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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.

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Speaker 3: But enough with that, let's get to the show.

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Speaker 2: Hello, everybody, we just watched that major presidential debate. Emily

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Speaker 2: unfortunately had to step away, but three of us will

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Speaker 2: hold down the ford.

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Speaker 3: I'll be extra loud, all right, double the analysis.

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Speaker 2: I'm sure that's not a problem for me, but in general,

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Speaker 2: certainly something some major moments. We've got a couple of

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Speaker 2: clips and other things that we can break down for everybody.

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Speaker 2: Will be taking some questions throughout the stream from our

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Speaker 2: supremium subscribers, so make sure you sign up Breakingpoints dot

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Speaker 2: com if you want to be able to take advantage.

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Speaker 2: But before we get to that, and even to some

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Speaker 2: of the clips, why don't we just give our general impressions.

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Speaker 3: Chrystal, what do you.

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Speaker 1: Think came in wanting to make this a referendum on Trump,

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Speaker 1: and she succeeded. Yes, she basically called every shot in

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Speaker 1: terms of what the topics, what the focus would be,

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Speaker 1: what he would have to respond to. She maintained an

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Speaker 1: affect of laughing in his face and rolling her eyes.

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Speaker 1: He was pissed off and angry almost from the jump.

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Speaker 1: And so, you know, I think for her this was

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Speaker 1: about as good a performance as possible. She was well

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Speaker 1: prepared and took it seriously and took him seriously. And

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Speaker 1: I don't think that he took her seriously. And it

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Speaker 1: showed he you know, he took the bait on every look,

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Speaker 1: whether it was his rallies or his indictments, or even

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Speaker 1: the Central Park five or his net worth that he

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Speaker 1: inherited from his dad. He was chasing after every single

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Speaker 1: ball that she was throwing.

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Speaker 2: Yeah, let me pick up on that, because I think

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Speaker 2: this is a really key point, and it's one where

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Speaker 2: I'm already and see amongst our right wing audience, the

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Speaker 2: ones that remain and others, is there is a tremendous

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Speaker 2: amount of outrage about the moderators and about ABC. And

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Speaker 2: I think we'll talk about this about how the fact

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Speaker 2: that these moderators did interject multiple times to quote unquote

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Speaker 2: fact check Trump. Many of the questions were frankly ridiculous

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Speaker 2: in my opinion, Like Tamo, if you ever met with Putin,

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Speaker 2: it was like, come on, what are we doing? Okay,

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Speaker 2: let's put that aside. Complaining about moderators is cope when

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Speaker 2: your candidate also did. You had multiple opportunities where you

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Speaker 2: took the bait, where you whiffed on the best answers,

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Speaker 2: where Kamala what I want to pick up on from

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Speaker 2: what you said, was totally in control every single time.

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Speaker 2: It was her worst issue. She puts a little bit

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Speaker 2: of bait in there that Trump is going to pick

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Speaker 2: up on, and he runs with it. The border section

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Speaker 2: was infuriating to me watching and waiting. This is a

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Speaker 2: This is the part where Trump is leading against Harris

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Speaker 2: as much as Harris is leading Trump on abortion.

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Speaker 3: I haven't even mentioned Trump's disastrous abortion PA.

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Speaker 4: We yeah, we got that.

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Speaker 3: We will have that company as well. But actually that's

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Speaker 3: a perfect example.

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Speaker 2: When I put them side by side on the abortion one,

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Speaker 2: Trump is all over the place giving the worst answers

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Speaker 2: humanly possible. All the stuff that she's tried to do previously,

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Speaker 2: none of it has worked. He doesn't try and bag

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Speaker 2: Kamma or move the direction. Kama brings up a border

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Speaker 2: the very first, the first border question, she.

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Speaker 3: Starts talking about his rally size.

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Speaker 2: Now we're litigating rallies during the damn border section and

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Speaker 2: then during every single other one, which was very good

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Speaker 2: for Kama or sorry, very good for Trump, any issue area.

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Speaker 2: Kamala lays as much bait in there as possible, and

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Speaker 2: Trump takes it, and he takes it and he whiffs it.

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Speaker 2: He validates every concern that she drops of. He only

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Speaker 2: cares about himself by litigating his rally size instead of

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Speaker 2: talking about the border and litigating his inheritance, instead of

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Speaker 2: talking about well, I don't even remember that about.

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Speaker 1: Her flip fluffing, ye, So that you're right, that's what

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Speaker 1: it was.

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Speaker 3: It was about cracking and flipbloff for me. And I'm

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Speaker 3: sitting here losing my mind being like, dude, what are

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Speaker 3: you doing?

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Speaker 2: And so, in general, yes, we're the moderator's biased. Yeah

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Speaker 2: I think so, But you know you're just going to

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Speaker 2: come across as a whiny baby, you know, only focusing

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Speaker 2: on that when you went into this, you voluntarily accepted

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Speaker 2: and honestly worse. Even within that bad framework, they gave

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Speaker 2: you a chance to shine where you.

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Speaker 3: Could have if he wanted to.

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Speaker 2: You've been in many you know, bias debates before, and

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Speaker 2: he screwed it. I mean, he absolutely whifted on every

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Speaker 2: major issue that was best for him.

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Speaker 1: I want to get Ryan, but real quick, what that

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Speaker 1: reminded me of. Remember the famous Newt Gingridge, Oh course

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Speaker 1: moment where John King asked him this question about he

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Speaker 1: had like asked his wife for an open marriage while

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Speaker 1: she had cancer.

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Speaker 4: I mean, it was a horrible thing.

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Speaker 1: You did, right, But they open up with this question, right,

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Speaker 1: and Newt Gingrich goes in on the moderators and turns

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Speaker 1: it into a great moment. If you're Donald Trump, you

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Speaker 1: come in knowing the moderators are probably going to be

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Speaker 1: asking her easier questions. Might do it be doing a

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Speaker 1: little fact check? Trump at the top of his game,

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Speaker 1: not only handles that, but turns that into an asset.

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Speaker 5: Yeah, he's a deeply wounded man. Like for him across

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Speaker 5: for him not to be able to let anything slide,

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Speaker 5: like nothing, even with the presidency in his grasp, the

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Speaker 5: depth of insecurity he must feel in whatever soul he

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Speaker 5: has inside of him to not just your point is

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Speaker 5: exactly right that they're talking about her flip flops, they're

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Speaker 5: talking about the border these it's a ninety minute debate.

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Speaker 5: These are going to be the rounds where you have

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Speaker 5: to score the most amount of points.

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Speaker 4: Right, they're all tilted in your favor.

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Speaker 5: He's just pummeling her in these rounds. Instead, they're not

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Speaker 5: leaving my rally earlier, and they don't even go to

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Speaker 5: her rallies. In fact, they're fake, Like she went into

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Speaker 5: the fake thing. They're paying AI, fake AI people to

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Speaker 5: go to her rallies, and yeah, exactly. Then you're like,

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Speaker 5: it's like, what are we even talking about now? I

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Speaker 5: don't remember.

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Speaker 2: It was actually during the flip flop, during the border section,

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Speaker 2: they were litigating Donald Trump's cases.

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Speaker 3: Excuse me, because excuse me.

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Speaker 1: He took the opening him saying something about bibles to

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Speaker 1: be like, let me tell you about criminals this guy

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Speaker 1: right here, and of course he goes, you know, all

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Speaker 1: in and you know, same thing.

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Speaker 4: Uh.

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Speaker 1: The January sixth section was also disastrous for him because

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Speaker 1: he gets asked the question, he gets asked, He gets

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Speaker 1: asked the question, Okay, you said for a long time

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Speaker 1: that he won by a landslide. In the past several weeks,

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Speaker 1: you said, you know that you lost by whisker, and

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Speaker 1: seemed to admit that you lost. No, I didn't admit

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Speaker 1: that I was being sarcastic. I won by a lance

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Speaker 1: and then good goes in although the core cases and

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Speaker 1: they were biased and there was so much evidence. I

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Speaker 1: mean again, spending time and energy relitigating one of the

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Speaker 1: things people hate about you, No, I mean his the

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Speaker 1: other the the other thing about the demeanor of the

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Speaker 1: two of them, I think was important as well, because

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Speaker 1: you know, some of a lot of this is optics,

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Speaker 1: and one of the things we said is she needs

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Speaker 1: to maintain this sort of like, you know, rolling her eyes,

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Speaker 1: being above the fray, looking down her note, making him small.

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Speaker 4: And she did that.

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Speaker 1: Her facial expressions were very relaxed. She was the one

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Speaker 1: that was having fun at his expense. That's a real

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Speaker 1: role reversal. If you think back to how much fun

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Speaker 1: he had at Hillary Clinton's expense, how much fun he

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Speaker 1: had at Lil Marco's expense, how much fun he had

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Speaker 1: at Low Energy Jeb Bush's expense. He was not having

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Speaker 1: any fun up there tonight. And you know that's one

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Speaker 1: of his comedic his ability to play to an audience,

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Speaker 1: play to a crowd, that is his superpower, and that

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Speaker 1: was wholly absent to me.

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Speaker 5: Yeah, I totally did what she That's hard to do

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Speaker 5: for her to kind of ridicule him without looking petty

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Speaker 5: or like a jerk, Like there's a very fine line

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Speaker 5: to walk there, And she didn't really come off as

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Speaker 5: a jerk at all, Like she came off as like

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Speaker 5: exactly like you said, like she she hit that well.

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Speaker 3: Yeah, And for.

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Speaker 5: People who didn't follow the Lex Friedman interview or didn't

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Speaker 5: listen to Lex preopid interview, you know, he's one of

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Speaker 5: these guys who is like, I love a lot of

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Speaker 5: things about you, but I don't like January sixth. I

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Speaker 5: don't like that you challenge the election, and why can't

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Speaker 5: you just say that you lost? And clearly either he

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Speaker 5: was ready to pan or his advisors were like, please,

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Speaker 5: just please, I'm gonna want to ask you about this,

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Speaker 5: Please just say you lost and he and he finally says,

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Speaker 5: I lost by a whisker, right, And it was absolutely

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Speaker 5: not being sarcastic.

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Speaker 3: Right, And he was not listen to it.

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Speaker 2: I listened to it multiple times genuinely kind of a

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Speaker 2: historic moment, and I was like, well, maybe this is

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Speaker 2: a new strategy.

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Speaker 3: This behind it.

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Speaker 2: And then I mean, this is the thing, and you know,

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Speaker 2: I'll say this too. JD. Just today did they all

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Speaker 2: in summit and they asked him, would you have certified

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Speaker 2: the election? He's like, no, I would have had an

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Speaker 2: alternate state. I'm like, okay, here we go like he's like,

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Speaker 2: this is what we want to do. This is what

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Speaker 2: we want to do. This is what we want to

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Speaker 2: do two months before the election. Okay, this is this

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Speaker 2: is it is what we've decided to go with two

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Speaker 2: months before the election. The number one reason why a

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Speaker 2: lot of suburban people voted against you in twenty twenty two, right,

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Speaker 2: arguably one of the huge hits on him in that race.

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Speaker 1: But you need no high I can't really blame JD

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Speaker 1: because I think a big part of the reason he

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Speaker 1: got the vice presidential gig is because he had said

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Speaker 1: that before totally. And there's like like, that's why he's

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Speaker 1: in the slot.

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Speaker 4: So he's like, this is my job, just sick.

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Speaker 2: How about we just don't say it? How about we

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Speaker 2: just talk about the border again. We're like, oh, you know,

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Speaker 2: that's an interesting thing. We should talk about the board and Trump.

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Speaker 2: Trump could have told JD. Look, yeah, I know you've

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Speaker 2: said that and I got you on the ticket. Well

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Speaker 2: we're done with that.

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Speaker 5: We're moving on.

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Speaker 2: And another thing is that he inexplicably disavowsed JD Vans,

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Speaker 2: who gave him the greatest lay up of all time,

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Speaker 2: and he said JD said, yeah, he would veto a

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Speaker 2: national abortion maan. So they asked him about it, like, hey,

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Speaker 2: JD says, you're going to veto a national abortion ban.

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Speaker 2: And he's like, well, in fairness, we hadn't discussed it. Yeah,

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Speaker 2: let's keep the door open to what a six percent policy?

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Speaker 3: What are we doing here?

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Speaker 2: It's like every single level calculation the Trump, the calibration

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Speaker 2: was gone. It was the react of Trump, the angry Trump.

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Speaker 2: It was totally not in control. I can already guarantee

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Speaker 2: you he's just going to complain about the moderators. I

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Speaker 2: think it is a high likelihood that he does not

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Speaker 2: participate in another debate after what, which would be another

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Speaker 2: win for Commala, which would be a massive win for Kamala,

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Speaker 2: who has to memorize whunch of scripted baited answers rights

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Speaker 2: said boom, Yeah, now you just go rally for two

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Speaker 2: more months, maybe do one more bullshit interview with Dana

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Speaker 2: Bash and yet you know that that's it.

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Speaker 3: So I just can't get over this.

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Speaker 5: And I would think some people also probably noticed if

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Speaker 5: they're voting on this abortion question, that his two points clash.

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Speaker 5: Like he says he really believes that on a moral

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Speaker 5: level it should be left to the states, then he

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Speaker 5: also won't say that he'd veto a national abortion BD. Right,

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Speaker 5: that's not leaving it to the.

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Speaker 3: States, that's right.

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Speaker 1: It's I don't even really understand why he is sticking

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Speaker 1: on this, Like jd. Vance is actually very like what

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Speaker 1: he said in the past.

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Speaker 4: He actually embraces.

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Speaker 3: All the friends yes was.

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Speaker 4: On abortion, like yah, yeah, right, So jd.

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Speaker 1: Van should be like, no, no, we're good, We're not

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Speaker 1: going to and you can't. I genuinely don't understand that,

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Speaker 1: especially because he clearly knows he's got a.

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Speaker 4: Problem on abortion.

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Speaker 1: He clearly, you know, as soon as Roe versus Wade

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Speaker 1: was overturned, he knew it was going to be a problem.

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Speaker 1: He was all over the place on this floor amendment,

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Speaker 1: and it was mess Since we're talking so much about abortion,

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Speaker 1: we have a little bit of this exchange, so let's

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Speaker 1: go ahead and play it. This is D three guys,

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Speaker 1: if we could play a little bit of this exchange

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Speaker 1: on abortion.

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Speaker 3: You're running me. JD.

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Speaker 6: Vance has said that you would veto if it did

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Speaker 6: come to your desk.

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Speaker 7: Well, I didn't discuss it with JD. In all fairness, JD.

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Speaker 7: And I don't mind if he has a certain view,

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Speaker 7: but I think you was speaking of me, but I

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Speaker 7: really didn't. Look, we don't have to discuss it because

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Speaker 7: she'd never be able to get it, just like she

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Speaker 7: couldn't get student loans. They couldn't get is that did

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Speaker 7: even come close to get any student loans. They taunted

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Speaker 7: young people and a lot of other people that had loans.

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Speaker 7: They can never get this approved. So it doesn't matter

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Speaker 7: what she says about going to Congress. So wonderful, let's

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Speaker 7: go to Congress do it. But the fact is that

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Speaker 7: for years they wanted to get it out of Congress

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Speaker 7: and out of the federal government, and we did something

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Speaker 7: that everybody said couldn't be done, and now you have

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Speaker 7: a vote of the people on abortion.

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Speaker 1: He went on this long tangent too about student loan debt.

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Speaker 1: I mean, I know what he's trying to say, which

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Speaker 1: is like, Okay, well you claim you're going to codify ROW,

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Speaker 1: but you're not going to have the vote sit do it.

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Speaker 3: It is an opportunity you actually got through that.

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Speaker 4: Couldn't figure out, like he was.

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Speaker 5: Saying, posing things, and you won't be able to deliver

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Speaker 5: that right.

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Speaker 1: I mean, listen, I would love for Kammel in that

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Speaker 1: moment to be like, that's why I'm going to get

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Speaker 1: rid of the filibuster so that we can codify roversus way.

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Speaker 1: But she, in the section did the polar opposite of

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Speaker 1: what Trump did, Like in the border section, which is

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Speaker 1: the stronger issue for him, she extended the conversation of abortion.

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Speaker 1: She kept going in she kept going in on and

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Speaker 1: going back to it, and then he would feel like, oh,

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Speaker 1: I got to respond in some kind of a way,

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Speaker 1: and so and she brought up visceral examples, and he

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Speaker 1: kept saying, you know, oh, everybody wanted this to be done,

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Speaker 1: and she said, no, those women who were bleeding out

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Speaker 1: in parking lots, they did not want this. The majority

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Speaker 1: of the country doesn't want That's why in red state

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Speaker 1: after red state they chose freedom. She said, is how

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Speaker 1: she framed it. And the other thing that I kept

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Speaker 1: thinking about in this section, Bryan, is the way that

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Speaker 1: Biden handled the abortion answers in the last debate.

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Speaker 4: Do you guys.

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Speaker 5: Remember this He's finished by talking about immigrants raping people.

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Speaker 4: Yes, yes he did.

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Speaker 1: And now Trump is the one who's like, you know,

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Speaker 1: bringing up his own worst issues. But yeah, and Biden

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Speaker 1: gets asked the abortion question last time and everyone's like,

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Speaker 1: all right, oh, this is the layup for him, and

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Speaker 1: he starts talking incomprehensibly about an undocumented immigrant raping someone,

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Speaker 1: like what what thing?

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Speaker 3: Where news here?

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Speaker 2: Kamala's campaign will now ask for another debate according to

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Speaker 2: the one.

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Speaker 3: Yeah, I would do, you know, I certainly would do.

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Speaker 2: After whatever we all hell this witness, I think we

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Speaker 2: should talk then about what we've been alluding to is that,

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Speaker 2: you know, there's this concept of like frame control, where

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Speaker 2: Kamala was just totally in control of the frame constantly.

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Speaker 2: So we're talking about the border, Oh no, no, no, no,

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Speaker 2: We're gonna make a little thing about rallies that you're

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Speaker 2: going to take, and then oh well, let's also talk

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Speaker 2: about you said, migrant crime reminds me of crime because

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Speaker 2: you're a criminal and and he's like, wait, no, no,

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Speaker 2: I'm not a criminal, you know. And it's like, what

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Speaker 2: are we doing? No, you're supposed to be. And actually,

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Speaker 2: that's one of Trump's most powerful things is that he

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Speaker 2: was always in setting control of the narrative. He was

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Speaker 2: somebody who could pivot the discussion where he wanted it

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Speaker 2: to go. So we have the perfect example here, guys.

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Speaker 2: Let's go ahead and prepare D four. This is exactly

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Speaker 2: where Trump is talking about. Trump has asked a question

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Speaker 2: about the border. Kamala's initially asked about the border. In

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Speaker 2: her border answer, she gives a rally, a rally com

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Speaker 2: We were all sitting here at the desk, and I

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Speaker 2: was like, here we go. He's going to take debit

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Speaker 2: and then immediately that's what he does. He focuses on himself,

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Speaker 2: not on the issue. So D four, let's take a listen.

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Speaker 3: And I'll tell you something.

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Speaker 6: He's going to talk about immigration a lot tonight, even

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Speaker 6: when it's not the subject that is being raised. And

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Speaker 6: I'm going to actually do something really unusual, and I'm

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Speaker 6: going to invite you to attend one of Donald Trump's

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Speaker 6: rallies because it's a really interesting thing to watch. You

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Speaker 6: will see during the course of his rallies he talks

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Speaker 6: about fictional characters like Hannibal Lecter. He will talk about

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Speaker 6: win Mills cause cancer. And what you will also notice

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Speaker 6: is that people start leaving his rallies early out of

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Speaker 6: exhaustion and boredom. And I will tell you the one

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Speaker 6: thing you will not hear him talk about is you.

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Speaker 6: You will not hear him talk about your needs, your dreams,

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Speaker 6: and your need and your desires.

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Speaker 7: First time he responders to the rallies, she said, people

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Speaker 7: start leaving. People don't go to her rallies. There's no

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Speaker 7: reason to go. And the people that do go, she's

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Speaker 7: busting him in and paying them to be there and

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Speaker 7: then showing them in a different light, so she can't

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Speaker 7: talk about that.

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Speaker 3: People don't leave my rallies.

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Speaker 7: We have the biggest rallies, the most incredible rallies in

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Speaker 7: the history of politics. That's because people want to take

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Speaker 7: their country back. Our country is being lost. We're a

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Speaker 7: failing nation. And it happened three and a half years ago.

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Speaker 7: And what's going on here. You're going to end up

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Speaker 7: in World War three. Just to go into another subject,

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Speaker 7: what they have done to our country by allowing these

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Speaker 7: millions and millions of people to come into our country.

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Speaker 7: And look at what's happening to the towns all over

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Speaker 7: the United States, and a lot of towns don't want

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Speaker 7: to talk. It's not going to be Aurora or Springfield.

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Speaker 7: A lot of towns don't want to talk about it

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Speaker 7: because they're so embarrassed by it. In Springfield, they're eating

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Speaker 7: the dogs the people that came in. They're eating the cats,

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Speaker 7: they're eating they're eating the pets of the people that

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Speaker 7: live there. And this is what's happening in our country.

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Speaker 7: And it's a shame as far as rallies are concerned.

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Speaker 7: As far as the reason they go is, they like

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Speaker 7: what I say. They want to bring our country back.

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Speaker 7: They want to make America great against very simple phrase,

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Speaker 7: make America great again. She's destroying this country and if

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Speaker 7: she becomes president, this country doesn't have a chance of success.

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Speaker 7: Not only success, will end up being Venezuela on steroids.

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Speaker 2: That's a perfect example in that you know what we

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Speaker 2: just watch. He takes a question about the border, spends

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Speaker 2: probably seventy percent of it talking about the rallies in it.

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Speaker 2: He also has to bring up a pet hoax at

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Speaker 2: least as far as we know right now, about Haitian

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Speaker 2: migrants eating pets, and he's not talking about I mean,

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Speaker 2: that's the other thing. Why don't we have to do

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Speaker 2: with the pets? Lake and Riley? We all know lincln

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Speaker 2: Riley's name. You could say that, you could bring up

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Speaker 2: any legitimate case of migrant crime, and you're not going

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Speaker 2: to get interjected. What the moderator saying, Hey, actually, you know,

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Speaker 2: we talked to the city manager or whatever of Springfield

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Speaker 2: and then they say that's not true. It's like he

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Speaker 2: took the worst decision possible in every single moment there,

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Speaker 2: but most importantly, Ris got under his skin and got

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Speaker 2: him to with the answer on the border whenever.

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Speaker 3: I mean, did he even say borders are I'm trying

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Speaker 3: to think.

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Speaker 4: I believe one time he said it.

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Speaker 2: The moderator instead is that at one saying you, Kamala,

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Speaker 2: you were put in charge of the border Trump. It's

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Speaker 2: like complete incoherence. If you're watching that and you're a

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Speaker 2: normal person who're genuinely concerned about immigration or the border

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Speaker 2: or whatever, what did you get.

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Speaker 3: Out of that? Yeah, that's the question.

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Speaker 5: You have to here quick fact, the immigrants are not

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Speaker 5: eating cats. They're actually children who identify as cats.

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Speaker 1: Oh no, okay, transgender children in yeah, criminals species.

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Speaker 4: Okay.

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Speaker 1: See that's the other thing effect that came out in

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Speaker 1: a couple of places because like, we knew what the

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Speaker 1: fuck he was talking about with the whole pet Haitian

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Speaker 1: migrant thing. Because our brains are rotten. We're online way

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Speaker 1: too much. There are millions upon millions of Americans at

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Speaker 1: home who are like, what are you even talking about?

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Speaker 4: In fact, a.

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Speaker 1: Someone very close to me who is like not that

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Speaker 1: political and definitely not super online, was like, if you're

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Speaker 1: gonna make up some shit, at least make it believable,

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Speaker 1: you know, like, this is just preposterous and weird.

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Speaker 4: Sorry, didn't it.

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Speaker 5: Come from a Springfield town meeting?

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Speaker 3: It's not.

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Speaker 5: Isn't some like super far right wing for a right

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Speaker 5: wing lunatic who I have.

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Speaker 3: I can tell you the genesis.

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Speaker 2: The genesis of it is that there was a Facebook

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Speaker 2: post in the Springfield community or whatever, in a group

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Speaker 2: on the group it said I hear from my neighbors

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Speaker 2: daughters coud. It was like my neighbor's daughter's friends says

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Speaker 2: that the Haitians are eating cats or eating pets.

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Speaker 3: That's one.

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Speaker 2: Two is a viral video. A video goes viral of

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Speaker 2: a black woman who was arrested for eating a cat. Okay,

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Speaker 2: but it turns out that that video did not take

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Speaker 2: place in Springfield, Ohio, and she is an American American,

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Speaker 2: she is not hate.

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Speaker 1: So it's actually the native born people who are eating.

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Speaker 3: The cats out.

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Speaker 2: She's probably also she's probably just a drug addict, but okay,

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Speaker 2: let's put it that.

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Speaker 3: Yeah, and that's the genesis.

439
00:20:14,480 --> 00:20:18,560
Speaker 4: There was also a fake photo of a guy a goose.

440
00:20:18,359 --> 00:20:22,440
Speaker 1: Which Columbus, and there was no indication that the man

441
00:20:22,480 --> 00:20:26,520
Speaker 1: was an immigrant, was a member of the Kennedy family.

442
00:20:28,200 --> 00:20:30,240
Speaker 2: I think we should normalize eating geese. But anyway, that's

443
00:20:30,560 --> 00:20:34,080
Speaker 2: a whole separate conversation. I think fish and game rags

444
00:20:34,160 --> 00:20:36,560
Speaker 2: are way too hiding.

445
00:20:36,680 --> 00:20:37,320
Speaker 3: I think we should.

446
00:20:37,520 --> 00:20:39,680
Speaker 2: I mean, there's all these dreamly like greasy, we're such

447
00:20:39,680 --> 00:20:40,399
Speaker 2: a rich country.

448
00:20:40,400 --> 00:20:42,560
Speaker 3: We got these tasty ducks sitting in those ponds for

449
00:20:44,600 --> 00:20:46,120
Speaker 3: put that. I'll put it all aside.

450
00:20:46,280 --> 00:20:51,440
Speaker 1: Anyway, he's so brained, not only then, right that he

451
00:20:51,560 --> 00:20:54,720
Speaker 1: brings up this whole thing that most.

452
00:20:54,440 --> 00:20:56,560
Speaker 4: People, even like won't even know.

453
00:20:56,480 --> 00:20:59,560
Speaker 1: What you're talking about, let alone what Kamala Harris has

454
00:20:59,600 --> 00:21:02,200
Speaker 1: to do with, let alone that it even involves immigrants,

455
00:21:02,240 --> 00:21:04,639
Speaker 1: Like they just have no idea what you're talking about.

456
00:21:04,960 --> 00:21:06,719
Speaker 4: And there are other instances.

457
00:21:06,200 --> 00:21:09,240
Speaker 1: Of that as well, where it's like, oh, when he

458
00:21:09,640 --> 00:21:12,440
Speaker 1: in the rally answer, in that same answer, he's talking

459
00:21:12,440 --> 00:21:15,440
Speaker 1: about these conspiracies, Oh, she's bussing in people, et cetera,

460
00:21:15,760 --> 00:21:18,680
Speaker 1: which again normally people haven't heard of, they don't care about.

461
00:21:18,840 --> 00:21:22,159
Speaker 1: It's just I hadn't even heard that particular conspiracy. He

462
00:21:22,240 --> 00:21:26,280
Speaker 1: refers to the January sixth rioters as J six right,

463
00:21:26,320 --> 00:21:30,480
Speaker 1: which is also very like online lingo, subcultural lngo. And

464
00:21:31,280 --> 00:21:33,520
Speaker 1: you know, I do think that they're like a victim

465
00:21:33,560 --> 00:21:36,399
Speaker 1: of their own success on Twitter, like it's too much

466
00:21:36,560 --> 00:21:39,119
Speaker 1: of a right wing echo chamber and they're drinking too

467
00:21:39,200 --> 00:21:41,080
Speaker 1: much of their own kool aid. They're high on their

468
00:21:41,080 --> 00:21:44,200
Speaker 1: own supply, and they think that this stuff is like legit,

469
00:21:44,520 --> 00:21:49,040
Speaker 1: Lands has national purchase and any most people who are

470
00:21:49,119 --> 00:21:52,040
Speaker 1: at all for grabs in this election are just like,

471
00:21:52,119 --> 00:21:54,280
Speaker 1: I literally don't even know what the fuck you're talking about.

472
00:21:54,359 --> 00:21:54,720
Speaker 4: Right now.

473
00:21:54,880 --> 00:21:57,280
Speaker 5: He has spent so and I was sort of joking

474
00:21:57,320 --> 00:21:59,760
Speaker 5: earlier when I said that getting kicked off of Twitter

475
00:22:00,280 --> 00:22:02,679
Speaker 5: hurt his ability to be in touch with what's going on,

476
00:22:02,720 --> 00:22:05,640
Speaker 5: but not really because instead he was on truth social right,

477
00:22:06,080 --> 00:22:10,440
Speaker 5: and that puts you in a subcultural genre where you

478
00:22:10,520 --> 00:22:13,600
Speaker 5: start using words and talking to people who are just

479
00:22:13,640 --> 00:22:17,280
Speaker 5: nowhere near the median. You're using words that they understand, right,

480
00:22:17,440 --> 00:22:20,119
Speaker 5: but anybody who's not in true social doesn't.

481
00:22:20,240 --> 00:22:21,960
Speaker 2: Got some big news. I had to confirm it before

482
00:22:21,960 --> 00:22:25,800
Speaker 2: I read it. Taylor swift As endorsed Kamala Harris that

483
00:22:25,800 --> 00:22:27,879
Speaker 2: debate she just posted. She says, like many of you,

484
00:22:27,960 --> 00:22:30,600
Speaker 2: I watched the debate tonight. If you haven't already, now

485
00:22:30,680 --> 00:22:32,280
Speaker 2: is a great time to do your research on the

486
00:22:32,280 --> 00:22:34,320
Speaker 2: issues at hand. As a voter, I make sure to

487
00:22:34,320 --> 00:22:37,240
Speaker 2: watch and read everything I can about their propose. Recently,

488
00:22:37,240 --> 00:22:40,320
Speaker 2: I was made aware of AI falsely endorsing Trump was

489
00:22:40,359 --> 00:22:42,440
Speaker 2: posted to a site. It conjured up my fears around

490
00:22:42,600 --> 00:22:44,600
Speaker 2: blah blah blah. I will be casting my vote for

491
00:22:44,680 --> 00:22:47,040
Speaker 2: Kamala Harris and Tim Watson the twenty twenty four election.

492
00:22:47,280 --> 00:22:49,440
Speaker 2: I'm voting for Kamala because she fights for the rights

493
00:22:49,440 --> 00:22:50,359
Speaker 2: and causes I believe.

494
00:22:50,600 --> 00:22:52,240
Speaker 3: I think she steady handed, gifted leader.

495
00:22:52,400 --> 00:22:58,760
Speaker 2: She also posted a picture with her cat cat lady.

496
00:23:00,280 --> 00:23:03,440
Speaker 2: We all knew it was coming, but oh my God,

497
00:23:03,520 --> 00:23:06,240
Speaker 2: with love and hope, Taylor Swift childless cat lady.

498
00:23:06,640 --> 00:23:08,840
Speaker 4: Oh, I'm sure this is real.

499
00:23:09,359 --> 00:23:09,880
Speaker 3: Swear to God.

500
00:23:10,440 --> 00:23:12,119
Speaker 2: That's why I had to be one hundred percent. I

501
00:23:12,200 --> 00:23:15,560
Speaker 2: just went to our Instagram page. I refreshed it. I

502
00:23:15,600 --> 00:23:17,120
Speaker 2: read it right off of it myself.

503
00:23:17,280 --> 00:23:20,040
Speaker 1: Well, this comes right on the heels of our cat conversation.

504
00:23:20,240 --> 00:23:23,359
Speaker 1: So it's a you know, wow, there flip flu how

505
00:23:23,400 --> 00:23:24,639
Speaker 1: they feel about cats they.

506
00:23:24,520 --> 00:23:27,520
Speaker 3: Didn't even is a big one.

507
00:23:27,560 --> 00:23:29,280
Speaker 2: That the tailor thing actually is a big one. I

508
00:23:29,280 --> 00:23:32,359
Speaker 2: mean people have exaggerated it before. The most pop she's like,

509
00:23:32,680 --> 00:23:35,720
Speaker 2: she sends, you know, pop culture is the most famous person.

510
00:23:35,680 --> 00:23:37,240
Speaker 5: Probably the world register.

511
00:23:37,359 --> 00:23:40,600
Speaker 3: I mean yeah, because people register to vote. Now, look,

512
00:23:40,640 --> 00:23:41,639
Speaker 3: you could be right, Crystal.

513
00:23:41,680 --> 00:23:43,880
Speaker 2: I just I'm not discounting it, especially in a row

514
00:23:43,960 --> 00:23:46,679
Speaker 2: row row your vote thing, this whole cat stuff. I mean,

515
00:23:46,680 --> 00:23:49,800
Speaker 2: You've got tens of millions of people who are following her.

516
00:23:49,840 --> 00:23:52,520
Speaker 2: She'll be on tour. I only know this because I'm

517
00:23:52,520 --> 00:23:56,040
Speaker 2: trying to get tickets right before the election in the

518
00:23:56,080 --> 00:24:00,680
Speaker 2: critical battleground states in Miami and indianapol I'm just saying,

519
00:24:00,720 --> 00:24:02,760
Speaker 2: if she, you know, does Pepper some of that in there,

520
00:24:02,840 --> 00:24:05,800
Speaker 2: But I do think you know that is it's it's

521
00:24:05,840 --> 00:24:08,520
Speaker 2: significant in a certain way, not just the tailor thing.

522
00:24:08,880 --> 00:24:12,720
Speaker 2: The media conversation after this relative to how it was

523
00:24:12,760 --> 00:24:14,200
Speaker 2: after Biden is night and day.

524
00:24:14,240 --> 00:24:14,600
Speaker 4: Oh yeah.

525
00:24:14,640 --> 00:24:17,560
Speaker 2: You can imagine the backflips that they're doing on CNN

526
00:24:17,600 --> 00:24:22,440
Speaker 2: and MSNBC. You can imagine the absolute coping Jesse Water

527
00:24:22,560 --> 00:24:25,040
Speaker 2: tears over how bad the moderators were.

528
00:24:25,400 --> 00:24:26,880
Speaker 3: You just don't want to be in that position.

529
00:24:27,000 --> 00:24:30,120
Speaker 2: You want to be celebrating good stuff your candidate did,

530
00:24:30,160 --> 00:24:32,119
Speaker 2: and they didn't have nearly enough moments for that.

531
00:24:32,359 --> 00:24:33,960
Speaker 4: Yeah, yeah, no, that's it.

532
00:24:34,000 --> 00:24:35,679
Speaker 1: I just want to know where Taylor Swift was at

533
00:24:35,680 --> 00:24:37,679
Speaker 1: the DMC when I was promised a special guest, So

534
00:24:37,680 --> 00:24:38,400
Speaker 1: we got to lead on.

535
00:24:39,880 --> 00:24:42,399
Speaker 3: Want nor did we get Beyonce, So it's like, what

536
00:24:42,440 --> 00:24:42,880
Speaker 3: are we doing?

537
00:24:45,560 --> 00:24:49,000
Speaker 1: There was an interesting moment where Ryan beforehand you asked

538
00:24:49,080 --> 00:24:51,600
Speaker 1: us to take the over the under on Kamala doing

539
00:24:51,640 --> 00:24:54,600
Speaker 1: her like I'm speaking yes, And we got a big

540
00:24:54,640 --> 00:24:57,000
Speaker 1: surprise on that one, which is it was actually drunk

541
00:24:57,400 --> 00:24:58,200
Speaker 1: multiple times?

542
00:24:58,280 --> 00:24:59,560
Speaker 4: Did he multiple times?

543
00:24:59,760 --> 00:25:01,640
Speaker 5: Once time he said quiet please.

544
00:25:04,560 --> 00:25:06,680
Speaker 3: His inner girl boss, I'm talking.

545
00:25:06,880 --> 00:25:08,639
Speaker 1: Perhaps this is a way for him to try to

546
00:25:08,680 --> 00:25:11,399
Speaker 1: win the woman vote over by channeling his.

547
00:25:11,400 --> 00:25:12,439
Speaker 4: Inner girl boss.

548
00:25:12,520 --> 00:25:16,160
Speaker 1: Yes we have we have D six is a little

549
00:25:16,200 --> 00:25:19,280
Speaker 1: bit of that Trump. But I'm speaking reprising problems.

550
00:25:19,280 --> 00:25:20,679
Speaker 5: See very sassy, very.

551
00:25:20,520 --> 00:25:23,800
Speaker 1: Sassy Trump, reprising Kamala's famous line piece of you, Mike

552
00:25:23,840 --> 00:25:25,080
Speaker 1: Pencil's take a listen to that.

553
00:25:25,560 --> 00:25:28,679
Speaker 7: She gave up at least twelve and probably fourteen or

554
00:25:28,680 --> 00:25:32,080
Speaker 7: fifteen different policies, Like she was big on defund the

555
00:25:32,119 --> 00:25:36,600
Speaker 7: police in Minnesota. She went out, I'm talking now, if

556
00:25:36,640 --> 00:25:42,879
Speaker 7: you don't mind, please, does that sound familiar? She went out,

557
00:25:44,119 --> 00:25:46,120
Speaker 7: she went out in Minnesota.

558
00:25:46,560 --> 00:25:48,840
Speaker 1: You know there are her face was very active too.

559
00:25:48,880 --> 00:25:53,400
Speaker 1: That was clearly very intentional her faces. There were times

560
00:25:53,520 --> 00:25:55,000
Speaker 1: where she would actively go like.

561
00:25:55,600 --> 00:25:57,720
Speaker 3: It was a little Wretchen Whitford to me for me,

562
00:25:58,520 --> 00:25:59,080
Speaker 3: she studied.

563
00:25:59,160 --> 00:26:01,520
Speaker 1: There were times where she almost like had a look

564
00:26:01,520 --> 00:26:03,159
Speaker 1: of like pity on her face.

565
00:26:03,200 --> 00:26:04,680
Speaker 4: She was laughing at him.

566
00:26:04,880 --> 00:26:07,679
Speaker 1: It was night and day obviously with Joe Biden, but

567
00:26:07,760 --> 00:26:12,360
Speaker 1: it was also very different affect from what Trump had

568
00:26:12,400 --> 00:26:15,560
Speaker 1: in this debate, where he was just straight on not

569
00:26:15,600 --> 00:26:18,720
Speaker 1: looking at her at all, straight on, angry mug to

570
00:26:18,760 --> 00:26:24,040
Speaker 1: the camera. And you know, I think she was It

571
00:26:24,080 --> 00:26:28,040
Speaker 1: was I think a smart play on in her regard,

572
00:26:28,119 --> 00:26:31,520
Speaker 1: and like I said before, like they thought through how

573
00:26:31,600 --> 00:26:34,960
Speaker 1: they wanted this debate to go. They thought through the

574
00:26:35,000 --> 00:26:38,160
Speaker 1: spots they were going to pick. I guarantee they even practiced. Okay,

575
00:26:38,200 --> 00:26:40,320
Speaker 1: when he brings up criminal immigrants, you're going to say

576
00:26:40,520 --> 00:26:43,040
Speaker 1: you're the criminal dot dot dot, and then he's going

577
00:26:43,119 --> 00:26:45,120
Speaker 1: to go in on that when you get asked.

578
00:26:44,960 --> 00:26:45,680
Speaker 4: About flip flop.

579
00:26:45,680 --> 00:26:47,399
Speaker 1: Apparently there was a plan to bring up like his

580
00:26:47,480 --> 00:26:49,880
Speaker 1: dad's networth or whatever it was that throw him off track.

581
00:26:49,920 --> 00:26:54,880
Speaker 1: There they he has become predictable enough so much that

582
00:26:54,920 --> 00:26:57,639
Speaker 1: they knew what his points were going to be and

583
00:26:57,680 --> 00:26:58,920
Speaker 1: how she could throw him off.

584
00:26:58,960 --> 00:27:02,040
Speaker 5: And they even tell her rafted in her opening remarks

585
00:27:02,080 --> 00:27:05,639
Speaker 5: where she said, you know you're gonna here's what you're

586
00:27:05,640 --> 00:27:06,399
Speaker 5: going to see today.

587
00:27:06,480 --> 00:27:07,280
Speaker 3: Yeah, we have some of that.

588
00:27:07,359 --> 00:27:09,280
Speaker 5: You're going to see a guy that talks about himself.

589
00:27:09,320 --> 00:27:10,040
Speaker 5: We can roll that one.

590
00:27:10,040 --> 00:27:11,120
Speaker 3: Why don't we? Why don't we? Guys?

591
00:27:11,160 --> 00:27:14,960
Speaker 2: That's really sting, because this is important. This was the

592
00:27:15,000 --> 00:27:17,359
Speaker 2: set piece. She telegraphed what she was going to do,

593
00:27:17,680 --> 00:27:20,440
Speaker 2: then she did it, and he takes the bab every time,

594
00:27:20,640 --> 00:27:21,640
Speaker 2: zero discipline.

595
00:27:21,760 --> 00:27:22,680
Speaker 3: It was ridiculous.

596
00:27:22,760 --> 00:27:25,560
Speaker 2: Let's take a listen to her please from the from

597
00:27:25,560 --> 00:27:27,640
Speaker 2: the beginning of what she was going to do, d one.

598
00:27:27,880 --> 00:27:29,800
Speaker 6: But I'm going to tell you all on this debate tonight,

599
00:27:30,320 --> 00:27:32,960
Speaker 6: you're going to hear from the same old tired.

600
00:27:32,720 --> 00:27:35,480
Speaker 3: Playbook, a bunch of lies.

601
00:27:35,320 --> 00:27:38,920
Speaker 6: Grievances, and name calling. What you're going to hear tonight

602
00:27:39,800 --> 00:27:43,280
Speaker 6: is it detailed and dangerous plan called Project twenty twenty

603
00:27:43,320 --> 00:27:46,679
Speaker 6: five that the former president intends on implementing if he

604
00:27:46,760 --> 00:27:51,199
Speaker 6: were elected to gain I believe very strongly that the

605
00:27:51,240 --> 00:27:55,600
Speaker 6: American people want a president who understands the importance of

606
00:27:55,760 --> 00:27:58,000
Speaker 6: bringing us together, knowing we have so much more in

607
00:27:58,040 --> 00:28:00,879
Speaker 6: common than what separates us. And I pledged you to

608
00:28:01,200 --> 00:28:02,960
Speaker 6: be a president for all Americans.

609
00:28:03,400 --> 00:28:04,080
Speaker 4: So there you go.

610
00:28:04,520 --> 00:28:06,879
Speaker 1: Like you said, Ryan, she set up you know what

611
00:28:06,920 --> 00:28:09,760
Speaker 1: that reminded me of in the moment and did rewatching

612
00:28:09,760 --> 00:28:10,080
Speaker 1: it there.

613
00:28:10,880 --> 00:28:14,920
Speaker 4: Remember when Chris Christy destroyed Marc because he said what

614
00:28:15,160 --> 00:28:15,760
Speaker 4: he said.

615
00:28:16,320 --> 00:28:21,000
Speaker 1: He said he has his memorized talking points, and then

616
00:28:21,320 --> 00:28:25,640
Speaker 1: Marco Rubio goes on to recite his memorized talking points

617
00:28:25,680 --> 00:28:28,359
Speaker 1: and use them over again, and then Christy's able to

618
00:28:28,480 --> 00:28:30,399
Speaker 1: see he's doing the thing I told you he was

619
00:28:30,400 --> 00:28:32,920
Speaker 1: going to do. And Kamala did that exact same thing

620
00:28:32,920 --> 00:28:35,359
Speaker 1: with Trump, like here's what you're going to hear tonight.

621
00:28:35,480 --> 00:28:37,240
Speaker 1: And then when he would do something like this, See

622
00:28:37,280 --> 00:28:39,160
Speaker 1: I told you this is what he was going to do.

623
00:28:40,000 --> 00:28:41,040
Speaker 3: Yeah, you're exactly right.

624
00:28:41,080 --> 00:28:42,600
Speaker 2: So I was just telling you, guys, well that clip

625
00:28:42,640 --> 00:28:45,240
Speaker 2: was playing with a reporter who's in the room the

626
00:28:45,240 --> 00:28:47,520
Speaker 2: spin room, asked Lindsey Graham, how did you think that

627
00:28:48,080 --> 00:28:50,920
Speaker 2: the debate went? He said the debate team should be

628
00:28:50,920 --> 00:28:55,120
Speaker 2: fired and that Trump was unprepared quote disaster. As you said, Crystal,

629
00:28:55,200 --> 00:28:58,880
Speaker 2: it's never this is like when remember they were saying

630
00:28:58,880 --> 00:29:01,920
Speaker 2: that about Biden and then Jim Clyburn originally he's the

631
00:29:01,960 --> 00:29:04,280
Speaker 2: original Kope, He's like, oh, he wasn't well prepared.

632
00:29:04,320 --> 00:29:06,080
Speaker 3: He was reciting facts.

633
00:29:06,280 --> 00:29:08,680
Speaker 4: They did a lot of throwing the staff under the bus.

634
00:29:08,680 --> 00:29:10,960
Speaker 1: Remember it was oh they worked him too hard and

635
00:29:11,000 --> 00:29:14,479
Speaker 1: they were having him memorize too many facts or whatever

636
00:29:14,560 --> 00:29:16,080
Speaker 1: instead of just letting Joe be Joe.

637
00:29:16,160 --> 00:29:17,000
Speaker 4: Yeah, there was a lot of that.

638
00:29:17,320 --> 00:29:18,120
Speaker 3: We're going to watch that now.

639
00:29:18,160 --> 00:29:20,600
Speaker 2: I mean Trump is a capricious man, He's deeply sensitive.

640
00:29:20,640 --> 00:29:23,160
Speaker 2: So what's going to happen. He is going to he's

641
00:29:23,200 --> 00:29:24,760
Speaker 2: kind of lash out at his staff. We're going to

642
00:29:24,760 --> 00:29:28,040
Speaker 2: see the multiple truths and others. I wouldn't be surprised

643
00:29:28,080 --> 00:29:30,040
Speaker 2: if we start to see you know who was at

644
00:29:30,080 --> 00:29:34,320
Speaker 2: Susie Wiles and Chris las de Vita. Already there's major

645
00:29:34,400 --> 00:29:39,000
Speaker 2: tension in the campaign and Corey Lewindower. Corey's going to

646
00:29:39,120 --> 00:29:41,960
Speaker 2: use this against them, But gee, they screwed you, mister.

647
00:29:42,120 --> 00:29:45,040
Speaker 2: They are the ones who screwed you. And Laura Lumer

648
00:29:45,200 --> 00:29:47,760
Speaker 2: was on the plane with Trump right today all the way.

649
00:29:47,920 --> 00:29:49,520
Speaker 2: Guarantee you She'll be like, oh, you got to get

650
00:29:49,600 --> 00:29:50,240
Speaker 2: rid of those people.

651
00:29:50,280 --> 00:29:52,240
Speaker 1: So look when Trump, the one that told him about

652
00:29:52,240 --> 00:29:53,760
Speaker 1: the Haitian cat situes.

653
00:29:53,920 --> 00:29:57,200
Speaker 2: Trump is in a bad spot. What happens is he

654
00:29:57,360 --> 00:30:00,880
Speaker 2: always retreats to the most sycophantic people who are the

655
00:30:00,960 --> 00:30:02,600
Speaker 2: most willing. We saw this and used to be the

656
00:30:03,200 --> 00:30:05,400
Speaker 2: Hills when I was Yeah, when I was covering him

657
00:30:05,400 --> 00:30:06,720
Speaker 2: in the White House, I saw this all the time.

658
00:30:06,760 --> 00:30:09,480
Speaker 2: Like when things got bad, it wasn't Jared Nvanka, it

659
00:30:09,560 --> 00:30:12,560
Speaker 2: was the Bannons, the you know, the Jenna ellisis all

660
00:30:12,560 --> 00:30:14,760
Speaker 2: these other people. So I predict something like that now.

661
00:30:14,920 --> 00:30:17,600
Speaker 2: Mike Lindell Bingo exactly. I think that this is an

662
00:30:17,680 --> 00:30:21,000
Speaker 2: overstock CEO and that's only going to make things worse, right,

663
00:30:21,080 --> 00:30:23,320
Speaker 2: It's going to make things even worse as we get

664
00:30:23,360 --> 00:30:24,240
Speaker 2: into the overall stream.

665
00:30:24,360 --> 00:30:26,120
Speaker 5: This is a really good point because this takes us

666
00:30:26,160 --> 00:30:28,320
Speaker 5: beyond the theater of the debate, and I think the

667
00:30:28,320 --> 00:30:33,080
Speaker 5: theater itself doesn't really change the debate, doesn't really change

668
00:30:33,120 --> 00:30:35,240
Speaker 5: the race that much, like it could have if Kamala

669
00:30:35,280 --> 00:30:38,360
Speaker 5: completely face planted or if like Trump fell off the stage.

670
00:30:38,720 --> 00:30:41,360
Speaker 5: But you know, I don't see this moving the poles

671
00:30:41,400 --> 00:30:42,880
Speaker 5: a whole lot in one way or another. But the way

672
00:30:42,880 --> 00:30:45,960
Speaker 5: that it will substantively affect the race is exactly what

673
00:30:46,000 --> 00:30:48,200
Speaker 5: you're talking about. The way that Trump reacts to it

674
00:30:48,200 --> 00:30:51,120
Speaker 5: because he can't handle it. He was humiliated by a

675
00:30:51,160 --> 00:30:54,040
Speaker 5: person he has contempt for, and right, he's going to

676
00:30:54,080 --> 00:30:57,400
Speaker 5: take it out now on people like las A Vita.

677
00:30:57,480 --> 00:30:59,240
Speaker 3: Yeah, people who were like professionals and the.

678
00:30:59,200 --> 00:31:01,320
Speaker 4: People is worst side of him, yes, and.

679
00:31:02,040 --> 00:31:05,320
Speaker 5: The retreat to the yeah, exactly, to the worst people

680
00:31:05,360 --> 00:31:08,680
Speaker 5: around him. And those worst people around him will use

681
00:31:08,720 --> 00:31:13,160
Speaker 5: this to their advantage. And so there's only what how

682
00:31:13,160 --> 00:31:15,200
Speaker 5: many days left? There's not enough time for him to

683
00:31:15,240 --> 00:31:17,080
Speaker 5: be fifty five upending the race.

684
00:31:17,600 --> 00:31:19,600
Speaker 4: Some states are you know, starting to vote like.

685
00:31:19,760 --> 00:31:22,360
Speaker 3: Now North Carolina, that's a disaster.

686
00:31:22,440 --> 00:31:24,160
Speaker 2: And North Carolina, as we were talking about in our

687
00:31:24,200 --> 00:31:26,400
Speaker 2: pre show, has the high chance of actually being the

688
00:31:26,480 --> 00:31:29,280
Speaker 2: number two according to Nate Silver tipping point state. So

689
00:31:29,320 --> 00:31:30,840
Speaker 2: there's a lot of there's a lot of problems that

690
00:31:30,880 --> 00:31:33,840
Speaker 2: happened for Trump tonight. I I genuinely, I mean, look,

691
00:31:33,880 --> 00:31:35,520
Speaker 2: everyone always said that Hillary won.

692
00:31:35,840 --> 00:31:38,120
Speaker 3: You know, the general consis was Hillary won all three debates,

693
00:31:38,240 --> 00:31:41,160
Speaker 3: she still lost the election. Okay, so we'll see, you know,

694
00:31:41,200 --> 00:31:42,720
Speaker 3: he could I think you'd probably still win.

695
00:31:42,840 --> 00:31:45,920
Speaker 4: I think census was also kind of wrong, was I.

696
00:31:45,920 --> 00:31:48,080
Speaker 3: Don't disagree with you, I'm saying the media.

697
00:31:49,000 --> 00:31:51,960
Speaker 2: The media conversation around it was that Trump had lost

698
00:31:52,000 --> 00:31:53,240
Speaker 2: quote unquote all three debates.

699
00:31:53,320 --> 00:31:55,480
Speaker 3: Yeah, so look, could he still win? Yeah?

700
00:31:55,560 --> 00:31:55,800
Speaker 4: Sure?

701
00:31:56,120 --> 00:31:59,000
Speaker 2: What will this have effect on the polls? I don't

702
00:31:59,040 --> 00:32:00,760
Speaker 2: know what do you guys? Do you think she'll get

703
00:32:00,760 --> 00:32:01,120
Speaker 2: a bump?

704
00:32:01,200 --> 00:32:02,600
Speaker 3: Yeah? You think, like maybe one.

705
00:32:03,040 --> 00:32:05,440
Speaker 4: I think I do think she will get a bump.

706
00:32:05,720 --> 00:32:08,200
Speaker 1: I think it will be certainly not as consequential as

707
00:32:08,240 --> 00:32:12,960
Speaker 1: the Biden debate, obviously, but we do have very unique

708
00:32:12,960 --> 00:32:17,080
Speaker 1: circumstances here. People feel like they don't really know who

709
00:32:17,160 --> 00:32:21,280
Speaker 1: Kamala Harris is and this was her first really big

710
00:32:21,520 --> 00:32:24,200
Speaker 1: test on a giant stage, and I think the ratings

711
00:32:24,200 --> 00:32:26,920
Speaker 1: for this are going to be astronomical. I know, I

712
00:32:26,960 --> 00:32:29,240
Speaker 1: mean just from the like normal people aren't really political

713
00:32:29,320 --> 00:32:30,920
Speaker 1: in my life that were like texting me about it

714
00:32:30,960 --> 00:32:33,040
Speaker 1: today and what I just I have a feeling the

715
00:32:33,120 --> 00:32:36,360
Speaker 1: nation was tuning into this, and certainly they will be

716
00:32:36,400 --> 00:32:39,360
Speaker 1: tuning into the clips that get you know, run and pulled.

717
00:32:39,080 --> 00:32:42,600
Speaker 4: From it for sure. And you know, she passed the test.

718
00:32:42,640 --> 00:32:44,800
Speaker 1: She did more than pass the test, and he the

719
00:32:44,880 --> 00:32:48,760
Speaker 1: worst side of him was on display. So I do

720
00:32:48,800 --> 00:32:51,520
Speaker 1: think that the polls will shift some. Do I think

721
00:32:51,560 --> 00:32:52,960
Speaker 1: that it's going to be massive?

722
00:32:53,240 --> 00:32:53,360
Speaker 3: No?

723
00:32:53,600 --> 00:32:55,800
Speaker 1: Does it go back to, you know, more like what

724
00:32:55,800 --> 00:32:58,320
Speaker 1: it was going into the convention when she had a

725
00:32:58,360 --> 00:33:01,240
Speaker 1: pretty clear lead, but you know, still very much on

726
00:33:01,280 --> 00:33:03,920
Speaker 1: an I think that's probably where we're headed. And then

727
00:33:03,960 --> 00:33:07,520
Speaker 1: the question is does that sustain? Is she able to

728
00:33:07,600 --> 00:33:11,080
Speaker 1: sustain that, because to Ryan's point, you don't have to

729
00:33:11,120 --> 00:33:13,600
Speaker 1: sustain it for that long, Like we're down to the

730
00:33:13,600 --> 00:33:17,360
Speaker 1: wire already, and Kamo says, now she wants to do

731
00:33:17,400 --> 00:33:19,240
Speaker 1: another debate. Do you guys think Trump is going to

732
00:33:19,320 --> 00:33:20,000
Speaker 1: want to do this again?

733
00:33:20,200 --> 00:33:22,880
Speaker 2: I do not think he well, it depends. So he

734
00:33:23,000 --> 00:33:25,880
Speaker 2: has agreed to NBC and Fox. She has only agreed,

735
00:33:25,920 --> 00:33:28,880
Speaker 2: I believe to NBC. So is he going to agree

736
00:33:28,920 --> 00:33:30,960
Speaker 2: to an NBC News debate? Like I have a high

737
00:33:31,400 --> 00:33:33,760
Speaker 2: maybe have agreed to Fox? She?

738
00:33:33,880 --> 00:33:35,600
Speaker 3: I mean, I'm not sure.

739
00:33:35,400 --> 00:33:38,320
Speaker 2: She would agree to fix just because look, when you're already,

740
00:33:38,360 --> 00:33:40,280
Speaker 2: when you came out of a good debate and then

741
00:33:40,320 --> 00:33:41,880
Speaker 2: you just say, oh, I'm not going to you know,

742
00:33:42,000 --> 00:33:45,160
Speaker 2: acquiesce to his sycophantic people. Even though the moderators on

743
00:33:45,200 --> 00:33:47,680
Speaker 2: this one were buyased in favor of you, There'd be

744
00:33:47,760 --> 00:33:50,479
Speaker 2: enough media cover that she could probably get away with it.

745
00:33:50,560 --> 00:33:52,560
Speaker 2: I think it is a very legitimate question of if

746
00:33:52,600 --> 00:33:55,680
Speaker 2: Trump participates in another debate. I'm not ready to say

747
00:33:55,680 --> 00:33:58,920
Speaker 2: he won't, but just because his vanity generally gets the

748
00:33:58,920 --> 00:34:01,320
Speaker 2: better of him and he thinks he can take someone

749
00:34:01,520 --> 00:34:02,080
Speaker 2: and he's agreed.

750
00:34:02,080 --> 00:34:03,560
Speaker 3: I mean, look, he agreed to debate Biden.

751
00:34:03,640 --> 00:34:05,880
Speaker 2: But at this point, now he's got a debate which

752
00:34:05,920 --> 00:34:08,080
Speaker 2: got Biden out of the race, which was objectively a

753
00:34:08,080 --> 00:34:11,000
Speaker 2: disaster for Trump and the Trump campaign, and now he

754
00:34:11,080 --> 00:34:13,319
Speaker 2: is another debate where he's going to one hundred percent

755
00:34:13,320 --> 00:34:15,120
Speaker 2: what's gonna happen? He's going to blame the moderators, and

756
00:34:15,160 --> 00:34:17,960
Speaker 2: he's gonna blame his staff. Does he have the wherewithal

757
00:34:18,239 --> 00:34:21,360
Speaker 2: to accept another debate under those circumstances. I'm not one

758
00:34:21,440 --> 00:34:23,960
Speaker 2: hundred percent sure. He might have taken away. Both debates

759
00:34:24,000 --> 00:34:26,120
Speaker 2: in this race so far were bad for me, so

760
00:34:26,200 --> 00:34:28,040
Speaker 2: why would I do another one? But I actually that

761
00:34:28,040 --> 00:34:30,880
Speaker 2: helps Kamala as well. I think he'd probably rather She

762
00:34:30,920 --> 00:34:32,480
Speaker 2: probably a little bit of a bump. I mean, I

763
00:34:32,520 --> 00:34:34,520
Speaker 2: certainly don't think the election was won or lost or

764
00:34:34,560 --> 00:34:37,000
Speaker 2: anything like that tonight, but I think it is very

765
00:34:37,000 --> 00:34:41,040
Speaker 2: consequential in that he blew a moment where both she rose.

766
00:34:40,840 --> 00:34:42,359
Speaker 3: To the place where she needed to be.

767
00:34:42,920 --> 00:34:44,719
Speaker 2: She's probably reassured a lot of vodors about like the

768
00:34:44,760 --> 00:34:47,680
Speaker 2: who are you question, and then worse every time she

769
00:34:47,719 --> 00:34:50,759
Speaker 2: didn't want to reassure them about anything that she fake believes.

770
00:34:50,920 --> 00:34:54,399
Speaker 2: She just laid up this very classic attack on Trump

771
00:34:54,440 --> 00:34:56,439
Speaker 2: if he only cares about himself, and then he would

772
00:34:56,520 --> 00:35:00,400
Speaker 2: validate those by taking debate on all of these ridiculous

773
00:35:00,440 --> 00:35:03,080
Speaker 2: So on the issues front, he really failed to actually

774
00:35:03,160 --> 00:35:05,160
Speaker 2: shine in the ways that I think he needed to,

775
00:35:05,239 --> 00:35:08,400
Speaker 2: and that's objectively a disaster for his campaign.

776
00:35:08,600 --> 00:35:11,879
Speaker 5: Yeah, yeah, he hasn't gotten over Biden leaving the race yet.

777
00:35:11,920 --> 00:35:13,319
Speaker 4: That was what I kept talking about Biden.

778
00:35:13,400 --> 00:35:15,760
Speaker 5: He's probably going to like fume about that for days

779
00:35:17,960 --> 00:35:20,399
Speaker 5: on truth and maybe jump over to Twitter with that.

780
00:35:20,920 --> 00:35:24,760
Speaker 5: And part of that is part of not accepting Kamala

781
00:35:24,760 --> 00:35:28,839
Speaker 5: Harris as his opponent comes from I think him just

782
00:35:28,920 --> 00:35:32,399
Speaker 5: not respecting her whatsoever, holding her in complete contempt. And

783
00:35:32,480 --> 00:35:35,600
Speaker 5: when you hold your adversary and contempt, it only come

784
00:35:35,719 --> 00:35:37,000
Speaker 5: it only comes back to bite you.

785
00:35:37,239 --> 00:35:37,439
Speaker 2: Yeah.

786
00:35:37,520 --> 00:35:40,800
Speaker 1: Right, Should we take some questions, that's absolutely right, Yeah,

787
00:35:40,840 --> 00:35:43,120
Speaker 1: go ahead and pull up some questions. One last thought

788
00:35:43,160 --> 00:35:45,080
Speaker 1: I had before we get to the questions is I

789
00:35:45,120 --> 00:35:50,240
Speaker 1: think we also learned a lot about Kamala's theory, political

790
00:35:50,280 --> 00:35:53,440
Speaker 1: theory of the case, and her approach in this debate.

791
00:35:53,880 --> 00:35:54,560
Speaker 4: This was not a.

792
00:35:54,520 --> 00:35:57,680
Speaker 1: Debate about here's my policy, Here's how I'm in a delivery.

793
00:35:57,719 --> 00:36:00,799
Speaker 1: It was an attempt to turn it into referendum on

794
00:36:00,920 --> 00:36:01,799
Speaker 1: Donald trump.

795
00:36:01,719 --> 00:36:04,440
Speaker 5: One policy fifteen thousand dollars for startups.

796
00:36:04,800 --> 00:36:07,640
Speaker 1: Yeah right, it WHI was not a bad There was

797
00:36:07,680 --> 00:36:09,080
Speaker 1: also I actually.

798
00:36:08,760 --> 00:36:10,279
Speaker 4: Was at the bathroom. You guys told me about this.

799
00:36:10,360 --> 00:36:13,480
Speaker 1: But Trump gets asked about healthcare and what did he say?

800
00:36:13,560 --> 00:36:15,480
Speaker 4: Like, I have some concepts and.

801
00:36:16,560 --> 00:36:16,840
Speaker 3: I have it.

802
00:36:17,000 --> 00:36:19,359
Speaker 2: I have the concepts of a plan. I have some

803
00:36:19,400 --> 00:36:22,040
Speaker 2: concept as a plan quote, but I'm not president.

804
00:36:21,800 --> 00:36:24,880
Speaker 1: Right, okay, So but it was you know, there was

805
00:36:25,200 --> 00:36:29,640
Speaker 1: very little policy, and that was clearly by design. And

806
00:36:29,840 --> 00:36:34,000
Speaker 1: they also started running this ad today I think where

807
00:36:34,080 --> 00:36:38,239
Speaker 1: it was a reprisal of Obama's crowd size joke.

808
00:36:39,120 --> 00:36:40,360
Speaker 4: And so you know that.

809
00:36:40,160 --> 00:36:45,400
Speaker 1: That rally line was planned to coincide with the Obama

810
00:36:46,000 --> 00:36:49,280
Speaker 1: rally size joke, and you know, so they're they're leaning

811
00:36:49,320 --> 00:36:52,000
Speaker 1: into that as well. That was like their equivalent I

812
00:36:52,000 --> 00:36:54,160
Speaker 1: think of that little Girl was Me moment that they

813
00:36:54,160 --> 00:36:55,280
Speaker 1: had planned in advance.

814
00:36:58,480 --> 00:36:59,799
Speaker 3: So we have a question here.

815
00:37:00,160 --> 00:37:02,720
Speaker 2: Reminder to everybody who was watching on YouTube or rumbo

816
00:37:02,800 --> 00:37:04,799
Speaker 2: or anywhere else who's not watching on locals, we're taking

817
00:37:04,880 --> 00:37:07,239
Speaker 2: questions from our premium subscribers. If you do want to

818
00:37:07,239 --> 00:37:10,360
Speaker 2: ask a question, become a premium subscriber breakingpoints dot com.

819
00:37:10,400 --> 00:37:12,600
Speaker 2: So this is first one is a great one from

820
00:37:12,760 --> 00:37:17,640
Speaker 2: Jude one, two three four. Was this worse for Trump

821
00:37:17,680 --> 00:37:21,200
Speaker 2: than the Biden debate in twenty twenty? Great question for.

822
00:37:21,320 --> 00:37:22,720
Speaker 4: The Biden debate in twenty twenty.

823
00:37:22,760 --> 00:37:24,640
Speaker 3: The one, the first, the bad one.

824
00:37:25,760 --> 00:37:27,640
Speaker 2: I don't have to think about it, I'm not sure

825
00:37:28,080 --> 00:37:29,960
Speaker 2: if I had to say, I think this one was

826
00:37:30,000 --> 00:37:34,520
Speaker 2: probably worse, just because first time against Kamala Biden is

827
00:37:34,520 --> 00:37:38,040
Speaker 2: such a known quantity, so many more questions about Kamala

828
00:37:38,440 --> 00:37:40,960
Speaker 2: and her abilities you rising to her.

829
00:37:41,200 --> 00:37:43,799
Speaker 4: I think the state were hiring the spy, h why

830
00:37:43,840 --> 00:37:44,600
Speaker 4: it matters.

831
00:37:44,840 --> 00:37:47,560
Speaker 5: And the opportunity was so much greater, Like there was

832
00:37:47,600 --> 00:37:50,600
Speaker 5: so much damage he could have done because she's not known.

833
00:37:51,440 --> 00:37:53,000
Speaker 5: There's only so much you can do to a twenty

834
00:37:53,040 --> 00:37:55,080
Speaker 5: twenty Biden, and.

835
00:37:55,160 --> 00:37:59,920
Speaker 1: Those views of her are hardening very quickly. So every

836
00:38:00,080 --> 00:38:03,840
Speaker 1: opportunity you miss to define her, throw her off balance,

837
00:38:03,920 --> 00:38:06,080
Speaker 1: make her appear like you know, the word clouds that

838
00:38:06,120 --> 00:38:10,000
Speaker 1: we got that were incompetent, make her appear like that caricatureish,

839
00:38:10,160 --> 00:38:13,879
Speaker 1: incompetent person that you know, has that image that has

840
00:38:13,920 --> 00:38:17,200
Speaker 1: been spun up over these number of years. Every time

841
00:38:17,239 --> 00:38:21,000
Speaker 1: you miss those opportunities, the clock is ticking down to

842
00:38:21,160 --> 00:38:22,760
Speaker 1: election day point by point.

843
00:38:23,280 --> 00:38:24,200
Speaker 4: So you know.

844
00:38:24,280 --> 00:38:27,160
Speaker 1: Also that Biden debate, I believe it was probably a

845
00:38:27,200 --> 00:38:29,680
Speaker 1: little earlier too, so there was also probably more time

846
00:38:30,280 --> 00:38:33,280
Speaker 1: to recover from it. But they were also just both

847
00:38:33,320 --> 00:38:37,759
Speaker 1: individuals whose images were largely hardened, so it was the

848
00:38:37,800 --> 00:38:38,879
Speaker 1: stakes were a bit lower.

849
00:38:39,000 --> 00:38:42,200
Speaker 2: It was actually later September twenty ninth, crazy to think about.

850
00:38:42,239 --> 00:38:44,560
Speaker 2: I know, wow, September twenty nine, I think twenty twenty

851
00:38:44,600 --> 00:38:46,200
Speaker 2: all right, what else have we got here?

852
00:38:46,400 --> 00:38:47,640
Speaker 3: They say, oh.

853
00:38:47,719 --> 00:38:49,960
Speaker 2: Question, what were your thoughts on the foreign policy sections

854
00:38:50,040 --> 00:38:52,040
Speaker 2: of the debate. Yeah, I think we get all guests.

855
00:38:52,400 --> 00:38:54,880
Speaker 2: I mean this, lady, I'll let you guys handle Israel.

856
00:38:55,120 --> 00:38:58,880
Speaker 2: On Ukraine ridiculous, she basically implied that the only acceptable

857
00:38:58,880 --> 00:39:02,960
Speaker 2: condition of victory in Ukraine his total Ukrainian victory. It's like, okay,

858
00:39:03,120 --> 00:39:04,880
Speaker 2: we're going to be there until the goddamn end of

859
00:39:04,880 --> 00:39:08,160
Speaker 2: the century. Then if that's the plan. On Afghanistan, she

860
00:39:08,320 --> 00:39:10,719
Speaker 2: is both defending the first time that a Democrat has

861
00:39:10,719 --> 00:39:12,320
Speaker 2: defended Biden's withdrawal of Afghanistan.

862
00:39:12,440 --> 00:39:13,719
Speaker 3: Cool. I think the side.

863
00:39:13,760 --> 00:39:14,160
Speaker 4: Let's give her.

864
00:39:14,280 --> 00:39:16,840
Speaker 1: Kana Procy was out there on the Sunday defending it

865
00:39:17,320 --> 00:39:17,879
Speaker 1: at the time.

866
00:39:18,000 --> 00:39:21,520
Speaker 2: So she's like, well, it's good that we got out

867
00:39:21,560 --> 00:39:23,080
Speaker 2: and now we're not paying for it. And I was like, oh,

868
00:39:23,120 --> 00:39:24,719
Speaker 2: this is good, you know, this is good. And at

869
00:39:24,760 --> 00:39:27,640
Speaker 2: the end she's like, and he invited a terrorist to

870
00:39:27,800 --> 00:39:30,360
Speaker 2: Camp David. I'm like, well, you know, we were fighting

871
00:39:30,360 --> 00:39:33,840
Speaker 2: a war against him. So that's probably how you should

872
00:39:34,000 --> 00:39:36,680
Speaker 2: end a war. You want to negotiate at Camp David.

873
00:39:36,680 --> 00:39:37,960
Speaker 2: There's a lot of bad people that have been at

874
00:39:37,960 --> 00:39:40,359
Speaker 2: Camp David. That's how you get some shit to be over.

875
00:39:40,800 --> 00:39:43,839
Speaker 2: It's just didn't coherent. So anyways, that was my general thoughts.

876
00:39:43,840 --> 00:39:44,680
Speaker 2: I'll let you guys handle it.

877
00:39:46,000 --> 00:39:49,480
Speaker 5: On Ukraine, I noticed a little not the whine on

878
00:39:49,560 --> 00:39:52,080
Speaker 5: behalf of Republicans, but there was a moment where the

879
00:39:53,160 --> 00:39:55,479
Speaker 5: David and we were saying, you know, do you want

880
00:39:55,800 --> 00:39:58,080
Speaker 5: Ukraine to win this war? Yes? Multiple times, that's right,

881
00:39:59,040 --> 00:40:01,080
Speaker 5: and Trump's says I want the war to end.

882
00:40:01,400 --> 00:40:02,200
Speaker 3: Yeah.

883
00:40:02,000 --> 00:40:06,760
Speaker 5: Unusually anti war for a presidential candidate. Against the war by.

884
00:40:06,640 --> 00:40:08,480
Speaker 2: Far, in my opinion, like his best answer, because he

885
00:40:08,520 --> 00:40:10,760
Speaker 2: gave the same one to CNN and the media freaked

886
00:40:10,760 --> 00:40:13,080
Speaker 2: out about it then too, and he's obviously on the

887
00:40:13,120 --> 00:40:15,040
Speaker 2: side of the American people who want to also end

888
00:40:15,080 --> 00:40:15,359
Speaker 2: the war.

889
00:40:15,520 --> 00:40:18,880
Speaker 5: But then when he circled over to Kamala Harris for

890
00:40:18,920 --> 00:40:21,279
Speaker 5: that question, he said, I want to ask you about

891
00:40:21,280 --> 00:40:27,200
Speaker 5: support for Ukraine, which is different than saying to ask

892
00:40:27,200 --> 00:40:28,799
Speaker 5: you about support for your grand That's different than saying

893
00:40:28,840 --> 00:40:30,839
Speaker 5: you want Ukraine to win the war. It's a much

894
00:40:30,880 --> 00:40:33,239
Speaker 5: softer way of letting her point into it. But then

895
00:40:33,280 --> 00:40:34,000
Speaker 5: she still went in with.

896
00:40:34,080 --> 00:40:38,439
Speaker 1: The equivalent questions would be, you know, does you are

897
00:40:38,480 --> 00:40:40,000
Speaker 1: you going to just continue.

898
00:40:39,560 --> 00:40:41,840
Speaker 4: This war forever? What point do you?

899
00:40:42,040 --> 00:40:42,759
Speaker 3: At what point do you?

900
00:40:43,000 --> 00:40:44,879
Speaker 4: Is it negotiating and the war?

901
00:40:45,280 --> 00:40:45,440
Speaker 3: Right?

902
00:40:45,680 --> 00:40:48,319
Speaker 1: I mean listen on the foreign policy. So first of all,

903
00:40:48,360 --> 00:40:50,600
Speaker 1: I thought, over all the foreign policy section was Trump's

904
00:40:50,640 --> 00:40:51,319
Speaker 1: strongest section.

905
00:40:51,480 --> 00:40:52,279
Speaker 4: Yes, I thought of.

906
00:40:52,280 --> 00:40:55,240
Speaker 1: The whole debate was was that section. They were roughly

907
00:40:55,280 --> 00:40:59,160
Speaker 1: at a draw in terms of the substance. I mean

908
00:40:59,360 --> 00:41:03,160
Speaker 1: Kama's is the answer was exactly what Kama was Israel

909
00:41:03,280 --> 00:41:07,120
Speaker 1: answer has been the question was framing was actually kind

910
00:41:07,120 --> 00:41:10,400
Speaker 1: of sympathetic to Palestinians. It was like, hey, this has

911
00:41:10,440 --> 00:41:12,560
Speaker 1: been a lot of suffering and this many have died

912
00:41:13,120 --> 00:41:16,960
Speaker 1: and nothing has changed. What would you do different? Nothing

913
00:41:17,640 --> 00:41:21,719
Speaker 1: layup to, you know, put some distance between yourself and

914
00:41:21,760 --> 00:41:26,040
Speaker 1: this president and this horrifically like, you know, atrocious policy

915
00:41:26,120 --> 00:41:28,239
Speaker 1: that is wildly unpopular. But we all knew she wasn't

916
00:41:28,239 --> 00:41:29,680
Speaker 1: going to do that. We talked about it before, and

917
00:41:29,880 --> 00:41:33,840
Speaker 1: she went through her whole like memorized, same things she

918
00:41:33,880 --> 00:41:36,319
Speaker 1: said at the convention, same things she says every time

919
00:41:36,320 --> 00:41:38,879
Speaker 1: she gets these answer, So that sucked. Obviously Trump sucks

920
00:41:38,920 --> 00:41:41,840
Speaker 1: on Israel. You know, he's always and his line is

921
00:41:41,880 --> 00:41:42,959
Speaker 1: always to say, oh, this never.

922
00:41:42,880 --> 00:41:43,440
Speaker 3: Would have happened.

923
00:41:44,400 --> 00:41:46,520
Speaker 4: Okay, well it did, so what now?

924
00:41:46,719 --> 00:41:51,960
Speaker 1: Right in terms of Ukraine, you know, on the substance,

925
00:41:52,080 --> 00:41:55,800
Speaker 1: obviously the worst crime that we committed on Ukraine was

926
00:41:55,840 --> 00:41:58,440
Speaker 1: scuttling and now we have even more confirmation the way

927
00:41:58,480 --> 00:42:01,680
Speaker 1: we scuttled this early piece deal that could have could

928
00:42:01,680 --> 00:42:06,000
Speaker 1: have avoided so much tragedy and loss, et cetera. And

929
00:42:06,600 --> 00:42:09,200
Speaker 1: you know, there's no indication that she has any desire

930
00:42:09,239 --> 00:42:12,399
Speaker 1: to break from the Biden policy on Ukraine. I also

931
00:42:12,400 --> 00:42:14,080
Speaker 1: would be remiss if I didn't say it's one of

932
00:42:14,120 --> 00:42:17,240
Speaker 1: the areas where his policy is actually the most popular

933
00:42:17,960 --> 00:42:20,279
Speaker 1: in terms of you know, when people ask Howsie doing

934
00:42:20,320 --> 00:42:22,319
Speaker 1: on this? In that issue, this is one of the

935
00:42:22,360 --> 00:42:24,759
Speaker 1: areas where he pulls the best. So to separate my

936
00:42:24,800 --> 00:42:27,440
Speaker 1: own feelings on the issue from you know, what I

937
00:42:27,440 --> 00:42:30,439
Speaker 1: think how it will be received. All her bluster about

938
00:42:30,480 --> 00:42:33,880
Speaker 1: the Taliban and Afghanistan and what she said about Ukraine

939
00:42:33,960 --> 00:42:35,840
Speaker 1: and standing with our allies, and that's why we have

940
00:42:35,880 --> 00:42:38,320
Speaker 1: to turn a page on Donald Trump. And also baiting

941
00:42:38,400 --> 00:42:42,879
Speaker 1: him there too, remember about foreign leaders having contempt for him.

942
00:42:42,960 --> 00:42:45,560
Speaker 1: She did not that sex as well, which he again

943
00:42:45,640 --> 00:42:47,920
Speaker 1: took the bait and spent an amount of time talking

944
00:42:47,960 --> 00:42:49,080
Speaker 1: about Victor orbon for.

945
00:42:49,040 --> 00:42:50,600
Speaker 4: God knows what reason.

946
00:42:51,200 --> 00:42:54,040
Speaker 1: But I think that the way she presented those things,

947
00:42:55,160 --> 00:42:57,879
Speaker 1: even though I disagree with her in certain very key

948
00:42:57,880 --> 00:42:59,840
Speaker 1: and important ways, I think it probably did land with

949
00:43:00,080 --> 00:43:00,760
Speaker 1: general audience.

950
00:43:00,760 --> 00:43:03,520
Speaker 2: The funny thing is on the Orbon point, It's like,

951
00:43:03,680 --> 00:43:06,400
Speaker 2: you know, we would be lucky if fifteen percent of

952
00:43:06,400 --> 00:43:09,440
Speaker 2: this country knew who Immanuel Macrone was, like the president.

953
00:43:10,000 --> 00:43:13,640
Speaker 2: It's like to name check Victor orbon Like.

954
00:43:16,440 --> 00:43:19,160
Speaker 1: Because this is a leader that there's a fixation with

955
00:43:19,280 --> 00:43:21,720
Speaker 1: in online right wing subcultures.

956
00:43:22,200 --> 00:43:24,799
Speaker 4: You you know, you drop a true social or.

957
00:43:26,440 --> 00:43:30,640
Speaker 2: I'm like, yeah, Grandma in Wisconsin definitely knows who Victor

958
00:43:30,800 --> 00:43:31,360
Speaker 2: Orbon is.

959
00:43:31,400 --> 00:43:32,440
Speaker 3: Bro Like, Yeah.

960
00:43:32,560 --> 00:43:35,959
Speaker 2: Can can people even name the Prime Minister of the UK?

961
00:43:36,160 --> 00:43:36,799
Speaker 3: Probably not?

962
00:43:37,080 --> 00:43:40,400
Speaker 2: Like, no way, and let that's like our closest ally

963
00:43:40,480 --> 00:43:43,040
Speaker 2: let alone the d president of Hungary.

964
00:43:43,640 --> 00:43:45,440
Speaker 5: Right and maybe somebody in the comments is gonna help

965
00:43:45,520 --> 00:43:48,120
Speaker 5: us out here, because I have had no success finding

966
00:43:48,160 --> 00:43:50,560
Speaker 5: out what the heck Kamala Harris was talking about with

967
00:43:50,880 --> 00:43:56,160
Speaker 5: this thing we're accusing Trump China ships to China.

968
00:43:56,680 --> 00:44:00,799
Speaker 1: Like remember early on she said Trump sold us sound

969
00:44:01,360 --> 00:44:05,920
Speaker 1: by giving our chips to China to make their military

970
00:44:06,000 --> 00:44:07,120
Speaker 1: better or something like that.

971
00:44:07,320 --> 00:44:08,319
Speaker 4: Yeah, I don't know what.

972
00:44:08,400 --> 00:44:09,359
Speaker 3: There's gotta be something.

973
00:44:09,440 --> 00:44:11,880
Speaker 1: I'm sure there's some something if I had to guess,

974
00:44:11,920 --> 00:44:14,160
Speaker 1: even like confused, like I don't know what you're talking about.

975
00:44:14,200 --> 00:44:16,879
Speaker 2: But it's also also certainly not true because the Trump

976
00:44:16,920 --> 00:44:19,680
Speaker 2: administration banned Huawei, the ad Siphius.

977
00:44:19,320 --> 00:44:23,359
Speaker 5: That it arrested like the vice president of right, well

978
00:44:23,440 --> 00:44:23,759
Speaker 5: that was.

979
00:44:23,760 --> 00:44:24,600
Speaker 3: I think that was Canada.

980
00:44:24,640 --> 00:44:28,239
Speaker 2: I'm pretty sure you're talking about possibly with us anyway.

981
00:44:28,239 --> 00:44:29,000
Speaker 3: We don't need to get back.

982
00:44:29,239 --> 00:44:32,680
Speaker 1: But she took the tack in that hole, in that

983
00:44:32,719 --> 00:44:36,320
Speaker 1: whole portion of trying to ount hawk yes, Trump on China.

984
00:44:36,840 --> 00:44:39,720
Speaker 1: She even was like, you sent a tweet about President

985
00:44:39,800 --> 00:44:41,239
Speaker 1: she congratulating him.

986
00:44:41,400 --> 00:44:43,640
Speaker 4: Oh and she did the labakh Yes, your favorite.

987
00:44:43,719 --> 00:44:44,880
Speaker 3: Kamala is a lab leaker.

988
00:44:45,160 --> 00:44:47,560
Speaker 2: She was like, she congratulated President she when he was

989
00:44:47,600 --> 00:44:49,040
Speaker 2: covering up the origins of COVID.

990
00:44:49,080 --> 00:44:52,600
Speaker 5: I'm like, whoa, what you know?

991
00:44:53,200 --> 00:44:53,440
Speaker 3: You know?

992
00:44:53,520 --> 00:44:53,840
Speaker 5: Kama?

993
00:44:53,960 --> 00:44:57,319
Speaker 3: Okay, wait, okay, Ryan, let's at least take that bro.

994
00:44:57,520 --> 00:44:59,440
Speaker 3: We want it took US four years.

995
00:44:59,520 --> 00:45:03,359
Speaker 2: We got the the vice president of a democratic administration

996
00:45:03,440 --> 00:45:05,880
Speaker 2: to admit at least that there were quote unquote questions

997
00:45:06,080 --> 00:45:06,880
Speaker 2: around the cod The.

998
00:45:07,000 --> 00:45:10,720
Speaker 5: Boniest way for her to finish her closing remarks be like, oh,

999
00:45:11,120 --> 00:45:14,960
Speaker 5: and by the way, Trump funded the wuhan.

1000
00:45:14,600 --> 00:45:19,120
Speaker 3: Yeah, yes, yes, and then he covered it up. Yeah,

1001
00:45:19,800 --> 00:45:22,560
Speaker 3: Fauci and Trump Trump, Fauci funded.

1002
00:45:23,120 --> 00:45:27,279
Speaker 5: Just skip Fauci Trump, Yeah, Trump funded the Obama had

1003
00:45:27,520 --> 00:45:28,440
Speaker 5: had a moratorium.

1004
00:45:28,520 --> 00:45:29,080
Speaker 3: Yeah, that's right.

1005
00:45:29,160 --> 00:45:32,480
Speaker 2: Yeah, he lifted, reversed, gotorum.

1006
00:45:33,239 --> 00:45:37,320
Speaker 4: He would have melted right, game over, games set.

1007
00:45:37,200 --> 00:45:39,759
Speaker 5: And every Democrat would be like, yes, that's exactly what.

1008
00:45:40,280 --> 00:45:43,240
Speaker 3: Yes, yes, yeah, you're right, you're absolutely.

1009
00:45:42,920 --> 00:45:47,000
Speaker 1: In the spin room immediately afterwards or whoever, they never

1010
00:45:47,040 --> 00:45:47,480
Speaker 1: believed in.

1011
00:45:47,400 --> 00:45:48,080
Speaker 5: A natural origin.

1012
00:45:49,280 --> 00:45:52,120
Speaker 2: One last question, I think from Parah al Baran, what

1013
00:45:52,200 --> 00:45:54,359
Speaker 2: was the single most determinative moment in the debate and

1014
00:45:54,400 --> 00:45:56,759
Speaker 2: what do you anticipate the cope will be the one

1015
00:45:56,760 --> 00:45:59,640
Speaker 2: that we played, which where he responded on rallies.

1016
00:45:59,719 --> 00:46:01,840
Speaker 3: That was that was when it was solidified for me.

1017
00:46:01,920 --> 00:46:04,240
Speaker 2: I think that was roughly what twenty five thirty minutes

1018
00:46:04,320 --> 00:46:06,200
Speaker 2: or so, and it was the first time of the

1019
00:46:06,200 --> 00:46:08,400
Speaker 2: border section, and I said, that's it. He's lost. He

1020
00:46:08,440 --> 00:46:12,040
Speaker 2: lost it. He has no discipline. He let himself get

1021
00:46:12,120 --> 00:46:13,920
Speaker 2: riled up and angry, and from then on, I think

1022
00:46:13,960 --> 00:46:15,600
Speaker 2: it would just continue to be downhill. And he did

1023
00:46:15,600 --> 00:46:16,799
Speaker 2: it over and over and over again.

1024
00:46:16,880 --> 00:46:20,000
Speaker 5: If people were watching from the skycam, they have seen

1025
00:46:20,040 --> 00:46:24,640
Speaker 5: Sager flopping around like a yeah.

1026
00:46:23,000 --> 00:46:23,400
Speaker 3: So.

1027
00:46:26,400 --> 00:46:28,120
Speaker 2: You believe in things and you see them go to

1028
00:46:28,160 --> 00:46:30,400
Speaker 2: shit on national television, You're like, okay.

1029
00:46:30,160 --> 00:46:34,000
Speaker 1: All right. I'm torn between that moment or that series

1030
00:46:34,040 --> 00:46:36,120
Speaker 1: of moments where she just you know, throws out the

1031
00:46:36,120 --> 00:46:39,480
Speaker 1: bait and he just chases after it like you know whatever,

1032
00:46:39,640 --> 00:46:44,000
Speaker 1: but or the abortion exchange, because I do think that's true,

1033
00:46:44,960 --> 00:46:46,840
Speaker 1: and this is you know, it was kind of Kamala

1034
00:46:46,920 --> 00:46:52,200
Speaker 1: ask frankly because she normally is the one who gets

1035
00:46:52,200 --> 00:46:54,799
Speaker 1: a predictable question and screws it all up. There was

1036
00:46:54,880 --> 00:46:57,480
Speaker 1: nothing more predictable in this debate than that you were

1037
00:46:57,480 --> 00:47:00,040
Speaker 1: going to get asked about abortion. Like you knew this

1038
00:47:00,120 --> 00:47:02,200
Speaker 1: question was coming. You know, specifically you're going to get

1039
00:47:02,200 --> 00:47:04,839
Speaker 1: asked about a national abortion band, which Jade Vance had

1040
00:47:04,840 --> 00:47:06,080
Speaker 1: said you would veto.

1041
00:47:06,360 --> 00:47:07,279
Speaker 4: You knew this.

1042
00:47:07,440 --> 00:47:12,279
Speaker 1: Was coming, and you can't handle You still don't know

1043
00:47:12,320 --> 00:47:15,680
Speaker 1: what to say on this issue. I think It's just

1044
00:47:16,200 --> 00:47:19,080
Speaker 1: that one is so consequential to so many voters. It's

1045
00:47:19,160 --> 00:47:22,120
Speaker 1: clearly been such a motivating factor, and it's just such

1046
00:47:22,160 --> 00:47:26,200
Speaker 1: a clear winner for Democrats that you know, I do

1047
00:47:26,239 --> 00:47:29,640
Speaker 1: think that that also was a very determinive moment.

1048
00:47:30,719 --> 00:47:33,600
Speaker 5: What do you think, right, Yeah, the knock on Paris

1049
00:47:33,680 --> 00:47:37,520
Speaker 5: is that she doesn't prepare. Instead, Trump didn't prepare, and

1050
00:47:37,600 --> 00:47:40,040
Speaker 5: you've just he flopped. I think that's that's right, like

1051
00:47:40,960 --> 00:47:43,319
Speaker 5: him her being able to just lead him by the

1052
00:47:43,360 --> 00:47:49,040
Speaker 5: nose around it just made him look ridiculous, Yeah, and

1053
00:47:49,360 --> 00:47:52,240
Speaker 5: made him miss all the opportunities he has to score

1054
00:47:52,280 --> 00:47:55,720
Speaker 5: points where his policies are more popular.

1055
00:47:56,080 --> 00:47:59,239
Speaker 2: Interesting, So apparently Trump himself actually just came into the

1056
00:48:00,080 --> 00:48:01,520
Speaker 2: been into the spin room, of course.

1057
00:48:01,920 --> 00:48:04,000
Speaker 3: So that's that's generally a bad.

1058
00:48:04,040 --> 00:48:05,600
Speaker 4: That's the sign he knows it went back. You know.

1059
00:48:05,680 --> 00:48:08,200
Speaker 1: I also knew he realized towards the end it went

1060
00:48:08,239 --> 00:48:11,040
Speaker 1: bad because there was a moment when they were getting

1061
00:48:11,080 --> 00:48:13,680
Speaker 1: to the final questions where he starts trying to rattle

1062
00:48:13,719 --> 00:48:17,640
Speaker 1: off everything that he'd clearly you know, prepare, like fracking

1063
00:48:17,719 --> 00:48:20,719
Speaker 1: and medicare for end in private insurance. It was like, oh,

1064
00:48:20,800 --> 00:48:23,320
Speaker 1: you realize the clock is ticking down.

1065
00:48:23,719 --> 00:48:24,480
Speaker 5: All your good stuff.

1066
00:48:24,480 --> 00:48:26,000
Speaker 4: You're trying. You're like, oh shit, I didn't.

1067
00:48:26,160 --> 00:48:28,600
Speaker 3: I saw that too. His last statement, he was trying

1068
00:48:28,640 --> 00:48:30,480
Speaker 3: to just spray and pray all about there.

1069
00:48:30,760 --> 00:48:31,880
Speaker 4: That's exactly where it's.

1070
00:48:31,719 --> 00:48:32,319
Speaker 3: Been long time.

1071
00:48:32,360 --> 00:48:34,560
Speaker 2: That's the other problem, you know, I realized very early

1072
00:48:34,600 --> 00:48:37,879
Speaker 2: on is statistically the vast majority of people only watch

1073
00:48:37,920 --> 00:48:41,120
Speaker 2: for like thirty minutes, Like almost nobody watches this entire thing.

1074
00:48:41,160 --> 00:48:42,680
Speaker 3: You're very rare. If you do.

1075
00:48:42,760 --> 00:48:44,440
Speaker 2: You watch the first thirty like get a sense of it,

1076
00:48:44,440 --> 00:48:46,279
Speaker 2: and you go to bed, especially if you're on the

1077
00:48:46,320 --> 00:48:48,880
Speaker 2: East Coast and those where that was when Trump really whiffed.

1078
00:48:49,560 --> 00:48:52,600
Speaker 2: They had whifted on abortion and then he whifted on immigration,

1079
00:48:52,800 --> 00:48:55,680
Speaker 2: back to back, the two most consequential issues of this

1080
00:48:55,840 --> 00:48:59,080
Speaker 2: entire election. So that was my takeaway, and knowing him too,

1081
00:48:59,120 --> 00:49:01,640
Speaker 2: the fact that he's in that spin room. He is

1082
00:49:01,680 --> 00:49:05,279
Speaker 2: there because he probably immediately turned on the television afterwards,

1083
00:49:05,560 --> 00:49:07,319
Speaker 2: saw the coverage and he goes, I need to go

1084
00:49:07,360 --> 00:49:08,719
Speaker 2: out there and I need to reclaim.

1085
00:49:08,360 --> 00:49:13,279
Speaker 1: He's trying to trying to change the narrative. Spin It's

1086
00:49:13,360 --> 00:49:15,080
Speaker 1: I mean, those days are those days.

1087
00:49:14,920 --> 00:49:16,359
Speaker 4: Are kind of over, you know.

1088
00:49:16,480 --> 00:49:19,600
Speaker 1: It's I think the spin room used to be a

1089
00:49:19,640 --> 00:49:22,719
Speaker 1: lot more consequential than it is at this point. But

1090
00:49:23,480 --> 00:49:26,960
Speaker 1: you know, to your point about his closing statement, the message.

1091
00:49:26,520 --> 00:49:27,960
Speaker 4: There is very effective.

1092
00:49:28,000 --> 00:49:30,080
Speaker 1: It's like, Okay, you got all these great ideas, where

1093
00:49:30,080 --> 00:49:32,080
Speaker 1: were they for three and a half years. How does

1094
00:49:32,080 --> 00:49:33,840
Speaker 1: it take you to the very end of the debate

1095
00:49:33,880 --> 00:49:36,280
Speaker 1: before that ever comes out of your mouth? Totally because

1096
00:49:36,280 --> 00:49:38,040
Speaker 1: that should have been what He could have hit her

1097
00:49:38,080 --> 00:49:41,080
Speaker 1: on that over over and over and over again, and

1098
00:49:41,320 --> 00:49:44,880
Speaker 1: that's how you get a message to actually sink in.

1099
00:49:45,320 --> 00:49:46,680
Speaker 1: You can't just say it once at the end of

1100
00:49:46,719 --> 00:49:47,479
Speaker 1: the debate that.

1101
00:49:47,480 --> 00:49:47,840
Speaker 4: Needed to do.

1102
00:49:47,960 --> 00:49:51,080
Speaker 1: That could have been a refrain, you know, no matter

1103
00:49:51,160 --> 00:49:54,520
Speaker 1: what she was talking about, on Ukraine, on healthcare, on energy,

1104
00:49:54,640 --> 00:49:57,319
Speaker 1: whatever it was, he could have been saying that, and

1105
00:49:57,560 --> 00:50:00,560
Speaker 1: it doesn't come out till the very end when he realizes, like, shit,

1106
00:50:00,640 --> 00:50:02,680
Speaker 1: I got to do something to try to turn this

1107
00:50:02,800 --> 00:50:04,640
Speaker 1: around and put lipstick on this pig.

1108
00:50:04,800 --> 00:50:07,279
Speaker 3: Yeah, that's right, all right. Any closing thoughts, Ryan, what

1109
00:50:07,320 --> 00:50:09,120
Speaker 3: do you think I.

1110
00:50:09,040 --> 00:50:11,520
Speaker 5: Think Trump going out to the spin room is great

1111
00:50:11,600 --> 00:50:13,680
Speaker 5: evidence of the point that you were making earlier that

1112
00:50:13,719 --> 00:50:16,000
Speaker 5: this could that he's going to unravel for a week

1113
00:50:16,080 --> 00:50:18,520
Speaker 5: or two, but so much more could still happen, like

1114
00:50:18,880 --> 00:50:22,440
Speaker 5: maybe there's a break breakthrough in Ukraine or something like

1115
00:50:22,680 --> 00:50:27,400
Speaker 5: the collapse over there, like the election is still wide open.

1116
00:50:27,520 --> 00:50:28,399
Speaker 3: Yes, that's the point.

1117
00:50:28,520 --> 00:50:31,480
Speaker 1: Yeah, that's absolutely Do you so you what do you

1118
00:50:31,480 --> 00:50:33,720
Speaker 1: think is going to happen with the polls with regard

1119
00:50:33,760 --> 00:50:34,320
Speaker 1: to this debate?

1120
00:50:34,360 --> 00:50:37,359
Speaker 5: If anything, I think probably I think she probably does

1121
00:50:37,360 --> 00:50:42,160
Speaker 5: get a little tiny bump from people leaving Trump. Yeah,

1122
00:50:41,760 --> 00:50:43,520
Speaker 5: like a couple of people, you know.

1123
00:50:43,480 --> 00:50:45,120
Speaker 3: You know. And also I think she's going to raise

1124
00:50:45,160 --> 00:50:46,680
Speaker 3: eight Absolutely.

1125
00:50:46,200 --> 00:50:50,040
Speaker 2: She's getting so much money, like like a hundred million

1126
00:50:50,120 --> 00:50:50,680
Speaker 2: dollars like.

1127
00:50:50,640 --> 00:50:53,040
Speaker 5: In a week or and she just has to make

1128
00:50:53,080 --> 00:50:56,080
Speaker 5: people not hate her. Yeah, and she did fine, right,

1129
00:50:56,160 --> 00:50:58,719
Speaker 5: and that if that's the goal in that debate.

1130
00:50:58,480 --> 00:51:02,040
Speaker 1: And be an acceptable people be able to envision you

1131
00:51:02,120 --> 00:51:03,799
Speaker 1: in the role and like rise the case.

1132
00:51:03,920 --> 00:51:05,239
Speaker 5: Still no idea what she stands for.

1133
00:51:05,719 --> 00:51:07,160
Speaker 4: Still no idea what she stands for?

1134
00:51:07,760 --> 00:51:08,120
Speaker 3: Last night?

1135
00:51:08,239 --> 00:51:11,960
Speaker 1: Yeah, no, I mean I think I think we've covered

1136
00:51:12,000 --> 00:51:12,279
Speaker 1: it all.

1137
00:51:12,480 --> 00:51:13,560
Speaker 4: Not a good knight for Trump.

1138
00:51:13,800 --> 00:51:17,000
Speaker 1: Not determinative, right, I think she did herself a lot

1139
00:51:17,000 --> 00:51:20,400
Speaker 1: of favors. And the question has been can she like

1140
00:51:20,480 --> 00:51:23,239
Speaker 1: vibe and meme her way into November?

1141
00:51:23,920 --> 00:51:25,719
Speaker 4: And every day that goes.

1142
00:51:25,520 --> 00:51:27,640
Speaker 1: By We're closer to her being able to pull that

1143
00:51:27,680 --> 00:51:29,560
Speaker 1: off because she's going to get a phenomenal news cycle

1144
00:51:29,560 --> 00:51:31,719
Speaker 1: out of this, right, She's going to get a phenomenal

1145
00:51:31,760 --> 00:51:34,200
Speaker 1: news cycle. The clips are going to be circulating. He's

1146
00:51:34,280 --> 00:51:37,160
Speaker 1: going to be fuming and doing himself no favors. There's

1147
00:51:37,200 --> 00:51:39,200
Speaker 1: going to be all kinds of like leaks out of

1148
00:51:39,239 --> 00:51:41,800
Speaker 1: his campaign, this one, throwing this one under the bus,

1149
00:51:41,840 --> 00:51:46,279
Speaker 1: and all that stuff. And you know, so I think

1150
00:51:46,360 --> 00:51:50,440
Speaker 1: she's the strategy of running out the clock and vibing

1151
00:51:50,480 --> 00:51:53,120
Speaker 1: and meming till November is kind of working out.

1152
00:51:52,960 --> 00:51:55,440
Speaker 2: So certainly could work also now Taylor Swift is waight in.

1153
00:51:55,480 --> 00:51:57,920
Speaker 2: So yeah, my general one is just what a missed opportunity.

1154
00:51:57,960 --> 00:52:01,040
Speaker 2: And it just shows you that the Trump, the you know,

1155
00:52:01,120 --> 00:52:04,680
Speaker 2: the chaotic Trump, the one that everybody said shouldn't appear,

1156
00:52:04,960 --> 00:52:08,040
Speaker 2: he just can't help himself sometimes. And if you're such

1157
00:52:08,040 --> 00:52:10,520
Speaker 2: an easy mark for Kamala, who's not it, let's be

1158
00:52:10,560 --> 00:52:12,400
Speaker 2: hout it, like we're not looking at the most talented

1159
00:52:12,400 --> 00:52:14,640
Speaker 2: politician in modern American history.

1160
00:52:14,719 --> 00:52:15,960
Speaker 3: I think a lot of people are going to read

1161
00:52:15,960 --> 00:52:16,279
Speaker 3: into that.

1162
00:52:16,600 --> 00:52:20,239
Speaker 2: And you, certainly, at the very least you really did

1163
00:52:20,280 --> 00:52:23,120
Speaker 2: not give yourself the opportunity to be that change candidate

1164
00:52:23,160 --> 00:52:25,080
Speaker 2: that people wanted you to be.

1165
00:52:25,480 --> 00:52:27,600
Speaker 3: From those undecided voters we saw in the New York Times.

1166
00:52:27,680 --> 00:52:29,759
Speaker 2: You give Kamala an eagle shot at that, and that

1167
00:52:29,960 --> 00:52:33,040
Speaker 2: very much at You know that that ethos through the

1168
00:52:33,080 --> 00:52:34,359
Speaker 2: election going up.

1169
00:52:34,440 --> 00:52:35,840
Speaker 3: It could be what costs you at the end of the.

1170
00:52:35,840 --> 00:52:38,719
Speaker 2: Day when we're such, when we're this tight, everything matters,

1171
00:52:38,760 --> 00:52:39,560
Speaker 2: and the stakes were crazy.

1172
00:52:39,600 --> 00:52:43,560
Speaker 1: There was no he His greatest asset is like his

1173
00:52:43,760 --> 00:52:46,879
Speaker 1: charm and his levity and when he makes people laugh

1174
00:52:46,920 --> 00:52:49,920
Speaker 1: when they don't even want to laugh. And there was none,

1175
00:52:50,920 --> 00:52:53,160
Speaker 1: none of that side of him tonight.

1176
00:52:53,440 --> 00:52:55,759
Speaker 4: So yeah, it be interesting to see what he's saying.

1177
00:52:56,520 --> 00:52:59,560
Speaker 2: All Right, we will have we will have comprehensive coverage

1178
00:52:59,600 --> 00:53:01,120
Speaker 2: continue in here on breaking points.

1179
00:53:01,200 --> 00:53:02,480
Speaker 3: So we will see you all later.

1180
00:53:12,360 --> 00:53:12,400
Speaker 6: H