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Speaker 1: Hey, guys, ready or not, twenty twenty four is here

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Speaker 1: and we here at breaking points, are already thinking of

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Speaker 1: ways we can up our game for this critical election.

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Speaker 2: We rely on our premium subs to expand coverage, upgrade

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Speaker 2: the studio ad staff, give you, guys, the best independent coverage.

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Speaker 3: That is possible.

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Speaker 2: If you like what we're all about, it just means

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Speaker 2: the absolute world to have your support. But enough with that,

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Speaker 2: let's get to the show. Good morning, everybody, Happy Tuesday.

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Speaker 2: We have an amazing show for everybody today.

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Speaker 3: What do we have, Prystal?

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Speaker 4: Indeed we do.

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Speaker 1: We got Logan back in house to give us the

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Speaker 1: latest update on his model, and also some new polling developments,

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Speaker 1: both with regards to the presidential race in Pennsylvania specifically

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Speaker 1: and with regard to Senate races. Texas may be more

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Speaker 1: interesting than people previously thought, so we'll take a look

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Speaker 1: at all of that. Also, Kamala Harris yesterday announcing her

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Speaker 1: policy plan for black men, and it is really something

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Speaker 1: apparently I don't know. Well, allow to save all of

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Speaker 1: my commentary on that for that involves week involves we

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Speaker 1: involve giving and mail mentors and most neoliberal thing I've

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Speaker 1: literally ever seen, so we'll dig into that. Also might

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Speaker 1: be going on Joe Rogan Kamala Harris yesterday we covered,

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Speaker 1: but Trump may be going on with Joe Rogan and today,

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Speaker 1: so we felt the need to get this into the

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Speaker 1: show today.

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Speaker 4: But apparently her people are in talks, so it'll be interesting.

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Speaker 3: I'm hoping. I think it'd be fun.

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Speaker 1: Clearly we're trying to make a pitch for the mail

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Speaker 1: vote bro vote with all this crypto and Rogan doings,

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Speaker 1: so we'll dig into that. We also Trump making some

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Speaker 1: truly wild comments that we wanted to make sure and

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Speaker 1: cover and what that could pretend in terms of election

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Speaker 1: day in a future Trump possible administration. We're also going

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Speaker 1: to take a look at this supposed third assassination attempt

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Speaker 1: on Trump, which appears to be nothing of the sort.

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Speaker 4: We'll bring you all of the details there.

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Speaker 1: We also wanted to take some time out to take

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Speaker 1: a look at the real estate market in Florida. You know,

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Speaker 1: Florida experienced this massive during COVID. Post COVID boom, many

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Speaker 1: people move to the state. You know, Ronda Standis and

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Speaker 1: other politicians really really bragging about that, very proud of that.

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Speaker 1: Some of that may be reversing now, so we're going

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Speaker 1: to dig into the real estate market there, especially exacerbated

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Speaker 1: now by the state being hit by two very severe hurricanes.

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Speaker 1: We've got some once again horrific updates for you out

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Speaker 1: of Israel as well, including a New York Times report

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Speaker 1: about how Israel has been systematically using Palestinians as human

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Speaker 1: shield well documented sourced actually to the soldiers themselves who

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Speaker 1: are engaged in this practice.

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Speaker 4: So will break all of that down for you as well.

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Speaker 2: That's right, before we get to any of that, make

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Speaker 2: sure you go ahead subscribe Breakingpoints dot com.

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Speaker 3: You get access to our exclusive.

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Speaker 2: Election content, including one of our segments today with Logan,

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Speaker 2: So if you want to be able to watch that

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Speaker 2: and everything the show uncut AMAS, you can take advantage

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Speaker 2: Breakingpoints dot Com become premubscriber. Let's get to Logan joining

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Speaker 2: us now, Logan Phillips, our exclusive election forecaster, Logan.

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Speaker 3: We love seeing you here at the desk.

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Speaker 5: Welcome back, man, I love to be here.

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Speaker 3: Awesome. All right, let's dig into it.

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Speaker 2: You've got your forecast to the White House is going

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Speaker 2: to put that up there on the screen. We've only

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Speaker 2: got twenty days until the presidential election. You currently have it, Actually,

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Speaker 2: it's narrowed a little bit since we talked last time.

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Speaker 2: You have it fifty five forty five for Kamala Harris. Effectively,

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Speaker 2: in my head, that's like a toss up, right, you know,

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Speaker 2: with only five percent margin or so. So talk to

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Speaker 2: us about some of the movement within that why things

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Speaker 2: have maybe tightened with a little bit with less time

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Speaker 2: to go now before the rate.

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Speaker 6: Yeah, there's two reasons. Donal Trump skins a little bit

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Speaker 6: in the national polls. We seem to more movement in

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Speaker 6: the national polls as we do in some of these

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Speaker 6: swing states. Yeah, but you know, Harris's lead is crept

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Speaker 6: a little bit under three percent nationally. And the other

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Speaker 6: thing is we had to rush the poles showing Trump

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Speaker 6: aheaded Michigan in Wisconsin. Now, right, some of these were

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Speaker 6: lower quality polls, but they were enough for them that

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Speaker 6: they at least for me and I think everyone else,

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Speaker 6: they kind of pulled it a little closer. So, either

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Speaker 6: that's true or not. We're gonna get a better sense

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Speaker 6: in the next few days. But it's certainly a canary

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Speaker 6: in the coal mine for Harris.

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Speaker 3: Got it all right, Well, let's let's sorry, go ahead, Crysal, Yeah,

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Speaker 3: all right, well let's continue.

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Speaker 2: Let's continue then on the electoral college, because this is

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Speaker 2: where what you were just talking about with the swing states,

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Speaker 2: this stuff really matters. So A two please if we

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Speaker 2: can put that up on the screen. Here, you have

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Speaker 2: in the overall seven key swing states, you actually have

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Speaker 2: Trump up by point five. They're in the state of

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Speaker 2: Pennsylvania arguably the most important one Wisconsin, though you have

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Speaker 2: Harris up by one in Nevada. I want to come

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Speaker 2: back to this because you have Harris up by one

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Speaker 2: point six. It's a little bit different than what I've

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Speaker 2: seen elsewhere. Trump up in North Carolina, and then you

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Speaker 2: also have Wisconsin pretty well close there. So maybe explain

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Speaker 2: a little bit of where things are here in the forecast.

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Speaker 2: Also I misspoke, I apologize. Pennsylvania, you have Hairs up

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Speaker 2: by one point three. Just explain a little bit here

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Speaker 2: this margin some of the movement again that we've seen here,

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Speaker 2: and your theory of whether they'll all move together or

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Speaker 2: they won't.

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Speaker 6: Yeah, to some Pomey, they definitely will move together. But

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Speaker 6: to quiet, there still can be that gap. And if

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Speaker 6: the election is as close as the pole suggest and

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Speaker 6: there is a big pulling miss. You could absolutely see division, right,

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Speaker 6: but if either canon overperforms even by like one and

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Speaker 6: a half points, they could sweep all of them potentially. Yeah,

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Speaker 6: And I think there's something really interesting going on right because,

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Speaker 6: like the honestly, like at least since twenty twelve, we've

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Speaker 6: seen Midwestern states that are a little bit more white

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Speaker 6: like shift very very fast towards Republicans. Yeah, and Democrats

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Speaker 6: start to zoom forward in the Sun Belt so fast.

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Speaker 6: The states like Jordia that weren't even close in play,

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Speaker 6: you know, are going for them if they win the

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Speaker 6: popular vote by enough. This year, it seems like the

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Speaker 6: breaks have been stopped on both of those trends and

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Speaker 6: maybe even reversed. And I'm wondering if you have something

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Speaker 6: to do with the strategic objectives for both parties. The

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Speaker 6: iceberg for the GOP is their low performance with non

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Speaker 6: white voters that will kill them as the country becomes

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Speaker 6: majority minority. And for Democrats, the short term iceberg, the

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Speaker 6: one that almost cost them in twenty twenty and did

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Speaker 6: cost them election in sixteen, is their poor performance with

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Speaker 6: white voters. And so perhaps these as both parties achieving

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Speaker 6: their goals to some degree, which has caused the map

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Speaker 6: to kind of shift a little bit in the other direction,

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Speaker 6: where Democrats are doing better than they did in the

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Speaker 6: Midwest last time relative to the national vote, and actually

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Speaker 6: maybe even worse than Georgian Arizona.

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Speaker 5: Yeah.

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Speaker 2: So sticking with that point, you're specifically talking about Democratic

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Speaker 2: gains with white voters, probably white college educated voters, and

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Speaker 2: then Trump and get Republican performance with black and Latino votes,

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Speaker 2: specifically men, which we're about to get to.

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Speaker 3: In a little bit.

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Speaker 6: Yeah, yeah, yeah, and mostly how much it doug goes

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Speaker 6: in reality. I mean, there's a constant trend of polls

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Speaker 6: underrating Democratic support of black voters, and you know, New

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Speaker 6: York Times Nate Cohen went into this recently as one

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Speaker 6: of the possibilities, right, is that some of the supporters

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Speaker 6: that are some black voters that say they're going to

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Speaker 6: support Republicans don't often vote necessarily their low propensity voters. Yeah,

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Speaker 6: so it hasn't always shown up. Part of that's due habits,

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Speaker 6: some of that is due to the GOT efforts in

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Speaker 6: the black commun You're often targeted more towards Democratic groups, right,

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Speaker 6: and Republicans haven't really put much effort or resources in

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Speaker 6: they're just starting to where they're not going to catch

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Speaker 6: up in one cycle.

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Speaker 1: Yeah, we're going to cover in the next blocks on

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Speaker 1: the Kamala Harris's effort to reach men in general, black

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Speaker 1: men specifically. And I've had the same question in my

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Speaker 1: mind because back in twenty twenty, there were also a

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Speaker 1: lot of polls that showed like, oh, Joe Biden might

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Speaker 1: underperform with black men, but then when it came to

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Speaker 1: election day, he had the same performances Democrats typically have.

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Speaker 1: So I think that's a big question mark.

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Speaker 4: We wanted you to.

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Speaker 1: Dig into a little bit of Pennsylvania because I imagine

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Speaker 1: your assessment is the same as ours, the same with

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Speaker 1: a lot of other people, that Pennsylvania may be effectively the.

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Speaker 4: Whole ball game.

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Speaker 1: There's some interesting early voting data that I wanted you

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Speaker 1: to take a look at and tell us what, if anything,

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Speaker 1: we should make of it. Tom Bonnier, who's with Target Smart,

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Speaker 1: which is a Democratic aligned firm.

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Speaker 4: But you know, I mean, their data is just data.

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Speaker 4: She's taking a look at it.

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Speaker 1: So let's put this thread up on the screen. Let

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Speaker 1: me show you a few pieces of this. So he says,

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Speaker 1: if you look at the vote report in Pennsylvania. So

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Speaker 1: far Democrats have a solid advantage in terms of party registration.

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Speaker 1: That the gap is smaller than it was in twenty

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Speaker 1: twenty at the same point, but that doesn't tell the

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Speaker 1: whole story. Go ahead to the next one. Here we

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Speaker 1: can take a look, he says. Let's look at the

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Speaker 1: early vote by modeled partisanship, so not just what people

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Speaker 1: self identify, but what their target. Smart modeling suggests their

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Speaker 1: vote will be. It shows a wider dem lead than

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Speaker 1: at this point in twenty twenty.

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Speaker 4: Why is that.

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Speaker 1: The answer as simple, the model believes that the unaffiliate

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Speaker 1: voters are more Democratic than they were in twenty twenty.

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Speaker 1: If we could go to the next one as well,

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Speaker 1: He's been pointing out that there appears to have been

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Speaker 1: in multiple states a huge surge in Black women registering

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Speaker 1: to vote and so far also turning out to vote.

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Speaker 1: He says, looking at the racial breakdown of women early

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Speaker 1: voters in PA, we see the biggest increases among women

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Speaker 1: of color, especially Black women, whose turnout is two hundred

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Speaker 1: and forty eight percent of their turnout at this point

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Speaker 1: in twenty twenty, compared to one hundred and forty six

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Speaker 1: percent for white women, so women in general turning out

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Speaker 1: at higher rates than they do in twenty twenty. What,

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Speaker 1: if anything, do you make of these numbers? How should

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Speaker 1: we think about these things?

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Speaker 6: Yeah, I don't know if it can tell us too

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Speaker 6: much about who's going to win, because it's so hard

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Speaker 6: to interpret early vote accurately, especially getting how much the

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Speaker 6: electorate is changing with the early voting habits post COVID.

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Speaker 6: That being said, it does tell us a story of

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Speaker 6: what the parties you're trying to do and whether they're

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Speaker 6: being successful. Republicans were trying really hard to reverse some

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Speaker 6: of the fears about early voting and voting by mail, Jess.

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Speaker 6: Maybe they've made some ground on that front. That doesn't

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Speaker 6: mean they're going to win the election. Some of these

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Speaker 6: guys would have voted on election day. But it's a

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Speaker 6: lot easier when you have a GOTV operation to get

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Speaker 6: people to vote early because you don't have to then

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Speaker 6: worry about them in the final stretch, and you can

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Speaker 6: focus your resource.

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Speaker 1: You can kind of check them off and focus on

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Speaker 1: the people who you're still working to persuade to.

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Speaker 6: Turn out exactly, and then on the democratic front, right

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Speaker 6: as we're just talking about the fear is, how are

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Speaker 6: they going to have the same level of turnouf with

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Speaker 6: black voters, especially in Philadelphia and Milwaukee. And so we're

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Speaker 6: seeing some good signs in Pennsylvania Wisconsin on that front

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Speaker 6: for Dems. And you know, turnout was high across the board.

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Speaker 6: It was a little lower in some of these cities.

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Speaker 6: And twenty twenty relative to the rest of the state,

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Speaker 6: Democrats managed to win anyway, and you know they're hoping

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Speaker 6: that that doesn't happen in twenty twenty four. And this

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Speaker 6: is a sign that they're planned to change. This is working.

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Speaker 6: And you know, the Harris campaign, everyone says has a

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Speaker 6: pretty great GEOTV operation. I think there's a question mark

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Speaker 6: on Trump's because he has had his super packs take

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Speaker 6: the lead on that they're using some new stratus jeez,

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Speaker 6: and could work out. It could also kind of blow

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Speaker 6: up in their face. And a lot of GOP operatives

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Speaker 6: are worried about that.

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Speaker 5: That.

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Speaker 1: Well, Elon is a big part of the turn on

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Speaker 1: operation of Pennsylvania.

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Speaker 3: Yes, the America Pack.

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Speaker 6: Yes, yeah, So sometimes innovation in politics is very important

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Speaker 6: can work.

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Speaker 5: And Elon himself is kind of interesting because.

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Speaker 6: The guy either kills it or it fails it's a

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Speaker 6: good way for that's a very good way for you.

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Speaker 3: Can we put the New York Times pull up on screen?

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Speaker 2: I want to talk to you about this A four

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Speaker 2: please mystery repeats Harris up by four and Pa, according

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Speaker 2: to the New York Times, Trump up by six in Arizona.

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Speaker 2: So there was a previous theory that all seven swing

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Speaker 2: states would either go one way or the other way

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Speaker 2: kind of how they did in twenty twenty. This time,

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Speaker 2: like you just said, we see a rid of a

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Speaker 2: reversal in that trend. This both of the parties are

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Speaker 2: fighting to accomplish the two things that cost them previous elections.

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Speaker 2: Is that what you see going on here? What are

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Speaker 2: the key characteristics of why and how there could be

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Speaker 2: a ten point spread between these two critical swing states.

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Speaker 6: So I think it's unlikely it's that big, but it's possible. Right,

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Speaker 6: it's probably the spread of Polsters have it, or at

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Speaker 6: least anything I can think of off the cuff. But

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Speaker 6: the New York Times theory of the case, and they're smart,

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Speaker 6: so maybe they're right. Yeah, is that Democrats are genuinely

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Speaker 6: doing better with white voters, especially white college educated voters,

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Speaker 6: and that is enabling them to do better in the Midwest,

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Speaker 6: but they are losing ground with non white voters and

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Speaker 6: therefront and performing in the sun Belt. So they see

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Speaker 6: the national vote being worse for Democrats and a lot

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Speaker 6: closer than everyone else's showing right now, and they show

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Speaker 6: but they still have Democrats winning for that Midwest path.

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Speaker 2: And that would be a twenty twenty two scenario, right

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Speaker 2: because that's what we talked a lot about yesterday. Times

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Speaker 2: both budding on this political realignment. In this scenario, would

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Speaker 2: you expect Arizona, Georgia, and Nevada to all move similarly?

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Speaker 2: Because I saw it in your forecast. You have Nevada

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Speaker 2: Harris up, but you know I've seen Trump up there

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Speaker 2: almost by six points in some places, which is a

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Speaker 2: crazy reversal. When's the last time Republicans one, I want

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Speaker 2: to say two thousand and four.

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Speaker 3: Yes, it's a long time.

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Speaker 6: I saw the same pole, and I think that one

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Speaker 6: was an ally. I'd be shocked if you one. I

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Speaker 6: want to be shocked to be one about it, but

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Speaker 6: I'd be shocked be one by six. I think that

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Speaker 6: Nevada is probably a little easier for Dems than maybe

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Speaker 6: even the other three Midwest states. Based off the current polling.

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Speaker 6: But it's a hard state to poll, and the GOP

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Speaker 6: it's been their white whale, and it's not because it's

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Speaker 6: an uncatchable one.

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Speaker 5: They're barely losing.

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Speaker 3: Yet every time it's like this close, so they could win.

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Speaker 6: And in twenty fourteen they just had Democrats went completely

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Speaker 6: a wall in the state and PLP won the House

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Speaker 6: seats by combined eighteen percent. I think they won the

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Speaker 6: governor race by forty. So like there's the you can't

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Speaker 6: roll out of. It is a reason it's on the

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Speaker 6: swing state list.

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Speaker 1: Yeah, I mean it's such a unique state demographically, and

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Speaker 1: also just with the union density and the nature of

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Speaker 1: the i mean the culinary workers union and how much

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Speaker 1: the service sector are dominated. So it's not like you know,

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Speaker 1: hardcat construction unions which have really shifted towards Trump.

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Speaker 4: It's the service.

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Speaker 1: Sector unions which have stayed more in the Democratic camp.

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Speaker 1: But you know, still you have a state where there

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Speaker 1: was hit very hard by COVID, where economic concerns are

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Speaker 1: really paramount, where the demographics may not at this point

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Speaker 1: in time, particularly favor Democrats in terms of you know,

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Speaker 1: some of the realignments and some of the ships. But

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Speaker 1: you know, to go back to your point about if

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Speaker 1: the New York Times theory is correct about the shifts

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Speaker 1: in the electorate, if Kamala Harris wins those quote unquote

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Speaker 1: blue Wall states but loses all the other ones, she

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Speaker 1: wins two seventy to sixty eight, Like I mean, right,

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Speaker 1: am I doing that math right as close as it

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Speaker 1: could effectively possibly with Nebraska, with which kind of terrifies me,

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Speaker 1: just given the way that the post election last time went,

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Speaker 1: with all the conspiracy theories and all of the ink

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Speaker 1: January six and all of the chaos. Like, if it

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Speaker 1: is that razor thin, I think we're in. I won't

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Speaker 1: ask you to a pine on that piece, but I

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Speaker 1: think we're in for some very troubled times post election day.

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Speaker 1: If it is truly that narrow of a margin.

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Speaker 5: I know what you're talking about, Chris. So I think

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Speaker 5: everyone in the country will handle that very piece.

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Speaker 1: Somewhere's gonna be like, Okay, we're so great, we congratulate

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Speaker 1: our new presidential victor.

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Speaker 4: We'll I'll move forward.

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Speaker 1: I wanted to add I did want you to have

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Speaker 1: pine though on this phenomena of quote unquote trash polls

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Speaker 1: and whether you think this is a real thing. We

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Speaker 1: could put the real clear politics average up here. These

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Speaker 1: are all of the pencil recent Pennsylvania polls, and many

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Speaker 1: of them are favoring Trump, but also many of them.

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Speaker 4: Are partisan polls.

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Speaker 1: A few of them are ones that I think you

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Speaker 1: could you could classify in that junk poll or trash

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Speaker 1: pole status. So talk to us about the rise of

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Speaker 1: some of these new pollsters and how we should be

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Speaker 1: thinking about that in terms of these these states and

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Speaker 1: these numbers.

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Speaker 6: Yeah, well, you know, I don't really like to talk

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Speaker 6: about this, and my fellow you know, polster pull averagers

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Speaker 6: out there, but RCB does have a bit of a

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Speaker 6: tendency to include some of the GOP internal polls and

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Speaker 6: managed to take off some of the high quality polls

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Speaker 6: that might show that Democrats ahead sometimes.

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Speaker 5: So yeah, it might be a little skewed.

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Speaker 6: I think there is some concerns, especially for as Musen Trafalgar,

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Speaker 6: you know as Muson in particular. They had a poll

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Speaker 6: a year ago that they put out that they said

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Speaker 6: proved that doctor Fauci had killed more people than anyone

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Speaker 6: since the Holocaust.

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Speaker 5: And so there's five thirty eight.

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Speaker 4: Then I'd exactly like straight shooting.

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Speaker 6: With that, I don't bet almost anyone, right, Like I

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Speaker 6: might lower the rating, but like it's a high standard

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Speaker 6: for me.

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Speaker 5: But Resnution just kind of met that and vaulted over it.

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Speaker 5: So some of these are a little less reputable than Okay.

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Speaker 2: Well, My question though, is and the reason why I'm

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Speaker 2: focusing on it, is that this was such a key

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Speaker 2: part of the twenty twenty two story. Is that if

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Speaker 2: you had and I put this out like a couple

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Speaker 2: of days ago, and one of the common responses I

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Speaker 2: got is, look, you know, even by Republicans, they're like, look,

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Speaker 2: liberals are not wrong. But there were a lot of

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Speaker 2: crappy stuff in the overall polling averages leading up to

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Speaker 2: twenty twenty two, which led to a false picture where

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Speaker 2: if you scroll down and you look at Maris, New

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Speaker 2: York Times, Sienna, they all mostly had Fetterman up by

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Speaker 2: a couple of points, and they were right right. And

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Speaker 2: so if we want to for the viewer out there

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Speaker 2: who doesn't just want who wants to look for themselves

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Speaker 2: and try and figure this out not necessarily rely on

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Speaker 2: a waiting measure, how should they think about it? Like,

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Speaker 2: how do you think about it when you're rating different people.

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Speaker 2: Is it just accuracy?

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Speaker 3: Is it?

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Speaker 2: You know, like samples, just talk to us about that,

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Speaker 2: because I think we have an audience that really wants

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Speaker 2: to get in the ways here.

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Speaker 5: Yeah, yeah, I think. I think. I guess she's a

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Speaker 5: big part of it.

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Speaker 6: And you know, it does just because you got to

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Speaker 6: right one cycle doesn't mean you get it right the

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Speaker 6: next cycle.

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Speaker 3: Right.

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Speaker 6: And a lot of these posters have a tendency to

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Speaker 6: miss a little to the left, a little to the right,

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Speaker 6: and it makes it harder. Sometimes they change their approach.

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Speaker 6: Emerson used to miss to the left. Now they appear

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Speaker 6: to be to the right of most polsters change their strategy,

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Speaker 6: so that makes it a little harder.

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Speaker 5: I would say, I think one.

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Speaker 1: Of the ones that's shifted to the self identification of

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Speaker 1: like you know how you voted last time.

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Speaker 6: I believe that Emerson uses that, but I'm not absolutely

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Speaker 6: sure they definitely include that in all of their polls. Yeah,

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Speaker 6: and that's also that's a really good point, right, Like

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Speaker 6: that's the gamble polsters. Some posters are taking some of

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Speaker 6: like the Maybe they're not like New York Times or

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Speaker 6: Maris like the top ones, but ones that are still rapputable.

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Speaker 5: It's sort of like a shortcut.

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Speaker 6: They're saying, Okay, if the electric's like e's actually like

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Speaker 6: twenty twenty, how are these voters going to vote? But

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Speaker 6: we know for in fact the electric's not going to

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Speaker 6: be like twenty twenty. Yeah, right, because that was the

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Speaker 6: highest turnout election in American history, if we unless we

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Speaker 6: go back before women had the right to vote, and

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Speaker 6: which I don't think we should.

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Speaker 2: You said previously, you talked about how you think turnout

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Speaker 2: will be a little bit less this time around. So

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Speaker 2: where do you think things was around twenty sixteen twenty twenty, Like,

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Speaker 2: what are our benchmarks here?

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Speaker 5: You're making to hire for me? It's lolasier to be

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Speaker 5: right if I just take less than.

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Speaker 3: The highest turnout. Yeah, yeah, I.

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Speaker 5: Don't really know to answer that question.

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Speaker 6: That's such a hard one to estimate, And that is

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Speaker 6: why Poster's job is so hard, because you have to

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Speaker 6: get a sample of the electorate with people who aren't

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Speaker 6: responding to phone calls as much to get an idea

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Speaker 6: of both how likely they are to vote and who

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Speaker 6: are they going to vote for instead. Honestly, the best

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Speaker 6: approach are ones like selzer uses in Iowa, where you

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Speaker 6: just call people on voter registration files and you ask

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Speaker 6: you figure out how likely they are to vote by

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Speaker 6: asking them some questions, then you can project turnout. But

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Speaker 6: even then you get that's part of why polls are

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Speaker 6: a lot more accurate at the last second, because it's

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Speaker 6: not just that people change their mind, is that people

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Speaker 6: might commit to voting or not voting.

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Speaker 3: Yes, yeah, that's such a key point.

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Speaker 4: Yeah, that is a great point.

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Speaker 1: Let's kind of move on to the Senate forecast, and

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Speaker 1: for those of you who are premium subscribers, we're gonna

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Speaker 1: have this posted early exclusively for you. We're gonna have

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Speaker 1: a posted later in the week for all. But if

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Speaker 1: you want to get this heads up straight from Logan

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Speaker 1: as soon as possible, which we know you all do,

441
00:18:16,520 --> 00:18:19,760
Speaker 1: go and subscribe Breakingpoints dot com. All right, let's go

442
00:18:19,800 --> 00:18:21,400
Speaker 1: and put up this.

443
00:18:25,119 --> 00:18:28,119
Speaker 2: Kamala Harris is out with some new policy proposals. She

444
00:18:28,200 --> 00:18:31,400
Speaker 2: needs to win over black voters, specifically black mail voter,

445
00:18:31,520 --> 00:18:35,200
Speaker 2: so she appeared on the Shade Room Predominantly black podcast.

446
00:18:35,240 --> 00:18:37,000
Speaker 3: We're going to talk about that. Let's take a listen.

447
00:18:37,160 --> 00:18:41,760
Speaker 7: President Barack Obama, he was campaigning for you in Pittsburgh

448
00:18:41,840 --> 00:18:45,040
Speaker 7: before some students at the University of Pittsburgh, which is

449
00:18:45,040 --> 00:18:49,200
Speaker 7: my alma mater, and he said some things that really

450
00:18:49,400 --> 00:18:50,720
Speaker 7: ruffled some feathers.

451
00:18:50,320 --> 00:18:50,879
Speaker 5: In the news.

452
00:18:51,040 --> 00:18:54,480
Speaker 7: He said, it makes me think you aren't just feeling

453
00:18:54,480 --> 00:18:56,880
Speaker 7: the idea of having a woman as a president. You're

454
00:18:56,920 --> 00:18:59,600
Speaker 7: coming up with other alternatives and other reasons for that.

455
00:19:00,080 --> 00:19:01,919
Speaker 7: We have not seen the same kind of energy and

456
00:19:01,920 --> 00:19:05,200
Speaker 7: turnout in all corners of our neighborhoods and community as

457
00:19:05,200 --> 00:19:08,440
Speaker 7: we saw when I was running. So when you hear

458
00:19:08,480 --> 00:19:10,680
Speaker 7: those words, I'm sure you were briefed on the situation.

459
00:19:11,359 --> 00:19:13,879
Speaker 7: You know, a former Ohio State Senator Nina Turner, she

460
00:19:13,960 --> 00:19:16,879
Speaker 7: came out on CNN and said, why are you, you know,

461
00:19:16,920 --> 00:19:19,560
Speaker 7: putting black men up against the wall and pressuring them

462
00:19:19,560 --> 00:19:22,199
Speaker 7: into something that possibly, you know, they don't want to

463
00:19:22,200 --> 00:19:23,719
Speaker 7: do if they want to vote for you or not.

464
00:19:23,800 --> 00:19:26,040
Speaker 7: So my question to you is do you think that

465
00:19:26,080 --> 00:19:28,920
Speaker 7: what President Obama said was the right thing to say.

466
00:19:30,320 --> 00:19:32,440
Speaker 8: Let me tell you, I am very proud to have

467
00:19:32,560 --> 00:19:37,680
Speaker 8: the support of President Obama and that he is out

468
00:19:38,040 --> 00:19:41,280
Speaker 8: traveling to talk with voters about what is at stake

469
00:19:41,320 --> 00:19:41,959
Speaker 8: in this election.

470
00:19:42,800 --> 00:19:44,160
Speaker 4: I'm very proud.

471
00:19:43,960 --> 00:19:46,040
Speaker 3: To have his support.

472
00:19:46,480 --> 00:19:50,080
Speaker 8: What is also important is one to understand, like, as

473
00:19:50,119 --> 00:19:52,520
Speaker 8: I said, I intend to earn the vote of everyone,

474
00:19:53,160 --> 00:19:58,680
Speaker 8: including black men. Two, pay attention to everything that President

475
00:19:58,680 --> 00:20:02,240
Speaker 8: Obama talked about, because he talked about at length.

476
00:20:02,280 --> 00:20:03,800
Speaker 3: The danger of Donald Trump.

477
00:20:04,960 --> 00:20:08,960
Speaker 8: The danger I think is really important to focus on

478
00:20:09,160 --> 00:20:13,480
Speaker 8: the stakes of this election. And there are two choices,

479
00:20:14,960 --> 00:20:21,640
Speaker 8: two choices. And I ask everyone to look at the background,

480
00:20:21,800 --> 00:20:24,000
Speaker 8: look at the work, look at the words.

481
00:20:24,280 --> 00:20:27,919
Speaker 2: Hmm, all right, so pretty clearly she is she may

482
00:20:27,960 --> 00:20:30,239
Speaker 2: not be too so happy with Barack Obama. He's put

483
00:20:30,280 --> 00:20:33,440
Speaker 2: her in a little bit of a bind. I mean, look,

484
00:20:33,680 --> 00:20:37,479
Speaker 2: anybody running for office as opposed to Obama, in his

485
00:20:38,320 --> 00:20:43,480
Speaker 2: masterly sinecure just lecturing all of us mere mortals, actually

486
00:20:43,520 --> 00:20:45,680
Speaker 2: has to grapple with like he no longer has to

487
00:20:45,680 --> 00:20:47,960
Speaker 2: get himself elected. And also I would say he never

488
00:20:48,040 --> 00:20:49,840
Speaker 2: did that when he was trying to get himself elected.

489
00:20:50,080 --> 00:20:54,080
Speaker 2: It's only now that he's influencer Netflix, Obomba, his.

490
00:20:54,080 --> 00:20:57,600
Speaker 1: Era, the whole like my Brother's Keeper thing. It's pretty

491
00:20:57,600 --> 00:21:01,960
Speaker 1: consistent with his politics of you know, black respectability.

492
00:21:02,280 --> 00:21:03,119
Speaker 3: I think you're not wrong.

493
00:21:03,200 --> 00:21:04,880
Speaker 2: I guess I would just put it as like this

494
00:21:05,040 --> 00:21:07,360
Speaker 2: nakedness of I mean, he literally was like I want

495
00:21:07,359 --> 00:21:09,840
Speaker 2: to speak to the brothers out there, I'd be like,

496
00:21:09,960 --> 00:21:13,399
Speaker 2: some of y'all ain't voting for women, and you're making

497
00:21:13,440 --> 00:21:16,240
Speaker 2: things up. I'm like, dude, you are literally trying to

498
00:21:16,240 --> 00:21:19,320
Speaker 2: tell people not only what to think, but if what

499
00:21:19,359 --> 00:21:20,080
Speaker 2: they think.

500
00:21:20,000 --> 00:21:21,879
Speaker 3: Is not going along with you, that you're a straight

501
00:21:21,960 --> 00:21:22,720
Speaker 3: up sexist.

502
00:21:23,080 --> 00:21:25,680
Speaker 2: That is an insane thing to do for any group,

503
00:21:25,760 --> 00:21:28,119
Speaker 2: not just black people. I mean, if some Indian person

504
00:21:28,200 --> 00:21:30,919
Speaker 2: was to my Indian brothers out there.

505
00:21:30,680 --> 00:21:32,119
Speaker 3: Like, who the fuck are you.

506
00:21:32,119 --> 00:21:32,720
Speaker 4: To be talking?

507
00:21:32,960 --> 00:21:35,760
Speaker 1: I have to think, yeah, well, I mean I think

508
00:21:35,960 --> 00:21:39,439
Speaker 1: so two things are possible. One is that he actually

509
00:21:39,560 --> 00:21:42,199
Speaker 1: got crosswise with the way Kamala wanted to message this.

510
00:21:42,280 --> 00:21:45,800
Speaker 1: And that's actually my guess because she has been very

511
00:21:45,840 --> 00:21:49,399
Speaker 1: careful to not fall into the Hillary Clinton trap of

512
00:21:49,480 --> 00:21:54,320
Speaker 1: being you know, actively contemptfual of voters or messaging like

513
00:21:54,600 --> 00:21:57,440
Speaker 1: she doesn't have to earn their vote, she's just entitled

514
00:21:57,440 --> 00:21:57,840
Speaker 1: to it.

515
00:21:58,200 --> 00:21:59,960
Speaker 4: Also, she's really.

516
00:21:59,680 --> 00:22:03,600
Speaker 1: Of thank god this messaging around like what's important about

517
00:22:03,640 --> 00:22:07,320
Speaker 1: this election is my trailblazing status, Like she has dodged.

518
00:22:07,040 --> 00:22:08,960
Speaker 4: All of that, even you'll recall, And she.

519
00:22:08,960 --> 00:22:11,560
Speaker 1: Got asked that question on CNN by Dana Pash of

520
00:22:11,720 --> 00:22:15,720
Speaker 1: like like teed her up to trash Trump over his

521
00:22:15,760 --> 00:22:18,000
Speaker 1: comments about she's not really black or whatever, She's just

522
00:22:18,040 --> 00:22:21,040
Speaker 1: like same old playbook, Let's move on, And so I

523
00:22:21,080 --> 00:22:24,000
Speaker 1: think it's likely that she's actually not happy about this

524
00:22:24,080 --> 00:22:28,520
Speaker 1: messaging from Obama. It's also possible, though, that they feel

525
00:22:28,520 --> 00:22:29,960
Speaker 1: like he has the.

526
00:22:30,119 --> 00:22:34,280
Speaker 4: Cred to lecture black He doesn't. Nobody does.

527
00:22:34,320 --> 00:22:38,920
Speaker 1: No one should right to lecture blackmail voters. Whereas obviously

528
00:22:38,960 --> 00:22:41,119
Speaker 1: if it was her trying to pull that off, it

529
00:22:41,160 --> 00:22:43,800
Speaker 1: would go even more poorly than it did with Obama.

530
00:22:43,840 --> 00:22:44,639
Speaker 4: But I don't know.

531
00:22:44,720 --> 00:22:46,600
Speaker 1: I thought with her pivot there, it seemed to me

532
00:22:46,720 --> 00:22:50,359
Speaker 1: like she was actively unhappy about this direction. When we

533
00:22:50,359 --> 00:22:53,240
Speaker 1: were talking to Logan previously, you mentioned that there is

534
00:22:53,359 --> 00:22:55,359
Speaker 1: a lot of discussion online of like, oh, Kamala is

535
00:22:55,400 --> 00:22:57,879
Speaker 1: doing this media blitz now because their internals must be

536
00:22:57,920 --> 00:23:00,760
Speaker 1: really poor, and by and large, I think Logan analysis

537
00:23:00,760 --> 00:23:03,119
Speaker 1: of like, also, it's almost election day, and like, of

538
00:23:03,160 --> 00:23:06,240
Speaker 1: course the candidates are likely to be doing media appearances.

539
00:23:06,520 --> 00:23:09,159
Speaker 1: I think that's largely true, but it does seem like

540
00:23:09,240 --> 00:23:12,959
Speaker 1: there is a particular nervousness around black mail voters.

541
00:23:12,960 --> 00:23:15,520
Speaker 3: Specifically, that is true, she's doing Charlemagne today.

542
00:23:15,359 --> 00:23:19,679
Speaker 1: As evidenced by this podcast Charlemagne the you know, the

543
00:23:19,720 --> 00:23:22,480
Speaker 1: policy proposals we're about to talk about and rip apart

544
00:23:22,920 --> 00:23:25,919
Speaker 1: the Obama comments, et cetera. There does seem to be

545
00:23:25,960 --> 00:23:29,760
Speaker 1: some nervousness about that specific demographic group that they're kind

546
00:23:29,800 --> 00:23:31,440
Speaker 1: of telegraphing in some of these moves.

547
00:23:31,480 --> 00:23:33,680
Speaker 2: Absolutely, because I mean, look, it's a game of margins,

548
00:23:33,720 --> 00:23:35,440
Speaker 2: and it's one of those where I guess just stick

549
00:23:35,480 --> 00:23:37,040
Speaker 2: on this point. You know, everyone's like, oh, the internals

550
00:23:37,119 --> 00:23:39,240
Speaker 2: must be bad if she's going on Fox News, I rogan,

551
00:23:39,280 --> 00:23:40,720
Speaker 2: I'm like, what if the internal show that it's a

552
00:23:40,760 --> 00:23:42,520
Speaker 2: fifty to fifty race, and if I had only a

553
00:23:42,560 --> 00:23:45,440
Speaker 2: fifty percent shot of accomplishing the single most important thing

554
00:23:45,720 --> 00:23:47,600
Speaker 2: I'll ever do in my life, I would be doing

555
00:23:47,640 --> 00:23:50,400
Speaker 2: some crazy shit to make sure that that got from

556
00:23:50,400 --> 00:23:52,880
Speaker 2: fifty to fifty one to fifty two. Even fifty point

557
00:23:52,920 --> 00:23:55,359
Speaker 2: five is better than fifty. So maybe that's just me.

558
00:23:55,480 --> 00:23:57,679
Speaker 2: But let's put B two up on the screen just

559
00:23:57,720 --> 00:24:00,720
Speaker 2: to set up again why this policy propose is coming

560
00:24:00,880 --> 00:24:03,479
Speaker 2: from Harry anton Over at CNN. No matter how you

561
00:24:03,480 --> 00:24:06,160
Speaker 2: splice the data, Trump seems to be the strongest Republican

562
00:24:06,200 --> 00:24:09,560
Speaker 2: with black voters since nineteen sixty. Young black men in

563
00:24:09,600 --> 00:24:12,720
Speaker 2: particular have trended right towards Trump runs, cutting the DEM

564
00:24:12,760 --> 00:24:15,720
Speaker 2: margin by forty points from twenty twelve. But Trump is

565
00:24:15,760 --> 00:24:18,800
Speaker 2: doing historically well with black women too, So that is

566
00:24:18,840 --> 00:24:21,080
Speaker 2: the key point is that this is the biggest realignment

567
00:24:21,119 --> 00:24:23,879
Speaker 2: of black voters, at least poised to be since the

568
00:24:23,920 --> 00:24:24,800
Speaker 2: Civil rights era.

569
00:24:25,040 --> 00:24:29,840
Speaker 1: I want to say though that I I'm reserving judgment

570
00:24:29,920 --> 00:24:32,600
Speaker 1: until it actually happens. Sure, because we did see these

571
00:24:32,640 --> 00:24:37,240
Speaker 1: same trends heading into the Biden twenty twenty run, where

572
00:24:37,359 --> 00:24:39,919
Speaker 1: you know, he was trailing how Hillary Clinton did, and

573
00:24:39,960 --> 00:24:42,080
Speaker 1: there was a big discussion about this, and on an

574
00:24:42,119 --> 00:24:44,959
Speaker 1: election day, black voters overall showed up for him and

575
00:24:45,080 --> 00:24:50,280
Speaker 1: basically the same numbers as previously. So and there has

576
00:24:50,400 --> 00:24:52,440
Speaker 1: been some polling that's been contradictory. And I put a

577
00:24:52,480 --> 00:24:53,920
Speaker 1: lot of stock in the New York Times pool because

578
00:24:53,920 --> 00:24:56,520
Speaker 1: they did a super sample of black voters. That means

579
00:24:56,520 --> 00:24:58,840
Speaker 1: they had a larger groups that were able to look more,

580
00:24:58,920 --> 00:25:01,720
Speaker 1: you know, in detail at this data. But there have

581
00:25:01,800 --> 00:25:04,199
Speaker 1: been other polls that have show Kamala performing just as

582
00:25:04,200 --> 00:25:07,000
Speaker 1: well with black voters as Biden did last time around.

583
00:25:07,400 --> 00:25:09,720
Speaker 1: So to me, it's not definitive that this is going

584
00:25:09,800 --> 00:25:12,480
Speaker 1: to manifest, but there's certainly been a significant amount of

585
00:25:12,480 --> 00:25:15,679
Speaker 1: polling data that suggests it could. And as I said before,

586
00:25:16,080 --> 00:25:19,320
Speaker 1: the Kamala Harris team seems to be projecting some nervousness

587
00:25:19,320 --> 00:25:22,159
Speaker 1: that this trend with black men in particular could be

588
00:25:22,200 --> 00:25:26,600
Speaker 1: the case. I'm fairly persuaded with the numbers on how

589
00:25:26,640 --> 00:25:29,760
Speaker 1: many new black women registered to vote and are showing

590
00:25:29,840 --> 00:25:31,720
Speaker 1: up in the early voting periods and the states that

591
00:25:31,760 --> 00:25:34,000
Speaker 1: we have data to say, I don't think that she

592
00:25:34,119 --> 00:25:36,120
Speaker 1: probably is going to have an issue there with black women.

593
00:25:36,200 --> 00:25:39,920
Speaker 1: We also see women in general this large gender gap

594
00:25:39,960 --> 00:25:42,720
Speaker 1: in you know, with women favoring Kamala and a large

595
00:25:42,720 --> 00:25:46,400
Speaker 1: gender gap with men more favorable towards Trump. So I'm

596
00:25:46,440 --> 00:25:49,320
Speaker 1: definitely more skeptical about the black women piece of this,

597
00:25:49,520 --> 00:25:52,120
Speaker 1: but I think it's definitely possible with black men.

598
00:25:52,200 --> 00:25:52,880
Speaker 3: Yeah, definitely.

599
00:25:52,920 --> 00:25:57,280
Speaker 2: And well, again to underscore I guess the policy proposal,

600
00:25:57,320 --> 00:25:59,560
Speaker 2: whether they whether it's true or not, they seem to

601
00:25:59,560 --> 00:26:01,400
Speaker 2: believe it and they're acting in that way.

602
00:26:01,400 --> 00:26:02,719
Speaker 3: So let's put this up on the screen.

603
00:26:03,240 --> 00:26:08,040
Speaker 2: Kamala now has some new opportunity agenda for black men.

604
00:26:08,119 --> 00:26:11,280
Speaker 2: Let me just go through it. Provide one million loan

605
00:26:11,560 --> 00:26:14,520
Speaker 2: dollar loans one million loans that are fully forgivable up

606
00:26:14,560 --> 00:26:17,080
Speaker 2: to twenty thousand dollars for black entrepreneurs and others to

607
00:26:17,080 --> 00:26:22,399
Speaker 2: start a business. Support education, training and mentorship programs that

608
00:26:22,520 --> 00:26:25,520
Speaker 2: lead to good paying jobs for black men, including pathways

609
00:26:25,520 --> 00:26:30,120
Speaker 2: to become teachers. Protect cryptocurrency investments so black men who

610
00:26:30,160 --> 00:26:32,960
Speaker 2: make them know that their money is safe. Launch a

611
00:26:33,119 --> 00:26:38,400
Speaker 2: national health initiative focused on illnesses that disproportionately impact black men.

612
00:26:38,760 --> 00:26:44,680
Speaker 2: And legalize recreational marijuana to create opportunities for Black Americans

613
00:26:44,760 --> 00:26:49,040
Speaker 2: to succeed in this new industry. You called it peak neoliberalism,

614
00:26:49,080 --> 00:26:53,000
Speaker 2: and I genuinely do think that is so accurate because

615
00:26:53,560 --> 00:26:55,560
Speaker 2: I mean, let's just fix cite.

616
00:26:55,400 --> 00:26:57,040
Speaker 3: On this a little bit. So we're going to provide

617
00:26:57,080 --> 00:26:58,600
Speaker 3: a million dollars in loans.

618
00:26:58,320 --> 00:27:01,399
Speaker 2: To specifically people for the their skin. M Okay, so

619
00:27:01,440 --> 00:27:02,840
Speaker 2: we're going to affirmatively it doesn't.

620
00:27:02,600 --> 00:27:05,120
Speaker 4: Mean to say it says black entrepreneurs and others. Oh yeah,

621
00:27:05,119 --> 00:27:06,240
Speaker 4: so it's not even really clear.

622
00:27:06,880 --> 00:27:09,160
Speaker 2: It's just okay, Well, I guess then we're just cherry

623
00:27:09,200 --> 00:27:11,119
Speaker 2: picking what exactly that means. Some of it will go

624
00:27:11,119 --> 00:27:15,040
Speaker 2: to black people. Cool, we're going to support mentorship programs.

625
00:27:15,200 --> 00:27:17,360
Speaker 2: I want everyone out there in your life to ask

626
00:27:17,400 --> 00:27:20,040
Speaker 2: yourself if you want a mentor provided to you by

627
00:27:20,040 --> 00:27:23,840
Speaker 2: the government. That's an insane thing to do. We're going

628
00:27:23,920 --> 00:27:28,520
Speaker 2: to provide government mentor. Here is your government issued mentor

629
00:27:28,680 --> 00:27:31,600
Speaker 2: to make sure that you live a better life.

630
00:27:31,600 --> 00:27:33,600
Speaker 1: And that is some pure Obama eraship.

631
00:27:33,680 --> 00:27:35,480
Speaker 4: Yeah, definitely, it really is.

632
00:27:35,600 --> 00:27:38,200
Speaker 1: I mean that was like his My Brother's Keeper program

633
00:27:38,240 --> 00:27:39,960
Speaker 1: and all of that. But yeah, I mean I saw

634
00:27:40,240 --> 00:27:44,000
Speaker 1: Perry Bacon Jr. Who's I think he's still the Washington Post, right,

635
00:27:44,480 --> 00:27:49,199
Speaker 1: the Washing Post previously at NBC, himself a black man, saying, like,

636
00:27:49,560 --> 00:27:51,960
Speaker 1: you know, I don't really love the idea being put

637
00:27:52,000 --> 00:27:55,720
Speaker 1: out there that black men specifically need mentors. The other

638
00:27:55,760 --> 00:27:58,720
Speaker 1: one that really gets me is, okay, crypto, let's just

639
00:27:58,760 --> 00:27:59,960
Speaker 1: put a pin in that, because I have a lot

640
00:28:00,240 --> 00:28:02,560
Speaker 1: to say about that one.

641
00:28:02,720 --> 00:28:03,560
Speaker 4: The health one.

642
00:28:04,440 --> 00:28:07,080
Speaker 1: So they describe this in you know, in the greater

643
00:28:07,160 --> 00:28:14,160
Speaker 1: detailed part as a National Equity Health Initiative focused from

644
00:28:14,200 --> 00:28:17,879
Speaker 1: the like National Institute of Health on illnesses that disproportionately

645
00:28:17,920 --> 00:28:20,760
Speaker 1: impact black men. And this is where I really can

646
00:28:20,800 --> 00:28:23,199
Speaker 1: dig into how what I mean by like this is

647
00:28:23,200 --> 00:28:27,359
Speaker 1: the peak of neoliberalism, Why can't you just run on

648
00:28:28,040 --> 00:28:30,560
Speaker 1: universal health care so that we don't have to pick

649
00:28:30,600 --> 00:28:34,320
Speaker 1: and choose, Like, oh, if you got prostate cancer, maybe

650
00:28:34,320 --> 00:28:36,760
Speaker 1: we'll care about that and do a health equity initiative,

651
00:28:36,800 --> 00:28:39,720
Speaker 1: not even giving you care, but some study at the NIH,

652
00:28:39,960 --> 00:28:42,640
Speaker 1: thank you very much, Or like oh, if you need.

653
00:28:42,560 --> 00:28:44,080
Speaker 4: IVF, maybe we'll pay for that.

654
00:28:44,320 --> 00:28:47,520
Speaker 1: How about we just have healthcare that would, yes, actually

655
00:28:47,560 --> 00:28:51,480
Speaker 1: disproportunately benefit black men and other marginalized group, but would

656
00:28:51,520 --> 00:28:56,480
Speaker 1: help everybody and you know, not be like pathetically inadequate

657
00:28:56,520 --> 00:28:59,640
Speaker 1: and patronizing as many of these things are. And that's

658
00:28:59,640 --> 00:29:02,040
Speaker 1: what drives crazy about this is We've talked about this

659
00:29:02,080 --> 00:29:06,120
Speaker 1: a nauseum, but it's just worth reminding people the policies.

660
00:29:06,200 --> 00:29:08,840
Speaker 1: I'm not saying that it is never the case that

661
00:29:08,920 --> 00:29:10,920
Speaker 1: it makes sense to have policies that are specific to

662
00:29:10,960 --> 00:29:13,560
Speaker 1: a demographic group. I'm not saying that like blanket across

663
00:29:13,600 --> 00:29:17,040
Speaker 1: the board, but we know from history that the policies

664
00:29:17,080 --> 00:29:20,840
Speaker 1: that have most improved the lives and economic status of

665
00:29:20,880 --> 00:29:25,200
Speaker 1: Black Americans have been universal policies like lifting the minimum wage,

666
00:29:25,240 --> 00:29:27,240
Speaker 1: like increasing rates of unionization.

667
00:29:27,800 --> 00:29:28,680
Speaker 4: Like you know, in a.

668
00:29:28,640 --> 00:29:32,120
Speaker 1: Theoretical world where democrats still cared about and talked about healthcare,

669
00:29:32,240 --> 00:29:35,080
Speaker 1: universal health care. And so that's why this sort of

670
00:29:35,200 --> 00:29:39,400
Speaker 1: like let me do some niche, little bullshit programs for

671
00:29:39,480 --> 00:29:42,520
Speaker 1: some targeted demographic group drives me so crazy.

672
00:29:42,600 --> 00:29:44,360
Speaker 2: And I mean again, you know, just to stick with

673
00:29:44,400 --> 00:29:46,240
Speaker 2: And this is part of why the whole equity mindset

674
00:29:46,280 --> 00:29:49,320
Speaker 2: is so stupid. When they're like health initiatives on prostate cancer,

675
00:29:49,360 --> 00:29:52,040
Speaker 2: it's like, you know, prostate cancer is a cancer that

676
00:29:52,080 --> 00:29:55,000
Speaker 2: affects most men generally, specifically people.

677
00:29:54,760 --> 00:29:57,560
Speaker 3: Who are poor and unhealthy. Well, you know, if we.

678
00:29:57,520 --> 00:30:00,960
Speaker 2: Talk about diseases that are the worst, most impactful on

679
00:30:01,240 --> 00:30:04,880
Speaker 2: black communities, it's the same statistically for people who are

680
00:30:04,920 --> 00:30:07,400
Speaker 2: poor and who don't have access to healthcare, eat a

681
00:30:07,440 --> 00:30:10,680
Speaker 2: shitty diet. So it's like, it's not complicated to think

682
00:30:10,720 --> 00:30:13,480
Speaker 2: about it that way. And also if you if you

683
00:30:13,480 --> 00:30:15,280
Speaker 2: put it that way, it sounds a lot better, right, Hey,

684
00:30:15,440 --> 00:30:19,600
Speaker 2: all these diseases that disgrationally impact you know, men who

685
00:30:19,640 --> 00:30:23,680
Speaker 2: are old, obese, diabetic, We're going to try and fix that.

686
00:30:23,680 --> 00:30:26,480
Speaker 2: That will help black people, help white people, it'll help everybody.

687
00:30:26,520 --> 00:30:28,040
Speaker 2: You know, there's a lot of poor white people out

688
00:30:28,080 --> 00:30:31,360
Speaker 2: there too, also suffer from prostate cancer. From diabetes and

689
00:30:31,400 --> 00:30:34,400
Speaker 2: from a lot of this stuff. So that's nonsense. Look

690
00:30:34,480 --> 00:30:36,600
Speaker 2: on the weed thing, you can keep everybody here knows

691
00:30:36,600 --> 00:30:38,720
Speaker 2: that I'm against weed, all right, I think it's bad.

692
00:30:39,000 --> 00:30:41,480
Speaker 2: But how if I was black and I was, like, man,

693
00:30:41,560 --> 00:30:43,800
Speaker 2: I would be so insulted that one of the key

694
00:30:43,960 --> 00:30:47,520
Speaker 2: pillars is let's legalize weed. They're like, oh, let's give

695
00:30:47,560 --> 00:30:48,600
Speaker 2: you people drugs?

696
00:30:48,800 --> 00:30:49,080
Speaker 3: Is that?

697
00:30:49,320 --> 00:30:49,400
Speaker 2: Like?

698
00:30:49,480 --> 00:30:53,080
Speaker 3: How is that not so insulting to these people to

699
00:30:53,160 --> 00:30:55,960
Speaker 3: be like, oh, they really like to smoke weed? Right, Like,

700
00:30:56,120 --> 00:30:58,400
Speaker 3: what the fuck this? We're going to.

701
00:30:58,480 --> 00:31:01,960
Speaker 2: Legalize drugs specifically for a specific demographic if you want to.

702
00:31:02,120 --> 00:31:04,320
Speaker 2: But she didn't even mention, you know, that's one of

703
00:31:04,320 --> 00:31:06,480
Speaker 2: those really, Look, I don't agree with it. People are like, oh,

704
00:31:06,520 --> 00:31:09,400
Speaker 2: black people just portually get arrested for it or whatever

705
00:31:09,520 --> 00:31:11,400
Speaker 2: or have in the past, so it needs to be

706
00:31:11,520 --> 00:31:14,720
Speaker 2: you know, redistributed with some criminal justice bullshit. Fine, doesn't

707
00:31:14,720 --> 00:31:16,040
Speaker 2: make a lot of sense to me still with the

708
00:31:16,080 --> 00:31:17,320
Speaker 2: current data, but I could.

709
00:31:17,200 --> 00:31:18,400
Speaker 3: Understand that on this one.

710
00:31:18,440 --> 00:31:20,640
Speaker 2: It's literally like, we need to legalize weed, and we

711
00:31:20,680 --> 00:31:22,600
Speaker 2: need to legalize it so that you can sell it

712
00:31:22,800 --> 00:31:24,560
Speaker 2: and you can do a better job of being a

713
00:31:24,600 --> 00:31:27,479
Speaker 2: fucking legal drug dealer. I'm like, how is that not

714
00:31:28,040 --> 00:31:31,520
Speaker 2: so insulting to people that it's like, that is the

715
00:31:31,600 --> 00:31:35,120
Speaker 2: epitome in my head of handoutism, and it's like and

716
00:31:35,160 --> 00:31:37,800
Speaker 2: it doesn't get called racist or anything by the media,

717
00:31:37,920 --> 00:31:39,920
Speaker 2: and that's that's the pinnacle of racism.

718
00:31:40,080 --> 00:31:42,440
Speaker 3: Yeah, to me, legalize drugs for you.

719
00:31:43,000 --> 00:31:46,200
Speaker 1: What, I support the policy, right, I support both the

720
00:31:46,520 --> 00:31:49,920
Speaker 1: legalizing and I support the you know, the idea of

721
00:31:50,120 --> 00:31:51,800
Speaker 1: this is the community. It's been most impact, is it

722
00:31:51,840 --> 00:31:54,920
Speaker 1: We're opening up this new business opportunity, like, let's do

723
00:31:55,040 --> 00:31:55,480
Speaker 1: things in there.

724
00:31:55,520 --> 00:31:57,720
Speaker 4: I'm good with all of that. But you're so right to.

725
00:31:57,680 --> 00:32:00,320
Speaker 1: Put it as a specific plank framed in life. This

726
00:32:00,360 --> 00:32:02,680
Speaker 1: is our blackmail agenda is really something. Yeah, here's weak

727
00:32:02,800 --> 00:32:06,600
Speaker 1: for Let's talk about crypto though, because there is so

728
00:32:06,760 --> 00:32:10,120
Speaker 1: much going on with the fact again that they put

729
00:32:10,600 --> 00:32:15,000
Speaker 1: the crypto plank in this particular policy proposal, and it's

730
00:32:15,000 --> 00:32:18,080
Speaker 1: no secret why. There's actually, you know, significant pulling that

731
00:32:18,160 --> 00:32:22,000
Speaker 1: suggests that black men are you know, disproportionately actually holders

732
00:32:22,080 --> 00:32:26,240
Speaker 1: of crypto. So that's part of why they include this plank.

733
00:32:26,320 --> 00:32:30,200
Speaker 1: That's that's their logic. But there also has been Crypto

734
00:32:30,280 --> 00:32:32,480
Speaker 1: has already won this election. Let me just say that,

735
00:32:32,760 --> 00:32:35,920
Speaker 1: right the Biden administration, through Gary Gensler at the SEC,

736
00:32:36,280 --> 00:32:39,720
Speaker 1: they have aggressively enforced the laws that are on the

737
00:32:39,720 --> 00:32:43,720
Speaker 1: books against crypto, against scams, and against you know things,

738
00:32:43,760 --> 00:32:46,520
Speaker 1: people getting scammed in the financial world in general, and

739
00:32:46,560 --> 00:32:49,840
Speaker 1: Crypto has been subject to that enforcement. And there has

740
00:32:49,880 --> 00:32:53,640
Speaker 1: been over years now a large and concerted effort that

741
00:32:53,800 --> 00:32:56,280
Speaker 1: was very visible when it's Sam Bankman freed, but has

742
00:32:56,600 --> 00:33:01,800
Speaker 1: very much continued at large scale after that. And Crypto

743
00:33:01,880 --> 00:33:06,200
Speaker 1: is now one of the largest corporate contributors that industry

744
00:33:06,640 --> 00:33:09,880
Speaker 1: to the presidential campaign and down ballot campaigns in this

745
00:33:09,920 --> 00:33:12,440
Speaker 1: whole cycle. This is one of the areas whe Kamala

746
00:33:12,520 --> 00:33:15,920
Speaker 1: has really pretty consistently signaled that she will actually be

747
00:33:16,000 --> 00:33:19,160
Speaker 1: different from Joe Biden. She will be more lax on enforcement.

748
00:33:19,560 --> 00:33:21,760
Speaker 1: And I was just reading this morning soccer. I didn't

749
00:33:21,800 --> 00:33:24,640
Speaker 1: know all of his backstory, but they've really made an

750
00:33:24,640 --> 00:33:28,280
Speaker 1: example of Katie Porter in particular, where in the weeks

751
00:33:28,320 --> 00:33:33,160
Speaker 1: before her election, a crypto affiliated pack dump ten million

752
00:33:33,240 --> 00:33:36,080
Speaker 1: dollars into ads against her. They didn't have anything to

753
00:33:36,120 --> 00:33:39,240
Speaker 1: do with cryptocurrency these ads, but into ads against her.

754
00:33:39,600 --> 00:33:42,719
Speaker 1: She loses, and that ended up being like a warning

755
00:33:42,760 --> 00:33:46,280
Speaker 1: shot at all Democrats and Republicans that hey, you better

756
00:33:46,320 --> 00:33:48,880
Speaker 1: not get crosswise here. And they've wrapped it all in

757
00:33:48,920 --> 00:33:52,280
Speaker 1: this language of like, oh, entrepreneurship and innovation, et cetera,

758
00:33:52,320 --> 00:33:57,880
Speaker 1: et cetera. And Trump completely flipped on crypto Kamala versus Biden.

759
00:33:57,960 --> 00:34:00,280
Speaker 1: She's completely you know, signaled that she's got to be

760
00:34:00,280 --> 00:34:04,160
Speaker 1: different on crypto too. And so you know that manifests

761
00:34:04,160 --> 00:34:06,600
Speaker 1: and things like saying that part of your blackmail agenda

762
00:34:06,680 --> 00:34:11,399
Speaker 1: is quote unquote protecting crypto assets. It's you know, it's

763
00:34:11,440 --> 00:34:14,480
Speaker 1: extraordinary to see the influence of money and politics.

764
00:34:14,000 --> 00:34:14,480
Speaker 4: In real time.

765
00:34:14,840 --> 00:34:16,680
Speaker 2: I have a conflict of interest on this one. I

766
00:34:16,760 --> 00:34:19,279
Speaker 2: like crypto. I'm a hodler myself. Yeah, you don't really

767
00:34:19,280 --> 00:34:21,879
Speaker 2: get scammed. H No, I actually did get scammed. Yeah,

768
00:34:21,880 --> 00:34:23,680
Speaker 2: as people here. No, I lost five thousand dollars on

769
00:34:23,719 --> 00:34:25,640
Speaker 2: a block flight by the way, actually finally got my

770
00:34:25,640 --> 00:34:27,480
Speaker 2: money back. I don't know how exactly that happened, but

771
00:34:27,560 --> 00:34:29,520
Speaker 2: one day I got an email and they're like, here,

772
00:34:29,640 --> 00:34:32,600
Speaker 2: you know, somehow the bankruptcy clawback stuff worked. So you know,

773
00:34:32,640 --> 00:34:35,600
Speaker 2: it only took a couple of years and being in

774
00:34:35,640 --> 00:34:38,239
Speaker 2: the in the weeds. But they're as what they point

775
00:34:38,239 --> 00:34:40,040
Speaker 2: out is that there are a lot I mean men

776
00:34:40,200 --> 00:34:43,640
Speaker 2: in particular from Robinhood, Crypto and all, especially back in

777
00:34:43,640 --> 00:34:46,520
Speaker 2: the twenty twenty one twenty twenty two era, probably did

778
00:34:46,560 --> 00:34:47,640
Speaker 2: buy a decent amount of crypto.

779
00:34:47,680 --> 00:34:49,040
Speaker 3: I bought a lot before that.

780
00:34:49,160 --> 00:34:51,400
Speaker 2: The point is is that what they are trying to

781
00:34:51,440 --> 00:34:53,359
Speaker 2: do is in This is just hand out shit.

782
00:34:53,640 --> 00:34:55,640
Speaker 3: This is not anything that has.

783
00:34:55,560 --> 00:34:58,360
Speaker 2: To do with what is the way that we should

784
00:34:58,360 --> 00:35:02,319
Speaker 2: have a well regulated like commerce and exchange. What should

785
00:35:02,360 --> 00:35:07,040
Speaker 2: the future of American monetary you know, policy look like, like,

786
00:35:07,040 --> 00:35:09,120
Speaker 2: how should we think about banking? How should we make

787
00:35:09,120 --> 00:35:11,600
Speaker 2: sure that people are protected? This is just pure like

788
00:35:11,719 --> 00:35:14,960
Speaker 2: trying to get into the weeds of quote unquote like

789
00:35:14,960 --> 00:35:18,359
Speaker 2: appealing to people by talking about some tiny, little specific thing,

790
00:35:18,360 --> 00:35:21,040
Speaker 2: which ends up, in my opinion, being very very patronizing.

791
00:35:21,120 --> 00:35:24,000
Speaker 2: So this entire thing, you know, I'm really hoping Charlemagne

792
00:35:24,000 --> 00:35:26,279
Speaker 2: has an interview with her today around like five pm.

793
00:35:26,320 --> 00:35:28,359
Speaker 2: It's gonna be live. I'm gonna be watching it, and

794
00:35:28,560 --> 00:35:30,439
Speaker 2: he does a good job of cutting to the core

795
00:35:30,480 --> 00:35:31,080
Speaker 2: of this stuff.

796
00:35:31,520 --> 00:35:32,400
Speaker 3: So I saw him recently.

797
00:35:32,400 --> 00:35:35,399
Speaker 2: He was just talking with Andrew Schaltz talking about young

798
00:35:35,440 --> 00:35:38,359
Speaker 2: black men and their appeal with Trump and I'm really

799
00:35:38,440 --> 00:35:41,760
Speaker 2: hoping he focuses in on that with her and just

800
00:35:41,760 --> 00:35:44,080
Speaker 2: just tries to get to the crux of like, what's

801
00:35:44,120 --> 00:35:47,640
Speaker 2: actually happening happening here and is it not very patronizing

802
00:35:47,719 --> 00:35:49,719
Speaker 2: the way that you were talking, both Obama and her

803
00:35:49,800 --> 00:35:51,520
Speaker 2: in the way that this being put for. And of

804
00:35:51,520 --> 00:35:54,239
Speaker 2: course you've got Bacari Sellers and all these other black

805
00:35:54,280 --> 00:35:57,200
Speaker 2: congressmen out there, like, look at Kamalo's incredible plan for

806
00:35:57,360 --> 00:35:59,839
Speaker 2: black men. I'm like, again, I cannot imagine how it's

807
00:35:59,800 --> 00:36:02,680
Speaker 2: still that would be if my leaders and I supported

808
00:36:02,719 --> 00:36:04,320
Speaker 2: Elders and all these other people.

809
00:36:04,400 --> 00:36:07,680
Speaker 3: This is what they were saying, is so good for you, you.

810
00:36:06,640 --> 00:36:09,000
Speaker 2: Know, It's just I don't know's there's so much lack

811
00:36:09,040 --> 00:36:11,480
Speaker 2: of individualism in the way that you even look at

812
00:36:11,520 --> 00:36:11,840
Speaker 2: any of this.

813
00:36:12,160 --> 00:36:15,160
Speaker 1: You know, Nina, we had Nina Turners and her Nina

814
00:36:15,200 --> 00:36:18,840
Speaker 1: Turner on yesterday. I encourage you to watch her her comments.

815
00:36:18,880 --> 00:36:21,120
Speaker 1: Her first reaction when she before she really read through

816
00:36:21,120 --> 00:36:23,160
Speaker 1: the plan details, was like, Okay, well, at least they're

817
00:36:23,160 --> 00:36:26,040
Speaker 1: trying to appeal to people through policy, and I think

818
00:36:26,080 --> 00:36:28,200
Speaker 1: that's fair. But it's also fair to look at the

819
00:36:28,200 --> 00:36:32,360
Speaker 1: policy and say this patronizing that and bad. Just to

820
00:36:32,920 --> 00:36:35,480
Speaker 1: dig one layer deeper on the crypto thing, because I've

821
00:36:35,480 --> 00:36:38,160
Speaker 1: been thinking a lot about this, the reason that so

822
00:36:38,239 --> 00:36:41,000
Speaker 1: many black part of the reason so many black men

823
00:36:41,160 --> 00:36:43,920
Speaker 1: have crypto investments is because they've been locked down on

824
00:36:44,000 --> 00:36:48,120
Speaker 1: so many other forms of wealth accumulation and wealth building,

825
00:36:48,640 --> 00:36:52,720
Speaker 1: lower home ownership rates, you know, discriminated against in terms

826
00:36:52,719 --> 00:36:54,719
Speaker 1: of banks and the mortgage rates that's their charge, or

827
00:36:54,719 --> 00:36:58,800
Speaker 1: whether they even approved for a loan, And so crypto

828
00:36:59,800 --> 00:37:03,719
Speaker 1: really offered this, you know, this utopian vision of like, well,

829
00:37:03,760 --> 00:37:06,120
Speaker 1: this is the new financials, this is how you're gonna

830
00:37:06,120 --> 00:37:07,960
Speaker 1: make it, This is how you're going to be able.

831
00:37:07,760 --> 00:37:09,000
Speaker 4: To build wealth.

832
00:37:09,480 --> 00:37:11,600
Speaker 1: And you know, some of that is genuine and some

833
00:37:11,680 --> 00:37:15,839
Speaker 1: of it has just been completely fraudulent in scams. So,

834
00:37:16,320 --> 00:37:18,880
Speaker 1: you know, again to get to like the neoliberal point

835
00:37:18,880 --> 00:37:21,600
Speaker 1: of this, rather than really doing anything that's going to

836
00:37:21,640 --> 00:37:24,879
Speaker 1: fundamentally address that lack of wealth accumulation, it's like, well,

837
00:37:24,880 --> 00:37:27,719
Speaker 1: we're just going to like keep enabling the scammers and

838
00:37:27,880 --> 00:37:31,799
Speaker 1: make sure that they're regulated more lightly so that they

839
00:37:31,800 --> 00:37:34,120
Speaker 1: can so that the people who have lots of crypto

840
00:37:34,239 --> 00:37:37,640
Speaker 1: or because crypto is also rife with massive inequality in

841
00:37:37,719 --> 00:37:40,080
Speaker 1: terms of who's benefiting and who's on the other end

842
00:37:40,280 --> 00:37:41,440
Speaker 1: sometimes getting screwed.

843
00:37:42,160 --> 00:37:43,160
Speaker 4: So we're going to make sure that.

844
00:37:43,120 --> 00:37:45,600
Speaker 1: Those people at the top can continue to get theirs

845
00:37:45,600 --> 00:37:48,520
Speaker 1: and continue to, like you know, in certain instances, screw

846
00:37:48,560 --> 00:37:48,959
Speaker 1: you over.

847
00:37:49,320 --> 00:37:50,640
Speaker 4: That's part of what's so disturbing her.

848
00:37:50,680 --> 00:37:54,160
Speaker 1: And just you know, the specific fight is really around

849
00:37:54,239 --> 00:37:59,280
Speaker 1: which agency is going to regulate crypto and do the enforcement,

850
00:37:59,360 --> 00:38:03,160
Speaker 1: and the SEC tends to be more aggressive. There's another body,

851
00:38:03,320 --> 00:38:07,360
Speaker 1: the CFTC that the crypto industry wants to be the

852
00:38:07,400 --> 00:38:10,680
Speaker 1: regulator because they think that they just basically won't really

853
00:38:10,680 --> 00:38:14,160
Speaker 1: conduct any oversight there. And like I said, at this point,

854
00:38:14,680 --> 00:38:17,040
Speaker 1: I think it's it doesn't really matter which of these

855
00:38:17,040 --> 00:38:19,920
Speaker 1: candidates wins because both of them have already signaled that

856
00:38:19,920 --> 00:38:22,040
Speaker 1: they're going to do what the crypto industry once.

857
00:38:22,239 --> 00:38:23,880
Speaker 4: So anyway, that's where we are.

858
00:38:23,920 --> 00:38:25,520
Speaker 1: We do have an axios ters you can just show

859
00:38:26,160 --> 00:38:28,840
Speaker 1: put up on the screen there B five just to

860
00:38:29,040 --> 00:38:31,320
Speaker 1: you know, back up what I was saying before about

861
00:38:31,680 --> 00:38:36,000
Speaker 1: the amount of money that this sector has donated, and

862
00:38:36,360 --> 00:38:41,719
Speaker 1: they've launched this whole campaign aimed at elites, at political

863
00:38:41,719 --> 00:38:44,400
Speaker 1: elites to convince them. There as a quote unquote crypto

864
00:38:44,520 --> 00:38:47,920
Speaker 1: voter who is going to be basing their vote on

865
00:38:48,440 --> 00:38:51,520
Speaker 1: whether crypto is regulated at the SEC or the CFTC,

866
00:38:51,800 --> 00:38:53,560
Speaker 1: that this is like the primary thing that they're going

867
00:38:53,560 --> 00:38:55,959
Speaker 1: to be voting on. There's no evidence that that's really

868
00:38:56,000 --> 00:38:58,920
Speaker 1: the case outside of you know, the Mark Cubans of

869
00:38:58,920 --> 00:39:00,640
Speaker 1: the world and like the people who kind of at.

870
00:39:00,520 --> 00:39:01,680
Speaker 4: The top of that industry.

871
00:39:02,040 --> 00:39:04,640
Speaker 1: But I think the politicians are buying that that's the case,

872
00:39:04,800 --> 00:39:07,120
Speaker 1: and they're certainly buying that they don't want to get

873
00:39:07,160 --> 00:39:09,719
Speaker 1: crosswise of this industry because of the amount of money

874
00:39:09,760 --> 00:39:13,560
Speaker 1: they had to spend against you if you if you

875
00:39:13,640 --> 00:39:15,279
Speaker 1: undercut them or if you piss them off.

876
00:39:17,960 --> 00:39:22,560
Speaker 2: Kamala Harris is now apparently in talks with Joe Rogan

877
00:39:22,880 --> 00:39:23,719
Speaker 2: to appear on the.

878
00:39:23,760 --> 00:39:24,760
Speaker 3: Joe Rogan podcast.

879
00:39:24,880 --> 00:39:25,680
Speaker 4: Not see this one coming.

880
00:39:25,800 --> 00:39:27,200
Speaker 3: I did not see it coming as well.

881
00:39:27,520 --> 00:39:29,560
Speaker 2: I think it's a welcome development and so just a

882
00:39:29,600 --> 00:39:32,920
Speaker 2: little bit more behind the scenes. Obviously, this just broke

883
00:39:32,960 --> 00:39:35,120
Speaker 2: and they didn't have much detail on it.

884
00:39:35,400 --> 00:39:37,960
Speaker 3: But what they say is that and I was actually

885
00:39:38,040 --> 00:39:38,799
Speaker 3: kind of curious about this.

886
00:39:38,840 --> 00:39:43,840
Speaker 2: They're like, Kamala's representatives met with Rogan's representatives, and I'm like,

887
00:39:43,880 --> 00:39:47,319
Speaker 2: which represents exactly maybe his agent? I mean as far

888
00:39:47,320 --> 00:39:49,800
Speaker 2: as I know, Yeah, like Amy's Jami meeting with I

889
00:39:49,800 --> 00:39:52,960
Speaker 2: would I would pay to see money of Jamie meeting with.

890
00:39:53,040 --> 00:39:54,760
Speaker 4: Somebody from Anita Dunn or whoever.

891
00:39:54,880 --> 00:39:57,000
Speaker 3: That would be hilariously.

892
00:39:57,400 --> 00:39:59,600
Speaker 2: Uh yeah, I think I mean Joe's again, I have

893
00:39:59,640 --> 00:40:01,720
Speaker 2: no insie knowledge, but I mean he has talked previously.

894
00:40:01,719 --> 00:40:04,000
Speaker 2: He's like as one booker and one manager, so maybe

895
00:40:04,040 --> 00:40:06,759
Speaker 2: as one of those people that has done it. But regardless,

896
00:40:07,200 --> 00:40:09,960
Speaker 2: this comes on the heels of Trump saying that he

897
00:40:10,120 --> 00:40:12,160
Speaker 2: would be he would be going on rogue and we

898
00:40:12,200 --> 00:40:14,120
Speaker 2: don't know if that's true, whether he had confirmed it

899
00:40:14,480 --> 00:40:17,479
Speaker 2: or any of not. Maybe it's the case that Joe

900
00:40:17,600 --> 00:40:19,000
Speaker 2: was trying to say, well, if I'm going to have

901
00:40:19,040 --> 00:40:21,320
Speaker 2: Trump and I want to have both one and extended

902
00:40:21,320 --> 00:40:21,680
Speaker 2: the offer.

903
00:40:21,719 --> 00:40:23,000
Speaker 3: That's what most people have done who.

904
00:40:22,840 --> 00:40:25,359
Speaker 2: Have interviewed both candidates, They've put in offers with both,

905
00:40:25,360 --> 00:40:27,879
Speaker 2: and usually it's either Trump or Comma or whatever who

906
00:40:27,920 --> 00:40:30,719
Speaker 2: will accept that. In this case, though, this actually now

907
00:40:30,760 --> 00:40:34,120
Speaker 2: has the chance of happening, and that would be kind

908
00:40:34,120 --> 00:40:36,520
Speaker 2: of amazing and it's funny again.

909
00:40:36,320 --> 00:40:37,160
Speaker 3: I want to come back to this.

910
00:40:37,200 --> 00:40:38,799
Speaker 2: There's so many people out there who are like, oh,

911
00:40:38,840 --> 00:40:42,080
Speaker 2: the internals must be bad. And I'm like, again, if

912
00:40:42,120 --> 00:40:46,160
Speaker 2: you are in a fifty fifty race and you want

913
00:40:46,200 --> 00:40:49,239
Speaker 2: to go and reach millions of people who may not

914
00:40:49,480 --> 00:40:53,160
Speaker 2: be engaging with the mainstream media, why would you not

915
00:40:53,360 --> 00:40:57,080
Speaker 2: go on this podcast? And look, I mean, I guess

916
00:40:57,120 --> 00:40:59,360
Speaker 2: the answer is you're not confident in what you believe

917
00:40:59,480 --> 00:41:02,279
Speaker 2: or in what say. The thing is, though Joe is

918
00:41:02,360 --> 00:41:06,120
Speaker 2: not is a curious interviewer. He doesn't usually get into

919
00:41:06,160 --> 00:41:09,440
Speaker 2: some prolonged back and forth or something him mostly just

920
00:41:09,440 --> 00:41:11,759
Speaker 2: asking questions, did back and listen. So if you want

921
00:41:11,760 --> 00:41:14,879
Speaker 2: to explain your actual thought process, which is what Joe Rogan, oh,

922
00:41:14,880 --> 00:41:16,480
Speaker 2: which is what Bernie Sanders did when he went on,

923
00:41:16,600 --> 00:41:18,200
Speaker 2: which is what Andrey Yang did when he went on,

924
00:41:18,280 --> 00:41:20,879
Speaker 2: which is what RFK Junior did whenever he went on,

925
00:41:21,000 --> 00:41:23,000
Speaker 2: I can't think of a better format to go in.

926
00:41:23,360 --> 00:41:26,479
Speaker 2: And also, if you have somebody, so Joe is probably

927
00:41:26,480 --> 00:41:28,040
Speaker 2: going to challenge her a little bit on some of

928
00:41:28,080 --> 00:41:30,160
Speaker 2: the things that he disagrees with her on. But he

929
00:41:30,239 --> 00:41:32,279
Speaker 2: is one of those people who said consistently he's like, look,

930
00:41:32,280 --> 00:41:35,120
Speaker 2: I'm mostly like liberal in many things. You know, I'm

931
00:41:35,200 --> 00:41:37,480
Speaker 2: very liberal on the issue of abortion. I'm very conservative

932
00:41:37,480 --> 00:41:39,960
Speaker 2: on the issue of guns traditionally, like was a Democrat

933
00:41:40,080 --> 00:41:41,680
Speaker 2: and all that, but I moved to Texas because of

934
00:41:41,719 --> 00:41:44,280
Speaker 2: my disagreement. I mean, that would give her a format

935
00:41:44,320 --> 00:41:47,200
Speaker 2: to talk to people out there who ness who might

936
00:41:47,239 --> 00:41:49,680
Speaker 2: align with his view. So I can't think of a

937
00:41:49,719 --> 00:41:52,640
Speaker 2: better place to go, not just Rogan, but any like

938
00:41:52,760 --> 00:41:56,080
Speaker 2: Manosphere era stuff where you think you could get at

939
00:41:56,160 --> 00:41:58,560
Speaker 2: least somewhat of an honest convo, Go for it, Like

940
00:41:58,640 --> 00:42:00,640
Speaker 2: if you're in a fifty to fifty election, you should

941
00:42:00,680 --> 00:42:02,960
Speaker 2: be doing it. Everyone was dunking on Kama for going

942
00:42:03,000 --> 00:42:04,440
Speaker 2: on call her daddy. I think Trump should go and

943
00:42:04,520 --> 00:42:05,360
Speaker 2: call her daddy.

944
00:42:05,360 --> 00:42:08,560
Speaker 3: I'm absolutely I think you should do it. He would

945
00:42:08,600 --> 00:42:11,040
Speaker 3: do well, That's what I don't understand the caution.

946
00:42:11,360 --> 00:42:14,279
Speaker 2: He's grew up on Howard Stern and in the New

947
00:42:14,360 --> 00:42:17,760
Speaker 2: York tabloids. You think he can't handle freaking Alex Cooper.

948
00:42:18,080 --> 00:42:20,440
Speaker 2: Of course he can. I mean, what are some of

949
00:42:20,480 --> 00:42:23,680
Speaker 2: his best moments in these mainstream media interviews with CNN

950
00:42:23,760 --> 00:42:26,759
Speaker 2: or with MSNBC, either when he spars or whatever, you know,

951
00:42:26,880 --> 00:42:29,400
Speaker 2: disarms them with a joke. So anyway, that's my opinion.

952
00:42:29,440 --> 00:42:31,440
Speaker 2: I think Kamas should go on then nelk boys Uh,

953
00:42:31,960 --> 00:42:36,439
Speaker 2: Trump should go on call her dad with absolutely, yeah

954
00:42:36,480 --> 00:42:39,960
Speaker 2: she should. Hey, she wants to talk about crypto crypto gambling.

955
00:42:40,000 --> 00:42:41,200
Speaker 2: She could be read a Steak dot com and.

956
00:42:41,200 --> 00:42:43,600
Speaker 1: You're getting the uh, you're getting the King of the Bros. Here,

957
00:42:43,600 --> 00:42:45,680
Speaker 1: she's going straight to the top show with White Brogan.

958
00:42:46,160 --> 00:42:46,359
Speaker 3: Good.

959
00:42:46,719 --> 00:42:48,560
Speaker 1: But I mean, okay, So there's a few things to

960
00:42:48,600 --> 00:42:50,839
Speaker 1: say about this. First of all, it's not without risk

961
00:42:51,040 --> 00:42:54,320
Speaker 1: for sure, because yeah, I mean, Joe is not a journalist.

962
00:42:54,360 --> 00:42:56,560
Speaker 1: He's not gonna do the like, you know, super adversary,

963
00:42:56,600 --> 00:42:58,880
Speaker 1: we're going to ask you five times whatever. But he

964
00:42:58,920 --> 00:43:01,000
Speaker 1: has made people look stupid on his show, just kind

965
00:43:01,040 --> 00:43:05,560
Speaker 1: of casually like humiliated a variety of people on his show,

966
00:43:06,200 --> 00:43:08,880
Speaker 1: and that is not on the question because he's a

967
00:43:09,000 --> 00:43:12,040
Speaker 1: good listener and he's just he's a good question asker.

968
00:43:12,120 --> 00:43:14,640
Speaker 4: So that's a risk for her. And we all know.

969
00:43:14,560 --> 00:43:17,440
Speaker 1: How she is like on her feet in these interviews,

970
00:43:17,440 --> 00:43:19,760
Speaker 1: even like on the view with softball questions.

971
00:43:20,120 --> 00:43:22,239
Speaker 4: She can definitely screw it up. There's no doubt about it.

972
00:43:22,280 --> 00:43:24,319
Speaker 4: So it's risky. I hope she does it.

973
00:43:24,520 --> 00:43:26,520
Speaker 1: I think it'd be very interesting to see. I think

974
00:43:26,520 --> 00:43:28,320
Speaker 1: it would be smart if she pulls it off. I

975
00:43:28,320 --> 00:43:30,319
Speaker 1: think it would be intelligent. If she doesn't pull it off,

976
00:43:30,360 --> 00:43:32,799
Speaker 1: then it will obviously be a mistake. The other thing

977
00:43:32,840 --> 00:43:35,640
Speaker 1: I just have to comment on though, is Sager, you

978
00:43:35,760 --> 00:43:39,680
Speaker 1: remember the way liberals smeared Bernie Sanders.

979
00:43:39,719 --> 00:43:41,200
Speaker 3: Yes, I do, Yes, I do.

980
00:43:41,239 --> 00:43:44,319
Speaker 1: Not so much, but just going on the podcast, but

981
00:43:44,800 --> 00:43:46,600
Speaker 1: Joe made this comment like, oh, I'll probably vote for

982
00:43:46,680 --> 00:43:49,600
Speaker 1: Bernie Sanders. They were like cool, the number one podcast

983
00:43:49,640 --> 00:43:51,759
Speaker 1: in the world said he would vote for me. Like,

984
00:43:51,880 --> 00:43:54,040
Speaker 1: let me make a thing of that, as a politician

985
00:43:54,080 --> 00:43:58,120
Speaker 1: would the number of liberals who absolutely smear how dare

986
00:43:58,120 --> 00:44:01,960
Speaker 1: you platform this racist sac is blah blah blah blah blah,

987
00:44:02,040 --> 00:44:03,879
Speaker 1: who are now going to be out there like, oh,

988
00:44:03,880 --> 00:44:06,840
Speaker 1: it's so great that christ Kamala was going on with

989
00:44:06,920 --> 00:44:09,480
Speaker 1: Joe Rogue and like, I just you know, I'm here

990
00:44:09,520 --> 00:44:11,560
Speaker 1: for it. I'm absolutely here for the way that these

991
00:44:11,560 --> 00:44:13,759
Speaker 1: people have zero principles or values and we'll just turn

992
00:44:13,800 --> 00:44:15,400
Speaker 1: on a dime when it suits them with their their

993
00:44:15,440 --> 00:44:16,280
Speaker 1: favorite candidates.

994
00:44:16,280 --> 00:44:18,160
Speaker 4: So looking forward, looking forward to Yeah.

995
00:44:18,080 --> 00:44:20,200
Speaker 2: Well you can stick with that theme actually, because what

996
00:44:20,360 --> 00:44:22,759
Speaker 2: also was announced is that she will be doing a

997
00:44:22,800 --> 00:44:25,400
Speaker 2: sit down interview with Brett Bayer over at Fox News

998
00:44:25,600 --> 00:44:28,120
Speaker 2: for a prolonged period of time. But I think it airs.

999
00:44:28,480 --> 00:44:30,719
Speaker 2: It either is today or at airsmorrow, I forget. Yeah,

1000
00:44:30,760 --> 00:44:34,920
Speaker 2: But the point is is that previously, remember Elizabeth Warren

1001
00:44:35,000 --> 00:44:37,239
Speaker 2: tried to get everybody on the DNC stage to raise

1002
00:44:37,280 --> 00:44:37,800
Speaker 2: their hand.

1003
00:44:37,680 --> 00:44:38,920
Speaker 3: In boycott Fox News.

1004
00:44:39,239 --> 00:44:42,520
Speaker 2: But now whenever its election time, like, yeah, well you

1005
00:44:42,560 --> 00:44:43,640
Speaker 2: should go on Fox.

1006
00:44:43,840 --> 00:44:46,359
Speaker 1: They've been loving Pete budaju Jeh on Fox News. That's

1007
00:44:46,400 --> 00:44:48,040
Speaker 1: like one of their favorite things because I mean he

1008
00:44:48,120 --> 00:44:51,080
Speaker 1: does he handles himself very well in the format, and

1009
00:44:51,160 --> 00:44:53,279
Speaker 1: so yeah, they really love when he goes on there.

1010
00:44:53,320 --> 00:44:55,120
Speaker 3: And Birthing went on Fox. He did a whole town

1011
00:44:55,160 --> 00:44:56,400
Speaker 3: home that was.

1012
00:44:56,440 --> 00:44:58,920
Speaker 1: One of the watch the best moments he did fantastic.

1013
00:44:59,000 --> 00:45:00,920
Speaker 1: He had a Fox News audi cheering for them, and

1014
00:45:01,000 --> 00:45:03,279
Speaker 1: so yeah, I mean Brett Baer, you know, he's going

1015
00:45:03,320 --> 00:45:05,880
Speaker 1: to frame things from kind of like a center right perspective,

1016
00:45:05,920 --> 00:45:08,719
Speaker 1: but he's not going to be like wildly unfair right there.

1017
00:45:08,960 --> 00:45:11,080
Speaker 3: He's like a sixty minute style journalist.

1018
00:45:11,280 --> 00:45:12,960
Speaker 2: He's just gonna sit there and be like, he used

1019
00:45:12,960 --> 00:45:14,960
Speaker 2: to say this about illegal immigrants, and now you say this,

1020
00:45:15,040 --> 00:45:16,759
Speaker 2: How do you square that he used to say this

1021
00:45:16,840 --> 00:45:17,560
Speaker 2: and now you say this?

1022
00:45:17,680 --> 00:45:19,400
Speaker 3: How it'll be it will be.

1023
00:45:19,560 --> 00:45:22,799
Speaker 2: Frankly, I think better than Dana Basher any of these

1024
00:45:22,840 --> 00:45:25,240
Speaker 2: other people who've interviewed her. I actually got the sixty

1025
00:45:25,239 --> 00:45:29,200
Speaker 2: minutes guys. Credit to them outside of the whole editing fiasco.

1026
00:45:29,280 --> 00:45:31,960
Speaker 2: But the actual journalist journalist. That's not the journalists at

1027
00:45:32,040 --> 00:45:34,400
Speaker 2: least I assume so. But the actual guy you interviewed her,

1028
00:45:34,480 --> 00:45:36,400
Speaker 2: he did a pretty good job, right, He has a decent.

1029
00:45:36,200 --> 00:45:36,839
Speaker 3: Amount follow ups.

1030
00:45:36,960 --> 00:45:40,000
Speaker 2: That's probably what we should expect here, And in general,

1031
00:45:40,160 --> 00:45:42,719
Speaker 2: you should be doing more of these things. So I

1032
00:45:42,800 --> 00:45:46,120
Speaker 2: keep seeing this like, oh, she must be losing and

1033
00:45:46,160 --> 00:45:47,520
Speaker 2: all that. I'm like, well, first of all, if you

1034
00:45:47,520 --> 00:45:49,000
Speaker 2: think you're losing, the best way to do is do

1035
00:45:49,040 --> 00:45:51,320
Speaker 2: something drastic. So I think that's good, even though I

1036
00:45:51,320 --> 00:45:53,239
Speaker 2: don't think it's all that drastic to go on any

1037
00:45:53,239 --> 00:45:55,239
Speaker 2: of the things. But you should always just be doing

1038
00:45:55,280 --> 00:45:57,960
Speaker 2: everything you possibly can to reach as many people that

1039
00:45:58,000 --> 00:46:00,600
Speaker 2: you can. Before an election, a lot people make up

1040
00:46:00,640 --> 00:46:02,919
Speaker 2: their minds right around right now on.

1041
00:46:02,840 --> 00:46:05,080
Speaker 3: Whether they're going to vote who they're going to vote for.

1042
00:46:05,200 --> 00:46:07,000
Speaker 3: So this is it, This is what you should be doing.

1043
00:46:07,040 --> 00:46:09,680
Speaker 2: Trump is doing a ton of podcasts in the lead up,

1044
00:46:09,680 --> 00:46:11,000
Speaker 2: and Kamalas should be doing more.

1045
00:46:11,440 --> 00:46:14,719
Speaker 1: Fox News has a large viewership and not News Channel.

1046
00:46:14,840 --> 00:46:17,560
Speaker 1: Not all of them are diehard Trump supporters. You know,

1047
00:46:17,680 --> 00:46:21,080
Speaker 1: they've got their Kamala's doing this whole whether I like

1048
00:46:21,120 --> 00:46:23,080
Speaker 1: it or not, She's doing this whole, Nikki Aley, Liz

1049
00:46:23,160 --> 00:46:26,759
Speaker 1: Cheney voter strategy, and there will be some of those

1050
00:46:26,800 --> 00:46:32,520
Speaker 1: people watching Fox News. So you know, again, it all

1051
00:46:32,520 --> 00:46:34,759
Speaker 1: depends is it a smart strategy. It all depends on

1052
00:46:34,800 --> 00:46:36,920
Speaker 1: how she does. I can't say that the last week's

1053
00:46:36,960 --> 00:46:39,359
Speaker 1: media strategy worked out particularly well for her.

1054
00:46:39,480 --> 00:46:42,440
Speaker 4: The sixty minutes interview not great. The view interview not great.

1055
00:46:42,840 --> 00:46:45,160
Speaker 1: But you know, apparently they have enough confidence that they

1056
00:46:45,200 --> 00:46:47,759
Speaker 1: think that these additional media appearances can help to clean

1057
00:46:47,760 --> 00:46:48,160
Speaker 1: things up.

1058
00:46:48,239 --> 00:46:50,600
Speaker 2: Definitely, all right, And oh, I said Jessee Trump was

1059
00:46:50,640 --> 00:46:54,240
Speaker 2: on Bustin' Busting with the Boys, which is a barstool podcast.

1060
00:46:54,239 --> 00:46:58,480
Speaker 3: Oh really incredible. I mean, Josie, he's doing.

1061
00:46:58,280 --> 00:47:00,319
Speaker 4: Many more podcasts than these rallies. This thing, this is

1062
00:47:00,360 --> 00:47:00,719
Speaker 4: really his.

1063
00:47:00,920 --> 00:47:03,160
Speaker 2: He seems to doing like one in one yeah, I mean, look,

1064
00:47:03,160 --> 00:47:05,080
Speaker 2: it doesn't take that long in film, right, So it's

1065
00:47:05,120 --> 00:47:06,600
Speaker 2: like one of those where why not you know, you

1066
00:47:06,600 --> 00:47:08,680
Speaker 2: can set it up and you can actually make it

1067
00:47:08,760 --> 00:47:10,279
Speaker 2: and reach a bunch of people who were talking about

1068
00:47:10,320 --> 00:47:13,640
Speaker 2: otherwise about college football. I wonder what the crossover is

1069
00:47:13,640 --> 00:47:16,279
Speaker 2: when college football and South and Trump. I mean, it

1070
00:47:16,280 --> 00:47:18,560
Speaker 2: doesn't take a genius to see these things. If anything,

1071
00:47:18,640 --> 00:47:21,279
Speaker 2: is crazy that it took so long for politicians to

1072
00:47:21,360 --> 00:47:24,680
Speaker 2: embrace charcass It's more of a lagging thing than it

1073
00:47:24,760 --> 00:47:25,960
Speaker 2: is something in the former