1 00:00:00,160 --> 00:00:04,360 Speaker 1: Imagine being fired for telling the truth. That's exactly what 2 00:00:04,480 --> 00:00:07,360 Speaker 1: happened to a friend of the show. So what I've 3 00:00:07,360 --> 00:00:11,400 Speaker 1: gotten to know throughout COVID doctor Martin Kolder. He's been 4 00:00:11,440 --> 00:00:14,880 Speaker 1: fired from Harvard University, where he's been since two thousand 5 00:00:14,880 --> 00:00:18,080 Speaker 1: and three, twenty one years of dedication. This is a 6 00:00:18,079 --> 00:00:21,400 Speaker 1: man who's a world renowned epidemiologist and biostatistician. This is 7 00:00:21,440 --> 00:00:25,000 Speaker 1: someone for decades who helped the CDC and the FDA 8 00:00:25,160 --> 00:00:29,120 Speaker 1: develop their post market vaccine safety systems. Why was he fired? 9 00:00:29,600 --> 00:00:32,919 Speaker 1: He was fired because he signed the Great Barrington Declaration. 10 00:00:33,000 --> 00:00:35,320 Speaker 1: When he warned us against lockdowns, when he told us 11 00:00:35,360 --> 00:00:38,080 Speaker 1: that kids should be kept in schools, that they should 12 00:00:38,080 --> 00:00:40,600 Speaker 1: be able to continue their lives. He told us the 13 00:00:40,640 --> 00:00:43,880 Speaker 1: truth about natural immunity. This is a man who warned 14 00:00:43,960 --> 00:00:47,280 Speaker 1: us about vaccines too, only telling us that not everyone 15 00:00:47,320 --> 00:00:50,360 Speaker 1: needed to get it. All of this has been proven right, 16 00:00:50,680 --> 00:00:54,520 Speaker 1: yet still fired from Harvard. So how much of this 17 00:00:54,600 --> 00:00:57,240 Speaker 1: is because he just didn't go along with the forced 18 00:00:57,360 --> 00:01:00,400 Speaker 1: scientific status quo. We're going to get his tap on 19 00:01:00,560 --> 00:01:03,560 Speaker 1: why he thinks he was fired also reflect a little 20 00:01:03,560 --> 00:01:07,400 Speaker 1: bit about what we know now since COVID as well. 21 00:01:07,600 --> 00:01:10,160 Speaker 1: He's a really good man. He is brave, he is honest, 22 00:01:10,200 --> 00:01:12,960 Speaker 1: he is fearless. He told us the truth during COVID. 23 00:01:13,000 --> 00:01:15,800 Speaker 1: He has faced big, big consequences as a result of it. 24 00:01:15,880 --> 00:01:17,880 Speaker 1: Trust me, you're not gonna want to miss this conversation 25 00:01:18,080 --> 00:01:25,880 Speaker 1: with doctor Martin Colder. Well, I'll start off saying, doctor 26 00:01:25,959 --> 00:01:29,399 Speaker 1: Martin Colder. Doctor you've asked me to call you Martin, 27 00:01:29,480 --> 00:01:32,120 Speaker 1: but just for the audience's purposes, I was going to 28 00:01:32,200 --> 00:01:34,440 Speaker 1: fuck you, doctor Colder, but I'm going to call you 29 00:01:34,480 --> 00:01:37,600 Speaker 1: Martin throughout the podcast as requested. So I just don't 30 00:01:37,600 --> 00:01:39,720 Speaker 1: want people to think I was disrespecting you. But it's 31 00:01:39,720 --> 00:01:41,759 Speaker 1: always an honor to have you on the show, Stir. 32 00:01:41,840 --> 00:01:44,319 Speaker 1: You've been on before. You're just a truth teller and 33 00:01:44,360 --> 00:01:46,720 Speaker 1: that's what we're going to get into in this episode. 34 00:01:46,720 --> 00:01:48,360 Speaker 1: But I just appreciate you making the time. 35 00:01:48,800 --> 00:01:51,000 Speaker 2: Well, thank you for having me on. It's great talking 36 00:01:51,000 --> 00:01:51,440 Speaker 2: to you again. 37 00:01:51,680 --> 00:01:54,880 Speaker 1: You know, So, Martin, I was dismayed, I'm sure as 38 00:01:54,920 --> 00:01:57,880 Speaker 1: you were, to see the news that you've been a 39 00:01:57,920 --> 00:02:02,080 Speaker 1: professor of medicine at Heartard University since two thousand and 40 00:02:02,160 --> 00:02:05,520 Speaker 1: three and they decided to fire you after twenty one 41 00:02:05,600 --> 00:02:08,720 Speaker 1: years of dedication, you know, for more than two decades. 42 00:02:08,760 --> 00:02:12,720 Speaker 1: You helped the CDC, the FDA develop post market vaccine 43 00:02:12,760 --> 00:02:16,400 Speaker 1: safety systems. I mean, you're internationally world renowned and they 44 00:02:16,440 --> 00:02:20,720 Speaker 1: decided to fire you. What was their explanation, Well. 45 00:02:20,600 --> 00:02:23,840 Speaker 3: We had a disagreement with the fundamental issue of science, 46 00:02:23,880 --> 00:02:27,600 Speaker 3: which is infection, the quited immunity. So we've known about 47 00:02:27,600 --> 00:02:30,600 Speaker 3: that since the thetium plague in four thirty BC, so 48 00:02:30,720 --> 00:02:34,720 Speaker 3: for almost two and a half thousand years. By putting 49 00:02:34,720 --> 00:02:38,160 Speaker 3: in the vaccine mandates, they are the fact to denying 50 00:02:39,840 --> 00:02:43,600 Speaker 3: basic science that we're known for a long time, forcing 51 00:02:43,639 --> 00:02:46,440 Speaker 3: people all that it has superior unity to get the vaccine. 52 00:02:47,080 --> 00:02:51,640 Speaker 3: So I argued against vaccine mandates both publicly and also 53 00:02:51,680 --> 00:02:55,400 Speaker 3: privately in my own case. And for example, at Harvard's 54 00:02:55,400 --> 00:02:59,639 Speaker 3: Bringing and Women's at Harvard's mass Teneral mass Dennal Brigham Hospital, 55 00:03:00,600 --> 00:03:01,440 Speaker 3: nazis were working. 56 00:03:01,440 --> 00:03:03,639 Speaker 2: Theyre any care of of. 57 00:03:03,639 --> 00:03:05,560 Speaker 3: COVID patients, and then they get COVID, so they were 58 00:03:05,600 --> 00:03:07,079 Speaker 3: all for a few weeks and then they go back 59 00:03:07,120 --> 00:03:09,519 Speaker 3: to work and they take care of w COVID patients. 60 00:03:09,960 --> 00:03:12,560 Speaker 3: But then when the vaccine came, they are fired because 61 00:03:14,240 --> 00:03:16,079 Speaker 3: they didn't take the vaccine, because they didn't need it. 62 00:03:16,240 --> 00:03:19,720 Speaker 3: They didn't they already had superior immunity from having had COVID, 63 00:03:20,240 --> 00:03:23,240 Speaker 3: And of course that was a decision made by the 64 00:03:23,560 --> 00:03:26,240 Speaker 3: bureaucrats hospital and University of Bureaucrats. 65 00:03:26,840 --> 00:03:28,399 Speaker 2: So I was in the same situation. 66 00:03:28,680 --> 00:03:32,119 Speaker 3: I didn't I never feeded the patients because a matter 67 00:03:32,120 --> 00:03:36,600 Speaker 3: of physician, I'm a PhD, apnologist and the biostatistician, so 68 00:03:37,800 --> 00:03:40,520 Speaker 3: I didn't need it. I have a genetic condition that 69 00:03:40,600 --> 00:03:45,920 Speaker 3: makes me uh a very h uwione deficiency called off 70 00:03:45,960 --> 00:03:48,600 Speaker 3: A one of the tryptian deficiency, so I didn't know 71 00:03:48,600 --> 00:03:50,280 Speaker 3: what the risk was from the vaccine for me. 72 00:03:50,960 --> 00:03:53,200 Speaker 2: And I also thought it was unethical. 73 00:03:52,720 --> 00:03:55,720 Speaker 3: Because all the people they need the vaccines because they 74 00:03:55,720 --> 00:03:59,520 Speaker 3: had the high risk of dying from COVID. So when 75 00:03:59,520 --> 00:04:02,600 Speaker 3: there's a VACS see if short as if you're pro vaccine, 76 00:04:02,720 --> 00:04:05,400 Speaker 3: suppose it's just a perfect vaccine that no side of 77 00:04:05,480 --> 00:04:08,400 Speaker 3: vicine does that. But suppose it was a perfect vaccine, 78 00:04:08,640 --> 00:04:10,840 Speaker 3: you wouldn't want to few pro vaccine. You wouldn't want 79 00:04:10,840 --> 00:04:12,320 Speaker 3: to give it to people who don't need it. When 80 00:04:12,320 --> 00:04:15,800 Speaker 3: there are people around the world, like my eighty seven 81 00:04:15,840 --> 00:04:17,880 Speaker 3: year old neighbor, for example, who hadn't gotten it yet, 82 00:04:18,080 --> 00:04:20,720 Speaker 3: so there was an unethical to take the vaccine if 83 00:04:20,760 --> 00:04:22,520 Speaker 3: you don't need it, if the other people who do 84 00:04:22,640 --> 00:04:23,000 Speaker 3: need it. 85 00:04:23,160 --> 00:04:26,200 Speaker 1: But you were right. I just I guess I could 86 00:04:26,320 --> 00:04:28,880 Speaker 1: maybe see at the very beginning of all of this, 87 00:04:29,240 --> 00:04:32,080 Speaker 1: you know, when we didn't really have the full information, 88 00:04:32,160 --> 00:04:33,920 Speaker 1: I still would think that was wrong. I would still 89 00:04:33,960 --> 00:04:38,200 Speaker 1: disagree with it. But everything you just laid out we 90 00:04:38,320 --> 00:04:41,200 Speaker 1: know to be true. I mean, that's just factual information. 91 00:04:41,320 --> 00:04:45,599 Speaker 1: So they're firing you over stating facts. 92 00:04:45,880 --> 00:04:48,720 Speaker 3: Well, it was true from four hundred and thirty BC 93 00:04:48,960 --> 00:04:54,560 Speaker 3: until two thousand and nineteen, and then it wasn't true 94 00:04:54,560 --> 00:04:58,040 Speaker 3: from twenty and twenty until twenty twenty three, I guess, 95 00:04:58,120 --> 00:05:00,920 Speaker 3: and now it's true again. So so I guess that's 96 00:05:00,920 --> 00:05:01,680 Speaker 3: one way to see it. 97 00:05:02,279 --> 00:05:04,839 Speaker 1: Do you think this is Harvard driven or do you 98 00:05:04,839 --> 00:05:07,480 Speaker 1: think they got some sort of external pressure because I 99 00:05:07,560 --> 00:05:10,600 Speaker 1: know that, you know, Anthony Fauci went to war against 100 00:05:10,680 --> 00:05:13,160 Speaker 1: you for speaking the truth and the other Great Barrington signers, 101 00:05:13,200 --> 00:05:15,320 Speaker 1: which we'll get into a bit. I mean, do you 102 00:05:15,360 --> 00:05:17,360 Speaker 1: do you think this is Harvard's decision or do they 103 00:05:17,360 --> 00:05:19,440 Speaker 1: face some sort of external pressure? 104 00:05:20,080 --> 00:05:24,320 Speaker 3: Well, it's the decision at that it's a decision by 105 00:05:24,360 --> 00:05:28,320 Speaker 3: the Harvard's Mass General Brigham Hospital where I worked, don 106 00:05:28,920 --> 00:05:34,160 Speaker 3: of Harvard Medical School, because they think they could have 107 00:05:34,200 --> 00:05:37,159 Speaker 3: given me an exemption. They gave exemptions to other faculty member, 108 00:05:37,240 --> 00:05:39,240 Speaker 3: other staff, so they could if they wanted, they could 109 00:05:39,240 --> 00:05:42,760 Speaker 3: have given me an exemption. There was plenty of medical 110 00:05:42,800 --> 00:05:45,560 Speaker 3: reasons to provide me an exemptions if they wanted to. 111 00:05:46,240 --> 00:05:48,080 Speaker 2: But of course there's also outside pressure. 112 00:05:50,279 --> 00:05:56,679 Speaker 3: The Mass General Brigham is the biggest recipience of research 113 00:05:56,680 --> 00:05:59,640 Speaker 3: funding FORMMIA except the tune of a billion dollars, more 114 00:05:59,680 --> 00:06:04,599 Speaker 3: than a billion dollars a year, and so of course 115 00:06:04,640 --> 00:06:08,640 Speaker 3: they are very sensitive to what the Anthony Fautschelt was 116 00:06:08,800 --> 00:06:11,160 Speaker 3: the head of the nationally City of Maggy and a 117 00:06:11,200 --> 00:06:14,360 Speaker 3: victial diseases as what Process Collins things was the head 118 00:06:14,360 --> 00:06:18,279 Speaker 3: of the NIH. So of course they're very sensitive to 119 00:06:18,320 --> 00:06:23,400 Speaker 3: outside pressure as well among these things. So I think 120 00:06:23,440 --> 00:06:25,880 Speaker 3: it's a combination. But I mean, I think Harvard was 121 00:06:25,920 --> 00:06:31,279 Speaker 3: sort of a leading also institute in pushing for the lockdowns. 122 00:06:31,360 --> 00:06:35,040 Speaker 3: That they were the first major university to close down 123 00:06:35,480 --> 00:06:40,080 Speaker 3: announced to have a remote learning at which other universities 124 00:06:40,120 --> 00:06:42,359 Speaker 3: and colleges sort of followed the Harvard lead. And also 125 00:06:42,480 --> 00:06:45,280 Speaker 3: High schools and elementary schools, So that was done long 126 00:06:45,360 --> 00:06:49,320 Speaker 3: before the government had any pressure to close schools universities, 127 00:06:49,520 --> 00:06:53,080 Speaker 3: so they sort of took a leading approach to close 128 00:06:53,160 --> 00:06:56,880 Speaker 3: down the educational institutions. 129 00:06:56,960 --> 00:06:59,279 Speaker 2: And during the lockdowns. 130 00:07:00,080 --> 00:07:03,719 Speaker 1: You do you think that this is about you telling 131 00:07:03,760 --> 00:07:06,960 Speaker 1: the truth? Or do you think this is because you 132 00:07:07,080 --> 00:07:10,800 Speaker 1: sort of challenged the scientific community? Right? I mean there 133 00:07:10,840 --> 00:07:14,160 Speaker 1: is this sort of forced consensus that was going on, 134 00:07:14,400 --> 00:07:17,800 Speaker 1: you know, led by the Fauci Anthony Fauci, led by 135 00:07:18,800 --> 00:07:20,400 Speaker 1: you know. I mean, do you do you think this 136 00:07:20,440 --> 00:07:22,120 Speaker 1: is about telling the truth or do you think this 137 00:07:22,160 --> 00:07:25,520 Speaker 1: is because you just you wouldn't go along with the program. 138 00:07:25,760 --> 00:07:28,720 Speaker 1: We wouldn't go along with the forced consensus. 139 00:07:29,560 --> 00:07:32,520 Speaker 3: So I don't know what the ultimate decision was based 140 00:07:32,560 --> 00:07:34,200 Speaker 3: on how they I don't know. 141 00:07:34,280 --> 00:07:36,640 Speaker 2: I don't know what they were thinking in their brains. 142 00:07:37,000 --> 00:07:40,160 Speaker 3: But there were all this long before before the vaccines, 143 00:07:40,200 --> 00:07:44,200 Speaker 3: that they were unhappy with me about speaking up about 144 00:07:44,200 --> 00:07:47,200 Speaker 3: the Great Brains To Declaration where we criticize school closures 145 00:07:47,200 --> 00:07:49,480 Speaker 3: and other lockdown measures and we argue for that at 146 00:07:49,480 --> 00:07:53,680 Speaker 3: detection of all the high risk people. So as soon 147 00:07:53,680 --> 00:07:56,160 Speaker 3: as that there were there were they were unt happy 148 00:07:56,200 --> 00:07:59,240 Speaker 3: about that. So and not not the colleagues that I 149 00:07:59,280 --> 00:08:01,440 Speaker 3: work with on a day the basis that I still 150 00:08:01,480 --> 00:08:04,520 Speaker 3: have an excellent relationship with everybody I worked with personally, 151 00:08:05,280 --> 00:08:10,280 Speaker 3: but the leadership certainly were unhappy about and had some 152 00:08:10,360 --> 00:08:12,640 Speaker 3: complaints about that and. 153 00:08:12,680 --> 00:08:15,239 Speaker 1: Remind people, you know, why did you sign the Great 154 00:08:15,240 --> 00:08:19,160 Speaker 1: Barrington Declaration and what did it stand for then? And 155 00:08:19,560 --> 00:08:21,880 Speaker 1: sort of what do we know now about what you 156 00:08:21,920 --> 00:08:22,520 Speaker 1: were saying then. 157 00:08:23,600 --> 00:08:28,400 Speaker 3: So the when the pandemic started, there was sort of 158 00:08:28,400 --> 00:08:31,720 Speaker 3: an artificial consensus, so they were trying to pretend that 159 00:08:31,760 --> 00:08:34,400 Speaker 3: there was a scientific constensus for school closest. 160 00:08:34,000 --> 00:08:35,440 Speaker 2: On lockdown, so there never was. 161 00:08:36,080 --> 00:08:38,840 Speaker 3: I was one of several infectious to sea sechnologists who 162 00:08:39,040 --> 00:08:41,520 Speaker 3: did not agree with it, but it was very hard 163 00:08:41,520 --> 00:08:44,240 Speaker 3: to make our words herb because we were only one. 164 00:08:44,280 --> 00:08:50,640 Speaker 3: So in October of twenty twenty, I met with Jay Bonacharia, 165 00:08:50,640 --> 00:08:53,440 Speaker 3: who was a doctor from Stanford and doctor sat Gup 166 00:08:53,600 --> 00:08:56,520 Speaker 3: from Oxcar. It was the world's preeminent infectious to cease 167 00:08:56,520 --> 00:09:01,280 Speaker 3: at neologists. We met being Great Barrington, Massachusetts and the 168 00:09:01,320 --> 00:09:03,920 Speaker 3: three of us after the Great Brington Declaration, where we 169 00:09:04,120 --> 00:09:09,319 Speaker 3: argued for better protection of older people like less staffotation 170 00:09:09,440 --> 00:09:11,920 Speaker 3: in nursing homes, they're more testing in nursing. 171 00:09:11,559 --> 00:09:15,240 Speaker 2: Homes and so on, and. 172 00:09:16,880 --> 00:09:18,640 Speaker 3: We argue that school should be open, and that we're 173 00:09:18,640 --> 00:09:21,400 Speaker 3: still in closed down society with lockdowns because. 174 00:09:23,320 --> 00:09:24,520 Speaker 2: Everybody can get effected. 175 00:09:24,559 --> 00:09:26,880 Speaker 3: But there's more than a thousand full difference in the 176 00:09:26,960 --> 00:09:29,680 Speaker 3: risk of mortality between the older people and the younger people. 177 00:09:30,920 --> 00:09:34,640 Speaker 3: So that was against Fauci and sort of the narrative. 178 00:09:35,360 --> 00:09:38,119 Speaker 3: But because there were three of us from three reasonably 179 00:09:38,320 --> 00:09:43,280 Speaker 3: respectable universities who all worked in the infectious disease, they 180 00:09:43,280 --> 00:09:46,160 Speaker 3: couldn't dismiss us completely. So then they sort of instead 181 00:09:46,240 --> 00:09:50,360 Speaker 3: started a campaign against us, as the NIS director of 182 00:09:50,400 --> 00:09:53,640 Speaker 3: Francis Collins wrote to do take tun of us, considering 183 00:09:53,679 --> 00:09:55,080 Speaker 3: us fringe at pineologists. 184 00:09:56,600 --> 00:09:59,520 Speaker 2: But I mean a lot of people agree with us. 185 00:09:59,559 --> 00:10:04,240 Speaker 3: So we quickly obtain over one hundred thousand, hundreds of 186 00:10:04,240 --> 00:10:06,080 Speaker 3: thousands of co signers. 187 00:10:06,240 --> 00:10:09,200 Speaker 2: This almost a million by now, including. 188 00:10:08,760 --> 00:10:13,080 Speaker 3: Tens of thousands of the scientists and health professionals. 189 00:10:13,320 --> 00:10:17,440 Speaker 2: So the work clearly of big Yeah, it was clearly. 190 00:10:17,080 --> 00:10:19,719 Speaker 3: Not a consensus for these in my view of very 191 00:10:19,760 --> 00:10:24,640 Speaker 3: unscientific pandemic messure that went against the basic principles of 192 00:10:24,679 --> 00:10:25,280 Speaker 3: public health. 193 00:10:25,679 --> 00:10:28,079 Speaker 1: Let's take a quick Commercial break more with Martin Kolder 194 00:10:28,200 --> 00:10:33,880 Speaker 1: on the other side. What do we know now? I mean, 195 00:10:33,880 --> 00:10:38,480 Speaker 1: we're still finding out about the harm that lockdowns had 196 00:10:38,600 --> 00:10:42,440 Speaker 1: on you know, kids, on you know, people in general. 197 00:10:42,440 --> 00:10:46,120 Speaker 1: I mean, there was just this information from the CDC 198 00:10:46,240 --> 00:10:50,920 Speaker 1: showing that the annual average of death related excessive alcohol 199 00:10:51,080 --> 00:10:57,000 Speaker 1: use increased twenty nine percent during COVID. We still don't 200 00:10:57,040 --> 00:11:00,040 Speaker 1: know the totality of the damage. But what do we do? 201 00:11:00,400 --> 00:11:01,360 Speaker 1: What do we know today? 202 00:11:02,760 --> 00:11:04,120 Speaker 2: You're right, we don't know all of it. 203 00:11:04,160 --> 00:11:06,079 Speaker 3: I mean, we know that test course has gone down 204 00:11:06,120 --> 00:11:10,600 Speaker 3: for kids in the US, differ in different states that 205 00:11:10,760 --> 00:11:13,880 Speaker 3: depending on how much the schools were closed. We know 206 00:11:14,000 --> 00:11:19,359 Speaker 3: there's increasing the mental health issues in well used alcoholism, 207 00:11:19,520 --> 00:11:23,959 Speaker 3: but also like opiate overdoses, we know there was less 208 00:11:24,160 --> 00:11:27,800 Speaker 3: cancer screening and cancer treatments, and that doesn't show up 209 00:11:27,840 --> 00:11:31,040 Speaker 3: in the mortality. Is the statics immediates with because you 210 00:11:31,040 --> 00:11:33,560 Speaker 3: don't die immediately different cancers because you don't get the 211 00:11:34,040 --> 00:11:37,200 Speaker 3: screened or treated. But that's something that will show up 212 00:11:37,240 --> 00:11:39,840 Speaker 3: in in the mortality statistics for years to come. 213 00:11:40,040 --> 00:11:41,280 Speaker 2: Somebody who maybe. 214 00:11:41,480 --> 00:11:44,440 Speaker 3: Will not die maybe two years from now that would 215 00:11:44,640 --> 00:11:48,920 Speaker 3: otherwise have lived now ten twenty years. So these things 216 00:11:49,000 --> 00:11:50,360 Speaker 3: is something that we have to live with for a 217 00:11:50,440 --> 00:11:55,120 Speaker 3: long time and it's very tragic, I think. But we 218 00:11:55,200 --> 00:12:00,960 Speaker 3: also have the verdict now in looking at overall mortality. 219 00:12:01,120 --> 00:12:04,600 Speaker 3: So you can compare access mortality from twenty twenty to 220 00:12:04,640 --> 00:12:07,480 Speaker 3: twenty twenty two to two so otherand twenty three, and 221 00:12:07,559 --> 00:12:11,280 Speaker 3: we see that the major Western countries, Among major Western countries, 222 00:12:11,360 --> 00:12:15,280 Speaker 3: the country that has the lowest access mortality is Sweden, 223 00:12:15,320 --> 00:12:19,160 Speaker 3: which is the country that famously did not lockdown. They 224 00:12:19,200 --> 00:12:21,480 Speaker 3: did the measures to protect other people and so on, 225 00:12:21,520 --> 00:12:25,600 Speaker 3: but they didn't They never closed the elementary schools, they 226 00:12:25,640 --> 00:12:30,079 Speaker 3: never closed the day cares, and they kept the businesses 227 00:12:30,080 --> 00:12:34,240 Speaker 3: and restaurants open, so and and so on. So we know, 228 00:12:34,400 --> 00:12:37,200 Speaker 3: as it's kind of so that's the combination in that 229 00:12:37,240 --> 00:12:41,680 Speaker 3: the lockdowns didn't really prevent any death at the same 230 00:12:41,720 --> 00:12:45,360 Speaker 3: time the lockdowns that it didn't prevent COVID desk at 231 00:12:45,360 --> 00:12:49,719 Speaker 3: the same time it caused death on other aspects of 232 00:12:49,760 --> 00:12:53,439 Speaker 3: public health like quadiovascular disease or or mental health or 233 00:12:54,679 --> 00:12:55,480 Speaker 3: cancer and so on. 234 00:12:56,480 --> 00:12:58,440 Speaker 1: Well, and our remember, you know, Sweden came out of 235 00:12:58,440 --> 00:13:01,840 Speaker 1: a great scrutiny for you know, the way they decided 236 00:13:01,840 --> 00:13:05,040 Speaker 1: to handle COVID, but you know, it looks like in 237 00:13:05,120 --> 00:13:07,640 Speaker 1: terms of outcomes as you laid out, you know, they 238 00:13:07,640 --> 00:13:08,440 Speaker 1: came out on top. 239 00:13:10,080 --> 00:13:12,920 Speaker 3: Yeah, we'll see the same thing in the in the US, 240 00:13:12,960 --> 00:13:16,640 Speaker 3: for example, Florida, they locked down in the spring there, 241 00:13:16,679 --> 00:13:20,160 Speaker 3: but then they sort of took a different, more focused 242 00:13:20,160 --> 00:13:24,760 Speaker 3: protection approach and the Florida did slightly better than California 243 00:13:24,800 --> 00:13:27,240 Speaker 3: if you if you look at age just that COVID 244 00:13:27,280 --> 00:13:32,640 Speaker 3: mortality even though California locked down very harshly, so sort 245 00:13:32,640 --> 00:13:35,280 Speaker 3: of Florida to do well hasn't the lowest in the 246 00:13:35,440 --> 00:13:38,000 Speaker 3: in the state, but it's on the on the on 247 00:13:38,040 --> 00:13:42,120 Speaker 3: the positive half of states. We could also compare South Dakota, 248 00:13:42,640 --> 00:13:45,840 Speaker 3: who didn't lock down much compared to North Dakota, not 249 00:13:46,000 --> 00:13:50,200 Speaker 3: just next to it, and they. 250 00:13:48,800 --> 00:13:51,760 Speaker 2: Have a very similar COVID mortality. 251 00:13:53,040 --> 00:13:56,280 Speaker 1: Well, and we knew from really early on in the 252 00:13:56,280 --> 00:14:00,840 Speaker 1: pandemic that young people were not as impacted as elderly. 253 00:14:01,800 --> 00:14:05,160 Speaker 1: Yet you know, our public health officials never drew that distinction. 254 00:14:06,440 --> 00:14:08,559 Speaker 2: Yeah, that's sort of shocking because. 255 00:14:10,280 --> 00:14:14,640 Speaker 3: When the COVID reached northern Italy with outbreak there and 256 00:14:14,640 --> 00:14:17,240 Speaker 3: in Iran, which was the two places also of China 257 00:14:17,280 --> 00:14:20,080 Speaker 3: would where there was sort of outbreaks at the earliest. 258 00:14:21,120 --> 00:14:23,920 Speaker 3: I got scared for about ten twenty minutes because I 259 00:14:24,040 --> 00:14:26,680 Speaker 3: realized that, okay, this is going to reach. 260 00:14:26,560 --> 00:14:30,640 Speaker 2: The whole world. Sooner or late, they will reach every 261 00:14:30,640 --> 00:14:33,800 Speaker 2: corner of the globe. So I quickly looked. 262 00:14:33,560 --> 00:14:35,600 Speaker 3: At the data from vu Wan because we didn't have 263 00:14:35,640 --> 00:14:37,880 Speaker 3: any I don't think we had any mortality in the 264 00:14:38,000 --> 00:14:41,400 Speaker 3: US by that time. So I looked at the Vuan data, 265 00:14:42,200 --> 00:14:46,040 Speaker 3: and obviously people of all ages would have gotten affected 266 00:14:46,280 --> 00:14:49,840 Speaker 3: in Wuhan, but of the people who died, it was 267 00:14:51,080 --> 00:14:55,320 Speaker 3: heavily weighted towards all the people. So I did some 268 00:14:55,520 --> 00:14:58,960 Speaker 3: back of the envelope calculations and I concluded that the 269 00:14:59,000 --> 00:15:01,880 Speaker 3: difference in mortal at risk of mortality was more than 270 00:15:01,880 --> 00:15:03,960 Speaker 3: a thousand and four difference between the old and the young. 271 00:15:04,440 --> 00:15:06,760 Speaker 3: So then it was obvious that okay, we can. I 272 00:15:06,840 --> 00:15:08,920 Speaker 3: was so I was relieved because as a parent, I 273 00:15:09,000 --> 00:15:11,720 Speaker 3: care more about my chillers lives for my own life, 274 00:15:12,200 --> 00:15:14,040 Speaker 3: so I knew they would be fine. I was never 275 00:15:14,080 --> 00:15:15,920 Speaker 3: worried about them. 276 00:15:16,640 --> 00:15:17,600 Speaker 2: So it was August done. 277 00:15:17,600 --> 00:15:20,000 Speaker 3: We should let kids live their lives young and also 278 00:15:20,080 --> 00:15:25,080 Speaker 3: go about their business while we sort of maintaining society 279 00:15:25,280 --> 00:15:28,200 Speaker 3: was important society. While we let older people make sure 280 00:15:28,240 --> 00:15:32,920 Speaker 3: older people are protected. Instead, we protected the laptop class 281 00:15:32,920 --> 00:15:35,000 Speaker 3: who could work from home even if we are twenty 282 00:15:35,040 --> 00:15:38,360 Speaker 3: five years old and miniscule risk. Or we had sixty 283 00:15:38,360 --> 00:15:41,080 Speaker 3: five year old cab drivers out there driving cabs, and 284 00:15:41,800 --> 00:15:44,040 Speaker 3: that's one of the professions where they are most at 285 00:15:44,120 --> 00:15:48,440 Speaker 3: hirisks to be exposed. So the lockdowns was the biggest 286 00:15:48,440 --> 00:15:51,800 Speaker 3: assault on the working class and the middle class here 287 00:15:51,840 --> 00:15:54,960 Speaker 3: in the US since the segregation and the Vietnam War. 288 00:15:56,160 --> 00:15:57,920 Speaker 1: Well, and and to a point that you made earlier, 289 00:15:57,920 --> 00:16:00,960 Speaker 1: I mean, there is a real deep and twisted irony. 290 00:16:01,040 --> 00:16:04,640 Speaker 1: And you know, we were praising all these nurses and 291 00:16:05,000 --> 00:16:08,080 Speaker 1: healthcare workers who worked during the height of the pandemic 292 00:16:08,160 --> 00:16:10,360 Speaker 1: and got sick with COVID as a result, and then 293 00:16:10,720 --> 00:16:13,760 Speaker 1: we fired them if they decided not to get the vaccine, 294 00:16:13,880 --> 00:16:16,560 Speaker 1: when when they already had built up immunity, which, as 295 00:16:16,600 --> 00:16:19,160 Speaker 1: you pointed out, has been a thing since the beginning 296 00:16:19,160 --> 00:16:19,560 Speaker 1: of time. 297 00:16:21,280 --> 00:16:25,120 Speaker 3: It's it's astonishing and tragic, I think, and I think 298 00:16:25,160 --> 00:16:27,640 Speaker 3: all those nurses should be higher and back, they should 299 00:16:27,640 --> 00:16:31,200 Speaker 3: be off with their jobs back, so as well as 300 00:16:31,240 --> 00:16:32,320 Speaker 3: everybody else was fired. 301 00:16:32,880 --> 00:16:34,960 Speaker 2: Well, you know, I. 302 00:16:35,240 --> 00:16:37,040 Speaker 1: Think in you know, having had a lot of these 303 00:16:37,080 --> 00:16:40,720 Speaker 1: conversations with like truth tellers and people like you and 304 00:16:40,920 --> 00:16:44,960 Speaker 1: doctor Badicharia and doctor Atlas, who I've all had, you know, 305 00:16:45,000 --> 00:16:49,600 Speaker 1: on on my show, it seems like COVID in its entirety, 306 00:16:49,680 --> 00:16:51,760 Speaker 1: you know, and obviously was never about the truth. It 307 00:16:51,760 --> 00:16:54,160 Speaker 1: was never about the facts, it was never about the evidence. 308 00:16:55,040 --> 00:16:58,160 Speaker 1: It was more about people getting in line and then 309 00:16:58,200 --> 00:17:03,240 Speaker 1: punishing any dissenters. And that really was across the all fields. Right. 310 00:17:03,240 --> 00:17:05,400 Speaker 1: If you're in the media, you spoke out, they try 311 00:17:05,440 --> 00:17:07,679 Speaker 1: to punish you. If you're in the scientific community as 312 00:17:07,720 --> 00:17:10,480 Speaker 1: you are, they try to punish you. And it seems 313 00:17:10,520 --> 00:17:13,360 Speaker 1: like it was more about just shut up and cement. 314 00:17:15,119 --> 00:17:18,439 Speaker 3: It was a very authoritarian mindset, yes, And to me 315 00:17:18,560 --> 00:17:22,119 Speaker 3: that's sort of shocking. I thought that freewa speech was 316 00:17:22,160 --> 00:17:25,680 Speaker 3: sort of a pillar that everybody agreed on, and I 317 00:17:25,720 --> 00:17:28,359 Speaker 3: guess that's no longer the case, which is tragic. And 318 00:17:28,440 --> 00:17:31,200 Speaker 3: I think if we don't get back to the mindset 319 00:17:31,240 --> 00:17:33,159 Speaker 3: of fido or speech, I think that's the end of 320 00:17:33,240 --> 00:17:38,680 Speaker 3: Western civilization. I know, and I mean I know scientists 321 00:17:38,680 --> 00:17:41,280 Speaker 3: who were fired, I know physicians, nurses was fired. 322 00:17:41,359 --> 00:17:44,280 Speaker 2: I know journalist who was fired so on. 323 00:17:44,440 --> 00:17:47,320 Speaker 3: So yeah, it hit a lot of people, So I'm 324 00:17:47,359 --> 00:17:49,960 Speaker 3: not I'm not surprised that a lot of people just 325 00:17:50,040 --> 00:17:50,359 Speaker 3: to say it. 326 00:17:50,359 --> 00:17:52,440 Speaker 2: Don't going to shot my mouth. I'm not going to 327 00:17:52,600 --> 00:17:52,960 Speaker 2: risk my. 328 00:17:54,680 --> 00:17:59,520 Speaker 3: Income and my family for this, So I fully understand 329 00:17:59,560 --> 00:18:01,280 Speaker 3: that people would not speak out. 330 00:18:01,680 --> 00:18:04,720 Speaker 1: No, I like you in the sense of I can 331 00:18:04,760 --> 00:18:07,840 Speaker 1: see why people did not, but you know, like you, 332 00:18:08,000 --> 00:18:10,640 Speaker 1: I just I can't be one of those people. I'd 333 00:18:10,720 --> 00:18:14,200 Speaker 1: rather you know, if someone tells me you can't press 334 00:18:14,240 --> 00:18:16,840 Speaker 1: the red button, but pressing the red button is what 335 00:18:17,000 --> 00:18:18,640 Speaker 1: needs to be done, or is the right thing to do, 336 00:18:18,720 --> 00:18:21,000 Speaker 1: I'm just gonna do it, and I guess take the 337 00:18:21,040 --> 00:18:22,400 Speaker 1: consequences as they come. 338 00:18:23,119 --> 00:18:23,760 Speaker 2: Thank you, Lisa. 339 00:18:23,760 --> 00:18:25,760 Speaker 3: I'm glad that you have that attitude, and I think 340 00:18:25,800 --> 00:18:28,840 Speaker 3: that's important to have people like you so well, You're. 341 00:18:28,720 --> 00:18:30,960 Speaker 1: You're much more brave than me because this is my job. 342 00:18:31,119 --> 00:18:33,480 Speaker 1: You know, Like, I think you were a total coward 343 00:18:33,600 --> 00:18:35,960 Speaker 1: if you work in the media and you're unwilling to 344 00:18:35,960 --> 00:18:39,840 Speaker 1: be honest. But like you risked your career at Harvard 345 00:18:39,920 --> 00:18:42,119 Speaker 1: to speak out. I mean you didn't. You didn't have to, 346 00:18:42,200 --> 00:18:44,200 Speaker 1: you know, I mean, I think what you guys did 347 00:18:44,280 --> 00:18:44,920 Speaker 1: is what's brave. 348 00:18:45,359 --> 00:18:49,320 Speaker 3: I have to disagree with that. I'm a scientist. If 349 00:18:49,359 --> 00:18:53,040 Speaker 3: I was a chemist, I could keep quiet, But I'm 350 00:18:53,560 --> 00:18:56,400 Speaker 3: I'm an affection to SASE scientists, so it's my job 351 00:18:56,440 --> 00:18:58,840 Speaker 3: to speak up. I have no other choice in my view, 352 00:18:59,240 --> 00:19:01,720 Speaker 3: you know, That's all. 353 00:19:01,880 --> 00:19:04,880 Speaker 1: I read the column that you wrote. You had mentioned, 354 00:19:05,080 --> 00:19:08,359 Speaker 1: I know you're the CDC. You're briefly on the COVID 355 00:19:08,440 --> 00:19:12,200 Speaker 1: vaccine the Safety Technical work Group. It didn't last long 356 00:19:12,200 --> 00:19:14,359 Speaker 1: because again, you know, they don't they don't like people 357 00:19:14,359 --> 00:19:17,040 Speaker 1: who tell the truth or raised questions these days. But 358 00:19:17,080 --> 00:19:19,679 Speaker 1: you had mentioned that something that didn't sit right you 359 00:19:19,800 --> 00:19:22,399 Speaker 1: with you was that the randomized control trials for the 360 00:19:22,400 --> 00:19:25,560 Speaker 1: COVID vaccines were not properly designed. What do you mean 361 00:19:25,640 --> 00:19:29,840 Speaker 1: by that and how does that impact I guess the 362 00:19:29,880 --> 00:19:33,000 Speaker 1: safety of a vaccine or what we know about a 363 00:19:33,080 --> 00:19:34,040 Speaker 1: vaccine safety. 364 00:19:35,240 --> 00:19:40,320 Speaker 3: So whenever drag or vaccine is approved by FDA, they 365 00:19:40,359 --> 00:19:44,399 Speaker 3: have to do this. You need to do randomized trials 366 00:19:44,440 --> 00:19:47,720 Speaker 3: to show that it works. And so the good thing 367 00:19:47,800 --> 00:19:50,840 Speaker 3: with the COVID trials was that was randomized. That's a 368 00:19:50,880 --> 00:19:54,480 Speaker 3: good thing. The bad thing was that the outcome they 369 00:19:54,480 --> 00:19:59,119 Speaker 3: looked at was symptomatic disease. Now at all of this 370 00:19:59,240 --> 00:20:02,120 Speaker 3: on artless. But I don't really care if you're homesick 371 00:20:02,160 --> 00:20:08,080 Speaker 3: for a few days because I have to be in 372 00:20:08,119 --> 00:20:11,040 Speaker 3: bed for two days. What I care about is if 373 00:20:11,119 --> 00:20:13,600 Speaker 3: you die. I don't want you to die. I don't 374 00:20:13,600 --> 00:20:16,760 Speaker 3: want you to a little hospitalize either, So but that's 375 00:20:16,800 --> 00:20:20,679 Speaker 3: what matters. But these trials, the randomized trials that was 376 00:20:20,720 --> 00:20:25,879 Speaker 3: designed by fire Cera Moderna, they evaluated symptomatic COVID disease. 377 00:20:27,200 --> 00:20:32,760 Speaker 3: They didn't evaluate mortality or they recorded it. But they 378 00:20:32,800 --> 00:20:37,919 Speaker 3: recruited mostly young and middle aged adults, so they were 379 00:20:37,960 --> 00:20:40,760 Speaker 3: going to survive COVID no matter what the vast majority, 380 00:20:40,840 --> 00:20:43,159 Speaker 3: whether they were on the vaccine or the placebo. So 381 00:20:43,200 --> 00:20:46,960 Speaker 3: therefore it's not very informative in terms of seeing if 382 00:20:47,080 --> 00:20:49,800 Speaker 3: it prevents mortality or not. It's the informative in terms 383 00:20:49,880 --> 00:20:54,040 Speaker 3: of symptomatic disease, but that's only relevant or very little importance. 384 00:20:55,000 --> 00:20:56,800 Speaker 2: So they designed it wrongly. 385 00:20:56,520 --> 00:21:01,480 Speaker 3: And then and then they stop the trials too soon also, 386 00:21:01,560 --> 00:21:04,720 Speaker 3: so they only monitor this for a few months, and 387 00:21:04,760 --> 00:21:06,760 Speaker 3: we usually had trials that can go on for years 388 00:21:06,760 --> 00:21:11,920 Speaker 3: and years for cancer drag or something like that. So 389 00:21:12,320 --> 00:21:15,919 Speaker 3: that's also inappro inappropriate because that means we don't know. 390 00:21:15,960 --> 00:21:19,840 Speaker 3: We don't have strong randomized evidence whether for the long 391 00:21:19,920 --> 00:21:25,680 Speaker 3: time effect, both of efficacy and address reactions. So they 392 00:21:25,720 --> 00:21:32,119 Speaker 3: should have done designed these differently. And then they did correctly, 393 00:21:32,160 --> 00:21:36,240 Speaker 3: I think, decide not to recruit people who had already 394 00:21:36,280 --> 00:21:39,280 Speaker 3: had COVID and too when they had they had a few, 395 00:21:39,320 --> 00:21:41,199 Speaker 3: but they sort of removed that from the analysis, and 396 00:21:41,200 --> 00:21:43,760 Speaker 3: I think that was correct because we don't need these 397 00:21:43,840 --> 00:21:46,800 Speaker 3: vaccines for those. But then what was wrong was even 398 00:21:46,840 --> 00:21:50,200 Speaker 3: though it was tested on people without who hadn't had COVID, 399 00:21:50,760 --> 00:21:54,560 Speaker 3: it was also man that for people who had already 400 00:21:54,600 --> 00:21:59,080 Speaker 3: had COVID. But you don't think it would would would work, Uh, 401 00:21:59,200 --> 00:22:04,320 Speaker 3: we don't need So they were also using those trials 402 00:22:04,359 --> 00:22:07,680 Speaker 3: to do extrapolation that we didn't know. They also didn't 403 00:22:07,720 --> 00:22:09,639 Speaker 3: look at transmission. They could have done that if they 404 00:22:09,680 --> 00:22:13,520 Speaker 3: wanted to, but they didn't. But CDC was anyhow arguing 405 00:22:13,560 --> 00:22:17,080 Speaker 3: that this will stop transmission, which of course it didn't. 406 00:22:17,400 --> 00:22:21,840 Speaker 3: So the trials were designed were flawed. That doesn't mean 407 00:22:21,840 --> 00:22:24,800 Speaker 3: that the vaccine didn't save some people's life. I think 408 00:22:24,800 --> 00:22:27,600 Speaker 3: the vaccine did say in twenty twenty one, the lives 409 00:22:27,640 --> 00:22:31,240 Speaker 3: of older people when it comes to yago people, I 410 00:22:31,240 --> 00:22:34,919 Speaker 3: think is the big question mark, how what the benefit 411 00:22:35,040 --> 00:22:35,800 Speaker 3: this creature was? 412 00:22:36,000 --> 00:22:42,760 Speaker 1: Quick break stay with us? You Also, the CDC sort 413 00:22:42,760 --> 00:22:46,000 Speaker 1: of continuously changed the definition of what it means to 414 00:22:46,359 --> 00:22:48,920 Speaker 1: be vaccinated, changed the definition of it, you know. I 415 00:22:48,960 --> 00:22:51,400 Speaker 1: mean they kind of like twisted these things to meet 416 00:22:51,400 --> 00:22:54,000 Speaker 1: the criteria of what they knew the vaccine was doing. 417 00:22:54,560 --> 00:22:58,800 Speaker 1: Should we be worried about future vaccines? Has the process 418 00:22:58,880 --> 00:23:02,480 Speaker 1: been like taged and diminished in the kind of vaccine, 419 00:23:02,560 --> 00:23:05,359 Speaker 1: like the the what vaccines need to go through to 420 00:23:05,359 --> 00:23:07,080 Speaker 1: be put out to market? It just seems like the 421 00:23:07,160 --> 00:23:10,440 Speaker 1: rush nature in this sort of the failures and making 422 00:23:10,480 --> 00:23:13,120 Speaker 1: sure these were as safe and effective as they could be, 423 00:23:13,200 --> 00:23:16,359 Speaker 1: sort of the twisting of definitions like should we be 424 00:23:16,400 --> 00:23:19,640 Speaker 1: concerned about future vaccines? That sort of the approval process 425 00:23:19,640 --> 00:23:20,800 Speaker 1: has now been diminished. 426 00:23:21,280 --> 00:23:22,600 Speaker 2: Yeah, So I think. 427 00:23:24,440 --> 00:23:28,399 Speaker 3: I understand why people don't trust vaccines anymore because the 428 00:23:28,480 --> 00:23:31,119 Speaker 3: way that the COVID vaccine was handled was very poorly. 429 00:23:32,160 --> 00:23:35,400 Speaker 3: So I understand that then people start questioning. 430 00:23:34,920 --> 00:23:36,399 Speaker 2: You the vaccines. 431 00:23:38,000 --> 00:23:41,399 Speaker 3: Like tribate vaccines, but I mean sound vaccines are very important, 432 00:23:41,440 --> 00:23:44,760 Speaker 3: like the musle vaccines are very important, and the poorio vaccines. 433 00:23:46,119 --> 00:23:47,520 Speaker 2: But I don't know what the future. 434 00:23:47,600 --> 00:23:50,080 Speaker 3: I don't know if we will go back to doing 435 00:23:50,119 --> 00:23:51,919 Speaker 3: it in a more thorough way that we used to 436 00:23:51,960 --> 00:23:54,680 Speaker 3: do it, or if this is the new the new 437 00:23:54,680 --> 00:23:56,240 Speaker 3: way of doing things, And if this is a new 438 00:23:56,240 --> 00:23:59,800 Speaker 3: way of doing things, then nowahouldn't test that? And I 439 00:23:59,800 --> 00:24:02,520 Speaker 3: think think CDC has an enormous trust problem, and I 440 00:24:02,560 --> 00:24:03,440 Speaker 3: realized it themselves. 441 00:24:03,480 --> 00:24:04,560 Speaker 2: Now I don't know. 442 00:24:04,560 --> 00:24:06,680 Speaker 3: I don't think that quite realizes what is due to 443 00:24:07,440 --> 00:24:13,480 Speaker 3: but we have a trust problem. My thinking, my principle 444 00:24:13,560 --> 00:24:18,040 Speaker 3: is basic that if you have a scientist who refuses 445 00:24:18,119 --> 00:24:22,119 Speaker 3: to debate other scientists of of who have a different perspective, 446 00:24:22,160 --> 00:24:23,320 Speaker 3: you simply trust them. 447 00:24:23,720 --> 00:24:24,600 Speaker 2: We should always. 448 00:24:24,359 --> 00:24:28,680 Speaker 3: Trust scientists who are willing to put themselves out there 449 00:24:28,760 --> 00:24:33,640 Speaker 3: and discuss and debate their views with other scientists who 450 00:24:33,760 --> 00:24:34,440 Speaker 3: think differently. 451 00:24:35,359 --> 00:24:37,959 Speaker 1: Well, I think what's scary and where we are now 452 00:24:38,040 --> 00:24:39,720 Speaker 1: which is not a good place to be in it 453 00:24:39,760 --> 00:24:41,679 Speaker 1: And it's because of her, the failure of our public 454 00:24:41,680 --> 00:24:45,320 Speaker 1: health officials and also mind you you know higher education 455 00:24:45,560 --> 00:24:50,400 Speaker 1: like have Harvard firing people like you. Is that they've 456 00:24:50,440 --> 00:24:53,359 Speaker 1: lost all this trust and lost all this faith over 457 00:24:53,800 --> 00:24:57,160 Speaker 1: a virus. It even the CDC acknowledges now is essentially 458 00:24:57,160 --> 00:24:59,840 Speaker 1: the flu right you know, even you had mentioned polio. Okay, 459 00:24:59,880 --> 00:25:02,880 Speaker 1: so adults for polios at fifteen to thirty percent fatality rate, 460 00:25:02,880 --> 00:25:06,760 Speaker 1: that's a real fatality rate, right. So what happens if 461 00:25:06,800 --> 00:25:09,639 Speaker 1: we have a virus in the future with a real, 462 00:25:09,760 --> 00:25:13,639 Speaker 1: real fatality rate and you have an entire population that 463 00:25:13,760 --> 00:25:16,040 Speaker 1: doesn't trust your public health officials now has a fear 464 00:25:16,080 --> 00:25:19,080 Speaker 1: of vaccines, has a fear of what we're told. So 465 00:25:19,119 --> 00:25:20,720 Speaker 1: it's like, you know what happens, then. 466 00:25:21,880 --> 00:25:25,359 Speaker 3: Well that's a problem. Supposed that comes a very serious pandemic. 467 00:25:25,440 --> 00:25:28,560 Speaker 3: I suppose we come up with the vaccine that's perfect, 468 00:25:28,720 --> 00:25:31,480 Speaker 3: no flaws. There are people who are not going to 469 00:25:31,560 --> 00:25:34,480 Speaker 3: take the vaccine because they don't trust CDC or FJA anymore. 470 00:25:35,800 --> 00:25:37,440 Speaker 1: I mean, if you tell me to get it, I'll 471 00:25:37,440 --> 00:25:41,679 Speaker 1: get it. But if the faucies of the world tell me, 472 00:25:41,760 --> 00:25:44,720 Speaker 1: I'll tell them to pound stand. You know, I what 473 00:25:44,800 --> 00:25:46,000 Speaker 1: if a thing I want to get you on because 474 00:25:46,040 --> 00:25:49,280 Speaker 1: I thought this was interesting and totally a side note 475 00:25:50,560 --> 00:25:52,320 Speaker 1: you had written in the column that you wrote in 476 00:25:52,320 --> 00:25:54,919 Speaker 1: the column that you had about that you worked for 477 00:25:55,000 --> 00:25:59,879 Speaker 1: human rights organization in Guatemala in nineteen eighty and you 478 00:26:00,160 --> 00:26:03,400 Speaker 1: had two colleagues that were stabbed and a hand grenade 479 00:26:03,400 --> 00:26:05,480 Speaker 1: that was thrown in the house where you all lived 480 00:26:05,480 --> 00:26:07,360 Speaker 1: and worked. Tell us about that story. 481 00:26:08,520 --> 00:26:11,399 Speaker 3: Yeah, So after it was a student, I worked as 482 00:26:11,400 --> 00:26:17,800 Speaker 3: the human rights observing Guatemala in nineteen eighty nine, and 483 00:26:17,920 --> 00:26:21,800 Speaker 3: this was during the military dictatorship there, so people who 484 00:26:21,840 --> 00:26:25,080 Speaker 3: were opposing and was trying There was no freedom of speech, 485 00:26:25,119 --> 00:26:27,400 Speaker 3: for example, so people who were speaking up, they were 486 00:26:27,840 --> 00:26:32,119 Speaker 3: sometimes killed. Sometimes that just disappeared, was taken from the 487 00:26:32,119 --> 00:26:33,680 Speaker 3: street and nobody knew what happened to them. 488 00:26:34,240 --> 00:26:37,400 Speaker 2: So there were several very brave Guatemalas. 489 00:26:37,440 --> 00:26:40,359 Speaker 3: There was the mothers of the disappears, for example, whose 490 00:26:40,600 --> 00:26:42,680 Speaker 3: sons and daughters had been disappeared and who were sort 491 00:26:42,680 --> 00:26:44,720 Speaker 3: of demonstrating and trying to find out what happened to 492 00:26:44,760 --> 00:26:48,800 Speaker 3: their children. There were campusenos who was working against enforced 493 00:26:48,960 --> 00:26:54,400 Speaker 3: military conscriptions. There were trade unionists, student groups, women's groups 494 00:26:55,040 --> 00:26:58,840 Speaker 3: and so on who were oppressed because they didn't have 495 00:26:58,880 --> 00:27:01,680 Speaker 3: the feedom of speech to speak cup. So we were 496 00:27:01,680 --> 00:27:06,440 Speaker 3: there to accompany them as the international because the military 497 00:27:06,520 --> 00:27:09,679 Speaker 3: had were concerned about the international reputations. So I was 498 00:27:09,720 --> 00:27:13,520 Speaker 3: walking around with these people. It's very brave Guatemalans to 499 00:27:13,720 --> 00:27:17,640 Speaker 3: help protect them from something happening to them, and we 500 00:27:17,640 --> 00:27:20,159 Speaker 3: were a nuisance to the military dictators. So at one 501 00:27:20,240 --> 00:27:22,320 Speaker 3: point they tried to scare us away from the country. 502 00:27:22,359 --> 00:27:24,560 Speaker 3: So two of my college were stabbed as they were 503 00:27:24,560 --> 00:27:27,640 Speaker 3: working on the street, and at one point they threw 504 00:27:27,720 --> 00:27:31,880 Speaker 3: hangunade into the house, our house where sort of everybody 505 00:27:31,920 --> 00:27:37,199 Speaker 3: lived and worked. So at that time, I guess I 506 00:27:37,320 --> 00:27:40,280 Speaker 3: sort of risked my life to support the freedom of 507 00:27:40,320 --> 00:27:47,000 Speaker 3: speech and democracy and the lives of people. So it 508 00:27:47,080 --> 00:27:49,000 Speaker 3: was an easy decision to do the same other wriddle 509 00:27:49,080 --> 00:27:54,880 Speaker 3: pandemic because while I was landed and there were takedowns 510 00:27:54,920 --> 00:27:58,359 Speaker 3: from highest sources of them as director against me, I 511 00:27:58,480 --> 00:28:02,200 Speaker 3: never I never risked my life to do during this pandemic. 512 00:28:02,359 --> 00:28:05,640 Speaker 1: So I guess what do you think the toughest part 513 00:28:06,000 --> 00:28:09,760 Speaker 1: about that, about just going through COVID has has been 514 00:28:09,800 --> 00:28:14,000 Speaker 1: for you? You know, I assume it's it's got to 515 00:28:14,040 --> 00:28:17,960 Speaker 1: be really disheartening to have spent you know, your entire 516 00:28:18,000 --> 00:28:21,920 Speaker 1: career really trying to help the public, inform the public, 517 00:28:22,080 --> 00:28:27,199 Speaker 1: keep the public safe, and then to be slandered in 518 00:28:27,240 --> 00:28:29,840 Speaker 1: the manner in which you've been, that's got to be 519 00:28:30,240 --> 00:28:31,520 Speaker 1: that's got to be really frustrating. 520 00:28:32,280 --> 00:28:34,600 Speaker 3: I think the hardest part is so in the past 521 00:28:34,800 --> 00:28:37,800 Speaker 3: when I meet new people and we talked and so 522 00:28:37,880 --> 00:28:39,720 Speaker 3: what do you do? And I say, I'm a scientist. 523 00:28:40,480 --> 00:28:42,440 Speaker 3: And I was always so proud to say, oh, I'm 524 00:28:42,480 --> 00:28:46,040 Speaker 3: a scientist, and that was sort of my self identity 525 00:28:46,080 --> 00:28:49,200 Speaker 3: and private entity. And now people ask I can no 526 00:28:49,320 --> 00:28:51,840 Speaker 3: longer say that, I'm not long proud to say that 527 00:28:51,880 --> 00:28:54,280 Speaker 3: I'm a scientist because I think science has failed, the 528 00:28:54,320 --> 00:28:57,200 Speaker 3: scientists community has failed during this pandemic. 529 00:28:58,160 --> 00:29:01,240 Speaker 2: So and it's. 530 00:29:01,080 --> 00:29:06,719 Speaker 3: Disheartening that that the scientific community was not able to 531 00:29:06,720 --> 00:29:09,240 Speaker 3: to to to sort of stand up and do the 532 00:29:09,320 --> 00:29:14,760 Speaker 3: right thing during this pandemic. But uh basically did while 533 00:29:14,840 --> 00:29:18,720 Speaker 3: they were told by the by the leadership in that 534 00:29:18,840 --> 00:29:19,960 Speaker 3: of Foucy and others. 535 00:29:20,480 --> 00:29:22,560 Speaker 2: And that's true. 536 00:29:24,120 --> 00:29:27,320 Speaker 3: That's that's that's that's sad that we cannot be proud 537 00:29:27,320 --> 00:29:29,040 Speaker 3: to be of being scientists anymore. 538 00:29:30,520 --> 00:29:33,280 Speaker 1: Where can people stay on top of your work? Where 539 00:29:33,320 --> 00:29:34,640 Speaker 1: is the best place for them to find you? 540 00:29:35,400 --> 00:29:38,520 Speaker 3: So together with well they can reach They can see 541 00:29:38,520 --> 00:29:41,480 Speaker 3: me on Twitter or LinkedIn other social media like cab 542 00:29:41,560 --> 00:29:45,680 Speaker 3: or ghats through social but also with the able to 543 00:29:45,760 --> 00:29:49,040 Speaker 3: try and Scott Atlas, we we have the sort of 544 00:29:49,040 --> 00:29:52,880 Speaker 3: the Academy for Science and Freedom together with the Hillsdale College, 545 00:29:53,760 --> 00:29:56,760 Speaker 3: which is an attempt to sort of restore the integrity 546 00:29:57,240 --> 00:29:59,600 Speaker 3: of the scientific community. And that's maybe a long. 547 00:30:01,000 --> 00:30:01,120 Speaker 1: Well. 548 00:30:01,160 --> 00:30:03,280 Speaker 3: I never doubted that we will eventually prove the right 549 00:30:03,400 --> 00:30:06,800 Speaker 3: about the pandemic when it comes to academia. I think 550 00:30:06,880 --> 00:30:09,360 Speaker 3: it's the fifty fifty child that we're able to sort 551 00:30:09,360 --> 00:30:12,640 Speaker 3: of steer the right ship in the right direction, versus 552 00:30:12,640 --> 00:30:17,160 Speaker 3: is sort of going further downhill. So we'll see how 553 00:30:17,200 --> 00:30:19,160 Speaker 3: that works, but at least you have to try it. 554 00:30:19,560 --> 00:30:22,680 Speaker 3: So I've Kennedy for Science and Freedom. 555 00:30:22,760 --> 00:30:25,160 Speaker 1: Martin Colder, I just want to thank you. I've got 556 00:30:25,280 --> 00:30:27,480 Speaker 1: to know a lot of you guys throughout COVID, and 557 00:30:27,720 --> 00:30:30,560 Speaker 1: I just it really is brave what you guys have done. 558 00:30:30,680 --> 00:30:33,200 Speaker 1: I don't think people really fully understand just what you 559 00:30:33,200 --> 00:30:36,240 Speaker 1: guys have been put through, the thing, you know, just 560 00:30:36,320 --> 00:30:38,880 Speaker 1: even attacks for your family, just all of it. And 561 00:30:39,720 --> 00:30:41,800 Speaker 1: you really are a brave man, a good man, And 562 00:30:42,200 --> 00:30:43,760 Speaker 1: I just want to thank you for the bottom of 563 00:30:43,760 --> 00:30:46,760 Speaker 1: my heart for being so brave and really just fighting 564 00:30:46,800 --> 00:30:48,040 Speaker 1: for the truth so fearlessly. 565 00:30:49,000 --> 00:30:52,160 Speaker 3: And thank you Lisa, because to be honest, I haven't. 566 00:30:52,520 --> 00:30:56,280 Speaker 3: I don't have a very good esteemed to most journalists anymore, 567 00:30:56,360 --> 00:31:00,720 Speaker 3: but you are shining light in the dark a professional 568 00:31:00,720 --> 00:31:01,320 Speaker 3: there right now. 569 00:31:01,760 --> 00:31:03,440 Speaker 1: Thank you, sir. That means the world to me. I 570 00:31:03,480 --> 00:31:05,800 Speaker 1: really appreciate you making the time. I'm looking forward to 571 00:31:06,080 --> 00:31:09,440 Speaker 1: saying all the things that you guys accomplish at Hillsdale 572 00:31:09,640 --> 00:31:12,719 Speaker 1: and just everything moving forward, and just really appreciate you. 573 00:31:13,000 --> 00:31:14,239 Speaker 2: Thank you, thanks for having me on. 574 00:31:15,440 --> 00:31:18,360 Speaker 1: That was doctor Martin Kolder. Just really appreciate him making 575 00:31:18,400 --> 00:31:20,200 Speaker 1: the time. He's a good man, he's a brave man. 576 00:31:20,400 --> 00:31:22,280 Speaker 1: I want to thank you guys at home for listening. 577 00:31:22,440 --> 00:31:24,440 Speaker 1: I also want to think John Cassio and my producer 578 00:31:24,480 --> 00:31:26,400 Speaker 1: for putting the show together. Until next time,