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Speaker 1: Hey, guys, thanks for listening to Breaking Points with Crystal

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Speaker 1: and Sager. We're going to be totally upfront with you.

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Speaker 1: We took a big risk going independent to make this work.

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Speaker 1: We need your support to beat the corporate media CNN, Fox, MSNBC.

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Speaker 1: They are ripping this country apart. They are making millions

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Speaker 1: of dollars doing it to help support our mission of

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Speaker 1: making all of us hate each other, less hate the

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Speaker 1: hour early before everyone else. You get to hear our

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Speaker 1: reactions to each other's monologues. You get to participate and

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Speaker 1: weekly ask me any things, and you don't need to

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Speaker 1: hear our annoying voices pitching you like I am right now?

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Speaker 1: com become a Premium member today, which is available in

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Speaker 1: the show notes. Enjoy the show, guys, Good morning, everybody,

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Speaker 1: Happy Tuesday. We have an amazing show for everybody today.

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Speaker 1: What do we have pristl indeed we do. Lots of

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Speaker 1: interestings have to get into today. Also a first time

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Speaker 1: guest Heather Long. We've been referencing her stuff a lot

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Speaker 1: on the show. She's an economics reporter colleague of Jeff

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Speaker 1: Stein's over at the Washington Post, so we wanted to

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Speaker 1: have her on. She also just got a big promotion

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Speaker 1: over there, so we can talk to her about that,

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Speaker 1: and lots of other obviously economic news, including continuing inflation concerns,

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Speaker 1: what that means as we come into the holiday season,

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Speaker 1: as you guys know, if you exist in this country,

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Speaker 1: lots of news about Facebook, lots of questions about this whistleblower,

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Speaker 1: lots of interesting details to kind of dig into their

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Speaker 1: who's behind her, what's her agenda, and what is the

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Speaker 1: most important information to take from the leak of these

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Speaker 1: thousands of documents. We'll get into that. Some new curious

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Speaker 1: details about January sixth. We'll tread a little carefully here,

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Speaker 1: but you know, we've been looking into how many potential

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Speaker 1: federal agents may have been there, may have been involved,

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Speaker 1: other informants, operators, et cetera. Some new indications there that

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Speaker 1: we want to bring to you. Obama is out saying

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Speaker 1: quiet part out loud as he can as he campaigns

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Speaker 1: for Democratic candidates about the mood of the Democratic base.

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Speaker 1: Some horrific new details revealed about some of the I mean,

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Speaker 1: just unconscionable experimentation that's taking place on animals, and doctor

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Speaker 1: Fauci is of course involved as a leader of the

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Speaker 1: National Institute of Health. Tell you about that. Also, you guys,

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Speaker 1: remember that whole situation with Kamala Harris was supposed to

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Speaker 1: be on the View and then seconds before they bring

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Speaker 1: her out, suddenly they pulled to the hosts because they

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Speaker 1: test positive allegedly for coronavirus, and then it turns out

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Speaker 1: they didn't actually have coronavirus. The whole thing was a mess.

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Speaker 1: They never had an explanation of what actually happened here

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Speaker 1: because they'd given the Vice presidents obvious that's all cleared

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Speaker 1: the day before that they'd all been PCR tested and

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Speaker 1: that they were good to go. Now the View has

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Speaker 1: thrown their nurse under the bus. I guess she is.

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Speaker 1: We're going to get to that the fall girls. That

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Speaker 1: will tell you all about that, But we wanted to

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Speaker 1: start with the Facebook story that is so dominating mainstream

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Speaker 1: media right now. Right so, I'm sure everybody saw basically

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Speaker 1: the Facebook papers files. Everybody is referring to have been

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Speaker 1: all over the Internet in the last two days. Essentially,

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Speaker 1: what happened is that Francis Hogan, I hope I'm saying

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Speaker 1: her name correctly, she has come out. She's a former

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Speaker 1: Facebook product manager. She has troves and thousands and thousands

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Speaker 1: of pages of documents. Originally she was leaking and working

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Speaker 1: exclusively with the Wall Street Journal. Now we know that

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Speaker 1: she's actually expanded that to an entire consortium of journalists,

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Speaker 1: many different media organizations, a consortium that she handpicked and selected.

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Speaker 1: And that's the important part, which is that this consortium,

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Speaker 1: this media leak is highly orchestrated by both Francis Hogan

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Speaker 1: and also some people who are funding her who may

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Speaker 1: not necessarily who have a little bit of a bone

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Speaker 1: to pick with Facebook. Now Ben Smith of The New

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Speaker 1: York Times revealed some of this. Let's put this up

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Speaker 1: there on the screen. What we essentially learn here is

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Speaker 1: that Francis Hoogan had met with the Wall Street Journal,

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Speaker 1: originally was leaking her documents, but then all of a sudden,

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Speaker 1: a former Democratic political operative named Bill Burton, who used

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Speaker 1: to work for Barack Obama, all of a sudden was

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Speaker 1: hired in order to manage the process. And what we

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Speaker 1: learn further is that Bill Burton begins setting up meetings

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Speaker 1: with all of these different media outlets, creating this kind

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Speaker 1: of like group chat on Slack in which he requires

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Speaker 1: them to kind of work together and wait before they

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Speaker 1: go ahead and publish the documents. Now, this is specially

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Speaker 1: for a number of reasons. Anytime we start seeing pr

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Speaker 1: PR officials getting paid by people who aren't necessarily the

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Speaker 1: whistleblower themselves, I've got a lot of questions. And we

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Speaker 1: have also learned who the person who is funding some

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Speaker 1: of these operations are. And Glenn Greenwald has shed a

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Speaker 1: lot of light on this. Let's put this up there

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Speaker 1: on the screen from his sub stack, Pierre oh Midyar's

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Speaker 1: financing of the Facebook whistleblower campaign reveals a great deal

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Speaker 1: is his headline there and what he points out Pierre Omidjar,

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Speaker 1: for those of you who don't know, he made his

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Speaker 1: fortune in eBay. He was a long time libertarian. He

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Speaker 1: funded a lot of libertarian causes. But what Glenn points

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Speaker 1: to is that when you have oligarchs who are financing

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Speaker 1: various different projects, and you guys should remember that Glenn

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Speaker 1: knows this because Pierre Omidjar famously financed the Intercept after

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Speaker 1: the Snowden leaks. He was an actual believer in libertarianism,

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Speaker 1: but as Glenn points to, while he was working there

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Speaker 1: all the way up until twenty fifteen, Ohmadjar had nothing.

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Speaker 1: You know, really, he really did not do anything. However,

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Speaker 1: he says to quote, there was never a single occasion

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Speaker 1: to my knowledge, when he attempted to override our journalistic independence. However,

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Speaker 1: what he talks about is that the arrival of Donald

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Speaker 1: Trump on the political scene changed all of that. As

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Speaker 1: Trump send it to the presidency, Omajar became maniacally, monomaniacally

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Speaker 1: obsessed with opposing Trump. Although he stopped tweeting in March

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Speaker 1: twenty nineteen, his twenty fifteen twenty nineteen twitter presents showed

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Speaker 1: that he basically was indistinguishable from the standard daily hysterical

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Speaker 1: MSNBC panels or New York Times op eds. In other words,

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Speaker 1: what happened there is that oh Maajar his libertarianism was

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Speaker 1: only up to a certain point. He was a doctrinaire

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Speaker 1: personal liberal, and his overriding discussed with Trump really started

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Speaker 1: to have him compromise his principles. He became obsessed with

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Speaker 1: the idea that Facebook was responsible for you know, gaslight

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Speaker 1: or for radicalizing the public, whereas you know, I think

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Speaker 1: it's maybe people like Pierre Omanjar, but that's a whole

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Speaker 1: other story. And essentially what has been revealed here is

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Speaker 1: that this is really just a financed campaign by for

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Speaker 1: Francis Hugen and the Facebook whistleblower, by a rival oligarch

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Speaker 1: essentially who hates Trump and has an idea, life logical

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Speaker 1: agenda that doesn't diminish necessarily what the papers are, right,

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Speaker 1: and we can talk about some of that, but there's

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Speaker 1: just a lot of fishy financing. Number one and two.

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Speaker 1: When you look at this whistleblower herself, she says she's

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Speaker 1: currently living in Puerto Rico because she bought bitcoin very early. Cool.

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Speaker 1: You know me too all about bitcoin. I am not

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Speaker 1: a crypto millionaire. Important didn't have enough money to become one.

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Speaker 1: But now she's living down in Puerto Rico, hanging out

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Speaker 1: with her quote crypto friends. You know why because there's

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Speaker 1: no capital gains tax down there for Puerto Rico residents. Well,

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Speaker 1: so there's a lot going on. There is a lot

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Speaker 1: going on, and I think it's important to separate a

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Speaker 1: few things out, just as you were doing there. So listen, Reporters, journalists,

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Speaker 1: they get information from all kinds of sources, some of

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Speaker 1: them above board, some of them very much not above

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Speaker 1: board all the time. Oftentimes, the people who you're receiving

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Speaker 1: information or documents or leaks from have an ideological agenda,

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Speaker 1: They have an ax to grind, They have a certain

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Speaker 1: political perspective that they want out there, or some sort

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Speaker 1: of political goal ultimately in mind. Not always the case,

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Speaker 1: but oftentimes the case. You know. A good example of

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Speaker 1: this that we talked about was the Hunter Biden laptop.

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Speaker 1: Of course, like came from the sketchiest possible. Yeah, and

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Speaker 1: we were very open about it, you know, but it

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Speaker 1: doesn't matter. What matters is what is the information and

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Speaker 1: what is its relevance, And let's sort through that and

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Speaker 1: figure out, you know, what is in the public good

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Speaker 1: here and what's in the public interest of transparency to

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Speaker 1: know about a company in Facebook run by a billionaire

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Speaker 1: that has a tremendous amount of power, although that power

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Speaker 1: may be diminishing. We'll get to that in a moment.

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Speaker 1: So it's important to separate those two things out. However,

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Speaker 1: it also is very important to know if the leaker

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Speaker 1: or whistleblower, however you want to peg Francis Hogan, it's

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Speaker 1: important to know what the ideological agenda is, yes, because

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Speaker 1: this is one of the things we talk about on

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Speaker 1: the show all the time, especially applies oftentimes in any

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Speaker 1: sort of like national security or foreign policy stuff. Follow

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Speaker 1: the money, follow them, follow the ideological agenda, and remember that,

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Speaker 1: you know, everything is being pushed in a certain direction.

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Speaker 1: And that's what you see very clearly with the you know,

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Speaker 1: very polished rollout of Francis Hogan, where she selects to

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Speaker 1: start with a reporter at the Wall Street Journal who

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Speaker 1: she feels, because of his past reporting, is going to

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Speaker 1: view the information in the light that she wants it

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Speaker 1: to him too. Okay, So she starts with that, and

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Speaker 1: then after giving the Wall Street Journal an exclusive for

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Speaker 1: a time, and we covered some of the revelations there

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Speaker 1: which were interesting, including that Facebook, you know, they'd lied

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Speaker 1: about their treatment of elites versus everybody else, and they

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Speaker 1: basically give like white glove treatment to celebrities and political officials,

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Speaker 1: et cetera. So after the Wall Street Journal has their

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Speaker 1: crack at it, that's when she opens the door to

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Speaker 1: this handpicked consortium that they invite onto a zoom call

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Speaker 1: to say, hey, we'll give you guys a crack at it.

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Speaker 1: You all got to work together. We're going to put

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Speaker 1: this embargo in place. This of it is being run

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Speaker 1: by Bill Burton, who, as you point out, former Obama guy.

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Speaker 1: Aspects of this, she says that she has her own

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Speaker 1: financial resources, this is the Ben Smith piece, but that

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Speaker 1: she's accepted help from nonprofit groups that are backed by

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Speaker 1: Pierre Ohmadyar for travel and similar expenses. So she's being

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Speaker 1: funded in a certain sense from this other rival billionaire. Yes,

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Speaker 1: And so it's just important to have that frame in

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Speaker 1: mind as you're looking at this. And of course the

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Speaker 1: political end result is also really important, because even though

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Speaker 1: you do have some people on the right who are

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Speaker 1: actually serious about antitrust and serious about dealing with power

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Speaker 1: and not just interested in like, well, we want to

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Speaker 1: be the censors, not y'all, And even though you do

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Speaker 1: have some people on the left who are similarly serious,

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Speaker 1: we know that there is a dominant strain within the

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Speaker 1: Democratic Party that mostly wants to use these sorts of

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Speaker 1: revelations just to censor and not to challenge power, not

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Speaker 1: to actually think more deeply about the way, not just

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Speaker 1: face Book, but Google. I just saw Google like removed

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Speaker 1: a left leaning news outlet from YouTube, the way that

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Speaker 1: all of these tech oligarchs have so much hold on society,

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Speaker 1: and what we can do about it. So I think

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Speaker 1: those are the pieces that are important to separate out,

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Speaker 1: important to understand what her ideological lean is. She's been,

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Speaker 1: to her credit, pretty upfront. She's been open about what

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Speaker 1: she wants to see happen. Important to understand that and

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Speaker 1: also important to deal with the information and for us

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Speaker 1: to think deeply about what this means about how we

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Speaker 1: might foster a better democracy where you know, you have

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Speaker 1: free speech truly honored and you don't have these tech

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Speaker 1: oligarchs responsible for who gets to say what in the

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Speaker 1: public square. I think that's the most important part. And

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Speaker 1: this isn't really to besmirch her. It's more to say,

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Speaker 1: how is this information being used and to what agenda?

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Speaker 1: And increasingly all across the mainstream media, we are seeing

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Speaker 1: it used as justification for trying to sensor Facebook, either

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Speaker 1: pressure Facebook into self center or really pressuring Congress and

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Speaker 1: the White House and more in order to sensor Facebook.

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Speaker 1: We've already seen the current White House try to dictate

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Speaker 1: to Facebook what posts should stay up and what should not.

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Speaker 1: We've seen them say that if you're banned from Facebook,

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Speaker 1: you should be banned from other platforms. But increasingly, Crystal,

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Speaker 1: I am so frustrated about this because it presumes that

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Speaker 1: Facebook is the most important place, you know, for everything.

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Speaker 1: And guess what, guys, the most important part of the

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Speaker 1: Facebook documents to me. Let's put this up there from

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Speaker 1: the Verge, which is that inside Facebook's Lost Generation they

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Speaker 1: find Facebook's own data shows that it has an increasingly

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Speaker 1: aging boomer user base, that the majority of the people

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Speaker 1: who are active on the platform are real or sorry,

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Speaker 1: are aging, that they are aging up, that young people

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Speaker 1: increasingly are abandoning not just the core product of Blue Facebook,

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Speaker 1: but Instagram as well. My friend Alex Kantrowitz, who has

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Speaker 1: his own to Big Technology newsletter, let's put this up there.

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Speaker 1: This is he grabbed this from inside of the Facebook papers.

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Speaker 1: Their own data shows that teenagers spend two to three

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Speaker 1: times more time on TikTok than they do on Instagram,

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Speaker 1: and TikTok has currently surpassed Instagram for time on app,

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Speaker 1: which means that they have your attention for more time

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Speaker 1: than Instagram has. That is the entire ballgame. So beneath

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Speaker 1: all of this crystal is this monomoniacal obsession with Facebook. Oh,

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Speaker 1: we need to get Facebook to censor. And it's all

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Speaker 1: just because that is where the boomers are. In terms

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Speaker 1: of a broader American culture, it is gradically diminishing in

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Speaker 1: its effect. That's the biggest story in the whole world

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Speaker 1: to me. So this whole like, oh, we got to

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Speaker 1: break up Facebook regulate Facebook. Yeah, I mean that's like

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Speaker 1: a near term problem. But if we want to talk

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Speaker 1: about actual, you know, technology in the future, I think Facebook,

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Speaker 1: by their own admission, Mark Zuckerberg yesterday on his earn

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Speaker 1: went out and said, I believe we actually have this tweet,

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Speaker 1: let's put it up there, which is that he said

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Speaker 1: Facebook will be moving to retooling to make serving young

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Speaker 1: adults the north star rather than optimizing for older people.

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Speaker 1: He says the shift will take years and not months.

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Speaker 1: So to me, the only part of this story that

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Speaker 1: Facebook itself is reacting to is the now Emperor has

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Speaker 1: no clothes moment where you're like, wait, Facebook is kind

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Speaker 1: of a dying company. Now. I'm not going to say

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Speaker 1: they don't make billions trillions of dollars. Definitely true, but

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Speaker 1: it is going much more in the vein of Microsoft,

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Speaker 1: where it's just like this enterprise software that makes a

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Speaker 1: lot of money, but it's like really boring as opposed

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Speaker 1: to the actual driver of culture and politics. So in

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Speaker 1: the near term it's definitely true. But I would say

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Speaker 1: in the future and where the discussion should be focused,

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Speaker 1: it should be a lot more than Facebook. I mean,

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Speaker 1: the fact of the matter is that these same issues

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Speaker 1: that we talk about with Facebook apply to all of

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Speaker 1: these giant tech and social media companies. Whether or not

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Speaker 1: Facebook is on its way in doubtful or on its

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Speaker 1: way out more likely, some of the same principles apply here.

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Speaker 1: And also I would say, look obviously, I mean, listen,

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Speaker 1: I have a teenage daughter. Yeah, she would laugh her

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Speaker 1: head off to think of even getting on Facebook, and

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Speaker 1: she spends way more time on TikTok than she has

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Speaker 1: an Instagram account. She sort of occasionally uses it, yeah yeah,

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Speaker 1: I mean she tabbles it, but she definitely is more

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Speaker 1: sort of addicted to TikTok, no doubt about it. Even

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Speaker 1: my eight year old son would tell you, like, Facebook's

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Speaker 1: for old people, I mean, right, like the conventional wisdom

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Speaker 1: about it is in fact true. On the other hand,

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Speaker 1: we do know right now that Facebook was really instrumental

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Speaker 1: for Trump. I mean they leaned, they leaned very heavily

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Speaker 1: into Facebook. And fortunately or unfortunately, boomers are very politically powerful, right,

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Speaker 1: So this is a group that votes, This is a

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Speaker 1: group that you know and gauges in a lot of

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Speaker 1: cringe meaning and all of those things. So I don't

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Speaker 1: want to say that Facebook is like irrelevant to politics,

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Speaker 1: because I just think that that is not accurate at

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Speaker 1: this time. Is it going to you know, be like

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Speaker 1: a cultural trendsetter among young people? Know? I mean, Zuckerberg

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Speaker 1: is trying to retool it. They are changing the name, even,

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Speaker 1: they're investing in building the metaverse. I don't really know

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Speaker 1: what that means, but probably because I'm too old to

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Speaker 1: understand it. But that's the direction that they're going in

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Speaker 1: to try to recapture the attention of young people here.

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Speaker 1: But there's another issue that I think is important to

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Speaker 1: kind of separate out, which is that there's a difference

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Speaker 1: between being, you know, having the ability to have a

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Speaker 1: platform and being able to say what you want to

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Speaker 1: say without censorship, which is something I am like extremely

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Speaker 1: in support of and I think the banning of Trump

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Speaker 1: and the censorship that we've seen of figures on the

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Speaker 1: ideological right and the ideological left think is a horrific

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Speaker 1: infringement on people's free speech rights because at this point,

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Speaker 1: the public square is these online social media spaces. Part

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Speaker 1: of what we do learn in this revealed though, is

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Speaker 1: that they juice the algorithm to not just sort of

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Speaker 1: allow content that maybe you know, less than ideal or

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Speaker 1: super inflammatory design to make you angry and make you feel,

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Speaker 1: you know, those sort of rageful emotions, but they elevated

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Speaker 1: that so it was not like a neutral surfacing of content.

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Speaker 1: I think that's an important thing to ultimately think about.

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Speaker 1: But look, the bottom line with all of this is

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Speaker 1: that we don't want to take the power from one

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Speaker 1: billionaire Mark Zuckerberg and hand it to another like Pierre

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Speaker 1: oh Midyar. We don't want to take the power from

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Speaker 1: Mark Zuckerberg and hand it to like Joe Biden and

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Speaker 1: Kamal Harris. Oh right, these platforms really need to have

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Speaker 1: their power checked. And you know this isn't like a

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Speaker 1: personal front to either Pierre oh Madiar or Mark zucker

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Speaker 1: It's or Joe Biden for that matter, You should not

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Speaker 1: have one person who has so much control over what

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Speaker 1: are absolutely critical spaces of public debate. There should be

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Speaker 1: a lot more of a democratic process of thinking through

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Speaker 1: how these spaces are operated, how the algorithm works, how things.

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Speaker 1: Because you're going to have certain content, hate speech and

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Speaker 1: threats and those sorts of things that are out of bounds,

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Speaker 1: where do we draw those lines, how do we make

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Speaker 1: sure and this to me is maybe the most critical part,

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Speaker 1: how do we make sure those lines are drawn and

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Speaker 1: enforced in a transparent and consistent manner. Because that's the

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Speaker 1: other thing that you learn from these Facebook files is

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Speaker 1: it's wildly inconsistent of their pants, and there's tons of

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Speaker 1: politics that are involved. They're worried about a backlash from

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Speaker 1: the right, and then they're worried they don't like the

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Speaker 1: content of this outlet or that outlet. So these are

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Speaker 1: not like content neutral. Here's the rule. We're going to

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Speaker 1: apply it, and we're going to disseminate to everyone why

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Speaker 1: and how we applied it. No, these are are deeply

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Speaker 1: political decisions that they that comes across very clearly. There's

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Speaker 1: different treatment for elites versus the rank and file. Because

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Speaker 1: they're worried about pr blow ups if the elites are

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Speaker 1: wrongly censored. They know that their automated algorithms for pulling

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Speaker 1: content are deeply flawed. They know all of these things,

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Speaker 1: and they consistently lie to you about the way that

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Speaker 1: their platform will ultimately operates. So I think there are

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Speaker 1: things to take from this that are interesting, But the

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Speaker 1: overall point here is that, of course, what it's mostly

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Speaker 1: being used to drive towards is just more censorship and

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Speaker 1: more you know, sort of like power vested in a

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Speaker 1: different group of people to decide what's allowed on the

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Speaker 1: platform and what's not. That would be my takeaways. Well,

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Speaker 1: I'm very big believer in algorithmic transparency and in moderation transparency.

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Speaker 1: I think these companies should be should be forced by

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Speaker 1: the FCC in order to publish their moderation guidelines so

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Speaker 1: that way we know whether they're going they're abiding by

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Speaker 1: their rules or not not. That way, there's no politics.

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Speaker 1: You're just like, look, these are the rules, this is

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Speaker 1: what they are, this is how we came to them.

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Speaker 1: You either follow it or you don't, and that is

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Speaker 1: you know. Unfortunately, that kind of common sense stuff doesn't

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Speaker 1: have a lot of headway here in Washington, because, as

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Speaker 1: you said, the real battle is over trying to censor

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Speaker 1: each other, not actually making it a fair playing ground. Yeah,

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Speaker 1: for everybody. And speaking of that January sixth long been

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Speaker 1: pointed at. It's Facebook's fault apparently, and not you know,

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Speaker 1: Trump the president, fostering all this stuff. I don't know

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Speaker 1: why we can't assign more human agency to people. Facebook

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Speaker 1: is not going to force you to go out and

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Speaker 1: storm the capitol, Okay, being in a Facebook group like

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Speaker 1: I've been in some crazy Facebook groups before too, mostly

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Speaker 1: fan ones for TV shows. But let me tell you something,

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Speaker 1: there's some weird stuff that goes down, and nobody forced

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Speaker 1: me to do anything, and nobody forced those people to

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Speaker 1: act like weirdos either, Okay that being said. Representative Thomas Massey,

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Speaker 1: in a most recent congressional hearing, confronted Attorney General Merrick

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Speaker 1: Garland over alleged federal conspirators who were involved in the

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Speaker 1: January sixth capital riots. He put together a mashup of

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Speaker 1: a certain individual who there has been a lot of

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Speaker 1: attention paid to as people have gone through a lot

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Speaker 1: of the video on what happened on January sixth, and

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Speaker 1: we have to be honest. It's extraordinarily suspicious behavior. We

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Speaker 1: actually have that mashup of this individual both on the

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Speaker 1: night of January fifth and during the course of January

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Speaker 1: sixth talking about storming the capitol. After we show you

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Speaker 1: the video, and for those of you who are just listening,

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Speaker 1: you'll be able to hear it as well, we'll tell

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Speaker 1: you a little bit more about this man and what

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Speaker 1: we've learned. Let's take a listen to that video. I

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Speaker 1: never get back tomorrow. I don't even like to say

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Speaker 1: it because I'll be arrested. We need we need to

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Speaker 1: go I'll say it, all right, we need to go

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Speaker 1: in to the capital. Let go out there. I'm we

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Speaker 1: gonna go to jail January tomorrow. We need to go

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Speaker 1: into the capitol, into the capitol. That that thats for

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Speaker 1: that don don the problem speaking. We go to the the capital,

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Speaker 1: the capital of this direction the capitals that Okay, So

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Speaker 1: that was the mash up of all of the different

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Speaker 1: times where you saw this individual saying we need to

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Speaker 1: go into the capitol, all the way until the time

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Speaker 1: that he was actually at the very very front of

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Speaker 1: the group that actually went on into the capitol. Look,

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Speaker 1: obviously Trump also said, hey guys, we're going down to

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Speaker 1: the Capitol, So let's not absolve anybody hear about what

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00:23:16,320 --> 00:23:19,239
Speaker 1: exactly was going on. But this is a question of

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Speaker 1: is this, you know, an agent provocateur? Is this some

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Speaker 1: federal you know agent himself? Is Chris Brothers and sisters

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00:23:26,320 --> 00:23:29,320
Speaker 1: seemed to think he might be. They called him, so

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Speaker 1: you can believe them if you want. There has been

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Speaker 1: now an interesting investigation. This is from a site revolver

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Speaker 1: right wing site, grown Greenwall has spoken with them in

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Speaker 1: the past and they were some of the first in

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Speaker 1: order to get in order to look into this reporting.

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Speaker 1: And we give credit wherever it is due because this

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Speaker 1: is a very thorough report. Can I just pause you there?

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Speaker 1: When mainstream media refuses to cover and investigate these things,

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Speaker 1: we have no choice to cite the people who are

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Speaker 1: you have to look to ideological outlets because they're the

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Speaker 1: only ones who were looking into it, That's right. So

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Speaker 1: with that being said, you know, we went through the

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Speaker 1: report and he definitely you know, brings the receipts in

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Speaker 1: terms of it's all about screenshots and screenshots and here's

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Speaker 1: what happened, and here's the old website, here's the news

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Speaker 1: so with that being said, go ahead and land there.

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Speaker 1: So let's put this on the screen. It's the title,

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Speaker 1: Meet ray Epps, the well, he says, the FED protected provocateur.

429
00:24:20,200 --> 00:24:22,959
Speaker 1: We don't know that, that's not proven. The provocateur who

430
00:24:23,000 --> 00:24:25,320
Speaker 1: appears to have led a very first one six attack

431
00:24:25,359 --> 00:24:29,120
Speaker 1: on the US Capitol. Now ray Epps, the individual who

432
00:24:29,240 --> 00:24:33,240
Speaker 1: you heard and saw there in that video was originally

433
00:24:33,320 --> 00:24:38,240
Speaker 1: placed on the FBI Washington Field Offices Seeking Information list.

434
00:24:38,280 --> 00:24:42,480
Speaker 1: He was identified as Suspect number sixteen. There was an

435
00:24:42,480 --> 00:24:45,800
Speaker 1: Arizona Central article written about mister ray Epps. He was

436
00:24:45,920 --> 00:24:49,040
Speaker 1: of the four hundred and fifty eighty six suspects listed

437
00:24:49,080 --> 00:24:53,399
Speaker 1: on the FBI's Capital Violence Most Wanted List. Like I said,

438
00:24:53,680 --> 00:24:57,480
Speaker 1: suspect number sixteen. They said that he was controlling the crowd.

439
00:24:57,520 --> 00:24:59,480
Speaker 1: They could see some of the stuff that he was saying.

440
00:25:00,240 --> 00:25:02,000
Speaker 1: Obviously he was right there on the front line of

441
00:25:02,040 --> 00:25:04,359
Speaker 1: the very very first group in order to breach the

442
00:25:04,359 --> 00:25:07,480
Speaker 1: Capitol itself. So what they go through and they show

443
00:25:08,080 --> 00:25:12,520
Speaker 1: is that from three point thirty seven am, sorry, from

444
00:25:12,680 --> 00:25:17,119
Speaker 1: January eighth, twenty twenty one, until three thirty seven am

445
00:25:17,240 --> 00:25:22,119
Speaker 1: on January July first, twenty twenty one, every archived version

446
00:25:22,200 --> 00:25:26,800
Speaker 1: of the FBI gov's website shows Ray Epps as suspect

447
00:25:27,000 --> 00:25:32,199
Speaker 1: number sixteen. However, on July first, at that time, Epps

448
00:25:32,480 --> 00:25:36,640
Speaker 1: was taken off of the website. There is no explanation

449
00:25:36,960 --> 00:25:40,480
Speaker 1: as to why he was not. There was no announcement

450
00:25:40,800 --> 00:25:43,960
Speaker 1: around whether his home had been raided, there was non

451
00:25:43,960 --> 00:25:49,040
Speaker 1: announcement about being arrested. He was simply disappeared from the

452
00:25:49,080 --> 00:25:53,359
Speaker 1: list itself. Now this doesn't necessarily mean that he is

453
00:25:53,359 --> 00:25:56,919
Speaker 1: a Federal Cooperator Act. There's no proof necessarily of that.

454
00:25:57,280 --> 00:26:00,800
Speaker 1: But he wasn't arrested, He hasn't been arraigned, he hasn't

455
00:26:00,840 --> 00:26:04,560
Speaker 1: been named in court as many of the January sixth,

456
00:26:04,600 --> 00:26:07,400
Speaker 1: you know, defendants and all those people have. We simply

457
00:26:07,440 --> 00:26:10,560
Speaker 1: know that he was on a public most wanted list

458
00:26:10,600 --> 00:26:13,760
Speaker 1: identified as suspect number sixteen, and then he was taken

459
00:26:13,800 --> 00:26:16,800
Speaker 1: off of it six months later, which does seem to

460
00:26:16,840 --> 00:26:20,199
Speaker 1: be a deliberate action. It's as if he was just

461
00:26:20,280 --> 00:26:23,959
Speaker 1: disappeared and given the central role that he seems to

462
00:26:24,000 --> 00:26:27,960
Speaker 1: have played in instigating the crowd once again, Trump also

463
00:26:27,960 --> 00:26:29,600
Speaker 1: did so as well, so it's not like he was

464
00:26:29,640 --> 00:26:32,040
Speaker 1: the only person, but he certainly was in there and

465
00:26:32,119 --> 00:26:33,920
Speaker 1: was certainly pushing, and he certainly was at the very

466
00:26:34,000 --> 00:26:37,600
Speaker 1: very front of the group himself that it seems mighty

467
00:26:37,600 --> 00:26:40,280
Speaker 1: suspicious to me. So that's what we know, Crystal, right. So,

468
00:26:40,440 --> 00:26:43,600
Speaker 1: and there's a couple other pieces here. So as is

469
00:26:43,600 --> 00:26:47,919
Speaker 1: demonstrated by that video, Ray Epps features in any number

470
00:26:48,000 --> 00:26:50,560
Speaker 1: of videos that have been passed around of that day,

471
00:26:51,200 --> 00:26:54,240
Speaker 1: including in you know New York Times coverage their recreation

472
00:26:54,400 --> 00:26:57,159
Speaker 1: of what happened and went down on January sixth, So

473
00:26:57,400 --> 00:27:00,320
Speaker 1: he featured prominently. As you guys probably know, the was

474
00:27:00,359 --> 00:27:03,800
Speaker 1: a left wing effort to identify a lot of these

475
00:27:03,840 --> 00:27:07,399
Speaker 1: individuals to effectively like turn them into law enforcement. There

476
00:27:07,480 --> 00:27:12,159
Speaker 1: was not just pro public like a grassroots effort to

477
00:27:12,280 --> 00:27:16,560
Speaker 1: identify these individuals and turn them into law enforcement. Epps

478
00:27:16,760 --> 00:27:22,400
Speaker 1: was identified very quickly, very quickly, within days of January eleventh. Yeah,

479
00:27:22,520 --> 00:27:25,600
Speaker 1: by January eleventh, Internet sluice had said, hey, this is

480
00:27:25,640 --> 00:27:27,480
Speaker 1: the guy, this is where he lives, this is his

481
00:27:27,560 --> 00:27:30,639
Speaker 1: Facebook profile. He gave an interview to a local paper

482
00:27:30,760 --> 00:27:32,919
Speaker 1: admitting he was there and some of the things that

483
00:27:33,000 --> 00:27:35,880
Speaker 1: he was up to. So this wasn't if your law

484
00:27:35,960 --> 00:27:40,200
Speaker 1: enforcement and you know, obviously they have been charging plenty

485
00:27:40,240 --> 00:27:43,040
Speaker 1: of people who were there trespassing at the Capitol. If

486
00:27:43,040 --> 00:27:46,040
Speaker 1: you're interested in going after someone who seems to have

487
00:27:46,119 --> 00:27:48,199
Speaker 1: played a fair I don't want to say central, but

488
00:27:48,240 --> 00:27:51,880
Speaker 1: he seems to have played a significant, oul an outsized role.

489
00:27:51,920 --> 00:27:54,600
Speaker 1: That's a good way of putting it and encouraging people

490
00:27:55,040 --> 00:27:58,159
Speaker 1: to break into the Capitol. If you're interested in that

491
00:27:58,200 --> 00:28:00,280
Speaker 1: type of person, this seems like a no brainer you'd

492
00:28:00,320 --> 00:28:03,199
Speaker 1: go after this guy. And yet for months he was

493
00:28:03,240 --> 00:28:06,199
Speaker 1: on this list as suspect sixteen and there were no

494
00:28:06,680 --> 00:28:10,880
Speaker 1: to our knowledge, no arrest made, nothing happened, even though

495
00:28:10,880 --> 00:28:14,480
Speaker 1: again random people on the internet were easily able to

496
00:28:14,520 --> 00:28:16,720
Speaker 1: identify this guy, where he lives, what he does, his

497
00:28:16,800 --> 00:28:19,359
Speaker 1: Facebook profile, what plumber he uses. I mean, all of

498
00:28:19,440 --> 00:28:23,439
Speaker 1: these things were easily available. So that is strange to

499
00:28:23,520 --> 00:28:26,719
Speaker 1: start with, and then the fact that he's just disappeared

500
00:28:26,720 --> 00:28:30,200
Speaker 1: from the website is strange. And then also you mentioned

501
00:28:30,240 --> 00:28:34,919
Speaker 1: Thomas Massey, who you know has been sharing this video

502
00:28:34,960 --> 00:28:38,600
Speaker 1: compilation that we showed you. He also asked Merrit Garland

503
00:28:39,040 --> 00:28:42,920
Speaker 1: directly about this guy, and Garland really fumbled around and

504
00:28:42,960 --> 00:28:46,720
Speaker 1: looked very uncomfortable, and ultimately, you know, effectively dodged the question.

505
00:28:46,960 --> 00:28:50,480
Speaker 1: So look, here's what we know. To bottom line it.

506
00:28:51,480 --> 00:28:55,520
Speaker 1: We know that there was at least one FED informant

507
00:28:55,680 --> 00:28:58,800
Speaker 1: who was involved at the Capitol that day. We know

508
00:28:58,920 --> 00:29:03,480
Speaker 1: that we don't know much on affidavits. Yes, we don't

509
00:29:03,520 --> 00:29:07,440
Speaker 1: know much beyond that. And we also know from how

510
00:29:07,480 --> 00:29:10,920
Speaker 1: the FBI operates that typically you wouldn't have just one

511
00:29:10,960 --> 00:29:13,360
Speaker 1: person at a big event like this. We know that

512
00:29:13,480 --> 00:29:17,560
Speaker 1: some of these groups have been infiltrated sort of notoriously

513
00:29:18,120 --> 00:29:23,160
Speaker 1: by federal agents. I mean, the Proud Boys founder was

514
00:29:23,200 --> 00:29:26,640
Speaker 1: a farmer. Well, that's part of the thing. Crystal Arizona

515
00:29:27,400 --> 00:29:31,560
Speaker 1: Arizona Central reports that EPP's his name and address was

516
00:29:31,600 --> 00:29:35,320
Speaker 1: listed in a leak to database of oath Keeper, not

517
00:29:35,480 --> 00:29:39,440
Speaker 1: members necessarily, but from their websites as people who are

518
00:29:39,480 --> 00:29:42,080
Speaker 1: you know, listed as affiliated with the group. And we

519
00:29:42,160 --> 00:29:45,440
Speaker 1: do know that organizations like that oath Keepers three percent

520
00:29:45,880 --> 00:29:49,120
Speaker 1: these people are riddled with Feds. Like that's basically how

521
00:29:49,160 --> 00:29:51,840
Speaker 1: it's been like that since what the nineteen nineties or

522
00:29:51,880 --> 00:29:54,600
Speaker 1: something ever since Oklahoma City, and so you know it

523
00:29:54,600 --> 00:29:58,360
Speaker 1: wouldn't be a surprise necessarily, and again this isn't even

524
00:29:58,640 --> 00:30:02,240
Speaker 1: alleged he's a federal agent. Only we know there's a

525
00:30:02,440 --> 00:30:06,280
Speaker 1: long history. The Proud Boys founder or whatever, Enrique Torio,

526
00:30:06,320 --> 00:30:08,640
Speaker 1: I think it's name. That guy has a long time

527
00:30:08,720 --> 00:30:11,760
Speaker 1: federal informant. We know there's a long history of informants

528
00:30:11,760 --> 00:30:14,360
Speaker 1: and others who have worked with the FBI who have

529
00:30:14,400 --> 00:30:17,400
Speaker 1: been involved. And look, maybe he was doing it at

530
00:30:17,440 --> 00:30:21,320
Speaker 1: his own behest and then he turned cooperator. That's very possible. Yeah, right,

531
00:30:21,640 --> 00:30:24,360
Speaker 1: somebody who already had history. He says he's a law

532
00:30:24,360 --> 00:30:27,640
Speaker 1: abiding citizen and that he didn't do anything wrong. It's

533
00:30:27,680 --> 00:30:30,920
Speaker 1: actually not known whether he breached the capitol himself, like

534
00:30:30,960 --> 00:30:34,160
Speaker 1: as in whether he actually entered it or not. I

535
00:30:34,240 --> 00:30:37,120
Speaker 1: will say the fact that they have the video and

536
00:30:37,120 --> 00:30:38,960
Speaker 1: for those who are listening, he was literally there the

537
00:30:39,080 --> 00:30:42,360
Speaker 1: night before January fifth, talking about how they have to

538
00:30:42,440 --> 00:30:45,720
Speaker 1: go into the capitol. That is quite stark. Yeah, I

539
00:30:45,760 --> 00:30:48,200
Speaker 1: mean that is the I have not seen that from

540
00:30:48,360 --> 00:30:51,360
Speaker 1: other people who were protesters or not, and it would

541
00:30:51,400 --> 00:30:55,200
Speaker 1: cast some doubt that there weren't some provocateurs and bad

542
00:30:55,240 --> 00:30:57,800
Speaker 1: actors within the group who steered things in that direction.

543
00:30:57,880 --> 00:31:01,080
Speaker 1: This is also not to absolve many of more march

544
00:31:01,120 --> 00:31:04,080
Speaker 1: to the capitol as well. That's right. Listen, this was

545
00:31:04,120 --> 00:31:07,280
Speaker 1: a horrible day. I mean it really was a terrible day.

546
00:31:07,840 --> 00:31:11,240
Speaker 1: It was incredibly fraught. Thank god there weren't more lives lost.

547
00:31:12,080 --> 00:31:16,080
Speaker 1: It was a dangerous and extraordinarily chaotic situation. This is

548
00:31:16,120 --> 00:31:18,240
Speaker 1: not to downplay any of that. This is not to

549
00:31:18,320 --> 00:31:24,160
Speaker 1: downplay Trump's wildly irresponsible, reckless role of incitement, how he

550
00:31:24,240 --> 00:31:27,080
Speaker 1: seemed to delight in what was going on, all of

551
00:31:27,120 --> 00:31:29,200
Speaker 1: those things like. This isn't to downplay it. It's actually

552
00:31:29,200 --> 00:31:30,680
Speaker 1: to say, this was a horrible day, and I want

553
00:31:30,680 --> 00:31:32,280
Speaker 1: to know how it actually happened. Yeah, that's right. Yeah,

554
00:31:32,320 --> 00:31:39,120
Speaker 1: not like the DC ideologically driven narrative of what happened

555
00:31:39,120 --> 00:31:42,520
Speaker 1: and why. I want to actually understand how it came

556
00:31:42,560 --> 00:31:46,200
Speaker 1: to this point. And so if there were, if there

557
00:31:46,200 --> 00:31:49,920
Speaker 1: were federal agents who were involved in incitement, I want

558
00:31:49,920 --> 00:31:53,000
Speaker 1: to know that, yeah, because it certainly, lord knows, wouldn't

559
00:31:53,000 --> 00:31:56,880
Speaker 1: be the first time that you had federal agents who

560
00:31:56,920 --> 00:32:01,120
Speaker 1: were deeply involved in crafting plot to the point that

561
00:32:01,280 --> 00:32:03,120
Speaker 1: you know, those plots like the Gretchen whitmor thing that

562
00:32:03,160 --> 00:32:05,920
Speaker 1: we covered may not have ever come to fruition if

563
00:32:05,960 --> 00:32:08,640
Speaker 1: it wasn't for all the many Feds involved being like

564
00:32:08,800 --> 00:32:10,800
Speaker 1: here go here, and here's the money to do it,

565
00:32:10,800 --> 00:32:13,200
Speaker 1: and let's call these guys and I've gotten a great idea.

566
00:32:13,480 --> 00:32:16,080
Speaker 1: We saw this with the War on Terror. How many

567
00:32:16,160 --> 00:32:20,800
Speaker 1: young Musslim men were effectively preyed upon by federal agents, radicalized,

568
00:32:21,160 --> 00:32:24,280
Speaker 1: talked into some tangential involvement in a plot, and then

569
00:32:24,320 --> 00:32:27,360
Speaker 1: they're snapped up and criminalized and thrown in prison for

570
00:32:27,400 --> 00:32:29,800
Speaker 1: the rest of their lives to serve a political agenda

571
00:32:29,840 --> 00:32:32,600
Speaker 1: and help heighten the careers of politicians who are involved

572
00:32:32,600 --> 00:32:36,640
Speaker 1: in this. So that's why we're covering this because we

573
00:32:36,800 --> 00:32:39,240
Speaker 1: actually care about what happened on that day, and not

574
00:32:39,400 --> 00:32:41,760
Speaker 1: just from like an ideological agenda. Bring it back to

575
00:32:41,800 --> 00:32:44,360
Speaker 1: the Facebook segment. We care because we know how it's

576
00:32:44,400 --> 00:32:47,520
Speaker 1: being used. They want this to be some maga thing

577
00:32:47,560 --> 00:32:50,560
Speaker 1: which was organized on Facebook, so they can sensor Facebook

578
00:32:50,600 --> 00:32:52,680
Speaker 1: and so then they can use a security state in

579
00:32:52,760 --> 00:32:56,160
Speaker 1: order to criminalize, you know, half the population. Now I

580
00:32:56,360 --> 00:32:58,920
Speaker 1: want it to be, Hey, how does this happen? How

581
00:32:58,960 --> 00:33:01,120
Speaker 1: exactly do we get bunch of people who have no

582
00:33:01,240 --> 00:33:04,320
Speaker 1: faith in the entire system and believe an idiot like

583
00:33:04,360 --> 00:33:06,440
Speaker 1: Trump and are willing to put their life on the

584
00:33:06,480 --> 00:33:09,680
Speaker 1: line for a complete fantasy. That's a lot more interesting

585
00:33:09,760 --> 00:33:13,400
Speaker 1: question to me. And also with this does come out

586
00:33:13,480 --> 00:33:16,120
Speaker 1: in terms of federal cooperators and all of that who

587
00:33:16,120 --> 00:33:20,400
Speaker 1: were involved and possibly even instigators. It undermines the central

588
00:33:20,440 --> 00:33:24,840
Speaker 1: idea that the Feds themselves should be responsible for surveilling

589
00:33:25,120 --> 00:33:28,200
Speaker 1: and for you know, creating even more operations against these

590
00:33:28,240 --> 00:33:30,760
Speaker 1: types of It's a very central question, are you keep

591
00:33:30,800 --> 00:33:34,200
Speaker 1: actually keeping us safe? Are you making more are you

592
00:33:34,240 --> 00:33:36,280
Speaker 1: creating more credit? I want to be more safe, I

593
00:33:36,320 --> 00:33:38,600
Speaker 1: want to live in more harmonious place. And I'm beginning

594
00:33:38,680 --> 00:33:41,000
Speaker 1: to suspect I think many of you are too, that

595
00:33:41,080 --> 00:33:43,280
Speaker 1: the people tasked with that are not doing so good

596
00:33:43,280 --> 00:33:46,440
Speaker 1: of a job. Yes, that's all. And the other piece

597
00:33:46,480 --> 00:33:49,680
Speaker 1: of this that we wanted to rental here is there

598
00:33:49,760 --> 00:33:52,160
Speaker 1: was a piece that was making the rounds yesterday and

599
00:33:52,240 --> 00:33:56,320
Speaker 1: sided on cable news. Although even some of the sort

600
00:33:56,360 --> 00:34:01,240
Speaker 1: of most iconic resistance sits were a little of this piece.

601
00:34:01,320 --> 00:34:04,440
Speaker 1: Let's sort of this up from Rolling Stone. So again,

602
00:34:05,040 --> 00:34:08,800
Speaker 1: so the headline here says exclusive January sixth. Protest organizers

603
00:34:08,840 --> 00:34:12,640
Speaker 1: say they participated in dozens of planning meetings with members

604
00:34:12,680 --> 00:34:16,759
Speaker 1: of Congress and White House staff. Now that headline and

605
00:34:16,800 --> 00:34:20,080
Speaker 1: the way that it was portrayed by some of the

606
00:34:20,400 --> 00:34:24,240
Speaker 1: I would say less above board actors, is that members

607
00:34:24,280 --> 00:34:29,000
Speaker 1: of Congress were directly involved in planning the incursion into

608
00:34:29,080 --> 00:34:31,799
Speaker 1: the Capitol. That's what it sounds like, right, But if

609
00:34:31,800 --> 00:34:34,960
Speaker 1: you actually read through the piece, they were involved in

610
00:34:35,040 --> 00:34:40,640
Speaker 1: planning the protests exactly. Protests are allowed, even if it's

611
00:34:40,680 --> 00:34:44,560
Speaker 1: for a cause that's a pure ridiculous fantasy and that

612
00:34:44,640 --> 00:34:47,839
Speaker 1: you don't support. You're still allowed to protest, and you're

613
00:34:47,880 --> 00:34:51,720
Speaker 1: allowed to be involved in planning that protest. That's really

614
00:34:51,760 --> 00:34:55,799
Speaker 1: all that this piece ultimately alleges. And so when we

615
00:34:55,840 --> 00:35:02,080
Speaker 1: talk about how there's an ideological agenda among Democrats to

616
00:35:02,640 --> 00:35:05,480
Speaker 1: you know, make this into it was its Facebook's fault

617
00:35:05,560 --> 00:35:10,400
Speaker 1: and it's these particular political members of Congress who have

618
00:35:10,560 --> 00:35:14,719
Speaker 1: power their rival opponents, it's their fault. And then you know,

619
00:35:14,760 --> 00:35:17,080
Speaker 1: on the right you have an attempt to say like, oh,

620
00:35:17,200 --> 00:35:19,600
Speaker 1: this was all just federal agents and there was no

621
00:35:19,760 --> 00:35:22,319
Speaker 1: organic anything, and of course Trump's totally absolved in all

622
00:35:22,360 --> 00:35:25,880
Speaker 1: of this. So anyway, all of this is to say,

623
00:35:26,040 --> 00:35:29,600
Speaker 1: we're trying to sort through what we actually know and

624
00:35:30,000 --> 00:35:32,440
Speaker 1: come to some understanding of how we came to that

625
00:35:32,640 --> 00:35:37,160
Speaker 1: point that is not just solely filtered through an ideological lens. Exactly, right. Hey,

626
00:35:37,200 --> 00:35:40,760
Speaker 1: So remember how we told you how awesome premium membership was. Well,

627
00:35:40,800 --> 00:35:42,920
Speaker 1: here we are again to remind you that becoming a

628
00:35:42,960 --> 00:35:45,640
Speaker 1: premium member means you don't have to listen to our

629
00:35:45,680 --> 00:35:48,520
Speaker 1: constant please for you to subscribe. So what are you

630
00:35:48,520 --> 00:35:51,080
Speaker 1: waiting for? Become a premium member today by going to

631
00:35:51,200 --> 00:35:53,560
Speaker 1: Breakingpoints dot com, which you can click on in the

632
00:35:53,560 --> 00:35:58,879
Speaker 1: show notes. Our former president Barack Obama has been out

633
00:35:58,920 --> 00:36:02,080
Speaker 1: campaigning for or Terry mccolliffe in Virginia and whoever the

634
00:36:02,120 --> 00:36:04,000
Speaker 1: Democrat is that's running for governor of New Jersey. I

635
00:36:04,000 --> 00:36:07,600
Speaker 1: can't remember his name. And he had a pretty interesting moment,

636
00:36:08,160 --> 00:36:13,040
Speaker 1: fairly revealing, quiet, part out loud moment while candle hating

637
00:36:13,680 --> 00:36:16,240
Speaker 1: in New Jersey. Yeah, he kind of told on himself

638
00:36:16,280 --> 00:36:19,280
Speaker 1: here on this one, but also told on Joe Biden

639
00:36:19,560 --> 00:36:22,120
Speaker 1: and on how the way that the Democratic base may

640
00:36:22,160 --> 00:36:23,799
Speaker 1: be feeling right now, let's take a listen to that.

641
00:36:24,400 --> 00:36:28,160
Speaker 1: I know why, Sometimes folks just get tired and maybe

642
00:36:28,200 --> 00:36:31,760
Speaker 1: they say, ah, you know, I'm not gonna bother voting

643
00:36:31,800 --> 00:36:34,960
Speaker 1: this time. But here's the thing. We can't afford to

644
00:36:34,960 --> 00:36:39,960
Speaker 1: be tired. I remember twenty sixteen, folks said, you know,

645
00:36:40,239 --> 00:36:44,880
Speaker 1: I'm not inspired. You know, Obama was okay, but we

646
00:36:44,920 --> 00:36:47,600
Speaker 1: didn't get everything I wanted. So I'm just gonna sit

647
00:36:47,640 --> 00:36:50,120
Speaker 1: in the the next day. And you know, y' all know

648
00:36:50,160 --> 00:36:54,960
Speaker 1: how that turned out. That's what happens when you're not

649
00:36:55,000 --> 00:37:00,480
Speaker 1: paying attention. That's what happens when you become complacent or

650
00:37:00,520 --> 00:37:04,640
Speaker 1: you let your frustration lead to inaction. We cannot afford

651
00:37:04,719 --> 00:37:07,359
Speaker 1: to be tired because of the young people here and

652
00:37:07,400 --> 00:37:11,640
Speaker 1: the ones who are coming. I know it's hard. Phil

653
00:37:11,719 --> 00:37:14,800
Speaker 1: doesn't claim he's gonna solve every problem in New Jersey

654
00:37:14,880 --> 00:37:18,240
Speaker 1: right away. I didn't solve every problem when I was president.

655
00:37:18,680 --> 00:37:22,960
Speaker 1: But the fact is that as hard as it is,

656
00:37:24,160 --> 00:37:28,359
Speaker 1: we can still make it better. It's hard to undo

657
00:37:28,600 --> 00:37:32,080
Speaker 1: the legacy of discrimination that goes back centuries, but we

658
00:37:32,120 --> 00:37:35,360
Speaker 1: can make it better. It's hard to deal with special

659
00:37:35,400 --> 00:37:38,359
Speaker 1: interests who want to keep the status quo when you're

660
00:37:38,400 --> 00:37:40,759
Speaker 1: trying to make the economy more fair and just, but

661
00:37:40,880 --> 00:37:44,799
Speaker 1: you can make it better. It's hard in a big

662
00:37:44,840 --> 00:37:47,800
Speaker 1: country where people disagree to get everybody moving in the

663
00:37:47,840 --> 00:37:49,920
Speaker 1: same direction. But we can do better than we're doing well.

664
00:37:50,760 --> 00:37:55,200
Speaker 1: We really can't. We can make it better. And when

665
00:37:55,200 --> 00:37:59,080
Speaker 1: you've got the right person in the job. We might

666
00:37:59,120 --> 00:38:02,760
Speaker 1: not get every single person employed, but we can get

667
00:38:02,920 --> 00:38:06,800
Speaker 1: more people more jobs. We may not get every child

668
00:38:06,840 --> 00:38:08,960
Speaker 1: the best education in the world, right here in Newark,

669
00:38:09,200 --> 00:38:11,960
Speaker 1: we can give a lot more kids the better education

670
00:38:12,080 --> 00:38:15,919
Speaker 1: here in Newark. I didn't get every American healthcare, but boy,

671
00:38:15,960 --> 00:38:18,600
Speaker 1: we got a whole lot more people in America. How

672
00:38:18,719 --> 00:38:23,480
Speaker 1: sure it makes the difference when we decide to make

673
00:38:23,520 --> 00:38:26,919
Speaker 1: things better. When you've got somebody in your corner who's

674
00:38:26,960 --> 00:38:30,120
Speaker 1: shown you that they will work for you, who has

675
00:38:30,160 --> 00:38:33,880
Speaker 1: a track record of accomplishment, you got to go out

676
00:38:33,960 --> 00:38:37,400
Speaker 1: there and work for them, not because everything's going to

677
00:38:37,440 --> 00:38:40,320
Speaker 1: suddenly be perfect, but because it's going to be better

678
00:38:41,200 --> 00:38:46,239
Speaker 1: and you're preventing others from making it worse. So there's

679
00:38:46,280 --> 00:38:49,920
Speaker 1: a lot that's interesting there. First of all, classic Obama,

680
00:38:50,640 --> 00:38:54,040
Speaker 1: rather than demanding anything of the political class, it's on you.

681
00:38:54,440 --> 00:38:56,839
Speaker 1: It's your fault you didn't show up. It's not his fault.

682
00:38:56,880 --> 00:38:59,080
Speaker 1: It's not his fault that he didn't meet your expectation.

683
00:38:59,200 --> 00:39:01,960
Speaker 1: It's not his fault that Democrats have been promising prescription

684
00:39:02,040 --> 00:39:04,680
Speaker 1: drug reforms since two thousand and six and haven't delivered.

685
00:39:05,200 --> 00:39:09,120
Speaker 1: It's your fault for being lazy and complacent and failing

686
00:39:09,160 --> 00:39:11,600
Speaker 1: to take action. That's number one. The other thing that's

687
00:39:11,640 --> 00:39:15,839
Speaker 1: really interesting here is, look, what is Obama's interest right now?

688
00:39:15,880 --> 00:39:19,480
Speaker 1: Obama's interest is in preserving Obama's legacy, and so he's

689
00:39:19,600 --> 00:39:22,239
Speaker 1: very invested in this narrative that like, well, there's just

690
00:39:22,280 --> 00:39:25,840
Speaker 1: not that much that politicians can really do. Right The

691
00:39:25,920 --> 00:39:28,359
Speaker 1: healthcare thing is particularly revealing. It's like, we didn't get

692
00:39:28,400 --> 00:39:31,880
Speaker 1: everybody health care, even though that was your promise, but

693
00:39:32,000 --> 00:39:35,080
Speaker 1: you know, we did get some people healthcare. We can't

694
00:39:35,120 --> 00:39:37,640
Speaker 1: do that much, but we can do some tinkering around

695
00:39:37,640 --> 00:39:42,280
Speaker 1: the edges here. So the message is lower your expectations.

696
00:39:43,280 --> 00:39:46,560
Speaker 1: Even in a best case scenario like Obama had when

697
00:39:46,560 --> 00:39:48,960
Speaker 1: he had control of Congress and a super majority in

698
00:39:49,000 --> 00:39:54,080
Speaker 1: the Senate sixty we're going to dramatically underperform even in

699
00:39:54,120 --> 00:39:57,640
Speaker 1: the best case scenario. So just accept that, you know,

700
00:39:57,719 --> 00:40:00,399
Speaker 1: what you're going to get is effectively peanuts. And if

701
00:40:00,400 --> 00:40:03,600
Speaker 1: you don't show up enthusiastically to vote in favor of

702
00:40:03,640 --> 00:40:06,799
Speaker 1: those peanuts every damn time, that's on you and never

703
00:40:06,880 --> 00:40:09,400
Speaker 1: on the politician. Yeah, what they want to do is

704
00:40:09,520 --> 00:40:13,960
Speaker 1: basically make it so that their record is completely pristine.

705
00:40:14,080 --> 00:40:16,880
Speaker 1: There's nothing better that he could have done. And also,

706
00:40:17,080 --> 00:40:19,560
Speaker 1: look at the other guy. They suck. That's all Obama

707
00:40:19,640 --> 00:40:21,640
Speaker 1: is saying. How far of a cry is that from

708
00:40:21,680 --> 00:40:25,360
Speaker 1: two thousand and eight. It's amazing, actually, But it's important

709
00:40:25,400 --> 00:40:28,279
Speaker 1: to watch because Obama is admitting a couple of things there.

710
00:40:28,520 --> 00:40:31,160
Speaker 1: Number one, that his two thousand and eight promise was

711
00:40:31,160 --> 00:40:34,239
Speaker 1: a total and complete failure. But number two, that's the

712
00:40:34,280 --> 00:40:37,880
Speaker 1: first time I've ever heard him actually admit that people

713
00:40:38,160 --> 00:40:42,480
Speaker 1: realize that they were not getting what he promised back

714
00:40:42,520 --> 00:40:46,080
Speaker 1: in twenty sixteen, and that I've played that clip so

715
00:40:46,160 --> 00:40:48,799
Speaker 1: many different times where Obama would come out and be like,

716
00:40:49,320 --> 00:40:51,440
Speaker 1: justine on my name, notp be on the ballot, My

717
00:40:51,640 --> 00:40:54,320
Speaker 1: legacy is on the ballot, Justice is on the ballot.

718
00:40:54,320 --> 00:40:57,080
Speaker 1: The last speachit he gave of the Hillary twenty sixteen

719
00:40:57,120 --> 00:41:01,160
Speaker 1: campaign and boom, complete and total failure. That's the first

720
00:41:01,160 --> 00:41:05,040
Speaker 1: time I've ever heard him actually reckon with that. But worse, Crystal,

721
00:41:05,360 --> 00:41:07,760
Speaker 1: as you said, it tells us where we are with Biden.

722
00:41:08,040 --> 00:41:12,240
Speaker 1: Because Obama knows that this is Biden's twenty ten moment.

723
00:41:12,480 --> 00:41:14,799
Speaker 1: He can see the exact same change within the air.

724
00:41:15,040 --> 00:41:18,480
Speaker 1: You know. Speaking of Virginia, I just looked Emerson College,

725
00:41:18,480 --> 00:41:21,680
Speaker 1: which had the most accurate poll of twenty thirteen governor's race,

726
00:41:21,840 --> 00:41:24,760
Speaker 1: has Glenn Youngkin up by one percent in their final

727
00:41:24,800 --> 00:41:27,880
Speaker 1: poll of the race. Maybe it's total bs okay, I

728
00:41:27,960 --> 00:41:30,880
Speaker 1: have no idea. I would personally bet that Republicans are

729
00:41:30,920 --> 00:41:33,320
Speaker 1: generally undercounted as they have been over the last I

730
00:41:33,320 --> 00:41:36,759
Speaker 1: don't know six years in polls. And look, maybe we're

731
00:41:36,760 --> 00:41:39,240
Speaker 1: going to see a massive upset. But as Kyle Condack

732
00:41:39,280 --> 00:41:42,080
Speaker 1: said on our show yesterday, if mccaulliff wins by one

733
00:41:42,320 --> 00:41:45,240
Speaker 1: in a Biden plus ten state, that's a total disaster.

734
00:41:45,600 --> 00:41:49,760
Speaker 1: I mean, you lost nine points. That's exactly what's happening here.

735
00:41:50,000 --> 00:41:54,520
Speaker 1: Obama sees the same apathy and his only response is yeah,

736
00:41:54,560 --> 00:41:56,560
Speaker 1: but the other guy suck. How did it work out

737
00:41:56,600 --> 00:41:59,000
Speaker 1: for you in twenty ten? But more importantly, what does

738
00:41:59,040 --> 00:42:02,880
Speaker 1: that say about you? Man? You were elected to transcend

739
00:42:03,120 --> 00:42:05,160
Speaker 1: all of that? And I actually encourage people. I read

740
00:42:05,200 --> 00:42:08,880
Speaker 1: his book, and Obama's a smart guy, but he rationalizes

741
00:42:09,120 --> 00:42:12,760
Speaker 1: everything every turn. It's not his fault, it's the other people's.

742
00:42:12,880 --> 00:42:15,720
Speaker 1: So I was boxed in by the system. Your job

743
00:42:16,120 --> 00:42:18,200
Speaker 1: is to be elected to transcend that. I've got books

744
00:42:18,200 --> 00:42:22,319
Speaker 1: with lbjrfk FDR back there, you know many more at home.

745
00:42:22,520 --> 00:42:25,359
Speaker 1: The history of the American presidency is exactly or at

746
00:42:25,440 --> 00:42:28,799
Speaker 1: least the good ones who transcend all of those things

747
00:42:28,800 --> 00:42:30,840
Speaker 1: and they figure out a way and they create a

748
00:42:30,880 --> 00:42:33,040
Speaker 1: new era. And he had all the tools and he

749
00:42:33,080 --> 00:42:35,239
Speaker 1: completely broke. He had all the tools and more and

750
00:42:35,320 --> 00:42:38,080
Speaker 1: at a pivot point, and this is why his time

751
00:42:38,080 --> 00:42:41,440
Speaker 1: in office so important and leads us to where we

752
00:42:41,480 --> 00:42:44,640
Speaker 1: are today, leads us to Trump, leads us to this

753
00:42:44,760 --> 00:42:50,239
Speaker 1: moment of the national depression and nihilism effectively, because what's

754
00:42:50,400 --> 00:42:54,880
Speaker 1: that speech? Not only right, we were like, I mean,

755
00:42:54,920 --> 00:42:57,080
Speaker 1: we're not even going to promise you that much anymore.

756
00:42:57,120 --> 00:42:58,680
Speaker 1: Like at least we used to try to get you

757
00:42:58,800 --> 00:43:01,400
Speaker 1: to believe in something. Now we're gonna say, well, we

758
00:43:01,480 --> 00:43:03,920
Speaker 1: can't really do all that much for you, but you

759
00:43:03,960 --> 00:43:06,080
Speaker 1: should probably vote for us anyway, because the other dude

760
00:43:06,160 --> 00:43:08,600
Speaker 1: is worse. I mean, that's that's what they've collapsed down to.

761
00:43:09,160 --> 00:43:13,279
Speaker 1: And you know, you see with Obama, how the only

762
00:43:13,360 --> 00:43:16,120
Speaker 1: time he really jumps into the political phrase is not

763
00:43:16,160 --> 00:43:18,000
Speaker 1: something he likes. He doesn't like to get his hands

764
00:43:18,040 --> 00:43:22,120
Speaker 1: dirty and such are such tawdry affairs. The only time

765
00:43:22,160 --> 00:43:25,040
Speaker 1: he does it is to stop like the Bernie Sanders

766
00:43:25,200 --> 00:43:30,000
Speaker 1: type movements. Why, because Obama's trying to persuade you, like,

767
00:43:30,760 --> 00:43:33,960
Speaker 1: Obama Care Lets be Real is not that great, but

768
00:43:34,080 --> 00:43:35,960
Speaker 1: it's a little bit better, and it was the best

769
00:43:36,000 --> 00:43:39,040
Speaker 1: we could do at the time. Bernie and his ilk

770
00:43:39,080 --> 00:43:43,800
Speaker 1: are saying, no, actually, we could have universal healthcare for everyone.

771
00:43:44,239 --> 00:43:50,920
Speaker 1: Obama has a personal, deep, personal interest in proving that

772
00:43:50,920 --> 00:43:54,120
Speaker 1: that's false, proving that that's impossible, and so that's why

773
00:43:54,160 --> 00:43:57,640
Speaker 1: you see him intervening to make sure Keith Ellison doesn't

774
00:43:57,719 --> 00:43:59,799
Speaker 1: end up head of the DNC. Then instead you get

775
00:44:00,200 --> 00:44:04,080
Speaker 1: Obama's guy, Tom Perez. That's why he makes sure to

776
00:44:04,680 --> 00:44:06,920
Speaker 1: intervene in the last moments of the Democratic Programmy this

777
00:44:07,000 --> 00:44:08,680
Speaker 1: time around, to make sure that it ends up being

778
00:44:08,800 --> 00:44:11,840
Speaker 1: Joe Biden and that Bernie Sanders is stopped in his

779
00:44:12,000 --> 00:44:14,319
Speaker 1: tracks and he's making phone calls behind the scenes. So

780
00:44:15,000 --> 00:44:19,480
Speaker 1: that's what his interest is. There's also in Virginia, just

781
00:44:19,520 --> 00:44:21,719
Speaker 1: to show you the way that this plays out sort

782
00:44:21,760 --> 00:44:27,000
Speaker 1: of on the ground. This contest in Virginia is effectively

783
00:44:27,000 --> 00:44:31,440
Speaker 1: coming down to whether mccaulliff could scare people enough about Trump.

784
00:44:31,520 --> 00:44:34,040
Speaker 1: It's not about a forward looking agenda for mcaullff. It's

785
00:44:34,080 --> 00:44:36,560
Speaker 1: not really about a forward looking agenda for Glenn Youngkin either.

786
00:44:36,840 --> 00:44:39,160
Speaker 1: It's about who can sort of freak the other side out. More.

787
00:44:39,760 --> 00:44:42,280
Speaker 1: Let's sarw this Harry Anton tweet up on the screen,

788
00:44:42,280 --> 00:44:46,680
Speaker 1: because this is really interesting. Trump is still even though

789
00:44:46,680 --> 00:44:49,839
Speaker 1: he's not president, even though he's deep platformed, even though

790
00:44:49,880 --> 00:44:53,880
Speaker 1: Joe Biden is president, Trump is still leading Biden in

791
00:44:54,000 --> 00:44:59,600
Speaker 1: Google searches. Furthermore, Biden and Trump are tied for the

792
00:44:59,640 --> 00:45:03,680
Speaker 1: percent of Virginia voters who say each is motivating them

793
00:45:03,920 --> 00:45:07,000
Speaker 1: to vote. So you have the same number of Virginia

794
00:45:07,080 --> 00:45:09,759
Speaker 1: voters who were saying I hate Donald Trump so much

795
00:45:09,760 --> 00:45:12,319
Speaker 1: that I'm going to vote for Terry mccaulliffe as you

796
00:45:12,360 --> 00:45:14,640
Speaker 1: have voters who are saying, I hate Biden so much,

797
00:45:15,000 --> 00:45:18,680
Speaker 1: I'm going to vote for Glenn Youngkin. And that's kind

798
00:45:18,680 --> 00:45:20,200
Speaker 1: of what it comes down to you. I mean, I

799
00:45:20,239 --> 00:45:23,960
Speaker 1: will say in the end, I think if Trump did

800
00:45:23,960 --> 00:45:27,600
Speaker 1: not exist, this is a very winnable race for Glenn Youngkin,

801
00:45:28,239 --> 00:45:31,520
Speaker 1: and I think if he loses, even by a narrow margin,

802
00:45:31,640 --> 00:45:34,160
Speaker 1: I think you can pretty much directly point at Trump

803
00:45:34,600 --> 00:45:37,799
Speaker 1: and say that the Trump effect really hurt Youngkin and

804
00:45:37,840 --> 00:45:40,000
Speaker 1: caused him not to be able to win in a

805
00:45:40,080 --> 00:45:42,239
Speaker 1: state that you know he has a real shot at

806
00:45:42,280 --> 00:45:45,960
Speaker 1: given the overall national apathy. But as you pointed out before,

807
00:45:46,200 --> 00:45:49,560
Speaker 1: like if it's a one point mccauliff win or it's

808
00:45:49,600 --> 00:45:52,360
Speaker 1: a one point mccauliff loss, this is still a really

809
00:45:52,440 --> 00:45:54,560
Speaker 1: bad sign for Democrats in the state that not only

810
00:45:54,560 --> 00:45:57,480
Speaker 1: did Binen win by ten points, Ralph blackface northumb one

811
00:45:58,000 --> 00:46:00,880
Speaker 1: by nine points. So it's not like we just showed

812
00:46:00,960 --> 00:46:03,200
Speaker 1: up in droves for Joe Biden because we love Uncle

813
00:46:03,280 --> 00:46:04,960
Speaker 1: Joe so much. This is a state that's now a

814
00:46:05,040 --> 00:46:08,800
Speaker 1: nine or ten point democratic state. That's sort of the baseline.

815
00:46:08,920 --> 00:46:12,440
Speaker 1: I am going to be stunned if mccauliffe does lose,

816
00:46:12,719 --> 00:46:14,120
Speaker 1: I mean as much, you know, I'm kind of hoping

817
00:46:14,160 --> 00:46:16,080
Speaker 1: for it, honestly, just it'd be a great headline. And

818
00:46:16,120 --> 00:46:17,920
Speaker 1: also I just I think people need to wake up

819
00:46:17,920 --> 00:46:20,120
Speaker 1: a little bit about what's going on in terms of

820
00:46:20,200 --> 00:46:22,600
Speaker 1: Joe Biden and a lot of the national democratic mood.

821
00:46:22,880 --> 00:46:26,000
Speaker 1: And it's fascinating to me that, as you said, Trump's

822
00:46:26,080 --> 00:46:29,200
Speaker 1: Google searches are out of twenty fifteen low and he's

823
00:46:29,239 --> 00:46:33,240
Speaker 1: still beating the sitting president of the United States. That's wild,

824
00:46:33,560 --> 00:46:36,000
Speaker 1: and it just goes to show you the level of

825
00:46:36,280 --> 00:46:40,239
Speaker 1: enthusiasm there with Biden is beginning to match, not even

826
00:46:40,320 --> 00:46:43,080
Speaker 1: Obama levels. It's worse than what we're seeing, and that's

827
00:46:43,120 --> 00:46:45,319
Speaker 1: what led to Obama really saying the quiet part out

828
00:46:45,360 --> 00:46:48,640
Speaker 1: loud there. Indeed, all right, we've got a really sad

829
00:46:48,800 --> 00:46:52,120
Speaker 1: story to bring you here that you may have seen.

830
00:46:52,480 --> 00:46:55,760
Speaker 1: There's been a lot of discussion about this particular item.

831
00:46:55,840 --> 00:46:58,920
Speaker 1: So let's sort this substack post from Leyton wood House

832
00:46:59,000 --> 00:47:04,520
Speaker 1: up on the screen breaking down the US government funded

833
00:47:04,880 --> 00:47:07,680
Speaker 1: animal experiments. Yeah, I did not know about them that

834
00:47:07,719 --> 00:47:13,680
Speaker 1: are ongoing, and you know, Layton really details these in horrific,

835
00:47:14,840 --> 00:47:18,240
Speaker 1: in horrific detail. So the one that really caught people's attention,

836
00:47:18,320 --> 00:47:20,719
Speaker 1: I'll just read from the beginning of this piece. The

837
00:47:20,800 --> 00:47:23,800
Speaker 1: National Institute of Allergy and Infectious Disease is the division

838
00:47:23,960 --> 00:47:26,759
Speaker 1: of the NIH that's run by Anthony Fauci funded a

839
00:47:26,760 --> 00:47:31,400
Speaker 1: recent experiment in Tunisia in which lab technicians placed sedated

840
00:47:31,480 --> 00:47:37,160
Speaker 1: beagles dogs heads in mesh cages and allowed starved sand

841
00:47:37,200 --> 00:47:41,359
Speaker 1: flies to feast on them alive, to feast on the

842
00:47:41,360 --> 00:47:44,480
Speaker 1: dogs alive. Then they repeated the test outdoors with the

843
00:47:44,480 --> 00:47:48,040
Speaker 1: beagles placed in cages in the desert overnight for nine

844
00:47:48,239 --> 00:47:51,640
Speaker 1: consecutive nights in an area of Tunisia where sandflies were

845
00:47:51,680 --> 00:47:54,920
Speaker 1: abundant and ZVL, the disease caused by the parasite that

846
00:47:54,960 --> 00:48:00,759
Speaker 1: the sand flies carry was endemic. So these beagles are sedated,

847
00:48:01,200 --> 00:48:05,919
Speaker 1: headsput in mesh cages, were left outside, and the sand

848
00:48:06,000 --> 00:48:10,279
Speaker 1: flies literally eat them to death. I mean, the most

849
00:48:10,280 --> 00:48:13,319
Speaker 1: horrific thing that you can possibly imagine. And what's more,

850
00:48:14,360 --> 00:48:18,200
Speaker 1: there's allegation that the scientists slit the dog's vocal cords

851
00:48:18,800 --> 00:48:28,040
Speaker 1: so that they wouldn't have to listen to their anguished howls. Horrible, horrible,

852
00:48:28,360 --> 00:48:31,160
Speaker 1: horrible thing to think about. Horrible to know that our

853
00:48:31,160 --> 00:48:35,720
Speaker 1: government is funding it, and there's actually been some bipartisan

854
00:48:36,080 --> 00:48:41,520
Speaker 1: opposition to this particular procedure, but also our funding routine

855
00:48:41,520 --> 00:48:44,759
Speaker 1: funding of these type of animal experiments, which you know,

856
00:48:45,239 --> 00:48:48,239
Speaker 1: Layton kind of makes it like focuses on Fauci here

857
00:48:48,600 --> 00:48:53,680
Speaker 1: with some justification because is you know, part of leadership.

858
00:48:53,680 --> 00:48:58,160
Speaker 1: And also reportedly there's this quote in here from a

859
00:48:58,160 --> 00:49:01,120
Speaker 1: whistleblower who is quote in a major New York Times

860
00:49:01,200 --> 00:49:03,720
Speaker 1: x sposa of animal abuse at the US Meat Animal

861
00:49:03,760 --> 00:49:07,399
Speaker 1: Research Center in Nebraska, who says that the reason for

862
00:49:07,600 --> 00:49:11,600
Speaker 1: the what they describe as animal centric culture, meaning culture

863
00:49:11,800 --> 00:49:16,480
Speaker 1: centered around experimentation on animals, is people like Fauci and

864
00:49:16,680 --> 00:49:20,440
Speaker 1: another leader, Collins. They really below the quote is they

865
00:49:20,480 --> 00:49:23,040
Speaker 1: really believe in that animal model. It's a huge impact

866
00:49:23,080 --> 00:49:25,759
Speaker 1: having those two at the HELM, the two directors on

867
00:49:25,880 --> 00:49:28,520
Speaker 1: question commitment to animal testing, says the tone for science

868
00:49:28,560 --> 00:49:30,840
Speaker 1: as a whole thanks to them. It is industry standard

869
00:49:30,920 --> 00:49:33,239
Speaker 1: and careers are based on it. So the allegation here

870
00:49:33,280 --> 00:49:35,560
Speaker 1: is that tone comes from the top. Fauci is one

871
00:49:35,560 --> 00:49:40,760
Speaker 1: of those leaders who really believes in animal experimentation as essential.

872
00:49:41,000 --> 00:49:42,920
Speaker 1: Let's go ahead and throw this New York Post report

873
00:49:43,040 --> 00:49:46,120
Speaker 1: up on the screen that shows bipartisan I could see

874
00:49:46,160 --> 00:49:47,759
Speaker 1: that photo there for those of your watch. So the

875
00:49:47,840 --> 00:49:51,760
Speaker 1: beagles with their heads in the cage is terrible. Bipartisan

876
00:49:52,320 --> 00:49:56,600
Speaker 1: legislators demanding answers. There's also some movement in terms of

877
00:49:57,120 --> 00:50:01,720
Speaker 1: a bipartisan bill to try to eliminate funding for these

878
00:50:02,000 --> 00:50:07,960
Speaker 1: types of experiments. Activists have used some on the libertarian

879
00:50:08,040 --> 00:50:10,080
Speaker 1: rights in particular, like Rand Paul is one of the

880
00:50:10,120 --> 00:50:13,680
Speaker 1: people who's supporting these efforts. They're aversion to sort of

881
00:50:13,760 --> 00:50:16,720
Speaker 1: like wasteful government spending. They've used that to say basically,

882
00:50:16,840 --> 00:50:18,600
Speaker 1: you should get on board with getting rid of this

883
00:50:18,680 --> 00:50:21,120
Speaker 1: because also, look, this isn't a topic that I know

884
00:50:21,640 --> 00:50:25,000
Speaker 1: an extensive amount about, but from reading and preparation for

885
00:50:25,040 --> 00:50:27,680
Speaker 1: the segment, science has moved a lot, and that what

886
00:50:27,680 --> 00:50:31,400
Speaker 1: we're able to do in order to test has developed

887
00:50:31,440 --> 00:50:36,719
Speaker 1: greatly with technology with AI. And so the argument is

888
00:50:36,760 --> 00:50:40,360
Speaker 1: that these experiments, if they were ever necessary, not clear

889
00:50:40,400 --> 00:50:43,480
Speaker 1: that they are are really not necessary anymore. And what's more,

890
00:50:43,960 --> 00:50:49,120
Speaker 1: oftentimes they don't actually even provide effective data about how

891
00:50:49,440 --> 00:50:54,640
Speaker 1: various treatments or parasites or whatever is they're testing, how

892
00:50:54,680 --> 00:50:58,960
Speaker 1: this would play out in human beings. That oftentimes there's

893
00:50:59,000 --> 00:51:02,840
Speaker 1: a huge error rate, and so the dogs or whatever

894
00:51:02,880 --> 00:51:06,799
Speaker 1: animal is being tortured and tested on it doesn't even

895
00:51:06,960 --> 00:51:10,720
Speaker 1: provide data that's really useful or relevant to human beings.

896
00:51:11,160 --> 00:51:14,959
Speaker 1: So pretty horrific what's going on, and that I think,

897
00:51:15,080 --> 00:51:17,160
Speaker 1: you know, most people have no idea that we're funding

898
00:51:17,160 --> 00:51:19,799
Speaker 1: this sort of stuff. No, I had no idea. First

899
00:51:19,800 --> 00:51:21,759
Speaker 1: of all, I have the beagle, love beagles, and so

900
00:51:21,840 --> 00:51:23,600
Speaker 1: that I did not know the beagles are actually the

901
00:51:23,640 --> 00:51:27,080
Speaker 1: standard dog used in experimentations which is disgusting to me

902
00:51:27,160 --> 00:51:30,200
Speaker 1: for a variety of reasons. And Layton actually got a

903
00:51:30,360 --> 00:51:33,719
Speaker 1: good response from the University of Georgia, which is one

904
00:51:33,719 --> 00:51:36,879
Speaker 1: of the stories that they talk about the like they

905
00:51:36,920 --> 00:51:39,680
Speaker 1: call it like a dog model. Because the disease has

906
00:51:39,719 --> 00:51:43,400
Speaker 1: no cure, Unfortunately, animals part of this trial must be euthanized.

907
00:51:43,680 --> 00:51:46,000
Speaker 1: We do not take lightly the decision to use such

908
00:51:46,040 --> 00:51:49,000
Speaker 1: animals in our research, but really what it is and

909
00:51:49,040 --> 00:51:51,200
Speaker 1: look there has to be balanced, right obviously in terms

910
00:51:51,239 --> 00:51:54,040
Speaker 1: of experimentation and more is that the way that the

911
00:51:54,080 --> 00:51:57,359
Speaker 1: dogs and the animals themselves are even treated throughout the experiment,

912
00:51:57,640 --> 00:52:02,080
Speaker 1: it's clearly incredibly cruel. And you know, like you said,

913
00:52:02,120 --> 00:52:06,120
Speaker 1: debarking cutting out their cutting out their vocal cords, letting

914
00:52:06,400 --> 00:52:09,640
Speaker 1: flies like eat them to death. It's not the same

915
00:52:09,640 --> 00:52:11,799
Speaker 1: as you know, testing out a vaccine or something. And

916
00:52:11,840 --> 00:52:14,319
Speaker 1: even then maybe we should all have a discussion. So

917
00:52:14,760 --> 00:52:16,319
Speaker 1: I try to look at this in the same way

918
00:52:16,320 --> 00:52:19,479
Speaker 1: that we did gain of function, which was okay, gain

919
00:52:19,480 --> 00:52:22,840
Speaker 1: a function. We all began to learn about it because

920
00:52:22,880 --> 00:52:25,120
Speaker 1: of the lab leak. Now here's the thing, whether the

921
00:52:25,200 --> 00:52:27,120
Speaker 1: lab leak's true or not, and we'll probably never know

922
00:52:27,239 --> 00:52:29,800
Speaker 1: at this point although I strongly suspect that it is true,

923
00:52:30,280 --> 00:52:32,920
Speaker 1: you often say this. I think we have enough information

924
00:52:33,040 --> 00:52:36,600
Speaker 1: now to say, hey, if there's a fifty something percent

925
00:52:36,680 --> 00:52:38,680
Speaker 1: chance and I think it's more like ninety that this

926
00:52:38,760 --> 00:52:41,360
Speaker 1: caused a pandemic, maybe we tighten up all the restrictions

927
00:52:41,360 --> 00:52:42,759
Speaker 1: around the same. Maybe we don't do it at all.

928
00:52:42,800 --> 00:52:44,959
Speaker 1: Maybe the public should have some sort of a say.

929
00:52:45,200 --> 00:52:48,400
Speaker 1: And that's what I am heartened and hoping. Like, obviously

930
00:52:48,400 --> 00:52:50,480
Speaker 1: this is coming in a culture war story. People are like, oh,

931
00:52:50,520 --> 00:52:53,759
Speaker 1: fauci and puppies, and look, that's actually completely true. But

932
00:52:54,160 --> 00:52:57,400
Speaker 1: really what it is is maybe we should have Congress

933
00:52:57,640 --> 00:53:00,880
Speaker 1: who appropriates and I did not know this already billion

934
00:53:00,960 --> 00:53:06,239
Speaker 1: dollars a year on different medical experiments, set some standards

935
00:53:06,480 --> 00:53:09,720
Speaker 1: as to what the US government is going to fund

936
00:53:10,080 --> 00:53:13,640
Speaker 1: and if there is a culture from the top saying no,

937
00:53:13,640 --> 00:53:17,719
Speaker 1: no, no no, dog experiments are actually pretty crucial last time

938
00:53:17,760 --> 00:53:20,640
Speaker 1: I checked. These people are not gods. They do not

939
00:53:20,680 --> 00:53:24,279
Speaker 1: create the rules on their own. It's our money where

940
00:53:24,320 --> 00:53:27,600
Speaker 1: the public we get to decide how and what and

941
00:53:27,640 --> 00:53:30,200
Speaker 1: where things are going to be done in our name.

942
00:53:30,480 --> 00:53:32,600
Speaker 1: And I would just encourage you that if you were

943
00:53:32,640 --> 00:53:35,440
Speaker 1: a dog person like me now I have a cat,

944
00:53:35,480 --> 00:53:38,200
Speaker 1: so I'm also a cat person, but a person. But

945
00:53:38,600 --> 00:53:40,719
Speaker 1: if you take a look at that photo and you

946
00:53:40,800 --> 00:53:42,640
Speaker 1: tell me whether you're cool with that, and I'm going

947
00:53:42,719 --> 00:53:44,680
Speaker 1: to say, no, I'm not. And I think it's important

948
00:53:44,680 --> 00:53:46,719
Speaker 1: that we all see exactly what's going here. And this

949
00:53:46,800 --> 00:53:48,920
Speaker 1: is a much deeper story, but factory if people know

950
00:53:49,480 --> 00:53:52,839
Speaker 1: exactly how those factory farms and all those things. I've

951
00:53:52,880 --> 00:53:55,880
Speaker 1: had the misfortune of having to drive past the slaughterhouse

952
00:53:55,880 --> 00:53:57,880
Speaker 1: in Amarillo, Texas, and I can tell you, like you

953
00:53:58,040 --> 00:54:00,000
Speaker 1: never want to hear or see any of that stuff

954
00:54:00,160 --> 00:54:05,520
Speaker 1: in your lifetime. Yes, Glenn was on Rising at that's right,

955
00:54:05,600 --> 00:54:10,520
Speaker 1: oh wow, and talked about us. He's I looked at

956
00:54:10,560 --> 00:54:12,600
Speaker 1: him on this issue because he's very passionate about it,

957
00:54:12,760 --> 00:54:15,200
Speaker 1: very much more knowledge about it, and reported on on

958
00:54:15,280 --> 00:54:18,000
Speaker 1: factory farms and on animal experimentation, all of this stuff,

959
00:54:18,520 --> 00:54:24,239
Speaker 1: and with regard to the necessity of animal experimentation, which

960
00:54:24,280 --> 00:54:27,120
Speaker 1: is what the proponents argue, like, look, yeah, it's awful.

961
00:54:27,160 --> 00:54:28,759
Speaker 1: This is what the University of George is saying. Of

962
00:54:28,840 --> 00:54:30,879
Speaker 1: course it's awful. Of course we don't like doing it,

963
00:54:31,320 --> 00:54:33,799
Speaker 1: but we're trying to save human lives and so there's

964
00:54:33,840 --> 00:54:37,200
Speaker 1: a balance here that has to be struck. Glenn compared

965
00:54:37,239 --> 00:54:40,000
Speaker 1: it to the argument that people make in favor of torture,

966
00:54:40,160 --> 00:54:43,080
Speaker 1: which is, you can come up with some sort of

967
00:54:44,040 --> 00:54:48,799
Speaker 1: theoretical scenario, the ticking time bomb, that if you could

968
00:54:48,840 --> 00:54:51,439
Speaker 1: torture this one person into telling you, you could stop

969
00:54:51,440 --> 00:54:53,600
Speaker 1: it and you could save all these lives. And so

970
00:54:53,760 --> 00:54:57,200
Speaker 1: people who are proponents of torture, they'll can cock these

971
00:54:57,239 --> 00:55:00,160
Speaker 1: elaborate scenarios to make you feel like, okay, well, we

972
00:55:00,160 --> 00:55:02,720
Speaker 1: we have to sanction this because people's lives are at stake,

973
00:55:03,080 --> 00:55:07,440
Speaker 1: when in reality that scenario actually never plays out. And

974
00:55:07,520 --> 00:55:09,920
Speaker 1: so Glenn made that comparison here of like, yeah, you

975
00:55:09,960 --> 00:55:13,680
Speaker 1: can concoct, of course, scenarios where it's like, well, would

976
00:55:13,719 --> 00:55:17,399
Speaker 1: you torture a puppy to cure everybody of cancer? All right?

977
00:55:17,480 --> 00:55:19,960
Speaker 1: And you'd say, well, I mean it's horrible, but I

978
00:55:19,960 --> 00:55:21,799
Speaker 1: guess if we're going to cure all these people, then

979
00:55:21,840 --> 00:55:24,040
Speaker 1: I guess I'm going to have to justify it. But

980
00:55:24,520 --> 00:55:28,600
Speaker 1: that's not actually in reality the landscape that we're facing,

981
00:55:29,080 --> 00:55:33,520
Speaker 1: especially with technological advances, where a lot of this experimentation

982
00:55:33,840 --> 00:55:37,279
Speaker 1: can happen using technology where no animals have to be

983
00:55:37,360 --> 00:55:41,640
Speaker 1: harmed at all. So even this idea that like, oh

984
00:55:42,000 --> 00:55:45,240
Speaker 1: there's a difficult balance here and sometimes we have to

985
00:55:45,280 --> 00:55:48,600
Speaker 1: test on animals to save human lives, even that is

986
00:55:48,680 --> 00:55:51,480
Speaker 1: somewhat questionable. Now I feel like I can't do this

987
00:55:51,600 --> 00:55:54,360
Speaker 1: segment without saying that honestly, I feel like a gigantic

988
00:55:54,440 --> 00:55:58,040
Speaker 1: hypocrite talking about this because the factory farm treatment is awful.

989
00:55:58,920 --> 00:56:01,399
Speaker 1: I'm not a vegan. I eat animals that come from

990
00:56:01,400 --> 00:56:04,279
Speaker 1: those factory farms, and so I just want to put

991
00:56:04,280 --> 00:56:07,239
Speaker 1: out there that, like, this is a really difficult and

992
00:56:07,320 --> 00:56:11,040
Speaker 1: challenging subject. And I am by no means like pure

993
00:56:11,880 --> 00:56:15,759
Speaker 1: or being totally ideologically consistent here if I'm being honest, Well,

994
00:56:15,760 --> 00:56:17,600
Speaker 1: so am I. And look, this is the thing. It's

995
00:56:17,640 --> 00:56:20,000
Speaker 1: not on you, And we did not design the meat

996
00:56:20,080 --> 00:56:23,560
Speaker 1: supply chain, okay, Like it's on the public to make

997
00:56:23,600 --> 00:56:25,680
Speaker 1: it so that there are certain standards that we can

998
00:56:25,719 --> 00:56:28,280
Speaker 1: make it so that we can live, we can both

999
00:56:28,440 --> 00:56:33,080
Speaker 1: all eat a healthy diet and also life saving treatment

1000
00:56:33,120 --> 00:56:35,640
Speaker 1: of life answer and all those things, and also not

1001
00:56:35,719 --> 00:56:38,320
Speaker 1: have people tortured in our name. And this is where

1002
00:56:38,560 --> 00:56:40,960
Speaker 1: you see the intersection. I mean, in the factory farm industry,

1003
00:56:40,960 --> 00:56:42,920
Speaker 1: it's just all about profit, which is that you you know,

1004
00:56:43,000 --> 00:56:45,919
Speaker 1: the the animals themselves are just commodities. You can treat

1005
00:56:45,960 --> 00:56:48,279
Speaker 1: them horrible and actually it's worse for the animal. It's

1006
00:56:48,280 --> 00:56:50,480
Speaker 1: worse for you too, in terms of what you're eating

1007
00:56:50,520 --> 00:56:52,880
Speaker 1: and the diet and all that. I would really encourage

1008
00:56:52,920 --> 00:56:55,840
Speaker 1: people to look into the actual stuff that those animals

1009
00:56:55,840 --> 00:56:58,320
Speaker 1: are eating and how it would affect you your hormone

1010
00:56:58,400 --> 00:57:00,840
Speaker 1: levels and more. I have personally made that choice, but

1011
00:57:01,080 --> 00:57:04,239
Speaker 1: once again, it should not be on me. This is

1012
00:57:04,680 --> 00:57:06,759
Speaker 1: not something that where you should have to go through

1013
00:57:06,800 --> 00:57:08,960
Speaker 1: and make sure what you're putting in your body is

1014
00:57:09,000 --> 00:57:11,160
Speaker 1: not you know, not even about ethics, but really about

1015
00:57:11,280 --> 00:57:13,920
Speaker 1: over your health and their health. They should make it

1016
00:57:14,000 --> 00:57:16,440
Speaker 1: so that it is more sound. So I would put

1017
00:57:16,480 --> 00:57:18,880
Speaker 1: it as a much more systemic problem. That's exactly how

1018
00:57:18,880 --> 00:57:20,880
Speaker 1: I see this one. And to me, it just highlights

1019
00:57:20,880 --> 00:57:23,200
Speaker 1: the fact that Fauci is a creature of the system.

1020
00:57:23,440 --> 00:57:26,680
Speaker 1: Gain of function was and is part of the scientific

1021
00:57:26,720 --> 00:57:30,920
Speaker 1: function of system, which then possibly created this horrific pandemic.

1022
00:57:31,160 --> 00:57:35,160
Speaker 1: These you know, begal experiments, these animal experiments are being highlighted,

1023
00:57:35,320 --> 00:57:37,880
Speaker 1: you know, for a variety of reasons. But it's a

1024
00:57:38,040 --> 00:57:40,800
Speaker 1: creature of the system. In which they see it as necessary,

1025
00:57:40,840 --> 00:57:42,600
Speaker 1: and they want to hide the truth just like they

1026
00:57:42,640 --> 00:57:45,200
Speaker 1: do from gain to function. From you, it's your money

1027
00:57:45,320 --> 00:57:47,440
Speaker 1: and you get to decide how we actually want to

1028
00:57:47,480 --> 00:57:49,400
Speaker 1: do with it, regardless of what all the myths are.

1029
00:57:49,640 --> 00:57:51,440
Speaker 1: And I think that we should try at least our

1030
00:57:51,480 --> 00:57:54,040
Speaker 1: best in order to at least raise awareness and possibly

1031
00:57:54,120 --> 00:57:56,320
Speaker 1: have these lawmakers do something about it. Okay, what a

1032
00:57:56,320 --> 00:57:59,000
Speaker 1: good friend Soccer is. He'll even justify my moral hypocrisy

1033
00:57:59,040 --> 00:58:02,640
Speaker 1: for me, Thank you, Black just on my own all right,

1034
00:58:03,000 --> 00:58:06,360
Speaker 1: big update on a story that we brought you before. Okay,

1035
00:58:06,560 --> 00:58:09,520
Speaker 1: you remember Kamala Harris was supposed to do this big

1036
00:58:09,640 --> 00:58:12,920
Speaker 1: view interview. She doesn't talk depressed that often because it

1037
00:58:12,960 --> 00:58:15,200
Speaker 1: doesn't really go that well when she usually does. So

1038
00:58:15,440 --> 00:58:18,160
Speaker 1: this was a big deal. It was build in advance,

1039
00:58:18,200 --> 00:58:21,040
Speaker 1: a view, was really talenting, etc. So comes to showtime

1040
00:58:21,400 --> 00:58:24,280
Speaker 1: and they're halfway through the show. They are just about

1041
00:58:24,400 --> 00:58:28,080
Speaker 1: to bring out the vice president and suddenly there's a

1042
00:58:28,160 --> 00:58:32,640
Speaker 1: kind of a strangeness on set and they actually tell

1043
00:58:34,040 --> 00:58:37,919
Speaker 1: to Anna Navarro and Sunny Houston that they have to leave,

1044
00:58:38,640 --> 00:58:42,280
Speaker 1: and it turns out that they have received a positive

1045
00:58:42,400 --> 00:58:46,080
Speaker 1: COVID test. Yes again, so there's a lot of stranges here,

1046
00:58:46,080 --> 00:58:49,680
Speaker 1: because you're like, wouldn't you have tested before the middle

1047
00:58:49,760 --> 00:58:52,680
Speaker 1: of the show, Like, wouldn't you have had this figured out? Right?

1048
00:58:53,120 --> 00:58:55,560
Speaker 1: And then we learn after the fact from some reporting

1049
00:58:55,600 --> 00:58:57,040
Speaker 1: from I think The Daily Beast and a couple other

1050
00:58:57,080 --> 00:59:01,120
Speaker 1: outlets that the Vice President's office is extremely pissed off

1051
00:59:01,240 --> 00:59:05,280
Speaker 1: because they were told the night before their requirement was

1052
00:59:05,320 --> 00:59:08,080
Speaker 1: that all everybody involved would be PCR tested as a

1053
00:59:08,120 --> 00:59:11,160
Speaker 1: gold standard test. The night before they were given the

1054
00:59:11,200 --> 00:59:14,240
Speaker 1: all clear. Everybody's tested, everybody's negative, and so they're like,

1055
00:59:14,280 --> 00:59:18,160
Speaker 1: what the hell happened? And then after being told mid

1056
00:59:18,560 --> 00:59:22,880
Speaker 1: show that they're positive for COVID, Anna and Sonny both

1057
00:59:23,000 --> 00:59:25,800
Speaker 1: take like a million other COVID tests and they're all negative.

1058
00:59:25,840 --> 00:59:29,040
Speaker 1: So it's a false positive, which on a PCR test

1059
00:59:29,360 --> 00:59:32,840
Speaker 1: is incredibly Yeah, you went through the data, this is incredible.

1060
00:59:32,960 --> 00:59:37,400
Speaker 1: It basically doesn't happen. Okay, So something happened. There was

1061
00:59:37,440 --> 00:59:41,440
Speaker 1: some screw up or potential plot, I don't know, but

1062
00:59:42,000 --> 00:59:43,360
Speaker 1: this did not go smoothly, and there were a lot

1063
00:59:43,400 --> 00:59:46,440
Speaker 1: of unanswered questions, and the Vice President's office even was

1064
00:59:46,520 --> 00:59:48,800
Speaker 1: never able to get satisfied that they had They still

1065
00:59:48,800 --> 00:59:51,080
Speaker 1: don't have an answer about what the hell happened here?

1066
00:59:51,160 --> 00:59:55,160
Speaker 1: Well allegedly answered yes, right, yeah, put that out there

1067
00:59:55,160 --> 00:59:57,760
Speaker 1: as well. So here's the latest. Let's say this tear

1068
00:59:57,760 --> 01:00:00,959
Speaker 1: sheet up on the screen. Some body had to take

1069
01:00:01,000 --> 01:00:04,280
Speaker 1: the fall, and so who do they pick but their

1070
01:00:05,000 --> 01:00:09,440
Speaker 1: nurse they're on Saffy Nurse, Nurse Wendy. The View ditched

1071
01:00:09,480 --> 01:00:13,320
Speaker 1: its hero nurse after Kamala Harris COVID chaos. The registered

1072
01:00:13,360 --> 01:00:16,640
Speaker 1: nurse was once touted as the talk show's own Florence Nightingale,

1073
01:00:16,720 --> 01:00:19,600
Speaker 1: but apparently she had to take the fall for last

1074
01:00:19,640 --> 01:00:24,400
Speaker 1: month's on air testing meltdown. Here's a little bit from

1075
01:00:24,440 --> 01:00:27,160
Speaker 1: that piece. They say. Multiple people familiar with the matter

1076
01:00:27,200 --> 01:00:29,400
Speaker 1: told The Daily Beast that falling me on air fiasco.

1077
01:00:29,520 --> 01:00:32,600
Speaker 1: Last month, the daytime talk show ditched its health and

1078
01:00:32,640 --> 01:00:35,840
Speaker 1: safety manager. Her name is Wendy Livingstone, whom the program

1079
01:00:35,880 --> 01:00:38,360
Speaker 1: affectionately referred to as Nurse Wendy and once labeled a

1080
01:00:38,400 --> 01:00:43,560
Speaker 1: health care hero during an effusive tribute. ABC says Wendy

1081
01:00:43,600 --> 01:00:45,840
Speaker 1: has not been fired. She remains a part of the

1082
01:00:45,920 --> 01:00:49,400
Speaker 1: health and safety team supporting testing and vaccine verification. So

1083
01:00:49,520 --> 01:00:51,840
Speaker 1: what that seems to indicate is that they've taken her

1084
01:00:51,880 --> 01:00:54,320
Speaker 1: out of that role. She doesn't work for the show anymore.

1085
01:00:54,400 --> 01:00:58,960
Speaker 1: She's been significantly demoted. So they decided to take this

1086
01:00:59,080 --> 01:01:02,400
Speaker 1: like working class registered nurse and make her the fall

1087
01:01:02,440 --> 01:01:06,280
Speaker 1: guy for their whole disastrous situation or whatever happened. Yeah,

1088
01:01:06,320 --> 01:01:09,880
Speaker 1: and look, you raised a lot of questions in that monologue,

1089
01:01:09,920 --> 01:01:13,000
Speaker 1: which is that PCR false negatives almost will never happen.

1090
01:01:13,160 --> 01:01:16,040
Speaker 1: Also very convenient, the kamalog just didn't have to do

1091
01:01:16,240 --> 01:01:19,360
Speaker 1: the interview also, or sorry that she'd have to do

1092
01:01:19,400 --> 01:01:21,360
Speaker 1: an interview with two of the people who might have

1093
01:01:21,400 --> 01:01:24,560
Speaker 1: asked her tough questions once again, then you come to

1094
01:01:24,600 --> 01:01:27,120
Speaker 1: the fact that there was this bizarre on air apology

1095
01:01:27,440 --> 01:01:31,120
Speaker 1: from the executive producer of the view to them saying, hey,

1096
01:01:31,200 --> 01:01:35,640
Speaker 1: we're super sorry, and then everybody just dropped it and look,

1097
01:01:35,800 --> 01:01:39,480
Speaker 1: it's a mighty fishy incident. These things generally don't happen.

1098
01:01:39,760 --> 01:01:44,000
Speaker 1: And then weeks later the nurse somehow is the lady

1099
01:01:44,080 --> 01:01:48,200
Speaker 1: who takes the fall, and there was never an explanation around, oh,

1100
01:01:48,160 --> 01:01:51,520
Speaker 1: what happened The nurse screwed it up or whatever. If

1101
01:01:51,560 --> 01:01:53,600
Speaker 1: that was true, then they should have said. So they

1102
01:01:53,680 --> 01:01:56,360
Speaker 1: just quietly kind of take her off. She's the fall

1103
01:01:56,400 --> 01:02:00,280
Speaker 1: guy for all of this and you found this. This

1104
01:02:00,320 --> 01:02:03,680
Speaker 1: is how they used to treat this nurse. This is

1105
01:02:03,680 --> 01:02:05,600
Speaker 1: how well they thought of her. Just to give you

1106
01:02:05,640 --> 01:02:09,080
Speaker 1: an idea of how her stature was within the team

1107
01:02:09,320 --> 01:02:12,919
Speaker 1: before she got canned. Let's take a lesson your optimism,

1108
01:02:13,400 --> 01:02:16,640
Speaker 1: your kindness do not go unrecognized by those of us

1109
01:02:16,640 --> 01:02:20,000
Speaker 1: here at the View. She is adorably kind, compassionate, and

1110
01:02:20,040 --> 01:02:22,080
Speaker 1: she's made me feel taken care of and as a

1111
01:02:22,080 --> 01:02:25,120
Speaker 1: MoMA myself, that doesn't happen very often. A very special

1112
01:02:25,160 --> 01:02:28,480
Speaker 1: thank you to Nurse Wendy for everything you've done to

1113
01:02:28,640 --> 01:02:31,560
Speaker 1: keep the View family safe and sound. Thank you so

1114
01:02:31,680 --> 01:02:34,680
Speaker 1: much for all your incredible work and how amazing you are.

1115
01:02:34,840 --> 01:02:37,880
Speaker 1: We love you, and you have been absolutely integral to

1116
01:02:37,920 --> 01:02:40,880
Speaker 1: getting the ladies of the View through this time. Thank

1117
01:02:40,920 --> 01:02:44,800
Speaker 1: you so much, Wendy for keeping us safe this year.

1118
01:02:45,160 --> 01:02:48,480
Speaker 1: I have never had so many cotton swamps up my

1119
01:02:48,680 --> 01:02:52,080
Speaker 1: nose in my entire lifetime. I don't think we could

1120
01:02:52,080 --> 01:02:54,920
Speaker 1: have gotten through this without her. She's been an enormous asset.

1121
01:02:55,160 --> 01:02:58,720
Speaker 1: She is our own Florenstein Camp. Hey, Nurse Wendy. I

1122
01:02:58,760 --> 01:03:01,600
Speaker 1: just wanted to say, Nurses Rock, we love you, Thank

1123
01:03:01,600 --> 01:03:07,640
Speaker 1: you for everything you do. Thank you, thank you very much,

1124
01:03:10,000 --> 01:03:14,000
Speaker 1: our own floor, our hero our I mean, I will say,

1125
01:03:14,040 --> 01:03:16,080
Speaker 1: of course Flord's night and Gale is sort of like

1126
01:03:16,320 --> 01:03:21,760
Speaker 1: founder originior of the nursing profession, treating soldiers during the

1127
01:03:21,760 --> 01:03:25,200
Speaker 1: Crimean War, and there are it could be sort of

1128
01:03:25,200 --> 01:03:27,560
Speaker 1: a battlefield there with the ladies of the View, no

1129
01:03:27,600 --> 01:03:30,160
Speaker 1: doubt about it. But look, I think there's a larger

1130
01:03:30,280 --> 01:03:34,080
Speaker 1: metaphor here for the country when it benefited the View

1131
01:03:34,840 --> 01:03:38,080
Speaker 1: to hold her up. Oh, we love our essential workers

1132
01:03:38,160 --> 01:03:40,919
Speaker 1: so amazing our in Florence Nightingale, you kept us safe,

1133
01:03:40,920 --> 01:03:43,320
Speaker 1: et cetera, et cetera. That's what they did. When that

1134
01:03:43,440 --> 01:03:45,439
Speaker 1: was like, you know, good, a good look for them,

1135
01:03:45,800 --> 01:03:48,560
Speaker 1: and then the minute it was inconvenient, they were happy

1136
01:03:48,600 --> 01:03:51,000
Speaker 1: to kick her to the curb and have her take

1137
01:03:51,000 --> 01:03:53,280
Speaker 1: the fall for whatever the hell happened there on that

1138
01:03:53,320 --> 01:03:58,120
Speaker 1: faithful day. Very very interesting. Yes, I want answers, it's

1139
01:03:58,160 --> 01:04:00,400
Speaker 1: the bottom line. It still remains one of the more

1140
01:04:00,440 --> 01:04:02,840
Speaker 1: I mean here, Look, they got huge ratings, they got

1141
01:04:02,880 --> 01:04:04,760
Speaker 1: a ton of media play out of this, like oh

1142
01:04:04,800 --> 01:04:07,880
Speaker 1: my god, you're pulled off live on the air. It

1143
01:04:07,960 --> 01:04:09,880
Speaker 1: was nuts, right, and then they're like, oh, it's a

1144
01:04:09,920 --> 01:04:12,120
Speaker 1: false positive. Even though that almost never happens. Then the

1145
01:04:12,200 --> 01:04:15,080
Speaker 1: Vice Presidence, you know, doesn't do this interview with two

1146
01:04:15,120 --> 01:04:17,360
Speaker 1: of the people who might have asked her the toughest

1147
01:04:17,400 --> 01:04:20,040
Speaker 1: questions while they're there, it's a total fluff piece. And

1148
01:04:20,080 --> 01:04:22,800
Speaker 1: then they are completely freaked out about what's going on.

1149
01:04:23,160 --> 01:04:26,520
Speaker 1: Then they offer some you know, crazy apology which doesn't

1150
01:04:26,520 --> 01:04:29,480
Speaker 1: make any sense. And now the nurse, who, by their

1151
01:04:29,520 --> 01:04:32,680
Speaker 1: own estimation, was you know, the hero, the Flora Sidingale,

1152
01:04:32,840 --> 01:04:35,960
Speaker 1: who manages the whole process, now she's taken off of

1153
01:04:36,000 --> 01:04:38,720
Speaker 1: the entire thing. Now, you know, we don't know all

1154
01:04:38,720 --> 01:04:40,520
Speaker 1: the details, but I don't think we're getting the full story.

1155
01:04:40,800 --> 01:04:44,120
Speaker 1: I'm team nurse Wendy's all yeah, I'm team Nurse Wendy too.

1156
01:04:44,280 --> 01:04:47,000
Speaker 1: I blame somebody much higher up. Indeed, here we go. Wow,

1157
01:04:47,120 --> 01:04:49,160
Speaker 1: you guys must really like listening to our voices. Well,

1158
01:04:49,160 --> 01:04:51,200
Speaker 1: I know this is annoying instead of making you listen

1159
01:04:51,200 --> 01:04:53,760
Speaker 1: to a Viagra commercial. When you're done, check out the

1160
01:04:53,760 --> 01:04:56,480
Speaker 1: other podcast I do with Marshall Kasoff called The Realignment.

1161
01:04:56,560 --> 01:04:58,600
Speaker 1: We talk a lot about the deeper issues that are

1162
01:04:58,680 --> 01:05:02,080
Speaker 1: changing realigning in American society. You always need more Crystal

1163
01:05:02,080 --> 01:05:04,840
Speaker 1: and Zagur in your daily lives. Take care, guys, Crystal,

1164
01:05:04,880 --> 01:05:06,640
Speaker 1: what are you taking a look at? Well? Guys, the

1165
01:05:06,680 --> 01:05:09,840
Speaker 1: biggest COVID threat to Americans does not come from the

1166
01:05:09,920 --> 01:05:13,560
Speaker 1: vaccine hesidant. It is not, in fact anti mask Karen's

1167
01:05:13,600 --> 01:05:17,920
Speaker 1: refusing to wear their pandemic protection and being jerks about it.

1168
01:05:17,960 --> 01:05:22,440
Speaker 1: Is not Kyrie Irving liking post about vaccines being microchips,

1169
01:05:22,560 --> 01:05:26,920
Speaker 1: not even Nicki Minaj and her cousin's friends swollen balls. No,

1170
01:05:27,440 --> 01:05:30,240
Speaker 1: biggest pandemic threat comes from an older and much more

1171
01:05:30,240 --> 01:05:34,680
Speaker 1: intractable foe. Greed. Greed of pharmaceutical companies looking to profit

1172
01:05:34,720 --> 01:05:37,040
Speaker 1: as much as they possibly can off of a life

1173
01:05:37,080 --> 01:05:41,600
Speaker 1: saving vaccine, combined with the corruption and cowardice of politicians

1174
01:05:41,640 --> 01:05:44,640
Speaker 1: like Joe Biden who are unwilling to stand up to

1175
01:05:44,760 --> 01:05:48,840
Speaker 1: those pharmaceutical companies. This deadly combination has made it so

1176
01:05:48,920 --> 01:05:54,400
Speaker 1: that only point seven percent of vaccine doses have gone

1177
01:05:54,440 --> 01:05:57,560
Speaker 1: to poor countries. Now we are learning new details of

1178
01:05:57,720 --> 01:05:59,600
Speaker 1: just how far these companies are willing to go in

1179
01:05:59,640 --> 01:06:01,920
Speaker 1: the life they were willing to tell in order to

1180
01:06:01,960 --> 01:06:04,360
Speaker 1: protect their bottom line. Let me tell you a little

1181
01:06:04,360 --> 01:06:06,960
Speaker 1: story here about one of the worst actors involved, the

1182
01:06:07,040 --> 01:06:10,240
Speaker 1: company of Maderna. Now you will recall at the beginning

1183
01:06:10,240 --> 01:06:12,920
Speaker 1: of the pandemic, wealthy nations, the World Health Organization, and

1184
01:06:13,000 --> 01:06:15,600
Speaker 1: big farm alike. They were all singing the same tune.

1185
01:06:16,120 --> 01:06:18,880
Speaker 1: They said, we needed a World War II level effort,

1186
01:06:19,040 --> 01:06:21,480
Speaker 1: all in it together to develop a vaccine and then

1187
01:06:21,560 --> 01:06:24,760
Speaker 1: to go out and vaccinate the whole world through Operation

1188
01:06:24,880 --> 01:06:27,880
Speaker 1: Warp Speed. Here in the US we were integral to

1189
01:06:27,880 --> 01:06:30,720
Speaker 1: the development of several of those vaccines, including what turned

1190
01:06:30,760 --> 01:06:34,480
Speaker 1: out to be the most effective version, Maderna. Now this

1191
01:06:34,560 --> 01:06:38,480
Speaker 1: mass mobilization and significant funding came on top of years

1192
01:06:38,600 --> 01:06:41,440
Speaker 1: of publicly funded research, which led to the development of

1193
01:06:41,480 --> 01:06:44,520
Speaker 1: that mRNA technology that, of course allowed the Maderna and

1194
01:06:44,560 --> 01:06:48,440
Speaker 1: the Pfizer vaccines to be created so rapidly. In fact,

1195
01:06:48,960 --> 01:06:51,840
Speaker 1: no vaccine owed more to the US taxpayer than Maderna's.

1196
01:06:52,040 --> 01:06:53,880
Speaker 1: They were little more than a startup when they jumped

1197
01:06:53,880 --> 01:06:56,480
Speaker 1: in the great vaccine race, and the US government backed

1198
01:06:56,520 --> 01:06:59,400
Speaker 1: them bigly. According to The New York Times, when the

1199
01:06:59,440 --> 01:07:02,880
Speaker 1: Maderna partnership was first proposed to doctor Fauci, he said, quote,

1200
01:07:03,160 --> 01:07:06,520
Speaker 1: go for it, whatever it costs, don't worry about it.

1201
01:07:06,760 --> 01:07:09,200
Speaker 1: And the US government kept their word, flooding the effort

1202
01:07:09,280 --> 01:07:12,000
Speaker 1: with resources of all kinds. So, for those of you

1203
01:07:12,080 --> 01:07:15,760
Speaker 1: keeping track at home, you funded the mRNA research, you

1204
01:07:15,840 --> 01:07:19,320
Speaker 1: funded the Maderna vaccine development, and your government moved heaven

1205
01:07:19,360 --> 01:07:21,640
Speaker 1: and earth to make sure that every issue and wrinkle

1206
01:07:21,680 --> 01:07:25,360
Speaker 1: and hiccup in that vaccine development was ultimately sorted out.

1207
01:07:25,800 --> 01:07:29,200
Speaker 1: They even brought in top military brass to make sure

1208
01:07:29,400 --> 01:07:33,480
Speaker 1: that every single obstacle would be removed. But now the

1209
01:07:33,520 --> 01:07:36,920
Speaker 1: Maderna has their publicly funded vaccine, they want to keep

1210
01:07:36,960 --> 01:07:38,960
Speaker 1: all the private profits for themselves, and they want to

1211
01:07:38,960 --> 01:07:42,320
Speaker 1: milk it for every last dollar they possibly can, even

1212
01:07:42,400 --> 01:07:46,440
Speaker 1: if that means risking another pandemic. After all, they did

1213
01:07:46,520 --> 01:07:50,120
Speaker 1: profit very handsomely off of this one. In fact, Maderna

1214
01:07:50,200 --> 01:07:52,720
Speaker 1: has limited production of their vaccine and sold it almost

1215
01:07:52,720 --> 01:07:55,960
Speaker 1: exclusively to the rich world, where governments can afford to

1216
01:07:55,960 --> 01:07:58,800
Speaker 1: pay premium prices. Here's the New York Times with that

1217
01:07:58,840 --> 01:08:02,880
Speaker 1: report headlined Maderna racing for profits keeps COVID vaccine out

1218
01:08:02,920 --> 01:08:05,640
Speaker 1: of reach of poor quote. Maderna has shipped a greater

1219
01:08:05,720 --> 01:08:08,240
Speaker 1: share of its doses to wealthy countries than any other

1220
01:08:08,360 --> 01:08:11,440
Speaker 1: vaccine manufacturer. That's according to Affinity, a data firm that

1221
01:08:11,520 --> 01:08:14,800
Speaker 1: tracks vaccine shipments. They are behaving as if they have

1222
01:08:14,920 --> 01:08:19,320
Speaker 1: absolutely no responsibility beyond maximizing the return on investment, said

1223
01:08:19,320 --> 01:08:22,080
Speaker 1: doctor Tom freed In, a former head of the CDC,

1224
01:08:22,880 --> 01:08:25,639
Speaker 1: a for profit company, only caring about profits who could

1225
01:08:25,640 --> 01:08:28,320
Speaker 1: have seen that coming. Now. For their part, Maderna says

1226
01:08:28,360 --> 01:08:30,720
Speaker 1: that they ask for government funding to scale up their

1227
01:08:30,720 --> 01:08:32,840
Speaker 1: production but didn't receive it, and that they are so

1228
01:08:33,000 --> 01:08:36,520
Speaker 1: sad that only rich countries have essentially received their vaccine.

1229
01:08:36,840 --> 01:08:40,440
Speaker 1: Of course, if you genuinely wanted to increase production capacity,

1230
01:08:40,560 --> 01:08:43,920
Speaker 1: there is a simple and obvious way drop the patent

1231
01:08:43,960 --> 01:08:46,720
Speaker 1: protection and provide the details of how to make the

1232
01:08:46,800 --> 01:08:50,960
Speaker 1: vaccine so that manufacturers around the world can start churning

1233
01:08:50,960 --> 01:08:55,360
Speaker 1: out millions of lower cost doses. Now, the Biden administration,

1234
01:08:55,439 --> 01:08:58,320
Speaker 1: they claim to be pressing Maderna to do more to

1235
01:08:58,400 --> 01:09:01,800
Speaker 1: expand production and to drop the patent. At the same time,

1236
01:09:01,880 --> 01:09:05,000
Speaker 1: though they're saying, uh, well, we don't have the legal

1237
01:09:05,040 --> 01:09:08,800
Speaker 1: authority to unilaterally share the vaccine recipe with the rest

1238
01:09:08,880 --> 01:09:11,839
Speaker 1: of the world. Of all the excuses, though, the biggest

1239
01:09:11,840 --> 01:09:13,840
Speaker 1: one for not sharing the vaccine has always been that

1240
01:09:13,880 --> 01:09:16,360
Speaker 1: these third world countries can't possibly produce the vaccines to

1241
01:09:16,400 --> 01:09:18,679
Speaker 1: our standards. Well, we're now seeing just what a bold

1242
01:09:18,720 --> 01:09:21,960
Speaker 1: face life that excuse ultimately was. It turns out not

1243
01:09:22,040 --> 01:09:24,599
Speaker 1: only do pharmaceutical makers around the globe have the ability

1244
01:09:24,640 --> 01:09:27,960
Speaker 1: to produce the vaccines, scientists in South Africa are making

1245
01:09:28,040 --> 01:09:30,160
Speaker 1: a concerted effort to pull off what would be a

1246
01:09:30,200 --> 01:09:35,640
Speaker 1: truly incredible feat. They're trying to reverse engineer the Maderna vaccine,

1247
01:09:35,920 --> 01:09:39,200
Speaker 1: cracking the code of that vaccine recipe so that they

1248
01:09:39,240 --> 01:09:42,000
Speaker 1: can have a chance at a premium vaccine for their

1249
01:09:42,000 --> 01:09:44,960
Speaker 1: own population. This effort is received backing for the World

1250
01:09:44,960 --> 01:09:47,640
Speaker 1: Health Organization, which is helping coordinate training and source raw

1251
01:09:47,720 --> 01:09:50,640
Speaker 1: materials for the effort. One young scientist involved in the

1252
01:09:50,640 --> 01:09:53,200
Speaker 1: effort said quote, we are doing this for Africa at

1253
01:09:53,240 --> 01:09:55,960
Speaker 1: this moment, and that drives us. We can no longer

1254
01:09:56,040 --> 01:10:00,160
Speaker 1: rely on these big superpowers to come in and save us.

1255
01:10:00,200 --> 01:10:04,360
Speaker 1: Think of the insanity here. Maderna could just give them

1256
01:10:04,400 --> 01:10:08,800
Speaker 1: the recipe, opening the floodgates for more production. The Biden administration,

1257
01:10:09,120 --> 01:10:13,080
Speaker 1: which funded the Maderna vaccine, could exercise margin rights, lift

1258
01:10:13,080 --> 01:10:18,080
Speaker 1: the patent protections and also open the floodgates. Instead, Africa

1259
01:10:18,120 --> 01:10:20,479
Speaker 1: is left should try to crack the code and divine

1260
01:10:20,520 --> 01:10:22,960
Speaker 1: the process. In a last ditch effort to access what

1261
01:10:23,040 --> 01:10:27,320
Speaker 1: should have always been publicly available, and make no mistake

1262
01:10:27,360 --> 01:10:32,520
Speaker 1: about it, the consequences for our own population of this greed, cowardice,

1263
01:10:32,520 --> 01:10:36,040
Speaker 1: and corruption will be deadly. We can get every less

1264
01:10:36,080 --> 01:10:38,680
Speaker 1: solitary soul in our own country vaccinated, and it is

1265
01:10:38,720 --> 01:10:40,519
Speaker 1: not going to matter much in the end. If new

1266
01:10:40,600 --> 01:10:44,559
Speaker 1: variants are constantly emerging from an unvaccinated global South, the

1267
01:10:44,600 --> 01:10:47,479
Speaker 1: pandemic will never end so long as billions of people

1268
01:10:47,520 --> 01:10:50,439
Speaker 1: remain vulnerable as a laboratory for COVID to mutate and

1269
01:10:50,560 --> 01:10:54,240
Speaker 1: jump the vaccines that we've already created. It's an unconscionable

1270
01:10:54,320 --> 01:10:58,439
Speaker 1: and frankly murderous crime to hoard this vaccine artificially decreasing supply,

1271
01:10:58,760 --> 01:11:01,680
Speaker 1: keeping prices premiums so that some pharma execs somewhere can

1272
01:11:01,720 --> 01:11:04,599
Speaker 1: get a bigger yacht. Stop worrying about the anti mask

1273
01:11:04,720 --> 01:11:08,160
Speaker 1: Karen's and start worrying about the real COVID criminals, the

1274
01:11:08,200 --> 01:11:11,559
Speaker 1: CEOs and the politicians who would let millions die to

1275
01:11:11,640 --> 01:11:14,759
Speaker 1: protect their profits and Sager. That's the very last updates

1276
01:11:14,760 --> 01:11:17,400
Speaker 1: to this story. The Biden administration said, ah, We've done

1277
01:11:17,400 --> 01:11:20,479
Speaker 1: a legal review, and unfortunately one more thing I promise.

1278
01:11:20,840 --> 01:11:23,040
Speaker 1: Just wanted to make sure you knew about my podcast

1279
01:11:23,040 --> 01:11:25,880
Speaker 1: with Kyle Kolinski. It's called Crystal, Kyle and Friends, where

1280
01:11:25,880 --> 01:11:28,679
Speaker 1: we do long form interviews with people like Noam Chomsky,

1281
01:11:28,760 --> 01:11:32,040
Speaker 1: Cornell West, and Glenn Greenwald. You can listen on any

1282
01:11:32,080 --> 01:11:35,479
Speaker 1: podcast platform, or you can subscribe over on substack to

1283
01:11:35,479 --> 01:11:37,479
Speaker 1: get the video a day early. We're going to stop

1284
01:11:37,479 --> 01:11:40,160
Speaker 1: bugging you now enjoy all right, Sager, what are you

1285
01:11:40,160 --> 01:11:42,839
Speaker 1: looking at? Well? If we're being honest, in many aspects

1286
01:11:42,840 --> 01:11:45,240
Speaker 1: of American lives, it really does not matter who the

1287
01:11:45,280 --> 01:11:48,800
Speaker 1: president is. The president rarely has as much control as

1288
01:11:48,840 --> 01:11:50,360
Speaker 1: we may think over most of the things that we

1289
01:11:50,400 --> 01:11:53,000
Speaker 1: interact with on a daily basis. The only place that

1290
01:11:53,080 --> 01:11:56,719
Speaker 1: they really have total and complete control is foreign policy.

1291
01:11:56,960 --> 01:11:59,960
Speaker 1: That is why who we elect as president, their faculty,

1292
01:12:00,400 --> 01:12:04,559
Speaker 1: their judgment, their worldview is arguably the most important thing

1293
01:12:04,600 --> 01:12:08,280
Speaker 1: about them. Even though consistently most Americans never really care

1294
01:12:08,360 --> 01:12:10,519
Speaker 1: that much about foreign policy and rank it as a

1295
01:12:10,520 --> 01:12:14,280
Speaker 1: top priority. It's especially important when you're dealing with nuclear

1296
01:12:14,320 --> 01:12:17,840
Speaker 1: powers and matters of war. A miscalculation, as we learned

1297
01:12:17,880 --> 01:12:20,719
Speaker 1: in the Cuban missile crisis, can literally be a matter

1298
01:12:20,760 --> 01:12:23,920
Speaker 1: of life or death. For tens of millions of people.

1299
01:12:24,240 --> 01:12:27,960
Speaker 1: That is why I am getting increasingly dismayed by Joe

1300
01:12:27,960 --> 01:12:33,599
Speaker 1: Biden's cavalier, confused and apparently contradictory statements on Taiwan. Now, Taiwan,

1301
01:12:33,680 --> 01:12:36,599
Speaker 1: as many of you know, is the island, territory, or nation,

1302
01:12:36,760 --> 01:12:39,200
Speaker 1: depending on who you ask, off of the coast of China.

1303
01:12:39,840 --> 01:12:42,880
Speaker 1: Taiwan was originally the refuge of the nationalists who lost

1304
01:12:42,880 --> 01:12:45,200
Speaker 1: the Chinese Civil War in the nineteen forties. It has

1305
01:12:45,200 --> 01:12:48,960
Speaker 1: since developed into a thriving democracy and a technological powerhouse

1306
01:12:49,120 --> 01:12:52,160
Speaker 1: by nearly all measures. It's a mostly separate ethnic group

1307
01:12:52,200 --> 01:12:54,719
Speaker 1: almost at this point from China, but that doesn't stop

1308
01:12:54,760 --> 01:12:57,320
Speaker 1: the Chinese Communist Party from claiming it as its own.

1309
01:12:57,479 --> 01:13:00,360
Speaker 1: The CCP views Taiwan's existence as an affront to its

1310
01:13:00,439 --> 01:13:04,519
Speaker 1: legitimacy of governance over all Chinese peoples. Now, rhetoric from

1311
01:13:04,560 --> 01:13:08,559
Speaker 1: the CCP in recent months has escalated significantly, Chinese President

1312
01:13:08,640 --> 01:13:12,639
Speaker 1: Shihingping vowing that what they call peaceful reunification with Taiwan.

1313
01:13:13,000 --> 01:13:17,160
Speaker 1: As we have seen multiple instances of Chinese military aircraft

1314
01:13:17,320 --> 01:13:20,639
Speaker 1: penetrating what's called the Taiwanese defense zone. In the aerial

1315
01:13:20,680 --> 01:13:24,759
Speaker 1: defense zone, it leaves everyone asking the question, so, what's

1316
01:13:24,800 --> 01:13:27,880
Speaker 1: America going to do if something happens out there? Now,

1317
01:13:27,960 --> 01:13:31,479
Speaker 1: the answer is pretty complicated, because our relations with Taiwan

1318
01:13:31,920 --> 01:13:35,520
Speaker 1: are not entirely up to the president. The Taiwan Relations

1319
01:13:35,640 --> 01:13:40,320
Speaker 1: Act of nineteen seventy nine establishes non diplomatic relations with Taiwan,

1320
01:13:40,600 --> 01:13:44,360
Speaker 1: effectively not recognizing it as a country, but also kind

1321
01:13:44,360 --> 01:13:48,360
Speaker 1: of doing so militarily. It does not guarantee defense of Taiwan,

1322
01:13:48,800 --> 01:13:51,960
Speaker 1: only that the United States can provision Taiwan with the

1323
01:13:51,960 --> 01:13:56,240
Speaker 1: military capability to defend itself if needed. Now, on a broader,

1324
01:13:56,320 --> 01:14:00,160
Speaker 1: more conceptual level, this is known as strategic ambiguity. Now,

1325
01:14:00,120 --> 01:14:02,360
Speaker 1: it doesn't say that the US will defend Taiwan, and

1326
01:14:02,400 --> 01:14:05,080
Speaker 1: it also doesn't not say it. So that's the effective

1327
01:14:05,200 --> 01:14:08,360
Speaker 1: US policy towards Taiwan has been now for four decades

1328
01:14:08,640 --> 01:14:11,360
Speaker 1: at least until Joe Biden spoke in his most recent

1329
01:14:11,439 --> 01:14:13,760
Speaker 1: town hall. Let's take a list and listen carefully to

1330
01:14:13,840 --> 01:14:18,280
Speaker 1: exactly what he says. China just tested a hypersonic missile.

1331
01:14:18,640 --> 01:14:21,120
Speaker 1: What will you do to keep up with them militarily?

1332
01:14:21,320 --> 01:14:25,280
Speaker 1: And can you vow to protect Taiwan? Yes, and yes,

1333
01:14:26,800 --> 01:14:35,880
Speaker 1: we are militarily China Russia and the rest of the

1334
01:14:35,920 --> 01:14:40,240
Speaker 1: world knows we have the most powerful military and history

1335
01:14:40,280 --> 01:14:43,400
Speaker 1: of the world. Don't worry about whether they're going to

1336
01:14:43,439 --> 01:14:46,000
Speaker 1: be more powerful. But you do have to worry about

1337
01:14:46,520 --> 01:14:48,720
Speaker 1: is whether or not they're going to engage in activities

1338
01:14:48,800 --> 01:14:50,559
Speaker 1: will put them in a position where there may make

1339
01:14:50,600 --> 01:14:54,839
Speaker 1: a serious mistake. And so I have had I've spoken

1340
01:14:54,920 --> 01:14:57,320
Speaker 1: and spent more time with Shijingping than any other world

1341
01:14:57,400 --> 01:15:03,040
Speaker 1: leader has. That is an extraordinary statement. Biden answered definitively

1342
01:15:03,160 --> 01:15:06,040
Speaker 1: that the US would defend Taiwan. That is a major

1343
01:15:06,120 --> 01:15:09,519
Speaker 1: change in American foreign policy. Except that hours later that

1344
01:15:09,600 --> 01:15:12,400
Speaker 1: a White House put out a statement by Jensaki saying, quote,

1345
01:15:12,479 --> 01:15:15,920
Speaker 1: the President was not announcing any change in our policy,

1346
01:15:16,200 --> 01:15:18,799
Speaker 1: nor has he made a decision to change our policy.

1347
01:15:19,040 --> 01:15:22,599
Speaker 1: There is no change in policy. In other words, what

1348
01:15:22,640 --> 01:15:25,000
Speaker 1: Biden just said is not the official position of the

1349
01:15:25,080 --> 01:15:28,120
Speaker 1: US government, or is it. Now, Look, this is the

1350
01:15:28,160 --> 01:15:30,640
Speaker 1: worst of all worlds. If Joe Biden is saying we're

1351
01:15:30,680 --> 01:15:33,760
Speaker 1: going to defend Taiwan, then okay, that's policy. That would

1352
01:15:33,800 --> 01:15:36,400
Speaker 1: certainly change the calculus in Beijing as to whether they're

1353
01:15:36,400 --> 01:15:37,880
Speaker 1: going to make a go for that island or not.

1354
01:15:38,240 --> 01:15:41,599
Speaker 1: But instead Biden is saying one thing definitively, and then

1355
01:15:41,640 --> 01:15:45,160
Speaker 1: the White House is effectively saying he misspoke, and actually

1356
01:15:45,360 --> 01:15:48,439
Speaker 1: maybe he wils to do something, maybe not. If anything,

1357
01:15:48,720 --> 01:15:52,200
Speaker 1: that level of drawing back commitment could actually signal to

1358
01:15:52,280 --> 01:15:54,600
Speaker 1: the Chinese, oh, if you do go for it, we

1359
01:15:54,680 --> 01:15:58,000
Speaker 1: won't do anything, which in turn could actually influence their

1360
01:15:58,040 --> 01:16:01,000
Speaker 1: calculus to make a go for the island. Now, as

1361
01:16:01,000 --> 01:16:03,040
Speaker 1: some of you know, I'm pretty obsessed with the First

1362
01:16:03,080 --> 01:16:05,400
Speaker 1: World War. One of the reasons that war broke out

1363
01:16:05,400 --> 01:16:09,280
Speaker 1: in nineteen fourteen was specifically because of lack of clear

1364
01:16:09,320 --> 01:16:13,000
Speaker 1: communication from world leaders as to what their real intentions were.

1365
01:16:13,240 --> 01:16:15,280
Speaker 1: The Kaiser would say one thing, and then the Foreign

1366
01:16:15,320 --> 01:16:17,720
Speaker 1: Office would say another, and then the ambassador would say

1367
01:16:17,760 --> 01:16:21,240
Speaker 1: something else. Now, the lack of clarity and communication left

1368
01:16:21,280 --> 01:16:25,160
Speaker 1: the interpretations up to a series of autocratic rulers. And

1369
01:16:25,240 --> 01:16:28,040
Speaker 1: at that point, when the decision is in the hands

1370
01:16:28,040 --> 01:16:30,960
Speaker 1: of a single man, it takes only one misreading of

1371
01:16:31,000 --> 01:16:33,639
Speaker 1: a situation for tens of millions of people to die

1372
01:16:33,960 --> 01:16:37,120
Speaker 1: with nuclear weapons. Now we're talking about hundreds of millions

1373
01:16:37,160 --> 01:16:40,000
Speaker 1: of people lives at stake, and the same level of

1374
01:16:40,040 --> 01:16:43,879
Speaker 1: potential miscalculation by human beings. One reason I am highlighting

1375
01:16:43,920 --> 01:16:46,600
Speaker 1: this now is because I believe the potential for a

1376
01:16:46,640 --> 01:16:49,479
Speaker 1: major escalation in Asia is higher than it has ever

1377
01:16:49,520 --> 01:16:53,920
Speaker 1: been before, not because China is rising, but conversely because

1378
01:16:53,920 --> 01:16:56,840
Speaker 1: it may have peaked already. I've become obsessed recently with

1379
01:16:56,880 --> 01:17:00,000
Speaker 1: an argument advanced by how Brands that the Chinese economy

1380
01:17:00,080 --> 01:17:03,519
Speaker 1: as we know is basically completely fake. Evergrand was just

1381
01:17:03,520 --> 01:17:05,960
Speaker 1: the tip of the iceberg. It's tech companies, while good,

1382
01:17:06,040 --> 01:17:09,400
Speaker 1: are artificial state constructions. The foundation of its economy is

1383
01:17:09,520 --> 01:17:13,479
Speaker 1: graft and horse trading among senior Communist Party members. Such

1384
01:17:13,479 --> 01:17:16,920
Speaker 1: a system can only go on for so long. With COVID,

1385
01:17:16,960 --> 01:17:20,800
Speaker 1: with global economic disruptions, perhaps the music might stop domestically.

1386
01:17:21,080 --> 01:17:23,920
Speaker 1: And it's precisely at that moment when a power believes

1387
01:17:23,920 --> 01:17:25,920
Speaker 1: that it may have peaked, when it has done all

1388
01:17:25,960 --> 01:17:28,599
Speaker 1: it can through domestic policy, that it may be at

1389
01:17:28,600 --> 01:17:32,559
Speaker 1: its economic peak, that war is actually most likely in history.

1390
01:17:32,880 --> 01:17:35,439
Speaker 1: It's the time rationally that would be the best to

1391
01:17:35,520 --> 01:17:39,360
Speaker 1: make a military move, or to consolidate power and potentially

1392
01:17:39,360 --> 01:17:44,080
Speaker 1: attain or redirect more resources back to the declining state. Now,

1393
01:17:44,080 --> 01:17:46,679
Speaker 1: it's not without precedent. Look at how Russia has behaved

1394
01:17:46,720 --> 01:17:50,280
Speaker 1: under Putin despite that it's an economic and demographic complete joke.

1395
01:17:50,600 --> 01:17:52,920
Speaker 1: It would also explain Germany's behavior in the First World

1396
01:17:52,960 --> 01:17:55,800
Speaker 1: War Japan's in the Second World War. In all three

1397
01:17:55,840 --> 01:17:59,120
Speaker 1: cases it entails a lashing out and ignition of a

1398
01:17:59,160 --> 01:18:02,800
Speaker 1: major war, and in all three cases clear communication from

1399
01:18:02,800 --> 01:18:06,720
Speaker 1: the United States or Great Britain could have prevented it.

1400
01:18:06,960 --> 01:18:10,160
Speaker 1: Now it was precisely because of confusion that millions of

1401
01:18:10,280 --> 01:18:13,599
Speaker 1: people have died previously. Joe Biden is playing with fire

1402
01:18:13,760 --> 01:18:16,080
Speaker 1: when he says one thing, the White House says another.

1403
01:18:16,320 --> 01:18:18,720
Speaker 1: People's lives are at stake, and we need a hell

1404
01:18:18,760 --> 01:18:21,320
Speaker 1: of a lot better right now. This is the thing. Gristle.

1405
01:18:21,520 --> 01:18:23,600
Speaker 1: I used to be very worried about this whenever it

1406
01:18:23,600 --> 01:18:26,040
Speaker 1: came to Trump and North Korea, now when they were

1407
01:18:26,080 --> 01:18:29,720
Speaker 1: talking joining us now to talk about inflation and all

1408
01:18:29,760 --> 01:18:32,040
Speaker 1: that's going on with the economy. As someone who's work

1409
01:18:32,080 --> 01:18:34,599
Speaker 1: we have really relied upon. Here. How they're long, she's

1410
01:18:34,680 --> 01:18:37,680
Speaker 1: economics correspondent for the Washington Post. Great to have you, hew,

1411
01:18:37,680 --> 01:18:42,240
Speaker 1: they're welcome. Good to see hi. Could you just give

1412
01:18:42,320 --> 01:18:44,920
Speaker 1: us an overview? And I think we have your latest

1413
01:18:44,920 --> 01:18:46,679
Speaker 1: piece here that we can throw up on the screen

1414
01:18:46,840 --> 01:18:50,000
Speaker 1: about inflation. If we can put that element up on

1415
01:18:50,000 --> 01:18:52,840
Speaker 1: the screen, guys, uncomfortable. Inflation is here and it is

1416
01:18:52,920 --> 01:18:56,080
Speaker 1: changing the economy. American families and businesses are altering their

1417
01:18:56,080 --> 01:19:00,240
Speaker 1: habits as they increasingly believe high prices are here to day.

1418
01:19:01,040 --> 01:19:03,639
Speaker 1: Give us how there are just an overview of where

1419
01:19:03,680 --> 01:19:06,280
Speaker 1: we stand with regards to inflation and what goods in

1420
01:19:06,320 --> 01:19:11,960
Speaker 1: particular are driving those numbers. Yeah, it's really astounding. Obviously

1421
01:19:12,080 --> 01:19:15,400
Speaker 1: we have inflation, depending upon which measure you look at,

1422
01:19:15,680 --> 01:19:18,799
Speaker 1: that's at a thirteen year high, or in some cases,

1423
01:19:18,880 --> 01:19:20,720
Speaker 1: if you look at some of the other gauges, you

1424
01:19:20,760 --> 01:19:23,679
Speaker 1: could even argue it's at over a twenty year high.

1425
01:19:24,000 --> 01:19:26,559
Speaker 1: So people are feeling it. I was really stunned to

1426
01:19:26,600 --> 01:19:30,360
Speaker 1: see the latest CNBC polling that shows that people are

1427
01:19:30,400 --> 01:19:34,160
Speaker 1: as concerned in America about inflation now as they are

1428
01:19:34,200 --> 01:19:37,639
Speaker 1: about the coronavirus. And a lot of that reason they're

1429
01:19:37,680 --> 01:19:41,000
Speaker 1: so concerned is just what you said. People are feeling

1430
01:19:41,000 --> 01:19:43,519
Speaker 1: it in so many areas. You know, it used to

1431
01:19:43,560 --> 01:19:45,920
Speaker 1: be in the spring and summer everybody was talking about

1432
01:19:45,920 --> 01:19:49,479
Speaker 1: the used car prices and the lumber price is soaring. Well,

1433
01:19:49,520 --> 01:19:51,599
Speaker 1: if you weren't buying a used car, maybe you didn't

1434
01:19:51,640 --> 01:19:55,280
Speaker 1: feel it. But now we just see inflation across the board.

1435
01:19:55,800 --> 01:19:58,920
Speaker 1: And not only do we see it in furniture and

1436
01:19:59,000 --> 01:20:04,040
Speaker 1: appliances TVs, but it's also food price inflation is very high.

1437
01:20:04,160 --> 01:20:06,600
Speaker 1: Almost any kind of protein, any kind of meat, or

1438
01:20:06,640 --> 01:20:08,960
Speaker 1: even eggs you would buy at the store, up about

1439
01:20:09,000 --> 01:20:12,120
Speaker 1: ten percent. And the one that really worries me. Of course,

1440
01:20:12,120 --> 01:20:15,400
Speaker 1: people are focused on those gas prices up about a

1441
01:20:15,479 --> 01:20:18,400
Speaker 1: dollar from a year ago, but the one that really

1442
01:20:18,400 --> 01:20:21,599
Speaker 1: worries me is rent prices have taken off. They are

1443
01:20:21,640 --> 01:20:24,919
Speaker 1: near a twenty year high in many parts of the country,

1444
01:20:24,960 --> 01:20:27,040
Speaker 1: and this time around it's not being driven by New

1445
01:20:27,120 --> 01:20:30,880
Speaker 1: York and San Francisco, the big coastal cities. The really

1446
01:20:30,920 --> 01:20:33,240
Speaker 1: big surges are in places that we used to think

1447
01:20:33,240 --> 01:20:38,720
Speaker 1: of as affordable, like Phoenix, Arizona, or Boise, Idaho, or Spokane, Washington.

1448
01:20:39,360 --> 01:20:41,880
Speaker 1: So it's just getting harder and harder if you're a

1449
01:20:41,960 --> 01:20:45,639
Speaker 1: working class family. Those gas prices are up, food prices

1450
01:20:46,040 --> 01:20:49,040
Speaker 1: hard to get any sort of rental right now, and

1451
01:20:49,560 --> 01:20:52,960
Speaker 1: there just seems to be no end in sight to this,

1452
01:20:53,120 --> 01:20:55,760
Speaker 1: And that's really my main concern in that piece. I'm

1453
01:20:55,840 --> 01:20:59,800
Speaker 1: the era of uncomfortable inflation is here, whether it stays

1454
01:20:59,800 --> 01:21:03,320
Speaker 1: at I don't know, but it's certainly going to be

1455
01:21:03,680 --> 01:21:06,960
Speaker 1: well above that two percent we're used to. So what's

1456
01:21:07,000 --> 01:21:09,080
Speaker 1: the cause, Heather, That's really what it all comes down to.

1457
01:21:09,160 --> 01:21:10,960
Speaker 1: We try to cover a lot of the stuff of

1458
01:21:11,000 --> 01:21:13,880
Speaker 1: what you're discussing, the supply chain crisis, obviously with used

1459
01:21:13,920 --> 01:21:16,880
Speaker 1: cars as well, you know, micro chips get involved. Then

1460
01:21:16,920 --> 01:21:19,240
Speaker 1: we have the port backlog, we have a trucking thing.

1461
01:21:20,000 --> 01:21:23,080
Speaker 1: What is the cause of some of the most significant

1462
01:21:23,120 --> 01:21:26,519
Speaker 1: inflation that we see for the pocketbook of those who

1463
01:21:26,560 --> 01:21:29,840
Speaker 1: are middle class Americans. Well, you're absolutely right that the

1464
01:21:29,920 --> 01:21:33,040
Speaker 1: number one cause right now is the supply chain backlogs

1465
01:21:33,040 --> 01:21:36,360
Speaker 1: that you just outline really well. And that's what's free

1466
01:21:36,439 --> 01:21:39,519
Speaker 1: freaking people out. Can they get their holiday at gifts?

1467
01:21:39,560 --> 01:21:42,400
Speaker 1: But also, and we're starting to see some people rushing

1468
01:21:42,439 --> 01:21:45,080
Speaker 1: to get toilet paper again in some parts of America,

1469
01:21:45,240 --> 01:21:48,839
Speaker 1: or alcohol has run short various types of liquors because

1470
01:21:49,040 --> 01:21:52,479
Speaker 1: they just can't restock the shelves enough. In most parts

1471
01:21:52,520 --> 01:21:54,599
Speaker 1: of the country, it's almost a joke. If you order

1472
01:21:54,680 --> 01:21:57,920
Speaker 1: something like a couch right now, it's at least six

1473
01:21:58,000 --> 01:22:02,160
Speaker 1: months wait. But I think for me, what's really worrying,

1474
01:22:02,600 --> 01:22:05,680
Speaker 1: obviously the supply chain issues are likely to linger. At

1475
01:22:05,760 --> 01:22:09,360
Speaker 1: least we're hearing through summer of twenty twenty two, so

1476
01:22:09,400 --> 01:22:12,400
Speaker 1: we've got over a half year more of this. But

1477
01:22:12,479 --> 01:22:15,120
Speaker 1: I think the bigger problem is we're starting to see

1478
01:22:15,400 --> 01:22:18,960
Speaker 1: some other drivers of inflation picking up. And what I

1479
01:22:19,040 --> 01:22:22,840
Speaker 1: mean by that is we're starting to see restaurants aggressively

1480
01:22:22,920 --> 01:22:28,120
Speaker 1: raised prices or home goods aggressively raised prices because of

1481
01:22:28,160 --> 01:22:30,760
Speaker 1: the supply chain, but also because they're having to pay

1482
01:22:30,760 --> 01:22:33,599
Speaker 1: their workers more. Some of those labor shortage issues are

1483
01:22:33,600 --> 01:22:37,360
Speaker 1: now feeding through into inflation. Similarly, a lot of those

1484
01:22:37,400 --> 01:22:43,440
Speaker 1: housing price woes are feeding through into those higher rent prices,

1485
01:22:43,720 --> 01:22:46,280
Speaker 1: and so those things are not temporary. The White House

1486
01:22:46,280 --> 01:22:48,800
Speaker 1: and the Federal Reserve loves to say, hey, it's short term,

1487
01:22:48,880 --> 01:22:52,719
Speaker 1: it's temporary, it's transitory. But when you start to see,

1488
01:22:52,920 --> 01:22:56,360
Speaker 1: even if they can clear those supply chain backlogs, these

1489
01:22:56,439 --> 01:23:01,040
Speaker 1: labor shortage issues and the rent rising rent are going

1490
01:23:01,080 --> 01:23:04,880
Speaker 1: to linger well. And this is where things get interesting, right,

1491
01:23:04,920 --> 01:23:08,839
Speaker 1: because one man's labor shortage issue is another man's ability

1492
01:23:08,840 --> 01:23:11,519
Speaker 1: to earn a higher wage, or, as you've documented, leave

1493
01:23:11,560 --> 01:23:13,519
Speaker 1: a job they really didn't like and go somewhere else

1494
01:23:13,560 --> 01:23:15,519
Speaker 1: and earn a lot more money or potentially go on

1495
01:23:15,600 --> 01:23:19,400
Speaker 1: strike and bargain for better conditions. So how do we

1496
01:23:19,439 --> 01:23:22,000
Speaker 1: square the fact that, on the one hand, things actually

1497
01:23:22,000 --> 01:23:24,200
Speaker 1: seem pretty good for workers. You have people who feel

1498
01:23:24,200 --> 01:23:27,640
Speaker 1: confident enough to leave their jobs. You do see wages

1499
01:23:27,800 --> 01:23:31,080
Speaker 1: that have been stagnant for decades starting to increase. You

1500
01:23:31,120 --> 01:23:34,360
Speaker 1: see a lot of activity, whether it's at John Deere

1501
01:23:34,760 --> 01:23:37,120
Speaker 1: or AATZI threatening to strike. You see a lot of

1502
01:23:37,160 --> 01:23:40,360
Speaker 1: sort of labor activity that also signals that workers feel

1503
01:23:40,400 --> 01:23:43,360
Speaker 1: like they can bargain here for a better deal. And

1504
01:23:43,479 --> 01:23:45,479
Speaker 1: on the other hand, you have a plurality of Americans

1505
01:23:45,479 --> 01:23:47,920
Speaker 1: who are worried about a recession, who believe a recession

1506
01:23:48,000 --> 01:23:51,360
Speaker 1: is coming in the next year. You have these supply

1507
01:23:51,520 --> 01:23:55,519
Speaker 1: chain issues, You've got inflation spiking. So how do you

1508
01:23:55,560 --> 01:23:58,120
Speaker 1: make sense of this overall picture that seems to be

1509
01:23:58,160 --> 01:24:01,559
Speaker 1: a real mix bag for people? It is, and it's

1510
01:24:01,600 --> 01:24:05,200
Speaker 1: a good word, mixed bag. It's certainly I called it,

1511
01:24:05,280 --> 01:24:07,640
Speaker 1: I think in a piece in early September the I

1512
01:24:07,720 --> 01:24:11,560
Speaker 1: don't know economy. We've just not seen these funky dynamics

1513
01:24:11,600 --> 01:24:14,519
Speaker 1: that we're in right now, and it's not clear how

1514
01:24:14,560 --> 01:24:17,160
Speaker 1: it's all going to end or even what the right

1515
01:24:17,240 --> 01:24:21,240
Speaker 1: policy response should be from Washington and other parts of

1516
01:24:21,280 --> 01:24:24,360
Speaker 1: the world. The European Central Bank is meeting this week

1517
01:24:24,400 --> 01:24:27,599
Speaker 1: as well, so it is a very confusing time, and

1518
01:24:27,640 --> 01:24:30,000
Speaker 1: I just go back to first principles in the sense

1519
01:24:30,080 --> 01:24:33,360
Speaker 1: that you're right, it's a good sign that these wages

1520
01:24:33,400 --> 01:24:37,240
Speaker 1: are finally picking up. Particularly I look at restaurant grocery

1521
01:24:37,240 --> 01:24:40,240
Speaker 1: store workers. For the first time in US history, the

1522
01:24:40,400 --> 01:24:44,080
Speaker 1: average pay for those workers is above fifteen dollars an hour.

1523
01:24:44,200 --> 01:24:47,920
Speaker 1: That happened over the summer. Basically, fifteen is almost a

1524
01:24:48,000 --> 01:24:50,960
Speaker 1: factor the minimum wage in the United States right now.

1525
01:24:51,600 --> 01:24:54,439
Speaker 1: Many workers say they won't even look at a job

1526
01:24:54,479 --> 01:24:59,080
Speaker 1: that doesn't pay at least fifteen dollars an hour. But

1527
01:24:59,400 --> 01:25:03,720
Speaker 1: the big but there is if you look, those wage increases,

1528
01:25:03,840 --> 01:25:07,280
Speaker 1: as great as they are, are almost entirely wiped out

1529
01:25:07,400 --> 01:25:12,840
Speaker 1: by rising inflation. So the optimistic scenario is usually when

1530
01:25:12,880 --> 01:25:15,559
Speaker 1: prices go up, I mean, excuse me, wages go up.

1531
01:25:15,720 --> 01:25:17,680
Speaker 1: They don't get cut later. It's not like we're going

1532
01:25:17,720 --> 01:25:20,360
Speaker 1: to hit March and those wages are going to go

1533
01:25:20,400 --> 01:25:23,559
Speaker 1: from fifteen dollars back to thirteen. So wages when they

1534
01:25:23,560 --> 01:25:26,080
Speaker 1: go up usually stay up, and the hope is that

1535
01:25:26,240 --> 01:25:30,920
Speaker 1: inflation will eventually come back down a little bit. But again,

1536
01:25:31,120 --> 01:25:34,040
Speaker 1: whether that's going to come back down enough is my

1537
01:25:34,200 --> 01:25:37,360
Speaker 1: big concern for people to really feel like they're finally

1538
01:25:37,400 --> 01:25:41,400
Speaker 1: getting ahead in twenty twenty two. Right, Yeah, I mean

1539
01:25:41,439 --> 01:25:43,360
Speaker 1: that's the question. When do you think that we'll know

1540
01:25:43,560 --> 01:25:46,360
Speaker 1: and have the answers kind of definitively will it be

1541
01:25:46,400 --> 01:25:48,559
Speaker 1: a year from now, two years from now? Does it

1542
01:25:48,600 --> 01:25:51,360
Speaker 1: depend more on COVID is the White House? Who are

1543
01:25:51,360 --> 01:25:55,080
Speaker 1: the actual key players who are going to be determiners here. Yeah,

1544
01:25:55,120 --> 01:25:57,320
Speaker 1: that's a great question. I think the key thing to

1545
01:25:57,400 --> 01:26:00,800
Speaker 1: watch is definitely what's going on with this supply chain.

1546
01:26:01,880 --> 01:26:05,320
Speaker 1: Certainly there was some size of relief on wall stream,

1547
01:26:05,439 --> 01:26:08,360
Speaker 1: even just in the last few hours, as finally we're

1548
01:26:08,439 --> 01:26:11,519
Speaker 1: starting to see a little bit of come off on

1549
01:26:11,560 --> 01:26:14,960
Speaker 1: some of those shipping costs. They are still astronomically high

1550
01:26:14,960 --> 01:26:17,639
Speaker 1: compared to where they were even in the spring our

1551
01:26:17,720 --> 01:26:20,880
Speaker 1: last winter, but they have come off a little bit

1552
01:26:21,000 --> 01:26:24,519
Speaker 1: from the September all time record highs that we saw,

1553
01:26:25,080 --> 01:26:27,840
Speaker 1: So in that sense, there's maybe a little bit of

1554
01:26:27,920 --> 01:26:30,519
Speaker 1: sign of hope that at least it may not get

1555
01:26:30,600 --> 01:26:33,880
Speaker 1: worse in the coming months. But certainly when does it

1556
01:26:33,920 --> 01:26:36,800
Speaker 1: really get better? When are we back to something that

1557
01:26:36,840 --> 01:26:40,400
Speaker 1: looks more normal again? A lot of CEOs now are

1558
01:26:40,439 --> 01:26:44,240
Speaker 1: saying that won't happen until summer twenty twenty two, So

1559
01:26:44,280 --> 01:26:47,080
Speaker 1: I think we won't really know a lot until we

1560
01:26:47,200 --> 01:26:49,920
Speaker 1: get through the holiday seasons. Clearly going to be a crunch,

1561
01:26:50,360 --> 01:26:53,120
Speaker 1: and can we work things out in the spring, which

1562
01:26:53,120 --> 01:26:56,280
Speaker 1: tends to be a little bit slower shipping period, right,

1563
01:26:56,800 --> 01:26:58,360
Speaker 1: and how they're Finally, one of the things that I

1564
01:26:58,400 --> 01:27:01,200
Speaker 1: wanted to get from you is you have been tracking

1565
01:27:01,479 --> 01:27:04,439
Speaker 1: the great resignation, the number of historic number of workers

1566
01:27:04,479 --> 01:27:07,360
Speaker 1: who are leaving their jobs and switching industries, and some

1567
01:27:07,400 --> 01:27:09,760
Speaker 1: of the dynamics and trends that are behind that. How

1568
01:27:09,840 --> 01:27:12,240
Speaker 1: much of that is attributable to I saw a quote

1569
01:27:12,240 --> 01:27:14,160
Speaker 1: where someone said, you know, when you realize your boss

1570
01:27:14,240 --> 01:27:17,400
Speaker 1: during a pandemic will literally kill you or sacrifice your life,

1571
01:27:18,160 --> 01:27:20,840
Speaker 1: that changes your relationship to that employment. And in fact,

1572
01:27:20,880 --> 01:27:26,320
Speaker 1: we do see workers disproportionately leaving retail, restaurant work, those

1573
01:27:26,360 --> 01:27:31,679
Speaker 1: sort of frontline essential nursing you know, nursing home workers.

1574
01:27:31,960 --> 01:27:35,280
Speaker 1: That was the most dangerous industry in the country last year.

1575
01:27:35,320 --> 01:27:37,400
Speaker 1: So you see a lot of workers moving out of

1576
01:27:37,439 --> 01:27:40,000
Speaker 1: those industries that were really forced out of the front lines.

1577
01:27:40,479 --> 01:27:43,320
Speaker 1: How much do you think a sort of pandemic rethinking

1578
01:27:43,960 --> 01:27:48,040
Speaker 1: of what their employment was accounts for this big shift

1579
01:27:48,080 --> 01:27:53,040
Speaker 1: in workers. I think this is a huge, huge factor.

1580
01:27:53,120 --> 01:27:56,080
Speaker 1: I've been writing about this since the spring. This is

1581
01:27:56,120 --> 01:27:58,719
Speaker 1: the biggest shakeup in the labor market that we've seen

1582
01:27:58,840 --> 01:28:01,519
Speaker 1: since World War Two. And what I mean by that

1583
01:28:01,640 --> 01:28:05,360
Speaker 1: is this pandemic has affected everyone. You know, We've had

1584
01:28:05,400 --> 01:28:09,120
Speaker 1: over seven hundred thousand deaths in this country. It's affected

1585
01:28:09,200 --> 01:28:12,160
Speaker 1: high wage workers, low wage workers, all different types of

1586
01:28:12,200 --> 01:28:15,320
Speaker 1: communities across the US. And it also a lot of

1587
01:28:15,320 --> 01:28:17,960
Speaker 1: restaurant workers. When you ask them, why are you quitting now?

1588
01:28:18,080 --> 01:28:20,200
Speaker 1: They say two things, you know, they say Number one

1589
01:28:21,560 --> 01:28:24,800
Speaker 1: the pandemic. When I was off for a bit on unemployment,

1590
01:28:24,840 --> 01:28:26,559
Speaker 1: it was the first time in my life I really

1591
01:28:26,600 --> 01:28:29,000
Speaker 1: slowed down, you know that I had a minute to think,

1592
01:28:29,080 --> 01:28:31,280
Speaker 1: what do I want in my life? You know? Is

1593
01:28:31,320 --> 01:28:32,920
Speaker 1: this what I want to be doing? Is this how

1594
01:28:32,920 --> 01:28:35,599
Speaker 1: I want to do? My family? I call it yolo

1595
01:28:35,760 --> 01:28:38,760
Speaker 1: on steroids. We only live once on steroids. Sure, we

1596
01:28:38,800 --> 01:28:40,559
Speaker 1: all knew you should seize the day and all that

1597
01:28:40,640 --> 01:28:43,760
Speaker 1: kind of advice, but to have that time finally to

1598
01:28:43,840 --> 01:28:46,880
Speaker 1: be able to really think about it. I think has

1599
01:28:46,960 --> 01:28:49,800
Speaker 1: galvanized people. The other key thing that I hear right now,

1600
01:28:49,840 --> 01:28:51,479
Speaker 1: and I just want to say one of the numbers

1601
01:28:51,520 --> 01:28:55,240
Speaker 1: really quickly. Over thirty million people have quit their jobs

1602
01:28:55,240 --> 01:28:58,120
Speaker 1: so far this year. That was through August. We have

1603
01:28:58,200 --> 01:29:00,840
Speaker 1: the data through August. If we could you at roughly

1604
01:29:00,920 --> 01:29:03,920
Speaker 1: that pace, we will end the year with over forty

1605
01:29:03,960 --> 01:29:07,479
Speaker 1: five million people quitting their job. We have just never

1606
01:29:07,520 --> 01:29:10,880
Speaker 1: seen anything close to this. But it's not just quits.

1607
01:29:10,920 --> 01:29:14,280
Speaker 1: We have millions more people retiring early. And on a

1608
01:29:14,320 --> 01:29:17,640
Speaker 1: positive side, we have an uptick in people starting new businesses,

1609
01:29:17,760 --> 01:29:21,200
Speaker 1: almost a near a thirty year high and starting new businesses,

1610
01:29:21,240 --> 01:29:24,360
Speaker 1: So we see people making these decisions in so many

1611
01:29:24,400 --> 01:29:27,120
Speaker 1: different areas. And the other thing I hear, which you

1612
01:29:27,240 --> 01:29:29,920
Speaker 1: really went to the heart of, is burnout. I was

1613
01:29:29,920 --> 01:29:33,360
Speaker 1: talking to a server yesterday in Memphis, Tennessee, and he

1614
01:29:33,400 --> 01:29:35,920
Speaker 1: said to me, you know, not only is the job

1615
01:29:36,000 --> 01:29:38,439
Speaker 1: harder now than it used to be because we don't

1616
01:29:38,479 --> 01:29:41,160
Speaker 1: have enough staff so we're all waiting more tables, But

1617
01:29:41,240 --> 01:29:42,880
Speaker 1: he said to me, I was just stunned to hear this.

1618
01:29:42,920 --> 01:29:45,240
Speaker 1: He said, you wouldn't believe it. The number of people

1619
01:29:45,320 --> 01:29:49,719
Speaker 1: who are under tipping right now are leaving zero tips.

1620
01:29:49,439 --> 01:29:54,040
Speaker 1: It's just all of these factors are coming together and

1621
01:29:54,080 --> 01:29:58,679
Speaker 1: people are saying I've had enough. Wow, it's really amazing. Well, Heather,

1622
01:29:58,760 --> 01:30:00,000
Speaker 1: we want to thank you for coming on the show.

1623
01:30:00,040 --> 01:30:02,760
Speaker 1: We really appreciate it. Congratulations on your new I guess

1624
01:30:02,840 --> 01:30:05,160
Speaker 1: is it a promotion, I don't know. Move within the

1625
01:30:05,200 --> 01:30:08,120
Speaker 1: Wahington Post to the columns. We will absolutely be having

1626
01:30:08,120 --> 01:30:10,360
Speaker 1: you on again and reading with great earnest. We use

1627
01:30:10,360 --> 01:30:12,360
Speaker 1: your work all the time, so thank you. Thanks Heather.

1628
01:30:12,439 --> 01:30:16,880
Speaker 1: Great to have you, Thank you, take care absolutely, and

1629
01:30:17,000 --> 01:30:19,840
Speaker 1: thank you guys so much for watching. We really appreciate it.

1630
01:30:19,840 --> 01:30:22,040
Speaker 1: It's just awesome to do the show every day. And

1631
01:30:22,200 --> 01:30:24,400
Speaker 1: you know we've been ending the show this way for

1632
01:30:24,439 --> 01:30:28,240
Speaker 1: a reason, but we consistently see wild swings in our

1633
01:30:28,280 --> 01:30:30,439
Speaker 1: YouTube revenue and that just makes us so that we

1634
01:30:30,479 --> 01:30:33,160
Speaker 1: can't plan as a business. We have great improvements that

1635
01:30:33,200 --> 01:30:35,120
Speaker 1: we want to do. The only thing we can rely

1636
01:30:35,200 --> 01:30:37,960
Speaker 1: on are you, the premium subscribers, So we really appreciate you.

1637
01:30:38,280 --> 01:30:40,320
Speaker 1: Anytime that you guys joining you can support us. We

1638
01:30:40,360 --> 01:30:45,000
Speaker 1: have some awesome, awesome technological developments to debut next week

1639
01:30:45,040 --> 01:30:47,200
Speaker 1: and I really can't wait for you guys to see it.

1640
01:30:47,200 --> 01:30:48,960
Speaker 1: It's been in the work for months and months and months,

1641
01:30:49,000 --> 01:30:52,160
Speaker 1: and it's only possible. It's only possible because of the

1642
01:30:52,240 --> 01:30:55,519
Speaker 1: lifetime members, because of all of the monthly, yearly everything.

1643
01:30:55,560 --> 01:30:58,240
Speaker 1: Your guys' support gives us the assurance that we can

1644
01:30:58,280 --> 01:31:00,320
Speaker 1: go out and spend a lot of money in order

1645
01:31:00,320 --> 01:31:02,840
Speaker 1: to improve the show, to make it widely available for

1646
01:31:02,920 --> 01:31:06,040
Speaker 1: as many people as humanly possible. That is absolutely right.

1647
01:31:06,120 --> 01:31:09,320
Speaker 1: We appreciate you guys every single day. We think about

1648
01:31:09,320 --> 01:31:11,960
Speaker 1: you every day when we're crafting this show too. Hope

1649
01:31:12,000 --> 01:31:14,120
Speaker 1: you have a great day. We'll have some stuff for

1650
01:31:14,200 --> 01:31:16,639
Speaker 1: you tomorrow and a full show back for you on Thursday.

1651
01:31:16,680 --> 01:31:32,320
Speaker 1: We'll see you then see you Thursday. Thanks for listening

1652
01:31:32,360 --> 01:31:34,240
Speaker 1: to the show, guys, we really appreciate it. To help

1653
01:31:34,280 --> 01:31:36,320
Speaker 1: other people find the show, go ahead and leave us

1654
01:31:36,360 --> 01:31:39,360
Speaker 1: a five star rating on Apple Podcasts or wherever you

1655
01:31:39,439 --> 01:31:42,679
Speaker 1: get your podcasts. Really helps other people find the show

1656
01:31:42,960 --> 01:31:46,479
Speaker 1: as always special. Thank you to Supercast for powering our

1657
01:31:46,520 --> 01:31:49,040
Speaker 1: premium membership. If you want to find out more, go

1658
01:31:49,080 --> 01:31:51,080
Speaker 1: to Crystalansager dot com.