1 00:00:03,840 --> 00:00:09,960 Speaker 1: It's that time, time, time, time, Luck and load. 2 00:00:11,119 --> 00:00:12,960 Speaker 2: Michael Very Show is. 3 00:00:12,840 --> 00:00:13,440 Speaker 3: On the air. 4 00:00:19,400 --> 00:00:19,599 Speaker 1: Hey. 5 00:00:19,680 --> 00:00:22,640 Speaker 3: Montana is the mother of a seventeen year old high 6 00:00:22,680 --> 00:00:27,880 Speaker 3: school girl in Pittsburgh. She said they registered her daughter 7 00:00:27,920 --> 00:00:30,680 Speaker 3: to vote at school and told her who to vote for. 8 00:00:31,760 --> 00:00:35,199 Speaker 2: And I'll give you a hint who that was? Uh 9 00:00:35,440 --> 00:00:36,519 Speaker 2: not Donald Trump? 10 00:00:39,240 --> 00:00:41,920 Speaker 4: Before I started this video, I'm going to say this 11 00:00:42,080 --> 00:00:45,640 Speaker 4: is a personal experience of minds, something me and my 12 00:00:45,760 --> 00:00:49,239 Speaker 4: daughter is dealing with. And I have proof just in 13 00:00:49,280 --> 00:00:52,920 Speaker 4: case my video is deleted for new reason. I just 14 00:00:52,960 --> 00:00:56,560 Speaker 4: want to put that out there. Today. My seventeen year 15 00:00:56,600 --> 00:00:59,160 Speaker 4: old daughter was pulled at a class and was told 16 00:00:59,240 --> 00:00:59,880 Speaker 4: she needed. 17 00:00:59,680 --> 00:01:01,520 Speaker 2: To runch to vote. 18 00:01:01,800 --> 00:01:06,880 Speaker 4: Not only what she told how to register, she was 19 00:01:06,959 --> 00:01:09,399 Speaker 4: told who she should vote for. 20 00:01:09,720 --> 00:01:11,040 Speaker 2: And these are her words. 21 00:01:11,319 --> 00:01:13,360 Speaker 4: And I'm going to upload proof at the end of 22 00:01:13,360 --> 00:01:15,800 Speaker 4: this video, and I'm coming with ports to the morrow 23 00:01:16,480 --> 00:01:19,520 Speaker 4: because why them what y'all pull my daughter out of 24 00:01:19,560 --> 00:01:22,679 Speaker 4: glass selling her who to vote for. I am her 25 00:01:22,760 --> 00:01:26,320 Speaker 4: mother and I have yet to have this conversation with 26 00:01:26,400 --> 00:01:30,559 Speaker 4: her about the upcoming election. I have not said any 27 00:01:30,600 --> 00:01:33,800 Speaker 4: consent forms telling y'all that my daughter can register to 28 00:01:33,920 --> 00:01:38,240 Speaker 4: vote at school. I'm gonna just jump right into these screenshots. 29 00:01:39,360 --> 00:01:44,040 Speaker 4: That's just it, because y'all played with the wrong mom. 30 00:01:44,160 --> 00:01:48,560 Speaker 4: Here's the first page. I'm gonna leave this one for 31 00:01:48,640 --> 00:01:52,040 Speaker 4: a couple of seconds so y'all can read it, talking 32 00:01:52,080 --> 00:01:55,320 Speaker 4: about pissed selling my daughter who. 33 00:01:55,200 --> 00:01:55,680 Speaker 5: To vote for. 34 00:01:56,360 --> 00:01:56,840 Speaker 6: You're right. 35 00:01:57,880 --> 00:02:04,640 Speaker 4: Here's the second page. This is what we're going We're 36 00:02:04,680 --> 00:02:09,959 Speaker 4: going to Pittsburgh public high schools telling children who to 37 00:02:10,040 --> 00:02:15,120 Speaker 4: vote for. Let's make this make sense. I have never 38 00:02:15,160 --> 00:02:18,000 Speaker 4: seen it like this in my life. I have never 39 00:02:18,040 --> 00:02:21,960 Speaker 4: seen it. This is just like disgusting at this point. 40 00:02:22,480 --> 00:02:28,240 Speaker 3: MSNBC's Alex Wagner hosted a union town hall in Michigan, 41 00:02:28,240 --> 00:02:31,760 Speaker 3: where she was surprised to find out that the union 42 00:02:31,840 --> 00:02:37,040 Speaker 3: workers in Michigan, they don't care about January sixth, You 43 00:02:37,200 --> 00:02:38,680 Speaker 3: insider media people. 44 00:02:39,360 --> 00:02:42,320 Speaker 2: They don't give a damn about it. They don't even 45 00:02:42,360 --> 00:02:43,360 Speaker 2: know what day it is. 46 00:02:44,639 --> 00:02:49,040 Speaker 3: They care about our country collapsing, inflation, the economy, illegal immigration, 47 00:02:49,160 --> 00:02:52,520 Speaker 3: and crime. See only the media care about January sixth, 48 00:02:52,520 --> 00:02:55,240 Speaker 3: and not because they care about January sixth. They thought 49 00:02:55,280 --> 00:02:56,640 Speaker 3: that's how they were going to take Trump. 50 00:02:56,680 --> 00:02:57,400 Speaker 2: Now, listen to this. 51 00:02:57,840 --> 00:02:59,799 Speaker 6: Talk to me about your level of interest in a 52 00:03:00,200 --> 00:03:01,639 Speaker 6: the criminal charges and. 53 00:03:01,600 --> 00:03:06,600 Speaker 1: So forth, uh, February sixth, January six So. 54 00:03:06,600 --> 00:03:09,720 Speaker 2: I remember that day. I know he was the standing president. 55 00:03:11,520 --> 00:03:13,919 Speaker 3: I'm not familiar with the chargers they are getting brought 56 00:03:13,919 --> 00:03:14,680 Speaker 3: against him for that. 57 00:03:14,760 --> 00:03:18,160 Speaker 1: I don't I'm not following that charge for the you know, 58 00:03:18,200 --> 00:03:19,440 Speaker 1: there's multiple court cases going on. 59 00:03:19,480 --> 00:03:20,400 Speaker 2: I'm just not familiar with it. 60 00:03:20,680 --> 00:03:22,400 Speaker 6: I mean, that doesn't sound like it's going to be 61 00:03:22,400 --> 00:03:25,320 Speaker 6: a factor in deciding who to vote for. No, Okay, 62 00:03:25,400 --> 00:03:27,840 Speaker 6: so when I when I say January sixth, what do 63 00:03:27,880 --> 00:03:28,240 Speaker 6: you think? 64 00:03:28,440 --> 00:03:28,560 Speaker 7: Oh? 65 00:03:28,600 --> 00:03:30,280 Speaker 2: I just remember seeing it on the news, like all 66 00:03:30,320 --> 00:03:32,000 Speaker 2: the riots and stuff. Don't really know what it was 67 00:03:32,000 --> 00:03:34,120 Speaker 2: about or what happened though, did it? 68 00:03:34,200 --> 00:03:35,560 Speaker 6: I mean, how did it make you feel when you 69 00:03:35,560 --> 00:03:35,920 Speaker 6: saw it? 70 00:03:36,320 --> 00:03:36,520 Speaker 7: Oh? 71 00:03:36,600 --> 00:03:36,960 Speaker 3: I don't know. 72 00:03:37,000 --> 00:03:38,360 Speaker 2: I don't really feel any way about it. 73 00:03:38,400 --> 00:03:38,720 Speaker 3: I don't. 74 00:03:39,480 --> 00:03:43,040 Speaker 2: I mean, people showed their emotion. I guess probably in 75 00:03:43,080 --> 00:03:46,560 Speaker 2: the wrong way, but it happened. Here's a secret for you, Alex. 76 00:03:46,680 --> 00:03:49,160 Speaker 3: Most Americans don't care about January sixth because they know 77 00:03:49,240 --> 00:03:52,160 Speaker 3: it's a hoax. They're smarter than you give them credit 78 00:03:52,200 --> 00:03:56,040 Speaker 3: for being. People see through what you've done. They watched 79 00:03:56,080 --> 00:03:59,920 Speaker 3: Antifa and BLM riot and burn cities to the ground 80 00:04:00,960 --> 00:04:03,280 Speaker 3: while you and your colleague standing in front of the 81 00:04:03,320 --> 00:04:08,800 Speaker 3: fire called it mostly peaceful protests. Then some little old 82 00:04:08,840 --> 00:04:14,360 Speaker 3: ladies are walking through the Capitol and the Capitol police 83 00:04:14,400 --> 00:04:17,480 Speaker 3: are walking along to and you call it the worst 84 00:04:17,480 --> 00:04:23,320 Speaker 3: attack on American soil in our history. People know better, 85 00:04:24,360 --> 00:04:30,480 Speaker 3: people understand what's going on. Here's a perfect example of 86 00:04:30,520 --> 00:04:33,240 Speaker 3: how quote fact checking by the media goes in one 87 00:04:33,279 --> 00:04:35,640 Speaker 3: direction and only one direction. 88 00:04:36,200 --> 00:04:39,200 Speaker 2: We watched the debate. We watch what David Muir did. 89 00:04:39,360 --> 00:04:41,000 Speaker 2: We watched exactly what they did. 90 00:04:42,160 --> 00:04:44,520 Speaker 3: Kamala Harris tells the story of a woman who bled 91 00:04:44,560 --> 00:04:47,960 Speaker 3: out outside of a hospital because they wouldn't perform a 92 00:04:48,000 --> 00:04:50,680 Speaker 3: life saving abortion, because we've got to have abortion. This 93 00:04:50,720 --> 00:04:53,479 Speaker 3: woman died because she couldn't have an abortion. Abortion saves lives. 94 00:04:55,080 --> 00:04:58,640 Speaker 3: The media keeps repeating it, and so some people believed it. 95 00:05:00,080 --> 00:05:04,600 Speaker 3: But it turns out that's not true. The woman died 96 00:05:05,320 --> 00:05:08,720 Speaker 3: because she had an abortion. Here's what beck Ramaswami on 97 00:05:08,800 --> 00:05:11,440 Speaker 3: CNN with Casey Hunt, and she tried to cite that 98 00:05:11,520 --> 00:05:12,320 Speaker 3: story as fact. 99 00:05:14,160 --> 00:05:15,160 Speaker 2: She wished she hadn't. 100 00:05:16,160 --> 00:05:18,640 Speaker 8: We need to speak about stone cold, hard truths and 101 00:05:18,720 --> 00:05:21,200 Speaker 8: have that debate, even when it's uncomfortable in the open. 102 00:05:21,680 --> 00:05:23,200 Speaker 2: That's how I think we're going to save the country. 103 00:05:23,279 --> 00:05:23,960 Speaker 2: It's a big part of. 104 00:05:23,920 --> 00:05:26,000 Speaker 8: Why I wrote this book, and I also think that 105 00:05:26,040 --> 00:05:28,480 Speaker 8: i'd like to see that standard applied a little more 106 00:05:28,520 --> 00:05:31,480 Speaker 8: even handedly across the board. In that same debate, you 107 00:05:31,520 --> 00:05:34,880 Speaker 8: had Kamala Harris making the claim, also repeatedly many times since, 108 00:05:35,200 --> 00:05:38,120 Speaker 8: that women are bleeding out in parking lots when there 109 00:05:38,160 --> 00:05:40,400 Speaker 8: isn't a shred of evidence of a single woman. 110 00:05:40,720 --> 00:05:44,640 Speaker 9: There was actually a woman who died in Georgia who 111 00:05:45,320 --> 00:05:48,719 Speaker 9: because she there were two women, in fact, one in particular, 112 00:05:48,760 --> 00:05:51,599 Speaker 9: who couldn't receive the care that she needed. 113 00:05:51,680 --> 00:05:53,599 Speaker 8: There's no evidence of a woman bleeding out in a 114 00:05:53,600 --> 00:05:55,279 Speaker 8: parking lot. 115 00:05:55,960 --> 00:05:58,720 Speaker 9: Have you seen evidence of patient pets, Like, if we're 116 00:05:58,720 --> 00:06:00,400 Speaker 9: going to talk about evidence, have you seen evidence of 117 00:06:00,440 --> 00:06:02,240 Speaker 9: Haitian migrants eating pets having. 118 00:06:02,080 --> 00:06:02,760 Speaker 2: Gone to Springfield. 119 00:06:02,800 --> 00:06:04,240 Speaker 8: I didn't see that evidence, But what I will say 120 00:06:04,360 --> 00:06:05,560 Speaker 8: is I'm bringing that up because you brought up the 121 00:06:05,640 --> 00:06:08,200 Speaker 8: Haitian migrant point. There are residents in the community that 122 00:06:08,200 --> 00:06:10,640 Speaker 8: are pointed to that there isn't even that level of 123 00:06:10,640 --> 00:06:12,960 Speaker 8: a shred of evidence to support a single woman in 124 00:06:12,960 --> 00:06:15,440 Speaker 8: the United States bleeding out in a parking lot. That's 125 00:06:15,440 --> 00:06:17,640 Speaker 8: been a repeated claim made by Kamala Harris. 126 00:06:17,720 --> 00:06:18,480 Speaker 2: So I think when we're. 127 00:06:18,320 --> 00:06:20,080 Speaker 8: Getting into fact checking, I think we should apply the 128 00:06:20,080 --> 00:06:22,320 Speaker 8: same standard three hundred and sixty degrees. And I think 129 00:06:22,320 --> 00:06:25,599 Speaker 8: we should not use Kamala Harris's quote there to sidestep 130 00:06:25,640 --> 00:06:27,080 Speaker 8: a debate about abortion policy. 131 00:06:28,760 --> 00:06:30,080 Speaker 2: This is a kind of people you're dealing with. 132 00:06:30,080 --> 00:06:32,359 Speaker 3: It's kind of people that get into government grifters and 133 00:06:32,440 --> 00:06:37,560 Speaker 3: grafters and thieves. Six New York City Department of Education 134 00:06:37,760 --> 00:06:42,920 Speaker 3: employees used forged permission slips to take their own kids 135 00:06:42,920 --> 00:06:47,240 Speaker 3: and grandkids to Disney World and other city funded trips 136 00:06:47,279 --> 00:06:51,280 Speaker 3: that were meant for homeless students. The story from The 137 00:06:51,400 --> 00:06:53,160 Speaker 3: Star Right Arrow News. 138 00:06:53,760 --> 00:06:56,960 Speaker 10: New details have emerged about a misuse of funds within 139 00:06:57,040 --> 00:07:01,440 Speaker 10: New York City's public school system. Recently, least investigative report 140 00:07:01,520 --> 00:07:05,080 Speaker 10: revealing six school employees took their own kids on trips 141 00:07:05,080 --> 00:07:08,760 Speaker 10: to Disney World instead of using the money on homeless students. 142 00:07:09,279 --> 00:07:13,320 Speaker 10: The report details how instead of providing educational enrichment trips 143 00:07:13,360 --> 00:07:16,840 Speaker 10: for students living in shelters, they took their own children 144 00:07:16,960 --> 00:07:20,520 Speaker 10: or grandchildren on trips to places like Florida, New Orleans, 145 00:07:20,720 --> 00:07:24,640 Speaker 10: and Washington, d c. Even to Broadway shows. At the 146 00:07:24,680 --> 00:07:27,960 Speaker 10: center of the scandal is Linda Wilson, the Queen's regional 147 00:07:28,000 --> 00:07:31,800 Speaker 10: manager for the office that supports students in temporary housing. 148 00:07:32,280 --> 00:07:34,000 Speaker 5: The scheme, which ran from. 149 00:07:33,800 --> 00:07:37,800 Speaker 10: Twenty sixteen to twenty nineteen, involved the misuse of three 150 00:07:37,880 --> 00:07:41,760 Speaker 10: hundred thousand dollars of federal grant money meant to help 151 00:07:41,800 --> 00:07:46,200 Speaker 10: homeless children. Investigators allege that Wilson not only brought her 152 00:07:46,240 --> 00:07:49,640 Speaker 10: own children on these trips, but encouraged her colleagues to 153 00:07:49,680 --> 00:07:53,640 Speaker 10: do the same, telling them what happens here stays with us. 154 00:07:54,320 --> 00:07:57,160 Speaker 10: Wilson denies the allegations. In an interview with The New 155 00:07:57,240 --> 00:08:01,320 Speaker 10: York Post. She calls the investigation of which, insisting she 156 00:08:01,360 --> 00:08:04,240 Speaker 10: didn't take her daughters on the trips or advise her 157 00:08:04,240 --> 00:08:07,840 Speaker 10: staff to do so. The report claims Wilson forged permission 158 00:08:07,880 --> 00:08:12,200 Speaker 10: slips and bypassed Department of Education protocols by using an 159 00:08:12,200 --> 00:08:16,920 Speaker 10: outside agency to handle travel arrangements. In some cases, the 160 00:08:16,960 --> 00:08:20,080 Speaker 10: students didn't even visit the college campuses they were meant 161 00:08:20,160 --> 00:08:23,600 Speaker 10: to tour. A whistleblower blew the lid off the scandal, 162 00:08:23,880 --> 00:08:26,840 Speaker 10: claiming most of the homeless students listed on the paperwork 163 00:08:27,160 --> 00:08:29,239 Speaker 10: never actually attended these trips. 164 00:08:29,720 --> 00:08:31,400 Speaker 2: One employee even tried. 165 00:08:31,160 --> 00:08:35,040 Speaker 10: To defend herself, saying Wilson encouraged it and had no 166 00:08:35,200 --> 00:08:37,080 Speaker 10: reason to believe this was. 167 00:08:37,080 --> 00:08:38,040 Speaker 2: Against the rules. 168 00:08:38,720 --> 00:08:42,600 Speaker 10: The investigation recommends that Wilson and the other employees involved 169 00:08:42,920 --> 00:08:45,840 Speaker 10: be fired and required to pay back the money spent 170 00:08:46,040 --> 00:08:49,720 Speaker 10: on their family trips. Wilson has send claims she's retired, 171 00:08:49,840 --> 00:08:52,480 Speaker 10: and the Department of Education confirmed that none of the 172 00:08:52,520 --> 00:08:55,960 Speaker 10: employees named in the report are currently employed with the 173 00:08:56,000 --> 00:09:00,000 Speaker 10: New York City Public Schools. 174 00:09:00,120 --> 00:09:03,240 Speaker 3: As of this year, the United States ranks twenty fifth 175 00:09:03,280 --> 00:09:07,719 Speaker 3: globally in education, according to the World Population Review. Now, 176 00:09:07,760 --> 00:09:10,720 Speaker 3: I don't know what standards they're using, but I don't 177 00:09:10,760 --> 00:09:13,679 Speaker 3: think it's off. I think we have lost our place, 178 00:09:13,679 --> 00:09:20,000 Speaker 3: We've lost our way. We're behind Finland, Switzerland, South Korea, 179 00:09:20,320 --> 00:09:20,960 Speaker 3: and many more. 180 00:09:22,480 --> 00:09:25,120 Speaker 2: We struggle in key areas like math. 181 00:09:27,240 --> 00:09:35,280 Speaker 3: We underperform relative to other developed nations. And I will 182 00:09:35,360 --> 00:09:37,400 Speaker 3: tell you you want to know how. You know we 183 00:09:37,520 --> 00:09:45,199 Speaker 3: underperform because we have to import computer programmers. And you 184 00:09:45,280 --> 00:09:48,080 Speaker 3: may say, ah, that's just because Indians and Chinese are 185 00:09:48,120 --> 00:09:51,680 Speaker 3: willing to work for less. Actually that's partly true. It's 186 00:09:51,679 --> 00:09:56,360 Speaker 3: also true that the universities brought in Indians and Chinese 187 00:09:56,360 --> 00:09:59,360 Speaker 3: to be teaching assistants because they would do it for 188 00:09:59,440 --> 00:10:02,560 Speaker 3: free and change forgetting to come here and studying. And 189 00:10:02,640 --> 00:10:06,080 Speaker 3: now those tas have become professors and they want other 190 00:10:06,120 --> 00:10:09,160 Speaker 3: Indians to come. Yeah, all that's true, and that is 191 00:10:09,200 --> 00:10:13,160 Speaker 3: why you're engineering in math departments now at universities are 192 00:10:13,200 --> 00:10:13,800 Speaker 3: all Indians. 193 00:10:14,040 --> 00:10:18,520 Speaker 2: That's fact. But it's also the case that. 194 00:10:18,400 --> 00:10:23,040 Speaker 3: We are not graduating out of our high schools kids 195 00:10:23,160 --> 00:10:28,480 Speaker 3: who have an interest, an interest in engineering and a 196 00:10:28,600 --> 00:10:34,079 Speaker 3: proficiency in the math necessary to do it. In dirty 197 00:10:34,080 --> 00:10:38,520 Speaker 3: little secret, that's also true of doctors. I've been spending 198 00:10:38,520 --> 00:10:41,640 Speaker 3: a lot of time during my mom's last few years 199 00:10:41,640 --> 00:10:43,480 Speaker 3: and with my dad having been ill off and on 200 00:10:43,520 --> 00:10:47,160 Speaker 3: over the last few years in hospitals. And you walk 201 00:10:47,240 --> 00:10:51,400 Speaker 3: through the major hospitals of the the esteemed Houston Medical Center, 202 00:10:52,960 --> 00:10:57,040 Speaker 3: and the name the last names are Rama Badrin and Vankot, 203 00:10:57,160 --> 00:11:01,800 Speaker 3: Ramen and Vacotation, Run and Ready and Paatel and. 204 00:11:01,600 --> 00:11:04,040 Speaker 2: On and on and on. And there's a reason for. 205 00:11:04,040 --> 00:11:09,960 Speaker 3: That, because our young people are not being inspired to 206 00:11:10,160 --> 00:11:15,880 Speaker 3: study math and science. You don't need to email me 207 00:11:15,920 --> 00:11:17,880 Speaker 3: how you don't like the Indians or you don't this, 208 00:11:18,120 --> 00:11:21,920 Speaker 3: or did some excuse did any of your kids study 209 00:11:21,960 --> 00:11:25,840 Speaker 3: math or science. If they did good on you, we 210 00:11:25,920 --> 00:11:28,640 Speaker 3: have to make a big deal out of stem stem stem, 211 00:11:29,559 --> 00:11:32,480 Speaker 3: like it's some big deal for your kids to learn math. 212 00:11:33,720 --> 00:11:37,200 Speaker 3: We stop learning math in this country. Our kids don't 213 00:11:37,240 --> 00:11:41,439 Speaker 3: learn math. They learn how not to offend other kids. 214 00:11:42,679 --> 00:11:44,760 Speaker 3: They learned that a boy can chop his wiener off 215 00:11:44,800 --> 00:11:47,240 Speaker 3: and be a girl. They don't learn that crap. 216 00:11:47,240 --> 00:11:47,840 Speaker 2: In other countries. 217 00:11:47,840 --> 00:11:51,920 Speaker 3: They learn math, math, math, math. We haven't had a 218 00:11:51,960 --> 00:11:54,520 Speaker 3: white kid or a black kid win a spelling bee 219 00:11:54,840 --> 00:11:59,680 Speaker 3: in probably thirty years because the Indians come here and 220 00:11:59,679 --> 00:12:02,480 Speaker 3: I've got cousins, my wife's cousins, I consider my cousins. 221 00:12:02,760 --> 00:12:03,640 Speaker 2: And that's what they do. 222 00:12:04,320 --> 00:12:07,920 Speaker 3: They drill every evening, drill, drill, drill, and they win 223 00:12:07,960 --> 00:12:08,760 Speaker 3: the spelling bees. 224 00:12:09,640 --> 00:12:10,360 Speaker 2: We don't do that. 225 00:12:11,320 --> 00:12:15,120 Speaker 3: We play football, baseball, bass and that's fine, cheerleading, volleyball. 226 00:12:16,240 --> 00:12:19,800 Speaker 3: But we don't focus on the academics. And that wouldn't 227 00:12:19,800 --> 00:12:22,479 Speaker 3: be a problem if other people didn't focus on the academics, 228 00:12:22,480 --> 00:12:24,400 Speaker 3: if we could drag the whole world down to our stators. 229 00:12:24,400 --> 00:12:29,319 Speaker 2: But they don't. They study, they work on it. Okay, 230 00:12:29,320 --> 00:12:30,600 Speaker 2: I've vented enough on that. 231 00:12:31,960 --> 00:12:35,440 Speaker 3: Twenty twenty result twenty twenty two results from the Program 232 00:12:35,480 --> 00:12:40,320 Speaker 3: for International Student Assessment showed US students scoring below the 233 00:12:40,320 --> 00:12:44,680 Speaker 3: OECD average in mathematics while performing around average in reading 234 00:12:44,880 --> 00:12:51,040 Speaker 3: and science. That's the National Center for Education Statistics. Our 235 00:12:51,080 --> 00:12:54,600 Speaker 3: schools have become in doctrination centers for the progressive agenda, 236 00:12:55,080 --> 00:13:03,640 Speaker 3: not institutions of learning. Teachers are teaching our kids what 237 00:13:03,840 --> 00:13:05,160 Speaker 3: to think, not how to think. 238 00:13:07,200 --> 00:13:08,760 Speaker 2: Teach your kids how to think. 239 00:13:10,559 --> 00:13:17,480 Speaker 3: Why does an apple if you release it, fall to 240 00:13:17,520 --> 00:13:21,240 Speaker 3: the ground because of gravity? What is gravity? What is 241 00:13:21,280 --> 00:13:25,360 Speaker 3: the reason for gravity? Well, I just hope it up 242 00:13:25,400 --> 00:13:31,240 Speaker 3: doesn't upset somebody. President Trump says he will close the 243 00:13:31,240 --> 00:13:34,040 Speaker 3: Department of Education. Guess what, that's the best thing you 244 00:13:34,040 --> 00:13:37,520 Speaker 3: can do for education in this country and return education 245 00:13:37,760 --> 00:13:38,800 Speaker 3: back to the States. 246 00:13:40,320 --> 00:13:43,760 Speaker 1: We spend more money for pupil than any other country 247 00:13:43,880 --> 00:13:46,600 Speaker 1: by far, and yet we're at the bottom of the 248 00:13:46,679 --> 00:13:50,319 Speaker 1: list out of forty we're ranked about number forty. And 249 00:13:50,360 --> 00:13:52,920 Speaker 1: I'm going to close the Department of Education and move 250 00:13:53,200 --> 00:13:56,319 Speaker 1: education back to the States, and we're going to do 251 00:13:56,360 --> 00:13:56,959 Speaker 1: it fast. 252 00:13:58,559 --> 00:14:02,600 Speaker 2: Maybe I'll have you do that. I'll use Lee. Maybe 253 00:14:02,600 --> 00:14:05,160 Speaker 2: I'll have you. You could do it. That's not too easy. 254 00:14:05,880 --> 00:14:09,000 Speaker 2: We'll get somebody great. We'll get lee Zelden is here 255 00:14:09,040 --> 00:14:11,319 Speaker 2: with us tonight. We'll get I think, well, I think 256 00:14:11,360 --> 00:14:16,360 Speaker 2: that's a job for me. He says. 257 00:14:17,679 --> 00:14:21,960 Speaker 3: Some states will fall behind initially, but others will flourish. 258 00:14:22,320 --> 00:14:23,760 Speaker 2: It'll be the red states that will succeed. 259 00:14:24,640 --> 00:14:27,600 Speaker 3: This will create competition, and competition is good, my friends. 260 00:14:28,000 --> 00:14:30,320 Speaker 3: He also said he would end the invasion and the 261 00:14:30,360 --> 00:14:31,600 Speaker 3: destruction of America. 262 00:14:31,680 --> 00:14:33,280 Speaker 2: And I like this, but. 263 00:14:33,280 --> 00:14:36,280 Speaker 1: It takes centuries to build a unique character of each state, 264 00:14:36,800 --> 00:14:38,400 Speaker 1: and we are going to and you know when you 265 00:14:38,480 --> 00:14:42,240 Speaker 1: do that. So the number one rated country is Norway. 266 00:14:43,080 --> 00:14:45,200 Speaker 1: The number two is like Denmark, and you. 267 00:14:45,160 --> 00:14:46,520 Speaker 2: Know, on and on it goes. 268 00:14:47,040 --> 00:14:48,880 Speaker 1: Spend much less money than we do, and they have 269 00:14:49,000 --> 00:14:53,680 Speaker 1: the finest education in New York City. A few years 270 00:14:53,720 --> 00:14:56,040 Speaker 1: ago with Deblasio, who is one of the worst mayors 271 00:14:56,080 --> 00:14:58,320 Speaker 1: in history, by the way, he said, we're going to 272 00:14:58,400 --> 00:15:01,800 Speaker 1: go with the Norwegian that didn't work out too well. Okay, 273 00:15:02,480 --> 00:15:04,920 Speaker 1: you know when they start throwing the teachers out the window, 274 00:15:04,960 --> 00:15:05,920 Speaker 1: that wasn't working out. 275 00:15:05,960 --> 00:15:07,160 Speaker 2: They don't do that in Norway. 276 00:15:07,800 --> 00:15:10,520 Speaker 1: Historically, they haven't thrown too many teachers out the window 277 00:15:10,560 --> 00:15:11,160 Speaker 1: in Norway. 278 00:15:11,880 --> 00:15:13,360 Speaker 2: But we're going to make it good. And you know 279 00:15:13,400 --> 00:15:13,880 Speaker 2: what's going to. 280 00:15:13,920 --> 00:15:17,120 Speaker 1: Happen is out of the fifty states, you're going to 281 00:15:17,200 --> 00:15:21,600 Speaker 1: have thirty five like different ones. Iowa will do good. 282 00:15:21,800 --> 00:15:24,760 Speaker 1: A lot of the states will do very good. I 283 00:15:24,800 --> 00:15:28,320 Speaker 1: can think of probably thirty thirty. Five will be dode 284 00:15:28,360 --> 00:15:33,040 Speaker 1: and five will be okay, ten will be okay. You'll 285 00:15:33,040 --> 00:15:36,720 Speaker 1: have four or five that will be terrible. But that's okay. 286 00:15:36,800 --> 00:15:40,600 Speaker 1: We have to control it. But you'll you'll have Idaho 287 00:15:41,400 --> 00:15:43,720 Speaker 1: or you'll have Idaho will do a great job. They 288 00:15:43,880 --> 00:15:45,840 Speaker 1: you know, no debt, no this do they run a 289 00:15:45,840 --> 00:15:50,120 Speaker 1: great state. A lot of places will have great ageacy. 290 00:15:50,160 --> 00:15:53,920 Speaker 1: We'll have education that can compete with Norway and Denmarket. 291 00:15:54,520 --> 00:15:58,000 Speaker 1: But we'll have certain piece certain places, and it's the 292 00:15:58,080 --> 00:16:01,800 Speaker 1: same places like Gavin Newscombe, who's a terrible governor. You'll 293 00:16:01,800 --> 00:16:04,280 Speaker 1: probably have a problem in California. But what you do 294 00:16:04,320 --> 00:16:06,920 Speaker 1: is you give it to the local communities and they'll 295 00:16:06,920 --> 00:16:10,400 Speaker 1: have a great educational system. You don't want to give 296 00:16:10,400 --> 00:16:13,640 Speaker 1: it to somebody like Kamala because she destroyed San Francisco 297 00:16:13,680 --> 00:16:18,640 Speaker 1: and then destroyed the whole state. But reckless migration policy 298 00:16:18,720 --> 00:16:21,440 Speaker 1: can change it very quickly, and it can destroy everything 299 00:16:21,440 --> 00:16:23,760 Speaker 1: in its way, just like we've seen in London. And 300 00:16:23,880 --> 00:16:28,120 Speaker 1: Paris and Minneapolis. Look at what's happened in London. Look 301 00:16:28,160 --> 00:16:31,920 Speaker 1: what's happening in Paris. If Kamala Harris wins this election, 302 00:16:32,080 --> 00:16:35,440 Speaker 1: she will flood Pennsylvania cities and towns with illegal migrants 303 00:16:35,440 --> 00:16:39,880 Speaker 1: from all over the world, and Pennsylvania will never be 304 00:16:40,040 --> 00:16:40,520 Speaker 1: the same. 305 00:16:40,600 --> 00:16:46,480 Speaker 2: You will never be the same. When I'm president. 306 00:16:46,640 --> 00:16:51,360 Speaker 1: All migrant flights to Pennsylvania will stop immediately. By the way, 307 00:16:52,840 --> 00:16:57,520 Speaker 1: all migrant flights not only to Pennsylvania, everywhere. 308 00:16:58,840 --> 00:16:58,960 Speaker 2: Now. 309 00:16:59,040 --> 00:17:00,760 Speaker 1: But how about they get But you know, we just 310 00:17:00,800 --> 00:17:03,240 Speaker 1: found that out a few months ago. They say, no, no, 311 00:17:03,280 --> 00:17:05,679 Speaker 1: we're fighting, and in the meantime people are just pouring and no, no, 312 00:17:05,720 --> 00:17:07,760 Speaker 1: we want to do it. And then we learned that 313 00:17:07,800 --> 00:17:10,200 Speaker 1: the airplanes are flying. That means that, you know, it's 314 00:17:10,240 --> 00:17:14,359 Speaker 1: just a big kind job. Remember this. For a long time, 315 00:17:14,720 --> 00:17:17,879 Speaker 1: she's been talking about her experience at McDonald's. I worked 316 00:17:17,880 --> 00:17:20,600 Speaker 1: at McDonald's over the French fries who were so hot. 317 00:17:21,480 --> 00:17:23,560 Speaker 1: I think I'm going to go to a McDonald's next week. 318 00:17:23,600 --> 00:17:25,960 Speaker 1: Someplace I'm going to go might not be atre in 319 00:17:26,040 --> 00:17:28,879 Speaker 1: your place. I'm going to go to a McDonald's and 320 00:17:28,960 --> 00:17:31,280 Speaker 1: I'm going to work the French fry job for about 321 00:17:31,280 --> 00:17:32,000 Speaker 1: a half an hour. 322 00:17:32,920 --> 00:17:34,159 Speaker 2: I want to see how it is. 323 00:17:36,119 --> 00:17:38,359 Speaker 1: But she says she worked since she grew up in 324 00:17:38,560 --> 00:17:39,760 Speaker 1: cereble conditions. 325 00:17:39,760 --> 00:17:41,440 Speaker 2: She worked at McDonald's, who was such. 326 00:17:41,680 --> 00:17:45,840 Speaker 1: She never worked there, and these fake news reporters will 327 00:17:45,880 --> 00:17:46,720 Speaker 1: never report it. 328 00:17:46,760 --> 00:17:47,400 Speaker 2: They don't want to. 329 00:17:47,359 --> 00:17:48,760 Speaker 1: Report it because they have. 330 00:17:48,680 --> 00:17:53,640 Speaker 2: Fake they have fake they don't want to report it. 331 00:17:54,160 --> 00:17:57,040 Speaker 1: She never worked at McDonald's, but it was a big 332 00:17:57,080 --> 00:17:59,679 Speaker 1: part of her resume. They went and they went to 333 00:17:59,720 --> 00:18:01,760 Speaker 1: the different places that you work here, that. 334 00:18:01,840 --> 00:18:03,359 Speaker 2: You were here? Did you work here? 335 00:18:04,320 --> 00:18:04,640 Speaker 3: She said. 336 00:18:04,680 --> 00:18:05,879 Speaker 2: We don't know who the hell she is. 337 00:18:05,960 --> 00:18:07,840 Speaker 5: Leave us alone with making hamburgers. 338 00:18:09,359 --> 00:18:12,399 Speaker 1: We will end the invasion of small town Pennsylvania, and 339 00:18:12,440 --> 00:18:16,399 Speaker 1: we will end the destruction of America. It's destroying our 340 00:18:16,440 --> 00:18:18,359 Speaker 1: cut eighteen. 341 00:18:18,400 --> 00:18:21,880 Speaker 11: We're talking about paper ballots, but that actually might be 342 00:18:21,960 --> 00:18:23,320 Speaker 11: one of the smartest. 343 00:18:22,840 --> 00:18:25,040 Speaker 2: Systems the Michael Verie Show, because. 344 00:18:24,880 --> 00:18:26,640 Speaker 11: Russia cannot hack a piece of paper. 345 00:18:27,520 --> 00:18:32,560 Speaker 3: Now for a moment, we're going to start it over. 346 00:18:33,440 --> 00:18:38,720 Speaker 3: I want to give some context. I saw a video 347 00:18:40,119 --> 00:18:46,400 Speaker 3: a group of black Christians who were singing about being 348 00:18:46,440 --> 00:18:49,040 Speaker 3: on the Trump train and part of what they call 349 00:18:49,119 --> 00:18:54,960 Speaker 3: the Mega Gang. It's men and women, it's an expression 350 00:18:54,960 --> 00:18:59,040 Speaker 3: of their political support. The audio is not as good 351 00:18:59,040 --> 00:19:01,960 Speaker 3: as I wish it could have been, but I think 352 00:19:01,960 --> 00:19:06,639 Speaker 3: you're going to get the point. And look, it's not 353 00:19:06,680 --> 00:19:13,600 Speaker 3: a policy discussion. But something's changing, folks. You know in 354 00:19:13,600 --> 00:19:15,439 Speaker 3: two thousand and eight, the crush on I Got a 355 00:19:15,440 --> 00:19:20,119 Speaker 3: crush on Obama girl, that video, that song was everywhere 356 00:19:21,359 --> 00:19:30,080 Speaker 3: this year it is whites blacks, his Spanish, hispanis English Spanish. 357 00:19:30,960 --> 00:19:34,159 Speaker 3: There was a group in India talking about the world 358 00:19:34,200 --> 00:19:36,240 Speaker 3: needs and they were singing I think it was Punjabi, 359 00:19:36,240 --> 00:19:38,159 Speaker 3: it might have been Telabu. I can't remember what language 360 00:19:38,160 --> 00:19:41,160 Speaker 3: it was we who were singing about how the world 361 00:19:41,200 --> 00:19:46,320 Speaker 3: needs America and America needs Trump. There is it's cool 362 00:19:46,359 --> 00:19:49,040 Speaker 3: to be for Trump. It's as if things got so 363 00:19:49,359 --> 00:19:53,879 Speaker 3: bad that now people are saying, this is our last hope. 364 00:19:55,359 --> 00:20:00,040 Speaker 3: The only people that want Kamala are the hopeless, the 365 00:20:00,000 --> 00:20:02,280 Speaker 3: the people that have no hope, the people for whom 366 00:20:02,359 --> 00:20:05,600 Speaker 3: the world is already a dreadful place. They don't understand 367 00:20:05,600 --> 00:20:07,800 Speaker 3: that the world can be better, and some of them 368 00:20:07,880 --> 00:20:09,560 Speaker 3: are part of the reason the world is not better. 369 00:20:10,080 --> 00:20:10,960 Speaker 2: And that's just a fact. 370 00:20:11,640 --> 00:20:14,480 Speaker 3: That's why I Ran is behind her, for instance, That's 371 00:20:14,520 --> 00:20:17,960 Speaker 3: why the gang leaders and the BLM and the trainees 372 00:20:18,040 --> 00:20:22,320 Speaker 3: and every transitioner, and that's why they're all for her. 373 00:20:22,720 --> 00:20:24,720 Speaker 2: They're not going to be happy. She's not going to 374 00:20:24,760 --> 00:20:27,040 Speaker 2: make them happy. Nothing's going to make this group of 375 00:20:27,080 --> 00:20:27,760 Speaker 2: people happy. 376 00:20:27,920 --> 00:20:30,480 Speaker 3: This is the very frust because they hate Daddy, they 377 00:20:30,480 --> 00:20:34,200 Speaker 3: hate their life. Hamas. They're not going to be happy. 378 00:20:34,280 --> 00:20:37,439 Speaker 3: You could obliterate it. Israel Hamas is not going to 379 00:20:37,440 --> 00:20:40,840 Speaker 3: be happy. You do realize that once they don't have 380 00:20:40,880 --> 00:20:43,040 Speaker 3: the Jews to hate, if they could, if they could 381 00:20:43,040 --> 00:20:46,399 Speaker 3: exterminate the Jews, which is their dream, they did have 382 00:20:46,480 --> 00:20:50,080 Speaker 3: to come after us because their leaders need a way 383 00:20:50,080 --> 00:20:54,200 Speaker 3: to keep them angry. It's not that they've been wronged 384 00:20:54,240 --> 00:20:57,719 Speaker 3: and that wound can be salved. There are certain people 385 00:20:58,200 --> 00:21:03,560 Speaker 3: that will never be happy, and keeping them unhappy is 386 00:21:03,680 --> 00:21:04,440 Speaker 3: part of the trick. 387 00:21:06,160 --> 00:21:08,760 Speaker 2: I mean, if you look. I saw a story the 388 00:21:08,800 --> 00:21:11,439 Speaker 2: other day about let's see if I can find it. No, 389 00:21:11,480 --> 00:21:12,959 Speaker 2: I can't. I don't want to waste your time. 390 00:21:13,520 --> 00:21:16,720 Speaker 3: It was about how big pharma, but this is not 391 00:21:16,720 --> 00:21:21,280 Speaker 3: how it was presented. It was the obesity crisis is 392 00:21:21,320 --> 00:21:27,840 Speaker 3: being addressed by new drugs with high hopes, and my 393 00:21:27,920 --> 00:21:33,119 Speaker 3: immediate reaction was wait a minute, we have a polluted, 394 00:21:33,720 --> 00:21:37,760 Speaker 3: fake food supply. Most people are eating food. It's not 395 00:21:37,800 --> 00:21:41,760 Speaker 3: even food anymore. It's man made. It's evil, it's chemicals, 396 00:21:42,400 --> 00:21:45,240 Speaker 3: it's toxic, it's carcinogeny. 397 00:21:44,960 --> 00:21:48,520 Speaker 2: That means cancer causing remont. It's stuff you shouldn't put 398 00:21:48,520 --> 00:21:48,960 Speaker 2: in your body. 399 00:21:48,960 --> 00:21:52,280 Speaker 3: Your grandparents never did, never would. That's why they weren't fat. 400 00:21:52,720 --> 00:21:54,920 Speaker 3: It's stuff that affects your mood and your hormones and 401 00:21:55,000 --> 00:21:59,560 Speaker 3: all of this. And instead of fixing the food supply, 402 00:21:59,680 --> 00:22:04,120 Speaker 3: which is it's not natural any longer, instead of fixing that, 403 00:22:05,000 --> 00:22:09,120 Speaker 3: big pharmer creates another product, because why wouldn't they. Let's 404 00:22:09,160 --> 00:22:13,880 Speaker 3: get you hooked on that too, because why wouldn't they? Right, 405 00:22:15,000 --> 00:22:20,880 Speaker 3: all right, anyway, So I just I wanted to share 406 00:22:20,960 --> 00:22:23,480 Speaker 3: this because I really enjoyed it, and I hope the 407 00:22:23,520 --> 00:22:24,560 Speaker 3: audio is not too terrible. 408 00:22:24,600 --> 00:22:25,880 Speaker 2: We're gonna boost it up a little loud. 409 00:22:25,880 --> 00:22:27,880 Speaker 3: I'm sorry if this comes through your speaker's too loud, 410 00:22:28,200 --> 00:22:29,959 Speaker 3: But I just want you to hear as much as 411 00:22:29,960 --> 00:22:32,120 Speaker 3: you can of it, and I just want you to process. 412 00:22:32,160 --> 00:22:34,160 Speaker 3: Don't worry about whether it's the best song you ever 413 00:22:34,200 --> 00:22:35,160 Speaker 3: heard or anything like that. 414 00:22:35,560 --> 00:22:38,480 Speaker 2: I just want you to think about it's different. 415 00:22:38,920 --> 00:22:41,440 Speaker 3: This twenty twenty four race feels like two thousand and 416 00:22:41,520 --> 00:22:45,000 Speaker 3: eight for the Democrats, where everything was going Obama's way, 417 00:22:45,200 --> 00:22:48,840 Speaker 3: Everything in pop culture was going Obama's way. I want 418 00:22:48,840 --> 00:22:52,879 Speaker 3: you to notice how many people who are not typically 419 00:22:52,920 --> 00:22:56,560 Speaker 3: for a Republican are coming out and saying, we got 420 00:22:56,600 --> 00:22:58,719 Speaker 3: to be for Trump. And they know that by saying this, 421 00:22:59,280 --> 00:23:04,240 Speaker 3: they're surprising people because they weren't supposed to have these opinions. 422 00:23:04,760 --> 00:23:07,480 Speaker 3: And by golly, they do. All right, here we. 423 00:23:07,440 --> 00:23:25,320 Speaker 12: Got you know, he did. 424 00:23:42,200 --> 00:23:44,760 Speaker 7: The mom. 425 00:23:44,880 --> 00:23:50,800 Speaker 2: No you no, Mom, you can like. 426 00:23:52,960 --> 00:23:54,640 Speaker 12: You best. Beware they look. 427 00:23:54,560 --> 00:23:58,200 Speaker 2: In if you don't. 428 00:23:56,160 --> 00:23:58,720 Speaker 12: Actually you can't find one. 429 00:23:58,800 --> 00:24:05,000 Speaker 7: That kid around. 430 00:24:08,160 --> 00:24:14,760 Speaker 5: Lost all that, you know, the stray. 431 00:24:17,359 --> 00:24:22,480 Speaker 12: Because you want to pay news tape, good news, Thank 432 00:24:22,520 --> 00:24:23,960 Speaker 12: good Jesus. 433 00:24:26,040 --> 00:24:29,360 Speaker 5: He loves you. You know, he done. 434 00:24:35,200 --> 00:24:38,720 Speaker 7: Job the first election in that country and the right 435 00:24:38,840 --> 00:24:39,320 Speaker 7: and direction. 436 00:24:40,800 --> 00:24:44,520 Speaker 13: Let's check him. Pay your mail and this is really 437 00:24:44,600 --> 00:24:48,440 Speaker 13: right and me want those a man's one meal a him. 438 00:24:49,000 --> 00:24:54,879 Speaker 13: You have said they had a great inflation thesis. 439 00:24:54,240 --> 00:24:54,439 Speaker 4: And the. 440 00:24:57,160 --> 00:25:33,560 Speaker 7: Buzz the intro justus rights. 441 00:25:05,560 --> 00:25:38,080 Speaker 11: An undocumented immigrant is not a criminal. 442 00:25:38,200 --> 00:25:40,800 Speaker 2: The Michael Berry Show, we have to correct course. 443 00:25:40,840 --> 00:25:44,679 Speaker 3: In his conversation, one of the things that I have 444 00:25:45,600 --> 00:25:50,800 Speaker 3: tried to do, especially this election season, is to amplify 445 00:25:51,119 --> 00:25:54,080 Speaker 3: messages that come from other people. It doesn't have to 446 00:25:54,119 --> 00:25:58,480 Speaker 3: be my words. If they're good ideas, I want to 447 00:25:58,520 --> 00:26:03,240 Speaker 3: share them. I can't possibly put five hours of great 448 00:26:03,440 --> 00:26:06,760 Speaker 3: ideas out there every day. I don't even claim to. 449 00:26:08,200 --> 00:26:11,760 Speaker 3: I read a lot. I don't watch a lot of 450 00:26:13,160 --> 00:26:16,480 Speaker 3: news quote unquote news. I don't watch a lot of 451 00:26:16,520 --> 00:26:18,760 Speaker 3: what other people watch. Not because I'm some great person, 452 00:26:18,760 --> 00:26:23,160 Speaker 3: I just don't. I do read a lot, and then 453 00:26:23,240 --> 00:26:26,480 Speaker 3: I am presented by our team with clips of things, 454 00:26:27,320 --> 00:26:30,800 Speaker 3: and if it's something that I find compelling, we share 455 00:26:30,840 --> 00:26:35,200 Speaker 3: it with you. And I think some of you appreciate that. 456 00:26:36,280 --> 00:26:38,720 Speaker 3: So this is one of those examples. I did not 457 00:26:38,960 --> 00:26:42,240 Speaker 3: know this woman. Her name is Courtney Swan. She's an 458 00:26:42,320 --> 00:26:47,919 Speaker 3: integrative nutritionist whatever that is, and a self proclaimed real foodist, 459 00:26:49,080 --> 00:26:52,080 Speaker 3: and she is on a mission to transform the way 460 00:26:52,160 --> 00:26:55,399 Speaker 3: America eats. She got a Master of Science and Nutrition 461 00:26:55,520 --> 00:26:58,920 Speaker 3: and Integrative Health from Maryland University of Integrative Health, and 462 00:26:58,960 --> 00:27:04,960 Speaker 3: she is big on what she calls real foodology. And 463 00:27:05,040 --> 00:27:10,159 Speaker 3: this is something I believe in. I see how fat 464 00:27:10,240 --> 00:27:13,240 Speaker 3: we've become, and I don't care. Someone must be fatten 465 00:27:13,200 --> 00:27:18,280 Speaker 3: and be fat. But my bone joint doctors tell me 466 00:27:19,320 --> 00:27:22,879 Speaker 3: that we've got bone joint problems that are a crisis 467 00:27:23,080 --> 00:27:23,760 Speaker 3: in this country. 468 00:27:23,840 --> 00:27:25,080 Speaker 2: The levels of them. 469 00:27:25,080 --> 00:27:30,800 Speaker 3: Are exploding, heart attacks at a younger age, strokes at 470 00:27:30,800 --> 00:27:35,200 Speaker 3: a younger age, things related to obesity, and a very 471 00:27:35,320 --> 00:27:40,800 Speaker 3: low quality of life. And it's not necessarily all people's fault. 472 00:27:41,000 --> 00:27:43,040 Speaker 3: It's not just a question of well, you, fatty, you're 473 00:27:43,040 --> 00:27:48,280 Speaker 3: eating too much. What has changed is the food that 474 00:27:48,440 --> 00:27:53,520 Speaker 3: is being created and people don't realize what's in it, 475 00:27:54,800 --> 00:27:59,320 Speaker 3: and that scares me so anyway, Courtney Swan spoke at 476 00:27:59,320 --> 00:28:02,000 Speaker 3: the American Health the Nutrition event hosted by Senator Ron 477 00:28:02,080 --> 00:28:05,160 Speaker 3: Johnson about how the chemical companies have been poisoning our food. 478 00:28:05,880 --> 00:28:07,840 Speaker 3: I know some of you're going to thank Michael. You're 479 00:28:07,840 --> 00:28:11,760 Speaker 3: going conspiracy theory. Okay, that doesn't make it any less true. 480 00:28:11,960 --> 00:28:14,120 Speaker 3: Guess what, The COVID vaccine wasn't a vaccine either. 481 00:28:14,800 --> 00:28:15,880 Speaker 5: My name is Courtney Swan. 482 00:28:15,960 --> 00:28:18,080 Speaker 14: I have a master's of science and nutrition, and I 483 00:28:18,160 --> 00:28:20,320 Speaker 14: host the Real Foodology podcast. And thank you so much 484 00:28:20,320 --> 00:28:24,080 Speaker 14: for listening to us today. Our food is being tainted 485 00:28:24,160 --> 00:28:28,040 Speaker 14: by dangerous chemicals and it's making us sick. In two 486 00:28:28,080 --> 00:28:30,840 Speaker 14: thousand and nine, I started to get debilitating stomach aches. 487 00:28:30,920 --> 00:28:34,040 Speaker 14: I bounced around between specialists with no clarity for two 488 00:28:34,160 --> 00:28:37,080 Speaker 14: years until twenty eleven, when I was diagnosed with the 489 00:28:37,119 --> 00:28:39,760 Speaker 14: gluten intolerance. I was also at the time to told 490 00:28:39,920 --> 00:28:42,480 Speaker 14: I was also told to avoid corn and soy, which 491 00:28:42,480 --> 00:28:46,840 Speaker 14: are common food sensitivities amongst my generation. Unfortunately, my story 492 00:28:46,920 --> 00:28:49,480 Speaker 14: is not unique. Clueless to how this was connected to 493 00:28:49,520 --> 00:28:52,480 Speaker 14: our food system, I started to do some digging. What 494 00:28:52,600 --> 00:28:56,640 Speaker 14: I found was alarming our current agriculture system. Origin story 495 00:28:56,680 --> 00:29:03,520 Speaker 14: involves large chemical companies, farmers, chemists. Eighty five percent of 496 00:29:03,560 --> 00:29:05,800 Speaker 14: the food that you were consuming started from a patented 497 00:29:05,840 --> 00:29:09,080 Speaker 14: seed sold by a chemical corporation that was responsible for 498 00:29:09,120 --> 00:29:13,120 Speaker 14: creating agent orange in the Vietnam War. Why are chemical 499 00:29:13,120 --> 00:29:17,320 Speaker 14: companies feeding America? Corn, soy, and wheat are not only 500 00:29:17,360 --> 00:29:20,040 Speaker 14: the most common allergens, but are among the most heavily 501 00:29:21,120 --> 00:29:25,320 Speaker 14: hasticide sprayed crops today. In nineteen seventy four, the US 502 00:29:25,360 --> 00:29:28,480 Speaker 14: started spraying our crops with an herbicide called glyphosate, and 503 00:29:28,560 --> 00:29:30,800 Speaker 14: in the early nineteen nineties we began to see the 504 00:29:30,800 --> 00:29:33,320 Speaker 14: release of genetically modified foods into our food supply. 505 00:29:34,320 --> 00:29:35,000 Speaker 5: It all seems to. 506 00:29:34,960 --> 00:29:37,400 Speaker 14: Begin with a chemical company by the name ig Farban, 507 00:29:38,320 --> 00:29:41,800 Speaker 14: the later parent company of Bear Farbin, provided the chemicals 508 00:29:41,880 --> 00:29:46,120 Speaker 14: used in Nazi nerve agents and gas chambers. Years later, 509 00:29:46,200 --> 00:29:49,120 Speaker 14: a second chemical company, Monsanto, joined the war industry with 510 00:29:49,120 --> 00:29:52,160 Speaker 14: a production of agent orange, a toxin used during the 511 00:29:52,240 --> 00:29:55,200 Speaker 14: Vietnam War. When the wars ended, these companies needed a 512 00:29:55,240 --> 00:29:58,640 Speaker 14: market for their chemicals, so they pivoted to killing bugs 513 00:29:58,640 --> 00:30:02,920 Speaker 14: and pests on American farmlands. Monsanto began marketing glypha sate 514 00:30:02,960 --> 00:30:06,520 Speaker 14: with catchy name Roundup. They claimed that these chemicals were 515 00:30:06,560 --> 00:30:10,080 Speaker 14: harmless and that they safeguarded our crops from pests. So 516 00:30:10,200 --> 00:30:14,280 Speaker 14: farmers started spraying these supposedly safe chemicals on our farmland. 517 00:30:14,960 --> 00:30:17,480 Speaker 14: They solved the bug problem, but they also killed the crops. 518 00:30:17,960 --> 00:30:22,760 Speaker 14: Monsanto offered a solution with the creation of genetically modified 519 00:30:22,800 --> 00:30:27,640 Speaker 14: otherwise known as GMO, crops that resisted the glyphasate. 520 00:30:27,000 --> 00:30:28,400 Speaker 5: In the round up that they were spraying. 521 00:30:29,400 --> 00:30:32,880 Speaker 14: These round up ready crops allow farmers to spray entire 522 00:30:32,960 --> 00:30:36,640 Speaker 14: fields of glyphasate to kill off pests without harming the plants. 523 00:30:36,960 --> 00:30:40,120 Speaker 14: But our food is left covered in toxic chemical residue 524 00:30:40,120 --> 00:30:43,720 Speaker 14: that doesn't wash dry or cook off. Not only is 525 00:30:43,720 --> 00:30:45,880 Speaker 14: it sprayed to kill pests, but in the final stages 526 00:30:45,920 --> 00:30:48,520 Speaker 14: of harvest, it is sprayed on the wheat to dry 527 00:30:48,520 --> 00:30:51,640 Speaker 14: it out. Grains that go into bread and cereals that 528 00:30:51,640 --> 00:30:54,840 Speaker 14: are in grocery stores and homes of Americans are heavily 529 00:30:54,880 --> 00:30:59,360 Speaker 14: sprayed with these toxins. It's also being sprayed on oats, chickpeas, 530 00:30:59,640 --> 00:31:03,160 Speaker 14: all mend potatoes, and more. You can assume that if 531 00:31:03,200 --> 00:31:07,400 Speaker 14: it's not organic, it is likely contaminated with glyphosate. In America, 532 00:31:07,520 --> 00:31:10,520 Speaker 14: organic food by law, cannot contain GMOs and glyphosate, and 533 00:31:10,560 --> 00:31:14,360 Speaker 14: they are more expensive compared to conventionally grown options. Americans 534 00:31:14,400 --> 00:31:16,960 Speaker 14: are being forced to pay more for food that isn't poisoned. 535 00:31:21,640 --> 00:31:22,960 Speaker 5: The Environmental Working Group. 536 00:31:22,760 --> 00:31:25,280 Speaker 14: Reported a test of popular wheat based products and found 537 00:31:25,280 --> 00:31:30,120 Speaker 14: glyphosate contamination in eighty to ninety percent of the products 538 00:31:30,120 --> 00:31:31,280 Speaker 14: on grocery store shelves. 539 00:31:31,560 --> 00:31:33,480 Speaker 5: Popular foods like cheerios. 540 00:31:33,320 --> 00:31:38,040 Speaker 14: Goldfish, chickpeapasta like Bonza nature Valley bars were found to 541 00:31:38,040 --> 00:31:41,640 Speaker 14: have concerning levels of glyphosate. If that is not alarming enough, 542 00:31:41,680 --> 00:31:46,280 Speaker 14: glyphosate is produced by and distributed from China. In twenty eighteen, 543 00:31:46,480 --> 00:31:51,320 Speaker 14: Bayer bought Monsanto. They currently have patented soybeans corn, canola, 544 00:31:51,360 --> 00:31:53,640 Speaker 14: and sugar beets, and they are the largest distributor of 545 00:31:53,680 --> 00:31:57,760 Speaker 14: GMO corn and soybean seeds. Americans deserve a straight answer. 546 00:31:57,800 --> 00:32:01,880 Speaker 14: Why does an agrochemical company own where our food comes from? Currently, 547 00:32:01,920 --> 00:32:03,800 Speaker 14: eighty five to one hundred percent of corn and soy 548 00:32:03,840 --> 00:32:06,920 Speaker 14: crops in the US are genetically modified. Eighty percent of 549 00:32:06,960 --> 00:32:11,360 Speaker 14: GMOs are engineered to withstand glyphosate, and it is staggering. 550 00:32:11,480 --> 00:32:15,480 Speaker 14: Two hundred and eighty million pounds of glyphosate are sprayed 551 00:32:15,480 --> 00:32:19,000 Speaker 14: on American crops annually. We are eating this round up 552 00:32:19,000 --> 00:32:22,160 Speaker 14: ready corn, But unlike GMO crops, humans are not round 553 00:32:22,200 --> 00:32:24,720 Speaker 14: up ready. We are not resistant to these toxins, and 554 00:32:24,760 --> 00:32:29,280 Speaker 14: it's causing neurological damage, intocrne disrupt disruption, It's harming our 555 00:32:29,280 --> 00:32:33,880 Speaker 14: reproductive health, and it's affecting fetal development. Glyphosate is classified 556 00:32:33,880 --> 00:32:37,720 Speaker 14: as a carcinogen by the World Health Organization's International Agency. 557 00:32:37,280 --> 00:32:38,360 Speaker 5: For Research on Cancer. 558 00:32:39,120 --> 00:32:41,640 Speaker 14: It is also suspected to contribute towards the rise and 559 00:32:41,680 --> 00:32:46,520 Speaker 14: coeliac disease and gluten and gluten sensitivities. They're finding glyphosate 560 00:32:46,560 --> 00:32:50,719 Speaker 14: and human breast milk placentas are organs and even sperm 561 00:32:50,880 --> 00:32:53,480 Speaker 14: it's also being found in our rain and our drinking water. 562 00:32:55,320 --> 00:32:58,120 Speaker 14: Until January of twenty twenty two, many companies made efforts 563 00:32:58,160 --> 00:33:02,160 Speaker 14: to obscure the presence of GMO's and pesticides in food products. 564 00:33:02,080 --> 00:33:03,320 Speaker 5: From American consumers. 565 00:33:03,640 --> 00:33:06,960 Speaker 14: It was only then that legislation came into effect mandating 566 00:33:06,960 --> 00:33:10,800 Speaker 14: that these companies disclose such ingredients with a straightforward label 567 00:33:11,040 --> 00:33:14,080 Speaker 14: stating made with bioengineered ingredients, but it's very small on 568 00:33:14,120 --> 00:33:18,520 Speaker 14: the package. Meanwhile, glyphosate still isn't labeled on our food. 569 00:33:18,960 --> 00:33:22,800 Speaker 14: Parents in America are unknowingly feeding their children these toxic foods. 570 00:33:23,920 --> 00:33:27,800 Speaker 14: Doctor Don Huber, a glycos researcher, warns that glyphosate will 571 00:33:27,800 --> 00:33:32,400 Speaker 14: make the outlawed nineteen seventies and secticide DDT look harmless 572 00:33:32,880 --> 00:33:37,360 Speaker 14: in comparison to glyphosate. Why is the US government subsidizing 573 00:33:37,360 --> 00:33:41,160 Speaker 14: the most pesticide sprayed crops using tax payer dollars? These 574 00:33:41,200 --> 00:33:43,160 Speaker 14: are the exact foods they're driving. 575 00:33:42,840 --> 00:33:44,440 Speaker 5: The epidemic of chronic disease. 576 00:33:45,080 --> 00:33:48,080 Speaker 14: These crops, heavily sprayed with glyphasaate, are then processed into 577 00:33:48,160 --> 00:33:51,160 Speaker 14: high fruitose, corn syrup and refined vegetable oils, which are 578 00:33:51,240 --> 00:33:54,680 Speaker 14: key ingredients for the ultra processed for foods that line 579 00:33:54,760 --> 00:33:58,600 Speaker 14: our supermarket shelves and fill our children's lunches in schools 580 00:33:58,640 --> 00:34:02,680 Speaker 14: across the nation. Children across America are consuming food such 581 00:34:02,720 --> 00:34:04,440 Speaker 14: as goldfish and cheerios that are loaded with. 582 00:34:04,480 --> 00:34:05,120 Speaker 5: Slack to stake. 583 00:34:05,920 --> 00:34:09,440 Speaker 14: These crops also feed our livestock, which then produce the eggs, dairy, 584 00:34:09,480 --> 00:34:10,920 Speaker 14: and meat products that we consume. 585 00:34:11,520 --> 00:34:12,960 Speaker 5: They are in everything