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Speaker 1: Hello the Internet, and welcome to Season twenty seven, episode

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Speaker 1: three night Feist for April eighteen, two thousand eighteen. My

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Speaker 1: name is Jack O'Brien a K. I'm Jack Jack in

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Speaker 1: the New York Groove. That is ace freely courtesy of

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Speaker 1: Snarky Dessad on Twitter. Nailed it, and I am thrilled

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Speaker 1: to be joined as always by my co host, Mr

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Speaker 1: Miles Greg. Yeah, well you know, Miles gray is my

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Speaker 1: favorite color. Why I felt so symbolic yesterday smoking cool

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Speaker 1: with weed. I just want to be a big star.

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Speaker 1: Thank you to a Catfish Hunter seventy eight for that

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Speaker 1: one that all nineties bullshit song. A gay is a

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Speaker 1: welcome so much feeling in your voice. I mean, you know, honestly,

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Speaker 1: I that song. I really liked a good song, and

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Speaker 1: no like in an unhealthy way. So yeah, but anyway,

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Speaker 1: let's let's not make this about me. Why am I

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Speaker 1: h We can't believe that had a real purpose. Oh yeah,

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Speaker 1: let's okay, Oh yeah, section because I'm Miles great anyway, Yes,

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Speaker 1: that's that's how we do this. And we are thrilled

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Speaker 1: to be joined in our third seat by the hilarious

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Speaker 1: comedian Marlena Rodrigue, What song will you be seeing? Um? Okay,

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Speaker 1: I'll started the do you to pay for that? Just

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Speaker 1: those two? Just just also the lyrics lightly, so it's

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Speaker 1: a pair. I'm not a fair use segment, but yes

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Speaker 1: I like it. You go. Oh that had a purpose

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Speaker 1: because prior to recording I was just screaming, scream singing

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Speaker 1: the entire song. And I think you probably thought, where

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Speaker 1: the funk? Am I? What this dude happen? Who will

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Speaker 1: stop talking about Adam Durrett's prolific celebrity data as we

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Speaker 1: looked at his Wikipedia. Don't forget just the magnitude of

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Speaker 1: settling that we are faced with, Right, white guy with dreads? Yeah, Marlena,

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Speaker 1: what is something from your search history that is revealing

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Speaker 1: about who you are? Oh? Revealing about who I am?

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Speaker 1: We are? I might have I might have done this wrong. Um,

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Speaker 1: but I have a habit of um getting really high

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Speaker 1: and convincing myself. I definitely have herpes. Wow, do the

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Speaker 1: same thing, but cancer? Okay, right, way cooler one. I

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Speaker 1: used to do that when I was in my teenage.

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Speaker 1: M No reason, there's no reason at all, But every

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Speaker 1: single time I am just so sure. And so that's

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Speaker 1: what I'm googling all the time, just like do I

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Speaker 1: have herpes? Like what which one is the herd? Simplex? Um,

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Speaker 1: why do I have? How long? How long do I have?

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Speaker 1: The cold that I think people? I remember that was

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Speaker 1: the thing when I was a teenager. I read it's

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Speaker 1: like sometimes people get a cold before outbreak or something,

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Speaker 1: and that had me all funked up because out of

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Speaker 1: cold and I was like, oh, I've heard pies or whatever.

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Speaker 1: I mean mistake was that, I you know, how like

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Speaker 1: really hot people just have her bees you know that.

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Speaker 1: I mean, you know, yeah, it's like every reality. Well

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Speaker 1: it's very common, so I think, yeah, just by sheer

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Speaker 1: volume of course. Yeah. In college, it was like the

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Speaker 1: hottest guy had ever seen. UM paid attention to me.

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Speaker 1: And the first night that we ever like hooked up,

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Speaker 1: not even we didn't even do it. It was very sweet.

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Speaker 1: It was wonderful. And then UM we were just like

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Speaker 1: hanging out at his apartment and he was like, I

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Speaker 1: tell you something. I was like, oh what, and he

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Speaker 1: was like, I have heart bees and I was like, no,

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Speaker 1: you don't. After it, and then that happened three more

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Speaker 1: times and then uh, and then I had to believe

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Speaker 1: it but he told you didn't work out. It didn't.

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Speaker 1: It was just a back and forth in that moment

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Speaker 1: of like yes I do and like no, it was

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Speaker 1: real bad. Yeah, you were to getting over the perception

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Speaker 1: that yet and I never you know, I never got

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Speaker 1: to sucistic. I never got to raw dog with him.

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Speaker 1: I'm sorry, so sorry to hear that. Well, now his

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Speaker 1: dad is president, so you know it's rough. Yeah, it

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Speaker 1: as Marlene. What is something you think is underrated? Um? Underrated? Okay,

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Speaker 1: now I did and understanding correctly and underrated about myself?

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Speaker 1: Whatever you want anything? Yeah, no, I like this. No, no, no, no, no.

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Speaker 1: This is why we like. This is the form it's

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Speaker 1: meant to be. And I don't think that everybody should

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Speaker 1: be like my sense of humor is underrated. My shoulders,

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Speaker 1: that's where we're going. She's viciously scratching something out of

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Speaker 1: her not I can't do that. Um underrated about you?

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Speaker 1: About me? As everything is is. I was in the

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Speaker 1: first high school production of Cats, like the first licensed

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Speaker 1: to product like what do you mean? Correct? Thank you?

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Speaker 1: And I was also in the most underrated role, which

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Speaker 1: was the cat's chorus. Now, as you all obviously understand

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Speaker 1: the cat's course is the group of understudies um not

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Speaker 1: only learned the entire show, um, but never we're actually

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Speaker 1: on stage and just stood backstage in front of a

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Speaker 1: mic and saying all the words no, not, we didn't

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Speaker 1: even get that far. Yeah, yeah, I thought that was

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Speaker 1: extremely underrated half of society. Rum Tum Tugger is a

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Speaker 1: curious cat. You know, thank you so much. Would you

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Speaker 1: say that that play in general is is underrated? I

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Speaker 1: would say musical, I would say it's it's deeply underrated.

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Speaker 1: Did T. S. Eliott had a lot of backstories behind

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Speaker 1: those cats? I know, isn't that interesting? A lot of

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Speaker 1: a lot of them. Do yourself a favor, get crazy

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Speaker 1: high and just start reading that Wikipedia, like weird little stories. T. S.

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Speaker 1: Eliott wrote about like neighborhood strays. Yeah, and like really

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Speaker 1: huge backstories. One was like a paid whore and just

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Speaker 1: and then got old. Now like no one, like my

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Speaker 1: mom does the exact same thing with animals when she

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Speaker 1: adopts them. So she said back stories, Yeah, like she

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Speaker 1: was the first catch she adopted was this cat or

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Speaker 1: like her that had given birth to a litter of cats,

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Speaker 1: and all the kittens were adopted and like her friend

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Speaker 1: whose house the cat given birth. She's like, I got

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Speaker 1: homes for everyone except for the mother, and my mom goes,

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Speaker 1: I will take her, okay. And then when suddenly I

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Speaker 1: go over there, what fun? Like what is this catch

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Speaker 1: you guys? She was a single mother on the streets

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Speaker 1: with nowhere to go, and I was like okay, and

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Speaker 1: then I just asked around. I was like, okay, so

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Speaker 1: this is what happened. She loves to do that. Then

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Speaker 1: now she has put that fixation on possums. My mom

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Speaker 1: is a possum. My mom go the worst. This is

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Speaker 1: what happened. Let me bust them in here. My mom

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Speaker 1: capes for possums. She has. She's a fucking card carrying

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Speaker 1: member of like the Possum Society or some But they

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Speaker 1: get a bad rap because they don't have her bees

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Speaker 1: or I'm sorry, herpie. Oh sorry, guy got put in

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Speaker 1: my brain. They don't have rabies and that's why you

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Speaker 1: can kiss them. But yeah, she's like, you know, like

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Speaker 1: it's not they have rabies and things like that. They're

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Speaker 1: really docile or whatever. They just look they do not

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Speaker 1: have rabies. Yeah, they just look like they just look

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Speaker 1: like total ship because they have like pink eyes and

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Speaker 1: weird and like jagged ass teeth. And my mom's like,

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Speaker 1: you can't just assume that. And I'm like, okay, well,

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Speaker 1: their mouths are incredibly clean, and then she's like yeah,

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Speaker 1: it's like and yeah, and so she like feeds them

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Speaker 1: now and like they get along with my cat. My

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Speaker 1: mom's got a whole menagerie going on. Their wild possums.

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Speaker 1: They're wild possums that hang out with my mom's cats

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Speaker 1: because my mom has like gotten the cats used to

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Speaker 1: the possums because my mom she's never touched the possum.

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Speaker 1: But she sees again, she saw possum with a litter,

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Speaker 1: and she goes, it's a single mother. Oh and the kids,

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Speaker 1: they just they need water because in the summery it

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Speaker 1: was hot and in the valley like it's dry as ship,

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Speaker 1: so like the animals do come out looking for water.

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Speaker 1: So she just she turned her backyard into the fucking

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Speaker 1: you know, the neighborhood spot for possums. Congrats on her

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Speaker 1: having a backyard. Look at me. Look, I didn't mean

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Speaker 1: to flex on you. We're out here, uh, but that

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Speaker 1: just going back to the T. S. Eliot thing. I

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Speaker 1: was so surprised by that because Cats is such a

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Speaker 1: piece of culture that is looked down on by like

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Speaker 1: high faluting like New Yorkers and stuff. And the fact

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Speaker 1: that it was like based on a T. S. Eliot

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Speaker 1: work is like the last thing you would express. So yeah,

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Speaker 1: check out the Wikipedia of Cats is dope. I'm sorry,

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Speaker 1: just one question. You said your high school was the

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Speaker 1: first high school to do a production of Cats. What

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Speaker 1: is your high school? Your high school like a special theater.

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Speaker 1: I went to two high schools at the same time,

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Speaker 1: so in the morning, I'm sorry, how is that possible? Um?

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Speaker 1: So I have a fake idea. It sounds like a

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Speaker 1: wacky eighties comedy, Like then you run out and like

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Speaker 1: put a backwards hat on and a fake mustache. I

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Speaker 1: would say, that's like a fair That is exactly. Uh.

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Speaker 1: We would go to regular high school in the morning,

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Speaker 1: so from like seven thirty to twelve thirty, we'd take

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Speaker 1: like math and science, and then we'd all jump in

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Speaker 1: a bus about twenty of us and we would go

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Speaker 1: to Hartford downtown whatever and uh yeah, the dirty water

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Speaker 1: and m and then we would from one to four

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Speaker 1: fifteen do like whatever. So I was a voice major

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Speaker 1: for three years and then I switched to theater. No,

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Speaker 1: I heard it. You gave us a taste of Whitney.

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Speaker 1: I'm really really talented at like at like the bads singing,

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Speaker 1: like bad singing that sounds like really good. Yeah yeah, okay,

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Speaker 1: you know, but um, good singing that is a different challenge.

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Speaker 1: What is that? Can you give us an example of,

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Speaker 1: like something people would have heard of that is bad

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Speaker 1: singing that sounds good? Um? I like to take gold

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Speaker 1: Link songs and turn them in too, operrett Us, So

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Speaker 1: perchance I want to be more than whole knees. That's awesome.

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Speaker 1: What is something that is overrated about yourself? But it's

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Speaker 1: not supposed to be it's not supposed to but that,

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Speaker 1: But that's what would be Like this, Yo, you're changing

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Speaker 1: the game, and see from your underrated about yourself, we

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Speaker 1: got to an underrated about the world. And here I

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Speaker 1: want to think of something that is genuinely overrated. Um,

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Speaker 1: hating Beyonce is overrated. I feel like some people who

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Speaker 1: hate Beyonce because she's overrated, Like those people think she's overrated? Yeah,

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Speaker 1: I can go themselves. Yes, I think they're very cool

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Speaker 1: for not liking Beyonce. I think those are people who

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Speaker 1: just have to be contrarian, because I mean you can.

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Speaker 1: I mean I could look at the sun and know

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Speaker 1: that it's the sun, okay, and I could look at

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Speaker 1: Beyonce and know that is a god entity from another dimension,

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Speaker 1: only a goddess. Yeah did you see the twitter that?

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Speaker 1: Did you see? Someone tweeted about their conversation with their

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Speaker 1: mom was live texting them while watching the Coachella live

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Speaker 1: stream about Beyonce and she's like, oh my god, I

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Speaker 1: can't believe. How have I not known about this? This

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Speaker 1: is impossibly a spectacular this performance. She's in her fourth outfit.

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Speaker 1: Oh my good. Yeah, she's like I thought she was

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Speaker 1: a lot before, but I never had seen it as

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Speaker 1: it's like this long. These sex are like full on paragraphs,

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Speaker 1: and I was like, see, that's what happens when she's

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Speaker 1: the best cooked. I do feel like this is the

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Speaker 1: point at which everybody has been forced to admit that

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Speaker 1: Beyonce is great, Like that that show, for whatever reason,

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Speaker 1: was the point like that even the people who were

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Speaker 1: like funck Beyonce are now like shit, I was I

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Speaker 1: was wrong, Like I kind of had a feeling I

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Speaker 1: was wrong before, but now I know that I'm completely wrong.

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Speaker 1: A kind of ye kind of bit off more than

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Speaker 1: that two it was two hours. Yeah, all right. And finally, Orlanta,

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Speaker 1: what does a myth? What is something people think it's

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Speaker 1: true that you know to be false. I okay, so uh,

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Speaker 1: I have a very tiny one, um, and then a

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Speaker 1: bigger one. So the tiny one is that Nordstrom will

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Speaker 1: take any return that is that is false. Uh. They

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Speaker 1: have they used to work there, and they have like

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Speaker 1: a whole system for not taking returns, a lot of

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Speaker 1: loopholes because before people always thought Norston was the place

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Speaker 1: you would buy something because if you leave the tag on,

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Speaker 1: they will always take it back. Even then they'd be like,

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Speaker 1: if you take the tag off, you can bring it back. Okay, yeah,

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Speaker 1: if you take But at this point they will kind

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Speaker 1: no longer do that because everybody's take advantage and they

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Speaker 1: really keep track of like the bitches coming in returning

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Speaker 1: all the time, and they start marking you down there,

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Speaker 1: like they'll send you a letter being like stop it,

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Speaker 1: You're no longer allowed to come here, even though their

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Speaker 1: entire brand as you can return when Yeah, I know

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Speaker 1: that's crazy. Should let Lacey know because I know Lacy

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Speaker 1: a big he loves the scams, they'll get you. And

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Speaker 1: Target has a forensics department. They have like labs to forens.

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Speaker 1: Like they put some return product under a black light

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Speaker 1: and like see all the it looks like a Jackson

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Speaker 1: Pollock and they're like this was an electric tea kettle

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Speaker 1: are everywhere. Yeah, we cannot take this. Uh that's crazy.

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Speaker 1: They have a friends. Okay, so that's a small myth.

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Speaker 1: Plus they will not take your ship, thank you. Other

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Speaker 1: myth Cuba not really there, Cuba one, Yeah, not really there,

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Speaker 1: but that the people are deprived and there for super

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Speaker 1: unhappy and suffering. Right. Um I went, and they're fucking

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Speaker 1: so happy, um and not like not like we know

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Speaker 1: where deprepped and we're very happy. They don't. They just

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Speaker 1: kind of don't know. And it's really fascinating to see

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Speaker 1: like they don't have phones, or they have phones, but

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Speaker 1: not to the extent that we do. They don't have

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Speaker 1: like as much entertainment. They just have so much less.

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Speaker 1: And I really thought I was gonna show up and

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Speaker 1: see like sad people, and I what I actually saw

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Speaker 1: was like people that were very very present and seemingly

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Speaker 1: content in their lives and it was really beautiful. And

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Speaker 1: then does that bum you out too, because you came

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Speaker 1: into it thinking it was going to be like that,

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Speaker 1: because that's how I felt, like, okay, because yeah, when

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Speaker 1: I went to Africa, I was like, man, I felt

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Speaker 1: the same thing. I was like, I don't know what

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Speaker 1: I'm gonna see, like blah blah blah. And then you

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Speaker 1: realize it's just human nature right to make the best

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Speaker 1: of your situation. It's not everyone lives comparatively like people

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Speaker 1: aren't in Cuba thinking man, if I have four g

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Speaker 1: L T E man like blah blah blah, Like you

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Speaker 1: know what I mean, And so to them, there's no

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Speaker 1: other reason but just but to be happy. And then

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Speaker 1: I was kind of like, damn, like I felt shitty

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Speaker 1: that I was even like projecting my relative comfort and

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Speaker 1: technological access and like and and projecting that on a

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Speaker 1: so and be like, oh, that that must be terrible

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Speaker 1: for them. And I was like, yeah, you know what,

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Speaker 1: that's because I'm used to it and I've been coddled

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Speaker 1: by this like advanced technology or whatever, and yeah, yeah,

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Speaker 1: it's not the basis of my happiness. That's that's I

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Speaker 1: guess that's what you learned too, is that's not what

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Speaker 1: makes you happy they have to filter their water like

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Speaker 1: they like when you visit, you can't drink their water.

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Speaker 1: But also they can't drink their water. It's not like

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Speaker 1: they're used to it or something, and it's like they

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Speaker 1: don't even they're not even a little bit going to

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Speaker 1: complain about that. Yeah, it was, it was pretty cool,

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Speaker 1: but still you know, Oh, A great tip is if

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Speaker 1: you visit, don't stay in the hotels because the hote

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Speaker 1: that means of money goes to the government and no

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Speaker 1: one knows what happens. But if you stay in a cosa,

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Speaker 1: which is essentially a b and b uh, that money

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Speaker 1: go to the community and it helps like build help

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Speaker 1: them also in those hotels, it might hit you with

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Speaker 1: that sonic ray. I just heard a really interesting interview

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Speaker 1: with somebody who's been doing a lot of studies on

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Speaker 1: loneliness in America and Western culture, but America in particular,

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Speaker 1: and how much lonelier our culture is than just like

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Speaker 1: every other culture. Like now that we have all this

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Speaker 1: technology and stuff, we like, people are reporting It used

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Speaker 1: to be that you had an average of four to

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Speaker 1: five close friends, and now modern people report zero close friends.

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Speaker 1: They're just like, uh, not really like they ask you

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Speaker 1: to define like like they say, Okay, do you like

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Speaker 1: have somebody who you can trust with this? Do you

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Speaker 1: have somebody you can trust with it? And like by

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Speaker 1: the definition, they're like, oh, you have zero close friends

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Speaker 1: trust like and yeah they There's a really interesting interview

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Speaker 1: on uh some podcasts that I'm drawing to blank on

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Speaker 1: but basically saying that a lot of our health problems,

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Speaker 1: a lot of our mental health problems are just essentially

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Speaker 1: the fact that we've cut ourselves off from socializing and

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Speaker 1: social networks. Um So, I don't know, we'll talk more

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Speaker 1: about that at a later date, but I'm sure that's

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Speaker 1: at least partially why people in these other countries that

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Speaker 1: don't have for G connectivity are actually seem happier than

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Speaker 1: you might expect. Yeah, we lose our humanity with the

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Speaker 1: more technology we embrace, right, I think that's just goes

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Speaker 1: hand in hand. It's crazy how easily they can just

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Speaker 1: talk to other people right right in American people like

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Speaker 1: I think I'm gonna call the cops on these black

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Speaker 1: guys who are sitting down right, That's that's where we're

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Speaker 1: a I won't even say ship to them. I'm just

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Speaker 1: kidding you. Know what, I think, I want the police

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Speaker 1: to talk to that. That's right, she just didn't talk

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Speaker 1: to because they were sitting there, because she doesn't know

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Speaker 1: how to talk to people, and we don't know how

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Speaker 1: to talk to each other. Hey, that brings us to

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Speaker 1: the modern world, the news of the day. We're trying

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Speaker 1: to take a sample of the global uh slash national

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Speaker 1: share consciousness. What people are thinking. You're talking about right now? Uh.

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Speaker 1: So we want to start out with an image that

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Speaker 1: went viral yesterday. Stormy Daniels released the police sketch of

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Speaker 1: the man who threatened her, which I think that was

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Speaker 1: when she told her story about the guy coming up

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Speaker 1: and threatening her on sixty minutes she told that story, Uh,

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Speaker 1: I think everybody was like, oh, well, give us tell

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Speaker 1: us who that person was, or like, look through all

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Speaker 1: the pictures in America, let's find this motherfucker in America.

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Speaker 1: Let's find everyone. Let's look through everybody find them. But

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Speaker 1: so she did a police sketch with somebody who you know,

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Speaker 1: police sketches are generally not super well trusted and scientifically

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Speaker 1: they're not great and sometimes they uh make your memory

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Speaker 1: of somebody's face less accurate because you're having to like

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Speaker 1: match are having to go back and forth between your

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Speaker 1: memory of the thing and then what the drawing looks like,

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Speaker 1: and it sometimes gets blended other times. Super producer Ana

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Speaker 1: Josnie was saying that she thinks that sometimes people end

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Speaker 1: up describing someone who is, you know, familiar to them

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Speaker 1: and not necessarily the stranger who they're trying to describe.

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Speaker 1: Which is interesting because so this picture came out, Um,

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Speaker 1: people were saying young Willem Dafoe, Tom Brady, uh, Starship

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Speaker 1: Troopers star Casper van Dean, and the puppet from Team

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Speaker 1: America all blended together. Um, and it really does look

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Speaker 1: like a blend of all those things. And then this

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Speaker 1: morning tmz uh posted an article pointing out that, uh,

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Speaker 1: it's actually just her husband. The drawing is her husband.

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Speaker 1: It looks almost identical to like her third husband. It's

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Speaker 1: it's very crazy how much it looks like her husband. Like, oh, yeah,

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Speaker 1: I mean they may have a point. Also, what a

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Speaker 1: barber that guy suck? Yeah, his eyebrows are a mess,

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Speaker 1: but so aggressively trying to be handsome. Yeah, he looks

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Speaker 1: like mm a Barbie or like like if there was

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Speaker 1: a m M a toy. That's what he would be anyway.

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Speaker 1: So yeah, this guy Brendan Miller. Uh I thin guess

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Speaker 1: that's her husband. Yeah, just like him. Very strange. Uh

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Speaker 1: this maybe it was maybe it was him though. Yeah.

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Speaker 1: To be fair to sketch artists, uh and this one

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Speaker 1: in particular, this one seemed like they're somebody released some

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Speaker 1: of the drawings this person has done before based on

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Speaker 1: you know, descriptions, and they're like spot on. So this

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Speaker 1: is apparently the best sketch artist in America, the Guinness

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Speaker 1: World Record holder for being the most successful sketch right, which, yeah,

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Speaker 1: that so great. They found the right person to do

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Speaker 1: the job. That just seems weird that they looks so

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Speaker 1: much like. And we'll see if this, you know, ends

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Speaker 1: up leading to the arrest of the person who threatened

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Speaker 1: Stormy Daniels because she's saying, you know, I got a

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Speaker 1: hundred thirty one thousand dollars for the person who can

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Speaker 1: identify this person, which is funny because hundred thirty is

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Speaker 1: what Michael Cohen offered her to stf you. Uh, so

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Speaker 1: you know, she's you know, kind of taking a shot

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Speaker 1: at him. She had a whole nine hundred and nine

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Speaker 1: thousand more than her hundred more whoa do math, math class?

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Speaker 1: Take a seat art schools. I barely went to morning.

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Speaker 1: I was I was rehearsing for cats. But but that

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Speaker 1: brings up Michael Cohen, because yesterday I was reading this

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Speaker 1: thing about how just like how even shadier this dude

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Speaker 1: looks like when you really sort of look at his neighborhood,

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Speaker 1: where he's from, his family, so everyone knows he's friends

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Speaker 1: with Felix Sayer, who's like a lot of people are

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Speaker 1: saying like he might be his connection to Russia or whatever,

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Speaker 1: because that guy, Felix Sater, his dad was like a

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Speaker 1: coppo in a organized crime syndicate that was considered to

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Speaker 1: be one of Russia's largest um And then we find

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Speaker 1: out that his uncle owned a Brooklyn social club which

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Speaker 1: was a well known meeting spot for members of both

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Speaker 1: the Italian and Russian UH mafia. So in like the

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Speaker 1: seventies and eighties, and then they're saying, up until the nineties,

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Speaker 1: it was considered some people, I think, I guess some

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Speaker 1: people law enforcement, we're considering it the sort of headquarters

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Speaker 1: where the Russian mafia literally ran their entire crime organization

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Speaker 1: out of UH. And that's like a place that Michael

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Speaker 1: Collins family owns. It's like he owned Bada Bing essentially

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Speaker 1: basically it's called the elbe uh. And so it's it's

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Speaker 1: just it's just interesting to look at. I guess the

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Speaker 1: more you know, I think we're starting to see this pattern.

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Speaker 1: I think we're talking about it yesterday about how this

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Speaker 1: is just sort of like just the the doufy ist

398
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Speaker 1: h white people mafia ever of like just really inept criminals.

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Speaker 1: Uh and and now we're seeing like that's the world.

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Speaker 1: Michael Colin also grew up in like where his uncle

401
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Speaker 1: owned a mob hang out, so of course he's probably

402
00:23:04,400 --> 00:23:06,600
Speaker 1: gonna be had that mindset a little bit. I mean,

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Speaker 1: if you hear him talk once, it almost like just

404
00:23:10,680 --> 00:23:14,359
Speaker 1: the mafia is just pouring off of him, Like you

405
00:23:14,440 --> 00:23:17,240
Speaker 1: just feel like, Okay, this guy's out of central casting

406
00:23:17,359 --> 00:23:22,639
Speaker 1: for mafiosa. Right. Uh. Yeah, so it's not overly surprising.

407
00:23:22,720 --> 00:23:25,040
Speaker 1: And also the fact that he like threatens to do

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Speaker 1: physical harm to people on a regular basis, Yeah, I

409
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Speaker 1: don't think that's part of your law school training, right.

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Speaker 1: I don't know, it feels like it might be like

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Speaker 1: one of those night class electives. But I guess, like

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Speaker 1: I don't know. If you're screaming that you'll fuck someone's

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Speaker 1: soul over the phone, is like, I don't know what,

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Speaker 1: I don't know. That really feels like something they teach him,

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00:23:43,960 --> 00:23:46,280
Speaker 1: like Harvard Law, and well he did not go there.

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Speaker 1: I think he went to the clown School of Law

417
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Speaker 1: or whatever the place what I do to he was

418
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Speaker 1: going to be disgusting, Yeah, wasn't he Wasn't he like

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Speaker 1: a big personal injury lawyer. Yeah. So basically he made

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Speaker 1: an entire he built himself on having like those commerced

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Speaker 1: l booth you in accident. Thanks to Michael Cohen, I

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Speaker 1: got three million dollars. All right, we're gonna take a

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00:24:10,880 --> 00:24:22,760
Speaker 1: quick break. We'll be right back. And we're back, and

424
00:24:23,160 --> 00:24:26,560
Speaker 1: we are having sort of an extended tax day today,

425
00:24:27,280 --> 00:24:31,480
Speaker 1: which everybody wants to talk about. People love talking about taxes. Uh.

426
00:24:31,880 --> 00:24:37,320
Speaker 1: But yeah, so the I R. S website crashed yesterday,

427
00:24:37,400 --> 00:24:40,800
Speaker 1: so they extended it for I think today, just today,

428
00:24:40,840 --> 00:24:42,960
Speaker 1: maybe today or maybe I know. They definitely had to

429
00:24:42,960 --> 00:24:45,520
Speaker 1: extend it because they're like, hey, sorry, y'all crashed our

430
00:24:45,520 --> 00:24:48,880
Speaker 1: website because who knows. Of course it crashed on tax day,

431
00:24:49,080 --> 00:24:51,199
Speaker 1: but doing your taxes, getting your taxes in as a

432
00:24:51,200 --> 00:24:54,960
Speaker 1: big serious deal in America, and Miles you were pointing

433
00:24:54,960 --> 00:25:00,000
Speaker 1: out that that's not really the case anywhere. Okay, imagine

434
00:25:00,040 --> 00:25:03,080
Speaker 1: and everyone has done taxes in this room, and they're confusing,

435
00:25:03,400 --> 00:25:05,880
Speaker 1: and most of the time you have to consult a

436
00:25:05,920 --> 00:25:08,359
Speaker 1: person at H and R Block, an accountant, or use

437
00:25:08,440 --> 00:25:11,720
Speaker 1: turbo tax. And because the ship is so complicated, and

438
00:25:11,760 --> 00:25:15,159
Speaker 1: the reason is so complicated is because tax prepares lobby

439
00:25:15,200 --> 00:25:18,960
Speaker 1: the government regularly to keep the tax code as confusing

440
00:25:19,040 --> 00:25:22,199
Speaker 1: as fucking possible. So our only option is to go

441
00:25:22,320 --> 00:25:26,240
Speaker 1: to these places. Okay, there's an H and R Block lobby, yes,

442
00:25:26,440 --> 00:25:29,880
Speaker 1: oh yeah, big so yeah, there is such a thing

443
00:25:29,960 --> 00:25:32,639
Speaker 1: as big tax now, so into it. Who makes turbo tax?

444
00:25:32,880 --> 00:25:37,040
Speaker 1: They spend two million dollars on ship, Like basically they

445
00:25:37,040 --> 00:25:39,320
Speaker 1: do not want to simplify the tax code like outright,

446
00:25:39,400 --> 00:25:41,840
Speaker 1: Like that's in lobbying documents that that is what they're

447
00:25:41,880 --> 00:25:45,200
Speaker 1: stated purposes for their lobbying efforts. So when you look

448
00:25:45,240 --> 00:25:49,159
Speaker 1: at other countries like Denmark or Sweden, or Spain or Japan,

449
00:25:49,359 --> 00:25:51,919
Speaker 1: they already have systems in place where the government like

450
00:25:52,000 --> 00:25:54,920
Speaker 1: sends you a prepared return, they estimate your taxes using

451
00:25:54,960 --> 00:25:58,880
Speaker 1: information your employer and the bank already have because obviously

452
00:25:58,960 --> 00:26:01,080
Speaker 1: they know everything that the acts, like the institutions of

453
00:26:01,080 --> 00:26:03,840
Speaker 1: these countries. You know, in the UK, most people don't

454
00:26:03,840 --> 00:26:06,840
Speaker 1: follow returns, like the government will calculate your liability or

455
00:26:06,880 --> 00:26:08,800
Speaker 1: your refund and send you a check or a bill

456
00:26:08,880 --> 00:26:13,240
Speaker 1: unless you're self employed. Now in my other homeland, Japan,

457
00:26:13,680 --> 00:26:16,720
Speaker 1: very simple system, okay, So the Japanese version of the

458
00:26:16,720 --> 00:26:19,800
Speaker 1: I r S, which is the cocos. So they gather

459
00:26:19,960 --> 00:26:22,119
Speaker 1: all the pertinent data for each work or their income,

460
00:26:22,160 --> 00:26:25,040
Speaker 1: taxable benefits, number of personal exemptions, tax with held and

461
00:26:25,080 --> 00:26:28,320
Speaker 1: so on, and they compute how much taxpayer ohs down

462
00:26:28,320 --> 00:26:31,920
Speaker 1: to the fucking last penny, the last yen. And they

463
00:26:31,920 --> 00:26:34,800
Speaker 1: have precision withholding, so like they know exactly how to

464
00:26:34,840 --> 00:26:37,480
Speaker 1: calculate everything, and they'll just send you a postcard just

465
00:26:37,520 --> 00:26:39,199
Speaker 1: telling you, hey, this is what you made, this is

466
00:26:39,200 --> 00:26:41,360
Speaker 1: your refund amount, or this is what we're actually gonna

467
00:26:41,359 --> 00:26:44,159
Speaker 1: have to take out because you underpaid your taxes, and

468
00:26:44,200 --> 00:26:46,720
Speaker 1: we can just take that out of your account and boom,

469
00:26:46,760 --> 00:26:49,199
Speaker 1: you're done. That tell us how much we are Just

470
00:26:49,320 --> 00:26:52,360
Speaker 1: tell us why do I have to tell you? Why

471
00:26:52,400 --> 00:26:55,159
Speaker 1: am I paying somebody to tell me how much to

472
00:26:55,200 --> 00:26:58,160
Speaker 1: pay you the funk is this it made in addition

473
00:26:58,200 --> 00:27:01,040
Speaker 1: to the like turbo tax is of the world. I

474
00:27:01,440 --> 00:27:03,560
Speaker 1: bet it has something to do with the fact that

475
00:27:04,160 --> 00:27:08,520
Speaker 1: really really rich people can pay other can pay like

476
00:27:08,960 --> 00:27:13,080
Speaker 1: attorneys and you know, accountants to find ways to get

477
00:27:13,119 --> 00:27:15,760
Speaker 1: them to like not pay tax. Of course, yeah, because

478
00:27:15,800 --> 00:27:19,680
Speaker 1: the thing is so fucking complicated. Yeah, then you need

479
00:27:19,720 --> 00:27:22,320
Speaker 1: someone because also, let's be real, tax preparation services are

480
00:27:22,359 --> 00:27:25,280
Speaker 1: like they're in an existential crisis because algorithms and ship,

481
00:27:25,600 --> 00:27:27,320
Speaker 1: like the need to go to a human at an

482
00:27:27,440 --> 00:27:30,760
Speaker 1: H and R block is becoming like that business is shrinking,

483
00:27:30,760 --> 00:27:32,280
Speaker 1: which is why they had to get into like the

484
00:27:32,320 --> 00:27:34,879
Speaker 1: turbo tax game of offering ship like H and R

485
00:27:34,920 --> 00:27:36,720
Speaker 1: block at home or I think is whatever they're do

486
00:27:36,800 --> 00:27:40,439
Speaker 1: it yourself website services. So they're like up against it.

487
00:27:40,480 --> 00:27:43,720
Speaker 1: So it behooves them to make ship as complicated as possible.

488
00:27:43,840 --> 00:27:47,480
Speaker 1: Now we are trying to change ship. Elizabeth Warren introduced

489
00:27:47,480 --> 00:27:50,760
Speaker 1: a bill last year that would completely simplify the tax

490
00:27:50,840 --> 00:27:53,239
Speaker 1: code and make it easier for people to just have

491
00:27:53,320 --> 00:27:55,680
Speaker 1: Uncle Sam just send you the bill or be like, hey, brother,

492
00:27:55,680 --> 00:27:59,240
Speaker 1: you getting this refund um. And also it'll cut down

493
00:27:59,440 --> 00:28:02,800
Speaker 1: on so much eating up productivity for human beings and

494
00:28:02,840 --> 00:28:04,199
Speaker 1: save a lot of money in the long run if

495
00:28:04,200 --> 00:28:06,359
Speaker 1: you do ship like this. But again, when you got

496
00:28:06,400 --> 00:28:08,159
Speaker 1: people putting money at this thing to make it as

497
00:28:08,160 --> 00:28:11,200
Speaker 1: complicated as possible, we have this same thing year after

498
00:28:11,280 --> 00:28:13,160
Speaker 1: year after year. I feel like these stories come out

499
00:28:13,240 --> 00:28:15,359
Speaker 1: all the time where we're just talking about why can't

500
00:28:15,359 --> 00:28:17,719
Speaker 1: our tax would be more simple? Here's why uh, And

501
00:28:17,760 --> 00:28:20,359
Speaker 1: like the people who are arguing for keeping it as

502
00:28:20,400 --> 00:28:22,960
Speaker 1: complicated saying, well, we don't want to extend the reach

503
00:28:22,960 --> 00:28:25,640
Speaker 1: of the government. You don't want them doing your taxes,

504
00:28:25,640 --> 00:28:27,200
Speaker 1: Like can you really trust the I R S to

505
00:28:27,280 --> 00:28:29,800
Speaker 1: tell you what they're gonna do? Well, all of these

506
00:28:29,800 --> 00:28:31,960
Speaker 1: programs are voluntary, so even if the thing you got

507
00:28:31,960 --> 00:28:33,840
Speaker 1: from the government you didn't agree with, you can opt

508
00:28:33,840 --> 00:28:35,120
Speaker 1: out of it and do it yourself, or you can

509
00:28:35,119 --> 00:28:38,080
Speaker 1: be like, Okay, that looks cool, Yeah I'm with that. Again.

510
00:28:38,640 --> 00:28:40,640
Speaker 1: It's just a headache because it's one of those things

511
00:28:40,680 --> 00:28:43,800
Speaker 1: where most people in other countries are like what you'll

512
00:28:43,800 --> 00:28:46,280
Speaker 1: have to walk you do a what box full of

513
00:28:46,360 --> 00:28:49,800
Speaker 1: receipts and like panic over what kind of food you

514
00:28:49,800 --> 00:28:51,720
Speaker 1: can write off as an entertainment expense or whatever. It's

515
00:28:51,720 --> 00:28:54,040
Speaker 1: just it's crazy. You can tell that it's a good

516
00:28:54,040 --> 00:28:58,680
Speaker 1: idea to simplify the taxes, because when the Republicans introduced

517
00:28:58,680 --> 00:29:02,080
Speaker 1: their tax cuts, they claimed that they were making it

518
00:29:02,160 --> 00:29:05,240
Speaker 1: so that you could just file your taxes on one

519
00:29:05,280 --> 00:29:09,080
Speaker 1: side of a postcard. So like when they're lying about

520
00:29:09,240 --> 00:29:11,200
Speaker 1: having a good idea, even though they don't have it,

521
00:29:11,240 --> 00:29:14,760
Speaker 1: you can tell that that's right, probably worth looking into.

522
00:29:14,800 --> 00:29:17,080
Speaker 1: Obviously they're not going to do anything with it. But

523
00:29:18,080 --> 00:29:22,640
Speaker 1: I love tax time, isn't it the Oh, it's my favorite.

524
00:29:22,760 --> 00:29:25,320
Speaker 1: Are you to do a lot of tin works? I

525
00:29:25,360 --> 00:29:28,920
Speaker 1: take way less exemptions than I should, and so it's

526
00:29:29,000 --> 00:29:31,160
Speaker 1: kind of like a savings account and I get a

527
00:29:31,200 --> 00:29:36,360
Speaker 1: return every year, and then I buy something dumb year

528
00:29:36,520 --> 00:29:42,600
Speaker 1: a computer. Oh, you idiot, fool, you fool. Don't do

529
00:29:42,680 --> 00:29:45,600
Speaker 1: the pointing and the clicking. Well, I hope it's a

530
00:29:45,640 --> 00:29:48,040
Speaker 1: nice computer. Thank you so much. Okay, well there's hit

531
00:29:48,080 --> 00:29:51,320
Speaker 1: a nice computer. Yes, okay, that's part of why it

532
00:29:51,440 --> 00:29:54,840
Speaker 1: was dumb. Like you only do two things. Yeah, it's

533
00:29:54,880 --> 00:29:59,200
Speaker 1: like you don't need any on gaming tower? Needed the

534
00:29:59,240 --> 00:30:02,720
Speaker 1: gaming tower? I need the graphics card. How am I

535
00:30:02,720 --> 00:30:05,280
Speaker 1: going to watch two Ford music video clips? And New

536
00:30:05,320 --> 00:30:08,480
Speaker 1: Kis on the block. So we talked yesterday about the

537
00:30:08,520 --> 00:30:11,800
Speaker 1: fact that there is some tension going on in the

538
00:30:11,840 --> 00:30:16,920
Speaker 1: executive branch. The president and his cabinet are sort of

539
00:30:16,960 --> 00:30:23,040
Speaker 1: not agreeing on sanctions over Russia. In the aftermath of

540
00:30:23,240 --> 00:30:28,440
Speaker 1: the assassination of the former Russian spy, America punished Russia

541
00:30:28,480 --> 00:30:32,240
Speaker 1: a little more forcefully than the UK and France, and

542
00:30:32,440 --> 00:30:34,520
Speaker 1: when Trump found out about that, he was very mad.

543
00:30:35,000 --> 00:30:38,080
Speaker 1: We talked about this yesterday, just an update. So they

544
00:30:38,160 --> 00:30:40,720
Speaker 1: threw Nicki Haley under the bus. They were like, when

545
00:30:40,720 --> 00:30:43,959
Speaker 1: she said that we were doing these sanctions, she was confused.

546
00:30:44,320 --> 00:30:48,840
Speaker 1: So yesterday Nikki Haley just straight up said in public,

547
00:30:49,480 --> 00:30:54,480
Speaker 1: I don't get confused. She was just like, I don't

548
00:30:54,520 --> 00:30:57,000
Speaker 1: like her politics sometimes, but I like this. I like

549
00:30:57,120 --> 00:30:59,840
Speaker 1: that a lot and cudd love. The guy who said

550
00:30:59,880 --> 00:31:03,360
Speaker 1: that she got confused came out and was like, oh, yeah,

551
00:31:03,400 --> 00:31:07,440
Speaker 1: sorry that, I'm so sorry. She would never be confused.

552
00:31:07,480 --> 00:31:11,800
Speaker 1: I was actually confused. I'm actually I'm a nobody. That's

553
00:31:11,840 --> 00:31:14,520
Speaker 1: also such like a a loose thing to say about

554
00:31:14,520 --> 00:31:16,560
Speaker 1: a person or do they were confused, and to just

555
00:31:16,680 --> 00:31:19,480
Speaker 1: say about yourself I do that is not an option

556
00:31:19,560 --> 00:31:24,800
Speaker 1: in my brain. I never get I go right or

557
00:31:24,880 --> 00:31:28,240
Speaker 1: left right, There is no there is no no confusing down.

558
00:31:28,280 --> 00:31:30,360
Speaker 1: That was not part of my operating system. But yeah,

559
00:31:30,520 --> 00:31:32,520
Speaker 1: I think it's also the first time I've heard anyone

560
00:31:32,560 --> 00:31:34,800
Speaker 1: from the administration be like, oh, that was a mistake.

561
00:31:35,160 --> 00:31:37,440
Speaker 1: I shouldn't have said that, right, Like not even when

562
00:31:37,520 --> 00:31:40,040
Speaker 1: John Kelly saying like crazy ship like, oh, slavery was

563
00:31:40,080 --> 00:31:44,520
Speaker 1: the best time in America because families were together. Excuse me,

564
00:31:44,520 --> 00:31:48,480
Speaker 1: how's that now? Yeah, he's not like, yeah, I shouldn't

565
00:31:48,520 --> 00:31:51,000
Speaker 1: have You're right, Like, that's just sort of sounds like

566
00:31:51,080 --> 00:31:53,360
Speaker 1: a foreign language to me when I hear that. Also

567
00:31:53,760 --> 00:31:56,440
Speaker 1: on this front, there was legislation that we had talked

568
00:31:56,440 --> 00:32:00,840
Speaker 1: about last week that was supposedly had bipartisans report to

569
00:32:01,120 --> 00:32:05,640
Speaker 1: protect the Mueller investigation that has officially been killed obviously

570
00:32:06,920 --> 00:32:12,440
Speaker 1: too much crying up. I was all wet when I

571
00:32:12,480 --> 00:32:15,680
Speaker 1: hear bipartisan support. Who I get going, you know what

572
00:32:15,680 --> 00:32:19,240
Speaker 1: I mean, I'm just like, let's get ready, um, and

573
00:32:19,280 --> 00:32:22,960
Speaker 1: then it goes away, and because just goes just the

574
00:32:23,000 --> 00:32:29,680
Speaker 1: mention of Mitch McConnell, Yeah, I like, yeah, he's uh,

575
00:32:30,120 --> 00:32:31,880
Speaker 1: he won't do it, But I Chuck Grassley, I think

576
00:32:31,880 --> 00:32:33,640
Speaker 1: it's just like I don't give a funk. We're gonna

577
00:32:33,680 --> 00:32:35,400
Speaker 1: we're gonna move this thing out of committee and he

578
00:32:35,400 --> 00:32:37,200
Speaker 1: will still take a vote on it. I mean sure,

579
00:32:37,360 --> 00:32:41,200
Speaker 1: but that means fun all if right, it's not getting

580
00:32:41,200 --> 00:32:44,040
Speaker 1: done without me. But so you have a theory about

581
00:32:44,040 --> 00:32:47,240
Speaker 1: where things are going to go next? How I have

582
00:32:47,320 --> 00:32:50,800
Speaker 1: a theory based on watching the news right, Uh, which

583
00:32:50,880 --> 00:32:55,240
Speaker 1: news I can't but let's be h, only watch the

584
00:32:55,240 --> 00:32:59,320
Speaker 1: Girbel's network. So right now, people like Devin noon Is,

585
00:32:59,440 --> 00:33:02,880
Speaker 1: Bob good Lot, and Trey Goudy, the three horsemen of Focoury,

586
00:33:03,680 --> 00:33:07,880
Speaker 1: are asking Rod Rosenstein for like unredacted versions of James

587
00:33:07,920 --> 00:33:10,680
Speaker 1: Comby's contemporaneous memos that he was taking when he was

588
00:33:10,680 --> 00:33:12,120
Speaker 1: talking to Trump, because they're like, oh, we're gonna have

589
00:33:12,120 --> 00:33:13,840
Speaker 1: need to look at that, Like there's there's stuff in

590
00:33:13,880 --> 00:33:16,320
Speaker 1: there that the dossier made of. It's all like, it's

591
00:33:16,320 --> 00:33:19,080
Speaker 1: all confusion, It makes no sense. They keep man. Devin

592
00:33:19,280 --> 00:33:21,600
Speaker 1: Is on handity just couldn't stop talking about the fucking

593
00:33:21,640 --> 00:33:24,720
Speaker 1: dossier and then somehow remembering that he basically needed to

594
00:33:24,720 --> 00:33:28,040
Speaker 1: create a false conflict with Rod Rosenstein to begin this

595
00:33:28,120 --> 00:33:30,920
Speaker 1: new attack on him. So what it looks like is

596
00:33:31,160 --> 00:33:34,520
Speaker 1: they're asking for these notes. The Justice Department is like,

597
00:33:34,680 --> 00:33:37,720
Speaker 1: you're asking for evidence in an active investigation, Like that's

598
00:33:37,760 --> 00:33:40,200
Speaker 1: kind of weird, like it's open. So they're sort of like,

599
00:33:40,760 --> 00:33:42,720
Speaker 1: what do we say here is the only one that

600
00:33:42,760 --> 00:33:45,200
Speaker 1: can do that? Well, I mean like, obviously that's evidence

601
00:33:45,240 --> 00:33:47,560
Speaker 1: that he is looking at that Robert Mueller is too.

602
00:33:47,760 --> 00:33:49,800
Speaker 1: But the Congress is saying, you know, because we have

603
00:33:49,880 --> 00:33:51,720
Speaker 1: oversight on things like this, we also want to be

604
00:33:51,720 --> 00:33:53,920
Speaker 1: a party to looking at this evidence. And they're like,

605
00:33:54,800 --> 00:33:57,520
Speaker 1: it's not really the law works, but they know that

606
00:33:57,560 --> 00:33:59,880
Speaker 1: because all they want is to be able to say

607
00:34:00,160 --> 00:34:02,360
Speaker 1: we asked Rod Rosenstein to look at these things and

608
00:34:02,400 --> 00:34:04,680
Speaker 1: he said no, he's still wilding on us, and this

609
00:34:04,720 --> 00:34:07,240
Speaker 1: could be contempt of Congress or whatever. And I think

610
00:34:07,240 --> 00:34:10,160
Speaker 1: it's clearly again whenever they can try and drum up

611
00:34:10,200 --> 00:34:12,600
Speaker 1: some kind of fake gas conflict, I think that maybe

612
00:34:12,680 --> 00:34:15,400
Speaker 1: that's where this is headed, because they definitely took the

613
00:34:15,440 --> 00:34:17,200
Speaker 1: rounds yesterday of talking and be like, well, we're trying

614
00:34:17,239 --> 00:34:19,399
Speaker 1: to get these notes and we'll see these memos, we'll

615
00:34:19,400 --> 00:34:22,440
Speaker 1: see what happens, and setting him up for a conflict.

616
00:34:22,480 --> 00:34:24,279
Speaker 1: It's like I asked him to do an impossible thing

617
00:34:26,320 --> 00:34:29,400
Speaker 1: that he was supposed to give them yesterday. Rod Rosenstein

618
00:34:29,440 --> 00:34:30,920
Speaker 1: had a deadline of yesterday, and he said, I need

619
00:34:30,960 --> 00:34:33,480
Speaker 1: an extension because he's trying to figure out. He's like, Okay,

620
00:34:33,520 --> 00:34:35,200
Speaker 1: we gotta huddle up. What the fund are they trying

621
00:34:35,200 --> 00:34:37,920
Speaker 1: to do asking us for this? Uh so, I mean

622
00:34:37,920 --> 00:34:39,960
Speaker 1: it's a small thing that could turn into a big thing.

623
00:34:40,120 --> 00:34:42,560
Speaker 1: But just keep a lookout if you hear those three

624
00:34:42,640 --> 00:34:45,440
Speaker 1: dummies trying to be like, Oh, he's so uncooperative, I

625
00:34:45,480 --> 00:34:47,000
Speaker 1: don't know what to do. Maybe he needs to be

626
00:34:47,120 --> 00:34:53,360
Speaker 1: fired type. I wish under oath started when they started working, right,

627
00:34:53,480 --> 00:34:55,480
Speaker 1: just they were always under oath and we could arrest

628
00:34:55,520 --> 00:34:58,399
Speaker 1: them for being such lying. I just don't understand how

629
00:34:58,520 --> 00:35:04,239
Speaker 1: lying is just totally above board, right what. Yeah, it's

630
00:35:04,239 --> 00:35:07,680
Speaker 1: a many sided complex thing where you have people on

631
00:35:07,719 --> 00:35:09,799
Speaker 1: the left who try to not lie and then that

632
00:35:09,840 --> 00:35:11,880
Speaker 1: doesn't really work for them all the time, and then

633
00:35:11,920 --> 00:35:14,080
Speaker 1: you have on the right people love to lie. They

634
00:35:14,080 --> 00:35:16,160
Speaker 1: don't give a fuck, and I mean a lot of

635
00:35:16,160 --> 00:35:18,200
Speaker 1: time they're getting what they want. Yeah, I don't know,

636
00:35:18,239 --> 00:35:23,040
Speaker 1: it's I wish I just knew. I wish someone was like, oh, like, yeah,

637
00:35:23,080 --> 00:35:26,240
Speaker 1: you could play by the rules and you'll do okay

638
00:35:26,400 --> 00:35:33,200
Speaker 1: or could lie zero the fun you want? Absolutely nothing

639
00:35:33,200 --> 00:35:35,439
Speaker 1: wrong with Yeah, I mean a whole either way, left

640
00:35:35,560 --> 00:35:38,280
Speaker 1: or right. It's all lies to me. Everyone is obviously

641
00:35:38,320 --> 00:35:40,239
Speaker 1: going to push their version of the reality that they

642
00:35:40,280 --> 00:35:42,440
Speaker 1: want people to believe in. Uh, and it's up to

643
00:35:42,520 --> 00:35:44,799
Speaker 1: us to kind of use our own sound minds to

644
00:35:44,800 --> 00:35:47,319
Speaker 1: look at it and be like this seems motivated in

645
00:35:47,360 --> 00:35:54,160
Speaker 1: a weird word right on either side, Yeah, we are

646
00:35:54,239 --> 00:35:57,960
Speaker 1: up sound mind. Bright Bart has been emailing me. I

647
00:35:58,280 --> 00:36:00,640
Speaker 1: signed up for their email and a new letter. So

648
00:36:00,840 --> 00:36:04,480
Speaker 1: that's probably why he's an ally in the fight against

649
00:36:04,520 --> 00:36:07,640
Speaker 1: the white genocide, right exactly. But I like to keep

650
00:36:07,680 --> 00:36:09,560
Speaker 1: an eye on what what they're doing, what they're telling

651
00:36:09,600 --> 00:36:15,440
Speaker 1: their fans and uh so their latest pursuit, uh, they

652
00:36:15,520 --> 00:36:19,359
Speaker 1: are asking their fans to write to Congress and tell

653
00:36:19,400 --> 00:36:23,440
Speaker 1: them that conservative speech is not hate speech. So this

654
00:36:23,600 --> 00:36:27,600
Speaker 1: thing that we pointed out last week where Ted Cruz

655
00:36:27,640 --> 00:36:31,400
Speaker 1: was asking Mark Zuckerberg why he was shutting down Diamond

656
00:36:31,440 --> 00:36:35,120
Speaker 1: and Silk, Diamond and Silk, and Mark Zuckerberg for some

657
00:36:35,160 --> 00:36:37,719
Speaker 1: reason didn't know that they hadn't done that, and that

658
00:36:37,800 --> 00:36:42,400
Speaker 1: was actually uh, diamond and Silk misunderstanding a like form

659
00:36:42,480 --> 00:36:45,439
Speaker 1: email that they had received. So this is a thing

660
00:36:45,480 --> 00:36:50,520
Speaker 1: that they're really trying to push on, is the idea that, uh,

661
00:36:50,560 --> 00:36:53,960
Speaker 1: people are conflating conservative speech with hate speech. And I

662
00:36:54,000 --> 00:36:59,200
Speaker 1: think the reason they're doing that is because, uh, they

663
00:36:59,400 --> 00:37:03,040
Speaker 1: are hate speech. What are you gonna say, because I

664
00:37:03,080 --> 00:37:06,759
Speaker 1: would they hate speech. Yeah, they don't want to be

665
00:37:06,840 --> 00:37:10,680
Speaker 1: shut down, like you need to have your speech police

666
00:37:11,560 --> 00:37:14,760
Speaker 1: when you are saying things that are you know, riling

667
00:37:14,840 --> 00:37:18,080
Speaker 1: up hate and racism and people. Uh, and that has

668
00:37:18,160 --> 00:37:23,040
Speaker 1: become a mainstream, like a big part of the conservative agenda.

669
00:37:23,440 --> 00:37:29,120
Speaker 1: So yes, policing people's language for actual like hate and

670
00:37:29,760 --> 00:37:33,680
Speaker 1: violence and incitement of violence is a thing that needs

671
00:37:33,719 --> 00:37:37,080
Speaker 1: to happen. But they're not going to there, like it's

672
00:37:37,120 --> 00:37:40,279
Speaker 1: not hate speeches, dog listling it is dangerous to them.

673
00:37:40,600 --> 00:37:42,600
Speaker 1: But yeah, wait, so how are they even phrasing it?

674
00:37:42,640 --> 00:37:44,319
Speaker 1: In this email? They're like, are we we have a

675
00:37:44,360 --> 00:37:47,200
Speaker 1: war that we have to fight? Yeah, tell Congress Collen,

676
00:37:47,280 --> 00:37:51,800
Speaker 1: conservative speeches not hate speech. After weeks of dodging answers,

677
00:37:51,800 --> 00:37:55,279
Speaker 1: they talk about the Zuckerberg thing, Uh, and then they

678
00:37:55,320 --> 00:37:58,800
Speaker 1: say for years, companies like Google and Facebook have been banning, blocking,

679
00:37:58,840 --> 00:38:02,680
Speaker 1: and censoring any thing that goes against their worldview. That

680
00:38:02,800 --> 00:38:06,120
Speaker 1: fucking fallacy is so tired to me when they talk

681
00:38:06,239 --> 00:38:09,520
Speaker 1: that dumb shit. It's funny how they're only outraged when

682
00:38:09,960 --> 00:38:12,080
Speaker 1: a person on the right is being told like they

683
00:38:12,120 --> 00:38:16,839
Speaker 1: shouldn't just spread anti Semitic bullshit or islamophobic nonsense. They're like, oh,

684
00:38:16,880 --> 00:38:19,799
Speaker 1: that's you're censering my hate speech. But when fucking swastikas

685
00:38:19,800 --> 00:38:21,960
Speaker 1: and nooses show up places and I don't see that

686
00:38:21,960 --> 00:38:24,600
Speaker 1: ship on Fox News, they're not concerned with hate speech

687
00:38:24,600 --> 00:38:28,440
Speaker 1: in any form anyway. Like, so it's they have this,

688
00:38:28,680 --> 00:38:31,759
Speaker 1: It's just fucking yeah, they're trying to hide hide the

689
00:38:31,840 --> 00:38:35,040
Speaker 1: idea that it's actually a problem, so they would never

690
00:38:35,080 --> 00:38:37,839
Speaker 1: tell you about, you know, swastikas or news is um

691
00:38:37,960 --> 00:38:40,800
Speaker 1: and I think this is actually a bigger problem for

692
00:38:41,160 --> 00:38:47,760
Speaker 1: liberals than people are acknowledging or realizing. In the Comy interview,

693
00:38:47,800 --> 00:38:51,680
Speaker 1: Blitz he acknowledged that the whole reason that he basically

694
00:38:51,760 --> 00:38:55,239
Speaker 1: tipped the election in Trump's favor was he was concerned

695
00:38:55,480 --> 00:38:59,120
Speaker 1: of being seen as having a liberal bias by not

696
00:38:59,480 --> 00:39:02,879
Speaker 1: releasing the fact that they were reopening the investigation into

697
00:39:02,960 --> 00:39:06,719
Speaker 1: Hillary Clinton's email. Um. He was just concerned about being

698
00:39:06,760 --> 00:39:10,359
Speaker 1: seen as having a liberal bias, and Comey's fairness goes

699
00:39:10,440 --> 00:39:12,560
Speaker 1: too far right, you know what I mean, Like he

700
00:39:12,640 --> 00:39:15,160
Speaker 1: hits fair and then he's like, let me just show

701
00:39:15,160 --> 00:39:19,120
Speaker 1: everyone how fair is really done right exactly. And Obama too,

702
00:39:19,360 --> 00:39:20,960
Speaker 1: he didn't want to say that because he thought it

703
00:39:21,000 --> 00:39:23,480
Speaker 1: was gonna look crazy if he's the one telling people, hey,

704
00:39:23,640 --> 00:39:25,200
Speaker 1: you might want to look out for this Russia ship

705
00:39:25,280 --> 00:39:28,080
Speaker 1: or whatever. He was very sensitive that he didn't want

706
00:39:28,080 --> 00:39:30,640
Speaker 1: to appear that way. And it's just crazy because this

707
00:39:30,719 --> 00:39:33,759
Speaker 1: is like when facts are facts, right left or right,

708
00:39:33,800 --> 00:39:36,520
Speaker 1: we just have to accept them. Yeah, and I understand

709
00:39:36,920 --> 00:39:40,719
Speaker 1: the Russia investigation there was less to actually go out

710
00:39:40,760 --> 00:39:43,520
Speaker 1: with because it was such a sort of ongoing thing

711
00:39:43,600 --> 00:39:47,919
Speaker 1: and confidential thing that publicizing it could have been problematic.

712
00:39:47,960 --> 00:39:50,840
Speaker 1: But you know, you don't need to tell the world

713
00:39:50,880 --> 00:39:53,040
Speaker 1: that you're going to spend the next three days looking

714
00:39:53,040 --> 00:39:56,080
Speaker 1: into whether there might even be a chance that Hillary

715
00:39:56,680 --> 00:40:00,480
Speaker 1: did something wrong, like six days before the election. But

716
00:40:00,760 --> 00:40:04,879
Speaker 1: in his mind it was like, if he didn't do that,

717
00:40:04,960 --> 00:40:09,120
Speaker 1: he was having a liberal bias. So they're constantly shifting

718
00:40:09,360 --> 00:40:12,719
Speaker 1: the grounds on which we're having these discussions. And it's

719
00:40:12,760 --> 00:40:17,440
Speaker 1: also you know, Facebook is not an inherently conservative platform.

720
00:40:17,560 --> 00:40:21,759
Speaker 1: But they were incredibly helpful to the conservative cause during

721
00:40:21,760 --> 00:40:25,440
Speaker 1: the two thousand and sixteen election because they were concerned

722
00:40:25,440 --> 00:40:29,040
Speaker 1: about there were people hammering them right at the beginning

723
00:40:29,080 --> 00:40:31,400
Speaker 1: of the two thousand sixteen election about having a liberal

724
00:40:31,400 --> 00:40:34,239
Speaker 1: bias and about like wanting to help Hillary and having

725
00:40:34,280 --> 00:40:37,279
Speaker 1: helped Obama. And I just think that that's something that

726
00:40:37,400 --> 00:40:40,920
Speaker 1: the left really needs to grapple with, is allowing the

727
00:40:41,040 --> 00:40:45,080
Speaker 1: right to sort of set the different goal lines on which,

728
00:40:45,160 --> 00:40:47,600
Speaker 1: like we have these conversations. I mean, I think as

729
00:40:47,719 --> 00:40:50,480
Speaker 1: dismissive as the right is about their own hypocrisy, I

730
00:40:50,520 --> 00:40:51,960
Speaker 1: think on the left you just have to be just

731
00:40:52,000 --> 00:40:54,760
Speaker 1: as dismissive of these like just bullshit claims of being

732
00:40:55,080 --> 00:40:57,680
Speaker 1: censored or whatever, Like you're just saying that ship that

733
00:40:57,760 --> 00:41:00,719
Speaker 1: is not true. You're saying that to convince yourself that

734
00:41:00,840 --> 00:41:04,000
Speaker 1: you are not actually saying some dumb, inaccurate, hateful ship

735
00:41:04,360 --> 00:41:06,680
Speaker 1: or whatever. And in the past, I think because the

736
00:41:06,760 --> 00:41:10,520
Speaker 1: left hasn't had a voice because The New York Times

737
00:41:10,640 --> 00:41:15,000
Speaker 1: was completely subject to this criticism of you know, well,

738
00:41:15,040 --> 00:41:18,319
Speaker 1: now you're being biased, so they couldn't come out like

739
00:41:18,520 --> 00:41:20,239
Speaker 1: the New York Times has this thing where they have

740
00:41:20,360 --> 00:41:22,799
Speaker 1: to tell both sides of the story. You know, they're

741
00:41:23,120 --> 00:41:27,040
Speaker 1: objective journalists, so they know the rights. Fox News and

742
00:41:27,080 --> 00:41:30,680
Speaker 1: the left didn't really have anything even though people were

743
00:41:30,760 --> 00:41:33,600
Speaker 1: saying that the truth has a liberal bias. I guess,

744
00:41:33,840 --> 00:41:36,480
Speaker 1: but I do think things like crooked media and just

745
00:41:36,560 --> 00:41:40,320
Speaker 1: the podcasting landscape in general is going to be helpful

746
00:41:40,800 --> 00:41:44,200
Speaker 1: for just constantly resetting. Okay, here's what they're saying, has

747
00:41:44,239 --> 00:41:47,520
Speaker 1: a you know, is a liberal bias, but it's not

748
00:41:47,680 --> 00:41:49,560
Speaker 1: actually living And I guess the thing is too. As

749
00:41:49,760 --> 00:41:51,600
Speaker 1: much as they want to say, well, you know, conservative

750
00:41:51,600 --> 00:41:54,160
Speaker 1: speech is in hate speech, will look at the kind

751
00:41:54,200 --> 00:41:56,960
Speaker 1: of media that people who are acting out hate crimes.

752
00:41:57,239 --> 00:42:00,000
Speaker 1: Where are they getting their rocks off? From a media standpoint,

753
00:42:00,080 --> 00:42:03,000
Speaker 1: What Twitter accounts do they visit, What websites do they visit?

754
00:42:03,360 --> 00:42:06,040
Speaker 1: And you know, recently like Ben Shapiro, who's just a

755
00:42:06,080 --> 00:42:10,040
Speaker 1: fucking loser, has been attacking emails from that guy. Did

756
00:42:10,120 --> 00:42:13,360
Speaker 1: you get emails from that guy? You get what are

757
00:42:13,360 --> 00:42:15,600
Speaker 1: you trying to say? What? I don't know? I think

758
00:42:16,360 --> 00:42:20,640
Speaker 1: ever open that. Yeah, but he's been attacking one of

759
00:42:20,680 --> 00:42:23,759
Speaker 1: our friends on Twitter, but not attacking her, but just

760
00:42:23,840 --> 00:42:27,120
Speaker 1: being like, well, look at this guys like retweeting her

761
00:42:27,160 --> 00:42:31,520
Speaker 1: and then just letting his like, right, So this guy

762
00:42:31,719 --> 00:42:34,640
Speaker 1: in in uh in Montreal, I think right, it was

763
00:42:34,680 --> 00:42:37,200
Speaker 1: in Quebec, Like at the beginning of last year, this

764
00:42:37,239 --> 00:42:39,239
Speaker 1: man shot a bunch of people at a mosque and

765
00:42:39,320 --> 00:42:42,560
Speaker 1: killed six people. And during the trial they started doing

766
00:42:42,640 --> 00:42:45,640
Speaker 1: some forensic research on his like sort of activity on

767
00:42:45,680 --> 00:42:48,680
Speaker 1: the internet in the weeks media diet. Yeah, before the attack,

768
00:42:49,160 --> 00:42:52,359
Speaker 1: this guy checked the Twitter feeds of just all the

769
00:42:52,400 --> 00:42:56,320
Speaker 1: top right wing American commentators as well as conspiracy theorists

770
00:42:56,360 --> 00:42:58,960
Speaker 1: all right, white supremacist, neo not like all of it,

771
00:42:59,000 --> 00:43:02,120
Speaker 1: Like we was checking out Ben Shapiro and fucking even

772
00:43:02,120 --> 00:43:06,280
Speaker 1: Tucker Carlson, Richard Spencer and culture Mike Sernovich, Alex Jones,

773
00:43:06,360 --> 00:43:08,919
Speaker 1: Like what's crazy is this happening in Canada? But these

774
00:43:08,920 --> 00:43:12,160
Speaker 1: people are tuning into our crazy ass fucking hate talk

775
00:43:12,360 --> 00:43:14,480
Speaker 1: to get them all pumped up. And again, this is

776
00:43:14,520 --> 00:43:16,880
Speaker 1: an example of ship that you want to hide behind

777
00:43:17,040 --> 00:43:20,480
Speaker 1: the description of it being conservative, but it shouldn't even

778
00:43:20,520 --> 00:43:23,160
Speaker 1: be a discussion of what these people are saying. And

779
00:43:23,200 --> 00:43:25,160
Speaker 1: they can hide behind the ambiguity of their language all

780
00:43:25,200 --> 00:43:27,759
Speaker 1: they want to, but it's very clear what kind of

781
00:43:27,800 --> 00:43:30,920
Speaker 1: agenda they're pushing. And then very easy for them be like, well, look,

782
00:43:30,960 --> 00:43:32,920
Speaker 1: I didn't say that explicitly, and that's not fair to

783
00:43:32,960 --> 00:43:35,000
Speaker 1: paint me with that because that person had just happened

784
00:43:35,000 --> 00:43:37,000
Speaker 1: to like what I was saying. But I mean, at

785
00:43:37,040 --> 00:43:39,520
Speaker 1: some point we have to acknowledge the overlap with these

786
00:43:39,600 --> 00:43:42,760
Speaker 1: kinds of things. Well, I wish we could have that conversation,

787
00:43:42,920 --> 00:43:45,240
Speaker 1: but we can't because of the because of the veil

788
00:43:45,320 --> 00:43:48,399
Speaker 1: of hate speech and calling it conservative. But like when

789
00:43:48,440 --> 00:43:50,840
Speaker 1: people were coming out or they still are, but people

790
00:43:50,840 --> 00:43:53,680
Speaker 1: are coming at Roseanne right and they're like that show

791
00:43:53,719 --> 00:43:57,080
Speaker 1: shouldn't be allowed to be on the air. But it's

792
00:43:57,120 --> 00:43:59,919
Speaker 1: the same thing as like you subscribing to the Bright

793
00:44:00,040 --> 00:44:02,719
Speaker 1: part emails. It's like it's kind of good to get

794
00:44:02,719 --> 00:44:06,279
Speaker 1: that sensibility. And what they're doing is they're having those

795
00:44:06,320 --> 00:44:09,000
Speaker 1: debates that we're having a Thanksgiving, they're having them on TV,

796
00:44:09,320 --> 00:44:12,879
Speaker 1: so like we're all hearing both sides, and like, I

797
00:44:12,920 --> 00:44:16,640
Speaker 1: think whoever Rosanne is right now can be problematic on

798
00:44:16,680 --> 00:44:20,240
Speaker 1: its own, but I do think there's value to getting

799
00:44:20,880 --> 00:44:23,480
Speaker 1: that point of view on TV in a way that's

800
00:44:23,480 --> 00:44:25,600
Speaker 1: like controlled, you know what I mean. Like, at the

801
00:44:25,680 --> 00:44:29,759
Speaker 1: end of the day, you have like liberal ABC essentially

802
00:44:30,440 --> 00:44:32,719
Speaker 1: having a leash on all of it. Well, right, And

803
00:44:32,760 --> 00:44:35,160
Speaker 1: I think it is valid for people to understand if

804
00:44:35,160 --> 00:44:39,000
Speaker 1: you're you have anti immigrant sensibility in terms of your politics,

805
00:44:39,280 --> 00:44:41,040
Speaker 1: if you can describe that in a way that is

806
00:44:41,080 --> 00:44:43,880
Speaker 1: devoid of well, I don't want rapists and murderers to

807
00:44:43,960 --> 00:44:47,360
Speaker 1: come into my neighborhood. That's different than saying I'm worried

808
00:44:47,400 --> 00:44:50,440
Speaker 1: about like, if you have economic reasons, then sure you

809
00:44:50,440 --> 00:44:52,240
Speaker 1: should be able to talk that up. But the fact

810
00:44:52,320 --> 00:44:56,000
Speaker 1: is a lot of that xenophobia can be debunked, like

811
00:44:56,080 --> 00:44:57,880
Speaker 1: especially the arguments that they have by a lot of

812
00:44:57,920 --> 00:45:01,279
Speaker 1: studies and data and things like that. So yes, I

813
00:45:01,320 --> 00:45:04,160
Speaker 1: think it is important because conservatives just used to be like, well,

814
00:45:04,200 --> 00:45:06,280
Speaker 1: I think we're spending too much money on these programs

815
00:45:06,360 --> 00:45:08,839
Speaker 1: or whatever, and now it's turning into look at these

816
00:45:08,920 --> 00:45:11,319
Speaker 1: lazy people on welfare. They should be drug tested right

817
00:45:11,360 --> 00:45:13,239
Speaker 1: before they can get any kind of benefits. They should

818
00:45:13,239 --> 00:45:15,719
Speaker 1: blah blah blah, and like that's where you can tell

819
00:45:15,760 --> 00:45:18,520
Speaker 1: that there is clearly a tinge of some other. It's

820
00:45:18,560 --> 00:45:23,000
Speaker 1: not about exactly just saving money. It's about disenfranchising people

821
00:45:23,000 --> 00:45:25,279
Speaker 1: and pulling out safety nets for certain people because they

822
00:45:25,280 --> 00:45:27,759
Speaker 1: don't look like and there's always been a tinge like

823
00:45:27,840 --> 00:45:32,560
Speaker 1: Reagan was continged to death, but yeah, I mean that

824
00:45:32,600 --> 00:45:36,080
Speaker 1: should have become way more mainstream. And yeah, I think

825
00:45:36,120 --> 00:45:39,239
Speaker 1: that's a good point. We'll stop treating conservative speech like

826
00:45:39,320 --> 00:45:43,279
Speaker 1: hates between you take the hatred out of the conservative platform. Well,

827
00:45:43,280 --> 00:45:45,879
Speaker 1: I feel like as a Latina where I'm like well

828
00:45:45,920 --> 00:45:48,680
Speaker 1: aware of the fact that I'm part of what's about

829
00:45:48,719 --> 00:45:52,040
Speaker 1: to become like the biggest voting group, and I think,

830
00:45:52,200 --> 00:45:56,080
Speaker 1: like conservatives and everyone, honestly it's like terrified of that,

831
00:45:56,360 --> 00:46:00,719
Speaker 1: terrified of full on losing the majority already. And so

832
00:46:01,000 --> 00:46:03,399
Speaker 1: you know, if we make you scared to even show

833
00:46:03,480 --> 00:46:06,799
Speaker 1: up at the voting booth, right, then you won't, right.

834
00:46:06,920 --> 00:46:10,120
Speaker 1: And that's why they've done so much to redistrict and

835
00:46:10,200 --> 00:46:14,399
Speaker 1: gerrymander and suppress votes, because that's the only way they

836
00:46:14,400 --> 00:46:18,680
Speaker 1: can fight off something that is a mathematical advantage. Uh yeah,

837
00:46:18,719 --> 00:46:20,520
Speaker 1: And so yeah, you might as well just double down

838
00:46:20,520 --> 00:46:22,200
Speaker 1: on being like, well, then maybe we can just get

839
00:46:22,200 --> 00:46:25,560
Speaker 1: white people to be more aggressively about their own identities

840
00:46:25,719 --> 00:46:27,319
Speaker 1: to get them to vote for us at the poll.

841
00:46:27,400 --> 00:46:28,879
Speaker 1: I mean, when they're not going to win any people

842
00:46:28,880 --> 00:46:31,239
Speaker 1: of color, when they sat back and looked at the demographics.

843
00:46:31,239 --> 00:46:34,200
Speaker 1: They were like, Okay, we need to change our platform

844
00:46:34,360 --> 00:46:37,800
Speaker 1: and just make our focus outreach to the Latin American

845
00:46:37,840 --> 00:46:41,879
Speaker 1: community and you know, immigrant community. How do you think

846
00:46:41,920 --> 00:46:44,080
Speaker 1: that worked in two thousands sixteen? Do you feel like

847
00:46:44,640 --> 00:46:47,480
Speaker 1: they did a good job? And think about Latinos can

848
00:46:47,520 --> 00:46:51,719
Speaker 1: be very we are white. Latinos can be very very like,

849
00:46:52,200 --> 00:46:54,279
Speaker 1: you know what, we just came here for the opportunities.

850
00:46:54,320 --> 00:46:56,600
Speaker 1: We don't want any trouble. Like, if you want us

851
00:46:56,640 --> 00:47:00,200
Speaker 1: to be white, that's fine. Um, we would per for

852
00:47:00,400 --> 00:47:03,680
Speaker 1: it in many scenarios. But I think a lot of

853
00:47:03,760 --> 00:47:09,360
Speaker 1: Latinos actually put ownership on being anti immigrant and being

854
00:47:09,520 --> 00:47:12,440
Speaker 1: like they vote against their own interests. Yeah, I think

855
00:47:12,440 --> 00:47:16,200
Speaker 1: that's human nature. I think especially for to is to assimilate,

856
00:47:16,239 --> 00:47:18,719
Speaker 1: and if part of assimilating is like taking on sort

857
00:47:18,760 --> 00:47:22,000
Speaker 1: of like political position, then so be it. YEA. Yeah. Well,

858
00:47:22,000 --> 00:47:24,200
Speaker 1: when I went to a Trump rally to hang out

859
00:47:24,239 --> 00:47:27,719
Speaker 1: with my friends in May of that was a joke.

860
00:47:28,880 --> 00:47:30,239
Speaker 1: I was doing a piece where I was trying to

861
00:47:30,320 --> 00:47:34,160
Speaker 1: understand Trump voters. I saw many Mexican American people that

862
00:47:34,200 --> 00:47:36,359
Speaker 1: were from Orange County that were there, and they had

863
00:47:36,360 --> 00:47:38,040
Speaker 1: the same thing. They were like well, you know what,

864
00:47:38,160 --> 00:47:40,960
Speaker 1: my family came here legally, and I don't think it's

865
00:47:41,000 --> 00:47:42,799
Speaker 1: fair that blah blah blah. And that's like I heard

866
00:47:42,800 --> 00:47:46,480
Speaker 1: that a lot more than anything. And even many immigrants,

867
00:47:46,560 --> 00:47:48,960
Speaker 1: not just people from Mexico or Guatemala and anything. There

868
00:47:48,960 --> 00:47:50,680
Speaker 1: were Asian people that were doing it. There was a

869
00:47:50,680 --> 00:47:53,160
Speaker 1: group of Chinese people that were there saying, you know, man,

870
00:47:53,200 --> 00:47:55,880
Speaker 1: that internalized racism. Man, I think it's a fear. I

871
00:47:55,880 --> 00:47:59,319
Speaker 1: think it's fear of like I'm so lucky that this

872
00:47:59,400 --> 00:48:03,040
Speaker 1: country made room for me, but clearly there isn't enough

873
00:48:03,160 --> 00:48:05,840
Speaker 1: room for all of us. So you guys were just late,

874
00:48:06,160 --> 00:48:09,400
Speaker 1: like I can't. Yeah, my grandparents voted for Trump, and

875
00:48:09,440 --> 00:48:12,360
Speaker 1: it's like I tried to understand that there's literally a

876
00:48:12,440 --> 00:48:15,919
Speaker 1: language barrier, like they like don't speak English. And it's

877
00:48:15,960 --> 00:48:19,600
Speaker 1: like even more that, wait, what where are they from

878
00:48:19,719 --> 00:48:23,680
Speaker 1: Puerto Rico? Wow? How do they feel even with all

879
00:48:23,680 --> 00:48:25,319
Speaker 1: the ship that went down on the hurricane, do they

880
00:48:25,440 --> 00:48:28,120
Speaker 1: feel are they angered by that? In their response, I

881
00:48:28,120 --> 00:48:31,960
Speaker 1: think my grandma's very like like I'm not there anymore, yeah,

882
00:48:33,440 --> 00:48:35,400
Speaker 1: out of mind, kind of like you know, there's a

883
00:48:35,440 --> 00:48:39,160
Speaker 1: reason I left, and there's a lot of that there's

884
00:48:39,160 --> 00:48:41,680
Speaker 1: a lot of that with Latinos. There's a lot of infighting,

885
00:48:41,719 --> 00:48:44,000
Speaker 1: there's a lot of self loathing, but it all comes

886
00:48:44,000 --> 00:48:45,920
Speaker 1: out like this, like I'm just going to vote for

887
00:48:45,920 --> 00:48:48,279
Speaker 1: Trump so nobody else can come and do what I did,

888
00:48:48,440 --> 00:48:52,080
Speaker 1: and and it gets weird or yeah, if you live

889
00:48:52,080 --> 00:48:55,640
Speaker 1: in fear of conservative white people, you'll adopt their mannerisms.

890
00:48:55,640 --> 00:48:57,279
Speaker 1: It should be like, no, I'm one of the good ones,

891
00:48:58,360 --> 00:49:01,320
Speaker 1: so please don't harm me because is I'm actually falling

892
00:49:01,360 --> 00:49:03,839
Speaker 1: in line with what you believe. And then like you'd

893
00:49:03,840 --> 00:49:05,920
Speaker 1: be like Diamond and Silk, where Ted Cruiz will be like,

894
00:49:06,080 --> 00:49:08,680
Speaker 1: now look at these the women of color that you

895
00:49:08,719 --> 00:49:10,919
Speaker 1: are blah blah blah. It's like, shut the funk up, brother,

896
00:49:10,960 --> 00:49:13,560
Speaker 1: this is not real. Hey, thank you, my man. I'm

897
00:49:13,560 --> 00:49:17,880
Speaker 1: working on. I'm working on us even speak Spanish because

898
00:49:18,040 --> 00:49:20,560
Speaker 1: our parents were so scared that we would like have

899
00:49:20,640 --> 00:49:25,080
Speaker 1: accents and couldn't pull off being like I look white

900
00:49:25,640 --> 00:49:29,000
Speaker 1: and that was cool for them. They were like, no,

901
00:49:29,600 --> 00:49:31,840
Speaker 1: like gret she won't have to deal with any real weird,

902
00:49:31,920 --> 00:49:34,759
Speaker 1: real weird racist ship because you could pass for white, right.

903
00:49:35,680 --> 00:49:39,200
Speaker 1: I have given two full barbaros to this conversation. Yeah,

904
00:49:39,440 --> 00:49:42,560
Speaker 1: you could pass. Oh my god, you have barbaros jokes too.

905
00:49:43,200 --> 00:49:46,239
Speaker 1: Oh my god, Oh my god. Me and my brother

906
00:49:46,360 --> 00:49:51,880
Speaker 1: will not stop with Michael. It's Michael Miles, It's Michael.

907
00:49:53,080 --> 00:49:55,799
Speaker 1: It always sounds like it's about to week and by

908
00:49:55,880 --> 00:50:01,080
Speaker 1: pass for white, you mean, all right, we're gonna take

909
00:50:01,120 --> 00:50:12,280
Speaker 1: a quick break. We'll be right back. And we're back,

910
00:50:13,040 --> 00:50:17,280
Speaker 1: and we wanted to talk about a couple of women

911
00:50:17,600 --> 00:50:23,239
Speaker 1: icons of Cardi B. Out has apparently become a pro

912
00:50:23,360 --> 00:50:28,640
Speaker 1: life Yes, Cardi b is a pro life icon right now,

913
00:50:29,320 --> 00:50:32,200
Speaker 1: She's never said anything even remotely close about being anti

914
00:50:32,239 --> 00:50:36,640
Speaker 1: abortion anyway. However, this is the great part that basically,

915
00:50:37,360 --> 00:50:40,600
Speaker 1: I think Ben Shapiro again he comes up again. He

916
00:50:40,719 --> 00:50:43,439
Speaker 1: found a clip of Cardi B on the Breakfast Club

917
00:50:43,440 --> 00:50:46,560
Speaker 1: talking to Charlemagne about why she's like wanted to have

918
00:50:46,680 --> 00:50:50,040
Speaker 1: her kid. Uh and because she basically said, she's like,

919
00:50:50,080 --> 00:50:52,759
Speaker 1: I'm twenty five years old, I'm a ch millionaire. Yes

920
00:50:52,800 --> 00:50:54,640
Speaker 1: that's a quote. Uh, you know what I'm saying, I'm

921
00:50:54,680 --> 00:50:56,640
Speaker 1: prepared for this. In other words, you know, she was like,

922
00:50:56,920 --> 00:50:59,160
Speaker 1: I'm looking at my life situation. I can handle a child.

923
00:50:59,200 --> 00:51:02,120
Speaker 1: I'm choosing to have my child. Uh. You know. Then

924
00:51:02,120 --> 00:51:03,480
Speaker 1: she went on to talk about. She's like, you know,

925
00:51:03,520 --> 00:51:05,120
Speaker 1: a lot of women were coming up to me saying, Oh,

926
00:51:05,160 --> 00:51:08,200
Speaker 1: I feel sorry for you. Your career is over, And

927
00:51:08,239 --> 00:51:10,279
Speaker 1: Cardi B says, just like, why can't I have both?

928
00:51:10,280 --> 00:51:12,200
Speaker 1: Why do I have to choose a career or a baby?

929
00:51:12,520 --> 00:51:14,360
Speaker 1: And she said, I want my kid now. So a

930
00:51:14,360 --> 00:51:16,560
Speaker 1: lot of people have been like gathering these quotes to

931
00:51:16,560 --> 00:51:19,680
Speaker 1: be like, listen to her go up against the feminist idea.

932
00:51:19,760 --> 00:51:22,480
Speaker 1: This is what faith Wire said in an argument about this.

933
00:51:22,520 --> 00:51:24,960
Speaker 1: They said, does it Cardi B. Quote doesn't believe in

934
00:51:25,000 --> 00:51:27,400
Speaker 1: the feminist idea of not being able to be both

935
00:51:27,520 --> 00:51:32,080
Speaker 1: pregnant and successful. Yes, right, that's that's what feminism is.

936
00:51:32,600 --> 00:51:36,280
Speaker 1: She couldn't be more pro choice in this scenario. She's

937
00:51:36,360 --> 00:51:41,640
Speaker 1: spelling out that she thought about it and chose to

938
00:51:41,680 --> 00:51:46,440
Speaker 1: have a child, have the child knowing there was another option. Yes, exactly,

939
00:51:46,520 --> 00:51:50,239
Speaker 1: she had a choice. It sounds like wait a second, now,

940
00:51:50,280 --> 00:51:52,279
Speaker 1: I don't know, I don't know. I might be high,

941
00:51:52,280 --> 00:51:53,839
Speaker 1: we might just be high. I don't know if maybe

942
00:51:53,880 --> 00:51:56,279
Speaker 1: there was a choice, I don't know. But yeah, it's

943
00:51:56,280 --> 00:52:00,320
Speaker 1: just funny again how there's such a lack of couple

944
00:52:00,320 --> 00:52:02,359
Speaker 1: of people on that side that they were like, oh, well,

945
00:52:02,360 --> 00:52:07,520
Speaker 1: Cardi B had a child, so she's a pro life icon. Like, yeah,

946
00:52:07,680 --> 00:52:11,319
Speaker 1: it's any woman who doesn't abort the baby is pro life.

947
00:52:11,360 --> 00:52:14,879
Speaker 1: Did you know that I did? Every mother, every mother

948
00:52:14,920 --> 00:52:17,560
Speaker 1: in the world, every mother is pro life coming at you.

949
00:52:17,760 --> 00:52:19,879
Speaker 1: So okay, well, you know Cardi is having a big

950
00:52:19,880 --> 00:52:22,120
Speaker 1: week so she can throw a pro life icon on

951
00:52:22,160 --> 00:52:25,120
Speaker 1: her list of achievements. It is kind of sad, like

952
00:52:25,239 --> 00:52:28,720
Speaker 1: for the bench Shapiroes of the world, who's a small, tiny,

953
00:52:28,719 --> 00:52:31,840
Speaker 1: tiny man both in stature and just as a person.

954
00:52:32,520 --> 00:52:36,680
Speaker 1: Uh but yeah, that that they are struggling that much

955
00:52:36,760 --> 00:52:43,239
Speaker 1: to have people actually making their viewpoints relevant, right, they

956
00:52:43,320 --> 00:52:47,600
Speaker 1: are on board with a dying point of view. It's

957
00:52:47,640 --> 00:52:51,360
Speaker 1: just funny because they just basically, hey, fellow kids, the

958
00:52:51,440 --> 00:52:54,319
Speaker 1: whole pro life things, like, hey, fellow kids, you know

959
00:52:54,360 --> 00:52:57,840
Speaker 1: that card I B that you like, Right, she's a

960
00:52:57,920 --> 00:53:07,040
Speaker 1: Bodak bother. I don't know, she's Bantai abortion. It's like,

961
00:53:07,080 --> 00:53:11,200
Speaker 1: so fucking wag them up, man, get the funk out

962
00:53:11,200 --> 00:53:14,520
Speaker 1: of her fucking lane. Obviously, Rihanna is pro choice because

963
00:53:14,560 --> 00:53:19,400
Speaker 1: she named her album anti, So thank you so much. There. Um.

964
00:53:19,719 --> 00:53:22,040
Speaker 1: We also just wanted to talk about Barbara Bush, who

965
00:53:22,040 --> 00:53:27,080
Speaker 1: passed yesterday. Who you know, I guess just based on

966
00:53:27,520 --> 00:53:31,000
Speaker 1: her appearance, I had always sort of associated her with

967
00:53:31,160 --> 00:53:36,560
Speaker 1: a kind lady um. And I do remember in two

968
00:53:36,560 --> 00:53:40,520
Speaker 1: thousand five, while visiting victims of Hurricane Katrina at the

969
00:53:40,560 --> 00:53:45,399
Speaker 1: Astro Dome, her saying some wildly problematic shit about how

970
00:53:45,480 --> 00:53:50,600
Speaker 1: like because they're underprivileged anyway, this is working quote very

971
00:53:50,680 --> 00:53:53,600
Speaker 1: well for them, um, which The New York Times, by

972
00:53:53,640 --> 00:53:57,720
Speaker 1: the way, described as her candor sometimes got her in trouble.

973
00:53:57,960 --> 00:54:01,239
Speaker 1: That's not candor, that is just being a fucking classist,

974
00:54:01,760 --> 00:54:06,600
Speaker 1: racist loon. Um. But that's not the point, right. I

975
00:54:06,640 --> 00:54:08,799
Speaker 1: do want to also focus on the fact that, yeah,

976
00:54:09,239 --> 00:54:13,879
Speaker 1: you know, she was also just kind of a hard

977
00:54:13,920 --> 00:54:18,400
Speaker 1: ass badass. Like I assumed that her obituaries would not

978
00:54:18,560 --> 00:54:21,080
Speaker 1: be the most interesting obituaries to read, and like she

979
00:54:21,239 --> 00:54:25,760
Speaker 1: was actually crazy interesting. And like there are these quotes

980
00:54:25,760 --> 00:54:28,319
Speaker 1: from her childhood friends who would say that they would

981
00:54:28,360 --> 00:54:31,080
Speaker 1: come on the school bus in the morning and they say, quote,

982
00:54:31,160 --> 00:54:33,680
Speaker 1: it would be all planned, nobody's going to talk to

983
00:54:33,800 --> 00:54:36,160
Speaker 1: June this morning. You'd sit there on the bus with

984
00:54:36,200 --> 00:54:38,360
Speaker 1: your friends and no one spoke to you. It was

985
00:54:38,400 --> 00:54:40,759
Speaker 1: a dreadful feeling. So Barbara was coming on the bus

986
00:54:40,760 --> 00:54:42,360
Speaker 1: and being like, you're not talking to her. You're not

987
00:54:42,400 --> 00:54:45,560
Speaker 1: talking to her, you're talking to me. This excommunicating out here.

988
00:54:45,680 --> 00:54:48,359
Speaker 1: So that's one one of her friends, just like real

989
00:54:48,480 --> 00:54:56,160
Speaker 1: housewiving right in the just like world class like legendary

990
00:54:56,239 --> 00:54:59,640
Speaker 1: mean girl. Uh. And then another childhood friend is giving

991
00:54:59,680 --> 00:55:02,440
Speaker 1: a high pathetical scenario and she said she'd call ahead

992
00:55:02,480 --> 00:55:05,560
Speaker 1: and say, we're not going to speak to June this morning,

993
00:55:05,840 --> 00:55:10,879
Speaker 1: so again they can June. Man, two different people, two

994
00:55:10,880 --> 00:55:13,600
Speaker 1: different people are talking about how she froze this girl

995
00:55:13,719 --> 00:55:16,359
Speaker 1: June out when she was like a child. What did

996
00:55:16,440 --> 00:55:19,120
Speaker 1: June do? Yeah, And she would also, like me, probably

997
00:55:19,120 --> 00:55:23,000
Speaker 1: wore pink on a Wednesday, right, she wore white after

998
00:55:23,120 --> 00:55:25,640
Speaker 1: Labor Day, so she can get the funk. She would

999
00:55:25,680 --> 00:55:29,160
Speaker 1: make fun of her friends for like stammering or you know,

1000
00:55:29,719 --> 00:55:36,160
Speaker 1: oh no she was today today. Yeah, um damn. She's

1001
00:55:36,200 --> 00:55:40,279
Speaker 1: like the originator of all this cool original Billy Madison. Right.

1002
00:55:40,560 --> 00:55:43,399
Speaker 1: In reading her obituary, you really get the sense that

1003
00:55:43,440 --> 00:55:46,920
Speaker 1: she was sort of the brains and the balls behind

1004
00:55:47,040 --> 00:55:50,440
Speaker 1: the operation, like behind their couple like that. It's just

1005
00:55:50,520 --> 00:55:53,960
Speaker 1: interesting that, uh, you know. There's also a quote in

1006
00:55:54,000 --> 00:55:56,759
Speaker 1: one of the obituaries where someone says, people always said

1007
00:55:56,840 --> 00:55:59,680
Speaker 1: Nancy Reagan would kill you if you said bad stuff

1008
00:55:59,680 --> 00:56:03,239
Speaker 1: about her, says one staff aide who worked closely with

1009
00:56:03,280 --> 00:56:05,480
Speaker 1: the Bushes. But I always thought Mrs Bush was the

1010
00:56:05,480 --> 00:56:10,560
Speaker 1: one who would kill you, um, which I don't know.

1011
00:56:08,400 --> 00:56:13,640
Speaker 1: I well, I didn't know that about Nancy Reagan either.

1012
00:56:13,800 --> 00:56:16,640
Speaker 1: I just think it's interesting to like we should take

1013
00:56:16,640 --> 00:56:19,080
Speaker 1: a look back at first ladies who were you know,

1014
00:56:20,040 --> 00:56:22,279
Speaker 1: like this, who were just you know, it was at

1015
00:56:22,280 --> 00:56:26,440
Speaker 1: a time when a lot of like brilliant and really

1016
00:56:26,560 --> 00:56:29,799
Speaker 1: tough women had to sort of sublimate themselves to their

1017
00:56:29,880 --> 00:56:32,560
Speaker 1: husband's careers. And like, I really feel like in a

1018
00:56:32,600 --> 00:56:35,480
Speaker 1: lot of cases you'll find that it was basically the

1019
00:56:35,520 --> 00:56:38,960
Speaker 1: women like who are calling the shots, like because Reagan

1020
00:56:39,200 --> 00:56:41,840
Speaker 1: did not seem like a very tough person, but apparently

1021
00:56:41,920 --> 00:56:44,840
Speaker 1: Nancy was just like not fucking around. But it's also

1022
00:56:44,920 --> 00:56:47,520
Speaker 1: that thing of like the husband and the wife could

1023
00:56:47,520 --> 00:56:51,640
Speaker 1: have the same exact behavior, and the woman's would be

1024
00:56:51,760 --> 00:56:55,680
Speaker 1: much more received as hostile, where the man's would be

1025
00:56:55,760 --> 00:57:00,120
Speaker 1: received as like tough boy, does he get it right? Right? Know?

1026
00:57:00,360 --> 00:57:03,759
Speaker 1: And so like I always wonder in scenarios where we

1027
00:57:03,800 --> 00:57:06,000
Speaker 1: are talking about it like that how much of it

1028
00:57:06,120 --> 00:57:08,560
Speaker 1: was was that how much of it was just a

1029
00:57:08,680 --> 00:57:12,359
Speaker 1: woman saying things right? I mean she had full right

1030
00:57:12,400 --> 00:57:15,359
Speaker 1: to to maybe say yeah, no, I totally like I'm

1031
00:57:15,440 --> 00:57:18,400
Speaker 1: saying that, I fucking respect this, like I I think

1032
00:57:18,400 --> 00:57:21,040
Speaker 1: it's awesome because people have like genuine affection for her,

1033
00:57:21,320 --> 00:57:25,000
Speaker 1: but also seemed to be terrified of her, like yeah,

1034
00:57:25,040 --> 00:57:26,640
Speaker 1: and like when then when you look at like what

1035
00:57:26,680 --> 00:57:30,120
Speaker 1: their depictions are descriptions of her childhood time too was

1036
00:57:30,160 --> 00:57:33,439
Speaker 1: even like you know, she basically told everybody she ran

1037
00:57:33,520 --> 00:57:36,640
Speaker 1: ship from Jump Street if it was the school bus,

1038
00:57:36,680 --> 00:57:39,840
Speaker 1: she fucking ran who even spoke to whom you know

1039
00:57:39,840 --> 00:57:43,080
Speaker 1: what I mean? And then taking shots at uh, who's

1040
00:57:43,120 --> 00:57:46,080
Speaker 1: at Geraldine Ferraro she referred to as quote that four

1041
00:57:46,120 --> 00:57:49,480
Speaker 1: million dollar I can't say it, but it rhymes with rich.

1042
00:57:50,160 --> 00:57:52,720
Speaker 1: And then everyone's like, so she referred to this person

1043
00:57:52,720 --> 00:57:54,960
Speaker 1: as a four million dollar bitch, just like that was

1044
00:57:55,000 --> 00:57:57,840
Speaker 1: her nickname. But then she knew the optics that she

1045
00:57:58,000 --> 00:57:59,840
Speaker 1: was like the description of this right of her, like

1046
00:57:59,840 --> 00:58:01,880
Speaker 1: she was mortified that she had, let's slip the mask

1047
00:58:02,240 --> 00:58:04,840
Speaker 1: that had concealed the mean streak that had first emerged

1048
00:58:04,880 --> 00:58:08,200
Speaker 1: in her childhood. She immediately apologized to Ferraro and kept

1049
00:58:08,200 --> 00:58:11,680
Speaker 1: her salty tongue in place for years afterward. So I

1050
00:58:11,720 --> 00:58:13,800
Speaker 1: don't know if the salty tongue thing is after Do

1051
00:58:13,800 --> 00:58:16,720
Speaker 1: you remember when Jeb was about to run and or

1052
00:58:16,800 --> 00:58:19,600
Speaker 1: like was running and um, there was a sound bite

1053
00:58:19,600 --> 00:58:21,600
Speaker 1: of her going like, I don't know, there's got to

1054
00:58:21,640 --> 00:58:24,680
Speaker 1: be another family that should be doing this right Like

1055
00:58:25,320 --> 00:58:28,000
Speaker 1: she was essentially like I don't it can't just be

1056
00:58:28,240 --> 00:58:30,840
Speaker 1: two families that we're just going to keep going back

1057
00:58:30,880 --> 00:58:37,120
Speaker 1: and forth. And then she got in trouble. They were like, yeah, yeah,

1058
00:58:37,120 --> 00:58:39,800
Speaker 1: that's why I feel like I bet yo. Those Bush children,

1059
00:58:39,840 --> 00:58:43,160
Speaker 1: the sons of George H. W. Bush, we're probably so

1060
00:58:43,280 --> 00:58:46,080
Speaker 1: shook of their mother, like if that's her description, because

1061
00:58:46,120 --> 00:58:49,040
Speaker 1: if you look at Jeb and g W, they're like, well,

1062
00:58:50,240 --> 00:58:52,080
Speaker 1: like as if their mom would be like, is your

1063
00:58:52,120 --> 00:58:57,280
Speaker 1: finger painting? Are you a fucking dumb fuck? That's weird?

1064
00:58:57,400 --> 00:59:01,400
Speaker 1: It looks like a fucking toe painting on the track. Jeb,

1065
00:59:02,320 --> 00:59:05,160
Speaker 1: what a fucking name? Huh? I'm sorry, ladies, he's an

1066
00:59:05,160 --> 00:59:08,280
Speaker 1: idiot and it was Jeff. But I want you to

1067
00:59:08,320 --> 00:59:10,880
Speaker 1: be embarrassed the rest of your life, you, Jeb? But

1068
00:59:14,600 --> 00:59:19,280
Speaker 1: uh is that sure for Jebediah Oh. Apparently, according to

1069
00:59:19,280 --> 00:59:22,600
Speaker 1: the super producer on a Hosnier, Jeb is not sure

1070
00:59:22,680 --> 00:59:25,480
Speaker 1: for Jebediah it is an acronym for his full name,

1071
00:59:25,520 --> 00:59:28,880
Speaker 1: which is John Ellis Bush Sr. Or because you know why,

1072
00:59:28,880 --> 00:59:31,560
Speaker 1: because John was probably like Barbara's father, and she's like,

1073
00:59:31,640 --> 00:59:36,440
Speaker 1: he would be disappointed in your Jeb funk out of here, John,

1074
00:59:37,080 --> 00:59:40,280
Speaker 1: I can't even I can hear my father's earned rattling.

1075
00:59:41,400 --> 00:59:45,080
Speaker 1: So uh yeah, I mean, look, you know you were

1076
00:59:45,200 --> 00:59:49,720
Speaker 1: clearly the matriarch of a dynastic political family. Uh so,

1077
00:59:50,000 --> 00:59:52,480
Speaker 1: you know, shots to you. You know, it's never it's

1078
00:59:52,520 --> 00:59:54,720
Speaker 1: never nice. You never want to hear about anyone passing away.

1079
00:59:54,880 --> 00:59:56,680
Speaker 1: But it seemed like she did it on her terms too,

1080
00:59:56,720 --> 00:59:59,720
Speaker 1: because she, I think, refused to have any more life

1081
01:00:00,240 --> 01:00:03,480
Speaker 1: saving procedures over the weekend. They reported, so and just

1082
01:00:03,760 --> 01:00:07,720
Speaker 1: real quick, right before I die, nobody talked to June. Yeah, right,

1083
01:00:08,480 --> 01:00:11,120
Speaker 1: and talk to June. June. I know you showed up.

1084
01:00:12,320 --> 01:00:15,960
Speaker 1: We are not talked like she's like wiping her head

1085
01:00:16,000 --> 01:00:18,479
Speaker 1: with a wash cloth and she's like, who let this

1086
01:00:18,880 --> 01:00:27,120
Speaker 1: bitch in here? June? The police to dollar bitch, Marlene,

1087
01:00:27,200 --> 01:00:29,640
Speaker 1: has been a pleasure having you for having me, guys,

1088
01:00:29,680 --> 01:00:32,000
Speaker 1: so super fun. Where can people find you? Um, I'm

1089
01:00:32,040 --> 01:00:36,920
Speaker 1: on Twitter at Marlena Rodrigues. I'm on Instagram at Marlena

1090
01:00:37,000 --> 01:00:40,560
Speaker 1: Got a Life and just google me. Just get in there. Um.

1091
01:00:40,680 --> 01:00:44,560
Speaker 1: But I run a stand up show in complete darkness

1092
01:00:44,640 --> 01:00:47,200
Speaker 1: called Dark and that'll be on me fourth at the

1093
01:00:47,240 --> 01:00:49,480
Speaker 1: later Ciperion, So get in there. So the theater is

1094
01:00:49,520 --> 01:00:53,760
Speaker 1: completely dark, yeah, and we blindfold the audience and the comics. Damn.

1095
01:00:53,760 --> 01:00:57,880
Speaker 1: And then you pickpocket though I wish when's your show?

1096
01:00:57,960 --> 01:01:01,400
Speaker 1: But trying to do the stereotypis on. Well, I'll be

1097
01:01:01,440 --> 01:01:04,800
Speaker 1: there when is it. Hey, if you're wealthy in the

1098
01:01:04,800 --> 01:01:06,760
Speaker 1: Los Angeles area, please bring cash to the shows the

1099
01:01:06,760 --> 01:01:08,840
Speaker 1: castole the show there will be March for Zel after

1100
01:01:09,960 --> 01:01:12,240
Speaker 1: keep all of your money loosely in your front pocket

1101
01:01:13,200 --> 01:01:15,280
Speaker 1: front pocket. Yeah, because it's just peeking out. And I

1102
01:01:15,320 --> 01:01:18,400
Speaker 1: can just say because if someone's sitting you know, somebody

1103
01:01:18,440 --> 01:01:23,400
Speaker 1: sitting down, check that doesn't feel you. That's your privilege. Miles,

1104
01:01:23,400 --> 01:01:25,320
Speaker 1: where can people find you? Can find me on Twitter

1105
01:01:25,360 --> 01:01:29,520
Speaker 1: and Instagram at Miles of Gray. And also, yes, I

1106
01:01:29,560 --> 01:01:32,360
Speaker 1: was a very special guest on the newest episode of

1107
01:01:32,360 --> 01:01:35,320
Speaker 1: Culture Kings that came out today. So I joined Jakis

1108
01:01:35,800 --> 01:01:38,760
Speaker 1: and Edgar, a very very very levable guests from The

1109
01:01:38,800 --> 01:01:41,680
Speaker 1: Daily Zeitgeist on their show and I entered the Kingdom

1110
01:01:41,920 --> 01:01:45,200
Speaker 1: of Culture and we talked about whether or not any

1111
01:01:45,240 --> 01:01:47,920
Speaker 1: of us have paid ourselves at concerts. The answer to

1112
01:01:48,040 --> 01:01:50,600
Speaker 1: that is yes, I have, So check that out. You

1113
01:01:50,640 --> 01:01:53,120
Speaker 1: can find me at Jack Underscore O'Brien on Twitter. We

1114
01:01:53,200 --> 01:01:55,840
Speaker 1: are at Daily Zeitgeist on Twitter. We're at the Daily

1115
01:01:55,920 --> 01:01:58,919
Speaker 1: Zeitgeist on Instagram. We have a Facebook fan page and

1116
01:01:59,200 --> 01:02:01,800
Speaker 1: a website Daily's like guys dot com where we post

1117
01:02:01,840 --> 01:02:05,320
Speaker 1: our episodes and our foot where we link off to

1118
01:02:05,560 --> 01:02:08,960
Speaker 1: the information that we talked about in two days episode.

1119
01:02:09,720 --> 01:02:11,800
Speaker 1: That's gonna do it for today, Miles, what are we

1120
01:02:11,840 --> 01:02:13,840
Speaker 1: gonna write out? Okay? So where you know, it's it's

1121
01:02:13,840 --> 01:02:15,520
Speaker 1: Weed week and I'm just doing like a lot of

1122
01:02:15,560 --> 01:02:18,480
Speaker 1: weed themed outro songs. Uh. This one is by the Internet.

1123
01:02:18,600 --> 01:02:21,000
Speaker 1: We played a track by the Internet before shout out

1124
01:02:21,000 --> 01:02:24,439
Speaker 1: to Ellie's very on the Internet. This song is called Getaway, Uh.

1125
01:02:24,440 --> 01:02:27,480
Speaker 1: And you know it's just about just taking off the space,

1126
01:02:27,600 --> 01:02:29,840
Speaker 1: you know, with the magical plants. Uh. And it's just

1127
01:02:29,880 --> 01:02:33,280
Speaker 1: a great beat. The production is amazing and yeah, take

1128
01:02:33,280 --> 01:02:36,760
Speaker 1: care of yourself, guys, So you use it for an escape,

1129
01:02:36,840 --> 01:02:41,040
Speaker 1: mis I do? I use the premier problems? Yeah? Yeah, typically, Uh,

1130
01:02:41,080 --> 01:02:43,280
Speaker 1: if I see like a family walking down the street,

1131
01:02:43,360 --> 01:02:45,760
Speaker 1: that just affects me very deeply. I think of my

1132
01:02:45,800 --> 01:02:48,640
Speaker 1: own situation as you've heard. I think on the hundredth episode,

1133
01:02:48,680 --> 01:02:50,120
Speaker 1: we went over that. If you want to hear about

1134
01:02:50,160 --> 01:02:53,640
Speaker 1: that trauma, it's right there. All right, Yeah, we just

1135
01:02:53,680 --> 01:02:59,520
Speaker 1: tip though you know it's chill man. All right, that's

1136
01:02:59,520 --> 01:03:01,640
Speaker 1: gonna do it for today. We will be back tomorrow

1137
01:03:01,680 --> 01:03:05,840
Speaker 1: because it is a daily podcast. Let's talk together now,

1138
01:03:05,920 --> 01:03:12,360
Speaker 1: she wanna fuck with me? Me live live dream, all

1139
01:03:12,400 --> 01:03:19,280
Speaker 1: those of my money trees, such beautiful company, fucking on

1140
01:03:19,520 --> 01:03:23,360
Speaker 1: the father. I'm staying down side, but I'm still driving

1141
01:03:23,360 --> 01:03:28,080
Speaker 1: around my own I'm still living out longer issues of

1142
01:03:28,200 --> 01:03:32,439
Speaker 1: my ootion and you're lowing up my phone outsigain by

1143
01:03:32,520 --> 01:03:37,960
Speaker 1: some motion by closes whose that could be worse. So

1144
01:03:38,080 --> 01:03:41,000
Speaker 1: to calm her nerves, I just tell the all that

1145
01:03:41,560 --> 01:03:45,880
Speaker 1: and the light that's so spices me. My CoA be

1146
01:03:46,120 --> 01:03:53,200
Speaker 1: the pilot. Let's get by, Let's get away, Let's get away,

1147
01:03:54,240 --> 01:04:00,400
Speaker 1: let's sit away, baby, Let's get by. Money doesn't my

1148
01:04:00,560 --> 01:04:06,600
Speaker 1: frown das maybe we can make my game to day

1149
01:04:07,720 --> 01:04:13,880
Speaker 1: when the need is computing and ras a shine. I

1150
01:04:14,160 --> 01:04:18,480
Speaker 1: can't be working for you the day, I was saying

1151
01:04:19,840 --> 01:04:22,560
Speaker 1: in it, I kind of ways been. These are in

1152
01:04:22,800 --> 01:04:28,720
Speaker 1: my champagne every day we celebrate the brain fuck your

1153
01:04:28,840 --> 01:04:32,920
Speaker 1: little phons. A million ain't enough, But I'm still driving

1154
01:04:32,920 --> 01:04:36,240
Speaker 1: around of my own way, still living out on that

1155
01:04:36,960 --> 01:04:39,800
Speaker 1: it shows of my new chick and you blowing up

1156
01:04:39,920 --> 01:04:45,480
Speaker 1: my phone out all here's wrong wa wa, but it

1157
01:04:45,640 --> 01:04:50,560
Speaker 1: could be worse. Broke came your life shoot all of

1158
01:04:50,880 --> 01:04:56,320
Speaker 1: and listen, says me, my co I be the Byele,

1159
01:04:57,240 --> 01:05:04,240
Speaker 1: Let's take you away, Let's step Why listen? Why listene?

1160
01:05:04,680 --> 01:05:11,560
Speaker 1: Why baby plastic by? It doesn't fall from trees nor

1161
01:05:12,880 --> 01:05:21,840
Speaker 1: baby we can make by the It's kind of has

1162
01:05:21,920 --> 01:05:26,800
Speaker 1: a shot, I promised me. The Funny Dome