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Speaker 1: Hi, I'm Molly John Fast and this is Fast Politics,

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Speaker 1: where we discuss the top political headlines with some of

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Speaker 1: today's best minds, and an appeals court judge has declared

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Speaker 1: DeSantis's band on transgender care to be unconstitutional. We have

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Speaker 1: such a great joke for you today. Recovering polster Adam

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Speaker 1: Carlson stops by to talk about his analysis of the

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Speaker 1: twenty twenty four polls. Don't worry, It's not terrible. Then

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Speaker 1: we'll talk to the Washington Post Sarah Ellison about how

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Speaker 1: disinformation circles affect our media. But first we have legendary

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Speaker 1: campaign manager and emotional support pundant, the author of the

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Speaker 1: conspiracy to in America Five Ways my old Party is

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Speaker 1: driving our democracy to autocracy. The Lincoln Projects owned Stuart Stevens.

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Speaker 1: Welcome back to Fast Politics. Stuart Stevens.

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Speaker 2: Hidekra me to a party.

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Speaker 1: I'm such a fan of yours. I was thinking about

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Speaker 1: it because I was thinking, like, now we can talk

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Speaker 1: campaign with someone who has done many campaigns but also

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Speaker 1: has a sort of nice, not too crazy way about him.

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Speaker 1: I feel like campaigns make a person a little unhinged.

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Speaker 2: They do, and most people work in campaigns and then

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Speaker 2: they grow up and they do something else. As my

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Speaker 2: long time partner Rush Street for and I used to say,

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Speaker 2: we'd look around after every cycle and we go like,

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Speaker 2: what's wrong with us? We still want to do campaigns.

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Speaker 2: But you know, I think I probably in a lot

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Speaker 2: of ways represented the worst of the American political system

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Speaker 2: because I just like campaign I was never really interested

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Speaker 2: in that thing called government, and it gave me a

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Speaker 2: very simplistic and shallow and what proved to be ultimately

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Speaker 2: dangerous value system, which is I was happy if I

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Speaker 2: won and I was sad if I lost, And you know,

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Speaker 2: that worked all great up until Trump. Then I had

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Speaker 2: asked self, like, how is it that I didn't see this?

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Speaker 2: There's not, unfortunately, any good answer I've come up with.

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Speaker 2: And I think it's absurd to think that Trump hijacked

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Speaker 2: the party. Nobody made anybody vote for Donald Trump, and

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Speaker 2: Donald Trump is so popular in the Republican Party, and

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Speaker 2: the party has become Donald Trump because it's what the

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Speaker 2: party wants. Let's quit pretending, you know that there's some

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Speaker 2: party that we're gonna go.

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Speaker 1: Let you it's interesting to me. One of the things

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Speaker 1: that I think a lot of us spend probably way

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Speaker 1: too much time thinking about is why is Donald Trump

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Speaker 1: so popular? Like still and again he's not so popular, right,

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Speaker 1: he's not, but he has a certain thing that people

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Speaker 1: still like about him, despite the fact that he's a

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Speaker 1: convicted felon and out on bail for three other cases.

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Speaker 2: You can't get hung up on these little details, right exactly.

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Speaker 1: But the question is, like, I think that some of

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Speaker 1: this just comes down to, like, charismatic politicians do better

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Speaker 1: with the electorate. I mean, is that possible? Is it

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Speaker 1: just that simple?

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Speaker 2: Listen, I'm pretty harsh about this, but I think I've

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Speaker 2: earned a right to be harsh because I know these people,

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Speaker 2: and I dealt with the Republican electorate. I don't think

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Speaker 2: there's anything flattering that you can say about the Republican electorate.

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Speaker 2: We can't blame this on Fox. At any given moment,

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Speaker 2: the most watching Fox are three million and seventy plus

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Speaker 2: million voted for Trump. There's more information available to voters

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Speaker 2: today in America than any time or any place in history.

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Speaker 2: I mean an actual true statement. It's not North Korea.

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Speaker 2: You know, it's not Mississippi in nineteen sixty five, when

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Speaker 2: there was people referred to being behind the Magnolia curtain

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Speaker 2: because one family owned all the newspapers, and it's not

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Speaker 2: that way. I think at the heart of Trump is race.

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Speaker 2: And Trump's coalition is eighty five percent white in a

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Speaker 2: country that is sixty fifty nine percent white less. So

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Speaker 2: the time we finished this and I think that ultimately

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Speaker 2: that is the reality of what happened to the Republican Party.

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Speaker 2: And now I get in this argument with my still

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Speaker 2: Republican friends and they go, well, so let me get

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Speaker 2: this stressory. You think everybody voted for Trump is a racist,

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Speaker 2: and it's just no. But I think everybody who voted

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Speaker 2: for Trump pretty much thought something was more important to

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Speaker 2: them than having a racist as president, because you can't

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Speaker 2: deny that Donald Trump is a racist. And sixty percent

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Speaker 2: of the electorate was non college educated whites. That's now

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Speaker 2: forty percent and dropping. It's the fastest shrinking demographic in America,

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Speaker 2: and I think that is at the fear of what

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Speaker 2: drives so much of trump Ism. And they're right, they

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Speaker 2: are losing control and America's headed to become a majority

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Speaker 2: minority country, and in many ways it already has. If

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Speaker 2: you're sixteen years and younger, in America, the majority are

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Speaker 2: non white, you know, and odds look really really good

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Speaker 2: they're going to be non white when they turn eighteen.

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Speaker 2: And that is at the root of all of this.

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Speaker 2: I think, you know, I do not understand these CEOs

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Speaker 2: who support Donald Trump. I think it's shameful. I think

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Speaker 2: they should be shamed. I think to Steve Schwartzman, of

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Speaker 2: the world, would you rather be a CEO in Russia?

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Speaker 2: You have a pretty good year.

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Speaker 1: It's a very short term way of thinking of the world.

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Speaker 2: You look at Blackstone, Steve Schwartzman, So you've got a

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Speaker 2: convicted felon in New York. Blackstone is over four thousand

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Speaker 2: employees from New York. So is what Steve Schwartzman is

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Speaker 2: CEO sending a message to his employees that the rule

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Speaker 2: of law in New York State doesn't matter. That's interesting

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Speaker 2: because I imagine if you work for Blackstone, they actually

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Speaker 2: expect you to adhere to the laws of New York State.

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Speaker 1: If Blackstone were hiring convicted felons, like if you want

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Speaker 1: a job at Blackstone and you owe more than one

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Speaker 1: hundred million dollars, like yes, for fraud, would you get hired?

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Speaker 2: Absolutely not. You can go to the Blackstone Code of Ethics,

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Speaker 2: which is prominent, and I just don't understand why there

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Speaker 2: should be a higher standard for being an intern at

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Speaker 2: Blackstone than being president.

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Speaker 1: Right, all right, exactly.

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Speaker 2: And I think that those like Steve Schwartzman and Jamie

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Speaker 2: Dimond has said nice things about Donald Trump before, famously

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Speaker 2: at the Davos. I don't know what he said about

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Speaker 2: who he's going to vote for at this stage. If

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Speaker 2: he said anything, I think a lot of people are

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Speaker 2: telling him to shut up, shut up and durabble. I

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Speaker 2: think it is foolish to think that you can have

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Speaker 2: the benefits of a democracy that you're enjoining now and

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Speaker 2: elect a non democratic president, someone who is going to

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Speaker 2: lead the country for four years, non wall d democratic

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Speaker 2: and Trump obviously does not support democracy. I mean, there's

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Speaker 2: no pretense of it. And if you think that Donald

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Speaker 2: Trump won't come after you, you're feeding the alligator hoping

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Speaker 2: he'll eat you. Last.

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Speaker 1: Well, it's the Mitch McConnell saying, right.

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Speaker 2: It is precisely the miss McConnell thing that workout. Mitch.

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Speaker 2: I've talked about this before, you know. When I was

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Speaker 2: writing this book, it was all a lie. I stumbled

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Speaker 2: across the memoirs of friends on pathin who was a

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Speaker 2: Pressian aristocrat responsible more than anybody else for ushering Hitler

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Speaker 2: into power. So he wrote his memoir in nineteen fifty three.

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Speaker 2: Now things had gone a little sideway, I mean, a

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Speaker 2: one hundred million killed World War two Holocaust, and he

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Speaker 2: still was defending supporting Hitler. And there are phrases that

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Speaker 2: he uses is if memoir that are literally verbade him

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Speaker 2: of what Ms McConnell said, that we will change him.

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Speaker 2: There are more of us, He will have to adapt

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Speaker 2: to us. So I wonder how did Mitch McConnell feel, well,

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Speaker 2: his colleagues were running for their lives and their own offers.

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Speaker 2: How did that work out? And still mits McConnell is

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Speaker 2: afraid to say Donald Trump's name in public. So I

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Speaker 2: think it's a historic failure of a party. And ultimately,

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Speaker 2: I mean that's I said about the selection. The selection

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Speaker 2: isn't remotely about Donald Trump. It's about each of us.

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Speaker 2: We know who Donald Trump is, He's just who are we?

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Speaker 2: And I think it's a character tist. You know, I

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Speaker 2: am so offended by these Trump supporters that say, you know,

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Speaker 2: the system was rigged. We had to resort to what

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Speaker 2: you know, storming the Capitol and all of this. So

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Speaker 2: let me get this straight. There are Americans who actually

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Speaker 2: were prosecuted, were hunted, were tortured, were murdered to stop

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Speaker 2: them from participating in the system. And they're called black America.

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Speaker 2: So how did they react. They didn't storm the capital

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Speaker 2: and violence easier. They stayed in the system, They registered

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Speaker 2: more voters, they continue to believe in the system. And

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Speaker 2: yet the overwhelmingly middle class white voters that support Trump

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Speaker 2: have walked away from America. And I think it is

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Speaker 2: shameful and I have no need to understand them. I really,

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Speaker 2: I don't want to understand the guy in the camp

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Speaker 2: all switch sweatshirt. I just want him walk up.

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Speaker 1: Yeah. No, So let's talk about right now. We are

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Speaker 1: still in this ecosystem where we don't really know know

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Speaker 1: quite what the results from Trump's criminal conviction are going

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Speaker 1: to be, though it does seem like there is some

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Speaker 1: movement there. And I recently read something where that actually,

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Speaker 1: Hunter Biden's trial is not hurting Biden as much as

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Speaker 1: Trump World wanted it to. That actually people can have

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Speaker 1: two thoughts at the same time, you know, shockingly, So

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Speaker 1: I'm curious to know what you You know, we're sort

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Speaker 1: of in this weird period run up to the conventions,

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Speaker 1: and I'm wondering what you think that Biden world should

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Speaker 1: be doing and are they doing? What do you think?

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Speaker 2: I am a great admirer of the Biden campaign. I

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Speaker 2: think they ran a brilliant campaign in twenty twenty that

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Speaker 2: they don't get enough credit for. You know, be the

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Speaker 2: incumbent president is incredibly difficult, and you know, nineteen seventy six,

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Speaker 2: we passed campaign financing, so each Democratic Republican nominee got

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Speaker 2: the same amount of money, and under that system, it

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Speaker 2: did level the playing field. Under that system, Bush lost

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Speaker 2: and Carter lost. So then in two thousand and eight

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Speaker 2: Obama walked away from that system, so he spent a

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Speaker 2: general election about three hundred and seventy million. McCain spent

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Speaker 2: eighty four million. So, as always happens, once nobody steps

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Speaker 2: out of the system, everybody steps out. So twenty twelve

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Speaker 2: was the first time since nineteen seventy two Nixon McGovern

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Speaker 2: the two candidates were running against each other who were

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Speaker 2: not in the federal funding system Romney Obama. Romney lost,

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Speaker 2: so Biden beat An incumbent president not in the federal

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Speaker 2: funding system, so it's fair at last, when is the

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Speaker 2: last time that happened? Well, the answer happens to be

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Speaker 2: Herbert Hoover and he had a bad year. So I

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Speaker 2: have tremendous respect for what the Biden campaign does. They

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Speaker 2: have this quality that is so rare in politics, which

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Speaker 2: is patience. And you know, there is this overwhelming human

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Speaker 2: tendency to day trade politics, so you have you know,

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Speaker 2: Biden goes out and has a lousy press conference after

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Speaker 2: this Special Council's finding, and you know, you have people

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Speaker 2: like Ezra Client writing you should get out, this is

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Speaker 2: it right, and then a few weeks later he gives

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Speaker 2: a great state of the Union space you go, well,

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Speaker 2: maybe you shouldn't get out, and politics is not for

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Speaker 2: day traders. You know. My greatest worry where i'm the

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Speaker 2: Biden campaign would be peaking too early strangers that may seem,

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Speaker 2: because I think there is a great narrative in American

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Speaker 2: tradition of coming from behind, and I think the greatest

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Speaker 2: danger for the Biden campaign is they're going to start

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Speaker 2: leading too early, and then they may drop back, and

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Speaker 2: then it's harder to go back again. You know, I

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Speaker 2: have no contact with the Biden campaign, so this is

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Speaker 2: just purely outsider. I think that they understand the rhythm

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Speaker 2: of this campaign and there is no need to win

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Speaker 2: every news cycle that I think he'll probably be behind

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Speaker 2: until the Democratic Convention, and then I think after the

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Speaker 2: Invention they'll be able to come out and prosecute a

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Speaker 2: campaign against Trump. That the elements are being laid for now.

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Speaker 2: And if I had to make a bet now, I

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Speaker 2: don't think the race is going to be particularly close.

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Speaker 2: I think it'll be close to about October twentieth, and

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Speaker 2: then it's going to be like nineteen eighty and when

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Speaker 2: Carter started to drop. I don't understand what you get

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Speaker 2: when you vote for Donald Trump. What do you get

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Speaker 2: when you vote for Republicans? I don't know. There's no

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Speaker 2: policy except Project twenty twenty five, which God knows they

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Speaker 2: don't want to talk about much because it is overwhelmingly unpopular.

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Speaker 1: One of the things that I was struck by this

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Speaker 1: weekend was that Trump was in Nevada and he said

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Speaker 1: to the group, I will make it so you don't

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Speaker 1: have to pay taxes on tips anymore, a wildly unpopular thing.

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Speaker 1: It's not clear how many people actually do pay taxes

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Speaker 1: on tips. But that ability to just say whatever he

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Speaker 1: would any interest in the possibility of being actually able

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Speaker 1: to do it. Do you think that helps him? I mean,

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Speaker 1: I feel like that that's the thing where I'm like,

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Speaker 1: he's not bound by the truth at all.

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Speaker 2: No, I mean, this has always been the case. He

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Speaker 2: was going to balance the budget in four years, said

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Speaker 2: so when a Washington Post interview, he was going to

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Speaker 2: make health care a beautiful plan for health care Mexico,

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Speaker 2: was going to pay for the wall, as Mark Cuban

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Speaker 2: famously said, he is the guy who will say anything

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Speaker 2: at closing time to get laid right, all right. And

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Speaker 2: I think that his ability to do that is reduced

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Speaker 2: every day because the difference between what he has said

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Speaker 2: he was going to do and what he does is greater,

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Speaker 2: and that includes to what he has actually done. So

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Speaker 2: he's actually taken away roe v. Eight. Okay, let's live

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Speaker 2: in that world. He actually is supporting putin. Let's live

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Speaker 2: in that world.

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Speaker 1: What do you think about those polls that say people

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Speaker 1: don't believe that Trump actually was the person who took

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Speaker 1: away roe v. Wade.

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Speaker 2: It's troubling. I think that's why if you're sitting in

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Speaker 2: a Biden campaign, you want to spend over a billion dollars,

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Speaker 2: and I think that's you know, as that old phrase goes,

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Speaker 2: campaigns matter, and I think that there are a lot

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Speaker 2: of very substantive, impressive, life affecting positive changes that have

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Speaker 2: been brought by the Biden administration. Unemployment at record lows,

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Speaker 2: you have stock markets at record highs. That does affect

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Speaker 2: people more than realize because of the one ks. You

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Speaker 2: have wages rising. All of this actually is a positive

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Speaker 2: underpinning to people. People who now are paying thirty three

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Speaker 2: dollars for insulin know that people who are going to

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Speaker 2: pay lesser than Haler's know that now it is always

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Speaker 2: difficult for any incumbent to get credit for what they've done.

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Speaker 2: In two thousand and four, were sitting focus groups in

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Speaker 2: the Bush campaign, and one of the great goals of

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Speaker 2: the Bush administration was to reduce taxes for those in

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Speaker 2: the lower income So the goal was family of four

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Speaker 2: making forty thousand dollars or less would pay no income tax,

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Speaker 2: which happened under Bush. So we would sit in focus

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Speaker 2: groups with people who no longer were paying income tax

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Speaker 2: and would ask them, are you paying more income tax

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Speaker 2: now under Bush or not, they say I'm paying more now,

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Speaker 2: and then you would generally point out where you're actually

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Speaker 2: not paying any income tax now, and they would say, well,

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Speaker 2: I'm paying more in taxes, and they just wouldn't believe you.

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Speaker 2: And that's why in two thousand and four, among other reasons,

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Speaker 2: we decided correctly, I think, really led by Carl Rowe,

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Speaker 2: who I do think is a genius, that there were

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Speaker 2: very few persuadable voters. I mean we would show people

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Speaker 2: ads that, like you know, Mark McKinnon and I had

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Speaker 2: made about women voting in Afghanistan, and people would cry,

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Speaker 2: I mean openly cry. Men would cry. And then they'd say,

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Speaker 2: you know, I'm never going to vote for him. That's

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Speaker 2: the best thing I've ever seen. I'm never going to

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Speaker 2: vote for And out of that strategy of what came

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Speaker 2: to be known as Fortress precincts, which the way you

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Speaker 2: could win, the path to win was very simple. Where

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Speaker 2: you got sixty percent, you needed to get sixty three percent.

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Speaker 2: Where you got fifty two, you needed to get fifty five.

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Speaker 2: You had to just increase your margin by just a

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Speaker 2: little in every one of these precincts and not go

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Speaker 2: after persuading voters. And I think that the Biden campaign

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Speaker 2: is in much the same reality now. So Biden won

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Speaker 2: by eight million votes, Trump lost. He needs new customers.

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Speaker 2: You start with the question how many Biden twenty Trump

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Speaker 2: twenty four voters are there? Some? I don't think there's

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Speaker 2: massive amounts. So what is Trump doing to get new customers?

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Speaker 2: As far as I can tell, he's saying, if you're

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Speaker 2: not a long term, devoted customer here, we don't want

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Speaker 2: your business. Which people hear that, and I think they react.

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Speaker 2: There was a lot of behind, you know, Nikki Haley,

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Speaker 2: and ultimately politics is more about addition and subtraction. And

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Speaker 2: you know, one of my favorite clients in Haley Barber,

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Speaker 2: you know, ran for governor Mississippi after a career in politics,

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Speaker 2: and Haley like to say, it's better to be for

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Speaker 2: the future because it's going to happen anyway. And you know,

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Speaker 2: the Republican Party is basically at war with the modern world,

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Speaker 2: and I think they're going to lose.

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Speaker 1: I would literally sit here with you all day because

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Speaker 1: you just are so soothing. But I think that's a

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Speaker 1: really good point that the Republican Party is at war

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Speaker 1: with the future. Thank you so much, Stewart Stevens. I

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Speaker 1: really appreciate you. Spring is here, and I bet you

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Speaker 1: are trying to look fashionable, So why not pick up

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Speaker 1: head to fastpolitics dot com. Adam Carlson is a former

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Speaker 1: and recovering Democratic polster. Adam, welcome back. I think of

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Speaker 1: you as a fan favorite.

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Speaker 3: Oh wow, that's very flattering. Well, I'm really happy to

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Speaker 3: be here. Thanks for having me back.

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Speaker 1: Because we deal with polls, right, I hate polls. You

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Speaker 1: probably don't hate poles as much as I hate poles,

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Speaker 1: since you're a recovering pollster, But I find polls to

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Speaker 1: be very annoying. But they're really the only indicator we

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Speaker 1: have ultimately, right. We can do turnout on the primaries,

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Speaker 1: but that's kind of different, so we have to sort

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Speaker 1: of use them. But they are sort of a blunt instrument.

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Speaker 1: And what is sort of the state of modern polling

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Speaker 1: right now?

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Speaker 3: I think that the state of mone and polling is

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Speaker 3: in plus right now. If you're doing a phone poll,

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Speaker 3: response rates have never been lowered. This has been covered

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Speaker 3: a ton, This has been a reason to criticize polls.

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Speaker 3: You're lucky to get a one percent response rate, as in,

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Speaker 3: if you contact one hundred people, you're lucky to get

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Speaker 3: one person to actually answer and finish your holl You

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Speaker 3: have to call people on their cell phones now, which

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Speaker 3: is a better way of contacting them, but it's a

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Speaker 3: lot harder to get a hold of folks because you

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Speaker 3: call our ID show the unknown number. You're not really

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Speaker 3: ever sure if the people who are answering those unknown

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Speaker 3: numbers are representative of the broader population or if they're

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Speaker 3: more engaged or kind of weirdos. It's a bit imprecise,

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Speaker 3: and there's things you can do on the back end

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Speaker 3: to try and retro sit them. People you're polling to

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Speaker 3: be representative of the population. But again, you're making a

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Speaker 3: lot of assumptions each time you're doing that. So each

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Speaker 3: assumption that each polster makes and how much thought and

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Speaker 3: rigor they put into it can affect the accuracy and

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Speaker 3: can introduce bias. So, like you said, it's a blunk instrument.

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Speaker 3: It's never been harder to pull than it is right now,

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Speaker 3: there's online polls. Of course there's live texts, people are

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Speaker 3: trying different things, But it was a lot easier to

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Speaker 3: be a polster ten twenty third years ago than it

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Speaker 3: is today.

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Speaker 1: Explained to us sort of what we're seeing in these

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Speaker 1: free Biden pre Biden Trump five months out polling.

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Speaker 3: Let me step back for a second here, and I

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Speaker 3: think that the rise of the five thirty eight in

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Speaker 3: Nate Silver Next starting in two thousand and eight was

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Speaker 3: great for visibility for polling, and then by thirty eight

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Speaker 3: in particular and others as well had really good cycles

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Speaker 3: in two thousand and eight twenty twelve, and they're seen

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Speaker 3: as like these oracles, people doing these models. But historically

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Speaker 3: polling error is pretty high in one direction or another.

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Speaker 3: So twenty sixteen and twenty twenty eight underestimated Trump twice.

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Speaker 3: So there's this working assumption that because the polls underestimated

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Speaker 3: Trump twice in twenty sixteen and twenty twenty, that they'll

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Speaker 3: do it a third time. So to answer your question,

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Speaker 3: right now, Trump leads Biden, maybe by a point, maybe

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Speaker 3: it's tied nationally, that's depending on which aggregate you look at.

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Speaker 3: That's kind of where we're at right now. Biden got

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Speaker 3: a roughly two point bump after Trump's conviction or thirty

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Speaker 3: four or felony convictions, and nationally we don't have a

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Speaker 3: lot of state pulling. It's compared before and after right now,

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Speaker 3: so things are tight nationally. But people assume that because

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Speaker 3: Poles underestimated Trump in twenty sixteen and twenty twenty, that

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Speaker 3: they'll do it again in twenty twenty four. And that's

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Speaker 3: not necessarily how polling error works. That's happened in both directions.

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Speaker 3: In twenty twelve, underestimated Obama and this spill sally a

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Speaker 3: much closer race than it ended up being against Smith Romney.

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Speaker 3: It's tempting to say that again like Biden needs to

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Speaker 3: be ahead by a lot more because the Poles will

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Speaker 3: underestimate Trump again, But we just don't know that's the case,

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Speaker 3: especially because I would bet good money that a lot

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Speaker 3: of posters have made adjustments ince then.

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Speaker 1: This is why I wanted to have you on this

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Speaker 1: podcast because it strikes me and you and I can

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Speaker 1: both go into this right now, that there may be

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Speaker 1: and again we don't know because we don't have algorithmic

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Speaker 1: transparency and this is obviously not an algorithm, but we

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Speaker 1: don't have the transparency for the numbers to see exactly

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Speaker 1: how they're waiting these numbers to try and create the

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Speaker 1: sort of this is an electorate that is very difficult

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Speaker 1: to predict, right, And so the question is they're trying to,

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Speaker 1: yet again pull to explain an electorate that there is

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Speaker 1: not a lot that you can't completely explain, right.

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Speaker 3: Yeah, this is the challenge every year. It's always easier

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Speaker 3: in retrospect to see what the errors were, and I

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Speaker 3: think a lot of posters are trying in good faith

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Speaker 3: to figure it out and to get it right, to

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Speaker 3: learn from previous mistakes. There's also a reputational risk for

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Speaker 3: getting it wrong in the same direction a third time.

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Speaker 3: So in twenty sixteen, it was okay, we underestimated the

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Speaker 3: turnout or the Trump percentage of non college educated white voters.

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Speaker 3: In twenty twenty kind of underestimated the Republicans kind of

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Speaker 3: coming home to Trump. We've made it a lot closer

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Speaker 3: than the polls and anticipated as a Biden one, but

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Speaker 3: it was he's supposed to win by a lot more.

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Speaker 4: And this time we don't really know.

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Speaker 3: I mean, no polster is going to nor should they

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Speaker 3: reveal their secret sauce in terms of all, right, we're

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Speaker 3: going to comperment with this, but we are seeing some weirdness,

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Speaker 3: historical weirdness in the polls. We're seeing Trump winning a larger,

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Speaker 3: historically large number of people of color in the polls,

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Speaker 3: the largest in some cases since the Civil Rights Act

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Speaker 3: was passed, in which I find hard to believe. You

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Speaker 3: never quite know, but that could be the artifact of

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Speaker 3: them all changing their not all, but the way they're sampling,

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Speaker 3: or a way to reaching people, or maybe they're trying

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Speaker 3: something different, or maybe it's real.

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Speaker 4: I have my doubts, right, I have.

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Speaker 1: My doubts too, a lot of these. So let's talk

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Speaker 1: about cross tabs for truth. A lot of these numbers

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Speaker 1: look a little bit dicey. Explain to us like some

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Speaker 1: of these sort of the things you've seen in the

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Speaker 1: cross tabs. Besides this largest racial realignment since the voting

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Speaker 1: right to that.

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Speaker 3: Yeah, So every month I'm behind for May, but every

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Speaker 3: month I put together of higher quality national polls. I

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Speaker 3: dig through and manually enter all the cross that bindings

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Speaker 3: to see where the trends are releatant to twenty twenty

433
00:23:56,520 --> 00:23:58,119
Speaker 3: and what holes are showing are going to be the

434
00:23:58,160 --> 00:24:01,440
Speaker 3: biggest shifts again, we'll be, but what polls are capturing

435
00:24:01,520 --> 00:24:03,800
Speaker 3: right now? So this kind of smooths out any one

436
00:24:03,880 --> 00:24:06,920
Speaker 3: polster who's finding something super weird and also solves the

437
00:24:06,960 --> 00:24:09,679
Speaker 3: problem of looking at tiny sample sizes. This isn't a

438
00:24:09,680 --> 00:24:12,359
Speaker 3: perfect way of doing this, but it is better than

439
00:24:12,400 --> 00:24:14,280
Speaker 3: anything else that we have out there. So we have

440
00:24:14,320 --> 00:24:17,200
Speaker 3: a lot of regular forecasts, right I'm like, like, here's

441
00:24:17,200 --> 00:24:19,280
Speaker 3: the average of the polls. Here's real clear politics, here's

442
00:24:19,280 --> 00:24:21,840
Speaker 3: five thirty eight. This is trying to go under the service. Okay,

443
00:24:21,880 --> 00:24:24,800
Speaker 3: so Biden is down from four years ago. Where is

444
00:24:24,800 --> 00:24:28,440
Speaker 3: it happening among So every single month we're seeing black

445
00:24:28,520 --> 00:24:33,600
Speaker 3: voters shifting away from Biden and towards Trump by twenty

446
00:24:33,600 --> 00:24:36,119
Speaker 3: plus points compared to twenty twenty. We're still looking at

447
00:24:36,200 --> 00:24:39,160
Speaker 3: like a you know, eighty twenty type margin, but it's

448
00:24:39,280 --> 00:24:41,280
Speaker 3: above ninety ten in twenty twenty.

449
00:24:41,400 --> 00:24:42,520
Speaker 4: That's a huge shift.

450
00:24:42,720 --> 00:24:45,000
Speaker 3: And the polls right now are showing that Trump will

451
00:24:45,000 --> 00:24:47,800
Speaker 3: get the highest share of black voters since before nineteen

452
00:24:47,840 --> 00:24:49,680
Speaker 3: sixty four, so in a very.

453
00:24:49,640 --> 00:24:50,440
Speaker 4: Very very long time.

454
00:24:50,640 --> 00:24:53,320
Speaker 3: Based on why, there's a bunch of theories as to

455
00:24:53,400 --> 00:24:55,800
Speaker 3: why this is the case, one of which is that

456
00:24:56,000 --> 00:24:58,280
Speaker 3: this is real movement. This is based off of frustration

457
00:24:58,359 --> 00:25:01,280
Speaker 3: with Biden, based off of not following through on promises,

458
00:25:01,359 --> 00:25:03,440
Speaker 3: or impact of inflation or et cetera. But that doesn't

459
00:25:03,440 --> 00:25:05,800
Speaker 3: really explain why it's afecting black voters more than let's say,

460
00:25:05,840 --> 00:25:08,400
Speaker 3: Hispanic voters are non college educated white voters. I don't

461
00:25:08,400 --> 00:25:10,560
Speaker 3: find that super convinced it could be part of it.

462
00:25:10,680 --> 00:25:13,080
Speaker 3: But there are also other theories too, right that there

463
00:25:13,080 --> 00:25:15,600
Speaker 3: are just satisfaction with Biden is super high right now,

464
00:25:15,600 --> 00:25:18,280
Speaker 3: and so black voters are just expressing their frustration. This

465
00:25:18,359 --> 00:25:20,920
Speaker 3: is called expressive responding, where you're not really thinking about

466
00:25:20,960 --> 00:25:23,439
Speaker 3: it as a binary election. You're kind of just like,

467
00:25:23,600 --> 00:25:25,639
Speaker 3: I'm pissed at Biden, and you know what, I'm going

468
00:25:25,680 --> 00:25:27,200
Speaker 3: to say, I'm undecided, or I'm going to say I

469
00:25:27,320 --> 00:25:28,000
Speaker 3: vote for Trump, and.

470
00:25:28,000 --> 00:25:29,280
Speaker 4: Maybe you will, maybe you won't.

471
00:25:29,280 --> 00:25:32,000
Speaker 3: If we're using history as any guide, the base generally

472
00:25:32,040 --> 00:25:35,240
Speaker 3: comes home. This is also weird election. My personal theory,

473
00:25:35,280 --> 00:25:37,720
Speaker 3: the one I share with a few other polling nerds.

474
00:25:37,760 --> 00:25:39,080
Speaker 3: It has to do and this might be getting a

475
00:25:39,080 --> 00:25:39,840
Speaker 3: little in the weeds.

476
00:25:39,920 --> 00:25:41,480
Speaker 1: Please get in the weeds with us.

477
00:25:41,800 --> 00:25:45,280
Speaker 3: There are the ways of putting guardrails demographically. When you're

478
00:25:45,280 --> 00:25:46,919
Speaker 3: sealing the poll right, you don't want to get too

479
00:25:46,960 --> 00:25:48,760
Speaker 3: many white people, you don't want to get too many

480
00:25:48,840 --> 00:25:51,880
Speaker 3: college educated people. And there are some people that are

481
00:25:51,880 --> 00:25:55,639
Speaker 3: just easier to reach when you're polling colled educated folks,

482
00:25:55,680 --> 00:25:58,840
Speaker 3: white folks, women, people who lean more democratic. And those

483
00:25:58,880 --> 00:26:01,359
Speaker 3: are people as well, whether you're doing phone or online now,

484
00:26:01,400 --> 00:26:03,880
Speaker 3: because there much more inter as savvy than they used

485
00:26:03,920 --> 00:26:06,760
Speaker 3: to be five ten years ago. So what happens is

486
00:26:06,760 --> 00:26:08,840
Speaker 3: you put these guardrails up called quotas, make sure you're

487
00:26:08,880 --> 00:26:11,440
Speaker 3: not getting too many of one group. So you fill

488
00:26:11,520 --> 00:26:14,639
Speaker 3: up the easy buckets first, right, you fill up white voters,

489
00:26:14,680 --> 00:26:17,000
Speaker 3: you fill up seniors you feel up called it educated

490
00:26:17,160 --> 00:26:19,760
Speaker 3: and women, and then you're left with Okay, at the end,

491
00:26:19,800 --> 00:26:23,520
Speaker 3: we're scrambling to get black, Hispanic or Republican leaning voters,

492
00:26:23,600 --> 00:26:26,520
Speaker 3: younger voters, people who are much much, much harder to reach,

493
00:26:26,720 --> 00:26:29,560
Speaker 3: and so then you're kind of left with this weird

494
00:26:29,640 --> 00:26:33,480
Speaker 3: group or non representative group of young conservative people of

495
00:26:33,520 --> 00:26:35,879
Speaker 3: color who are not representing population, but they're who you

496
00:26:35,960 --> 00:26:38,440
Speaker 3: have left to reach, and so you get a couple

497
00:26:38,520 --> 00:26:40,359
Speaker 3: of those to fill out your quotas. And then at

498
00:26:40,359 --> 00:26:42,280
Speaker 3: the end, because you still don't have enough of them,

499
00:26:42,320 --> 00:26:44,480
Speaker 3: because again, they're very very hard to reach, and it's

500
00:26:44,600 --> 00:26:46,920
Speaker 3: very expensive to reach them, and you may not be

501
00:26:46,960 --> 00:26:49,560
Speaker 3: able to hit your deadlines. If you're just keep trying to,

502
00:26:49,600 --> 00:26:51,280
Speaker 3: you know, ram your head against the ball trying to

503
00:26:51,320 --> 00:26:53,919
Speaker 3: reach them, you upweight them. So what that means is

504
00:26:54,560 --> 00:26:58,240
Speaker 3: you make them basically worth more than one of themselves

505
00:26:58,440 --> 00:27:01,159
Speaker 3: in the actual final pool. Right, you wait, but the

506
00:27:01,280 --> 00:27:04,119
Speaker 3: entire sample to be representative of whatever you're trying to

507
00:27:04,119 --> 00:27:06,560
Speaker 3: go for. Let's say Red's registered voters or likely voters

508
00:27:06,600 --> 00:27:08,720
Speaker 3: in a particular state. So not only are you getting

509
00:27:08,720 --> 00:27:12,160
Speaker 3: people who aren't representative, you're making them more impactful than

510
00:27:12,560 --> 00:27:14,919
Speaker 3: they normally would be otherwise and you're down waiting. So

511
00:27:15,040 --> 00:27:17,240
Speaker 3: basically early on you're getting all these like white seniors

512
00:27:17,840 --> 00:27:21,040
Speaker 3: at college, which is maybe why you're seeing Biden holding

513
00:27:21,119 --> 00:27:24,400
Speaker 3: up better among white voters and seniors and things like that,

514
00:27:24,520 --> 00:27:27,040
Speaker 3: and while you see him slipping among young voters and

515
00:27:27,080 --> 00:27:29,320
Speaker 3: people of color. The truth is it's probably somewhere in

516
00:27:29,359 --> 00:27:31,800
Speaker 3: the middle of all these things. It's hard for me

517
00:27:31,960 --> 00:27:34,480
Speaker 3: to believe based on that a rematch election in a

518
00:27:34,640 --> 00:27:36,520
Speaker 3: very very long time. But it's hard for me to

519
00:27:36,560 --> 00:27:39,879
Speaker 3: see like these massive, massive swings in a rematch election

520
00:27:40,080 --> 00:27:42,720
Speaker 3: where people, most normal people don't want to think or

521
00:27:42,760 --> 00:27:46,000
Speaker 3: talk about this election. People are upset with their choices.

522
00:27:46,280 --> 00:27:48,000
Speaker 3: I don't know most of the conversations I've had with

523
00:27:48,040 --> 00:27:51,240
Speaker 3: people who aren't politically engaged, or just like Okay, I

524
00:27:51,280 --> 00:27:53,200
Speaker 3: guess we're doing this, or don't even know who the

525
00:27:53,240 --> 00:27:56,640
Speaker 3: nominees are still in June. So in that case, you'd

526
00:27:56,640 --> 00:27:59,520
Speaker 3: expect some movement on the margins, like yeah, okay, maybe

527
00:27:59,520 --> 00:28:02,320
Speaker 3: Biden lou Is, you know, three or four percentage points

528
00:28:02,720 --> 00:28:04,800
Speaker 3: among certain groups, gains, maybe some.

529
00:28:04,880 --> 00:28:05,600
Speaker 4: Back here or there.

530
00:28:05,600 --> 00:28:08,840
Speaker 3: But these twenty point swings, fifteen point swings would be,

531
00:28:09,280 --> 00:28:13,640
Speaker 3: let's just say, unprecedented, especially when both candidates are such

532
00:28:13,720 --> 00:28:15,760
Speaker 3: known quantities and very unpopular.

533
00:28:16,160 --> 00:28:19,800
Speaker 1: One of the things you said, which I thought was

534
00:28:20,160 --> 00:28:23,920
Speaker 1: very interesting, I'm doing this annoying thing that people do

535
00:28:24,280 --> 00:28:27,560
Speaker 1: where they talk about a tweet. It's a very annoying

536
00:28:27,600 --> 00:28:29,920
Speaker 1: thing when people do it. To me, I think they're stupid.

537
00:28:30,080 --> 00:28:32,880
Speaker 1: But you had a tweet that showed subthlet the effect

538
00:28:32,920 --> 00:28:36,240
Speaker 1: of so much anxiety on the left that Biden is

539
00:28:36,320 --> 00:28:39,280
Speaker 1: losing this saying that he should be winning by fifteen points,

540
00:28:39,520 --> 00:28:42,440
Speaker 1: but he's not actually in a terrible place right now,

541
00:28:42,480 --> 00:28:43,160
Speaker 1: is hey.

542
00:28:43,240 --> 00:28:46,480
Speaker 3: No, he's one, I mean historically normal pulling air away

543
00:28:46,520 --> 00:28:51,160
Speaker 3: from winning fairly comfortably. But Trump's also was one pulling

544
00:28:51,280 --> 00:28:53,800
Speaker 3: away from winning fairly comfortably too. But essentially we're looking

545
00:28:53,840 --> 00:28:56,040
Speaker 3: at a I mean five thirty eight released their forecast

546
00:28:56,080 --> 00:28:58,560
Speaker 3: today basically a coin flip, Biden as a fifty three

547
00:28:58,560 --> 00:29:02,000
Speaker 3: percent chance of winning, Trump as forty seven, and that's

548
00:29:02,040 --> 00:29:04,640
Speaker 3: been tightening since the last couple of months. And they

549
00:29:04,640 --> 00:29:09,080
Speaker 3: incorporate fundamentals like economics, consumer sentiment in addition to polling.

550
00:29:09,320 --> 00:29:11,600
Speaker 3: You know, if you look at polls today, Trump is

551
00:29:11,680 --> 00:29:14,640
Speaker 3: likely to win. But again, polls are not this far out,

552
00:29:14,720 --> 00:29:17,160
Speaker 3: are not meant to be predictive of what's happening in November.

553
00:29:17,200 --> 00:29:20,600
Speaker 3: Thought like, okay, this is again an imperfect snapshot, but

554
00:29:20,640 --> 00:29:22,800
Speaker 3: the best toool we had, as you mentioned earlier, of

555
00:29:22,840 --> 00:29:24,680
Speaker 3: where the race is right now. But we also have

556
00:29:24,800 --> 00:29:27,600
Speaker 3: these eyebrow race hitting shifts right and it's like, okay,

557
00:29:27,640 --> 00:29:29,800
Speaker 3: which one of these are real? Are they canceling each

558
00:29:29,840 --> 00:29:32,520
Speaker 3: other out? You know, is Biden doing as well among

559
00:29:32,600 --> 00:29:36,160
Speaker 3: seniors as good polls are showing? Is that counteracting other stuff?

560
00:29:36,160 --> 00:29:37,000
Speaker 3: So we don't really know.

561
00:29:37,120 --> 00:29:38,920
Speaker 1: And that was why I wanted to have you on

562
00:29:39,360 --> 00:29:42,280
Speaker 1: because the other thing I wanted you to talk about,

563
00:29:42,360 --> 00:29:46,360
Speaker 1: which I am struck by, is that in almost all

564
00:29:46,400 --> 00:29:52,400
Speaker 1: of these polls you have down ticket Democrats, namely senators

565
00:29:52,400 --> 00:29:56,280
Speaker 1: in swing states. And I'm thinking about Ohio here and

566
00:29:56,480 --> 00:29:59,480
Speaker 1: share odd is a once in a lifetime politician. But

567
00:29:59,680 --> 00:30:02,800
Speaker 1: also so he's running about ten points ahead of his competition.

568
00:30:02,920 --> 00:30:05,560
Speaker 1: He's running like fifteen points ahead of Biden.

569
00:30:05,360 --> 00:30:07,640
Speaker 3: And your friends, like the NPR Maris pulled up tea

570
00:30:07,720 --> 00:30:08,920
Speaker 3: out today that had him.

571
00:30:09,200 --> 00:30:10,720
Speaker 4: I think he was up five and.

572
00:30:10,640 --> 00:30:12,880
Speaker 3: Biden was down seven. And that's the first poll we've

573
00:30:12,880 --> 00:30:15,360
Speaker 3: had there in a while. That's actually the neat good quality.

574
00:30:15,480 --> 00:30:19,920
Speaker 1: Yeah, this Biden down brought the rest of the ticket

575
00:30:20,160 --> 00:30:24,239
Speaker 1: up for Democrats. See that in Pennsylvania, you see that

576
00:30:24,360 --> 00:30:28,680
Speaker 1: in Wisconsin. Saw that Michigan is seems a little tighter

577
00:30:28,720 --> 00:30:30,760
Speaker 1: in the center race. But I mean, you're seeing that

578
00:30:30,840 --> 00:30:32,840
Speaker 1: in a lot of these polls. So make that make

579
00:30:32,960 --> 00:30:33,520
Speaker 1: sense for me.

580
00:30:33,920 --> 00:30:35,960
Speaker 4: So I think there's two things going on.

581
00:30:37,040 --> 00:30:39,480
Speaker 3: There's a lot of races and what you're referring to

582
00:30:39,960 --> 00:30:44,959
Speaker 3: in those other states, So like Pennsylvania, Arizona, Wisconsin, Right, Arizona.

583
00:30:44,520 --> 00:30:47,680
Speaker 1: Ruben is running way ahead. Now I think Carrie Lake

584
00:30:48,160 --> 00:30:49,400
Speaker 1: is her own problem.

585
00:30:49,800 --> 00:30:53,240
Speaker 3: Yeah, she the unique case. Yeah, so talk about Arizona first.

586
00:30:53,320 --> 00:30:56,520
Speaker 3: So that's an open seat. Here's the cinema about running

587
00:30:56,520 --> 00:31:00,000
Speaker 3: for re election Carry Lake versus Ruben Geego. So Carry

588
00:31:00,040 --> 00:31:03,920
Speaker 3: Lake is running way behind Trump and Geago is running

589
00:31:03,960 --> 00:31:07,280
Speaker 3: a couple points ahead of Biden. That's a different situation

590
00:31:07,320 --> 00:31:09,719
Speaker 3: because Carry Lake is very well known and not very

591
00:31:09,760 --> 00:31:12,160
Speaker 3: well liked, and there's even been kind of whispers among

592
00:31:12,200 --> 00:31:17,080
Speaker 3: Republican operatives that they might just triage that race, they

593
00:31:17,120 --> 00:31:19,560
Speaker 3: might give up on her at some point, and that's

594
00:31:19,640 --> 00:31:21,720
Speaker 3: too early to say, but the fact they're even talking

595
00:31:21,760 --> 00:31:25,000
Speaker 3: about that in a state like Arizona is very telling.

596
00:31:25,240 --> 00:31:30,200
Speaker 3: But these other races in Nevada, in Wisconsin, and Pennsylvania,

597
00:31:30,520 --> 00:31:35,080
Speaker 3: you have the Democratic candidacity incumbent running out evenly with

598
00:31:35,080 --> 00:31:37,280
Speaker 3: Biden a little bit more, maybe a point or two

599
00:31:37,320 --> 00:31:40,560
Speaker 3: ahead on average, but the Republican is way behind Trump.

600
00:31:40,600 --> 00:31:41,800
Speaker 3: So a lot of that might have to do with

601
00:31:41,920 --> 00:31:44,400
Speaker 3: name recognition. They're like, I don't really know this person.

602
00:31:44,680 --> 00:31:47,120
Speaker 3: I'm not going to necessarily so that they'll probably, you know,

603
00:31:47,320 --> 00:31:50,120
Speaker 3: come home and vote the Republican We don't really know yet.

604
00:31:50,280 --> 00:31:52,120
Speaker 3: We don't really know if there's going to be we're

605
00:31:52,120 --> 00:31:54,160
Speaker 3: going to see a big return to split ticket voting

606
00:31:54,160 --> 00:31:57,360
Speaker 3: this year. It's been on the decline in recent cycles.

607
00:31:57,520 --> 00:32:01,880
Speaker 3: We only have, I believe, two senators that represent states

608
00:32:01,880 --> 00:32:04,840
Speaker 3: said the other party one in twenty twenty. That's Susan

609
00:32:04,880 --> 00:32:06,800
Speaker 3: Collins and Maine and Ron Johnson in Wisconsin.

610
00:32:06,840 --> 00:32:07,160
Speaker 4: That's it.

611
00:32:07,200 --> 00:32:09,920
Speaker 3: The other ninety eight senators represent states that they're party

612
00:32:09,920 --> 00:32:12,280
Speaker 3: won at the presidential level in twenty twenty. So it's

613
00:32:12,560 --> 00:32:14,840
Speaker 3: spliticket voting is not a big thing. The poles are

614
00:32:14,840 --> 00:32:18,520
Speaker 3: showing that it might be, particularly in Ohio, where I

615
00:32:18,520 --> 00:32:21,040
Speaker 3: think Sharon Brown's winning like ten percent of Trump voters,

616
00:32:21,440 --> 00:32:24,120
Speaker 3: has a much higher favorability rating. And then there's also

617
00:32:24,240 --> 00:32:27,560
Speaker 3: John Tester in Montana running in a deep, deep red

618
00:32:27,600 --> 00:32:31,120
Speaker 3: state but has shown some resiliency in the past, even

619
00:32:31,120 --> 00:32:34,160
Speaker 3: more so than Shah Brown. So they face uphill battles,

620
00:32:34,360 --> 00:32:37,480
Speaker 3: particularly if split ticket voting does not increase. They need

621
00:32:37,680 --> 00:32:40,360
Speaker 3: to win a bunch of Trump voters to have a chance.

622
00:32:40,560 --> 00:32:43,400
Speaker 3: But what I'm seeing elsewhere is that it's not that

623
00:32:43,560 --> 00:32:48,960
Speaker 3: Democrats are necessarily senate. Democrats are massively outperforming Biden. It's

624
00:32:49,000 --> 00:32:53,000
Speaker 3: that Senate Republican candidates are massively underperforming Trump. I kind

625
00:32:53,040 --> 00:32:55,640
Speaker 3: of expect a great convergence towards the end when people

626
00:32:55,640 --> 00:32:58,200
Speaker 3: start paying attention to these races a bit more. But

627
00:32:58,400 --> 00:33:01,560
Speaker 3: how much that converges, Like does Biden's numbers go up

628
00:33:01,760 --> 00:33:03,520
Speaker 3: or did the Senate Democrats numbers go down?

629
00:33:03,640 --> 00:33:04,640
Speaker 4: And that remains to be seen.

630
00:33:04,880 --> 00:33:08,920
Speaker 1: I've done some light covering of these Senate candidates and

631
00:33:08,960 --> 00:33:12,200
Speaker 1: they are bad. Like you know, they tend to be

632
00:33:12,800 --> 00:33:17,240
Speaker 1: a lot of rich people who can self fund and

633
00:33:17,760 --> 00:33:20,280
Speaker 1: you know, may not be the best person for the candidate.

634
00:33:20,320 --> 00:33:24,240
Speaker 1: There's a lot of carpetbagging going on. I'm thinking about Wisconsin.

635
00:33:25,120 --> 00:33:30,640
Speaker 1: In Pennsylvania you have Dave McCormick, you have Eric Hovedy.

636
00:33:30,920 --> 00:33:35,000
Speaker 1: In Wisconsin you have these rich white guys who you know,

637
00:33:35,160 --> 00:33:38,560
Speaker 1: can sell fund but aren't necessarily even from the places

638
00:33:38,560 --> 00:33:39,440
Speaker 1: they want to represent.

639
00:33:39,840 --> 00:33:40,040
Speaker 2: Right.

640
00:33:40,120 --> 00:33:42,800
Speaker 3: So in Montana you have Tim Sheehey grew up in

641
00:33:42,840 --> 00:33:46,560
Speaker 3: Minnesota and so elsewhere, came back to Montana. As you mentioned,

642
00:33:46,640 --> 00:33:48,600
Speaker 3: Dave McCormick's I still lives in Connecticut.

643
00:33:48,720 --> 00:33:51,320
Speaker 1: Oh no, Westbark, Connecticut. Yes, we love it.

644
00:33:51,760 --> 00:33:54,920
Speaker 3: Yeah, And running in Pennsylvania. I have Eric Hovdy in

645
00:33:54,960 --> 00:33:57,960
Speaker 3: Wisconsin who was supposed to be campaigning in Wisconsin but

646
00:33:58,000 --> 00:34:01,280
Speaker 3: instead was at the beach in the Beach in California

647
00:34:01,320 --> 00:34:03,600
Speaker 3: where he I think spill whims Or has a house there.

648
00:34:03,760 --> 00:34:07,200
Speaker 3: And even Sam Brown and Nevada ran for Congress in Texas.

649
00:34:07,240 --> 00:34:08,680
Speaker 3: I believe this a couple of years ago.

650
00:34:08,800 --> 00:34:10,960
Speaker 1: I'm sorry, I love this so much so.

651
00:34:11,000 --> 00:34:13,520
Speaker 3: Their strategy Steam Days is the head of a seeing

652
00:34:13,520 --> 00:34:15,839
Speaker 3: of recruit a lot of these candidates. Yeah, like you said,

653
00:34:15,880 --> 00:34:18,279
Speaker 3: they want these self funding candidates. They think that a

654
00:34:18,400 --> 00:34:21,040
Speaker 3: first time candidates for the most part, who don't have

655
00:34:21,040 --> 00:34:23,960
Speaker 3: like a legislative baggage, which is theoretically a plus. But

656
00:34:23,960 --> 00:34:27,240
Speaker 3: they're also pretty untested as candidates, which has not gone

657
00:34:27,280 --> 00:34:30,760
Speaker 3: well for downballot Republican candidates in twenty twenty and twenty

658
00:34:30,800 --> 00:34:33,040
Speaker 3: twenty two, and they coughed up some pretty winnable races

659
00:34:33,040 --> 00:34:36,000
Speaker 3: with some pretty undisciplined candidates.

660
00:34:36,040 --> 00:34:36,720
Speaker 4: I'll put it lately.

661
00:34:36,920 --> 00:34:40,279
Speaker 1: That money is supposed to go to Trump's legal fees. Noah,

662
00:34:40,560 --> 00:34:43,640
Speaker 1: thank you so much for making this make sense a

663
00:34:43,640 --> 00:34:47,239
Speaker 1: little bit. You know, I think that it's all we have,

664
00:34:47,960 --> 00:34:50,319
Speaker 1: so we just have to make it fucking work. But

665
00:34:50,400 --> 00:34:53,279
Speaker 1: we have to realize that it really is a blunt indicator.

666
00:34:53,719 --> 00:34:55,480
Speaker 3: Yeah, and I would say that we still have a

667
00:34:55,520 --> 00:34:58,200
Speaker 3: long way to go. I know polls are frustrating and confusing,

668
00:34:58,280 --> 00:35:01,760
Speaker 3: and I totally get that. I would not overly focus

669
00:35:01,880 --> 00:35:04,920
Speaker 3: on polls until we get to Labor Day, just for

670
00:35:05,000 --> 00:35:08,759
Speaker 3: everyone's mental sanity. I'll be following it closely, but you

671
00:35:08,840 --> 00:35:11,120
Speaker 3: all don't have to. It's okay. Things will become much

672
00:35:11,120 --> 00:35:12,600
Speaker 3: clear after the conventions.

673
00:35:12,800 --> 00:35:20,640
Speaker 1: Thank you, Thank Nally. Sarah Ellison is a reporter at

674
00:35:20,680 --> 00:35:26,160
Speaker 1: the Washington Post. Welcome too Fast Politics, Sarah.

675
00:35:25,560 --> 00:35:27,399
Speaker 5: Thank you so much for having me.

676
00:35:27,920 --> 00:35:30,319
Speaker 1: So one of the things you've been writing about, which

677
00:35:30,360 --> 00:35:32,440
Speaker 1: is one of the many things that keeps me up

678
00:35:32,440 --> 00:35:35,320
Speaker 1: at night. I have a couple. It's a teared system

679
00:35:35,400 --> 00:35:37,560
Speaker 1: of things that keep me up at night. But is

680
00:35:37,920 --> 00:35:42,319
Speaker 1: Trump was found guilty and immediately pivoted to trying to

681
00:35:42,480 --> 00:35:46,400
Speaker 1: tear down the legal system, one of the last great

682
00:35:46,440 --> 00:35:51,680
Speaker 1: sort of norms in our very kind of shaky American democracy.

683
00:35:52,120 --> 00:35:54,760
Speaker 1: Can you explain to us sort of what that looked

684
00:35:54,800 --> 00:35:57,160
Speaker 1: like and what the consequences of it are?

685
00:35:57,760 --> 00:36:01,759
Speaker 5: Sure he didn't even wait for the verse. What we

686
00:36:01,760 --> 00:36:05,520
Speaker 5: were watching during that entire trial is that it was.

687
00:36:05,560 --> 00:36:08,920
Speaker 5: You know, for months, his advisors expected that he would

688
00:36:08,920 --> 00:36:12,920
Speaker 5: be convicted by a New York jury, and they were

689
00:36:12,960 --> 00:36:17,640
Speaker 5: hopeful that he would not be convicted, but just in case,

690
00:36:18,400 --> 00:36:22,760
Speaker 5: he and his team waged an all out war against

691
00:36:22,840 --> 00:36:26,400
Speaker 5: the judicial system before the verdict even came in, hoping

692
00:36:26,520 --> 00:36:29,160
Speaker 5: to whatever that verdict was going to be, he was

693
00:36:29,200 --> 00:36:32,719
Speaker 5: going to blood the political damage and position himself as

694
00:36:32,760 --> 00:36:38,080
Speaker 5: a martyr. And you saw that day after day, Trump

695
00:36:38,120 --> 00:36:42,840
Speaker 5: attacking the judge, the judge's family, Trump attacking the gag

696
00:36:42,960 --> 00:36:45,920
Speaker 5: order that the judge placed on him so he wouldn't

697
00:36:45,920 --> 00:36:49,440
Speaker 5: intimidate witnesses in the case. But I think the thing

698
00:36:49,480 --> 00:36:52,480
Speaker 5: that people really were struck by is that it wasn't

699
00:36:52,520 --> 00:36:55,759
Speaker 5: just Trump. It was and it wasn't just Trump's surrogates,

700
00:36:55,800 --> 00:36:58,040
Speaker 5: you know, the people that you normally see going on

701
00:36:58,080 --> 00:37:02,239
Speaker 5: social media to repeat his attacks and amplify his attacks.

702
00:37:02,920 --> 00:37:06,160
Speaker 5: You saw a totally different branch of government. You saw

703
00:37:06,280 --> 00:37:10,759
Speaker 5: members of Congress show up to attack again, not just

704
00:37:10,840 --> 00:37:14,600
Speaker 5: the judge, but the jury system. Like Tommy Tuberville said,

705
00:37:14,920 --> 00:37:18,200
Speaker 5: these so called Americans who were serving on the jury, right,

706
00:37:18,360 --> 00:37:21,720
Speaker 5: and like, we don't have anything better than the jury

707
00:37:21,760 --> 00:37:23,800
Speaker 5: of our peers, Like that's as good as it gets,

708
00:37:23,840 --> 00:37:26,640
Speaker 5: Like that's all we can offer. And so you know,

709
00:37:26,719 --> 00:37:30,080
Speaker 5: what we were struck by is that it's all politics.

710
00:37:30,280 --> 00:37:35,560
Speaker 5: It's all for Trump and his allies. There's no institution

711
00:37:36,080 --> 00:37:39,680
Speaker 5: of our democracy that they are unafraid to attack, and

712
00:37:39,960 --> 00:37:42,120
Speaker 5: these attacks on the judiciary, Like the judiciary is the

713
00:37:42,160 --> 00:37:45,160
Speaker 5: most popular branch of government. It's something that people still

714
00:37:45,239 --> 00:37:48,560
Speaker 5: have some faith in. And every academic we talked to

715
00:37:48,719 --> 00:37:52,440
Speaker 5: said that this case felt a body blow to that trust.

716
00:37:52,640 --> 00:37:55,320
Speaker 5: And so we're just sort of watching it degrade before

717
00:37:55,360 --> 00:37:55,800
Speaker 5: our eyes.

718
00:37:56,280 --> 00:37:58,200
Speaker 1: So why is it?

719
00:37:58,280 --> 00:37:58,640
Speaker 5: A mean?

720
00:37:58,840 --> 00:38:01,359
Speaker 1: I want you're on this straight news side, so I

721
00:38:01,360 --> 00:38:04,719
Speaker 1: don't want to make you give an opinion here, but

722
00:38:04,880 --> 00:38:07,880
Speaker 1: I'm curious. It's sort of if you try to make

723
00:38:07,920 --> 00:38:11,080
Speaker 1: it make sense to me. Why is it that when

724
00:38:11,120 --> 00:38:15,959
Speaker 1: Trump goes after a branch of government like he's doing

725
00:38:15,960 --> 00:38:18,560
Speaker 1: with the judiciary right now, but he has done with

726
00:38:18,880 --> 00:38:23,040
Speaker 1: Congress and with our elections are free and fair elections.

727
00:38:23,360 --> 00:38:26,640
Speaker 1: Why is it that that works? And it doesn't work

728
00:38:26,640 --> 00:38:28,719
Speaker 1: with everyone, It only works with his people. But why

729
00:38:28,760 --> 00:38:31,839
Speaker 1: does it work with his people? And why is it

730
00:38:32,239 --> 00:38:34,160
Speaker 1: why can nothing penetrate that?

731
00:38:34,719 --> 00:38:36,880
Speaker 5: I mean, one of the things. I just did a

732
00:38:36,920 --> 00:38:42,399
Speaker 5: piece on the effort post January sixth, twenty twenty one,

733
00:38:42,840 --> 00:38:46,480
Speaker 5: to keep Trump's voice off of social media, right, like,

734
00:38:46,560 --> 00:38:50,719
Speaker 5: there is this effort across the board Twitter, Facebook, YouTube

735
00:38:51,040 --> 00:38:54,080
Speaker 5: after January sixth. The idea was that Trump's message needed

736
00:38:54,120 --> 00:38:58,319
Speaker 5: to be curtailed because it caused violence right the IDAAE

737
00:38:58,480 --> 00:39:02,120
Speaker 5: and violated you know, all these social media platforms had

738
00:39:02,280 --> 00:39:06,440
Speaker 5: laid around with different standards and trust in safety teams

739
00:39:06,480 --> 00:39:10,560
Speaker 5: and efforts to make their platforms quote unquote safer and

740
00:39:10,640 --> 00:39:13,759
Speaker 5: more reliable, and then after January sixth, there was this

741
00:39:14,040 --> 00:39:17,799
Speaker 5: across the board fear that Trump had used his platform

742
00:39:17,920 --> 00:39:22,000
Speaker 5: to encourage violence, and that is a clear violation of

743
00:39:22,040 --> 00:39:25,600
Speaker 5: everybody's policies. So he was taken off of social media

744
00:39:25,680 --> 00:39:28,680
Speaker 5: and it was like banning him from a twenty first

745
00:39:28,680 --> 00:39:32,200
Speaker 5: century town square. And the idea was, this is going

746
00:39:32,239 --> 00:39:36,680
Speaker 5: to protect people from these harmful messages. And what we

747
00:39:36,800 --> 00:39:40,200
Speaker 5: looked at was that three years later that had been

748
00:39:40,239 --> 00:39:43,719
Speaker 5: an abject failure because Trump's message was as strong as effort.

749
00:39:44,040 --> 00:39:49,040
Speaker 5: More people believe that January sixth was a peaceful protest

750
00:39:49,160 --> 00:39:51,800
Speaker 5: than they did immediately in the aftermath of that case.

751
00:39:52,400 --> 00:39:56,120
Speaker 5: And so Trump is a potent political force. His messages

752
00:39:56,200 --> 00:39:59,960
Speaker 5: get out even though all he's doing is posting on

753
00:40:00,120 --> 00:40:03,680
Speaker 5: true social And what we sort of dug into there

754
00:40:03,800 --> 00:40:05,520
Speaker 5: was why is that This is a long way of

755
00:40:05,560 --> 00:40:10,080
Speaker 5: answering your question, but why is that message so crucial

756
00:40:10,120 --> 00:40:13,520
Speaker 5: for people to continue to get out there? It feels

757
00:40:13,640 --> 00:40:16,960
Speaker 5: very obvious in some ways, but there are both political

758
00:40:17,000 --> 00:40:22,120
Speaker 5: advantages to mimicking his messages. You see that with Elie Stephonic,

759
00:40:22,160 --> 00:40:24,800
Speaker 5: you see that with Jim Jordan. There's a tremendous amount

760
00:40:25,080 --> 00:40:27,440
Speaker 5: you can get out of Donald Trump if you are

761
00:40:27,480 --> 00:40:31,760
Speaker 5: a Republican trying to advance your career. There are also

762
00:40:31,840 --> 00:40:37,680
Speaker 5: great financial benefits for people people who have spread his

763
00:40:37,800 --> 00:40:40,960
Speaker 5: messages and created mini media empires out of doing that.

764
00:40:41,360 --> 00:40:43,560
Speaker 5: And that is you know, when Trump went to war

765
00:40:43,560 --> 00:40:47,600
Speaker 5: with Fox News after the twenty twenty election, there was

766
00:40:47,640 --> 00:40:53,760
Speaker 5: a whole outpouring of new conservative voices who were finding

767
00:40:53,800 --> 00:40:59,080
Speaker 5: their way to make money off of election denialism and

768
00:40:59,160 --> 00:41:02,160
Speaker 5: Donald Trump, and Steve Bannon told me for a story

769
00:41:02,160 --> 00:41:05,560
Speaker 5: that I did recently that that's what the economy of

770
00:41:05,600 --> 00:41:09,319
Speaker 5: the Internet relies on the Trumps of the world and

771
00:41:09,360 --> 00:41:12,120
Speaker 5: the mini Trumps of the world to get that message

772
00:41:12,160 --> 00:41:16,160
Speaker 5: out and to create clickbit content, to create viral content.

773
00:41:16,520 --> 00:41:19,560
Speaker 5: So there's a real financial benefit to doing that, and

774
00:41:19,600 --> 00:41:22,680
Speaker 5: then there's just the community benefit of you're with Trump.

775
00:41:23,040 --> 00:41:26,759
Speaker 5: And a very strong message that I think people genuinely

776
00:41:26,840 --> 00:41:30,280
Speaker 5: believe is that the federal government has been weaponized against

777
00:41:30,360 --> 00:41:33,200
Speaker 5: Donald Trump. In all of these cases, whether they're state

778
00:41:33,239 --> 00:41:38,080
Speaker 5: cases or federal cases, are being kind of manipulated by

779
00:41:38,239 --> 00:41:41,640
Speaker 5: Joe Biden. I mean, this is the message and being

780
00:41:41,680 --> 00:41:47,520
Speaker 5: weaponized against an opposition leader. And that is a strong

781
00:41:47,560 --> 00:41:50,440
Speaker 5: message that Donald Trump has seeded, and he's done it

782
00:41:50,480 --> 00:41:54,719
Speaker 5: with his allies, and people genuinely believe that. And now

783
00:41:54,760 --> 00:41:59,920
Speaker 5: we're dealing Marco Rubio, who used to attack Trump pretty

784
00:42:00,400 --> 00:42:04,720
Speaker 5: strongly in the twenty sixteen election, is sending a message

785
00:42:04,719 --> 00:42:10,440
Speaker 5: to his followers on X that watching Donald Trump's trial

786
00:42:10,600 --> 00:42:12,440
Speaker 5: was like watching a show trial in Cuba.

787
00:42:12,840 --> 00:42:13,040
Speaker 2: Right.

788
00:42:13,120 --> 00:42:16,520
Speaker 5: That was insane, right, I mean, you can call it

789
00:42:16,840 --> 00:42:18,680
Speaker 5: say a lot of things about that case, and I

790
00:42:18,719 --> 00:42:20,959
Speaker 5: know a lot of people about the hush money case

791
00:42:21,000 --> 00:42:23,360
Speaker 5: and their different views on the strength of the case

792
00:42:23,440 --> 00:42:25,600
Speaker 5: and whether it should have been brought, But it wasn't

793
00:42:25,640 --> 00:42:26,600
Speaker 5: a show trial.

794
00:42:26,800 --> 00:42:27,520
Speaker 1: Right right?

795
00:42:27,719 --> 00:42:27,959
Speaker 2: Right?

796
00:42:28,080 --> 00:42:31,640
Speaker 1: No? No, I mean here's a question for you though,

797
00:42:31,920 --> 00:42:34,759
Speaker 1: if you were looking at this sort of like, I mean,

798
00:42:34,840 --> 00:42:40,279
Speaker 1: how much of Americans are in that information bubble? Right this?

799
00:42:40,800 --> 00:42:44,280
Speaker 1: You know? I mean what seventy seven million, eighty million

800
00:42:44,280 --> 00:42:47,200
Speaker 1: Americans voted for Donald Trump? When you look at there's

801
00:42:47,280 --> 00:42:49,880
Speaker 1: all sorts of polling that came out last week about

802
00:42:49,920 --> 00:42:53,440
Speaker 1: how like if you read the newspaper, you're like eighty

803
00:42:53,440 --> 00:42:55,759
Speaker 1: percent more likely you vote for Biden, right if you

804
00:42:56,480 --> 00:42:59,840
Speaker 1: just read any newspaper, right except possibly the New York Post.

805
00:43:00,400 --> 00:43:04,120
Speaker 1: So is it, Joss? This information bubble is a just

806
00:43:04,280 --> 00:43:08,600
Speaker 1: tech companies giving us sort of this pableum that isn't

807
00:43:08,960 --> 00:43:12,600
Speaker 1: actual verified news sources. I mean, is that where this

808
00:43:12,920 --> 00:43:15,800
Speaker 1: where the sort of echo chamber is being built?

809
00:43:15,960 --> 00:43:18,920
Speaker 5: Or is there something I'm missing here? It's such a

810
00:43:18,920 --> 00:43:21,319
Speaker 5: good question, and I've actually talked to a bunch of

811
00:43:21,800 --> 00:43:27,239
Speaker 5: misinformation researchers about this, who say themselves that we have

812
00:43:27,920 --> 00:43:32,360
Speaker 5: wildly over credited the power of social media.

813
00:43:32,800 --> 00:43:36,560
Speaker 1: Oh good, thank you. You know, I ask everyone this

814
00:43:36,680 --> 00:43:39,640
Speaker 1: question and most people either like, don't answer it or

815
00:43:39,680 --> 00:43:43,279
Speaker 1: tell me I'm dumb. So to hear someone actually like

816
00:43:43,480 --> 00:43:47,000
Speaker 1: address this is like probably the best interview I've ever done.

817
00:43:47,040 --> 00:43:49,759
Speaker 1: So explain to me why we're overestimating it because I

818
00:43:50,440 --> 00:43:51,200
Speaker 1: love to hear it.

819
00:43:51,400 --> 00:43:53,920
Speaker 5: Yeah, I mean, this is like I shouldn't be answering

820
00:43:53,920 --> 00:43:56,040
Speaker 5: because I only really have half the answer, but I

821
00:43:56,160 --> 00:44:00,480
Speaker 5: was fine. It's brilliant researcher from Harvard. His name is Johailer,

822
00:44:00,840 --> 00:44:03,759
Speaker 5: he has one I mean, he's just so well regarded

823
00:44:03,840 --> 00:44:07,279
Speaker 5: in the world of online disinformation, and he has been

824
00:44:07,320 --> 00:44:10,640
Speaker 5: studying it for a quarter of a century. And he

825
00:44:10,920 --> 00:44:14,000
Speaker 5: said to me in a relatively brief interview, although I've

826
00:44:14,000 --> 00:44:16,759
Speaker 5: read his book and was asking about it, he was

827
00:44:16,800 --> 00:44:20,080
Speaker 5: the person who said, we have focused too much on

828
00:44:20,120 --> 00:44:22,480
Speaker 5: the impact of social media. And he's like, now I'm

829
00:44:22,480 --> 00:44:25,320
Speaker 5: going to after a quarter of a century, I'm turning

830
00:44:25,360 --> 00:44:29,839
Speaker 5: my research efforts into looking at the political economy of

831
00:44:29,920 --> 00:44:32,840
Speaker 5: this country and the way that it has created. And

832
00:44:32,880 --> 00:44:35,399
Speaker 5: he didn't use this term exactly, but I think it's

833
00:44:35,400 --> 00:44:38,640
Speaker 5: such a relevant way for us to think about this.

834
00:44:39,080 --> 00:44:44,120
Speaker 5: We talk about the supply of disinformation constantly and how

835
00:44:44,160 --> 00:44:47,839
Speaker 5: to stem the supply of disinformation. We don't talk as

836
00:44:47,920 --> 00:44:51,920
Speaker 5: much about the demand for it and how hotent that is.

837
00:44:52,360 --> 00:44:54,799
Speaker 5: And I think that, I mean, it's that's more than like,

838
00:44:54,960 --> 00:44:57,200
Speaker 5: let's not go sit in anymore diners and talk to

839
00:44:57,200 --> 00:45:01,200
Speaker 5: people about why they might believe conspirac theories. But I'm

840
00:45:01,200 --> 00:45:03,120
Speaker 5: going to piece together a few interviews that I've done

841
00:45:03,160 --> 00:45:05,920
Speaker 5: with different people about this, which is that during COVID,

842
00:45:06,200 --> 00:45:08,839
Speaker 5: there was a time where people felt like they were

843
00:45:08,880 --> 00:45:12,560
Speaker 5: being fed information that turned out to not be true

844
00:45:12,719 --> 00:45:16,960
Speaker 5: later right like at the beginning of COVID, Anthony Fauchu

845
00:45:17,000 --> 00:45:18,640
Speaker 5: was saying, don't wear a mask. You don't need to

846
00:45:18,680 --> 00:45:21,440
Speaker 5: wear a mask, and then the you know, the advice

847
00:45:21,600 --> 00:45:26,680
Speaker 5: changed and people can find sort of real reasons in

848
00:45:26,760 --> 00:45:30,880
Speaker 5: that moment to think that the authorities are telling you

849
00:45:31,000 --> 00:45:35,000
Speaker 5: the truth, even though with such a fluid moment, people

850
00:45:35,000 --> 00:45:37,279
Speaker 5: didn't really know what the truth was. Where did the

851
00:45:37,360 --> 00:45:38,279
Speaker 5: virus come from?

852
00:45:38,360 --> 00:45:38,400
Speaker 2: What?

853
00:45:38,920 --> 00:45:41,200
Speaker 5: You know, the whole world was turned upside down, so

854
00:45:41,280 --> 00:45:44,319
Speaker 5: that kind of put people in a frame of mind

855
00:45:44,080 --> 00:45:46,920
Speaker 5: that you didn't know what to believe. And then on

856
00:45:47,040 --> 00:45:49,560
Speaker 5: that year was just so nuts because then you had

857
00:45:49,560 --> 00:45:52,240
Speaker 5: the election and you had the conspiracies about the election.

858
00:45:52,880 --> 00:45:56,719
Speaker 5: And I think during that period the notion of when

859
00:45:56,760 --> 00:45:59,560
Speaker 5: I talk to people about who know way more than

860
00:45:59,560 --> 00:46:02,160
Speaker 5: I do and have studied this, they say that that

861
00:46:02,280 --> 00:46:04,719
Speaker 5: was sort of the stew that led us it was

862
00:46:04,920 --> 00:46:09,880
Speaker 5: such a disruption in society about what people believed was

863
00:46:09,920 --> 00:46:14,040
Speaker 5: true and what they could rely upon that now we're

864
00:46:14,160 --> 00:46:18,759
Speaker 5: in this moment where the demand for answers is so

865
00:46:19,000 --> 00:46:22,640
Speaker 5: great and the supply of like definitive answers are sort

866
00:46:22,680 --> 00:46:25,600
Speaker 5: of they're scarcer than the demand, so people sort of

867
00:46:25,600 --> 00:46:28,640
Speaker 5: fill in the gaps in their own way. If that

868
00:46:29,000 --> 00:46:30,000
Speaker 5: makes sense.

869
00:46:30,280 --> 00:46:33,640
Speaker 1: No, it actually does. This is like I have to

870
00:46:33,680 --> 00:46:35,960
Speaker 1: tell you sometimes I have a question and I just

871
00:46:36,000 --> 00:46:40,359
Speaker 1: can't fucking get anyone to answer it. And this idea

872
00:46:40,480 --> 00:46:42,520
Speaker 1: of and one of the reasons why I love having

873
00:46:42,600 --> 00:46:45,760
Speaker 1: a podcast is because I get to ask people questions

874
00:46:45,800 --> 00:46:48,720
Speaker 1: that I need to answer to, and you know, different

875
00:46:48,800 --> 00:46:52,120
Speaker 1: kinds of people, et cetera. But this idea that the

876
00:46:52,160 --> 00:46:56,480
Speaker 1: information we needed was not available and so bad information

877
00:46:56,680 --> 00:46:59,520
Speaker 1: filled the void makes so much sense.

878
00:47:00,080 --> 00:47:03,480
Speaker 5: Yeah, and I'll add one other like data point into

879
00:47:03,520 --> 00:47:07,520
Speaker 5: this from again people whose job it is to study

880
00:47:08,080 --> 00:47:11,480
Speaker 5: bad information and how it travels. And I think everybody

881
00:47:11,560 --> 00:47:14,040
Speaker 5: understands this a lot better now. But we've we focused

882
00:47:14,080 --> 00:47:18,279
Speaker 5: so much on like top down bad information, like what

883
00:47:18,320 --> 00:47:21,200
Speaker 5: does the Russian government want to do? What does Iran

884
00:47:21,280 --> 00:47:23,719
Speaker 5: want to do? What does China want to do? And

885
00:47:23,760 --> 00:47:28,200
Speaker 5: that's all there still. But what these researchers have told

886
00:47:28,239 --> 00:47:31,239
Speaker 5: me is that there's a much because we've established this

887
00:47:31,320 --> 00:47:33,840
Speaker 5: and there's now a narrative and it's like the government

888
00:47:33,880 --> 00:47:37,080
Speaker 5: is weaponized, or you know, the government is weaponized against

889
00:47:37,080 --> 00:47:41,360
Speaker 5: its enemies, or the government is lying to you about COVID,

890
00:47:41,760 --> 00:47:46,279
Speaker 5: the election was stolen. Those are big, big narratives. And

891
00:47:46,360 --> 00:47:51,080
Speaker 5: you can have any random person on Twitter can take

892
00:47:51,120 --> 00:47:54,400
Speaker 5: a photograph of, you know, a ballot in a trash

893
00:47:54,440 --> 00:47:58,759
Speaker 5: can and say what is this? It looks like X

894
00:47:58,920 --> 00:48:02,040
Speaker 5: is happening and then and that's like a bottom up

895
00:48:02,440 --> 00:48:04,640
Speaker 5: effort as opposed to a top down effort. And you

896
00:48:04,640 --> 00:48:08,840
Speaker 5: don't even need to want to be creating a different narrative,

897
00:48:08,880 --> 00:48:13,040
Speaker 5: but that one data point of a random user on

898
00:48:13,080 --> 00:48:17,480
Speaker 5: Twitter can get picked up and just spread around in

899
00:48:17,520 --> 00:48:21,680
Speaker 5: a way that is sort of entirely divorced from the

900
00:48:21,719 --> 00:48:25,359
Speaker 5: initial intent of that poster. But the idea being that, like,

901
00:48:25,440 --> 00:48:28,440
Speaker 5: it's not just someone is feeding you a line of

902
00:48:28,480 --> 00:48:31,480
Speaker 5: a created narrative. It is that the narrative is there

903
00:48:32,160 --> 00:48:36,520
Speaker 5: and you can bottom up contribute to that. It's the

904
00:48:36,560 --> 00:48:38,600
Speaker 5: old thing of like I'm just asking questions, what is

905
00:48:38,640 --> 00:48:41,399
Speaker 5: this ballot? Doing here on the street, and then like, boy,

906
00:48:41,440 --> 00:48:43,600
Speaker 5: are there going to be you know, ten other people

907
00:48:43,680 --> 00:48:45,200
Speaker 5: who are going to pick that up and have their

908
00:48:45,200 --> 00:48:48,359
Speaker 5: own answer, And then Gateway Pundit is going to come

909
00:48:48,400 --> 00:48:50,560
Speaker 5: in and write a story about it, and then that's

910
00:48:50,600 --> 00:48:53,120
Speaker 5: a headline that then can be picked up and kind

911
00:48:53,160 --> 00:48:55,920
Speaker 5: of taken and done something else with. So these are

912
00:48:56,280 --> 00:48:59,560
Speaker 5: I think it's it's people who study what we call

913
00:48:59,640 --> 00:49:03,600
Speaker 5: dissem information and misinformation are moving away from those terms

914
00:49:03,920 --> 00:49:07,880
Speaker 5: because they're totally ineffective. You can't ever convince anybody that

915
00:49:07,880 --> 00:49:10,640
Speaker 5: they've fallen for a piece of bad information. It's just

916
00:49:10,680 --> 00:49:15,759
Speaker 5: like a completely losing exercise, right, And it's also like

917
00:49:15,800 --> 00:49:19,080
Speaker 5: it moves faster than you ever could try to tamp

918
00:49:19,160 --> 00:49:21,600
Speaker 5: it down. So we talked to secretaries of State's office

919
00:49:21,640 --> 00:49:24,319
Speaker 5: who say, well, last time we tried to have a

920
00:49:24,360 --> 00:49:26,839
Speaker 5: strong social media policy where we would like knock down

921
00:49:26,880 --> 00:49:29,000
Speaker 5: these false rumors, they don't even try to do it

922
00:49:29,000 --> 00:49:32,400
Speaker 5: anymore because it doesn't work. And so I think that

923
00:49:32,440 --> 00:49:35,040
Speaker 5: we're kind of moving into I don't know, is this

924
00:49:35,120 --> 00:49:39,799
Speaker 5: like two point zero bad information studies where people are

925
00:49:39,840 --> 00:49:43,719
Speaker 5: really realizing there's no putting the toothpaste back in the

926
00:49:43,760 --> 00:49:46,440
Speaker 5: bottle or whatever, like the election was stolen in twenty

927
00:49:46,480 --> 00:49:48,439
Speaker 5: twenty is a narrative that is out there. It doesn't

928
00:49:48,440 --> 00:49:50,839
Speaker 5: matter how many court cases or how many Donald Trump

929
00:49:50,840 --> 00:49:54,400
Speaker 5: appointed judges say that that wasn't the case. Like, it's there.

930
00:49:54,640 --> 00:50:00,400
Speaker 5: And so the question is, now, what does society do

931
00:50:00,760 --> 00:50:04,320
Speaker 5: with that information? And it all comes back to the

932
00:50:04,640 --> 00:50:08,560
Speaker 5: original Donald Trump verdict story, which is that there are

933
00:50:08,600 --> 00:50:10,680
Speaker 5: a lot of people. I mean, you can have that

934
00:50:10,880 --> 00:50:14,040
Speaker 5: that is a fact that had happened. There was a

935
00:50:14,080 --> 00:50:18,480
Speaker 5: guilty verdict thirty four counts, a jury of his peers.

936
00:50:18,120 --> 00:50:20,279
Speaker 1: And if you want to you know, if you do

937
00:50:20,400 --> 00:50:22,919
Speaker 1: crimes in New York, you got to sit in front

938
00:50:22,960 --> 00:50:25,359
Speaker 1: of a New York jury. If you do crimes in Mississippi,

939
00:50:25,440 --> 00:50:28,960
Speaker 1: maybe they don't necessarily care. If you do crimes or

940
00:50:29,160 --> 00:50:33,560
Speaker 1: Palm Beach. Maybe he'd get a better, more partisan jury

941
00:50:33,640 --> 00:50:35,919
Speaker 1: that would let him off in Palm Beach. But look,

942
00:50:36,000 --> 00:50:39,080
Speaker 1: Hunter Biden just got found guilty, and he had a

943
00:50:39,160 --> 00:50:42,080
Speaker 1: jury of his peers in the state of Delaware where

944
00:50:42,080 --> 00:50:45,279
Speaker 1: his father is pretty much Elvis, and he got found

945
00:50:45,320 --> 00:50:48,360
Speaker 1: guilty too, which means the law is the law for

946
00:50:48,440 --> 00:50:51,920
Speaker 1: everyone and is a real win for our justice system,

947
00:50:52,320 --> 00:50:55,319
Speaker 1: and we should all be celebrating it because this is

948
00:50:55,760 --> 00:51:00,000
Speaker 1: what we want, is a blind justice system that looks

949
00:51:00,120 --> 00:51:02,600
Speaker 1: set the facts and that does what it's supposed to do.

950
00:51:03,040 --> 00:51:06,640
Speaker 5: Yeah, I mean, your weight is very apt here, and

951
00:51:06,680 --> 00:51:09,360
Speaker 5: it was, you know, I was talking to people before

952
00:51:09,520 --> 00:51:14,040
Speaker 5: the Hunter verdict came down, obviously because it just happened.

953
00:51:14,440 --> 00:51:16,960
Speaker 5: But the lesson there was exactly what you just said,

954
00:51:17,239 --> 00:51:21,240
Speaker 5: which is that the justice system is not captured because

955
00:51:21,520 --> 00:51:25,120
Speaker 5: the president's own son was just found guilty of felonies.

956
00:51:25,280 --> 00:51:28,880
Speaker 5: So the justice system itself is sort of standing standing

957
00:51:28,960 --> 00:51:32,600
Speaker 5: up for democracy. And that was the sort of split

958
00:51:32,680 --> 00:51:37,959
Speaker 5: headline that we had the day after Trump's hush money

959
00:51:38,040 --> 00:51:42,680
Speaker 5: verdict was the justice system worked, and it's been really

960
00:51:42,719 --> 00:51:46,440
Speaker 5: harmed by all of the attacks. And the vast majority

961
00:51:46,440 --> 00:51:49,880
Speaker 5: of Republicans felt that that jury was corrupt and that

962
00:51:49,960 --> 00:51:53,680
Speaker 5: the case was wrongly decided, and that is due to

963
00:51:53,719 --> 00:51:58,040
Speaker 5: Donald Trump's very concerted effort to discredit that jury and

964
00:51:58,080 --> 00:52:00,800
Speaker 5: that entire proceeding. But if you look at the facts,

965
00:52:01,120 --> 00:52:03,480
Speaker 5: the justice system sort of did its job, and it

966
00:52:03,480 --> 00:52:06,200
Speaker 5: did its job again with Hunter Biden. And so it

967
00:52:06,360 --> 00:52:09,120
Speaker 5: takes a long time to have these verdicts come out,

968
00:52:09,239 --> 00:52:11,120
Speaker 5: but they do, and just to add one other thought,

969
00:52:11,120 --> 00:52:13,200
Speaker 5: which is when you talk about you know, that's why

970
00:52:13,320 --> 00:52:16,719
Speaker 5: Jack Smith brought his case in Florida, and he didn't

971
00:52:16,719 --> 00:52:19,319
Speaker 5: even want to fight over the venue. He just went

972
00:52:19,400 --> 00:52:23,040
Speaker 5: directly to Donald Trump's backyard to bring that case and.

973
00:52:23,239 --> 00:52:26,160
Speaker 1: It happened to work out very well for Donald Trump.

974
00:52:26,200 --> 00:52:31,600
Speaker 1: Thank you so much, Sarah. Really appreciate you. Really great

975
00:52:31,600 --> 00:52:34,000
Speaker 1: to have you. Thank you, thank you for having me.

976
00:52:34,040 --> 00:52:38,600
Speaker 5: It was a pleasure a moment.

977
00:52:40,120 --> 00:52:43,360
Speaker 3: Jesse Cannon by John Fest I got to tell you,

978
00:52:43,400 --> 00:52:47,120
Speaker 3: after hearing these recordings of mister and Missus Alito, I

979
00:52:47,160 --> 00:52:48,120
Speaker 3: don't want to hang out.

980
00:52:47,960 --> 00:52:53,719
Speaker 1: With them, Alito, no go. There were some recordings of

981
00:52:53,800 --> 00:52:58,799
Speaker 1: Missus Alito, mister Alito and also Justice Roberts. They were

982
00:52:59,000 --> 00:53:02,520
Speaker 1: done by a woman who that's sort of her thing.

983
00:53:02,680 --> 00:53:07,640
Speaker 1: She does these tapes. I thought that they said pretty

984
00:53:07,680 --> 00:53:10,560
Speaker 1: much what we thought they would say, but you know,

985
00:53:10,600 --> 00:53:13,960
Speaker 1: it's still kind of striking. The woman who recorded her

986
00:53:13,960 --> 00:53:18,120
Speaker 1: as a woman called Lauren windsor Missus Alito. I want

987
00:53:18,160 --> 00:53:20,839
Speaker 1: a sacred Heart of Jesus flag because I have to

988
00:53:20,840 --> 00:53:24,480
Speaker 1: look across the lagoon at the Pride flag next month.

989
00:53:24,640 --> 00:53:28,360
Speaker 1: So Missus Alito, she wants to let her freak flag

990
00:53:28,560 --> 00:53:34,480
Speaker 1: fly and for that she is our moment of Buckray.

991
00:53:35,560 --> 00:53:38,920
Speaker 1: That's it for this episode of Fast Politics. Tune in

992
00:53:38,960 --> 00:53:42,160
Speaker 1: every Monday, Wednesday, and Friday to hear the best minds

993
00:53:42,160 --> 00:53:45,400
Speaker 1: in politics makes sense of all this chaos. If you

994
00:53:45,520 --> 00:53:48,200
Speaker 1: enjoyed what you've heard, please send it to a friend

995
00:53:48,239 --> 00:53:51,800
Speaker 1: and keep the conversation going. And again, thanks for listening.