1 00:00:00,160 --> 00:00:03,440 Speaker 1: Hello the Internet, and welcome to this episode of the 2 00:00:03,560 --> 00:00:07,880 Speaker 1: Weekly Zeitgeist. Uh. These are some of our favorite segments 3 00:00:08,119 --> 00:00:13,680 Speaker 1: from this week, all edited together into one uh NonStop 4 00:00:13,800 --> 00:00:22,040 Speaker 1: infotainment last stravaganza. Uh yeah, So, without further ado, here 5 00:00:22,280 --> 00:00:26,479 Speaker 1: is the Weekly Zeitgeist. So we wanted to start off 6 00:00:26,600 --> 00:00:31,000 Speaker 1: with a video that went viral over the weekend that 7 00:00:31,040 --> 00:00:34,839 Speaker 1: was made by actually the video director of dead Spin, uh, 8 00:00:34,840 --> 00:00:39,480 Speaker 1: Timothy Burke. It's like a super cut of all these 9 00:00:39,560 --> 00:00:43,840 Speaker 1: local news stations who were given the same script from 10 00:00:43,920 --> 00:00:48,400 Speaker 1: Sinclair Media, where they're basically making a commentary on how 11 00:00:48,520 --> 00:00:53,200 Speaker 1: the mainstream media is lying to people. Which is interesting 12 00:00:53,240 --> 00:00:56,160 Speaker 1: because the Sinclair Broadcasting Group they own right now about 13 00:00:56,200 --> 00:00:59,200 Speaker 1: like a hundred seventy three affiliate stations around the country, 14 00:01:00,280 --> 00:01:02,840 Speaker 1: and there's a merger right now that they're trying to 15 00:01:02,840 --> 00:01:05,600 Speaker 1: get pushed through which would combine them with Tribune Media, 16 00:01:06,000 --> 00:01:09,040 Speaker 1: and that would mean that seven out of ten households 17 00:01:09,080 --> 00:01:11,560 Speaker 1: in this country would be served by a Sinclair station 18 00:01:11,640 --> 00:01:14,160 Speaker 1: in some form. So I guess the way to think 19 00:01:14,200 --> 00:01:18,360 Speaker 1: of it is because Sinclair owns all these local news stations, 20 00:01:18,400 --> 00:01:20,720 Speaker 1: they can tell all these news stations what to say 21 00:01:20,800 --> 00:01:23,840 Speaker 1: during their broadcast. It's not ABC or NBC or CBS 22 00:01:23,959 --> 00:01:27,600 Speaker 1: or whatever. It's at the affiliate stations. The ownership is 23 00:01:27,640 --> 00:01:29,800 Speaker 1: the ones that are giving these directives straight down to 24 00:01:29,800 --> 00:01:32,200 Speaker 1: the anchors, and a lot of anchors were very uncomfortable 25 00:01:32,200 --> 00:01:35,160 Speaker 1: with having to do what they call these must read segments. 26 00:01:35,200 --> 00:01:37,399 Speaker 1: And this was a must read coming from on high 27 00:01:37,480 --> 00:01:43,080 Speaker 1: from Sinclair, which is a right leaning Trump friendly media group, 28 00:01:43,520 --> 00:01:48,920 Speaker 1: so leaning exactly. So you'll see when they're vampires, vampires 29 00:01:49,000 --> 00:01:52,000 Speaker 1: that live in cofference. Yeah, and then they're basically trying 30 00:01:52,040 --> 00:01:54,760 Speaker 1: to gaslight the entire country. So basically, this is a 31 00:01:54,840 --> 00:01:59,880 Speaker 1: super cut of one of the scary messages about fake news. 32 00:02:00,000 --> 00:02:01,919 Speaker 1: It's out there, but when you cut them on together 33 00:02:01,960 --> 00:02:04,520 Speaker 1: and realize they're all lockstep saying the same thing, it's 34 00:02:04,600 --> 00:02:07,080 Speaker 1: fucking scary. So check this out. I am Fox and 35 00:02:07,120 --> 00:02:11,200 Speaker 1: Antonio's Jessica Headley and I'm Ryan Wolf. Our greatest responsibility 36 00:02:11,360 --> 00:02:14,040 Speaker 1: is to serve our treasure. Valley communities, deal pass a 37 00:02:14,120 --> 00:02:18,000 Speaker 1: LUs Crucis communities, Eastern Eye with communities, Mid Michigan communities. 38 00:02:18,280 --> 00:02:21,840 Speaker 1: We're extremely proud of the quality, balanced journalism that CDs 39 00:02:21,880 --> 00:02:31,320 Speaker 1: four News produces, but in country plaguing our country, sharing 40 00:02:31,360 --> 00:02:34,080 Speaker 1: of biased and false news has to become all too 41 00:02:34,080 --> 00:02:38,080 Speaker 1: common on social media. More alarming, some media outlets publish 42 00:02:38,120 --> 00:02:41,840 Speaker 1: the same fake stories without checking facts first. The sharing 43 00:02:41,880 --> 00:02:45,239 Speaker 1: of biased and false news has become too common on 44 00:02:45,560 --> 00:02:57,839 Speaker 1: social media. Qualities are without checking first, unfortunatelyforms their own 45 00:02:59,120 --> 00:03:06,080 Speaker 1: and amend and controlling and extremely dangerous. This is extremely 46 00:03:06,160 --> 00:03:10,040 Speaker 1: dangerous to our democracy. This is extremely dangerous to our democracy. 47 00:03:10,280 --> 00:03:15,320 Speaker 1: This is extremely dangerous to its extremely democracy. This is 48 00:03:15,400 --> 00:03:19,120 Speaker 1: extremely dangerous to our democracy. This is extremely dangerous to 49 00:03:19,200 --> 00:03:24,639 Speaker 1: our democracy. Yes, so that is extremely dangerous. Yeah, so 50 00:03:24,840 --> 00:03:27,240 Speaker 1: basically right now, So imagine if this merger goes through, 51 00:03:27,280 --> 00:03:30,800 Speaker 1: they will control two stations, and Tribune Media also holds 52 00:03:31,160 --> 00:03:34,280 Speaker 1: a lot of stations in swing states like Pennsylvania, North Carolina, 53 00:03:34,320 --> 00:03:38,000 Speaker 1: Ohio and also massive markets like New York, Chicago in 54 00:03:38,280 --> 00:03:42,080 Speaker 1: l a um so, more than likely all you Americans 55 00:03:42,160 --> 00:03:46,480 Speaker 1: night getting people out there probably live in a Sinclair market. Uh. 56 00:03:46,560 --> 00:03:49,120 Speaker 1: And most people get their news still from their local 57 00:03:49,200 --> 00:03:51,320 Speaker 1: news because they still feel they can trust it, because 58 00:03:51,320 --> 00:03:52,800 Speaker 1: they're like, oh, these are people from my town. They're 59 00:03:52,840 --> 00:03:55,320 Speaker 1: not getting their fucking orders from somewhere else. Right. That 60 00:03:55,440 --> 00:03:58,640 Speaker 1: is rapidly changing when we focus on news bias we 61 00:03:58,840 --> 00:04:01,680 Speaker 1: tend to focus on now sational news Fox News versus 62 00:04:01,920 --> 00:04:05,840 Speaker 1: you know, the right focuses on CNN. But yeah, local 63 00:04:05,920 --> 00:04:11,360 Speaker 1: news is widely biased in some cases. And uh, you know, 64 00:04:11,440 --> 00:04:13,840 Speaker 1: when you look at, for instance, the number of how 65 00:04:13,920 --> 00:04:17,960 Speaker 1: they report on crime, there's a huge bias towards reporting 66 00:04:18,000 --> 00:04:21,840 Speaker 1: crimes by people of color, Like the crimes they put 67 00:04:21,920 --> 00:04:24,120 Speaker 1: on the local news will be people of color, and 68 00:04:24,240 --> 00:04:26,880 Speaker 1: only like ten percent of the crimes committed are people 69 00:04:26,960 --> 00:04:30,359 Speaker 1: of color. Right, And I mean this is a logical 70 00:04:31,320 --> 00:04:35,440 Speaker 1: evolution from the traditional conservative media strategy, which is they 71 00:04:35,520 --> 00:04:38,240 Speaker 1: have the money. The right always has more money. So 72 00:04:38,440 --> 00:04:41,000 Speaker 1: that's you saw this happen in talk radio right once 73 00:04:41,040 --> 00:04:46,400 Speaker 1: the last time you heard a left voice on the radio. Yeah, 74 00:04:46,400 --> 00:04:49,719 Speaker 1: because we're on podcasting exactly. It's true. I think people 75 00:04:49,920 --> 00:04:54,800 Speaker 1: got into podcasting, and podcasting is partially growing because there 76 00:04:55,000 --> 00:05:00,719 Speaker 1: wasn't a left alternative to uh, you know, local talk radio. 77 00:05:00,960 --> 00:05:04,159 Speaker 1: And you're seeing this now like luckily, right, like our 78 00:05:04,279 --> 00:05:08,440 Speaker 1: generation and the generation that comes after us, uh doesn't 79 00:05:08,560 --> 00:05:11,800 Speaker 1: watch local news, which is good. Like this strategy. As 80 00:05:11,920 --> 00:05:14,320 Speaker 1: as terrifying as that video was to hear, and it 81 00:05:14,480 --> 00:05:16,680 Speaker 1: was really scary, like you know, yeah, it's like some 82 00:05:16,839 --> 00:05:19,680 Speaker 1: fucking orwelling, and it really was. But the thing to 83 00:05:19,800 --> 00:05:24,240 Speaker 1: remember is just like, Okay, don't watch local news. Wait 84 00:05:24,320 --> 00:05:27,320 Speaker 1: you don't already, great, keep not watching local news. I 85 00:05:27,400 --> 00:05:29,320 Speaker 1: think it's important though, too, because most people will have 86 00:05:29,440 --> 00:05:31,600 Speaker 1: to interact at some point with someone who watches this. 87 00:05:31,839 --> 00:05:35,000 Speaker 1: It takes it for reality. And what's crazy is a 88 00:05:35,080 --> 00:05:38,159 Speaker 1: few people, like in full Wars types dudes, were retweeting 89 00:05:38,200 --> 00:05:41,120 Speaker 1: it with no context, being like, check this out. And 90 00:05:41,560 --> 00:05:43,280 Speaker 1: the response from a lot of people on the right 91 00:05:43,400 --> 00:05:46,479 Speaker 1: was like, yes, you check out the mainstream media. They're 92 00:05:46,520 --> 00:05:49,040 Speaker 1: all fucking brainwashed. And then like other people in the 93 00:05:49,160 --> 00:05:51,440 Speaker 1: twitter threads would be like, you know, this is owned 94 00:05:51,440 --> 00:05:55,040 Speaker 1: by a conservative guy and it's pro Trump propaganda arm 95 00:05:55,080 --> 00:05:57,800 Speaker 1: and their weaponizing your local news. And they were like, well, 96 00:05:57,839 --> 00:06:01,400 Speaker 1: all I'm seeing is CBS, ABC, AN, NBC. Tell me 97 00:06:01,480 --> 00:06:03,920 Speaker 1: how this is like right leaning. They're all against Trump 98 00:06:04,200 --> 00:06:06,080 Speaker 1: and a lot of people you have to understand get it. 99 00:06:06,160 --> 00:06:09,440 Speaker 1: Affiliate news stations are independently owned, but they just have 100 00:06:09,520 --> 00:06:11,480 Speaker 1: an agreement with CBS. They'll be like, okay, funk with 101 00:06:11,600 --> 00:06:14,279 Speaker 1: you will air your shows, but we'll do the local news. 102 00:06:14,360 --> 00:06:16,400 Speaker 1: We'll put the CBS logo on it. But you don't 103 00:06:16,440 --> 00:06:18,720 Speaker 1: tell us what to run, because that's just part of, 104 00:06:18,880 --> 00:06:21,800 Speaker 1: you know, keeping CBS from controlling all the news everywhere. 105 00:06:22,080 --> 00:06:25,000 Speaker 1: So with these independent stations, they actually do get their 106 00:06:25,040 --> 00:06:27,520 Speaker 1: marching orders from Sinclair, which is why they post shit 107 00:06:27,920 --> 00:06:30,440 Speaker 1: like the other must runs have been stuff like the 108 00:06:30,520 --> 00:06:33,479 Speaker 1: me too movement is getting out of control and like yeah, 109 00:06:33,640 --> 00:06:36,160 Speaker 1: or just like mentioning stories that are in another state, 110 00:06:36,279 --> 00:06:38,120 Speaker 1: like you'll be in Tulsa and they'll be talking about 111 00:06:38,120 --> 00:06:40,240 Speaker 1: someone in St. Louis who got their job taken away 112 00:06:40,279 --> 00:06:43,800 Speaker 1: because they're conservative. So yeah. But the silver lining on 113 00:06:43,880 --> 00:06:48,159 Speaker 1: this is that the people watching local news are dying 114 00:06:49,760 --> 00:06:53,440 Speaker 1: because they are really dumb and have gutted our healthcare system. 115 00:06:54,000 --> 00:06:56,360 Speaker 1: So the only old people, and they're dying at a 116 00:06:56,520 --> 00:07:00,440 Speaker 1: rapid rate. The death rate is going up and people 117 00:07:00,480 --> 00:07:02,479 Speaker 1: aren't going to live as long as they did before. 118 00:07:02,640 --> 00:07:06,120 Speaker 1: So I think we're in the clear. If we all die, 119 00:07:06,520 --> 00:07:08,640 Speaker 1: we don't have to deal with this problem. Unfortunately, there 120 00:07:08,720 --> 00:07:12,040 Speaker 1: was a report released last week that says that news 121 00:07:12,200 --> 00:07:15,800 Speaker 1: that is fake travels way faster and way further on 122 00:07:15,880 --> 00:07:22,800 Speaker 1: Twitter and social media, essentially, because that's really damn That 123 00:07:23,000 --> 00:07:26,520 Speaker 1: is an actual study by m I T was basically 124 00:07:26,760 --> 00:07:30,960 Speaker 1: two guys who experienced the Boston bombing living in Boston, 125 00:07:31,360 --> 00:07:33,280 Speaker 1: and we're like, you know, the only place you could 126 00:07:33,280 --> 00:07:35,520 Speaker 1: get reports was on social media. So they saw, like 127 00:07:35,960 --> 00:07:39,240 Speaker 1: you know, that what they read was fake. So they 128 00:07:39,320 --> 00:07:43,360 Speaker 1: did h A. They basically ingested all of Twitter from 129 00:07:43,400 --> 00:07:48,080 Speaker 1: two thousand six to two thousand six and exactly uh, 130 00:07:48,280 --> 00:07:52,200 Speaker 1: and they found that stories that were fake traveled faster, 131 00:07:52,480 --> 00:07:55,640 Speaker 1: got more retweets, got more likes, And they were like, yeah, 132 00:07:55,640 --> 00:07:58,120 Speaker 1: it kind of makes sense because fake stories are able 133 00:07:58,160 --> 00:08:00,240 Speaker 1: to say whatever the funk they want to write. Yeah, 134 00:08:00,280 --> 00:08:03,520 Speaker 1: so it's just wish fulfillment, right. So I think this 135 00:08:03,720 --> 00:08:07,560 Speaker 1: is a problem in any medium. That that's the thing 136 00:08:07,840 --> 00:08:11,000 Speaker 1: about this particular story that they did the illustration about, 137 00:08:11,040 --> 00:08:14,440 Speaker 1: because it could go either way. They're talking about fake news, 138 00:08:14,480 --> 00:08:17,800 Speaker 1: which is something the right also talks about. So that's 139 00:08:18,080 --> 00:08:21,000 Speaker 1: why I think they're able to be like, well, what 140 00:08:21,440 --> 00:08:25,720 Speaker 1: they're talking about CNN or they say talking about Fox News. 141 00:08:25,720 --> 00:08:29,040 Speaker 1: We won't say pizza gate, but we'll misinform you well. 142 00:08:29,080 --> 00:08:31,880 Speaker 1: And then some of these guys have done pizza Gate stories, 143 00:08:32,480 --> 00:08:35,200 Speaker 1: some of these affiliates, Like I remember last year there 144 00:08:35,240 --> 00:08:37,719 Speaker 1: was a story where what are these like guys on 145 00:08:37,880 --> 00:08:41,480 Speaker 1: the local news was very plainly all right and just 146 00:08:41,600 --> 00:08:44,360 Speaker 1: reporting on pizza Gate as though it was a real thing. 147 00:08:45,040 --> 00:08:48,559 Speaker 1: Sinclair Executive forced their stations to run pro Trump and 148 00:08:48,679 --> 00:08:53,560 Speaker 1: anti Clinton segments during their evening and morning local news programs. 149 00:08:53,640 --> 00:08:56,280 Speaker 1: It's just that this was the one that they sent 150 00:08:56,440 --> 00:08:59,280 Speaker 1: out that was a word for words script that they 151 00:08:59,360 --> 00:09:04,000 Speaker 1: had to read sort of uh, you know, casting expersions 152 00:09:04,160 --> 00:09:07,559 Speaker 1: on the national news that people got, which you know, 153 00:09:08,120 --> 00:09:10,120 Speaker 1: and a lot of anchors have problem with it because 154 00:09:10,120 --> 00:09:12,000 Speaker 1: they're like, this is not fucking like you know what 155 00:09:12,040 --> 00:09:14,400 Speaker 1: I mean, Like the few people that are left that 156 00:09:14,480 --> 00:09:18,240 Speaker 1: are like, this is fucked Like, we can't just be wholesale. 157 00:09:18,440 --> 00:09:20,880 Speaker 1: We're counting on our We're counting on our local run 158 00:09:21,000 --> 00:09:24,920 Speaker 1: burgundies like be the voice of reason and the Edward 159 00:09:25,000 --> 00:09:28,400 Speaker 1: Armorrows to stand up. That's amazing. Yeah, I cannot wait 160 00:09:28,520 --> 00:09:30,439 Speaker 1: for that. Like I want to see them March. I 161 00:09:30,520 --> 00:09:32,760 Speaker 1: want to see their strike. I want to see them 162 00:09:32,800 --> 00:09:38,920 Speaker 1: former union more at ten We're hell no, we won't go. Yeah, 163 00:09:39,160 --> 00:09:40,880 Speaker 1: we'll see if we're gonna have a sick and tired 164 00:09:40,920 --> 00:09:43,280 Speaker 1: and not gonna take it anymore moment coming out on 165 00:09:43,320 --> 00:09:47,439 Speaker 1: one of these broadcasts in December Kushner bragged that the 166 00:09:47,520 --> 00:09:51,000 Speaker 1: Trump campaign had struck a deal with Sinclair executives to 167 00:09:51,120 --> 00:09:55,160 Speaker 1: provide exclusive interviews during the primaries and presidential campaign, and 168 00:09:55,440 --> 00:09:59,600 Speaker 1: Sinclair agreed to run them as is without any commentary. Cool. 169 00:10:00,040 --> 00:10:03,240 Speaker 1: So yeah, so that one, there's one side for you, 170 00:10:03,480 --> 00:10:06,280 Speaker 1: if nothing else, that shows the power of Sinclair Media. 171 00:10:06,440 --> 00:10:09,880 Speaker 1: That clip, and based on what they've done in the past, 172 00:10:09,960 --> 00:10:14,480 Speaker 1: it's clearly going to be a problem for democracy. The 173 00:10:14,520 --> 00:10:16,640 Speaker 1: Trump I want to see it go as far right 174 00:10:16,679 --> 00:10:18,640 Speaker 1: as it can go. I want to see some fucking 175 00:10:18,960 --> 00:10:23,000 Speaker 1: you know dude named like Chuck mcgonicall just be like 176 00:10:23,480 --> 00:10:27,520 Speaker 1: now more with the weather. Here's a jew. It's just 177 00:10:27,679 --> 00:10:29,880 Speaker 1: like a guy dressed like a rabbi, Like just like 178 00:10:30,040 --> 00:10:33,040 Speaker 1: my rabbi from my bar was like, you know, I 179 00:10:33,320 --> 00:10:36,360 Speaker 1: I'm feeling because I can control it. I'm feeling right. 180 00:10:36,520 --> 00:10:40,480 Speaker 1: Tomorrows does about the chem trail report? Right, Oh, well, 181 00:10:40,520 --> 00:10:42,560 Speaker 1: we're putting him out there and we're making him make 182 00:10:42,640 --> 00:10:46,800 Speaker 1: you gay, So good luck. So that's a stay indoors 183 00:10:46,840 --> 00:10:53,120 Speaker 1: warning from weather Rabbi, the weather Jew. So yesterday there 184 00:10:53,440 --> 00:10:58,280 Speaker 1: was a active shooter on the YouTube campus in northern California. UM. 185 00:10:58,760 --> 00:11:01,880 Speaker 1: It was one of the those situations, where as the 186 00:11:01,920 --> 00:11:05,480 Speaker 1: story was developing, we were getting updates on Twitter about 187 00:11:05,640 --> 00:11:09,160 Speaker 1: you know, facts that people on the ground knew that 188 00:11:09,440 --> 00:11:12,240 Speaker 1: turned out to be completely false, that it was like 189 00:11:12,320 --> 00:11:14,640 Speaker 1: a love triangle thing. I think that was started by 190 00:11:14,720 --> 00:11:20,800 Speaker 1: CNNs like expert on uh something and uh, like the 191 00:11:21,000 --> 00:11:24,640 Speaker 1: front page of Drudge Report is covering this to make 192 00:11:24,720 --> 00:11:28,120 Speaker 1: it seem like the shooter, which was a woman for once, 193 00:11:29,240 --> 00:11:32,760 Speaker 1: was this like right when I heard about the actor shooter, 194 00:11:33,000 --> 00:11:35,360 Speaker 1: I was like, oh my god, like who isn't It's 195 00:11:35,360 --> 00:11:36,679 Speaker 1: like it's a woman. I was like, oh, so she 196 00:11:36,880 --> 00:11:42,480 Speaker 1: has got a reason. It was like instantly really right. Uh. 197 00:11:42,960 --> 00:11:45,880 Speaker 1: But so the way the right is responding to the 198 00:11:45,960 --> 00:11:48,839 Speaker 1: shooter is, uh, you know, on the front page of 199 00:11:48,920 --> 00:11:53,760 Speaker 1: Drudge you see it covered as both uh you know, 200 00:11:54,200 --> 00:11:57,520 Speaker 1: portraying her as this like freaky, deaky leftist who was 201 00:11:57,600 --> 00:12:03,040 Speaker 1: into weird sexual stuff and Peter like the quote on 202 00:12:03,160 --> 00:12:06,720 Speaker 1: the front page of drudges wants you to be sex slaves, 203 00:12:07,000 --> 00:12:10,960 Speaker 1: which she actually like advocates for abstinence. So I don't 204 00:12:11,400 --> 00:12:13,520 Speaker 1: see how that is they too, I think something out 205 00:12:13,520 --> 00:12:16,160 Speaker 1: of contexts the system wants you to be sex slaved 206 00:12:16,280 --> 00:12:18,400 Speaker 1: or something like that. But wants you to be sex 207 00:12:18,800 --> 00:12:21,920 Speaker 1: to make it seem like she was into some weird 208 00:12:22,120 --> 00:12:27,240 Speaker 1: leftist sexual thing, but no, she was actually pro abstinence. 209 00:12:28,200 --> 00:12:33,200 Speaker 1: But basically her motives, it seems like we're actually based 210 00:12:33,280 --> 00:12:38,679 Speaker 1: on YouTube. She thought that YouTube was you know, demonetizing 211 00:12:39,040 --> 00:12:42,400 Speaker 1: and hiding her channel from her audience and wasn't giving 212 00:12:42,440 --> 00:12:46,280 Speaker 1: her good enough placement in search results essentially, which is 213 00:12:46,520 --> 00:12:49,440 Speaker 1: a complaint that you hear people a lot of YouTube, Yeah, 214 00:12:49,520 --> 00:12:53,800 Speaker 1: from a lot of YouTube users. And uh, Incredibly, when 215 00:12:53,840 --> 00:12:56,320 Speaker 1: you go to the Drudge Report, one of the top 216 00:12:56,440 --> 00:13:03,800 Speaker 1: headlines basically agrees with her. It's like oppressive YouTube censorship 217 00:13:03,880 --> 00:13:07,760 Speaker 1: policies spill over to violence, so they're actually blaming YouTube 218 00:13:07,800 --> 00:13:10,800 Speaker 1: policies for the shooter rather than being like, well, she 219 00:13:11,000 --> 00:13:15,760 Speaker 1: was clearly disturbed. Um so, Jared, you were talking about 220 00:13:15,920 --> 00:13:18,160 Speaker 1: you wrote an article kind of covering the way this 221 00:13:18,640 --> 00:13:21,599 Speaker 1: was covered on the right because there was just a 222 00:13:21,720 --> 00:13:26,040 Speaker 1: lot of misinformation throughout the day, right, Yeah, and then 223 00:13:26,080 --> 00:13:28,040 Speaker 1: there's a lot of stuff just made up, like that 224 00:13:28,160 --> 00:13:33,120 Speaker 1: whole peda like animal rights activist thing. Like I was 225 00:13:33,280 --> 00:13:37,960 Speaker 1: kind of surprised. My girlfriend is vegan and I had 226 00:13:38,000 --> 00:13:43,319 Speaker 1: no idea she was like a radical leftist right until 227 00:13:43,400 --> 00:13:46,320 Speaker 1: I saw the right wing coverage. But what interesting thing 228 00:13:46,440 --> 00:13:48,280 Speaker 1: is like, even with the Drudge like you're saying, how 229 00:13:48,320 --> 00:13:50,800 Speaker 1: they're talking about they bring up the censorship angle, right, 230 00:13:51,080 --> 00:13:53,040 Speaker 1: And it seems like even when I was reading the 231 00:13:53,160 --> 00:13:55,720 Speaker 1: post you wrote today Jared about it, like how they're 232 00:13:55,760 --> 00:13:57,959 Speaker 1: sort of taking the censorship tak with this too, and 233 00:13:57,960 --> 00:13:59,880 Speaker 1: they're being like, see what happens when you censor people, 234 00:14:00,240 --> 00:14:02,760 Speaker 1: Like they break and they start attacking, and like they're 235 00:14:02,840 --> 00:14:05,880 Speaker 1: using like the hashtag censorship kills the sort of way 236 00:14:05,960 --> 00:14:08,480 Speaker 1: to spin it, Like is that a pretty popular tack 237 00:14:08,640 --> 00:14:10,800 Speaker 1: that people have been taking with this. I mean, it's 238 00:14:11,280 --> 00:14:15,320 Speaker 1: it's kind of weird, Like some people um in right 239 00:14:15,360 --> 00:14:18,880 Speaker 1: wing media have really sort of stepped away from going 240 00:14:18,960 --> 00:14:21,840 Speaker 1: on that angle, but a lot of them, uh, are 241 00:14:21,920 --> 00:14:24,920 Speaker 1: really going into it that, you know, really trying to 242 00:14:25,000 --> 00:14:30,280 Speaker 1: prop up the fact that the shooter had uploaded videos 243 00:14:30,560 --> 00:14:35,400 Speaker 1: on her channel being like super critical of YouTube steam 244 00:14:35,400 --> 00:14:43,840 Speaker 1: monetization and like essentially like d prioritization of videos that 245 00:14:44,120 --> 00:14:46,640 Speaker 1: had any sort of controversial topic, which has been like 246 00:14:46,680 --> 00:14:50,120 Speaker 1: a huge thing in conservative media for the last few months. 247 00:14:50,760 --> 00:14:53,440 Speaker 1: But that was kind of weird to me because you 248 00:14:53,520 --> 00:14:55,480 Speaker 1: know that Alex Jones Is of the World have spent 249 00:14:55,560 --> 00:14:58,920 Speaker 1: the last especially couple of months really ramping up the 250 00:14:58,960 --> 00:15:02,080 Speaker 1: red rick for that being like being like, oh, if 251 00:15:02,120 --> 00:15:05,360 Speaker 1: we're censored, this is life or fucking death or something, 252 00:15:05,440 --> 00:15:09,000 Speaker 1: you know, and like claiming that tech companies want to 253 00:15:09,040 --> 00:15:13,960 Speaker 1: like murder Christians and stuff. It's crazy would think that 254 00:15:14,040 --> 00:15:16,600 Speaker 1: they yeah, you would think they would just like bolt running, 255 00:15:17,000 --> 00:15:20,680 Speaker 1: yeah from that storyline, but they're actually being like, yeah, 256 00:15:20,760 --> 00:15:24,160 Speaker 1: this is what happens. Uh. That top story on Drudge 257 00:15:24,200 --> 00:15:28,760 Speaker 1: Report links through to a PJ Media story where there 258 00:15:29,080 --> 00:15:32,520 Speaker 1: they talk about how she was motivated by censorship of 259 00:15:32,640 --> 00:15:37,280 Speaker 1: her YouTube channel and then talk about a Trump supporting 260 00:15:37,640 --> 00:15:43,240 Speaker 1: woman whose channel was like hidden they say, and just yeah, 261 00:15:43,360 --> 00:15:47,720 Speaker 1: connecting themselves to the complaints of a shooter. Like rather 262 00:15:47,800 --> 00:15:49,880 Speaker 1: than being like, wow, this has gotten way out of hand, 263 00:15:50,280 --> 00:15:53,240 Speaker 1: they're just like kind of on board with it. Yeah. 264 00:15:53,280 --> 00:15:55,880 Speaker 1: And I think it's because like a lot of alternative 265 00:15:56,000 --> 00:16:00,640 Speaker 1: media types, like the type of content creators that like 266 00:16:00,960 --> 00:16:03,800 Speaker 1: will never be on Fox News or never be you know, 267 00:16:03,920 --> 00:16:06,320 Speaker 1: talking to Russia Limbaugh, all they have as a YouTube channel, 268 00:16:06,680 --> 00:16:09,600 Speaker 1: The thought of like getting demonetized on YouTube is so 269 00:16:10,280 --> 00:16:14,960 Speaker 1: it's their life, and uh, I think what we're seeing 270 00:16:15,080 --> 00:16:18,840 Speaker 1: is them getting incredibly desperate because it takes a lot 271 00:16:19,000 --> 00:16:22,320 Speaker 1: of mental gymnastics, is at least like from my perspective, 272 00:16:22,560 --> 00:16:26,080 Speaker 1: to align yourself with a shooter and sort of you know, 273 00:16:26,240 --> 00:16:30,240 Speaker 1: issue this sort of dark I don't want to say warning, 274 00:16:30,360 --> 00:16:33,400 Speaker 1: but you know what I mean, where is well there 275 00:16:33,440 --> 00:16:36,040 Speaker 1: is insisting that insisting like this is what you get 276 00:16:36,120 --> 00:16:39,480 Speaker 1: when you try to do this right. I mean, my 277 00:16:39,560 --> 00:16:44,160 Speaker 1: own YouTube videos have um, you know, dozens of hits 278 00:16:44,560 --> 00:16:46,800 Speaker 1: and um, you know, I don't have many subscribers, but 279 00:16:47,760 --> 00:16:50,960 Speaker 1: it makes me, it makes me have a murderous blood 280 00:16:51,040 --> 00:16:55,240 Speaker 1: lusts and that's totally justified. Totally yeah. I mean, your 281 00:16:55,360 --> 00:16:57,360 Speaker 1: art is your life, and they're trying to take away 282 00:16:57,400 --> 00:17:01,600 Speaker 1: your life and therefore, uh no, it one thing that 283 00:17:01,680 --> 00:17:05,560 Speaker 1: I actually agree with on the organization. By the way, 284 00:17:05,560 --> 00:17:08,520 Speaker 1: when I say Drudge has this, Drudge just organizes different 285 00:17:08,560 --> 00:17:11,000 Speaker 1: stories and then rewrites the headlines for them. So I'm 286 00:17:11,000 --> 00:17:13,920 Speaker 1: not saying Drudge is writing these things. He's organizing the stories, 287 00:17:14,760 --> 00:17:18,560 Speaker 1: but he has underneath, like the top story claiming you know, 288 00:17:19,040 --> 00:17:22,320 Speaker 1: this is YouTube's doing and they had it coming. He 289 00:17:22,440 --> 00:17:26,520 Speaker 1: has a story about how basically the two sides in 290 00:17:26,600 --> 00:17:30,000 Speaker 1: America are more polarized than they've ever been. This is 291 00:17:30,040 --> 00:17:32,800 Speaker 1: a claim by a physicist, which is something you hear 292 00:17:32,840 --> 00:17:36,000 Speaker 1: a lot, but this physicist, UH points out that we're 293 00:17:36,240 --> 00:17:40,280 Speaker 1: consuming more news than we've ever consumed before, and we're 294 00:17:40,359 --> 00:17:44,960 Speaker 1: getting more and more polarized, like even now, we're getting 295 00:17:45,000 --> 00:17:47,440 Speaker 1: more polarized than we were even like a couple of 296 00:17:47,520 --> 00:17:51,119 Speaker 1: months ago. And I think that really seems to be 297 00:17:51,280 --> 00:17:53,280 Speaker 1: I don't know, it seems like we've turned a corner. 298 00:17:53,400 --> 00:17:54,920 Speaker 1: Like we we were talking about the Q and on 299 00:17:55,080 --> 00:17:58,040 Speaker 1: thing being fringe, but there was just a study that 300 00:17:58,080 --> 00:18:01,480 Speaker 1: I talked about earlier this week where people ingested all 301 00:18:01,600 --> 00:18:05,240 Speaker 1: of Twitter from UH two thousand six to two sixteen 302 00:18:05,720 --> 00:18:08,359 Speaker 1: and looked at which stories traveled the most, and the 303 00:18:08,400 --> 00:18:11,159 Speaker 1: stories that were lies traveled the best because they were 304 00:18:11,240 --> 00:18:15,760 Speaker 1: wish fulfillment to people who, you know, wanted their beliefs confirmed. 305 00:18:16,080 --> 00:18:19,120 Speaker 1: And I just think that as we get more polarized, 306 00:18:19,359 --> 00:18:21,920 Speaker 1: the more we need fake stories to be true to 307 00:18:22,200 --> 00:18:27,600 Speaker 1: confirm our beliefs. So there's going to be this economy 308 00:18:27,960 --> 00:18:31,040 Speaker 1: of fake news stories that just kind of bubbles up 309 00:18:31,280 --> 00:18:36,159 Speaker 1: because that's what the sort of landscape demands. All Right, 310 00:18:36,200 --> 00:18:39,160 Speaker 1: We're gonna take a quick break and we'll be right back, 311 00:18:47,600 --> 00:18:52,399 Speaker 1: and we're back. The debate surrounding news I feel like 312 00:18:52,520 --> 00:18:56,720 Speaker 1: hasn't evolved with the world we now live in. I 313 00:18:56,800 --> 00:18:59,920 Speaker 1: think we still talk about stories and like whether they're 314 00:19:00,080 --> 00:19:03,159 Speaker 1: true or false, Like the Sinclair thing they were, like, 315 00:19:03,320 --> 00:19:06,160 Speaker 1: you know a lot of people have bias and tell 316 00:19:06,280 --> 00:19:09,600 Speaker 1: these fake stories just based on their bias, and um 317 00:19:10,119 --> 00:19:14,320 Speaker 1: So I've talked before about how nine eleven. The big 318 00:19:14,440 --> 00:19:18,560 Speaker 1: problem with our ability to stop the September eleventh attacks 319 00:19:19,000 --> 00:19:22,159 Speaker 1: and in the aftermath of the September eleventh attacks was 320 00:19:22,480 --> 00:19:26,639 Speaker 1: our ability to basically sort through all the data that 321 00:19:26,760 --> 00:19:30,639 Speaker 1: we had. Like during the Cold War, intelligence gathering was 322 00:19:30,680 --> 00:19:32,760 Speaker 1: a big thing. It was just like you got these 323 00:19:33,200 --> 00:19:36,840 Speaker 1: few scraps from your Russian spies and then like you 324 00:19:37,080 --> 00:19:40,240 Speaker 1: put them together into a coherent picture. And suddenly, with 325 00:19:40,359 --> 00:19:44,119 Speaker 1: the advent of like information technology, we had just fire 326 00:19:44,240 --> 00:19:46,760 Speaker 1: hoses of information coming at us, and we didn't know 327 00:19:46,920 --> 00:19:50,400 Speaker 1: how to sort through all that information. And that made 328 00:19:50,480 --> 00:19:54,040 Speaker 1: it so that we didn't get to the nine eleven 329 00:19:54,080 --> 00:19:56,960 Speaker 1: attackers before it happened, because we knew about that, Like 330 00:19:57,080 --> 00:19:59,480 Speaker 1: that was a story you heard in the aftermath, like 331 00:19:59,560 --> 00:20:02,400 Speaker 1: how did we knew about these people, but we didn't 332 00:20:02,440 --> 00:20:04,320 Speaker 1: stop them. It was because they were like one of 333 00:20:04,560 --> 00:20:08,600 Speaker 1: thousands of things we knew about. And I feel like 334 00:20:08,680 --> 00:20:12,439 Speaker 1: the same thing is happening with how we addressed news, 335 00:20:12,600 --> 00:20:15,880 Speaker 1: Like we have just all this news coming at us now, 336 00:20:16,240 --> 00:20:18,800 Speaker 1: and the question is not like whether some of it 337 00:20:19,000 --> 00:20:22,840 Speaker 1: is false or whether some of it is true all 338 00:20:22,920 --> 00:20:26,760 Speaker 1: the time, but rather like what we choose to focus on, 339 00:20:27,280 --> 00:20:30,399 Speaker 1: And like this story about the border caravan, you know, 340 00:20:30,600 --> 00:20:34,800 Speaker 1: people are focusing on this like it is this unprecedented 341 00:20:34,920 --> 00:20:39,240 Speaker 1: thing and it's something that's happened every year, and yes 342 00:20:39,320 --> 00:20:41,919 Speaker 1: it's happening, and yet like they're not making the story up, 343 00:20:42,240 --> 00:20:46,359 Speaker 1: but by focusing on it, they're misleading you. It's basically well, 344 00:20:46,359 --> 00:20:48,520 Speaker 1: and it's a story that is like we now have 345 00:20:48,600 --> 00:20:51,879 Speaker 1: a president where this kind of story is politically advantageous 346 00:20:51,880 --> 00:20:54,159 Speaker 1: to the president because he can weaponize and distort it 347 00:20:54,520 --> 00:20:57,280 Speaker 1: to evoke like this idea that like if it's you know, 348 00:20:57,359 --> 00:21:01,159 Speaker 1: other countries they have refugees arriving on boats and they're like, oh, 349 00:21:01,240 --> 00:21:03,840 Speaker 1: people are just crashing the shores and trying to get 350 00:21:03,840 --> 00:21:05,879 Speaker 1: in our country or or storming the gates of our 351 00:21:05,920 --> 00:21:07,880 Speaker 1: borders and things like that, and this is like kind 352 00:21:07,920 --> 00:21:10,280 Speaker 1: of that perfect imagery that he needs, and then he 353 00:21:10,320 --> 00:21:12,280 Speaker 1: can like pump his own dick up and be like, oh, 354 00:21:12,359 --> 00:21:14,720 Speaker 1: you know, I told Mexico to break up the caravans, 355 00:21:14,760 --> 00:21:16,400 Speaker 1: and they did because I told him, And now we'll 356 00:21:16,440 --> 00:21:18,879 Speaker 1: have the military there to fucking shoot people who are 357 00:21:18,880 --> 00:21:20,920 Speaker 1: seeking political sound like, what the funk are you going 358 00:21:20,960 --> 00:21:24,280 Speaker 1: on about? It's it's very weird. And I think another 359 00:21:24,400 --> 00:21:27,560 Speaker 1: reason too, is we also don't actually we just focus 360 00:21:27,680 --> 00:21:30,560 Speaker 1: on what is happening and not focusing on what is 361 00:21:30,680 --> 00:21:33,440 Speaker 1: the root cause. Right, So, like, if it's these migrants, 362 00:21:33,680 --> 00:21:36,359 Speaker 1: why don't you doing some more stories about Honduras and 363 00:21:36,560 --> 00:21:39,720 Speaker 1: what it is these people are trying to escape because 364 00:21:39,800 --> 00:21:42,399 Speaker 1: that might resonate or that might at least help people 365 00:21:42,560 --> 00:21:45,000 Speaker 1: understand the world we live in, because everything isn't just 366 00:21:45,320 --> 00:21:48,200 Speaker 1: what happened or what might happen this season on the 367 00:21:48,240 --> 00:21:50,720 Speaker 1: New Jersey Shore, which I am very much interested in, 368 00:21:50,840 --> 00:21:52,960 Speaker 1: but I also want to know why people are moving 369 00:21:53,040 --> 00:21:54,960 Speaker 1: and with the situations they're trying to escape. And I 370 00:21:55,000 --> 00:21:57,879 Speaker 1: think that's another way our media does betray us, or 371 00:21:58,000 --> 00:22:01,560 Speaker 1: as a disservice, is might not actually focusing on like, oh, well, 372 00:22:02,000 --> 00:22:04,760 Speaker 1: why is this happening, not just it is happening, just 373 00:22:04,840 --> 00:22:08,080 Speaker 1: being like oh that's and also overarching, like we need 374 00:22:08,119 --> 00:22:11,040 Speaker 1: to look at statistics, like just because the local news 375 00:22:11,160 --> 00:22:16,800 Speaker 1: reports a crime doesn't mean that there aren't fewer crimes happening. 376 00:22:16,920 --> 00:22:19,200 Speaker 1: Like crime is at an all time low, but the 377 00:22:19,280 --> 00:22:22,600 Speaker 1: way that people talk on Fox News and just looking 378 00:22:22,680 --> 00:22:25,440 Speaker 1: at your local news, you would never suspect that crime 379 00:22:25,560 --> 00:22:28,480 Speaker 1: is an all time low. Way, but it's at an 380 00:22:28,520 --> 00:22:30,240 Speaker 1: all time low, and it has been going down for 381 00:22:30,440 --> 00:22:34,280 Speaker 1: years because of you know a number of different factors 382 00:22:34,400 --> 00:22:37,880 Speaker 1: that people never mentioned, and they don't mention those overall 383 00:22:38,359 --> 00:22:43,720 Speaker 1: statistical trends because it's more interesting and just more consumable 384 00:22:43,840 --> 00:22:46,520 Speaker 1: to tell the bite size stories of the crimes. Right. 385 00:22:46,920 --> 00:22:48,760 Speaker 1: I feel like we've lost a lot of empathy in 386 00:22:48,840 --> 00:22:52,280 Speaker 1: this nation, and there's no focus on mental health. I 387 00:22:52,359 --> 00:22:54,199 Speaker 1: think like a lot of these like news channels, they 388 00:22:54,200 --> 00:22:58,200 Speaker 1: always yeah, I agree, like it's sensationalize is crime, but 389 00:22:58,600 --> 00:23:01,600 Speaker 1: some some people just need like mental health services. And 390 00:23:01,680 --> 00:23:04,360 Speaker 1: instead of just being like this is a crazy man, 391 00:23:04,520 --> 00:23:07,360 Speaker 1: like hey, wait, like someone who the system failed. Wait 392 00:23:07,440 --> 00:23:11,399 Speaker 1: a second, you know, yeah, man too brings that up, 393 00:23:11,560 --> 00:23:20,000 Speaker 1: you know, sensationalizing mental health, that's pretty deep when Kanye 394 00:23:20,119 --> 00:23:23,800 Speaker 1: came out. I mean, everything we're saying is basically summarizing 395 00:23:23,840 --> 00:23:26,000 Speaker 1: the points made an anchor man. They don't give away 396 00:23:26,000 --> 00:23:32,600 Speaker 1: the secret to our philosophical north star is little no effect. 397 00:23:32,840 --> 00:23:34,600 Speaker 1: But yeah, I think that's another reason too that we 398 00:23:35,200 --> 00:23:37,960 Speaker 1: we never really give people context, like we expect people 399 00:23:38,000 --> 00:23:40,120 Speaker 1: to already know or we have to explain to them, 400 00:23:40,160 --> 00:23:42,760 Speaker 1: like you know, especially when you think about how segregation 401 00:23:42,840 --> 00:23:45,320 Speaker 1: works in this country, A lot of people just go, oh, 402 00:23:45,600 --> 00:23:48,600 Speaker 1: like an unarmed black person was shot or whatever, and 403 00:23:49,080 --> 00:23:53,560 Speaker 1: not many people understand how through like legal segregation, through 404 00:23:53,600 --> 00:23:57,120 Speaker 1: like housing initiatives in this country and the highways. Yeah exactly, 405 00:23:57,400 --> 00:24:00,159 Speaker 1: we were redlining. We were making sure and and we 406 00:24:00,200 --> 00:24:02,320 Speaker 1: talked about this yesterday. But redlining was the practice of 407 00:24:02,400 --> 00:24:06,680 Speaker 1: identifying neighborhoods that were undesirable or where people would not 408 00:24:06,880 --> 00:24:10,440 Speaker 1: get loans and things, basically essentially to just say, keep 409 00:24:10,640 --> 00:24:14,000 Speaker 1: black people in these sections, or keep minorities in these neighborhoods, 410 00:24:14,080 --> 00:24:16,960 Speaker 1: and if they try and get out, just deny them 411 00:24:17,160 --> 00:24:19,240 Speaker 1: alone or give it at such a rate that it's 412 00:24:19,280 --> 00:24:24,359 Speaker 1: not really it's an untenable situation for them. And yeah, exactly, 413 00:24:24,600 --> 00:24:26,960 Speaker 1: And what people don't realize is that, like especially like 414 00:24:27,080 --> 00:24:29,440 Speaker 1: as a lot of black people migrated to the North 415 00:24:29,720 --> 00:24:31,879 Speaker 1: out of the South in the early twentieth century for like, 416 00:24:32,040 --> 00:24:34,880 Speaker 1: you know, industrial centers like my grandparents did. They moved 417 00:24:34,880 --> 00:24:39,200 Speaker 1: to Chicago from the South, Chicago the Dan Ryan and 418 00:24:39,720 --> 00:24:42,320 Speaker 1: in those neighborhoods. The way they were dealing with this 419 00:24:42,480 --> 00:24:45,200 Speaker 1: influx of of people of color was, you know, they've 420 00:24:45,320 --> 00:24:49,440 Speaker 1: just created these very distinct neighborhoods that they segregated people. 421 00:24:49,480 --> 00:24:52,159 Speaker 1: And the segregation is much more intense. Like you think, oh, 422 00:24:52,440 --> 00:24:54,080 Speaker 1: in the South, it must be crazy. No, it's actually 423 00:24:54,119 --> 00:24:55,960 Speaker 1: like the Northeast and ship and some in the in 424 00:24:56,040 --> 00:24:58,879 Speaker 1: the Midwest, that's where it's the most pronounced. This American 425 00:24:58,960 --> 00:25:03,840 Speaker 1: Life did under cover story where they sent people. They 426 00:25:03,920 --> 00:25:07,640 Speaker 1: send people to enquire about apartments in New York City, 427 00:25:08,080 --> 00:25:12,280 Speaker 1: and it was white couple and then a black couple. 428 00:25:12,640 --> 00:25:15,399 Speaker 1: And they would go and the black couple had better credit, 429 00:25:15,600 --> 00:25:19,359 Speaker 1: better all the things that the landlord was supposed to 430 00:25:19,400 --> 00:25:22,440 Speaker 1: be looking for, and they would be turned away and 431 00:25:22,480 --> 00:25:25,080 Speaker 1: the white couple would be shown the apartment and basically 432 00:25:25,520 --> 00:25:28,440 Speaker 1: courted to go there. And so that's the way that 433 00:25:28,520 --> 00:25:30,959 Speaker 1: these things are enforced. It's like sort of a soft 434 00:25:31,480 --> 00:25:34,880 Speaker 1: form of segregation where it or like an invisible form 435 00:25:34,920 --> 00:25:37,360 Speaker 1: of segregation. It's not soft in the sense that it's 436 00:25:37,359 --> 00:25:39,560 Speaker 1: easy to get around well, and people who don't realize, 437 00:25:39,560 --> 00:25:41,400 Speaker 1: they're like, oh, those people are just poor and that's 438 00:25:41,400 --> 00:25:43,159 Speaker 1: why they live there. It's like, no, that area is 439 00:25:43,200 --> 00:25:45,560 Speaker 1: designed to keep people in there and not coming into 440 00:25:45,600 --> 00:25:49,080 Speaker 1: other areas, because whether it's like blockbusting practices or like 441 00:25:49,359 --> 00:25:51,399 Speaker 1: black people would begin to move into white places, and 442 00:25:51,480 --> 00:25:54,880 Speaker 1: those realtors would hire black people to create this illusion 443 00:25:54,960 --> 00:25:57,159 Speaker 1: of like a black takeover and like being like, hey, 444 00:25:57,160 --> 00:25:58,560 Speaker 1: you probably want like to a white family, Hey, you 445 00:25:58,640 --> 00:26:01,040 Speaker 1: probably want to sell your home, and then jack up 446 00:26:01,080 --> 00:26:03,399 Speaker 1: the price for a black family to buy that home. Also, 447 00:26:03,600 --> 00:26:07,040 Speaker 1: like you also think about how schools and services get funded. 448 00:26:07,160 --> 00:26:08,959 Speaker 1: A lot of it's from property taxes too, So if 449 00:26:08,960 --> 00:26:11,080 Speaker 1: you're in the hood, there's not a lot of tax 450 00:26:11,160 --> 00:26:13,600 Speaker 1: revenue being generated, so that means the schools are underfunded. 451 00:26:13,800 --> 00:26:16,159 Speaker 1: That means the schools get more segregated. And again we 452 00:26:16,320 --> 00:26:18,960 Speaker 1: just want to act like it's it's all these other things. Again, 453 00:26:19,040 --> 00:26:21,000 Speaker 1: I think a lot of the times when we present stories, 454 00:26:21,200 --> 00:26:23,440 Speaker 1: people don't fully understand the context of even how we 455 00:26:23,560 --> 00:26:25,280 Speaker 1: get the situation. And like, one other point I want 456 00:26:25,320 --> 00:26:28,080 Speaker 1: to bring up is that, like one theory that is 457 00:26:28,119 --> 00:26:31,160 Speaker 1: going around is that obviously not it's like the theory, 458 00:26:31,240 --> 00:26:32,480 Speaker 1: but you know a lot of people are sort of like, 459 00:26:32,600 --> 00:26:36,120 Speaker 1: why does you know black white segregation have any kind 460 00:26:36,160 --> 00:26:38,639 Speaker 1: of bearing or influence on fatal police shootings? What's that 461 00:26:38,720 --> 00:26:42,560 Speaker 1: segregated Black communities are just more heavily policed than others. 462 00:26:43,160 --> 00:26:45,840 Speaker 1: And in a study from thirteen showed that in Milwaukee 463 00:26:46,240 --> 00:26:50,520 Speaker 1: in Wisconsin has the highest like sort of like racism 464 00:26:50,680 --> 00:26:53,840 Speaker 1: racial index. Uh. It's it's a state racism index where 465 00:26:53,840 --> 00:26:57,480 Speaker 1: it basically takes uh it looks at things like residential segregation, 466 00:26:57,760 --> 00:27:03,199 Speaker 1: disparities and educational attainment and employment status, economic status, incarceration status. Uh, 467 00:27:03,280 --> 00:27:06,480 Speaker 1: and they score each of these Wisconsin tops the list 468 00:27:06,560 --> 00:27:08,400 Speaker 1: for all of these for when you when they factor 469 00:27:08,440 --> 00:27:11,040 Speaker 1: all these things in and when they looked at Milwaukee specifically, 470 00:27:11,320 --> 00:27:14,080 Speaker 1: the state's largest city, half of black men between the 471 00:27:14,119 --> 00:27:16,399 Speaker 1: ages thirty and forty have been in jail at some 472 00:27:16,480 --> 00:27:18,720 Speaker 1: point in their lives and the city zip code five 473 00:27:18,800 --> 00:27:22,560 Speaker 1: three two oh six black and has the highest incarceration 474 00:27:22,720 --> 00:27:26,280 Speaker 1: rate like anything in any county there. So basically what 475 00:27:26,400 --> 00:27:29,320 Speaker 1: happens is the more segregated a place becomes your only 476 00:27:29,440 --> 00:27:31,920 Speaker 1: underlying people's biases that are fed by the news. Where 477 00:27:31,920 --> 00:27:33,680 Speaker 1: if you if you think, oh, you're only showing news 478 00:27:33,760 --> 00:27:36,600 Speaker 1: about people of color or like the violence being bad 479 00:27:36,680 --> 00:27:40,240 Speaker 1: in like uh in these neighborhoods, then immediately the police 480 00:27:40,280 --> 00:27:41,440 Speaker 1: are going to be like, oh, well, now I'm in 481 00:27:41,480 --> 00:27:44,000 Speaker 1: a black neighborhood. I'm not in oh I deal with 482 00:27:44,119 --> 00:27:46,159 Speaker 1: regular people who might not have to get shot. I'm 483 00:27:46,240 --> 00:27:48,679 Speaker 1: immediately on the defense because now I'm in this crazy thing. 484 00:27:48,720 --> 00:27:51,040 Speaker 1: And like there's all these subtle factors all play into 485 00:27:51,080 --> 00:27:53,320 Speaker 1: sort of how we relate to the world. And yeah, 486 00:27:53,320 --> 00:27:55,800 Speaker 1: I think it's a very important thing for people to 487 00:27:55,920 --> 00:27:58,159 Speaker 1: kind of realize all of these stories have much more 488 00:27:58,240 --> 00:28:00,800 Speaker 1: complex context. I feel like that's really like I lived 489 00:28:00,840 --> 00:28:03,080 Speaker 1: in Chicago for about ten years before I moved out here, 490 00:28:03,400 --> 00:28:07,320 Speaker 1: and like Rama Manual is just systematically shutting down schools 491 00:28:07,480 --> 00:28:10,040 Speaker 1: like an impoverish neighborhoods, and then I just pulled it up, 492 00:28:10,160 --> 00:28:13,720 Speaker 1: like Chicago closes more schools and black neighborhood Chicago students 493 00:28:13,800 --> 00:28:16,040 Speaker 1: had budget cuts. It's all of this stuff, like and 494 00:28:16,119 --> 00:28:18,399 Speaker 1: then there are these like some of my friends were teachers, 495 00:28:18,440 --> 00:28:19,480 Speaker 1: and I don't know if this is true or not, 496 00:28:19,520 --> 00:28:22,399 Speaker 1: but they were telling me that um Ram had this 497 00:28:22,520 --> 00:28:25,000 Speaker 1: like initiative of like, look, we're building new schools and 498 00:28:25,040 --> 00:28:27,680 Speaker 1: new charter schools, but these schools were empty because he 499 00:28:27,760 --> 00:28:31,200 Speaker 1: was adding them in neighborhoods that didn't need them, or 500 00:28:31,359 --> 00:28:35,520 Speaker 1: like prominent neighborhoods where like neighborhoods on the West Side 501 00:28:35,640 --> 00:28:37,639 Speaker 1: or even the south side, and and some up in 502 00:28:37,680 --> 00:28:40,080 Speaker 1: the north like an uptown where you really needed it, 503 00:28:40,360 --> 00:28:43,640 Speaker 1: they weren't getting them and he was just shutting them down. Yeah, 504 00:28:43,720 --> 00:28:47,720 Speaker 1: I mean, and in Chicago, like a story that I 505 00:28:48,120 --> 00:28:51,440 Speaker 1: hadn't really connected to the current spade of violence and 506 00:28:51,760 --> 00:28:55,240 Speaker 1: murder was that they shut the Cabrini Green housing project 507 00:28:55,360 --> 00:28:57,880 Speaker 1: down like a number of years ago, and that was 508 00:28:57,920 --> 00:29:01,960 Speaker 1: a high crime area, but they basically turned it into 509 00:29:02,280 --> 00:29:06,160 Speaker 1: high income a living area and didn't give all the 510 00:29:06,520 --> 00:29:08,840 Speaker 1: poor people who had lived there before a place to go. 511 00:29:09,200 --> 00:29:13,920 Speaker 1: So like that created just a horrible Yeah. So I 512 00:29:14,000 --> 00:29:16,640 Speaker 1: don't know, these are, uh, we're kind of all over 513 00:29:16,680 --> 00:29:18,400 Speaker 1: the map, but I do just want to talk about 514 00:29:18,440 --> 00:29:21,560 Speaker 1: Jeff Bezos. You're just listening in Jeff Bezos. It was 515 00:29:21,560 --> 00:29:26,880 Speaker 1: a problem Jeff, he started this whole thing. But I 516 00:29:27,000 --> 00:29:29,640 Speaker 1: do think, you know, it's important to keep in mind 517 00:29:29,800 --> 00:29:33,680 Speaker 1: that the our role as news consumers is not just 518 00:29:33,800 --> 00:29:37,680 Speaker 1: to look at individual stories and determine, you know, whether 519 00:29:37,800 --> 00:29:41,920 Speaker 1: they're true or not, but to actually find the context. 520 00:29:42,040 --> 00:29:45,680 Speaker 1: And you know, the Redlining story is a story that 521 00:29:45,920 --> 00:29:48,960 Speaker 1: I just learned about on that this American Life episode 522 00:29:49,000 --> 00:29:53,440 Speaker 1: like four or five years ago, and I believe that 523 00:29:53,880 --> 00:29:56,600 Speaker 1: I couldn't believe that I hadn't been told that that's 524 00:29:56,640 --> 00:29:59,840 Speaker 1: like the most important story of the twentieth century when 525 00:29:59,840 --> 00:30:02,720 Speaker 1: it us to like how American life has lived in 526 00:30:03,400 --> 00:30:06,040 Speaker 1: the current world, and it puts all these different things 527 00:30:06,120 --> 00:30:09,040 Speaker 1: in perspective. But it's not talked about talked about you 528 00:30:09,080 --> 00:30:13,080 Speaker 1: but I think we're now coming into a world where 529 00:30:13,400 --> 00:30:16,480 Speaker 1: we have access to all this different information, and you know, 530 00:30:16,680 --> 00:30:21,120 Speaker 1: this new generation has the ability to, you know, find 531 00:30:21,280 --> 00:30:24,240 Speaker 1: those important stories and tell those important stories. I've seen 532 00:30:24,240 --> 00:30:26,480 Speaker 1: a lot of people, a lot of zeitgangers out there 533 00:30:26,520 --> 00:30:28,840 Speaker 1: doing the good work and telling people about the British 534 00:30:28,880 --> 00:30:33,720 Speaker 1: Cold Guest study, either in the context of the gun conversation, 535 00:30:33,960 --> 00:30:36,640 Speaker 1: and you know, Redlining is another one of those stories 536 00:30:36,760 --> 00:30:40,280 Speaker 1: that is it's like a Keystone. It's when we got 537 00:30:40,400 --> 00:30:42,320 Speaker 1: to get into Coole Hannah Jones on this show. Right, 538 00:30:42,360 --> 00:30:46,440 Speaker 1: we really do, but she's amazing. But yeah, again I 539 00:30:46,520 --> 00:30:50,000 Speaker 1: think we we do definitely do people disservice, not like 540 00:30:50,080 --> 00:30:51,880 Speaker 1: we as a show, but just at the people, and 541 00:30:51,960 --> 00:30:54,880 Speaker 1: you like journalists by not at least telling people why 542 00:30:55,000 --> 00:30:57,920 Speaker 1: like sure, there's a caravan, right, but also explain to 543 00:30:57,960 --> 00:31:02,640 Speaker 1: people why there's this caravan, like celebrate there's just big 544 00:31:02,680 --> 00:31:04,840 Speaker 1: fans of Dodge. It's actually being paid for by Chrysler. 545 00:31:05,160 --> 00:31:08,200 Speaker 1: Check out this caravan. Huh. They're running from something, they 546 00:31:08,280 --> 00:31:11,080 Speaker 1: need help from something, and it's weird because again, you know, 547 00:31:11,160 --> 00:31:12,960 Speaker 1: there was like this Netflix show we brought up called 548 00:31:13,040 --> 00:31:14,360 Speaker 1: Go Back To Where You Came From. It's like an 549 00:31:14,400 --> 00:31:16,720 Speaker 1: Australian reality show where a lot of like sort of 550 00:31:16,800 --> 00:31:21,240 Speaker 1: anti immigrants, xenophobic people had to actually understand where the 551 00:31:21,320 --> 00:31:23,600 Speaker 1: refugees were coming from and what they were escaping, and 552 00:31:23,720 --> 00:31:26,760 Speaker 1: many people, oh, it started to click for them because 553 00:31:27,240 --> 00:31:29,640 Speaker 1: you know, when you're that in proximity of truth, like 554 00:31:29,760 --> 00:31:32,760 Speaker 1: you can't deny them and then you instantly oh shit, okay, 555 00:31:32,800 --> 00:31:35,320 Speaker 1: I get it. There were also like stories about um 556 00:31:35,560 --> 00:31:37,960 Speaker 1: when Ice was coming into town, like especially like small 557 00:31:38,040 --> 00:31:42,680 Speaker 1: Texas towns, like it was like a meat manufacturing town, 558 00:31:42,800 --> 00:31:47,640 Speaker 1: Like that's like a slaughterhouse town. And um, people they 559 00:31:47,680 --> 00:31:50,560 Speaker 1: had worked with for years decades all of a sudden 560 00:31:50,680 --> 00:31:54,360 Speaker 1: gone and then the like town locals, We're like, oh 561 00:31:54,440 --> 00:31:57,680 Speaker 1: my god, where did this person go? He was deported? No, 562 00:31:57,800 --> 00:31:59,840 Speaker 1: they they're only supposed to do the bad guys and 563 00:32:00,440 --> 00:32:03,280 Speaker 1: not realizing like this is going to affect everything and 564 00:32:03,360 --> 00:32:05,600 Speaker 1: people you know and people you care about. But it's 565 00:32:05,640 --> 00:32:07,959 Speaker 1: like that context of like we're keeping the wall up 566 00:32:08,040 --> 00:32:09,880 Speaker 1: to keep the bad womans out. It's easy to say 567 00:32:09,880 --> 00:32:12,040 Speaker 1: that in the Middle America, where you probably don't have 568 00:32:12,200 --> 00:32:15,720 Speaker 1: much interaction with people like immigrants, or or have firsthand 569 00:32:15,840 --> 00:32:18,560 Speaker 1: experience with the outside world or just you know, my 570 00:32:18,680 --> 00:32:21,480 Speaker 1: community was very insular. It was like the first time 571 00:32:21,520 --> 00:32:23,640 Speaker 1: I had Thai food was when I moved to Chicago. 572 00:32:23,800 --> 00:32:25,240 Speaker 1: I had no idea what it was, and he thought 573 00:32:25,240 --> 00:32:27,320 Speaker 1: it was shitty Chinese. I was like, what are these 574 00:32:27,400 --> 00:32:32,040 Speaker 1: noodles are? But it was like everybody was like Christian 575 00:32:32,320 --> 00:32:34,520 Speaker 1: a Christians, so like for a very long time, I 576 00:32:34,640 --> 00:32:37,800 Speaker 1: was like ignorant on like Judaism and like understand like 577 00:32:37,840 --> 00:32:39,760 Speaker 1: some of my friends were like oh, this is a 578 00:32:39,880 --> 00:32:41,880 Speaker 1: very Jewish holiday, and I was like, what does that mean? 579 00:32:42,040 --> 00:32:47,480 Speaker 1: You know, you may even Jesus Christ. Look how small 580 00:32:47,560 --> 00:32:50,680 Speaker 1: that fellas had come here. You're gonna want to see this, 581 00:32:50,800 --> 00:32:57,080 Speaker 1: mom and dad. They wear these little things. And I 582 00:32:57,160 --> 00:33:00,360 Speaker 1: wanted to start out talking about the Maler investigation because 583 00:33:00,440 --> 00:33:05,600 Speaker 1: we talked about this story that broke in the Washington 584 00:33:05,680 --> 00:33:08,040 Speaker 1: Post a few days back, the one that said that 585 00:33:08,200 --> 00:33:12,880 Speaker 1: Trump is not a target of a criminal investigation. He 586 00:33:13,080 --> 00:33:16,560 Speaker 1: is a subject. So he's like somehow involved. He's not 587 00:33:16,680 --> 00:33:20,280 Speaker 1: a witness, which is the most innocent, uh sort of 588 00:33:20,360 --> 00:33:23,280 Speaker 1: way you can be involved in an investigation, but he's 589 00:33:23,280 --> 00:33:28,280 Speaker 1: also not the target. Uh. And the immediate reaction to 590 00:33:28,560 --> 00:33:32,880 Speaker 1: that among sort of the mainstream media for the most part, 591 00:33:33,600 --> 00:33:38,080 Speaker 1: was that Mueller is sort of slow rolling this, trying 592 00:33:38,200 --> 00:33:44,240 Speaker 1: to you know, draw Trump into a interview, and that, 593 00:33:45,080 --> 00:33:47,240 Speaker 1: uh is what That's what we reported. We were like, yeah, 594 00:33:47,320 --> 00:33:50,000 Speaker 1: so that that must be what it is. But the 595 00:33:50,120 --> 00:33:52,880 Speaker 1: more you think about it, and I actually read an 596 00:33:52,960 --> 00:33:56,360 Speaker 1: article on the Hill from a law professor at I 597 00:33:56,440 --> 00:34:01,520 Speaker 1: think George Washington, who who I thought for a second, like, 598 00:34:01,600 --> 00:34:03,160 Speaker 1: after I read it, I was like, this must be 599 00:34:03,200 --> 00:34:05,520 Speaker 1: a Fox News talking ahead because he was like, when 600 00:34:05,680 --> 00:34:08,640 Speaker 1: is the media going to accept that Trump is not 601 00:34:09,480 --> 00:34:12,440 Speaker 1: a criminal target, that like the Muller investigation might not 602 00:34:12,600 --> 00:34:14,520 Speaker 1: go the way they think it's going to go. He 603 00:34:14,719 --> 00:34:18,840 Speaker 1: might not get caught up in this thing. Um. And 604 00:34:20,040 --> 00:34:22,160 Speaker 1: you know, I I looked this guy up. I was 605 00:34:22,200 --> 00:34:25,680 Speaker 1: expecting him to be like Sean Hannity's main legal expert, 606 00:34:26,440 --> 00:34:31,279 Speaker 1: but he is just a liberal law school person. Uh 607 00:34:31,560 --> 00:34:33,440 Speaker 1: that I guess. I guess he has written some weird 608 00:34:33,480 --> 00:34:36,040 Speaker 1: problematic stuff, Miles, you were pointing out is another weird 609 00:34:36,080 --> 00:34:38,719 Speaker 1: blog post. But I mean, I get the article has 610 00:34:38,760 --> 00:34:41,000 Speaker 1: written pretty you know, a politically just sort of like 611 00:34:41,080 --> 00:34:43,920 Speaker 1: trying to look at Look, there's not a lot adding 612 00:34:44,040 --> 00:34:46,279 Speaker 1: up so far. And this is the thing I think 613 00:34:46,400 --> 00:34:48,960 Speaker 1: even since the beginning, like whenever, you know, when we've 614 00:34:48,960 --> 00:34:50,640 Speaker 1: talked about should we talk about this thing and the 615 00:34:50,680 --> 00:34:52,759 Speaker 1: mother thing or not, like we've always kind of just 616 00:34:53,040 --> 00:34:56,160 Speaker 1: said on and off Mike that it's like this. A 617 00:34:56,239 --> 00:34:57,719 Speaker 1: lot of people are putting a lot of their eggs 618 00:34:57,760 --> 00:35:00,440 Speaker 1: in the basket because this is like the one logical 619 00:35:00,640 --> 00:35:03,839 Speaker 1: thing that could bring a conclusion that people would want 620 00:35:04,320 --> 00:35:06,520 Speaker 1: in terms of like some kind of karmic justice and 621 00:35:06,600 --> 00:35:09,920 Speaker 1: also kind of invalidate two thousand sixteen, which people are 622 00:35:10,000 --> 00:35:12,880 Speaker 1: still that's like a wound that people are still you know, 623 00:35:13,160 --> 00:35:15,879 Speaker 1: dealing with, right, So I get what the point he's 624 00:35:15,920 --> 00:35:17,840 Speaker 1: making of just sort of like yeah, because you know, 625 00:35:18,160 --> 00:35:19,719 Speaker 1: he brings up a lot of points, like people on 626 00:35:19,840 --> 00:35:22,160 Speaker 1: seeing them just like oh man, he's totally fucked or whatever. 627 00:35:22,239 --> 00:35:24,560 Speaker 1: And yeah, and even yesterday we were whenever that was 628 00:35:24,600 --> 00:35:26,200 Speaker 1: maybe the day before, I don't know, times a blur, 629 00:35:26,640 --> 00:35:28,560 Speaker 1: uh that you know, we were saying you can go 630 00:35:28,680 --> 00:35:31,960 Speaker 1: from a subject to a target to that's still the case. 631 00:35:32,120 --> 00:35:34,279 Speaker 1: That's still the case. That's not the main takeaway. That 632 00:35:34,320 --> 00:35:37,440 Speaker 1: shouldn't be your first instinct. And like, there were no 633 00:35:37,640 --> 00:35:42,080 Speaker 1: stories in the immediate aftermath of this revelation in the 634 00:35:42,160 --> 00:35:44,400 Speaker 1: Washington Poster in the New York Times that said what 635 00:35:44,520 --> 00:35:46,759 Speaker 1: this guy was saying, which is this is really good 636 00:35:46,840 --> 00:35:50,200 Speaker 1: news for Trump. This seems to suggest, Okay, if they 637 00:35:50,239 --> 00:35:52,440 Speaker 1: had said he was a subject but not a target 638 00:35:52,880 --> 00:35:57,040 Speaker 1: like when the investigation was starting, that wouldn't have been 639 00:35:57,560 --> 00:35:59,759 Speaker 1: like a good or a bad thing, because you know, 640 00:36:00,360 --> 00:36:03,120 Speaker 1: but he's been investigating him for like over a year 641 00:36:03,239 --> 00:36:07,760 Speaker 1: now and he still hasn't found anything that immediately ties 642 00:36:07,880 --> 00:36:10,680 Speaker 1: him to the crime. That's not to say that he 643 00:36:10,840 --> 00:36:13,080 Speaker 1: didn't commit a crime, and there's certainly a lot of 644 00:36:13,160 --> 00:36:17,240 Speaker 1: smoke there, but it just might be that they aren't 645 00:36:17,239 --> 00:36:19,319 Speaker 1: gonna be able to find the evidence right, or it's 646 00:36:19,320 --> 00:36:20,960 Speaker 1: just a bunch of people around him, we're doing the 647 00:36:21,000 --> 00:36:23,440 Speaker 1: crimes right, you know. I feel like it is like 648 00:36:23,760 --> 00:36:26,560 Speaker 1: at this point, the Maller investigation does or sort of 649 00:36:26,600 --> 00:36:29,160 Speaker 1: feel like when you're like trying to like undo a 650 00:36:29,239 --> 00:36:31,720 Speaker 1: breakup or something. You're like, well, maybe if this happens 651 00:36:31,840 --> 00:36:33,560 Speaker 1: at the work and then and then it's like that 652 00:36:33,640 --> 00:36:35,520 Speaker 1: doesn't work, You're like, well, maybe if I do this, 653 00:36:35,760 --> 00:36:37,440 Speaker 1: this will work. And it's been going on for so 654 00:36:37,560 --> 00:36:40,719 Speaker 1: long it's like, I mean not that we should just 655 00:36:40,920 --> 00:36:44,320 Speaker 1: accept that Trump is I mean, absolutely not, but it 656 00:36:44,440 --> 00:36:47,120 Speaker 1: does seem like, you know, every time there's a new thing, 657 00:36:47,200 --> 00:36:49,399 Speaker 1: it's like we're kind of grasping at a straw there, 658 00:36:49,520 --> 00:36:51,680 Speaker 1: and then that doesn't go through, and then it's another thing. Yeah. 659 00:36:51,680 --> 00:36:53,759 Speaker 1: I mean, the sexiest thing has been like indictments of 660 00:36:53,800 --> 00:36:56,800 Speaker 1: people like Paul Manafort, but even the Russians were like whatever, 661 00:36:56,880 --> 00:36:58,560 Speaker 1: those are people that they just found like fraud and 662 00:36:58,600 --> 00:37:00,640 Speaker 1: other things like that. But I think at the end 663 00:37:00,680 --> 00:37:04,160 Speaker 1: of the day. It's it's hard to speculate either direction, right, Like, 664 00:37:04,280 --> 00:37:06,480 Speaker 1: there's not enough for you to be like, oh nothing, 665 00:37:06,640 --> 00:37:09,239 Speaker 1: like like guys come off it. And there's also not 666 00:37:09,480 --> 00:37:11,880 Speaker 1: enough also to be just nutting yourself when you're like 667 00:37:15,280 --> 00:37:17,279 Speaker 1: so yeah, I think it really all depends on how 668 00:37:17,320 --> 00:37:22,040 Speaker 1: you look. I'm just so hesitant because this dude, Like, honestly, 669 00:37:22,920 --> 00:37:24,920 Speaker 1: I don't know what will stick to this guy that 670 00:37:25,080 --> 00:37:27,600 Speaker 1: will get get even the Republicans in the House to 671 00:37:27,920 --> 00:37:31,239 Speaker 1: say like even a bad thing about him. So regardless 672 00:37:31,280 --> 00:37:33,319 Speaker 1: of this, if you really want to go to sleep 673 00:37:33,360 --> 00:37:35,120 Speaker 1: at night and and give yourself a north star to 674 00:37:35,200 --> 00:37:38,360 Speaker 1: live by, focus on the midterms, and just work on 675 00:37:38,560 --> 00:37:40,719 Speaker 1: just taking back the House in the Senate like that, 676 00:37:40,960 --> 00:37:43,720 Speaker 1: that's that's really how you're going to curb his power. 677 00:37:43,960 --> 00:37:46,720 Speaker 1: Human beings can actually do stuff. Yeah, because Bobby Digital 678 00:37:46,800 --> 00:37:50,520 Speaker 1: is not going to come through and be like that 679 00:37:50,640 --> 00:37:53,960 Speaker 1: was my rismation. By the way, it would have been 680 00:37:54,000 --> 00:37:58,239 Speaker 1: another when when when the switch to Bobby Digital for 681 00:37:58,280 --> 00:38:05,000 Speaker 1: that one album? What about Bobby Muller or Bobby Okay, Mary, 682 00:38:06,480 --> 00:38:15,400 Speaker 1: Bobby Mueller, Bobby Durst. I know you you want to 683 00:38:15,440 --> 00:38:17,960 Speaker 1: marry Robert Durst because that was a handle. I think 684 00:38:18,000 --> 00:38:20,640 Speaker 1: you were explaining Durst is too long and fortune or 685 00:38:20,719 --> 00:38:23,640 Speaker 1: Durst three. I think three would have been a dope one. 686 00:38:23,840 --> 00:38:26,680 Speaker 1: I will say that, yes, I would marry Robert Durst. 687 00:38:27,280 --> 00:38:29,920 Speaker 1: Moving on, well, just because I want to die, just 688 00:38:29,960 --> 00:38:32,040 Speaker 1: because I'm looking to die, an efficient way to go. 689 00:38:32,280 --> 00:38:34,040 Speaker 1: All right, We're going to take a quick break. We'll 690 00:38:34,080 --> 00:38:45,360 Speaker 1: be right bat and we're back. We wanted to finally 691 00:38:45,640 --> 00:38:50,320 Speaker 1: cover the story of one of the good people teaching 692 00:38:50,400 --> 00:38:54,600 Speaker 1: our children, uh, doing the Lord's work down in Florida. 693 00:38:54,960 --> 00:38:58,640 Speaker 1: UM what her name is Di and she is a 694 00:38:58,680 --> 00:39:02,560 Speaker 1: social studies teacher at Chris River Middle School UH in Florida. 695 00:39:03,080 --> 00:39:09,080 Speaker 1: And she was known online as Kiana Dalachov, which is 696 00:39:09,480 --> 00:39:14,840 Speaker 1: the pseudonymous host of a white supremacist podcast called Unapologetic, 697 00:39:15,320 --> 00:39:19,800 Speaker 1: where she talked some crazy shit about race science and 698 00:39:20,760 --> 00:39:26,360 Speaker 1: uh just everything anti semitis there. The crazy thing was, 699 00:39:26,560 --> 00:39:30,160 Speaker 1: I think HuffPo outed her like March eight, and her 700 00:39:30,280 --> 00:39:35,000 Speaker 1: defense was all my comments that were quote political satire 701 00:39:35,160 --> 00:39:39,680 Speaker 1: and exaggeration, and the persona was a quote unquote hobby. 702 00:39:40,200 --> 00:39:43,320 Speaker 1: I'm a part time racist. I'm a I'm a hobbyist. 703 00:39:43,400 --> 00:39:46,920 Speaker 1: Race I got a hobby. Lobby actually is the lobby 704 00:39:46,960 --> 00:39:50,279 Speaker 1: store of racist exactly, and I worked there, and she 705 00:39:50,520 --> 00:39:52,480 Speaker 1: was also bragging like on her show, like she was like, 706 00:39:52,520 --> 00:39:54,759 Speaker 1: you know, I'm a teacher and I actually inject all 707 00:39:54,800 --> 00:39:56,879 Speaker 1: this ship into my teachings and things like I don't 708 00:39:57,000 --> 00:40:00,800 Speaker 1: know it. Yeah, they just don't fucking realize frequency. And 709 00:40:00,920 --> 00:40:04,279 Speaker 1: so basically you know that did not, uh sort of 710 00:40:04,440 --> 00:40:07,960 Speaker 1: rub parents the school district the right way, and she 711 00:40:08,160 --> 00:40:13,440 Speaker 1: only finally today resigned after much pressure. So we will 712 00:40:13,480 --> 00:40:15,839 Speaker 1: see what happens. But it's crazy, Like just to give 713 00:40:15,840 --> 00:40:17,680 Speaker 1: you an example, like the kind of ship that they're 714 00:40:17,680 --> 00:40:19,319 Speaker 1: talking on our show, there was like one episode where 715 00:40:19,320 --> 00:40:21,439 Speaker 1: there's a guy on who's like, I don't like racist either, 716 00:40:21,719 --> 00:40:23,960 Speaker 1: even though probably in the most technical sense of the word, 717 00:40:24,160 --> 00:40:26,560 Speaker 1: you could probably say I'm racist because I do believe 718 00:40:26,600 --> 00:40:29,400 Speaker 1: that some races of people are inferior and superior in 719 00:40:29,480 --> 00:40:31,759 Speaker 1: certain ways. I would never say black people are you know, 720 00:40:32,000 --> 00:40:35,440 Speaker 1: crap people their inferior at everything, but there are certain 721 00:40:35,480 --> 00:40:38,160 Speaker 1: things certain races can do better. Asians are way better 722 00:40:38,239 --> 00:40:40,359 Speaker 1: at math and the aggregate than white people, and white 723 00:40:40,400 --> 00:40:43,160 Speaker 1: people build cultures better than Asian people are black people, 724 00:40:43,320 --> 00:40:45,600 Speaker 1: and we can view it all throughout history. So that's 725 00:40:45,640 --> 00:40:47,279 Speaker 1: what her guest says, and then as a host, she 726 00:40:47,400 --> 00:40:50,960 Speaker 1: responds with I think I would align myself similarly to 727 00:40:51,120 --> 00:40:54,480 Speaker 1: your sentiment there, like I would pretty much say, yeah, okay, 728 00:40:54,520 --> 00:40:57,640 Speaker 1: if believing that certain races specialize in certain things makes 729 00:40:57,680 --> 00:41:00,720 Speaker 1: me racist, then I guess that's what I am, because 730 00:41:00,760 --> 00:41:03,719 Speaker 1: I do share your sentiment there. Everything you said like 731 00:41:03,880 --> 00:41:06,040 Speaker 1: meshes perfectly with what you know. I'm kind of like 732 00:41:06,160 --> 00:41:09,279 Speaker 1: thinking on the inside here. So yes, that was a 733 00:41:09,440 --> 00:41:15,000 Speaker 1: woman teaching the children social studies. Social that is double 734 00:41:15,080 --> 00:41:17,759 Speaker 1: messed up. She did say that as an adult, my 735 00:41:17,840 --> 00:41:20,960 Speaker 1: decisions are my own. My family has nothing whatsoever to 736 00:41:21,040 --> 00:41:23,920 Speaker 1: do with my social media accounts or my podcast. Okay, 737 00:41:24,040 --> 00:41:26,040 Speaker 1: leave my family out of it. But what's lurking in 738 00:41:26,120 --> 00:41:28,359 Speaker 1: that family's closet, you know what I mean? A hood 739 00:41:30,120 --> 00:41:32,600 Speaker 1: from them. My humbily asked for forgiveness as it was 740 00:41:32,640 --> 00:41:35,320 Speaker 1: never my intention to cause them grief while engaging in 741 00:41:35,360 --> 00:41:38,560 Speaker 1: a hobby on my personal time. I mean, the kind 742 00:41:38,600 --> 00:41:41,240 Speaker 1: of retweets that she deleted were like, white privilege proved 743 00:41:41,280 --> 00:41:44,600 Speaker 1: to me that it exists, Show me statistics that prove 744 00:41:44,680 --> 00:41:48,920 Speaker 1: what you just longing to get fired? Well that that's 745 00:41:48,920 --> 00:41:51,399 Speaker 1: because she was using her fake as you know Twitter name, 746 00:41:51,800 --> 00:41:54,000 Speaker 1: and then was even like, this is just just underlying 747 00:41:54,000 --> 00:41:55,640 Speaker 1: her sitting as a teacher. She says, this is a 748 00:41:55,640 --> 00:41:58,400 Speaker 1: tweet that was deleted. You know, America's education system is 749 00:41:58,440 --> 00:42:00,839 Speaker 1: designed to enable victimization when tachers are forced to learn 750 00:42:00,840 --> 00:42:04,120 Speaker 1: about institutional racism and prove it's real when it isn't. 751 00:42:04,360 --> 00:42:06,560 Speaker 1: I literally feel brain cells dying as I read this 752 00:42:06,600 --> 00:42:10,839 Speaker 1: bullshit hashtags any morning not the No Doubt song. So yeah, 753 00:42:11,719 --> 00:42:18,520 Speaker 1: she definitely was listening to that Sunday Morning. Yeah, so 754 00:42:18,680 --> 00:42:20,959 Speaker 1: she's out of here. So yeah. And for some reason 755 00:42:21,040 --> 00:42:24,000 Speaker 1: when I was picturing this happening in my mind, I 756 00:42:24,040 --> 00:42:26,680 Speaker 1: don't know what I was expecting, but I wasn't expecting 757 00:42:26,760 --> 00:42:30,680 Speaker 1: her to look so like the exact blend of all 758 00:42:30,800 --> 00:42:33,640 Speaker 1: of my teachers growing up. And yeah, she looks exactly. 759 00:42:33,640 --> 00:42:36,320 Speaker 1: If you look at this photo, you will see elements 760 00:42:36,440 --> 00:42:40,360 Speaker 1: of like other teachers. That is my teacher. Yeah, so 761 00:42:41,080 --> 00:42:44,239 Speaker 1: computer sheds like nice teacher eyes too. Yeah, she just 762 00:42:44,360 --> 00:42:49,799 Speaker 1: looks like yeah, well, never never trust a teach her 763 00:42:49,840 --> 00:42:56,759 Speaker 1: with a kind smile. Yeah. The lyrics to poison, Uh, 764 00:42:57,239 --> 00:42:59,000 Speaker 1: I don't know, kids, keep an eye on your teachers. 765 00:42:59,600 --> 00:43:01,400 Speaker 1: Sorry to throw that onto you kids. Not only are 766 00:43:01,440 --> 00:43:04,480 Speaker 1: you in responsible for your safety is school. Please monitor 767 00:43:04,680 --> 00:43:07,960 Speaker 1: the racist behavior. Make sure they're not intentionally injecting racist 768 00:43:08,040 --> 00:43:14,120 Speaker 1: ideals in der social str That's all the education you need, Bro, 769 00:43:14,200 --> 00:43:20,600 Speaker 1: I didn't go to college. Bro. All right, that's gonna 770 00:43:20,680 --> 00:43:24,480 Speaker 1: do it. For this week's weekly Zeite, guys, please like 771 00:43:24,640 --> 00:43:28,400 Speaker 1: and review the show. If you like the show, h 772 00:43:28,840 --> 00:43:32,680 Speaker 1: means the world to Miles. He needs your validation. Folks. 773 00:43:33,320 --> 00:43:36,359 Speaker 1: I hope you're having a great weekend and I will 774 00:43:36,400 --> 00:43:37,719 Speaker 1: talk to you Monday. By