1 00:00:03,840 --> 00:00:08,360 Speaker 1: It's that time, time, time, time, Luck and load. 2 00:00:11,400 --> 00:00:21,560 Speaker 2: Michael Varry Show is on the air. It's Charlie from 3 00:00:21,560 --> 00:00:22,360 Speaker 2: BlackBerry Smoke. 4 00:00:22,760 --> 00:00:24,680 Speaker 1: I can feel a good one coming on. It's the 5 00:00:24,720 --> 00:00:25,720 Speaker 1: Michael Berry Show. 6 00:00:27,080 --> 00:00:30,000 Speaker 3: Any attempt to restrict drinking and driving here is viewed 7 00:00:30,000 --> 00:00:32,199 Speaker 3: by some as downright undemocratic. 8 00:00:32,560 --> 00:00:36,120 Speaker 4: To preparing for the four year anniversary of Russia's passing, 9 00:00:36,880 --> 00:00:41,159 Speaker 4: which was the seventeenth, which would have been what a Monday, 10 00:00:43,600 --> 00:00:46,920 Speaker 4: we went through some of our favorite Rush Limball audio 11 00:00:47,080 --> 00:00:49,519 Speaker 4: and we only played a small bit of it, but 12 00:00:49,600 --> 00:00:53,080 Speaker 4: I thought, just as a treat so it doesn't go 13 00:00:53,080 --> 00:00:55,160 Speaker 4: to waste, I'd like to share a few that I 14 00:00:55,200 --> 00:00:55,920 Speaker 4: really enjoyed. 15 00:00:56,720 --> 00:01:02,560 Speaker 2: One was Rush at his best, and that is being. 16 00:01:02,440 --> 00:01:07,679 Speaker 4: Funny but also revealing something that many people probably didn't know, 17 00:01:08,400 --> 00:01:15,040 Speaker 4: which is how Kamala Harris came up in politics, and 18 00:01:15,080 --> 00:01:18,680 Speaker 4: that is as the side piece of the very powerful 19 00:01:19,000 --> 00:01:22,000 Speaker 4: mayor at the time of San Francisco who would go 20 00:01:22,000 --> 00:01:24,120 Speaker 4: on to be the Speaker of the House in California. 21 00:01:25,120 --> 00:01:29,600 Speaker 4: And while he was married, she was his mistress and 22 00:01:30,200 --> 00:01:31,600 Speaker 4: she gave him. 23 00:01:31,760 --> 00:01:34,119 Speaker 2: Well we know what he did for her. 24 00:01:35,440 --> 00:01:40,120 Speaker 4: We don't know exactly what she did for him, But 25 00:01:40,319 --> 00:01:41,720 Speaker 4: Rush kind of made it clear. 26 00:01:41,880 --> 00:01:46,560 Speaker 5: I have two stories about Kamala Harris. One's from the 27 00:01:46,600 --> 00:01:52,280 Speaker 5: Spectator and one is it's a one of the one 28 00:01:52,280 --> 00:01:58,600 Speaker 5: of the oddball sports websites. The NBA has fired a 29 00:01:58,640 --> 00:02:03,480 Speaker 5: freelance photographer because he insulted Kamala Harris. 30 00:02:03,520 --> 00:02:05,200 Speaker 2: His name is Bill Baptiste. 31 00:02:05,480 --> 00:02:09,160 Speaker 5: He's an independent contractor had the deal terminated by the elite. 32 00:02:09,680 --> 00:02:14,440 Speaker 4: Bill Baptiste, by the way, is a Houstonian. He's also 33 00:02:14,560 --> 00:02:18,080 Speaker 4: a listener to our show. When that happened, he reached 34 00:02:18,080 --> 00:02:20,520 Speaker 4: out to me and we talked every day for a while. 35 00:02:21,520 --> 00:02:27,000 Speaker 4: This poor guy was incredibly well regarded in professional sports 36 00:02:27,040 --> 00:02:33,720 Speaker 4: and had decades of experience, and they destroyed this man's career, 37 00:02:34,320 --> 00:02:39,320 Speaker 4: destroyed his career, And people don't seem to care when 38 00:02:39,400 --> 00:02:43,160 Speaker 4: somebody who's not a public figure is destroyed in this 39 00:02:43,240 --> 00:02:45,959 Speaker 4: way that they now have to figure out they can't 40 00:02:46,000 --> 00:02:49,360 Speaker 4: pay their rent, They have to live with the shame, 41 00:02:49,520 --> 00:02:53,880 Speaker 4: the frustration, the hurt, the anguish. Everything you've poured your 42 00:02:53,880 --> 00:02:55,520 Speaker 4: life into is taken away from you. 43 00:02:56,560 --> 00:02:58,799 Speaker 2: I mean, this was devastating to him. 44 00:02:58,880 --> 00:03:01,360 Speaker 4: Rewind that A few says from I want people to 45 00:03:01,400 --> 00:03:05,160 Speaker 4: hear this, this story because I know this guy personally 46 00:03:05,240 --> 00:03:08,359 Speaker 4: and to watch what it did to him. And you know, 47 00:03:08,560 --> 00:03:11,000 Speaker 4: everyone else has moved on to the next next big 48 00:03:11,040 --> 00:03:12,600 Speaker 4: thing in the news, but not him. 49 00:03:15,000 --> 00:03:21,480 Speaker 5: The NBA has fired a freelance photographer because he insulted 50 00:03:21,960 --> 00:03:22,760 Speaker 5: Kamala Harris. 51 00:03:22,760 --> 00:03:24,400 Speaker 2: His name is Bill Baptiste. 52 00:03:24,680 --> 00:03:27,880 Speaker 5: He's an independent contractor had the deal terminated by the 53 00:03:28,000 --> 00:03:35,880 Speaker 5: league after he posted a sexist Facebook post referencing Kamala Harris. 54 00:03:38,960 --> 00:03:44,080 Speaker 5: He posted an image that read Joe and the hoe. 55 00:03:44,520 --> 00:03:46,240 Speaker 2: Hoe. 56 00:03:46,840 --> 00:03:50,040 Speaker 5: Now, what do you think that's about Joe and the hoe? 57 00:03:50,200 --> 00:03:53,000 Speaker 2: Well, it takes me to the second story they got 58 00:03:53,000 --> 00:03:53,240 Speaker 2: read of. 59 00:03:53,400 --> 00:03:57,840 Speaker 5: By the way, it's no secret but public knowledge that 60 00:03:58,000 --> 00:04:03,760 Speaker 5: Kamala Harris slapped her up into California political life by 61 00:04:03,800 --> 00:04:09,320 Speaker 5: being a very public escort and mattress for California Democrat 62 00:04:09,480 --> 00:04:12,280 Speaker 5: Kingmaker Willie Brown. Now, some people read this story mattress. 63 00:04:12,280 --> 00:04:15,280 Speaker 5: Didn't he mean mistress? No, I think they meant mattress here. 64 00:04:18,000 --> 00:04:21,960 Speaker 5: I think Dove Fisher is the author of the story. 65 00:04:23,240 --> 00:04:26,560 Speaker 5: So we have two different stories here that are trading 66 00:04:26,720 --> 00:04:29,400 Speaker 5: off the known. 67 00:04:31,160 --> 00:04:34,520 Speaker 2: Fact that she was Willie Brown's mattress. 68 00:04:34,560 --> 00:04:37,000 Speaker 4: Since we're celebrating Rush Limbaugh and I enjoy hearing his 69 00:04:37,080 --> 00:04:42,040 Speaker 4: voice I hope you do too. Another clip from him 70 00:04:42,680 --> 00:04:48,000 Speaker 4: that I referenced earlier in the week, and it's about 71 00:04:48,160 --> 00:04:51,960 Speaker 4: the fact that Democrats never tell voters what they're going 72 00:04:52,040 --> 00:04:55,800 Speaker 4: to do once they're elected, because if they did, voters 73 00:04:55,800 --> 00:04:58,280 Speaker 4: would vote against them. It'd be like news of Hunter 74 00:04:58,320 --> 00:05:03,360 Speaker 4: Biden's laptops. So they talk in terms of rainbows and butterflies, 75 00:05:03,680 --> 00:05:05,800 Speaker 4: but that's not what they deliver. 76 00:05:07,360 --> 00:05:13,440 Speaker 5: But if you're really stop to think about it, mob behavior, bullying, 77 00:05:14,600 --> 00:05:20,200 Speaker 5: the appearance of insane rage and anger is all they 78 00:05:20,200 --> 00:05:24,359 Speaker 5: have left. They don't have any issues, their policies to 79 00:05:24,440 --> 00:05:28,360 Speaker 5: run on for the same old reason they can't be honest. 80 00:05:29,600 --> 00:05:33,120 Speaker 5: Oh they've got plenty of policies. Oh they got plenty issues. 81 00:05:34,240 --> 00:05:38,359 Speaker 5: Oh they have plenty of ideas. They just don't dare 82 00:05:38,520 --> 00:05:43,520 Speaker 5: tell anybody what they are not at the run up 83 00:05:43,520 --> 00:05:44,400 Speaker 5: to election time. 84 00:05:44,640 --> 00:05:47,560 Speaker 4: That's the sort of thing that you expect to hear 85 00:05:47,760 --> 00:05:50,160 Speaker 4: me or whoever else you listen. 86 00:05:50,000 --> 00:05:52,480 Speaker 2: To talk about. 87 00:05:53,520 --> 00:05:58,240 Speaker 4: But when Rush was describing these things, in many cases, 88 00:05:58,279 --> 00:06:00,719 Speaker 4: he was the only one described them, and to the 89 00:06:00,800 --> 00:06:04,200 Speaker 4: audience to which he spoke, he was often the only 90 00:06:04,240 --> 00:06:09,039 Speaker 4: political commentary they were getting that was real. The average 91 00:06:09,360 --> 00:06:15,600 Speaker 4: worker was not listening to Bill Buckley or George will 92 00:06:16,279 --> 00:06:20,520 Speaker 4: or Bill Crystal or any of the others. Rush was 93 00:06:20,520 --> 00:06:24,560 Speaker 4: bringing the university to the masses, and that's how you 94 00:06:24,600 --> 00:06:31,080 Speaker 4: build a movement. He also said something else, and I 95 00:06:31,120 --> 00:06:34,800 Speaker 4: love the spot native is the sense of urgency he's 96 00:06:34,839 --> 00:06:37,640 Speaker 4: talking about. When he said that the only thing that 97 00:06:37,800 --> 00:06:40,000 Speaker 4: is certain is right now. 98 00:06:41,200 --> 00:06:45,560 Speaker 5: Someone told me I think, I think this is good. 99 00:06:45,600 --> 00:06:46,920 Speaker 2: Advice may be helpful. 100 00:06:48,200 --> 00:06:51,280 Speaker 5: The only thing that any of us are certain of 101 00:06:51,480 --> 00:06:57,440 Speaker 5: is right now today. That's why I thank God every 102 00:06:57,440 --> 00:07:00,560 Speaker 5: morning when I wake up, I thank God that I did. 103 00:07:00,680 --> 00:07:04,440 Speaker 5: I try to make it the best day I can 104 00:07:05,160 --> 00:07:10,640 Speaker 5: no matter what. Don't look too far ahead. I certainly 105 00:07:10,720 --> 00:07:16,080 Speaker 5: don't look too far back. I try to remain as 106 00:07:16,200 --> 00:07:22,560 Speaker 5: committed to the idea what's supposed to happen will happen 107 00:07:22,600 --> 00:07:28,600 Speaker 5: when it's meant to. I mentioned at the outset of 108 00:07:28,600 --> 00:07:30,560 Speaker 5: this the first day I told you that I have 109 00:07:30,640 --> 00:07:38,760 Speaker 5: a personal relationship with Jesus Christ. It is of the 110 00:07:38,800 --> 00:07:47,000 Speaker 5: immense value strength, confidence, and that's why I'm able to 111 00:07:47,040 --> 00:07:51,400 Speaker 5: remain fully committed to the idea of that what is 112 00:07:51,440 --> 00:07:57,320 Speaker 5: supposed to happen will happen when it's meant to. There's 113 00:07:57,360 --> 00:08:00,520 Speaker 5: some comfort in knowing that some things are not in 114 00:08:00,600 --> 00:08:06,520 Speaker 5: our hands. It's a lot of fear associated with that too, 115 00:08:06,800 --> 00:08:14,000 Speaker 5: but there is some comfort. It's helpful, God, It's helpful 116 00:08:14,040 --> 00:08:21,320 Speaker 5: to be able to trust them, to believe in a. 117 00:08:19,880 --> 00:08:20,840 Speaker 1: In a higher planet. 118 00:08:23,320 --> 00:08:27,200 Speaker 5: What a maroon Michael Berry show, What an ignorandom? 119 00:08:29,800 --> 00:08:33,600 Speaker 4: I think it is that the geeks shall inherit the earth, 120 00:08:33,960 --> 00:08:34,760 Speaker 4: not the meek. 121 00:08:35,400 --> 00:08:37,200 Speaker 2: This is a glorious time. 122 00:08:37,800 --> 00:08:40,760 Speaker 4: You know, the old uh kind of jab learned to 123 00:08:40,840 --> 00:08:43,800 Speaker 4: code that the Left would throw at people when they 124 00:08:43,800 --> 00:08:47,040 Speaker 4: would lose their jobs as a coal miner, Well, learn 125 00:08:47,120 --> 00:08:52,040 Speaker 4: to code. My late brother's son, Brayden, is a computer programmer, 126 00:08:52,280 --> 00:08:54,240 Speaker 4: and I don't know where that came from, because we 127 00:08:54,280 --> 00:08:57,760 Speaker 4: are a family full of cops and plant workers, with 128 00:08:57,840 --> 00:09:01,480 Speaker 4: one talk show host, nobody in our family. We can 129 00:09:01,480 --> 00:09:06,559 Speaker 4: barely turn a computer on, much less code and program. 130 00:09:06,880 --> 00:09:09,240 Speaker 4: But he does, and I love it. Well, this is 131 00:09:09,240 --> 00:09:14,640 Speaker 4: such a glorious time. The mindset of America is accountability 132 00:09:15,040 --> 00:09:18,960 Speaker 4: and transparency. We know that there is behind the curtain 133 00:09:19,040 --> 00:09:22,240 Speaker 4: this wizard, and we don't know what that wizard is. 134 00:09:22,280 --> 00:09:24,520 Speaker 4: And we know we're pouring all our money in and 135 00:09:24,600 --> 00:09:27,480 Speaker 4: nuns coming back. But how on earth do we solve 136 00:09:27,480 --> 00:09:32,040 Speaker 4: this problem. It's intransigent, it's too complex to ever solve. 137 00:09:32,160 --> 00:09:35,840 Speaker 4: We've heard that, right, And yet here comes along Elon, 138 00:09:36,400 --> 00:09:41,760 Speaker 4: who's somewhere on the autism scale, pure genius in a 139 00:09:41,800 --> 00:09:46,679 Speaker 4: way that I can hardly comprehend, his reasoning skills, his 140 00:09:46,720 --> 00:09:51,760 Speaker 4: ability to process things on a multiplanetary level, and he 141 00:09:51,840 --> 00:09:57,959 Speaker 4: brings within these young, really smart guys and they start 142 00:09:58,000 --> 00:10:00,280 Speaker 4: tearing apart the details and going here's your way, and 143 00:10:00,320 --> 00:10:02,680 Speaker 4: here's your waste, and here's your waste. Well, one of 144 00:10:02,679 --> 00:10:05,600 Speaker 4: the names that has come to my attention because of 145 00:10:05,640 --> 00:10:10,800 Speaker 4: Elon is on Twitter and the handle is data Republican, 146 00:10:11,040 --> 00:10:14,400 Speaker 4: and she says republican with a small R, as in 147 00:10:14,559 --> 00:10:17,160 Speaker 4: a person who believes in the republic. This dollar government, 148 00:10:17,200 --> 00:10:20,600 Speaker 4: representative government. And so I started reading everything that was said. 149 00:10:20,600 --> 00:10:24,240 Speaker 4: I noticed how many people were quoting this very influential woman, 150 00:10:25,120 --> 00:10:27,880 Speaker 4: and so I reached out by direct message to her, 151 00:10:28,400 --> 00:10:30,400 Speaker 4: and she said, I'd be glad to do it, but 152 00:10:30,480 --> 00:10:33,520 Speaker 4: I need you to talk to my guy, and that's 153 00:10:33,520 --> 00:10:37,080 Speaker 4: Sean Hendricks, because I need a translator when we do 154 00:10:37,120 --> 00:10:40,680 Speaker 4: the interview. So Sean came on and I said, well, 155 00:10:40,760 --> 00:10:43,200 Speaker 4: can we talk to you first, and why do we 156 00:10:43,280 --> 00:10:44,800 Speaker 4: need a translatter? 157 00:10:44,960 --> 00:10:46,040 Speaker 2: Does she not speak? 158 00:10:46,080 --> 00:10:49,959 Speaker 4: And he said, oh, she's deaf and mute, And I thought, wow, 159 00:10:50,080 --> 00:10:52,360 Speaker 4: it's you know, you hear these stories ramone people that 160 00:10:52,440 --> 00:10:54,760 Speaker 4: don't have sight, so they have extra you know, they 161 00:10:54,760 --> 00:10:55,440 Speaker 4: can hear better. 162 00:10:55,760 --> 00:10:57,079 Speaker 2: It's like you have a heightened sense. 163 00:10:57,559 --> 00:11:00,480 Speaker 4: But anyway, I think it's an inspirational story in addition 164 00:11:00,480 --> 00:11:03,200 Speaker 4: to everything else. Sean Hendricks is our guest, and I 165 00:11:03,240 --> 00:11:05,440 Speaker 4: appreciate you making yourself available to us. 166 00:11:05,440 --> 00:11:08,960 Speaker 1: Good sir, No, absolutely, thanks for having us on. 167 00:11:09,080 --> 00:11:12,280 Speaker 3: It's always great to get outside the X space and 168 00:11:12,400 --> 00:11:15,000 Speaker 3: talk about this on a broader platform so people are aware. 169 00:11:15,240 --> 00:11:16,920 Speaker 2: Well, I told you before we started. 170 00:11:16,960 --> 00:11:19,160 Speaker 4: I don't normally prep guests, but I did Sean because 171 00:11:19,200 --> 00:11:21,360 Speaker 4: I knew he probably didn't know much about us. Is 172 00:11:21,400 --> 00:11:24,160 Speaker 4: that a lot of national talk shows do their show 173 00:11:24,480 --> 00:11:26,720 Speaker 4: as if everybody is on Twitter all day long and 174 00:11:26,800 --> 00:11:27,280 Speaker 4: knows what. 175 00:11:27,200 --> 00:11:29,480 Speaker 2: The top story is. I do our show so that. 176 00:11:29,440 --> 00:11:30,960 Speaker 4: The guy that gets out of the plant on his 177 00:11:31,040 --> 00:11:33,440 Speaker 4: drive home you understand what we're talking about. So if 178 00:11:33,440 --> 00:11:34,840 Speaker 4: there's an acronym, I explain it. 179 00:11:35,520 --> 00:11:36,040 Speaker 2: And I want to. 180 00:11:36,040 --> 00:11:39,120 Speaker 4: First talk about who Data Republican is, and then we're 181 00:11:39,120 --> 00:11:42,040 Speaker 4: going to get to you and what data Republican is 182 00:11:42,080 --> 00:11:44,400 Speaker 4: doing that came to the attention of Elon that's been 183 00:11:44,440 --> 00:11:48,240 Speaker 4: so important to these numbers we're bandying about about government corruption. 184 00:11:50,880 --> 00:11:53,079 Speaker 1: Yeah, she's she was just what. 185 00:11:53,320 --> 00:11:55,120 Speaker 3: She was one of my early followers when I was 186 00:11:55,120 --> 00:11:58,079 Speaker 3: doing Western North Carolina disaster relief, and that's how we connected, 187 00:11:58,600 --> 00:12:01,760 Speaker 3: and she was basically, you could learn to code, it 188 00:12:01,800 --> 00:12:04,040 Speaker 3: goes beyond that, you have to learn to build, Like 189 00:12:04,080 --> 00:12:06,320 Speaker 3: there's a you know, AI can code, but it's like 190 00:12:06,440 --> 00:12:08,319 Speaker 3: really knowing what you're building is what matters. 191 00:12:08,360 --> 00:12:09,040 Speaker 1: And that's what she did. 192 00:12:09,080 --> 00:12:11,840 Speaker 3: She's a tool builder and so she's an old colonel 193 00:12:12,080 --> 00:12:15,480 Speaker 3: database engineer, but she's taken to building tools that parse 194 00:12:15,559 --> 00:12:18,440 Speaker 3: all this data and present it in a way that 195 00:12:18,520 --> 00:12:21,440 Speaker 3: the regular person can look and see how the money flows. 196 00:12:22,040 --> 00:12:24,280 Speaker 3: And I guess, you know, we just didn't realize how 197 00:12:24,320 --> 00:12:26,720 Speaker 3: much we needed and wanted that, And now that it's 198 00:12:26,720 --> 00:12:29,480 Speaker 3: out there, people are just blown away and how much 199 00:12:29,559 --> 00:12:33,040 Speaker 3: money is moving into these mysterious areas that no one 200 00:12:33,120 --> 00:12:36,000 Speaker 3: has representation of or transparency through. 201 00:12:37,480 --> 00:12:40,800 Speaker 4: So let's talk about those tools and explain those tools 202 00:12:40,880 --> 00:12:43,440 Speaker 4: to those of us who are not computer programmers and 203 00:12:43,520 --> 00:12:47,479 Speaker 4: not real tech savvy. Why are those tools important. 204 00:12:49,160 --> 00:12:54,040 Speaker 3: Well, she's taken one point eight terabytes of publicly available 205 00:12:54,160 --> 00:12:56,160 Speaker 3: data and put it into the front end. It's on 206 00:12:56,200 --> 00:12:59,440 Speaker 3: a website called datarepublican dot com. So you can go 207 00:12:59,520 --> 00:13:02,600 Speaker 3: in and tie in an officer search. You got some 208 00:13:02,679 --> 00:13:06,800 Speaker 3: guy who's ranting and raving about Trump shutting down USAID. Well, 209 00:13:06,800 --> 00:13:08,880 Speaker 3: funny enough, you type his name into the search and 210 00:13:08,920 --> 00:13:10,920 Speaker 3: you see the seven charities that are receiving money from 211 00:13:11,040 --> 00:13:12,160 Speaker 3: USAID that he's. 212 00:13:12,040 --> 00:13:12,520 Speaker 1: A part of. 213 00:13:12,960 --> 00:13:16,520 Speaker 3: Well, now you can filter his bias through where he's 214 00:13:16,520 --> 00:13:19,440 Speaker 3: getting money from and help understand why this guy's so upset. 215 00:13:19,760 --> 00:13:21,920 Speaker 1: They used to hide in the shadows of this stuff. 216 00:13:21,960 --> 00:13:24,199 Speaker 3: You know, now we can go and look, so, well, 217 00:13:24,240 --> 00:13:27,440 Speaker 3: he's actually tied to these charities. Where are those charities 218 00:13:27,640 --> 00:13:30,080 Speaker 3: getting their money from? So you put their charity number 219 00:13:30,120 --> 00:13:33,160 Speaker 3: into the system and it shows all the grants coming in, 220 00:13:33,240 --> 00:13:36,400 Speaker 3: and you can basically do your research to find out 221 00:13:36,480 --> 00:13:39,320 Speaker 3: these powerful people where their money's coming from. And then 222 00:13:39,320 --> 00:13:42,720 Speaker 3: you start to understand their reasons they make the decisions 223 00:13:42,720 --> 00:13:45,200 Speaker 3: they're making, the reasons they're fighting so hard to keep 224 00:13:45,240 --> 00:13:47,720 Speaker 3: this stuff quiet because this has been a huge flush 225 00:13:47,800 --> 00:13:52,320 Speaker 3: fund there and it's not Republican and Democrats. It's both right, 226 00:13:52,440 --> 00:13:54,679 Speaker 3: it's not one side or the other. Everyone's had their 227 00:13:54,679 --> 00:13:56,880 Speaker 3: hand in this cookie jar. And that's what we're looking 228 00:13:56,880 --> 00:13:58,920 Speaker 3: to do is get people transparency through. 229 00:13:58,760 --> 00:13:59,840 Speaker 1: Data through facts. 230 00:14:00,240 --> 00:14:02,439 Speaker 3: And that's something that we've had pulled over our eyes 231 00:14:02,440 --> 00:14:05,000 Speaker 3: for many, many years. And with AI and you know 232 00:14:05,040 --> 00:14:09,199 Speaker 3: amazing tool builders like data, we can see this stuff. 233 00:14:09,240 --> 00:14:09,440 Speaker 1: Now. 234 00:14:09,920 --> 00:14:11,680 Speaker 2: I'm going to ask some dumb questions because I'm not 235 00:14:11,679 --> 00:14:13,840 Speaker 2: afraid to ask dumb questions. The only way I learned anything. 236 00:14:14,280 --> 00:14:16,800 Speaker 2: How do you get access to this data? 237 00:14:17,200 --> 00:14:20,160 Speaker 4: Is this data now being made available because somebody has 238 00:14:20,160 --> 00:14:22,920 Speaker 4: to hand the data set to you to make sense 239 00:14:22,960 --> 00:14:23,240 Speaker 4: of it. 240 00:14:25,280 --> 00:14:27,800 Speaker 3: Well, right, So a lot of this because of how 241 00:14:28,360 --> 00:14:31,920 Speaker 3: charities work is transparent. Form nine nineties are kind of 242 00:14:31,960 --> 00:14:36,000 Speaker 3: like where you come out in detail, you know what 243 00:14:36,040 --> 00:14:38,280 Speaker 3: your charity's doing. I mean you get a tax exemption, 244 00:14:38,520 --> 00:14:40,800 Speaker 3: so there is some transparency that comes along with that. 245 00:14:41,120 --> 00:14:42,800 Speaker 3: I can't just set up a nonprofit and tell the 246 00:14:42,800 --> 00:14:46,320 Speaker 3: government like, hey, you can't look inside, right, So there's 247 00:14:46,360 --> 00:14:48,600 Speaker 3: a lot of there's a lot more regulation over a 248 00:14:48,680 --> 00:14:51,000 Speaker 3: five to one C three and then we have like 249 00:14:51,040 --> 00:14:53,200 Speaker 3: there's donor advised fun I mean, there's just so many 250 00:14:53,280 --> 00:14:55,000 Speaker 3: layers to this charity. 251 00:14:55,040 --> 00:14:55,520 Speaker 1: It's funny. 252 00:14:55,600 --> 00:14:58,240 Speaker 3: Even before this data republican thing broke, when I was 253 00:14:58,320 --> 00:15:01,320 Speaker 3: up in western North Carolina, I saw so much fraud 254 00:15:01,360 --> 00:15:03,080 Speaker 3: with the whole charity system. I used to tell people 255 00:15:03,160 --> 00:15:05,440 Speaker 3: the only thing I trust less than the government is charities. 256 00:15:06,000 --> 00:15:07,560 Speaker 1: And then all of a sudden two three. 257 00:15:07,360 --> 00:15:09,880 Speaker 3: Months later, That's why I think I connected so much 258 00:15:09,920 --> 00:15:11,760 Speaker 3: with her, as she was showing me why I felt 259 00:15:11,800 --> 00:15:14,080 Speaker 3: that way. I could feel it. I just didn't have 260 00:15:14,120 --> 00:15:16,600 Speaker 3: the data to prove it. But yeah, this data, these 261 00:15:16,680 --> 00:15:18,640 Speaker 3: these the irs website have a lot of these data 262 00:15:18,640 --> 00:15:22,320 Speaker 3: sets available. But unless you can cross connect all the data, 263 00:15:22,320 --> 00:15:24,320 Speaker 3: it doesn't really mean anything. If I look at the 264 00:15:24,640 --> 00:15:27,560 Speaker 3: Kaiser Foundation health Plan Incorporated and I see that it 265 00:15:27,600 --> 00:15:31,480 Speaker 3: received eighty two million or eighty two billion, sorry, eighty 266 00:15:31,480 --> 00:15:37,360 Speaker 3: two billion dollars, right, what does that mean? Then go 267 00:15:37,400 --> 00:15:38,560 Speaker 3: through way and we parse it out and see that 268 00:15:38,640 --> 00:15:42,400 Speaker 3: actually only eleven million of that was taxpayer funds. But 269 00:15:42,440 --> 00:15:45,280 Speaker 3: it was eleven million of taxpayer funds? Why did tax 270 00:15:45,320 --> 00:15:47,080 Speaker 3: payer money go there? So you can start to dig 271 00:15:47,160 --> 00:15:50,360 Speaker 3: in and and again, data does not mean a conviction. Right, 272 00:15:50,400 --> 00:15:52,760 Speaker 3: doesn't mean that have eleven millions had right? It could 273 00:15:52,760 --> 00:15:54,680 Speaker 3: have been a very good reason we sent that money there. 274 00:15:54,720 --> 00:15:56,600 Speaker 3: And we've had people use this and say, look at Tyser, 275 00:15:56,640 --> 00:15:59,800 Speaker 3: they're stealing money from the taxpayer. No, no, no, you 276 00:16:00,080 --> 00:16:00,960 Speaker 3: had a dig deeper than that. 277 00:16:01,120 --> 00:16:04,040 Speaker 4: But Sean, what we were doing before you guys, is 278 00:16:04,040 --> 00:16:06,480 Speaker 4: we were sitting back and going, wait a second, how 279 00:16:06,520 --> 00:16:09,400 Speaker 4: do they drive a rolls Royce when they're a nonprofit 280 00:16:09,560 --> 00:16:12,280 Speaker 4: And he says he only makes anything. We had no tools. 281 00:16:12,280 --> 00:16:14,160 Speaker 4: You talk about a tool. We had not tools to 282 00:16:14,200 --> 00:16:14,840 Speaker 4: do these things with. 283 00:16:15,040 --> 00:16:15,560 Speaker 2: Hold with me. 284 00:16:16,000 --> 00:16:18,920 Speaker 4: His name if you're on Twitter is Sean at Sean 285 00:16:19,000 --> 00:16:22,120 Speaker 4: Hendricks and that's d r I x Sean. She is 286 00:16:22,200 --> 00:16:25,560 Speaker 4: Data Republican and you can find them at data Republican 287 00:16:25,640 --> 00:16:28,120 Speaker 4: dot com. You can sign up to subscribe for three 288 00:16:28,120 --> 00:16:30,000 Speaker 4: bucks a month and you get all their stuff. I 289 00:16:30,120 --> 00:16:34,200 Speaker 4: did Data Republican dot com. He's Sean Hendricks. More with him. 290 00:16:35,120 --> 00:16:37,680 Speaker 1: He just shows me what it's like to be, you know, 291 00:16:37,840 --> 00:16:38,520 Speaker 1: a real man. 292 00:16:38,720 --> 00:16:40,920 Speaker 2: I have never met someone so wonderful. 293 00:16:41,000 --> 00:16:41,840 Speaker 5: I call him Rhythm. 294 00:16:42,080 --> 00:16:47,040 Speaker 4: Michael Berry, Elon and many others have been very complementary 295 00:16:47,080 --> 00:16:49,360 Speaker 4: of the work these folks are doing at Data Republican 296 00:16:49,440 --> 00:16:53,160 Speaker 4: dot com. These are number cruncher, computer genius kind of 297 00:16:53,200 --> 00:16:56,200 Speaker 4: people genius for me. They they may not like that title, 298 00:16:56,240 --> 00:16:59,160 Speaker 4: but for me, it is sean when you talk about 299 00:16:59,200 --> 00:17:02,680 Speaker 4: this data from which you're pulling all the you know, 300 00:17:02,760 --> 00:17:05,360 Speaker 4: you're making sense of it and analyzing it for us, 301 00:17:06,160 --> 00:17:09,760 Speaker 4: was that data available before or has something happened with 302 00:17:09,840 --> 00:17:12,040 Speaker 4: Trump that this was now the doors were open and 303 00:17:12,080 --> 00:17:13,520 Speaker 4: they go come in here and take a look. 304 00:17:15,119 --> 00:17:17,959 Speaker 3: You know, I'm not quite sure how long Form nine 305 00:17:18,040 --> 00:17:21,800 Speaker 3: nineties have been public. You know, I just know that 306 00:17:22,040 --> 00:17:25,280 Speaker 3: at the Taxes Them organization, your Form nine ninety is 307 00:17:25,320 --> 00:17:27,720 Speaker 3: public disclosure and it's available. 308 00:17:29,040 --> 00:17:30,640 Speaker 1: I mean as far as they know, it's always been 309 00:17:30,680 --> 00:17:31,040 Speaker 1: that way. 310 00:17:32,400 --> 00:17:35,240 Speaker 3: And so yeah, the data is there, just there was 311 00:17:35,280 --> 00:17:37,880 Speaker 3: no tool, right, No one had sat. 312 00:17:37,760 --> 00:17:38,879 Speaker 1: Down and built this tool. 313 00:17:39,400 --> 00:17:42,240 Speaker 3: And you know what I think what happens is like, 314 00:17:42,560 --> 00:17:44,119 Speaker 3: until there's a problem, you don't need you don't know, 315 00:17:44,160 --> 00:17:46,600 Speaker 3: you don't know that you need a tool, right, And 316 00:17:46,720 --> 00:17:48,880 Speaker 3: so we see there's a problem, We see that there's 317 00:17:48,960 --> 00:17:54,480 Speaker 3: mass spending with no direction and no transparency, and so 318 00:17:54,880 --> 00:17:57,120 Speaker 3: she's like, well, we need a tool for this. And 319 00:17:57,160 --> 00:18:00,200 Speaker 3: when she started building it, it just you know, if 320 00:18:00,200 --> 00:18:02,560 Speaker 3: we invent something, you know, there's there's. 321 00:18:02,359 --> 00:18:03,040 Speaker 1: Two ways it can go. 322 00:18:03,080 --> 00:18:05,399 Speaker 3: Nobody wants that invention, or everybody wants it, it seems like 323 00:18:05,480 --> 00:18:10,120 Speaker 3: right and just people wanted to know where their money's going. 324 00:18:10,119 --> 00:18:12,679 Speaker 3: And I think we're all so tired of paying a 325 00:18:12,720 --> 00:18:17,240 Speaker 3: premium on groceries, a premium on fuel, property taxes, income taxes, 326 00:18:17,840 --> 00:18:18,600 Speaker 3: you know, death. 327 00:18:18,840 --> 00:18:20,400 Speaker 1: I mean, it just goes on and on and on. 328 00:18:20,560 --> 00:18:22,360 Speaker 3: All our money goes out and we don't get much 329 00:18:22,359 --> 00:18:25,000 Speaker 3: for it, I feel like, and so now there's a 330 00:18:25,040 --> 00:18:28,120 Speaker 3: tool to go see where is our money going, especially 331 00:18:28,200 --> 00:18:30,159 Speaker 3: in this nine to ninety world. And I think the 332 00:18:30,160 --> 00:18:32,760 Speaker 3: biggest thing was that if the charity system hadn't been 333 00:18:32,880 --> 00:18:35,080 Speaker 3: used to move so much cash around, there had been 334 00:18:35,119 --> 00:18:38,040 Speaker 3: no need for a tool. But that's the fact that 335 00:18:38,040 --> 00:18:42,720 Speaker 3: it has been us age. We're talking just an unimaginable 336 00:18:42,840 --> 00:18:45,919 Speaker 3: amount of cash that's being moved around and there's no 337 00:18:46,000 --> 00:18:47,919 Speaker 3: way to sort it out with some kind of very 338 00:18:48,359 --> 00:18:51,160 Speaker 3: very elegant tool. And that's what she what she created. 339 00:18:51,240 --> 00:18:53,760 Speaker 3: That's why she's become so popular. 340 00:18:54,720 --> 00:18:58,560 Speaker 4: Well, because you know, if you can't if you've got 341 00:18:58,560 --> 00:19:01,360 Speaker 4: this amazing uranium but you can't refine it, or you've 342 00:19:01,400 --> 00:19:03,680 Speaker 4: got oil reserves but you can't pull out of the earth, 343 00:19:03,880 --> 00:19:06,840 Speaker 4: it's worth nothing to anyone. But now it's worth things 344 00:19:06,920 --> 00:19:09,720 Speaker 4: because we can write stories about it, I can do 345 00:19:09,840 --> 00:19:11,919 Speaker 4: shows about it. But I could have never We couldn't 346 00:19:11,960 --> 00:19:13,600 Speaker 4: make sense of any of this. We wouldn't have even 347 00:19:13,640 --> 00:19:17,400 Speaker 4: really known that it existed. Sean Hendricks is our guest 348 00:19:17,480 --> 00:19:20,879 Speaker 4: data Republican dot com Sewan. You use the term that 349 00:19:20,960 --> 00:19:25,320 Speaker 4: these supposed nonprofits, these NGOs are moving cash around so 350 00:19:25,440 --> 00:19:27,160 Speaker 4: much that makes it harder to understand. 351 00:19:27,840 --> 00:19:29,040 Speaker 2: Do you get the sense that. 352 00:19:29,000 --> 00:19:32,760 Speaker 4: The moving of cash in this way is an attempt 353 00:19:32,760 --> 00:19:35,440 Speaker 4: to launder or obscure or what? 354 00:19:35,800 --> 00:19:37,520 Speaker 2: Do you think the reasoning for that is To the 355 00:19:37,560 --> 00:19:38,679 Speaker 2: extent you can tell, I. 356 00:19:38,720 --> 00:19:42,120 Speaker 3: Want to be I want to be careful to allege. Right, 357 00:19:42,840 --> 00:19:46,320 Speaker 3: what I can say is how they do it is 358 00:19:46,359 --> 00:19:50,280 Speaker 3: the outcome of obscuring and confusing the data. Right, This 359 00:19:50,359 --> 00:19:52,560 Speaker 3: stuff goes overseas and we lose track of it. It 360 00:19:52,600 --> 00:19:54,480 Speaker 3: goes from company to company. It's harder to track. 361 00:19:54,920 --> 00:19:55,080 Speaker 1: Now. 362 00:19:55,080 --> 00:19:57,359 Speaker 3: I can't speak to intentions that don't have You know, 363 00:19:57,760 --> 00:19:59,760 Speaker 3: I can't prove somebody's intention, but I can say, is 364 00:19:59,800 --> 00:20:02,960 Speaker 3: there actions one to one hundred percent make it very 365 00:20:02,960 --> 00:20:06,600 Speaker 3: hard to track where the money goes. Now, whether that's 366 00:20:06,640 --> 00:20:08,320 Speaker 3: intentional or not. I can't speak to that, and that 367 00:20:08,359 --> 00:20:10,359 Speaker 3: will come in time. We will start to find out 368 00:20:10,640 --> 00:20:13,800 Speaker 3: the intentionality behind it as we start finding people, and 369 00:20:13,880 --> 00:20:16,080 Speaker 3: it's really easy for us. They make it very easy. 370 00:20:16,080 --> 00:20:18,720 Speaker 3: Those who are screaming the loudest, we just go look 371 00:20:18,760 --> 00:20:21,639 Speaker 3: into them and it's like almost every time, you know, 372 00:20:21,840 --> 00:20:23,919 Speaker 3: you know, the senators are screaming a lot of US. 373 00:20:23,920 --> 00:20:24,640 Speaker 1: I went and looked. 374 00:20:24,800 --> 00:20:27,080 Speaker 3: Every one of them had voted for the Omniumbus Spending 375 00:20:27,119 --> 00:20:31,159 Speaker 3: Bill twenty twenty four that funded this US eight. Right, 376 00:20:31,240 --> 00:20:33,919 Speaker 3: So when you find the person's squeaking, they had a 377 00:20:33,960 --> 00:20:34,720 Speaker 3: piece of it going. 378 00:20:34,840 --> 00:20:35,080 Speaker 1: You know. 379 00:20:35,480 --> 00:20:38,000 Speaker 4: Now again, it's kind of funny because we always said 380 00:20:38,000 --> 00:20:40,439 Speaker 4: in the country the hitting dogs squeels first. It's kind 381 00:20:40,480 --> 00:20:43,560 Speaker 4: of funny because they're joining attention to themselves by the 382 00:20:43,640 --> 00:20:45,239 Speaker 4: fact that they're screaming about it. 383 00:20:46,640 --> 00:20:49,560 Speaker 3: Oh yeah, every time they get into a beef with 384 00:20:49,640 --> 00:20:52,359 Speaker 3: Elon or jd Vance. As soon as I see it, 385 00:20:52,680 --> 00:20:55,080 Speaker 3: I'm like straight into the engine. I start pumping names in. 386 00:20:55,440 --> 00:20:59,080 Speaker 3: We start doing research and lo and behold, you're tied 387 00:20:59,119 --> 00:21:02,120 Speaker 3: to six or seven different things. No wonder you're screaming 388 00:21:02,160 --> 00:21:05,040 Speaker 3: because you're you're gravy trains about to get cut off. 389 00:21:06,119 --> 00:21:10,560 Speaker 3: You know, and so yeah, I mean it's it's almost 390 00:21:10,600 --> 00:21:12,600 Speaker 3: too much to process. And just give me an idea. 391 00:21:12,720 --> 00:21:15,159 Speaker 3: In the charity funding tab we have one hundred and 392 00:21:15,160 --> 00:21:20,520 Speaker 3: fifty six thousand different funds totaling seven hundred and twenty 393 00:21:20,520 --> 00:21:26,480 Speaker 3: three billion dollars, with three hundred and fourteen billion being 394 00:21:26,600 --> 00:21:30,080 Speaker 3: government grants. Right, so we're talking three hundred and twenty 395 00:21:30,119 --> 00:21:34,280 Speaker 3: two billion dollars of total taxpayer money that's being moved around. 396 00:21:35,600 --> 00:21:36,159 Speaker 1: It's wild. 397 00:21:36,840 --> 00:21:39,320 Speaker 4: I mean, this is an amount of money that exceeds that. 398 00:21:39,520 --> 00:21:41,800 Speaker 4: This is more than double what was sent to Ukraine. 399 00:21:42,200 --> 00:21:43,200 Speaker 4: You could fight an. 400 00:21:43,200 --> 00:21:46,360 Speaker 2: Entire world, an entire war with. 401 00:21:46,440 --> 00:21:49,240 Speaker 4: A major military superpower for the kind of money we're 402 00:21:49,240 --> 00:21:49,920 Speaker 4: talking about here. 403 00:21:51,359 --> 00:21:55,159 Speaker 3: Oh yeah, I mean this is this is unimaginable amount 404 00:21:55,200 --> 00:21:59,159 Speaker 3: of dollars. And we wonder why everything's so expensive. I 405 00:21:59,200 --> 00:22:01,720 Speaker 3: mean gold right now surging to three thousand dollars an ounce, 406 00:22:02,080 --> 00:22:05,120 Speaker 3: you know, a printing money and just pumping it into 407 00:22:05,119 --> 00:22:05,720 Speaker 3: the globe. 408 00:22:05,960 --> 00:22:08,520 Speaker 1: Of course, everything's expensive. What do you expect when you 409 00:22:08,560 --> 00:22:11,800 Speaker 1: do that stuff? But this is just a small piece 410 00:22:11,840 --> 00:22:12,280 Speaker 1: of it. You know. 411 00:22:12,560 --> 00:22:14,840 Speaker 3: I think the next four years, I think we're going 412 00:22:14,880 --> 00:22:17,960 Speaker 3: to be awestruck and what we find, what our budget 413 00:22:18,000 --> 00:22:20,240 Speaker 3: really looks like and I hear people say all the time, 414 00:22:20,480 --> 00:22:22,280 Speaker 3: Oh well, I mean, even if you took the stuff 415 00:22:22,280 --> 00:22:24,479 Speaker 3: that we have to pay for, it wouldn't put us 416 00:22:24,480 --> 00:22:27,040 Speaker 3: in a deficit. And it's like somehow that that's good 417 00:22:27,119 --> 00:22:27,879 Speaker 3: enough reason just to. 418 00:22:27,880 --> 00:22:28,879 Speaker 1: Stay in debt forever. 419 00:22:29,080 --> 00:22:31,439 Speaker 3: Imagine that I told my wife, well, I can't make 420 00:22:31,520 --> 00:22:33,280 Speaker 3: enough money to pay out the credit cards, so please 421 00:22:33,359 --> 00:22:35,439 Speaker 3: keep spending as much as you want on the credit cards. 422 00:22:36,560 --> 00:22:38,080 Speaker 1: They don't live in a real world like we do. 423 00:22:38,600 --> 00:22:40,399 Speaker 3: And now we can use this data to hold our 424 00:22:40,400 --> 00:22:44,680 Speaker 3: politicians accountable. We should fire our politicians for not balancing 425 00:22:44,720 --> 00:22:45,280 Speaker 3: our budget. 426 00:22:47,040 --> 00:22:51,440 Speaker 2: It's it's staggering. 427 00:22:51,520 --> 00:22:56,119 Speaker 4: You know what's amazing is we're a month into the 428 00:22:56,119 --> 00:23:01,240 Speaker 4: Trump presidency and we've already discovered all of these amazing things. 429 00:23:01,600 --> 00:23:03,960 Speaker 4: And you guys are just getting better by the day. 430 00:23:04,440 --> 00:23:08,119 Speaker 4: You're just now getting your feet wet to figure out 431 00:23:08,280 --> 00:23:10,960 Speaker 4: how to dive into these data sets, and you're going 432 00:23:11,040 --> 00:23:12,840 Speaker 4: to notice the things that they're coding. 433 00:23:12,880 --> 00:23:15,360 Speaker 2: You know, I saw the other day that Elon. 434 00:23:15,240 --> 00:23:19,280 Speaker 4: Was talking about the fact that they had the Social 435 00:23:19,320 --> 00:23:24,080 Speaker 4: Security Administration had some some millions of people who had 436 00:23:24,119 --> 00:23:25,520 Speaker 4: as their death date false. 437 00:23:25,720 --> 00:23:26,919 Speaker 2: So they can never die. 438 00:23:27,080 --> 00:23:29,840 Speaker 4: So you've got millions of people who could who are 439 00:23:29,960 --> 00:23:32,240 Speaker 4: supposedly one hundred and fifty years old, getting a Social 440 00:23:32,240 --> 00:23:35,520 Speaker 4: Security check and of course that doesn't exist. That means 441 00:23:35,520 --> 00:23:39,240 Speaker 4: it's a check going to some conspiracy ring, some fraud ring. 442 00:23:39,880 --> 00:23:43,520 Speaker 4: Once these things become clear, we're going to understand that 443 00:23:43,600 --> 00:23:45,200 Speaker 4: we shouldn't even be running. 444 00:23:44,920 --> 00:23:46,280 Speaker 2: A deficit as a country. 445 00:23:46,600 --> 00:23:49,600 Speaker 4: It is absurd that we would even be running a 446 00:23:49,680 --> 00:23:52,919 Speaker 4: deficit as a country when you consider the work you 447 00:23:52,960 --> 00:23:56,200 Speaker 4: guys are doing and all the dollars that are exposed. 448 00:23:56,640 --> 00:23:59,200 Speaker 4: In just a moment, we will continue with Sean Hendrix. 449 00:23:59,560 --> 00:24:03,520 Speaker 4: The website is Data Republican dot com. It's three bucks 450 00:24:03,560 --> 00:24:06,040 Speaker 4: a month to subscribe. I encourage you to do it 451 00:24:06,080 --> 00:24:07,760 Speaker 4: only because I did, and I like to support the 452 00:24:07,800 --> 00:24:11,239 Speaker 4: work of folks like this. Sean Hendricks is not the 453 00:24:11,760 --> 00:24:14,800 Speaker 4: Data Republican. That is a woman with whom we will 454 00:24:14,800 --> 00:24:17,439 Speaker 4: also be speaking in the near future through a translator. 455 00:24:17,640 --> 00:24:20,879 Speaker 4: Sean Hendrix is part of her group and was willing 456 00:24:20,880 --> 00:24:22,920 Speaker 4: to speak to us today. And I am so excited 457 00:24:22,920 --> 00:24:25,320 Speaker 4: about what they're doing because I think this is how 458 00:24:25,320 --> 00:24:28,200 Speaker 4: you bring real change. I think this is how you 459 00:24:28,840 --> 00:24:32,520 Speaker 4: make things in a bite sized manner. In a way 460 00:24:32,720 --> 00:24:35,720 Speaker 4: that it's accessible to the general republic, to people that 461 00:24:35,760 --> 00:24:39,320 Speaker 4: don't turn on computers. Oh that's where all my money's going. Okay, 462 00:24:39,720 --> 00:24:43,040 Speaker 4: now I can be enraged. This is how you message 463 00:24:43,080 --> 00:24:47,199 Speaker 4: a campaign strategically to win, and that I find to 464 00:24:47,200 --> 00:24:50,159 Speaker 4: be very excited. And when I don't mean elections, I 465 00:24:50,200 --> 00:24:51,719 Speaker 4: mean fixing our dad dumb country. 466 00:24:51,760 --> 00:24:54,480 Speaker 2: I have kids. Sean Henders is our guest Data Republican 467 00:24:54,520 --> 00:24:54,880 Speaker 2: dot com. 468 00:24:54,880 --> 00:24:57,120 Speaker 1: More coming up, we're going. 469 00:24:57,119 --> 00:25:00,480 Speaker 2: To be changing the name of the Gulf of Mexico to. 470 00:25:00,800 --> 00:25:04,000 Speaker 5: The Gulf of Michael Barry, which has a beautiful room. 471 00:25:05,960 --> 00:25:06,160 Speaker 1: Well. 472 00:25:06,680 --> 00:25:10,760 Speaker 4: John Hendris is our guest Data Republican dot com. This 473 00:25:10,760 --> 00:25:13,080 Speaker 4: this is a small group that Elon Musk has been 474 00:25:13,119 --> 00:25:15,879 Speaker 4: talking a lot about the great work that they're doing 475 00:25:15,920 --> 00:25:21,520 Speaker 4: and exposing the governmental fraud and waste. Sean, I don't 476 00:25:21,520 --> 00:25:22,800 Speaker 4: know if you have a list in front of you 477 00:25:22,920 --> 00:25:24,879 Speaker 4: or if there are a few that come to mind, 478 00:25:24,920 --> 00:25:27,960 Speaker 4: But when you look at the waste and fraud allegedly 479 00:25:28,400 --> 00:25:31,439 Speaker 4: that you guys have exposed, were there some things that 480 00:25:31,560 --> 00:25:34,760 Speaker 4: jumped out at you that really seemed more egregious than 481 00:25:34,760 --> 00:25:35,120 Speaker 4: the rest? 482 00:25:36,760 --> 00:25:38,679 Speaker 3: You know, I'm going to turn the Social Security thing 483 00:25:38,720 --> 00:25:40,680 Speaker 3: on its head a little bit. And also real quick, 484 00:25:41,040 --> 00:25:44,760 Speaker 3: the data Republican site is free you can We're subscription 485 00:25:45,040 --> 00:25:47,000 Speaker 3: paid for, so if you donate, that's great. 486 00:25:47,280 --> 00:25:48,760 Speaker 1: We don't want to pay all this data. 487 00:25:48,800 --> 00:25:51,199 Speaker 3: We want everyone to have access to it, but we 488 00:25:51,280 --> 00:25:53,920 Speaker 3: are donation driven, So I do appreciate you putting that 489 00:25:53,960 --> 00:25:56,520 Speaker 3: out there. The thing of the social security side, the 490 00:25:56,560 --> 00:25:58,640 Speaker 3: thing that struck me this morning when I was looking 491 00:25:58,680 --> 00:26:02,119 Speaker 3: through it is, yeah, we talk about the money, but 492 00:26:02,320 --> 00:26:04,640 Speaker 3: social security numbers vote right? 493 00:26:05,000 --> 00:26:05,440 Speaker 1: What if? 494 00:26:05,800 --> 00:26:08,120 Speaker 3: And this isn't I'm just theorizing here, but like, that's 495 00:26:08,160 --> 00:26:11,080 Speaker 3: a lot of people still on a voter record. If 496 00:26:11,119 --> 00:26:13,320 Speaker 3: they're alive in the social security system, are they still 497 00:26:13,359 --> 00:26:15,600 Speaker 3: alive in the voter roles? I mean that's managed state 498 00:26:15,640 --> 00:26:18,760 Speaker 3: by state, And so I want to dig deeper and 499 00:26:18,800 --> 00:26:22,960 Speaker 3: built buy the voter registration information from a state and 500 00:26:23,000 --> 00:26:25,359 Speaker 3: then go compare it to whatever we can find on 501 00:26:25,359 --> 00:26:29,760 Speaker 3: this this you know, death false flag on the social 502 00:26:29,840 --> 00:26:30,480 Speaker 3: Security numbers. 503 00:26:30,520 --> 00:26:31,760 Speaker 1: Maybe it's bigger than just money. 504 00:26:32,200 --> 00:26:34,439 Speaker 3: You know, we always you know, the old joke is 505 00:26:34,480 --> 00:26:37,879 Speaker 3: my dad, my granddad voted Republican up until the day 506 00:26:37,920 --> 00:26:39,639 Speaker 3: he died, and he voted a Democrat ever since. 507 00:26:40,320 --> 00:26:44,480 Speaker 1: You know, so, But I want to dig into that 508 00:26:44,480 --> 00:26:45,880 Speaker 1: because like sometimes we're focused on. 509 00:26:45,800 --> 00:26:47,480 Speaker 3: The money, and it's like, well, what is the bigger 510 00:26:47,920 --> 00:26:49,880 Speaker 3: what's the bigger purpose behind the money? 511 00:26:49,880 --> 00:26:52,119 Speaker 1: What are they doing with the money? And that's the thing. 512 00:26:52,160 --> 00:26:53,600 Speaker 3: We really find out that it has a lot to 513 00:26:53,640 --> 00:26:57,200 Speaker 3: do with the uniparty and this idea of democracy. Right, 514 00:26:57,359 --> 00:27:00,960 Speaker 3: these people on both sides, this uniparty, but leaves without 515 00:27:01,040 --> 00:27:04,320 Speaker 3: them sitting in the ivory tower guiding our lives. 516 00:27:04,040 --> 00:27:05,080 Speaker 1: And making our decisions. 517 00:27:05,280 --> 00:27:08,159 Speaker 3: That the Western world would collapse without the genius of 518 00:27:08,200 --> 00:27:11,440 Speaker 3: these these government workers, right. I mean, they've put themselves 519 00:27:11,520 --> 00:27:14,440 Speaker 3: in a ruling class, a truly a ruling elite, and 520 00:27:14,960 --> 00:27:18,600 Speaker 3: that money is to prop up that ideology. And so 521 00:27:18,760 --> 00:27:21,000 Speaker 3: it's yeah, sure it's a waste of money, but even worse, 522 00:27:21,080 --> 00:27:25,679 Speaker 3: it's paying for bad ideologies across the globe. 523 00:27:26,119 --> 00:27:28,240 Speaker 1: And you know, now we're seeing the damage of it. 524 00:27:29,560 --> 00:27:32,680 Speaker 4: We are, and and you know, I think part of 525 00:27:32,920 --> 00:27:35,960 Speaker 4: why these things are allowed to happen is because this 526 00:27:36,080 --> 00:27:40,840 Speaker 4: information is obfuscated, This information is withheld, It stays behind 527 00:27:40,880 --> 00:27:44,679 Speaker 4: the curtain. The public doesn't know, and so what we 528 00:27:44,760 --> 00:27:47,439 Speaker 4: don't see in front of us, we can't concentrate on. 529 00:27:47,640 --> 00:27:51,800 Speaker 4: So we tend to focus instead on congressional sex scandals 530 00:27:52,240 --> 00:27:54,560 Speaker 4: on you know who said a nasty thing to the other, 531 00:27:54,600 --> 00:27:57,080 Speaker 4: and it keeps us spatting with each other when what 532 00:27:57,200 --> 00:27:59,600 Speaker 4: really matters is the dollars and cents that we're wasting 533 00:27:59,600 --> 00:28:02,639 Speaker 4: in the problems that aren't being solved. Sean, when you 534 00:28:02,680 --> 00:28:05,320 Speaker 4: look at where Data Republican is going and in this 535 00:28:05,440 --> 00:28:09,960 Speaker 4: very brief period of time, is this burst of popularity 536 00:28:10,040 --> 00:28:12,159 Speaker 4: and celebrity to some extent on Twitter? 537 00:28:12,200 --> 00:28:12,560 Speaker 2: For sure? 538 00:28:13,200 --> 00:28:15,880 Speaker 4: What do you see as being the future for her 539 00:28:16,000 --> 00:28:19,159 Speaker 4: and you and all of this because there is a 540 00:28:19,200 --> 00:28:21,240 Speaker 4: lot to a lot of work to be done here. 541 00:28:21,280 --> 00:28:23,119 Speaker 2: Do you see yourself joining doose? 542 00:28:23,240 --> 00:28:27,240 Speaker 4: Do you see yourself becoming an official organization or have 543 00:28:27,320 --> 00:28:28,240 Speaker 4: you even thought about that? 544 00:28:29,880 --> 00:28:31,800 Speaker 3: Well, we did talk about that, and I think stand 545 00:28:31,840 --> 00:28:34,639 Speaker 3: Independent makes the most sense. There's a lot of politics 546 00:28:34,640 --> 00:28:39,480 Speaker 3: with those and you know it's ran by people who 547 00:28:39,480 --> 00:28:42,440 Speaker 3: are in the Trump administration, and you know, for us, 548 00:28:42,480 --> 00:28:44,680 Speaker 3: we want to look at this holistically. I want to 549 00:28:44,680 --> 00:28:46,640 Speaker 3: be able to look and not have to worry about 550 00:28:46,680 --> 00:28:48,320 Speaker 3: if there's a D and R next to the person 551 00:28:48,480 --> 00:28:51,320 Speaker 3: that we're finding data on. And so we definitely, we 552 00:28:51,360 --> 00:28:53,760 Speaker 3: definitely had that conversation about stand independent. Now are we 553 00:28:53,880 --> 00:28:57,680 Speaker 3: here to help. Absolutely, But the independent part I think 554 00:28:57,680 --> 00:29:00,320 Speaker 3: gives us more flexibility to focus. I mean, I lively 555 00:29:00,400 --> 00:29:02,560 Speaker 3: messaged her two days ago, was like, hey, look I 556 00:29:02,640 --> 00:29:04,720 Speaker 3: need a tool where I can do a bulk in 557 00:29:04,840 --> 00:29:06,000 Speaker 3: go officer search. 558 00:29:06,680 --> 00:29:08,640 Speaker 1: And like the next morning she's like, it's done. 559 00:29:09,040 --> 00:29:13,080 Speaker 3: You know, there's no approvals, there's no board of directors. 560 00:29:12,880 --> 00:29:14,920 Speaker 1: It's like, we. 561 00:29:14,800 --> 00:29:17,040 Speaker 3: Find it valuable, we jump on it, and we get 562 00:29:17,080 --> 00:29:21,200 Speaker 3: it done amazingly, just amazing speed. And so I love 563 00:29:21,240 --> 00:29:24,200 Speaker 3: that flexibility and I love not being tied to a 564 00:29:24,200 --> 00:29:27,560 Speaker 3: certain political party or another. The goal is for all 565 00:29:27,600 --> 00:29:30,040 Speaker 3: Americans to have access to where their money is going, 566 00:29:30,080 --> 00:29:33,760 Speaker 3: and we'll just keep building tools as problems arise. That's 567 00:29:33,800 --> 00:29:36,480 Speaker 3: the future and that's the goal. Is just to keep 568 00:29:36,520 --> 00:29:39,360 Speaker 3: serving the American people by giving them transparency through data. 569 00:29:40,760 --> 00:29:42,480 Speaker 2: What kind of feedback have you received? 570 00:29:42,520 --> 00:29:45,720 Speaker 4: I mean, obviously I sent a nice message to Data 571 00:29:45,720 --> 00:29:48,680 Speaker 4: Republican herself that this is fantastic, and Elon has said 572 00:29:48,680 --> 00:29:50,880 Speaker 4: you're great, and Charlie Kirkis said you're great, and a 573 00:29:50,920 --> 00:29:54,080 Speaker 4: lot of Twitter fhows. What kind of feedback are you 574 00:29:54,120 --> 00:29:58,000 Speaker 4: getting in terms of hate or pushback or criticism. 575 00:29:57,360 --> 00:30:02,400 Speaker 3: And what is that criticism, Well, the biggest criticism is 576 00:30:02,440 --> 00:30:04,040 Speaker 3: that we're causing. 577 00:30:03,680 --> 00:30:05,960 Speaker 1: People to lose jobs. Right. 578 00:30:06,160 --> 00:30:07,560 Speaker 3: You know a lot of these a lot of this 579 00:30:07,640 --> 00:30:10,680 Speaker 3: money was propping up, you know, these businesses that you know, 580 00:30:10,760 --> 00:30:14,040 Speaker 3: even like popping up media companies, you know, political was 581 00:30:14,080 --> 00:30:16,000 Speaker 3: taking that's going to get blows my mind. And most 582 00:30:16,040 --> 00:30:19,320 Speaker 3: how much money political not political, but media companies were 583 00:30:19,320 --> 00:30:22,000 Speaker 3: getting like political, like why are they getting these huge 584 00:30:22,000 --> 00:30:25,920 Speaker 3: subscription numbers? And so one of the one of the criticisms, 585 00:30:26,160 --> 00:30:29,480 Speaker 3: oh you're costing jobs. Well I'm sorry, but when the 586 00:30:29,560 --> 00:30:31,720 Speaker 3: government decided to shut the country down for COVID, I 587 00:30:31,840 --> 00:30:34,040 Speaker 3: lost my job, you know what I mean, Like nobody 588 00:30:34,080 --> 00:30:36,640 Speaker 3: cried about it. Then it's just part of how it works. 589 00:30:36,680 --> 00:30:38,920 Speaker 3: If it's if it's not an effective part of government, 590 00:30:39,000 --> 00:30:40,840 Speaker 3: it's got to go. And I know that sucks for 591 00:30:40,920 --> 00:30:42,680 Speaker 3: the family, and I know that sucks for the person 592 00:30:42,760 --> 00:30:45,520 Speaker 3: that's that's there and working. But this isn't a charity. 593 00:30:45,760 --> 00:30:47,840 Speaker 3: Our government is not a charity, and we got to 594 00:30:47,840 --> 00:30:49,920 Speaker 3: get away from that mindset. It needs to be efficient, 595 00:30:50,240 --> 00:30:52,000 Speaker 3: and it needs to serve the people, and it needs 596 00:30:52,000 --> 00:30:56,040 Speaker 3: to steward our money well or will stop trusting him 597 00:30:56,080 --> 00:30:58,920 Speaker 3: with it? You know, that the government needs to fear 598 00:30:59,040 --> 00:31:01,800 Speaker 3: the people again, and they don't. They just they just 599 00:31:02,800 --> 00:31:06,000 Speaker 3: pillage and pillage and pillage with no end in sight. 600 00:31:06,640 --> 00:31:09,320 Speaker 3: And you know, I hope we can keep moving that 601 00:31:09,440 --> 00:31:10,040 Speaker 3: ball forward. 602 00:31:11,480 --> 00:31:11,760 Speaker 1: Sean. 603 00:31:11,920 --> 00:31:15,520 Speaker 4: I'm so impressed with you, guys. There's so much talent 604 00:31:15,640 --> 00:31:19,280 Speaker 4: in this country. There's so much incredible talent on the 605 00:31:19,400 --> 00:31:23,040 Speaker 4: sidelines in this country that we if we call it 606 00:31:23,240 --> 00:31:23,640 Speaker 4: to bear. 607 00:31:23,840 --> 00:31:26,400 Speaker 2: You know, you see these nations that rise. 608 00:31:26,240 --> 00:31:29,320 Speaker 4: Up and fight off an imperialist country, or fight off 609 00:31:29,360 --> 00:31:32,160 Speaker 4: their enemy, and everyone pitches in, you know, the World 610 00:31:32,200 --> 00:31:35,680 Speaker 4: War two, Rosie the Riveter. I see this mindset of 611 00:31:35,760 --> 00:31:38,560 Speaker 4: people like you. You know, you get your background, mister beast. 612 00:31:38,560 --> 00:31:40,360 Speaker 4: Who would have guessed I mean, and I don't know 613 00:31:40,440 --> 00:31:43,840 Speaker 4: data Republicans background, but obviously she's brilliant. I see these people, 614 00:31:43,880 --> 00:31:47,280 Speaker 4: everybody kind of pitching in in a sort of altruistic 615 00:31:47,360 --> 00:31:49,840 Speaker 4: way that says, hey, let's fix our country, guys. 616 00:31:50,200 --> 00:31:50,720 Speaker 1: And I got it. 617 00:31:50,920 --> 00:31:51,640 Speaker 2: I mean, it's a. 618 00:31:51,640 --> 00:31:54,280 Speaker 4: Little corny and a little hokey maybe that I feel 619 00:31:54,320 --> 00:31:56,600 Speaker 4: this way, but it really inspires me. 620 00:31:56,920 --> 00:31:59,440 Speaker 2: It does. And by that I mean to say thank 621 00:31:59,480 --> 00:32:00,600 Speaker 2: you for the great work you're doing. 622 00:32:02,760 --> 00:32:06,000 Speaker 1: Absolutely, I I think like a lot of people. 623 00:32:06,080 --> 00:32:09,680 Speaker 3: I just wanted to be left alone, and we realized 624 00:32:09,760 --> 00:32:12,400 Speaker 3: after the Hurricane Helene storm that we had to step 625 00:32:12,480 --> 00:32:12,680 Speaker 3: back in. 626 00:32:12,800 --> 00:32:14,240 Speaker 1: The people who want to be left loan have to 627 00:32:14,360 --> 00:32:14,880 Speaker 1: enter the chat. 628 00:32:15,520 --> 00:32:18,040 Speaker 3: And you know, even I knew that being political is 629 00:32:18,120 --> 00:32:20,920 Speaker 3: a risk, and I even told my family, Look, I'd 630 00:32:21,000 --> 00:32:23,400 Speaker 3: rather lose my job than lose my country. And so 631 00:32:23,840 --> 00:32:26,200 Speaker 3: you know, about four months ago I became political in 632 00:32:26,280 --> 00:32:28,800 Speaker 3: the sense of getting active and making sure that our 633 00:32:28,840 --> 00:32:31,800 Speaker 3: government's doing what it's supposed to be doing. And that 634 00:32:31,880 --> 00:32:34,880 Speaker 3: shouldn't be that shouldn't be controversial. We should all be active. 635 00:32:34,880 --> 00:32:36,760 Speaker 3: We should be going to our local city council meeting. 636 00:32:37,160 --> 00:32:39,560 Speaker 3: See what these people are doing, hold them accountable. And 637 00:32:39,560 --> 00:32:41,320 Speaker 3: that's the big thing with Data Republican is we're giving 638 00:32:41,360 --> 00:32:42,000 Speaker 3: people a tool. 639 00:32:41,920 --> 00:32:42,280 Speaker 1: To see that. 640 00:32:42,880 --> 00:32:45,280 Speaker 3: But you need to go on your local level, hold 641 00:32:45,440 --> 00:32:49,160 Speaker 3: your local politicians accountable, hold your state accountable. They're all 642 00:32:49,280 --> 00:32:52,120 Speaker 3: wasting your money without a doubt, you know, go look 643 00:32:52,120 --> 00:32:53,960 Speaker 3: at the things or spending. Go to the budget meeting, 644 00:32:54,120 --> 00:32:56,160 Speaker 3: ask for compy of the budget and throw it into AI, 645 00:32:56,760 --> 00:32:59,280 Speaker 3: take it, cut, paste it into gross and have it 646 00:32:59,400 --> 00:33:02,560 Speaker 3: break down what they're spending. Your city barged on and 647 00:33:02,640 --> 00:33:05,120 Speaker 3: make sure it makes sense. And if it doesn't, make 648 00:33:05,200 --> 00:33:09,200 Speaker 3: it known, it takes everyone being involved. The reason we 649 00:33:09,280 --> 00:33:11,200 Speaker 3: got too we're at is because we all turned our 650 00:33:11,240 --> 00:33:13,760 Speaker 3: heads and just focused on us and said, I'm sure 651 00:33:13,760 --> 00:33:15,840 Speaker 3: they've got it, and we turned around a decade later 652 00:33:15,880 --> 00:33:17,160 Speaker 3: I'm like, oh my god, I think they. 653 00:33:17,160 --> 00:33:17,640 Speaker 1: Don't got it. 654 00:33:17,800 --> 00:33:20,560 Speaker 2: They've been self feeling. John Hendricks, you are awesome. 655 00:33:20,800 --> 00:33:21,400 Speaker 1: Will be in touch. 656 00:33:21,600 --> 00:33:22,800 Speaker 2: Keep up the great work, my man. 657 00:33:24,440 --> 00:33:30,320 Speaker 1: Thank you so much, ELSNS looking, thank you, and good 658 00:33:30,480 --> 00:33:30,640 Speaker 1: night