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

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

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

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

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

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Speaker 3: Coverage that is possible.

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

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

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

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

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Speaker 3: What do we have personal?

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Speaker 1: Indeed, we do a lot of political news, wild stuff

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Speaker 1: going on. So Trump facing a second assassination attempt this morning.

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Speaker 1: We have a look at some really deranged social media

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Speaker 1: postings from the alleged attempt at assassin, so we'll get

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Speaker 1: into everything we know there. We've also got a whole

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Speaker 1: lot of post debate polls now things starting to come

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Speaker 1: into focus. Also, excuse me for this very cheesy cringe

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Speaker 1: thing I'm about to say, Trump and Taylor Swift not

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Speaker 1: a love story. Yeah, I had to do the thing,

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Speaker 1: all right. In addition, jd Vance spending his time attacking

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Speaker 1: yours truly and also Zenjilani and we have zed on

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Speaker 1: show to talk about that and also just to get

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Speaker 1: into war what the hell is going on there? Jadi

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Speaker 1: was on a bunch of the Sunday shows yesterday talking

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Speaker 1: about the whole.

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Speaker 4: Haitian pet situation. So a lot to dig into there

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Speaker 4: for sure.

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Speaker 1: Also Trump in his Laura Lumor era, what does that

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Speaker 1: mean for him and the campaign? What does the potential

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Speaker 1: fallout as Lumor and Marjorie Taylor Green are also completely

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Speaker 1: beefing in the messiest way possible.

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Speaker 4: So a lot that's interesting there.

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Speaker 1: Bill Maher making a stunning prediction saying it is over

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Speaker 1: over for Donald Trump. Yeah, we will see if he

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Speaker 1: is right. Could be Also speaking of messiness, messy fight

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Speaker 1: beef between Jill Stein and AOC that we can dig

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Speaker 1: into as well.

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Speaker 4: After Jill Stein was on the Breakfast Club. Very interesting

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Speaker 4: appearance there.

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Speaker 3: Yes, that will be very interesting.

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Speaker 2: Now, as Crystal said, we're going to go ahead and

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Speaker 2: just go straight into this second second attempted assassination of

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Speaker 2: Donald Trump's Let's go ahead and put this up there

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Speaker 2: on the screen. We've got some of the details now

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Speaker 2: on the suspect. The alleged shooter is suspect's name is

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Speaker 2: Ryan Routh. He's in custody following that assassination attempt on

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Speaker 2: Trump at the Florida Golf Club. On the right, For

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Speaker 2: those who are watching, you could see the photo of

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Speaker 2: him whenever he was arrested by authorities. The story behind

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Speaker 2: this is honestly quite crazy. So we can go to

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Speaker 2: the next part please, which is a map that shows

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Speaker 2: a little bit of how some of this went down.

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Speaker 3: Now, according to Sean Hannity.

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Speaker 2: Who was on the phone with Trump and actually was

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Speaker 2: supposed to golf with Trump that day, he said that

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Speaker 2: Donald Trump was playing on the fifth hole of the

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Speaker 2: West Palm Beach golf Course. It is the quote long

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Speaker 2: part in the northeastern corner. So for those who are looking,

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Speaker 2: the green is about fifty yards from South Congress Avenue.

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Speaker 2: The six tea box is right at the end of

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Speaker 2: the road. You could see exactly on the map where

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Speaker 2: all of this went down. Now, the alleged way that

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Speaker 2: this all happened is that Donald Trump was golfing the

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Speaker 2: Secret Service agents were scouting a couple of holes ahead

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Speaker 2: of him. During that scouting, one agent spotted a man

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Speaker 2: with a long gun, which has now been confirmed to

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Speaker 2: be an ak forty seven in a so called nest

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Speaker 2: where there were two bags and a long rifle that

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Speaker 2: were found. The agents began firing at him, So at

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Speaker 2: no point, according to the official narrative, there any shots

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Speaker 2: squeezed off by Ryan. Routh dropped his weapon or I

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Speaker 2: guess leaned it up against the defence, ran away, so

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Speaker 2: the Secret Service agents did not hit him. He was

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Speaker 2: able to get into his car. A nearby bystander actually

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Speaker 2: was able to take a photo of Routh's car and

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Speaker 2: his license plate, which allowed police to zero in on

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Speaker 2: the type of vehicle they were searching for. He was

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Speaker 2: actually able to exit the county before he was then

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Speaker 2: arrested by Sheriff's deputies. So that is the official of

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Speaker 2: what we've got. We actually have here some of the

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Speaker 2: sound of the sheriff kind of breaking some of this down.

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Speaker 2: Sheriff Rick Bradshaw giving a press conference following by a

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Speaker 2: Secret Service investigation.

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Speaker 3: Let's take a listen.

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Speaker 5: Afternoon call came out, shots fired. That was called in

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Speaker 5: by Secret Service. Because we're in constant contact with them

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Speaker 5: all the time. We were notified of that and we

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Speaker 5: had units here that immediately sealed off the area. Fortunately

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Speaker 5: we were able to locate a witness that came to

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Speaker 5: us and said, hey, I saw the guy running out

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Speaker 5: of the bushes. He jumped into a black Nissan and

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Speaker 5: I took a picture of the vehicle and the tank,

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Speaker 5: which was great. So we had that information. Our Real

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Speaker 5: Time Crime Center put it out to the license plate

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Speaker 5: readers and we were able to get a hit on

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Speaker 5: that vehicle on nine ninety five as it was headed

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Speaker 5: into Martin County. We got a hold of Martin County

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Speaker 5: Sheriff's office alerted them and they spotted the vehicle and

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Speaker 5: pulled it over and detained the guy. After that, we

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Speaker 5: took the victim. I'm sorry. The witness that witnessed the

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Speaker 5: incident took flew him up there and he identified as

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Speaker 5: the person that he saw running out of the bushes

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Speaker 5: that jumped into the car. Now in the bushes where

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Speaker 5: this guy was is an eight K forty seven style

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Speaker 5: rifle with a scope, two backpacks which were hung on

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Speaker 5: the fist that had a ceramic tile in him, and

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Speaker 5: a go pro which he was going to take pictures.

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Speaker 6: Notes.

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Speaker 5: They have an agent that jumps one hole ahead of

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Speaker 5: time to where the president was at and he was

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Speaker 5: able to spot this rifle barrel sticking out of the

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Speaker 5: fens and immediately engage that individual, at which time the

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Speaker 5: individual took far.

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Speaker 3: So that's what we got right now, Crystal.

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Speaker 2: Now social media has now come out about mister Ryan Routh.

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Speaker 3: Let's just say a little bit of a lunatic. But

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Speaker 3: I will say he's.

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Speaker 2: A lunatic who spent quite a long time in Ukraine

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Speaker 2: recently seems to have made it his life's cause to

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Speaker 2: support the Ukrainian military. He appointed himself ahead of the

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Speaker 2: International Volunteer Office. He was quoted by the New York

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Speaker 2: Times and by Semaphore he allegedly met here in one,

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Speaker 2: Washington with members of Congress, the US Helsinki Commission, which

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Speaker 2: directs military resources to Ukraine. I mean, you know, certainly

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Speaker 2: something his social media has got self published books and others.

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Speaker 2: Members of the Ukrainian International Legion have actually come out

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Speaker 2: previously to this and said he was a lunatic.

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Speaker 3: They had nothing to do with them.

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Speaker 2: But at the very least, you know, he had claimed

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Speaker 2: to have had multiple meetings with the US Defense Ministry,

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Speaker 2: shuttling back and forth between there. So he's a troubled individual.

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Speaker 2: Nobody who wants to shoot the President is like a

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Speaker 2: normal person, So let's just say that. But it's clearly

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Speaker 2: there was something enough going on that he was found

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Speaker 2: incredible enough to be quoted by these US news agencies.

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Speaker 2: It also, does, you know, raise a real question here

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Speaker 2: about US Secret Service.

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Speaker 3: So you could view it two ways.

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Speaker 2: Well, they had a person who was ahead of him, Yeah,

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Speaker 2: and he saw the gun and he shot at him.

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Speaker 2: The other thing is, well, should he really have been

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Speaker 2: on the golf course at all? And the sheriff does

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Speaker 2: get to that, But before you, before we get to

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Speaker 2: the sheriff, do you want to weigh in on any

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Speaker 2: of this.

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Speaker 1: Yeah, I'll get to ryan else in a bit, because

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Speaker 1: they're going to show some of the social media postings,

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Speaker 1: et cetera. We can, you know, do our best to

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Speaker 1: dig into the psyche of a clearly durranged individual, but

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Speaker 1: there will be, of course, a lot more questions for

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Speaker 1: the Secret Service here. It appears that he came within

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Speaker 1: some five hundred yards, which we are about to show

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Speaker 1: the clip. You know, that is a further distance than

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Speaker 1: the last guy, and this one didn't get any shots off.

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Speaker 1: So Secret Service clearly did a better job in this instance.

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Speaker 1: But there still will obviously be questions of how you

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Speaker 1: could have even this close of a call. In addition,

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Speaker 1: they just completed Congress just completed report on the manifest

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Speaker 1: security failures of the Secret Service with regard to the

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Speaker 1: attempted assassination, the previous one in Butler, where obviously, you know,

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Speaker 1: the president came within a quarter inch of his of

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Speaker 1: losing his life there on a stage in front of

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Speaker 1: rally goers, and one of the rally goers did lose

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Speaker 1: his life was murdered there because of those incredible failures.

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Speaker 1: So this will raise a lot more questions of how

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Speaker 1: he was even able to come this close. But yeah,

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Speaker 1: the social media postings when we get there are really something.

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Speaker 1: It seems that Ukraine was an absolute fixation for this guy.

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Speaker 1: He was running a website that he claimed was, you know,

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Speaker 1: for foreign fighters from around the world to be able

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Speaker 1: to sign up to go fight in Ukraine. He has

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Speaker 1: multiple postings where he's like, I want to go fight

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Speaker 1: and die for the Ukrainians their war.

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Speaker 3: He wrote a book about that. He said, why nuclear war,

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Speaker 3: Oh Jesus, I didn't know that it's the thing. Look, Haley,

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Speaker 3: which you know, I'm just going to.

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Speaker 2: Move away from his musings and just like, Okay, what

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Speaker 2: do we actually know about this guy? And like, what

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Speaker 2: we know is that he was in Ukraine for months,

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Speaker 2: he was running an organization. He was found credible enough

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Speaker 2: to be quoted by The New York Times by Semaphore,

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Speaker 2: who assumed to be believe that he was some person

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Speaker 2: who was involved in this cast I have to believe

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Speaker 2: that he at the very least had some credibility to

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Speaker 2: allegedly get meetings with the Defense Ministry.

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Speaker 3: He was always on social media.

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Speaker 2: Now, look, it's certainly possible that he was fooling everybody.

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Speaker 2: So it was kind of embarrassing for multiple news outlets too.

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Speaker 2: Who and the person who quoted him, Thomas Gibbons Steff,

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Speaker 2: in my opinion, the best military reporter who's out there.

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Speaker 2: He's done multiple reports actually about Israel, about the misconduct

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Speaker 2: of the IDF. He's done some of the reports in

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Speaker 2: Ukraine about Ukrainian friendly fire which killed their own citizens.

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Speaker 2: He was a banned from Ukraine by the Ukrainians. He's

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Speaker 2: done a lot of good reporting on Afghanistan himself. As

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Speaker 2: a former US Marine, I followed him for over a decade.

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Speaker 2: I remember covering the Pentagon and seeing him there. I

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Speaker 2: think he's very, very talented, and so for him to

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Speaker 2: quote him, he has written a piece now this morning

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Speaker 2: said yeah, he said he was laughing when he got

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Speaker 2: off the phone with him because he thought he was

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Speaker 2: in over his head. But he still quoted him, and

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Speaker 2: he put him in the story. So I'm like, Okay, well,

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Speaker 2: I think there's something. I think that the US Helsinki

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Speaker 2: Commission and the government need to answer questions about whether

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Speaker 2: they directed resources and worked with this individual. I like

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Speaker 2: I said, I don't want to say they were all

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Speaker 2: in together. The National Legion of Ukraine literally denounced him

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Speaker 2: earlier and they put out multiple threats saying don't work

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Speaker 2: with this guy. But his life's mission was apparently enough

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Speaker 2: to get him involved with Afghan fighters who wanted to

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Speaker 2: go to Ukraine. That seemed to be like the major

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Speaker 2: conduit that he was trying to run and help here

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Speaker 2: in Washington.

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Speaker 3: So is he crazy, absolutely, and we will get to that.

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Speaker 2: But he was crazy enough, you know, to also bamboozle

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Speaker 2: his way into quite a few big level rooms here.

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Speaker 4: I think he also had quite a lengthy rap sheet.

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Speaker 1: I mean yes. In addition, he you know, in two

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Speaker 1: thousand and two he was charged with having a weapon

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Speaker 1: of mass destruction because he had a fully automatic AK

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Speaker 1: forty seven. He had AK forty seven in this instance

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Speaker 1: as well, So I also have a lot of questions

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Speaker 1: about how he obtained.

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Speaker 4: This weapon, whether it was lawful.

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Speaker 1: To me, it seems insane that someone with this previous

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Speaker 1: charge and he had like barricaded himself in somewhere. It

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Speaker 1: was like a wild scene.

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Speaker 2: Two thousand and two he had was like a fleeing

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Speaker 2: the cop situation. He barricaded himself in two thousand and two.

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Speaker 2: When he was arrested, he was actually charged with weapons

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Speaker 2: of mass destruction charge in North Carolina, I had multiple

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Speaker 2: traffic violations and if his son was like, as far

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Speaker 2: as I know, he's only ever been arrested for attack

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Speaker 2: for traffic violation, I'm like, all right, bro, there's also

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Speaker 2: barricaded himself in a room.

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Speaker 4: With the automatic.

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Speaker 7: LA.

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Speaker 1: I mean to me, it's insane that someone who has

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Speaker 1: that on the like to me, and once you have

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Speaker 1: that on your record, that's it.

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Speaker 2: I have to check. It depends where he bought it too,

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Speaker 2: it depends. I mean, there should also be a failure

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Speaker 2: of a background checks, so yeah, that would be that. Yeah,

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Speaker 2: it's happened multiple times. There was a shooting back in time.

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Speaker 2: I'm forgetting exactly. I think it was in somewhere in Texas.

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Speaker 2: It was a church and the person never legally obtain

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Speaker 2: a weapon. It was actually a huge failure of the

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Speaker 2: background check system. So that actually could be interesting if

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Speaker 2: he legally obtained it. If he legally obtained it as well,

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Speaker 2: what the tie in who the funding was for the

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Speaker 2: first doesn't appear to have a job. I mean, that's

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Speaker 2: kind of the weird thing about this. He's flitting about

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Speaker 2: living on the beach in Hawaii, at one point bragging

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Speaker 2: about skimpy girls in bikinis around him from text messages

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Speaker 2: that I reviewed, but then also appears to have had

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Speaker 2: at least some funds to be able to travel back

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Speaker 2: and forth to Ukraine to Washington. Multiple photos of here

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Speaker 2: in DC in a suit and tie outside the capital,

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Speaker 2: you know, implying that he was meeting with people. Listen,

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Speaker 2: they're crazy people all around the city, some of them

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Speaker 2: work inside the capitol. So like, was he just fronting

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Speaker 2: this entire time? Like I said, I think that could

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Speaker 2: be the case. They're also the secret Service. Questions here

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Speaker 2: are bounding, you know. Rocanna is already calling for the

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Speaker 2: director of the Secret Service to appear back in Washington.

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Speaker 2: The acting director is actually currently down in Florida right now.

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Speaker 2: But to have, as he says, two assassination attempts in

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Speaker 2: sixty days on the former president is unacceptable. The sheriff

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Speaker 2: actually opined a little bit on this. Let's take a

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Speaker 2: listen to what he had to say.

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Speaker 5: Well, you got to understand, the golf course is surrounded

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Speaker 5: by shrubbery, so when somebody gets into the shrubbery, they're

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Speaker 5: pretty much out of sight, all right. And at this

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Speaker 5: level that he is at right now, he's not the

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Speaker 5: city president. If he was, we would have had this

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Speaker 5: higher golf course around it. Well, because he's not, the

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Speaker 5: security is limited to the areas that the Secret Service

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Speaker 5: deems possible.

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Speaker 3: So there you go.

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Speaker 2: So it's about the actual security perimeter around that. It

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Speaker 2: does seem absolutely crazy. I mean, I could tell you actually,

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Speaker 2: whenever I was on White House duty, often had to

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Speaker 2: go to the golf course with Trump and they had

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Speaker 2: that thing a lockdown.

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Speaker 8: Man.

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Speaker 2: So the first time that I heard this, I was

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Speaker 2: honestly shocked, because I'd seen a little bit of the

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Speaker 2: security perimeter whenever Trump was President here. He would go

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Speaker 2: to Sterling, Virginia and golf at the Trump National Golf Course,

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Speaker 2: which is nearby, And I had to do that a

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Speaker 2: couple of times whenever I was running pool duty. Basically

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Speaker 2: just sit in the car away for him to be done.

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Speaker 2: But you know, you get to see and observe a

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Speaker 2: little bit of where it all is. Secret Service is

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Speaker 2: always tracking his movement. They're like, hey, he's on the

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Speaker 2: eighth hole. No, he's one of the ninth hole. They've

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Speaker 2: got a whole perimeter around that in terms of the

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Speaker 2: people who are around him. So for him to be

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Speaker 2: able to get within you know, several hundred yards of

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Speaker 2: the president, you know, with the long range weapon. Also,

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Speaker 2: I mean, I don't think enough people are paying attention

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Speaker 2: to the fact that they took a shot at him

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Speaker 2: and they missed. Not only do they miss, he's able

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Speaker 2: to actually lead the gap.

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Speaker 3: And drive away.

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Speaker 2: So I'm like, well, then you don't have a secure

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Speaker 2: perimeter clearly around it or something like that.

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Speaker 3: Yeah, never would have happened. Seacret Service has got a

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Speaker 3: lot of questions here and we haven't.

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Speaker 2: Had this many attempted assassination attempts legit ones on a

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Speaker 2: former president since Gerald Ford in the nineteen seventies, in

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Speaker 2: the same actually similar time frame. I think it was

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Speaker 2: seventeen days where somebody came very close to killing him twice.

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Speaker 3: One of them was a Manson family.

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Speaker 1: I mean, Christ, it seems clear like we need to

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Speaker 1: beef up security around former President Trump, like he should

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Speaker 1: have the level of Secret Service protection that you know,

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Speaker 1: a sitting president would have, because you know, the thing

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Speaker 1: that is most troubling to me is, in some ways,

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Speaker 1: this seems like a horrifying new normal. You know, once

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Speaker 1: these hor horrible, terrifying bad ideas get out there in

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Speaker 1: the public, there's often a copycat effect. You know, you've

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Speaker 1: seen this with school shootings as well, and you say

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Speaker 1: it even with you know, epidemics of suicide in areas.

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Speaker 1: Once a bad idea takes hold, you know, there's no

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Speaker 1: reason why we should think that Ryan Ralth will be

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Speaker 1: the last person who gets it in their head that

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Speaker 1: they're going to take a shot at former President Trump

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Speaker 1: or an other high level elected official. So you know,

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Speaker 1: to me, it's it's a no brainer. Like I said, Listen,

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Speaker 1: they did their job. They made sure he didn't get

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Speaker 1: a shot off. They were able to capture him through

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Speaker 1: some of the fortunate good work of local law enforcement

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Speaker 1: as well. But there's no reason why this individual should

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Speaker 1: have been able to get even this close to former

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Speaker 1: President Trump. And you know, I mean that golf course.

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Speaker 1: It's it's right there on the.

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Speaker 3: Stage, right right on the show, as we showed in

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Speaker 3: the mask.

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Speaker 4: Yeah, you could see where he was.

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Speaker 1: Was probably not a difficult place to get to if

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Speaker 1: you just you know, duck offence or jump offence or whatever,

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Speaker 1: and you're right there within hundreds of yards of the

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Speaker 1: former president potentially future president. So you know, it's it's

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Speaker 1: wild when you realize how actually insecure all of these

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Speaker 1: situations are. Whether it's a rally, which you can understand

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Speaker 1: is very difficult situation to control, but there were manifest

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Speaker 1: incredible failures there, or him just going out to do

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Speaker 1: something he does quite frequently, play golf on one of

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Speaker 1: his golf co.

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Speaker 3: Thing on the planet. You're like, oh, it's Sunday, Yeah,

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Speaker 3: Trump is gonna be.

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Speaker 4: He's gonna be golfing somewhere.

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Speaker 3: He's like a clock.

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Speaker 6: Yeah.

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Speaker 1: I saw some people online like I already know he

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Speaker 1: was gonna be golfing.

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Speaker 4: I was like, it's a day that.

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Speaker 1: Ends in why, like that's the majority of what he

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Speaker 1: spends his time doing.

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Speaker 2: I feel a bit of this way, the way that

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Speaker 2: I always do about TSA, where I'm like, this is

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Speaker 2: all fake.

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Speaker 3: You know me, hours of my life have.

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Speaker 2: Been wasted by the US Secret Service, waiting in line

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Speaker 2: for them to pat me down, taking people's nicotine vapes

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Speaker 2: away in the White House, going through your bag and

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Speaker 2: making sure your laptop is Meanwhile, you're shaking me, you know,

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Speaker 2: everybody else who's ever coming to the White House down.

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Speaker 2: I'm to submit my Social Security number and all this

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Speaker 2: other stuff, which I always thought, yeah, fine, you know,

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Speaker 2: I'm walking into the White House.

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Speaker 3: But now you get two.

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Speaker 2: Incidents in sixty days, I'm like, okay, jokers, what was

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Speaker 2: all of that for?

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Speaker 3: Was this all fake?

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Speaker 2: The entire time? This is you know, it's like, have

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Speaker 2: you just been wasting our time? But you can't even

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Speaker 2: do the very basics of your job. And as we

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Speaker 2: covered after the first attempted assassination, a lot of that

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Speaker 2: ended up being correct. You had the Columbia nightmare with

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Speaker 2: all those agents. You've had multiple incidents where people were

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Speaker 2: able to get close to the president, huge failures. There's

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Speaker 2: some meltdown going on on Kamala's Secret Service detail. This

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Speaker 2: whole agency obviously just needs to be totally burned to

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Speaker 2: the ground and reform well.

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Speaker 1: And that was one of the things we said after

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Speaker 1: the first attempt too, is there's an illusion I had

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Speaker 1: an illusion of, like, you know, oh, the protection around

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Speaker 1: these high level individuals, these protectees are going to be

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Speaker 1: is going to be air tight like rocks, like there's

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Speaker 1: no way someone could penetrate. And so it's not only

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Speaker 1: us that notice like, oh this is not so as difficult,

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Speaker 1: it's not so so hardened as we thought that it was.

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Speaker 1: You know, it's unhinged individuals like Ryan Ralph who also

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Speaker 1: saw that and said, hey, I think I could I

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Speaker 1: think I could do something here and tried to take

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Speaker 1: matters into his own hands. So, you know, unfortunately, like

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Speaker 1: I said, I fear that this could be a new normal.

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Speaker 1: And so that's why there's there's no doubt in my

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Speaker 1: mind like the level of protection, the resources that are

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Speaker 1: being dedicated to his protection in particular, should be dramatically increased.

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Speaker 3: Very scary. Let's go, as you said, we tease this now, mister.

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Speaker 4: Ralth's everybody wants to know this guy is yeah.

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Speaker 2: Put this up there. He doesn't really fit. The only

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Speaker 2: thing you could really pin him on is Ukraine. Everything

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Speaker 2: else cannot really So here's, for example, some tweets recently

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Speaker 2: he said, I would like to buy a rocket from

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Speaker 2: you to Elons. I wish to load it with a

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Speaker 2: warhead for Putin's Black Sea mansion bunker. Can you give

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Speaker 2: me a price? It can be old and used as

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Speaker 2: not returning List's phone number and phone number aid dot

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Speaker 2: in Ukraine at gmail dot com. He also asked Elton

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Speaker 2: John if he would do a tribute song to Ukraine.

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Speaker 2: He also wanted one from Dave Matthews Band and several

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Speaker 2: other artists. Let's also put the next one please up

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Speaker 2: on the screen. This has got funny summary. Ryan Ralth

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Speaker 2: voted for Trump, donated Tulci Gabbard, Andrew Yang, Tom Steyer, Beto,

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Speaker 2: Elizabeth Warren, and has tweets that like this yearning for

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Speaker 2: a Nikki Haley vivik Ramaswami ticket, which is to say,

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Speaker 2: it's a bit hard to put him in a convenient

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Speaker 2: little box. Certainly funny because you're like, really vivake. He

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Speaker 2: was the only person who was even somewhat consistent about Ukraine.

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Speaker 4: Yeah, that was interesting. The Nikki Haley part makes sense.

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Speaker 2: Yeah, the Nikki Haley thing totally tracks. But VIVEQ like

428
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Speaker 2: what I'm like, did you ever listen to the guy

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Speaker 2: as usual? Do not expect ideological cohesion and reason from

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Speaker 2: somebody who tries to kill the press.

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Speaker 1: Well, plenty of average voters have voting histories and interests

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Speaker 1: that look like this too.

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Speaker 3: So this was a crime. A lot of people would

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Speaker 3: be guilty. Finally, he actually have some words from Ryan himself.

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Speaker 2: He sat down with Newsweek for an interview I think

436
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Speaker 2: it was about two years ago or so inside of Ukraine,

437
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Speaker 2: talking about why he supports the cause.

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Speaker 3: Let's take a listen.

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Speaker 6: Please tell me who you are and why are you here?

440
00:19:41,160 --> 00:19:45,720
Speaker 7: Fifty six from the US from North Carolina originally so

441
00:19:45,880 --> 00:19:47,520
Speaker 7: live in Hawaii now, so it flew all the way

442
00:19:47,560 --> 00:19:51,000
Speaker 7: from Hawaii here. So the question as far as why

443
00:19:51,040 --> 00:19:54,240
Speaker 7: I'm here, so me. You know, a lot of the

444
00:19:54,280 --> 00:19:57,480
Speaker 7: other conflicts are gray, but this conflict is definitely black

445
00:19:57,520 --> 00:20:00,640
Speaker 7: and white. This is about good versus evil. This is

446
00:20:00,680 --> 00:20:03,280
Speaker 7: a storybook, you know, any movie we've ever watched. This

447
00:20:03,359 --> 00:20:08,040
Speaker 7: is definitely evil against good. I mean, we're battling a

448
00:20:08,040 --> 00:20:11,359
Speaker 7: situation here where you know, the Ukrainians and the rest

449
00:20:11,359 --> 00:20:15,320
Speaker 7: of the world are caring and kind and generous and

450
00:20:15,760 --> 00:20:19,320
Speaker 7: unselfish and take care of one another, and it's just

451
00:20:19,359 --> 00:20:22,600
Speaker 7: a matter of you know, we need to stand up

452
00:20:22,600 --> 00:20:25,200
Speaker 7: for that. That is the most important thing in the world,

453
00:20:25,280 --> 00:20:27,720
Speaker 7: is just to show human beings that we're kind and

454
00:20:27,800 --> 00:20:29,639
Speaker 7: we're caring, and that we take care of one another

455
00:20:29,680 --> 00:20:30,560
Speaker 7: and the world.

456
00:20:30,480 --> 00:20:33,840
Speaker 3: Is united and some sort of coherence there keep it together.

457
00:20:33,880 --> 00:20:36,040
Speaker 2: He was doing a lot of interviews. A YouTuber actually

458
00:20:36,119 --> 00:20:39,359
Speaker 2: ran into him on the street. It appears in whenever

459
00:20:39,480 --> 00:20:41,160
Speaker 2: he was trying to recruit people, He's like, I'm looking

460
00:20:41,160 --> 00:20:42,680
Speaker 2: for people who want to tear down the system.

461
00:20:42,680 --> 00:20:43,960
Speaker 3: I'm looking for mercenaries.

462
00:20:44,000 --> 00:20:48,640
Speaker 2: So yeah, clearly he had something going on within him.

463
00:20:48,680 --> 00:20:50,320
Speaker 2: Like I said, I mean, my main question here is

464
00:20:50,320 --> 00:20:51,960
Speaker 2: I'm like, hey, did any members of Congress meet with

465
00:20:51,960 --> 00:20:55,359
Speaker 2: this guy? I'm like, Ukrainian armed forces to what involvement

466
00:20:55,640 --> 00:20:58,000
Speaker 2: did you have with Ryan Rauth and the gentleman?

467
00:20:58,200 --> 00:21:00,159
Speaker 3: Is there a grand conspiracy? I'm not saying that, but

468
00:21:00,280 --> 00:21:02,880
Speaker 3: I mean, at the very least it is. It revealed

469
00:21:02,880 --> 00:21:03,320
Speaker 3: something to.

470
00:21:03,280 --> 00:21:06,320
Speaker 2: Me about the Ukrainian cause, and also I've been speaking

471
00:21:06,359 --> 00:21:09,160
Speaker 2: with others. A lot of people don't with all war

472
00:21:09,240 --> 00:21:11,840
Speaker 2: zones all you know, crazy chaotic situations.

473
00:21:11,920 --> 00:21:13,880
Speaker 3: Yeah, weirdos flock to them.

474
00:21:14,200 --> 00:21:16,520
Speaker 2: Anybody in America who just picks up arms to go

475
00:21:16,560 --> 00:21:20,000
Speaker 2: fight for free in Ukraine and something all together going

476
00:21:20,040 --> 00:21:22,960
Speaker 2: on there, and you know, there's something that clearly was

477
00:21:22,960 --> 00:21:25,480
Speaker 2: involved here for them too. Shows their desperation for who

478
00:21:25,480 --> 00:21:27,000
Speaker 2: they're willing to work with.

479
00:21:27,080 --> 00:21:29,679
Speaker 1: And it's also like people who have a fixation on

480
00:21:29,760 --> 00:21:31,800
Speaker 1: being at the center of history, you know what I mean.

481
00:21:32,040 --> 00:21:33,000
Speaker 3: So there's a lot of people like that.

482
00:21:33,200 --> 00:21:35,160
Speaker 1: Yeah, there are a lot of people like that, and they,

483
00:21:35,280 --> 00:21:38,119
Speaker 1: you know, flock to conflicts like this one or like

484
00:21:38,160 --> 00:21:41,679
Speaker 1: others to try to you know, be live out whatever

485
00:21:41,800 --> 00:21:45,640
Speaker 1: grand narrative idea they're trying to. They're trying to live out,

486
00:21:45,720 --> 00:21:47,679
Speaker 1: by the way, for people who are just listening and

487
00:21:47,760 --> 00:21:48,440
Speaker 1: not watching.

488
00:21:48,840 --> 00:21:52,119
Speaker 4: In that video, he has his hair dyed yed half

489
00:21:52,240 --> 00:21:54,080
Speaker 4: no half blue and half yellow.

490
00:21:54,880 --> 00:21:56,400
Speaker 3: Yeah I thought it was an American thing.

491
00:21:56,520 --> 00:21:58,679
Speaker 1: Well, he has an American T shirt on and then

492
00:21:58,720 --> 00:22:00,959
Speaker 1: the hair is dyed Ukraine and yellow and blue. Just

493
00:22:00,960 --> 00:22:03,359
Speaker 1: to show you, you know, the level of commitment he

494
00:22:03,440 --> 00:22:05,760
Speaker 1: had to this, cause I don't know, the thing I

495
00:22:05,800 --> 00:22:07,919
Speaker 1: was thinking about is how easy it is to like

496
00:22:08,160 --> 00:22:10,439
Speaker 1: trick the news Meetia. I can't even really blame him, Like,

497
00:22:10,880 --> 00:22:13,919
Speaker 1: you know, you set up a website, you set up

498
00:22:13,920 --> 00:22:18,360
Speaker 1: an email address at ukrainead dot com or whatever, and

499
00:22:19,200 --> 00:22:21,400
Speaker 1: you get a couple people. If you can get one

500
00:22:21,440 --> 00:22:25,040
Speaker 1: person to quote you as a credible source, then most

501
00:22:25,040 --> 00:22:27,280
Speaker 1: outlets that come after that are just going to look at, Oh,

502
00:22:27,280 --> 00:22:30,240
Speaker 1: Semaphore quoted it right, Newsweek interview, This must be legit.

503
00:22:30,400 --> 00:22:32,800
Speaker 1: And like I said, I mean it takes given the

504
00:22:32,880 --> 00:22:35,800
Speaker 1: number of quotes they have to amass and churn out

505
00:22:35,840 --> 00:22:38,720
Speaker 1: their pieces, like it makes sense. You just go like, oh, well,

506
00:22:38,800 --> 00:22:41,360
Speaker 1: so and so over at Semaphore, the reporter you talked about,

507
00:22:41,359 --> 00:22:43,240
Speaker 1: he said him seriously and he's a credible guy. Like

508
00:22:43,280 --> 00:22:44,879
Speaker 1: all right, if you takes them seriously, then I'm going

509
00:22:44,960 --> 00:22:47,680
Speaker 1: to take him seriously. And next thing you know he's

510
00:22:47,680 --> 00:22:50,120
Speaker 1: built up this profile is if he's this like credible

511
00:22:50,160 --> 00:22:52,560
Speaker 1: individual on the Ukrainian cause, but.

512
00:22:52,480 --> 00:22:54,200
Speaker 2: He also could have been a credible individual in the

513
00:22:54,280 --> 00:22:56,480
Speaker 2: Ukrainian cause. I mean, I mean that's the thing I

514
00:22:56,520 --> 00:22:57,919
Speaker 2: want to know. Did they meete with him, did they

515
00:22:57,920 --> 00:23:00,399
Speaker 2: funnel on any resources to him? Not the Ukraine as

516
00:23:00,440 --> 00:23:03,560
Speaker 2: the US. I'm probably more involved interested in that because

517
00:23:03,880 --> 00:23:06,119
Speaker 2: what we have been hearing for over two years is

518
00:23:06,160 --> 00:23:11,760
Speaker 2: that every possible variation of grifter, of arms dealer, of

519
00:23:11,840 --> 00:23:14,520
Speaker 2: sketchy individual is that there is a ton of money

520
00:23:14,800 --> 00:23:16,840
Speaker 2: to be made in Ukraine and that it's you know,

521
00:23:16,880 --> 00:23:20,639
Speaker 2: it's a totally buyer's market. And if you look at

522
00:23:20,680 --> 00:23:22,760
Speaker 2: some of the people, like we've covered the arms dealer

523
00:23:22,760 --> 00:23:24,760
Speaker 2: in the past, the guy who bought a yacht who

524
00:23:24,840 --> 00:23:27,080
Speaker 2: is criminally not even allowed to be in arms sales,

525
00:23:27,080 --> 00:23:31,119
Speaker 2: but he's printing money off of Ukraine. Malcolm Nantz, you know,

526
00:23:31,320 --> 00:23:34,040
Speaker 2: was quoted in the same story about stolen Valor that

527
00:23:34,160 --> 00:23:37,520
Speaker 2: Ryan Routh was in Thomas Gibbons snaffs. So there's a

528
00:23:37,520 --> 00:23:39,960
Speaker 2: lot of crazy folks, a lot of them US citizens,

529
00:23:39,960 --> 00:23:42,520
Speaker 2: who are involved in this. But and that's one thing.

530
00:23:42,560 --> 00:23:44,600
Speaker 2: It's fine to be crazy. It's another when you put

531
00:23:44,680 --> 00:23:47,840
Speaker 2: guns in their hand. Now, according to the stuff that

532
00:23:47,880 --> 00:23:50,240
Speaker 2: I've seen so far, it does not appear that he

533
00:23:50,280 --> 00:23:53,760
Speaker 2: did actually fight for the Ukrainian cause. He was based

534
00:23:53,840 --> 00:23:58,080
Speaker 2: either in in Leviv or in Kiev at various different

535
00:23:58,080 --> 00:24:02,280
Speaker 2: times with this international or organization for Volunteers is what

536
00:24:02,320 --> 00:24:04,480
Speaker 2: he called it in terms of his meetings with the

537
00:24:04,520 --> 00:24:07,280
Speaker 2: Defense Ministry. But yeah, like you said, it could be

538
00:24:07,320 --> 00:24:08,800
Speaker 2: that he was fronting this whole time. But he could

539
00:24:08,800 --> 00:24:12,480
Speaker 2: have used that to a certain end, like getting meetings

540
00:24:12,600 --> 00:24:14,600
Speaker 2: with members you know, I know, to getting me mad

541
00:24:14,640 --> 00:24:15,720
Speaker 2: with them of Congress. It was like, hey, I was

542
00:24:15,760 --> 00:24:18,320
Speaker 2: quoted by the New York Times, right, yeah, parlayed.

543
00:24:17,960 --> 00:24:20,000
Speaker 3: That something interesting. Absolutely.

544
00:24:20,400 --> 00:24:23,240
Speaker 2: Anyway, I'm interested in the FBI investigation. Not that they'll

545
00:24:23,280 --> 00:24:26,240
Speaker 2: ever tell us anything, I guess, at least in this case.

546
00:24:26,240 --> 00:24:28,520
Speaker 2: They took him alive, so hopefully he'll have to go

547
00:24:28,600 --> 00:24:31,280
Speaker 2: to trial or there will at some point there will

548
00:24:31,320 --> 00:24:34,960
Speaker 2: be a plea bargain or some you know, files released

549
00:24:34,960 --> 00:24:37,520
Speaker 2: through the judicial system to learn a little bit about this.

550
00:24:38,040 --> 00:24:41,240
Speaker 2: Some questions about the gun that he obtained, his own

551
00:24:41,320 --> 00:24:43,399
Speaker 2: travel back and forth from Ukraine.

552
00:24:43,480 --> 00:24:45,760
Speaker 3: But there were some there were some weird stuff, you know,

553
00:24:45,640 --> 00:24:46,600
Speaker 3: you know, I'm joking.

554
00:24:46,600 --> 00:24:49,920
Speaker 4: He's actually a good point though. If that is actually

555
00:24:49,960 --> 00:24:51,919
Speaker 4: a good point, the fact that they took him alive

556
00:24:52,160 --> 00:24:54,760
Speaker 4: is the best sign that is there's no grand conspiracy.

557
00:24:54,840 --> 00:24:57,439
Speaker 3: Fair enough, right, Well, they took Oswald live.

558
00:24:57,320 --> 00:24:59,639
Speaker 1: Too, Yeah, but that didn't last. It didn't last.

559
00:24:59,880 --> 00:25:02,439
Speaker 2: Was it's only twenty four hours in right, yep, everybody

560
00:25:02,480 --> 00:25:03,840
Speaker 2: got to watch the TV very dark.

561
00:25:03,920 --> 00:25:05,240
Speaker 3: Let's see what happens to this gentleman.

562
00:25:07,920 --> 00:25:10,439
Speaker 2: Let's turn down to the presidential race, where he's got

563
00:25:10,440 --> 00:25:12,399
Speaker 2: a lot of new polling that's come in since that

564
00:25:12,440 --> 00:25:15,159
Speaker 2: presidential debate. Let's put this up there on the screen.

565
00:25:15,240 --> 00:25:18,800
Speaker 2: Nate Silver's general analysis. He says, today's update after an

566
00:25:18,800 --> 00:25:21,800
Speaker 2: Atlas Intel poll cut against what was otherwise strong day

567
00:25:21,800 --> 00:25:22,679
Speaker 2: of polling for Harris.

568
00:25:23,000 --> 00:25:25,560
Speaker 3: It is a highly rated poll. Resist the temptation to unskew.

569
00:25:25,920 --> 00:25:28,320
Speaker 2: Still enough good data for her that the race is

570
00:25:28,400 --> 00:25:30,840
Speaker 2: now officially in toss up range.

571
00:25:30,880 --> 00:25:33,159
Speaker 3: So he hasn't given us a latest update.

572
00:25:33,200 --> 00:25:36,240
Speaker 2: The last one I saw for his projection was sixty forty,

573
00:25:36,280 --> 00:25:38,640
Speaker 2: so toss up range. I'm assuming he's moving more into

574
00:25:38,680 --> 00:25:41,640
Speaker 2: like fifty five forty five, and whatever his latest.

575
00:25:41,400 --> 00:25:44,520
Speaker 1: He's any considers would be anything over a forty percent

576
00:25:44,600 --> 00:25:46,159
Speaker 1: chance to be toss up. I could see that, So

577
00:25:46,240 --> 00:25:49,320
Speaker 1: sixty forty he still considers to be toss up. But yeah,

578
00:25:49,359 --> 00:25:50,959
Speaker 1: we haven't had an update since then to see if

579
00:25:50,960 --> 00:25:51,800
Speaker 1: it's moved even.

580
00:25:51,600 --> 00:25:52,320
Speaker 4: More towards her.

581
00:25:52,400 --> 00:25:55,280
Speaker 2: I think that's actually quite reasonable, especially considering you know again,

582
00:25:55,320 --> 00:25:57,600
Speaker 2: if you had a forty percent chance of something crazy.

583
00:25:57,359 --> 00:25:58,760
Speaker 3: Happen, you would take it pretty seriously.

584
00:25:58,800 --> 00:26:00,960
Speaker 2: Oh yeah, he would be like, Okay, I think that's

585
00:26:01,359 --> 00:26:04,520
Speaker 2: quite quite a very reasonable result.

586
00:26:04,640 --> 00:26:06,240
Speaker 3: Let's put this next one up here.

587
00:26:06,600 --> 00:26:09,800
Speaker 2: This arguably was the most important and it was released

588
00:26:09,920 --> 00:26:12,520
Speaker 2: of this Iowa Seltzer poll. This is one of the

589
00:26:12,520 --> 00:26:15,639
Speaker 2: polls that arguably drove Joe Biden out of the race

590
00:26:16,000 --> 00:26:19,240
Speaker 2: because it showed him so far down in the state

591
00:26:19,280 --> 00:26:23,880
Speaker 2: of Iowa, which then translated to Michigan and to nearby states.

592
00:26:23,920 --> 00:26:27,399
Speaker 2: So this new Des Moines Register poll actually shows Trump

593
00:26:27,480 --> 00:26:31,879
Speaker 2: leading Harris by only four points amongst likely Iowa voters, quote,

594
00:26:31,880 --> 00:26:35,240
Speaker 2: a far slimmer margin than the eighteen point lead that

595
00:26:35,320 --> 00:26:39,520
Speaker 2: Donald Trump enjoyed over Democratic Joe Biden in the late spring.

596
00:26:39,680 --> 00:26:42,600
Speaker 2: So in this poll they have him at forty seven percent,

597
00:26:42,840 --> 00:26:46,600
Speaker 2: Kamala at forty three rfk Junior actually still getting some

598
00:26:46,720 --> 00:26:49,520
Speaker 2: six percent here because it appears he's been unable to

599
00:26:49,520 --> 00:26:52,760
Speaker 2: get himself off of the ballot. Now, obviously we don't

600
00:26:52,800 --> 00:26:54,800
Speaker 2: know how that is going to split, and if you

601
00:26:54,920 --> 00:26:58,159
Speaker 2: were to count all of those people in the Trump category,

602
00:26:58,520 --> 00:27:01,560
Speaker 2: then certainly he'd be leading by quite a bit more

603
00:27:01,640 --> 00:27:03,840
Speaker 2: at the same time, they did this poll after he'd

604
00:27:03,880 --> 00:27:06,520
Speaker 2: dropped out of the race. So maybe some people are

605
00:27:06,520 --> 00:27:08,600
Speaker 2: just ride or die and they want to vote for him. Anyways,

606
00:27:08,800 --> 00:27:11,560
Speaker 2: he's changed his tune in some cases, he said, and

607
00:27:11,600 --> 00:27:14,040
Speaker 2: sometimes he said, if you live in an uncompetitive state,

608
00:27:14,080 --> 00:27:14,840
Speaker 2: you should vote for me.

609
00:27:15,160 --> 00:27:17,240
Speaker 3: If you live in a battleground state, you shouldn't vote

610
00:27:17,240 --> 00:27:17,439
Speaker 3: for me.

611
00:27:17,520 --> 00:27:20,399
Speaker 2: But regardless, a four percent lead in the state of

612
00:27:20,440 --> 00:27:22,960
Speaker 2: Iowa very far from the eighteen point lead.

613
00:27:22,800 --> 00:27:23,560
Speaker 3: He had over Biden.

614
00:27:23,720 --> 00:27:27,960
Speaker 2: Yeah, and implies a tie specifically amongst the demographic that

615
00:27:28,000 --> 00:27:31,280
Speaker 2: he would need the most in places like Michigan and

616
00:27:31,400 --> 00:27:34,720
Speaker 2: Wisconsin and surrounding areas of the Midwest, which is why

617
00:27:34,760 --> 00:27:37,439
Speaker 2: it was so important that Biden poll last time around.

618
00:27:37,600 --> 00:27:41,919
Speaker 1: So in comparison in twenty twenty, Trump won Iowa, everyone

619
00:27:41,920 --> 00:27:42,960
Speaker 1: expects him to win Iowa.

620
00:27:43,000 --> 00:27:44,399
Speaker 4: Like, yeah, let's be clear about that.

621
00:27:44,440 --> 00:27:46,320
Speaker 1: This poll isn't about like, oh my god, Comlin hars

622
00:27:46,359 --> 00:27:49,879
Speaker 1: has a chance in Iowa. It's because this poll is

623
00:27:50,000 --> 00:27:52,159
Speaker 1: so highly rated And I'll talk a little bit more

624
00:27:52,160 --> 00:27:54,520
Speaker 1: about that in a moment that people really pay attention

625
00:27:54,600 --> 00:27:55,680
Speaker 1: to it, and why it.

626
00:27:55,680 --> 00:27:58,040
Speaker 4: Was such a big deal that Joe Biden.

627
00:27:57,800 --> 00:28:01,240
Speaker 1: Was losing the state by eighteen points, and it's the

628
00:28:01,280 --> 00:28:04,400
Speaker 1: state that Trump won last time by eight points. So

629
00:28:04,440 --> 00:28:08,080
Speaker 1: the fact that in this poll Kamala has had Trump's

630
00:28:08,119 --> 00:28:11,080
Speaker 1: margin from his you know, victory margin in Iowa last

631
00:28:11,080 --> 00:28:16,120
Speaker 1: time around is a really you know, eyebrow raising result.

632
00:28:16,560 --> 00:28:19,560
Speaker 1: And as you said, you kind of extrapolate out from that, like, Okay,

633
00:28:19,600 --> 00:28:22,280
Speaker 1: then how is he doing in these other states that.

634
00:28:22,200 --> 00:28:23,880
Speaker 4: Are nearby to Iowa.

635
00:28:24,359 --> 00:28:27,359
Speaker 1: But the reason why, again this poll is so taken

636
00:28:27,480 --> 00:28:31,840
Speaker 1: so seriously in terms of Washington opinion is because an

637
00:28:31,880 --> 00:28:34,720
Speaker 1: Cell's or the pollster has such a unique track record

638
00:28:34,760 --> 00:28:37,159
Speaker 1: of being incredibly accurate in the state of Iowa. You

639
00:28:37,160 --> 00:28:40,520
Speaker 1: guys might recall back in the twenty twenty primary, when

640
00:28:40,560 --> 00:28:44,920
Speaker 1: she pulled the Iowa caucuses. It was a bad result

641
00:28:45,000 --> 00:28:48,280
Speaker 1: for Peter Pete Bootage Edge going into the Iowa caucuses,

642
00:28:48,640 --> 00:28:51,960
Speaker 1: and his team, led by Liz Smith, was able to

643
00:28:52,000 --> 00:28:54,600
Speaker 1: basically like pull the whole poll because they were so

644
00:28:54,760 --> 00:28:58,080
Speaker 1: worried about what that poll would indicate for them and

645
00:28:58,120 --> 00:28:59,959
Speaker 1: what sort of narrative could come out of them.

646
00:29:00,200 --> 00:29:02,160
Speaker 4: Because people do take it so seriously.

647
00:29:02,600 --> 00:29:04,840
Speaker 1: So that's why even though this is a poll of

648
00:29:04,840 --> 00:29:07,520
Speaker 1: a state that no one expects Kamalaiyers to win. Why

649
00:29:07,560 --> 00:29:10,200
Speaker 1: it's such a big deal post debate that she's within

650
00:29:10,280 --> 00:29:13,600
Speaker 1: striking distance here only four points of Donald Trump is

651
00:29:13,640 --> 00:29:16,840
Speaker 1: because it has such a track record of being incredibly accurate.

652
00:29:16,960 --> 00:29:18,160
Speaker 4: So really interesting there.

653
00:29:18,360 --> 00:29:20,920
Speaker 1: Yeah, RFK Junior is going to stay on the ballot

654
00:29:20,920 --> 00:29:22,440
Speaker 1: in Iowa. He's going to be on the ballot in

655
00:29:22,440 --> 00:29:24,680
Speaker 1: a number of states because he pulled out so late

656
00:29:24,960 --> 00:29:26,640
Speaker 1: that it was actually too late to get him off

657
00:29:26,680 --> 00:29:29,680
Speaker 1: the ballot in quite a number of places. In North Carolina,

658
00:29:29,760 --> 00:29:31,920
Speaker 1: he was successfully able to get his name off of

659
00:29:31,960 --> 00:29:35,520
Speaker 1: the ballot, but it actually could you know, caused quite

660
00:29:35,520 --> 00:29:37,479
Speaker 1: a lot of problems for that state because they had

661
00:29:37,520 --> 00:29:40,040
Speaker 1: already printed the ballots, they were ready to go out

662
00:29:40,080 --> 00:29:43,080
Speaker 1: and start their mail in balloting process. They're one of

663
00:29:43,120 --> 00:29:45,200
Speaker 1: the earliest states in the country with all of that,

664
00:29:45,640 --> 00:29:48,160
Speaker 1: so I had to delay that by several weeks and

665
00:29:48,280 --> 00:29:50,920
Speaker 1: incur a significant expense in order to get his name

666
00:29:50,960 --> 00:29:54,120
Speaker 1: off the ballot. Other states said no, sorry, too late.

667
00:29:54,240 --> 00:29:56,000
Speaker 1: You're here, you're you know you're going to be on

668
00:29:56,040 --> 00:29:58,560
Speaker 1: the ballot, and Iowa is one of those. So, you know,

669
00:29:58,640 --> 00:30:00,880
Speaker 1: we'll see whether that takes any votes.

670
00:30:00,640 --> 00:30:01,400
Speaker 4: From Trump at the end.

671
00:30:01,440 --> 00:30:03,040
Speaker 1: Of the day in a state like Iowa or others

672
00:30:03,080 --> 00:30:05,000
Speaker 1: where he remains on the ballot, but it is expected

673
00:30:05,040 --> 00:30:06,200
Speaker 1: that he will be there in November.

674
00:30:06,240 --> 00:30:07,840
Speaker 3: So Iowa, that was a big one.

675
00:30:07,920 --> 00:30:09,800
Speaker 2: Let's go to the next one because this is actually

676
00:30:09,960 --> 00:30:13,000
Speaker 2: useful just to look at a lot of the post

677
00:30:13,040 --> 00:30:16,600
Speaker 2: debate polling landscape. And so we have here quote seven

678
00:30:16,760 --> 00:30:20,120
Speaker 2: A and B rated polls post debate, so ABC News

679
00:30:20,160 --> 00:30:23,120
Speaker 2: and IPSOS, this had Harris up by plus six. That

680
00:30:23,200 --> 00:30:25,840
Speaker 2: was actually very significant because that was Harris plus six

681
00:30:25,880 --> 00:30:29,479
Speaker 2: amongst likely voters. Reuter's IPSOS, so they had Harris up

682
00:30:29,480 --> 00:30:32,640
Speaker 2: by five. Yahoo News, You Gov, they had Harris up

683
00:30:32,640 --> 00:30:35,800
Speaker 2: by four. You had others Harrop four times. You gove

684
00:30:35,840 --> 00:30:38,800
Speaker 2: Harris four. Data for progress Harris four. And it was

685
00:30:38,840 --> 00:30:41,400
Speaker 2: Atlas Intel. That's the one that Nate referenced a little

686
00:30:41,400 --> 00:30:43,440
Speaker 2: bit earlier that showed Trump up by three.

687
00:30:43,520 --> 00:30:46,200
Speaker 3: So this was in the national election.

688
00:30:46,680 --> 00:30:50,040
Speaker 2: Obviously, this is a little bit over the map when

689
00:30:50,080 --> 00:30:53,920
Speaker 2: you include the Atlas one, but outliers certainly are ones

690
00:30:54,200 --> 00:30:56,959
Speaker 2: that exist, and so it's actually better that they publish

691
00:30:57,000 --> 00:30:59,120
Speaker 2: it so we can just consider and look at all

692
00:30:59,160 --> 00:31:02,720
Speaker 2: of that things are possible. Atlasontel's correct everybody else is wrong,

693
00:31:02,840 --> 00:31:04,960
Speaker 2: or if you just kind of look at the overall

694
00:31:05,000 --> 00:31:07,320
Speaker 2: average of this, you would say there's a relative Harris

695
00:31:07,360 --> 00:31:07,960
Speaker 2: bump here.

696
00:31:08,240 --> 00:31:10,160
Speaker 3: And now, remember she does need to win.

697
00:31:10,120 --> 00:31:13,160
Speaker 2: The popular vote by two to three points in order

698
00:31:13,200 --> 00:31:15,880
Speaker 2: to maintain an electoral college victory, so you shouldn't be

699
00:31:15,960 --> 00:31:18,400
Speaker 2: celebrating too much. You should also remember that Joe Biden

700
00:31:18,480 --> 00:31:21,640
Speaker 2: was beating Trump by even larger margins in twenty twenty

701
00:31:21,680 --> 00:31:24,840
Speaker 2: and twenty sixteen. So I guess, really what I would

702
00:31:24,840 --> 00:31:27,120
Speaker 2: say is, I think that Nate's analysis of we're back

703
00:31:27,160 --> 00:31:30,800
Speaker 2: to toss up just seems the probably best way to

704
00:31:30,840 --> 00:31:34,400
Speaker 2: look at the analysis. In general, there's been too much

705
00:31:34,440 --> 00:31:37,480
Speaker 2: public polling now and a lot of ways that people

706
00:31:37,480 --> 00:31:40,080
Speaker 2: have reacted since that show that Donald Trump did not

707
00:31:40,200 --> 00:31:42,560
Speaker 2: do well enough in the debate to consider even doing

708
00:31:42,640 --> 00:31:44,480
Speaker 2: it again. In general, I think I was a major

709
00:31:44,520 --> 00:31:47,320
Speaker 2: missed opportunity, as I said, because why would you take

710
00:31:47,640 --> 00:31:50,840
Speaker 2: somebody who doesn't do well in scripted interviews or it's

711
00:31:50,880 --> 00:31:54,400
Speaker 2: scripted situations and just give her, you know less, or

712
00:31:54,440 --> 00:31:56,240
Speaker 2: and just give her the least amount of time the

713
00:31:56,280 --> 00:31:58,040
Speaker 2: best possible performance for her to be able to run

714
00:31:58,080 --> 00:32:00,680
Speaker 2: on when she can continue challenging saying, hey, I want

715
00:32:00,720 --> 00:32:03,840
Speaker 2: to do another debate. She's not I think forcing it

716
00:32:03,880 --> 00:32:06,560
Speaker 2: too hard. She's probably pretty happy to be where she is.

717
00:32:06,600 --> 00:32:08,400
Speaker 2: But for Trump to be the first one to come

718
00:32:08,400 --> 00:32:10,760
Speaker 2: out and just be like, there will be no third debate,

719
00:32:11,040 --> 00:32:13,520
Speaker 2: I still think it remains a problem for him. And

720
00:32:13,760 --> 00:32:17,160
Speaker 2: because sixty seven million people watched it on television, probably

721
00:32:17,240 --> 00:32:21,440
Speaker 2: eighty to ninety million consumed the content overall, that's half

722
00:32:21,560 --> 00:32:25,040
Speaker 2: of all registered voters in this country. And you know, look,

723
00:32:25,120 --> 00:32:27,560
Speaker 2: maybe I'm wrong, maybe we're just so polarized people don't

724
00:32:27,640 --> 00:32:29,040
Speaker 2: vote on that stuff anymore.

725
00:32:29,120 --> 00:32:30,560
Speaker 3: But there's not a lot of evidence of that.

726
00:32:30,640 --> 00:32:35,560
Speaker 2: Considering the twenty twenty two Roe versus Wade voting, where

727
00:32:35,600 --> 00:32:38,560
Speaker 2: you had a lot of people who previously voted Republican

728
00:32:38,680 --> 00:32:41,440
Speaker 2: who ended up voting Democrat or who had not previously

729
00:32:41,480 --> 00:32:44,720
Speaker 2: voted same would stop the steal. There's been tons of

730
00:32:45,160 --> 00:32:50,400
Speaker 2: major margins that do not fall within the in polarization metrics.

731
00:32:50,440 --> 00:32:53,600
Speaker 2: So for example, Josh Shapiro beating Doug Mastrano by such

732
00:32:53,600 --> 00:32:57,200
Speaker 2: big numbers, Yeah, John Fetterman winning by a decent margin there,

733
00:32:57,640 --> 00:33:00,560
Speaker 2: Carrie Lake getting destroyed right now in a lot of

734
00:33:00,600 --> 00:33:02,920
Speaker 2: the polling that we see in Arizona. So you just

735
00:33:02,960 --> 00:33:05,640
Speaker 2: can't tell me that there aren't at least some swing

736
00:33:05,720 --> 00:33:06,880
Speaker 2: voters that are up for graphs.

737
00:33:06,920 --> 00:33:09,040
Speaker 1: Yeah, I mean, even if it's just marginal, we're talking

738
00:33:09,080 --> 00:33:11,080
Speaker 1: about a race, it's going to be one on the margins. Yes,

739
00:33:11,200 --> 00:33:13,800
Speaker 1: So no, I think it's a major strategic error for

740
00:33:13,880 --> 00:33:16,640
Speaker 1: Trump to be like no, absolutely not no more debates,

741
00:33:16,640 --> 00:33:18,960
Speaker 1: which is why I still hold open a possibility he

742
00:33:19,080 --> 00:33:22,040
Speaker 1: may yet change his mind, especially if the polling becomes,

743
00:33:22,160 --> 00:33:24,760
Speaker 1: you know, more consistently in the direction of Kamala Harris

744
00:33:24,760 --> 00:33:27,200
Speaker 1: plus four or five six. And you know what was

745
00:33:27,240 --> 00:33:29,800
Speaker 1: noteworthy about the in fact, can we put back up

746
00:33:29,840 --> 00:33:32,200
Speaker 1: the graphic we just had a three up on the

747
00:33:32,240 --> 00:33:35,840
Speaker 1: screen because it has not just the actual poll results,

748
00:33:35,840 --> 00:33:38,320
Speaker 1: but then you can see them plotted on a chart.

749
00:33:38,400 --> 00:33:40,000
Speaker 1: I thought this was kind of useful. You can see

750
00:33:40,040 --> 00:33:42,960
Speaker 1: where the debate is, and then all of the polls

751
00:33:43,000 --> 00:33:46,560
Speaker 1: post debate, save for the one, which again we shouldn't discarred.

752
00:33:46,600 --> 00:33:48,600
Speaker 1: It's important to keep track of that one, but all

753
00:33:48,640 --> 00:33:51,120
Speaker 1: of the other ones are really clustered in a similar place.

754
00:33:51,360 --> 00:33:52,600
Speaker 4: Whereas prior to the debate.

755
00:33:53,280 --> 00:33:55,680
Speaker 1: First of all, the overall sort of like average of

756
00:33:55,720 --> 00:33:58,720
Speaker 1: the polls was lower, and also they were scattered over

757
00:33:58,840 --> 00:34:01,240
Speaker 1: a wider plot, So I thought that was interesting to

758
00:34:01,240 --> 00:34:03,640
Speaker 1: see the post debate result there. The other question with

759
00:34:03,720 --> 00:34:06,400
Speaker 1: debates is, you know, it's not uncommon that there's a

760
00:34:06,440 --> 00:34:08,840
Speaker 1: bump coming out of a debate. It's also not uncommon

761
00:34:08,840 --> 00:34:11,839
Speaker 1: that that bump goes away. Two more points to make

762
00:34:11,840 --> 00:34:13,760
Speaker 1: before we get to some of the other polling. Number

763
00:34:13,800 --> 00:34:17,960
Speaker 1: one of all the various like electoral prediction models that

764
00:34:18,040 --> 00:34:24,160
Speaker 1: exist now, Nate Silver's is the most pessimistic for Kamala Harris.

765
00:34:24,200 --> 00:34:27,799
Speaker 1: The other ones all project her to you know, have again,

766
00:34:27,840 --> 00:34:29,560
Speaker 1: it's like a in the toss up range, but like

767
00:34:29,560 --> 00:34:32,040
Speaker 1: a fifty six or sixty percent chance of winning the

768
00:34:32,040 --> 00:34:34,279
Speaker 1: electoral college. Need is a little bit of an outlier

769
00:34:34,440 --> 00:34:36,600
Speaker 1: in terms of being pessimistic. Now, he's also the person

770
00:34:36,640 --> 00:34:40,160
Speaker 1: who sort of like invented this whole genre, so you know,

771
00:34:40,239 --> 00:34:43,040
Speaker 1: I think it's worth taking seriously what his model is saying.

772
00:34:43,080 --> 00:34:45,320
Speaker 1: And he was closer to being accurate a twenty sixteen

773
00:34:45,400 --> 00:34:47,800
Speaker 1: than a lot of other individuals too. But just wanted

774
00:34:47,800 --> 00:34:50,400
Speaker 1: to point that out. And then another thing that stuck

775
00:34:50,400 --> 00:34:52,759
Speaker 1: with me that I saw someone point out online is,

776
00:34:53,200 --> 00:34:57,359
Speaker 1: on the one hand, I think there's an appropriate skepticism

777
00:34:57,480 --> 00:35:01,400
Speaker 1: of the polls of a potential miss honestly in either direction.

778
00:35:02,239 --> 00:35:05,319
Speaker 1: One thing that is different, though, because sometimes I get

779
00:35:05,360 --> 00:35:07,759
Speaker 1: start getting these like twenty sixteen vibes, which I think

780
00:35:07,800 --> 00:35:11,319
Speaker 1: probably everybody has had it at different moments. But one

781
00:35:11,360 --> 00:35:14,440
Speaker 1: thing that's genuinely different between Kamala Harris's profile and Hillary

782
00:35:14,440 --> 00:35:17,759
Speaker 1: Clinton's profile is even though Hillary was up more in

783
00:35:17,840 --> 00:35:21,680
Speaker 1: the polls at this point, she always had a very

784
00:35:21,760 --> 00:35:25,480
Speaker 1: negative favorability rating. She was like underwater by like sixteen

785
00:35:25,520 --> 00:35:29,799
Speaker 1: points on the favorability rating. Kamala is like even And

786
00:35:29,880 --> 00:35:33,279
Speaker 1: to me, that makes the scenario very different. You know,

787
00:35:33,360 --> 00:35:36,440
Speaker 1: that was always sort of looming over the potential Hillary

788
00:35:36,480 --> 00:35:39,719
Speaker 1: Clinton results is basically like, yeah, the poles says she's up,

789
00:35:39,760 --> 00:35:42,120
Speaker 1: but man, people really don't like this lady. And that

790
00:35:42,239 --> 00:35:44,520
Speaker 1: is not the same dynamic here with Kamala Harris, which

791
00:35:44,520 --> 00:35:46,360
Speaker 1: I think could end up being significant.

792
00:35:45,880 --> 00:35:47,359
Speaker 3: Certainly possible. You know.

793
00:35:47,680 --> 00:35:50,439
Speaker 2: It's just there's so many confounding variables that I really

794
00:35:50,480 --> 00:35:52,080
Speaker 2: just think it's better to just like present all the

795
00:35:52,120 --> 00:35:53,920
Speaker 2: info and be like, you can make up what you

796
00:35:54,000 --> 00:35:56,319
Speaker 2: want from it. I guess I could see it in

797
00:35:56,400 --> 00:35:59,799
Speaker 2: all different ones I could actually see a major democratic miss.

798
00:36:00,080 --> 00:36:02,600
Speaker 2: It's unable to capture the same way that happened in

799
00:36:02,640 --> 00:36:03,279
Speaker 2: twenty twenty two.

800
00:36:03,320 --> 00:36:05,400
Speaker 3: That's the most recent polling myst that we have.

801
00:36:05,719 --> 00:36:08,759
Speaker 2: They or we're off by five or so points. A

802
00:36:08,800 --> 00:36:11,840
Speaker 2: lot of that was Roe versus Way. There's been so

803
00:36:11,960 --> 00:36:14,880
Speaker 2: much dynamic change in the electorate in just the last

804
00:36:15,040 --> 00:36:17,320
Speaker 2: ninety days, you know, last one hundred days or whatever.

805
00:36:17,640 --> 00:36:20,239
Speaker 2: For Kamala, that's a pretty And that's the other thing,

806
00:36:20,280 --> 00:36:23,160
Speaker 2: is that a problem for polling. Almost would forgive them.

807
00:36:23,239 --> 00:36:26,160
Speaker 2: It's such a crazy scenario. It's difficult to poll only

808
00:36:26,440 --> 00:36:28,839
Speaker 2: for one hundred days and try to get to peg

809
00:36:28,960 --> 00:36:32,120
Speaker 2: like who exactly is voting or not and not be

810
00:36:32,160 --> 00:36:34,160
Speaker 2: able to capture that. I could do it the other way,

811
00:36:34,200 --> 00:36:36,600
Speaker 2: which is that look is very possible that Trump's strength

812
00:36:36,719 --> 00:36:39,520
Speaker 2: is understated. With all of this, you've got the whole

813
00:36:39,719 --> 00:36:43,000
Speaker 2: likely voter problem of you've got people who are traditional

814
00:36:43,080 --> 00:36:44,680
Speaker 2: Democrats who like answering polls.

815
00:36:44,680 --> 00:36:46,720
Speaker 3: This is a big twenty twenty thesis.

816
00:36:46,719 --> 00:36:48,960
Speaker 2: So that we could have replicated that, maybe we're been

817
00:36:49,040 --> 00:36:52,040
Speaker 2: unable to solve. There's some other interesting stuff that points

818
00:36:52,400 --> 00:36:54,399
Speaker 2: more in the Harris direction. Let's put this up there

819
00:36:54,440 --> 00:36:57,520
Speaker 2: for example, it is just from the Financial Times. This

820
00:36:57,640 --> 00:37:01,000
Speaker 2: is significant just because it does show some divergence on

821
00:37:01,040 --> 00:37:04,400
Speaker 2: the economy. FT finds that Kamala quote better represents the

822
00:37:04,440 --> 00:37:06,920
Speaker 2: interests of middle class. It says forty nine to thirty

823
00:37:06,920 --> 00:37:09,080
Speaker 2: six for Kamala Harris small business.

824
00:37:09,320 --> 00:37:10,000
Speaker 3: See that's the.

825
00:37:09,920 --> 00:37:12,640
Speaker 2: One where I'm just like, really, is that really true?

826
00:37:12,800 --> 00:37:13,840
Speaker 2: Forty eight to thirty.

827
00:37:13,600 --> 00:37:15,719
Speaker 1: Seven passion business, She said it.

828
00:37:15,840 --> 00:37:18,400
Speaker 2: Yeah, But you know, small business owners are the most

829
00:37:18,600 --> 00:37:20,240
Speaker 2: conservative people by Democrats.

830
00:37:20,239 --> 00:37:22,520
Speaker 1: But you have to keep you have to keep in mind, though,

831
00:37:22,840 --> 00:37:25,760
Speaker 1: this is a poll of everyone, right, So you're asking

832
00:37:25,880 --> 00:37:28,120
Speaker 1: everyone who do you think will be better for small business?

833
00:37:28,200 --> 00:37:30,680
Speaker 1: I think if you just ask small business owners you

834
00:37:30,719 --> 00:37:32,759
Speaker 1: would maybe get a different result, because you're right, they

835
00:37:32,800 --> 00:37:35,120
Speaker 1: do tend to be conservative. But this is like you're

836
00:37:35,160 --> 00:37:37,960
Speaker 1: asking the entire electorate who do you think will be

837
00:37:37,960 --> 00:37:38,880
Speaker 1: better for these groups?

838
00:37:39,160 --> 00:37:42,279
Speaker 2: So, yeah, okay, so small business was for is it

839
00:37:42,360 --> 00:37:45,080
Speaker 2: forty eight to thirty seven? Union members says forty five

840
00:37:45,120 --> 00:37:48,080
Speaker 2: to thirty five. Blue collar forty three to two thirty six.

841
00:37:48,160 --> 00:37:50,719
Speaker 2: I will say that on Trump, you know, I don't

842
00:37:50,719 --> 00:37:53,000
Speaker 2: necessarily want to be where he is. They have him

843
00:37:53,080 --> 00:37:56,839
Speaker 2: at sixty four to twenty for large corporations on who

844
00:37:56,880 --> 00:37:59,320
Speaker 2: they think you would be better for, and sixty seven

845
00:37:59,400 --> 00:38:03,200
Speaker 2: to nineteen on wealthy people. So that was the individual

846
00:38:03,239 --> 00:38:06,840
Speaker 2: ones the overall economy, and I think that's kind of interesting.

847
00:38:07,080 --> 00:38:10,200
Speaker 2: The respondents also of those who were more likely to

848
00:38:10,239 --> 00:38:14,279
Speaker 2: trust Harris than Trump on the economy, actually watched the

849
00:38:14,440 --> 00:38:16,920
Speaker 2: entire debate, so that was fascinating.

850
00:38:17,040 --> 00:38:18,160
Speaker 3: I would say, overall.

851
00:38:17,960 --> 00:38:20,399
Speaker 2: Is very, very favorable for her, So you know, take

852
00:38:20,440 --> 00:38:22,839
Speaker 2: it for however you want. I'd never seen her beat

853
00:38:22,960 --> 00:38:25,720
Speaker 2: him on the economy. You know this badly before. Yeah,

854
00:38:25,760 --> 00:38:28,600
Speaker 2: I would more put it as an outlier, but again

855
00:38:28,800 --> 00:38:31,040
Speaker 2: it could be one that you could look to and say,

856
00:38:31,320 --> 00:38:34,439
Speaker 2: if Trump does lose the election on the margins by

857
00:38:34,440 --> 00:38:36,640
Speaker 2: a couple of points, and it's in these swing states,

858
00:38:36,640 --> 00:38:39,399
Speaker 2: it very much could be because of issues like this,

859
00:38:39,520 --> 00:38:42,960
Speaker 2: where if you feel the thing is Trump, the Republicans

860
00:38:43,480 --> 00:38:47,760
Speaker 2: lost twenty twenty two even though they had a huge

861
00:38:47,800 --> 00:38:50,600
Speaker 2: margin on the economy. So that shows you that Roe

862
00:38:50,640 --> 00:38:53,040
Speaker 2: and stop steal can actually overcome even when you're winning

863
00:38:53,040 --> 00:38:53,960
Speaker 2: on the overall economy.

864
00:38:54,040 --> 00:38:54,200
Speaker 3: Yeah.

865
00:38:54,239 --> 00:38:56,359
Speaker 2: Well, if you're just tied on the economy, that's bad enough.

866
00:38:56,600 --> 00:38:58,640
Speaker 2: If you're tied here and you get this big row

867
00:38:58,960 --> 00:39:00,920
Speaker 2: benefit there. I could see that being a big problem

868
00:39:00,920 --> 00:39:02,600
Speaker 2: for them. So again I have no idea what's going

869
00:39:02,600 --> 00:39:04,399
Speaker 2: to happen. I still think Trump could very easily win,

870
00:39:05,000 --> 00:39:07,319
Speaker 2: but I would say there's certainly danger signs for him.

871
00:39:07,360 --> 00:39:09,320
Speaker 2: And in such a close race, you should just always

872
00:39:09,320 --> 00:39:11,160
Speaker 2: be doing your best in order to try and you know,

873
00:39:11,640 --> 00:39:12,920
Speaker 2: go across the finish line.

874
00:39:13,160 --> 00:39:15,680
Speaker 3: You were not the underdog, you know, throughout this entire thing.

875
00:39:15,960 --> 00:39:18,200
Speaker 2: Now you're kind of putting yourself in a category where look,

876
00:39:18,200 --> 00:39:19,680
Speaker 2: a month from now, we could say, hey, this is

877
00:39:19,680 --> 00:39:21,040
Speaker 2: the things are not looking at gred for you.

878
00:39:21,239 --> 00:39:23,440
Speaker 1: Yeah, yeah, I think if she can even get in

879
00:39:23,440 --> 00:39:25,719
Speaker 1: the ballpark with him on the economy, it's yeah, that's

880
00:39:25,760 --> 00:39:27,759
Speaker 1: what I mean, pretty devastating for him. And you know,

881
00:39:27,840 --> 00:39:32,279
Speaker 1: Republicans historically have typically that there's an instinct among the

882
00:39:32,320 --> 00:39:34,640
Speaker 1: American public to just assume Republicans are going to be

883
00:39:34,640 --> 00:39:36,960
Speaker 1: better on the economy. And then Donald Trump that was

884
00:39:37,160 --> 00:39:40,719
Speaker 1: always his core strength because you know, he's the businessman,

885
00:39:40,800 --> 00:39:43,840
Speaker 1: et cetera, et cetera. And you always point out sagerback

886
00:39:43,880 --> 00:39:45,640
Speaker 1: in twenty twenty and when we're looking at the polls

887
00:39:45,680 --> 00:39:47,879
Speaker 1: and saying to the Trump people like you guys are told,

888
00:39:48,000 --> 00:39:50,600
Speaker 1: are toast, you don't have a chance. That was the

889
00:39:50,680 --> 00:39:52,640
Speaker 1: number they would always point to. Yes, but he has

890
00:39:52,680 --> 00:39:55,959
Speaker 1: this significant edge on the economy, and look, it wasn't enough.

891
00:39:56,239 --> 00:39:57,719
Speaker 4: He's still lost, but.

892
00:39:58,520 --> 00:40:01,680
Speaker 1: That was indicative of there is more strength for him

893
00:40:01,680 --> 00:40:04,600
Speaker 1: here than we thought. So when I see these numbers

894
00:40:04,640 --> 00:40:06,759
Speaker 1: and yeah, could be an outlier. We shall also point

895
00:40:06,760 --> 00:40:10,800
Speaker 1: out financial times we cover before they have been asking

896
00:40:10,840 --> 00:40:13,600
Speaker 1: you know, who's better on the economy, and their previous

897
00:40:13,640 --> 00:40:16,560
Speaker 1: poll had Harris basically tied with Trump. This pole has

898
00:40:16,640 --> 00:40:19,000
Speaker 1: her up by a little bit. So they've been seeing

899
00:40:19,040 --> 00:40:21,520
Speaker 1: this trend for Kamala Harris as not consistent with some

900
00:40:21,560 --> 00:40:23,560
Speaker 1: of the other poles that we've seen, where he continues

901
00:40:23,600 --> 00:40:26,279
Speaker 1: to have a clear edge over her on the economy.

902
00:40:26,520 --> 00:40:28,640
Speaker 1: But like I said, if she can even narrow that

903
00:40:28,680 --> 00:40:32,680
Speaker 1: gap and get within striking distance, that's more devastating for him,

904
00:40:32,719 --> 00:40:35,440
Speaker 1: honestly than almost any of the other polling data that

905
00:40:35,440 --> 00:40:40,520
Speaker 1: I've seen, because that's their bet. And she was able

906
00:40:40,840 --> 00:40:44,560
Speaker 1: in that debate because she moved the conversation where she

907
00:40:44,760 --> 00:40:48,600
Speaker 1: wanted it to go. He got so distracted and enraged,

908
00:40:48,640 --> 00:40:51,960
Speaker 1: et cetera, that he wasn't able to consistently land his

909
00:40:52,120 --> 00:40:55,000
Speaker 1: points that him and his campaign have wanted him to

910
00:40:55,080 --> 00:41:01,920
Speaker 1: be making on the economy. If he decides he's genuinely

911
00:41:01,920 --> 00:41:05,239
Speaker 1: not going to do another debate, he's outside of paid communications,

912
00:41:05,320 --> 00:41:08,640
Speaker 1: not going to have a lot of opportunities to continue

913
00:41:08,640 --> 00:41:11,560
Speaker 1: to land those points and to the point about them,

914
00:41:11,760 --> 00:41:14,360
Speaker 1: you know, not really hitting hard on the economy and

915
00:41:14,440 --> 00:41:17,000
Speaker 1: getting distracted in ways that the Hairs campaign wanted them

916
00:41:17,040 --> 00:41:19,960
Speaker 1: to get distracted with. Harry Anton was pointing out over

917
00:41:20,040 --> 00:41:23,600
Speaker 1: on CNN, Actually the biggest search terms being associated with

918
00:41:23,640 --> 00:41:26,480
Speaker 1: Donald Trump's name now have to do with the eating

919
00:41:26,920 --> 00:41:29,440
Speaker 1: their eating their dogs, eating the cats, eating the pets

920
00:41:29,800 --> 00:41:32,760
Speaker 1: Haitian situation, which we're about to talk about with za Jalani.

921
00:41:32,880 --> 00:41:35,200
Speaker 1: But let's take a listen to Entin's analysis there.

922
00:41:35,520 --> 00:41:38,640
Speaker 9: Yeah, what are the rising things that people are googling

923
00:41:38,680 --> 00:41:41,920
Speaker 9: along with Donald Trump's name. It's not what Donald Trump's

924
00:41:41,920 --> 00:41:47,240
Speaker 9: campaign would necessarily want, right, It's eating pets, it's eating dogs,

925
00:41:47,480 --> 00:41:51,680
Speaker 9: it's eating cats. Obviously that was Donald Trump's moment on

926
00:41:51,719 --> 00:41:54,279
Speaker 9: the debate stage. Of course, that's a fagazy story, it's

927
00:41:54,320 --> 00:41:56,400
Speaker 9: not real, it's fake, yet he went after it.

928
00:41:56,600 --> 00:41:57,560
Speaker 10: This is a disaster.

929
00:41:57,840 --> 00:42:00,279
Speaker 9: Who the heck if you're running a presidential camp that

930
00:42:00,320 --> 00:42:03,400
Speaker 9: you'd want your name being Google with eating pets, eating dogs,

931
00:42:03,440 --> 00:42:04,360
Speaker 9: eating cats like that.

932
00:42:04,440 --> 00:42:05,120
Speaker 10: That's gracious.

933
00:42:05,680 --> 00:42:08,960
Speaker 4: Well, I mean maybe he thinks it's a win, so

934
00:42:09,480 --> 00:42:11,799
Speaker 4: they do think it's a win. The Trump at least

935
00:42:12,239 --> 00:42:12,880
Speaker 4: thinks it's a win.

936
00:42:13,040 --> 00:42:15,319
Speaker 3: He thinks it's a win, so does JD. I'll say it.

937
00:42:15,320 --> 00:42:18,920
Speaker 1: All, No, say someone out because we'll get ze in

938
00:42:18,960 --> 00:42:20,640
Speaker 1: the next one. So go ahead and just give us

939
00:42:20,640 --> 00:42:22,480
Speaker 1: your top line thoughts on this.

940
00:42:22,719 --> 00:42:25,200
Speaker 2: I think that they are making the same mistake that

941
00:42:25,200 --> 00:42:27,600
Speaker 2: they all made during Stop the Steal, which is they

942
00:42:27,640 --> 00:42:34,200
Speaker 2: believe that anything that directionally points or causes argument around

943
00:42:34,239 --> 00:42:36,279
Speaker 2: the issue that they think they are going to win on,

944
00:42:36,400 --> 00:42:40,799
Speaker 2: like immigration. They believe that anything anything is justified in

945
00:42:40,880 --> 00:42:44,239
Speaker 2: talking about in backing up and not for surrendering on

946
00:42:44,600 --> 00:42:47,399
Speaker 2: in order to focus the conversation. Now, as I had

947
00:42:47,480 --> 00:42:50,560
Speaker 2: said to them at that time, I think they're fundamentally incorrect,

948
00:42:50,680 --> 00:42:53,239
Speaker 2: because I think a lying to people is I'm gonna

949
00:42:53,239 --> 00:42:55,400
Speaker 2: put morals out of it. Lining to people are saying

950
00:42:55,440 --> 00:42:58,840
Speaker 2: things that are incorrect, give you too much to be

951
00:42:59,120 --> 00:43:02,560
Speaker 2: discredited on when people say, then I don't believe anything

952
00:43:02,600 --> 00:43:05,480
Speaker 2: that you say, So for example, stop the steal. Everyone

953
00:43:05,560 --> 00:43:09,560
Speaker 2: was like, look, it's not about Bamboos and Mike Lindell

954
00:43:09,719 --> 00:43:11,600
Speaker 2: and all of us. I'm like, well, Trump thinks it is.

955
00:43:11,640 --> 00:43:14,520
Speaker 2: But they're like, it's about mail in balloting laws in

956
00:43:14,560 --> 00:43:15,839
Speaker 2: the state of Pennsylvania.

957
00:43:15,880 --> 00:43:18,120
Speaker 3: I go, hey, bro, but that's not what people are

958
00:43:18,120 --> 00:43:18,680
Speaker 3: talking about.

959
00:43:18,880 --> 00:43:20,800
Speaker 2: You guys are saying that the allegtions should not be

960
00:43:20,840 --> 00:43:23,759
Speaker 2: certified because the Pennsylvania Supreme Court made a ruling on

961
00:43:23,840 --> 00:43:26,520
Speaker 2: mail in ballots. That's not the same thing that you're

962
00:43:26,520 --> 00:43:28,879
Speaker 2: talking about. So you want to talk about Haitians, Let's

963
00:43:28,920 --> 00:43:31,840
Speaker 2: talk about it all day long, about TPS, the legitimacy

964
00:43:31,840 --> 00:43:34,719
Speaker 2: of migrant law, asylum, etc. I think that's a winning

965
00:43:34,760 --> 00:43:37,960
Speaker 2: issue for Republicans, and polls show that. But when you

966
00:43:37,960 --> 00:43:41,560
Speaker 2: start claiming people are eating pets and dogs, and then

967
00:43:41,640 --> 00:43:44,600
Speaker 2: when you get discredited on that, and then even worse,

968
00:43:44,920 --> 00:43:48,239
Speaker 2: you start to take anecdotal evidence as fact in and

969
00:43:48,320 --> 00:43:52,000
Speaker 2: of itself. The current defense is my constituents say, listen,

970
00:43:52,120 --> 00:43:54,480
Speaker 2: I'm going to give you news. Most people who are

971
00:43:54,480 --> 00:43:58,080
Speaker 2: interested in politics are stupid and weird. Like, if you

972
00:43:58,120 --> 00:44:00,320
Speaker 2: are at the local level, and by the way, include

973
00:44:00,360 --> 00:44:02,479
Speaker 2: myself in that. So if you were at the local level,

974
00:44:02,480 --> 00:44:05,520
Speaker 2: and you're calling your congressman. I've manned enough of these phones.

975
00:44:05,719 --> 00:44:07,080
Speaker 2: If you have the time out of the middle of

976
00:44:07,120 --> 00:44:09,520
Speaker 2: your day to call your congressman and complain, you're freaking

977
00:44:09,560 --> 00:44:13,680
Speaker 2: weirdo ninety eight percent of the time. So that we're

978
00:44:13,680 --> 00:44:15,839
Speaker 2: just going to take these people's word. I mean, how

979
00:44:15,880 --> 00:44:19,640
Speaker 2: many times do we see these bullshit election affidavits.

980
00:44:19,080 --> 00:44:20,839
Speaker 3: That were completely fake fake?

981
00:44:21,080 --> 00:44:22,960
Speaker 2: You don't stop the seal, Oh I saw this, blah

982
00:44:23,000 --> 00:44:25,520
Speaker 2: blah blah, fake, did an investigation? Fake, oh saw this.

983
00:44:25,640 --> 00:44:27,960
Speaker 2: Judge literally looks at it, laughs and throws out of

984
00:44:28,040 --> 00:44:30,200
Speaker 2: the courtroom. They see that as evidence of the conspiracy,

985
00:44:30,400 --> 00:44:33,360
Speaker 2: which is part of the issue. So I mean, in general,

986
00:44:33,520 --> 00:44:35,880
Speaker 2: they have this idea of directional truth.

987
00:44:36,040 --> 00:44:40,000
Speaker 3: Now look, in their defense, it's for real though sent

988
00:44:40,040 --> 00:44:41,600
Speaker 3: dystopian con it is.

989
00:44:41,640 --> 00:44:44,360
Speaker 2: But I'll give their defense on this is that Trump

990
00:44:44,600 --> 00:44:47,040
Speaker 2: tells small lies to tell bigger truths, like he tells

991
00:44:47,040 --> 00:44:49,680
Speaker 2: small eyes about Haitians to get us talking about X,

992
00:44:49,760 --> 00:44:50,080
Speaker 2: Y and Z.

993
00:44:50,680 --> 00:44:52,480
Speaker 3: And you know, I have to take myself out of it.

994
00:44:52,520 --> 00:44:55,360
Speaker 2: In twenty sixteen, if someone shit like this was happening

995
00:44:55,360 --> 00:44:59,480
Speaker 2: when he did the Cauzier Khan, the Access Hollywood the

996
00:44:59,600 --> 00:45:01,600
Speaker 2: jud you know, all this stuff. I was like, there's

997
00:45:01,640 --> 00:45:03,279
Speaker 2: no way this guy could win, and he's still won.

998
00:45:03,560 --> 00:45:06,160
Speaker 2: So maybe they are right and maybe their theory is correct.

999
00:45:06,360 --> 00:45:08,840
Speaker 2: I don't think there's enough recent evidence to show that

1000
00:45:08,880 --> 00:45:09,200
Speaker 2: it's right.

1001
00:45:09,280 --> 00:45:10,320
Speaker 3: Yeah, I think you look stupid.

1002
00:45:10,640 --> 00:45:13,600
Speaker 2: I actually think that what it does is it validates

1003
00:45:13,840 --> 00:45:18,560
Speaker 2: this idea of well anything, It validates like Russia Gate. Oh,

1004
00:45:18,600 --> 00:45:23,920
Speaker 2: because we have Oleg Deripaska and an adossier that Christopher

1005
00:45:23,920 --> 00:45:25,640
Speaker 2: Steele put together that says you.

1006
00:45:25,560 --> 00:45:26,319
Speaker 3: Know, X, Y and Z.

1007
00:45:26,719 --> 00:45:29,480
Speaker 2: We spent two years as a country litigating that. And

1008
00:45:29,520 --> 00:45:33,560
Speaker 2: Democrats rightfully where I think we're eviscerated for believing that,

1009
00:45:33,640 --> 00:45:35,759
Speaker 2: you know, Donald Trump peede on somebody and there was

1010
00:45:36,160 --> 00:45:38,600
Speaker 2: a video of it. That's the same you know thing

1011
00:45:38,640 --> 00:45:40,440
Speaker 2: that you're you're doing here. We're like, oh, well, I

1012
00:45:40,480 --> 00:45:42,759
Speaker 2: heard from a neighbor's daughter's friend on Facebook.

1013
00:45:42,880 --> 00:45:44,840
Speaker 1: By the way, the Facebook lady is like, yeah, just

1014
00:45:45,120 --> 00:45:47,880
Speaker 1: she regrets putting it up there. She's like, and she

1015
00:45:48,000 --> 00:45:50,720
Speaker 1: heard it from like somebody, and somebody was like third

1016
00:45:50,719 --> 00:45:52,759
Speaker 1: hand potential possibility.

1017
00:45:52,840 --> 00:45:54,400
Speaker 3: My top line is just listen.

1018
00:45:54,520 --> 00:45:56,359
Speaker 2: You know, I think people are smart, and I think

1019
00:45:56,360 --> 00:45:58,520
Speaker 2: they're actually a lot smarter than you give them credit for.

1020
00:45:58,600 --> 00:46:02,120
Speaker 2: And I think when you are telling lies and they

1021
00:46:02,160 --> 00:46:05,759
Speaker 2: see through that, they both don't trust you. And you know,

1022
00:46:05,800 --> 00:46:08,960
Speaker 2: this whole jiu jitsu, there's this high IQ jiu jitsu

1023
00:46:09,120 --> 00:46:09,920
Speaker 2: right that goes on.

1024
00:46:10,200 --> 00:46:12,560
Speaker 3: I called it high IQ. Stop the steal at the time.

1025
00:46:12,600 --> 00:46:14,840
Speaker 3: I don't think it works. I just don't.

1026
00:46:14,880 --> 00:46:17,560
Speaker 2: I think that poll after poll after polls is the

1027
00:46:17,680 --> 00:46:20,840
Speaker 2: chaos and all this stuff around Trump is actually what

1028
00:46:21,000 --> 00:46:23,680
Speaker 2: people feel exhausted by. That's part of the reason he

1029
00:46:23,760 --> 00:46:26,040
Speaker 2: lost to twenty twenty election. Stop the Steal was a

1030
00:46:26,120 --> 00:46:29,200
Speaker 2: huge hindrance to them in twenty twenty two. I see

1031
00:46:29,200 --> 00:46:31,799
Speaker 2: no evidence that it will work this time. Listen, they're

1032
00:46:31,840 --> 00:46:34,080
Speaker 2: the ones running, so maybe they are right, and if

1033
00:46:34,120 --> 00:46:35,359
Speaker 2: they win, I'll eat it.

1034
00:46:35,400 --> 00:46:38,480
Speaker 3: But I don't. I don't know. I mean, at the.

1035
00:46:38,480 --> 00:46:40,880
Speaker 2: Very least, I personally, I think it's ridiculous and stupid.

1036
00:46:41,120 --> 00:46:44,799
Speaker 2: But listen, there's maybe enough people who the pets thing

1037
00:46:44,840 --> 00:46:48,479
Speaker 2: gets them thinking about the migrant situation and that's enough

1038
00:46:48,480 --> 00:46:51,319
Speaker 2: for them to vote Republican. Again, I don't see any

1039
00:46:51,520 --> 00:46:54,040
Speaker 2: I don't see evidence recently that that is correct. I

1040
00:46:54,040 --> 00:46:56,440
Speaker 2: think it's actually a really bad way to do politics.

1041
00:46:56,480 --> 00:46:59,040
Speaker 2: I also think, you know, for them too. You're betting

1042
00:46:59,080 --> 00:47:01,400
Speaker 2: everything on the line here, guys, Like, if you lose,

1043
00:47:01,560 --> 00:47:04,400
Speaker 2: you're done, like your net. Think about it serious in

1044
00:47:04,480 --> 00:47:07,600
Speaker 2: terms of being taken seriously as a party apparatus. I

1045
00:47:07,719 --> 00:47:09,439
Speaker 2: know this Trump is exempt from this just because he's

1046
00:47:09,440 --> 00:47:11,440
Speaker 2: like bigger above that category.

1047
00:47:11,480 --> 00:47:14,520
Speaker 3: But for everybody else jd included. You're a young man, dude.

1048
00:47:14,560 --> 00:47:15,920
Speaker 3: You know you got to live your whole life in

1049
00:47:15,920 --> 00:47:16,319
Speaker 3: this town.

1050
00:47:16,560 --> 00:47:18,720
Speaker 2: If you lose, you're gonna be one of those senators

1051
00:47:18,880 --> 00:47:21,400
Speaker 2: who's a lifer. You want to be like Josh Holly

1052
00:47:21,440 --> 00:47:23,000
Speaker 2: put his fist up and hasn't seen a light of

1053
00:47:23,040 --> 00:47:24,240
Speaker 2: day in four years.

1054
00:47:24,280 --> 00:47:26,719
Speaker 3: I don't want to be like that. Yeah, So it's

1055
00:47:26,760 --> 00:47:30,959
Speaker 3: like why why now? And there's no no choice. Yeah,

1056
00:47:31,480 --> 00:47:32,879
Speaker 3: going on, it is genuinely over.

1057
00:47:33,000 --> 00:47:35,239
Speaker 2: Yeah, you either win, you or put it everything you

1058
00:47:35,239 --> 00:47:38,400
Speaker 2: were either win or in my opinion, like sign up

1059
00:47:38,400 --> 00:47:39,960
Speaker 2: for the Holly category like enjoy.

1060
00:47:40,080 --> 00:47:41,640
Speaker 3: Yeah, because I don't think it's a fun place to be.

1061
00:47:42,080 --> 00:47:44,919
Speaker 1: Well, we were talking about this on Thursday after our show,

1062
00:47:45,200 --> 00:47:47,160
Speaker 1: and I said, because we were we were looking at

1063
00:47:47,160 --> 00:47:49,960
Speaker 1: the like polymarket odds on whether Trump was going to.

1064
00:47:49,960 --> 00:47:53,200
Speaker 3: Say cat Yes, didn't say it, by the way, he

1065
00:47:53,239 --> 00:47:53,760
Speaker 3: said pats.

1066
00:47:53,800 --> 00:47:56,320
Speaker 1: But I said, he's going to talk about this because

1067
00:47:56,440 --> 00:47:58,760
Speaker 1: he thinks this is good for him, because he can't

1068
00:47:58,800 --> 00:48:01,760
Speaker 1: tell the difference between good and bad publicity. He thinks

1069
00:48:01,840 --> 00:48:04,479
Speaker 1: any intention on him is good, and it's been driving

1070
00:48:04,520 --> 00:48:06,560
Speaker 1: him crazy that he's not been the main character.

1071
00:48:07,120 --> 00:48:10,360
Speaker 4: So the public has developed.

1072
00:48:09,840 --> 00:48:12,439
Speaker 1: Some in the media and the political class every he's

1073
00:48:12,440 --> 00:48:16,040
Speaker 1: developed some immunity to Trump's insanity.

1074
00:48:15,520 --> 00:48:16,240
Speaker 4: Over the years.

1075
00:48:16,680 --> 00:48:19,960
Speaker 1: So the things that send the media into a tizzy

1076
00:48:20,080 --> 00:48:22,440
Speaker 1: that worked in twenty sixteen, they don't work the same

1077
00:48:22,480 --> 00:48:24,839
Speaker 1: way in twenty twenty four. Right, like the you know,

1078
00:48:24,960 --> 00:48:27,960
Speaker 1: she turned black thing? Everyone is for one day like

1079
00:48:28,360 --> 00:48:30,480
Speaker 1: what the hell? And then they moved on, and Kamlires

1080
00:48:30,560 --> 00:48:32,719
Speaker 1: very smartly, was like, same old playbook, who cares, Let's

1081
00:48:32,719 --> 00:48:35,400
Speaker 1: move on, let's talk about you. So this is the

1082
00:48:35,400 --> 00:48:39,480
Speaker 1: first time he said something outrageous, disgusting, insane enough that

1083
00:48:39,560 --> 00:48:42,920
Speaker 1: it did send everybody into a tizzy. And so he

1084
00:48:43,239 --> 00:48:46,400
Speaker 1: likes being in that situation again where he gets to

1085
00:48:46,760 --> 00:48:50,960
Speaker 1: control the narrative. But yeah, it's not the same as

1086
00:48:51,000 --> 00:48:55,200
Speaker 1: twenty sixteen because this is yes, it feeds into a

1087
00:48:55,360 --> 00:48:57,680
Speaker 1: I guess, the conversation about immigration, but I would argue

1088
00:48:57,760 --> 00:49:01,200
Speaker 1: it actually undercuts your position on immigration because you're not

1089
00:49:01,239 --> 00:49:04,160
Speaker 1: talking about this as an economic issue, you're not talking

1090
00:49:04,160 --> 00:49:06,920
Speaker 1: about this as a housing issue. You're talking about it

1091
00:49:07,000 --> 00:49:10,719
Speaker 1: in an incredibly sorry, racist way. And so people look

1092
00:49:10,760 --> 00:49:13,480
Speaker 1: at this and go, oh, like, oh, that's what this is.

1093
00:49:13,440 --> 00:49:14,400
Speaker 4: Actually all about.

1094
00:49:14,719 --> 00:49:17,280
Speaker 1: So the framing on the issue is the polar opposite

1095
00:49:17,320 --> 00:49:20,040
Speaker 1: of what you would want. And number two, it validates

1096
00:49:20,080 --> 00:49:22,440
Speaker 1: the democratic frame of like, these people are just weird,

1097
00:49:22,640 --> 00:49:24,280
Speaker 1: Like they're just a bunch of weird freaks.

1098
00:49:24,560 --> 00:49:26,360
Speaker 4: And when they're googling you.

1099
00:49:26,239 --> 00:49:28,880
Speaker 1: With pets and dogs and cats and whatever, and you

1100
00:49:28,960 --> 00:49:31,839
Speaker 1: think it's great that people are making tiktoks making fun

1101
00:49:31,880 --> 00:49:33,920
Speaker 1: of you. You don't even see that they're like mocking

1102
00:49:33,960 --> 00:49:37,400
Speaker 1: you to your face. You think this is wonderful for you.

1103
00:49:37,840 --> 00:49:41,799
Speaker 1: But the reality is that this actually just validates the

1104
00:49:41,840 --> 00:49:45,239
Speaker 1: democratic framing the way they have wanted, the lens they've

1105
00:49:45,320 --> 00:49:48,400
Speaker 1: wanted to apply to you. So being the main character

1106
00:49:48,560 --> 00:49:50,880
Speaker 1: in this instance not always the thing I think you

1107
00:49:50,960 --> 00:49:51,560
Speaker 1: ultimately want.

1108
00:49:51,760 --> 00:49:53,440
Speaker 2: The reason I'm just not willing to is I'm a

1109
00:49:53,480 --> 00:49:55,480
Speaker 2: cynical person, and I think that there's a lot of

1110
00:49:55,520 --> 00:49:57,640
Speaker 2: people out there who may like it. I think that

1111
00:49:57,680 --> 00:50:00,279
Speaker 2: there are people who really enjoy the media getting.

1112
00:50:00,400 --> 00:50:01,759
Speaker 3: Upset and liberals.

1113
00:50:01,920 --> 00:50:04,200
Speaker 2: I think that, look, there's a decent enough evidence on

1114
00:50:04,239 --> 00:50:06,160
Speaker 2: the immigration question as well, that a lot of people

1115
00:50:06,160 --> 00:50:08,719
Speaker 2: who care about immigration don't care about economics at all.

1116
00:50:08,719 --> 00:50:10,200
Speaker 3: They're worried about demographic change.

1117
00:50:10,200 --> 00:50:12,000
Speaker 4: Those people are already voted, yes.

1118
00:50:12,120 --> 00:50:15,120
Speaker 2: But you know, let's say it's not even about swaying,

1119
00:50:15,120 --> 00:50:17,759
Speaker 2: it's about getting those people out to vote. Maybe that's

1120
00:50:18,000 --> 00:50:20,800
Speaker 2: enough to get them off the couch or their relatives.

1121
00:50:20,800 --> 00:50:23,560
Speaker 2: The immigration situation has been crazy enough that, you know,

1122
00:50:23,640 --> 00:50:26,319
Speaker 2: maybe it's enough that for them to forgive that or

1123
00:50:26,360 --> 00:50:28,839
Speaker 2: to think about this whole policy thing again. I don't

1124
00:50:28,840 --> 00:50:30,680
Speaker 2: see evidence for that, but I'm not going to discount

1125
00:50:30,719 --> 00:50:32,400
Speaker 2: that possibility. He has turned out people.

1126
00:50:32,560 --> 00:50:34,000
Speaker 1: I'm going to waund that possiblity.

1127
00:50:34,239 --> 00:50:34,360
Speaker 2: You know.

1128
00:50:34,400 --> 00:50:35,920
Speaker 1: The other thing here.

1129
00:50:35,920 --> 00:50:38,320
Speaker 3: Did win in twenty sixteen, he won.

1130
00:50:38,360 --> 00:50:41,160
Speaker 1: He won in twenty sixteen, he lost, But he's been

1131
00:50:41,200 --> 00:50:45,320
Speaker 1: losing ever since. Lost in twenty eighteen, lost in twenty twenty,

1132
00:50:45,560 --> 00:50:48,160
Speaker 1: lost in twenty twenty two. This guy does not have

1133
00:50:48,239 --> 00:50:50,279
Speaker 1: the touch in the sense that he used to. And

1134
00:50:50,320 --> 00:50:52,120
Speaker 1: this will fit in with, you know, the conversation we're

1135
00:50:52,120 --> 00:50:55,719
Speaker 1: about to have about Laura Lumer. Like his posture in

1136
00:50:55,800 --> 00:50:59,560
Speaker 1: twenty sixteen was tabloid, it was sensationalist, it was New

1137
00:50:59,640 --> 00:51:03,759
Speaker 1: York pos right, it was the tabloid like finger on

1138
00:51:03,840 --> 00:51:06,799
Speaker 1: the pulse in a raunchy, over the top, obnoxious way,

1139
00:51:06,920 --> 00:51:09,560
Speaker 1: but yeah, finger on the pulse. Then in twenty twenty,

1140
00:51:09,560 --> 00:51:11,719
Speaker 1: he's like Fox News Grandpa, which there still is a

1141
00:51:11,800 --> 00:51:14,840
Speaker 1: large appetite for in the country, right, mainstream sort of

1142
00:51:14,840 --> 00:51:17,720
Speaker 1: conservative Fox News Grandpa talking points.

1143
00:51:18,200 --> 00:51:20,120
Speaker 4: That's good enough to get him close.

1144
00:51:20,600 --> 00:51:23,080
Speaker 1: Now it's like truth social or like you know, the

1145
00:51:23,440 --> 00:51:26,919
Speaker 1: weird echo chambers on Twitter listening to Laura Lumer taking

1146
00:51:26,960 --> 00:51:30,440
Speaker 1: advice from her as if she's a positive asset for

1147
00:51:30,520 --> 00:51:33,920
Speaker 1: your campaign. I just think he's completely lost the plot.

1148
00:51:34,000 --> 00:51:38,120
Speaker 1: And Dave Weigel tweeted this, which I think is really true.

1149
00:51:38,239 --> 00:51:41,320
Speaker 1: He's like, sometimes you're living rent free in your opponent's

1150
00:51:41,360 --> 00:51:43,440
Speaker 1: head because you pissed your pants and they think it's

1151
00:51:43,520 --> 00:51:47,399
Speaker 1: really funny. Like not all publicity is good publicity. And

1152
00:51:48,320 --> 00:51:50,480
Speaker 1: we already know from the polls we just covered this

1153
00:51:50,600 --> 00:51:52,640
Speaker 1: did not go well for him, Like it did not

1154
00:51:52,760 --> 00:51:53,520
Speaker 1: go well for him.

1155
00:51:53,680 --> 00:51:56,720
Speaker 4: The more people, the more people were familiar.

1156
00:51:56,280 --> 00:51:57,960
Speaker 1: With the debate and things that he had to say

1157
00:51:57,960 --> 00:52:00,600
Speaker 1: of the debate, like the pets thing, the less they

1158
00:52:00,640 --> 00:52:03,359
Speaker 1: are to support Donald Trump. So in a sense, like

1159
00:52:03,400 --> 00:52:06,360
Speaker 1: the verdict is already in with the polling and what

1160
00:52:06,440 --> 00:52:08,560
Speaker 1: has come out of that. She's narrowed the gap on

1161
00:52:08,560 --> 00:52:11,200
Speaker 1: the economy, She's even narrowed the gap on immigration and

1162
00:52:11,239 --> 00:52:14,520
Speaker 1: how who people think would be better on that issue?

1163
00:52:14,840 --> 00:52:18,279
Speaker 1: She was seen as She's she's improved in favorability. Donald

1164
00:52:18,320 --> 00:52:21,480
Speaker 1: Trump has fallen in favorability post debate. The polling has

1165
00:52:21,520 --> 00:52:25,000
Speaker 1: been almost uniformly better for her. So like I sort

1166
00:52:25,000 --> 00:52:26,640
Speaker 1: of feel like the jury is already in with the

1167
00:52:26,719 --> 00:52:28,200
Speaker 1: data that we already have, and you can say these

1168
00:52:28,200 --> 00:52:28,680
Speaker 1: poles are.

1169
00:52:28,560 --> 00:52:29,800
Speaker 3: All off, that's my point.

1170
00:52:29,640 --> 00:52:33,040
Speaker 1: But but we're looking at poles, We're looking at the

1171
00:52:33,040 --> 00:52:35,400
Speaker 1: trend line, right, And so even if you say a

1172
00:52:35,440 --> 00:52:38,200
Speaker 1: given pole is off in their methodology, if the trend

1173
00:52:38,239 --> 00:52:41,319
Speaker 1: line moved in her direction, that still is representative or

1174
00:52:41,360 --> 00:52:44,640
Speaker 1: reflective of a real change that actually happened, given that

1175
00:52:44,640 --> 00:52:46,040
Speaker 1: they're using the same methodology.

1176
00:52:46,080 --> 00:52:47,600
Speaker 2: But if he wins, what is he going to take

1177
00:52:47,600 --> 00:52:49,080
Speaker 2: away from this? What are him and JD going to

1178
00:52:49,080 --> 00:52:51,080
Speaker 2: take away from this? I mean, if you win the election,

1179
00:52:51,239 --> 00:52:54,040
Speaker 2: you know, and you pursue this, you get put back

1180
00:52:54,040 --> 00:52:56,160
Speaker 2: into the White House. I mean, I think that's frankly,

1181
00:52:56,400 --> 00:52:58,200
Speaker 2: like we need all need to grapple with that. Then

1182
00:52:58,239 --> 00:53:00,160
Speaker 2: we're like, okay, well we're gonna have to have some

1183
00:53:00,160 --> 00:53:04,320
Speaker 2: twenty sixteen ever conversations again about like, all right, clearly

1184
00:53:04,600 --> 00:53:06,920
Speaker 2: there's something going on here, you know, people are.

1185
00:53:08,280 --> 00:53:10,040
Speaker 4: It could also be though in spite of this, not

1186
00:53:10,120 --> 00:53:11,680
Speaker 4: because of this, but possible.

1187
00:53:11,719 --> 00:53:12,239
Speaker 3: Yeah.

1188
00:53:12,320 --> 00:53:14,560
Speaker 2: At the very length, when you win, all sins are forgiven.

1189
00:53:14,680 --> 00:53:16,520
Speaker 2: And so if you look at it and you think

1190
00:53:16,560 --> 00:53:19,440
Speaker 2: about it, if they win based on this, I would

1191
00:53:19,440 --> 00:53:21,200
Speaker 2: say it actually gives them the lead way to do

1192
00:53:21,320 --> 00:53:24,399
Speaker 2: whatever they want. They can say, listen, we've said this,

1193
00:53:24,760 --> 00:53:28,839
Speaker 2: We got away with this Americans when we told our

1194
00:53:28,880 --> 00:53:29,760
Speaker 2: directional truths.

1195
00:53:29,960 --> 00:53:30,600
Speaker 3: They listened.

1196
00:53:30,800 --> 00:53:34,680
Speaker 2: So mass deportation on the table, any family separation back

1197
00:53:34,719 --> 00:53:36,840
Speaker 2: on the table. We're not listening to the media criticism.

1198
00:53:36,960 --> 00:53:39,600
Speaker 2: We're not listening to any of this bullshit anymore. We're unhinged,

1199
00:53:39,640 --> 00:53:41,200
Speaker 2: and frankly, I don't think they would be wrong. You know,

1200
00:53:41,239 --> 00:53:43,080
Speaker 2: if they do win the election, even when they were

1201
00:53:43,080 --> 00:53:45,279
Speaker 2: conducting themselves this way and all that, I think it

1202
00:53:45,280 --> 00:53:48,160
Speaker 2: tells you something pretty clear about where things are going.

1203
00:53:48,200 --> 00:53:50,680
Speaker 2: You may not like that direction, but it's very possible.

1204
00:53:50,719 --> 00:53:53,480
Speaker 2: So I guess I'm just this is a test of

1205
00:53:53,480 --> 00:53:56,319
Speaker 2: political theories. My theory is that you should not lie

1206
00:53:56,320 --> 00:54:00,200
Speaker 2: to people, do the directional truth. My theory is that

1207
00:54:00,600 --> 00:54:04,719
Speaker 2: constantly trying to validate, you know, this partisan bullshit like

1208
00:54:04,760 --> 00:54:07,399
Speaker 2: no offense, Christopher Rufo, but this whole thing about like, oh, well,

1209
00:54:07,440 --> 00:54:10,480
Speaker 2: some African guys forty five miles away barbecue a cat

1210
00:54:10,520 --> 00:54:13,000
Speaker 2: in twenty twenty three, I'm like, yeah, but that's not

1211
00:54:13,040 --> 00:54:14,920
Speaker 2: what we're talking about here, and that's.

1212
00:54:14,800 --> 00:54:18,160
Speaker 1: Not even potentially reality. But anyway, you paid five thousand

1213
00:54:18,120 --> 00:54:20,240
Speaker 1: dollars though, Yeah, whatever, regardless.

1214
00:54:19,800 --> 00:54:21,879
Speaker 3: Of whether it's true or not. I'm just like, but

1215
00:54:21,920 --> 00:54:24,319
Speaker 3: that's not actually what he said. That's not what he said.

1216
00:54:24,400 --> 00:54:25,960
Speaker 3: They said X Y and see.

1217
00:54:26,239 --> 00:54:28,399
Speaker 2: Now, I mean I think politicians should have to tell

1218
00:54:28,440 --> 00:54:31,080
Speaker 2: the truth. I think that when they say things based

1219
00:54:31,120 --> 00:54:35,240
Speaker 2: on quote unquote anecdotal evidence, as you know, as backing

1220
00:54:35,360 --> 00:54:38,880
Speaker 2: up allegedly. You know, I'll put it this way, just

1221
00:54:38,920 --> 00:54:41,200
Speaker 2: because some of your constituents said that X, Y and

1222
00:54:41,320 --> 00:54:43,680
Speaker 2: Z was true, you know, he's jad keep saying it.

1223
00:54:43,719 --> 00:54:46,200
Speaker 2: My constituents keeps saying this is true, my constituents.

1224
00:54:46,440 --> 00:54:47,759
Speaker 1: So he has produced seven months up.

1225
00:54:47,800 --> 00:54:49,640
Speaker 2: But go on, Yeah, but even if that's the case,

1226
00:54:49,920 --> 00:54:52,000
Speaker 2: that's not a good enough standard to come out of

1227
00:54:52,040 --> 00:54:57,279
Speaker 2: your mouth, Like your extraordinary claims require extraordinary evidence. You

1228
00:54:57,440 --> 00:55:00,000
Speaker 2: have to be able to And also as a politician,

1229
00:55:00,080 --> 00:55:01,680
Speaker 2: I mean, part of the reason that we don't live

1230
00:55:01,680 --> 00:55:03,719
Speaker 2: in a quote unquote direct democracy and we do live

1231
00:55:03,880 --> 00:55:06,560
Speaker 2: in a republic is this idea that the founding fathers

1232
00:55:06,600 --> 00:55:11,279
Speaker 2: had of mediation between the whims and the whims and

1233
00:55:11,320 --> 00:55:12,279
Speaker 2: the like, the.

1234
00:55:12,960 --> 00:55:15,760
Speaker 3: Movement of the mob and considered people.

1235
00:55:15,800 --> 00:55:18,360
Speaker 2: That's specifically, the entire job of the United States Senate

1236
00:55:18,440 --> 00:55:21,520
Speaker 2: is to cool the temperature of the country, to provide

1237
00:55:21,640 --> 00:55:25,600
Speaker 2: due diligence and deliberation around where things are now. Throughout

1238
00:55:25,640 --> 00:55:29,960
Speaker 2: our history there has been deep vacillation between wanting the diligent,

1239
00:55:30,080 --> 00:55:33,000
Speaker 2: the professor, the Obama and then the id people like

1240
00:55:33,080 --> 00:55:35,600
Speaker 2: Donald Trump or many other populos, not even at the

1241
00:55:35,719 --> 00:55:38,719
Speaker 2: national level, at the state level too. So I could

1242
00:55:38,760 --> 00:55:41,600
Speaker 2: be again, they could be right, like they really could

1243
00:55:41,600 --> 00:55:46,200
Speaker 2: be running some sort of Richard Nixon style nineteen sixty

1244
00:55:46,200 --> 00:55:49,040
Speaker 2: eight silent majority. The media treated Nixon the same way.

1245
00:55:49,160 --> 00:55:51,880
Speaker 2: The problem I have is I read about Nixon. Nixon

1246
00:55:51,880 --> 00:55:53,719
Speaker 2: probably had like a one to sixty, IQ, we might

1247
00:55:53,760 --> 00:55:55,960
Speaker 2: be one of the smartest people who has ever held.

1248
00:55:55,800 --> 00:55:56,640
Speaker 3: The Oval office.

1249
00:55:56,719 --> 00:55:58,759
Speaker 2: It was a lot more disciplined, he was a lot

1250
00:55:58,800 --> 00:56:02,200
Speaker 2: more considered. Sure, morals weren't always there necessarily, but I

1251
00:56:02,239 --> 00:56:04,800
Speaker 2: think he was a very smart man, a very calculating man,

1252
00:56:04,920 --> 00:56:06,920
Speaker 2: and in many cases he was a very good president.

1253
00:56:06,960 --> 00:56:09,760
Speaker 2: So I don't see the same, you know, the same

1254
00:56:09,880 --> 00:56:12,440
Speaker 2: link between them. But they have a theory, and the

1255
00:56:12,440 --> 00:56:14,680
Speaker 2: theory has worked. I mean, anybody who can win the

1256
00:56:14,719 --> 00:56:18,040
Speaker 2: Oval that's something. And you know that's something that I

1257
00:56:18,080 --> 00:56:20,279
Speaker 2: know because in that moment I said, how could this

1258
00:56:20,320 --> 00:56:22,319
Speaker 2: man ever get elected? And he did so, I mean

1259
00:56:22,360 --> 00:56:25,680
Speaker 2: it shattered my political consciousness for all time. I can

1260
00:56:25,719 --> 00:56:27,400
Speaker 2: never just sit here and just be like, no, I

1261
00:56:27,400 --> 00:56:30,000
Speaker 2: don't think it's going to work. I mean, really believe

1262
00:56:30,239 --> 00:56:32,080
Speaker 2: I could be totally wrong about the way that I

1263
00:56:32,320 --> 00:56:33,799
Speaker 2: viewed the public, and I've been proved wrong on the

1264
00:56:33,800 --> 00:56:35,120
Speaker 2: show so many different times.

1265
00:56:35,400 --> 00:56:39,239
Speaker 1: The theory they have of Americans is deeply cynical. He

1266
00:56:39,320 --> 00:56:43,160
Speaker 1: might be right, because I mean, think about what they've

1267
00:56:43,440 --> 00:56:47,200
Speaker 1: incited in this town, not just against the legal, by

1268
00:56:47,200 --> 00:56:49,920
Speaker 1: the way Haitian residents of this town, but against the

1269
00:56:49,920 --> 00:56:51,920
Speaker 1: whole town. You have the mayor, you of the governor

1270
00:56:52,000 --> 00:56:55,360
Speaker 1: begging for them to stop, because now it's not just

1271
00:56:55,440 --> 00:56:57,600
Speaker 1: Haitians who go to those elementary schools that have been

1272
00:56:57,600 --> 00:57:00,520
Speaker 1: subject to bomb threats. It's not just Haitians that want

1273
00:57:00,520 --> 00:57:02,960
Speaker 1: to seek treatment at the hospital that's been subject to

1274
00:57:03,440 --> 00:57:04,040
Speaker 1: bomb threats.

1275
00:57:04,080 --> 00:57:04,600
Speaker 4: It's not just.

1276
00:57:04,600 --> 00:57:07,680
Speaker 1: Haitians that are like under siege in this little Ohio

1277
00:57:07,800 --> 00:57:11,000
Speaker 1: town that JD. Vans, by the way, represents as his constituents.

1278
00:57:11,360 --> 00:57:16,040
Speaker 1: It's this entire town. And so, yeah, their bet is

1279
00:57:16,080 --> 00:57:19,280
Speaker 1: that actually the core concerns that people have again about

1280
00:57:19,280 --> 00:57:23,120
Speaker 1: immigration are not actually about housing, wages, what cetera, et cetera,

1281
00:57:23,360 --> 00:57:25,120
Speaker 1: are the things that you talk about, soeer it's not

1282
00:57:25,160 --> 00:57:28,840
Speaker 1: actually about that, it's actually just like racist. We don't

1283
00:57:28,880 --> 00:57:30,800
Speaker 1: like these people because they're different, and we want them out,

1284
00:57:31,200 --> 00:57:33,480
Speaker 1: and so we're gonna plan to that. We're going to

1285
00:57:33,560 --> 00:57:35,960
Speaker 1: lean into that. That's the bet that they're making. And

1286
00:57:36,880 --> 00:57:39,320
Speaker 1: I just don't believe that. I don't think most Americans

1287
00:57:40,120 --> 00:57:43,479
Speaker 1: want to see themselves as racists. I don't think they

1288
00:57:43,760 --> 00:57:47,479
Speaker 1: want to have their policy views or who they vote

1289
00:57:47,480 --> 00:57:52,760
Speaker 1: for for president driven by just like explicit racist fear mongering.

1290
00:57:53,320 --> 00:57:56,640
Speaker 1: And so it's a little bit it's too naked, right,

1291
00:57:56,680 --> 00:57:59,240
Speaker 1: it's too mask off. And this is what the conversation

1292
00:57:59,320 --> 00:58:01,360
Speaker 1: we had about the life Kamala Harris she turned Black

1293
00:58:01,400 --> 00:58:02,720
Speaker 1: thing too, where I was like, this is not going

1294
00:58:02,800 --> 00:58:07,840
Speaker 1: to work because it's too naked a racial appeal and

1295
00:58:08,400 --> 00:58:10,960
Speaker 1: most people you got your you know, you got your

1296
00:58:10,960 --> 00:58:13,840
Speaker 1: people out there or who are cool with that. Unfortunately,

1297
00:58:13,920 --> 00:58:16,080
Speaker 1: that is a reality that exists and has always existed

1298
00:58:16,080 --> 00:58:19,760
Speaker 1: in American and probably always will exist. The overwhelming majority

1299
00:58:19,760 --> 00:58:23,280
Speaker 1: of Americans really do believe in like the best ideal of.

1300
00:58:23,400 --> 00:58:25,640
Speaker 4: The melting pot. They don't want.

1301
00:58:25,440 --> 00:58:30,960
Speaker 1: To see themselves as explicitly sexist, racist, xenophobic, whatever, and

1302
00:58:31,040 --> 00:58:34,200
Speaker 1: you're kind of stripping them a plausible deniability here with

1303
00:58:34,280 --> 00:58:36,920
Speaker 1: this whole Haitian pet situation.

1304
00:58:37,440 --> 00:58:40,000
Speaker 4: So that's why I think, to.

1305
00:58:40,000 --> 00:58:42,360
Speaker 1: Me, it's just very clear that this is a fail,

1306
00:58:42,400 --> 00:58:44,439
Speaker 1: that it's already a fail even and I'm not saying

1307
00:58:44,480 --> 00:58:46,800
Speaker 1: that it doesn't mean he can't win, but if he does,

1308
00:58:46,880 --> 00:58:48,600
Speaker 1: it will be in spite of this, because we already

1309
00:58:48,600 --> 00:58:51,160
Speaker 1: see the way the poll numbers have moved against him

1310
00:58:51,680 --> 00:58:54,480
Speaker 1: post debate when this became the Congress.

1311
00:58:54,560 --> 00:58:55,280
Speaker 3: Counter is simple.

1312
00:58:55,360 --> 00:58:58,160
Speaker 2: The counter is is that rapid demographic change doesn't mean

1313
00:58:58,160 --> 00:59:00,200
Speaker 2: that you're racist. It means that you want control roll

1314
00:59:00,640 --> 00:59:02,360
Speaker 2: over that, even uncontrolled system.

1315
00:59:02,680 --> 00:59:04,240
Speaker 1: I mean, that's that's not what they're saying.

1316
00:59:04,280 --> 00:59:06,160
Speaker 3: No, no, no, But I'm thinking about this is what

1317
00:59:06,560 --> 00:59:06,840
Speaker 3: this is.

1318
00:59:07,000 --> 00:59:09,040
Speaker 2: Look, if you get somebody to vote for Trump in

1319
00:59:09,120 --> 00:59:11,800
Speaker 2: spite of this on the immigration question, it's going to.

1320
00:59:11,800 --> 00:59:14,200
Speaker 3: Be this all right. I got two choices.

1321
00:59:14,360 --> 00:59:17,480
Speaker 2: I got a candidate who We had more illegal immigrants

1322
00:59:17,560 --> 00:59:21,600
Speaker 2: enter the country under their terrain than a decade before.

1323
00:59:21,880 --> 00:59:23,960
Speaker 2: We have the highest level of the foreign born population

1324
00:59:24,040 --> 00:59:27,320
Speaker 2: since the nineteen hundreds, We have ethnic strife. Do we

1325
00:59:27,400 --> 00:59:32,640
Speaker 2: want to live in a Balkanized America of ethnic enclaves

1326
00:59:32,680 --> 00:59:35,200
Speaker 2: in various different cities where half of these people don't

1327
00:59:35,240 --> 00:59:38,560
Speaker 2: speak any English. The vast majority of them are semi literate,

1328
00:59:38,800 --> 00:59:40,760
Speaker 2: they don't have a high school degree. I mean, by

1329
00:59:40,800 --> 00:59:44,000
Speaker 2: the way, these Haitians, these people are here under TPS,

1330
00:59:44,000 --> 00:59:45,760
Speaker 2: which is supposed to be temporary, but they're not even

1331
00:59:45,760 --> 00:59:46,520
Speaker 2: supposed to be here.

1332
00:59:46,880 --> 00:59:49,000
Speaker 1: We don't actually even some of them. I'm sure that's

1333
00:59:49,000 --> 00:59:51,320
Speaker 1: true for some of them. Some of them the indication

1334
00:59:51,400 --> 00:59:53,680
Speaker 1: from the mayor and other authorities, they actually have been

1335
00:59:53,720 --> 00:59:55,960
Speaker 1: here for years they moved into the town from other

1336
00:59:55,960 --> 00:59:58,080
Speaker 1: places because there were job opportunities.

1337
00:59:58,440 --> 01:00:02,479
Speaker 2: So the ones okay, listen, So I'm just what I'm saying,

1338
01:00:04,200 --> 01:00:08,600
Speaker 2: migrant That s implies forever permanence. They're here under TPS,

1339
01:00:08,760 --> 01:00:10,840
Speaker 2: which is supposed to be they're supposed to go back.

1340
01:00:10,920 --> 01:00:12,640
Speaker 3: So when are you going back? And that's part of

1341
01:00:12,640 --> 01:00:13,080
Speaker 3: the problem.

1342
01:00:13,280 --> 01:00:15,520
Speaker 2: In America, we have an immigration system where you can

1343
01:00:15,560 --> 01:00:17,000
Speaker 2: just come here and say, oh, I fear for my life,

1344
01:00:17,040 --> 01:00:19,000
Speaker 2: and you get to stay here forever. Basically, even if

1345
01:00:19,000 --> 01:00:20,520
Speaker 2: the court tells you to leave, you don't have to leave.

1346
01:00:20,520 --> 01:00:23,920
Speaker 2: There's no enforcement. You're in a town of Springfield, Ohio.

1347
01:00:23,960 --> 01:00:26,240
Speaker 2: You're what is it, sixty thousand people, Your mayor and

1348
01:00:26,280 --> 01:00:28,400
Speaker 2: your leaders have decided to invite others. You didn't necessarily

1349
01:00:28,440 --> 01:00:30,560
Speaker 2: sign off for that. The federal government puts you there,

1350
01:00:30,720 --> 01:00:32,800
Speaker 2: and you say, listen, this is intolerable to me.

1351
01:00:32,960 --> 01:00:35,160
Speaker 3: I don't want to live this way. Now.

1352
01:00:35,320 --> 01:00:38,320
Speaker 2: Look, my parents aren't immigrants, so this is complicated. But

1353
01:00:39,120 --> 01:00:40,640
Speaker 2: all I need to do is go back and read

1354
01:00:40,720 --> 01:00:43,120
Speaker 2: enough history where let's put yourself in the shoes of

1355
01:00:43,160 --> 01:00:47,919
Speaker 2: these waspy elites or others. And it's eighteen thirty. You're

1356
01:00:47,960 --> 01:00:51,920
Speaker 2: in this newly industrialized economy. You're previously an agrarian society.

1357
01:00:52,160 --> 01:00:54,440
Speaker 2: You and your parents, you know, your family goes back

1358
01:00:54,440 --> 01:00:57,360
Speaker 2: to Jamestown or fought in the Revolutionary War. And now

1359
01:00:57,360 --> 01:01:00,200
Speaker 2: your whole neighborhood is Irish and people are wasted all

1360
01:01:00,200 --> 01:01:02,600
Speaker 2: the time beating the crap out of their wives working

1361
01:01:02,840 --> 01:01:03,640
Speaker 2: at the factory.

1362
01:01:03,720 --> 01:01:06,080
Speaker 3: I mean, listen, is it legitimate.

1363
01:01:05,640 --> 01:01:07,320
Speaker 4: Pulling out the anti Irish bigotry?

1364
01:01:07,960 --> 01:01:10,800
Speaker 2: They passed prohibition because these people were drinking a leader.

1365
01:01:11,200 --> 01:01:13,840
Speaker 1: Tell me about the Italians. I'll tell you the problem

1366
01:01:13,920 --> 01:01:17,760
Speaker 1: with them. But I've been saying they immigrated. They okay,

1367
01:01:18,000 --> 01:01:18,480
Speaker 1: but yeah.

1368
01:01:18,640 --> 01:01:20,720
Speaker 3: We shut down immigration about fifty years.

1369
01:01:20,720 --> 01:01:24,040
Speaker 1: But this is the point, is every single wave of

1370
01:01:24,120 --> 01:01:28,360
Speaker 1: migration we've had, like there have been, you know, similar

1371
01:01:28,480 --> 01:01:30,880
Speaker 1: fear mongering about these girls. They'll never integrate and they'll

1372
01:01:30,920 --> 01:01:33,480
Speaker 1: never learn the language, and they'll never be part of society.

1373
01:01:33,480 --> 01:01:36,720
Speaker 1: We're gonna have these Balkanized ethnic enclave neighborhoods, et cetera,

1374
01:01:36,760 --> 01:01:40,680
Speaker 1: et cetera. And every single time, guess what generation later,

1375
01:01:40,800 --> 01:01:43,840
Speaker 1: they're just American. Their kids are speaking English, they're eating McDonald's,

1376
01:01:43,840 --> 01:01:46,120
Speaker 1: they're doing the whole shing. You talk to the people

1377
01:01:46,160 --> 01:01:48,680
Speaker 1: in the town, you know, not the ones that like,

1378
01:01:48,800 --> 01:01:51,360
Speaker 1: you know, right wing YouTubers were interviewing that we're calling

1379
01:01:51,400 --> 01:01:55,240
Speaker 1: the Haitian immigrants quote unquote sand monkeys. Yes, this was

1380
01:01:55,280 --> 01:01:59,000
Speaker 1: proffered as evidence that this was legitimate. You know that

1381
01:01:59,080 --> 01:02:01,960
Speaker 1: this was a legitimate criticism. But if you talk to

1382
01:02:02,200 --> 01:02:04,320
Speaker 1: a lot of the people in the town, this was

1383
01:02:04,360 --> 01:02:07,360
Speaker 1: a town that was struggling, right. It was like the

1384
01:02:07,360 --> 01:02:09,960
Speaker 1: town that I lived in Ohio where the jobs had

1385
01:02:09,960 --> 01:02:12,960
Speaker 1: gone away. They had seen a massive population, a depopulation,

1386
01:02:13,640 --> 01:02:16,720
Speaker 1: and that's death for a town. It's death for you know,

1387
01:02:16,760 --> 01:02:21,920
Speaker 1: the infrastructure, it's death for the tax base, the schools, everything.

1388
01:02:22,400 --> 01:02:27,600
Speaker 1: I don't doubt that there are entirely legitimate concerns about

1389
01:02:27,720 --> 01:02:30,400
Speaker 1: you know, when a group, whatever group it is, wherever

1390
01:02:30,440 --> 01:02:32,280
Speaker 1: they come from, moves into the town, just like in

1391
01:02:32,360 --> 01:02:35,040
Speaker 1: Texas and Austin, right in other places where white people

1392
01:02:35,040 --> 01:02:36,840
Speaker 1: have moved in and it's like, oh shit, the housing

1393
01:02:36,880 --> 01:02:39,120
Speaker 1: prices are going up, et cetera, et cetera. I don't

1394
01:02:39,240 --> 01:02:42,280
Speaker 1: doubt that there have been challenges there, but there have

1395
01:02:42,400 --> 01:02:45,080
Speaker 1: also been really positive things. The pastors are saying, Hey,

1396
01:02:45,080 --> 01:02:47,800
Speaker 1: the churches are full again. You've had a huge community

1397
01:02:47,920 --> 01:02:52,160
Speaker 1: rallying around actually the patient migrants, Haitian migrants to the region,

1398
01:02:52,480 --> 01:02:55,040
Speaker 1: white people eating at the like Haitian restaurants, to show

1399
01:02:55,120 --> 01:02:56,720
Speaker 1: solidarity the.

1400
01:02:57,760 --> 01:02:58,080
Speaker 8: Good But.

1401
01:03:00,280 --> 01:03:02,240
Speaker 4: Disagrees allans.

1402
01:03:02,680 --> 01:03:04,240
Speaker 3: Yeah, whatever it is, I've had it. I had it

1403
01:03:04,280 --> 01:03:05,000
Speaker 3: when I was in Miami.

1404
01:03:05,040 --> 01:03:08,520
Speaker 1: Disagree, disagree, But in any case, you know, I just

1405
01:03:09,240 --> 01:03:11,320
Speaker 1: you and I see this very differently. That's been very

1406
01:03:11,320 --> 01:03:13,960
Speaker 1: clear in our discussions before. But to go back to

1407
01:03:14,040 --> 01:03:18,320
Speaker 1: just like the political point here, I just don't think

1408
01:03:18,600 --> 01:03:22,640
Speaker 1: that the reality for most Americans is that they experience

1409
01:03:22,680 --> 01:03:26,040
Speaker 1: in their daily lives this sense of like deep ethnic

1410
01:03:26,120 --> 01:03:27,480
Speaker 1: and racial strife.

1411
01:03:27,880 --> 01:03:29,280
Speaker 4: That's just not the reality.

1412
01:03:29,440 --> 01:03:33,400
Speaker 1: And Americans have complicated views on immigration, I think more

1413
01:03:33,400 --> 01:03:35,760
Speaker 1: complicated than the views in Europe, because we do have

1414
01:03:35,840 --> 01:03:38,840
Speaker 1: this conception and this reality as a nation of immigrants,

1415
01:03:38,880 --> 01:03:42,160
Speaker 1: and that is a core American value. So while it's

1416
01:03:42,200 --> 01:03:45,400
Speaker 1: completely legitimate to have debates about how many immigrants and

1417
01:03:45,440 --> 01:03:47,360
Speaker 1: how many can we process, and what are the burdens

1418
01:03:47,360 --> 01:03:53,440
Speaker 1: on the resources, et cetera, this sort of naked racial appeal,

1419
01:03:54,720 --> 01:03:57,920
Speaker 1: I already think the data shows proves it's a bridge

1420
01:03:57,920 --> 01:03:59,920
Speaker 1: too far for people, and it's not the way that

1421
01:04:00,120 --> 01:04:00,720
Speaker 1: think about.

1422
01:04:00,480 --> 01:04:01,880
Speaker 3: These A lot of people like to think that. I

1423
01:04:01,920 --> 01:04:03,000
Speaker 3: don't necessarily believe it.

1424
01:04:03,040 --> 01:04:05,640
Speaker 2: I think that, if anything, pouring more all of these

1425
01:04:05,640 --> 01:04:07,760
Speaker 2: illegals into the country over the last five years has

1426
01:04:07,760 --> 01:04:10,400
Speaker 2: probably exacerbated it to a level which, as you know,

1427
01:04:10,440 --> 01:04:12,800
Speaker 2: I don't necessarily want to see it. That's just my

1428
01:04:12,880 --> 01:04:15,120
Speaker 2: last counter is that at the end of the day,

1429
01:04:15,320 --> 01:04:19,200
Speaker 2: you have massive foreign born population here in the country

1430
01:04:19,280 --> 01:04:22,280
Speaker 2: that has always led to major strife. Now, you can

1431
01:04:22,320 --> 01:04:24,880
Speaker 2: just whitewash fifty years of history, but that's not how

1432
01:04:24,920 --> 01:04:26,840
Speaker 2: people saw it at the time. People, you know, we

1433
01:04:26,840 --> 01:04:29,440
Speaker 2: were fighting World War One. The Irish population didn't want

1434
01:04:29,440 --> 01:04:31,920
Speaker 2: to fight because we were supporting the English, and they

1435
01:04:31,920 --> 01:04:34,320
Speaker 2: were like, hey, we fled the English. The Germans were

1436
01:04:34,360 --> 01:04:36,520
Speaker 2: literally pro Kaiser during World War Two.

1437
01:04:36,600 --> 01:04:38,160
Speaker 1: They fought World War One, Okay, anyway.

1438
01:04:37,920 --> 01:04:38,360
Speaker 3: Fight okay.

1439
01:04:38,400 --> 01:04:41,080
Speaker 2: Well, during World War Two there was a massive Nazi

1440
01:04:41,120 --> 01:04:43,000
Speaker 2: fifth column here in the United States because of the

1441
01:04:43,080 --> 01:04:46,760
Speaker 2: German population. Ask the SS who had great files on

1442
01:04:46,840 --> 01:04:47,920
Speaker 2: all of our people.

1443
01:04:48,280 --> 01:04:49,240
Speaker 3: There is a problem.

1444
01:04:49,360 --> 01:04:51,360
Speaker 2: Now, does that mean that Japanese people should have been

1445
01:04:51,360 --> 01:04:53,480
Speaker 2: thrown in Terman camp and Germans and all of them

1446
01:04:53,480 --> 01:04:56,240
Speaker 2: should have been racially discriminated against. No, what I'm saying

1447
01:04:56,320 --> 01:04:59,680
Speaker 2: is foreign born populations at very very high levels cause

1448
01:04:59,760 --> 01:05:02,880
Speaker 2: re strife inside of a country. They people at that

1449
01:05:02,960 --> 01:05:06,040
Speaker 2: time responded to it by shutting down the border for

1450
01:05:06,120 --> 01:05:09,520
Speaker 2: fifty some years and restricting immigration so that all of

1451
01:05:09,560 --> 01:05:12,800
Speaker 2: those people could assimilate, which led to the Golden boom

1452
01:05:12,880 --> 01:05:15,520
Speaker 2: of the fifties, the sixties, and the seventies. It was

1453
01:05:15,560 --> 01:05:18,760
Speaker 2: only in sixty five that the Immigration Naturalization Act changed

1454
01:05:18,800 --> 01:05:22,560
Speaker 2: after some fifty years of assimilative policy that was instituted.

1455
01:05:22,760 --> 01:05:24,200
Speaker 2: If you want to live in a society that you

1456
01:05:24,240 --> 01:05:26,680
Speaker 2: and I probably want to live in more socially democratic.

1457
01:05:26,920 --> 01:05:29,200
Speaker 2: In Denmark, for example, if you're Muslim, you don't get

1458
01:05:29,240 --> 01:05:31,120
Speaker 2: to play the Quran if you're in school, they're like, oh,

1459
01:05:31,160 --> 01:05:33,960
Speaker 2: you're Muslim, that's cool, we don't do that here. In France,

1460
01:05:33,960 --> 01:05:36,080
Speaker 2: same thing, you're not wearing that hijab, and they have

1461
01:05:36,120 --> 01:05:38,560
Speaker 2: major problems with that. If you want to live in

1462
01:05:38,600 --> 01:05:40,880
Speaker 2: a socially democratic country. A lot of the times they

1463
01:05:40,920 --> 01:05:45,560
Speaker 2: have deeply restrictive immigration policy, specifically over resource questions and

1464
01:05:45,640 --> 01:05:49,000
Speaker 2: over ethnic homogeneity. I'm not saying that everybody has to

1465
01:05:49,200 --> 01:05:51,280
Speaker 2: look the same. I think people should speak the same.

1466
01:05:51,360 --> 01:05:54,040
Speaker 2: So when people come here and the vast majority of

1467
01:05:54,040 --> 01:05:56,520
Speaker 2: them are semi literate and Spanish and they don't speak

1468
01:05:56,520 --> 01:05:57,080
Speaker 2: into English.

1469
01:05:57,240 --> 01:05:58,160
Speaker 3: Is a huge problem.

1470
01:05:58,360 --> 01:06:00,360
Speaker 2: Like you can't even pass a test to be able

1471
01:06:00,360 --> 01:06:03,600
Speaker 2: to enter into the most basic citizenship guidelines. No, sorry,

1472
01:06:03,800 --> 01:06:05,480
Speaker 2: you have to speak English to be able to come here.

1473
01:06:05,600 --> 01:06:07,440
Speaker 2: I don't think that's racist. You could call it that

1474
01:06:07,760 --> 01:06:09,240
Speaker 2: if you want it. And that's part of the issue,

1475
01:06:09,280 --> 01:06:12,440
Speaker 2: is that everything that gets described as racist, or even

1476
01:06:12,480 --> 01:06:15,080
Speaker 2: talking about ethnic conflict or you you know, everyone. I

1477
01:06:15,120 --> 01:06:16,760
Speaker 2: don't think it's racist to say that there were a

1478
01:06:16,800 --> 01:06:19,080
Speaker 2: lot of people here who were huge drunks, A lot

1479
01:06:19,120 --> 01:06:22,000
Speaker 2: of them were immigrants. In the nineteen tens, we passed

1480
01:06:22,000 --> 01:06:25,440
Speaker 2: prohibition because of them, because America was so fed up

1481
01:06:25,440 --> 01:06:27,640
Speaker 2: and including women who were all getting the crap beaten

1482
01:06:27,640 --> 01:06:29,560
Speaker 2: out of them. You can whitewash that if you want,

1483
01:06:29,800 --> 01:06:32,040
Speaker 2: go listen to the people at the time who pass

1484
01:06:32,120 --> 01:06:35,760
Speaker 2: those laws, Like you have to think and consider about

1485
01:06:35,800 --> 01:06:38,000
Speaker 2: what is legitimate and not and so I don't think

1486
01:06:38,000 --> 01:06:39,440
Speaker 2: it's necessarily racist.

1487
01:06:39,480 --> 01:06:41,240
Speaker 3: Now some people are racist, that's not true.

1488
01:06:41,400 --> 01:06:46,440
Speaker 1: I again the points about what should the level of

1489
01:06:46,480 --> 01:06:50,520
Speaker 1: immigration be over what period of time. I think it

1490
01:06:50,560 --> 01:06:54,080
Speaker 1: should be a lot more. You think it should be zero, Okay, by.

1491
01:06:54,000 --> 01:06:55,960
Speaker 3: The way, I think we should show the public it's not.

1492
01:06:55,920 --> 01:07:00,400
Speaker 1: A warrior position. But again I think people hold on.

1493
01:07:01,120 --> 01:07:04,240
Speaker 1: I think those points are a fine debate for a

1494
01:07:04,280 --> 01:07:06,400
Speaker 1: country to have. I do not think it is a

1495
01:07:06,440 --> 01:07:10,480
Speaker 1: fine debate to rain down a to invite a campaign

1496
01:07:10,520 --> 01:07:14,400
Speaker 1: of terror against a small town based on yes, racist

1497
01:07:15,000 --> 01:07:17,320
Speaker 1: neo Nazi fueled. By the way, these are the people

1498
01:07:17,320 --> 01:07:21,800
Speaker 1: that originally were spreading the rumors was patients eating pets.

1499
01:07:22,760 --> 01:07:27,520
Speaker 1: That is racist, okay, And that's my point. That's my

1500
01:07:27,640 --> 01:07:32,120
Speaker 1: point is that when Trump, if Trump was making a

1501
01:07:32,200 --> 01:07:34,600
Speaker 1: kay and Republicans were making a case as they were

1502
01:07:34,640 --> 01:07:38,200
Speaker 1: previously about like too many and chaos at the border

1503
01:07:38,240 --> 01:07:41,720
Speaker 1: and crime which by the again undocumented immigrants commune less

1504
01:07:41,760 --> 01:07:44,240
Speaker 1: crime than the native born population, and actually less crime

1505
01:07:44,240 --> 01:07:44,920
Speaker 1: than documentar armor.

1506
01:07:44,960 --> 01:07:45,720
Speaker 3: It's outside.

1507
01:07:45,960 --> 01:07:49,120
Speaker 1: But again, when you're in that realm, you're talking about housing,

1508
01:07:49,200 --> 01:07:51,360
Speaker 1: you're talking about you know, the issues in this okay,

1509
01:07:52,040 --> 01:07:58,080
Speaker 1: But when you make a naked racist appeal that is undeniable, right,

1510
01:07:58,240 --> 01:08:02,320
Speaker 1: it's not even plausible, and it's just a lie. You

1511
01:08:02,400 --> 01:08:04,240
Speaker 1: are going to lose people, and you're going to lose

1512
01:08:04,240 --> 01:08:07,040
Speaker 1: ground on the issue. And again, I don't even think

1513
01:08:07,040 --> 01:08:07,880
Speaker 1: this is my opinion.

1514
01:08:07,920 --> 01:08:08,840
Speaker 4: This is what the.

1515
01:08:09,200 --> 01:08:12,640
Speaker 1: Polls and the data show at this point. But you know,

1516
01:08:12,760 --> 01:08:14,520
Speaker 1: to go back to the core of the debate here,

1517
01:08:14,960 --> 01:08:18,519
Speaker 1: like this town is kind of a model example, right,

1518
01:08:18,680 --> 01:08:21,599
Speaker 1: I mean, this is an extreme situation. There's some dispute,

1519
01:08:21,600 --> 01:08:23,960
Speaker 1: by the way, about the twenty thousand figure, but we'll

1520
01:08:24,000 --> 01:08:26,559
Speaker 1: put that aside. There was a significant influx of migrants

1521
01:08:26,600 --> 01:08:28,960
Speaker 1: to the town, There's no doubt about that. There's no

1522
01:08:29,040 --> 01:08:31,800
Speaker 1: doubt that there have been I think the issues with

1523
01:08:32,040 --> 01:08:34,880
Speaker 1: you know, a lot of the Haitian immigrants there hadn't

1524
01:08:34,880 --> 01:08:38,280
Speaker 1: previously driven, and there's like you know, traffic accidents. There

1525
01:08:38,280 --> 01:08:40,920
Speaker 1: has been some increase in housing prices, although that has

1526
01:08:40,960 --> 01:08:45,439
Speaker 1: also been widely overstated. There's been an increase in burden

1527
01:08:45,520 --> 01:08:49,960
Speaker 1: on the public school in particular needing like second language learning,

1528
01:08:50,040 --> 01:08:53,320
Speaker 1: like those are real concerns. But there also has been

1529
01:08:53,520 --> 01:08:57,679
Speaker 1: a huge increase in the vitality prosperity of the area,

1530
01:08:57,840 --> 01:09:01,240
Speaker 1: huge increase in terms of the average age. Again, I've

1531
01:09:01,280 --> 01:09:03,240
Speaker 1: lived in one of these towns that's dying and the

1532
01:09:03,240 --> 01:09:06,519
Speaker 1: population is getting sucked down, and it's a huge boon

1533
01:09:06,640 --> 01:09:10,440
Speaker 1: to have new population coming in, which is something conservatives

1534
01:09:10,439 --> 01:09:13,760
Speaker 1: recognized when it's Florida that's receiving the population and it's

1535
01:09:13,800 --> 01:09:17,320
Speaker 1: white people, right or Texas receiving the population and it's

1536
01:09:17,360 --> 01:09:20,479
Speaker 1: white people. But suddenly when it's you know, Haitians, some

1537
01:09:20,520 --> 01:09:23,120
Speaker 1: of whom again have been here for years, suddenly it's

1538
01:09:23,200 --> 01:09:25,240
Speaker 1: you know, a massive crisis and a massive problem. And

1539
01:09:25,280 --> 01:09:28,960
Speaker 1: there's and there's no there's no recognition of any of

1540
01:09:29,000 --> 01:09:31,439
Speaker 1: the any of the many benefits that do exist on

1541
01:09:31,439 --> 01:09:32,000
Speaker 1: the other side.

1542
01:09:32,000 --> 01:09:34,360
Speaker 3: Because they're white. It's because they're illegally here.

1543
01:09:34,640 --> 01:09:37,000
Speaker 4: They're not the Haitians are not illegally.

1544
01:09:38,320 --> 01:09:41,280
Speaker 1: Bullsh but that's not but but that is different to

1545
01:09:41,320 --> 01:09:45,439
Speaker 1: say I object to the program. To say it's a

1546
01:09:45,479 --> 01:09:48,680
Speaker 1: program I object to is totally different from saying that

1547
01:09:48,720 --> 01:09:51,599
Speaker 1: this they're illegally here. They are not illegally here here,

1548
01:09:51,800 --> 01:09:55,320
Speaker 1: they're here legally, and it's not fos pre.

1549
01:09:55,280 --> 01:09:59,439
Speaker 2: Time because they're fleeing from a temporary situation that we

1550
01:09:59,479 --> 01:10:02,120
Speaker 2: are very much uh implicated by the way.

1551
01:10:02,000 --> 01:10:04,080
Speaker 3: And creating over doing here buddy in the world gets

1552
01:10:04,080 --> 01:10:04,280
Speaker 3: to come.

1553
01:10:04,400 --> 01:10:06,280
Speaker 4: But they're not there illegally.

1554
01:10:06,479 --> 01:10:09,000
Speaker 1: They're they're legally, they're they are in a lot of

1555
01:10:09,000 --> 01:10:11,080
Speaker 1: ways like the model minority group.

1556
01:10:11,600 --> 01:10:12,960
Speaker 4: They've got jobs, they're.

1557
01:10:12,800 --> 01:10:16,520
Speaker 1: Working hard, they're going to church, they're building community institutions.

1558
01:10:16,560 --> 01:10:19,080
Speaker 1: They followed the process that was set out for them

1559
01:10:19,120 --> 01:10:23,720
Speaker 1: by this government. They're here legally, and so no, you

1560
01:10:23,760 --> 01:10:26,519
Speaker 1: look at it, and you know, maybe you can nitpick

1561
01:10:26,560 --> 01:10:28,200
Speaker 1: abo okay, but they you know, some of them don't

1562
01:10:28,200 --> 01:10:30,680
Speaker 1: speak English or whatever. But it seems to me the

1563
01:10:30,720 --> 01:10:36,120
Speaker 1: primary difference, the primary difference in not recognizing any of

1564
01:10:36,200 --> 01:10:38,880
Speaker 1: the upsides of this population is that they're not why

1565
01:10:39,080 --> 01:10:39,479
Speaker 1: you're A're.

1566
01:10:39,439 --> 01:10:41,160
Speaker 2: Totally right, but it's not about being white. It's about

1567
01:10:41,200 --> 01:10:43,320
Speaker 2: the fact that the factory owners love cheap labor. I

1568
01:10:43,360 --> 01:10:45,000
Speaker 2: was just talking to somebody who was down there as

1569
01:10:45,040 --> 01:10:45,519
Speaker 2: a reporter.

1570
01:10:45,800 --> 01:10:47,160
Speaker 3: He's telling they're making good wages.

1571
01:10:47,280 --> 01:10:49,519
Speaker 2: Yes, they're making good wages, which is more than which

1572
01:10:49,560 --> 01:10:51,439
Speaker 2: is less than they were paying the native born citizens.

1573
01:10:51,479 --> 01:10:53,800
Speaker 3: So that's why we should factory guys like, oh, it's great,

1574
01:10:53,800 --> 01:10:55,200
Speaker 3: I don't have to deal with these white drives.

1575
01:10:55,520 --> 01:10:59,160
Speaker 1: Let me, let me, let me take you out of it.

1576
01:10:59,280 --> 01:11:03,200
Speaker 1: Because you so things like unions, but you know Jdvance

1577
01:11:03,240 --> 01:11:06,400
Speaker 1: has a zero percent scoring record with the AFLCIO.

1578
01:11:06,960 --> 01:11:08,280
Speaker 4: Trump is a union bestor.

1579
01:11:08,200 --> 01:11:10,680
Speaker 1: Like no, no, but hold on, hold on, hold on, hold on,

1580
01:11:11,040 --> 01:11:15,280
Speaker 1: but hold On a second, Republicans only care about things

1581
01:11:15,360 --> 01:11:19,200
Speaker 1: like wages and housing when they can use it as

1582
01:11:19,200 --> 01:11:21,360
Speaker 1: a way to scapegoat migrants.

1583
01:11:21,560 --> 01:11:22,519
Speaker 4: If you care about.

1584
01:11:22,360 --> 01:11:26,800
Speaker 1: Wages, which I do, then there are a lot better

1585
01:11:26,880 --> 01:11:30,400
Speaker 1: ways to increase the wages of the native born population

1586
01:11:31,000 --> 01:11:33,759
Speaker 1: than scapegoating migrants and lying and say they're eating pets.

1587
01:11:34,400 --> 01:11:35,800
Speaker 4: If you care about.

1588
01:11:36,160 --> 01:11:39,040
Speaker 1: Lowering the price of housing, make it more affordable accessible,

1589
01:11:39,439 --> 01:11:42,919
Speaker 1: there are a lot better ways than s gooting immigrants

1590
01:11:43,000 --> 01:11:45,960
Speaker 1: and saying they're eating pets. So I think their concern

1591
01:11:46,040 --> 01:11:50,000
Speaker 1: on this issue is not genuine. Again, this is not

1592
01:11:50,080 --> 01:11:52,640
Speaker 1: about you, This is about them. Their concern on this

1593
01:11:52,720 --> 01:11:55,320
Speaker 1: issue is not genuine. And the reason I know that

1594
01:11:55,680 --> 01:11:58,719
Speaker 1: is because none of their other policy prescriptions or stated

1595
01:11:58,720 --> 01:11:59,960
Speaker 1: concerns have to do.

1596
01:12:00,320 --> 01:12:01,000
Speaker 4: With those issues.

1597
01:12:01,040 --> 01:12:03,559
Speaker 3: If apply to you, then or what do you mean?

1598
01:12:03,640 --> 01:12:05,759
Speaker 2: Well, how does it flip saying well, if you support

1599
01:12:05,800 --> 01:12:08,439
Speaker 2: mass migration, but just because you vote for the pro Act,

1600
01:12:08,520 --> 01:12:10,240
Speaker 2: how can you possibly pre pro labor?

1601
01:12:10,280 --> 01:12:12,200
Speaker 3: It's just not true, of course it is no. But

1602
01:12:12,240 --> 01:12:15,880
Speaker 3: it's not because because it is a massive.

1603
01:12:15,720 --> 01:12:20,000
Speaker 1: The primary problem for workers in this country is not immigrants.

1604
01:12:20,680 --> 01:12:21,519
Speaker 4: It's not immigrants.

1605
01:12:21,560 --> 01:12:26,800
Speaker 1: I mean, in fact, immigrants, the influx and population has

1606
01:12:26,920 --> 01:12:30,679
Speaker 1: increased our GDP. Now I know that's a hold on Well,

1607
01:12:30,680 --> 01:12:33,599
Speaker 1: that's the point, and that's why I support the policies

1608
01:12:33,640 --> 01:12:37,000
Speaker 1: that I support to make sure that when the GDP increases,

1609
01:12:37,640 --> 01:12:43,479
Speaker 1: that those fruits that increased productivity is distributed more more,

1610
01:12:43,640 --> 01:12:48,160
Speaker 1: you know, generously among all working class populations. So there

1611
01:12:48,200 --> 01:12:52,160
Speaker 1: are much better solutions to housing and wages than scapegoating

1612
01:12:52,200 --> 01:12:56,200
Speaker 1: immigrants and lying and inciting like a racist hate campaign

1613
01:12:56,200 --> 01:13:00,320
Speaker 1: against this town based on a third hand Facebook account

1614
01:13:00,439 --> 01:13:01,599
Speaker 1: of someone eating a pet.

1615
01:13:01,960 --> 01:13:04,679
Speaker 3: Look in the pet thing. It is not fair. Nobody's

1616
01:13:04,720 --> 01:13:07,080
Speaker 3: defending I know you're not defending that, but I'm.

1617
01:13:06,880 --> 01:13:10,200
Speaker 2: Saying that whenever it comes to the legitimate concerns about like, oh,

1618
01:13:10,280 --> 01:13:12,880
Speaker 2: the factory are in, the mayor likes it. Listen, since

1619
01:13:12,880 --> 01:13:15,760
Speaker 2: what have we ever trusted factory own rich people in town.

1620
01:13:15,920 --> 01:13:18,080
Speaker 1: This was a democratic call, and this was a democratically

1621
01:13:18,120 --> 01:13:20,479
Speaker 1: elected mayor. Yes, they have a chance to vote him

1622
01:13:20,479 --> 01:13:23,559
Speaker 1: out of office, and they don't because the town has

1623
01:13:23,720 --> 01:13:26,519
Speaker 1: been in certain key ways, not every way, but in

1624
01:13:26,600 --> 01:13:30,320
Speaker 1: certain ways has been improved by the fact that you've

1625
01:13:30,320 --> 01:13:35,040
Speaker 1: had more jobs, more vitality. These immigrants who are there

1626
01:13:35,120 --> 01:13:38,799
Speaker 1: legally are contributing to the community, are paying their taxes

1627
01:13:38,880 --> 01:13:40,960
Speaker 1: by all accounts, are you know, buy and large minding

1628
01:13:41,000 --> 01:13:43,759
Speaker 1: their business and doing their thing and being good neighbors,

1629
01:13:44,400 --> 01:13:48,720
Speaker 1: and that piece that there's yes there. I'm not going

1630
01:13:48,760 --> 01:13:50,720
Speaker 1: to deny that there is. Like you know that there's

1631
01:13:50,760 --> 01:13:52,720
Speaker 1: friction and there's growing pains, and all of those things

1632
01:13:52,720 --> 01:13:54,920
Speaker 1: are real. I'm not dismissing that. I'm not saying that

1633
01:13:54,960 --> 01:13:57,040
Speaker 1: you're like racist if you think that that's I'm sure

1634
01:13:57,080 --> 01:14:00,280
Speaker 1: a reality. But you also can't ignore that there have

1635
01:14:00,320 --> 01:14:03,160
Speaker 1: been benefits to having this population there, just as there

1636
01:14:03,200 --> 01:14:05,160
Speaker 1: have been benefits of like you know, the white people

1637
01:14:05,160 --> 01:14:07,439
Speaker 1: that move to Austin or that moved to Florida or

1638
01:14:07,520 --> 01:14:11,320
Speaker 1: wherever that created additional vitality for those areas too.

1639
01:14:11,400 --> 01:14:11,519
Speaker 10: Well.

1640
01:14:11,520 --> 01:14:14,240
Speaker 2: The fundamental difference is those are legal US citizens and

1641
01:14:14,320 --> 01:14:17,920
Speaker 2: these people are not. Now, maybe these hates are there legally, well, okay,

1642
01:14:18,080 --> 01:14:20,200
Speaker 2: well we'll see, you know what, when we legally are

1643
01:14:20,200 --> 01:14:22,439
Speaker 2: required to send them back, I hope that we also do.

1644
01:14:22,760 --> 01:14:28,600
Speaker 2: But second to this is the simple question around managed

1645
01:14:28,720 --> 01:14:33,400
Speaker 2: change manage demographics. They came here on an unregulated system

1646
01:14:33,439 --> 01:14:35,800
Speaker 2: where anybody in the world who shows up at the

1647
01:14:35,840 --> 01:14:38,639
Speaker 2: southern border and says, I fear for my life, gets

1648
01:14:38,640 --> 01:14:41,000
Speaker 2: to stay here for years on end. It gets a

1649
01:14:41,040 --> 01:14:44,120
Speaker 2: work permit because the Biden administration that releases them into

1650
01:14:44,160 --> 01:14:46,519
Speaker 2: the country. Trump did it too, so he's not off.

1651
01:14:46,600 --> 01:14:48,960
Speaker 2: So did George W. Bush and the rest.

1652
01:14:49,080 --> 01:14:51,640
Speaker 3: I think that's wrong, especially.

1653
01:14:51,160 --> 01:14:54,439
Speaker 2: Whenever most people who aren't so conveniently at the southern

1654
01:14:54,479 --> 01:14:57,120
Speaker 2: border have to apply and pay a lot of fees,

1655
01:14:57,760 --> 01:15:00,760
Speaker 2: you know, to legally take a freaking English and you

1656
01:15:00,800 --> 01:15:02,599
Speaker 2: know some other guy from Guatemala g has to come

1657
01:15:02,640 --> 01:15:04,559
Speaker 2: here and he doesn't have to take anything is to

1658
01:15:04,600 --> 01:15:07,320
Speaker 2: work illegally on the back end. But this is the

1659
01:15:07,360 --> 01:15:10,080
Speaker 2: big question. Now, as I said, if Trump wins, I

1660
01:15:10,120 --> 01:15:12,080
Speaker 2: think it will be because of this. I think enough

1661
01:15:12,120 --> 01:15:14,320
Speaker 2: people will look past that. You may call it racist,

1662
01:15:14,320 --> 01:15:15,040
Speaker 2: but they'll say.

1663
01:15:15,000 --> 01:15:17,240
Speaker 4: Look, wait, no, wait, do you not think it's racist?

1664
01:15:17,600 --> 01:15:18,639
Speaker 1: The pets thing.

1665
01:15:19,160 --> 01:15:22,280
Speaker 2: I mean, like listener, okay, when we say races, like

1666
01:15:22,320 --> 01:15:25,680
Speaker 2: what does that mean? Like, look, well, I mean this

1667
01:15:25,840 --> 01:15:28,040
Speaker 2: is the issue. This is uncomfortable territory.

1668
01:15:28,240 --> 01:15:30,360
Speaker 4: But it's not uncomfortable. It's very clear.

1669
01:15:30,439 --> 01:15:32,479
Speaker 2: Well, as Mary and Williamson said, what are we going

1670
01:15:32,520 --> 01:15:35,519
Speaker 2: to ignore that there are like weird practices sometimes in

1671
01:15:35,520 --> 01:15:36,520
Speaker 2: the Haitian community.

1672
01:15:36,600 --> 01:15:37,559
Speaker 3: Like, I'm not saying the.

1673
01:15:37,640 --> 01:15:40,080
Speaker 4: Majority share the religion of JD.

1674
01:15:40,200 --> 01:15:43,360
Speaker 2: Vanson our which are yeah, okay, but there's Santaia, which

1675
01:15:43,400 --> 01:15:46,200
Speaker 2: is a well documented thing and has had a long

1676
01:15:46,240 --> 01:15:48,080
Speaker 2: time in the Caribbean community.

1677
01:15:48,280 --> 01:15:54,240
Speaker 1: Take a third hand lie and smear an entire community

1678
01:15:54,280 --> 01:15:54,559
Speaker 1: with it.

1679
01:15:54,560 --> 01:15:57,800
Speaker 4: That is the definition of racism.

1680
01:15:58,439 --> 01:16:00,639
Speaker 3: I mean, listen, calling the.

1681
01:16:00,560 --> 01:16:03,280
Speaker 1: Definition of racism and how it does not apply to

1682
01:16:03,280 --> 01:16:03,559
Speaker 1: the same.

1683
01:16:03,560 --> 01:16:07,080
Speaker 2: The definition of racism is explicitly being biased against someone

1684
01:16:07,160 --> 01:16:10,720
Speaker 2: purely because of their race. And I don't necessarily think

1685
01:16:10,760 --> 01:16:12,439
Speaker 2: that that's where we're at here now do I think

1686
01:16:12,479 --> 01:16:13,959
Speaker 2: that we are in a situation?

1687
01:16:14,360 --> 01:16:16,240
Speaker 3: I mean, look, was it biased? Is it?

1688
01:16:17,280 --> 01:16:18,840
Speaker 2: I'm trying to think of the ways and look, people

1689
01:16:18,880 --> 01:16:21,240
Speaker 2: would say, always twisting themselves in the knots. It's just

1690
01:16:21,280 --> 01:16:23,800
Speaker 2: because my barrier for like what I call racist is high,

1691
01:16:23,800 --> 01:16:25,479
Speaker 2: because I think it's a very misused word.

1692
01:16:25,520 --> 01:16:26,719
Speaker 3: In franklyship are stupid.

1693
01:16:26,760 --> 01:16:29,080
Speaker 1: But sometimes you got to call a spade a spade.

1694
01:16:29,120 --> 01:16:31,200
Speaker 2: I mean, and when you look as they're black, I

1695
01:16:31,200 --> 01:16:32,719
Speaker 2: have a problem with them. Yeah, I'd be like, yeah,

1696
01:16:32,760 --> 01:16:35,000
Speaker 2: that's racist. But you know, just when you oh, there's

1697
01:16:35,040 --> 01:16:37,599
Speaker 2: an issue here in the Haitian community specific, when you.

1698
01:16:37,560 --> 01:16:40,840
Speaker 1: Take an issue and you smear an entire community with

1699
01:16:40,880 --> 01:16:42,479
Speaker 1: it and which was not even true.

1700
01:16:42,520 --> 01:16:44,040
Speaker 3: It was just a lie. Yes, it is not true.

1701
01:16:44,640 --> 01:16:48,320
Speaker 1: I mean that's like textbook racism. And yeah, the term

1702
01:16:48,360 --> 01:16:52,959
Speaker 1: gets turnized you, but sometimes it applies, and it applies

1703
01:16:53,200 --> 01:16:56,320
Speaker 1: pretty clearly here. So, you know, to wrap up, and

1704
01:16:56,400 --> 01:16:58,320
Speaker 1: perhaps since we are going to talk to that about

1705
01:16:58,320 --> 01:16:59,519
Speaker 1: this as well, and we got to get onto the

1706
01:16:59,520 --> 01:17:00,760
Speaker 1: rest of this show and we're going to have more

1707
01:17:00,760 --> 01:17:04,040
Speaker 1: conversations about immigration, et cetera, which I know you all

1708
01:17:04,320 --> 01:17:07,679
Speaker 1: appreciate and I enjoy exchanging with you on this as well.

1709
01:17:07,960 --> 01:17:11,599
Speaker 1: But to wrap it up, the reason that I think

1710
01:17:12,200 --> 01:17:18,439
Speaker 1: this is a clear political fail, the whole PET thing

1711
01:17:19,040 --> 01:17:22,400
Speaker 1: is a clear political fail for Trump is I just

1712
01:17:22,439 --> 01:17:25,559
Speaker 1: don't think that Americans are this racist. I just don't.

1713
01:17:25,840 --> 01:17:28,600
Speaker 1: I think that they see it this as disgusting. I

1714
01:17:28,640 --> 01:17:31,439
Speaker 1: think we have the polling that shows they know that

1715
01:17:31,479 --> 01:17:33,479
Speaker 1: it's not true. They know that it's a lie. People

1716
01:17:33,520 --> 01:17:37,360
Speaker 1: don't like being lied to either, And so you know,

1717
01:17:37,439 --> 01:17:41,519
Speaker 1: whatever valid concerns there are about immigration, su're fine, you're

1718
01:17:41,520 --> 01:17:44,920
Speaker 1: actually undercutting your position on that by front loading with

1719
01:17:45,160 --> 01:17:49,920
Speaker 1: just like this explicitly racist nazi back to line.

1720
01:17:49,920 --> 01:17:52,160
Speaker 2: Without taking your words, I will say I think it's

1721
01:17:52,200 --> 01:17:56,400
Speaker 2: a mistake to generally wager whole reputation on this whole

1722
01:17:56,680 --> 01:17:58,439
Speaker 2: Haitian thing. I'd much rather have a lot of the

1723
01:17:58,960 --> 01:18:01,960
Speaker 2: talk that I just gave around demographics and management and

1724
01:18:02,320 --> 01:18:04,200
Speaker 2: all of that. But you know, at the same time, listen,

1725
01:18:04,280 --> 01:18:06,320
Speaker 2: I mean, they're the ones who got themselves elected.

1726
01:18:06,439 --> 01:18:08,080
Speaker 3: Maybe they know something that I don't.

1727
01:18:08,160 --> 01:18:11,240
Speaker 2: I'm not pollyannaish to believe that everybody thinks about these

1728
01:18:11,280 --> 01:18:12,800
Speaker 2: things the way that I do, or that you know,

1729
01:18:12,800 --> 01:18:15,280
Speaker 2: the so called better angels. I think a lot of

1730
01:18:15,280 --> 01:18:17,800
Speaker 2: that is fake, to be honest, and so we'll find

1731
01:18:17,840 --> 01:18:20,000
Speaker 2: out on the ballot box. And if they win, I

1732
01:18:20,200 --> 01:18:21,920
Speaker 2: actually do think some of a lot of it is

1733
01:18:22,160 --> 01:18:24,680
Speaker 2: basically all of it will come back to immigration. And

1734
01:18:24,760 --> 01:18:26,719
Speaker 2: if that's true, then I think liberal shoud ask themselves

1735
01:18:26,720 --> 01:18:28,400
Speaker 2: a lot of quite now if they lose too, we

1736
01:18:28,439 --> 01:18:30,400
Speaker 2: should also talk a lot about too, about the way

1737
01:18:30,400 --> 01:18:32,320
Speaker 2: that we when you can be on a winning side

1738
01:18:32,320 --> 01:18:33,880
Speaker 2: of an issue and how you screw that up. And

1739
01:18:33,960 --> 01:18:36,400
Speaker 2: there's probably a lot of evidence here if they lose

1740
01:18:36,400 --> 01:18:38,800
Speaker 2: the election on this, and I would hope that they

1741
01:18:38,800 --> 01:18:41,519
Speaker 2: take that away. If they do lose, but knowing them,

1742
01:18:41,720 --> 01:18:42,800
Speaker 2: that's certainly.

1743
01:18:42,439 --> 01:18:43,599
Speaker 1: Not not on the table.

1744
01:18:46,240 --> 01:18:48,599
Speaker 2: At the same time, there has been a new war

1745
01:18:48,680 --> 01:18:50,880
Speaker 2: declared by Donald Trump. Let's put this up there on

1746
01:18:50,920 --> 01:18:55,360
Speaker 2: the screen, he declares yesterday, quote I hate Taylor Swift

1747
01:18:55,400 --> 01:18:59,080
Speaker 2: all caps. They're on through social It is unclear currently

1748
01:18:59,160 --> 01:19:03,120
Speaker 2: what exactly did this. His initial reaction to the Taylor

1749
01:19:03,160 --> 01:19:05,920
Speaker 2: Swift endorsement of Kamala Harris after the debate was that

1750
01:19:05,960 --> 01:19:09,679
Speaker 2: he likes Britney Mahomes much better. That is, Patrick Mahomes's wife,

1751
01:19:09,720 --> 01:19:11,640
Speaker 2: who had appeared. I don't know if she's posted pro

1752
01:19:11,680 --> 01:19:12,400
Speaker 2: Trump content on the.

1753
01:19:12,400 --> 01:19:14,439
Speaker 1: Shit, liked something on Instagram, maybe.

1754
01:19:14,280 --> 01:19:18,000
Speaker 2: Because people are so fridiculous, it's common anyway, So Brittany

1755
01:19:18,040 --> 01:19:20,000
Speaker 2: Mahomes likes some pro Trump stuff, and Trump says, I'm

1756
01:19:20,000 --> 01:19:21,959
Speaker 2: actually more of a fan of Brittany Mahomes.

1757
01:19:21,960 --> 01:19:23,519
Speaker 3: Okay, well, let's put.

1758
01:19:23,360 --> 01:19:26,160
Speaker 2: This up there on the screen. The Democrats responded to this,

1759
01:19:26,600 --> 01:19:30,479
Speaker 2: also bringing in some tailor. This is incredible because this

1760
01:19:30,520 --> 01:19:32,599
Speaker 2: is real, by the way, it says, Donald Trump's week

1761
01:19:32,640 --> 01:19:35,200
Speaker 2: of whining and spouting conspiracy theories has voters on both

1762
01:19:35,240 --> 01:19:38,000
Speaker 2: sides of the aisle ready to forget that he existed

1763
01:19:38,080 --> 01:19:41,400
Speaker 2: all caps. The American people want out of the woods

1764
01:19:41,439 --> 01:19:44,000
Speaker 2: of the chaos and division of Trump Era, leave behind

1765
01:19:44,040 --> 01:19:47,519
Speaker 2: the blank space of Trump's broken promises, and begin again

1766
01:19:47,600 --> 01:19:51,360
Speaker 2: by electing Vice President Harris to ensure America's future opportunity

1767
01:19:51,479 --> 01:19:55,000
Speaker 2: is long lived. Voters know all too well how dangerous

1768
01:19:55,000 --> 01:19:57,200
Speaker 2: Trump and his Project twenty twenty five agenda will be

1769
01:19:57,280 --> 01:19:59,880
Speaker 2: if he wins this November. We can make sure this

1770
01:20:00,000 --> 01:20:01,760
Speaker 2: this is the last time we have to deal with

1771
01:20:01,800 --> 01:20:05,360
Speaker 2: this endgame of jacking up taxes all the middle class, ripping.

1772
01:20:05,160 --> 01:20:06,160
Speaker 3: Away American freedoms.

1773
01:20:06,280 --> 01:20:08,680
Speaker 2: Together, we can turn the page on Trump Era and

1774
01:20:08,680 --> 01:20:12,320
Speaker 2: write a new chapter where all Americans breathe easy, knowing

1775
01:20:12,320 --> 01:20:15,000
Speaker 2: we strong leadership of the Helm. We can make sure

1776
01:20:15,120 --> 01:20:17,760
Speaker 2: the story of us is one of progress and show

1777
01:20:17,800 --> 01:20:20,320
Speaker 2: Donald Trump we are not going back to December of

1778
01:20:20,360 --> 01:20:23,519
Speaker 2: twenty twenty like ever so PEP For those who didn't

1779
01:20:23,520 --> 01:20:26,840
Speaker 2: get there were a lot of tail Swift references.

1780
01:20:26,640 --> 01:20:27,639
Speaker 3: Inside of that one.

1781
01:20:27,840 --> 01:20:29,320
Speaker 2: You only have to be a weirdo like me to

1782
01:20:29,439 --> 01:20:33,600
Speaker 2: understand every single one in terms of what this endorsement

1783
01:20:33,600 --> 01:20:36,840
Speaker 2: actually means. Very likely he could be reacting to this.

1784
01:20:36,960 --> 01:20:39,000
Speaker 2: Let's put it up there on the screen. There has

1785
01:20:39,080 --> 01:20:43,120
Speaker 2: now been some four to five hundred percent increase in

1786
01:20:43,280 --> 01:20:47,240
Speaker 2: voter registration. Now keep in mind this also happened after

1787
01:20:47,400 --> 01:20:52,200
Speaker 2: the debate, so we can't singularly link it to Taylor Swift.

1788
01:20:52,240 --> 01:20:55,240
Speaker 2: We do know that in the twenty four hours after

1789
01:20:55,280 --> 01:20:58,320
Speaker 2: she posted a link in her Instagram story, some half

1790
01:20:58,320 --> 01:21:00,920
Speaker 2: a million people did visit vote dot gov. We don't

1791
01:21:00,960 --> 01:21:04,360
Speaker 2: know the exact number of people, but exactly four hundred

1792
01:21:04,360 --> 01:21:07,360
Speaker 2: and five thousand of those people were referred directly from

1793
01:21:07,400 --> 01:21:11,040
Speaker 2: the Swift Instagram page quote. Such a number dwarfs the

1794
01:21:11,080 --> 01:21:15,439
Speaker 2: website's usual traffic, which averages only some thirty thousand visitors

1795
01:21:15,479 --> 01:21:18,360
Speaker 2: per day according to Target Smart. It has led to

1796
01:21:18,400 --> 01:21:22,440
Speaker 2: that increase in voter registration somewhere between nine to ten thousand.

1797
01:21:22,120 --> 01:21:23,719
Speaker 3: People per hour.

1798
01:21:23,960 --> 01:21:29,559
Speaker 2: Crystal signing up so declaring Warren Taylor Swift probably the

1799
01:21:29,560 --> 01:21:32,240
Speaker 2: most beloved pop star in the United States, possibly the

1800
01:21:32,240 --> 01:21:37,280
Speaker 2: world most popular figure, specifically amongst women, the demographic that

1801
01:21:37,320 --> 01:21:40,439
Speaker 2: Trump is suffering the most with not a smart strategy.

1802
01:21:40,800 --> 01:21:42,080
Speaker 3: I guess I could just put it that way.

1803
01:21:42,680 --> 01:21:44,000
Speaker 1: No forty chests on this one.

1804
01:21:43,960 --> 01:21:45,439
Speaker 3: Oh, there's no. I mean, I don't think it's forty

1805
01:21:45,479 --> 01:21:46,559
Speaker 3: chess on any of this stuff. I think a lot

1806
01:21:46,600 --> 01:21:47,240
Speaker 3: of it is stupid.

1807
01:21:47,479 --> 01:21:49,360
Speaker 4: It's like gut reaction.

1808
01:21:49,800 --> 01:21:51,320
Speaker 2: Yeah, it's like, Oh, she doesn't like me, so I

1809
01:21:51,360 --> 01:21:53,280
Speaker 2: don't like her. I'm like, Okay, let's see how it

1810
01:21:53,280 --> 01:21:53,720
Speaker 2: works out.

1811
01:21:53,880 --> 01:21:54,200
Speaker 3: Listen.

1812
01:21:54,240 --> 01:21:56,439
Speaker 2: I could be totally wrong, you know, but even other

1813
01:21:56,520 --> 01:21:59,519
Speaker 2: Republicans are like, hey, this is a really bad idea.

1814
01:21:59,600 --> 01:22:02,640
Speaker 2: There's no reason. Luckily, you know Taylor herself. She's not

1815
01:22:02,720 --> 01:22:04,679
Speaker 2: trying to get too political. If you read her post,

1816
01:22:04,720 --> 01:22:07,000
Speaker 2: she's like, do your own research, vote for wherever you want.

1817
01:22:07,320 --> 01:22:11,080
Speaker 2: But I'm supporting Kamla. It's unlikely that she'll do anything.

1818
01:22:11,160 --> 01:22:13,599
Speaker 2: Maybe Travis Kelcey or any of that will get involved.

1819
01:22:13,600 --> 01:22:15,880
Speaker 2: But I guess the real point and why it's dumb,

1820
01:22:16,240 --> 01:22:19,200
Speaker 2: is just it's the ultimate tabloid headline. This is the

1821
01:22:19,280 --> 01:22:22,200
Speaker 2: type of thing that actually penetrates. It's like this in

1822
01:22:22,320 --> 01:22:25,200
Speaker 2: parts right. This is the type of thing on TikTok

1823
01:22:25,320 --> 01:22:28,720
Speaker 2: on Instagram. You're checking out at the grocery store and

1824
01:22:28,760 --> 01:22:31,120
Speaker 2: you look at the magazine thing you'sed like Trump declares,

1825
01:22:31,280 --> 01:22:33,880
Speaker 2: I hate it's so clippable, it's so soundbiteish.

1826
01:22:34,240 --> 01:22:36,040
Speaker 3: And that's part of the reason I think it's stupid.

1827
01:22:36,080 --> 01:22:38,680
Speaker 2: It feeds into what is he doing this time, like, oh,

1828
01:22:38,720 --> 01:22:41,080
Speaker 2: he said, what you know, because it's not Mika Persinski

1829
01:22:41,120 --> 01:22:41,760
Speaker 2: we're talking about here.

1830
01:22:41,800 --> 01:22:42,519
Speaker 3: This is Taylor Swift.

1831
01:22:42,560 --> 01:22:44,679
Speaker 2: This is the most popular lady in the United States. Yeah,

1832
01:22:44,720 --> 01:22:47,280
Speaker 2: this is the last vestige of the monoculture that we

1833
01:22:47,360 --> 01:22:50,280
Speaker 2: have here. So yeah, why, well you know why. But

1834
01:22:50,400 --> 01:22:52,640
Speaker 2: I mean the reason is because it's Trump. This is

1835
01:22:52,640 --> 01:22:53,080
Speaker 2: what he does.

1836
01:22:53,160 --> 01:22:55,240
Speaker 1: I mean, my hot take about the Taylor endorsement was

1837
01:22:55,240 --> 01:22:57,080
Speaker 1: that it probably won't matter. And my hot take about

1838
01:22:57,120 --> 01:22:58,960
Speaker 1: Trump saying I hate Taylor Swift is that it probably

1839
01:22:58,960 --> 01:23:00,719
Speaker 1: won't matter. But that's the and make it a smart

1840
01:23:00,720 --> 01:23:04,000
Speaker 1: idea because there's certainly a possibility that it could matter

1841
01:23:04,160 --> 01:23:06,320
Speaker 1: on the margins. And the other thing is, I don't

1842
01:23:06,320 --> 01:23:07,880
Speaker 1: know if you guys we mentioned on the show, but

1843
01:23:07,880 --> 01:23:09,160
Speaker 1: I don't know if you guys saw this. There was

1844
01:23:09,200 --> 01:23:12,960
Speaker 1: this whole a while back, like fake AI generated campaign

1845
01:23:13,000 --> 01:23:16,960
Speaker 1: to pretend like Taylor Swift had endorsed Trump, and of

1846
01:23:17,000 --> 01:23:19,960
Speaker 1: course she hadn't, and she never intended to endorse Trump,

1847
01:23:19,960 --> 01:23:20,799
Speaker 1: et cetera, et cetera.

1848
01:23:21,240 --> 01:23:23,440
Speaker 4: And if she ever had a thought.

1849
01:23:23,200 --> 01:23:25,320
Speaker 1: Of staying out of this race, which she's not a

1850
01:23:25,400 --> 01:23:28,080
Speaker 1: particularly political person, she has weigh in before she has

1851
01:23:28,160 --> 01:23:31,479
Speaker 1: endorsed Democrats before. But you know, if she ever had

1852
01:23:31,479 --> 01:23:34,360
Speaker 1: a thought about staying out of this race, that door

1853
01:23:34,479 --> 01:23:37,879
Speaker 1: was really closed for her by that fake Trump campaign.

1854
01:23:37,920 --> 01:23:39,720
Speaker 1: Because then you just feel like like I got to

1855
01:23:39,760 --> 01:23:41,840
Speaker 1: set the record street, you know, I have to come

1856
01:23:41,880 --> 01:23:44,160
Speaker 1: out and say something because of And then I think

1857
01:23:44,240 --> 01:23:46,880
Speaker 1: the whole childless cat Lady's thing also apparently got under

1858
01:23:46,880 --> 01:23:47,680
Speaker 1: her skin based on.

1859
01:23:47,640 --> 01:23:48,360
Speaker 4: The way that she freezed.

1860
01:23:48,400 --> 01:23:50,400
Speaker 3: She does love cat her endorsement, she.

1861
01:23:50,439 --> 01:23:53,280
Speaker 1: Is a childless cat lady, so she she felt personally

1862
01:23:53,360 --> 01:23:55,639
Speaker 1: attacked and made a point of that in her endorsement,

1863
01:23:55,960 --> 01:23:57,479
Speaker 1: you know, with the pose with the cat and signing

1864
01:23:57,520 --> 01:24:02,080
Speaker 1: a childless cat lady whatever. So if I were to

1865
01:24:02,120 --> 01:24:05,120
Speaker 1: make an argument that this matters, it would be that,

1866
01:24:05,240 --> 01:24:08,400
Speaker 1: as you were saying, Sager, she hasn't like overly inserted

1867
01:24:08,439 --> 01:24:11,280
Speaker 1: herself into the race. But if he's out there tweeting

1868
01:24:11,320 --> 01:24:14,840
Speaker 1: provocations and being aggressive. You know, I hate Taylor Swift

1869
01:24:14,880 --> 01:24:16,800
Speaker 1: and he can if he continues to go in on that,

1870
01:24:17,240 --> 01:24:21,120
Speaker 1: then maybe that forces her to be more engaged. Maybe

1871
01:24:21,120 --> 01:24:23,879
Speaker 1: that pushes her to be you know, more overtly political,

1872
01:24:23,920 --> 01:24:26,160
Speaker 1: to cut some ads, to appear at some rallies.

1873
01:24:26,400 --> 01:24:26,839
Speaker 4: Whatever.

1874
01:24:28,040 --> 01:24:30,519
Speaker 1: The other thing that just not that we could ever

1875
01:24:30,520 --> 01:24:33,479
Speaker 1: get into Trump's psyche, but he definitely did like Taylor

1876
01:24:33,520 --> 01:24:35,760
Speaker 1: Swift previously the way he talked about her. There's a

1877
01:24:35,760 --> 01:24:38,960
Speaker 1: famous video two of him driving car with Baron in

1878
01:24:39,040 --> 01:24:41,920
Speaker 1: passenger seat listening to blank Space, So we know he

1879
01:24:42,000 --> 01:24:45,679
Speaker 1: has enjoyed her music in the past, and he got

1880
01:24:45,720 --> 01:24:49,920
Speaker 1: asked about her kind of recently before the endorsement, and

1881
01:24:50,120 --> 01:24:52,040
Speaker 1: this is what he had to say about how he

1882
01:24:52,040 --> 01:24:53,080
Speaker 1: felt about Taylor Swift.

1883
01:24:53,080 --> 01:24:56,760
Speaker 11: Then what do you think about Taylor Swift was one

1884
01:24:56,760 --> 01:24:58,080
Speaker 11: of the most famous people right now.

1885
01:24:58,600 --> 01:25:01,760
Speaker 8: Yeah, I think she's beautiful, very beautiful. I find her

1886
01:25:01,880 --> 01:25:07,000
Speaker 8: very beautiful. I think she's liberal. She probably doesn't like Trump,

1887
01:25:08,160 --> 01:25:12,240
Speaker 8: but I hear she's very talented, but I think she's

1888
01:25:12,400 --> 01:25:16,400
Speaker 8: very I think she's very beautiful actually.

1889
01:25:17,040 --> 01:25:19,640
Speaker 4: Unusually unusually beautiful.

1890
01:25:19,840 --> 01:25:21,639
Speaker 3: So yeah, I mean usually he has the sense.

1891
01:25:21,800 --> 01:25:24,519
Speaker 2: So he never attacked Oprah, right, he never attacked because

1892
01:25:24,520 --> 01:25:27,360
Speaker 2: he always respected one of the only people he ever feared,

1893
01:25:27,400 --> 01:25:28,799
Speaker 2: reportedly Michelle Obama.

1894
01:25:28,840 --> 01:25:31,559
Speaker 3: Taylor. You know that's the similar one where it's.

1895
01:25:31,400 --> 01:25:32,479
Speaker 1: Like the tabloid part of him.

1896
01:25:32,479 --> 01:25:34,799
Speaker 4: He respect celebrity, respect, celebrity power.

1897
01:25:34,960 --> 01:25:38,280
Speaker 2: Know, you know how popular some people are and you know,

1898
01:25:38,439 --> 01:25:40,880
Speaker 2: then in terms of there's one thing to say it

1899
01:25:40,880 --> 01:25:42,960
Speaker 2: doesn't matter, which I think actually fine, you could say

1900
01:25:43,000 --> 01:25:45,640
Speaker 2: that's a legitimate opinion. It's just another to be like

1901
01:25:45,680 --> 01:25:49,280
Speaker 2: I hate Taylor Swift and it's like for what possible reason.

1902
01:25:49,080 --> 01:25:52,960
Speaker 1: And I think it makes you look like kind of childish, Yeah,

1903
01:25:53,080 --> 01:25:54,240
Speaker 1: childish exactly.

1904
01:25:54,280 --> 01:25:56,160
Speaker 3: It gets centered around what me.

1905
01:25:56,439 --> 01:25:58,400
Speaker 2: I actually think one of the most potent democratic attacks

1906
01:25:58,479 --> 01:26:01,040
Speaker 2: is he cares about himself and about Yeah, that's what

1907
01:26:01,160 --> 01:26:04,000
Speaker 2: it all feeds into. And just yeah, everybody mag out

1908
01:26:04,000 --> 01:26:06,360
Speaker 2: there's like there's a strategy behind I'm like, no, there's not, Guys,

1909
01:26:06,400 --> 01:26:09,040
Speaker 2: there's not. You know, just how can you still say that?

1910
01:26:09,080 --> 01:26:11,759
Speaker 2: You know, after all this time, there's no forty chess.

1911
01:26:11,960 --> 01:26:15,280
Speaker 2: He's just capriciously saw something, decided to tweet it and

1912
01:26:15,320 --> 01:26:17,519
Speaker 2: there's no thought or anything behind it.

1913
01:26:17,600 --> 01:26:19,599
Speaker 3: Now will it matter it will be the end result?

1914
01:26:19,760 --> 01:26:21,479
Speaker 3: Probably not. But it's just like, why it's not a

1915
01:26:21,520 --> 01:26:21,960
Speaker 3: smart play?

1916
01:26:22,040 --> 01:26:24,080
Speaker 1: Definitely not helpful. Yeah, there you go for sure, it's

1917
01:26:24,120 --> 01:26:27,240
Speaker 1: not helpful. Is it like, you know, super damaging? Who knows,

1918
01:26:27,320 --> 01:26:30,879
Speaker 1: but definitely not like a really savvy strategy here exactly?

1919
01:26:33,520 --> 01:26:37,400
Speaker 1: All right, to continue the pets conversation, We're happy to

1920
01:26:37,439 --> 01:26:39,120
Speaker 1: be joined this morning by a great friend of the show,

1921
01:26:39,280 --> 01:26:42,000
Speaker 1: Zed Jalani. You guys all need to go and subscribe

1922
01:26:42,120 --> 01:26:43,360
Speaker 1: to Zed's newsletter.

1923
01:26:43,400 --> 01:26:45,160
Speaker 4: What is it called the American Saga? Is that the

1924
01:26:45,240 --> 01:26:45,680
Speaker 4: name of it?

1925
01:26:46,400 --> 01:26:46,639
Speaker 12: Yeah?

1926
01:26:46,680 --> 01:26:49,400
Speaker 11: Exactly, I have the you were out just the Americansaga

1927
01:26:49,479 --> 01:26:51,480
Speaker 11: dot com so on substick amazing.

1928
01:26:51,800 --> 01:26:55,160
Speaker 1: Everybody should definitely check that out. So Zed and I

1929
01:26:55,200 --> 01:26:58,360
Speaker 1: were able to provoke the ire of value presdential candidate

1930
01:26:58,439 --> 01:27:00,320
Speaker 1: Jade Vance. We'll get to that in a moment, but

1931
01:27:00,720 --> 01:27:04,040
Speaker 1: center Vance was on the Sunday shows making his case

1932
01:27:04,680 --> 01:27:08,920
Speaker 1: for sort of acknowledging that the Haitian pets lie was

1933
01:27:09,200 --> 01:27:12,960
Speaker 1: maybe not true, but also giving quite a noteworthy explanation

1934
01:27:13,080 --> 01:27:15,479
Speaker 1: for why he continues to lean into it. Let's listen

1935
01:27:15,520 --> 01:27:16,720
Speaker 1: to a little bit of how that went.

1936
01:27:17,040 --> 01:27:21,320
Speaker 13: My constituents had brought approximately a dozen separate concerns to me.

1937
01:27:21,840 --> 01:27:25,160
Speaker 13: Ten of them are verifiable and confirmable, and a couple

1938
01:27:25,200 --> 01:27:28,240
Speaker 13: of them I talk about because my constituents are telling

1939
01:27:28,280 --> 01:27:30,679
Speaker 13: me firsthand that they're seeing these things.

1940
01:27:30,920 --> 01:27:32,759
Speaker 10: So I have two options, Dana.

1941
01:27:33,000 --> 01:27:35,280
Speaker 13: I could ignore them, which is what the American media

1942
01:27:35,280 --> 01:27:38,200
Speaker 13: has done for years to this community, or I can

1943
01:27:38,240 --> 01:27:40,880
Speaker 13: actually talk about what people are telling me. And of

1944
01:27:40,920 --> 01:27:43,439
Speaker 13: course many of the things that the media says are

1945
01:27:43,479 --> 01:27:46,720
Speaker 13: completely baseless have since been confirmed.

1946
01:27:46,960 --> 01:27:48,840
Speaker 10: For example, I was told.

1947
01:27:48,640 --> 01:27:51,439
Speaker 13: Dana that the American by the American media that it

1948
01:27:51,479 --> 01:27:55,040
Speaker 13: was baseless that migrants were capturing the geese from the

1949
01:27:55,080 --> 01:27:57,280
Speaker 13: local park pond and eating them.

1950
01:27:57,479 --> 01:27:59,080
Speaker 10: And yet there are nine to one to one.

1951
01:27:58,880 --> 01:28:01,639
Speaker 13: Calls from well before or this ever became a viral

1952
01:28:01,720 --> 01:28:05,879
Speaker 13: sensation of people complaining about that exact thing happening.

1953
01:28:06,160 --> 01:28:08,719
Speaker 14: First of all, the Clark County Sheriff and the Ohio

1954
01:28:08,800 --> 01:28:12,160
Speaker 14: Department of Natural Resources reviewed eleven months of nine to

1955
01:28:12,160 --> 01:28:15,920
Speaker 14: one one calls. They only identified two instances of people

1956
01:28:16,000 --> 01:28:20,160
Speaker 14: alleging patians were taking geese out of park's. They found

1957
01:28:20,360 --> 01:28:25,479
Speaker 14: zero evidence to substantiate those claims. But you're not just

1958
01:28:25,560 --> 01:28:29,880
Speaker 14: a bystander. You're the senator from Ohio. So instead of

1959
01:28:30,280 --> 01:28:33,760
Speaker 14: saying things that are wrong and actually causing the hospitals,

1960
01:28:33,760 --> 01:28:37,160
Speaker 14: the schools, the government buildings to be evacuated because of

1961
01:28:37,240 --> 01:28:40,800
Speaker 14: bomb threats, because of the cats and dogs thing.

1962
01:28:41,160 --> 01:28:43,160
Speaker 13: But I want to start with something he said which

1963
01:28:43,160 --> 01:28:45,800
Speaker 13: I think is frankly disgusting and is more appropriate for

1964
01:28:45,840 --> 01:28:49,240
Speaker 13: a democratic propagandist than it is for an American journalist.

1965
01:28:49,479 --> 01:28:52,240
Speaker 13: There is nothing that I have said that has led

1966
01:28:52,280 --> 01:28:56,280
Speaker 13: to threats against these hospitals. These hospitals, the bomb threats

1967
01:28:56,320 --> 01:29:00,280
Speaker 13: and so forth. It's disgusting. The violence is disgusting. We

1968
01:29:00,360 --> 01:29:00,960
Speaker 13: condemn it.

1969
01:29:01,120 --> 01:29:03,920
Speaker 14: We condemn all violence under this happened after you and

1970
01:29:04,120 --> 01:29:06,840
Speaker 14: President the debate stage.

1971
01:29:09,520 --> 01:29:12,360
Speaker 10: You asked a question, go ahead and answer it.

1972
01:29:12,640 --> 01:29:13,120
Speaker 3: After that.

1973
01:29:13,800 --> 01:29:18,479
Speaker 15: What if I have to create stories so that the

1974
01:29:18,520 --> 01:29:21,640
Speaker 15: American media actually pays attention to the suffering of the

1975
01:29:21,680 --> 01:29:24,040
Speaker 15: American people, then that's what I'm going to do.

1976
01:29:24,160 --> 01:29:24,320
Speaker 7: Dan.

1977
01:29:24,800 --> 01:29:27,639
Speaker 1: If I have to create stories, he says, to get

1978
01:29:27,640 --> 01:29:29,599
Speaker 1: people to pay attention to this, then that's what I'm

1979
01:29:29,600 --> 01:29:32,280
Speaker 1: going to do. It seems like a pretty extraordinary enssionment.

1980
01:29:31,920 --> 01:29:32,200
Speaker 12: To the Z.

1981
01:29:34,120 --> 01:29:36,760
Speaker 11: Yeah, and I think if you watch the rest of

1982
01:29:36,800 --> 01:29:39,760
Speaker 11: the clip and what he's talking about. Basically he substantiates

1983
01:29:39,840 --> 01:29:42,760
Speaker 11: that by saying that he has had constituents call in

1984
01:29:42,880 --> 01:29:45,400
Speaker 11: saying they've heard rumors about other people's pets, you know,

1985
01:29:45,439 --> 01:29:47,240
Speaker 11: being taken, so on and so forth. So you know,

1986
01:29:48,000 --> 01:29:50,680
Speaker 11: we would use those calls to create the story to

1987
01:29:50,760 --> 01:29:53,559
Speaker 11: draw attention to this legitimate issue. I mean the problem

1988
01:29:53,640 --> 01:29:56,360
Speaker 11: with that is, you know, you're a us centator. Right,

1989
01:29:56,360 --> 01:29:59,880
Speaker 11: You're not someone trolling Facebook for rumors. You're not, you know,

1990
01:30:00,120 --> 01:30:03,960
Speaker 11: taking information that doesn't hasn't been substantiated by anyone, whether

1991
01:30:04,000 --> 01:30:05,880
Speaker 11: it be a reporter, whether it be police or local

1992
01:30:05,880 --> 01:30:09,120
Speaker 11: officials or even local NGO. You know, you have to

1993
01:30:09,120 --> 01:30:11,519
Speaker 11: be responsible with how you respond to those things. Right,

1994
01:30:11,560 --> 01:30:14,000
Speaker 11: And the reality is not one person in that town

1995
01:30:14,479 --> 01:30:17,519
Speaker 11: I stepped forward and said my dog or my cat

1996
01:30:17,640 --> 01:30:21,759
Speaker 11: was eaten by somebody, by a Haitian person or anyone

1997
01:30:21,760 --> 01:30:23,880
Speaker 11: else for that matter, because then you would end up

1998
01:30:23,880 --> 01:30:26,080
Speaker 11: filing a police report, they would be a press story

1999
01:30:26,120 --> 01:30:28,320
Speaker 11: about it, and they would catch whoever was responsible. They

2000
01:30:28,320 --> 01:30:30,080
Speaker 11: would have rent make an arrest, so on and so forth.

2001
01:30:30,800 --> 01:30:33,200
Speaker 11: The way that these urban legends spread through communities is

2002
01:30:33,280 --> 01:30:36,439
Speaker 11: usually that somebody says, oh, my neighbor lost their cat.

2003
01:30:36,520 --> 01:30:38,360
Speaker 11: Could have been a coyote, but could have also been

2004
01:30:38,400 --> 01:30:40,559
Speaker 11: an immigrant, and someone posted on Facebook, and people say, oh,

2005
01:30:40,760 --> 01:30:43,280
Speaker 11: the Haitians are eating cats. I've heard that. Oh you've

2006
01:30:43,280 --> 01:30:45,720
Speaker 11: heard that. We've all heard that over the weekend. I

2007
01:30:45,760 --> 01:30:49,120
Speaker 11: heard that. Forty years ago in the Atlanta area where

2008
01:30:49,120 --> 01:30:51,839
Speaker 11: I live, when Koreans are moving in, there were rumors

2009
01:30:51,880 --> 01:30:55,360
Speaker 11: about cats disappearing right, because in Korea, you know, dogs

2010
01:30:55,560 --> 01:30:57,400
Speaker 11: in the Far East is probably the only place in

2011
01:30:57,400 --> 01:31:00,320
Speaker 11: the world where there is some common accepted practice meeting

2012
01:31:00,360 --> 01:31:02,800
Speaker 11: cats and dogs, even though it's not that common among

2013
01:31:02,840 --> 01:31:05,000
Speaker 11: the people, and it's kind of falling out of fashion

2014
01:31:05,040 --> 01:31:07,480
Speaker 11: for a lot of people. And it's actually almost impossible

2015
01:31:07,479 --> 01:31:10,080
Speaker 11: to find a creative American or Chinese American who would

2016
01:31:10,120 --> 01:31:12,280
Speaker 11: do that here in the United States. But that's how

2017
01:31:12,280 --> 01:31:15,680
Speaker 11: these rumors spread and start, right, And I think you know,

2018
01:31:15,840 --> 01:31:19,679
Speaker 11: if Vans and Trump want to know how politically salient

2019
01:31:19,720 --> 01:31:21,800
Speaker 11: it is that they're doing this. You GOV did a

2020
01:31:21,840 --> 01:31:24,320
Speaker 11: poll where they found only nine percent of Americans think

2021
01:31:24,360 --> 01:31:25,280
Speaker 11: it's definitely true.

2022
01:31:25,320 --> 01:31:27,080
Speaker 12: Right, So for the first time, the.

2023
01:31:27,080 --> 01:31:29,960
Speaker 11: Republicans are kind of losing an immigration debate in the

2024
01:31:29,960 --> 01:31:31,840
Speaker 11: past three years. Right, So was that really the best

2025
01:31:31,840 --> 01:31:34,240
Speaker 11: move in the world to rely on Facebook rumors?

2026
01:31:34,240 --> 01:31:34,439
Speaker 1: Here?

2027
01:31:34,560 --> 01:31:37,160
Speaker 2: Well, Zed, you got tangled a little bit with the

2028
01:31:37,240 --> 01:31:40,240
Speaker 2: vice presidential candidate B two B. Please guys, let's put

2029
01:31:40,240 --> 01:31:43,120
Speaker 2: it up there on the screen. Zed, you tweeted this

2030
01:31:43,200 --> 01:31:46,280
Speaker 2: springfield was declining for years until they saw on increasing

2031
01:31:46,360 --> 01:31:48,920
Speaker 2: jobs and growth driven by people moving in that means

2032
01:31:48,960 --> 01:31:51,920
Speaker 2: more wealth, healthier budgets. Are there no upsized immigration in

2033
01:31:51,960 --> 01:31:53,960
Speaker 2: your view, what about Usha's parents? Would they have stayed

2034
01:31:54,000 --> 01:31:57,080
Speaker 2: in India? JD replies to you, dude, I've always liked you,

2035
01:31:57,120 --> 01:31:58,839
Speaker 2: so maybe they should be a longer conversation.

2036
01:31:58,920 --> 01:31:59,880
Speaker 3: But come on, are there no oup?

2037
01:32:00,000 --> 01:32:02,920
Speaker 2: Sized immigration is a radically different question from should we

2038
01:32:02,960 --> 01:32:05,720
Speaker 2: drop twenty thousand people from a radically different culture in

2039
01:32:05,760 --> 01:32:08,640
Speaker 2: a small Ohio town in a matter of years? He

2040
01:32:08,720 --> 01:32:12,759
Speaker 2: goes on significantly, But consider if he were here today,

2041
01:32:12,960 --> 01:32:14,440
Speaker 2: what would you say to him?

2042
01:32:15,439 --> 01:32:18,960
Speaker 11: Well, look, I actually relate a lot to JD in

2043
01:32:19,320 --> 01:32:22,559
Speaker 11: some ways, right, We have a similar life story in

2044
01:32:22,560 --> 01:32:23,360
Speaker 11: a few different ways.

2045
01:32:23,400 --> 01:32:24,000
Speaker 12: I mean, for.

2046
01:32:24,040 --> 01:32:27,320
Speaker 11: One, I think that some of what he's voicing is

2047
01:32:27,360 --> 01:32:29,560
Speaker 11: probably his actual view, right. I Mean, they're all politicians,

2048
01:32:29,600 --> 01:32:31,920
Speaker 11: they're all trying to win an electoral race. But I

2049
01:32:31,960 --> 01:32:35,400
Speaker 11: think that his life's trajectory kind of suggests that maybe

2050
01:32:35,439 --> 01:32:38,120
Speaker 11: he really seems to believe what he's saying. He's someone

2051
01:32:38,160 --> 01:32:40,800
Speaker 11: who grew up in a town where I think his

2052
01:32:41,000 --> 01:32:43,760
Speaker 11: parents and particularly his grandparents were from a culture or

2053
01:32:43,840 --> 01:32:46,800
Speaker 11: subculture that he saw was dying. I think when he

2054
01:32:46,840 --> 01:32:49,519
Speaker 11: wrote his memoir He'll Billy Elegy, he analyzed that in

2055
01:32:49,560 --> 01:32:51,000
Speaker 11: sort of a personal way, right, he was kind of

2056
01:32:51,080 --> 01:32:53,960
Speaker 11: letting out his trauma or his childhood experiences. He kind

2057
01:32:53,960 --> 01:32:56,800
Speaker 11: of blamed the people around him, He blamed kind of

2058
01:32:56,800 --> 01:32:59,800
Speaker 11: cultural tendencies, so on and so forth. Once he got

2059
01:32:59,800 --> 01:33:01,720
Speaker 11: that out of his system, I think over the next

2060
01:33:01,720 --> 01:33:03,120
Speaker 11: few years after that, he started to look at it

2061
01:33:03,160 --> 01:33:05,479
Speaker 11: in a more sociological way, right, he said, well, why

2062
01:33:05,520 --> 01:33:07,760
Speaker 11: were these people engaged in these counter productive you know,

2063
01:33:07,800 --> 01:33:10,679
Speaker 11: habits and cultures. Maybe you know, there's these larger problems

2064
01:33:10,680 --> 01:33:14,080
Speaker 11: with globalization, with job flight, with the easy access to

2065
01:33:14,120 --> 01:33:17,719
Speaker 11: drugs and counter productive materials. And I think he started

2066
01:33:17,720 --> 01:33:19,439
Speaker 11: to make more of a political analysis about it, where

2067
01:33:19,439 --> 01:33:22,040
Speaker 11: he sees himself as representing those people. And part of

2068
01:33:22,080 --> 01:33:23,760
Speaker 11: what he did is, you know, he moved back from

2069
01:33:23,800 --> 01:33:25,679
Speaker 11: the Bay Area. He had gone to a law school,

2070
01:33:25,840 --> 01:33:28,599
Speaker 11: made money out out on the West Coast. He moved

2071
01:33:28,600 --> 01:33:30,840
Speaker 11: back to Ohio, and he tried to say, I need

2072
01:33:30,880 --> 01:33:32,559
Speaker 11: to represent those people. I need to be a voice

2073
01:33:32,560 --> 01:33:35,360
Speaker 11: for them. And look, I mean, I it's not That's

2074
01:33:35,439 --> 01:33:36,400
Speaker 11: the similar a story for.

2075
01:33:36,479 --> 01:33:37,120
Speaker 12: Me in many ways.

2076
01:33:37,120 --> 01:33:39,000
Speaker 11: You know, I was born and raised outside of Atlanta

2077
01:33:39,120 --> 01:33:41,120
Speaker 11: and went to DC for a long time, and eventually

2078
01:33:41,160 --> 01:33:43,000
Speaker 11: I fought the colin to come home and so I

2079
01:33:43,040 --> 01:33:44,720
Speaker 11: came back here, you know, a couple of years ago,

2080
01:33:45,560 --> 01:33:47,639
Speaker 11: and you know a lot of people I grew up

2081
01:33:47,680 --> 01:33:51,320
Speaker 11: around were white folks and a little bit poorer and

2082
01:33:51,479 --> 01:33:54,200
Speaker 11: working class places like Mapleton where I was born, and

2083
01:33:54,320 --> 01:33:56,400
Speaker 11: you know a lot of them flew their rebel flag, right.

2084
01:33:56,439 --> 01:33:58,360
Speaker 11: But also my parents were immigrants, so you know, I

2085
01:33:58,400 --> 01:34:01,680
Speaker 11: knew Indians and Nigerians and Mexicans and people from all

2086
01:34:01,760 --> 01:34:04,720
Speaker 11: kinds of backgrounds growing up. And you know, you could

2087
01:34:04,760 --> 01:34:08,120
Speaker 11: say those are different groups of people, but there's something

2088
01:34:08,200 --> 01:34:10,360
Speaker 11: all those groups sharing common. And I want JD to

2089
01:34:10,400 --> 01:34:12,800
Speaker 11: hear this is that people look down upon them, right.

2090
01:34:12,920 --> 01:34:15,920
Speaker 11: People say, you know, they're poor and ENERGYCID, they're backwards,

2091
01:34:15,960 --> 01:34:21,840
Speaker 11: they follow weird customs, culture traditions and religions that they're always.

2092
01:34:21,560 --> 01:34:22,400
Speaker 12: Going to be in that station.

2093
01:34:22,520 --> 01:34:24,960
Speaker 11: But everyone I knew, from from white folks flying the

2094
01:34:24,960 --> 01:34:28,519
Speaker 11: Confederate flag to African Americans to all these you know,

2095
01:34:28,560 --> 01:34:31,200
Speaker 11: migrants and immigrants who are coming into the area, you know,

2096
01:34:31,240 --> 01:34:33,080
Speaker 11: all of them were working to try to improve themselves

2097
01:34:33,120 --> 01:34:34,000
Speaker 11: and better their families.

2098
01:34:34,080 --> 01:34:34,320
Speaker 12: Right.

2099
01:34:34,360 --> 01:34:39,040
Speaker 11: And you know, I think when JD makes arguments about

2100
01:34:39,160 --> 01:34:42,200
Speaker 11: you know, housing prices or about you know, the logistical

2101
01:34:42,240 --> 01:34:44,519
Speaker 11: issues traffic, healthcare costs, on and so forth.

2102
01:34:44,680 --> 01:34:46,520
Speaker 12: Those are all fair things to say about.

2103
01:34:46,240 --> 01:34:48,599
Speaker 11: The growing pains and immigration, I mean those those happen

2104
01:34:49,120 --> 01:34:51,559
Speaker 11: in every circumstance where large numbers of people are moving in.

2105
01:34:51,560 --> 01:34:53,960
Speaker 11: It's happening in metro Atlanta and in Codd County right now,

2106
01:34:54,000 --> 01:34:55,960
Speaker 11: where I grew up. I mean, those are largely not

2107
01:34:55,960 --> 01:34:58,280
Speaker 11: even immigrants from the rest of the world. From the

2108
01:34:58,320 --> 01:35:00,559
Speaker 11: rest of the country though, and we're having issues transit,

2109
01:35:00,600 --> 01:35:03,599
Speaker 11: with traffic, with infrastructure, so on and so forth. Those

2110
01:35:03,640 --> 01:35:05,439
Speaker 11: are all fair points to make. But I think when

2111
01:35:05,479 --> 01:35:08,479
Speaker 11: he starts making it a cultural argument, you know, I

2112
01:35:08,479 --> 01:35:09,960
Speaker 11: think in some of his sweets you talked about how

2113
01:35:10,000 --> 01:35:12,200
Speaker 11: people are from a very different culture, right, and I

2114
01:35:12,280 --> 01:35:14,400
Speaker 11: think that that, you know, alays into what he's talking

2115
01:35:14,400 --> 01:35:16,920
Speaker 11: about the animals and the pets. You know, it's kind

2116
01:35:16,920 --> 01:35:19,360
Speaker 11: of suggesting that these are kind of like an alien

2117
01:35:19,360 --> 01:35:22,720
Speaker 11: group of folks, they're not compatible with us here in

2118
01:35:22,760 --> 01:35:26,040
Speaker 11: the United States, that they somehow have some kind of

2119
01:35:26,040 --> 01:35:30,080
Speaker 11: inferior or backwards attitude. And look, that's JD. That's exactly

2120
01:35:30,080 --> 01:35:32,640
Speaker 11: how people talk about your ancestors, about Scott's Irish, right, Like,

2121
01:35:32,640 --> 01:35:35,080
Speaker 11: where's the term cracker come from in the US context,

2122
01:35:35,080 --> 01:35:38,679
Speaker 11: you know, it was a term used to derogate poor

2123
01:35:38,720 --> 01:35:42,080
Speaker 11: people Scott's Irish, largely in the South, who were seen

2124
01:35:42,240 --> 01:35:45,800
Speaker 11: as just following alien customs. They were ill temper, they're

2125
01:35:45,840 --> 01:35:49,240
Speaker 11: quick to fight with each other, they were very backwards,

2126
01:35:49,920 --> 01:35:51,920
Speaker 11: and they could never make any things of themselves.

2127
01:35:52,000 --> 01:35:54,040
Speaker 12: Of course, you know that's wrong, JD. Because you're you're

2128
01:35:54,040 --> 01:35:54,639
Speaker 12: a US citor.

2129
01:35:54,720 --> 01:35:56,840
Speaker 11: Now, you went to a law school, but when you

2130
01:35:56,840 --> 01:35:58,599
Speaker 11: were growing up, I'm sure plenty of people look down

2131
01:35:58,680 --> 01:36:01,280
Speaker 11: upon you and they said that you're just you know,

2132
01:36:01,320 --> 01:36:04,559
Speaker 11: your your white trash, you're backwards, your family's all messed up.

2133
01:36:04,560 --> 01:36:06,519
Speaker 11: They could list a million different ways of things that

2134
01:36:06,560 --> 01:36:08,800
Speaker 11: they that were wrong. But you knew that you were

2135
01:36:08,880 --> 01:36:10,800
Speaker 11: you were worth more than that, right, And I think

2136
01:36:10,840 --> 01:36:12,559
Speaker 11: that's that's a lot of what I would say about

2137
01:36:12,560 --> 01:36:15,439
Speaker 11: these people. They're you know, you can't judge them. I

2138
01:36:15,479 --> 01:36:18,559
Speaker 11: think in in this way that kind of makes them

2139
01:36:18,560 --> 01:36:20,439
Speaker 11: in this category where they're never going to make anything

2140
01:36:20,439 --> 01:36:23,599
Speaker 11: of themselves. Because the reality is loc Haitians have been

2141
01:36:23,600 --> 01:36:26,000
Speaker 11: in the US and large numbers since probably the nineteen sixties.

2142
01:36:26,000 --> 01:36:29,080
Speaker 11: There's like half a million Haitian Americans in Florida right

2143
01:36:29,120 --> 01:36:30,960
Speaker 11: when I don't think Florida Republicans are going to be

2144
01:36:31,040 --> 01:36:34,640
Speaker 11: quick to demonize those people because it would be politically toxic.

2145
01:36:34,320 --> 01:36:35,000
Speaker 12: For them to do so.

2146
01:36:35,680 --> 01:36:36,960
Speaker 11: And I don't think it's going to be any different

2147
01:36:37,000 --> 01:36:38,280
Speaker 11: from these people moving into Springfield.

2148
01:36:38,360 --> 01:36:41,759
Speaker 12: Right. Springfield was losing population for a number of years.

2149
01:36:41,800 --> 01:36:41,960
Speaker 3: Right.

2150
01:36:42,080 --> 01:36:44,320
Speaker 11: You know, I went to grad school up in Syracuse.

2151
01:36:44,360 --> 01:36:47,240
Speaker 11: I was there for twelve months to my masters. Syracuse

2152
01:36:47,280 --> 01:36:48,960
Speaker 11: and a lot of those upstate New York towns, all

2153
01:36:49,000 --> 01:36:52,080
Speaker 11: those rost belt towns, de industrialized towns, weren't a debt

2154
01:36:52,160 --> 01:36:55,519
Speaker 11: spiral because people moving out meant that you had not

2155
01:36:55,560 --> 01:36:58,080
Speaker 11: only fewer jobs, but you also had fewer you had

2156
01:36:58,160 --> 01:37:01,320
Speaker 11: less tax revenue, right, meaning they and fund services, meaning

2157
01:37:01,360 --> 01:37:04,160
Speaker 11: that they couldn't keep a lot of the city going

2158
01:37:04,400 --> 01:37:05,519
Speaker 11: as people continue to move out.

2159
01:37:05,560 --> 01:37:06,000
Speaker 12: So they were.

2160
01:37:05,880 --> 01:37:07,559
Speaker 11: Constantly trying to get people to move in, and that's

2161
01:37:07,560 --> 01:37:10,759
Speaker 11: what Springfield did. Around twenty fourteen, they started a campaign

2162
01:37:10,760 --> 01:37:13,120
Speaker 11: and said, hey, people need to move here, along with

2163
01:37:13,160 --> 01:37:14,920
Speaker 11: a bunch of other towns in Ohio, by the way,

2164
01:37:15,040 --> 01:37:17,360
Speaker 11: and they found some success by having people from the

2165
01:37:17,360 --> 01:37:20,280
Speaker 11: rest of the country, people from other countries, start moving

2166
01:37:20,320 --> 01:37:24,439
Speaker 11: into Springfield, start taking jobs, start working, providing you know, revenue,

2167
01:37:24,479 --> 01:37:27,280
Speaker 11: economic growth. I mean, look, it's true that a lot

2168
01:37:27,320 --> 01:37:30,680
Speaker 11: of big employers and big business want immigrants to come

2169
01:37:30,680 --> 01:37:33,400
Speaker 11: to the country to loosen the labor market, sometimes the

2170
01:37:33,400 --> 01:37:35,479
Speaker 11: lower wages, to give them more of an affordable deal.

2171
01:37:35,720 --> 01:37:38,639
Speaker 11: But that doesn't really mean that in every circumstance possible,

2172
01:37:39,280 --> 01:37:41,760
Speaker 11: you know, immigrants are bad for your community or bad

2173
01:37:41,800 --> 01:37:44,200
Speaker 11: for your country. Right in a place that's dying, that

2174
01:37:44,280 --> 01:37:46,559
Speaker 11: needs people to come back, it needs people to come

2175
01:37:46,560 --> 01:37:50,280
Speaker 11: from anywhere to come there and develop and start actually,

2176
01:37:50,400 --> 01:37:53,360
Speaker 11: you know, not only bring new jobs, but also tax revenue,

2177
01:37:53,400 --> 01:37:55,479
Speaker 11: new construction, housing, and so on and so forth. It's

2178
01:37:55,520 --> 01:37:57,280
Speaker 11: not really a bad thing to have people moving there

2179
01:37:57,560 --> 01:38:00,960
Speaker 11: and actually rejuvenate the place. Of course, there'll be growing

2180
01:38:00,960 --> 01:38:03,439
Speaker 11: pains and doing that, but a sure way to respond

2181
01:38:03,479 --> 01:38:05,280
Speaker 11: to that would be to go to that community, understand

2182
01:38:05,320 --> 01:38:07,840
Speaker 11: their needs and talk it out rationally, right, rather than

2183
01:38:07,840 --> 01:38:10,680
Speaker 11: turning it into a giant political circus that has, unfortunately

2184
01:38:10,800 --> 01:38:12,000
Speaker 11: now these racial overtones.

2185
01:38:12,160 --> 01:38:16,520
Speaker 1: Yeah, Zad, your response was very compelling and also very diplomatic.

2186
01:38:16,880 --> 01:38:18,800
Speaker 1: Mine was a little less though I had put it

2187
01:38:18,920 --> 01:38:22,960
Speaker 1: up on the screen. What Jad said to you kind

2188
01:38:22,960 --> 01:38:27,360
Speaker 1: of irritated me because now that he's provoked this whole

2189
01:38:27,880 --> 01:38:31,040
Speaker 1: out rageous racial panic. He wants to say, Oh, let's

2190
01:38:31,040 --> 01:38:33,680
Speaker 1: have a nuanced conversation about housing, Which is my point here.

2191
01:38:33,680 --> 01:38:36,160
Speaker 1: I said, when you insist on spreading neo Nazi fueled

2192
01:38:36,160 --> 01:38:40,400
Speaker 1: smears about immigrants, which these pet cat dog lies were

2193
01:38:40,439 --> 01:38:44,240
Speaker 1: fueled by literal neo Nazis leading to bomb threats, kind

2194
01:38:44,240 --> 01:38:47,000
Speaker 1: of closes the space for this intellectual discussion about pluses

2195
01:38:47,000 --> 01:38:50,360
Speaker 1: and minuses of immigration that you're now retreating to. Dude,

2196
01:38:50,439 --> 01:38:52,400
Speaker 1: he didn't like that very much, she says, Crystal Ball,

2197
01:38:52,439 --> 01:38:55,160
Speaker 1: I really hate neoliberalism. I'm a populist. Also, Crystal Ball,

2198
01:38:55,200 --> 01:38:58,200
Speaker 1: anyone who doesn't think twenty thousand cheap laborers should be

2199
01:38:58,280 --> 01:39:01,120
Speaker 1: dropped on a small Ohio town is a neo Nazi,

2200
01:39:01,160 --> 01:39:03,240
Speaker 1: which is not what I said. But in any case,

2201
01:39:03,280 --> 01:39:05,719
Speaker 1: I would also say someone who has a zero percent

2202
01:39:05,840 --> 01:39:08,839
Speaker 1: voting record with the AFLCIO and who owes his position

2203
01:39:09,040 --> 01:39:12,400
Speaker 1: in significant part to a billionaire backer maybe doesn't really

2204
01:39:12,439 --> 01:39:14,040
Speaker 1: have a lot of like to stand on with regard

2205
01:39:14,120 --> 01:39:17,400
Speaker 1: to populism. But putting that aside, z, I'll bring you

2206
01:39:17,439 --> 01:39:20,559
Speaker 1: in for the diplomatic response here. You know, when you

2207
01:39:20,720 --> 01:39:25,799
Speaker 1: lead with the very racial angle, that's just about culture

2208
01:39:26,479 --> 01:39:30,679
Speaker 1: and is also just a total lie and not about

2209
01:39:30,720 --> 01:39:35,320
Speaker 1: any of these more legitimate topics of conversation. I don't

2210
01:39:35,320 --> 01:39:40,360
Speaker 1: think that helps enable that broader, more nuanced, potential theoretical

2211
01:39:40,400 --> 01:39:44,599
Speaker 1: conversation that he now wants to have after initially starting

2212
01:39:44,600 --> 01:39:45,200
Speaker 1: this panic.

2213
01:39:46,520 --> 01:39:48,120
Speaker 12: Yeah, I mean, I think that's exactly right.

2214
01:39:48,160 --> 01:39:51,400
Speaker 11: Like, look, if someone was trying to talk about, you know, Israeli.

2215
01:39:51,479 --> 01:39:53,320
Speaker 11: This is a topic that's been all over the news

2216
01:39:53,360 --> 01:39:56,439
Speaker 11: the past almost a year now, and they started with

2217
01:39:56,439 --> 01:39:59,160
Speaker 11: an anti Semitic conspiracy theory, right, they can't really fall

2218
01:39:59,200 --> 01:40:00,880
Speaker 11: back and say, wow, look, I just want to have

2219
01:40:00,920 --> 01:40:02,400
Speaker 11: a conversation about foreign policy.

2220
01:40:02,479 --> 01:40:03,040
Speaker 1: That's a great point.

2221
01:40:03,080 --> 01:40:04,800
Speaker 11: You know, you need you need to be careful about

2222
01:40:04,800 --> 01:40:06,160
Speaker 11: how you engage in these things. And I think this

2223
01:40:06,240 --> 01:40:08,320
Speaker 11: is something that Republicans are learning because, like I said,

2224
01:40:08,360 --> 01:40:11,439
Speaker 11: this is probably the first time and during the Biden

2225
01:40:11,439 --> 01:40:14,120
Speaker 11: administration that they're really losing an immigration debate where they

2226
01:40:14,160 --> 01:40:17,639
Speaker 11: said something that people just don't believe that make them look,

2227
01:40:18,320 --> 01:40:20,160
Speaker 11: you know, like they're trying to start some kind of

2228
01:40:20,200 --> 01:40:22,920
Speaker 11: racial or cultural conflict rather than deal with the very

2229
01:40:22,920 --> 01:40:25,680
Speaker 11: real challenges of I think, you know, increasing levels of

2230
01:40:25,680 --> 01:40:28,360
Speaker 11: immigration and at the same time you know, I want

2231
01:40:28,360 --> 01:40:32,160
Speaker 11: to say something about you know, he questioned your your posture.

2232
01:40:31,800 --> 01:40:32,560
Speaker 12: As a populist.

2233
01:40:32,960 --> 01:40:35,400
Speaker 11: But the reality is that the history of populism in

2234
01:40:35,439 --> 01:40:38,040
Speaker 11: the United States and some cent elsewhere, but I know

2235
01:40:38,040 --> 01:40:42,400
Speaker 11: more about the United States, is that when we develop

2236
01:40:42,439 --> 01:40:45,880
Speaker 11: these kind of US versus them frames, you know, immigration

2237
01:40:46,000 --> 01:40:48,040
Speaker 11: and race and culture does get drawn into that at times.

2238
01:40:48,120 --> 01:40:50,320
Speaker 12: Right, So, like I'm reading this book about Tom Watson.

2239
01:40:50,920 --> 01:40:54,040
Speaker 11: Tom Watson was this great you know, Georgia populist right,

2240
01:40:54,520 --> 01:40:57,759
Speaker 11: and the first half of his life he was fighting

2241
01:40:57,760 --> 01:41:00,599
Speaker 11: against convict leasing, which was like ninety percent blas in Georgia,

2242
01:41:00,600 --> 01:41:03,280
Speaker 11: which is like slavery by another name, you know, used

2243
01:41:03,280 --> 01:41:05,839
Speaker 11: by many of the richest and wealthiest politicians in Georgia

2244
01:41:05,880 --> 01:41:08,720
Speaker 11: to undercut wages and also just to expose prisoners to

2245
01:41:08,760 --> 01:41:11,160
Speaker 11: brutal conditions I mean, far worse than prison labor today.

2246
01:41:11,200 --> 01:41:12,719
Speaker 12: I mean, it basically was slavery.

2247
01:41:13,400 --> 01:41:15,840
Speaker 11: But in the second half of his life he became

2248
01:41:15,880 --> 01:41:18,479
Speaker 11: basically an outright white nationalist right and you know, he

2249
01:41:18,600 --> 01:41:20,439
Speaker 11: was against African Americans and so.

2250
01:41:20,320 --> 01:41:20,800
Speaker 12: On and so forth.

2251
01:41:20,840 --> 01:41:22,400
Speaker 11: I mean, this is a guy who went from organizing

2252
01:41:22,439 --> 01:41:26,000
Speaker 11: bands of men to protect blacks from lynching to advocating

2253
01:41:26,000 --> 01:41:27,559
Speaker 11: for those various same things in the second half of

2254
01:41:27,560 --> 01:41:29,760
Speaker 11: his life, and like that was all part of the

2255
01:41:29,800 --> 01:41:34,759
Speaker 11: populist tradition in Georgia. Right, you could mobilize people against

2256
01:41:34,800 --> 01:41:37,360
Speaker 11: the landed gentry and like the big farms and being

2257
01:41:37,360 --> 01:41:39,840
Speaker 11: a very populist, but also you could say, hey, we

2258
01:41:39,920 --> 01:41:43,040
Speaker 11: have a white interest against black folks, against Jews, Catholics,

2259
01:41:43,120 --> 01:41:45,080
Speaker 11: on and so forth. And I think you know, Vance

2260
01:41:45,200 --> 01:41:48,439
Speaker 11: needs to consider that trajectory for his own life, Right,

2261
01:41:48,880 --> 01:41:50,840
Speaker 11: does he want to fall into that kind of dark

2262
01:41:50,880 --> 01:41:51,840
Speaker 11: side of populism?

2263
01:41:51,880 --> 01:41:53,639
Speaker 12: Does he want to be someone I.

2264
01:41:53,560 --> 01:41:56,160
Speaker 11: Mean questioning I legal immigration, talking about border security. All

2265
01:41:56,200 --> 01:41:58,000
Speaker 11: those things are valid, and that's always going to be

2266
01:41:58,040 --> 01:42:00,000
Speaker 11: a case. It's always been the case in American policy.

2267
01:42:00,240 --> 01:42:03,240
Speaker 11: Those things are hot by topics. Republican Party in particular

2268
01:42:03,280 --> 01:42:06,360
Speaker 11: has always been very active and talking about them. But

2269
01:42:06,920 --> 01:42:10,439
Speaker 11: when it comes to actually suggesting that, you know, this

2270
01:42:10,600 --> 01:42:12,760
Speaker 11: latest wave of immigrants whoever coming to the United States,

2271
01:42:12,800 --> 01:42:14,200
Speaker 11: in the case of the Haitians, they are legal, they

2272
01:42:14,200 --> 01:42:17,160
Speaker 11: have legal status and their TPS, you know that they're

2273
01:42:17,240 --> 01:42:20,879
Speaker 11: somehow incompatible with our values, with our culture. At that point,

2274
01:42:21,000 --> 01:42:23,320
Speaker 11: you're kind of chopping up people who are just trying to.

2275
01:42:23,240 --> 01:42:25,240
Speaker 12: Work and get by and pitting them against each other.

2276
01:42:25,320 --> 01:42:28,240
Speaker 11: Right, And you know, you want to talk about big

2277
01:42:28,280 --> 01:42:30,439
Speaker 11: employers and what they do to undercut wages and why

2278
01:42:30,439 --> 01:42:33,840
Speaker 11: they advocate for a looser immigration. That's all fair and good,

2279
01:42:34,479 --> 01:42:36,960
Speaker 11: but once we start, you know, having a conflict between

2280
01:42:37,000 --> 01:42:41,080
Speaker 11: people from varying ethnicities and ancestries and cultures. I mean, look,

2281
01:42:41,760 --> 01:42:43,920
Speaker 11: one of Donald Trump's worst moments on the debate stage

2282
01:42:43,920 --> 01:42:45,240
Speaker 11: is when he stood up there and said he didn't

2283
01:42:45,280 --> 01:42:46,640
Speaker 11: have a health care plan. He had a concept of

2284
01:42:46,640 --> 01:42:49,040
Speaker 11: a health care plan. Somewhere in this country right now,

2285
01:42:49,080 --> 01:42:50,920
Speaker 11: a husband and wife are talking about how they can't

2286
01:42:50,920 --> 01:42:54,000
Speaker 11: afford you know, life saving procedure or how they're facing

2287
01:42:54,040 --> 01:42:56,559
Speaker 11: bankruptcy and tiers are streaming down their face. I mean,

2288
01:42:56,640 --> 01:42:58,400
Speaker 11: jad spend a little bit of time talking to your

2289
01:42:58,400 --> 01:43:00,599
Speaker 11: boss about how he's going to address that problem. I mean,

2290
01:43:00,600 --> 01:43:03,400
Speaker 11: there's so many problems you can address in this country

2291
01:43:03,439 --> 01:43:06,120
Speaker 11: without hitting you know, the latest poor guy who have

2292
01:43:06,240 --> 01:43:07,800
Speaker 11: arrived on our shores is just trying to make a

2293
01:43:07,800 --> 01:43:09,519
Speaker 11: business for himself and a life for himself and a

2294
01:43:09,560 --> 01:43:13,280
Speaker 11: family in Ohio right against another person who's also trying

2295
01:43:13,280 --> 01:43:14,920
Speaker 11: to do that, right, And that's that happens to be

2296
01:43:14,920 --> 01:43:15,840
Speaker 11: the case in Springfield.

2297
01:43:15,920 --> 01:43:17,519
Speaker 2: So that let me push you a little bit, and

2298
01:43:17,600 --> 01:43:19,960
Speaker 2: let's think about this. Donald Trump passed the Tax Cuts

2299
01:43:20,000 --> 01:43:24,080
Speaker 2: and Jobs Act. He abandoned a lot of the so

2300
01:43:24,160 --> 01:43:28,400
Speaker 2: called like economic policy that he ran on if he

2301
01:43:28,560 --> 01:43:30,679
Speaker 2: ever believed it in the first place, and he got

2302
01:43:30,720 --> 01:43:33,160
Speaker 2: ten million more votes. And in fact, if you look

2303
01:43:33,200 --> 01:43:35,639
Speaker 2: at a lot of the political science research on immigration

2304
01:43:35,720 --> 01:43:37,680
Speaker 2: and others, some of the people who vote for him

2305
01:43:37,720 --> 01:43:41,920
Speaker 2: on immigration don't care about the economic concern. So maybe

2306
01:43:42,000 --> 01:43:43,799
Speaker 2: in an era I mean crystalizer that have a massive

2307
01:43:43,800 --> 01:43:46,960
Speaker 2: debate on this, maybe in an era of rapid demographic change,

2308
01:43:47,000 --> 01:43:50,080
Speaker 2: the cultural argument is actually the one that resonates.

2309
01:43:49,760 --> 01:43:50,840
Speaker 3: The most with people.

2310
01:43:51,120 --> 01:43:53,600
Speaker 2: So, I mean, you may think it's immoral, or you

2311
01:43:53,600 --> 01:43:57,200
Speaker 2: may think it's wrong, but what is your confidence that

2312
01:43:57,280 --> 01:43:59,440
Speaker 2: it is the political loser that you believe.

2313
01:43:59,160 --> 01:43:59,439
Speaker 3: It to be.

2314
01:44:00,640 --> 01:44:03,439
Speaker 11: Look, I think it probably depends on where and when

2315
01:44:03,439 --> 01:44:06,960
Speaker 11: you're talking about, particularly in Europe. I think that there

2316
01:44:07,000 --> 01:44:08,720
Speaker 11: is a represent and actually I'm going to write a

2317
01:44:08,760 --> 01:44:09,360
Speaker 11: story about that.

2318
01:44:09,360 --> 01:44:10,200
Speaker 12: There was a good paper on it.

2319
01:44:10,240 --> 01:44:12,880
Speaker 11: There is a representation gap between public officials and the

2320
01:44:12,920 --> 01:44:15,320
Speaker 11: general public. The general public does think immigration is happening

2321
01:44:15,320 --> 01:44:18,240
Speaker 11: too quickly. The base of changes is too rapid, and

2322
01:44:18,560 --> 01:44:21,200
Speaker 11: they tend to I think most of their backlashes about culture.

2323
01:44:21,360 --> 01:44:23,920
Speaker 11: Eric Kaufman, who's a kind of a political scientist, a

2324
01:44:23,920 --> 01:44:26,040
Speaker 11: little bit conservative leading, but very fair and honest, has

2325
01:44:26,080 --> 01:44:28,559
Speaker 11: said that in the survey work, that's what they find.

2326
01:44:28,600 --> 01:44:30,880
Speaker 11: It's not really about economic it's not about logistics. It's

2327
01:44:30,880 --> 01:44:34,280
Speaker 11: about culture. People think their culture is being replaced under attack,

2328
01:44:34,320 --> 01:44:36,200
Speaker 11: and that it's dwindling compared to some kind of foreign

2329
01:44:36,240 --> 01:44:38,040
Speaker 11: culture which they don't really like or understand.

2330
01:44:39,040 --> 01:44:40,559
Speaker 12: That's particularly the case in Europe.

2331
01:44:40,760 --> 01:44:44,360
Speaker 11: In the United States, some of the immigration backlash, I'm

2332
01:44:44,400 --> 01:44:47,120
Speaker 11: probably most of the immigration backlash honestly, is dealing with

2333
01:44:47,160 --> 01:44:49,920
Speaker 11: those factors. But I don't think it really shows up

2334
01:44:49,960 --> 01:44:52,160
Speaker 11: as a political winner overall. I don't think there's a

2335
01:44:52,200 --> 01:44:57,160
Speaker 11: ton of evidence that Americans believe that their culture overall

2336
01:44:57,280 --> 01:45:02,679
Speaker 11: is being overwhelmed or somehow asumed or replaced by foreign cultures,

2337
01:45:02,920 --> 01:45:05,080
Speaker 11: not just because there's a different nature in the in

2338
01:45:05,120 --> 01:45:07,840
Speaker 11: the nature of the countries right, the United States is

2339
01:45:07,880 --> 01:45:10,679
Speaker 11: not found on ethnicity. It's not founded on one religion

2340
01:45:10,760 --> 01:45:13,479
Speaker 11: or creed. Really, it's founded more based on you know,

2341
01:45:13,520 --> 01:45:16,040
Speaker 11: there was a set of Northern Europeans or wasped who

2342
01:45:16,080 --> 01:45:18,599
Speaker 11: found in the US. But each wave of immigrants who

2343
01:45:18,640 --> 01:45:21,880
Speaker 11: came in, you know, successfully assimilated and while at the

2344
01:45:21,880 --> 01:45:24,559
Speaker 11: same time somewhat changing the culture at a pace and

2345
01:45:24,680 --> 01:45:27,120
Speaker 11: rate that I think has generally been accepted by Americans.

2346
01:45:27,880 --> 01:45:28,080
Speaker 4: You know.

2347
01:45:28,280 --> 01:45:31,920
Speaker 11: You mentioned, for instance, that like Trump increased his minority votes,

2348
01:45:32,200 --> 01:45:33,920
Speaker 11: but I think part of that also is in twenty

2349
01:45:33,960 --> 01:45:37,400
Speaker 11: twenty he barely talked about immigration real relative to twenty sixteen,

2350
01:45:38,040 --> 01:45:40,479
Speaker 11: I think he had shifted to other issues. I think

2351
01:45:40,600 --> 01:45:43,880
Speaker 11: things like him, really his COVID lockdowns probably appealed to

2352
01:45:43,920 --> 01:45:46,599
Speaker 11: a lot of people who maybe don't really particularly mind immigration,

2353
01:45:46,680 --> 01:45:50,479
Speaker 11: don't particularly mind you know, a more diverse culture in

2354
01:45:50,520 --> 01:45:54,160
Speaker 11: some ways, but maybe we're aggravated by democratic, you know,

2355
01:45:54,520 --> 01:45:58,080
Speaker 11: bureaucratic demands in one onech way shape or form. I

2356
01:45:58,120 --> 01:46:00,799
Speaker 11: do think, Sager, what you're describing probably is very powerful

2357
01:46:00,800 --> 01:46:02,920
Speaker 11: in the Republican Party at this moment. I think a

2358
01:46:02,920 --> 01:46:05,479
Speaker 11: lot of them probably would crack down even a legal migration,

2359
01:46:05,560 --> 01:46:07,600
Speaker 11: which I think is part of their complain about the

2360
01:46:07,680 --> 01:46:09,040
Speaker 11: Haitians and about TPS.

2361
01:46:09,520 --> 01:46:12,120
Speaker 12: But I'm not so sure it's such a winner overall.

2362
01:46:12,240 --> 01:46:14,559
Speaker 11: Like I'll give you an example, my governor here in Georgia,

2363
01:46:14,600 --> 01:46:17,160
Speaker 11: Brian Kemp, Like he made a point to go in

2364
01:46:17,240 --> 01:46:21,640
Speaker 11: campaign before first and second generation immigrant community. So like

2365
01:46:21,640 --> 01:46:24,040
Speaker 11: he went to a de Valley event outside Global Mall,

2366
01:46:24,080 --> 01:46:26,519
Speaker 11: which is this big like you know, South Asian, Indian

2367
01:46:26,520 --> 01:46:30,880
Speaker 11: and Pakistani shopping center in Georgia. And I don't think

2368
01:46:30,880 --> 01:46:34,040
Speaker 11: he said anything beyond you know, condemning illegal immigration, the

2369
01:46:34,080 --> 01:46:36,840
Speaker 11: same rote things as everyone else. And the guy is

2370
01:46:36,840 --> 01:46:39,320
Speaker 11: sitting on a sixty one or sixty three percent approval rating.

2371
01:46:39,360 --> 01:46:42,000
Speaker 11: And I think John Hassa probably lays awake at night

2372
01:46:42,040 --> 01:46:44,559
Speaker 11: hoping the NRC does not recruit in percent it because

2373
01:46:45,160 --> 01:46:47,439
Speaker 11: you know, a state like Georgia Old South, you know,

2374
01:46:47,560 --> 01:46:50,120
Speaker 11: used to be a creatile confederacy, is also a state

2375
01:46:50,160 --> 01:46:52,320
Speaker 11: that's rapidly changing. And yet you know, you go to

2376
01:46:52,320 --> 01:46:54,280
Speaker 11: a small town I do improv comedy in a small

2377
01:46:54,320 --> 01:46:57,240
Speaker 11: town that voted seventy five percent for Trump, and yet

2378
01:46:57,280 --> 01:46:59,880
Speaker 11: you know, every every street corner is an immigrant. The

2379
01:47:00,200 --> 01:47:02,880
Speaker 11: Hispanic festival happening. You know, you know, half my team

2380
01:47:02,920 --> 01:47:05,839
Speaker 11: is Asian or black, right, Like, that's a Republican county

2381
01:47:05,880 --> 01:47:08,040
Speaker 11: that I'm in, right Like, I think for the most

2382
01:47:08,080 --> 01:47:10,240
Speaker 11: part of people in this country are accepting of those things,

2383
01:47:10,760 --> 01:47:12,400
Speaker 11: and the people in the middle.

2384
01:47:12,520 --> 01:47:14,719
Speaker 12: What they don't like is lawlessness. They don't like chaos.

2385
01:47:14,720 --> 01:47:16,960
Speaker 11: They don't like border towns being overwhelmed and then people

2386
01:47:16,960 --> 01:47:19,080
Speaker 11: being shipped this way or that way, and they feel

2387
01:47:19,120 --> 01:47:21,800
Speaker 11: like disorderly right like people are being put upon. I

2388
01:47:21,800 --> 01:47:24,320
Speaker 11: think that's what they dislike. But America is one of

2389
01:47:24,360 --> 01:47:26,040
Speaker 11: the last countries on Earth. I think we're going to

2390
01:47:26,080 --> 01:47:28,280
Speaker 11: get away with this argument that, like, you know, you

2391
01:47:28,320 --> 01:47:31,479
Speaker 11: can't you can't have anybody but wasps in the country.

2392
01:47:32,240 --> 01:47:35,280
Speaker 11: We're not that kind of people. That's not I don't

2393
01:47:35,320 --> 01:47:37,480
Speaker 11: think that really gets to who we are as Americans.

2394
01:47:37,840 --> 01:47:40,040
Speaker 11: And that's where JD, I think, is making a political

2395
01:47:40,080 --> 01:47:43,120
Speaker 11: misstep here. And even if he feels that way, Look, dude,

2396
01:47:43,280 --> 01:47:45,280
Speaker 11: like this country is going to be like sixty to

2397
01:47:45,280 --> 01:47:47,759
Speaker 11: seventy percent white for your entire lifetime.

2398
01:47:47,840 --> 01:47:49,800
Speaker 12: Dude, you're not. You got to get people to have

2399
01:47:49,800 --> 01:47:51,880
Speaker 12: more babies. White folks gotta have more babies. That's it's

2400
01:47:51,920 --> 01:47:53,320
Speaker 12: not my fault they're not having more babies.

2401
01:47:53,400 --> 01:47:55,200
Speaker 11: I think even JD has said is at one point

2402
01:47:55,400 --> 01:47:57,559
Speaker 11: that they need to have more kids. So like work

2403
01:47:57,600 --> 01:48:00,280
Speaker 11: on family policy to get that achieved. But you don't

2404
01:48:00,320 --> 01:48:02,240
Speaker 11: have to worry about being, you know, your culture being

2405
01:48:02,280 --> 01:48:04,720
Speaker 11: wiped out. I'm less than one percent of the country.

2406
01:48:04,600 --> 01:48:07,680
Speaker 11: My culture, my culture is very strong, our families are

2407
01:48:07,720 --> 01:48:10,519
Speaker 11: very strong. I feel very secure in it. But that's

2408
01:48:10,560 --> 01:48:12,919
Speaker 11: partly on me, right, It's partly about how I engage

2409
01:48:12,960 --> 01:48:16,559
Speaker 11: to preserve my traditions and my culture. And you know,

2410
01:48:16,800 --> 01:48:18,599
Speaker 11: I think JD has every right to do that with

2411
01:48:18,640 --> 01:48:20,120
Speaker 11: his with his fambilanage.

2412
01:48:20,120 --> 01:48:22,760
Speaker 12: Going back to eastern Kentucky z To.

2413
01:48:23,120 --> 01:48:25,360
Speaker 1: Bolster your point, you know, you made the point about

2414
01:48:25,400 --> 01:48:28,080
Speaker 1: the governor, the Republican governor of Georgia. The Republican governor

2415
01:48:28,120 --> 01:48:31,080
Speaker 1: of Ohio also came out and said basically like stop

2416
01:48:31,280 --> 01:48:33,840
Speaker 1: doing this, you know, stop doing what you're doing. And

2417
01:48:33,880 --> 01:48:36,639
Speaker 1: he also is, you know, quite popular in the state

2418
01:48:36,680 --> 01:48:41,120
Speaker 1: of Ohio. One election handily last time, you know, actually

2419
01:48:41,120 --> 01:48:43,920
Speaker 1: outperformed Jade Vance by quite a significant margin. I think

2420
01:48:43,920 --> 01:48:46,599
Speaker 1: he also didn't have as strong as an opponent as JD. Vance.

2421
01:48:46,960 --> 01:48:49,680
Speaker 1: But to bolster your point about the politics of this,

2422
01:48:49,960 --> 01:48:54,000
Speaker 1: put B three up on the screen. It's not just

2423
01:48:54,040 --> 01:48:56,040
Speaker 1: some of the aspects that you point to that I

2424
01:48:56,040 --> 01:48:58,479
Speaker 1: think Americans don't like. I think they also don't like

2425
01:48:58,560 --> 01:49:03,960
Speaker 1: being lied to, and and of overwhelming majority of Americans,

2426
01:49:04,160 --> 01:49:06,320
Speaker 1: you know, huge gap between those who think that this

2427
01:49:06,560 --> 01:49:09,040
Speaker 1: is true and those who think that it is false.

2428
01:49:09,439 --> 01:49:13,639
Speaker 1: So majority fifty four percent say this is false, twenty

2429
01:49:13,680 --> 01:49:16,920
Speaker 1: six percent say that it is true. A majority of

2430
01:49:16,920 --> 01:49:22,080
Speaker 1: Trump voters do buy the Haitian pet lie. Effectively, no

2431
01:49:22,200 --> 01:49:25,559
Speaker 1: Harris voters buy it. And then the independence it was,

2432
01:49:25,680 --> 01:49:28,479
Speaker 1: you know, quite lopsided in favor of No, this is

2433
01:49:28,520 --> 01:49:30,400
Speaker 1: a lie. If you look at men, fifty four percent

2434
01:49:30,439 --> 01:49:32,400
Speaker 1: say it's a lie. If you look at women, fifty

2435
01:49:32,400 --> 01:49:35,680
Speaker 1: five percent say it's a lie. So yes, within the

2436
01:49:35,720 --> 01:49:38,599
Speaker 1: Republican base, they buy whatever it is that Trump wants

2437
01:49:38,680 --> 01:49:41,519
Speaker 1: to sell them. But they're already voting for Donald Trump,

2438
01:49:41,920 --> 01:49:45,240
Speaker 1: and more of those you know, swing voters, independence, et cetera,

2439
01:49:45,880 --> 01:49:49,160
Speaker 1: they see pretty clearly through the game that they're playing here.

2440
01:49:49,600 --> 01:49:53,040
Speaker 11: Yeah, and look, I think that I'm not someone who's

2441
01:49:53,080 --> 01:49:57,200
Speaker 11: saying that, like any skepticism towards immigration, particularly when we're

2442
01:49:57,200 --> 01:49:59,960
Speaker 11: talking about the lawlessness that happens, you know, at the border,

2443
01:50:00,400 --> 01:50:02,840
Speaker 11: drugs and crime and guns and gangs and so on

2444
01:50:02,880 --> 01:50:05,519
Speaker 11: and so forth, it should be taboo. Obviously should not

2445
01:50:05,560 --> 01:50:06,960
Speaker 11: be taboo. And I think when you do the same

2446
01:50:07,000 --> 01:50:09,680
Speaker 11: polls of Americans about those issues. They're very concerned about it,

2447
01:50:09,720 --> 01:50:12,800
Speaker 11: and it's a perfectly legitimate thing for the Republicans to

2448
01:50:12,800 --> 01:50:15,200
Speaker 11: address and bring up that Biden has has failed to

2449
01:50:15,240 --> 01:50:17,960
Speaker 11: handle a lot of that properly and create a more

2450
01:50:18,080 --> 01:50:21,200
Speaker 11: orderly immigration system. I think where they're like, like you said,

2451
01:50:21,240 --> 01:50:23,479
Speaker 11: I think where they're really kind of falling off is

2452
01:50:23,520 --> 01:50:27,439
Speaker 11: by creating this kind of cultural conflict between saying, you know, like, okay,

2453
01:50:27,439 --> 01:50:29,600
Speaker 11: I'll give you guys an example like Douglas Murray. Right,

2454
01:50:29,640 --> 01:50:32,160
Speaker 11: it's like this kind of posh, right wing British commentator.

2455
01:50:33,000 --> 01:50:36,679
Speaker 11: You know, after there were some rights in the UK, yeah, right,

2456
01:50:36,960 --> 01:50:39,360
Speaker 11: very much. So after there were some riots in the UK.

2457
01:50:39,439 --> 01:50:41,240
Speaker 11: There was there was a stabbing actually I think it

2458
01:50:41,280 --> 01:50:44,120
Speaker 11: was by an African migrant who was a Christian background.

2459
01:50:44,400 --> 01:50:46,760
Speaker 11: For some reason, someone spent a rumor it was Muslims.

2460
01:50:46,800 --> 01:50:49,160
Speaker 11: So there are all these riots aimed at mosques and

2461
01:50:49,160 --> 01:50:51,960
Speaker 11: the Muslim communities, and then Murray comes up and says, look,

2462
01:50:52,000 --> 01:50:54,040
Speaker 11: this is the result of you know, you don't let

2463
01:50:54,120 --> 01:50:55,920
Speaker 11: us talk about immigration, and what do you expect blah

2464
01:50:55,920 --> 01:50:59,120
Speaker 11: blah blah, And it's like, dude, every election in the

2465
01:50:59,160 --> 01:51:01,720
Speaker 11: West is particular in Europe for the past like ten years,

2466
01:51:01,760 --> 01:51:04,040
Speaker 11: has been about immigration. He's constantly all over the news,

2467
01:51:04,120 --> 01:51:05,880
Speaker 11: daily mails, so on, and so forth. But I think

2468
01:51:05,920 --> 01:51:08,439
Speaker 11: really what he means, the frustration he's feeling is you

2469
01:51:08,520 --> 01:51:10,360
Speaker 11: can't just say that, why don't we just keep our

2470
01:51:10,360 --> 01:51:11,080
Speaker 11: countries white?

2471
01:51:11,160 --> 01:51:11,360
Speaker 1: Right?

2472
01:51:11,439 --> 01:51:15,519
Speaker 11: Like, That's probably what he feels, And I think that

2473
01:51:15,960 --> 01:51:18,040
Speaker 11: there is a faction in the Republican Party who feels

2474
01:51:18,040 --> 01:51:21,759
Speaker 11: that way. But my counter to that is that that faction,

2475
01:51:21,840 --> 01:51:24,320
Speaker 11: I think is very online, Like they tend to be

2476
01:51:25,320 --> 01:51:29,080
Speaker 11: people who have prestigious positions, that think tanks who tweet

2477
01:51:29,120 --> 01:51:31,320
Speaker 11: a lot and put out white papers. But in the

2478
01:51:31,360 --> 01:51:36,360
Speaker 11: actual world of Republicans, you know, you go to Florida, Texas, Georgia,

2479
01:51:36,720 --> 01:51:40,200
Speaker 11: you see diverse communities, you know, voting Republican. You see

2480
01:51:40,479 --> 01:51:43,439
Speaker 11: people in verious small towns in world parts of the

2481
01:51:43,479 --> 01:51:46,800
Speaker 11: country welcoming you know, to Hanno's and people who have

2482
01:51:47,840 --> 01:51:50,280
Speaker 11: roots who are one or two generations removed from the

2483
01:51:50,360 --> 01:51:52,320
Speaker 11: United States and from European American culture.

2484
01:51:52,400 --> 01:51:52,599
Speaker 12: Right.

2485
01:51:52,920 --> 01:51:56,240
Speaker 11: I think in the actual world there isn't quite nearly

2486
01:51:56,240 --> 01:51:59,559
Speaker 11: as much hostility towards these things as you might see

2487
01:51:59,600 --> 01:52:02,280
Speaker 11: among you know, certain right wing influencers among the Charlie

2488
01:52:02,320 --> 01:52:04,559
Speaker 11: Kirks of the world, among some of the people maybe

2489
01:52:04,640 --> 01:52:08,840
Speaker 11: JD follows on Twitter or on social media. And I

2490
01:52:08,840 --> 01:52:11,920
Speaker 11: think the Republican Party he needs to calibrate for that

2491
01:52:11,920 --> 01:52:12,240
Speaker 11: if it.

2492
01:52:12,240 --> 01:52:13,000
Speaker 12: Wants to survive.

2493
01:52:13,080 --> 01:52:16,480
Speaker 11: And I'm not doing the twenty twelve you know autopsies

2494
01:52:16,479 --> 01:52:19,400
Speaker 11: saying they have to be one hundred percent pro legalize everybody,

2495
01:52:19,760 --> 01:52:21,800
Speaker 11: loose immigration policies.

2496
01:52:21,400 --> 01:52:22,240
Speaker 12: So on and so forth.

2497
01:52:22,720 --> 01:52:25,559
Speaker 11: But they do have to avoid being racist, right, They

2498
01:52:25,600 --> 01:52:27,920
Speaker 11: have to avoid being racist, and they have to avoid

2499
01:52:28,160 --> 01:52:30,280
Speaker 11: looking like they just want the country to be full

2500
01:52:30,280 --> 01:52:32,160
Speaker 11: of white folks, because that's not the country anymore. And

2501
01:52:32,160 --> 01:52:34,280
Speaker 11: a lot of people who are curious about voting Republican,

2502
01:52:34,320 --> 01:52:37,200
Speaker 11: who agree with Republicans on taxes, who agree with Republicans

2503
01:52:37,200 --> 01:52:38,440
Speaker 11: on social policy.

2504
01:52:38,040 --> 01:52:39,439
Speaker 12: They want, you know, strong police.

2505
01:52:39,920 --> 01:52:42,400
Speaker 11: They're kind of skeptical about abortion, the morality of abortion,

2506
01:52:42,439 --> 01:52:45,160
Speaker 11: particularities Latin American immigrants are a lot of people who

2507
01:52:45,200 --> 01:52:47,719
Speaker 11: want to vote Republican. I'm not going to vote Republican

2508
01:52:47,760 --> 01:52:49,599
Speaker 11: if they feel like they're being insulted every day, right,

2509
01:52:49,680 --> 01:52:51,760
Speaker 11: or someone's going to spread some racist theory about their

2510
01:52:51,760 --> 01:52:54,599
Speaker 11: group every day. If they're putting those kinds of people

2511
01:52:54,600 --> 01:52:57,400
Speaker 11: into power, right, and that I think is the line

2512
01:52:57,439 --> 01:53:00,759
Speaker 11: they need to kind of straddle. And I think Vance

2513
01:53:00,800 --> 01:53:03,599
Speaker 11: needs to understand this that a lot of what he's

2514
01:53:03,640 --> 01:53:06,960
Speaker 11: saying about global capital, a lot of what he's saying

2515
01:53:07,320 --> 01:53:09,479
Speaker 11: about families and how hard it is for his family

2516
01:53:09,479 --> 01:53:12,120
Speaker 11: are true, and they resonate very well with people for

2517
01:53:12,120 --> 01:53:12,920
Speaker 11: for good reason.

2518
01:53:13,280 --> 01:53:15,080
Speaker 12: But man, you gotta you got to you gotta take

2519
01:53:15,200 --> 01:53:15,599
Speaker 12: race and.

2520
01:53:15,520 --> 01:53:18,280
Speaker 11: Culture out of it, right, You've got to understand that

2521
01:53:18,439 --> 01:53:20,880
Speaker 11: a lot of the conservative cultural values you value are

2522
01:53:20,920 --> 01:53:22,679
Speaker 11: the same ones. Probably a lot of those folks coming

2523
01:53:22,680 --> 01:53:25,639
Speaker 11: into Springfield from from Haiti value right. They probably value

2524
01:53:25,680 --> 01:53:28,280
Speaker 11: strong families. They're probably kind of skeptical about abortion. They

2525
01:53:28,439 --> 01:53:31,120
Speaker 11: probably want good policing. I mean, I haven't heard about

2526
01:53:31,120 --> 01:53:32,880
Speaker 11: any big crime wave as a result of these people,

2527
01:53:32,920 --> 01:53:35,160
Speaker 11: probably because they're sick of that from where they came from.

2528
01:53:35,400 --> 01:53:36,200
Speaker 12: They're happy to be in a.

2529
01:53:36,200 --> 01:53:38,879
Speaker 11: Country with a rule blaw with police where people criminals

2530
01:53:38,880 --> 01:53:41,120
Speaker 11: do get punished, where if somebody ate.

2531
01:53:41,120 --> 01:53:42,760
Speaker 12: A cat, they would be punished for it. Right, we'd

2532
01:53:42,760 --> 01:53:43,920
Speaker 12: all hear about it, we all know about it.

2533
01:53:43,920 --> 01:53:46,120
Speaker 11: Wouldn't have to work rely on this blurry video that

2534
01:53:46,200 --> 01:53:49,479
Speaker 11: Chris Ruppo's sending around, you know, like UFO Bigfoot style, right.

2535
01:53:49,439 --> 01:53:51,920
Speaker 2: So, well, we're going to find out if you're right

2536
01:53:52,000 --> 01:53:54,880
Speaker 2: or not said, I'm very curious. I'm of several minds

2537
01:53:54,880 --> 01:53:57,960
Speaker 2: about it, as we've talked about for ad nauseum. Now

2538
01:53:58,000 --> 01:54:01,080
Speaker 2: at the show, I really appreciate you as always, Thank

2539
01:54:01,120 --> 01:54:02,720
Speaker 2: you for coming on and we hope to see you

2540
01:54:02,720 --> 01:54:03,559
Speaker 2: against you great.

2541
01:54:03,360 --> 01:54:03,920
Speaker 4: To see a zad.

2542
01:54:03,920 --> 01:54:09,160
Speaker 1: Thank you. So there's been a lot of discussion about

2543
01:54:09,640 --> 01:54:12,800
Speaker 1: individual who appears to be a major advisor to President Trump.

2544
01:54:12,800 --> 01:54:15,559
Speaker 4: That would be Laura Lumer. And I'll save it for

2545
01:54:15,600 --> 01:54:17,639
Speaker 4: Sager to explain who this lady is because she could

2546
01:54:17,640 --> 01:54:18,519
Speaker 4: probably do about her job.

2547
01:54:18,560 --> 01:54:20,439
Speaker 3: Maybe you should do it so she doesn't. Lumer me.

2548
01:54:20,880 --> 01:54:23,720
Speaker 1: Well, okay, so let's go and put her tweet up

2549
01:54:23,760 --> 01:54:26,040
Speaker 1: on the screen. This is just some of her recent work,

2550
01:54:26,880 --> 01:54:30,200
Speaker 1: where she even got a visibility limited warning for hateful

2551
01:54:30,240 --> 01:54:33,960
Speaker 1: conduct from Elon Musk's Twitter. She says, if Kamala Harris wins,

2552
01:54:34,480 --> 01:54:37,200
Speaker 1: the White House will smell like curry, and White House

2553
01:54:37,200 --> 01:54:39,560
Speaker 1: speeches will be facilitated by a call center, and the

2554
01:54:39,560 --> 01:54:41,720
Speaker 1: American people will only be able to convey their feedback

2555
01:54:41,760 --> 01:54:43,960
Speaker 1: through a customer satisfaction survey. At the end of the

2556
01:54:43,960 --> 01:54:46,800
Speaker 1: call that nobody will understand you get it, guys, because

2557
01:54:46,840 --> 01:54:48,480
Speaker 1: Kamala Harris is half Indian.

2558
01:54:48,800 --> 01:54:50,280
Speaker 4: Lol, isn't that funny.

2559
01:54:51,240 --> 01:54:53,920
Speaker 1: This is also the lady that went on Tim Poole's

2560
01:54:54,120 --> 01:54:58,240
Speaker 1: broadcast and called for Democrats to be executed for treason.

2561
01:54:59,000 --> 01:55:03,320
Speaker 1: He actually took down the episode because of her calling

2562
01:55:03,400 --> 01:55:07,400
Speaker 1: for the murder mass murder of Democrats. So this is

2563
01:55:07,440 --> 01:55:11,000
Speaker 1: the person that we're talking about here. And you know,

2564
01:55:11,120 --> 01:55:13,120
Speaker 1: this is something that I've been talking a bit about.

2565
01:55:13,360 --> 01:55:17,680
Speaker 1: Sager is twenty sixteen Trump, Tabloid Trump, twenty twenty Trump,

2566
01:55:17,760 --> 01:55:20,320
Speaker 1: Fox News Trump twenty twenty four. Trump is like truth

2567
01:55:20,360 --> 01:55:24,760
Speaker 1: social Trump, And there is no better emblem of that evolution,

2568
01:55:25,040 --> 01:55:28,600
Speaker 1: in my view than his association with this person who's

2569
01:55:28,640 --> 01:55:31,280
Speaker 1: been flying on his plane and he's, you know, always

2570
01:55:31,320 --> 01:55:34,200
Speaker 1: like louding her and touting how smart she is and

2571
01:55:34,240 --> 01:55:35,800
Speaker 1: how insightful, et cetera, et cetera.

2572
01:55:35,920 --> 01:55:37,880
Speaker 2: Well, you asked me earlier in the show, he said,

2573
01:55:37,960 --> 01:55:39,920
Speaker 2: what is racist or not? And I think that's pretty

2574
01:55:40,040 --> 01:55:41,800
Speaker 2: curly racist. By the way, if you want to know

2575
01:55:42,080 --> 01:55:46,160
Speaker 2: the reason why, it is because specifically about the rape

2576
01:55:46,320 --> 01:55:50,760
Speaker 2: linking the practice of race to the well documented love

2577
01:55:50,800 --> 01:55:53,400
Speaker 2: of white nationalists. Was just talking about how Indians quote

2578
01:55:53,440 --> 01:55:56,320
Speaker 2: eat curry and always smell like it. What does she

2579
01:55:56,360 --> 01:55:59,560
Speaker 2: say in terms of the link anyway, I won't even

2580
01:56:00,080 --> 01:56:04,880
Speaker 2: dignify it. But continuing I think with this vein is

2581
01:56:05,800 --> 01:56:09,960
Speaker 2: funny to me. It is recognized now that these people

2582
01:56:10,000 --> 01:56:14,800
Speaker 2: around Trump are a problem, specifically by others who previously

2583
01:56:14,840 --> 01:56:18,000
Speaker 2: would have backed these people up. So Marjorie Taylor Green

2584
01:56:18,360 --> 01:56:20,920
Speaker 2: being the prime example for me because she then begins

2585
01:56:21,000 --> 01:56:22,640
Speaker 2: attacking Laura Lumer.

2586
01:56:22,680 --> 01:56:25,680
Speaker 3: Now, the thing is about Lumer. She's been banned and unbanned.

2587
01:56:25,200 --> 01:56:27,800
Speaker 2: From social media for like the entire time that I've

2588
01:56:27,840 --> 01:56:32,400
Speaker 2: been involved in conservative circles. She's one of those people

2589
01:56:32,400 --> 01:56:34,640
Speaker 2: who she calls it getting lumored. That was the jocos

2590
01:56:34,720 --> 01:56:36,560
Speaker 2: making earlier, where she can stick a camera in your

2591
01:56:36,600 --> 01:56:39,240
Speaker 2: face and ask you a question. I mean, she is

2592
01:56:39,800 --> 01:56:43,840
Speaker 2: I think best described as like a genuine like apparatic.

2593
01:56:44,480 --> 01:56:47,920
Speaker 2: She recently, after Elon bought Twitter, has been back on

2594
01:56:48,000 --> 01:56:50,000
Speaker 2: Twitter and she's been fighting and beefing.

2595
01:56:50,240 --> 01:56:51,720
Speaker 3: She's very very pro Trump.

2596
01:56:51,920 --> 01:56:54,360
Speaker 2: The only topic I've seen her engage with like outside

2597
01:56:54,400 --> 01:56:57,920
Speaker 2: of Trump is on Israel, where she debated Dave Smith earlier.

2598
01:56:58,240 --> 01:57:02,360
Speaker 1: Yeah, zero heads just put those extremely extremely pro Israel.

2599
01:57:02,440 --> 01:57:04,200
Speaker 4: It's like a key issue for her.

2600
01:57:04,400 --> 01:57:07,400
Speaker 3: So that's uh, that's Lumer, I guess in a nutshells.

2601
01:57:07,400 --> 01:57:10,200
Speaker 2: It's always been kind of a right wing provocateur. I

2602
01:57:10,240 --> 01:57:12,360
Speaker 2: remember seeing her at sea pack and they banned her, and.

2603
01:57:12,600 --> 01:57:14,040
Speaker 4: Yeah, she ran for Congress.

2604
01:57:14,040 --> 01:57:15,800
Speaker 3: She lost, She ran for Congress, She's lost.

2605
01:57:16,040 --> 01:57:19,640
Speaker 1: I mean she's you know, pretty overt with her biases

2606
01:57:19,880 --> 01:57:21,680
Speaker 1: and her just insant.

2607
01:57:21,840 --> 01:57:23,000
Speaker 3: I don't even know how to describe.

2608
01:57:23,040 --> 01:57:26,520
Speaker 2: I mean, she just genuinely is like she takes the

2609
01:57:26,600 --> 01:57:30,680
Speaker 2: Trump posting to its most logical conclusion. And what I

2610
01:57:30,720 --> 01:57:32,120
Speaker 2: mean by that is just like Trump can never do

2611
01:57:32,160 --> 01:57:34,360
Speaker 2: any wrong, Trump is always good, Like Trump must be

2612
01:57:34,440 --> 01:57:37,160
Speaker 2: protected at all costs. So she leverages that she'll back

2613
01:57:37,240 --> 01:57:39,360
Speaker 2: up basically anything that the guy says, yeah or and

2614
01:57:39,480 --> 01:57:41,200
Speaker 2: it's always like an attack dog on the left.

2615
01:57:41,200 --> 01:57:42,160
Speaker 3: So that's why they love her.

2616
01:57:42,120 --> 01:57:46,320
Speaker 1: And specificiously anti DeSantis too. She shows you it's anyone

2617
01:57:46,880 --> 01:57:48,640
Speaker 1: who is oppositional to Trump at all.

2618
01:57:48,640 --> 01:57:50,720
Speaker 2: And so that's important because what that means is that

2619
01:57:50,760 --> 01:57:53,400
Speaker 2: Trump feels the most comfortable with people like her and

2620
01:57:53,520 --> 01:57:55,600
Speaker 2: others who are around him. Everybody around him has to

2621
01:57:55,720 --> 01:58:00,640
Speaker 2: validate him at all times and current constantly manages personality,

2622
01:58:00,640 --> 01:58:02,720
Speaker 2: which is why I actually thought that they Marjorie Taylor

2623
01:58:02,760 --> 01:58:07,000
Speaker 2: Green breaking with la Lumer was interesting because Marjorie previously

2624
01:58:07,000 --> 01:58:08,720
Speaker 2: would be one of those people who would you know,

2625
01:58:08,760 --> 01:58:09,720
Speaker 2: she's very close with Trump.

2626
01:58:09,720 --> 01:58:10,880
Speaker 3: She's always backing up Trump.

2627
01:58:10,920 --> 01:58:13,400
Speaker 2: But they've split, maybe only once publicly on the whole

2628
01:58:13,480 --> 01:58:15,240
Speaker 2: Kevin McCarthy thing, right.

2629
01:58:15,080 --> 01:58:17,800
Speaker 3: But that's basically it. So yeah, she then started to

2630
01:58:17,800 --> 01:58:19,920
Speaker 3: attack Lumer. I started to pay attention.

2631
01:58:20,040 --> 01:58:23,200
Speaker 2: Yeah, so this is interesting because she thinks, clearly, Marjorie

2632
01:58:23,280 --> 01:58:26,640
Speaker 2: thinks that Lumor is a bad influence on Trump, shouldn't

2633
01:58:26,640 --> 01:58:28,960
Speaker 2: be around Trump, and is bad reputationally for him.

2634
01:58:29,000 --> 01:58:33,280
Speaker 1: See, I feel like it's more petty interpersonal I see,

2635
01:58:33,640 --> 01:58:36,080
Speaker 1: is what I actually think it is, because Lumor has

2636
01:58:36,120 --> 01:58:38,400
Speaker 1: his ear. You know, she may have some other parts

2637
01:58:38,400 --> 01:58:41,000
Speaker 1: of him, but that will leave that speculation to others.

2638
01:58:41,440 --> 01:58:44,280
Speaker 1: They've been very friendly with one another, and I think

2639
01:58:44,320 --> 01:58:47,000
Speaker 1: Marjorie Taylor Green is jealous of the access that Laura

2640
01:58:47,040 --> 01:58:50,160
Speaker 1: Lumoor has right now. In any case, after the Curry tweet,

2641
01:58:50,640 --> 01:58:53,280
Speaker 1: Marjorie Taylor Green decided this was a bridge too far.

2642
01:58:53,480 --> 01:58:56,080
Speaker 1: She put on a Twitter post and she also went

2643
01:58:56,120 --> 01:58:58,840
Speaker 1: to the cameras and denounced Laura Lumor.

2644
01:58:58,920 --> 01:59:00,240
Speaker 4: Let's take a listen to what she had to say.

2645
01:59:00,600 --> 01:59:03,280
Speaker 16: This is such an important election. I don't think that

2646
01:59:03,440 --> 01:59:07,720
Speaker 16: she has the experience or the right mentality to advise

2647
01:59:08,480 --> 01:59:11,920
Speaker 16: very important. I'm not involved in their conversations, so I

2648
01:59:11,960 --> 01:59:14,840
Speaker 16: can't weigh in on that, but I do know this

2649
01:59:15,000 --> 01:59:18,480
Speaker 16: that her rhetoric, in her tone is does not.

2650
01:59:18,440 --> 01:59:19,680
Speaker 1: Match the base, does.

2651
01:59:19,600 --> 01:59:22,680
Speaker 16: Not match MAGA, does not match less Republicans. I know,

2652
01:59:23,320 --> 01:59:27,560
Speaker 16: and I am completely denouncing it. I'm over it, and

2653
01:59:27,600 --> 01:59:31,760
Speaker 16: I would encourage anyone else that matches her statements to stop.

2654
01:59:32,360 --> 01:59:35,440
Speaker 1: So this triggered one of the messiest Twitter fights I've

2655
01:59:35,520 --> 01:59:37,880
Speaker 1: ever seen. We can put I'm not going to read

2656
01:59:37,880 --> 01:59:39,480
Speaker 1: all of this, guys, but we can put this up

2657
01:59:39,480 --> 01:59:42,400
Speaker 1: on this Green just to show you how ugly this

2658
01:59:42,560 --> 01:59:46,760
Speaker 1: got and how fast Laura Lumer tweets in part, Hey,

2659
01:59:46,840 --> 01:59:49,600
Speaker 1: Marjorie Taylor Green, remember when you destroyed your family so

2660
01:59:49,640 --> 01:59:52,480
Speaker 1: you could have a have sex with a zen gief.

2661
01:59:52,560 --> 01:59:53,400
Speaker 4: I don't know what that is.

2662
01:59:53,600 --> 01:59:57,640
Speaker 1: Cosplayer, tell me again how you and the RB's in

2663
01:59:57,680 --> 02:00:01,760
Speaker 1: your pants are representatives of the GOP. And it went

2664
02:00:01,800 --> 02:00:04,880
Speaker 1: on from there, so which also I wanted to put

2665
02:00:04,920 --> 02:00:07,120
Speaker 1: up because to give you a sense of Laura Lumer

2666
02:00:07,480 --> 02:00:08,280
Speaker 1: and who she is.

2667
02:00:08,760 --> 02:00:10,400
Speaker 4: And how she operates anybody.

2668
02:00:10,560 --> 02:00:13,800
Speaker 1: So yeah, and Marjorie Taylor Green wasn't the only one

2669
02:00:13,800 --> 02:00:16,800
Speaker 1: who came out. I believe Tom Tillis was also Senate

2670
02:00:16,800 --> 02:00:22,320
Speaker 1: in North Carolina Republican senator was also coming out against her. Trump.

2671
02:00:22,440 --> 02:00:25,320
Speaker 1: This became enough of an issue because it isn't just

2672
02:00:25,560 --> 02:00:27,600
Speaker 1: you know about these like messy beefs, but this is

2673
02:00:27,640 --> 02:00:30,720
Speaker 1: a genuine question of who has Trump's ear? Why is

2674
02:00:30,720 --> 02:00:33,640
Speaker 1: he engaging in some of these seemingly insane tactics and

2675
02:00:33,680 --> 02:00:36,800
Speaker 1: indulging some of the seemingly insane conspiracy theories that he

2676
02:00:36,840 --> 02:00:40,840
Speaker 1: is indulging seemingly to his campaign's detriment. So he got

2677
02:00:40,840 --> 02:00:43,040
Speaker 1: asked about it out on the campaign trail. Let's take

2678
02:00:43,040 --> 02:00:44,080
Speaker 1: a listen to his response.

2679
02:00:44,760 --> 02:00:47,760
Speaker 2: You Republican colleagues, are your allies who are concerned about

2680
02:00:47,760 --> 02:00:49,320
Speaker 2: your pose relationship with Laura Lumer?

2681
02:00:50,320 --> 02:00:52,240
Speaker 3: Well, I don't know what they would say.

2682
02:00:52,520 --> 02:00:55,800
Speaker 17: Laura has been a supporter of mine, just like a

2683
02:00:55,800 --> 02:00:58,000
Speaker 17: lot of people are supporters, and she's been a supporter

2684
02:00:58,080 --> 02:01:02,240
Speaker 17: of mine. She speaks very positively of the campaign. I'm

2685
02:01:02,280 --> 02:01:04,560
Speaker 17: not sure why you asked that question. But Laura is

2686
02:01:04,600 --> 02:01:08,880
Speaker 17: a supporter. I don't control Laura. Laura has to say

2687
02:01:08,920 --> 02:01:11,240
Speaker 17: what you want. She's a free spirit.

2688
02:01:11,840 --> 02:01:12,400
Speaker 3: Well, I don't know.

2689
02:01:12,440 --> 02:01:14,480
Speaker 17: I mean, look, I can't tell Laura what to do.

2690
02:01:14,520 --> 02:01:19,040
Speaker 17: Laura's a supporter. I have a lot of supporters. But

2691
02:01:19,320 --> 02:01:25,480
Speaker 17: so I don't know what exactly you're referring to. That's okay, yeah, please,

2692
02:01:26,480 --> 02:01:28,880
Speaker 17: I just don't know. Laura's a supporter. I don't know

2693
02:01:29,160 --> 02:01:32,960
Speaker 17: she is. She is a strong person, she's got strong opinions,

2694
02:01:33,000 --> 02:01:34,200
Speaker 17: and I don't know what she said.

2695
02:01:34,200 --> 02:01:35,520
Speaker 4: But that's not up to me.

2696
02:01:35,560 --> 02:01:36,320
Speaker 12: She's a supporter.

2697
02:01:37,080 --> 02:01:39,480
Speaker 1: She's a supporter. She's a free spirit. I have a

2698
02:01:39,520 --> 02:01:41,560
Speaker 1: lot of supporters. Yeah, but not all those supporters are

2699
02:01:41,600 --> 02:01:43,760
Speaker 1: writing on your plane with you. Yeah, then and going

2700
02:01:43,800 --> 02:01:46,080
Speaker 1: to the nine to eleven memorial with you and whatever.

2701
02:01:46,240 --> 02:01:48,640
Speaker 3: Yeah. She's been pictured with him now several times.

2702
02:01:48,720 --> 02:01:51,240
Speaker 2: Put this up there on the screen, like, for example,

2703
02:01:51,400 --> 02:01:55,240
Speaker 2: we have multiple photos of them like hugging and being

2704
02:01:55,280 --> 02:01:58,120
Speaker 2: around each other. She's made herself like a permanent presence

2705
02:01:58,400 --> 02:02:02,000
Speaker 2: at mar al Lago. So it's just demonstrates again the

2706
02:02:02,040 --> 02:02:05,000
Speaker 2: same problem that Trump always has, where he will surround

2707
02:02:05,080 --> 02:02:07,240
Speaker 2: himself with the people who not only tell him what

2708
02:02:07,560 --> 02:02:10,280
Speaker 2: to hear, but like his most loyal people. He believes

2709
02:02:10,280 --> 02:02:13,000
Speaker 2: that loyalty is the chief and the most important virtue

2710
02:02:13,280 --> 02:02:14,320
Speaker 2: for those who are around him.

2711
02:02:14,320 --> 02:02:15,840
Speaker 3: People will always.

2712
02:02:15,560 --> 02:02:18,160
Speaker 2: Defend him, especially whenever things get bad for him. He

2713
02:02:18,200 --> 02:02:20,360
Speaker 2: did this during Access Hollywood. He would retreat. He would

2714
02:02:20,360 --> 02:02:23,200
Speaker 2: surround himself whenever he was president and he would say,

2715
02:02:23,480 --> 02:02:27,120
Speaker 2: Charlottesville whatever, he would retreat again to like his closest

2716
02:02:27,280 --> 02:02:29,200
Speaker 2: people who would always be willing to back him up.

2717
02:02:29,240 --> 02:02:31,880
Speaker 2: Part of the reason that he loves Jesse Waters and

2718
02:02:31,880 --> 02:02:34,000
Speaker 2: always Fox News other people because they're always defend him,

2719
02:02:34,000 --> 02:02:37,040
Speaker 2: Greg Guttfeld and others, and Lumri fouls in that category.

2720
02:02:37,080 --> 02:02:38,720
Speaker 2: I think the people will fly with him around on

2721
02:02:38,720 --> 02:02:41,080
Speaker 2: the plane to always sell him what he's doing is good,

2722
02:02:41,520 --> 02:02:43,800
Speaker 2: backed him up on stop the steal or any of

2723
02:02:43,840 --> 02:02:44,400
Speaker 2: the other stuff.

2724
02:02:44,440 --> 02:02:46,440
Speaker 3: And Trump is the most comfortable there.

2725
02:02:46,440 --> 02:02:48,560
Speaker 2: And frankly is one of the worst things about him,

2726
02:02:48,600 --> 02:02:51,680
Speaker 2: right because that means that he's always never actually getting

2727
02:02:51,760 --> 02:02:55,200
Speaker 2: checked by anybody who is around him, and in general,

2728
02:02:55,280 --> 02:02:57,520
Speaker 2: you know, on a long enough timeline, these people end

2729
02:02:57,600 --> 02:02:59,920
Speaker 2: up triumphing in his personal orbit. Although sometimes he does

2730
02:03:00,000 --> 02:03:03,560
Speaker 2: listen if remember this too. He also personally has no loyalty.

2731
02:03:03,640 --> 02:03:05,960
Speaker 2: So if she does become a problem, he'll aspire her

2732
02:03:06,040 --> 02:03:07,640
Speaker 2: or he'll never see her again, which I could also

2733
02:03:07,680 --> 02:03:08,200
Speaker 2: see happening.

2734
02:03:08,240 --> 02:03:10,640
Speaker 1: Do you think that he will listen to the criticism

2735
02:03:10,680 --> 02:03:11,760
Speaker 1: and distance himself from her.

2736
02:03:11,840 --> 02:03:13,160
Speaker 3: I don't know. I mean I haven't.

2737
02:03:13,600 --> 02:03:16,040
Speaker 2: I haven't seen a report that she's been around him yet.

2738
02:03:16,520 --> 02:03:19,600
Speaker 2: But at this point, like looking at where things are,

2739
02:03:19,680 --> 02:03:22,600
Speaker 2: I don't think it's reached like a critical mass level yet.

2740
02:03:22,600 --> 02:03:25,440
Speaker 2: But for him sometimes the bar is if I even

2741
02:03:25,480 --> 02:03:26,960
Speaker 2: have to take a question about it, you're done.

2742
02:03:27,080 --> 02:03:31,040
Speaker 1: You know that this association is driving Chris Losovita and

2743
02:03:31,080 --> 02:03:32,080
Speaker 1: Susie Wiles oh.

2744
02:03:32,080 --> 02:03:33,080
Speaker 3: Yeah, crazy. Yeah.

2745
02:03:33,360 --> 02:03:36,880
Speaker 2: Well, they also hate that because that controls that diminishes

2746
02:03:36,920 --> 02:03:39,560
Speaker 2: their access to the candidate, because these are exactly type

2747
02:03:39,560 --> 02:03:41,000
Speaker 2: of people will be like, don't listen to your advisors,

2748
02:03:41,000 --> 02:03:42,280
Speaker 2: don't listen to whatever.

2749
02:03:42,320 --> 02:03:44,800
Speaker 3: Everything you do is amazing, and like okay.

2750
02:03:44,560 --> 02:03:46,240
Speaker 1: Well, and you can see, you know, in the debate,

2751
02:03:46,680 --> 02:03:49,160
Speaker 1: right the first fifteen minutes of Trump are like the

2752
02:03:49,320 --> 02:03:51,600
Speaker 1: Chris Losovita fifteen minutes.

2753
02:03:51,640 --> 02:03:54,080
Speaker 4: It's you know, it's hitting the points on the economy.

2754
02:03:54,680 --> 02:03:57,480
Speaker 1: In the last five minutes where he suddenly remembered like,

2755
02:03:57,520 --> 02:03:59,600
Speaker 1: oh my god, I'm supposed to say, like, if you

2756
02:03:59,640 --> 02:04:01,400
Speaker 1: were going to all these problems, why didn't you do it?

2757
02:04:01,440 --> 02:04:04,600
Speaker 1: And here's the issues and in between was the Laura

2758
02:04:04,680 --> 02:04:09,600
Speaker 1: Lumor influence and that's what ends up the problem is

2759
02:04:09,680 --> 02:04:11,520
Speaker 1: even if you only have a dash of Laura Lumor,

2760
02:04:11,520 --> 02:04:13,720
Speaker 1: which there was more than a dash in that debate performance,

2761
02:04:13,800 --> 02:04:16,440
Speaker 1: but what is the what is the thing everyone's talking

2762
02:04:16,480 --> 02:04:19,080
Speaker 1: about it after it? It's pets, right, it's they're eating

2763
02:04:19,080 --> 02:04:21,040
Speaker 1: the dogs, they're eating the cats, They're eating the pets.

2764
02:04:21,560 --> 02:04:25,280
Speaker 1: And so you only need you know, an instant, an

2765
02:04:25,280 --> 02:04:30,000
Speaker 1: instant relapse to Laura Lumor mode, and I you know,

2766
02:04:30,040 --> 02:04:31,960
Speaker 1: it would not be surprising at all if she was

2767
02:04:31,960 --> 02:04:34,080
Speaker 1: the one that was talking in his ear right before

2768
02:04:34,080 --> 02:04:36,000
Speaker 1: the debate about that, and then that's what comes out,

2769
02:04:36,080 --> 02:04:39,640
Speaker 1: and then that becomes the moment. So in any case,

2770
02:04:40,160 --> 02:04:44,560
Speaker 1: interesting drama, interesting infighting playing out. Turfour's playing out, and

2771
02:04:44,560 --> 02:04:46,480
Speaker 1: I think also indicative of the fact that they don't

2772
02:04:46,560 --> 02:04:49,480
Speaker 1: feel like things are going particularly well for them right now.

2773
02:04:50,080 --> 02:04:51,760
Speaker 4: They feel like the Poles should.

2774
02:04:51,480 --> 02:04:55,080
Speaker 1: Look better, you know, I think obviously he could win,

2775
02:04:55,520 --> 02:04:58,360
Speaker 1: there's no doubt about that. He's the Poles are very close.

2776
02:04:58,400 --> 02:05:00,880
Speaker 1: The Electoral College is even closer. But I do think

2777
02:05:00,880 --> 02:05:02,640
Speaker 1: they have a sense that things are not going the

2778
02:05:02,680 --> 02:05:04,680
Speaker 1: way they want them to go. And when that happens,

2779
02:05:04,680 --> 02:05:06,640
Speaker 1: then you start to get all these like ugly messy

2780
02:05:06,640 --> 02:05:07,080
Speaker 1: fights too.

2781
02:05:07,160 --> 02:05:08,440
Speaker 3: That's a good point, all right, Let's move on.

2782
02:05:11,200 --> 02:05:14,080
Speaker 1: So AOS and Jill Stein have been feuding at Jill

2783
02:05:14,120 --> 02:05:16,720
Speaker 1: Stein of course being the nominee for the Green Party,

2784
02:05:16,880 --> 02:05:19,160
Speaker 1: and in the midst of this feud she has now

2785
02:05:19,200 --> 02:05:22,040
Speaker 1: gone on the Breakfast Club and had pretty.

2786
02:05:21,920 --> 02:05:24,320
Speaker 4: Like pretty heated exchange.

2787
02:05:23,840 --> 02:05:27,320
Speaker 1: With Democrat Artisan Angela Rye. Let's take a listen to

2788
02:05:27,400 --> 02:05:28,400
Speaker 1: a little bit of how that went.

2789
02:05:28,680 --> 02:05:31,920
Speaker 6: And it is the talking point of AOC the other day,

2790
02:05:31,960 --> 02:05:35,080
Speaker 6: who is taking her marching orders from the DNC. This

2791
02:05:35,200 --> 02:05:38,440
Speaker 6: is exactly what they say, that we are only running

2792
02:05:38,480 --> 02:05:39,640
Speaker 6: for president.

2793
02:05:39,280 --> 02:05:42,000
Speaker 18: Color as parenting talking points instead of us looking at

2794
02:05:42,000 --> 02:05:44,040
Speaker 18: basic math. The one thing that AOC has done that

2795
02:05:44,120 --> 02:05:47,400
Speaker 18: you haven't is win some election. How many voting members

2796
02:05:47,440 --> 02:05:51,800
Speaker 18: in the United States House of Representatives Republican, Democrat and independent?

2797
02:05:51,880 --> 02:05:52,560
Speaker 3: How many total?

2798
02:05:53,120 --> 02:05:54,480
Speaker 6: How many total are there?

2799
02:05:54,600 --> 02:05:56,480
Speaker 4: What is it six hundred some?

2800
02:05:56,920 --> 02:05:58,640
Speaker 18: No, no, it's four hundred and thirty five.

2801
02:05:58,720 --> 02:06:00,839
Speaker 6: But I would like to respond this is the framing

2802
02:06:01,200 --> 02:06:05,320
Speaker 6: of the empire and the oligarchy and white supremacy and colonialism,

2803
02:06:05,320 --> 02:06:07,880
Speaker 6: which wants you to feel that resistance is futile. This

2804
02:06:08,000 --> 02:06:09,200
Speaker 6: is about a voter blaming.

2805
02:06:12,480 --> 02:06:15,280
Speaker 18: No, what you're not going to say is that I'm

2806
02:06:15,280 --> 02:06:18,640
Speaker 18: ever imperiading anything at the hands of white supremacy. This

2807
02:06:18,720 --> 02:06:20,800
Speaker 18: is something that's very different. This is me asking you

2808
02:06:20,840 --> 02:06:21,560
Speaker 18: again it's a bible.

2809
02:06:21,640 --> 02:06:26,960
Speaker 3: I'm just the same talking points you get.

2810
02:06:27,200 --> 02:06:29,200
Speaker 18: This is not DNC talking points. This is my research

2811
02:06:29,240 --> 02:06:31,440
Speaker 18: and sadly for you, the research says you have never

2812
02:06:31,480 --> 02:06:32,080
Speaker 18: won an election.

2813
02:06:32,360 --> 02:06:34,360
Speaker 1: All right, so lot to say about that piece. I

2814
02:06:34,400 --> 02:06:36,760
Speaker 1: also want to show you those were some of the pieces.

2815
02:06:36,360 --> 02:06:39,000
Speaker 4: That were being shared by liberals who are.

2816
02:06:38,920 --> 02:06:40,080
Speaker 3: On the Yeah.

2817
02:06:40,080 --> 02:06:42,720
Speaker 1: I mean, listen, you should know how many members are

2818
02:06:42,720 --> 02:06:47,080
Speaker 1: Congress there are that that is legitimately embarrassing. The piece

2819
02:06:47,160 --> 02:06:49,640
Speaker 1: that doctor jistein herself wanted to share, let me go

2820
02:06:49,640 --> 02:06:51,760
Speaker 1: ahead and show you now where she talks more about,

2821
02:06:51,800 --> 02:06:54,080
Speaker 1: you know, her point of view and why she.

2822
02:06:54,080 --> 02:06:55,800
Speaker 4: Believes that you should vote for the Green Party. Let's

2823
02:06:55,840 --> 02:06:56,320
Speaker 4: take a loss on.

2824
02:06:56,560 --> 02:06:59,800
Speaker 6: Every vote cast for our campaign. Is a vote against

2825
02:07:00,640 --> 02:07:04,520
Speaker 6: is a shot across the bow of the endless war machine.

2826
02:07:04,560 --> 02:07:07,680
Speaker 6: To say that we the people are getting organized, we

2827
02:07:07,720 --> 02:07:11,720
Speaker 6: are moving forward, we are growing, We have organization and

2828
02:07:11,760 --> 02:07:14,480
Speaker 6: infrastructure that we have never had before. We've never been

2829
02:07:14,520 --> 02:07:17,720
Speaker 6: able to break through like we are now because Green's

2830
02:07:17,720 --> 02:07:19,120
Speaker 6: have been ahead of the curve on a lot of

2831
02:07:19,160 --> 02:07:22,800
Speaker 6: things like climate change, on reparations, on healthcare as a

2832
02:07:22,880 --> 02:07:23,440
Speaker 6: human right.

2833
02:07:23,760 --> 02:07:25,920
Speaker 1: And I do think that is one of the most

2834
02:07:25,920 --> 02:07:29,600
Speaker 1: compelling arguments you can make for the Green Party is

2835
02:07:30,040 --> 02:07:33,600
Speaker 1: number one, Trump and Kamala Harris, like Kamala Harris's vice

2836
02:07:33,640 --> 02:07:36,120
Speaker 1: president to Joe Biden, both of them are pro genocide,

2837
02:07:36,160 --> 02:07:39,320
Speaker 1: so as just like a moral issue, there are certainly

2838
02:07:39,360 --> 02:07:42,960
Speaker 1: a significant number of people, especially Muslim Americans, who just

2839
02:07:43,000 --> 02:07:45,440
Speaker 1: say I can't support that. I don't care if you

2840
02:07:45,480 --> 02:07:47,520
Speaker 1: are lesser, evil, whatever, I just can't support it. And

2841
02:07:47,560 --> 02:07:51,000
Speaker 1: then the other piece that I think is her most

2842
02:07:51,040 --> 02:07:54,840
Speaker 1: compelling argument is like, listen, we by being out there

2843
02:07:55,000 --> 02:07:58,080
Speaker 1: as a sort of protest party, we have pushed the

2844
02:07:58,120 --> 02:08:03,560
Speaker 1: conversation on this set of issues around climate change, around reparations,

2845
02:08:03,760 --> 02:08:08,160
Speaker 1: around you know, sort of pushing the Overton window of

2846
02:08:08,320 --> 02:08:10,760
Speaker 1: what can be discussed in American politics. And I think

2847
02:08:10,800 --> 02:08:12,840
Speaker 1: that's legitimate. I think there is a real case to

2848
02:08:12,880 --> 02:08:14,760
Speaker 1: be made for that. To get back to a little

2849
02:08:14,760 --> 02:08:17,040
Speaker 1: bit of the AOC part, here's part of the argument

2850
02:08:17,120 --> 02:08:19,440
Speaker 1: she's been making against jill Stein. She says, nobody needs

2851
02:08:19,480 --> 02:08:21,640
Speaker 1: talking points to know jill Stein hasn't won so much

2852
02:08:21,640 --> 02:08:24,000
Speaker 1: as a bingo game. If you actually give a damn

2853
02:08:24,040 --> 02:08:27,360
Speaker 1: about people, you organize, build power and infrastructure and win.

2854
02:08:28,240 --> 02:08:31,160
Speaker 1: Keith Ellison, the Attorney General of Minnesota, also going in

2855
02:08:31,240 --> 02:08:32,800
Speaker 1: on jill Stein for some reason.

2856
02:08:32,800 --> 02:08:34,200
Speaker 4: At this point. He says, if you've ever.

2857
02:08:34,080 --> 02:08:37,320
Speaker 1: Been annoyed by politicians who only show up at election time,

2858
02:08:37,360 --> 02:08:39,240
Speaker 1: then you've got to be annoyed with doctor jill Stein.

2859
02:08:39,280 --> 02:08:42,720
Speaker 1: She claims to be an unconventional alternative, but she's nauseatingly conventional.

2860
02:08:43,120 --> 02:08:46,160
Speaker 1: She shows up every four years making lavish promises, but

2861
02:08:46,200 --> 02:08:50,560
Speaker 1: has no record of producing anything except Republican victories, hard

2862
02:08:50,680 --> 02:08:53,160
Speaker 1: pass and the last thing I'll share with you, which

2863
02:08:53,200 --> 02:08:56,480
Speaker 1: could be a key to why you see, you know,

2864
02:08:56,560 --> 02:08:59,400
Speaker 1: democratic attacks against jill Stein not just from Keith Ellison

2865
02:08:59,400 --> 02:09:01,560
Speaker 1: and EOC, but from others as well. At this point

2866
02:09:01,600 --> 02:09:05,120
Speaker 1: in Time's put this up on the screen. Polling suggests

2867
02:09:05,120 --> 02:09:09,560
Speaker 1: that she's doing quite well among Muslim American voters. This

2868
02:09:09,640 --> 02:09:12,640
Speaker 1: is from the Council on American Islamic Relations. It shows her,

2869
02:09:12,960 --> 02:09:15,680
Speaker 1: this is Yashar Ali who's tweeting this shows her getting

2870
02:09:15,680 --> 02:09:19,360
Speaker 1: a solid share of their votes in key battleground states.

2871
02:09:19,600 --> 02:09:23,680
Speaker 1: So in Arizona you've got Jill Stein actually leading the

2872
02:09:23,720 --> 02:09:27,400
Speaker 1: field among Muslim voters thirty five percent. Also in Michigan

2873
02:09:27,800 --> 02:09:32,160
Speaker 1: critically forty percent. She's winning among Muslim voters. Pennsylvania twenty

2874
02:09:32,200 --> 02:09:36,160
Speaker 1: five percent, Wisconsin forty four percent. Again, that's another state

2875
02:09:36,200 --> 02:09:40,120
Speaker 1: where she actually leads the field among Muslim voters. So

2876
02:09:41,000 --> 02:09:42,720
Speaker 1: you know, as a percent of the population, you're talking

2877
02:09:42,760 --> 02:09:46,160
Speaker 1: about a relatively small slice, but small slice could make

2878
02:09:46,160 --> 02:09:47,800
Speaker 1: a difference in some of these key states.

2879
02:09:47,920 --> 02:09:50,840
Speaker 2: Zaber, Yeah, absolutely, I don't know exactly what we were

2880
02:09:50,840 --> 02:09:54,400
Speaker 2: talking about the motivation here. Yeah, Keith Ellison and AOC,

2881
02:09:54,720 --> 02:09:57,840
Speaker 2: I mean, the problem for AOC and Keith Ellison is

2882
02:09:57,880 --> 02:10:01,000
Speaker 2: that they're the exact people who run up against this

2883
02:10:01,120 --> 02:10:04,880
Speaker 2: like party line talk and now are enforcers of it.

2884
02:10:05,200 --> 02:10:08,240
Speaker 2: So you, in my I mean, you actually have less credibility.

2885
02:10:08,320 --> 02:10:10,440
Speaker 2: So like the people who attack Jill Stein, who are

2886
02:10:10,480 --> 02:10:13,560
Speaker 2: just democratic apparatrics, I'm like, yeah, that's fair. Like you know,

2887
02:10:13,600 --> 02:10:15,920
Speaker 2: it's like you people believe that the party is a

2888
02:10:15,960 --> 02:10:19,520
Speaker 2: solution to everything. But AOC you know, went on the

2889
02:10:19,600 --> 02:10:23,360
Speaker 2: DNC stage and said Kam was working tirelessly for a ceasefire,

2890
02:10:23,880 --> 02:10:26,560
Speaker 2: as in trying to like fool Gaza.

2891
02:10:26,200 --> 02:10:29,919
Speaker 3: Voters, even a voter. I'm like, that's yeah, bullshit.

2892
02:10:30,040 --> 02:10:33,280
Speaker 2: You know, like you you are trying to message to

2893
02:10:33,280 --> 02:10:37,480
Speaker 2: people incorrectly and lie to them, and Jill Stein is

2894
02:10:37,520 --> 02:10:39,800
Speaker 2: telling them the truth. I don't think there's or at

2895
02:10:39,880 --> 02:10:42,080
Speaker 2: least the truth in the way that they believe it.

2896
02:10:42,480 --> 02:10:46,640
Speaker 2: And that's something that let's take the election out of it,

2897
02:10:46,960 --> 02:10:49,240
Speaker 2: as you would probably be on Jill Stein's side if

2898
02:10:49,240 --> 02:10:51,400
Speaker 2: there was no Commo, there was no Trump, there was

2899
02:10:51,400 --> 02:10:53,320
Speaker 2: no election, Like let's say this was happening in twenty

2900
02:10:53,440 --> 02:10:55,800
Speaker 2: twenty one. I'm not so sure that she takes a

2901
02:10:55,840 --> 02:10:58,120
Speaker 2: current posture that she is right now and the stakes

2902
02:10:58,120 --> 02:11:01,680
Speaker 2: weren't as diff as different on other issues. So that's

2903
02:11:01,680 --> 02:11:03,560
Speaker 2: where I kind of have an issue where you know,

2904
02:11:03,600 --> 02:11:06,600
Speaker 2: you previously ran a guest system. Now your systemic enforce her,

2905
02:11:06,800 --> 02:11:10,640
Speaker 2: and you're actively using your old image as a revolutionary

2906
02:11:10,680 --> 02:11:13,040
Speaker 2: to go after a chess sign and a third party.

2907
02:11:13,080 --> 02:11:13,720
Speaker 3: I think that's wrong.

2908
02:11:14,240 --> 02:11:18,120
Speaker 1: Yeah, I think that at this point I mean, I

2909
02:11:18,200 --> 02:11:20,960
Speaker 1: just I think we need to see AOC as decided

2910
02:11:21,240 --> 02:11:25,040
Speaker 1: that she is going to try to work within the system, right,

2911
02:11:25,120 --> 02:11:28,160
Speaker 1: that's her political She previously had a different political theory

2912
02:11:28,160 --> 02:11:31,200
Speaker 1: of change, which was much more adversarial, and she does

2913
02:11:31,240 --> 02:11:33,480
Speaker 1: not hold that theory of political change anymore, at least

2914
02:11:33,480 --> 02:11:35,480
Speaker 1: she does not act on that theory of political change.

2915
02:11:35,480 --> 02:11:37,680
Speaker 1: So I guess I don't see her that different from

2916
02:11:37,680 --> 02:11:40,000
Speaker 1: any other like Democratic Party apparatic.

2917
02:11:40,160 --> 02:11:41,879
Speaker 4: She is a Democratic Party partisan.

2918
02:11:41,880 --> 02:11:43,560
Speaker 3: But you and I follow this day to day. Oh yeah,

2919
02:11:43,600 --> 02:11:44,600
Speaker 3: average person is not going.

2920
02:11:44,520 --> 02:11:46,000
Speaker 1: To be Yeah, I mean, I guess what I would

2921
02:11:46,040 --> 02:11:49,120
Speaker 1: say is a few things. Number one, I don't think

2922
02:11:49,120 --> 02:11:51,160
Speaker 1: that this is an intellig I don't think this is

2923
02:11:51,200 --> 02:11:53,360
Speaker 1: forty tests from AOC. I don't think this is an

2924
02:11:53,360 --> 02:12:01,560
Speaker 1: intelligence strategy because people who have very genuine, extremely legitimate

2925
02:12:01,760 --> 02:12:06,280
Speaker 1: moral concerns about voting for a candidate who support a genocide,

2926
02:12:06,720 --> 02:12:08,920
Speaker 1: Like if you're just yelling at them and shaming them

2927
02:12:09,040 --> 02:12:10,840
Speaker 1: and how kid you and they're just you know, Jill

2928
02:12:10,880 --> 02:12:13,960
Speaker 1: Stein's an idiot, Like, I don't think that that's an

2929
02:12:13,960 --> 02:12:16,840
Speaker 1: effective pitch. I think you're more likely to harden them

2930
02:12:16,960 --> 02:12:21,080
Speaker 1: against the Democratic Party or harden their commitment to voting

2931
02:12:21,120 --> 02:12:24,520
Speaker 1: Green parties, so on efficacy, I think it's foolish. There's

2932
02:12:24,520 --> 02:12:27,480
Speaker 1: something about this conversation that I've been thinking about that

2933
02:12:29,160 --> 02:12:31,920
Speaker 1: really kind of drives me crazy on both sides. Which

2934
02:12:32,720 --> 02:12:35,200
Speaker 1: for doctor Jill Stein, like I understand her position too.

2935
02:12:35,280 --> 02:12:36,960
Speaker 1: She's trying to win votes for the Green Party and

2936
02:12:36,960 --> 02:12:38,680
Speaker 1: that's her job, and she's you know, she's going to

2937
02:12:38,720 --> 02:12:40,520
Speaker 1: go out there and make her case and make the

2938
02:12:40,520 --> 02:12:43,600
Speaker 1: most compelling case she can as well. But there's a

2939
02:12:43,640 --> 02:12:47,720
Speaker 1: discourse around this that assumes that there is a good

2940
02:12:47,760 --> 02:12:50,960
Speaker 1: answer to this question, and that that's like there is

2941
02:12:51,040 --> 02:12:53,160
Speaker 1: one answer. Either the right thing to do as a

2942
02:12:53,240 --> 02:12:55,080
Speaker 1: lefty is to vote for Kam Layers, or the right

2943
02:12:55,080 --> 02:12:56,680
Speaker 1: thing to do as a lefty is to vote for

2944
02:12:56,800 --> 02:12:59,800
Speaker 1: the Green Party. There's a lot of certainty and a

2945
02:13:00,080 --> 02:13:04,080
Speaker 1: lot of like moral outrage around this, and I think

2946
02:13:04,120 --> 02:13:06,800
Speaker 1: it is more likely that there just is no good

2947
02:13:06,800 --> 02:13:09,680
Speaker 1: answer here, Like you're kind of checkmated. That's how I

2948
02:13:09,720 --> 02:13:13,320
Speaker 1: feel like. On the one hand, I think there are

2949
02:13:13,360 --> 02:13:17,080
Speaker 1: a lot of very compelling and troubling reasons why I

2950
02:13:17,120 --> 02:13:18,840
Speaker 1: do not want to see Donald Trump back in the

2951
02:13:18,880 --> 02:13:21,000
Speaker 1: White House. I think those reasons have been on full

2952
02:13:21,040 --> 02:13:23,920
Speaker 1: display over the past number of weeks, I think he

2953
02:13:24,000 --> 02:13:26,760
Speaker 1: would be worse on Israel. Even if that is like

2954
02:13:26,800 --> 02:13:29,120
Speaker 1: the narrow lens of your focus, I think there's something

2955
02:13:29,160 --> 02:13:30,920
Speaker 1: powerful and like the French model of this, sort of

2956
02:13:30,960 --> 02:13:33,520
Speaker 1: like anti right wing coalition or you could say anti

2957
02:13:33,560 --> 02:13:36,200
Speaker 1: fascist coalition that came together to defeat the right wing

2958
02:13:36,280 --> 02:13:42,040
Speaker 1: party there. But ultimately, also you're asking people to do

2959
02:13:42,160 --> 02:13:46,040
Speaker 1: something that is morally very difficult, and that doesn't move

2960
02:13:46,080 --> 02:13:49,360
Speaker 1: you away from the fundamental dynamics of lesser evil voting

2961
02:13:49,520 --> 02:13:52,600
Speaker 1: over a long period of time. But it also is

2962
02:13:52,640 --> 02:13:54,560
Speaker 1: not clear to me that a vote for the Green

2963
02:13:54,560 --> 02:13:57,160
Speaker 1: Party is any sort of a magic bullet either, like

2964
02:13:57,200 --> 02:14:00,880
Speaker 1: a silver bullet either, because the point of look, you

2965
02:14:00,960 --> 02:14:03,120
Speaker 1: have been running the strategy for a number of years

2966
02:14:03,160 --> 02:14:06,000
Speaker 1: and it hasn't disrupted the duopoly. Like the result of

2967
02:14:06,040 --> 02:14:08,480
Speaker 1: you getting a significant number of votes in twenty sixteen

2968
02:14:08,960 --> 02:14:12,080
Speaker 1: was the Democratic Party crushing the left and moving further

2969
02:14:12,160 --> 02:14:14,240
Speaker 1: to the right. So it's not like that strategy has

2970
02:14:14,240 --> 02:14:19,000
Speaker 1: paid off either. So I think in these like electoral calculations,

2971
02:14:19,320 --> 02:14:20,360
Speaker 1: in some ways.

2972
02:14:21,560 --> 02:14:23,160
Speaker 4: It's a misplaced focus.

2973
02:14:23,320 --> 02:14:25,760
Speaker 1: The better place to focus is probably on, you know,

2974
02:14:25,800 --> 02:14:28,840
Speaker 1: building a powerful labor movement and those sort of you know,

2975
02:14:28,920 --> 02:14:32,880
Speaker 1: democratic organizing, because I don't think either one of the

2976
02:14:33,000 --> 02:14:37,560
Speaker 1: answers to the narrow electoral question are particularly like the

2977
02:14:37,640 --> 02:14:39,000
Speaker 1: answer or a good answer.

2978
02:14:39,440 --> 02:14:39,640
Speaker 3: Yeah.

2979
02:14:39,680 --> 02:14:42,120
Speaker 2: Fair, But then it's about strategy too. I think Jill

2980
02:14:42,160 --> 02:14:44,360
Speaker 2: Stein was on one operating in the way that she's

2981
02:14:44,400 --> 02:14:47,080
Speaker 2: supposed to, which is, I'm trying to win votes. The

2982
02:14:47,120 --> 02:14:49,840
Speaker 2: AOC one is a negative one of like, no, you

2983
02:14:49,920 --> 02:14:53,040
Speaker 2: shouldn't because this is And in general, I think that

2984
02:14:53,040 --> 02:14:55,840
Speaker 2: comes back to voter shaming. Yeah, I think voter shaming

2985
02:14:55,920 --> 02:14:59,160
Speaker 2: is bad. I think, especially in a democratic.

2986
02:14:58,840 --> 02:15:01,480
Speaker 4: I mean it's bad, and I think it's counterproductive.

2987
02:15:01,600 --> 02:15:03,560
Speaker 3: Yes, yeah, oh yeah, Because there's also a lot.

2988
02:15:03,480 --> 02:15:05,720
Speaker 1: Of voter shaming that goes in the other direction, not

2989
02:15:05,760 --> 02:15:08,800
Speaker 1: from Jill Stein, but of people who are weighing this

2990
02:15:08,920 --> 02:15:12,280
Speaker 1: calculation and in the balance want to vote for Kamala Harris.

2991
02:15:12,400 --> 02:15:14,240
Speaker 1: There is a lot of voter shaming at them as well.

2992
02:15:14,280 --> 02:15:14,400
Speaker 10: Well.

2993
02:15:14,440 --> 02:15:18,640
Speaker 2: For that's kind of stupid too, Yeah, looking shaming people

2994
02:15:18,680 --> 02:15:21,839
Speaker 2: because how they vote is dumb, very counterproductive, and historically

2995
02:15:21,880 --> 02:15:24,080
Speaker 2: it does not work. It makes people dig in even

2996
02:15:24,160 --> 02:15:27,080
Speaker 2: more and in general, you're just not you know. Somebody

2997
02:15:27,080 --> 02:15:29,280
Speaker 2: asked a question of recently and they were like, should

2998
02:15:29,280 --> 02:15:32,560
Speaker 2: news commentators have to disclose who they vote for? And

2999
02:15:32,600 --> 02:15:34,760
Speaker 2: it actually made me realize and like, who you vote

3000
02:15:34,760 --> 02:15:37,839
Speaker 2: for actually does not tell you all that much interesting

3001
02:15:37,840 --> 02:15:40,800
Speaker 2: stuff about you. For example, if Dick Cheney is voting

3002
02:15:40,840 --> 02:15:43,360
Speaker 2: for Kamala and AOC is voting for Kamala, or, do

3003
02:15:43,440 --> 02:15:46,800
Speaker 2: those two things give you like an accurate representation of

3004
02:15:46,880 --> 02:15:49,000
Speaker 2: their like full sit views. I mean, some people could

3005
02:15:49,040 --> 02:15:51,840
Speaker 2: say yes, right, but I don't think actually it is.

3006
02:15:52,080 --> 02:15:54,800
Speaker 2: So Instead, you need to look at issues and various

3007
02:15:54,840 --> 02:15:57,120
Speaker 2: reasons why. Let's say Muslim people are going to be

3008
02:15:57,200 --> 02:15:58,960
Speaker 2: voting for Jill Stein, you might be.

3009
02:15:58,880 --> 02:16:00,000
Speaker 3: Making a pretty damn good case.

3010
02:16:00,440 --> 02:16:04,240
Speaker 2: And if the case is telling them a lie Comma's

3011
02:16:04,240 --> 02:16:07,600
Speaker 2: working tilesty for a ceasefire, yeah, instead of hey, Trump

3012
02:16:07,600 --> 02:16:08,840
Speaker 2: will be way worse on Israel.

3013
02:16:08,920 --> 02:16:11,360
Speaker 3: I mean that's actually not a bad case, right, Yeah.

3014
02:16:11,400 --> 02:16:14,320
Speaker 3: I mean sometimes it's an honest case. It's very important. Yeah.

3015
02:16:14,320 --> 02:16:17,440
Speaker 2: For example, if you're pro Trump, or or if you

3016
02:16:17,440 --> 02:16:19,200
Speaker 2: were one of those people who's like I wanted Trump

3017
02:16:19,280 --> 02:16:22,720
Speaker 2: to do X, Y and Z, the common retort from

3018
02:16:22,720 --> 02:16:25,000
Speaker 2: the right is like, okay, dude, but Kamala is going

3019
02:16:25,040 --> 02:16:27,640
Speaker 2: to be ten times worse and you know, what they're

3020
02:16:27,680 --> 02:16:30,760
Speaker 2: not wrong. That's a fine enough case. Sometimes I don't

3021
02:16:30,760 --> 02:16:33,080
Speaker 2: want to live that way. But that is true, and

3022
02:16:33,400 --> 02:16:35,440
Speaker 2: same true on the Israel issue. But then you should

3023
02:16:35,440 --> 02:16:38,119
Speaker 2: be saying that and not she's doing the best possible

3024
02:16:38,160 --> 02:16:40,080
Speaker 2: job that she can, cause that's bullshit too. Yeah, and

3025
02:16:40,120 --> 02:16:41,240
Speaker 2: that's what bugs that's what.

3026
02:16:41,160 --> 02:16:41,720
Speaker 3: Actually bugs me.

3027
02:16:41,879 --> 02:16:43,080
Speaker 1: Yes, I agree with all of that.

3028
02:16:43,280 --> 02:16:45,680
Speaker 3: All right, Uh wow, long show today. I hope you

3029
02:16:45,680 --> 02:16:46,360
Speaker 3: guys enjoyed it.

3030
02:16:46,440 --> 02:16:48,199
Speaker 2: We have plenty of We actually had to drop some stuff,

3031
02:16:48,200 --> 02:16:49,440
Speaker 2: so we're gonna have even more tomorrow.

3032
02:16:49,640 --> 02:16:52,200
Speaker 1: We've already basically got it to the show ready to

3033
02:16:52,240 --> 02:16:52,960
Speaker 1: go for tomorrow.

3034
02:16:53,120 --> 02:16:53,640
Speaker 3: We'll see you that