1 00:00:00,240 --> 00:00:04,680 Speaker 1: From UFOs to psychic powers and government conspiracies. History is 2 00:00:04,760 --> 00:00:09,080 Speaker 1: riddled with unexplained events. You can turn back now or 3 00:00:09,200 --> 00:00:12,079 Speaker 1: learn the stuff they don't want you to know. A 4 00:00:12,200 --> 00:00:25,439 Speaker 1: production of I Heart Radio. Hello, welcome back to the show. 5 00:00:25,480 --> 00:00:28,080 Speaker 1: My name is Matt, my name is Noel. They called 6 00:00:28,160 --> 00:00:30,680 Speaker 1: a Ben. We are joined as always with our super 7 00:00:30,720 --> 00:00:35,199 Speaker 1: producer Alexis code name dot Holiday Jackson. Most importantly, you 8 00:00:35,280 --> 00:00:38,199 Speaker 1: are you. You are here, and that makes this the 9 00:00:38,320 --> 00:00:41,920 Speaker 1: stuff they don't want you to know. It is Thursday. 10 00:00:41,960 --> 00:00:45,440 Speaker 1: If you're hearing this in linear time, if you practice 11 00:00:45,520 --> 00:00:47,800 Speaker 1: linear time and you're listening to this on the day 12 00:00:47,840 --> 00:00:50,280 Speaker 1: it comes out, and that means it is time for 13 00:00:50,440 --> 00:00:54,880 Speaker 1: our listener male segment. I want to start out today 14 00:00:55,240 --> 00:00:58,760 Speaker 1: by giving a no holds barred shout out to our 15 00:00:58,880 --> 00:01:03,240 Speaker 1: very own Matt Fred for going scorched earth on those voicemails. 16 00:01:03,400 --> 00:01:05,720 Speaker 1: We are, we are on top of it, and we 17 00:01:05,800 --> 00:01:11,400 Speaker 1: are digging up some fantastic, interesting, hilarious, disturbing stuff. Spoiler. 18 00:01:11,520 --> 00:01:14,320 Speaker 1: We may have a celebrity appearance at the end of 19 00:01:14,360 --> 00:01:17,080 Speaker 1: today's show. That will be up to you to decide. 20 00:01:17,200 --> 00:01:21,479 Speaker 1: But for now, we are learning about crime. We're learning 21 00:01:21,480 --> 00:01:26,560 Speaker 1: about heist we're learning about mysterious signals in Moscow, which 22 00:01:26,560 --> 00:01:29,680 Speaker 1: should be familiar to anybody who heard our recent episodes. 23 00:01:29,959 --> 00:01:33,639 Speaker 1: And then we're also going to take a deep dive 24 00:01:34,160 --> 00:01:38,440 Speaker 1: into the world of criminal justice and child protection, into 25 00:01:38,760 --> 00:01:42,560 Speaker 1: the bleeding edge of predictive analytics. But first, I think 26 00:01:42,600 --> 00:01:46,319 Speaker 1: it's fair to say all of us were very excited 27 00:01:46,600 --> 00:01:50,000 Speaker 1: when we received a correspondence about something that's very near 28 00:01:50,080 --> 00:01:55,080 Speaker 1: and dear to our hearts. Heist, good old fashioned robberies, 29 00:01:55,240 --> 00:01:57,560 Speaker 1: almost like something out of the Wild West. And I 30 00:01:57,600 --> 00:01:59,800 Speaker 1: don't want to be too glib about it, because this 31 00:02:00,080 --> 00:02:03,440 Speaker 1: is a serious thing. It is almost out of the 32 00:02:03,440 --> 00:02:06,760 Speaker 1: Wild West, but more like the the western world of 33 00:02:06,800 --> 00:02:10,919 Speaker 1: today and the times of covid Um. Amazon and any 34 00:02:11,000 --> 00:02:14,359 Speaker 1: kind of online shopping is obviously exploded, making some very 35 00:02:14,600 --> 00:02:18,360 Speaker 1: rich people even richer. Um. Well, other other people have 36 00:02:18,440 --> 00:02:21,359 Speaker 1: maybe not fared quite so well um during this uh, 37 00:02:21,520 --> 00:02:24,240 Speaker 1: this pandemic. Um. But I don't know if I'm kind 38 00:02:24,280 --> 00:02:27,000 Speaker 1: of just editorializing here, but it would seem that this 39 00:02:27,080 --> 00:02:31,359 Speaker 1: explosion in shipping has led to some opportunists kind of 40 00:02:31,400 --> 00:02:35,400 Speaker 1: finding their way into the picture and robbing train cars, 41 00:02:35,880 --> 00:02:37,840 Speaker 1: much more so than have been happening in the past 42 00:02:38,000 --> 00:02:44,080 Speaker 1: apparently since robberies of Union Pacific freight cars has gone 43 00:02:44,200 --> 00:02:49,200 Speaker 1: up by a whopping three hundred and fifty percent UM, 44 00:02:49,240 --> 00:02:53,520 Speaker 1: and it's apparently pretty easy. Like in downtown Los Angeles, 45 00:02:53,600 --> 00:02:57,160 Speaker 1: there are some train tracks that are very easily accessed, 46 00:02:57,280 --> 00:03:00,760 Speaker 1: you know by surface streets, and folks are waiting till 47 00:03:00,800 --> 00:03:04,240 Speaker 1: the trains are stopped, um, sometimes for long periods of time, 48 00:03:04,960 --> 00:03:07,360 Speaker 1: and jumping onto the back of them and cutting open 49 00:03:07,480 --> 00:03:10,080 Speaker 1: the big shipping containers like the kind you'd see stacked 50 00:03:10,160 --> 00:03:14,200 Speaker 1: you know on massive freight ships, UM and cutting the 51 00:03:14,200 --> 00:03:16,720 Speaker 1: locks with bolt cutters and having their way with the 52 00:03:16,760 --> 00:03:21,400 Speaker 1: contents UM. Typically looking for ones that are packed with 53 00:03:21,760 --> 00:03:26,320 Speaker 1: smaller items like Amazon packages or packages from Target or 54 00:03:26,360 --> 00:03:29,200 Speaker 1: FedEx or whatever. And what do they do. They go 55 00:03:29,280 --> 00:03:31,919 Speaker 1: through these packages, find the things that are the easiest 56 00:03:31,960 --> 00:03:36,920 Speaker 1: to carry and resell and throw everything else onto the tracks. UM. 57 00:03:36,960 --> 00:03:39,520 Speaker 1: There are several videos you can watch, you know, local 58 00:03:39,600 --> 00:03:42,840 Speaker 1: Los Angeles reporting on this that show, uh, the aftermath 59 00:03:42,920 --> 00:03:45,320 Speaker 1: of this, and it's it's insane. It just looks like 60 00:03:45,360 --> 00:03:49,960 Speaker 1: these train tracks are absolutely buried in garbage, UM, most 61 00:03:50,000 --> 00:03:52,440 Speaker 1: of which are these types of packages that we're talking about. 62 00:03:52,520 --> 00:03:56,400 Speaker 1: So I don't know It's hard to correlate directly, but 63 00:03:57,120 --> 00:04:00,760 Speaker 1: that rise in that period of time wouldn't be surprised 64 00:04:00,800 --> 00:04:03,480 Speaker 1: if it was in some way pandemic related in terms 65 00:04:03,480 --> 00:04:06,400 Speaker 1: of just the likelihood that they're going to find something 66 00:04:06,440 --> 00:04:08,440 Speaker 1: like that, you know, in one of these lines of 67 00:04:08,560 --> 00:04:13,400 Speaker 1: stopped cars. UM Union Pacific says that they are trying 68 00:04:13,400 --> 00:04:19,200 Speaker 1: to increase surveillance, UM and security. You know, that's pretty 69 00:04:19,320 --> 00:04:21,719 Speaker 1: new and developing stories, So I'm wondering what they can 70 00:04:21,720 --> 00:04:24,159 Speaker 1: Actually they're gonna start having like, you know, people on 71 00:04:24,240 --> 00:04:27,360 Speaker 1: horseback following the trains, like with you know, with six 72 00:04:27,440 --> 00:04:30,080 Speaker 1: guns or whatever. Like, I mean, I don't know what 73 00:04:30,120 --> 00:04:33,680 Speaker 1: the options are here, um, but it is very interesting. 74 00:04:33,920 --> 00:04:36,640 Speaker 1: Railroad bulls are a real thing. And of course I 75 00:04:36,680 --> 00:04:38,599 Speaker 1: did the dumb thing by launching in the story because 76 00:04:38,600 --> 00:04:40,320 Speaker 1: it was so fascinating and not mentioning that it came 77 00:04:40,400 --> 00:04:44,880 Speaker 1: from wonderful, amazing listener T Dog who wrote in with 78 00:04:44,960 --> 00:04:47,720 Speaker 1: this email essentially just a link to the story and 79 00:04:47,839 --> 00:04:50,520 Speaker 1: saying maybe more depressing and shocking rather than strange, but 80 00:04:50,560 --> 00:04:53,560 Speaker 1: I thought the story belongs with you. And the depressing part, 81 00:04:53,680 --> 00:04:57,000 Speaker 1: I mean, the littering alone is depressing, especially when you 82 00:04:57,000 --> 00:04:58,839 Speaker 1: look at it and see. It absolutely is just kind 83 00:04:58,839 --> 00:05:02,200 Speaker 1: of gross behavior. But some of the packages that are 84 00:05:02,200 --> 00:05:06,080 Speaker 1: getting discarded because the individual items are apparently not worth 85 00:05:06,440 --> 00:05:10,800 Speaker 1: the time of these thieves are COVID nineteen tests. There 86 00:05:10,800 --> 00:05:13,440 Speaker 1: are just, like, you know, hundreds of these getting thrown. 87 00:05:13,520 --> 00:05:15,279 Speaker 1: That doesn't make sense. I guess maybe because they'd have 88 00:05:15,360 --> 00:05:18,680 Speaker 1: to bring them in bulk and that's harder to do. Um, 89 00:05:18,720 --> 00:05:21,000 Speaker 1: But it seems like that's an item that's just being tossed, 90 00:05:21,400 --> 00:05:24,120 Speaker 1: obviously not getting to people who need them. Yeah, and 91 00:05:24,160 --> 00:05:28,000 Speaker 1: there's there's a larger context here to the tee dog. 92 00:05:28,040 --> 00:05:31,520 Speaker 1: I'm sure you're aware of this, but I think maybe 93 00:05:31,560 --> 00:05:33,680 Speaker 1: we have talked about it off air. I don't know 94 00:05:33,720 --> 00:05:36,960 Speaker 1: if we've approached this on air, but there is a 95 00:05:37,120 --> 00:05:42,120 Speaker 1: theft epidemic happening in the West Coast, specifically in San Francisco. 96 00:05:42,880 --> 00:05:46,799 Speaker 1: It's been called a shoplifters paradise now because thefts under 97 00:05:46,920 --> 00:05:52,080 Speaker 1: nine and fifty dollars are more or less in practice decriminalized. 98 00:05:52,240 --> 00:05:54,920 Speaker 1: Like that's why you'll see a lot of places that 99 00:05:54,960 --> 00:05:58,440 Speaker 1: have just closed entire stores. I think in San Francisco alone, 100 00:05:58,600 --> 00:06:03,680 Speaker 1: Walgreen's closed twin two stores. And most people aren't stealing 101 00:06:04,240 --> 00:06:07,280 Speaker 1: just for fun. They're stealing because they feel like they 102 00:06:07,360 --> 00:06:09,360 Speaker 1: need to do so, you know what I mean. I 103 00:06:09,400 --> 00:06:12,159 Speaker 1: think that's important to remember. And you made an excellent point, Noel, 104 00:06:12,440 --> 00:06:16,760 Speaker 1: about the the economic factors that are going in here. 105 00:06:16,760 --> 00:06:18,719 Speaker 1: I think it was most deaf who said some steal 106 00:06:18,720 --> 00:06:22,840 Speaker 1: for fun, but more steel to eat, you know. I mean, 107 00:06:22,839 --> 00:06:25,320 Speaker 1: I'm certainly like I used the word opportunists, and that's 108 00:06:25,320 --> 00:06:27,840 Speaker 1: certainly a part of it. Um. But I'm sure this 109 00:06:27,920 --> 00:06:31,119 Speaker 1: is something that's being done so that people can flip 110 00:06:31,160 --> 00:06:34,279 Speaker 1: some of these products and and eat um. You're right, though, Ben, 111 00:06:34,320 --> 00:06:35,960 Speaker 1: I didn't mention this, and it's a really good point. 112 00:06:36,240 --> 00:06:39,160 Speaker 1: One reason for the rise in these types of crimes 113 00:06:39,240 --> 00:06:42,359 Speaker 1: is the fact that some of these uh penalties have 114 00:06:42,480 --> 00:06:46,400 Speaker 1: been you know, significantly reduced um for like these types 115 00:06:46,400 --> 00:06:49,480 Speaker 1: of one off you know crimes um and and folks 116 00:06:49,480 --> 00:06:53,000 Speaker 1: are essentially just don't really care or there it's worth 117 00:06:53,080 --> 00:06:56,080 Speaker 1: It's much more worth risking it um, you know, for 118 00:06:56,120 --> 00:06:59,000 Speaker 1: the potential of like a big payoff. And didn't l 119 00:06:59,080 --> 00:07:02,000 Speaker 1: A p D also say that they're not going to 120 00:07:02,160 --> 00:07:07,480 Speaker 1: respond to robbery reports on trains unless the company unless 121 00:07:07,560 --> 00:07:12,960 Speaker 1: Union Pacific specifically asked them to Union Pacific specifically ask yeah, 122 00:07:13,000 --> 00:07:15,120 Speaker 1: we got that. Oh that is a mouthful. I'm not 123 00:07:15,200 --> 00:07:17,679 Speaker 1: quite sure about that, but I just know that because 124 00:07:17,720 --> 00:07:20,720 Speaker 1: of what you're talking about, the prosecution of misdemeanors has 125 00:07:20,760 --> 00:07:24,760 Speaker 1: been suspended uh in l A County, which is the 126 00:07:24,880 --> 00:07:27,960 Speaker 1: very reason that this exploded. So maybe my my COVID 127 00:07:28,000 --> 00:07:30,840 Speaker 1: theory is off the mark um, but it wouldn't surprise 128 00:07:30,880 --> 00:07:33,000 Speaker 1: me if there is a combination of the two. Wow, 129 00:07:33,600 --> 00:07:36,640 Speaker 1: just in reading that CBS Local article that was sent 130 00:07:36,640 --> 00:07:40,600 Speaker 1: to us, I imagine that the first thing Union Pacific 131 00:07:40,640 --> 00:07:46,280 Speaker 1: can do is kind of upgrade their lock system, because 132 00:07:46,400 --> 00:07:49,640 Speaker 1: I mean even CBS Local is saying that the locks 133 00:07:49,640 --> 00:07:53,600 Speaker 1: are easy to cut, and you know, I'm sure there's 134 00:07:53,640 --> 00:07:57,679 Speaker 1: ways around that, guys. Just victory. I love that victory 135 00:07:57,680 --> 00:08:01,160 Speaker 1: of the reporter, uh, you know, talk into a Union 136 00:08:01,200 --> 00:08:04,920 Speaker 1: Pacific rep in front of like, uh, in front of 137 00:08:05,120 --> 00:08:08,240 Speaker 1: a cargo container on a train and then say, no, 138 00:08:08,520 --> 00:08:10,200 Speaker 1: what kind of locks you have here? And then like 139 00:08:10,360 --> 00:08:12,880 Speaker 1: they reach into their pocket and pull out their lock 140 00:08:12,960 --> 00:08:16,800 Speaker 1: pick and they just don't ever point out that it's 141 00:08:16,840 --> 00:08:20,119 Speaker 1: weird for them to have one. Yeah. Well, and another 142 00:08:20,120 --> 00:08:22,400 Speaker 1: thing to consider too, it's just how this could potentially 143 00:08:22,400 --> 00:08:26,040 Speaker 1: affect l a county's supply chain. Um, because a lot 144 00:08:26,040 --> 00:08:28,960 Speaker 1: of stuff is coming into the system through these rail cars. Um. 145 00:08:29,320 --> 00:08:32,360 Speaker 1: The l A is one of the largest receivers of 146 00:08:32,520 --> 00:08:35,679 Speaker 1: these types of goods in the entire country. So uh, 147 00:08:35,720 --> 00:08:39,280 Speaker 1: there could big picture be more to be worried about 148 00:08:39,320 --> 00:08:42,120 Speaker 1: than just a few people losing their Amazon packages. Um. 149 00:08:42,160 --> 00:08:45,080 Speaker 1: They estimated, or at least the carrier estimated that the 150 00:08:45,240 --> 00:08:49,200 Speaker 1: damages from these types of thefts amount of two around 151 00:08:49,240 --> 00:08:52,400 Speaker 1: five million dollars. But they said that it doesn't include 152 00:08:52,520 --> 00:08:57,160 Speaker 1: losses to their customers, um in terms of like the 153 00:08:57,440 --> 00:09:00,439 Speaker 1: customers of the of the rail line um or are uh. 154 00:09:00,480 --> 00:09:03,440 Speaker 1: They said impact on Union Pacifics operations in the entire 155 00:09:03,480 --> 00:09:06,800 Speaker 1: Los Angeles County supply chain. Uh and that was reported 156 00:09:07,160 --> 00:09:10,520 Speaker 1: on in d TV. Yeah. I mean unless you beef 157 00:09:10,600 --> 00:09:14,720 Speaker 1: up security around specific areas, which then you know, if 158 00:09:14,720 --> 00:09:17,840 Speaker 1: you're looking to score on the contents of these containers, 159 00:09:17,880 --> 00:09:20,200 Speaker 1: then you could just move to a different place, right. 160 00:09:20,600 --> 00:09:24,080 Speaker 1: Uh if you if you bolster security in one area, 161 00:09:24,120 --> 00:09:26,600 Speaker 1: you could just go to another. Uh. You could also 162 00:09:26,679 --> 00:09:34,559 Speaker 1: like have security teams attached to these not horseback in 163 00:09:34,640 --> 00:09:39,959 Speaker 1: six guns. Right. Um. Well, you're right though, I mean 164 00:09:40,000 --> 00:09:42,200 Speaker 1: the fact that this is an open area that's like 165 00:09:42,240 --> 00:09:44,280 Speaker 1: easily accessible. But then you gotta wonder, like is it 166 00:09:44,360 --> 00:09:48,320 Speaker 1: a matter of just traffic, you know, like maybe it's 167 00:09:48,360 --> 00:09:50,360 Speaker 1: harder for them to change up, you know, where the 168 00:09:50,400 --> 00:09:52,680 Speaker 1: train stops because of you know, the way the train 169 00:09:52,760 --> 00:09:54,360 Speaker 1: they have to like change the whole schedule of the 170 00:09:54,360 --> 00:09:56,640 Speaker 1: way the trains run or something. But that's you're right, 171 00:09:56,679 --> 00:09:59,040 Speaker 1: there's got to be something, even if it involves overhauling 172 00:09:59,080 --> 00:10:01,480 Speaker 1: their system, because I guess it's it's easy to forget 173 00:10:01,559 --> 00:10:05,559 Speaker 1: sometimes how antiquated these rail lines are. You know, it's 174 00:10:05,640 --> 00:10:07,880 Speaker 1: old infrastructure that still is kind of the best game 175 00:10:07,880 --> 00:10:10,240 Speaker 1: in talent for this type of shipping. So there's somewhat 176 00:10:10,280 --> 00:10:12,160 Speaker 1: limited in some ways as to what they can do. 177 00:10:12,960 --> 00:10:17,000 Speaker 1: And also we should say the quiet part out loud here. Uh. 178 00:10:17,040 --> 00:10:19,959 Speaker 1: There there is a virtual certainty that there are a 179 00:10:20,000 --> 00:10:23,360 Speaker 1: lot of individual actors here. But I would argue there's 180 00:10:23,480 --> 00:10:27,000 Speaker 1: more of a certainty that these are organized These are 181 00:10:27,000 --> 00:10:30,760 Speaker 1: acts of organized crime, because the opportunity is there, and 182 00:10:30,800 --> 00:10:34,040 Speaker 1: then you can use you know, the power of numbers. 183 00:10:34,480 --> 00:10:37,240 Speaker 1: If you look at the videos that have that pop 184 00:10:37,320 --> 00:10:40,120 Speaker 1: up in the news reporting this, you'll see that it's 185 00:10:40,520 --> 00:10:44,360 Speaker 1: not a small amount of stuff getting boosted. They are 186 00:10:44,480 --> 00:10:48,520 Speaker 1: racking hundreds of cars, hundreds of cargo containers. Rather now, 187 00:10:48,600 --> 00:10:50,080 Speaker 1: it's it's a great point, Bat, I mean, it does 188 00:10:50,120 --> 00:10:52,120 Speaker 1: feel more like a ring of some kind, you know, 189 00:10:52,240 --> 00:10:55,240 Speaker 1: with cooperation and good timing and some sort of central 190 00:10:55,320 --> 00:10:58,760 Speaker 1: leadership rather than just you know, individuals that are just 191 00:10:58,800 --> 00:11:03,240 Speaker 1: like coming and exploiting this situation. It's a really good 192 00:11:03,240 --> 00:11:04,680 Speaker 1: point because again, I mean you look at some of 193 00:11:04,679 --> 00:11:07,280 Speaker 1: the images like on this Indie TV article. I mean 194 00:11:07,400 --> 00:11:10,160 Speaker 1: that's the it's it's it's from left to right as 195 00:11:10,200 --> 00:11:12,840 Speaker 1: far as the eye can see in the frame, you know, 196 00:11:13,200 --> 00:11:16,640 Speaker 1: this trash it just kind of goes on and on. Um. 197 00:11:16,679 --> 00:11:20,600 Speaker 1: It is an absolute pile. So something to follow. Um. 198 00:11:20,640 --> 00:11:23,959 Speaker 1: I hope they figure it out. But it's definitely an 199 00:11:23,960 --> 00:11:28,040 Speaker 1: odd situation. And maybe it's a matter of l A 200 00:11:28,120 --> 00:11:31,240 Speaker 1: county working with the uh you know, the train line 201 00:11:31,240 --> 00:11:34,439 Speaker 1: to make these crimes more prosecutable. But then to your 202 00:11:34,440 --> 00:11:37,040 Speaker 1: point Ben about the you know, the overload in their 203 00:11:37,160 --> 00:11:39,920 Speaker 1: judicial system, I mean, it could be just not a 204 00:11:40,000 --> 00:11:42,360 Speaker 1: huge priority for them. Um. And at the end of 205 00:11:42,400 --> 00:11:45,680 Speaker 1: the day, unless there's a real impact you know, the 206 00:11:45,720 --> 00:11:50,280 Speaker 1: supply chain and infrastructure, probably something that's just gonna be 207 00:11:50,280 --> 00:11:53,679 Speaker 1: dealt with in insurance claims. So thank you t Dog 208 00:11:53,840 --> 00:11:56,200 Speaker 1: for that tip on that story and something. We're gonna 209 00:11:56,240 --> 00:11:58,120 Speaker 1: keep an eye on the meantime, we're gonna take a 210 00:11:58,200 --> 00:12:07,319 Speaker 1: break and then we'll be back with more snermail. All right, 211 00:12:07,400 --> 00:12:09,720 Speaker 1: we are back and we will be jumping to the 212 00:12:09,720 --> 00:12:13,840 Speaker 1: phone lines. Uh quit. Couple of notes here, guys. Got 213 00:12:13,840 --> 00:12:17,280 Speaker 1: a message from Michael on the case very recently who 214 00:12:17,360 --> 00:12:21,880 Speaker 1: asked us to look into the business plot. I saw that. Yes, yes, 215 00:12:23,040 --> 00:12:26,240 Speaker 1: oh Michael, I I cannot remember if I if I 216 00:12:26,280 --> 00:12:29,120 Speaker 1: had replied, But let's do it on air just really quickly. 217 00:12:29,640 --> 00:12:33,360 Speaker 1: You are in for a treat. A spoiler alert. We 218 00:12:33,440 --> 00:12:38,120 Speaker 1: have a special interview that oh time is funny archive 219 00:12:38,200 --> 00:12:42,840 Speaker 1: A one. Uh it may be out now, I think, yeah, 220 00:12:42,960 --> 00:12:45,840 Speaker 1: but we do check it out. We speak in depth 221 00:12:45,960 --> 00:12:50,480 Speaker 1: with the world's foremost living expert on the business plot, 222 00:12:50,520 --> 00:12:53,160 Speaker 1: at least the foremost expert who is willing to speak 223 00:12:53,160 --> 00:12:56,360 Speaker 1: about it publicly. So stay tuned to that. And we 224 00:12:56,440 --> 00:13:01,960 Speaker 1: have a another secret pride jecked on the way in 225 00:13:02,280 --> 00:13:04,440 Speaker 1: in a few months that might be of interest to you. 226 00:13:04,520 --> 00:13:07,440 Speaker 1: But yeah, business plot. The timing on that was uncanny, 227 00:13:07,640 --> 00:13:10,040 Speaker 1: wasn't it. It was perfect because I think it was 228 00:13:10,160 --> 00:13:12,439 Speaker 1: just as we were recording the episode is when markin 229 00:13:13,200 --> 00:13:18,560 Speaker 1: us uh and and just one of the shout out guys, 230 00:13:18,559 --> 00:13:21,360 Speaker 1: some anonymous so and so let us know about a 231 00:13:21,400 --> 00:13:25,800 Speaker 1: show called Lex. It was called Lex I Worship His Shadow. 232 00:13:26,760 --> 00:13:28,760 Speaker 1: I had never heard of it. I ended up watching 233 00:13:28,760 --> 00:13:33,320 Speaker 1: the pilot episode. One of the strangest nineties sci fi 234 00:13:33,480 --> 00:13:36,880 Speaker 1: shows I've ever seen. The reason why this anonymous person 235 00:13:36,960 --> 00:13:38,800 Speaker 1: sent it to us because it has some kind of 236 00:13:38,840 --> 00:13:45,960 Speaker 1: AI like judicial system within it. But anyway, yeah, Lex 237 00:13:46,000 --> 00:13:49,600 Speaker 1: with two X is it's just a weird show, probably 238 00:13:49,600 --> 00:13:52,319 Speaker 1: not worth your time, but a weird little relic to 239 00:13:52,880 --> 00:13:55,200 Speaker 1: jump into, all right, but we did. We had so 240 00:13:55,200 --> 00:13:57,880 Speaker 1: many great messages. I want to jump to someone who 241 00:13:57,920 --> 00:14:02,000 Speaker 1: called in named Yah Yah guys. UM, so my name 242 00:14:02,000 --> 00:14:05,319 Speaker 1: is Yah Yeah, not actually, but you can call me that. UM. 243 00:14:05,640 --> 00:14:09,760 Speaker 1: I work in healthcare and UM just been listening to 244 00:14:10,679 --> 00:14:15,920 Speaker 1: you know, the Havannah episode. UM. The thing that seems 245 00:14:15,960 --> 00:14:17,760 Speaker 1: to be income and is it like a lot of 246 00:14:17,800 --> 00:14:20,040 Speaker 1: the symptoms that you described are are kind of like 247 00:14:20,080 --> 00:14:26,960 Speaker 1: symptoms of neuroinflammation. UM. And it makes me question whether 248 00:14:27,040 --> 00:14:32,280 Speaker 1: this grouping of people have like, uh, medications that they 249 00:14:32,320 --> 00:14:35,920 Speaker 1: have to take UM, whether it be vaccines or some 250 00:14:36,000 --> 00:14:40,560 Speaker 1: sort of like preventative malaria medication something for travel. Like 251 00:14:40,600 --> 00:14:44,480 Speaker 1: a lot of people within the government and UM, in 252 00:14:44,560 --> 00:14:48,720 Speaker 1: the intelligence agencies and diplomats and stuff, UM end up 253 00:14:48,720 --> 00:14:54,680 Speaker 1: getting like extra UM extra vaccines and like malaria medication 254 00:14:54,760 --> 00:14:59,440 Speaker 1: and stuff that uh, your ordinary citizen wouldn't be taking UM. 255 00:14:59,560 --> 00:15:02,800 Speaker 1: And it makes me question if maybe there's something going 256 00:15:02,880 --> 00:15:05,880 Speaker 1: on that they I don't know, maybe there are people 257 00:15:05,880 --> 00:15:08,360 Speaker 1: that are like not tolerating that. Not to sound like 258 00:15:08,680 --> 00:15:10,960 Speaker 1: a wild anti VAXX or anything like that, I'm not, 259 00:15:11,000 --> 00:15:15,040 Speaker 1: I promise, but UM just just curious because again, what 260 00:15:15,040 --> 00:15:17,960 Speaker 1: what would the groups of people have in come And 261 00:15:17,960 --> 00:15:21,320 Speaker 1: and again a lot of these symptoms sound very similar 262 00:15:21,320 --> 00:15:23,520 Speaker 1: to things you would find in somebody who's dealing with 263 00:15:24,240 --> 00:15:28,520 Speaker 1: UM something affecting their nervous system, obviously the brain specifically. 264 00:15:29,040 --> 00:15:34,000 Speaker 1: All right, well, thanks for keeping it objective and interesting UM, 265 00:15:34,120 --> 00:15:38,080 Speaker 1: and for all the entertainment. Thanks by neural neural inflammation. 266 00:15:38,120 --> 00:15:41,120 Speaker 1: Why didn't we think of that? Right? It didn't jump 267 00:15:41,120 --> 00:15:43,920 Speaker 1: into my mind at all when we were creating that episode. 268 00:15:44,560 --> 00:15:48,240 Speaker 1: And Guya makes a great point that when you know 269 00:15:48,280 --> 00:15:52,520 Speaker 1: when you're traveling abroad, maybe you've experienced this to a 270 00:15:52,520 --> 00:15:56,480 Speaker 1: certain area where there's a prevalent disease or a prevalent 271 00:15:56,520 --> 00:16:00,720 Speaker 1: sickness and illness that you just that you or immune 272 00:16:00,720 --> 00:16:03,920 Speaker 1: system hasn't dealt with because of where you've lived for 273 00:16:04,080 --> 00:16:06,920 Speaker 1: most of your life, you will have to get extra medications, 274 00:16:06,960 --> 00:16:10,680 Speaker 1: a certain vaccine or something like that. Um, it only 275 00:16:10,720 --> 00:16:14,680 Speaker 1: makes sense that diplomats functioning in another another country, let's say, 276 00:16:14,880 --> 00:16:17,680 Speaker 1: like a Caribbean country like Cuba, may have to get 277 00:16:17,840 --> 00:16:22,240 Speaker 1: specific other, you know, medications. I can totally see the 278 00:16:22,320 --> 00:16:25,600 Speaker 1: reasoning there, right, because that is we know that is 279 00:16:25,640 --> 00:16:29,400 Speaker 1: something that is true. Service members who function in you know, 280 00:16:29,440 --> 00:16:32,960 Speaker 1: every arm of the military have to get extra vaccines, 281 00:16:33,080 --> 00:16:39,560 Speaker 1: take extra medications to fight locally specific diseases. UM. It 282 00:16:39,760 --> 00:16:41,840 Speaker 1: may for me, I don't know what you guys think. 283 00:16:41,880 --> 00:16:44,680 Speaker 1: It may work for one location. But when you see 284 00:16:44,800 --> 00:16:48,680 Speaker 1: the symptoms of havana syndrome, you know, affecting people who 285 00:16:48,680 --> 00:16:51,640 Speaker 1: have been all over the world stationed in different places, 286 00:16:51,800 --> 00:16:55,360 Speaker 1: it makes me think maybe it's not that, or maybe 287 00:16:55,360 --> 00:17:01,120 Speaker 1: it's something specific to you know, diplomatic personnel general not 288 00:17:01,120 --> 00:17:04,439 Speaker 1: not depending on where they're traveling to. So multiple So 289 00:17:04,560 --> 00:17:08,360 Speaker 1: it could be one of multiple possible causes, So we're 290 00:17:08,400 --> 00:17:10,360 Speaker 1: not saying it would be the entire thing. I mean, 291 00:17:10,400 --> 00:17:14,399 Speaker 1: that makes sense to me. Anybody who has traveled in 292 00:17:14,800 --> 00:17:18,960 Speaker 1: uh governmental or even in geocapacity is well aware of 293 00:17:19,160 --> 00:17:21,160 Speaker 1: how much stuff you have to get shot up with. 294 00:17:21,600 --> 00:17:25,399 Speaker 1: But the other, the other point I think that we 295 00:17:25,440 --> 00:17:29,840 Speaker 1: need to raise here, yahya, is the question of familiarity 296 00:17:30,000 --> 00:17:34,080 Speaker 1: with medication or dose. Like the people in the State 297 00:17:34,080 --> 00:17:36,879 Speaker 1: Department are not getting shot up with some kind of 298 00:17:36,920 --> 00:17:43,000 Speaker 1: bleeding edge experimental drugs. Right, the the possible side effects, 299 00:17:43,560 --> 00:17:47,880 Speaker 1: the efficacy, all that stuff has been extensively researched. So 300 00:17:47,960 --> 00:17:51,639 Speaker 1: that would mean if there were a medication that was 301 00:17:51,800 --> 00:17:55,720 Speaker 1: common that was causing these effects or these symptoms in 302 00:17:56,000 --> 00:17:59,680 Speaker 1: uh An a sizeable amount of people, then for that 303 00:17:59,800 --> 00:18:04,440 Speaker 1: not to be reported would would imply a cover up, right, 304 00:18:04,480 --> 00:18:08,440 Speaker 1: which is exciting. I'm just logically walking through this um. 305 00:18:08,520 --> 00:18:11,159 Speaker 1: But but it is possible that it could be at 306 00:18:11,240 --> 00:18:15,160 Speaker 1: least in some cases a cause. Referencing again those controversial 307 00:18:15,160 --> 00:18:19,960 Speaker 1: studies from and twenty nineteen that did that did appear 308 00:18:20,000 --> 00:18:25,200 Speaker 1: to find physical alterations to people's to people's brains. Again, 309 00:18:25,680 --> 00:18:27,960 Speaker 1: you know, there are a bunch of scientists who disagree 310 00:18:27,960 --> 00:18:31,040 Speaker 1: with those findings, the jury is still sort of outs. 311 00:18:32,000 --> 00:18:33,879 Speaker 1: I'm just very happy that you are called in with 312 00:18:33,920 --> 00:18:37,199 Speaker 1: this possibility so that I could even so that we 313 00:18:37,240 --> 00:18:40,520 Speaker 1: could even like ponder it. Uh. And we're certainly has 314 00:18:40,560 --> 00:18:42,560 Speaker 1: been you said. We're certainly not saying that this is 315 00:18:42,560 --> 00:18:46,280 Speaker 1: the cause or the only cause, or any cause for 316 00:18:46,440 --> 00:18:50,399 Speaker 1: the Havana syndrome symptoms. It's just something to to think about. 317 00:18:51,080 --> 00:18:53,639 Speaker 1: Um Wow. Well, hey, guys, if you're up, if you're 318 00:18:53,720 --> 00:18:56,960 Speaker 1: up for I've got another message from somebody about the 319 00:18:57,000 --> 00:19:03,600 Speaker 1: Havana syndrome episode. Okay, And then here's a message from Gumby. Yes, 320 00:19:03,760 --> 00:19:06,520 Speaker 1: my name is Gumby. I'm just letting you know that 321 00:19:06,560 --> 00:19:10,400 Speaker 1: I was listening to your podcast just recently about the 322 00:19:10,400 --> 00:19:14,600 Speaker 1: the Moscow UH incident stuff. I was a young marine 323 00:19:14,640 --> 00:19:19,200 Speaker 1: back in four station in Moscow. I knew Clayton lone Tree, 324 00:19:19,240 --> 00:19:22,640 Speaker 1: the one with the espionage of the sex of secrets. 325 00:19:22,680 --> 00:19:25,240 Speaker 1: I know him for six months while I was stationed 326 00:19:25,240 --> 00:19:30,320 Speaker 1: in Moscow. Um. Also during that time, I would always 327 00:19:30,720 --> 00:19:33,919 Speaker 1: see over my detachment commander's office. He would have a 328 00:19:34,000 --> 00:19:36,840 Speaker 1: hot dog in the window and underneath there was little 329 00:19:36,960 --> 00:19:40,399 Speaker 1: note saying I would like it well done, please and 330 00:19:40,440 --> 00:19:42,639 Speaker 1: I would ask him what before why he had that 331 00:19:42,760 --> 00:19:44,960 Speaker 1: up there, and he said it was because the microwaves 332 00:19:45,000 --> 00:19:47,720 Speaker 1: that would come in to listen to us while we 333 00:19:47,760 --> 00:19:51,760 Speaker 1: were in the embassy's um. And every once in a 334 00:19:51,840 --> 00:19:54,800 Speaker 1: while I was here, noises, you know, like a hype. 335 00:19:54,880 --> 00:19:57,879 Speaker 1: It's sound in my hear, you know, in my head, 336 00:19:58,760 --> 00:20:02,080 Speaker 1: and it would be so severe that it would be 337 00:20:02,119 --> 00:20:04,200 Speaker 1: a headache and that and I would hear whispering. That's 338 00:20:04,240 --> 00:20:08,639 Speaker 1: that I was losing my mind. But that's that's basically 339 00:20:08,680 --> 00:20:10,840 Speaker 1: what happened to us after in Russia. And it was 340 00:20:10,880 --> 00:20:14,199 Speaker 1: an interesting thing, you know, for a young marine. I 341 00:20:14,280 --> 00:20:16,760 Speaker 1: was only twenty years old, turned one while I was 342 00:20:16,760 --> 00:20:21,960 Speaker 1: out there, and it was interesting. Keep up the good work, guys. 343 00:20:22,240 --> 00:20:27,800 Speaker 1: I enjoy listening to you. Uh. Some of these messages 344 00:20:27,840 --> 00:20:31,080 Speaker 1: we get, guys, like like this one from Gumby the 345 00:20:31,240 --> 00:20:35,480 Speaker 1: first person experience of the Moscow signal at the time 346 00:20:35,480 --> 00:20:37,760 Speaker 1: when it was active, or at least it was believed 347 00:20:37,760 --> 00:20:41,520 Speaker 1: to be active. Uh No, they did that. I know, 348 00:20:41,640 --> 00:20:47,439 Speaker 1: I know they can't say. I'm pretty sure, but wow, 349 00:20:47,480 --> 00:20:50,200 Speaker 1: thank you so much, sir for calling in and telling 350 00:20:50,240 --> 00:20:53,960 Speaker 1: us that story. The idea of your detachment Commander's hot 351 00:20:54,000 --> 00:21:00,040 Speaker 1: dog by the window. Hilarious. I love it. I of 352 00:21:00,119 --> 00:21:05,679 Speaker 1: my hot dogs, medium, rare person um. But but just 353 00:21:05,800 --> 00:21:11,560 Speaker 1: knowing that you had auditory effects from something that was 354 00:21:11,600 --> 00:21:13,960 Speaker 1: going on while you were there, Right, you're saying that 355 00:21:14,000 --> 00:21:16,520 Speaker 1: you heard high pitched noise in your head that would 356 00:21:16,520 --> 00:21:19,320 Speaker 1: give you a headache. You're having effects of you know, 357 00:21:20,080 --> 00:21:22,880 Speaker 1: it sounded like you were hearing whispering, which that's got 358 00:21:22,880 --> 00:21:28,399 Speaker 1: to be an unsettling experience, right, Oh god, Okay, nope, nope, 359 00:21:29,119 --> 00:21:32,480 Speaker 1: too close to home. Yeah, we put that in there. 360 00:21:32,600 --> 00:21:36,240 Speaker 1: If you heard some sorceress there, that was us. But yeah, 361 00:21:36,320 --> 00:21:39,440 Speaker 1: it's I mean, it is startling too, especially if you're 362 00:21:39,440 --> 00:21:44,800 Speaker 1: talking about tradecraft or surveillance, because even the people who 363 00:21:44,840 --> 00:21:48,560 Speaker 1: are supposed to be protecting you in your role as 364 00:21:48,600 --> 00:21:51,600 Speaker 1: a deployed marine may not be at liberty to tell 365 00:21:51,640 --> 00:21:56,120 Speaker 1: you what's actually happening. Right Uh And that's you know, unfortunately, 366 00:21:56,160 --> 00:21:58,479 Speaker 1: that's a tale as old as time. You can go 367 00:21:58,560 --> 00:22:02,000 Speaker 1: back on forth on how necessary that is, how mission 368 00:22:02,040 --> 00:22:04,800 Speaker 1: critical that kind of secrecy is. But when it gets 369 00:22:04,880 --> 00:22:09,080 Speaker 1: to the point where people are experiencing unexplained, damaging things 370 00:22:09,480 --> 00:22:14,120 Speaker 1: happening to their bodies, uh, I feel like that's ethically 371 00:22:14,320 --> 00:22:17,800 Speaker 1: unsound to deny them that knowledge. And you see that 372 00:22:17,960 --> 00:22:21,520 Speaker 1: with stories about exposure to depleted uranium. You see that 373 00:22:21,880 --> 00:22:25,960 Speaker 1: with the long tragic saga of agent Orange. These stories 374 00:22:26,440 --> 00:22:30,480 Speaker 1: continue today, and sometimes the argument of a greater good 375 00:22:31,000 --> 00:22:34,800 Speaker 1: or needs no basis don't really hold water, because right now, 376 00:22:35,200 --> 00:22:37,440 Speaker 1: no matter how rich or poor you are, you get 377 00:22:37,560 --> 00:22:41,600 Speaker 1: one body that might change, might change later, but for 378 00:22:41,720 --> 00:22:45,480 Speaker 1: right now, the body you have is the only one 379 00:22:45,560 --> 00:22:49,359 Speaker 1: you get to keep. So uh so, I I can 380 00:22:49,400 --> 00:22:53,240 Speaker 1: totally understand being very defensive or feeling left out in 381 00:22:53,280 --> 00:22:57,040 Speaker 1: the cold, as they used to say, uh by this 382 00:22:57,160 --> 00:22:59,400 Speaker 1: kind of surveillance stuff, if it has we can talk 383 00:22:59,440 --> 00:23:02,600 Speaker 1: about the v A two, which I think, uh gumby 384 00:23:02,840 --> 00:23:05,720 Speaker 1: you would be very certainly will have opinions on as well. 385 00:23:05,760 --> 00:23:09,400 Speaker 1: Like the v A is has been known for turning 386 00:23:09,440 --> 00:23:14,400 Speaker 1: down legitimate medical grievances. And if there is not an 387 00:23:14,400 --> 00:23:20,840 Speaker 1: official cause or official explanation, official attribution for whatever you 388 00:23:20,880 --> 00:23:24,280 Speaker 1: may be experiencing medical condition or disability, then the v 389 00:23:24,440 --> 00:23:28,000 Speaker 1: A is quite adept at denying coverage. And I just 390 00:23:28,200 --> 00:23:31,720 Speaker 1: I don't have words for how unjust that is. Sorry, 391 00:23:31,720 --> 00:23:34,560 Speaker 1: that's a tangent, but it's an important one. I'd argue 392 00:23:33,920 --> 00:23:37,600 Speaker 1: it is. I'm going to jump really quickly to something 393 00:23:37,640 --> 00:23:42,640 Speaker 1: that Gumby mentioned. He said he knows or new maybe 394 00:23:42,800 --> 00:23:48,359 Speaker 1: Clayton Loan Tree, who was a marine and Soviet double agent. Uh. 395 00:23:48,960 --> 00:23:53,360 Speaker 1: I believe we mentioned him in that episode. Maybe we didn't. 396 00:23:53,400 --> 00:23:57,879 Speaker 1: Maybe we like kind of referenced him. Oh, we've referenced him. 397 00:23:57,920 --> 00:24:00,560 Speaker 1: I think in a previous Listener Male episode where someone 398 00:24:00,640 --> 00:24:03,399 Speaker 1: called in speaking about that. Yeah, he was. He was 399 00:24:03,440 --> 00:24:07,080 Speaker 1: mentioned previously when Jim called in with those stories. I 400 00:24:07,119 --> 00:24:09,840 Speaker 1: don't think we actually said his name though, Clayton Loan Tree. 401 00:24:10,240 --> 00:24:15,920 Speaker 1: But wow, apparently Gumby knew him. Uh, and he did 402 00:24:16,000 --> 00:24:21,440 Speaker 1: get released from lock up, I think in Uh. He 403 00:24:21,600 --> 00:24:24,920 Speaker 1: also later went on he's still alive today Loan Tree, 404 00:24:25,000 --> 00:24:28,560 Speaker 1: and she went on to be an expert witness in 405 00:24:28,600 --> 00:24:32,840 Speaker 1: the cases against other people accused of spying for the KGB. 406 00:24:33,359 --> 00:24:36,720 Speaker 1: I don't want to say anything else. You don't want 407 00:24:36,720 --> 00:24:41,120 Speaker 1: to make a honey pot statement. Okay, alright to ten rule. 408 00:24:43,640 --> 00:24:47,120 Speaker 1: Oh Man, Well, thank you again, Gumby, thank you yah 409 00:24:47,200 --> 00:24:50,480 Speaker 1: ya for sending us those great messages. If you've got 410 00:24:50,560 --> 00:24:52,720 Speaker 1: you know, experience with anything like this, we want to 411 00:24:52,720 --> 00:24:55,280 Speaker 1: hear from you. Two. If you're listening to this right 412 00:24:55,280 --> 00:24:57,679 Speaker 1: now and thinking about calling in, we highly encourage you 413 00:24:57,800 --> 00:25:00,320 Speaker 1: to do so. No matter what you want to talk about, 414 00:25:00,520 --> 00:25:02,800 Speaker 1: we want to hear from you. So we're gonna take 415 00:25:02,840 --> 00:25:06,360 Speaker 1: a quick break and come back with more messages from you. 416 00:25:13,000 --> 00:25:16,760 Speaker 1: And we've returned, we're going to we're going to go 417 00:25:16,800 --> 00:25:21,240 Speaker 1: into something um dark but important, and then we're going 418 00:25:21,320 --> 00:25:24,320 Speaker 1: to try to bring bring the mood up maybe just 419 00:25:24,400 --> 00:25:29,120 Speaker 1: a little bit, with that possible celebrity appearance we teased earlier, 420 00:25:29,640 --> 00:25:34,000 Speaker 1: So stick with us. We received an excellent piece of correspondence. 421 00:25:34,040 --> 00:25:37,080 Speaker 1: We had a lot of correspondence actually with some of 422 00:25:37,119 --> 00:25:41,960 Speaker 1: our conversation about the juvenile justice system, of our conversation 423 00:25:42,000 --> 00:25:46,040 Speaker 1: about incarceration, some of our conversation about the foster care system, 424 00:25:46,119 --> 00:25:47,760 Speaker 1: and there is going to be a full episode of 425 00:25:47,760 --> 00:25:50,760 Speaker 1: that on the way, but for now, we want to 426 00:25:50,840 --> 00:25:56,480 Speaker 1: extend a heartfelt thanks to one of our fellow conspiracy realists, who, 427 00:25:56,760 --> 00:25:59,840 Speaker 1: due to the nature of the information they've conveyed, must 428 00:26:00,040 --> 00:26:03,560 Speaker 1: main anonymous. UH. And as always, you have a story 429 00:26:03,560 --> 00:26:06,320 Speaker 1: you want to share that your fellow listeners need to know, 430 00:26:06,400 --> 00:26:09,360 Speaker 1: and you're feeling a little squirrelly about it. Uh, we 431 00:26:09,520 --> 00:26:12,640 Speaker 1: do try our best to protect anonymity, and if you're 432 00:26:12,640 --> 00:26:15,000 Speaker 1: not comfortable reached out with a show thing, you can 433 00:26:15,000 --> 00:26:17,400 Speaker 1: reach out to me personally. We we always shout out 434 00:26:17,400 --> 00:26:21,160 Speaker 1: our social media. Here we go. This email from anonymous 435 00:26:21,440 --> 00:26:27,160 Speaker 1: starts by naming the various positions this individual is occupied 436 00:26:27,200 --> 00:26:29,720 Speaker 1: in the justice system. And this email is little in depth, 437 00:26:29,800 --> 00:26:32,880 Speaker 1: so we're gonna stop at different parts and talk it over, 438 00:26:32,920 --> 00:26:36,080 Speaker 1: explore it with each other. So it starts this way. Officer, 439 00:26:36,200 --> 00:26:41,480 Speaker 1: probation Officer, diversion officer, pre trial release officer, community corrections, 440 00:26:41,520 --> 00:26:45,560 Speaker 1: case manager for sex offenders, Certified bond Commissioner, Investigator of 441 00:26:45,640 --> 00:26:50,120 Speaker 1: child abuse and fatality, social worker, placement EVALUAID which means 442 00:26:50,160 --> 00:26:54,400 Speaker 1: assessing the rehabilitation needs of juveniles facing incarceration, et cetera. 443 00:26:54,720 --> 00:26:58,360 Speaker 1: That's the cold open of this correspondence. Are anonymous sources 444 00:26:58,800 --> 00:27:01,040 Speaker 1: in these roles. I have been a trainers, supervisor, and 445 00:27:01,080 --> 00:27:05,080 Speaker 1: expert witness. I have attended and presented a many national conferences. 446 00:27:05,280 --> 00:27:08,240 Speaker 1: I'm also a data nerd who provides input and feedback 447 00:27:08,280 --> 00:27:12,880 Speaker 1: to a statewide child abuse research team in cooperation with 448 00:27:13,600 --> 00:27:16,679 Speaker 1: just gonna redact that. Uh, please don't assume that my 449 00:27:16,880 --> 00:27:20,639 Speaker 1: roles and affiliations make me pro cop or biased. I 450 00:27:20,640 --> 00:27:22,800 Speaker 1: will be the first to say that the criminal justice 451 00:27:22,800 --> 00:27:26,840 Speaker 1: and child protection systems are deeply flawed. I only remain 452 00:27:26,920 --> 00:27:30,480 Speaker 1: in these fields because change of major systems must happen 453 00:27:30,600 --> 00:27:34,359 Speaker 1: from within. Now that is that is a valid point. 454 00:27:34,359 --> 00:27:37,760 Speaker 1: It's also an argument that just candidly not everyone's going 455 00:27:37,800 --> 00:27:41,159 Speaker 1: to agree with. And our anonymous source gives us the 456 00:27:41,200 --> 00:27:44,280 Speaker 1: following here is what they don't want you to know. 457 00:27:44,880 --> 00:27:48,760 Speaker 1: Number One, we criminal justice and child protection have many 458 00:27:48,800 --> 00:27:55,280 Speaker 1: scientifically validated tools that accurately predict elevated risk of criminal recidivism, 459 00:27:55,359 --> 00:28:01,160 Speaker 1: child abuse, substance dependency, truancy, etcetera. Recidivism is the likelihood 460 00:28:01,200 --> 00:28:05,320 Speaker 1: to commit more crimes after you've committed a couple in 461 00:28:05,320 --> 00:28:10,000 Speaker 1: the past. So this source has verified that predictive analytics, 462 00:28:10,400 --> 00:28:13,200 Speaker 1: which we talked about in the past, is being implemented 463 00:28:13,440 --> 00:28:19,040 Speaker 1: in multiple jurisdictions to direct practices and services. Anonymous, you 464 00:28:19,080 --> 00:28:24,199 Speaker 1: have provided us a fascinating link to a nonprofit a 465 00:28:24,359 --> 00:28:29,040 Speaker 1: ECF dot org, which talks about using data analytics to 466 00:28:29,240 --> 00:28:33,119 Speaker 1: quote work for children and families. This is also, by 467 00:28:33,119 --> 00:28:36,639 Speaker 1: the way, very much response to our AI Prosecutor episode 468 00:28:36,680 --> 00:28:39,840 Speaker 1: from earlier and shout out to all the legal vehicles 469 00:28:40,000 --> 00:28:42,480 Speaker 1: in Germany touch based with us on that. Thank you. 470 00:28:43,120 --> 00:28:47,560 Speaker 1: Uh So, this person is saying that predictive analytics is 471 00:28:47,600 --> 00:28:52,160 Speaker 1: both validated and accurate, but is still seen as a 472 00:28:52,200 --> 00:28:56,520 Speaker 1: tool of bias and discrimination. And then here's the juice. 473 00:28:56,560 --> 00:28:59,320 Speaker 1: That's why I tune into the show, folks. This fellow 474 00:28:59,360 --> 00:29:02,480 Speaker 1: listener gave us data points that a lot of the 475 00:29:02,480 --> 00:29:06,520 Speaker 1: public doesn't know what failing the first grade and not 476 00:29:06,640 --> 00:29:12,600 Speaker 1: any other grade is a validated indicator of sex offender recidivism. 477 00:29:12,640 --> 00:29:15,920 Speaker 1: This was taken out of assessment tools because it's not 478 00:29:15,960 --> 00:29:20,320 Speaker 1: politically correct. Isn't that crazy? That doesn't make sense to me? 479 00:29:20,800 --> 00:29:24,120 Speaker 1: And that's from the nineteen nineties. It's saying mm hmm 480 00:29:24,920 --> 00:29:28,160 Speaker 1: that that the assessment I guess the and some of 481 00:29:28,200 --> 00:29:32,520 Speaker 1: these outdated markers have like stuck around for too long. 482 00:29:33,360 --> 00:29:36,760 Speaker 1: Wait wait, hold on, hold on. So that's saying that 483 00:29:36,840 --> 00:29:41,880 Speaker 1: for some reason, whatever leaps are supposed to happen cognitively 484 00:29:42,040 --> 00:29:45,320 Speaker 1: during the first grade, if you kind of if you 485 00:29:45,640 --> 00:29:48,440 Speaker 1: can't get past some of those things or or you know, 486 00:29:48,480 --> 00:29:51,160 Speaker 1: get your mind wrapped around some of those things at 487 00:29:51,200 --> 00:29:55,719 Speaker 1: that age, then you are more likely to commit another crime. 488 00:29:56,440 --> 00:29:59,240 Speaker 1: After the first crime you've committed, especially a crime that 489 00:29:59,280 --> 00:30:03,160 Speaker 1: we have your category rized as a sex offender. That's 490 00:30:03,200 --> 00:30:07,800 Speaker 1: the specificity there is is very strange to me. Also, 491 00:30:08,400 --> 00:30:11,160 Speaker 1: just candidly, I feel like, glad it's only the first 492 00:30:11,160 --> 00:30:15,000 Speaker 1: grade because your boy here took kindergarten twice lack of 493 00:30:15,080 --> 00:30:19,440 Speaker 1: social skills true story. So I don't know what it 494 00:30:19,520 --> 00:30:22,640 Speaker 1: is about specifically about first grade and and be interested. 495 00:30:22,800 --> 00:30:26,480 Speaker 1: I think we all be interested to hear um everybody 496 00:30:26,480 --> 00:30:29,560 Speaker 1: else's reaction to that. This keeps going. This second one 497 00:30:29,600 --> 00:30:32,040 Speaker 1: makes a little more sense. The zip code of your 498 00:30:32,040 --> 00:30:36,360 Speaker 1: residency at birth and proximity to a liquor store increases 499 00:30:36,400 --> 00:30:39,920 Speaker 1: the likelihood that you will commit a crime of violence. 500 00:30:40,200 --> 00:30:43,360 Speaker 1: This study originated out of Houston, but was confirmed via 501 00:30:43,480 --> 00:30:49,000 Speaker 1: national analysis, so they extrapolated, right, I mean that makes 502 00:30:49,000 --> 00:30:52,520 Speaker 1: sense to me. You don't see a ton of package 503 00:30:52,520 --> 00:30:56,560 Speaker 1: stores in the really really nice neighborhoods, and insurance agencies, 504 00:30:56,600 --> 00:31:00,720 Speaker 1: all insurance companies, excuse me, already use zip coe information 505 00:31:00,800 --> 00:31:04,720 Speaker 1: to determine, you know, like the likelihood of vandalism to 506 00:31:04,760 --> 00:31:08,920 Speaker 1: your car or an accident or something like that. You know. Um, 507 00:31:08,960 --> 00:31:14,080 Speaker 1: it does seem kind of cold though, because Yeah, it 508 00:31:14,160 --> 00:31:15,920 Speaker 1: puts people in a box. You know what I mean, 509 00:31:16,560 --> 00:31:18,600 Speaker 1: all of these do? I mean that one is still 510 00:31:18,840 --> 00:31:22,320 Speaker 1: being used. Uh, it's apparently, Yeah, a data point that 511 00:31:22,400 --> 00:31:25,840 Speaker 1: people are using, which is unfair because not everybody can 512 00:31:25,920 --> 00:31:29,120 Speaker 1: afford to live in the best ZIP code for their child. 513 00:31:29,320 --> 00:31:31,719 Speaker 1: You know what I mean. You were saying the one 514 00:31:31,720 --> 00:31:36,600 Speaker 1: about first grade though, was removed, right, Uh it was. Yeah, 515 00:31:36,640 --> 00:31:39,080 Speaker 1: it was taken out because it was too there's too 516 00:31:39,160 --> 00:31:41,560 Speaker 1: much of a of a hot button issue. And it 517 00:31:41,640 --> 00:31:44,560 Speaker 1: does feel like it it does, you know, without us 518 00:31:44,760 --> 00:31:48,960 Speaker 1: seeing the methodology. Um, you know, like like we pointed 519 00:31:48,960 --> 00:31:51,360 Speaker 1: out that was a tool used in the nineties, but 520 00:31:51,520 --> 00:31:55,960 Speaker 1: without us seeing the methodology, that feels almost like pre crime, 521 00:31:56,320 --> 00:31:59,040 Speaker 1: you know, sure. I mean, so does the package store one. 522 00:31:59,080 --> 00:32:02,520 Speaker 1: And a little problematic beyond that if you pair it 523 00:32:02,600 --> 00:32:04,600 Speaker 1: with the you know what you mentioned about the types 524 00:32:04,640 --> 00:32:08,080 Speaker 1: of neighborhoods that it seems to be targeting. Um, it's 525 00:32:08,200 --> 00:32:11,880 Speaker 1: very interesting. I mean, so your anonymous emailer has insight 526 00:32:11,960 --> 00:32:15,280 Speaker 1: access to these uh methods that normal people wouldn't have. 527 00:32:15,360 --> 00:32:18,200 Speaker 1: That's right, right, Yeah, that's correct. This person is speaking 528 00:32:18,280 --> 00:32:21,600 Speaker 1: from firsthand experience in the multiple positions that they have 529 00:32:21,640 --> 00:32:24,600 Speaker 1: occupied over the years. Uh, and they're trying to fight 530 00:32:24,640 --> 00:32:29,040 Speaker 1: the good fight. There are um, there are a couple 531 00:32:29,120 --> 00:32:32,480 Speaker 1: of other things. And then one last important point this 532 00:32:33,120 --> 00:32:39,080 Speaker 1: anonymous fellow conspiracy realist has made. The next one is uh. 533 00:32:39,280 --> 00:32:42,000 Speaker 1: Next one is also kind of weird quote. The number 534 00:32:42,000 --> 00:32:45,120 Speaker 1: of long term friends you have is an accurate predictor 535 00:32:45,240 --> 00:32:50,920 Speaker 1: of criminal recidivism and probation compliance. I'm not sure how 536 00:32:50,960 --> 00:32:54,960 Speaker 1: to interpret that. This is apparently implemented in a criminal 537 00:32:55,000 --> 00:32:57,800 Speaker 1: justice tool called the l s I. But if it 538 00:32:57,920 --> 00:32:59,959 Speaker 1: says what I think it says in correct us if 539 00:33:00,000 --> 00:33:03,440 Speaker 1: we're off base here, Anonymous, it sounds like they're saying 540 00:33:03,600 --> 00:33:08,840 Speaker 1: having a sense of community makes you less likely to 541 00:33:08,880 --> 00:33:11,720 Speaker 1: commit more crimes? Is that what they're saying? Because it 542 00:33:11,760 --> 00:33:14,480 Speaker 1: could be read the other way as well, Right, Yeah, 543 00:33:14,520 --> 00:33:17,200 Speaker 1: I was wondering the same thing. I don't know. It 544 00:33:17,280 --> 00:33:19,840 Speaker 1: seems like the kind of thing you hear people say about, 545 00:33:20,200 --> 00:33:22,320 Speaker 1: you know, serial killers when they find them, like, oh, 546 00:33:22,360 --> 00:33:24,840 Speaker 1: they were always a loner and then then kept themselves 547 00:33:24,880 --> 00:33:29,000 Speaker 1: and all that. But again, that's almost like become a cliche, um, 548 00:33:29,080 --> 00:33:32,520 Speaker 1: and to use that in advance as a determining factor 549 00:33:32,720 --> 00:33:34,840 Speaker 1: of whether or not someone's likely to commit crimes seems 550 00:33:34,880 --> 00:33:38,280 Speaker 1: a little tricky. Some people are just you know, not 551 00:33:38,560 --> 00:33:41,560 Speaker 1: super social. Yeah. And then there's another one that's not 552 00:33:41,560 --> 00:33:45,200 Speaker 1: in the US. This is in New Zealand. Uh. New 553 00:33:45,280 --> 00:33:49,200 Speaker 1: Zealand is able to assess children at the age of 554 00:33:49,320 --> 00:33:52,800 Speaker 1: five and at that tender each the system is able 555 00:33:52,840 --> 00:33:56,040 Speaker 1: to predict who admits these kids will grow up to 556 00:33:56,080 --> 00:34:00,760 Speaker 1: be a financial burden to the criminal, welfare and medical systems. 557 00:34:00,800 --> 00:34:04,400 Speaker 1: And this apparently is done by UH figuring out and 558 00:34:04,480 --> 00:34:08,800 Speaker 1: quantifying the number of adverse experiences the kid was exposed 559 00:34:08,800 --> 00:34:14,440 Speaker 1: to by that point, which is frightening but logical. Unless 560 00:34:14,480 --> 00:34:18,399 Speaker 1: this sounds cold, you know, these aren't. This isn't as 561 00:34:18,480 --> 00:34:23,440 Speaker 1: though there's some Orwellian plan to like pre ruined children's lives. 562 00:34:24,040 --> 00:34:28,839 Speaker 1: They're trying to make a more efficient system. They're trying 563 00:34:28,880 --> 00:34:33,880 Speaker 1: to lessen the burden on the system. Now, um, but 564 00:34:33,960 --> 00:34:36,439 Speaker 1: this is this is a lot of food for disturbing thought. 565 00:34:36,520 --> 00:34:40,120 Speaker 1: Anonymous goes on to say something that I think, unfortunately 566 00:34:40,160 --> 00:34:43,040 Speaker 1: speak to a lot of our fellow listeners. Quote. They 567 00:34:43,080 --> 00:34:45,400 Speaker 1: say ignorance is bliss, But what they don't say is 568 00:34:45,440 --> 00:34:49,040 Speaker 1: insight is a burden. When one's mind is full of validated, 569 00:34:49,200 --> 00:34:52,840 Speaker 1: predictive analytics and tens of thousands of hours of interviews 570 00:34:52,840 --> 00:34:57,360 Speaker 1: and assessments. One can read people too well. Cold reading, 571 00:34:57,480 --> 00:35:00,239 Speaker 1: I thought you'd appreciate this man is a party trick 572 00:35:00,360 --> 00:35:03,400 Speaker 1: used by hustlers and con men for fun and entertainment. 573 00:35:03,920 --> 00:35:08,080 Speaker 1: Profiling is a trained step above cold reading. Then there 574 00:35:08,120 --> 00:35:10,440 Speaker 1: are those of us who can meet a child and 575 00:35:10,480 --> 00:35:15,480 Speaker 1: see that child's past trauma and future hurdles. We are cursed. 576 00:35:15,880 --> 00:35:18,840 Speaker 1: I welcome a computer telling me who and what needs attention, 577 00:35:19,120 --> 00:35:21,359 Speaker 1: because that computer can be turned off at the end 578 00:35:21,360 --> 00:35:24,520 Speaker 1: of the shift. Unlike my knowledge and insight, it's always on, 579 00:35:24,719 --> 00:35:27,520 Speaker 1: it's always lingering, it's always telling me more than I 580 00:35:27,560 --> 00:35:31,680 Speaker 1: want to know about that, for instance, young Sandy blonde 581 00:35:31,760 --> 00:35:36,040 Speaker 1: lady at safeweight. Uh. And then the letter concludes. But 582 00:35:36,160 --> 00:35:38,400 Speaker 1: I thought this would be I mean, this is going 583 00:35:38,440 --> 00:35:40,680 Speaker 1: to be controversial, right for for a lot of people. 584 00:35:40,719 --> 00:35:44,160 Speaker 1: The idea we have people in in the audience with 585 00:35:44,239 --> 00:35:47,160 Speaker 1: us today who have children in first grade, you know 586 00:35:47,200 --> 00:35:51,879 Speaker 1: what I mean. Yeah, Yeah, that is a tough thing 587 00:35:51,960 --> 00:35:54,399 Speaker 1: to think about. I know that that exists just from 588 00:35:54,440 --> 00:35:59,080 Speaker 1: interactions I've had making some past shows with people who 589 00:35:59,239 --> 00:36:01,680 Speaker 1: work in this kind kind of field, the field of 590 00:36:01,680 --> 00:36:06,319 Speaker 1: psychology and assessment and just how how much of a 591 00:36:06,360 --> 00:36:10,160 Speaker 1: toll that takes on you, um, not only with assessing people, 592 00:36:10,160 --> 00:36:14,920 Speaker 1: but you know, in many ways internalizing other people's stuff 593 00:36:15,040 --> 00:36:18,719 Speaker 1: that they're dealing with. Right. Um, My heart goes out 594 00:36:18,719 --> 00:36:22,240 Speaker 1: to you, anonymous person who sent this to us, because 595 00:36:22,239 --> 00:36:24,880 Speaker 1: that follow this stuff. I mean, I'm assuming all of 596 00:36:24,920 --> 00:36:28,320 Speaker 1: these data points are real and correct, and you've backed 597 00:36:28,320 --> 00:36:31,759 Speaker 1: them up, many of them and I looked in the 598 00:36:31,760 --> 00:36:37,440 Speaker 1: source and it's legit. Yeah, And that's tough. Yeah. It's 599 00:36:37,480 --> 00:36:40,800 Speaker 1: something that we didn't talk about in the AI prosecution 600 00:36:40,880 --> 00:36:47,000 Speaker 1: episode because we we didn't talk about the enormously dangerous 601 00:36:47,120 --> 00:36:51,680 Speaker 1: mental and emotional burden that has put upon people who 602 00:36:51,840 --> 00:36:55,120 Speaker 1: have to fight the darkness in this way, you know 603 00:36:55,160 --> 00:36:58,000 Speaker 1: what I mean, It can destroy people. And I believe 604 00:36:58,080 --> 00:37:02,040 Speaker 1: that's why in many aspect to law enforcement, especially like 605 00:37:02,760 --> 00:37:05,920 Speaker 1: specific types of child abuse. UH, in many parts of 606 00:37:05,960 --> 00:37:10,160 Speaker 1: the law enforcement world, individuals are cycled out on a 607 00:37:10,239 --> 00:37:13,440 Speaker 1: rotating basis because it's too heavy for one person. But 608 00:37:14,400 --> 00:37:18,560 Speaker 1: thank you so much for this, Thank you so much 609 00:37:18,600 --> 00:37:21,440 Speaker 1: for this information. For everybody out there who's fighting to 610 00:37:21,640 --> 00:37:25,160 Speaker 1: protect kids and make the world a better place, thank 611 00:37:25,239 --> 00:37:28,120 Speaker 1: you as well. And if you have experience with this. 612 00:37:28,480 --> 00:37:30,920 Speaker 1: If you have other data points that you want to share, 613 00:37:31,239 --> 00:37:34,120 Speaker 1: we would love to hear from you. Uh, we don't 614 00:37:34,120 --> 00:37:36,799 Speaker 1: want to end on such a heavy note. Uh. So 615 00:37:37,040 --> 00:37:38,759 Speaker 1: we have one correction just came in. Now we'll keep 616 00:37:38,800 --> 00:37:41,800 Speaker 1: this person anonymous as well. Uh. They wanted to point 617 00:37:41,800 --> 00:37:46,200 Speaker 1: out that vending machines that sell underwear is a specifically 618 00:37:46,280 --> 00:37:50,160 Speaker 1: weird Japanese thing, and it's very true. It's not all 619 00:37:50,239 --> 00:37:52,880 Speaker 1: of and we knew that. Yeah. I think that was 620 00:37:53,320 --> 00:37:56,080 Speaker 1: in relation to the farts in jar story. Uh. And 621 00:37:56,120 --> 00:37:59,040 Speaker 1: I maybe tried to um cast two wide a net. 622 00:37:59,040 --> 00:38:02,120 Speaker 1: They're absolutely scifically a Japanese thing. I think we maybe 623 00:38:02,120 --> 00:38:03,839 Speaker 1: even did a pick up on that one in the night. 624 00:38:03,840 --> 00:38:07,279 Speaker 1: We've kind of made it stupider. No, we knew, we 625 00:38:07,520 --> 00:38:10,000 Speaker 1: very much. Uh, We're very much aware. And it is 626 00:38:10,080 --> 00:38:13,480 Speaker 1: never our Uh. Then this ties into the idea of 627 00:38:13,480 --> 00:38:19,320 Speaker 1: predictive analytics. It is never our aim to generalize. And 628 00:38:19,360 --> 00:38:21,239 Speaker 1: I want to I want to shout out this anonymous 629 00:38:21,280 --> 00:38:24,160 Speaker 1: person because you wrote such a great comparison. At the 630 00:38:24,239 --> 00:38:26,600 Speaker 1: very end of your letter, you said it's like say 631 00:38:26,640 --> 00:38:29,919 Speaker 1: Europeans eat horses, when maybe just some French people do 632 00:38:30,360 --> 00:38:34,759 Speaker 1: so so so points and thank you and we hear you. 633 00:38:35,080 --> 00:38:37,200 Speaker 1: Um this we're just doing on the fly because it 634 00:38:37,200 --> 00:38:39,319 Speaker 1: came in. It's an important point. But we did say 635 00:38:39,360 --> 00:38:42,640 Speaker 1: we wanted to end on an up note. Your pals 636 00:38:42,760 --> 00:38:44,719 Speaker 1: over here. Stuff they don't want you to know might 637 00:38:44,760 --> 00:38:49,759 Speaker 1: be coming up in the world, folks. Uh, we have Matt. 638 00:38:49,760 --> 00:38:51,520 Speaker 1: I'm gonna be honest with you. I haven't listened to 639 00:38:51,560 --> 00:38:55,040 Speaker 1: this yet, but we have what Matt tells us maybe 640 00:38:55,080 --> 00:38:58,600 Speaker 1: a celebrity appearance in our voicemail. Oh well, yes, it 641 00:38:58,840 --> 00:39:02,439 Speaker 1: most definitely is. Uh and you'll you'll find out why 642 00:39:02,480 --> 00:39:04,600 Speaker 1: here we go. Now, you know you guys want me 643 00:39:04,640 --> 00:39:07,799 Speaker 1: to say it. I mean, who else is gonna do it? Oh? 644 00:39:07,880 --> 00:39:11,919 Speaker 1: My crown. There's only there's only one way to say 645 00:39:11,960 --> 00:39:16,480 Speaker 1: that word, okay, and it's on the crown. Because you know, 646 00:39:17,960 --> 00:39:21,320 Speaker 1: whenever you think about the word I'm a crown, you 647 00:39:21,440 --> 00:39:23,960 Speaker 1: and crown, all you think about is transformers come on them. 648 00:39:24,080 --> 00:39:28,239 Speaker 1: They suck a cons on dots. That's what that's what 649 00:39:28,320 --> 00:39:30,680 Speaker 1: you think about. And you know I heard you talking 650 00:39:30,680 --> 00:39:32,200 Speaker 1: the other day and I said to myself, I gotta 651 00:39:32,280 --> 00:39:33,960 Speaker 1: leave a missed for him. You played on the ear, 652 00:39:34,000 --> 00:39:35,520 Speaker 1: gonna play it here? I don't care. It's for you guys. 653 00:39:35,680 --> 00:39:39,360 Speaker 1: Enjoy it. Oh my crown, it's here. But is it 654 00:39:39,440 --> 00:39:43,360 Speaker 1: gonna do anything? I don't know what do you guys think? Personally? 655 00:39:43,400 --> 00:39:46,680 Speaker 1: I just another saying. Ain't nobody dying from it? But whatever? 656 00:39:47,480 --> 00:39:50,960 Speaker 1: What's that? Well? You want to say something? Oh? Hold on, 657 00:39:52,120 --> 00:39:55,280 Speaker 1: my name is Optimus Prime, leader of the Auto box 658 00:39:55,360 --> 00:40:00,279 Speaker 1: from the planet cliper trod. Oh, the beautiful planet cliper Ron. 659 00:40:00,760 --> 00:40:04,359 Speaker 1: I remember it well. We used to transform and roll 660 00:40:04,400 --> 00:40:10,520 Speaker 1: out all the time. Anyway, I'm just sitting here and 661 00:40:10,600 --> 00:40:15,400 Speaker 1: I thought, you know what, oh my crown, not to 662 00:40:15,440 --> 00:40:21,920 Speaker 1: be confused with Crown. Sorry, I couldn't help myself. Have 663 00:40:22,000 --> 00:40:26,120 Speaker 1: a nice stay, gents the whole days. Merry Christmas, enjoy 664 00:40:26,160 --> 00:40:28,960 Speaker 1: your winter, wol of day, whatever you want to call it. 665 00:40:29,200 --> 00:40:32,279 Speaker 1: Do you think? Keep up the great work. I love 666 00:40:32,360 --> 00:40:36,640 Speaker 1: the podcast. Don't stop ever, choose I would be the saying. 667 00:40:36,640 --> 00:40:41,440 Speaker 1: Good point? Is that his real voice? We'll never know? Yeah, 668 00:40:41,480 --> 00:40:44,360 Speaker 1: this is a man of many voices. Who is this person? 669 00:40:45,280 --> 00:40:48,759 Speaker 1: I thought, Okay, peep behind the curtain here vols uh. 670 00:40:48,760 --> 00:40:51,279 Speaker 1: When I was talking this up for the entirety of 671 00:40:51,320 --> 00:40:53,600 Speaker 1: this week's listening to mails, something, I thought we were 672 00:40:53,640 --> 00:40:56,839 Speaker 1: going to George Lopez. Who we are? We are? I'm 673 00:40:56,880 --> 00:41:00,520 Speaker 1: so sorry I had to take us down that just quickly. 674 00:41:03,719 --> 00:41:07,880 Speaker 1: Which accent is the guy's real accent? I don't, I 675 00:41:07,880 --> 00:41:10,160 Speaker 1: don't want to know. Maybe he is. He is a 676 00:41:10,239 --> 00:41:12,879 Speaker 1: robot in disguise. It does give me an idea though. 677 00:41:12,920 --> 00:41:16,319 Speaker 1: Maybe the next variant will be called Decepticon, and then 678 00:41:16,360 --> 00:41:20,480 Speaker 1: the Omicron variant can fight the Decepticon variant and save 679 00:41:20,760 --> 00:41:27,200 Speaker 1: the planet. Wow. Wow, Well let's go to George Lopez 680 00:41:27,320 --> 00:41:31,960 Speaker 1: for more. Hi, my name is George Lopez, future President 681 00:41:31,960 --> 00:41:35,720 Speaker 1: of the United States of America. Yes, the comedian. I'm 682 00:41:35,760 --> 00:41:40,320 Speaker 1: just coining because you guys remember touch the topic clearly 683 00:41:41,000 --> 00:41:45,560 Speaker 1: digging deep into the Montauk Project. There's a lot of 684 00:41:45,680 --> 00:41:50,880 Speaker 1: history on Long Island about it. Government has hidden it 685 00:41:51,040 --> 00:41:55,360 Speaker 1: was before Air Force Space would be a good episode. 686 00:41:55,400 --> 00:41:57,520 Speaker 1: Thank you, and I love the show, been here in 687 00:41:57,640 --> 00:42:01,680 Speaker 1: for years. I did that? Is him? Really? I don't know? 688 00:42:01,760 --> 00:42:04,280 Speaker 1: Did you call him back? Is it an idea? I did? 689 00:42:04,360 --> 00:42:07,080 Speaker 1: And the mailbox was full. Was in an l A number. 690 00:42:07,080 --> 00:42:10,880 Speaker 1: And he's a busy guy. I mean, he's got an 691 00:42:10,880 --> 00:42:14,239 Speaker 1: amazing podcast. I don't know if you guys have heard omg, oh, 692 00:42:14,280 --> 00:42:20,400 Speaker 1: what is it. Yeah, yeah, it is. It's great. Uh, 693 00:42:20,400 --> 00:42:23,359 Speaker 1: it's on the O MG High, that's it. And and 694 00:42:23,400 --> 00:42:26,240 Speaker 1: also you know, uh, if this is not the George 695 00:42:26,280 --> 00:42:29,959 Speaker 1: Lopez with the podcast to MG High, well then you 696 00:42:30,000 --> 00:42:34,720 Speaker 1: are our famous George Lopez. Uh on car stuff. For years, 697 00:42:35,000 --> 00:42:38,120 Speaker 1: there was this awesome caller who I'm still personal friends 698 00:42:38,160 --> 00:42:42,400 Speaker 1: with named Glenn Beck. And uh and Glenn, we still 699 00:42:42,600 --> 00:42:46,200 Speaker 1: Scott Knight kept our word man. We still never had 700 00:42:46,239 --> 00:42:49,040 Speaker 1: any name jokes. We just refer to you as the 701 00:42:49,160 --> 00:42:52,439 Speaker 1: Glenn Beck. You're the you're the one in our book man. 702 00:42:52,920 --> 00:42:54,960 Speaker 1: Hell well, you know. And and if if this is 703 00:42:55,000 --> 00:42:59,600 Speaker 1: not the George Lopez of stand up comedy and podcast 704 00:42:59,640 --> 00:43:02,600 Speaker 1: and tell visual fame, then I hope this George Lopez's 705 00:43:02,600 --> 00:43:04,560 Speaker 1: stand up career is going well. Yeah, I mean too, 706 00:43:04,560 --> 00:43:06,400 Speaker 1: He's going to be the next president of the the United States, 707 00:43:06,400 --> 00:43:09,719 Speaker 1: So I mean that somes going well. I like and 708 00:43:10,320 --> 00:43:12,480 Speaker 1: you know, it's definitely not a job I want. I 709 00:43:12,520 --> 00:43:14,799 Speaker 1: don't know about you guys, but uh yeah, no, thank 710 00:43:14,840 --> 00:43:19,319 Speaker 1: you fakes. But with that, we are going to call 711 00:43:19,400 --> 00:43:24,400 Speaker 1: it a day. We will be back tomorrow with more stuff. 712 00:43:24,440 --> 00:43:26,879 Speaker 1: They don't want you to know. In the meantime, we 713 00:43:26,920 --> 00:43:30,640 Speaker 1: want to thank anonymous. We want to thank George Lopez. 714 00:43:30,920 --> 00:43:34,319 Speaker 1: We want to thank oh mcgroan. We want to thank 715 00:43:34,400 --> 00:43:38,080 Speaker 1: yah yah te dog Gumby and everybody who's tuned in. 716 00:43:38,120 --> 00:43:39,879 Speaker 1: If you want to be part of the show, we'd 717 00:43:39,960 --> 00:43:42,160 Speaker 1: love to have you. We try to be easy to 718 00:43:42,200 --> 00:43:44,600 Speaker 1: find online, boy do we ever. You can find us 719 00:43:44,640 --> 00:43:47,000 Speaker 1: on Twitter, you can find us on YouTube. You can 720 00:43:47,040 --> 00:43:51,239 Speaker 1: find us on Facebook with the handle Conspiracy Stuff. You 721 00:43:51,239 --> 00:43:54,359 Speaker 1: can also find our Facebook group Here's where it gets crazy. Um. 722 00:43:54,400 --> 00:43:57,359 Speaker 1: If you would like to find us elsewhere, you can 723 00:43:57,440 --> 00:44:00,000 Speaker 1: use the handle at Conspiracy Stuff show, which we are 724 00:44:00,000 --> 00:44:02,160 Speaker 1: on Instagram and those things doing for you. There are 725 00:44:02,239 --> 00:44:04,719 Speaker 1: more analog ways to get in touch with us. That's right, 726 00:44:04,960 --> 00:44:08,200 Speaker 1: use your mouth in your phone will be waiting by ours. 727 00:44:10,320 --> 00:44:13,880 Speaker 1: I like it. I just like company. I don't know, 728 00:44:14,000 --> 00:44:16,200 Speaker 1: is that what it is? It reminds me of sitcoms. 729 00:44:16,239 --> 00:44:19,240 Speaker 1: I was thinking about this. Um, I was over because 730 00:44:19,320 --> 00:44:21,840 Speaker 1: I just fritter time away on Twitter. I was on 731 00:44:21,880 --> 00:44:25,000 Speaker 1: Twitter and it just hit me, Um, whatever happened to 732 00:44:25,000 --> 00:44:29,120 Speaker 1: all the bonkers sitcom premises of Yesteryear? Like I missed 733 00:44:29,200 --> 00:44:32,000 Speaker 1: that stuff? When when someone the writer's room was like, 734 00:44:32,160 --> 00:44:35,160 Speaker 1: you know what, No, they meet an alien he's friendly, 735 00:44:35,520 --> 00:44:37,919 Speaker 1: but he's always just about to kill and eat their cat. 736 00:44:38,280 --> 00:44:40,920 Speaker 1: Or they're like, oh this guy married a jinn. My 737 00:44:41,040 --> 00:44:43,640 Speaker 1: dead mom possessed my car, Like how did that? Like 738 00:44:43,680 --> 00:44:46,000 Speaker 1: it was so in depth that they had to explain 739 00:44:46,120 --> 00:44:49,480 Speaker 1: the set up in the theme song, right the best. 740 00:44:49,960 --> 00:44:51,839 Speaker 1: I think we're due for, like a second, I think 741 00:44:51,840 --> 00:44:54,320 Speaker 1: we're due for a renaissance of that kind of television. 742 00:44:55,640 --> 00:44:59,279 Speaker 1: Maybe it'll be us well maybe, Well then I look 743 00:44:59,440 --> 00:45:02,399 Speaker 1: forward to next Twitter Fritter. Uh that that was one 744 00:45:02,400 --> 00:45:06,000 Speaker 1: of my favorite phrases so we've had thus far. But hey, 745 00:45:06,040 --> 00:45:08,000 Speaker 1: if you do want to call us, our number is 746 00:45:08,040 --> 00:45:11,560 Speaker 1: one eight three three s t d w y t K. 747 00:45:12,040 --> 00:45:14,799 Speaker 1: When you call in, give yourself a cool nickname, and 748 00:45:14,960 --> 00:45:16,799 Speaker 1: we just don't want to say your real name on air. 749 00:45:16,880 --> 00:45:18,960 Speaker 1: If if that's okay, we'd love to know if we 750 00:45:19,040 --> 00:45:22,759 Speaker 1: can use your voice and message on one of these episodes, 751 00:45:23,120 --> 00:45:25,600 Speaker 1: and you've got three minutes. We do ask that you 752 00:45:25,640 --> 00:45:28,080 Speaker 1: try to limit the number of back to back calls 753 00:45:28,440 --> 00:45:30,040 Speaker 1: that you send in, but we do want to hear 754 00:45:30,080 --> 00:45:32,520 Speaker 1: from you, so please don't let that stop You just 755 00:45:32,680 --> 00:45:34,680 Speaker 1: helps us get through them a little faster. And we 756 00:45:34,719 --> 00:45:39,600 Speaker 1: are caught up at this point that's very exciting for us. Um. 757 00:45:39,640 --> 00:45:42,320 Speaker 1: If you don't want to send us a voice message, instead, 758 00:45:42,440 --> 00:45:46,440 Speaker 1: consider sending us a good old fashioned email. It takes links, 759 00:45:46,480 --> 00:45:48,960 Speaker 1: it takes all kinds of stuff, and there's no limitations there. 760 00:45:49,200 --> 00:45:53,200 Speaker 1: We read everything you send us our email addresses conspiracy 761 00:45:53,400 --> 00:46:14,399 Speaker 1: at i heart radio dot com. Ye stuff they don't 762 00:46:14,400 --> 00:46:16,960 Speaker 1: want you to know. Is a production of I heart Radio. 763 00:46:17,280 --> 00:46:19,520 Speaker 1: For more podcasts from my heart Radio, visit the i 764 00:46:19,600 --> 00:46:22,520 Speaker 1: heart radio app, Apple Podcasts, or wherever you listen to 765 00:46:22,560 --> 00:46:23,360 Speaker 1: your favorite shows.