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Speaker 1: Hello the Internet, and welcome to Season one thirty one,

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Speaker 1: episode five of Daily Night Die, a production of My

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Speaker 1: Heart Radio. This is a podcast where we take a

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Speaker 1: deep dive into America's share continents and say, officially, off

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Speaker 1: the top, fuck the Koch Brothers and Fox News. It's Friday,

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Speaker 1: May First. My name is Jack O'Brien a K. Jacko

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Speaker 1: is in quar He's feeling like a loner, but he

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Speaker 1: knows that this might last. Jacko stayed at home. He

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Speaker 1: doesn't want Corona. He thinks Stan Patrick is an ass.

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Speaker 1: Get back, get back, get back inside your goddamn homes.

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Speaker 1: Get back, get back inside is where we all belong.

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Speaker 1: Get back, Jacko. That is courtesy of war Can r

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Speaker 1: R and I'm thrilled to beat point as always buy

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Speaker 1: my co host, Mr Miles Gray. Miles Gray a k A.

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Speaker 1: The inventor of the Gray Old Clinic a k A

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Speaker 1: John's Popkins a k A Weaders Sinai a k A

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Speaker 1: First Press, Hiterian a k A Doobie Houser e d

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Speaker 1: a k A. Gray is anatomy aka No Scrubs aka

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Speaker 1: the Hood Doctor a k A. Hard House a k

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Speaker 1: A General Host, spital ak nurse Jack, Oh, that would

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Speaker 1: be you. But thank you to Walter Chesna Jr. For

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Speaker 1: those strings of medically induced a kas hell yeah, Walter Chestnuts.

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Speaker 1: Then a while. Good to see you again, my friend,

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Speaker 1: and we are thrilled to be joined all the way

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Speaker 1: from the East coast by the hilarious and talented and

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Speaker 1: brilliant Bridget Todd. Hello. Thank you so much for having me. Wow,

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Speaker 1: what an intro. No thanks, It's great to be with

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Speaker 1: you here. I mean to think, just the last time

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Speaker 1: we were to get there, we were Jack and I Anna.

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Speaker 1: We were flying willy nilly around the country while probably

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Speaker 1: COVID nineteen was spreading. But what and now look at

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Speaker 1: us now here we are. I know we did you.

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Speaker 1: I had no idea that would be one of the

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Speaker 1: last times I was doing a podcast thing. I r L.

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Speaker 1: I wasn't remote in my kitchen, you know. Yeah, man,

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Speaker 1: what a time. So Bridget, how's DC? What's the What

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Speaker 1: are the vibrations in the capital. I really wouldn't know,

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Speaker 1: because I haven't left my house in a very long time.

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Speaker 1: I think the vibe here like we're lucky that we

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Speaker 1: have a mayor who seems to be sort of on it,

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Speaker 1: you know, we get very clear information from our mayor

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Speaker 1: every day about the numbers and the cases and all

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Speaker 1: of that. So I'm lucky for that because some people

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Speaker 1: don't have that kind of leadership. Certainly we don't have

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Speaker 1: that kind of leadership federally, so it's nice to have

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Speaker 1: to feel like someone like a grown up is in charge. Yeah, yeah, yeah, word,

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Speaker 1: do you have weird? Do you have weird? Like? Are

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Speaker 1: there we wear products that are having shortages? You know,

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Speaker 1: like l A, you can't get garlic. I don't know really,

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Speaker 1: I don't know who the garlic plug is in Los Angeles,

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Speaker 1: but if you're the garlic Connect, well holler at me

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Speaker 1: because I'm in for at least two pounds literally. Ours

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Speaker 1: is definitely flower, Like everybody has decided how they're getting

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Speaker 1: through the pandemic is baking, and you people can't find flower.

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Speaker 1: And I actually have a friend who is a professional baker,

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Speaker 1: and she's like, yeah, I can't, I can't like make

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Speaker 1: my my goods because everybody has decided, Oh I'm a

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Speaker 1: professional baker, now I need flowers. So definitely flower yeast.

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Speaker 1: Everyone's doing that like sour dough starter, Like it's interesting.

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Speaker 1: We are all coping in these very weird ways, like

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Speaker 1: there's a pandemic, I better get really into gardening. Yeah,

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Speaker 1: I'm not at that level of of pandemic yet where

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Speaker 1: I've gone into the baking phase. I don't know if

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Speaker 1: I will. But it's always interesting to see people. I've

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Speaker 1: been surprised at the kinds of people I've seen suddenly

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Speaker 1: be like, I make my own yeast, and I'm like,

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Speaker 1: you're actually making like Pruno. But I guess that's yeah, yeah,

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Speaker 1: yeah that those people are way more ambitious than I am.

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Speaker 1: I will just say back, is the one new skill

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Speaker 1: you've picked up, like based like teaching preschoolers over zoom

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Speaker 1: or like monitoring like zom educations. Essentially that's your new skill? Yeah,

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Speaker 1: and that very poorly. What has it been like as

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Speaker 1: a parent, Like, what is this time like as someone

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Speaker 1: with I don't have kids? What is it like as

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Speaker 1: someone who has kids? You know, I've got a today.

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Speaker 1: My three year old is a four year old. He's

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Speaker 1: a man now, will be uh he will be going

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Speaker 1: out and getting a job now. Yes, yes, but it's

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Speaker 1: it's all right. It's it's a fun age like uh,

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Speaker 1: four and two, it's an okay age for this because

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Speaker 1: like sometimes they'll ask really sad questions like how come

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Speaker 1: I never get to see my friends? Or why can

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Speaker 1: I see my friends for my birthday? But then they

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Speaker 1: kind of forget about that after a couple of minutes.

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Speaker 1: Uh So, yeah, I mean it's tricky, but it's it's good,

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Speaker 1: it's a lot of it's a lot of fun to

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Speaker 1: spend a lot of time with them right now. Or

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Speaker 1: you hit them with like the overly complex answer, it's like, well,

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Speaker 1: because there's an elected official at the top who refuses

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Speaker 1: to accept you know, I guess they generally accepted reality

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Speaker 1: and science around the topic, therefore completely boxed the situation

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Speaker 1: and has led to, i mean, just really poor outcomes

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Speaker 1: for everyone. So yeah, yeah, that's why. That's they have

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Speaker 1: an endless amount of patients to just keep asking me

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Speaker 1: what things are and why things are the way they are.

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Speaker 1: So don't have you been stumped? What's the latest thing

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Speaker 1: you've been stumped trying to explain to? Yeah, I can't,

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Speaker 1: I can't think of it, but I've definitely been stumped

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Speaker 1: on the regular of how to how to uh convey

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Speaker 1: very complicated uh questions. What one that I got within

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Speaker 1: the past week is why do things die, Um, which

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Speaker 1: is why Yeah, yeah, why do they? Actually I never

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Speaker 1: thought about that. No, I was saying that was a

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Speaker 1: question from you tune. Hey, Jack, can ask you something?

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Speaker 1: Why why do things die? Man? Yeah? Quick? Yeah, all right,

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Speaker 1: Bridget We're gonna get to know you a little bit

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Speaker 1: better in a moment. First, we're gonna tell our listeners

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Speaker 1: a couple of the things we're talking about. We're gonna

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Speaker 1: look at this article from former CEO of Permanente, which

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Speaker 1: is like one of the biggest hospital chains in the country. Uh,

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Speaker 1: he's a doctor, and he just had some good perspective

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Speaker 1: on like sort of where we're at and what it

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Speaker 1: actually means to kind of open open the country back up,

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Speaker 1: like what that decision is actually about. We got yet

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Speaker 1: another just keeping the ball in the air with regards

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Speaker 1: to our interest in Mike Pence's decision not to wear

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Speaker 1: the mask at the Mayo clinic. Uh, so we'll talk

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Speaker 1: about that. That came at the end of last week. Um.

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Speaker 1: Trump is mad. Uh, he's he's furious. He can't believe

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Speaker 1: that there's pulling numbers. I think there was a quote

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Speaker 1: from him that I'm not gonna lose the fucking Joe Biden,

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Speaker 1: like he just he has this entitlement because he's like

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Speaker 1: killing Biden at a fundraising and so he just thinks,

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Speaker 1: you know this, this should be easy. I actually woke

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Speaker 1: up this morning to an email from one Donald J.

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Speaker 1: Trump because I get that bright Bart uh mailing I'm

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Speaker 1: on that bright Bart mailing list to just kind of,

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Speaker 1: you know, to them on that that bright Bart board

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Speaker 1: of trustees you know me. But yeah, it was it

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Speaker 1: was interesting to see the tone he's taken right now. Uh.

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Speaker 1: And then we're going to try and pick a movie

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Speaker 1: uh to rewatch over the weekend for our Monday rewatch.

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Speaker 1: We are going to look at America's horny nous as

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Speaker 1: it relates to the rest of the world. All of that,

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Speaker 1: there's all these uh COVID documentaries that are heading our way,

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Speaker 1: all that plenty more. But first, bridget, we like task

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Speaker 1: our guests, what is something from your search history that

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Speaker 1: is revealing about who you are? What a good question?

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Speaker 1: Something from my search history that is revealing about who

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Speaker 1: I am. The last thing I did a Google deep

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Speaker 1: dive on was Janet Hubert a k A. The original

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Speaker 1: mom on Fresh Prince Fresh Prince of bel Air. I

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Speaker 1: don't know if you saw it. Recently, they had a

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Speaker 1: little neighbor union of the Fresh Prince cast um and

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Speaker 1: my whole thing is, you know, if y'all don't know,

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Speaker 1: Janet Hubert was originally the first and I would say,

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Speaker 1: the best, the most iconic mom on the show. And

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Speaker 1: then she was replaced by another actress and she clearly

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Speaker 1: never got over this. This has been a beef that

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Speaker 1: she has held for thirty years. She has commented on

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Speaker 1: it for thirty years. Anytime, but the Fresh Prince cast

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Speaker 1: has anything. She responds and is still salty till this day.

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Speaker 1: That woman is a pillar of salt, and honestly I

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Speaker 1: respect it. So I saw that the Fresh Prince cast

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Speaker 1: had reunited and I thought, oh, I would have to

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Speaker 1: see if Janet had something to say or had something

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Speaker 1: to say, had some response. Uh yeah, I just really

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Speaker 1: respect a long held beef, like it's been thirty years,

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Speaker 1: still mad. Yeah what happened? Wait, so did she have

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Speaker 1: anything to say or no? She I didn't find that

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Speaker 1: she had anything to say. But the last time the

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Speaker 1: cast reunited, like two years ago, she was like, of

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Speaker 1: course these assholes are reuniting without me, like same old ship,

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Speaker 1: like still angry. So basically her version of events is

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Speaker 1: that honestly like you and me, obviously, yeah, I'm like,

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Speaker 1: because I get it. Aunt Vivu became a few shades

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Speaker 1: lighter when she definitely did w what's her name, Daphne

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Speaker 1: Maxwell read took good memory. I haven't pulled up right

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Speaker 1: now because I want to make sure I have everyone's

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Speaker 1: names right. I just want to say, I know I

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Speaker 1: shouldn't have said that. She she just she deserves to

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Speaker 1: have her full name, all three names, all three names.

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Speaker 1: It sounds like what happened was that when the show

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Speaker 1: initially started, it wasn't supposed to be just about fresh Prince,

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Speaker 1: like just about his character. You know, all the other

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Speaker 1: side characters had plot lines like you saw, like viv

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Speaker 1: was a African American studies professor. She had her own

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Speaker 1: like plot lines like the episode where she wants to

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Speaker 1: be a dancer and the African dance episode right like

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Speaker 1: she had good She had good plot lines. And so

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Speaker 1: it sounds like as the show progressed, audiences just really

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Speaker 1: wanted more Will Smith and she was like, wait, no,

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Speaker 1: I didn't sign on to be on the Will Smith Show.

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Speaker 1: I signed on to be like on a show, and

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Speaker 1: though they wrote her off, you know, more bell air

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Speaker 1: less Fresh Prince is yes, and you know, to this

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Speaker 1: day she is still so salty about it, like it

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Speaker 1: clearly made a huge impression on her. Um, I don't

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Speaker 1: blame her. I just kind of respect that she's been

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Speaker 1: angry for this long. Like if this beef, if this

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Speaker 1: beef was if this people the person it would be

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Speaker 1: in its thirties, it's been she's been nurturing here for

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Speaker 1: so long. Yeah, I mean she was in the original

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Speaker 1: Broadway production of Cats, So you know, I will not

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Speaker 1: I don't. I've never seen this. I don't know how

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Speaker 1: to pronounce the name, but it says Hubert was the

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Speaker 1: original tantomal tantomime in the first Broadway chantomeal of the

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Speaker 1: first Broadway run of Cats, So maybe she had that

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Speaker 1: cat's head on where she was like she was like,

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Speaker 1: um no, I don't know who this young man is

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Speaker 1: who just randomly met Quincy Jones. I will this show

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Speaker 1: will be about me. Well, I respect the beef though.

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Speaker 1: Viv was my age at the start of Fresh Prince,

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Speaker 1: according to Wikipedia, so that makes me feel old as fuck.

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Speaker 1: What do you mean, Like, oh, at the time where

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Speaker 1: she took the role. Yeah, no, I googled Aunt Vivian

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Speaker 1: and you know, they break out the actress Jen Hubert

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Speaker 1: for one through three, Daphne Maxwell read four through six,

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Speaker 1: and then age of the character thirty nine through so

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Speaker 1: that was that was forty this is forty. Yeah, it's funny.

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Speaker 1: They seem so like old on a show. Like when

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Speaker 1: I was watching as a kid, I was like, oh,

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Speaker 1: there's some grown up. Now I'm like, yeah, that's basically

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Speaker 1: my age. And then I fuck you up though, because

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Speaker 1: you get you sort of you live with these perceptions

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Speaker 1: of what an age is and what it looks like

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Speaker 1: and what the behavior is, and then you grow up

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Speaker 1: and then you're like, don't subscribe to those weird beliefs,

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Speaker 1: and you're like, am I in my mid thirties, I

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Speaker 1: feel like I'm fourteen? I think in some parts of

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Speaker 1: my mind it's weird. How Yeah, because in my mind,

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Speaker 1: I'm like, no, man, when you're like when you're like

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Speaker 1: thirty eight, like you look like an old person, because

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Speaker 1: that's what TV looked like. As from my perspective as

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Speaker 1: a child, it's I definitely identify my age more as

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Speaker 1: Hillary's age than Aunt Viv's age first Night, right, like,

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Speaker 1: Hillary seemed very old and mature and cool to me

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Speaker 1: when I was a kid first watching that show at

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Speaker 1: the oldest time Hillary. At this point, I thought, I

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Speaker 1: can't see myself being older than anyone, but I'm probably

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Speaker 1: uncle Phil, my brother used to have such a massive

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Speaker 1: crush on the actress that played Hillary. He would like,

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Speaker 1: he's gonna be so embarrassed. I'm saying, let's hope he

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Speaker 1: never hears it. He would write her letters like he

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Speaker 1: was obsessed with her. Who wasn't Katherine Parsons was? I

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Speaker 1: loved her too when she was in major pain. I

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Speaker 1: was here we go, she's crossing over into the mainstream.

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Speaker 1: Everyone will know the queen. What else was she? And

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Speaker 1: was she in Ladies? Man? She was? She's been in

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Speaker 1: a few things since then. But I don't I don't know.

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Speaker 1: I don't know what what exactly she made of her career,

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Speaker 1: like whether or not she was trying. I don't know

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Speaker 1: what happened Karen Parsons. I said, Catherine Parsons, excuse me, yeah,

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Speaker 1: put some respect on her. Absolutely botch that. I apologize.

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Speaker 1: So now I know he's gonna find you. I know,

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Speaker 1: what is something you think is underrated bridget something I

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Speaker 1: think is underrated. Um, and this is coming from someone

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Speaker 1: who is not a sports person at all. Dennis Rodman

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Speaker 1: in the nineties. You know, people have been talking about

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Speaker 1: Dennis Rodman lately. I unfortunately have nothing to add from

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Speaker 1: a sports perspective, but I watched this clip and it's

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Speaker 1: also related to my overrated thing as well. UM. I

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Speaker 1: watched this clip of Oprah interviewing him and he's talking

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Speaker 1: about his gender and his sexuality. And it's funny because

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Speaker 1: when I was young, I feel like everybody treated him

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Speaker 1: like a joke, like he was something creak, and what

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Speaker 1: he was saying was about gender and about sexuality was

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Speaker 1: actually like very progressive. He was talking about how he

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Speaker 1: thinks in some in some capacities he could be like

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Speaker 1: gay or by mentally, but he grew up around women

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Speaker 1: until he was always sort of discomfortable, like not comfortable

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Speaker 1: around men, you know, really being honest about gender and

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Speaker 1: playing with gender in all these interesting ways. And I

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Speaker 1: feel like, at least in my community back then, he

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Speaker 1: was like like a freak to laugh at when actually

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Speaker 1: he was like really progressive. And if he had said

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Speaker 1: that ship today we would be applauding him. But back

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Speaker 1: then we treated like a big joke. Yeah, no, totally

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Speaker 1: by nineties standards. He was like a you know, something

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Speaker 1: to gok at. But I totally agree he was like

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Speaker 1: he would have been like it really is interesting to

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Speaker 1: think about what his career would be like if he

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Speaker 1: were in league today. Absolutely. Yeah. Also it's interesting how

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Speaker 1: he would also play with that because he would do

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Speaker 1: one thing. It would start off small where people would

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Speaker 1: point something out, and then he would and tag he

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Speaker 1: be like, all right, watch me turn this up even

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Speaker 1: more to the points like watch me wear this wedding dress.

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Speaker 1: And then now you have some time because before you

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Speaker 1: were ncomfortable because I had too many ear rings and

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Speaker 1: my fingernails were painted. Now try this one off. Definitely

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Speaker 1: I loved that, and I think we I feel like

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Speaker 1: he really help did a good job of holding a

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Speaker 1: mirror up to our misconceptions and our anxieties and are

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Speaker 1: discomfort around a lot of things when it comes to

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Speaker 1: gender and sex. And the fact that Michael Jordan's had

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Speaker 1: to go drag him out of bed on the Vegas

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Speaker 1: Strip during the season, like personally with his own Michael

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Speaker 1: Jordan's hands was pretty he's a great detail. What is

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Speaker 1: something you think is overridded? This is a little controversial.

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Speaker 1: It's a fuego take. I'm gonna own it's it's tough

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Speaker 1: for me to say this, but Oprah Winfrey, I have

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Speaker 1: to say. I mean, I've been an O. I haven't

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Speaker 1: been an Oprah stated my whole life. Color Purple is

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Speaker 1: one of my favorite movies. Like her performance in it

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Speaker 1: was life changing for me. But like ay, I watched

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Speaker 1: the interview where Dennis Roman is being interviewed by Oprah,

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Speaker 1: and she can constantly is like, are you gay? Are

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Speaker 1: you gay? Are you buy? Or you buy? And he's

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Speaker 1: like expressing this very progressive, the layered expression of gender

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Speaker 1: and sexuality, and she can only and again it's the nineties,

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Speaker 1: so you know whatever, but she could only understand it

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Speaker 1: through so are you gay or what? Like that's the

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Speaker 1: only way she can understand it. And today, you know,

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Speaker 1: in the time of coronavirus, if we're going to be

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Speaker 1: really real, the reason why we have a lot of

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Speaker 1: these like huckster fake doctors like your doctor oz Is

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Speaker 1: and your doctor Phils is Oprah and so Oprah, I

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Speaker 1: love you, but like, do's something Oprah like it's that cool.

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Speaker 1: Like it's almost like, yeah, you'd like Oprah to do

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Speaker 1: something about it, like or at least on and be

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Speaker 1: like hey, like talk to them, pull them aside, do something.

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Speaker 1: You're like, hey, I gave you this, fucking don't do

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Speaker 1: this with the platform exactly. So I don't want to,

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Speaker 1: you know, blame a woman for the behavior of a man.

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Speaker 1: But she did give these people a platform, and I

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Speaker 1: just part of me is like Oprah Honey like Dr

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Speaker 1: Philis and Walt Ship on TV about coronavirus, Like even

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Speaker 1: doctor is like, yeah, people can die. What's wroble? Uh?

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Speaker 1: When she like when she first gave the world doctors

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Speaker 1: Phil and Oz did, were were they um as bad?

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Speaker 1: Like I feel like they might have taken things up

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Speaker 1: a step or two since then. But I do think

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Speaker 1: the Robinin thing is really interesting to think about because

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Speaker 1: I do feel like she's always been really good at

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Speaker 1: like mining the zeitgeist, like knowing what Like she's she's

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Speaker 1: almost a mirror for like what we are a warts

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Speaker 1: and all. Like she's good at like being in touch

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Speaker 1: with what everybody's you know, general thoughts and ideas and

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Speaker 1: morality is at a given time and you'll you'll see

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Speaker 1: like outdated shit if you look back at you know, what,

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Speaker 1: what she was saying and doing in the eighties and nineties. Yeah,

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Speaker 1: I think that's true. I completely agree that she really

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Speaker 1: has a way of putting her finger on something in

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Speaker 1: the culture and sort of poking at it and perhaps

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Speaker 1: just like revealing dark stuff about all of us that

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Speaker 1: we maybe don't want to put a mirror up to.

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Speaker 1: And like, you know, I think in the nineties people

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Speaker 1: were obsessed with like is so and so gay? Is

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Speaker 1: so and so gay? Like that that is how we

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Speaker 1: that's like how we understand how a lot of people

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Speaker 1: understood sexuality, and like there was like I mean I

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Speaker 1: remember growing up, were like the worst thing you could

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Speaker 1: be was gay, and that like if someone was gay

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Speaker 1: or even the insinuation, they had to go on TV

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Speaker 1: and you know, have a press conference about it. So really,

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Speaker 1: I mean she wasn't alone in in that in that

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Speaker 1: attitude of course, Well, yeah, I mean her because there

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Speaker 1: was still a lot of spectacle in her show to

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Speaker 1: like aside from like early on, there were a lot

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Speaker 1: of things are just like yeah, make a mess up

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Speaker 1: and another time then I think she got It's interesting

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Speaker 1: because yeah, you see her evolved as a host to

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Speaker 1: and producer of her content. But I was just reading

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Speaker 1: the first time she met Dr Phil was when she

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Speaker 1: was being sued by cattlemen in the beef industry and

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Speaker 1: Texas and she had hired Dr Phil to counsel her

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Speaker 1: through this difficult period and that's when she learned her

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Speaker 1: head on approach to life counseling through Dr Phil. So yeah,

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Speaker 1: that's uh, we have we have this lawsuit with the

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Speaker 1: beef industry to think or the emergence of Doctor Phil

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Speaker 1: where they mad at her first saying beef was like

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Speaker 1: not good for you. Basically there's claiming, yes, she was

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Speaker 1: defaming the industry with some segment that she had done,

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Speaker 1: so Jesus can't win in the You should go back

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Speaker 1: and watch some of her old shows and segments, like

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Speaker 1: you said, like some of them are fucking wild. Remember

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Speaker 1: when she lost all that weight and she pulled a

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Speaker 1: wagon full of fat out on the show to demonstrate

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Speaker 1: how much weight she lost. It was like literally a

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Speaker 1: wagon stacked with like fat to demonstrate how much bat

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Speaker 1: she had lost. Yeah, it was I remember, I think

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Speaker 1: who someone I think made lampooned like it was like

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Speaker 1: in Living color or somebody did something of a similar. Yeah.

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Speaker 1: Look oh here, hold on, let me hit you out

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Speaker 1: with the wild screen share real quick. This is the

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Speaker 1: beauty of zoom now since we can all be there,

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Speaker 1: that's the wagon. Oh it looks like sucks cat. Uh yeah,

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Speaker 1: there's just all kinds of I must Actually there's there

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Speaker 1: there's an archive right where you can get all old

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Speaker 1: Oprah's because I think I need to do that. It

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Speaker 1: is wild, like like that is a that is a

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Speaker 1: rabbit hole I will gladly go down. But I mean,

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Speaker 1: I think she had people on who were helping perpetuate

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Speaker 1: the myth of the satanic panic in the eighties, and

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Speaker 1: I know that, uh, the Rainbow Party sexual moral panic

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Speaker 1: is specifically associated with her. So I mean she's got

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Speaker 1: she's got those shows in her past that are like

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Speaker 1: the dumbest that America has to offer. I just I

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Speaker 1: think in the end, you like, we look at Oprah

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Speaker 1: as like a fucking near god. So she should be

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Speaker 1: able to from Mount Olympus just take back Dr Phil

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Speaker 1: and Dr oz Is fame that she's so you know,

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Speaker 1: generously gave, she should be able to take it away.

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Speaker 1: And I'd like to see it exercise that power as

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Speaker 1: our protector and maker of lists of things we should

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Speaker 1: buy on Amazon Prime. Absolutely. Uh. And finally, bridget what

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Speaker 1: is a myth? What's something people think is true you

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00:22:22,320 --> 00:22:25,320
Speaker 1: know to be false? Ah, this is another Fago take.

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Speaker 1: I've been defending this take on Twitter all yesterday. I

401
00:22:28,960 --> 00:22:33,720
Speaker 1: think it is a myth that wealthy white tech dudes

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Speaker 1: who are like known for like one specific thing or

403
00:22:37,359 --> 00:22:40,159
Speaker 1: like got big on one specific success. It is a

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00:22:40,200 --> 00:22:44,680
Speaker 1: myth that those guys are uniquely smart or uniquely geniuses,

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Speaker 1: or are the kind of people that we should be

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Speaker 1: going to for guiding advice or guiding you know, takes

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Speaker 1: on other issues. And I'll say it, I'm talking about

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Speaker 1: Elon Musk. Elon Musk, Yes, like what I gonna say it.

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Speaker 1: I'm gonna go there, Elon Musk. Maybe isn't that smart

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Speaker 1: of a guy, Like he's tweeting wild shit about coronavirus, dangerous,

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Speaker 1: unhelpful shit about coronavirus. And it's one of those things

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Speaker 1: where certainly he's very successful, he has a lot of

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Speaker 1: business acumen. I'm not gonna say he doesn't have that.

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00:23:17,600 --> 00:23:19,760
Speaker 1: That's not true. But I think this idea that we

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Speaker 1: should be listening to him for thoughtful takes about a

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Speaker 1: public health pandemic is out of this is like wild,

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Speaker 1: you know, And I think that, like, I think that

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Speaker 1: someone who has demonstrated that they can't be trusted with

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Speaker 1: their own platform perhaps is not someone who is like

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Speaker 1: uniquely a genius. Also, somebody who invites like chaos agent

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Speaker 1: Azalea Banks into their home and life. Maybe that's not smart, right,

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Speaker 1: Like maybe maybe he like has some blind spots and

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Speaker 1: which just take him as he is. Yeah, I mean

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Speaker 1: of inviting Azalea Banks into your home, it will always

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Speaker 1: end with some kind of Twitter moment, right, like if

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Speaker 1: you do that, right, if you do that, you get

427
00:23:55,280 --> 00:23:58,440
Speaker 1: what you get? Like, like, how smart could you really be? Well? Yeah,

428
00:23:58,480 --> 00:24:01,200
Speaker 1: she was just collaborating with rhymes on a song, right,

429
00:24:01,359 --> 00:24:05,159
Speaker 1: and she like live tweeted being there and then not

430
00:24:05,280 --> 00:24:07,760
Speaker 1: being there or something. She live tweeted being in his

431
00:24:07,880 --> 00:24:10,280
Speaker 1: house and basically she was like, oh, all he does

432
00:24:10,320 --> 00:24:12,280
Speaker 1: this do drugs all day? Like they're so fucked up.

433
00:24:12,600 --> 00:24:15,840
Speaker 1: And her being in his home led to his own

434
00:24:15,920 --> 00:24:19,440
Speaker 1: shareholders subpoena being both Grimes and his daily Banks about

435
00:24:19,480 --> 00:24:22,160
Speaker 1: his business. So like, clearly that was not a savvy

436
00:24:22,200 --> 00:24:26,239
Speaker 1: business decision. You know, he's just you know, it's like

437
00:24:26,320 --> 00:24:29,320
Speaker 1: it's like anything you have, these Bill Gates and Elon

438
00:24:29,400 --> 00:24:33,359
Speaker 1: Musk figures that helped like a certain we can we

439
00:24:33,400 --> 00:24:36,040
Speaker 1: can sort of project our own ambitions onto them be

440
00:24:36,119 --> 00:24:37,880
Speaker 1: like you see, they just did it on their own,

441
00:24:38,000 --> 00:24:41,640
Speaker 1: but not knowing the extreme privilege Bill Gates even came from,

442
00:24:41,640 --> 00:24:45,440
Speaker 1: like how early he was interacting with computers before anyone else,

443
00:24:45,880 --> 00:24:48,320
Speaker 1: or even like Elon Musk, how we always talk about

444
00:24:48,640 --> 00:24:54,000
Speaker 1: growing up with fucking rubies and loose rights. It's like

445
00:24:54,119 --> 00:24:56,600
Speaker 1: we all do. Yeah, like when you start there, when

446
00:24:56,600 --> 00:24:59,879
Speaker 1: they're when there's that much capital around you as a child,

447
00:25:01,040 --> 00:25:04,560
Speaker 1: you're already starting a few levels up and so your

448
00:25:04,720 --> 00:25:07,080
Speaker 1: your shitty ideas, you'll be around people who help you

449
00:25:07,080 --> 00:25:10,120
Speaker 1: mold those very quickly. Uh, and you can you can

450
00:25:10,160 --> 00:25:12,320
Speaker 1: move from there. But yeah, like it's you know, like

451
00:25:12,400 --> 00:25:13,960
Speaker 1: they help us feel like you know, there's like the

452
00:25:13,960 --> 00:25:16,080
Speaker 1: new Tony Starks or some ship where it's like this

453
00:25:16,160 --> 00:25:19,600
Speaker 1: guy's sick, dude, he makes flame doors, smoke sweed like

454
00:25:19,680 --> 00:25:22,360
Speaker 1: fucking he calls divers who are trying to rescue kids

455
00:25:22,440 --> 00:25:27,200
Speaker 1: pedophiles such a hero man. Yeah, Yeah, there's this weird

456
00:25:27,240 --> 00:25:30,880
Speaker 1: thing that happened where um, Jeffrey Dahmer like came into

457
00:25:30,920 --> 00:25:34,720
Speaker 1: the public eye right after Silence of the Lambs came out,

458
00:25:34,720 --> 00:25:37,920
Speaker 1: and everybody was obsessed with cannibals, and we sort of

459
00:25:37,960 --> 00:25:43,280
Speaker 1: like manifested this like real world cannibal into existence. And

460
00:25:43,440 --> 00:25:48,240
Speaker 1: I think I think that aspect of him was over exaggerated.

461
00:25:48,240 --> 00:25:51,600
Speaker 1: But there are these weird times when like really iconic

462
00:25:52,119 --> 00:25:56,800
Speaker 1: um fictional characters pop up and then we like create

463
00:25:56,920 --> 00:26:01,879
Speaker 1: our real world version. I agree that uh elon Musk,

464
00:26:02,000 --> 00:26:05,800
Speaker 1: we just we needed a Tony Stark character, like somebody

465
00:26:05,840 --> 00:26:10,600
Speaker 1: who could help be the figurehead and uh so like

466
00:26:10,640 --> 00:26:14,040
Speaker 1: the cool person who knows how to do stuff. Wow,

467
00:26:14,240 --> 00:26:17,280
Speaker 1: like tech was kind of taking over our world and

468
00:26:17,320 --> 00:26:19,800
Speaker 1: becoming cool. Yeah, And I think, but it's easy to

469
00:26:19,840 --> 00:26:23,320
Speaker 1: get to feel like that he's larger than life because

470
00:26:23,320 --> 00:26:25,200
Speaker 1: when you look at the things that are being achieved,

471
00:26:25,200 --> 00:26:28,159
Speaker 1: they're not insignificant by any stretch of the imagination. So

472
00:26:28,200 --> 00:26:30,560
Speaker 1: it's not like a total fucking smoke and mirror show.

473
00:26:30,560 --> 00:26:32,280
Speaker 1: And I don't mean to say that anyone who's like

474
00:26:32,320 --> 00:26:35,960
Speaker 1: wowed by him is wrong. I think you can understand,

475
00:26:36,040 --> 00:26:38,920
Speaker 1: sure those things are cool, but his takes on everything

476
00:26:38,960 --> 00:26:42,320
Speaker 1: else I can't do. Tell me about ugly as trucks

477
00:26:42,400 --> 00:26:45,440
Speaker 1: and like electric cars. Fuck aside from that, bro, I

478
00:26:45,440 --> 00:26:47,760
Speaker 1: don't care about your music taste because you can't wrap

479
00:26:48,520 --> 00:26:52,480
Speaker 1: you look all dusty. There's nothing about you else I

480
00:26:52,520 --> 00:26:55,280
Speaker 1: need to know outside of your expertise. So let's leave

481
00:26:55,320 --> 00:26:57,840
Speaker 1: it there, sir. That's exactly how I feel. I think

482
00:26:57,840 --> 00:26:59,960
Speaker 1: that we I think you're totally right that we need

483
00:27:00,119 --> 00:27:02,919
Speaker 1: these larger than life figures, and then we assume that

484
00:27:02,920 --> 00:27:06,320
Speaker 1: because someone is good at something specific, but that means

485
00:27:06,320 --> 00:27:07,800
Speaker 1: that they're going to be a genius when it comes

486
00:27:07,840 --> 00:27:09,800
Speaker 1: to everything. And I just think that, like, if there's

487
00:27:09,840 --> 00:27:11,879
Speaker 1: one thing that this pandemic has taught us, that is

488
00:27:11,920 --> 00:27:15,440
Speaker 1: that not everybody has like a useful or helpful take.

489
00:27:15,720 --> 00:27:17,239
Speaker 1: And just because you're good at one thing that I mean,

490
00:27:17,240 --> 00:27:19,320
Speaker 1: you're gonna that that's going to apply to like a

491
00:27:19,640 --> 00:27:23,960
Speaker 1: literal public health emergency, right, I mean yeah, I guess

492
00:27:24,000 --> 00:27:26,040
Speaker 1: at the end of the day too, it's just your ego, right,

493
00:27:26,160 --> 00:27:29,000
Speaker 1: Like you feel compelled to scream ship that you don't

494
00:27:29,040 --> 00:27:31,760
Speaker 1: scream about ship you don't know about because your ego

495
00:27:31,840 --> 00:27:35,359
Speaker 1: cannot help itself. That's why he's like, this is fascism,

496
00:27:35,520 --> 00:27:38,440
Speaker 1: Like to shut the funk up, man, Nobody. I get

497
00:27:38,520 --> 00:27:41,240
Speaker 1: you have a captive audience on a shareholder call or whatever,

498
00:27:41,600 --> 00:27:44,760
Speaker 1: but like leave it alone. Yeah. I mean. The other

499
00:27:44,800 --> 00:27:48,320
Speaker 1: thing is that, like, you know, people being smarter than

500
00:27:48,320 --> 00:27:51,320
Speaker 1: other people is like maybe a degree level of like

501
00:27:51,680 --> 00:27:57,320
Speaker 1: you know, they're smarter, but because of the society that

502
00:27:57,359 --> 00:28:00,960
Speaker 1: we live in, there like a million times richer and

503
00:28:01,119 --> 00:28:04,320
Speaker 1: more powerful, and therefore it just like I think that

504
00:28:04,440 --> 00:28:07,120
Speaker 1: also gets reflected in there and too, just like how

505
00:28:07,160 --> 00:28:09,760
Speaker 1: we judge them and we just assume, well, they must

506
00:28:09,800 --> 00:28:15,200
Speaker 1: be a million times smarter and there's just no such thing. Wait,

507
00:28:15,240 --> 00:28:18,399
Speaker 1: what did you say that mixed was between knowledge and skill?

508
00:28:18,760 --> 00:28:21,000
Speaker 1: I was saying. I was just saying that, like, you know,

509
00:28:21,440 --> 00:28:25,439
Speaker 1: a person who's smarter than other people might be smarter,

510
00:28:26,080 --> 00:28:29,399
Speaker 1: but there because like these people are like millions of

511
00:28:29,440 --> 00:28:33,119
Speaker 1: times richer than other people, are more powerful, like they're

512
00:28:33,160 --> 00:28:38,080
Speaker 1: able to I think that gets like projected onto how

513
00:28:38,120 --> 00:28:41,280
Speaker 1: we view these people, and it's just right well, and

514
00:28:41,320 --> 00:28:43,880
Speaker 1: I think it's pretty I think it's pretty well documented,

515
00:28:43,960 --> 00:28:49,480
Speaker 1: right because it's ten percent luck, twenty percent skill, concentrated

516
00:28:49,520 --> 00:28:54,000
Speaker 1: power of will, five percent pleasure, fifty pain, and a

517
00:28:54,120 --> 00:28:57,600
Speaker 1: hundred percent reason to remember the name. Okay, I gotta

518
00:28:57,640 --> 00:29:03,440
Speaker 1: go wait, what is that from that fort minors? So,

519
00:29:07,000 --> 00:29:11,920
Speaker 1: you know, fucking from I'm sorry, bro, Lincoln Park has

520
00:29:11,920 --> 00:29:16,640
Speaker 1: to be fucked up. Huh. All right, let's take a

521
00:29:16,720 --> 00:29:20,640
Speaker 1: quick break to ponder that that reality and we'll be

522
00:29:20,760 --> 00:29:35,960
Speaker 1: right back. And we're back. Uh. And there's a article

523
00:29:36,080 --> 00:29:41,000
Speaker 1: by a guy who used to be the CEO of Permanente. Uh.

524
00:29:41,600 --> 00:29:44,440
Speaker 1: You know, so he has some experience and overall like

525
00:29:44,680 --> 00:29:49,840
Speaker 1: public health policy. Um on those he's like one of

526
00:29:49,840 --> 00:29:53,680
Speaker 1: those good Kaiser Foundation heads where afterwards he wrote books

527
00:29:53,680 --> 00:29:55,360
Speaker 1: about like or I don't know, I mean, based on

528
00:29:55,400 --> 00:29:57,440
Speaker 1: the titles of his books, he's like, yeah, why the

529
00:29:57,480 --> 00:30:00,360
Speaker 1: health care system isn't really working for you? You know,

530
00:30:00,400 --> 00:30:03,920
Speaker 1: he's not, like, I mean, guys, we provide a one

531
00:30:04,040 --> 00:30:09,000
Speaker 1: service to every single human being in the United States. Yeah, exactly.

532
00:30:09,120 --> 00:30:12,840
Speaker 1: So he recognized that the system is fucked and uh

533
00:30:12,880 --> 00:30:16,360
Speaker 1: he also just kind he wrote this article that I

534
00:30:16,400 --> 00:30:20,560
Speaker 1: thought underlined like three ways that we're not thinking about

535
00:30:20,600 --> 00:30:26,120
Speaker 1: the process of reopening in the most accurate way. One

536
00:30:26,120 --> 00:30:29,520
Speaker 1: of the things he points out is that whenever we

537
00:30:29,560 --> 00:30:33,640
Speaker 1: stop sheltering in place and we we will have to stop,

538
00:30:34,160 --> 00:30:38,960
Speaker 1: the virus will come back and people will get sick. Um,

539
00:30:39,120 --> 00:30:43,480
Speaker 1: like that the ideas we aren't quarantining and like hoping

540
00:30:43,520 --> 00:30:47,400
Speaker 1: the virus will go away while we're quarantining. We're quarantining

541
00:30:47,400 --> 00:30:51,000
Speaker 1: to give hospitals time to make room for us when

542
00:30:51,040 --> 00:30:54,520
Speaker 1: we get sick, and you know, prepare doctors so we

543
00:30:54,600 --> 00:30:57,960
Speaker 1: don't make doctors sick. But he's like, this isn't like

544
00:30:58,040 --> 00:31:01,880
Speaker 1: fatalistic or pessimistic. This is just a biological fact that

545
00:31:01,960 --> 00:31:07,200
Speaker 1: like once people stop social distancing, uh, you know people,

546
00:31:07,320 --> 00:31:11,320
Speaker 1: the will see the numbers go back up again. Right, Well,

547
00:31:11,320 --> 00:31:13,720
Speaker 1: I think some people are actually connecting like their own

548
00:31:13,760 --> 00:31:16,520
Speaker 1: personal boredom with like yeah, dude, I'm so bored. So

549
00:31:16,560 --> 00:31:22,960
Speaker 1: this coronavirus is probably fucked right now. Yeah, And then

550
00:31:23,120 --> 00:31:27,240
Speaker 1: he he was also just talking about how um yeah,

551
00:31:27,280 --> 00:31:29,400
Speaker 1: I mean it kind of all ties back to that.

552
00:31:29,440 --> 00:31:33,520
Speaker 1: But like the idea of I had assumed that we

553
00:31:34,200 --> 00:31:38,080
Speaker 1: could still like you know what, once we started testing

554
00:31:38,120 --> 00:31:43,040
Speaker 1: and people knew like whether they had it or not,

555
00:31:43,160 --> 00:31:47,600
Speaker 1: we could like quarantine and sort of it would go away.

556
00:31:47,640 --> 00:31:51,160
Speaker 1: And he said that that ships sailed back in February,

557
00:31:51,200 --> 00:31:55,720
Speaker 1: like it's too widespread to do the like contact tracing

558
00:31:55,800 --> 00:31:58,800
Speaker 1: that they did in China. Uh So in order to

559
00:31:58,840 --> 00:32:01,560
Speaker 1: reopen the country, you just need to go location by

560
00:32:01,600 --> 00:32:04,800
Speaker 1: location and look at stuff like whether the hospitals have

561
00:32:04,920 --> 00:32:06,960
Speaker 1: space for all the people who are going to get

562
00:32:06,960 --> 00:32:10,520
Speaker 1: sick when you reopen um and then just like put

563
00:32:11,360 --> 00:32:15,960
Speaker 1: things in place, policies in place in those locations, and

564
00:32:16,000 --> 00:32:19,440
Speaker 1: have testing so that you know, you have people have

565
00:32:19,520 --> 00:32:23,200
Speaker 1: some idea of whether they have have the virus or not,

566
00:32:23,840 --> 00:32:26,920
Speaker 1: and then you just emphasize the importance of are not.

567
00:32:28,160 --> 00:32:30,440
Speaker 1: I've been seeing more and more headlines about the fact

568
00:32:30,440 --> 00:32:34,000
Speaker 1: that like the numbers that we're paying attention to, which

569
00:32:34,040 --> 00:32:36,120
Speaker 1: is like number of people who have it and the

570
00:32:36,200 --> 00:32:39,880
Speaker 1: number of people who have died, are not like that.

571
00:32:40,680 --> 00:32:44,040
Speaker 1: First of all, they're somewhat arbitrary because we're under counting

572
00:32:44,040 --> 00:32:46,960
Speaker 1: the number of people who died and vastly undercounting the

573
00:32:47,040 --> 00:32:49,280
Speaker 1: number of people who have it because of how bad

574
00:32:49,320 --> 00:32:53,520
Speaker 1: the testing is. But it's also just kind of a

575
00:32:53,600 --> 00:32:58,400
Speaker 1: confusing number. And the best way to look at it

576
00:32:58,440 --> 00:33:02,160
Speaker 1: is something called are not, which is uh the rate

577
00:33:02,520 --> 00:33:07,320
Speaker 1: like basically um if if you have if a disease

578
00:33:07,320 --> 00:33:10,520
Speaker 1: hasn't R not it's written like R and then a

579
00:33:10,560 --> 00:33:15,240
Speaker 1: little like zero below, not like an A U G

580
00:33:15,480 --> 00:33:20,040
Speaker 1: H T. Yeah, and if if it has a R

581
00:33:20,200 --> 00:33:23,880
Speaker 1: not of one, that means for every one person who

582
00:33:23,880 --> 00:33:28,360
Speaker 1: gets sick, they will pass the disease onto one other person,

583
00:33:28,960 --> 00:33:33,600
Speaker 1: so the rate will be flat. And so anything over

584
00:33:33,720 --> 00:33:36,440
Speaker 1: one and you're going to see the curve bending upwards,

585
00:33:36,520 --> 00:33:39,640
Speaker 1: and anything underword under one, you're going to see the

586
00:33:39,640 --> 00:33:42,480
Speaker 1: curve bending downwards. And so he's just saying like that

587
00:33:42,760 --> 00:33:45,959
Speaker 1: is the most important number to pay attention to. The

588
00:33:46,000 --> 00:33:51,120
Speaker 1: founders of Instagram created a website called rt alive UH,

589
00:33:51,520 --> 00:33:55,040
Speaker 1: which is rate of Transmission UM, and they have it

590
00:33:55,160 --> 00:33:59,600
Speaker 1: broken out by state, and it's basically, you know, we've

591
00:33:59,680 --> 00:34:03,320
Speaker 1: made progress through social distancing, through having like nine percent

592
00:34:03,400 --> 00:34:07,000
Speaker 1: of the country shut down UH. And so all of

593
00:34:07,120 --> 00:34:12,120
Speaker 1: these are not numbers are going from like well over

594
00:34:12,239 --> 00:34:16,520
Speaker 1: one to under one over the course of the past month,

595
00:34:17,040 --> 00:34:20,200
Speaker 1: but you know they'll go right back up once we

596
00:34:20,360 --> 00:34:25,880
Speaker 1: stopped social distancing. So UM, that's kind of the number

597
00:34:25,960 --> 00:34:28,359
Speaker 1: to be paying attention to because it also takes into

598
00:34:28,440 --> 00:34:33,239
Speaker 1: some into account like population size and UM. It's just

599
00:34:34,040 --> 00:34:38,120
Speaker 1: it was interesting. It's like an article, a short article,

600
00:34:38,160 --> 00:34:41,000
Speaker 1: but it's definitely going to change the way that I

601
00:34:41,000 --> 00:34:45,200
Speaker 1: am looking at and thinking about the overall issue. Yeah,

602
00:34:45,280 --> 00:34:48,120
Speaker 1: something that you said that I really want to amplify,

603
00:34:48,200 --> 00:34:51,160
Speaker 1: and like plus one, it's the idea that we really

604
00:34:51,200 --> 00:34:52,880
Speaker 1: don't because of how the testing is a round, we

605
00:34:52,920 --> 00:34:56,080
Speaker 1: really don't know and probably won't know the actual numbers

606
00:34:56,080 --> 00:34:58,160
Speaker 1: of who got it, who died from it. That's one

607
00:34:58,160 --> 00:35:00,879
Speaker 1: of my biggest concerns is that after this is all over,

608
00:35:01,360 --> 00:35:04,120
Speaker 1: we won't even ever get a clear picture of what

609
00:35:04,160 --> 00:35:06,799
Speaker 1: we were dealing with. And I just I hate the

610
00:35:06,880 --> 00:35:09,480
Speaker 1: idea that this history that we're living through is going

611
00:35:09,520 --> 00:35:11,600
Speaker 1: to be erased and not preserved and we won't even

612
00:35:11,640 --> 00:35:14,520
Speaker 1: have an accurate account of what's happening. That's like something

613
00:35:14,520 --> 00:35:19,480
Speaker 1: that I guess I associate that more with a bygone history,

614
00:35:19,520 --> 00:35:21,640
Speaker 1: you know, in I would think that we would have

615
00:35:21,840 --> 00:35:24,680
Speaker 1: we would be able to preserve an accurate account of

616
00:35:24,680 --> 00:35:26,959
Speaker 1: what we what we all recently lived through, and coming

617
00:35:26,960 --> 00:35:28,759
Speaker 1: to realize that that's not the case. It's it's really

618
00:35:29,160 --> 00:35:32,000
Speaker 1: not just scary about sort of I don't know, like

619
00:35:32,040 --> 00:35:35,319
Speaker 1: psychically disorienting in a kind of way. Well, I think

620
00:35:35,360 --> 00:35:38,719
Speaker 1: also too, we could put the effort into it and

621
00:35:38,920 --> 00:35:42,480
Speaker 1: endeavor to try and accurately determine what the true cost

622
00:35:42,719 --> 00:35:46,120
Speaker 1: was by you know, speaking to the health experts, like

623
00:35:46,200 --> 00:35:48,879
Speaker 1: people in other countries have said, you know, how much

624
00:35:48,920 --> 00:35:51,920
Speaker 1: they suspect actually what other deaths they would probably as

625
00:35:52,000 --> 00:35:54,520
Speaker 1: doctors a tribute to this because of lack of care

626
00:35:54,560 --> 00:35:57,680
Speaker 1: and things like that. But just knowing that the tactics

627
00:35:57,719 --> 00:35:59,799
Speaker 1: that have been being taken here of just being like,

628
00:36:00,120 --> 00:36:02,319
Speaker 1: let's not test are initially we just didn't want to

629
00:36:02,320 --> 00:36:04,720
Speaker 1: test because we didn't want to get an embarrassing number

630
00:36:04,800 --> 00:36:09,960
Speaker 1: on the test, so let's not test. So yeah, I mean, yeah,

631
00:36:10,239 --> 00:36:12,719
Speaker 1: having to know that we're also fighting that, like you know,

632
00:36:12,880 --> 00:36:17,480
Speaker 1: the suppression of that knowledge is really also totally funked

633
00:36:17,520 --> 00:36:22,080
Speaker 1: up and frightening. Yeah. Absolutely. I mean with Puerto Rico

634
00:36:22,160 --> 00:36:26,240
Speaker 1: and Hurricane Maria, the way that they like eventually figured

635
00:36:26,280 --> 00:36:29,000
Speaker 1: out was just like looking at the overall rate of

636
00:36:29,920 --> 00:36:33,839
Speaker 1: deaths like at that time normally and then comparing that

637
00:36:33,880 --> 00:36:37,800
Speaker 1: to overall rate of deaths like during the time after

638
00:36:38,600 --> 00:36:42,040
Speaker 1: the hurricane. And I feel like that's probably what will

639
00:36:42,160 --> 00:36:45,879
Speaker 1: end up having to resort to here. Although there are

640
00:36:47,160 --> 00:36:50,080
Speaker 1: orders in place in a lot of places in America

641
00:36:50,200 --> 00:36:52,520
Speaker 1: that are like preserve the body or at least a

642
00:36:52,520 --> 00:36:55,480
Speaker 1: tissue sample so that we can test everything, like once

643
00:36:55,600 --> 00:37:00,000
Speaker 1: the crisis is over, just so we have a better idea. Um.

644
00:37:00,040 --> 00:37:02,440
Speaker 1: But yeah, there's a lot of chaos and a lot

645
00:37:02,480 --> 00:37:07,040
Speaker 1: of political forces at work. I was just kind of

646
00:37:07,040 --> 00:37:09,480
Speaker 1: looking or just thinking about just with Puerto Rico and

647
00:37:09,520 --> 00:37:14,799
Speaker 1: the death toll, like how there were so many competing numbers. Uh,

648
00:37:14,840 --> 00:37:17,680
Speaker 1: And you know, I'm not sure that the official version,

649
00:37:17,960 --> 00:37:19,600
Speaker 1: you know, that's the thing. It's like, we can compare

650
00:37:19,640 --> 00:37:22,160
Speaker 1: that and say that's probably what happened, but the version

651
00:37:22,200 --> 00:37:24,719
Speaker 1: that the government is going to acknowledge, like, no, it

652
00:37:24,800 --> 00:37:27,759
Speaker 1: wasn't that bad. And I think that's where, you know,

653
00:37:28,239 --> 00:37:31,640
Speaker 1: that's that's where I think the real hard bit of

654
00:37:31,680 --> 00:37:33,440
Speaker 1: coming out of this is going to happen, where we

655
00:37:33,480 --> 00:37:35,799
Speaker 1: have to really look in the eye, like all the

656
00:37:35,840 --> 00:37:40,120
Speaker 1: people we've let down, and how quickly some people will

657
00:37:40,120 --> 00:37:42,319
Speaker 1: are be will be willing to ignore that like our

658
00:37:42,360 --> 00:37:45,440
Speaker 1: own neighbors, and rather would move on to the comfort

659
00:37:45,520 --> 00:37:49,200
Speaker 1: of a world where, you know, such widespread pain didn't exist.

660
00:37:49,680 --> 00:37:54,120
Speaker 1: But you know, I'm hoping hopefully people can confront that

661
00:37:54,239 --> 00:37:56,120
Speaker 1: a bit more coming out of this, because I think

662
00:37:56,160 --> 00:37:58,560
Speaker 1: that's the only positive thing we can take out of this.

663
00:37:58,600 --> 00:38:02,520
Speaker 1: Is try and you know, replicate this kind of disregard

664
00:38:02,800 --> 00:38:05,000
Speaker 1: for our neighbors that got us to this place and

665
00:38:05,080 --> 00:38:08,719
Speaker 1: to begin with absolutely, And I think for me, as

666
00:38:08,760 --> 00:38:11,480
Speaker 1: soon as I heard that the that like and this

667
00:38:11,520 --> 00:38:13,520
Speaker 1: is was not surprising to me. As soon as I

668
00:38:13,560 --> 00:38:17,600
Speaker 1: heard that COVID was ravaging black and brown communities, I

669
00:38:17,680 --> 00:38:20,640
Speaker 1: knew that was going to change the public perception of

670
00:38:20,680 --> 00:38:24,000
Speaker 1: the virus. I knew it. I knew it immediately. And

671
00:38:25,000 --> 00:38:29,360
Speaker 1: it's just I think even I mean this, I paid

672
00:38:29,680 --> 00:38:32,160
Speaker 1: I take no joy in saying this, and it pains

673
00:38:32,200 --> 00:38:34,520
Speaker 1: me to say. I think a lot of people, even

674
00:38:34,600 --> 00:38:37,680
Speaker 1: progressive people, even people that I like, respect, I think

675
00:38:37,719 --> 00:38:40,880
Speaker 1: there is something about black and brown death, black and

676
00:38:40,920 --> 00:38:43,879
Speaker 1: brown pain that like doesn't hit the same way for them.

677
00:38:43,920 --> 00:38:45,960
Speaker 1: And I think that, like, it's no surprise that all

678
00:38:46,000 --> 00:38:49,319
Speaker 1: of these reopened Michigan reopen, this reopen, that all of

679
00:38:49,360 --> 00:38:55,279
Speaker 1: these rallies we saw after it became clearer which communities

680
00:38:55,320 --> 00:38:57,320
Speaker 1: were at at the most at risk for this. I

681
00:38:57,320 --> 00:38:59,480
Speaker 1: think that's not not an accident, you know. I think

682
00:38:59,520 --> 00:39:01,680
Speaker 1: that like we have to sort of I think that

683
00:39:01,719 --> 00:39:05,040
Speaker 1: this will hopefully, like you were saying, Miles, we will

684
00:39:05,320 --> 00:39:08,799
Speaker 1: have to look at some hard truth. Look at some

685
00:39:08,800 --> 00:39:11,360
Speaker 1: stuff we don't want to look at about ourselves, about

686
00:39:11,400 --> 00:39:13,799
Speaker 1: how we treat our neighbors, about how we view them,

687
00:39:13,840 --> 00:39:16,000
Speaker 1: if we view them the same way as we view ourselves,

688
00:39:16,000 --> 00:39:18,200
Speaker 1: Like I think, we're really going to have to do

689
00:39:18,239 --> 00:39:23,279
Speaker 1: a lot of looking within at the end of all this.

690
00:39:23,360 --> 00:39:25,800
Speaker 1: I hope you do, and you know, and I challenge

691
00:39:25,840 --> 00:39:29,399
Speaker 1: people to look within yourself, to think of what your

692
00:39:29,440 --> 00:39:33,400
Speaker 1: responses to hearing things like that, and not to judge yourself.

693
00:39:33,920 --> 00:39:37,400
Speaker 1: But you know, we were a product of this entire

694
00:39:37,520 --> 00:39:41,600
Speaker 1: system that we've been raised in as Americans. So look

695
00:39:41,640 --> 00:39:43,520
Speaker 1: at that for a second at least give yourself the

696
00:39:43,560 --> 00:39:46,360
Speaker 1: moment say, oh, maybe I am looking at that not

697
00:39:46,480 --> 00:39:49,160
Speaker 1: as humanely as I could. I might not be looking

698
00:39:49,200 --> 00:39:51,759
Speaker 1: that in this with the same amount of compassion as

699
00:39:51,800 --> 00:39:54,719
Speaker 1: I might if it were someone who looked exactly like me,

700
00:39:54,800 --> 00:39:57,680
Speaker 1: came from the exact place I did. It's hard, It

701
00:39:57,920 --> 00:40:01,120
Speaker 1: is fucking hard. You don't develop those kind the skills overnight.

702
00:40:01,400 --> 00:40:04,640
Speaker 1: And I understand, I don't. You know, I'm a bit pessimistic.

703
00:40:04,680 --> 00:40:06,719
Speaker 1: I don't count I don't count on most people coming

704
00:40:06,760 --> 00:40:10,640
Speaker 1: out of this learning those lessons. But I'm hoping that

705
00:40:10,760 --> 00:40:13,799
Speaker 1: people because there is this time of like you know,

706
00:40:13,960 --> 00:40:18,480
Speaker 1: relative slowness in terms of like the pace of life,

707
00:40:18,520 --> 00:40:21,120
Speaker 1: that you can for a moment take stock and understand

708
00:40:21,120 --> 00:40:23,239
Speaker 1: that we are living in like a system that is

709
00:40:23,239 --> 00:40:27,319
Speaker 1: breaking down. Um and it's and you might just be

710
00:40:27,600 --> 00:40:29,560
Speaker 1: it's just like looking at a piece of bread that

711
00:40:29,600 --> 00:40:31,440
Speaker 1: has mold on it. You're just not at the moldy

712
00:40:31,520 --> 00:40:35,040
Speaker 1: part yet, but the motherfucker is molding. So you can

713
00:40:35,080 --> 00:40:38,040
Speaker 1: be do the hard bit and recognize that maybe your

714
00:40:38,120 --> 00:40:40,480
Speaker 1: piece of bread is not has not molded over yet,

715
00:40:40,520 --> 00:40:42,839
Speaker 1: but it's coming and we need to really look out

716
00:40:42,840 --> 00:40:45,040
Speaker 1: for the parts that are moldy. Okay, well moldy bread

717
00:40:45,040 --> 00:40:47,560
Speaker 1: metaphor over. I mean, I just want to I I

718
00:40:47,600 --> 00:40:49,480
Speaker 1: agree so much. I want to share something. I think

719
00:40:49,600 --> 00:40:51,600
Speaker 1: if I can have like a vulnerable moment, you know,

720
00:40:51,680 --> 00:40:54,520
Speaker 1: it isn't easy to acknowledge your blind spots and your

721
00:40:54,560 --> 00:40:56,799
Speaker 1: privileges and all of this at a moment earlier in

722
00:40:56,840 --> 00:40:59,879
Speaker 1: the week where you know. So, I'm a huge Beyonce fan,

723
00:41:00,080 --> 00:41:02,799
Speaker 1: love Beyonce in the behald in the behind all of that.

724
00:41:03,440 --> 00:41:06,640
Speaker 1: Beyonce's mother, Tina Knowles, shared an image on Instagram of

725
00:41:06,640 --> 00:41:09,880
Speaker 1: a family friend who unfortunately passed away from coronavirus, and

726
00:41:10,200 --> 00:41:13,279
Speaker 1: she shared a picture of how Beyonce when she was

727
00:41:13,320 --> 00:41:15,319
Speaker 1: a child was a flower girl at her wedding. This

728
00:41:15,320 --> 00:41:18,000
Speaker 1: woman I think was a medical professional or first responder

729
00:41:18,080 --> 00:41:21,000
Speaker 1: or a nurse, and you know, I just I shared

730
00:41:21,040 --> 00:41:22,400
Speaker 1: that and I was like, oh, like thinking of the

731
00:41:22,440 --> 00:41:24,799
Speaker 1: Knowles family. You know, this is so sad. And someone

732
00:41:24,920 --> 00:41:26,800
Speaker 1: was like, why are you thinking of the Knowles family.

733
00:41:26,920 --> 00:41:29,200
Speaker 1: Why are you not thinking about the this like woman

734
00:41:29,320 --> 00:41:31,680
Speaker 1: who was a nurse who was at the front lines

735
00:41:31,719 --> 00:41:35,200
Speaker 1: of this pandemic. Shouldn't shouldn't she shouldn't she be the

736
00:41:35,239 --> 00:41:38,000
Speaker 1: one that you're keeping in your thoughts, not necessarily Beyonce

737
00:41:38,160 --> 00:41:39,840
Speaker 1: and her family. And I was like, you know what,

738
00:41:39,880 --> 00:41:42,120
Speaker 1: You're right, like what is And I had to really

739
00:41:42,160 --> 00:41:43,640
Speaker 1: take a beat and be like what is it in

740
00:41:43,760 --> 00:41:46,760
Speaker 1: me that when I heard this news my first thought

741
00:41:46,840 --> 00:41:49,520
Speaker 1: was like, oh, poor Beyonce, poor Noels family, and not

742
00:41:49,760 --> 00:41:53,280
Speaker 1: like wow, this woman was a nurse, her like she died,

743
00:41:53,320 --> 00:41:57,000
Speaker 1: she lost her life fighting this pandemic. And I immediately

744
00:41:57,040 --> 00:41:59,319
Speaker 1: just like I had to really sit with that. It

745
00:41:59,320 --> 00:42:02,000
Speaker 1: was uncomfortable. I did really sit with like, well, is

746
00:42:02,000 --> 00:42:04,120
Speaker 1: it the fact that Beyonce is a celebrity and that

747
00:42:04,239 --> 00:42:06,520
Speaker 1: I really like her, you know, and that I I

748
00:42:06,560 --> 00:42:10,160
Speaker 1: feel like I know her in heavy quotes, you know. Um,

749
00:42:10,239 --> 00:42:12,239
Speaker 1: I had to really do some sitting with that, and

750
00:42:12,280 --> 00:42:15,000
Speaker 1: it wasn't fun and it wasn't comfortable, but I really

751
00:42:15,040 --> 00:42:18,359
Speaker 1: had to I I should be able to be better

752
00:42:18,400 --> 00:42:22,080
Speaker 1: than that, and I have to interrogate why I wasn't

753
00:42:22,080 --> 00:42:23,440
Speaker 1: in that moment, you know. And so I think that

754
00:42:23,520 --> 00:42:25,200
Speaker 1: it's a this is a I think you're right. This

755
00:42:25,239 --> 00:42:27,720
Speaker 1: is a moment for all of us to be doing

756
00:42:27,719 --> 00:42:29,719
Speaker 1: that kind of thinking. And it's not easy, you know,

757
00:42:29,840 --> 00:42:34,239
Speaker 1: we're all products of this. Alright, Let's talk about the

758
00:42:34,280 --> 00:42:38,600
Speaker 1: President and how he's feeling right now, because the stress

759
00:42:39,000 --> 00:42:42,920
Speaker 1: might be getting to him. He apparently recently just be

760
00:42:43,160 --> 00:42:51,080
Speaker 1: rated his uh campaign manager bread parsk par Scale Parscale. Uh,

761
00:42:52,040 --> 00:42:54,160
Speaker 1: you don't. He doesn't deserve the respect of a proper

762
00:42:54,200 --> 00:42:57,440
Speaker 1: pronunciation of his name, but he went he was the

763
00:42:57,560 --> 00:43:01,360
Speaker 1: digital guy on the first campaign, and now he's the

764
00:43:01,400 --> 00:43:04,120
Speaker 1: full on campaign manager. Yeah, you know, you don't want

765
00:43:04,120 --> 00:43:08,160
Speaker 1: that job. It seems like it seems like the President

766
00:43:08,280 --> 00:43:11,120
Speaker 1: that now that some bad numbers are coming out following,

767
00:43:11,520 --> 00:43:16,360
Speaker 1: you know, his discussion of how we should be injecting bleach.

768
00:43:17,000 --> 00:43:20,640
Speaker 1: Uh our doctors. Well, well, I didn't say. I'm just

769
00:43:20,640 --> 00:43:22,600
Speaker 1: saying that it could be. It could you could have

770
00:43:22,640 --> 00:43:25,279
Speaker 1: a function of disinfecting. That was the intent. I never

771
00:43:25,400 --> 00:43:27,320
Speaker 1: said that, Okay, and if I was, I was joking.

772
00:43:27,560 --> 00:43:32,160
Speaker 1: But I think it's tough. Yeah, exactly, It's just, oh man,

773
00:43:32,239 --> 00:43:34,160
Speaker 1: let me get a fucking let me get a jumbo

774
00:43:34,239 --> 00:43:37,840
Speaker 1: of some sunlight real quick. Got red tops and sunlight.

775
00:43:38,040 --> 00:43:42,319
Speaker 1: So Brad Parscale, he really tried. Uh. It seemed like,

776
00:43:42,400 --> 00:43:45,319
Speaker 1: you know, it was clear to most people what the

777
00:43:45,320 --> 00:43:49,359
Speaker 1: the campaign road map was just fucking ring the bell

778
00:43:49,440 --> 00:43:52,480
Speaker 1: of the economy and like we've never don't risk it now,

779
00:43:53,040 --> 00:43:56,160
Speaker 1: don't risk it now, come on home to Donald Trump,

780
00:43:56,239 --> 00:43:58,960
Speaker 1: where we don't give a funk about anybody, but we'll

781
00:43:59,000 --> 00:44:03,440
Speaker 1: pretend for until November. So after you know, the pandemic hit.

782
00:44:03,760 --> 00:44:07,640
Speaker 1: It basically just upended everything. And because these people are

783
00:44:07,719 --> 00:44:10,840
Speaker 1: so inelegant and they're thinking, and that is such a

784
00:44:10,920 --> 00:44:13,919
Speaker 1: nice way of saying it, Uh, they are really scrambling

785
00:44:14,160 --> 00:44:16,360
Speaker 1: to figure out what the funk to do. So I

786
00:44:16,400 --> 00:44:20,600
Speaker 1: think one of the first things, um was that you know,

787
00:44:21,400 --> 00:44:24,120
Speaker 1: people were saying, Okay, maybe do these get in front

788
00:44:24,120 --> 00:44:26,440
Speaker 1: of these people or whatever, get your name out there,

789
00:44:26,480 --> 00:44:29,160
Speaker 1: because you can't do rallies anymore, because that's what he loves.

790
00:44:29,280 --> 00:44:31,680
Speaker 1: And then the ship started going south in the rallies

791
00:44:31,760 --> 00:44:35,080
Speaker 1: because these weren't like leaks that were happening. He was

792
00:44:35,160 --> 00:44:38,200
Speaker 1: just doing this ship in full view of the public

793
00:44:38,239 --> 00:44:41,920
Speaker 1: with cameras rolling, and naturally the numbers started tanking. So

794
00:44:42,400 --> 00:44:45,800
Speaker 1: Trump got so pissed he threatened to sue par Scale

795
00:44:45,880 --> 00:44:50,960
Speaker 1: Parscal because the numbers were so bad. Now just threatened

796
00:44:51,000 --> 00:44:54,319
Speaker 1: to sue his campaign manager because he was like, what

797
00:44:54,360 --> 00:44:56,719
Speaker 1: the funk are these full numbers? I should sue you

798
00:44:58,000 --> 00:45:04,560
Speaker 1: for doing your job. So again, this is a man

799
00:45:04,600 --> 00:45:09,120
Speaker 1: who's completely incapable of even understanding what his role is

800
00:45:09,200 --> 00:45:14,480
Speaker 1: in reality and existing as another life form and how

801
00:45:14,520 --> 00:45:17,880
Speaker 1: other people may view you as this existing life for him.

802
00:45:18,200 --> 00:45:20,600
Speaker 1: So another interesting thing in some of these articles say

803
00:45:20,600 --> 00:45:24,400
Speaker 1: that a few days before the LISOL present Great LISOL

804
00:45:24,880 --> 00:45:29,160
Speaker 1: power point presentation he did uh he was confronted with

805
00:45:29,600 --> 00:45:32,280
Speaker 1: like really bad poll numbers, not just from par Scale,

806
00:45:32,320 --> 00:45:38,560
Speaker 1: but from uh Mitt. Romney's niece Ronna what's her other anyway,

807
00:45:38,600 --> 00:45:42,480
Speaker 1: she's the chair of the rnc UM And these numbers

808
00:45:42,480 --> 00:45:45,520
Speaker 1: were basically saying, Joe Biden will fucking smoke you in

809
00:45:45,560 --> 00:45:50,239
Speaker 1: November because these performances are so fucking bad, and they

810
00:45:50,239 --> 00:45:53,320
Speaker 1: were begging him. They said, look, if you can't stop

811
00:45:53,440 --> 00:45:56,560
Speaker 1: doing the briefings, like our suggestion is the reason these

812
00:45:56,640 --> 00:45:59,160
Speaker 1: numbers are bad is because of these fucked up briefings.

813
00:45:59,160 --> 00:46:01,840
Speaker 1: Now we can island back or if you've got to

814
00:46:01,880 --> 00:46:06,200
Speaker 1: be out there, just don't answer any questions. That's something

815
00:46:06,280 --> 00:46:11,840
Speaker 1: they suggested to him. Just damn being quiet would actually

816
00:46:11,880 --> 00:46:13,600
Speaker 1: be better, Like, you know what you can do to

817
00:46:13,640 --> 00:46:16,440
Speaker 1: improve your numbers, just stop talking. Yeah, I mean that's

818
00:46:16,440 --> 00:46:18,239
Speaker 1: what they're that's what they're saying, but they have to

819
00:46:18,239 --> 00:46:20,920
Speaker 1: say it and think weird asked ways of like you

820
00:46:20,960 --> 00:46:23,680
Speaker 1: can do them, but just don't answer questions. That's not

821
00:46:23,719 --> 00:46:27,680
Speaker 1: gonna He's not gonna understand what you mean. He just means, yeah, fine, okay,

822
00:46:27,719 --> 00:46:29,799
Speaker 1: I'll just say what the funk I want then up there,

823
00:46:30,280 --> 00:46:32,480
Speaker 1: you know, which is essentially what is going on. So

824
00:46:32,520 --> 00:46:35,840
Speaker 1: it's it's really really um I think indicative of the

825
00:46:35,880 --> 00:46:39,839
Speaker 1: fact that he really is failing to understand. We've seen

826
00:46:39,880 --> 00:46:42,960
Speaker 1: time and again he's failing to understand just the essential

827
00:46:43,040 --> 00:46:46,359
Speaker 1: science around this pandemic. He's failing to understand his own

828
00:46:46,520 --> 00:46:49,239
Speaker 1: role as a leader, and even in a like a

829
00:46:49,360 --> 00:46:54,240
Speaker 1: fucking broader sense, like an existential fucking level. This man

830
00:46:54,600 --> 00:46:59,040
Speaker 1: is does not even understand how his existence is affecting

831
00:46:59,160 --> 00:47:02,600
Speaker 1: what the new who's is about himself the president of

832
00:47:02,600 --> 00:47:07,520
Speaker 1: the United States, and will sue his campaign manager. Mm hmm.

833
00:47:09,040 --> 00:47:12,640
Speaker 1: It's so it's so like if it wasn't something that

834
00:47:12,680 --> 00:47:15,520
Speaker 1: we were living through, it would almost be funny, right Like,

835
00:47:15,560 --> 00:47:17,600
Speaker 1: if it wasn't something that we had to deal with.

836
00:47:17,800 --> 00:47:20,320
Speaker 1: It's so out there that it would almost be humorous

837
00:47:20,360 --> 00:47:22,920
Speaker 1: to have to have a president that is this not

838
00:47:23,040 --> 00:47:27,720
Speaker 1: just as bad at leading, but this bad like understanding

839
00:47:27,800 --> 00:47:29,680
Speaker 1: how people see him, you know what I mean. Like

840
00:47:30,360 --> 00:47:32,800
Speaker 1: if someone told me, you're making things worse by just talking,

841
00:47:32,840 --> 00:47:35,520
Speaker 1: so just shut up, that tell me a lot, Like

842
00:47:35,760 --> 00:47:37,720
Speaker 1: you're a hater. You're a hater. You're a hater. Because

843
00:47:37,719 --> 00:47:40,080
Speaker 1: that's the other thing too, They say, he famously always

844
00:47:40,080 --> 00:47:42,720
Speaker 1: does this if polls are bad or if data is bad,

845
00:47:42,840 --> 00:47:46,200
Speaker 1: he doesn't believe it. He just doesn't believe it. That's

846
00:47:46,239 --> 00:47:48,480
Speaker 1: just how it works. So no one and a lot

847
00:47:48,480 --> 00:47:51,320
Speaker 1: of insiders saying, like the mistake they made was showing

848
00:47:51,400 --> 00:47:54,640
Speaker 1: him poll numbers that were bad because it's never gonna

849
00:47:54,800 --> 00:47:57,120
Speaker 1: it will It's never worked. It will never work, alright,

850
00:47:57,120 --> 00:47:59,080
Speaker 1: because let's take one more break and we'll come back

851
00:47:59,120 --> 00:48:15,280
Speaker 1: with bullshit and we're back. And one kind of topic

852
00:48:15,320 --> 00:48:19,440
Speaker 1: of conversation that I've seen many different kind of opposing

853
00:48:19,520 --> 00:48:24,320
Speaker 1: takes on is is horny nous during the core corny

854
00:48:24,400 --> 00:48:29,560
Speaker 1: nous um. So what one piece of evidence we had

855
00:48:29,600 --> 00:48:32,759
Speaker 1: been kind of looking at in the past was a

856
00:48:33,200 --> 00:48:37,960
Speaker 1: report that Chinese drug stores were completely out of condoms

857
00:48:38,680 --> 00:48:42,480
Speaker 1: and that that was like their version of toilet paper.

858
00:48:43,040 --> 00:48:45,239
Speaker 1: But people are now saying that that might have had

859
00:48:45,280 --> 00:48:48,440
Speaker 1: more to do with the supply chain than it does

860
00:48:48,719 --> 00:48:52,560
Speaker 1: with how much sex everybody was having. Well that and

861
00:48:52,640 --> 00:48:56,000
Speaker 1: like people just I think maybe projecting what they thought there.

862
00:48:56,560 --> 00:48:58,160
Speaker 1: You know, they thought it was gonna be COVID coit

863
00:48:58,239 --> 00:49:01,160
Speaker 1: as fast, you know, and it was like, I better

864
00:49:01,160 --> 00:49:05,719
Speaker 1: get nine thousand condoms because trust me, I haven't examined

865
00:49:05,719 --> 00:49:08,480
Speaker 1: the existential damage that's being done by this. But one

866
00:49:08,520 --> 00:49:10,520
Speaker 1: thing I know, I'm in a house with someone else

867
00:49:10,560 --> 00:49:12,840
Speaker 1: that I have constual sex with. Oh that's what's happening.

868
00:49:13,040 --> 00:49:16,960
Speaker 1: Cut to worldwide global depressive states, from people who are

869
00:49:17,000 --> 00:49:20,520
Speaker 1: not horny UM and are just sort of like because

870
00:49:20,520 --> 00:49:24,200
Speaker 1: at first, so you know, we've I thought, and most

871
00:49:24,280 --> 00:49:27,320
Speaker 1: of us thought logically were like yeah, probably yeah, people

872
00:49:27,320 --> 00:49:30,479
Speaker 1: probably having more sex than indoors. But yeah, condom sales

873
00:49:30,600 --> 00:49:32,680
Speaker 1: just weigh down. Actually, like in Europe and in the

874
00:49:32,760 --> 00:49:35,560
Speaker 1: United States, And that actually makes more sense when we

875
00:49:35,600 --> 00:49:38,080
Speaker 1: now that we are living in this reality like no

876
00:49:38,080 --> 00:49:41,759
Speaker 1: one's moving around freely, uh to like socialize or date

877
00:49:41,880 --> 00:49:45,960
Speaker 1: like they used to. UM, And actually it seems like

878
00:49:46,000 --> 00:49:50,160
Speaker 1: all this confusion and chaos around us and uncertainty makes

879
00:49:50,239 --> 00:49:55,920
Speaker 1: us less horny. I don't I, I don't know. I

880
00:49:55,960 --> 00:49:58,239
Speaker 1: think it's maybe ramped up other parts of our like

881
00:49:58,960 --> 00:50:02,280
Speaker 1: libidos and like bizarre ways, maybe other than like pure

882
00:50:02,280 --> 00:50:06,040
Speaker 1: physical needs where you're like, you know, admiring the cactus,

883
00:50:06,400 --> 00:50:08,960
Speaker 1: the cacti in your yard, but you know you're like

884
00:50:09,040 --> 00:50:13,040
Speaker 1: rubbing the Mrs Butterworth bottle. Yeah, just kind of thick

885
00:50:14,000 --> 00:50:15,759
Speaker 1: like I have under my pillows so no one sees

886
00:50:17,640 --> 00:50:24,160
Speaker 1: my midnight lover. Oh yeah, I mean quarantine horny nous.

887
00:50:24,160 --> 00:50:27,359
Speaker 1: It's funny. I was I was peeking into Tinder because

888
00:50:27,360 --> 00:50:29,600
Speaker 1: I was just curious, like what's Tinder Like during the quarantine,

889
00:50:29,880 --> 00:50:32,440
Speaker 1: so many Tinder profiles I's al were like, if you're

890
00:50:32,440 --> 00:50:35,640
Speaker 1: not willing to break quarantine, don't bother swiping. Like I

891
00:50:35,680 --> 00:50:37,640
Speaker 1: do think people are still out there like getting it

892
00:50:37,680 --> 00:50:39,880
Speaker 1: in in the quarantine. They are. I mean I know

893
00:50:40,040 --> 00:50:43,640
Speaker 1: single friends who are like like working on like you know,

894
00:50:44,200 --> 00:50:46,799
Speaker 1: you thought they were working on another negotiation with like

895
00:50:46,880 --> 00:50:50,960
Speaker 1: Cuba or something like top level, high level diplomatic negotiations

896
00:50:50,960 --> 00:50:54,640
Speaker 1: in terms of like their own contact tracing what time

897
00:50:54,680 --> 00:50:57,080
Speaker 1: windows have looked like since they had interacted with other

898
00:50:57,120 --> 00:50:59,560
Speaker 1: people in what context that was. If they are then

899
00:50:59,640 --> 00:51:02,240
Speaker 1: willing to then just be it's weird. It's like forcing

900
00:51:02,320 --> 00:51:05,919
Speaker 1: some people to be like exclusive though, too, because they're like, look,

901
00:51:06,200 --> 00:51:09,040
Speaker 1: if we do this, fuck it, like you'll be the

902
00:51:09,080 --> 00:51:11,200
Speaker 1: only person whose house I go to, like I'm not

903
00:51:11,239 --> 00:51:14,040
Speaker 1: seeing anybody else. And they're like, it's it's like a

904
00:51:14,080 --> 00:51:18,839
Speaker 1: weird you know, sub sub exclusivity, sublu getting it in there. Yeah,

905
00:51:19,520 --> 00:51:22,880
Speaker 1: I've never felt more for people who have like secret families,

906
00:51:22,920 --> 00:51:25,439
Speaker 1: people who are like creeping on the side. It's gotta

907
00:51:25,440 --> 00:51:29,560
Speaker 1: be tough out there for them. I've never felt secret families.

908
00:51:29,600 --> 00:51:35,480
Speaker 1: Someone family community. It's in tad you know how many

909
00:51:35,560 --> 00:51:39,920
Speaker 1: children think their father is dead. Oh my god? You

910
00:51:39,960 --> 00:51:42,960
Speaker 1: know how many because of this? Because the secret the

911
00:51:42,960 --> 00:51:45,760
Speaker 1: man cannot dip out to see the secret family anymore,

912
00:51:46,320 --> 00:51:49,840
Speaker 1: they will have to say that he's dead. I don't know.

913
00:51:49,880 --> 00:51:52,160
Speaker 1: What else are you gonna do? I don't know what

914
00:51:52,200 --> 00:51:54,279
Speaker 1: you do or else you say? That's I don't know.

915
00:51:54,400 --> 00:51:56,600
Speaker 1: Is it easier to say, look, your dad's a scumbag

916
00:51:56,719 --> 00:51:59,480
Speaker 1: and like he's got this other family were like you know,

917
00:51:59,840 --> 00:52:02,120
Speaker 1: I don't know, or you have a secret mother. Look

918
00:52:02,200 --> 00:52:05,920
Speaker 1: it's all secret family. Uh Twitter, let us know what's how?

919
00:52:06,080 --> 00:52:09,760
Speaker 1: How are you? How are you handling this? Very curious?

920
00:52:09,920 --> 00:52:12,000
Speaker 1: All three I don't want to like tell tales out

921
00:52:12,000 --> 00:52:14,800
Speaker 1: of school. All three of us are quarantining with a

922
00:52:15,120 --> 00:52:18,840
Speaker 1: like a partner. No I am YouTube both are? I

923
00:52:18,880 --> 00:52:21,719
Speaker 1: mean I I think it's different when you're in a

924
00:52:21,840 --> 00:52:25,560
Speaker 1: like long term, like committed thing. You know. It's like

925
00:52:26,600 --> 00:52:28,040
Speaker 1: I think a lot of my friends who I see

926
00:52:28,040 --> 00:52:30,600
Speaker 1: on Instagram like making sadough starter kids, I know they

927
00:52:30,600 --> 00:52:32,319
Speaker 1: wouldn't be doing that if they had somebody in their

928
00:52:32,320 --> 00:52:33,799
Speaker 1: house they can up sex with. I guess that's what

929
00:52:33,800 --> 00:52:35,960
Speaker 1: I'm saying. That was like, that was funny because that

930
00:52:36,000 --> 00:52:39,239
Speaker 1: was like a reductor's tweet last week or something. Yes, yes, right,

931
00:52:39,480 --> 00:52:42,600
Speaker 1: it's like, yeah, are you bone appetite for cat recipe

932
00:52:42,680 --> 00:52:45,279
Speaker 1: levels of horny or do you live someone you have

933
00:52:45,360 --> 00:52:48,520
Speaker 1: consensual sex with? Right? I think yeah, I really think

934
00:52:48,520 --> 00:52:51,960
Speaker 1: that's true. But yeah. The other thing though, back to

935
00:52:52,000 --> 00:52:54,440
Speaker 1: the supply chain though, Jack, is the thing that you know,

936
00:52:55,120 --> 00:52:59,040
Speaker 1: the global condom shortage is probably going to be a

937
00:52:59,080 --> 00:53:02,440
Speaker 1: reality because Malaysia they're strict lockdown rules and they are

938
00:53:02,480 --> 00:53:07,440
Speaker 1: one of the top rubber producers and major sources of condoms. Um.

939
00:53:07,520 --> 00:53:11,080
Speaker 1: So it's like I think one of this one company, Carrits,

940
00:53:11,120 --> 00:53:14,600
Speaker 1: they make one in five condoms. Uh. They're saying like

941
00:53:14,640 --> 00:53:16,919
Speaker 1: they've had a close three of their factories and they're

942
00:53:17,000 --> 00:53:22,160
Speaker 1: probably doing two million fewer condoms than normal during this period.

943
00:53:22,239 --> 00:53:24,680
Speaker 1: So they're saying, hey, look, if you don't need to

944
00:53:24,760 --> 00:53:27,239
Speaker 1: maybe save them because that's i mean, contraception is very

945
00:53:27,280 --> 00:53:29,160
Speaker 1: important to other parts of the world where like they

946
00:53:29,160 --> 00:53:32,359
Speaker 1: don't have the same access to medical care. So that's

947
00:53:32,360 --> 00:53:36,359
Speaker 1: actually a sort of darker dimension to all of that

948
00:53:36,440 --> 00:53:38,719
Speaker 1: to say, like they're kind of being like, Okay, maybe

949
00:53:38,760 --> 00:53:41,480
Speaker 1: we also need to be really mindful of this because

950
00:53:41,520 --> 00:53:44,000
Speaker 1: of now not just the it's not the lack of hornings.

951
00:53:44,080 --> 00:53:47,960
Speaker 1: It's because we can't work work the rubber factories, right,

952
00:53:48,719 --> 00:53:51,440
Speaker 1: And you do call them rubbers. You're always calling them rubbers,

953
00:53:51,880 --> 00:53:58,560
Speaker 1: call them rubbers. I think that's what I think I've

954
00:53:58,560 --> 00:54:01,360
Speaker 1: ever called it. I don't think i've called it. What

955
00:54:01,400 --> 00:54:03,440
Speaker 1: if I ever called it? I think condom. I don't

956
00:54:03,480 --> 00:54:11,040
Speaker 1: think I've ever used a Jimmy. Yeah, Jimmy calls him

957
00:54:11,719 --> 00:54:15,600
Speaker 1: Jimmy's was like a thing for a month in the

958
00:54:15,680 --> 00:54:19,480
Speaker 1: early nineties, but I feel like the Jimmy capp was

959
00:54:19,520 --> 00:54:25,000
Speaker 1: definitely nineties. Rap gave his Jimmy caps, but sex tried

960
00:54:25,080 --> 00:54:28,560
Speaker 1: to make that a thing. Yeah, I was like, hey girl,

961
00:54:28,840 --> 00:54:30,040
Speaker 1: I need to go to the store to get one

962
00:54:30,040 --> 00:54:34,239
Speaker 1: of those Lisa left Eye Lopez eye patches real quick. Yeah, Honestly,

963
00:54:34,520 --> 00:54:37,560
Speaker 1: like kudos to Lisa left Lopez for like rocking the

964
00:54:37,600 --> 00:54:39,680
Speaker 1: condom over her eye and like teaching us all about

965
00:54:39,719 --> 00:54:42,560
Speaker 1: like you know, safe sex, like talking about it. Honestly.

966
00:54:43,239 --> 00:54:46,399
Speaker 1: My uncle used to be the director of Soul Train

967
00:54:46,520 --> 00:54:48,480
Speaker 1: or like the A d On Soul Train, and I

968
00:54:48,520 --> 00:54:51,040
Speaker 1: would go as a kid, like whenever there were artists

969
00:54:51,080 --> 00:54:52,800
Speaker 1: that I was wanted to see, and I saw TLC

970
00:54:53,000 --> 00:54:56,080
Speaker 1: in that era, and I remember that was another uncomfortable

971
00:54:56,080 --> 00:54:58,080
Speaker 1: conversation my dad had to have with me because she

972
00:54:58,239 --> 00:55:01,480
Speaker 1: had this was a condom eyepatch phase of Lisa Left

973
00:55:01,520 --> 00:55:03,640
Speaker 1: I Lopez, and he just said it was like he

974
00:55:03,760 --> 00:55:06,759
Speaker 1: just was very dismissive of what it was about. But

975
00:55:06,880 --> 00:55:10,759
Speaker 1: later on, after the one AIDS walk, he told me

976
00:55:10,760 --> 00:55:13,719
Speaker 1: what a condom was, just personally just let you in

977
00:55:13,760 --> 00:55:18,920
Speaker 1: on my mental history of don't kind of knowledge. I'm

978
00:55:18,960 --> 00:55:21,560
Speaker 1: glad you. I'm glad you figured it out eventually. Yeah.

979
00:55:21,680 --> 00:55:24,160
Speaker 1: I took a handful because they were free at the

980
00:55:24,200 --> 00:55:26,600
Speaker 1: AIDS Walk, and my dad like saw what I had,

981
00:55:26,600 --> 00:55:29,239
Speaker 1: you know, because like those things like swag bags. He's like,

982
00:55:29,239 --> 00:55:31,360
Speaker 1: what's your kid? And I'm like, I'm all these condoms.

983
00:55:31,400 --> 00:55:32,960
Speaker 1: He's like, what the funk are you doing with these?

984
00:55:32,960 --> 00:55:35,400
Speaker 1: I'm like, I don't know. They're free and you're six,

985
00:55:35,440 --> 00:55:39,279
Speaker 1: you grab whatever is free. Uh, but you know you

986
00:55:39,400 --> 00:55:41,680
Speaker 1: still got him to this day, right, still got him

987
00:55:41,719 --> 00:55:48,680
Speaker 1: to this day. Alright, speaking of things to do instead

988
00:55:48,680 --> 00:55:52,840
Speaker 1: of have sex, Uh, it's time to choose our rewatch

989
00:55:52,960 --> 00:55:57,840
Speaker 1: movie for the weekend. Yeah. I put together a list

990
00:55:58,120 --> 00:56:00,560
Speaker 1: of movies that are available on netflo X. I just

991
00:56:00,640 --> 00:56:04,800
Speaker 1: kind of went through the top Metacritic ones, uh because

992
00:56:04,840 --> 00:56:07,480
Speaker 1: they because they allow you to swort by what's on Netflix,

993
00:56:07,560 --> 00:56:11,719
Speaker 1: what's on Prime Snow. Piercer is on Netflix. That's a

994
00:56:12,120 --> 00:56:14,600
Speaker 1: I feel like that might be a decent pick. It's

995
00:56:14,600 --> 00:56:18,120
Speaker 1: a little got a little post apocalyptic is um in there,

996
00:56:18,880 --> 00:56:23,120
Speaker 1: And there's also is just so hot right now, So

997
00:56:23,960 --> 00:56:27,680
Speaker 1: hot right now. Yeah, So that's kind of at the

998
00:56:27,680 --> 00:56:30,360
Speaker 1: top of my list. We also have Marvel's uh The

999
00:56:30,400 --> 00:56:36,760
Speaker 1: Avengers just near the top because again apocalyptic and uh,

1000
00:56:36,920 --> 00:56:40,160
Speaker 1: everybody's seen it. I will say this on another thing

1001
00:56:40,160 --> 00:56:44,600
Speaker 1: on your list, they have bolded and under written underlined it. Uh.

1002
00:56:44,800 --> 00:56:47,360
Speaker 1: Is Her which I've only seen the first twenty minutes of.

1003
00:56:48,000 --> 00:56:50,799
Speaker 1: Oh I love that movie. It's funny. But why did

1004
00:56:50,840 --> 00:56:52,880
Speaker 1: you only see the first twenty minutes? What happened? Because

1005
00:56:52,920 --> 00:56:55,600
Speaker 1: I grew up in a house like screeners all the time,

1006
00:56:55,719 --> 00:56:58,400
Speaker 1: so a lot of movies were like watched on DVD,

1007
00:56:58,800 --> 00:57:01,759
Speaker 1: so I never had like I sometimes won't respect the

1008
00:57:01,800 --> 00:57:04,160
Speaker 1: sanctity of the running time of the film, and I'll

1009
00:57:04,160 --> 00:57:06,840
Speaker 1: start watching on be like what, oh, come outside, you

1010
00:57:06,880 --> 00:57:09,000
Speaker 1: wanta smoke a blunt? And then I pose it and

1011
00:57:09,000 --> 00:57:10,839
Speaker 1: then I forget what I'm doing. And then I haven't

1012
00:57:10,840 --> 00:57:15,560
Speaker 1: watched her. Um so yeah, but I want to because

1013
00:57:17,000 --> 00:57:18,720
Speaker 1: people always have thoughts about it. But I don't know

1014
00:57:18,720 --> 00:57:22,520
Speaker 1: if it's because it's good or whatever. But hey, I

1015
00:57:22,520 --> 00:57:26,320
Speaker 1: think it's good. It's got the disembodied voice of Scarlett Johansson,

1016
00:57:26,440 --> 00:57:28,440
Speaker 1: So if that's your thing, you might give it a shot.

1017
00:57:28,520 --> 00:57:31,480
Speaker 1: Oh yes, and you know how I love an actress

1018
00:57:31,480 --> 00:57:40,280
Speaker 1: of color Butterworth Bottle. And then I think I think

1019
00:57:40,320 --> 00:57:42,720
Speaker 1: we picked our movie. If it's got to be, I'd

1020
00:57:42,720 --> 00:57:46,120
Speaker 1: hate to pick too Asian people against each other. I know,

1021
00:57:46,200 --> 00:57:48,120
Speaker 1: you know she's gonna be playing Angela Davis. It's an

1022
00:57:48,240 --> 00:57:56,080
Speaker 1: upcoming movie ship. Alright, let's do her. Well, we'll rewatch her.

1023
00:57:56,280 --> 00:57:58,920
Speaker 1: Let's do her. Yeah, I mean, at least I know

1024
00:57:59,000 --> 00:58:01,560
Speaker 1: I'll bring fresh It's something I've not seen, so I

1025
00:58:01,600 --> 00:58:09,800
Speaker 1: may have fresher eyes. Yeah, fresh eyes. Realize fresh eyes. Okay.

1026
00:58:09,840 --> 00:58:13,000
Speaker 1: And then just in terms of I figured there are

1027
00:58:13,040 --> 00:58:17,760
Speaker 1: probably quite a few documentaries coming our way about COVID nineteen.

1028
00:58:18,560 --> 00:58:22,720
Speaker 1: And yeah, they it turns out there twenty in the

1029
00:58:22,760 --> 00:58:28,120
Speaker 1: works right now and right now like in major like

1030
00:58:28,200 --> 00:58:30,200
Speaker 1: not just like oh we we we just spoke to

1031
00:58:30,240 --> 00:58:32,680
Speaker 1: twenty people who are working around with a COVID documentary

1032
00:58:32,760 --> 00:58:36,880
Speaker 1: like no, like quimby fucking Hulu. People are like putting

1033
00:58:36,960 --> 00:58:42,240
Speaker 1: documentaries together. But I don't know. Look, I understand you

1034
00:58:42,280 --> 00:58:45,680
Speaker 1: should this, this moment should be documented. I'm not talking.

1035
00:58:45,880 --> 00:58:48,520
Speaker 1: I don't say that's not a worthy premise, But some

1036
00:58:48,600 --> 00:58:51,520
Speaker 1: of these platforms seem to be wanting to take them

1037
00:58:51,520 --> 00:58:55,720
Speaker 1: to market, like relatively quickly, to capitalize on this. And

1038
00:58:55,880 --> 00:58:59,920
Speaker 1: I don't know, I can't imagine fucking anybody like wanting

1039
00:59:00,080 --> 00:59:04,720
Speaker 1: to harm themselves more by getting more like entrenched in

1040
00:59:04,760 --> 00:59:09,240
Speaker 1: this story. I don't know. Yeah, I'm trying to imagine

1041
00:59:09,240 --> 00:59:12,200
Speaker 1: what they would look like, and I'm picturing like the

1042
00:59:12,240 --> 00:59:16,400
Speaker 1: COVID nineteen commercials with all the like stock footage, because

1043
00:59:16,920 --> 00:59:20,439
Speaker 1: like you can't really go out and do physical productions.

1044
00:59:20,600 --> 00:59:22,960
Speaker 1: I think, well, they are I think maybe these people

1045
00:59:23,000 --> 00:59:25,920
Speaker 1: are embedding themselves with them so they're like I'm not

1046
00:59:25,960 --> 00:59:27,720
Speaker 1: going anywhere. But you know, they're all different, Like some

1047
00:59:27,840 --> 00:59:30,240
Speaker 1: are talking about like I get it, like some projects

1048
00:59:30,240 --> 00:59:34,320
Speaker 1: focus on the food industry or like other nonprofit organizations,

1049
00:59:34,320 --> 00:59:37,560
Speaker 1: and I think those are Honestly, those stories are going

1050
00:59:37,600 --> 00:59:42,920
Speaker 1: to be harrowing and should be entered into the public

1051
00:59:42,960 --> 00:59:45,840
Speaker 1: record and consciousness for people to understand just what the

1052
00:59:45,920 --> 00:59:48,680
Speaker 1: actual true toll is of this kind of thing. But

1053
00:59:49,200 --> 00:59:51,320
Speaker 1: it's just weird because part of these articles are talking

1054
00:59:51,320 --> 00:59:54,360
Speaker 1: about how like Quimby is really trying to get theirs out.

1055
00:59:54,440 --> 00:59:59,920
Speaker 1: It's like, Quimby, come on now, nobody asked you already. Yeah,

1056
01:00:00,000 --> 01:00:03,240
Speaker 1: you're already hurting from stealing people's ideas on other shows. Yeah.

1057
01:00:04,000 --> 01:00:07,160
Speaker 1: By the way, ABC News does a pretty good roundup

1058
01:00:07,200 --> 01:00:10,360
Speaker 1: of everything happening in COVID nineteen and they are the

1059
01:00:10,440 --> 01:00:16,120
Speaker 1: number one TV show every day basically on all cable

1060
01:00:16,200 --> 01:00:19,560
Speaker 1: and network news. People are really tune into ABC. And

1061
01:00:19,600 --> 01:00:24,360
Speaker 1: also David Muir, the anchor f fellow doesn't know what

1062
01:00:24,440 --> 01:00:27,560
Speaker 1: to do with his hands king, So, uh, I see,

1063
01:00:28,360 --> 01:00:30,640
Speaker 1: is that something you picked up at ABC News because

1064
01:00:30,680 --> 01:00:32,880
Speaker 1: you famously also worked at ABC. No, I did work

1065
01:00:32,920 --> 01:00:35,920
Speaker 1: at ABC News when I was in my early twenties,

1066
01:00:36,280 --> 01:00:40,920
Speaker 1: and maybe maybe it was all just uh yeah, it's

1067
01:00:40,960 --> 01:00:45,800
Speaker 1: all really building man. Yeah. Uh, Bridget, it's been so

1068
01:00:45,880 --> 01:00:50,760
Speaker 1: wonderful having you as always. Um where can people find

1069
01:00:50,840 --> 01:00:54,960
Speaker 1: you and follow you? You can find me on Twitter

1070
01:00:55,240 --> 01:00:57,920
Speaker 1: at Bridget Marie. You can find me on Instagram at

1071
01:00:57,920 --> 01:01:00,400
Speaker 1: Bridget Marie in d C. And you can out from

1072
01:01:00,400 --> 01:01:03,080
Speaker 1: my new I Heart Media podcast coming out on July seven,

1073
01:01:03,160 --> 01:01:05,640
Speaker 1: called there are No Girls on the Internet, So hit

1074
01:01:05,680 --> 01:01:07,120
Speaker 1: me up in any of those places and I would

1075
01:01:07,120 --> 01:01:10,200
Speaker 1: love to keep talking. Uh. And is there a tweet

1076
01:01:10,280 --> 01:01:14,720
Speaker 1: or some other work of social media you've been enjoying? Yes?

1077
01:01:14,840 --> 01:01:18,880
Speaker 1: And I actually have two tweets, if that's okay. So

1078
01:01:18,920 --> 01:01:20,560
Speaker 1: the first tweet that I found that I loved is

1079
01:01:20,640 --> 01:01:24,880
Speaker 1: by Dave underscore Horowitz. Uh. The postal Service does not

1080
01:01:24,960 --> 01:01:27,400
Speaker 1: exist to turn a profit. It exists to remind us

1081
01:01:27,400 --> 01:01:29,960
Speaker 1: that the freckles in our eyes are mirror images had

1082
01:01:30,000 --> 01:01:36,000
Speaker 1: when week is they're perfectly a line that's so, But

1083
01:01:36,080 --> 01:01:38,760
Speaker 1: that was I was gonna think it, but you know, um.

1084
01:01:38,840 --> 01:01:41,120
Speaker 1: And then another tweet. Um. It was one of those

1085
01:01:41,120 --> 01:01:43,280
Speaker 1: tweets going around where you're meant to quote tweet it

1086
01:01:43,280 --> 01:01:45,560
Speaker 1: with your response, and it said, you know, do you

1087
01:01:45,600 --> 01:01:47,680
Speaker 1: have a teacher that impacted you and stuck with you

1088
01:01:47,720 --> 01:01:50,360
Speaker 1: and changed your life? And I was really thrilled to

1089
01:01:50,360 --> 01:01:52,840
Speaker 1: see that. I gotta shout out a former student in

1090
01:01:52,880 --> 01:01:55,320
Speaker 1: mine from when I taught at Howard University. She quote

1091
01:01:55,320 --> 01:01:57,880
Speaker 1: tweeted that and said yes, she gave me a being

1092
01:01:57,920 --> 01:01:59,960
Speaker 1: a ruin to my four point oh and tagged me

1093
01:02:00,440 --> 01:02:04,120
Speaker 1: so shout out to my former student Phoenix, thank you

1094
01:02:04,160 --> 01:02:06,000
Speaker 1: for calling me out for giving you a bee like

1095
01:02:06,080 --> 01:02:10,440
Speaker 1: nine years ago. There you go. Hey, hey, you respect

1096
01:02:10,440 --> 01:02:13,440
Speaker 1: to age long beef, though I do for coming full circle.

1097
01:02:13,480 --> 01:02:16,640
Speaker 1: I respect, I respect a long held beef. You perfume

1098
01:02:16,640 --> 01:02:22,280
Speaker 1: you love a nice, dry, aged beef. It's true, Miles,

1099
01:02:22,280 --> 01:02:24,959
Speaker 1: we can people find you. And what's a tweet you've

1100
01:02:25,000 --> 01:02:28,120
Speaker 1: been enjoying? Okay? I like so many tweets. One thing

1101
01:02:28,160 --> 01:02:29,840
Speaker 1: I just do want to shout out is if you

1102
01:02:29,880 --> 01:02:33,640
Speaker 1: haven't if you liked the Fresh Prince. Uh, there's there's

1103
01:02:33,640 --> 01:02:35,840
Speaker 1: a video that someone just extracted the part where the

1104
01:02:35,960 --> 01:02:37,959
Speaker 1: entire cash is. Look, you had a montage of James

1105
01:02:38,040 --> 01:02:40,560
Speaker 1: Avery a gay uncle phil um and it will make

1106
01:02:40,560 --> 01:02:45,120
Speaker 1: you cry Okay if you needed to cry even harder. Um.

1107
01:02:45,160 --> 01:02:48,040
Speaker 1: A few tweets that I like, Oh man, this is

1108
01:02:48,440 --> 01:02:51,960
Speaker 1: I can't I just can't pick just one. Um. This

1109
01:02:52,040 --> 01:02:55,000
Speaker 1: is from at Okay Claire. She just said fuck, I

1110
01:02:55,040 --> 01:02:57,600
Speaker 1: just sexted someone realistically, And it's a screen grab of

1111
01:02:57,640 --> 01:02:59,640
Speaker 1: her text threat. It says the person on the other

1112
01:02:59,640 --> 01:03:02,920
Speaker 1: side that want to sex she says, Okay, okay, you start.

1113
01:03:03,400 --> 01:03:05,640
Speaker 1: I touch your penis with my hand while we kiss.

1114
01:03:05,760 --> 01:03:07,960
Speaker 1: After a little bit, I let my hand go limp

1115
01:03:08,040 --> 01:03:11,600
Speaker 1: because my wrist is tired. I start worrying about carpal tunnel.

1116
01:03:11,920 --> 01:03:21,840
Speaker 1: I will not come what. Another one this is from

1117
01:03:22,480 --> 01:03:25,520
Speaker 1: z z z Ac twenty two. How old were you

1118
01:03:25,560 --> 01:03:28,160
Speaker 1: when the guitar hero crowd booed at you for trying

1119
01:03:28,200 --> 01:03:35,560
Speaker 1: your best? Um? Oh my goodness, oh my goodness. Another

1120
01:03:35,600 --> 01:03:40,840
Speaker 1: one is from uh. This is from Germaine Lucier. It says,

1121
01:03:40,880 --> 01:03:42,680
Speaker 1: here's the real thing I just found in my parents

1122
01:03:42,800 --> 01:03:45,080
Speaker 1: house that I must have got in the junket swag

1123
01:03:45,160 --> 01:03:48,520
Speaker 1: bag and even then been so fascinated I kept it.

1124
01:03:48,760 --> 01:03:51,600
Speaker 1: Now she's talking about press junkets that happened for like

1125
01:03:51,640 --> 01:03:55,360
Speaker 1: films and things like that. And this promotional item is

1126
01:03:55,400 --> 01:03:57,200
Speaker 1: going to shock you too, core when I showed it

1127
01:03:57,200 --> 01:04:00,560
Speaker 1: to you. It is a soul patch from um, the

1128
01:04:00,640 --> 01:04:06,520
Speaker 1: movie Swordfish. And it is a Swordfish soul patch. Up.

1129
01:04:11,800 --> 01:04:16,000
Speaker 1: Can't be real, man, that cannot be real. It looks

1130
01:04:16,040 --> 01:04:19,800
Speaker 1: like some some really bone headed idea that someone would

1131
01:04:19,800 --> 01:04:22,840
Speaker 1: have a lastly, okay, when you said soul patch, I

1132
01:04:22,840 --> 01:04:26,640
Speaker 1: immediately was like it can't be swordfish because John Travolta

1133
01:04:26,720 --> 01:04:28,959
Speaker 1: sul patch in that movie is one of the all

1134
01:04:29,040 --> 01:04:34,920
Speaker 1: time bed works of facial hair, the Balta Swordfish patch.

1135
01:04:35,040 --> 01:04:38,680
Speaker 1: And then finally, this is from Dave Mitsoni who says

1136
01:04:38,760 --> 01:04:43,160
Speaker 1: offering Brittany burns down her gym as today's disassociation portal.

1137
01:04:43,160 --> 01:04:44,960
Speaker 1: I don't know if you've seen this clip where Britney

1138
01:04:44,960 --> 01:04:48,320
Speaker 1: Spears talks about how her jim burned down, but again,

1139
01:04:48,800 --> 01:04:53,120
Speaker 1: a fantastic way to describe it, a disassociation portal, Hi, guys,

1140
01:04:53,160 --> 01:04:54,600
Speaker 1: And in my gym right now, I haven't been in

1141
01:04:54,640 --> 01:04:57,280
Speaker 1: here for like six months because I burned my gym down.

1142
01:04:57,400 --> 01:05:02,040
Speaker 1: Unfortunately I had to candle and yeah, one thing led

1143
01:05:02,080 --> 01:05:09,680
Speaker 1: to another and I burned it down one another and yeah, yeah.

1144
01:05:10,080 --> 01:05:12,360
Speaker 1: It seemed like she was also like explaining it to

1145
01:05:12,400 --> 01:05:14,760
Speaker 1: a parent nervously, like, you know, and I burned it down.

1146
01:05:14,800 --> 01:05:16,320
Speaker 1: I don't know, mom, Like I had the candles here

1147
01:05:16,320 --> 01:05:17,960
Speaker 1: and like one thing they led to another, you know,

1148
01:05:18,080 --> 01:05:21,200
Speaker 1: burn it down. Sorry, I hope nothing actually tragic happened there.

1149
01:05:21,240 --> 01:05:24,520
Speaker 1: But I'll praise be to comrade Britty. Thank you. Those

1150
01:05:24,520 --> 01:05:27,560
Speaker 1: are my tweets for an day, all right. Uh, some

1151
01:05:27,560 --> 01:05:33,480
Speaker 1: tweets I've been enjoying a breal at Saddical tweeted one

1152
01:05:33,480 --> 01:05:35,800
Speaker 1: of the prettiest colors to exist is that of the

1153
01:05:35,840 --> 01:05:39,640
Speaker 1: Baja blast from Taco bell Uh and that is true,

1154
01:05:40,400 --> 01:05:44,800
Speaker 1: Um and caring till Gareth tweeted The tower of things

1155
01:05:44,840 --> 01:05:47,640
Speaker 1: I've stacked under my laptop to get a decent zoom

1156
01:05:47,680 --> 01:05:51,440
Speaker 1: angle is Borderline caps for sale. I don't know if

1157
01:05:51,480 --> 01:05:55,600
Speaker 1: you guys know that book, but that crashed me. Um.

1158
01:05:56,080 --> 01:05:58,840
Speaker 1: You can find me on Twitter at Jack Underscore O'Brien.

1159
01:05:58,920 --> 01:06:01,160
Speaker 1: You can find us on Twitter at daily zey Geys

1160
01:06:01,200 --> 01:06:03,440
Speaker 1: for at the Daily Zeygeist on Instagram. We have a

1161
01:06:03,440 --> 01:06:07,360
Speaker 1: Facebook fan page and a website, Daily Zeitgeis dot com

1162
01:06:07,360 --> 01:06:10,560
Speaker 1: where we post our episodes and our footnotes where we

1163
01:06:10,600 --> 01:06:12,360
Speaker 1: link off to the information that we talked about in

1164
01:06:12,400 --> 01:06:16,040
Speaker 1: today's episode, as well as the song we ride out

1165
01:06:16,080 --> 01:06:19,800
Speaker 1: on Miles? What are we riding out on today? This

1166
01:06:20,120 --> 01:06:24,320
Speaker 1: is a remix of an artist named Mia doy Todd

1167
01:06:24,560 --> 01:06:27,720
Speaker 1: who's a great songwriter and her mother is actually an

1168
01:06:27,760 --> 01:06:31,439
Speaker 1: accomplished Japanese American judge, so shout out to her mother.

1169
01:06:31,880 --> 01:06:34,760
Speaker 1: But this is actually a remix by Flying Lotus of

1170
01:06:34,800 --> 01:06:37,640
Speaker 1: her song called My Room is White, um, and it's

1171
01:06:37,800 --> 01:06:41,640
Speaker 1: really really dope remix of a great song and her

1172
01:06:41,720 --> 01:06:44,560
Speaker 1: vocals are great. But you know, Flo had took to

1173
01:06:44,720 --> 01:06:50,080
Speaker 1: shout out to another San Fernando Valley great love Flying limits.

1174
01:06:50,120 --> 01:06:52,480
Speaker 1: All right, Well, the Daily Zeitgeis is the production of

1175
01:06:52,520 --> 01:06:55,040
Speaker 1: my Heart Radio. For more podcast from my Heart Radio,

1176
01:06:55,160 --> 01:06:58,480
Speaker 1: visit the I Heart Radio app, Apple podcast wherever you

1177
01:06:58,520 --> 01:07:01,280
Speaker 1: listen to your favorite show, that is going to do

1178
01:07:01,320 --> 01:07:03,560
Speaker 1: it for this morning. We'll be back this afternoon to

1179
01:07:03,600 --> 01:07:06,240
Speaker 1: tell you what's trending. I hope you guys are well.

1180
01:07:06,600 --> 01:07:42,040
Speaker 1: Talk to that Bite Bite