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Speaker 1: Hello the Internet, and welcome to season two sixty, episode

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Speaker 1: four of dir Days Day production of My Heart Radio.

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Speaker 1: This is a podcast where we take a deep dive

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Speaker 1: into America's sharing consciousness. And it's Thursday, October two? What

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Speaker 1: does that mean? Miles? National Civics Day? National? Wow? We

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Speaker 1: could really do with that National Civics Day, considering most

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Speaker 1: people have no idea how anything works in our country.

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Speaker 1: National Black Cat Day, shout out to my black cat

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Speaker 1: and also a national American peroda. Yeah, man, people don't

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Speaker 1: even talk. The thing is, they don't. People don't adopt

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Speaker 1: black cats out of superstition, and I think in general,

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Speaker 1: like like just literally anti blackness, like the black I

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Speaker 1: don't know about the black cat and what it evokes

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Speaker 1: in whatever culture I was raised in. But yeah, one

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Speaker 1: the only reason I have to like a black cat anyway,

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Speaker 1: I have two cats because when we went to adopt

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Speaker 1: a cat, they were like, this is a bonded there,

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Speaker 1: and then we were like, well, we can't split them up.

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Speaker 1: So that it turns out it's actually just as easy

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Speaker 1: having two cats at least some money. So the black

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Speaker 1: cats start feeling themselves like more and more as Halloween approaches. Oh, yeah. Yeah.

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Speaker 1: When Black Panther came out, she was feeling it. I

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Speaker 1: was like, you don't get big time for black just building,

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Speaker 1: don't don't do anything. Well, my name is Jack O'Brien

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Speaker 1: a K. I hopped off the plane at l A

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Speaker 1: X with a dream in my card again clog them

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Speaker 1: to the land up fame XS. Whoa am I gonna

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Speaker 1: fit in? Jumped in the cab here I am for

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Speaker 1: the first time. Look to my right and I see

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Speaker 1: the Hollywood sign. This is also crazy. Everybody's tearing at

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Speaker 1: their insides. My thighs are literate and my hands sound

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Speaker 1: like citris. Mrs Mrs Kenter thanks me for eating her son.

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Speaker 1: Then my friend turned on the lights and put the

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Speaker 1: tell a Tubbies on. Put the tell a Tubbies on,

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Speaker 1: put the tell a Tubbies on. So I put my

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Speaker 1: hands up there playing my show the Butterflies Fly Away.

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Speaker 1: Oh yeah, moving my hips like yeah, I got my

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Speaker 1: hands up there playing my show. Some what babies saved

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Speaker 1: my life today? Yeah, yeah, yeah, yeah, Jack O'Brien's gonna

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Speaker 1: be okay. That is courtesy of Mr lex Lugie, Mr Lugubrious,

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Speaker 1: in reference to my theory that Teletubby's seems so trippy

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Speaker 1: because baby mind and tripping mind are the same. But yeah,

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Speaker 1: I appreciate. I appreciate that it just opened with the straight,

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Speaker 1: straightforward lyrics of that song for a little while because

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Speaker 1: I like to look at the look and Miles his

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Speaker 1: eyes when he's like, is he just going to sing

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Speaker 1: the fucking party in the US, And I'm like, he's going.

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Speaker 1: He's floating, y'all, He's floating. Anyways, I'm thrilled to be

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Speaker 1: joined as always by my co host Mr Miles Mr

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Speaker 1: Miles Gray, who loves limp fries a K. I wish

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Speaker 1: it was a little bit softer. I wish it was

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Speaker 1: a dollar. I wish I had a fry who would

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Speaker 1: limp I would call? Or I wish I had rabbit

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Speaker 1: in a fat in a vat with a Merlo and hollow. Okay, look,

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Speaker 1: I'm yeah. I mean I don't drink a lot of Merlo,

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Speaker 1: but you know, shout off, shout out hollow. You know,

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Speaker 1: love the little braided bread. But I definitely like a

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Speaker 1: limp fry, shout out LOCKERNI on the discord. Oh and also,

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Speaker 1: who was it? Somebody on Twitter hit me up and

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Speaker 1: went to, uh, what was it? Dicks in Seattle. Was like, hey,

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Speaker 1: I got the fries, and I was like, you're looking good,

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Speaker 1: looking good. That was Scott. Shout out Scott, I see

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Speaker 1: nice and soft that fries Dicks driving in in in Seattle. Perfect, perfect,

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Speaker 1: not a little they got a little, a little bit

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Speaker 1: of external crunch, but inside soft, mashed, softer than Drake

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Speaker 1: Mashy potades. Well, Miles, we are thrilled to be joined

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Speaker 1: in our third de seat by a brilliant and talented

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Speaker 1: podcaster who you know from Invisible and her spinoff fashion

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Speaker 1: podcast Articles of Interest, which just dropped the first episode

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Speaker 1: of season two. It's Avery Truffle. Maybe I wish I

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Speaker 1: had I don't have a song. I wish these were

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Speaker 1: so impressive. I like, I like just really humiliating myself

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Speaker 1: when we have an esteemed guest on so that this

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Speaker 1: lined up perfectly with just a long song. I just

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Speaker 1: have to say, Myles, I feel like what you really

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Speaker 1: like is poutine, like what you were describing, ushy fry

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Speaker 1: like with the I was like that, oh yeah, yeah,

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Speaker 1: cusp putine exactly and see. But the thing is with poutine,

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Speaker 1: it's the gravy that that brings it to the soggys.

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Speaker 1: It's like I like when they come out the fryer, Like,

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Speaker 1: I'm like, wow, you did that, you did that with

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Speaker 1: the soft fry. But again, it's a very divisive. That's

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Speaker 1: a that's an important dividing line. Yes, yes, a lot

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Speaker 1: of even past guest Karama Donqua was tweeting me, She's like,

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Speaker 1: what is wrong with you? M yeah, I mean look,

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Speaker 1: I saw the download numbers. I saw my follower account drop.

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Speaker 1: I get it. You know, Stamper cut our listenership was

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Speaker 1: cutting half for some I know. I'm just talking about

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Speaker 1: fried potato sticks. All right, Avery, We're gonna get to

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Speaker 1: know you a little bit better in a moment. First,

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Speaker 1: we're gonna tell our listeners a couple of the things

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Speaker 1: that we're talking about today. We're gonna talk about student

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Speaker 1: performance scores are down, which is to be expected, and

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Speaker 1: I think it's we we all can agree right that

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Speaker 1: the reason is teachers unions. Thank you. So we'll talk

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Speaker 1: about that. We might check in with why police are

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Speaker 1: a bad idea. Maybe we are going to talk about

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Speaker 1: your podcast and your men's wear your Suits episode. Avery

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Speaker 1: spreads a toura, but then how that kind of ties

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Speaker 1: into sneaker culture. Oh yeah, curious to hear your thoughts

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Speaker 1: on that, and then your new season which is all

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Speaker 1: about preppy or I guess not ivy culture. Yeah, it's

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Speaker 1: like it's a whole discussion if preppy and ivy are

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Speaker 1: the same thing and if anyone even uses either of

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Speaker 1: those words anymore. But we'll get into it. Yeah, just

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Speaker 1: a c slater and say by the bell I think yeah, yeah.

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Speaker 1: And my sister called used it like when she you know,

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Speaker 1: she was into like she wore cross colors and was like,

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Speaker 1: taught me very early on. She was like, you look

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Speaker 1: like a prep Yeah. Yeah. I was like, well, that's

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Speaker 1: I will not allow that. I will just because I

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Speaker 1: have this flannel with my fleece vest. I did have

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Speaker 1: my hair like parted to this, I looked like one

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Speaker 1: of the bad guys from Caddyshack. Incredible reference exactly all

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Speaker 1: that plenty more. But first, Avery, we like to ask

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

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Speaker 1: last night I was researching the humors, you know, humorism.

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Speaker 1: It was like this, yeah, like this uh theory of

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Speaker 1: how health worked before germ theory because a friend of

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Speaker 1: mine gave blood and then she was like I suddenly

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Speaker 1: felt so much better. I was like, whoa, that's we

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Speaker 1: It's like blood letting used to be the way that

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Speaker 1: that doctors cured everything. And I was like, oh, what's

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Speaker 1: that called again? Oh, it's called humorism. And it's like

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Speaker 1: you have these four You've like phlegm and two kinds

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Speaker 1: of bile and blood, and they all need to be imbalanced.

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Speaker 1: And so it was like a totally like flat earth

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Speaker 1: are kind of thing. I was like, maybe humorism is real,

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Speaker 1: just like looking into the history of of humorism and

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Speaker 1: trying to remember what that was all about. But it

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Speaker 1: is kind of fascinating. It's like a superstitious form of

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Speaker 1: medicine that you'd think would have some crazy resurgence right now. Yeah,

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Speaker 1: it did seem like at the time they thought everything

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Speaker 1: was caused by there being too much blood in your body.

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Speaker 1: They're just like, you're too plunged to listen. Maybe there's

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Speaker 1: something to it. Yeah, But then we went all the

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Speaker 1: way in the other direction and nothing, No bad things

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Speaker 1: are caused by that. Maybe maybe we need to take

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Speaker 1: another look. It also strikes me as very unprofitable, like that,

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Speaker 1: like that form of medicine is it gonna make anyone money,

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Speaker 1: so I could all say, what do I take doc

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Speaker 1: let a little bit? Yeah, yeah, yea. I guess they're

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Speaker 1: the safe way to do it. That's the other humors

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Speaker 1: that are that are trickier though, with like the flegm

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Speaker 1: in the bile, Like what do you do with those?

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Speaker 1: I don't know. I just found myself very curious about

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Speaker 1: the four four humors. Yeah, this like when I Google

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Speaker 1: do the Google image search of the quadrants, I'm like,

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Speaker 1: I'm just looking at this and being like that was

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Speaker 1: explaining health. It's metal as hell. It's so you'd think

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Speaker 1: it would be like, oh hey, I'm like an I

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Speaker 1: n F J and I'm phlegmatic like one of those

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Speaker 1: like New Age revivals right now. Exactly. It's like you

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Speaker 1: have an overrepresentation representation of fire and earth with what right? Yeah,

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Speaker 1: I mean it was a time when surgeon and barber

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Speaker 1: were the same job. It was just a person person

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Speaker 1: who had sharp things at their in the room that

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Speaker 1: they worked in and not afraid to use them. Yeah,

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Speaker 1: what is something you think is overrated? Okay, here's here's

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Speaker 1: my my hot take. Like the Daily the podcast, I

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Speaker 1: love it as a as a as a show. It's great,

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Speaker 1: but I recently went out of the country for the

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Speaker 1: first time since uh COVID, and I was like, oh right,

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Speaker 1: I only listened to the daily all the time, and

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Speaker 1: so much of that news was like really American, not exclusively,

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Speaker 1: but like very very American. And then suddenly when I

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Speaker 1: was in Europe, everyone was so aware of so much

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Speaker 1: international news. I was like, man, I gotta I gotta

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Speaker 1: branch out. This is like it's a great resource, but

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Speaker 1: it is not enough daily newscasts. But wait, what there's

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Speaker 1: glaciers in Pakistan that are Michael Abenadi. He's going to jail.

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Speaker 1: He was Stormy Daniel's lawyer. We really need to be

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Speaker 1: worried about. Yeah, I think that that just goes for

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Speaker 1: podcasts with the word daily in in the title. In general,

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Speaker 1: I mean, you know, not not all, not all not

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Speaker 1: I mean, well will occasionally swing the focus to international things,

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Speaker 1: but it's it's a delicate balance of trying to be

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Speaker 1: we're such a big country, you know, and then you

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Speaker 1: also have to be aware of like everything going on

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Speaker 1: in this country. You can't be too I mean it's

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Speaker 1: like I can either talk about we can talk about

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Speaker 1: what's going on with Giselle and Tom Brady, or we

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Speaker 1: can talk about Union. I don't know what's the b

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Speaker 1: I don't know how you do it. I don't know.

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Speaker 1: I'm in awe. I don't know how when in doubt,

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Speaker 1: choose Tom Brady. That's always. That's the shorthand for a

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Speaker 1: culture com terrific. Isn't me like friends with the Santis

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Speaker 1: now or something like they're no friends? Yeah, like they

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Speaker 1: they're they're buddies. They text. Everyone's a milkshake duck. I

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Speaker 1: hate it? Yeah? What is uh? What something you think

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Speaker 1: is underrated? Well? Then this is the part two is

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Speaker 1: like the BBC. After being abroad and being like, wow,

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Speaker 1: I don't know anything about what's going on in the world.

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Speaker 1: I have supplemented my daily American podcast with the BBC.

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Speaker 1: It's like, oh right, this is actually a really great way,

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Speaker 1: even though they just ended their Arab service, which is

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Speaker 1: which is sad, but otherwise it's like a relatively good

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Speaker 1: way to get an idea of what's going on in

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Speaker 1: the world. So I love the BBC Global News and

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Speaker 1: kind of calming the accidents, are calming the accident? Do

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Speaker 1: they have a good podcast? The BBC? Oh my god,

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Speaker 1: the BBC Global News is actually incredible. They update it frequently,

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Speaker 1: like multiple times a day, from all over, just because

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Speaker 1: they're so sprawling and massive, and they have journalists everywhere

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Speaker 1: and they're just filing all these reports all the time.

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Speaker 1: It's it's great. We update multiple times a day and

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Speaker 1: we don't have journalists anywhere. It's so impressive. Underrated all

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Speaker 1: all multiple updates. Underrated. All Right, I'm gonna check it out.

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Speaker 1: I haven't been listening to the Daily, but I'm gonna.

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Speaker 1: I'm gonna give the BBC Global News a shot. Well,

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Speaker 1: we'll see, we'll see what this bb what whether there's

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Speaker 1: anything to this. BBC heard of them before, right, I

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Speaker 1: discovered the British bar Broadcasting Service goes to Europe once.

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Speaker 1: Have you heard about b c C? I think not. No, no,

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Speaker 1: that female thing, it's brands. Let's take a quick break.

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Speaker 1: We'll be right back. And we're back, and we're starting

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Speaker 1: to get some scores in the National Assessment of Educational

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Speaker 1: Progress dropped their performance review of ever educational system and

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Speaker 1: it's the first one since the pandemic, and the results

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Speaker 1: are not great. No, nope, nope, nope, uh pretty pretty

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Speaker 1: pretty big drops. They said the survey of fourth and

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Speaker 1: eighth graders found that math scores fell in nearly every state.

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Speaker 1: No state showed significant improvements in reading, and the lowest

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Speaker 1: performing students saw the largest declines in achievement. And there's

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Speaker 1: a lot of takes flying out there from it wasn't

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Speaker 1: really that bad that they these kids the scores dropped too.

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Speaker 1: We need to We need the teachers unions to be

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Speaker 1: absolutely obliterated because they had way too much influence in

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Speaker 1: doing this and they were wrong. They're not scientists, bus,

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Speaker 1: but it is clear the performance went down, and many

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Speaker 1: studies show this consistently, and sadly, it also shows that

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Speaker 1: the lower income areas were the hardest hit again, which

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Speaker 1: just causes more concern for increased inequality down the road,

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Speaker 1: because these are like all years for someone's education, especially

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Speaker 1: in like subjects like math and things like that. This

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Speaker 1: this is from this Atlantic article. They also said the

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Speaker 1: districts with fully remote instructions saw declines and test scores

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Speaker 1: up to three times greater than districts that had in

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Speaker 1: person instruction for the majority of the school year. When

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Speaker 1: the declines again were particularly start for lower achieving the

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Speaker 1: minority students. Yeah, I mean that My experience was online school,

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Speaker 1: and my kids are much younger than fourth to eighth grade.

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Speaker 1: But it you know, if I were working in a

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Speaker 1: job where I was not able to like be there

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Speaker 1: with like like have one eye on what they were

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Speaker 1: doing like that, it would have been absolutely impossible. And

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Speaker 1: I think doubly so when if they were at an

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Speaker 1: age where they don't believe everything I tell them, Like

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Speaker 1: you know, like what once you get to fourth to

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Speaker 1: eighth grade, like they're like, yeah, okay, like they're doing

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Speaker 1: what they think they need to to get away with

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Speaker 1: lying or at least that I'll speak for myself from

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Speaker 1: from fourth to eighth grade, I'm just doing what I

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Speaker 1: think I can get. That was Maggiavelli up in that,

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Speaker 1: so like, of course, of course, I mean, you know,

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Speaker 1: I think around the world. You know, we saw a

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Speaker 1: lot of countries kept their schools open, and we're pointing

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Speaker 1: to things that, like the studies were showing kids weren't

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Speaker 1: necessarily the biggest threat vector in terms of transmission, and

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Speaker 1: kids weren't getting as seriously ill as adults. And you know,

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Speaker 1: many of the critics of the closures like point to

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Speaker 1: this and like or like, but look, every every other

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Speaker 1: place saw like they knew that it was low and

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Speaker 1: we still had to keep the schools closed. But school

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Speaker 1: closures were mostly welcomed by parents, like it wasn't a

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Speaker 1: huge like the like a lot of polling showed that

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Speaker 1: this wasn't as divisive as an issue as it as

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Speaker 1: it was, although many parents were talking about, like the

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Speaker 1: how difficult it would be to manage remote learning and

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Speaker 1: working remotely during the pandemic, But I don't know, like

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Speaker 1: the other thing that they also point to is especially

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Speaker 1: like low income and minority parents were at a much

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Speaker 1: higher rate excepting of school closure and waiting for absolute

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Speaker 1: safety before putting their kids in school because I think

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Speaker 1: just in general, I think they were seeing firsthand how

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Speaker 1: much more like how brutal COVID can be while trying

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Speaker 1: to earn a living in a dangerous setting. So you know,

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Speaker 1: everyone's calculus is different. I think that the one the

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Speaker 1: one thing that should be pointed out though, is that

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Speaker 1: a lot of this isn't permanent and Mississippi students have

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Speaker 1: completely recovered in their reading scores, and in a study

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Speaker 1: in Ohio found that the current pace of recovery and

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Speaker 1: reading would pretty much eliminate the state's learning loss. Younger

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Speaker 1: elementary school kids tended to have made up ground much

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Speaker 1: quicker in the last year, but older students are recovering

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Speaker 1: a little more slowly. And again in you know, race

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Speaker 1: or family income are very also very predictive of you

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Speaker 1: know what that recovery is going to look like. Yeah,

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Speaker 1: I mean, so we're we're in the midst of like

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Speaker 1: a sprint to bounce back from this, to get the

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Speaker 1: students caught up, like with all this missed learning and

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Speaker 1: people's responses the teachers have too good, Like that's that's

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Speaker 1: how we're going to solve this is by not giving

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Speaker 1: teachers the protections they meet. It doesn't doesn't quite work

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Speaker 1: out in my brain. I also think we should all

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Speaker 1: have to take these tests because I bet we're all

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Speaker 1: like I think my math scores have also fallen since

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Speaker 1: the pandemic. I think we're all spiritually and mentally fucked

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Speaker 1: up still from the pandemic. I think it was bad

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Speaker 1: for all of us. And yeah, we were like we

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Speaker 1: we probably need to have a little bit of I

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Speaker 1: don't know, patients with ourselves. And also, yeah, I mean,

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Speaker 1: the thing that I always thought when we were talking

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Speaker 1: about this over the pandemic was like, yeah, but kids

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Speaker 1: are like way more resilient than the rest of us,

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Speaker 1: so they'll probably be okay in the long run. But yeah,

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Speaker 1: and I do feel like the mental health thing is

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Speaker 1: like the X factor. You know. My friends who are

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Speaker 1: teachers were like, I'm spending so much time, you know,

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Speaker 1: like fourth eighth grade, you're like starting to have existential crises.

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Speaker 1: You know'd be like, who am I as like some

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Speaker 1: and separate from my parents, And my teacher friends were like,

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Speaker 1: I'm spending so much of my time just like talking

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Speaker 1: to kids about how they're doing and like regulating that

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Speaker 1: because they also don't have each other and like their

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Speaker 1: parents are busy, and so yeah, I hope once they

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Speaker 1: can like regain some sense of stability, it will allow

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Speaker 1: for bounce back. But it's really sad. I mean I

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Speaker 1: think that, you know, again, it was a very complex situation,

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Speaker 1: especially in the early stages when we knew very little,

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Speaker 1: and the binaries seemed to be stay alive or go

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Speaker 1: to school, and that was basically what that was sort

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Speaker 1: of what the discussion was centered around. And I mean, yeah,

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Speaker 1: when you look at the data, it has to be

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Speaker 1: said that school closures for those extended periods may not

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Speaker 1: have been the best move, especially when you consider that

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Speaker 1: like that it was widening the gap between rich and

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Speaker 1: poor kids. But you know, rather than just going all

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Speaker 1: in and being like and this is like, you know,

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Speaker 1: this daily beast thing, this person is like. Look, when

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Speaker 1: the Republicans take power, it was like, wait, hold on

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Speaker 1: what they're like. And I'm not for sham investigations, but

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Speaker 1: they absolutely need to talk to like they need to

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Speaker 1: get the heads of the teachers unions up there to

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Speaker 1: explain what the heck is going on? Like that is

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Speaker 1: the that direction, that energy is completely misdirected, in my opinion.

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Speaker 1: But you know, I think the biggest thing, too is

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Speaker 1: rather than just comparing yourselves, like, well, look what happened

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Speaker 1: in these like in in Western Europe or this place

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Speaker 1: or this that place, the US is not like other countries.

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Speaker 1: You know, we're exceptional in some good ways and also

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Speaker 1: in some terrifying fucking ways. And you look at how

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Speaker 1: many people died and how little government seemed to care

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Speaker 1: about the preciousness of like human life. That wouldn't inspire

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Speaker 1: confidence in me as a teacher or someone having to

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Speaker 1: work in the pandemic When the message being reflected back

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Speaker 1: to me is you will die, and that's fine. And

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Speaker 1: if you die, who gives a ship like that's a

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Speaker 1: fund up that's a fund up environment to operate in.

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Speaker 1: And again, union busting is not the answer here. But

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Speaker 1: I think, like anything, right in America, we don't have

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Speaker 1: this thing where we go through something, we learned something,

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Speaker 1: and then we go back and be like, this is

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Speaker 1: what we learned and this is how it will inform

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Speaker 1: future decision making, because we just we tend to not

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Speaker 1: do that. And I think that's not a good pattern

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Speaker 1: for our country because it just undermines people's faith in

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Speaker 1: certain institutions when we can't be like, well, hey, dude,

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Speaker 1: I guess well we learned something from that fucking pandemic.

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Speaker 1: Here's what we're learning, here's what we can how we

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Speaker 1: can apply these things. But yeah, it's just hard to

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Speaker 1: find the right way to navigate a fucking pandemic when

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Speaker 1: half the country thinks keeping people safe as a genocide.

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Speaker 1: Right there, Also, is it settled science that this was

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Speaker 1: the wrong move to keep like schools closed. And I

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Speaker 1: think it's just saying when you're when you're putting it

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Speaker 1: all together that the what the what the transmission was

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Speaker 1: like in a school, and what the actual like potential

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Speaker 1: threat to the safety to the students was was. I

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Speaker 1: guess for people who want to really lean into it

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Speaker 1: feels overblown. But again, I don't think it's necessarily something

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Speaker 1: where I don't think it's it's incorrect to consider the

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Speaker 1: samety of people and making the best decision based off

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Speaker 1: of that. I think the bigger issue is we had

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Speaker 1: so much noise coming from certain parts of our economy

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Speaker 1: about going getting back to normal that it completely muddied

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Speaker 1: people's ability to actually look at the situation and then

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Speaker 1: figure out what the best way to solve that is, right,

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Speaker 1: And if you know, teachers were at risk, so I

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Speaker 1: mean teachers were dying. That teachers were dying, and like

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Speaker 1: what message like human, Like, what kind of message does

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Speaker 1: that send to young growing humans that like we're like, yeah,

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Speaker 1: but we got to keep those test scores up so

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Speaker 1: that you can compete in the global economy. Like I

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Speaker 1: don't know, like even in retrospects, like knowing that the

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Speaker 1: spread wasn't that bad with kids, it still was bad

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Speaker 1: for like kids could spread it to teachers and right,

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Speaker 1: we didn't know about transmission at all. And like parents

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Speaker 1: and yeah, totally, yeah, that's why I think, you know, again,

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Speaker 1: it's just more about seeing that other when again, other

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Speaker 1: countries are doing it, and I guess looking at those

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Speaker 1: results that people are immediately just like, well fuck and

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Speaker 1: the and the fucking scores went down. But again, I

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Speaker 1: don't think a lot of the criticisms are necessarily that genuine,

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Speaker 1: because like the underpinnings of it typically end up on

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Speaker 1: some version of like well you teachers, unions have too

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Speaker 1: much power, or like some other weird end goal which

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Speaker 1: isn't necessarily the health and safety of every person in

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Speaker 1: the country, like look what it took to business, Look

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Speaker 1: what it did that, and then like this, where this

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Speaker 1: one I bet in the Daily Beach is truly being like, well,

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Speaker 1: you know, good luck, liberals. You just gave all the

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Speaker 1: people who are like school choice advocates all the AMMO

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Speaker 1: they need. So like this, I think this study is

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Speaker 1: being weaponized in some ways, and other people are just

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Speaker 1: sort of objectively being like, yeah, the score is dipped.

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Speaker 1: They're tending to recover here. Some this was the fallout

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Speaker 1: of it. But again I think more than like what

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Speaker 1: happened here with the school closure is the biggest indictment

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Speaker 1: is more about how generally is a country we fucking

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Speaker 1: handled the pandemic and getting focused on this I think

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Speaker 1: give like sort of excuses every other failure, and maybe

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Speaker 1: you have to like have more protections in place when

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Speaker 1: you don't have a functional health care system. You know,

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Speaker 1: like maybe maybe like that the people who are have

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Speaker 1: a union looking out for them are going to be

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Speaker 1: a little bit more cautious when they know that if

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Speaker 1: they do get COVID and have to go to the hospital,

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Speaker 1: it could bankrupt them. Yeah like that that what about that? Maybe? Maybe?

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Speaker 1: So maybe what about a good argument or even to

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Speaker 1: the or even for the people who are like, well,

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Speaker 1: you know, adults are the ones that are gonna get sick, Well,

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Speaker 1: then why are the fucking bars open? Right? Yeah? Those

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Speaker 1: bounced back. If you're if you're fucking that concerned, then

425
00:23:55,280 --> 00:23:57,800
Speaker 1: like be consistent with that, you know what I mean,

426
00:23:57,920 --> 00:24:00,119
Speaker 1: Like rather than being like it's just gonna be all.

427
00:24:00,119 --> 00:24:04,840
Speaker 1: It's also why isn't Chili's open? Like calm? That doesn't

428
00:24:05,000 --> 00:24:08,920
Speaker 1: But that doesn't paint me as like a back Yeah,

429
00:24:09,280 --> 00:24:12,280
Speaker 1: it comes back to the bias against anything that's not profitable,

430
00:24:12,440 --> 00:24:15,600
Speaker 1: and schools are not profitable in the short term. And

431
00:24:15,680 --> 00:24:17,359
Speaker 1: I think that's what's kind of wild is just to

432
00:24:17,440 --> 00:24:20,560
Speaker 1: see people's response to this shows like as a country,

433
00:24:20,720 --> 00:24:24,800
Speaker 1: like we're completely losing our grip on being humane. Yes,

434
00:24:25,320 --> 00:24:28,320
Speaker 1: you know, like they're this woman was arrested in Arizona

435
00:24:28,440 --> 00:24:30,840
Speaker 1: recently because she was feeding the needy and a park

436
00:24:31,240 --> 00:24:34,119
Speaker 1: and the laws don't allow you to serve food in

437
00:24:34,240 --> 00:24:37,920
Speaker 1: a charitable nature, Like we're we're criminalizing ship like that,

438
00:24:38,119 --> 00:24:40,440
Speaker 1: and also having like these wild takes or they're like

439
00:24:40,720 --> 00:24:43,720
Speaker 1: the teachers unions have way too much power because teachers

440
00:24:43,760 --> 00:24:45,800
Speaker 1: were dying and they were looking out for their the

441
00:24:45,920 --> 00:24:49,080
Speaker 1: workers involved in this union, but just using like these

442
00:24:49,119 --> 00:24:51,680
Speaker 1: scores to sort of completely say that this is a

443
00:24:51,880 --> 00:24:54,600
Speaker 1: this is a failure and if they want better wages,

444
00:24:55,000 --> 00:24:57,320
Speaker 1: well the unions really screwed them over, because now they

445
00:24:57,359 --> 00:24:59,840
Speaker 1: look like they don't know what they're doing. Right. It

446
00:25:00,080 --> 00:25:03,359
Speaker 1: was it was a difficult situation, you know, the teachers

447
00:25:03,680 --> 00:25:07,600
Speaker 1: like we got the results we got, and it's just

448
00:25:07,720 --> 00:25:10,920
Speaker 1: America is not great at dealing with difficult situations. It

449
00:25:10,960 --> 00:25:14,200
Speaker 1: would seem at this at this point in our evolution.

450
00:25:14,560 --> 00:25:16,359
Speaker 1: Also any sort of like what it could have should

451
00:25:16,400 --> 00:25:19,360
Speaker 1: have about COVID feels ridiculous to be like, we shouldn't

452
00:25:19,400 --> 00:25:22,960
Speaker 1: have been wiping down surfaces that didn't do anything. It's like, well, okay, yeah,

453
00:25:23,080 --> 00:25:26,760
Speaker 1: we didn't know, Like and all those times they're like,

454
00:25:26,800 --> 00:25:28,920
Speaker 1: don't wear a mask, you know what I mean, we

455
00:25:29,000 --> 00:25:31,640
Speaker 1: were throwing spaghetti at the wall. We had no idea, Like, yeah,

456
00:25:31,680 --> 00:25:33,000
Speaker 1: there's a lot of things we should have done, a

457
00:25:33,080 --> 00:25:35,000
Speaker 1: lot of things we should have done differently. I don't know.

458
00:25:35,560 --> 00:25:39,320
Speaker 1: It's funny in retrospect that I was disinfecting my cheerios

459
00:25:39,400 --> 00:25:42,560
Speaker 1: boxes when I got some home from the grocery store.

460
00:25:43,680 --> 00:25:46,679
Speaker 1: But I'm I'm also like not calling for the heads

461
00:25:46,760 --> 00:25:50,040
Speaker 1: of the of the people who suggested that it could

462
00:25:50,080 --> 00:25:55,080
Speaker 1: be spread by you know, particles on cheerio boxes, because

463
00:25:55,600 --> 00:25:58,520
Speaker 1: we just didn't know, and everyone was freaking out, understandably,

464
00:25:58,920 --> 00:26:03,200
Speaker 1: and and it did kill a million people, Yes, and again,

465
00:26:03,320 --> 00:26:06,840
Speaker 1: try operating in good faith, like and what's the best

466
00:26:06,920 --> 00:26:09,440
Speaker 1: interest for your own health or your community's health. When

467
00:26:09,600 --> 00:26:12,440
Speaker 1: you live you have millions of people who would just

468
00:26:12,520 --> 00:26:15,000
Speaker 1: be like, why you wearing a mask? Why are you

469
00:26:15,119 --> 00:26:17,880
Speaker 1: doing this? Let me get in your ship, Like we're

470
00:26:18,200 --> 00:26:19,840
Speaker 1: That's what I'm saying, Like, if I think for people

471
00:26:19,880 --> 00:26:22,359
Speaker 1: who want to make a really easy comparison. It's like,

472
00:26:22,400 --> 00:26:25,680
Speaker 1: well they didn't do that in like South Korea or whatever.

473
00:26:25,800 --> 00:26:28,200
Speaker 1: It's like, we're not We're not dealing with the same ship.

474
00:26:28,640 --> 00:26:31,240
Speaker 1: Were also in South Korea, the government was like bringing

475
00:26:31,359 --> 00:26:34,119
Speaker 1: people food to be like, hey, we know you're locked up.

476
00:26:34,400 --> 00:26:36,520
Speaker 1: Here's a fucking care package because we know you have

477
00:26:36,720 --> 00:26:39,359
Speaker 1: to eat, because we understand that, as you know, just

478
00:26:39,480 --> 00:26:42,800
Speaker 1: a concept rather than our version, which is like a

479
00:26:43,000 --> 00:26:46,560
Speaker 1: salute the people who are whose only financial recourse is

480
00:26:46,640 --> 00:26:49,280
Speaker 1: to go buy groceries for people with more money. Right,

481
00:26:49,720 --> 00:26:53,320
Speaker 1: all right, let's uh, let's move on to maybe the

482
00:26:53,640 --> 00:26:59,080
Speaker 1: police are a bad fucking idea Part two, recurring segment.

483
00:26:59,160 --> 00:27:01,639
Speaker 1: We have So a couple of weeks back, the Edmonton

484
00:27:01,720 --> 00:27:04,639
Speaker 1: Police released a composite of a suspect in a twenty

485
00:27:04,760 --> 00:27:08,560
Speaker 1: nineteen sexual assault. A black man who or a black

486
00:27:08,680 --> 00:27:12,480
Speaker 1: male I will say who, judging from the image, presumably

487
00:27:12,640 --> 00:27:17,040
Speaker 1: escaped on the Polar Express because the the image they

488
00:27:17,080 --> 00:27:21,760
Speaker 1: released makes him look twelve years old. And it's not

489
00:27:21,880 --> 00:27:25,000
Speaker 1: a curse like it like you say, like Polar Express,

490
00:27:25,080 --> 00:27:27,520
Speaker 1: You're like, are are you a computer animated kid? It's

491
00:27:27,520 --> 00:27:32,200
Speaker 1: a computer animated twelve year old. What yes, and so

492
00:27:32,480 --> 00:27:36,200
Speaker 1: what they did was they used DNA phenotyping, which is

493
00:27:36,359 --> 00:27:40,199
Speaker 1: the process of predicting a physical appearance and ancestry from

494
00:27:40,359 --> 00:27:46,000
Speaker 1: unidentified DNA evidence. This is not a set There is

495
00:27:46,080 --> 00:27:49,480
Speaker 1: not a settled science around this. The cops bought the

496
00:27:49,760 --> 00:27:54,359
Speaker 1: composite from a company called parabin Nano Labs, which sounds

497
00:27:54,480 --> 00:27:58,400
Speaker 1: very official. They routinely provide this service to law enforcement,

498
00:27:58,800 --> 00:28:01,399
Speaker 1: and the Edmonton Police claim in this tactic was taken

499
00:28:01,480 --> 00:28:03,800
Speaker 1: because the public needs to get this person off the streets.

500
00:28:03,880 --> 00:28:07,680
Speaker 1: Even though they admitted that the composite was not accurate,

501
00:28:08,200 --> 00:28:12,159
Speaker 1: it turns out that's a massive understatement. Less than a

502
00:28:12,200 --> 00:28:15,879
Speaker 1: week later, the Edmonton Police issued an apology over the

503
00:28:16,000 --> 00:28:20,480
Speaker 1: use of DNA phenotyping after a massive backlash for its

504
00:28:20,680 --> 00:28:25,440
Speaker 1: broad characterization of just a black man again could be

505
00:28:25,520 --> 00:28:29,040
Speaker 1: a black child, which experts expressed concern would lead to

506
00:28:29,200 --> 00:28:32,520
Speaker 1: mass surveillance of any black man approximately five ft four.

507
00:28:33,000 --> 00:28:36,639
Speaker 1: Oh my god, d NA po typing sounds like phrenology

508
00:28:36,800 --> 00:28:41,560
Speaker 1: or something that is like arcane. That is wild, especially

509
00:28:41,600 --> 00:28:43,800
Speaker 1: a couple of that would like and this is who

510
00:28:43,880 --> 00:28:49,000
Speaker 1: did it? Face is so specific, but so it's like

511
00:28:49,040 --> 00:28:52,720
Speaker 1: a police sketch. But it's not. It's based on kind

512
00:28:52,760 --> 00:28:56,520
Speaker 1: of less than a police sketch, which already you know,

513
00:28:56,960 --> 00:29:01,240
Speaker 1: very very problematic. But one geneticist called the quote science

514
00:29:01,280 --> 00:29:05,480
Speaker 1: of extracting facial profiles from d NA quote dangerous snake oil,

515
00:29:05,800 --> 00:29:08,800
Speaker 1: while one taxpayer complaining the government is wasting money on

516
00:29:08,960 --> 00:29:16,040
Speaker 1: racist astrology for cops. Oh my god. Yes, you know,

517
00:29:16,160 --> 00:29:19,200
Speaker 1: we always hear that the problem with algorithms is human bias.

518
00:29:19,320 --> 00:29:23,480
Speaker 1: And this is like the visual manifestation of using science

519
00:29:23,560 --> 00:29:28,240
Speaker 1: to dress up human bias. That's so scary, that's and yeah,

520
00:29:28,360 --> 00:29:33,600
Speaker 1: to be like, oh, it is heritage and history to manufacture.

521
00:29:33,640 --> 00:29:36,680
Speaker 1: It also gives d N a evidence a bad name,

522
00:29:39,480 --> 00:29:42,680
Speaker 1: like and from this d NA we will conjure this

523
00:29:43,000 --> 00:29:47,800
Speaker 1: image of like a composite that a computer made. But yeah,

524
00:29:47,880 --> 00:29:50,920
Speaker 1: the company that provides the service, pair Bien, also does

525
00:29:51,040 --> 00:29:55,080
Speaker 1: DNA matching, but this specific service is called Snapshot, was

526
00:29:55,200 --> 00:29:58,840
Speaker 1: first released in and a lot of people in the

527
00:29:58,920 --> 00:30:03,080
Speaker 1: field of DNA rees were skeptical of Snapshot and continue

528
00:30:03,120 --> 00:30:05,440
Speaker 1: to be. For one things, the company's science has yet

529
00:30:05,480 --> 00:30:10,040
Speaker 1: to be published in any peer reviewed literature. So that's

530
00:30:10,440 --> 00:30:12,480
Speaker 1: that's one of those things that like we generally look

531
00:30:12,560 --> 00:30:15,440
Speaker 1: for in our science. I mean, do you wonder how

532
00:30:15,480 --> 00:30:19,000
Speaker 1: they came up with the name snapshot. It sounds too

533
00:30:19,400 --> 00:30:23,720
Speaker 1: like cute and in effect, you know, it's like snapchat

534
00:30:24,280 --> 00:30:26,840
Speaker 1: or like a snap Judge, it's like that's not you

535
00:30:26,920 --> 00:30:31,240
Speaker 1: aren't even trying snapshot. Yeah, hey, this will take off.

536
00:30:31,360 --> 00:30:35,160
Speaker 1: Yeah yeah, it does feel focus grouped. Yes, it feels

537
00:30:35,200 --> 00:30:38,880
Speaker 1: that came out of like Mattel, Like Mattel's like focus grouping,

538
00:30:39,000 --> 00:30:41,960
Speaker 1: like for coming up with the name of like a

539
00:30:42,480 --> 00:30:47,280
Speaker 1: snapshot Barbie, like fucked up kid's toy. It's like two

540
00:30:47,360 --> 00:30:50,280
Speaker 1: drops of blood in the receptacle container in fifteen minutes

541
00:30:50,320 --> 00:30:53,880
Speaker 1: and then it will reveal your new image snapshot. That's

542
00:30:53,880 --> 00:30:57,360
Speaker 1: like the BuzzFeed personality test of the future. Totally and

543
00:30:57,480 --> 00:31:00,600
Speaker 1: like that a world will just give figure it out.

544
00:31:01,160 --> 00:31:03,600
Speaker 1: See what cartoon, what Looney Tunes character we are by

545
00:31:03,680 --> 00:31:05,720
Speaker 1: dropping our blood into a vial? Oh my god, I

546
00:31:05,800 --> 00:31:08,440
Speaker 1: could totally see if I don't even answer questions anywhere

547
00:31:10,200 --> 00:31:12,760
Speaker 1: a version of the future where like you know, the

548
00:31:12,880 --> 00:31:15,800
Speaker 1: twenty three and me goes down a path where you're

549
00:31:15,800 --> 00:31:17,959
Speaker 1: like spitting a cup and then like they do all

550
00:31:18,040 --> 00:31:22,680
Speaker 1: sorts of fun like personality tests exactly it's like, have

551
00:31:22,840 --> 00:31:26,160
Speaker 1: you tried a belliage. It's not like hair die job,

552
00:31:26,320 --> 00:31:28,560
Speaker 1: like that would really look good for you, Like what

553
00:31:29,160 --> 00:31:32,320
Speaker 1: given your ancestry, right, yeah, I don't have a hair.

554
00:31:32,560 --> 00:31:36,840
Speaker 1: You're looking at me. You're telling much you mean, but

555
00:31:37,000 --> 00:31:40,360
Speaker 1: there there's basically no way to know how they're accomplishing

556
00:31:40,440 --> 00:31:43,440
Speaker 1: what they say they are. Their response to the criticism is,

557
00:31:43,520 --> 00:31:46,000
Speaker 1: we're not in the business to write papers. The results

558
00:31:46,040 --> 00:31:50,800
Speaker 1: speak for themselves. So results are up, my man, and

559
00:31:50,960 --> 00:31:55,040
Speaker 1: they're bad. A genetist whose work parabin admits they partly

560
00:31:55,120 --> 00:31:59,400
Speaker 1: based their technique on suspects that Parabun is just generating

561
00:31:59,440 --> 00:32:02,920
Speaker 1: a bunch of generic faces and then using the DNA

562
00:32:03,080 --> 00:32:06,400
Speaker 1: info to tweak these faces and fill in the blanks.

563
00:32:06,760 --> 00:32:10,160
Speaker 1: It's there, ah knows, Oh my god. Yeah, it really

564
00:32:10,360 --> 00:32:12,560
Speaker 1: is very similar to their notes. Wasn't that kind of

565
00:32:12,680 --> 00:32:17,120
Speaker 1: what they did with Yeah, I'm like, right, this is

566
00:32:17,240 --> 00:32:22,280
Speaker 1: like the takedown is making itself right right, Yeah, so

567
00:32:22,880 --> 00:32:26,360
Speaker 1: that would explain why the composite looks so broad and

568
00:32:26,560 --> 00:32:30,240
Speaker 1: just yeah or just be like, what the like land

569
00:32:30,280 --> 00:32:31,960
Speaker 1: that you say that it really does feel like a

570
00:32:32,080 --> 00:32:34,720
Speaker 1: creative player function in a sports game when it's like

571
00:32:34,840 --> 00:32:37,560
Speaker 1: you're the seventeen, like eight faces you can then funk

572
00:32:37,560 --> 00:32:40,080
Speaker 1: if you could funk with from there because this one

573
00:32:40,280 --> 00:32:44,080
Speaker 1: like how like it's a like this fucking mug shot

574
00:32:44,320 --> 00:32:46,960
Speaker 1: looks like a fucking thirteen year old twelve year old.

575
00:32:47,120 --> 00:32:50,200
Speaker 1: Well that's so this is what's wild. Okay, So from

576
00:32:50,280 --> 00:32:54,440
Speaker 1: the DNA testing that they're doing, they can't even determine

577
00:32:54,520 --> 00:32:59,760
Speaker 1: a person's age using so they chose the age of

578
00:33:00,680 --> 00:33:05,240
Speaker 1: you know, fourteen, and like that's the point that we

579
00:33:05,320 --> 00:33:08,160
Speaker 1: discussed recently, like with with regards to the l A

580
00:33:08,240 --> 00:33:13,120
Speaker 1: City Council's like racist comments. It's interesting that they chose

581
00:33:13,200 --> 00:33:16,080
Speaker 1: to spread a picture of a black child when they

582
00:33:16,080 --> 00:33:19,000
Speaker 1: couldn't possibly know the age. Like the other ing and

583
00:33:19,120 --> 00:33:23,400
Speaker 1: targeting of black children is like real, and it's a

584
00:33:23,480 --> 00:33:28,080
Speaker 1: cultural sickness that I feel like comes from the dissonance

585
00:33:28,120 --> 00:33:30,960
Speaker 1: that occurs in the brain of a person who's cultural

586
00:33:31,040 --> 00:33:35,000
Speaker 1: conditioning tells them to be racist against black people, but

587
00:33:35,120 --> 00:33:38,560
Speaker 1: whose humanity tells them that these are fucking children and

588
00:33:38,680 --> 00:33:42,959
Speaker 1: to like to help smooth over that dissonist dissonance, they

589
00:33:43,040 --> 00:33:46,800
Speaker 1: like grasp for anything they can to like find something

590
00:33:46,920 --> 00:33:56,080
Speaker 1: that others Black children like yeah like it, and yeah,

591
00:33:56,120 --> 00:33:57,959
Speaker 1: I don't know that in terms of skin color, one

592
00:33:58,000 --> 00:34:00,880
Speaker 1: expert estimated the scientists would only be able to predict

593
00:34:00,920 --> 00:34:04,680
Speaker 1: someone's skin color using DNA with twenty five percent accuracy.

594
00:34:05,520 --> 00:34:09,200
Speaker 1: They went all in on his complexion too. Yeah yeah,

595
00:34:10,080 --> 00:34:12,800
Speaker 1: but this is in Canada, right, Yeah, this is in Canada.

596
00:34:12,960 --> 00:34:17,640
Speaker 1: But this is also um. So the cops in Edmonton

597
00:34:17,680 --> 00:34:20,880
Speaker 1: apologize for using a tech, it doesn't mean they'll necessarily stop.

598
00:34:20,960 --> 00:34:25,080
Speaker 1: And in the NYPD announced that there they've no longer

599
00:34:25,239 --> 00:34:28,360
Speaker 1: used Snapshot in their investigations. But then more than a

600
00:34:28,440 --> 00:34:31,360
Speaker 1: year later, it turned out that they had maintained a

601
00:34:31,440 --> 00:34:34,600
Speaker 1: relationship with the company. I knew. I was like, I

602
00:34:34,640 --> 00:34:36,440
Speaker 1: had a thinking feeling. I was like, cool, this is

603
00:34:36,480 --> 00:34:43,400
Speaker 1: gonna some American Yeah, the police, you know, is going

604
00:34:43,440 --> 00:34:45,000
Speaker 1: to be like, all right, we got this, Like new

605
00:34:45,080 --> 00:34:48,799
Speaker 1: technology seems pretty lu hopefully this this this was from

606
00:34:48,920 --> 00:34:52,160
Speaker 1: five years ago. This from a local news broadcast in Denver.

607
00:34:52,600 --> 00:34:56,080
Speaker 1: When they're they're they're like heralding the arrival of d

608
00:34:56,280 --> 00:35:00,680
Speaker 1: N A phenotyping putting a face on crime. What if

609
00:35:00,719 --> 00:35:03,080
Speaker 1: you could see what a suspect looks like just from

610
00:35:03,120 --> 00:35:05,719
Speaker 1: the DNA left behind. It sounds like sci fi. But

611
00:35:05,760 --> 00:35:07,640
Speaker 1: Aurora Police or some of the first in the country

612
00:35:07,719 --> 00:35:10,120
Speaker 1: to use his cutting edge technology try to catch the

613
00:35:10,160 --> 00:35:13,880
Speaker 1: bad guys. But Denver seven Jacqueline Allen found some question

614
00:35:13,960 --> 00:35:16,960
Speaker 1: whether the science is ready. Private companies say they can

615
00:35:17,040 --> 00:35:19,480
Speaker 1: use your DNA to make predictions about what you look like,

616
00:35:19,600 --> 00:35:23,080
Speaker 1: your skin color, eye color, painting a digital picture of

617
00:35:23,200 --> 00:35:26,560
Speaker 1: your face, but some researchers are concerned about how accurate

618
00:35:26,640 --> 00:35:30,880
Speaker 1: that is, so we tried it ourselves. So they go on.

619
00:35:31,239 --> 00:35:34,400
Speaker 1: But again like the like the buyinary here is like

620
00:35:34,920 --> 00:35:40,680
Speaker 1: new technology to catch the bad guy, some people who

621
00:35:40,719 --> 00:35:42,960
Speaker 1: actually know what the funk they're talking about are like,

622
00:35:43,160 --> 00:35:47,120
Speaker 1: not so fucking quick, right, Yeah, it just shows again

623
00:35:47,200 --> 00:35:50,400
Speaker 1: like it's this always there's going there's always like the

624
00:35:50,520 --> 00:35:53,160
Speaker 1: side that's like, yes, spend more money so I have

625
00:35:53,280 --> 00:35:56,720
Speaker 1: to do less work to actually catch somebody like hey, buddy,

626
00:35:56,760 --> 00:36:01,439
Speaker 1: your face looks like this racist fucking a I algorithm face,

627
00:36:01,560 --> 00:36:04,640
Speaker 1: so it was you um or they have then they'll

628
00:36:04,640 --> 00:36:06,640
Speaker 1: actually have to use DNA to match that. But and

629
00:36:06,719 --> 00:36:09,520
Speaker 1: then on the other side of just people trying to

630
00:36:09,600 --> 00:36:14,239
Speaker 1: say this is fucking dangerous, it's pseudo science. Yeah, I

631
00:36:14,320 --> 00:36:18,000
Speaker 1: mean just think about who has like these companies are

632
00:36:18,280 --> 00:36:20,880
Speaker 1: like when you read the history of these companies they

633
00:36:20,920 --> 00:36:24,919
Speaker 1: get like hundreds of millions of dollars of cash infusions

634
00:36:25,080 --> 00:36:30,200
Speaker 1: from you know, venture capital firms, and who where where

635
00:36:30,320 --> 00:36:33,239
Speaker 1: is the money on the other side of that, you

636
00:36:33,320 --> 00:36:35,800
Speaker 1: know who who's balancing that out by looking out for

637
00:36:36,520 --> 00:36:40,200
Speaker 1: people who are getting wrongly convicted. It's like public defenders

638
00:36:40,480 --> 00:36:43,840
Speaker 1: and ship you know, like people who are you know,

639
00:36:44,040 --> 00:36:48,040
Speaker 1: not not making any money. And then you know, also

640
00:36:48,600 --> 00:36:50,719
Speaker 1: it would be interesting to look at the sourcing of

641
00:36:50,880 --> 00:36:54,040
Speaker 1: that local news story because they got to try it

642
00:36:54,120 --> 00:36:57,239
Speaker 1: out themselves, like a fun little like party game. So

643
00:36:57,760 --> 00:37:01,279
Speaker 1: they obviously did that story with the operation of the

644
00:37:01,600 --> 00:37:08,480
Speaker 1: DNA evidence like company that they were reporting on. Also,

645
00:37:08,560 --> 00:37:12,800
Speaker 1: just the political ramifications of like circulating pictures of people

646
00:37:13,160 --> 00:37:16,440
Speaker 1: at Nebula, Like yeah, yeah, I was just thinking, I

647
00:37:16,560 --> 00:37:18,640
Speaker 1: like met someone recently. He was like, oh, yeah, I

648
00:37:18,719 --> 00:37:21,160
Speaker 1: really hope Donald Trump runs again. I don't really agree

649
00:37:21,160 --> 00:37:22,680
Speaker 1: with him on anything, but like crime, we have to

650
00:37:22,719 --> 00:37:25,040
Speaker 1: close the border. You know. He's like these illegals, they're

651
00:37:25,200 --> 00:37:27,279
Speaker 1: like causing He's like what did he say? He was like,

652
00:37:27,320 --> 00:37:29,560
Speaker 1: my wife got mugged the other day. I was like,

653
00:37:29,600 --> 00:37:31,200
Speaker 1: how do you know it was an illegal immigrant? And

654
00:37:31,320 --> 00:37:33,760
Speaker 1: he was like, you don't and this guy was an immigrant,

655
00:37:33,840 --> 00:37:35,759
Speaker 1: you know, he was like, you don't know, it wasn't

656
00:37:35,760 --> 00:37:38,000
Speaker 1: an illegal immigrant, you know, just plays into like this

657
00:37:38,280 --> 00:37:44,279
Speaker 1: larger political paranoia that we're so so it's like for

658
00:37:44,400 --> 00:37:47,359
Speaker 1: some people to number one voting issue above everything else

659
00:37:47,480 --> 00:37:49,640
Speaker 1: is like, am I safe as my family safe against

660
00:37:49,719 --> 00:37:53,040
Speaker 1: like these other these other people. So that's so to

661
00:37:53,160 --> 00:37:58,400
Speaker 1: imagine just like more imagery, more faces, more more images

662
00:37:58,480 --> 00:38:01,759
Speaker 1: put up on TV of this is maybe probably a

663
00:38:01,880 --> 00:38:07,719
Speaker 1: danger people with this like yeah, ethnic background, like that's terrifying, right, yeah,

664
00:38:08,200 --> 00:38:11,440
Speaker 1: I mean yeah, people are definitely going through mean world

665
00:38:11,560 --> 00:38:14,840
Speaker 1: syndrome of just having that just put right back in

666
00:38:14,920 --> 00:38:18,239
Speaker 1: their face. And you know, we talked about the proliferation

667
00:38:18,320 --> 00:38:21,279
Speaker 1: of like ring cameras and home surveillance and all this

668
00:38:21,400 --> 00:38:24,560
Speaker 1: other stuff, and like the fucking next door app and

669
00:38:24,640 --> 00:38:28,040
Speaker 1: ship like that just feeds and feeds and feeds your

670
00:38:28,239 --> 00:38:32,600
Speaker 1: like if you have, if you're your cognitive biasedes biases

671
00:38:32,760 --> 00:38:36,040
Speaker 1: aimed towards what the folks going on out there. Everything

672
00:38:36,120 --> 00:38:38,759
Speaker 1: is so fucking unsafe. There's no shortage of ways to

673
00:38:38,840 --> 00:38:41,359
Speaker 1: fucking freak yourself out. There's no fucking like you could

674
00:38:41,880 --> 00:38:45,120
Speaker 1: turn on any fucking channel, look at any app, whatever,

675
00:38:45,239 --> 00:38:48,840
Speaker 1: there's something to reinforce that. And yeah, it's it's becoming

676
00:38:48,880 --> 00:38:51,279
Speaker 1: a really effective tool and it's the entire it's one

677
00:38:51,280 --> 00:38:53,520
Speaker 1: of the biggest things Republicans are running on now. It's

678
00:38:53,520 --> 00:38:57,560
Speaker 1: just like crime wave that's not there. Yeah, there's money

679
00:38:57,600 --> 00:39:00,480
Speaker 1: in the fear. Yeah yeah, all right, let's take a

680
00:39:00,560 --> 00:39:03,839
Speaker 1: quick break, we'll come back. We'll talk about men's war,

681
00:39:15,320 --> 00:39:19,080
Speaker 1: and we're back. And yeah, I just I I just

682
00:39:19,280 --> 00:39:23,040
Speaker 1: checked out your podcast Articles of Interest, Avery and the

683
00:39:23,120 --> 00:39:26,920
Speaker 1: Men's Where the Suits episode, which kind of dove into

684
00:39:27,239 --> 00:39:30,680
Speaker 1: men's whear, was super fascinating. It got it this idea

685
00:39:31,440 --> 00:39:33,719
Speaker 1: that I've always been aware of, but I hadn't really

686
00:39:33,840 --> 00:39:38,120
Speaker 1: like heard people kind of put words to it. But

687
00:39:38,280 --> 00:39:44,200
Speaker 1: this idea that I guess it's called spreads to see.

688
00:39:44,360 --> 00:39:45,840
Speaker 1: I'm a man, so I have to like say it,

689
00:39:45,920 --> 00:39:47,920
Speaker 1: like I don't even give a shit about it. But

690
00:39:48,040 --> 00:39:52,319
Speaker 1: you love yelling things in other languages, that's true, that's

691
00:39:52,360 --> 00:39:55,000
Speaker 1: kind of my thing. But so you you actually get

692
00:39:55,040 --> 00:39:58,480
Speaker 1: at this while talking to this like I guess self

693
00:39:58,600 --> 00:40:03,200
Speaker 1: self described men's where like nerd and in this store

694
00:40:03,640 --> 00:40:06,320
Speaker 1: that is like men's wear, like the highest level of

695
00:40:06,440 --> 00:40:10,000
Speaker 1: men's wear, dandiest men's wear store in modern America, and

696
00:40:10,080 --> 00:40:13,239
Speaker 1: it calls itself the armory, which I thought was it

697
00:40:13,400 --> 00:40:16,040
Speaker 1: still has to like slather itself in like violence and

698
00:40:16,160 --> 00:40:19,279
Speaker 1: like praditional masculinity, but like that where you get your

699
00:40:19,400 --> 00:40:27,480
Speaker 1: weapons and by that we mean kerchiefs and yeah, but

700
00:40:27,800 --> 00:40:29,880
Speaker 1: hearing you talk about it made me realize that like

701
00:40:30,120 --> 00:40:33,759
Speaker 1: since yeah, I guess it's since as you outline, like

702
00:40:33,880 --> 00:40:37,880
Speaker 1: since the like courts where royals and like high society

703
00:40:37,960 --> 00:40:40,800
Speaker 1: women and men were all dressed in like jewels and

704
00:40:40,960 --> 00:40:44,239
Speaker 1: lace and like wigs like since that time, and you

705
00:40:44,360 --> 00:40:47,200
Speaker 1: talk about the one person who kind of created this advent.

706
00:40:47,360 --> 00:40:51,200
Speaker 1: But the one central thing in men's fashion is that

707
00:40:51,360 --> 00:40:54,520
Speaker 1: men need to look great while appearing not to care,

708
00:40:55,520 --> 00:40:58,799
Speaker 1: like appearing not to try, which I thought was such

709
00:40:58,840 --> 00:41:02,239
Speaker 1: an interesting insight. Men have to appear like they don't

710
00:41:02,320 --> 00:41:04,760
Speaker 1: care about fashion and like they are up to weigh

711
00:41:04,920 --> 00:41:10,640
Speaker 1: more important things. And this is so true, you know,

712
00:41:10,760 --> 00:41:16,000
Speaker 1: it's interesting, Like this was also especially true. This wasn't

713
00:41:16,040 --> 00:41:18,120
Speaker 1: in the episode, but it's actually in this season of

714
00:41:18,239 --> 00:41:21,160
Speaker 1: Articles of Interest, which is all about preppy clothes, and

715
00:41:21,400 --> 00:41:24,000
Speaker 1: that starts with the history of Brooks Brothers, which was

716
00:41:24,120 --> 00:41:28,560
Speaker 1: one of the earliest ready to wear manufacturers. It was

717
00:41:28,600 --> 00:41:31,120
Speaker 1: one of the first places you could go and not

718
00:41:31,320 --> 00:41:33,160
Speaker 1: have to get fitted for a tailor to make you

719
00:41:33,200 --> 00:41:35,080
Speaker 1: a customed suit. You could go and just buy something

720
00:41:35,120 --> 00:41:36,719
Speaker 1: off the rack, like Brooks Brothers is one of the

721
00:41:36,760 --> 00:41:39,520
Speaker 1: first places to to do that. And that was huge

722
00:41:40,120 --> 00:41:43,160
Speaker 1: in America in like the early days of the American

723
00:41:43,320 --> 00:41:47,520
Speaker 1: Democratic experiment, because it was this like democratic way of dressing.

724
00:41:48,000 --> 00:41:51,479
Speaker 1: Like poorer people who thought they'd never own a suit

725
00:41:51,719 --> 00:41:54,799
Speaker 1: or who only wore secondhand things could now like buy

726
00:41:54,960 --> 00:41:57,759
Speaker 1: a ready to wear suit at a much lower price point.

727
00:41:58,080 --> 00:42:01,800
Speaker 1: And something that was so interesting about that is like

728
00:42:02,239 --> 00:42:06,120
Speaker 1: it created this idea that because you could just buy

729
00:42:06,239 --> 00:42:08,520
Speaker 1: clothes off the rack men, there were no ready made

730
00:42:08,560 --> 00:42:10,600
Speaker 1: clothes for women. There were like only ready made clothes

731
00:42:10,680 --> 00:42:12,600
Speaker 1: for men. You don't get ready made clothes for women

732
00:42:12,640 --> 00:42:15,400
Speaker 1: into like the nineteenth century, and so it created or

733
00:42:15,480 --> 00:42:18,400
Speaker 1: until the yeah, late nineteenth century, and so it created

734
00:42:18,440 --> 00:42:20,560
Speaker 1: this idea that like, oh, men don't have to care

735
00:42:20,880 --> 00:42:24,320
Speaker 1: because they are these companies that will care for them. Meanwhile,

736
00:42:24,400 --> 00:42:26,600
Speaker 1: women had to like keep up and you sow their

737
00:42:26,640 --> 00:42:30,680
Speaker 1: own clothes and keep up with fashion journals themselves. And

738
00:42:30,760 --> 00:42:32,120
Speaker 1: it was this whole thing. It was like well, men

739
00:42:32,200 --> 00:42:34,960
Speaker 1: have to care about politics and economics, and women largely

740
00:42:35,040 --> 00:42:39,000
Speaker 1: weren't allowed to, and so you know, created this idea

741
00:42:39,080 --> 00:42:42,439
Speaker 1: that it's like foolish or or silly to care about

742
00:42:42,480 --> 00:42:45,120
Speaker 1: what you wear when it's something that we obviously all

743
00:42:45,320 --> 00:42:48,160
Speaker 1: have to do. So there's this culture in men's wear.

744
00:42:49,040 --> 00:42:52,200
Speaker 1: Or even if you do buy a really expensive whatever

745
00:42:52,680 --> 00:42:55,600
Speaker 1: sport coat, whatever dandy thing you like, you're supposed to

746
00:42:55,680 --> 00:42:58,320
Speaker 1: leave it like unbuttoned or like a little ruffled, or

747
00:42:58,360 --> 00:43:01,279
Speaker 1: like the collar a little a little bedraggled. You don't

748
00:43:01,280 --> 00:43:04,040
Speaker 1: want to look too too buttoned up or like you

749
00:43:04,200 --> 00:43:07,879
Speaker 1: care too much. Yeah, this reminded me of the hairy

750
00:43:07,920 --> 00:43:12,120
Speaker 1: styles conversation because that like that seems to be the

751
00:43:12,239 --> 00:43:17,239
Speaker 1: person who is the most you know, fashion forward, you

752
00:43:17,360 --> 00:43:21,239
Speaker 1: know i icon and in the modern world. And for

753
00:43:21,320 --> 00:43:24,719
Speaker 1: a long time he stuck to this like he would

754
00:43:24,760 --> 00:43:30,279
Speaker 1: wear these very like attention grabbing, like just openly beautiful

755
00:43:30,640 --> 00:43:33,759
Speaker 1: articles of clothing, but like he wore it in a

756
00:43:33,840 --> 00:43:37,080
Speaker 1: way that it seemed like they were just like thrown

757
00:43:37,160 --> 00:43:39,839
Speaker 1: at him and whatever happened, the stick was like part

758
00:43:39,880 --> 00:43:44,480
Speaker 1: of the outfit was draped. And and that still like

759
00:43:44,600 --> 00:43:46,760
Speaker 1: sends to me, tends to be the case with Timothy

760
00:43:46,840 --> 00:43:49,320
Speaker 1: shallow May will go like his thing will be like

761
00:43:49,400 --> 00:43:52,520
Speaker 1: shirtless under a beautiful suit jacket or you know. But

762
00:43:53,680 --> 00:43:56,600
Speaker 1: then then I think, I think, you know, when Styles

763
00:43:56,640 --> 00:43:59,879
Speaker 1: wore that like silk shirt and jewelry to the met guy,

764
00:44:00,120 --> 00:44:04,200
Speaker 1: uh and he like he actually looked like he had

765
00:44:04,400 --> 00:44:09,000
Speaker 1: bathed that, like his hair was combed, his jewelry was

766
00:44:09,120 --> 00:44:12,600
Speaker 1: in place. He looked like he had yeah, taken a shower,

767
00:44:12,880 --> 00:44:15,439
Speaker 1: like he had done his nails and like that really

768
00:44:15,719 --> 00:44:18,040
Speaker 1: because I had not fully I've been like, well, he's

769
00:44:18,080 --> 00:44:20,640
Speaker 1: worn stuff like that before, right, But it was that

770
00:44:21,440 --> 00:44:25,040
Speaker 1: he wasn't putting the spreads toura into it. It was

771
00:44:25,160 --> 00:44:30,080
Speaker 1: like kind of openly, you know, a a presentation of

772
00:44:30,239 --> 00:44:34,680
Speaker 1: like beauty out Now that it seemed like it, you know,

773
00:44:34,800 --> 00:44:37,640
Speaker 1: it really made an impact. Everybody like kind of lost

774
00:44:37,719 --> 00:44:40,080
Speaker 1: their mind over it, even though it was, you know,

775
00:44:40,480 --> 00:44:44,160
Speaker 1: not that different from some of the stuff he's worn before.

776
00:44:45,000 --> 00:44:47,040
Speaker 1: And I mean there's a really interesting conversation to be

777
00:44:47,160 --> 00:44:50,279
Speaker 1: had there also about like whiteness and who gets to

778
00:44:50,400 --> 00:44:54,120
Speaker 1: look like disheveled and like they don't care, And it's

779
00:44:54,239 --> 00:44:58,480
Speaker 1: really interesting, Like I really realized this in this season

780
00:44:58,520 --> 00:45:02,040
Speaker 1: about preppy clothes where you know, in the early days

781
00:45:02,600 --> 00:45:05,400
Speaker 1: of preppy in like the nineties, nine thirties on the

782
00:45:05,480 --> 00:45:09,200
Speaker 1: campus of Princeton, these guys have like extreme spreads it toura.

783
00:45:09,360 --> 00:45:11,120
Speaker 1: You know, they have holes and that's why they have

784
00:45:11,280 --> 00:45:14,239
Speaker 1: like the patches on their elbows because they they're like

785
00:45:14,320 --> 00:45:17,960
Speaker 1: their sweaters are pilling their their khakis have rough edges.

786
00:45:18,040 --> 00:45:21,520
Speaker 1: You know, they look like kind of kind of gross

787
00:45:21,600 --> 00:45:24,319
Speaker 1: in some ways, like allah early shallow me. But then

788
00:45:24,360 --> 00:45:27,680
Speaker 1: when you get to sort of the evolution of like

789
00:45:28,400 --> 00:45:31,919
Speaker 1: you know, by the nineties, when you have the low

790
00:45:32,040 --> 00:45:35,359
Speaker 1: heads and the origins of street style and like hip

791
00:45:35,440 --> 00:45:39,200
Speaker 1: hop infuse Tommy Hill figure, that's all about looking like

792
00:45:39,440 --> 00:45:42,239
Speaker 1: fresh and looking clean. But it's arguably a lot of

793
00:45:42,280 --> 00:45:46,400
Speaker 1: the same clothes just worn in like really different styles,

794
00:45:46,560 --> 00:45:47,880
Speaker 1: and a lot of it has to do with like

795
00:45:48,239 --> 00:45:50,960
Speaker 1: the culture around who is wearing it. If there is

796
00:45:51,000 --> 00:45:54,880
Speaker 1: a culture where like spreads toura is considered you know,

797
00:45:55,160 --> 00:46:00,160
Speaker 1: cool or not right, Yeah, And I think this also

798
00:46:00,239 --> 00:46:04,439
Speaker 1: ties into sneaker culture, like that's the one place where

799
00:46:04,520 --> 00:46:08,080
Speaker 1: men are allowed to like focus their inner stheet, like

800
00:46:08,400 --> 00:46:10,640
Speaker 1: I think, and at least in some culture. I was

801
00:46:10,719 --> 00:46:14,760
Speaker 1: actually at a child's birthday party. Yeah, I was invited.

802
00:46:14,800 --> 00:46:17,720
Speaker 1: I didn't just like show up judging all the fashion.

803
00:46:17,800 --> 00:46:23,520
Speaker 1: Maybe it was on the west side of Los Angeles,

804
00:46:23,600 --> 00:46:27,040
Speaker 1: which is a totally different world than kind of further

805
00:46:27,360 --> 00:46:31,440
Speaker 1: further east, and like I had Jordan's on and every

806
00:46:31,520 --> 00:46:36,480
Speaker 1: other dead had like the same. They all looked very preppy.

807
00:46:36,600 --> 00:46:38,840
Speaker 1: It was like and I couldn't tell if it was

808
00:46:38,920 --> 00:46:42,480
Speaker 1: like this this style of clothing had really like come

809
00:46:42,520 --> 00:46:45,200
Speaker 1: back in a in a strong way just on the

810
00:46:45,280 --> 00:46:47,560
Speaker 1: west side of l A. Or if I that was

811
00:46:47,800 --> 00:46:50,840
Speaker 1: just but yeah, they all had like kind of loafers

812
00:46:51,239 --> 00:46:56,279
Speaker 1: or you know, canvas like bringing that East coast. Yeah,

813
00:46:56,560 --> 00:46:58,400
Speaker 1: it was funny because I was just in d C.

814
00:46:58,560 --> 00:47:01,080
Speaker 1: And I was in Georgetown, and I was like I

815
00:47:01,280 --> 00:47:03,879
Speaker 1: was looking at that prep style. It dead in its

816
00:47:03,960 --> 00:47:06,800
Speaker 1: fucking eye, and it was like every dude is wearing

817
00:47:06,960 --> 00:47:10,320
Speaker 1: a fucking patterned shirt with a fleece vest over it.

818
00:47:10,520 --> 00:47:12,239
Speaker 1: Like I'm not lying, Like there's like a crew of

819
00:47:12,320 --> 00:47:17,000
Speaker 1: five dudes. Everybody had a final shirt, fleece vest, khaki's

820
00:47:17,440 --> 00:47:20,200
Speaker 1: some kind of like boat adjacent shoe. And I was

821
00:47:20,280 --> 00:47:22,560
Speaker 1: like this is I was like freaking me out. I

822
00:47:22,680 --> 00:47:24,959
Speaker 1: was like, is this a bit? But it just felt

823
00:47:25,040 --> 00:47:27,960
Speaker 1: like uniform. I mean, the question is, Miles, do you

824
00:47:28,040 --> 00:47:30,440
Speaker 1: think that's like a resurgence. Do you think that's like

825
00:47:30,480 --> 00:47:31,879
Speaker 1: a new thing, or do you think it's something that's

826
00:47:31,920 --> 00:47:35,120
Speaker 1: never gone away. I don't. I think it's like because

827
00:47:35,160 --> 00:47:39,080
Speaker 1: to me it looks like how my parents would dress kids,

828
00:47:39,160 --> 00:47:41,920
Speaker 1: and like the late eighties, you know, they're like you

829
00:47:41,920 --> 00:47:45,360
Speaker 1: should look like a little yuppie like and that swag.

830
00:47:45,960 --> 00:47:48,600
Speaker 1: And then I think then, like in the nineties, we

831
00:47:48,680 --> 00:47:51,200
Speaker 1: all gore grungy and ship and had are like you know,

832
00:47:51,400 --> 00:47:54,360
Speaker 1: punk or emo or hip hop phase or whatever. And

833
00:47:54,400 --> 00:47:57,000
Speaker 1: then I think, I don't know if for whatever reason,

834
00:47:57,080 --> 00:47:59,000
Speaker 1: I think now it's like I think just people are

835
00:47:59,080 --> 00:48:02,560
Speaker 1: really back to just being able to signal their wealth

836
00:48:02,680 --> 00:48:05,279
Speaker 1: or socioeconomic status to what they wear, even if it's

837
00:48:05,320 --> 00:48:07,520
Speaker 1: not really like their style. It's like, well, when I

838
00:48:07,640 --> 00:48:11,480
Speaker 1: wear this, people know I'm probably an ivy type dude,

839
00:48:11,880 --> 00:48:14,600
Speaker 1: or you know, like I have a good job because

840
00:48:14,680 --> 00:48:17,719
Speaker 1: I'm I'm wearing the uniform of a person that does that.

841
00:48:19,400 --> 00:48:22,080
Speaker 1: You get to talk to like there, I forget the

842
00:48:22,160 --> 00:48:24,000
Speaker 1: name of the company, but there's like a company that

843
00:48:24,640 --> 00:48:27,120
Speaker 1: all of the fashion houses and all of the like

844
00:48:27,280 --> 00:48:30,799
Speaker 1: clothing manufacturers consult to be like, Okay, here's what we're

845
00:48:30,920 --> 00:48:34,560
Speaker 1: doing two years from now, and it raises like a

846
00:48:34,600 --> 00:48:37,680
Speaker 1: really interesting chicken in the egg thing. But yeah, there

847
00:48:37,719 --> 00:48:40,839
Speaker 1: are these like trend forecasting companies. I feel like after

848
00:48:40,920 --> 00:48:44,200
Speaker 1: the pandemic, there's been so much conversation around like what's

849
00:48:44,200 --> 00:48:46,440
Speaker 1: the trend? What's in trend right now? You guys, it's

850
00:48:46,440 --> 00:48:49,360
Speaker 1: like Barbie Core, It's clown Core, it's normal Core, like

851
00:48:49,440 --> 00:48:51,960
Speaker 1: all these cores, you know, they're all these trends right now.

852
00:48:52,280 --> 00:48:54,120
Speaker 1: And I feel like it's just because we're sort of

853
00:48:54,680 --> 00:49:00,439
Speaker 1: reacclimating and trying to like understand each other again. And yeah,

854
00:49:00,480 --> 00:49:02,120
Speaker 1: so it got me thinking about this company called w

855
00:49:02,280 --> 00:49:06,600
Speaker 1: GS and that most like most major fashion houses consult

856
00:49:06,760 --> 00:49:08,640
Speaker 1: to be like what is going to be what is

857
00:49:08,680 --> 00:49:11,040
Speaker 1: going to be in? And so I talked to them

858
00:49:11,280 --> 00:49:14,480
Speaker 1: about trends and how there's so many trends now and

859
00:49:14,840 --> 00:49:19,919
Speaker 1: my personal theory for why preppy and no one uses

860
00:49:19,960 --> 00:49:21,279
Speaker 1: that word, even when I talk to the CEO of

861
00:49:21,360 --> 00:49:23,160
Speaker 1: Brooks Brothers, he was like, we don't use that word.

862
00:49:23,239 --> 00:49:25,000
Speaker 1: And then you look at their website and it's like

863
00:49:26,280 --> 00:49:29,800
Speaker 1: tennis sweaters worn over, you know, it's like the same clothes,

864
00:49:30,120 --> 00:49:32,680
Speaker 1: but now we call them classics, or we call them basic,

865
00:49:32,840 --> 00:49:34,360
Speaker 1: or you know, you go to Uniclo and it's like

866
00:49:34,560 --> 00:49:37,640
Speaker 1: preppy clothes. Those are just classics. And I think why

867
00:49:37,760 --> 00:49:41,120
Speaker 1: they're having a moment now, you know, it's arguable whether

868
00:49:41,160 --> 00:49:42,759
Speaker 1: they're like having a moment or they never went away,

869
00:49:43,040 --> 00:49:45,280
Speaker 1: but it's because they're like a way out from trends

870
00:49:45,360 --> 00:49:46,799
Speaker 1: people who are like, you know what, I can't keep

871
00:49:46,880 --> 00:49:49,560
Speaker 1: up with all these trends. I'm just gonna address like

872
00:49:49,760 --> 00:49:52,719
Speaker 1: in a classic the classic way that I don't have

873
00:49:52,840 --> 00:49:56,399
Speaker 1: to think about. That's that's like like, oh, so we're

874
00:49:56,480 --> 00:49:58,320
Speaker 1: back to being like I don't have the men on

875
00:49:58,400 --> 00:50:00,759
Speaker 1: the band. Yeah, yeah, yeah, exactly. That's a new version

876
00:50:00,800 --> 00:50:03,400
Speaker 1: of that totally. Now fuck it. I will wear my

877
00:50:03,600 --> 00:50:06,239
Speaker 1: fucking powdern flannel with my fleece fest and look, no

878
00:50:06,360 --> 00:50:07,879
Speaker 1: shade if you dressed like that, I don't give a ship.

879
00:50:08,080 --> 00:50:10,080
Speaker 1: I think there's a way to doing well. Yeah yeah,

880
00:50:10,200 --> 00:50:12,560
Speaker 1: but yeah, I think when I look at it too,

881
00:50:12,680 --> 00:50:15,440
Speaker 1: I don't get as overwhelmed, like because I used to

882
00:50:15,520 --> 00:50:19,160
Speaker 1: be super up on street where from college on, and

883
00:50:19,239 --> 00:50:21,080
Speaker 1: then like I started like having to be in the

884
00:50:21,160 --> 00:50:24,400
Speaker 1: real world and like, oh okay, I don't have the

885
00:50:24,520 --> 00:50:27,120
Speaker 1: money to wear all where this ship all the time.

886
00:50:27,480 --> 00:50:30,040
Speaker 1: But I think it just more forced me into a

887
00:50:30,080 --> 00:50:33,080
Speaker 1: place of like, woa, my what is my own style?

888
00:50:33,200 --> 00:50:35,960
Speaker 1: And I'm just being like, I'm still I'm still fifteen

889
00:50:36,040 --> 00:50:38,359
Speaker 1: years old in the San Fernando Valley, So I will

890
00:50:38,400 --> 00:50:42,640
Speaker 1: wear basketball shorts, sweat pants, T shirts, hoodies and just

891
00:50:42,960 --> 00:50:45,160
Speaker 1: the that's that's kind of work. That's kind of my

892
00:50:45,200 --> 00:50:48,319
Speaker 1: own Like I don't and it's not that I don't

893
00:50:48,520 --> 00:50:50,160
Speaker 1: I'm necessarily saying like I don't have the time to

894
00:50:50,239 --> 00:50:51,960
Speaker 1: figure that sh it out. I'm like, that's just kind

895
00:50:52,000 --> 00:50:53,920
Speaker 1: of where I landed in terms of what my personal

896
00:50:53,960 --> 00:50:55,960
Speaker 1: style is. No, it means you thought, I mean, that's

897
00:50:56,000 --> 00:50:58,040
Speaker 1: like an incredible thing. It just means you know who

898
00:50:58,120 --> 00:51:00,040
Speaker 1: you are and you know what you like. And I

899
00:51:00,080 --> 00:51:05,160
Speaker 1: think a lot of people haven't done that work. You know. Yeah,

900
00:51:05,200 --> 00:51:07,920
Speaker 1: if you just want to dress in a generally manageable, acceptable,

901
00:51:08,480 --> 00:51:12,880
Speaker 1: culturally acceptable way, that literally opens doors for you. Pretty

902
00:51:12,920 --> 00:51:16,040
Speaker 1: clothes are like a tool, you know. You're like, yeah,

903
00:51:16,120 --> 00:51:19,040
Speaker 1: it's like code switching of clothing. Yeah, where in the

904
00:51:19,120 --> 00:51:21,759
Speaker 1: uniform and like an it's open to anyone. It's like

905
00:51:21,800 --> 00:51:23,320
Speaker 1: the keys to the Kingdom and like you can just

906
00:51:23,400 --> 00:51:25,360
Speaker 1: have them. It's kind of amazing. It is kind of

907
00:51:25,400 --> 00:51:26,919
Speaker 1: like yeah, because it's sort of like what a maga

908
00:51:27,000 --> 00:51:29,160
Speaker 1: hat does. Like if you're out a rally, like you're like,

909
00:51:29,200 --> 00:51:31,160
Speaker 1: guess what, just because I wore this hat and they

910
00:51:31,200 --> 00:51:34,839
Speaker 1: have it doesn't mean because the hat there, they did

911
00:51:34,920 --> 00:51:38,000
Speaker 1: not really analyze more than like, got the hat, all right? Good?

912
00:51:38,040 --> 00:51:41,239
Speaker 1: Would me? You know? I remember once I, yeah, I

913
00:51:41,520 --> 00:51:43,160
Speaker 1: like did coverage at a Trump rally and I was like,

914
00:51:43,239 --> 00:51:46,000
Speaker 1: fucking person, I'm gonna wear a red hat and everybody

915
00:51:46,080 --> 00:51:48,239
Speaker 1: was like, hey, what's that fella like coming out? He

916
00:51:48,280 --> 00:51:53,400
Speaker 1: didn't even say anything on it was this is I

917
00:51:53,480 --> 00:51:55,560
Speaker 1: think just the way I'd be able to navigate these

918
00:51:55,600 --> 00:51:59,040
Speaker 1: people as somebody who's navigated white culture pretty frequently. I'm like,

919
00:51:59,400 --> 00:52:01,759
Speaker 1: this might and it didn't. I think, like you're saying,

920
00:52:02,120 --> 00:52:04,960
Speaker 1: especially for people who are in situations where you're gonna

921
00:52:05,000 --> 00:52:07,200
Speaker 1: be just a snap judgment is going to be made

922
00:52:07,200 --> 00:52:09,480
Speaker 1: on your pearance. You show up in the clothing of

923
00:52:09,760 --> 00:52:13,040
Speaker 1: whatever their world is, and without thinking, they're like, well,

924
00:52:13,239 --> 00:52:16,160
Speaker 1: all the markers are there of person who is if

925
00:52:16,239 --> 00:52:19,520
Speaker 1: the same socio economic bracket or culture one hundred percent

926
00:52:19,600 --> 00:52:21,480
Speaker 1: and I have to say, like, when I did this research,

927
00:52:21,640 --> 00:52:23,719
Speaker 1: I've been working on this for months now, I really

928
00:52:23,760 --> 00:52:25,880
Speaker 1: thought it would be going to Kennebunk Board to like

929
00:52:26,040 --> 00:52:29,320
Speaker 1: interview people named Muffy periodically. But I was about to

930
00:52:29,440 --> 00:52:36,360
Speaker 1: use that word literally, yeah, yeah, I actually I actually

931
00:52:36,400 --> 00:52:38,279
Speaker 1: interviewed someone who was like, yeah, I dated a girl

932
00:52:38,360 --> 00:52:42,239
Speaker 1: named Pussy, like preppy names are the best, but the

933
00:52:43,200 --> 00:52:47,200
Speaker 1: But really I ended up interviewing almost like mostly New Yorkers,

934
00:52:47,560 --> 00:52:51,160
Speaker 1: mostly black and Jewish New Yorkers. And the story is

935
00:52:51,239 --> 00:52:54,359
Speaker 1: like black and Jewish and very Japanese. It is only

936
00:52:54,440 --> 00:52:57,360
Speaker 1: a small percentage of it that is actually like waspy.

937
00:52:57,640 --> 00:53:01,520
Speaker 1: It is a really fascinating story of how like so

938
00:53:01,680 --> 00:53:04,800
Speaker 1: many different groups have taken on different versions of this

939
00:53:04,960 --> 00:53:08,239
Speaker 1: look and actually made it their own. And and now

940
00:53:08,320 --> 00:53:10,080
Speaker 1: I love it, Like knowing the whole history, I'm like,

941
00:53:10,160 --> 00:53:13,800
Speaker 1: this is the coolest your American story there In in

942
00:53:13,880 --> 00:53:16,120
Speaker 1: the first episode of the new season, you talked about

943
00:53:16,200 --> 00:53:20,920
Speaker 1: this book that was sort of a like sociological study

944
00:53:21,160 --> 00:53:26,520
Speaker 1: of Ivy League culture in the mid century that was done.

945
00:53:27,080 --> 00:53:29,879
Speaker 1: Wasn't it like a Japanese author had like come through

946
00:53:30,000 --> 00:53:34,120
Speaker 1: to like take photographs and because it was just It's

947
00:53:34,160 --> 00:53:35,799
Speaker 1: not the sort of thing that you would do if

948
00:53:35,880 --> 00:53:37,640
Speaker 1: you were living in the moment. But because it was

949
00:53:37,760 --> 00:53:42,400
Speaker 1: this like sociological thing, it like really captured all the

950
00:53:42,800 --> 00:53:47,400
Speaker 1: weird little sort of shrugged off gestures and styles and

951
00:53:47,840 --> 00:53:51,000
Speaker 1: and kind of made it very influential, right, yeah, yeah, yeah.

952
00:53:51,000 --> 00:53:53,000
Speaker 1: It was like no one would think at the time

953
00:53:53,080 --> 00:53:54,759
Speaker 1: that the book was written to be like isn't it

954
00:53:54,840 --> 00:53:58,160
Speaker 1: so amazing They're wearing loafers without socks, but you know

955
00:53:58,320 --> 00:54:01,240
Speaker 1: these this this Japanese author was like this is so interesting,

956
00:54:01,400 --> 00:54:03,840
Speaker 1: Like look at what's going on here. And so this

957
00:54:04,000 --> 00:54:07,040
Speaker 1: book called Take Ivy, which in later episodes of You

958
00:54:07,360 --> 00:54:10,560
Speaker 1: will be revealed is like a pun, it's a it's

959
00:54:10,600 --> 00:54:14,400
Speaker 1: a word play on the Dave Brubeck song Take five

960
00:54:15,000 --> 00:54:21,359
Speaker 1: became like the bible for this look that then had

961
00:54:21,400 --> 00:54:24,839
Speaker 1: a huge moment in the early OS and like Jay

962
00:54:24,960 --> 00:54:28,279
Speaker 1: Crew Jenna Lions era, Like I saw Take Ivy for

963
00:54:28,440 --> 00:54:31,880
Speaker 1: sale at a j Crew around that time, there's like

964
00:54:31,960 --> 00:54:37,240
Speaker 1: this huge preppy revival, you know, like Andre three thousand,

965
00:54:37,840 --> 00:54:42,400
Speaker 1: you know, Backpack Rap, Vampire Weekend, Gossip Girl. There was

966
00:54:42,440 --> 00:54:46,239
Speaker 1: this like preppy moment that I think our time now

967
00:54:46,840 --> 00:54:50,840
Speaker 1: is reference there because like recent nostalgia is also and

968
00:54:51,080 --> 00:54:54,719
Speaker 1: yet totally and it's time. But take Ivy was a

969
00:54:54,880 --> 00:54:58,600
Speaker 1: huge part of it. That's like relic from still like

970
00:55:00,239 --> 00:55:01,759
Speaker 1: like when I look at the images, I'm like, is

971
00:55:01,840 --> 00:55:05,120
Speaker 1: this a J Crew or like early Abercrombie look book

972
00:55:05,640 --> 00:55:08,680
Speaker 1: right exactly exactly, or a main leandor like it looks

973
00:55:09,000 --> 00:55:12,480
Speaker 1: so I mean it looks one must admit it looks good.

974
00:55:12,719 --> 00:55:15,319
Speaker 1: Like they look good. Yeah, yeah, I mean like it's

975
00:55:15,360 --> 00:55:20,520
Speaker 1: it's a vibe, it's it's a particular look, right, but

976
00:55:20,640 --> 00:55:23,480
Speaker 1: don't but but pay attention to your sneakers, people like

977
00:55:23,600 --> 00:55:25,879
Speaker 1: you can you can still dress preppy and not where

978
00:55:25,960 --> 00:55:29,880
Speaker 1: the not where like they're ja cru cells, like to

979
00:55:30,360 --> 00:55:33,160
Speaker 1: the types of sneakers the Nike kill Shot and the

980
00:55:33,520 --> 00:55:36,400
Speaker 1: Stan Smith's and like those were the only sneakers that

981
00:55:36,480 --> 00:55:39,000
Speaker 1: I saw at that birthday party that now people now

982
00:55:40,480 --> 00:55:44,920
Speaker 1: people rock the Alexander McQueen version of Smith. I had,

983
00:55:44,960 --> 00:55:46,759
Speaker 1: like the thicker one to like these are actually six

984
00:55:47,200 --> 00:55:52,520
Speaker 1: dollar versions. I'm like, they still look the soul is

985
00:55:52,640 --> 00:55:55,680
Speaker 1: just thicker. Fine, good for you, you have spent more money.

986
00:55:55,760 --> 00:55:58,160
Speaker 1: But that is not style. And that's another interesting part

987
00:55:58,200 --> 00:56:00,360
Speaker 1: too about fashion is so many people now just to

988
00:56:00,440 --> 00:56:04,160
Speaker 1: quate the fucking price with some level of like aesthetic

989
00:56:04,719 --> 00:56:07,920
Speaker 1: viability or uniqueness. When it's like this ship is sold,

990
00:56:07,960 --> 00:56:10,279
Speaker 1: it's a fucking illusion and you just have just have

991
00:56:10,560 --> 00:56:14,320
Speaker 1: chunky looking stand Smiths on have you covered rep culture

992
00:56:14,400 --> 00:56:17,360
Speaker 1: at all, like people who are doing like replicas of

993
00:56:17,440 --> 00:56:20,800
Speaker 1: like expensive sneakers, like getting them from the factories, like

994
00:56:20,840 --> 00:56:23,279
Speaker 1: people working at the factories. Well, I haven't done it

995
00:56:23,320 --> 00:56:25,120
Speaker 1: with sneakers, but I did do a whole episode where

996
00:56:25,160 --> 00:56:30,880
Speaker 1: I interviewed the icon himself, Dapper Dan, and he Dapper

997
00:56:30,960 --> 00:56:38,160
Speaker 1: Dan most famously like stole yeah, basically soul the like

998
00:56:38,320 --> 00:56:41,320
Speaker 1: Gucci logo and the Louis Bhutan logo in like the

999
00:56:41,400 --> 00:56:45,320
Speaker 1: eighties and nineties, and just print really high quality like

1000
00:56:45,520 --> 00:56:49,160
Speaker 1: amazing leather outfit, like he was the first one to

1001
00:56:49,280 --> 00:56:54,080
Speaker 1: make jumpsuits like leather, Gucci printed jumpsuits, like they weren't

1002
00:56:54,160 --> 00:56:56,799
Speaker 1: doing that like that. The whole reason you see people

1003
00:56:56,880 --> 00:57:00,680
Speaker 1: wearing like designer jumpsuits is because they were credible, high

1004
00:57:00,760 --> 00:57:04,680
Speaker 1: quality knockoffs. And then the whole saga is like Gucci

1005
00:57:04,840 --> 00:57:08,640
Speaker 1: started copying Dapper down. It was like he's ripping off

1006
00:57:09,640 --> 00:57:11,960
Speaker 1: who which is? And now it's kind of a happy

1007
00:57:12,000 --> 00:57:15,319
Speaker 1: story because now Gucci like kind of bought Dapper Down

1008
00:57:15,440 --> 00:57:17,040
Speaker 1: and he works within them, so it's sort of a

1009
00:57:17,120 --> 00:57:20,800
Speaker 1: happy ending. Well. Dapper Down said this beautiful thing to

1010
00:57:20,960 --> 00:57:22,479
Speaker 1: me that I think about all the time. He said,

1011
00:57:22,560 --> 00:57:27,480
Speaker 1: these symbols don't just represent brands, like the interlocking geez,

1012
00:57:28,200 --> 00:57:35,560
Speaker 1: represent like prosperity and wellness and and like health in

1013
00:57:35,640 --> 00:57:38,160
Speaker 1: a weird way to like have these symbols, they're almost

1014
00:57:38,200 --> 00:57:41,640
Speaker 1: like the ancient scarab or the NC. You know, they're

1015
00:57:41,720 --> 00:57:46,280
Speaker 1: like powerful symbols that everyone should have access to. And honestly, like,

1016
00:57:47,120 --> 00:57:49,800
Speaker 1: I have a I have a pen pal who's incarcerated,

1017
00:57:50,040 --> 00:57:52,560
Speaker 1: and the very first letter he sent me has like

1018
00:57:52,680 --> 00:57:56,640
Speaker 1: Gucci logos all around the letter, as like that that's

1019
00:57:56,720 --> 00:57:59,080
Speaker 1: the power of this stuff. It's not it's like not

1020
00:57:59,200 --> 00:58:01,760
Speaker 1: even about the brand anymore. It's just like a symbol

1021
00:58:02,280 --> 00:58:06,360
Speaker 1: that means so much more and it has nothing to

1022
00:58:06,400 --> 00:58:08,680
Speaker 1: do with like the quality of the leather or or anything.

1023
00:58:08,800 --> 00:58:11,720
Speaker 1: So i'mlike, ever since then, I'm like all about knockoffs.

1024
00:58:11,800 --> 00:58:14,960
Speaker 1: I think they're they're fantastic. I'll be a like tricky

1025
00:58:15,080 --> 00:58:18,800
Speaker 1: terrain for designers to navigate, but so much innovation comes

1026
00:58:18,840 --> 00:58:21,480
Speaker 1: from it. It's really interesting. Yeah, and it just also

1027
00:58:21,520 --> 00:58:23,840
Speaker 1: I think it forces a conversation about like what makes

1028
00:58:23,960 --> 00:58:26,920
Speaker 1: like what's the important part? Is it the visual aesthetic?

1029
00:58:27,080 --> 00:58:29,680
Speaker 1: Is that the design of something? Or is it if

1030
00:58:29,720 --> 00:58:33,240
Speaker 1: I put it under a fucking like microscope? Is the

1031
00:58:33,400 --> 00:58:36,520
Speaker 1: stitching right? Because that's how a real thing is made.

1032
00:58:36,600 --> 00:58:38,240
Speaker 1: And it's like, well, am I doing it? Are you

1033
00:58:38,400 --> 00:58:40,640
Speaker 1: dressing because you like the way it looks? Or you

1034
00:58:40,840 --> 00:58:43,800
Speaker 1: dress because it's purely like a symbol of your wealth

1035
00:58:43,920 --> 00:58:46,640
Speaker 1: or a signal of that, And it's it's always funny,

1036
00:58:46,720 --> 00:58:48,720
Speaker 1: especially in sneaker culture. You hear people like I would

1037
00:58:48,720 --> 00:58:52,120
Speaker 1: never wear a fuck if fake Jordan's or whatever. And

1038
00:58:52,720 --> 00:58:55,840
Speaker 1: again it shows how some people have just ascribed like,

1039
00:58:55,960 --> 00:58:58,439
Speaker 1: well that the real thing has value and that's something

1040
00:58:58,480 --> 00:59:00,840
Speaker 1: I'm going for. And if I don't want the cheap thing,

1041
00:59:00,960 --> 00:59:03,760
Speaker 1: because that means you're you don't have what it takes

1042
00:59:03,840 --> 00:59:07,600
Speaker 1: to earn like the real thing. But the pursuit of

1043
00:59:07,720 --> 00:59:10,040
Speaker 1: that is fucking dumb too, Like it gives a ship

1044
00:59:10,120 --> 00:59:12,560
Speaker 1: if you can afford the real things, Like that's dumb

1045
00:59:12,600 --> 00:59:15,840
Speaker 1: as fuck. There's nothing objectively cool about that. It's just

1046
00:59:15,960 --> 00:59:18,160
Speaker 1: a way to differentiate, and I think it kind of

1047
00:59:18,240 --> 00:59:22,440
Speaker 1: blows up the pursuit of like these high end items

1048
00:59:22,480 --> 00:59:24,520
Speaker 1: and what they actually really mean. And I love how

1049
00:59:24,600 --> 00:59:27,480
Speaker 1: frustrated people get, especially when like celebrity is like like

1050
00:59:27,760 --> 00:59:29,960
Speaker 1: Chad Johnson, He's like, I don't I don't buy real

1051
00:59:30,000 --> 00:59:31,760
Speaker 1: ship at all. Ever, He's like, why would I waste

1052
00:59:31,800 --> 00:59:35,000
Speaker 1: my money? Yeah? Yeah. The rep sneakers subreddit is like

1053
00:59:35,160 --> 00:59:39,600
Speaker 1: one large exploration of like, you know, materialism in the

1054
00:59:40,160 --> 00:59:45,760
Speaker 1: philosophical sense and like the ship of theseus. It's so

1055
00:59:46,120 --> 00:59:49,240
Speaker 1: it's so interesting. Alright, Avery, we could we could talk

1056
00:59:49,280 --> 00:59:52,080
Speaker 1: to you for hours about the stuff. Well after that,

1057
00:59:53,680 --> 00:59:56,160
Speaker 1: but where can people find you? Follow you, hear you

1058
00:59:56,240 --> 00:59:58,960
Speaker 1: all that good stuff? Well, check out articles of interest

1059
00:59:59,040 --> 01:00:02,440
Speaker 1: where you get your podcasts called articles of Interest. And

1060
01:00:03,280 --> 01:00:06,320
Speaker 1: I'm on Twitter. My last name is Truffleman and that's

1061
01:00:06,360 --> 01:00:09,000
Speaker 1: my handle tr you f F the l Man. Those

1062
01:00:09,040 --> 01:00:12,640
Speaker 1: are the places I live. But thank you. Someone just

1063
01:00:12,720 --> 01:00:14,560
Speaker 1: was so fascinating. I'm like, I have so many more

1064
01:00:14,600 --> 01:00:17,720
Speaker 1: thoughts on sneaker culture, but yeah, thank you. And is

1065
01:00:17,800 --> 01:00:20,000
Speaker 1: there a tweet or some of the work of social

1066
01:00:20,080 --> 01:00:22,880
Speaker 1: media you've been enjoying. Um, I've been really enjoying the

1067
01:00:23,040 --> 01:00:27,200
Speaker 1: meme about like the spirit Halloween costumes that everyone is

1068
01:00:27,320 --> 01:00:29,640
Speaker 1: sharing of just like what is it? What is the meme?

1069
01:00:29,720 --> 01:00:33,320
Speaker 1: Like the only costume? Uh? And there was one recently

1070
01:00:33,440 --> 01:00:36,960
Speaker 1: with like, I don't know the this episode of SpongeBob

1071
01:00:37,040 --> 01:00:40,920
Speaker 1: SquarePants where he makes doodle Bob. Who do you know

1072
01:00:41,000 --> 01:00:44,800
Speaker 1: this episode? Yeah? Uh, that's my that's my favorite where

1073
01:00:44,840 --> 01:00:47,000
Speaker 1: it's like an image of doodle Bob. It's like the

1074
01:00:47,080 --> 01:00:51,400
Speaker 1: only Halloween costume. I love that meme. That's amazing. Miles,

1075
01:00:51,440 --> 01:00:53,600
Speaker 1: where can people find you with a tweet you've been enjoying?

1076
01:00:54,120 --> 01:00:56,600
Speaker 1: Find me on Twitter and Instagram at Miles of Gray.

1077
01:00:56,920 --> 01:00:59,880
Speaker 1: Check Jack and I out on our basketball podcast off

1078
01:01:00,000 --> 01:01:03,800
Speaker 1: acual NBA basketball podcast. Somehow they let us keep saying

1079
01:01:03,880 --> 01:01:07,160
Speaker 1: our dumb ideas out loud and it's an NBA product.

1080
01:01:07,200 --> 01:01:10,920
Speaker 1: It's called Miles and Jack Got Mad Boostie. It's a

1081
01:01:11,000 --> 01:01:15,080
Speaker 1: fantastic show. Check in this week. Uh, just always fantastic guest.

1082
01:01:15,120 --> 01:01:18,240
Speaker 1: New episode just dropped today. Uh. And also I'm always

1083
01:01:18,480 --> 01:01:22,080
Speaker 1: with Sophia Alexandra talking ninety day Fiance over at four

1084
01:01:22,200 --> 01:01:26,360
Speaker 1: twenty day Fiance. Now, let's see some tweets that I like. First,

1085
01:01:26,440 --> 01:01:29,200
Speaker 1: one has guess Paula Vegan Alan at Paula Vigan, Alan

1086
01:01:29,240 --> 01:01:33,720
Speaker 1: tweeted dear Kanye if I was your mother and anlysts

1087
01:01:34,600 --> 01:01:38,240
Speaker 1: uh fucking ship got me, and then another one from

1088
01:01:38,880 --> 01:01:43,120
Speaker 1: at Soma Kazima tweeting, nah they clapp him back now

1089
01:01:43,240 --> 01:01:47,520
Speaker 1: and posted a video of these girls on TikTok doing

1090
01:01:47,640 --> 01:01:51,440
Speaker 1: like p o V influencers trying Indian food for the

1091
01:01:51,520 --> 01:01:54,720
Speaker 1: first time. And it's just it's just so good because

1092
01:01:56,080 --> 01:01:58,480
Speaker 1: that the tweets said, nah they clapp him back now.

1093
01:01:59,120 --> 01:02:01,360
Speaker 1: And this is so good because if you've ever seen

1094
01:02:01,440 --> 01:02:03,920
Speaker 1: these videos of like white people trying Indian food for

1095
01:02:03,960 --> 01:02:06,520
Speaker 1: the first time, it has the exact same vibe of

1096
01:02:06,560 --> 01:02:09,600
Speaker 1: it being so exotic sized, like what's this And I'm

1097
01:02:09,600 --> 01:02:11,920
Speaker 1: just gonna play the first couple of seconds because it's genius.

1098
01:02:12,600 --> 01:02:21,120
Speaker 1: Hi from the shots. And we got Indian food actually,

1099
01:02:22,120 --> 01:02:26,680
Speaker 1: but I heard they were similar Pakistan's yeah paki. Yeah,

1100
01:02:26,840 --> 01:02:28,640
Speaker 1: we didn't get to gap, but we got chicken tikum

1101
01:02:28,760 --> 01:02:32,120
Speaker 1: sala because the manager said it was good. Also he

1102
01:02:32,200 --> 01:02:34,000
Speaker 1: said he said a tip is to eat it with

1103
01:02:34,160 --> 01:02:40,280
Speaker 1: yogurt and then we have none. I just love their

1104
01:02:40,360 --> 01:02:46,600
Speaker 1: fucking paper like big in. These girls are killing it,

1105
01:02:46,920 --> 01:02:52,600
Speaker 1: so yeah, shout out to that ticktime. Amazing, that's great.

1106
01:02:52,840 --> 01:02:55,840
Speaker 1: Some tweets. I've been enjoying Logan Dean Goes Boy detective tweeter.

1107
01:02:55,920 --> 01:02:59,320
Speaker 1: Big Farmership periodically release quay ludes for a limited time,

1108
01:02:59,440 --> 01:03:03,560
Speaker 1: like Narco. Mick Ribs, Oh my god, Oh my god.

1109
01:03:04,440 --> 01:03:09,880
Speaker 1: Somebody tweeted, oh cool Boobs tweeted. M at cool Boobs tweeted.

1110
01:03:10,000 --> 01:03:13,160
Speaker 1: Was just reminded of the Staples logo reveal, and I

1111
01:03:13,200 --> 01:03:18,720
Speaker 1: guess this is a historical document, but it's like you

1112
01:03:18,880 --> 01:03:21,320
Speaker 1: just kind of have to watch it. But they take

1113
01:03:21,440 --> 01:03:24,240
Speaker 1: the L that has like the little bent down staple

1114
01:03:24,760 --> 01:03:28,600
Speaker 1: and then it like slowly, like everything else disappears. They

1115
01:03:28,720 --> 01:03:31,480
Speaker 1: zoom in on that L and then the L slowly

1116
01:03:31,600 --> 01:03:35,480
Speaker 1: like gets an erection so that it looks like a

1117
01:03:38,960 --> 01:03:42,200
Speaker 1: giant explodion. Is very strange. I highly recommend you go

1118
01:03:42,400 --> 01:03:45,000
Speaker 1: check it out. Also, the Staples logo was cool. I

1119
01:03:45,040 --> 01:03:46,680
Speaker 1: don't know why they messed with it. It was good.

1120
01:03:46,760 --> 01:03:51,120
Speaker 1: It was obviously staple. And then, uh, somebody tweeted a

1121
01:03:51,200 --> 01:03:56,080
Speaker 1: picture I think a photoshop its spirit Halloween costume, conservative

1122
01:03:56,120 --> 01:03:59,200
Speaker 1: guy Scared of Cities, and it's just a conservative looking

1123
01:03:59,280 --> 01:04:03,000
Speaker 1: dude with like a helicopter on his T shirt that

1124
01:04:03,040 --> 01:04:05,440
Speaker 1: says like hold the line and a flag on a

1125
01:04:05,480 --> 01:04:07,840
Speaker 1: shirt and it says I saw that thing on the news.

1126
01:04:08,200 --> 01:04:12,680
Speaker 1: Too many of those people there can't park forward super duty,

1127
01:04:13,160 --> 01:04:19,680
Speaker 1: not scared, bro, This is just a good uh. You

1128
01:04:19,760 --> 01:04:23,200
Speaker 1: can find me on Twitter at Jack Underscore O'Brien. You

1129
01:04:23,240 --> 01:04:25,520
Speaker 1: can find us on Twitter at Daily Zekeeist. We're at

1130
01:04:25,560 --> 01:04:28,000
Speaker 1: the Daily Zegheist on Instagram. We have a Facebook fan

1131
01:04:28,040 --> 01:04:30,200
Speaker 1: page on a website, Daily Zekeeist dot com where we

1132
01:04:30,280 --> 01:04:33,680
Speaker 1: post our episodes. On our footnotes, we link off to

1133
01:04:33,680 --> 01:04:36,040
Speaker 1: the information that we talked about in today's episode, as

1134
01:04:36,040 --> 01:04:38,120
Speaker 1: well as a song that we think you might enjoy. Miles,

1135
01:04:38,280 --> 01:04:40,280
Speaker 1: what song can we think people might names? Man? Time

1136
01:04:40,360 --> 01:04:45,360
Speaker 1: for some experimental hip hop from England. This is just

1137
01:04:45,560 --> 01:04:47,960
Speaker 1: a group. I don't know. They're called Baby Father, but

1138
01:04:48,080 --> 01:04:49,960
Speaker 1: if you know Dean Blunt, this is a project Dean

1139
01:04:50,000 --> 01:04:53,080
Speaker 1: Blend is working on and this track is called Penelope

1140
01:04:53,200 --> 01:04:55,360
Speaker 1: Freestyle to Beat. It's just like the second I started

1141
01:04:55,360 --> 01:04:57,120
Speaker 1: playing and I was like, oh, this instrumental is interesting

1142
01:04:57,560 --> 01:05:00,440
Speaker 1: and I always like any any experimental hip hop, so

1143
01:05:00,720 --> 01:05:03,600
Speaker 1: check this one out. The fantastic track Penelope free Style

1144
01:05:03,680 --> 01:05:06,280
Speaker 1: by baby Father. All right, we will link off to

1145
01:05:06,360 --> 01:05:08,840
Speaker 1: that in the footnotes. The days guys a production of

1146
01:05:08,920 --> 01:05:10,960
Speaker 1: I Heart Radio. For more podcasts for my heart Radio

1147
01:05:11,120 --> 01:05:13,320
Speaker 1: is the heart Radio app, Apple podcast or wherever you

1148
01:05:13,400 --> 01:05:15,080
Speaker 1: listen to your favorite shows. That is going to do

1149
01:05:15,160 --> 01:05:17,600
Speaker 1: it for us this morning, back this afternoon to tell

1150
01:05:17,640 --> 01:05:19,280
Speaker 1: you what is trending and we will talk to you

1151
01:05:19,320 --> 01:05:22,680
Speaker 1: all then. Bye bye m