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

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

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

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

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

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

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Speaker 1: listen to the entire show ad free and uncut, an

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

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

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

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

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

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

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

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Speaker 1: because Crystal is back, so is actually amazing. How are

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Speaker 1: you good to see you? I am good. It is

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Speaker 1: nice to be back. I have to say I started

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Speaker 1: to get a little itchy after I don't do the

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Speaker 1: show for n but Marshall held it down really well.

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Speaker 1: So I did a great job. Fortunate to have a

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Speaker 1: great fill and lots of cool stuff to talk I

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Speaker 1: don't know about cool interesting stuff to talk about today.

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Speaker 1: The Virginia Governor's race always kind of a bellweather of

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Speaker 1: the national mood and one of the only races in

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Speaker 1: the country that happens in these weird off years. So

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Speaker 1: we're going to give you an update on what's going

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Speaker 1: on there. Some really weird, terrible takes on COVID, both

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Speaker 1: from Jimmy Kimmel, also from the ACLU Glenn Greenwad of

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Speaker 1: course all over calling them out for their flip flops

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Speaker 1: on that. We're also going to give you an update

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Speaker 1: on Elizabeth Holmes. She's, of course the former CEO of

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Speaker 1: Fair Nots. On her trial, opening arguments are being opening

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Speaker 1: statements are being made. This week, I've got an update

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Speaker 1: for you on the Mansion crime family. You've got a

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Speaker 1: little media take for is Thomas Sprank, one of my

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Speaker 1: favorite political authors on the planet, is going to be

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Speaker 1: here in the studio. But we wanted to start with

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Speaker 1: what looks to be a very difficult, very bad month

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Speaker 1: for Joe Biden is there's no getting around it, Joe

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Speaker 1: Biden is having probably the worst month of a modern president,

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Speaker 1: actually almost since Barack Obama back in August of two

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Speaker 1: thousand and nine. So let's go ahead and put this

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Speaker 1: up there on the screen. This is from Yugov and

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Speaker 1: Economist's actually quite a good poll, and it shows there

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Speaker 1: that Biden's approval rating is under forty percent for the

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Speaker 1: first time that we've seen in a national So overall

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Speaker 1: you're seeing thirty nine percent approval fifty percent disapproval. But

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Speaker 1: the numbers that I would focus on on are the

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Speaker 1: registered voter number, where he's still at forty three percent

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Speaker 1: and fifty three percent respectively. Amongst Democrats even it's seventy

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Speaker 1: seven and fifteen. Amongst the GOP it's nine to eighty nine.

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Speaker 1: But the independent number there is the one that matters

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Speaker 1: perhaps most above all, thirty five percent approval fifty six

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Speaker 1: percent disapproval. Don't worry, Kamalas still has worse favorable old

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Speaker 1: favorability ratings despite the fact she literally hasn't even done anything.

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Speaker 1: People still have residual memories of her. But Crystal, there's

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Speaker 1: no getting around it, which is that delta Afghanistan, a

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Speaker 1: general lack or a feeling of malaise throughout the country.

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Speaker 1: It's destroying him. I mean, it really is. And I

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Speaker 1: was trying to think about it. I was like, was

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Speaker 1: it Afghanistan specifically? I think what it is is that

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Speaker 1: Biden was elected in order to try and stem the

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Speaker 1: feeling of chaos and to get a hand along COVID

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Speaker 1: and so people. And again, you can fairly blame him

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Speaker 1: or not, but people look at the media coverage in

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Speaker 1: particular of Afghanistan, they see the rising number of DELTA cases.

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Speaker 1: They still see that the partisan tension is at an

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Speaker 1: all time high within the country, and they're well, why

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Speaker 1: aren't you doing your job? And I mean, I sympathize

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Speaker 1: in one way, which is actually quite hard and actually

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Speaker 1: to do anything about that. But there are many things

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Speaker 1: that he could have done in the preceding months in

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Speaker 1: order to try and get a better handle on that

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Speaker 1: have a different orientation on COVID and more So that's

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Speaker 1: just kind of my read on why he's I think,

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Speaker 1: really screwed heading into the midterms. He's really floundering and

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Speaker 1: of course it's always important to remember that Democrats needed

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Speaker 1: to have a historically good performance, like the best in

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Speaker 1: recent history, just in order to hang on to the

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Speaker 1: House and hang on to the Senate. So it was

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Speaker 1: the landscape was always going to be very difficult. Biden

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Speaker 1: has been unwilling to do things like buck the parliamentarian

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Speaker 1: or get rid of the filibuster in order to make

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Speaker 1: the playing field a little more level, especially through redistricting reform.

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Speaker 1: So Democrats walk on to the playing field, so to speak,

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Speaker 1: with a multi point disadvantage going in. Then you're the

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Speaker 1: party in power, and we know historically what happens. You've

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Speaker 1: got the people whose team just lost. I don't know

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Speaker 1: why I'm using all these sports metaphors today, but the

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Speaker 1: Republicans are going to be a lot more fired up

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Speaker 1: because they're pissed off because they're out of power and

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Speaker 1: they want to get their people back in so they

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Speaker 1: feel like they have a sayan government again. That's very motivating,

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Speaker 1: Whereas you know, on the Democrats on the other side,

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Speaker 1: they got rid of Trump, they got their guy in,

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Speaker 1: they went back to brunch, so there's just a lot

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Speaker 1: less energy on that side. With regards to Afghanistan versus

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Speaker 1: other issues. It is interesting I dug into this poll, which,

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Speaker 1: by the way, total side note, they asked a question

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Speaker 1: about like nine to eleven truthers, oh, and there was

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Speaker 1: a third of Americans who were like, the government was

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Speaker 1: probably in on it. Total side note there anyway, Also

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Speaker 1: in this pool, they asked people what their top issues are. Afghanistan,

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Speaker 1: foreign policy is dead. Last number one is healthcare makes sense.

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Speaker 1: Number two is jobs. Number three is climate change. So

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Speaker 1: you have these things coming together of a media that

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Speaker 1: was overwhelmingly awful lot Afghanistan, that just trashed him routine

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Speaker 1: that definitely, he definitely took a hit from that, but

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Speaker 1: you also have this sense that you know, he's not

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Speaker 1: really getting much done at this point. I think that's it.

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Speaker 1: And if you think, you know, we've covered some of

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Speaker 1: these the approach of different countries around the world to COVID,

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Speaker 1: and whether you like those approaches or not, you can

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Speaker 1: kind of articulate what their strategy is. You can articulate

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Speaker 1: what Israel is doing, you can articulate what Australia is doing,

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Speaker 1: and you can articulate what New Zealand is doing, what

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Speaker 1: Sweden is doing. You can't really articulate. Biden hasn't laid

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Speaker 1: out like, here's our plan in our strategy, here's what

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Speaker 1: we're calling it, here's how we're approaching it, here are

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Speaker 1: the milestones. And some of that stuff is just theater.

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Speaker 1: But the other thing that we learned during COVID is

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Speaker 1: when people are in these times of uncertainty and they're

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Speaker 1: trying to figure out our school's going to be open,

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Speaker 1: or my kids at risk? Am I at risk? What's

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Speaker 1: going on in my community? Just having that like we've

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Speaker 1: got this and here's the plan energy it actually really matters.

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Speaker 1: So you saw that at the beginning of his administration,

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Speaker 1: when the vaccine rollout was going well, when they immediately

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Speaker 1: came in right away passed a fairly sizable relief package

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Speaker 1: that hit people's pocketbooks right away. And now over time,

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Speaker 1: as months and months and months have ticked by without

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Speaker 1: further action and without any seeming direction of Okay, this

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Speaker 1: is what we're doing, and these are our priorities, and

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Speaker 1: these are the benchmarks for what we consider success. I

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Speaker 1: think all of those things really weigh on the public

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Speaker 1: in terms of their perception of this president's I think

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Speaker 1: you're right, and I keep pointing to the public health

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Speaker 1: as being the number one issue where he's already receding.

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Speaker 1: He started his presidency with over seventy five percent approval

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Speaker 1: rating on COVID. That's down to fifty. And it's like

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Speaker 1: you said, it's all about the floundering nature of the message.

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Speaker 1: And also Biden just really isn't out there that much.

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Speaker 1: He doesn't speak that much before the camera. He isn't

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Speaker 1: doing a lot of the soothing work that really Trump

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Speaker 1: failed to do whenever he weaponize and make it a

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Speaker 1: culture war, every time there was mass and stuff on lockdowns.

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Speaker 1: Biden promised to do the opposite, but really isn't doing

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Speaker 1: a lot of that. I mostly think that's the reason.

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Speaker 1: And within a vacuum, what rises is opposition. So Amy

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Speaker 1: Walter from the Cook Political Report, let's put this up

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Speaker 1: there on the screen, and it basically just solidifies what

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Speaker 1: you were saying, which is that the biggest worry for

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Speaker 1: Biden and Democrats is that the intensity of opposition to

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Speaker 1: the president is also on the rise while his strong

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Speaker 1: approval has dropped. So an intensity mismatch like this is

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Speaker 1: a big turnout advantage for Republicans, especially in a tight race.

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Speaker 1: And so in those tight Senate races in the battleground states,

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Speaker 1: even in terms of turnout, in terms of where you

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Speaker 1: want to run up the score for, you know, the

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Speaker 1: bigger ones, it's gonna be a problem. And I really

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Speaker 1: do think you're looking at some sort of like twenty

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Speaker 1: ten like phenomenon. That being said, look, there is a

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Speaker 1: long time to go. But what is the one thing

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Speaker 1: that could change his trajectory. It's some piece of large

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Speaker 1: legislation that's not going anywhere. Like Joe Manchin, this came

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Speaker 1: out from Axios. Let's put this up there on the screen,

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Speaker 1: has already come out and said privately actually to Biden.

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Speaker 1: So let's put the Axios tweet there from Jonathan Swan.

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Speaker 1: And what does he talk about, which is that Manchin

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Speaker 1: is privately warning that he won't support more than one

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Speaker 1: point five trillion of Biden's three point five trillion dollar plan.

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Speaker 1: So a flagship piece of legislation from the Biden administration.

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Speaker 1: What he literally had said and considered his legacy is

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Speaker 1: if that is true and Joe Manchin is going to

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Speaker 1: stick to that, then you're talking about only one third

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Speaker 1: in terms of this stuff that could be touted some

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Speaker 1: of the most transformational legislation, which Biden wants to see

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Speaker 1: himself on par with LBJ the Great Society and all that.

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Speaker 1: That's not going to happen at one point five trillion,

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Speaker 1: even paired with the Bipartisan Infrastructure Plan. So pair all

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Speaker 1: this together and Obamacare, which looks very much like what

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Speaker 1: the Reconciliation Plan will end up looking at some sort

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Speaker 1: of like hobnob together thing. Nobody can really tell you

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Speaker 1: what's in it those two thousand pages. All of that

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Speaker 1: together it's going to create the same phenomenon where people

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Speaker 1: are like, yeah, I guess it's all right, and so

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Speaker 1: they're not really going to come out and vote, and

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Speaker 1: then the opposition is just so fear so intense, Yeah,

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Speaker 1: around COVID lockdowns and more's to total disaster. Yeah, I mean,

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Speaker 1: midterms are all about who's going to turn out. So

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Speaker 1: that's why what Amy Walter is pointing out there of

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Speaker 1: Democrats are kind of disengaged. They're like, yeah, the Biden

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Speaker 1: presidency is fine, but are they super motivated to go

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Speaker 1: out to the polls. There's no signs of that. And

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Speaker 1: Republicans on the other side are very motivated and there

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Speaker 1: remember in the early days of the Biden presidency. We

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Speaker 1: kept talking about how he's really not a good villain.

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Speaker 1: They're not doing a good job of making this guy

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Speaker 1: into some sort of like a villainous caricature. And now

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Speaker 1: those numbers of strong disapproval are starting to really harden.

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Speaker 1: When you have every look the individual congressional candidates, what

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Speaker 1: they run on, whether they're good candidates or not. That

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Speaker 1: stuff is almost irrelevant in these days. Every race is

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Speaker 1: completely nationalized. So what's happening at the top, what's happening

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Speaker 1: with the Biden administration, how people feel about that, That's

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Speaker 1: basically the whole ballgame. And as you rightly point out

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Speaker 1: the fact that Manson is digging his heels in, I

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Speaker 1: mean he wrote that op ed as well. Now he

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Speaker 1: looks privately warning. I mean, anytime you see these private

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Speaker 1: warnings leaked, it's because they want this to be written

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Speaker 1: up in the press. Now, look what Democrats are hoping,

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Speaker 1: and what Joe Biden is hoping is that Mansion is

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Speaker 1: posturing for his home state constituency. It's a conservative state. Now, look,

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Speaker 1: you guys know, I think this is all kind of

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Speaker 1: bs because West Virginia is a populous state. West Virginia's

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Speaker 1: a state that could benefit more than anyone from new

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Speaker 1: job creation, from universal pre k, from universal community college,

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Speaker 1: from the child tax credit. But he likes to posture

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Speaker 1: that he's willing to go against his own party and

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Speaker 1: be his own man and be independent minded, etc. Etc.

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Speaker 1: So the question is is this just posturing and pandering

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Speaker 1: to what he thinks people want to hear, or is

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Speaker 1: he actually going to draw a hard line that limits

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Speaker 1: this package to one and a half or even one

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Speaker 1: trillion dollars was the other number that he floated some

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Speaker 1: of the things that he is posing. He's always been,

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Speaker 1: of course skeptical of the climate change provisions. I've pointed

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Speaker 1: out before he heads the committee in the Senate that

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Speaker 1: would be writing a lot of those climate change related provisions.

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Speaker 1: He's also apparently trying a means test, further means test,

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Speaker 1: the child text credit, potentially means test even things like

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Speaker 1: universal pre k, universal community college, trying to pair every

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Speaker 1: single thing back. So meanwhile, you know, the clock is

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Speaker 1: ticking and people feel like they haven't seen a direction

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Speaker 1: from this administration in quite a while, So that's definitely

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Speaker 1: a big problem. The obvious other factor here is that

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Speaker 1: you have a delta variant that continues to be a

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Speaker 1: major issue, especially in parts of the country that have

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Speaker 1: lower vaccination rates. In Florida that has a decently high

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Speaker 1: vaccination rate but has still been hit really, really hard

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Speaker 1: by coronavirus case. There's a lot of speculation about why

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Speaker 1: that is the case. But the sense of optimism that

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Speaker 1: people had, I mean, I know you and I felt

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Speaker 1: this way too. There was the sense of like, Okay,

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Speaker 1: we're beyond this and things are going to be kind

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Speaker 1: of normal, and we're the masters are going to go away,

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Speaker 1: and we're not gonna have to worry about schools closing

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Speaker 1: down and all that stuff. People are now feeling really nervous,

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Speaker 1: really scared, really uncertain, really unhappy, and all of that

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Speaker 1: uncertainty looks some of it's not Biden's fault, but that's

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Speaker 1: the reality of the climate right now. And then you

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Speaker 1: add to that that creates economic uncertainty, that creates, you know,

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Speaker 1: increasing you can have businesses closing or people just even

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Speaker 1: without official government shutdowns. What we learned last time around

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Speaker 1: is what the government tells you in terms of shutdowns,

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Speaker 1: it's almost irrelevant because if people feel nervous, they're not

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Speaker 1: going to go out, They're not going to shop, They're

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Speaker 1: not going to spend money, so that creates problems for

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Speaker 1: people even if you don't have official shutdowns. And layer

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Speaker 1: on top of that, let's put this last tear sheet

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Speaker 1: up on the screen again from well, this is the

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Speaker 1: case count, which you can see is not good. And

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Speaker 1: by the way, that last little dip is I wouldn't

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Speaker 1: take too much heart from that because people oftentimes don't

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Speaker 1: report over labor Day. But you know, we've certainly seen worse.

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Speaker 1: But the situation is not good. The number of deaths

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Speaker 1: and hospitalizations, all those things continuing to rise. So that's

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Speaker 1: a bad situation. But then throw that last hair sheet

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Speaker 1: up on the screen. This is regards to the economic situation.

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Speaker 1: You have increasing economic uncertainty, a recovery that is stalling out,

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Speaker 1: and at the same time, the pandemic era benefits and

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Speaker 1: social safety net that were constructed to help people cope

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Speaker 1: with this crisis are piece by piece going away, the

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Speaker 1: most recent one being that seven million people lost unemployment

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Speaker 1: benefits ironically and horrifyingly on Labor Day. Why because you

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Speaker 1: had in the pandemic era programs unemployment was expanded so

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Speaker 1: that it would cover gig workers and freelancers and contract workers,

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Speaker 1: which is a massive part of the economy. That unemployment

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Speaker 1: should include those people period, whether it's a pandemic or not,

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Speaker 1: it's insane that it doesn't. But Biden didn't push to

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Speaker 1: keep that provision in place, and so you just had

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Speaker 1: millions of Americans lose unemployment benefits at a time where

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Speaker 1: you have increasing economic uncertainty. It's not a good situation. Yeah,

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Speaker 1: and we covered you know, he had the disastrous jobs report.

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Speaker 1: They only added two hundred and fifty two thousand jobs

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Speaker 1: over the labor day or sorry, over the course of

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Speaker 1: August that we expected nine hundred thousand jobs. So which

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Speaker 1: is the second gigantic misses that we've had. Second the

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Speaker 1: big gigantic miss of the Biden administration, and the first

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Speaker 1: really of the delta variants. So you couple all that together,

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Speaker 1: it's a bad situation. And you got no big legislation

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Speaker 1: that's already whatever this is going to be at the

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Speaker 1: most titanic fight in Washington. Saince Obamacare or Tax Cuts

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Speaker 1: and Jobs Act. And you know who knows, it's September ninth,

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Speaker 1: they're coming back next week. We'll see. I doubt anything's

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Speaker 1: really going to pass until like December. Maybe there's a

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Speaker 1: debt ceiling fight, which I'm sure is going to be

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Speaker 1: a nice fight one to Yeah, truly reliving the hits

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Speaker 1: of the Obama years, h Aghanistan, debt ceiling and some

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Speaker 1: you know, cobble together large piece of legislation like this.

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Speaker 1: Couple that together with COVID, Yeah, not good. I mean, really,

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Speaker 1: just to sum it up, you've got a media pylon,

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Speaker 1: you have policy failures, and you have a national climate

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Speaker 1: that some of which is out of his hands that's

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Speaker 1: also really dire. So add those things together and it's

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Speaker 1: it's not a good situation that Biden and the Democrats

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Speaker 1: find themselves in right now. And speaking of that, I

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Speaker 1: mentioned before one of the only races that's happening this

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Speaker 1: year political races is the governor election, gubernatorial election in

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Speaker 1: my home state of Virginia, and it pits Terry mccauliffe, who,

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Speaker 1: of course a long time Bill Clinton friend, DNC fundraiser, dude,

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Speaker 1: very well known, and also happens to have been the

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Speaker 1: former governor of Virginia, where his approval ratings were pretty

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Speaker 1: high when he was governor of Virginia. I mean, obviously

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Speaker 1: he's not really my Cumpty. But Virginia the very suburban state.

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Speaker 1: That's why it's increasingly trended blue. You've got the Northern

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Speaker 1: Virginia suburbs that really dominate voting in the state at

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Speaker 1: this point. When you couple that with the Richmond suburbs

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Speaker 1: and Virginia Beach and the Hampton Roads area, that's essentially

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Speaker 1: what you're talking about in terms of the political makeup

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Speaker 1: of the state. At this point, Democrats have found a

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Speaker 1: very strong base in those Northern Virginia suburbs. Virginia has

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Speaker 1: really become a blue state. I mean, it's dominated by

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Speaker 1: Democrats at this point. You have a Democratic governor, House, Senate,

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Speaker 1: to senators. Everything is Democratic. Obviously went for Biden, and

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Speaker 1: went for Hillary before that, and went for Barack Obama.

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Speaker 1: So this state has increasingly become a reliable one for Democrats. However,

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Speaker 1: this race does not yet seem to be in the

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Speaker 1: bag for Terry mccaulliff. His opponent is like finance guy

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Speaker 1: named Glenn Youngkin, who I have to say is kind

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Speaker 1: of a good fit. Again, none of these people are

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Speaker 1: really like obviously, but this is kind of a good

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Speaker 1: fit for some very suburban electorate. Even if he has

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Speaker 1: more radical positions. He's pretty good at posturing as like

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Speaker 1: a sort of mainstream, suburban type Republican. He just released

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Speaker 1: an internal poll, and again internal polls you should really

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Speaker 1: take with a lot of grains of salt. That showed

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Speaker 1: and we could put this up on the screen, that

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Speaker 1: showed Young Kin with a narrow lead over Terry mccaulliff

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Speaker 1: forty eight, forty six with activists. She's a leftist activist,

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Speaker 1: Princess Blanding receiving three percent, which you know, if those

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Speaker 1: numbers get a little higher, they could be significant here

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Speaker 1: and changing the course of the race. Most of the

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Speaker 1: public polling I've seen has had in five All of

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Speaker 1: the public polling i've seen has had mccaulliffe with an

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Speaker 1: edge here. I still think it is very much Terry

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Speaker 1: mcculliff's race to lose. But the fact that this is

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Speaker 1: even so much in question at this point is again

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Speaker 1: a bad sign for Democrats. I mentioned earlier Young Ken,

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Speaker 1: who wealthy guys poured a ton of money into this race.

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Speaker 1: He also dramatically outspent Terry mccalliff in the early days

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Speaker 1: of this race, and he could be seeing some benefit

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Speaker 1: from that now. We're post Labor Day and both campaigns

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Speaker 1: are going to be pouring lots of cash and that

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Speaker 1: might change the game. But he's trying to lean into

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Speaker 1: this just very like suburban type message. He's trying to

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Speaker 1: distance himself from Trump, who endorsed him, who we really

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Speaker 1: I think wish didn't endorse him ultimately because the former

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Speaker 1: president not popular at all in the state. Here's the

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Speaker 1: type of messaging that young kin is running on. It's

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Speaker 1: not your imagination. Consumer prices are going up, and to

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Speaker 1: make matters worse, Virginia is only one of thirteen states

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Speaker 1: to tax grow. As governor, I will eliminate Virginia's grocery

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Speaker 1: tax career. Politicians will call it radical, but to me,

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Speaker 1: it's just common sense. Because saving a little extra on

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Speaker 1: milk and bread and all of this it adds up.

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Speaker 1: It's time to make it a little easier to live,

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Speaker 1: work and raise a family here in Virginia. People thought

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Speaker 1: about it. It's a little weird that the corn price,

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Speaker 1: for those of you guys who are listening and not watching,

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Speaker 1: it only drops two cents. Not that impressive of a game,

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Speaker 1: but you can see what he's trying to do here.

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Speaker 1: So it's not a bad ad. That's exactly the type

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Speaker 1: of campaign he needs to run. Like you said, at

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Speaker 1: the end of the day, is you're really going to win.

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Speaker 1: It would be hard to see, but Biden's approval rating

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Speaker 1: the national mood of the country and more by trying

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Speaker 1: to tap into those more bipartisan where the independence might join,

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Speaker 1: like on rising prices at the grocery store, or talking

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Speaker 1: about gas tax or you know, talking about the general

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Speaker 1: issues and then lock down the It's another thing that

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Speaker 1: he's been really big on. He's like, I'm a business owner.

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Speaker 1: I've been trying to talk about small business. I could

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Speaker 1: see that possibly resonating. The problem is is that every

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Speaker 1: time he opens his mouth, what does Terry mccaliff say,

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Speaker 1: Radical Glenn Youngin endorsed by Donald Trump? So can you

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Speaker 1: get over that? I don't know it's going to be

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Speaker 1: a good test because, yeah, Glenn Youngin does not want

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Speaker 1: Trump's endorsement. He may say whatever he wants in order

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Speaker 1: for the base to come out, but Trump being in

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Speaker 1: the race is the worst possible thing that could happen

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Speaker 1: to him. That's how Ed Gillespie got clobbered back in

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Speaker 1: twenty seventeen. Because Nova is just overwhelmingly, despite the fact

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Speaker 1: that they have voted Republican some in the past, are

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Speaker 1: just absolutely the constituency that would hate any sort of

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Speaker 1: Trump type candidate. He is uniquely tailored kind of for

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Speaker 1: that environment. So it's interesting. I mean, he released a

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Speaker 1: new list of policy priorities and it's really a lot

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Speaker 1: of the same stuff. It's tax cuts but also new spending,

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Speaker 1: so it's not like nothing pointing towards the groceries tax

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Speaker 1: trying to lean very very hard into the dynamic and

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Speaker 1: the demographic it would be the most hard hit by

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Speaker 1: lockdowns by any sort of stringent public health maneuvers also

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Speaker 1: talking about vaccine mandates, being skeptical of that mass mandates

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Speaker 1: that you know, that is where I do see the

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Speaker 1: most energy on the right that I've seen in such

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Speaker 1: a long time. I mean, I'm recalling that kind of

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Speaker 1: pre tea party era where there were those town halls

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Speaker 1: where the senators went home and it was like a

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Speaker 1: total disaster and there was like, yeah, the screaming and

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Speaker 1: all that. When you go when you look at some

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Speaker 1: of these school board meetings, parents who are against mass

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Speaker 1: mandates very much the same type of energy. It could

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Speaker 1: be cover ship biased, you know, it could be more.

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Speaker 1: I'm not quite sure, you know, because some polls come

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Speaker 1: out and say that parents do support masks in school.

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Speaker 1: But again, is it like a soft support, is it

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Speaker 1: like a sure And then the people who are the

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Speaker 1: most adamantly opposed against it would be the ones who

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Speaker 1: are really going to come out and vote. Trying to

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Speaker 1: read the mood of the country right now is hard.

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Speaker 1: If he were to win, it would be one of

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Speaker 1: the biggest political upsets you'd be up there with like

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Speaker 1: Gavin Newsome actually getting recalled in the next couple of days. Yeah,

429
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Speaker 1: I just I don't know if it is going to happen.

430
00:23:10,920 --> 00:23:13,880
Speaker 1: But looking at his messaging, looking at that poll, that's

431
00:23:13,880 --> 00:23:18,120
Speaker 1: important to say, Wow, this is where things could be trending. Yeah,

432
00:23:19,080 --> 00:23:21,080
Speaker 1: I can kind of make a case either way. On

433
00:23:21,119 --> 00:23:26,160
Speaker 1: the one hand, you do see, unlike at the congressional level,

434
00:23:26,280 --> 00:23:29,320
Speaker 1: at the Senate level, and certainly at the presidential level,

435
00:23:29,760 --> 00:23:34,480
Speaker 1: unlike at the federal level, you do see people making

436
00:23:34,520 --> 00:23:38,960
Speaker 1: sort of less partisan decisions for governor. So then in Kentucky,

437
00:23:39,080 --> 00:23:42,199
Speaker 1: Kentucky lefted a Democratic governor Andy this year. See that

438
00:23:42,240 --> 00:23:45,000
Speaker 1: in Maryland they elected a Republican Larry Hogan, who was

439
00:23:45,119 --> 00:23:47,879
Speaker 1: able to successfully sort of separate himself I think the

440
00:23:47,960 --> 00:23:51,080
Speaker 1: National Republican Party. Now. I will say that Hogan was

441
00:23:51,119 --> 00:23:54,760
Speaker 1: a lot more outspoken in his criticism of Trump. He

442
00:23:54,800 --> 00:23:57,960
Speaker 1: didn't try to play this little habit both ways game,

443
00:23:58,320 --> 00:24:00,960
Speaker 1: which I think voters really kind of hate when they

444
00:24:01,000 --> 00:24:03,840
Speaker 1: can see that, like they can see what you're doing right.

445
00:24:04,720 --> 00:24:07,879
Speaker 1: It reminds me of another Kentucky candidate, Alison Lundergon Grimes,

446
00:24:07,880 --> 00:24:10,800
Speaker 1: who obviously Obama was dramatically unpopular in the state. She

447
00:24:10,840 --> 00:24:13,560
Speaker 1: was running against Mitch McConnell, and they asked her, did

448
00:24:13,600 --> 00:24:16,040
Speaker 1: you vote for Barack Obama? And she just she couldn't answer.

449
00:24:16,119 --> 00:24:17,679
Speaker 1: She basically melted down. I was the hand of her

450
00:24:17,680 --> 00:24:20,320
Speaker 1: campaign because people can see when you're trying to have

451
00:24:20,440 --> 00:24:23,120
Speaker 1: it both ways. He wants to play to the Trump bass,

452
00:24:23,359 --> 00:24:25,359
Speaker 1: but he also wants to appeal to people who find

453
00:24:25,400 --> 00:24:28,720
Speaker 1: Trump to be awful and important in the Northern Virginia suburbs.

454
00:24:29,040 --> 00:24:32,040
Speaker 1: And I do think that that kind of comes through things.

455
00:24:32,280 --> 00:24:38,000
Speaker 1: Very difficult to separate yourself from the national leader of

456
00:24:38,040 --> 00:24:40,360
Speaker 1: a party if you're not willing to just like very

457
00:24:40,359 --> 00:24:45,639
Speaker 1: aggressively and you know, full throated, make do those condemnations

458
00:24:45,680 --> 00:24:49,720
Speaker 1: and do that distancing. He's not willing to go that far.

459
00:24:50,800 --> 00:24:52,720
Speaker 1: On the other hand, like I was saying, you do

460
00:24:52,800 --> 00:24:55,040
Speaker 1: see voters thinking in a little bit less of a

461
00:24:55,080 --> 00:24:59,480
Speaker 1: sort of partisan way at the goubernatorial level. You know,

462
00:24:59,600 --> 00:25:05,280
Speaker 1: you see Massachusetts, Vermont with Republican governors. So it's certainly possible.

463
00:25:05,880 --> 00:25:09,400
Speaker 1: Kyle Condick, who was with Larry Sabbadet's Crystal Ball down

464
00:25:09,440 --> 00:25:12,400
Speaker 1: at UVA, he noted a while back that to win,

465
00:25:13,080 --> 00:25:15,760
Speaker 1: could young Kin would need to do ten plus points

466
00:25:15,840 --> 00:25:18,639
Speaker 1: better than Trump did in Virginia last year, which is

467
00:25:18,680 --> 00:25:22,800
Speaker 1: a tall order. However, that sort of improvement is actually

468
00:25:22,880 --> 00:25:27,959
Speaker 1: common in Virginia for non presidential party gubernatorial candidates, So

469
00:25:28,080 --> 00:25:31,639
Speaker 1: it's certainly not without historical precedent. Again, why are we

470
00:25:31,720 --> 00:25:34,560
Speaker 1: watching this so closely other than I live in Virginia

471
00:25:34,600 --> 00:25:36,280
Speaker 1: so it kind of matters to me personally who the

472
00:25:36,320 --> 00:25:41,399
Speaker 1: governor is. But Virginia has been kind of a Bellweather Creed.

473
00:25:41,440 --> 00:25:43,879
Speaker 1: Deeds went up against Bob he was a Democrat, went

474
00:25:43,960 --> 00:25:46,240
Speaker 1: up against Bob McDonald back in two thousand and nine.

475
00:25:46,720 --> 00:25:52,400
Speaker 1: Deeds got destroyed, Like, wasn't even close. Bob McDonald wins

476
00:25:52,520 --> 00:25:54,320
Speaker 1: in two thousand and nine, and that was really a

477
00:25:54,359 --> 00:25:57,080
Speaker 1: sort of canary in the coal mine for the Tea

478
00:25:57,119 --> 00:25:59,600
Speaker 1: Party era, and that's why you're cantor loss too. That

479
00:25:59,640 --> 00:26:02,600
Speaker 1: was another that was Yeah, that's true. That's a great point.

480
00:26:02,640 --> 00:26:05,639
Speaker 1: That's another big one. Then you had Terry mccalluff and

481
00:26:05,640 --> 00:26:09,080
Speaker 1: you had Ralph Northam kind of presaging again this suburban

482
00:26:09,280 --> 00:26:13,640
Speaker 1: move among the country towards Democrats. So this is one

483
00:26:13,680 --> 00:26:17,440
Speaker 1: to watch if Youngkin pulls up off an upset here,

484
00:26:17,960 --> 00:26:22,720
Speaker 1: which would again, he's definitely he's definitely the underdog. I

485
00:26:22,760 --> 00:26:25,919
Speaker 1: still think this is Terry mccalliff's race to lose overwhelmingly,

486
00:26:26,359 --> 00:26:28,920
Speaker 1: but if he was able to pull off an upset,

487
00:26:29,080 --> 00:26:34,399
Speaker 1: that would be a disastrous sign for Democrats. So this

488
00:26:34,520 --> 00:26:36,600
Speaker 1: is definitely one to watch. It also the House and

489
00:26:36,640 --> 00:26:38,520
Speaker 1: the Senate or at stake right now too, so those

490
00:26:38,600 --> 00:26:40,960
Speaker 1: races will be interesting to keep an eye on as well. Yeah,

491
00:26:41,000 --> 00:26:43,160
Speaker 1: that's right. Hey, So remember how we told you how

492
00:26:43,200 --> 00:26:46,199
Speaker 1: awesome premium membership was, Well, here we are again to

493
00:26:46,280 --> 00:26:49,040
Speaker 1: remind you that becoming a premium member means you don't

494
00:26:49,080 --> 00:26:52,320
Speaker 1: have to listen to our constant please for you to subscribe.

495
00:26:52,600 --> 00:26:54,800
Speaker 1: So what are you waiting for? Become a Premium member

496
00:26:54,840 --> 00:26:57,320
Speaker 1: today by going to Breakingpoints dot com, which you can

497
00:26:57,359 --> 00:27:00,199
Speaker 1: click on in the show notes. All right, we've have

498
00:27:00,240 --> 00:27:06,480
Speaker 1: some extremely cringe, I would say sociopathic takes on vaccines

499
00:27:06,760 --> 00:27:09,000
Speaker 1: coming from a variety of corners. We like to keep

500
00:27:09,040 --> 00:27:12,520
Speaker 1: you updated on the worst takes all around with regards

501
00:27:12,560 --> 00:27:17,080
Speaker 1: to coronavirus, vaccines, masks, and all the rest. Latest addition

502
00:27:17,359 --> 00:27:20,520
Speaker 1: involves our friend Jimmy Kimmel. Let's take a listen to

503
00:27:20,600 --> 00:27:22,640
Speaker 1: what he had to say. The number of new cases

504
00:27:22,720 --> 00:27:25,480
Speaker 1: is up more than three hundred percent from a year ago.

505
00:27:25,800 --> 00:27:28,760
Speaker 1: Doctor Fauci said that if hospitals get any more over crowded,

506
00:27:28,760 --> 00:27:30,680
Speaker 1: they're going to have to make some very tough choices

507
00:27:31,000 --> 00:27:33,760
Speaker 1: about who gets an ICU. Bet of that joy doesn't

508
00:27:33,760 --> 00:27:36,960
Speaker 1: seem so tough to me. Vaccinated person having a heart attack, Yes,

509
00:27:36,960 --> 00:27:39,560
Speaker 1: come right on him, We'll take care of you. Unvaccinated

510
00:27:39,680 --> 00:27:43,320
Speaker 1: guy who gobbled horse goo rest in peace. Wheezy you'r

511
00:27:44,200 --> 00:27:50,640
Speaker 1: that's hilarious. That's sick, cheering for people's deaths, so funny,

512
00:27:50,880 --> 00:27:52,919
Speaker 1: great humor. I mean, this is just part of a

513
00:27:52,920 --> 00:27:58,600
Speaker 1: trend that we've seen of people believing that if you

514
00:27:58,720 --> 00:28:01,520
Speaker 1: don't get the vaccine, you actually deserved to die, and

515
00:28:01,560 --> 00:28:03,639
Speaker 1: that we should cheer for that and deny healthcare and

516
00:28:03,640 --> 00:28:06,720
Speaker 1: deny people healthcare. I mean, I was I'm still floored

517
00:28:06,800 --> 00:28:10,200
Speaker 1: by this doctor that went on MSNBC received zero pushback

518
00:28:10,240 --> 00:28:13,560
Speaker 1: when they were like, yeah, if you don't have the vaccine,

519
00:28:13,600 --> 00:28:16,520
Speaker 1: then you shouldn't get healthcare. I mean, again, from people

520
00:28:16,560 --> 00:28:20,520
Speaker 1: who supposedly support universal health care and healthcare is a

521
00:28:20,600 --> 00:28:24,360
Speaker 1: human right, that's just horrifying. Jimmy Kimmel was famous, and

522
00:28:24,840 --> 00:28:26,919
Speaker 1: I went back and I checked the dates. May of

523
00:28:26,960 --> 00:28:31,400
Speaker 1: twenty seventeen, remember, and look, God bless him. His baby

524
00:28:31,480 --> 00:28:35,040
Speaker 1: had heart surgery and it was heart wrenching experience for him.

525
00:28:35,400 --> 00:28:38,600
Speaker 1: He had to go through this nightmare. I thought his son,

526
00:28:38,800 --> 00:28:42,520
Speaker 1: little baby was gonna die. But he parlayed that by

527
00:28:42,560 --> 00:28:45,280
Speaker 1: working with Chuck Schumer's office and more in order to

528
00:28:45,320 --> 00:28:50,239
Speaker 1: push for not repealing and replacing Obamacare. Right, let's all

529
00:28:50,280 --> 00:28:54,440
Speaker 1: remember that. So Kimmel himself made all of these emotional

530
00:28:54,480 --> 00:28:59,160
Speaker 1: pleas and talks about wanting and needing affordable healthcare, the

531
00:28:59,280 --> 00:29:01,600
Speaker 1: need to have a better health care system. He says,

532
00:29:01,640 --> 00:29:04,280
Speaker 1: I cannot believe that some people have to go through

533
00:29:04,320 --> 00:29:08,320
Speaker 1: this without health care. He is actually talking about what

534
00:29:08,400 --> 00:29:11,040
Speaker 1: these none of these all these people are saying they

535
00:29:11,120 --> 00:29:15,680
Speaker 1: want to repeal the core tenant of Obamacare, which made

536
00:29:15,680 --> 00:29:18,480
Speaker 1: it so that you can't deny people health care based

537
00:29:18,560 --> 00:29:22,360
Speaker 1: on pre existing conditions. So which is it? Are you

538
00:29:22,520 --> 00:29:27,360
Speaker 1: for actually providing people real health care regardless of some circumstance.

539
00:29:27,600 --> 00:29:29,720
Speaker 1: And once you open this door, it's so funny to

540
00:29:29,720 --> 00:29:32,640
Speaker 1: be watching this because it's a libertarian dream. They've always

541
00:29:32,720 --> 00:29:35,920
Speaker 1: wanted to have health care be able to deny to

542
00:29:35,960 --> 00:29:38,520
Speaker 1: people with diabetes, to people who are fat, people with

543
00:29:38,640 --> 00:29:42,200
Speaker 1: BMI over like twenty five, or charge them more, or

544
00:29:42,240 --> 00:29:43,880
Speaker 1: make it so that if you engage, if you eat

545
00:29:43,880 --> 00:29:46,040
Speaker 1: at McDonald's, you know, like once a week or whatever

546
00:29:46,080 --> 00:29:48,680
Speaker 1: that mayleans, you have to charge more of your health care.

547
00:29:48,880 --> 00:29:51,640
Speaker 1: I think exactly. I think that's immoral. You know why,

548
00:29:51,760 --> 00:29:54,440
Speaker 1: because people get raised in all sorts of different conditions,

549
00:29:54,600 --> 00:29:56,080
Speaker 1: and it makes it so that when they get sick,

550
00:29:56,240 --> 00:29:57,959
Speaker 1: they need to make sure or we need to make

551
00:29:58,000 --> 00:29:59,959
Speaker 1: sure that somebody is actually gonna go ahead and take

552
00:30:00,080 --> 00:30:02,440
Speaker 1: care of them. What he's talking about is some sort

553
00:30:02,560 --> 00:30:07,480
Speaker 1: of deeply libertarian fantasy of being able to deny people

554
00:30:07,520 --> 00:30:12,280
Speaker 1: healthcare based upon their past previous choices. If we treat alcoholics,

555
00:30:12,360 --> 00:30:14,880
Speaker 1: which I think we should, if we treat people who

556
00:30:14,920 --> 00:30:17,600
Speaker 1: are addicted to drugs, which I think they should, which

557
00:30:17,640 --> 00:30:20,280
Speaker 1: we should. Should we not also do the same if

558
00:30:20,320 --> 00:30:22,920
Speaker 1: you're gonna make the choice not to get the vaccine,

559
00:30:23,000 --> 00:30:26,880
Speaker 1: of course, I mean, I cannot think of anything more

560
00:30:26,960 --> 00:30:30,360
Speaker 1: abhorrent than pushing this type of stuff. And yet the

561
00:30:30,400 --> 00:30:35,760
Speaker 1: weaponization of all of this by elite media spaces is terrible.

562
00:30:35,800 --> 00:30:38,160
Speaker 1: I mean, Brian Stelter, you know the great you know

563
00:30:38,240 --> 00:30:41,120
Speaker 1: CNN media janitor. He tweeted this out and it is

564
00:30:41,160 --> 00:30:44,040
Speaker 1: incredibly revealing. Let's put this up on screen. He says, quote,

565
00:30:44,080 --> 00:30:48,479
Speaker 1: an unvaccinated minority that doesn't watch the news or trust

566
00:30:48,520 --> 00:30:52,280
Speaker 1: the news is putting the vaccinated majority at undue risk.

567
00:30:52,600 --> 00:30:55,479
Speaker 1: There's no way around that reality. Now. Number one, of

568
00:30:55,480 --> 00:30:57,640
Speaker 1: course he has to make it about the news. But

569
00:30:57,720 --> 00:30:59,959
Speaker 1: number two, how do you think it got there? Brian?

570
00:31:00,280 --> 00:31:02,880
Speaker 1: How did we get to this point? Why do so

571
00:31:03,000 --> 00:31:05,640
Speaker 1: many people not trust the news? Why do so many

572
00:31:05,640 --> 00:31:07,760
Speaker 1: people not trust what you have to say? Why do

573
00:31:07,880 --> 00:31:11,280
Speaker 1: so many people not trust? Maybe MSNBC who has a

574
00:31:11,320 --> 00:31:14,960
Speaker 1: doctor on who says, screw those people? I as a doctor,

575
00:31:15,120 --> 00:31:17,600
Speaker 1: am I going to go ahead and deny that in healthcare.

576
00:31:17,800 --> 00:31:20,160
Speaker 1: You put all that together, I have a pretty easy

577
00:31:20,200 --> 00:31:22,560
Speaker 1: an answer for you, but they don't want to hear

578
00:31:22,600 --> 00:31:25,760
Speaker 1: that real answer. That's that's the great tragedy of this all. Yeah,

579
00:31:25,840 --> 00:31:28,200
Speaker 1: it is funny because in that tweet, it's like he

580
00:31:28,280 --> 00:31:32,440
Speaker 1: almost gets it. It's like, yeah, they don't trust the news.

581
00:31:33,520 --> 00:31:36,360
Speaker 1: Think about that, Brian, why do you think that could be?

582
00:31:36,840 --> 00:31:38,920
Speaker 1: What do you think? I mean, even in the past

583
00:31:38,960 --> 00:31:42,000
Speaker 1: few weeks, we have perfect examples from like let's bring

584
00:31:42,040 --> 00:31:44,280
Speaker 1: on John Bolton to talk about why we should stay

585
00:31:44,280 --> 00:31:47,960
Speaker 1: in Afghanistan for forever. Well, let's publish a Kandie Rice

586
00:31:48,080 --> 00:31:52,000
Speaker 1: outed or make the same case. I mean, like they

587
00:31:52,120 --> 00:31:56,840
Speaker 1: just embarrass and lie and propagandaize at every single turn,

588
00:31:57,400 --> 00:31:59,760
Speaker 1: and then we can tune into you know, Chris Kuoo

589
00:32:00,240 --> 00:32:03,840
Speaker 1: covering his brother's scandals, and then you're like, they don't

590
00:32:03,920 --> 00:32:07,080
Speaker 1: trust us. It's their fault, right, It's all on them.

591
00:32:07,400 --> 00:32:09,600
Speaker 1: It's actually something we're going to talk to Thomas frank

592
00:32:09,640 --> 00:32:13,160
Speaker 1: about because he comes from a left perspective but is

593
00:32:13,200 --> 00:32:16,400
Speaker 1: really good on this, which is that the media and

594
00:32:16,920 --> 00:32:22,000
Speaker 1: the political class, rather than focusing on like why is

595
00:32:22,040 --> 00:32:24,760
Speaker 1: it that there're such a large proportion of Americans that

596
00:32:24,880 --> 00:32:27,320
Speaker 1: don't trust the government and don't trust the media, and

597
00:32:27,360 --> 00:32:30,560
Speaker 1: so we're very skeptical of the vaccines. All of the

598
00:32:30,560 --> 00:32:33,560
Speaker 1: blame gets put on the individual people. Yes, it's this

599
00:32:33,800 --> 00:32:40,960
Speaker 1: very individualistic, sort of like bootstrapsy personal responsibility narrative applied

600
00:32:41,040 --> 00:32:45,920
Speaker 1: to a global pandemic and all used to again convince people.

601
00:32:46,000 --> 00:32:50,720
Speaker 1: It's weaponized to convince people that your average American is stupid,

602
00:32:50,880 --> 00:32:53,480
Speaker 1: they can't be trusted, they should be held in contempt,

603
00:32:53,840 --> 00:32:58,040
Speaker 1: and we the elites, we're the smart ones, we understand

604
00:32:58,080 --> 00:33:01,640
Speaker 1: the science. Just trust us and we'll handle this for you.

605
00:33:01,840 --> 00:33:05,120
Speaker 1: So that's why this type of thinking is so dangerous,

606
00:33:05,240 --> 00:33:08,000
Speaker 1: and you know, it also speaks to Liz Brunan had

607
00:33:08,000 --> 00:33:10,920
Speaker 1: a great piece about this, again from a left perspective, saying,

608
00:33:11,200 --> 00:33:15,720
Speaker 1: don't cheerlead the deaths of people who didn't get vaccinated.

609
00:33:16,120 --> 00:33:19,720
Speaker 1: There's such a lack of any sort of culture of

610
00:33:20,240 --> 00:33:25,800
Speaker 1: tolerance or forgiveness, or humility or care and concern. All

611
00:33:25,840 --> 00:33:29,840
Speaker 1: of the sort of clout and status is gained by

612
00:33:30,360 --> 00:33:34,680
Speaker 1: picking someone out and shaming them and deriding them and

613
00:33:34,760 --> 00:33:40,000
Speaker 1: cheerleading their literal death. And that's just a disgusting, immoral

614
00:33:40,040 --> 00:33:44,200
Speaker 1: direction to go in and it's also completely counter to

615
00:33:44,280 --> 00:33:49,720
Speaker 1: what any sort of liberal or progressive or left ideology

616
00:33:50,120 --> 00:33:52,800
Speaker 1: actually looks like and stands for. And look, that's what

617
00:33:52,880 --> 00:33:54,680
Speaker 1: screwed us in the beginning. And I'm not you know,

618
00:33:54,800 --> 00:33:57,440
Speaker 1: we're not putting anybody off. The Trump is the one

619
00:33:57,520 --> 00:34:00,520
Speaker 1: responsible for a lot of this, which is that bipolling

620
00:34:00,960 --> 00:34:05,440
Speaker 1: the entire electorate along coronavirus restrictions. We are the only

621
00:34:05,520 --> 00:34:11,319
Speaker 1: developed country on Earth which actually got more disunited during

622
00:34:11,320 --> 00:34:14,200
Speaker 1: a pandemic, the only one every single other country you

623
00:34:14,239 --> 00:34:17,839
Speaker 1: saw mass coalescing around the leader. Yes, there is some

624
00:34:17,880 --> 00:34:22,920
Speaker 1: dissatisfaction France, Britain, across the Western world, not even close

625
00:34:23,080 --> 00:34:25,880
Speaker 1: to the madness that we have here. But when you

626
00:34:25,920 --> 00:34:28,560
Speaker 1: live within that dynamic and you're Biden or you're the media,

627
00:34:28,600 --> 00:34:30,200
Speaker 1: and you claim that Trump was the one who was

628
00:34:30,239 --> 00:34:32,360
Speaker 1: doing this, well, they have just as much of a

629
00:34:32,440 --> 00:34:35,560
Speaker 1: role and they're not relinquishing that role. And that's why

630
00:34:35,680 --> 00:34:37,520
Speaker 1: I want to point to this to say that it

631
00:34:37,600 --> 00:34:40,759
Speaker 1: is probably the single worst thing that you could do

632
00:34:40,880 --> 00:34:43,319
Speaker 1: to confirm the fears of a lot of these people

633
00:34:43,360 --> 00:34:45,440
Speaker 1: who don't trust the system and who don't want to

634
00:34:45,440 --> 00:34:47,759
Speaker 1: get a vaccine. A lot of them look at it

635
00:34:47,880 --> 00:34:51,840
Speaker 1: as the road too, even more so onerous restrictions and

636
00:34:51,920 --> 00:34:54,040
Speaker 1: say by the government and what you should and should

637
00:34:54,080 --> 00:34:56,239
Speaker 1: not do. The booster shot is a good example, which

638
00:34:56,280 --> 00:34:59,440
Speaker 1: is that look at the booster roll out, total disaster.

639
00:35:00,000 --> 00:35:02,480
Speaker 1: It came out and they said everybody needs a booster

640
00:35:02,840 --> 00:35:05,920
Speaker 1: After six months, then the New York Times reports that

641
00:35:05,960 --> 00:35:09,040
Speaker 1: the Biden administration got out ahead of its skis and

642
00:35:09,360 --> 00:35:12,799
Speaker 1: that they may have to revise the booster recommendation. So

643
00:35:12,960 --> 00:35:16,799
Speaker 1: which is it? And then they say that actually there

644
00:35:16,800 --> 00:35:20,879
Speaker 1: were two career FDA officials who resigned from the administration

645
00:35:21,360 --> 00:35:25,240
Speaker 1: over this entire thing around boosters. If that had happened

646
00:35:25,280 --> 00:35:28,360
Speaker 1: under Trump, I think we all know how the reporting

647
00:35:28,440 --> 00:35:31,040
Speaker 1: exactly would have gone. So you look at that all

648
00:35:31,080 --> 00:35:34,160
Speaker 1: together and you say, well, what is happening here or

649
00:35:34,200 --> 00:35:36,719
Speaker 1: what about for somebody like me? I got vaccinated? Now

650
00:35:36,880 --> 00:35:38,600
Speaker 1: code do I need a booster shot? I don't know.

651
00:35:38,680 --> 00:35:40,279
Speaker 1: I mean, he is the government going to tell me

652
00:35:40,320 --> 00:35:43,080
Speaker 1: that should it only be for people who are over

653
00:35:43,160 --> 00:35:46,719
Speaker 1: sixty five? Should it be for people who are immunal compromised?

654
00:35:47,440 --> 00:35:50,160
Speaker 1: The way they have set and rolled out each of

655
00:35:50,200 --> 00:35:55,439
Speaker 1: these recommendations has had absolute disaster. Same thing Chrystal's looking

656
00:35:55,440 --> 00:35:57,880
Speaker 1: at Johnson and Johnson. Do you remember that Johnson and

657
00:35:57,920 --> 00:36:00,719
Speaker 1: Johnson pause which we were talking about how it was

658
00:36:00,760 --> 00:36:03,719
Speaker 1: going to be a disaster. There had been an exponential

659
00:36:03,760 --> 00:36:06,640
Speaker 1: increase in the number of vaccine appointments and for every

660
00:36:06,640 --> 00:36:09,400
Speaker 1: single day until which date, Which date you can go

661
00:36:09,440 --> 00:36:11,279
Speaker 1: and you can track it the exact day that they

662
00:36:11,280 --> 00:36:14,040
Speaker 1: put the pause on Johnson and Johnson. That was, as

663
00:36:14,080 --> 00:36:16,760
Speaker 1: we predicted at the time, one of the biggest gifts

664
00:36:16,760 --> 00:36:19,080
Speaker 1: to the anti vaxxers that you could have ever had.

665
00:36:19,320 --> 00:36:21,880
Speaker 1: So we need to have a lot more talk and

666
00:36:21,960 --> 00:36:25,759
Speaker 1: discussion around the way that they themselves have failed to

667
00:36:25,840 --> 00:36:29,080
Speaker 1: communicate all of this to be if I can't understand

668
00:36:29,120 --> 00:36:32,480
Speaker 1: the booster, how is somebody who is going about their

669
00:36:32,560 --> 00:36:34,480
Speaker 1: day to day life and this is the only podcast

670
00:36:34,560 --> 00:36:36,760
Speaker 1: or show that they listen to. What are they supposed

671
00:36:36,800 --> 00:36:38,719
Speaker 1: to do? You know, it's my job to sort through

672
00:36:38,719 --> 00:36:40,920
Speaker 1: all that information for them. That's the problem that we

673
00:36:40,960 --> 00:36:44,520
Speaker 1: have right now. Yeah, And because this has been politically

674
00:36:44,680 --> 00:36:47,160
Speaker 1: polarized from the very beginning, and I do think you're

675
00:36:47,239 --> 00:36:49,120
Speaker 1: right to place a lot of the blame for that

676
00:36:49,480 --> 00:36:52,600
Speaker 1: in so like making it terrible from the jump, A

677
00:36:52,640 --> 00:36:54,880
Speaker 1: lot of that lies at the feet of Donald Trump.

678
00:36:55,400 --> 00:37:00,520
Speaker 1: Because we've had this polarized reaction, I'm actually convinced that

679
00:37:00,719 --> 00:37:04,440
Speaker 1: this sort of middle course is the correct course in

680
00:37:04,520 --> 00:37:08,719
Speaker 1: terms of COVID. Schools should be open. We should be

681
00:37:09,200 --> 00:37:13,560
Speaker 1: encouraging very strongly and using various tools that are I

682
00:37:13,600 --> 00:37:17,160
Speaker 1: supposed to get people vaccinated. We should I mean masks

683
00:37:17,200 --> 00:37:19,120
Speaker 1: are not masks is probably not that big of a

684
00:37:19,160 --> 00:37:22,279
Speaker 1: deal at this point. They work. Sure, if you're an

685
00:37:22,280 --> 00:37:25,160
Speaker 1: indoor setting that's really close, good to wear them. Outdoors

686
00:37:25,200 --> 00:37:27,680
Speaker 1: you definitely, you know, are going to be fine without them.

687
00:37:28,600 --> 00:37:32,319
Speaker 1: A sort of reasoned middle approach is what's called for.

688
00:37:32,719 --> 00:37:37,800
Speaker 1: And because you've had this political polarization over coronavirus, nobody

689
00:37:37,880 --> 00:37:40,960
Speaker 1: is basically falling. Everybody's at the extremes. You've got the

690
00:37:41,040 --> 00:37:43,879
Speaker 1: extreme like I've never I hate Ma'm never gonna wear

691
00:37:43,880 --> 00:37:47,640
Speaker 1: a mask, and like any sort of restriction is an

692
00:37:47,680 --> 00:37:51,360
Speaker 1: infringement on my liberty and I'm never gonna get a vaccine.

693
00:37:51,400 --> 00:37:54,040
Speaker 1: You've got this like extreme reaction over here, and then

694
00:37:54,080 --> 00:37:56,799
Speaker 1: you have an extreme reaction over here. That's like there

695
00:37:56,880 --> 00:37:59,839
Speaker 1: was one case three counties over we got to shut

696
00:37:59,880 --> 00:38:02,440
Speaker 1: down on the school. We got to go back into lockdown.

697
00:38:02,480 --> 00:38:06,120
Speaker 1: We got a double mask. And so both of these

698
00:38:06,280 --> 00:38:10,719
Speaker 1: are you know, one is vastly overestimating the risk to themselves,

699
00:38:10,840 --> 00:38:13,719
Speaker 1: especially since those people in that camp are all vaccinated.

700
00:38:14,000 --> 00:38:17,719
Speaker 1: This one is dramatically underestimating the risk to themselves and

701
00:38:17,760 --> 00:38:22,279
Speaker 1: to their communities. And because it's become so polarized, there's

702
00:38:22,640 --> 00:38:26,560
Speaker 1: very very few, certainly public officials, but very few people

703
00:38:26,600 --> 00:38:31,239
Speaker 1: in general who are taking just sort of like a reasoned,

704
00:38:31,760 --> 00:38:35,560
Speaker 1: moderate risk assessment type approach because what's been rewarded in

705
00:38:35,600 --> 00:38:39,239
Speaker 1: our political system is like all in are all out,

706
00:38:39,440 --> 00:38:42,720
Speaker 1: and it's made it so it's very hard to respond

707
00:38:42,760 --> 00:38:46,319
Speaker 1: to this thing effectively. Yeah, and speaking of you know,

708
00:38:46,680 --> 00:38:50,200
Speaker 1: going all in or all out, the culture warification of

709
00:38:50,239 --> 00:38:52,200
Speaker 1: all of this is a story that we like to

710
00:38:52,200 --> 00:38:55,160
Speaker 1: stick to the ACLU. So let's go ahead and put

711
00:38:55,200 --> 00:38:57,440
Speaker 1: this up there on the screen from Glenn Greenwald. He

712
00:38:57,480 --> 00:39:00,359
Speaker 1: did a very good report here, which is that the ACU,

713
00:39:00,680 --> 00:39:07,040
Speaker 1: prior to COVID denounced mandates and coercive measures to fight pandemics. Now,

714
00:39:07,160 --> 00:39:09,400
Speaker 1: in a New York Times op ed, they have completely

715
00:39:09,440 --> 00:39:13,279
Speaker 1: reversed their view. So let's go back and look exactly

716
00:39:13,560 --> 00:39:17,319
Speaker 1: at what the ACLU had previously talked about. Now, what

717
00:39:17,360 --> 00:39:19,680
Speaker 1: they had said is that pandemic preparedness, the need for

718
00:39:19,719 --> 00:39:24,399
Speaker 1: public health, not a law enforcement national security approach. Now,

719
00:39:24,440 --> 00:39:26,879
Speaker 1: to go back and read this not that long ago,

720
00:39:27,200 --> 00:39:30,240
Speaker 1: in two thousand and eight, the group explained its purpose

721
00:39:30,320 --> 00:39:34,279
Speaker 1: this way. Quote the report examines the relationship between civil

722
00:39:34,320 --> 00:39:37,600
Speaker 1: liberties and public health and contemporary US pandemic planning. It's

723
00:39:37,680 --> 00:39:41,759
Speaker 1: key warning quote. Not all public health interventions have been

724
00:39:41,880 --> 00:39:45,760
Speaker 1: nine or beneficial. However, too often fears aroused by disease

725
00:39:45,800 --> 00:39:50,160
Speaker 1: and epidemics have encouraged abuses of state power. Atrocities large

726
00:39:50,160 --> 00:39:52,880
Speaker 1: and small have been committed in the name of protecting

727
00:39:53,040 --> 00:39:56,719
Speaker 1: public health. And what they specifically point to is that

728
00:39:56,800 --> 00:40:00,759
Speaker 1: coercion and brute force are rarely necessary. In fact, they

729
00:40:00,800 --> 00:40:04,759
Speaker 1: are generally counter productive. So back in two thousand and

730
00:40:04,800 --> 00:40:10,719
Speaker 1: eight they were specifically against law enforcement mandates, especially for

731
00:40:11,080 --> 00:40:15,520
Speaker 1: vaccines and other coercive measures. Then in twenty fifteen they

732
00:40:15,640 --> 00:40:19,480
Speaker 1: reiterated the exact same thing. What happened in two thousand

733
00:40:19,560 --> 00:40:24,239
Speaker 1: and fifteen, Well, what ended up happening is that right

734
00:40:24,520 --> 00:40:28,799
Speaker 1: after that they came out and Donald Trump won the presidency,

735
00:40:29,200 --> 00:40:31,959
Speaker 1: and they raised over a billion dollars from a bunch

736
00:40:32,000 --> 00:40:36,040
Speaker 1: of liberals around the Trump travel ban or whatever, and

737
00:40:36,120 --> 00:40:40,800
Speaker 1: they had to turn into Democratic Party app erratchets. They also,

738
00:40:40,920 --> 00:40:43,759
Speaker 1: I think had and this is again something Glen's been

739
00:40:43,800 --> 00:40:47,000
Speaker 1: great on us reporting this transition. There was a real

740
00:40:47,080 --> 00:40:50,600
Speaker 1: kind of crisis and meltdown within the organization after Charlotte's Yeah, Ov,

741
00:40:50,719 --> 00:40:55,440
Speaker 1: because they defended the right of those white supremacist protesters

742
00:40:55,480 --> 00:40:58,799
Speaker 1: to be there, and so that triggered a real sort

743
00:40:58,800 --> 00:41:03,040
Speaker 1: of rethink within the organization. And but you know that

744
00:41:03,040 --> 00:41:06,560
Speaker 1: that defense of their free speech rights, as ibhorrant as

745
00:41:06,600 --> 00:41:11,120
Speaker 1: their views may be, has a long history within the ACLU.

746
00:41:11,200 --> 00:41:13,480
Speaker 1: I mean this is where they really made their name.

747
00:41:14,280 --> 00:41:17,480
Speaker 1: Scoky right, Skoky Illinois, the wide Nationalists rally that they

748
00:41:17,560 --> 00:41:19,800
Speaker 1: defended and went to bat for. I think it was

749
00:41:19,840 --> 00:41:22,120
Speaker 1: even a Jewish lawyer. Yeah, made it so that they

750
00:41:22,280 --> 00:41:25,640
Speaker 1: could march that a town full of Holocaust survived. That

751
00:41:25,719 --> 00:41:28,319
Speaker 1: is correct, Yeah, that is correct. And so I mean

752
00:41:28,560 --> 00:41:30,799
Speaker 1: here's the thing Glenn really got them dead to rights here,

753
00:41:31,239 --> 00:41:34,880
Speaker 1: Like there's just a total flip flop. Now they're writing

754
00:41:34,920 --> 00:41:38,640
Speaker 1: the op ed saying that vaccine mandates are not an

755
00:41:38,640 --> 00:41:42,439
Speaker 1: in civil liberties. Yeah, here's what they're saying now, far

756
00:41:42,480 --> 00:41:46,960
Speaker 1: from compromising them. Vaccine mandates actually further civil liberties. They

757
00:41:47,000 --> 00:41:50,240
Speaker 1: protect the most vulnerable people with disabilities and fragile immune systems,

758
00:41:50,320 --> 00:41:53,280
Speaker 1: children too young to be vaccinated, and communities of color

759
00:41:53,400 --> 00:41:56,439
Speaker 1: hit hard by the disease. Now you all know, I'm

760
00:41:56,480 --> 00:42:00,239
Speaker 1: in favor of vaccine mandates in some instances. I think

761
00:42:00,239 --> 00:42:02,440
Speaker 1: if you're a teacher, you should be vaccinated. I think

762
00:42:02,480 --> 00:42:04,560
Speaker 1: if you're a nurse, I think, especially if you work

763
00:42:04,600 --> 00:42:06,640
Speaker 1: at a nursing home, you should be vaccinating. I think

764
00:42:06,640 --> 00:42:09,040
Speaker 1: this are servicemen and women who are serving here and

765
00:42:09,040 --> 00:42:11,560
Speaker 1: over the seas is a readiness issue. They've already signed

766
00:42:11,600 --> 00:42:13,239
Speaker 1: up with the you know, given their bodies to the

767
00:42:13,280 --> 00:42:15,640
Speaker 1: US federal government. A lot of senses, I think they

768
00:42:15,640 --> 00:42:19,920
Speaker 1: should also be vaccinated. But I expect the ACLU to

769
00:42:20,000 --> 00:42:23,160
Speaker 1: be taking positions on these issues in favor of civil

770
00:42:23,200 --> 00:42:27,319
Speaker 1: liberties that make me uncomfortable. That's their historic positioning, that's

771
00:42:27,360 --> 00:42:30,360
Speaker 1: their whole job is to be kind of radicals on

772
00:42:30,480 --> 00:42:35,200
Speaker 1: the issues of civil liberties. So now they're saying yes,

773
00:42:35,280 --> 00:42:39,600
Speaker 1: vaccine mandates basically in any instance, and just you know,

774
00:42:39,920 --> 00:42:45,560
Speaker 1: not so long ago, total opposite take on I mean,

775
00:42:45,880 --> 00:42:49,160
Speaker 1: on the very same issue on pandemics and state control

776
00:42:49,239 --> 00:42:53,000
Speaker 1: and vaccine mandates, and their right to be fearful. They

777
00:42:53,120 --> 00:42:56,560
Speaker 1: were right originally to be fearful of the way that

778
00:42:56,719 --> 00:42:59,520
Speaker 1: once a state gets a certain amount of control or

779
00:42:59,600 --> 00:43:02,960
Speaker 1: certain power, that they never relinquish it. That's something we

780
00:43:03,000 --> 00:43:04,960
Speaker 1: talked about from the beginning of the pandemic. We talked

781
00:43:04,960 --> 00:43:07,000
Speaker 1: to Glen about it from the beginning of the pandemic

782
00:43:07,080 --> 00:43:10,840
Speaker 1: that look, certain things aren't necessary in an emergency. Certain

783
00:43:10,840 --> 00:43:13,640
Speaker 1: things are justified in an emergency that don't happen in

784
00:43:13,680 --> 00:43:16,400
Speaker 1: normal times. But just look at nine to eleven and

785
00:43:16,440 --> 00:43:18,840
Speaker 1: the way that you know, everybody was freaked out and

786
00:43:18,880 --> 00:43:21,280
Speaker 1: there was all this like fear porn on the news,

787
00:43:21,840 --> 00:43:25,040
Speaker 1: and it convinced people that we should give up all

788
00:43:25,120 --> 00:43:28,720
Speaker 1: of these civil rights and liberties. We should allow government

789
00:43:28,800 --> 00:43:31,640
Speaker 1: to have mass surveillance, We should allow these drone strikes

790
00:43:31,680 --> 00:43:33,919
Speaker 1: to go on without any real due process. We should

791
00:43:33,960 --> 00:43:38,160
Speaker 1: allow people to be held indefinitely forever, and Guantano mobay,

792
00:43:38,239 --> 00:43:41,399
Speaker 1: we should go to war with you know, no justification

793
00:43:41,560 --> 00:43:46,000
Speaker 1: or even a pretense of a justification. So the fear

794
00:43:46,480 --> 00:43:49,239
Speaker 1: of all of this is that once you hand those

795
00:43:49,280 --> 00:43:52,320
Speaker 1: powers to the state, they don't relinquish it that is

796
00:43:52,360 --> 00:43:55,600
Speaker 1: a very like that is a very good thing to

797
00:43:55,680 --> 00:43:59,480
Speaker 1: fear and has a lot of historic justification. The aclo

798
00:43:59,880 --> 00:44:02,760
Speaker 1: U used to understand that, they wrote in that original piece,

799
00:44:03,920 --> 00:44:07,000
Speaker 1: if that fear justifies the suspension of liberties and the

800
00:44:07,040 --> 00:44:09,799
Speaker 1: institution of an emergency state, then freedom and the rule

801
00:44:09,840 --> 00:44:12,839
Speaker 1: of law will be permanently suspended. Those were their fears then,

802
00:44:13,600 --> 00:44:18,360
Speaker 1: now totally singing a totally different tune with no real

803
00:44:18,400 --> 00:44:22,120
Speaker 1: explanation of why things are different now than they were,

804
00:44:22,160 --> 00:44:24,920
Speaker 1: then they're not different. And actually Glenn even found another

805
00:44:25,000 --> 00:44:28,279
Speaker 1: example from May of twenty twenty, so not barely a

806
00:44:28,360 --> 00:44:31,920
Speaker 1: year ago, where they were against immunity passports, you know,

807
00:44:31,960 --> 00:44:35,520
Speaker 1: in terms of vaccines. Why because they said the division

808
00:44:35,520 --> 00:44:39,080
Speaker 1: would likely worsen existing racial disability and economic disparities in

809
00:44:39,080 --> 00:44:42,480
Speaker 1: America and lead people struggling to afford basic necessities to

810
00:44:42,560 --> 00:44:46,919
Speaker 1: deliberately risk their health. I completely agree with the past

811
00:44:47,000 --> 00:44:50,120
Speaker 1: days tail you the but clowning really of this organization

812
00:44:50,560 --> 00:44:53,520
Speaker 1: is very satis see sad, because they were you know,

813
00:44:53,800 --> 00:44:58,439
Speaker 1: righteous fighters on sometimes unpopular causes which standing the test

814
00:44:58,520 --> 00:45:01,120
Speaker 1: of time as uncomfortable. Well as it may be, we

815
00:45:01,160 --> 00:45:03,000
Speaker 1: should go back and say that it was probably a

816
00:45:03,000 --> 00:45:05,440
Speaker 1: good thing that people have a right to assemble and

817
00:45:05,480 --> 00:45:07,560
Speaker 1: to march. Even there. If there are some of the

818
00:45:07,600 --> 00:45:11,239
Speaker 1: most despicable people on earth, they are the United States citizens.

819
00:45:11,400 --> 00:45:14,280
Speaker 1: That really is kind of what the country is all about.

820
00:45:14,880 --> 00:45:16,920
Speaker 1: And if you go and you look, as you're saying,

821
00:45:17,200 --> 00:45:19,759
Speaker 1: with the mandates which are now being really pushed and

822
00:45:19,800 --> 00:45:23,120
Speaker 1: embraced by the Biden administration, the Biden administration sees it

823
00:45:23,160 --> 00:45:25,280
Speaker 1: as their last resort. They're like, look, we did everything

824
00:45:25,480 --> 00:45:28,120
Speaker 1: we possibly could, which I actually disagree with. Given the

825
00:45:28,160 --> 00:45:31,839
Speaker 1: fact that you did that great monologue on all of

826
00:45:31,880 --> 00:45:35,239
Speaker 1: these public health contractors who gobbled up all of this

827
00:45:35,360 --> 00:45:39,640
Speaker 1: government money and who were very ineffectual at actually pushing

828
00:45:39,719 --> 00:45:42,440
Speaker 1: for vaccination campaigns. I don't think they have done nearly

829
00:45:42,480 --> 00:45:45,200
Speaker 1: what they should in terms of getting in terms of

830
00:45:45,200 --> 00:45:47,360
Speaker 1: getting people to really do it. And if they really

831
00:45:47,560 --> 00:45:49,880
Speaker 1: were for it, they should call Trump right now and

832
00:45:49,920 --> 00:45:52,200
Speaker 1: ask him to cut a PSA. If he denies it,

833
00:45:52,239 --> 00:45:54,120
Speaker 1: that's a story and they can blame him. I don't

834
00:45:54,120 --> 00:45:55,719
Speaker 1: think he could deny it. I think he would have

835
00:45:55,719 --> 00:45:58,479
Speaker 1: to film one, some sort of national PSA that would

836
00:45:58,520 --> 00:46:02,000
Speaker 1: run everywhere asking yes, he's an ego maniac, and he

837
00:46:02,000 --> 00:46:04,080
Speaker 1: would need Biden to ask him. Biden should ask him

838
00:46:04,120 --> 00:46:06,680
Speaker 1: in the interest of public health. These are exactly the

839
00:46:06,719 --> 00:46:09,239
Speaker 1: type of things where I think that they absolutely have

840
00:46:09,440 --> 00:46:12,560
Speaker 1: not done everything they can and are now moving towards

841
00:46:12,719 --> 00:46:16,680
Speaker 1: the stick approach, encouraging more people in the private sector

842
00:46:17,040 --> 00:46:19,840
Speaker 1: after the full authorization of the Pfizer vaccine, to go

843
00:46:19,920 --> 00:46:23,200
Speaker 1: ahead and institute more mandates. And look, maybe it'll work.

844
00:46:23,360 --> 00:46:26,719
Speaker 1: But here's the thing, where's the line? Doctor Fauci January

845
00:46:26,800 --> 00:46:30,640
Speaker 1: twenty first, twenty twenty one, said seventy eighty five percent

846
00:46:30,640 --> 00:46:33,480
Speaker 1: of Americans adults should be vaccinated for there to be

847
00:46:33,520 --> 00:46:36,840
Speaker 1: heard immunity. We're almost at We're almost past seventy percent

848
00:46:36,920 --> 00:46:39,560
Speaker 1: in terms of the one dose figure. So what is it?

849
00:46:39,640 --> 00:46:42,560
Speaker 1: I mean, nobody really seems to know. And that's the

850
00:46:42,600 --> 00:46:45,040
Speaker 1: bigger problem. There's just muddy messaging on this all around.

851
00:46:45,120 --> 00:46:47,400
Speaker 1: The issue with herd immunity is that while you have

852
00:46:47,560 --> 00:46:50,360
Speaker 1: overall seventy five percent of adults now have received a

853
00:46:50,400 --> 00:46:53,640
Speaker 1: single dose, you have pockets obviously where it's much much lower, correct,

854
00:46:53,680 --> 00:46:57,760
Speaker 1: And so while you have a national number that's been reached,

855
00:46:58,200 --> 00:47:01,759
Speaker 1: in individual areas nowhere close to her immunity, which is

856
00:47:01,800 --> 00:47:04,760
Speaker 1: why you're having these horrendous soundbreaks. But just to show

857
00:47:04,800 --> 00:47:10,960
Speaker 1: you how ugly things can get when you justify anything

858
00:47:11,160 --> 00:47:15,040
Speaker 1: in the name of pandemic protections. It's a really crazy

859
00:47:15,080 --> 00:47:19,719
Speaker 1: story out of South Korea. The president, let's throw this

860
00:47:19,880 --> 00:47:22,880
Speaker 1: tears sheet up on the screen. President of a million

861
00:47:23,000 --> 00:47:26,680
Speaker 1: member Korean federation Confederation of Trade Unions, kind of a

862
00:47:26,680 --> 00:47:30,680
Speaker 1: more militant trade union group, was arrested in a pre

863
00:47:30,920 --> 00:47:34,280
Speaker 1: dawn raid of his sole office, where he had taken

864
00:47:34,280 --> 00:47:37,560
Speaker 1: flight from threats of arrest. On September second, hundreds of

865
00:47:37,719 --> 00:47:42,719
Speaker 1: police encircled the building for this union leader as officers

866
00:47:42,800 --> 00:47:45,680
Speaker 1: pride opened the door. A local court had issued and

867
00:47:45,800 --> 00:47:50,040
Speaker 1: arrest weren't for Yang after prosecutors alleged he had violated

868
00:47:50,239 --> 00:47:56,200
Speaker 1: COVID social distancing laws by organizing a rally in downtown Soul.

869
00:47:56,880 --> 00:47:59,520
Speaker 1: His group had organized that rally on July third, calling

870
00:47:59,560 --> 00:48:03,160
Speaker 1: on the government to address inequality deepened by the pandemic.

871
00:48:03,440 --> 00:48:06,920
Speaker 1: Government did not permit the rally, sighting super spreader concerns.

872
00:48:07,840 --> 00:48:10,680
Speaker 1: Even with the government not sanctioning the rally, about eight

873
00:48:10,760 --> 00:48:15,360
Speaker 1: thousand union members gathered carefully following government guidelines for social distancing.

874
00:48:15,680 --> 00:48:19,520
Speaker 1: After the rally, three people tested positive for COVID, and

875
00:48:19,560 --> 00:48:22,880
Speaker 1: there is zero evidence that they got it at that event,

876
00:48:23,120 --> 00:48:25,640
Speaker 1: meaning they probably had it beforehand they showed up at

877
00:48:25,680 --> 00:48:29,280
Speaker 1: the event. There's no indication that there was any COVID

878
00:48:29,320 --> 00:48:31,640
Speaker 1: spread at this event. What we've learned at this point

879
00:48:31,840 --> 00:48:34,960
Speaker 1: is that, look, it's not that there's zero risk outside,

880
00:48:35,000 --> 00:48:37,520
Speaker 1: but there's pretty low risk outside if you're doing a

881
00:48:37,600 --> 00:48:41,000
Speaker 1: rally outside. They arrested the Sky and threw them in jail.

882
00:48:42,000 --> 00:48:44,040
Speaker 1: They're still calling for a general strike. By the way,

883
00:48:44,040 --> 00:48:47,480
Speaker 1: in October twentieth, good for them, and upon arrest, Yang

884
00:48:47,560 --> 00:48:52,120
Speaker 1: began a hunger strike calling for his release. So listen,

885
00:48:52,680 --> 00:48:58,440
Speaker 1: different country, different wildly different approach. But this is the

886
00:48:58,520 --> 00:49:00,680
Speaker 1: type of slippery slope that you get on when you

887
00:49:00,719 --> 00:49:06,560
Speaker 1: start to think that any state intervention is justified to uh,

888
00:49:06,760 --> 00:49:10,160
Speaker 1: stem the stem the tide, to stop the spread of

889
00:49:10,239 --> 00:49:15,560
Speaker 1: COVID whatsoever. And so this is extraordinarily dystopian and frankly,

890
00:49:15,600 --> 00:49:17,880
Speaker 1: it's what some people in this country would like to see. No,

891
00:49:18,080 --> 00:49:20,520
Speaker 1: that's why we're highlighting this because they would like to

892
00:49:20,520 --> 00:49:22,680
Speaker 1: see this, and it's a good example of how once

893
00:49:22,719 --> 00:49:24,200
Speaker 1: you have it, they're not going to take it away,

894
00:49:24,200 --> 00:49:26,839
Speaker 1: and they will use it to justify the policies that

895
00:49:26,880 --> 00:49:29,839
Speaker 1: they then want, and that is exactly what we all

896
00:49:29,880 --> 00:49:32,840
Speaker 1: want to avoid, which is union busting in the guise

897
00:49:32,880 --> 00:49:35,759
Speaker 1: of COVIDE. You can imagine it right here at home.

898
00:49:35,840 --> 00:49:41,439
Speaker 1: Oh right, ah, cobsolutely right. I remember what was his name,

899
00:49:41,800 --> 00:49:44,839
Speaker 1: the Amazon worker, Christian Small's. They did the same thing.

900
00:49:45,000 --> 00:49:48,440
Speaker 1: They were like, oh, you you know, violated some fake

901
00:49:48,520 --> 00:49:52,640
Speaker 1: COVID guidelines, So you're fired. Is organizing very union? It

902
00:49:52,760 --> 00:49:55,320
Speaker 1: was there, you go, It's already happened to your people,

903
00:49:55,360 --> 00:49:56,600
Speaker 1: and they're going to try and do it at the

904
00:49:56,600 --> 00:49:59,640
Speaker 1: private level and eventually it'll get there to the public. Yeah,

905
00:49:59,680 --> 00:50:01,880
Speaker 1: that's absolutely true. So let's go ahead and get to

906
00:50:01,920 --> 00:50:05,840
Speaker 1: this next one. Story. We've been following with great interest,

907
00:50:05,840 --> 00:50:08,320
Speaker 1: and I see that many of you are interested as well.

908
00:50:08,440 --> 00:50:13,560
Speaker 1: So the Elizabeth Holmes trial started yesterday. Opening arguments were

909
00:50:13,560 --> 00:50:16,840
Speaker 1: made by both the prosecution and the defense. So this

910
00:50:16,960 --> 00:50:18,520
Speaker 1: is interesting. Let's go ahead and put this up there

911
00:50:18,520 --> 00:50:20,920
Speaker 1: on the screen. We went ahead and told you already

912
00:50:20,960 --> 00:50:24,120
Speaker 1: that missus Holmes is going to claim basically a fake

913
00:50:24,320 --> 00:50:27,799
Speaker 1: me too defense about how her relationship with a person

914
00:50:27,840 --> 00:50:31,280
Speaker 1: who's actually subordinate. Sonny Balwani also worked at that company,

915
00:50:31,520 --> 00:50:35,560
Speaker 1: bullied her into defrauding investors and of course screwing over

916
00:50:35,600 --> 00:50:37,719
Speaker 1: a lot of people who use her home tests. But

917
00:50:38,040 --> 00:50:41,200
Speaker 1: the defense is pairing that by trying to seem as

918
00:50:41,239 --> 00:50:44,520
Speaker 1: if she was a normal business investor. So what they

919
00:50:44,560 --> 00:50:48,440
Speaker 1: say is this quote, failure is not a crime. The

920
00:50:48,480 --> 00:50:51,640
Speaker 1: defense says, Elizabeth Holmes did not go to work every

921
00:50:51,680 --> 00:50:55,319
Speaker 1: day intending to lie, cheat and steal. The government would

922
00:50:55,320 --> 00:50:59,000
Speaker 1: have you believe that her entire company, her entire life

923
00:50:59,120 --> 00:51:02,000
Speaker 1: is a fraud. Well, I think there's a decent case

924
00:51:02,239 --> 00:51:06,120
Speaker 1: to be made there. They say, quote that she worked

925
00:51:06,160 --> 00:51:08,480
Speaker 1: herself to the bone for fifteen years trying to make

926
00:51:08,560 --> 00:51:11,640
Speaker 1: lab testing cheaper and more accessible. She poured her heart

927
00:51:11,680 --> 00:51:14,439
Speaker 1: and soul into that effort. In the end, their nose

928
00:51:14,520 --> 00:51:17,880
Speaker 1: failed and missus Holmes walked away with nothing. But failure

929
00:51:17,960 --> 00:51:20,359
Speaker 1: is not a crime. Trying your hardest and coming up

930
00:51:20,400 --> 00:51:23,000
Speaker 1: short is not a crime. So they're trying two different things.

931
00:51:23,200 --> 00:51:26,600
Speaker 1: Number one, she was just a misguided investor, and you

932
00:51:26,640 --> 00:51:30,120
Speaker 1: know she she was just did her damnedest and you know,

933
00:51:30,280 --> 00:51:33,040
Speaker 1: absolutely did her best every single day, woke up wanted

934
00:51:33,080 --> 00:51:36,040
Speaker 1: to create these cheaper blood tests. It didn't work out,

935
00:51:36,239 --> 00:51:39,080
Speaker 1: and that was with the whole tobacle. But the government

936
00:51:39,239 --> 00:51:43,080
Speaker 1: actually has a pretty good case, as anybody has reviewed

937
00:51:43,080 --> 00:51:45,640
Speaker 1: the evidence there, Crystal that actually she did wake up

938
00:51:45,800 --> 00:51:49,360
Speaker 1: beginning around like year three when they realized this technology

939
00:51:49,400 --> 00:51:51,760
Speaker 1: wasn't going to work, and was like, oh, I really

940
00:51:51,840 --> 00:51:53,840
Speaker 1: like being on all these magazine covers and called the

941
00:51:53,880 --> 00:51:56,400
Speaker 1: female Steve Jobs. So I'm going to lower my voice

942
00:51:56,400 --> 00:52:00,200
Speaker 1: and I'm gonna wear these black sweaters. And also she

943
00:52:00,280 --> 00:52:02,880
Speaker 1: was a billionaire. That seems like I'm pretty good incentive

944
00:52:03,040 --> 00:52:06,919
Speaker 1: in order to try and create financial chickanery. So all

945
00:52:07,040 --> 00:52:09,680
Speaker 1: you couple all that together, and the government and the

946
00:52:09,719 --> 00:52:12,720
Speaker 1: prosecution they put together, you know, all of these lists

947
00:52:12,719 --> 00:52:15,640
Speaker 1: of witnesses and evidence, but you went deep on the

948
00:52:15,719 --> 00:52:19,320
Speaker 1: text messages of this little me too couple. Yeah. Yeah,

949
00:52:19,360 --> 00:52:24,360
Speaker 1: So as part of discovery, a lot of her text

950
00:52:24,360 --> 00:52:28,200
Speaker 1: messages with Sonny Balwani, who again, as you said, she's

951
00:52:28,239 --> 00:52:30,759
Speaker 1: basically trying to pin this all on him and use

952
00:52:30,960 --> 00:52:34,480
Speaker 1: what they're describing as a Spengali defense. Yes, so basically

953
00:52:34,600 --> 00:52:39,399
Speaker 1: like I was this helpless young woman and he led

954
00:52:39,440 --> 00:52:42,080
Speaker 1: me into this fraud, and really I was in this

955
00:52:42,160 --> 00:52:45,359
Speaker 1: abusive relationship and so it was all very coercive and

956
00:52:45,400 --> 00:52:48,560
Speaker 1: it was all on him, not on me. So that's

957
00:52:48,560 --> 00:52:52,040
Speaker 1: why these text messages are relevant, and it wasn't. I

958
00:52:52,080 --> 00:52:54,480
Speaker 1: can't take credit. John Kerry Rout, who was the one,

959
00:52:54,560 --> 00:52:56,800
Speaker 1: the reporter from the Wall Street Journal who initially broke

960
00:52:56,880 --> 00:52:58,560
Speaker 1: this story and it was like a dog with a

961
00:52:58,600 --> 00:53:02,840
Speaker 1: bone on this thing, really posed the horrendous levels of

962
00:53:02,960 --> 00:53:08,240
Speaker 1: fraud and lies within that company, starting with Elizabeth Holmes.

963
00:53:08,480 --> 00:53:11,640
Speaker 1: He dug into these text messages, and the picture you

964
00:53:11,719 --> 00:53:16,080
Speaker 1: get is not convenient for Elizabeth Holmes defense that she

965
00:53:16,239 --> 00:53:19,520
Speaker 1: was just this poor helpless thing and it was Sunny Balwai.

966
00:53:19,600 --> 00:53:21,920
Speaker 1: It was really driving the ship and encouraging them to

967
00:53:21,960 --> 00:53:25,279
Speaker 1: go in this fraudulent interaction because he a lot of

968
00:53:25,320 --> 00:53:29,560
Speaker 1: times raises concerns yes, saying you know, we got to

969
00:53:29,560 --> 00:53:32,319
Speaker 1: get this figured out. We got to get more of

970
00:53:32,360 --> 00:53:35,080
Speaker 1: the test done because one of the problems was they're

971
00:53:35,080 --> 00:53:37,400
Speaker 1: supposed to be able to do these finger pricks. Because

972
00:53:37,400 --> 00:53:39,440
Speaker 1: the whole thing was like, oh, people hate needles, this

973
00:53:39,480 --> 00:53:42,040
Speaker 1: will be so much less intrusive, so you just do

974
00:53:42,120 --> 00:53:43,960
Speaker 1: this finger prick and you can get all this range

975
00:53:44,000 --> 00:53:46,359
Speaker 1: of test results. Well, the problem was that the finger

976
00:53:46,440 --> 00:53:49,680
Speaker 1: prick didn't work for most of the tests that people

977
00:53:49,719 --> 00:53:52,160
Speaker 1: could get, so they were having to still do the

978
00:53:52,239 --> 00:53:54,760
Speaker 1: old fashion, the same thing that any other lab testing

979
00:53:54,760 --> 00:53:58,160
Speaker 1: company does, draw the blood from the vein and you know,

980
00:53:58,200 --> 00:54:00,800
Speaker 1: get a real needle in there at the which was

981
00:54:00,840 --> 00:54:04,520
Speaker 1: their big companies. So Balwani kept expressing her like, we

982
00:54:04,600 --> 00:54:06,440
Speaker 1: got to get these tests figured out, we got to

983
00:54:06,440 --> 00:54:09,279
Speaker 1: get more of them through the finger prick. And she

984
00:54:09,560 --> 00:54:13,560
Speaker 1: was a lot more interested in the praise over being

985
00:54:13,600 --> 00:54:17,120
Speaker 1: on Fortune or being Glamour's Woman of the Year and

986
00:54:18,000 --> 00:54:20,719
Speaker 1: you know, being on CNBC and being hailed as the

987
00:54:20,719 --> 00:54:23,880
Speaker 1: female stave Jobs. She was a lot more interested in

988
00:54:23,920 --> 00:54:26,000
Speaker 1: that part of the conversation than she was in the

989
00:54:26,040 --> 00:54:28,719
Speaker 1: part of the conversation that was like, yeah, we got

990
00:54:28,760 --> 00:54:30,839
Speaker 1: to make sure that the substance of what's going on

991
00:54:30,960 --> 00:54:35,080
Speaker 1: here matches anything close to what we were portraying it

992
00:54:35,120 --> 00:54:38,480
Speaker 1: as both to the press and to the American people,

993
00:54:38,680 --> 00:54:42,799
Speaker 1: to our own customers, and to the investors who have

994
00:54:42,880 --> 00:54:45,600
Speaker 1: been led to believe that all these tests are being

995
00:54:45,640 --> 00:54:49,600
Speaker 1: done through finger pricks. There's another element of this, which

996
00:54:49,640 --> 00:54:53,160
Speaker 1: is that you know, would be relevant to the case

997
00:54:53,920 --> 00:54:57,080
Speaker 1: how many of the tests were inaccurate, because it's not

998
00:54:57,200 --> 00:54:59,680
Speaker 1: just that they were not being done through the finger prick.

999
00:55:00,080 --> 00:55:02,520
Speaker 1: Also that their whole lab was such a disaster that

1000
00:55:02,560 --> 00:55:04,759
Speaker 1: there were a lot of just incorrect tests. People were

1001
00:55:04,760 --> 00:55:08,000
Speaker 1: getting results that were wrong. Who relied on this for

1002
00:55:08,160 --> 00:55:12,520
Speaker 1: you know, health, important health decisions, And there's some question

1003
00:55:12,600 --> 00:55:16,759
Speaker 1: about what happened here. But the database that stored all

1004
00:55:16,840 --> 00:55:22,359
Speaker 1: of those results, they destroyed those servers. Okay, first, they

1005
00:55:22,400 --> 00:55:25,200
Speaker 1: had sent the government, the prosecutors in the case, They

1006
00:55:25,239 --> 00:55:28,759
Speaker 1: sent them a copy of the database, but it was

1007
00:55:29,840 --> 00:55:33,399
Speaker 1: encrypted in a format that basically made it useless, and

1008
00:55:33,760 --> 00:55:36,719
Speaker 1: they didn't give them the encryption key so that they

1009
00:55:36,719 --> 00:55:39,440
Speaker 1: could unlock it at all to look at it. Now,

1010
00:55:39,800 --> 00:55:42,400
Speaker 1: that all sounds very nefarious. On the other hand, the

1011
00:55:42,400 --> 00:55:45,760
Speaker 1: government didn't really try to look at the data until

1012
00:55:45,840 --> 00:55:47,960
Speaker 1: a couple years later, because this case is dragged on

1013
00:55:48,040 --> 00:55:50,120
Speaker 1: for years and years and been pushed off for years

1014
00:55:50,120 --> 00:55:53,360
Speaker 1: and years. But of course they give the government this

1015
00:55:53,480 --> 00:55:58,719
Speaker 1: sort of like useless data and then immediately destroy the servers.

1016
00:55:59,239 --> 00:56:02,799
Speaker 1: So as part of this case, they don't actually have

1017
00:56:03,480 --> 00:56:06,279
Speaker 1: all the data of those test results and whether or

1018
00:56:06,360 --> 00:56:10,440
Speaker 1: not they're accurate. So obviously that presents a major challenge

1019
00:56:11,000 --> 00:56:14,080
Speaker 1: for the prosecutors here. But again, if you're looking at

1020
00:56:14,120 --> 00:56:18,440
Speaker 1: these at these text messages. It's you know, not really

1021
00:56:18,480 --> 00:56:21,879
Speaker 1: convenient for the narrative. And also it's pretty hard and

1022
00:56:22,160 --> 00:56:28,680
Speaker 1: pretty unprecedented to effectively use this Savengali defense, because just

1023
00:56:28,719 --> 00:56:32,800
Speaker 1: because you're in a difficult or abusive relationship, that doesn't

1024
00:56:32,840 --> 00:56:35,759
Speaker 1: mean that you're not culpable for crimes that you could

1025
00:56:35,760 --> 00:56:39,839
Speaker 1: make raising money and defrauding people, right, right, So it's

1026
00:56:39,880 --> 00:56:42,680
Speaker 1: a pretty you know, it's going to be a pretty

1027
00:56:42,719 --> 00:56:46,200
Speaker 1: tough case for her to make, but you can start

1028
00:56:46,239 --> 00:56:50,880
Speaker 1: to see the way that they're trying to engender sympathy

1029
00:56:50,960 --> 00:56:54,400
Speaker 1: for her among the jury. In the opening arguments, her

1030
00:56:54,640 --> 00:56:57,359
Speaker 1: team made sure to mention she's a new mom, and

1031
00:56:58,280 --> 00:57:00,520
Speaker 1: you can sort of see the way that that they're

1032
00:57:00,560 --> 00:57:03,280
Speaker 1: portraying this. By the way, at the same time, don't worry,

1033
00:57:03,360 --> 00:57:06,000
Speaker 1: she hasn't lost all her money. She's apparently doing well

1034
00:57:06,120 --> 00:57:08,719
Speaker 1: enough to live while this whole trial is going on.

1035
00:57:08,760 --> 00:57:10,160
Speaker 1: Let's throw this up on the screen. I think that's

1036
00:57:10,200 --> 00:57:13,279
Speaker 1: from CNBC. She's doing well enough to live on the

1037
00:57:13,320 --> 00:57:17,200
Speaker 1: grounds of one hundred and thirty five million dollars Silicon

1038
00:57:17,280 --> 00:57:22,960
Speaker 1: Valley estate during this trial. So she's still living large

1039
00:57:23,080 --> 00:57:26,880
Speaker 1: even as her whole empire collapsed around her. Yeah, there's

1040
00:57:26,920 --> 00:57:28,360
Speaker 1: just kind of a little bit of a beauty to that.

1041
00:57:28,400 --> 00:57:31,200
Speaker 1: I think her husband is independently wealthy and they married

1042
00:57:31,200 --> 00:57:34,800
Speaker 1: after the entire Thereinos debacle, So there you go. It's

1043
00:57:34,880 --> 00:57:37,520
Speaker 1: kind of a fitting place for her to ride all

1044
00:57:37,520 --> 00:57:40,080
Speaker 1: of this out. And you know, as you said, with

1045
00:57:40,160 --> 00:57:42,840
Speaker 1: the prosecution, there is going to be some difficulty, but

1046
00:57:42,920 --> 00:57:45,360
Speaker 1: really what they have. All they have to show is

1047
00:57:45,400 --> 00:57:48,160
Speaker 1: that she defrauded people when she took their money, if

1048
00:57:48,200 --> 00:57:51,160
Speaker 1: she had some knowledge that the tests themselves were not

1049
00:57:51,200 --> 00:57:53,960
Speaker 1: as efficacious as she was presenting, right, That's really what

1050
00:57:54,000 --> 00:57:57,440
Speaker 1: they had to show. And John Carreyu himself has basically

1051
00:57:57,520 --> 00:58:01,480
Speaker 1: exposed a decent and threshold in order to show that

1052
00:58:01,600 --> 00:58:04,840
Speaker 1: level of information. But regardless, the trial itself tells us

1053
00:58:04,840 --> 00:58:09,280
Speaker 1: a lot about our economic system. Yeah, about the media,

1054
00:58:09,360 --> 00:58:12,360
Speaker 1: and so we're going about very much. So, I mean,

1055
00:58:12,480 --> 00:58:16,120
Speaker 1: she was the ultimate girl boss. I actually went to

1056
00:58:17,160 --> 00:58:19,120
Speaker 1: when I lived in New York. I got invited to

1057
00:58:19,200 --> 00:58:23,360
Speaker 1: this like glamorous woman of the Year thing, So cringe.

1058
00:58:23,600 --> 00:58:26,920
Speaker 1: She was there being celebrated, as you know. I mean,

1059
00:58:27,000 --> 00:58:32,120
Speaker 1: she was so hyped like she was the next huge thing.

1060
00:58:32,680 --> 00:58:36,000
Speaker 1: The list of investors, I mean, just like a who's

1061
00:58:36,040 --> 00:58:40,880
Speaker 1: who of elites, wealthy elites in America. They all loved

1062
00:58:40,920 --> 00:58:45,800
Speaker 1: the story of this young woman first billionaire, and they

1063
00:58:45,960 --> 00:58:49,160
Speaker 1: bought into that story. And it also says it says

1064
00:58:49,160 --> 00:58:52,880
Speaker 1: something about that whole girl Boss ethos. It also says

1065
00:58:52,880 --> 00:58:55,280
Speaker 1: a lot about the culture of Silicon Valley, because there

1066
00:58:55,360 --> 00:58:57,400
Speaker 1: is a culture there of like fake it till you

1067
00:58:57,480 --> 00:59:00,920
Speaker 1: make it, And so part of what she has argued

1068
00:59:00,960 --> 00:59:02,280
Speaker 1: in the past. I don't think this is going to

1069
00:59:02,360 --> 00:59:04,680
Speaker 1: factor really into her defense here because it's not a

1070
00:59:04,680 --> 00:59:07,600
Speaker 1: great defense legally speaking. But what she's arguing in the

1071
00:59:07,600 --> 00:59:09,880
Speaker 1: past is basically, look, I didn't do anything different from

1072
00:59:09,920 --> 00:59:12,640
Speaker 1: what the guys were doing. They were lying and stretching

1073
00:59:12,720 --> 00:59:17,080
Speaker 1: the truth as well. And so yeah, yeah, but you know,

1074
00:59:17,160 --> 00:59:21,000
Speaker 1: and it's also like that, I'm sure she's right about that,

1075
00:59:21,440 --> 00:59:25,160
Speaker 1: but also it's really different when people's lives and health

1076
00:59:25,200 --> 00:59:27,760
Speaker 1: are ata. That's a difference. Your product isn't really It's

1077
00:59:27,760 --> 00:59:30,440
Speaker 1: not like, oh, the search engine doesn't quite work as

1078
00:59:30,480 --> 00:59:32,480
Speaker 1: well as we claim that it is. It's like, no,

1079
00:59:32,640 --> 00:59:36,440
Speaker 1: you're giving people wrong health information. You know. There's a

1080
00:59:36,480 --> 00:59:40,840
Speaker 1: text message where Balwani tells her that their most critical

1081
00:59:40,880 --> 00:59:43,440
Speaker 1: labs where they're doing the pin prick testing that they're

1082
00:59:43,520 --> 00:59:47,320
Speaker 1: a disaster, and she says, I know. So. I mean,

1083
00:59:47,360 --> 00:59:50,960
Speaker 1: they're very aware that this is all a mess, that

1084
00:59:51,000 --> 00:59:53,320
Speaker 1: it's not nearly what they're portraying it to the public,

1085
00:59:53,440 --> 00:59:56,800
Speaker 1: and people's like important health decisions are risk here, So

1086
00:59:56,840 --> 00:59:59,200
Speaker 1: that's why this matters. That's exactly right. Wow, you guys

1087
00:59:59,280 --> 01:00:01,160
Speaker 1: must really like what's to our voices? Well, I know

1088
01:00:01,200 --> 01:00:03,160
Speaker 1: this is annoying. Instead of making you listen to a

1089
01:00:03,240 --> 01:00:06,240
Speaker 1: Viagra commercial. When you're done, check out the other podcast

1090
01:00:06,280 --> 01:00:08,600
Speaker 1: I do with Marshal Costsoff called The Realignment. We talk

1091
01:00:08,640 --> 01:00:11,480
Speaker 1: a lot about the deeper issues that are changing realigning

1092
01:00:11,560 --> 01:00:14,240
Speaker 1: in American society. You always need more Crystal and soog

1093
01:00:14,240 --> 01:00:16,960
Speaker 1: in your daily lives. Take care, guys, Crystal, what are

1094
01:00:17,000 --> 01:00:19,760
Speaker 1: you taking a look at? Well? Joe Manchin is now

1095
01:00:19,760 --> 01:00:23,360
Speaker 1: telling insiders that he will not support a Biden reconciliation

1096
01:00:23,480 --> 01:00:26,959
Speaker 1: package higher than one point five trillion. That price tag

1097
01:00:27,000 --> 01:00:29,840
Speaker 1: would be a major blow to poor and working class

1098
01:00:29,880 --> 01:00:33,160
Speaker 1: Americans who would overwhelmingly benefit from the child tax credit,

1099
01:00:33,440 --> 01:00:37,120
Speaker 1: from expanded Medicare, from free pre K, from free community college,

1100
01:00:37,160 --> 01:00:40,000
Speaker 1: and so much more. It would be a particular blow

1101
01:00:40,040 --> 01:00:43,120
Speaker 1: we should mention in poor states like Mansion's own home

1102
01:00:43,160 --> 01:00:46,560
Speaker 1: state of West Virginia. But limiting the price tag would

1103
01:00:46,640 --> 01:00:49,040
Speaker 1: be a boon to the wealthy and to Corporate America,

1104
01:00:49,040 --> 01:00:51,200
Speaker 1: as it would mean that their taxes would stay in

1105
01:00:51,240 --> 01:00:53,840
Speaker 1: the low to non existent range where they are currently.

1106
01:00:54,240 --> 01:00:56,880
Speaker 1: It would mean that oil and gas companies can continue

1107
01:00:56,920 --> 01:00:59,760
Speaker 1: their plunder of the planet unabated. It would mean that

1108
01:00:59,840 --> 01:01:03,040
Speaker 1: not a penny of profit would be stripped from pharmaceutical

1109
01:01:03,080 --> 01:01:06,600
Speaker 1: giants who can currently gouge the federal government without recourse.

1110
01:01:07,040 --> 01:01:10,240
Speaker 1: By keeping the gravy train rolling, Manson himself gets to

1111
01:01:10,280 --> 01:01:12,840
Speaker 1: remain a favored son of Corporate America with all the

1112
01:01:12,920 --> 01:01:17,720
Speaker 1: attendant contributions and job prospects that that all entails. But

1113
01:01:18,440 --> 01:01:21,680
Speaker 1: corruption and grift are not just the business model of

1114
01:01:21,800 --> 01:01:25,200
Speaker 1: Daddy Mansion. According to a bombshell report from the intercepts

1115
01:01:25,240 --> 01:01:28,520
Speaker 1: Ryan Grim, we are learning that in the Mansion clan,

1116
01:01:28,800 --> 01:01:32,200
Speaker 1: corporate greed and malfesis. Well, it's a family affair. Allow

1117
01:01:32,240 --> 01:01:36,400
Speaker 1: me to explain Manchin's daughter. Her name is Heather Brush.

1118
01:01:36,440 --> 01:01:40,520
Speaker 1: She's the former head of West Virginia drug maker Mylon Pharmaceuticals.

1119
01:01:40,840 --> 01:01:42,920
Speaker 1: Now Mylon has been in the news recently because it's

1120
01:01:43,000 --> 01:01:46,040
Speaker 1: West Virginia plant is being shut down and thousands of

1121
01:01:46,120 --> 01:01:49,000
Speaker 1: jobs there are being moved overseas, as we covered on

1122
01:01:49,000 --> 01:01:52,400
Speaker 1: this show, a move that Manchin would likely oppose if

1123
01:01:52,400 --> 01:01:54,760
Speaker 1: it weren't for the fact that his daughter got a

1124
01:01:54,800 --> 01:01:58,480
Speaker 1: sweetheart multimillion dollar golden parachute as part of the business

1125
01:01:58,560 --> 01:02:01,280
Speaker 1: deal that ultimately led to the closure of that plant.

1126
01:02:01,640 --> 01:02:04,400
Speaker 1: By the way, Brush was never qualified to hold this

1127
01:02:04,440 --> 01:02:07,760
Speaker 1: position to start with. She was given a fake MBA

1128
01:02:08,040 --> 01:02:11,240
Speaker 1: by West Virginia University after her daddy was elected governor

1129
01:02:11,320 --> 01:02:14,880
Speaker 1: of the state, with grades quote pulled out of thin air,

1130
01:02:15,240 --> 01:02:18,920
Speaker 1: a scandal that led to multiple resignations at WVU. But

1131
01:02:19,040 --> 01:02:21,520
Speaker 1: it gets so much worse than that. We are now

1132
01:02:21,640 --> 01:02:25,960
Speaker 1: learning that while she ran Mylin, Brush colluded directly in

1133
01:02:26,040 --> 01:02:29,360
Speaker 1: a price fixing scheme that jacked up the cost of

1134
01:02:29,440 --> 01:02:34,160
Speaker 1: life saving epipins now, while also collaborating with Pfizer to

1135
01:02:34,240 --> 01:02:38,080
Speaker 1: create a monopoly for the product. These maneuvers made Mylin

1136
01:02:38,200 --> 01:02:41,920
Speaker 1: and Brush millions, while leaving those who literally need that

1137
01:02:42,000 --> 01:02:45,680
Speaker 1: product as a matter of survival struggling to afford the cost.

1138
01:02:46,120 --> 01:02:48,040
Speaker 1: There are a couple of pieces here, so let's start

1139
01:02:48,040 --> 01:02:50,480
Speaker 1: with the Pfeiser collusion. To understand that you got to

1140
01:02:50,520 --> 01:02:53,240
Speaker 1: have just a little bit of market background. Mylin bought

1141
01:02:53,240 --> 01:02:56,120
Speaker 1: the rights to sell EpiPens from Murk back in two

1142
01:02:56,160 --> 01:02:58,920
Speaker 1: thousand and seven. As part of that deal, Mylon agreed

1143
01:02:58,960 --> 01:03:02,760
Speaker 1: to produce and mark the EpiPen delivery device, but another

1144
01:03:02,840 --> 01:03:07,080
Speaker 1: drug maker called King Pharmaceuticals, they actually produced the medicine

1145
01:03:07,080 --> 01:03:09,800
Speaker 1: that went in the delivery device, so this was all

1146
01:03:09,800 --> 01:03:13,920
Speaker 1: going beautifully. Mylin began routinely jacking up the price of EpiPens,

1147
01:03:13,920 --> 01:03:17,160
Speaker 1: amassing larger and larger profits, but there was some trouble

1148
01:03:17,200 --> 01:03:21,440
Speaker 1: on the horizon. A less costly EpiPen alternative called Adrina

1149
01:03:21,440 --> 01:03:24,520
Speaker 1: Click was beginning to eat into their market share. What

1150
01:03:24,600 --> 01:03:27,960
Speaker 1: to do? What to do? Well, collude directly with Pfizer

1151
01:03:27,960 --> 01:03:30,640
Speaker 1: to rig the market. Of course, in newly released emails,

1152
01:03:30,760 --> 01:03:34,400
Speaker 1: Brush is caught collaborating with Pfizer to kill the Adrena

1153
01:03:34,400 --> 01:03:40,160
Speaker 1: Click product, leaving EpiPens as the sole option. Pfeiser acquired

1154
01:03:40,480 --> 01:03:43,960
Speaker 1: King Pharmaceuticals. Again, they're the ones that make the actual medicine,

1155
01:03:44,120 --> 01:03:47,400
Speaker 1: which cut them in on half the profits for the EpiPens,

1156
01:03:47,640 --> 01:03:50,880
Speaker 1: meaning that now Pfizer stood to financially benefit from killing

1157
01:03:50,920 --> 01:03:53,320
Speaker 1: their own low cost competitor in order to reap the

1158
01:03:53,400 --> 01:03:57,320
Speaker 1: margins from the higher priced EpiPen product. Brush's emails reveal

1159
01:03:57,360 --> 01:04:00,920
Speaker 1: communications to lock in that product monopoly to the benefit

1160
01:04:00,960 --> 01:04:04,800
Speaker 1: of herself, Mylon, and Pfizer, and to the detriment of

1161
01:04:04,840 --> 01:04:08,080
Speaker 1: those who actually needed that medicine. But that wasn't enough.

1162
01:04:08,520 --> 01:04:11,720
Speaker 1: Under Brush Mylin also hatched a scheme that they labeled

1163
01:04:11,760 --> 01:04:15,680
Speaker 1: Project X two to eliminate the sale of single EpiPens

1164
01:04:15,720 --> 01:04:18,360
Speaker 1: and require that they be purchased in a two pack.

1165
01:04:18,760 --> 01:04:22,680
Speaker 1: A PowerPoint slide recently revealed in federal courts nakedly states

1166
01:04:22,720 --> 01:04:25,760
Speaker 1: the goal of this whole project. The goal, they say,

1167
01:04:26,000 --> 01:04:29,080
Speaker 1: of the double pack was to double revenue. Of course,

1168
01:04:29,400 --> 01:04:32,320
Speaker 1: after deciding this was a great way to increase profits,

1169
01:04:32,440 --> 01:04:35,560
Speaker 1: the team at Mylin under Brush went into overdrive to

1170
01:04:35,720 --> 01:04:40,320
Speaker 1: manufacture a medical justification, with one email among Mylin employees

1171
01:04:40,440 --> 01:04:44,440
Speaker 1: explicitly stating quote, Senior management is having a meeting with

1172
01:04:44,480 --> 01:04:46,920
Speaker 1: Heather April one and wanted to provide her with an

1173
01:04:47,000 --> 01:04:50,040
Speaker 1: update on Project X two. I know that you were

1174
01:04:50,120 --> 01:04:54,560
Speaker 1: working on creating a medical rationale for Project X two.

1175
01:04:54,920 --> 01:04:57,400
Speaker 1: I'm pulling a slide deck together that will be used

1176
01:04:57,960 --> 01:05:00,760
Speaker 1: and just so you know, the corporate thievery is truly

1177
01:05:00,840 --> 01:05:05,160
Speaker 1: a family affair. In the Mansion family, Manchin's wife gave

1178
01:05:05,200 --> 01:05:07,920
Speaker 1: her daughter innisis from her position as head of the

1179
01:05:08,000 --> 01:05:12,360
Speaker 1: National Association of State Boards of Education by lobbying states

1180
01:05:12,760 --> 01:05:17,640
Speaker 1: to require schools to stock EpiPens. So, to summarize, under

1181
01:05:17,680 --> 01:05:21,400
Speaker 1: Joe Manchin's daughter, Mylon jacked up the price locked in

1182
01:05:21,440 --> 01:05:24,880
Speaker 1: a product monopoly, jacked up the price some war, and

1183
01:05:24,920 --> 01:05:28,800
Speaker 1: then worked to eliminate single pack sales with zero medical

1184
01:05:28,880 --> 01:05:32,920
Speaker 1: justification simply so they could double their revenue, all with

1185
01:05:33,080 --> 01:05:38,520
Speaker 1: the explicit understanding that for their customers, their lives depend

1186
01:05:38,600 --> 01:05:41,440
Speaker 1: on the product, so they have no choice but to

1187
01:05:41,480 --> 01:05:45,520
Speaker 1: suck it up and pay whatever Mylon decided to charge.

1188
01:05:45,560 --> 01:05:49,040
Speaker 1: There are no words to describe this type of exploitative,

1189
01:05:49,520 --> 01:05:54,120
Speaker 1: morally bankrupt, and sociopathic behavior. It fills me with pure

1190
01:05:54,520 --> 01:05:57,960
Speaker 1: disgust that is only amplified by the knowledge that this

1191
01:05:58,080 --> 01:06:03,360
Speaker 1: type of criminality underpins our entire healthcare system, bought politicians,

1192
01:06:03,720 --> 01:06:08,400
Speaker 1: price fixing, price gouging monopolies, every single person involved on

1193
01:06:08,520 --> 01:06:11,600
Speaker 1: the take, with the cost in dollars, sickness and death

1194
01:06:11,960 --> 01:06:15,919
Speaker 1: passed on to the most vulnerable among us. It's disgusting.

1195
01:06:16,280 --> 01:06:18,720
Speaker 1: So next time the media tries to tell you Joe

1196
01:06:18,760 --> 01:06:22,480
Speaker 1: Manchin opposes the reconciliation package because he's just trying to

1197
01:06:22,560 --> 01:06:26,880
Speaker 1: represent his conservative state. Do not fall for their nonsense.

1198
01:06:27,240 --> 01:06:29,960
Speaker 1: His motives are just the same as his daughters, to

1199
01:06:30,040 --> 01:06:35,480
Speaker 1: protect corporate profits and his own personal interests above everything else.

1200
01:06:35,840 --> 01:06:38,960
Speaker 1: And it's so disgusting here, Soger, because you see it all.

1201
01:06:39,360 --> 01:06:42,720
Speaker 1: You see the way that the politician gets his daughter

1202
01:06:42,800 --> 01:06:45,400
Speaker 1: the job. You see the one more thing I promise.

1203
01:06:45,760 --> 01:06:47,960
Speaker 1: Just wanted to make sure you knew about my podcast

1204
01:06:47,960 --> 01:06:50,760
Speaker 1: with Kyle Kolinski. It's called Crystal, Kyle and Friends, where

1205
01:06:50,800 --> 01:06:53,600
Speaker 1: we do long form interviews with people like Nom Chomsky,

1206
01:06:53,680 --> 01:06:56,959
Speaker 1: Cornell West, and Glenn Greenwald. You can listen on any

1207
01:06:57,000 --> 01:07:00,400
Speaker 1: podcast platform, or you can subscribe over on subs to

1208
01:07:00,400 --> 01:07:02,760
Speaker 1: get the video a day early. We're gonna stop bugging

1209
01:07:02,800 --> 01:07:05,800
Speaker 1: you now, enjoy all right, Zager, what are you looking at? Well?

1210
01:07:05,840 --> 01:07:08,880
Speaker 1: Perhaps one of the most frustrating things about DC is

1211
01:07:08,920 --> 01:07:12,400
Speaker 1: watching people just lie, and not just lie, but lie

1212
01:07:12,560 --> 01:07:15,000
Speaker 1: that everybody knows is a lie. The person who's telling

1213
01:07:15,040 --> 01:07:18,400
Speaker 1: it knows it's a lie, the audience knows it's a lie. Ostensibly,

1214
01:07:18,440 --> 01:07:21,560
Speaker 1: there are consequences for lying, at least in your official capacity.

1215
01:07:21,880 --> 01:07:24,040
Speaker 1: But as long as the right party controls levers of

1216
01:07:24,080 --> 01:07:26,920
Speaker 1: power in Congress, most people just get away with it.

1217
01:07:26,960 --> 01:07:29,360
Speaker 1: They lie straight to your face and there's nothing really

1218
01:07:29,360 --> 01:07:31,040
Speaker 1: that you can do about it. And if you haven't

1219
01:07:31,080 --> 01:07:33,680
Speaker 1: picked up on my drift, oh I'm talking about it's

1220
01:07:33,720 --> 01:07:37,360
Speaker 1: doctor Anthony Fauci recent exchange with Senator Ran Paul of Kentucky,

1221
01:07:37,560 --> 01:07:40,280
Speaker 1: in which he denied that the National Institute of Health

1222
01:07:40,400 --> 01:07:44,120
Speaker 1: ever funded gain of function research at the Wuhan Institute

1223
01:07:44,160 --> 01:07:47,439
Speaker 1: of Virology. This fact, of course, is being relevant because

1224
01:07:47,480 --> 01:07:50,120
Speaker 1: there is a high degree of probability that the gain

1225
01:07:50,160 --> 01:07:53,480
Speaker 1: of function research being conducted at the Wuhan lab is

1226
01:07:53,560 --> 01:07:58,400
Speaker 1: responsible for the outbreak of coronavirus. Now, let's review Fauci

1227
01:07:58,480 --> 01:08:01,760
Speaker 1: and Paul's exchange on July twentieth, twenty twenty one, to

1228
01:08:01,800 --> 01:08:04,400
Speaker 1: see exactly the lie that he told before that body.

1229
01:08:05,240 --> 01:08:07,680
Speaker 1: Doctor Fauci, knowing that it is a crime to lie

1230
01:08:07,720 --> 01:08:10,600
Speaker 1: to Congress, do you wish to retract your statement of

1231
01:08:10,640 --> 01:08:13,920
Speaker 1: May eleventh, where you claimed that the NIH never funded

1232
01:08:13,920 --> 01:08:17,280
Speaker 1: gain of function research in Wuhan. Senator Poll, I have

1233
01:08:17,400 --> 01:08:21,360
Speaker 1: never lied before the Congress, and I do not retract

1234
01:08:21,960 --> 01:08:26,479
Speaker 1: that statement. This paper that you were referring to was

1235
01:08:26,600 --> 01:08:31,080
Speaker 1: judged by qualified staff up and down the chain as

1236
01:08:31,120 --> 01:08:35,799
Speaker 1: not being gain of function. What was Let me finish,

1237
01:08:35,880 --> 01:08:39,519
Speaker 1: shake an animal virus and you increase the transibility to humans. Right,

1238
01:08:39,560 --> 01:08:42,120
Speaker 1: you're saying that's not gain of function. That is correct.

1239
01:08:42,200 --> 01:08:45,080
Speaker 1: And Senator Pool, you do not know what you were

1240
01:08:45,120 --> 01:08:48,840
Speaker 1: talking about, quite frankly, and I want to say that officially,

1241
01:08:49,280 --> 01:08:52,960
Speaker 1: you do not know what you were talking about. Okay,

1242
01:08:53,000 --> 01:08:56,920
Speaker 1: you get an read for the NIH Can I gain function?

1243
01:08:57,080 --> 01:09:00,840
Speaker 1: This is your definition that you guys wrote. It says

1244
01:09:00,880 --> 01:09:06,240
Speaker 1: that scientific research that increases the transmility of transmissibility among

1245
01:09:06,320 --> 01:09:10,559
Speaker 1: animals is gain of function. They took animal viruses that

1246
01:09:10,720 --> 01:09:14,960
Speaker 1: only occur in animals and they increase their transmissibility to humans.

1247
01:09:15,240 --> 01:09:17,280
Speaker 1: How you can say that is not gain of function?

1248
01:09:17,400 --> 01:09:19,960
Speaker 1: It is not. It's a dance and you're dancing around

1249
01:09:19,960 --> 01:09:23,920
Speaker 1: this because you're trying to obscure responsibility for four million

1250
01:09:23,960 --> 01:09:28,120
Speaker 1: people dying around the world from a pandemic. There you

1251
01:09:28,160 --> 01:09:31,519
Speaker 1: have it. Rand Paul gave Fauci every opportunity to retract

1252
01:09:31,520 --> 01:09:35,000
Speaker 1: his lie at the National Institute of Health and THENIAID

1253
01:09:35,600 --> 01:09:39,559
Speaker 1: ever funded gain of function research at the Wuhan lab. Fauci,

1254
01:09:39,760 --> 01:09:42,400
Speaker 1: as you see, plays word games. He tries to distract.

1255
01:09:42,560 --> 01:09:45,320
Speaker 1: He says, yeah, yeah, we funded research at the Wuhan

1256
01:09:45,439 --> 01:09:49,200
Speaker 1: Lab that enhanced back coronaviruses. But you see, technically we

1257
01:09:49,360 --> 01:09:51,880
Speaker 1: just don't call it gain of function. At the time,

1258
01:09:52,080 --> 01:09:54,280
Speaker 1: it was transparent and it was a word game. It

1259
01:09:54,320 --> 01:09:57,400
Speaker 1: was a lie to mislead the American public. But now

1260
01:09:57,439 --> 01:10:00,839
Speaker 1: we have something even better. It's smoking gun that Fauci

1261
01:10:00,920 --> 01:10:03,280
Speaker 1: did in fact lie to Congress. And it is in

1262
01:10:03,320 --> 01:10:06,040
Speaker 1: not some quack who is saying this this time, it

1263
01:10:06,080 --> 01:10:10,439
Speaker 1: is cold hard documents from the EcoHealth Alliance themselves, that

1264
01:10:10,479 --> 01:10:13,080
Speaker 1: group which served as the conduit as the funding for

1265
01:10:13,120 --> 01:10:16,080
Speaker 1: gain of function research to the Wuhan Lab from our

1266
01:10:16,120 --> 01:10:19,000
Speaker 1: own government. The documents were released by the Freedom of

1267
01:10:19,000 --> 01:10:22,960
Speaker 1: Information Act requests to the intercept. They show details of

1268
01:10:23,040 --> 01:10:26,439
Speaker 1: the exact grants provided by the National Institute of Health

1269
01:10:26,760 --> 01:10:30,479
Speaker 1: under the direction of Fauci and Francis Collins for gain

1270
01:10:30,640 --> 01:10:34,439
Speaker 1: of function research. Critically, this is the particular part from

1271
01:10:34,479 --> 01:10:37,960
Speaker 1: doctor Richard ebright Of, a professor of chemistry and biology

1272
01:10:38,000 --> 01:10:42,200
Speaker 1: at Rutgers, who reviewed these documents. Quote the materials show

1273
01:10:42,479 --> 01:10:46,040
Speaker 1: that the twenty fourteen twenty nineteen NIH grants to Eco

1274
01:10:46,120 --> 01:10:49,679
Speaker 1: Health with subcontracts to the Wuhan Institute of Virology funded

1275
01:10:49,800 --> 01:10:53,840
Speaker 1: gain of function research as defined in federal policy in

1276
01:10:53,880 --> 01:10:58,400
Speaker 1: effect from twenty fourteen to twenty seventeen, and potential pat

1277
01:10:58,400 --> 01:11:02,599
Speaker 1: pandemic pathogen enhancement as defined in federal policy in effect

1278
01:11:02,600 --> 01:11:06,280
Speaker 1: from twenty seventeen to present. In other words, the documents

1279
01:11:06,400 --> 01:11:09,640
Speaker 1: prove that Fauci's own guidelines, which he wrote himself, that

1280
01:11:09,680 --> 01:11:12,360
Speaker 1: he was lying to Congress, the National Institute of Health

1281
01:11:12,520 --> 01:11:15,240
Speaker 1: funded gain a function research at the Wuhan Lab, while

1282
01:11:15,280 --> 01:11:18,679
Speaker 1: we knew the broad contours of that at an official level,

1283
01:11:18,880 --> 01:11:21,800
Speaker 1: that is no longer in dispute, which means that this

1284
01:11:21,840 --> 01:11:25,080
Speaker 1: is a lie that Fauci told. And yet, whenever this

1285
01:11:25,160 --> 01:11:27,960
Speaker 1: information comes to light on Tuesday, did it even break

1286
01:11:28,080 --> 01:11:31,760
Speaker 1: national news? Of course not. CNN even had Fauci on

1287
01:11:31,880 --> 01:11:34,639
Speaker 1: their network after the release of the documents, they didn't

1288
01:11:34,640 --> 01:11:36,720
Speaker 1: ask him about it. White House won't address it either.

1289
01:11:37,000 --> 01:11:39,920
Speaker 1: To date, not a single major outlet save Fox News,

1290
01:11:39,960 --> 01:11:43,200
Speaker 1: has even covered the documents, and no Democratic legislature has

1291
01:11:43,240 --> 01:11:45,519
Speaker 1: said a word. Whenever it got picked up and it

1292
01:11:45,560 --> 01:11:48,400
Speaker 1: was trending on Twitter, Twitter actually covered up the reason

1293
01:11:48,400 --> 01:11:50,760
Speaker 1: it was trending, saying that he was trending because he

1294
01:11:50,880 --> 01:11:54,120
Speaker 1: was talking about hospital ICU beds when it was really

1295
01:11:54,160 --> 01:11:57,160
Speaker 1: about how he got caught straight up lying to Congress.

1296
01:11:57,439 --> 01:12:00,000
Speaker 1: But Fauci's lies are not even the only things revealed

1297
01:12:00,120 --> 01:12:03,439
Speaker 1: in this document dump. Even more disturbing are the description

1298
01:12:03,680 --> 01:12:07,840
Speaker 1: by EcoHealth Alliance of the conditions within the lab just

1299
01:12:07,920 --> 01:12:11,040
Speaker 1: how dangerous this type of research is to conduct. Their

1300
01:12:11,080 --> 01:12:15,679
Speaker 1: own grant proposal says quote field work involves the highest

1301
01:12:15,760 --> 01:12:19,640
Speaker 1: risk of exposure to sahars or coves while working in

1302
01:12:19,680 --> 01:12:24,040
Speaker 1: caves with high bat density overhead and potential for fecal

1303
01:12:24,160 --> 01:12:27,720
Speaker 1: dust to be inhaled. More So, Elena Chan, a molecular

1304
01:12:27,720 --> 01:12:31,360
Speaker 1: biologist who reviewed the documents, told the Intercept quote in

1305
01:12:31,400 --> 01:12:34,799
Speaker 1: this proposal, they point out that they know how risky

1306
01:12:34,880 --> 01:12:38,280
Speaker 1: this work is. They keep talking about how people potentially

1307
01:12:38,280 --> 01:12:41,680
Speaker 1: getting bitten, and they keep records of everyone who has

1308
01:12:41,760 --> 01:12:45,519
Speaker 1: gotten bitten. So here's the question, where do those records

1309
01:12:45,560 --> 01:12:49,439
Speaker 1: exist today? Does Eco Health Alliance maintain a database of

1310
01:12:49,479 --> 01:12:51,799
Speaker 1: all of those who were bitten by bats and monkeys

1311
01:12:51,840 --> 01:12:54,759
Speaker 1: inside the Wuhan Institute of Virology. I'd love to answer

1312
01:12:54,800 --> 01:12:56,880
Speaker 1: that question. And if we had a real government that

1313
01:12:57,040 --> 01:12:59,439
Speaker 1: wasn't obsessed with January sixth, and we had a Wuhan

1314
01:12:59,479 --> 01:13:02,639
Speaker 1: commission instead. Those are the types of things they might

1315
01:13:02,640 --> 01:13:04,439
Speaker 1: be able to get their hands on. But that's not

1316
01:13:04,479 --> 01:13:07,400
Speaker 1: the problem. Is it it's a lie? Is it a lie?

1317
01:13:07,439 --> 01:13:10,360
Speaker 1: If nobody acknowledges the lie, and nobody investigates the lie,

1318
01:13:10,360 --> 01:13:13,240
Speaker 1: and nobody has any consequences for telling the lie. That's

1319
01:13:13,240 --> 01:13:16,320
Speaker 1: the more philosophical question that I am prepared to answer.

1320
01:13:16,680 --> 01:13:19,960
Speaker 1: But the more information that comes out regarding this situation,

1321
01:13:20,320 --> 01:13:22,320
Speaker 1: the more clear it is that the very people in

1322
01:13:22,400 --> 01:13:25,160
Speaker 1: charge of running the pandemic may have caused this thing

1323
01:13:25,320 --> 01:13:28,160
Speaker 1: in the first place. That's kind of the amazing part here, Crystal,

1324
01:13:28,240 --> 01:13:30,720
Speaker 1: not only in terms of the document on Fauci, but

1325
01:13:30,760 --> 01:13:33,599
Speaker 1: also they're like, this is all right. We are very

1326
01:13:33,680 --> 01:13:35,960
Speaker 1: lucky to be joined now by one of my absolute

1327
01:13:36,080 --> 01:13:40,200
Speaker 1: favorite authors, which is actually true. His book The People

1328
01:13:40,360 --> 01:13:43,439
Speaker 1: Know is now out on paperback. He's also author of

1329
01:13:43,720 --> 01:13:47,080
Speaker 1: What's the Matter with Kansas? Listen Liberal? What other ones

1330
01:13:47,160 --> 01:13:52,160
Speaker 1: you got out there? The Wrecking Crew? This About this Town? Yeah,

1331
01:13:52,200 --> 01:13:55,559
Speaker 1: there we go, My study of Washington, DC. You should

1332
01:13:55,600 --> 01:13:58,360
Speaker 1: literally read all of his books. I cannot recommend them

1333
01:13:58,400 --> 01:14:01,400
Speaker 1: highly enough. Great to see you to it's so great

1334
01:14:01,439 --> 01:14:05,240
Speaker 1: to be here and you guys, congratulations on everything, all

1335
01:14:05,280 --> 01:14:08,120
Speaker 1: the success that that you've had with your show. Thank you, Joe,

1336
01:14:08,479 --> 01:14:10,360
Speaker 1: thank you very much. Well. I mean, you're an inspiration

1337
01:14:10,400 --> 01:14:12,080
Speaker 1: in a lot of ways of some of the core

1338
01:14:12,120 --> 01:14:14,760
Speaker 1: themes of the show. One of the things that you

1339
01:14:14,840 --> 01:14:18,960
Speaker 1: were extraordinarily prescient on, which is relevant to the release

1340
01:14:19,040 --> 01:14:21,960
Speaker 1: of your book in paperback, is the way that the

1341
01:14:22,000 --> 01:14:26,880
Speaker 1: pandemic has been used to once again vilify populism and

1342
01:14:27,439 --> 01:14:31,960
Speaker 1: meaning vilifying regular people and weaponizing this all to say, look,

1343
01:14:32,000 --> 01:14:35,920
Speaker 1: these people are idiots. Trust us, were the scientists, Yes,

1344
01:14:36,160 --> 01:14:39,479
Speaker 1: we got this covered. I know. So I'm so sick

1345
01:14:39,520 --> 01:14:41,840
Speaker 1: of it that I you know, it's almost it's and

1346
01:14:41,880 --> 01:14:44,120
Speaker 1: it's also to me so obvious and it's hard to

1347
01:14:44,160 --> 01:14:47,519
Speaker 1: talk about. But the whole you know, last four years,

1348
01:14:47,520 --> 01:14:50,920
Speaker 1: it feels like it's been a kind of struggle of

1349
01:14:50,960 --> 01:14:56,160
Speaker 1: what you would call authorized authorities to suppress various challenges

1350
01:14:56,200 --> 01:14:58,519
Speaker 1: to themselves. And one of the things that you you know,

1351
01:14:58,400 --> 01:15:00,519
Speaker 1: you see all these things that they were saying, you know,

1352
01:15:00,880 --> 01:15:04,280
Speaker 1: there's something something has gone wrong with the American people.

1353
01:15:04,320 --> 01:15:08,400
Speaker 1: They don't respect, they don't respect credentialed authority anymore. They

1354
01:15:08,400 --> 01:15:11,040
Speaker 1: were saying this four years ago, and then the pandemic

1355
01:15:11,120 --> 01:15:14,400
Speaker 1: seemed to make that even more urgent. You know, we

1356
01:15:14,479 --> 01:15:17,000
Speaker 1: had to respect science, we had to listen to the science,

1357
01:15:17,000 --> 01:15:21,120
Speaker 1: et cetera, et cetera, which, of course I do. I'm vaccinated,

1358
01:15:21,120 --> 01:15:23,320
Speaker 1: I wear a mask, I do all those things. But

1359
01:15:23,400 --> 01:15:27,640
Speaker 1: it's it's been a fascinating time that the especially the

1360
01:15:27,680 --> 01:15:30,679
Speaker 1: way to get back to the original subject, the way

1361
01:15:30,840 --> 01:15:36,439
Speaker 1: the sort of American commentary class has turned against what

1362
01:15:36,520 --> 01:15:40,080
Speaker 1: they what they call populism. This is fascinating to me.

1363
01:15:40,360 --> 01:15:44,040
Speaker 1: You know, way back when in the nineteen eighties, I

1364
01:15:44,080 --> 01:15:46,599
Speaker 1: went to graduate school in history and I thought, well,

1365
01:15:46,640 --> 01:15:49,280
Speaker 1: I'm going to you know, I'm going to study populism.

1366
01:15:49,360 --> 01:15:52,280
Speaker 1: I was fascinated by this movement from the eighteen nineties,

1367
01:15:52,840 --> 01:15:57,720
Speaker 1: and historians generally speaking, really were fond of populism. They

1368
01:15:57,720 --> 01:16:00,360
Speaker 1: wrote nice things about it. There's this great book that

1369
01:16:00,400 --> 01:16:02,280
Speaker 1: came out in the seventies. You know, all these people

1370
01:16:02,320 --> 01:16:05,800
Speaker 1: were writing about it. Everybody loved populism, and there were

1371
01:16:05,840 --> 01:16:08,400
Speaker 1: a lot of people in Washington that liked populism too.

1372
01:16:08,640 --> 01:16:11,320
Speaker 1: I remember there was a faction of sort of left

1373
01:16:11,320 --> 01:16:15,360
Speaker 1: wing Democrats that called their annual meeting like the New

1374
01:16:15,479 --> 01:16:18,080
Speaker 1: Populist Conference or so, I forget what that what they

1375
01:16:18,160 --> 01:16:22,160
Speaker 1: called it. Barack Obama even called himself a populist at

1376
01:16:22,200 --> 01:16:24,639
Speaker 1: one Wow. And then and then all of a sudden

1377
01:16:24,680 --> 01:16:28,280
Speaker 1: it changed, you know, and instead they decided, no, populists

1378
01:16:28,280 --> 01:16:32,920
Speaker 1: are these terrible, these these sort of monstrous, the monstrous creatures.

1379
01:16:33,600 --> 01:16:36,600
Speaker 1: Populists are people that don't know their rightful place in

1380
01:16:36,640 --> 01:16:40,240
Speaker 1: the hierarchy, by which I mean they're lowly placed. Yeah,

1381
01:16:40,320 --> 01:16:45,840
Speaker 1: Populists are people that don't listen to authorized authority. And

1382
01:16:46,080 --> 01:16:49,479
Speaker 1: it's it's just been the strangest damn thing anyhow, So

1383
01:16:49,520 --> 01:16:51,680
Speaker 1: I tried wrote a whole book about it. You know,

1384
01:16:51,720 --> 01:16:54,040
Speaker 1: it's interesting time. Let's go in and put your most

1385
01:16:54,040 --> 01:16:56,479
Speaker 1: recent article here up on the screen. It's the healthcare

1386
01:16:56,520 --> 01:17:00,439
Speaker 1: system stupid in lemon diplomatique and so whenever, what are

1387
01:17:00,479 --> 01:17:03,240
Speaker 1: you trying to get at there? In terms of populace

1388
01:17:03,280 --> 01:17:06,479
Speaker 1: is now an insult in the US, especially when applied

1389
01:17:06,479 --> 01:17:09,519
Speaker 1: to the anti expertise reactions to the current pandemic. But

1390
01:17:09,560 --> 01:17:11,800
Speaker 1: the true history of US populism is a long fight

1391
01:17:11,880 --> 01:17:15,439
Speaker 1: to replace medical experts at the service of the well

1392
01:17:15,439 --> 01:17:17,280
Speaker 1: being of ordinary people. What do you mean by that

1393
01:17:17,320 --> 01:17:20,320
Speaker 1: in the context of this pandemic. So I'm fascinated by

1394
01:17:20,400 --> 01:17:24,280
Speaker 1: this idea that the populism, that what it means is

1395
01:17:24,320 --> 01:17:29,000
Speaker 1: a rebuke of learning, because it's not. Historically, if you

1396
01:17:29,040 --> 01:17:32,799
Speaker 1: look at the original populist movement, it was uprising against

1397
01:17:32,880 --> 01:17:35,120
Speaker 1: the elites of the time of the eighteen nineties. But

1398
01:17:35,640 --> 01:17:41,840
Speaker 1: the populists did not dislike learning itself. They respected it,

1399
01:17:41,920 --> 01:17:45,000
Speaker 1: they honored it. These were this was a mass movement

1400
01:17:45,200 --> 01:17:47,280
Speaker 1: of farmers and workers. By the way, they were not

1401
01:17:47,360 --> 01:17:52,439
Speaker 1: highly educated people, but they did admire learning and they

1402
01:17:52,560 --> 01:17:56,360
Speaker 1: tried to you know, they would have experts on economics

1403
01:17:56,360 --> 01:17:58,760
Speaker 1: and political science and whatnot come out in lecture to

1404
01:17:58,840 --> 01:18:01,479
Speaker 1: their local farmers alliance and this kind of thing. So

1405
01:18:01,760 --> 01:18:04,200
Speaker 1: I was puzzled by that. And every time I heard

1406
01:18:04,280 --> 01:18:07,519
Speaker 1: someone say that populism was this rejection of science, I

1407
01:18:07,520 --> 01:18:12,120
Speaker 1: said to myself, what would a populist healthcare system actually

1408
01:18:12,160 --> 01:18:15,479
Speaker 1: look like? You know, let's let's reframe the question slightly.

1409
01:18:15,800 --> 01:18:17,400
Speaker 1: And once you put it that way and you start

1410
01:18:17,400 --> 01:18:21,960
Speaker 1: digging in the history of populist movements in America, you

1411
01:18:22,000 --> 01:18:23,920
Speaker 1: know what, and you know what would they what would

1412
01:18:23,960 --> 01:18:26,799
Speaker 1: they do about the healthcare situation? That we're in the answer,

1413
01:18:27,320 --> 01:18:31,280
Speaker 1: it becomes apparent immediately what populous were about was not

1414
01:18:32,200 --> 01:18:36,839
Speaker 1: rejecting medical expertise. It was about making medicine available to everyone,

1415
01:18:36,960 --> 01:18:40,519
Speaker 1: making medical expertise available to everyone. This is and there

1416
01:18:40,560 --> 01:18:43,360
Speaker 1: are many examples of this, probably the most famous being

1417
01:18:43,439 --> 01:18:46,280
Speaker 1: Harry Truman's you know, universal health care plan in the

1418
01:18:46,320 --> 01:18:50,040
Speaker 1: nineteen forties, which which you know didn't go anywhere. But

1419
01:18:50,360 --> 01:18:53,320
Speaker 1: the idea was not to reject medical science. It was

1420
01:18:53,320 --> 01:18:57,960
Speaker 1: to make it accessible to everyone. And the really fascinating

1421
01:18:58,600 --> 01:19:01,320
Speaker 1: side of this, and once you start looking into this

1422
01:19:01,600 --> 01:19:06,720
Speaker 1: is not populism's war on science. Populism respected science. It's

1423
01:19:06,800 --> 01:19:10,880
Speaker 1: science's war on populism, by which I mean the medical

1424
01:19:10,920 --> 01:19:15,439
Speaker 1: profession who stopped Truman's health care plan, right the AMA. Yeah,

1425
01:19:15,720 --> 01:19:18,320
Speaker 1: And what were the grounds on which they stopped it?

1426
01:19:18,360 --> 01:19:23,000
Speaker 1: They said, this was this was unethical to have politicians being,

1427
01:19:23,200 --> 01:19:25,479
Speaker 1: you know, being able to order doctors around. It's a

1428
01:19:25,520 --> 01:19:28,280
Speaker 1: reversal of the traditional hierarchy. You know, how can that

1429
01:19:28,360 --> 01:19:31,519
Speaker 1: be permitted? It can't, And this is still the argument today.

1430
01:19:31,680 --> 01:19:34,160
Speaker 1: You know, you have to know your place in the

1431
01:19:34,200 --> 01:19:37,800
Speaker 1: social hierarchy. One of the things that we've tracked with

1432
01:19:38,120 --> 01:19:42,400
Speaker 1: interest and oftentimes discussed is the way that you know,

1433
01:19:42,479 --> 01:19:45,960
Speaker 1: the media has loved these stories of like, oh, look

1434
01:19:46,000 --> 01:19:49,559
Speaker 1: at these people having a pool party, or look at

1435
01:19:49,560 --> 01:19:52,479
Speaker 1: this moron who didn't get vaccinated and now he's dead,

1436
01:19:52,760 --> 01:19:56,080
Speaker 1: and effectively cheerleading that and turning it all into this

1437
01:19:56,160 --> 01:19:59,200
Speaker 1: individual responsibility narrative. There's been a lot less interest in

1438
01:19:59,200 --> 01:20:01,800
Speaker 1: asking the question of, oh, hey, why is it that

1439
01:20:01,880 --> 01:20:05,679
Speaker 1: so many other developed nations have a better healthcare system?

1440
01:20:05,920 --> 01:20:08,559
Speaker 1: That lo and behold has led to more people getting

1441
01:20:08,600 --> 01:20:11,679
Speaker 1: vaccinated because they have a relationship with the healthcare system

1442
01:20:11,680 --> 01:20:13,840
Speaker 1: where you have millions of Americans have no relationship with

1443
01:20:13,880 --> 01:20:16,719
Speaker 1: the helpcareers, and in that relationship, they hate and fear

1444
01:20:16,880 --> 01:20:19,519
Speaker 1: the medical st right. They know that's where you go

1445
01:20:19,600 --> 01:20:22,519
Speaker 1: to get bankrupt, that's right. You know. We actually covered

1446
01:20:22,600 --> 01:20:27,720
Speaker 1: a survey where some proportion of people who were uninsured,

1447
01:20:27,920 --> 01:20:29,920
Speaker 1: who by the way, the uninsured er less likely to

1448
01:20:29,920 --> 01:20:33,240
Speaker 1: get vaccinated. One of their fears was that, I know

1449
01:20:33,280 --> 01:20:35,400
Speaker 1: they say it's free, but I think I'm going to

1450
01:20:35,439 --> 01:20:38,599
Speaker 1: get charged. Of course, not without justification, shutting down the road,

1451
01:20:38,640 --> 01:20:41,639
Speaker 1: and who knows how they'll add on to it. And yeah,

1452
01:20:41,680 --> 01:20:44,960
Speaker 1: there is tons of suspicion of that of that kind

1453
01:20:45,000 --> 01:20:48,000
Speaker 1: of thing, but also ask yourself, how did this become

1454
01:20:48,720 --> 01:20:50,280
Speaker 1: a culture war? I mean, this is one of the

1455
01:20:50,360 --> 01:20:53,760
Speaker 1: most lamentable aspects of this whole thing, and a big

1456
01:20:53,800 --> 01:20:57,000
Speaker 1: part of it is exactly what you're describing, This determination

1457
01:20:57,400 --> 01:21:00,360
Speaker 1: of the of the sort of well educated in our

1458
01:21:00,400 --> 01:21:04,920
Speaker 1: society to you know, rub the faces of their inferiors

1459
01:21:05,000 --> 01:21:07,519
Speaker 1: in in their you know, in their failure and their

1460
01:21:07,560 --> 01:21:10,000
Speaker 1: sickness and this kind of thing. It's like, that's not

1461
01:21:10,160 --> 01:21:12,479
Speaker 1: how you persuade people. I don't know, maybe this is

1462
01:21:12,520 --> 01:21:14,920
Speaker 1: gonna be this is I think this is like a

1463
01:21:14,960 --> 01:21:20,280
Speaker 1: really novel idea to a lot of Americans. But scolding

1464
01:21:20,320 --> 01:21:24,479
Speaker 1: people doesn't generally bring them around. Scolding people in this manner,

1465
01:21:25,000 --> 01:21:27,720
Speaker 1: And I often think, you know, in the in the

1466
01:21:28,280 --> 01:21:31,920
Speaker 1: big picture historical, you know, like, how would you handle

1467
01:21:32,000 --> 01:21:34,599
Speaker 1: either We've had other pandemics in American life, and we've

1468
01:21:34,640 --> 01:21:39,160
Speaker 1: handled them much better. And why is that. Well, one

1469
01:21:39,160 --> 01:21:42,599
Speaker 1: of the reasons is because the people who are causing,

1470
01:21:42,680 --> 01:21:45,320
Speaker 1: you know, who are not getting vaccinated now. Back then

1471
01:21:45,520 --> 01:21:49,960
Speaker 1: had organizations that you could go to, for example, labor unions,

1472
01:21:50,000 --> 01:21:54,120
Speaker 1: for example, neighborhood clubs, you know, whatever, churches, whatever, and

1473
01:21:54,400 --> 01:21:59,280
Speaker 1: those organizations are by and large gone today, and so

1474
01:21:59,439 --> 01:22:04,400
Speaker 1: they experience this whole conversation about healthcare and vaccinations as

1475
01:22:04,520 --> 01:22:08,519
Speaker 1: one way street, as people like us yelling at people

1476
01:22:08,600 --> 01:22:11,880
Speaker 1: like them, and that's just not a good way to,

1477
01:22:12,800 --> 01:22:15,240
Speaker 1: you know, to sell this stuff. No, you're exactly right.

1478
01:22:15,320 --> 01:22:17,160
Speaker 1: And part of the thing we tracked this in our

1479
01:22:17,160 --> 01:22:20,040
Speaker 1: show today, there is a new call. Jimmy Kimmel just

1480
01:22:20,080 --> 01:22:22,439
Speaker 1: did a big call yesterday on his show and he

1481
01:22:22,560 --> 01:22:24,280
Speaker 1: was like, you know, and he was making a joke,

1482
01:22:24,320 --> 01:22:26,479
Speaker 1: but he was saying, well, if you're vaccinated and you

1483
01:22:26,479 --> 01:22:28,720
Speaker 1: have a heart attack, will treat you. And if you're

1484
01:22:28,800 --> 01:22:32,840
Speaker 1: not vaccinated, you know, rip essentially just I mean, really

1485
01:22:32,920 --> 01:22:36,440
Speaker 1: celebrating the death of people who won't want to get vaccinated.

1486
01:22:36,760 --> 01:22:40,080
Speaker 1: And oh yeah, as I pointed out, this flies entirely

1487
01:22:40,120 --> 01:22:43,760
Speaker 1: in the face of the original idea behind Obamacare, which

1488
01:22:43,760 --> 01:22:46,360
Speaker 1: you fought to protect, which is you should not be

1489
01:22:46,360 --> 01:22:49,400
Speaker 1: able to deny people healthcare based upon a pre existing condition.

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01:22:49,880 --> 01:22:52,960
Speaker 1: So I'm curious, you know how it because I look,

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01:22:53,000 --> 01:22:55,400
Speaker 1: I've tracked culture war how it rots the brains of

1492
01:22:55,400 --> 01:22:57,240
Speaker 1: people on the right, but it's very clear that it's

1493
01:22:57,280 --> 01:22:59,760
Speaker 1: also very it's very much on the left as well.

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01:23:00,040 --> 01:23:02,080
Speaker 1: I used to write about this as well, remember what's

1495
01:23:02,080 --> 01:23:04,960
Speaker 1: the matter with courses. I was astonished by this once,

1496
01:23:05,160 --> 01:23:07,840
Speaker 1: you know, I started digging into it. It's everywhere now

1497
01:23:07,880 --> 01:23:13,000
Speaker 1: it's both sides. And there's also this, you know, what

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01:23:13,040 --> 01:23:16,320
Speaker 1: you're describing is this kind of punitive impulse on the left,

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01:23:16,680 --> 01:23:20,000
Speaker 1: this impulse to scold and correct and punish, discipline and

1500
01:23:20,040 --> 01:23:24,200
Speaker 1: punish on the left. And that is I don't want

1501
01:23:24,240 --> 01:23:26,360
Speaker 1: to say it's new, because somebody will immediately call in

1502
01:23:26,320 --> 01:23:27,960
Speaker 1: and be like, no, no, no, there's there. We can

1503
01:23:28,000 --> 01:23:29,760
Speaker 1: trace this all the way back to whatever, you know,

1504
01:23:30,040 --> 01:23:32,800
Speaker 1: but it's something that's that that feels new to me

1505
01:23:33,000 --> 01:23:36,920
Speaker 1: and feels recent and feels shocking and feels really uncomfortable.

1506
01:23:36,920 --> 01:23:39,760
Speaker 1: And you see it also in the demands for censorship,

1507
01:23:39,800 --> 01:23:42,840
Speaker 1: which you guys know all about, and uh, you know

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01:23:42,920 --> 01:23:44,960
Speaker 1: this is this is all over the place in the

1509
01:23:45,000 --> 01:23:47,280
Speaker 1: in the the sort of new liberalism, and it's it's

1510
01:23:48,640 --> 01:23:50,240
Speaker 1: and I know we don't have a whole lot of

1511
01:23:50,240 --> 01:23:52,519
Speaker 1: time to go into every argument that I've made in

1512
01:23:52,560 --> 01:23:54,400
Speaker 1: the last couple of years, but I just want to

1513
01:23:54,400 --> 01:23:57,000
Speaker 1: say I want to emphasize this. This is not how

1514
01:23:57,040 --> 01:24:01,719
Speaker 1: you build a left movement. Right scolding people and shushing

1515
01:24:01,720 --> 01:24:04,960
Speaker 1: people and telling people to go off and die. That's

1516
01:24:05,000 --> 01:24:06,920
Speaker 1: not how you do it. Do you think that that's

1517
01:24:06,960 --> 01:24:11,439
Speaker 1: their goal, though, because to me, it's so clear that

1518
01:24:11,439 --> 01:24:15,920
Speaker 1: that scolding and censorship and constant purification of you know,

1519
01:24:16,040 --> 01:24:20,360
Speaker 1: everybody must have always believed the correct things from birth.

1520
01:24:20,840 --> 01:24:23,519
Speaker 1: It's so obvious that that's not the way to build

1521
01:24:23,600 --> 01:24:27,640
Speaker 1: a left movement me. But it seems to me that

1522
01:24:27,640 --> 01:24:29,559
Speaker 1: that's not even their goal. It seems to me that

1523
01:24:29,600 --> 01:24:33,440
Speaker 1: oftentimes the goal is I'm going to show how virtuous

1524
01:24:33,479 --> 01:24:35,679
Speaker 1: I am. I'm going to build my own personal cloud.

1525
01:24:35,720 --> 01:24:37,600
Speaker 1: This is good for my brand, this is good for

1526
01:24:37,640 --> 01:24:41,000
Speaker 1: my personal profile on Twitter or whatever. It's The goal

1527
01:24:41,120 --> 01:24:43,640
Speaker 1: is not to persuade people to get vaccinated or to

1528
01:24:43,680 --> 01:24:47,280
Speaker 1: build a movement that could end in universal healthcare. The

1529
01:24:47,320 --> 01:24:50,880
Speaker 1: goal is their own sort of personal prestige, yeah, righteousness,

1530
01:24:50,920 --> 01:24:55,360
Speaker 1: personal self righteousness, or alternately therapy. Christopher Lash wrote about

1531
01:24:55,360 --> 01:24:59,479
Speaker 1: this back back in the seventies. This is but you're

1532
01:24:59,520 --> 01:25:02,839
Speaker 1: exactly right that the goal is not to build a movement,

1533
01:25:03,240 --> 01:25:06,240
Speaker 1: and uh, you know, it's it's to feel good about yourself,

1534
01:25:06,280 --> 01:25:09,200
Speaker 1: to feel like you're more right. It's the old impulse. Uh,

1535
01:25:09,400 --> 01:25:11,800
Speaker 1: you know, this is This has been a problem in

1536
01:25:13,320 --> 01:25:16,719
Speaker 1: left land since forever that you know, there's there's, there's

1537
01:25:16,760 --> 01:25:20,160
Speaker 1: there's two basic impulses at war. One is, we've got

1538
01:25:20,200 --> 01:25:22,120
Speaker 1: to build if we want to if we want to

1539
01:25:22,160 --> 01:25:24,760
Speaker 1: reform this society in a democratic way, if we want

1540
01:25:24,760 --> 01:25:27,439
Speaker 1: to make healthcare universal, if we want to make the

1541
01:25:27,479 --> 01:25:30,519
Speaker 1: economy not so predatory, you know, if we want to

1542
01:25:30,520 --> 01:25:32,720
Speaker 1: do any of these things, the only way to do

1543
01:25:32,760 --> 01:25:36,240
Speaker 1: it is with a mass movement of ordinary working class people.

1544
01:25:36,320 --> 01:25:38,519
Speaker 1: That is, that's that's how it's done. We know that

1545
01:25:38,640 --> 01:25:41,240
Speaker 1: from history. That's you know, it's that's that's pretty clear.

1546
01:25:41,479 --> 01:25:45,960
Speaker 1: The other impulse on the left is I'm better than you,

1547
01:25:45,960 --> 01:25:49,760
Speaker 1: you know, and the people who are who are on

1548
01:25:49,800 --> 01:25:52,519
Speaker 1: the left for that reason, are not generally interested in

1549
01:25:52,560 --> 01:25:55,799
Speaker 1: building a mass movement. They're interested in purging. They're interested

1550
01:25:55,840 --> 01:26:00,000
Speaker 1: in kicking people out. They're interested in subtraction, not addition. Yeah,

1551
01:26:00,200 --> 01:26:02,640
Speaker 1: it's interesting, especially in the context and we have this

1552
01:26:02,680 --> 01:26:04,760
Speaker 1: tear sheet. Let's ahead and put the Guardian one up

1553
01:26:04,800 --> 01:26:06,280
Speaker 1: there on the screen, because I do think this is

1554
01:26:06,360 --> 01:26:11,360
Speaker 1: very important. That's a good photo. No, for those who

1555
01:26:11,400 --> 01:26:14,439
Speaker 1: are just listening, it's liberals want to blame right wing

1556
01:26:14,479 --> 01:26:17,439
Speaker 1: misinformation for our problems get real. You talk a little

1557
01:26:17,439 --> 01:26:21,800
Speaker 1: bit a story there of listening to a speech by

1558
01:26:21,880 --> 01:26:25,880
Speaker 1: Hillary Clinton and Melinda Gates, which I can't imagine that was.

1559
01:26:25,920 --> 01:26:28,400
Speaker 1: That was I remember that like it was yesterday. Tell

1560
01:26:28,479 --> 01:26:32,240
Speaker 1: us about what it was. In twenty fifteen, I was

1561
01:26:32,280 --> 01:26:35,599
Speaker 1: writing Listen Liberal, and I went to a Clinton Foundation

1562
01:26:35,680 --> 01:26:39,479
Speaker 1: event in New York and they were a big part

1563
01:26:39,479 --> 01:26:43,280
Speaker 1: of it was celebrating social media as as a kind

1564
01:26:43,280 --> 01:26:48,760
Speaker 1: of millennium. You know, social media had had destroyed all

1565
01:26:48,840 --> 01:26:52,640
Speaker 1: the barriers to uh, you know, to anybody can participate

1566
01:26:52,680 --> 01:26:56,479
Speaker 1: in any conversation. Now, social media was like it was like,

1567
01:26:57,800 --> 01:26:59,840
Speaker 1: I mean, it's like a religious thing. It was. It

1568
01:26:59,880 --> 01:27:02,880
Speaker 1: was the dawning of of of the of the Golden

1569
01:27:02,920 --> 01:27:04,960
Speaker 1: Age or something like that. And they they they all

1570
01:27:05,000 --> 01:27:07,280
Speaker 1: agreed on this, and we were supposed to sort of

1571
01:27:07,320 --> 01:27:11,040
Speaker 1: worship Silicon Valley and worship the entrepreneurs who had built

1572
01:27:11,920 --> 01:27:15,080
Speaker 1: social media. And I thought that was very, very amusing.

1573
01:27:15,160 --> 01:27:19,639
Speaker 1: It was all about like complete freedom of expression, you know, Facebook, Twitter,

1574
01:27:19,760 --> 01:27:24,040
Speaker 1: it's so so so wonderful. And now these I don't

1575
01:27:24,040 --> 01:27:27,799
Speaker 1: know if it's the same liberals, but but but generally speaking,

1576
01:27:27,920 --> 01:27:31,000
Speaker 1: liberals from that faction of the Democratic party are so

1577
01:27:31,760 --> 01:27:36,200
Speaker 1: keen to censor social media and you know, to to

1578
01:27:36,320 --> 01:27:39,160
Speaker 1: suppress misinformation. By the way, I was thinking about this

1579
01:27:39,240 --> 01:27:43,439
Speaker 1: on the way over here, because you know, we're I've

1580
01:27:43,439 --> 01:27:45,799
Speaker 1: been on the left a long time. I'm considerably older

1581
01:27:45,800 --> 01:27:49,160
Speaker 1: than you guys, and censorship was always something that we

1582
01:27:49,200 --> 01:27:51,479
Speaker 1: identified with the other side. We see something that this

1583
01:27:51,560 --> 01:27:53,639
Speaker 1: is something that right wingers did. We on the left

1584
01:27:53,720 --> 01:27:57,040
Speaker 1: knew better than that, you know, for all sorts of reasons.

1585
01:27:57,400 --> 01:28:01,080
Speaker 1: But it's it is fascinating to me that the that

1586
01:28:01,120 --> 01:28:04,200
Speaker 1: liberals now are absolutely sold on the idea that we

1587
01:28:04,240 --> 01:28:07,240
Speaker 1: have to suppress misinformation or else they will never be

1588
01:28:07,280 --> 01:28:10,200
Speaker 1: able to win another election in this country. And you know,

1589
01:28:10,240 --> 01:28:12,839
Speaker 1: it's just it's so wrong headed in so many ways.

1590
01:28:13,560 --> 01:28:15,400
Speaker 1: But it also you know, just think of what you

1591
01:28:15,400 --> 01:28:18,559
Speaker 1: could do with that, right if we really are Okay,

1592
01:28:18,600 --> 01:28:21,320
Speaker 1: and I'm counterfactual here, ok, I'm going to play around

1593
01:28:21,320 --> 01:28:24,960
Speaker 1: because I'm I'm not the language police. I'd let people

1594
01:28:25,040 --> 01:28:27,160
Speaker 1: say whatever the hell they want. But I just wrote

1595
01:28:27,160 --> 01:28:31,320
Speaker 1: a whole book about how academics, foundation people, liberals, all

1596
01:28:31,360 --> 01:28:34,679
Speaker 1: these people are using the word populist wrong. Yes, when

1597
01:28:34,680 --> 01:28:38,840
Speaker 1: do I get to suppress them? Hey, guys, thanks so

1598
01:28:38,880 --> 01:28:40,960
Speaker 1: much for watching. If you want to see that full interview,

1599
01:28:41,000 --> 01:28:43,360
Speaker 1: it goes to all of our premium subscribers. We do

1600
01:28:43,400 --> 01:28:45,519
Speaker 1: two of those long form ones per month. This is

1601
01:28:45,600 --> 01:28:48,240
Speaker 1: just one of those awesome conversations. You can become a

1602
01:28:48,280 --> 01:28:51,599
Speaker 1: subscriber right there down in the description. We really appreciate it,

1603
01:28:51,680 --> 01:28:55,080
Speaker 1: and as always, we just appreciate your support so much.

1604
01:28:55,120 --> 01:28:57,680
Speaker 1: It just means absolutely the world keeps us with the

1605
01:28:57,720 --> 01:28:59,800
Speaker 1: ability to do the work here that we do every day.

1606
01:29:00,080 --> 01:29:02,559
Speaker 1: Thank you, absolutely love you, guys. We'll see you next week.

1607
01:29:17,160 --> 01:29:19,479
Speaker 1: Thanks for listening to the show, guys, we really appreciate it.

1608
01:29:19,479 --> 01:29:21,519
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1611
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1613
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