1
00:00:01,400 --> 00:00:05,440
Speaker 1: Welcome to Behind the Bastards, the only podcast where the host,

2
00:00:05,680 --> 00:00:09,960
Speaker 1: Robert Evans could easily, and I mean easily, defeat Lebron

3
00:00:10,039 --> 00:00:13,680
Speaker 1: James at basketball. Not a problem, not even a challenge.

4
00:00:13,760 --> 00:00:17,360
Speaker 1: Everyone knows it. Everybody agrees. Let's just move on. Having

5
00:00:17,400 --> 00:00:20,760
Speaker 1: made the point. This is Remember, I've seen your dunk

6
00:00:21,000 --> 00:00:23,599
Speaker 1: I've seen your dunk reels on TikTok. You're very kid,

7
00:00:23,960 --> 00:00:28,319
Speaker 1: Thank you, thank you, Yes, unparalleled. Some would say, um, now,

8
00:00:28,600 --> 00:00:33,360
Speaker 1: Jamie bad, I'm speaking Jamie Loftus, How how are you,

9
00:00:33,720 --> 00:00:39,360
Speaker 1: Jamie Loftus. I'm so, I'm so, I'm all over the place,

10
00:00:39,400 --> 00:00:42,080
Speaker 1: but I'm good. I'm all right, all things considered. I

11
00:00:42,200 --> 00:00:45,640
Speaker 1: brought my cat on a cross country flight yesterday. So

12
00:00:46,240 --> 00:00:48,320
Speaker 1: that's what did you do? Was he good? What was

13
00:00:48,360 --> 00:00:53,440
Speaker 1: the vibe? Was good? We were we were sitting like

14
00:00:54,080 --> 00:00:56,360
Speaker 1: I was in the two rows. I was the only

15
00:00:56,400 --> 00:01:01,840
Speaker 1: person that wasn't on the way to celebrate someone's thirtieth birthday.

16
00:01:01,880 --> 00:01:03,840
Speaker 1: But they really took to the cat. They were we

17
00:01:04,000 --> 00:01:07,839
Speaker 1: were all an emotional support unit. They were all watching

18
00:01:07,920 --> 00:01:11,959
Speaker 1: Naruto on iPads. I was listening to an Amityville Horror

19
00:01:12,000 --> 00:01:15,840
Speaker 1: audio book and just reaching down and petting my cat

20
00:01:15,959 --> 00:01:18,319
Speaker 1: for six hours. It was. It was a real treat.

21
00:01:18,560 --> 00:01:22,039
Speaker 1: How are you, Robert? I'm good, um, by which I

22
00:01:22,080 --> 00:01:25,840
Speaker 1: mean terrible, by which I mean normal. Um okay, so

23
00:01:25,920 --> 00:01:28,960
Speaker 1: nothing's changed since we last spoke that I just flew to.

24
00:01:29,200 --> 00:01:31,640
Speaker 1: I was in Texas from my brother's wedding, and so

25
00:01:31,680 --> 00:01:34,200
Speaker 1: I was. I got to be as I was when

26
00:01:34,240 --> 00:01:37,120
Speaker 1: I left Texas there the day a new shitty law

27
00:01:37,200 --> 00:01:40,840
Speaker 1: came into being. Um, okay, you need to stop going

28
00:01:40,880 --> 00:01:43,240
Speaker 1: back your jinks. Yeah, I mean when I moved to

29
00:01:43,400 --> 00:01:46,000
Speaker 1: l A, I had just like immediately. It was immediately

30
00:01:46,040 --> 00:01:49,480
Speaker 1: after I attended the protests for Wendy Davis at the

31
00:01:49,520 --> 00:01:54,120
Speaker 1: Capitol over the over abortion. Um, so that's just me

32
00:01:54,200 --> 00:01:57,840
Speaker 1: and Texas. Baby. Wait, Robert, what is your what is

33
00:01:58,560 --> 00:02:01,880
Speaker 1: I'm what is your vibe at a wedding? I can't

34
00:02:01,920 --> 00:02:04,240
Speaker 1: picture you at a wedding, so I need to have

35
00:02:04,320 --> 00:02:06,440
Speaker 1: trouble picturing me too at a wedding, Jamie. But I

36
00:02:06,480 --> 00:02:10,960
Speaker 1: was to it was very Catholic wedding. Did you get

37
00:02:11,000 --> 00:02:13,920
Speaker 1: to eat the tiny bread? No? No, no, I don't

38
00:02:13,919 --> 00:02:16,000
Speaker 1: I don't take I love the tiny bread. It tastes

39
00:02:16,040 --> 00:02:21,480
Speaker 1: so good. Tucksolved. I had to wear a tux I have.

40
00:02:22,280 --> 00:02:27,280
Speaker 1: Where's the pictures? I felt bad about killing the photographer,

41
00:02:27,320 --> 00:02:29,520
Speaker 1: but I just couldn't let there be a chance of

42
00:02:29,560 --> 00:02:32,240
Speaker 1: those photos getting out. So send me a pick of

43
00:02:32,240 --> 00:02:35,600
Speaker 1: you what I had to do? A smiling with teeth

44
00:02:35,720 --> 00:02:41,000
Speaker 1: in the pics? No, but I did get extremely drunk

45
00:02:41,120 --> 00:02:44,480
Speaker 1: at the it was thankfully it was um It was

46
00:02:44,639 --> 00:02:46,720
Speaker 1: a Catholic wedding, but it was also a Mexican wedding,

47
00:02:46,720 --> 00:02:50,000
Speaker 1: so the food was incredible and I was able to

48
00:02:50,040 --> 00:02:54,200
Speaker 1: get very drunk afterwards, so that I can't believe you

49
00:02:54,320 --> 00:02:58,799
Speaker 1: smiled with teeth. Also, my brother's happy. I guess that's

50
00:02:58,840 --> 00:03:01,920
Speaker 1: important too. Yeah, who gives a ship? I don't know

51
00:03:01,960 --> 00:03:08,480
Speaker 1: your brother allegedly whatever, Jamie, what how do you feel

52
00:03:08,520 --> 00:03:13,359
Speaker 1: about the death of all hope? I feel, I feel

53
00:03:13,639 --> 00:03:17,240
Speaker 1: I feel very numb to it. Yeah, that's a good

54
00:03:17,240 --> 00:03:19,760
Speaker 1: way to feel about the death of all hope, Jamie. Today,

55
00:03:20,200 --> 00:03:22,440
Speaker 1: I'm going to tell you a story, and it's a

56
00:03:22,480 --> 00:03:25,360
Speaker 1: story about the end of the world. Now, this story

57
00:03:25,360 --> 00:03:28,880
Speaker 1: doesn't involve a nuclear holocaust or global war. The culprit

58
00:03:28,960 --> 00:03:33,560
Speaker 1: for our incipient apocalypse is the modern information ecosystem, which

59
00:03:33,600 --> 00:03:37,720
Speaker 1: has doomed us all and cannot be reformed. Now to

60
00:03:37,800 --> 00:03:40,160
Speaker 1: make it clear why I'm gonna tell you a story

61
00:03:40,200 --> 00:03:43,120
Speaker 1: about ivermectin. I guess you've heard a lot about iver

62
00:03:43,240 --> 00:03:46,400
Speaker 1: met in the last couple of days, haven't you. You

63
00:03:46,560 --> 00:03:50,920
Speaker 1: sure have course paste um all that tends to be

64
00:03:52,000 --> 00:03:54,360
Speaker 1: how people talk about it in social media. These idiots

65
00:03:54,400 --> 00:03:58,800
Speaker 1: are taking horse paste um, which is It's one of

66
00:03:58,840 --> 00:04:01,560
Speaker 1: those things where people who love horse paste will be like,

67
00:04:01,840 --> 00:04:03,680
Speaker 1: we're not taking horse paste. Is. There's a bunch of

68
00:04:03,720 --> 00:04:07,119
Speaker 1: different formulations. There's even human versions, and that's true. They're

69
00:04:07,160 --> 00:04:09,800
Speaker 1: like a horse paste is the meanest possible I've I've

70
00:04:09,800 --> 00:04:12,640
Speaker 1: seen versions of that, like saying it's horse paste is

71
00:04:13,000 --> 00:04:17,400
Speaker 1: a little bit inaccurate when they say something else scary,

72
00:04:17,520 --> 00:04:23,400
Speaker 1: I'm actually taking sheep dip um. But a lot of

73
00:04:23,440 --> 00:04:26,040
Speaker 1: people are taking the human version of iver mecht in too,

74
00:04:26,200 --> 00:04:28,680
Speaker 1: particularly when talking about Joe Rogan. Joe Rogan isn't going

75
00:04:28,720 --> 00:04:31,560
Speaker 1: to a feed store in getting apple flavored horse paste.

76
00:04:31,600 --> 00:04:34,360
Speaker 1: He's getting ivermectin prescribed him by a doctor because he's

77
00:04:34,440 --> 00:04:38,160
Speaker 1: rich um. And ivermectin is very much kind of a

78
00:04:38,240 --> 00:04:41,080
Speaker 1: miracle medicine, just not in the purpose is being used

79
00:04:41,080 --> 00:04:43,640
Speaker 1: for um. It was discovered in nineteen seventy five and

80
00:04:43,720 --> 00:04:46,200
Speaker 1: went on sale widely in the early nineteen eighties, and

81
00:04:46,279 --> 00:04:48,679
Speaker 1: it is still today one of the most potent anti

82
00:04:48,760 --> 00:04:52,640
Speaker 1: parasitic medications in existence. It is effective in livestock and

83
00:04:52,720 --> 00:04:55,560
Speaker 1: also in humans. It is credited with curing a once

84
00:04:55,720 --> 00:04:59,280
Speaker 1: devastating illness called river blindness, which I feel like the

85
00:04:59,400 --> 00:05:04,840
Speaker 1: name describes more or less the problem. Um, I don't agree.

86
00:05:06,000 --> 00:05:10,240
Speaker 1: What is parasites from unclean water make you blind and

87
00:05:11,720 --> 00:05:16,120
Speaker 1: stops that? Okay, it's very it's very good stuff. The

88
00:05:16,200 --> 00:05:19,400
Speaker 1: scientists who discovered it won a Nobel Prize UM and

89
00:05:19,560 --> 00:05:21,640
Speaker 1: in two thousand fifteen it was even found that the

90
00:05:21,680 --> 00:05:24,960
Speaker 1: anti parasitic drug is also effective at disrupting the transmission

91
00:05:25,000 --> 00:05:29,000
Speaker 1: of malaria UM, which is great. And when taken as directed,

92
00:05:29,080 --> 00:05:32,360
Speaker 1: iver mecton is extremely safe with minimal side effects, and

93
00:05:32,440 --> 00:05:34,240
Speaker 1: it is cheap enough to produce that you can find

94
00:05:34,279 --> 00:05:37,320
Speaker 1: it all over the world, or you could anyway. Before

95
00:05:37,360 --> 00:05:40,200
Speaker 1: about like six this month, six or so months ago,

96
00:05:41,360 --> 00:05:44,520
Speaker 1: iver macton has developed I think a really toxic fan base,

97
00:05:44,880 --> 00:05:48,159
Speaker 1: and it's the Rick and Morty of anti parasitic drugs

98
00:05:50,040 --> 00:05:57,200
Speaker 1: sure um, And like Rick and Morty, it will stop

99
00:05:58,040 --> 00:06:04,080
Speaker 1: herds of horses from shifting worms out. It acts. Yeah, people,

100
00:06:04,120 --> 00:06:07,479
Speaker 1: they have horses watching early seasons of ricking mortial ther

101
00:06:08,040 --> 00:06:10,680
Speaker 1: to see what will happened to their bodies. You give

102
00:06:11,080 --> 00:06:14,960
Speaker 1: season four, it'll keep shitting worms. So in September of

103
00:06:15,800 --> 00:06:18,960
Speaker 1: Australian researchers found that huge doses of iron mectin, when

104
00:06:19,320 --> 00:06:23,200
Speaker 1: ministered in a laboratory setting might stop or could stop

105
00:06:23,279 --> 00:06:26,239
Speaker 1: replication of COVID in cell cultures in less than forty

106
00:06:26,279 --> 00:06:30,240
Speaker 1: eight hours. This was potentially a big deal for obvious reasons,

107
00:06:30,320 --> 00:06:33,760
Speaker 1: but also these are cell cultures, right, This is not

108
00:06:34,400 --> 00:06:37,240
Speaker 1: in the human body. These are in in in a

109
00:06:37,400 --> 00:06:40,760
Speaker 1: very controlled laboratory setting. So this is a very useful

110
00:06:40,800 --> 00:06:43,359
Speaker 1: piece of data. And obviously follow up studies were immediately

111
00:06:43,360 --> 00:06:45,920
Speaker 1: commissioned around the world to see if maybe this might

112
00:06:46,000 --> 00:06:49,680
Speaker 1: be something that could help with COVID. Now pre vaccine

113
00:06:49,760 --> 00:06:52,600
Speaker 1: doctors were looking at a wide variety of medications and

114
00:06:52,760 --> 00:06:56,320
Speaker 1: treatment options that might act as stop gaps until there

115
00:06:56,440 --> 00:06:59,320
Speaker 1: was a vaccine. One group of physicians who were doing

116
00:06:59,400 --> 00:07:03,960
Speaker 1: this was the Frontline COVID nineteen Critical Care Alliance or

117
00:07:04,120 --> 00:07:08,000
Speaker 1: f l c c c UM. This group had been

118
00:07:08,080 --> 00:07:11,080
Speaker 1: formed by a number of critical care specialists with different

119
00:07:11,120 --> 00:07:13,640
Speaker 1: medical backgrounds who wanted to try and hash together new

120
00:07:13,720 --> 00:07:16,720
Speaker 1: ideas for treating the virus. Their first stab at this

121
00:07:16,920 --> 00:07:20,480
Speaker 1: was to use cortico steroids to reduce mortality in severe

122
00:07:20,560 --> 00:07:24,120
Speaker 1: COVID cases. Now, the man most behind this particular idea

123
00:07:24,200 --> 00:07:27,080
Speaker 1: was a guy named Dr Umberto Maduri. He's known as

124
00:07:27,160 --> 00:07:31,400
Speaker 1: the Guru of cortico steroids in lung disease. Conventional wisdom,

125
00:07:31,960 --> 00:07:34,280
Speaker 1: what an amazing I hope there's a T shirt for that.

126
00:07:34,400 --> 00:07:36,280
Speaker 1: I hope there's a T Yeah, he should get They

127
00:07:36,280 --> 00:07:38,520
Speaker 1: announced him like it's a w w E wrestler when

128
00:07:38,560 --> 00:07:40,960
Speaker 1: he comes out at medical conferences. I mean funcket. I

129
00:07:40,960 --> 00:07:43,560
Speaker 1: want him to get a two Chains album, Like why not?

130
00:07:44,400 --> 00:07:46,760
Speaker 1: I want to hook up with him? Why not? Yeah?

131
00:07:47,680 --> 00:07:50,800
Speaker 1: Um so yeah, this guy has this idea that like, hey,

132
00:07:50,880 --> 00:07:53,920
Speaker 1: maybe cortico steroids might be useful in this situation, and

133
00:07:54,000 --> 00:07:57,360
Speaker 1: that was very controversial at the time. Conventional wisdom um

134
00:07:57,840 --> 00:08:00,640
Speaker 1: was that steroids like that do more harm than good

135
00:08:00,680 --> 00:08:04,160
Speaker 1: when treating a virus, like when treating a coronavirus. But

136
00:08:04,360 --> 00:08:06,520
Speaker 1: Dr Marduri and his colleagues were pretty sure that their

137
00:08:06,560 --> 00:08:09,480
Speaker 1: solution would help, and they distributed a new hospital protocol

138
00:08:09,600 --> 00:08:13,600
Speaker 1: called MATH plus for patients hospitalized with severe COVID. Hospitals

139
00:08:13,640 --> 00:08:15,760
Speaker 1: began trying it out because again, this is early in

140
00:08:15,840 --> 00:08:18,559
Speaker 1: the virus. There's not it's kind of like throwing everything

141
00:08:18,600 --> 00:08:21,880
Speaker 1: at the wall and seeing what sticks. Um, And there's

142
00:08:21,880 --> 00:08:24,960
Speaker 1: evidence that this seriously slowed down mortality. It seems to

143
00:08:25,120 --> 00:08:29,600
Speaker 1: have worked. Hospital administrators noticed rapid slowdowns and mortality when

144
00:08:29,600 --> 00:08:33,160
Speaker 1: they adopted this, specifically for people who were very sick. Um,

145
00:08:34,160 --> 00:08:37,319
Speaker 1: when you hire the guru, that's great, you're bringing the guru.

146
00:08:37,440 --> 00:08:39,559
Speaker 1: So yeah, um, And there was of course, you know,

147
00:08:39,679 --> 00:08:42,240
Speaker 1: they kind of started adopting this before there was a

148
00:08:42,320 --> 00:08:44,559
Speaker 1: huge body of science, but a body of science was

149
00:08:44,720 --> 00:08:48,240
Speaker 1: built as they started adopting this, and a large UK

150
00:08:48,440 --> 00:08:52,240
Speaker 1: patient study in June of showed that steroid treatment that

151
00:08:52,320 --> 00:08:57,000
Speaker 1: the FLCCC suggested really worked. The MATH plus protocol was greenlit,

152
00:08:57,080 --> 00:09:00,240
Speaker 1: and hospitals around the United States praise for ed in

153
00:09:00,360 --> 00:09:01,880
Speaker 1: for the f l c c C, who at this

154
00:09:02,000 --> 00:09:04,679
Speaker 1: point looked like hard working doctors doing their damnedest to

155
00:09:04,720 --> 00:09:08,280
Speaker 1: find creative ways to save lives in an incredibly challenging situation.

156
00:09:09,160 --> 00:09:13,000
Speaker 1: Wait were they not? Well, this is not an easy

157
00:09:13,160 --> 00:09:19,600
Speaker 1: answer to that question. Jamie, Okay, because um, they definitely

158
00:09:19,679 --> 00:09:21,520
Speaker 1: did a good thing there and saved a lot of

159
00:09:21,600 --> 00:09:23,920
Speaker 1: lives with that, they have also gone on to do

160
00:09:24,320 --> 00:09:28,200
Speaker 1: some sketchy things And I don't have an easy summary

161
00:09:28,360 --> 00:09:30,679
Speaker 1: for you of like the f l c c C is,

162
00:09:30,760 --> 00:09:34,880
Speaker 1: like they're horrible grifters or there you know, decent medical

163
00:09:35,240 --> 00:09:37,840
Speaker 1: you know, people who got something wrong or their their truth.

164
00:09:38,120 --> 00:09:39,640
Speaker 1: Like I don't. I don't have an easy answer for

165
00:09:39,679 --> 00:09:42,640
Speaker 1: you for what these people are. But things take a

166
00:09:42,720 --> 00:09:45,880
Speaker 1: turn at this point. So one of the doctors, one

167
00:09:45,920 --> 00:09:47,640
Speaker 1: of the co founders of the f l c c C,

168
00:09:47,840 --> 00:09:50,960
Speaker 1: was a guy named Dr Pierre Corey. Now Dr Corey

169
00:09:51,120 --> 00:09:54,719
Speaker 1: was not the brains behind Dr Murdery's cortico steroid plan,

170
00:09:54,880 --> 00:09:56,880
Speaker 1: but he did helped found the f l c c C.

171
00:09:57,520 --> 00:10:00,760
Speaker 1: He was very interested in the early in the early

172
00:10:00,880 --> 00:10:04,240
Speaker 1: data that started coming out about iver mechton. In October,

173
00:10:05,120 --> 00:10:07,800
Speaker 1: he and other FLCCC doctors noted that there had been

174
00:10:07,880 --> 00:10:11,840
Speaker 1: several small successful trials using iver mecton as a preventative measure.

175
00:10:12,200 --> 00:10:15,679
Speaker 1: These studies were not large or particularly high quality. We'll

176
00:10:15,679 --> 00:10:17,559
Speaker 1: talk a little bit about them later, but in those

177
00:10:17,640 --> 00:10:19,520
Speaker 1: pre vaccine days, a case could be made that they

178
00:10:19,520 --> 00:10:22,240
Speaker 1: were not being irresponsible by adding iver mecton to their

179
00:10:22,320 --> 00:10:25,960
Speaker 1: math plus protocol alongside a new preventative protocol called i'm

180
00:10:26,000 --> 00:10:29,959
Speaker 1: ask plus. There's not vaccines yet. The pandemic October is

181
00:10:30,040 --> 00:10:33,599
Speaker 1: kind of at the fucking worst it's been um and

182
00:10:34,000 --> 00:10:36,280
Speaker 1: you know, you could also say, like, well, they kind

183
00:10:36,320 --> 00:10:38,199
Speaker 1: of took a little bit of a stab on cortico

184
00:10:38,280 --> 00:10:40,920
Speaker 1: steroids and that wound up saving lives. Might as well

185
00:10:40,960 --> 00:10:43,600
Speaker 1: give it a shot with especially since iver mechten, when

186
00:10:43,720 --> 00:10:47,720
Speaker 1: taken in quantities for humans, that's prescribed by a doctor

187
00:10:47,880 --> 00:10:51,600
Speaker 1: fairly minimal risks. Right. I've never known anyone who's had

188
00:10:51,720 --> 00:10:55,920
Speaker 1: river blindness, So yes, exactly exactly, you don't and I

189
00:10:56,320 --> 00:10:59,760
Speaker 1: spray you with a lot of contaminated river water, Jamie.

190
00:11:00,320 --> 00:11:02,400
Speaker 1: You do. You've been doing a lot of experiments, But

191
00:11:02,600 --> 00:11:04,439
Speaker 1: I I do believe when you say, it's for the

192
00:11:04,480 --> 00:11:08,920
Speaker 1: greater good of some So these guys are kind of

193
00:11:09,000 --> 00:11:13,559
Speaker 1: operating off of the goodwill of having been semi successful

194
00:11:13,640 --> 00:11:18,360
Speaker 1: before to experiment with, and they're they're also operating. You

195
00:11:18,400 --> 00:11:21,839
Speaker 1: do have to acknowledge the situation when you're dealing with

196
00:11:21,920 --> 00:11:27,079
Speaker 1: a pandemic of this severity, you can't necessarily wait, like

197
00:11:27,240 --> 00:11:29,160
Speaker 1: you have to make You have to kind of triage

198
00:11:29,240 --> 00:11:32,240
Speaker 1: when you wait to try something. And I can see

199
00:11:32,280 --> 00:11:34,839
Speaker 1: in the case of being like look when you when

200
00:11:34,960 --> 00:11:38,559
Speaker 1: taken when when giving people like normal human doses of

201
00:11:38,640 --> 00:11:42,520
Speaker 1: iver mactin very minimal risk of side effects. If it

202
00:11:43,160 --> 00:11:46,920
Speaker 1: might help, it's worth trying. You know you can you

203
00:11:47,000 --> 00:11:49,240
Speaker 1: can make that case. And that's the case these people

204
00:11:49,280 --> 00:11:52,040
Speaker 1: were making it at this point. They're not being bastards

205
00:11:52,120 --> 00:11:55,280
Speaker 1: that I can tell um. And they imagine they're making

206
00:11:55,280 --> 00:11:59,280
Speaker 1: a shipload of money also would that be I don't

207
00:11:59,480 --> 00:12:02,319
Speaker 1: I don't have that information, Jamie, some of this. So

208
00:12:02,440 --> 00:12:03,959
Speaker 1: one of the troubles with this, This is gonna be

209
00:12:03,960 --> 00:12:05,240
Speaker 1: a little bit of a messier because a lot of

210
00:12:05,280 --> 00:12:07,160
Speaker 1: this is still breaking. And in fact, one of the

211
00:12:07,200 --> 00:12:09,640
Speaker 1: studies that I was talking about earlier, an article just

212
00:12:09,840 --> 00:12:13,680
Speaker 1: dropped today kind of talking about it. So I think

213
00:12:13,720 --> 00:12:15,640
Speaker 1: that we will learn more about the f l c

214
00:12:15,800 --> 00:12:17,400
Speaker 1: c C in time as a result of some of

215
00:12:17,440 --> 00:12:20,360
Speaker 1: the things we'll talk about. I don't know the extent

216
00:12:20,480 --> 00:12:22,800
Speaker 1: to which people are making a profit off of it.

217
00:12:22,880 --> 00:12:25,439
Speaker 1: I don't know enough to allege any that kind of

218
00:12:25,760 --> 00:12:30,520
Speaker 1: fiscal wrongdoing. But there's something weird here at some being

219
00:12:30,640 --> 00:12:33,680
Speaker 1: on the cutting edge as usual, Robert, thank you, Jamie,

220
00:12:34,040 --> 00:12:36,400
Speaker 1: thank you. I am on the cutting edge like I

221
00:12:36,520 --> 00:12:39,679
Speaker 1: am in the cutting edge of basketball strategies, here in

222
00:12:39,720 --> 00:12:43,480
Speaker 1: the cutting edge of weddings, on the cutting edge of

223
00:12:43,920 --> 00:12:46,520
Speaker 1: COVID analysis, on the cutting edge of smiling with your

224
00:12:46,559 --> 00:12:49,319
Speaker 1: teeth and pictures. Thank you, thank you. You know I

225
00:12:49,440 --> 00:12:52,079
Speaker 1: invented the four pointer recently. No one had ever done

226
00:12:52,160 --> 00:12:56,360
Speaker 1: that in basket No kidding, Wow right, that's right, make

227
00:12:56,480 --> 00:13:01,040
Speaker 1: me fire you again. So at this point, it's also

228
00:13:01,080 --> 00:13:04,640
Speaker 1: important to enough that the FLCCC, they're saying, we're adding

229
00:13:04,920 --> 00:13:08,120
Speaker 1: this might we're recommending this in certain situations for people

230
00:13:08,120 --> 00:13:11,920
Speaker 1: who are sick and as a potential prophylactic to prevent COVID.

231
00:13:12,440 --> 00:13:15,880
Speaker 1: They were not billing iver mectin as a replacement or

232
00:13:15,920 --> 00:13:18,880
Speaker 1: an alternative to the vaccine, and in fact, they're early

233
00:13:19,040 --> 00:13:22,120
Speaker 1: advocacy of iver mectin discussed it purely as a stop

234
00:13:22,160 --> 00:13:25,439
Speaker 1: gap vaccines are not available at this point. There's some

235
00:13:25,559 --> 00:13:28,040
Speaker 1: evidence that this might help stem the tide of infections,

236
00:13:28,120 --> 00:13:31,240
Speaker 1: and we are at capacity in hospital, so this might

237
00:13:31,400 --> 00:13:35,360
Speaker 1: reduce infections that might improve outcomes. We're going to recommend

238
00:13:35,440 --> 00:13:37,880
Speaker 1: people take it until there's a vaccine, right, and I'm

239
00:13:37,880 --> 00:13:40,240
Speaker 1: gonna quote from Yahoo News here to talk about some

240
00:13:40,320 --> 00:13:44,079
Speaker 1: people who did use it in that situation. In a

241
00:13:44,160 --> 00:13:47,720
Speaker 1: February local news segment, a Midland, Texas woman describes how

242
00:13:47,760 --> 00:13:50,360
Speaker 1: she learned about iver mectin backed in October from the Internet,

243
00:13:50,440 --> 00:13:52,120
Speaker 1: and she and her family had been taking it in

244
00:13:52,160 --> 00:13:55,199
Speaker 1: animal form ever since. Though she wasn't taking the tablets

245
00:13:55,240 --> 00:13:58,080
Speaker 1: for humans as the f LCCC recommends. In a way,

246
00:13:58,160 --> 00:14:00,599
Speaker 1: she was taking it as intended as a bridge to

247
00:14:00,679 --> 00:14:03,719
Speaker 1: the vaccine. I just got my first vaccine shot a

248
00:14:03,800 --> 00:14:06,200
Speaker 1: few days ago, So no more horse paste, she told

249
00:14:06,240 --> 00:14:09,320
Speaker 1: the reporter. So that is I do want to acknowledge here,

250
00:14:09,760 --> 00:14:13,360
Speaker 1: that's not being unreasonable, like right, maybe I would recommend

251
00:14:13,400 --> 00:14:15,439
Speaker 1: get the human version if you can. But whatever, people,

252
00:14:15,720 --> 00:14:17,800
Speaker 1: I know a lot of poor people in the country.

253
00:14:17,880 --> 00:14:20,440
Speaker 1: Sometimes you take veterinary medicine because it's what you can afford.

254
00:14:21,720 --> 00:14:23,840
Speaker 1: I mean that the turn of phrase. So no more

255
00:14:24,200 --> 00:14:29,200
Speaker 1: horse paste alone. But I'm not gonna say this is

256
00:14:29,280 --> 00:14:32,200
Speaker 1: the most responsible decision of person could have made. But

257
00:14:32,320 --> 00:14:35,840
Speaker 1: she got her vaccine right, and she there was I

258
00:14:35,960 --> 00:14:38,640
Speaker 1: want you to I want you to type fl c

259
00:14:38,800 --> 00:14:41,920
Speaker 1: c C into Google and pull up their web page

260
00:14:41,960 --> 00:14:44,640
Speaker 1: and take a look at it. Because when she says

261
00:14:44,680 --> 00:14:47,520
Speaker 1: she found it on the internet, and because this person

262
00:14:47,560 --> 00:14:49,560
Speaker 1: took the vaccine, I don't know, that can mean a

263
00:14:49,600 --> 00:14:51,880
Speaker 1: lot of things. That can mean somebody's like seeing someone

264
00:14:51,960 --> 00:14:55,880
Speaker 1: on Reddit talk about taking random medication or like on Facebook.

265
00:14:56,400 --> 00:14:57,760
Speaker 1: But if you look at the f l c c

266
00:14:57,920 --> 00:15:03,880
Speaker 1: C page, this doesn't take credit. Call care dot com Yeah, yeah, yeah, yeah,

267
00:15:04,040 --> 00:15:07,320
Speaker 1: it's a very reputable looking website. These are real asked

268
00:15:07,400 --> 00:15:12,080
Speaker 1: doctors with real Jamie Lakes Community College popa for you

269
00:15:12,240 --> 00:15:16,760
Speaker 1: twenty times and then it gets to the this had

270
00:15:16,800 --> 00:15:19,160
Speaker 1: to have been an s e O disaster for the

271
00:15:19,280 --> 00:15:22,800
Speaker 1: finger Figure Lakes Community College. Sorry, I forgot, I had

272
00:15:22,840 --> 00:15:24,880
Speaker 1: a picture of I forgot. I had a picture of

273
00:15:24,960 --> 00:15:26,880
Speaker 1: Joe Rogan in a tab and I just like it

274
00:15:27,000 --> 00:15:30,360
Speaker 1: was like a jump scare Um, okay, COVID nineteen, critical

275
00:15:30,400 --> 00:15:33,640
Speaker 1: care dot com. This does look like how I picture

276
00:15:34,880 --> 00:15:37,720
Speaker 1: medical website to look like. Okay, and you can you

277
00:15:37,840 --> 00:15:40,720
Speaker 1: can see how a concerned parent in the middle of

278
00:15:40,800 --> 00:15:44,520
Speaker 1: a horrible fucking plague could come to this and be like, Okay, well,

279
00:15:44,560 --> 00:15:47,040
Speaker 1: this seems like a reasonable thing to do for my

280
00:15:47,160 --> 00:15:50,680
Speaker 1: family until I can get the vaccine, like avoid censorship

281
00:15:50,800 --> 00:15:53,880
Speaker 1: connects to f l c c C alliance here, there's

282
00:15:53,960 --> 00:15:57,640
Speaker 1: definitely definitely and that I think is is newer. Like

283
00:15:57,800 --> 00:16:00,680
Speaker 1: you can see some kind of griff to your things

284
00:16:01,160 --> 00:16:04,600
Speaker 1: getting in here, right, um, but you can also see

285
00:16:04,640 --> 00:16:07,800
Speaker 1: how a perfectly reasonable person just trying to like do

286
00:16:07,960 --> 00:16:09,960
Speaker 1: what's best for their family could be like, okay, well

287
00:16:09,960 --> 00:16:13,200
Speaker 1: I'll give it a shot, right. And that's where fast too,

288
00:16:13,440 --> 00:16:19,640
Speaker 1: like everything quickly and in February, you know you October

289
00:16:19,920 --> 00:16:25,320
Speaker 1: to like January, October, January. People. I can see people

290
00:16:25,400 --> 00:16:27,760
Speaker 1: just being like, okay, well this seems like it might help.

291
00:16:28,160 --> 00:16:31,320
Speaker 1: I can't get a vaccine. So far, so good? Right,

292
00:16:31,480 --> 00:16:34,440
Speaker 1: so far the fl C c C I can't. I'm sure,

293
00:16:34,560 --> 00:16:37,720
Speaker 1: I'm sure there are things doctors could could quickly complain

294
00:16:37,760 --> 00:16:39,920
Speaker 1: about here. There's definitely a debate to be had about

295
00:16:39,960 --> 00:16:44,480
Speaker 1: certainly desperate, but there's no perfect choices you can make

296
00:16:44,560 --> 00:16:48,680
Speaker 1: in a fucking pandemic either. Um. That said, while they

297
00:16:48,760 --> 00:16:52,240
Speaker 1: haven't really gone off, they haven't broke bad yet. There

298
00:16:52,320 --> 00:16:56,000
Speaker 1: were early signs that something was awry. In December of

299
00:16:56,920 --> 00:17:00,080
Speaker 1: Dr Pierre Corey testified to a Senate panel about I

300
00:17:00,240 --> 00:17:05,440
Speaker 1: for mectin, which he called a wonder drug. Now, when

301
00:17:05,520 --> 00:17:08,399
Speaker 1: you hear the term wonder drug and they are not

302
00:17:08,760 --> 00:17:13,000
Speaker 1: talking about delauded. The only wonder drug which I call

303
00:17:13,080 --> 00:17:17,840
Speaker 1: a wonder drug because it's wonderful. What is that? You know,

304
00:17:17,920 --> 00:17:22,359
Speaker 1: I don't know what a drug is. Delatted is the

305
00:17:22,480 --> 00:17:29,720
Speaker 1: Toyota tacoma of opiates. It's liable, it's hard working, it's comfortable.

306
00:17:29,880 --> 00:17:37,120
Speaker 1: Oh my god, it's so good like um yeah, yeah,

307
00:17:37,480 --> 00:17:42,520
Speaker 1: because fuck oxy um delatted, baby, it's all about delatted. Okay,

308
00:17:42,680 --> 00:17:46,560
Speaker 1: that's good information for when I begin taking opiates. Yeah. Absolutely,

309
00:17:46,600 --> 00:17:49,960
Speaker 1: everybody needs good information and that information is tried a

310
00:17:50,040 --> 00:17:56,440
Speaker 1: lauded sponsors of the podcast. By the way, wait, he

311
00:17:56,560 --> 00:17:58,720
Speaker 1: called it a lot a wonder drug to the Senate,

312
00:17:58,800 --> 00:18:01,960
Speaker 1: which is not in court. He called it a wonder drug. Okay,

313
00:18:02,040 --> 00:18:05,520
Speaker 1: that doesn't sound good. That doesn't sound good. That's not

314
00:18:06,440 --> 00:18:10,600
Speaker 1: very especially since there is data in December of that

315
00:18:10,680 --> 00:18:13,119
Speaker 1: suggests this might be a useful and and it's perfectly

316
00:18:13,119 --> 00:18:15,280
Speaker 1: it would have been perfectly reasonably said, hey, we've got

317
00:18:15,359 --> 00:18:18,000
Speaker 1: some data. This might help. Here's the situations in which

318
00:18:18,040 --> 00:18:21,159
Speaker 1: the data suggests it might help. This is my recommendations

319
00:18:21,480 --> 00:18:23,960
Speaker 1: that might be how a responsible doctor would say it.

320
00:18:24,280 --> 00:18:31,240
Speaker 1: You don't call it doctor oz rhetoric exactly. Yeah, Well

321
00:18:31,520 --> 00:18:35,840
Speaker 1: with the Senate, and so number one it this Senate

322
00:18:35,920 --> 00:18:39,720
Speaker 1: panel was a Homeland Security Senate panel. So I don't

323
00:18:39,760 --> 00:18:43,240
Speaker 1: know why the funk they're talking about that. Why none

324
00:18:43,280 --> 00:18:46,320
Speaker 1: of you people like you're not even good at homeland security.

325
00:18:46,400 --> 00:18:51,639
Speaker 1: Why are you talking about fucking COVID nineteen killing time?

326
00:18:51,920 --> 00:18:55,439
Speaker 1: That's so bizarry, let's get a doctor up here. Now.

327
00:18:55,680 --> 00:19:02,040
Speaker 1: The panel was chaired by Wisconsin Senator Ron Johnson, because flag,

328
00:19:02,520 --> 00:19:06,359
Speaker 1: that's a real red flag right there. Okay, Now, the

329
00:19:06,480 --> 00:19:10,240
Speaker 1: problem is that because of the fl CCCS reputation with

330
00:19:10,320 --> 00:19:14,400
Speaker 1: Cortico steroids, Dr Pierre Corey isn't doesn't seem when he's

331
00:19:14,400 --> 00:19:16,760
Speaker 1: coming up front, he's not just some yahoo. He is

332
00:19:16,840 --> 00:19:20,440
Speaker 1: a real doctor working with an organization that took a

333
00:19:20,680 --> 00:19:23,680
Speaker 1: very bold stab early in the pandemic and was very

334
00:19:23,800 --> 00:19:27,840
Speaker 1: right about it, like and which then immediately jokerfied themselves

335
00:19:27,880 --> 00:19:30,040
Speaker 1: and then they went jography. Yeah exactly, but like you

336
00:19:30,080 --> 00:19:34,080
Speaker 1: can see why this is so dangerous, right, um? Right?

337
00:19:34,400 --> 00:19:36,600
Speaker 1: And I also understand, I mean with Ron Johnson, there's

338
00:19:36,600 --> 00:19:39,640
Speaker 1: no excuse for anything he does. But I understand from

339
00:19:39,720 --> 00:19:44,600
Speaker 1: like a regular, like a person consuming this media with

340
00:19:44,720 --> 00:19:48,560
Speaker 1: not a lot of information, why it might have seemed

341
00:19:48,640 --> 00:19:51,000
Speaker 1: like not the worst most dangerous thing in the world

342
00:19:51,040 --> 00:19:56,200
Speaker 1: to do so at this point, there's some shady stuff

343
00:19:56,240 --> 00:20:01,440
Speaker 1: going on that Senate testimony is questionable, right um, But

344
00:20:01,520 --> 00:20:04,560
Speaker 1: there's also not really anything to suggest at the end

345
00:20:04,600 --> 00:20:06,800
Speaker 1: of that ever mectin is about to become a public

346
00:20:06,840 --> 00:20:09,879
Speaker 1: health problem. And in fact, while the US started ramping

347
00:20:09,960 --> 00:20:13,719
Speaker 1: up and distributing vaccines at the tail end of early one,

348
00:20:14,080 --> 00:20:17,359
Speaker 1: huge chunks of Latin America started adopting ever mectin as

349
00:20:17,400 --> 00:20:21,119
Speaker 1: a standard treatment protocol. And the reasoning for this is

350
00:20:21,160 --> 00:20:24,080
Speaker 1: as bleak as it is understandable. Latin America has some

351
00:20:24,160 --> 00:20:27,480
Speaker 1: of the worst COVID death rates on the planet. Whitespread

352
00:20:27,560 --> 00:20:30,399
Speaker 1: poverty meant that while the vaccine was starting to get

353
00:20:30,480 --> 00:20:32,600
Speaker 1: rolled out in the United States, it was not going

354
00:20:32,720 --> 00:20:35,600
Speaker 1: to be anywhere in the near future for millions tens

355
00:20:35,640 --> 00:20:38,040
Speaker 1: of millions of people in Latin America. So while the

356
00:20:38,119 --> 00:20:41,359
Speaker 1: wealthy countries hoarded vaccines for their own people, doctors in

357
00:20:41,440 --> 00:20:44,080
Speaker 1: South and Central America looked at the early evidence on

358
00:20:44,119 --> 00:20:46,119
Speaker 1: iver mactin and said, this is the best we can

359
00:20:46,200 --> 00:20:49,800
Speaker 1: fucking do and we can afford it, you know, yeah,

360
00:20:50,680 --> 00:20:54,120
Speaker 1: which is very sad, that's extremely blak. Yeah, it's real

361
00:20:54,240 --> 00:20:58,680
Speaker 1: fucking bleak. Um and Peru included the drug and its

362
00:20:58,760 --> 00:21:01,639
Speaker 1: basic treatment guide lines, and one health minister in the

363
00:21:01,720 --> 00:21:05,440
Speaker 1: country told Nature magazine that clinical trials investigating the drugs

364
00:21:05,480 --> 00:21:10,359
Speaker 1: efficacy had trouble recruiting control group participants because there were

365
00:21:10,440 --> 00:21:13,920
Speaker 1: so many people already on the drug. Basically, they recommended

366
00:21:13,960 --> 00:21:16,520
Speaker 1: people take this and then they had trouble studying it

367
00:21:16,600 --> 00:21:21,080
Speaker 1: because they couldn't find people who weren't taking it. Um wow, okay,

368
00:21:21,200 --> 00:21:25,840
Speaker 1: So it just and was this like a very fast process,

369
00:21:26,000 --> 00:21:29,000
Speaker 1: like it went zero okay, And it's it's fast in

370
00:21:29,080 --> 00:21:32,640
Speaker 1: part because you know, unlike when hydroxy cloquine, which we'll

371
00:21:32,640 --> 00:21:35,160
Speaker 1: talk about a bit later, kind of went viral, there's

372
00:21:35,200 --> 00:21:37,280
Speaker 1: not a lot of that ship, right, It's not just

373
00:21:37,400 --> 00:21:39,479
Speaker 1: like an o TC thing like people had to get

374
00:21:39,520 --> 00:21:41,920
Speaker 1: it prescribed. You don't just walk into a CD SID.

375
00:21:42,200 --> 00:21:44,880
Speaker 1: You could walk into stores down the corner and pick

376
00:21:44,960 --> 00:21:48,159
Speaker 1: up iver mecton. Because especially in like rural at in America,

377
00:21:48,160 --> 00:21:50,600
Speaker 1: any rural place, there's a shiploaded animal feed stores. It's

378
00:21:50,600 --> 00:21:54,840
Speaker 1: all over the place. Over the counter veterinary drug. Yeah, yeah,

379
00:21:55,000 --> 00:21:57,600
Speaker 1: it's over the counter veterinary drug. It's not super you

380
00:21:57,640 --> 00:21:59,480
Speaker 1: do have to get it prescribed for a person, but

381
00:21:59,520 --> 00:22:01,560
Speaker 1: I think most these people are taking the veterinary version.

382
00:22:01,600 --> 00:22:04,840
Speaker 1: But even the person version, it's extreme, especially since a

383
00:22:04,920 --> 00:22:09,160
Speaker 1: lot of Latin America a lot of huge amount of parasites,

384
00:22:09,160 --> 00:22:11,480
Speaker 1: so a lot of people are taking this anyway. It's available,

385
00:22:11,600 --> 00:22:14,160
Speaker 1: is the point. It's available, and it's cheap, so it's

386
00:22:14,480 --> 00:22:17,080
Speaker 1: once these people here, this might protect your family from COVID.

387
00:22:17,400 --> 00:22:20,280
Speaker 1: They actually have the ability to get this stuff immediately.

388
00:22:20,960 --> 00:22:24,440
Speaker 1: Um In Bolivia, healthcare workers pretty much instantly distributed three

389
00:22:24,840 --> 00:22:27,880
Speaker 1: and fifty thousand doses. I Ever, met In also grew

390
00:22:27,960 --> 00:22:31,240
Speaker 1: popular in South America for the same reasons poverty and

391
00:22:31,359 --> 00:22:36,600
Speaker 1: desperation um so from the website Pharmaceutical Technology quote. The

392
00:22:36,640 --> 00:22:39,560
Speaker 1: pro iver met In campaign has taken a particularly stronghold

393
00:22:39,600 --> 00:22:42,480
Speaker 1: in South Africa, where coronavirus infection rates are among the

394
00:22:42,560 --> 00:22:44,920
Speaker 1: worst in the continent and the vaccine program has yet

395
00:22:44,960 --> 00:22:47,680
Speaker 1: to cover all the country's most vulnerable. Some doctors have

396
00:22:47,760 --> 00:22:50,879
Speaker 1: been prescribing the worm drug to COVID nineteen patients, claiming

397
00:22:50,880 --> 00:22:54,440
Speaker 1: anecdotally that it alleviates virus symptoms, despite the South African

398
00:22:54,520 --> 00:22:58,600
Speaker 1: Health Products Regulatory Authority warning against its use. I ever

399
00:22:58,720 --> 00:23:01,280
Speaker 1: met In is also thriving the country's black market, where

400
00:23:01,280 --> 00:23:03,960
Speaker 1: one tablet can sell for as much as twenty five pounds,

401
00:23:04,280 --> 00:23:07,240
Speaker 1: and sales of veterinary forms of the drug have skyrocketed.

402
00:23:07,600 --> 00:23:10,720
Speaker 1: Grassroots collectives such as the iver Metin Interest Group formed

403
00:23:10,760 --> 00:23:14,440
Speaker 1: of South African health practitioners, public health experts and medical scientists,

404
00:23:14,680 --> 00:23:17,400
Speaker 1: have campaigned for approval of the drug, while civil rights

405
00:23:17,480 --> 00:23:20,120
Speaker 1: group afro Form earlier this year filed a court case

406
00:23:20,160 --> 00:23:25,920
Speaker 1: against SAFFRA, which is the South African Health Products Regulating Authority,

407
00:23:26,080 --> 00:23:29,080
Speaker 1: to have the treatment approved for COVID nineteen patients. After

408
00:23:29,200 --> 00:23:32,080
Speaker 1: initially allowing controlled compassionate use of the drug in an

409
00:23:32,119 --> 00:23:34,800
Speaker 1: attempt to curb illegal sales, the health agency this month

410
00:23:34,840 --> 00:23:37,320
Speaker 1: received a High court order to permit the off label

411
00:23:37,400 --> 00:23:43,440
Speaker 1: prescription of iver mectin by doctors. Iver met And also

412
00:23:43,560 --> 00:23:46,639
Speaker 1: took off in the Philippines, where viral social media posts

413
00:23:46,720 --> 00:23:49,800
Speaker 1: sent the product flying off the shelves of veterinary suppliers.

414
00:23:50,080 --> 00:23:52,680
Speaker 1: One doctor was found to have printed eight thousand iver

415
00:23:52,840 --> 00:23:57,600
Speaker 1: mettin pills using his own recipe. The Philippines FDA. Yeah,

416
00:23:57,720 --> 00:24:00,240
Speaker 1: the Philippines f d A attempted to reign this in

417
00:24:00,359 --> 00:24:03,000
Speaker 1: and issued warnings that were not heated, but they also

418
00:24:03,080 --> 00:24:05,640
Speaker 1: approved too limited studies on the use of iver mectin

419
00:24:05,720 --> 00:24:08,520
Speaker 1: in hospitals, admitting that they had been pressured to do

420
00:24:08,720 --> 00:24:12,240
Speaker 1: so by sheer public demand. So when we talk about

421
00:24:12,240 --> 00:24:16,359
Speaker 1: I'm curious about, like how this information because you're saying

422
00:24:16,400 --> 00:24:18,800
Speaker 1: like that there were like viral posts that got the

423
00:24:18,840 --> 00:24:23,040
Speaker 1: word out very quickly. Were they just post from regular

424
00:24:23,119 --> 00:24:25,359
Speaker 1: people that were taking off where they're like groups that

425
00:24:25,440 --> 00:24:29,080
Speaker 1: were posting like how was So here's the way we're

426
00:24:29,080 --> 00:24:32,280
Speaker 1: gonna talk about this more. But you have at the

427
00:24:32,359 --> 00:24:36,040
Speaker 1: top of the list, you have actual scientific studies. Right,

428
00:24:36,880 --> 00:24:38,440
Speaker 1: We're going to analyze a little bit, some of what

429
00:24:38,520 --> 00:24:40,800
Speaker 1: you're sketchy, some of what you're real, some of which

430
00:24:40,800 --> 00:24:43,800
Speaker 1: show a potential benefit. Those filter down to the f

431
00:24:43,960 --> 00:24:46,680
Speaker 1: l C c C and some a couple other similar

432
00:24:46,760 --> 00:24:49,840
Speaker 1: groups who are made up of doctors and start advising

433
00:24:49,920 --> 00:24:55,240
Speaker 1: people to take iver mactin. That filters down to influencers too,

434
00:24:55,320 --> 00:24:58,320
Speaker 1: people in media figures and whatnot who start advising people

435
00:24:58,359 --> 00:25:00,240
Speaker 1: to take it, and that filters down to like face book,

436
00:25:00,240 --> 00:25:02,920
Speaker 1: groups and ship where people start spreading memes and what

437
00:25:03,119 --> 00:25:08,680
Speaker 1: the bassist area of the human psyche hidden Facebook groups. Okay,

438
00:25:08,800 --> 00:25:12,320
Speaker 1: and that's how you get from the FLCCC saying doctors

439
00:25:12,400 --> 00:25:15,640
Speaker 1: should consider prescribing this too. I'm going to buy horse

440
00:25:15,720 --> 00:25:18,359
Speaker 1: paste and give it to my children. So it's just

441
00:25:18,400 --> 00:25:21,280
Speaker 1: like the most sinister game of telephone ever, Yes, and

442
00:25:21,400 --> 00:25:23,800
Speaker 1: it is. I do want to note as we as

443
00:25:23,840 --> 00:25:27,879
Speaker 1: everybody continues laughing at the fucking stupid ass Americans who

444
00:25:27,920 --> 00:25:31,359
Speaker 1: could easily get a free vaccine and take fucking horse paste,

445
00:25:31,920 --> 00:25:34,800
Speaker 1: most of the people taking this stuff in mass have

446
00:25:35,000 --> 00:25:37,840
Speaker 1: no options and are incredibly poor and live in the

447
00:25:37,920 --> 00:25:42,000
Speaker 1: periphery in countries rights. What else are they've gonna fucking do?

448
00:25:43,080 --> 00:25:45,400
Speaker 1: Doctors are telling them. There are a lot of doctors,

449
00:25:45,680 --> 00:25:48,560
Speaker 1: and again they're very shady doctors, usually working off a

450
00:25:48,720 --> 00:25:51,520
Speaker 1: very bad scientist, but they're fucking doctors and they're telling

451
00:25:51,600 --> 00:25:53,800
Speaker 1: these people this could help your family, and they can't

452
00:25:53,840 --> 00:25:56,320
Speaker 1: get a fucking vaccine. They have no options, right, Like,

453
00:25:56,440 --> 00:25:58,720
Speaker 1: what are they? You're not dumb if you're in the Philippines,

454
00:25:58,720 --> 00:26:00,280
Speaker 1: if you're in Latin America, South americ and you're like,

455
00:26:00,359 --> 00:26:03,080
Speaker 1: this is what else am I gonna do, you know, right,

456
00:26:03,119 --> 00:26:05,560
Speaker 1: if it it's the only option there's there's it's so

457
00:26:05,760 --> 00:26:08,119
Speaker 1: urgent that there's no I mean, there's no time to

458
00:26:08,200 --> 00:26:12,520
Speaker 1: get that's that's what is like sticking out to be

459
00:26:12,600 --> 00:26:15,280
Speaker 1: here as like especially frustrating because there are very few

460
00:26:15,320 --> 00:26:18,560
Speaker 1: options and like no time to get better information. So

461
00:26:18,720 --> 00:26:20,560
Speaker 1: it is you're saying, what are you going to do?

462
00:26:21,000 --> 00:26:22,919
Speaker 1: And it's it's also important to note that a lot

463
00:26:23,000 --> 00:26:24,960
Speaker 1: of these people and a lot of these communities and

464
00:26:24,960 --> 00:26:27,200
Speaker 1: their communities, I grew up in a community like not

465
00:26:27,280 --> 00:26:29,640
Speaker 1: on like this. In the US, there's a decent chunk

466
00:26:29,680 --> 00:26:32,960
Speaker 1: of of veterinary medicines that work just as well on

467
00:26:33,119 --> 00:26:37,000
Speaker 1: people and are cheaper and more available. And sometimes poor

468
00:26:37,119 --> 00:26:40,520
Speaker 1: people do that because again, what the funk else do

469
00:26:40,600 --> 00:26:43,880
Speaker 1: you want me to do? Like my kid is sick? Um,

470
00:26:44,080 --> 00:26:46,400
Speaker 1: and it doesn't like it's not always a bad idea,

471
00:26:46,440 --> 00:26:48,480
Speaker 1: like it's never the thing that doctors are recommened, but

472
00:26:48,520 --> 00:26:50,919
Speaker 1: fucking people do it, and there's things that it can

473
00:26:51,000 --> 00:26:53,639
Speaker 1: work on, because like, what else are you gonna fucking do? Um?

474
00:26:54,240 --> 00:26:56,960
Speaker 1: There's different anyway, I know, I'm not advising you to

475
00:26:57,040 --> 00:26:59,680
Speaker 1: go by veterinary medicine for your family I'm saying people

476
00:26:59,720 --> 00:27:01,280
Speaker 1: have done it for a long time, and it's not

477
00:27:01,359 --> 00:27:04,080
Speaker 1: always a bad idea, and that's part of why people

478
00:27:04,119 --> 00:27:06,639
Speaker 1: are like, well, sure, you know, I've taken like I

479
00:27:06,720 --> 00:27:08,920
Speaker 1: had to give my kids some fucking antibiotics or whatever

480
00:27:09,080 --> 00:27:12,000
Speaker 1: like that I got from a you know, like or

481
00:27:12,640 --> 00:27:15,240
Speaker 1: I've mected because you got a fucking uh because you

482
00:27:15,320 --> 00:27:17,600
Speaker 1: got a fucking parasite and I gave him, you know,

483
00:27:17,680 --> 00:27:19,879
Speaker 1: a small dose of horse paste because I couldn't afford

484
00:27:19,920 --> 00:27:21,640
Speaker 1: to go to a doctor and get it prescribed. I'm

485
00:27:21,680 --> 00:27:25,000
Speaker 1: sure a number of these people like, again, these are

486
00:27:25,040 --> 00:27:27,440
Speaker 1: not dumb people. I just really want to because so

487
00:27:27,560 --> 00:27:29,520
Speaker 1: much of the discourse around this is like making fun

488
00:27:29,600 --> 00:27:31,200
Speaker 1: of the idiots in America who do it, and a

489
00:27:31,280 --> 00:27:32,800
Speaker 1: lot of them are very dumb and funk a lot

490
00:27:32,880 --> 00:27:35,520
Speaker 1: of those people because they could be getting a vaccine um.

491
00:27:36,240 --> 00:27:40,639
Speaker 1: But like most of these people just don't have an option, right,

492
00:27:40,680 --> 00:27:42,800
Speaker 1: which like trickles down in so many different ways of

493
00:27:43,600 --> 00:27:46,639
Speaker 1: like how broken the health care system is, Like that

494
00:27:46,680 --> 00:27:48,959
Speaker 1: wouldn't even be a necessity. You wouldn't need to make

495
00:27:49,000 --> 00:27:52,359
Speaker 1: that judgment call off if there were actual, you know,

496
00:27:52,600 --> 00:27:57,920
Speaker 1: more viable options made available. But you know what, viable options.

497
00:27:58,160 --> 00:28:03,119
Speaker 1: Everyone has, Jamie, what to engage with some light product

498
00:28:03,200 --> 00:28:06,800
Speaker 1: and services, some light or some heavy. You know, you

499
00:28:06,880 --> 00:28:09,280
Speaker 1: can you can stick, you can just kind of business,

500
00:28:09,520 --> 00:28:11,480
Speaker 1: just the tip of the products and services, or you

501
00:28:11,520 --> 00:28:15,920
Speaker 1: can go all the way in. That's your business, you know. Yeah,

502
00:28:16,320 --> 00:28:19,200
Speaker 1: we don't. We don't judge, we don't ask questions. We

503
00:28:19,359 --> 00:28:25,120
Speaker 1: just we just sell people products and occasionally services. Wonder products,

504
00:28:25,240 --> 00:28:30,399
Speaker 1: Wonder services. Yeah, Wonder products and Wonder services. All right,

505
00:28:30,480 --> 00:28:40,840
Speaker 1: here's an ad Ah. We're back. And boy, I don't

506
00:28:40,880 --> 00:28:44,880
Speaker 1: know about you, but all of my depression thinking about

507
00:28:45,120 --> 00:28:50,560
Speaker 1: the desperation that would lead people in cash for nations

508
00:28:51,000 --> 00:28:56,080
Speaker 1: to self medicate because uh, wealthy nations have hoarded the

509
00:28:56,200 --> 00:29:00,440
Speaker 1: vaccine in many cases for profit. Um. I don't know

510
00:29:00,480 --> 00:29:01,800
Speaker 1: where I was going with this. I was trying to

511
00:29:01,840 --> 00:29:03,560
Speaker 1: make a product and services joke, but now I'm just

512
00:29:03,640 --> 00:29:07,680
Speaker 1: sad again. How are you doing, Jamie, you know, talking

513
00:29:07,720 --> 00:29:13,000
Speaker 1: about pharmaceuticals under capitalism. I'm flying high. I feel incredible.

514
00:29:13,080 --> 00:29:15,520
Speaker 1: I don't have a problem in the world. Everything is

515
00:29:15,720 --> 00:29:18,760
Speaker 1: perfect and great. Yeah, I want to die. I mean,

516
00:29:18,880 --> 00:29:20,560
Speaker 1: I don't know we're what we're a half hour into

517
00:29:20,600 --> 00:29:23,120
Speaker 1: the episode. I absolutely want to you know, just walk

518
00:29:23,160 --> 00:29:25,360
Speaker 1: into traffic, Robert, is that what you want to hear?

519
00:29:25,840 --> 00:29:27,640
Speaker 1: Because that's where I'm always at at this point in

520
00:29:27,680 --> 00:29:31,080
Speaker 1: the episode, That's where we're at. That's where we're at.

521
00:29:31,280 --> 00:29:38,760
Speaker 1: That's just so we're at. Jamie. You like science, Yeah, sure, yeah,

522
00:29:39,000 --> 00:29:43,480
Speaker 1: I'm nothing against silence. I got nothing against science. I

523
00:29:43,560 --> 00:29:45,240
Speaker 1: know what, do I have a brain for it? No?

524
00:29:45,400 --> 00:29:47,480
Speaker 1: Does it make sense to me? No? No, of course not.

525
00:29:47,560 --> 00:29:53,880
Speaker 1: I'm I'm glad people do it also, No, yeah, yeah,

526
00:29:53,960 --> 00:29:56,080
Speaker 1: which is my way to think I hate science. We're

527
00:29:56,120 --> 00:29:58,760
Speaker 1: gonna talk a little bit about We're gonna talk a

528
00:29:58,800 --> 00:30:05,280
Speaker 1: little bit about um fucking uh. One of the problems

529
00:30:05,560 --> 00:30:09,360
Speaker 1: that science has, which is so the basic idea behind

530
00:30:09,640 --> 00:30:14,200
Speaker 1: you know, doing science is you you conduct studies to

531
00:30:14,320 --> 00:30:19,240
Speaker 1: test hypotheses, and you publish those results, and generally you

532
00:30:19,360 --> 00:30:21,760
Speaker 1: do small studies at first to kind of see if

533
00:30:22,080 --> 00:30:24,880
Speaker 1: if there's anything further to investigate or in you know,

534
00:30:24,960 --> 00:30:27,680
Speaker 1: those small studies, if if they're promising, kind of lead

535
00:30:27,720 --> 00:30:29,880
Speaker 1: to larger studies, and eventually you build a body of

536
00:30:29,960 --> 00:30:32,920
Speaker 1: evidence that leads you to one conclusion or another. Right,

537
00:30:33,040 --> 00:30:35,760
Speaker 1: that's the broad idea of how to sell the kind

538
00:30:35,760 --> 00:30:39,440
Speaker 1: of science you learn in when you're in first grade. Yeah,

539
00:30:39,840 --> 00:30:43,600
Speaker 1: that is that all that ship gets published, and oftentimes

540
00:30:43,640 --> 00:30:47,160
Speaker 1: it means that these tiny studies are getting published and

541
00:30:47,240 --> 00:30:49,520
Speaker 1: then people just assume, well, that's a study and it

542
00:30:49,600 --> 00:30:51,160
Speaker 1: says this is good, so I'm going to do it,

543
00:30:51,480 --> 00:30:55,040
Speaker 1: and then whole industries crop up around that while scientists

544
00:30:55,080 --> 00:30:57,720
Speaker 1: are still trying to figure out if it works. And

545
00:30:57,800 --> 00:30:59,960
Speaker 1: then another shady thing about it is that there's play

546
00:31:00,080 --> 00:31:02,120
Speaker 1: is that lets you publish studies before the studies have

547
00:31:02,200 --> 00:31:05,360
Speaker 1: been peer reviewed, which has some benefits. I've I've found

548
00:31:05,440 --> 00:31:08,479
Speaker 1: some writing as two people say why that can be useful, um,

549
00:31:08,640 --> 00:31:11,760
Speaker 1: But it also means that shady people who build themselves

550
00:31:11,800 --> 00:31:14,280
Speaker 1: as scientists can put up a study that isn't really

551
00:31:14,360 --> 00:31:17,120
Speaker 1: a study and hasn't been peer reviewed and has massive

552
00:31:17,240 --> 00:31:20,640
Speaker 1: laws and make it look like there's evident supporting something

553
00:31:20,760 --> 00:31:22,600
Speaker 1: when in fact there was not. And that's what we're

554
00:31:22,640 --> 00:31:27,080
Speaker 1: going to talk about now. So Peru was as as

555
00:31:27,160 --> 00:31:29,360
Speaker 1: far as I found, I think, the first nation to

556
00:31:29,520 --> 00:31:33,440
Speaker 1: include iver mecton in its national coronavirus treatment guidelines. This

557
00:31:33,640 --> 00:31:36,360
Speaker 1: was based on findings in a pre print of a

558
00:31:36,440 --> 00:31:39,760
Speaker 1: study by health analytics company surges Fere and again a

559
00:31:39,960 --> 00:31:43,760
Speaker 1: preprint not yet peer reviewed, so they're they're sticking to

560
00:31:43,920 --> 00:31:46,960
Speaker 1: rough draft, right, you know, but if these are publicly

561
00:31:47,080 --> 00:31:49,280
Speaker 1: I do think that it's like that is like a

562
00:31:50,720 --> 00:31:54,920
Speaker 1: an ethics thing, Like no one knows what preprint means,

563
00:31:55,320 --> 00:31:57,800
Speaker 1: so it's like you have to make I I wish

564
00:31:57,880 --> 00:32:01,000
Speaker 1: that that was made clearer to I don't know. I

565
00:32:01,040 --> 00:32:03,960
Speaker 1: don't know what I'm saying. It's really like I understand

566
00:32:04,000 --> 00:32:06,080
Speaker 1: that if you're a scientist, you know what a preprint means,

567
00:32:06,120 --> 00:32:08,360
Speaker 1: and you know that this cannot be taken at face value.

568
00:32:08,440 --> 00:32:12,360
Speaker 1: This is preliminary ship. Uh, but I feel like you

569
00:32:12,440 --> 00:32:15,760
Speaker 1: need to make that as readily apparent to the layman

570
00:32:15,960 --> 00:32:22,280
Speaker 1: as possible. Yeah. Um, And I don't know. It's so

571
00:32:22,960 --> 00:32:27,040
Speaker 1: let's talk about that Surgis Fear study. Sokay, before we

572
00:32:27,120 --> 00:32:29,200
Speaker 1: talk about that, I do I want to talk about

573
00:32:29,240 --> 00:32:31,800
Speaker 1: Surgius Fear a little bit because they've been involved in

574
00:32:32,000 --> 00:32:35,520
Speaker 1: a controversy over the last medicine that wasn't really a

575
00:32:35,560 --> 00:32:38,640
Speaker 1: medicine that went viral over COVID nineteen, which of course

576
00:32:38,800 --> 00:32:42,920
Speaker 1: is hydroxy clerk wine. Now, if you've forgotten, hydroxychlork wine

577
00:32:42,960 --> 00:32:45,360
Speaker 1: was a medicine that doctors briefly thought, based on some

578
00:32:45,480 --> 00:32:49,760
Speaker 1: early studies, might have efficacy in treating COVID nineteen. Those

579
00:32:49,840 --> 00:32:52,160
Speaker 1: early studies, while they were still trying to figure out

580
00:32:52,160 --> 00:32:54,320
Speaker 1: if it actually did have efficacy, were turned into a

581
00:32:54,440 --> 00:32:57,800
Speaker 1: magical cure, all because Trump started tweeting about them. He

582
00:32:57,960 --> 00:32:59,920
Speaker 1: was desperate to open the country back up and the

583
00:33:00,000 --> 00:33:02,080
Speaker 1: get the economy back on track in time for the election.

584
00:33:02,400 --> 00:33:05,320
Speaker 1: Several people died trying to treat themselves with hydroxy chloroquine

585
00:33:05,400 --> 00:33:09,200
Speaker 1: or drugs they thought were hydroxychloroquine. All the controversy over

586
00:33:09,280 --> 00:33:12,640
Speaker 1: this drug obscured the fact that serious scientists were actually

587
00:33:12,680 --> 00:33:15,040
Speaker 1: trying to understand if it might be useful for COVID.

588
00:33:15,440 --> 00:33:18,880
Speaker 1: In mid May, the Lancet published an article suggesting that

589
00:33:19,000 --> 00:33:22,280
Speaker 1: it was dangerous for patients with COVID to take hydroxy clorquin.

590
00:33:22,760 --> 00:33:26,000
Speaker 1: This study was almost immediately retracted because the authors were

591
00:33:26,080 --> 00:33:29,520
Speaker 1: unable to independently verify their data set, which had come

592
00:33:29,600 --> 00:33:33,400
Speaker 1: from a large proprietary collection of electronic health records analyzed

593
00:33:33,440 --> 00:33:36,280
Speaker 1: by Surgis Spear. So Surgis Spear had put together these

594
00:33:36,280 --> 00:33:38,480
Speaker 1: health records that they were using to make claims that

595
00:33:38,600 --> 00:33:42,160
Speaker 1: hydroxy clorquin was dangerous for certain patients. But when they

596
00:33:42,240 --> 00:33:45,560
Speaker 1: attempted to verify the data set, Surgis Spear said, we

597
00:33:45,680 --> 00:33:48,920
Speaker 1: can't show you the health records. We can't actually show

598
00:33:48,960 --> 00:33:52,040
Speaker 1: you the records themselves, which like to study being retracted

599
00:33:52,040 --> 00:33:55,960
Speaker 1: because they can't verify it. Yeah, now it might not

600
00:33:56,040 --> 00:33:58,200
Speaker 1: seem like a problem because again, as we now know,

601
00:33:58,320 --> 00:34:01,600
Speaker 1: hydroxychlorkquin is not helpful and treating COVID nineteen. So the

602
00:34:01,680 --> 00:34:03,960
Speaker 1: facture I mean, which is like luck of the job.

603
00:34:04,120 --> 00:34:07,760
Speaker 1: But that's so that's they can get that far into

604
00:34:07,840 --> 00:34:10,640
Speaker 1: publishing something because they're like, oh, I don't know, but

605
00:34:12,440 --> 00:34:15,440
Speaker 1: it's not even really luck of the draw because that

606
00:34:16,080 --> 00:34:19,719
Speaker 1: thing doesn't seem to have been true. Um, And when

607
00:34:19,800 --> 00:34:23,200
Speaker 1: the study got retracted, that just fueled paranoia that there

608
00:34:23,280 --> 00:34:26,719
Speaker 1: was a conspiracy to trick people out of taking hydroxy clarquine.

609
00:34:27,160 --> 00:34:30,919
Speaker 1: The next month, June, another paper was retracted, this time

610
00:34:31,000 --> 00:34:34,080
Speaker 1: from the New England Journal of Medicine, due to unverifiable

611
00:34:34,200 --> 00:34:36,800
Speaker 1: data from Surgio sphere. That study had found that a

612
00:34:36,920 --> 00:34:40,240
Speaker 1: variety of heart of heart medications had no safety concerns

613
00:34:40,280 --> 00:34:43,440
Speaker 1: when administered to COVID patients. The fact that these papers

614
00:34:43,480 --> 00:34:46,399
Speaker 1: were being retracted after many doctors had taken action based

615
00:34:46,440 --> 00:34:48,759
Speaker 1: on their findings. Was disastrous in the midst of an

616
00:34:48,800 --> 00:34:54,600
Speaker 1: already chaotic time. I encourage. An Australian bioethicist called it catastrophic. Quote.

617
00:34:54,920 --> 00:34:57,640
Speaker 1: It is problematic for their journals involved, It is problematic

618
00:34:57,719 --> 00:35:00,920
Speaker 1: for the integrity of science, It is probably matic from medicine,

619
00:35:00,960 --> 00:35:03,440
Speaker 1: and it is problematic for the notion of clinical trials

620
00:35:03,480 --> 00:35:07,600
Speaker 1: and evidence generation. This right up from Nature explains exactly

621
00:35:07,680 --> 00:35:12,160
Speaker 1: why Surgi Sphear's data was problematic. Quote. Both papers relied

622
00:35:12,200 --> 00:35:16,000
Speaker 1: on propriety proprietary data analyzed from electronic health records that

623
00:35:16,040 --> 00:35:18,680
Speaker 1: were apparently gathered from hundreds of hospitals around the world

624
00:35:18,719 --> 00:35:22,160
Speaker 1: by Surgi Sphere, but after critics raised questions about the studies,

625
00:35:22,200 --> 00:35:24,480
Speaker 1: the firm did not make its raw data available to

626
00:35:24,560 --> 00:35:27,920
Speaker 1: third party auditors for validation. According to the attraction notice

627
00:35:27,960 --> 00:35:30,680
Speaker 1: in the Lancet, Surgi Sphere was concerned that transferring the

628
00:35:30,760 --> 00:35:34,680
Speaker 1: data would violate client agreements and confidentiality requirements. Since we

629
00:35:34,760 --> 00:35:37,000
Speaker 1: do not have the ability to verify the primary data

630
00:35:37,120 --> 00:35:39,800
Speaker 1: or primary data source, I no longer have confidence in

631
00:35:39,840 --> 00:35:42,720
Speaker 1: the in the origination or and veracity of the data,

632
00:35:43,040 --> 00:35:45,719
Speaker 1: nor the findings they have led to, said mandep mea

633
00:35:46,280 --> 00:35:49,600
Speaker 1: cardiologist at Brigham and Women's Hospital in Boston, Massachusetts, who

634
00:35:49,640 --> 00:35:53,880
Speaker 1: was the lead author on both studies. So this is

635
00:35:55,920 --> 00:36:00,200
Speaker 1: and again with SURGEI sphere, there's something going on here

636
00:36:00,280 --> 00:36:02,520
Speaker 1: and I don't know what it is with these guys.

637
00:36:03,200 --> 00:36:06,920
Speaker 1: It's it's do you have any inkling of it? Just

638
00:36:07,000 --> 00:36:08,800
Speaker 1: sounds like the sort of thing where it's like, what

639
00:36:09,600 --> 00:36:14,800
Speaker 1: is the end game for doing that? It may be

640
00:36:14,920 --> 00:36:18,520
Speaker 1: as simple as they're just kind of a shady company,

641
00:36:18,920 --> 00:36:24,040
Speaker 1: um who's not very good at who was trying like

642
00:36:24,440 --> 00:36:26,919
Speaker 1: that there They were trying to like make a quick

643
00:36:27,000 --> 00:36:32,360
Speaker 1: buck providing these records to research scientists, but um weren't

644
00:36:32,400 --> 00:36:36,160
Speaker 1: actually able to give the scientists as much information as

645
00:36:36,200 --> 00:36:37,960
Speaker 1: they would need to be able to use that kind

646
00:36:38,000 --> 00:36:44,839
Speaker 1: of stuff. UM short sighted, Like, yeah, that sounds very bizarre. Yeah,

647
00:36:44,960 --> 00:36:46,600
Speaker 1: and it's it's a bunch of ships like that and

648
00:36:46,680 --> 00:36:49,040
Speaker 1: it's coming in like you're getting like one of the

649
00:36:49,120 --> 00:36:54,520
Speaker 1: problems with this is that, um, they they approve a

650
00:36:54,640 --> 00:36:59,080
Speaker 1: study like or sorry they so the when the hydroxy

651
00:36:59,120 --> 00:37:02,279
Speaker 1: clorquin article comes out saying that it's dangerous to give

652
00:37:02,360 --> 00:37:04,560
Speaker 1: to certain patients, they stop a bunch of studies to

653
00:37:04,680 --> 00:37:07,680
Speaker 1: trying to determine whether or not hydroxy workin works, and

654
00:37:07,760 --> 00:37:11,400
Speaker 1: then they have to restart those studies later after it's retracted,

655
00:37:11,719 --> 00:37:13,840
Speaker 1: which slows down the period of time after which we

656
00:37:13,920 --> 00:37:17,200
Speaker 1: get concrete evidence that it doesn't work. So again, even

657
00:37:17,280 --> 00:37:19,960
Speaker 1: though like it might not seem like that's a bad saying,

658
00:37:20,000 --> 00:37:22,880
Speaker 1: it actually slows down the process of figuring out that

659
00:37:22,960 --> 00:37:25,400
Speaker 1: hydroxy quorkin doesn't work. It's all part of this problem.

660
00:37:26,040 --> 00:37:29,320
Speaker 1: Um that Yeah, that makes total sense because I'm so

661
00:37:29,440 --> 00:37:31,719
Speaker 1: I'm so naive in these areas and I'm like, wait

662
00:37:32,520 --> 00:37:37,799
Speaker 1: that wood fuck things up. Okay, Yeah, I love it's

663
00:37:37,920 --> 00:37:40,520
Speaker 1: just bad. Now. One of the co authors of both

664
00:37:40,640 --> 00:37:44,600
Speaker 1: retracted studies was a guy named Sapon Decide, and he's

665
00:37:44,640 --> 00:37:48,000
Speaker 1: the founder of Surgei Sphere, so he's founds the company

666
00:37:48,120 --> 00:37:50,360
Speaker 1: and is also one of the authors of both of

667
00:37:50,400 --> 00:37:54,200
Speaker 1: the studies that get retracted. Um. And while his co

668
00:37:54,360 --> 00:37:56,200
Speaker 1: authors kind of all come out and say, hey, we're

669
00:37:56,400 --> 00:37:58,560
Speaker 1: were we no longer stand by these studies because of

670
00:37:58,640 --> 00:38:01,399
Speaker 1: issues with the data, he's notely quiet. For the most part.

671
00:38:01,440 --> 00:38:03,320
Speaker 1: I think he agrees to retract one of them and

672
00:38:03,360 --> 00:38:06,560
Speaker 1: not the other. Now and two thousand and one or

673
00:38:06,600 --> 00:38:10,520
Speaker 1: twenty one. Sapon Decide was the co author of another

674
00:38:10,640 --> 00:38:14,160
Speaker 1: study using data from his company, surge Sphere, which claimed

675
00:38:14,200 --> 00:38:17,080
Speaker 1: to find a large reduction in COVID mortality when patients

676
00:38:17,080 --> 00:38:20,600
Speaker 1: were given iver mecten. It was first published to the

677
00:38:20,680 --> 00:38:24,840
Speaker 1: Social Sciences preprint server SSR in on April six and

678
00:38:24,920 --> 00:38:28,080
Speaker 1: a second version was posted on April nineteenth, And this

679
00:38:28,320 --> 00:38:30,839
Speaker 1: is what caused PERU to add iver mecton to their

680
00:38:30,960 --> 00:38:36,240
Speaker 1: national standards of care. So this guy, whose record couldn't

681
00:38:36,280 --> 00:38:41,880
Speaker 1: be shadier visa v COVID nineteen studies, puts out another preprint,

682
00:38:42,239 --> 00:38:45,919
Speaker 1: so not peer reviewed, not a finished thing on a server,

683
00:38:46,400 --> 00:38:50,080
Speaker 1: because it immediately shows like, look, COVID iver mecton reduces

684
00:38:50,160 --> 00:38:54,160
Speaker 1: COVID nineteen deaths and whole nations start taking action based

685
00:38:54,200 --> 00:38:58,839
Speaker 1: on this. Now that is so can't they like I'm right,

686
00:38:58,920 --> 00:39:02,120
Speaker 1: I'm like trying to it. They just put his credibility on.

687
00:39:02,600 --> 00:39:04,759
Speaker 1: I mean he doesn't have any credibility obviously, but just like,

688
00:39:04,840 --> 00:39:09,279
Speaker 1: can how can you continue to publish preprints when your

689
00:39:09,480 --> 00:39:20,160
Speaker 1: track record is that horrific? Like how how? Yeah? That's why? Fuck? Okay,

690
00:39:20,400 --> 00:39:23,120
Speaker 1: So so that preprint comes out and that that is

691
00:39:23,200 --> 00:39:29,279
Speaker 1: what like result in ivermectin taking off. Yeah, that's what

692
00:39:29,440 --> 00:39:31,560
Speaker 1: results in it taking off In Latin America. The f

693
00:39:31,719 --> 00:39:33,279
Speaker 1: l c c C, I think, has much more of

694
00:39:33,320 --> 00:39:35,000
Speaker 1: a job of the tape. But this this feeds into

695
00:39:35,040 --> 00:39:37,400
Speaker 1: that too because it's one of the studies that they're siting.

696
00:39:38,080 --> 00:39:42,480
Speaker 1: So one of that studies authors again, Sapondasi has co

697
00:39:42,640 --> 00:39:45,400
Speaker 1: authors on these studies who are more credible people, and

698
00:39:45,760 --> 00:39:48,320
Speaker 1: one of the studies co authors pulls it from the

699
00:39:48,440 --> 00:39:51,759
Speaker 1: pre print server because, as he told Nature, he did

700
00:39:51,800 --> 00:39:54,080
Speaker 1: not feel it was ready for pure review. So it

701
00:39:54,200 --> 00:39:57,600
Speaker 1: does get pulled, but the damage is done. By that point,

702
00:39:57,680 --> 00:40:00,200
Speaker 1: he's already convinced the Peruvian government to add it to

703
00:40:00,239 --> 00:40:04,520
Speaker 1: their official like COVID protocol, and Bolivia followed soon after. Now,

704
00:40:04,640 --> 00:40:07,640
Speaker 1: when the study seems like the pattern with this, right,

705
00:40:07,760 --> 00:40:09,879
Speaker 1: it's just like you put something out, you say, oh, sorry,

706
00:40:09,960 --> 00:40:12,120
Speaker 1: never mind, that information is terrible, but it's too late

707
00:40:12,200 --> 00:40:17,000
Speaker 1: because the information has already had consequence. There's again when

708
00:40:17,040 --> 00:40:19,520
Speaker 1: you look at like the way the disinformation spreads, it's

709
00:40:19,520 --> 00:40:22,960
Speaker 1: a lot like how COVID spreads, Like you have, they're

710
00:40:22,960 --> 00:40:26,719
Speaker 1: both they're both spreading. It's like a person fox up

711
00:40:26,800 --> 00:40:29,440
Speaker 1: and walks into a room without a mask on, not

712
00:40:29,640 --> 00:40:33,640
Speaker 1: realizing he's been exposed, and he might realize an hour later,

713
00:40:33,760 --> 00:40:35,440
Speaker 1: but by that point he's already passed it on to

714
00:40:35,520 --> 00:40:37,719
Speaker 1: four people who then all go to the grocery store whatever.

715
00:40:37,840 --> 00:40:41,480
Speaker 1: Like it's it's the same way with disinformation. It spreads

716
00:40:41,640 --> 00:40:44,120
Speaker 1: like a virus and it and it's like just too yeah.

717
00:40:44,200 --> 00:40:47,640
Speaker 1: So it just takes like one bad actor intentionally doing

718
00:40:47,719 --> 00:40:51,400
Speaker 1: it to Jesus chrisis. And I think it's often a

719
00:40:51,520 --> 00:40:54,920
Speaker 1: mix of bad actors and people who are acting in

720
00:40:55,040 --> 00:41:00,600
Speaker 1: good faith but aren't quite careful enough. Um now, So

721
00:41:01,080 --> 00:41:04,400
Speaker 1: the good news is that PERUME removes iver mectin from

722
00:41:04,400 --> 00:41:06,960
Speaker 1: their treatment guidelines as soon as the study gets pulled.

723
00:41:07,040 --> 00:41:09,520
Speaker 1: But by that point other South American nations have started

724
00:41:09,600 --> 00:41:12,200
Speaker 1: using it and they don't all stop. And again, even

725
00:41:12,239 --> 00:41:15,080
Speaker 1: outside of that, regardless of what the state health authorities

726
00:41:15,080 --> 00:41:18,279
Speaker 1: are saying, people are now taking it in mass right. So,

727
00:41:18,680 --> 00:41:21,800
Speaker 1: back in January of one, the n i H, the

728
00:41:21,880 --> 00:41:24,320
Speaker 1: National Institutes of Health in the United States had changed

729
00:41:24,360 --> 00:41:26,960
Speaker 1: its guidance on iver mectin for the COVID treatment from

730
00:41:27,040 --> 00:41:31,319
Speaker 1: against to neither for nor against. So there's enough data.

731
00:41:31,480 --> 00:41:35,520
Speaker 1: By January the sayre not against this, and we're hedging

732
00:41:35,880 --> 00:41:40,400
Speaker 1: it's complicated. Yeah, exactly, Okay, got it. Now, in a

733
00:41:40,520 --> 00:41:43,840
Speaker 1: reasonable world, this would not have counted as a positive endorsement.

734
00:41:44,000 --> 00:41:46,560
Speaker 1: But we don't live in a reasonable world. The NIH

735
00:41:46,760 --> 00:41:49,800
Speaker 1: made this change after Dr Corey, from the fl C

736
00:41:50,000 --> 00:41:53,120
Speaker 1: c C and w H O consultant Dr Andrew Hill,

737
00:41:53,280 --> 00:41:56,800
Speaker 1: presented data to the n i H Treatments Guidelines Panel.

738
00:41:57,239 --> 00:42:00,279
Speaker 1: That same month, Dr Corey released a study with the

739
00:42:00,440 --> 00:42:02,680
Speaker 1: f l C c C co founders and several other

740
00:42:02,800 --> 00:42:06,000
Speaker 1: doctors that they believed would convince the CDC and FDA

741
00:42:06,320 --> 00:42:10,120
Speaker 1: to approve iver mect in for use against COVID. Now,

742
00:42:10,560 --> 00:42:13,759
Speaker 1: by this point, doctor Corey had become convinced that iver

743
00:42:13,920 --> 00:42:15,960
Speaker 1: met in was a bona fide wonder drug, as he

744
00:42:16,080 --> 00:42:18,920
Speaker 1: told the Senate, but the people he asked to publish

745
00:42:19,000 --> 00:42:20,840
Speaker 1: his study, the study that he thought was going to

746
00:42:20,880 --> 00:42:24,239
Speaker 1: convince the FDA to approve it for COVID, we're less convinced.

747
00:42:24,960 --> 00:42:29,799
Speaker 1: Frontiers is an open access platform for peer reviewed science journalism,

748
00:42:30,120 --> 00:42:33,120
Speaker 1: and they investigated the integrity of the study and announced

749
00:42:33,200 --> 00:42:35,800
Speaker 1: on March second that they were rejecting the article for

750
00:42:36,080 --> 00:42:39,760
Speaker 1: quote a series of strong unsupported claims based on studies

751
00:42:39,800 --> 00:42:43,120
Speaker 1: with insufficient statistical significance and at times without the use

752
00:42:43,200 --> 00:42:46,200
Speaker 1: of control groups. Oh my god, this guy is going

753
00:42:46,239 --> 00:42:49,480
Speaker 1: to have to start publishing in like Highlights magazine. This

754
00:42:49,719 --> 00:42:53,359
Speaker 1: is so ridiculous. Now, I'm not a scientist, Jamie, I'm

755
00:42:53,400 --> 00:42:57,320
Speaker 1: in fact legally the opposite, um, but I know that

756
00:42:57,480 --> 00:43:00,680
Speaker 1: control groups are important. If you want to know if

757
00:43:00,719 --> 00:43:02,759
Speaker 1: the thing does something, you need a group of people

758
00:43:02,800 --> 00:43:08,120
Speaker 1: who aren't doing the thing and movies before they can

759
00:43:08,200 --> 00:43:12,200
Speaker 1: come out much less fucking pharmaceutical like. That's absolutely yeah.

760
00:43:13,360 --> 00:43:16,959
Speaker 1: So by this point, vaccines were increasingly available in mass

761
00:43:17,040 --> 00:43:20,200
Speaker 1: around the United States. In December, it had made sense

762
00:43:20,280 --> 00:43:23,560
Speaker 1: that iver Mecton had been on the FLCCCS protocol because

763
00:43:24,040 --> 00:43:27,160
Speaker 1: kind of a desperate time. But by March, iver Mecton

764
00:43:27,280 --> 00:43:29,719
Speaker 1: is still part of their protocol, but none of the

765
00:43:29,840 --> 00:43:33,239
Speaker 1: vaccines had been added to their recommended preventative protocol. So

766
00:43:33,400 --> 00:43:38,280
Speaker 1: this is the point where they're very clearly doing something shady. Yeah, exactly,

767
00:43:38,800 --> 00:43:42,359
Speaker 1: fucking December, people can't get vaccines. There's evidence iver Metin

768
00:43:42,680 --> 00:43:46,440
Speaker 1: might help. It's debatable whether or not it's responsible to

769
00:43:46,520 --> 00:43:50,759
Speaker 1: put it on there, but still completely but there's an

770
00:43:50,960 --> 00:43:55,440
Speaker 1: ument more sense to make attempt to make that argument prevactive.

771
00:43:55,480 --> 00:43:59,120
Speaker 1: By March, motherfucker's are walking into their cvs and getting

772
00:43:59,200 --> 00:44:01,960
Speaker 1: vaccinated and they still haven't added that to their protocol.

773
00:44:02,040 --> 00:44:03,839
Speaker 1: But the horse paste, I mean again, they're not telling

774
00:44:03,880 --> 00:44:05,279
Speaker 1: people to take the horse pace, They're telling people to

775
00:44:05,320 --> 00:44:06,960
Speaker 1: get it prescribed. But whatever, I'm gonna call it horse

776
00:44:07,000 --> 00:44:11,520
Speaker 1: paste sometimes. So Dr Corey also grew more combat combative

777
00:44:11,600 --> 00:44:14,799
Speaker 1: from this point forward, telling the Huffington's Post quote when

778
00:44:14,880 --> 00:44:17,240
Speaker 1: I came out and told the world that cortico steroids

779
00:44:17,280 --> 00:44:19,360
Speaker 1: were critical to save lives. I got crushed for that

780
00:44:19,560 --> 00:44:21,600
Speaker 1: until the recovery trial came out and it became the

781
00:44:21,640 --> 00:44:26,719
Speaker 1: standard of care worldwide overnight. Which is true that cortico steroids,

782
00:44:26,880 --> 00:44:29,040
Speaker 1: that use was criticized and they wind up being helpful.

783
00:44:29,120 --> 00:44:32,800
Speaker 1: But also, wasn't your idea? Broheim? Quick? Yeah, like what

784
00:44:33,000 --> 00:44:35,120
Speaker 1: you Is that actually his voice? Or is that just

785
00:44:35,360 --> 00:44:38,760
Speaker 1: you just made him Ben Shapiro. Everyone's been Shapiro, Sophia.

786
00:44:39,040 --> 00:44:40,560
Speaker 1: It was about to say, like, what is it? I

787
00:44:40,719 --> 00:44:42,399
Speaker 1: was like, do you just wanted to sound like a dork?

788
00:44:42,600 --> 00:44:45,600
Speaker 1: And then I found out that was your Ben Shapiro voice? Okay,

789
00:44:45,719 --> 00:44:49,959
Speaker 1: that all tracks. That's 's just float probably right, Yeah,

790
00:44:50,400 --> 00:44:52,440
Speaker 1: if I hate him, there, Ben Shapiro, that's the way

791
00:44:52,480 --> 00:44:57,160
Speaker 1: it works. Again. I'm just like, what is the end game?

792
00:44:58,280 --> 00:45:03,160
Speaker 1: There's no endgame, Jamie. It's Joker Ship. I hate it

793
00:45:03,320 --> 00:45:06,520
Speaker 1: is Joker Ship. It is Joker Ship. It's it's and

794
00:45:06,640 --> 00:45:09,759
Speaker 1: you know what's Joaquin Phoenix got to say about any

795
00:45:09,800 --> 00:45:11,880
Speaker 1: of this. That's what I want to know, Jamie. I

796
00:45:11,920 --> 00:45:14,560
Speaker 1: don't know. He's like five six. I can't hear him.

797
00:45:14,840 --> 00:45:18,239
Speaker 1: Oh okay, so I forgot your You're a you're a

798
00:45:18,880 --> 00:45:25,160
Speaker 1: height chauvinist. So the other thing about cortico steroids, well,

799
00:45:25,160 --> 00:45:27,400
Speaker 1: he's right that people were like, I don't think this

800
00:45:27,560 --> 00:45:29,960
Speaker 1: is a good idea, and we're proven wrong when the

801
00:45:30,080 --> 00:45:34,080
Speaker 1: FLCCC embraced cortico steroids. Cortico steroids were also very quickly

802
00:45:34,120 --> 00:45:38,640
Speaker 1: shown via extremely reputable studies to be useful in COVID treatments, right,

803
00:45:39,160 --> 00:45:43,279
Speaker 1: um it, it's actual science backed it up. And the

804
00:45:43,400 --> 00:45:46,880
Speaker 1: same unequivocal evidence did not come out for iver mecton.

805
00:45:47,600 --> 00:45:52,279
Speaker 1: Well we start to get right, yeah at this point. Yeah,

806
00:45:52,480 --> 00:45:56,840
Speaker 1: and and so we have not especially by March. Again,

807
00:45:56,920 --> 00:45:59,279
Speaker 1: it's still a mix of small studies that shows not

808
00:45:59,400 --> 00:46:01,439
Speaker 1: all of which suggests that it works, some of which

809
00:46:01,440 --> 00:46:06,800
Speaker 1: are shady, whereas by March there's fucking excellent data that

810
00:46:06,880 --> 00:46:11,120
Speaker 1: the vaccines are very effective. Um so it's not the

811
00:46:11,280 --> 00:46:13,640
Speaker 1: same thing, you know, it just isn't. He's trying to

812
00:46:13,719 --> 00:46:17,480
Speaker 1: he's trying to make that that claim because the it's

813
00:46:17,560 --> 00:46:20,840
Speaker 1: it's his organizations claim to fame. But like, it's not

814
00:46:21,000 --> 00:46:24,080
Speaker 1: the same situation. There were quickly studies that backed up

815
00:46:24,080 --> 00:46:27,319
Speaker 1: the cortico steroids thing there aren't isn't the same body

816
00:46:27,360 --> 00:46:29,720
Speaker 1: of evidence for ivermectin, And there's a lot of evidence

817
00:46:29,760 --> 00:46:32,239
Speaker 1: for vaccines, and you're not telling people to take vaccines. Yeah,

818
00:46:33,400 --> 00:46:36,759
Speaker 1: it's fucked up. Uh Yeah, this is absolutely fucked up.

819
00:46:37,960 --> 00:46:40,360
Speaker 1: So when he was asked why he's not telling people

820
00:46:40,400 --> 00:46:43,239
Speaker 1: to get vaccinated, Dr Pierre Corey said, most of what

821
00:46:43,400 --> 00:46:45,680
Speaker 1: we feel, and especially me, is that the data on

822
00:46:45,800 --> 00:46:48,960
Speaker 1: vaccines is moving so fast and it's non transparent. I

823
00:46:49,120 --> 00:46:51,799
Speaker 1: just really don't know what to say about these vaccines.

824
00:46:51,880 --> 00:46:53,879
Speaker 1: I just don't feel comfortable with the kind of data

825
00:46:53,920 --> 00:46:57,759
Speaker 1: that we're getting again, the big ivermine. I cannot be

826
00:46:57,880 --> 00:47:01,879
Speaker 1: more specific about this at this time. Yes, the data

827
00:47:01,960 --> 00:47:04,680
Speaker 1: is not transparent enough. What about the fucking Surgis spear

828
00:47:04,719 --> 00:47:08,640
Speaker 1: study showing ivermectin is useful. Things had to get pulled

829
00:47:08,680 --> 00:47:11,000
Speaker 1: because they wouldn't give anyone access to the fucking medical

830
00:47:11,120 --> 00:47:16,000
Speaker 1: data anyway. In February, YouTube pulled two videos from the

831
00:47:16,040 --> 00:47:19,560
Speaker 1: December eight Senate hearing where Dr Corey called it a

832
00:47:19,600 --> 00:47:22,600
Speaker 1: wonder drug. Specifically, they pulled the portions discussing iver mecton

833
00:47:22,640 --> 00:47:26,040
Speaker 1: and this included part of Dr Corey's testimony. Ron Johnson,

834
00:47:26,080 --> 00:47:29,440
Speaker 1: a Republican senator from Wisconsin, immediately took to the pages

835
00:47:29,480 --> 00:47:31,640
Speaker 1: of the Wall Street Journal to author an op ed

836
00:47:31,800 --> 00:47:36,759
Speaker 1: titled YouTube cancels the US Senate. God, every part of

837
00:47:36,840 --> 00:47:40,160
Speaker 1: that sentence is the biggest loser ship I've ever heard

838
00:47:40,200 --> 00:47:46,160
Speaker 1: of my night. Absolute virgin stuff, right Jesus, Yeah yeah

839
00:47:47,960 --> 00:47:52,040
Speaker 1: so quote and this is from Ron Johnson. Dr Corey

840
00:47:52,160 --> 00:47:54,319
Speaker 1: is part of a world renowned group of physicians who

841
00:47:54,400 --> 00:47:57,960
Speaker 1: developed a groundbreaking use of cortico steroids to treat hospitalized

842
00:47:58,000 --> 00:48:00,799
Speaker 1: COVID patients. His testimony at a May Senate hearing helped

843
00:48:00,880 --> 00:48:05,040
Speaker 1: doctors rethink treatment protocols and saved lives. At the December hearing,

844
00:48:05,080 --> 00:48:07,839
Speaker 1: he presented evidence regarding the use of ivermectin a cheap

845
00:48:07,880 --> 00:48:10,680
Speaker 1: and widely available drug that treats tropical diseases caused by

846
00:48:10,719 --> 00:48:13,680
Speaker 1: parasites for prevention an early treatment of COVID nineteen. He

847
00:48:13,800 --> 00:48:16,520
Speaker 1: described a just published study from Argentina in which about

848
00:48:16,560 --> 00:48:19,720
Speaker 1: eight hundred healthcare workers received ivermectin and four hundred didn't.

849
00:48:19,960 --> 00:48:22,799
Speaker 1: None of the eight hundred contracted COVID nineteen fifty eight

850
00:48:22,880 --> 00:48:27,160
Speaker 1: percent of the four hundred did. So here's the thing

851
00:48:27,239 --> 00:48:30,200
Speaker 1: about that. Here's the thing about makes you think what

852
00:48:30,440 --> 00:48:32,600
Speaker 1: Ron Johnson said, you're telling me there's gonna be holes

853
00:48:32,640 --> 00:48:35,240
Speaker 1: in this. This is the one that, like, just today

854
00:48:35,680 --> 00:48:40,839
Speaker 1: there's a great BuzzFeed news article about that Argentinean study, UM,

855
00:48:41,200 --> 00:48:43,880
Speaker 1: which is super inconsistent. One of the problems with it

856
00:48:44,080 --> 00:48:46,600
Speaker 1: is that depending on like where you read, like what

857
00:48:46,760 --> 00:48:48,520
Speaker 1: part of the study you read, it gives you different

858
00:48:48,640 --> 00:48:50,680
Speaker 1: numbers of how many people were actually part of the

859
00:48:50,760 --> 00:48:55,000
Speaker 1: test group and control group. UM. Like it's it's it's

860
00:48:55,080 --> 00:48:58,760
Speaker 1: just not a well conducted study, and there's actually debate,

861
00:48:59,239 --> 00:49:02,200
Speaker 1: there's actually a serious question as to whether or not

862
00:49:02,600 --> 00:49:08,759
Speaker 1: the study was conducted at all. UM. So, again, this

863
00:49:08,920 --> 00:49:10,759
Speaker 1: just came out, So I'm going to scroll down to

864
00:49:11,440 --> 00:49:17,000
Speaker 1: the relevant point here. UM. Yeah. Meanwhile, the clinical trial

865
00:49:17,120 --> 00:49:20,440
Speaker 1: database stated stated there were two participants, but other things

866
00:49:20,480 --> 00:49:22,640
Speaker 1: didn't add up. It said the control group had seventy

867
00:49:22,680 --> 00:49:24,640
Speaker 1: two women and twenty six men, even though the paper

868
00:49:24,719 --> 00:49:27,360
Speaker 1: said fifty one women and forty eight men. The ages

869
00:49:27,400 --> 00:49:30,759
Speaker 1: also seemed mathematically improbable. The paper states that nearly se

870
00:49:31,440 --> 00:49:34,680
Speaker 1: participants taking the therapy were under age forty. Despite this,

871
00:49:34,840 --> 00:49:37,279
Speaker 1: the clinical trial website states that the median age, the

872
00:49:37,320 --> 00:49:39,399
Speaker 1: age at the midpoint of the group was forty two.

873
00:49:40,000 --> 00:49:42,920
Speaker 1: Those might have been errors. Carvallo conceded in the interview

874
00:49:42,960 --> 00:49:45,359
Speaker 1: which was which is one of the study authors, which

875
00:49:45,400 --> 00:49:49,640
Speaker 1: was largely conducted large errors. We are not a statistical people,

876
00:49:49,760 --> 00:49:52,399
Speaker 1: he said. We are not statistical people, he said, Which

877
00:49:52,400 --> 00:49:54,480
Speaker 1: is like, if you're doing a study, you should be

878
00:49:54,960 --> 00:49:57,719
Speaker 1: someone in the study should be a statistical person because

879
00:49:57,760 --> 00:49:59,840
Speaker 1: you're using statistics to try to show that the medicine

880
00:49:59,840 --> 00:50:06,880
Speaker 1: where um, yes, it's wow, okay, okay, So this is

881
00:50:06,960 --> 00:50:11,080
Speaker 1: just a fucking disaster. They're doing a terrible job at

882
00:50:11,200 --> 00:50:17,200
Speaker 1: like even pr cleanup is just like nonsense, it's just parts. Yeah,

883
00:50:17,360 --> 00:50:21,680
Speaker 1: and it's the journal charges uh, like the BuzzFeed found

884
00:50:21,719 --> 00:50:24,319
Speaker 1: that the journal, which is a very new journal UM

885
00:50:24,600 --> 00:50:27,960
Speaker 1: charged two thousand dollars almost to publish the article. UM,

886
00:50:28,080 --> 00:50:30,520
Speaker 1: and then after BuzzFeed asked about the feed, they dropped

887
00:50:30,600 --> 00:50:35,160
Speaker 1: the price on their website. UM. Carvallo admitted the study

888
00:50:35,200 --> 00:50:38,160
Speaker 1: author admitted that local drugmakers had covered the expense of

889
00:50:38,200 --> 00:50:40,239
Speaker 1: publishing the study and that he and his colleagues had

890
00:50:40,239 --> 00:50:44,080
Speaker 1: paid the rest out of pocket. Um, there's a bunch shocked.

891
00:50:44,640 --> 00:50:50,799
Speaker 1: That's weird here, UM, and it's it isn't weird. Yeah,

892
00:50:51,160 --> 00:50:54,920
Speaker 1: there's it's We're gonna talk about a lot of other uh,

893
00:50:56,600 --> 00:50:59,600
Speaker 1: sketchy shit. And one of the problems is that like

894
00:51:00,080 --> 00:51:02,600
Speaker 1: least one of the hospitals where the study was supposedly

895
00:51:02,640 --> 00:51:06,879
Speaker 1: conducted denies that it was conducted there. Um. So there's

896
00:51:06,880 --> 00:51:10,440
Speaker 1: a lot that's wrong with this study, Like the study

897
00:51:10,480 --> 00:51:13,840
Speaker 1: that Ron Johnson, again is what Dr Corey cited in

898
00:51:13,920 --> 00:51:16,160
Speaker 1: the Senate and was what Ron Johnson points out as like,

899
00:51:16,200 --> 00:51:21,800
Speaker 1: look what he's being canceled for sharing science is toxic.

900
00:51:22,080 --> 00:51:27,160
Speaker 1: Especially that I mean it's like that truly wasn't even

901
00:51:27,200 --> 00:51:29,160
Speaker 1: something that would have occurred to me, that the study

902
00:51:29,239 --> 00:51:33,480
Speaker 1: didn't even happen, Like they couldn't be bothered to create

903
00:51:33,560 --> 00:51:37,440
Speaker 1: a fake fucking study it's not the only time, and

904
00:51:37,560 --> 00:51:40,000
Speaker 1: it seems more likely that, like there were some places

905
00:51:40,040 --> 00:51:41,840
Speaker 1: where they did a study and did it kind of

906
00:51:41,960 --> 00:51:45,040
Speaker 1: poorly because like also large parts of it, like the

907
00:51:45,120 --> 00:51:48,160
Speaker 1: control group stuff was taken on the honor system. Um,

908
00:51:49,440 --> 00:51:55,680
Speaker 1: so you shouldn't do that. This is this is the

909
00:51:55,800 --> 00:52:01,000
Speaker 1: most opposite in terms of steaks comparison. But I've been

910
00:52:01,120 --> 00:52:04,520
Speaker 1: deep in hot dog culture for the last couple of months,

911
00:52:05,000 --> 00:52:08,839
Speaker 1: and there was a study that was released last week

912
00:52:08,920 --> 00:52:10,560
Speaker 1: saying that every time you eat a hot dog you

913
00:52:10,640 --> 00:52:14,479
Speaker 1: lose thirty six minutes of your one human life, which

914
00:52:14,560 --> 00:52:18,600
Speaker 1: is such a wild and bizarre claim to make, and

915
00:52:18,719 --> 00:52:22,200
Speaker 1: if you bear it out, it's very like anyone can

916
00:52:22,280 --> 00:52:26,600
Speaker 1: publish a study and it's and I feel like any

917
00:52:26,680 --> 00:52:30,840
Speaker 1: time and obviously it's like I'm is kind of that

918
00:52:31,000 --> 00:52:34,080
Speaker 1: at the highest level and the highest stakes possible. But

919
00:52:34,160 --> 00:52:38,879
Speaker 1: whenever something gets published, it's just like people are going

920
00:52:38,960 --> 00:52:41,280
Speaker 1: off of the headline of like, well, if a study

921
00:52:41,400 --> 00:52:45,759
Speaker 1: says it, it must be true, and there's very little Uh, well,

922
00:52:45,880 --> 00:52:49,400
Speaker 1: who is conducting the study, what are their qualifications, do

923
00:52:49,640 --> 00:52:53,040
Speaker 1: they have any reason to have ill intent or whatever?

924
00:52:53,160 --> 00:52:56,560
Speaker 1: Like all I have to say this studies bullshit and

925
00:52:56,880 --> 00:52:59,680
Speaker 1: I firmly believe the hot dog thirty six minutes study

926
00:52:59,800 --> 00:53:06,080
Speaker 1: is bullshit because clearly each hot dog takes ninety minutes

927
00:53:06,120 --> 00:53:09,240
Speaker 1: off of your life. Um, if that were true, Robert,

928
00:53:09,239 --> 00:53:12,239
Speaker 1: I would be rocketing backwards in time right now. I

929
00:53:12,280 --> 00:53:17,280
Speaker 1: would be in seventeen something. I would be wearing fucking

930
00:53:17,400 --> 00:53:20,800
Speaker 1: five D petticoats. I don't I don't know where it

931
00:53:20,800 --> 00:53:23,240
Speaker 1: would be. I would not be I would not be alive,

932
00:53:23,320 --> 00:53:27,680
Speaker 1: and I would be transcending dimensions in time. It's just

933
00:53:27,960 --> 00:53:31,800
Speaker 1: I just feel like it's demonstrably untrue. Also, being happy

934
00:53:31,920 --> 00:53:36,280
Speaker 1: makes you live longer, so I very least it evens

935
00:53:36,320 --> 00:53:40,920
Speaker 1: out people happy. Well, it is my potential, it is

936
00:53:41,000 --> 00:53:44,880
Speaker 1: my It is my stance that hot dogs do kill people,

937
00:53:45,239 --> 00:53:48,480
Speaker 1: and that that's not a bad thing because climate change, Baby,

938
00:53:49,200 --> 00:53:54,360
Speaker 1: we got to reduce emissions. Do you like hot dogs, Robert?

939
00:53:54,920 --> 00:53:58,200
Speaker 1: I love hot dogs, Jamie. How what's your weight, what's

940
00:53:58,239 --> 00:54:01,560
Speaker 1: your what's your like? What's your go to? I mean,

941
00:54:02,760 --> 00:54:05,440
Speaker 1: is literally any hot dog and I throw everything on it.

942
00:54:05,840 --> 00:54:08,759
Speaker 1: But the best hot dog I've ever had, Jamie, And

943
00:54:08,920 --> 00:54:10,480
Speaker 1: I guess we can argue as to whether or not

944
00:54:10,520 --> 00:54:12,200
Speaker 1: it's a hot dog. I was in Lisbon and I

945
00:54:12,320 --> 00:54:14,640
Speaker 1: was at this street market and it was the bun

946
00:54:15,120 --> 00:54:17,239
Speaker 1: was black because it had squid ink in it. And

947
00:54:17,320 --> 00:54:19,960
Speaker 1: instead of a hot dog, it was an octopus tentacle

948
00:54:20,360 --> 00:54:22,960
Speaker 1: and there was like some sort of weird creamy salad on.

949
00:54:23,040 --> 00:54:26,959
Speaker 1: It was incredible. It was so fucking tasty. Oh my god.

950
00:54:27,200 --> 00:54:28,759
Speaker 1: So I have to tell you, Robert, and this is

951
00:54:28,800 --> 00:54:30,600
Speaker 1: gonna be really hard to hear. What you ate was

952
00:54:30,680 --> 00:54:32,960
Speaker 1: not a hot dog. It was a piece of an octopus.

953
00:54:33,600 --> 00:54:37,320
Speaker 1: I think it's at that sounds like it was literally

954
00:54:37,360 --> 00:54:39,560
Speaker 1: an amazing day for you. If it's a hot dog,

955
00:54:39,960 --> 00:54:43,040
Speaker 1: it's a hot dog. It's a hot dog. You have

956
00:54:43,239 --> 00:54:47,160
Speaker 1: the goll to to zoom dot you I am tell

957
00:54:47,239 --> 00:54:51,160
Speaker 1: me octopus is hot dog. I cannot believe that you

958
00:54:51,440 --> 00:54:53,879
Speaker 1: can claim to be a hot dog lover and say

959
00:54:53,920 --> 00:54:57,000
Speaker 1: that it is possible to discriminate about what is or

960
00:54:57,080 --> 00:55:01,319
Speaker 1: isn't a hot dog based on the kind of meat involved. Look,

961
00:55:02,200 --> 00:55:06,520
Speaker 1: a hot dog is a mixture of garbage. You can

962
00:55:06,600 --> 00:55:12,520
Speaker 1: do it in ocean trash, but that's one piece of

963
00:55:12,600 --> 00:55:16,319
Speaker 1: ocean trash. You need the different butts of five things

964
00:55:16,360 --> 00:55:20,040
Speaker 1: in there were probably filled with plastic because of the

965
00:55:20,120 --> 00:55:23,320
Speaker 1: post and then vegetarian hot dogs are made out of

966
00:55:23,320 --> 00:55:27,759
Speaker 1: different vegetable trash. So it's like, sorry, I'm going to

967
00:55:27,840 --> 00:55:31,600
Speaker 1: take this debate offline. You listen to these products and services.

968
00:55:33,400 --> 00:55:36,759
Speaker 1: She and I prepare to engage in a traditional traditional

969
00:55:38,360 --> 00:55:42,759
Speaker 1: knife fight of our people. I liked red huts in

970
00:55:42,800 --> 00:55:54,720
Speaker 1: New Jersey, so they're enjoy your products and services. We're back,

971
00:55:55,080 --> 00:55:58,400
Speaker 1: and I'm livid at Jamie lived, but we have to

972
00:55:58,440 --> 00:56:04,440
Speaker 1: put our differences aside. Bleeding to talk about ivermectin the

973
00:56:04,520 --> 00:56:10,040
Speaker 1: hot dog of anti parasitic medications. I mean that's an

974
00:56:10,080 --> 00:56:13,839
Speaker 1: accurate comparison. Hot dogs get cot talks, get bad enough

975
00:56:13,920 --> 00:56:17,560
Speaker 1: rep but you know getting an unfair rep too. It's

976
00:56:17,560 --> 00:56:21,839
Speaker 1: saved a lot of lives before. You know this before yeah,

977
00:56:21,880 --> 00:56:27,359
Speaker 1: before it got before found YouTube. Yeah, we're not canceling ivermected.

978
00:56:28,120 --> 00:56:32,040
Speaker 1: If you get a parasite, please take it. If you

979
00:56:32,160 --> 00:56:35,799
Speaker 1: go into the river and start feeling blind, take some ivermectin.

980
00:56:36,880 --> 00:56:40,239
Speaker 1: But you know that you can't deny it. You can't

981
00:56:40,280 --> 00:56:43,839
Speaker 1: deny it. It's proven. River blindness is just that's going

982
00:56:43,880 --> 00:56:46,080
Speaker 1: to stick with me because I just didn't stay the

983
00:56:46,200 --> 00:56:50,960
Speaker 1: funk away from rivers. Jamie. It's like people in Philadelphia

984
00:56:51,160 --> 00:56:55,560
Speaker 1: so far jumping in the flooded streets. It's like I've

985
00:56:55,640 --> 00:56:58,440
Speaker 1: walked down the street in Philadelphia. I've smelled the sewers.

986
00:56:58,480 --> 00:57:01,280
Speaker 1: You should not be in that water, guy, you really

987
00:57:01,400 --> 00:57:05,759
Speaker 1: should not of Yeah, the subways in New York. It's

988
00:57:05,880 --> 00:57:08,560
Speaker 1: just wow to to be alive at the end of

989
00:57:08,600 --> 00:57:11,799
Speaker 1: the world. It's it's amazing. No fun. It looked way

990
00:57:11,880 --> 00:57:15,239
Speaker 1: more fun in movies, yeah, because it seems like you

991
00:57:15,320 --> 00:57:17,240
Speaker 1: were going to fall deeply in love and then the

992
00:57:17,320 --> 00:57:19,080
Speaker 1: world was going to end. It turns out that's not

993
00:57:19,160 --> 00:57:21,600
Speaker 1: how it goes. And also in the movies, every single

994
00:57:21,680 --> 00:57:23,680
Speaker 1: person doesn't have a U t I. But it turns

995
00:57:23,680 --> 00:57:26,080
Speaker 1: out when the world falls apart, everybody starts getting U

996
00:57:26,160 --> 00:57:29,120
Speaker 1: t I s. I've got a U t I on

997
00:57:29,280 --> 00:57:33,800
Speaker 1: Splash Mountain once. That was my sound t I. Yeah,

998
00:57:33,880 --> 00:57:36,720
Speaker 1: I'm surprised that you don't hear about that more. Every

999
00:57:36,760 --> 00:57:41,080
Speaker 1: time I tell the ant people people should talk about

1000
00:57:41,080 --> 00:57:43,080
Speaker 1: their U t E s, they're very uncomfortable. And I

1001
00:57:43,160 --> 00:57:45,680
Speaker 1: feel like if I knew I've had have you ever

1002
00:57:45,720 --> 00:57:48,040
Speaker 1: had a conversation with someone and after they're like, I

1003
00:57:48,120 --> 00:57:49,880
Speaker 1: had a U t I when we hung out that day,

1004
00:57:49,920 --> 00:57:53,360
Speaker 1: and that's why I was being very bizarre in my behavior.

1005
00:57:53,800 --> 00:57:56,120
Speaker 1: I feel like you should we should just normalize telling

1006
00:57:56,200 --> 00:57:57,600
Speaker 1: each other we have U, T I S. So then

1007
00:57:57,640 --> 00:58:04,040
Speaker 1: if you're being a weird hang, there's context. M we

1008
00:58:04,120 --> 00:58:06,160
Speaker 1: could get like a necklace of some sort or a

1009
00:58:06,280 --> 00:58:15,360
Speaker 1: bracelet like a swinger's party. Yeah, but so um yeah

1010
00:58:18,000 --> 00:58:21,600
Speaker 1: Johnson talked about this Argentinean study is full of ship

1011
00:58:21,800 --> 00:58:27,280
Speaker 1: and an idiot um um and fuck him. I should

1012
00:58:27,280 --> 00:58:32,440
Speaker 1: also note that even even based on the inaccurate uh like,

1013
00:58:32,640 --> 00:58:35,120
Speaker 1: even like the study itself is bad, but even based

1014
00:58:35,160 --> 00:58:37,400
Speaker 1: on what the study said, he got it wrong, like

1015
00:58:37,520 --> 00:58:40,360
Speaker 1: the study claims to have had uh. He claims that

1016
00:58:40,400 --> 00:58:44,120
Speaker 1: the study had eight hundred participants, it had three hundred, um,

1017
00:58:44,360 --> 00:58:46,840
Speaker 1: which means that even based on his own claims, he

1018
00:58:46,960 --> 00:58:50,360
Speaker 1: got the study wrong by a third. Um well, he said,

1019
00:58:50,440 --> 00:58:54,000
Speaker 1: he's not like. I mean, look, these guys aren't stats guys.

1020
00:58:54,320 --> 00:58:58,280
Speaker 1: There's there's science, guys, and science famously doesn't involve numbers

1021
00:58:58,440 --> 00:59:01,600
Speaker 1: or accuracy. So I should also note that there was

1022
00:59:01,680 --> 00:59:04,360
Speaker 1: a follow up study in Argentina or released in July

1023
00:59:05,360 --> 00:59:08,640
Speaker 1: that showed quote no significant effect on preventing the hospitalization

1024
00:59:08,680 --> 00:59:11,360
Speaker 1: of patients with COVID nineteen that goes against the claims

1025
00:59:11,400 --> 00:59:15,600
Speaker 1: of a prophylactic effects. And this is how many demonstrative

1026
00:59:15,600 --> 00:59:19,840
Speaker 1: evidence against this. At this point we haven't even gotten

1027
00:59:19,840 --> 00:59:22,720
Speaker 1: into the worst one. Um. But again it's all part

1028
00:59:22,760 --> 00:59:25,480
Speaker 1: of the same problem where it is not bad and

1029
00:59:25,560 --> 00:59:28,000
Speaker 1: it is fact, in fact, a necessary part of medical

1030
00:59:28,040 --> 00:59:30,520
Speaker 1: science to do a series of small studies into whether

1031
00:59:30,720 --> 00:59:33,320
Speaker 1: something might work before you do larger studies that are

1032
00:59:33,400 --> 00:59:37,640
Speaker 1: more robust. The problem with that is idiots and grifters

1033
00:59:37,760 --> 00:59:40,000
Speaker 1: who will take this study on thirty people that may

1034
00:59:40,120 --> 00:59:43,080
Speaker 1: one day be useful and eventually arriving at a treatment,

1035
00:59:43,360 --> 00:59:46,160
Speaker 1: and instead say, start buying up all of this ship

1036
00:59:46,320 --> 00:59:48,800
Speaker 1: that you can and take it. And if anyone tells

1037
00:59:48,840 --> 00:59:51,560
Speaker 1: you not to, it's not because the science isn't ready yet,

1038
00:59:51,600 --> 00:59:54,400
Speaker 1: it's because they're trying to stop you from taking control

1039
00:59:54,480 --> 00:59:55,960
Speaker 1: of your own health and they don't want you to.

1040
00:59:56,280 --> 00:59:58,040
Speaker 1: They want to but a micro chip in your body

1041
00:59:58,080 --> 01:00:04,320
Speaker 1: and your yeah, it's a threat. Here. Independence listen to

1042
01:00:04,440 --> 01:00:09,880
Speaker 1: me about your healthcare. I did m m A. Anyone

1043
01:00:09,920 --> 01:00:13,880
Speaker 1: who did mm A. There's certain things I will listen

1044
01:00:13,920 --> 01:00:16,440
Speaker 1: to people who did m m A about, like, for example,

1045
01:00:16,600 --> 01:00:18,480
Speaker 1: m m A if Joe Rogan, if I have a

1046
01:00:18,560 --> 01:00:21,240
Speaker 1: problem getting someone in a headlock, and Joe Rogan offers

1047
01:00:21,320 --> 01:00:24,360
Speaker 1: me advice. I will take that advice. Motherfucker's pretty good

1048
01:00:24,400 --> 01:00:27,440
Speaker 1: at that. I'm not going to take Joe Rogan's advice

1049
01:00:27,480 --> 01:00:31,439
Speaker 1: about whether or not vaccines are legitimate. Well, look, i'll

1050
01:00:31,520 --> 01:00:34,000
Speaker 1: meet you. I'll meet you there. If if I needed

1051
01:00:34,040 --> 01:00:36,880
Speaker 1: to learn how to look sweatier than anyone's ever looked

1052
01:00:36,920 --> 01:00:39,240
Speaker 1: in a fully air conditioned room, I would ask Joe

1053
01:00:39,360 --> 01:00:43,400
Speaker 1: Rogan because he has done the hours for that. He's

1054
01:00:43,480 --> 01:00:46,960
Speaker 1: done it for over ten thousand hours. He's he's the

1055
01:00:47,000 --> 01:00:49,960
Speaker 1: best looking sweaty in a small room. He's incredible at

1056
01:00:50,040 --> 01:00:53,919
Speaker 1: it virtue, so he's got the money. It's it's there's

1057
01:00:54,400 --> 01:00:57,600
Speaker 1: it's a fair conditioned thing. Man, Like, what is wrong

1058
01:00:57,640 --> 01:01:02,800
Speaker 1: with you? Anyway? I believe that because the art episodes

1059
01:01:03,400 --> 01:01:06,360
Speaker 1: that first of all, it's performance, right, No, it's but

1060
01:01:06,520 --> 01:01:09,760
Speaker 1: the guest is never sweaty. I think that he's the

1061
01:01:09,840 --> 01:01:12,920
Speaker 1: room is forty two degrees and he's just sweating, sweating,

1062
01:01:12,960 --> 01:01:15,760
Speaker 1: sweatings because of all of the random pills he takes.

1063
01:01:15,840 --> 01:01:19,520
Speaker 1: That looks his brain is under an intense amount of

1064
01:01:19,640 --> 01:01:24,919
Speaker 1: pressure from all of those pills. God, what a loser. Okay,

1065
01:01:25,360 --> 01:01:28,280
Speaker 1: it's amazing. It's amazing that he's the most single, most

1066
01:01:28,400 --> 01:01:32,680
Speaker 1: influential person in global media. Um, and he looks like

1067
01:01:32,800 --> 01:01:36,280
Speaker 1: a stick of salami. He looks like a thumb. Fuck

1068
01:01:36,360 --> 01:01:42,040
Speaker 1: to hot dog again with the hot dog slander. Think

1069
01:01:42,080 --> 01:01:50,080
Speaker 1: they're the same shade of red Jamie, So yeah and again.

1070
01:01:50,240 --> 01:01:52,480
Speaker 1: One of the other problems with this so again. One

1071
01:01:52,520 --> 01:01:54,760
Speaker 1: problem is that you get a bunch of small studies.

1072
01:01:54,840 --> 01:01:57,720
Speaker 1: People will pick and choose and grab studies that really

1073
01:01:57,760 --> 01:02:01,120
Speaker 1: may not be as as because they're not super scientific literate.

1074
01:02:01,560 --> 01:02:03,680
Speaker 1: They may think that that study says more than it does.

1075
01:02:03,720 --> 01:02:05,600
Speaker 1: Another problem is that when you have a bunch of

1076
01:02:05,640 --> 01:02:08,880
Speaker 1: small studies, you might get It's very common you can

1077
01:02:08,920 --> 01:02:11,160
Speaker 1: have five or six small studies that are all good

1078
01:02:11,240 --> 01:02:14,280
Speaker 1: studies and I'll tell you opposite things because they're small.

1079
01:02:14,680 --> 01:02:17,640
Speaker 1: And when you have a small study, minor variables can

1080
01:02:17,760 --> 01:02:20,240
Speaker 1: throw off your results, which is part of why again,

1081
01:02:20,320 --> 01:02:23,760
Speaker 1: science is an iterative process. But the way put blushing works,

1082
01:02:23,800 --> 01:02:25,840
Speaker 1: all the studies are just getting shotguned out into the

1083
01:02:25,880 --> 01:02:28,720
Speaker 1: public sphere. This is not an issue with obscure topics

1084
01:02:28,760 --> 01:02:30,959
Speaker 1: because researchers are the only ones looking at the data

1085
01:02:31,040 --> 01:02:33,800
Speaker 1: and they understand how this stuff actually works. But it's

1086
01:02:33,840 --> 01:02:36,920
Speaker 1: a problem with these epidemics because again there's all these

1087
01:02:36,960 --> 01:02:39,400
Speaker 1: fucking grifters out there looking for alternatives to the deep

1088
01:02:39,440 --> 01:02:42,680
Speaker 1: State vaccine. And then, of course there is the other

1089
01:02:42,760 --> 01:02:45,800
Speaker 1: another issue, which is that not every scientist involved in

1090
01:02:45,880 --> 01:02:48,720
Speaker 1: the research process is acting in good faith. You have

1091
01:02:48,800 --> 01:02:51,480
Speaker 1: guys like doctor to Sigh and Surges Sphere putting out

1092
01:02:51,520 --> 01:02:55,760
Speaker 1: shady data for unclear reasons, but probably with some financial benefit.

1093
01:02:56,200 --> 01:02:58,000
Speaker 1: And then you have people who put up studies and

1094
01:02:58,040 --> 01:03:01,720
Speaker 1: public porpositories that have not been peer reviewed, and they

1095
01:03:01,800 --> 01:03:03,960
Speaker 1: know that most of the public won't know the difference,

1096
01:03:03,960 --> 01:03:06,160
Speaker 1: they'll just see that it's a study. And you have

1097
01:03:06,320 --> 01:03:09,440
Speaker 1: guys like Dr Pierre Corey, who, when he was criticized

1098
01:03:09,480 --> 01:03:12,440
Speaker 1: for his sketchy Senate testimony, said I still stand by it,

1099
01:03:12,520 --> 01:03:14,400
Speaker 1: and I think history will prove it to be true,

1100
01:03:15,000 --> 01:03:20,160
Speaker 1: even though history didn't. So by early nearly all of

1101
01:03:20,240 --> 01:03:22,360
Speaker 1: the studies that purported to show a benefit from iver

1102
01:03:22,480 --> 01:03:26,120
Speaker 1: mectin use were small. There was one hugely influential exception,

1103
01:03:26,520 --> 01:03:29,800
Speaker 1: a November study published by Dr Ahmed el Ghazar of

1104
01:03:29,880 --> 01:03:33,480
Speaker 1: Binja University in Egypt. It claimed to be a randomized

1105
01:03:33,560 --> 01:03:36,240
Speaker 1: control study that had found early iver met in use

1106
01:03:36,360 --> 01:03:39,760
Speaker 1: not only reduced transmission of COVID but reduced mortality by

1107
01:03:39,800 --> 01:03:43,720
Speaker 1: as much as nine If true, this would have been

1108
01:03:44,400 --> 01:03:48,320
Speaker 1: huge world changing news. This would have meant that a cheap,

1109
01:03:48,560 --> 01:03:52,600
Speaker 1: widely available anti parasitic was as effective as the best vaccines.

1110
01:03:53,360 --> 01:03:55,959
Speaker 1: The fact that this study was so large, again there's

1111
01:03:56,200 --> 01:03:58,840
Speaker 1: like four hundred people. I think in this study um

1112
01:03:59,040 --> 01:04:01,400
Speaker 1: had impacts that ripple out far and minde because most

1113
01:04:01,480 --> 01:04:05,080
Speaker 1: of the studies are smaller. In cases like ivermectin, when

1114
01:04:05,120 --> 01:04:07,840
Speaker 1: researchers are analyzing a bunch of far flung little studies

1115
01:04:08,040 --> 01:04:10,280
Speaker 1: to try to determine whether or not something works, they

1116
01:04:10,360 --> 01:04:12,800
Speaker 1: like to bunch all of those studies together and do

1117
01:04:12,960 --> 01:04:16,240
Speaker 1: something called a meta analysis. To explain what a meta

1118
01:04:16,240 --> 01:04:18,280
Speaker 1: analysis is, I'm going to quote from a write up

1119
01:04:18,320 --> 01:04:21,960
Speaker 1: by epidemiologist Giddy and my earrowitz Cats, who again is

1120
01:04:21,960 --> 01:04:27,240
Speaker 1: an epidemiologist and who like analyzes scientific studies for a

1121
01:04:27,320 --> 01:04:30,200
Speaker 1: living uh, and is thus the kind of person you

1122
01:04:30,240 --> 01:04:33,120
Speaker 1: would go to for information about this, as opposed to

1123
01:04:33,160 --> 01:04:37,040
Speaker 1: a random pulmonologist anyway. Quote. To solve the problem of

1124
01:04:37,120 --> 01:04:40,200
Speaker 1: multiple small trials, we conduct things called systematic reviews and

1125
01:04:40,240 --> 01:04:44,080
Speaker 1: meta analyzes. These are scientific aggregations of research that pool

1126
01:04:44,160 --> 01:04:46,000
Speaker 1: all of the known studies on a topic into a

1127
01:04:46,080 --> 01:04:48,960
Speaker 1: single place and then combine them into a statistical model

1128
01:04:49,040 --> 01:04:50,880
Speaker 1: so we can see what the overall effect of a

1129
01:04:50,920 --> 01:04:53,480
Speaker 1: drug might be. Instead of a dozen small studies, we

1130
01:04:53,560 --> 01:04:56,520
Speaker 1: get one big aggregated estimate, which in theory is the

1131
01:04:56,600 --> 01:04:59,120
Speaker 1: final word on whether or not a treatment is effective.

1132
01:05:00,240 --> 01:05:02,800
Speaker 1: The only problem with these analyzes is that if a

1133
01:05:02,920 --> 01:05:05,720
Speaker 1: single study has a large enough number of participants or

1134
01:05:05,760 --> 01:05:09,240
Speaker 1: a huge effect, it can sway the overall trend into

1135
01:05:09,360 --> 01:05:12,680
Speaker 1: something positive, even though on the whole the studies have

1136
01:05:12,800 --> 01:05:16,040
Speaker 1: not found a result. Now, generally this isn't a huge issue,

1137
01:05:16,120 --> 01:05:18,000
Speaker 1: but it does mean that you sometimes have an entire

1138
01:05:18,080 --> 01:05:21,080
Speaker 1: body of literature saying that something works using the gold

1139
01:05:21,120 --> 01:05:24,200
Speaker 1: standard aggregation of many studies that is actually based on

1140
01:05:24,240 --> 01:05:28,760
Speaker 1: the results of a single piece of research. Uh, yeah,

1141
01:05:28,840 --> 01:05:31,480
Speaker 1: you see. And how this could be a problem this

1142
01:05:31,960 --> 01:05:36,160
Speaker 1: I you know, I'm starting to get the picture of

1143
01:05:36,480 --> 01:05:40,000
Speaker 1: how this ship. Uh and what is I mean, it's

1144
01:05:40,360 --> 01:05:44,120
Speaker 1: what is the fucking solution? I don't you know that?

1145
01:05:44,240 --> 01:05:46,440
Speaker 1: That is the thing. The problem is very clear to me.

1146
01:05:46,760 --> 01:05:49,480
Speaker 1: The way that the way that we have the way

1147
01:05:49,520 --> 01:05:53,200
Speaker 1: that medical scientific studies are released and shared, and that

1148
01:05:53,320 --> 01:05:57,320
Speaker 1: this information like it does not work with the way

1149
01:05:57,440 --> 01:06:01,400
Speaker 1: the modern information ecosystem works, right, and that is a

1150
01:06:01,520 --> 01:06:04,840
Speaker 1: problem if you're looking for a solution. I'm not a scientist,

1151
01:06:04,880 --> 01:06:10,240
Speaker 1: I'm not your guy. I am a disinformation study or professionally,

1152
01:06:10,320 --> 01:06:14,000
Speaker 1: and I can tell you where the problem is coming in, right, right,

1153
01:06:14,080 --> 01:06:16,280
Speaker 1: the problem, I mean, the way you just laid it out,

1154
01:06:16,320 --> 01:06:20,960
Speaker 1: the problem is extremely clear, but the actionable solution is

1155
01:06:23,040 --> 01:06:24,680
Speaker 1: not at all. It's a mix of thing. You know.

1156
01:06:24,760 --> 01:06:27,160
Speaker 1: It's not just that this stuff gets published early in

1157
01:06:27,200 --> 01:06:29,200
Speaker 1: people at cherry pick studies. It's also this problem of

1158
01:06:29,280 --> 01:06:31,000
Speaker 1: like some of these studies are sketchy, some of these

1159
01:06:31,000 --> 01:06:33,120
Speaker 1: places allow you to publish things before the period. Like

1160
01:06:33,240 --> 01:06:35,560
Speaker 1: there's a number of problems, but the problems are clear,

1161
01:06:36,000 --> 01:06:39,440
Speaker 1: the solution less so so, and the consequences are extremely

1162
01:06:39,600 --> 01:06:44,120
Speaker 1: clear yea too. And the stakes are extreme, are really high. Okay,

1163
01:06:44,720 --> 01:06:48,640
Speaker 1: So in June, it's just what it feels like to

1164
01:06:48,680 --> 01:06:51,320
Speaker 1: have Joe Rogan's brain. It just feels like really tight,

1165
01:06:51,720 --> 01:06:56,080
Speaker 1: Like how sweaty are you right now? Jamie? I'm I'm

1166
01:06:56,120 --> 01:07:01,560
Speaker 1: sucking drenched and I'm sitting in me freezer. So I

1167
01:07:01,720 --> 01:07:04,280
Speaker 1: feel like I might feel like he feels. Now is

1168
01:07:04,400 --> 01:07:08,479
Speaker 1: your best friend an incredible jiu jitsu expert who also

1169
01:07:08,560 --> 01:07:10,920
Speaker 1: believes the moon landing was fake in the Earth is flat?

1170
01:07:11,160 --> 01:07:13,840
Speaker 1: Because if so, you might actually just be Joe Rogan.

1171
01:07:15,360 --> 01:07:20,000
Speaker 1: Wait a second, that would explain so much of you do.

1172
01:07:20,200 --> 01:07:23,360
Speaker 1: Hang out with Eddie Bravo a lot. So I keep

1173
01:07:23,480 --> 01:07:27,240
Speaker 1: screaming to for comedians to move to Austin and then

1174
01:07:27,280 --> 01:07:29,600
Speaker 1: they hate it and then they leave because it's a

1175
01:07:29,760 --> 01:07:33,800
Speaker 1: terrible place anyway. Um So. In June, the first large

1176
01:07:33,840 --> 01:07:36,440
Speaker 1: meta analysis of iver mectin studies was published in the

1177
01:07:36,480 --> 01:07:40,840
Speaker 1: American Journal of Therapeutics. It found quote moderate certainty evidence

1178
01:07:41,000 --> 01:07:44,160
Speaker 1: finds that large reductions and COVID nineteen deaths are possible

1179
01:07:44,280 --> 01:07:47,200
Speaker 1: using iver mectin. Now that kind of wording and a

1180
01:07:47,320 --> 01:07:52,040
Speaker 1: meta analysis published in a reputable journal had huge reverberations.

1181
01:07:52,320 --> 01:07:54,960
Speaker 1: By the end of June, iver mecton was being discussed

1182
01:07:55,000 --> 01:07:57,760
Speaker 1: on Our Friend Joe Rogan Show in its first ever

1183
01:07:57,960 --> 01:08:01,040
Speaker 1: emergency episode was so importan and he did an emergency

1184
01:08:01,080 --> 01:08:03,720
Speaker 1: is just giving all thoughts a chance from her. I

1185
01:08:03,760 --> 01:08:06,800
Speaker 1: don't know what's wrong with I think every thought a chance.

1186
01:08:07,280 --> 01:08:10,080
Speaker 1: I think it's vacated. He might be. We'll talk about Joe,

1187
01:08:10,160 --> 01:08:13,480
Speaker 1: and we'll talk about Joe in part two. Honestly, YEA.

1188
01:08:14,120 --> 01:08:18,840
Speaker 1: In this emergency episode, Dr Corey sits down Joe Rogan,

1189
01:08:19,120 --> 01:08:20,960
Speaker 1: Dr Pierre Corey of the f l C c C

1190
01:08:21,439 --> 01:08:23,960
Speaker 1: and Brett Weinstein, who will talk about in part two

1191
01:08:24,040 --> 01:08:26,719
Speaker 1: but is a grifter, uh, sit down to talk about

1192
01:08:26,760 --> 01:08:29,800
Speaker 1: how iver mectin is a fucking wonder drug. Now that

1193
01:08:30,000 --> 01:08:34,040
Speaker 1: episode dropped days after that first meta analysis was published.

1194
01:08:34,080 --> 01:08:36,920
Speaker 1: I cannot overstate the influence of having that big meta

1195
01:08:37,000 --> 01:08:40,200
Speaker 1: analysis like played on kind of making this look more

1196
01:08:40,840 --> 01:08:43,920
Speaker 1: like a thing than it really is. Weinstein claimed, quote,

1197
01:08:44,680 --> 01:08:48,120
Speaker 1: the censorship campaign obscuring iver mectin is a prophylactic against

1198
01:08:48,160 --> 01:08:51,000
Speaker 1: stars cove two and as a treatment for COVID nineteen kills.

1199
01:08:51,320 --> 01:08:55,320
Speaker 1: Is it about shareholders in EU as? Now this discussion

1200
01:08:55,400 --> 01:08:58,760
Speaker 1: merged with Rogan's own worries about vaccine passports and whether

1201
01:08:58,920 --> 01:09:02,320
Speaker 1: or not young healthy people needed the vaccine. Ever, Mecton

1202
01:09:02,439 --> 01:09:05,519
Speaker 1: was now built as a replacement to the vaccine, where

1203
01:09:05,560 --> 01:09:08,479
Speaker 1: six months before Dr Corey himself had pushed it as

1204
01:09:08,560 --> 01:09:11,400
Speaker 1: just a stop gap until the vaccine was ready, and

1205
01:09:11,560 --> 01:09:14,920
Speaker 1: for a while that meta analysis, and Dr Elgassar's study

1206
01:09:15,200 --> 01:09:17,920
Speaker 1: gave Dr Corey and other iver mectin advocates a link

1207
01:09:18,040 --> 01:09:20,519
Speaker 1: to stand on. They could point to this massive study

1208
01:09:20,560 --> 01:09:23,640
Speaker 1: and say, hey, why isn't the mainstream media covering this?

1209
01:09:23,840 --> 01:09:25,960
Speaker 1: It must be because I ever, mecton is a generic

1210
01:09:26,080 --> 01:09:28,040
Speaker 1: over the counter drug, and so they're not big farm

1211
01:09:28,160 --> 01:09:31,559
Speaker 1: is not going to make money, so they're hiding it. Now.

1212
01:09:31,880 --> 01:09:34,800
Speaker 1: The reality is that iver Metton was sucking everywhere. It

1213
01:09:34,880 --> 01:09:37,679
Speaker 1: was all over alternative media, like the Joe Rogan podcast,

1214
01:09:37,760 --> 01:09:40,840
Speaker 1: which has a vastly larger reach than any mainstream news network.

1215
01:09:40,880 --> 01:09:42,800
Speaker 1: He gets like a hundred million downloads in a month.

1216
01:09:43,479 --> 01:09:47,440
Speaker 1: Reputable reporter, Yeah, like CNN is not as fucking influential

1217
01:09:47,479 --> 01:09:50,719
Speaker 1: as Joe Rogan. At this point, reputable reporters were hesitant

1218
01:09:50,760 --> 01:09:53,760
Speaker 1: to write too favorably about iver mectin, though, because as

1219
01:09:53,840 --> 01:09:56,559
Speaker 1: soon as that Egyptian study dropped, there were questions about

1220
01:09:56,560 --> 01:10:00,800
Speaker 1: its veracity. And the study of course proved to be gus, which,

1221
01:10:01,320 --> 01:10:03,960
Speaker 1: as we talked about earlier, throws the entire net meta

1222
01:10:04,000 --> 01:10:08,479
Speaker 1: analysis into question. Gideon my Erowitz Coon or whatever Gideon

1223
01:10:08,600 --> 01:10:10,160
Speaker 1: MK is how he writes on the I've read his

1224
01:10:10,200 --> 01:10:13,120
Speaker 1: full name early whatever, Gideon that epidemiologist I quoted earlier.

1225
01:10:13,439 --> 01:10:16,479
Speaker 1: He has a hobby of analyzing bad scientific studies and

1226
01:10:16,520 --> 01:10:19,679
Speaker 1: pointing out why they're disreputable. He is an actual scientist

1227
01:10:19,760 --> 01:10:23,040
Speaker 1: and an actual epidemiologist. He's not a Joe rogue, and

1228
01:10:23,160 --> 01:10:26,360
Speaker 1: unlike Dr Corey, he specializes in a field relevant to

1229
01:10:26,600 --> 01:10:29,120
Speaker 1: talking about whether or not iver mect and fucking works.

1230
01:10:29,640 --> 01:10:34,639
Speaker 1: In July, he wrote a devastating piece about Dr Elgasar's study.

1231
01:10:34,920 --> 01:10:37,360
Speaker 1: A number of his technical criticisms of the study are

1232
01:10:37,439 --> 01:10:40,040
Speaker 1: not things I understand, but this bit here should be

1233
01:10:40,120 --> 01:10:45,240
Speaker 1: clear to everyone. Quote the entire introduction appears to be plagiarized. Indeed,

1234
01:10:45,360 --> 01:10:48,200
Speaker 1: it's very easy to confirm this. A copy pasted a

1235
01:10:48,280 --> 01:10:51,240
Speaker 1: few phrases from different paragraphs into Google, and it is

1236
01:10:51,280 --> 01:10:53,960
Speaker 1: immediately apparent that most of the introduction has been lifted

1237
01:10:53,960 --> 01:10:57,840
Speaker 1: from elsewhere online without attribution or acknowledgement. So I hope

1238
01:10:57,880 --> 01:11:00,599
Speaker 1: of it like the first chapter of A Babysitter's Right

1239
01:11:00,680 --> 01:11:03,760
Speaker 1: off the bag. That's a problem. That's a little bit

1240
01:11:03,840 --> 01:11:06,280
Speaker 1: of a problem. Right, that's a little bit of a problem.

1241
01:11:08,640 --> 01:11:11,320
Speaker 1: But what's worse is that the numbers in the study

1242
01:11:11,640 --> 01:11:15,840
Speaker 1: are frankly impossible which has thrown considerable doubt again on

1243
01:11:16,000 --> 01:11:18,479
Speaker 1: whether or not the study was actually conducted at all.

1244
01:11:18,840 --> 01:11:23,479
Speaker 1: Quote in Table four, the study shows means, standard deviation,

1245
01:11:23,600 --> 01:11:26,160
Speaker 1: and ranges for recovery time and patients within the study.

1246
01:11:26,479 --> 01:11:28,760
Speaker 1: The issue is that with the reported range of nine

1247
01:11:28,800 --> 01:11:30,800
Speaker 1: to twenty five days, a mean of eighteen, and the

1248
01:11:30,880 --> 01:11:34,080
Speaker 1: standard deviation of eight, there are very few configurations of

1249
01:11:34,160 --> 01:11:36,280
Speaker 1: numbers that would leave you with this result. You can

1250
01:11:36,360 --> 01:11:39,240
Speaker 1: even calculate this yourself using this tool developed by the

1251
01:11:39,280 --> 01:11:42,080
Speaker 1: clever fraud detectives James Heather's, Nick Brown, Jordan and Ia

1252
01:11:42,360 --> 01:11:45,080
Speaker 1: and Tim Vandersey. To have a mean of eighteen days.

1253
01:11:45,160 --> 01:11:48,040
Speaker 1: Consistent with the other values, the majority of the patients

1254
01:11:48,040 --> 01:11:49,400
Speaker 1: in this group would have had to stay in the

1255
01:11:49,479 --> 01:11:53,600
Speaker 1: hospital for either nine or twenty five days exactly. So

1256
01:11:53,640 --> 01:11:56,080
Speaker 1: a lot of like when you actually do the data

1257
01:11:56,479 --> 01:12:00,640
Speaker 1: weird shit. Somehow, it gets even worse. Turns out that

1258
01:12:00,720 --> 01:12:03,080
Speaker 1: the authors uploaded the actual data they used for the

1259
01:12:03,160 --> 01:12:06,920
Speaker 1: study into an online repository. While the data is locked,

1260
01:12:07,760 --> 01:12:10,240
Speaker 1: one of the like people in analyzing this managed to

1261
01:12:10,280 --> 01:12:12,280
Speaker 1: guess the password in the file, which was one two

1262
01:12:12,360 --> 01:12:15,640
Speaker 1: three four, and gain an act access to the anonymous

1263
01:12:15,680 --> 01:12:17,960
Speaker 1: patient level information that the authors used to put the

1264
01:12:17,960 --> 01:12:22,800
Speaker 1: paper together. I've got a copy, and it's amazing how

1265
01:12:22,840 --> 01:12:25,679
Speaker 1: obvious the flaws are even at a casual glance. For example,

1266
01:12:25,760 --> 01:12:28,880
Speaker 1: the study reports getting ethical approval and beginning approval in

1267
01:12:28,960 --> 01:12:31,240
Speaker 1: beginning on the eighth of June, But in the data

1268
01:12:31,280 --> 01:12:33,719
Speaker 1: file uploaded by the authors onto the website of the preprint,

1269
01:12:33,800 --> 01:12:35,960
Speaker 1: fully one third of the people who died from COVID

1270
01:12:36,040 --> 01:12:39,080
Speaker 1: nineteen were already dead when the researchers started to recruit

1271
01:12:39,120 --> 01:12:41,880
Speaker 1: their patients. Unless they were getting dead people to consent

1272
01:12:42,000 --> 01:12:45,519
Speaker 1: to participate in the trial, that's not really possible. Moreover,

1273
01:12:45,680 --> 01:12:48,680
Speaker 1: about the entire group of patients who were recruited for

1274
01:12:48,720 --> 01:12:52,400
Speaker 1: the support supposedly prospecs perspective randomized trial appeared to have

1275
01:12:52,479 --> 01:12:55,639
Speaker 1: been hospitalized before the study even started, which is either

1276
01:12:55,720 --> 01:12:57,960
Speaker 1: a mind boggling breach of ethics or a very bad

1277
01:12:58,040 --> 01:13:00,439
Speaker 1: sign of potential fraud. Even worse, if you look at

1278
01:13:00,479 --> 01:13:02,760
Speaker 1: the values for different patients, it appears that most of

1279
01:13:02,840 --> 01:13:05,800
Speaker 1: groups Group four are simply clones of each other, with

1280
01:13:05,920 --> 01:13:10,480
Speaker 1: the same or largely similar initials co morbidities, lymphocyte scores, etcetera.

1281
01:13:11,000 --> 01:13:17,799
Speaker 1: So this is the worst life. Like we're recruiting ghosts

1282
01:13:18,160 --> 01:13:21,280
Speaker 1: were recruiting clumps. We got a lot of ghosts in

1283
01:13:21,360 --> 01:13:24,960
Speaker 1: the study, the big farmaties. I want you to know

1284
01:13:25,040 --> 01:13:30,760
Speaker 1: what ghosts have to say about medicine, so I will like,

1285
01:13:31,120 --> 01:13:39,880
Speaker 1: oh my god, mhm, problems that not mistakes but like lies. Yeah,

1286
01:13:40,080 --> 01:13:42,040
Speaker 1: it's a lot of problems. And getting is not the

1287
01:13:42,120 --> 01:13:44,640
Speaker 1: only guy breaking this down and blowing A number of

1288
01:13:44,680 --> 01:13:47,639
Speaker 1: people try to But by the time this gets thoroughly debunked,

1289
01:13:47,680 --> 01:13:49,920
Speaker 1: it had been downloaded a hundred and fifty thousand times

1290
01:13:50,000 --> 01:13:53,200
Speaker 1: and cited in two different meta analyzes that showed iver

1291
01:13:53,360 --> 01:13:55,920
Speaker 1: mectmus having a huge medical benefit, and it was the

1292
01:13:56,080 --> 01:14:01,080
Speaker 1: largest study in both meta analyzes. So again, when you've

1293
01:14:01,080 --> 01:14:03,479
Speaker 1: got a bunch of small studies and one big study,

1294
01:14:03,600 --> 01:14:06,120
Speaker 1: this one involved foreign to test subjects, that large study

1295
01:14:06,240 --> 01:14:08,439
Speaker 1: can skew the results of a meta analysis, which is

1296
01:14:08,479 --> 01:14:11,400
Speaker 1: what happened here. Quote. If you look at those large

1297
01:14:11,400 --> 01:14:15,040
Speaker 1: aggregate models and remove just this single study, ivermectin loses

1298
01:14:15,120 --> 01:14:18,160
Speaker 1: almost all of its purported benefits. Take the recent meta

1299
01:14:18,200 --> 01:14:20,200
Speaker 1: analysis by Bryant at All that has been all over

1300
01:14:20,240 --> 01:14:22,600
Speaker 1: the news. They found a sixty two percent reduction in

1301
01:14:22,720 --> 01:14:24,800
Speaker 1: risk of death for people who were treated with ivermectin

1302
01:14:24,880 --> 01:14:28,120
Speaker 1: compared to controls when combining randomized trials. However, if you

1303
01:14:28,160 --> 01:14:30,519
Speaker 1: remove the Algazar paper from their model and rerun it,

1304
01:14:30,800 --> 01:14:34,000
Speaker 1: the benefit goes from six to fifty two percent and

1305
01:14:34,120 --> 01:14:38,439
Speaker 1: largely loses its statistical significance. There's no benefit scene whatsoever

1306
01:14:38,560 --> 01:14:41,120
Speaker 1: for people who have severe COVID nineteen, and the confidence

1307
01:14:41,160 --> 01:14:44,960
Speaker 1: intervals for people with mild or moderate disease become extremely wide.

1308
01:14:45,240 --> 01:14:47,439
Speaker 1: If you include another study that was published after the

1309
01:14:47,479 --> 01:14:50,280
Speaker 1: Bryant meta analyses came out, which found no benefit for

1310
01:14:50,320 --> 01:14:52,639
Speaker 1: iver mected on death, the benefits scene in the model

1311
01:14:52,680 --> 01:14:56,960
Speaker 1: disappear entirely. For another recent meta analysis, simply excluding el

1312
01:14:57,000 --> 01:15:00,960
Speaker 1: Gazar is enough to remove the positive effect entirely, and

1313
01:15:01,160 --> 01:15:04,680
Speaker 1: so in one fell swoop, the very best scientific case

1314
01:15:04,720 --> 01:15:07,200
Speaker 1: for iver mecton as a COVID treatment kind of collapses

1315
01:15:07,720 --> 01:15:10,360
Speaker 1: within the medical field reaction to the word Gidding and

1316
01:15:10,439 --> 01:15:13,040
Speaker 1: others had done busting this bad study was Swift, the

1317
01:15:13,160 --> 01:15:16,320
Speaker 1: preprint Servery that had published dr Elgazar study before peer

1318
01:15:16,360 --> 01:15:19,840
Speaker 1: review pulled it due to ethical concerns. The meta analyzes, though,

1319
01:15:19,840 --> 01:15:24,599
Speaker 1: are still out there and still being cited, and that's

1320
01:15:25,560 --> 01:15:27,200
Speaker 1: I guess all. We're gonna talk about in part one.

1321
01:15:28,800 --> 01:15:34,400
Speaker 1: Oh good's it's probably yeah, this is this is this

1322
01:15:34,640 --> 01:15:39,920
Speaker 1: is so troubling, I mean and it's I mean, I

1323
01:15:40,000 --> 01:15:42,120
Speaker 1: knew the studies were gonna be it was gonna be

1324
01:15:42,280 --> 01:15:46,400
Speaker 1: bad for sure, but this is like a level of

1325
01:15:47,520 --> 01:15:53,360
Speaker 1: disinformation and negligence that I had not anticipated. Wow, Wow, Wow,

1326
01:15:53,840 --> 01:16:01,320
Speaker 1: what name? What a nightmare? Um all, Jamie, you got

1327
01:16:01,439 --> 01:16:07,920
Speaker 1: a plug things? Oh yeah, I could plug things. Uh here,

1328
01:16:08,120 --> 01:16:10,439
Speaker 1: here's a plug. You can listen to all of ac

1329
01:16:10,800 --> 01:16:16,960
Speaker 1: cast out now, which is my podcast about the history

1330
01:16:17,200 --> 01:16:24,559
Speaker 1: of Kathy comics and twentieth century American feminism. Uh yeah,

1331
01:16:24,880 --> 01:16:27,840
Speaker 1: or you could uh listen to the Bechtel Cast, or

1332
01:16:27,920 --> 01:16:32,920
Speaker 1: you could follow me on Twitter or Instagram and Twitter

1333
01:16:33,080 --> 01:16:37,720
Speaker 1: is Jamie left his help. Instagram's Jamie christ Superstar. And

1334
01:16:37,880 --> 01:16:40,559
Speaker 1: that's all. I think. That That's all I have to say. Oh. Also, also,

1335
01:16:40,840 --> 01:16:46,360
Speaker 1: I am still soliciting hot dog recommendations. I've been to

1336
01:16:46,439 --> 01:16:49,240
Speaker 1: a lot of places I've tried. I think, all the

1337
01:16:49,520 --> 01:16:52,000
Speaker 1: all the big dogs, all the places that are on

1338
01:16:52,120 --> 01:16:54,280
Speaker 1: the listicles, I've been to all of those. But if

1339
01:16:54,320 --> 01:16:58,360
Speaker 1: there is an obscure hot dog place that you think

1340
01:16:58,439 --> 01:17:03,880
Speaker 1: I should try in the Continental us because I cannot

1341
01:17:04,479 --> 01:17:09,120
Speaker 1: we can't go anywhere. Uh, let me know, I'm interested. Yeah, Oh,

1342
01:17:09,280 --> 01:17:13,120
Speaker 1: there's a great there's a great uh hot dog place

1343
01:17:13,200 --> 01:17:15,599
Speaker 1: in Lisbon where you can get something that I will

1344
01:17:15,680 --> 01:17:17,920
Speaker 1: argue as a hot dog, where you can get a

1345
01:17:18,000 --> 01:17:21,320
Speaker 1: piece of octopus on a hot dog bun. If it's random,

1346
01:17:21,640 --> 01:17:25,280
Speaker 1: it's a hot dog. It's not random meat. If it's

1347
01:17:25,320 --> 01:17:28,120
Speaker 1: just one meat, it could be random. You could just

1348
01:17:28,400 --> 01:17:31,799
Speaker 1: stick your knife in the ocean. Sometimes you're gonna get random.

1349
01:17:31,840 --> 01:17:36,400
Speaker 1: It could be wearing a Jack Skellington sweatshirt. That's not random, Jamie,

1350
01:17:36,560 --> 01:17:42,760
Speaker 1: that's a popular media phenomenon. I look, I I I

1351
01:17:42,880 --> 01:17:45,280
Speaker 1: had a Jack Skellington hoodie before I had ever seen

1352
01:17:45,360 --> 01:17:49,040
Speaker 1: that damn movie. And then I watched it Certain Dido

1353
01:17:49,880 --> 01:17:53,200
Speaker 1: or Ring creepy. Yeah, I know. Before. Well, that's just

1354
01:17:53,320 --> 01:17:55,040
Speaker 1: if you want to be taken serious by the kids

1355
01:17:55,080 --> 01:17:57,519
Speaker 1: who play Hackey Sack outside, you gotta have a Jack

1356
01:17:57,560 --> 01:18:00,240
Speaker 1: Skellington t shirt. That's just how the social time it

1357
01:18:00,400 --> 01:18:03,599
Speaker 1: was at that time. Well, there's some free advice if

1358
01:18:03,640 --> 01:18:07,200
Speaker 1: you want children to like um in two thousand and seven.

1359
01:18:07,600 --> 01:18:10,160
Speaker 1: In two thousand and seven, if you're traveling back in

1360
01:18:10,280 --> 01:18:13,160
Speaker 1: time in two thousand and seven, and it is critical

1361
01:18:13,720 --> 01:18:17,599
Speaker 1: that fourteen year olds think you're cool. Jamie Loftis has

1362
01:18:19,320 --> 01:18:21,840
Speaker 1: the I have a thirty dollar solution for you. It's

1363
01:18:21,880 --> 01:18:25,160
Speaker 1: called the Jack Skellington Hood solution for you is more

1364
01:18:25,240 --> 01:18:28,240
Speaker 1: money back then though, so keep that in mind. Yeah,

1365
01:18:28,280 --> 01:18:31,439
Speaker 1: that's good. That's a couple of weeks of allowance. Well,

1366
01:18:31,560 --> 01:18:34,080
Speaker 1: follow us a pasters spot on, turn Instagram or at

1367
01:18:34,120 --> 01:18:37,080
Speaker 1: cool Zone Media for all the things. We'll be back Thursday.

1368
01:18:37,200 --> 01:18:40,160
Speaker 1: I oh,