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

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Speaker 1: Episode five of the Daily Like production of I 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 incretiousness, deep into It's Friday, November eleventh, eleven

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Speaker 1: eleven Veterans Day, you know, like it was at the

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Speaker 1: eleventh hour of the eleventh day of the eleventh month.

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Speaker 1: I used to play so many Veterans Day of things

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Speaker 1: at Forest Lawn Memorial because I was a school band.

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Speaker 1: Also National Sunday Day. You feel like they missed it.

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Speaker 1: But it's Sunday Day. Yeah, I mean for for a

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Speaker 1: ice cream Sunday Sunday. Okay, yeah, I should have put

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Speaker 1: that on a Sunday, right, But anyways, it's good. Friday

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Speaker 1: is a good day for ice cream Sundays, you know,

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Speaker 1: shout out to all the veterans out there, and yeah,

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Speaker 1: my kids are home from school, so it's it is

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Speaker 1: Veterans Day in this household. Did you ever did you

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Speaker 1: get I didn't really get Veterans Off still on high

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Speaker 1: school I went to and it was like one off

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Speaker 1: once I remember, and it wasn't there. I'm here for it.

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Speaker 1: I mean, kid, you need rest. I think that's the

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Speaker 1: main thing here for any day off. Yeah, that's why

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Speaker 1: I was like all Saints Day, like why don't you

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Speaker 1: like Catholic high school? And like fuck yes, all the Saints,

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Speaker 1: all the fleet and eleven plus eleven equals two eleven

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Speaker 1: eleven twenty two. So I mean there's like probably some

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Speaker 1: numerology ship that your audible numerologists would be happy to

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Speaker 1: talk to you about. Robbin from the rehearsal reach out

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Speaker 1: to him National Robin Day ended up on upright on

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Speaker 1: miracle status. Anyways, my name's Jack O'Brien, a k Crispity

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Speaker 1: crunch itty appples Jack. That is courtesy of my dumb brain.

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Speaker 1: Shout out to the listeners who chimed in sharing your

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Speaker 1: truth that you actually like mush apples, or that some

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Speaker 1: people are like, yeah, my my significant other likes red

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Speaker 1: delicious apple. That's a real problem. We I don't know.

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Speaker 1: I can't I can't deal, but I do want to

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Speaker 1: shout out Cassie who said, I'm so sorry to report

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Speaker 1: that I'm a soft apple stand in fact, I get

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Speaker 1: an apple that is too hard, I punch it. If

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Speaker 1: I get an apple that is too hard to punch it,

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Speaker 1: something I've done since I was a kid, saying it,

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Speaker 1: saying it out loud. Now it's embarrassing. I don't think

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Speaker 1: you should be embarrassed. Do your truth. If your preferred version,

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Speaker 1: your platonic ideal of an apple is just a bag

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Speaker 1: of apple sauce and an apple skin bag, good, good

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Speaker 1: for you. I'm glad to know for me that y'all exist.

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Speaker 1: The punching is interesting, though, Yeah, I mean, look, I'm

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Speaker 1: not going to psychoanalyze that, but you know what, go ahead,

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Speaker 1: you know, as long as they are the right texture

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Speaker 1: for you, get it how you need. I did start

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Speaker 1: psychoanalyzing all these people in my head. I was like,

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Speaker 1: I bet they had at a young age an apple

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Speaker 1: that wasn't ripe yet, and that like sucked them for

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Speaker 1: crispy apples forever, because now they're like, the only safe

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Speaker 1: apple is an apple that yields to my teeth immediately. Anyways,

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Speaker 1: I'm thrilled to be joined as always by my co host,

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Speaker 1: Mr Miles Miles Gray, And I'm sorry, but the Cold

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Speaker 1: Play a k s keep coming. Light produce up above,

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Speaker 1: have you once down below? When it's cereal, you just

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Speaker 1: let it go. But if you never check out, They'll

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Speaker 1: never know just what your cards were, and itch, will

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Speaker 1: godde your bones, oh home and ignited your bones, and

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Speaker 1: I will try to find my wallet. That's based on

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Speaker 1: the you know, terrible experience of for getting your wallet

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Speaker 1: at the grocery store. Do you put stuff back? Or

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Speaker 1: do just ditched the cart and vanish journey guided along

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Speaker 1: by a cold Play song another one that I don't know.

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Speaker 1: I'm starting to feel like maybe I just don't like

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Speaker 1: cold Play or have managed this is one of the

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Speaker 1: most over you for me. I didn't. I was I

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Speaker 1: really wasn't knowing what Coldplay was really till this song,

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Speaker 1: and then I was like, oh, this song that's in

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Speaker 1: every promo package for like a sporting event. They always

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Speaker 1: use it at the end with the lights will go.

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Speaker 1: Never mind. Anyway, we're doing the same conversation we did

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Speaker 1: when I did this a k last time. Shout out

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Speaker 1: to Piroke. Was this another? Is this the same Coldplay songs? Okay?

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Speaker 1: I was lying when I said I was gonna go

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Speaker 1: listen to it. I apologize, Miles. We are thrilled to

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Speaker 1: be joined in our third seat by a very funny

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Speaker 1: stand up comic, writer, actor, and host of the new

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Speaker 1: podcast Parenting as a joke. Please welcome to the show.

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Speaker 1: Oh Fear Eisenberg. Hello, Miles and Jack, Welcome. I am

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Speaker 1: I have a hardcore, hardcore crunchy apple stands. Yeah, as

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Speaker 1: I said it, I was like, you know what, that's

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Speaker 1: the apple is going to be very pleased. Twitter core

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Speaker 1: can be soft, but that outside better be crapy apple people,

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Speaker 1: what happened to you? Yeah? That is in your mind.

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Speaker 1: A soft apple would immediately signal to my brain something

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Speaker 1: is wrong with this, Like I don't continue a bite

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Speaker 1: when the first one isn't like if it's like, I'm

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Speaker 1: like yeah, and if you are hitting your fruit, you

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Speaker 1: need to take a deeper dive into your psyche of

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Speaker 1: what that's about. I actually appreciate that because I I

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Speaker 1: have like weird food rituals that I can't think of

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Speaker 1: right now, but like I I could totally if I

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Speaker 1: was into soft apples, I would be doing that. I

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Speaker 1: actually feel like it's not out of anger. It's just

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Speaker 1: like get the food exactly how you want it, and

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Speaker 1: you haven't like refined the process since child it when

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Speaker 1: first like I punch it? Yeah, yeah, I fear where

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Speaker 1: are you coming to us from? I'm coming to you

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Speaker 1: from Brooklyn, New York, hot of hotbed of fun. It's

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Speaker 1: good fun. And I'm hearing some sirens in the background.

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Speaker 1: Oh yeah, you know they're I like her medically seal

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Speaker 1: every opening of this entire apartment. Yet still, yeah, let

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Speaker 1: the Brooklyn in. You know. I feel like if we

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Speaker 1: were cutting to you in a like Marvel movie, and

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Speaker 1: it's like, how do we let them know that this

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Speaker 1: is truly Gotham city? This is truly Also, I feel like,

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Speaker 1: because I'm in Brooklyn, I'm just surrounded by podcasters. I'm

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Speaker 1: sure every single person here is like, y, it is funny. Yeah,

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Speaker 1: how often we're like where you like? Brooklyn? Totally noticed that? Yeah, exactly.

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Speaker 1: I wonder if anyone's ever been seen into a podcast

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Speaker 1: recorded in Brooklyn and heard another podcast they listened to

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Speaker 1: bleeding in through the wall like okay, wait a second

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Speaker 1: next to each other. Yes, it's happened to me. I

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Speaker 1: was talking to someone in a podcast because just like

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Speaker 1: you heard an ambulance, it was like just a really

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Speaker 1: loud motorcycle, but we both heard it. We're like, oh,

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Speaker 1: where do you live? And it was within the block. Yeah,

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Speaker 1: We're like we could have met in person, but now right, right, right, Yeah,

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Speaker 1: there'll be some fan who's like trying to hear the

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Speaker 1: same siren and it's like based on the Doppler effect

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Speaker 1: from this recording in that one I have and what

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Speaker 1: I've seen from radio calls around there to this intersection

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Speaker 1: like the seeing in Fugitive where they're like analyzing the

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Speaker 1: phone call. I could I could definitely see a podcast

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Speaker 1: fan like triangulating a location with that sort of science. Yeah. Absolutely.

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Speaker 1: If Hey, if we have the kind of peril social relationships,

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Speaker 1: I think we do get a better time to that.

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Speaker 1: All right, if you're we're going to get to know

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Speaker 1: you a little bit better in a moment. First, we're

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Speaker 1: gonna tell our listeners a couple of things we're talking about.

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Speaker 1: We're gonna just check in for a bracing cup of

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Speaker 1: hot Fox news. Cope, We're going to just just listen

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Speaker 1: to them freaking out about the results of the mid term.

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Speaker 1: We're gonna talk about the New York Times and how

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Speaker 1: they are covering the good news for progressives, which seems

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Speaker 1: like they're ignoring a lot of it. So we'll talk

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Speaker 1: about that. Then if we have time, we might even

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Speaker 1: get into a preview of a couple holiday classics in

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Speaker 1: the making coming from Netflix, all of that plenty more.

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Speaker 1: But first off, fair, we like to ask our guests,

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Speaker 1: what is something from your search history? Okay, So I'm

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Speaker 1: starting to travel again, you know, touring during doing stand up,

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Speaker 1: and because I haven't done it in a little while,

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Speaker 1: I find hotel rooms. I never loved them, but I

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Speaker 1: never thought about them, but now I'm I just I

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Speaker 1: want to make them better. Anyways, So I was looking

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Speaker 1: at like hotel room hacks, like how to make your

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Speaker 1: hotel of a better experience because I'm not staying in

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Speaker 1: for four seasons. Let me just point that out. Yeah

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Speaker 1: that though, you're like, because the Four Seasons is an

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Speaker 1: absolute horror show? Yeah, how do I dial up this

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Speaker 1: experience to make it like a little more comforting? Right right? Yeah? No,

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Speaker 1: I'm hoping for a Hampton in you know what I'm saying.

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Speaker 1: So one of the things I find, especially if you're

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Speaker 1: talking all the time, is like humidity. I find hotel

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Speaker 1: rooms super dry. So I was like, there's got to

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Speaker 1: be some people talking about hotel humid of higher hacks. Yeah. Yeah,

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Speaker 1: turns out like there's many people who tackled this issue,

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Speaker 1: right the internet comes through where exactly where we would

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Speaker 1: expect to like what is the most what is the

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Speaker 1: one hotel room hack that, like, what is the one

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Speaker 1: that you are Now you're like, okay, I'm definitely bringing

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Speaker 1: that into So I kind of want to try this

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Speaker 1: humidifier one. So you have to have binder clips, Like

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Speaker 1: you need to bring a clip with you, some sort

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Speaker 1: of clip, and then you're supposed to grab one of

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Speaker 1: their hand towels or face towels and just soak it,

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Speaker 1: ring it out and then clip it to the outside

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Speaker 1: of whatever air event is in your room. And it

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Speaker 1: should basically, as they said, make the air like moist

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Speaker 1: and uh yeah moistened feel good. So it seems it

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Speaker 1: seems like an over promise there, sure, but I'm gonna trying.

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Speaker 1: In my mind, I would do something that would cause

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Speaker 1: like some terrible plumbing things like yeah, I just need

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Speaker 1: the shower running all night right full steam. What I

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Speaker 1: assumed was going to be the answer, And in fact,

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Speaker 1: I've done that before. Oh yeah, I do that just

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Speaker 1: for all my clothes. I'm like, time to go to

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Speaker 1: the dry leader. Oh yeah, that's right, Yeah, I do

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Speaker 1: that for clothes. If I heard that somewhere and have

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Speaker 1: just assumed that it was, you know, gospel. I mean,

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Speaker 1: what a colossal waste of water, and we'll like, let's

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Speaker 1: do it. Come. Yeah, these rooms aren't so dry. I

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Speaker 1: wouldn't have to use up all the portable water in

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Speaker 1: the area. Thank you, thank you. And also one time

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Speaker 1: I got a lot of splash on my on my

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Speaker 1: clothes and they were too wet to wear. So they're like,

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Speaker 1: I didn't get p on these pants. I was trying

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Speaker 1: to steam them in the bathroom. They're like, okay, dude.

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Speaker 1: No one even asked, Oh, since you travel so much.

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Speaker 1: I was asked because as somebody who's been lived in

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Speaker 1: a lot of hotels and work and things like that,

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Speaker 1: do you have a relationship with Mario Lopez? You know,

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Speaker 1: always this is I've always like, how much money are you? An?

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Speaker 1: I'm like, I want to know. I don't who else

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Speaker 1: has that kind of ubiquity, you know what I mean? Like,

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Speaker 1: if you turn on a fucking TV in the United

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Speaker 1: States in a hotel, the first fucking guy you're gonna

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Speaker 1: hear it's like, Hey, it's Mario Lopez. I'm like talking

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Speaker 1: to you about the hotel and the brand and all

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Speaker 1: the great things, so uplifting, how the television works. Yeah,

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Speaker 1: I just there's something I feel it's wild. I mean,

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Speaker 1: I'm really like, were you paid seventeen million dollars or

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Speaker 1: are you mad because you got paid like six bucks? Whatever?

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Speaker 1: What is what something that you think is overrated? Okay,

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Speaker 1: probably unpopular, but I'm I'm doubling down this, especially because

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Speaker 1: I live in Brooklyn. Beyond Burger not a fan, Okay,

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Speaker 1: Like I'm am I fan of a plant based diet

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Speaker 1: because of all the good things that comes with it,

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Speaker 1: including health and probably uh doing the best thing you

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Speaker 1: can for this planet. Yes, but Beyond Burger is grown,

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Speaker 1: let's just say, in a lab, right, Yeah, and that

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Speaker 1: bothers you. Yeah yeah, because part of you just well

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Speaker 1: you know, and you know when you cut it Beyond Burger,

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Speaker 1: it bleeds. So that's like that's the thing why it's

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Speaker 1: sort of tasty. It's like mimicking meat. Anyways. I just

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Speaker 1: think the whole thing is I think we hail it

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Speaker 1: as to be this kind of something that is so

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Speaker 1: like we say plant based makes it sound like it

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Speaker 1: was grown and cut, but that has grown in a lab.

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Speaker 1: They figured out how to make it bleed. You know,

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Speaker 1: because all the vegetarians are like, you know what, I'm

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Speaker 1: miss murder exactly. I can't watch an artichoke card. Stop,

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Speaker 1: do we know what the blood is from? Like? What

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Speaker 1: have they even? In red meat it's called mild globin

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Speaker 1: or whatever comes out. Yeah, so they mean, I know

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Speaker 1: it's not blood, but like what how do they how

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Speaker 1: do they create such an effect? I'm I mean, I

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Speaker 1: think the nicest way to say it is that it

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Speaker 1: is like extracted and then injected. But it might just

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Speaker 1: be a chemic co reaction. I don't know, mm hmm. Yeah.

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Speaker 1: I think there's there's something they've figured out. I mean,

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Speaker 1: I think, yeah, it's the the draw that I think

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Speaker 1: for some people is more for like people who would

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Speaker 1: never like who don't normally eat plant based and it's like, hey, idiot,

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Speaker 1: you like burger right, yeah, okay, fucking try this? Oh

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Speaker 1: wow yeah and look that wasn't fucking beef. Can you

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Speaker 1: do that for a couple of days a week so

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Speaker 1: we don't fuck this whole planet over? But there is

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Speaker 1: I feel like there is, like I've I've read that there.

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Speaker 1: I guess like the appeal is like maybe starting to

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Speaker 1: wane um because people just get into other kinds of

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Speaker 1: plant based diets. But yeah, yeah, Also it's not like

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Speaker 1: it's less expensive. You know, the the Kobe beef burger

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Speaker 1: is eleven dollars and then the Beyond Burger is eleven fifty.

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Speaker 1: You're like, right, I think I feel like they're Yeah,

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Speaker 1: it hails from a like technocratic impulse where like technology

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Speaker 1: fixes everything, We're we're good here that I think it's

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Speaker 1: probably in the process of dying out a little bit,

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Speaker 1: like it's you know, it's been it's been on the

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Speaker 1: decline for a long time. We we talked about it

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Speaker 1: with respect to like Iron Man and Elon Musk, like

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Speaker 1: that that whole impulse. But I don't know, I made

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Speaker 1: peace with the fact that every food that I've ever

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Speaker 1: eaten was constructed in a lab. But because like that's

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Speaker 1: like food, Nacho cheese, Derito's were have been have had

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Speaker 1: more like R and D and like hours of education

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Speaker 1: dumped into their creation that like to make sure that

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Speaker 1: their mouth feel is like satisfying and yet leaves you

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Speaker 1: wanting more. And I'm like, yeah, I mean, this is

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Speaker 1: this is what we do. This is the height of

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Speaker 1: Western civilization as currently defined. Unfortunately, so I might as

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Speaker 1: well partake in it and like the Beyond I guess

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Speaker 1: the fact that the Beyond Burger kind of no matter

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Speaker 1: how hard I tried, no matter where I look, there's

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Speaker 1: no nacho che Doritos on like artisanal menus. So I

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Speaker 1: I feel you there though, Soon's right, well, like it's

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Speaker 1: in like farm farm to table fresh restaurants with Beyond Burger,

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Speaker 1: and it's like this, this was might as well be

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Speaker 1: delivered to you by someone in a white coat. But

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Speaker 1: it's yeah, Dorito's. It's the Dorito's at the plant based diet.

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Speaker 1: I mean that's true. I've never opened up in my

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Speaker 1: entire life bag of Doritos and thought, are these old? Right?

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Speaker 1: Like fresh off the whatever press? Can I conceptualize even

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Speaker 1: four of the ingredients that are on the back? Sugar

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Speaker 1: that's the only one I can guarantee? Hey, corn, corn,

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Speaker 1: There you go. What is something you think is underrated? Okay,

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Speaker 1: another food thing? And I know a lot of people

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Speaker 1: talk about food things, but here we go. On election night,

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Speaker 1: I was too nervous to cook, so we ardered pizza.

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Speaker 1: We kind of over ordered pizza, which is what I

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Speaker 1: love to do. And then it's been a while, but

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Speaker 1: the next morning, I was rushed and I just took

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Speaker 1: a piece out of the fridge of cold pizza with

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Speaker 1: the cheese in that sort of hard sheath that it

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Speaker 1: was made on the top, and I shoved it in

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Speaker 1: my mouth and I was like, this is heaven. But

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Speaker 1: this I mean, and I was like, I could sell

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Speaker 1: this for as a breakfast at an artisanal farm to

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Speaker 1: table joint in Brooklyn because it's so good. And he

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Speaker 1: could even just double down on what it is, because

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Speaker 1: that it would seem like ironic to be like cold pizza. Yeah,

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Speaker 1: he caught about last night, and what's that. It's like,

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Speaker 1: it's a cold pizza slice. Man's just candle wax hard.

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Speaker 1: That's that's what you're here for. I love cold pizza.

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Speaker 1: I mean it was like it's for the longest time

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Speaker 1: I would either I hated how the microwave would just

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Speaker 1: turn the fucking crust to like a weapon. And then

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Speaker 1: once I started doing the show with Jack, he swears

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Speaker 1: by his pan method of reheating, so like, I've started

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Speaker 1: to reheat my pizza slices better, but I still love

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Speaker 1: like would just rip it out of the zip block

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Speaker 1: because you threw them all the slices in a zip

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Speaker 1: block the night before and just have that first slice. Yeah,

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Speaker 1: it's good. It's like the ingredients found each other in

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Speaker 1: that fridge at night right, exactly up. That's a higher quality.

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Speaker 1: All right, let's take a quick break. We'll be right back.

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Speaker 1: Let's talk some news and we're back, and I think

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Speaker 1: it's time to check in with Fox News again. It's

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Speaker 1: it's always nice. Look how they're reacting to bad news

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Speaker 1: for their party. Love a little fascist freak out. I

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Speaker 1: think we can have a little Fox News rage as

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Speaker 1: a little treat for everybody this Friday morning. Why not,

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Speaker 1: because they are still angrily dealing with what the heck

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Speaker 1: happened in these mid terms. I thought it was a

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Speaker 1: red wave. Here's a fantastic supercut from Katabu on Twitter.

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Speaker 1: I can't believe John Federman wall this is in fact

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Speaker 1: bad for the Democrats. They're gonna misread. This is like, oh,

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Speaker 1: we want Joe Biden was not punished this morning. Had

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Speaker 1: there been a big red wave, everybody would be going

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Speaker 1: blame Joe Biden. Can't say that. You can't say that

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Speaker 1: right now. It's still a win for pro lifers. This

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Speaker 1: new generation is totally brandwashed. When we just owned the Libs.

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Speaker 1: We didn't win those races. This is not a surprise.

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Speaker 1: We knew it would be extremely tight. We got the

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Speaker 1: Red Way, the Red Tide, whatever it was, it doesn't

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Speaker 1: matter at this point. They're always going to spend things

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Speaker 1: against this. Single women and voters under forty have been

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Speaker 1: captured by Democrats. So we need these ladies to get married. Okay,

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Speaker 1: I've been saying that for years, right, Yeah, So that's

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Speaker 1: they're they're starting like they're having a they're having an

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Speaker 1: interesting week. There was one where Tucker Carlson, I think

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Speaker 1: night last night or the day before, he was like, now,

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Speaker 1: what happens to all these people who we gave millions

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Speaker 1: of dollars to? Like he's he's so mad at likes

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Speaker 1: going to I don't know what it is. I think

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Speaker 1: I think he's more speaking on behalf of probably these

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Speaker 1: mega downers that he convinced to go all in on

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Speaker 1: these mid terms, like this terrible fucking point hand and

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Speaker 1: is now trying to put put it at someone else's

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Speaker 1: feet when let's be real, like him and Hannity have

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Speaker 1: some pretty outsized power in terms of how the GOP

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Speaker 1: might speak. I mean, can we also just have a

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Speaker 1: moment to recognize that. I guess it's gen z. They

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Speaker 1: do not do surveys. Too many surveys, too many surveys

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Speaker 1: already in their life. They're like, I'm not, dude, a survey. Yeah,

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Speaker 1: like I don't pick up calls from my fucking Graham. Yeah, survey,

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Speaker 1: we'll show up. Yeah. I mean, although I you know,

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Speaker 1: I do think just yelling, yelling at your viewers is

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Speaker 1: the way that they've always energized their party, So I

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Speaker 1: would really which I feel like it's all part of this,

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Speaker 1: you know, basically dominant submissive relationship they all have with

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Speaker 1: each other, and now they're just it's like, how do

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Speaker 1: you what are you doing? You guys? Bad bad bad bad,

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Speaker 1: and so everyone could be like okay, and like it

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Speaker 1: will it will actually energize them. So I'm a little

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Speaker 1: bit I I just see that, and I get I

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Speaker 1: want to revel in it, but it concerns me. Well.

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Speaker 1: I think it is interesting though, is how few people

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Speaker 1: who like Republicans actually did lose elections. They didn't go

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Speaker 1: straight to the full shit thing, which is interesting. I'm

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Speaker 1: like a lot of people suspect that it could be

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Speaker 1: because of like the lawsuits that are hanging around, and

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Speaker 1: like potential other legal issues that might arise from that

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Speaker 1: kind of like election denialism, that may have hampered the

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Speaker 1: appetite to do that. But that was one thing I

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Speaker 1: was fully like, Okay, because before we heard like people

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Speaker 1: in certain countries like we already want an audit of

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Speaker 1: the vote, like before election day. So that felt like

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Speaker 1: a preview of things to come. But it hasn't quite

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Speaker 1: materialized in the way I had feared. Yeah, and that's

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Speaker 1: super cut. I forget who said it, but just the

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Speaker 1: and Biden wasn't punished totally sounds Yeah, that was totally

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Speaker 1: sounds like when the Grinch is mad that the Christmas

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Speaker 1: still went on. Yeah, it came with no ribbons, came

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Speaker 1: with no books. Yeah, here's the sound of singing. Yeah. Right,

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Speaker 1: So let's talk about because I also feel like there's

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Speaker 1: a inability to cope with what we've seen in some

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Speaker 1: you know, more local but very like yeah, I guess

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Speaker 1: also in the Fetterman race, but like progressive values had

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Speaker 1: a really good day at the pole, and specifically like

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Speaker 1: the crime wave narrative that I think a lot of

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Speaker 1: the mainstream media, even though they're supposedly liberal they really

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Speaker 1: bought into this that like crime wave is going to

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Speaker 1: scare voters. We must democrats, must double down on police,

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Speaker 1: must do this, and like it's been just a persistent

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Speaker 1: narrative ever since Chase A. Bootine in San Francisco, like

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Speaker 1: was recalled. The media has been like progressive politics is

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Speaker 1: a loser, it's a it's a wave, We're all fucked,

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Speaker 1: and that that just really hasn't born out. But we're

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Speaker 1: still not really seeing that messaging breakthrough. No, it's it's

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Speaker 1: interesting again, no one's really talking. There were a lot

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Speaker 1: of progressive days that either were elected or reelected across

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Speaker 1: the country, you know, like this is like like Philly, Chicago, Iowa, Texas,

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Speaker 1: Oklahoma City, like a whole assortment of states from red

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Speaker 1: to purple to blue. You know, they had it all

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Speaker 1: and Oklahoma City. I just want to point out to

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Speaker 1: not necessarily a place or like Iowa, Texas where the

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Speaker 1: shorthand of the media is like, oh woke bastion, Like

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Speaker 1: you know, San Francisco, although like that one with Boudine

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Speaker 1: was a little bit of an out liar because San

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Speaker 1: Francisco is like a little more of a unique quantity

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Speaker 1: when you look at electoral politics billionaires like per square

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Speaker 1: mile of any locations. Most people are like, it's all dreadlocks,

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Speaker 1: and so like, no, it isn't. But anyway, in many

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Speaker 1: of these areas though, where progressive days were elected or

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Speaker 1: reelected there, they also have significant minority populations, and those

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Speaker 1: are the communities that tend to experience much of the

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Speaker 1: crime firsthand. So they are truly the ones too when

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Speaker 1: they're voting, are the ones seeing like, man, this kind

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Speaker 1: of fucked up policy does not work. In fact, it's

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Speaker 1: so regressive it actually just feels like people are just

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Speaker 1: held in captivity for money, which they are. I want

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Speaker 1: to put this quote from law professor Laura bas Alone,

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Speaker 1: who's from the University of San Francisco, was on Democracy

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Speaker 1: Now this morning. She said, was sort of describing what

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Speaker 1: is happening. Is this quote this understanding said, I think

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Speaker 1: what all this tells you is that this experiment, this

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Speaker 1: experiment with criminal justice reformed this understanding that we can't

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Speaker 1: incarcerate our way to safety, that the kind of cruelty

424
00:24:44,760 --> 00:24:47,159
Speaker 1: that some of these punishments are exerting on people to

425
00:24:47,280 --> 00:24:50,000
Speaker 1: no good effect. And then the other additional problems like

426
00:24:50,040 --> 00:24:53,960
Speaker 1: wrongful conviction or just criminalizing poverty so that rich people

427
00:24:53,960 --> 00:24:56,560
Speaker 1: who are dangerous can buy their way out, but poor

428
00:24:56,600 --> 00:24:59,880
Speaker 1: people have to stay inside. That there are a lot

429
00:25:00,080 --> 00:25:04,119
Speaker 1: voters who realize that none of these policies are humane,

430
00:25:04,440 --> 00:25:08,960
Speaker 1: just or effective. Yeah. Well, and I think just also,

431
00:25:09,800 --> 00:25:13,080
Speaker 1: like just let's turn a complete blind eye to all

432
00:25:13,280 --> 00:25:16,480
Speaker 1: the white color crime, like it is so focused so

433
00:25:16,560 --> 00:25:20,160
Speaker 1: specific on you know, basically a poor person, a poor

434
00:25:20,280 --> 00:25:23,719
Speaker 1: or a crazy person is going to shoot you. That's it, right,

435
00:25:24,320 --> 00:25:27,359
Speaker 1: rob you and shoot your assault you and shoot you

436
00:25:27,400 --> 00:25:29,720
Speaker 1: whatever that is, and that that's it, and and why

437
00:25:29,840 --> 00:25:31,600
Speaker 1: is that? You know, well that gets a little muddy.

438
00:25:32,080 --> 00:25:35,159
Speaker 1: But all all of the white color crime, all of

439
00:25:35,200 --> 00:25:37,600
Speaker 1: that is just always sort of like no, no, that's

440
00:25:37,720 --> 00:25:41,400
Speaker 1: under control, which is because you could, yeah, like you could,

441
00:25:41,480 --> 00:25:44,480
Speaker 1: you could probably drop pretty interesting lines to like corporate

442
00:25:44,520 --> 00:25:48,399
Speaker 1: profit hearing and poverty to the people they're like and

443
00:25:48,440 --> 00:25:52,280
Speaker 1: then those people are like, oh, I'm poor and violent.

444
00:25:52,760 --> 00:25:55,479
Speaker 1: I think the real violence is actually happening in the

445
00:25:55,480 --> 00:25:58,360
Speaker 1: c suites of a lot of these corporations. But I mean,

446
00:25:58,480 --> 00:26:01,399
Speaker 1: I was just in, uh, I was in took my

447
00:26:01,680 --> 00:26:04,440
Speaker 1: son because it was day off school to the mat

448
00:26:04,800 --> 00:26:06,760
Speaker 1: and just looking, you know, there's still some of the

449
00:26:06,800 --> 00:26:09,320
Speaker 1: galleries are the Sackler Galleries. And we all know about

450
00:26:09,320 --> 00:26:13,440
Speaker 1: the Sacklers and their involvement in profiting so highly off

451
00:26:13,520 --> 00:26:17,880
Speaker 1: of oxycode and and selling opiates and marketing that, and

452
00:26:17,960 --> 00:26:21,760
Speaker 1: you know, I think there was there was definitely something

453
00:26:22,160 --> 00:26:25,480
Speaker 1: talked about were those people? Yeah, is why isn't that

454
00:26:25,520 --> 00:26:28,880
Speaker 1: a story every single day? You know? Of course, I think, yeah,

455
00:26:28,920 --> 00:26:32,240
Speaker 1: when we have such like media consolidation with the billionaire class,

456
00:26:32,280 --> 00:26:34,280
Speaker 1: like they know, it's like, dude, that's the people, the

457
00:26:34,320 --> 00:26:36,480
Speaker 1: guys who owned this place, they might not want stories

458
00:26:36,520 --> 00:26:39,719
Speaker 1: like that coming out of talk about the poor people,

459
00:26:39,840 --> 00:26:44,280
Speaker 1: all right. They affectively marketed and created a problem that

460
00:26:44,400 --> 00:26:47,919
Speaker 1: is still killing hundreds of thousands of people, like killing

461
00:26:47,920 --> 00:26:51,080
Speaker 1: people every day in the local media. And instead the

462
00:26:51,119 --> 00:26:54,240
Speaker 1: local media is focused on like too much shoplifting and CBS.

463
00:26:54,800 --> 00:26:57,320
Speaker 1: Oh yeah. And I obviously I live in New York,

464
00:26:57,520 --> 00:26:59,919
Speaker 1: so that is a place that is the story of

465
00:27:00,000 --> 00:27:04,040
Speaker 1: crime always exists. And I know people who some of

466
00:27:04,040 --> 00:27:07,440
Speaker 1: my families in Canada, but even other places, they're always like, god,

467
00:27:07,480 --> 00:27:10,120
Speaker 1: I got New York must be so scary right now,

468
00:27:10,680 --> 00:27:15,240
Speaker 1: And I'm like it is that That was one of

469
00:27:15,240 --> 00:27:18,040
Speaker 1: the social media responses I saw the people on you know,

470
00:27:18,240 --> 00:27:21,160
Speaker 1: l A had a lot of progressive candidates do very

471
00:27:21,160 --> 00:27:26,240
Speaker 1: well and progressive ballot measures, and the existing sheriff get

472
00:27:26,359 --> 00:27:30,639
Speaker 1: voted out, like definitively, and I saw a lot of

473
00:27:30,640 --> 00:27:32,760
Speaker 1: people being like, well, you must be the only person

474
00:27:32,840 --> 00:27:36,200
Speaker 1: from l A who hasn't been mugged or robbed this year.

475
00:27:36,480 --> 00:27:39,040
Speaker 1: And I've been here my whole life family. Yeah. Never,

476
00:27:39,320 --> 00:27:42,680
Speaker 1: it's we're we're good here. You're just seeing Fox News

477
00:27:42,840 --> 00:27:48,600
Speaker 1: is of Los Angeles. It's it's wild how much Fox

478
00:27:48,640 --> 00:27:51,600
Speaker 1: News focuses on like very specific cities and like getting

479
00:27:51,600 --> 00:27:54,200
Speaker 1: a narrative going what has to because it's saying, look

480
00:27:54,280 --> 00:27:57,680
Speaker 1: what happens in the cities where these libs live. They

481
00:27:57,680 --> 00:27:59,760
Speaker 1: think they know it all, and there's ship on the

482
00:27:59,760 --> 00:28:02,359
Speaker 1: ground out like right, that's really what they're all trying.

483
00:28:02,480 --> 00:28:04,800
Speaker 1: And it's so bad. And it's funny because there are

484
00:28:04,880 --> 00:28:07,679
Speaker 1: so many like boomer tweets where people are like, oh,

485
00:28:07,680 --> 00:28:09,960
Speaker 1: like you see like a post about crime in like

486
00:28:09,960 --> 00:28:11,879
Speaker 1: New York and they're like, I've always wanted to go

487
00:28:11,960 --> 00:28:14,680
Speaker 1: back to New York City, you know, but I guess

488
00:28:14,760 --> 00:28:17,199
Speaker 1: that's never gonna happen with the way things look. I

489
00:28:17,280 --> 00:28:19,600
Speaker 1: just I just I cared too much about my safety.

490
00:28:19,640 --> 00:28:22,080
Speaker 1: I'm like, you y'all are really eating this ship up.

491
00:28:22,359 --> 00:28:24,040
Speaker 1: Yeah yeah, and you know, for those of us who

492
00:28:24,040 --> 00:28:26,320
Speaker 1: live here, we're like, good keep up, keep that pr

493
00:28:26,400 --> 00:28:29,800
Speaker 1: going out because we need less people. Yeah exactly. Yeah,

494
00:28:29,840 --> 00:28:31,320
Speaker 1: you want you, yeah, you want something like out of

495
00:28:31,359 --> 00:28:33,199
Speaker 1: town and be like maybe I'll go to Brooklyn and

496
00:28:33,240 --> 00:28:36,520
Speaker 1: you want their first I want to be like, no,

497
00:28:36,600 --> 00:28:40,040
Speaker 1: I mean, I remember before the pandemic. You know, I've

498
00:28:40,040 --> 00:28:42,200
Speaker 1: lived your twenty years and just before the pandemic, sitting

499
00:28:42,200 --> 00:28:45,400
Speaker 1: on a subway and just watching you know what, I'm

500
00:28:45,440 --> 00:28:49,200
Speaker 1: just gonna call very entitled tourists who you know, they

501
00:28:49,200 --> 00:28:52,200
Speaker 1: were a little too casual with their New York experience

502
00:28:52,240 --> 00:28:54,479
Speaker 1: on the subway, and I just want to just like,

503
00:28:54,520 --> 00:28:56,360
Speaker 1: I don't want anyone to be afraid, but I was like,

504
00:28:56,480 --> 00:28:59,520
Speaker 1: shouldn't you be just a little more afraid? Like you

505
00:28:59,520 --> 00:29:03,760
Speaker 1: don't know the place you're visiting? You're visiting right, seriously?

506
00:29:04,920 --> 00:29:07,760
Speaker 1: But so the New York Times I want to specifically

507
00:29:07,800 --> 00:29:12,160
Speaker 1: call out for their lack of coverage and not not

508
00:29:12,240 --> 00:29:15,640
Speaker 1: just lack of coverage of like this progressive movement and

509
00:29:15,760 --> 00:29:19,680
Speaker 1: grassroots movement that we're seeing, like come through and start

510
00:29:19,760 --> 00:29:23,240
Speaker 1: to show real promise in some of these local elections.

511
00:29:23,440 --> 00:29:26,160
Speaker 1: And you know, in the big what was supposed to

512
00:29:26,200 --> 00:29:30,360
Speaker 1: be like the focus of the election night, what with

513
00:29:30,480 --> 00:29:34,400
Speaker 1: Fetterman defeating Oz. But like there, I don't I don't

514
00:29:34,440 --> 00:29:37,280
Speaker 1: feel like they've really figured out how to spin that.

515
00:29:37,720 --> 00:29:40,840
Speaker 1: And to that point, The New York Times the day

516
00:29:40,880 --> 00:29:45,400
Speaker 1: after the election published a piece in the opinion section,

517
00:29:45,680 --> 00:29:49,160
Speaker 1: but it was very much couched in, like here statistics

518
00:29:49,160 --> 00:29:51,440
Speaker 1: and here are the facts, and we talked to posters

519
00:29:51,440 --> 00:29:55,720
Speaker 1: and a Harvard sociologists. The article is titled for Republicans,

520
00:29:56,080 --> 00:30:00,800
Speaker 1: crime pays no matter what else happens, And the entire

521
00:30:01,040 --> 00:30:05,880
Speaker 1: premise of the article is that the Republicans really doubled

522
00:30:05,880 --> 00:30:09,600
Speaker 1: down on crime in this election. I'm just gonna read

523
00:30:09,600 --> 00:30:14,160
Speaker 1: a quote like they quote a Democratic polster is reinforcing

524
00:30:14,240 --> 00:30:17,280
Speaker 1: this point that like it's a winning it's a winner

525
00:30:17,320 --> 00:30:20,800
Speaker 1: for Republicans and a loser for Democrats. And this is

526
00:30:20,840 --> 00:30:23,719
Speaker 1: a quote from a poster. The mid terms will be

527
00:30:23,800 --> 00:30:27,000
Speaker 1: remembered as a toxic campaign, but an effective one in

528
00:30:27,080 --> 00:30:31,719
Speaker 1: labeling Democrats as pro crime, Greenberg wrote in How Democrats

529
00:30:31,760 --> 00:30:37,480
Speaker 1: Mishandled Crime a November three American Prospect article when voters

530
00:30:37,480 --> 00:30:39,880
Speaker 1: in our survey were asked what they feared the most

531
00:30:39,920 --> 00:30:43,520
Speaker 1: if Democrats win full control, and then like just chose

532
00:30:43,560 --> 00:30:46,160
Speaker 1: crime and homelessness out of control. You know, all all

533
00:30:46,240 --> 00:30:49,840
Speaker 1: of the talking points that go along with this, But

534
00:30:49,920 --> 00:30:54,520
Speaker 1: the article just I think they they wrote it before

535
00:30:54,840 --> 00:30:58,320
Speaker 1: the election results and just removed a couple of the

536
00:30:58,360 --> 00:31:02,680
Speaker 1: more strongly worded part. It's because they even mentioned Pennsylvania.

537
00:31:02,880 --> 00:31:06,120
Speaker 1: The Republican focus on crime is reflected in spending data

538
00:31:06,160 --> 00:31:09,160
Speaker 1: on November three, and the reason Republican attacks on crimer

539
00:31:09,240 --> 00:31:12,920
Speaker 1: so potent, Lee Jao, a reporter at Fox, Republicans have

540
00:31:12,960 --> 00:31:16,000
Speaker 1: spent a hundred and fifty seven million on crime related ads,

541
00:31:16,480 --> 00:31:19,560
Speaker 1: and the breakdown is even starker in the Pennsylvania Senate race,

542
00:31:19,600 --> 00:31:22,760
Speaker 1: where Republicans have spent nearly twelve million on crime ads

543
00:31:22,760 --> 00:31:25,600
Speaker 1: compared to two point five million on the economy and inflation.

544
00:31:26,160 --> 00:31:29,040
Speaker 1: And they don't go on to mention that that was

545
00:31:29,240 --> 00:31:33,480
Speaker 1: a loser, that was a losing strategy, and it just

546
00:31:34,000 --> 00:31:36,160
Speaker 1: it goes down like they go they go down to

547
00:31:36,320 --> 00:31:39,720
Speaker 1: interview like Paul the gala and be he's like it

548
00:31:39,760 --> 00:31:42,320
Speaker 1: worked for Clinton. They just need to be really tough

549
00:31:42,360 --> 00:31:45,840
Speaker 1: on crime and double down on policing and the death

550
00:31:45,880 --> 00:31:50,840
Speaker 1: penalty and just all these like old school like nineties

551
00:31:50,920 --> 00:31:55,320
Speaker 1: political to work after the riots. Yeah, like you know

552
00:31:55,360 --> 00:31:56,840
Speaker 1: what I mean, like, what the what the funk are

553
00:31:56,880 --> 00:31:59,960
Speaker 1: we talking? Yeah, then maybe when people were ignorant to

554
00:32:00,040 --> 00:32:04,200
Speaker 1: ship like it's so weird. I'm wondering when the new

555
00:32:04,320 --> 00:32:06,760
Speaker 1: like when all corporate media, like, I mean, they're never

556
00:32:06,800 --> 00:32:09,600
Speaker 1: going to be like they've really shown they are so

557
00:32:09,680 --> 00:32:12,640
Speaker 1: out of touch. Nothing they said is just is in

558
00:32:12,720 --> 00:32:15,640
Speaker 1: touch with anything. The amount of red wave coming, red

559
00:32:15,680 --> 00:32:18,720
Speaker 1: wave come in coverage on the New York Times like

560
00:32:18,760 --> 00:32:21,720
Speaker 1: this was this was an article from what October nine

561
00:32:21,960 --> 00:32:25,240
Speaker 1: Democrats feared Red October has arrived. Many Democrats hoped it

562
00:32:25,240 --> 00:32:27,640
Speaker 1: would be a weird election. But with election day just

563
00:32:27,680 --> 00:32:31,240
Speaker 1: three weeks away, the big terms aren't shaping up that way.

564
00:32:31,680 --> 00:32:35,960
Speaker 1: And but let's pretend that motivated people. Let's just pretend

565
00:32:36,080 --> 00:32:38,840
Speaker 1: that it was there was some potential, and let's just pretend.

566
00:32:39,160 --> 00:32:41,440
Speaker 1: You know, even in New York, where if you were

567
00:32:41,440 --> 00:32:43,600
Speaker 1: a Democrat, people are always like, oh, your vote, and

568
00:32:43,720 --> 00:32:46,200
Speaker 1: you know it counts, but it doesn't really count. You know.

569
00:32:46,360 --> 00:32:49,800
Speaker 1: I was at a show with a bunch of people

570
00:32:49,800 --> 00:32:52,120
Speaker 1: that work in politics, and they were like, you, every

571
00:32:52,200 --> 00:32:55,880
Speaker 1: vote is going to count tomorrow, Okay, yeah, yeah, And

572
00:32:56,640 --> 00:32:59,200
Speaker 1: I'm a nw to voting so I just became an

573
00:32:59,200 --> 00:33:02,440
Speaker 1: American citizen recently, but I was definitely gonna do it. Thanks.

574
00:33:02,880 --> 00:33:05,480
Speaker 1: But I do feel I haven't seen the note the

575
00:33:05,560 --> 00:33:07,760
Speaker 1: numbers on the turnout, but I felt like it was

576
00:33:08,440 --> 00:33:12,160
Speaker 1: really good. So I don't like that we are driven

577
00:33:12,200 --> 00:33:15,840
Speaker 1: by fear. Yeah, I mean New York was a little different.

578
00:33:15,840 --> 00:33:18,120
Speaker 1: It wasn't great for Democrats, which a lot of people

579
00:33:18,160 --> 00:33:22,120
Speaker 1: were surprised because the party ended up fighting a bunch

580
00:33:22,120 --> 00:33:25,280
Speaker 1: of like left like candidates on the left, like spent

581
00:33:25,360 --> 00:33:29,600
Speaker 1: more energy fighting candidates on the left than like attacking

582
00:33:29,760 --> 00:33:33,560
Speaker 1: like this crime like Lee's Eldon's crime wave insistence, which

583
00:33:33,600 --> 00:33:36,880
Speaker 1: motivated a lot of Republicans to come out, like in

584
00:33:36,920 --> 00:33:39,360
Speaker 1: an interesting way, because I think that's where New York

585
00:33:39,400 --> 00:33:41,800
Speaker 1: is a little different, because it is so blue. Every

586
00:33:41,840 --> 00:33:46,320
Speaker 1: Republicans like exactly get them all out, like they fully

587
00:33:46,320 --> 00:33:48,160
Speaker 1: turned up. While I was like, it's fine, I don't know,

588
00:33:48,440 --> 00:33:50,240
Speaker 1: New York is not that blue. By the way. New

589
00:33:50,280 --> 00:33:54,360
Speaker 1: York is first of all, historically like there they've been

590
00:33:54,480 --> 00:33:57,600
Speaker 1: like they were pro slavery, at the beginning of like

591
00:33:57,640 --> 00:34:00,640
Speaker 1: they when it was you know, the Dutch East Indian

592
00:34:01,000 --> 00:34:04,240
Speaker 1: colony founding it, and like that kind of reverberated down

593
00:34:04,240 --> 00:34:08,440
Speaker 1: through the politics. There's a lot of Republican mayors and

594
00:34:08,480 --> 00:34:12,040
Speaker 1: ship there's a former chief of police mayor, like New

595
00:34:12,120 --> 00:34:15,600
Speaker 1: York City has like very you're you're right, it's like

596
00:34:15,719 --> 00:34:19,800
Speaker 1: very specific and unexpected politics that don't really fit into

597
00:34:19,880 --> 00:34:22,120
Speaker 1: the overall narrative. I mean more in the sense of

598
00:34:22,120 --> 00:34:24,200
Speaker 1: like for the Republican voter, they can look at a

599
00:34:24,280 --> 00:34:28,560
Speaker 1: Democrat governor, senator, other leaders in that sense to say

600
00:34:28,600 --> 00:34:32,120
Speaker 1: the leadership is blue and that is a motivating force

601
00:34:32,160 --> 00:34:34,440
Speaker 1: for people to come out. But I'm wondering, like, you know,

602
00:34:34,920 --> 00:34:36,839
Speaker 1: so there have been so many bad takes and shout

603
00:34:36,880 --> 00:34:38,399
Speaker 1: out to the people on Twitter that I've just been

604
00:34:38,440 --> 00:34:42,640
Speaker 1: collecting everyone's terrible bad faith arguments prior to the election,

605
00:34:43,040 --> 00:34:46,080
Speaker 1: because we really should be like what's your strategy for

606
00:34:46,160 --> 00:34:49,200
Speaker 1: like having better like a better way to engage with

607
00:34:49,239 --> 00:34:51,480
Speaker 1: like the stories that are happening, rather than seeing like

608
00:34:51,560 --> 00:34:53,799
Speaker 1: what the herd is doing them, Like, well, here's my

609
00:34:53,880 --> 00:34:56,880
Speaker 1: take on the herd mentality, right, just all editorial, just

610
00:34:57,000 --> 00:35:00,360
Speaker 1: all editorial. Yeah, it's all covering it like it's a

611
00:35:00,360 --> 00:35:03,960
Speaker 1: sporting event and when what like, So this article doesn't

612
00:35:03,960 --> 00:35:06,960
Speaker 1: explicitly do this, but it does essentially do this, which

613
00:35:07,000 --> 00:35:10,440
Speaker 1: I think is sort of the mainstream Democrat and mainstream

614
00:35:10,440 --> 00:35:13,879
Speaker 1: media apparatus sort of I don't know conception of how

615
00:35:13,920 --> 00:35:18,360
Speaker 1: Democrats can possibly conceive of crime. They can either double

616
00:35:18,440 --> 00:35:21,759
Speaker 1: down on like like basically be a Republican about it

617
00:35:21,760 --> 00:35:24,399
Speaker 1: and be like we need to fund like extra fund

618
00:35:24,400 --> 00:35:26,879
Speaker 1: the police and support the death penalty like Clinton did.

619
00:35:27,360 --> 00:35:31,319
Speaker 1: We can ignore that crime is a problem, or just

620
00:35:31,400 --> 00:35:35,400
Speaker 1: say defund the police and offer no further context. Like

621
00:35:35,440 --> 00:35:37,960
Speaker 1: those are the three options that they're dealing with in

622
00:35:38,040 --> 00:35:42,799
Speaker 1: this article, and it's just like a Tucker carlson Ian

623
00:35:43,000 --> 00:35:47,640
Speaker 1: bad faith argument of like how how to even approach this?

624
00:35:48,040 --> 00:35:52,040
Speaker 1: And so they published this article after this overall strategy

625
00:35:52,280 --> 00:35:54,720
Speaker 1: was shown to backfire in a lot of like really

626
00:35:54,719 --> 00:35:58,760
Speaker 1: significant ways for the Republican Party, and they completely ignore

627
00:35:59,840 --> 00:36:05,080
Speaker 1: anywhere where there's like this alternative messaging that came through

628
00:36:05,160 --> 00:36:08,080
Speaker 1: and worked like at a local level that you know,

629
00:36:08,200 --> 00:36:13,359
Speaker 1: we talked on yesterday's episode about Kenneth Mahia, who ran

630
00:36:13,560 --> 00:36:17,440
Speaker 1: a campaign that was he's like thirty one just really focused.

631
00:36:17,920 --> 00:36:21,160
Speaker 1: He he was a defund the police candidate, and that

632
00:36:21,239 --> 00:36:27,160
Speaker 1: was like his most explicit position, and he outperformed both

633
00:36:27,280 --> 00:36:31,600
Speaker 1: mayoral candidates, both the like very mainstream Democratic candidate and

634
00:36:31,640 --> 00:36:35,799
Speaker 1: also the you know, fake Democrat Republican Rick Cruso. He

635
00:36:36,040 --> 00:36:40,920
Speaker 1: vastly outperformed them by just giving specifics, by just being like,

636
00:36:41,239 --> 00:36:44,359
Speaker 1: here's like when when you say defund the police, look

637
00:36:44,360 --> 00:36:48,200
Speaker 1: how much they are funded compared to everything else, And

638
00:36:48,640 --> 00:36:53,160
Speaker 1: like so all you needed to do was speak honestly

639
00:36:53,360 --> 00:36:57,839
Speaker 1: and respect people's intelligence on the subject instead of like

640
00:36:57,920 --> 00:37:01,960
Speaker 1: this whole Paul Begala names Carville thing where it's all

641
00:37:02,120 --> 00:37:04,600
Speaker 1: this like smoking mirrors and we have to message it

642
00:37:04,680 --> 00:37:07,920
Speaker 1: this way and people don't understand. You can't get them

643
00:37:07,920 --> 00:37:10,920
Speaker 1: in touch with their safety unless you do a real horrible,

644
00:37:11,239 --> 00:37:14,720
Speaker 1: violent active front of them and in front of the police.

645
00:37:14,800 --> 00:37:17,040
Speaker 1: Dumbest thing I heard since my mama tried to put

646
00:37:17,040 --> 00:37:20,480
Speaker 1: a boot on my head and call it about what

647
00:37:20,520 --> 00:37:23,480
Speaker 1: the are you talking about? I think it all you're

648
00:37:23,520 --> 00:37:25,359
Speaker 1: what you have to say. They're all broke down when

649
00:37:25,400 --> 00:37:29,560
Speaker 1: you said and respect their other person's intelligence. That is ridiculous.

650
00:37:29,600 --> 00:37:33,200
Speaker 1: We do not do that, Okay, can do that. That's

651
00:37:34,680 --> 00:37:37,680
Speaker 1: work like, so, I I do think this goes like

652
00:37:38,120 --> 00:37:42,080
Speaker 1: each generation gets a little bit savvier at dealing with

653
00:37:42,360 --> 00:37:45,320
Speaker 1: the media than the previous generation. But the media is

654
00:37:45,440 --> 00:37:50,000
Speaker 1: run by older generations and they are working with assumptions

655
00:37:50,320 --> 00:37:54,080
Speaker 1: that like people are different than they actually are. And

656
00:37:54,120 --> 00:37:56,520
Speaker 1: that's what Like we saw Gen Z actually come out

657
00:37:56,520 --> 00:37:59,839
Speaker 1: and vote and they didn't vote the way that anybody

658
00:38:00,080 --> 00:38:03,359
Speaker 1: in the mainstream media expected them too. And it's like, yeah,

659
00:38:03,400 --> 00:38:06,880
Speaker 1: they voted in a way that seems like they're just

660
00:38:06,920 --> 00:38:11,920
Speaker 1: getting at the problem right, aligned with their values and

661
00:38:12,080 --> 00:38:15,160
Speaker 1: based on policies and based on you know, the stuff

662
00:38:15,160 --> 00:38:17,919
Speaker 1: that we're trying to actually talk about in a real

663
00:38:17,920 --> 00:38:21,240
Speaker 1: way instead of yeah, is all the smoke and mirrors

664
00:38:21,280 --> 00:38:24,320
Speaker 1: and the this is gonna happen. Just wait, you're gonna

665
00:38:24,320 --> 00:38:26,480
Speaker 1: wake up and all your rights are gonna be stripped

666
00:38:26,480 --> 00:38:28,920
Speaker 1: away and then what are you gonna do? Yeah, And

667
00:38:29,000 --> 00:38:31,560
Speaker 1: it's I keep comparing it to like that m Night

668
00:38:31,600 --> 00:38:35,880
Speaker 1: Shamalan movie The Village, where they really think you just

669
00:38:36,000 --> 00:38:38,440
Speaker 1: keep telling everybody the same ship over. You don't want

670
00:38:38,440 --> 00:38:40,120
Speaker 1: to go out there, you don't want to see what's

671
00:38:40,160 --> 00:38:42,759
Speaker 1: out there. But guess what, most people are living out there.

672
00:38:42,920 --> 00:38:46,560
Speaker 1: You don't actually live, so your village asked messaging doesn't

673
00:38:46,560 --> 00:38:49,759
Speaker 1: resonate to somebody village lives who lives in the area.

674
00:38:49,880 --> 00:38:52,319
Speaker 1: Or they're like, yeah, that's the motherfucking airplane. Yeah you

675
00:38:52,400 --> 00:38:54,439
Speaker 1: didn't hear about it that in the village. Well that's

676
00:38:54,480 --> 00:38:57,800
Speaker 1: on y'all. And this whole election, I feel like it

677
00:38:57,880 --> 00:39:00,120
Speaker 1: was really defined, at least to me, is what I'm seeing,

678
00:39:00,480 --> 00:39:04,360
Speaker 1: like broadly by just people beginning to feel the disconnect

679
00:39:04,400 --> 00:39:07,279
Speaker 1: between policies that uphold the status quo and what their

680
00:39:07,320 --> 00:39:09,879
Speaker 1: actual day to day lives are like, and from they're

681
00:39:10,000 --> 00:39:12,680
Speaker 1: using their own intelligence to be like I see somebody

682
00:39:12,680 --> 00:39:14,919
Speaker 1: who's destitute, or I look at my own situation where

683
00:39:14,920 --> 00:39:16,759
Speaker 1: I can barely afford housing, and I don't think the

684
00:39:17,280 --> 00:39:19,480
Speaker 1: plan should be Yo, get kicked these people out to

685
00:39:19,520 --> 00:39:22,640
Speaker 1: the Mojave desert where they can just expire in the sun.

686
00:39:23,080 --> 00:39:27,120
Speaker 1: It's I think we need more affordable housing, right. You know,

687
00:39:27,160 --> 00:39:30,000
Speaker 1: they're like the funk is going on, these woke people

688
00:39:30,440 --> 00:39:35,719
Speaker 1: know what about tax cuts for luxury planes? I do?

689
00:39:35,920 --> 00:39:38,799
Speaker 1: I do have to call out this Harvard sociologist though,

690
00:39:39,080 --> 00:39:42,560
Speaker 1: for they they made this claim, so they were like

691
00:39:43,080 --> 00:39:46,920
Speaker 1: democrats want to claim that crime isn't a problem, but

692
00:39:47,000 --> 00:39:50,000
Speaker 1: that ignores that crime is a problem in you know,

693
00:39:50,160 --> 00:39:54,280
Speaker 1: black neighborhoods and poor neighborhoods, so you know, not funding

694
00:39:54,320 --> 00:39:58,959
Speaker 1: the police is racist, is essentially the argument that they make.

695
00:39:59,520 --> 00:40:02,520
Speaker 1: And it's like, like, to your point, Miles, we saw

696
00:40:02,719 --> 00:40:06,160
Speaker 1: that people who live in neighborhoods that are affected by

697
00:40:06,520 --> 00:40:10,560
Speaker 1: higher crime are not buying into this bullshit narrative that like,

698
00:40:10,680 --> 00:40:14,920
Speaker 1: the way to attack this is by fucking funding a

699
00:40:15,040 --> 00:40:18,239
Speaker 1: police force that acts like an occupying army. Like they

700
00:40:18,280 --> 00:40:21,680
Speaker 1: know that this is bullshit, and getting Paul Begala and

701
00:40:21,719 --> 00:40:27,160
Speaker 1: a Harvard sociologist to tell them otherwise, isn't isn't tricking anyone? Yeah,

702
00:40:27,280 --> 00:40:29,840
Speaker 1: well yeah, give them all don't remember that's how we

703
00:40:29,880 --> 00:40:31,600
Speaker 1: saw Thanks good mall guns. Why does the name one

704
00:40:31,640 --> 00:40:34,120
Speaker 1: have a gun? Yeah, exactly. And then even then a

705
00:40:34,120 --> 00:40:36,000
Speaker 1: lot of people are like, no, I don't, I don't

706
00:40:36,000 --> 00:40:40,200
Speaker 1: even think that. What they also, yeah, they quote that

707
00:40:40,440 --> 00:40:42,600
Speaker 1: so because this is a crime article, they had to

708
00:40:42,640 --> 00:40:46,800
Speaker 1: like quote the crime statistics, which are very like complicated,

709
00:40:47,040 --> 00:40:50,319
Speaker 1: and they point in different directions and different parts of

710
00:40:50,320 --> 00:40:53,200
Speaker 1: the country, and they're like, but the one thing we're

711
00:40:53,239 --> 00:40:57,399
Speaker 1: seeing is more gun violence and more murders, but they

712
00:40:57,400 --> 00:41:00,239
Speaker 1: don't mention like because there are way more guns, and

713
00:41:00,280 --> 00:41:03,720
Speaker 1: anytime there's more access to guns, that's what happens in

714
00:41:03,920 --> 00:41:07,880
Speaker 1: this country, because again, that's just seen as a I

715
00:41:07,880 --> 00:41:11,680
Speaker 1: guess childish argument because it doesn't take into account the

716
00:41:11,719 --> 00:41:15,040
Speaker 1: reality that like, well, you know, gun manufacturers own all

717
00:41:15,040 --> 00:41:17,640
Speaker 1: of us, so we can't actually say that were you

718
00:41:17,719 --> 00:41:21,160
Speaker 1: a child? Good funk out of here, right exactly, Quiet

719
00:41:21,200 --> 00:41:25,880
Speaker 1: daddy's listening, right exactly. Gotta be with Wayne Lapierre continuing

720
00:41:25,880 --> 00:41:28,960
Speaker 1: to search Kenneth Mahia on The New York Times just

721
00:41:29,040 --> 00:41:31,480
Speaker 1: to see, like what when will they mention this race

722
00:41:31,560 --> 00:41:34,799
Speaker 1: that is like a great blueprint for how the Democratic

723
00:41:34,840 --> 00:41:39,960
Speaker 1: Party should move, like all at once yesterday and the

724
00:41:40,080 --> 00:41:43,760
Speaker 1: only mentioned so far is a Halloween article about how

725
00:41:43,800 --> 00:41:48,120
Speaker 1: like when Democrats go against each other it gets nasty folks.

726
00:41:48,560 --> 00:41:53,000
Speaker 1: And they quote his opponent claiming that he is a

727
00:41:53,320 --> 00:41:57,560
Speaker 1: anarchist and an anti Semite. They they put that in

728
00:41:57,600 --> 00:42:02,560
Speaker 1: there and he's not, and it's like absolute. But that's

729
00:42:02,680 --> 00:42:06,360
Speaker 1: that's the only thing that they've mentioned about this candidate

730
00:42:06,400 --> 00:42:11,640
Speaker 1: who just you know, used I mean, that's what I mean,

731
00:42:11,680 --> 00:42:15,000
Speaker 1: that's that's the smear for people who believe that less

732
00:42:15,239 --> 00:42:19,319
Speaker 1: physical police presence and like more support for communities is

733
00:42:19,360 --> 00:42:22,319
Speaker 1: the answer. Is they ready to go? Yeah you anarchy, right,

734
00:42:22,400 --> 00:42:27,399
Speaker 1: yeah right, exactly, awless society, you want just nothing right right?

735
00:42:27,520 --> 00:42:30,399
Speaker 1: And as a Jew, I will say, you know, most

736
00:42:30,400 --> 00:42:32,319
Speaker 1: people are anti Semite, so you just sort of like

737
00:42:32,360 --> 00:42:34,279
Speaker 1: you just that's like a penny, you just get rid

738
00:42:34,320 --> 00:42:42,000
Speaker 1: of that. Alright, Let's take a quick break, we'll come back,

739
00:42:42,040 --> 00:42:55,680
Speaker 1: we'll talk holiday movies. We'll be right back, and we're back,

740
00:42:56,120 --> 00:42:59,879
Speaker 1: and let's let's talk about So Disney is bringing the

741
00:43:00,080 --> 00:43:05,520
Speaker 1: Santa Claus cinematic Universe to Disney Plus streaming, which, if

742
00:43:05,520 --> 00:43:09,759
Speaker 1: you're not familiar, the Santa Claus movies have always been

743
00:43:09,800 --> 00:43:13,040
Speaker 1: pretty fucked up, since the original is the only Christmas

744
00:43:13,040 --> 00:43:15,920
Speaker 1: movie where Santa Claus dies in the first ten minutes.

745
00:43:16,400 --> 00:43:19,400
Speaker 1: Yeah yeah, yeah yeah. And it's also I think the

746
00:43:19,440 --> 00:43:22,800
Speaker 1: only Christmas movie to feature references to an actual adult

747
00:43:22,840 --> 00:43:29,319
Speaker 1: sex hotline that real nineties kids called Amazing, Amazing, Thank

748
00:43:29,440 --> 00:43:32,240
Speaker 1: Me that leads to a nine hundred line with adult

749
00:43:32,280 --> 00:43:35,040
Speaker 1: content and high charges to nine year old girls called

750
00:43:35,040 --> 00:43:37,520
Speaker 1: the eight hundred Line ended up ringing up more than

751
00:43:37,560 --> 00:43:41,799
Speaker 1: five hundred dollars in charges, but Anyways, Mary Christmas. It's

752
00:43:41,840 --> 00:43:44,319
Speaker 1: kind of hard to separate Tim Allen, who is the

753
00:43:44,360 --> 00:43:47,799
Speaker 1: star of the original one of the producers of this

754
00:43:47,840 --> 00:43:50,399
Speaker 1: new show they're bringing to Disney. Plus that's basically a

755
00:43:50,400 --> 00:43:54,479
Speaker 1: series set in that universe. It's hard to separate Tim

756
00:43:54,520 --> 00:43:59,640
Speaker 1: Allen the Santa Claus from his outspoken public persona where

757
00:43:59,680 --> 00:44:03,400
Speaker 1: he kind of routinely winds about the oppression he faces

758
00:44:03,719 --> 00:44:07,800
Speaker 1: as a Hollywood conservative who charges I think a million

759
00:44:07,800 --> 00:44:10,520
Speaker 1: dollars per stand up show, so we all we all

760
00:44:10,520 --> 00:44:13,120
Speaker 1: feel struggled. Man. I think about him every night. I

761
00:44:13,120 --> 00:44:15,399
Speaker 1: pray for him right as you lay on your pile

762
00:44:15,440 --> 00:44:18,880
Speaker 1: of cash. But you can you can really read this

763
00:44:19,280 --> 00:44:23,320
Speaker 1: show as a story that is symbolically about Trump deciding

764
00:44:23,360 --> 00:44:26,880
Speaker 1: to run for election with Santa as the stand in

765
00:44:27,000 --> 00:44:30,840
Speaker 1: for Trump, because in this newly released trailer, Santa discovers

766
00:44:30,880 --> 00:44:33,840
Speaker 1: that people don't believe in him anymore. There's an opening

767
00:44:33,840 --> 00:44:37,880
Speaker 1: scene in which a hysterical woman throws a wine bottle

768
00:44:37,920 --> 00:44:39,960
Speaker 1: at his head. Wait a second, is there any other

769
00:44:40,040 --> 00:44:43,640
Speaker 1: kind I was? I'm not any other kind of woman.

770
00:44:44,000 --> 00:44:48,000
Speaker 1: That's what's written in the script. Sterical woman one and

771
00:44:48,040 --> 00:44:52,920
Speaker 1: Santa notices that the magic meter approval rating is plummeting,

772
00:44:53,440 --> 00:44:56,719
Speaker 1: and so he decides to retire for the good of Christmas.

773
00:44:57,080 --> 00:45:02,000
Speaker 1: He doesn't urge his fans to hang Bernard the Alpha

774
00:45:02,360 --> 00:45:07,160
Speaker 1: or anyone, but the language of the moment is, so,

775
00:45:07,239 --> 00:45:10,720
Speaker 1: for the good of Christmas, I'm retiring, recalls the rhetoric

776
00:45:10,760 --> 00:45:13,680
Speaker 1: surrounding calls for Trump to can see the election. But

777
00:45:13,800 --> 00:45:16,760
Speaker 1: then it turns out that the person after him sucks

778
00:45:17,239 --> 00:45:22,560
Speaker 1: and and and and he's called Joe Biden. Right, he's

779
00:45:22,560 --> 00:45:28,560
Speaker 1: a much older Santa Claus Brandon clause. But there's there's

780
00:45:28,600 --> 00:45:31,960
Speaker 1: a legit. There's a legit quote from the trailer I

781
00:45:32,040 --> 00:45:36,000
Speaker 1: retired to so I hired the wrong guy, and so

782
00:45:36,080 --> 00:45:40,040
Speaker 1: he has to come back and you know, triumphantly returned

783
00:45:40,040 --> 00:45:42,760
Speaker 1: to the North Pole, removed the new Santa from power

784
00:45:43,400 --> 00:45:47,839
Speaker 1: a bloody I have to assume, yeah, exactly. I mean,

785
00:45:48,239 --> 00:45:52,400
Speaker 1: also famous for wearing red hat. You know, it couldn't

786
00:45:52,400 --> 00:45:54,600
Speaker 1: be any clear. I mean, yeah, it feels like one

787
00:45:54,640 --> 00:45:57,360
Speaker 1: of those things where Tim Allen doesn't realize what he's doing,

788
00:45:58,360 --> 00:46:00,640
Speaker 1: you know, like he's like yeah, and then like they

789
00:46:00,719 --> 00:46:03,320
Speaker 1: don't like him, so he leaves. But then they realize

790
00:46:03,360 --> 00:46:05,440
Speaker 1: this new guys, are you talking about Donald Trump? He's

791
00:46:05,480 --> 00:46:11,640
Speaker 1: like ship, yeah, right, maybe I was thinking about that.

792
00:46:12,160 --> 00:46:15,480
Speaker 1: I think, yeah, why would I be talking about him?

793
00:46:15,520 --> 00:46:21,680
Speaker 1: It's Christmas? Okay, I mean yeah it is. Also it's

794
00:46:22,800 --> 00:46:24,400
Speaker 1: I put this in the category in my husband I

795
00:46:24,400 --> 00:46:27,440
Speaker 1: talked about this time, like nobody asked for that. You know,

796
00:46:28,800 --> 00:46:32,000
Speaker 1: where's the holiday movie? It's concerned? Are we like, hey,

797
00:46:32,040 --> 00:46:34,799
Speaker 1: is there a Santa Tale about how one fox up?

798
00:46:34,800 --> 00:46:37,799
Speaker 1: And uh, the old one has to come back? And

799
00:46:37,880 --> 00:46:43,200
Speaker 1: it's like no, no, no one needs thattionary tale about

800
00:46:43,280 --> 00:46:46,280
Speaker 1: regime change? Is there anything like that that we could

801
00:46:46,560 --> 00:46:50,480
Speaker 1: What's what's a binge worthy Santa Tale? So at the

802
00:46:50,520 --> 00:46:53,560
Speaker 1: end doesn't charge for the gifts? How does this work? Yeah?

803
00:46:53,640 --> 00:46:58,680
Speaker 1: We don't, actually don't. But I mean it's just so funny.

804
00:46:58,800 --> 00:47:00,880
Speaker 1: On one side, you have this on Disney Plus. Or

805
00:47:00,920 --> 00:47:03,600
Speaker 1: it's like, yeah, maybe Joe Biden sucks and Trump should

806
00:47:03,600 --> 00:47:05,760
Speaker 1: come back. And then and Or's like it's all about

807
00:47:05,920 --> 00:47:11,240
Speaker 1: armed revolution and you're like so much. I haven't watched

808
00:47:11,239 --> 00:47:16,480
Speaker 1: It's it's like it's like hard, it's hard Star Wars.

809
00:47:17,760 --> 00:47:20,719
Speaker 1: Oh yeah, and it's all right, it's all about the

810
00:47:20,719 --> 00:47:24,920
Speaker 1: place state, yeah, and revolutionaries, but like you know, deeping

811
00:47:25,000 --> 00:47:29,120
Speaker 1: into that story. Both sides, truly both sides. There's dudes

812
00:47:29,160 --> 00:47:31,560
Speaker 1: like you're taking a piss in it, you know what

813
00:47:31,640 --> 00:47:33,840
Speaker 1: I mean. Like there's just stuff you don't see in

814
00:47:33,960 --> 00:47:36,839
Speaker 1: like like Star Wars is so sanitized, so Lettle, it's

815
00:47:37,000 --> 00:47:41,640
Speaker 1: it's so great. I don't know there's someone taking like

816
00:47:41,640 --> 00:47:43,359
Speaker 1: you wouldn't see someone taking a piss in a Star

817
00:47:43,400 --> 00:47:46,520
Speaker 1: Wars film. That's been my number one complaint since I

818
00:47:48,560 --> 00:47:50,840
Speaker 1: saw Star Wars for the first time. Right in a

819
00:47:50,880 --> 00:47:53,239
Speaker 1: helmet they take a piss in a helmet and then

820
00:47:53,239 --> 00:47:55,120
Speaker 1: someone else puts it on. No, that does not happen.

821
00:47:55,800 --> 00:48:00,160
Speaker 1: That would be the prankster Star Wars. It's like, no,

822
00:48:00,280 --> 00:48:01,799
Speaker 1: I love it. I mean the Star Wars is big

823
00:48:01,800 --> 00:48:05,440
Speaker 1: in my family. My son's name is Lucas. Oh my god.

824
00:48:06,400 --> 00:48:09,080
Speaker 1: Wow yeah sup. Producer Justin says it's the best Star

825
00:48:09,120 --> 00:48:12,440
Speaker 1: Wars property ever made. So you are correct at him.

826
00:48:13,080 --> 00:48:16,960
Speaker 1: Oh okay, Now we're showing up in the back. You

827
00:48:17,000 --> 00:48:22,560
Speaker 1: see that, Yeah, that's end Or and then that's tattoo.

828
00:48:23,080 --> 00:48:25,000
Speaker 1: I'm holding up my Star Wars books. Just for those

829
00:48:25,000 --> 00:48:27,600
Speaker 1: who don't understand this is not a visual medium. Who

830
00:48:27,600 --> 00:48:33,760
Speaker 1: made and or Tony Gilroy made it? Did Tony Gilroy?

831
00:48:33,880 --> 00:48:40,920
Speaker 1: Is he the one who made Michael Clayton. Yeah, Born Films, right, yeah,

832
00:48:41,000 --> 00:48:44,360
Speaker 1: he wrote he wrote the Born Films made Michael Clayton,

833
00:48:44,360 --> 00:48:47,960
Speaker 1: which has a very good like anti corporate message, the

834
00:48:48,000 --> 00:48:53,799
Speaker 1: Born Films anti Cia message. Yeah, all right, Well, if

835
00:48:54,160 --> 00:48:57,160
Speaker 1: it's been such a pleasure having you on the podcast,

836
00:48:57,200 --> 00:49:00,160
Speaker 1: where can people find you? Follow you here? You all

837
00:49:00,239 --> 00:49:04,239
Speaker 1: that good stuff? Thanks? Thanks Jack, Thanks Myles. I'm at well.

838
00:49:04,360 --> 00:49:07,239
Speaker 1: My new podcast is called parenting is a joke with

839
00:49:07,360 --> 00:49:09,799
Speaker 1: I heart media, So you can find that wherever you

840
00:49:10,120 --> 00:49:12,279
Speaker 1: get your podcasts, and you can follow me on the

841
00:49:12,320 --> 00:49:15,880
Speaker 1: socials at O fira E. Most importantly based on this

842
00:49:15,920 --> 00:49:18,360
Speaker 1: capitalist talk at the end, you can find me on

843
00:49:18,440 --> 00:49:24,000
Speaker 1: Venmo at Opera. There goes important if you want to

844
00:49:24,080 --> 00:49:25,800
Speaker 1: if you want to just talk through Venmo, I'm happy

845
00:49:25,800 --> 00:49:30,480
Speaker 1: to do that. Uh. And is there a tweet or

846
00:49:30,600 --> 00:49:32,960
Speaker 1: some of the work of social media you've been enjoying,

847
00:49:33,360 --> 00:49:35,799
Speaker 1: you know right now? I am sort of I am

848
00:49:35,920 --> 00:49:39,719
Speaker 1: enjoying where people are deactivating their Twitter account and then

849
00:49:39,880 --> 00:49:42,640
Speaker 1: taking a screenshot of that and putting it on their Instagram.

850
00:49:42,960 --> 00:49:46,920
Speaker 1: That's a post. It is the most you know, for

851
00:49:47,040 --> 00:49:49,120
Speaker 1: to be virtuous, Like look at the thing, like no

852
00:49:49,200 --> 00:49:52,600
Speaker 1: one could just leave, Just leave, Okay, I don't need

853
00:49:52,680 --> 00:49:59,360
Speaker 1: to like celebrate your leaving on a different meta social situation.

854
00:49:59,560 --> 00:50:03,959
Speaker 1: It's a rates to me. Just leave. It's okay. Gotta

855
00:50:03,960 --> 00:50:07,040
Speaker 1: announced though, gotta announced. Miles, where can people find you?

856
00:50:07,200 --> 00:50:10,120
Speaker 1: And what is the tweet you've been find me? Hat

857
00:50:10,160 --> 00:50:12,640
Speaker 1: miles of ground on Twitter and Instagram? I am wow,

858
00:50:12,680 --> 00:50:16,480
Speaker 1: I know how to say that? Find fing? Does us

859
00:50:17,320 --> 00:50:21,760
Speaker 1: Jack and Miles on our one hundred percent top rated

860
00:50:21,920 --> 00:50:25,279
Speaker 1: basketball podcast Miles and Jack got mad boost these um

861
00:50:26,080 --> 00:50:29,399
Speaker 1: percent top rated? Yeah, I'm just create. It's like funny,

862
00:50:29,400 --> 00:50:32,719
Speaker 1: you got to create new like words that don't mean

863
00:50:32,760 --> 00:50:35,040
Speaker 1: anything but sound good like a politician would say. I

864
00:50:35,040 --> 00:50:38,960
Speaker 1: mean it's on top rated, so we know yeah yeah obviously.

865
00:50:39,400 --> 00:50:42,200
Speaker 1: Um And also for twenty Day Fiance this week with

866
00:50:42,280 --> 00:50:45,839
Speaker 1: Lydia Popovitch. Actually Lydia Papovitch is helping me guest host,

867
00:50:45,880 --> 00:50:50,240
Speaker 1: so check that out. Some tweets that I like, well, okay,

868
00:50:50,239 --> 00:50:52,360
Speaker 1: this is just this one is from at Pink Underscore

869
00:50:52,400 --> 00:50:54,880
Speaker 1: Priests as it says, I'm begging the spiritual girlies to

870
00:50:54,920 --> 00:50:58,400
Speaker 1: do a little reading on recognizing propaganda. How the right

871
00:50:58,480 --> 00:51:02,400
Speaker 1: infiltrates occult space is the current rise of fascism, etcetera.

872
00:51:02,440 --> 00:51:04,560
Speaker 1: Because I see so many of you falling for hyper

873
00:51:04,560 --> 00:51:07,840
Speaker 1: conservative ideology when it's presented to you through the terms

874
00:51:07,880 --> 00:51:10,919
Speaker 1: like divine feminine, uh, and I just see like, yeah,

875
00:51:10,920 --> 00:51:14,360
Speaker 1: that that space. I feel like that's maybe Steve Bannon

876
00:51:14,400 --> 00:51:17,160
Speaker 1: has his eyes on the woo woo space as the

877
00:51:17,200 --> 00:51:19,960
Speaker 1: next block you can maybe turn out. And then Sarah

878
00:51:20,000 --> 00:51:23,040
Speaker 1: Mayer at Sarah Meyer NYC. This is just like an

879
00:51:23,040 --> 00:51:25,160
Speaker 1: election day tweet that was so funny. He said, I

880
00:51:25,200 --> 00:51:27,920
Speaker 1: just voted and was approached by an elderly woman looking

881
00:51:28,000 --> 00:51:31,879
Speaker 1: on her NYC ballot for doctor Oz. I don't really

882
00:51:31,920 --> 00:51:34,480
Speaker 1: know where to go from here, perhaps to the bar.

883
00:51:37,480 --> 00:51:41,680
Speaker 1: Where is doctor Oz? Oh? Nope, me, you don't even

884
00:51:41,680 --> 00:51:44,080
Speaker 1: know what fun is dude? What are you watching how

885
00:51:44,160 --> 00:51:47,839
Speaker 1: much Fox? You just think there's like three candidates? Okay, okay,

886
00:51:48,800 --> 00:51:52,759
Speaker 1: you can find me on Twitter at Jack Underscore O'Brien

887
00:51:53,360 --> 00:51:58,120
Speaker 1: tweet then enjoying Katie at Skadi for twenty tweeted. My

888
00:51:58,239 --> 00:52:01,560
Speaker 1: uber driver yelled, oh Jesus, what is that and then said, oh,

889
00:52:01,760 --> 00:52:03,920
Speaker 1: it's the good Year blimp. I thought it was a ghost,

890
00:52:05,239 --> 00:52:07,640
Speaker 1: which is both very funny and not what you want

891
00:52:07,640 --> 00:52:12,000
Speaker 1: to hear. From your uber driver next. But also whenever

892
00:52:12,040 --> 00:52:14,439
Speaker 1: I see the Goodyear Blimp, I have that same thought.

893
00:52:14,640 --> 00:52:18,080
Speaker 1: I'm like, what the fun? Oh really? Yeah? Not not

894
00:52:18,160 --> 00:52:21,839
Speaker 1: whenever I'll say I've I frequently had seen the big

895
00:52:21,880 --> 00:52:25,560
Speaker 1: as Goodyear blimp hovering in the sky and like out

896
00:52:25,600 --> 00:52:27,719
Speaker 1: of the corner of my eye, and it's just so

897
00:52:27,960 --> 00:52:31,400
Speaker 1: unlike anything that my brain is ready to process in

898
00:52:31,440 --> 00:52:34,960
Speaker 1: that spot. And the way some people are with cow's

899
00:52:34,960 --> 00:52:37,440
Speaker 1: where they're like cal when they see one when they

900
00:52:37,520 --> 00:52:40,880
Speaker 1: drive by. I am that for life with Goodyear Blimp,

901
00:52:41,080 --> 00:52:44,359
Speaker 1: but like to a degree where I like get very

902
00:52:44,440 --> 00:52:47,520
Speaker 1: excited and make my kids come outside or you know,

903
00:52:47,760 --> 00:52:50,120
Speaker 1: look and we'll be like pointing there, like no, no, no no,

904
00:52:50,239 --> 00:52:54,080
Speaker 1: it's right over there. You're like, okay, Dad, I swear

905
00:52:54,120 --> 00:52:59,839
Speaker 1: it was there the wind probably. Yeah, there's just something

906
00:52:59,880 --> 00:53:02,600
Speaker 1: of out when the good Year Blip is out. Like

907
00:53:02,680 --> 00:53:04,759
Speaker 1: even if it's like for some golf tournament, I don't

908
00:53:04,760 --> 00:53:07,879
Speaker 1: give a shit about there's like a feeling, I mean

909
00:53:08,320 --> 00:53:12,520
Speaker 1: something is happening. Yeah, Like I guess whenever you're at

910
00:53:12,600 --> 00:53:15,359
Speaker 1: like a sporting event in stereo is like, hey, I'm

911
00:53:15,400 --> 00:53:18,520
Speaker 1: at a good event because the glimps here. Yeah, I

912
00:53:18,680 --> 00:53:21,719
Speaker 1: just blimps. I do. I know this is like an

913
00:53:21,760 --> 00:53:25,319
Speaker 1: old Internet take, but you know, if if the era

914
00:53:25,440 --> 00:53:28,759
Speaker 1: of blimps came back, I would I would not object. Jack,

915
00:53:28,800 --> 00:53:31,520
Speaker 1: You're the father of old Internet takes. Thank you. You're

916
00:53:31,560 --> 00:53:34,279
Speaker 1: allowed to dabbling that, like you know what I mean?

917
00:53:34,360 --> 00:53:37,680
Speaker 1: Like nobody with you. You can find us on Twitter

918
00:53:37,719 --> 00:53:40,800
Speaker 1: at Daily Zygeist. We're at the Daily Zieist on Instagram.

919
00:53:40,840 --> 00:53:42,960
Speaker 1: We have a Facebook fan page on a website daily

920
00:53:43,040 --> 00:53:45,560
Speaker 1: zis dot com where we post our episodes. On our

921
00:53:45,680 --> 00:53:48,680
Speaker 1: foot note, we link off to the information that we

922
00:53:48,719 --> 00:53:50,919
Speaker 1: talked about in today's episode, as well as a song

923
00:53:50,960 --> 00:53:54,880
Speaker 1: that we think you might enjoy. Man, this is a

924
00:53:54,880 --> 00:53:58,840
Speaker 1: good track. This is a a track by Cartoons c

925
00:53:59,120 --> 00:54:02,359
Speaker 1: A R R o O n S with Nigel Hall,

926
00:54:03,080 --> 00:54:07,440
Speaker 1: great R and BS like soul singer. It's called Groceries

927
00:54:07,760 --> 00:54:10,520
Speaker 1: and it's just such a It's like it's like a

928
00:54:10,560 --> 00:54:13,840
Speaker 1: funky modern soul track. Cartoons is like this really interesting

929
00:54:13,880 --> 00:54:17,480
Speaker 1: like producer, bassist, multi instrumentalists. So it's like got a

930
00:54:17,520 --> 00:54:20,080
Speaker 1: little we got a little nice funk feel to it.

931
00:54:20,120 --> 00:54:22,480
Speaker 1: But it's like the production feels a little more modern,

932
00:54:22,600 --> 00:54:26,440
Speaker 1: but Nigel Hall's voice just like fantastic. Uh, and together.

933
00:54:26,480 --> 00:54:28,279
Speaker 1: It's just like one of those great combinations of like

934
00:54:28,320 --> 00:54:31,560
Speaker 1: a great vocalist with a great instrumentalist and you've got

935
00:54:31,600 --> 00:54:34,319
Speaker 1: this track called Groceries. So this is actually a good

936
00:54:34,320 --> 00:54:37,120
Speaker 1: track to take into your Friday and maybe watch some

937
00:54:37,680 --> 00:54:41,719
Speaker 1: Fox frustration clips. You know, yeah clips don't actually tune in,

938
00:54:41,760 --> 00:54:43,239
Speaker 1: but they're not no no, no, I don't give them.

939
00:54:43,239 --> 00:54:45,960
Speaker 1: Don't give that. So the social meds is lousy with

940
00:54:46,560 --> 00:54:49,040
Speaker 1: just people losing their mind on funk. Yeah, just follow

941
00:54:49,120 --> 00:54:52,440
Speaker 1: cat Abu or one of those Twitter you know, Ason

942
00:54:52,560 --> 00:54:54,719
Speaker 1: A c y n or whatever. Alright, well we will

943
00:54:54,760 --> 00:54:58,200
Speaker 1: link off to Groceries in the footnotes. Like Guys is

944
00:54:58,200 --> 00:55:00,160
Speaker 1: a production of I heeart Radio for more pods has

945
00:55:00,160 --> 00:55:02,000
Speaker 1: from my Heart Radio, visit the i Heart Radio app,

946
00:55:02,000 --> 00:55:04,640
Speaker 1: Apple podcast, or wherever you listen to your favorite shows.

947
00:55:04,800 --> 00:55:06,480
Speaker 1: That is going to do it for us this morning,

948
00:55:06,840 --> 00:55:10,040
Speaker 1: back this afternoon to tell you what is trending and

949
00:55:10,360 --> 00:55:13,320
Speaker 1: we will talk to you all done. Bye bye m

950
00:55:14,520 --> 00:55:14,560
Speaker 1: h