,920 Speaker 1: talk about my appearance. And you know, if you look 556 00:32:37,920 --> 00:32:41,840 Speaker 1: at the woman in question, I find it very credible 557 00:32:41,880 --> 00:32:44,480 Speaker 1: that Cuomo would comment on her appearance. I don't think 558 00:32:44,520 --> 00:32:47,160 Speaker 1: that that's a stretch at all. And I'm just bringing 559 00:32:47,160 --> 00:32:51,160 Speaker 1: this up because get ready to kind of stay with 560 00:32:51,280 --> 00:32:56,320 Speaker 1: our prepare for the battle ahead mentality today. Get ready 561 00:32:56,520 --> 00:33:01,280 Speaker 1: for the double standards that we saw in the first 562 00:33:01,280 --> 00:33:05,240 Speaker 1: four years of Trump. Going forward under a Binden administration 563 00:33:05,480 --> 00:33:10,440 Speaker 1: will be just mind blowing. They won't have any standards, 564 00:33:10,440 --> 00:33:14,440 Speaker 1: accept double standards. They will just everything that they've said 565 00:33:14,440 --> 00:33:17,720 Speaker 1: in the past, whether it's about the grounds for impeachment, 566 00:33:17,960 --> 00:33:20,280 Speaker 1: whether it's about the Me Too movement, women have a right, 567 00:33:20,520 --> 00:33:24,920 Speaker 1: women have a right to be believed, was the That 568 00:33:25,160 --> 00:33:29,560 Speaker 1: was the line, that was the claim that was made whenever, 569 00:33:30,080 --> 00:33:33,160 Speaker 1: whether it was Trump or Kavanaugh, ay, any Republican was 570 00:33:33,200 --> 00:33:36,360 Speaker 1: accused of anything, and there were some people like Cosby 571 00:33:36,760 --> 00:33:42,760 Speaker 1: and Weinstein who weren't politicians but were I guess democrats. 572 00:33:42,800 --> 00:33:47,080 Speaker 1: Winstein's clearly a Democrat who were guilty. And so yeah, 573 00:33:47,120 --> 00:33:49,000 Speaker 1: those women did have a right to believed because they 574 00:33:49,000 --> 00:33:52,640 Speaker 1: were telling the truth. But now all of a sudden, 575 00:33:52,680 --> 00:33:56,040 Speaker 1: when it's Cuomo, they're gonna they're gonna avoid talking about 576 00:33:56,040 --> 00:33:58,000 Speaker 1: this story and they're gonna take his word for it, 577 00:33:58,160 --> 00:34:00,120 Speaker 1: and they'll let him get away with the formulation that 578 00:34:00,160 --> 00:34:02,560 Speaker 1: he gave you there where he's just saying, oh, yes, 579 00:34:02,640 --> 00:34:05,400 Speaker 1: she has a right to come forward. Well, what does 580 00:34:05,440 --> 00:34:07,880 Speaker 1: that mean. We were told that she has a right 581 00:34:07,920 --> 00:34:10,640 Speaker 1: to be believed. Hillary Clinton said about women coming forward 582 00:34:10,640 --> 00:34:12,840 Speaker 1: with allegations, they have a right to be believed. And 583 00:34:13,160 --> 00:34:16,279 Speaker 1: now we when there's a Democrat he's in trouble, all 584 00:34:16,280 --> 00:34:18,920 Speaker 1: of a sudden, now we have a Oh, I don't know, 585 00:34:19,120 --> 00:34:21,680 Speaker 1: I don't know if we can really take that seriously anymore. 586 00:34:21,719 --> 00:34:27,480 Speaker 1: That's standard that we were using to try to eviscerate Republicans. 587 00:34:27,960 --> 00:34:31,120 Speaker 1: Maybe we need to be a little more thoughtful about 588 00:34:31,120 --> 00:34:32,680 Speaker 1: how we do this. Maybe we need to be a 589 00:34:32,719 --> 00:34:38,680 Speaker 1: little more evidentiary in the way that we approached these things, 590 00:34:38,760 --> 00:34:42,960 Speaker 1: and I sit here saying wow, no, no, no, duh, 591 00:34:43,000 --> 00:34:48,040 Speaker 1: no surprise, huh. And Cuomo is going to get away 592 00:34:48,080 --> 00:34:52,040 Speaker 1: with this. There will be no consequences from whatsoever Democrat 593 00:34:52,080 --> 00:34:54,040 Speaker 1: voters in New York State where I am, at least 594 00:34:54,040 --> 00:34:56,319 Speaker 1: for now, I don't know what it's going to take 595 00:34:56,400 --> 00:34:59,560 Speaker 1: them to realize this guy's a nightmare. I don't know. 596 00:34:59,600 --> 00:35:01,439 Speaker 1: I mean, you'd think that at this point they would 597 00:35:01,440 --> 00:35:04,080 Speaker 1: have figured it out, and they want anybody but him. 598 00:35:04,160 --> 00:35:07,120 Speaker 1: The media loves this guy. They love him so he 599 00:35:07,160 --> 00:35:09,359 Speaker 1: can get away with anything. And he's about to get 600 00:35:09,400 --> 00:35:12,479 Speaker 1: away with these sexual sexual harassment allegations. That's for sure. 601 00:35:14,200 --> 00:35:16,960 Speaker 1: You're in the freedom Hunt. This is the buck Sexton 602 00:35:17,040 --> 00:35:20,799 Speaker 1: Show podcast from more buck Head to buck sexton dot 603 00:35:20,800 --> 00:35:24,880 Speaker 1: com and remember to subscribe to the podcast. What are 604 00:35:24,920 --> 00:35:28,200 Speaker 1: we really seeing when it comes to the results of 605 00:35:28,200 --> 00:35:31,640 Speaker 1: these lockdowns and what has the data told us so 606 00:35:31,680 --> 00:35:34,799 Speaker 1: far about so many of these expert predictions when it 607 00:35:34,800 --> 00:35:37,440 Speaker 1: comes to COVID nineteen and how we're supposed to handle it. 608 00:35:38,120 --> 00:35:41,120 Speaker 1: We're joined out by Phil Kirpin. He's a syndicated columnist 609 00:35:41,560 --> 00:35:46,400 Speaker 1: and also the president of American Commitment. Phil Thanks for 610 00:35:46,400 --> 00:35:48,920 Speaker 1: making the time great to be with you. Let's talk 611 00:35:48,920 --> 00:35:53,279 Speaker 1: about schools first. What is the data tell us about 612 00:35:53,280 --> 00:35:57,440 Speaker 1: school lockdowns at this stage, or I should just say 613 00:35:57,440 --> 00:36:00,480 Speaker 1: school closures, it's not even really lockdowns. Closing school and 614 00:36:00,640 --> 00:36:06,880 Speaker 1: doing only virtual learning probably the single biggest policy mistake 615 00:36:07,120 --> 00:36:09,239 Speaker 1: of the entire year, which is hanging a lot because 616 00:36:09,239 --> 00:36:11,960 Speaker 1: we've had a lot of policy mistakes. It's interesting, the 617 00:36:11,960 --> 00:36:15,319 Speaker 1: original CDC guidance on schools was really balanced, and I 618 00:36:15,320 --> 00:36:17,799 Speaker 1: think anyone who actually read it and paid attention would 619 00:36:17,800 --> 00:36:20,200 Speaker 1: not have closed schools. And yet we had sort of 620 00:36:20,200 --> 00:36:22,759 Speaker 1: this panic contagion that swept the whole country and all 621 00:36:22,800 --> 00:36:24,600 Speaker 1: the schools were closed, and a lot of them never 622 00:36:24,640 --> 00:36:29,239 Speaker 1: reopened or opened on very limited part time schedules. And 623 00:36:29,320 --> 00:36:30,960 Speaker 1: it's interesting. There was a study in the Journal of 624 00:36:31,000 --> 00:36:33,480 Speaker 1: the American Medical Association a couple of weeks ago. They 625 00:36:33,480 --> 00:36:36,560 Speaker 1: looked at just the impact of elementary school closures and 626 00:36:36,680 --> 00:36:39,680 Speaker 1: just for two months in the spring, and they calculated 627 00:36:39,760 --> 00:36:44,319 Speaker 1: five million years of life lost from two months of 628 00:36:44,400 --> 00:36:47,120 Speaker 1: elementary school closures, which is probably more years of life 629 00:36:47,120 --> 00:36:50,799 Speaker 1: lost than we're going to have from the coronavirus. There's 630 00:36:50,840 --> 00:36:55,640 Speaker 1: a very strong relationship between educational attainment and not just income, 631 00:36:56,200 --> 00:36:59,080 Speaker 1: but life expectancy as well. The difference between a high 632 00:36:59,120 --> 00:37:02,080 Speaker 1: school graduate and high school dropout, on average is about 633 00:37:02,120 --> 00:37:06,600 Speaker 1: five years of life expectancy. The online learning is not 634 00:37:06,719 --> 00:37:09,040 Speaker 1: working for a lot of people. For some kids, it's fine, 635 00:37:09,960 --> 00:37:11,759 Speaker 1: some of them are doing okay, but a lot of 636 00:37:11,840 --> 00:37:14,040 Speaker 1: kids are failing. A lot more kids than ever failed 637 00:37:14,760 --> 00:37:19,680 Speaker 1: with traditional school, and that has major long term consequences, 638 00:37:19,719 --> 00:37:24,200 Speaker 1: both economic and health consequences. And so we're essentially imposing 639 00:37:24,400 --> 00:37:30,080 Speaker 1: enormous harms and enormous enormous costs on children societally, even 640 00:37:30,120 --> 00:37:33,880 Speaker 1: though children are atists near zero risks, certainly much lower 641 00:37:34,000 --> 00:37:37,040 Speaker 1: risk with coronavirus than they are from seasonal flu, which 642 00:37:37,120 --> 00:37:40,880 Speaker 1: is five to ten times more deadly for children than coronavirus, 643 00:37:41,239 --> 00:37:43,239 Speaker 1: and that we tolerate and that we think is a 644 00:37:43,320 --> 00:37:46,440 Speaker 1: perfectly acceptable low level of risk. And so children have 645 00:37:46,560 --> 00:37:51,680 Speaker 1: really been the biggest losers in our policy response to COVID. 646 00:37:51,760 --> 00:37:57,200 Speaker 1: It feels increasingly feel like the elimination of any tolerable 647 00:37:57,320 --> 00:37:59,759 Speaker 1: risk when it comes to COVID has been at the 648 00:37:59,760 --> 00:38:02,920 Speaker 1: same of a lot of the policies that we see 649 00:38:03,239 --> 00:38:06,840 Speaker 1: and restaurants in New York City have just been closed 650 00:38:06,880 --> 00:38:10,120 Speaker 1: as of this week. Contact racing shown that they were 651 00:38:10,200 --> 00:38:14,719 Speaker 1: responsible for they believe about one percent of the spread. 652 00:38:15,160 --> 00:38:18,400 Speaker 1: So what are what have we learned about? Where is 653 00:38:18,440 --> 00:38:21,239 Speaker 1: the virus spreading in New York And it's and it's 654 00:38:21,320 --> 00:38:23,680 Speaker 1: environs because that's a that's also a good proxy for 655 00:38:23,680 --> 00:38:26,319 Speaker 1: where it would be spreading in other densely populated parts 656 00:38:26,360 --> 00:38:29,840 Speaker 1: of the country. Well, the data the New York published, 657 00:38:29,880 --> 00:38:32,319 Speaker 1: and it's interesting because they published you know, very very 658 00:38:32,360 --> 00:38:34,960 Speaker 1: similar data back in May and then ignored it, and 659 00:38:35,000 --> 00:38:38,000 Speaker 1: now they're finding the same thing again, which is almost 660 00:38:38,000 --> 00:38:41,000 Speaker 1: all of the spread is inside of homes, inside of households. 661 00:38:41,080 --> 00:38:43,919 Speaker 1: And you know, New York of course has a lot 662 00:38:44,040 --> 00:38:47,239 Speaker 1: of high density residential, a lot of multi family, you know, 663 00:38:47,280 --> 00:38:50,520 Speaker 1: apartment buildings, and so you know, maybe a little bit 664 00:38:50,520 --> 00:38:53,400 Speaker 1: different there and some other places, but by and large, 665 00:38:53,600 --> 00:38:55,960 Speaker 1: I think it's now pretty clear from the contact tracing 666 00:38:55,960 --> 00:38:59,279 Speaker 1: we've seen all over the country that there's not a 667 00:38:59,280 --> 00:39:02,120 Speaker 1: lot of spread places like restaurants and retail and so 668 00:39:02,160 --> 00:39:05,399 Speaker 1: for the spread tends to happen sort of the one 669 00:39:05,440 --> 00:39:08,759 Speaker 1: to one person to person spread tends to happen inside 670 00:39:08,760 --> 00:39:10,960 Speaker 1: of homes. Now we also have this other problem of 671 00:39:11,320 --> 00:39:14,080 Speaker 1: these occasional sort of super spread or events which are 672 00:39:14,120 --> 00:39:17,400 Speaker 1: hard to predict, and we still don't really know why 673 00:39:17,560 --> 00:39:20,359 Speaker 1: some small percentage of people with this virus and it's 674 00:39:20,400 --> 00:39:23,040 Speaker 1: only maybe ten percent something like that seemed to be 675 00:39:23,080 --> 00:39:25,920 Speaker 1: responsible for, you know, a lot of the spread. And 676 00:39:25,960 --> 00:39:27,959 Speaker 1: so you know, if you got on the average person 677 00:39:28,080 --> 00:39:31,440 Speaker 1: gets this virus infects zero or one other people, and 678 00:39:31,600 --> 00:39:33,680 Speaker 1: then but then you've got this small group that affects 679 00:39:33,719 --> 00:39:35,720 Speaker 1: tons of people, and you know, we still don't really 680 00:39:35,760 --> 00:39:38,919 Speaker 1: know what makes them different and why they tend to 681 00:39:38,960 --> 00:39:41,720 Speaker 1: infect lots of people. And I wish with more research 682 00:39:41,840 --> 00:39:44,680 Speaker 1: we're going into that because that would be very useful 683 00:39:44,680 --> 00:39:47,080 Speaker 1: to sort of identify and be able to predict what 684 00:39:47,160 --> 00:39:51,040 Speaker 1: those characteristics are. But by and large, what we saw 685 00:39:51,040 --> 00:39:52,600 Speaker 1: in the New York did, and it was remarkable because 686 00:39:52,640 --> 00:39:55,040 Speaker 1: Governor Cuomo came out and he said, look, here's the data. 687 00:39:55,160 --> 00:39:57,920 Speaker 1: Seventy five percent of transmission is in homes, one percent 688 00:39:58,040 --> 00:40:01,960 Speaker 1: is in restaurants. So I'm closing us. And you know, 689 00:40:02,000 --> 00:40:03,759 Speaker 1: then he said, well, you know, because it's something we 690 00:40:03,800 --> 00:40:05,640 Speaker 1: can do. You know, we can't close homes, we can 691 00:40:05,760 --> 00:40:08,920 Speaker 1: close restaurants. But of course, just because you can do something, 692 00:40:09,000 --> 00:40:11,719 Speaker 1: doesn't mean that it's actually you know, he said, you know, 693 00:40:11,760 --> 00:40:13,840 Speaker 1: it's only a small difference, but it's something we can do. 694 00:40:14,080 --> 00:40:16,080 Speaker 1: You know, but if you look at the data, but 695 00:40:16,440 --> 00:40:19,480 Speaker 1: it's more likely to be a negative difference than a 696 00:40:19,520 --> 00:40:22,200 Speaker 1: positive difference, because if you say, you know, we're going 697 00:40:22,239 --> 00:40:25,759 Speaker 1: to push gatherings and holiday gatherings and dinners and all 698 00:40:25,760 --> 00:40:28,000 Speaker 1: this kind of stuff out of restaurants where people are 699 00:40:28,000 --> 00:40:31,080 Speaker 1: being very strict with their distancing and their hygiene and 700 00:40:31,120 --> 00:40:33,520 Speaker 1: all this stuff, we're gonna push them out. We're gonna close. 701 00:40:33,719 --> 00:40:35,920 Speaker 1: Now they're gonna take place in homes instead. You know, 702 00:40:35,960 --> 00:40:37,520 Speaker 1: some of them won't take place at all, but a 703 00:40:37,560 --> 00:40:40,560 Speaker 1: lot of them will take place in homes instead without 704 00:40:40,560 --> 00:40:43,440 Speaker 1: any of those precautions. And so in my judgment, the 705 00:40:43,760 --> 00:40:47,680 Speaker 1: restaurant closure is not only economically devastating, but it's more 706 00:40:47,719 --> 00:40:50,799 Speaker 1: likely to increase transmission than to decrease it because people 707 00:40:50,800 --> 00:40:53,239 Speaker 1: are going to meet in home settings instead. Well, this 708 00:40:53,320 --> 00:40:56,400 Speaker 1: was a concern also last winter or late late in 709 00:40:56,440 --> 00:40:59,520 Speaker 1: the winter, when we recognize that New York City was 710 00:40:59,560 --> 00:41:03,239 Speaker 1: facing this first big wave of COVID cases. They went 711 00:41:03,280 --> 00:41:06,920 Speaker 1: into the fifteen days to stop the spread, and the 712 00:41:06,960 --> 00:41:09,319 Speaker 1: stay at home orders, and a lot of people are saying, well, 713 00:41:09,360 --> 00:41:12,279 Speaker 1: hold on a second, We've had this virus is all 714 00:41:12,280 --> 00:41:14,920 Speaker 1: over the place already, and now what you're going to 715 00:41:14,960 --> 00:41:17,320 Speaker 1: be doing by shutting down the schools, shutting down anywhere 716 00:41:17,320 --> 00:41:19,840 Speaker 1: for people to places for people to go, is you 717 00:41:19,920 --> 00:41:24,720 Speaker 1: might actually be forcing And you mentioned multigenerational, multi family homes, 718 00:41:24,800 --> 00:41:27,839 Speaker 1: dense housing, which is all over New York City where 719 00:41:27,840 --> 00:41:31,400 Speaker 1: people it's very difficult to really stay far away from others. 720 00:41:31,760 --> 00:41:34,040 Speaker 1: It may have effectively sent everyone home to infect their 721 00:41:34,040 --> 00:41:37,960 Speaker 1: family members inadvertently, but that was always a concern. Yeah, 722 00:41:38,040 --> 00:41:40,759 Speaker 1: I think that that almost certainly was a big part 723 00:41:40,800 --> 00:41:43,120 Speaker 1: of what happened in New York back in the spring. Now, 724 00:41:43,120 --> 00:41:45,279 Speaker 1: the good thing you've got going for you now in 725 00:41:45,400 --> 00:41:48,440 Speaker 1: New York is, you know, so many people have already 726 00:41:48,440 --> 00:41:50,960 Speaker 1: had it. You have a very high level of community immunity, 727 00:41:51,000 --> 00:41:53,239 Speaker 1: probably higher than anywhere else in the United States. And 728 00:41:53,280 --> 00:41:55,800 Speaker 1: so if you look at the New York state numbers, 729 00:41:56,040 --> 00:41:58,480 Speaker 1: it's now mostly outside of the New York City area 730 00:41:58,520 --> 00:41:59,920 Speaker 1: and sort of the rest of the state is kind 731 00:41:59,920 --> 00:42:03,640 Speaker 1: of catching up New York City. If you look at 732 00:42:03,640 --> 00:42:07,360 Speaker 1: the hospital utilization in the emergency room data, you've actually 733 00:42:07,400 --> 00:42:12,239 Speaker 1: got lower emergency room visits for respiratory illnesses and influenza 734 00:42:12,280 --> 00:42:15,760 Speaker 1: like illness now than you know, any of the previous 735 00:42:15,800 --> 00:42:18,600 Speaker 1: five years this time of year. So you're actually lower 736 00:42:18,640 --> 00:42:22,120 Speaker 1: than normal in New York City, I think because you've 737 00:42:22,120 --> 00:42:24,800 Speaker 1: got a lot of community immunity to COVID and because 738 00:42:24,800 --> 00:42:27,160 Speaker 1: the other factor, which is happening everywhere in the world 739 00:42:27,280 --> 00:42:31,160 Speaker 1: right now with very little attention paid to it. There's 740 00:42:31,200 --> 00:42:33,799 Speaker 1: almost no flu activity this year. And we don't know 741 00:42:33,840 --> 00:42:37,040 Speaker 1: if that's because the you know, the policy measures like 742 00:42:37,120 --> 00:42:40,160 Speaker 1: the masks and the distancing and school closures are somehow 743 00:42:40,200 --> 00:42:42,759 Speaker 1: more effective for flu than they are for COVID, or 744 00:42:42,800 --> 00:42:45,719 Speaker 1: if the virus itself has somehow disrupted. We don't really 745 00:42:45,719 --> 00:42:48,720 Speaker 1: know why it's the case, but it's a remarkable story 746 00:42:48,760 --> 00:42:50,920 Speaker 1: because remember the experts that we're gonna have this twindemic 747 00:42:50,920 --> 00:42:52,680 Speaker 1: flu is going to hit at the same time as COVID, 748 00:42:52,880 --> 00:42:55,600 Speaker 1: all the hospital is gonna be overwhelmed. Instead, we've got 749 00:42:55,920 --> 00:42:58,920 Speaker 1: you know, the mildest flu season since at least twenty fifteen, 750 00:42:59,000 --> 00:43:01,160 Speaker 1: and maybe you know, see if it doesn't take off 751 00:43:01,160 --> 00:43:04,279 Speaker 1: at all, maybe the mildest flue season on records. So 752 00:43:04,320 --> 00:43:08,000 Speaker 1: you've got you know, really under utilization of hospitals in 753 00:43:08,040 --> 00:43:10,240 Speaker 1: a place like New York City that has relatively little 754 00:43:10,360 --> 00:43:13,360 Speaker 1: COVID activity because we're not saying any fluid. I pulled 755 00:43:13,440 --> 00:43:16,520 Speaker 1: some numbers last week. I'm glad you brought that up. Phil. 756 00:43:16,520 --> 00:43:21,000 Speaker 1: I'm speaking of Phili Kirpin, syndicated columnist, journalist, and at Phil, 757 00:43:21,520 --> 00:43:24,640 Speaker 1: I looked at the initial Now, now I had someone, right, 758 00:43:24,680 --> 00:43:27,560 Speaker 1: I've had people right into me since to say, we're 759 00:43:27,600 --> 00:43:31,000 Speaker 1: not really testing for flu the way that we normally do. 760 00:43:31,080 --> 00:43:33,160 Speaker 1: And to that, I say, okay, because I am asking. 761 00:43:33,200 --> 00:43:34,880 Speaker 1: You know, so sometimes people are asking a question and 762 00:43:34,920 --> 00:43:37,600 Speaker 1: they're really trying to push a conclusion. I'm actually asking 763 00:43:37,600 --> 00:43:41,200 Speaker 1: the question. But I pose to the audience. I said, 764 00:43:41,920 --> 00:43:44,680 Speaker 1: you know, the initial data on the CDC website for 765 00:43:44,719 --> 00:43:47,880 Speaker 1: the first week of December, and and I think it 766 00:43:47,960 --> 00:43:49,920 Speaker 1: was it was low for what they actually had for COVID. 767 00:43:49,960 --> 00:43:51,920 Speaker 1: So this was initial data. So the numbers are clearly 768 00:43:51,960 --> 00:43:53,919 Speaker 1: going to go up, and you know, maybe it went 769 00:43:53,960 --> 00:43:56,160 Speaker 1: from you know, maybe I might even go up by 770 00:43:56,160 --> 00:43:57,880 Speaker 1: a factor of ten, let's say, right, I mean, it 771 00:43:57,880 --> 00:44:00,359 Speaker 1: could go up substantially, But the initial data said that 772 00:44:00,440 --> 00:44:05,480 Speaker 1: they had something like two thousand plus COVID debts in 773 00:44:05,520 --> 00:44:08,360 Speaker 1: the first week of December that we're officially COVID, you know, 774 00:44:08,400 --> 00:44:12,879 Speaker 1: meaning that this is what they had three three from 775 00:44:12,960 --> 00:44:17,040 Speaker 1: the flu. Now I can understand more COVID I could 776 00:44:17,120 --> 00:44:20,399 Speaker 1: under but there's clearly something going on here. I mean, 777 00:44:20,440 --> 00:44:23,960 Speaker 1: you mentioned some of the possibilities. There's no way that 778 00:44:24,120 --> 00:44:27,400 Speaker 1: you have almost a factor of a thousand more COVID 779 00:44:27,480 --> 00:44:29,919 Speaker 1: debts than you do flu debts given what we would 780 00:44:29,960 --> 00:44:33,279 Speaker 1: see in a normal flu season. That's not possible. Well, 781 00:44:34,239 --> 00:44:38,440 Speaker 1: you know, flue peaks are more often in January February 782 00:44:38,520 --> 00:44:40,560 Speaker 1: than they are in November and December time. Sometimes you 783 00:44:40,600 --> 00:44:43,480 Speaker 1: have in earlier flu seasons. So you know a lot 784 00:44:43,520 --> 00:44:45,279 Speaker 1: of people say, well, you know flu's not here yet, 785 00:44:45,320 --> 00:44:48,239 Speaker 1: it's still coming. That might be true, but we've never 786 00:44:48,280 --> 00:44:50,960 Speaker 1: seen levels this low. We've never seen levels this low. 787 00:44:50,960 --> 00:44:53,640 Speaker 1: And if you look at the CDC flu testing data, 788 00:44:54,200 --> 00:44:59,640 Speaker 1: it's down about ninety almost one hundred percent some weeks, 789 00:44:59,640 --> 00:45:01,759 Speaker 1: and we've at like ninety eight percent reduction from the 790 00:45:01,760 --> 00:45:04,840 Speaker 1: five year average. And it's not that we're not testing. 791 00:45:04,920 --> 00:45:08,920 Speaker 1: The flu tests are actually higher than the five year average, 792 00:45:08,920 --> 00:45:11,520 Speaker 1: and they're actually at a record high. At the number 793 00:45:11,520 --> 00:45:13,760 Speaker 1: of flu tests at the CDC tracks and the CDC 794 00:45:13,880 --> 00:45:16,719 Speaker 1: only tracks clinical labs and public health labs, so they 795 00:45:16,719 --> 00:45:18,840 Speaker 1: don't track you know, like the rapid tests in the 796 00:45:18,920 --> 00:45:21,200 Speaker 1: doctor's office. That's not in the stats, so they only 797 00:45:21,200 --> 00:45:23,160 Speaker 1: have thousands of tests. They don't have millions of tests. 798 00:45:23,840 --> 00:45:27,160 Speaker 1: But it's still it indicates that I think one of 799 00:45:27,200 --> 00:45:32,200 Speaker 1: three things is going on. Buck Either, we've got the 800 00:45:32,280 --> 00:45:35,160 Speaker 1: public health measures that are being implemented for some reason 801 00:45:35,200 --> 00:45:37,520 Speaker 1: are very effective at stopping flu, even though they don't 802 00:45:37,520 --> 00:45:41,000 Speaker 1: seem to be. They're not effective. It's stopping covid right right, 803 00:45:41,080 --> 00:45:42,719 Speaker 1: So that's a little hard to believe, although a lot 804 00:45:42,760 --> 00:45:45,520 Speaker 1: of people have been saying that or somehow the covid 805 00:45:45,640 --> 00:45:49,000 Speaker 1: virus itself disrupts the flu virus, which is possible. There's 806 00:45:49,000 --> 00:45:52,440 Speaker 1: a phenomenon called viral interference, and this was actually how 807 00:45:52,440 --> 00:45:54,560 Speaker 1: swine flu ended back in two thousand and nine. The 808 00:45:54,640 --> 00:45:57,439 Speaker 1: rhinovirus came in and it's sort of just knocked it out, 809 00:45:57,480 --> 00:45:59,840 Speaker 1: you know, people got that instead, and it's sort of 810 00:46:00,040 --> 00:46:01,560 Speaker 1: locked it out. And there was some hope. There was 811 00:46:01,600 --> 00:46:04,080 Speaker 1: actually an article, you know, months ago, hoping that flu 812 00:46:04,160 --> 00:46:06,960 Speaker 1: season would come in and sort of disrupt covid that 813 00:46:07,040 --> 00:46:09,720 Speaker 1: definitely didn't happen, but maybe the opposite happened. Maybe COVID 814 00:46:09,760 --> 00:46:12,520 Speaker 1: disrupted flu, and you know, once you get COVID, your 815 00:46:12,960 --> 00:46:16,960 Speaker 1: mucus build up blocks flu, or some mechanism causes viral interference. 816 00:46:17,320 --> 00:46:19,719 Speaker 1: Or the third possibility is that we've got some sort 817 00:46:19,719 --> 00:46:22,960 Speaker 1: of a data artifact where maybe you know, we're get 818 00:46:23,000 --> 00:46:25,439 Speaker 1: so many false positives for COVID that people get flu, 819 00:46:25,520 --> 00:46:28,040 Speaker 1: they test false positive, it goes into the stats as 820 00:46:28,080 --> 00:46:32,399 Speaker 1: of COVID case instead of a flu case. Maybe there's 821 00:46:32,400 --> 00:46:34,440 Speaker 1: a timing issue where even though we have lots of 822 00:46:34,440 --> 00:46:37,200 Speaker 1: flu tests, people are only taking the flu test after 823 00:46:37,280 --> 00:46:39,399 Speaker 1: they get a negative COVID test back, and by then 824 00:46:39,520 --> 00:46:42,680 Speaker 1: flu is not detectable anymore. Some people have suggested that, 825 00:46:42,719 --> 00:46:46,160 Speaker 1: so they're basically there are three possibilities, in my judgment, 826 00:46:46,200 --> 00:46:51,000 Speaker 1: Either the policies are actually stopping flu somehow there's actual 827 00:46:51,160 --> 00:46:53,479 Speaker 1: viral interference, or we've got some sort of a data 828 00:46:53,560 --> 00:46:55,799 Speaker 1: artifact based on the sequence and the way that we're 829 00:46:55,840 --> 00:46:58,759 Speaker 1: doing the testing that's causing the flu cases to be 830 00:46:58,920 --> 00:47:01,319 Speaker 1: mischaracterized as COVID. So it's got to be one of 831 00:47:01,320 --> 00:47:03,799 Speaker 1: those three things. I'm not sure which it is, or 832 00:47:03,800 --> 00:47:07,200 Speaker 1: if it's a combination. But I wish there were a 833 00:47:07,280 --> 00:47:10,440 Speaker 1: lot more curiosity about this, you know, among the media 834 00:47:10,480 --> 00:47:13,080 Speaker 1: and among the public health officials, because it's a pretty 835 00:47:13,120 --> 00:47:16,080 Speaker 1: remarkable of phenomenon. Talk to me about this, and we're 836 00:47:16,080 --> 00:47:19,720 Speaker 1: speaking of Phil Kirpin. He is the president of American Commitment, 837 00:47:19,719 --> 00:47:23,799 Speaker 1: and he's a syndicated columnist. Phil. I see all these charts, 838 00:47:23,800 --> 00:47:25,320 Speaker 1: and I've I've looked at some of the data myself, 839 00:47:25,320 --> 00:47:29,880 Speaker 1: and they show mask mandates going into place on a timeline. 840 00:47:30,360 --> 00:47:34,040 Speaker 1: And you know, for a state, right whether it's California 841 00:47:34,160 --> 00:47:37,200 Speaker 1: or Hawaii or New York or wherever mask mandate goes 842 00:47:37,200 --> 00:47:40,680 Speaker 1: into effect, and then you have countless charts where you 843 00:47:40,920 --> 00:47:43,799 Speaker 1: just give it time and the case is just skyrocket 844 00:47:44,000 --> 00:47:47,200 Speaker 1: after the mandate goes into effect. What can we just 845 00:47:47,280 --> 00:47:51,000 Speaker 1: tell from the numbers about this as a policy? Can 846 00:47:51,120 --> 00:47:54,160 Speaker 1: can we draw any conclusions or you can you draw 847 00:47:54,200 --> 00:47:58,160 Speaker 1: any conclusions from what we're seeing. I don't think masks 848 00:47:58,160 --> 00:48:02,440 Speaker 1: have any effect mask mandates, You know, we should we 849 00:48:02,440 --> 00:48:05,400 Speaker 1: should differentiate the two masked mandates and masks are not 850 00:48:05,480 --> 00:48:08,759 Speaker 1: necessarily synonymous, because just because the mandates in an area 851 00:48:08,800 --> 00:48:11,319 Speaker 1: doesn't mean everyone's wearing them or wearing them properly or 852 00:48:11,360 --> 00:48:14,080 Speaker 1: handling them properly and so forth. You know, the reason 853 00:48:14,280 --> 00:48:19,000 Speaker 1: historically we've never recommended masks outside of medical settings is 854 00:48:19,040 --> 00:48:22,279 Speaker 1: it's actually really hard to use a mask properly, to 855 00:48:22,320 --> 00:48:24,520 Speaker 1: make sure you never touch the outside, to remove it 856 00:48:24,560 --> 00:48:27,239 Speaker 1: and carefully and throw it out or wash it without 857 00:48:27,280 --> 00:48:29,919 Speaker 1: ever touching the outside. And you know, that's why we've 858 00:48:30,000 --> 00:48:32,799 Speaker 1: never recommended them in non medical settings, because even if 859 00:48:32,840 --> 00:48:35,880 Speaker 1: they work sort of conceptually in sort of a lab test, 860 00:48:36,239 --> 00:48:39,040 Speaker 1: we never had confidence that people would use them correctly 861 00:48:39,040 --> 00:48:42,280 Speaker 1: in a way that actually could be beneficial. And I 862 00:48:42,320 --> 00:48:44,520 Speaker 1: think that based on the data that I'm seeing, you know, 863 00:48:44,640 --> 00:48:47,319 Speaker 1: it's sort of you could go either way on whether 864 00:48:47,320 --> 00:48:49,480 Speaker 1: they work in idealized setting. There is a lot of 865 00:48:49,520 --> 00:48:51,839 Speaker 1: lab data showing that they probably would be beneficial if 866 00:48:51,840 --> 00:48:55,560 Speaker 1: they were used sort of perfectly, but in practice, I 867 00:48:55,600 --> 00:48:58,080 Speaker 1: don't see any evidence that they've been beneficial at all. 868 00:48:58,120 --> 00:49:01,560 Speaker 1: And you know, there's cherry picking that goes on. And 869 00:49:01,640 --> 00:49:04,040 Speaker 1: the CDC had a couple of very low quality studies 870 00:49:04,040 --> 00:49:07,399 Speaker 1: looking at Arizona and Kansas, where they essentially just cherry 871 00:49:07,440 --> 00:49:11,200 Speaker 1: picked their end dates and their comparators and said, look, 872 00:49:11,480 --> 00:49:15,080 Speaker 1: masks to the reason we saw a decline. And you know, 873 00:49:15,120 --> 00:49:19,120 Speaker 1: if you look at kind of what's happened seasonally, you 874 00:49:19,640 --> 00:49:22,880 Speaker 1: have essentially identical patterns in places with and without mask mandates, 875 00:49:22,920 --> 00:49:25,919 Speaker 1: if they've got the same geography in the same sort 876 00:49:25,960 --> 00:49:28,359 Speaker 1: of time of year, and so I don't think that 877 00:49:28,400 --> 00:49:30,600 Speaker 1: they make a difference one way or the other. You 878 00:49:30,600 --> 00:49:34,040 Speaker 1: could argue some have suggested they may actually be harmful. 879 00:49:34,120 --> 00:49:36,799 Speaker 1: The reason that the normodic states have all avoided the 880 00:49:36,880 --> 00:49:40,439 Speaker 1: mask mandates, you know, Sweden, Denmark, Norway and so forth, 881 00:49:40,440 --> 00:49:43,080 Speaker 1: as they say, look, you know, the mask doesn't really 882 00:49:43,120 --> 00:49:45,760 Speaker 1: do that much, especially the way a typical person handles 883 00:49:45,760 --> 00:49:47,520 Speaker 1: it is not well trained, the way as a surgeon 884 00:49:47,560 --> 00:49:49,680 Speaker 1: would be, and so forth. But if you tell people 885 00:49:49,920 --> 00:49:52,880 Speaker 1: that the mask protects you, then suddenly they're going to 886 00:49:52,920 --> 00:49:55,080 Speaker 1: stand right next to each other for prolonged periods of 887 00:49:55,120 --> 00:49:57,279 Speaker 1: time with masks on, and they're going to think they 888 00:49:57,320 --> 00:49:59,399 Speaker 1: don't need to keep their distance. And oh and I'm 889 00:49:59,400 --> 00:50:01,680 Speaker 1: sure people have mild code. They might go out of 890 00:50:01,680 --> 00:50:04,040 Speaker 1: the house even if they're feeling set because mask on 891 00:50:04,400 --> 00:50:06,279 Speaker 1: and so the you know, a false belief that a 892 00:50:06,360 --> 00:50:08,680 Speaker 1: mask will protect you might actually put you at more resk. 893 00:50:08,760 --> 00:50:10,399 Speaker 1: This is what I've been saying you're gonna have people 894 00:50:10,440 --> 00:50:12,400 Speaker 1: and say, well, maybe I got COVID, but my symptoms 895 00:50:12,440 --> 00:50:14,359 Speaker 1: aren't that bad and I'm wearing a mask, so I'm 896 00:50:14,400 --> 00:50:16,640 Speaker 1: good to go. It's like, no, this is a bad idea. 897 00:50:16,680 --> 00:50:19,920 Speaker 1: There's a bad idea, but I could guarantee that's been 898 00:50:19,960 --> 00:50:22,560 Speaker 1: happening all over the country, all over the world. Phil, Look, 899 00:50:22,600 --> 00:50:25,279 Speaker 1: I appreciate that you're willing to take take a look 900 00:50:25,280 --> 00:50:27,640 Speaker 1: at the data here on the numbers and come to 901 00:50:27,680 --> 00:50:30,320 Speaker 1: conclusions that you know aren't right in line with the consensus. 902 00:50:30,360 --> 00:50:33,399 Speaker 1: I feel like this is the brainwashing that has gone 903 00:50:33,400 --> 00:50:35,520 Speaker 1: on on this issue is unlike anything else I've ever 904 00:50:35,560 --> 00:50:36,759 Speaker 1: seen in my life. I just want to give you 905 00:50:36,840 --> 00:50:39,280 Speaker 1: the last word. Yeah, I mean, probably the most frightening 906 00:50:39,280 --> 00:50:41,440 Speaker 1: thing of the past year buck has been the extent 907 00:50:41,520 --> 00:50:45,120 Speaker 1: to which people not only accepted all of these various 908 00:50:45,200 --> 00:50:48,560 Speaker 1: arbitrary government decrees, but demanded them and welcomed them and 909 00:50:48,640 --> 00:50:51,919 Speaker 1: cheered them on. And I think the extent to which 910 00:50:51,960 --> 00:50:56,560 Speaker 1: a large portion of the public supports the heavy handed 911 00:50:57,000 --> 00:51:00,719 Speaker 1: government policy response is probably the most frightening takeaway of 912 00:51:00,719 --> 00:51:03,160 Speaker 1: this whole thing. And uh, you know, it means we 913 00:51:03,160 --> 00:51:05,520 Speaker 1: could we could see this again every time there's a disease. 914 00:51:05,600 --> 00:51:08,080 Speaker 1: So I am, I am concerned about that, and I 915 00:51:08,120 --> 00:51:11,680 Speaker 1: share your uh, you know, I share your sentiments on that. 916 00:51:12,120 --> 00:51:15,480 Speaker 1: Bill Kirpin, President of American Commitment, Phil really appreciate it. 917 00:51:15,560 --> 00:51:17,160 Speaker 1: Talk to you soon, all right, have a good one.