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Speaker 1: Hello, They're happy Wednesday, and welcome to another episode of

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Speaker 1: the Chuck Podcast. No, I am not in my normal studio.

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Speaker 1: I'm coming to you from Midtown Manhattan, because sometimes New

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Speaker 1: York just comes a calling a little bit of work.

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Speaker 1: Was participating in a few different conferences that are taking

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Speaker 1: place in the lovely New York City area. In the

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Speaker 1: world of media and advertising and digital. I will say this,

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Speaker 1: it is fascinating to see in all of these in

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Speaker 1: these different entities, how everybody markets, how AI is a

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Speaker 1: part of their products. Right whether they have truly empowered

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Speaker 1: the actual AI is an open question in my book

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Speaker 1: on some of these entities that are pitching AI driven marketing,

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Speaker 1: AI driven buying, AI driven messaging. It feels as if

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Speaker 1: it's like the early days in the Internet when everybody

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Speaker 1: wanted to show off they had a website. Hey, we've

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Speaker 1: got a website www. Come to our website dot com. Right.

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Speaker 1: There is that feeling here where just say there's a

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Speaker 1: I even saw. I even saw a cleaning service now

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Speaker 1: advertising themselves as a tech specialty cleaning service. They know

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Speaker 1: how to clean in the highly you know, which is,

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Speaker 1: by the way, obviously something that maybe some companies would

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Speaker 1: care about. But essentially they're saying that you can, we

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Speaker 1: will help clean your data centers and show respect for

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Speaker 1: the equipment as we clean the data centers. We're experts

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Speaker 1: on that. So everybody trying to get the peace of this,

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Speaker 1: of this small, narrow, growing sector. We think it's a

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Speaker 1: growing sector of the economy. I think there's some concern

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Speaker 1: that it is a self eating it's sort of a

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Speaker 1: self feeding and self eating economic ecosystem that's being developed.

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Speaker 1: But there definitely seems to be just say, there's some

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Speaker 1: AI in it, and let's market it. Hey, whatever your

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Speaker 1: business is, claim it's AI driven. Welcome to my food truck,

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Speaker 1: AI driven taco recipes. Right. You can sort of feel

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Speaker 1: that shift as we transition in this economy. But look,

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Speaker 1: I've got my interview today is with one of the

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Speaker 1: probably smartest data guys inside the Democratic Party. His name's

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Speaker 1: Tom Bonyer. He is the former CEO of Target Smart,

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Speaker 1: the largest voter file company on the Blue side of

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Speaker 1: the Isle, and he primarily wanted to book him because

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Speaker 1: he basically confessed that he was wrong about the Democratic

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Speaker 1: Party's voter registration problem, that it indeed is a problem,

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Speaker 1: was a problem, and continues to be a problem, and

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Speaker 1: so we spend a little bit time doing a data

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Speaker 1: dive essentially on the Democratic Party's erosion over the years,

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Speaker 1: particularly over the last year. And I think for those

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Speaker 1: of you that are trying to figure out what's going

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Speaker 1: to happen to the loyal opposition on that side of

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Speaker 1: the aisle, I think this will be a fascinating conversation.

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Speaker 1: It is not all doom and gloom, but there's some

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Speaker 1: hard truths being spoken in the conversation, and I appreciate

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Speaker 1: mister Bonner's time and for accepting the premise of the

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Speaker 1: discussion that we had. But before I get to that,

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Speaker 1: it is Wednesday. So a few things that I do

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Speaker 1: try to keep up with on Wednesday's one is we'll

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Speaker 1: take a we'll dip our toes into the campaign twenty

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Speaker 1: twenty five twenty twenty six arena give you a few

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Speaker 1: updates there, including what's happening in the great State of Maine,

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Speaker 1: and then we'll have my top five list. My top

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Speaker 1: five list this week is top five political comebacks, and

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Speaker 1: I will get to more details on that when we

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Speaker 1: get to it. On the other side of the interview.

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Speaker 1: For those of you that listen to this podcast in

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Speaker 1: one and one giant download, and of course we will

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Speaker 1: have a little ass chuck. But it is also Wednesday,

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Speaker 1: which means my lead is going to be a bit

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Speaker 1: of a preview of my substack posts. So those of

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Speaker 1: you that do subscribe to my free substack, and as

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Speaker 1: you know, I am not trying to milk you for

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Speaker 1: a subscription on that. It is a free Thingfortunately or unfortunately,

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Speaker 1: if you're part of the world of substack and you

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Speaker 1: don't charge for your substack, the algorithm doesn't necessarily make

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Speaker 1: it easy to find your free substack. The algorithm favors

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Speaker 1: any substack that is going to make substack a couple

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Speaker 1: of bucks, as well as yourself. I totally love that

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Speaker 1: many people do that. I am not at all saying that.

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Speaker 1: I'm just telling you what I am trying to build

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Speaker 1: is something that is a bit more advertiser driven, advertisers supported,

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Speaker 1: so that we don't have any paywalls. I don't want

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Speaker 1: to have audience capture. I think that is a huge

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Speaker 1: problem in our media ecosystem, and so I do not

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Speaker 1: want to put myself in an audience capture situation. So

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Speaker 1: hopefully you have subscribed to my free substack. And if

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Speaker 1: substack has been a place where you've been a little

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Speaker 1: hesitant to go because there's this constant harassing of subscribing,

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Speaker 1: of paying money, I promise you I am not going

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Speaker 1: to be one of those one of those folks, And

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Speaker 1: I don't want to sound like I'm being dismissive of

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Speaker 1: those that do want subscription. I think you know. My

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Speaker 1: philosophy on this, for what it's worth, is that I

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Speaker 1: think civics journalism that is about the broader electorate everybody

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Speaker 1: ought to have access to that, Especially journalism I think

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Speaker 1: does can be behind a paywall. If you provide a

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Speaker 1: specialty expertise and you put some extra work into something

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Speaker 1: that is unique and proprietary on the data front or

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Speaker 1: on a specific issue or a topic, I think that

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Speaker 1: that's more than worthy of being behind a paywall. But

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Speaker 1: my focus is a little bit. It is a It

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Speaker 1: is a derivative of the shutdown showdown that we're in

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Speaker 1: the midst of right now, and I think the Democrats

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Speaker 1: have to figure out how to declare victory and get

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Speaker 1: out of this because I do think every day that

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Speaker 1: goes by now, look, I think they've gotten everything they

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Speaker 1: can hope to get out of this shutdown when you

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Speaker 1: are on the lower ground, right, and they have the

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Speaker 1: lower ground on this one because it's the Republicans that

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Speaker 1: propose the clean continuing resolution for just an additional six weeks.

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Speaker 1: So when you are choosing to do what the Democrats do,

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Speaker 1: you're doing it because you have a point to make,

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Speaker 1: and you're doing it because you're trying to bring some

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Speaker 1: attention to a specific issue. Right. You had Ted Cruz

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Speaker 1: shutting down the guver to try to bring more attention

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Speaker 1: to the implementation of Obamacare, for better or for worse

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Speaker 1: on that front, and on this case, I think you

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Speaker 1: have you had Donald Trump trying you know, he essentially

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Speaker 1: orchestrated the shutdown in nineteen and eighteen and nineteen in

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Speaker 1: order to bring more attention to his inability to get

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Speaker 1: his border wall funded at the time. So this one,

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Speaker 1: the Democrats say, is about healthcare and is about specifically

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Speaker 1: subsidies for the Affordable Care Act also known as Obamacare.

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Speaker 1: So I know I'm going to sound like a broken

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Speaker 1: record here. If that truly is the reason you're doing this,

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Speaker 1: declare victory and open the government. And the thing is

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Speaker 1: is that I do think you're going to see diminishing returns.

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Speaker 1: It's pretty clear that you're you know, and I do

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Speaker 1: think that this is This gets to the larger point

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Speaker 1: I'm talking about in my substack column this week, which

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Speaker 1: is how much energy do you to vote to opposing

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Speaker 1: Donald Trump versus how much energy do you devote to

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Speaker 1: opposing a future Donald Trump? What do I mean by that? Right?

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Speaker 1: There's mitigation tactics to deal with what you're dealing with

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Speaker 1: in the moment, and then there's longer term strategies to

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Speaker 1: essentially try to make sure we don't have another demagogue

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Speaker 1: hijack a political party in our process. Again, right, Donald

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Speaker 1: Trump's rise is exposed to extraordinary amounts of vulnerabilities, whether

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Speaker 1: it is the ability to enrich yourself while in office,

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Speaker 1: if it's the ability to weaponize political agencies. And this

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Speaker 1: is where it comes to if you look at what

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Speaker 1: they're doing with the government shutdown, one of the consistent patterns,

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Speaker 1: and we've all engaged in it in ways to try

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Speaker 1: to create guardrails around Trump, has been this assumption that

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Speaker 1: shame or political or sort of generic political pressure would

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Speaker 1: have a real impact. Shame has had no impact. In

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Speaker 1: fact that the incredible superpower Donald Trump has in some

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Speaker 1: ways is not feeling shame. The access Hollywood tape is

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Speaker 1: sort of the best piece of evidence of that that

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Speaker 1: you essentially never you know, January sixth is arguably the

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Speaker 1: next pest piece of evidence. Maybe you can flip the

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Speaker 1: two and what would normally shame almost any other politician

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Speaker 1: in our history, including one Richard Nixon shamed him into resignation,

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Speaker 1: does not work with him.

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Speaker 2: Right.

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Speaker 1: If you're hoping that touching the hot stove, which this

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Speaker 1: government shutdown is doing that Trump touching the hot stove

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Speaker 1: is going to burn his hand off. What if I

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Speaker 1: told you he didn't have the information? You know, there's

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Speaker 1: nothing in the feedback loop he is getting that tells

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Speaker 1: him his hand is burning. He feels no pain. Well,

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Speaker 1: he puts his hand on said hot stove. And so

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Speaker 1: if you're dealing with somebody essentially that's willing to shoot

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Speaker 1: the hostage, right in this case, just lay off more

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Speaker 1: federal government workers in the agencies that Democrats seem to

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Speaker 1: care more about than generically Republicans do. That blowback would

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Speaker 1: somehow bother him, right because swing voters don't like this

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Speaker 1: in either way. But if your feedback loop is all

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Speaker 1: about owning the Libs and pleasing your base. Well, then

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Speaker 1: he has no Then the incentives you think would work

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Speaker 1: under almost any other normal pre Trumpian circumstance doesn't work

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Speaker 1: in this scenario. But if you're if you look at

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Speaker 1: it through the prism. And this is something that I

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Speaker 1: think Democrats have had a hard time with for a

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Speaker 1: long time, which is learning how to declare victory even

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Speaker 1: if it's a one point victory, right, learning how to

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Speaker 1: embrace it. Donald Trump knows how to declare victory even

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Speaker 1: when he loses, literally on January sixth, But on even

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Speaker 1: on some issues he's somehow trying to declare victory in

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Speaker 1: using taxpayer dollars to bail out Argentina. And by the way,

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Speaker 1: he's made it a quid pro quo, essentially saying if

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Speaker 1: Argentina throws out Malay Hell, it will make an enemy

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Speaker 1: of the United States, yet another tast of our demagoguery

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Speaker 1: and another personalization of the presidency that erodes our ability

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Speaker 1: to be the moral authority on democracy around the world.

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Speaker 1: And we have lost all of our moral authority on

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Speaker 1: that front, and then some going back there. But sometimes

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Speaker 1: when you are frustrated by a situation you end up.

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Speaker 1: You know, you can get so frustrated. I've had similar situations.

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Speaker 1: It's been a long time since I've done this, but

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Speaker 1: I'm remember punching a hole in drywall once, so mad.

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Speaker 1: I punched a wall. I knew it was drywall. Put

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Speaker 1: a hole in it didn't make me feel any better.

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Speaker 1: For a moment, you think, Wow, I'm so strong, it's drywall. Please. Second,

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Speaker 1: I suddenly had to patch up a hole in my wall.

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Speaker 1: That was pain in the ass. Then I had to

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Speaker 1: repaint right then, of course you realize, oh, I can't

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Speaker 1: just paint the patch anyway. You see where I'm going.

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Speaker 1: It costs yourself a whole hell of a lot more

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Speaker 1: work sometimes when you just want to express frustration for

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Speaker 1: frustration's sake. And I think we're entering that situation. And

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Speaker 1: every day that goes by, that this shutdown goes, the

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Speaker 1: less it becomes about healthcare, and the more it becomes

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Speaker 1: about how the shutdown is impacting everyday lives, how it's

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Speaker 1: making Thanksgiving. You know, if we get to get close,

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Speaker 1: start getting close to Thanksgiving, travel, and we're keeping parents

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Speaker 1: from their kids, grandparents from their grandkids, that's not going

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Speaker 1: to help anybody. And again, the base of the Republican

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Speaker 1: Party is going to be a lot more comfortable feeling

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Speaker 1: their handget letting their hand burn up on the stove

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Speaker 1: than any part of the Democratic Party on this front.

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Speaker 1: And right now you've got healthcare into the forefront. You've

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Speaker 1: got Republicans talking amongst themselves like this is a real problem,

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Speaker 1: they've got to do something about it. You've got people

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Speaker 1: like Marjorie Taylor Green making the case for an expansion

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Speaker 1: or an extension of these healthcare subsidies. So you're winning

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Speaker 1: the argument. That's all you have the power to do

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Speaker 1: in this situation. You're not going to be able to

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Speaker 1: get them to do any more than that. But if

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Speaker 1: you're winning the argument, then you're likely to get the

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Speaker 1: legislation that you're hoping for. But more importantly, you're probably

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Speaker 1: not going to You've at least given yourself something to

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Speaker 1: run on if they fail to do this. But if

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Speaker 1: you continue to keep the government shut down thinking every day, boy,

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Speaker 1: you know, some of the stupid rhetoric that is leaked

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Speaker 1: out on the Democratic side, not a good look for

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Speaker 1: Chuck Schumer to basically imply, oh, every day this gets better,

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Speaker 1: it doesn't get better for the rest of us. It

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Speaker 1: may get better for your politics, but it's not getting

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Speaker 1: better for anybody else. For the government to be shut

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Speaker 1: down every day. If you're participating in the travel industry

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Speaker 1: by train or plane, you're dealing with the federal government,

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Speaker 1: and you're dealing with federal workers who have no promise

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Speaker 1: of a paycheck coming in on time. So be careful

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Speaker 1: of what words you're using there on that front. And

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Speaker 1: so at some point you got to ask yourself, what

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Speaker 1: is what is dragging this on longer? Hey, look, I

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Speaker 1: think we're Congressional Republican leaders know this, and then till

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Speaker 1: Donald Trump engages, Republicans aren't going to budget anything. So

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Speaker 1: what's your planning to get Donald Trump involved in these talks?

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Speaker 1: That's my That would be my question to Democrats. What's

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Speaker 1: your what's your If your goal is the healthcare subject,

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Speaker 1: You've got to get Donald Trump's attention. He's busy blowing

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Speaker 1: up votes with questionable legal authority. I would argue he

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Speaker 1: has yet to explain his legal authority on this, and

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Speaker 1: Congress has been crickets on this instead focused on the shutdown.

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Speaker 1: In some ways understandable but this is You know, the

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Speaker 1: Trump administration doesn't stop if you've shut down the government,

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Speaker 1: but apparently congressional oversight does. That's a problem. He's doing

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Speaker 1: his victory lap in the Middle East, where are he's

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Speaker 1: seen the first signs of his big victory Suddenly could

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Speaker 1: already backing off some of their guarantees, claiming Hamas is

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Speaker 1: backed off of some of their promises. You know, if

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Speaker 1: Trump wants this legacy achievement, the work is actually only

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Speaker 1: just begun. The hard work. The easy part was getting

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Speaker 1: the signing ceremony that he got. The hard part is

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Speaker 1: going to take a lot of handholding. That's going to

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Speaker 1: take a lot of intervention. That's going to take a

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Speaker 1: ton of work, and some of it is going to

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Speaker 1: take Trump himself intervening. Yet again, there's a reason results

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Speaker 1: matter more than promises, just like there's a reason Morgan

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Speaker 1: and Morgan is America's largest injury law firm. For the

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Speaker 1: last thirty five years, they've recovered twenty five bills million

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Speaker 1: dollars for more than half a million clients. It includes

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Speaker 1: cases where insurance companies offered next to nothing, just hoping

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Speaker 1: to get away with paying as little as possible. Morgan

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Speaker 1: and Morgan fought back ended up winning millions. In fact,

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Speaker 1: in Pennsylvania, one client was awarded twenty six million dollars,

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Speaker 1: which was a staggering forty times the amount that the

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Speaker 1: insurance company originally offered. That original offer six hundred and

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Speaker 1: fifty thousand dollars twenty six million, six hundred fifty thousand dollars.

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Speaker 1: So with more than one thousand lawyers across the country,

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Speaker 1: they know how to deliver for everyday people. If you're injured,

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Speaker 1: you need a lawyer, you need somebody to get your back.

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Speaker 1: Check out for the People dot com Slash podcast or

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Speaker 1: dial pound Law Pound five to nine law on your

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Speaker 1: cell phone. And remember all law firms are not the same.

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Speaker 1: So check out Morgan and Morgan. Their fee is free

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Speaker 1: unless they win. As you're looking at ways to you're

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Speaker 1: frustrated with this administration. If you're among those folks that are,

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Speaker 1: I imagine there's quite a few folks listening to this

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Speaker 1: podcast that are, I would just ask yourself what balance.

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Speaker 1: Are you striking here? What's more important trying to oppose

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Speaker 1: Trump in any way you can right now or trying

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Speaker 1: to prevent another Trump from happening in the future, because

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Speaker 1: we do have some long term, bigger adjustments that have

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Speaker 1: to be made. Take the idea of profiting off the presidency.

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Speaker 1: If this essentially goes unchecked, you know it's probably going

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Speaker 1: to go unpunished. But if it's going to go unchecked,

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Speaker 1: then you're only going to encourage other people to run

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Speaker 1: for office as a way to enrich themselves. That is

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Speaker 1: how you go from a political party being turned into

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Speaker 1: a kleptocracy, which Donald Trump has done to this current

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Speaker 1: Republican party. I mean, he's openly open about it, right

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Speaker 1: it is. It is everybody. Everything is a transaction. You

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Speaker 1: want to raise money with Donald Trump's likeness, pay the

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Speaker 1: man you want to beget in his good graces, give

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Speaker 1: him a plane. You want to make sure you get

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Speaker 1: what you want out of him, you better put his

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Speaker 1: face on a coin. The point is is that he

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Speaker 1: is already turned the party into a kleptocracy. If nothing

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Speaker 1: gets changed, we probably need a constitutional amendment because you're

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Speaker 1: not going to be able to force a future president

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Speaker 1: or a vice president to force them to put their

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Speaker 1: holdings in a blind trust to sort of enforce that mechanism.

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Speaker 1: Separation of powers prevents Congress from passing any such law

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Speaker 1: from pulling that off. So you're going to need a

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Speaker 1: constitutional amendment. It is crystal clear we need some sort

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Speaker 1: of constitutional men. The emolument's clause was not enough. It's

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Speaker 1: in there. If Congress chose to use it as a

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Speaker 1: way to provide some oversight, they could. But are we

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Speaker 1: impeaching this man a third time? Do we think the

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Speaker 1: impeachment process is really an effective process given how it's

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Speaker 1: at this point been turned into just some sort of

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Speaker 1: political gambit now that isn't taken very seriously, and that

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Speaker 1: politicians may not fear the way that they once that

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Speaker 1: Richard Nixon actually did fear it back in nineteen seventy four.

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Speaker 1: So it's pretty clear we need a constitutional movement. What

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Speaker 1: kind of work is being done to do that. We

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Speaker 1: do have a fusion of big tech money and government.

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Speaker 1: It is so infused. We have not had a relationship

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Speaker 1: between titans of industry and the government so intertwined since

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Speaker 1: the nineteen teens and twenties, since the age of the

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Speaker 1: robber Barons, teapot Dome all that. You know, the nineteen

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Speaker 1: twenties began with us losing our mind by banning alcohol

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Speaker 1: right after the nineteen eighteen pandemic, and it ends with

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Speaker 1: the stock market crash that essentially unravels the world economy

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Speaker 1: and plants the seeds for World War two. Other than that,

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Speaker 1: it was a terrific decade. Well, we have a similar

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Speaker 1: situation where we have industry and government extraordinarily intertwined that

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Speaker 1: again needs this is this is bigger than just opposing Trump.

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Speaker 1: This is a systemic problem that needs some sort of

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Speaker 1: constitutional intervention. I think on campaign finance that's pretty crystal clear.

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Speaker 1: And at some point the voters are going to demand

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Speaker 1: a regulatory our regulatory party parties to actually put some

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Speaker 1: sort of guardrails on big tech and how it exploits

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Speaker 1: or try to prevent it from exploiting the population for

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Speaker 1: either political gain or financial gain. So you look at

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Speaker 1: the different you know, I look at my role in journalism,

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Speaker 1: and I'm trying to focus on figuring out how can

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Speaker 1: we reanimate, rebuild, and create a better business model for

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Speaker 1: local media because I think that has become a foundational

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Speaker 1: problem in our in our broken information ecosystem. I think

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Speaker 1: there's so many facets here that need to be dealt with. Look,

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Speaker 1: we've got to, we've got to we're rigging our electoral lines.

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Speaker 1: This mad dash of the redistricting wars is actually we're

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Speaker 1: taking a step back from what was actually some momentum

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Speaker 1: and progress made to depoliticizing this process. Now we've essentially

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Speaker 1: scrapped the entire thing and almost are overpartisanizing it. Of course,

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Speaker 1: partisanship is how we got to such a polarized moment,

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Speaker 1: which essentially provided the blueprint for a guy like Trump

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Speaker 1: to exploit. So if you're hoping to prevent the next Trump,

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Speaker 1: you've got to figure out how deep polarize for number one,

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Speaker 1: nonpartisan redistricting. Oops, we are literally going backwards on this issue.

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Speaker 1: But this is something again that you could make a

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Speaker 1: constitutional amendment in some form or another, and I think

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Speaker 1: you're going to have to no law, no active Congress,

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Speaker 1: a political act of Congress is going to deal with

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Speaker 1: this in a way that I think would would be

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Speaker 1: treated fairly and not exploited for partisan gain. And then

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Speaker 1: the other is open primaries, and I think it's about

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Speaker 1: time to test the premise of whether taxpayer funded partisan

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Speaker 1: primaries are even legal, are constitutional. I think there needs

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Speaker 1: to be another look at this. But the fact is

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Speaker 1: we have to get rid of partisan primaries if we

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Speaker 1: want to be a functional democracy. If you don't want

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Speaker 1: us to be a functional democracy, then be my guest,

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Speaker 1: let's have more partisan primaries. But the idea that the

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Speaker 1: taxpayers can fund an election to decide who the head

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Speaker 1: of a private organization is seems you know again, I

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Speaker 1: guess I would apply it this way. Imagine any other

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Speaker 1: private club having taxpayer funded dollars being used by some

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Speaker 1: sort of private organization to decide how their leadership works

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Speaker 1: with sort of little with no say by those folks

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Speaker 1: that are paying those taxes. So I think under any

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Speaker 1: other circumstance, Supreme Court would say it was unconstitutional. I'm

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Speaker 1: trying to figure out how it's not for political parties,

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Speaker 1: and we have figure out how to depoliticize the Justice Department, right,

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Speaker 1: it is clearly vulnerable to politicizing and weaponization. And I

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Speaker 1: think you know, if you look at what happened in

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Speaker 1: the nineteen you know, three of our most important constitutional

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Speaker 1: men in the twentieth century, we're giving women the right

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Speaker 1: to vote, direct election to senators, and the income tax,

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Speaker 1: and in some ways all three of them were out

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Speaker 1: of this sort of we were growing close to being

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Speaker 1: very undemocratic, more undemocratic at the time, and we had

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Speaker 1: to come up, we had to actually add some constitutional

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Speaker 1: amendments to improve the democracy, to improve public's ability to

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Speaker 1: hold the democracy, and big business accountable as well. In fact,

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Speaker 1: the income tax was a part of that push. And

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Speaker 1: if you know, we're not quite repeating what happened in

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Speaker 1: the early part of the twentieth century, but boy, it

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Speaker 1: looks awfully familiar. And the response in that era was

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Speaker 1: some serious constitutional reform. And there's a lot more energy

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Speaker 1: right now on the laugh being focused solely on trying

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Speaker 1: to oppose a guy that may be in office only

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Speaker 1: two and a half more years that constitutionally, well, he'll

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Speaker 1: only be in office for two and a half more years. Look,

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Speaker 1: it doesn't mean you capitulate to Trump, right, you don't

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Speaker 1: do what these idiots in the corporate space have done

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Speaker 1: and in academia, and they've just folded right without actually

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Speaker 1: testing that the law was on their side. The law

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Speaker 1: on these media companies that have all capitulated and paid

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Speaker 1: these ridiculous ransoms. That's what they were. They were extortion,

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Speaker 1: was ransom. The law was under side and they chose

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Speaker 1: not to use the law. So that's capitulation. That's not mitigation.

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Speaker 1: Mitigation is filing suit, forcing his actions into the court,

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Speaker 1: getting overside hearings. But it's also looking ahead to make

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Speaker 1: sure how do we not get into this position again.

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Speaker 1: It's not just about rebuilding. Look, the Democratic Party has

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Speaker 1: got plenty of problems on their own, but the fact

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Speaker 1: is the country was vulnerable to this. Our institutions were

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Speaker 1: vulnerable to this politicizing, to this weaponization. We thought we

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Speaker 1: were operating on shame and norms, and we had many

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Speaker 1: a president abide by shame, who could be shamed and

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Speaker 1: would abide by norms. Donald Trump showed that if you

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Speaker 1: were shameless and you have a you have sort of

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Speaker 1: a a and you really are comfortable being that shameless

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Speaker 1: and he is again he's a guy that puts his

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Speaker 1: hand in the hot stove and does not feel pain.

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Speaker 1: Then you've got to build new guardrails. We've done it

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Speaker 1: before and we clearly need to do it again. So

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Speaker 1: that's the basis of my substack this week. I think

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Speaker 1: it fits pretty well here with theurrent situation with the shutdown,

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Speaker 1: and you know there is a point you know right now,

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Speaker 1: the fact that so many Democrats are desperately trying to

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Speaker 1: make the case that this shutdown strategy is working is

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Speaker 1: just the moment that you got to say, pull ripcord.

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Speaker 1: You've done enough, You've made your point, You've got it

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Speaker 1: out there, and now it is on them. They have

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Speaker 1: made this commitment in some ways. If they fail on this,

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Speaker 1: it hands you an easy to litigate issue in the

432
00:28:33,680 --> 00:28:38,480
Speaker 1: twenty twenty six elections. All right, speaking of twenty twenty six,

433
00:28:38,560 --> 00:28:43,760
Speaker 1: they have a few sort of a few campaign nuggets

434
00:28:44,160 --> 00:28:46,080
Speaker 1: to deal with. The biggest one, of course, is Maine.

435
00:28:46,560 --> 00:28:50,280
Speaker 1: We've been talking about Maine for quite some time. And

436
00:28:50,360 --> 00:28:53,280
Speaker 1: I do think that Janet Mills and Graham Platner now

437
00:28:53,320 --> 00:28:59,000
Speaker 1: are going to turn into a fascinating avatars for this

438
00:28:59,160 --> 00:29:03,320
Speaker 1: larger fight of old versus new in the Democratic Party.

439
00:29:03,320 --> 00:29:05,440
Speaker 1: I think this will be less about sort of left

440
00:29:05,520 --> 00:29:08,400
Speaker 1: versus right within the Democratic Party and more about old

441
00:29:08,480 --> 00:29:13,360
Speaker 1: versus new. Symbolically the Janet. You know the fact that

442
00:29:13,440 --> 00:29:17,800
Speaker 1: Chuck Schumer, but it's give me a second here to

443
00:29:17,880 --> 00:29:20,200
Speaker 1: check his age. I want to have this exactly right.

444
00:29:20,240 --> 00:29:22,240
Speaker 1: I think Chuck Schumer is seventy eight these days. But

445
00:29:22,760 --> 00:29:26,280
Speaker 1: excuse me, seventy four. Didn't mean to age him, Senator Schumer,

446
00:29:26,280 --> 00:29:30,440
Speaker 1: my apologies for aging give. But when seventy four year

447
00:29:30,480 --> 00:29:33,200
Speaker 1: old Chuck Schumer says, isn't this great that they've recruited

448
00:29:33,240 --> 00:29:37,280
Speaker 1: seventy seven year old Janet Mills for us sense? I

449
00:29:37,280 --> 00:29:41,200
Speaker 1: mean the fact that a party that has just dealt

450
00:29:41,240 --> 00:29:45,520
Speaker 1: with a ton of sort of age obstacles for their

451
00:29:45,600 --> 00:29:50,680
Speaker 1: rising stars. Right, Nancy Pelosi staying in office for year

452
00:29:50,800 --> 00:29:53,880
Speaker 1: after year after year after year, believing she alone is

453
00:29:53,880 --> 00:29:56,720
Speaker 1: the only one that could lead to Democrats. She was

454
00:29:56,720 --> 00:30:01,160
Speaker 1: a terrific leader for the House Democrats. They I assume

455
00:30:01,280 --> 00:30:06,160
Speaker 1: at some point house office building will feature her name.

456
00:30:06,200 --> 00:30:09,280
Speaker 1: The Pelosi House Office building is, I assume in the

457
00:30:09,360 --> 00:30:15,400
Speaker 1: work somewhere. She is deserving of lots of flowers. One

458
00:30:15,400 --> 00:30:19,760
Speaker 1: of the few people to lose a speakership, you know more,

459
00:30:19,920 --> 00:30:22,640
Speaker 1: not from inside her own party, but for losing control

460
00:30:22,680 --> 00:30:25,560
Speaker 1: and then coming back and getting the speaker'scavel back. That

461
00:30:25,600 --> 00:30:29,840
Speaker 1: doesn't happen often. It's happened before, but not often, and

462
00:30:29,920 --> 00:30:33,720
Speaker 1: so she certainly is historic in a number of ways,

463
00:30:33,720 --> 00:30:37,920
Speaker 1: including being the first woman Speaker of the House. But

464
00:30:38,400 --> 00:30:42,840
Speaker 1: this generation of leaders just is sticks and sticks and sticks.

465
00:30:44,640 --> 00:30:50,240
Speaker 1: And the fact that the Democrats, what the leadership of

466
00:30:50,320 --> 00:30:53,000
Speaker 1: the Democratic Party thinks is their best candidate is someone

467
00:30:53,040 --> 00:30:56,560
Speaker 1: who's five years older than the current incumbent, who's been

468
00:30:56,600 --> 00:31:02,600
Speaker 1: in office since the end of the twentieth sire seems

469
00:31:02,600 --> 00:31:06,000
Speaker 1: like they're giving up their best. The best case against

470
00:31:06,080 --> 00:31:08,800
Speaker 1: Susan Collins is she's been in office too long, and

471
00:31:08,840 --> 00:31:11,560
Speaker 1: she's been there too long. How is it that the

472
00:31:11,600 --> 00:31:16,000
Speaker 1: best that the leadership of the Democratic Party thinks the

473
00:31:16,040 --> 00:31:18,680
Speaker 1: best person to knock off an incumbent like that is

474
00:31:18,720 --> 00:31:24,840
Speaker 1: somebody who's one older and two a current statewide elected official.

475
00:31:28,880 --> 00:31:31,880
Speaker 1: I think this is going to be an extraordinarily fascinating

476
00:31:32,480 --> 00:31:38,960
Speaker 1: primary in some ways, the primary maybe maybe more have

477
00:31:39,080 --> 00:31:41,560
Speaker 1: more fireworks in it than the eventual general election. Look,

478
00:31:41,600 --> 00:31:44,560
Speaker 1: I think Susan Collins is in trouble regardless who she faces.

479
00:31:44,920 --> 00:31:47,560
Speaker 1: But I'll tell you this, when you're in an anti

480
00:31:47,600 --> 00:31:50,440
Speaker 1: incumbent environment, you don't want to be holding a holding

481
00:31:50,480 --> 00:31:52,560
Speaker 1: a major office while you're trying to run as any

482
00:31:52,960 --> 00:31:56,000
Speaker 1: you know, Like, I think this is a huge problem

483
00:31:56,040 --> 00:32:01,080
Speaker 1: for shared Brown in Ohio. He is the checker who

484
00:32:01,080 --> 00:32:04,960
Speaker 1: has been in office longer than the guy he's running against. Right,

485
00:32:05,600 --> 00:32:09,360
Speaker 1: and in the type of election where in some ways

486
00:32:09,360 --> 00:32:14,520
Speaker 1: you're trying you're as a party as a whole, you're

487
00:32:14,560 --> 00:32:19,520
Speaker 1: trying to elect new to replace old. And yet two

488
00:32:19,560 --> 00:32:26,120
Speaker 1: of their biggest recruits are folks in their seventies. And

489
00:32:26,120 --> 00:32:30,240
Speaker 1: if Janet Mills wins, she'll be the oldest freshman elected

490
00:32:30,280 --> 00:32:35,440
Speaker 1: senator ever. It's just after the Democrats featured the oldest

491
00:32:35,520 --> 00:32:39,760
Speaker 1: elected president ever. Of course, Donald Trump's going to break

492
00:32:39,800 --> 00:32:44,200
Speaker 1: that record by replacing with this, by replacing Joe Biden

493
00:32:44,240 --> 00:32:50,400
Speaker 1: on that one. But it's fat and for what it's worth,

494
00:32:50,600 --> 00:32:55,600
Speaker 1: with her first day in office, and you already have

495
00:32:58,240 --> 00:33:02,360
Speaker 1: the first attack ad on Janet Mills from Graham Plattin

496
00:33:02,440 --> 00:33:05,080
Speaker 1: or the Oyster Farmer. I know, I finally learned his

497
00:33:05,120 --> 00:33:06,760
Speaker 1: first and last name. For those of you that been

498
00:33:06,840 --> 00:33:10,880
Speaker 1: keep keeping track. Here here's what the ad does. A

499
00:33:10,960 --> 00:33:13,719
Speaker 1: woman in the spot itself, so it's not the candidate

500
00:33:13,800 --> 00:33:16,440
Speaker 1: detecting Janet Mills by name, but in the spot, a

501
00:33:16,520 --> 00:33:18,840
Speaker 1: woman in the spot says, Janet Mills again, she was

502
00:33:18,840 --> 00:33:21,760
Speaker 1: a good governor, but I think it's time for a change,

503
00:33:23,160 --> 00:33:25,640
Speaker 1: So welcome to what I think is now a new

504
00:33:25,720 --> 00:33:30,400
Speaker 1: Democratic Party headache. This is not recruiting Roy Cooper in

505
00:33:30,400 --> 00:33:33,000
Speaker 1: North Carolina, and frankly, it's not even recruiting Shared Brown

506
00:33:33,000 --> 00:33:35,880
Speaker 1: in Ohio because you could argue that Shared Brown was

507
00:33:37,280 --> 00:33:39,040
Speaker 1: I'm torn at his race. I think he is the

508
00:33:39,040 --> 00:33:42,600
Speaker 1: best possible candidate they could get in this moment who

509
00:33:42,600 --> 00:33:45,400
Speaker 1: could raise him, and he rose raised a big chunk

510
00:33:45,440 --> 00:33:48,760
Speaker 1: of money. The question is whether the Democratic Party is

511
00:33:48,800 --> 00:33:51,160
Speaker 1: going to support him. They didn't really help him out

512
00:33:51,240 --> 00:33:53,760
Speaker 1: of his jam as much two years ago. He was

513
00:33:54,240 --> 00:33:58,360
Speaker 1: very frustrated, particularly on the trans issue, how little backup

514
00:33:58,400 --> 00:34:00,960
Speaker 1: he got from the national Party to help him out

515
00:34:01,000 --> 00:34:04,600
Speaker 1: on that race. On this one, this is going to

516
00:34:04,600 --> 00:34:07,520
Speaker 1: become a massive primary headache. There's going to be a

517
00:34:07,560 --> 00:34:11,560
Speaker 1: massive amount of money spent in the primary that arguably

518
00:34:11,640 --> 00:34:14,880
Speaker 1: might be better suited for the general election.

519
00:34:16,760 --> 00:34:17,400
Speaker 2: But we'll see.

520
00:34:17,480 --> 00:34:20,719
Speaker 1: Look, the one thing, and this was the subject of

521
00:34:20,719 --> 00:34:23,360
Speaker 1: my substec last week, one thing we learned is that

522
00:34:24,000 --> 00:34:27,719
Speaker 1: nobody you know, if a King Jeffries or somebody who's

523
00:34:27,760 --> 00:34:30,400
Speaker 1: threatened you as a local candidate in the name of

524
00:34:30,440 --> 00:34:33,480
Speaker 1: aking Jeffries or Chuck Schumer by saying the National Party's

525
00:34:33,520 --> 00:34:36,279
Speaker 1: not going to support you. Is anybody going to take

526
00:34:36,320 --> 00:34:40,840
Speaker 1: them seriously? I mean, Graham Platner, are you really not

527
00:34:41,000 --> 00:34:43,240
Speaker 1: going to help his candidacy if he wins the primary

528
00:34:43,280 --> 00:34:46,400
Speaker 1: and knocks off a sitting governor and a Democratic primary.

529
00:34:48,040 --> 00:34:51,560
Speaker 1: He's not going to take those threats seriously because what

530
00:34:51,640 --> 00:34:53,880
Speaker 1: other states do you have on the board, Chuck Schumer

531
00:34:53,960 --> 00:34:57,640
Speaker 1: that you can target? And look, you know, I get it.

532
00:34:57,760 --> 00:35:04,480
Speaker 1: Governors in general are ritible fundraisers, and certainly in a

533
00:35:04,560 --> 00:35:06,920
Speaker 1: larger state like North Carolina, make a lot of sense

534
00:35:08,320 --> 00:35:12,359
Speaker 1: in this This is one of those unique cases where

535
00:35:12,360 --> 00:35:14,360
Speaker 1: it may not make the sense you think it makes

536
00:35:14,760 --> 00:35:17,480
Speaker 1: on this front. Don't get me wrong. There's a lot

537
00:35:17,480 --> 00:35:22,560
Speaker 1: of smart people in and around Schumer world. I've known JB.

538
00:35:22,640 --> 00:35:24,840
Speaker 1: Push a long time, and I know the case he

539
00:35:24,880 --> 00:35:27,400
Speaker 1: would make to me on this one about oh, you

540
00:35:27,400 --> 00:35:31,000
Speaker 1: don't understand sitting governor's Chuck, I understand, I get it,

541
00:35:31,640 --> 00:35:34,000
Speaker 1: I get it. I do think you guys have adopted

542
00:35:34,040 --> 00:35:40,400
Speaker 1: yourself quite the headache, and it may be a headache

543
00:35:40,600 --> 00:35:45,200
Speaker 1: you're going to wish you didn't acquire some six to

544
00:35:45,280 --> 00:35:50,319
Speaker 1: eight months eight months from now. All right with that,

545
00:35:51,040 --> 00:35:53,600
Speaker 1: I will leave the campaign trail. There's actually a lot

546
00:35:53,600 --> 00:35:55,000
Speaker 1: more I want to get on, but hey, I've gone

547
00:35:55,320 --> 00:35:57,680
Speaker 1: a good thirty seven minutes here before the interview, and

548
00:35:57,719 --> 00:36:00,960
Speaker 1: I actually think in some case is if you're in

549
00:36:00,960 --> 00:36:04,400
Speaker 1: a campaign mood and you want to talk more campaign

550
00:36:04,440 --> 00:36:07,440
Speaker 1: twenty twenty six, twenty eight, then you're really going to

551
00:36:07,480 --> 00:36:11,400
Speaker 1: enjoy this interview with Tom Bonnier. And so with that,

552
00:36:11,719 --> 00:36:13,680
Speaker 1: let's sneak in a break and I'll see on the

553
00:36:13,719 --> 00:36:16,120
Speaker 1: other side with my top five list and a little

554
00:36:16,160 --> 00:36:30,160
Speaker 1: last chuck. So one of the topics I've certainly brought

555
00:36:30,239 --> 00:36:32,319
Speaker 1: up quite a few times has to do with just

556
00:36:32,440 --> 00:36:35,640
Speaker 1: simply democratic voter registration, and it has been in a

557
00:36:35,800 --> 00:36:44,600
Speaker 1: consistent downward trend, arguably now for five years. And what's

558
00:36:44,640 --> 00:36:49,279
Speaker 1: been a head scratcher has been the sort of at

559
00:36:49,360 --> 00:36:51,799
Speaker 1: times what has appeared as a lack of urgency among

560
00:36:51,920 --> 00:36:56,040
Speaker 1: some party leaders about this trend line registration. And it

561
00:36:56,160 --> 00:36:59,920
Speaker 1: turned out that what the Republicans did starting in arguably

562
00:37:00,120 --> 00:37:02,640
Speaker 1: for the twenty twenty election. But certainly, and maybe this

563
00:37:02,719 --> 00:37:05,000
Speaker 1: is about COVID, and with my guest here we're going

564
00:37:05,040 --> 00:37:06,600
Speaker 1: to talk about that a little bit, is how much

565
00:37:06,920 --> 00:37:11,400
Speaker 1: how much this initial setback was during COVID when the

566
00:37:11,440 --> 00:37:15,160
Speaker 1: Republicans were more comfortable doing in person than the Democrats were.

567
00:37:15,680 --> 00:37:18,360
Speaker 1: But the fact is we're here. There was one I

568
00:37:18,400 --> 00:37:20,480
Speaker 1: believe the folks of our decision desk put out a

569
00:37:20,480 --> 00:37:23,040
Speaker 1: stat that should I think that the last year, Democrats

570
00:37:23,040 --> 00:37:25,839
Speaker 1: have lost a million registered voters. Among the states that

571
00:37:25,960 --> 00:37:29,160
Speaker 1: keep track of that, Republicans have lost about one hundred thousand.

572
00:37:29,680 --> 00:37:33,279
Speaker 1: And of course, no party or independent, whatever the delineation

573
00:37:33,480 --> 00:37:36,279
Speaker 1: is by state, is where all these extra voters have come.

574
00:37:36,560 --> 00:37:39,600
Speaker 1: Tom Bonyer is a longtime Democratic strategist, former CEO of

575
00:37:39,640 --> 00:37:42,760
Speaker 1: Target Smart, the sort of the chief voter file company

576
00:37:43,560 --> 00:37:47,040
Speaker 1: for Team Blue these days. When I was at NBC,

577
00:37:47,080 --> 00:37:49,680
Speaker 1: we actually worked with Target Smart as well, and in

578
00:37:49,680 --> 00:37:53,080
Speaker 1: fact RNBC poll combines Target Smart work with one of

579
00:37:53,080 --> 00:37:56,759
Speaker 1: the key voter file companies on the on Team Red

580
00:37:57,840 --> 00:38:00,000
Speaker 1: and Tom Bonier, in a New York Times interview, goes, hey,

581
00:38:00,960 --> 00:38:03,600
Speaker 1: I was dismissive of these voter registration numbers, and I

582
00:38:03,760 --> 00:38:06,919
Speaker 1: was wrong. He's here today to talk more about that. Tim,

583
00:38:06,960 --> 00:38:10,160
Speaker 1: Good to see you, Good to be here. So let's

584
00:38:10,160 --> 00:38:15,719
Speaker 1: start with this. Where did this begin? Because for essentially

585
00:38:15,800 --> 00:38:20,320
Speaker 1: the first fifteen years of this century, Democrats were making

586
00:38:20,480 --> 00:38:25,480
Speaker 1: the registration progress right Barack Obama's campaign and sort of

587
00:38:25,520 --> 00:38:28,000
Speaker 1: the success of its administration. And that's sort of a

588
00:38:28,080 --> 00:38:30,000
Speaker 1: if you look at an overall fifty year trend, if

589
00:38:30,040 --> 00:38:32,919
Speaker 1: you have a two term president, it does usually help

590
00:38:33,000 --> 00:38:37,680
Speaker 1: your party in the voter registration column. But they hit

591
00:38:37,719 --> 00:38:40,560
Speaker 1: a wall somewhere, and the question was why did it happen?

592
00:38:40,880 --> 00:38:44,680
Speaker 1: It started with COVID, But where has it gone and

593
00:38:44,840 --> 00:38:46,960
Speaker 1: how have you come to the conclusion that this turned

594
00:38:47,000 --> 00:38:49,840
Speaker 1: out to be something we should have focused more on.

595
00:38:50,440 --> 00:38:53,040
Speaker 3: Yeah, I mean you could actually even put the start

596
00:38:53,040 --> 00:38:57,399
Speaker 3: of it even further back, potentially to seventeen when you

597
00:38:57,520 --> 00:39:00,919
Speaker 3: saw now it had a different impact at that point

598
00:39:00,920 --> 00:39:05,160
Speaker 3: in terms of Trump's first term, but the Democratic Party

599
00:39:05,320 --> 00:39:10,840
Speaker 3: brand after the Bernie Clinton primary wasn't great, and so

600
00:39:10,880 --> 00:39:13,680
Speaker 3: what you saw at that point, starting in twenty seventeen

601
00:39:13,719 --> 00:39:18,759
Speaker 3: and going forward was fewer people registering or identifying as Democrats,

602
00:39:18,880 --> 00:39:21,560
Speaker 3: but it wasn't really impacting the vote at that point.

603
00:39:21,640 --> 00:39:24,319
Speaker 3: Because of the negative reaction to Trump's first term. There

604
00:39:24,360 --> 00:39:27,279
Speaker 3: was a lot of enthusiasm, especially among younger voters going

605
00:39:27,320 --> 00:39:30,880
Speaker 3: into the twenty eighteen midterms, So these voters were registering

606
00:39:30,920 --> 00:39:35,319
Speaker 3: as unaffiliated voters but were still voting for Democrats. And

607
00:39:35,360 --> 00:39:38,400
Speaker 3: so you're right, it was more around the pandemic in

608
00:39:38,400 --> 00:39:43,040
Speaker 3: twenty twenty, where initially you saw a bigger drop in

609
00:39:43,120 --> 00:39:45,640
Speaker 3: terms of the percent of registered voters and states of

610
00:39:45,760 --> 00:39:48,200
Speaker 3: partisan registration, which is more than half the states, and

611
00:39:48,200 --> 00:39:50,600
Speaker 3: it's a very diverse sample of states in terms of

612
00:39:50,680 --> 00:39:54,480
Speaker 3: red states, blue states, purple states. You saw that number

613
00:39:54,920 --> 00:39:58,960
Speaker 3: dropping even more. But it was spikey then because you

614
00:39:59,000 --> 00:40:03,680
Speaker 3: remember the Black Lives Matter movement, and after George Floyd's murder,

615
00:40:04,360 --> 00:40:09,160
Speaker 3: you saw where there was more organizing happened generally driven

616
00:40:09,200 --> 00:40:12,080
Speaker 3: by that movement. You did see some more spikes and

617
00:40:12,160 --> 00:40:17,319
Speaker 3: Democratic registration leading into that election. So if you want

618
00:40:17,320 --> 00:40:20,279
Speaker 3: to see where it really went south for Democrats was

619
00:40:20,360 --> 00:40:26,439
Speaker 3: generally just during that four year period of President Biden's presidency,

620
00:40:26,680 --> 00:40:30,040
Speaker 3: where it followed the polling numbers again, the Democratic Party

621
00:40:30,040 --> 00:40:34,200
Speaker 3: brand was heading south. And what we saw, and you

622
00:40:34,280 --> 00:40:36,239
Speaker 3: mentioned that quote I have in the New York Times

623
00:40:36,280 --> 00:40:39,520
Speaker 3: about being wrong, what I was very specifically wrong about

624
00:40:39,800 --> 00:40:43,319
Speaker 3: was this calculation that will make it's okay maybe that

625
00:40:43,480 --> 00:40:46,120
Speaker 3: you know, what we saw during Trump's first term is

626
00:40:46,160 --> 00:40:49,200
Speaker 3: something we would see repeated that while fewer people were

627
00:40:49,200 --> 00:40:53,560
Speaker 3: identifying with the party or registering more importantly with the party.

628
00:40:54,040 --> 00:40:55,279
Speaker 2: That you looked at.

629
00:40:55,160 --> 00:40:58,680
Speaker 3: These unaffiliated voters and they looked more like Democratic voters,

630
00:40:58,719 --> 00:41:02,040
Speaker 3: meaning they were they were more women than men, they

631
00:41:02,040 --> 00:41:05,640
Speaker 3: were color and in the end that didn't bear out.

632
00:41:05,680 --> 00:41:09,520
Speaker 3: These are exactly the voters that President Trump over performed with.

633
00:41:10,080 --> 00:41:13,839
Speaker 1: Right, here's election. So let's start with the just the

634
00:41:13,880 --> 00:41:17,360
Speaker 1: mechanics of voter registration. You know, you could argue that

635
00:41:17,400 --> 00:41:22,279
Speaker 1: a political party has one job get members, right like that. Ultimately,

636
00:41:23,000 --> 00:41:25,719
Speaker 1: you have one job in a particularly if you run

637
00:41:25,760 --> 00:41:28,320
Speaker 1: a county party or a state party. You know, a

638
00:41:28,400 --> 00:41:31,080
Speaker 1: national party, you could argue is sort of in some

639
00:41:31,120 --> 00:41:34,200
Speaker 1: ways making sure you have healthy chapters right all over

640
00:41:34,239 --> 00:41:36,640
Speaker 1: the country. But certainly on a state and local level,

641
00:41:36,640 --> 00:41:39,400
Speaker 1: you have one job. I'm a Floridian, a former Floridian,

642
00:41:39,440 --> 00:41:42,279
Speaker 1: and I you know, I always I have marveled at

643
00:41:42,280 --> 00:41:46,279
Speaker 1: the incompetency of the state Democratic Party because it's the

644
00:41:46,400 --> 00:41:50,400
Speaker 1: voters have performed better. Right for the longest time, Democrats

645
00:41:50,480 --> 00:41:53,600
Speaker 1: used to overperform their organization. And it would be one

646
00:41:53,600 --> 00:41:55,120
Speaker 1: of those things, Boy, if you ever actually spent some

647
00:41:55,160 --> 00:41:58,439
Speaker 1: money on organization, this could happen. And then everything went

648
00:41:58,680 --> 00:42:04,200
Speaker 1: in the reverse, and the Republicans just simply made a

649
00:42:04,200 --> 00:42:07,920
Speaker 1: concerted effort at register voters and the Democratic Party didn't.

650
00:42:08,120 --> 00:42:11,879
Speaker 1: And I've never what is in the you know, why

651
00:42:11,960 --> 00:42:16,319
Speaker 1: isn't this first and foremost? Why do Democrats outsource this

652
00:42:16,520 --> 00:42:18,759
Speaker 1: more it appears than the Republicans do.

653
00:42:19,360 --> 00:42:22,600
Speaker 3: Yeah, well, this is a complicated one, and you hit

654
00:42:22,640 --> 00:42:25,279
Speaker 3: on some of the key elements of this. And Democrats

655
00:42:25,320 --> 00:42:28,520
Speaker 3: have invested in voter registration to your point, generally not

656
00:42:29,080 --> 00:42:32,040
Speaker 3: through the party. There are some reasons just in terms

657
00:42:32,080 --> 00:42:33,680
Speaker 3: of the type of money you can spend. For the

658
00:42:33,719 --> 00:42:38,000
Speaker 3: longest time, Democrats had organizations like Acorn no longer that

659
00:42:38,040 --> 00:42:41,719
Speaker 3: were very successful in registering voters. It's all they did, right,

660
00:42:42,000 --> 00:42:44,600
Speaker 3: They had one job. Right, it's non partisan work. So

661
00:42:44,680 --> 00:42:48,280
Speaker 3: what that generally means or overwhelmingly non partisan work, meaning.

662
00:42:48,080 --> 00:42:52,920
Speaker 1: The least partisan work is in legal terms, it's non partisan.

663
00:42:52,600 --> 00:42:55,560
Speaker 3: Right, So five O one C three Generally a lot

664
00:42:55,560 --> 00:42:57,800
Speaker 3: of these organizations are registered as five O one C

665
00:42:57,920 --> 00:43:01,480
Speaker 3: threes or five to one C fours, meaning that they can't

666
00:43:01,480 --> 00:43:04,280
Speaker 3: go out and say, you know, are you a Democrat

667
00:43:04,360 --> 00:43:06,839
Speaker 3: or a Republican and then only register the Democrats. It's

668
00:43:06,840 --> 00:43:10,800
Speaker 3: not partisan registration, so they would register people based on demographics,

669
00:43:10,840 --> 00:43:13,400
Speaker 3: so they would go to college campuses, they would go

670
00:43:14,040 --> 00:43:15,600
Speaker 3: two neighborhoods.

671
00:43:14,960 --> 00:43:17,520
Speaker 1: Where you know, you would get a larger share of

672
00:43:17,520 --> 00:43:20,080
Speaker 1: who you're registering. But it's not like they wouldn't register

673
00:43:20,160 --> 00:43:22,320
Speaker 1: somebody that wanted to be a Republican, a libertarian or

674
00:43:22,400 --> 00:43:23,120
Speaker 1: green part whatever.

675
00:43:23,400 --> 00:43:25,680
Speaker 3: It was simple math that if you were getting more

676
00:43:25,719 --> 00:43:30,120
Speaker 3: people on one side than another, it generally worked out fine.

677
00:43:30,160 --> 00:43:32,880
Speaker 3: And again that was something that worked well for Democrats.

678
00:43:32,920 --> 00:43:34,920
Speaker 3: And again it was this calculus that well, in the end,

679
00:43:34,920 --> 00:43:38,239
Speaker 3: it doesn't matter if they self identify or identifying that

680
00:43:38,320 --> 00:43:41,200
Speaker 3: voter registration card as a Democrat, as long as they're

681
00:43:41,320 --> 00:43:45,080
Speaker 3: voting for and with the party. And for the longest time,

682
00:43:45,280 --> 00:43:48,640
Speaker 3: that was a calculus that was okay. And you know,

683
00:43:48,640 --> 00:43:50,080
Speaker 3: I should point out even when you look at the

684
00:43:50,160 --> 00:43:54,759
Speaker 3: last four years or even last year, there were democratic

685
00:43:54,880 --> 00:43:59,400
Speaker 3: or progressive entities that they'd overwhelmingly nonpartisan voter registration that

686
00:43:59,480 --> 00:44:03,640
Speaker 3: were still getting results. But the problem was with the

687
00:44:03,719 --> 00:44:06,440
Speaker 3: lack of the partisan element, with a lack of investment

688
00:44:06,560 --> 00:44:11,799
Speaker 3: in partisan voter registration, the margins weren't nearly where they

689
00:44:11,840 --> 00:44:15,239
Speaker 3: were in the past. And what's striking to me if

690
00:44:15,280 --> 00:44:17,719
Speaker 3: you want to look at the impact of this, I

691
00:44:17,760 --> 00:44:20,600
Speaker 3: looked at turnout just in terms of partisan registration across

692
00:44:20,640 --> 00:44:23,200
Speaker 3: the battleground states. Now four of the seven battleground states

693
00:44:23,320 --> 00:44:25,880
Speaker 3: offer partisan registration, so it's not all of them, but

694
00:44:26,000 --> 00:44:29,880
Speaker 3: again a pretty good sample the differential on turnout. If

695
00:44:29,920 --> 00:44:33,080
Speaker 3: you compare twenty twenty where Joe Biden won in twenty

696
00:44:33,120 --> 00:44:36,760
Speaker 3: twenty four where Donald Trump won, the differential on turnout

697
00:44:36,800 --> 00:44:40,040
Speaker 3: between Democrats and Republicans twenty twenty four to twenty twenty

698
00:44:40,120 --> 00:44:45,160
Speaker 3: was less than a point. I mean, the swing was minimal,

699
00:44:45,640 --> 00:44:49,279
Speaker 3: but the deciding factor and why the result ended up

700
00:44:49,320 --> 00:44:52,920
Speaker 3: being this landslide from an electoral college perspective for Donald

701
00:44:52,960 --> 00:44:56,400
Speaker 3: Trump was because there were just so many more registered

702
00:44:56,400 --> 00:44:59,120
Speaker 3: Republicans in twenty twenty four and fewer To the point

703
00:44:59,160 --> 00:45:01,840
Speaker 3: you made earlier, it wasn't just that the Democratic numbers

704
00:45:01,840 --> 00:45:05,080
Speaker 3: were stagnant. There were actually fewer registered Democrats. So Democrats

705
00:45:05,120 --> 00:45:07,680
Speaker 3: going into the selection in order to win would have

706
00:45:07,760 --> 00:45:11,640
Speaker 3: had to have gotten higher turnout among partisan Democrats than

707
00:45:11,640 --> 00:45:14,840
Speaker 3: they got in twenty twenty, which was almost impossible. And

708
00:45:14,880 --> 00:45:17,520
Speaker 3: we think that twenty twenty have records setting turnout and

709
00:45:17,560 --> 00:45:20,560
Speaker 3: Democrats did quite well in turnout. For Vice President Harris

710
00:45:20,600 --> 00:45:24,200
Speaker 3: to accomplish that would have been incredibly difficult.

711
00:45:24,440 --> 00:45:28,080
Speaker 1: Have you examined the Republican tactics and because they do

712
00:45:28,120 --> 00:45:31,279
Speaker 1: it more in a more partisan basis than the Democratic side,

713
00:45:31,320 --> 00:45:32,400
Speaker 1: is there something to be learned?

714
00:45:32,840 --> 00:45:36,600
Speaker 3: Yeah, I mean to the extent that I'm you know,

715
00:45:37,120 --> 00:45:39,360
Speaker 3: can dig into it, and that it's out there and

716
00:45:39,400 --> 00:45:40,960
Speaker 3: a lot of it he is out there in the public.

717
00:45:41,000 --> 00:45:44,400
Speaker 3: I think they've been very proud of what they especially

718
00:45:44,400 --> 00:45:46,680
Speaker 3: in states like Pennsylvania.

719
00:45:45,840 --> 00:45:48,760
Speaker 1: They work. Look, arguably, it is all they thought about

720
00:45:48,960 --> 00:45:53,160
Speaker 1: starting in twenty seventeen was we can't you know, it

721
00:45:53,200 --> 00:45:55,719
Speaker 1: was like it reminded me of Karl Rove after two thousand. Hey,

722
00:45:55,719 --> 00:45:58,160
Speaker 1: I don't want to have a margin like that again.

723
00:45:59,560 --> 00:46:03,040
Speaker 1: Let's try to improve in all of these key battleground states.

724
00:46:03,080 --> 00:46:05,920
Speaker 1: And back then it was Florida and Ohio. This time

725
00:46:06,360 --> 00:46:09,880
Speaker 1: it was it was the Big three, but particularly with Pennsylvania.

726
00:46:09,960 --> 00:46:10,480
Speaker 2: Well, that's right.

727
00:46:10,520 --> 00:46:12,480
Speaker 3: I mean when you look at their post mortem after

728
00:46:12,520 --> 00:46:14,279
Speaker 3: the twenty twelve election, where they said, look, we're not

729
00:46:14,320 --> 00:46:17,200
Speaker 3: going to win another national election if we continue to

730
00:46:17,280 --> 00:46:20,520
Speaker 3: do as poorly as we do with these emerging demographics,

731
00:46:20,560 --> 00:46:23,880
Speaker 3: especially younger voters, and then they didn't really do anything

732
00:46:23,920 --> 00:46:24,399
Speaker 3: about it.

733
00:46:25,000 --> 00:46:27,520
Speaker 1: Ironically, the autopsy was right, they just didn't know Donald

734
00:46:27,520 --> 00:46:29,440
Speaker 1: Trump was the answer, so that was going to win

735
00:46:29,480 --> 00:46:31,400
Speaker 1: him over at more diverse I mean, it is a

736
00:46:31,400 --> 00:46:35,040
Speaker 1: strange thing. Now. I did mean to sort of interrupt

737
00:46:35,040 --> 00:46:37,080
Speaker 1: your trade of thought, but I've thought about that autopsy.

738
00:46:37,320 --> 00:46:40,000
Speaker 1: So were they right? It just they were wrong about

739
00:46:40,000 --> 00:46:42,360
Speaker 1: who the right person was. I mean, you know anyway,

740
00:46:42,440 --> 00:46:43,840
Speaker 1: but I do, but I digress.

741
00:46:43,920 --> 00:46:45,680
Speaker 2: Just at the time, I don't think nor would they.

742
00:46:45,600 --> 00:46:47,399
Speaker 1: Don't think that's what right three percent in mind?

743
00:46:47,440 --> 00:46:49,279
Speaker 2: No, oh no, no, certainly not.

744
00:46:49,840 --> 00:46:52,359
Speaker 3: And so when you look at their actual tactics now,

745
00:46:52,960 --> 00:46:55,480
Speaker 3: a lot of it looks a lot like what Democrats

746
00:46:55,480 --> 00:46:59,160
Speaker 3: were doing again a decade ago, two decades ago, especially

747
00:46:59,400 --> 00:47:01,799
Speaker 3: you know, the sixcessful efforts of the Obama campaign. We

748
00:47:01,840 --> 00:47:05,040
Speaker 3: have to remember that the Obama campaign in two thousand

749
00:47:05,040 --> 00:47:08,680
Speaker 3: and eight, they're organizing with younger voters with something A

750
00:47:08,719 --> 00:47:10,080
Speaker 3: lot of people looked at it and said, well, look,

751
00:47:10,120 --> 00:47:12,759
Speaker 3: these younger voters don't vote, even especially not in presidential

752
00:47:12,760 --> 00:47:16,839
Speaker 3: primary elections, and that campaign saw an opportunity there and

753
00:47:16,960 --> 00:47:19,759
Speaker 3: they put not only their candidate there, but their resources

754
00:47:19,960 --> 00:47:23,719
Speaker 3: organizing on college campuses. It's arguably what won them the

755
00:47:23,760 --> 00:47:27,319
Speaker 3: primary and then carried through to the general election. And

756
00:47:27,600 --> 00:47:30,080
Speaker 3: Republicans in a lot of ways followed that model where

757
00:47:30,120 --> 00:47:33,600
Speaker 3: they just had a presence on college campuses that generally

758
00:47:33,640 --> 00:47:37,839
Speaker 3: would be thought of as quite hostile but for Republican

759
00:47:38,760 --> 00:47:42,360
Speaker 3: or Republican electives, for Republican candidates. But what they recognized,

760
00:47:42,400 --> 00:47:44,359
Speaker 3: I think accurately, was that it wasn't a matter if

761
00:47:44,360 --> 00:47:47,840
Speaker 3: they didn't need to win these areas. They just needed

762
00:47:47,880 --> 00:47:51,160
Speaker 3: to turn around the numbers enough they needed to not

763
00:47:51,400 --> 00:47:54,319
Speaker 3: get out among younger voters. And you look at what

764
00:47:54,480 --> 00:47:58,480
Speaker 3: they created there. It's incredible, especially among younger men. And

765
00:47:58,520 --> 00:48:02,680
Speaker 3: these are numbers that are holding still. They're reillent, especially

766
00:48:02,719 --> 00:48:07,960
Speaker 3: among young men when we look at President Trump's overall numbers.

767
00:48:08,000 --> 00:48:10,479
Speaker 3: You know, frankly in the Toilvet at the moment, they're

768
00:48:10,600 --> 00:48:13,719
Speaker 3: still out registering Democrats among younger men.

769
00:48:14,400 --> 00:48:16,160
Speaker 1: You know, I have a thesis on that that it's

770
00:48:16,239 --> 00:48:19,800
Speaker 1: COVID have I always I have a gen Z focus

771
00:48:19,840 --> 00:48:25,080
Speaker 1: group in my household to college students and my younger

772
00:48:25,239 --> 00:48:28,920
Speaker 1: My younger one was sort of you know, let me

773
00:48:28,960 --> 00:48:31,840
Speaker 1: put it this way. He and his friends. I would say,

774
00:48:31,920 --> 00:48:34,880
Speaker 1: you know, think about this. Your first interaction with government

775
00:48:35,000 --> 00:48:38,680
Speaker 1: is COVID and for some of these guys, right the

776
00:48:38,719 --> 00:48:41,439
Speaker 1: first time they've dealt with government, it took them away

777
00:48:41,440 --> 00:48:44,960
Speaker 1: from their friends. And I think that is a I

778
00:48:45,000 --> 00:48:46,960
Speaker 1: think this is going to be a generational thing with

779
00:48:47,040 --> 00:48:51,040
Speaker 1: these guys. But we'll see, right, it's only one cycle.

780
00:48:51,080 --> 00:48:53,160
Speaker 1: But that's just the thesis I have that this is

781
00:48:53,200 --> 00:48:55,160
Speaker 1: more COVID related than we fully appreciate.

782
00:48:55,960 --> 00:48:58,200
Speaker 3: I think that's absolutely right. And in fact, you know,

783
00:48:58,239 --> 00:49:02,160
Speaker 3: I shared generally a lot of the things that I

784
00:49:02,200 --> 00:49:03,880
Speaker 3: will share, I would say most of the things I

785
00:49:03,920 --> 00:49:06,200
Speaker 3: share is a partisan Democrat that I share in public

786
00:49:06,239 --> 00:49:08,840
Speaker 3: are going to appear to be more favorable for Democrats.

787
00:49:08,880 --> 00:49:10,920
Speaker 3: But in November of twenty twenty three, I shared some

788
00:49:11,000 --> 00:49:14,080
Speaker 3: analysis I put together. It was looking at the voter

789
00:49:14,160 --> 00:49:17,600
Speaker 3: registration gender gap among voters under the age of twenty five,

790
00:49:17,760 --> 00:49:20,080
Speaker 3: and it was really for me, sounding the alarm where

791
00:49:20,160 --> 00:49:23,640
Speaker 3: among all of the party registration states, the gender gap

792
00:49:23,680 --> 00:49:26,719
Speaker 3: among these younger voters was twenty six points. In Pennsylvania,

793
00:49:26,719 --> 00:49:31,279
Speaker 3: it's almost thirty seven points. And to me, that was

794
00:49:31,520 --> 00:49:34,840
Speaker 3: a flashing red alarm that that's something that that's something

795
00:49:34,840 --> 00:49:38,080
Speaker 3: that holds, and that we don't do something about it,

796
00:49:38,600 --> 00:49:41,239
Speaker 3: we're not going to win. And I think your point, yeah,

797
00:49:41,360 --> 00:49:45,960
Speaker 3: certainly came out of COVID. These were you know, it's complex,

798
00:49:46,000 --> 00:49:49,480
Speaker 3: but when you put these younger men, especially in a

799
00:49:49,520 --> 00:49:54,160
Speaker 3: situation where suddenly their lives are being lived almost entirely online,

800
00:49:55,120 --> 00:49:56,960
Speaker 3: and the sort of interactions they were having and the

801
00:49:56,960 --> 00:49:59,080
Speaker 3: connections they were making, and then sort of the lack

802
00:49:59,160 --> 00:50:01,480
Speaker 3: of real world since they had, I think it had

803
00:50:02,120 --> 00:50:04,160
Speaker 3: a massive impact. You know, when you look at the

804
00:50:04,239 --> 00:50:07,960
Speaker 3: Navigator surveys from after the election, which is a great

805
00:50:08,040 --> 00:50:12,239
Speaker 3: data set of large sample sized post election surveys, they

806
00:50:12,280 --> 00:50:15,440
Speaker 3: asked the question about how much political news do you consume?

807
00:50:15,560 --> 00:50:18,520
Speaker 3: And there's a straight line correlation between the answer to

808
00:50:18,560 --> 00:50:22,200
Speaker 3: that question and for whom you voted, Meaning the people

809
00:50:22,280 --> 00:50:24,680
Speaker 3: say I consume a lot of political news. Vice President

810
00:50:24,680 --> 00:50:27,640
Speaker 3: Harris won by six points, but those who say that

811
00:50:27,760 --> 00:50:31,759
Speaker 3: I consume no or almost none, Donald Trump one by

812
00:50:31,800 --> 00:50:35,720
Speaker 3: almost fifteen points. And again we talked about these voters

813
00:50:35,719 --> 00:50:38,839
Speaker 3: as low information voters. They're overwhelmingly younger, and they were

814
00:50:38,840 --> 00:50:41,160
Speaker 3: more men than women. We talked about them as low

815
00:50:41,160 --> 00:50:44,400
Speaker 3: information voters. They're not exactly low information voters. They're consuming

816
00:50:44,520 --> 00:50:49,400
Speaker 3: so much information, but they aren't consuming over political information

817
00:50:49,520 --> 00:50:53,319
Speaker 3: in the spaces that Democrats generally were contesting or communicating it.

818
00:50:53,760 --> 00:50:58,480
Speaker 1: Have you studied this, you know, it does feel as

819
00:50:58,480 --> 00:51:04,160
Speaker 1: if you know sort of how often the first is

820
00:51:04,200 --> 00:51:06,520
Speaker 1: it like when you register somebody for the first time

821
00:51:06,520 --> 00:51:09,799
Speaker 1: for your party? How you know what kind of stickiness

822
00:51:09,840 --> 00:51:12,239
Speaker 1: is that? Is that a ten year stick? Is that

823
00:51:12,320 --> 00:51:16,160
Speaker 1: a generational stick? Is that? Like, you know, have you

824
00:51:16,239 --> 00:51:19,560
Speaker 1: been able have you looked at this through generational prisms?

825
00:51:19,600 --> 00:51:22,000
Speaker 1: You know? I always it's fascinating to me that my

826
00:51:22,040 --> 00:51:27,640
Speaker 1: generation's the most pro Trump generation Gen X, and I

827
00:51:27,800 --> 00:51:31,000
Speaker 1: attribute it to growing up Reagan, as I call it, right,

828
00:51:31,120 --> 00:51:34,239
Speaker 1: that that was our formative years were Reagan, Right, that

829
00:51:34,440 --> 00:51:37,200
Speaker 1: was the president during when we were both from you know,

830
00:51:37,800 --> 00:51:40,239
Speaker 1: Nancy Reagan showing up on different strokes, and then you

831
00:51:40,280 --> 00:51:43,760
Speaker 1: know it was just sort of it was there and

832
00:51:44,440 --> 00:51:46,920
Speaker 1: economy was pretty good, right, you know, it was in

833
00:51:46,960 --> 00:51:48,880
Speaker 1: the end of the Cold War, right, we won something.

834
00:51:49,000 --> 00:51:52,120
Speaker 1: So that's my explanation for it. But I have no

835
00:51:52,200 --> 00:51:55,239
Speaker 1: idea whether I'm just sort of going through my head

836
00:51:55,320 --> 00:51:57,719
Speaker 1: and sort of saying, well, you know, how much is

837
00:51:57,760 --> 00:52:02,240
Speaker 1: that early commitment to a party matter long term.

838
00:52:02,400 --> 00:52:07,280
Speaker 3: Yeah, it's incredibly important. And the phenomena that you mentioned,

839
00:52:07,360 --> 00:52:10,800
Speaker 3: or the theory that you that you just positive is

840
00:52:10,840 --> 00:52:13,960
Speaker 3: actually something the political scientists have studied and shown that

841
00:52:14,040 --> 00:52:16,759
Speaker 3: who at present, when you're in those formative years and

842
00:52:16,800 --> 00:52:19,080
Speaker 3: again will depend for the individual in terms of when

843
00:52:19,560 --> 00:52:22,680
Speaker 3: tuning into these things. But people talk about broadly the culture,

844
00:52:23,320 --> 00:52:26,880
Speaker 3: which a somewhat nebulous, but certainly Ronald Reagan in the

845
00:52:26,920 --> 00:52:30,640
Speaker 3: eighties as a member of gen X myself, it was

846
00:52:30,719 --> 00:52:32,759
Speaker 3: ubiquitous from a cultural perspective.

847
00:52:33,880 --> 00:52:35,120
Speaker 2: And yeah, so.

848
00:52:36,840 --> 00:52:41,359
Speaker 3: The biggest impact is your household composition in a lot

849
00:52:41,400 --> 00:52:43,600
Speaker 3: of ways as well, or at least maybe next in

850
00:52:43,680 --> 00:52:58,560
Speaker 3: line between the phenomena. So what your parents are, what

851
00:52:58,600 --> 00:53:01,640
Speaker 3: your parents are has huge impact. Now I'll be curious

852
00:53:01,640 --> 00:53:04,400
Speaker 3: to see if that holds. It would suggest that maybe

853
00:53:04,440 --> 00:53:08,080
Speaker 3: now that's less sticky. But wherever to your original question,

854
00:53:08,719 --> 00:53:11,560
Speaker 3: When someone registers with a party, they tend to stay

855
00:53:11,600 --> 00:53:14,799
Speaker 3: there and it takes time. Generally they'll start voting the

856
00:53:14,880 --> 00:53:18,240
Speaker 3: other way before they switch. And so we talk about

857
00:53:18,239 --> 00:53:22,319
Speaker 3: these ancestral democrats in places like West Virginia throughout the show.

858
00:53:22,400 --> 00:53:25,600
Speaker 1: Let's just say that's the last spot of the generational

859
00:53:25,600 --> 00:53:29,160
Speaker 1: Democrats as Appalachia. Right, It's like Kentucky, West Virginia. It's

860
00:53:29,200 --> 00:53:32,759
Speaker 1: like the last Southern Ohio. I don't feel like you

861
00:53:32,880 --> 00:53:34,200
Speaker 1: have it in the Deep South anymore.

862
00:53:34,320 --> 00:53:36,640
Speaker 3: You don't know they're gone. They're gone at this point,

863
00:53:36,800 --> 00:53:39,800
Speaker 3: and they are going. You know, Pennsylvania actually produces data

864
00:53:39,800 --> 00:53:42,040
Speaker 3: on party switchers on a very regular basis, and you

865
00:53:42,080 --> 00:53:44,800
Speaker 3: see it still happening too, and it's.

866
00:53:44,680 --> 00:53:48,279
Speaker 1: All Appalachia like areas like Western Pa.

867
00:53:48,440 --> 00:53:49,560
Speaker 2: Yeah, that's right, you know.

868
00:53:49,600 --> 00:53:52,440
Speaker 3: And Pennsylvania's fascinating to me because again you mentioned the

869
00:53:52,760 --> 00:53:55,600
Speaker 3: success the Republicans had. They had massive investment in part

870
00:53:55,640 --> 00:53:58,319
Speaker 3: of the registration there, not just in twenty twenty four,

871
00:53:58,360 --> 00:54:00,319
Speaker 3: but going back four or five years before or that,

872
00:54:00,360 --> 00:54:02,880
Speaker 3: with great success. What's interesting to me is if you

873
00:54:02,880 --> 00:54:05,200
Speaker 3: look at this moment now, they have some court races

874
00:54:05,239 --> 00:54:08,719
Speaker 3: there that maybe aren't getting in a lot of attention nationally,

875
00:54:08,840 --> 00:54:13,040
Speaker 3: but are in Pennsylvania and are incredibly important in a

876
00:54:13,080 --> 00:54:17,120
Speaker 3: lot of ways. And Democrats are actually doing among new registrants,

877
00:54:17,280 --> 00:54:19,919
Speaker 3: are actually doing better than they did four and even

878
00:54:20,040 --> 00:54:23,439
Speaker 3: eight years ago. So it's something that I'm looking at.

879
00:54:24,200 --> 00:54:26,160
Speaker 3: They're not doing much better but they're doing a point

880
00:54:26,200 --> 00:54:28,400
Speaker 3: or two better. Which is this a bit of a turnaround,

881
00:54:28,400 --> 00:54:30,000
Speaker 3: I don't know, but it's.

882
00:54:29,840 --> 00:54:32,480
Speaker 1: In Shapiro related. I mean, he's a popular governor.

883
00:54:32,600 --> 00:54:34,400
Speaker 2: Right, That's a big part of it.

884
00:54:35,239 --> 00:54:39,840
Speaker 3: But an important point here is even with that happening,

885
00:54:41,080 --> 00:54:44,160
Speaker 3: the net numbers are still getting worse for Democrats. Part

886
00:54:44,200 --> 00:54:46,920
Speaker 3: of it is because of who is being removed from

887
00:54:46,960 --> 00:54:49,080
Speaker 3: the file to put it in a passway, which part

888
00:54:49,120 --> 00:54:51,120
Speaker 3: of that is death. Part of that is people moving

889
00:54:51,120 --> 00:54:53,120
Speaker 3: out of the states. Part of that is purging, but

890
00:54:53,200 --> 00:54:55,600
Speaker 3: that's generally negative. The people who are in their eighties

891
00:54:55,640 --> 00:54:59,480
Speaker 3: are actually more Democratic than not. People who get purged

892
00:54:59,480 --> 00:55:02,239
Speaker 3: off the file tend to be more Democrats. So Republicans

893
00:55:02,280 --> 00:55:05,040
Speaker 3: are still actually gaining in the net there, even while

894
00:55:05,080 --> 00:55:08,279
Speaker 3: Democrats are doing better among new registrants.

895
00:55:08,360 --> 00:55:09,759
Speaker 2: So another thing to keep an eye on.

896
00:55:10,400 --> 00:55:13,320
Speaker 1: In twenty twelve after that election, and I feel like

897
00:55:13,360 --> 00:55:16,080
Speaker 1: the most prominent person making this argument was Tom I

898
00:55:16,120 --> 00:55:18,600
Speaker 1: think that Tom Bevan over real clear that there was

899
00:55:18,640 --> 00:55:21,239
Speaker 1: a missing white vote, that there was this chunk of

900
00:55:21,280 --> 00:55:24,640
Speaker 1: people not voting, and that was the explanation for why

901
00:55:24,800 --> 00:55:30,920
Speaker 1: Romney so underperformed, particularly in certain places. I was a

902
00:55:30,920 --> 00:55:34,520
Speaker 1: bit skeptical, and I think some people were. And then

903
00:55:34,600 --> 00:55:38,520
Speaker 1: twenty sixteen happened, and then twenty happened, at twenty twenty

904
00:55:38,520 --> 00:55:42,280
Speaker 1: four happened, And you can't help but wonder how much

905
00:55:42,400 --> 00:55:47,320
Speaker 1: of the Trump gain is missing. Is voters that weren't participating,

906
00:55:48,080 --> 00:55:51,200
Speaker 1: say in the first twelve years of this century, versus

907
00:55:52,080 --> 00:55:53,040
Speaker 1: those that switched.

908
00:55:53,760 --> 00:55:58,800
Speaker 3: Yeah, yeah, it's a big part of it. I mean, obviously,

909
00:55:58,800 --> 00:56:01,880
Speaker 3: the entire equation changed so radically from twenty twelve that

910
00:56:01,920 --> 00:56:04,000
Speaker 3: it's hard to point the one thing right because we've

911
00:56:04,040 --> 00:56:08,480
Speaker 3: seen that these voters who were more consistent voting better

912
00:56:08,640 --> 00:56:13,800
Speaker 3: educated Again. Traditionally Republican voters voted for Romney in twenty twelve,

913
00:56:13,880 --> 00:56:15,360
Speaker 3: voted for mckenial to.

914
00:56:15,600 --> 00:56:17,879
Speaker 1: I live in the last Romney precinct of Arlington, as

915
00:56:17,880 --> 00:56:19,960
Speaker 1: I call it. There you go, right, you know, And

916
00:56:20,000 --> 00:56:22,560
Speaker 1: they haven't voted Republicans since in this area, you know,

917
00:56:23,320 --> 00:56:26,359
Speaker 1: And so I wouldn't call them liberal Democrats.

918
00:56:25,960 --> 00:56:30,759
Speaker 3: No, by note, but those voters have voted, They likely

919
00:56:30,840 --> 00:56:34,640
Speaker 3: voted for Clinton, They almost certainly voted for Biden and

920
00:56:34,640 --> 00:56:37,239
Speaker 3: Fort Harris. These are the voters who are voting in

921
00:56:37,280 --> 00:56:41,239
Speaker 3: these lower turnout elections. That's the reason why fairly well documented.

922
00:56:41,239 --> 00:56:43,880
Speaker 3: The Democrats are doing better in these lower turnout, especially

923
00:56:43,920 --> 00:56:46,360
Speaker 3: these special elections, that used to be the great advantage

924
00:56:46,360 --> 00:56:50,480
Speaker 3: for Republicans and that has turned on its head. And so, yeah,

925
00:56:50,719 --> 00:56:54,239
Speaker 3: there are more of these lower turnout white voters who

926
00:56:54,239 --> 00:56:56,759
Speaker 3: are coming out when Trump is on the ballot. They

927
00:56:56,760 --> 00:57:00,439
Speaker 3: didn't come out in twenty eighteen. Not enough of them

928
00:57:00,560 --> 00:57:03,240
Speaker 3: came out twenty twenty two to have a red wave election.

929
00:57:03,400 --> 00:57:08,120
Speaker 3: We'll see what happens this year in New Jersey, in

930
00:57:08,200 --> 00:57:11,640
Speaker 3: Virginia and Pennsylvania and other places. See what happens next year.

931
00:57:11,800 --> 00:57:13,680
Speaker 3: But the other element of this that we've been talking

932
00:57:13,680 --> 00:57:20,160
Speaker 3: about is Republican improvements among younger voters, especially younger voters

933
00:57:20,160 --> 00:57:22,560
Speaker 3: of coloring, younger white men. And so I don't know

934
00:57:22,600 --> 00:57:24,760
Speaker 3: that you can count those in terms of the missing

935
00:57:24,880 --> 00:57:28,880
Speaker 3: white vote. Sure, these voters who demographically generally would be

936
00:57:28,960 --> 00:57:31,880
Speaker 3: a smaller share of the electorate and now have been

937
00:57:32,040 --> 00:57:36,240
Speaker 3: ascendant under Trump. I will say, when you look at

938
00:57:36,280 --> 00:57:39,520
Speaker 3: the polling numbers now, and you look at what drives

939
00:57:39,560 --> 00:57:42,840
Speaker 3: Trump's reasonably good numbers when he was elected and when

940
00:57:42,880 --> 00:57:46,240
Speaker 3: he was inaugurated to where they quickly went. The voters

941
00:57:46,280 --> 00:57:48,360
Speaker 3: who dropped the most were these same voters who swung

942
00:57:48,400 --> 00:57:51,400
Speaker 3: the most towards him. So these younger now have overwhelmingly

943
00:57:51,480 --> 00:57:53,760
Speaker 3: negative numbers. But like I said a few minutes ago,

944
00:57:54,240 --> 00:57:56,760
Speaker 3: when you look at the partisan registration, younger white men

945
00:57:56,800 --> 00:58:00,880
Speaker 3: are still registering overwhelmingly Republican, which tells me Republicans are

946
00:58:00,920 --> 00:58:04,400
Speaker 3: doing the nuts and bolts, blocking and tackling. We're doing

947
00:58:04,400 --> 00:58:07,080
Speaker 3: the registration at the local level and holding on to

948
00:58:07,200 --> 00:58:08,160
Speaker 3: some of those margins.

949
00:58:10,120 --> 00:58:12,720
Speaker 1: If the Democratic Party pointed to one thing, do they

950
00:58:12,760 --> 00:58:16,760
Speaker 1: have a do they have a base problem or a persuasion.

951
00:58:16,200 --> 00:58:23,640
Speaker 3: Problem, Well, look, time will tell. I mean from both perspectives,

952
00:58:23,720 --> 00:58:26,360
Speaker 3: I think Democrats feel better about where they are now

953
00:58:26,440 --> 00:58:32,360
Speaker 3: in terms of Trump's popularity. But I think there's two

954
00:58:32,400 --> 00:58:35,520
Speaker 3: parts to this equation. Right, There's how well will Democrats

955
00:58:35,560 --> 00:58:39,480
Speaker 3: do in the elections happening next month and then the

956
00:58:39,520 --> 00:58:43,640
Speaker 3: elections next year just based on an anti Trump, anti

957
00:58:43,680 --> 00:58:46,600
Speaker 3: Republican sentiment, which history would tell us, And we don't

958
00:58:46,600 --> 00:58:49,600
Speaker 3: have to go back any further team, but historically we

959
00:58:49,640 --> 00:58:51,560
Speaker 3: could go back as far as we want and find

960
00:58:51,560 --> 00:58:54,360
Speaker 3: Democrats should do quite well in these elections just because

961
00:58:54,360 --> 00:58:58,200
Speaker 3: of anti incumbency and especially because of Trump and his

962
00:58:58,280 --> 00:59:02,600
Speaker 3: little popularity numbers to the big question is are Democrats

963
00:59:02,640 --> 00:59:05,640
Speaker 3: able to connect the dots and give voters a reason

964
00:59:05,680 --> 00:59:08,200
Speaker 3: to vote for them? From the positive case, can we

965
00:59:08,240 --> 00:59:12,200
Speaker 3: get to the point where people feel better about the

966
00:59:12,240 --> 00:59:15,320
Speaker 3: Democrat Party, where more people are associating and affiliating with

967
00:59:15,360 --> 00:59:18,600
Speaker 3: the Democratic Party. Why I'm watching these voter registration numbers

968
00:59:18,680 --> 00:59:21,920
Speaker 3: so closely now because that's where you would expect to

969
00:59:22,040 --> 00:59:25,479
Speaker 3: see it first before the election, is more people when

970
00:59:26,000 --> 00:59:28,320
Speaker 3: they go you know, maybe it's just they're getting their

971
00:59:28,360 --> 00:59:33,000
Speaker 3: driver's license, maybe it's not even effort to voter registration,

972
00:59:33,160 --> 00:59:35,280
Speaker 3: but they have a few boxes they could check. And

973
00:59:35,360 --> 00:59:39,640
Speaker 3: right now, those younger voters are overwhelmingly just saying unaffiliated,

974
00:59:39,880 --> 00:59:42,200
Speaker 3: just as we did a year ago, three years ago,

975
00:59:42,320 --> 00:59:46,000
Speaker 3: more years ago. And so for Democrats to really be

976
00:59:46,160 --> 00:59:52,560
Speaker 3: able to maximize their potential and these upcoming elections, I

977
00:59:52,560 --> 00:59:54,320
Speaker 3: think that's where you're going to see it is them

978
00:59:54,440 --> 00:59:56,680
Speaker 3: being able to build that positive and so to me,

979
00:59:57,160 --> 01:00:01,400
Speaker 3: it's both it's persuasion and position kids persuading the people

980
01:00:02,080 --> 01:00:05,160
Speaker 3: to get to the point where they enter that mobilization

981
01:00:05,640 --> 01:00:09,280
Speaker 3: category where they're going to be turnout targets for democraticaintents.

982
01:00:09,560 --> 01:00:13,680
Speaker 1: Do you think the Democrats are resting almost counting too

983
01:00:13,800 --> 01:00:16,400
Speaker 1: much on Trump voters not showing up when Trump's not

984
01:00:16,400 --> 01:00:19,160
Speaker 1: on the ballot. Like it. It's sort of like I

985
01:00:19,200 --> 01:00:21,560
Speaker 1: hear this talk all the time. Well, Democrats will be fine,

986
01:00:21,840 --> 01:00:25,840
Speaker 1: and it may actually be a way of reason to

987
01:00:26,120 --> 01:00:31,080
Speaker 1: sort of matter, you know, be careful thinking twenty twenty six,

988
01:00:31,160 --> 01:00:34,160
Speaker 1: if it goes well for Democrats, is somehow a harbinger

989
01:00:34,160 --> 01:00:38,320
Speaker 1: for twenty eight, considering if quote unquote the Trump voter

990
01:00:38,800 --> 01:00:43,960
Speaker 1: just simply doesn't show up again for midterms. They know

991
01:00:44,080 --> 01:00:47,080
Speaker 1: this too, right, They know they have this problem, and

992
01:00:47,120 --> 01:00:48,720
Speaker 1: it does sound as if they're going to make more

993
01:00:48,760 --> 01:00:51,200
Speaker 1: of an effort to see if they can they can

994
01:00:51,280 --> 01:00:54,520
Speaker 1: get these voters more engaged in elections that don't involve Trump.

995
01:00:58,400 --> 01:01:00,880
Speaker 1: Do you send let me tell you what. I sense

996
01:01:00,880 --> 01:01:04,920
Speaker 1: that Democrats are almost counting on this phenomenon, and I

997
01:01:04,960 --> 01:01:08,560
Speaker 1: would be weary of counting on the phenomenon given how

998
01:01:08,640 --> 01:01:09,920
Speaker 1: much money they're throwing at this.

999
01:01:11,200 --> 01:01:13,640
Speaker 3: Yeah, look, that's a hard one to read in terms

1000
01:01:13,680 --> 01:01:17,720
Speaker 3: of what's happening tactically on the ground. I do think

1001
01:01:17,840 --> 01:01:20,040
Speaker 3: that you know, again, based on the history, You're right,

1002
01:01:20,120 --> 01:01:22,760
Speaker 3: the Democrats are looking at this and making a calculus

1003
01:01:22,760 --> 01:01:25,960
Speaker 3: that in the end, historically these voters haven't come out

1004
01:01:26,000 --> 01:01:29,840
Speaker 3: with Donald Trump is not on the ballot, so therefore

1005
01:01:29,880 --> 01:01:32,240
Speaker 3: we should do better. And you know, the special elections

1006
01:01:32,360 --> 01:01:35,240
Speaker 3: so far have proven that true.

1007
01:01:35,480 --> 01:01:39,880
Speaker 1: Look very so everything looks similar to twenty seventeen, except

1008
01:01:39,920 --> 01:01:43,320
Speaker 1: the Democratic Party is unfavorable. Ready, Yeah, like that's the

1009
01:01:43,360 --> 01:01:45,960
Speaker 1: one thing that's different. It's much higher, that's right, and

1010
01:01:46,000 --> 01:01:48,040
Speaker 1: that's why I think. You know, obviously, Democrats have been

1011
01:01:48,080 --> 01:01:52,160
Speaker 1: going very hard on healthcare during this shutdown, and that

1012
01:01:52,240 --> 01:01:55,160
Speaker 1: to me tells me that they are making an effort

1013
01:01:55,240 --> 01:01:58,680
Speaker 1: to appeal not just to the mobilization universe, not that

1014
01:01:59,480 --> 01:02:01,400
Speaker 1: the audience doesn't want to hear that message, but to

1015
01:02:01,480 --> 01:02:04,320
Speaker 1: those swing voters. I mean, when they have a message

1016
01:02:04,320 --> 01:02:07,880
Speaker 1: that Marjorie Taylor Green is agreeing with, suggest there's something

1017
01:02:07,960 --> 01:02:10,440
Speaker 1: there and there's an opportunity and an effort to appeal

1018
01:02:10,600 --> 01:02:15,520
Speaker 1: to these swing voters who likely voted for Trump last

1019
01:02:15,600 --> 01:02:18,800
Speaker 1: year but are potentially part of that. You know, maybe

1020
01:02:18,840 --> 01:02:23,520
Speaker 1: fifteen well, let's say fifteen percent of the country who

1021
01:02:24,120 --> 01:02:27,320
Speaker 1: voted for him felt favorably about when he took office

1022
01:02:27,360 --> 01:02:31,120
Speaker 1: and don't feel that way now. When you hear Democrats

1023
01:02:31,120 --> 01:02:36,120
Speaker 1: have a brand problem? What is it that the problem

1024
01:02:36,240 --> 01:02:38,919
Speaker 1: is that people don't know what the party does stand for,

1025
01:02:39,240 --> 01:02:41,800
Speaker 1: or that people do know what the party stands for

1026
01:02:41,840 --> 01:02:45,000
Speaker 1: and they don't like it. How do you view the

1027
01:02:45,080 --> 01:02:49,400
Speaker 1: quote brand problem? Is it just not not very well

1028
01:02:49,440 --> 01:02:52,600
Speaker 1: defined or frankly defined in an unpopular way.

1029
01:02:52,920 --> 01:02:55,120
Speaker 3: You know, look, I'm a numbers guy, not a policy

1030
01:02:55,240 --> 01:02:56,880
Speaker 3: or a messaging guy. But when you look at the

1031
01:02:57,000 --> 01:03:00,360
Speaker 3: numbers from the twenty four election again, and you look

1032
01:03:00,400 --> 01:03:02,640
Speaker 3: at the exit polls, you look at the Navigator survey,

1033
01:03:03,360 --> 01:03:07,120
Speaker 3: there was a big problem in terms of awareness of issues.

1034
01:03:07,240 --> 01:03:12,320
Speaker 3: You looked at sort of the four signature legislative accomplishments

1035
01:03:12,320 --> 01:03:15,840
Speaker 3: of President Biden in Democrats while he was in and

1036
01:03:15,960 --> 01:03:18,880
Speaker 3: in each of those a Navigator tested this a majority,

1037
01:03:19,000 --> 01:03:22,320
Speaker 3: in some cases over sixty percent of Americans said they

1038
01:03:22,360 --> 01:03:25,600
Speaker 3: didn't know anything about them. And then a real kick

1039
01:03:25,640 --> 01:03:29,280
Speaker 3: in the pants for Democrats. More independent voters said that

1040
01:03:29,360 --> 01:03:35,280
Speaker 3: Donald Trump did more on infrastructure when in office than

1041
01:03:35,480 --> 01:03:36,640
Speaker 3: Joe Biden did.

1042
01:03:36,560 --> 01:03:39,360
Speaker 1: So just by saying Infrastructure week. Even though it failed,

1043
01:03:39,760 --> 01:03:40,520
Speaker 1: it stuck.

1044
01:03:41,040 --> 01:03:44,480
Speaker 2: So in our very online circle, that was the meme. Right,

1045
01:03:44,520 --> 01:03:45,360
Speaker 2: That was a running joke.

1046
01:03:45,520 --> 01:03:48,920
Speaker 1: Oh it's infrastructure, right, and yet it turned out people

1047
01:03:48,960 --> 01:03:51,360
Speaker 1: have thought, oh that Donald Trump cares about infrastructure.

1048
01:03:51,720 --> 01:03:54,480
Speaker 2: That's exactly right. I mean, that's what bubble make it

1049
01:03:54,560 --> 01:03:54,920
Speaker 2: up the.

1050
01:03:54,840 --> 01:04:00,360
Speaker 1: Others, so you believe it is a it's an aware farness.

1051
01:04:00,560 --> 01:04:04,600
Speaker 1: So it's sort of it's more message penetration. The message

1052
01:04:04,640 --> 01:04:09,360
Speaker 1: itself might be working if they knew how to mar

1053
01:04:09,880 --> 01:04:13,200
Speaker 1: So this would be a marketing problem as much. You

1054
01:04:13,240 --> 01:04:14,760
Speaker 1: may have a good brand, but if you don't market

1055
01:04:14,800 --> 01:04:16,400
Speaker 1: it correctly, nobody knows your brand.

1056
01:04:17,040 --> 01:04:18,000
Speaker 2: Well, yeah, you know.

1057
01:04:18,280 --> 01:04:19,800
Speaker 3: I think there's two ways to look at this question.

1058
01:04:19,880 --> 01:04:22,920
Speaker 3: One is the previous four years when when Democrats were

1059
01:04:22,960 --> 01:04:25,200
Speaker 3: in power, at least in the White House. And then

1060
01:04:25,240 --> 01:04:28,280
Speaker 3: there's the question of now where Democrats don't control anything.

1061
01:04:28,280 --> 01:04:31,080
Speaker 3: And I think there's you know, that has always been

1062
01:04:31,080 --> 01:04:33,160
Speaker 3: a challenge for the party that is out of power,

1063
01:04:33,280 --> 01:04:36,000
Speaker 3: and how do you find your own proactive agenda. I mean,

1064
01:04:36,000 --> 01:04:38,600
Speaker 3: we can go back to nineteen be four in the

1065
01:04:38,600 --> 01:04:41,720
Speaker 3: Contract with America and New Gingrich and now Republicans successfully

1066
01:04:41,720 --> 01:04:46,240
Speaker 3: we're able to brand some type of actual agenda. I

1067
01:04:46,280 --> 01:04:48,800
Speaker 3: think that's a lot more challenging in the issue environment

1068
01:04:48,880 --> 01:04:52,000
Speaker 3: and just the media consumption environment, where in now to

1069
01:04:52,040 --> 01:04:54,040
Speaker 3: get voters to pay attention to these things. I think

1070
01:04:54,040 --> 01:04:57,120
Speaker 3: the shutdown again we see Democrats talking more specifically about

1071
01:04:57,200 --> 01:04:59,800
Speaker 3: healthcare is a good step in that direction. I just

1072
01:04:59,800 --> 01:05:03,000
Speaker 3: think it's much more challenging these days to get that proactive,

1073
01:05:03,040 --> 01:05:07,040
Speaker 3: positive message out there in agenda out there, when in

1074
01:05:07,120 --> 01:05:09,840
Speaker 3: the end Democrats don't have the ability to really move

1075
01:05:09,880 --> 01:05:10,800
Speaker 3: any of this forward.

1076
01:05:11,280 --> 01:05:14,560
Speaker 1: All right, I want to geek out, uh do geek

1077
01:05:14,600 --> 01:05:21,200
Speaker 1: out on some states. And so you know there's you

1078
01:05:21,560 --> 01:05:24,920
Speaker 1: look at the you look at the seven swing states,

1079
01:05:27,280 --> 01:05:29,520
Speaker 1: and is it in your head a hard seven, meaning

1080
01:05:29,520 --> 01:05:35,320
Speaker 1: you got the three Midwestern states right, Pennsylvania, Wisconsin, Uh, Michigan.

1081
01:05:35,720 --> 01:05:39,520
Speaker 1: Then you got the sun Belt states of Arizona, Nevada, Georgia,

1082
01:05:39,560 --> 01:05:45,040
Speaker 1: North Carolina. Is there is is eight closer to seven?

1083
01:05:45,440 --> 01:05:48,360
Speaker 1: I you new Hampshire? Or is eight closer than to nine?

1084
01:05:48,480 --> 01:05:50,760
Speaker 1: You see what I mean? Is it those seven and

1085
01:05:50,840 --> 01:05:53,640
Speaker 1: everybody else? Or do you think there's a couple other

1086
01:05:53,680 --> 01:05:56,920
Speaker 1: states still sort of you know, on the outside looking

1087
01:05:56,960 --> 01:05:59,000
Speaker 1: and they could jump into the to the.

1088
01:05:59,000 --> 01:06:01,800
Speaker 3: Battleground now you know, if you wanted to look at

1089
01:06:01,840 --> 01:06:04,400
Speaker 3: obviously the map and where states were moving in twenty

1090
01:06:04,400 --> 01:06:07,040
Speaker 3: twenty four relative to twenty twenty you had a handful

1091
01:06:07,080 --> 01:06:09,720
Speaker 3: of states that I think you would have a very

1092
01:06:09,760 --> 01:06:13,440
Speaker 3: strong argument for saying, you know, they shouldn't be considered

1093
01:06:13,480 --> 01:06:16,400
Speaker 3: it swing states in any sense, but they were getting closer.

1094
01:06:16,520 --> 01:06:18,440
Speaker 2: New Hampshire was one of them. Yet Minnesota.

1095
01:06:18,440 --> 01:06:20,800
Speaker 1: Look, even Minnesota has been sitting there on the cost

1096
01:06:20,880 --> 01:06:22,919
Speaker 1: by have you Minnesota the way I viewed New Jersey.

1097
01:06:22,960 --> 01:06:26,480
Speaker 1: For Republicans it always it's always close. But Charlie Brown,

1098
01:06:26,600 --> 01:06:28,600
Speaker 1: you know, Lucy always pulls the football.

1099
01:06:28,200 --> 01:06:30,240
Speaker 3: Well well, and for them it'd be there, you know,

1100
01:06:30,360 --> 01:06:33,439
Speaker 3: three three hundred and fortieth electoral vote. It's not really

1101
01:06:33,440 --> 01:06:37,160
Speaker 3: relevant from a strategic perspective, right, And so no, I

1102
01:06:37,440 --> 01:06:39,160
Speaker 3: you know, I think at this point the seven states

1103
01:06:39,160 --> 01:06:41,760
Speaker 3: are fairly solidified, at least if we're looking at the

1104
01:06:41,800 --> 01:06:43,080
Speaker 3: next couple of years here.

1105
01:06:43,400 --> 01:06:45,320
Speaker 2: Obviously it will continue to evolve.

1106
01:06:45,480 --> 01:06:50,320
Speaker 3: Democrats have have been interested in Texas and Florida for

1107
01:06:50,360 --> 01:06:52,400
Speaker 3: a long time for obviously, you know, to put those

1108
01:06:52,400 --> 01:06:54,800
Speaker 3: two in the same category, it's somewhat unfair given that

1109
01:06:55,200 --> 01:06:59,480
Speaker 3: Democrats have won Florida and not too distant at least

1110
01:06:59,520 --> 01:07:03,400
Speaker 3: in our life time, and at this point they're moving

1111
01:07:03,440 --> 01:07:08,440
Speaker 3: in different directions. So you know, for various reasons. So

1112
01:07:08,520 --> 01:07:10,640
Speaker 3: you know, Texas will always be part of the conversation

1113
01:07:10,760 --> 01:07:14,240
Speaker 3: for Democrats, at least further out from election day.

1114
01:07:15,160 --> 01:07:20,080
Speaker 1: But you're you're more pessimistic on Florida Solidify. Are you

1115
01:07:20,120 --> 01:07:22,640
Speaker 1: more pessimistic on Florida versus Texas if you were to pick.

1116
01:07:22,480 --> 01:07:26,200
Speaker 3: One, Yeah, I am. I mean, look, you had just

1117
01:07:26,280 --> 01:07:29,439
Speaker 3: negative trends there. I think Democrats can still win there,

1118
01:07:29,600 --> 01:07:34,280
Speaker 3: especially in the sort of dynamic we have now without

1119
01:07:34,320 --> 01:07:39,040
Speaker 3: Trump on the ballot in a midterm election, Democrats would

1120
01:07:39,040 --> 01:07:41,720
Speaker 3: have a chance there. In the presidential election, I think

1121
01:07:41,720 --> 01:07:44,400
Speaker 3: it's more challenging. You know, it's not only just been

1122
01:07:44,440 --> 01:07:47,800
Speaker 3: sort of a persuasion element and you know, who is

1123
01:07:47,840 --> 01:07:51,160
Speaker 3: the Democratic standard bearer for Floridians who they look at

1124
01:07:51,600 --> 01:07:54,680
Speaker 3: identify with with that party. I think that's been a challenge.

1125
01:07:54,960 --> 01:08:00,160
Speaker 3: But just out migration, the migration patterns of just and

1126
01:08:00,400 --> 01:08:03,840
Speaker 3: very difficult for Democrats, where you've had Democrats moving, especially

1127
01:08:03,880 --> 01:08:06,680
Speaker 3: during the pandemic, moving out of the state, and that

1128
01:08:06,760 --> 01:08:08,320
Speaker 3: seems to continue.

1129
01:08:08,360 --> 01:08:12,160
Speaker 1: Where really Democrats are moving out and Northeast Republicans are

1130
01:08:12,200 --> 01:08:14,480
Speaker 1: moving in basically not.

1131
01:08:14,840 --> 01:08:17,759
Speaker 2: Just northeast, but yeah, yeah, Midwest.

1132
01:08:20,360 --> 01:08:22,960
Speaker 1: So if you take the seven battleground states, and you

1133
01:08:23,040 --> 01:08:27,400
Speaker 1: take Kamala Harris's states and you put them together, the

1134
01:08:27,439 --> 01:08:30,400
Speaker 1: max number of Senate seats that Democrats could win as

1135
01:08:30,439 --> 01:08:35,920
Speaker 1: fifty two. What that tells you is they've got very

1136
01:08:35,960 --> 01:08:38,080
Speaker 1: little margin for air if they want to be competitive

1137
01:08:38,760 --> 01:08:44,120
Speaker 1: in the Senate. Now, look, both parties were so polarized,

1138
01:08:44,160 --> 01:08:46,719
Speaker 1: both parties are sort of it's very difficult to win

1139
01:08:46,760 --> 01:08:50,960
Speaker 1: a Senate seat these days. In the other side, state right,

1140
01:08:51,160 --> 01:08:55,760
Speaker 1: it's you know, Susan Collins and is probably the last

1141
01:08:55,800 --> 01:08:58,439
Speaker 1: Republican that will represent me. But you know, at least

1142
01:08:58,439 --> 01:09:01,200
Speaker 1: in at least for the foreseeable future. She may represent

1143
01:09:01,240 --> 01:09:03,280
Speaker 1: it another six years for all we know, but she's

1144
01:09:03,320 --> 01:09:06,439
Speaker 1: probably the last of her come. So the question that

1145
01:09:06,520 --> 01:09:08,559
Speaker 1: Democrats have to do they have to figure out how

1146
01:09:08,600 --> 01:09:13,760
Speaker 1: to at least have I would argue another four to

1147
01:09:13,880 --> 01:09:16,200
Speaker 1: six states where they can win Senate seats. Maybe they

1148
01:09:16,240 --> 01:09:18,560
Speaker 1: can't win it into presidential but they've got to be

1149
01:09:18,600 --> 01:09:22,080
Speaker 1: able to compete in Senate races. What are those next

1150
01:09:22,160 --> 01:09:26,040
Speaker 1: four to six that you think Democrats ought to be

1151
01:09:26,320 --> 01:09:28,240
Speaker 1: I mean, if they want to be competitive in the Senate,

1152
01:09:28,360 --> 01:09:31,080
Speaker 1: they got to start prioritizing. Now I've got some in

1153
01:09:31,120 --> 01:09:35,120
Speaker 1: my head, but I don't want to poison poison the conversation.

1154
01:09:35,200 --> 01:09:36,519
Speaker 1: So I'm curious where you go first.

1155
01:09:36,680 --> 01:09:38,639
Speaker 3: Well, well, it's a question of if you're looking at

1156
01:09:38,640 --> 01:09:41,520
Speaker 3: this from a demographic and sort of political trend perspective

1157
01:09:41,720 --> 01:09:45,960
Speaker 3: versus you know, the actual opportunities in the individual campis right,

1158
01:09:46,000 --> 01:09:47,640
Speaker 3: like we saw what, Yeah, you.

1159
01:09:47,640 --> 01:09:49,439
Speaker 1: Could make both because I look at an Ohio and

1160
01:09:49,479 --> 01:09:51,120
Speaker 1: I don't think there's much of a chance in Ohio,

1161
01:09:51,200 --> 01:09:55,320
Speaker 1: but Sharon Brown is an overperformer. So in this specific instance,

1162
01:09:56,040 --> 01:09:58,640
Speaker 1: accept the premise that Ohio this year is going to

1163
01:09:58,640 --> 01:10:03,519
Speaker 1: be competitive. I'm skeptical, but obviously he's been a you

1164
01:10:03,560 --> 01:10:06,920
Speaker 1: know the guy, the guy won nearly eight years ago.

1165
01:10:07,040 --> 01:10:08,960
Speaker 1: So yeah, no, that's right.

1166
01:10:09,000 --> 01:10:11,880
Speaker 3: I mean, look from the actual demographic trends and where

1167
01:10:11,920 --> 01:10:15,760
Speaker 3: states have gone under Donald Trump. Like bizarrely, Utah is

1168
01:10:15,760 --> 01:10:18,200
Speaker 3: one of those states that stands up. There's actually underperformed

1169
01:10:18,240 --> 01:10:20,880
Speaker 3: for Republicans, it's underperformed for Trump. It's one that has

1170
01:10:20,960 --> 01:10:24,400
Speaker 3: trended and actually does have somewhat favorable demographic trends. You

1171
01:10:24,439 --> 01:10:26,400
Speaker 3: have a big question that you have to ask yourself

1172
01:10:26,400 --> 01:10:28,439
Speaker 3: if you're trying to answer this is where do you

1173
01:10:28,479 --> 01:10:32,200
Speaker 3: think Latino voters go. Obviously, Donald Trump has driven a

1174
01:10:32,320 --> 01:10:37,479
Speaker 3: huge overperformance with Republicans among Latino voters. Do you believe

1175
01:10:37,520 --> 01:10:40,640
Speaker 3: that's something that is just related to Trump? How do

1176
01:10:40,680 --> 01:10:44,439
Speaker 3: you see what's happening with the mass deatients and very

1177
01:10:44,520 --> 01:10:47,240
Speaker 3: public authoritarian acts advice out there? And how does that

1178
01:10:47,360 --> 01:10:50,519
Speaker 3: impact that vote? Because in the end, again, Utah has

1179
01:10:52,320 --> 01:10:56,840
Speaker 3: a quick, fast growing Latino population. Texas obviously is a

1180
01:10:56,840 --> 01:11:01,040
Speaker 3: big part of that conversation and will be tested next

1181
01:11:01,120 --> 01:11:04,800
Speaker 3: year in terms of where we are. But again, if

1182
01:11:04,800 --> 01:11:09,519
Speaker 3: you look at opportunities, I agree Ohio, just from Shared

1183
01:11:09,560 --> 01:11:13,840
Speaker 3: Brown as someone who is a performer there, with a

1184
01:11:14,000 --> 01:11:18,040
Speaker 3: much more hostile environment for Republicans and Donald Trump not

1185
01:11:18,200 --> 01:11:20,439
Speaker 3: on the ballot, you have to believe he has a

1186
01:11:20,560 --> 01:11:25,120
Speaker 3: very good chance to win there. But look, you're right,

1187
01:11:25,160 --> 01:11:28,479
Speaker 3: I mean the number of opportunities for Democrats above and

1188
01:11:28,640 --> 01:11:31,639
Speaker 3: beyond those states the Vice President Harris won or those

1189
01:11:31,680 --> 01:11:35,120
Speaker 3: swing states, you know there are few and far between. Again,

1190
01:11:35,160 --> 01:11:36,600
Speaker 3: that's where you have to look at things like what

1191
01:11:36,720 --> 01:11:42,560
Speaker 3: happened in Nebraska where you had Osborne running as an independent.

1192
01:11:56,240 --> 01:11:57,840
Speaker 1: Is that a better strate? I mean, you look at

1193
01:11:57,880 --> 01:12:00,639
Speaker 1: the Plaine states, right, you look at the the northern

1194
01:12:00,720 --> 01:12:04,400
Speaker 1: tier where it wasn't that long ago where you had

1195
01:12:04,640 --> 01:12:09,000
Speaker 1: two Democratic senators from North Dakota for a brief period,

1196
01:12:09,080 --> 01:12:12,759
Speaker 1: for reasonable period of time, two Democratic senators from South Dakota,

1197
01:12:14,640 --> 01:12:19,000
Speaker 1: two Democratic senators in Montana. Is that lost for a

1198
01:12:19,040 --> 01:12:23,160
Speaker 1: generation or or is it that? And is that a

1199
01:12:23,200 --> 01:12:26,800
Speaker 1: Democratic brand issue or is it an issue? Is it?

1200
01:12:26,960 --> 01:12:29,040
Speaker 1: Is it like a specific issue that the problem that

1201
01:12:29,120 --> 01:12:29,800
Speaker 1: Democrats have?

1202
01:12:30,439 --> 01:12:32,760
Speaker 3: Yes, I don't know. I think we'll get a good

1203
01:12:32,800 --> 01:12:34,479
Speaker 3: sense of that next year. The question is, you know,

1204
01:12:34,520 --> 01:12:38,720
Speaker 3: can Democrats recruit and run populist candidates who are not

1205
01:12:38,920 --> 01:12:41,519
Speaker 3: connected to the negative brand of the party. Obviously the

1206
01:12:41,520 --> 01:12:43,720
Speaker 3: brand of the party of the Democrat Party is not

1207
01:12:43,760 --> 01:12:46,080
Speaker 3: going to turn around anytime soon in those states. But

1208
01:12:46,400 --> 01:12:49,200
Speaker 3: to your point, Democrats have had great success in the

1209
01:12:49,280 --> 01:12:53,240
Speaker 3: last two decades in those states running.

1210
01:12:53,080 --> 01:12:58,280
Speaker 1: Well, they're populous states, that's right, They're populous before their DNR, right,

1211
01:12:58,360 --> 01:13:01,280
Speaker 1: and that's what tells that's why I assume they're still

1212
01:13:01,320 --> 01:13:10,440
Speaker 1: potentially in play because they're not settled. They're culturally conservative,

1213
01:13:10,960 --> 01:13:15,680
Speaker 1: but they want an activist government. Those states benefit from

1214
01:13:15,680 --> 01:13:16,960
Speaker 1: an activist government.

1215
01:13:16,720 --> 01:13:19,720
Speaker 3: Well, and right now they're not benefiting from the activism

1216
01:13:19,760 --> 01:13:23,040
Speaker 3: of the current government. When you look at what is happening.

1217
01:13:23,120 --> 01:13:25,680
Speaker 3: You know, you can throw Iowa in there too, when

1218
01:13:25,680 --> 01:13:28,160
Speaker 3: you look at what soy being with the tariffs and

1219
01:13:29,280 --> 01:13:36,080
Speaker 3: negatively impacted these populations have been under this presidency, and

1220
01:13:36,360 --> 01:13:40,040
Speaker 3: then not just the tariffs, obviously, just through federal grants

1221
01:13:40,120 --> 01:13:42,439
Speaker 3: for farms and that sort of thing. It's had an

1222
01:13:42,479 --> 01:13:45,880
Speaker 3: overwhelmingly negative impact. And so for Democrats to test this,

1223
01:13:45,960 --> 01:13:47,880
Speaker 3: they're going to need to run candidates who can run

1224
01:13:47,920 --> 01:13:51,960
Speaker 3: on that populous message, who have some credibility and that perspective,

1225
01:13:52,040 --> 01:13:55,479
Speaker 3: and obviously rely on this still being forefront of their

1226
01:13:55,560 --> 01:13:59,840
Speaker 3: minds and Trump and not doing a turnaround in the

1227
01:14:00,000 --> 01:14:00,800
Speaker 3: next couple of years.

1228
01:14:00,800 --> 01:14:05,000
Speaker 1: Here some of this, you know, sometimes you got to

1229
01:14:05,000 --> 01:14:08,679
Speaker 1: do triage. What what blue states? You know, the thing

1230
01:14:08,760 --> 01:14:11,920
Speaker 1: that made the popular vote go Trump's direction was not

1231
01:14:12,040 --> 01:14:15,240
Speaker 1: the seven battleground states. It was the fact that Illinois,

1232
01:14:15,560 --> 01:14:20,519
Speaker 1: New Jersey right were four point races five point races.

1233
01:14:20,560 --> 01:14:26,559
Speaker 1: You're like, whoa right of the blue states? Where should

1234
01:14:26,560 --> 01:14:33,559
Speaker 1: the party be? Hey, don't drop the ball here. I've

1235
01:14:33,600 --> 01:14:35,519
Speaker 1: always had New Jersey to me is at the top

1236
01:14:35,560 --> 01:14:38,799
Speaker 1: of the list. But but what after New I assume

1237
01:14:38,840 --> 01:14:40,519
Speaker 1: you agree on that on New Jersey where else would

1238
01:14:40,560 --> 01:14:43,719
Speaker 1: you be telling the party, hey, you know you better

1239
01:14:44,000 --> 01:14:46,040
Speaker 1: you better keep a better eye out on here, and

1240
01:14:46,040 --> 01:14:48,479
Speaker 1: you better do a little more a little more work.

1241
01:14:48,840 --> 01:14:49,600
Speaker 2: Well, you know.

1242
01:14:49,640 --> 01:14:53,320
Speaker 3: To me, this is an interesting dynamic because it illuminates

1243
01:14:53,360 --> 01:14:56,360
Speaker 3: the problem with you know, I think where the party

1244
01:14:56,520 --> 01:14:59,360
Speaker 3: brand identity issue that we've been talking about actually has

1245
01:14:59,400 --> 01:15:01,759
Speaker 3: a bigger impat is in these states. Because I mentioned

1246
01:15:01,800 --> 01:15:04,799
Speaker 3: how when you look at the turnout data in twenty

1247
01:15:04,800 --> 01:15:07,040
Speaker 3: twenty four relative twenty twenty in the battleground states, there

1248
01:15:07,080 --> 01:15:08,599
Speaker 3: was almost no difference between those.

1249
01:15:09,000 --> 01:15:10,240
Speaker 2: It was just it was minimal.

1250
01:15:10,840 --> 01:15:13,719
Speaker 1: But we had no difference in three straight elections, right,

1251
01:15:14,000 --> 01:15:16,760
Speaker 1: that's sixteen, twenty and twenty four. They were more the

1252
01:15:16,880 --> 01:15:18,759
Speaker 1: same than different those seven states.

1253
01:15:18,840 --> 01:15:22,880
Speaker 3: Yeah, but where the turnout truly created for Democrats was

1254
01:15:22,920 --> 01:15:25,519
Speaker 3: in these blue states and especially these Northeastern and mid

1255
01:15:25,560 --> 01:15:31,639
Speaker 3: Atlantic states, where democratic turnout was just abysmal. New Jersey

1256
01:15:31,680 --> 01:15:33,840
Speaker 3: actually had a little bit of both, where it had

1257
01:15:33,840 --> 01:15:36,280
Speaker 3: a cratering of democratic turnout and it also had these

1258
01:15:36,360 --> 01:15:39,240
Speaker 3: unaffiliated voters who were more fiscally sensitive in New Jersey

1259
01:15:39,280 --> 01:15:41,760
Speaker 3: than probably any other state. A lot of that just

1260
01:15:41,840 --> 01:15:47,280
Speaker 3: due to property taxes. Sure, but that drove the massive

1261
01:15:47,360 --> 01:15:50,519
Speaker 3: underperformance of Vice President Harris in those states, and so

1262
01:15:50,800 --> 01:15:52,160
Speaker 3: you know, I don't look at any of those at

1263
01:15:52,160 --> 01:15:54,880
Speaker 3: this point and say Republicans are poised to turn this

1264
01:15:55,040 --> 01:15:59,360
Speaker 3: into a longer term trend. Sure, mobilization worries me less

1265
01:15:59,439 --> 01:16:03,240
Speaker 3: than because mobilization is something that can be fixed with

1266
01:16:03,320 --> 01:16:06,439
Speaker 3: a single campaign and a single cycle. Persuasion can as well,

1267
01:16:06,479 --> 01:16:09,840
Speaker 3: but it's it's tougher. And so again, it's not to

1268
01:16:09,880 --> 01:16:12,920
Speaker 3: say that Republicans won't have opportunities in these states, but

1269
01:16:12,960 --> 01:16:15,840
Speaker 3: if we're looking at it now holistically, there's not a state,

1270
01:16:16,240 --> 01:16:18,360
Speaker 3: a blue state that I look at and say, well, gosh,

1271
01:16:18,400 --> 01:16:21,240
Speaker 3: this is one where we're certainly going to be in

1272
01:16:21,280 --> 01:16:24,120
Speaker 3: trouble and other than sort of generically, again, if we

1273
01:16:24,160 --> 01:16:27,280
Speaker 3: want to look at where their potential liability from Democratic

1274
01:16:27,439 --> 01:16:31,439
Speaker 3: brand identity issues, it's going to be universally across these states.

1275
01:16:32,280 --> 01:16:34,680
Speaker 1: Two of the battleground states where Democrats have had an

1276
01:16:34,880 --> 01:16:38,840
Speaker 1: enormous amount of success are Georgia and Arizona. These are

1277
01:16:38,840 --> 01:16:42,719
Speaker 1: two states that Barack Obama could never carry. He'd come close,

1278
01:16:43,600 --> 01:16:47,439
Speaker 1: he'd make them more competitive, but there were you know,

1279
01:16:48,760 --> 01:16:54,439
Speaker 1: couldn't win any races in those states. Are they just

1280
01:16:54,600 --> 01:16:59,840
Speaker 1: uniquely allergic to Trump. Is this the suburban switch? And

1281
01:17:00,120 --> 01:17:02,200
Speaker 1: those two states with just you know, I always said

1282
01:17:02,200 --> 01:17:06,120
Speaker 1: Phoenix is America's largest suburb, right in Atlanta arguably a

1283
01:17:06,120 --> 01:17:09,040
Speaker 1: close second. You know, they're just two. Is it due

1284
01:17:09,080 --> 01:17:12,800
Speaker 1: to the suburban shift to the Democrats that those two

1285
01:17:12,840 --> 01:17:16,400
Speaker 1: states in particular basically went from red to battleground.

1286
01:17:17,600 --> 01:17:21,320
Speaker 3: There's a few dynamics at play in both of those states.

1287
01:17:21,800 --> 01:17:24,320
Speaker 3: You know, certainly that suburban shift is a big part

1288
01:17:24,360 --> 01:17:28,920
Speaker 3: of it. They just have a fairly significant, well educated

1289
01:17:29,720 --> 01:17:33,479
Speaker 3: white voter population, these voters who have swung since Trump

1290
01:17:33,920 --> 01:17:36,479
Speaker 3: emerged onto the scene towards Democrats, and so that's a

1291
01:17:36,479 --> 01:17:40,040
Speaker 3: big part of it. Another thing is Asian American voters

1292
01:17:40,080 --> 01:17:47,360
Speaker 3: API voters in Georgia, massive, massively fast growing era of

1293
01:17:47,400 --> 01:17:49,400
Speaker 3: the electorate. There just when you look at the difference

1294
01:17:49,439 --> 01:17:52,360
Speaker 3: between twenty sixteen and twenty twenty, where Hillary Clinton lost

1295
01:17:52,360 --> 01:17:55,880
Speaker 3: the state and Joe Biden won it, that margin swing

1296
01:17:56,000 --> 01:18:00,280
Speaker 3: was almost entirely defined just by not just population but

1297
01:18:00,400 --> 01:18:03,160
Speaker 3: turnout and growth among API voters. Now, it's worth noting

1298
01:18:03,439 --> 01:18:07,160
Speaker 3: the same AAPI voters swung towards Trump in twenty twenty four,

1299
01:18:07,439 --> 01:18:09,960
Speaker 3: and then the Poles are now swinging back against so

1300
01:18:10,320 --> 01:18:13,120
Speaker 3: perhaps an emerging swing group. They're not as many of

1301
01:18:13,160 --> 01:18:16,200
Speaker 3: those API voters in Arizona as are in Georgia, but

1302
01:18:16,280 --> 01:18:19,040
Speaker 3: still an significant element. And then I think in terms

1303
01:18:19,080 --> 01:18:22,479
Speaker 3: of Latino voters, Trump didn't get the same sort of

1304
01:18:22,560 --> 01:18:25,920
Speaker 3: swing from Latino voters in those states as he got

1305
01:18:26,040 --> 01:18:30,439
Speaker 3: in some other states like Nevada, Lan Texas, Florida, And

1306
01:18:30,479 --> 01:18:32,160
Speaker 3: so that's part of the recipe as well.

1307
01:18:32,840 --> 01:18:35,040
Speaker 1: I mean, not to oversimplify this, but you know what

1308
01:18:35,080 --> 01:18:38,439
Speaker 1: you're describing in both and what you see, and I

1309
01:18:38,520 --> 01:18:42,240
Speaker 1: just feel like that Latino voters that Democrats assumed that

1310
01:18:42,960 --> 01:18:46,040
Speaker 1: Obama's percentage was their percentage, when when you look at

1311
01:18:46,040 --> 01:18:49,479
Speaker 1: these first gen and second gen voters, they're just more

1312
01:18:49,479 --> 01:18:53,920
Speaker 1: economic sense, they're economically sensitive, and to me, they behave

1313
01:18:54,080 --> 01:18:57,559
Speaker 1: just like regular old swing voters, because swing voters are

1314
01:18:57,640 --> 01:18:59,720
Speaker 1: usually economically sensitive.

1315
01:18:59,520 --> 01:18:59,960
Speaker 2: That's right.

1316
01:19:00,120 --> 01:19:02,280
Speaker 3: And that's where I think that you know, the pandemic

1317
01:19:02,360 --> 01:19:05,439
Speaker 3: had a huge impact. It's why you saw some of

1318
01:19:05,479 --> 01:19:08,000
Speaker 3: these bigger swings in the Rio Grand Valley is because

1319
01:19:08,080 --> 01:19:11,000
Speaker 3: the way that especially the hospitality industry was hit by

1320
01:19:11,040 --> 01:19:15,599
Speaker 3: the pandemic in the closures and yeah, I mean these

1321
01:19:15,640 --> 01:19:19,720
Speaker 3: are Hispanic voters are are they very much meet the

1322
01:19:19,720 --> 01:19:22,120
Speaker 3: profile of swing voters. I do think you're seeing that

1323
01:19:22,200 --> 01:19:25,599
Speaker 3: acknowledged by these campaigns now where you know, I think

1324
01:19:25,640 --> 01:19:27,800
Speaker 3: for a while Democrats were perhaps making the mistake of

1325
01:19:27,840 --> 01:19:31,120
Speaker 3: treating Hispanic voters as if they were only mobilization targets

1326
01:19:31,160 --> 01:19:32,880
Speaker 3: and price.

1327
01:19:33,000 --> 01:19:36,760
Speaker 1: And frankly talking the wrong issue. That's right, Immigration was

1328
01:19:36,800 --> 01:19:42,080
Speaker 1: not the number one issue among these voters. Four years ago,

1329
01:19:42,160 --> 01:19:44,960
Speaker 1: I operated on the thesis that Trump was a temporary

1330
01:19:46,120 --> 01:19:48,960
Speaker 1: brand for the Republicans and that when the quote unquote

1331
01:19:49,880 --> 01:19:52,880
Speaker 1: Chamber of Commerce brand came back, you know, it would

1332
01:19:52,920 --> 01:19:56,160
Speaker 1: bring us to I always said Colorado and Virginia. You

1333
01:19:56,160 --> 01:19:58,519
Speaker 1: look at a Glenn Youngkin, You're like, Glenn Youngkin can

1334
01:19:58,600 --> 01:20:01,560
Speaker 1: succeed in both the Colorado Virginia, Right, the sort of

1335
01:20:01,640 --> 01:20:06,519
Speaker 1: the Chamber of Commerce type pitch. I'm less sure now.

1336
01:20:06,560 --> 01:20:08,800
Speaker 1: I mean, I think the I think once you have

1337
01:20:08,840 --> 01:20:13,320
Speaker 1: a second term that it probably defines that Trump's now

1338
01:20:13,880 --> 01:20:17,080
Speaker 1: it's Trump's party. He's not borrowing the party anymore, right,

1339
01:20:17,160 --> 01:20:22,320
Speaker 1: he has molded the party. Is that wing. Is that

1340
01:20:22,360 --> 01:20:27,000
Speaker 1: wing of the party just dormant, dead, no longer registered Republicans.

1341
01:20:27,000 --> 01:20:30,519
Speaker 1: I mean the Paul Ryan Wing. Are they now registering

1342
01:20:30,520 --> 01:20:31,200
Speaker 1: as independent?

1343
01:20:32,840 --> 01:20:35,919
Speaker 3: I think it's a big question of to what extent

1344
01:20:36,240 --> 01:20:38,760
Speaker 3: Republicans who are not Trump are able to pull it

1345
01:20:38,960 --> 01:20:42,840
Speaker 3: off a convincing enough impersonation of him to be able

1346
01:20:42,880 --> 01:20:46,120
Speaker 3: to have electoral success. Because I agree, don't. I don't

1347
01:20:46,160 --> 01:20:49,400
Speaker 3: see a world where the party goes back to where they.

1348
01:20:49,280 --> 01:20:51,720
Speaker 1: Were before now right away. I mean, you're certainly not.

1349
01:20:51,840 --> 01:20:53,600
Speaker 1: You know, it's going to take an election cycle or

1350
01:20:53,640 --> 01:20:54,479
Speaker 1: two before they would.

1351
01:20:54,680 --> 01:20:59,440
Speaker 3: It'll take them losing badly in elections with not convincing

1352
01:20:59,560 --> 01:21:02,720
Speaker 3: enough Trump like clone. You know, when you look at

1353
01:21:02,760 --> 01:21:07,760
Speaker 3: twenty twenty two, perhaps that is indicative of how the

1354
01:21:07,800 --> 01:21:14,439
Speaker 3: party could free itself of Trump's shadow, in that you

1355
01:21:14,640 --> 01:21:17,320
Speaker 3: had a lot of Republican candidates for the Senate who

1356
01:21:17,360 --> 01:21:19,760
Speaker 3: are running as Trump clones, whether it was you know,

1357
01:21:19,800 --> 01:21:23,240
Speaker 3: doctor Oz and Pennsylvania. You go across these these races

1358
01:21:23,280 --> 01:21:26,000
Speaker 3: that they should have won based on the history of

1359
01:21:26,040 --> 01:21:31,160
Speaker 3: midterm elections credit president who was historically unpopular. They should

1360
01:21:31,160 --> 01:21:32,880
Speaker 3: have won them, but they didn't win them because of

1361
01:21:32,880 --> 01:21:38,040
Speaker 3: these candidates, Herschelwalker being another one, you know, and all

1362
01:21:38,120 --> 01:21:40,880
Speaker 3: races that they should have won and they didn't. So

1363
01:21:41,479 --> 01:21:44,360
Speaker 3: post Trump, are they able to find candidates who can

1364
01:21:44,360 --> 01:21:48,280
Speaker 3: pull off more convincing impersonations. Then I think it's it's

1365
01:21:48,280 --> 01:21:52,040
Speaker 3: stickier because from a primary perspective, it's the way you

1366
01:21:52,160 --> 01:21:54,439
Speaker 3: win a Republican primary now, and I don't expect that

1367
01:21:54,520 --> 01:21:59,799
Speaker 3: to change. Can they Can they win general elections without

1368
01:22:00,040 --> 01:22:03,920
Speaker 3: one named Donald Trump on the ballot with that mega mentality?

1369
01:22:03,920 --> 01:22:05,800
Speaker 3: I'm just not so sure, all right?

1370
01:22:06,080 --> 01:22:10,839
Speaker 1: With the last minute or two here the stay polling,

1371
01:22:11,479 --> 01:22:15,160
Speaker 1: I'm a I'm generally bullish on polling, meaning I kind

1372
01:22:15,160 --> 01:22:18,360
Speaker 1: of think that people. I hate the averaging of polls

1373
01:22:18,400 --> 01:22:22,120
Speaker 1: because I think it's created the illusion of accuracy when

1374
01:22:22,160 --> 01:22:25,320
Speaker 1: a poll is there to essentially give you an estimate

1375
01:22:25,920 --> 01:22:28,600
Speaker 1: and it's you know, if you just pay attention to

1376
01:22:28,640 --> 01:22:30,680
Speaker 1: margins of error. Polling has been fine over the last

1377
01:22:30,720 --> 01:22:33,960
Speaker 1: ten years. The problem is we have this, you know,

1378
01:22:34,040 --> 01:22:36,320
Speaker 1: real clear politics in five point thirty eight gave us

1379
01:22:36,360 --> 01:22:40,479
Speaker 1: the the the somehow the illusion that there was there

1380
01:22:40,560 --> 01:22:44,120
Speaker 1: was pure accuracy in what was a freaking survey. Okay,

1381
01:22:44,479 --> 01:22:47,000
Speaker 1: so it that would drive me bonkers. And that's why

1382
01:22:47,040 --> 01:22:50,679
Speaker 1: I hate pull, averaging and all of those things. All

1383
01:22:50,720 --> 01:22:55,080
Speaker 1: that said, what's your preferred methodology to get up these days?

1384
01:22:55,080 --> 01:22:59,320
Speaker 1: In order to feel like you've got a good handle

1385
01:23:00,080 --> 01:23:03,519
Speaker 1: on public opinion research. What kind of methodology are you

1386
01:23:03,560 --> 01:23:06,679
Speaker 1: looking for these days compared to save twenty years ago.

1387
01:23:07,080 --> 01:23:09,719
Speaker 3: Well, and I agree with everything you said in terms

1388
01:23:09,760 --> 01:23:11,719
Speaker 3: of the state of polling, and I think polsters should

1389
01:23:11,720 --> 01:23:15,800
Speaker 3: be applauded because they've adapted and evolved quite admirably.

1390
01:23:16,360 --> 01:23:16,599
Speaker 1: Great.

1391
01:23:17,360 --> 01:23:17,840
Speaker 2: It's hard.

1392
01:23:18,920 --> 01:23:19,960
Speaker 1: It's never been harder.

1393
01:23:20,200 --> 01:23:22,559
Speaker 2: No, it's never been harder, and it just keeps getting harder.

1394
01:23:22,600 --> 01:23:27,479
Speaker 3: You know, Apple putting into place a date that'll make

1395
01:23:27,520 --> 01:23:29,920
Speaker 3: things even harder for bolsters because the call just be

1396
01:23:29,960 --> 01:23:31,360
Speaker 3: funneled right to junk folders.

1397
01:23:31,400 --> 01:23:33,200
Speaker 2: So you know what I look for.

1398
01:23:34,360 --> 01:23:38,439
Speaker 3: Mixed mode survey data collection is incredibly important now. I

1399
01:23:38,439 --> 01:23:39,920
Speaker 3: think it's one of the things that we learned. And

1400
01:23:39,960 --> 01:23:42,439
Speaker 3: again I think most polsters are doing a great job.

1401
01:23:42,520 --> 01:23:42,840
Speaker 2: So they are.

1402
01:23:43,160 --> 01:23:44,960
Speaker 1: We put that in a little bit of American for people.

1403
01:23:45,040 --> 01:23:48,360
Speaker 1: Mixed mode for those that don't follow the industry means what.

1404
01:23:48,760 --> 01:23:52,280
Speaker 3: So that means they're collecting data by not just one method.

1405
01:23:52,439 --> 01:23:56,320
Speaker 3: So they're texting people, they're doing online surveys, they're calling people,

1406
01:23:56,400 --> 01:24:00,400
Speaker 3: they're calling their landline. Some people still into landline.

1407
01:24:00,000 --> 01:24:03,920
Speaker 1: So they're almost picking a mode based on the demographic preference. Right,

1408
01:24:03,960 --> 01:24:06,519
Speaker 1: if you know younger people prefer text a web, then

1409
01:24:06,560 --> 01:24:09,120
Speaker 1: you text a web. Everybody under the age of thirty, right,

1410
01:24:09,800 --> 01:24:11,759
Speaker 1: landlines over the age of seventy, etcetera.

1411
01:24:11,920 --> 01:24:14,479
Speaker 3: Right, Every mode has its bias, and so if you

1412
01:24:14,520 --> 01:24:17,440
Speaker 3: can collect data through multiple modes, it gets more expensive.

1413
01:24:17,560 --> 01:24:22,080
Speaker 3: But you look at most accurate polsters. That's that's what

1414
01:24:22,120 --> 01:24:23,920
Speaker 3: they're doing at this point, and I think you're just

1415
01:24:24,000 --> 01:24:26,719
Speaker 3: going to see You're going to see more of.

1416
01:24:26,640 --> 01:24:27,240
Speaker 2: That going forward.

1417
01:24:27,320 --> 01:24:29,000
Speaker 3: I will say, you know, the other thing that drives

1418
01:24:29,040 --> 01:24:32,040
Speaker 3: me crazy with the polling, beyond the averaging of poles

1419
01:24:32,840 --> 01:24:34,759
Speaker 3: is the cross tab diving.

1420
01:24:35,240 --> 01:24:38,679
Speaker 1: Oh my god, that's it. That's worse s right, Like, oh,

1421
01:24:38,920 --> 01:24:39,679
Speaker 1: don't do that.

1422
01:24:41,080 --> 01:24:44,960
Speaker 3: You know, we'll see movement among independent white women in

1423
01:24:45,040 --> 01:24:47,639
Speaker 3: one state between one pole and another, and then write

1424
01:24:47,680 --> 01:24:49,760
Speaker 3: a front page story about how they moved. And the

1425
01:24:49,760 --> 01:24:53,120
Speaker 3: reality is none of that has the level of fidelity

1426
01:24:53,200 --> 01:24:56,160
Speaker 3: that we could, you know, provide that level of credit.

1427
01:24:56,200 --> 01:24:57,920
Speaker 1: We used to have a rule at the NBC News

1428
01:24:57,920 --> 01:25:02,000
Speaker 1: pole and a journal pole and Hart mcinturf are both

1429
01:25:02,120 --> 01:25:04,720
Speaker 1: like this, two poles in a row and a subgroup.

1430
01:25:05,120 --> 01:25:07,439
Speaker 1: Don't go crazy when you see a switch two poles

1431
01:25:07,479 --> 01:25:09,920
Speaker 1: in a row, and that was always the rule. We

1432
01:25:10,000 --> 01:25:12,880
Speaker 1: did not ever write about a swing until we saw

1433
01:25:12,920 --> 01:25:16,479
Speaker 1: two poles in a row. You know, even then, you

1434
01:25:16,520 --> 01:25:18,760
Speaker 1: know you're talking about a subset of eighty to one

1435
01:25:18,800 --> 01:25:21,840
Speaker 1: hundred and twenty. You know, on some of these demographics

1436
01:25:22,880 --> 01:25:23,479
Speaker 1: cross tabs.

1437
01:25:23,520 --> 01:25:26,120
Speaker 2: But anyway, only everyone would follow your lead on that.

1438
01:25:27,240 --> 01:25:29,960
Speaker 1: It's fair enough, and let me get out, get you

1439
01:25:29,960 --> 01:25:31,800
Speaker 1: out in here on this. What's the three public the

1440
01:25:31,880 --> 01:25:35,000
Speaker 1: non partisan polls that you're like when they come out?

1441
01:25:35,360 --> 01:25:38,040
Speaker 1: I read it all. I read all of it. I

1442
01:25:38,120 --> 01:25:39,400
Speaker 1: go into the demos and everything.

1443
01:25:39,479 --> 01:25:40,400
Speaker 2: Who are you know?

1444
01:25:40,439 --> 01:25:43,120
Speaker 3: What's funny is is I have spent less and less

1445
01:25:43,160 --> 01:25:45,439
Speaker 3: time this year digging into the polls, which I think

1446
01:25:45,479 --> 01:25:46,439
Speaker 3: has beeny for me.

1447
01:25:46,600 --> 01:25:47,880
Speaker 2: But you know, look, I.

1448
01:25:49,880 --> 01:25:51,880
Speaker 3: Love the New York Times polls. I don't love how

1449
01:25:51,920 --> 01:25:54,600
Speaker 3: people sometimes cover them or how they digest them, but

1450
01:25:54,640 --> 01:25:56,320
Speaker 3: I think they do an incredible job.

1451
01:25:56,439 --> 01:25:59,960
Speaker 1: I love I love their transparency, that's right, I mean

1452
01:26:00,120 --> 01:26:04,320
Speaker 1: their analysis. It's funny how a couple of times they've

1453
01:26:04,400 --> 01:26:08,479
Speaker 1: literally been your poll told you the answer and you

1454
01:26:08,560 --> 01:26:12,840
Speaker 1: didn't write it. But anyway, I agree their transparency I

1455
01:26:13,000 --> 01:26:13,839
Speaker 1: should be commended.

1456
01:26:14,080 --> 01:26:16,320
Speaker 3: I've mentioned the navigator surveys. I think they do a

1457
01:26:16,320 --> 01:26:18,120
Speaker 3: great job, you know. I mean that I think we

1458
01:26:18,160 --> 01:26:20,360
Speaker 3: get a little bit too obsessed about who was the

1459
01:26:20,400 --> 01:26:22,600
Speaker 3: accurate polster last time. You have a whole bunch of

1460
01:26:22,600 --> 01:26:26,720
Speaker 3: polsters who tend to have out outcomes that are more Republican.

1461
01:26:27,280 --> 01:26:30,160
Speaker 3: You have some that are reliably more democratic. And if

1462
01:26:30,200 --> 01:26:32,880
Speaker 3: the election swings one way, then those polsters look good,

1463
01:26:32,880 --> 01:26:34,920
Speaker 3: and if it swings the other way, look good.

1464
01:26:34,960 --> 01:26:35,800
Speaker 2: And I think we need to.

1465
01:26:35,880 --> 01:26:39,720
Speaker 1: I just want consistency, Like I know, quinnip X consistent.

1466
01:26:39,880 --> 01:26:42,759
Speaker 1: I think they have a bit of a lien. They're consistent. Emerson,

1467
01:26:43,360 --> 01:26:44,680
Speaker 1: I think they have a bit of a lien, but

1468
01:26:44,680 --> 01:26:47,960
Speaker 1: it's consistent. Like, as long as it's consistent, then I

1469
01:26:47,960 --> 01:26:50,320
Speaker 1: can I do my own math. All right, I'm gonna

1470
01:26:50,320 --> 01:26:52,320
Speaker 1: add to or I'm going to subtract to or whatever

1471
01:26:52,360 --> 01:26:57,320
Speaker 1: it is, and that's where I go. But but that's usually,

1472
01:26:57,360 --> 01:26:59,200
Speaker 1: I'm sure what you look for consistency.

1473
01:26:59,320 --> 01:27:01,000
Speaker 3: Yeah, no, that's a exactly right. You need to be

1474
01:27:01,040 --> 01:27:03,800
Speaker 3: able to make some of your own mental adjustments.

1475
01:27:03,160 --> 01:27:04,360
Speaker 2: And calculations for sure.

1476
01:27:04,439 --> 01:27:07,200
Speaker 1: Yeah, Tom ban here, this was appreciate you gecking out

1477
01:27:07,200 --> 01:27:12,360
Speaker 1: with me, and uh, we'll see how the vote. Do

1478
01:27:12,400 --> 01:27:15,600
Speaker 1: you see evidence that that that the party is throwing

1479
01:27:15,800 --> 01:27:17,799
Speaker 1: real energy in voter registration yet.

1480
01:27:17,720 --> 01:27:19,960
Speaker 3: Or not, Well, you're seeing it, and again you're seeing

1481
01:27:20,680 --> 01:27:23,559
Speaker 3: you're seeing more of these outside groups that have existed

1482
01:27:23,560 --> 01:27:25,800
Speaker 3: that had success last time around are doing it too

1483
01:27:25,840 --> 01:27:30,040
Speaker 3: in terms of party party doing and registration. I will say, uh,

1484
01:27:30,479 --> 01:27:33,120
Speaker 3: I've heard a lot more talk about that happening, a

1485
01:27:33,160 --> 01:27:36,000
Speaker 3: lot more people pushing for that happening. I believe you

1486
01:27:36,040 --> 01:27:38,320
Speaker 3: will see investment from the party and that as we

1487
01:27:38,360 --> 01:27:40,080
Speaker 3: get into the midterm elections next week.

1488
01:27:40,880 --> 01:27:44,719
Speaker 1: I'd imagine they want to show something on that front,

1489
01:27:44,760 --> 01:27:47,120
Speaker 1: that's for sure. Tom, appreciate the time, great to talk

1490
01:27:47,160 --> 01:28:01,280
Speaker 1: with you. Thank you well if you enjoyed that deep

1491
01:28:01,360 --> 01:28:07,559
Speaker 1: dive into data voter registration issues inside on the left

1492
01:28:07,560 --> 01:28:10,639
Speaker 1: hand side of the aisle these days, what states are

1493
01:28:10,800 --> 01:28:15,800
Speaker 1: moving in which direction, what we're watching for, And it's

1494
01:28:15,840 --> 01:28:19,360
Speaker 1: just a reminder we've got an election night coming up,

1495
01:28:19,400 --> 01:28:22,479
Speaker 1: and less less than a month I'm going to have

1496
01:28:22,479 --> 01:28:25,160
Speaker 1: some special election night plans to be sharing with you

1497
01:28:25,720 --> 01:28:28,200
Speaker 1: right here very soon. We're very excited about it here

1498
01:28:28,280 --> 01:28:33,360
Speaker 1: at the worldwide headquarters of the Chuck Podcast, and it

1499
01:28:33,360 --> 01:28:37,360
Speaker 1: will be it will be fascinating. But New Jersey is

1500
01:28:39,439 --> 01:28:41,519
Speaker 1: going to be the first place where we find out,

1501
01:28:41,840 --> 01:28:45,360
Speaker 1: you know, is a new Trump coalition. Is there a

1502
01:28:45,360 --> 01:28:48,760
Speaker 1: real realignment here that took place, or was some of

1503
01:28:48,800 --> 01:28:51,479
Speaker 1: this shift to Trump even in some blue states like

1504
01:28:52,120 --> 01:28:56,280
Speaker 1: New Jersey more of a unique twenty twenty four thing

1505
01:28:56,320 --> 01:28:59,880
Speaker 1: and more of a phenomenon about the Biden Harris administration.

1506
01:29:00,080 --> 01:29:02,400
Speaker 1: So that will be a telltale sign here. So it

1507
01:29:02,479 --> 01:29:09,080
Speaker 1: is Wednesday, which means I have a top five list.

1508
01:29:04,680 --> 01:29:10,000
Speaker 3: Top top top.

1509
01:29:12,520 --> 01:29:14,479
Speaker 1: I thought I have a little a little more fun.

1510
01:29:14,520 --> 01:29:16,639
Speaker 1: I do want to have, you know, monthly check ins

1511
01:29:16,720 --> 01:29:20,800
Speaker 1: on my top five Senate race flips, my top five

1512
01:29:20,880 --> 01:29:23,120
Speaker 1: governor's race flips. But in this one, I decided to

1513
01:29:23,120 --> 01:29:30,960
Speaker 1: do a top five list on comebacks. On political comebacks

1514
01:29:31,240 --> 01:29:34,240
Speaker 1: of possible, there's sort of five political comebacks that I

1515
01:29:34,320 --> 01:29:38,840
Speaker 1: think are reasonably viable. These are people essentially running to

1516
01:29:39,000 --> 01:29:43,519
Speaker 1: reclaim an office that they once held. I believe in

1517
01:29:43,640 --> 01:29:47,280
Speaker 1: just about every one of these scenarios, these folks lost

1518
01:29:47,560 --> 01:29:50,920
Speaker 1: or were pushed out for a variety for a variety

1519
01:29:50,960 --> 01:29:54,400
Speaker 1: of reasons. So my top five list is top five.

1520
01:29:54,520 --> 01:29:58,000
Speaker 1: So Andrew Cuomo's doesn't make this list because he never

1521
01:29:58,160 --> 01:30:01,840
Speaker 1: served as mayor. So yes, it's a political comeback, but

1522
01:30:01,880 --> 01:30:05,559
Speaker 1: he's not trying to run for the same office. But

1523
01:30:05,640 --> 01:30:10,640
Speaker 1: there is somebody in my top five list that I

1524
01:30:10,680 --> 01:30:12,720
Speaker 1: will get to. He's in my fifth slot that is

1525
01:30:12,840 --> 01:30:16,840
Speaker 1: running for his old office in twenty twenty five, and

1526
01:30:16,880 --> 01:30:20,280
Speaker 1: we will find out in a mere three weeks, perhaps

1527
01:30:20,320 --> 01:30:23,720
Speaker 1: a month later due to runoffs the runoff rules in

1528
01:30:23,760 --> 01:30:27,160
Speaker 1: said city, where we'll see if that comeback. It's a

1529
01:30:27,240 --> 01:30:30,960
Speaker 1: unique comeback opportunity. But here it is my top five

1530
01:30:32,200 --> 01:30:35,720
Speaker 1: most likely political comebacks where this person can win back

1531
01:30:35,760 --> 01:30:39,200
Speaker 1: a seat they once held and they're essentially running for

1532
01:30:39,400 --> 01:30:42,519
Speaker 1: their old office. Number one on that list somebody with

1533
01:30:42,560 --> 01:30:45,320
Speaker 1: a very famous name that has a junior next to it.

1534
01:30:45,320 --> 01:30:49,880
Speaker 1: It is Jesse Jackson junior. He of course had his

1535
01:30:50,080 --> 01:30:53,880
Speaker 1: own problems that led him to have to serve time.

1536
01:30:54,439 --> 01:30:59,600
Speaker 1: He essentially was misusing campaign funds for personal gain and

1537
01:30:59,640 --> 01:31:01,599
Speaker 1: had to pay a price for that. He served his time,

1538
01:31:01,840 --> 01:31:04,760
Speaker 1: and he now wants to run for office again, and

1539
01:31:04,800 --> 01:31:08,200
Speaker 1: in fact, he has an open house seat to run

1540
01:31:08,280 --> 01:31:11,479
Speaker 1: for in his community. His brother, by the way, does

1541
01:31:11,520 --> 01:31:14,760
Speaker 1: serve in Congress right now, but he wants to He's

1542
01:31:14,760 --> 01:31:17,400
Speaker 1: going to run in the second congressional district in Illinois.

1543
01:31:17,439 --> 01:31:21,679
Speaker 1: It's the seat being vacated by congress by Robin Kelly,

1544
01:31:21,680 --> 01:31:25,719
Speaker 1: who is running in that very crowded us Centate primary

1545
01:31:25,720 --> 01:31:30,040
Speaker 1: to replace the retiring Dick Durbin. Look, I think Jackson Junior,

1546
01:31:30,479 --> 01:31:33,759
Speaker 1: the Jackson name, the Jackson political operation is very formidable

1547
01:31:33,800 --> 01:31:37,200
Speaker 1: in the Chicago area. The Jackson name means quite a

1548
01:31:37,240 --> 01:31:44,360
Speaker 1: bit in a positive in many communities in Chicago. How

1549
01:31:44,439 --> 01:31:49,120
Speaker 1: he how he asks for forgiveness will matter, and in

1550
01:31:49,160 --> 01:31:53,559
Speaker 1: his comeback bit he has spoken with with so far,

1551
01:31:53,680 --> 01:31:56,040
Speaker 1: I think with a reasonable amount of humble buy that

1552
01:31:56,160 --> 01:32:00,760
Speaker 1: he's been eating with it. And so I of all

1553
01:32:00,800 --> 01:32:04,280
Speaker 1: the comeback bits in fact that I'm going to highlight here,

1554
01:32:04,320 --> 01:32:06,920
Speaker 1: I think he's the only one that's going to end

1555
01:32:07,000 --> 01:32:09,439
Speaker 1: up back in the office that he wants out. I

1556
01:32:09,520 --> 01:32:12,479
Speaker 1: think he is the best shot of anybody obviously, why

1557
01:32:12,479 --> 01:32:15,080
Speaker 1: I put him number one, So Jesse Jackson Junior, I

1558
01:32:15,120 --> 01:32:18,240
Speaker 1: think number one on the list of most likely to

1559
01:32:18,280 --> 01:32:21,280
Speaker 1: get their old job back on that front, So number

1560
01:32:21,320 --> 01:32:24,800
Speaker 1: two on that list is going to be I'm putting

1561
01:32:24,800 --> 01:32:27,800
Speaker 1: Corey Bush. She is running for her old seatback against

1562
01:32:27,800 --> 01:32:29,880
Speaker 1: the person that defeated her in her primary in Wesley Bell.

1563
01:32:30,600 --> 01:32:34,479
Speaker 1: I think sort of the reason. Do I think she

1564
01:32:34,760 --> 01:32:38,280
Speaker 1: ends up losing? I do. I think it was a

1565
01:32:38,320 --> 01:32:41,519
Speaker 1: bit of her style that rubbed her constituents the wrong way.

1566
01:32:41,600 --> 01:32:45,520
Speaker 1: She was not seen as very good at basic constituency services.

1567
01:32:47,560 --> 01:32:50,280
Speaker 1: But the fact that this is so fresh, so recent,

1568
01:32:51,520 --> 01:32:55,400
Speaker 1: you are also going to have a democratic electorate, I

1569
01:32:55,400 --> 01:32:58,160
Speaker 1: think that is looking to be more feisty and wants

1570
01:32:58,160 --> 01:33:00,800
Speaker 1: to be a bit more confrontational. That actually could help

1571
01:33:01,520 --> 01:33:04,360
Speaker 1: Corey Bush in that race. So I think you have

1572
01:33:04,400 --> 01:33:07,559
Speaker 1: to put her in the number two slot of most

1573
01:33:07,640 --> 01:33:11,000
Speaker 1: likely to get her to get her old job back.

1574
01:33:12,280 --> 01:33:17,720
Speaker 1: It's and it could be. It could the stuff that

1575
01:33:17,760 --> 01:33:20,599
Speaker 1: worked against her in her last primary may not work

1576
01:33:20,640 --> 01:33:23,000
Speaker 1: against her as strongly as it did the first time.

1577
01:33:23,080 --> 01:33:26,400
Speaker 1: Number three on my list is a candidacy that it

1578
01:33:26,439 --> 01:33:29,519
Speaker 1: appears to be more likely than not. What's funny is

1579
01:33:29,520 --> 01:33:32,720
Speaker 1: that there were actually two people in this race that

1580
01:33:32,800 --> 01:33:35,960
Speaker 1: could have qualified in this spot, but I wouldn't have

1581
01:33:36,160 --> 01:33:38,120
Speaker 1: put both of them in my third slot. And it's

1582
01:33:38,200 --> 01:33:42,040
Speaker 1: Johnny Sinunu. He's a former US senator. He is being

1583
01:33:42,040 --> 01:33:46,320
Speaker 1: recruited heavily to run again to try to get back

1584
01:33:46,360 --> 01:33:50,960
Speaker 1: into the US Senate. He lost to Jean Shaheen. This

1585
01:33:51,080 --> 01:33:53,559
Speaker 1: time he's running to try to he would be running

1586
01:33:53,560 --> 01:33:55,680
Speaker 1: to replace him. Now he hasn't announced yet, so you

1587
01:33:55,680 --> 01:33:58,639
Speaker 1: could say he's a probable candidate. He of course would

1588
01:33:58,640 --> 01:34:01,120
Speaker 1: be in a primary with Scott Brown, who is also

1589
01:34:01,160 --> 01:34:03,840
Speaker 1: a former US Senator, who would be running for the

1590
01:34:03,880 --> 01:34:06,920
Speaker 1: second time to try to win this specific seat. He

1591
01:34:06,960 --> 01:34:12,920
Speaker 1: actually ran against Gen h a cycle ago and did

1592
01:34:12,960 --> 01:34:17,000
Speaker 1: not win. Republicans are not very bullish on Brown's ability

1593
01:34:17,000 --> 01:34:19,400
Speaker 1: to win this open seat against the likely Democratic nomine

1594
01:34:19,439 --> 01:34:22,000
Speaker 1: Chris Pappus, but they're a lot more bullish on Sonunu.

1595
01:34:22,040 --> 01:34:24,960
Speaker 1: And part of it is Sonunu's brother is extraordinarily popular,

1596
01:34:24,960 --> 01:34:27,760
Speaker 1: the now former governor, Chris Snunu. He is somebody that

1597
01:34:27,880 --> 01:34:32,320
Speaker 1: seemed to navigate navigate the cranky New Hampshire Independent as

1598
01:34:32,360 --> 01:34:35,400
Speaker 1: well as anybody I've seen in New Hampshire in sometime,

1599
01:34:36,320 --> 01:34:39,000
Speaker 1: and he knew how to push back on Trump and

1600
01:34:39,040 --> 01:34:41,320
Speaker 1: he needed to, and he knew how to look. I

1601
01:34:41,320 --> 01:34:43,000
Speaker 1: think there's some people on the left that feel like

1602
01:34:43,040 --> 01:34:45,559
Speaker 1: he was too supportive at times of Trump. But if

1603
01:34:45,560 --> 01:34:48,640
Speaker 1: you're actually going to be successful independent, you got to

1604
01:34:48,640 --> 01:34:50,960
Speaker 1: know when to work with each side and when to

1605
01:34:51,320 --> 01:34:55,240
Speaker 1: oppose each side, and you got to sort of be

1606
01:34:55,360 --> 01:34:58,800
Speaker 1: sort of consistent with yourself and pulling that off. The

1607
01:34:58,840 --> 01:35:02,760
Speaker 1: sou brand is very strong in that state, and I

1608
01:35:02,800 --> 01:35:06,760
Speaker 1: think Johnson, who arguably lost because he was portrayed as

1609
01:35:06,800 --> 01:35:10,160
Speaker 1: being much too conservative for the state some four years ago,

1610
01:35:10,200 --> 01:35:14,720
Speaker 1: I think in a weird way, Trump has redefined conservatism,

1611
01:35:15,479 --> 01:35:19,559
Speaker 1: uh and in a way that is more it is

1612
01:35:19,640 --> 01:35:22,720
Speaker 1: more more of an online you know, too conservative is

1613
01:35:22,880 --> 01:35:26,599
Speaker 1: now seen as being sort of more maga than it

1614
01:35:26,680 --> 01:35:32,120
Speaker 1: is more ideological. And so the the ideological problems that

1615
01:35:32,160 --> 01:35:36,000
Speaker 1: were Johnny Suw's do Johnny because his father was a

1616
01:35:36,080 --> 01:35:41,720
Speaker 1: john was Johnson, who just different initial is not as

1617
01:35:41,760 --> 01:35:46,519
Speaker 1: I think, is not as the same deal breaker as

1618
01:35:46,560 --> 01:35:49,960
Speaker 1: it was in his original race against Shaheen, which was

1619
01:35:50,000 --> 01:35:51,639
Speaker 1: a massive race. So I put him in the number

1620
01:35:51,640 --> 01:35:53,679
Speaker 1: three column. I think the only reason he's not higher

1621
01:35:53,680 --> 01:35:54,760
Speaker 1: on the list is I think it's going to be

1622
01:35:54,800 --> 01:35:58,360
Speaker 1: a tough year for Republicans generically in New Hampshire's the

1623
01:35:58,360 --> 01:36:00,680
Speaker 1: type of state that that sort of ooves. You know,

1624
01:36:01,200 --> 01:36:03,760
Speaker 1: if the country's leaning left, New Hampshire's going to lean left.

1625
01:36:03,760 --> 01:36:06,280
Speaker 1: If the country's going to lean right, as we've seen

1626
01:36:06,320 --> 01:36:09,519
Speaker 1: New Hampshire is still a bit more slightly more center

1627
01:36:09,600 --> 01:36:11,840
Speaker 1: left than the country, or else Trump would have carried

1628
01:36:11,840 --> 01:36:16,640
Speaker 1: that state in twenty Fourty didn't. But if you see,

1629
01:36:16,680 --> 01:36:21,080
Speaker 1: if basically the generic battle it's tied nationally, then there's

1630
01:36:21,080 --> 01:36:24,120
Speaker 1: an opening for someone like Sinunu, and his brand name

1631
01:36:24,160 --> 01:36:26,840
Speaker 1: may help in that one. So he's number three, number fourth,

1632
01:36:26,840 --> 01:36:30,280
Speaker 1: the less I'm gonna put Shared Brown. The man raised

1633
01:36:30,320 --> 01:36:36,240
Speaker 1: eight million dollars in six weeks. Incredibly formidable. He knows Ohio,

1634
01:36:36,479 --> 01:36:39,200
Speaker 1: he knows how to do it. He's won in mid

1635
01:36:39,520 --> 01:36:43,320
Speaker 1: the midterm, the midterm environment. You know, his one loss

1636
01:36:44,080 --> 01:36:47,599
Speaker 1: was in the was in that presidential environment where more

1637
01:36:47,640 --> 01:36:50,439
Speaker 1: Trump and Vance voters showed up. So I think this

1638
01:36:50,600 --> 01:36:52,720
Speaker 1: is he certainly has a shot at this. I'm I

1639
01:36:52,800 --> 01:36:55,840
Speaker 1: think I think he's got an easy path to forty seven,

1640
01:36:55,880 --> 01:37:01,280
Speaker 1: an extraordinarily hard path to fifty percent plus one if

1641
01:37:01,320 --> 01:37:04,880
Speaker 1: he somehow he's If there was a libertarian Canada taking

1642
01:37:04,920 --> 01:37:09,719
Speaker 1: two or three points and winning number was forty seven

1643
01:37:09,760 --> 01:37:13,439
Speaker 1: point five to forty eight point five, that's how Shared

1644
01:37:13,479 --> 01:37:18,040
Speaker 1: Brown wins this race. We'll see what the eventual general

1645
01:37:18,080 --> 01:37:22,200
Speaker 1: election ballot looks like. But that's but I put Shared

1646
01:37:22,200 --> 01:37:25,240
Speaker 1: Brown number Fourtheless, in my fifth spot, I'm having a

1647
01:37:25,240 --> 01:37:28,320
Speaker 1: little fun with this. I do not necessarily believe this

1648
01:37:28,360 --> 01:37:30,559
Speaker 1: is the fifth most likely person. In fact, there are

1649
01:37:30,640 --> 01:37:33,280
Speaker 1: a whole bunch of other formers trying to get their

1650
01:37:34,160 --> 01:37:38,599
Speaker 1: trying to get their seats back here, some interesting members

1651
01:37:38,600 --> 01:37:42,000
Speaker 1: of Congress or in fact, the Byron Donalds. The seat

1652
01:37:42,000 --> 01:37:45,640
Speaker 1: that Byron Donalds is vacating in Florida has former New

1653
01:37:45,720 --> 01:37:48,080
Speaker 1: York Member of Congress Chris Collins running in the primary,

1654
01:37:48,320 --> 01:37:51,680
Speaker 1: former North Carolina Member of Congress Madison Cawthorne running in

1655
01:37:51,720 --> 01:37:54,160
Speaker 1: the primary, and neither one of them are likely to

1656
01:37:54,200 --> 01:37:57,800
Speaker 1: actually get close to winning that seat, which is why

1657
01:37:57,840 --> 01:38:00,640
Speaker 1: I didn't put him on the list. Jerry carl is

1658
01:38:00,680 --> 01:38:03,280
Speaker 1: thinking about running for his old seat in Alabama. We

1659
01:38:03,360 --> 01:38:06,840
Speaker 1: shall see there. So you do have a few other

1660
01:38:07,000 --> 01:38:11,040
Speaker 1: formers out there, but the former and also Tommy Thompson

1661
01:38:12,120 --> 01:38:14,280
Speaker 1: has said he's eighty five, and he said he may

1662
01:38:14,320 --> 01:38:16,360
Speaker 1: want to run for a fifth term for governor. I

1663
01:38:16,360 --> 01:38:19,280
Speaker 1: think I mentioned it last week, but I don't think

1664
01:38:19,320 --> 01:38:21,400
Speaker 1: he ends up running, which is why I didn't have

1665
01:38:21,439 --> 01:38:23,040
Speaker 1: a little fun put on the list. But the person

1666
01:38:23,040 --> 01:38:27,520
Speaker 1: I'm putting on the list is Javier Suarez my hometown

1667
01:38:27,560 --> 01:38:30,240
Speaker 1: of Miami. It's actually the city of Miami, Mayor. I

1668
01:38:30,280 --> 01:38:33,120
Speaker 1: actually never lived in the city of Miami. I grew

1669
01:38:33,200 --> 01:38:38,360
Speaker 1: up in the unincorporated Miami Dade County. Miami was what

1670
01:38:38,479 --> 01:38:41,160
Speaker 1: you put when you mailed a letter to my house.

1671
01:38:41,280 --> 01:38:45,559
Speaker 1: It was Miami, Florida. That's what was used. I was

1672
01:38:45,600 --> 01:38:47,559
Speaker 1: in Kendall, so we didn't have to have a town

1673
01:38:47,680 --> 01:38:49,800
Speaker 1: or a city. There are I think we're up to

1674
01:38:49,840 --> 01:38:53,120
Speaker 1: thirty three municipalities within Miami Dade County. When I grew up,

1675
01:38:53,160 --> 01:38:55,000
Speaker 1: it was just Dade County. They added the Miami for

1676
01:38:55,120 --> 01:39:00,679
Speaker 1: branding reasons. Frankly understandable, right. La County is La right,

1677
01:39:00,800 --> 01:39:06,559
Speaker 1: so why not? And Jamier Suarez is not only trying

1678
01:39:06,560 --> 01:39:09,120
Speaker 1: to get his old seatback. He was mayor of Miami

1679
01:39:09,200 --> 01:39:12,439
Speaker 1: from eighty five to ninety three, and briefly for about

1680
01:39:13,200 --> 01:39:15,519
Speaker 1: for a two month period in ninety seven, after the

1681
01:39:15,560 --> 01:39:19,360
Speaker 1: most corrupt mayor or election that the city of Miami's

1682
01:39:19,360 --> 01:39:21,320
Speaker 1: ever had. I'll get to that in a minute. But

1683
01:39:21,320 --> 01:39:24,320
Speaker 1: he's actually running to replace his son, Francis Suarez, whose

1684
01:39:24,400 --> 01:39:29,040
Speaker 1: term limited. Of course, you remember Francisuarez from his days

1685
01:39:29,040 --> 01:39:33,599
Speaker 1: as a presidential candidate. Briefly in twenty twenty four. I

1686
01:39:33,680 --> 01:39:37,840
Speaker 1: suspect he is. I wouldn't be shocked if he found

1687
01:39:37,880 --> 01:39:40,720
Speaker 1: his way into the Trump cabinet or found his way

1688
01:39:40,760 --> 01:39:44,600
Speaker 1: into an ambassador's ship. He toyed with the idea of

1689
01:39:44,680 --> 01:39:47,479
Speaker 1: running for governor, but he and DeSantis have not seen

1690
01:39:47,520 --> 01:39:51,679
Speaker 1: ey to I although being anti DeSantis hasn't been an

1691
01:39:51,760 --> 01:39:55,000
Speaker 1: issue in Trump world right If you told me, though,

1692
01:39:55,000 --> 01:39:58,160
Speaker 1: that Suarez was the running mate for Byron Donald's would

1693
01:39:58,520 --> 01:40:05,000
Speaker 1: totally shock me on that front. But he's a pretty

1694
01:40:05,040 --> 01:40:07,840
Speaker 1: ambitious guy, so I don't know if Donalds would want

1695
01:40:07,880 --> 01:40:11,360
Speaker 1: to have would trust him as a running mate, though

1696
01:40:11,400 --> 01:40:17,400
Speaker 1: I do think having South Miami ties might matter if

1697
01:40:17,439 --> 01:40:19,639
Speaker 1: the general election is indeed going to be competitive and close,

1698
01:40:19,720 --> 01:40:22,120
Speaker 1: and I think that's an open question, not one hundred

1699
01:40:22,160 --> 01:40:24,360
Speaker 1: percent convinced it will be. Look, I think there are

1700
01:40:24,360 --> 01:40:26,880
Speaker 1: two Democrats that might be able to make this a

1701
01:40:26,920 --> 01:40:30,639
Speaker 1: more competitive Varius David Jolly is certainly a qualified candidate,

1702
01:40:30,720 --> 01:40:33,560
Speaker 1: the former Republican congressman now switching parties as a Democrat.

1703
01:40:33,800 --> 01:40:37,719
Speaker 1: And Jerry Demmings, the mayor of Orlando of Orange County.

1704
01:40:38,040 --> 01:40:41,360
Speaker 1: Excuse me, the colonomy that encompasses Orlando, is thinking about

1705
01:40:41,400 --> 01:40:45,120
Speaker 1: running in theory, either one of them could potentially be

1706
01:40:45,160 --> 01:40:48,679
Speaker 1: a strong candidate. But boy does Donalds have a huge,

1707
01:40:48,960 --> 01:40:52,880
Speaker 1: huge head start. So but what's interesting about there's like

1708
01:40:53,200 --> 01:40:59,400
Speaker 1: over a dozen candidates running for Miami mayor and including

1709
01:40:59,680 --> 01:41:05,160
Speaker 1: a couple full of people who corrupt pasts have collided

1710
01:41:05,160 --> 01:41:11,400
Speaker 1: and intertwined in the past. Joj Coroyo, who was and

1711
01:41:12,120 --> 01:41:15,800
Speaker 1: Javier Suarez now Jaber Suarez, the father of Francisirez. Francisuirez

1712
01:41:15,800 --> 01:41:19,760
Speaker 1: has not endorsed his father. He wishes him well, is

1713
01:41:19,800 --> 01:41:24,120
Speaker 1: what he said, but he is not endorsed. Jabier Swirez

1714
01:41:24,160 --> 01:41:27,519
Speaker 1: won the most corrupt mayor's race. When you when you've

1715
01:41:27,520 --> 01:41:32,760
Speaker 1: heard about voter fraud issues, Suarez a Republican and this

1716
01:41:32,840 --> 01:41:35,439
Speaker 1: is this was all republican and Republican crime there in

1717
01:41:35,439 --> 01:41:38,400
Speaker 1: the city of Miami. He won a race in nineteen

1718
01:41:38,439 --> 01:41:44,639
Speaker 1: ninety seven basically by he He was never They could

1719
01:41:44,720 --> 01:41:47,400
Speaker 1: never say that the candidate himself knew this happened, but

1720
01:41:47,439 --> 01:41:51,640
Speaker 1: they did prove that somebody on his behalf stuffed the

1721
01:41:51,680 --> 01:41:55,040
Speaker 1: ballot box of absentee ballots. He basically won because of

1722
01:41:55,080 --> 01:41:58,240
Speaker 1: absentee ballots, and they were clearly fraudulent to the point

1723
01:41:58,280 --> 01:42:03,040
Speaker 1: of the election was overturned and he was not allowed

1724
01:42:03,080 --> 01:42:07,920
Speaker 1: to serve as mayor. Joe Kroyo, who himself has just

1725
01:42:08,120 --> 01:42:13,760
Speaker 1: lost a fifty plus million dollar civil suit, has sort

1726
01:42:13,800 --> 01:42:18,960
Speaker 1: of avoided any official criminal indictments, but has all sorts

1727
01:42:18,960 --> 01:42:23,479
Speaker 1: of ethical liabilities that that have followed him for years,

1728
01:42:23,560 --> 01:42:26,400
Speaker 1: was the other candidate in that race back in ninety seven. Well,

1729
01:42:26,479 --> 01:42:29,240
Speaker 1: Joe Kroyo is dealing is running again. There's just all

1730
01:42:29,720 --> 01:42:32,639
Speaker 1: It doesn't appear any of these guys are going to win.

1731
01:42:32,720 --> 01:42:36,280
Speaker 1: But if you're looking for a good old fashioned crazy

1732
01:42:36,439 --> 01:42:41,040
Speaker 1: race in Miami that's got a lot of corrupt tentacles

1733
01:42:41,080 --> 01:42:43,680
Speaker 1: sort of in it, that is a bit of the

1734
01:42:43,760 --> 01:42:46,599
Speaker 1: old Miami, And you know, it bums me out because

1735
01:42:46,640 --> 01:42:50,840
Speaker 1: I do think we're in general, the city and the

1736
01:42:50,880 --> 01:42:54,479
Speaker 1: County of Miami have been trying to move away from

1737
01:42:54,520 --> 01:42:59,120
Speaker 1: its reputation as being a bit corrupt in different parts,

1738
01:42:59,120 --> 01:43:02,280
Speaker 1: in different cities. And when you have thirty three municipalities,

1739
01:43:02,800 --> 01:43:07,559
Speaker 1: these small little, you know, enclaves within the county that

1740
01:43:07,680 --> 01:43:13,320
Speaker 1: frankly have been abused by ambitious officeholders who just wanted

1741
01:43:13,320 --> 01:43:16,439
Speaker 1: to enrich themselves. But it's like it's like my friends

1742
01:43:16,439 --> 01:43:19,479
Speaker 1: in Chicago and in cook County who always were in

1743
01:43:19,520 --> 01:43:22,519
Speaker 1: New Orleans and in Louisiana, you're always sort of running

1744
01:43:22,520 --> 01:43:25,040
Speaker 1: away from your reputation from corruption, and every time you

1745
01:43:25,040 --> 01:43:29,840
Speaker 1: think you turn the corner, then somebody essentially does it

1746
01:43:29,880 --> 01:43:33,559
Speaker 1: again and only sullies the entire reputation of the area.

1747
01:43:34,720 --> 01:43:37,400
Speaker 1: I imagine that there's sort of going to be some

1748
01:43:37,479 --> 01:43:41,360
Speaker 1: Suarez fatigue. That doesn't that also hurts Javier Suarez. But

1749
01:43:41,840 --> 01:43:43,800
Speaker 1: I do think the fact that he was involved in

1750
01:43:43,840 --> 01:43:47,080
Speaker 1: the worst, in the most documented case of voter fraud

1751
01:43:47,160 --> 01:43:50,160
Speaker 1: that we ever had again absentee ballots on the Republican

1752
01:43:50,240 --> 01:43:53,799
Speaker 1: side of the aisle for those of you keeping keeping score.

1753
01:43:54,720 --> 01:43:59,000
Speaker 1: But he is fifth on my list of most likely

1754
01:43:59,080 --> 01:44:01,880
Speaker 1: to be able to win a comeback to an old

1755
01:44:01,960 --> 01:44:06,360
Speaker 1: office that they once held. All right, that little trip

1756
01:44:06,400 --> 01:44:08,880
Speaker 1: down memory lane. I hope you enjoyed that top five list.

1757
01:44:08,960 --> 01:44:12,880
Speaker 1: So the top five most like lead political comebacks Jesse Jackson, Junior,

1758
01:44:12,960 --> 01:44:18,960
Speaker 1: Corey Bush, Johnny Sinunu, Sheard Brown, and one Javier Souarez

1759
01:44:19,400 --> 01:44:33,920
Speaker 1: for the City of Miami mayor. All right, let's do

1760
01:44:33,960 --> 01:44:39,680
Speaker 1: some ass chuck. Ass chuck. All right, let's do some

1761
01:44:39,720 --> 01:44:41,960
Speaker 1: ass chuck. This one comes from Frank and he says, Hey, Chuck,

1762
01:44:41,960 --> 01:44:44,679
Speaker 1: I always enjoy when you mentioned Seminole County or anything

1763
01:44:44,680 --> 01:44:48,599
Speaker 1: around Florida. Seminole County, that's where my mother lives. He goes,

1764
01:44:48,640 --> 01:44:50,599
Speaker 1: I grew up near Lake Jessup, but now live in

1765
01:44:50,760 --> 01:44:53,479
Speaker 1: Loudon County. There you go, Virginia. So this is my

1766
01:44:53,560 --> 01:44:56,920
Speaker 1: first commonwealth wide election. So I watched last week's Virginia

1767
01:44:56,920 --> 01:44:59,280
Speaker 1: Good a toilet to be closely. What stood out was

1768
01:44:59,320 --> 01:45:01,800
Speaker 1: how the moderate held the candidates accountable, pressing them when

1769
01:45:01,840 --> 01:45:04,439
Speaker 1: they dodge questions. Is someone familiar with how presidential debates

1770
01:45:04,479 --> 01:45:06,679
Speaker 1: are run, do you think that same approach could work

1771
01:45:06,680 --> 01:45:08,679
Speaker 1: at the national level or are there too many rules

1772
01:45:08,680 --> 01:45:11,479
Speaker 1: and behind the scenes constraints that prevent it. Thanks Frank.

1773
01:45:12,080 --> 01:45:15,280
Speaker 1: You know it's funny. I've been involved in both presidential debates,

1774
01:45:15,400 --> 01:45:21,679
Speaker 1: and in fact i've this is the first time I've

1775
01:45:21,720 --> 01:45:25,280
Speaker 1: not moderated a debate in Virginia governor. I think now

1776
01:45:25,320 --> 01:45:30,559
Speaker 1: going some fifteen years, I've moderated quite a few of

1777
01:45:30,560 --> 01:45:34,040
Speaker 1: the Virginia governor debates and quite a few Virginia Senate debates,

1778
01:45:35,840 --> 01:45:38,080
Speaker 1: and these two candids had a hard time agreeing to

1779
01:45:38,120 --> 01:45:41,320
Speaker 1: many debates. This is becoming a larger problem in general.

1780
01:45:41,800 --> 01:45:48,320
Speaker 1: But for the most part, you know, the fewer people involved,

1781
01:45:48,320 --> 01:45:50,960
Speaker 1: the better chance you have to do this. And if

1782
01:45:51,200 --> 01:45:53,559
Speaker 1: my understanding in this debate is that there were sort

1783
01:45:53,600 --> 01:45:56,639
Speaker 1: of fewer constraints, there wasn't You didn't have like multiple

1784
01:45:56,680 --> 01:45:58,880
Speaker 1: media partners where you got to have a whole bunch

1785
01:45:58,880 --> 01:46:01,880
Speaker 1: of people ask questions, right. That sort of takes up

1786
01:46:01,880 --> 01:46:05,959
Speaker 1: potential follow up time. That's number one. But in general,

1787
01:46:07,000 --> 01:46:10,800
Speaker 1: the candidates themselves don't fight like in some ways. I've

1788
01:46:10,840 --> 01:46:12,760
Speaker 1: always been able to get what I've wanted out of

1789
01:46:12,800 --> 01:46:15,160
Speaker 1: most of these debates and been able to make sure

1790
01:46:15,760 --> 01:46:18,799
Speaker 1: I've had the ability to do follow ups pretty closely.

1791
01:46:18,880 --> 01:46:23,040
Speaker 1: I did the Hogan also Brooks debate in twenty twenty four,

1792
01:46:24,160 --> 01:46:26,519
Speaker 1: and a lot of the debates in the DMV I've

1793
01:46:26,520 --> 01:46:29,040
Speaker 1: had the opportunity to do, and I've enjoyed them a lot.

1794
01:46:29,080 --> 01:46:34,040
Speaker 1: On the presidential level, the campaigns litigate everything beforehand, and

1795
01:46:34,080 --> 01:46:37,880
Speaker 1: so you will get you know, they will try to

1796
01:46:37,880 --> 01:46:42,240
Speaker 1: get in the specifics of that. The beauty of the

1797
01:46:42,240 --> 01:46:45,519
Speaker 1: Presidential Commission debates, although we may not have it, is

1798
01:46:45,520 --> 01:46:47,400
Speaker 1: that the Commission sort of was able to sort of

1799
01:46:48,120 --> 01:46:50,920
Speaker 1: hold firmer right now that you're going to pit media

1800
01:46:50,960 --> 01:46:54,080
Speaker 1: companies against each other in this. It's going to be

1801
01:46:54,800 --> 01:46:59,240
Speaker 1: a you know, sort of a war that ends up

1802
01:46:59,240 --> 01:47:03,200
Speaker 1: benefiting the camp candidates, and it takes takes out the

1803
01:47:03,280 --> 01:47:07,799
Speaker 1: ability of the moderator to be anything more than a mannequin,

1804
01:47:08,520 --> 01:47:12,200
Speaker 1: which is which is my concern. But look, I I

1805
01:47:12,720 --> 01:47:15,160
Speaker 1: watched bits and pizza of that debate as well, and

1806
01:47:15,360 --> 01:47:17,759
Speaker 1: I think the moderators did their best. It's never helpful

1807
01:47:17,800 --> 01:47:21,400
Speaker 1: when when one of the candidates just has no intention

1808
01:47:21,439 --> 01:47:25,000
Speaker 1: of abiding by the rules. Uh and it's it really

1809
01:47:25,040 --> 01:47:27,599
Speaker 1: sucks when that happens, because you, as the moderator, become

1810
01:47:27,640 --> 01:47:32,720
Speaker 1: the schoolmar and the time cop and the pleas and

1811
01:47:32,760 --> 01:47:34,760
Speaker 1: the this, and you want to be polite, you know.

1812
01:47:34,880 --> 01:47:36,759
Speaker 1: I always you know a lot of people are watching,

1813
01:47:38,320 --> 01:47:40,439
Speaker 1: and you know, as a moderator, I've always viewed it

1814
01:47:40,479 --> 01:47:43,000
Speaker 1: more as an umpire rule, which is I never wanted

1815
01:47:43,000 --> 01:47:47,599
Speaker 1: my name mentioned until paragraph five or six, if you're

1816
01:47:47,680 --> 01:47:49,960
Speaker 1: if you're in paragraph one. I feel that way. Feel

1817
01:47:50,000 --> 01:47:52,120
Speaker 1: the way about debate moderating, the way I feel about

1818
01:47:52,479 --> 01:47:57,320
Speaker 1: uh NBA refereeing, NFL refereeing baseball umpiring. If I know

1819
01:47:57,479 --> 01:48:00,160
Speaker 1: the name of the referee or the umpire. They you

1820
01:48:00,200 --> 01:48:03,200
Speaker 1: are way too involved in the in the game, right.

1821
01:48:04,000 --> 01:48:06,400
Speaker 1: You know it's not good that I know who that

1822
01:48:06,560 --> 01:48:09,120
Speaker 1: one of the most important NBA refs out there is

1823
01:48:09,120 --> 01:48:12,680
Speaker 1: a guy named Scott Foster. I don't you know that's bad? Right?

1824
01:48:12,720 --> 01:48:14,559
Speaker 1: That means there's been a lot of analysis about how

1825
01:48:14,600 --> 01:48:19,360
Speaker 1: Scott Foster covered, uh does games? So it is, it is,

1826
01:48:21,439 --> 01:48:24,040
Speaker 1: it is. I don't think that should be. You know,

1827
01:48:24,280 --> 01:48:28,559
Speaker 1: it's the candidate's debating, not the moderator involved in the debate. Right.

1828
01:48:28,800 --> 01:48:31,599
Speaker 1: In some ways, they're trying to h They're trying to

1829
01:48:32,040 --> 01:48:37,599
Speaker 1: surface information and surface a conversation. Look, I think they did,

1830
01:48:37,680 --> 01:48:40,120
Speaker 1: but you know, ultimately a debate only works if the

1831
01:48:40,160 --> 01:48:42,840
Speaker 1: candidates accept the premise. And I think that the difficulty

1832
01:48:42,840 --> 01:48:44,680
Speaker 1: that my friends had in that Virginia debate, HES had

1833
01:48:44,720 --> 01:48:48,599
Speaker 1: one of the candidates that that simply wanted to just

1834
01:48:48,800 --> 01:48:52,439
Speaker 1: not not allow was trying to rattle the other candidate.

1835
01:48:52,520 --> 01:48:55,280
Speaker 1: I understood her strategy. This is Winster Earld series. I

1836
01:48:55,360 --> 01:48:58,040
Speaker 1: understood her strategy. And trying to rattle it's what you

1837
01:48:58,080 --> 01:49:00,639
Speaker 1: do when you're behind. I mean, I don't I sort

1838
01:49:00,680 --> 01:49:02,840
Speaker 1: of I get the strategy. I don't I'm not going

1839
01:49:02,920 --> 01:49:05,559
Speaker 1: to condemn it, but it made the moderator's job that

1840
01:49:05,640 --> 01:49:11,160
Speaker 1: much harder. All right, next question comes from anonymous. Hey there,

1841
01:49:11,200 --> 01:49:13,000
Speaker 1: I enjoy your take on the events these days. Thank you.

1842
01:49:13,040 --> 01:49:15,040
Speaker 1: I have a major issue with the Hatch Act violation

1843
01:49:15,120 --> 01:49:18,439
Speaker 1: by posting political and partisan notices on a federal site.

1844
01:49:18,680 --> 01:49:23,040
Speaker 1: How about even how about Christy no trying to post

1845
01:49:23,640 --> 01:49:27,680
Speaker 1: video messages at airports? Anyway, what are the legal repercussions

1846
01:49:27,720 --> 01:49:31,400
Speaker 1: when leaders sanctioned these postings? The OSC complaint site seems

1847
01:49:31,439 --> 01:49:33,479
Speaker 1: to have been taken off line, So what recourse do

1848
01:49:33,520 --> 01:49:36,880
Speaker 1: we have as citizens? Well, let me do a little check.

1849
01:49:36,920 --> 01:49:39,320
Speaker 1: What happened to Kelly and Conway when she violated the

1850
01:49:39,360 --> 01:49:43,639
Speaker 1: Hatch Act. I believe she got I believe they that

1851
01:49:43,920 --> 01:49:48,240
Speaker 1: the OSC found she repeatedly violated the Hatchhack, but there

1852
01:49:48,280 --> 01:49:55,440
Speaker 1: was no punishment. The Office of the Special Council recommended

1853
01:49:55,439 --> 01:49:59,679
Speaker 1: her removal from federal service. But then once she left

1854
01:49:59,680 --> 01:50:04,080
Speaker 1: govern it's not like you could discipline er and the

1855
01:50:04,320 --> 01:50:06,840
Speaker 1: and the White House didn't accept the premise it. This

1856
01:50:06,880 --> 01:50:09,160
Speaker 1: is one of these things the Hatch Act is norms.

1857
01:50:10,160 --> 01:50:13,920
Speaker 1: The Hatch Act really isn't very well enforced, right. It

1858
01:50:14,000 --> 01:50:16,840
Speaker 1: is one of those that the it's like and it's

1859
01:50:16,960 --> 01:50:19,640
Speaker 1: it's almost held over the heads of people more like impeachment.

1860
01:50:19,720 --> 01:50:23,639
Speaker 1: You hope that the shame of violating it, like, hey,

1861
01:50:24,439 --> 01:50:26,080
Speaker 1: you know, we actually have this law that says you

1862
01:50:26,120 --> 01:50:30,920
Speaker 1: can't play you can't practice politics while serving, use your

1863
01:50:30,920 --> 01:50:35,800
Speaker 1: federal office for to advance your political agenda blatantly, right,

1864
01:50:35,920 --> 01:50:39,439
Speaker 1: And look, it's a this is a somewhat subjective, but

1865
01:50:39,520 --> 01:50:41,600
Speaker 1: we had sort of this third party, the Office of

1866
01:50:41,640 --> 01:50:46,880
Speaker 1: Special Council. Her violation, you know, was just simply talking

1867
01:50:46,880 --> 01:50:50,439
Speaker 1: about politics, and she was in an I have a

1868
01:50:50,640 --> 01:50:55,559
Speaker 1: tad more empathy for advisors in the West wing on

1869
01:50:55,680 --> 01:50:58,240
Speaker 1: the Hatch Act than I do for cabinet sectors. Like

1870
01:50:58,720 --> 01:51:00,160
Speaker 1: to me, there's no gray area at all.

1871
01:51:00,040 --> 01:51:00,160
Speaker 2: All.

1872
01:51:00,200 --> 01:51:04,720
Speaker 1: You can you can make some gray area arguments around

1873
01:51:05,680 --> 01:51:08,960
Speaker 1: West wing advisors who are constantly sort of in their

1874
01:51:09,040 --> 01:51:12,320
Speaker 1: their political appointees, and their only political appointees. They're not

1875
01:51:12,400 --> 01:51:15,160
Speaker 1: a percent of confirmation, you kind of know their political appointee.

1876
01:51:15,560 --> 01:51:18,920
Speaker 1: They're there to defend the politics of the administration. Anyway,

1877
01:51:19,600 --> 01:51:21,920
Speaker 1: I do think it's a it's it's it's a bit

1878
01:51:22,000 --> 01:51:24,559
Speaker 1: more gray area than than than maybe some of her

1879
01:51:24,560 --> 01:51:27,400
Speaker 1: political opponents want to admit. But The point is is

1880
01:51:27,479 --> 01:51:32,280
Speaker 1: that there's there's there's only teeth if if the administration

1881
01:51:32,400 --> 01:51:35,760
Speaker 1: accepts the premise, So Christine no blatant violation of the

1882
01:51:35,800 --> 01:51:38,280
Speaker 1: Hatch Act. You think this White House is going to

1883
01:51:38,320 --> 01:51:41,599
Speaker 1: accept the premise that she should be somehow garnished, pay

1884
01:51:41,720 --> 01:51:47,559
Speaker 1: removed from office, you know whatever. No, this gets to

1885
01:51:47,760 --> 01:51:50,840
Speaker 1: my larger point. Right, we've these were Hatch Act is

1886
01:51:50,880 --> 01:51:55,080
Speaker 1: a bit more. It was a bit more. It's almost

1887
01:51:55,200 --> 01:51:58,040
Speaker 1: like it's there so that we in the media can say, hey,

1888
01:51:58,080 --> 01:52:00,759
Speaker 1: so and so violated the Hatch Act. You voters decide

1889
01:52:00,800 --> 01:52:06,880
Speaker 1: whether you care. Right, it should embarrass presidents, but this

1890
01:52:07,120 --> 01:52:10,400
Speaker 1: president has politicized everything. I mean, this is one of

1891
01:52:10,439 --> 01:52:13,799
Speaker 1: my one of my concerns about what's happening with governing

1892
01:52:13,840 --> 01:52:16,960
Speaker 1: in America is that that the idea that you only

1893
01:52:17,000 --> 01:52:20,240
Speaker 1: govern for your supporters and you only punish those on

1894
01:52:20,600 --> 01:52:22,280
Speaker 1: the on the other side of you politically. I mean,

1895
01:52:22,320 --> 01:52:25,639
Speaker 1: this idea that they're not laying If you really want

1896
01:52:25,680 --> 01:52:27,599
Speaker 1: to just shrink government, you lay off across the board.

1897
01:52:27,840 --> 01:52:29,920
Speaker 1: Not laying off across the board. They're targeting the quote

1898
01:52:29,960 --> 01:52:35,679
Speaker 1: democratic agencies and they're leaving the quote Republican agencies alone.

1899
01:52:36,120 --> 01:52:38,960
Speaker 1: I didn't know we had democratic agencies or Republican agencies.

1900
01:52:39,000 --> 01:52:43,639
Speaker 1: But apparently Russell Voyd thinks we have democratic agencies. So

1901
01:52:43,720 --> 01:52:47,160
Speaker 1: this is this is a larger problem. The Hatch hack

1902
01:52:47,280 --> 01:52:50,439
Speaker 1: doesn't work, So we probably need to come up with

1903
01:52:50,479 --> 01:52:53,840
Speaker 1: something else that has a bit more teeth and is

1904
01:52:53,880 --> 01:52:59,360
Speaker 1: a bit more, a bit faster if we want to

1905
01:52:59,439 --> 01:53:02,200
Speaker 1: take this type of if we really want to take

1906
01:53:02,240 --> 01:53:06,160
Speaker 1: away this polarization. I mean, this gets back to good

1907
01:53:06,200 --> 01:53:11,000
Speaker 1: people with bad incentives will do bad things. The Hatch

1908
01:53:11,000 --> 01:53:16,520
Speaker 1: Act is something that was intended to service a potential

1909
01:53:17,600 --> 01:53:22,479
Speaker 1: piano over your head type of mindset as a political actor,

1910
01:53:22,479 --> 01:53:25,080
Speaker 1: that there would be embarrassment if you violated the Hatch Act.

1911
01:53:26,479 --> 01:53:32,200
Speaker 1: This administration is never embarrassed when they politicize things. So

1912
01:53:32,320 --> 01:53:36,240
Speaker 1: I think that's the definition of yet another norm if

1913
01:53:36,280 --> 01:53:37,080
Speaker 1: you will or.

1914
01:53:37,160 --> 01:53:37,720
Speaker 2: Law that.

1915
01:53:39,400 --> 01:53:42,080
Speaker 1: It's good intention. But it doesn't work. So we need

1916
01:53:42,120 --> 01:53:47,840
Speaker 1: to revisit it. Perhaps perhaps we need I don't want

1917
01:53:47,840 --> 01:53:49,680
Speaker 1: to put so many things, and you know, I don't

1918
01:53:49,720 --> 01:53:55,040
Speaker 1: think we need. I've advocated for a handful of constitutional amendments.

1919
01:53:55,120 --> 01:53:57,599
Speaker 1: I don't the idea that we'd have to make this

1920
01:53:57,640 --> 01:54:01,280
Speaker 1: a constitutional amendment seems ridiculous. We probably need real teeth there.

1921
01:54:01,360 --> 01:54:06,080
Speaker 1: Maybe it's huge fines you know that are that are

1922
01:54:06,720 --> 01:54:09,960
Speaker 1: you know, either resign or fine type of type of thing.

1923
01:54:11,160 --> 01:54:14,800
Speaker 1: But we need something better than what we have, that's

1924
01:54:14,840 --> 01:54:18,040
Speaker 1: for sure. All right. Next question comes from Mary W.

1925
01:54:18,280 --> 01:54:21,679
Speaker 1: Greetings again from Ruby Red, rural Ohio. All Right, so

1926
01:54:21,760 --> 01:54:24,040
Speaker 1: this is not a first time calls a second time.

1927
01:54:24,439 --> 01:54:25,880
Speaker 1: I just wanted to give you a big thank you

1928
01:54:25,880 --> 01:54:28,240
Speaker 1: for your interview with Paul Glasters. As a working class

1929
01:54:28,280 --> 01:54:30,400
Speaker 1: rural Ohio and I have two daughters, thirteen and eleven.

1930
01:54:30,439 --> 01:54:32,800
Speaker 1: My husband and I have been worried about affording college

1931
01:54:32,800 --> 01:54:34,920
Speaker 1: if our daughters choose to go. I had a huge

1932
01:54:34,920 --> 01:54:36,920
Speaker 1: loan that I could never make any headway on which

1933
01:54:36,920 --> 01:54:39,320
Speaker 1: I had for which I had forgiven by the Biden

1934
01:54:39,360 --> 01:54:45,080
Speaker 1: program for over forty thousand dollars. I left school in

1935
01:54:45,120 --> 01:54:47,440
Speaker 1: nineteen ninety nine and my education was basically worthless in

1936
01:54:47,480 --> 01:54:49,920
Speaker 1: the real world. I don't want that to happen to

1937
01:54:49,920 --> 01:54:51,720
Speaker 1: my own kids. I really enjoyed your interview, and when

1938
01:54:51,760 --> 01:54:54,680
Speaker 1: he said Berea College was oft in tuition free and

1939
01:54:54,760 --> 01:54:58,120
Speaker 1: was in Kentucky, I googled it immediately. It's only four

1940
01:54:58,120 --> 01:54:59,720
Speaker 1: hours from our house and we'll be at the top

1941
01:54:59,800 --> 01:55:02,240
Speaker 1: of the list if our daughters choose college over trade school.

1942
01:55:02,560 --> 01:55:04,440
Speaker 1: Thank you so much for that informative interview and all

1943
01:55:04,480 --> 01:55:06,520
Speaker 1: your insights on the craziness in the world. Mary w

1944
01:55:07,360 --> 01:55:08,800
Speaker 1: I have to tell you I've gotten a lot of

1945
01:55:08,920 --> 01:55:13,040
Speaker 1: I've gotten some terrific feedback on Paul's interview. Paul, if

1946
01:55:13,080 --> 01:55:19,240
Speaker 1: your ears are are birding good, it's that that just

1947
01:55:19,680 --> 01:55:23,120
Speaker 1: only reinforces what I hope to make this podcast about,

1948
01:55:23,160 --> 01:55:25,680
Speaker 1: which is to give you more information, give you more

1949
01:55:26,120 --> 01:55:30,120
Speaker 1: expose more more good ideas that are out there. I've

1950
01:55:30,200 --> 01:55:32,280
Speaker 1: said that one of the things I want to do is, look,

1951
01:55:32,280 --> 01:55:33,920
Speaker 1: I'm I'm going to be on the news at the

1952
01:55:33,920 --> 01:55:35,680
Speaker 1: top of these things, but I want to. I want

1953
01:55:35,680 --> 01:55:38,320
Speaker 1: to you know, I believe in more light than heat,

1954
01:55:38,880 --> 01:55:41,520
Speaker 1: and podcasts should provide more light than heat. What do

1955
01:55:41,560 --> 01:55:45,560
Speaker 1: I mean by that that you're trying to provide more information,

1956
01:55:45,720 --> 01:55:49,600
Speaker 1: new information, not necessarily make people feel good with your

1957
01:55:49,600 --> 01:55:52,680
Speaker 1: takedowns and your trolls and your memes and all that business.

1958
01:55:52,760 --> 01:55:55,360
Speaker 1: I know that's how you light up the Twitter sphere,

1959
01:55:55,360 --> 01:55:57,200
Speaker 1: and that's how you light up your YouTube or your

1960
01:55:57,240 --> 01:56:00,880
Speaker 1: TikTok and oh look, I've got all these likes but

1961
01:56:00,920 --> 01:56:03,040
Speaker 1: are you actually making people's lives better? Are you giving

1962
01:56:03,040 --> 01:56:06,520
Speaker 1: them better tools to live a better life? Most of

1963
01:56:06,520 --> 01:56:12,520
Speaker 1: these political podcast are just griffs. Sadly, these are partisan

1964
01:56:12,600 --> 01:56:15,120
Speaker 1: hacks who some of them don't believe half of what

1965
01:56:15,160 --> 01:56:17,640
Speaker 1: they're preaching. This is left and right. I'm not going

1966
01:56:17,720 --> 01:56:20,680
Speaker 1: to sit here and name names. They know who they are,

1967
01:56:22,080 --> 01:56:25,400
Speaker 1: and they're just exploiting an incentive structure that rewards that

1968
01:56:25,440 --> 01:56:29,400
Speaker 1: behavior unfortunately. But anyway, this warms my heart. And like

1969
01:56:29,440 --> 01:56:33,200
Speaker 1: I said, I got a lot of direct feedback about

1970
01:56:33,200 --> 01:56:36,560
Speaker 1: this one too, because the cost of tuition is too

1971
01:56:36,640 --> 01:56:39,720
Speaker 1: damn high. It's so many of the so called great schools,

1972
01:56:39,800 --> 01:56:40,400
Speaker 1: that's for sure.

1973
01:56:40,760 --> 01:56:41,000
Speaker 3: All right.

1974
01:56:41,080 --> 01:56:44,680
Speaker 1: Last question, this one comes from Duncan from Arizona. He says,

1975
01:56:44,720 --> 01:56:46,600
Speaker 1: it's given the AI and robotics are set to take

1976
01:56:46,640 --> 01:56:48,520
Speaker 1: a big chunk out of the job market. What is

1977
01:56:48,520 --> 01:56:51,920
Speaker 1: the likelihood of a universal basic income in the United States?

1978
01:56:53,000 --> 01:56:56,080
Speaker 1: I think you're going to see this experiment expand outside

1979
01:56:56,080 --> 01:56:58,600
Speaker 1: of what we've seen so far. I think it was Stockton, California,

1980
01:56:58,600 --> 01:57:01,600
Speaker 1: has tried this Ubia. I think there's a few other

1981
01:57:01,720 --> 01:57:06,160
Speaker 1: municipalities of toyed with it. Universal basic income UBI Andrew

1982
01:57:06,240 --> 01:57:15,320
Speaker 1: Yang's presidential campaign talked about it. You know what social security.

1983
01:57:16,160 --> 01:57:18,280
Speaker 1: One could argue, we're already doing it for a big

1984
01:57:18,360 --> 01:57:22,800
Speaker 1: chunk of the population, right, Disability and social security are

1985
01:57:22,840 --> 01:57:27,080
Speaker 1: a form of essentially income replacement because you can't work

1986
01:57:27,280 --> 01:57:32,040
Speaker 1: or you're too old to work. So we're sort of

1987
01:57:32,800 --> 01:57:35,080
Speaker 1: I would argue, we kind of have a system in place.

1988
01:57:37,520 --> 01:57:39,760
Speaker 1: You know, we're going to go through quite a few changes.

1989
01:57:41,880 --> 01:57:44,080
Speaker 1: I know that the prediction of the three day, four

1990
01:57:44,160 --> 01:57:46,480
Speaker 1: day work week has been out there for a long time,

1991
01:57:49,200 --> 01:57:53,840
Speaker 1: but I think that's more real than ever now. That

1992
01:57:53,880 --> 01:57:57,240
Speaker 1: doesn't mean that people aren't going to have multiple The

1993
01:57:57,320 --> 01:57:59,520
Speaker 1: question is what is going to be What will full

1994
01:57:59,560 --> 01:58:02,360
Speaker 1: time work be defined by? Well, full time work be

1995
01:58:02,440 --> 01:58:07,560
Speaker 1: defined by three days a week of working minimum, and

1996
01:58:07,600 --> 01:58:11,880
Speaker 1: what does that look like? Right, it's possible that that's

1997
01:58:12,000 --> 01:58:14,800
Speaker 1: what's classified as that. That doesn't mean you won't see people,

1998
01:58:15,800 --> 01:58:20,200
Speaker 1: you know, sort of do it. I think arguably firefighters.

1999
01:58:21,280 --> 01:58:23,480
Speaker 1: I grew up with a couple of people who were

2000
01:58:24,080 --> 01:58:27,080
Speaker 1: firefighters who also had side hustles. You know, they because

2001
01:58:27,120 --> 01:58:29,160
Speaker 1: it was like you were twenty four hours on, forty

2002
01:58:29,200 --> 01:58:31,880
Speaker 1: eight hours off, twenty four hours on, forty eight hours off.

2003
01:58:32,600 --> 01:58:35,960
Speaker 1: It's a you know, where they do a side hustle

2004
01:58:36,000 --> 01:58:37,919
Speaker 1: of some sort. Maybe it would be a small business,

2005
01:58:37,960 --> 01:58:40,840
Speaker 1: maybe it would be deliveries, maybe it's real estate. You know,

2006
01:58:40,880 --> 01:58:45,240
Speaker 1: there's all sorts of Some teachers have, you know, acquired

2007
01:58:45,480 --> 01:58:50,120
Speaker 1: second jobs in the summers, even if as they're paid

2008
01:58:50,120 --> 01:58:53,360
Speaker 1: full time. But it's it's that So it's not as

2009
01:58:53,400 --> 01:58:56,200
Speaker 1: if I don't think people are going to only work

2010
01:58:56,240 --> 01:58:58,440
Speaker 1: three days a week. But what is going to be

2011
01:58:58,440 --> 01:59:01,879
Speaker 1: the definition of full time work, I think is certainly

2012
01:59:02,280 --> 01:59:06,280
Speaker 1: going to be an open question going forward. And I

2013
01:59:06,360 --> 01:59:10,240
Speaker 1: think we're going to need you know, it is I

2014
01:59:10,320 --> 01:59:14,720
Speaker 1: am I'm a bit skeptical. I think the idea of

2015
01:59:15,000 --> 01:59:18,440
Speaker 1: income replacement when needed is going to continue to be

2016
01:59:19,360 --> 01:59:24,280
Speaker 1: something that is a benefit. But I I'm not sure

2017
01:59:24,400 --> 01:59:27,600
Speaker 1: the human species is going to be comfortable just being

2018
01:59:27,600 --> 01:59:29,160
Speaker 1: paid not to work. And I know some of the

2019
01:59:29,160 --> 01:59:30,760
Speaker 1: others I'd love to be paid not to work. Would

2020
01:59:30,800 --> 01:59:34,800
Speaker 1: you would you have a fulfilling life? Would you be

2021
01:59:35,240 --> 01:59:37,520
Speaker 1: literally pick up something else and find a way to

2022
01:59:37,560 --> 01:59:42,240
Speaker 1: make money because you were kind of bored in different ways?

2023
01:59:42,280 --> 01:59:47,520
Speaker 1: So I do think you're going to see in you know,

2024
01:59:47,720 --> 01:59:51,320
Speaker 1: some form of this. I believe fear of AI job

2025
01:59:51,400 --> 01:59:54,960
Speaker 1: displacement is going to be a crucial issue in the

2026
01:59:54,960 --> 01:59:59,480
Speaker 1: twenty twenty eight presidential election cycle. And if you aren't,

2027
01:59:59,680 --> 02:00:01,280
Speaker 1: if you're think about running for president, you better have

2028
02:00:01,280 --> 02:00:04,160
Speaker 1: a real plan. You know, are you going to be

2029
02:00:04,240 --> 02:00:04,840
Speaker 1: a champion of you?

2030
02:00:04,920 --> 02:00:05,120
Speaker 2: Bi?

2031
02:00:06,160 --> 02:00:08,480
Speaker 1: Uh? Is that going to be part of your thing?

2032
02:00:08,640 --> 02:00:11,000
Speaker 1: Is there a job retraining? Is there? That? You know?

2033
02:00:11,200 --> 02:00:11,600
Speaker 2: What?

2034
02:00:11,600 --> 02:00:12,040
Speaker 1: What is?

2035
02:00:12,120 --> 02:00:12,360
Speaker 2: What?

2036
02:00:12,360 --> 02:00:14,520
Speaker 1: What is your hope if you're hoping to collect dollars

2037
02:00:14,560 --> 02:00:17,640
Speaker 1: from the AI companies and what are you going to

2038
02:00:17,760 --> 02:00:19,720
Speaker 1: use with that money? If it is indeed, indeed, is

2039
02:00:19,720 --> 02:00:22,720
Speaker 1: it intended simply for income replacement or is it going

2040
02:00:22,800 --> 02:00:28,040
Speaker 1: to be for job retraining? But a very simple question

2041
02:00:28,280 --> 02:00:30,280
Speaker 1: open the door to what I think could be a

2042
02:00:30,400 --> 02:00:33,240
Speaker 1: very uh what to obviously a very long answer there.

2043
02:00:33,240 --> 02:00:37,200
Speaker 1: But I do think that this is that this will

2044
02:00:37,880 --> 02:00:41,280
Speaker 1: the fear of AI job displacement is going to be

2045
02:00:41,320 --> 02:00:45,880
Speaker 1: a really animating issue. And you know, in a in

2046
02:00:45,920 --> 02:00:48,600
Speaker 1: a by the way, in a sort of separate scenario

2047
02:00:48,600 --> 02:00:51,200
Speaker 1: at this same trade conference that I was participating in

2048
02:00:51,240 --> 02:00:57,240
Speaker 1: here in the digital ad community, and this this seed

2049
02:00:57,320 --> 02:00:59,760
Speaker 1: was planted by a good friend of mine recently, and

2050
02:01:00,440 --> 02:01:04,800
Speaker 1: I think he's right, which is, if we don't believe

2051
02:01:04,800 --> 02:01:08,280
Speaker 1: anything we see anymore on the internet, right, and with

2052
02:01:08,400 --> 02:01:12,680
Speaker 1: these AI visual tools, you know, I'm sorry. I look

2053
02:01:12,720 --> 02:01:15,120
Speaker 1: at stuff where I'm following on social media and someone

2054
02:01:15,160 --> 02:01:18,040
Speaker 1: will say, hey, that's obvious AI slop, and I use

2055
02:01:18,120 --> 02:01:21,840
Speaker 1: my old fifty three year old eyes, I squint. Is

2056
02:01:21,880 --> 02:01:28,280
Speaker 1: it obvious? What am I missing? Right? I think it's

2057
02:01:28,320 --> 02:01:31,120
Speaker 1: going to be a lot easier to just assume everything is.

2058
02:01:31,360 --> 02:01:33,600
Speaker 1: There's going to be almost an assumption that everything you

2059
02:01:33,760 --> 02:01:38,440
Speaker 1: see on the Internet is AI enhanced or created. So

2060
02:01:38,480 --> 02:01:41,440
Speaker 1: what does that mean? It's going to put a premium

2061
02:01:41,480 --> 02:01:44,320
Speaker 1: on face to face. It's going to put a premium

2062
02:01:44,360 --> 02:01:50,120
Speaker 1: on live in person, maybe to a lesser extent live streams,

2063
02:01:51,960 --> 02:01:56,400
Speaker 1: but even that could get aied, right. I know of

2064
02:01:56,480 --> 02:02:00,200
Speaker 1: another person who is trying to clone themselves to ye

2065
02:02:00,920 --> 02:02:07,879
Speaker 1: do more survey research, qualitative survey research. Obviously you you

2066
02:02:07,880 --> 02:02:10,720
Speaker 1: you know, we're an AI version of said person can

2067
02:02:10,800 --> 02:02:14,840
Speaker 1: start doing Q and as uh that that that is

2068
02:02:14,880 --> 02:02:18,880
Speaker 1: I see the upside of doing collecting data that way.

2069
02:02:21,160 --> 02:02:25,880
Speaker 1: Call me, call me skeptical that that actual human beings

2070
02:02:25,920 --> 02:02:31,640
Speaker 1: will feel comfortable doing that. So, but it is interesting,

2071
02:02:31,680 --> 02:02:34,120
Speaker 1: I am. I do think we're going to see some

2072
02:02:34,280 --> 02:02:39,160
Speaker 1: interesting unintended consequences in this race to the AI, affication

2073
02:02:39,280 --> 02:02:44,800
Speaker 1: of of of the Internet, and politically a job displacement,

2074
02:02:44,880 --> 02:02:47,160
Speaker 1: those issues. That's definitely going to be in the forefront.

2075
02:02:48,240 --> 02:02:55,480
Speaker 1: But it's going to make human interaction a premium. I

2076
02:02:55,520 --> 02:02:58,280
Speaker 1: have for instance, I think customer service. If you want

2077
02:02:58,280 --> 02:03:00,440
Speaker 1: a human being, you may have to pay extra for it,

2078
02:03:00,880 --> 02:03:02,960
Speaker 1: and I have a feeling people will pay extra for it,

2079
02:03:05,680 --> 02:03:10,720
Speaker 1: but human beings. Dealing with a human being will be

2080
02:03:10,800 --> 02:03:14,720
Speaker 1: seen as a much better experience than dealing with a

2081
02:03:14,760 --> 02:03:18,480
Speaker 1: computer you cannot sort of reason with, even if you

2082
02:03:18,560 --> 02:03:22,520
Speaker 1: think you're reasoning with, said robot. All right, on that

2083
02:03:22,720 --> 02:03:29,720
Speaker 1: uplifting dystopian notes, go rewatch gataka right now, I tease

2084
02:03:29,880 --> 02:03:32,000
Speaker 1: with that, I'm going to take a twenty four hour break,

2085
02:03:33,040 --> 02:03:34,840
Speaker 1: but I will see you in twenty four hours until

2086
02:03:34,880 --> 02:03:35,480
Speaker 1: we upload again.