1 00:00:15,304 --> 00:00:15,824 Speaker 1: Pushkin. 2 00:00:20,264 --> 00:00:23,824 Speaker 2: I'm Brandy Seedrasni, and I wrote Conspiracy theorists made Tiffany 3 00:00:23,864 --> 00:00:27,024 Speaker 2: Dover into an anti vaccine icon. She's finally ready to 4 00:00:27,104 --> 00:00:29,824 Speaker 2: talk about it for NBC News, and it's the story 5 00:00:29,824 --> 00:00:30,264 Speaker 2: of the week. 6 00:00:31,544 --> 00:00:34,824 Speaker 1: I went to Basic Training in Fort Knox, Kentucky to 7 00:00:34,904 --> 00:00:38,304 Speaker 1: serve my country. My method of serving was to get 8 00:00:38,344 --> 00:00:40,424 Speaker 1: the Army to pay for me to do three days 9 00:00:40,424 --> 00:00:42,704 Speaker 1: at boot camp and let me be the first civilian 10 00:00:42,744 --> 00:00:44,944 Speaker 1: to ever fire a tank so I could write about 11 00:00:44,944 --> 00:00:47,704 Speaker 1: it in my book Man Made. We all have different 12 00:00:47,744 --> 00:00:51,344 Speaker 1: ways of giving back. I was so nervous the night 13 00:00:51,384 --> 00:00:55,024 Speaker 1: before Basic training that I couldn't fall asleep until two hundred, 14 00:00:55,744 --> 00:00:57,984 Speaker 1: which was a real problem because I had to wake 15 00:00:58,064 --> 00:01:01,384 Speaker 1: up at four forty five. When I got there, a 16 00:01:01,464 --> 00:01:04,904 Speaker 1: barber immediately shaved my head, and then these two incredibly 17 00:01:05,024 --> 00:01:08,544 Speaker 1: hostile sergeants shoved a uniform in my hands and started 18 00:01:08,584 --> 00:01:11,424 Speaker 1: screaming me for putting it on too slowly. It should 19 00:01:11,504 --> 00:01:14,584 Speaker 1: not be taking this long to put boots on. They 20 00:01:14,624 --> 00:01:18,224 Speaker 1: screamed at me for not standing attention, for using sir 21 00:01:18,344 --> 00:01:21,264 Speaker 1: when I should have used drill sergeant, for my cap 22 00:01:21,424 --> 00:01:24,704 Speaker 1: being at a jaunty angle that looked totally straight to me. 23 00:01:25,384 --> 00:01:28,464 Speaker 1: I was stressed, sweating more than I'd ever in my life, 24 00:01:28,824 --> 00:01:31,544 Speaker 1: and it wasn't because it was ninety degrees out. Then 25 00:01:31,584 --> 00:01:34,824 Speaker 1: they forced me to eat this cold, ready to eat 26 00:01:34,984 --> 00:01:38,944 Speaker 1: chicken fajida at seven hundred, and they led me outside 27 00:01:38,944 --> 00:01:40,904 Speaker 1: finally to where they keep the tanks, and I stood 28 00:01:40,904 --> 00:01:44,104 Speaker 1: at attention and tried to listen to this lecture on tanking, 29 00:01:44,704 --> 00:01:47,584 Speaker 1: but instead I found that, to my great surprise, I 30 00:01:47,664 --> 00:01:50,504 Speaker 1: was sitting against a tree trunk, which was weird because 31 00:01:50,504 --> 00:01:53,344 Speaker 1: I didn't remember anyone ordering me to sit against a 32 00:01:53,344 --> 00:01:57,464 Speaker 1: tree trunk. I'd fainted for the first time of my 33 00:01:57,504 --> 00:02:01,144 Speaker 1: life at thirty eight years old. They said it was 34 00:02:01,184 --> 00:02:05,064 Speaker 1: because I locked my knees, but I blame the cold 35 00:02:05,064 --> 00:02:08,384 Speaker 1: fahedas and maybe the stress of pretending to be in 36 00:02:08,384 --> 00:02:11,744 Speaker 1: the army. The sergeant said that I had to fly home, 37 00:02:12,024 --> 00:02:15,424 Speaker 1: canceling my three days of boot camp, but I somehow 38 00:02:15,464 --> 00:02:18,304 Speaker 1: convinced them to let me stay and fire that tank. 39 00:02:19,264 --> 00:02:23,424 Speaker 1: I was really lucky, because when this woman in Tennessee fainted, 40 00:02:23,824 --> 00:02:26,704 Speaker 1: the consequences were far far worse. 41 00:02:33,624 --> 00:02:36,824 Speaker 3: Writing is hard. Who's got that kind of time when 42 00:02:36,824 --> 00:02:40,064 Speaker 3: you're already busy trying to feed you all stand. So 43 00:02:40,224 --> 00:02:43,624 Speaker 3: it turns on a Mike made the twiddles enop because 44 00:02:43,664 --> 00:02:47,024 Speaker 3: a journalist friend has got in that juble job. Out 45 00:02:47,024 --> 00:02:51,784 Speaker 3: of tories, single story, just listen to smart people speak. 46 00:02:53,544 --> 00:02:54,184 Speaker 1: Conversation. 47 00:02:54,584 --> 00:02:57,224 Speaker 3: Film with Information is the story of. 48 00:03:07,504 --> 00:03:10,064 Speaker 1: Tiffany Dover is a nurse in Tennessee who was one 49 00:03:10,064 --> 00:03:12,264 Speaker 1: of the very first in the nation to get a 50 00:03:12,264 --> 00:03:15,024 Speaker 1: COVID vaccine. When she got her shot in front of 51 00:03:15,024 --> 00:03:20,144 Speaker 1: local TV reporters, she fainted. Conspiracy theorists were convinced she died. 52 00:03:20,904 --> 00:03:24,984 Speaker 1: Brandy's a Drosny, a reporter at NBC, wrote articles, made 53 00:03:24,984 --> 00:03:27,944 Speaker 1: a podcast, and did on air reports trying to find 54 00:03:27,984 --> 00:03:32,704 Speaker 1: out what really happened to Tiffany Dover. Brandy, thank you 55 00:03:32,984 --> 00:03:35,824 Speaker 1: for coming on the show, and I think thank you 56 00:03:35,864 --> 00:03:37,944 Speaker 1: for telling me about this story, although maybe I would 57 00:03:37,944 --> 00:03:43,424 Speaker 1: have been better off never knowing about it. Same you 58 00:03:44,144 --> 00:03:48,184 Speaker 1: did this incredible podcast and on air reporting and articles 59 00:03:48,184 --> 00:03:52,264 Speaker 1: about Tiffany Dover. Who is she and what was her life? 60 00:03:52,504 --> 00:03:53,304 Speaker 1: Pre pandemic. 61 00:03:53,984 --> 00:03:59,264 Speaker 2: Tiffany Dover was a thirty one year old nurse manager 62 00:03:59,504 --> 00:04:02,664 Speaker 2: in Chattanooga, Tennessee. She was sort of beloved by her 63 00:04:02,704 --> 00:04:04,944 Speaker 2: team and she was just doing a really good job 64 00:04:05,064 --> 00:04:07,504 Speaker 2: she was a mom of two, She was a doting wife, 65 00:04:08,584 --> 00:04:10,744 Speaker 2: just a normal person. 66 00:04:11,144 --> 00:04:14,504 Speaker 1: And she is like a pretty blonde, blue eyed woman 67 00:04:14,544 --> 00:04:17,664 Speaker 1: who looks like all of the women like CNN covers 68 00:04:17,664 --> 00:04:18,384 Speaker 1: when there's a crime. 69 00:04:19,144 --> 00:04:21,624 Speaker 2: Yes, she is very much like that. She is your 70 00:04:21,704 --> 00:04:24,464 Speaker 2: sort of prototypical missing white woman. 71 00:04:25,104 --> 00:04:29,944 Speaker 1: Right. It almost seems fake how much she fits this stereotype. 72 00:04:29,944 --> 00:04:32,904 Speaker 1: Like she loves horses. There's pictures of her with horses 73 00:04:32,904 --> 00:04:34,464 Speaker 1: all over social media. 74 00:04:34,704 --> 00:04:37,784 Speaker 2: Yeah, I mean, I think that part of why her 75 00:04:37,824 --> 00:04:40,824 Speaker 2: story grabbed the attention of so many people was actually 76 00:04:40,864 --> 00:04:44,264 Speaker 2: because of the way she looked. She was beautiful, She 77 00:04:44,384 --> 00:04:47,184 Speaker 2: was all over social media. She posted about her whole life, 78 00:04:47,224 --> 00:04:50,024 Speaker 2: so you got to really see her from her twenties 79 00:04:50,384 --> 00:04:52,584 Speaker 2: until she became a mother, and like throughout her life, 80 00:04:52,864 --> 00:04:56,624 Speaker 2: you really feel like you knew her. She documented every 81 00:04:56,784 --> 00:04:58,864 Speaker 2: event of her life, including. 82 00:04:58,424 --> 00:05:02,464 Speaker 1: Her nursing work and COVID hits. Her job must get 83 00:05:02,664 --> 00:05:04,344 Speaker 1: insanely stressful. 84 00:05:03,864 --> 00:05:08,584 Speaker 2: Right, Yeah, the job stank. Honestly, the nurses really felt 85 00:05:08,584 --> 00:05:11,264 Speaker 2: like they were fighting this battle that the rest of 86 00:05:11,304 --> 00:05:14,464 Speaker 2: the hospital was just absolutely unaware of. You know, once 87 00:05:14,504 --> 00:05:16,184 Speaker 2: you got through those double doors, they said, it was 88 00:05:16,224 --> 00:05:18,544 Speaker 2: a whole different world because even people from the other 89 00:05:18,584 --> 00:05:21,264 Speaker 2: areas of the hospital. They didn't go in this place. 90 00:05:21,544 --> 00:05:26,544 Speaker 2: It really was an isolated, just place of constant death 91 00:05:26,744 --> 00:05:29,984 Speaker 2: and sadness and fear, and it's just it really it 92 00:05:30,024 --> 00:05:30,784 Speaker 2: was really hard. 93 00:05:31,064 --> 00:05:35,064 Speaker 1: And then finally the vaccines came out. I remember getting 94 00:05:35,144 --> 00:05:37,704 Speaker 1: my vaccine and waiting in line, and I just I 95 00:05:37,744 --> 00:05:42,984 Speaker 1: started crying because I thought, Oh, some small group of 96 00:05:43,424 --> 00:05:46,864 Speaker 1: experts have saved us while I sat in like a 97 00:05:46,944 --> 00:05:49,784 Speaker 1: room writing articles about zoom shirts, and I was just 98 00:05:49,824 --> 00:05:53,344 Speaker 1: really grateful and kind of in awe. I guess that 99 00:05:53,504 --> 00:05:56,624 Speaker 1: was in April or so. But back in December, the 100 00:05:56,664 --> 00:05:59,904 Speaker 1: first people to get the shots were healthcare workers. So 101 00:06:00,384 --> 00:06:04,744 Speaker 1: what happened on December seventeenth, twenty twenty at this hospital 102 00:06:04,784 --> 00:06:05,424 Speaker 1: in Chattanooga. 103 00:06:06,224 --> 00:06:08,864 Speaker 2: Tiffany Dover is told that they are going to do 104 00:06:08,904 --> 00:06:12,224 Speaker 2: the vaccine rollout and they're giving it to the COVID 105 00:06:12,424 --> 00:06:15,744 Speaker 2: unit first, and would she like to be on video 106 00:06:16,064 --> 00:06:18,224 Speaker 2: for the PR Department. Would that be okay? 107 00:06:18,304 --> 00:06:20,424 Speaker 1: She says sure, because they know it's going to be 108 00:06:20,544 --> 00:06:23,064 Speaker 1: a challenge to convince some people to get the vaccine, 109 00:06:23,064 --> 00:06:26,504 Speaker 1: so they want to prove that it's safe. I assume 110 00:06:26,544 --> 00:06:28,504 Speaker 1: that's why they're doing this. Lots of hospitals are doing 111 00:06:28,504 --> 00:06:28,904 Speaker 1: this right. 112 00:06:29,064 --> 00:06:31,224 Speaker 2: Right. The hospital had the fourth thought to say, you 113 00:06:31,264 --> 00:06:34,104 Speaker 2: know what, we are in an area where there is 114 00:06:34,144 --> 00:06:37,264 Speaker 2: a lot of vaccine hesitancy. The pr staff thought this 115 00:06:37,304 --> 00:06:41,064 Speaker 2: would be a great opportunity to highlight the safety of 116 00:06:41,064 --> 00:06:43,744 Speaker 2: the vaccine and how frontline workers were all lining up 117 00:06:43,744 --> 00:06:44,904 Speaker 2: and very excited to have it. 118 00:06:45,104 --> 00:06:49,784 Speaker 1: Okay, so they're live streaming this momentous event and Tiffany 119 00:06:49,864 --> 00:06:53,184 Speaker 1: is going to be getting the shot on live stream. 120 00:06:53,304 --> 00:06:57,784 Speaker 2: Yeah, so she got the vaccine. Everybody clapped, and then 121 00:06:58,304 --> 00:07:01,144 Speaker 2: she sat down and that was really the end of it. 122 00:07:01,904 --> 00:07:05,584 Speaker 2: But afterwards, a couple of people got back up, an administrator, 123 00:07:05,984 --> 00:07:08,024 Speaker 2: a doctor, and they talked about what the vaccine meant 124 00:07:08,024 --> 00:07:10,424 Speaker 2: to them. And then you heard someone off camera say, 125 00:07:11,184 --> 00:07:13,264 Speaker 2: do we want to get anybody else to talk? Maybe 126 00:07:13,264 --> 00:07:17,464 Speaker 2: a nurse, And that was the invitation for Tiffany Dover 127 00:07:17,584 --> 00:07:20,504 Speaker 2: to get up and talk about the vaccine. She got up, 128 00:07:20,744 --> 00:07:23,584 Speaker 2: she started talking about how this vaccine was light at 129 00:07:23,584 --> 00:07:25,704 Speaker 2: the end of the tunnel, and then you could just 130 00:07:26,664 --> 00:07:29,224 Speaker 2: see it in her eyes. She sort of got a 131 00:07:29,344 --> 00:07:34,064 Speaker 2: vacant look and she touches her forehead and she just says, 132 00:07:34,544 --> 00:07:38,624 Speaker 2: I'm sorry and collapses into the arms of a doctor 133 00:07:38,624 --> 00:07:42,144 Speaker 2: and an administrator behind her, and she dies. That's right, 134 00:07:42,304 --> 00:07:49,144 Speaker 2: thank you for having me. No, she faints, which happens 135 00:07:49,224 --> 00:07:54,864 Speaker 2: when people get vaccines. Sometimes Tiffany has this overactive vasovagal response, 136 00:07:54,944 --> 00:07:58,664 Speaker 2: so when she experiences pain, sometimes she just passes out. 137 00:07:58,704 --> 00:08:00,984 Speaker 2: It's something that our family knows about her. It's sort 138 00:08:00,984 --> 00:08:01,464 Speaker 2: of common. 139 00:08:02,064 --> 00:08:04,264 Speaker 1: It is not common. I've never heard of anyone having this. 140 00:08:04,344 --> 00:08:06,904 Speaker 1: And why if you had this thing where you faint 141 00:08:07,024 --> 00:08:10,024 Speaker 1: all the time at slight pain, why would you go 142 00:08:10,144 --> 00:08:12,864 Speaker 1: up there to be on camera when you get a shot. 143 00:08:13,144 --> 00:08:15,424 Speaker 2: So usually if she feels it coming on, she can 144 00:08:15,464 --> 00:08:17,264 Speaker 2: sit down and she'll be fine. But you know, when 145 00:08:17,304 --> 00:08:20,024 Speaker 2: you like you tell yourself something in your mind, You're like, 146 00:08:20,384 --> 00:08:22,744 Speaker 2: come on, body, do this thing. 147 00:08:23,144 --> 00:08:25,304 Speaker 1: As you get older, it happens more and more. I 148 00:08:25,384 --> 00:08:27,424 Speaker 1: know we won't get into that details here. 149 00:08:27,304 --> 00:08:31,544 Speaker 2: But trust me, but I've never gotten so many that 150 00:08:31,584 --> 00:08:33,544 Speaker 2: happens to me all the time. We have a lot 151 00:08:33,584 --> 00:08:34,784 Speaker 2: of fainters in this country. 152 00:08:34,864 --> 00:08:36,704 Speaker 1: So there's always that kid in your high school, right 153 00:08:36,704 --> 00:08:36,984 Speaker 1: who was. 154 00:08:36,984 --> 00:08:39,224 Speaker 2: Just fanning all the time though in gym class. 155 00:08:40,344 --> 00:08:41,144 Speaker 1: Have you ever fainnd it? 156 00:08:41,424 --> 00:08:43,784 Speaker 2: Yeah, I fainted on the subway once in New York. 157 00:08:44,064 --> 00:08:45,744 Speaker 1: Were you freaked out? I mean, that's a bad place 158 00:08:45,744 --> 00:08:46,064 Speaker 1: to faint. 159 00:08:46,384 --> 00:08:48,464 Speaker 2: No, No, it's a great place to faint. I feel 160 00:08:48,504 --> 00:08:50,184 Speaker 2: like everybody sort of comes together to help. 161 00:08:50,304 --> 00:08:53,504 Speaker 1: This is not what the Kitty Genevezi story tells us, 162 00:08:53,504 --> 00:08:55,944 Speaker 1: But I like that your story tells us that New 163 00:08:56,024 --> 00:08:57,864 Speaker 1: Yorkers will rally together and help. 164 00:08:58,184 --> 00:08:58,984 Speaker 2: I think that they do. 165 00:08:59,584 --> 00:09:02,944 Speaker 1: Okay, So what happens after Tiffany fans. 166 00:09:03,984 --> 00:09:08,544 Speaker 2: Tiffany faints, she gets back up, she gives another interview 167 00:09:08,704 --> 00:09:13,384 Speaker 2: to the local reporter and says, I'm fine. I faint 168 00:09:13,424 --> 00:09:16,544 Speaker 2: a lot. I'm still glad I got the vaccine. I'm 169 00:09:16,664 --> 00:09:18,904 Speaker 2: gonna go back to my job now. And she says 170 00:09:18,944 --> 00:09:22,024 Speaker 2: to one of our nurses, She's like, ugh, I just fainted, 171 00:09:22,664 --> 00:09:25,304 Speaker 2: and he said, yeah, I know, I saw you. It's 172 00:09:25,344 --> 00:09:28,544 Speaker 2: on Facebook live stream. And that's when she first realized 173 00:09:28,584 --> 00:09:31,384 Speaker 2: that this was going to embarrass her, at least locally. 174 00:09:31,504 --> 00:09:34,024 Speaker 2: She thought, you know, her nurse told her, you know, 175 00:09:34,064 --> 00:09:36,784 Speaker 2: don't worry about it. It's just a local broadcast. It 176 00:09:36,824 --> 00:09:39,824 Speaker 2: won't matter. Like It's going to be fine. And it's 177 00:09:39,864 --> 00:09:44,064 Speaker 2: being replayed thousands and thousands of times because people were 178 00:09:44,104 --> 00:09:47,944 Speaker 2: waiting for something like this. People in the spaces that 179 00:09:48,144 --> 00:09:51,144 Speaker 2: I sit in as a reporter, the anti vax spaces, 180 00:09:51,304 --> 00:09:55,224 Speaker 2: the conspiracy theory spaces, they were watching all of these 181 00:09:55,264 --> 00:09:58,184 Speaker 2: live streams all around the country and when they saw 182 00:09:58,384 --> 00:10:01,424 Speaker 2: Tiffany Feint, they shared it within their group. And the 183 00:10:01,544 --> 00:10:05,104 Speaker 2: underlying reason that they were sharing is, look at this, 184 00:10:05,584 --> 00:10:07,624 Speaker 2: it's obviously dangerous. 185 00:10:07,544 --> 00:10:10,664 Speaker 1: And this is where that night on like Fox or 186 00:10:10,704 --> 00:10:12,664 Speaker 1: info Wars or like who's putting this out? 187 00:10:12,864 --> 00:10:16,824 Speaker 2: So within the first night it was on info Wars. 188 00:10:17,224 --> 00:10:19,744 Speaker 1: Info Wars is the guy who thinks that water makes 189 00:10:19,744 --> 00:10:23,624 Speaker 1: the frogs gay? Right, what's his name, Alex Jones? Alex Jones, thanks? 190 00:10:23,784 --> 00:10:27,384 Speaker 2: So, uh, she's like headline news on this info Wars 191 00:10:27,424 --> 00:10:30,624 Speaker 2: program that night. But it's also like it was on Russia. 192 00:10:30,304 --> 00:10:33,824 Speaker 1: Today where Tucker Carson will soon be hired for trillions 193 00:10:33,824 --> 00:10:34,304 Speaker 1: of dollars. 194 00:10:34,544 --> 00:10:38,504 Speaker 2: No, I won't believe it. The far right party in 195 00:10:38,584 --> 00:10:42,664 Speaker 2: Austria was sharing it. It was literally everywhere. It was everywhere. 196 00:10:43,064 --> 00:10:46,584 Speaker 1: Okay, so it's everywhere and they're not saying she's dead yet. 197 00:10:46,664 --> 00:10:47,864 Speaker 1: How does that come about? 198 00:10:48,104 --> 00:10:50,944 Speaker 2: Right? So at first they're just showing the video literally 199 00:10:50,984 --> 00:10:53,744 Speaker 2: and it's like all over YouTube, and it's just nurse faints, 200 00:10:53,944 --> 00:10:56,584 Speaker 2: but they don't have that second part of the live 201 00:10:56,624 --> 00:11:00,184 Speaker 2: stream where she says I'm fine, everything's okay now, And 202 00:11:00,304 --> 00:11:03,264 Speaker 2: so over the next couple of days, that's when you 203 00:11:03,344 --> 00:11:07,824 Speaker 2: saw it morph into she actually died. These fake things 204 00:11:07,864 --> 00:11:12,464 Speaker 2: are going around and within a week it's just gone bananas, 205 00:11:12,544 --> 00:11:17,384 Speaker 2: like everybody's convinced she's dead, and the hospital decides, crap, 206 00:11:17,464 --> 00:11:18,544 Speaker 2: we have to do something about this. 207 00:11:18,864 --> 00:11:21,544 Speaker 1: Wait, but she does she seem dead? Is she on 208 00:11:21,584 --> 00:11:23,264 Speaker 1: social media or talking to reporters. 209 00:11:23,584 --> 00:11:27,584 Speaker 2: She's not because the hospital tells her this is gone 210 00:11:27,624 --> 00:11:28,664 Speaker 2: to croatia. 211 00:11:28,824 --> 00:11:30,784 Speaker 1: I like that as a phrase when rumors start to fly, 212 00:11:31,064 --> 00:11:34,784 Speaker 1: this has gone to croatia. I know, I mean as 213 00:11:34,784 --> 00:11:35,744 Speaker 1: big as it gets. 214 00:11:35,984 --> 00:11:41,544 Speaker 2: It's everywhere, like this rumor is flying so fast that 215 00:11:41,624 --> 00:11:44,944 Speaker 2: you are hurt or dead and it's going crazy. Don't 216 00:11:44,944 --> 00:11:47,944 Speaker 2: say anything. Just let us take care of it. People 217 00:11:47,944 --> 00:11:51,624 Speaker 2: were calling constantly saying, my dad's in there. Can I 218 00:11:51,624 --> 00:11:54,384 Speaker 2: talk to the manager? This is Tiffany's husband, Can I 219 00:11:54,384 --> 00:11:56,784 Speaker 2: talk to Tiffany? Like they were just trying all these 220 00:11:56,824 --> 00:11:59,544 Speaker 2: ways to talk to her. It was really disrupting their work. 221 00:11:59,784 --> 00:12:02,704 Speaker 1: We're the main people pushing this. Tiffany is dead rumor. 222 00:12:03,064 --> 00:12:06,024 Speaker 2: You have your anti vaxxers are the easiest ones to 223 00:12:06,064 --> 00:12:08,504 Speaker 2: identify people who are sort of looking for evidence that 224 00:12:08,544 --> 00:12:11,824 Speaker 2: the vaccine is going to cause harm, and Tiffany was 225 00:12:11,864 --> 00:12:15,824 Speaker 2: their evidence. And that's people like the woman named Robin Openshaw. 226 00:12:16,424 --> 00:12:19,504 Speaker 2: She goes by Green Smoothie Girl, and she lived in 227 00:12:19,584 --> 00:12:21,584 Speaker 2: Utah for a long time until COVID and then she 228 00:12:21,624 --> 00:12:24,984 Speaker 2: had to escape. As she puts it, to Florida. She 229 00:12:25,544 --> 00:12:27,744 Speaker 2: believes that COVID is a lie and that the beach 230 00:12:27,784 --> 00:12:31,624 Speaker 2: will heal you. But she was probably the most dedicated 231 00:12:31,664 --> 00:12:35,704 Speaker 2: Tiffany Truther. She offered one hundred thousand dollars bounty to 232 00:12:35,824 --> 00:12:39,584 Speaker 2: anyone who could bring her Tiffany Dover because she was 233 00:12:39,624 --> 00:12:41,664 Speaker 2: so convinced that Tiffany was dead. 234 00:12:41,904 --> 00:12:44,264 Speaker 1: And who were the other people who were the main 235 00:12:44,464 --> 00:12:47,224 Speaker 1: Tiffany is dead conspiracy theorists. 236 00:12:47,464 --> 00:12:50,504 Speaker 2: Again, you had the anti vaxxers, but then the other 237 00:12:50,584 --> 00:12:54,544 Speaker 2: section was sort of your old school conspiracy theorists, and 238 00:12:54,584 --> 00:12:57,024 Speaker 2: I think of them was like the nine to eleven truthers, 239 00:12:57,224 --> 00:13:00,664 Speaker 2: and COVID was sort of like Christmas, all of their 240 00:13:00,704 --> 00:13:04,264 Speaker 2: conspiracy theories coming together, Like I can tell you this 241 00:13:04,264 --> 00:13:08,184 Speaker 2: guy allegedly Dave he's gone sort of wild during COVID. 242 00:13:08,224 --> 00:13:11,104 Speaker 2: He also drinks his own urine for health. You sound 243 00:13:11,184 --> 00:13:14,624 Speaker 2: judge about that, You know what, it's the least problematic 244 00:13:14,664 --> 00:13:19,704 Speaker 2: thing he does. I think it's fine, Like whatever, whatever 245 00:13:19,744 --> 00:13:23,344 Speaker 2: does it for you. It was interesting for me to 246 00:13:23,464 --> 00:13:27,544 Speaker 2: learn sort of the backstory of Brian Wilkins. Brian is 247 00:13:27,864 --> 00:13:31,504 Speaker 2: this guy from Iowa. He has a website called the 248 00:13:31,544 --> 00:13:35,864 Speaker 2: COVID Blog. He you know, wanted to be a radio DJ. 249 00:13:36,144 --> 00:13:39,784 Speaker 2: He had a girlfriend and he lost that girlfriend, his 250 00:13:40,024 --> 00:13:45,304 Speaker 2: parents died, He sort of lost everything to conspiracy theories 251 00:13:45,624 --> 00:13:48,864 Speaker 2: and conspiracy theories he literally told me was the one 252 00:13:48,944 --> 00:13:52,264 Speaker 2: thing in his life that was worthwhile. It was the 253 00:13:52,424 --> 00:13:54,744 Speaker 2: meaning for his life was to get people not to 254 00:13:54,744 --> 00:13:55,664 Speaker 2: take the vaccine. 255 00:13:55,744 --> 00:13:58,264 Speaker 1: It it gives you purpose. It's a religion. We all 256 00:13:58,304 --> 00:14:00,384 Speaker 1: search for that, and I can understand. And these people 257 00:14:00,424 --> 00:14:04,344 Speaker 1: are are pretty good reporters. They're not stupid. They find 258 00:14:04,424 --> 00:14:07,024 Speaker 1: really good facts. They just come to kind of weird 259 00:14:07,144 --> 00:14:07,824 Speaker 1: on conclusion. 260 00:14:08,144 --> 00:14:10,824 Speaker 2: Yeah, exactly, Okay, lots. 261 00:14:10,664 --> 00:14:14,744 Speaker 1: Of people think Tiffany's dead and she's being hidden by 262 00:14:15,424 --> 00:14:18,624 Speaker 1: all the forces of evil, and the hospital is just 263 00:14:18,784 --> 00:14:22,944 Speaker 1: flooded with phone calls, like from Croatia. So how do 264 00:14:23,024 --> 00:14:23,624 Speaker 1: they deal with that? 265 00:14:24,104 --> 00:14:30,104 Speaker 2: Really poorly, They have this idea to not let Tiffany 266 00:14:30,144 --> 00:14:34,024 Speaker 2: talk because if she spoke again and made a mistake, 267 00:14:34,744 --> 00:14:37,304 Speaker 2: it would just ruin the hospital. And so here's what 268 00:14:37,344 --> 00:14:41,064 Speaker 2: they came up with. Their idea was to stand on 269 00:14:41,104 --> 00:14:45,104 Speaker 2: a staircase. There were about twenty people, nursing staff and administrators, 270 00:14:45,464 --> 00:14:49,384 Speaker 2: and they would all hold signs that said we support Tiffany. 271 00:14:49,504 --> 00:14:52,464 Speaker 2: With the day's date. Tiffany would stand right at the 272 00:14:52,464 --> 00:14:55,544 Speaker 2: foot of the stairs, right in the front, and she 273 00:14:55,624 --> 00:14:58,864 Speaker 2: would say nothing. And because they thought most of them 274 00:14:58,864 --> 00:15:00,944 Speaker 2: thought they were just taking a photo, people were just 275 00:15:01,104 --> 00:15:06,184 Speaker 2: kind of standing there awkwardly. It's very poorly lit. Everyone's 276 00:15:06,224 --> 00:15:09,024 Speaker 2: wearing a mask, so you can't really see anything. Tiffany 277 00:15:09,144 --> 00:15:11,904 Speaker 2: had forgotten her white coat that day, which she's required 278 00:15:11,944 --> 00:15:15,144 Speaker 2: to wear, so one of her bosses gave her somebody 279 00:15:15,184 --> 00:15:17,624 Speaker 2: else's vest and it didn't fit. It was too big. 280 00:15:17,944 --> 00:15:20,624 Speaker 2: And then this was the biggest piece of evidence. Her 281 00:15:20,664 --> 00:15:24,824 Speaker 2: hair in this video was parted in the middle, and 282 00:15:24,904 --> 00:15:27,304 Speaker 2: she for the other video wore her hair parted on 283 00:15:27,344 --> 00:15:30,384 Speaker 2: the side. People do change their parts, even though the 284 00:15:30,424 --> 00:15:32,744 Speaker 2: truthers were like a woman would never change her part, 285 00:15:32,784 --> 00:15:37,224 Speaker 2: like it absolutely happens. So for all of these reasons. 286 00:15:37,624 --> 00:15:40,544 Speaker 2: When this twenty one second video was put out on 287 00:15:40,544 --> 00:15:43,224 Speaker 2: the hospital's Facebook page, they meant it to be a 288 00:15:43,264 --> 00:15:47,824 Speaker 2: proof of life. But for Truthers, this was just a 289 00:15:48,144 --> 00:15:52,744 Speaker 2: bonanza of new footage to prove that she died. This 290 00:15:52,784 --> 00:15:54,944 Speaker 2: clearly isn't the same girl. It's a body double. 291 00:15:55,704 --> 00:15:57,744 Speaker 1: Do they have a theory of who this body double is? 292 00:15:58,664 --> 00:16:03,864 Speaker 2: They do? They do? And what's really sad here is 293 00:16:03,864 --> 00:16:06,144 Speaker 2: because you know, not only did this response from the 294 00:16:06,144 --> 00:16:08,384 Speaker 2: hospital make things worse for Tiffany, but it brought in 295 00:16:08,384 --> 00:16:11,784 Speaker 2: another victim, and her name was Amber Honey. And they 296 00:16:11,784 --> 00:16:15,944 Speaker 2: found Amber Hony by looking through Tiffany's photos on her 297 00:16:15,984 --> 00:16:16,624 Speaker 2: Facebook page. 298 00:16:16,704 --> 00:16:20,304 Speaker 1: Why is everyone named like Brandy, Tiffany Amber? This feels 299 00:16:20,304 --> 00:16:22,344 Speaker 1: like I'm doing a story on nineteen eighty's pornography. 300 00:16:23,064 --> 00:16:27,064 Speaker 2: Okay, a that's rude, but be like, come to the South. 301 00:16:27,304 --> 00:16:32,624 Speaker 2: We have My sister's names are Tanya and Christy and Brandy. 302 00:16:31,864 --> 00:16:35,944 Speaker 2: Oh yes, of course, what you need to get out 303 00:16:35,944 --> 00:16:37,824 Speaker 2: of your elite media bubble. 304 00:16:37,464 --> 00:16:40,544 Speaker 1: Friend, I guess so wow. 305 00:16:42,384 --> 00:16:45,624 Speaker 2: Anyway, so yes, Amber, which is a perfectly fine name 306 00:16:45,704 --> 00:16:50,184 Speaker 2: to have. Totally, Amber was picked out as the body double, 307 00:16:50,504 --> 00:16:53,504 Speaker 2: and so it made her life terrible because all of 308 00:16:53,544 --> 00:16:58,024 Speaker 2: these truthers started flooding her Facebook page and they doxed her, 309 00:16:58,144 --> 00:17:00,144 Speaker 2: and they called her and her whole family and they're like, 310 00:17:00,184 --> 00:17:02,304 Speaker 2: why are you standing in for Tiffany? It dover? 311 00:17:02,784 --> 00:17:06,024 Speaker 1: How could you Okay, So this must mess up Amber's 312 00:17:06,064 --> 00:17:09,064 Speaker 1: life now that people think she's part of the evil conspiracy. 313 00:17:09,344 --> 00:17:12,424 Speaker 2: Yeah, she's the bad guy. It does mess up her life. 314 00:17:12,424 --> 00:17:15,144 Speaker 2: She's getting all these death threats. People are saying, you know, 315 00:17:15,304 --> 00:17:18,664 Speaker 2: poor Tiffany, rip Tiffany, Amber is the bad guy. So 316 00:17:18,704 --> 00:17:21,424 Speaker 2: it was really bad. But Amber and Tiffany are friends, 317 00:17:21,464 --> 00:17:24,464 Speaker 2: and Amber said, I'm not going to say anything until 318 00:17:24,864 --> 00:17:27,144 Speaker 2: you want to say something. It's your story to tell. 319 00:17:27,224 --> 00:17:30,104 Speaker 2: But of course it wasn't. She wasn't allowed to because 320 00:17:30,104 --> 00:17:32,264 Speaker 2: the hospital still wouldn't let her speak even after this 321 00:17:32,304 --> 00:17:33,064 Speaker 2: whole debacle. 322 00:17:33,464 --> 00:17:36,344 Speaker 1: You know, I'm going to quickly defend the hospital's decision 323 00:17:36,384 --> 00:17:39,904 Speaker 1: here because I've written columns where I got a lot 324 00:17:39,944 --> 00:17:44,464 Speaker 1: of angry attention and I had some very good advice, 325 00:17:44,544 --> 00:17:46,544 Speaker 1: which was don't feed the trolls. So I don't think 326 00:17:46,584 --> 00:17:48,064 Speaker 1: that was so crazy of the hospital. 327 00:17:48,464 --> 00:17:52,744 Speaker 2: Yeah, this is sort of prevailing Internet wisdom. And sometimes 328 00:17:52,784 --> 00:17:56,224 Speaker 2: it's right. But in an instance like this, when you 329 00:17:56,264 --> 00:17:58,584 Speaker 2: put this information out into the world and then something 330 00:17:58,624 --> 00:18:02,304 Speaker 2: goes wrong, you have kind of a responsibility to answer 331 00:18:02,704 --> 00:18:05,264 Speaker 2: the questions that are there, because, honestly, we focus a 332 00:18:05,304 --> 00:18:06,944 Speaker 2: lot on the truthers, but there were a lot of 333 00:18:06,984 --> 00:18:10,944 Speaker 2: well meaning people who had a fine question. This person 334 00:18:11,024 --> 00:18:13,744 Speaker 2: used to post on social media all the time. She 335 00:18:13,944 --> 00:18:17,184 Speaker 2: got up and spoke for the vaccine. She can't just disappear. Now, 336 00:18:17,264 --> 00:18:19,144 Speaker 2: that's weird. Don't be weird. 337 00:18:19,944 --> 00:18:22,824 Speaker 1: When we come back, we'll follow Brandy as she tries 338 00:18:22,864 --> 00:18:26,904 Speaker 1: to prove that in a live person is alive. Turns 339 00:18:26,904 --> 00:18:29,304 Speaker 1: out it's not as easy as it sounds. But first, 340 00:18:29,624 --> 00:18:32,624 Speaker 1: our advertisers have an herbal remedy that will erase the 341 00:18:32,704 --> 00:18:42,904 Speaker 1: chip Bill Gates put into your bloodstream. So while these 342 00:18:42,904 --> 00:18:46,264 Speaker 1: conspiracy theorists are looking for Tiffany, you started looking for 343 00:18:46,264 --> 00:18:48,944 Speaker 1: her too. Like you, I would have called the hospital first. 344 00:18:48,984 --> 00:18:51,024 Speaker 1: What did they tell you when you called them looking 345 00:18:51,064 --> 00:18:51,544 Speaker 1: for Tiffany? 346 00:18:52,064 --> 00:18:54,704 Speaker 2: It was very boilerplate. We've said she's alive. Here's the 347 00:18:54,744 --> 00:18:57,224 Speaker 2: post we made on our website. Goodbye. I had to 348 00:18:57,264 --> 00:19:01,224 Speaker 2: go to Chattanooga and basically say I'm here, I'm outside 349 00:19:01,224 --> 00:19:04,304 Speaker 2: your hospital, Can someone from PR please speak to me? 350 00:19:04,664 --> 00:19:07,904 Speaker 2: They really wouldn't talk to me at all. Their explanation 351 00:19:08,344 --> 00:19:10,784 Speaker 2: was that Tiff didn't want to talk about any of this. 352 00:19:10,944 --> 00:19:13,064 Speaker 2: She wanted to do her job as a nurse manager 353 00:19:13,184 --> 00:19:16,744 Speaker 2: and let this stuff pass by, let it finish its course. Right. 354 00:19:17,024 --> 00:19:19,744 Speaker 1: Don't you feel like another stalker like the rest of 355 00:19:19,784 --> 00:19:21,824 Speaker 1: these conspiracy theorist people like I. 356 00:19:21,784 --> 00:19:26,144 Speaker 2: Have a business card? Yeah, of course, But you know, 357 00:19:26,304 --> 00:19:29,184 Speaker 2: half of reporting is bothering people who absolutely don't want 358 00:19:29,224 --> 00:19:29,664 Speaker 2: to talk to you. 359 00:19:29,824 --> 00:19:32,384 Speaker 1: And this is a person whose whole problem is people 360 00:19:32,504 --> 00:19:34,944 Speaker 1: bothering her because they want to find out the truth. 361 00:19:35,064 --> 00:19:37,024 Speaker 2: All I needed was her to say that. 362 00:19:37,344 --> 00:19:39,464 Speaker 1: Oh, so you think maybe she does want to talk 363 00:19:39,464 --> 00:19:39,624 Speaker 1: to you. 364 00:19:40,144 --> 00:19:43,264 Speaker 2: I thought so yeah, And so I went to her 365 00:19:43,304 --> 00:19:47,624 Speaker 2: house and stood outside her house for long stretches of 366 00:19:47,664 --> 00:19:50,384 Speaker 2: time like a weirdo, and I so I would run 367 00:19:50,384 --> 00:19:52,904 Speaker 2: into family members and I ran into them and I said, 368 00:19:53,144 --> 00:19:55,584 Speaker 2: does she want me to go away? If she does, 369 00:19:55,704 --> 00:19:59,104 Speaker 2: please let me know. And they told me no, she 370 00:19:59,184 --> 00:20:02,104 Speaker 2: wants to talk to you. She's just got a few 371 00:20:02,144 --> 00:20:04,064 Speaker 2: things that she needs to do. First. She needs to 372 00:20:04,104 --> 00:20:06,504 Speaker 2: talk to a lawyer or someone said something about she 373 00:20:06,584 --> 00:20:08,304 Speaker 2: has an nda. 374 00:20:07,704 --> 00:20:10,584 Speaker 1: So you do this entire podcast and you never get 375 00:20:10,584 --> 00:20:11,344 Speaker 1: to talk to Tiffany. 376 00:20:11,784 --> 00:20:16,824 Speaker 2: Yeah. It was totally unsatisfying and pretty sad actually, because 377 00:20:16,824 --> 00:20:19,904 Speaker 2: at the end of it, I do think, honestly, I 378 00:20:19,984 --> 00:20:23,464 Speaker 2: made things worse. I think that a lot of people 379 00:20:23,504 --> 00:20:26,664 Speaker 2: said at the end of episode five, see even an 380 00:20:26,744 --> 00:20:30,704 Speaker 2: NBC News reporter can't find a nurse in Chattanooga, Tennessee, 381 00:20:30,744 --> 00:20:31,864 Speaker 2: like she's clearly dead. 382 00:20:32,344 --> 00:20:33,384 Speaker 1: How setting was that? 383 00:20:33,904 --> 00:20:36,704 Speaker 2: It was really upsetting. It was like I was very sad, 384 00:20:37,304 --> 00:20:41,264 Speaker 2: Like I cried a lot. Oh no, yeah, that really sucked. 385 00:20:42,064 --> 00:20:45,384 Speaker 2: But then about a year later, I got a text 386 00:20:45,384 --> 00:20:47,504 Speaker 2: from her, just totally out of the blue. 387 00:20:48,384 --> 00:20:50,144 Speaker 1: Why does she want to talk to you now after 388 00:20:50,184 --> 00:20:50,824 Speaker 1: all this time? 389 00:20:51,504 --> 00:20:53,544 Speaker 2: You know? She told me, Actually she said that she 390 00:20:53,584 --> 00:20:55,424 Speaker 2: had been thinking about it for a while, she had 391 00:20:55,464 --> 00:20:57,464 Speaker 2: wanted to talk to me. Then she quit her job 392 00:20:57,504 --> 00:21:00,024 Speaker 2: at the hospital, so she finally could talk to me. 393 00:21:01,064 --> 00:21:03,264 Speaker 1: Oh so the hospital wasn't very upfront with you, and 394 00:21:03,304 --> 00:21:05,344 Speaker 1: they implied that Tiffany didn't want to talk. 395 00:21:05,464 --> 00:21:08,624 Speaker 2: Oh they lied, like a uh yeah, see this this 396 00:21:08,664 --> 00:21:12,304 Speaker 2: plays into the conspiracy theorists that hospitals are liars. I mean, 397 00:21:12,664 --> 00:21:16,904 Speaker 2: it's definitely bad pr but yeah, they did lie. They lied. 398 00:21:17,424 --> 00:21:19,544 Speaker 1: That's horrible. Did she quit because of this? 399 00:21:19,784 --> 00:21:21,944 Speaker 2: She quit because of what was happening at the hospital. Yeah, 400 00:21:21,984 --> 00:21:25,944 Speaker 2: there was a brief moment where she wanted to post 401 00:21:25,984 --> 00:21:29,624 Speaker 2: on her Instagram just photos from her vacation, and that's 402 00:21:29,624 --> 00:21:32,464 Speaker 2: all she did. But a lot of people said that 403 00:21:32,584 --> 00:21:35,824 Speaker 2: her ski helmet was evidence that it wasn't her, that 404 00:21:35,864 --> 00:21:38,544 Speaker 2: it was really amber. When she got back, she got 405 00:21:38,624 --> 00:21:43,504 Speaker 2: in trouble. She got a letter basically saying we recommend 406 00:21:43,504 --> 00:21:46,224 Speaker 2: that you delete your account and if you keep posting 407 00:21:46,224 --> 00:21:48,744 Speaker 2: on social media, then you could be terminated. 408 00:21:48,864 --> 00:21:51,024 Speaker 1: Right, She didn't feel like they're being supportive as they 409 00:21:51,024 --> 00:21:53,224 Speaker 1: should have, like they were part of this thing, this 410 00:21:53,344 --> 00:21:56,384 Speaker 1: original plan of giving a shot to the fainting girl. 411 00:21:57,184 --> 00:22:01,064 Speaker 2: Yeah, it's true. It was really demoralizing for her to 412 00:22:01,064 --> 00:22:03,264 Speaker 2: feel like she had done this great job. But inside 413 00:22:03,264 --> 00:22:05,064 Speaker 2: her own hospital, she just felt like she was in 414 00:22:05,104 --> 00:22:07,824 Speaker 2: trouble a lot, and like all this was her fault 415 00:22:07,944 --> 00:22:08,984 Speaker 2: that she had fainted. 416 00:22:09,184 --> 00:22:12,864 Speaker 1: Okay, so if you finally go see her, what's it 417 00:22:12,984 --> 00:22:15,464 Speaker 1: like to see her in person? Is she beautiful? 418 00:22:17,064 --> 00:22:21,264 Speaker 2: She's so pretty? She really is. That's the thing I mean. 419 00:22:21,504 --> 00:22:25,104 Speaker 2: So I was driving with my producer from Atlanta to 420 00:22:25,304 --> 00:22:27,624 Speaker 2: Chattanooga on the day that we're meeting her, and I 421 00:22:27,664 --> 00:22:31,264 Speaker 2: had this like flash of fear, like what if she's awful, 422 00:22:31,664 --> 00:22:33,864 Speaker 2: or like what if she's you know, just not the 423 00:22:33,904 --> 00:22:35,184 Speaker 2: person that I've built up in my. 424 00:22:35,264 --> 00:22:37,744 Speaker 1: Mind projected so much onto her. You've never talked to her, 425 00:22:37,784 --> 00:22:39,944 Speaker 1: You've been thinking about her for years and looking at 426 00:22:39,984 --> 00:22:42,464 Speaker 1: pictures of her in social media. Oh yeah, of course, 427 00:22:42,464 --> 00:22:43,224 Speaker 1: you don't meet your. 428 00:22:43,064 --> 00:22:45,304 Speaker 2: Heroes one hundred percent. So I was like, oh, she 429 00:22:45,384 --> 00:22:49,424 Speaker 2: could be awful. Yeah, I was really afraid. But the 430 00:22:49,544 --> 00:22:51,744 Speaker 2: second that I met her at this restaurant, we met 431 00:22:51,784 --> 00:22:53,464 Speaker 2: for a drink, which turned into dinner. 432 00:22:53,504 --> 00:22:55,584 Speaker 1: It's a good date when a drink turns into dinner. 433 00:22:55,824 --> 00:22:58,264 Speaker 2: I know. It went really well, and then we decided 434 00:22:58,304 --> 00:23:00,224 Speaker 2: the next day. I said, can I please come over 435 00:23:00,224 --> 00:23:02,704 Speaker 2: to your house and make this podcast? And she said, yeah, 436 00:23:02,824 --> 00:23:03,344 Speaker 2: let's do it. 437 00:23:03,864 --> 00:23:05,424 Speaker 1: When you get to talk to her, what does she 438 00:23:05,504 --> 00:23:08,984 Speaker 1: say about how these conspiracy theorists affected her life? 439 00:23:09,224 --> 00:23:11,944 Speaker 2: She talked about, how does it feel when people come 440 00:23:11,944 --> 00:23:15,344 Speaker 2: to your house with GoPros on their head and or 441 00:23:15,504 --> 00:23:18,184 Speaker 2: walking around your yard while you're a babysitting your three 442 00:23:18,184 --> 00:23:20,944 Speaker 2: month old nephew, and you know how does it feel 443 00:23:20,984 --> 00:23:24,464 Speaker 2: when a guy who calls himself the vaccine police and 444 00:23:24,824 --> 00:23:28,744 Speaker 2: makes videos with blowtorches and big guns like comes to 445 00:23:28,784 --> 00:23:30,704 Speaker 2: your front door? Scary awful? 446 00:23:31,384 --> 00:23:34,504 Speaker 1: Are you thinking that if you get some facts like 447 00:23:34,544 --> 00:23:37,264 Speaker 1: you can prove she's alive, you're going to change the 448 00:23:37,304 --> 00:23:38,424 Speaker 1: conspiracy theorist. 449 00:23:38,264 --> 00:23:40,984 Speaker 2: Minds one hundred percent? Yeah? Absolutely. 450 00:23:41,144 --> 00:23:43,704 Speaker 1: That makes you crazier than them, I know, but I. 451 00:23:43,664 --> 00:23:46,584 Speaker 2: Thought if I got her, I could change the mind 452 00:23:46,624 --> 00:23:49,584 Speaker 2: of one conspiracy theorist. And then I thought it would 453 00:23:49,624 --> 00:23:53,224 Speaker 2: be like a feel good into the podcast. It will 454 00:23:53,264 --> 00:23:56,024 Speaker 2: surprise you, I'm sure shock you even to know that. 455 00:23:56,144 --> 00:23:58,824 Speaker 2: A lot of the people commented on the projects that 456 00:23:58,864 --> 00:24:01,704 Speaker 2: we did, saying that it was a lie, it was 457 00:24:01,744 --> 00:24:04,824 Speaker 2: a deep fake, she was ai, it was a body double, 458 00:24:04,864 --> 00:24:07,704 Speaker 2: et cetera, et cetera. So what she did next was 459 00:24:08,264 --> 00:24:11,584 Speaker 2: this guy who has his own sort of anti vax 460 00:24:11,664 --> 00:24:14,104 Speaker 2: podcast invited her on and. 461 00:24:14,024 --> 00:24:16,024 Speaker 1: She said, yes, Wait, did she convince the guy that 462 00:24:16,064 --> 00:24:16,584 Speaker 1: she's alive? 463 00:24:16,864 --> 00:24:18,064 Speaker 2: She did. No. 464 00:24:18,264 --> 00:24:20,704 Speaker 1: Would this proves your theory that you can change these 465 00:24:20,704 --> 00:24:21,584 Speaker 1: people's minds? 466 00:24:22,064 --> 00:24:24,704 Speaker 2: I mean, yeah, a conspiracy theorists that thought she was 467 00:24:24,744 --> 00:24:27,304 Speaker 2: dead or injured. He said, you have convinced me. I 468 00:24:27,344 --> 00:24:29,544 Speaker 2: do not think you're dead. I do not think you're injured. 469 00:24:30,184 --> 00:24:32,584 Speaker 2: And he told his audience, and then in his comments 470 00:24:32,624 --> 00:24:34,104 Speaker 2: people were like, you've convinced me. 471 00:24:34,264 --> 00:24:37,104 Speaker 1: Okay, did you get your hundred thousand dollars? 472 00:24:38,064 --> 00:24:40,624 Speaker 2: No, I have to be very clear about this because 473 00:24:40,664 --> 00:24:43,384 Speaker 2: Robin OpenShot to her audience does say this all the time, 474 00:24:43,424 --> 00:24:45,744 Speaker 2: like she was trying to get a hundred thousand dollars, 475 00:24:45,784 --> 00:24:48,624 Speaker 2: Like I wasn't trying to like win her hundred thousand dollars. 476 00:24:49,024 --> 00:24:50,784 Speaker 2: But no, she did not give it to me. And 477 00:24:50,824 --> 00:24:53,704 Speaker 2: she still very much thinks that Tiffany's dead. 478 00:24:54,224 --> 00:24:55,624 Speaker 1: Wait, what does she need to give up the one 479 00:24:55,664 --> 00:24:56,184 Speaker 1: hundred grand? 480 00:24:57,584 --> 00:25:00,304 Speaker 2: So I emailed her and I said, hey, let's get 481 00:25:00,344 --> 00:25:03,824 Speaker 2: back together. I have that zoom you were looking for. Yeah, 482 00:25:03,864 --> 00:25:06,784 Speaker 2: you know, let's do this. And she said, oh no, 483 00:25:06,944 --> 00:25:09,944 Speaker 2: that's not enough. She said, Now I want to go 484 00:25:09,984 --> 00:25:13,184 Speaker 2: to Tennessee to her home, and I want to interview 485 00:25:13,184 --> 00:25:16,384 Speaker 2: her on camera. I want all of her medical records, 486 00:25:16,784 --> 00:25:19,904 Speaker 2: and she must show a willingness to tell the truth 487 00:25:19,984 --> 00:25:22,224 Speaker 2: about what happened to her. That's a quote, so like, 488 00:25:22,344 --> 00:25:24,264 Speaker 2: clearly nothing would be acceptable. 489 00:25:24,384 --> 00:25:26,184 Speaker 1: Oh so she's starting to sound like she's not a 490 00:25:26,464 --> 00:25:29,824 Speaker 1: true conspiracy believer and she's just a huckster. 491 00:25:30,984 --> 00:25:32,144 Speaker 2: I mean, who knows. 492 00:25:32,344 --> 00:25:35,184 Speaker 1: Sounds like she just wants ratings for her little YouTube show. 493 00:25:35,464 --> 00:25:39,144 Speaker 2: Maybe I don't know. She seemed to really care about 494 00:25:39,184 --> 00:25:40,424 Speaker 2: Tiffany as a person. 495 00:25:41,464 --> 00:25:44,064 Speaker 1: Has this story changed the way you think about dealing 496 00:25:44,104 --> 00:25:45,384 Speaker 1: with conspiracy theorists? 497 00:25:45,624 --> 00:25:49,264 Speaker 2: It kind of made me more empathetic with conspiracy theorists. 498 00:25:49,304 --> 00:25:52,464 Speaker 2: I think that a lot of our coverage of conspiracy 499 00:25:52,504 --> 00:25:56,184 Speaker 2: theories and conspiratorial communities is sort of like, oh, look 500 00:25:56,224 --> 00:26:00,224 Speaker 2: at these crazy people, and sometimes like, that's kind of true, 501 00:26:00,424 --> 00:26:02,504 Speaker 2: But I always give people the benefit of the doubt. 502 00:26:03,184 --> 00:26:08,544 Speaker 1: You're a giver. Mmm, that's just me, Brandy. You wrote 503 00:26:08,624 --> 00:26:12,624 Speaker 1: conspirac theorists made Tiffany Dover into an anti vaccine icon. 504 00:26:13,104 --> 00:26:16,104 Speaker 1: She's finally ready to talk about it for NBC News. 505 00:26:16,624 --> 00:26:18,864 Speaker 1: Thank you so much for coming on the podcast. 506 00:26:19,464 --> 00:26:21,024 Speaker 2: Thank you, Joel, this was so fun. 507 00:26:22,344 --> 00:26:26,024 Speaker 1: Trying to change people's minds with facts is a horrible 508 00:26:26,024 --> 00:26:29,224 Speaker 1: misunderstanding of what it is to be human. It's like 509 00:26:29,264 --> 00:26:32,664 Speaker 1: you're assuming that our brains are logic computers. They are 510 00:26:32,664 --> 00:26:35,664 Speaker 1: not at all. We don't even have access to most 511 00:26:35,664 --> 00:26:38,224 Speaker 1: of what our brains are doing. Most of my brain, 512 00:26:38,264 --> 00:26:41,344 Speaker 1: for instance, is definitely not focused on reading these words 513 00:26:41,384 --> 00:26:44,904 Speaker 1: right now. I'm guessing it's busy thinking about either food 514 00:26:44,984 --> 00:26:48,184 Speaker 1: or sex, maybe a weird combination of both. I have 515 00:26:48,264 --> 00:26:51,544 Speaker 1: no idea. The best we can do is control the 516 00:26:51,584 --> 00:26:55,744 Speaker 1: water we're swimming in by listening to experts from trusted institutions, 517 00:26:56,424 --> 00:27:00,384 Speaker 1: consuming information from large organizations where a lot of people 518 00:27:00,424 --> 00:27:04,664 Speaker 1: are vetting it, and most importantly of all, listening to 519 00:27:04,824 --> 00:27:09,704 Speaker 1: this podcast, You, my friend, are doing God's work. Next 520 00:27:09,704 --> 00:27:12,584 Speaker 1: week we'll talk to Virginia Heffernan about how she went 521 00:27:12,624 --> 00:27:16,784 Speaker 1: to Taiwan and fell in love with computer chips. 522 00:27:19,104 --> 00:27:22,304 Speaker 3: At the end of the show, what's next for joel Stein? 523 00:27:22,464 --> 00:27:25,944 Speaker 3: Maybe he'll take a napper poker round online. 524 00:27:26,584 --> 00:27:30,664 Speaker 1: Our show is produced by Joey fish Ground, Mola Bard, 525 00:27:30,944 --> 00:27:34,784 Speaker 1: and Nishavenka. It was edited by Lydia jeden Kopp. Our 526 00:27:34,824 --> 00:27:37,624 Speaker 1: engineer is Amanda kai Wang and our executive producer is 527 00:27:37,824 --> 00:27:41,704 Speaker 1: Catherin Cherradoh. Our theme song was produced by Jonathan Colton. 528 00:27:42,184 --> 00:27:44,744 Speaker 1: A special thanks to my voice coach Vicky Merrick and 529 00:27:44,864 --> 00:27:49,384 Speaker 1: my consulting producer Laurence Alasnik. To find more Pushkin podcasts, 530 00:27:49,544 --> 00:27:53,784 Speaker 1: listen on the iHeartRadio app Apple podcasts or wherever you 531 00:27:53,824 --> 00:27:58,144 Speaker 1: listen to your podcasts. I'm Joel Stein and this is 532 00:27:58,224 --> 00:28:01,384 Speaker 1: Story of the Week. Do you still talk to Tiffany 533 00:28:01,384 --> 00:28:01,824 Speaker 1: as your. 534 00:28:01,664 --> 00:28:04,904 Speaker 2: Relationship over I do. Do you talk to a lot 535 00:28:04,944 --> 00:28:07,264 Speaker 2: of your former subjects? 536 00:28:07,424 --> 00:28:10,184 Speaker 1: Almost none. There's one guy my last book who calls 537 00:28:10,224 --> 00:28:12,384 Speaker 1: me every few months like he's my grandfather. But other 538 00:28:12,464 --> 00:28:17,224 Speaker 1: than that, I really don't much. I do, you're much 539 00:28:17,304 --> 00:28:20,864 Speaker 1: more likable. No, yeah, I just like, you're not going 540 00:28:20,904 --> 00:28:21,824 Speaker 1: to talk to me after this? 541 00:28:22,264 --> 00:28:25,544 Speaker 2: Clearly No, We're now best friends. I'm going to send 542 00:28:25,584 --> 00:28:26,424 Speaker 2: you a Christmas card.