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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: 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: 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: 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, Brystal. Indeed, we do a plethora

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Speaker 1: of big stories to bring in this morning. Of course,

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Speaker 1: We're going to update you on the omicron virus and

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Speaker 1: variant and everything that Joe Biden said about that where

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Speaker 1: we seem to be headed. Few updates for you about

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Speaker 1: exactly what is going on there. Jack Dorsey stepping down

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Speaker 1: as head of CEO at CEO of Twitter a little

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Speaker 1: bit troubling his replacements. Some of the comments have been made,

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Speaker 1: so we'll get into that. Chris Cuomo under major brussure

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Speaker 1: at CNN as new revelations about just how directly he

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Speaker 1: was involved in his brother's defense, how he leveraged his

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Speaker 1: media connections to try to help him with the cover up.

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Speaker 1: I'm not sure CNN knew that all of this was

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Speaker 1: going on, so they have been forced to release his

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Speaker 1: statement first time that they've really had much to say

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Speaker 1: at all about what's going on there. So we'll give

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Speaker 1: you all of those details. Also, big news out of Bessemer, Alabama.

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Speaker 1: You'll recall workers at the Amazon warehouse there. They had

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Speaker 1: been trying to unionize. That effort had been defeated, but

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Speaker 1: all along those involved with the organizing efforts said, hey,

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Speaker 1: this was not on the up and up. Amazon cheated

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Speaker 1: and this was unfair practices. Well, the NLRB at this

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Speaker 1: point has agreed with them. They are calling for a

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Speaker 1: new election there down in Bessemer, Alabama, So obviously that

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Speaker 1: is huge news. Also, our great friend of the show,

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Speaker 1: doctor Fauci making some comments quite eyebrow raising. We will

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Speaker 1: get to that in a moment, but we wanted to

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Speaker 1: start with the very latest on the new omicron variant.

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Speaker 1: Joe Biden making some comments yesterday about his plans to

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Speaker 1: deal with that virus. Let's take a listen to that.

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Speaker 1: The best protection I know you're tired of me say this,

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Speaker 1: The best protection against this new variant or any of

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Speaker 1: the variants out there once we've been dealing with already,

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Speaker 1: is getting fully vaccinated and getting a booster shot. Most

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Speaker 1: Americans are fully vaccinated but not yet boosted. If you're

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Speaker 1: eighteen years or over and got fully vaccinated before June

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Speaker 1: the first go get the booster shot today. They're free,

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Speaker 1: and they're available at eighty thousand locations coast to coast.

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Speaker 1: A fully vaccinated booster person is the most protected against COVID.

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Speaker 1: Do not wait, go get your booster if it's time

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Speaker 1: for you to do so. And if you are not vaccinated,

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Speaker 1: now's the time to get vaccinated and take your children

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Speaker 1: to be vaccinated. Every child age five or older can

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Speaker 1: get safe, effective vaccines. Now, I like the way he

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Speaker 1: calls them fully vaccinateed booster people. So a couple things

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Speaker 1: hit the totality of effectively what he's saying here is

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Speaker 1: in addition to the travel band, which even some of

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Speaker 1: his allies and the doctor we talked to you, Yester said,

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Speaker 1: this is really going to do anything. This is more

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Speaker 1: theater than anything else. He's effectively saying, Look, we're not

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Speaker 1: looking at any lockdowns, but we want you to get

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Speaker 1: vaccinated and we want you to get boosters. This caught

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Speaker 1: both of our attention yesterday because prior to yesterday, the

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Speaker 1: CDC's guidance was that adults can get a booster, yes,

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Speaker 1: but that only people who are elderly should get a booster. Well,

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Speaker 1: that guidance has now officially been changed because of this

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Speaker 1: new variant. Let's throw that tear sheet up on the screen.

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Speaker 1: The CDC strengthened its booster recommendations as worries mount over

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Speaker 1: the omicron variant, prompted by growing concerns, the CDC and

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Speaker 1: Prevention Center for Disease Control and Prevention on Monday said

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Speaker 1: all American adults should get booster doses of the available

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Speaker 1: coronavirus vaccines. Adults age eighteen and olders should get a

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Speaker 1: booster shot when they are six months past the initial

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Speaker 1: immunization with Pfizer or Maderna or two months after the

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Speaker 1: single shot JNJA vaccine, which has proven to be somewhat

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Speaker 1: less effective than the two dose Pfizer and Maderna mRNA versions.

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Speaker 1: The CDC had previously said Americans over age fifty, as

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Speaker 1: well as those ages eighteen and older living in long

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Speaker 1: term care facilities, should get booster shows, while other adults

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Speaker 1: may decide to do so based on their individual risk.

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Speaker 1: So shift in language here, but also significant. Now you

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Speaker 1: have a sort of blanket encouragement for all adults to

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Speaker 1: get their booster full disclosure. I did get mine over

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Speaker 1: the weekend. I was taking my kid to get his

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Speaker 1: first job and decided I may as well go ahead

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Speaker 1: and get my booster as well. I had very little,

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Speaker 1: minimal side effects, just so you guys know. Full transparency.

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Speaker 1: But this does mark a shift in terms of how

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Speaker 1: the CDC is talking about boosters, and this is something

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Speaker 1: we tracked for a while. Yes, because frankly, there isn't

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Speaker 1: a lot of evidence that boosters are particularly needed at

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Speaker 1: this point, only for elderly people. For elderly people, it

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Speaker 1: seems to work pretty well, right, And so you know,

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Speaker 1: one of the things that has been a little bit

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Speaker 1: misleading about some of the media presentation of the vaccine

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Speaker 1: effectiveness is while yes, breakthrough infections all a thing, and

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Speaker 1: the efficacy with regards to getting COVID at all does

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Speaker 1: seem to weigh somewhat over time, you still have a

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Speaker 1: lot of protection against severe hospitalization and death. Oh yes, so,

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Speaker 1: and I actually it's bothered me that they haven't frontloaded

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Speaker 1: with that information because ultimately you want people to know

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Speaker 1: that the vaccines do in fact work and it is

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Speaker 1: worth going out and getting them. Yeah. I think that

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Speaker 1: this is the communication of on this has been a mess,

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Speaker 1: and this is what we flagged on this, which is

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Speaker 1: the President came out and said everybody should get a

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Speaker 1: booster now. At the time that he made that statement,

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Speaker 1: that was not a recommendation from the CDC, leading me

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Speaker 1: and many other people to be like, hold on a second,

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Speaker 1: did Biden just go ahead of what CDC guidance was.

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Speaker 1: Then the CDC hours later changes guidance. Now. The reason

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Speaker 1: I'm dubious and skeptical on this is that remember the

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Speaker 1: original booster guidance from the CDC and also from the FDA,

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Speaker 1: we had those two top scientists at the FDA resigned,

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Speaker 1: specifically over Biden and the White House getting over at

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Speaker 1: SKIS and recommending boosters for all Americans. The two scientists resign.

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Speaker 1: Then the CDC came out and said, okay, okay, we're

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Speaker 1: going to revise our guidance on the booster. The official

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Speaker 1: guidance is it's only for people who are sixty five

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Speaker 1: or sorry, fifty years and older, and also people who

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Speaker 1: are eighteen plus who work in a high risk environment.

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Speaker 1: That was the only eligibility. Two weeks three weeks later,

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Speaker 1: they change it November I think it was twenty November, Yeah, nineteenth,

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Speaker 1: they came out and they changed a guidance too. Everyone

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Speaker 1: is eligible for a booster, as in, you can go

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Speaker 1: get one if you want, but you should only get one,

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Speaker 1: should being the not the can should get one if

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Speaker 1: you're fifty years older plus eighteen and you work in

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Speaker 1: a high risk environment. So all of this has changed

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Speaker 1: within the span of a month and a half. Now,

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Speaker 1: look I understand. You know, my public health friends will

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Speaker 1: be like, yeah, but omicron, you know the variant and changes.

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Speaker 1: But you have to make this case very publicly to

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Speaker 1: people or they're going to be like, I don't understand

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Speaker 1: what's happening, and that seems to be the real problem.

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Speaker 1: I completely agree with you. Look double vaccinated, Like, yes,

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Speaker 1: you can get a break through infection. It happened to me.

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Speaker 1: It does, you know, decrease your odds of it like

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Speaker 1: population wide and all that, and it's gonna, you know,

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Speaker 1: dramatically protect you from hospitalization and death. For a lot

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Speaker 1: of the people who are worried about side effects and

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Speaker 1: all of that. Myocarditis is the one that is cited

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Speaker 1: a lot. Your risk is actually much higher from getting myocarcaditis,

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Speaker 1: even when you're young, from actually getting COVID, specifically long COVID,

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Speaker 1: and especially those people who are a little bit older

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Speaker 1: thirty five, forty or whatever and above. If you look

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Speaker 1: at the risks there, Look, it's something you should decide

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Speaker 1: for yourself, but it's something that I think we should

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Speaker 1: address here on the show. Hospitalization and death. And then look,

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Speaker 1: there's risks from getting COVID, and you know, there's a

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Speaker 1: quote unquote risk. There are side effects, of course from

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Speaker 1: also getting the vaccine when you give it to hundreds

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Speaker 1: of millions of people. You should compare those two things

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Speaker 1: side by side. It's pretty clear. You know which side

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Speaker 1: I think, personally think you should fall on. Can I

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Speaker 1: also say yeh on the booster thing. I decided to

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Speaker 1: get it because I don't want to get COVID, Like

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Speaker 1: even though it worried about it. It's not fun, but

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Speaker 1: I wasn't worried about being in the hospital. I wasn't

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Speaker 1: worried about dying. But I, you know, just like I

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Speaker 1: get the flu shot, like, I didn't really want to

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Speaker 1: get COVID. So that's why I got it. But I

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Speaker 1: do want to say, for people who got the Johnson

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Speaker 1: and Johnson vaccine, you really should get a second one

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Speaker 1: because that one, first of all, almost all of the

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Speaker 1: protection against getting COVID goes away. You still do have

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Speaker 1: significant protection against hospitalization and death, but it is significantly

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Speaker 1: less than with the mRNA vaccine. So if you got

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Speaker 1: the J and J vaccine, you should go get another

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Speaker 1: one because that one just hasn't held up as well

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Speaker 1: as the other two. Have another thing that just broke

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Speaker 1: at least I just saw this morning, which you should

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Speaker 1: take with a million grains of salt, because we're talking

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Speaker 1: about a pharmaceutical executive who has a financial interest in

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Speaker 1: everybody getting boosters and getting more vaccines. But the CEO

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Speaker 1: of Maderna, which of course makes what has turned out

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Speaker 1: to be the most effective vac scene, is saying that

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Speaker 1: he doesn't think that the vaccines are going to hold

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Speaker 1: up all that well against omicron. Now that is speculation

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Speaker 1: at this point because it's just too early to say,

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Speaker 1: but I'll just read to you what he is saying.

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Speaker 1: He said the high number of mutations on the spike

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Speaker 1: protein with omicron, which is of course what the virus

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Speaker 1: uses to infect human cells, and the rapids spread of

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Speaker 1: their variant in South Africa suggested that the current crop

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Speaker 1: of vaccines may need to be modified next year. He said, quote,

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Speaker 1: there is no world I think where the effectiveness is

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Speaker 1: the same level we had with the delta variant. I

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Speaker 1: think it's going to be a material drop. I just

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Speaker 1: don't know how much because we need to wait for

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Speaker 1: the data. But all the scientists I've talked to are like,

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Speaker 1: this is not going to be good. That's what someone

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Speaker 1: who has a direct financial interest in us having boosters

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Speaker 1: and having vaccines a new vaccine every year, for a

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Speaker 1: new variant every year. That's what he's saying. That doesn't

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Speaker 1: mean it's wrong, means you should take that into account.

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Speaker 1: And on that note, you know, while the stock markets

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Speaker 1: dropped and oil futures dropped and there was financial fall

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Speaker 1: up for most companies because of the omicron variant. And

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Speaker 1: by the way, these comments knew from the Maderna CEO

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Speaker 1: has sent the market even lower. Well, it hasn't been

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Speaker 1: bad news for everyone, has it. Let's take a listen

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Speaker 1: to an interview with the Pfeiser CEO on CNBC. Do

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Speaker 1: you see this happening every year? We either get a

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Speaker 1: booster boost, a regular booster of the same vaccine, or

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Speaker 1: a slightly different vaccine every year to deal with what

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Speaker 1: we're seeing with these mutations. Is that what you first

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Speaker 1: see is it's almost like a I mean, for Pfizer,

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Speaker 1: you'd be selling these things every year, and not that

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Speaker 1: you want to do that. I'm sure you're not hoping

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Speaker 1: for that, but it'll be almost like an annuity for Pfizer.

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Speaker 1: I didn't make a projection months ago, but the most

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Speaker 1: likely scenario. It is that we will meet after the

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Speaker 1: third dose annual revaccinations against of it for multiple reasons,

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Speaker 1: because of the immunity that would be waiting, because of

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Speaker 1: the virus that I'm sure will be maintained around the

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Speaker 1: world for the years to come, and also because of

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Speaker 1: the need of variant that will emerge. I'm more confident

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Speaker 1: right now that this would be the case than I

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Speaker 1: was when I made the projection. I think we are

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Speaker 1: going to have an annual revaccination. I don't know how

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Speaker 1: we're going to call it, but would be an annual revaccination,

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Speaker 1: and that should be able to keep us really safe.

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Speaker 1: I mean, you love the just nakedness of the financial press,

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Speaker 1: like the stock I'm sure you don't want to I

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Speaker 1: love this to happen stock prices. This is like an

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Speaker 1: annuity for a visor, right with the stock prices right

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Speaker 1: there along the side. And listen, as we talked about yesterday,

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Speaker 1: the ideal, most profitable situation for these companies is to

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Speaker 1: make a vaccine that actually works so people want it,

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Speaker 1: and then sell it at premium prices to the rich

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Speaker 1: world and keep the world unvaccinated so that we do

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Speaker 1: continue to churn out variant after variant after variant, which

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Speaker 1: is why it would be so important if the Biden

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Speaker 1: administration would stopped us talking about lifting patent protections and

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Speaker 1: actually put some muscle behind it, get behind the existing

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Speaker 1: proposal at the World Traded Organization, or write a new proposal,

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Speaker 1: and most importantly put their muscle behind pressuring Germany in

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Speaker 1: particular to get on board with this as well, because

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Speaker 1: it is unconscionable, unconscionable that you only have six or

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Speaker 1: seven percent of Africa vaccinated, that the poor world has

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Speaker 1: basically been left out of this entirely is just absolutely disgusting. Yeah,

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Speaker 1: and I would also say that that's a lot of

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Speaker 1: that needs to be done in order to reclaim a

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Speaker 1: lot of ground that has been given to people who

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Speaker 1: are very skeptical of vaccine because you hear this, I mean,

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Speaker 1: what are you supposed to think the guys literally saying

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Speaker 1: that you need a shot every year. Three months ago,

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Speaker 1: that was considered a conspiracy theory in the United States,

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Speaker 1: that you're going to have to have boosters over and

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Speaker 1: over again. And that's actually something that is cited by

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Speaker 1: a lot of people who don't want the vaccine because

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Speaker 1: they're like Look, even if I get it, then I

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Speaker 1: still might get it, and then I might have to

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Speaker 1: keep getting one over and over again, and I simply

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Speaker 1: don't want to or you know, risk compound year over year.

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Speaker 1: I get it, Like I completely understand. And you know,

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Speaker 1: why should you trust the CEO of Visor and especially

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Speaker 1: when they have a direct financial incentive in order to

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Speaker 1: do so. And then you look at what the government

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Speaker 1: is doing, which is essentially embracing this policy. Now, who

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Speaker 1: is actually running the show? Is it the actual scientists?

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Speaker 1: We will be seen change their minds on booster shots

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Speaker 1: three times in the last eight weeks, or is it

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Speaker 1: the CEO? I mean, we need to reclaim some sort

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Speaker 1: of public trust, and that's part of the problem. I

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Speaker 1: just think this is completely ridiculous. And you know, I'll

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Speaker 1: put my cars on the table. I'm deeply skeptical, and

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Speaker 1: I found in my own experience, I don't I'm not

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Speaker 1: getting good information like I got, you know, two doses

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Speaker 1: of maderna and then I got COVID. Do I need

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Speaker 1: a booster shot? There's no official guidance on that because

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Speaker 1: natural immunity is not currently recognized by the CDC whatsoever

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Speaker 1: in terms of its guidance on whether you should get

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Speaker 1: shots or not. And look, I realize like how I'm

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Speaker 1: beginning to sound, but the to somebody who went out

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Speaker 1: and sought out the vaccine as early as possible. And

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Speaker 1: then also you see this and you say, okay, well,

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Speaker 1: you know, I'm a young man, got tubidosis, a madernal,

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Speaker 1: also got covid of natural immunity. Do I really need

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Speaker 1: a booster shot every single year? Or and this is

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Speaker 1: from a population wide basis, what if we have it

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Speaker 1: such that boosters instead of being recommended necessarily for everybody,

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Speaker 1: we focus on the ultimate metric, in my opinion, which

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Speaker 1: matters the most hospitalization and death. If we can reduce

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Speaker 1: that every single year and every year, let's say that

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Speaker 1: we do have a booster shot every year, and you know,

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Speaker 1: it'll be like the flu vaccine, which is that, oh there,

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Speaker 1: you know this particular strain of flu, Well, look who

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Speaker 1: everyone should get a flu shot, but in general, like

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Speaker 1: who are that they really need to be given to

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Speaker 1: the elderly? And well, you know, for the flu is

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Speaker 1: actually very much more deadly to children. But with covid

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Speaker 1: in particular, you could say, okay, if you're old, then yes,

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Speaker 1: like you should probably get a booster shot, maybe every year,

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Speaker 1: just to make sure that you're going to be okay.

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Speaker 1: Do you have to recommend it? Though? For everybody else

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Speaker 1: this embraces to men COVID zero type thinking, which of

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Speaker 1: course he has the direct financial incentive in pushing an endemic.

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Speaker 1: Model would not push it towards this. It would say

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Speaker 1: the option is available to those who are in a

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Speaker 1: high risk category immunal compromise, et cetera. But for everybody else, Yeah,

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Speaker 1: you're probably going to get some strain of COVID at

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Speaker 1: some point in your life. I think everybody just needs

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Speaker 1: to accept that right now. And the real question is

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Speaker 1: around mitigation and making sure that hospitalization and death is

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Speaker 1: as low as possible. But let me say, yeah, with

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Speaker 1: your point that probably everyone's going to get COVID at

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Speaker 1: some point in their life. If you have been vaccinated,

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Speaker 1: that is a much less risky and potentially deadly scenario

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Speaker 1: for you than if you are unvaccinated. So, look, these

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Speaker 1: companies are not good actors, and the fact that we

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Speaker 1: are dependent on people who have invested financial interest in

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Speaker 1: this is growth. And the incredibly unfortunate side effect of

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Speaker 1: that is, in part it does fuel it fuels true

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Speaker 1: conspiracy theories about how they want to just to make money,

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Speaker 1: but it also fuels false conspiracy theories about the vaccines

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Speaker 1: themselves being nefarious or not working. When we have seen

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Speaker 1: through you know, hundreds of millions of trials around the

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Speaker 1: world at this point there are very safe, minimal risk,

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Speaker 1: and highly effective, especially when it comes to hospitalization and death.

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Speaker 1: And the biggest crime that they are committing is by

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Speaker 1: not making this a public good so that it could

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Speaker 1: be more widely available ultimately to the globe. That is really,

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Speaker 1: I mean, it really is an unconscionable, immoral situation, and

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Speaker 1: I think also gets to this core issue that you know,

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Speaker 1: I've had with our healthcare system for a long time,

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Speaker 1: which is that when profit is at the center, that

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Speaker 1: is the core value rather than health. So this should

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Speaker 1: always you know, from at the beginning, we had all

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Speaker 1: to si, oh, we're in it together in World War

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Speaker 1: two style mobilization effort, etc. Bullshit, bullshit. This should have

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Speaker 1: been a public good. This should have been something where

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Speaker 1: you know, we make it as cheaply available to the

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Speaker 1: world as possible. But that isn't you know, in the

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Speaker 1: interest of Maderna and Sizor and other companies involved, and

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Speaker 1: we less we forget that you the US taxpayer funded

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Speaker 1: and created and helped develop this technology too. So it's

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Speaker 1: not like these companies were white knights who saved us all.

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Speaker 1: They leveraged research that had been publicly funded and ongoing

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Speaker 1: for years, and we gave them big upfront payments. We

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Speaker 1: moved mountains to make sure that the development happened. When

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Speaker 1: the trials weren't, you know, they couldn't find enough diverse

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Speaker 1: participants for the trials, we made sure they had that

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Speaker 1: and the parts they needed, and we went on board

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Speaker 1: and trains to get those parts. I mean, the US

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Speaker 1: taxpayer is responsible for these vaccines and we should be

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Speaker 1: the ones having to say over who it is made

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Speaker 1: available to in the world. Just one more piece, this

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Speaker 1: great reporting from Lefong over at the Intercept. That's just

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Speaker 1: how nefarious these corporate actors are and how we never should,

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Speaker 1: you know, trust them in terms of their interests. Here,

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Speaker 1: Pfizer is now lobbying to thwart whistleblowers from exposing corporate fraud.

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Speaker 1: They're among the big pharma companies trying to block legislation

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Speaker 1: strengthening whistleblowers ability to report this law. And this is

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Speaker 1: really interesting because this is actually a bipartisan effort, let

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Speaker 1: impart by Chuck Grassley, a Republican of course, out of Iowa.

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Speaker 1: And so this law has historically returned sixty seven billion

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Speaker 1: dollars to the government. Whistleblowers have successfully helped uncover wrongdoing

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Speaker 1: by military contractors, banks, and pharmaceutical companies. But this law

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Speaker 1: protecting whistleblowers who are exposing corporate fraud, this has been

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Speaker 1: eroded over time, in particular by a recent Supreme Court decision.

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Speaker 1: And this to me is nuts, but it's effectively what

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Speaker 1: the Supreme Court decision said is that if the company

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Speaker 1: has any ongoing contracts with the government, then we don't

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Speaker 1: believe your fraud claims, because surely the government wouldn't do

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Speaker 1: business with a company that was engaged in fraud. Yeah.

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Speaker 1: I've never met a defense contractor that didn't engage in

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Speaker 1: fraud exactly Like this is insane, but that's what the

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Speaker 1: Supreme Court decided. And something else we've of course talked

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Speaker 1: about on the show, how the main value and main

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Speaker 1: thing that advocates of some of these justices have looked

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Speaker 1: for is that they will be reliable allies for corporate America.

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Speaker 1: So Chuck Grassley and others including Republicans and Democrats, have

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Speaker 1: been trying to update this law. Pfizer and some of

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Speaker 1: their big big pharma allies have been standing with them

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Speaker 1: to lobby against it aggressively. Yeah, and I was just

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Speaker 1: end with, you know, with Matt Stoler. I referenced his tweet,

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Speaker 1: but I wanted to make sure you guys saw it

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Speaker 1: all today. Let's put it up there on the screen

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Speaker 1: where he says, quote new variants from unvaccinated areas that

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Speaker 1: force us to get boosters is literally the business model

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Speaker 1: of big pharma. And I think that, Crystal, that's what

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Speaker 1: you continue to hammer home. And I think that we

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Speaker 1: should all really realize here, which is that a lot

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Speaker 1: of this with the booster shot, its efficacy around the guidance,

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Speaker 1: around the financial interest, and more. I don't think that

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Speaker 1: we're having the correct conversation around it. I think it's

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Speaker 1: both either resetting and putting expectations for people who are

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Speaker 1: really afraid of COVID that this is something that will

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Speaker 1: have to be done population wide over and over again,

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Speaker 1: when that's probably not realistic in terms of a US

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Speaker 1: population wide basis. Two feeding and directly showing that these

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Speaker 1: people want boosters forever for financial interest. And then three,

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Speaker 1: we're the guidance around it changes all the time, and

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Speaker 1: I think just moves us away from where I would

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Speaker 1: say the center of a gravity of American public opinion is,

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Speaker 1: but also just science generally. So look, it's the most

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Speaker 1: honest conversation we could try and have on this. It's

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Speaker 1: a very fraught topic. I bet a lot of people

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Speaker 1: at home are freaked out and are like, I don't

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Speaker 1: know what to do. Should I get one? Should I not?

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Speaker 1: I get messages from people all the time like here's

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Speaker 1: my specific case. By the way, I'm not a doctor,

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Speaker 1: so don't ask me. Please stop asking me whether your

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Speaker 1: boyfriend should get the second JAT or whatever. Look, and

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Speaker 1: it's early days with omicron. We really don't know much there,

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Speaker 1: and I'm gonna wait till you know actual scientists evaluate this,

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Speaker 1: not Maderna's CEO exactly. But I guess to sum it

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Speaker 1: all up, you are correct to think that these pharmaceutical

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Speaker 1: giants are nefarious actors. But their game isn't creating a

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Speaker 1: vaccine that doesn't work and then making you get it.

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Speaker 1: The game is to have the rich world, be the

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Speaker 1: piggy bank, charge premium prices and then allow these variants

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Speaker 1: to circulate, and just as Mats Doller said, in the

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Speaker 1: unvaccinated world, that is how they end up with the

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Speaker 1: largest possible profit. And so that is the that is

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Speaker 1: the angle and the conspiracy that you should be very

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Speaker 1: concerned about, Mary Leria, that's right, speaking of conspiracy and

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Speaker 1: something that we've been tracking here for a long time.

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Speaker 1: I know some people are tired of hearing it, but

430
00:22:54,400 --> 00:22:58,960
Speaker 1: I frankly cannot get over the total and complete transformation

431
00:22:59,040 --> 00:23:04,480
Speaker 1: of doctor Fauci into an outright political actor within the media.

432
00:23:04,560 --> 00:23:07,639
Speaker 1: The transition took like six seven months during the actual

433
00:23:07,680 --> 00:23:10,879
Speaker 1: COVID period of twenty twenty, but is fully complete. And

434
00:23:11,400 --> 00:23:14,800
Speaker 1: watching him in particular grapple with all of the questions

435
00:23:14,840 --> 00:23:17,399
Speaker 1: around his own role and gain a function research in

436
00:23:17,440 --> 00:23:20,520
Speaker 1: the origin of COVID in the first place, all came

437
00:23:20,560 --> 00:23:23,520
Speaker 1: to four over the weekend. This was basically completely ignored

438
00:23:23,760 --> 00:23:25,320
Speaker 1: by the media, and I guess I have to give

439
00:23:25,440 --> 00:23:27,800
Speaker 1: CBS some credit because they pressed him on it a

440
00:23:27,840 --> 00:23:29,920
Speaker 1: little bit. So let's put this up there on the screen.

441
00:23:29,920 --> 00:23:32,080
Speaker 1: Actually tweeted it out over the weekend. But there's a

442
00:23:32,080 --> 00:23:34,840
Speaker 1: section of this transcript, which is very important. Margaret Brennan

443
00:23:34,880 --> 00:23:39,280
Speaker 1: to faced the Nation asks doctor Fauci, quote, Beijing acknowledges,

444
00:23:39,359 --> 00:23:42,200
Speaker 1: now they don't think that it originated in a market.

445
00:23:42,240 --> 00:23:45,840
Speaker 1: She's referencing COVID. He says, quote, well, it may not

446
00:23:45,920 --> 00:23:49,000
Speaker 1: have originated in the market, but it certainly could have.

447
00:23:49,359 --> 00:23:51,600
Speaker 1: I mean, I don't think that they admitted it that

448
00:23:51,640 --> 00:23:54,040
Speaker 1: it didn't originate. I think they're saying they don't know

449
00:23:54,040 --> 00:23:56,880
Speaker 1: how it originated. And so she continues to press him

450
00:23:57,280 --> 00:24:01,040
Speaker 1: even more within the transcript, Crystal, and he continues to

451
00:24:01,080 --> 00:24:04,520
Speaker 1: bring it back to the wet market theory four or

452
00:24:04,640 --> 00:24:08,440
Speaker 1: five different times. And this is remarkable to me because

453
00:24:08,880 --> 00:24:12,320
Speaker 1: the amount of evidence currently on the wet market wet

454
00:24:12,320 --> 00:24:14,840
Speaker 1: market hypothesis is you would have to believe that a

455
00:24:14,920 --> 00:24:19,159
Speaker 1: Liotian bat one thousand miles away somehow was able to

456
00:24:19,280 --> 00:24:22,199
Speaker 1: come to Wuhan and then it was you know, like

457
00:24:22,320 --> 00:24:25,879
Speaker 1: maybe eaten or bit what was it bit a panglin

458
00:24:26,240 --> 00:24:30,000
Speaker 1: and then that panglin was eaten by a human or

459
00:24:31,000 --> 00:24:33,480
Speaker 1: what's more likely, What did we just learn from documents

460
00:24:33,560 --> 00:24:37,280
Speaker 1: released literally two weeks ago, which is that that specific

461
00:24:37,400 --> 00:24:40,959
Speaker 1: Layotan bat which had a virus, which was ninety eight

462
00:24:41,040 --> 00:24:44,760
Speaker 1: percent genetically similar to the current COVID nineteen was actually

463
00:24:44,760 --> 00:24:47,760
Speaker 1: being specifically studied and used in experiments at the Wuhan

464
00:24:47,800 --> 00:24:51,040
Speaker 1: Institute of Virology. You tell me which one is a

465
00:24:51,080 --> 00:24:54,560
Speaker 1: little bit more likely. Once again, if that the latter

466
00:24:54,640 --> 00:24:57,439
Speaker 1: one about the Wuhan Institute, the lab leak and all

467
00:24:57,440 --> 00:25:00,840
Speaker 1: of that is true, then it directly implicates doctor Fauci.

468
00:25:00,920 --> 00:25:02,520
Speaker 1: But you and I were talking. I mean, you read

469
00:25:02,560 --> 00:25:05,760
Speaker 1: this transcript. It's bonkers. I mean, it's like, actually crazy,

470
00:25:05,840 --> 00:25:08,080
Speaker 1: it actually is. Because I was a little bit like,

471
00:25:08,119 --> 00:25:10,040
Speaker 1: I just read that one part and I was like, okay,

472
00:25:10,080 --> 00:25:12,280
Speaker 1: But then you go on and you read the whole thing.

473
00:25:12,600 --> 00:25:15,719
Speaker 1: The thing that stood out to me is she asks

474
00:25:15,760 --> 00:25:19,719
Speaker 1: about do we need to further regulate gain a function research,

475
00:25:19,840 --> 00:25:22,560
Speaker 1: and he's like, no, we already did that. We're good

476
00:25:22,560 --> 00:25:25,280
Speaker 1: to go. No problem there. She reversed the regulation on

477
00:25:25,560 --> 00:25:28,639
Speaker 1: and then then she asked him if we need to

478
00:25:28,720 --> 00:25:31,120
Speaker 1: further regulate wet markets and he's like, oh, one hundred

479
00:25:31,119 --> 00:25:33,840
Speaker 1: percent right. So hold on a second. So the one

480
00:25:33,920 --> 00:25:36,760
Speaker 1: with no with no evidence behind it that needs to

481
00:25:36,760 --> 00:25:38,760
Speaker 1: be regulated, the one with a ton of evidence behind

482
00:25:38,800 --> 00:25:41,640
Speaker 1: it and actually with a bunch of US government dollars

483
00:25:41,880 --> 00:25:46,520
Speaker 1: that he that he contributes and controls. Oh, that stuff

484
00:25:46,800 --> 00:25:48,840
Speaker 1: needs to be regulated, right, Well, in the other thing,

485
00:25:48,800 --> 00:25:51,240
Speaker 1: We'm sorry, not regulated. The other thing that reminded me

486
00:25:51,359 --> 00:25:53,760
Speaker 1: of a point we have been making for a long

487
00:25:53,800 --> 00:25:56,560
Speaker 1: time is, you know, the reason that you weren't allowed

488
00:25:56,600 --> 00:25:59,920
Speaker 1: to talk about the lab leak hypothesis originally was because

489
00:26:00,040 --> 00:26:02,919
Speaker 1: it was supposedly racist to talk about, right. That was

490
00:26:02,960 --> 00:26:06,879
Speaker 1: the That was the trump card, no pun intended used

491
00:26:06,880 --> 00:26:10,240
Speaker 1: to shut down any discussion in the press about the

492
00:26:10,320 --> 00:26:13,480
Speaker 1: lably hypothesis. People are being censored on different social media

493
00:26:13,480 --> 00:26:16,119
Speaker 1: platforms or even discussing it because it was quote unquote racist.

494
00:26:16,560 --> 00:26:19,119
Speaker 1: But he goes on to talk about these wet markets.

495
00:26:19,160 --> 00:26:21,840
Speaker 1: I mean, it's to me, it's a much more sort

496
00:26:21,880 --> 00:26:26,040
Speaker 1: of caricaturish and potentially racist commentary that he's making there

497
00:26:26,080 --> 00:26:31,520
Speaker 1: about like all these weird animals it markets, And yeah,

498
00:26:31,600 --> 00:26:34,720
Speaker 1: I mean that to me was a lot more problematic

499
00:26:34,920 --> 00:26:39,440
Speaker 1: than the idea that as is the case oftentimes. I mean,

500
00:26:39,560 --> 00:26:41,960
Speaker 1: this would not be even close to the first time

501
00:26:42,000 --> 00:26:45,159
Speaker 1: that something escaped out of a lab, Like, how is

502
00:26:45,200 --> 00:26:48,600
Speaker 1: that racist? That was just so it reminded me of

503
00:26:48,640 --> 00:26:52,439
Speaker 1: that as well. But he really does, repeatedly throughout this

504
00:26:52,600 --> 00:26:57,120
Speaker 1: interview go back to his conviction that it still may

505
00:26:57,160 --> 00:26:59,879
Speaker 1: have come out of the wet market and points to

506
00:26:59,880 --> 00:27:02,359
Speaker 1: the fact that and I think that this is true,

507
00:27:02,720 --> 00:27:05,479
Speaker 1: that they made sure to like clean out that scrub

508
00:27:05,520 --> 00:27:07,920
Speaker 1: the wet market and remove all the animals and everything

509
00:27:08,280 --> 00:27:11,320
Speaker 1: early on, he insinuates that's, you know, sort of part

510
00:27:11,320 --> 00:27:13,600
Speaker 1: of a cover it. But they also did weird things

511
00:27:13,720 --> 00:27:16,200
Speaker 1: at the lab. They scrubbed the server there in September

512
00:27:16,240 --> 00:27:18,840
Speaker 1: two nine, they changed the air conditioning unit and all

513
00:27:18,840 --> 00:27:21,600
Speaker 1: that stuff. That part he doesn't seem to take as

514
00:27:21,680 --> 00:27:24,479
Speaker 1: evidence of a cover up, even though it potentially is.

515
00:27:24,560 --> 00:27:27,280
Speaker 1: It's truly nuts. And look, as I said it over again,

516
00:27:27,560 --> 00:27:31,120
Speaker 1: even the Chinese don't try and push the lab leak theory, sorry,

517
00:27:31,160 --> 00:27:34,040
Speaker 1: the wet market theory. They're like their theory is basically like, oh,

518
00:27:34,080 --> 00:27:35,919
Speaker 1: it was on some goods and you know, it like

519
00:27:35,960 --> 00:27:38,359
Speaker 1: made its way here and that's kind of how it happened.

520
00:27:38,359 --> 00:27:40,080
Speaker 1: And by the way, just stop asking a lot of questions.

521
00:27:40,119 --> 00:27:42,359
Speaker 1: If you're in China, yeah, you know, just just zip it.

522
00:27:42,400 --> 00:27:43,960
Speaker 1: And if you do, if you don't sip it, yeah

523
00:27:44,000 --> 00:27:46,760
Speaker 1: you're going to prison. That's that's what they've been doing

524
00:27:46,960 --> 00:27:49,600
Speaker 1: over there in May of twenty twenty as recently they

525
00:27:49,600 --> 00:27:52,239
Speaker 1: were not even standing by the wet market theory. So

526
00:27:52,560 --> 00:27:55,199
Speaker 1: that just goes to show you there is not a

527
00:27:55,359 --> 00:28:00,359
Speaker 1: single realistic iota of evidence behind the wet markets specific theory.

528
00:28:00,359 --> 00:28:02,879
Speaker 1: I'm not saying zoonotic origin. I'm saying the wet market

529
00:28:02,920 --> 00:28:06,680
Speaker 1: specific theory. There's a ton more circumstantial on the lab week.

530
00:28:07,040 --> 00:28:10,040
Speaker 1: Guess which one Fauci is contributing to. And really I

531
00:28:10,080 --> 00:28:11,760
Speaker 1: found this next clip that we're about to show you,

532
00:28:11,880 --> 00:28:14,760
Speaker 1: I really found it disgusting. Look. I don't like Ted Cruz.

533
00:28:14,800 --> 00:28:17,680
Speaker 1: I don't particularly love Rand Paul either. Okay, they're both

534
00:28:17,760 --> 00:28:21,959
Speaker 1: very partisan actors, etc. But they are elected United States senators.

535
00:28:22,320 --> 00:28:25,760
Speaker 1: Doctor Fauci is the government official and specifically supposed to

536
00:28:25,800 --> 00:28:28,040
Speaker 1: be a nonpartisan and at the very least try to

537
00:28:28,080 --> 00:28:31,159
Speaker 1: have some trust with the American people. Now, when Margaret

538
00:28:31,160 --> 00:28:34,200
Speaker 1: Brennan presses him on what do you think about you know,

539
00:28:34,440 --> 00:28:37,720
Speaker 1: the quote unquote attacks by Rand Paul or Ted Cruz

540
00:28:37,720 --> 00:28:40,880
Speaker 1: says you should be prosecuted. Look at how much of

541
00:28:40,920 --> 00:28:43,680
Speaker 1: like a Rachel mattout viewer that this guy turns into.

542
00:28:44,000 --> 00:28:46,800
Speaker 1: Just take a listen to this. So anybody who spends

543
00:28:47,040 --> 00:28:50,680
Speaker 1: lies and threatens and all that theater that goes on

544
00:28:51,560 --> 00:28:55,120
Speaker 1: with some of the investigations and the congressional committees and

545
00:28:55,160 --> 00:28:59,640
Speaker 1: the Rand polls and all that other nonsense, that's noise, Margaret,

546
00:29:00,080 --> 00:29:03,600
Speaker 1: that's noise. I know what my job is. Senator Cruz

547
00:29:03,720 --> 00:29:08,400
Speaker 1: told the attorney general you should be prosecuted. Yeah, I

548
00:29:08,520 --> 00:29:13,360
Speaker 1: have to laugh at that I should be prosecuted. What

549
00:29:13,480 --> 00:29:18,160
Speaker 1: happened on January sixth? Senator, do you think that this

550
00:29:18,280 --> 00:29:22,880
Speaker 1: is about making you a scapegoat to deflect course President Trump.

551
00:29:23,040 --> 00:29:26,080
Speaker 1: Of course you have to be asleep not to figure

552
00:29:26,080 --> 00:29:28,840
Speaker 1: that one out. Well, there are a lot of Republican

553
00:29:28,920 --> 00:29:33,920
Speaker 1: senators taking aim at this. I mean, that's okay. I'm

554
00:29:33,920 --> 00:29:36,120
Speaker 1: just going to do my job and I'm going to

555
00:29:36,120 --> 00:29:38,600
Speaker 1: be saving lives, and they're going to be lying. It

556
00:29:38,720 --> 00:29:43,240
Speaker 1: seems another layer of danger to play politics around matters

557
00:29:43,280 --> 00:29:46,280
Speaker 1: of life and death right exactly exactly, And to me,

558
00:29:47,360 --> 00:29:51,720
Speaker 1: that's unbelievably bad because all I want to do is

559
00:29:51,760 --> 00:29:55,400
Speaker 1: save people's lives. And I mean, anybody who's looking at

560
00:29:55,440 --> 00:30:00,120
Speaker 1: this carefully realizes that there's a distinct anti scigence in

561
00:30:00,800 --> 00:30:04,520
Speaker 1: flavor to this so if they get up and criticize science,

562
00:30:05,000 --> 00:30:07,719
Speaker 1: nobody's gonna know what they're talking about. But if they

563
00:30:07,760 --> 00:30:11,280
Speaker 1: get up and really aim their bullets at Tony Fauci, well,

564
00:30:11,280 --> 00:30:13,760
Speaker 1: people could recognize there as a person there, so it's

565
00:30:13,800 --> 00:30:18,400
Speaker 1: easy to criticize. But they're really criticizing science because I

566
00:30:18,520 --> 00:30:24,520
Speaker 1: represent science. That's dangerous. Oh okay, he represents science. It's

567
00:30:24,840 --> 00:30:27,760
Speaker 1: the ego of this man is unbelievable. Look, I know,

568
00:30:28,000 --> 00:30:31,240
Speaker 1: I know it sounds partisan, but anybody who is able

569
00:30:31,280 --> 00:30:32,760
Speaker 1: to look at this, you don't even have to like

570
00:30:32,800 --> 00:30:37,080
Speaker 1: Ted Cruz, Rand Paul or whatever. You cannot declare yourself science.

571
00:30:37,160 --> 00:30:40,040
Speaker 1: And what did we just point to preceding this is

572
00:30:40,200 --> 00:30:44,960
Speaker 1: ignoring actual facts and evidence and pushing a hypothesis because

573
00:30:45,000 --> 00:30:47,560
Speaker 1: you have a direct interest in making sure that one

574
00:30:47,640 --> 00:30:51,400
Speaker 1: is true and one is not true. It's just completely crazy.

575
00:30:51,440 --> 00:30:53,920
Speaker 1: And this is the man who runs a lot of

576
00:30:53,960 --> 00:30:56,760
Speaker 1: our policy. Yeah, that's the thing is, like you have

577
00:30:56,840 --> 00:30:59,920
Speaker 1: to please, like I'm begging the wine mobs of America,

578
00:31:00,120 --> 00:31:03,239
Speaker 1: like wake up and see for what it is. You

579
00:31:03,280 --> 00:31:07,280
Speaker 1: cannot behave this way. I don't really care that much

580
00:31:07,280 --> 00:31:09,160
Speaker 1: about the Ted Cruise comment, to be honest with you,

581
00:31:09,200 --> 00:31:13,600
Speaker 1: but the I am science. Thing is just so profoundly

582
00:31:14,440 --> 00:31:18,520
Speaker 1: wrong and unhelpful. I mean, just as much as Ted

583
00:31:18,560 --> 00:31:22,360
Speaker 1: Cruz and Rand Paul, any sort of conspiracy theorist minded person,

584
00:31:22,480 --> 00:31:24,760
Speaker 1: let's put them aside, would want to turn him into

585
00:31:25,120 --> 00:31:27,520
Speaker 1: into science, because then you can put if you can

586
00:31:27,560 --> 00:31:30,520
Speaker 1: poke holes in a fallible human being, then well, I mean,

587
00:31:30,880 --> 00:31:33,360
Speaker 1: that is a really bad state of affairs for you

588
00:31:33,400 --> 00:31:35,640
Speaker 1: to then lean into and say, yeah, you're right, I

589
00:31:35,680 --> 00:31:38,200
Speaker 1: am science, and when you attack me, you're attacking science,

590
00:31:38,520 --> 00:31:41,960
Speaker 1: when we know provably that he has been an incredibly

591
00:31:42,000 --> 00:31:45,560
Speaker 1: fallible human being who was wrong about mass to start with,

592
00:31:45,840 --> 00:31:50,080
Speaker 1: and you know, and wrong because he was just lying,

593
00:31:50,280 --> 00:31:52,600
Speaker 1: not because he had bad information and came to America,

594
00:31:52,640 --> 00:31:55,160
Speaker 1: oh now we know more. No, because he wanted to

595
00:31:55,320 --> 00:31:58,840
Speaker 1: make sure that frontline healthcare workers had the ppe they needed,

596
00:31:58,840 --> 00:32:00,400
Speaker 1: which is a noble goal, but you don't have to

597
00:32:00,400 --> 00:32:03,280
Speaker 1: lie to the American people about it. That was one.

598
00:32:03,600 --> 00:32:06,160
Speaker 1: Of course, we know the changing narrative on herd immunity

599
00:32:06,320 --> 00:32:08,760
Speaker 1: and how he changed his numbers on what percent of

600
00:32:08,760 --> 00:32:11,120
Speaker 1: the population we need to have immunity before you could

601
00:32:11,160 --> 00:32:13,840
Speaker 1: consider it having heard immunity, and he admitted that he

602
00:32:13,880 --> 00:32:16,320
Speaker 1: did that based on what he thought the public could handle.

603
00:32:16,880 --> 00:32:19,800
Speaker 1: At that point, of course, we know he's got a

604
00:32:19,880 --> 00:32:24,920
Speaker 1: direct personal interest in pushing towards the zoonotic origin thesis

605
00:32:25,040 --> 00:32:27,760
Speaker 1: or apparently holding on for dear life to the wet

606
00:32:27,760 --> 00:32:32,480
Speaker 1: market thesis versus the Labe hypothesis. So if you put

607
00:32:32,520 --> 00:32:35,840
Speaker 1: yourself in that position, if you lean into that saying yeah,

608
00:32:35,840 --> 00:32:39,040
Speaker 1: you're right, I am science, then he's correct that it

609
00:32:39,080 --> 00:32:44,840
Speaker 1: makes it easy to sort of undermine scientific consensus writ large,

610
00:32:44,880 --> 00:32:48,720
Speaker 1: because every human being is going to ultimately be fallible.

611
00:32:48,760 --> 00:32:52,880
Speaker 1: So that's why this is so bad and damaging and

612
00:32:52,960 --> 00:32:57,800
Speaker 1: also just incredibly incredibly egotistical to be like, if you're

613
00:32:57,840 --> 00:33:01,440
Speaker 1: attacking me, you are actually attacked science when you know

614
00:33:01,720 --> 00:33:05,000
Speaker 1: there are a lot a lot of bad faith attacks

615
00:33:05,040 --> 00:33:08,480
Speaker 1: on doctor Fauci. There's a lot of total conspiracy and

616
00:33:08,520 --> 00:33:12,560
Speaker 1: insanity around doctor Fauci, but there are also good faith

617
00:33:12,800 --> 00:33:18,080
Speaker 1: critiques that are about him not adhering to the science,

618
00:33:18,480 --> 00:33:21,480
Speaker 1: not following the data, and just being upfront with people

619
00:33:21,480 --> 00:33:24,440
Speaker 1: and acting more like a spin doctor and a politician

620
00:33:24,720 --> 00:33:26,640
Speaker 1: than a public health official, which is what he is

621
00:33:26,680 --> 00:33:28,680
Speaker 1: doing and is not what he was asked to do.

622
00:33:28,920 --> 00:33:30,760
Speaker 1: It's a betrayal of the public trust in my opinion,

623
00:33:30,840 --> 00:33:35,480
Speaker 1: Actually we're a lot worse off because of it. Let's

624
00:33:35,480 --> 00:33:39,160
Speaker 1: get to the next segment. This was set the Internet

625
00:33:39,400 --> 00:33:43,640
Speaker 1: on fire, specifically Twitter yesterday the big headline news Jack

626
00:33:43,720 --> 00:33:46,840
Speaker 1: Dorsey is leaving Twitter. So let's go ahead and put

627
00:33:46,880 --> 00:33:49,280
Speaker 1: this up there on the screen. He wrote a very

628
00:33:49,320 --> 00:33:51,640
Speaker 1: long goodbye email. I'm not going to read it all

629
00:33:51,680 --> 00:33:54,120
Speaker 1: to you. It's basically, after sixteen years of having a

630
00:33:54,200 --> 00:33:57,280
Speaker 1: role in a co founder, CEO, etc. Of this company,

631
00:33:57,320 --> 00:33:59,760
Speaker 1: I have decided it's finally time for me to leave.

632
00:34:00,360 --> 00:34:02,760
Speaker 1: What he gets to and the most important part is

633
00:34:02,800 --> 00:34:06,960
Speaker 1: he says that he will appoint a new CEO whose

634
00:34:07,040 --> 00:34:10,080
Speaker 1: name is Paragu agar Wah. So a lot of questions

635
00:34:10,080 --> 00:34:14,000
Speaker 1: are currently a rising. What does Parague agar Wall believe

636
00:34:14,040 --> 00:34:16,839
Speaker 1: about Twitter? Who is Parague Agarwalal? Okay, so let's get

637
00:34:16,840 --> 00:34:19,920
Speaker 1: a little bit into his background. Paragu he started as

638
00:34:19,960 --> 00:34:22,760
Speaker 1: an engineer at the company. He is a longtime fixture

639
00:34:22,760 --> 00:34:25,640
Speaker 1: within the engineering community of Silicon Valley. From what I

640
00:34:25,640 --> 00:34:27,879
Speaker 1: have heard, he's actually pretty well liked once again within

641
00:34:27,920 --> 00:34:30,920
Speaker 1: the engineering community, and he was a CTO of Twitter,

642
00:34:30,960 --> 00:34:36,040
Speaker 1: the chief technology officer. Here's the problem, though, Paragu is

643
00:34:36,080 --> 00:34:38,920
Speaker 1: an engineering type who is now the CEO of a

644
00:34:38,960 --> 00:34:43,240
Speaker 1: company who doesn't really have engineering problems. This company's problem

645
00:34:43,280 --> 00:34:47,520
Speaker 1: is that they have big socio metapolitical questions to answer.

646
00:34:47,880 --> 00:34:51,080
Speaker 1: What does free speech mean? What does regular Should we

647
00:34:51,120 --> 00:34:54,480
Speaker 1: amplify this or not? Our business model says one thing,

648
00:34:54,800 --> 00:34:58,600
Speaker 1: our politics say another. Democracy is another thing. All of

649
00:34:58,640 --> 00:35:02,239
Speaker 1: elites are on our platform. Regulating this public sphere is

650
00:35:02,280 --> 00:35:05,000
Speaker 1: really difficult to do that. You actually need to have

651
00:35:05,040 --> 00:35:08,040
Speaker 1: some principles. Now here's the thing about Jack Dorsey. I'm

652
00:35:08,040 --> 00:35:09,640
Speaker 1: not going to say the guy was the best CEO

653
00:35:09,960 --> 00:35:11,960
Speaker 1: in the world, but at the very least, and I'd

654
00:35:11,960 --> 00:35:14,880
Speaker 1: say this on a personal level, personal level, he was

655
00:35:14,920 --> 00:35:17,919
Speaker 1: actually kind of committed to free speech. As in, look,

656
00:35:17,920 --> 00:35:20,239
Speaker 1: I get it, Evan Trump from the platform, New York

657
00:35:20,320 --> 00:35:22,279
Speaker 1: Post all of that. If anything, his crime is being

658
00:35:22,320 --> 00:35:24,880
Speaker 1: negligent and only running the company for like, you know,

659
00:35:24,920 --> 00:35:27,320
Speaker 1: ten percent of his time while he's co CEO. Square

660
00:35:27,840 --> 00:35:30,200
Speaker 1: that being said, and this isn't just me Glenn Greenwald

661
00:35:30,239 --> 00:35:32,600
Speaker 1: and others who have been in dialogue with him, he

662
00:35:32,680 --> 00:35:35,919
Speaker 1: personally was committed to free speech, trying to very big

663
00:35:35,960 --> 00:35:39,640
Speaker 1: believer in bitcoin decentralization and the inability of someone like

664
00:35:39,719 --> 00:35:43,000
Speaker 1: himself in order to run the public square, launching Blue Sky,

665
00:35:43,080 --> 00:35:45,640
Speaker 1: which was you know, an alternative which would have been

666
00:35:45,680 --> 00:35:48,640
Speaker 1: decentralized and all of that and not would have allowed deplatforming.

667
00:35:48,760 --> 00:35:50,520
Speaker 1: What I'm saying is is he was not perfect, and

668
00:35:50,560 --> 00:35:52,799
Speaker 1: the company that he built ultimately did become a very

669
00:35:52,840 --> 00:35:55,960
Speaker 1: censorious place, but that he himself at least did not

670
00:35:56,000 --> 00:35:59,160
Speaker 1: abide by that. This new guy is actually way worse

671
00:35:59,280 --> 00:36:02,520
Speaker 1: and is much more more of a reflection of exactly

672
00:36:02,560 --> 00:36:05,840
Speaker 1: that censorious lean behind the Twitter staff. And this is

673
00:36:05,840 --> 00:36:09,000
Speaker 1: an interview that he gave just last year after the election.

674
00:36:09,320 --> 00:36:12,319
Speaker 1: And I also want to say this pre January sixth,

675
00:36:12,360 --> 00:36:15,319
Speaker 1: That's why it's so important, pre January sixth, in how

676
00:36:15,400 --> 00:36:19,560
Speaker 1: paragog Arwal, the new CEO, was talking as recently about

677
00:36:19,840 --> 00:36:22,080
Speaker 1: the way that they would be regulating content. So let's

678
00:36:22,120 --> 00:36:23,799
Speaker 1: put this up there on the screen. It was an

679
00:36:23,800 --> 00:36:29,479
Speaker 1: interview with MIT Technology Review. Quote. Our role is not

680
00:36:29,560 --> 00:36:33,600
Speaker 1: to be bound by the First Amendment, okay, but our

681
00:36:33,680 --> 00:36:38,160
Speaker 1: role is to serve a healthy public conversation, and our

682
00:36:38,280 --> 00:36:42,200
Speaker 1: moves are reflective of things that we believe lead to

683
00:36:42,239 --> 00:36:46,239
Speaker 1: a healthier public conversation. Now that should scare the hell

684
00:36:46,280 --> 00:36:50,120
Speaker 1: out of you. Why Because he is explicitly casting aside

685
00:36:50,400 --> 00:36:53,520
Speaker 1: the First Amendment in favor of what he and the

686
00:36:53,560 --> 00:36:57,879
Speaker 1: team at Twitter decides is a healthy public conversation. Now,

687
00:36:57,920 --> 00:37:00,799
Speaker 1: as we found out, this team does not believe that

688
00:37:00,800 --> 00:37:03,520
Speaker 1: the Hunter Biden laptop story at the time would have

689
00:37:03,560 --> 00:37:07,640
Speaker 1: added to a quote healthy public conversation. And whenever you

690
00:37:07,719 --> 00:37:10,600
Speaker 1: say things like we're not bound by First Amendment, you're

691
00:37:10,640 --> 00:37:14,120
Speaker 1: also explicitly saying we're not bound by freedom of the press.

692
00:37:14,320 --> 00:37:16,759
Speaker 1: We are not bound by the ability for people to

693
00:37:16,840 --> 00:37:21,320
Speaker 1: express themselves and have a healthy debate within a public sphere. Instead, Crystal,

694
00:37:21,480 --> 00:37:24,240
Speaker 1: what they are pointing to is that we don't really

695
00:37:24,280 --> 00:37:27,680
Speaker 1: believe in being bound by this arcade idea. They are

696
00:37:27,719 --> 00:37:32,200
Speaker 1: almost imbuing themselves, he specifically with godlike powers and saying, no,

697
00:37:32,280 --> 00:37:35,920
Speaker 1: it's our job to create a healthy public conversation. And

698
00:37:36,040 --> 00:37:38,480
Speaker 1: by doing that, they're going to pick and choose what

699
00:37:38,560 --> 00:37:41,480
Speaker 1: gets amplified, what gets not, what gets censored, what doesn't.

700
00:37:42,040 --> 00:37:45,040
Speaker 1: And I would point out that agar Wall himself has

701
00:37:45,239 --> 00:37:48,640
Speaker 1: you know, he's had some problematic tweets that he's had

702
00:37:48,640 --> 00:37:50,920
Speaker 1: in the past, and you know, oh, oh yeah, it's

703
00:37:50,920 --> 00:37:54,760
Speaker 1: actually kind of hilarious because he didn't go and scrub

704
00:37:54,960 --> 00:37:57,840
Speaker 1: all the tweets, which it's like, dude, did you not

705
00:37:58,000 --> 00:38:00,640
Speaker 1: know that you were going to be the CEO of Twitter?

706
00:38:00,760 --> 00:38:03,000
Speaker 1: I mean I'm assuming that that was going to be

707
00:38:03,080 --> 00:38:04,920
Speaker 1: one that you were going to go ahead and look to.

708
00:38:05,480 --> 00:38:08,480
Speaker 1: And yeah, so he didn't. He didn't go ahead and

709
00:38:08,719 --> 00:38:11,480
Speaker 1: scrub all of his tweets. In twenty ten, he tweeted quote,

710
00:38:11,680 --> 00:38:14,320
Speaker 1: if they're not going to make a distinction between Muslims

711
00:38:14,360 --> 00:38:17,480
Speaker 1: and extremists, then why should I distinguish between white people

712
00:38:17,560 --> 00:38:22,440
Speaker 1: and racists? Wait a little bit of a problem. Now,

713
00:38:22,719 --> 00:38:26,520
Speaker 1: I'll give you. I'll give you the context, because he

714
00:38:26,560 --> 00:38:31,839
Speaker 1: claims the context he was quoting as if Manvi from

715
00:38:31,920 --> 00:38:36,000
Speaker 1: The Daily Show. Look, I mean you see you Twitter conversation?

716
00:38:36,080 --> 00:38:39,040
Speaker 1: Is that healthy conversation? Is that a healthy public square?

717
00:38:39,440 --> 00:38:41,759
Speaker 1: I mean, look, the other thing that's funny is if

718
00:38:41,800 --> 00:38:44,600
Speaker 1: you this interview was actually a very good interview. Yes,

719
00:38:44,719 --> 00:38:49,160
Speaker 1: they asked him a lot of really salient questions, and

720
00:38:49,239 --> 00:38:52,480
Speaker 1: part of it is they push him on, well, okay,

721
00:38:52,520 --> 00:38:55,239
Speaker 1: what are your metrics for a healthy conversation? Like, give

722
00:38:55,239 --> 00:38:58,160
Speaker 1: me some specifics here about what are you looking for?

723
00:38:58,320 --> 00:38:59,960
Speaker 1: What are the metrics? How are you going to do

724
00:39:00,239 --> 00:39:02,799
Speaker 1: with it? What are your strategies and it's just all

725
00:39:02,920 --> 00:39:09,080
Speaker 1: this fuzzy, amorphous, Silicon Valley speak that ultimately means nothing.

726
00:39:09,440 --> 00:39:11,719
Speaker 1: And he goes on after he says that thing about

727
00:39:11,719 --> 00:39:13,400
Speaker 1: our role is not to be bound by the First Amendment.

728
00:39:13,760 --> 00:39:17,120
Speaker 1: He said, the kinds of things that we do about

729
00:39:17,160 --> 00:39:21,319
Speaker 1: this is focus less on thinking about free speech but

730
00:39:21,520 --> 00:39:25,200
Speaker 1: thinking about how the times have changed. One of the

731
00:39:25,280 --> 00:39:27,719
Speaker 1: changes today that we see is speech is easy on

732
00:39:27,760 --> 00:39:30,279
Speaker 1: the internet, most people can speak. Where our role is

733
00:39:30,320 --> 00:39:34,120
Speaker 1: particularly emphasized is who can be heard. The scarce commodity today.

734
00:39:34,280 --> 00:39:36,839
Speaker 1: Commodity today is attention. There's a lot of content out there,

735
00:39:36,840 --> 00:39:38,319
Speaker 1: a lot of tweets out there, and not all of

736
00:39:38,320 --> 00:39:41,239
Speaker 1: it gets attention, so subset of it gets attention. And

737
00:39:41,320 --> 00:39:45,760
Speaker 1: so increasingly our role is moving towards how we recommend content,

738
00:39:46,360 --> 00:39:48,879
Speaker 1: and that sort of is a struggle that we're working

739
00:39:48,960 --> 00:39:51,200
Speaker 1: through in terms of how we make sure these recommendation

740
00:39:51,239 --> 00:39:54,279
Speaker 1: systems that we're building, how we direct people's attention is

741
00:39:54,360 --> 00:39:58,360
Speaker 1: leading to a healthy public conversation that is most participatory.

742
00:39:58,840 --> 00:40:02,399
Speaker 1: So if you unpack that, what he's saying is, look,

743
00:40:02,440 --> 00:40:06,040
Speaker 1: first of all, First Amendment, whatever times have change, right,

744
00:40:06,360 --> 00:40:10,240
Speaker 1: and so what we're focused on is what gets heard,

745
00:40:10,960 --> 00:40:13,840
Speaker 1: so that gives you a little bit of insight into

746
00:40:13,960 --> 00:40:17,120
Speaker 1: what some of their strategies probably already are and will

747
00:40:17,160 --> 00:40:21,160
Speaker 1: be going forward. Which is rather than just blanket like

748
00:40:21,239 --> 00:40:24,120
Speaker 1: sort of you know, censorship or banning or pushing off

749
00:40:24,120 --> 00:40:25,960
Speaker 1: the platform, which they may do, they'll do some of

750
00:40:26,000 --> 00:40:30,200
Speaker 1: as well, it's more suppressing, it's a little more under

751
00:40:30,239 --> 00:40:33,280
Speaker 1: the radar, so making sure that the things that actually

752
00:40:33,280 --> 00:40:35,480
Speaker 1: get promoted and are likely to show up in your

753
00:40:35,520 --> 00:40:39,520
Speaker 1: feed are the things that they deem to be healthy conversation,

754
00:40:40,480 --> 00:40:45,160
Speaker 1: which is again why at the very least these companies

755
00:40:45,200 --> 00:40:49,160
Speaker 1: should be forced to disclose what their algorithms are, what

756
00:40:49,200 --> 00:40:53,680
Speaker 1: their procedures are, because otherwise you're flying blind. You may

757
00:40:53,800 --> 00:40:56,120
Speaker 1: feel like I don't think people are seeing this tweet.

758
00:40:56,160 --> 00:40:58,040
Speaker 1: I don't feel like people are able to search for

759
00:40:58,360 --> 00:41:00,480
Speaker 1: my content and see what I'm doing here, and not

760
00:41:00,560 --> 00:41:03,000
Speaker 1: just on Twitter but YouTube and everywhere else. Yes, which

761
00:41:03,000 --> 00:41:04,719
Speaker 1: we deal with all the time. We deal with all

762
00:41:04,760 --> 00:41:07,319
Speaker 1: the time where you feel like you're going crazy because

763
00:41:07,320 --> 00:41:09,440
Speaker 1: you're like there's something going on here, but you can

764
00:41:09,520 --> 00:41:13,120
Speaker 1: never prove it because all of this stuff is completely opaque.

765
00:41:13,200 --> 00:41:17,200
Speaker 1: You can never learn what's actually going on behind the scenes.

766
00:41:17,560 --> 00:41:20,520
Speaker 1: And so I think what this really points to is

767
00:41:20,880 --> 00:41:23,960
Speaker 1: we have got to know how they are making these

768
00:41:24,040 --> 00:41:28,319
Speaker 1: godlike decisions about what a healthy conversation is and what

769
00:41:28,480 --> 00:41:32,120
Speaker 1: is in sinots. Obviously they don't feel bound quote our

770
00:41:32,239 --> 00:41:35,160
Speaker 1: role is not to be bound by the First Amendment. Okay,

771
00:41:35,360 --> 00:41:38,080
Speaker 1: so what are you bound by and how exactly are

772
00:41:38,120 --> 00:41:40,359
Speaker 1: you making those determinis what you're bound by is the

773
00:41:40,400 --> 00:41:42,919
Speaker 1: mob of your employees, which they have cave to over

774
00:41:42,960 --> 00:41:46,200
Speaker 1: and over again. And Jack, I mean in some limited instances,

775
00:41:46,239 --> 00:41:48,600
Speaker 1: like I'm saying, was pushing back in this case, I

776
00:41:48,600 --> 00:41:51,040
Speaker 1: don't expect that at all. Look, I have talked to

777
00:41:51,080 --> 00:41:54,920
Speaker 1: some of these Silicon Valley engineering types. In my general opinion,

778
00:41:54,920 --> 00:41:57,000
Speaker 1: these people don't have a damn clue. Okay, they have

779
00:41:57,080 --> 00:42:01,239
Speaker 1: no idea because they engineered this amazing technology, but they

780
00:42:01,239 --> 00:42:05,320
Speaker 1: are not equipped to understand the socio political implications of

781
00:42:05,360 --> 00:42:08,880
Speaker 1: the technology itself. I don't think Twitter has an engineering problem.

782
00:42:08,960 --> 00:42:10,960
Speaker 1: I don't think they have even a product problem. Yes,

783
00:42:11,000 --> 00:42:13,439
Speaker 1: they need to add like a subscription product. Okay, that's easy,

784
00:42:13,440 --> 00:42:15,839
Speaker 1: and they're going to print billions of dollars. What they

785
00:42:15,880 --> 00:42:19,120
Speaker 1: have to decide is how do we talk on the Internet.

786
00:42:19,320 --> 00:42:23,279
Speaker 1: What gets amplified what gets not Should we abide by

787
00:42:23,400 --> 00:42:25,640
Speaker 1: a consistent standard or should we have it so that

788
00:42:25,680 --> 00:42:28,759
Speaker 1: our employees are going to revolt against this, revolt against that.

789
00:42:29,080 --> 00:42:31,880
Speaker 1: How do you actually have a standard on which you

790
00:42:31,880 --> 00:42:35,239
Speaker 1: can apply so that everybody buys into those rules, as

791
00:42:35,280 --> 00:42:38,080
Speaker 1: you said, at least be required to publish what those

792
00:42:38,120 --> 00:42:41,520
Speaker 1: moderation standards are. Right now, it's up to mister Agarwall,

793
00:42:41,600 --> 00:42:44,520
Speaker 1: and mister Agarwall has told us specifically, I do not

794
00:42:44,640 --> 00:42:48,000
Speaker 1: want to abide by the First Amendment in my content decisions.

795
00:42:48,320 --> 00:42:51,880
Speaker 1: And you know, a lot of people who observe the want,

796
00:42:52,280 --> 00:42:55,080
Speaker 1: want of free speech, of a First Amendment type environment

797
00:42:55,320 --> 00:42:57,680
Speaker 1: on the Internet, you should be very disappointed, I think

798
00:42:57,920 --> 00:43:00,560
Speaker 1: by this choice today, I think is tremendous failure on

799
00:43:00,640 --> 00:43:04,239
Speaker 1: the part of Twitter, their their their board of directors

800
00:43:04,520 --> 00:43:05,840
Speaker 1: and all of that. And I think it's going to

801
00:43:05,840 --> 00:43:08,320
Speaker 1: be a disaster in twenty twenty three when Trump is

802
00:43:08,400 --> 00:43:11,920
Speaker 1: running again, or we have an election cycle Hunter Biden laptop.

803
00:43:11,960 --> 00:43:14,399
Speaker 1: It's going to be times twenty in my opinion. And

804
00:43:14,960 --> 00:43:20,600
Speaker 1: Twitter occupies a very unique space in the information ecosystem. It's,

805
00:43:20,680 --> 00:43:23,360
Speaker 1: you know, disproportionally where elites are. I mean, this is

806
00:43:23,400 --> 00:43:26,759
Speaker 1: where elite caught every journalist. We look at our show, right, like,

807
00:43:26,800 --> 00:43:29,759
Speaker 1: how many of it our tweets? Yeah, exactly, exactly. So

808
00:43:30,000 --> 00:43:35,719
Speaker 1: it's it's very very elite driven, which makes it disproportionately impactful. Yes,

809
00:43:35,960 --> 00:43:38,719
Speaker 1: So who's running the ship there and what sorts of

810
00:43:38,760 --> 00:43:43,279
Speaker 1: decisions they're making have just you know, massive consequences for

811
00:43:43,400 --> 00:43:46,200
Speaker 1: what ultimately ends up being seen and heard and the

812
00:43:46,239 --> 00:43:49,319
Speaker 1: type of discourse we're able to have. Absolutely, Okay, some

813
00:43:49,400 --> 00:43:53,760
Speaker 1: bombshell news, some great news. Frankly out of besper Bessemer, Alabama.

814
00:43:53,920 --> 00:43:56,719
Speaker 1: You guys will recall we covered this year extensively the

815
00:43:57,480 --> 00:44:01,920
Speaker 1: Amazon warehouse down in Bessemer. There was effort to unionize

816
00:44:01,960 --> 00:44:05,000
Speaker 1: that warehouse. Ultimately, when the vote came down, it was

817
00:44:05,040 --> 00:44:09,560
Speaker 1: a dramatic loss for the union. However, we talked to

818
00:44:09,600 --> 00:44:12,479
Speaker 1: the president of the union that was trying to organize them,

819
00:44:12,680 --> 00:44:15,600
Speaker 1: and we talked to other reporters who were down there

820
00:44:15,600 --> 00:44:17,640
Speaker 1: on the scene, and they said there was a lot

821
00:44:17,719 --> 00:44:21,120
Speaker 1: of funny business going on here, and in particular, the

822
00:44:21,200 --> 00:44:25,040
Speaker 1: thing that they consistently pointed to was that Amazon had

823
00:44:25,320 --> 00:44:30,319
Speaker 1: a post office box installed on their property that they

824
00:44:30,360 --> 00:44:34,360
Speaker 1: effectively had control over at least gave the employees, the

825
00:44:34,400 --> 00:44:39,920
Speaker 1: feeling that Amazon was sort of controlling this election process. Now,

826
00:44:40,200 --> 00:44:45,520
Speaker 1: the National Labor Relations Board, the regional directors in that

827
00:44:45,760 --> 00:44:50,400
Speaker 1: area had laid out very specifically all of the parameters

828
00:44:50,440 --> 00:44:52,640
Speaker 1: of the election, when it's going to happen, how long

829
00:44:52,680 --> 00:44:56,200
Speaker 1: the mail in vote's going to occur. And Amazon asked

830
00:44:56,239 --> 00:45:00,239
Speaker 1: to have this drop box put on the property. They

831
00:45:00,320 --> 00:45:05,280
Speaker 1: said specifically no, and Amazon goes ahead and does it anyway. Anyway,

832
00:45:05,640 --> 00:45:09,400
Speaker 1: there were also other problems in terms of One of

833
00:45:09,400 --> 00:45:13,480
Speaker 1: the things they're pointing to is that workers were effectively

834
00:45:13,640 --> 00:45:17,600
Speaker 1: polled for union support, which again is illegal, by being

835
00:45:17,640 --> 00:45:20,640
Speaker 1: told that if they don't support the union, they need

836
00:45:20,640 --> 00:45:24,799
Speaker 1: to pick up anti union sort of propaganda or like merchandise,

837
00:45:25,239 --> 00:45:28,160
Speaker 1: and so that gave them a very clear sense of

838
00:45:28,200 --> 00:45:31,239
Speaker 1: which workers were pro union and which workers were anti union. Again,

839
00:45:31,280 --> 00:45:34,840
Speaker 1: this is illegal. You can't pull the workers in advance

840
00:45:34,880 --> 00:45:37,600
Speaker 1: because this is putting you undue pressure on them in

841
00:45:37,640 --> 00:45:40,920
Speaker 1: a very public way. So the bottom line of all

842
00:45:40,960 --> 00:45:46,000
Speaker 1: of this is that the regional NLRB agreed with the

843
00:45:46,200 --> 00:45:50,359
Speaker 1: union and the union organizers that this election was improper

844
00:45:50,400 --> 00:45:55,239
Speaker 1: and that Amazon had illegally violated workers' rights in the

845
00:45:55,280 --> 00:45:57,840
Speaker 1: way that they went about this, both with regards to

846
00:45:57,960 --> 00:46:00,960
Speaker 1: the mailbox and with regards to these sort of this

847
00:46:01,080 --> 00:46:05,120
Speaker 1: method that they use to pull publicly their employees. And

848
00:46:05,160 --> 00:46:09,760
Speaker 1: so they have issued an order granting Bessemer Amazon workers

849
00:46:09,840 --> 00:46:13,320
Speaker 1: a new election. Stuart Applebaum, who's the president of the Retail,

850
00:46:13,320 --> 00:46:15,200
Speaker 1: Wholesale and Department Store Union, let's go ahead and throw

851
00:46:15,239 --> 00:46:17,680
Speaker 1: the tear sheet up on the screen, said that the

852
00:46:17,719 --> 00:46:22,040
Speaker 1: decision substantiates, substantiates their claims that the first vote on

853
00:46:22,120 --> 00:46:25,400
Speaker 1: unionized in Amazon warehouse was tainted by what the union

854
00:46:25,440 --> 00:46:30,200
Speaker 1: called illegal misconduct that interfered with the election. Quote. Today's

855
00:46:30,200 --> 00:46:33,560
Speaker 1: decision confirms what we were saying all along that Amazon's

856
00:46:33,560 --> 00:46:36,919
Speaker 1: intimidation and interference prevented workers from having a fair say

857
00:46:37,239 --> 00:46:40,080
Speaker 1: and whether they wanted a union in their workplace. And

858
00:46:40,120 --> 00:46:43,200
Speaker 1: as the regional director is indicated, that is both unacceptable

859
00:46:43,600 --> 00:46:47,319
Speaker 1: and illegal. So the process going forward, the date for

860
00:46:47,360 --> 00:46:51,080
Speaker 1: the new election has not been sent set. Amazon has

861
00:46:51,200 --> 00:46:54,759
Speaker 1: until I think December thirteenth to appeal this to now

862
00:46:54,800 --> 00:46:58,640
Speaker 1: the National neighbor National Labor Relations Board, which of course

863
00:46:58,680 --> 00:47:01,040
Speaker 1: the members of which have been set by the Biden administration.

864
00:47:01,160 --> 00:47:04,440
Speaker 1: So they're much more pro union than you know, Trumpets

865
00:47:04,440 --> 00:47:07,520
Speaker 1: stacked it with a bunch of anti union lawyers, and

866
00:47:07,560 --> 00:47:10,279
Speaker 1: it had a very anti worker stance. So they have

867
00:47:10,360 --> 00:47:12,760
Speaker 1: a good shot at prevailing even at the national level.

868
00:47:13,120 --> 00:47:15,560
Speaker 1: In the meantime, they haven't set the date, and the

869
00:47:15,600 --> 00:47:19,759
Speaker 1: election may actually go on before that appeal has been

870
00:47:20,000 --> 00:47:23,239
Speaker 1: fully like, that process has fully occurred, if you read

871
00:47:23,239 --> 00:47:25,320
Speaker 1: between the lines. And there's a new Washington Post article

872
00:47:25,360 --> 00:47:28,080
Speaker 1: out about this this morning as well. It seems like

873
00:47:28,239 --> 00:47:32,720
Speaker 1: because the regional analogy specifically set these terms and Amazon

874
00:47:32,760 --> 00:47:35,000
Speaker 1: asked for this dropbox and they said no, and then

875
00:47:35,040 --> 00:47:37,120
Speaker 1: they did it anyway, Like I think they pissed these

876
00:47:37,120 --> 00:47:39,520
Speaker 1: people off. Yeah, where they're like, no, I told you

877
00:47:39,520 --> 00:47:41,040
Speaker 1: you can't do this, and then you went and did

878
00:47:41,080 --> 00:47:43,680
Speaker 1: it anyway. And so you know, this is a a

879
00:47:43,719 --> 00:47:46,000
Speaker 1: great win for the union, and obviously the odds are

880
00:47:46,080 --> 00:47:48,360
Speaker 1: still still a long shot. But I'd also say the

881
00:47:48,480 --> 00:47:50,879
Speaker 1: environment's a lot different now than it was at the time.

882
00:47:50,960 --> 00:47:53,080
Speaker 1: That's right, it is very different, and it's very important

883
00:47:53,080 --> 00:47:55,560
Speaker 1: to understand that. That being said, the deck was stacked

884
00:47:55,560 --> 00:47:58,160
Speaker 1: against them from the first place. I also, and look, Stewart,

885
00:47:58,200 --> 00:48:01,000
Speaker 1: you know, if you're listening, I'm sorry, but you pointed

886
00:48:01,040 --> 00:48:04,040
Speaker 1: out this excellent article at the time. I forget who

887
00:48:04,040 --> 00:48:08,200
Speaker 1: wrote it, specifically about the failures of union drives, and

888
00:48:08,239 --> 00:48:11,279
Speaker 1: it was pointing to Amazon but also in the modern era.

889
00:48:11,360 --> 00:48:12,960
Speaker 1: And what they point to is that a lot of

890
00:48:12,960 --> 00:48:17,600
Speaker 1: the organizers themselves were young activists who were speaking social

891
00:48:17,760 --> 00:48:21,000
Speaker 1: justice speak to a lot of these people, emphasizing black

892
00:48:21,040 --> 00:48:24,440
Speaker 1: lives matter to a bunch of Amazon employees when you know,

893
00:48:24,680 --> 00:48:27,200
Speaker 1: we have seen time and time again on our show,

894
00:48:27,239 --> 00:48:29,880
Speaker 1: the Jacobin Poll and more, what are the things that

895
00:48:29,960 --> 00:48:33,640
Speaker 1: actual working class people, even working class Black people, want

896
00:48:33,680 --> 00:48:36,440
Speaker 1: to hear whenever it comes to both unions and too politics.

897
00:48:36,520 --> 00:48:38,360
Speaker 1: They want to hear about how it's going to impact

898
00:48:38,360 --> 00:48:41,160
Speaker 1: their wage, their life and all of that. And instead

899
00:48:41,400 --> 00:48:43,960
Speaker 1: they were having social justice speak kind of being pushed

900
00:48:43,960 --> 00:48:46,719
Speaker 1: towards them as the opening message, which turned a lot

901
00:48:46,719 --> 00:48:49,399
Speaker 1: of these people off in the ultimate election. How much

902
00:48:49,440 --> 00:48:52,440
Speaker 1: did the Amazon dropbox change. I literally have no idea.

903
00:48:52,480 --> 00:48:54,680
Speaker 1: And it's not just about that. I mean, we've covered

904
00:48:54,680 --> 00:48:58,920
Speaker 1: this on our show. They change the traffic lights outside

905
00:48:58,960 --> 00:49:03,520
Speaker 1: of the outside of the area the warehouse so that

906
00:49:03,760 --> 00:49:05,520
Speaker 1: worker I think it was a sped up the red

907
00:49:05,600 --> 00:49:07,560
Speaker 1: light or something like that, so that people could not

908
00:49:07,640 --> 00:49:10,839
Speaker 1: come and congregate and organize in that drive. Amazon made

909
00:49:10,840 --> 00:49:14,160
Speaker 1: them sit through all of these informational sessions. They basically

910
00:49:14,200 --> 00:49:16,040
Speaker 1: went right up to the line, if not over the

911
00:49:16,080 --> 00:49:19,319
Speaker 1: line legality. Right. Yeah, at the very least they have

912
00:49:19,360 --> 00:49:21,600
Speaker 1: at least been recognized of going over the line. I

913
00:49:21,600 --> 00:49:24,120
Speaker 1: am not minimizing that. I want these people to have

914
00:49:24,200 --> 00:49:26,120
Speaker 1: the best and to have better lives and all of that,

915
00:49:26,280 --> 00:49:28,360
Speaker 1: but it's also on the Union and them to actually

916
00:49:28,360 --> 00:49:30,520
Speaker 1: try and message this thing properly if they're going to

917
00:49:30,560 --> 00:49:34,200
Speaker 1: try again, and the national environment would be very conducive

918
00:49:34,239 --> 00:49:37,000
Speaker 1: to this. I really believe this. The Great Resignation is

919
00:49:37,040 --> 00:49:40,400
Speaker 1: already happening. Yes, Amazon has thrown I think it was

920
00:49:40,440 --> 00:49:43,960
Speaker 1: seventeen eighteen whatever dollars minimum wage. They talk about healthcare,

921
00:49:44,280 --> 00:49:48,080
Speaker 1: all of this, but people, and Amazon specifically has already

922
00:49:48,120 --> 00:49:51,200
Speaker 1: admitted that they're having trouble hiring people in the middle

923
00:49:51,239 --> 00:49:54,160
Speaker 1: of a labor shortage. There has never been more bargaining

924
00:49:54,200 --> 00:49:56,759
Speaker 1: power for these people than right now, So right now

925
00:49:56,800 --> 00:49:58,480
Speaker 1: would be the time to do it. I do think

926
00:49:58,480 --> 00:50:00,560
Speaker 1: it's on the Union to try again and to actually

927
00:50:00,600 --> 00:50:03,640
Speaker 1: message it effectively this time. I think I'm trying to remember.

928
00:50:03,640 --> 00:50:05,640
Speaker 1: I think it was in the nation that piece that

929
00:50:05,680 --> 00:50:08,439
Speaker 1: you referenced at the time. I found it very eye

930
00:50:08,480 --> 00:50:11,280
Speaker 1: opening to me personally. I'm like, oh, this is also

931
00:50:11,280 --> 00:50:14,120
Speaker 1: why I failed. It's not just Amazon exactly. This is

932
00:50:14,160 --> 00:50:16,720
Speaker 1: about talking to people about what they really care about.

933
00:50:16,880 --> 00:50:18,319
Speaker 1: And like you said, look, you don't have to not

934
00:50:18,440 --> 00:50:21,560
Speaker 1: care or whatever about Black Lives Matter or social justice.

935
00:50:21,600 --> 00:50:23,800
Speaker 1: But whenever you're trying to talk to somebody and convince

936
00:50:23,880 --> 00:50:26,160
Speaker 1: them to do something in this way, you have to

937
00:50:26,239 --> 00:50:28,520
Speaker 1: lead with a lot more of what is actually going

938
00:50:28,560 --> 00:50:30,560
Speaker 1: to do for your life. What are your actual concerns

939
00:50:30,560 --> 00:50:32,840
Speaker 1: about what's happening here on the job one hundred percent?

940
00:50:32,880 --> 00:50:35,000
Speaker 1: And look, I mean I wasn't there. I don't know

941
00:50:35,080 --> 00:50:38,200
Speaker 1: how the messaging was done to what extent. I don't

942
00:50:38,200 --> 00:50:40,239
Speaker 1: know how reflective that article was or not. I think

943
00:50:40,280 --> 00:50:43,000
Speaker 1: the biggest issue is simply the way that the deck

944
00:50:43,040 --> 00:50:45,759
Speaker 1: is stacked against workers in all of these places. That's

945
00:50:45,800 --> 00:50:48,640
Speaker 1: obviously the overarching problem why we have such low unionization

946
00:50:48,719 --> 00:50:51,400
Speaker 1: rates in the country. But if ever there was a time,

947
00:50:51,920 --> 00:50:54,440
Speaker 1: it is now. And I don't want to get anybody's

948
00:50:54,440 --> 00:50:57,000
Speaker 1: hopes up because very likely the election goes the way

949
00:50:57,040 --> 00:50:59,360
Speaker 1: the last one did, and it wasn't close. It was

950
00:50:59,360 --> 00:51:01,920
Speaker 1: like two thirds to one start. It was rough roughly

951
00:51:01,960 --> 00:51:05,799
Speaker 1: something like that two to one effectively in the end count. So,

952
00:51:06,200 --> 00:51:12,600
Speaker 1: you know, very difficult odds. Very much the odds are

953
00:51:12,600 --> 00:51:14,880
Speaker 1: stacked against them and they have a big hill to

954
00:51:14,920 --> 00:51:19,600
Speaker 1: climb here. But what we've been tracking is how much

955
00:51:19,840 --> 00:51:24,280
Speaker 1: there is a different feel in the air now with workers,

956
00:51:24,320 --> 00:51:27,400
Speaker 1: whether they're walking out of their fast food jobs on mass,

957
00:51:27,880 --> 00:51:31,759
Speaker 1: whether they are authorizing strikes in the strike wave that

958
00:51:31,760 --> 00:51:35,280
Speaker 1: we've seen across the country, whether they're the Starbucks workers

959
00:51:35,320 --> 00:51:38,200
Speaker 1: who in a couple different locations now have filed and

960
00:51:38,239 --> 00:51:42,680
Speaker 1: are trying to unionize. There is a lot of momentum

961
00:51:42,800 --> 00:51:46,720
Speaker 1: at this moment behind workers who are trying to claim

962
00:51:46,800 --> 00:51:49,160
Speaker 1: a little bit more power and a little bit more

963
00:51:49,200 --> 00:51:54,360
Speaker 1: in terms of scheduling, in terms of benefits, in terms

964
00:51:54,440 --> 00:51:58,439
Speaker 1: of wages, and all of those things. So Amazon will

965
00:51:58,480 --> 00:52:01,680
Speaker 1: do everything that they possibly can to make sure that

966
00:52:01,719 --> 00:52:05,480
Speaker 1: the result turns out the same way again. You know,

967
00:52:05,600 --> 00:52:09,040
Speaker 1: in the past, they've fired workers, as we covered yesterday,

968
00:52:09,760 --> 00:52:13,759
Speaker 1: fired a young homeless man who was working at their

969
00:52:13,760 --> 00:52:18,719
Speaker 1: warehouse in Staten Island because seemingly he became an outspoken

970
00:52:18,760 --> 00:52:21,839
Speaker 1: advocate for the union and that was unacceptable to them,

971
00:52:21,880 --> 00:52:25,520
Speaker 1: so they fired him. Christian Smalls, of course fired And

972
00:52:25,640 --> 00:52:28,239
Speaker 1: there are other instances across the country where they have

973
00:52:28,440 --> 00:52:32,400
Speaker 1: been caught retaliating against workers who have wanted to organize.

974
00:52:32,480 --> 00:52:34,960
Speaker 1: So I don't think anyone should delude themselves about the

975
00:52:35,000 --> 00:52:38,080
Speaker 1: tactics they are able and willing to use in this instance,

976
00:52:38,400 --> 00:52:42,800
Speaker 1: and just how difficult it is to certify, to certify

977
00:52:42,840 --> 00:52:45,840
Speaker 1: an union, to join a union. But they are getting

978
00:52:45,840 --> 00:52:47,839
Speaker 1: another shot at it. It's something we're going to watch

979
00:52:48,160 --> 00:52:51,440
Speaker 1: very closely, and it will be really interesting. I mean,

980
00:52:51,440 --> 00:52:53,960
Speaker 1: this is almost like an in a lab test case

981
00:52:54,440 --> 00:52:57,600
Speaker 1: of the difference between when this was happening at the

982
00:52:57,640 --> 00:53:02,000
Speaker 1: beginning of last year versus now, and whether there really

983
00:53:02,120 --> 00:53:07,440
Speaker 1: is a different environment for workers and their power and

984
00:53:07,480 --> 00:53:09,759
Speaker 1: their ability to assert themselves in the workplace. I think

985
00:53:09,800 --> 00:53:12,120
Speaker 1: things have changed a lot. I think things could really

986
00:53:12,120 --> 00:53:14,239
Speaker 1: this could be a big one, in my opinion. We'll see.

987
00:53:14,280 --> 00:53:16,200
Speaker 1: I'm not ready to get my hopes up there, but

988
00:53:16,239 --> 00:53:20,239
Speaker 1: we will watch it closely. Okay, big news for the

989
00:53:20,280 --> 00:53:24,360
Speaker 1: Cuomo brothers. It's another story we've been following really closely.

990
00:53:24,480 --> 00:53:27,800
Speaker 1: So new information was put out by New York Attorney

991
00:53:27,800 --> 00:53:30,600
Speaker 1: General Letitia James, who's now running for governor of New

992
00:53:30,680 --> 00:53:36,239
Speaker 1: York about just how involved brother CNN primetime host Chris

993
00:53:36,320 --> 00:53:41,080
Speaker 1: Cuomo was in the attempted response and ultimately cover up

994
00:53:41,440 --> 00:53:45,319
Speaker 1: of some of Andrew Cuomo's bad behavior, especially with regards

995
00:53:45,560 --> 00:53:47,800
Speaker 1: to a number of the women who were coming forward

996
00:53:48,200 --> 00:53:52,040
Speaker 1: and alleging either harassment or outright sexual assault. Let's go

997
00:53:52,040 --> 00:53:54,399
Speaker 1: ahead and throw this tweet up on the screen. This

998
00:53:54,440 --> 00:53:57,399
Speaker 1: is from our friend Brian Schwartz over at CNBC. He says,

999
00:53:57,400 --> 00:54:00,640
Speaker 1: CNN host Chris Cuomo used his sources is to get

1000
00:54:00,680 --> 00:54:04,799
Speaker 1: info on brother Andrew Cuomo's accusers. He also engaged with

1001
00:54:04,880 --> 00:54:08,680
Speaker 1: sources to get a read on upcoming stories that took

1002
00:54:08,760 --> 00:54:11,359
Speaker 1: aim at his brother. I have a lead on the

1003
00:54:11,400 --> 00:54:16,320
Speaker 1: wedding girl, Cuomo texted Top eight at the time, Melissa DeRosa,

1004
00:54:16,760 --> 00:54:19,399
Speaker 1: and there is a lot more than this, so they

1005
00:54:19,719 --> 00:54:22,399
Speaker 1: He was texting Durosa saying, please let me help with

1006
00:54:22,800 --> 00:54:26,120
Speaker 1: prep as Andrew Cuomo is having to respond to these

1007
00:54:26,239 --> 00:54:29,480
Speaker 1: repeated allegations. Then he texts her and says, I have

1008
00:54:29,560 --> 00:54:31,719
Speaker 1: a lead on the wedding girl. That's in reference to

1009
00:54:32,080 --> 00:54:37,040
Speaker 1: someone who alleged misconduct at a wedding. CNN issue a comment. So, first,

1010
00:54:37,200 --> 00:54:39,760
Speaker 1: first off, they didn't say anything about it. They declined

1011
00:54:39,760 --> 00:54:43,920
Speaker 1: to comment, But then as more and more media outlets,

1012
00:54:43,960 --> 00:54:46,520
Speaker 1: including The Washington Post, I'm including a lot of sort

1013
00:54:46,560 --> 00:54:49,640
Speaker 1: of top flight elite media type places, started to run

1014
00:54:49,680 --> 00:54:52,840
Speaker 1: the story. They ultimately issued a comment hours after the

1015
00:54:52,880 --> 00:54:56,120
Speaker 1: publication of the initial articles saying that the news organization

1016
00:54:56,280 --> 00:54:59,160
Speaker 1: would be reviewing the documents. The thousands of pages of

1017
00:54:59,160 --> 00:55:01,759
Speaker 1: additional transg and exhibits that were released today by the

1018
00:55:01,760 --> 00:55:04,960
Speaker 1: New York Attorney General deserve a thorough review and consideration.

1019
00:55:05,080 --> 00:55:08,319
Speaker 1: CNN spokesman Matt Dornick said, we will be having conversations

1020
00:55:08,320 --> 00:55:11,480
Speaker 1: and seeking additional clarity about their significance as they relate

1021
00:55:11,719 --> 00:55:14,680
Speaker 1: to CNN over the next several days. Some of the

1022
00:55:14,880 --> 00:55:18,600
Speaker 1: additional information that has just come out is also centering

1023
00:55:18,680 --> 00:55:22,160
Speaker 1: around Ronan. Ferroll was writing a piece about some of

1024
00:55:22,200 --> 00:55:26,080
Speaker 1: the accusers, and Chris Cuomo was trying to use his

1025
00:55:26,239 --> 00:55:30,120
Speaker 1: media contacts within the industry to figure out what does

1026
00:55:30,200 --> 00:55:33,720
Speaker 1: Ronan have, how many women? When's the story going to drop?

1027
00:55:34,040 --> 00:55:38,319
Speaker 1: So actually using his sort of professional network that he

1028
00:55:38,480 --> 00:55:42,160
Speaker 1: has gained in part as being this high level host

1029
00:55:42,200 --> 00:55:47,080
Speaker 1: at CNN in order to help his brother, the governor

1030
00:55:47,120 --> 00:55:49,560
Speaker 1: of New York. Of course, at a time when he's

1031
00:55:49,560 --> 00:55:53,520
Speaker 1: having his brother on and you know, doing their little

1032
00:55:53,560 --> 00:55:56,200
Speaker 1: Dog and Pony show about swabbing the nose and having

1033
00:55:56,480 --> 00:55:59,400
Speaker 1: a grand old time dur back when his brother was

1034
00:55:59,600 --> 00:56:02,359
Speaker 1: a co hero. I think it's totally nuts. And I

1035
00:56:02,400 --> 00:56:04,600
Speaker 1: know it may be tiresome or whatever to hear us

1036
00:56:04,640 --> 00:56:07,680
Speaker 1: talk about it, but this is the most concrete example

1037
00:56:07,880 --> 00:56:12,960
Speaker 1: of the intertwinement between the people in power the people

1038
00:56:12,960 --> 00:56:16,280
Speaker 1: who are supposed to cover them. I mean Cuomo himself.

1039
00:56:16,360 --> 00:56:18,719
Speaker 1: Chris Cuomo opened his show last night and did not

1040
00:56:18,840 --> 00:56:22,160
Speaker 1: address this. CNN allowed him to go on the air

1041
00:56:22,360 --> 00:56:26,600
Speaker 1: after this was revealed, which is unbelievable, and look like

1042
00:56:27,000 --> 00:56:30,520
Speaker 1: at one point he was talking to Melissa de Rosa,

1043
00:56:30,560 --> 00:56:34,360
Speaker 1: the governor secretary, via text, saying quote, you need to

1044
00:56:34,480 --> 00:56:38,239
Speaker 1: trust me. We are making mistakes we cannot afford, and

1045
00:56:38,280 --> 00:56:42,520
Speaker 1: then intimately involved with Melissa in digging up dirt on

1046
00:56:42,600 --> 00:56:44,759
Speaker 1: some of the accusers. He said, you know, I think

1047
00:56:44,800 --> 00:56:47,360
Speaker 1: we have a lead on so and so. But he

1048
00:56:47,960 --> 00:56:51,680
Speaker 1: was talking with his sources. I mean, what they point

1049
00:56:51,719 --> 00:56:55,760
Speaker 1: to is that Cuomo, we already know he helped draft

1050
00:56:55,760 --> 00:56:59,920
Speaker 1: a reply or draft a statement from Andrew Cuomo denying

1051
00:57:00,200 --> 00:57:03,920
Speaker 1: the accusation that alone is already a complete breach, and

1052
00:57:04,000 --> 00:57:06,040
Speaker 1: yet we heard, oh, he's his brother. I mean you

1053
00:57:06,080 --> 00:57:08,359
Speaker 1: wouldn't you know, who wouldn't do that. This is way

1054
00:57:08,400 --> 00:57:11,520
Speaker 1: worse using your contacts from the job that you have

1055
00:57:11,640 --> 00:57:14,319
Speaker 1: at a news organization in order to try and dig

1056
00:57:14,400 --> 00:57:17,520
Speaker 1: up dirt on the women accusing your governor brother of

1057
00:57:17,600 --> 00:57:21,560
Speaker 1: sexual assault. It is outright corruption. The fact that CNN

1058
00:57:21,840 --> 00:57:24,479
Speaker 1: did not take him off the air and immediately fire

1059
00:57:24,560 --> 00:57:27,360
Speaker 1: him is outrageous. And we were talking about this, Crystal.

1060
00:57:27,480 --> 00:57:29,600
Speaker 1: There's no way in hell that Chris Cuomo told the

1061
00:57:29,600 --> 00:57:32,000
Speaker 1: truth to Jeff Zucker and CNN. He probably was like

1062
00:57:32,200 --> 00:57:34,040
Speaker 1: he didn't think his tax were going to come out, right,

1063
00:57:34,280 --> 00:57:36,680
Speaker 1: He's like, ah, you know, hell yeah, he's my brother.

1064
00:57:36,920 --> 00:57:40,080
Speaker 1: High help. Yeah, I had a phone call or talk

1065
00:57:40,120 --> 00:57:42,240
Speaker 1: to my brother. Yeah, exactly what. We're not going to

1066
00:57:42,320 --> 00:57:44,400
Speaker 1: talk to my brother. He's family. You know. They like

1067
00:57:44,480 --> 00:57:46,280
Speaker 1: to remind us of that all the time whenever they

1068
00:57:46,280 --> 00:57:48,760
Speaker 1: were on the show together. You put all that together,

1069
00:57:48,920 --> 00:57:51,960
Speaker 1: That is not what happened here. This was deep in

1070
00:57:52,000 --> 00:57:56,040
Speaker 1: the weeds helping orchestrate a campaign of smears against the

1071
00:57:56,080 --> 00:57:58,640
Speaker 1: women who were accusing Andrew Cuomo. And it also goes

1072
00:57:58,680 --> 00:58:01,200
Speaker 1: to show how long it's been happen. Okay, we only

1073
00:58:01,240 --> 00:58:03,640
Speaker 1: know the texts whenever it comes to this, did he

1074
00:58:03,640 --> 00:58:05,720
Speaker 1: help him on COVID messaging? Did he help him on

1075
00:58:05,760 --> 00:58:07,880
Speaker 1: COVID policy? We know that he had him on his show,

1076
00:58:08,040 --> 00:58:11,280
Speaker 1: What about before that? I've played it here before. Chris

1077
00:58:11,320 --> 00:58:14,320
Speaker 1: Cuomo has been having his brother on his network since

1078
00:58:14,360 --> 00:58:17,480
Speaker 1: his time at ABC News. How long have they been

1079
00:58:17,520 --> 00:58:20,640
Speaker 1: in codes together in order to help his brother's political

1080
00:58:20,720 --> 00:58:23,000
Speaker 1: career in the state of New York. This could just

1081
00:58:23,040 --> 00:58:25,000
Speaker 1: be the tip of the iceberg. I really think it is.

1082
00:58:25,200 --> 00:58:29,760
Speaker 1: We've talked about this. Look sexual assault stuff on Cuomo. Yeah, look,

1083
00:58:29,840 --> 00:58:33,440
Speaker 1: it's bad, but I personally think what he did, which

1084
00:58:33,520 --> 00:58:37,040
Speaker 1: was way worse, was sentenced to death by accident, but

1085
00:58:37,160 --> 00:58:40,520
Speaker 1: still sentenced nonetheless thousands of elderly people in nursing homes

1086
00:58:40,560 --> 00:58:44,400
Speaker 1: through his policy using the liability shield and shielding these

1087
00:58:44,480 --> 00:58:48,680
Speaker 1: nursing companies from any liability from the families of those

1088
00:58:48,760 --> 00:58:51,520
Speaker 1: from the people who had victims, and then even worse,

1089
00:58:51,880 --> 00:58:54,680
Speaker 1: covering up COVID debts and more from his office in

1090
00:58:54,680 --> 00:58:57,080
Speaker 1: the state of New York so that to avoid federal scrutiny.

1091
00:58:57,120 --> 00:58:59,400
Speaker 1: And on top of that, profiting millions of dollars off

1092
00:58:59,400 --> 00:59:02,880
Speaker 1: the book outright abusive office, a terrible decision, and he

1093
00:59:02,960 --> 00:59:05,920
Speaker 1: never apologized to the American people. No, it's disgusting. And

1094
00:59:05,920 --> 00:59:08,720
Speaker 1: then to learn that, you know, I mean, it's a

1095
00:59:08,720 --> 00:59:11,880
Speaker 1: low bar. But Chris Cuomo has the highest rated show

1096
00:59:12,440 --> 00:59:17,240
Speaker 1: on the failing that CNN network, and he's very influential.

1097
00:59:17,320 --> 00:59:20,960
Speaker 1: Oh yeah, he's close. Reportedly they're close buddies with Jeff Zucker,

1098
00:59:21,000 --> 00:59:24,280
Speaker 1: who runs better book of course, and so the way

1099
00:59:24,320 --> 00:59:27,880
Speaker 1: they've handled this it's just, I mean, there's no way

1100
00:59:27,920 --> 00:59:30,320
Speaker 1: to spin it other than just they like him and

1101
00:59:30,360 --> 00:59:32,040
Speaker 1: he gets good ratings, so they're going to look the

1102
00:59:32,040 --> 00:59:34,440
Speaker 1: other way almost no matter what. You know, this is

1103
00:59:34,480 --> 00:59:37,200
Speaker 1: the first time I really have seen them feel even

1104
00:59:37,560 --> 00:59:42,240
Speaker 1: pressure enough to have to say anything about what was

1105
00:59:42,280 --> 00:59:45,200
Speaker 1: going on with Chris Cuomo. Oftentimes, when these stories come out,

1106
00:59:45,280 --> 00:59:47,920
Speaker 1: they just they don't comment. They dismiss it. They say,

1107
00:59:48,120 --> 00:59:49,880
Speaker 1: we've already said what we want to say on that.

1108
00:59:50,480 --> 00:59:52,479
Speaker 1: So for Cuomo to go and do his show last

1109
00:59:52,520 --> 00:59:55,960
Speaker 1: night and not say a word, I mean, it really

1110
00:59:56,000 --> 00:59:59,720
Speaker 1: boggles my mind. Because we don't have bosses, but if

1111
00:59:59,720 --> 01:00:02,200
Speaker 1: there were something that was like this big that was

1112
01:00:02,240 --> 01:00:05,280
Speaker 1: swirling about us. Of course we tell you what was

1113
01:00:05,320 --> 01:00:10,240
Speaker 1: going on. That's just like basic character to be. I'd

1114
01:00:10,240 --> 01:00:13,040
Speaker 1: be like, look, guys, here's the deal. You know, yeah,

1115
01:00:13,120 --> 01:00:15,840
Speaker 1: like here's what they all truth. Your eyes screwed up

1116
01:00:15,840 --> 01:00:18,320
Speaker 1: in this way. I mean like at a certain point

1117
01:00:18,360 --> 01:00:22,320
Speaker 1: you got to own it, like this is wildly inappropriate

1118
01:00:22,480 --> 01:00:25,280
Speaker 1: and unethical. And remember when Brian Stelter went on what

1119
01:00:25,440 --> 01:00:28,880
Speaker 1: was it, Jimmen or something, Colbert Colbert, I think, yeah,

1120
01:00:28,920 --> 01:00:31,400
Speaker 1: and he was like, wow, this is so complic I think,

1121
01:00:32,200 --> 01:00:37,440
Speaker 1: crazy situation. It's a crazy situation. Complex of interests happen

1122
01:00:37,640 --> 01:00:40,880
Speaker 1: all the time. There's a very clear playbook for how

1123
01:00:40,920 --> 01:00:43,680
Speaker 1: you handle it, and this ain't it. It's not a

1124
01:00:43,680 --> 01:00:47,440
Speaker 1: close call, so it's pretty wild. The other detail here

1125
01:00:47,480 --> 01:00:51,000
Speaker 1: that's that's pretty interesting, is you know, of course he

1126
01:00:51,120 --> 01:00:54,120
Speaker 1: says Chris Cuomo that, oh, you didn't even think about

1127
01:00:54,320 --> 01:00:56,600
Speaker 1: the conflict. He was just thinking about his family, and

1128
01:00:56,640 --> 01:00:59,280
Speaker 1: I was just thinking, here's this literal quote. His almost

1129
01:00:59,320 --> 01:01:01,560
Speaker 1: the only focus he said was quote, how do I

1130
01:01:01,600 --> 01:01:04,480
Speaker 1: protect my family? How do I help protect him? Probably

1131
01:01:04,520 --> 01:01:06,800
Speaker 1: should have been thinking more about how I protect myself,

1132
01:01:06,800 --> 01:01:09,440
Speaker 1: which just never occurred to me. So he's casting himself.

1133
01:01:09,480 --> 01:01:11,560
Speaker 1: It's like, oh, he's just so selfless. It was just

1134
01:01:11,640 --> 01:01:16,800
Speaker 1: helping us, It's right. But then they catch him in

1135
01:01:16,840 --> 01:01:20,800
Speaker 1: these texts telling Melissa Durosa again the top aid to

1136
01:01:21,240 --> 01:01:25,800
Speaker 1: quote delete this thread now, also indicating he knew this

1137
01:01:25,920 --> 01:01:28,680
Speaker 1: wasn't okay. You knew this was not okay. And also

1138
01:01:28,760 --> 01:01:30,720
Speaker 1: one other just little detail here that's kind of funny,

1139
01:01:30,840 --> 01:01:35,640
Speaker 1: is Liz Smith. Apparently she makes a cameo here. I

1140
01:01:35,680 --> 01:01:37,800
Speaker 1: assume it's the same Lismith, and he was spelled well.

1141
01:01:37,840 --> 01:01:39,760
Speaker 1: They don't never specify. They just say that she was

1142
01:01:39,800 --> 01:01:44,200
Speaker 1: like an outside advisor and she was the one actor

1143
01:01:44,240 --> 01:01:46,400
Speaker 1: in all of this that Melissa de Rosa was like,

1144
01:01:46,840 --> 01:01:49,480
Speaker 1: we're just going to stay the course and take go

1145
01:01:49,640 --> 01:01:52,680
Speaker 1: hard on these allegations, and Liz is like, well that's

1146
01:01:52,680 --> 01:01:54,760
Speaker 1: what you've been doing and it hasn't been working out well.

1147
01:01:54,840 --> 01:01:59,040
Speaker 1: So anyway, just shows you how these networks, how these

1148
01:01:59,040 --> 01:02:03,440
Speaker 1: circles run. That top Pete Boodage advisor Liz Smith also

1149
01:02:03,520 --> 01:02:09,400
Speaker 1: involved in the Cuomo in Berglio classic. All right, Zachery,

1150
01:02:09,400 --> 01:02:11,960
Speaker 1: you looll get at well. Longtime listeners will tire of

1151
01:02:12,000 --> 01:02:14,080
Speaker 1: hearing me say this, but I think it bears repeating

1152
01:02:14,160 --> 01:02:16,960
Speaker 1: over and over again. The most pernicious form of media

1153
01:02:17,000 --> 01:02:19,560
Speaker 1: bias that exists is not what they choose to show you.

1154
01:02:19,760 --> 01:02:23,480
Speaker 1: What they choose not to show you, selective coverage, selective outrage.

1155
01:02:23,560 --> 01:02:26,000
Speaker 1: It breeds the taste that cares the attention of the

1156
01:02:26,080 --> 01:02:28,720
Speaker 1: ruling class and the conditions of millions of people who

1157
01:02:28,760 --> 01:02:31,800
Speaker 1: watch cable news to look at politics in the way

1158
01:02:31,880 --> 01:02:34,600
Speaker 1: that is shaped from above. That is why I am

1159
01:02:34,640 --> 01:02:37,480
Speaker 1: truly puzzled at the current lack of media coverage and

1160
01:02:37,760 --> 01:02:41,760
Speaker 1: of the recent Christmas parade massacre in Wakesha, Wisconsin, where

1161
01:02:42,000 --> 01:02:44,680
Speaker 1: six victims ranging from an eight year old boy to

1162
01:02:44,720 --> 01:02:47,280
Speaker 1: an eighty one year old man, were mowed down by

1163
01:02:47,360 --> 01:02:50,280
Speaker 1: Daryl Brooks Junior. Now we knew shortly after the crime

1164
01:02:50,360 --> 01:02:53,160
Speaker 1: was committed mister Brooks was released on bail that the

1165
01:02:53,160 --> 01:02:56,360
Speaker 1: district attorney that Milwaukee said that should never have been

1166
01:02:56,400 --> 01:02:58,560
Speaker 1: granted in the first place, and that he's a long

1167
01:02:58,640 --> 01:03:02,440
Speaker 1: time violent felon, and then well, it kind of just disappeared.

1168
01:03:02,640 --> 01:03:05,600
Speaker 1: It seemed like all reporting and inquiry into him just vanished,

1169
01:03:05,640 --> 01:03:08,280
Speaker 1: and not just vanished when it was reported, his name

1170
01:03:08,400 --> 01:03:11,800
Speaker 1: was kept out of the media. Weirdly, both Washington Posts

1171
01:03:11,840 --> 01:03:16,160
Speaker 1: and CNN posting stories that say from CNN quote Lakesha

1172
01:03:16,240 --> 01:03:18,880
Speaker 1: will hold a moment of silence today, marking one week

1173
01:03:18,920 --> 01:03:21,120
Speaker 1: since a car drove through a city Christmas preve and

1174
01:03:21,160 --> 01:03:23,560
Speaker 1: from the Washington Post quote, here's what we know so

1175
01:03:23,640 --> 01:03:25,360
Speaker 1: far on the sequence of events that led to the

1176
01:03:25,400 --> 01:03:29,320
Speaker 1: Waukesha tragedy caused by an suv. Hmm, a car in

1177
01:03:29,360 --> 01:03:32,120
Speaker 1: an suv. They just did it out of nowhere. Huh. Look,

1178
01:03:32,400 --> 01:03:35,120
Speaker 1: let's be honest. They are afraid of making this racial,

1179
01:03:35,360 --> 01:03:38,040
Speaker 1: but it is not their job to assess it either way.

1180
01:03:38,360 --> 01:03:40,400
Speaker 1: It's just a report on the facts. And when you

1181
01:03:40,440 --> 01:03:42,720
Speaker 1: look a little deeper into mister Brooks, it does not

1182
01:03:42,840 --> 01:03:46,240
Speaker 1: paint a one dimensional portrait. Okay. Brooks apparently has a

1183
01:03:46,320 --> 01:03:49,640
Speaker 1: very long and bizarre posting history, which includes sympathy with

1184
01:03:49,720 --> 01:03:54,360
Speaker 1: the black Hebrew Israelites, anti Semitic memes, and including admiration

1185
01:03:54,520 --> 01:03:57,600
Speaker 1: for Hitler. He bragged in the past about calling himself

1186
01:03:57,640 --> 01:04:00,360
Speaker 1: a terrorist and in some of his old videos a

1187
01:04:00,440 --> 01:04:03,240
Speaker 1: quote killer in the city, and he generally seemed to

1188
01:04:03,360 --> 01:04:07,040
Speaker 1: revel in anarchy of the George Floyd protests, posting incendiary

1189
01:04:07,120 --> 01:04:10,920
Speaker 1: updates around wishing violence towards some whites. In general, he

1190
01:04:11,000 --> 01:04:14,440
Speaker 1: seems like a violent, off kilter loser with the social

1191
01:04:14,480 --> 01:04:17,400
Speaker 1: media history to back all of that up, and perhaps

1192
01:04:17,600 --> 01:04:19,840
Speaker 1: that points to the motive. But the problem with our

1193
01:04:19,880 --> 01:04:22,720
Speaker 1: media is their selective coverage. Lack of coverage of these

1194
01:04:22,760 --> 01:04:26,440
Speaker 1: incidents leads to the correct assumption by many people in

1195
01:04:26,480 --> 01:04:29,360
Speaker 1: this country that when violence is perpetrated by people whose

1196
01:04:29,400 --> 01:04:32,200
Speaker 1: ideas are at least tangentially linked to those in the

1197
01:04:32,240 --> 01:04:35,400
Speaker 1: media and the people institutional left agree with, then it's

1198
01:04:35,440 --> 01:04:39,120
Speaker 1: okay justified. Ignored memory hold it leads worse to a

1199
01:04:39,120 --> 01:04:41,600
Speaker 1: mindset that if the other side can get away with violence,

1200
01:04:41,680 --> 01:04:44,000
Speaker 1: or at the very least avoid the national reckoning that

1201
01:04:44,040 --> 01:04:46,919
Speaker 1: seems to follow any violence tangentially tied to the right,

1202
01:04:47,120 --> 01:04:50,360
Speaker 1: that perhaps even more violence is than justified. Getting out

1203
01:04:50,360 --> 01:04:53,600
Speaker 1: of this Hella situation is the Gordian Knot of today's politics,

1204
01:04:53,720 --> 01:04:55,840
Speaker 1: and it requires doing what I am doing just now.

1205
01:04:56,160 --> 01:04:58,919
Speaker 1: Just tell the truth, tell people what happened. So let's

1206
01:04:58,920 --> 01:05:01,480
Speaker 1: continue on to tip top of mister Daryl brooks bizarre

1207
01:05:01,480 --> 01:05:04,240
Speaker 1: social media presence. Here's what else that we know about him.

1208
01:05:04,760 --> 01:05:08,600
Speaker 1: Brooks was diagnosed with bipolar disorder and depression at age eleven.

1209
01:05:08,640 --> 01:05:11,120
Speaker 1: When he was growing up in Milwaukee, his father was

1210
01:05:11,160 --> 01:05:13,760
Speaker 1: an alcoholic, and he grew up in an abusive environment

1211
01:05:13,760 --> 01:05:17,000
Speaker 1: surrounded by drugs. He began committing crimes as early as

1212
01:05:17,040 --> 01:05:19,920
Speaker 1: age seventeen. He was charged for battery, and then he

1213
01:05:20,000 --> 01:05:21,600
Speaker 1: was in and out of prison and in trouble with

1214
01:05:21,600 --> 01:05:25,120
Speaker 1: the law across three different states, including sexual abuse of

1215
01:05:25,160 --> 01:05:27,880
Speaker 1: a minor. He appears to have had a long problem

1216
01:05:27,880 --> 01:05:30,680
Speaker 1: with methamphetamine use and has been charged on and off

1217
01:05:30,680 --> 01:05:33,280
Speaker 1: many times with gun charges and a recent attempt at

1218
01:05:33,360 --> 01:05:36,000
Speaker 1: killing people in a fight with the car. Now, as

1219
01:05:36,040 --> 01:05:38,480
Speaker 1: to the crime itself, here's actually where things get kind

1220
01:05:38,480 --> 01:05:42,320
Speaker 1: of strange. Around four thirty pm last Sunday, Wilkesha police

1221
01:05:42,360 --> 01:05:45,240
Speaker 1: were called to a domestic disturbance between Brooks and one

1222
01:05:45,240 --> 01:05:48,480
Speaker 1: of his ex girlfriends. It was after this domestic disturbance

1223
01:05:48,640 --> 01:05:51,320
Speaker 1: Brooks barreled his car into the Christmas parade with the

1224
01:05:51,400 --> 01:05:54,240
Speaker 1: video that you've all seen. As of yet, there is

1225
01:05:54,280 --> 01:05:57,360
Speaker 1: still no motive. Was this somebody who had completely snapped?

1226
01:05:57,640 --> 01:05:59,760
Speaker 1: Was he planning it all along? So far he's been

1227
01:06:00,240 --> 01:06:03,040
Speaker 1: with intentional homicide. Perhaps there is evidence that we are

1228
01:06:03,080 --> 01:06:05,720
Speaker 1: not aware of yet from the police about a so

1229
01:06:05,800 --> 01:06:09,680
Speaker 1: called premeditated crime. As for Brooks, victims six have died

1230
01:06:09,720 --> 01:06:12,080
Speaker 1: so far, all of whose debts who've been charged with.

1231
01:06:12,400 --> 01:06:15,439
Speaker 1: Seven children remain in the hospital as of Sunday, three

1232
01:06:15,480 --> 01:06:19,040
Speaker 1: in serious condition, three in fair condition, one in good condition.

1233
01:06:19,360 --> 01:06:21,600
Speaker 1: Two others were released from the hospital before the weekend.

1234
01:06:21,880 --> 01:06:23,520
Speaker 1: And at least the great side of this is that

1235
01:06:23,560 --> 01:06:26,000
Speaker 1: two million dollars have been raised so far on GoFundMe

1236
01:06:26,200 --> 01:06:28,600
Speaker 1: to support the victims, a link to which we will

1237
01:06:28,600 --> 01:06:31,120
Speaker 1: include in the description of this video. That's what we know.

1238
01:06:31,480 --> 01:06:33,320
Speaker 1: It's really not hard to do all of this, and

1239
01:06:33,360 --> 01:06:34,880
Speaker 1: it says a lot about the current state of our

1240
01:06:34,920 --> 01:06:38,000
Speaker 1: media that they selectively cover which crimes they'll amplify and

1241
01:06:38,080 --> 01:06:40,760
Speaker 1: which they don't. It's actually an acknowledgement on their part

1242
01:06:40,840 --> 01:06:42,919
Speaker 1: that coverage itself can drive a lot of the way

1243
01:06:43,080 --> 01:06:45,720
Speaker 1: that people think about current events, what should be done

1244
01:06:45,720 --> 01:06:48,320
Speaker 1: and what shouldn't be. But it highlights also that in

1245
01:06:48,360 --> 01:06:51,720
Speaker 1: the long run, these people cannot win. Not saying corporate

1246
01:06:51,760 --> 01:06:54,400
Speaker 1: media won't be around forever, but you know, twenty years ago,

1247
01:06:54,440 --> 01:06:56,280
Speaker 1: we didn't even have the Internet to at least revel

1248
01:06:56,320 --> 01:06:58,720
Speaker 1: so much of what they're doing or not covering. We

1249
01:06:58,760 --> 01:07:01,760
Speaker 1: did not have shows like this one. Right now, most

1250
01:07:01,800 --> 01:07:04,960
Speaker 1: Americans have the means if they so choose to seek

1251
01:07:05,000 --> 01:07:08,040
Speaker 1: out some information for themselves. Is why the battles of

1252
01:07:08,080 --> 01:07:11,440
Speaker 1: the future are over who controls these alternative flows of information.

1253
01:07:12,040 --> 01:07:14,880
Speaker 1: I choose to believe people are smart enough to decipher

1254
01:07:14,880 --> 01:07:17,680
Speaker 1: information and interpret it for themselves, no matter what the

1255
01:07:17,720 --> 01:07:20,120
Speaker 1: facts may be. And while things are bleak right now,

1256
01:07:20,200 --> 01:07:22,480
Speaker 1: I do think that eventually, at least I hope so,

1257
01:07:22,720 --> 01:07:25,560
Speaker 1: they will get better. And that's really what annoyed me, Cristal.

1258
01:07:25,600 --> 01:07:28,080
Speaker 1: I've seen a lot of people online point this out

1259
01:07:28,120 --> 01:07:30,280
Speaker 1: as well. They just want to know what was going on.

1260
01:07:30,760 --> 01:07:33,720
Speaker 1: And if you want to hear my reaction to Sagre's monologue,

1261
01:07:33,760 --> 01:07:39,920
Speaker 1: become a premium subscriber today at Breakingpoints dot com. Crystal,

1262
01:07:39,960 --> 01:07:42,080
Speaker 1: what are you taking a look at? Well? Guys? Back

1263
01:07:42,080 --> 01:07:44,600
Speaker 1: when Hillary Clinton was in the midst of her doomed

1264
01:07:44,680 --> 01:07:47,720
Speaker 1: run for resident, her communications director coined a lament that

1265
01:07:47,760 --> 01:07:51,120
Speaker 1: they would employ every time the campaign inevitably crashed into

1266
01:07:51,160 --> 01:07:54,120
Speaker 1: the rocks over and over again. Quote, we are not

1267
01:07:54,200 --> 01:07:56,880
Speaker 1: allowed to have nice things, they would say. After a

1268
01:07:56,880 --> 01:08:00,000
Speaker 1: pandemic and an economic crash collided with a completely toxic

1269
01:08:00,080 --> 01:08:03,000
Speaker 1: political atmosphere and tribal news media seemingly intent on making

1270
01:08:03,040 --> 01:08:05,160
Speaker 1: everything worse. It is a sentiment that much of the

1271
01:08:05,160 --> 01:08:08,800
Speaker 1: American public could likely relate to while watching Hillary this

1272
01:08:08,840 --> 01:08:11,480
Speaker 1: week make her not so triumphant return to the racial

1273
01:08:11,520 --> 01:08:15,480
Speaker 1: Matdow conspiracy Hour. It really hit me from a political perspective.

1274
01:08:15,840 --> 01:08:18,400
Speaker 1: There is maybe no one in the entire country more

1275
01:08:18,439 --> 01:08:21,040
Speaker 1: to blame for offering the current trash state of our

1276
01:08:21,080 --> 01:08:25,680
Speaker 1: politics than one Hillary Rodham Clinton, certainly with regards to

1277
01:08:25,720 --> 01:08:28,840
Speaker 1: the trash state of the Democratic Party. You see, it

1278
01:08:28,920 --> 01:08:30,760
Speaker 1: didn't have to be this way. We didn't have to

1279
01:08:30,760 --> 01:08:34,600
Speaker 1: be trapped in a hellish invented discourse about misinformation and disinformation.

1280
01:08:35,080 --> 01:08:36,800
Speaker 1: We didn't have to spend the last four years of

1281
01:08:36,840 --> 01:08:40,280
Speaker 1: media resources and public attention chasing down and down increasingly

1282
01:08:40,320 --> 01:08:43,760
Speaker 1: insane Russian conspiracies. Democrats didn't have to double down on

1283
01:08:43,760 --> 01:08:46,560
Speaker 1: the same elitism and policy and adequacy that led to

1284
01:08:46,640 --> 01:08:49,400
Speaker 1: their electoral decimation. We didn't have to be stuck with

1285
01:08:49,439 --> 01:08:52,800
Speaker 1: a Reagan era neo lberal relic as president that only

1286
01:08:52,840 --> 01:08:55,439
Speaker 1: seems good when you compare him either to Trump or

1287
01:08:55,479 --> 01:08:58,080
Speaker 1: to the supposed dream team of Kamala Harris and Pete

1288
01:08:58,080 --> 01:09:01,320
Speaker 1: Boodage that were apparently being threatened with. So what the

1289
01:09:01,320 --> 01:09:04,000
Speaker 1: hell happened? We'll brace yourself because I want to play

1290
01:09:04,000 --> 01:09:06,880
Speaker 1: a little clip from the Mattow HRC interview so we

1291
01:09:06,920 --> 01:09:09,400
Speaker 1: can begin to explore how we ended up in such

1292
01:09:09,439 --> 01:09:13,400
Speaker 1: a maddening and terrible place. So Rachel asked Hillary about

1293
01:09:13,400 --> 01:09:16,280
Speaker 1: a recent Atlantic piece arguing that liberal democracy is eroding

1294
01:09:16,320 --> 01:09:19,400
Speaker 1: an autocracy is on the rise. Here's a portion of

1295
01:09:19,439 --> 01:09:23,479
Speaker 1: how Hillary responded. Because I do think that we are

1296
01:09:23,560 --> 01:09:31,200
Speaker 1: facing a crisis of democracy, crisis of legitimacy, a crisis

1297
01:09:31,200 --> 01:09:34,040
Speaker 1: that really goes to the heart of what the future

1298
01:09:34,360 --> 01:09:38,360
Speaker 1: of our country and many others around the world will be.

1299
01:09:39,160 --> 01:09:43,840
Speaker 1: So I spend my time trying to figure out what

1300
01:09:43,880 --> 01:09:47,720
Speaker 1: we can do about it, and I am not ever

1301
01:09:47,760 --> 01:09:50,920
Speaker 1: going to give up, because there's just too much at stake.

1302
01:09:51,840 --> 01:09:55,160
Speaker 1: But first and foremost, we have to make sure more

1303
01:09:55,200 --> 01:09:58,799
Speaker 1: people besides people like you, me An Applebaum and others

1304
01:09:59,280 --> 01:10:04,519
Speaker 1: who share our concerns see what we see, because I

1305
01:10:04,600 --> 01:10:09,360
Speaker 1: think that the role of disinformation, the way that propaganda

1306
01:10:09,439 --> 01:10:15,000
Speaker 1: has been really weaponized, and the increasing ability to manipulate

1307
01:10:15,120 --> 01:10:20,320
Speaker 1: people through algorithms and other forms of artificial intelligence will

1308
01:10:20,360 --> 01:10:26,200
Speaker 1: only make this harder to combat. Now, Rachel asked former

1309
01:10:26,200 --> 01:10:28,639
Speaker 1: Secretary Clinton a question that could have led to any

1310
01:10:28,720 --> 01:10:31,920
Speaker 1: number of places. You might explore the rot of neoliberalism,

1311
01:10:31,920 --> 01:10:34,200
Speaker 1: which has failed to deliver for millions of people, creating

1312
01:10:34,560 --> 01:10:37,839
Speaker 1: vast gulfs of inequality that have left desperate people searching

1313
01:10:37,880 --> 01:10:40,800
Speaker 1: for easy answers. In Strong Men, you could discuss the

1314
01:10:40,880 --> 01:10:43,719
Speaker 1: huge refugee flows triggered by war and by climate change

1315
01:10:43,720 --> 01:10:46,439
Speaker 1: that made it easy for natives to scapegoat immigrants and

1316
01:10:46,479 --> 01:10:49,559
Speaker 1: promise a return to past glory. You could talk about

1317
01:10:49,560 --> 01:10:52,240
Speaker 1: the collapse of traditional centers of meaning, from community to

1318
01:10:52,320 --> 01:10:55,240
Speaker 1: church to family, the degrading of every human being into

1319
01:10:55,240 --> 01:10:57,800
Speaker 1: nothing more than their worth as a consumer. But for

1320
01:10:57,880 --> 01:11:01,000
Speaker 1: Hillary Clinton, the problem is not a of that, it's

1321
01:11:01,040 --> 01:11:05,400
Speaker 1: social media companies, misinformation and disinformation. She would go on

1322
01:11:05,680 --> 01:11:08,679
Speaker 1: to bring up the same topic over and over again,

1323
01:11:08,760 --> 01:11:13,040
Speaker 1: often unprompted, throughout this entire interview. Now, in fairness, Hillary

1324
01:11:13,040 --> 01:11:15,920
Speaker 1: should know a thing or two about misinformation, because ever

1325
01:11:16,000 --> 01:11:18,559
Speaker 1: since the moment she lost her election and doomed us

1326
01:11:18,560 --> 01:11:21,120
Speaker 1: all to four terrible years under Donald Trump, she has

1327
01:11:21,120 --> 01:11:24,800
Speaker 1: been running a very successful propaganda campaign to convince the

1328
01:11:24,800 --> 01:11:28,320
Speaker 1: public that our biggest problem is in fact misinformation, and

1329
01:11:28,360 --> 01:11:30,599
Speaker 1: that the answer to this problem lies in handing more

1330
01:11:30,640 --> 01:11:34,040
Speaker 1: power over to people like Hillary Clinton. I mean this,

1331
01:11:34,160 --> 01:11:37,000
Speaker 1: by the way, very literally. In Jonathan Allen and Amy

1332
01:11:37,000 --> 01:11:40,439
Speaker 1: Parton's book Shattered, they actually detail how Clinton and her

1333
01:11:40,479 --> 01:11:44,679
Speaker 1: team plotted to deflect, blame, and spin their loss how else,

1334
01:11:44,920 --> 01:11:49,479
Speaker 1: by blaming Russian misinformation. Here's the quote. In calls with

1335
01:11:49,520 --> 01:11:52,120
Speaker 1: advisors and political surrogates in the days after the election,

1336
01:11:52,200 --> 01:11:55,320
Speaker 1: Hillary declined to take responsibility for her own loss. Quote.

1337
01:11:55,439 --> 01:11:58,960
Speaker 1: She's not being particularly self reflective, said one longtime ally

1338
01:11:59,000 --> 01:12:01,799
Speaker 1: who was on calls with her after the election. Instead,

1339
01:12:01,880 --> 01:12:05,040
Speaker 1: Hillary kept pointing her finger at Komi and Russia. She

1340
01:12:05,200 --> 01:12:08,160
Speaker 1: wants to make sure all these narratives get spun the

1341
01:12:08,240 --> 01:12:11,360
Speaker 1: right way. This person said that strategy had been set

1342
01:12:11,400 --> 01:12:15,519
Speaker 1: within twenty four hours of her concession speech. Now, muk

1343
01:12:15,600 --> 01:12:18,880
Speaker 1: and Podesta assembled her comms team and at their Brooklyn

1344
01:12:18,920 --> 01:12:21,240
Speaker 1: headquarters to engineer the case that the election was not

1345
01:12:21,479 --> 01:12:24,200
Speaker 1: entirely on the up and up. For a couple of hours,

1346
01:12:24,240 --> 01:12:27,320
Speaker 1: with shakeshat containers littering the room, they went over the

1347
01:12:27,320 --> 01:12:30,080
Speaker 1: script they would pitch to the press and the public. Already,

1348
01:12:30,160 --> 01:12:33,120
Speaker 1: Russian hacking was the centerpiece of the argument. In Brooklyn,

1349
01:12:33,120 --> 01:12:35,920
Speaker 1: her team coalesced around the idea that Russian hacking was

1350
01:12:35,960 --> 01:12:39,559
Speaker 1: the major unreported story of the campaign, overshadowed by the

1351
01:12:39,640 --> 01:12:43,599
Speaker 1: contents of stolen emails and Hilly's Hillary's own private server

1352
01:12:43,800 --> 01:12:46,919
Speaker 1: in broglio, And as far as Hillary Clinton is concerned,

1353
01:12:46,920 --> 01:12:49,400
Speaker 1: the plan to quote make sure all these narratives get

1354
01:12:49,439 --> 01:12:52,679
Speaker 1: spun the right way, Well, that's gone exceedingly well, hasn't it.

1355
01:12:52,720 --> 01:12:55,200
Speaker 1: To use the language of the newly created discourse, they

1356
01:12:55,320 --> 01:12:59,200
Speaker 1: very effectively weaponize misinformation to convince the media and the

1357
01:12:59,200 --> 01:13:02,560
Speaker 1: Democratic base that the biggest national problem was in fact misinformation.

1358
01:13:03,200 --> 01:13:05,599
Speaker 1: Roberr head around that one. Now Here we are five

1359
01:13:05,680 --> 01:13:07,720
Speaker 1: years later, and rather than do a single moment of

1360
01:13:07,720 --> 01:13:10,280
Speaker 1: soul searching about how the Democratic Party could possibly have

1361
01:13:10,400 --> 01:13:13,439
Speaker 1: lost to someone like Donald Trump, Reland ever considered that

1362
01:13:13,520 --> 01:13:15,760
Speaker 1: maybe they should stop running candidates who look like they'd

1363
01:13:15,800 --> 01:13:17,840
Speaker 1: be more comfortable in a modicle and a top at

1364
01:13:18,240 --> 01:13:20,919
Speaker 1: Reland actually try to figure out what the real concerns

1365
01:13:20,920 --> 01:13:23,519
Speaker 1: and issues are for voters. They have instead leveraged all

1366
01:13:23,600 --> 01:13:26,920
Speaker 1: of their messaging and institutional muscle to fret over what

1367
01:13:27,000 --> 01:13:30,479
Speaker 1: moms are saying in boomer Facebook groups. Of course, every

1368
01:13:30,520 --> 01:13:33,639
Speaker 1: liberal media outlet totally obsessed with the topic too. Ben

1369
01:13:33,680 --> 01:13:38,439
Speaker 1: Smith's recent column exposes how top executives at Sanate, NBC News,

1370
01:13:38,720 --> 01:13:42,479
Speaker 1: the ap, Axios, and other major US outlets they've been

1371
01:13:42,479 --> 01:13:45,960
Speaker 1: dialing into Zoom meetings led by Harvard Schorenstein Center on

1372
01:13:46,120 --> 01:13:50,680
Speaker 1: Media to learn how to combat misinformation. Katie Kirk just

1373
01:13:50,800 --> 01:13:55,280
Speaker 1: led an Aspen Institute Commission on Information Disorder, among other

1374
01:13:55,400 --> 01:13:59,560
Speaker 1: luminaries like Facebook's former chief security officer, Kremlin critic and

1375
01:13:59,560 --> 01:14:03,920
Speaker 1: Gary kay Asparov, and Prince Harry. For some reason, Ben

1376
01:14:03,960 --> 01:14:07,240
Speaker 1: Smith himself moderated a quote Truth the k panel at

1377
01:14:07,240 --> 01:14:10,599
Speaker 1: Bloomberg's New Economy Forum. Now, all of these elite actors,

1378
01:14:10,640 --> 01:14:13,759
Speaker 1: from the democratic politicians, the media executives, they love this topic.

1379
01:14:13,880 --> 01:14:16,960
Speaker 1: It's perfect. It doesn't implicate them at all, doesn't require

1380
01:14:17,000 --> 01:14:18,960
Speaker 1: them to give up any of their goodies, and best

1381
01:14:19,000 --> 01:14:22,720
Speaker 1: of all, it hands them even more power as gatekeepers

1382
01:14:22,720 --> 01:14:26,120
Speaker 1: and official arbiters of the truth. After all, the previous

1383
01:14:26,120 --> 01:14:28,439
Speaker 1: controllers of the narrative were feeling a little nervous that

1384
01:14:28,479 --> 01:14:30,880
Speaker 1: the people might be getting ideas of their own and

1385
01:14:30,920 --> 01:14:34,320
Speaker 1: straying from the prescribed program. Legacy media didn't have to

1386
01:14:34,320 --> 01:14:37,000
Speaker 1: be pushed all that hard to embrace the agenda of

1387
01:14:37,080 --> 01:14:40,719
Speaker 1: crushing misinformation. Coming from the people in order to regain

1388
01:14:40,840 --> 01:14:45,840
Speaker 1: their own elite monopoly on misinformation only high class propaganda

1389
01:14:45,880 --> 01:14:49,280
Speaker 1: and conspiracy theories please things like Russia Gate and WMD's

1390
01:14:49,320 --> 01:14:51,880
Speaker 1: and the idea that the stock market is real. So

1391
01:14:52,040 --> 01:14:55,520
Speaker 1: insummation our current hell world of demands for more censorship,

1392
01:14:55,880 --> 01:14:59,360
Speaker 1: lesser evil politics, and a perplexing inability of the Democratic

1393
01:14:59,400 --> 01:15:02,680
Speaker 1: Party to ad us a single real Conservative voters that

1394
01:15:02,840 --> 01:15:06,080
Speaker 1: was all set in motion by HRC it's thanks to

1395
01:15:06,160 --> 01:15:10,000
Speaker 1: an intentional plot hatched by Hillary and her paid operatives

1396
01:15:10,120 --> 01:15:13,000
Speaker 1: to distract the public from their terrible campaign and their

1397
01:15:13,080 --> 01:15:16,439
Speaker 1: even worse candidate, a sigh up which she continues to

1398
01:15:16,680 --> 01:15:19,360
Speaker 1: this very day on one of the most influential political

1399
01:15:19,400 --> 01:15:22,280
Speaker 1: shows out there. And that, my friends, is why we

1400
01:15:22,640 --> 01:15:26,720
Speaker 1: are not allowed to have nice things, sager. Hillary really

1401
01:15:26,760 --> 01:15:28,840
Speaker 1: ran the gamut in that interview. She also made sure

1402
01:15:28,880 --> 01:15:32,880
Speaker 1: to get in some like warhawkish stuff on afghanisty and

1403
01:15:32,920 --> 01:15:35,639
Speaker 1: if you want to hear my reaction to Crystal's monologue,

1404
01:15:35,640 --> 01:15:41,559
Speaker 1: become a premium subscriber today at Breakingpoints dot Com. Joining

1405
01:15:41,640 --> 01:15:45,240
Speaker 1: us now is a Brad Wilcox of the American Enterprise Institute.

1406
01:15:45,280 --> 01:15:48,400
Speaker 1: Longtime friend somebody I found really interesting. Wrote a new

1407
01:15:48,400 --> 01:15:50,559
Speaker 1: piece here. Let's put it up there on the screen,

1408
01:15:50,760 --> 01:15:55,040
Speaker 1: how liberals can be happier. Found it pretty interesting, Brad.

1409
01:15:55,240 --> 01:15:58,000
Speaker 1: We promise it's not a culture war segment. Just welcome

1410
01:15:58,040 --> 01:16:00,439
Speaker 1: to the show. Tell us about what you think here,

1411
01:16:00,479 --> 01:16:02,560
Speaker 1: what do you what are you guys laying out in

1412
01:16:02,640 --> 01:16:05,160
Speaker 1: this piece? You know, we'll stalk. What we see in

1413
01:16:05,200 --> 01:16:08,000
Speaker 1: the research over and over again is that conservatives tend

1414
01:16:08,000 --> 01:16:11,280
Speaker 1: to be happier on average and liberals. And we wanted

1415
01:16:11,320 --> 01:16:12,800
Speaker 1: to kind of look at what's going on here. And

1416
01:16:12,880 --> 01:16:15,200
Speaker 1: there are some scholars who think it's about the way

1417
01:16:15,240 --> 01:16:18,280
Speaker 1: in which consertives might be more happy with inequality or

1418
01:16:18,280 --> 01:16:21,040
Speaker 1: more comfortable, you know, sort of the way things are basically,

1419
01:16:21,360 --> 01:16:23,920
Speaker 1: but it turns out that's actually not what explains this

1420
01:16:24,040 --> 01:16:28,200
Speaker 1: gap between conservatisms. Actually sort of how connected these two

1421
01:16:28,240 --> 01:16:31,400
Speaker 1: groups are to our core institutions in America, things like

1422
01:16:31,520 --> 01:16:35,840
Speaker 1: you know, family, faith, and community. And once we look

1423
01:16:35,840 --> 01:16:39,519
Speaker 1: at those factors in our regression models, we find that

1424
01:16:39,640 --> 01:16:42,439
Speaker 1: those are the things that help to kind of explain

1425
01:16:42,560 --> 01:16:45,719
Speaker 1: the gap. In fact, liberals who are married with kids,

1426
01:16:46,120 --> 01:16:48,439
Speaker 1: who are happy with their families, who are engaged in

1427
01:16:48,439 --> 01:16:53,160
Speaker 1: the religious communities, who are you know, civically involved. These

1428
01:16:53,160 --> 01:16:55,559
Speaker 1: are the liberals who are more likely both men and

1429
01:16:55,640 --> 01:16:58,519
Speaker 1: women to be happy. So there's a kind of basically

1430
01:16:58,520 --> 01:17:01,719
Speaker 1: a path to happiness that run through our core American

1431
01:17:01,760 --> 01:17:06,040
Speaker 1: institutions for both conservatives and for liberals. I thought the

1432
01:17:06,120 --> 01:17:09,080
Speaker 1: piece was really interesting, and as you point out, I mean,

1433
01:17:09,120 --> 01:17:12,200
Speaker 1: this is data is pretty consistent over time that concern.

1434
01:17:12,240 --> 01:17:13,800
Speaker 1: I mean, this is something I'm about for a while

1435
01:17:13,800 --> 01:17:15,960
Speaker 1: that conservitives tend to be happier. I always bought into

1436
01:17:16,000 --> 01:17:19,439
Speaker 1: the ideas because hey, they're more comfortable with the status quo.

1437
01:17:19,560 --> 01:17:22,320
Speaker 1: So liberals are sort of angsting over whatever's going on

1438
01:17:22,360 --> 01:17:24,639
Speaker 1: in the world, and we might count myself in that camp.

1439
01:17:25,560 --> 01:17:27,479
Speaker 1: The part of it that I guess I had a

1440
01:17:27,479 --> 01:17:30,400
Speaker 1: big question about is if religion is a big part

1441
01:17:30,400 --> 01:17:33,240
Speaker 1: of this, Like that's for me not really an answer

1442
01:17:33,360 --> 01:17:35,720
Speaker 1: because I can't make myself believe something that I don't

1443
01:17:35,800 --> 01:17:39,400
Speaker 1: ultimately believe. So there are sort of substitutes for a

1444
01:17:39,520 --> 01:17:46,559
Speaker 1: formal church religion experience that exist in modern America. Yeah, saga, Chris,

1445
01:17:46,600 --> 01:17:48,720
Speaker 1: So I think there is a story here in the

1446
01:17:48,840 --> 01:17:51,920
Speaker 1: data that's about also kind of community life as well.

1447
01:17:52,160 --> 01:17:54,880
Speaker 1: And so what we see in the research with this

1448
01:17:55,040 --> 01:17:58,400
Speaker 1: UGUV survey is that liberal women, for instance, like yourself,

1449
01:17:58,800 --> 01:18:01,400
Speaker 1: who are kind of set us with their community engagement.

1450
01:18:01,400 --> 01:18:03,479
Speaker 1: That could be you know, the local school PTO. It

1451
01:18:03,520 --> 01:18:06,240
Speaker 1: could be you know, being involved in you know, some

1452
01:18:06,360 --> 01:18:09,760
Speaker 1: kind of athletic group with your kids, whatever. If you're

1453
01:18:09,840 --> 01:18:12,200
Speaker 1: kind of engaged in your community in that kind of way,

1454
01:18:12,240 --> 01:18:15,880
Speaker 1: that seems to kind of deliver also a high level

1455
01:18:15,920 --> 01:18:19,920
Speaker 1: of or high level of happiness for women. So let

1456
01:18:19,920 --> 01:18:23,520
Speaker 1: me ask you a more philosophical question, why does happiness

1457
01:18:23,560 --> 01:18:27,120
Speaker 1: matter as a society? Like can we look at and

1458
01:18:27,120 --> 01:18:29,599
Speaker 1: this is what you guys do at the family studies

1459
01:18:29,920 --> 01:18:33,760
Speaker 1: in the issue for family studies, what is good outcomes?

1460
01:18:33,920 --> 01:18:36,559
Speaker 1: Or I guess what outcomes which I might consider good

1461
01:18:36,680 --> 01:18:41,439
Speaker 1: are correlated with happiness for the general population. Well, you know,

1462
01:18:41,680 --> 01:18:45,240
Speaker 1: saga we see in the research is that these kinds

1463
01:18:45,240 --> 01:18:47,559
Speaker 1: of outcomes tend to cluster together in terms of things

1464
01:18:47,600 --> 01:18:51,519
Speaker 1: like happiness, anxiety, and depression. And as both of you

1465
01:18:51,560 --> 01:18:54,240
Speaker 1: are aware, we've seen a big spike in America recently

1466
01:18:54,280 --> 01:18:56,760
Speaker 1: in deaths of despair, you know, which is sort of

1467
01:18:56,800 --> 01:18:59,439
Speaker 1: one manifestation of people kind of losing a sense of

1468
01:18:59,520 --> 01:19:03,679
Speaker 1: purpose direction, and also of course happiness oftentimes as well,

1469
01:19:04,120 --> 01:19:06,880
Speaker 1: and so you know, the story here in part two

1470
01:19:07,000 --> 01:19:09,920
Speaker 1: is that Americans who are able to forge ties you know,

1471
01:19:10,000 --> 01:19:13,439
Speaker 1: in marriage forged ties and religious community or forged ties

1472
01:19:13,479 --> 01:19:17,280
Speaker 1: and some kind of secular local civil institution are much

1473
01:19:17,280 --> 01:19:19,639
Speaker 1: more likely to be kind of flourishing across the board.

1474
01:19:20,640 --> 01:19:23,640
Speaker 1: And happiness is just kind of one indicator of that flourishing.

1475
01:19:24,000 --> 01:19:25,360
Speaker 1: And so I think we need to be thinking about

1476
01:19:25,400 --> 01:19:28,600
Speaker 1: how we're doing as a country and encouraging you know,

1477
01:19:28,640 --> 01:19:33,439
Speaker 1: Americans to plug into these core social institutions today. I mean,

1478
01:19:33,439 --> 01:19:36,840
Speaker 1: that's actually, in its way a provocative and radical notion

1479
01:19:36,960 --> 01:19:39,880
Speaker 1: in this country, especially over the past forty years since

1480
01:19:39,920 --> 01:19:42,320
Speaker 1: the Reagan era, where the priority has really been around

1481
01:19:43,040 --> 01:19:47,000
Speaker 1: profit machanisimization. You know, jobs were shipped overseas as long

1482
01:19:47,000 --> 01:19:48,960
Speaker 1: as it was going to up GDP by a couple

1483
01:19:49,040 --> 01:19:53,080
Speaker 1: of percentage points. And pushing back against that notion of

1484
01:19:53,240 --> 01:19:55,000
Speaker 1: just the free market is the only thing we should

1485
01:19:55,000 --> 01:19:57,960
Speaker 1: care about is actually a value more associated with the

1486
01:19:58,040 --> 01:20:00,400
Speaker 1: left at this point. So as someone who comes from

1487
01:20:00,439 --> 01:20:04,320
Speaker 1: a more conservative perspective, are there sort of economic policy

1488
01:20:04,360 --> 01:20:07,840
Speaker 1: implications or any sort of policy implications that come with

1489
01:20:08,400 --> 01:20:11,800
Speaker 1: a focus and a prioritization of happiness as a nation,

1490
01:20:11,840 --> 01:20:14,400
Speaker 1: which frankly is just not something that we've really focused

1491
01:20:14,400 --> 01:20:17,600
Speaker 1: on for a long time. Well, Chrystal, I think in

1492
01:20:17,680 --> 01:20:19,400
Speaker 1: terms of thinking about economic policy, you need to do

1493
01:20:19,439 --> 01:20:24,120
Speaker 1: a much better job of making it easier for Americans

1494
01:20:24,160 --> 01:20:26,800
Speaker 1: who don't have a college degree and are not on

1495
01:20:26,880 --> 01:20:31,080
Speaker 1: the college track to flourish both in school and in

1496
01:20:31,120 --> 01:20:33,840
Speaker 1: the labor force. And so one concrete idea, for instance,

1497
01:20:33,840 --> 01:20:36,280
Speaker 1: would be to have a wage subsidy, and that would

1498
01:20:36,320 --> 01:20:38,560
Speaker 1: also kind of push us in the direction of a

1499
01:20:38,680 --> 01:20:40,280
Speaker 1: kind of family wage. That would be kind of one

1500
01:20:40,280 --> 01:20:44,439
Speaker 1: way of kind of making an economic policy more family friendly.

1501
01:20:44,760 --> 01:20:47,040
Speaker 1: So that would be sort of one example of the

1502
01:20:47,120 --> 01:20:50,960
Speaker 1: kind of policy measure I'd also would want to stress too,

1503
01:20:51,040 --> 01:20:53,959
Speaker 1: the ways in which currently are are means system programs

1504
01:20:54,000 --> 01:20:57,679
Speaker 1: like Medicaid, for instance, end up penalizing marriage for working

1505
01:20:57,720 --> 01:21:00,519
Speaker 1: class families with kids, making it more are you know,

1506
01:21:00,640 --> 01:21:04,880
Speaker 1: financially difficult to you know, to get married, And so

1507
01:21:04,920 --> 01:21:07,240
Speaker 1: I think we could also think about ways to eliminate

1508
01:21:07,280 --> 01:21:11,400
Speaker 1: that marriage penalty embedded in our mean sessted programs like

1509
01:21:11,520 --> 01:21:17,000
Speaker 1: Medicaid for instance. And what about rethinking our approach and

1510
01:21:17,080 --> 01:21:20,280
Speaker 1: framework work with regards to trade, because one of the

1511
01:21:20,320 --> 01:21:23,120
Speaker 1: things that has decimated so many communities and as far

1512
01:21:23,120 --> 01:21:25,760
Speaker 1: as people out of where they grew up is you know,

1513
01:21:25,840 --> 01:21:27,880
Speaker 1: there's no jobs left there. So the factory that was

1514
01:21:27,920 --> 01:21:29,960
Speaker 1: there when their parents or grandparents that they had a

1515
01:21:30,000 --> 01:21:33,360
Speaker 1: stable middle class life able to support a family that's

1516
01:21:33,400 --> 01:21:37,479
Speaker 1: now gone away. So their implications there as well. Yeah,

1517
01:21:37,840 --> 01:21:39,880
Speaker 1: as you know, I mean, David author and MIT has

1518
01:21:39,920 --> 01:21:42,559
Speaker 1: found that the China trade truck was linked to the

1519
01:21:42,600 --> 01:21:45,360
Speaker 1: loss of about two million jobs in America and that

1520
01:21:45,439 --> 01:21:48,200
Speaker 1: in turn was linked to market declients in marriage and

1521
01:21:48,280 --> 01:21:50,920
Speaker 1: marketing creases in single parenthods. So you know, we have

1522
01:21:50,960 --> 01:21:53,920
Speaker 1: to think about how our trade policies and how our

1523
01:21:53,960 --> 01:21:58,080
Speaker 1: public policies more generally do or do not foster good

1524
01:21:58,120 --> 01:22:01,479
Speaker 1: paying jobs for ordinary Americans. That's certainly also kind of

1525
01:22:01,479 --> 01:22:04,559
Speaker 1: a policy issue to keep on the agenda for thinking

1526
01:22:04,600 --> 01:22:08,559
Speaker 1: about ordinary families across the US. Yeah, and then you

1527
01:22:08,560 --> 01:22:10,360
Speaker 1: know the last thing I have here, Brad, which is,

1528
01:22:10,400 --> 01:22:11,479
Speaker 1: you know, I've been a fan of this and I

1529
01:22:11,560 --> 01:22:14,240
Speaker 1: excited David's paper here on the show in the past

1530
01:22:14,280 --> 01:22:17,240
Speaker 1: as well. But beyond you know, the general policy implication,

1531
01:22:17,840 --> 01:22:20,720
Speaker 1: the mindset shift has to happen. Do you see that

1532
01:22:20,840 --> 01:22:23,960
Speaker 1: happening within the institutional right, or is it still just

1533
01:22:24,000 --> 01:22:28,240
Speaker 1: a very nascent movement, you know, Saga. I do see

1534
01:22:28,640 --> 01:22:32,760
Speaker 1: among younger conservatives a dramatic kind of rethinking about the

1535
01:22:32,800 --> 01:22:36,840
Speaker 1: sort of character of public policy, and sort of they're

1536
01:22:36,880 --> 01:22:39,240
Speaker 1: thinking about economics as well. So there's a much greater

1537
01:22:39,280 --> 01:22:43,519
Speaker 1: concern about thinking through policies that would sort of shore

1538
01:22:43,640 --> 01:22:47,559
Speaker 1: up the economic fortunes of working in middle class families

1539
01:22:48,120 --> 01:22:49,880
Speaker 1: as we go forward. Now, of course, there are still

1540
01:22:49,920 --> 01:22:52,960
Speaker 1: I think, you know, many older conservatives you know, on

1541
01:22:53,000 --> 01:22:56,519
Speaker 1: Capitol Hill and elsewhere, who haven't kind of made that shift,

1542
01:22:56,920 --> 01:22:59,400
Speaker 1: But there's certainly a real openness, and the part of

1543
01:22:59,439 --> 01:23:02,080
Speaker 1: younger concern is to rethinking account of policy with an

1544
01:23:02,080 --> 01:23:05,800
Speaker 1: eye towards strengthening American families. Yeah, I would hope. So,

1545
01:23:06,040 --> 01:23:09,680
Speaker 1: Brad really appreciate your analysis work all of that. Will

1546
01:23:09,680 --> 01:23:11,680
Speaker 1: put links down in the description to look at some

1547
01:23:11,720 --> 01:23:15,000
Speaker 1: of brad works. I've cited many of your studies here

1548
01:23:15,000 --> 01:23:17,040
Speaker 1: in my monologues. I find the work invaluable. So we

1549
01:23:17,080 --> 01:23:19,400
Speaker 1: really appreciate you joining us. Thank you, Yeah, fascinating stuff.

1550
01:23:19,400 --> 01:23:23,080
Speaker 1: Thank you, Brad, Thanks chys, Thanks learn absolutely, thank you

1551
01:23:23,120 --> 01:23:25,800
Speaker 1: guys so much for watching. We really appreciate it you guys,

1552
01:23:25,880 --> 01:23:28,759
Speaker 1: keep us alive here. We are coming up on six months,

1553
01:23:28,800 --> 01:23:32,080
Speaker 1: which is just totally nuts here as a show. As

1554
01:23:32,120 --> 01:23:34,479
Speaker 1: we've said, we've got meetings. Actually we literally won today

1555
01:23:35,000 --> 01:23:38,679
Speaker 1: about bringing on some more people, expanding the show, bringing

1556
01:23:38,680 --> 01:23:41,280
Speaker 1: you guys more content, and laying the groundwork for what

1557
01:23:41,320 --> 01:23:44,000
Speaker 1: we need in order to make sure our midterm coverage

1558
01:23:44,000 --> 01:23:47,360
Speaker 1: and eventually presidential coverage is the absolute best in the business.

1559
01:23:47,479 --> 01:23:49,519
Speaker 1: But we can't do it without your support. I mean,

1560
01:23:49,520 --> 01:23:52,400
Speaker 1: we've noted this a million times, but you know, demodetization

1561
01:23:52,840 --> 01:23:54,760
Speaker 1: really does come for us on a lot of the

1562
01:23:54,800 --> 01:23:58,000
Speaker 1: most controversial topics that we pick, or in the way

1563
01:23:58,040 --> 01:24:00,080
Speaker 1: that we curate our content to make it so but

1564
01:24:00,120 --> 01:24:02,320
Speaker 1: it's the absolute best for you, but makes it so

1565
01:24:02,360 --> 01:24:05,040
Speaker 1: that we don't actually make any money on YouTube. It's fine.

1566
01:24:05,160 --> 01:24:07,160
Speaker 1: We design the business that way. That's why we have

1567
01:24:07,240 --> 01:24:10,519
Speaker 1: a premium subscribers membership and all of that. The link

1568
01:24:10,600 --> 01:24:12,479
Speaker 1: is down in the description. So we really appreciate you

1569
01:24:12,520 --> 01:24:14,479
Speaker 1: can help us so we can continue to grow as

1570
01:24:14,560 --> 01:24:16,400
Speaker 1: big as we can and really just spread the word.

1571
01:24:16,479 --> 01:24:18,680
Speaker 1: So thank you, Love you guys, have a great day,

1572
01:24:18,760 --> 01:24:20,240
Speaker 1: have a great Wednesday. We'll see you back here with

1573
01:24:20,280 --> 01:24:37,560
Speaker 1: a full show on Thursday See Thursday