1 00:00:02,080 --> 00:00:05,760 Speaker 1: This is Wins and Losses with Clay Travis. Clay talks 2 00:00:05,800 --> 00:00:09,879 Speaker 1: with the most entertaining people in sports, entertainment and business. 3 00:00:10,160 --> 00:00:21,560 Speaker 1: Now here's Clay Travis. Welcome in Wins and Losses Podcast. 4 00:00:21,600 --> 00:00:23,280 Speaker 1: I am Clay Travis. I hope all of you are 5 00:00:23,280 --> 00:00:25,520 Speaker 1: having a fantastic time wherever you may be across this 6 00:00:25,600 --> 00:00:28,160 Speaker 1: great country or this great land. We are joined by 7 00:00:28,160 --> 00:00:30,440 Speaker 1: a guy that I think has been doing incredible work, 8 00:00:31,000 --> 00:00:34,040 Speaker 1: a warding off Team Apocalypse, as he sometimes says it. 9 00:00:34,200 --> 00:00:37,519 Speaker 1: He is Alex Barnson, a former New York Times reporter 10 00:00:37,600 --> 00:00:41,839 Speaker 1: who has been focused on the coronavirus and the response 11 00:00:41,880 --> 00:00:44,760 Speaker 1: of our government. Obviously, we talk a lot about politics 12 00:00:44,760 --> 00:00:48,080 Speaker 1: and the intersection of sports as it pertains to the 13 00:00:48,159 --> 00:00:50,160 Speaker 1: return of sports, and so I thought he was gonna 14 00:00:50,200 --> 00:00:53,760 Speaker 1: be and is a perfect guest for us. So welcome in, Alex. 15 00:00:54,200 --> 00:00:56,280 Speaker 1: I appreciate you joining us. For people who may not 16 00:00:56,440 --> 00:00:59,520 Speaker 1: have followed you on Twitter or been reading the books 17 00:00:59,560 --> 00:01:02,200 Speaker 1: that you have put out that are available on Amazon. 18 00:01:02,720 --> 00:01:05,560 Speaker 1: What is your background? Kind of introduce yourself to our 19 00:01:05,600 --> 00:01:10,480 Speaker 1: audience as best you can. Sure, So, I worked for 20 00:01:10,480 --> 00:01:13,640 Speaker 1: the New York Times from until two thousand and ten. 21 00:01:13,680 --> 00:01:16,080 Speaker 1: I was a reporter. I've been a reporter since I 22 00:01:16,120 --> 00:01:21,120 Speaker 1: graduated college in ninety four and uh to ten. I 23 00:01:21,200 --> 00:01:25,120 Speaker 1: mainly did investigative reporting, business really business investigating. Before I 24 00:01:25,200 --> 00:01:27,240 Speaker 1: covered the drug industry, a lot of stuff like that. 25 00:01:27,760 --> 00:01:30,400 Speaker 1: And then in two dozen six, I wrote uh, a 26 00:01:30,400 --> 00:01:32,560 Speaker 1: spy novel because I've been in a rack in a 27 00:01:32,880 --> 00:01:35,080 Speaker 1: two three and oh four for The Times, not not 28 00:01:35,120 --> 00:01:37,759 Speaker 1: for that long, but for a few months, and I 29 00:01:37,880 --> 00:01:40,120 Speaker 1: and I wound up writing the spine novel called The 30 00:01:40,160 --> 00:01:44,520 Speaker 1: Faithful Spy about a CIA operative who converts to Islam 31 00:01:45,000 --> 00:01:46,880 Speaker 1: and get sent back to the United States and al 32 00:01:46,920 --> 00:01:49,040 Speaker 1: Qaeda doesn't really trust him because they know he's American, 33 00:01:49,160 --> 00:01:51,280 Speaker 1: and and the CIA doesn't really trust him because they 34 00:01:51,320 --> 00:01:54,200 Speaker 1: know he converted. And that book did pretty well. Actually, 35 00:01:54,240 --> 00:01:57,040 Speaker 1: it became a number one New York Times bestseller in 36 00:01:57,080 --> 00:02:00,680 Speaker 1: paperback in two thousand and eight. And so writing these 37 00:02:00,680 --> 00:02:03,440 Speaker 1: spine novels or took over my my life for a 38 00:02:03,520 --> 00:02:06,640 Speaker 1: number of years, um uh and uh. And I left 39 00:02:06,640 --> 00:02:09,200 Speaker 1: The Times in two thousand and ten um and to 40 00:02:09,200 --> 00:02:12,160 Speaker 1: to become a full time novelist um. Which is interesting 41 00:02:12,200 --> 00:02:16,200 Speaker 1: because because I really think of myself more. And even 42 00:02:16,240 --> 00:02:18,040 Speaker 1: when I was writing these books, I thought of myself 43 00:02:18,040 --> 00:02:20,560 Speaker 1: more of a journalist than a novelist, and sometimes I 44 00:02:20,840 --> 00:02:23,200 Speaker 1: kind of wish that I had been able to, you know, 45 00:02:23,320 --> 00:02:26,360 Speaker 1: express my imagination more freely, because I think that can 46 00:02:26,440 --> 00:02:28,919 Speaker 1: make a really great novel. And sometimes I felt like 47 00:02:28,960 --> 00:02:31,400 Speaker 1: I was a little bit bound by my desire to 48 00:02:31,440 --> 00:02:35,079 Speaker 1: write authentic fiction rather than doing stuff that was a 49 00:02:35,120 --> 00:02:37,200 Speaker 1: little bit more magical. But that's that's a that's a 50 00:02:37,240 --> 00:02:39,959 Speaker 1: total side issue. But but it is interesting to me 51 00:02:40,080 --> 00:02:42,040 Speaker 1: that I went then went back to journalism, so I 52 00:02:42,040 --> 00:02:45,880 Speaker 1: found I wound up after um, after a number of 53 00:02:45,960 --> 00:02:48,760 Speaker 1: years writing these spine novels in two dozen nineteen was 54 00:02:48,800 --> 00:02:51,000 Speaker 1: really two seventeen eighteen, I wrote the book, but in 55 00:02:51,000 --> 00:02:52,919 Speaker 1: two nineteen it came out. I wrote a book called 56 00:02:52,919 --> 00:02:56,480 Speaker 1: Tell Your Children, which is about cannabis and um and 57 00:02:56,560 --> 00:02:59,520 Speaker 1: the dangers that it may present for some people. And 58 00:02:59,600 --> 00:03:02,880 Speaker 1: I wrote that, sorry, I hope that this is not 59 00:03:02,960 --> 00:03:05,079 Speaker 1: too big a digression, but I sort of want people 60 00:03:05,120 --> 00:03:08,080 Speaker 1: to understand my whole career because sometimes people say, oh, 61 00:03:08,120 --> 00:03:10,560 Speaker 1: he's just trading on his you know, the fact that 62 00:03:10,560 --> 00:03:13,000 Speaker 1: he worked for the New York Times for a little while, um, 63 00:03:13,080 --> 00:03:14,639 Speaker 1: when in fact I worked for the Times for ten 64 00:03:14,720 --> 00:03:17,520 Speaker 1: years but the reality is I've been a journalist almost 65 00:03:17,520 --> 00:03:21,480 Speaker 1: my whole life. Um uh. In any case, this book 66 00:03:21,560 --> 00:03:24,520 Speaker 1: called Tell Your Children I wrote because my wife is 67 00:03:24,520 --> 00:03:28,040 Speaker 1: a psychiatrist who deals with the criminal mentally ill, and 68 00:03:28,080 --> 00:03:30,360 Speaker 1: she would tell me about all these terrible cases she'd 69 00:03:30,360 --> 00:03:32,800 Speaker 1: seeing where what the people had in common who had 70 00:03:32,840 --> 00:03:35,800 Speaker 1: come to her you know, attention or people she was treating, 71 00:03:36,480 --> 00:03:39,840 Speaker 1: um was that they were really heavy cannabis users. And 72 00:03:39,880 --> 00:03:42,080 Speaker 1: I actually didn't believe that. Okay, I did not believe 73 00:03:42,200 --> 00:03:45,120 Speaker 1: this was a real problem, and I and I kind 74 00:03:45,120 --> 00:03:47,720 Speaker 1: of pushed back on her. But you know, she's the psychiatrist. 75 00:03:47,760 --> 00:03:49,600 Speaker 1: She's the one with the many years of medical training. 76 00:03:49,680 --> 00:03:51,680 Speaker 1: She's the one who actually sees these people. She's the 77 00:03:51,720 --> 00:03:56,600 Speaker 1: one who, um, you know, who got you know, who 78 00:03:56,600 --> 00:03:59,760 Speaker 1: got all this training. And she told me, you know, essentially, 79 00:03:59,760 --> 00:04:01,840 Speaker 1: after a year or more of listening to me talk 80 00:04:01,880 --> 00:04:03,680 Speaker 1: about stuff about which I didn't know what I was 81 00:04:03,680 --> 00:04:05,680 Speaker 1: talking about, she said, why don't you go read the papers? 82 00:04:05,760 --> 00:04:07,680 Speaker 1: So I went and read this stuff and realized, of 83 00:04:07,720 --> 00:04:09,520 Speaker 1: course she was right. She knew exactly what she was 84 00:04:09,560 --> 00:04:12,720 Speaker 1: talking about, and I wanted to realizing that there was 85 00:04:12,720 --> 00:04:16,760 Speaker 1: a book here, not just in the idea that people, um, 86 00:04:16,800 --> 00:04:18,960 Speaker 1: you know, that cannabis is a real risk to people's 87 00:04:19,000 --> 00:04:21,800 Speaker 1: mental health. Not everybody, but some people. But also the 88 00:04:21,839 --> 00:04:23,720 Speaker 1: fact that nobody knew this and there were sort of 89 00:04:23,720 --> 00:04:27,360 Speaker 1: marching towards uh full legalization of this drug and no 90 00:04:27,400 --> 00:04:29,800 Speaker 1: one really had any idea of the risks, and then 91 00:04:29,800 --> 00:04:32,040 Speaker 1: it was actually being sold to people of medicine. So 92 00:04:32,120 --> 00:04:34,160 Speaker 1: that book became to tell your children, and that came 93 00:04:34,160 --> 00:04:38,360 Speaker 1: out in early twenty nineteen. Uh. And that's directly relevant 94 00:04:38,400 --> 00:04:41,480 Speaker 1: to this because because as soon as I wrote that book, 95 00:04:41,920 --> 00:04:44,919 Speaker 1: essentially I became a cast out from the world of journalists, 96 00:04:45,080 --> 00:04:48,440 Speaker 1: certainly in the world of the elite uh New York 97 00:04:48,480 --> 00:04:53,960 Speaker 1: slash Washington academic you know a slash New York Times 98 00:04:54,000 --> 00:04:58,320 Speaker 1: slash uh you know, Ivy League pedigree journalism. I became 99 00:04:58,360 --> 00:05:01,080 Speaker 1: a traitor to the class. So so you know, I 100 00:05:01,120 --> 00:05:03,000 Speaker 1: went to Yale, I worked for the New York Times. 101 00:05:03,360 --> 00:05:06,880 Speaker 1: There's nothing that people who who who work at those places, 102 00:05:06,920 --> 00:05:08,400 Speaker 1: you know, work at the New York Times lotion puss 103 00:05:08,520 --> 00:05:11,640 Speaker 1: like less than somebody who who work there, And doesn't 104 00:05:11,760 --> 00:05:14,920 Speaker 1: you know, play in the sandbox. And by saying that 105 00:05:14,960 --> 00:05:17,520 Speaker 1: you know that cannabis is actually kind of a dangerous 106 00:05:17,600 --> 00:05:20,400 Speaker 1: drug for some people, and that you know, by the 107 00:05:20,400 --> 00:05:23,039 Speaker 1: way you hear that, you know that there are millions 108 00:05:23,040 --> 00:05:25,520 Speaker 1: of black people in prison for for you know, for 109 00:05:25,600 --> 00:05:28,120 Speaker 1: having one join in their pockets, and that's completely untrue. 110 00:05:28,240 --> 00:05:29,520 Speaker 1: You can you know, you can look at what the 111 00:05:29,560 --> 00:05:33,560 Speaker 1: statistics are and they're completely not that. Um. You know 112 00:05:33,680 --> 00:05:37,480 Speaker 1: when when I when I pointed that out, people hated 113 00:05:37,560 --> 00:05:40,600 Speaker 1: me and uh, and it became very hard for me 114 00:05:40,680 --> 00:05:45,000 Speaker 1: to get of national publicity for this book, aside from 115 00:05:45,040 --> 00:05:47,760 Speaker 1: Fox and some other conservative outlets. And that was when 116 00:05:47,800 --> 00:05:51,400 Speaker 1: I really saw for myself that polarization in the media 117 00:05:51,600 --> 00:05:54,599 Speaker 1: just how deep it is. So fast forward to March 118 00:05:54,720 --> 00:05:57,440 Speaker 1: of this year. Um, and again I apologize for the 119 00:05:57,520 --> 00:06:00,080 Speaker 1: length of but but but it really doesn't form what 120 00:06:00,120 --> 00:06:03,239 Speaker 1: I've been doing the last six months. March of this year, 121 00:06:03,720 --> 00:06:06,640 Speaker 1: you know, really January, we all start hearing about this virus. 122 00:06:06,760 --> 00:06:10,720 Speaker 1: There's this terrible videos coming out of China, very scary stuff. 123 00:06:10,960 --> 00:06:13,440 Speaker 1: The hospitals are being overrun. We hear it's going to 124 00:06:13,520 --> 00:06:16,920 Speaker 1: spread all over China. It's going to be completely impossible 125 00:06:17,000 --> 00:06:20,920 Speaker 1: to stop. Um. You know, the the there's a travel 126 00:06:21,000 --> 00:06:23,440 Speaker 1: band from China. There's an argument about what it's going 127 00:06:23,480 --> 00:06:26,680 Speaker 1: to make any difference. February, nothing really happens for a 128 00:06:26,720 --> 00:06:29,400 Speaker 1: little while, and then the hospitals in parts of northern 129 00:06:29,480 --> 00:06:32,840 Speaker 1: Italy start getting overrun. And then and then all of 130 00:06:32,880 --> 00:06:36,440 Speaker 1: a sudden, it's here, the the the the Stars Cove 131 00:06:36,520 --> 00:06:39,720 Speaker 1: two is in Seattle, it's in New York. It's here. 132 00:06:40,080 --> 00:06:43,039 Speaker 1: And suddenly, in a matter of days, we shut down 133 00:06:43,200 --> 00:06:45,360 Speaker 1: not just the United States, we shut down the whole world. 134 00:06:46,320 --> 00:06:48,680 Speaker 1: And and I certainly was nervous. I think, I think 135 00:06:48,680 --> 00:06:51,040 Speaker 1: anybody where you know where the pulse was nervous at 136 00:06:51,080 --> 00:06:54,760 Speaker 1: that time. UM. But I but I started to you know, 137 00:06:54,800 --> 00:06:58,760 Speaker 1: I started to read everything I could find about um, 138 00:06:58,800 --> 00:07:02,440 Speaker 1: about what the prediction war, and why we had taken 139 00:07:02,440 --> 00:07:07,000 Speaker 1: such a drastic and dramatic action. And more than anything else, 140 00:07:07,040 --> 00:07:10,600 Speaker 1: there was one paper from a place called Imperial College, London, 141 00:07:10,920 --> 00:07:14,600 Speaker 1: which works with the World Health Organization, that drove this 142 00:07:14,720 --> 00:07:18,920 Speaker 1: incredible action in mid March, and the paper said two 143 00:07:18,920 --> 00:07:21,160 Speaker 1: million people in the United States might die if there's 144 00:07:21,200 --> 00:07:24,120 Speaker 1: a lockdown, uh, you know, half million people. And I'm sorry, 145 00:07:24,120 --> 00:07:26,600 Speaker 1: if there's no lockdown. A half million people in Britain 146 00:07:26,680 --> 00:07:28,920 Speaker 1: might die if there's no lockdown. We have to we 147 00:07:28,960 --> 00:07:35,560 Speaker 1: have to take incredibly uh dramatic action and so um 148 00:07:35,600 --> 00:07:38,400 Speaker 1: and so I read that paper and this was in 149 00:07:38,680 --> 00:07:42,080 Speaker 1: mid March, and I'll never forget. You know, I'm in uh, 150 00:07:42,120 --> 00:07:45,840 Speaker 1: you know, at home reading this on my computer and 151 00:07:45,840 --> 00:07:49,560 Speaker 1: I realized, wait a minute, the vast, vast majority of 152 00:07:49,600 --> 00:07:52,720 Speaker 1: deaths that are predicted here are in people over over 153 00:07:52,800 --> 00:07:55,840 Speaker 1: eighty and seventy really really eighty, but you know, and 154 00:07:55,880 --> 00:07:58,520 Speaker 1: then an affair number in the seven eight band. This 155 00:07:58,720 --> 00:08:01,960 Speaker 1: just doesn't look at that tame interest to people under seventy. 156 00:08:02,080 --> 00:08:03,800 Speaker 1: And that's not to say it's not real. It's not 157 00:08:03,840 --> 00:08:05,760 Speaker 1: to say it's not dangerous. It's not to say it 158 00:08:05,800 --> 00:08:09,000 Speaker 1: can't hurt people. But but but my impression of this, 159 00:08:09,120 --> 00:08:10,640 Speaker 1: like a lot of people have been, this is going 160 00:08:10,680 --> 00:08:13,559 Speaker 1: to be the Spanish flu. This is gonna kill pregnant women, 161 00:08:13,600 --> 00:08:16,320 Speaker 1: and it's gonna kill children, and it's gonna kill healthy adults, 162 00:08:16,760 --> 00:08:19,560 Speaker 1: and you know, there's there's gonna be people dropping dead 163 00:08:19,560 --> 00:08:21,680 Speaker 1: in the streets. And all of a sudden, I realized 164 00:08:21,920 --> 00:08:25,360 Speaker 1: that's not what this is at all. This is this 165 00:08:25,480 --> 00:08:29,320 Speaker 1: is this is a virus that really affects people who 166 00:08:29,320 --> 00:08:32,240 Speaker 1: are at severe risk because of their age or because 167 00:08:32,240 --> 00:08:35,559 Speaker 1: they're really severely ill with other conditions, and and it's 168 00:08:35,600 --> 00:08:39,240 Speaker 1: like the scale self from my eyes. And ever since then, UM, 169 00:08:39,240 --> 00:08:41,880 Speaker 1: I've been trying to trying to talk, trying to get 170 00:08:41,880 --> 00:08:45,120 Speaker 1: people to talk reasonably about what the risks are and 171 00:08:45,280 --> 00:08:48,040 Speaker 1: what we should be doing. And that doesn't mean we 172 00:08:48,080 --> 00:08:50,319 Speaker 1: should be doing nothing. It means that we should stop 173 00:08:50,360 --> 00:08:54,200 Speaker 1: pretending that everybody's an equal risk here. Everybody's that you know, 174 00:08:54,280 --> 00:08:57,280 Speaker 1: anything near equal risk here, And maybe we should be 175 00:08:57,280 --> 00:08:59,560 Speaker 1: trying to protect the people are the most vulnerable. But 176 00:08:59,760 --> 00:09:03,040 Speaker 1: why on earth are we letting this destroy our society? 177 00:09:03,160 --> 00:09:05,760 Speaker 1: Who we have? And everything that I've reported practically in 178 00:09:05,800 --> 00:09:09,240 Speaker 1: the last five months has only served to make me 179 00:09:09,320 --> 00:09:12,480 Speaker 1: feel more strongly about this. And I'll just give you 180 00:09:12,520 --> 00:09:15,000 Speaker 1: one example and then and then I'll stop talking. Let you, 181 00:09:15,000 --> 00:09:18,880 Speaker 1: you know, ask questions. UM. There was a lot of 182 00:09:18,920 --> 00:09:24,080 Speaker 1: talk in two thousand seven about what if another um, 183 00:09:24,120 --> 00:09:27,280 Speaker 1: you know, bad flu hits uh. You know, there's been 184 00:09:27,360 --> 00:09:30,200 Speaker 1: the Antwracks attacks in two thousand and one. George W. 185 00:09:30,360 --> 00:09:33,480 Speaker 1: Bush was very concerned about bio terrorism. There had also 186 00:09:33,520 --> 00:09:35,640 Speaker 1: been the stars scaring you know three, there had been 187 00:09:35,679 --> 00:09:38,079 Speaker 1: a swine flu scare you know five, And so we 188 00:09:38,160 --> 00:09:41,040 Speaker 1: spent a lot of time back then really thinking about this. 189 00:09:41,280 --> 00:09:45,720 Speaker 1: Very smart people, um, you know, in government, outside government, uh, 190 00:09:45,840 --> 00:09:49,280 Speaker 1: people who have been experts on pandemics uh, and they 191 00:09:49,320 --> 00:09:53,520 Speaker 1: all basically reached the same conclusion, which is a big 192 00:09:53,559 --> 00:09:56,679 Speaker 1: lockdown is not a great idea like this is, even 193 00:09:56,760 --> 00:09:58,880 Speaker 1: even if it's really serious, even if it's on the 194 00:09:58,960 --> 00:10:02,280 Speaker 1: order of the Spanish flu. What you want is you 195 00:10:02,280 --> 00:10:04,760 Speaker 1: want to encourage sick people to stay home. You may 196 00:10:04,760 --> 00:10:08,080 Speaker 1: want to temporarily close schools, you know, maybe for maybe 197 00:10:08,160 --> 00:10:11,559 Speaker 1: for a few weeks. Maybe you encourage people to telecommute, 198 00:10:12,000 --> 00:10:14,839 Speaker 1: maybe you encourage people not to use you know, mass 199 00:10:14,880 --> 00:10:18,760 Speaker 1: public transportation at the height of this. But the idea 200 00:10:18,880 --> 00:10:23,199 Speaker 1: that that this that the correct response to a pandemic, 201 00:10:23,320 --> 00:10:27,120 Speaker 1: even a really severe pandemic, would be to shut down 202 00:10:27,160 --> 00:10:30,160 Speaker 1: the world, with all the pain that that would cause 203 00:10:30,920 --> 00:10:34,240 Speaker 1: our economy and all the pain that would cause people working, 204 00:10:34,320 --> 00:10:36,040 Speaker 1: and all the pain it would cause children not to 205 00:10:36,080 --> 00:10:37,480 Speaker 1: be able to go to school, not to be able 206 00:10:37,480 --> 00:10:39,880 Speaker 1: to see their friends, some of those children at very 207 00:10:39,920 --> 00:10:43,600 Speaker 1: severe risk you know, being an abusive homes uh, you know, 208 00:10:43,800 --> 00:10:46,680 Speaker 1: or or children with special needs who really are are 209 00:10:46,720 --> 00:10:49,880 Speaker 1: you know need need people who are who are well 210 00:10:49,920 --> 00:10:51,920 Speaker 1: trained to take care of them, and it's very, very 211 00:10:51,920 --> 00:10:54,520 Speaker 1: difficult for their parents to take care of them. Seven. 212 00:10:54,960 --> 00:10:58,439 Speaker 1: All of that was considered and and people said, let's 213 00:10:58,440 --> 00:11:01,520 Speaker 1: not panic when this happen. Let's have a bunch of rules, 214 00:11:01,920 --> 00:11:06,800 Speaker 1: reasonable rules that we're going to follow. And and unfortunately, 215 00:11:06,840 --> 00:11:10,360 Speaker 1: when the moment came this March, we threw all of 216 00:11:10,400 --> 00:11:13,520 Speaker 1: that away and we have been suffering for it ever since. 217 00:11:15,040 --> 00:11:18,319 Speaker 1: So much to unpack there. I'm Clay Travis's wins and losses, 218 00:11:18,320 --> 00:11:21,200 Speaker 1: and we're talking with Alex Barrenson, former New York Times 219 00:11:21,200 --> 00:11:23,679 Speaker 1: employee who has been covering the coronavirus since March. As 220 00:11:23,679 --> 00:11:26,600 Speaker 1: you heard him say, Okay, I'm gonna unpack, I'm gonna 221 00:11:26,600 --> 00:11:30,439 Speaker 1: go back in several different directions. You mentioned this expert forecast, 222 00:11:30,520 --> 00:11:33,640 Speaker 1: this Nile Ferguson I believe is his name, at the 223 00:11:33,679 --> 00:11:38,200 Speaker 1: Imperial College of London. Why did he get it wrong 224 00:11:38,480 --> 00:11:43,280 Speaker 1: so badly? And why did so many people believe his 225 00:11:43,480 --> 00:11:46,280 Speaker 1: forecast to such an extent Because there were a lot 226 00:11:46,360 --> 00:11:49,080 Speaker 1: of forecasts out there. What I've been saying is the 227 00:11:49,200 --> 00:11:54,559 Speaker 1: fear porn lad the media to adopt the worst possible forecast. 228 00:11:55,400 --> 00:11:59,720 Speaker 1: How what happened there? That that particular forecast became, for 229 00:11:59,800 --> 00:12:03,520 Speaker 1: lie of a better term, viral and the central lynchpin 230 00:12:03,720 --> 00:12:07,800 Speaker 1: of many decisions to lock down around the globe leading 231 00:12:07,840 --> 00:12:12,000 Speaker 1: to disastrous consequences. I believe what was it about that 232 00:12:12,040 --> 00:12:16,439 Speaker 1: forecast that so captured the public's imagination and the media's imagination. 233 00:12:17,040 --> 00:12:19,959 Speaker 1: So that's a that's a great, great question play. And 234 00:12:20,160 --> 00:12:22,600 Speaker 1: and you know, in in in in the law. So 235 00:12:23,040 --> 00:12:25,280 Speaker 1: I've written these two booklets as you, as you were 236 00:12:25,360 --> 00:12:27,200 Speaker 1: kind enough to mention, And the second one is about 237 00:12:27,240 --> 00:12:29,240 Speaker 1: the lockdown. The first one is really about death and 238 00:12:29,280 --> 00:12:32,319 Speaker 1: what a worst case projection might be in the US 239 00:12:32,400 --> 00:12:35,439 Speaker 1: and howard counting death and has there been overcounting all 240 00:12:35,480 --> 00:12:38,200 Speaker 1: of those questions. The second one is about lockdown and 241 00:12:38,200 --> 00:12:43,480 Speaker 1: and so and so it is fascinating that that Neil Ferguson, 242 00:12:43,520 --> 00:12:48,040 Speaker 1: the Professor Ferguson Um, became the authority on this because 243 00:12:48,040 --> 00:12:50,319 Speaker 1: he's not a doctor, okay, and he's not a virologist. 244 00:12:50,440 --> 00:12:53,760 Speaker 1: He's a physicist by training, and his specialty is making 245 00:12:53,800 --> 00:12:57,920 Speaker 1: these epidemiologic models, which he has actually failed that tremendously 246 00:12:58,000 --> 00:13:01,600 Speaker 1: in the past. Right, you are exactly right, he has 247 00:13:01,640 --> 00:13:05,080 Speaker 1: failed tremendously at those models. And at one point he 248 00:13:05,080 --> 00:13:07,679 Speaker 1: said the two d million people might die from from 249 00:13:07,720 --> 00:13:10,280 Speaker 1: swine flu, you know, five and you know, I mean 250 00:13:10,280 --> 00:13:13,000 Speaker 1: that number was a joke, okay, But but nobody ever 251 00:13:13,040 --> 00:13:17,439 Speaker 1: seems to remember the mistakes that he's made. So so 252 00:13:17,559 --> 00:13:19,599 Speaker 1: a couple of other are a couple of issues. The 253 00:13:20,600 --> 00:13:23,160 Speaker 1: first is you need to know how lethal the viruses, 254 00:13:23,440 --> 00:13:26,880 Speaker 1: and it appears that the virus is less lethal than 255 00:13:26,920 --> 00:13:29,600 Speaker 1: we thought it was, uh in you know, in in 256 00:13:29,840 --> 00:13:32,280 Speaker 1: January through March. Now, there's a couple of reasons for that. 257 00:13:32,480 --> 00:13:35,320 Speaker 1: First of all, the data from China, nobody really knew 258 00:13:35,800 --> 00:13:38,240 Speaker 1: what to make of it. Nobody really knew if we 259 00:13:38,280 --> 00:13:41,840 Speaker 1: could believe it. But there's a much even more serious 260 00:13:41,880 --> 00:13:44,440 Speaker 1: and deep problem than that, which is you need to 261 00:13:44,520 --> 00:13:48,240 Speaker 1: know how many people are being infected. And with this virus, 262 00:13:48,320 --> 00:13:50,360 Speaker 1: it appears that there are a tremendous number of people 263 00:13:50,400 --> 00:13:53,600 Speaker 1: who are infected who basically don't know it. They're either 264 00:13:53,640 --> 00:13:57,080 Speaker 1: asymptomatic or so lightly symptomatic that if they were not tested, 265 00:13:57,360 --> 00:14:00,320 Speaker 1: they would never know it. And because of that, this 266 00:14:00,440 --> 00:14:03,480 Speaker 1: is actually much less lethal than we thought it was 267 00:14:03,559 --> 00:14:06,480 Speaker 1: back then, okay, And it appears that there may be 268 00:14:06,520 --> 00:14:09,080 Speaker 1: a significant number of people who never can get it 269 00:14:09,120 --> 00:14:11,679 Speaker 1: at all, and we don't know how many that is, 270 00:14:11,920 --> 00:14:13,760 Speaker 1: but there, but there. But there's been a big and 271 00:14:13,840 --> 00:14:17,040 Speaker 1: ongoing argument in the scientific community about what's called T 272 00:14:17,240 --> 00:14:19,520 Speaker 1: cell cross reactivity, which, by the way, the New York 273 00:14:19,520 --> 00:14:23,120 Speaker 1: Times finally wrote about. They wrote about today literally as 274 00:14:23,160 --> 00:14:25,600 Speaker 1: we're talking about this, they wrote, we're talking about this 275 00:14:25,680 --> 00:14:27,400 Speaker 1: for people out there who are listening. Who knows when 276 00:14:27,400 --> 00:14:31,440 Speaker 1: they'll be listening. Officially, we're talking on Monday, uh, the 277 00:14:31,520 --> 00:14:34,400 Speaker 1: seventeenth of August. And there's an article today about that 278 00:14:34,440 --> 00:14:36,080 Speaker 1: in The New York Times, about the fact that there 279 00:14:36,080 --> 00:14:38,400 Speaker 1: may be a ton of people who have immunity to 280 00:14:38,480 --> 00:14:42,600 Speaker 1: this virus and trying to figure out why Suddenly, for instance, 281 00:14:42,640 --> 00:14:45,080 Speaker 1: in New York the infection rate just fell off a 282 00:14:45,120 --> 00:14:47,560 Speaker 1: cliff And as you imagine, I've seen as well, the 283 00:14:47,600 --> 00:14:50,760 Speaker 1: same thing now is happening in the South. Indeed, Florida 284 00:14:50,840 --> 00:14:53,720 Speaker 1: Governor Ron de Santis just came out and basically said 285 00:14:54,000 --> 00:14:56,600 Speaker 1: the bottom has fallen out of the outbreak in quotation 286 00:14:56,680 --> 00:14:59,680 Speaker 1: marks in Florida as well. Well, good for him for 287 00:14:59,720 --> 00:15:02,000 Speaker 1: saying it, because it's true and he's been he's been 288 00:15:02,040 --> 00:15:04,320 Speaker 1: better on this, and uh, you know, they're more forward 289 00:15:04,360 --> 00:15:07,080 Speaker 1: thinking on this than anybody else, and the media hates 290 00:15:07,120 --> 00:15:09,640 Speaker 1: him for it, and he has not benefited politically for it. 291 00:15:09,920 --> 00:15:12,320 Speaker 1: He clearly is only doing it because he believes that 292 00:15:12,360 --> 00:15:14,800 Speaker 1: he's doing the right thing, and and good for him 293 00:15:14,840 --> 00:15:17,960 Speaker 1: for that. Um uh, you know, But to your point, 294 00:15:18,080 --> 00:15:20,080 Speaker 1: your point is here, I think a good one the 295 00:15:20,160 --> 00:15:23,520 Speaker 1: death rate and the number of infections. If you don't 296 00:15:23,600 --> 00:15:29,080 Speaker 1: know those two numbers, then whatever epidemiological expert forecast you 297 00:15:29,160 --> 00:15:34,080 Speaker 1: create is essentially valueless because your numerator and your denomic 298 00:15:34,280 --> 00:15:37,880 Speaker 1: nator are both have issues. So it's almost impossible to 299 00:15:37,880 --> 00:15:42,040 Speaker 1: come up with a reliable, predictive forecast that is exactly correct. 300 00:15:42,040 --> 00:15:44,120 Speaker 1: That is that, so if a thousand people have died, 301 00:15:44,240 --> 00:15:46,760 Speaker 1: who know, a thousand people have died, and we think 302 00:15:46,800 --> 00:15:49,360 Speaker 1: ten thousand were infected, that's a ten death rate. Okay, 303 00:15:49,360 --> 00:15:51,640 Speaker 1: that means one person at ten who got it has died. 304 00:15:51,920 --> 00:15:54,440 Speaker 1: That's terrible. Okay that that you know, that would mean 305 00:15:54,560 --> 00:15:56,200 Speaker 1: you know, thirty million people in the U s would 306 00:15:56,240 --> 00:15:59,480 Speaker 1: die if everybody got it. Okay, But if the truth 307 00:15:59,560 --> 00:16:01,680 Speaker 1: is that a million people have already gotten in, not 308 00:16:01,800 --> 00:16:04,960 Speaker 1: ten thousand and one thousand people have died, that's a 309 00:16:05,000 --> 00:16:07,480 Speaker 1: death rate of one tenth of one percent. It's one 310 00:16:07,520 --> 00:16:11,440 Speaker 1: one what I just said, Okay, And that would mean 311 00:16:11,840 --> 00:16:15,040 Speaker 1: that three hundred thousand people in the US would die 312 00:16:15,200 --> 00:16:17,640 Speaker 1: if if everybody got it. Okay, Well you know, and 313 00:16:17,720 --> 00:16:19,960 Speaker 1: that's so you could say thople with a lot of people. 314 00:16:20,160 --> 00:16:22,840 Speaker 1: But that's because the US is a big country. Okay. 315 00:16:23,080 --> 00:16:27,680 Speaker 1: Smoking preventably killed half million people in the US every year, 316 00:16:28,200 --> 00:16:30,800 Speaker 1: So we get big numbers when you have big countries. 317 00:16:31,200 --> 00:16:36,160 Speaker 1: But so so Ferguson made this estimate, and you know, 318 00:16:36,200 --> 00:16:38,680 Speaker 1: and that people around him made this estimate and they 319 00:16:38,720 --> 00:16:43,760 Speaker 1: didn't really know what the numbers were. Okay, that is forgivable, 320 00:16:43,840 --> 00:16:46,520 Speaker 1: by the way, it's early in an epidemic. You are 321 00:16:46,640 --> 00:16:49,720 Speaker 1: you are, you're guessing. You're going with you know, sort 322 00:16:49,760 --> 00:16:52,960 Speaker 1: of dirty data from China. You don't really have much 323 00:16:53,000 --> 00:16:56,840 Speaker 1: from a western countries. Yet it is forgivable. What is 324 00:16:56,880 --> 00:17:01,400 Speaker 1: not forgivable is when more data comes in and you 325 00:17:01,600 --> 00:17:05,480 Speaker 1: update not to tell people the truth. And Ferguson and 326 00:17:05,560 --> 00:17:08,600 Speaker 1: this was the tweet actually that got me noticed more 327 00:17:08,640 --> 00:17:11,520 Speaker 1: than any other. This was this was about ten days 328 00:17:11,560 --> 00:17:14,280 Speaker 1: after that first paper came out. So Ferguson, who had 329 00:17:14,320 --> 00:17:19,560 Speaker 1: gotten the coronavirus By this time, Umu was testifying remotely 330 00:17:19,840 --> 00:17:22,679 Speaker 1: to a British parliamentary committee and he said, oh, you 331 00:17:22,720 --> 00:17:24,920 Speaker 1: know how I said half a million people might die 332 00:17:25,040 --> 00:17:28,040 Speaker 1: from the coronavirus if we didn't do anything in the UK. 333 00:17:28,760 --> 00:17:32,840 Speaker 1: Let's make it and you know there will be no 334 00:17:33,520 --> 00:17:35,400 Speaker 1: There will be a spike and it will be over 335 00:17:35,440 --> 00:17:38,480 Speaker 1: by mid April or late April, and after that I 336 00:17:38,520 --> 00:17:41,320 Speaker 1: think it's going to be Okay. That was basically what 337 00:17:41,359 --> 00:17:44,640 Speaker 1: he said. Okay, it was a It was a monumental 338 00:17:44,760 --> 00:17:48,159 Speaker 1: change in his forecast that he that he that he 339 00:17:48,320 --> 00:17:51,200 Speaker 1: tried to pass off as well, this is just kind 340 00:17:51,200 --> 00:17:54,000 Speaker 1: of an adjustment here, and this is because we locked down. 341 00:17:54,080 --> 00:17:57,760 Speaker 1: It's not true. Okay, he made a monumental change in 342 00:17:57,800 --> 00:18:01,639 Speaker 1: the forecast, and the media used to acknowledge it or 343 00:18:02,000 --> 00:18:04,600 Speaker 1: or or ask him what had happened, or call him on. 344 00:18:05,080 --> 00:18:07,879 Speaker 1: And that was when I realized, this is just like 345 00:18:07,960 --> 00:18:11,800 Speaker 1: how your children, only the steaks are much much bigger. 346 00:18:11,840 --> 00:18:15,159 Speaker 1: This has become a politicized issue already. This is about 347 00:18:15,240 --> 00:18:17,720 Speaker 1: people who want us to be in lockdown. They want 348 00:18:17,720 --> 00:18:20,479 Speaker 1: to push us there, um you know, for whatever reason, 349 00:18:20,880 --> 00:18:24,199 Speaker 1: because they're genuinely afraid, or because you know, they have 350 00:18:24,359 --> 00:18:28,320 Speaker 1: other uh, you know, they have other motivations which which 351 00:18:28,320 --> 00:18:31,800 Speaker 1: are not necessarily obvious to me at this time. But 352 00:18:31,800 --> 00:18:33,760 Speaker 1: but there's going to be a fight here and it's 353 00:18:33,840 --> 00:18:36,399 Speaker 1: not only going to be about science. And that was 354 00:18:36,640 --> 00:18:39,320 Speaker 1: and that was something that I knew could happen because 355 00:18:39,320 --> 00:18:41,960 Speaker 1: of how your children be sure to catch live editions 356 00:18:42,000 --> 00:18:44,720 Speaker 1: about kicked the coverage with Clay Travis week days at 357 00:18:44,760 --> 00:18:48,920 Speaker 1: six am Eastern, three am Pacific. Why did and this 358 00:18:49,000 --> 00:18:51,720 Speaker 1: is becomes a fascinating question. We're talking with Alex Brinson. 359 00:18:52,119 --> 00:18:54,520 Speaker 1: You can go read his two different books that he's 360 00:18:54,520 --> 00:18:56,520 Speaker 1: published on Amazon, which I'm gonna get to you here 361 00:18:56,520 --> 00:19:01,160 Speaker 1: in a moment. But you've elucidated one of major issues 362 00:19:01,200 --> 00:19:03,800 Speaker 1: that I think has gone with the coverage of the 363 00:19:03,800 --> 00:19:06,280 Speaker 1: coronavirus from the get go. And I'm curious, as a 364 00:19:06,320 --> 00:19:09,960 Speaker 1: member of the former New York Times media establishment, for 365 00:19:10,080 --> 00:19:12,359 Speaker 1: lack of a better phrase, how you would analyze this. 366 00:19:13,000 --> 00:19:18,359 Speaker 1: It seems to me that there are anecdotal outlier cases 367 00:19:18,480 --> 00:19:22,160 Speaker 1: which have driven the coverage of the coronavirus since this started. 368 00:19:22,240 --> 00:19:25,440 Speaker 1: In other words, thirty five year old person dies, Oh 369 00:19:25,480 --> 00:19:28,199 Speaker 1: my god, pregnant woman's got it, her baby's got it 370 00:19:28,320 --> 00:19:32,080 Speaker 1: now and when we actually look at the raw data, 371 00:19:32,480 --> 00:19:35,240 Speaker 1: the numbers tell us a different story, and a much 372 00:19:35,280 --> 00:19:39,000 Speaker 1: more calming story. And so, for instance, Uh, it seems 373 00:19:39,040 --> 00:19:42,399 Speaker 1: to me that emotion has totally overtaken the way that 374 00:19:42,440 --> 00:19:45,240 Speaker 1: this story was covered. And I thought it was crystallized 375 00:19:45,240 --> 00:19:47,040 Speaker 1: when the New York Times, on I think it was 376 00:19:47,119 --> 00:19:51,080 Speaker 1: Memorial Day weekend writes like a hundred thousand deaths and 377 00:19:51,200 --> 00:19:54,639 Speaker 1: incalculable lost as their headline with just a bunch of 378 00:19:54,680 --> 00:19:58,440 Speaker 1: different names on it. What has happened here? Why has 379 00:19:58,520 --> 00:20:03,600 Speaker 1: a motion overtaken the media? Why has logic and probability 380 00:20:03,640 --> 00:20:05,679 Speaker 1: and all of these things not taken route? Because I 381 00:20:05,760 --> 00:20:07,560 Speaker 1: keep and I'm just gonna put this out, a lot 382 00:20:07,560 --> 00:20:11,040 Speaker 1: of people will be listening from a sports perspective. Uh, 383 00:20:11,160 --> 00:20:14,160 Speaker 1: kids driving to college campuses are more likely to die 384 00:20:14,320 --> 00:20:16,760 Speaker 1: driving to their college campus in a car accident than 385 00:20:16,800 --> 00:20:19,080 Speaker 1: they are from the coronavirus. They're more likely to die 386 00:20:19,080 --> 00:20:21,680 Speaker 1: of the flu murder. Uh, They're more likely to die 387 00:20:21,720 --> 00:20:24,399 Speaker 1: of drug overdose. They're more likely to die of drinking 388 00:20:24,440 --> 00:20:27,960 Speaker 1: too much alcohol. All of these are more dangerous threats 389 00:20:27,960 --> 00:20:30,520 Speaker 1: if you're a parent with a college age student. Yet 390 00:20:30,640 --> 00:20:32,760 Speaker 1: right now, sports are being shut down in the Big 391 00:20:32,760 --> 00:20:36,040 Speaker 1: ten and the Pack twelve because of this overwhelming fear 392 00:20:36,119 --> 00:20:39,920 Speaker 1: porn which people still can't escape. Why did the media 393 00:20:40,040 --> 00:20:43,840 Speaker 1: fail so much talking to the public about this story 394 00:20:43,920 --> 00:20:46,440 Speaker 1: and fail so much by the way that they almost 395 00:20:46,480 --> 00:20:49,919 Speaker 1: managed to destroy their own business because you know, like 396 00:20:50,040 --> 00:20:54,560 Speaker 1: fear maybe well lead, but the advertising market destroyed when 397 00:20:54,560 --> 00:20:57,760 Speaker 1: you shut down the economy, It's like your ratings may 398 00:20:57,800 --> 00:21:00,760 Speaker 1: go up on MSNBC and CNN and Fox News as 399 00:21:00,800 --> 00:21:03,480 Speaker 1: well to a certain extent, but also nobody can buy 400 00:21:03,520 --> 00:21:06,680 Speaker 1: anything because the economy is collapsed. It's like that. Yeah, 401 00:21:06,680 --> 00:21:09,840 Speaker 1: people more watched, but you almost destroyed the entire country 402 00:21:09,840 --> 00:21:12,040 Speaker 1: in the process. Why did they get it wrong? How 403 00:21:12,040 --> 00:21:16,359 Speaker 1: did this happen? Another great question? So there are several 404 00:21:16,400 --> 00:21:18,760 Speaker 1: factors to play here. First of all, don't underestimate the 405 00:21:18,760 --> 00:21:22,119 Speaker 1: amount of real raw here that there was in mid March, 406 00:21:22,240 --> 00:21:25,480 Speaker 1: late March, yes, even in early April, especially even among 407 00:21:25,560 --> 00:21:29,360 Speaker 1: people who are media members who should be more analytical 408 00:21:29,400 --> 00:21:32,080 Speaker 1: at least in my mind, and less emotion base. They 409 00:21:32,119 --> 00:21:34,480 Speaker 1: gave into it as well. Well. I wouldn't you know. 410 00:21:34,480 --> 00:21:36,439 Speaker 1: I don't think there's better people in the media have 411 00:21:36,600 --> 00:21:39,239 Speaker 1: cool heads. Yeah, maybe there's a few war reporters out 412 00:21:39,240 --> 00:21:40,880 Speaker 1: there who have cool heads. But you know, you don't 413 00:21:40,880 --> 00:21:42,719 Speaker 1: you don't get you get into media because you like, 414 00:21:43,359 --> 00:21:47,359 Speaker 1: you like action and controversy and something new every day. Okay, 415 00:21:47,359 --> 00:21:50,320 Speaker 1: it's not necessarily something that leads to to uh, you know, 416 00:21:50,440 --> 00:21:54,440 Speaker 1: a lot of like you know, reasoned analysis exactly exactly. 417 00:21:54,600 --> 00:21:57,480 Speaker 1: But but so remember it was bad in New York 418 00:21:57,560 --> 00:22:00,719 Speaker 1: for a few days. Okay, there were there were you 419 00:22:00,720 --> 00:22:03,280 Speaker 1: know that the the the bubble of excess death was real. 420 00:22:03,760 --> 00:22:07,399 Speaker 1: What happened at Elmhurst was real. Now, where are things 421 00:22:07,400 --> 00:22:10,800 Speaker 1: that we didn't understand at that time, including that, you know, 422 00:22:10,840 --> 00:22:13,439 Speaker 1: the rush to put them up people on ventilators was 423 00:22:13,520 --> 00:22:15,760 Speaker 1: killing a bunch of people, and that the quality of 424 00:22:15,800 --> 00:22:18,679 Speaker 1: care at some of these hospitals, unfortunately, probably was not 425 00:22:18,920 --> 00:22:20,960 Speaker 1: very good. You know, these some of these some of 426 00:22:20,960 --> 00:22:23,600 Speaker 1: the city's municipal hospitals. You know, they struggle at the 427 00:22:23,600 --> 00:22:25,960 Speaker 1: best of times, and these were not the best of times. 428 00:22:26,000 --> 00:22:29,720 Speaker 1: But but but but the fear, the fear was real. Okay, 429 00:22:30,240 --> 00:22:35,199 Speaker 1: and so and and people very very quickly decided to 430 00:22:35,240 --> 00:22:38,800 Speaker 1: blame Donald Trump. You have failed us, and it is 431 00:22:38,840 --> 00:22:42,280 Speaker 1: your fault that people are dying. And that became a 432 00:22:42,400 --> 00:22:45,560 Speaker 1: very comforting narrative for people in the media, and it 433 00:22:45,680 --> 00:22:47,760 Speaker 1: is not it is not giving anything away to say 434 00:22:47,760 --> 00:22:51,720 Speaker 1: that outside of Fox, Donald Trump is not just not light, 435 00:22:52,000 --> 00:22:55,000 Speaker 1: but that he is despised by many people in the media, 436 00:22:55,280 --> 00:22:59,600 Speaker 1: and so and so. So they started as a genuine 437 00:23:00,280 --> 00:23:04,560 Speaker 1: fear of the unknown. Okay, And and then and and 438 00:23:04,600 --> 00:23:06,360 Speaker 1: but you know, I was in the city in March. Okay, 439 00:23:06,400 --> 00:23:09,639 Speaker 1: I don't I I you know, my uh my mother 440 00:23:09,760 --> 00:23:12,359 Speaker 1: and brother live in New York City, uh, you know, 441 00:23:12,480 --> 00:23:14,560 Speaker 1: and I was in to see I was in to 442 00:23:14,600 --> 00:23:17,640 Speaker 1: see them a bunch and it was it was scary, 443 00:23:17,840 --> 00:23:20,199 Speaker 1: you know, do not not because of what was happening, 444 00:23:20,200 --> 00:23:22,959 Speaker 1: but just because of the emptiness of the streets and 445 00:23:23,000 --> 00:23:26,040 Speaker 1: this feeling that, you know, the end is upon us. Okay. 446 00:23:26,200 --> 00:23:28,920 Speaker 1: So that was That's not five months ago, though, Clay. 447 00:23:28,960 --> 00:23:31,600 Speaker 1: So what's happened since then? Well, unfortunately a couple of 448 00:23:31,600 --> 00:23:34,320 Speaker 1: things in that. First of all, people in the media, 449 00:23:34,520 --> 00:23:37,239 Speaker 1: for the most part, there are exceptions, but are not 450 00:23:37,240 --> 00:23:40,080 Speaker 1: good at math. Okay, they're not good at statistics. They're 451 00:23:40,119 --> 00:23:44,280 Speaker 1: not good at math, and they and they haven't ever 452 00:23:44,440 --> 00:23:49,280 Speaker 1: put this in context, either for themselves or for anybody else. So, 453 00:23:49,280 --> 00:23:52,480 Speaker 1: so Clay forty five children under the age of fifteen 454 00:23:52,640 --> 00:23:55,439 Speaker 1: died of coronavirus as of August first had died of 455 00:23:55,440 --> 00:23:58,880 Speaker 1: coronavirus in the United States. And and you know, forty 456 00:23:58,960 --> 00:24:00,879 Speaker 1: five children. That that's had like a lot of children, 457 00:24:00,920 --> 00:24:03,720 Speaker 1: and obviously slowly five children, slowly, five children too many. 458 00:24:03,920 --> 00:24:07,879 Speaker 1: But thirteen thousand children in that age group have died 459 00:24:07,960 --> 00:24:11,000 Speaker 1: in the United States in the last six months. So 460 00:24:11,040 --> 00:24:13,919 Speaker 1: that's one in three hundred. More children have died of 461 00:24:14,000 --> 00:24:17,439 Speaker 1: drowning and in car accidents and um and of and 462 00:24:17,520 --> 00:24:20,480 Speaker 1: of abuse and neglect and of cancer and of many 463 00:24:20,600 --> 00:24:25,040 Speaker 1: many other things. So but journalists have never put these 464 00:24:25,080 --> 00:24:27,479 Speaker 1: numbers in context. I don't think they. I don't think 465 00:24:27,480 --> 00:24:29,879 Speaker 1: they understand them. And I think the handful who do 466 00:24:30,040 --> 00:24:33,320 Speaker 1: understand them, for the most part politically, are not interested 467 00:24:33,640 --> 00:24:37,399 Speaker 1: in offering context. Another thing that happened with the media 468 00:24:37,960 --> 00:24:40,760 Speaker 1: is that the media quickly realized, and this is you 469 00:24:40,760 --> 00:24:43,280 Speaker 1: can see it, okay, it's it's overt on places like 470 00:24:43,359 --> 00:24:46,800 Speaker 1: CNN and MSNBC, that this was the perfect issue to 471 00:24:46,880 --> 00:24:51,080 Speaker 1: beat Donald Trump over the head with because Trump, you know, 472 00:24:51,160 --> 00:24:55,119 Speaker 1: and I'm a registered political independent, Okay, um, you know, 473 00:24:55,240 --> 00:24:58,919 Speaker 1: my core political philosophy if it's anything is It's impossible 474 00:24:58,960 --> 00:25:02,919 Speaker 1: to be too cynical about our politics these days, really, 475 00:25:03,480 --> 00:25:07,280 Speaker 1: But but the media, the media saw that Trump's sort of, 476 00:25:07,359 --> 00:25:10,639 Speaker 1: you know, his his arrogance and his bluff and his 477 00:25:10,720 --> 00:25:13,159 Speaker 1: desire to make a joke out of things that played 478 00:25:13,280 --> 00:25:17,080 Speaker 1: incredibly badly when it came to this, and and so, 479 00:25:17,440 --> 00:25:19,520 Speaker 1: and they realized it, and they have and they have 480 00:25:19,640 --> 00:25:22,720 Speaker 1: nearly destroyed him with it, and so that's been very 481 00:25:22,840 --> 00:25:27,119 Speaker 1: very effective for them. So so to me, what happened 482 00:25:27,119 --> 00:25:30,760 Speaker 1: in March and April is forgivable. Okay, it's forgivable that 483 00:25:30,800 --> 00:25:33,920 Speaker 1: a bunch of people panicked, and some of us recognized 484 00:25:33,960 --> 00:25:37,680 Speaker 1: earlier than others that this wasn't all it was made 485 00:25:37,680 --> 00:25:39,960 Speaker 1: out to be, and that this was going to be manageable, 486 00:25:39,960 --> 00:25:41,960 Speaker 1: and that the hospitals are not going to be overrun, 487 00:25:42,280 --> 00:25:44,560 Speaker 1: and it really should be something that we as a 488 00:25:44,640 --> 00:25:48,840 Speaker 1: society should just should just try to go about our 489 00:25:48,880 --> 00:25:52,480 Speaker 1: business and let the medical system handle this as as 490 00:25:52,560 --> 00:25:55,919 Speaker 1: has happened now in places like Florida and Arizona, and 491 00:25:56,000 --> 00:25:59,399 Speaker 1: some people didn't realize as quickly. But everything that's happened 492 00:25:59,520 --> 00:26:04,960 Speaker 1: since has been to a greater or lesser extent politically 493 00:26:05,040 --> 00:26:08,080 Speaker 1: driven and that makes it very hard for me um 494 00:26:08,119 --> 00:26:11,800 Speaker 1: to accept. This is also fascinating to me. So let's 495 00:26:11,800 --> 00:26:15,480 Speaker 1: go back to uh, let's go back to Florida and Arizona, 496 00:26:15,480 --> 00:26:18,720 Speaker 1: which you just mentioned. Florida and Arizona as we speak. 497 00:26:18,800 --> 00:26:23,159 Speaker 1: On August seventeen, effectively, again, Ron de Santis came out, 498 00:26:23,600 --> 00:26:25,560 Speaker 1: I'm gonna read some of the data points that he 499 00:26:25,640 --> 00:26:28,160 Speaker 1: just tweeted, and frankly, he had to tweet it because 500 00:26:28,160 --> 00:26:31,360 Speaker 1: I don't think anybody would cover it otherwise, which goes 501 00:26:31,400 --> 00:26:34,720 Speaker 1: into the media coverage of this on a straightforward basis. 502 00:26:34,760 --> 00:26:37,560 Speaker 1: So I'm reading directly from front. De santiss tweets earlier 503 00:26:37,600 --> 00:26:40,679 Speaker 1: today he said Florida's reporting the lowest number of cases 504 00:26:41,720 --> 00:26:45,240 Speaker 1: and sixty since mid June. Emergency room visits for COVID 505 00:26:45,280 --> 00:26:49,240 Speaker 1: like illness or down sixty percent since July seven. Hospital 506 00:26:49,240 --> 00:26:54,280 Speaker 1: admissions for COVID are down sixty since July. The number 507 00:26:54,400 --> 00:26:58,760 Speaker 1: of COVID positive patients currently hospitalized is down fort since 508 00:26:58,880 --> 00:27:02,760 Speaker 1: July one, and they have twenty six point four percent 509 00:27:02,800 --> 00:27:06,480 Speaker 1: of all hospital beds available in the state. Of all 510 00:27:06,760 --> 00:27:10,800 Speaker 1: ICU beds, the pre pandemic percentages, by the way, twelve 511 00:27:10,840 --> 00:27:14,080 Speaker 1: point six percent available nine point three percent of ICU 512 00:27:14,160 --> 00:27:19,520 Speaker 1: beds available. So the worst case scenario basically happen for 513 00:27:19,640 --> 00:27:23,200 Speaker 1: as you would call it, team apocalypse in Florida and 514 00:27:23,280 --> 00:27:28,480 Speaker 1: in Arizona, and we handled it without really a substantial 515 00:27:28,560 --> 00:27:31,960 Speaker 1: loss of life. Now, nothing like what happened in New 516 00:27:32,040 --> 00:27:35,240 Speaker 1: York and in New Jersey. As we look forward with 517 00:27:35,280 --> 00:27:38,840 Speaker 1: the data now they're from Florida in Arizona, does anything 518 00:27:39,000 --> 00:27:42,600 Speaker 1: change or are people so committed to the idea that 519 00:27:42,680 --> 00:27:46,840 Speaker 1: the coronavirus is, uh, you know, the most devastating thing 520 00:27:46,880 --> 00:27:49,960 Speaker 1: that's going to happen in anybody's lifetime, that there's no 521 00:27:50,080 --> 00:27:53,240 Speaker 1: ability to acknowledge that we can start to get back 522 00:27:53,240 --> 00:27:56,560 Speaker 1: to normalcy now. I mean, so that's a that's a 523 00:27:56,560 --> 00:27:58,479 Speaker 1: political question. I don't have the answer that I've been 524 00:27:58,520 --> 00:28:01,399 Speaker 1: leaving for for the reality shed in you know, for 525 00:28:01,600 --> 00:28:05,399 Speaker 1: three months plus now, and you would think that you're 526 00:28:05,440 --> 00:28:09,000 Speaker 1: you're right, Like the worst case happened, Okay, the states unlocked. 527 00:28:09,080 --> 00:28:12,359 Speaker 1: There was rapid, uncontrolled spread all over the sun Belt 528 00:28:12,880 --> 00:28:17,520 Speaker 1: and and and nothing terrible and the fraction of the 529 00:28:17,560 --> 00:28:20,840 Speaker 1: deaths of New York and New Jersey as a result, 530 00:28:21,400 --> 00:28:23,600 Speaker 1: that's right, I think, you know, if the Florida peak 531 00:28:23,640 --> 00:28:27,119 Speaker 1: death day might have been three hundred. Um you know, Texas, 532 00:28:27,200 --> 00:28:29,520 Speaker 1: I think around three hundred. Also, you know, this is 533 00:28:29,560 --> 00:28:31,920 Speaker 1: a fraction of New York and and and it looks 534 00:28:31,960 --> 00:28:34,960 Speaker 1: like death or death in Arizona are definitely trending down. Okay, 535 00:28:35,000 --> 00:28:38,040 Speaker 1: Florida Texas have been a couple of weeks behind Arizona, 536 00:28:38,080 --> 00:28:39,960 Speaker 1: So they may be they may be still on the 537 00:28:39,960 --> 00:28:42,040 Speaker 1: flat part of the plateau, or they may be trending 538 00:28:42,080 --> 00:28:44,280 Speaker 1: down too. But it is going to be harder and 539 00:28:44,360 --> 00:28:48,440 Speaker 1: harder to argue that this that this is not over. Okay, 540 00:28:48,480 --> 00:28:50,760 Speaker 1: if it's if it's certainly in the sun Belt, and 541 00:28:50,800 --> 00:28:53,840 Speaker 1: that and that we didn't do anything. Those states really 542 00:28:53,840 --> 00:28:56,600 Speaker 1: didn't do anything. So you're hearing somehow that the masked 543 00:28:56,640 --> 00:28:59,440 Speaker 1: mandates made the difference, or closing bars made the difference. 544 00:28:59,480 --> 00:29:01,719 Speaker 1: I mean, this is this is nonsense. First of all, 545 00:29:01,720 --> 00:29:03,400 Speaker 1: a lot of people in the states were wearing masks 546 00:29:03,440 --> 00:29:06,560 Speaker 1: before the mandates. And second of all, bar closings like 547 00:29:06,720 --> 00:29:09,880 Speaker 1: that's that's what stopped this this incredible, once in a 548 00:29:09,920 --> 00:29:12,520 Speaker 1: lifetime epidemic. We closed a few bars for a couple 549 00:29:12,520 --> 00:29:14,520 Speaker 1: of weeks. I mean, I mean, you know, people are 550 00:29:14,520 --> 00:29:17,880 Speaker 1: saying stuff with a straight face. So here's here's here's 551 00:29:17,880 --> 00:29:20,080 Speaker 1: what I've wondered. I've wondered how long it will take 552 00:29:20,080 --> 00:29:22,680 Speaker 1: for the media to acknowledge reality, and then I've wondered 553 00:29:22,720 --> 00:29:24,800 Speaker 1: how long it will take from that reality to percolate 554 00:29:24,840 --> 00:29:28,120 Speaker 1: into the people who are so afraid still right now, 555 00:29:28,200 --> 00:29:30,600 Speaker 1: And it does seem to me like the divide is 556 00:29:30,600 --> 00:29:33,880 Speaker 1: getting sharper, The divide between people who are afraid and 557 00:29:33,960 --> 00:29:37,640 Speaker 1: not afraid is getting sharper, and I and I don't 558 00:29:37,680 --> 00:29:40,720 Speaker 1: know what fixes that. We're talking to Alex Berenson. You 559 00:29:40,720 --> 00:29:43,360 Speaker 1: can follow him on Twitter. I'll tweet out the link 560 00:29:43,400 --> 00:29:46,480 Speaker 1: to his profile. He's had incredible data analysis from the 561 00:29:46,520 --> 00:29:51,960 Speaker 1: get go. Okay, what made you willing to question the 562 00:29:52,080 --> 00:29:55,640 Speaker 1: overriding narrative. I've obviously done it in the world of sports, 563 00:29:55,720 --> 00:29:59,080 Speaker 1: and it's astounding to me how many members of what 564 00:29:59,200 --> 00:30:02,280 Speaker 1: I call the blue checkmark brigade in sports media have 565 00:30:02,480 --> 00:30:06,240 Speaker 1: been buying into these apocalyptic theories from the get go, 566 00:30:06,800 --> 00:30:09,680 Speaker 1: such that they get their furious at me for sharing 567 00:30:09,720 --> 00:30:12,680 Speaker 1: any kind of positive news, for suggesting that sports can 568 00:30:12,720 --> 00:30:16,000 Speaker 1: be played. I've labeled them all Corona bros. In the 569 00:30:16,040 --> 00:30:20,240 Speaker 1: sports media. It's like they're rooting for the worst possible outcome. 570 00:30:20,400 --> 00:30:23,200 Speaker 1: Right the minute that an athlete tests positive, they're the 571 00:30:23,240 --> 00:30:25,280 Speaker 1: first ones to run to Twitter and be like, oh 572 00:30:25,320 --> 00:30:26,920 Speaker 1: my god. You know, look at what's happened with the 573 00:30:26,960 --> 00:30:30,000 Speaker 1: Miami Marlins. A bunch of healthy guys are testing positive 574 00:30:30,040 --> 00:30:32,120 Speaker 1: for a virus they never would have known they had 575 00:30:32,560 --> 00:30:35,200 Speaker 1: unless we were testing them aggressively, right. I mean that's 576 00:30:35,240 --> 00:30:40,320 Speaker 1: the reality, and so it's crazy. In my universe, there's 577 00:30:40,360 --> 00:30:44,480 Speaker 1: hardly anybody sharing actual facts and combating what I would 578 00:30:44,480 --> 00:30:47,080 Speaker 1: call the fear porn, which tries to make it such 579 00:30:47,120 --> 00:30:49,840 Speaker 1: that sports can't be played, that your son can't play 580 00:30:49,880 --> 00:30:52,680 Speaker 1: little League, that your daughter can't play soccer. All these 581 00:30:52,720 --> 00:30:54,720 Speaker 1: things are certainly get to schools, which I want to 582 00:30:54,720 --> 00:30:57,480 Speaker 1: get to in a moment. Why do you think that 583 00:30:57,480 --> 00:31:00,120 Speaker 1: that the media? And I'm curious on this perspective from you. 584 00:31:00,560 --> 00:31:02,760 Speaker 1: It used to be you said, you know, be cynical, 585 00:31:02,880 --> 00:31:05,520 Speaker 1: be skeptical. I would say that in general, I am 586 00:31:05,560 --> 00:31:08,920 Speaker 1: a skeptic. I tend to be skeptical of every and 587 00:31:09,000 --> 00:31:11,640 Speaker 1: any and everything. Maybe that's my legal background, maybe that's 588 00:31:11,760 --> 00:31:15,360 Speaker 1: my natural persona. But it seems to me that the 589 00:31:15,440 --> 00:31:21,200 Speaker 1: media completely abandoned that natural skepticism and not only abandoned 590 00:31:21,200 --> 00:31:25,800 Speaker 1: the natural skepticism, but severely policed anyone who did it 591 00:31:26,000 --> 00:31:31,720 Speaker 1: by into the overriding narrative of complete danger, instead of 592 00:31:31,760 --> 00:31:35,120 Speaker 1: being rebels, or instead of being people who pushed back 593 00:31:35,160 --> 00:31:37,760 Speaker 1: against the tide, which I think is what you would 594 00:31:37,800 --> 00:31:42,560 Speaker 1: hope journalists would do. When did journalists become the people 595 00:31:42,600 --> 00:31:45,960 Speaker 1: who are out there enforcing what opinions people can have? 596 00:31:46,360 --> 00:31:49,280 Speaker 1: And how has it impacted you? In what I'm imagining, 597 00:31:49,360 --> 00:31:52,160 Speaker 1: You're now the black sheep of the New York Times fraternity. 598 00:31:52,400 --> 00:31:57,360 Speaker 1: You're completely ostracized. So so you know, it fascinates man. 599 00:31:57,440 --> 00:31:59,320 Speaker 1: And I don't know how much you hate you get 600 00:31:59,320 --> 00:32:01,760 Speaker 1: I I'm engine you get a lot of too, yes, 601 00:32:04,120 --> 00:32:06,240 Speaker 1: Like I want their grandmas to die, right, That's the 602 00:32:06,280 --> 00:32:07,960 Speaker 1: thing I get the most. Like you don't care about 603 00:32:08,000 --> 00:32:09,960 Speaker 1: old people dying, and I would saying no, I wish 604 00:32:09,960 --> 00:32:12,640 Speaker 1: everybody was immortal, right, I wish? But you know, two 605 00:32:12,640 --> 00:32:15,480 Speaker 1: point eight million people die every day in this every year, 606 00:32:15,520 --> 00:32:19,480 Speaker 1: in this country, undred a day. Everything has to be 607 00:32:19,560 --> 00:32:23,920 Speaker 1: balanced contextually. This idea that the coronavirus has to dictate 608 00:32:24,000 --> 00:32:27,400 Speaker 1: every decision that we make as social policy for the 609 00:32:27,560 --> 00:32:31,320 Speaker 1: entire year is crazy to me. It's a childlike understanding 610 00:32:31,320 --> 00:32:34,760 Speaker 1: of nuance and complexity. Yet I see people who value 611 00:32:34,880 --> 00:32:39,120 Speaker 1: their own knowledge of nuance and complexity fully embracing it, 612 00:32:39,160 --> 00:32:41,320 Speaker 1: and I just wonder what in the world is going 613 00:32:41,360 --> 00:32:44,440 Speaker 1: on in their brains. Yeah, so, I mean, look, look, 614 00:32:44,480 --> 00:32:47,680 Speaker 1: I mean I could call associated parent. You know, people 615 00:32:47,720 --> 00:32:49,880 Speaker 1: people tell me, people have told me, you know, not 616 00:32:49,880 --> 00:32:51,640 Speaker 1: not the blue checks so much. I hope some of 617 00:32:51,640 --> 00:32:54,280 Speaker 1: the checks said they hope I die. Yeah, yeah, people 618 00:32:54,440 --> 00:32:57,400 Speaker 1: people regularly blue check Margargade regularly. They remembers saying I 619 00:32:57,400 --> 00:32:58,600 Speaker 1: hope you get this and I hope you die. They 620 00:32:58,680 --> 00:33:00,520 Speaker 1: even some of the people out there, have you even 621 00:33:00,520 --> 00:33:02,760 Speaker 1: taken a step further. I've got three young kids and 622 00:33:02,800 --> 00:33:05,680 Speaker 1: they're in school now, and you know when I mentioned that, 623 00:33:05,720 --> 00:33:07,480 Speaker 1: they're like, I hope your kids get sick and die. 624 00:33:07,560 --> 00:33:10,880 Speaker 1: That would serve you, right, Like whot children to die? Like, 625 00:33:10,920 --> 00:33:13,960 Speaker 1: I mean, this is crazy to me, That's right, It's crazy. 626 00:33:13,960 --> 00:33:16,200 Speaker 1: I mean, and you know, my, my somebody and somebody 627 00:33:16,600 --> 00:33:19,200 Speaker 1: somebody said, well, Fauci says he's getting death threats. It's like, well, 628 00:33:19,400 --> 00:33:21,200 Speaker 1: you know what, you know the old joke, if you 629 00:33:21,240 --> 00:33:23,040 Speaker 1: ain't cheating, you ain't trying at this point, if you 630 00:33:23,080 --> 00:33:25,720 Speaker 1: ain't getting death threats, I get death threats every day, 631 00:33:25,720 --> 00:33:31,840 Speaker 1: come on all the time, right, So so you know, look, 632 00:33:32,400 --> 00:33:37,160 Speaker 1: there's Trump that the Trump hatred is enormous, and the 633 00:33:37,480 --> 00:33:40,280 Speaker 1: and the sort of innumeracy of the media is enormous, 634 00:33:40,360 --> 00:33:44,120 Speaker 1: and I guess, I guess you know, the group think 635 00:33:44,240 --> 00:33:48,400 Speaker 1: is enormous, okay, and and people and it's unfortunate because 636 00:33:48,520 --> 00:33:51,520 Speaker 1: it means that you know, there there are there are 637 00:33:51,840 --> 00:33:55,560 Speaker 1: many social media making it worse. Is social media making 638 00:33:55,600 --> 00:33:58,040 Speaker 1: group think worse? In your mind? As somebody who worked 639 00:33:58,040 --> 00:33:59,840 Speaker 1: at The New York Times in a pre basically so 640 00:34:00,200 --> 00:34:03,400 Speaker 1: media era. Oh absolutely, it's made it much worse. And 641 00:34:03,440 --> 00:34:06,040 Speaker 1: there's something else that's happening which is not much discussed, 642 00:34:06,040 --> 00:34:08,120 Speaker 1: but which has definitely been a real problem at the 643 00:34:08,120 --> 00:34:09,480 Speaker 1: New York Times. And I think it's a problem at 644 00:34:09,480 --> 00:34:13,680 Speaker 1: workplaces in general, which is so texting makes it possible 645 00:34:13,920 --> 00:34:16,560 Speaker 1: to run conspiracies. And I mean, and I mean, you know, 646 00:34:16,600 --> 00:34:18,360 Speaker 1: I mean a real conspiracy in a way that you 647 00:34:18,400 --> 00:34:21,040 Speaker 1: couldn't before another There can be five people in a 648 00:34:21,160 --> 00:34:23,000 Speaker 1: room and one of them has an opinion that the 649 00:34:23,040 --> 00:34:26,000 Speaker 1: other four don't like, and the other four are able 650 00:34:26,040 --> 00:34:29,479 Speaker 1: to have a conversation about that fifth person in front 651 00:34:29,520 --> 00:34:34,160 Speaker 1: of him without him knowing, okay, And that makes it 652 00:34:34,360 --> 00:34:38,320 Speaker 1: easier to ostracize. It makes it easier to drive people 653 00:34:38,360 --> 00:34:41,560 Speaker 1: out because all of a sudden you say, you know what, 654 00:34:41,600 --> 00:34:43,640 Speaker 1: I'm going to tweet this, and everybody else like, okay, 655 00:34:43,719 --> 00:34:46,239 Speaker 1: let's you know, let's do it, let's jump in, or 656 00:34:46,360 --> 00:34:48,520 Speaker 1: or you know, it isn't even quite that over, it's 657 00:34:48,560 --> 00:34:50,800 Speaker 1: I'm going to tweet this, and you send it around 658 00:34:50,840 --> 00:34:53,120 Speaker 1: to the other three people who don't like the last 659 00:34:53,120 --> 00:34:55,160 Speaker 1: person in the room in there, and they just jump off. 660 00:34:55,719 --> 00:34:58,359 Speaker 1: So so there's been there's you know, I'm sure you've 661 00:34:58,400 --> 00:35:00,759 Speaker 1: heard it. Uh, you know it's called pilot, right, So 662 00:35:00,880 --> 00:35:03,439 Speaker 1: don pil is when you know a thousand people tell 663 00:35:03,480 --> 00:35:06,279 Speaker 1: you that you should never speak again. Yes, okay, And 664 00:35:06,320 --> 00:35:08,279 Speaker 1: you have to be a certain kind of person to 665 00:35:08,400 --> 00:35:13,000 Speaker 1: decide I don't care, right, and which you are? And 666 00:35:13,080 --> 00:35:15,320 Speaker 1: I think I am too, like I just I genuinely 667 00:35:15,360 --> 00:35:18,800 Speaker 1: don't care. I mean again, I don't see this as partisan. 668 00:35:18,840 --> 00:35:20,440 Speaker 1: I don't see it as democrat. I don't see it 669 00:35:20,480 --> 00:35:22,919 Speaker 1: as republican. You said you're a registered independent. I worked 670 00:35:22,920 --> 00:35:27,560 Speaker 1: on Al Gore's presidential campaign. I wasn't particularly political. I've 671 00:35:27,560 --> 00:35:30,520 Speaker 1: never voted for a Republican president. But I look at 672 00:35:30,520 --> 00:35:32,120 Speaker 1: all this and I'm like, you know, I'm a First 673 00:35:32,160 --> 00:35:35,520 Speaker 1: Amendment absolutist, and I love rigorous debate. And to me, 674 00:35:35,560 --> 00:35:37,239 Speaker 1: and I want to get to the analogy you've made 675 00:35:37,480 --> 00:35:39,960 Speaker 1: to me, I say, the decision to go to war 676 00:35:40,000 --> 00:35:42,879 Speaker 1: in Iraq is the biggest failure in the twenty first 677 00:35:42,960 --> 00:35:46,360 Speaker 1: century prior to our response to the coronavirus from a 678 00:35:46,400 --> 00:35:49,720 Speaker 1: social policy perspective. You've gone even further back and said 679 00:35:49,800 --> 00:35:52,640 Speaker 1: you think in years to come, we'll look back on 680 00:35:52,719 --> 00:35:56,040 Speaker 1: our response to the coronavirus as the worst decision in 681 00:35:56,120 --> 00:36:00,080 Speaker 1: American policy since the Vietnam War. Uh. That's fast an 682 00:36:00,080 --> 00:36:04,320 Speaker 1: eating to me, because what it would require is analysis 683 00:36:04,400 --> 00:36:08,560 Speaker 1: and recognition from so many people that they misdiagnosed and 684 00:36:08,680 --> 00:36:13,400 Speaker 1: misresponded to this instance in the Vietnam War because the 685 00:36:13,400 --> 00:36:17,200 Speaker 1: opposition was liberal. It seems like the media was willing 686 00:36:17,239 --> 00:36:19,359 Speaker 1: to acknowledge that because they were like, hey, we got 687 00:36:19,400 --> 00:36:23,000 Speaker 1: this one right. I think predominantly liberal media is not 688 00:36:23,120 --> 00:36:26,080 Speaker 1: going to be willing to acknowledge it with the coronavirus 689 00:36:26,120 --> 00:36:29,000 Speaker 1: because it wasn't the people who were liberal who were 690 00:36:29,080 --> 00:36:32,759 Speaker 1: leading the charge necessarily on Oh my god, this response 691 00:36:33,640 --> 00:36:36,960 Speaker 1: is totally ludicrous, right, No, it's gonna be very very 692 00:36:37,000 --> 00:36:39,640 Speaker 1: hard to get people to admit that. And and you 693 00:36:39,640 --> 00:36:42,719 Speaker 1: know what's going to happen is the people who don't 694 00:36:42,719 --> 00:36:44,280 Speaker 1: want to admit it are just gonna say a hundred 695 00:36:47,160 --> 00:36:49,000 Speaker 1: eight wherever it is that we we top out on 696 00:36:49,040 --> 00:36:53,560 Speaker 1: this again without acknowledging that that half those people were 697 00:36:53,560 --> 00:36:56,840 Speaker 1: in nursing homes and had a life expectancy in months, 698 00:36:57,320 --> 00:36:59,920 Speaker 1: and that a significant portion of the rest, we're really 699 00:37:00,280 --> 00:37:04,879 Speaker 1: very shick. Okay that that that In other words, if 700 00:37:04,920 --> 00:37:07,799 Speaker 1: you look ahead to next year, for instance, the death 701 00:37:07,880 --> 00:37:10,640 Speaker 1: rate may well be down or even at the end 702 00:37:10,680 --> 00:37:12,879 Speaker 1: of the months of this year, depending how on how 703 00:37:12,920 --> 00:37:15,879 Speaker 1: things go, because the people who got the coronavirus and 704 00:37:15,920 --> 00:37:18,279 Speaker 1: died may have died a month or two earlier than 705 00:37:18,320 --> 00:37:21,920 Speaker 1: they otherwise were. But we're not talking about, as you said, 706 00:37:22,200 --> 00:37:24,880 Speaker 1: kids under fifteen. When you look at the total number 707 00:37:25,000 --> 00:37:27,880 Speaker 1: of years loss of life, we're not talking about a 708 00:37:27,880 --> 00:37:30,760 Speaker 1: massive amount because the average person dying of the coronavirus 709 00:37:30,880 --> 00:37:33,759 Speaker 1: is older than the average age of person dying of 710 00:37:33,760 --> 00:37:37,120 Speaker 1: all causes. That's right, And at the same time, they 711 00:37:37,160 --> 00:37:39,920 Speaker 1: will be unwilling to admit the damage of the lockdown, 712 00:37:39,960 --> 00:37:43,200 Speaker 1: which has been so enormous. And this is something you know, 713 00:37:43,280 --> 00:37:45,719 Speaker 1: I think I might see list, you know as much 714 00:37:45,760 --> 00:37:49,200 Speaker 1: as anybody, because people email me who are in pain. 715 00:37:49,600 --> 00:37:51,920 Speaker 1: You know, you know, this is a funny thing about Twitter. 716 00:37:52,200 --> 00:37:54,399 Speaker 1: People feel that they you know, that they that they 717 00:37:54,480 --> 00:37:57,040 Speaker 1: know me and that and that they and that they 718 00:37:57,040 --> 00:37:58,719 Speaker 1: want to and that they want to open up to me. 719 00:37:59,080 --> 00:38:01,879 Speaker 1: And there are people who are in awful pain. Now. 720 00:38:02,120 --> 00:38:04,239 Speaker 1: Now look, I'm not gonna say that, you know, these 721 00:38:04,239 --> 00:38:06,840 Speaker 1: people were perfectly happy before this happened, and you know, 722 00:38:06,920 --> 00:38:09,480 Speaker 1: coronavirus is the only problem in their lives. But what 723 00:38:09,520 --> 00:38:12,799 Speaker 1: I'm saying is that if if you have some kind 724 00:38:12,840 --> 00:38:16,480 Speaker 1: of you know, psychiatric or psychological weakness, the last five 725 00:38:16,560 --> 00:38:19,400 Speaker 1: months had been terrible for you for a lot of 726 00:38:19,400 --> 00:38:23,880 Speaker 1: people of people out there, alex have young people, according 727 00:38:23,920 --> 00:38:26,640 Speaker 1: to a recent study that I saw, have considered suicide 728 00:38:27,000 --> 00:38:30,200 Speaker 1: and suicides and drug overdoses and everything else. Is we've 729 00:38:30,239 --> 00:38:32,360 Speaker 1: taken away people's ability to go to work, to go 730 00:38:32,440 --> 00:38:34,600 Speaker 1: to school, to go to church, to go to things 731 00:38:34,600 --> 00:38:37,480 Speaker 1: that connect them to the larger fabric of society. They 732 00:38:37,520 --> 00:38:39,720 Speaker 1: have fallen apart as well, and we're not talking hardly 733 00:38:39,760 --> 00:38:41,920 Speaker 1: at all about that. We're not talking about it at all. 734 00:38:42,040 --> 00:38:44,880 Speaker 1: And just the sheer turn that some people feel from 735 00:38:45,040 --> 00:38:47,640 Speaker 1: I mean the way people have behaved and the way 736 00:38:47,800 --> 00:38:50,160 Speaker 1: people with children who haven't let their children out of 737 00:38:50,200 --> 00:38:53,360 Speaker 1: the house for for months months, that's some people have 738 00:38:53,480 --> 00:38:56,480 Speaker 1: done that. Some people haven't done that. And so you know, 739 00:38:56,560 --> 00:38:59,680 Speaker 1: people you can find stories on Twitter without trying too hard. 740 00:38:59,719 --> 00:39:03,280 Speaker 1: A will proudly saying I haven't left my apartment since March. 741 00:39:04,560 --> 00:39:08,839 Speaker 1: What like, what are you doing? I don't care. If 742 00:39:08,840 --> 00:39:10,920 Speaker 1: you have a ten percent risk of dying from this thing, 743 00:39:10,960 --> 00:39:12,799 Speaker 1: what are you doing to yourself? And you don't, I mean, 744 00:39:12,840 --> 00:39:15,160 Speaker 1: you have a you have a you know, one one 745 00:39:15,239 --> 00:39:17,560 Speaker 1: percent risk if you're you know, forty year old guy 746 00:39:17,680 --> 00:39:21,400 Speaker 1: or whatever. You know, if the risk is miniscule. But 747 00:39:21,400 --> 00:39:26,719 Speaker 1: but people, people have wrenched themselves into terror about this, 748 00:39:26,800 --> 00:39:29,759 Speaker 1: and as a society, we are tearing ourselves up over it. 749 00:39:30,160 --> 00:39:33,080 Speaker 1: And you know, and and here's the thing about lockdowns. Okay, 750 00:39:33,480 --> 00:39:36,360 Speaker 1: you either lockdown too early or too late. Here's your choices. 751 00:39:36,760 --> 00:39:39,560 Speaker 1: You lock down like Britain when it's already spread all 752 00:39:39,560 --> 00:39:42,520 Speaker 1: over the place, in which case you still have uncontrolled 753 00:39:42,560 --> 00:39:45,319 Speaker 1: spread in nursing homes and and and you know, as 754 00:39:45,320 --> 00:39:47,880 Speaker 1: a result, the UK is the worst death rate anywhere 755 00:39:47,920 --> 00:39:50,640 Speaker 1: of any country in the world, any major country. And 756 00:39:50,680 --> 00:39:53,439 Speaker 1: they locked down very hard, but late, or you locked 757 00:39:53,480 --> 00:39:55,799 Speaker 1: down really early, like New Zealand, in which case you're 758 00:39:55,840 --> 00:39:58,960 Speaker 1: living in fear of the stupid things forever. And whenever 759 00:39:59,000 --> 00:40:00,719 Speaker 1: there's a case, you have to side whether or not 760 00:40:00,760 --> 00:40:04,359 Speaker 1: to walk down again. Or you treat it like what 761 00:40:04,400 --> 00:40:08,440 Speaker 1: it is, a manageable respiratory virus, and you go on 762 00:40:08,560 --> 00:40:11,560 Speaker 1: with life like the Swedes did. And yes, some people 763 00:40:11,600 --> 00:40:15,839 Speaker 1: will die and then you'll be done and life goes on. 764 00:40:16,320 --> 00:40:18,200 Speaker 1: How important is it for schools to be open? In 765 00:40:18,239 --> 00:40:20,840 Speaker 1: your mind? I've got three kids, twelve, nine and five. 766 00:40:21,000 --> 00:40:24,080 Speaker 1: Come Monday, all three of them a week from today 767 00:40:24,080 --> 00:40:26,279 Speaker 1: when we're talking, all three of them will be an 768 00:40:26,320 --> 00:40:30,040 Speaker 1: in person school on Monday, August where I live so 769 00:40:30,040 --> 00:40:32,600 Speaker 1: so so our kids are going back to school. Uh. 770 00:40:32,840 --> 00:40:35,960 Speaker 1: One week later, they're going back on September. One we before. 771 00:40:36,239 --> 00:40:38,719 Speaker 1: My kids are you know, a little bit younger than yours. Uh. 772 00:40:38,760 --> 00:40:40,480 Speaker 1: And for you know, we're in New York. We actually 773 00:40:40,560 --> 00:40:42,919 Speaker 1: seriously considered moving this summer. And I'm glad we didn't 774 00:40:42,960 --> 00:40:45,160 Speaker 1: because you know, places we thought we might have moved to. 775 00:40:45,239 --> 00:40:47,040 Speaker 1: They're now saying the schools are gonna be closed at 776 00:40:47,080 --> 00:40:49,920 Speaker 1: least through November. But fortunately they're at a little you know, 777 00:40:49,960 --> 00:40:52,960 Speaker 1: they're at a little private school, um, you know, in 778 00:40:53,040 --> 00:40:55,879 Speaker 1: New York State, and they'll be able to have five 779 00:40:55,960 --> 00:40:58,279 Speaker 1: day a week school, which is a uh you know, 780 00:40:58,360 --> 00:41:02,080 Speaker 1: which is so important for their mental health, for their learning, 781 00:41:02,280 --> 00:41:05,799 Speaker 1: for their socialization, for their understanding that life goes on, 782 00:41:05,880 --> 00:41:09,880 Speaker 1: for their physical growth. It's so vital that schools be open. 783 00:41:09,920 --> 00:41:13,040 Speaker 1: And it is so wrong that that the teachers unions 784 00:41:13,239 --> 00:41:15,920 Speaker 1: are refusing this and are fighting about this. It couldn't 785 00:41:16,040 --> 00:41:19,719 Speaker 1: be more wrong of all the things we've done. It 786 00:41:19,800 --> 00:41:23,080 Speaker 1: is the absolute worst, and and all over Europe, by 787 00:41:23,120 --> 00:41:26,480 Speaker 1: the way, schools are reopening. All over Asia, schools are 788 00:41:26,480 --> 00:41:30,160 Speaker 1: reopening this if they're if you want proof of anything, 789 00:41:30,800 --> 00:41:32,399 Speaker 1: or if you want proof in a way that they're 790 00:41:32,520 --> 00:41:34,839 Speaker 1: you know, the best possible proof that this is just 791 00:41:34,960 --> 00:41:37,600 Speaker 1: a totally political issue at this point. Look at the 792 00:41:37,640 --> 00:41:41,280 Speaker 1: fact that many jurisdictions are saying we're going to reopen 793 00:41:41,440 --> 00:41:45,160 Speaker 1: or consider reopening in late October early November. You know, 794 00:41:45,280 --> 00:41:49,319 Speaker 1: the right what what's happening in early November that might 795 00:41:49,480 --> 00:41:51,440 Speaker 1: cause that to happen. And by the way, if you 796 00:41:51,480 --> 00:41:54,360 Speaker 1: really cared, you'd want them open now because it's before 797 00:41:54,440 --> 00:41:57,600 Speaker 1: flu season. Instead, we're going to reopen as flu season 798 00:41:57,719 --> 00:42:01,120 Speaker 1: is coming back. Fox Sports ready has the best sports 799 00:42:01,160 --> 00:42:03,960 Speaker 1: talk lineup in the nation. Catch all of our shows 800 00:42:03,960 --> 00:42:07,200 Speaker 1: at Fox Sports Radio dot com and within the I 801 00:42:07,280 --> 00:42:10,280 Speaker 1: Heart Radio app search f s R to listen live. 802 00:42:11,440 --> 00:42:13,440 Speaker 1: We're talking to Alex Barrens and I'm Clay Travis. This 803 00:42:13,520 --> 00:42:17,320 Speaker 1: is the Wins and Losses Podcast. Um, there's so many 804 00:42:17,320 --> 00:42:21,160 Speaker 1: things here that continue to amaze me. Uh, why do 805 00:42:21,280 --> 00:42:25,840 Speaker 1: you think your social media feed has been so filtered 806 00:42:25,880 --> 00:42:28,080 Speaker 1: with Why do you think your books which went up 807 00:42:28,120 --> 00:42:32,399 Speaker 1: on Amazon have in many ways not been distributed like 808 00:42:32,560 --> 00:42:35,719 Speaker 1: they would? Why is Fox News the only place? I 809 00:42:35,719 --> 00:42:38,640 Speaker 1: think you've talked with Paul Feinbaum on his radio show. 810 00:42:39,200 --> 00:42:41,200 Speaker 1: But by and large, I would imagine you know the 811 00:42:41,400 --> 00:42:44,480 Speaker 1: quote unquote mainstream of the media. Many people have have 812 00:42:44,520 --> 00:42:46,120 Speaker 1: ignored you. I know the New York Times did a 813 00:42:46,160 --> 00:42:48,640 Speaker 1: piece I think Ben Smith, if I'm not mistaken, I 814 00:42:48,719 --> 00:42:51,560 Speaker 1: read a piece there. But why do you think you 815 00:42:51,600 --> 00:42:53,920 Speaker 1: have become persona non grata If you had been the 816 00:42:53,960 --> 00:42:56,840 Speaker 1: person out there saying we've got to shut down everything. 817 00:42:56,880 --> 00:42:59,160 Speaker 1: If in other words, if you instead of being the 818 00:42:59,200 --> 00:43:02,040 Speaker 1: guy who has said, hey, I think we're overreacting, if 819 00:43:02,080 --> 00:43:05,600 Speaker 1: you had been the overreact or, you would be lauded 820 00:43:05,640 --> 00:43:08,319 Speaker 1: by the media. It's wild to think about, right, same 821 00:43:08,320 --> 00:43:09,799 Speaker 1: thing would be true for me if I had been 822 00:43:09,800 --> 00:43:13,560 Speaker 1: the keing of shutdowns, lockdown sports can never play again. 823 00:43:14,000 --> 00:43:17,120 Speaker 1: My media colleagues in sports media would have been like, oh, 824 00:43:17,200 --> 00:43:19,719 Speaker 1: how brave of him, when the reality is saying what 825 00:43:19,800 --> 00:43:23,040 Speaker 1: you or I are saying is infinitely more brave than 826 00:43:23,920 --> 00:43:29,359 Speaker 1: following the herd. Yeah, I mean, it's just accurate. Yeah, right, 827 00:43:29,400 --> 00:43:31,359 Speaker 1: But I mean a lot of people agree with us 828 00:43:31,719 --> 00:43:34,080 Speaker 1: but won't say it publicly because they're worried about the 829 00:43:34,080 --> 00:43:36,839 Speaker 1: consequences or the ostracization. Because I'm sure you've heard from 830 00:43:36,840 --> 00:43:38,960 Speaker 1: a lot of people in your industry as I have, 831 00:43:39,040 --> 00:43:41,200 Speaker 1: who have said, hey, keep saying what you're saying, but 832 00:43:41,239 --> 00:43:44,000 Speaker 1: they don't want to say it themselves. Yep, I get that, 833 00:43:44,560 --> 00:43:46,719 Speaker 1: and I'm glad to hear you get it too. I mean, 834 00:43:46,920 --> 00:43:50,640 Speaker 1: although it's not a surprising, why do you listen? Look, people, 835 00:43:52,520 --> 00:43:55,680 Speaker 1: I've been saying to a lot of people. Uh, you're wrong, 836 00:43:55,960 --> 00:43:57,960 Speaker 1: You're wrong about this. Yes, you don't know what you're 837 00:43:57,960 --> 00:44:00,680 Speaker 1: talking about. And I've been saying and you know, and 838 00:44:00,719 --> 00:44:03,000 Speaker 1: I won't back down and you can't shut me up, 839 00:44:03,239 --> 00:44:05,600 Speaker 1: and I'm going to keep pointing to facts and statistics. 840 00:44:05,880 --> 00:44:07,640 Speaker 1: And I don't care if you think I used to 841 00:44:07,640 --> 00:44:09,640 Speaker 1: be a good journalist and I'm not anymore, because I'm 842 00:44:09,640 --> 00:44:12,680 Speaker 1: exactly the same journalist I would when you liked me. 843 00:44:13,040 --> 00:44:16,320 Speaker 1: I'm just saying something you don't like and people people 844 00:44:16,400 --> 00:44:19,640 Speaker 1: can't stand it, and um, you know again, I think, 845 00:44:19,640 --> 00:44:22,560 Speaker 1: as we have found, it takes a certain kind of 846 00:44:22,600 --> 00:44:26,200 Speaker 1: personality to be willing to say this stuff, and it's 847 00:44:26,239 --> 00:44:29,279 Speaker 1: easier just to shoot the messenger. And one of the 848 00:44:29,320 --> 00:44:32,279 Speaker 1: things that I've discovered actually recently on Twitter is that 849 00:44:32,400 --> 00:44:35,920 Speaker 1: there are people out their media, people, um, who just 850 00:44:35,960 --> 00:44:38,560 Speaker 1: blocked me preemptively, people I never know. Yeah, that happens 851 00:44:38,600 --> 00:44:41,480 Speaker 1: to me all the time. Yes, And it's like, what 852 00:44:41,560 --> 00:44:44,839 Speaker 1: do you think you're gaining from this? They are so 853 00:44:45,000 --> 00:44:49,279 Speaker 1: upset by having their narrative challenged that for people out 854 00:44:49,280 --> 00:44:51,640 Speaker 1: there who don't recognize what you're saying. People who are 855 00:44:51,719 --> 00:44:54,520 Speaker 1: in media, like I will like cape people I've never 856 00:44:54,520 --> 00:44:56,920 Speaker 1: interacted with. This happens to me all the time in sports. 857 00:44:57,000 --> 00:44:59,360 Speaker 1: They'll have a tweet out somebody else, so retweet it 858 00:44:59,640 --> 00:45:01,560 Speaker 1: and I'll be like, oh, that's interesting, I'm curious what 859 00:45:01,600 --> 00:45:03,359 Speaker 1: they said, and I'll go to read it and I'll 860 00:45:03,400 --> 00:45:06,279 Speaker 1: realize that they blocked me. I've never interacted with him, 861 00:45:06,560 --> 00:45:09,439 Speaker 1: I've never in any way, you know, like debated any 862 00:45:09,520 --> 00:45:13,359 Speaker 1: issue with him, and then boom, they've got me blocked. Yep. 863 00:45:13,560 --> 00:45:17,200 Speaker 1: I mean, the media is incredibly hyperpartisan right now. And 864 00:45:17,320 --> 00:45:19,920 Speaker 1: here's the thing. At Fox they know they're partisan. Okay, 865 00:45:20,280 --> 00:45:23,520 Speaker 1: the New York Times and CNN they're still pretending they're not. 866 00:45:23,640 --> 00:45:27,120 Speaker 1: Now that has sort of fallen away, but it's still 867 00:45:27,719 --> 00:45:31,680 Speaker 1: it's still there to some extent. And and um, you know, look, Paul, 868 00:45:31,680 --> 00:45:33,640 Speaker 1: Paul find out he's a really good guy. I'm really 869 00:45:33,680 --> 00:45:37,000 Speaker 1: glad he's had me on. Okay, but basically, aside from 870 00:45:37,040 --> 00:45:41,200 Speaker 1: Fox and One America another conservative outlets, he's the only one, 871 00:45:41,480 --> 00:45:43,040 Speaker 1: you know, I was. I was supposed to go on 872 00:45:43,080 --> 00:45:47,200 Speaker 1: CNBC several times. I had confirmed interviews, and they canceled 873 00:45:47,239 --> 00:45:49,680 Speaker 1: on me. CNN and Paul and Paul, by the way, 874 00:45:49,760 --> 00:45:51,680 Speaker 1: knows me from the novels which is why he you 875 00:45:51,719 --> 00:45:53,319 Speaker 1: know why, He's like, he's kind of a fan of 876 00:45:53,320 --> 00:45:55,239 Speaker 1: my novels, and that's why he had me on to 877 00:45:55,280 --> 00:46:00,160 Speaker 1: begin with. But you know CNN Aaron, you know Aaron Burnet, 878 00:46:00,320 --> 00:46:02,040 Speaker 1: she's a fan of my novel I was going to 879 00:46:02,120 --> 00:46:03,759 Speaker 1: go on with her a couple of months ago. That 880 00:46:03,840 --> 00:46:07,760 Speaker 1: got canceled, never rescheduled. So yeah, so there is clearly 881 00:46:07,840 --> 00:46:10,960 Speaker 1: a media blackout. And and look, I really am glad 882 00:46:11,000 --> 00:46:12,359 Speaker 1: to have the chance to talk to you. I'm glad 883 00:46:12,360 --> 00:46:14,160 Speaker 1: to have a chance to talk to Tucker Carlson and 884 00:46:14,239 --> 00:46:16,839 Speaker 1: Laura and and everybody else on Fox. But Fox does 885 00:46:16,880 --> 00:46:19,719 Speaker 1: that leached the whole country because that's also siload and 886 00:46:19,760 --> 00:46:22,120 Speaker 1: people need to hear what you and I have to say, 887 00:46:22,200 --> 00:46:24,840 Speaker 1: even if they think we're wrong, it would be better 888 00:46:25,120 --> 00:46:27,480 Speaker 1: for them to know that there's another side to this 889 00:46:28,080 --> 00:46:29,840 Speaker 1: and that you can debate it. And that goes to 890 00:46:30,040 --> 00:46:32,000 Speaker 1: a larger question. I'm sure you get this all the time. 891 00:46:32,320 --> 00:46:35,120 Speaker 1: I went to law school. It's interesting you made a 892 00:46:35,160 --> 00:46:37,040 Speaker 1: living as a novelist. I went and got an m 893 00:46:37,120 --> 00:46:40,080 Speaker 1: f A. At Vanderbilt. I've got to advanced graduate degrees 894 00:46:40,120 --> 00:46:42,440 Speaker 1: from Vanderbilt, all right, And prior to that, I went 895 00:46:42,480 --> 00:46:44,839 Speaker 1: to g W. You can like me or dislike me. 896 00:46:44,960 --> 00:46:48,160 Speaker 1: They're decent academic credentials for me. You went to Yale, 897 00:46:48,320 --> 00:46:50,279 Speaker 1: you worked at the at the New York Times for 898 00:46:50,320 --> 00:46:52,960 Speaker 1: a decade. One of the things I think that offends 899 00:46:53,000 --> 00:46:55,800 Speaker 1: people out there is we're part of their ruling class 900 00:46:56,239 --> 00:46:58,359 Speaker 1: of elites, whatever you want to call it, and we're 901 00:46:58,400 --> 00:47:02,200 Speaker 1: not succumbing to their story. But how you respond to 902 00:47:02,200 --> 00:47:03,759 Speaker 1: people out there who are listening to us? And I'm 903 00:47:03,800 --> 00:47:05,640 Speaker 1: sure people will pop in as soon as I tweet 904 00:47:05,680 --> 00:47:08,200 Speaker 1: this out. Oh, let's go listen to those guys. They're 905 00:47:08,239 --> 00:47:10,440 Speaker 1: not doctors, they're not lawyers. When did you get your 906 00:47:10,440 --> 00:47:14,479 Speaker 1: degree in virology? Are you an epidemiological expert? How would 907 00:47:14,480 --> 00:47:18,200 Speaker 1: you respond to that segment of Twitter that believes that 908 00:47:18,239 --> 00:47:21,000 Speaker 1: because you and I do not have medical degrees aren't 909 00:47:21,000 --> 00:47:25,839 Speaker 1: epidemiological pH d s, do not have advanced degrees in virology, 910 00:47:25,840 --> 00:47:29,000 Speaker 1: that we're not allowed to talk about this. So here's 911 00:47:29,040 --> 00:47:31,080 Speaker 1: what I say. I try to avoid talking about the 912 00:47:31,080 --> 00:47:33,960 Speaker 1: practice of medicine. And I stated far away from you know, 913 00:47:34,000 --> 00:47:36,000 Speaker 1: the h c Q debate, and there are people other 914 00:47:36,040 --> 00:47:37,440 Speaker 1: who want the same thing for me. By the way, 915 00:47:37,600 --> 00:47:40,200 Speaker 1: there are people more knowledgeable inside of hospitals and talk 916 00:47:40,239 --> 00:47:42,240 Speaker 1: about that. I've just looked at the data. But continue, 917 00:47:42,320 --> 00:47:47,000 Speaker 1: that's right, so so so so so. You know, medicine 918 00:47:47,040 --> 00:47:48,680 Speaker 1: is something that you get a degree, you know, and 919 00:47:48,719 --> 00:47:51,480 Speaker 1: you practice. That's between doctors and patients, and you know 920 00:47:51,600 --> 00:47:55,120 Speaker 1: how exactly the spike protein you know, enters the cell 921 00:47:55,280 --> 00:47:59,440 Speaker 1: and how the virus replicates. Those are difficult technical questions 922 00:47:59,560 --> 00:48:03,440 Speaker 1: I don't and to know anything about. But here's here's 923 00:48:03,440 --> 00:48:06,080 Speaker 1: what I can do. Okay, I can look at a model. 924 00:48:06,600 --> 00:48:09,759 Speaker 1: It says they're gonna be sixty five thousand people in 925 00:48:09,880 --> 00:48:13,279 Speaker 1: hospital beds in New York, New York State on April five, 926 00:48:13,560 --> 00:48:16,560 Speaker 1: And it is April five, and there are sixteen thousand 927 00:48:16,600 --> 00:48:20,000 Speaker 1: people in hospital beds in New York State that day, 928 00:48:20,160 --> 00:48:22,200 Speaker 1: and the models off by a factor of four, even 929 00:48:22,200 --> 00:48:24,480 Speaker 1: though it was only made a week ago. And I 930 00:48:24,520 --> 00:48:28,520 Speaker 1: can say, what on earth is going on here? Why 931 00:48:28,680 --> 00:48:31,160 Speaker 1: is this so wrong? How did you get this so wrong? 932 00:48:31,360 --> 00:48:34,200 Speaker 1: And what does it mean that it's so wrong? Okay? 933 00:48:34,480 --> 00:48:37,840 Speaker 1: Is it because you know little green men have taken 934 00:48:37,880 --> 00:48:40,000 Speaker 1: all those people out of hospital beds? Or is there 935 00:48:40,040 --> 00:48:42,399 Speaker 1: something wrong with the model. And if there's something wrong 936 00:48:42,440 --> 00:48:44,799 Speaker 1: with the model, what does it mean? What does it 937 00:48:44,840 --> 00:48:47,279 Speaker 1: mean about lockdowns? What does it mean about what our 938 00:48:47,320 --> 00:48:49,960 Speaker 1: response should be? And I can say to people, what 939 00:48:50,080 --> 00:48:53,080 Speaker 1: does it mean that you know fifty of the people 940 00:48:53,080 --> 00:48:55,440 Speaker 1: who died are in nursing homes? And why aren't we 941 00:48:55,440 --> 00:48:57,600 Speaker 1: talking about that all the time? And why aren't we 942 00:48:57,600 --> 00:49:00,920 Speaker 1: trying to protect those people instead of shutting schools when 943 00:49:01,000 --> 00:49:03,960 Speaker 1: kids aren't no risk? You do? And I always say 944 00:49:04,000 --> 00:49:07,600 Speaker 1: no risk, And I have to say there's there's obviously everything. 945 00:49:07,600 --> 00:49:10,200 Speaker 1: And here's the other thing that would tie in with 946 00:49:10,239 --> 00:49:12,560 Speaker 1: that to Alex, and I'm Clay Travis. You're listening to 947 00:49:12,560 --> 00:49:14,960 Speaker 1: Wins and Losses with Alex Barrinson as we finish up here, 948 00:49:15,040 --> 00:49:17,800 Speaker 1: here's the other thing that matters a great deal. Those 949 00:49:17,840 --> 00:49:22,840 Speaker 1: forecasts being wrong, actually, I believe led to a much 950 00:49:22,960 --> 00:49:26,920 Speaker 1: elevated death rate in New York and New Jersey because 951 00:49:26,960 --> 00:49:30,400 Speaker 1: they sent all those patients back into nursing homes because 952 00:49:30,440 --> 00:49:33,320 Speaker 1: they believed those forecasts that they were going to need 953 00:49:33,520 --> 00:49:37,200 Speaker 1: a hundred thousand plus hospital beds, when in reality, I 954 00:49:37,239 --> 00:49:40,640 Speaker 1: believe it peaked at nineteen thousand instead of a hundred 955 00:49:40,719 --> 00:49:44,359 Speaker 1: and forty thousand like the forecast. So the forecasters being 956 00:49:44,440 --> 00:49:48,600 Speaker 1: so wrong literally cost probably tens of thousands of additional 957 00:49:48,640 --> 00:49:52,319 Speaker 1: lives of people that would otherwise have survived because of 958 00:49:52,360 --> 00:49:56,560 Speaker 1: the overreaction. I mean, I don't think we can prove 959 00:49:56,600 --> 00:49:58,279 Speaker 1: that yet, but I think there's a there's a case 960 00:49:58,360 --> 00:50:01,960 Speaker 1: to be made there. Look, if there was one thing 961 00:50:02,239 --> 00:50:04,880 Speaker 1: I was good at as a journalist or you know, 962 00:50:05,040 --> 00:50:06,399 Speaker 1: you know a couple of things I was good at. 963 00:50:07,080 --> 00:50:10,640 Speaker 1: I was good at finding stuff in documents that people 964 00:50:10,680 --> 00:50:13,040 Speaker 1: didn't want me to find. But what I was really 965 00:50:13,040 --> 00:50:16,400 Speaker 1: good at was saying to people, Hey, you said X yesterday, 966 00:50:16,440 --> 00:50:21,040 Speaker 1: and you're saying why today, what what's changed? Why? Why 967 00:50:21,200 --> 00:50:24,080 Speaker 1: is it that you're that that that what you said 968 00:50:24,160 --> 00:50:26,759 Speaker 1: yesterday isn't what you're saying today and what's on the 969 00:50:26,760 --> 00:50:29,640 Speaker 1: ground is really z okay? And I don't need to 970 00:50:29,640 --> 00:50:32,520 Speaker 1: be an epidemiologist to ask those questions. I just need 971 00:50:32,560 --> 00:50:34,839 Speaker 1: to be able to look at the data myself a 972 00:50:34,880 --> 00:50:38,880 Speaker 1: little bit okay, And I don't claim to be an epidemiologist. 973 00:50:39,160 --> 00:50:41,839 Speaker 1: But but I challenge anybody to go back and look 974 00:50:41,840 --> 00:50:45,160 Speaker 1: at my my, uh my reporting for the New York 975 00:50:45,160 --> 00:50:47,400 Speaker 1: Times and say either that I'm some kind of you know, 976 00:50:47,600 --> 00:50:51,040 Speaker 1: right wing person, or that you know that my reporting 977 00:50:51,360 --> 00:50:53,719 Speaker 1: is an air tight Um, and you know even Ben 978 00:50:53,719 --> 00:50:55,600 Speaker 1: Smith and that piece, you know that let's not even 979 00:50:55,600 --> 00:50:57,799 Speaker 1: talk about the piece. You know, he said, like I 980 00:50:58,080 --> 00:50:59,919 Speaker 1: this guy was a good journalist at the New York Times. 981 00:51:00,120 --> 00:51:02,400 Speaker 1: And you know I will, I will, I will, I 982 00:51:02,480 --> 00:51:06,440 Speaker 1: will fight that battle to my grave. Uh. Final question 983 00:51:06,520 --> 00:51:08,880 Speaker 1: for you for people out there who have enjoyed our conversation, 984 00:51:08,920 --> 00:51:11,000 Speaker 1: we might need to have another conversation because I think 985 00:51:11,000 --> 00:51:13,040 Speaker 1: people are gonna absolutely love this. I've been talking with 986 00:51:13,080 --> 00:51:16,000 Speaker 1: Alex Barrenson, I'm Clay Travis wins and losses. How would 987 00:51:16,040 --> 00:51:17,920 Speaker 1: they find you? How can they read what you have 988 00:51:18,000 --> 00:51:20,799 Speaker 1: written on Amazon? How would you instruct them to be 989 00:51:20,840 --> 00:51:23,480 Speaker 1: able to to consume more of the content that you 990 00:51:23,520 --> 00:51:26,480 Speaker 1: were putting out there? Sure? So, I mean Twitter has 991 00:51:26,520 --> 00:51:28,600 Speaker 1: been my main outlet, and I will say, you know, 992 00:51:28,640 --> 00:51:31,680 Speaker 1: Twitter has been pretty good to me. I've been concerned 993 00:51:31,719 --> 00:51:33,120 Speaker 1: that they you know, they had they do seem to 994 00:51:33,160 --> 00:51:35,840 Speaker 1: have a commitment to freak speech. And um, you know 995 00:51:35,920 --> 00:51:38,239 Speaker 1: my audience has grown, you know, from fewer than ten 996 00:51:38,280 --> 00:51:41,080 Speaker 1: thousand almost two hundred thousand in the last few months. Um. 997 00:51:41,080 --> 00:51:44,640 Speaker 1: So it's just alexperience and on Twitter and just you know, 998 00:51:44,760 --> 00:51:46,880 Speaker 1: just my A L. E X B. E R E 999 00:51:47,160 --> 00:51:49,719 Speaker 1: N S O m UM. And then I have these 1000 00:51:49,760 --> 00:51:52,200 Speaker 1: two booklets out which you can get on Amazon or Apple. 1001 00:51:52,280 --> 00:51:54,880 Speaker 1: You can download them to UM. You know, I I 1002 00:51:55,120 --> 00:51:57,160 Speaker 1: there's another one I need to put out actually really 1003 00:51:57,160 --> 00:51:59,640 Speaker 1: about masks and schools, because as we've talked about, the 1004 00:51:59,640 --> 00:52:03,480 Speaker 1: school thing is crucial. Masks we haven't really talked about. UM. 1005 00:52:03,520 --> 00:52:07,440 Speaker 1: I think the mask issue is very interesting. UM. But 1006 00:52:07,440 --> 00:52:09,640 Speaker 1: but you know, if we have another conversation, we've talked 1007 00:52:09,640 --> 00:52:14,280 Speaker 1: about masks. But that's that's really it. You know, occasionally, UM, 1008 00:52:14,320 --> 00:52:16,399 Speaker 1: I write something that you know, Fox News will pick 1009 00:52:16,480 --> 00:52:18,640 Speaker 1: up or other outlets will pick up. But as we 1010 00:52:18,719 --> 00:52:21,319 Speaker 1: talked about the places like the New York Times op 1011 00:52:21,440 --> 00:52:24,120 Speaker 1: ed page or the Wall Street Journal OpEd page, UM, 1012 00:52:24,200 --> 00:52:27,480 Speaker 1: where I used to write, you know I've had I've 1013 00:52:27,480 --> 00:52:29,560 Speaker 1: had pieces published on both of those pages in the 1014 00:52:29,600 --> 00:52:31,759 Speaker 1: last couple of years. I'm not sure they're open to 1015 00:52:31,800 --> 00:52:35,719 Speaker 1: me anymore. UM. And that that's really disturbing. Again, you 1016 00:52:35,760 --> 00:52:38,600 Speaker 1: can think I'm totally wrong, and you're totally wrong, but 1017 00:52:38,680 --> 00:52:41,320 Speaker 1: people should hear us. They should hear that there's another 1018 00:52:41,360 --> 00:52:44,600 Speaker 1: side to this. Amen. And by the way, you've always 1019 00:52:44,600 --> 00:52:47,000 Speaker 1: got an opportunity if you want to write out kick. 1020 00:52:47,040 --> 00:52:49,440 Speaker 1: We're gonna have ten million readers this month. One reason 1021 00:52:49,440 --> 00:52:52,240 Speaker 1: we're blowing up is because I think people want debates, 1022 00:52:52,280 --> 00:52:55,280 Speaker 1: they want real discussion of issues, and so you're always 1023 00:52:55,360 --> 00:52:58,040 Speaker 1: welcome to check out out kick dot com and right 1024 00:52:58,120 --> 00:53:00,839 Speaker 1: for us anytime. We'd love to have it. All right, 1025 00:53:01,360 --> 00:53:03,719 Speaker 1: it's been a great pleasure. I I hope I didn't, 1026 00:53:03,760 --> 00:53:05,920 Speaker 1: you know, talk too much about about you know, the 1027 00:53:06,400 --> 00:53:08,520 Speaker 1: Cannabis book or that's but I do think people should 1028 00:53:08,600 --> 00:53:13,000 Speaker 1: know that that this my my contrarian views on this 1029 00:53:13,320 --> 00:53:17,040 Speaker 1: don't come out of nowhere. They come from serving understanding, unfortunately, 1030 00:53:17,400 --> 00:53:19,960 Speaker 1: of what the media has become, uh, you know, in 1031 00:53:20,000 --> 00:53:23,560 Speaker 1: the last decade. Amen, I appreciate you. I keep up 1032 00:53:23,600 --> 00:53:25,600 Speaker 1: the good work. I love the fact that you're not 1033 00:53:25,760 --> 00:53:28,239 Speaker 1: bending to the will of the masses. And we'll talk 1034 00:53:28,239 --> 00:53:31,360 Speaker 1: to you again. That's Alex Berenson. Go follow him on Twitter, 1035 00:53:31,680 --> 00:53:34,319 Speaker 1: read his books on Amazon. I am Clay Travis. This 1036 00:53:34,360 --> 00:53:37,359 Speaker 1: has been wins and losses. Be sure to catch live 1037 00:53:37,480 --> 00:53:40,560 Speaker 1: editions about Kicked. The coverage with Clay Travis weekdays at 1038 00:53:40,600 --> 00:53:42,759 Speaker 1: six am Eastern three am Pacific