1 00:00:00,080 --> 00:00:03,800 Speaker 1: It's never been more important to diversify your financial portfolio. Well, 2 00:00:03,840 --> 00:00:06,880 Speaker 1: that's right. The S ANDP is down twenty percent from 3 00:00:06,880 --> 00:00:09,200 Speaker 1: the last year, and this year looks even worse. Gold 4 00:00:09,280 --> 00:00:12,560 Speaker 1: and precious metals offer a hedge against inflation and stock 5 00:00:12,640 --> 00:00:16,479 Speaker 1: market volatility, and Legacy Precious Metals is the company can 6 00:00:16,480 --> 00:00:19,200 Speaker 1: and I trust protect your retirement account by rolling it 7 00:00:19,200 --> 00:00:21,920 Speaker 1: into a gold back I ra or have medals shipped 8 00:00:21,920 --> 00:00:24,960 Speaker 1: directly to your door. Call our friends at Legacy Precious 9 00:00:25,000 --> 00:00:28,600 Speaker 1: Medals today at eight six six, six nine one twenty 10 00:00:28,600 --> 00:00:59,760 Speaker 1: one seventy three, or a visit by Legacy goold dot com. 11 00:01:00,920 --> 00:01:05,080 Speaker 1: Look at threting. Oh we're rearing to go, aren't we? 12 00:01:05,360 --> 00:01:08,560 Speaker 1: Take that? It was repped up? Take what I'm rerapped up? 13 00:01:09,520 --> 00:01:11,040 Speaker 1: I got all kinds of stuff in front of me. 14 00:01:11,080 --> 00:01:15,039 Speaker 1: It pisses me off. Oh I'm gonna be pissed off 15 00:01:15,040 --> 00:01:16,919 Speaker 1: for the rest of the day. I'm just warning you. 16 00:01:17,080 --> 00:01:20,480 Speaker 1: I was that different than yesterday. Yesterday I was about 17 00:01:20,520 --> 00:01:23,119 Speaker 1: eighty seven percent pissed off. Today I'm heading for a hunt. 18 00:01:23,200 --> 00:01:24,840 Speaker 1: You have to get the pissed off meter every day, 19 00:01:24,880 --> 00:01:28,240 Speaker 1: then that's right, Not always seems like that's if your 20 00:01:28,560 --> 00:01:31,679 Speaker 1: makeup is to be sure, picked off right, but sometimes 21 00:01:31,680 --> 00:01:35,399 Speaker 1: there's little lulls. I'm saying, I'm I'm pinned in the 22 00:01:35,400 --> 00:01:39,320 Speaker 1: red the whole time today. That expression, I like it, 23 00:01:39,720 --> 00:01:41,680 Speaker 1: pinned in the red well, you know, like on a 24 00:01:41,800 --> 00:01:44,600 Speaker 1: volume meter. Yeah, but it's not a real expression. Pinned 25 00:01:44,600 --> 00:01:46,479 Speaker 1: in the red. Pinned in the red means you're over 26 00:01:46,520 --> 00:01:49,320 Speaker 1: modulating on a You're starting to pick up your own 27 00:01:49,360 --> 00:01:52,520 Speaker 1: lexicon and jargon like newsom. Yeah. Yeah, I've noticed that 28 00:01:52,920 --> 00:01:56,400 Speaker 1: dropping in these phrases lately. It's works for him. Look 29 00:01:56,440 --> 00:01:59,000 Speaker 1: at this, He's gonna be president, so what the hell. 30 00:01:59,080 --> 00:02:01,400 Speaker 1: Maybe he's got me. I'm just excited by that. Yeah, 31 00:02:01,400 --> 00:02:03,800 Speaker 1: I know, and I think we got we got tipped 32 00:02:03,840 --> 00:02:05,640 Speaker 1: off the other day when he vtailed that bill on 33 00:02:05,640 --> 00:02:07,880 Speaker 1: the joke because it was gonna be Governor Harrow. Oh yeah, 34 00:02:07,880 --> 00:02:11,160 Speaker 1: and he heard you and he heard that analysts say 35 00:02:11,240 --> 00:02:13,120 Speaker 1: that in the article and said, I don't want to 36 00:02:13,120 --> 00:02:16,440 Speaker 1: be Governor Harrow for president. Look, I know they listen 37 00:02:16,520 --> 00:02:19,120 Speaker 1: up there. I mean, we we get a readout. I 38 00:02:19,160 --> 00:02:21,120 Speaker 1: don't know if you've seen this, but no, I have not. 39 00:02:21,880 --> 00:02:24,000 Speaker 1: No this I'm not making this one up here. The 40 00:02:24,200 --> 00:02:27,799 Speaker 1: cities in the Red Cities where our podcast is popular. 41 00:02:28,880 --> 00:02:31,239 Speaker 1: Oh that's no idea. I have not seen outside of 42 00:02:31,280 --> 00:02:37,120 Speaker 1: Los Angeles. I've heard about this. Sack said, why download audience? Yea, Sacramento. 43 00:02:37,919 --> 00:02:40,320 Speaker 1: Is that lots of podcast I'm not making it up. Yeah, 44 00:02:40,360 --> 00:02:43,079 Speaker 1: lots of podcasts. Yeah, that's right. Who do you think 45 00:02:43,120 --> 00:02:47,160 Speaker 1: that is. It's a one industry town. And I think 46 00:02:47,200 --> 00:02:49,880 Speaker 1: that really got reped up with heads on the stick 47 00:02:50,000 --> 00:02:54,799 Speaker 1: years ago. That's right, permanent fans. They actually took. They 48 00:02:54,800 --> 00:02:57,639 Speaker 1: actually showed on some computer screen our website with one 49 00:02:57,639 --> 00:02:59,359 Speaker 1: of the politicians heads on a stick, and he was 50 00:02:59,400 --> 00:03:01,560 Speaker 1: pointing out like is that look at that? So I'm 51 00:03:01,600 --> 00:03:03,400 Speaker 1: telling you because people love it when you talk about 52 00:03:03,600 --> 00:03:06,680 Speaker 1: sure really anybody else, they're always politicians as much as 53 00:03:06,680 --> 00:03:08,760 Speaker 1: we do. Nobody does, no, And they were always worried. 54 00:03:08,760 --> 00:03:10,640 Speaker 1: They never know what's gonna catch on. And I'm telling 55 00:03:10,680 --> 00:03:13,880 Speaker 1: you somebody up there hurt President Heroin and call was 56 00:03:13,960 --> 00:03:18,600 Speaker 1: made Vitoh that's happened an hour after we talked. That's right, 57 00:03:21,240 --> 00:03:24,360 Speaker 1: Ken just vetoed that bill. No Governor Heroin, we can't 58 00:03:24,360 --> 00:03:28,880 Speaker 1: have that right speaking of Governor Heroin. I'm gonna use 59 00:03:28,919 --> 00:03:32,840 Speaker 1: it anyway, period, full stop. Uh. You know, this story 60 00:03:32,880 --> 00:03:35,400 Speaker 1: made news today if you weren't in a coma and 61 00:03:35,480 --> 00:03:37,920 Speaker 1: twenty twenty and you're listening to the show, which was dominated, 62 00:03:37,920 --> 00:03:41,200 Speaker 1: of course by the pandemic, there was an announcement made 63 00:03:41,200 --> 00:03:43,880 Speaker 1: by Governor Heroin. I believe it was that summer about 64 00:03:43,920 --> 00:03:47,760 Speaker 1: two years ago, that we're gonna stop selling new cars 65 00:03:47,760 --> 00:03:51,960 Speaker 1: that are gas powered, and we're gonna do that completely 66 00:03:52,760 --> 00:03:56,360 Speaker 1: by the year twenty thirty five. So if we look 67 00:03:56,400 --> 00:03:58,440 Speaker 1: to the future and you're trying to shop for a 68 00:03:58,480 --> 00:04:01,000 Speaker 1: gas powered car, a new car now, not a used car, 69 00:04:01,840 --> 00:04:04,440 Speaker 1: you won't be able to find, allegedly at anywhere for 70 00:04:04,520 --> 00:04:07,800 Speaker 1: sale in the state, a gasoline powered car. And the 71 00:04:07,800 --> 00:04:10,520 Speaker 1: reason it's in the news today two years later is 72 00:04:10,560 --> 00:04:12,920 Speaker 1: that they're going to start to phase it in. This 73 00:04:12,960 --> 00:04:15,839 Speaker 1: is all from the California Air Resources Board. By the way, 74 00:04:16,040 --> 00:04:18,279 Speaker 1: Mary Nichols, I think as John is gone, I think 75 00:04:18,320 --> 00:04:21,760 Speaker 1: she's yes, she is. Yeah. Some guy came from the 76 00:04:21,800 --> 00:04:23,560 Speaker 1: federal government. I saw I was going to head up 77 00:04:23,560 --> 00:04:26,039 Speaker 1: the You know, they're all the same person. I know 78 00:04:26,120 --> 00:04:27,800 Speaker 1: that it doesn't matter what their name is, they all 79 00:04:27,839 --> 00:04:31,680 Speaker 1: look the same. That's true. They're all these gnarled little trolls. 80 00:04:33,200 --> 00:04:36,479 Speaker 1: So it's by the way, is allegedly what is it 81 00:04:36,520 --> 00:04:38,960 Speaker 1: about twelve percent of new cars sold in the state 82 00:04:39,600 --> 00:04:43,080 Speaker 1: are non fossil fuel emitting cars. I guess is that's 83 00:04:43,080 --> 00:04:47,000 Speaker 1: a mouthful non fossil fuel emitting cars. I like that. 84 00:04:47,960 --> 00:04:52,240 Speaker 1: So it's thirty five percent by twenty twenty six, it 85 00:04:52,360 --> 00:04:55,560 Speaker 1: climbs to sixty eight percent by twenty thirty and then 86 00:04:55,720 --> 00:04:58,479 Speaker 1: twenty thirty five all of the new cars sold in 87 00:04:58,520 --> 00:05:02,680 Speaker 1: the state half easy road. Now let's wait and see 88 00:05:03,000 --> 00:05:08,560 Speaker 1: if anybody is going to ask Governor Heroin, where where 89 00:05:08,600 --> 00:05:12,200 Speaker 1: are we going to get the electricity to power millions 90 00:05:12,200 --> 00:05:15,080 Speaker 1: of electric cars? Where where's that coming from? What are 91 00:05:15,120 --> 00:05:18,600 Speaker 1: the upgrades to the grid? What are the news sources 92 00:05:18,680 --> 00:05:21,120 Speaker 1: of electrical power that are going to be in place 93 00:05:21,320 --> 00:05:24,680 Speaker 1: by twenty thirty five twenty twenty six, is he's less 94 00:05:24,680 --> 00:05:26,200 Speaker 1: than four years away? We have to be a thirty 95 00:05:26,200 --> 00:05:30,000 Speaker 1: five percent. Then they're not selling like that, No they're not. 96 00:05:30,040 --> 00:05:33,000 Speaker 1: They're they're too expensive for most people. That is a 97 00:05:33,000 --> 00:05:34,680 Speaker 1: big sticking point in a state with a lot of 98 00:05:34,680 --> 00:05:37,919 Speaker 1: poor people. Yeah, they're there. They're a lot of the 99 00:05:38,000 --> 00:05:43,479 Speaker 1: models cost double what the lower classes make, right, So 100 00:05:44,000 --> 00:05:47,680 Speaker 1: that's just announced in this Inflation Reduction Act whatever it's 101 00:05:47,720 --> 00:05:51,200 Speaker 1: called tax credits for people that buy electric but we 102 00:05:51,360 --> 00:05:53,760 Speaker 1: learned that a lot of cars don't qualify right now, 103 00:05:53,920 --> 00:05:58,000 Speaker 1: right because it has to be uh USA made entirely. 104 00:05:58,600 --> 00:06:02,000 Speaker 1: And a lot of the materials come from overseas because 105 00:06:02,400 --> 00:06:07,200 Speaker 1: for example, the mining for the cobalt and the lithium, 106 00:06:07,200 --> 00:06:10,560 Speaker 1: they come from places like the Congo in Central Africa, 107 00:06:11,200 --> 00:06:14,400 Speaker 1: where the Chinese own most of the mining rights, and 108 00:06:14,560 --> 00:06:19,240 Speaker 1: the Chinese employ women and children as slave laborers. Slavery 109 00:06:19,440 --> 00:06:23,800 Speaker 1: never went away, just morphed into more respectable industries, and 110 00:06:23,839 --> 00:06:27,680 Speaker 1: so the Chinese are enslaving African women and men and 111 00:06:27,839 --> 00:06:32,960 Speaker 1: children to mine, you know, cobalt, and it's one of 112 00:06:32,960 --> 00:06:35,800 Speaker 1: the major elements you need to build a battery for 113 00:06:35,839 --> 00:06:40,080 Speaker 1: an electric car. And we have no control over these mines. 114 00:06:40,440 --> 00:06:44,120 Speaker 1: We own very few of them. Eighty ninety percent are 115 00:06:44,120 --> 00:06:47,680 Speaker 1: owned by the by the Chinese. So they have to 116 00:06:47,680 --> 00:06:52,080 Speaker 1: come from America, from America or American owned companies, I guess, 117 00:06:52,680 --> 00:06:55,520 Speaker 1: and that's impossible. So I don't know what all these 118 00:06:55,560 --> 00:06:58,080 Speaker 1: mandates are. I guess this is massive virtue signaling in 119 00:06:58,120 --> 00:07:03,200 Speaker 1: an election year exactly because I saw they had you know, 120 00:07:03,200 --> 00:07:05,479 Speaker 1: they only times had a pull out, which you know, 121 00:07:05,640 --> 00:07:08,240 Speaker 1: makes a normal person's head snap. Newsom has like a 122 00:07:08,279 --> 00:07:11,080 Speaker 1: fifty two percent approval rating in the state, you know, 123 00:07:11,120 --> 00:07:14,360 Speaker 1: and you just want to like punch yourself in the nose. 124 00:07:14,440 --> 00:07:17,960 Speaker 1: I mean, I okay, And I said, well, the main 125 00:07:18,040 --> 00:07:20,320 Speaker 1: issues that Newsome voters are into, and number one is 126 00:07:20,360 --> 00:07:23,120 Speaker 1: climate change. It's like, all right, so you know that's 127 00:07:23,160 --> 00:07:25,680 Speaker 1: his audience. So he's got to issue all kinds of 128 00:07:25,760 --> 00:07:28,760 Speaker 1: virtue signaling statements. Yes, by twenty thirty five, we willn't 129 00:07:28,840 --> 00:07:32,360 Speaker 1: sell gas powered cars. Well, what are we driving the 130 00:07:32,560 --> 00:07:36,440 Speaker 1: electric cars really for? Who's going to buy one for me? 131 00:07:36,840 --> 00:07:40,800 Speaker 1: And uh, who's who's building the electrical grid? But nobody 132 00:07:40,840 --> 00:07:45,000 Speaker 1: asks him that gering to you. You won't see one idiot, 133 00:07:45,160 --> 00:07:48,560 Speaker 1: stinking reporter in the state say where are we getting 134 00:07:48,600 --> 00:07:51,520 Speaker 1: the electrical grid from? And how are people supposed to 135 00:07:51,520 --> 00:07:55,440 Speaker 1: get money? Go talk to people in East La. Go ahead, 136 00:07:55,480 --> 00:07:57,920 Speaker 1: ask him the guys who go work in the factories 137 00:07:58,000 --> 00:08:01,280 Speaker 1: or were lugging Amazon boxes for twelve dollars an hour 138 00:08:01,400 --> 00:08:03,520 Speaker 1: whatever they pay, Ask them where they're going to get 139 00:08:03,560 --> 00:08:06,960 Speaker 1: the seventy five thousand dollars for that Tesla. I really 140 00:08:06,960 --> 00:08:10,040 Speaker 1: shoubt that within four years they can put the infrastructure together, 141 00:08:10,040 --> 00:08:13,080 Speaker 1: which is the charging stations, and get the prices down 142 00:08:13,160 --> 00:08:15,160 Speaker 1: thirty five. I have no idea, but that's zero. Was 143 00:08:15,160 --> 00:08:17,280 Speaker 1: supposed to be selling new cars, but you know it's 144 00:08:17,280 --> 00:08:19,160 Speaker 1: going to happen. A lot of people are just going 145 00:08:19,200 --> 00:08:21,640 Speaker 1: to buy used cars and continue on with the fossil fuels. 146 00:08:21,640 --> 00:08:23,920 Speaker 1: Are just going to not buy new cars because either 147 00:08:23,960 --> 00:08:26,000 Speaker 1: they can't afford them and they don't want it. That's 148 00:08:26,000 --> 00:08:29,720 Speaker 1: what's going to happen. This is only at new produced cars, 149 00:08:29,800 --> 00:08:31,520 Speaker 1: and none of the other forty United States are going 150 00:08:31,560 --> 00:08:33,520 Speaker 1: to do this, and that includes a lot of poor 151 00:08:33,559 --> 00:08:36,000 Speaker 1: people anyway, or buying used cars. There's not that many 152 00:08:36,720 --> 00:08:39,600 Speaker 1: people at the lower income levels who buy brand new 153 00:08:39,679 --> 00:08:44,480 Speaker 1: cars releases. So mostly that seventy five hundred dollars subsidy 154 00:08:44,800 --> 00:08:47,800 Speaker 1: is a subsidy for wealthy people. Wealthy people are going 155 00:08:47,840 --> 00:08:50,959 Speaker 1: to get that off their off their Tesla's that that 156 00:08:51,120 --> 00:08:57,240 Speaker 1: that's that's It's like the college loan forgiveness bill today. 157 00:08:57,360 --> 00:09:01,240 Speaker 1: That's going to affect the wealthy. By the way, we're 158 00:09:01,360 --> 00:09:04,920 Speaker 1: way out in front. Even the weeny European countries such 159 00:09:04,920 --> 00:09:08,520 Speaker 1: as France, Spain, and Denmark have goals of phasing out 160 00:09:08,520 --> 00:09:10,960 Speaker 1: the sale of new gasoline powered vehicles. But they don't 161 00:09:10,960 --> 00:09:13,360 Speaker 1: have concrete mandates like we do. They don't have a 162 00:09:13,360 --> 00:09:15,560 Speaker 1: certain year where it's going to be zero. I read 163 00:09:15,840 --> 00:09:20,000 Speaker 1: they're just pushing it. I obsessively read all the latest 164 00:09:20,040 --> 00:09:24,080 Speaker 1: news on manufacturing of electric cars and the costs and 165 00:09:24,120 --> 00:09:28,360 Speaker 1: the availability of the minerals that you need, because I 166 00:09:28,480 --> 00:09:32,240 Speaker 1: suspect this is one of the old time great scams 167 00:09:33,080 --> 00:09:39,520 Speaker 1: in modern history. There is no possible way that they 168 00:09:39,559 --> 00:09:45,959 Speaker 1: can get cars built to meet Newsom's goals or his requirements. 169 00:09:46,120 --> 00:09:49,679 Speaker 1: It's impossible. In fact, the supply chain is going to 170 00:09:49,760 --> 00:09:52,839 Speaker 1: be more choked off. It's getting more difficult to get 171 00:09:52,840 --> 00:09:57,240 Speaker 1: the materials built for electric car batteries, not getting Every 172 00:09:57,400 --> 00:10:00,480 Speaker 1: indicator points to it being more and more difficult in 173 00:10:00,520 --> 00:10:04,319 Speaker 1: the next few years for a whole wide I am 174 00:10:04,360 --> 00:10:09,000 Speaker 1: an a sayer because it's impossible. It is simply a 175 00:10:09,120 --> 00:10:16,320 Speaker 1: cosmetic performance, theatrical bullcrap. It's horse crap. He can't do it. 176 00:10:16,320 --> 00:10:20,160 Speaker 1: It's not gonna have called the California rule. They we 177 00:10:20,280 --> 00:10:22,839 Speaker 1: have a waiver. We have the legal authority to set 178 00:10:22,880 --> 00:10:26,320 Speaker 1: our own auto pollution and mileage rules. Trump tried to 179 00:10:26,320 --> 00:10:29,560 Speaker 1: throw that out but it got halted, so that's the 180 00:10:29,600 --> 00:10:32,960 Speaker 1: reason California can do this with the ban on sales 181 00:10:33,520 --> 00:10:37,679 Speaker 1: of gas powered cars by the year twenty thirty five, 182 00:10:37,800 --> 00:10:42,640 Speaker 1: the new cars. However, there's a challenge by seventeen Republican 183 00:10:42,679 --> 00:10:45,880 Speaker 1: led states. This could end up in the United States 184 00:10:45,960 --> 00:10:49,439 Speaker 1: Supreme Court, and who knows, you know that court leans conservative. 185 00:10:49,920 --> 00:10:52,600 Speaker 1: They may take California's waiver away, which means we would 186 00:10:52,679 --> 00:10:55,040 Speaker 1: not have the ability to do that. Now. Allegedly a 187 00:10:55,040 --> 00:10:57,040 Speaker 1: bunch of states are going to follow us with this, 188 00:10:57,120 --> 00:10:58,760 Speaker 1: but we always hear that, don't we. By the way, 189 00:10:58,760 --> 00:11:00,360 Speaker 1: we heard that in two thousand and six they passed 190 00:11:00,400 --> 00:11:02,679 Speaker 1: the Global Emissions Actors. Yeah, I know, it's been seven 191 00:11:02,720 --> 00:11:05,240 Speaker 1: it's been what sixteen years. Nobody's following they're all gonna 192 00:11:05,240 --> 00:11:08,600 Speaker 1: follow us. This was our gas prices. They didn't follow us. 193 00:11:08,800 --> 00:11:11,120 Speaker 1: This was the sneaky backdoorway, and it started with that 194 00:11:11,280 --> 00:11:15,679 Speaker 1: bonehead Schwarzenegger right on through Brown and Newsom. It's a backdoorway. 195 00:11:15,840 --> 00:11:20,120 Speaker 1: The legislature would never pass something like this, so they 196 00:11:20,240 --> 00:11:23,600 Speaker 1: ran it through the California Air Resources Board, this bunch 197 00:11:23,600 --> 00:11:26,680 Speaker 1: of ninnies who we cannot elect and we cannot remove. 198 00:11:27,400 --> 00:11:30,480 Speaker 1: That's why it's coming out of that Commission. We got 199 00:11:30,520 --> 00:11:32,880 Speaker 1: more coming up, John and Ken, okay if I all right? 200 00:11:32,920 --> 00:11:34,440 Speaker 1: So the other thing we know that's got you in 201 00:11:34,480 --> 00:11:36,520 Speaker 1: the red because you already tried to talk about it throwing. 202 00:11:36,640 --> 00:11:38,920 Speaker 1: The first thing we talked about is the student debt 203 00:11:39,160 --> 00:11:43,520 Speaker 1: decision by biding. Oh my god, well, did you see 204 00:11:44,360 --> 00:11:47,880 Speaker 1: that you can get your college loan forgiven up to 205 00:11:48,280 --> 00:11:54,840 Speaker 1: ten thousand dollars if you and your spouse make two 206 00:11:55,120 --> 00:11:58,640 Speaker 1: hundred and fifty thousand dollars a year or less a 207 00:11:58,800 --> 00:12:01,760 Speaker 1: quarter of a million dollars. You two could be hauling 208 00:12:01,840 --> 00:12:05,640 Speaker 1: in and you get ten thousand dollars of your college 209 00:12:05,679 --> 00:12:09,920 Speaker 1: loans forgive, forgiven, eliminated. Looked it up among borrowers with 210 00:12:09,960 --> 00:12:13,319 Speaker 1: outstanding student debt, the median dead amount in twenty twenty 211 00:12:13,320 --> 00:12:16,480 Speaker 1: one was between twenty thousand and twenty five thousand. I 212 00:12:16,480 --> 00:12:19,760 Speaker 1: thought it'd be higher actually, but in twenty twenty, bachelor's 213 00:12:19,760 --> 00:12:22,640 Speaker 1: degree earners from public and private, nonprofit for year schools 214 00:12:22,840 --> 00:12:24,960 Speaker 1: who graduated with student debt had an average debt of 215 00:12:25,000 --> 00:12:28,199 Speaker 1: twenty eight thousand, four hundred. So yeah, this would put 216 00:12:28,200 --> 00:12:31,080 Speaker 1: a significant dent. And you know who's going to pay 217 00:12:31,120 --> 00:12:37,959 Speaker 1: for it? Everybody else? Why does everyone else who paid 218 00:12:38,000 --> 00:12:44,400 Speaker 1: their college debts or paid cash or didn't go to college. 219 00:12:44,880 --> 00:12:49,520 Speaker 1: Is this is three hundred billion dollars because these are 220 00:12:49,559 --> 00:12:55,800 Speaker 1: voters three hundred billion dollars of a giveaway them. Yeah, 221 00:12:55,800 --> 00:12:58,600 Speaker 1: I know, but there's way more voters who did aren't 222 00:12:58,600 --> 00:13:01,160 Speaker 1: going to benefit from this. I think it's only I 223 00:13:01,200 --> 00:13:03,000 Speaker 1: think it's only thirteen percent of the country that's going 224 00:13:03,040 --> 00:13:05,920 Speaker 1: to benefit from this. What why? Why? Why are we 225 00:13:05,920 --> 00:13:08,439 Speaker 1: bailing them out? Do you know what's gonna cost. It's 226 00:13:08,440 --> 00:13:10,160 Speaker 1: gonna cost they pay for it when it comes to 227 00:13:10,200 --> 00:13:14,600 Speaker 1: federal money. You know, it's more deficit. People just don't 228 00:13:14,600 --> 00:13:18,880 Speaker 1: react to that. They're gonna raise taxes to cover this. Yeah, 229 00:13:18,960 --> 00:13:23,640 Speaker 1: I know, there's thirty trillion. There's thirty trillion in death 230 00:13:23,800 --> 00:13:27,080 Speaker 1: Throw it on the pilot debt, right, I mean, that's 231 00:13:27,160 --> 00:13:32,080 Speaker 1: that's absolutely crazy. This is why college has cost so much, 232 00:13:32,559 --> 00:13:35,320 Speaker 1: because the federal government is willing to give out such 233 00:13:35,400 --> 00:13:39,200 Speaker 1: large loans and then if you can't pay the pay it, 234 00:13:39,679 --> 00:13:42,080 Speaker 1: they'll pay it. So do you know that's two thousand 235 00:13:42,120 --> 00:13:48,319 Speaker 1: dollars a person? Two thousand dollars a person taxes, right, right, 236 00:13:48,520 --> 00:13:50,559 Speaker 1: that's how much it is comes out to per person. 237 00:13:50,679 --> 00:13:54,760 Speaker 1: So people making a quarter of a million dollars. Both 238 00:13:54,840 --> 00:13:57,120 Speaker 1: husband and wife are going to get their loans forgiven. 239 00:13:58,200 --> 00:14:01,400 Speaker 1: Everybody else you got to pay two thousand and taxes 240 00:14:01,520 --> 00:14:04,679 Speaker 1: just to cover this. Is that not the craziest, most 241 00:14:04,720 --> 00:14:09,760 Speaker 1: bone headed, most ridiculous, unfair, outrageous garbage policy ever heard of. 242 00:14:10,600 --> 00:14:13,120 Speaker 1: And yet supporters are still mad. They wanted it higher. 243 00:14:13,160 --> 00:14:16,080 Speaker 1: They wanted as high as fifty thousand. Sure, of course, 244 00:14:16,880 --> 00:14:21,880 Speaker 1: because they're they're greedy, irresponsible bastards. You took out the loan, 245 00:14:22,360 --> 00:14:24,760 Speaker 1: you got the education. What do you come into me 246 00:14:24,920 --> 00:14:29,000 Speaker 1: for money for? But we wanted educated workforce. We encourage people, 247 00:14:29,040 --> 00:14:32,640 Speaker 1: so they got education, we should help them they got educated. No, no, no, 248 00:14:32,680 --> 00:14:35,160 Speaker 1: you want to give money to poor people to get 249 00:14:35,160 --> 00:14:38,160 Speaker 1: the smart kids from poor families educated. That's a good thing. 250 00:14:38,720 --> 00:14:41,640 Speaker 1: But but people who already made it. I mean, if 251 00:14:41,640 --> 00:14:43,320 Speaker 1: you're if you're hall In in in a quarter million, you 252 00:14:43,400 --> 00:14:46,920 Speaker 1: made it. You won, you won the race. Congratulations. Now 253 00:14:47,240 --> 00:14:51,480 Speaker 1: you're coming to everybody else more than forty million Americans. Oh, 254 00:14:51,520 --> 00:14:55,040 Speaker 1: a collective one point six trillion dollars in federal student loans. 255 00:14:55,240 --> 00:14:59,360 Speaker 1: That's the number. Yeah, yeah, and it's it's it's it's 256 00:14:59,720 --> 00:15:03,440 Speaker 1: when when the federal government started sending out these generous 257 00:15:03,480 --> 00:15:07,640 Speaker 1: loan packages or agreeing to guarantee these loan packages because 258 00:15:07,680 --> 00:15:11,720 Speaker 1: you get them through the banks. That led the universities 259 00:15:11,800 --> 00:15:15,840 Speaker 1: to start jacking up their fees. Why do you that's why? 260 00:15:15,880 --> 00:15:18,760 Speaker 1: That is the reason, that is overwhelmingly the reason why 261 00:15:19,040 --> 00:15:22,760 Speaker 1: college costs so much. Because people were willing to borrow 262 00:15:22,840 --> 00:15:26,000 Speaker 1: the money and the government was willing to facilitate the loans. 263 00:15:26,160 --> 00:15:28,720 Speaker 1: Why wouldn't the bank if you went into a bank 264 00:15:28,760 --> 00:15:31,600 Speaker 1: and wanted one hundred thousand dollars for college, Well, of 265 00:15:31,640 --> 00:15:35,320 Speaker 1: course they're going to give you the money because the 266 00:15:35,360 --> 00:15:39,680 Speaker 1: government's guaranteeing it. On top of that, you hadn't had 267 00:15:39,720 --> 00:15:43,200 Speaker 1: to pay it. For the last couple of years. During 268 00:15:43,240 --> 00:15:46,560 Speaker 1: the pandemic, they put a moratorium on federal student loan payments. 269 00:15:46,920 --> 00:15:49,120 Speaker 1: It was going to run out. Biden's extending it till 270 00:15:49,240 --> 00:15:51,480 Speaker 1: January of twenty twenty three, but he says that'll be 271 00:15:51,520 --> 00:15:54,040 Speaker 1: the last extension. This is what you get. So it's 272 00:15:54,040 --> 00:15:56,160 Speaker 1: like tenants that don't pay rent. This is what you 273 00:15:56,200 --> 00:16:02,080 Speaker 1: get from a senile president. He's senile and his administration 274 00:16:02,200 --> 00:16:05,960 Speaker 1: is so freaking socialist. But it doesn't even make sense anymore. 275 00:16:06,000 --> 00:16:08,040 Speaker 1: It's not even taken from the rich and given to 276 00:16:08,080 --> 00:16:10,200 Speaker 1: the poor. Now it's taken from the poor and giving 277 00:16:10,200 --> 00:16:13,480 Speaker 1: it to the rich. I really don't. I guess that's 278 00:16:13,520 --> 00:16:16,880 Speaker 1: just gross incompetence. The hell would you do that for? 279 00:16:18,120 --> 00:16:20,520 Speaker 1: Why would you? Why would you? Tax? Doing it? Because 280 00:16:20,520 --> 00:16:22,480 Speaker 1: they think it appeals to a base of voters that 281 00:16:22,520 --> 00:16:25,800 Speaker 1: they want to see in November. You at tax poor 282 00:16:25,840 --> 00:16:29,480 Speaker 1: people to give rich people a break out their college loans. 283 00:16:29,520 --> 00:16:31,920 Speaker 1: Have you not seen Biden and the Democrats are rising 284 00:16:31,920 --> 00:16:35,000 Speaker 1: in the polls? Yeah, we'll see in November. Okay, and 285 00:16:35,160 --> 00:16:38,760 Speaker 1: make it a comeback. Where'd you get that from the media? Yes, 286 00:16:38,880 --> 00:16:42,840 Speaker 1: headlines today's approval ratings over forty time in a while. 287 00:16:42,960 --> 00:16:46,000 Speaker 1: Oh give it, I'm having a heart attack here. Only 288 00:16:46,160 --> 00:16:49,000 Speaker 1: only six out of ten Americans can't stand him. They 289 00:16:49,000 --> 00:16:50,880 Speaker 1: weren't covering it when he was down in the thirties. 290 00:16:51,560 --> 00:16:55,560 Speaker 1: That's all. It's all. It's all horsecrap, it's all big, 291 00:16:55,600 --> 00:16:58,600 Speaker 1: stupid Nothing really matters until we get to November when 292 00:16:58,600 --> 00:17:00,520 Speaker 1: people actually vote. A lock and half up in between 293 00:17:00,560 --> 00:17:03,960 Speaker 1: now and then, I hate following, but but but it's 294 00:17:04,080 --> 00:17:06,080 Speaker 1: it's bad policy. I don't care what his reason is. 295 00:17:06,200 --> 00:17:09,720 Speaker 1: I don't care that's bad, bad, bad policy to take 296 00:17:09,960 --> 00:17:13,840 Speaker 1: two thousand bucks from every person in America and get 297 00:17:13,880 --> 00:17:17,040 Speaker 1: it to people making six figures. Good lord, all right, 298 00:17:17,040 --> 00:17:19,240 Speaker 1: we got more coming up, John and can Calf. All right, 299 00:17:19,280 --> 00:17:21,040 Speaker 1: we're gonna bring back the Boys line to just the 300 00:17:21,119 --> 00:17:23,760 Speaker 1: day after tomorrow, on Friday. So to leave a message, 301 00:17:23,880 --> 00:17:26,399 Speaker 1: of course, use the iHeartRadio app, which you hear a 302 00:17:26,400 --> 00:17:29,520 Speaker 1: lot about on this station. Use the microphone I kond 303 00:17:29,520 --> 00:17:31,199 Speaker 1: of leave a message called the toe free number one 304 00:17:31,200 --> 00:17:34,320 Speaker 1: eight seven seven moist eighty six one eight seven seven 305 00:17:34,440 --> 00:17:37,960 Speaker 1: six six four seven eight eight six before we go on. 306 00:17:38,960 --> 00:17:40,879 Speaker 1: I want to make sure you got more stuff you're 307 00:17:40,920 --> 00:17:42,480 Speaker 1: angry about, okay, because I don't want to. I don't 308 00:17:42,480 --> 00:17:44,400 Speaker 1: want to interfere with you. Oh yeah, No, I'm going 309 00:17:44,480 --> 00:17:47,480 Speaker 1: all day. Oh okay, because the next or I was 310 00:17:47,480 --> 00:17:51,040 Speaker 1: gonna do is really for me. So I'm not angry 311 00:17:51,040 --> 00:17:53,960 Speaker 1: about it. I don't have to vindicate something I believe 312 00:17:54,000 --> 00:17:55,480 Speaker 1: my whole life, and I can't believe I see it 313 00:17:55,480 --> 00:17:57,400 Speaker 1: in print. But you go ahead. Are you angry about 314 00:17:57,400 --> 00:18:00,679 Speaker 1: something we missed her? No? No, no for network Howard Carvan, 315 00:18:00,760 --> 00:18:02,840 Speaker 1: we got we got four hours. I don't want to 316 00:18:03,400 --> 00:18:06,360 Speaker 1: overwhelm the first half hour here. Well, generally you come 317 00:18:06,359 --> 00:18:09,360 Speaker 1: back and just get angry again. Well, the one more 318 00:18:09,359 --> 00:18:14,240 Speaker 1: thing about the Biden loan giveaway. Yes, it's probably not 319 00:18:14,280 --> 00:18:18,000 Speaker 1: even legal, because we were talking. Yeah, they probably will 320 00:18:18,040 --> 00:18:23,879 Speaker 1: be a challenge. Well, yeah, because constitutionally, Congress has to 321 00:18:23,920 --> 00:18:28,639 Speaker 1: create a law that Biden can then sign and do it. 322 00:18:28,720 --> 00:18:30,880 Speaker 1: But he does the amnesty thing. He does it. Well, 323 00:18:31,040 --> 00:18:36,240 Speaker 1: they this is a new thing, which Obama really popularized 324 00:18:36,320 --> 00:18:40,720 Speaker 1: this and then Trump was doing it too, executive actions, 325 00:18:41,080 --> 00:18:43,880 Speaker 1: many of which all three presidents had been thrown out 326 00:18:43,880 --> 00:18:47,560 Speaker 1: of court. Ultimately, but they do it to make a splash, 327 00:18:47,600 --> 00:18:50,280 Speaker 1: make a headline, and then get some policy and effect, 328 00:18:50,280 --> 00:18:52,680 Speaker 1: even if it's only for six months. And then sometimes 329 00:18:52,680 --> 00:18:55,159 Speaker 1: it's really difficult to roll back. We've seen that with 330 00:18:55,200 --> 00:18:59,640 Speaker 1: some of the immigration policies of Obama because I think 331 00:19:01,160 --> 00:19:05,159 Speaker 1: the Dreamer Act is still operating. And then with Trump, 332 00:19:05,200 --> 00:19:07,439 Speaker 1: it's been difficult for Biden to roll back some of 333 00:19:07,440 --> 00:19:12,480 Speaker 1: the restrictions on the Mexican migration. But ultimately it loses 334 00:19:12,640 --> 00:19:18,160 Speaker 1: because they didn't have the constitutional authority to do it. 335 00:19:18,160 --> 00:19:20,200 Speaker 1: It works for a while in some cases. I don't 336 00:19:20,240 --> 00:19:21,560 Speaker 1: know if this is going to work at all, but 337 00:19:21,640 --> 00:19:25,639 Speaker 1: it's that then all comes back to the US Senate. 338 00:19:26,560 --> 00:19:29,680 Speaker 1: That's the log jam, for better or for worse. Yeah, 339 00:19:29,720 --> 00:19:32,480 Speaker 1: because it's split, and then you had that you know, 340 00:19:32,520 --> 00:19:35,439 Speaker 1: that filibuster rule, right to get sixty votes to advance 341 00:19:35,520 --> 00:19:38,439 Speaker 1: something that's really next to impossible, particularly now that you 342 00:19:38,440 --> 00:19:41,240 Speaker 1: know not now. But the truth of it is, every 343 00:19:41,480 --> 00:19:44,639 Speaker 1: state gets two senators. So a lot of red states 344 00:19:44,680 --> 00:19:48,879 Speaker 1: are in some regards overrepresented in the United States. Well, 345 00:19:48,880 --> 00:19:51,640 Speaker 1: they are overrepresented. Yeah, I imagine. I mean I said 346 00:19:51,680 --> 00:19:53,840 Speaker 1: this last week. You got a state that's got one 347 00:19:53,880 --> 00:19:59,160 Speaker 1: congress person, right, that would be Liz Cheney Wyoming, Wyoming. Yeah, right, 348 00:19:59,400 --> 00:20:01,560 Speaker 1: but they got two senators. I mean that just seems 349 00:20:01,640 --> 00:20:05,400 Speaker 1: ridiculous on its face. And five hundred ninety three thousand people, Yeah, 350 00:20:05,480 --> 00:20:07,560 Speaker 1: it's right. It's usually about five hundred thousand people for 351 00:20:07,600 --> 00:20:11,480 Speaker 1: a congress representative. So Alaska, it's the same thing. Alaska 352 00:20:11,560 --> 00:20:14,920 Speaker 1: has has two Senators's not going away unless they reassemble 353 00:20:15,160 --> 00:20:17,960 Speaker 1: the way the senators formed. So it's this is why 354 00:20:17,960 --> 00:20:20,680 Speaker 1: these presidents are frustrated, and that's set for better for worse. 355 00:20:20,760 --> 00:20:22,240 Speaker 1: Some of the stuff that Trump wanted to do. Yeah, 356 00:20:22,320 --> 00:20:23,840 Speaker 1: we were kind of in favor of, especially going on 357 00:20:23,840 --> 00:20:26,119 Speaker 1: an immigration. But some of the stuff that Obamba was 358 00:20:26,160 --> 00:20:28,880 Speaker 1: trying to do with DACCA and some of his other programs, 359 00:20:28,880 --> 00:20:31,600 Speaker 1: like thank god we have this stalemates. Yeah. But bottom 360 00:20:31,600 --> 00:20:34,880 Speaker 1: line is these executive orders are often illegal and they 361 00:20:34,920 --> 00:20:38,840 Speaker 1: just get away with it because the justice system is 362 00:20:38,880 --> 00:20:42,439 Speaker 1: so slow when you file federal lawsuits. Oh what I 363 00:20:42,480 --> 00:20:44,960 Speaker 1: love is that when they get challenged like DACA did, 364 00:20:45,240 --> 00:20:47,000 Speaker 1: it takes so long to get to the courts, the 365 00:20:47,080 --> 00:20:49,280 Speaker 1: decision clenning as well. You know, you've already set up 366 00:20:49,280 --> 00:20:51,480 Speaker 1: this program to exist. People depend on it. It's not 367 00:20:51,560 --> 00:20:53,280 Speaker 1: lasted for ten years. Ah, what are you gonna do? 368 00:20:53,359 --> 00:20:55,040 Speaker 1: It's not really Yeah, it's not really head fair and 369 00:20:55,320 --> 00:20:57,760 Speaker 1: now it's not fair, right, it's it's it's depended on 370 00:20:57,840 --> 00:21:01,439 Speaker 1: by some people. But you talk about one freaking fair. 371 00:21:02,119 --> 00:21:05,760 Speaker 1: You imagine you imagine having to pay. I can't imagine 372 00:21:05,800 --> 00:21:08,359 Speaker 1: what my parents would have thought that they would they 373 00:21:08,400 --> 00:21:11,160 Speaker 1: would have to pay because they couldn't afford to send 374 00:21:11,200 --> 00:21:14,960 Speaker 1: me to college. Right, we don't want to go anyway. 375 00:21:15,160 --> 00:21:18,159 Speaker 1: But I know, but what you quit? But I paid 376 00:21:18,240 --> 00:21:23,280 Speaker 1: for it. I was working. So there were three semesters. 377 00:21:23,320 --> 00:21:25,679 Speaker 1: There were three and you don't want do you know? 378 00:21:25,720 --> 00:21:27,840 Speaker 1: Over you know, what number one reason I dropped out 379 00:21:28,119 --> 00:21:31,520 Speaker 1: because I was working full time? It is that I 380 00:21:32,680 --> 00:21:36,359 Speaker 1: was I was spending my days in school and my 381 00:21:36,480 --> 00:21:40,080 Speaker 1: night's working, and during the day I'd sit there and 382 00:21:40,119 --> 00:21:44,160 Speaker 1: I go, this isn't worth my money. I guess maybe 383 00:21:44,200 --> 00:21:45,800 Speaker 1: if my parents were paying, I would have stuck it 384 00:21:45,840 --> 00:21:48,880 Speaker 1: out longer. But I was paying, and I thought, why 385 00:21:48,880 --> 00:21:52,320 Speaker 1: am I working so hard and I'm getting this in return? 386 00:21:52,960 --> 00:21:55,960 Speaker 1: But you missed the big picture that's supposed to open 387 00:21:56,240 --> 00:21:58,440 Speaker 1: doors to jobs. Whether or not it's silly or not, 388 00:21:59,080 --> 00:22:01,840 Speaker 1: some employers look, that is something that they can rely on. 389 00:22:01,920 --> 00:22:04,159 Speaker 1: Always got a college degree. I got into radio on 390 00:22:04,240 --> 00:22:06,440 Speaker 1: the ball, then the dud that doesn't so I got 391 00:22:06,480 --> 00:22:08,480 Speaker 1: into radio a scam, but go with it. No, it 392 00:22:08,480 --> 00:22:10,680 Speaker 1: didn't Matter's how I felt. Well, it didn't matter. I 393 00:22:10,760 --> 00:22:12,639 Speaker 1: want her to work. I don't want to sit in class. 394 00:22:12,800 --> 00:22:14,560 Speaker 1: I hated school. I hate it. Then you ended up 395 00:22:14,560 --> 00:22:16,760 Speaker 1: in like a candy store or something in a for 396 00:22:16,880 --> 00:22:21,119 Speaker 1: three months. I ended up. I ended up here. My 397 00:22:21,280 --> 00:22:25,399 Speaker 1: my system worked. Yeah, that's another problem. Well then I 398 00:22:25,520 --> 00:22:27,600 Speaker 1: ended up here, so well, okay, how much did you 399 00:22:27,600 --> 00:22:30,359 Speaker 1: pay for school? Not a lot? We ended up I 400 00:22:30,359 --> 00:22:33,439 Speaker 1: went to a state school and I did get some 401 00:22:33,480 --> 00:22:35,800 Speaker 1: grant money, we borrowed some money. It wasn't a lot, though. 402 00:22:35,840 --> 00:22:37,959 Speaker 1: I mean, you know what the tuition was for me. 403 00:22:38,880 --> 00:22:41,320 Speaker 1: This is a long time ago, but for a state 404 00:22:41,359 --> 00:22:44,560 Speaker 1: school New York was only like three thousand dollars a year. Yeah. 405 00:22:44,600 --> 00:22:47,560 Speaker 1: Well it's in California for a woman board, which added 406 00:22:47,560 --> 00:22:49,840 Speaker 1: some more to that, but nothing tremendous for a Cow 407 00:22:49,920 --> 00:22:53,200 Speaker 1: States school. Now, if you're an in state student, it's 408 00:22:53,200 --> 00:22:56,679 Speaker 1: only eight thousand. Oh that's pretty good. I didn't know that. Yeah, 409 00:22:56,760 --> 00:22:59,880 Speaker 1: so's it's not much different when you adjust for inflation. 410 00:23:00,640 --> 00:23:04,600 Speaker 1: But no, there's there's Look, there's a lot of jobs 411 00:23:04,640 --> 00:23:07,439 Speaker 1: you can get, uh that you don't need a college 412 00:23:07,440 --> 00:23:09,399 Speaker 1: degree for. And really a lot of it has to 413 00:23:09,400 --> 00:23:12,760 Speaker 1: do with with your your work ethic and your drive, right, 414 00:23:13,240 --> 00:23:15,959 Speaker 1: you know, I I think, I think. And by the way, 415 00:23:16,000 --> 00:23:17,720 Speaker 1: there are a ton of degrees. I was just reading 416 00:23:17,760 --> 00:23:23,080 Speaker 1: about an administrator today. Uh, and they got a degree 417 00:23:23,080 --> 00:23:27,879 Speaker 1: and what was it. It was equity and social justice, right, 418 00:23:27,880 --> 00:23:30,200 Speaker 1: and so they got an administrative position. They were quote 419 00:23:31,280 --> 00:23:35,200 Speaker 1: administrative and social job. And I'm thinking, well, okay, well, 420 00:23:35,000 --> 00:23:39,000 Speaker 1: well that's not a degree. That is not a degree, 421 00:23:39,040 --> 00:23:41,679 Speaker 1: that is not any knowledge that's were and of course 422 00:23:41,880 --> 00:23:43,840 Speaker 1: the only place you can work is in some kind 423 00:23:43,880 --> 00:23:47,800 Speaker 1: of government administration system. But you can't you can't take 424 00:23:47,840 --> 00:23:51,680 Speaker 1: that out into the real world. So I'm I'm very, 425 00:23:52,040 --> 00:23:55,440 Speaker 1: very dubious and suspicious of a lot of these degrees. Now, 426 00:23:56,240 --> 00:23:58,439 Speaker 1: now you're just jealous because we went to college and 427 00:23:58,480 --> 00:24:01,040 Speaker 1: you didn't write Deba Martin. Oh, I wish I had 428 00:24:01,040 --> 00:24:03,720 Speaker 1: a social justice degree. I have your degree in Deborah 429 00:24:03,760 --> 00:24:08,200 Speaker 1: Mark broadcast journalism. It is yeah, it is a minor. 430 00:24:08,280 --> 00:24:13,000 Speaker 1: And political science. Political science is pretty minor. Yeah, that 431 00:24:13,080 --> 00:24:16,439 Speaker 1: turned usually turns out lawyers and politicians. You should have 432 00:24:16,440 --> 00:24:18,280 Speaker 1: been a You should have been a staffer from for 433 00:24:18,400 --> 00:24:22,240 Speaker 1: some dirtbag politician. Yeah. She would have been good walking 434 00:24:22,240 --> 00:24:24,159 Speaker 1: behind them with her little clipboard. Oh yeah, yeah. You 435 00:24:24,160 --> 00:24:26,399 Speaker 1: could have been a spokeshole. You could have been one 436 00:24:26,400 --> 00:24:28,720 Speaker 1: of the most chirpy little spokesh Yeah, I will. Yeah, 437 00:24:28,840 --> 00:24:32,080 Speaker 1: well it pays better for sure. All Right, when we 438 00:24:32,119 --> 00:24:34,240 Speaker 1: come back the story I was gonna do, but I 439 00:24:34,240 --> 00:24:37,200 Speaker 1: want to make sure John had vented enough for this hour. 440 00:24:37,480 --> 00:24:42,560 Speaker 1: I'll take another hour ahead. There's always another hour of science. 441 00:24:42,560 --> 00:24:45,400 Speaker 1: And it just confirms something that's been in my head 442 00:24:45,480 --> 00:24:47,639 Speaker 1: for years and I'm actually looking at it in printed. 443 00:24:47,680 --> 00:24:50,760 Speaker 1: I can't believe it. Coming up next John and ken Kind, Well, 444 00:24:50,760 --> 00:24:54,040 Speaker 1: you know we're on we're on verdict watch. And if 445 00:24:54,080 --> 00:24:57,400 Speaker 1: the plaintiffs get their way, you're at LA County taxpayer. 446 00:24:57,480 --> 00:24:59,600 Speaker 1: It could be seventy five million dollars going out the door. 447 00:25:00,119 --> 00:25:04,520 Speaker 1: Seventy five million. What are we talking about. That's the 448 00:25:04,560 --> 00:25:08,200 Speaker 1: case of the Kobe Bryant helicopter crash from early twenty twenty. 449 00:25:08,640 --> 00:25:12,320 Speaker 1: Vanessa Bryant and the husband of another family that was 450 00:25:12,440 --> 00:25:15,040 Speaker 1: killed are the plaintiffs in the civil case against the 451 00:25:15,040 --> 00:25:17,600 Speaker 1: county in the Sheriff's department. And that's what's on the line. 452 00:25:17,640 --> 00:25:19,720 Speaker 1: Are they that's what they're asking the jury to award 453 00:25:19,920 --> 00:25:23,080 Speaker 1: or in idiot jury five million dollars or idiot jurors 454 00:25:23,119 --> 00:25:29,480 Speaker 1: really going to award seventy five million. Seventy five million dollars, Yeah, 455 00:25:29,480 --> 00:25:31,760 Speaker 1: about forty two would go to Vanessa Bryant and the 456 00:25:31,760 --> 00:25:34,520 Speaker 1: rest would go to the other family they hauled in 457 00:25:34,520 --> 00:25:38,440 Speaker 1: the case. We'll talk about it after the news at 458 00:25:39,320 --> 00:25:42,800 Speaker 1: three o'clock. And then another thing. My eyes almost popped 459 00:25:42,800 --> 00:25:44,479 Speaker 1: out of my head last night because you know, if 460 00:25:44,480 --> 00:25:47,040 Speaker 1: you watch any local TV, it's all about these two 461 00:25:47,080 --> 00:25:50,000 Speaker 1: propositions twenty six and twenty seven, which is online gambling. 462 00:25:50,800 --> 00:25:53,600 Speaker 1: One popped up that wasn't was about a bill in Sacramento. 463 00:25:54,520 --> 00:25:57,360 Speaker 1: We'll tell you what that bill is because in this 464 00:25:57,440 --> 00:26:00,440 Speaker 1: age of inflation, oh, this could drive up cost of 465 00:26:00,440 --> 00:26:03,560 Speaker 1: your hamburger, John co Belt. We'll go into that after that. 466 00:26:03,920 --> 00:26:06,480 Speaker 1: By the way, I just saw an online ad for Prop. 467 00:26:06,520 --> 00:26:11,400 Speaker 1: Twenty seven, which is for legalizing on four online gambles. Okay, 468 00:26:11,720 --> 00:26:16,119 Speaker 1: the entire commercial, the entire commercial was about vote for 469 00:26:16,160 --> 00:26:19,600 Speaker 1: this proposition because this is going to fund homeless programs 470 00:26:20,000 --> 00:26:23,960 Speaker 1: for families and children. That's what they're doing. Actually, I 471 00:26:23,960 --> 00:26:25,840 Speaker 1: saw one on TV last night. They actually brought out 472 00:26:25,840 --> 00:26:28,000 Speaker 1: people from nonprofits to say they can't wait for this 473 00:26:28,040 --> 00:26:30,000 Speaker 1: to pass. They're going to get more money and they're excited. 474 00:26:30,560 --> 00:26:33,640 Speaker 1: You cannot tell at all that it's about online gambling, 475 00:26:34,160 --> 00:26:35,679 Speaker 1: because what they want to do is use some of 476 00:26:35,720 --> 00:26:37,920 Speaker 1: the proceeds. They want to use some of the proceeds 477 00:26:37,960 --> 00:26:40,760 Speaker 1: I guess for a homeless program. You're right. Generally the Prop. 478 00:26:40,840 --> 00:26:42,639 Speaker 1: Twenty seven ads that are in favor of it have 479 00:26:42,720 --> 00:26:44,399 Speaker 1: just been about how much it's gonna help with the 480 00:26:44,480 --> 00:26:49,320 Speaker 1: holes problem. And yeah, I mean, I mean, it's so preposterous. 481 00:26:49,320 --> 00:26:52,880 Speaker 1: They they run these focus groups and they find out 482 00:26:52,920 --> 00:26:55,160 Speaker 1: that if you say, aloll spend money on homeless, oh yes, 483 00:26:55,160 --> 00:26:57,200 Speaker 1: I'll vote for that. But if you say you want 484 00:26:57,200 --> 00:27:00,640 Speaker 1: to legalize online gambling, well I don't know about that. 485 00:27:01,440 --> 00:27:04,120 Speaker 1: It's a good one because there's no taxes involved. Right, 486 00:27:04,240 --> 00:27:06,639 Speaker 1: they're gonna They're saying we're gonna get money for the homeless, 487 00:27:06,640 --> 00:27:09,200 Speaker 1: but we're not gonna race. I can't stand with the 488 00:27:09,560 --> 00:27:14,200 Speaker 1: deceptive things that work on ignorant people, because that's most 489 00:27:14,200 --> 00:27:17,000 Speaker 1: of the bad laws in this state. All right. The 490 00:27:17,080 --> 00:27:20,119 Speaker 1: New York Times had a science story today that jumped 491 00:27:20,119 --> 00:27:22,760 Speaker 1: out at me, and a story on The John and 492 00:27:22,840 --> 00:27:26,280 Speaker 1: Ken Show also hit me at the same time. I remember, 493 00:27:26,320 --> 00:27:28,479 Speaker 1: this is really a long time ago, but you were 494 00:27:28,520 --> 00:27:31,560 Speaker 1: talking about how you once ran into somebody you thought 495 00:27:31,800 --> 00:27:34,840 Speaker 1: was your twin. Yeah, somebody that was not related to 496 00:27:34,920 --> 00:27:37,240 Speaker 1: the word, of course, the German doppelganger. I always like 497 00:27:37,240 --> 00:27:39,679 Speaker 1: the word doppelganger. I use that too. One I'm in 498 00:27:39,720 --> 00:27:41,639 Speaker 1: public and I see somebody that looks like somebody I know, 499 00:27:41,720 --> 00:27:46,159 Speaker 1: I go, there's your doppelganger. Yeah, what's amazing about this story? 500 00:27:46,200 --> 00:27:49,000 Speaker 1: And apparently some guy has taken photos, and they've been 501 00:27:49,040 --> 00:27:52,800 Speaker 1: studies done of people that were not related but somehow 502 00:27:52,920 --> 00:27:56,679 Speaker 1: found each other, and it's incredible how much they do 503 00:27:56,760 --> 00:27:58,720 Speaker 1: look alike. Did you look at the photos? John? I did? 504 00:27:58,760 --> 00:28:01,120 Speaker 1: I read that whole story this morn Yeah. How could 505 00:28:01,160 --> 00:28:03,840 Speaker 1: you not believe that these people weren't related when you 506 00:28:03,840 --> 00:28:06,760 Speaker 1: look at the photos of them, especially the two shirtless, 507 00:28:06,800 --> 00:28:14,320 Speaker 1: fat guys with tattoos that Pedro Lopez Soto and Alfred 508 00:28:15,040 --> 00:28:19,600 Speaker 1: Puieo Cadi Katko. The picture was taken in Barcelona in 509 00:28:19,680 --> 00:28:24,360 Speaker 1: twenty fifteen, and they look almost identical. They got I mean, 510 00:28:24,400 --> 00:28:29,720 Speaker 1: these two guys are slobs, huge bellies, big sagging breasts. 511 00:28:30,320 --> 00:28:33,600 Speaker 1: They got the same beard, same balding head, the same expression. 512 00:28:33,760 --> 00:28:37,200 Speaker 1: Everything is like almost identical. And then did you see 513 00:28:37,200 --> 00:28:39,320 Speaker 1: the pair of guys that leads off the article. You 514 00:28:39,360 --> 00:28:41,160 Speaker 1: would think they were a gay couple, but they're not. 515 00:28:41,240 --> 00:28:44,600 Speaker 1: They actually met through a band and they attended each 516 00:28:44,600 --> 00:28:47,560 Speaker 1: other's wedding. But they're kind of closing. Yeah, I know, 517 00:28:48,240 --> 00:28:53,320 Speaker 1: they really They got that little bearded yes, carefully quaffed beards, 518 00:28:53,640 --> 00:28:57,080 Speaker 1: carefully quaffed beard. And so the story goes on to 519 00:28:57,200 --> 00:28:59,440 Speaker 1: say that a study was done on some of these 520 00:28:59,600 --> 00:29:03,960 Speaker 1: looks and they found out that they actually do share DNA. 521 00:29:04,200 --> 00:29:07,360 Speaker 1: How about that? That makes sense? That makes sense. And 522 00:29:07,400 --> 00:29:10,640 Speaker 1: now here comes the part where I felt vindicated, because 523 00:29:10,680 --> 00:29:12,480 Speaker 1: I don't know why I came up at this, but 524 00:29:12,560 --> 00:29:15,320 Speaker 1: I said, you know, eventually, you're gonna have to find 525 00:29:15,360 --> 00:29:17,520 Speaker 1: people that look like you, because we're really going to 526 00:29:17,640 --> 00:29:21,200 Speaker 1: run out of faces. And sure enough, it's in the 527 00:29:21,240 --> 00:29:23,720 Speaker 1: story that there's so many billions of people on the planet, 528 00:29:23,760 --> 00:29:26,240 Speaker 1: there's on many, so many faces that are gonna form, 529 00:29:27,840 --> 00:29:30,760 Speaker 1: so there's a really good chance and somewhere in the 530 00:29:30,760 --> 00:29:32,480 Speaker 1: world there is somebody looks a hell of a lot 531 00:29:32,520 --> 00:29:35,000 Speaker 1: like you, and it's part of DNA, and it's part 532 00:29:35,000 --> 00:29:38,520 Speaker 1: of other factors, environmental and so forth. But it was 533 00:29:38,560 --> 00:29:41,240 Speaker 1: really it was really studying to me to see that, 534 00:29:41,280 --> 00:29:44,120 Speaker 1: because I said, yeah, that does make common sense to me. Yeah, well, 535 00:29:44,160 --> 00:29:47,920 Speaker 1: I mean's eight billion people. Of course, a lot of 536 00:29:47,960 --> 00:29:51,640 Speaker 1: people are gonna look like Now. I saw your doppelganger 537 00:29:52,560 --> 00:29:56,080 Speaker 1: in Germany. Coincidentally, I think you did tell me this 538 00:29:56,200 --> 00:29:59,160 Speaker 1: story once too. We were changing planes in Munich on 539 00:29:59,200 --> 00:30:02,360 Speaker 1: the way to Israel, and uh, there was a guy 540 00:30:02,360 --> 00:30:06,800 Speaker 1: in the airport and I just I like stopped stopped. 541 00:30:08,680 --> 00:30:12,560 Speaker 1: Oh my god, that's Ken. You should have gotten his name. 542 00:30:12,600 --> 00:30:16,640 Speaker 1: I you know, it frightened me. I thought it was 543 00:30:16,680 --> 00:30:20,760 Speaker 1: some kind of ghost right. Um. And then Nappleganger's genomes 544 00:30:20,760 --> 00:30:25,440 Speaker 1: are similar, but something called epigenomes and microbiomes are a 545 00:30:25,480 --> 00:30:28,400 Speaker 1: little different. This is all inside genetics stuff. But that's 546 00:30:28,400 --> 00:30:30,960 Speaker 1: what they found out in this study when they took 547 00:30:30,960 --> 00:30:34,680 Speaker 1: a look at these twins and discovered that they actually 548 00:30:34,720 --> 00:30:41,000 Speaker 1: did share some DNA. Absolutely remarkable and a good scientific 549 00:30:41,040 --> 00:30:46,440 Speaker 1: explanation for it. Um. They described them as facial algorithms. 550 00:30:47,680 --> 00:30:52,200 Speaker 1: And they did this study and this photographer took these pictures. 551 00:30:53,160 --> 00:30:55,200 Speaker 1: But I'm just trying to find the quote from the 552 00:30:55,200 --> 00:30:57,080 Speaker 1: guy that really excited me today when he when he 553 00:30:57,160 --> 00:31:02,520 Speaker 1: basically said that, oh yeah, doctor A. Stellar said, now, 554 00:31:02,560 --> 00:31:05,000 Speaker 1: there were so many people in the world that the 555 00:31:05,000 --> 00:31:08,880 Speaker 1: system is repeating itself. It's not unreasonable to assume that 556 00:31:08,920 --> 00:31:12,080 Speaker 1: you two might have a look like out there. There 557 00:31:12,080 --> 00:31:16,720 Speaker 1: are only so many ways to build a face. The 558 00:31:16,800 --> 00:31:19,360 Speaker 1: chances of you finding that person somewhere on this earth 559 00:31:19,400 --> 00:31:23,560 Speaker 1: are probably actually it's probably several people. When some of 560 00:31:23,560 --> 00:31:26,560 Speaker 1: those faces are badly constructed. I forget what you said. 561 00:31:26,560 --> 00:31:28,680 Speaker 1: You ran into the guys that looked like your New 562 00:31:28,760 --> 00:31:31,640 Speaker 1: York City. I was going to a comedy club with 563 00:31:31,760 --> 00:31:34,800 Speaker 1: my friends and we were standing just outside the club. 564 00:31:34,840 --> 00:31:37,400 Speaker 1: Maybe we're in line. And I looked across the street 565 00:31:37,920 --> 00:31:41,680 Speaker 1: and there was me across the street, and he had 566 00:31:41,760 --> 00:31:44,840 Speaker 1: even had my hair, my glasses. He had the same 567 00:31:44,960 --> 00:31:47,400 Speaker 1: kind of blue blazer that I used to wear. Then 568 00:31:49,120 --> 00:31:51,080 Speaker 1: it was like looking in a mirror when it crosses 569 00:31:51,160 --> 00:31:53,719 Speaker 1: over into clothing again, because I think I had it 570 00:31:53,760 --> 00:31:55,480 Speaker 1: on too, because we're going to the club, and I 571 00:31:55,520 --> 00:31:57,240 Speaker 1: think I remember it was a little dressed up, and 572 00:31:57,240 --> 00:31:59,040 Speaker 1: so I looked across the street as if it was 573 00:31:59,080 --> 00:32:00,920 Speaker 1: a mirror, and I think he was in front of 574 00:32:00,920 --> 00:32:03,640 Speaker 1: a restaurant. He didn't notice you though, I don't. I 575 00:32:03,640 --> 00:32:06,200 Speaker 1: don't think so, or maybe he ran. I know. That 576 00:32:06,320 --> 00:32:09,400 Speaker 1: scared me too. It's like, oh, hey, that's my face. 577 00:32:09,520 --> 00:32:14,240 Speaker 1: What are you doing? Come back here? All right? We 578 00:32:14,320 --> 00:32:17,560 Speaker 1: got more. Do you remember when we found raised doppelgangers? 579 00:32:18,520 --> 00:32:22,360 Speaker 1: We have found several of the two. One one was 580 00:32:22,400 --> 00:32:26,600 Speaker 1: a guy a few years ago. He got arrested. Remember 581 00:32:27,000 --> 00:32:29,400 Speaker 1: this guy got arrested, and that there was one. He 582 00:32:29,560 --> 00:32:32,760 Speaker 1: actually was the leader of a mariachi band and he 583 00:32:32,840 --> 00:32:39,160 Speaker 1: was photographed. He has kind of a generic sort of face. Yeah, 584 00:32:39,200 --> 00:32:40,400 Speaker 1: there's a lot of there's a there's a lot of 585 00:32:40,440 --> 00:32:43,160 Speaker 1: Ray Lopez is out there. John and Ken Show. Deborah 586 00:32:43,200 --> 00:32:45,920 Speaker 1: Mark has the news KFI AM six forty. It's never 587 00:32:45,960 --> 00:32:49,760 Speaker 1: been more important to diversify your financial portfolio. Well, that's right. 588 00:32:50,040 --> 00:32:52,920 Speaker 1: The SNP is down twenty percent from the last year, 589 00:32:52,960 --> 00:32:55,640 Speaker 1: and this year looks even worse. Gold and precious metals 590 00:32:55,680 --> 00:32:59,520 Speaker 1: offer a hedge against inflation and stock market volatility, and 591 00:32:59,720 --> 00:33:03,160 Speaker 1: Legacy Precious Medals is the company Cannon I Trust. 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