1 00:00:00,000 --> 00:00:02,040 Speaker 1: Oh you know what we forgot to mention. Yeah, it's 2 00:00:02,080 --> 00:00:06,240 Speaker 1: gonna mention it. The pastathon numbers, postathon numbers. Is that 3 00:00:06,240 --> 00:00:08,560 Speaker 1: what you meant? That's what I meant. Yeah, okay, yeah, 4 00:00:09,000 --> 00:00:11,240 Speaker 1: I had it in front of me. Here we were. 5 00:00:11,760 --> 00:00:13,840 Speaker 1: We were announcing numbers at three and five o'clock. So 6 00:00:13,960 --> 00:00:17,720 Speaker 1: that's why I say, until I don't remember that, Uh 7 00:00:17,800 --> 00:00:21,159 Speaker 1: we get three and five o'clock. Eric, Tony had a 8 00:00:21,560 --> 00:00:26,279 Speaker 1: drummer who played longer last week. His drummer was better 9 00:00:26,320 --> 00:00:29,440 Speaker 1: than your drummer. I'm sorry I couldn't afford a better drummer. 10 00:00:30,320 --> 00:00:32,800 Speaker 1: Seems to be a budget problem for Eric. They make 11 00:00:32,920 --> 00:00:36,040 Speaker 1: Eric pay for the drummer. Anyway, This sounds more like 12 00:00:36,280 --> 00:00:42,960 Speaker 1: the Revolutionary War or something. Yeah, Muskets should go off 13 00:00:43,640 --> 00:00:46,559 Speaker 1: one million, one hundred forty two thousand, nine hundred and 14 00:00:46,560 --> 00:00:53,880 Speaker 1: five dollars, an all time record, beating last year's total 15 00:00:53,920 --> 00:00:57,880 Speaker 1: of a million, thirty three thousand. But they're still counting. 16 00:00:58,400 --> 00:01:01,200 Speaker 1: They are. It's just like, well, yeah, the final final 17 00:01:01,280 --> 00:01:05,240 Speaker 1: total is not yet here because the event is over, 18 00:01:05,319 --> 00:01:08,120 Speaker 1: but they're still bringing in numbers like they do, like 19 00:01:08,160 --> 00:01:10,959 Speaker 1: they count votes after election day, you know, And that's right, yes, 20 00:01:12,200 --> 00:01:16,000 Speaker 1: but but that's that's an amazing figure. One million, one 21 00:01:16,080 --> 00:01:19,240 Speaker 1: hundred forty two, nine hundred and five dollars. Thank you 22 00:01:19,280 --> 00:01:21,720 Speaker 1: for all the generosity And did you look at the 23 00:01:21,800 --> 00:01:24,920 Speaker 1: cumulative numbers since twenty ten? That was the first KFI 24 00:01:25,080 --> 00:01:29,960 Speaker 1: pasta thon five point seven million dollars and seven hundred 25 00:01:29,959 --> 00:01:33,360 Speaker 1: and twenty seven thousand pounds of pasta and sauce just 26 00:01:33,400 --> 00:01:36,639 Speaker 1: this year. They you you've donated almost twenty seven thousand 27 00:01:36,680 --> 00:01:41,280 Speaker 1: pounds just this year. How about that? So it's it's 28 00:01:41,319 --> 00:01:43,440 Speaker 1: incredible what you do for Bruno. And if you could 29 00:01:43,440 --> 00:01:45,840 Speaker 1: just see how happy all those kids are every day 30 00:01:46,040 --> 00:01:49,040 Speaker 1: eating their bowls of pasta and Bruno's crew makes the 31 00:01:49,160 --> 00:01:54,520 Speaker 1: best pasta dishes imaginable. Has I've had a few incredible 32 00:01:54,560 --> 00:01:57,720 Speaker 1: restaurant the Anaheim White Ass and great sponsors like Smartin 33 00:01:57,760 --> 00:02:02,559 Speaker 1: Final and Wendy's Marilla involved in this wonderful every year 34 00:02:02,600 --> 00:02:06,880 Speaker 1: that this continues at another record breaking fashion. All right, 35 00:02:06,920 --> 00:02:09,000 Speaker 1: we turned out to a story, of course we've covered 36 00:02:09,040 --> 00:02:12,880 Speaker 1: all year on The John Ken Show and even last year, 37 00:02:13,440 --> 00:02:16,440 Speaker 1: and that's the attempt to knock out of office the 38 00:02:16,520 --> 00:02:20,560 Speaker 1: Los Angeles County District Attorney George Gascone. As you know, 39 00:02:20,600 --> 00:02:23,399 Speaker 1: the first recall didn't go far, and they went back 40 00:02:23,440 --> 00:02:25,600 Speaker 1: and they started over, and they raised a lot of money, 41 00:02:25,600 --> 00:02:28,560 Speaker 1: and they collected a lot of signatures, and they dropped 42 00:02:28,560 --> 00:02:31,240 Speaker 1: off all the signatures at the LA County Registrar Recorder's 43 00:02:31,320 --> 00:02:34,960 Speaker 1: office in Norwalk and said, all right, we believe we 44 00:02:35,040 --> 00:02:37,600 Speaker 1: have an adequate margin for the number you're going to 45 00:02:37,639 --> 00:02:40,560 Speaker 1: throw out for one reason or another. And then came 46 00:02:40,600 --> 00:02:43,560 Speaker 1: the sad news a month or two later, they said 47 00:02:43,600 --> 00:02:46,520 Speaker 1: that the recall did not qualify. There were not enough 48 00:02:46,560 --> 00:02:50,280 Speaker 1: signatures to qualify this for the ballot. They did think 49 00:02:50,320 --> 00:02:53,000 Speaker 1: that would be the end of it, but no, because 50 00:02:53,040 --> 00:02:56,320 Speaker 1: everyone assumes that the LA County Registrar's office is corrupt 51 00:02:56,720 --> 00:02:59,840 Speaker 1: and was never going to allow the district attorney to 52 00:02:59,840 --> 00:03:02,720 Speaker 1: be recalled. We have one party rule. We have a 53 00:03:02,760 --> 00:03:06,400 Speaker 1: one party corrupt machine running all of Los Angeles City 54 00:03:06,440 --> 00:03:10,520 Speaker 1: and County, and the Registrar Recorder's office is part of 55 00:03:10,520 --> 00:03:14,280 Speaker 1: the county machine. So we have this story by Tory 56 00:03:14,360 --> 00:03:18,280 Speaker 1: Richards from the Washington Examiner, who says it's been three 57 00:03:18,360 --> 00:03:22,560 Speaker 1: months since George Gascone beat a bipartisan recall effort in 58 00:03:22,639 --> 00:03:25,440 Speaker 1: LA but for several dozen volunteers, the election is far 59 00:03:25,480 --> 00:03:29,280 Speaker 1: from over. Three days a week. They entered an office 60 00:03:29,320 --> 00:03:33,079 Speaker 1: at the La County Registrar Recorder to begin a tedious 61 00:03:33,160 --> 00:03:36,800 Speaker 1: six hours stipped pouring over records bearing the names and 62 00:03:36,880 --> 00:03:40,600 Speaker 1: addresses of voters who wanted to be removed, who wanted 63 00:03:40,640 --> 00:03:44,360 Speaker 1: to remove the beleaguered prosecutor from office. You know, they've 64 00:03:44,440 --> 00:03:49,120 Speaker 1: thrown out almost two hundred thousand petitions. This Dean Logan 65 00:03:49,160 --> 00:03:56,560 Speaker 1: crowd petitions. I think they mean signatures, well, because the 66 00:03:56,880 --> 00:03:59,200 Speaker 1: petition can have more than one signal. Sure, all right, 67 00:03:59,240 --> 00:04:03,360 Speaker 1: we'll call it signatures. One hundred ninety five thousand signatures. Now, 68 00:04:03,600 --> 00:04:07,360 Speaker 1: doesn't that seem like an excessive amount? Right? Just when 69 00:04:07,400 --> 00:04:09,800 Speaker 1: you hear that that they threw out one hundred ninety 70 00:04:09,840 --> 00:04:14,160 Speaker 1: five thousand signatures, really well, that almost implies that the 71 00:04:14,200 --> 00:04:18,000 Speaker 1: signature collectors were corrupt and just threw down anything. Yeah, 72 00:04:18,040 --> 00:04:21,200 Speaker 1: but that's an enormous amount. That is an overwhelming amount. 73 00:04:21,400 --> 00:04:24,520 Speaker 1: The thing is, Dean Logan doesn't want us to know 74 00:04:24,800 --> 00:04:29,040 Speaker 1: what the truth is because they are putting up all 75 00:04:29,120 --> 00:04:35,000 Speaker 1: kinds of barriers and restrictions to wear out this crew 76 00:04:35,040 --> 00:04:39,000 Speaker 1: of investigators led by Steve Cooley, the former DA who 77 00:04:39,120 --> 00:04:43,760 Speaker 1: was helping to run the recall effort, and they have 78 00:04:43,880 --> 00:04:47,640 Speaker 1: volunteers here, a number of prosecutors, and they're showing up 79 00:04:47,680 --> 00:04:50,800 Speaker 1: every day, and Logan is doing everything he can to 80 00:04:52,120 --> 00:04:56,240 Speaker 1: make it nearly impossible. They go in there and they 81 00:04:56,279 --> 00:04:58,640 Speaker 1: can bring in pens and paper, but they can't access 82 00:04:58,720 --> 00:05:03,279 Speaker 1: electronic devices other than limited information on a county computer screen. 83 00:05:04,120 --> 00:05:06,800 Speaker 1: It will take almost two years to go through the records. 84 00:05:06,800 --> 00:05:09,800 Speaker 1: They say by that time Cast Gone may be voted 85 00:05:09,800 --> 00:05:12,520 Speaker 1: out in a twenty twenty four election. Well that's one 86 00:05:12,560 --> 00:05:16,640 Speaker 1: way to go about it. Tim Weinberger, spokesman for the campaign, said, 87 00:05:16,680 --> 00:05:21,800 Speaker 1: it's like working inside nineteen seventy. That's what they've been reduced. 88 00:05:21,920 --> 00:05:25,040 Speaker 1: It's like working in nineteen seventy pen and paper for everything, 89 00:05:25,279 --> 00:05:29,520 Speaker 1: and Logan's doing that on purpose. Oh yes, just get 90 00:05:29,520 --> 00:05:32,760 Speaker 1: them to give up. And the only recourse that Cooley 91 00:05:32,800 --> 00:05:36,560 Speaker 1: and his team has is to go to court. Yeah, 92 00:05:36,600 --> 00:05:41,440 Speaker 1: and tomorrow, as it turns out, they have a hearing 93 00:05:41,480 --> 00:05:43,919 Speaker 1: in front of a judge to force Stean Logan to 94 00:05:44,080 --> 00:05:49,000 Speaker 1: increase computerized record access along with giving them more days 95 00:05:49,040 --> 00:05:53,720 Speaker 1: and volunteers allowed into the building because apparently they probably 96 00:05:53,800 --> 00:05:55,640 Speaker 1: have more people that would like to be a part 97 00:05:55,680 --> 00:05:57,320 Speaker 1: of this and more days. They would like to do this, 98 00:05:57,440 --> 00:06:00,720 Speaker 1: but that's another way of slowing them down and discouraging. 99 00:06:00,760 --> 00:06:05,080 Speaker 1: Three days a week, six hours pen and paper. Yeah, 100 00:06:05,120 --> 00:06:06,880 Speaker 1: I think you would find that so cruel that you 101 00:06:06,920 --> 00:06:09,880 Speaker 1: would just say, I give up. Here's what Cooley says 102 00:06:09,880 --> 00:06:12,800 Speaker 1: about Dean Logan. What is dangerous is when you have 103 00:06:12,839 --> 00:06:17,200 Speaker 1: a terribly adapt recklessly incompetent registrar who probably has done 104 00:06:17,240 --> 00:06:20,000 Speaker 1: just about everything that could be done to frustrate a 105 00:06:20,080 --> 00:06:24,480 Speaker 1: legitimate and successful recall effort. Yeah, why is Logan trying 106 00:06:24,520 --> 00:06:28,080 Speaker 1: so hard to get Coolie's crew to give up? Why 107 00:06:28,080 --> 00:06:30,080 Speaker 1: not just let him in, Let him have free rein, 108 00:06:30,360 --> 00:06:33,680 Speaker 1: let him have access to all the computers. Let if 109 00:06:33,680 --> 00:06:36,080 Speaker 1: they want to prove this kind of corruption, they want 110 00:06:36,120 --> 00:06:38,120 Speaker 1: to go through all the trouble. Let them. You got 111 00:06:38,160 --> 00:06:40,640 Speaker 1: nothing to lose, and then you could have a big 112 00:06:40,720 --> 00:06:43,440 Speaker 1: laugh if they find out there was no corruption, there 113 00:06:43,560 --> 00:06:48,240 Speaker 1: was no mistakes. They're hiding behind the privacy argument that 114 00:06:48,400 --> 00:06:51,400 Speaker 1: voter records could contain a driver's license number or the 115 00:06:51,520 --> 00:06:54,520 Speaker 1: last the last four digits of a social security number, 116 00:06:54,960 --> 00:06:57,560 Speaker 1: and that could be a real security problem. Can't do 117 00:06:57,800 --> 00:07:02,559 Speaker 1: any you could super revised them, you can't do anything 118 00:07:02,600 --> 00:07:05,040 Speaker 1: with the last four digits of the social security numbers. 119 00:07:05,040 --> 00:07:14,600 Speaker 1: Stop it. That's they're doing this on purpose. Now there's 120 00:07:14,640 --> 00:07:17,360 Speaker 1: forty six down. They were forty six thousand signatures short. 121 00:07:17,880 --> 00:07:20,080 Speaker 1: So they don't have to prove that there was a 122 00:07:20,120 --> 00:07:23,880 Speaker 1: one one hundred and ninety five thousand signatures were thrown 123 00:07:23,880 --> 00:07:26,080 Speaker 1: at incorrectly. They only have to prove that forty six 124 00:07:26,120 --> 00:07:30,800 Speaker 1: thousand were right. And volunteers so far said they have 125 00:07:30,880 --> 00:07:35,160 Speaker 1: proved that thousands of errors have occurred after only looking 126 00:07:35,200 --> 00:07:39,960 Speaker 1: at a fraction of the petitions. So the county said 127 00:07:39,960 --> 00:07:43,360 Speaker 1: that employees have to monitor the volunteers, and we're short staff. 128 00:07:43,480 --> 00:07:46,400 Speaker 1: Training temporary workers takes three to five days to fully 129 00:07:46,440 --> 00:07:49,720 Speaker 1: familiarize them with the signature review process. Blah blah, blah, 130 00:07:49,720 --> 00:07:54,000 Speaker 1: blah blah. According to Cooley, this is death by a 131 00:07:54,080 --> 00:07:57,200 Speaker 1: thousand cuts, a slow death in darkness. That appears to 132 00:07:57,240 --> 00:08:04,800 Speaker 1: be their goal. Of course it is. And again the 133 00:08:04,840 --> 00:08:07,640 Speaker 1: three biggest reasons they threw out and I still remember 134 00:08:07,680 --> 00:08:11,440 Speaker 1: this the signatures either the signature didn't match, that didn't 135 00:08:11,440 --> 00:08:14,640 Speaker 1: turn out to be that many voters listed a wrong address, 136 00:08:15,200 --> 00:08:18,560 Speaker 1: and voters who signed multiple petitions. And I remember the 137 00:08:18,560 --> 00:08:21,040 Speaker 1: second of the third one were two of the bigger ones. 138 00:08:21,480 --> 00:08:23,840 Speaker 1: They were claiming that their voters are just they weren't 139 00:08:23,840 --> 00:08:26,560 Speaker 1: registered voters, either not at all or not in California 140 00:08:26,640 --> 00:08:29,640 Speaker 1: or not in LA County. That was their claim with 141 00:08:29,680 --> 00:08:34,120 Speaker 1: a large number of those so volunteers said, signatures can 142 00:08:34,240 --> 00:08:38,360 Speaker 1: change over time. But if I recall the reasons that 143 00:08:38,400 --> 00:08:41,800 Speaker 1: the La County regist throughout a lot of the signatures 144 00:08:41,880 --> 00:08:44,480 Speaker 1: is not because of signature matching. That was a smaller 145 00:08:44,559 --> 00:08:48,000 Speaker 1: number of the number that were rejected. It was really 146 00:08:48,040 --> 00:08:52,680 Speaker 1: that they claimed that these just weren't registered voters. So 147 00:08:52,679 --> 00:08:55,640 Speaker 1: so all they get is the most recent signature viewable 148 00:08:55,679 --> 00:08:59,360 Speaker 1: on the computer screen. If the signature appears to differently 149 00:08:59,400 --> 00:09:01,960 Speaker 1: slightly gray way, it's supposed to be given to accepting it. 150 00:09:03,040 --> 00:09:05,120 Speaker 1: That is the case too. That's what they do with 151 00:09:05,240 --> 00:09:07,160 Speaker 1: mail in ballots. But we don't know if they're doing 152 00:09:07,160 --> 00:09:11,320 Speaker 1: their job properly. We don't know if the word was whispered. 153 00:09:11,360 --> 00:09:13,839 Speaker 1: Of course, just throw out as many as we need 154 00:09:13,880 --> 00:09:18,079 Speaker 1: thrown out, make up a reason that we'll never let 155 00:09:18,120 --> 00:09:21,240 Speaker 1: them in to figure out the truth. That's what I 156 00:09:21,280 --> 00:09:23,800 Speaker 1: would do if I was a partisan to gascon, if 157 00:09:23,840 --> 00:09:26,760 Speaker 1: I was a part of the machine, I'd tell my people, Hey, 158 00:09:27,320 --> 00:09:30,880 Speaker 1: all we gotta do is deny them a certain amount 159 00:09:31,800 --> 00:09:34,719 Speaker 1: and then cover up the reasons, and we won't let 160 00:09:34,760 --> 00:09:37,400 Speaker 1: them in. We'll only give them a few hours a day, 161 00:09:37,520 --> 00:09:39,360 Speaker 1: a couple of days a week. We'll make them use 162 00:09:39,400 --> 00:09:42,720 Speaker 1: panted paper. We'll give them a headaches and upset stomachs, 163 00:09:42,720 --> 00:09:45,400 Speaker 1: and they'll all get tired and go away. Let them 164 00:09:45,400 --> 00:09:48,719 Speaker 1: go sue us. By time the whole thing works its 165 00:09:48,760 --> 00:09:50,640 Speaker 1: way through the court, it's going to be the next 166 00:09:50,640 --> 00:09:53,440 Speaker 1: election anyway. That's what I would tell them if I 167 00:09:53,640 --> 00:09:57,920 Speaker 1: was a corrupt partisan. Apparently they've got no training on 168 00:09:57,960 --> 00:10:01,440 Speaker 1: the computer system. They've been given no tra manuals. And 169 00:10:01,600 --> 00:10:03,800 Speaker 1: one argument I think they'd had that would be pretty 170 00:10:03,840 --> 00:10:08,959 Speaker 1: good is they claim the Registrar's office that duplicates have 171 00:10:09,000 --> 00:10:11,360 Speaker 1: to be thrown out, but it says in some instances 172 00:10:11,400 --> 00:10:14,280 Speaker 1: they're throwing out both the duplicate and the original signature, 173 00:10:14,320 --> 00:10:17,240 Speaker 1: which they shouldn't do. If you signed a petition twice, 174 00:10:17,320 --> 00:10:19,679 Speaker 1: one of them should county, that one should not count. 175 00:10:19,760 --> 00:10:24,000 Speaker 1: That is really egregious that they throw out all the 176 00:10:24,040 --> 00:10:28,520 Speaker 1: petitions you signed, or all all the signatures. Now, that's 177 00:10:28,600 --> 00:10:32,480 Speaker 1: really awful. No, I don't trust them at all, and 178 00:10:32,559 --> 00:10:36,080 Speaker 1: they shouldn't be trusted because Logan has a bad reputation 179 00:10:36,240 --> 00:10:39,120 Speaker 1: and a bad history. The county is corrupt. We all 180 00:10:39,160 --> 00:10:43,200 Speaker 1: know that bonding mysteriously. That recall felt just short too. 181 00:10:43,720 --> 00:10:47,280 Speaker 1: Everything falls just short. Oh look at that. It was 182 00:10:47,360 --> 00:10:52,560 Speaker 1: so close. We are so sorry. We got more coming up, 183 00:10:52,640 --> 00:10:55,480 Speaker 1: John and Ken Camp I am six forty live everywhere 184 00:10:55,480 --> 00:10:57,920 Speaker 1: in the iHeart Radio app. Well, if you were looking 185 00:10:58,040 --> 00:11:01,840 Speaker 1: for coverage over the weekend of that Twitter file dump, 186 00:11:02,640 --> 00:11:05,560 Speaker 1: this was news on our show Friday afternoon that Elon 187 00:11:05,679 --> 00:11:09,080 Speaker 1: Musk said he would release it. Turns out he was 188 00:11:09,120 --> 00:11:12,640 Speaker 1: doing it through a reporter named Matt Taiebe the files 189 00:11:12,760 --> 00:11:15,840 Speaker 1: on Twitter from back in twenty twenty and the discussions 190 00:11:15,880 --> 00:11:19,440 Speaker 1: that went on about the Hunter Biden laptop story. So 191 00:11:19,520 --> 00:11:21,880 Speaker 1: if you're looking over the weekend for coverage, you probably 192 00:11:21,920 --> 00:11:24,800 Speaker 1: had to look in certain places. Those would be more 193 00:11:24,920 --> 00:11:30,760 Speaker 1: right wing conservative websites. The New York Times, the LA Times, 194 00:11:30,840 --> 00:11:35,640 Speaker 1: the Washington Post, NBC News. They were largely ignored the story. 195 00:11:35,720 --> 00:11:38,120 Speaker 1: All the left wing sites didn't cover it. They didn't 196 00:11:38,160 --> 00:11:41,679 Speaker 1: cover it. Today, the White House spokeshole was asked about it. 197 00:11:41,720 --> 00:11:44,720 Speaker 1: You know what a response was, it's old news and 198 00:11:45,440 --> 00:11:49,040 Speaker 1: here's the new twist. Since Elon Musk took over Twitter. 199 00:11:49,160 --> 00:11:52,000 Speaker 1: The angle they have is that he's unleashing all the racists. 200 00:11:52,520 --> 00:11:55,320 Speaker 1: There's too much free speech and now it's become a 201 00:11:55,400 --> 00:11:58,960 Speaker 1: dark place of hate. Yeah, well, when you're when they're cornered, 202 00:11:59,200 --> 00:12:03,280 Speaker 1: they start screaming racism. Because I've been tracking all these 203 00:12:03,320 --> 00:12:06,080 Speaker 1: news stories over the years and what happens to the 204 00:12:06,120 --> 00:12:10,160 Speaker 1: public debate, and when the progressives are cornered about something 205 00:12:10,320 --> 00:12:15,760 Speaker 1: preposterous that they've done or proposing, they start screaming racism, racism. 206 00:12:15,840 --> 00:12:18,360 Speaker 1: You know. It's it's like to ward off evil spirits. 207 00:12:18,400 --> 00:12:21,600 Speaker 1: It's like garlic around your neck to keep the vampire away. 208 00:12:23,200 --> 00:12:27,880 Speaker 1: What it means is, you're right, we lost, we lost 209 00:12:27,920 --> 00:12:30,960 Speaker 1: the argument. We really did a bad thing. So we're 210 00:12:30,960 --> 00:12:33,360 Speaker 1: gonna scream racism to try to make you cour and 211 00:12:33,440 --> 00:12:38,160 Speaker 1: run away. Now, Well, what Tayibi discovered and looking through 212 00:12:38,160 --> 00:12:41,360 Speaker 1: these files and he's on substack, right, John, he's a 213 00:12:41,440 --> 00:12:43,680 Speaker 1: long time reporter, and he said, although he put this 214 00:12:43,720 --> 00:12:46,160 Speaker 1: on his Twitter feed, Oh he did, Yeah, it was 215 00:12:46,360 --> 00:12:49,880 Speaker 1: it was like thirty six separate tweets. What he tried 216 00:12:49,920 --> 00:12:52,080 Speaker 1: to say was both the Trump White House and the 217 00:12:52,160 --> 00:12:55,840 Speaker 1: Biden campaign back in twenty twenty. We're constantly reaching out 218 00:12:55,880 --> 00:12:58,960 Speaker 1: to Twitter to try to get stories squashed or to 219 00:12:59,040 --> 00:13:01,320 Speaker 1: try to get the covered as they wanted. But he 220 00:13:01,360 --> 00:13:03,480 Speaker 1: said what happened in the end was because of their 221 00:13:03,520 --> 00:13:06,959 Speaker 1: political leanings most of the time the Biden administration got 222 00:13:06,960 --> 00:13:10,280 Speaker 1: favorable treatment, and clearly on this laptop story, which turned 223 00:13:10,320 --> 00:13:13,000 Speaker 1: out to be true, they were all in for squelshing 224 00:13:13,040 --> 00:13:16,080 Speaker 1: the story on behalf of the Biden campaign. Oh, these 225 00:13:16,120 --> 00:13:21,520 Speaker 1: these are leftist totalitarians and authoritarians who do not believe 226 00:13:21,600 --> 00:13:25,240 Speaker 1: in the First Amendment. And in fact, it turns out, 227 00:13:25,280 --> 00:13:28,199 Speaker 1: as as Taiebe and others have been investigating the views 228 00:13:28,280 --> 00:13:34,720 Speaker 1: of various Democratic politicians, the First Amendment is too much 229 00:13:36,640 --> 00:13:39,439 Speaker 1: and they don't want a Twitter or any social media 230 00:13:39,559 --> 00:13:43,440 Speaker 1: situation where people can really say anything they want. It's 231 00:13:43,480 --> 00:13:46,840 Speaker 1: only you say anything you want as long as they approve. 232 00:13:47,360 --> 00:13:50,800 Speaker 1: And you know, Trump is in the same basket. Over 233 00:13:50,840 --> 00:13:54,400 Speaker 1: the weekend, he thinks the Constitution should be terminated, or 234 00:13:54,440 --> 00:13:56,760 Speaker 1: some parts of it should be terminated. He actually seized 235 00:13:56,800 --> 00:13:59,640 Speaker 1: on this frighting right to say, yeah, the elections should 236 00:13:59,640 --> 00:14:02,400 Speaker 1: be we should redo the election of twenty twenty. We've 237 00:14:02,480 --> 00:14:05,360 Speaker 1: so we've got a situation now where we're two sides 238 00:14:05,800 --> 00:14:09,120 Speaker 1: of this political universe are now they either want to 239 00:14:09,120 --> 00:14:12,720 Speaker 1: shred the Constitution or cancel some of the amendments because 240 00:14:12,720 --> 00:14:16,800 Speaker 1: they're frustrated that they can't control speech, they can't control writings, 241 00:14:16,840 --> 00:14:20,120 Speaker 1: they can't control the Internet. Only certain things could be 242 00:14:20,240 --> 00:14:23,560 Speaker 1: permitted for you to say, for you to think, for 243 00:14:23,680 --> 00:14:26,200 Speaker 1: you to write. I think going forward, what we have 244 00:14:26,240 --> 00:14:28,320 Speaker 1: to learn from this is Twitter as a private entity. 245 00:14:28,400 --> 00:14:29,680 Speaker 1: You have to look at it for what it is. 246 00:14:29,720 --> 00:14:31,880 Speaker 1: It's going to be a left wing outlet, right, You're 247 00:14:31,880 --> 00:14:34,200 Speaker 1: not going to go there. If you have any other viewpoints, 248 00:14:34,520 --> 00:14:36,520 Speaker 1: then to find that kind of news feed right, just 249 00:14:36,560 --> 00:14:39,040 Speaker 1: the way it is and musk that's the way it 250 00:14:39,080 --> 00:14:41,920 Speaker 1: has been now. I mean, some Republicans are promising hearings 251 00:14:41,920 --> 00:14:45,040 Speaker 1: over this. What can they really do? I they're looking 252 00:14:45,080 --> 00:14:50,240 Speaker 1: to see if Biden's crowd put pressure, was their government 253 00:14:50,280 --> 00:14:56,240 Speaker 1: pressure on Twitter? Did the government feed them false information? Oh? 254 00:14:56,280 --> 00:15:00,200 Speaker 1: That's what they're looking for here. The woman behind all 255 00:15:00,240 --> 00:15:04,280 Speaker 1: of this is the former top lawyer at Twitter. Actually 256 00:15:05,120 --> 00:15:08,440 Speaker 1: she had a great title Policy and Trust. She was 257 00:15:08,480 --> 00:15:12,200 Speaker 1: a head of Legal Policy and Trust. So it's Vijayagadi. 258 00:15:12,640 --> 00:15:17,280 Speaker 1: It's Soviet Union, George orwell terms where what the title 259 00:15:17,360 --> 00:15:22,280 Speaker 1: says or what the agency's title is is the opposite 260 00:15:22,280 --> 00:15:29,360 Speaker 1: of reality. It's supposed to lull the ignorant people into thinking, oh, well, 261 00:15:29,360 --> 00:15:32,400 Speaker 1: look at that. They care about my trust and my safety. 262 00:15:32,640 --> 00:15:37,200 Speaker 1: No they don't. They paid her seventeen million dollars last year. Yes, yeah, 263 00:15:37,320 --> 00:15:40,680 Speaker 1: there's a lot of money to be made in prohibiting speech. Yes, 264 00:15:40,760 --> 00:15:43,760 Speaker 1: exactly there is. It's good, it's a good business. But again, 265 00:15:43,800 --> 00:15:46,160 Speaker 1: we always ask you the same question when you're looking 266 00:15:46,200 --> 00:15:48,800 Speaker 1: at this. Imagine if the tables were turned and there 267 00:15:48,840 --> 00:15:54,080 Speaker 1: was a story about Trump that some social media squelsh censored, deleted, 268 00:15:54,320 --> 00:15:57,200 Speaker 1: and we found out two years later that they did 269 00:15:57,240 --> 00:16:00,240 Speaker 1: this to help the Trumpet. Imagine all the coverage and 270 00:16:00,320 --> 00:16:03,040 Speaker 1: all the outrage. I can still hear this over either 271 00:16:03,160 --> 00:16:07,080 Speaker 1: the January sixth stuff or Trump's phone call to the 272 00:16:07,160 --> 00:16:12,520 Speaker 1: Ukrainian president. A bombshell, A bombshell, another bombomshell. That story 273 00:16:12,880 --> 00:16:15,320 Speaker 1: about the woman that was she wasn't even in the limo, 274 00:16:15,760 --> 00:16:17,920 Speaker 1: but she claims that to remember, Trump tried to grab 275 00:16:17,920 --> 00:16:21,600 Speaker 1: the steering wheel from from the Secret Service driver. She 276 00:16:21,680 --> 00:16:23,760 Speaker 1: wasn't there. She was telling a secondhand story. But that 277 00:16:23,840 --> 00:16:27,440 Speaker 1: was a bombomshell. Bombshell, Well, yeah, because it's it's to 278 00:16:27,480 --> 00:16:29,400 Speaker 1: me as a bombshell too. But it's not getting that 279 00:16:29,440 --> 00:16:32,360 Speaker 1: work because it's because the media is our partisan outfits, 280 00:16:32,840 --> 00:16:35,840 Speaker 1: their public relation arms for the administration and for the 281 00:16:35,840 --> 00:16:38,480 Speaker 1: Democratic Party. That's what they are. Now. These all the 282 00:16:38,560 --> 00:16:41,600 Speaker 1: journalists and the editors, they're all progressives. They're they're getting 283 00:16:41,600 --> 00:16:44,520 Speaker 1: younger and younger. They've come out of school, and they 284 00:16:44,600 --> 00:16:47,000 Speaker 1: believe that their way is the way that the country 285 00:16:47,000 --> 00:16:49,760 Speaker 1: should run. And they're really out to squelch other points 286 00:16:49,800 --> 00:16:54,480 Speaker 1: of view and to suppress any bad news about their 287 00:16:54,520 --> 00:16:58,720 Speaker 1: side and enhance the good news. And I still remember 288 00:16:58,720 --> 00:17:02,440 Speaker 1: in twenty sixteen, sometime right before the election they also 289 00:17:02,520 --> 00:17:04,200 Speaker 1: going to do Times admitted this. They ran this big 290 00:17:04,280 --> 00:17:06,960 Speaker 1: editorial saying that's it, the gloves are off. We're no 291 00:17:07,000 --> 00:17:09,280 Speaker 1: longer Basically, they were saying, we're no longer going to 292 00:17:09,280 --> 00:17:13,600 Speaker 1: be this impartial. No. Trump is too dangerous to our freedom, 293 00:17:13,800 --> 00:17:16,119 Speaker 1: he's too dangerous to our future. We have to now 294 00:17:16,240 --> 00:17:18,399 Speaker 1: take the opposite side on everything and only report the 295 00:17:18,480 --> 00:17:20,919 Speaker 1: damaging stuff that we can find. And this is not 296 00:17:21,000 --> 00:17:22,840 Speaker 1: about our side. We don't report that stuff. No, this 297 00:17:22,880 --> 00:17:24,960 Speaker 1: is going to continue long after Trump. Trump was the 298 00:17:25,160 --> 00:17:27,720 Speaker 1: was the excuse, here's a big catalyst for this. But yeah, 299 00:17:27,760 --> 00:17:30,200 Speaker 1: but this is the speeded up this thing. This is there. 300 00:17:32,200 --> 00:17:36,320 Speaker 1: This is their religion, this is their belief system. They 301 00:17:36,320 --> 00:17:40,720 Speaker 1: don't believe in America because at the core they believe 302 00:17:40,800 --> 00:17:45,480 Speaker 1: that America is an illegitimate nation and it was built 303 00:17:45,560 --> 00:17:51,920 Speaker 1: on racism and sexism and stealing Native American land, and 304 00:17:52,040 --> 00:17:56,840 Speaker 1: that capitalism is immoral and wrong. All of everything that 305 00:17:56,880 --> 00:18:01,000 Speaker 1: America is about is wrong. So they are their job 306 00:18:01,200 --> 00:18:04,760 Speaker 1: is to slowly, day by day brainwash the public and 307 00:18:04,880 --> 00:18:09,399 Speaker 1: definitely brainwash the new generation going to college that the 308 00:18:09,480 --> 00:18:12,840 Speaker 1: America really is a hoax and everything we know about 309 00:18:12,840 --> 00:18:17,080 Speaker 1: it is a lie. Some of the journalists went after Taihebi, Oh, yeah, 310 00:18:17,520 --> 00:18:20,600 Speaker 1: what's he doing for this nationalist billionaire putting out this 311 00:18:20,680 --> 00:18:23,320 Speaker 1: film and with the irony is he's a Bernie Sanders 312 00:18:23,400 --> 00:18:29,720 Speaker 1: guy's he's very liberal to a point where the world changed, 313 00:18:29,800 --> 00:18:33,359 Speaker 1: And he said, well, I'm not doing this. You know, 314 00:18:33,600 --> 00:18:37,119 Speaker 1: I'm not doing propaganda. I'm not lying for people. I 315 00:18:37,200 --> 00:18:40,439 Speaker 1: might have an opinion, a political point of view, a 316 00:18:40,480 --> 00:18:42,879 Speaker 1: certain writing style, but I am not going to engage 317 00:18:42,880 --> 00:18:46,520 Speaker 1: in propaganda and suppression. All right, we got more coming up. 318 00:18:46,520 --> 00:18:48,760 Speaker 1: This is the Johnny ken Shaw on kf I Am 319 00:18:48,800 --> 00:18:51,640 Speaker 1: six forty Live Everywhere on the iHeart Radio act Off 320 00:18:51,640 --> 00:18:55,720 Speaker 1: for lab Stuff. Michael Michael Schellenberger is doing a story 321 00:18:55,760 --> 00:19:01,600 Speaker 1: on this as well, and he quotes huff Is saying, 322 00:19:02,480 --> 00:19:05,000 Speaker 1: why on earth would the Chinese ever allow us into 323 00:19:05,000 --> 00:19:08,679 Speaker 1: that laboratory if they're doing bioweapons development. They have their 324 00:19:08,680 --> 00:19:11,439 Speaker 1: own program going. They do not need our money. But 325 00:19:11,600 --> 00:19:14,800 Speaker 1: what they do need is our advanced biotechnology, and they 326 00:19:14,840 --> 00:19:17,800 Speaker 1: need our training. And when I look at this at 327 00:19:17,800 --> 00:19:19,920 Speaker 1: the end of the day, this looks like an exchange 328 00:19:19,920 --> 00:19:24,720 Speaker 1: of biotechnology for access to their laboratory. In other words, 329 00:19:24,720 --> 00:19:29,520 Speaker 1: we give them our latest biotechnology and exchange for seeing 330 00:19:29,560 --> 00:19:35,200 Speaker 1: what they're doing with that virus. Well, I see. And 331 00:19:37,040 --> 00:19:40,680 Speaker 1: even the head of the World Health Organization told European 332 00:19:40,680 --> 00:19:43,679 Speaker 1: officials in June that he thinks COVID leaked from a 333 00:19:43,680 --> 00:19:49,080 Speaker 1: catastrophic accident in the laboratory. Who said that The head 334 00:19:49,119 --> 00:19:53,159 Speaker 1: of the World Health Organization told European officials in June 335 00:19:53,920 --> 00:20:01,359 Speaker 1: that he thinks it was a laboratory accident, And huff 336 00:20:01,400 --> 00:20:04,520 Speaker 1: says after he started speaking out publicly in twenty twenty 337 00:20:04,560 --> 00:20:08,360 Speaker 1: his home was burglarized. He was harassed both in person 338 00:20:09,080 --> 00:20:15,200 Speaker 1: and with drones. Yeah, so I think there's all kinds 339 00:20:15,240 --> 00:20:19,480 Speaker 1: of dark secrets, and over time people are going to talk. 340 00:20:19,720 --> 00:20:22,960 Speaker 1: You can't keep these secrets forever. I mean, We've got 341 00:20:22,960 --> 00:20:24,840 Speaker 1: more coming up Toohn and Ken Cafe. I am six 342 00:20:25,000 --> 00:20:27,920 Speaker 1: forty live everywhere the iHeartRadio app well be checking out 343 00:20:27,920 --> 00:20:31,160 Speaker 1: the Idaho murderous story with Alex Stone coming up after 344 00:20:31,200 --> 00:20:35,480 Speaker 1: the news at four o'clock. A lot of people, I 345 00:20:35,720 --> 00:20:38,639 Speaker 1: shouldn't say, a lot of people, apparently one of the 346 00:20:38,720 --> 00:20:41,240 Speaker 1: fathers one of the girls who was murdered in that 347 00:20:41,359 --> 00:20:45,720 Speaker 1: off campus house at the University of Idaho as leading 348 00:20:45,760 --> 00:20:48,280 Speaker 1: the way in terms of speaking out. He's beginning to 349 00:20:48,320 --> 00:20:51,520 Speaker 1: have doubts about the police investigation. He's hired his own 350 00:20:51,880 --> 00:20:55,520 Speaker 1: private investigator. Is very frustrated. Said a few other things 351 00:20:55,520 --> 00:20:59,320 Speaker 1: too about the murders itself, which are interesting if true. 352 00:20:59,640 --> 00:21:01,679 Speaker 1: Will talk to Alex about this and more coming up 353 00:21:01,720 --> 00:21:05,600 Speaker 1: after the news at four o'clock. Well, here's a story 354 00:21:05,600 --> 00:21:08,960 Speaker 1: that just never goes away. After nearly three years. And 355 00:21:09,000 --> 00:21:11,440 Speaker 1: by the way, John, do you know that I think 356 00:21:11,600 --> 00:21:15,320 Speaker 1: next week, maybe even sooner, it'll be exactly three years 357 00:21:15,320 --> 00:21:17,920 Speaker 1: since the John and Ken Show first mentioned what would 358 00:21:17,920 --> 00:21:21,800 Speaker 1: turn out to be the coronavirus. Oh, yeah, December of 359 00:21:21,800 --> 00:21:24,399 Speaker 1: twenty nineteen, we started reading stories about something going on 360 00:21:24,440 --> 00:21:27,080 Speaker 1: in China for the virus, and then we talked about Wuhan, 361 00:21:27,200 --> 00:21:29,480 Speaker 1: and well, we know what that turned into, don't we. 362 00:21:30,560 --> 00:21:33,240 Speaker 1: A few months later the whole nation which was locked down. 363 00:21:34,400 --> 00:21:39,440 Speaker 1: Andrew Huff has emerged. Andrew Huff has got a brand 364 00:21:39,440 --> 00:21:43,520 Speaker 1: new book, The Truth about Wuhan. How I uncovered the 365 00:21:43,520 --> 00:21:48,239 Speaker 1: biggest lie in history. Andrew Huff used to be an 366 00:21:48,240 --> 00:21:52,120 Speaker 1: employee of Eco Health Alliance. Now, if you don't remember, 367 00:21:52,200 --> 00:21:55,800 Speaker 1: John will tell you who Eco Health Alliance is. Eco 368 00:21:55,880 --> 00:22:01,120 Speaker 1: Health Alliance was this medical organization that got major funding 369 00:22:01,760 --> 00:22:07,040 Speaker 1: from n Yeah, but of health, which is run by 370 00:22:07,200 --> 00:22:11,840 Speaker 1: Anthony Faucci. It was YEA and and Faucci would direct 371 00:22:11,960 --> 00:22:16,680 Speaker 1: these financial grants to these healthcare companies to do research. 372 00:22:17,080 --> 00:22:20,560 Speaker 1: So this was your tax money. This was Washington, DC 373 00:22:20,760 --> 00:22:23,919 Speaker 1: tax money that ended up with Eco Health Alliance. Eco 374 00:22:24,040 --> 00:22:27,320 Speaker 1: Health then sent it to the Wuhan lab. Yeah, they 375 00:22:27,320 --> 00:22:31,200 Speaker 1: were like the middleman involved with the funding. Here. Now, Hoff, 376 00:22:31,400 --> 00:22:33,960 Speaker 1: we should tell you this was never at the lab 377 00:22:33,960 --> 00:22:36,440 Speaker 1: in Wuhan. And that's the company actually put out a 378 00:22:36,440 --> 00:22:39,000 Speaker 1: statement this afternoon about the book. He was there from 379 00:22:39,040 --> 00:22:42,359 Speaker 1: twenty fourteen to twenty sixteen. You can imagine what he's 380 00:22:42,400 --> 00:22:45,320 Speaker 1: calling the biggest lie in history is that the pandemic 381 00:22:45,760 --> 00:22:49,200 Speaker 1: was the result of a lab leak and not something 382 00:22:49,359 --> 00:22:54,119 Speaker 1: from what they called a zoonotic origin and transferred to humans. 383 00:22:54,160 --> 00:22:56,840 Speaker 1: Yet no, they they've never found any animals that had 384 00:22:56,880 --> 00:23:02,480 Speaker 1: this particular coronavirus strain since the outbreak from the lab 385 00:23:02,840 --> 00:23:07,160 Speaker 1: and found one because he didn't happen that way. And 386 00:23:07,920 --> 00:23:11,520 Speaker 1: there's an ample reason for all the governments to cover 387 00:23:11,600 --> 00:23:14,720 Speaker 1: this up because the Chinese government was involved in this, 388 00:23:14,880 --> 00:23:17,439 Speaker 1: and so is the US government. We were financing it. 389 00:23:17,960 --> 00:23:20,800 Speaker 1: And that's one of the reasons that outside of Trump, 390 00:23:20,880 --> 00:23:28,240 Speaker 1: who's always you know, I always an independent right, he 391 00:23:28,320 --> 00:23:32,800 Speaker 1: doesn't align with anybody, he would go after China and 392 00:23:32,840 --> 00:23:34,760 Speaker 1: everybody would say, no, you can't do that. It's racist, 393 00:23:34,840 --> 00:23:38,240 Speaker 1: it's racist. You can't mention China again. And anytime anyone 394 00:23:38,240 --> 00:23:41,480 Speaker 1: in the media, anybody publicly started talking about the Chinese lab, 395 00:23:41,880 --> 00:23:44,879 Speaker 1: you were shut down as a conspiracy theorist. In fact, 396 00:23:44,920 --> 00:23:47,880 Speaker 1: if I'm correct, I think that Facebook and Twitter was 397 00:23:48,160 --> 00:23:52,600 Speaker 1: blocking posts or labeling posts as misinformation. If you talked 398 00:23:52,640 --> 00:23:56,119 Speaker 1: about this coming from the Chinese lab. Oh, there are 399 00:23:56,200 --> 00:23:58,600 Speaker 1: lots of government operatives who are out there urging them 400 00:23:58,600 --> 00:24:01,520 Speaker 1: to do that, including I think a guy who used 401 00:24:01,560 --> 00:24:04,800 Speaker 1: to be with this Eco Help alliance. Well he was, yeah, 402 00:24:04,840 --> 00:24:10,919 Speaker 1: the guy Dan Zach. He was the one who not 403 00:24:11,160 --> 00:24:15,480 Speaker 1: only directed the money from Fauci through Eco Health and 404 00:24:15,520 --> 00:24:18,960 Speaker 1: then onto Wuhan, but he was the first one to 405 00:24:19,160 --> 00:24:22,600 Speaker 1: put out the story that this jumped from a bat 406 00:24:22,640 --> 00:24:26,159 Speaker 1: at the wet market, or it's the bat that jumped 407 00:24:26,160 --> 00:24:30,479 Speaker 1: to the pango. It that that whole complicated scenario, and 408 00:24:30,520 --> 00:24:33,960 Speaker 1: so he pushed it hard, and he got a whole 409 00:24:33,960 --> 00:24:36,960 Speaker 1: bunch of scientists that he was friends with to sign 410 00:24:37,160 --> 00:24:42,960 Speaker 1: an official letter, an open letter to the public, which 411 00:24:42,960 --> 00:24:45,879 Speaker 1: they had published, which explained that this was not a 412 00:24:45,960 --> 00:24:50,000 Speaker 1: lab league, that this was from an animal. Much the 413 00:24:50,119 --> 00:24:52,000 Speaker 1: same way that I remember I mentioned the other day 414 00:24:52,040 --> 00:24:54,880 Speaker 1: there were fifty one people who worked with the CIA 415 00:24:54,920 --> 00:24:58,520 Speaker 1: and other intelligence agencies who got together and said that 416 00:24:59,080 --> 00:25:05,080 Speaker 1: the that the Hunter Biden laptop was Russian disinformation. This 417 00:25:05,160 --> 00:25:09,800 Speaker 1: is actually a tactic now that governments use people who 418 00:25:10,080 --> 00:25:13,040 Speaker 1: work in government or are connected to government. What they 419 00:25:13,240 --> 00:25:16,280 Speaker 1: do is you get the official letter. You get thirty 420 00:25:16,359 --> 00:25:19,200 Speaker 1: or forty or fifty or one hundred like minded people, 421 00:25:20,600 --> 00:25:22,760 Speaker 1: and they all go along because they all want to 422 00:25:22,760 --> 00:25:26,480 Speaker 1: get the research grants. Right. You can't be a free agent, 423 00:25:26,520 --> 00:25:29,240 Speaker 1: you can't act like Trump. You have to fall into 424 00:25:29,280 --> 00:25:31,919 Speaker 1: line if you want future money. So you sign the paper, 425 00:25:32,040 --> 00:25:33,639 Speaker 1: they publish it, they take an ad out in the 426 00:25:33,640 --> 00:25:37,600 Speaker 1: New York Times, whatever, and now you have the official story, 427 00:25:37,680 --> 00:25:39,679 Speaker 1: and if you speak out against it, it's like, I 428 00:25:39,680 --> 00:25:42,159 Speaker 1: don't know, there's a hundred scientists here. You say you 429 00:25:42,200 --> 00:25:44,719 Speaker 1: know more than these hundred scientists. You say you know 430 00:25:44,840 --> 00:25:48,760 Speaker 1: more than these fifty CIA officials. You see how it works. 431 00:25:49,720 --> 00:25:52,880 Speaker 1: So at the center of this again is what's called 432 00:25:52,920 --> 00:25:58,600 Speaker 1: gain a function research GoF and these are designed in 433 00:25:58,720 --> 00:26:02,280 Speaker 1: labs to figure out what they can do with the virus, 434 00:26:02,359 --> 00:26:04,920 Speaker 1: in some cases, to make it more potent, in some way, 435 00:26:04,960 --> 00:26:10,800 Speaker 1: to alter it. Now what the company Eco Alliance put 436 00:26:10,840 --> 00:26:13,840 Speaker 1: out today, I had not seen this story before, but 437 00:26:13,880 --> 00:26:17,359 Speaker 1: they put out a statement over a year ago saying 438 00:26:17,400 --> 00:26:20,720 Speaker 1: that the particular grant money that was sent from Eco 439 00:26:20,760 --> 00:26:24,119 Speaker 1: Health Alliance to the Wuhan Lab, and they said they 440 00:26:24,160 --> 00:26:27,080 Speaker 1: provided proof of this from the lab, that it was 441 00:26:27,320 --> 00:26:33,000 Speaker 1: done on coronavirus studies that were genetically far distant from 442 00:26:33,080 --> 00:26:35,639 Speaker 1: SARS cove two, which is what we ended up with. 443 00:26:37,320 --> 00:26:40,200 Speaker 1: Whatever they were. When I read this today, this statement, 444 00:26:40,600 --> 00:26:42,600 Speaker 1: the one thing I got from it is that, well, 445 00:26:43,000 --> 00:26:47,480 Speaker 1: it may not have been our grant money that resulted 446 00:26:47,840 --> 00:26:50,720 Speaker 1: in research at the Wuhan lab that resulted in the 447 00:26:50,760 --> 00:26:53,480 Speaker 1: coronavirus that leaked. It could have been some other money 448 00:26:53,520 --> 00:26:55,840 Speaker 1: that they got, the Chinese money. They're just trying to 449 00:26:55,880 --> 00:26:59,560 Speaker 1: say it certainly didn't come from our particular grant money 450 00:26:59,600 --> 00:27:02,840 Speaker 1: from NIH. I mean, clearly there are other sources that 451 00:27:02,920 --> 00:27:06,199 Speaker 1: this lab was funded, or they're just completely funded by 452 00:27:06,240 --> 00:27:08,919 Speaker 1: just NIH money, or they're just trying to confuse the issue. 453 00:27:09,000 --> 00:27:14,639 Speaker 1: They're trying to misdirect people. I mean, what Huff is 454 00:27:14,680 --> 00:27:18,399 Speaker 1: saying is that the Eco Health Alliance was working with 455 00:27:18,440 --> 00:27:21,719 Speaker 1: the Wuhan Lab on gain a function research with the 456 00:27:21,760 --> 00:27:25,800 Speaker 1: support of the US government, and he soon realized the 457 00:27:25,880 --> 00:27:29,280 Speaker 1: virus would never occur in nature and had been developed. 458 00:27:30,400 --> 00:27:33,800 Speaker 1: It had been developed into a much more powerful pathogen 459 00:27:34,000 --> 00:27:40,479 Speaker 1: in the lab, genetically engineered in Wuhan through funding by 460 00:27:40,520 --> 00:27:45,120 Speaker 1: the US government. Now, Huff was never at the lab 461 00:27:45,119 --> 00:27:47,800 Speaker 1: in Wuhan. I don't think he says that either, But 462 00:27:47,960 --> 00:27:50,000 Speaker 1: that's what the company is saying. He was never assigned there, 463 00:27:50,000 --> 00:27:55,640 Speaker 1: he didn't have any direct work there, But yes, that's 464 00:27:55,640 --> 00:27:59,720 Speaker 1: what they do. All I'm trying to say is the 465 00:27:59,760 --> 00:28:03,640 Speaker 1: other response from Eco Health Alliances at seventy five when 466 00:28:03,640 --> 00:28:07,960 Speaker 1: these viruses emerged. They do come from animal to human transmission. 467 00:28:08,640 --> 00:28:13,040 Speaker 1: They're relatively rarely like lab leak stuff or lab stuff. 468 00:28:14,560 --> 00:28:17,119 Speaker 1: Michael Schellenberger is doing a story on this as well, 469 00:28:18,119 --> 00:28:23,880 Speaker 1: and he quotes huff Is saying, why on earth would 470 00:28:23,880 --> 00:28:27,240 Speaker 1: the Chinese ever allow us into that laboratory If they're 471 00:28:27,280 --> 00:28:30,480 Speaker 1: doing bioweapons development, they have their own program going. They 472 00:28:30,480 --> 00:28:33,120 Speaker 1: do not need our money. But what they do need 473 00:28:33,280 --> 00:28:37,199 Speaker 1: is our advanced biotechnology, and they need our training. And 474 00:28:37,320 --> 00:28:39,120 Speaker 1: when I look at this at the end of the day, 475 00:28:39,160 --> 00:28:43,040 Speaker 1: this looks like an exchange of biotechnology for access to 476 00:28:43,200 --> 00:28:46,800 Speaker 1: their laboratory. In other words, we give them our latest 477 00:28:46,960 --> 00:28:51,800 Speaker 1: biotechnology and exchange for seeing what they're doing with that virus. 478 00:28:52,760 --> 00:28:58,920 Speaker 1: Oh I see. And even the head of the World 479 00:28:58,960 --> 00:29:03,240 Speaker 1: Health Organization told European officials in June that he thinks 480 00:29:03,320 --> 00:29:07,720 Speaker 1: COVID leaked from a catastrophic accident in the laboratory, who 481 00:29:07,760 --> 00:29:12,080 Speaker 1: said that the head of the World Health Organization told 482 00:29:12,160 --> 00:29:15,280 Speaker 1: European officials in June that he thinks it was a 483 00:29:15,360 --> 00:29:23,760 Speaker 1: laboratory accident, and huff says after he started speaking out 484 00:29:23,800 --> 00:29:27,040 Speaker 1: publicly in twenty twenty, his home was burglarized. He was 485 00:29:27,160 --> 00:29:34,880 Speaker 1: harassed both in person and with drones. Yeah, so I 486 00:29:34,920 --> 00:29:39,080 Speaker 1: think there's all kinds of dark secrets, and over time 487 00:29:39,120 --> 00:29:41,840 Speaker 1: people are going to talk. You can't keep these secrets forever. 488 00:29:42,680 --> 00:29:44,880 Speaker 1: I mean, we've got more coming up town in ken Cafe. 489 00:29:44,880 --> 00:29:47,440 Speaker 1: I am six forty live everywhere the iHeartRadio app. But 490 00:29:47,560 --> 00:29:50,959 Speaker 1: one of the parents of the four students who were 491 00:29:51,040 --> 00:29:54,560 Speaker 1: murdered at that off campus house in Idaho University of 492 00:29:54,560 --> 00:29:58,240 Speaker 1: Idaho students is speaking more than anybody else involved in 493 00:29:58,320 --> 00:30:01,880 Speaker 1: the story. His name is Stephen gun Kelvis, and we're 494 00:30:01,880 --> 00:30:04,560 Speaker 1: going to find out more from Alex Stone after the 495 00:30:04,560 --> 00:30:06,800 Speaker 1: news at four o'clock. He now has some doubts about 496 00:30:06,840 --> 00:30:11,440 Speaker 1: the investigation might be involving private investigators. He said some 497 00:30:11,520 --> 00:30:15,040 Speaker 1: things too about the murders, the methods, all of that. 498 00:30:15,400 --> 00:30:18,280 Speaker 1: The developments that we have today in that story are 499 00:30:18,320 --> 00:30:22,000 Speaker 1: coming up after the news at four o'clock. Well, when 500 00:30:22,000 --> 00:30:26,520 Speaker 1: I looked at this story, I said, why can't millionaires 501 00:30:26,520 --> 00:30:35,120 Speaker 1: collect unemployment? The headline is nineteen thousand millionaires collected unemployment 502 00:30:35,200 --> 00:30:40,080 Speaker 1: during the pandemic. Well, somebody who makes that much income 503 00:30:40,120 --> 00:30:42,440 Speaker 1: could be laid off. But I guess the feeling is 504 00:30:43,440 --> 00:30:48,600 Speaker 1: they should have the assets behind them to weather an 505 00:30:48,680 --> 00:30:52,560 Speaker 1: unemployment period and I have to rely on a government check. 506 00:30:53,440 --> 00:30:56,480 Speaker 1: Of course, just because you make a million dollars doesn't 507 00:30:56,480 --> 00:30:58,720 Speaker 1: mean you didn't spend a million dollars. I don't have 508 00:30:58,760 --> 00:31:01,560 Speaker 1: a lot of saving. It also doesn't matter what you 509 00:31:01,600 --> 00:31:05,960 Speaker 1: did with your money. You're American citizen, your taxpayer, and 510 00:31:06,000 --> 00:31:08,200 Speaker 1: we're all entitled to the same rights and the same 511 00:31:08,240 --> 00:31:11,080 Speaker 1: access to benefits. Yeah, they paid into the system, and 512 00:31:11,080 --> 00:31:15,520 Speaker 1: if they got laid off and they otherwise qualify for unemployment, 513 00:31:15,600 --> 00:31:19,520 Speaker 1: then but that was a story. Here. There's a senator 514 00:31:19,640 --> 00:31:24,920 Speaker 1: from Iowa, Joanie Ernst, who back in twenty twenty, she 515 00:31:25,000 --> 00:31:27,840 Speaker 1: tried to draw attention to the likelihood that millionaires would 516 00:31:27,840 --> 00:31:31,280 Speaker 1: get unemployment benefits, particularly galling to see them collect money 517 00:31:31,280 --> 00:31:33,680 Speaker 1: while so many lower wage workers were still on the 518 00:31:33,760 --> 00:31:37,320 Speaker 1: job and paying taxes to fund the system. Well, I 519 00:31:37,400 --> 00:31:39,160 Speaker 1: look at that, I said, they got laid off, they 520 00:31:39,160 --> 00:31:43,080 Speaker 1: got laid off. It's not like it's legal. They're trying 521 00:31:43,120 --> 00:31:47,440 Speaker 1: to make it illegal. In fact, they did. The Senate 522 00:31:47,440 --> 00:31:49,720 Speaker 1: passed to build in twenty eleven one hundred to zero, 523 00:31:49,840 --> 00:31:52,800 Speaker 1: but it never got its way through the House. They 524 00:31:52,920 --> 00:31:56,800 Speaker 1: just didn't take up the legislation, so it never became law. 525 00:31:56,960 --> 00:32:00,320 Speaker 1: This was after the two thousand and eight recession. Yeah, yeah, 526 00:32:00,360 --> 00:32:02,760 Speaker 1: this is This is in the cheap headline category for 527 00:32:04,520 --> 00:32:07,240 Speaker 1: it isn't she I see her name on a list 528 00:32:07,240 --> 00:32:10,680 Speaker 1: of people to run for president too. Oh she is. Yeah, 529 00:32:10,720 --> 00:32:12,560 Speaker 1: she's been ruined. Do you think this is a populous 530 00:32:12,640 --> 00:32:17,040 Speaker 1: stance to take? Yeah, exactly. Millionaires are in this title 531 00:32:17,080 --> 00:32:21,080 Speaker 1: to unemployment payments because a nineteen sixty four Labor Department 532 00:32:21,120 --> 00:32:23,680 Speaker 1: ruling said that states could not impose a means tests 533 00:32:24,160 --> 00:32:28,680 Speaker 1: on programs beneficial. If she was serious, she would close 534 00:32:28,880 --> 00:32:32,960 Speaker 1: the incredible number of loopholes that wealthy people have so 535 00:32:33,000 --> 00:32:35,240 Speaker 1: that they pay very little in taxes. And we've heard 536 00:32:35,280 --> 00:32:38,080 Speaker 1: all the stories about how little somebody like Elon Musk 537 00:32:38,160 --> 00:32:41,160 Speaker 1: or Jeff Bezos pays and sat taxes or Trump pays 538 00:32:41,160 --> 00:32:44,200 Speaker 1: in taxes. And all those loopholes are legal. They take 539 00:32:44,240 --> 00:32:48,240 Speaker 1: advantage of them, and sometimes they don't pay anything at tax. Yeah, 540 00:32:48,240 --> 00:32:50,680 Speaker 1: a lot of those loopholes. There's incentives in there for 541 00:32:50,760 --> 00:32:54,760 Speaker 1: businessmen to do things, and they benefit from those rules 542 00:32:54,760 --> 00:32:58,920 Speaker 1: and laws because supposedly it actually, you know, expands the economy. 543 00:32:59,000 --> 00:33:00,920 Speaker 1: That's why a lot of those things. Often though, there's 544 00:33:00,920 --> 00:33:03,680 Speaker 1: also special interest in lobbying efforts to get those loopholes 545 00:33:03,720 --> 00:33:07,160 Speaker 1: in there, and those deductions and those exemptions and things 546 00:33:07,160 --> 00:33:12,800 Speaker 1: like that that rich people take advantage of. So get 547 00:33:13,160 --> 00:33:16,880 Speaker 1: it says here that millionaires were eligible to sign up 548 00:33:16,880 --> 00:33:20,520 Speaker 1: when Congress expanded unemployment benefits at the start of the coronavirus. 549 00:33:21,040 --> 00:33:23,480 Speaker 1: That's the spring of twenty twenty, and that's when they 550 00:33:23,480 --> 00:33:26,880 Speaker 1: gave the six hundred dollars a week extra to whatever 551 00:33:27,000 --> 00:33:31,040 Speaker 1: the state was paying. So I mean the millionaires pay 552 00:33:31,120 --> 00:33:35,560 Speaker 1: extraordinary amounts of taxes. You're in the thirty nine and 553 00:33:35,560 --> 00:33:39,480 Speaker 1: a half percent tax Brackett if you're earning a million 554 00:33:39,520 --> 00:33:42,040 Speaker 1: dollars a year, So that means every dollar you make 555 00:33:42,280 --> 00:33:44,120 Speaker 1: and I forget what the cutoff point is, I think 556 00:33:44,120 --> 00:33:47,120 Speaker 1: two hundred and fifty thousand, So every dollar pass that 557 00:33:47,520 --> 00:33:51,760 Speaker 1: you're given about forty cents to the government. So here's 558 00:33:51,800 --> 00:33:54,600 Speaker 1: one time that the government basically shut down the world, 559 00:33:54,760 --> 00:33:58,240 Speaker 1: and you're getting a small amount back. I mean, these 560 00:33:58,280 --> 00:34:00,800 Speaker 1: people pay if you make a million dollars, paying hundreds 561 00:34:00,840 --> 00:34:04,440 Speaker 1: of thousands of dollars in federal taxes every year. Right, 562 00:34:04,600 --> 00:34:09,840 Speaker 1: So spare me the outrage. So her bill would require 563 00:34:09,960 --> 00:34:12,719 Speaker 1: anyone applying for an employment benefits to a test that 564 00:34:12,800 --> 00:34:17,600 Speaker 1: they fall below her one million dollar threshold of adjusted 565 00:34:17,640 --> 00:34:22,280 Speaker 1: gross income. It would have to clear the Democrat controlled Senate, 566 00:34:23,120 --> 00:34:25,719 Speaker 1: and then it would also have to clear the Finance Committee. 567 00:34:27,640 --> 00:34:29,719 Speaker 1: As I said, they did pass something like this back 568 00:34:29,719 --> 00:34:32,640 Speaker 1: in twenty eleven and it never got taken up by 569 00:34:32,680 --> 00:34:34,239 Speaker 1: the House. They're going to run out of time in 570 00:34:34,280 --> 00:34:38,920 Speaker 1: a few days, everyone is you notice notice there. You're 571 00:34:38,920 --> 00:34:41,439 Speaker 1: gonna see all kinds of crazy ideas unleashed in this 572 00:34:41,480 --> 00:34:44,600 Speaker 1: final month. Oh yeah, kind of lame duck session. This 573 00:34:44,680 --> 00:34:46,719 Speaker 1: lame duck session. And they're going to run out of 574 00:34:46,719 --> 00:34:49,960 Speaker 1: time very soon. And then first week in January, you 575 00:34:50,000 --> 00:34:52,799 Speaker 1: have the new Congress, and the Republicans in the new 576 00:34:52,800 --> 00:34:55,080 Speaker 1: Congress in the House are not going to be pushing 577 00:34:55,120 --> 00:35:00,200 Speaker 1: for blocking millionaires from collecting unemployment. That's not to be 578 00:35:00,239 --> 00:35:03,640 Speaker 1: a priority. She's she's doing the news to me here, 579 00:35:03,640 --> 00:35:05,560 Speaker 1: getting a cheap headline and a piece on this some 580 00:35:05,680 --> 00:35:09,840 Speaker 1: years back, The Atlantic said, in some cases it's couples 581 00:35:10,080 --> 00:35:13,720 Speaker 1: filing joint returns. One spouse does have a million dollar income, 582 00:35:13,760 --> 00:35:15,879 Speaker 1: but the other one is unemployed and may probably made 583 00:35:15,920 --> 00:35:18,400 Speaker 1: a lot less. But you see, collectively they look like 584 00:35:18,480 --> 00:35:20,960 Speaker 1: millionaires on paper. I mean they are from his income 585 00:35:21,040 --> 00:35:24,160 Speaker 1: or her income. But you know, there's a misconception that 586 00:35:24,280 --> 00:35:27,040 Speaker 1: I don't understand. Everybody's happy when the millionaires pay the 587 00:35:27,040 --> 00:35:30,760 Speaker 1: exorbitant taxes that they pay, right, everybody's happy when they pay, 588 00:35:30,840 --> 00:35:33,799 Speaker 1: but they get a few pennies back, and suddenly this 589 00:35:33,880 --> 00:35:36,359 Speaker 1: is the biggest crime of the centuries. I get out 590 00:35:36,360 --> 00:35:39,479 Speaker 1: of here, all right. When we return, we'll be talking 591 00:35:39,480 --> 00:35:44,239 Speaker 1: to Alex Stone, ABC News for KFI. The two surviving 592 00:35:44,320 --> 00:35:48,200 Speaker 1: roommates and that attack in Idaho that killed four people 593 00:35:48,640 --> 00:35:51,640 Speaker 1: have put out a statement. There's also stuff coming from 594 00:35:51,680 --> 00:35:54,120 Speaker 1: the father of one of the murder victims that her 595 00:35:54,200 --> 00:35:57,359 Speaker 1: stab wounds his daughter stab wounds were more severe than 596 00:35:57,400 --> 00:36:00,799 Speaker 1: the others, indicating maybe something We'll talk to Alex. Coming up. 597 00:36:00,840 --> 00:36:03,400 Speaker 1: Johnny Ken KF I AM six D forty Live everywhere, 598 00:36:03,440 --> 00:36:05,640 Speaker 1: the iHeartRadio app at Debra Mark Live in the twenty 599 00:36:05,640 --> 00:36:06,759 Speaker 1: four hour kf I news Room