1 00:00:00,840 --> 00:00:05,520 Speaker 1: Day, number one seventy three. All right, our two Sean 2 00:00:05,559 --> 00:00:07,920 Speaker 1: Hannity's show, Thanks for being with us, eight hundred nine 3 00:00:07,960 --> 00:00:09,600 Speaker 1: for one shots a number. You want to be a 4 00:00:09,600 --> 00:00:11,760 Speaker 1: part of the program. Well, if we're going to follow 5 00:00:11,800 --> 00:00:14,400 Speaker 1: the science, we got a lot of science yesterday, the 6 00:00:14,800 --> 00:00:20,240 Speaker 1: Major News study and Johns Hopkins has provided accurate information 7 00:00:20,600 --> 00:00:24,599 Speaker 1: all throughout this pandemic of COVID. And anyway, they determined 8 00:00:24,640 --> 00:00:28,680 Speaker 1: that all these lockdowns were ineffective and they were harmful, 9 00:00:29,040 --> 00:00:33,000 Speaker 1: and any future measures should be rejected out of hand. 10 00:00:33,159 --> 00:00:36,760 Speaker 1: In other words, don't make the same mistake again now, 11 00:00:36,960 --> 00:00:40,919 Speaker 1: especially when we were told by Biden and Faucian and company, 12 00:00:41,200 --> 00:00:44,720 Speaker 1: if you get vaccinated, you're never gonna get COVID. Okay, 13 00:00:44,760 --> 00:00:46,879 Speaker 1: that turned out not to be true. We'll never mandate 14 00:00:46,960 --> 00:00:50,640 Speaker 1: the vaccine. Yeah, that didn't turn out to be true either. 15 00:00:51,000 --> 00:00:53,120 Speaker 1: We may have to redefine what it means to be 16 00:00:53,200 --> 00:00:56,920 Speaker 1: fully vaccinated. Okay. The same people that ran out of 17 00:00:57,800 --> 00:01:03,360 Speaker 1: tests around Christmas at a time when predictably, you know, 18 00:01:03,440 --> 00:01:07,560 Speaker 1: people are getting together, you're gonna have higher incidents of COVID, 19 00:01:07,840 --> 00:01:10,200 Speaker 1: And they ran out of tests, and they ran out 20 00:01:10,200 --> 00:01:14,960 Speaker 1: of monoclonal antibodies and they never mass produced all these 21 00:01:15,000 --> 00:01:19,920 Speaker 1: anti virals Feizer, Murk and others when they knew that 22 00:01:19,959 --> 00:01:22,959 Speaker 1: these studies were shown they worked very effectively. Nobody ever 23 00:01:23,000 --> 00:01:26,039 Speaker 1: wants to talk about therapeutics, you know. I think this 24 00:01:26,200 --> 00:01:29,160 Speaker 1: debate over vax or don't vax is over. I think 25 00:01:29,200 --> 00:01:32,320 Speaker 1: everyone's pretty much made up their mind. I think most 26 00:01:32,319 --> 00:01:34,639 Speaker 1: people now are where I have been for a while. 27 00:01:34,680 --> 00:01:37,759 Speaker 1: And I don't trust Fauci. I don't trust Biden, Kamala Harris, 28 00:01:37,840 --> 00:01:41,480 Speaker 1: Jen Saki, the CDC, Will Lenski, or the NIH. I 29 00:01:41,480 --> 00:01:44,800 Speaker 1: don't trust any of them. And I again my mantra, 30 00:01:45,200 --> 00:01:49,360 Speaker 1: take it seriously, do your research, look at your unique 31 00:01:49,360 --> 00:01:52,080 Speaker 1: medical history, current condition, talk to your doctor doctors, and 32 00:01:52,080 --> 00:01:54,080 Speaker 1: then you're gonna have to make your own decision. And 33 00:01:54,120 --> 00:01:57,160 Speaker 1: then have a plan if whether you have a breakthrough case, 34 00:01:57,200 --> 00:02:00,200 Speaker 1: you're fully vaccinated and even have a booster, any of 35 00:02:00,200 --> 00:02:02,920 Speaker 1: those people are getting omicron and even people that had 36 00:02:02,960 --> 00:02:07,400 Speaker 1: COVID before they're getting it again. So what's your plan 37 00:02:07,520 --> 00:02:09,920 Speaker 1: if that happens? You don't want to, Oh, I just 38 00:02:09,960 --> 00:02:12,480 Speaker 1: test the positive? What do I do? Now? There's so 39 00:02:12,520 --> 00:02:14,359 Speaker 1: many people that call this show. What is that thing 40 00:02:14,400 --> 00:02:16,760 Speaker 1: that Hannity says? We need to ask our doctors about 41 00:02:17,120 --> 00:02:21,200 Speaker 1: monoclonal antibodies. And by the way, there's one specific one 42 00:02:21,280 --> 00:02:24,400 Speaker 1: that works better for amicron. And now we got the 43 00:02:24,480 --> 00:02:28,840 Speaker 1: supervariant of omicron and it is spreading or more contagious. 44 00:02:28,880 --> 00:02:32,560 Speaker 1: That's not good. There are thousands dying every single day 45 00:02:32,600 --> 00:02:36,040 Speaker 1: from omicron. Senator rand Paul has been in the forefront 46 00:02:36,080 --> 00:02:40,240 Speaker 1: of exposing all of this madness. And he also has 47 00:02:40,280 --> 00:02:43,200 Speaker 1: been in the forefront of digging down deep into the 48 00:02:43,240 --> 00:02:49,280 Speaker 1: origins of this virus in the Wuhan virology lab and 49 00:02:49,440 --> 00:02:53,120 Speaker 1: the NIH's involvement in doctor Fauci's lying about it, and 50 00:02:53,200 --> 00:02:55,320 Speaker 1: he joins us now he's also a medical doctor. How 51 00:02:55,320 --> 00:02:58,720 Speaker 1: are you, doctor, Senator ram Paul, good sean, thanks for 52 00:02:58,720 --> 00:03:03,440 Speaker 1: having me. You know. So, how is it possible that 53 00:03:03,560 --> 00:03:07,640 Speaker 1: we ran out of tests monoclonals and we never mass 54 00:03:07,720 --> 00:03:09,800 Speaker 1: produced the anti virals? Have you heard a lot of 55 00:03:09,800 --> 00:03:13,480 Speaker 1: good things as I have heard about the anti virals? Absolutely, 56 00:03:13,520 --> 00:03:16,000 Speaker 1: But the reason we ran out is central planning. It's 57 00:03:16,040 --> 00:03:19,360 Speaker 1: basically socialism. When you put all the directions in the 58 00:03:19,400 --> 00:03:22,120 Speaker 1: hand of a few people in government, they can never 59 00:03:22,160 --> 00:03:25,760 Speaker 1: figure out the right answer. I mean, always somewhat facetiously 60 00:03:25,840 --> 00:03:29,280 Speaker 1: and somewhat seriously, say that the Soviet Union failed. The 61 00:03:29,320 --> 00:03:31,960 Speaker 1: Soviet Union, communism failed because they couldn't determine the price 62 00:03:32,000 --> 00:03:34,760 Speaker 1: of bread. You said it too low. The bread's all gone. 63 00:03:34,800 --> 00:03:36,600 Speaker 1: You set the price too high, the bread rots on 64 00:03:36,640 --> 00:03:39,200 Speaker 1: the shelves. The only thing that can really figure out 65 00:03:39,240 --> 00:03:42,320 Speaker 1: the accurate price of bread is supplying demand in the marketplace, 66 00:03:42,400 --> 00:03:44,400 Speaker 1: millions of people bidding for it. But it's the same 67 00:03:44,480 --> 00:03:46,800 Speaker 1: way with medicine. I mean, the monoclonal antibodies should go 68 00:03:46,800 --> 00:03:49,520 Speaker 1: with it. Are the sickest people, so that would be demand, 69 00:03:49,520 --> 00:03:51,840 Speaker 1: and it goes day to day hospitals, you know, asking 70 00:03:51,840 --> 00:03:55,240 Speaker 1: for more monoclonal lat of bodies. And some states were 71 00:03:55,240 --> 00:03:57,600 Speaker 1: more proactive. I mean Florida of the Santis, did a 72 00:03:57,640 --> 00:04:00,400 Speaker 1: great job, was more proactive, got the monoclonal antimi to 73 00:04:00,400 --> 00:04:03,440 Speaker 1: be two people and probably saved thousands of lives. But 74 00:04:03,480 --> 00:04:05,840 Speaker 1: when the government gets involved with the distribution, see the 75 00:04:05,840 --> 00:04:09,360 Speaker 1: government owns all the monoclonal antibodies, that's a really rotten 76 00:04:09,440 --> 00:04:11,520 Speaker 1: idea to have one person. By the way, this is 77 00:04:11,560 --> 00:04:15,279 Speaker 1: an important point because Joe Biden never mentioned monoclonal lantibodies, 78 00:04:15,280 --> 00:04:17,279 Speaker 1: and he had them from day one. Until he gave 79 00:04:17,320 --> 00:04:20,760 Speaker 1: his vaccine mandate speech, and all of a sudden, we 80 00:04:20,760 --> 00:04:23,720 Speaker 1: had never had a shortage at all, Senator, and then 81 00:04:23,760 --> 00:04:27,400 Speaker 1: there became a shortage. You think there's a coincidence. I do, yeah. 82 00:04:27,440 --> 00:04:29,599 Speaker 1: And then the thing is is that they decided to 83 00:04:29,640 --> 00:04:32,960 Speaker 1: cut the old monoclonal lantibodies off, which admittedly aren't as 84 00:04:33,600 --> 00:04:36,200 Speaker 1: productive or as effective, but they cut them off before 85 00:04:36,200 --> 00:04:38,760 Speaker 1: the new ones arrived, and the doctors were still saying, 86 00:04:38,800 --> 00:04:41,000 Speaker 1: you know, there's still some benefit from the old ones. 87 00:04:41,000 --> 00:04:43,440 Speaker 1: The same way there's still some benefit from the old vaccine, 88 00:04:43,440 --> 00:04:46,480 Speaker 1: even though it's not perfect. But the old monoclonal antibodies 89 00:04:46,520 --> 00:04:49,240 Speaker 1: were discontinued by a government before there was a replacement. 90 00:04:49,279 --> 00:04:51,200 Speaker 1: So there were people in the mix in the first 91 00:04:51,200 --> 00:04:53,040 Speaker 1: couple of weeks of January where they couldn't get the 92 00:04:53,080 --> 00:04:56,000 Speaker 1: monoclonals at all. I think they're starting to catch up. 93 00:04:56,360 --> 00:04:59,600 Speaker 1: But socialism doesn't work, A planned economy doesn't work. There's 94 00:04:59,600 --> 00:05:02,960 Speaker 1: no way for the economy to react quickly. Think about Walmart. 95 00:05:03,040 --> 00:05:06,080 Speaker 1: You into by something at Walmart, they scan it. It's amazing, 96 00:05:06,120 --> 00:05:08,640 Speaker 1: it's immediately in the computer. Telling somebody we sold one 97 00:05:08,680 --> 00:05:11,080 Speaker 1: of those. They sell fifty of them. They know truck's 98 00:05:11,080 --> 00:05:12,840 Speaker 1: got to come with fifty of whatever you bought the 99 00:05:12,839 --> 00:05:16,440 Speaker 1: next day. So the marketplace really knows how and is 100 00:05:16,480 --> 00:05:20,880 Speaker 1: spectacular at resupplying their stores. A government can't do that 101 00:05:20,960 --> 00:05:23,240 Speaker 1: because they don't work on a profit system. You don't 102 00:05:23,240 --> 00:05:24,680 Speaker 1: have any way to know if the guy or the 103 00:05:24,720 --> 00:05:26,880 Speaker 1: woman in charge is doing a good job because you 104 00:05:26,920 --> 00:05:30,000 Speaker 1: don't measure profit. Most companies do it every day, every minute, 105 00:05:30,040 --> 00:05:32,799 Speaker 1: so you get the best and the most efficient managers 106 00:05:32,839 --> 00:05:35,600 Speaker 1: to try to replace goods. But now it's a disaster, 107 00:05:35,720 --> 00:05:37,840 Speaker 1: and this should be a warning side. We don't want 108 00:05:37,839 --> 00:05:40,359 Speaker 1: to socialize more of our medicine. We don't want to 109 00:05:40,360 --> 00:05:42,920 Speaker 1: have central planning. We particularly don't want someone like Falci, 110 00:05:42,960 --> 00:05:45,679 Speaker 1: who's been wrong on almost everything, to be in charge 111 00:05:45,680 --> 00:05:49,120 Speaker 1: of anything. You know, it's amazing because remember they said, oh, 112 00:05:49,160 --> 00:05:51,960 Speaker 1: well we didn't see our markan coming. How did they 113 00:05:52,000 --> 00:05:55,280 Speaker 1: not see it coming? Because we know that there's always mutations, 114 00:05:55,320 --> 00:05:58,320 Speaker 1: always new variants. You know, at some point we get 115 00:05:58,360 --> 00:06:01,400 Speaker 1: well it's called the endemic and this you know, we 116 00:06:01,480 --> 00:06:03,760 Speaker 1: live our normal lives and there's some version of it 117 00:06:03,760 --> 00:06:06,359 Speaker 1: out there, but it's not as lethal if I'm not 118 00:06:06,440 --> 00:06:10,560 Speaker 1: mistaken here, But you know, look at this study yesterday 119 00:06:10,640 --> 00:06:14,320 Speaker 1: by JOHNS Hopkins. I mean all the all the amount 120 00:06:14,360 --> 00:06:17,080 Speaker 1: of closures that took place, when you look at all 121 00:06:17,080 --> 00:06:21,240 Speaker 1: the draconian measures, and they determined that all of those lockdowns, 122 00:06:21,360 --> 00:06:24,560 Speaker 1: all of those measures were not only ineffective, but harmful, 123 00:06:24,960 --> 00:06:28,240 Speaker 1: and any future measures should be rejected out of hands 124 00:06:28,720 --> 00:06:32,760 Speaker 1: that strong language, after studying the impact that this has 125 00:06:32,800 --> 00:06:36,200 Speaker 1: had on society. Yeah, the Johns Hopkins study looked at 126 00:06:36,240 --> 00:06:38,520 Speaker 1: a bunch of studies, brought them together, looked at the 127 00:06:38,520 --> 00:06:40,920 Speaker 1: best studies, looked at quality, and tried to look at 128 00:06:40,960 --> 00:06:43,720 Speaker 1: those that were the most carefully controlled, and brought these 129 00:06:43,720 --> 00:06:46,800 Speaker 1: together to have large numbers of people involved and said, 130 00:06:47,200 --> 00:06:50,000 Speaker 1: guess what, it just didn't work. We've had other evidence 131 00:06:50,000 --> 00:06:51,920 Speaker 1: of this for a while. You remember in New York 132 00:06:51,960 --> 00:06:55,760 Speaker 1: when they started measuring where people contracted, and they're like, whoops, 133 00:06:55,800 --> 00:06:57,600 Speaker 1: people are getting it more often at home than they 134 00:06:57,600 --> 00:07:01,200 Speaker 1: are in restaurants. And so it was length of time 135 00:07:01,240 --> 00:07:04,320 Speaker 1: around people in the same air and combining people and 136 00:07:04,320 --> 00:07:06,400 Speaker 1: tell them they couldn't even go out, you know. Side 137 00:07:06,640 --> 00:07:09,000 Speaker 1: It was really the opposite of what we should have done. 138 00:07:09,279 --> 00:07:12,800 Speaker 1: So really, what's sad about this is the kind of 139 00:07:12,840 --> 00:07:15,880 Speaker 1: science we followed a sort of fourteenth century. You know, 140 00:07:15,920 --> 00:07:18,840 Speaker 1: the pope in the fourteenth century was definitely afraid of 141 00:07:18,880 --> 00:07:22,800 Speaker 1: the plague, and admittedly so was everybody else. He secluded himself, 142 00:07:22,840 --> 00:07:24,480 Speaker 1: which kind of worked a little bit, but they mostly 143 00:07:24,560 --> 00:07:27,160 Speaker 1: burned candles around him to try to burn the my asthma, 144 00:07:27,320 --> 00:07:30,480 Speaker 1: the mysterious forces in the air. And it made no 145 00:07:30,680 --> 00:07:33,840 Speaker 1: science to make sense because they didn't understand science. We've 146 00:07:33,920 --> 00:07:37,040 Speaker 1: understood the germ theory since the nineteenth century, and yet 147 00:07:37,040 --> 00:07:39,840 Speaker 1: we have people talking about doing things that made there's 148 00:07:39,880 --> 00:07:42,880 Speaker 1: no scientific evans. Putting up plaxi plexiglass around your kid, 149 00:07:43,720 --> 00:07:46,200 Speaker 1: it looks like you're you know, it looks moronic, and 150 00:07:46,280 --> 00:07:49,240 Speaker 1: it is. But m id Sigentist study this and said 151 00:07:49,320 --> 00:07:52,840 Speaker 1: you're better off having better circulation, and the plexiglass actually 152 00:07:52,920 --> 00:07:55,640 Speaker 1: interrupts the circulation of the class and actually makes it 153 00:07:55,720 --> 00:07:58,520 Speaker 1: more likely. Mask we found out that most of them 154 00:07:58,560 --> 00:08:01,800 Speaker 1: don't work, particularly with aerosolized things. It goes right around 155 00:08:01,840 --> 00:08:04,440 Speaker 1: your mask. Nobody can wear us damn mask tight enough 156 00:08:04,480 --> 00:08:07,160 Speaker 1: to work as it is. And then they say, well, 157 00:08:07,160 --> 00:08:09,400 Speaker 1: it only goes six feet, Well no, it doesn't. If 158 00:08:09,440 --> 00:08:11,240 Speaker 1: you're around somebody for a long period of time, it 159 00:08:11,280 --> 00:08:13,680 Speaker 1: may travel all the way across the room. But the 160 00:08:13,720 --> 00:08:16,560 Speaker 1: bottom line is we need to have good therapeutics, and 161 00:08:16,680 --> 00:08:19,400 Speaker 1: we do. And yet I've never heard Falci tell people 162 00:08:19,560 --> 00:08:21,840 Speaker 1: probably the most important thing your listeners need to hear. 163 00:08:22,360 --> 00:08:25,120 Speaker 1: If you were over fifty five or overweight and you 164 00:08:25,200 --> 00:08:27,840 Speaker 1: get sick, and you're getting sicker, you need to talk 165 00:08:27,840 --> 00:08:30,120 Speaker 1: to your doctor. And particularly in the first five days. 166 00:08:30,600 --> 00:08:33,560 Speaker 1: The treatments have like eighty nine percent success of keeping 167 00:08:33,600 --> 00:08:36,200 Speaker 1: you out of the hospital. If you wait till I 168 00:08:36,280 --> 00:08:38,920 Speaker 1: tell people work very well. I tell people to have 169 00:08:39,000 --> 00:08:41,320 Speaker 1: a plan and if you test positive, the sooner you 170 00:08:41,679 --> 00:08:44,520 Speaker 1: I know so many people that have had the infusion 171 00:08:45,280 --> 00:08:48,280 Speaker 1: or the shot now of monoclonal lantibodies. They're all better 172 00:08:48,320 --> 00:08:51,280 Speaker 1: within forty eight hours, and it always works better when 173 00:08:51,320 --> 00:08:53,280 Speaker 1: taken early. I wouldn't even wait till day five. The 174 00:08:53,360 --> 00:08:57,120 Speaker 1: problem with one size fits all medicine. You know, vaccine 175 00:08:57,240 --> 00:09:01,840 Speaker 1: and booster, vaccine and booster and mask those three things. 176 00:09:01,880 --> 00:09:04,760 Speaker 1: The problem is it doesn't work for everybody. Now that 177 00:09:04,800 --> 00:09:08,680 Speaker 1: we have breakthrough cases fully vaccinated, boostered people, natural immunity 178 00:09:08,720 --> 00:09:11,439 Speaker 1: people getting it at second time, now you've got to 179 00:09:11,480 --> 00:09:14,560 Speaker 1: focus on the therapeutics quick break more with Senator and 180 00:09:14,720 --> 00:09:17,960 Speaker 1: medical doctor Rampaul of Kentucky eight hundred nine one shuns 181 00:09:17,960 --> 00:09:19,640 Speaker 1: a number. We'll get to your calls at the bottom 182 00:09:19,679 --> 00:09:23,280 Speaker 1: of the half hour. Inflation under our current administration forty 183 00:09:23,320 --> 00:09:27,840 Speaker 1: year high, everything's more expensive. The Penwharton study families now 184 00:09:28,080 --> 00:09:31,080 Speaker 1: are paying the Biden inflation extra tax up to five 185 00:09:31,120 --> 00:09:34,280 Speaker 1: thousand dollars per household. That's how expensive it is, which 186 00:09:34,360 --> 00:09:37,040 Speaker 1: is why you need to find the big areas in 187 00:09:37,040 --> 00:09:40,040 Speaker 1: your life where you can save money, and your wireless 188 00:09:40,120 --> 00:09:42,680 Speaker 1: bill is one of them. Now many of you still 189 00:09:42,800 --> 00:09:46,280 Speaker 1: are with big carriers like Verizon AT and T T Mobile. 190 00:09:46,600 --> 00:09:49,880 Speaker 1: They're overcharging you. You can get the exact same service. 191 00:09:49,960 --> 00:09:54,160 Speaker 1: Let me repeat, exact same service from Pure Talk of 192 00:09:54,320 --> 00:09:57,640 Speaker 1: veteran O company at a fraction of the cost. The 193 00:09:57,679 --> 00:10:00,520 Speaker 1: same cell towers, same five G networks, same number of 194 00:10:00,559 --> 00:10:02,400 Speaker 1: bars on your phone. You can keep your phone, keep 195 00:10:02,400 --> 00:10:04,280 Speaker 1: your phone number you love more. And by the way, 196 00:10:04,320 --> 00:10:06,720 Speaker 1: the more lines you have, the more you're gonna save. 197 00:10:07,200 --> 00:10:10,120 Speaker 1: Right now, you can get four lines, four phones talk 198 00:10:10,200 --> 00:10:13,480 Speaker 1: tech Stata sixty four bucks. That's it. That's not per line, 199 00:10:13,520 --> 00:10:16,839 Speaker 1: that's total, all right, average family saving close to a 200 00:10:16,920 --> 00:10:19,959 Speaker 1: thousand dollars a year for the same service. Join the 201 00:10:20,120 --> 00:10:23,520 Speaker 1: Stampede that I'm a part of. Just dial pound two 202 00:10:23,600 --> 00:10:26,920 Speaker 1: fifty say the keyword save now, and this month you'll 203 00:10:26,920 --> 00:10:29,840 Speaker 1: save an additional twenty five percent off your first three months. 204 00:10:30,280 --> 00:10:33,400 Speaker 1: All right, pound two fifty keywords saved now. From Pure 205 00:10:33,400 --> 00:10:43,840 Speaker 1: Talk the Sean Hannity Show, a thermonuclear MMBA is salt 206 00:10:44,000 --> 00:11:06,320 Speaker 1: on Baby News. Nity is on right now. I continue 207 00:11:06,320 --> 00:11:10,320 Speaker 1: a senator and also medical doctor Rampaul of Kentucky. The 208 00:11:10,440 --> 00:11:13,480 Speaker 1: problem with this virus that I have seen, especially even 209 00:11:13,600 --> 00:11:17,719 Speaker 1: it's going on still today now in year three, if 210 00:11:17,760 --> 00:11:20,720 Speaker 1: you get a temperature, take two extra strength tile at 211 00:11:20,760 --> 00:11:24,839 Speaker 1: all and bring it down to normal levels. If your 212 00:11:24,960 --> 00:11:27,720 Speaker 1: oxygen saturation where it goes to ninety below, you better 213 00:11:27,760 --> 00:11:30,240 Speaker 1: go to the emergency room. But if you if you 214 00:11:30,280 --> 00:11:32,960 Speaker 1: get to that point and your oxygen it was ninety 215 00:11:32,960 --> 00:11:36,200 Speaker 1: five all six days, then day seven it's ninety and 216 00:11:36,240 --> 00:11:39,520 Speaker 1: then it goes to eighty four and then eighty at 217 00:11:39,559 --> 00:11:43,760 Speaker 1: that point, correct me if I'm wrong. The damage is done. 218 00:11:43,800 --> 00:11:47,040 Speaker 1: In other words, the covid pneumonia is there, covid lung 219 00:11:47,160 --> 00:11:49,520 Speaker 1: is there, and now you're in deep adam shift. If 220 00:11:49,520 --> 00:11:51,240 Speaker 1: you don't, if you know what I'm saying, But the 221 00:11:51,280 --> 00:11:53,640 Speaker 1: thing is is this is the great disservice of doctor 222 00:11:53,720 --> 00:11:56,320 Speaker 1: Valgie because there's such a differential in age and a 223 00:11:56,320 --> 00:11:59,040 Speaker 1: differential on risk factor. An eight year old is a 224 00:11:59,080 --> 00:12:01,640 Speaker 1: thousand times more likely to die in a ten year old. 225 00:12:01,720 --> 00:12:03,960 Speaker 1: Tenarre old has almost no risk of dying from this, 226 00:12:04,360 --> 00:12:06,040 Speaker 1: and so you treat them differently. You need to be 227 00:12:06,080 --> 00:12:08,600 Speaker 1: more concerned the older your arm. And it also has 228 00:12:08,640 --> 00:12:11,080 Speaker 1: to do with weight and being a male. But then 229 00:12:11,120 --> 00:12:13,600 Speaker 1: if we don't differentiate based on age and weight an 230 00:12:13,640 --> 00:12:16,960 Speaker 1: individual circumstances, we treat everybody the same. We really don't 231 00:12:16,960 --> 00:12:19,600 Speaker 1: have the resources to give everybody monoclon alt of bodies. 232 00:12:19,600 --> 00:12:21,280 Speaker 1: So it does need to be somewhat on your risk 233 00:12:21,360 --> 00:12:23,240 Speaker 1: and on how sick you are, and your doctor helps 234 00:12:23,240 --> 00:12:25,200 Speaker 1: you figure that out. But we get none of that. 235 00:12:25,320 --> 00:12:28,079 Speaker 1: And when the Great Barrington Declaration said we should try 236 00:12:28,160 --> 00:12:31,040 Speaker 1: to treat the elderly and those who live in group poems, 237 00:12:31,080 --> 00:12:34,040 Speaker 1: we should try to target more care and more surveillance. 238 00:12:35,679 --> 00:12:38,600 Speaker 1: And they ask you a question, why can't we produce 239 00:12:38,760 --> 00:12:41,360 Speaker 1: enough for everybody that gets it and wants it? Why 240 00:12:41,520 --> 00:12:44,079 Speaker 1: do why would there be a shortage for goodness sake? 241 00:12:44,120 --> 00:12:47,080 Speaker 1: With the United States of America. You know, we're the 242 00:12:47,080 --> 00:12:50,120 Speaker 1: ones that you know I have on doctor Malone's he 243 00:12:50,160 --> 00:12:55,160 Speaker 1: came under fire because he helped create the technology for 244 00:12:55,520 --> 00:12:59,920 Speaker 1: mRNA vaccines, and he's under fire because he has more 245 00:13:00,080 --> 00:13:03,600 Speaker 1: rigid requirements for the use of the technology and that 246 00:13:03,679 --> 00:13:09,640 Speaker 1: led to Fiza Madernam vaccinations. Okay for COVID and the problem, 247 00:13:09,679 --> 00:13:12,440 Speaker 1: the problem with treating everyone, John is this. You know, 248 00:13:12,480 --> 00:13:14,600 Speaker 1: we had a period of time where a million people 249 00:13:14,600 --> 00:13:16,560 Speaker 1: are there getting it. You have to keep in mind 250 00:13:16,559 --> 00:13:19,480 Speaker 1: that ninety nine percent get better without any treatment, so 251 00:13:19,600 --> 00:13:22,840 Speaker 1: you do really medically, it's not appropriate to treat everybody 252 00:13:22,880 --> 00:13:25,520 Speaker 1: the same. The vast majority of young healthy people don't 253 00:13:25,520 --> 00:13:27,920 Speaker 1: need any treatment at all. But it is making that 254 00:13:28,040 --> 00:13:31,400 Speaker 1: judgment call that a physician can help with. But this 255 00:13:31,480 --> 00:13:33,760 Speaker 1: is the real problem, is that you don't need no 256 00:13:34,000 --> 00:13:35,720 Speaker 1: not everybody needs a test either if you don't have 257 00:13:35,720 --> 00:13:37,960 Speaker 1: any symptoms. We shouldn't do millions of tests every day 258 00:13:38,000 --> 00:13:40,880 Speaker 1: for people without symptoms. But we also shouldn't be treating 259 00:13:40,920 --> 00:13:44,400 Speaker 1: people without it without significant symptoms either, and that judgment 260 00:13:44,400 --> 00:13:46,240 Speaker 1: will be made. It's sort of like, would would you 261 00:13:46,280 --> 00:13:49,000 Speaker 1: deny somebody that gets the flu and they want tamma flu. 262 00:13:49,080 --> 00:13:52,360 Speaker 1: Would we deny them that. I don't think we would. No. 263 00:13:52,480 --> 00:13:54,600 Speaker 1: I think the judgment, though, was made with a person, 264 00:13:54,800 --> 00:13:57,360 Speaker 1: and you have to make the judgment on risk of 265 00:13:57,360 --> 00:14:00,160 Speaker 1: treatment versus no treatment. And it would just like to 266 00:14:00,200 --> 00:14:03,520 Speaker 1: have people have the choice if they feel more comfortable, 267 00:14:03,559 --> 00:14:05,800 Speaker 1: they don't want to take the risk, and they feel 268 00:14:05,800 --> 00:14:08,240 Speaker 1: that this is the therapeutic of choice for them. I 269 00:14:08,280 --> 00:14:10,480 Speaker 1: think it should be readily available and if they have 270 00:14:10,520 --> 00:14:12,440 Speaker 1: to pay, you have to pay a certain degree of that. 271 00:14:12,520 --> 00:14:15,280 Speaker 1: But it's not completely that in the sense that I 272 00:14:15,280 --> 00:14:17,520 Speaker 1: don't think I would recommend that if a million people 273 00:14:17,559 --> 00:14:19,640 Speaker 1: get COVID a day, that we give them all monoculonal 274 00:14:19,680 --> 00:14:22,760 Speaker 1: antibodies or I'll still need to be some selective nature 275 00:14:22,840 --> 00:14:24,480 Speaker 1: to it and trying to figure out that's what we do. 276 00:14:24,520 --> 00:14:26,600 Speaker 1: Have positions, you do it in conjunction with a position 277 00:14:26,680 --> 00:14:30,080 Speaker 1: to figure it out, and ultimately they're definitely are people 278 00:14:30,080 --> 00:14:31,800 Speaker 1: that are helped by it. One of the things that 279 00:14:31,880 --> 00:14:34,680 Speaker 1: Fauci has not mentioned and is incredibly important is if 280 00:14:34,720 --> 00:14:38,440 Speaker 1: you are older and you get COVID, your spouse is 281 00:14:38,480 --> 00:14:41,160 Speaker 1: actually eligible to get the monocular antibodies, even if they're 282 00:14:41,160 --> 00:14:44,160 Speaker 1: not positive yet. And that's something that really can prevent 283 00:14:44,200 --> 00:14:47,360 Speaker 1: serious illness because it's so deadly or so much more deadly, 284 00:14:47,400 --> 00:14:50,760 Speaker 1: and the elderly that people don't know that, people don't 285 00:14:50,800 --> 00:14:52,720 Speaker 1: know they have to have treatment early. And they also 286 00:14:52,760 --> 00:14:55,520 Speaker 1: don't know that even without a positive test, an elderly 287 00:14:55,560 --> 00:14:57,960 Speaker 1: person can ask their doctor and often qualify for the 288 00:14:58,120 --> 00:15:00,800 Speaker 1: monoculon law. May I ask you this? Soldiers are now 289 00:15:00,840 --> 00:15:03,560 Speaker 1: being removed from the service because they refused the vaccine, 290 00:15:03,920 --> 00:15:07,360 Speaker 1: and now and what can only be described as they're 291 00:15:07,360 --> 00:15:11,520 Speaker 1: calling it involuntary separation, a directive signed by the Secretary 292 00:15:11,520 --> 00:15:15,560 Speaker 1: of the Army that they'll not be eligible for involuntary 293 00:15:15,600 --> 00:15:20,600 Speaker 1: separation pay and maybe subject to recoupment of any unearned 294 00:15:20,600 --> 00:15:24,720 Speaker 1: special or incentive pay that they might have received. Are 295 00:15:24,720 --> 00:15:27,520 Speaker 1: you kidding me? Completely unfair, Completely unfair, And I would 296 00:15:27,560 --> 00:15:30,360 Speaker 1: get rid of that. I'm part of legislation that would 297 00:15:30,360 --> 00:15:32,000 Speaker 1: reverse that and allow him to come back. I would 298 00:15:32,000 --> 00:15:34,480 Speaker 1: also allow the doctors and nurses to come back. And 299 00:15:34,600 --> 00:15:39,000 Speaker 1: here's the thing. The CDC has steadfastly tried to obscure 300 00:15:39,040 --> 00:15:41,680 Speaker 1: the truth from us, but they finally released last or 301 00:15:41,720 --> 00:15:45,360 Speaker 1: two weeks ago, a million person study, a million people 302 00:15:45,400 --> 00:15:48,040 Speaker 1: who got COVID. They wanted to know what's the risk 303 00:15:48,040 --> 00:15:51,720 Speaker 1: of being in the hospital if you're been vaccinated. It 304 00:15:51,800 --> 00:15:55,160 Speaker 1: was actually twenty times less if you're vaccinated and unvaccinated. 305 00:15:55,440 --> 00:15:59,000 Speaker 1: But they also released this interesting statistic if you've been 306 00:15:59,080 --> 00:16:03,160 Speaker 1: infected COVID but not vaccinated. That's my category. I've had 307 00:16:03,160 --> 00:16:06,880 Speaker 1: COVID but I wasn't vaccinated. I'm fifty five times less 308 00:16:06,920 --> 00:16:09,440 Speaker 1: likely to be in the hospital than someone who has 309 00:16:09,880 --> 00:16:12,960 Speaker 1: unvaccinated and not caught the infection. So really, what we 310 00:16:13,000 --> 00:16:15,760 Speaker 1: should do is all these soldiers, all these doctors, all 311 00:16:15,800 --> 00:16:18,560 Speaker 1: these nurses, all these firemen, all these policemen that have 312 00:16:18,600 --> 00:16:21,320 Speaker 1: already had it, let them go back to work. It's ridiculous. 313 00:16:21,320 --> 00:16:24,640 Speaker 1: There have no right. They are of no danger, Dean Wells. 314 00:16:24,680 --> 00:16:26,960 Speaker 1: In fact, they're safer than people go back to And 315 00:16:27,000 --> 00:16:29,720 Speaker 1: by the way, the next time you know somebody, La 316 00:16:29,840 --> 00:16:33,360 Speaker 1: Mayor Eric Garcetti defended his massless photo because they have 317 00:16:33,400 --> 00:16:36,800 Speaker 1: a mask mandate in Los Angeles. He says he held 318 00:16:36,880 --> 00:16:39,840 Speaker 1: his breath. Is that you know I didn't? Inhale, I 319 00:16:40,000 --> 00:16:42,360 Speaker 1: held my breath when I took off my mask. I'm like, 320 00:16:42,440 --> 00:16:44,760 Speaker 1: you gotta be kidding me. Well, right, I'm playing in 321 00:16:44,800 --> 00:16:46,760 Speaker 1: a couple hours and I'm gonna take my mask off 322 00:16:46,760 --> 00:16:48,720 Speaker 1: and see if the flight attendant would send me just 323 00:16:48,760 --> 00:16:51,440 Speaker 1: holding my breath. Yeah, good luck with that. Tell me 324 00:16:51,480 --> 00:16:53,280 Speaker 1: how that works out when you get arrested. All right, 325 00:16:53,960 --> 00:16:57,840 Speaker 1: I'll bell you a call for legal advice. All right, 326 00:16:57,920 --> 00:17:00,560 Speaker 1: my friend, Senator M Paul, Doctor M Paul, eight hundred 327 00:17:00,560 --> 00:17:02,160 Speaker 1: and nine for one, Shan, our number of your calls, 328 00:17:02,400 --> 00:17:05,640 Speaker 1: next quick break, right back, all right, twenty five nuns 329 00:17:05,640 --> 00:17:08,000 Speaker 1: at the top of the hour, eight hundred ninety four one, Sean. 330 00:17:08,280 --> 00:17:09,960 Speaker 1: If you want to be a part of the program, 331 00:17:10,359 --> 00:17:13,679 Speaker 1: let's say, how to Diane is an Arizona. What's going on? Diane? 332 00:17:13,720 --> 00:17:15,479 Speaker 1: How are you glad you called? Thanks for being will 333 00:17:15,520 --> 00:17:18,160 Speaker 1: us Hi. Sean, It's great to talk to you. I've 334 00:17:18,200 --> 00:17:20,800 Speaker 1: been listening to you since the days of Hannity and 335 00:17:20,880 --> 00:17:24,280 Speaker 1: Combs and you and I watch your show every night 336 00:17:24,320 --> 00:17:27,320 Speaker 1: and listen to your radio show every day while we're 337 00:17:27,320 --> 00:17:29,760 Speaker 1: waiting for our son to come out of school. He's 338 00:17:29,800 --> 00:17:32,000 Speaker 1: a special Meats child and he's a big fan too, 339 00:17:32,040 --> 00:17:35,520 Speaker 1: and a Trump supporter. And how old your son? My 340 00:17:35,600 --> 00:17:38,440 Speaker 1: son is fourteen. We moved here six years ago from 341 00:17:38,440 --> 00:17:42,600 Speaker 1: New York to Arizona, and I wanted to just chime 342 00:17:42,640 --> 00:17:45,040 Speaker 1: in a little bit on the Whoopee Goldberth thing. First 343 00:17:45,040 --> 00:17:46,920 Speaker 1: of all, in all the years I've listened to you, 344 00:17:46,960 --> 00:17:49,000 Speaker 1: I have to tell you I've never ever disagreed with 345 00:17:49,040 --> 00:17:52,200 Speaker 1: anything you've said. And thank you for keeping the conservative 346 00:17:52,280 --> 00:17:55,879 Speaker 1: voice alive for all of us. Thank you. There's a 347 00:17:55,880 --> 00:17:59,000 Speaker 1: butt coming. I've had this but call once or twice 348 00:17:59,000 --> 00:18:03,439 Speaker 1: in my life. Go ahead, but when I have to 349 00:18:03,480 --> 00:18:06,200 Speaker 1: tell you. When I heard you what you said about 350 00:18:06,200 --> 00:18:08,240 Speaker 1: Whoopy Gilbert the other night, it kind of was like 351 00:18:08,280 --> 00:18:10,120 Speaker 1: a knife to my heart. And let me just tell 352 00:18:10,119 --> 00:18:14,040 Speaker 1: you why I grew up, you know, with Jewish parents, 353 00:18:14,480 --> 00:18:19,000 Speaker 1: not very religious, but always brought up to respect where 354 00:18:19,000 --> 00:18:21,720 Speaker 1: we came from before my my loss. Both my parents 355 00:18:21,840 --> 00:18:26,080 Speaker 1: very young, and it's one thing they always ingrained in us. 356 00:18:26,160 --> 00:18:29,280 Speaker 1: Always remember. I always remember when I was a kid 357 00:18:29,320 --> 00:18:32,320 Speaker 1: hearing stories from my parents and my grandparents about the 358 00:18:32,320 --> 00:18:38,800 Speaker 1: Holocaust and very good friends of ours, her parents both 359 00:18:38,800 --> 00:18:41,240 Speaker 1: were in the Holocaust. When I had my first apartment, 360 00:18:41,359 --> 00:18:43,719 Speaker 1: my landlords came from the Holocaust and they all had 361 00:18:43,720 --> 00:18:46,520 Speaker 1: the numbers tattooed on their arms. So I can't tell 362 00:18:46,560 --> 00:18:49,360 Speaker 1: you I've heard numerous, numerous stories about what they went 363 00:18:49,400 --> 00:18:52,080 Speaker 1: through So when I heard the whole thing about whoopee, 364 00:18:52,080 --> 00:18:54,480 Speaker 1: how she said, you know, it wasn't it wasn't a 365 00:18:54,560 --> 00:18:58,120 Speaker 1: race thing. Now, she's been around a long time. She's 366 00:18:58,160 --> 00:19:01,719 Speaker 1: not a stupid person, and in her age group, everybody, 367 00:19:01,800 --> 00:19:04,639 Speaker 1: in one way or another, knows about the Holocaust. She 368 00:19:04,720 --> 00:19:07,280 Speaker 1: was a comedian and an actress long before she was 369 00:19:07,359 --> 00:19:10,640 Speaker 1: on the View. But the way I look at it is, unfortunately, 370 00:19:10,760 --> 00:19:14,760 Speaker 1: right now her and her cohorts on the View, they 371 00:19:14,840 --> 00:19:19,040 Speaker 1: love to just intentionally generalize and say things the holocausts 372 00:19:19,560 --> 00:19:24,720 Speaker 1: US equaling us, Trump fans, Nazis, and whoop he said 373 00:19:24,760 --> 00:19:28,240 Speaker 1: about the cages under the Trump administration, only that it 374 00:19:28,320 --> 00:19:32,760 Speaker 1: was like concentration camps. If she really was a human 375 00:19:32,840 --> 00:19:37,440 Speaker 1: being and knew what went on in those concentration camps, 376 00:19:37,480 --> 00:19:41,239 Speaker 1: she would never have said that. To say that it 377 00:19:41,320 --> 00:19:44,560 Speaker 1: wasn't a race thing. I mean, I don't even know 378 00:19:44,600 --> 00:19:48,960 Speaker 1: if ignorant is the right word. When point blank Hitler 379 00:19:49,240 --> 00:19:52,320 Speaker 1: threatened the annihilation of the Jews in nineteen thirty one, 380 00:19:52,359 --> 00:19:53,960 Speaker 1: he wanted to wipe him off the face of the earth. 381 00:19:54,359 --> 00:19:57,880 Speaker 1: He believed that the pure Germans were a superior race. 382 00:19:58,200 --> 00:20:00,879 Speaker 1: So when I hear people say things like that, it 383 00:20:01,000 --> 00:20:04,440 Speaker 1: just really really cuts me deep. Now, I know you're 384 00:20:04,480 --> 00:20:06,760 Speaker 1: not for boys, hiding people and all that, and I 385 00:20:06,800 --> 00:20:10,160 Speaker 1: totally respect that of you, but this, I just feel 386 00:20:10,160 --> 00:20:12,200 Speaker 1: it goes so much deeper. And like I said, it's 387 00:20:12,240 --> 00:20:15,359 Speaker 1: not like the view. It's her life, that's it. People 388 00:20:15,440 --> 00:20:18,320 Speaker 1: have been fired for far less. Look at Rosanne and 389 00:20:18,880 --> 00:20:22,600 Speaker 1: frankly because she was a Trump supporter, But like I said, whoop, 390 00:20:22,640 --> 00:20:26,200 Speaker 1: you was a comedian and an actress long before, so 391 00:20:26,320 --> 00:20:28,920 Speaker 1: it's not like you know, I mean, she went on 392 00:20:29,200 --> 00:20:33,280 Speaker 1: her apology tour that night on Colbert and got herself 393 00:20:33,400 --> 00:20:37,640 Speaker 1: dug much deeper. And then from what I hear, oh, 394 00:20:37,720 --> 00:20:41,919 Speaker 1: she's apologetic, but when she heard about her suspension, she 395 00:20:42,160 --> 00:20:46,320 Speaker 1: was so apologetic that she's like, screw this, I'm gonna quit, 396 00:20:46,760 --> 00:20:48,400 Speaker 1: you know what I mean. So she was By the way, 397 00:20:48,440 --> 00:20:51,960 Speaker 1: I have sources telling me that is I mean, real 398 00:20:52,040 --> 00:20:55,240 Speaker 1: good sources. That is a thousand percent not true that part. 399 00:20:55,320 --> 00:20:58,600 Speaker 1: But I'm listening very intently to what you're saying. It's 400 00:20:58,640 --> 00:21:00,800 Speaker 1: just like you know, I, like I said, I have 401 00:21:00,840 --> 00:21:05,119 Speaker 1: a special needs child and he was mentally abused in 402 00:21:05,160 --> 00:21:07,080 Speaker 1: New York in the school system, and that's why we 403 00:21:07,160 --> 00:21:10,120 Speaker 1: moved here and for as long as I can remember, 404 00:21:10,119 --> 00:21:12,880 Speaker 1: for as long as we thought he can understand anything. 405 00:21:12,880 --> 00:21:15,400 Speaker 1: And this was not from kids, this was from teachers 406 00:21:15,400 --> 00:21:19,960 Speaker 1: and administration. We've always tried to get him to understand 407 00:21:20,119 --> 00:21:25,359 Speaker 1: that you treat everybody every with human kindness and consideration. 408 00:21:26,040 --> 00:21:29,920 Speaker 1: That that is the first thing that we can remember 409 00:21:30,240 --> 00:21:33,560 Speaker 1: ever trying to instill in him. And just to hear 410 00:21:33,800 --> 00:21:36,520 Speaker 1: somebody like what be like I said, who isn't She's 411 00:21:36,560 --> 00:21:39,320 Speaker 1: not a stupid person, you know, to just go on 412 00:21:39,400 --> 00:21:41,960 Speaker 1: and they think they could just throw words like this 413 00:21:42,160 --> 00:21:46,960 Speaker 1: around what these families have suffered so deeply. I'm hearing 414 00:21:47,000 --> 00:21:50,280 Speaker 1: you loud and clear. Can I can I offer you 415 00:21:50,400 --> 00:21:53,600 Speaker 1: some insight that I have ye because I know her, 416 00:21:55,119 --> 00:21:57,240 Speaker 1: and take this any way you want to take it. 417 00:21:57,920 --> 00:22:00,520 Speaker 1: And you know, if you listen to my program and 418 00:22:00,560 --> 00:22:03,159 Speaker 1: watch my TV show, you've seen me in Israel. You 419 00:22:03,160 --> 00:22:06,880 Speaker 1: know I've been friends with bb for you know, twenty 420 00:22:06,880 --> 00:22:10,640 Speaker 1: five twenty seven years. Um, I knew a who would 421 00:22:10,640 --> 00:22:14,960 Speaker 1: barack shimum Perez Um. I can't even name all of 422 00:22:15,000 --> 00:22:16,439 Speaker 1: the people that I know I'm really good for. I 423 00:22:16,480 --> 00:22:19,280 Speaker 1: love Ron Dermer, I love Dorry Gold. These are all 424 00:22:19,320 --> 00:22:22,480 Speaker 1: friends of mine, and there's no bigger supporter in the 425 00:22:22,520 --> 00:22:26,600 Speaker 1: media than say me and Mark Levin of the State 426 00:22:26,600 --> 00:22:28,440 Speaker 1: of Israel that I can think of off the top 427 00:22:28,480 --> 00:22:32,320 Speaker 1: of my head. So you know that a part about me. 428 00:22:32,359 --> 00:22:35,840 Speaker 1: If I thought in any way there was any anti 429 00:22:35,880 --> 00:22:40,760 Speaker 1: Semitism in Whoopee's heart, I would have no problem calling 430 00:22:40,760 --> 00:22:43,840 Speaker 1: it out, you know. But I have to be honest 431 00:22:43,920 --> 00:22:46,680 Speaker 1: and tell you what I know. Let me, Whoopee Goldberg 432 00:22:46,800 --> 00:22:50,760 Speaker 1: is sort of like in real life, she's like peace 433 00:22:50,880 --> 00:22:57,160 Speaker 1: and love and happiness. And so what she said very inarticulately, 434 00:22:57,440 --> 00:23:01,200 Speaker 1: historically inaccurate, as you rightly point out. She did point 435 00:23:01,240 --> 00:23:03,679 Speaker 1: out one thing, and that was the evil or she 436 00:23:04,160 --> 00:23:08,160 Speaker 1: her words were man's inhumanity demand. And then she made 437 00:23:08,160 --> 00:23:10,159 Speaker 1: the statement, now, no, it's not about race, it's not 438 00:23:10,200 --> 00:23:13,640 Speaker 1: about race. Well, actually, the whole thing was about race 439 00:23:13,720 --> 00:23:20,040 Speaker 1: and the sickness, this evil, this deranged ideology called Nazism 440 00:23:20,119 --> 00:23:24,280 Speaker 1: led by a madman, and an evil madman at that 441 00:23:24,280 --> 00:23:33,000 Speaker 1: that slaughtered six million plus Jewish people in these concentration camps, 442 00:23:34,359 --> 00:23:36,720 Speaker 1: you know, believed in this sixth stuff. So she was 443 00:23:36,760 --> 00:23:40,040 Speaker 1: wrong on that point. And do I think it was 444 00:23:40,240 --> 00:23:46,639 Speaker 1: said from a point of maliciousness? No, I can pretty 445 00:23:46,720 --> 00:23:49,680 Speaker 1: much guarantee you. I think that her apology is sincere, 446 00:23:50,359 --> 00:23:53,280 Speaker 1: and the proof will be in the pudding. You know. 447 00:23:53,359 --> 00:23:55,920 Speaker 1: If ABC, as they said, they will going to give 448 00:23:55,960 --> 00:23:59,760 Speaker 1: her a second chance, we'll see if she learns and 449 00:24:00,080 --> 00:24:02,280 Speaker 1: meaning it wouldn't ever happen again. I would bet that 450 00:24:02,320 --> 00:24:05,600 Speaker 1: will never happen again. Does that give you any say 451 00:24:05,840 --> 00:24:08,040 Speaker 1: one thing? Yeah, you can beat me, you can beat 452 00:24:08,080 --> 00:24:10,320 Speaker 1: me up, keep going boring. No, I'm not going to 453 00:24:10,359 --> 00:24:12,199 Speaker 1: beat job. We love you too much, Sean. I mean 454 00:24:12,520 --> 00:24:14,600 Speaker 1: we thank god we have people like you who can 455 00:24:15,040 --> 00:24:20,280 Speaker 1: you know, who voice our views? A conservative, I don't 456 00:24:20,320 --> 00:24:22,439 Speaker 1: care about this country. I mean I come from a 457 00:24:22,480 --> 00:24:25,800 Speaker 1: military family too, and you know what's going on just 458 00:24:26,040 --> 00:24:28,320 Speaker 1: you know, kills us. And thank god we have people 459 00:24:28,320 --> 00:24:30,879 Speaker 1: like you and Tucker and Jesse and Laura and I 460 00:24:30,880 --> 00:24:32,720 Speaker 1: can go on and on. We watched the whole lineup. 461 00:24:32,800 --> 00:24:35,480 Speaker 1: I mean, um, but what I wanted to just say, 462 00:24:35,480 --> 00:24:37,960 Speaker 1: as far as yes, I agree what she she said 463 00:24:37,960 --> 00:24:41,680 Speaker 1: about it was a crime against the inhumanity of man. 464 00:24:42,160 --> 00:24:48,399 Speaker 1: But it wasn't all man. It was six million Jews, men, women. Listen, 465 00:24:48,440 --> 00:24:51,920 Speaker 1: every time everyone, everyone makes these Nazi analogies, these Holocaust 466 00:24:51,920 --> 00:24:55,159 Speaker 1: analogies that always screw it up. Yeah, let me let 467 00:24:55,160 --> 00:24:57,800 Speaker 1: me just say this. Let me say this in closing, 468 00:24:57,960 --> 00:25:02,040 Speaker 1: and um, and you have family that we're in the Holocaust, 469 00:25:02,080 --> 00:25:06,800 Speaker 1: they know. I urge everybody go to the History Channel, 470 00:25:06,920 --> 00:25:11,840 Speaker 1: go select on demand, watch the videos. You can see 471 00:25:11,880 --> 00:25:16,840 Speaker 1: it yourself. And it is a horror that is unimaginable, 472 00:25:17,359 --> 00:25:21,240 Speaker 1: evil on a scale unimaginable. You know, there was a 473 00:25:21,240 --> 00:25:24,000 Speaker 1: woman that passed away not that long ago. Her name 474 00:25:24,040 --> 00:25:28,000 Speaker 1: was Hannah from Brooklyn, and Hannah from Brooklyn survived the Holocaust, 475 00:25:28,520 --> 00:25:31,000 Speaker 1: and she was a regular call to this radio show 476 00:25:31,040 --> 00:25:32,600 Speaker 1: when I was local in New York and then when 477 00:25:32,600 --> 00:25:36,879 Speaker 1: I became national and the loveliest woman in the world. 478 00:25:37,040 --> 00:25:39,480 Speaker 1: And her daughter, Pearl, broke my heart when I heard 479 00:25:39,520 --> 00:25:43,760 Speaker 1: she passed away. And you know, anybody that had to 480 00:25:43,840 --> 00:25:46,439 Speaker 1: live through that, you know, if you want to make 481 00:25:46,480 --> 00:25:53,160 Speaker 1: it easy, watch Schindler's List. Watch that show, and it 482 00:25:53,240 --> 00:25:59,560 Speaker 1: captures a small portion of the horror and also the 483 00:25:59,680 --> 00:26:03,920 Speaker 1: horror of one man to help save lives. And there 484 00:26:03,960 --> 00:26:06,479 Speaker 1: are so many of those stories of good people in 485 00:26:06,520 --> 00:26:09,439 Speaker 1: the worst situation, risking that when I was for others, 486 00:26:10,080 --> 00:26:13,600 Speaker 1: and I hope that I hope people hear you and 487 00:26:13,840 --> 00:26:17,879 Speaker 1: hear your story, and I say this with great sadness. 488 00:26:18,000 --> 00:26:19,800 Speaker 1: I talk about and I talked about it in that 489 00:26:19,880 --> 00:26:24,159 Speaker 1: book that I researched very heavily and Deliver Us from Evil. 490 00:26:24,920 --> 00:26:28,440 Speaker 1: Is that last century over one hundred million human souls. 491 00:26:28,480 --> 00:26:33,840 Speaker 1: When you add up Mao China, Stalin Russia, Fascism, Nazism, 492 00:26:33,920 --> 00:26:39,600 Speaker 1: Imperial Japan, the Killing Fields, Cambodia, Paul Pot, etc. It's 493 00:26:39,600 --> 00:26:42,800 Speaker 1: over one hundred million souls, and we're probably underestimating it. 494 00:26:43,440 --> 00:26:49,879 Speaker 1: Evil exists. Nazism was real. It was about race, the 495 00:26:49,960 --> 00:26:55,480 Speaker 1: belief in a master race. It is sick, ugly, racist, twisted, 496 00:26:55,600 --> 00:26:59,600 Speaker 1: and it is dark, dark, dark evil. It's hard for 497 00:26:59,720 --> 00:27:02,520 Speaker 1: good people sometimes to wrap their mind around the fact 498 00:27:02,520 --> 00:27:06,639 Speaker 1: that there are evil people. Somebody that Molesta child is 499 00:27:06,680 --> 00:27:09,480 Speaker 1: an evil human being. You have to be evil to 500 00:27:09,520 --> 00:27:12,159 Speaker 1: be able to do that. And the same thing what 501 00:27:12,320 --> 00:27:16,719 Speaker 1: happened in these death camps, these concentration camps. It is 502 00:27:16,880 --> 00:27:22,440 Speaker 1: pure evil and people need to understand it. Get those 503 00:27:22,480 --> 00:27:25,359 Speaker 1: of my mother's last ward. Never forget yet, you know, 504 00:27:25,520 --> 00:27:28,879 Speaker 1: it's it's so important. I remember as a child, you know, 505 00:27:28,960 --> 00:27:31,639 Speaker 1: I grew up in a normal neighborhood. It was Jews, 506 00:27:31,640 --> 00:27:34,479 Speaker 1: Italians and Irish. We were all friends, everybody you know. 507 00:27:34,800 --> 00:27:36,520 Speaker 1: And I grew up in the same neighborhood. That was 508 00:27:36,560 --> 00:27:39,880 Speaker 1: my neighborhood too. Yeah, oh yeah, my right. My husband 509 00:27:39,920 --> 00:27:41,880 Speaker 1: told me to tell you that his sister got married 510 00:27:41,880 --> 00:27:44,560 Speaker 1: in Franklin Squid Jewish Center. My husband grew up in 511 00:27:44,640 --> 00:27:48,119 Speaker 1: Ireland Park. I grew up in Bayside. But I remember 512 00:27:48,119 --> 00:27:50,240 Speaker 1: going to school, walking to school my brother one day 513 00:27:50,240 --> 00:27:53,960 Speaker 1: and again we would never, you know, experienced anything, any 514 00:27:54,000 --> 00:27:57,159 Speaker 1: kind of anti Semitism before, just what we heard. I 515 00:27:57,200 --> 00:27:59,320 Speaker 1: was my brother's three years older than me, and one 516 00:27:59,359 --> 00:28:01,439 Speaker 1: day we were walking to school and they were a 517 00:28:01,440 --> 00:28:04,520 Speaker 1: bunch of older kids behind us, and I heard them 518 00:28:04,600 --> 00:28:09,240 Speaker 1: yell out where you going jew boy? And I said 519 00:28:09,240 --> 00:28:12,359 Speaker 1: to my brothers sad, what are they talking about? My 520 00:28:12,359 --> 00:28:14,720 Speaker 1: brother just looks at me, goes, Diane, that's what is 521 00:28:14,760 --> 00:28:18,040 Speaker 1: known as ignorant. Let me tell you something, and I 522 00:28:18,080 --> 00:28:20,960 Speaker 1: gotta leave you on this note. Anti Semitism is on 523 00:28:21,000 --> 00:28:25,919 Speaker 1: the rise. Iran now is a real, clear present danger 524 00:28:26,040 --> 00:28:29,080 Speaker 1: to the State of Israel. They are our closest alle 525 00:28:29,400 --> 00:28:34,399 Speaker 1: We never had a better president to the State of 526 00:28:34,400 --> 00:28:39,520 Speaker 1: Israel than Donald Trump, and um we better pay attention 527 00:28:39,600 --> 00:28:42,240 Speaker 1: to Iran because if they ever marry that they're sick 528 00:28:42,280 --> 00:28:47,320 Speaker 1: twisted ideology of convert or die with nuclear weapons, they 529 00:28:47,360 --> 00:28:52,479 Speaker 1: will try and annihilate Israel, and Israel will retaliate. Um. 530 00:28:53,000 --> 00:28:55,160 Speaker 1: You're a lovely woman, you got a heart of gold. 531 00:28:55,560 --> 00:28:59,440 Speaker 1: I hope you'll you'll consider my experience with this. I 532 00:28:59,440 --> 00:29:01,600 Speaker 1: wouldn't tell you if I didn't believe it. I think 533 00:29:01,600 --> 00:29:03,960 Speaker 1: you know that. No. I know, Sean, and we have 534 00:29:04,000 --> 00:29:05,920 Speaker 1: the utmost respect for you. We just want to thank 535 00:29:05,960 --> 00:29:08,600 Speaker 1: you for everything that you do. I hope the next 536 00:29:08,600 --> 00:29:11,320 Speaker 1: time you call you know we're not disagree, not that 537 00:29:11,360 --> 00:29:14,960 Speaker 1: we disagree. Really, we are in full agreement on being 538 00:29:15,000 --> 00:29:19,320 Speaker 1: historically accurate, and that is very important, and the seriousness 539 00:29:19,360 --> 00:29:22,880 Speaker 1: of it is I'm not glossing it over. Do I 540 00:29:22,920 --> 00:29:26,920 Speaker 1: think that probably she was arguing it from a place 541 00:29:27,000 --> 00:29:33,360 Speaker 1: of a lack of knowledge and inarticulate. Yes. Do I 542 00:29:33,400 --> 00:29:36,760 Speaker 1: Have I seen the type of anti semitism that you 543 00:29:36,880 --> 00:29:39,040 Speaker 1: described in your own life. No, I don't see it 544 00:29:39,080 --> 00:29:40,840 Speaker 1: in her. If I did, I promise you i'd call 545 00:29:40,880 --> 00:29:43,680 Speaker 1: it out. I promise you. That's good enough for me. Sean. 546 00:29:44,080 --> 00:29:46,680 Speaker 1: Oh God bless you always and your family. Okay, thank you, 547 00:29:46,880 --> 00:29:47,800 Speaker 1: quick break right back