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We had some 18 00:00:49,840 --> 00:00:54,080 Speaker 1: truly incredible outbreaks of white feminism that we want to 19 00:00:54,080 --> 00:00:57,240 Speaker 1: do bring to you here. The first is, of course, 20 00:00:57,280 --> 00:01:00,400 Speaker 1: we've been tracking the trave Elizabeth Holmes, former head of 21 00:01:00,520 --> 00:01:05,600 Speaker 1: Farahos looks like she lied to everyone, investors, customers, et 22 00:01:05,680 --> 00:01:10,000 Speaker 1: cetera about what her supposed breakthrough technology could actually do. 23 00:01:10,640 --> 00:01:13,560 Speaker 1: Made her the you know, this young female billionaire, but 24 00:01:13,680 --> 00:01:16,560 Speaker 1: he loved her. And now that all came crashing down, 25 00:01:16,600 --> 00:01:19,080 Speaker 1: and she's in fact, you know, facing trial for the 26 00:01:19,120 --> 00:01:22,319 Speaker 1: alleged crimes that she committed. Well, it was only a 27 00:01:22,440 --> 00:01:26,280 Speaker 1: matter of time before someone decided that all of this 28 00:01:26,319 --> 00:01:28,480 Speaker 1: had nothing to do with the fact that she committed 29 00:01:28,480 --> 00:01:32,120 Speaker 1: massive amounts of fraud and lied to everyone, but that 30 00:01:32,280 --> 00:01:35,560 Speaker 1: she's a woman. That's the real problem here. Let's throw 31 00:01:35,600 --> 00:01:38,320 Speaker 1: this off ed up on the screen from the New 32 00:01:38,400 --> 00:01:42,440 Speaker 1: York Times, The Elizabeth Holmes trial is a wake up 33 00:01:42,480 --> 00:01:46,160 Speaker 1: call for sexism and tech. This is written by Ellen Powell, 34 00:01:46,160 --> 00:01:49,880 Speaker 1: who used to be the head wasn't she had read it? Yeah, 35 00:01:49,920 --> 00:01:51,360 Speaker 1: she was a CEO of readit That's what I thought. 36 00:01:51,440 --> 00:01:54,000 Speaker 1: She got fired. She also claimed sexism. Yeah, there's a 37 00:01:54,320 --> 00:01:57,040 Speaker 1: full circle out right. Indeed, so she has an interest 38 00:01:57,080 --> 00:02:00,680 Speaker 1: in perpetuating this narrative here. But she basically said that, 39 00:02:01,400 --> 00:02:03,120 Speaker 1: you know, and there is some truth to the fact 40 00:02:03,160 --> 00:02:05,960 Speaker 1: that this fake it till you make it culture is 41 00:02:06,120 --> 00:02:09,320 Speaker 1: endemic in Silicon Valley and that it's populated with a 42 00:02:09,320 --> 00:02:12,200 Speaker 1: bunch of liars who think, effectively, anything is justified if 43 00:02:12,280 --> 00:02:15,560 Speaker 1: it is in service of getting their revolutionary technology to 44 00:02:15,680 --> 00:02:18,280 Speaker 1: market so they can transform the world, et cetera, et cetera. 45 00:02:18,840 --> 00:02:21,880 Speaker 1: But there is a big difference with Elizabeth Holmes, which 46 00:02:21,919 --> 00:02:24,800 Speaker 1: is that you know, when a search engine doesn't work 47 00:02:24,840 --> 00:02:27,839 Speaker 1: the way that it's exactly advertised, or the algorithm isn't 48 00:02:27,880 --> 00:02:29,800 Speaker 1: quite where you want it to be, you don't have 49 00:02:29,840 --> 00:02:33,360 Speaker 1: people's literal lives at stake. Whereas she was portraying this 50 00:02:33,440 --> 00:02:36,360 Speaker 1: to the public, they were relying on these blood tests 51 00:02:36,680 --> 00:02:41,280 Speaker 1: and it was all a complete lie fraud Potempkin Village, 52 00:02:42,160 --> 00:02:45,600 Speaker 1: where you know, they weren't the tests weren't accurate, they 53 00:02:45,639 --> 00:02:47,680 Speaker 1: weren't able to do the test that they claimed they 54 00:02:47,680 --> 00:02:50,040 Speaker 1: were able to do, and it was just absolutely on 55 00:02:50,080 --> 00:02:52,760 Speaker 1: a massive scale. I mean, these tests were in Walgreens, 56 00:02:53,160 --> 00:02:56,320 Speaker 1: This was rolled down across the country with much fanfare, 57 00:02:56,800 --> 00:03:01,280 Speaker 1: and she knew that there was a massive gulf between 58 00:03:01,320 --> 00:03:04,000 Speaker 1: what the public was being told in the actual reality 59 00:03:04,080 --> 00:03:06,920 Speaker 1: with you know, potentially really damaging consequences. That's what this 60 00:03:07,080 --> 00:03:11,840 Speaker 1: BS doesn't get. Like you said, if an HR enterprise 61 00:03:11,919 --> 00:03:16,760 Speaker 1: software doesn't work is advertised, Okay, you know my figures 62 00:03:16,960 --> 00:03:20,160 Speaker 1: cry for the fortune five hundreds that will suffer. But 63 00:03:20,720 --> 00:03:25,200 Speaker 1: when people make medical decisions based on faulty blood work, 64 00:03:25,360 --> 00:03:29,080 Speaker 1: which happened to many people who are in John Kerry 65 00:03:29,160 --> 00:03:33,079 Speaker 1: U's Bad Blood Book, they made terrible decisions about their 66 00:03:33,120 --> 00:03:37,680 Speaker 1: health that had real world consequences to their bodies based 67 00:03:37,760 --> 00:03:40,960 Speaker 1: upon the fake test results of this woman and her company. 68 00:03:41,120 --> 00:03:43,680 Speaker 1: That she knew that it was not in good faith 69 00:03:43,720 --> 00:03:46,280 Speaker 1: that she put out a product that you know, happened 70 00:03:46,320 --> 00:03:50,880 Speaker 1: to fail. It was a direct knowledge of the fraud 71 00:03:50,960 --> 00:03:54,280 Speaker 1: that she was perpetrating, both on Walgreens, her investors, and 72 00:03:54,360 --> 00:03:58,440 Speaker 1: on these actual people that had consequences. That's the difference 73 00:03:58,760 --> 00:04:01,360 Speaker 1: La and Powell. And like, here's the thing too, is 74 00:04:01,400 --> 00:04:03,400 Speaker 1: like this could have been written by her defense team 75 00:04:03,680 --> 00:04:06,400 Speaker 1: because we covered how she's leading into like a me 76 00:04:06,520 --> 00:04:12,800 Speaker 1: too defense And in this instance, the reverse of sexism 77 00:04:12,840 --> 00:04:15,880 Speaker 1: being a problem for Elizabeth Holmes is actually true. Is 78 00:04:15,920 --> 00:04:19,160 Speaker 1: actually the case because what she relied on, what made 79 00:04:19,200 --> 00:04:22,560 Speaker 1: her so famous was that she was this young female 80 00:04:22,920 --> 00:04:26,039 Speaker 1: tech head. That's part of why she was able to 81 00:04:26,160 --> 00:04:29,040 Speaker 1: attract all this investment, part of why she was on 82 00:04:29,160 --> 00:04:32,200 Speaker 1: all of these magazine covers why she was Glamour's Woman 83 00:04:32,240 --> 00:04:34,760 Speaker 1: of the Year. All of that stuff is because they 84 00:04:34,839 --> 00:04:38,160 Speaker 1: loved the story of you have this male dominated field 85 00:04:38,400 --> 00:04:41,000 Speaker 1: and oh my god, here's this woman who's breaking the 86 00:04:41,120 --> 00:04:45,040 Speaker 1: mold and she's the female Steve Jobs. She leaned into 87 00:04:45,080 --> 00:04:51,640 Speaker 1: her identity as a glass ceiling breaking, trailblazing woman. It's 88 00:04:51,800 --> 00:04:55,120 Speaker 1: part of why she was able to snow people and 89 00:04:55,160 --> 00:04:57,640 Speaker 1: get away with it for as long as she did. 90 00:04:58,000 --> 00:05:00,880 Speaker 1: So it's the exact opposite of what Ellen Powell is 91 00:05:00,960 --> 00:05:05,200 Speaker 1: saying here. She actually used her gender to enrich herself 92 00:05:05,279 --> 00:05:07,960 Speaker 1: at the expense of you know, all of these people 93 00:05:08,000 --> 00:05:10,000 Speaker 1: who relied on this medical data that turned out to 94 00:05:10,040 --> 00:05:12,240 Speaker 1: be complete trash. No, and you, as you point out, 95 00:05:12,279 --> 00:05:15,400 Speaker 1: this is a long stay. This is now a new 96 00:05:15,720 --> 00:05:19,640 Speaker 1: you know, defense mechanism for the worst people in our society. Yes, 97 00:05:20,080 --> 00:05:25,240 Speaker 1: another example of that. Yeah, Jennifer Rubin, who has undergone 98 00:05:25,320 --> 00:05:29,760 Speaker 1: this weird trans transformation into now she's like the biggest 99 00:05:29,800 --> 00:05:34,840 Speaker 1: Biden standout there, constantly getting retweeted by Ron Klain every 100 00:05:34,880 --> 00:05:38,160 Speaker 1: single article she writes, which apparently sadly get a lot 101 00:05:38,200 --> 00:05:42,120 Speaker 1: of us. They're just slavishly shilling for the Biden ministration. 102 00:05:42,160 --> 00:05:45,920 Speaker 1: I'm propaganda. So Alex Thompson, who's a solid reporter over 103 00:05:45,960 --> 00:05:49,000 Speaker 1: at Politico who covers the West wing there, he was 104 00:05:49,040 --> 00:05:52,480 Speaker 1: writing a piece about how she's gone through this transformation 105 00:05:52,600 --> 00:05:55,359 Speaker 1: and how she used to be extremely critical not just 106 00:05:55,440 --> 00:05:58,919 Speaker 1: of Barack Obama but also Joe Biden specifically under the 107 00:05:58,960 --> 00:06:02,000 Speaker 1: Obaman ministration, and ask you a very obvious question like, oh, well, 108 00:06:02,000 --> 00:06:04,680 Speaker 1: that's interesting, I wonder what happened and let's talk about 109 00:06:04,720 --> 00:06:10,240 Speaker 1: the change in your positioning here, to which she responded. 110 00:06:10,240 --> 00:06:12,920 Speaker 1: When they reached out for questioning, she sent back this 111 00:06:13,040 --> 00:06:17,600 Speaker 1: insane email that had in the subject line off the record, 112 00:06:17,760 --> 00:06:19,960 Speaker 1: which is not how you Actually they never agreed to 113 00:06:19,960 --> 00:06:22,720 Speaker 1: be a cool agreement. Yeah, you have to on both 114 00:06:22,760 --> 00:06:24,800 Speaker 1: sides agree. They never agreed for this to be off 115 00:06:24,800 --> 00:06:27,239 Speaker 1: the record. So Alex Stompson went ahead and publish this email, 116 00:06:27,240 --> 00:06:31,080 Speaker 1: which is quite interesting, in which she claims that the 117 00:06:31,240 --> 00:06:34,680 Speaker 1: reason they're writing about her is because of sexism and 118 00:06:34,760 --> 00:06:37,680 Speaker 1: also maybe because she's Jewish. I just have to read 119 00:06:37,760 --> 00:06:41,160 Speaker 1: you this email because this is amazing. How utterly predictable 120 00:06:41,200 --> 00:06:43,800 Speaker 1: that Politico would run the zillion's hit piece on a 121 00:06:43,880 --> 00:06:47,799 Speaker 1: prominent woman, especially when candid in her critiques of Politico's 122 00:06:47,839 --> 00:06:52,599 Speaker 1: hysterical clickbait style of coverage. Notion that I'm polarizing in 123 00:06:52,680 --> 00:06:55,960 Speaker 1: a newsroom is a take only Politico could come up 124 00:06:56,000 --> 00:06:57,880 Speaker 1: with by of course, running around to ask the question 125 00:06:57,920 --> 00:07:00,720 Speaker 1: in the first place. I trust this post superb news 126 00:07:00,760 --> 00:07:02,960 Speaker 1: side folks spend zero time thinking about me. This is 127 00:07:03,240 --> 00:07:06,839 Speaker 1: entirely appropriate. My only surprise is that sam Stein, is 128 00:07:06,880 --> 00:07:09,479 Speaker 1: a very good journalist, would become enmessed in such an 129 00:07:09,600 --> 00:07:14,520 Speaker 1: obviously misogynistic publication. Surely there are finer publications that would 130 00:07:14,520 --> 00:07:17,600 Speaker 1: have him. And by the way, what a low class 131 00:07:17,680 --> 00:07:22,040 Speaker 1: move to do this on gom kipper at the last moment. Yeah, 132 00:07:22,040 --> 00:07:26,400 Speaker 1: so and all. So she's saying, like, I mean, this 133 00:07:26,440 --> 00:07:29,600 Speaker 1: is an interesting story that Alex is pursuing. He used 134 00:07:29,640 --> 00:07:32,160 Speaker 1: to trash Biden, Yes, and that got you a lot 135 00:07:32,200 --> 00:07:34,400 Speaker 1: of clicks and a lot of prominence. Now it's very 136 00:07:34,400 --> 00:07:36,920 Speaker 1: convenient for you to praise him, and that gets you 137 00:07:36,960 --> 00:07:38,520 Speaker 1: a lot of clicks and a lot of love from 138 00:07:38,520 --> 00:07:40,640 Speaker 1: the White House, and I'm sure a lot of access here. 139 00:07:40,680 --> 00:07:44,440 Speaker 1: She's like their favorite journalists there, Now what's going on here? 140 00:07:44,880 --> 00:07:48,120 Speaker 1: And she goes right to this is all about sexism 141 00:07:48,160 --> 00:07:50,640 Speaker 1: and misogyny and maybe also because I'm Jewish, and Alex 142 00:07:50,680 --> 00:07:52,680 Speaker 1: points us out put his sweet up there on the screen, 143 00:07:52,760 --> 00:07:55,600 Speaker 1: which is that. Ron Klain, the White House Chief of Staff, 144 00:07:55,640 --> 00:07:59,000 Speaker 1: has retweeted or mentioned Ruben more than three dozen times 145 00:07:59,240 --> 00:08:02,880 Speaker 1: since midway mid May. The White House Press team, the DNC, 146 00:08:03,040 --> 00:08:06,320 Speaker 1: the State Department, and the Vice President's office have all 147 00:08:06,360 --> 00:08:09,840 Speaker 1: promoted her various columns and tweets from her recently. So 148 00:08:09,920 --> 00:08:13,240 Speaker 1: his coverage of her as a central defender and propagandist 149 00:08:13,320 --> 00:08:16,679 Speaker 1: with a Biden administration is in fact a legitimate story. 150 00:08:16,840 --> 00:08:19,440 Speaker 1: It has nothing to do with her sex. If it was, 151 00:08:19,480 --> 00:08:21,760 Speaker 1: by the way, people have written several stories about the 152 00:08:21,800 --> 00:08:24,280 Speaker 1: Lincoln Project and many other types in the same thing. 153 00:08:24,600 --> 00:08:26,960 Speaker 1: So it's just a low life move in order to 154 00:08:27,000 --> 00:08:29,040 Speaker 1: make And yeah, I'm glad she got burned on this email. 155 00:08:29,120 --> 00:08:31,000 Speaker 1: She wish she was even burned. She thought she was 156 00:08:31,000 --> 00:08:32,840 Speaker 1: off the record. That's not how it works. If you 157 00:08:32,840 --> 00:08:34,480 Speaker 1: think you'd be in Washington long enough to know that, 158 00:08:34,720 --> 00:08:37,240 Speaker 1: she certainly would be in a position to know that. 159 00:08:37,440 --> 00:08:40,000 Speaker 1: I mean, the thing that ties these things together here, 160 00:08:40,040 --> 00:08:42,319 Speaker 1: and why this is so enraging to me is like 161 00:08:42,600 --> 00:08:46,520 Speaker 1: when you just throw around sexism for everything, it becomes meaningless. 162 00:08:46,679 --> 00:08:49,760 Speaker 1: It ends up meaning nothing. And another thing is look 163 00:08:49,760 --> 00:08:53,760 Speaker 1: at how both of these incredibly powerful and wealthy women 164 00:08:54,360 --> 00:08:56,959 Speaker 1: are pretending to be in some sort of like state 165 00:08:57,040 --> 00:09:02,520 Speaker 1: of victimhood and using their gender in order to cover 166 00:09:02,679 --> 00:09:06,840 Speaker 1: for power. Basically, I mean for Ruben, she's explicitly like 167 00:09:07,000 --> 00:09:11,000 Speaker 1: protecting the Biden administration here by weaponizing her gender. And 168 00:09:11,000 --> 00:09:13,520 Speaker 1: then Ellen Powell on behalf of Elizabeth Holmes, who's also 169 00:09:13,640 --> 00:09:16,680 Speaker 1: using this at trial, is using it to cover her 170 00:09:16,880 --> 00:09:23,359 Speaker 1: massive fraud that she allegedly committed. So it's really disgusting 171 00:09:23,880 --> 00:09:28,160 Speaker 1: when these sorts of you know, legitimate thing racism, sexism, etc. 172 00:09:28,559 --> 00:09:32,840 Speaker 1: Identity based issues are weaponized by the powerful to try 173 00:09:32,880 --> 00:09:36,880 Speaker 1: to cover for their own failings, protect power, and make 174 00:09:36,920 --> 00:09:39,920 Speaker 1: them outselves out like there's some sort of victim. It's 175 00:09:40,200 --> 00:09:44,800 Speaker 1: disgusting display and Jennifer Ruben Elizabeth Holmes two key examples 176 00:09:44,800 --> 00:09:47,480 Speaker 1: here today. There you go, all right, guys, enjoy your day. 177 00:09:47,520 --> 00:09:49,400 Speaker 1: We'll have more for you later. Hey, So remember how 178 00:09:49,440 --> 00:09:52,559 Speaker 1: we told you how awesome premium membership was. Well, here 179 00:09:52,600 --> 00:09:55,000 Speaker 1: we are again to remind you that becoming a premium 180 00:09:55,040 --> 00:09:57,760 Speaker 1: member means you don't have to listen to our constant 181 00:09:57,760 --> 00:10:01,040 Speaker 1: pleas for you to subscribe. Are you waiting for Become 182 00:10:01,080 --> 00:10:03,960 Speaker 1: a Premium member today by going to Breakingpoints dot com, 183 00:10:03,960 --> 00:10:07,160 Speaker 1: which you can click on in the show notes. Today, 184 00:10:07,200 --> 00:10:09,480 Speaker 1: we wanted to bring you the story of a true 185 00:10:09,640 --> 00:10:14,080 Speaker 1: American hero. Beth mcgraf decided she was ready to quit 186 00:10:14,120 --> 00:10:18,080 Speaker 1: her job at Walmart, and she did it by announcing 187 00:10:18,320 --> 00:10:21,640 Speaker 1: on the intercom to all of the store associates and 188 00:10:21,679 --> 00:10:25,280 Speaker 1: customers exactly how she felt about that job and the people, 189 00:10:25,559 --> 00:10:30,160 Speaker 1: and the corporate culture and all of that distagalism. Attention 190 00:10:30,320 --> 00:10:33,959 Speaker 1: Walmart shoppers and associates. My name is Beth from Electronics. 191 00:10:34,040 --> 00:10:36,360 Speaker 1: I've been working at Walmart for almost five years, and 192 00:10:36,400 --> 00:10:39,239 Speaker 1: I can say that everyone here is overworked and underpaid. 193 00:10:39,640 --> 00:10:43,360 Speaker 1: The attendant policy is bullshit. We are treated from management 194 00:10:44,080 --> 00:10:47,160 Speaker 1: and customers poorly every day. Whenever we have a problem 195 00:10:47,200 --> 00:10:50,320 Speaker 1: with it, we're told that we're replaceable. I'm tired of 196 00:10:50,360 --> 00:10:54,479 Speaker 1: the constant gas lighting. This company treats their elderly associates 197 00:10:54,559 --> 00:10:58,320 Speaker 1: like shit. To Jared, our store manager, you're a pergirt, 198 00:10:58,880 --> 00:11:01,960 Speaker 1: Greta and Kathy, shame on y'all for treating your associates 199 00:11:02,000 --> 00:11:03,880 Speaker 1: the way you do. I hope you don't speak to 200 00:11:03,920 --> 00:11:06,760 Speaker 1: your families, the way you speak to us, shout out 201 00:11:06,800 --> 00:11:11,240 Speaker 1: to comedy, Patty Shardel, and so many more. Walmart doesn't 202 00:11:11,240 --> 00:11:15,480 Speaker 1: deserve y'all. Fuck manage it and fuck this job. I quit. 203 00:11:19,679 --> 00:11:24,520 Speaker 1: I just wonder how many service workers have wanted to 204 00:11:24,600 --> 00:11:29,000 Speaker 1: say very very similar things. I think this woman is 205 00:11:29,040 --> 00:11:33,000 Speaker 1: speaking for millions of people who want to tell their 206 00:11:33,080 --> 00:11:37,400 Speaker 1: corporate bosses, managers, and overlords to go f themselves. Yeah, 207 00:11:37,440 --> 00:11:41,000 Speaker 1: it's a pretty it's pretty amazing. But unfortunately, what are 208 00:11:41,000 --> 00:11:42,800 Speaker 1: we seeing. Let's put this up there on the screen. 209 00:11:43,160 --> 00:11:45,840 Speaker 1: More and more people are actually having to go and 210 00:11:45,920 --> 00:11:49,480 Speaker 1: work at Amazon or Walmart, and as we have seen, 211 00:11:50,160 --> 00:11:52,640 Speaker 1: the reason they're doing that is because, yes, Walmart is 212 00:11:52,720 --> 00:11:55,520 Speaker 1: raising its wages, but it comes with the price, which 213 00:11:55,520 --> 00:11:57,680 Speaker 1: is what did you see there with Beth, which is 214 00:11:57,679 --> 00:12:01,920 Speaker 1: that Beth is having to work, you know, under a 215 00:12:01,920 --> 00:12:06,720 Speaker 1: schedule that she doesn't necessarily have any saying wage ladder. Actually, Walmart, 216 00:12:06,720 --> 00:12:09,200 Speaker 1: as we've discussed, is better than Amazon in terms of 217 00:12:09,240 --> 00:12:12,600 Speaker 1: promoting outside of its associates. But whenever you work at 218 00:12:12,600 --> 00:12:15,520 Speaker 1: these places, you're basically at the total mercy of management 219 00:12:15,559 --> 00:12:17,400 Speaker 1: and you just don't have a lot of say in 220 00:12:17,400 --> 00:12:19,160 Speaker 1: your day to day life. They could schedule you at 221 00:12:19,240 --> 00:12:21,920 Speaker 1: night and then schedule you to open at six am 222 00:12:22,000 --> 00:12:24,960 Speaker 1: the next day. This stuff happens all the time, and 223 00:12:25,000 --> 00:12:28,160 Speaker 1: it's basically completely allowed in our labor law. For millions 224 00:12:28,160 --> 00:12:30,760 Speaker 1: of people, this is their day to day reality. People 225 00:12:30,800 --> 00:12:34,520 Speaker 1: like to portray it as, oh, it's, you know, temporary work. 226 00:12:34,720 --> 00:12:37,560 Speaker 1: She worked for five straight years. I don't think, you know, 227 00:12:37,600 --> 00:12:39,640 Speaker 1: it's not. She probably probably wanted to do something better, 228 00:12:39,920 --> 00:12:42,600 Speaker 1: not necessarily any other options where she lives. So yeah, 229 00:12:42,600 --> 00:12:44,480 Speaker 1: it's just a good example of what happens. I mean, 230 00:12:44,520 --> 00:12:48,559 Speaker 1: Walmart hollowed out so much of America, and now Amazon 231 00:12:48,960 --> 00:12:51,040 Speaker 1: is coming on top of that and doing the same 232 00:12:51,160 --> 00:12:54,240 Speaker 1: like Walmart sort of hollowed out like the little downtown 233 00:12:54,600 --> 00:12:58,280 Speaker 1: area and the local small businesses whatever, yeah, Main Street, 234 00:12:58,320 --> 00:13:01,240 Speaker 1: and then now Amazon is coming in and hollowing out 235 00:13:01,280 --> 00:13:05,360 Speaker 1: like suburban America and the malls and the sort of 236 00:13:05,440 --> 00:13:08,400 Speaker 1: like big box retailers and all of that, and leaving 237 00:13:08,440 --> 00:13:11,559 Speaker 1: with you with very few other options. I would like 238 00:13:11,640 --> 00:13:15,480 Speaker 1: to think that maybe Beth felt comfortable taking this particular 239 00:13:15,760 --> 00:13:18,920 Speaker 1: bold and brave stand right now because maybe there are 240 00:13:19,000 --> 00:13:21,400 Speaker 1: more job openings available and she feels like maybe there's 241 00:13:21,440 --> 00:13:24,120 Speaker 1: another opportunity out there for me because she hung in 242 00:13:24,160 --> 00:13:27,160 Speaker 1: there for five years and now something has either brought 243 00:13:27,200 --> 00:13:29,600 Speaker 1: her to the breaking point or made her feel embolden, like, 244 00:13:29,679 --> 00:13:30,880 Speaker 1: you know what, I'm going to be able to get 245 00:13:30,920 --> 00:13:34,320 Speaker 1: another job at a similar level that maybe actually treats 246 00:13:34,320 --> 00:13:36,440 Speaker 1: me like a human being, because I also think it's 247 00:13:36,559 --> 00:13:38,600 Speaker 1: very revealing what she says there, and she says, look, 248 00:13:38,600 --> 00:13:41,559 Speaker 1: we're underpaid and we're overworked, but she also just talks 249 00:13:41,600 --> 00:13:45,840 Speaker 1: about like not being treated in a basic, decent, dignified 250 00:13:45,960 --> 00:13:50,079 Speaker 1: human way by management, by the culture of the store, 251 00:13:50,440 --> 00:13:54,080 Speaker 1: even by you know, customers who were not kind, and 252 00:13:54,120 --> 00:13:56,480 Speaker 1: that's something we've seen in culture as well as like 253 00:13:56,559 --> 00:13:59,040 Speaker 1: service workers just treated by everyone as sort of like 254 00:13:59,400 --> 00:14:04,040 Speaker 1: disposable robots, less than human. So kudos to her. I 255 00:14:04,080 --> 00:14:08,280 Speaker 1: saw there was also an entire staff of a restaurant. 256 00:14:08,360 --> 00:14:10,600 Speaker 1: Did you see this one? Quit on mass I think 257 00:14:10,600 --> 00:14:12,839 Speaker 1: it's down in Georgia, And they just like posted just 258 00:14:12,920 --> 00:14:15,760 Speaker 1: closed the restaurant and posted a sign on the door 259 00:14:16,240 --> 00:14:18,440 Speaker 1: about what a terrible place it was to work, and 260 00:14:18,480 --> 00:14:21,120 Speaker 1: they all just walked out together and were like, screw 261 00:14:21,160 --> 00:14:23,600 Speaker 1: you guys, amount of here. So good, there you go, 262 00:14:23,920 --> 00:14:27,120 Speaker 1: American hero. All right, guys, A lot more for you later. Wow, 263 00:14:27,280 --> 00:14:29,320 Speaker 1: you guys must really like listening to our voices. Well, 264 00:14:29,320 --> 00:14:31,320 Speaker 1: I know this is annoying. Instead of making you listen 265 00:14:31,360 --> 00:14:33,880 Speaker 1: to a Viagra commercial. When you're done, check out the 266 00:14:33,920 --> 00:14:36,680 Speaker 1: other podcast I do with Marsha Kasloff called The Realignment. 267 00:14:36,720 --> 00:14:39,120 Speaker 1: We talk a lot about the deeper issues that are changing, 268 00:14:39,240 --> 00:14:42,280 Speaker 1: realigning in American society. You always need more Crystal and 269 00:14:42,320 --> 00:14:45,040 Speaker 1: Sag in your daily lives. Take care, guys. We've been 270 00:14:45,080 --> 00:14:47,240 Speaker 1: keeping in our eye on that Virginia governor's race, and 271 00:14:47,280 --> 00:14:50,120 Speaker 1: a new poll by the Washington Post is really eye popping. 272 00:14:50,160 --> 00:14:52,720 Speaker 1: So let's put it up there on the screen. Mccauluff 273 00:14:52,720 --> 00:14:56,520 Speaker 1: and Youngkin locked in a tight race for the Virginia governor. 274 00:14:56,560 --> 00:14:59,280 Speaker 1: And remember keep in mind that this is from the 275 00:14:59,360 --> 00:15:04,480 Speaker 1: Washington Post, semi local paper. Among registered voters, mccauliffe has 276 00:15:04,480 --> 00:15:08,440 Speaker 1: a forty nine to forty three edge. However, amongst likely 277 00:15:08,560 --> 00:15:13,320 Speaker 1: voters it's actually fifty percent to forty seven percent. Obviously 278 00:15:13,440 --> 00:15:16,080 Speaker 1: likely voters is what matters the most there. I mean, 279 00:15:16,120 --> 00:15:20,360 Speaker 1: it's pretty fascinating, Crystal, because Youngkin is really trying to 280 00:15:20,440 --> 00:15:22,920 Speaker 1: drive up his support in kind of the ex urban 281 00:15:22,960 --> 00:15:26,600 Speaker 1: parts of northern Virginia win over people who voted for 282 00:15:26,640 --> 00:15:30,520 Speaker 1: President Biden would consider themselves Republicans who don't like Trump. 283 00:15:30,720 --> 00:15:34,040 Speaker 1: Mccaulliffe is trying to tie Youngkin explicitly to Trump, do 284 00:15:34,120 --> 00:15:37,560 Speaker 1: what Gavin Newsom did to Larry Elder. But right now 285 00:15:37,640 --> 00:15:39,960 Speaker 1: you've got a pretty tight race going on. And as 286 00:15:40,000 --> 00:15:42,480 Speaker 1: you always say, Virginia is the ultimate bell weather because 287 00:15:42,520 --> 00:15:45,280 Speaker 1: it's off your election. That's right. It's like the only 288 00:15:45,320 --> 00:15:49,120 Speaker 1: real significant election that happens right after the presidential election. 289 00:15:49,400 --> 00:15:52,600 Speaker 1: Very unusual in these weird off years. And so you know, 290 00:15:52,640 --> 00:15:56,240 Speaker 1: you saw the Tea party waves sort of previewed by 291 00:15:56,280 --> 00:16:00,400 Speaker 1: Bob McDonald's romping win over Cree Deeds. You seen the 292 00:16:00,440 --> 00:16:02,640 Speaker 1: era of kind of the Biden Democrat and the shift 293 00:16:02,680 --> 00:16:06,280 Speaker 1: to suburban Democrats with the rise of Tarry mccaulliffe the 294 00:16:06,320 --> 00:16:08,200 Speaker 1: first time around when he used to be governor, and 295 00:16:08,200 --> 00:16:12,040 Speaker 1: then Ralph Northam also appealed to very similar demographic. So 296 00:16:12,240 --> 00:16:15,000 Speaker 1: if you dig into these poll results, what the analysis 297 00:16:15,040 --> 00:16:18,880 Speaker 1: from the Washington Post says is that mccauliffe is performing 298 00:16:18,960 --> 00:16:22,080 Speaker 1: basically the same as Northam in most areas of the state, 299 00:16:22,120 --> 00:16:24,440 Speaker 1: but the place where he's seen a lot of fallof 300 00:16:24,640 --> 00:16:27,880 Speaker 1: is in those exurban counties, so you know, not the 301 00:16:27,920 --> 00:16:31,520 Speaker 1: inner ring of suburbs with the one after that, and 302 00:16:31,880 --> 00:16:34,920 Speaker 1: that that's the area that Young Kin has picked up 303 00:16:34,920 --> 00:16:38,240 Speaker 1: a lot of support. Both of these candidates, even mccalluff, 304 00:16:38,280 --> 00:16:40,360 Speaker 1: who was the former governor and is like pretty well 305 00:16:40,360 --> 00:16:43,800 Speaker 1: known on the national stage, both of them are fairly undefined. 306 00:16:44,560 --> 00:16:48,800 Speaker 1: Young Kin in particular, though, is really quite unknown. One 307 00:16:48,800 --> 00:16:52,600 Speaker 1: thing I would say about this is Young Kin is 308 00:16:52,640 --> 00:16:56,240 Speaker 1: not Larry Elder. Larry Elder had a lot more inflammatory 309 00:16:56,320 --> 00:16:59,120 Speaker 1: things that he had said. He's this right wing radio personality, 310 00:16:59,200 --> 00:17:01,640 Speaker 1: sort of continued to lean into that, even as he's 311 00:17:01,720 --> 00:17:04,679 Speaker 1: running in a blue state of California. Young Cain doesn't 312 00:17:04,720 --> 00:17:06,960 Speaker 1: have that kind of baggage. So he is a better 313 00:17:07,040 --> 00:17:10,040 Speaker 1: candidate in that regard. But I still think you see 314 00:17:10,040 --> 00:17:12,440 Speaker 1: some signs that this race could go the same way 315 00:17:12,440 --> 00:17:16,000 Speaker 1: that California did, and ultimately mccaulliff could open up enough 316 00:17:16,000 --> 00:17:19,120 Speaker 1: of a lead to win this thing fairly comfortably. Which 317 00:17:19,160 --> 00:17:24,080 Speaker 1: is that right now there's a big enthusiasm deficit among Democrats, 318 00:17:24,119 --> 00:17:26,800 Speaker 1: which is why you see mcculloff doing okay when you're 319 00:17:26,800 --> 00:17:29,600 Speaker 1: just talking about registered voters and the race being extraordinarily 320 00:17:29,640 --> 00:17:32,200 Speaker 1: tight when you're talking about likely voters, Democrats are just 321 00:17:32,280 --> 00:17:34,960 Speaker 1: lose less enthusiastic right now now as we get down 322 00:17:35,000 --> 00:17:37,600 Speaker 1: the stretch. And also, I should say Young Kins is 323 00:17:37,880 --> 00:17:40,280 Speaker 1: very personally wealthy and spent a lot of money early 324 00:17:40,320 --> 00:17:43,200 Speaker 1: on to help to define the race and give himself 325 00:17:43,240 --> 00:17:46,520 Speaker 1: the edge that he's enjoying right now. So it is 326 00:17:46,640 --> 00:17:49,840 Speaker 1: very possible that as voter's minds are focused and as 327 00:17:49,880 --> 00:17:53,040 Speaker 1: more advertisements are run, and lord knows if Donald Trump 328 00:17:53,080 --> 00:17:56,320 Speaker 1: may weigh in inadvisably into this race and say something 329 00:17:56,359 --> 00:17:59,520 Speaker 1: about it. As term Calloff continues to make the case 330 00:17:59,560 --> 00:18:03,439 Speaker 1: about that extreme Texas abortion law and Roe versus Wade 331 00:18:03,800 --> 00:18:07,240 Speaker 1: being potentially undermined at the Supreme Court level, as he 332 00:18:07,280 --> 00:18:09,800 Speaker 1: starts to define young Kin in that way with the 333 00:18:09,840 --> 00:18:13,000 Speaker 1: more extreme parts of the Republican Party, you could see 334 00:18:13,160 --> 00:18:17,040 Speaker 1: number one, some of those exurban independent voters moving back 335 00:18:17,040 --> 00:18:19,720 Speaker 1: to the Democrats. And number two, I think you'll see 336 00:18:19,720 --> 00:18:22,480 Speaker 1: the Democrats starting to feel more of that existential Okay, 337 00:18:22,560 --> 00:18:24,080 Speaker 1: we've got to make sure that we don't get this 338 00:18:24,160 --> 00:18:28,040 Speaker 1: crazy guy young Kin in there. Ultimately, there was a 339 00:18:28,400 --> 00:18:30,040 Speaker 1: you always want to take these anecdotes with a grain 340 00:18:30,040 --> 00:18:32,520 Speaker 1: of salt because who knows if this is representative of 341 00:18:32,680 --> 00:18:34,720 Speaker 1: a broader population. But I did think that this was 342 00:18:34,760 --> 00:18:38,280 Speaker 1: an interesting comment from a voter that the Washington Post interviewed. 343 00:18:38,280 --> 00:18:42,440 Speaker 1: This guy named Timothy Davis, sixty two, retired law enforcement officer. 344 00:18:42,960 --> 00:18:46,159 Speaker 1: He lives down in Williamsburg. Voted for Trump in twenty 345 00:18:46,200 --> 00:18:50,280 Speaker 1: sixteen and then voted for Biden in twenty twenty. True 346 00:18:50,280 --> 00:18:54,359 Speaker 1: swing voter this year. Right now, he's undecided, he says. 347 00:18:54,440 --> 00:18:56,320 Speaker 1: I like some of the things in both parties. He 348 00:18:56,320 --> 00:18:57,920 Speaker 1: gave him a call of high marks for his work 349 00:18:57,920 --> 00:19:00,399 Speaker 1: on the economy and job creation during his time in office, 350 00:19:00,600 --> 00:19:02,439 Speaker 1: but he did not like his support for gun control 351 00:19:02,440 --> 00:19:05,720 Speaker 1: and abortion rights. Youngkin's appealing, he said, but the big 352 00:19:05,840 --> 00:19:08,960 Speaker 1: question for him was whether he is fealty to Trump, 353 00:19:09,280 --> 00:19:11,720 Speaker 1: who Davis said caused terrible damage and stomped all over 354 00:19:11,760 --> 00:19:14,199 Speaker 1: the constitution. He said, I'll take a closer look at 355 00:19:14,200 --> 00:19:17,040 Speaker 1: young Kin and try to decide if he's a true Trump. 356 00:19:17,160 --> 00:19:19,920 Speaker 1: Yes man, it's going to be really, really tough. That's 357 00:19:19,920 --> 00:19:21,680 Speaker 1: when I sit down on election day and say, Wow, 358 00:19:21,720 --> 00:19:25,080 Speaker 1: what's the worst of two evils. So that's the case 359 00:19:25,080 --> 00:19:27,080 Speaker 1: that Terry mccuff is already trying to make and is 360 00:19:27,119 --> 00:19:29,359 Speaker 1: going to continue to lean into. Is like, look, this 361 00:19:29,400 --> 00:19:32,680 Speaker 1: guy's basically electing Trump. He is Trump's but he supports 362 00:19:32,760 --> 00:19:35,000 Speaker 1: him and Youngkin because he doesn't want to piss off 363 00:19:35,000 --> 00:19:37,040 Speaker 1: the Republican base. Is kind of in a buying tier 364 00:19:37,080 --> 00:19:40,120 Speaker 1: because he doesn't want to distance himself too much from 365 00:19:40,160 --> 00:19:42,399 Speaker 1: the President. So I think that dynamic playing out is 366 00:19:42,400 --> 00:19:43,760 Speaker 1: going to be interesting. I think you're right. I think 367 00:19:43,840 --> 00:19:47,080 Speaker 1: ultimately Trump's Trump pushes mcauliff over the edge. In a 368 00:19:47,119 --> 00:19:49,119 Speaker 1: non Trump world, I actually think young Kin could have 369 00:19:49,119 --> 00:19:50,880 Speaker 1: a shot. He'd have a shot, He'd have a real shot. 370 00:19:50,960 --> 00:19:53,680 Speaker 1: I mean, look, I still think northern Virginia and Virginia 371 00:19:53,720 --> 00:19:56,320 Speaker 1: in particular are just a basically a blue state now. 372 00:19:56,359 --> 00:19:59,159 Speaker 1: But there's enough there that somebody like young Kin, some 373 00:19:59,240 --> 00:20:01,639 Speaker 1: sort of Hogan like figure, could pull it off. But 374 00:20:01,960 --> 00:20:04,840 Speaker 1: given the fact that Youngkin has to thread that line 375 00:20:04,880 --> 00:20:07,240 Speaker 1: and there's no way that he can, there's no that 376 00:20:07,280 --> 00:20:09,239 Speaker 1: way that he can try and denounce Trump the way 377 00:20:09,280 --> 00:20:12,680 Speaker 1: that Hogan has or other Republican governors in blue states, 378 00:20:12,840 --> 00:20:15,520 Speaker 1: I don't think that he ultimately pulls off that. Being said, look, 379 00:20:15,560 --> 00:20:17,320 Speaker 1: the bellweather is a bellweather, and we're going to keep 380 00:20:17,320 --> 00:20:20,919 Speaker 1: an eye on it. Fact it's even close. It is interesting. Yeah, 381 00:20:20,960 --> 00:20:23,680 Speaker 1: And the other thing that was interesting in this analysis 382 00:20:23,720 --> 00:20:27,639 Speaker 1: is what voters said that they cared about. The economy 383 00:20:27,680 --> 00:20:31,119 Speaker 1: and COVID continue to be really significant, seen as the 384 00:20:31,119 --> 00:20:34,040 Speaker 1: most important issues. One thing that I did take note 385 00:20:34,040 --> 00:20:36,880 Speaker 1: of is there's been a lot of conversation among Republicans 386 00:20:36,880 --> 00:20:40,200 Speaker 1: and suburban voters about critical race theory and education, et cetera. 387 00:20:41,560 --> 00:20:45,040 Speaker 1: It was a fairly narrow lead, but on the first 388 00:20:45,040 --> 00:20:47,280 Speaker 1: of all, the voters who were most concerned about education 389 00:20:47,400 --> 00:20:51,560 Speaker 1: preferred mccauliffe, and overall voters preferred mccauliff to Young Cain 390 00:20:51,720 --> 00:20:53,600 Speaker 1: on education. So I just thought that was kind of 391 00:20:53,600 --> 00:20:55,720 Speaker 1: an interesting note too, that that issue may not be 392 00:20:56,359 --> 00:20:59,960 Speaker 1: playing out as effectively for Republicans ultimately as they thought 393 00:21:00,080 --> 00:21:02,600 Speaker 1: that it would. Yeah, I think that's right. All right, guys, 394 00:21:02,600 --> 00:21:05,440 Speaker 1: thanks for watching. We'll have more for y'all later. Thanks 395 00:21:05,480 --> 00:21:07,560 Speaker 1: for listening to the show, guys, we really appreciate it. 396 00:21:07,560 --> 00:21:09,600 Speaker 1: To help other people find the show, go ahead and 397 00:21:09,640 --> 00:21:12,480 Speaker 1: leave us a five star rating on Apple Podcasts or 398 00:21:12,520 --> 00:21:15,720 Speaker 1: wherever you get your podcasts. Really helps other people find 399 00:21:15,840 --> 00:21:19,359 Speaker 1: the show as always special. Thank you to supercast for 400 00:21:19,480 --> 00:21:22,360 Speaker 1: powering our premium membership. If you want to find out more, 401 00:21:22,480 --> 00:21:24,680 Speaker 1: go to crystalansager dot com.