1 00:00:00,120 --> 00:00:02,520 Speaker 1: We're on from one to four every day, and after 2 00:00:02,560 --> 00:00:04,880 Speaker 1: four o'clock you can hear the podcast at the iHeart 3 00:00:05,040 --> 00:00:08,039 Speaker 1: Radio app or on the CAFI website. It's called John 4 00:00:08,080 --> 00:00:12,399 Speaker 1: and kennon demand anyway. Welcome demand. We actually show up 5 00:00:12,400 --> 00:00:14,800 Speaker 1: at your house. That's right, if you click on the app, 6 00:00:14,840 --> 00:00:16,480 Speaker 1: there we are. If you don't demand it, you don't 7 00:00:16,480 --> 00:00:18,040 Speaker 1: get it. We will be at your front door and 8 00:00:18,079 --> 00:00:19,680 Speaker 1: we'll do a three hour show right there in your 9 00:00:19,680 --> 00:00:23,599 Speaker 1: living room. Whatever topics you want. Just that's not a 10 00:00:23,640 --> 00:00:27,479 Speaker 1: bad get. Cost million dollars. Start doing that to a 11 00:00:27,560 --> 00:00:30,040 Speaker 1: road show. We'll take a million dollars. I would a 12 00:00:30,080 --> 00:00:32,199 Speaker 1: million dollars a house. Shure, we'll take request do a 13 00:00:32,240 --> 00:00:34,080 Speaker 1: three hour show for somebody in their house from their 14 00:00:34,120 --> 00:00:38,040 Speaker 1: living room. Yeah, you decide what we talk about, all right. 15 00:00:38,040 --> 00:00:41,400 Speaker 1: We got, of course money available. The caf I Cash 16 00:00:41,520 --> 00:00:44,400 Speaker 1: Refilled contest is coming up in about fifteen minutes. You'll 17 00:00:44,400 --> 00:00:46,360 Speaker 1: do one each hour, of course, with the keyword you 18 00:00:46,400 --> 00:00:48,920 Speaker 1: need to win some money. We're gonna start out a 19 00:00:49,000 --> 00:00:53,280 Speaker 1: little different today, only because I got fascinated reading these stories. 20 00:00:54,480 --> 00:00:57,520 Speaker 1: If you watch any commercial TV these days, you can't 21 00:00:57,520 --> 00:01:00,600 Speaker 1: miss the drug commercials, right, yes, and the one that 22 00:01:00,720 --> 00:01:03,960 Speaker 1: sticks in my head is because it comes from a 23 00:01:04,000 --> 00:01:09,319 Speaker 1: pop song of the nineteen seventies and it's oh, oh ozampic. 24 00:01:10,160 --> 00:01:13,480 Speaker 1: You remember it's magic. Oh yeah. They took that song 25 00:01:13,560 --> 00:01:17,320 Speaker 1: and turned it into a drug commercial. I've seen ozempic commercials. 26 00:01:17,360 --> 00:01:20,640 Speaker 1: I know people on ozempic, but I haven't heard the song. 27 00:01:20,880 --> 00:01:22,840 Speaker 1: I didn't know they. Oh you haven't seen the TV 28 00:01:22,880 --> 00:01:28,280 Speaker 1: commercials where they're singing, oh no, not ompic. No, you know. 29 00:01:28,400 --> 00:01:31,480 Speaker 1: It was designed for people with the type two diabetes 30 00:01:31,520 --> 00:01:34,399 Speaker 1: to improve blood sugar. That was I guess that. But 31 00:01:34,840 --> 00:01:37,880 Speaker 1: John knows people on it because it is helping people 32 00:01:37,920 --> 00:01:40,679 Speaker 1: with weight loss. She lived on the West side of 33 00:01:40,800 --> 00:01:44,880 Speaker 1: LA and ozempic is all the rage now. And when 34 00:01:44,880 --> 00:01:47,120 Speaker 1: I saw this story and then I read the whole thing, 35 00:01:47,440 --> 00:01:51,640 Speaker 1: I said, yes, I've noticed that for years and some people, 36 00:01:52,160 --> 00:01:57,560 Speaker 1: and the story is about ozempic face. It's a greater 37 00:01:57,920 --> 00:02:00,000 Speaker 1: you know. In fact, we just got an email from 38 00:02:00,520 --> 00:02:02,120 Speaker 1: I guess he's a doctor. I don't know, you know, 39 00:02:02,160 --> 00:02:05,120 Speaker 1: we get all these emails pitching show segments and he's like, 40 00:02:05,160 --> 00:02:08,680 Speaker 1: he can talk about ozempic face. And that got interested 41 00:02:08,680 --> 00:02:10,440 Speaker 1: again and look up the story because I saw it 42 00:02:10,480 --> 00:02:12,480 Speaker 1: the other day in the Daily Mail, along with the 43 00:02:12,480 --> 00:02:16,920 Speaker 1: illustration of people's face is just sinking in. And it's 44 00:02:17,000 --> 00:02:19,480 Speaker 1: not something you wouldn't This could have happened to you 45 00:02:19,520 --> 00:02:22,040 Speaker 1: even if you didn't take ozempic, but you had some 46 00:02:22,120 --> 00:02:26,760 Speaker 1: kind of dramatic weight loss. It's actually called facial aging. 47 00:02:27,120 --> 00:02:30,920 Speaker 1: You shrivel, you shrivel so. And this is the reason 48 00:02:31,000 --> 00:02:33,600 Speaker 1: I said, I've noticed this. I've run into people I've 49 00:02:33,600 --> 00:02:36,480 Speaker 1: known for years and they lose it's not a few pounds. 50 00:02:36,520 --> 00:02:39,400 Speaker 1: You have to lose a more dramatic amount of weight, right, 51 00:02:39,560 --> 00:02:41,480 Speaker 1: And I looked at their face and I said, God, 52 00:02:41,520 --> 00:02:44,919 Speaker 1: they look older. Yeah, your face. I don't say anything, 53 00:02:44,960 --> 00:02:46,960 Speaker 1: but it's like, your face looks like it's kind of 54 00:02:47,000 --> 00:02:50,079 Speaker 1: like really saggy, or it's wrinkly, or it's kind of aged. 55 00:02:50,320 --> 00:02:54,519 Speaker 1: Fat is a really good skin filler. And that's exactly 56 00:02:54,520 --> 00:02:57,119 Speaker 1: what the experts say in this story. If you keep 57 00:02:57,400 --> 00:03:01,240 Speaker 1: some weight on as you get older, you look younger. Yes. 58 00:03:02,400 --> 00:03:05,560 Speaker 1: The New York Times had a plastic surgeon doctor or 59 00:03:05,680 --> 00:03:08,320 Speaker 1: In Temper or in that's a good name. He said, 60 00:03:08,360 --> 00:03:11,160 Speaker 1: it's common for key areas of the face to deflate 61 00:03:11,400 --> 00:03:15,960 Speaker 1: with weight loss. The head looks like a basketball it's 62 00:03:16,000 --> 00:03:19,639 Speaker 1: losing air. Yeah, you look like a shriveled up browne. 63 00:03:20,040 --> 00:03:23,359 Speaker 1: When it comes to facial aging, fat is typically more 64 00:03:23,400 --> 00:03:27,200 Speaker 1: friend than foe. Weight loss can turn back your biological age, 65 00:03:27,400 --> 00:03:30,919 Speaker 1: but it tends to turn your facial clock forward. Well, 66 00:03:30,960 --> 00:03:34,000 Speaker 1: there is a bad side of that, is your facial clock. 67 00:03:34,560 --> 00:03:37,040 Speaker 1: And you know how probably a lot of people John 68 00:03:37,120 --> 00:03:39,920 Speaker 1: that you're talking about the you know Rono Zempic would 69 00:03:39,960 --> 00:03:44,480 Speaker 1: not want to have Zempic face. I see some women 70 00:03:45,360 --> 00:03:49,240 Speaker 1: who are very thin, like really thin, but as they 71 00:03:49,280 --> 00:03:53,480 Speaker 1: get older, they look shriveled and what they need is 72 00:03:53,480 --> 00:03:55,240 Speaker 1: to they need to I thought they do they do 73 00:03:55,320 --> 00:03:57,680 Speaker 1: face fillers. Isn't there some type of plastic surgery that 74 00:03:57,720 --> 00:03:59,360 Speaker 1: they can do like face fillers? Saying you have to 75 00:03:59,400 --> 00:04:02,200 Speaker 1: go get in jack actions injections right so they can 76 00:04:02,240 --> 00:04:04,320 Speaker 1: bloat your face back. I think, well, what are they? 77 00:04:04,360 --> 00:04:11,480 Speaker 1: What are they injections? There's there's no expert. Actually I'm 78 00:04:11,520 --> 00:04:14,200 Speaker 1: not an expert on this, but I know the different types. 79 00:04:14,240 --> 00:04:17,920 Speaker 1: But I'm not even exactly sure. What is in good 80 00:04:20,000 --> 00:04:21,600 Speaker 1: way of saying you have not had them? No, I 81 00:04:22,279 --> 00:04:26,000 Speaker 1: have not, Okay, I do need something tells me you've 82 00:04:26,000 --> 00:04:29,520 Speaker 1: considered them. Yes, of course you can't get too thin. Well, 83 00:04:29,720 --> 00:04:31,400 Speaker 1: I don't think I have to worry about it. I 84 00:04:31,440 --> 00:04:34,480 Speaker 1: have a few pounds here that just will not go away, 85 00:04:34,520 --> 00:04:36,240 Speaker 1: So I don't have to worry. You don't want to 86 00:04:36,440 --> 00:04:38,479 Speaker 1: call shriveled down? No, I definitely. I don't want to 87 00:04:38,480 --> 00:04:43,000 Speaker 1: have that face, the shrivel face. I don't want. Doctor 88 00:04:43,080 --> 00:04:46,400 Speaker 1: Paul Jared Frank, a dermatologist in New York, told The 89 00:04:46,440 --> 00:04:49,960 Speaker 1: New York Times. Everybody is either on it or asking 90 00:04:49,960 --> 00:04:51,960 Speaker 1: how to get on it. We haven't seen a prescription 91 00:04:52,040 --> 00:04:55,000 Speaker 1: drug with this much cocktail and dinner chatter since Can 92 00:04:55,040 --> 00:05:00,360 Speaker 1: anybody guess biagra bag? Which turns out the other there's 93 00:05:00,360 --> 00:05:04,799 Speaker 1: a good side effect of viagra? Oh what less likely 94 00:05:04,839 --> 00:05:07,240 Speaker 1: to die of a heart attack? Oh, I didn't know. 95 00:05:07,279 --> 00:05:09,839 Speaker 1: It's not true. Yeah, that was not a real intensive 96 00:05:09,880 --> 00:05:13,799 Speaker 1: study that's been duplicated. It just a headline from some website. No, no, no, this, this, 97 00:05:13,800 --> 00:05:18,160 Speaker 1: this was all over the place the other day. Really. Yeah, 98 00:05:18,160 --> 00:05:21,760 Speaker 1: I'll find it. But I guess you know, you have 99 00:05:21,800 --> 00:05:25,359 Speaker 1: to choose. Your heart will be a little healthier, but 100 00:05:25,880 --> 00:05:30,719 Speaker 1: you're gonna end up with well a permanent Oh you 101 00:05:30,760 --> 00:05:32,880 Speaker 1: have to take that much of it? Well, I would 102 00:05:32,960 --> 00:05:37,800 Speaker 1: imagine just a little bit, you know, that's what it does. Yeah, right, 103 00:05:38,240 --> 00:05:41,240 Speaker 1: different things up and now there's many competitors, so there's 104 00:05:41,240 --> 00:05:45,239 Speaker 1: not just the brand named Viagra. No, the doctor explained, 105 00:05:45,240 --> 00:05:47,240 Speaker 1: I see this every day. A fifty year old patient 106 00:05:47,279 --> 00:05:50,160 Speaker 1: will come in suddenly she's super skinny and needs filler, 107 00:05:50,480 --> 00:05:53,080 Speaker 1: which she never needed before. I look at and saying, 108 00:05:53,120 --> 00:05:55,040 Speaker 1: how long have you been on ozempic? And I'm right, 109 00:05:55,080 --> 00:05:56,960 Speaker 1: one hundred percent of the time. It's a drug of 110 00:05:57,040 --> 00:06:00,800 Speaker 1: choice these days for the one percent refers to. These 111 00:06:00,839 --> 00:06:05,000 Speaker 1: are wealthy people who obsess over their looks to the 112 00:06:05,040 --> 00:06:07,599 Speaker 1: point where if they hear a friend is losing weight 113 00:06:07,640 --> 00:06:09,600 Speaker 1: on those empic, oh yeah, they run and go get 114 00:06:09,680 --> 00:06:11,200 Speaker 1: I've heard a lot of chatter on the West Side 115 00:06:11,320 --> 00:06:15,760 Speaker 1: about a zempic and it's called an off label prescription. 116 00:06:17,080 --> 00:06:21,200 Speaker 1: Sometimes with drugs, doctors just find out that there is 117 00:06:21,200 --> 00:06:25,600 Speaker 1: a side effect that wasn't advertised, wasn't explained, and and 118 00:06:25,800 --> 00:06:29,560 Speaker 1: and you know, obviously if you control your your your diabetes, 119 00:06:29,560 --> 00:06:33,560 Speaker 1: your sugar, you also might lose weight. Yeah, turns out 120 00:06:33,600 --> 00:06:35,600 Speaker 1: it works. Even if you don't have diabetes, you can 121 00:06:35,640 --> 00:06:37,960 Speaker 1: lose weight. It's like they always say, the weight loss 122 00:06:38,000 --> 00:06:40,000 Speaker 1: drugs it'll trigger something in you to make you think 123 00:06:40,000 --> 00:06:43,080 Speaker 1: you're full, so you won't keep gobbling down the food. 124 00:06:43,080 --> 00:06:46,200 Speaker 1: And that's the key to weight loss. People just eat 125 00:06:46,240 --> 00:06:48,160 Speaker 1: too much, they overeat, they have to clean off their 126 00:06:48,160 --> 00:06:50,320 Speaker 1: plate or whatever. They're not even thinking. They just fill 127 00:06:50,360 --> 00:06:54,600 Speaker 1: their face. Then here's the part we were just talking about. 128 00:06:54,680 --> 00:06:59,159 Speaker 1: There is a non invasive thing that they do injections 129 00:06:59,240 --> 00:07:05,800 Speaker 1: of red serades and hyerlonic acid. These are fillers. Another 130 00:07:05,839 --> 00:07:13,600 Speaker 1: one is called Sculptra, which simulates collagen and oh yeah, yeah, 131 00:07:13,600 --> 00:07:17,000 Speaker 1: well yes, yes, they restore volume in your face. That's 132 00:07:17,040 --> 00:07:20,400 Speaker 1: how this acts. So the so the wealthy people that 133 00:07:20,440 --> 00:07:22,400 Speaker 1: went for the ozempic drug and loss later now coming 134 00:07:22,400 --> 00:07:25,040 Speaker 1: in for the face fillers to make up for their 135 00:07:25,440 --> 00:07:30,360 Speaker 1: ozempic face, which is shrinkingzepic face. Is that sounds polish? 136 00:07:30,680 --> 00:07:33,440 Speaker 1: My dad used to yell some word at me that 137 00:07:33,760 --> 00:07:38,400 Speaker 1: sounded like it sounded like ozempic. Yeah it wasn't azempic, 138 00:07:38,480 --> 00:07:41,480 Speaker 1: but it has that same sound, that same rhythm to it. 139 00:07:41,520 --> 00:07:45,600 Speaker 1: Looks like even uh Elon Musk used ozempic for some 140 00:07:45,680 --> 00:07:49,040 Speaker 1: weight loss. Kim Kardashian supposedly use the other product that's 141 00:07:49,080 --> 00:07:53,200 Speaker 1: we go Vi to lose weight. Um, so that's why 142 00:07:53,240 --> 00:07:57,280 Speaker 1: this had she had button plants, didn't she? She says 143 00:07:57,280 --> 00:07:59,560 Speaker 1: she did not. That's what she's always said. I mean 144 00:07:59,560 --> 00:08:02,640 Speaker 1: that naturally, you know, I've actually seen a lot of 145 00:08:02,680 --> 00:08:07,320 Speaker 1: women seriously in California with butts like that. Oh, it's 146 00:08:07,360 --> 00:08:09,240 Speaker 1: all fashion trend. Well, I don't know if it's a 147 00:08:09,280 --> 00:08:11,360 Speaker 1: fashion trend. I mean, it's just the way you're born. 148 00:08:11,560 --> 00:08:14,440 Speaker 1: Unless you do a lot of squats, they move fat 149 00:08:14,480 --> 00:08:16,520 Speaker 1: from one part of your body to the other. It's 150 00:08:16,520 --> 00:08:19,320 Speaker 1: not technically an implant. But I don't know if if 151 00:08:19,640 --> 00:08:22,240 Speaker 1: the people that I'm seeing have had that. What I'm 152 00:08:22,280 --> 00:08:24,200 Speaker 1: saying is maybe they they that's just the way that 153 00:08:24,240 --> 00:08:26,360 Speaker 1: they're they're built, or they've done a lot of squats. 154 00:08:26,520 --> 00:08:29,000 Speaker 1: It's not a natural. There are plenty of girls these 155 00:08:29,080 --> 00:08:31,720 Speaker 1: days in their twenties and thirties flying to different countries 156 00:08:31,720 --> 00:08:35,480 Speaker 1: to go get Brazilian butt lifts, the BBL surgeries. I know, 157 00:08:35,559 --> 00:08:37,800 Speaker 1: but these are older women. I don't know. Maybe they 158 00:08:37,800 --> 00:08:39,800 Speaker 1: are too, I don't know. Yeah, they're trying to compete 159 00:08:39,800 --> 00:08:43,000 Speaker 1: with Chris Jenner. Did she have a BBL two? She 160 00:08:43,080 --> 00:08:45,200 Speaker 1: might have, I don't know. I don't get her on 161 00:08:45,240 --> 00:08:48,679 Speaker 1: the show and ask her. That's right. Segment on Kardashian 162 00:08:48,760 --> 00:08:54,160 Speaker 1: body parts. All right, I found the viagra thing heart 163 00:08:54,360 --> 00:08:57,559 Speaker 1: Male heart attack survivors who took viagra had a low 164 00:08:57,640 --> 00:09:00,160 Speaker 1: risk of having another heart attack. The more frequently the 165 00:09:00,200 --> 00:09:03,360 Speaker 1: viagra doses, the more protection and offered against heart issues, 166 00:09:04,520 --> 00:09:08,440 Speaker 1: and it actually can help extend your life. People who 167 00:09:08,800 --> 00:09:14,120 Speaker 1: take viagra live longer than people who don't. Well, look 168 00:09:14,160 --> 00:09:16,120 Speaker 1: at that, because this has been around like twenty five 169 00:09:16,200 --> 00:09:18,040 Speaker 1: thirty years now, I think you've just got to get 170 00:09:18,080 --> 00:09:21,600 Speaker 1: the larger size pants. It's only a live with it. 171 00:09:23,400 --> 00:09:27,679 Speaker 1: More coming up, Yes, the eternal. You're gonna do commercials 172 00:09:27,679 --> 00:09:30,400 Speaker 1: now with more de Martin. Well maybe those will be okay. 173 00:09:30,440 --> 00:09:34,439 Speaker 1: Then it's not just for erections. It'll make you live longer. 174 00:09:35,640 --> 00:09:38,080 Speaker 1: The keyword is next. Johnny Ken caf I am six 175 00:09:38,240 --> 00:09:41,160 Speaker 1: forty live everywhere, the iHeartRadio app. Oh this just in. 176 00:09:41,440 --> 00:09:45,120 Speaker 1: We're gonna get more water pop the Champagne bottle. The 177 00:09:45,200 --> 00:09:48,320 Speaker 1: Department of Water Resources, after saying a couple of months 178 00:09:48,360 --> 00:09:51,719 Speaker 1: ago they could only give five percent of requested water supplies, 179 00:09:52,160 --> 00:09:57,160 Speaker 1: now says they can give thirty percent out but hope. 180 00:09:57,160 --> 00:10:00,199 Speaker 1: So this is for the twenty seven million people to 181 00:10:00,240 --> 00:10:01,880 Speaker 1: get water from this source, and I think one of 182 00:10:01,920 --> 00:10:03,920 Speaker 1: them is like the Metropolitan Water District, which was a 183 00:10:03,960 --> 00:10:06,880 Speaker 1: biggie in southern California. We had twenty four trillion gallons 184 00:10:06,920 --> 00:10:09,720 Speaker 1: of rain, we did, yeah, so they should have kept 185 00:10:09,720 --> 00:10:13,199 Speaker 1: some of it. As of Thursday, the statewide snowpack is 186 00:10:13,280 --> 00:10:16,640 Speaker 1: two hundred and sixteen percent of normal for the date. 187 00:10:17,160 --> 00:10:20,040 Speaker 1: And that's really good because the adults melt slowly, so 188 00:10:20,160 --> 00:10:23,800 Speaker 1: that can be captured. That's the idea. Lake Shasta is 189 00:10:23,800 --> 00:10:27,199 Speaker 1: at fifty five percent of capacity, like Orville sixty three. 190 00:10:27,480 --> 00:10:29,760 Speaker 1: So this means all those things that they found with 191 00:10:29,840 --> 00:10:31,760 Speaker 1: the drought, Like remember out there in the Hoover Dam 192 00:10:31,840 --> 00:10:35,439 Speaker 1: area and they found like body Lake Meade. Yeah, yeah, yeah. 193 00:10:35,240 --> 00:10:39,040 Speaker 1: Those mob killings, those mob killing people, they've had a 194 00:10:39,080 --> 00:10:41,040 Speaker 1: tough time. They were identifying for sure, every one of 195 00:10:41,040 --> 00:10:44,240 Speaker 1: the bodies, but I think, well, that collective belief was 196 00:10:44,240 --> 00:10:46,679 Speaker 1: that a lot of them were mobster after fifty years, 197 00:10:47,120 --> 00:10:49,720 Speaker 1: who else would do that? Who Well, stumps a guy 198 00:10:49,760 --> 00:10:52,160 Speaker 1: in his car in Lake Mead could have been a 199 00:10:52,200 --> 00:10:56,760 Speaker 1: boating accident. Now they suicide or not. I think they 200 00:10:56,760 --> 00:11:02,760 Speaker 1: found one guy in a in a drum yes, fine, drama, Yeah, yeah, 201 00:11:02,800 --> 00:11:07,120 Speaker 1: that's that's mom, all right. So uh as we mock 202 00:11:07,240 --> 00:11:11,040 Speaker 1: the annual homeless count of people on the streets of 203 00:11:11,280 --> 00:11:15,840 Speaker 1: LA County. We were so right about this. Yeah, and 204 00:11:15,920 --> 00:11:18,720 Speaker 1: you know, the RAND Corporation, they're not like some right 205 00:11:18,760 --> 00:11:22,000 Speaker 1: wing outfit. So anyway, by the way, the RAND people 206 00:11:22,600 --> 00:11:27,240 Speaker 1: are geniuses. They're very smart. I met a RAND researcher 207 00:11:27,240 --> 00:11:30,640 Speaker 1: once at a party, a woman, most intimidating woman I 208 00:11:30,760 --> 00:11:37,280 Speaker 1: ever spoke with. Seriously, she was so smart and analytical. 209 00:11:37,400 --> 00:11:41,600 Speaker 1: I was like, I even knew more than me about baseball. Gosh, yes, 210 00:11:41,679 --> 00:11:45,240 Speaker 1: she knew more than me. She was. She also very 211 00:11:45,240 --> 00:11:48,040 Speaker 1: good looking too. It was quite a package. Well, here 212 00:11:48,960 --> 00:11:53,160 Speaker 1: I hear the results of this report that they put out. LASA, 213 00:11:53,640 --> 00:11:58,559 Speaker 1: the inept corrupt Los Angeles Homeless Services Authority, put out 214 00:11:58,559 --> 00:12:00,640 Speaker 1: the news. It was late last year. Member was supposed 215 00:12:00,640 --> 00:12:01,600 Speaker 1: to come out in June. I don't think it came 216 00:12:01,600 --> 00:12:04,720 Speaker 1: out to August. That homelessness seems to be leveling off 217 00:12:04,720 --> 00:12:07,440 Speaker 1: in the county. There was just a five percent edition 218 00:12:07,520 --> 00:12:10,480 Speaker 1: during the two years of the pandemic, and we said, liar, liar, 219 00:12:10,520 --> 00:12:13,520 Speaker 1: pants on fire, right, And then we got word that 220 00:12:13,720 --> 00:12:16,240 Speaker 1: some took taking a look at a tract in Venice 221 00:12:16,679 --> 00:12:19,720 Speaker 1: where losses people said no, no homeless here, and everybody 222 00:12:19,760 --> 00:12:22,000 Speaker 1: went there and counted like dozens of homeless people. It's 223 00:12:22,040 --> 00:12:24,760 Speaker 1: like that doesn't make any sense. So they actually they 224 00:12:24,800 --> 00:12:28,720 Speaker 1: actually registered zeros in some neighborhoods where there were clearly 225 00:12:28,880 --> 00:12:32,760 Speaker 1: lots of homeless and you realized that this thing was 226 00:12:32,800 --> 00:12:36,000 Speaker 1: either botched or they were just lying to cover up 227 00:12:36,000 --> 00:12:40,240 Speaker 1: the problem. So what RAN did in this study they 228 00:12:40,240 --> 00:12:43,600 Speaker 1: went out time and time again, dozens of times over 229 00:12:43,640 --> 00:12:47,400 Speaker 1: a year to some areas of the county, and in 230 00:12:47,480 --> 00:12:51,240 Speaker 1: particular they found big problems with the homeless count from 231 00:12:51,320 --> 00:12:55,360 Speaker 1: Lasa on skid Row and in Hollywood and in Venice. 232 00:12:56,120 --> 00:12:59,200 Speaker 1: And they saw thirteen percent more on skid Row, fourteen 233 00:12:59,240 --> 00:13:01,679 Speaker 1: and a half percent more in Hollywood, and thirty two 234 00:13:01,720 --> 00:13:05,400 Speaker 1: percent more in Venice more. And that's where they had 235 00:13:05,440 --> 00:13:08,400 Speaker 1: the zeros. That's where they claim, They claim that things 236 00:13:08,480 --> 00:13:11,760 Speaker 1: were getting better, that there was less homeless. Do you 237 00:13:11,760 --> 00:13:14,000 Speaker 1: think there's a bone headed Bonden leading on Lassa to 238 00:13:14,080 --> 00:13:16,120 Speaker 1: make my count lower out there on the West Side 239 00:13:16,120 --> 00:13:18,040 Speaker 1: and in Venice. What you can do for me I do, 240 00:13:18,160 --> 00:13:21,000 Speaker 1: Plus they're incompetent. I gotta show that my plan is 241 00:13:21,000 --> 00:13:24,920 Speaker 1: working well. You get volunteers. I question anyone in the 242 00:13:25,040 --> 00:13:27,480 Speaker 1: right mind who wants to work in the middle of 243 00:13:27,520 --> 00:13:30,600 Speaker 1: the night counting homeless people. Odds are they can't count? 244 00:13:31,679 --> 00:13:35,040 Speaker 1: And I do think it was people who couldn't count lazy. 245 00:13:35,559 --> 00:13:39,160 Speaker 1: They couldn't had this stupid app, and the app would 246 00:13:39,200 --> 00:13:44,520 Speaker 1: malfunction and people would would enter their numbers, which may 247 00:13:44,520 --> 00:13:46,840 Speaker 1: have been off to begin with, and then the numbers 248 00:13:46,840 --> 00:13:50,000 Speaker 1: would come out of the back end and it's It 249 00:13:50,040 --> 00:13:53,080 Speaker 1: was a bad system with bad people, I mean not 250 00:13:53,160 --> 00:13:57,320 Speaker 1: bad people, incompetent people doing it. Look, LASSA is a 251 00:13:57,400 --> 00:14:01,120 Speaker 1: terrible organization and I don't think anybody of any decent 252 00:14:01,120 --> 00:14:03,360 Speaker 1: talent would work there. I don't anyone. I don't think 253 00:14:03,360 --> 00:14:05,840 Speaker 1: anybody of any decent intelligence would work there. If you 254 00:14:05,920 --> 00:14:08,080 Speaker 1: had your choice of all the jobs in the world, 255 00:14:08,280 --> 00:14:10,679 Speaker 1: and you were smart and you were sharp, and what 256 00:14:11,000 --> 00:14:13,800 Speaker 1: would you work at LASSA? Of all the places you 257 00:14:13,800 --> 00:14:17,760 Speaker 1: could work now in in this tech age, you pick LSA. 258 00:14:18,280 --> 00:14:21,680 Speaker 1: This study is basically not picking on the people as 259 00:14:21,760 --> 00:14:24,240 Speaker 1: much as it's saying the methodology has flawed because they 260 00:14:24,320 --> 00:14:29,160 Speaker 1: kept returning to what they called problem homeless areas time 261 00:14:29,160 --> 00:14:30,960 Speaker 1: and time again to get a more accurate look at 262 00:14:30,960 --> 00:14:33,880 Speaker 1: the homeless. These people walk around with the tablet one night. 263 00:14:34,560 --> 00:14:38,080 Speaker 1: It can't possibly be accurate. The methodology is created by people. 264 00:14:38,520 --> 00:14:44,440 Speaker 1: Some bonehead at LASSA. That was his idea, Let's go out, 265 00:14:44,560 --> 00:14:47,720 Speaker 1: you know, one night a year and in the dark 266 00:14:47,880 --> 00:14:50,520 Speaker 1: and see what we come up with. Now, so imagine 267 00:14:50,520 --> 00:14:52,440 Speaker 1: you're at that meeting. You'd look at him and goo, 268 00:14:52,440 --> 00:14:56,400 Speaker 1: are you nuts? But there was another trick that they 269 00:14:56,440 --> 00:14:59,360 Speaker 1: got caught. There was a three day cleanup that removed 270 00:14:59,400 --> 00:15:03,000 Speaker 1: tents from Centennial Park in Venice in June. Next month, 271 00:15:03,120 --> 00:15:07,200 Speaker 1: COUNT said thirteen percent declining homeless here. The decrease was 272 00:15:07,280 --> 00:15:10,120 Speaker 1: driven by fewer tents and makeshift shelters, but the number 273 00:15:10,120 --> 00:15:12,920 Speaker 1: of cars, vans and RVs remain the same. But by 274 00:15:13,000 --> 00:15:16,240 Speaker 1: later that month the population had rebounded to its formal level. 275 00:15:16,920 --> 00:15:19,320 Speaker 1: So and this is something we always talk about, you 276 00:15:19,360 --> 00:15:21,600 Speaker 1: know that. If that's true, it almost sounds like the 277 00:15:21,640 --> 00:15:23,400 Speaker 1: fix was in, let's do a clean up and then 278 00:15:23,400 --> 00:15:25,280 Speaker 1: when the COUNT people come through here, sure I'll come 279 00:15:25,320 --> 00:15:27,280 Speaker 1: up with a smaller number. Clean Up's okay if they 280 00:15:27,280 --> 00:15:29,480 Speaker 1: come back. That's after the COUNT clean up in June, 281 00:15:29,680 --> 00:15:32,800 Speaker 1: count it in July, and then in August everybody's back 282 00:15:32,840 --> 00:15:34,640 Speaker 1: and you know what, but we put out a number 283 00:15:34,640 --> 00:15:36,600 Speaker 1: that says, oh, we're doing great, and that is a 284 00:15:36,680 --> 00:15:39,040 Speaker 1: scam that I'm sure is arranged by the city council 285 00:15:39,080 --> 00:15:42,000 Speaker 1: members because you know what, these boobs have feelings too, 286 00:15:42,240 --> 00:15:45,400 Speaker 1: and people like Bonnen or Nitthi Aramin or Garcetti, they 287 00:15:45,440 --> 00:15:48,480 Speaker 1: get tired of getting constantly roasted and complained and dealing 288 00:15:48,480 --> 00:15:51,120 Speaker 1: with all the emails and phone calls, people talking them 289 00:15:51,120 --> 00:15:52,440 Speaker 1: all the time. What are you going to do something? 290 00:15:52,480 --> 00:15:54,640 Speaker 1: What are you going to do something? So they get 291 00:15:54,680 --> 00:15:56,320 Speaker 1: they get sick of it, and they just say, let's 292 00:15:56,320 --> 00:15:58,240 Speaker 1: fake the numbers. Who's gonna know, how are they going 293 00:15:58,280 --> 00:16:01,080 Speaker 1: to prove it? And here comes Rand Corporation. It's like, yeah, 294 00:16:01,080 --> 00:16:04,400 Speaker 1: they proved that your numbers were fake. Rand also found 295 00:16:04,400 --> 00:16:07,360 Speaker 1: out that there was a much higher incidence of chronic 296 00:16:07,760 --> 00:16:11,480 Speaker 1: homelessness that's a soft term for a vagrant, transients that 297 00:16:11,560 --> 00:16:14,320 Speaker 1: never go away. Nearly eighty percent told them they've been 298 00:16:14,320 --> 00:16:17,320 Speaker 1: homeless more than a year, fifty seven percent more than 299 00:16:17,360 --> 00:16:19,640 Speaker 1: three years. But what does that tell you? LASSA had 300 00:16:19,640 --> 00:16:23,000 Speaker 1: a lower number for those that is not then rising 301 00:16:23,040 --> 00:16:27,520 Speaker 1: rents rights. It's a lifestyle. No, it is a lifestyle. 302 00:16:27,640 --> 00:16:31,680 Speaker 1: It's a lifestyle. They've chosen. They've chosen to take the drugs. 303 00:16:31,720 --> 00:16:34,600 Speaker 1: They've chosen not to treat their medical and mental problems. 304 00:16:34,840 --> 00:16:38,320 Speaker 1: They've chosen to live in the street because they like it, 305 00:16:38,880 --> 00:16:41,000 Speaker 1: and they can get away with it because we have 306 00:16:41,080 --> 00:16:44,120 Speaker 1: no rules anymore. I'm telling you, a little by little, 307 00:16:44,240 --> 00:16:48,560 Speaker 1: all the myths, all the propaganda myths that these left 308 00:16:48,560 --> 00:16:53,600 Speaker 1: wing anarchist progressive jerks had been feeding through the media 309 00:16:53,640 --> 00:16:56,360 Speaker 1: to us are being proven to be nothing but lies. 310 00:16:57,080 --> 00:16:59,360 Speaker 1: It is a bunch of drug addicts and mental patients. 311 00:16:59,400 --> 00:17:01,600 Speaker 1: They've all been out there a long time. They come 312 00:17:01,680 --> 00:17:05,560 Speaker 1: from all over the country. This collectively is not our problem. 313 00:17:05,760 --> 00:17:11,640 Speaker 1: Society did not fail them. They failed themselves. And as usual, 314 00:17:11,760 --> 00:17:13,840 Speaker 1: they asked people, well, what would it take to get 315 00:17:13,880 --> 00:17:16,399 Speaker 1: you up the street? The Rand study said eighty percent 316 00:17:16,480 --> 00:17:20,080 Speaker 1: want their They want their private room. They told them 317 00:17:20,119 --> 00:17:24,479 Speaker 1: that I'll accept a hotel or a motel or a shelter, 318 00:17:24,560 --> 00:17:28,200 Speaker 1: but the shelter has to offer privacy. No group shelters. 319 00:17:28,359 --> 00:17:31,000 Speaker 1: A lot of sober living homes, a lot of them 320 00:17:31,000 --> 00:17:34,399 Speaker 1: will accept a private tent. And this is where I'm thinking, 321 00:17:34,560 --> 00:17:37,720 Speaker 1: this is what the desert's for. Why we got to 322 00:17:37,760 --> 00:17:41,200 Speaker 1: make the homeless City, Homeless, homeless village out in the desert. 323 00:17:41,280 --> 00:17:43,720 Speaker 1: They're all be happy in their little tents. Where's our 324 00:17:43,720 --> 00:17:45,880 Speaker 1: friend out there with the h Was it a bar 325 00:17:45,960 --> 00:17:48,600 Speaker 1: out in San Bernardino? Who was gonna he bought a 326 00:17:48,640 --> 00:17:51,280 Speaker 1: bus to take Yes? What happened with that? He said 327 00:17:51,320 --> 00:17:52,680 Speaker 1: he was gonna give them two weeks. I'm not sure 328 00:17:52,680 --> 00:17:54,760 Speaker 1: if it's been two weeks yet to clean up the 329 00:17:55,040 --> 00:17:56,720 Speaker 1: streets around his business. I think it was going to 330 00:17:56,800 --> 00:17:58,280 Speaker 1: be around the end of the month. Well, we're getting 331 00:17:58,359 --> 00:18:00,480 Speaker 1: We're gonna check back with him because I want to 332 00:18:00,600 --> 00:18:04,639 Speaker 1: see I want video of that. I'm taking homeless on 333 00:18:04,640 --> 00:18:06,960 Speaker 1: a trip. I was gonna drive one of the buses. Yeah, 334 00:18:07,160 --> 00:18:09,840 Speaker 1: slab City, here we come. You know that little sign 335 00:18:09,880 --> 00:18:12,119 Speaker 1: on the top of the bus. Yeah, right, welcome a 336 00:18:12,160 --> 00:18:16,920 Speaker 1: board slab City. Johnny ken CAF I am six forty 337 00:18:16,920 --> 00:18:19,359 Speaker 1: Live everywhere on the iHeartRadio app. I just found a 338 00:18:19,359 --> 00:18:22,879 Speaker 1: story that Diane Feinstein still hasn't decided if she's going 339 00:18:22,920 --> 00:18:26,040 Speaker 1: to run again or not. Yeah, it's getting crowded there 340 00:18:26,160 --> 00:18:28,120 Speaker 1: to challenge her. She says, I need a little bit 341 00:18:28,119 --> 00:18:33,040 Speaker 1: of time. So it's not this year. It's not it's 342 00:18:33,080 --> 00:18:36,040 Speaker 1: twenty twenty four. Her staff is starting to speak out 343 00:18:36,080 --> 00:18:40,160 Speaker 1: of anonymously to say it's getting bad. Her short term 344 00:18:40,240 --> 00:18:44,240 Speaker 1: memory is so poor that she often forgets she has 345 00:18:44,280 --> 00:18:47,200 Speaker 1: just been briefed on a topic and then gets bad 346 00:18:47,240 --> 00:18:51,280 Speaker 1: at them, accusing your staff of failing to brief her 347 00:18:51,840 --> 00:18:54,880 Speaker 1: right after they just did it. Yeah, so they tell 348 00:18:54,880 --> 00:18:56,960 Speaker 1: it happens as an element of denial. You just get 349 00:18:57,000 --> 00:18:58,919 Speaker 1: mad and you're act like, no, that didn't happen, and 350 00:18:58,960 --> 00:19:01,640 Speaker 1: why didn't you brief me? Right, So they tell her 351 00:19:01,680 --> 00:19:05,320 Speaker 1: something and then her reaction is, why didn't you tell 352 00:19:05,359 --> 00:19:08,280 Speaker 1: me what we just told you? Well, you didn't tell me. 353 00:19:09,040 --> 00:19:11,680 Speaker 1: So how do you think she's even gonna understand that 354 00:19:11,760 --> 00:19:13,560 Speaker 1: she has to run again next year? Or they know 355 00:19:13,680 --> 00:19:16,720 Speaker 1: that's a good question? Or will she say oh no, 356 00:19:16,880 --> 00:19:18,800 Speaker 1: and then you know a few months later, what what 357 00:19:18,880 --> 00:19:21,080 Speaker 1: are you asking me? Well, of course I'm going to run. 358 00:19:21,800 --> 00:19:25,359 Speaker 1: If if somehow she'd run and win, she would be 359 00:19:25,560 --> 00:19:28,560 Speaker 1: ninety seven at the end of her next term. She 360 00:19:28,760 --> 00:19:30,800 Speaker 1: is nine, she's ninety two or ninety three. Now she 361 00:19:31,080 --> 00:19:34,520 Speaker 1: is ninety she's ninety all right, yeah right, this wouldn't 362 00:19:34,520 --> 00:19:37,400 Speaker 1: be until late next year. Yeah, So if if she's 363 00:19:37,440 --> 00:19:39,560 Speaker 1: probably gonna turn ninety one, this year and ninety two 364 00:19:39,600 --> 00:19:42,720 Speaker 1: next year. Yeah, all right, then the term ends in 365 00:19:42,880 --> 00:19:46,199 Speaker 1: January of twenty ninety seven. At the end of the term, 366 00:19:46,240 --> 00:19:49,119 Speaker 1: it's a six year term. That's right, Yeah, twenty thirty. 367 00:19:49,160 --> 00:19:53,439 Speaker 1: This will take us through. Oh no, but if she 368 00:19:53,480 --> 00:19:57,480 Speaker 1: doesn't want to leave, well she might not win, is 369 00:19:57,520 --> 00:19:59,800 Speaker 1: the point. People keep making an issue of this. She 370 00:19:59,840 --> 00:20:03,000 Speaker 1: may not survived the primary. I wonder, but because now 371 00:20:03,040 --> 00:20:07,320 Speaker 1: we have that that Adam Schiff has jumped in, I 372 00:20:07,320 --> 00:20:10,960 Speaker 1: think we'd be better off with the dope Katie Porter. 373 00:20:11,080 --> 00:20:13,119 Speaker 1: The load from Orange County is another big one in there. 374 00:20:13,359 --> 00:20:16,240 Speaker 1: We're better off with Feinstein. Oh yeah, those two. Wow, 375 00:20:17,040 --> 00:20:22,440 Speaker 1: what a pair of He's a lunatic. He's a delusional loon. 376 00:20:23,560 --> 00:20:28,160 Speaker 1: He's just a creepy partisan. Whatever it is from my side, 377 00:20:29,040 --> 00:20:31,280 Speaker 1: although apparently last week or the week before he did 378 00:20:31,359 --> 00:20:35,120 Speaker 1: admit the time. Well, you know, this classified documents thing, 379 00:20:35,480 --> 00:20:37,760 Speaker 1: This is important because you think everybody would play it 380 00:20:37,800 --> 00:20:40,880 Speaker 1: down now that it's been found in Biden's garage. But well, 381 00:20:40,920 --> 00:20:44,560 Speaker 1: they're nervous because the Biden family is so corrupt. They're worried. 382 00:20:44,880 --> 00:20:47,720 Speaker 1: You know, these are these are random pages hidden here 383 00:20:47,800 --> 00:20:50,360 Speaker 1: and there and here, and they're thinking, Wow, what if 384 00:20:50,400 --> 00:20:54,840 Speaker 1: those pages were specifically hit on purpose? Oh because something 385 00:20:54,880 --> 00:20:57,679 Speaker 1: goods in it? Right, Yeah, that that has some connection. Well, 386 00:20:57,680 --> 00:20:59,920 Speaker 1: they're gonna open up there a Hunter Biden hearing soon. 387 00:21:00,000 --> 00:21:01,920 Speaker 1: And I think the publicans out that they control the 388 00:21:01,960 --> 00:21:04,680 Speaker 1: House of Representatives and that's what they promised to do. 389 00:21:04,840 --> 00:21:08,520 Speaker 1: And Jim Biden, Yeah, that's the brother. And there was 390 00:21:08,560 --> 00:21:11,280 Speaker 1: a report the other day that you know, after Biden 391 00:21:11,960 --> 00:21:14,959 Speaker 1: left the vice presidency he took in quite a bit 392 00:21:14,960 --> 00:21:18,680 Speaker 1: of money. Yeah he did. He got rich, He got rich, 393 00:21:18,920 --> 00:21:21,240 Speaker 1: and a lot of it is because his brother and 394 00:21:21,320 --> 00:21:24,720 Speaker 1: his son were working deals in his name yea, China, Ukraine, 395 00:21:25,760 --> 00:21:30,159 Speaker 1: among other places. I mean. And Jim Biden looks just 396 00:21:30,240 --> 00:21:32,000 Speaker 1: like Joe. I saw a picture of the two of them. 397 00:21:32,520 --> 00:21:35,639 Speaker 1: Oh really they were. They were face to face in profile, 398 00:21:35,960 --> 00:21:38,600 Speaker 1: and they were talking very close, as if they were whispering, 399 00:21:38,880 --> 00:21:42,200 Speaker 1: almost touching foreheads, and they're mirror images of each other. 400 00:21:42,280 --> 00:21:45,560 Speaker 1: And they look like two old mob bosses. That was 401 00:21:45,560 --> 00:21:48,840 Speaker 1: the expression on their faces. I'm thinking this picture sums 402 00:21:48,920 --> 00:21:51,840 Speaker 1: up everything. And the problem, of course is Biden's always 403 00:21:51,840 --> 00:21:53,760 Speaker 1: said I don't know where to think about my son's business. 404 00:21:53,800 --> 00:21:59,080 Speaker 1: I don't get involved yet. Just wait, I think. I 405 00:21:59,119 --> 00:22:01,400 Speaker 1: think that's why there's some criticism from his own party. 406 00:22:01,440 --> 00:22:03,960 Speaker 1: They're trying to sink them. Yeah, they know what's coming. 407 00:22:04,720 --> 00:22:08,639 Speaker 1: We were just talking about a homelessness. A Rand study 408 00:22:08,760 --> 00:22:12,840 Speaker 1: says that this loss annual homeless count is probably way 409 00:22:12,880 --> 00:22:15,960 Speaker 1: off because they did something more exactly. They kept going 410 00:22:16,000 --> 00:22:19,360 Speaker 1: back to the same census tracks for days, and their 411 00:22:19,400 --> 00:22:23,159 Speaker 1: numbers were quite different than losses. One night, holding it 412 00:22:23,320 --> 00:22:26,440 Speaker 1: in the dark too, Yeah, holding the tablet and trying 413 00:22:26,440 --> 00:22:30,200 Speaker 1: to stare down into a tent anybody in there. I see. 414 00:22:30,240 --> 00:22:35,600 Speaker 1: That's my distrust these these kind of you know, government surveys. 415 00:22:35,920 --> 00:22:39,159 Speaker 1: I don't trust them. I assume they're wrong or they're lies, 416 00:22:39,200 --> 00:22:42,560 Speaker 1: because they have every motivation to lie, and well they 417 00:22:42,600 --> 00:22:45,600 Speaker 1: want to underplay the number. Of course they do. There 418 00:22:45,600 --> 00:22:47,720 Speaker 1: had to be pressure. That's why I remember this got 419 00:22:47,720 --> 00:22:49,720 Speaker 1: delayed and I kept saying, why is this getting delayed? 420 00:22:49,800 --> 00:22:51,840 Speaker 1: And then when he finally came out, it's like, oh, 421 00:22:51,880 --> 00:22:54,360 Speaker 1: don't worry. Homelessness eased a bit during the pandemic, only 422 00:22:54,359 --> 00:22:56,920 Speaker 1: a five percent increase. That's, you know, within the margin 423 00:22:56,960 --> 00:23:00,439 Speaker 1: of errors. I've got, I've got two eyes. Stop telling 424 00:23:00,480 --> 00:23:03,560 Speaker 1: me I'm not seeing what I'm seeing. Stop that and 425 00:23:03,760 --> 00:23:07,520 Speaker 1: keep that in mind now with Bessetti as mayor, Yes, 426 00:23:07,640 --> 00:23:11,360 Speaker 1: because they're playing are up big that it's already working well. 427 00:23:11,400 --> 00:23:14,200 Speaker 1: And look, it looks like they did some good stuff 428 00:23:14,240 --> 00:23:16,440 Speaker 1: there in Venice. We've talked to Venice residents who have 429 00:23:16,520 --> 00:23:18,840 Speaker 1: been all over Bonnen and the homeless problem for years, 430 00:23:19,119 --> 00:23:21,439 Speaker 1: and they're saying, so far, so good. This is a 431 00:23:21,440 --> 00:23:24,200 Speaker 1: couple of big encampments they just cleared out. But you 432 00:23:24,320 --> 00:23:26,000 Speaker 1: got to give it time. Those people could come back. 433 00:23:26,040 --> 00:23:28,119 Speaker 1: That's what the Rand survey said, that people tend to 434 00:23:28,200 --> 00:23:30,679 Speaker 1: drift back again, or there could just be another new 435 00:23:30,760 --> 00:23:33,080 Speaker 1: encampment popping up. Because you can't This has got to 436 00:23:33,080 --> 00:23:35,119 Speaker 1: be a permanent fix. This can't be oh for a 437 00:23:35,119 --> 00:23:37,239 Speaker 1: few months, is nobody in that park or on that 438 00:23:37,280 --> 00:23:40,240 Speaker 1: street corner? Relocate them because the meth addics are always 439 00:23:40,240 --> 00:23:43,280 Speaker 1: going to be mat Slab City, Slab City, Slab City 440 00:23:43,359 --> 00:23:46,040 Speaker 1: is the answer to everything. We should do a show 441 00:23:46,080 --> 00:23:51,320 Speaker 1: from there. No no, because you get stabbed or oh, 442 00:23:51,359 --> 00:23:53,720 Speaker 1: I'm sure we will. Oh No. The stories we would 443 00:23:53,760 --> 00:23:56,600 Speaker 1: hear from the people that live there, they'd probably love 444 00:23:56,680 --> 00:23:59,000 Speaker 1: to be interviewed and tell their life story about why 445 00:23:59,080 --> 00:24:02,240 Speaker 1: they lab City and after twenty seconds. It really would 446 00:24:02,280 --> 00:24:04,600 Speaker 1: be fascinating, right, yeah, no government, no rules. I mean, 447 00:24:04,640 --> 00:24:08,800 Speaker 1: come on, you'd like that, wouldn't you. You hate rules? Oh, 448 00:24:08,840 --> 00:24:11,000 Speaker 1: I understand. I understand the spirit of it. I just 449 00:24:11,040 --> 00:24:12,960 Speaker 1: don't want to sit in my own feces all day. 450 00:24:13,040 --> 00:24:16,480 Speaker 1: It'd be a giant moist line. That was the possibility. 451 00:24:16,480 --> 00:24:21,679 Speaker 1: It could be anyway. Anyone identify themselves as calling from 452 00:24:21,680 --> 00:24:26,119 Speaker 1: an encampment. No, no, well, well but actually, Eric, in 453 00:24:26,160 --> 00:24:28,640 Speaker 1: the past, probably before you worked it, there were people 454 00:24:28,640 --> 00:24:31,080 Speaker 1: that said they're they're homeless and they're calling from I 455 00:24:31,080 --> 00:24:32,760 Speaker 1: saw a survey the day. I think ninety percent of 456 00:24:32,760 --> 00:24:35,320 Speaker 1: homeless people do have cell phones. Well, good, we'll put 457 00:24:35,320 --> 00:24:37,680 Speaker 1: out the call here. You know, we could we could 458 00:24:37,720 --> 00:24:39,720 Speaker 1: have the call. We could have Homeless Week on the 459 00:24:39,760 --> 00:24:45,320 Speaker 1: moist Line, a special edition, a theme. Wow. Yeah, you'll 460 00:24:45,359 --> 00:24:47,080 Speaker 1: get a lot of people faking it for fun. But 461 00:24:47,160 --> 00:24:50,440 Speaker 1: sure you could try. That's part of the moist Line 462 00:24:50,760 --> 00:24:55,760 Speaker 1: as well. We had another dead body in Nitya Rahman's district, 463 00:24:56,560 --> 00:25:00,320 Speaker 1: her council district in Sherman Oaks for last week. Story 464 00:25:00,400 --> 00:25:02,560 Speaker 1: was Yeah, there were three people who died on the 465 00:25:02,600 --> 00:25:07,400 Speaker 1: streets of Sherman Oaks outside some businesses this one. Oh 466 00:25:07,920 --> 00:25:12,240 Speaker 1: man was killed by a garbage truck. So he was 467 00:25:12,280 --> 00:25:16,560 Speaker 1: probably just lying there sleeping. He doesn't say that, but 468 00:25:16,840 --> 00:25:20,560 Speaker 1: well he probably was. Maybe maybe he was under Yeah, 469 00:25:20,560 --> 00:25:23,080 Speaker 1: they'll put boxes and stuff on top of themselves if 470 00:25:23,119 --> 00:25:26,399 Speaker 1: not a blanket or it's been cold. It's been probably 471 00:25:26,480 --> 00:25:29,480 Speaker 1: upper thirties in the valley for the last week or two. 472 00:25:30,000 --> 00:25:34,760 Speaker 1: So he's probably rolled up in a sleeping bag or blankets. Right, 473 00:25:35,200 --> 00:25:37,720 Speaker 1: And you can't I've seen these guys and you can't 474 00:25:37,800 --> 00:25:40,960 Speaker 1: see their head and you can't see their feet. It 475 00:25:41,080 --> 00:25:44,080 Speaker 1: just when you're driving a sanitation truck. Sure his ability 476 00:25:44,160 --> 00:25:47,080 Speaker 1: can be limited. No, so probably rolled right over the guy. 477 00:25:48,560 --> 00:25:51,919 Speaker 1: That's what I'm thinking here. Yeah. Uh. The quote is 478 00:25:52,040 --> 00:25:57,000 Speaker 1: believed to be unhoused. Oh that's according to office. He 479 00:25:57,160 --> 00:26:01,639 Speaker 1: believed believed to be on Sure, you're in a section 480 00:26:01,680 --> 00:26:04,480 Speaker 1: of Burbank Boulevard and Noble Avenue. He might have lived 481 00:26:04,520 --> 00:26:07,159 Speaker 1: in a four bedroom a couple of blocks away and 482 00:26:07,240 --> 00:26:09,840 Speaker 1: he just wanted to get some air that night. Right, 483 00:26:10,080 --> 00:26:14,000 Speaker 1: believed to be unhoused. This story how many? How many 484 00:26:14,040 --> 00:26:16,240 Speaker 1: housed people have been run over by a garbage truck? 485 00:26:18,680 --> 00:26:21,960 Speaker 1: This story says that apparently the number of homeless deaths 486 00:26:21,960 --> 00:26:24,320 Speaker 1: has risen from two a day in twenty fourteen to 487 00:26:24,480 --> 00:26:27,159 Speaker 1: five a day in twenty twenty, and that's already three 488 00:26:27,240 --> 00:26:30,680 Speaker 1: years out of date. So five homeless people die every 489 00:26:30,720 --> 00:26:33,200 Speaker 1: day in La County. Yeah, it's getting it's getting close 490 00:26:33,240 --> 00:26:38,320 Speaker 1: to two thousand people a year dine in the streets, right, 491 00:26:38,359 --> 00:26:40,679 Speaker 1: and they're telling us, don't worry, we're taking care of it. 492 00:26:40,760 --> 00:26:43,080 Speaker 1: Just give us more money. That's all we needed. More money. 493 00:26:43,119 --> 00:26:46,600 Speaker 1: We did account, Yeah, we did account Things are getting better. 494 00:26:46,880 --> 00:26:48,919 Speaker 1: I will clear out one encampment and then just go 495 00:26:48,960 --> 00:26:52,040 Speaker 1: away and leave us alone. Yeah. So now Bassetti got 496 00:26:52,080 --> 00:26:55,399 Speaker 1: the big headline for cleaning up the encampment near the 497 00:26:55,440 --> 00:26:57,880 Speaker 1: bridge Home Venice. What has she done since then, because 498 00:26:57,920 --> 00:27:00,760 Speaker 1: that's been about ten days now, right until she went 499 00:27:00,800 --> 00:27:02,840 Speaker 1: off to some mayor's conference. I know she's probably back now, 500 00:27:02,880 --> 00:27:04,800 Speaker 1: but I don't know what she's doing, all right. You know, 501 00:27:04,840 --> 00:27:07,560 Speaker 1: they really treat the public like children. It's like here's 502 00:27:07,560 --> 00:27:11,760 Speaker 1: a little shiny toy, and then you hope everybody carries 503 00:27:11,800 --> 00:27:14,520 Speaker 1: that glow with them for a couple of weeks, and 504 00:27:14,760 --> 00:27:16,840 Speaker 1: in the meantime nothing's done. Shouldn't one of those happen 505 00:27:16,920 --> 00:27:21,040 Speaker 1: every day? Shouldn't be seeing TV coverage of one hundred 506 00:27:21,080 --> 00:27:25,480 Speaker 1: people getting round it up every day. Oh yeah, yeah, definitely. 507 00:27:25,600 --> 00:27:28,600 Speaker 1: I mean just just round it up, round it up 508 00:27:29,240 --> 00:27:31,960 Speaker 1: like a rodeo. Yeah, it's a round up. Put on 509 00:27:32,000 --> 00:27:34,639 Speaker 1: the bus to slab City. All right, we got more 510 00:27:34,720 --> 00:27:37,680 Speaker 1: covered up, John and Ken KF I am six forty 511 00:27:37,840 --> 00:27:41,840 Speaker 1: live everywhere on the iHeartRadio app. Uh sorry, I just 512 00:27:41,840 --> 00:27:43,480 Speaker 1: looked at the picture that I can't get out of myself. 513 00:27:43,880 --> 00:27:47,119 Speaker 1: The Moist Line is returning tomorrow already, So if you 514 00:27:47,119 --> 00:27:49,800 Speaker 1: want to leave a message, you use the iHeartRadio app 515 00:27:49,840 --> 00:27:52,679 Speaker 1: as a microphone icon you can use in order to 516 00:27:52,760 --> 00:27:56,120 Speaker 1: connect to the Moist Line, and you can also call 517 00:27:56,160 --> 00:27:59,600 Speaker 1: the toll free number one eight seven seven Moist eighty 518 00:27:59,640 --> 00:28:04,560 Speaker 1: six one eight seven seven six six four seven eight 519 00:28:05,000 --> 00:28:07,960 Speaker 1: eight six. It's it's the mug shot of a guy 520 00:28:08,080 --> 00:28:11,960 Speaker 1: in Virginia. Oh this is oh my god, you have 521 00:28:11,960 --> 00:28:14,560 Speaker 1: to look John. It's a Fox News story West Virginia. 522 00:28:14,600 --> 00:28:18,520 Speaker 1: Man accused of kidnapping and burning woman with torch. And 523 00:28:19,320 --> 00:28:22,199 Speaker 1: you talk about crazy eyes. Oh is he the one 524 00:28:22,200 --> 00:28:25,720 Speaker 1: with the crossed eyes? Yeah, they're kind of looking inward. Yeah, 525 00:28:25,920 --> 00:28:28,600 Speaker 1: this guy's I saw this guy. Yeah, late yesterday. He's 526 00:28:28,640 --> 00:28:31,639 Speaker 1: got a huge beard, but he's got a completely, almost 527 00:28:31,680 --> 00:28:33,520 Speaker 1: completely bald head. In fact, he has like a little 528 00:28:33,520 --> 00:28:36,040 Speaker 1: cut on the front of his bald head that looks weird, 529 00:28:36,080 --> 00:28:38,880 Speaker 1: but it's a big zip. But yeah, the eyes and 530 00:28:39,320 --> 00:28:41,520 Speaker 1: between the eyes. His nose also has a chip off 531 00:28:41,520 --> 00:28:43,920 Speaker 1: of it. But his eyes are bugging out and they're 532 00:28:43,960 --> 00:28:47,120 Speaker 1: really creepy. I think he tried to do a pose 533 00:28:47,200 --> 00:28:53,080 Speaker 1: for the camera. Sammy Martz. They found the female victim 534 00:28:53,160 --> 00:28:57,720 Speaker 1: hiding underneath the Porch's just cold. Police. The suspect had 535 00:28:57,800 --> 00:29:00,760 Speaker 1: hit her in the face. She is escaped the residence 536 00:29:00,840 --> 00:29:03,200 Speaker 1: via the rear window and ran from the residence to hide. 537 00:29:03,520 --> 00:29:05,240 Speaker 1: He threatened to kill her and it burnt her with 538 00:29:05,280 --> 00:29:08,440 Speaker 1: a torch on her stomach and her leg. That's one 539 00:29:08,480 --> 00:29:11,960 Speaker 1: way to settle a domestic argument. That is one of 540 00:29:11,960 --> 00:29:15,360 Speaker 1: the most frightening faces you'll ever see. Oh, this is 541 00:29:15,360 --> 00:29:18,200 Speaker 1: a mugshot for all times. This makes Charles Manson looks sane. 542 00:29:18,560 --> 00:29:20,760 Speaker 1: That is kind of the comparison though, when Manson grew 543 00:29:20,800 --> 00:29:23,800 Speaker 1: the beard, and yeah, we got we got the picture 544 00:29:23,800 --> 00:29:25,520 Speaker 1: on Twitter, So go to the Johnny Ken Twitter and 545 00:29:25,600 --> 00:29:30,720 Speaker 1: you'll see it. Oh that was quick. What a lovely man. Oh, 546 00:29:30,760 --> 00:29:34,000 Speaker 1: he tortured her, struck her all over her body, sat 547 00:29:34,080 --> 00:29:36,880 Speaker 1: on her, and burnt her with a beautane torch. According 548 00:29:36,920 --> 00:29:40,120 Speaker 1: to the complaint, Well that's what happens when you mix 549 00:29:40,240 --> 00:29:42,280 Speaker 1: up at the wrong guy. Huh is this well he 550 00:29:42,440 --> 00:29:45,600 Speaker 1: has a girlfriend, was one of those dating app things? 551 00:29:45,720 --> 00:29:51,600 Speaker 1: Or it doesn't say what the connection was between them. 552 00:29:51,680 --> 00:29:57,360 Speaker 1: Did he break into the house or yeah? Um no, 553 00:29:57,680 --> 00:29:59,680 Speaker 1: it just says yeah. It just says she was being 554 00:29:59,680 --> 00:30:02,400 Speaker 1: treated by first responders. Marx was inside the residence and 555 00:30:02,480 --> 00:30:06,240 Speaker 1: possessed a gun. So oh, it is act. Did Admittie 556 00:30:06,280 --> 00:30:08,760 Speaker 1: did harm to the victim by striking and burning her? Yeah, 557 00:30:08,800 --> 00:30:12,160 Speaker 1: but one of the eyes is well they're both kind 558 00:30:12,160 --> 00:30:17,160 Speaker 1: of and they're pointing inward a bit. That's really creepy. 559 00:30:17,600 --> 00:30:22,960 Speaker 1: I get like that. Guess what happened on this date, 560 00:30:23,560 --> 00:30:28,160 Speaker 1: January twenty sixth, two thousand and nine. We take you 561 00:30:28,240 --> 00:30:32,080 Speaker 1: back on the John and Ken Show archives for an 562 00:30:32,080 --> 00:30:36,440 Speaker 1: event that was talked about for weeks, and particularly so 563 00:30:36,560 --> 00:30:41,200 Speaker 1: here in southern California because that's where this happened. No, 564 00:30:41,840 --> 00:30:44,840 Speaker 1: I know, I know, no, Oh no, okay, Eric shaking 565 00:30:44,840 --> 00:30:46,640 Speaker 1: his head that I'm going to be wrong, So never mind. Well, 566 00:30:46,680 --> 00:30:49,680 Speaker 1: go ahead, we just go ahead. I want to hear this. 567 00:30:49,800 --> 00:30:52,520 Speaker 1: I was going to say Kobe Bryant's death, not two 568 00:30:52,520 --> 00:30:54,680 Speaker 1: thousand and nine. Oh, I was saying three years ago. Okay, 569 00:30:54,720 --> 00:30:57,960 Speaker 1: I thought, oh, I thought you said three years ago, Steen, 570 00:30:58,160 --> 00:31:00,840 Speaker 1: fourteen years ago, two thousand. I need to take the 571 00:31:00,880 --> 00:31:03,040 Speaker 1: wax out of my ears. Sorry about that. What had 572 00:31:03,480 --> 00:31:10,200 Speaker 1: the birth of the octoplets? Nadya Suleiman? Remember we talked 573 00:31:10,200 --> 00:31:14,800 Speaker 1: about her because she gave birth on that date to 574 00:31:15,160 --> 00:31:18,680 Speaker 1: eight children, which was a record at the time. I 575 00:31:18,680 --> 00:31:21,280 Speaker 1: think it got surpassed. One case was kind of suspicious, 576 00:31:21,320 --> 00:31:22,760 Speaker 1: but I think there was somebody, a woman I had 577 00:31:22,840 --> 00:31:31,960 Speaker 1: nine Noah, Maliah, Isaiah, Naria, Jonah McKay, Josiah, and Jeremiah, 578 00:31:32,000 --> 00:31:34,400 Speaker 1: and there she put out a picture of them and 579 00:31:34,840 --> 00:31:38,280 Speaker 1: they're sitting on a couch and they're eating vegan donuts. 580 00:31:40,400 --> 00:31:45,280 Speaker 1: All all eight kids are vegans. They're vegans. So, yeah, 581 00:31:45,760 --> 00:31:50,400 Speaker 1: just another vegan story involving a whack job. Good thing. 582 00:31:50,400 --> 00:31:53,920 Speaker 1: I'm so normal. Something I noticed almost every day though, 583 00:31:54,240 --> 00:31:57,440 Speaker 1: there's there's like a vegan connection. I know. Well, that's 584 00:31:57,440 --> 00:31:59,320 Speaker 1: why you have me, so that at least there's one 585 00:31:59,400 --> 00:32:02,960 Speaker 1: normal vegan and right you imagine him birth eight kids 586 00:32:03,640 --> 00:32:14,000 Speaker 1: same time. No, hearty, you have no idea, oh gode, 587 00:32:15,680 --> 00:32:21,040 Speaker 1: uh yeah, exactly. So in looking at this picture. And 588 00:32:21,120 --> 00:32:23,840 Speaker 1: by the way, this story is inaccurate in some manner 589 00:32:23,920 --> 00:32:27,800 Speaker 1: because it's saying that they turned fourteen. Is my math wrong? 590 00:32:27,840 --> 00:32:29,760 Speaker 1: Or would that be two thousand and nine to twenty 591 00:32:29,840 --> 00:32:33,560 Speaker 1: twenty three? Right? Right, that would be. But then they're 592 00:32:33,600 --> 00:32:37,040 Speaker 1: saying in a picture Nadia Suliman very pregnant to twelve 593 00:32:37,160 --> 00:32:42,280 Speaker 1: two thousand and nine. It's impregnated artificially inseminated in two 594 00:32:42,320 --> 00:32:46,200 Speaker 1: thousand and nine. So something's not right, no well with them. 595 00:32:46,440 --> 00:32:49,760 Speaker 1: But maybe they're only turning thirteen. I don't know. But 596 00:32:50,320 --> 00:32:52,480 Speaker 1: the thing I noticed and looking at the picture, and 597 00:32:52,520 --> 00:32:55,240 Speaker 1: this has a lot to do with just how the 598 00:32:55,320 --> 00:33:00,160 Speaker 1: whole process of gestation and birth works. They don't look 599 00:33:00,280 --> 00:33:04,160 Speaker 1: the same age. They do somewhat look alike, but there's 600 00:33:04,200 --> 00:33:07,080 Speaker 1: a boy to the left who looks huge, and there 601 00:33:07,120 --> 00:33:08,560 Speaker 1: I don't know it's a boy or a girl in 602 00:33:08,560 --> 00:33:11,600 Speaker 1: the middle, and the couch who looks shrunken and maybe 603 00:33:11,640 --> 00:33:14,280 Speaker 1: eight years old. Did you see this picture? Yeah, I'm 604 00:33:14,280 --> 00:33:16,120 Speaker 1: looking at the picture, and you're right, they seem to 605 00:33:16,120 --> 00:33:19,040 Speaker 1: be all different sizes. Yeah, they could be like a 606 00:33:19,120 --> 00:33:21,960 Speaker 1: year or two years apart each. It's just because none 607 00:33:21,960 --> 00:33:24,239 Speaker 1: of them look like brothers and sisters to me. Oh, 608 00:33:24,280 --> 00:33:25,640 Speaker 1: you don't think so. I think the two boys to 609 00:33:25,680 --> 00:33:28,240 Speaker 1: the left could pass for it, and actually all four 610 00:33:28,360 --> 00:33:31,200 Speaker 1: to the left of the photo, but there were two 611 00:33:31,200 --> 00:33:33,280 Speaker 1: on the right. One looks sort of blunting, all right. Well, 612 00:33:33,320 --> 00:33:37,240 Speaker 1: who the insemination was that from? Oh and then there's 613 00:33:37,240 --> 00:33:39,200 Speaker 1: a taller girl in the back. She looks older too. 614 00:33:39,400 --> 00:33:43,240 Speaker 1: Was that was that from eight different men? Oh? You know, 615 00:33:43,400 --> 00:33:46,320 Speaker 1: I thought, he thought. I remember reading at the time 616 00:33:46,360 --> 00:33:49,160 Speaker 1: it was one donor. I don't think it was from 617 00:33:49,160 --> 00:33:51,400 Speaker 1: eight different men. Maybe they mixed up the vials. That 618 00:33:51,480 --> 00:33:57,240 Speaker 1: would be quite the insemination process, because basically, right, don't 619 00:33:57,240 --> 00:33:59,600 Speaker 1: you have an egg that splits into eight if they're 620 00:33:59,600 --> 00:34:05,640 Speaker 1: idad call otherwise different eggs? And you're right, she got implanted, 621 00:34:05,640 --> 00:34:07,240 Speaker 1: probably with a bunch of eggs to see what would 622 00:34:07,280 --> 00:34:10,439 Speaker 1: take right, right? Right? She had a whole garden in there. Yeah, 623 00:34:10,440 --> 00:34:13,240 Speaker 1: I forget how many I think. She eventually talked about 624 00:34:13,480 --> 00:34:16,879 Speaker 1: the many times she had tried this, well, and she 625 00:34:16,960 --> 00:34:19,520 Speaker 1: already has this time she hit the bonanza. Yeah, she 626 00:34:19,640 --> 00:34:23,920 Speaker 1: had six kids before the octoplets. Yeah she did. You're right, Yeah, 627 00:34:24,360 --> 00:34:27,440 Speaker 1: two is enough for me. I mentioned fourteen kids in 628 00:34:27,480 --> 00:34:30,160 Speaker 1: the house, and no wonder she was stripping and doing 629 00:34:30,200 --> 00:34:33,000 Speaker 1: porno for money. It's expensive to have kids. And no 630 00:34:33,080 --> 00:34:37,160 Speaker 1: guy who was going near that? I mean, you know, 631 00:34:37,400 --> 00:34:41,520 Speaker 1: you know, you know how you find a guy? Oh God, 632 00:34:41,560 --> 00:34:45,320 Speaker 1: don't go there, John, what's the data woman who was stripping, 633 00:34:45,680 --> 00:34:48,960 Speaker 1: doing porn and has fourteen kids at home? And that 634 00:34:49,080 --> 00:34:51,319 Speaker 1: is a tough match, tender match that up. I don't 635 00:34:51,320 --> 00:34:53,160 Speaker 1: know that that would be a tough well because it's 636 00:34:53,200 --> 00:34:55,359 Speaker 1: just a lot of responsibility you have to take on 637 00:34:55,520 --> 00:34:58,719 Speaker 1: right to help her. I guess that would be a 638 00:34:59,040 --> 00:35:00,719 Speaker 1: says they're doing well. Oh, I don't know how she 639 00:35:00,800 --> 00:35:03,319 Speaker 1: makes money these days. I haven't really kept up with 640 00:35:03,320 --> 00:35:05,640 Speaker 1: her life, but I don't want to know. We mentioned 641 00:35:05,680 --> 00:35:08,799 Speaker 1: her a few months ago, and uh, yeah, she's right. 642 00:35:08,880 --> 00:35:10,759 Speaker 1: She was doing everything that John mentioned. But then there 643 00:35:10,760 --> 00:35:12,920 Speaker 1: were books and stuff or I don't know, she's raising 644 00:35:12,960 --> 00:35:16,160 Speaker 1: a flock of vegans. They yeah, look at that. So 645 00:35:16,280 --> 00:35:18,560 Speaker 1: there you go, Deborah Mark more for your side, people 646 00:35:19,400 --> 00:35:21,919 Speaker 1: ate more for them? All right, more coming up, John 647 00:35:21,960 --> 00:35:23,640 Speaker 1: and ken KF. I am six forty