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Speaker 1: You're in the Freedom high This is the Buck Sexton Show.

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Speaker 1: Buck took the day off, but don't worry, We've still

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Speaker 1: got your covered. This is the best of the Buck

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Speaker 1: Sexton Show. Welcome to the Buck Sexton Show. Friends. Honored

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Speaker 1: and privileged to have you here with me. There are

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Speaker 1: only a few names that you can think of from

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Speaker 1: American history that we are all supposed to that we

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Speaker 1: all have some degree of reverence for right that we're

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Speaker 1: supposed to believe no matter who you are, where you

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Speaker 1: come from this country, you're supposed to think, well, that's

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Speaker 1: a great man. There are only a few names where

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Speaker 1: that is the case. And you can start with the

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Speaker 1: founding fathers, the people on Mount Rushmore, and you would

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Speaker 1: add Martin Luther King Junior, and you beat some people

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Speaker 1: would add I don't know. You know, they're a handful

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Speaker 1: of these names out there that when someone says who's

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Speaker 1: a great American and we can all agree on it,

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Speaker 1: there are only a handful of names that come to mind.

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Speaker 1: And for a lot of people, they were at least

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Speaker 1: under the impression until recently that Abraham Lincoln was one

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Speaker 1: of them, that Abraham Lincoln would be free from cancel

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Speaker 1: culture that this would be a guy that we could

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Speaker 1: all agree did something pretty extraordinary and wasn't perfect by

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Speaker 1: any means, But at the end of the day, he

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Speaker 1: was on the right side and was the commander in

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Speaker 1: chief of a military that ended slavery in the United States,

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Speaker 1: and that's a pretty remarkable thing. So we tend to

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Speaker 1: give him a lot of plaudits for this, and as

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Speaker 1: we know, he was assassinated afterwards for it. And but

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Speaker 1: Abraham Lincoln would be one of those names where you'd say, well,

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Speaker 1: the greatness of what he accomplished with the ending of slavery,

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Speaker 1: the greatness that he accomplished with all of this, wouldn't

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Speaker 1: that then him at least somewhat immune to these efforts

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Speaker 1: to destroy historical figures based upon some perception of what

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Speaker 1: they should be that's constantly changing and very new to

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Speaker 1: our current moment. But then I bring you the modern

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Speaker 1: American lib the left, the Democrats, and their wokeness, their

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Speaker 1: psychological disorder known as wokeness, and we have yet another

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Speaker 1: example of just how far that will go. You have

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Speaker 1: Abraham Lincoln as a name that a San Francisco high

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Speaker 1: school board or some kind of a committee that's looking

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Speaker 1: to rename schools, and it's in San fran and they

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Speaker 1: want to get rid of Abraham Lincoln's name from a

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Speaker 1: school because he was I believe the quote is insufficiently

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Speaker 1: committed to black lives mattering or to the matter of

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Speaker 1: black lives. Now, for the man that ordered hundreds of

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Speaker 1: thousands of Americans to their deaths or to extreme pain, mutilation,

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Speaker 1: being wounded on the battlefield to end slavery, to say

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Speaker 1: that he was insufficiently committed to black lives mattering would

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Speaker 1: seem to be the height of insanity, and it is.

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Speaker 1: But there's a reason behind all of this. So we

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Speaker 1: need to start examining what's really going on in this

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Speaker 1: country because we're at this point where we're told that

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Speaker 1: the Democrats are calling for unity, that Joe Biden and

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Speaker 1: his would be cabinet they're saying unify, and as we know,

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Speaker 1: unify really means bend the need of me, do what

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Speaker 1: I say, and we'll call it unity. But while they're

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Speaker 1: calling for this, we also see time and again they

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Speaker 1: don't particularly have any sense of unity to America as

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Speaker 1: we know it. There's something very different going on, and

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Speaker 1: it usually is incremental that this happens. They start with

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Speaker 1: something where we say okay, fine, you know, and this

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Speaker 1: is why when there was that old dust up about

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Speaker 1: about Confederate generals, I was saying, look, I'm I'm not

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Speaker 1: somebody that is gonna carry in any water for the

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Speaker 1: keep up some of these Confederate general's statue side of

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Speaker 1: this brief, it's, you know, it's a community decision, a

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Speaker 1: community standard. But understand this, they're coming for the founding

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Speaker 1: Father's next. In fact, Donald Trump said at the time,

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Speaker 1: well what about Jefferson, what about Washington? Are they gonna

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Speaker 1: Are they gonna tear down those statues? There is here

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Speaker 1: in New York City. I've seen this so many nights

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Speaker 1: because I go for walks sometimes. Right near what is

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Speaker 1: known as Columbus Circle, named for Christopher Columbus, is a

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Speaker 1: very large, very prominent statue of Christopher Columbus. There is

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Speaker 1: an army of NYPD officers that are deployed in a

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Speaker 1: huge circle with barricades, and they've got they've got all

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Speaker 1: kinds of additional e su and vehicles deployed. It's it's crazy.

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Speaker 1: And I've asked the cops. I've said, is this really

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Speaker 1: because you guys are worried that one night, the radical

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Speaker 1: left is just going to show up and destroy this

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Speaker 1: statue of Christopher Columbus. And they said, yes, absolutely, that

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Speaker 1: is why we are deployed here. And this is in

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Speaker 1: one of the ritzier parts of New York City. It's

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Speaker 1: outside the Time Warner Center. So even Deblasio realizes this

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Speaker 1: would get some attention. But they say that Columbus was

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Speaker 1: a genocidal essentially a genocidal maniac who was engaged in

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Speaker 1: the exploitation of humanity and so on and so forth.

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Speaker 1: They don't care that we celebrate Columbus for discovering the

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Speaker 1: New World for Europe and the rest of the world.

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Speaker 1: They don't care about that. That's not enough. And as

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Speaker 1: we see with Abraham Lincoln, it's not enough that he

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Speaker 1: was the commander in chief and the president who led

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Speaker 1: us into war, a war that did end slavery in

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Speaker 1: this country, and that he called for the freeing of

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Speaker 1: the slaves during that war. What's really happening here? There

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Speaker 1: is an essay that I came across. I've never I've

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Speaker 1: never even heard of this publication before, and I haven't

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Speaker 1: heard of this author before. But I thought this essay

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Speaker 1: was extraordinary, and I read constantly of the commentary all

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Speaker 1: over the web, and I'm always looking to see who's

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Speaker 1: worth reading because most of it, ninety percent of what's

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Speaker 1: published on the Internet, even by so called conservatives or

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Speaker 1: whatever it is, Really it's repetitive. It's an echo chamber.

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Speaker 1: It's just not worth spending much time on, at least

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Speaker 1: for me as someone who's reading this stuff all day long.

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Speaker 1: This was really good. It was at unheard dot com

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Speaker 1: and the author is Matthew Crawford, who is a fellow

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Speaker 1: at the Institute for Advanced Studies in Culture at the

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Speaker 1: University of Virginia. The title is How Raised Politics Liberated

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Speaker 1: the Elites And this is absolutely top notch analysis. It's phenomenal. Really,

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Speaker 1: it's a really really strong piece. And here let me

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Speaker 1: give you some of what we're talking about here and

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Speaker 1: why this I think defines our current moment for the

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Speaker 1: Democrat Party and for the left. The idea of a

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Speaker 1: common good, this is a quote from the piece, has

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Speaker 1: given way to a partition of citizens along the lines

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Speaker 1: of a moral hierarchy. Instead of feeling bound up in

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Speaker 1: a shared fate with one's country a countryman, one develops

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Speaker 1: an alternate, alternate solidarity that is placeless, the relatability across

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Speaker 1: national borders that the genteel folk feel in one another's company,

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Speaker 1: the gracious ease and trust, the shared points of reference

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Speaker 1: in high prestige opinion has something to do with their

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Speaker 1: uniformly high standing in the moral hierarchy that divides citizen

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Speaker 1: from citizen within their own nations. The decision making class

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Speaker 1: has discovered that it enjoys the mandate of Heaven, and

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Speaker 1: with this comes certain permissions, certain exemptions from democratic scruple.

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Speaker 1: This is spot on, this is excellent. He's talking about

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Speaker 1: how in our country now, because America, I mean, the

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Speaker 1: short version of this is that because America, according to

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Speaker 1: the left now is inherently racist and misogynist, it gives

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Speaker 1: the elites. It gives this ruling class a mentality that

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Speaker 1: they owe no allegiance to that entity, to America, at

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Speaker 1: least to the idea, to the ideals of traditional America.

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Speaker 1: They have something better, They're working for something better, and

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Speaker 1: so there's no need for them to debase themselves by

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Speaker 1: pretending that our flag waving, jingoistic, we love the founding

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Speaker 1: fathers in the Constitution nonsense, should in any way slow

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Speaker 1: their role. They get to do whatever they want. They

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Speaker 1: know better, you see, they're above it. But this is

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Speaker 1: a version of something I've said to you many times before.

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Speaker 1: There are those of us who take tremendous pride in

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Speaker 1: being American, and then there are those of us who

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Speaker 1: take pride in believing we are better than America, and

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Speaker 1: those are called liberals. Those are leftists. That's what they are,

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Speaker 1: That's how they think. The reason that they're constantly encouraging

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Speaker 1: the most toxic identity politics, racial politics, gender politics, the

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Speaker 1: reason they do this is because they've adopted a philosophy

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Speaker 1: that America is actually bad, that there's this moral rot

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Speaker 1: at the center of this country. They've identified it. It's

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Speaker 1: almost like they stumbled upon some secret knowledge and now

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Speaker 1: they're spreading this great wisdom to all the rest of us.

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Speaker 1: And anyone who rejects this, anyone who sees this for

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Speaker 1: the intense hypocrisy that it is, is shouted down. Part

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Speaker 1: of the patriarchy, part of the racist, misogynistic system. And

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Speaker 1: also it gives the people at the top a total

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Speaker 1: pass for not working for what we think of as

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Speaker 1: the common good, not working for what we consider to

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Speaker 1: be universal American values. They can live their lives. This

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Speaker 1: is why they can fly on private jets to climate

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Speaker 1: change conferences where they're going to talk about how you

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Speaker 1: should be. You know, walking three miles or biking ten

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Speaker 1: miles to work every day can put all that co

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Speaker 1: two in the air. Well, they're above you, you see,

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Speaker 1: they're working for this better world, this better place. You

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Speaker 1: are part of this traditional America that's just so racist

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Speaker 1: and misogynistic and so awful. And so this goes way beyond,

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Speaker 1: even way beyond the usual liberal hypocrisy. This is a

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Speaker 1: kind of religion of elites excellence, and they are devotees

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Speaker 1: of it. And they also get to think of themselves

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Speaker 1: as great heroes for standing up for the oppressed. I mean,

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Speaker 1: how many of you does this sound like your smug

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Speaker 1: neighbor who has a big Biden Harris sign in their yard, right?

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Speaker 1: Don't they always think that they're somehow so morally enlightened,

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Speaker 1: even if their own personal choices are really crappy, and

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Speaker 1: even if they don't really care about other people or

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Speaker 1: help them very much. But they stand for equality. In fact,

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Speaker 1: these days, they stand for equity the preferred term, which

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Speaker 1: is just the quality of outcome, which is Marxism backed

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Speaker 1: into this piece for a second quote. In the Revolt

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Speaker 1: of the Elites, Christopher Lash spelled out in greater detail

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Speaker 1: the role that claims of racial and sexual oppression play

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Speaker 1: in securing release from allegiance to the nation, not just

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Speaker 1: for those who identify as its victims, but for those

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Speaker 1: with the moral sensitivity to see victimization where it may

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Speaker 1: not be a parent, and who make this capacity a

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Speaker 1: touchstone of their identity. It becomes a token of moral

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Speaker 1: elevation by which we recognize one another and distinguish ourselves

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Speaker 1: from the broader run of citizens. Both Lash and Hannah

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Speaker 1: Arrant argue that black Americans serve a crucial function for

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Speaker 1: the white bourgeoisie as the emblement proof of America's illegitimacy.

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Speaker 1: They anchor a politics of repudiation in which the idea

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Speaker 1: of a common good has little purchase end quote, saying,

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Speaker 1: all those elitist, white college educated liberal Democrats out there,

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Speaker 1: the libs who are always talking about racism, they don't

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Speaker 1: do anything to solve racism. They don't spend any time

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Speaker 1: in black majority neighborhoods. They don't really know what's going

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Speaker 1: going on within the black community. But they love pointing

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Speaker 1: out the racism all around them all the time, even

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Speaker 1: where there's no actual racism. Sometimes they do this because

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Speaker 1: by demeaning traditional America American values, by saying that this

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Speaker 1: place is racist and wrong and evil, they're not bound

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Speaker 1: by the generally held conceptions of what makes a good

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Speaker 1: American citizen these days, because they know better. They're above it,

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Speaker 1: they're elevated beyond it. Doesn't this all sound exactly like

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Speaker 1: the ethos the modern philosophy of a democrat. Don't you

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Speaker 1: all have friends that are just like this. They've never

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Speaker 1: actually been in a high crime, majority minority neighborhood for

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Speaker 1: more than a couple of hours or maybe driving through it,

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Speaker 1: But they want to give you lectures about BLM. That's right,

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Speaker 1: They want to lecture you about BLM from their million

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Speaker 1: dollar house in an all white suburb. These are the

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Speaker 1: kind of we're talking about here, The ones who are frauds,

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Speaker 1: the ones who are fakes. How do they get away

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Speaker 1: with this in their own minds? This is how they

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Speaker 1: don't take pride in being Americans. They think they are

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Speaker 1: better than America, They know better than America, and they

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Speaker 1: want to transform this place in this image. And that's

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Speaker 1: what we are facing now going forward, Liberty, truth and

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Speaker 1: great hair. You're listening to the best of the Butt

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Speaker 1: Sexton Show, How Race Politics Liberated the Elites by Matthew Crawford.

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Speaker 1: Unheard dot Com is the site, and I just I

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Speaker 1: thought this was a fascinating analysis. And I like to

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Speaker 1: give people credit when they do something like this that

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Speaker 1: really advances the conversation. Other people just like to rip

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Speaker 1: people off and pretend it's there's no I want. I

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Speaker 1: want Matthew Crawford to get the High five deserves for this,

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Speaker 1: and he goes on, and I think we have to remember,

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Speaker 1: there's another way to prove this analysis or this line

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Speaker 1: of thinking, the legitimacy, the integrity of this philosophical approach,

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Speaker 1: because it's not only in America that this actually has

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Speaker 1: now spread. It's gone beyond American borders. So you'd think

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Speaker 1: that the left's unique revulsion at the longstanding history of

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Speaker 1: slavery in this country and then Jim Crow and segregation,

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Speaker 1: and you know, they say that they're they're confronting that

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Speaker 1: even today. That's what the left will tell you. But

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Speaker 1: yet there are BLM protests in London, in Paris, in Germany,

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Speaker 1: and the author points this out. This illegitimacy transcends any

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Speaker 1: particular historical facts about slavery and segregation, and indeed transcends America,

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Speaker 1: as one can surmise by the ease was with which

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Speaker 1: American grievance politics have been exported throughout the Western world.

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Speaker 1: In this we sometimes see the use of historical American

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Speaker 1: references that have been weirdly transposed, as when a house

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Speaker 1: once lived in by Rosa Parks was relocated from Detroit

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Speaker 1: to Berlin, the financial seat of the European Union. Under

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Speaker 1: the Empire of Christendom, the market for material relics from

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Speaker 1: the Passion of the Christ was similarly global. They left

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Speaker 1: the Holy Land and ended up in various seats of

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Speaker 1: earthly power, most recently the Transatlantic Festival of George Floyd

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Speaker 1: attests to the fact that it isn't simply America that

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Speaker 1: stands accused the social order is corrupt. Then, the labor

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Speaker 1: movement once had an alternative order to offer in its stead,

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Speaker 1: drawing on the socialist tradition. It was one that included

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Speaker 1: African Americans, not as African Americans, but as workers, and

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Speaker 1: this movement was fairly successful. What happened then, The prominence

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Speaker 1: of the term repressed in the nineteen sixties is significant

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Speaker 1: and marks a shift into a new terrain of psychologized politics.

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Speaker 1: The object of attack for the new left was no

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Speaker 1: longer leis a fair capitalism, but society, the Freudian super

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Speaker 1: ego more or less, with its insistence on standards of

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Speaker 1: behavior that are binding on all society, is to be

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Speaker 1: taken as inherently oppressive and discredited in the name of liberation. Effectively,

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Speaker 1: America is so oppressive, racist, evil, gender discriminatory. It's such

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Speaker 1: a bad place that the left can completely rewrite the

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Speaker 1: rules of what we should be trying to achieve in

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Speaker 1: this country. And on a personal level, they feel no

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Speaker 1: particular allegiance to traditional America, and they feel like their

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Speaker 1: actions are always justified because they're working for this greater,

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Speaker 1: idealized future. Isn't this every lib you know? Isn't this

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Speaker 1: every smug Biden voter you've come across in the last

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Speaker 1: year or so. I'm sure there are some exceptions, but

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Speaker 1: I'm betting it's most of them. Just to finish this up, quote,

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Speaker 1: if the ideal of a demoralized public sphere was a

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Speaker 1: signature aspiration of liberal secularism. It seems we have entered

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Speaker 1: a post secular age. Populism happened because it became widely

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Speaker 1: noticed that we have transition from a liberal society to

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Speaker 1: something that more closely resembles a corrupt theocracy. End quote. Yeah,

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Speaker 1: this is the religion of the elites we are talking about.

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Speaker 1: Buck took the day off, but don't worry, We've still

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Speaker 1: got your covered. This is the best of the Buck

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Speaker 1: Sexton Show. Big story about Eric Swawell, a member of

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Speaker 1: Congress and on the Intelligence Committee no less in the House,

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Speaker 1: who was targeted by a Chinese spy. People are now

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Speaker 1: paying more attention than they have in quite some time

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Speaker 1: to Chinese espionage and influence operations in the United States.

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Speaker 1: I wanted you all to get a real sense of

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Speaker 1: how far and why those operations really are, and so

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Speaker 1: we're bringing all our friend Gordon Chang to tell you

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Speaker 1: about it right now. He's the author of a book

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Speaker 1: you can get right now, ebook The Great US China

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Speaker 1: Tech War, and you can follow him on Twitter Gordon G. Chang.

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Speaker 1: If you want to know what's going on with China,

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Speaker 1: you should Gordon. Thanks so much, Thank you, Buck. So Gordon,

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Speaker 1: take us just from the broad strokes here because I've

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Speaker 1: spent some time on the Swallowell case this week, and

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Speaker 1: we can dig into that in a moment. But what

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Speaker 1: do people need to know about Chinese Communist Party influence

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Speaker 1: and espionage operations as a as a systematic threat that's

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Speaker 1: been going on for years in the US. Yeah, Well,

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Speaker 1: China's operations against the US have been going on for

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Speaker 1: years and indeed decades, and they are at all levels

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Speaker 1: of society. We're talking not just the White House, not

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Speaker 1: just the House and Senate, but also down to municipalities.

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Speaker 1: You know, the most interesting detail about the Swalwell investigation

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Speaker 1: is that they first came into contact with him, not

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Speaker 1: when he was on the House Intel Committee, which of

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Speaker 1: course would be of value to them, but when he

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Speaker 1: was a council member in Dublin City, California. They started early,

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Speaker 1: They helped to promote his campaigns. They obviously were trying

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Speaker 1: to intrate him, to influence him, and indeed, in a

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Speaker 1: sense it may have worked because even after the FBI

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Speaker 1: warned him that there was a possible Ministry of State

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Speaker 1: Security agent in his inner circle, Swalwell didn't talk about

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Speaker 1: China's threat to the US. It was all Russia, Russia, Russia,

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Speaker 1: and I think that was certainly helping China because that's

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Speaker 1: one of their narratives that it's not them. So we've

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Speaker 1: got to be concerned. And remember Swalwell was just one individual.

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Speaker 1: They're doing this across the country. No other nation has

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Speaker 1: posed such a big intelligence threat to the United States ever. Now,

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Speaker 1: tell us about some of the ways that they influenced,

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Speaker 1: specifically on the corporate side, and just if you can

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Speaker 1: add a little context here for the ways that they

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Speaker 1: can exert influence in a fashion that moves the needle

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Speaker 1: for them, But that may not be as obvious people.

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Speaker 1: I mean, we know that they're trying to get classified information.

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Speaker 1: We know about the cyber side of things. We hear

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Speaker 1: more about that than we do this other these other aspects.

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Speaker 1: But on influence operations, how is the Chinese commists part?

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Speaker 1: I mean the NBA, for example, right, we know the

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Speaker 1: NBA doesn't want to go against the CCP. Where else

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Speaker 1: are there pressure points in what we're seeing day to day? Well,

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Speaker 1: I'll take something from the headlines, and this is the

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Speaker 1: other side of the aisle. The Republican Governor of Georgia,

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Speaker 1: Brian Kemp he always tells the investment opportunities for China

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Speaker 1: in the Peach State. He was actually proud to be

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Speaker 1: pictured next to Houston's Consul general from China before, of

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Speaker 1: course the consul before the consulate was closed by the

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Speaker 1: State Department in July. So really, what they try to

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Speaker 1: do is they go after all of the states, They

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Speaker 1: go after many of the cities, dangling out sister city projects,

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Speaker 1: also trade and investment, all the rest of it. So

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Speaker 1: this is multidimensional and it's sometimes it looks harmless, as

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Speaker 1: it does in the case of Georgia, but it's part

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Speaker 1: of one malicious campaign. Whether we're talking Brian Kim, Eric Swalwell,

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Speaker 1: or whomever, we're talking to Gordon Chang, author The Great

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Speaker 1: US China Tech War, and you can follow him on Twitter,

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Speaker 1: Gordon g as in g Chang, Gordon, tell me about

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Speaker 1: the tech aspects of this and what we should be

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Speaker 1: prepared for going forward. I know you've written a book

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Speaker 1: on this recently. Yeah. What I tried to do was

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Speaker 1: to look at China's tech challenge to the US, because

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Speaker 1: if we go back a decade ago, China was not

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Speaker 1: considered to be a competitor to the US in tech

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Speaker 1: but now in certain areas, in certain crucial areas, China

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Speaker 1: is actually ahead of the US. So, for instance, in

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Speaker 1: quantum communications, they're not far behind. In quantum computing, which

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Speaker 1: is even more important, they can even be ahead if

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Speaker 1: we take their claims at face value of their new

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Speaker 1: supercomputer all sorts of things like artificial intelligence, big data,

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Speaker 1: they are even with US, if not ahead. This is

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Speaker 1: a multidimensional challenge. China is trying to collect the DNA

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Speaker 1: of Americans, and the question is what's up with that.

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Speaker 1: They've been doing that by hacking you know Anthem, the

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Speaker 1: second largest health insurer. That hack was disclosed in early

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Speaker 1: twenty fifteen. We know that they're buying up companies with

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Speaker 1: DNA profiles of Americans. They offer subsidized DNA and analysis.

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Speaker 1: So if you go to an ancestry company, chances are

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Speaker 1: that China has gotten your DNA. So this is really

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Speaker 1: a challenge to us really across the board. What would

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Speaker 1: China want with DNA? Gordon Two things buck. First of all,

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Speaker 1: biotechnology is one of the ten areas that designated in

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Speaker 1: their Nate in China twenty twenty five plan. That's a

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Speaker 1: ten year program to dominate technology. But there's something even

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Speaker 1: sinister about this. And as China is collecting American and

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Speaker 1: the DNA of others, it is also restricting, essentially prohibiting

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Speaker 1: the transfer of Chinese DNA too foreigners. They talk about

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Speaker 1: how they want to be cooperative with the world, but

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Speaker 1: they don't want us to see genetic material of Chinese.

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Speaker 1: And many people suspect, including some in the US government,

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Speaker 1: that China is actually using DNA genetic information to design

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Speaker 1: diseases targeting certain ethnic or racial groups. Now this gets

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Speaker 1: to the point where we've got to be obviously critically

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Speaker 1: concerned because we saw what the coronavirus did, and imagine

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Speaker 1: if it were engineered. I mean some people say it

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Speaker 1: was engineered, but whether it was engineered or not, it

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Speaker 1: is criminaled American society, and it's now killed about two

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Speaker 1: hundred and ninety thousand Americans. What Gordon, what Gordon is

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Speaker 1: allowing China? Is it all just straight up lying about

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Speaker 1: the numbers in suppression Because we hear all the COVID

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Speaker 1: numbers coming out of Europe, we hear about them in

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Speaker 1: South America, and obviously we're in a very bad spot

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Speaker 1: right now with COVID in the US. We don't hear

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Speaker 1: about huge outbreaks in China right now, or at least

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Speaker 1: it's certainly not making the news cycle. What's going on

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Speaker 1: a great question because the answer is we don't know.

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Speaker 1: We do know that on January twenty six, the Communist

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Speaker 1: Party formed its leading Group on the coronavirus, which is

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Speaker 1: essentially China's task force, and other than nine person roster,

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Speaker 1: there was only one health official. The rest of them

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Speaker 1: were propaganda workers as they're called in China and Communist

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Speaker 1: Party hacks, so you can see that really their emphasis

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Speaker 1: was controlling the narrative. And since that time end of January,

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Speaker 1: we haven't heard very much about what's going on in

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Speaker 1: China because they are suppressing information. You know. My sense

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Speaker 1: is that they have fewer cases than we do, far fewer,

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Speaker 1: because they use draconian methods. But we really don't know.

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Speaker 1: We hear about outbreaks across the country periodically, including big

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Speaker 1: cities like Shanghai, and then the news is just disappeared.

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Speaker 1: So I think that essentially they do have a problem,

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Speaker 1: they haven't mastered it, but nonetheless it's not as serious

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Speaker 1: as ours. Gordon. What is it that the Chinese Communist

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Speaker 1: Party wants to be the foreign policy going forward. I

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Speaker 1: mean Trump clearly confronted them in a way that they

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Speaker 1: were not used to. If we do go into a

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Speaker 1: Biden administration here, what is it that the Chinese Communist

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Speaker 1: Party wants to be our viewpoint? You know, it's essentially

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Speaker 1: what are they trying to achieve with the influence operations?

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Speaker 1: Put aside, the espionage is clear, right, they want to

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Speaker 1: steal our most valuable intellectual property and technology and they've

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Speaker 1: been doing this for many, many years and gotten away

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Speaker 1: with Well, we can't really it's incalculable, right, we can't

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Speaker 1: actually even know the full scope and damage. But in

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Speaker 1: terms of what they want our perception to be and

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Speaker 1: what they'd want a Biden administration foreign policy to look like,

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Speaker 1: what does that look like? Well, they want whoever is

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Speaker 1: inaugurated on January twenty to express subservience to China, because

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Speaker 1: we have seen this year but China try to overthrow

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Speaker 1: the government of the United States. And we know that

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Speaker 1: Cijun Ping, the Chinese ruler, has the view that there

430
00:27:45,320 --> 00:27:47,720
Speaker 1: is only one sovereign state in the world and only

431
00:27:47,720 --> 00:27:51,639
Speaker 1: one sovereign ruler, and that of course is China and

432
00:27:51,760 --> 00:27:55,560
Speaker 1: Ciji and Ping himself, so these are designs, you know.

433
00:27:55,600 --> 00:27:57,080
Speaker 1: You know a lot of people say un China just

434
00:27:57,119 --> 00:27:59,160
Speaker 1: wants to replace the US at the top of the

435
00:27:59,200 --> 00:28:04,360
Speaker 1: international system. That's wrong. China wants to overthrow that international

436
00:28:04,400 --> 00:28:07,440
Speaker 1: system and replace it with this notion of worldwide Chinese rule.

437
00:28:08,280 --> 00:28:10,199
Speaker 1: And we have seen that they're willing to go to

438
00:28:10,280 --> 00:28:14,240
Speaker 1: any lengths in order to accomplish that, including inciting violence

439
00:28:14,240 --> 00:28:16,440
Speaker 1: on American streets, which is what they did this year,

440
00:28:16,760 --> 00:28:19,399
Speaker 1: which is more than just subversion, that's an act of

441
00:28:19,440 --> 00:28:22,560
Speaker 1: war against the United States. So what we can see

442
00:28:22,840 --> 00:28:25,639
Speaker 1: is that China is trying to change our form of

443
00:28:25,680 --> 00:28:28,280
Speaker 1: government so that we are subservient to China and that

444
00:28:28,320 --> 00:28:31,720
Speaker 1: we're no longer a sovereign republic. I know many people

445
00:28:31,840 --> 00:28:35,280
Speaker 1: think that that is an extreme statement, but nonetheless that

446
00:28:35,400 --> 00:28:38,600
Speaker 1: is consistent with what we have seen China do, and

447
00:28:38,680 --> 00:28:42,200
Speaker 1: the more benign interpretations of their goals are not consistent

448
00:28:42,240 --> 00:28:45,240
Speaker 1: with the facts. Gordon, I'm sure that that it got

449
00:28:45,800 --> 00:28:50,960
Speaker 1: people's attention when you mentioned violence on US streets and

450
00:28:51,080 --> 00:28:54,640
Speaker 1: instigated by China. Tell us about that, Yes, Radio Free

451
00:28:54,680 --> 00:28:57,200
Speaker 1: Asia as a report, you know we've heard, of course,

452
00:28:57,520 --> 00:29:01,320
Speaker 1: the State Department closed the Houston Console in July China's

453
00:29:01,320 --> 00:29:04,280
Speaker 1: consulate and the Saint Department said it was a hub

454
00:29:04,320 --> 00:29:09,200
Speaker 1: of espionage. Well, that is fits all five of the

455
00:29:09,200 --> 00:29:13,560
Speaker 1: then Chinese consulates and indeed the embassy itself. Radio Free

456
00:29:13,560 --> 00:29:17,520
Speaker 1: Asia reports that an intelligence unit of the People's Liberation

457
00:29:17,680 --> 00:29:22,000
Speaker 1: Army based themselves in the Houston Consulate and there they

458
00:29:22,000 --> 00:29:26,360
Speaker 1: were using big data and artificial intelligence to identify Americans

459
00:29:26,480 --> 00:29:31,400
Speaker 1: likely to participate in ANTIFA and Black Lives Matter of protests.

460
00:29:31,800 --> 00:29:35,680
Speaker 1: And then the Chinese military sent those Americans videos via

461
00:29:35,760 --> 00:29:40,360
Speaker 1: TikTok on how to riot, So that is an act

462
00:29:40,400 --> 00:29:44,680
Speaker 1: of war. Also, you know, we have seen the Bureau

463
00:29:44,760 --> 00:29:47,479
Speaker 1: Chief for Europe of China Daily, which is an official

464
00:29:47,520 --> 00:29:52,880
Speaker 1: Communist Party publication, actually on Twitter encourage Americans to incited

465
00:29:52,960 --> 00:29:58,200
Speaker 1: Americans to commit violence. So this is this is across

466
00:29:58,240 --> 00:30:02,479
Speaker 1: the board China policy right now, and that is the

467
00:30:02,520 --> 00:30:06,640
Speaker 1: most malaia that we can think of. Gordon Chang, everybody

468
00:30:06,720 --> 00:30:09,440
Speaker 1: check out the Great US China Tech War and follow

469
00:30:09,520 --> 00:30:13,760
Speaker 1: him on Twitter. Gordon g Chang, Gordon, I always appreciate it.

470
00:30:13,760 --> 00:30:20,920
Speaker 1: Thanks for your expertise. Thank you. Buck Bucks off spreading

471
00:30:20,960 --> 00:30:24,560
Speaker 1: freedom coast to coast. This is the best of the

472
00:30:24,640 --> 00:30:31,360
Speaker 1: Buck Sexton Show. I also don't think we should get

473
00:30:31,360 --> 00:30:36,640
Speaker 1: too far ahead of ourselves on dealing with police reform

474
00:30:36,680 --> 00:30:40,760
Speaker 1: in that because they've already labeled us as being defund

475
00:30:40,800 --> 00:30:43,800
Speaker 1: the police. Anything we put forward in terms of the

476
00:30:43,880 --> 00:30:47,520
Speaker 1: organizational structure to change police in which I promise you

477
00:30:47,760 --> 00:30:51,480
Speaker 1: will occur. Promise you just think to yourself and give

478
00:30:51,520 --> 00:30:54,800
Speaker 1: me advice whether we should do that before January fifth,

479
00:30:55,120 --> 00:30:57,360
Speaker 1: because that's how they beat the living hell out of

480
00:30:57,400 --> 00:31:01,080
Speaker 1: us across the country. The same that we're talking about

481
00:31:01,080 --> 00:31:05,400
Speaker 1: defunding the police, we're not. We're talking about holding them accountable.

482
00:31:05,880 --> 00:31:08,720
Speaker 1: Biden didn't get the memo from the left. And I

483
00:31:08,800 --> 00:31:11,520
Speaker 1: know left wing activists and there are Bernie supporting folks

484
00:31:11,520 --> 00:31:13,640
Speaker 1: out there that people tell you know, when they say

485
00:31:13,680 --> 00:31:17,120
Speaker 1: defund the police, you know what they mean, defund the police. No,

486
00:31:17,200 --> 00:31:20,520
Speaker 1: they're serious about it. See see the Democrats keep keep

487
00:31:20,520 --> 00:31:23,000
Speaker 1: hoping they can convince every Oh no, no, no, that's

488
00:31:23,040 --> 00:31:25,440
Speaker 1: not when we when we say that thing, it's not

489
00:31:25,560 --> 00:31:28,440
Speaker 1: what we mean. We say defund the police. We mean

490
00:31:28,520 --> 00:31:33,600
Speaker 1: is you know, accountability. No, no, that is not that

491
00:31:33,760 --> 00:31:37,719
Speaker 1: is not, in fact, what the Democrat activist base wants.

492
00:31:37,760 --> 00:31:40,960
Speaker 1: They they they want no more of this. They want

493
00:31:41,040 --> 00:31:46,320
Speaker 1: defunding of police. There you go. Biden, though, is telling

494
00:31:46,360 --> 00:31:48,320
Speaker 1: you what's obvious. And of course our media won't ever

495
00:31:48,320 --> 00:31:52,160
Speaker 1: pick up on this because they don't want to upset

496
00:31:52,200 --> 00:31:55,400
Speaker 1: their a portion of their viewers who are left wing lunatics.

497
00:31:56,320 --> 00:31:58,720
Speaker 1: This was bad for Democrats in these house races. This

498
00:31:58,840 --> 00:32:02,080
Speaker 1: really hurt. It's a good thing that Joe Biden had

499
00:32:02,200 --> 00:32:05,680
Speaker 1: enough political consultants around him to tell him, Hey, the

500
00:32:05,800 --> 00:32:07,920
Speaker 1: numbers on this are not good. Don't don't go down

501
00:32:07,920 --> 00:32:14,520
Speaker 1: this aoc ilhan omar defund the police, crazy path. Don't

502
00:32:14,560 --> 00:32:16,280
Speaker 1: do that, because then you won't be able to fool

503
00:32:16,880 --> 00:32:20,360
Speaker 1: enough Americans into thinking that you're like moderate, good old

504
00:32:20,440 --> 00:32:22,720
Speaker 1: uncle Joe. You know, that was the big That was

505
00:32:22,760 --> 00:32:24,600
Speaker 1: the big problem. But there are going to be a

506
00:32:24,640 --> 00:32:27,480
Speaker 1: lot of fights about policing in the next four years,

507
00:32:27,520 --> 00:32:30,800
Speaker 1: that's for sure. The Democrats are convinced that they've gotten

508
00:32:31,040 --> 00:32:35,600
Speaker 1: They've created these these beachheads, they have these footholds, and

509
00:32:36,120 --> 00:32:39,480
Speaker 1: they change the language around all this. They talk about, how,

510
00:32:39,880 --> 00:32:43,720
Speaker 1: you know, police violence is this great threat to to

511
00:32:44,840 --> 00:32:47,200
Speaker 1: black and brown communities, and this is what they'll aways

512
00:32:47,240 --> 00:32:49,880
Speaker 1: say all the time. I mean, here, here's Karen Bass,

513
00:32:49,880 --> 00:32:52,640
Speaker 1: who was at one point being talked about as a

514
00:32:52,720 --> 00:32:55,320
Speaker 1: possible VP for Biden. Here she is telling everybody what

515
00:32:55,400 --> 00:32:58,360
Speaker 1: her view of policing is played nineteen. My understanding from

516
00:32:58,360 --> 00:33:00,800
Speaker 1: the proposal it is that it's a propos all about

517
00:33:00,880 --> 00:33:04,959
Speaker 1: racial equity. And I think considering the historical moment that

518
00:33:05,000 --> 00:33:08,680
Speaker 1: we're in post George Floyd, where people finally in the

519
00:33:08,720 --> 00:33:11,720
Speaker 1: United States understand that the issue of policing is a

520
00:33:11,800 --> 00:33:15,280
Speaker 1: question of systemic racism. We understand because of COVID, the

521
00:33:15,440 --> 00:33:19,240
Speaker 1: underlying health conditions, and so we have real issues in

522
00:33:19,320 --> 00:33:21,960
Speaker 1: this country. And what we saw over the last few

523
00:33:21,960 --> 00:33:25,080
Speaker 1: months is that maybe we can address some of these issues.

524
00:33:25,320 --> 00:33:28,520
Speaker 1: I think it makes absolute sense to do that at

525
00:33:28,520 --> 00:33:33,200
Speaker 1: the highest level. Why is there an issue of systemic

526
00:33:33,320 --> 00:33:37,080
Speaker 1: racism exactly? I really would like to have more of

527
00:33:37,120 --> 00:33:39,560
Speaker 1: this kind. I'd like to know what is the systemic

528
00:33:39,640 --> 00:33:43,040
Speaker 1: racism in law enforcement? I'm not eving getting it doesn't

529
00:33:43,040 --> 00:33:45,440
Speaker 1: exist or not. I don't. I think the answer is no.

530
00:33:45,560 --> 00:33:47,800
Speaker 1: But nonetheless, let's just get past that for right now.

531
00:33:48,840 --> 00:33:52,400
Speaker 1: What is it? What does it mean if we're going

532
00:33:52,480 --> 00:33:56,320
Speaker 1: to talk about disparate impact, which is this doctrine of

533
00:33:56,400 --> 00:33:59,120
Speaker 1: when some groups are affected by things more than others.

534
00:33:59,440 --> 00:34:04,680
Speaker 1: Inherently there must be a racial animus or racial inequality

535
00:34:04,720 --> 00:34:07,800
Speaker 1: involved in that. Well, I mean, as I've said to you,

536
00:34:08,000 --> 00:34:11,880
Speaker 1: that's not necessarily true, because then you'd have to address

537
00:34:11,960 --> 00:34:18,280
Speaker 1: the Asian supremacist US system, where we have Asian Americans

538
00:34:18,960 --> 00:34:23,080
Speaker 1: out earning white households in this country, and they have

539
00:34:23,120 --> 00:34:25,240
Speaker 1: been I think for about the last fifteen or twenty years,

540
00:34:26,160 --> 00:34:29,560
Speaker 1: and they've also had more economic gains under the Trump

541
00:34:29,560 --> 00:34:31,960
Speaker 1: administration than any other group. So it's kind of a

542
00:34:32,000 --> 00:34:35,960
Speaker 1: strange system of white supremacy when it doesn't actually make

543
00:34:36,000 --> 00:34:38,719
Speaker 1: sure that white people are advanced at the expense of

544
00:34:38,960 --> 00:34:41,640
Speaker 1: other people in this country. Right, So you have to

545
00:34:41,640 --> 00:34:43,759
Speaker 1: start with the facts what we know, and you can

546
00:34:43,840 --> 00:34:48,000
Speaker 1: also look at as I point out, gender inequality, sorry

547
00:34:48,000 --> 00:34:53,120
Speaker 1: I should say gender disparate impact. Violent crimes are ninety

548
00:34:53,160 --> 00:34:58,800
Speaker 1: percent plus committed by men. It is not anti mail

549
00:34:59,160 --> 00:35:03,160
Speaker 1: that there are more violent criminals who are prosecutor who

550
00:35:03,200 --> 00:35:05,720
Speaker 1: are met. That's just that's just that we have laws,

551
00:35:05,719 --> 00:35:08,480
Speaker 1: they're applicable, and that's how it shakes out. So I

552
00:35:08,560 --> 00:35:12,200
Speaker 1: just need I need to know where is this systemic

553
00:35:12,560 --> 00:35:16,960
Speaker 1: racism in law enforcement? Explain they say this and we're

554
00:35:16,960 --> 00:35:20,040
Speaker 1: all supposed to know. But what is systemically racist in

555
00:35:20,040 --> 00:35:23,800
Speaker 1: our cops are are mostly racist? Is that what it means?

556
00:35:23,920 --> 00:35:26,480
Speaker 1: I just want answers, but they're not going to give

557
00:35:26,560 --> 00:35:28,560
Speaker 1: us answers, are they. They're going to give us lecture.

558
00:35:31,840 --> 00:35:35,920
Speaker 1: You're in the Freedom Hut. This is the Buck Sexton Show.

559
00:35:36,520 --> 00:35:39,200
Speaker 1: Buck took the day off, but don't worry, We've still

560
00:35:39,239 --> 00:35:42,359
Speaker 1: got your covered. This is the best of the Buck

561
00:35:42,400 --> 00:35:48,920
Speaker 1: Sexton Show. Is there a doctor in the White House?

562
00:35:50,160 --> 00:35:54,840
Speaker 1: Not if you need an m d. This was written

563
00:35:54,840 --> 00:35:58,680
Speaker 1: by this guy, Joseph Epstein, And the subheading if this

564
00:35:58,719 --> 00:36:00,880
Speaker 1: is an editorial in the Wall Street Old Jill Biden

565
00:36:00,880 --> 00:36:06,720
Speaker 1: should think about dropping the honorific, which feels fraudulent even comic.

566
00:36:07,880 --> 00:36:11,640
Speaker 1: Let me just be very clear. It is fraudulent and comic.

567
00:36:11,680 --> 00:36:14,640
Speaker 1: It's absurd. Now, when is a fraudulent I mean the

568
00:36:14,680 --> 00:36:17,440
Speaker 1: notion that we should have to call this person who

569
00:36:17,520 --> 00:36:20,320
Speaker 1: got a PhD at fifty five because she was apparently

570
00:36:20,360 --> 00:36:22,879
Speaker 1: bored and you know, wanted to get more street cred

571
00:36:23,000 --> 00:36:27,439
Speaker 1: or something. Got a PhD at fifty five in some

572
00:36:27,520 --> 00:36:35,160
Speaker 1: kind of you know, educational field, and we're all supposed

573
00:36:35,160 --> 00:36:36,359
Speaker 1: to refer to as doctor. Now, well, let me be

574
00:36:36,440 --> 00:36:38,400
Speaker 1: very clear. This is a custom thing, this is a

575
00:36:38,440 --> 00:36:41,720
Speaker 1: cultural thing. There's no legal issue here, right, Call whatever

576
00:36:41,760 --> 00:36:45,520
Speaker 1: you want. So I don't really understand what they think

577
00:36:45,560 --> 00:36:47,400
Speaker 1: the big deal is here. And I want to be

578
00:36:47,520 --> 00:36:52,320
Speaker 1: very clear that when I look at this, I see

579
00:36:53,840 --> 00:36:55,680
Speaker 1: that there are people making a big deal is now.

580
00:36:55,760 --> 00:37:01,320
Speaker 1: I said back in August, doctor or Jill Biden shouldn't

581
00:37:01,360 --> 00:37:05,359
Speaker 1: be called doctor. This isn't a partisan statement. It's about reality.

582
00:37:05,440 --> 00:37:09,439
Speaker 1: That was back in August. So they wrote this piece

583
00:37:09,520 --> 00:37:12,560
Speaker 1: the Walls Through Journal a few months after. I was

584
00:37:12,840 --> 00:37:14,839
Speaker 1: already coming out there saying this because I think it's

585
00:37:14,920 --> 00:37:18,080
Speaker 1: very obvious. The whole thing is absurd. But you see,

586
00:37:18,280 --> 00:37:25,000
Speaker 1: they hate You're not allowed to mock. You are not

587
00:37:25,040 --> 00:37:29,319
Speaker 1: allowed to mock people in power when they're Democrats. You

588
00:37:29,360 --> 00:37:31,800
Speaker 1: can't do that. You're not allowed to poke fun at them.

589
00:37:32,440 --> 00:37:36,880
Speaker 1: They shut that down because it takes away from the

590
00:37:37,120 --> 00:37:40,000
Speaker 1: power and the perception of power that they're trying to

591
00:37:40,040 --> 00:37:43,200
Speaker 1: build for them. So, you know, I mean, Jill Biden

592
00:37:44,000 --> 00:37:47,200
Speaker 1: is not a doctor. And here's what this guy, this

593
00:37:47,239 --> 00:37:53,680
Speaker 1: guy writes, Madam first Lady missus Biden, Jill kiddo. Now

594
00:37:53,719 --> 00:37:55,719
Speaker 1: that people got mad about the kiddo thing, a bit

595
00:37:55,719 --> 00:37:59,200
Speaker 1: of advice on what may seem like a small but

596
00:37:59,280 --> 00:38:03,080
Speaker 1: I think is not on important matter. Any chance you

597
00:38:03,160 --> 00:38:07,560
Speaker 1: might drop the doctor before your name, Doctor Jill Biden

598
00:38:07,640 --> 00:38:10,480
Speaker 1: sounds and feels fraudulent, not to say a touch comic.

599
00:38:11,120 --> 00:38:15,279
Speaker 1: Your degree is, I believe an e an ed d.

600
00:38:15,760 --> 00:38:19,839
Speaker 1: Or a Doctor of Education earned at the University of

601
00:38:19,920 --> 00:38:25,160
Speaker 1: Delaware through a dissertation with the unpromising title student retention

602
00:38:25,280 --> 00:38:30,480
Speaker 1: at the community college level, meeting students' needs. A wise

603
00:38:30,520 --> 00:38:32,800
Speaker 1: man once said that no one should call himself doctor

604
00:38:32,880 --> 00:38:36,520
Speaker 1: unless he has delivered a child. Think about a doctor, Jill,

605
00:38:36,640 --> 00:38:42,799
Speaker 1: and forthwith drop the doc. I taught at Northwestern University

606
00:38:42,800 --> 00:38:45,520
Speaker 1: for thirty years without a doctorate or any advanced degree.

607
00:38:46,400 --> 00:38:49,920
Speaker 1: I have only a BA in absentia from the University

608
00:38:49,960 --> 00:38:53,719
Speaker 1: of Chicago in absentia because I took my final examination

609
00:38:53,800 --> 00:38:57,440
Speaker 1: on a pool table at headquarters Company ford Hood, Texas,

610
00:38:57,880 --> 00:39:00,680
Speaker 1: while serving in the Peacetime Army in the late nine fifties.

611
00:39:01,200 --> 00:39:03,719
Speaker 1: I do have an honorary doctorate, though I have yet

612
00:39:03,760 --> 00:39:06,560
Speaker 1: to report to the president of the school that awarded it.

613
00:39:06,719 --> 00:39:08,799
Speaker 1: I was fired the year after I received it. Not

614
00:39:08,920 --> 00:39:16,080
Speaker 1: I hope for allowing my honorary doctorate. That's right. So friends,

615
00:39:16,560 --> 00:39:19,239
Speaker 1: this is this is pretty straightforward. And I remember some

616
00:39:19,280 --> 00:39:21,200
Speaker 1: of you wrote any disagree with me on this, that's fine.

617
00:39:22,160 --> 00:39:24,120
Speaker 1: I think it's weird and if you if we can

618
00:39:24,200 --> 00:39:26,120
Speaker 1: argue about this, there's certainly arguing to be had on

619
00:39:26,160 --> 00:39:28,440
Speaker 1: both sides. I think it's weird to insist, because she

620
00:39:28,480 --> 00:39:31,080
Speaker 1: clearly does. Because there are tons of people out there

621
00:39:31,160 --> 00:39:34,520
Speaker 1: without doctorates. I'm sorry, with doctorates who don't want to

622
00:39:34,520 --> 00:39:37,359
Speaker 1: be called a doctor. There lots and lots and lots

623
00:39:37,360 --> 00:39:40,720
Speaker 1: of them. Um. I've always thought this was a little strange.

624
00:39:40,760 --> 00:39:42,719
Speaker 1: I never liked it. I had a we call them

625
00:39:42,760 --> 00:39:47,000
Speaker 1: headmasters at my grammar school, my primary school, so that's

626
00:39:47,040 --> 00:39:48,920
Speaker 1: that's what we had to call our principal, a headmaster,

627
00:39:49,760 --> 00:39:53,080
Speaker 1: and we had to call him doctor and he was

628
00:39:52,960 --> 00:39:55,719
Speaker 1: he wasn't a doctor. You know, we had some kind

629
00:39:55,760 --> 00:39:58,719
Speaker 1: of a doctorate in the humanities or whatever. And I

630
00:39:58,800 --> 00:40:03,000
Speaker 1: know that there's some there's some long standing tradition here

631
00:40:03,239 --> 00:40:06,160
Speaker 1: of people that are getting a you know, the PhD

632
00:40:06,320 --> 00:40:09,840
Speaker 1: came before the MD or whatever. I don't care. We've

633
00:40:09,920 --> 00:40:13,279
Speaker 1: we've evolved in our conversation about this. A doctor is

634
00:40:13,320 --> 00:40:16,719
Speaker 1: a person who is a doctor, right, and I think

635
00:40:16,719 --> 00:40:19,879
Speaker 1: that that's in it's it's delivered as an honorific, it's

636
00:40:19,880 --> 00:40:22,480
Speaker 1: delivered as a term of respect. I do not have

637
00:40:22,560 --> 00:40:27,480
Speaker 1: any respect for Jill Biden's PhD in community college retention.

638
00:40:28,239 --> 00:40:33,799
Speaker 1: I give zero, you know what's about that? And so

639
00:40:33,920 --> 00:40:36,759
Speaker 1: I'm not going to walk around and be told that

640
00:40:36,800 --> 00:40:38,200
Speaker 1: I have to I have to say this better. You

641
00:40:38,239 --> 00:40:42,200
Speaker 1: know this. If I insisted that Democrats call me Buck

642
00:40:42,320 --> 00:40:46,200
Speaker 1: the radio genius Sexton, they would have a right to say, now,

643
00:40:46,320 --> 00:40:49,200
Speaker 1: we're not actually going to do that. We're not actually

644
00:40:49,200 --> 00:40:51,479
Speaker 1: going to refer to him as the radio genius and say, well,

645
00:40:51,560 --> 00:40:54,080
Speaker 1: but why not, you know it, why not just be

646
00:40:54,120 --> 00:40:56,040
Speaker 1: polite and call him what he likes to be called.

647
00:40:56,760 --> 00:41:00,960
Speaker 1: They won't do that. So I I I had a

648
00:41:01,000 --> 00:41:04,239
Speaker 1: grandfather who had an honorary doctorate from Notre Dame No. One.

649
00:41:04,320 --> 00:41:08,520
Speaker 1: We never called him doctor. He wasn't a doctor. So

650
00:41:08,760 --> 00:41:12,719
Speaker 1: I think that this is this is just one of

651
00:41:12,760 --> 00:41:14,319
Speaker 1: these things that shouldn't have been such a big deal.

652
00:41:14,719 --> 00:41:20,120
Speaker 1: But the Libs and the machinery of Biden worship, that's

653
00:41:20,120 --> 00:41:23,200
Speaker 1: all kicking into gear. It's amazing. Oh this is sexist.

654
00:41:23,320 --> 00:41:27,200
Speaker 1: They say it's not sexist. Oh what they think that

655
00:41:27,200 --> 00:41:29,520
Speaker 1: if we were supposed to call him doctor Joe Biden

656
00:41:29,600 --> 00:41:33,840
Speaker 1: because of his PhD in education and in community college

657
00:41:33,840 --> 00:41:37,520
Speaker 1: retention or whatever, that we wouldn't make fun of him

658
00:41:37,520 --> 00:41:39,880
Speaker 1: for that. That's absurd. I mean, their point is absurd.

659
00:41:39,920 --> 00:41:42,759
Speaker 1: It's not it's not real. I would, of course make

660
00:41:42,840 --> 00:41:44,560
Speaker 1: fun of Joe Biden for that. I'd make fun of

661
00:41:44,600 --> 00:41:46,400
Speaker 1: anyone for that, and I think we have a right

662
00:41:46,440 --> 00:41:51,080
Speaker 1: to do that. But you'll you'll notice there's a particular

663
00:41:51,120 --> 00:41:57,360
Speaker 1: sensitivity around Biden and his wife and the First family

664
00:41:57,520 --> 00:42:00,880
Speaker 1: and all this stuff, because they'd don't want people to

665
00:42:00,920 --> 00:42:03,880
Speaker 1: start to realize how how silly this whole thing is.

666
00:42:04,360 --> 00:42:08,640
Speaker 1: That Joe Biden is a third tier mediocrity in every sense.

667
00:42:09,360 --> 00:42:11,640
Speaker 1: And they just figured that this is a guy we

668
00:42:11,719 --> 00:42:14,439
Speaker 1: could make president. They didn't spend enough time thinking about

669
00:42:14,440 --> 00:42:16,719
Speaker 1: should we make him president. They just figured out we can.

670
00:42:17,080 --> 00:42:20,080
Speaker 1: We can fool enough people with the media and with

671
00:42:20,120 --> 00:42:23,680
Speaker 1: social media allied together in a pandemic year, we could

672
00:42:23,719 --> 00:42:26,080
Speaker 1: we could get this guy to be president. And they're

673
00:42:26,120 --> 00:42:27,879
Speaker 1: all going to try to pretend like this is really

674
00:42:27,920 --> 00:42:30,240
Speaker 1: impressive and he's some great guy. Joe Biden's a clown,

675
00:42:31,360 --> 00:42:34,680
Speaker 1: and it's a little it is it's pretentious that her

676
00:42:34,680 --> 00:42:37,120
Speaker 1: wife that his wife rather goes around demanding to be

677
00:42:37,160 --> 00:42:40,839
Speaker 1: called doctor doctor Joe Biden. I'm sorry it is pretentious

678
00:42:41,440 --> 00:42:45,279
Speaker 1: because clearly she demands it. Because we know about it, right,

679
00:42:45,320 --> 00:42:47,520
Speaker 1: This isn't like it just is. It's not It's one

680
00:42:47,560 --> 00:42:52,040
Speaker 1: thing in the classroom on campus. I'm talking about it

681
00:42:52,040 --> 00:42:56,200
Speaker 1: in like general, in life, in general. You know, I

682
00:42:56,239 --> 00:42:59,320
Speaker 1: think Dick Cheney's wife has a has a doctor, and

683
00:42:59,400 --> 00:43:01,600
Speaker 1: no one calls her doctor Chenney like our missus Cheney.

684
00:43:01,640 --> 00:43:04,239
Speaker 1: There's tons of examples. The Wall Street Journal do its

685
00:43:04,239 --> 00:43:07,120
Speaker 1: credit fired back on this one because social media over

686
00:43:07,160 --> 00:43:10,759
Speaker 1: the weekend. Oh my gosh, how how dare you not

687
00:43:10,960 --> 00:43:15,239
Speaker 1: referred to as doctor Jill Biden. I just want to

688
00:43:15,239 --> 00:43:17,960
Speaker 1: know it. Has anyone who ever wrote a dissertation for

689
00:43:18,000 --> 00:43:20,840
Speaker 1: a PhD program at the University of Delaware. I'm just

690
00:43:20,840 --> 00:43:22,879
Speaker 1: gonna ask this question. Do you think I've ever not

691
00:43:22,960 --> 00:43:25,640
Speaker 1: gotten it? Do you think a University of Delaware has

692
00:43:25,640 --> 00:43:28,160
Speaker 1: ever been like, yeah, you're you're in their PhD program

693
00:43:28,640 --> 00:43:30,880
Speaker 1: and you finished a doctorate, but you know it just

694
00:43:31,040 --> 00:43:33,920
Speaker 1: wasn't really good, so we're not going to give you

695
00:43:33,920 --> 00:43:37,200
Speaker 1: your PhD. I'm just guessing I don't know. I have to.

696
00:43:37,239 --> 00:43:39,160
Speaker 1: I wonder if the state is even available. I'm guessing

697
00:43:39,160 --> 00:43:41,480
Speaker 1: the answer, though, is that you know, you show up,

698
00:43:41,520 --> 00:43:44,520
Speaker 1: you write the thing, you get the doctorate. So what

699
00:43:44,640 --> 00:43:48,279
Speaker 1: exactly is impressive about this? In what way am I

700
00:43:48,360 --> 00:43:52,319
Speaker 1: supposed to care about? No, of course not. Do you

701
00:43:52,360 --> 00:43:55,400
Speaker 1: think that? Do you think that if the roles were reversed,

702
00:43:55,400 --> 00:43:58,320
Speaker 1: if this was a Republican's wife, the Democrats would be

703
00:43:58,400 --> 00:44:01,000
Speaker 1: leaping to our defense. No? In fact, there was no

704
00:44:01,040 --> 00:44:04,799
Speaker 1: talk about the sexism of attacking Milani all the time.

705
00:44:04,840 --> 00:44:07,320
Speaker 1: There was no talking about the xenophobia of attacking her accent,

706
00:44:07,440 --> 00:44:09,760
Speaker 1: making fun of her a woman who speaks five She's

707
00:44:10,200 --> 00:44:13,920
Speaker 1: a highly successful international model who speaks five languages. But

708
00:44:14,000 --> 00:44:17,239
Speaker 1: they would they love making jokes about her, mocking her.

709
00:44:18,239 --> 00:44:21,719
Speaker 1: You think they made? You think they made jokes about this?

710
00:44:22,920 --> 00:44:25,080
Speaker 1: Would they make jokes about this if it was a Republican? Now,

711
00:44:25,800 --> 00:44:27,319
Speaker 1: they would if it was a Republican, Not if it's

712
00:44:27,320 --> 00:44:30,319
Speaker 1: a Democrat. So, oh, there's a little bit more here.

713
00:44:31,440 --> 00:44:34,319
Speaker 1: I want to read more from this guy's piece. The

714
00:44:34,480 --> 00:44:38,920
Speaker 1: PhD may have once held prestige, but that has been

715
00:44:38,920 --> 00:44:41,960
Speaker 1: diminished by the erosion of seriousness and the relaxation of

716
00:44:42,000 --> 00:44:46,640
Speaker 1: standards in university education generally at any rate outside the sciences,

717
00:44:47,239 --> 00:44:50,200
Speaker 1: getting a doctorate was then an arduous proceeding. One had

718
00:44:50,239 --> 00:44:53,680
Speaker 1: to pass examinations in two foreign languages, one of them

719
00:44:53,719 --> 00:44:57,000
Speaker 1: Greek or Latin, defend one's thesis, and take an oral

720
00:44:57,000 --> 00:45:01,320
Speaker 1: examination on general knowledge in one's field. At Columbia University

721
00:45:01,360 --> 00:45:03,920
Speaker 1: of an earlier day, a secretary sat outside the room

722
00:45:03,960 --> 00:45:07,080
Speaker 1: where these examinations were administered, a pitcher of water and

723
00:45:07,120 --> 00:45:10,560
Speaker 1: a glass on her desk. The water and glass were

724
00:45:10,560 --> 00:45:14,000
Speaker 1: there for the candidates who fainted a far cry. This

725
00:45:14,200 --> 00:45:16,799
Speaker 1: is from the few doctoral examinations I sat in on

726
00:45:16,880 --> 00:45:20,480
Speaker 1: during my teaching days, where candidates and teachers addressed one

727
00:45:20,520 --> 00:45:24,040
Speaker 1: another by first name, and the general atmosphere you're more

728
00:45:24,080 --> 00:45:29,640
Speaker 1: resembled a coffee clatch, doctor Jill. I note you acquired

729
00:45:29,640 --> 00:45:33,040
Speaker 1: your ed as recently as fifteen years ago or at

730
00:45:33,080 --> 00:45:37,560
Speaker 1: age fifty five, long after the terror had departed. The

731
00:45:37,680 --> 00:45:42,080
Speaker 1: prestige of honorary doctorates has declined even further. Such degrees

732
00:45:42,120 --> 00:45:47,200
Speaker 1: were once given exclusively to scholars, statements, statesmen, artists, and scientists.

733
00:45:47,719 --> 00:45:50,000
Speaker 1: Then rich men entered the list, usually in the hope

734
00:45:50,040 --> 00:45:52,000
Speaker 1: they would donate money to the schools that had granted

735
00:45:52,000 --> 00:45:56,840
Speaker 1: them their honorary degrees. My friends, my late friends. Saw Linowitz,

736
00:45:56,920 --> 00:46:00,439
Speaker 1: then chairman of Xerox, told me he had six three

737
00:46:00,560 --> 00:46:05,960
Speaker 1: honorary doctorates. Famoush television journalists who passed themselves off as intelligent,

738
00:46:06,120 --> 00:46:12,440
Speaker 1: followed entertainers who didn't bother feigning intelligence were next. At Northwestern,

739
00:46:12,600 --> 00:46:16,760
Speaker 1: recent honorary degree recipients and commencement speakers have included Stephen

740
00:46:16,800 --> 00:46:20,600
Speaker 1: Colbert and Seth Myers. I sent a complaining email to

741
00:46:20,640 --> 00:46:23,160
Speaker 1: the school's president about the low quality of such men,

742
00:46:23,480 --> 00:46:26,920
Speaker 1: of men, such sorry of such men as academic honor Rand's,

743
00:46:27,520 --> 00:46:30,880
Speaker 1: with the result that the following year, the commencement speaker

744
00:46:31,000 --> 00:46:34,279
Speaker 1: and honor rand was Billy Gene King, who, with the

745
00:46:34,320 --> 00:46:37,760
Speaker 1: graduating members of the schools women's tennis team, hit tennis

746
00:46:37,760 --> 00:46:40,640
Speaker 1: balls out to the audience of graduating students and parents

747
00:46:41,000 --> 00:46:43,399
Speaker 1: who had paid seventy thousand dollars a year for their

748
00:46:43,440 --> 00:46:47,560
Speaker 1: university education, or perhaps I should say, for their credential.

749
00:46:48,840 --> 00:46:54,120
Speaker 1: Political correctness has put paid to has put paid to

750
00:46:54,200 --> 00:46:58,000
Speaker 1: any true honor and honorary doctorate may once have possessed.

751
00:46:58,520 --> 00:47:01,880
Speaker 1: If you're ever looking for a similar similar to denote rarity,

752
00:47:02,400 --> 00:47:07,000
Speaker 1: try rarer than a contemporary university honorary degree list not

753
00:47:07,080 --> 00:47:10,399
Speaker 1: containing an African American woman. Then there are all those

754
00:47:10,480 --> 00:47:14,400
Speaker 1: honorary degrees bestowed on Bill Cosby, Charlie Rose, and others,

755
00:47:14,400 --> 00:47:18,800
Speaker 1: owing to their proven or alleged sexual predations, have to

756
00:47:18,600 --> 00:47:22,000
Speaker 1: have had to be rescinded between the honorary degrees given

757
00:47:22,000 --> 00:47:27,120
Speaker 1: to billionaires, the falsely intelligent entertainers, and the politically correct.

758
00:47:27,600 --> 00:47:30,960
Speaker 1: Just about all honor has been drained from honorary doctorates,

759
00:47:31,840 --> 00:47:35,279
Speaker 1: as your ed d or, E ed d Or, I

760
00:47:35,280 --> 00:47:37,920
Speaker 1: don't know how you even say this educational doctorate, Madame,

761
00:47:38,000 --> 00:47:40,400
Speaker 1: First Lady, hard owned, though hard earned though it may

762
00:47:40,440 --> 00:47:43,920
Speaker 1: have been, Please consider stowing it at least in public,

763
00:47:43,960 --> 00:47:46,719
Speaker 1: at least for now. Forget the small thrill of being

764
00:47:46,880 --> 00:47:49,399
Speaker 1: doctor Jill and settled for the larger thrill of living

765
00:47:49,400 --> 00:47:51,480
Speaker 1: for the next four years and the best public housing

766
00:47:51,520 --> 00:47:58,520
Speaker 1: the world has as First Lady Jill Biden. Yeah, completely

767
00:47:58,560 --> 00:48:01,000
Speaker 1: agree with this piece, which may not surprise that any

768
00:48:01,000 --> 00:48:04,120
Speaker 1: of you. I think it's completely correct. I think he's

769
00:48:04,120 --> 00:48:09,719
Speaker 1: spot on. I think Joe Biden is you know, I

770
00:48:09,760 --> 00:48:12,240
Speaker 1: think that she's a little high falutin here, and I agree,

771
00:48:12,520 --> 00:48:14,239
Speaker 1: and I think we are allowed to make fun of this.

772
00:48:14,360 --> 00:48:20,799
Speaker 1: I'm sorry. I am not simply not going to bend

773
00:48:20,800 --> 00:48:26,160
Speaker 1: the knee on this one because they say so. No interest,

774
00:48:26,760 --> 00:48:35,000
Speaker 1: no interest whatsoever. So that's what I would say. That's

775
00:48:35,040 --> 00:48:37,080
Speaker 1: where I am on this one. Not calling her doctor Joe,

776
00:48:37,080 --> 00:48:39,680
Speaker 1: don't call her Joe Biden the first lady. You can

777
00:48:39,680 --> 00:48:42,520
Speaker 1: call her first lady, that's fine, or Joe Biden, that's

778
00:48:42,520 --> 00:48:45,960
Speaker 1: her name. Joe Biden can hem and hall about this

779
00:48:45,960 --> 00:48:47,839
Speaker 1: as much as he wants, but really the more it's

780
00:48:47,880 --> 00:48:50,719
Speaker 1: just get ready for a lot of the of the

781
00:48:50,840 --> 00:48:52,839
Speaker 1: usual tactics you've seen in the past. They're gonna call

782
00:48:52,960 --> 00:48:56,560
Speaker 1: this person, They're gonna call this person. Weever, it is

783
00:48:57,120 --> 00:48:59,560
Speaker 1: in the role that is pointing out what's so obvious

784
00:48:59,560 --> 00:49:02,480
Speaker 1: to all of us sexist. Get ready for everything is

785
00:49:02,480 --> 00:49:05,520
Speaker 1: going to be sexist and racist again. That's that's the

786
00:49:05,600 --> 00:49:09,319
Speaker 1: future we're now heading toward in a Democrat bid administration.

787
00:49:09,320 --> 00:49:12,600
Speaker 1: Whenever they don't like something, it's sexist, it's racist. They're

788
00:49:12,640 --> 00:49:14,920
Speaker 1: not going to be arguing on the merits. They're not

789
00:49:14,920 --> 00:49:18,480
Speaker 1: going to allow for differences of opinion on things that

790
00:49:18,960 --> 00:49:20,680
Speaker 1: whenever they can get away with it, which is gonna

791
00:49:20,680 --> 00:49:23,440
Speaker 1: be a lot. They're gonna raise this as an issue.

792
00:49:24,320 --> 00:49:27,600
Speaker 1: They're gonna be telling people that this is the way

793
00:49:27,640 --> 00:49:33,080
Speaker 1: it has to be. And I'm sorry, I refuse, I refuse.

794
00:49:33,200 --> 00:49:35,560
Speaker 1: We gotta come up with something they already used hashtag resist.

795
00:49:35,640 --> 00:49:38,040
Speaker 1: We got to come up with a hashtag, you know,

796
00:49:38,640 --> 00:49:51,200
Speaker 1: go blank off libs, something like that, Liberty, truth and

797
00:49:51,520 --> 00:49:55,279
Speaker 1: great hair. You're listening to the best of the Buck

798
00:49:55,360 --> 00:50:03,480
Speaker 1: Sexton Show. Interesting. Sorry today at a time when I

799
00:50:03,600 --> 00:50:06,839
Speaker 1: know the Attorney General has come in for a lot

800
00:50:06,880 --> 00:50:10,200
Speaker 1: of criticism from Trump's supporters. Interesting story not getting a

801
00:50:10,200 --> 00:50:13,680
Speaker 1: whole lot of attention here, but a little bit. Special

802
00:50:13,760 --> 00:50:19,080
Speaker 1: Counsel Durham is expanding his team examining the origins of

803
00:50:19,200 --> 00:50:22,160
Speaker 1: the Russia collusion problem. Let me tell you what could

804
00:50:22,239 --> 00:50:25,040
Speaker 1: end up happening here, friends. Well, first, first, I'll give

805
00:50:25,040 --> 00:50:26,959
Speaker 1: you the update in the story. Fox News has learned

806
00:50:26,960 --> 00:50:30,000
Speaker 1: that Durham, the USE Attorney for Connecticut who bar appointed

807
00:50:30,120 --> 00:50:33,480
Speaker 1: in October a special Counsels adding prosecutors to his team.

808
00:50:34,840 --> 00:50:37,400
Speaker 1: It's unclear who they are, but Fox News a supporter

809
00:50:37,480 --> 00:50:39,920
Speaker 1: that Jeff j Jeff Jensen, the US Attorney for the

810
00:50:39,960 --> 00:50:42,840
Speaker 1: Eastern District of Missouri, stab by the Justice Department in

811
00:50:42,840 --> 00:50:45,080
Speaker 1: February or review the case of former AT Security advisor

812
00:50:45,080 --> 00:50:49,440
Speaker 1: Michael Flynn was helping the Durhm's investigation. So this is

813
00:50:49,520 --> 00:50:54,160
Speaker 1: this is interesting that that the Durham would be expanding

814
00:50:54,280 --> 00:50:56,880
Speaker 1: his team at this phase now he's a special counsel,

815
00:50:57,880 --> 00:51:01,479
Speaker 1: makes it a lot hard harder, makes it a lot

816
00:51:01,560 --> 00:51:06,520
Speaker 1: harder for anyone to just shut this down in a

817
00:51:06,520 --> 00:51:08,719
Speaker 1: Biden administration. I'm not saying it's impossible, but it makes

818
00:51:08,719 --> 00:51:12,520
Speaker 1: it more complicated, it makes it more politically costly. And

819
00:51:12,600 --> 00:51:15,120
Speaker 1: here's what I see happening. If they shut it down,

820
00:51:16,080 --> 00:51:18,480
Speaker 1: We've already established because they said this under Trump, if

821
00:51:18,480 --> 00:51:20,840
Speaker 1: they shut down they told us that if Trump shut

822
00:51:20,840 --> 00:51:23,680
Speaker 1: down the Special Collusion I'm sorry, Special Council probe into

823
00:51:23,719 --> 00:51:27,640
Speaker 1: Russia collusion, if they shut that down, they would impeach

824
00:51:27,719 --> 00:51:30,399
Speaker 1: him just for shutting it down. We might be able

825
00:51:30,400 --> 00:51:35,000
Speaker 1: to take the House back in two years. And depending

826
00:51:35,080 --> 00:51:38,680
Speaker 1: on what this Durham probe finds, wouldn't it be fair play?

827
00:51:38,920 --> 00:51:44,640
Speaker 1: Wouldn't it be justice? Dare I say if Durham gets

828
00:51:44,640 --> 00:51:49,440
Speaker 1: the goods on Biden and members of the members of

829
00:51:49,480 --> 00:51:52,680
Speaker 1: the Obama administration, I mean, who knows what he's really

830
00:51:52,680 --> 00:51:54,960
Speaker 1: going to find here, right, but people from the Obama

831
00:51:55,000 --> 00:51:58,200
Speaker 1: administration who could be back in the Biden administration and

832
00:51:58,360 --> 00:52:02,600
Speaker 1: Biden word shut down the Durham probe or even try to.

833
00:52:03,560 --> 00:52:07,359
Speaker 1: Maybe it's time for a little Democrat impeachment process and

834
00:52:07,440 --> 00:52:10,120
Speaker 1: maybe we'll see how they like it. You know, this

835
00:52:10,160 --> 00:52:14,680
Speaker 1: could happen. I know it's a ways out. But if

836
00:52:14,760 --> 00:52:18,040
Speaker 1: we do have a full accounting of Russia collusion, we

837
00:52:18,040 --> 00:52:20,960
Speaker 1: we'll see if the Democrats are a bunch of corrupt

838
00:52:21,840 --> 00:52:27,000
Speaker 1: deep state liars and their disgrace, and that the Obama

839
00:52:27,040 --> 00:52:30,799
Speaker 1: administration that Joe Biden was a part of at a

840
00:52:30,880 --> 00:52:34,920
Speaker 1: very high level was also a complete and utter disgrace.

841
00:52:35,480 --> 00:52:39,239
Speaker 1: So don't don't give up entirely on this. I said

842
00:52:39,320 --> 00:52:41,680
Speaker 1: Durham wasn't going to get it done before the election.

843
00:52:42,520 --> 00:52:44,360
Speaker 1: I didn't realize that there was going to be a

844
00:52:44,440 --> 00:52:47,319
Speaker 1: special counsel appointed after the election, or that he would

845
00:52:47,360 --> 00:52:50,600
Speaker 1: be appointed as a special counsel. And this could this

846
00:52:50,680 --> 00:52:53,400
Speaker 1: could change things quite a bit. This, this could be

847
00:52:54,840 --> 00:53:00,000
Speaker 1: very very relevant going forward because friends, the Russia calloo

848
00:53:00,280 --> 00:53:04,400
Speaker 1: stuff was was atrocious, and we know enough now to

849
00:53:04,440 --> 00:53:06,600
Speaker 1: know that everything we've said about how bad they were,

850
00:53:06,680 --> 00:53:11,160
Speaker 1: and how awful and egregious their actions were. We were

851
00:53:11,239 --> 00:53:14,439
Speaker 1: telling the truth, we were correct, and they were lying

852
00:53:14,480 --> 00:53:17,919
Speaker 1: about this stuff. So Durham being able to find out

853
00:53:18,000 --> 00:53:20,879
Speaker 1: more here and get to the point where he's able

854
00:53:20,880 --> 00:53:23,879
Speaker 1: to hold people accountable, I think that could really make

855
00:53:23,920 --> 00:53:27,560
Speaker 1: a big difference down the line. Not right now, but

856
00:53:27,719 --> 00:53:31,440
Speaker 1: down the line. This is a long fight, friends, Don't

857
00:53:31,560 --> 00:53:35,920
Speaker 1: don't feel dejected. Don't feel like you know all is

858
00:53:36,000 --> 00:53:38,160
Speaker 1: lost right now, because I understand there's a tough week

859
00:53:38,160 --> 00:53:42,719
Speaker 1: with the electoral Electoral College today and this is not

860
00:53:42,800 --> 00:53:45,799
Speaker 1: an easy time. But we still have a lot of

861
00:53:45,880 --> 00:53:49,400
Speaker 1: fights ahead and the Democrats are going to have their handsful,

862
00:53:49,440 --> 00:53:51,319
Speaker 1: and I hope this Durham probe makes things a whole

863
00:53:51,320 --> 00:53:59,120
Speaker 1: lot more challenging for them, that's for sure. Buck took

864
00:53:59,120 --> 00:54:02,000
Speaker 1: the day off. Don't worry, We've still got your covered.

865
00:54:02,719 --> 00:54:07,239
Speaker 1: This is the best of the Buck Sexton show. They

866
00:54:07,239 --> 00:54:10,920
Speaker 1: can ban me, they can throttle me, they can shadow

867
00:54:10,920 --> 00:54:15,200
Speaker 1: band all the things that they're doing, demonetize, you know,

868
00:54:15,440 --> 00:54:18,720
Speaker 1: they can scold me with these emails. There's no human

869
00:54:18,760 --> 00:54:20,560
Speaker 1: being that could win any of these arguments with me.

870
00:54:20,600 --> 00:54:25,040
Speaker 1: So now it's all. It's all from anonymous online accounts

871
00:54:25,080 --> 00:54:28,680
Speaker 1: from these mega social media companies. I mean, this is

872
00:54:28,680 --> 00:54:31,520
Speaker 1: like a cough gas nightmare. You're banned because you said

873
00:54:31,560 --> 00:54:35,400
Speaker 1: something not true. I shared an opinion and it's actually

874
00:54:35,560 --> 00:54:38,880
Speaker 1: rooted in fact. But who wants to debate me? No? No, sorry,

875
00:54:39,239 --> 00:54:44,960
Speaker 1: the fact checkers said you're wrong. Oh oh, the fact checkers. Well,

876
00:54:45,000 --> 00:54:47,640
Speaker 1: I'm sure people that spend their time doing fact checks

877
00:54:47,680 --> 00:54:52,040
Speaker 1: on social media are really smart and understand the complexities

878
00:54:52,040 --> 00:54:56,160
Speaker 1: of American politics as well as microbiology and COVID policy.

879
00:54:56,280 --> 00:54:58,840
Speaker 1: I'm sure there are a bunch of geniuses. You know

880
00:54:58,880 --> 00:55:02,960
Speaker 1: what this is, friends, The left was losing ground when

881
00:55:03,000 --> 00:55:06,360
Speaker 1: social media was never a truly open playing field, but

882
00:55:06,440 --> 00:55:10,520
Speaker 1: when there was an active censorship. And so what they've

883
00:55:10,520 --> 00:55:14,920
Speaker 1: done is they've bullied their buddies, their peers, Jack Dorsey

884
00:55:14,960 --> 00:55:17,480
Speaker 1: and Zuckerberg and the rest, and they've bullied them into

885
00:55:17,480 --> 00:55:22,960
Speaker 1: adopting these official stances that privilege, advance and support the

886
00:55:23,040 --> 00:55:27,680
Speaker 1: left wing narrative of events. This we talk about how

887
00:55:28,000 --> 00:55:30,239
Speaker 1: if we lose, and we'll talk about the Georgia Senate seat.

888
00:55:30,200 --> 00:55:31,520
Speaker 1: It's coming up here in a little bit too. But

889
00:55:31,560 --> 00:55:33,160
Speaker 1: if we lose the Senate, they're going to add DC

890
00:55:33,320 --> 00:55:36,200
Speaker 1: Puerto Rico Pack, the Supreme Court get obviously the filibuster

891
00:55:36,239 --> 00:55:39,479
Speaker 1: are getting rid of. It goes first. If we don't

892
00:55:39,480 --> 00:55:44,480
Speaker 1: get control of the ability to communicate freely online, we're done.

893
00:55:44,600 --> 00:55:48,359
Speaker 1: In the long term, conservatism is over. If they can

894
00:55:48,400 --> 00:55:50,239
Speaker 1: tell you what you can think and what you could say,

895
00:55:50,239 --> 00:55:53,280
Speaker 1: and how you can share information because we can't compete,

896
00:55:53,280 --> 00:55:54,839
Speaker 1: you can say, oh, buck, well, we can all start

897
00:55:54,840 --> 00:55:56,960
Speaker 1: writing to each other with quill pens and use snail

898
00:55:57,000 --> 00:56:00,040
Speaker 1: mail or something. We won't be able to compete. The

899
00:56:00,160 --> 00:56:03,719
Speaker 1: propaganda machine will become overwhelming. Again. Why do you think

900
00:56:03,719 --> 00:56:06,439
Speaker 1: they're so desperate to do this. It's pathetic, but it's

901
00:56:06,560 --> 00:56:13,080
Speaker 1: very effective. It's very effective. This is concerning, it's upsetting.

902
00:56:14,239 --> 00:56:17,040
Speaker 1: We gotta fight, friends, We gotta fight. We gotta fight

903
00:56:17,120 --> 00:56:21,840
Speaker 1: for these election results to be clear, to be real.

904
00:56:22,640 --> 00:56:24,920
Speaker 1: We have to see where there was fraud. We have

905
00:56:24,960 --> 00:56:26,680
Speaker 1: to find it. We have to put it out there.

906
00:56:26,880 --> 00:56:29,480
Speaker 1: And they're gonna tell you that fact checkers say this

907
00:56:29,560 --> 00:56:33,360
Speaker 1: isn't true, of course, and they're gonna tell you. Do

908
00:56:33,440 --> 00:56:36,560
Speaker 1: what you're told. Wear a mask, shut up, peasant. Sorry

909
00:56:36,800 --> 00:56:38,759
Speaker 1: if you lose your business, Sorry if you have a

910
00:56:38,800 --> 00:56:43,160
Speaker 1: mental breakdown. Mental health metrics in this country are in

911
00:56:43,360 --> 00:56:47,800
Speaker 1: the toilet. I mean, it's going terribly for people, kids

912
00:56:47,840 --> 00:56:50,080
Speaker 1: taken out of school. I just want to know when

913
00:56:50,120 --> 00:56:52,880
Speaker 1: I was advocating for schools to be open in August,

914
00:56:52,920 --> 00:56:55,839
Speaker 1: as I was, and as the President Trump was, When

915
00:56:55,880 --> 00:56:58,520
Speaker 1: I was advocating for schools to open, I wonder I

916
00:56:58,560 --> 00:57:00,360
Speaker 1: have thing to be able to go back and look. Yet,

917
00:57:00,480 --> 00:57:04,680
Speaker 1: how much fact checking and throttling of my usage of

918
00:57:04,719 --> 00:57:10,680
Speaker 1: these supposedly free and fair platforms online occurred? Do you

919
00:57:10,680 --> 00:57:14,120
Speaker 1: think that? Do I get an email from Twitter saying, hey,

920
00:57:14,480 --> 00:57:19,320
Speaker 1: Fouchi's actually a week will Democrat jackass and you were

921
00:57:19,440 --> 00:57:24,360
Speaker 1: right about schools. Sorry about that? No, No, I do not.

922
00:57:26,040 --> 00:57:28,439
Speaker 1: I do I get anybody saying, oh wow, great call

923
00:57:28,480 --> 00:57:30,040
Speaker 1: when I said that New York City was gonna lock

924
00:57:30,080 --> 00:57:32,160
Speaker 1: down again, that all these cities were gonna lock down again,

925
00:57:32,400 --> 00:57:34,040
Speaker 1: and that the stuff we were doing over the summer

926
00:57:34,040 --> 00:57:37,800
Speaker 1: when cases were low was just theater. No, I do

927
00:57:37,920 --> 00:57:40,760
Speaker 1: not get an apology for that. No one tells me sorry,

928
00:57:40,840 --> 00:57:45,040
Speaker 1: you were right. Wow. What has Fouchi been right about?

929
00:57:45,280 --> 00:57:47,600
Speaker 1: I just what has Fouchi said that? He goes, oh wow,

930
00:57:47,840 --> 00:57:51,680
Speaker 1: that was good. He saw that one coming. Of course,

931
00:57:51,720 --> 00:57:55,880
Speaker 1: Biden's keeping them on the classic bureaucrat status move. Have

932
00:57:56,040 --> 00:58:00,440
Speaker 1: somebody who's a total clown, but they have the right politics,

933
00:58:00,560 --> 00:58:03,040
Speaker 1: and you keep them around. You keep them around and

934
00:58:03,080 --> 00:58:07,040
Speaker 1: have them hide behind their credentials. You know, Fauci's not

935
00:58:07,120 --> 00:58:09,919
Speaker 1: some world class brain surgeon. Okay, he's a guy who's

936
00:58:09,920 --> 00:58:12,240
Speaker 1: a game. We got, you know, to metrics and the numbers.

937
00:58:12,720 --> 00:58:14,960
Speaker 1: And you know, I've been a doctor in public health

938
00:58:15,000 --> 00:58:18,080
Speaker 1: for a long time. Yeah, what what great public health

939
00:58:18,160 --> 00:58:23,200
Speaker 1: scourge did he help us defeat? Ask yourself that question.

940
00:58:23,200 --> 00:58:25,640
Speaker 1: Where where's his record? Where's his track record of success?

941
00:58:25,840 --> 00:58:29,200
Speaker 1: Or was he just hiding in the flabby folds of

942
00:58:29,240 --> 00:58:33,400
Speaker 1: bureaucracy for the last forty years? The flu season might

943
00:58:33,400 --> 00:58:35,960
Speaker 1: be bad this year. Be careful, wash your hands. Thanks,

944
00:58:36,000 --> 00:58:41,920
Speaker 1: doctor Fauci. Amazing, it's amazing, right. You would hope that

945
00:58:41,960 --> 00:58:45,480
Speaker 1: we could at least be honest about this, but we can't. Okay,

946
00:58:45,560 --> 00:58:49,040
Speaker 1: I've got more questions. I can say them here. Thankfully.

947
00:58:49,120 --> 00:58:51,200
Speaker 1: I don't get shut down on radio, so I can

948
00:58:51,280 --> 00:58:53,200
Speaker 1: tell you the truth on the radio. I try to

949
00:58:53,240 --> 00:58:55,720
Speaker 1: tell you the truth online those of you follow me.

950
00:58:56,320 --> 00:59:01,040
Speaker 1: But getting getting shut down, Yeah, what else am I

951
00:59:01,080 --> 00:59:02,600
Speaker 1: gonna do? But yeah, by the thir year. You're gonna

952
00:59:02,600 --> 00:59:04,960
Speaker 1: tell me I'm already I'm posting every I'm on Parlor

953
00:59:05,000 --> 00:59:08,760
Speaker 1: all the time. I'm posting there, of course. But this

954
00:59:08,840 --> 00:59:11,640
Speaker 1: is why I've been saying, we need these things, and

955
00:59:11,760 --> 00:59:14,240
Speaker 1: we need people to back them, and we need big

956
00:59:14,280 --> 00:59:18,120
Speaker 1: money to go into them, you know, Republican billionaires. I

957
00:59:18,160 --> 00:59:21,360
Speaker 1: put out my clarion call to you again. You want

958
00:59:21,360 --> 00:59:25,640
Speaker 1: to help save the country, stop funding another think tank

959
00:59:25,720 --> 00:59:30,320
Speaker 1: that does nothing, and fund a social media platform so

960
00:59:30,400 --> 00:59:33,520
Speaker 1: that it can actually get the user base necessary. And

961
00:59:33,560 --> 00:59:35,920
Speaker 1: by if it's Parlor, that's great. I love Parlor. I'm

962
00:59:35,960 --> 00:59:38,720
Speaker 1: using it every day, and I appreciate what the people

963
00:59:38,720 --> 00:59:41,240
Speaker 1: who are spearheading that are doing. I'm all about it.

964
00:59:41,280 --> 00:59:45,880
Speaker 1: But we need more. I want conservative movie studios. I

965
00:59:46,000 --> 00:59:50,320
Speaker 1: want conservative news organizations that don't have to worry and

966
00:59:50,360 --> 00:59:53,000
Speaker 1: shut down the moment that there's a boycott from some

967
00:59:53,040 --> 00:59:56,040
Speaker 1: of these left wing activists who the game they play,

968
00:59:56,080 --> 00:59:57,720
Speaker 1: it doesn't even have to be a boycott. They just

969
00:59:57,760 --> 01:00:00,400
Speaker 1: have to make people afraid they'll be a boycott. And

970
01:00:00,440 --> 01:00:02,880
Speaker 1: those you were saying, oh but buck, let's you know what,

971
01:00:03,000 --> 01:00:05,720
Speaker 1: we gotta dig more into the Sydney Powell thing or whatever,

972
01:00:05,800 --> 01:00:08,040
Speaker 1: I'm sitting here saying, look, I want to do all

973
01:00:08,080 --> 01:00:12,960
Speaker 1: of that. If they control the information flow, it doesn't matter.

974
01:00:14,080 --> 01:00:17,400
Speaker 1: This is the fight that is hanging above all these

975
01:00:17,400 --> 01:00:19,880
Speaker 1: other political fights we're having. If they can shut this down,

976
01:00:19,920 --> 01:00:22,560
Speaker 1: if they can censor you, they can stop people like

977
01:00:22,640 --> 01:00:26,440
Speaker 1: me from telling you the truth about things. What arguments

978
01:00:26,440 --> 01:00:28,320
Speaker 1: do you think we're going to win. We're in a

979
01:00:28,440 --> 01:00:31,040
Speaker 1: very divided country. There are a lot of Democrats. It

980
01:00:31,080 --> 01:00:33,560
Speaker 1: doesn't matter how bad, it doesn't matter what happens. We

981
01:00:33,560 --> 01:00:35,920
Speaker 1: could set it all new COVID record next week and

982
01:00:35,960 --> 01:00:38,360
Speaker 1: the week after and the week after, and they'll say, oh, well,

983
01:00:38,800 --> 01:00:40,840
Speaker 1: you know you're not locking down enough. And if the

984
01:00:40,840 --> 01:00:42,560
Speaker 1: cases go down or the next two weeks, guess what

985
01:00:42,600 --> 01:00:45,280
Speaker 1: they'll say, See, you lockdowns are great, they work really well.

986
01:00:46,080 --> 01:00:50,080
Speaker 1: And then what happens you stop and then what happened? Right?

987
01:00:50,120 --> 01:00:52,360
Speaker 1: I mean, this is not allowed, not allowed to even

988
01:00:52,360 --> 01:00:54,120
Speaker 1: think about it, not allowed to have a real discussion

989
01:00:54,160 --> 01:00:59,600
Speaker 1: about it. People are suffering because of this. People are

990
01:00:59,600 --> 01:01:05,360
Speaker 1: suffering because of bad policy, because of capricious and arbitrary

991
01:01:05,400 --> 01:01:08,200
Speaker 1: decision making by government officials who are going outside the

992
01:01:08,240 --> 01:01:11,840
Speaker 1: normal legislative process that checks and balances the accountability for

993
01:01:11,880 --> 01:01:15,560
Speaker 1: what's happening that's been wiped away. And you have people

994
01:01:15,600 --> 01:01:19,240
Speaker 1: like this, like this woman who is a restaurant owner,

995
01:01:20,400 --> 01:01:23,800
Speaker 1: a restaurant owner in California who put out a video

996
01:01:23,800 --> 01:01:26,160
Speaker 1: when viral, and I want to just narrate a little bit,

997
01:01:26,160 --> 01:01:28,840
Speaker 1: then you'll hear her voice. But she goes outside of

998
01:01:28,880 --> 01:01:34,760
Speaker 1: her restaurant. She spent eighty thousand dollars, a lot of

999
01:01:34,800 --> 01:01:36,760
Speaker 1: money for a small business, for a restaurant. I mean,

1000
01:01:36,760 --> 01:01:43,480
Speaker 1: I'm you know, spent eighty thousand dollars creating a really functional, cozy,

1001
01:01:44,160 --> 01:01:51,080
Speaker 1: substantial outdoor dining area in California. And after doing that,

1002
01:01:51,160 --> 01:01:53,680
Speaker 1: and she obeyed them a she bent the knee. And

1003
01:01:53,680 --> 01:01:55,600
Speaker 1: by the way, I don't say that disparagingly, but you know,

1004
01:01:55,680 --> 01:01:58,520
Speaker 1: she said, okay, government, I'll do what you say here.

1005
01:01:58,560 --> 01:02:00,520
Speaker 1: I'm trying to be a good citizen, you know. And

1006
01:02:00,680 --> 01:02:02,480
Speaker 1: she's expecting a little pad on the head from the

1007
01:02:02,520 --> 01:02:05,720
Speaker 1: governance is all right, we're gonna we're taking eighty thousand

1008
01:02:05,720 --> 01:02:09,120
Speaker 1: dollars out of your pocket. But once you've done that,

1009
01:02:09,960 --> 01:02:13,360
Speaker 1: we'll let you operate and sell your food to customers,

1010
01:02:13,640 --> 01:02:16,400
Speaker 1: but it has to be outside. And then they turn around,

1011
01:02:16,400 --> 01:02:20,080
Speaker 1: they say oh, I'm sorry. Too many cases, too many cases.

1012
01:02:20,080 --> 01:02:23,680
Speaker 1: So you're not allowed to open your restaurant anymore. You're

1013
01:02:23,720 --> 01:02:28,000
Speaker 1: you're not allowed to do this. And she walks outside

1014
01:02:28,200 --> 01:02:31,240
Speaker 1: and her outdoor dining and this is why it's it's

1015
01:02:31,240 --> 01:02:33,400
Speaker 1: so I mean, you can't you know, you can't see

1016
01:02:33,440 --> 01:02:35,600
Speaker 1: this if you're listening to this on a podcast or radio.

1017
01:02:36,120 --> 01:02:40,040
Speaker 1: But her outdoor dining area is right next to another

1018
01:02:40,960 --> 01:02:46,200
Speaker 1: outdoor dining area which is set up exclusively for the

1019
01:02:46,320 --> 01:02:51,000
Speaker 1: use of a movie production, which is considerably larger, more chairs,

1020
01:02:51,040 --> 01:02:54,320
Speaker 1: more tables, everything, movie production. It's sort of catering tables

1021
01:02:54,640 --> 01:02:58,840
Speaker 1: because Hollywood needs to be able to do its business.

1022
01:02:59,040 --> 01:03:01,080
Speaker 1: And if you're the mayor, or if you're Garcetti in

1023
01:03:01,120 --> 01:03:06,160
Speaker 1: Los Angeles, you gotta keep Hollywood happy. So her business

1024
01:03:06,240 --> 01:03:09,920
Speaker 1: goes up in smoke. She's out eighty thousand dollars. She

1025
01:03:10,040 --> 01:03:12,920
Speaker 1: may go bankrupt. She has to fire all of her employees.

1026
01:03:12,920 --> 01:03:15,960
Speaker 1: Remember there's no PPP anymore, there's no money coming, there's nothing.

1027
01:03:16,920 --> 01:03:19,560
Speaker 1: Because Nancy Pelosi wanted to make a political point. These

1028
01:03:19,600 --> 01:03:24,440
Speaker 1: democrats are vicious, vicious. It's gonna get worse too, if

1029
01:03:24,440 --> 01:03:27,760
Speaker 1: they actually managed to seize power with Biden here but

1030
01:03:28,360 --> 01:03:31,440
Speaker 1: here she is in her own words describing what she

1031
01:03:31,560 --> 01:03:35,840
Speaker 1: sees outside of her restaurant. This woman Marsden play it.

1032
01:03:37,000 --> 01:03:39,600
Speaker 1: So this is my place, the Pineapple Hill Grill in Saloon.

1033
01:03:39,720 --> 01:03:41,400
Speaker 1: If you go to my page, you can see all

1034
01:03:41,400 --> 01:03:44,280
Speaker 1: the work I did for outdoor dining, for tables being

1035
01:03:44,320 --> 01:03:47,440
Speaker 1: seven feet apart. And I come in today because I'm

1036
01:03:47,560 --> 01:03:51,280
Speaker 1: organizing a protest, and I came in to get stuff

1037
01:03:51,360 --> 01:03:56,520
Speaker 1: for that, and I walk into my parking lot and

1038
01:03:56,680 --> 01:04:06,600
Speaker 1: obviously Mayor Garcetti has approved this, has approved this being

1039
01:04:06,680 --> 01:04:11,760
Speaker 1: set up for, this being set up for for a

1040
01:04:11,840 --> 01:04:16,680
Speaker 1: movie company. I'm losing everything, everything I own is being

1041
01:04:16,720 --> 01:04:19,240
Speaker 1: taken away from me, and they set up a movie

1042
01:04:19,280 --> 01:04:23,680
Speaker 1: company right next to my outdoor patio, which is right

1043
01:04:23,720 --> 01:04:29,360
Speaker 1: over here. And people wonder why I'm protesting and why

1044
01:04:29,560 --> 01:04:33,479
Speaker 1: I have had enough. They have not given us money

1045
01:04:33,520 --> 01:04:36,160
Speaker 1: and they have shut us down. We cannot survive. My

1046
01:04:36,240 --> 01:04:41,800
Speaker 1: staff cannot survive. Look at this, tell me that this

1047
01:04:41,960 --> 01:04:46,360
Speaker 1: is dangerous. But right next to me as a slap

1048
01:04:46,400 --> 01:04:50,800
Speaker 1: in my face. It is is a slap in her face.

1049
01:04:51,920 --> 01:04:55,320
Speaker 1: And these morons in our media, and they're disgusting, who

1050
01:04:55,400 --> 01:04:58,360
Speaker 1: don't give more voice to women and men like this

1051
01:04:58,920 --> 01:05:00,760
Speaker 1: who have done everything there's a opposed to do, and

1052
01:05:00,800 --> 01:05:04,560
Speaker 1: then just based on the arbitrary whim of government power,

1053
01:05:05,520 --> 01:05:09,840
Speaker 1: they're ruined. Why should she accept that based on what?

1054
01:05:11,000 --> 01:05:12,840
Speaker 1: Let me tell you this. Do you think anyone from

1055
01:05:12,880 --> 01:05:14,720
Speaker 1: the government is going to come to help her? Does

1056
01:05:14,760 --> 01:05:17,480
Speaker 1: anyone feel sorry for her when her business goes under,

1057
01:05:17,560 --> 01:05:19,760
Speaker 1: when she can't make the rent payments for this business,

1058
01:05:20,200 --> 01:05:24,800
Speaker 1: when her life savings are drained? What do they think happens? No,

1059
01:05:25,440 --> 01:05:28,120
Speaker 1: the movie industry producers, the people that are connected that

1060
01:05:29,560 --> 01:05:33,360
Speaker 1: Garcetti and others like him, other Democrats who are particularly

1061
01:05:33,400 --> 01:05:35,520
Speaker 1: odious when it comes to this, all across the country.

1062
01:05:36,320 --> 01:05:39,920
Speaker 1: The ones who are connected, they're fine, They'll be fine.

1063
01:05:40,000 --> 01:05:42,919
Speaker 1: Does anyone feel sorry for this woman? In three months

1064
01:05:43,000 --> 01:05:45,160
Speaker 1: or six months, with the pandemic recedes as it will

1065
01:05:45,680 --> 01:05:48,280
Speaker 1: and she's bankrupt. No, it's sorry, start all over again.

1066
01:05:49,040 --> 01:05:55,280
Speaker 1: Your livelihood, your future was the cost of doing business. Sorry,

1067
01:05:55,920 --> 01:05:58,520
Speaker 1: that's the way that it had to be. Because doctor

1068
01:05:58,560 --> 01:06:03,280
Speaker 1: Fauci says, so oh no, not the movie producers. They're important. Sorry,

1069
01:06:03,440 --> 01:06:15,080
Speaker 1: Too bad for you. Bucks Off spreading freedom coast to coast.

1070
01:06:15,920 --> 01:06:22,280
Speaker 1: This is the best of the Buck Sexton Show. Does

1071
01:06:22,320 --> 01:06:25,400
Speaker 1: anyone even want to try to answer this question. Why

1072
01:06:25,520 --> 01:06:29,920
Speaker 1: is outdoor dining band in California? I want to know,

1073
01:06:30,080 --> 01:06:33,440
Speaker 1: Show me the study, show me where outdoor dining is

1074
01:06:33,480 --> 01:06:36,960
Speaker 1: a major transmission risk, And keep in mind there are

1075
01:06:37,000 --> 01:06:39,840
Speaker 1: activities that are allowed. Still there are plenty of things

1076
01:06:39,920 --> 01:06:41,880
Speaker 1: you can still do in California. I mean, I should

1077
01:06:42,000 --> 01:06:43,800
Speaker 1: say plenty. There are a bunch of things you can

1078
01:06:43,800 --> 01:06:46,920
Speaker 1: still do in California that are far riskier than outdoor dining,

1079
01:06:47,480 --> 01:06:51,640
Speaker 1: like go into a home depot or a lowse go

1080
01:06:51,680 --> 01:06:56,240
Speaker 1: into a costco. That's totally fine. Retail is open at

1081
01:06:56,360 --> 01:07:00,280
Speaker 1: limited capacity, but retail is open. Huh, we're Do you

1082
01:07:00,320 --> 01:07:03,520
Speaker 1: think you're safer being in a place where they limit

1083
01:07:03,520 --> 01:07:05,720
Speaker 1: the number of people indoors but there are still people

1084
01:07:05,760 --> 01:07:09,880
Speaker 1: indoors or being out in open air? Do they think?

1085
01:07:09,920 --> 01:07:11,680
Speaker 1: Do you think the virus is going to fly at

1086
01:07:11,720 --> 01:07:16,240
Speaker 1: you with open air flow? It's like a heat seeking missile.

1087
01:07:16,240 --> 01:07:19,600
Speaker 1: It's going to come at you from twenty feet away outdoors.

1088
01:07:20,880 --> 01:07:22,600
Speaker 1: I'm just I'm wondering. Does anyone want to try to

1089
01:07:22,600 --> 01:07:24,920
Speaker 1: answer this. No, they have no one. It's just be quiet,

1090
01:07:24,960 --> 01:07:28,320
Speaker 1: do what you're told. And I've had enough of be quiet,

1091
01:07:28,320 --> 01:07:30,720
Speaker 1: do what you're told I think this is wrong. I

1092
01:07:30,760 --> 01:07:33,760
Speaker 1: think this needs to stop. And I'm not the only one, obviously.

1093
01:07:33,760 --> 01:07:36,080
Speaker 1: It's why there's these protests happen thing. That's why people

1094
01:07:36,080 --> 01:07:39,440
Speaker 1: are speaking out against this. Kevin O'Leary, mister wonderful. I

1095
01:07:39,480 --> 01:07:42,200
Speaker 1: gotta say I've always I like Kevin O'Leary. I've interviewed him,

1096
01:07:42,240 --> 01:07:45,880
Speaker 1: a medium, good dude. Here he is asking the obvious questions.

1097
01:07:45,920 --> 01:07:49,920
Speaker 1: Play nine. How is it possible when I've spent sixty

1098
01:07:50,000 --> 01:07:53,400
Speaker 1: eighty thousand dollars on the back of the restaurant and

1099
01:07:53,520 --> 01:07:56,320
Speaker 1: the front of the restaurant to provide the seats and

1100
01:07:56,480 --> 01:08:01,440
Speaker 1: the heaters, and complied with the city ortance and was

1101
01:08:02,040 --> 01:08:05,240
Speaker 1: just about to reopen. No tents. This is not tented.

1102
01:08:05,280 --> 01:08:09,840
Speaker 1: This is outside with air flowing. I'm shut down, And

1103
01:08:10,080 --> 01:08:13,400
Speaker 1: right across the street is a big box retailer with

1104
01:08:13,520 --> 01:08:18,479
Speaker 1: food services, vending machines and open service courts inside the store,

1105
01:08:18,760 --> 01:08:23,680
Speaker 1: providing food inside of a big box walls around it.

1106
01:08:23,800 --> 01:08:25,920
Speaker 1: And you could argue to me that they have HEPA filters.

1107
01:08:25,960 --> 01:08:28,360
Speaker 1: I know with certainty they don't. So you're telling me

1108
01:08:28,400 --> 01:08:32,000
Speaker 1: the viral load in the outside of my restaurant is

1109
01:08:32,120 --> 01:08:35,080
Speaker 1: higher than the viral load inside of the big box

1110
01:08:35,080 --> 01:08:38,960
Speaker 1: which is enclosed. That's ridiculous, And there's no science claim

1111
01:08:39,000 --> 01:08:42,240
Speaker 1: on this. You people are making a comment of science statements.

1112
01:08:42,360 --> 01:08:47,240
Speaker 1: How can outside be less safe than inside? You heard

1113
01:08:47,240 --> 01:08:49,280
Speaker 1: God leave himself on your own air just moments ago

1114
01:08:49,360 --> 01:08:52,439
Speaker 1: talking about eating and restaurants outside with a mask on.

1115
01:08:52,920 --> 01:08:54,760
Speaker 1: So now I, as a share will have to go

1116
01:08:54,800 --> 01:08:58,160
Speaker 1: bankrupt and all the employees I have have to be

1117
01:08:58,240 --> 01:09:02,600
Speaker 1: laid off for the third time. Fine, this is totally unfair.

1118
01:09:02,800 --> 01:09:05,559
Speaker 1: This is just Los Angeles. Kevin, by the way, it's

1119
01:09:05,600 --> 01:09:07,200
Speaker 1: not just La How come I can be open to

1120
01:09:07,240 --> 01:09:11,080
Speaker 1: Miami in the same chain. I would love to see

1121
01:09:11,720 --> 01:09:15,360
Speaker 1: Fauci trying to explain that one. I know he's not

1122
01:09:15,400 --> 01:09:18,160
Speaker 1: making the decision. It's Los Angeles. Why can't he tell

1123
01:09:18,200 --> 01:09:20,599
Speaker 1: them not to do this? He'll weigh in on things

1124
01:09:20,640 --> 01:09:23,559
Speaker 1: whenever he feels like it. Dude, is to that open schools,

1125
01:09:23,600 --> 01:09:27,920
Speaker 1: don't open schools wearing masks, Wash your hands, don't breathe

1126
01:09:27,960 --> 01:09:30,880
Speaker 1: too much. This guy's got lots of opinions about what

1127
01:09:30,880 --> 01:09:33,320
Speaker 1: the public should be doing all the time. Why isn't

1128
01:09:33,320 --> 01:09:35,120
Speaker 1: he telling me? But but didn't have an opinion about

1129
01:09:35,160 --> 01:09:36,960
Speaker 1: how school should be open, even though all the data

1130
01:09:37,000 --> 01:09:41,000
Speaker 1: always always not only support of that proved that schools

1131
01:09:41,400 --> 01:09:45,679
Speaker 1: were effectively zero risk to children and not only zeros

1132
01:09:45,680 --> 01:09:48,160
Speaker 1: to children, but that children don't transmit this very easily

1133
01:09:48,160 --> 01:09:51,360
Speaker 1: at all to adults. If at all that's what we

1134
01:09:51,400 --> 01:09:53,960
Speaker 1: actually have seen in schools, Fouchi wouldn't speak up on that.

1135
01:09:54,040 --> 01:09:57,120
Speaker 1: Why doesn't want doesn't want the Democrats and the teachers'

1136
01:09:57,200 --> 01:09:59,960
Speaker 1: unions not to like him. Oh but he's non part

1137
01:10:00,120 --> 01:10:03,679
Speaker 1: If you think Fauci's not partisan, honestly, you know, somebody

1138
01:10:03,680 --> 01:10:06,599
Speaker 1: should go watch MSNBC because they're just not smart enough

1139
01:10:06,600 --> 01:10:08,960
Speaker 1: to handle reality. Does anyone have an answer to what

1140
01:10:09,280 --> 01:10:12,160
Speaker 1: mister wonderful Kevin O'Leary is talking about there? No, they

1141
01:10:12,160 --> 01:10:14,759
Speaker 1: do not. They don't even pretend to have an answer.

1142
01:10:14,800 --> 01:10:18,240
Speaker 1: They have no idea, right, They just say, well, that's

1143
01:10:18,240 --> 01:10:24,040
Speaker 1: what the people in charge are saying. Really really, yeah,

1144
01:10:24,080 --> 01:10:27,120
Speaker 1: this is where we are not even offered up any answers.

1145
01:10:27,640 --> 01:10:29,800
Speaker 1: I wonder if Kevin O'Leary will get if you put

1146
01:10:29,840 --> 01:10:31,759
Speaker 1: some of this stuff out there, if he'll get shadow

1147
01:10:31,760 --> 01:10:34,439
Speaker 1: banned on social media. By the way, the social media

1148
01:10:34,439 --> 01:10:37,200
Speaker 1: companies are doing great, aren't they? During this Amazon's doing

1149
01:10:37,240 --> 01:10:39,960
Speaker 1: great Washington Post doing great. All these a lot of

1150
01:10:40,000 --> 01:10:43,759
Speaker 1: these companies, they're not laying off people. They're not worried.

1151
01:10:44,560 --> 01:10:47,759
Speaker 1: Who's voice listen all of this, the small business owner,

1152
01:10:47,840 --> 01:10:52,920
Speaker 1: the independent American, the worker, the person who's still driving

1153
01:10:53,040 --> 01:10:56,439
Speaker 1: his truck, or the you know, the woman who's still

1154
01:10:56,680 --> 01:11:00,360
Speaker 1: at the grocery store, at the pharmacy. They're still doing

1155
01:11:00,400 --> 01:11:08,200
Speaker 1: their job. You're in the Freedom Hut. This is the

1156
01:11:08,320 --> 01:11:11,920
Speaker 1: Buck Sexton Show. Buck took the day off, but don't worry.

1157
01:11:12,120 --> 01:11:15,400
Speaker 1: We've still got your covered. This is the best of

1158
01:11:15,439 --> 01:11:21,960
Speaker 1: the Buck Sexton Show. What are we really seeing when

1159
01:11:22,000 --> 01:11:24,559
Speaker 1: it comes to the results of these lockdowns? And what

1160
01:11:24,640 --> 01:11:28,080
Speaker 1: has the data told us so far about so many

1161
01:11:28,080 --> 01:11:31,320
Speaker 1: of these expert predictions when it comes to COVID nineteen

1162
01:11:31,360 --> 01:11:34,120
Speaker 1: and how we're supposed to handle it. We're joined out

1163
01:11:34,120 --> 01:11:37,920
Speaker 1: by Phil Kirpin. He's a syndicated columnist and also the

1164
01:11:38,160 --> 01:11:42,320
Speaker 1: president of American Commitment. Phil, thanks for making the time

1165
01:11:42,560 --> 01:11:46,600
Speaker 1: great with Let's talk about schools first. What is the

1166
01:11:46,720 --> 01:11:52,120
Speaker 1: data tell us about school lockdowns at this stage? Or

1167
01:11:52,160 --> 01:11:54,720
Speaker 1: I should just say school closures. It's not even really lockdowns.

1168
01:11:54,720 --> 01:12:00,320
Speaker 1: Closing schools and doing only virtual learning. Probably the single

1169
01:12:00,360 --> 01:12:03,920
Speaker 1: biggest policy mistake of the entire year, which is hanging

1170
01:12:03,920 --> 01:12:05,839
Speaker 1: a lot because we've had a lot of policy mistakes.

1171
01:12:06,439 --> 01:12:10,200
Speaker 1: It's interesting. The original CDC guidance on schools was really balanced,

1172
01:12:10,200 --> 01:12:12,240
Speaker 1: and I think anyone who actually read it and paid

1173
01:12:12,240 --> 01:12:15,040
Speaker 1: attention would not have closed schools. And yet we had

1174
01:12:15,040 --> 01:12:17,719
Speaker 1: sort of this panic contagion that swept the whole country

1175
01:12:17,720 --> 01:12:19,280
Speaker 1: and all the schools were closed, and a lot of

1176
01:12:19,280 --> 01:12:23,400
Speaker 1: them never reopened or opened on very limited part time schedules.

1177
01:12:23,880 --> 01:12:26,080
Speaker 1: And it's interesting. There was a study in the Journal

1178
01:12:26,080 --> 01:12:28,439
Speaker 1: of the American Medical Association a couple of weeks ago.

1179
01:12:28,479 --> 01:12:31,680
Speaker 1: They looked at just the impact of elementary school closures

1180
01:12:31,680 --> 01:12:34,160
Speaker 1: and just for two months in the spring, and they

1181
01:12:34,200 --> 01:12:38,960
Speaker 1: calculated five million years of life lost from two months

1182
01:12:39,400 --> 01:12:42,040
Speaker 1: of elementary school closures, which is probably more years of

1183
01:12:42,040 --> 01:12:44,680
Speaker 1: life lost than we're going to have from the coronavirus.

1184
01:12:45,720 --> 01:12:50,000
Speaker 1: There's a very strong relationship between educational attainment and not

1185
01:12:50,080 --> 01:12:53,920
Speaker 1: just income, but life expectancy as well. The difference between

1186
01:12:53,960 --> 01:12:56,320
Speaker 1: a high school graduate and a high school dropout, on

1187
01:12:56,400 --> 01:13:00,920
Speaker 1: average is about five years of life expectancy. The online

1188
01:13:01,080 --> 01:13:03,240
Speaker 1: learning is not working for a lot of people. For

1189
01:13:03,280 --> 01:13:06,240
Speaker 1: some kids, it's fine some of them are doing okay,

1190
01:13:06,240 --> 01:13:08,200
Speaker 1: but a lot of kids are failing. A lot more

1191
01:13:08,240 --> 01:13:12,680
Speaker 1: kids than ever failed with traditional school, and that has

1192
01:13:12,840 --> 01:13:17,559
Speaker 1: major long term consequences, both economic and health consequences. And

1193
01:13:17,640 --> 01:13:22,080
Speaker 1: so we're essentially imposing enormous harms and enormous enormous costs

1194
01:13:22,640 --> 01:13:27,800
Speaker 1: on children societally, even though children are atists near zero risks,

1195
01:13:28,040 --> 01:13:31,320
Speaker 1: certainly much lower risk with coronavirus than they are from

1196
01:13:31,320 --> 01:13:34,400
Speaker 1: seasonal flu, which is five to ten times more deadly

1197
01:13:34,439 --> 01:13:37,680
Speaker 1: for children than coronavirus, and that we tolerate and that

1198
01:13:37,760 --> 01:13:40,760
Speaker 1: we think is a perfectly acceptable little level of risk.

1199
01:13:40,800 --> 01:13:44,200
Speaker 1: And so children have really been the biggest losers in

1200
01:13:44,240 --> 01:13:48,639
Speaker 1: our policy response to COVID. It feels increasingly feel like

1201
01:13:48,880 --> 01:13:53,320
Speaker 1: the elimination of any tolerable risk when it comes to

1202
01:13:53,360 --> 01:13:56,400
Speaker 1: COVID has been at the center of a lot of

1203
01:13:56,439 --> 01:14:00,599
Speaker 1: the policies that we see, and restaurant in New York

1204
01:14:00,640 --> 01:14:03,880
Speaker 1: City have just been closed as of this week, Contact

1205
01:14:04,000 --> 01:14:07,240
Speaker 1: Racing showed that they were responsible for they believe about

1206
01:14:07,360 --> 01:14:11,439
Speaker 1: one percent of the spread. So what are what have

1207
01:14:11,520 --> 01:14:15,360
Speaker 1: we learned about? Where is the virus spreading in New

1208
01:14:15,439 --> 01:14:17,800
Speaker 1: York and it's and its environs? Because that's a that's

1209
01:14:17,840 --> 01:14:19,759
Speaker 1: also a good proxy for where it would be spreading

1210
01:14:19,760 --> 01:14:23,120
Speaker 1: in other densely populated parts of the country. Well, the

1211
01:14:23,720 --> 01:14:25,960
Speaker 1: data the New York published, and it's interesting because they

1212
01:14:26,040 --> 01:14:28,840
Speaker 1: published you know, very very similar data back in May

1213
01:14:28,960 --> 01:14:31,160
Speaker 1: and then ignored it, and now they're finding the same

1214
01:14:31,200 --> 01:14:34,080
Speaker 1: thing again, which is almost all of the spread is

1215
01:14:34,160 --> 01:14:37,320
Speaker 1: inside of homes, inside of households. And you know, New

1216
01:14:37,360 --> 01:14:40,600
Speaker 1: York of course has a lot of high density residential,

1217
01:14:40,640 --> 01:14:43,479
Speaker 1: a lot of multi family, you know, apartment buildings, and

1218
01:14:44,240 --> 01:14:46,760
Speaker 1: so you know, maybe a little bit different there than

1219
01:14:46,840 --> 01:14:49,400
Speaker 1: some other places, but by and large, I think it's

1220
01:14:49,439 --> 01:14:51,680
Speaker 1: now pretty clear from the contact tracing we've seen all

1221
01:14:51,680 --> 01:14:54,960
Speaker 1: over the country that there's not a lot of spread

1222
01:14:55,040 --> 01:14:57,960
Speaker 1: in places like restaurants and retail, and so that the

1223
01:14:58,120 --> 01:15:00,920
Speaker 1: spread tends to happen sort of the one to one

1224
01:15:00,960 --> 01:15:04,320
Speaker 1: person to person spread tends to happen inside of homes.

1225
01:15:04,360 --> 01:15:07,240
Speaker 1: Now we also have this other problem of these occasional

1226
01:15:07,360 --> 01:15:10,000
Speaker 1: sort of super spread or events which are hard to predict,

1227
01:15:10,040 --> 01:15:14,000
Speaker 1: and we still don't really know why some small percentage

1228
01:15:14,000 --> 01:15:16,200
Speaker 1: of people with this virus and it's only maybe ten

1229
01:15:16,280 --> 01:15:19,760
Speaker 1: percent something like that seemed to be responsible for you know,

1230
01:15:19,800 --> 01:15:21,600
Speaker 1: a lot of the spread. And so you know, if

1231
01:15:21,600 --> 01:15:23,920
Speaker 1: you've got an AD, the average person gets this virus

1232
01:15:23,960 --> 01:15:27,200
Speaker 1: infects zero or one other people. And then but then

1233
01:15:27,200 --> 01:15:29,519
Speaker 1: you've got this small group that affects tons of people.

1234
01:15:29,560 --> 01:15:31,679
Speaker 1: And you know, we still don't really know what makes

1235
01:15:31,720 --> 01:15:35,120
Speaker 1: them different and why they tend to infect lots of people.

1236
01:15:35,160 --> 01:15:38,000
Speaker 1: And I wish with more research we're going into that

1237
01:15:38,080 --> 01:15:40,920
Speaker 1: because that would be very useful to sort of identify

1238
01:15:41,000 --> 01:15:44,200
Speaker 1: and be able to predict what those characteristics are. But

1239
01:15:44,360 --> 01:15:46,640
Speaker 1: by and large, what we saw in the New York

1240
01:15:46,720 --> 01:15:48,720
Speaker 1: hit and it was remarkable because Governor Cuomo came out

1241
01:15:48,720 --> 01:15:51,240
Speaker 1: and he said, look, here's the data. Seventy five percent

1242
01:15:51,320 --> 01:15:54,000
Speaker 1: of transmission is in homes, one percent is in restaurants.

1243
01:15:54,120 --> 01:15:57,800
Speaker 1: So I'm closing restaurants. And you know, then he said, well,

1244
01:15:57,840 --> 01:15:59,640
Speaker 1: you know, because it's something we can do. You know,

1245
01:15:59,640 --> 01:16:02,160
Speaker 1: we can't close homes, we can close restaurants. But of course,

1246
01:16:02,439 --> 01:16:05,240
Speaker 1: just because you can do something doesn't mean that it's

1247
01:16:05,280 --> 01:16:07,360
Speaker 1: actually you know, he said, you know, it's only a

1248
01:16:07,360 --> 01:16:09,439
Speaker 1: small difference, but it's something we can do. You know,

1249
01:16:09,479 --> 01:16:12,000
Speaker 1: but if you look at the data, but it's more

1250
01:16:12,080 --> 01:16:15,559
Speaker 1: likely to be a negative difference than a positive difference,

1251
01:16:15,600 --> 01:16:18,320
Speaker 1: because if you say, you know, we're going to push

1252
01:16:18,520 --> 01:16:21,240
Speaker 1: gatherings and holiday gatherings and dinners and all this kind

1253
01:16:21,240 --> 01:16:23,599
Speaker 1: of stuff out of restaurants where people are being very

1254
01:16:23,640 --> 01:16:26,880
Speaker 1: strict with their distancing and their hygiene and all this stuff,

1255
01:16:26,920 --> 01:16:29,200
Speaker 1: we're gonna push them out. We're gonna close. Now, they're

1256
01:16:29,200 --> 01:16:31,400
Speaker 1: gonna take place in homes instead. You know, some of

1257
01:16:31,400 --> 01:16:33,000
Speaker 1: them won't take place at all, but a lot of

1258
01:16:33,040 --> 01:16:36,000
Speaker 1: them will take place in homes instead without any of

1259
01:16:36,040 --> 01:16:39,759
Speaker 1: those precautions. And so in my judgment, the restaurant closure

1260
01:16:39,800 --> 01:16:43,280
Speaker 1: is not only economically devastating, but it's more likely to

1261
01:16:43,360 --> 01:16:46,200
Speaker 1: increase transmission than to decrease it because people are going

1262
01:16:46,240 --> 01:16:48,680
Speaker 1: to meet in home settings instead. Well, this was a

1263
01:16:48,680 --> 01:16:52,000
Speaker 1: concern also last winter or late late in the winter,

1264
01:16:52,560 --> 01:16:55,400
Speaker 1: when we recognize that New York City was facing this

1265
01:16:55,600 --> 01:16:58,800
Speaker 1: first big wave of COVID cases. They went into the

1266
01:17:00,000 --> 01:17:02,479
Speaker 1: fifteen days to stop the spread and the stay at

1267
01:17:02,479 --> 01:17:04,519
Speaker 1: home orders, and a lot of people are saying, well,

1268
01:17:04,520 --> 01:17:07,439
Speaker 1: hold on a second, We've had this virus is all

1269
01:17:07,479 --> 01:17:10,080
Speaker 1: over the place already, and now what you're going to

1270
01:17:10,160 --> 01:17:12,479
Speaker 1: be doing by shutting down the schools, shutting down anywhere

1271
01:17:12,479 --> 01:17:15,000
Speaker 1: for people to places for people to go, is you

1272
01:17:15,080 --> 01:17:19,920
Speaker 1: might actually be forcing and you mentioned multigenerational, multifamily homes,

1273
01:17:20,000 --> 01:17:23,000
Speaker 1: dense housing, which is all over New York City where

1274
01:17:23,040 --> 01:17:26,559
Speaker 1: people it's very difficult to really stay far away from others.

1275
01:17:26,960 --> 01:17:29,200
Speaker 1: It may have effectively sent everyone home to infect their

1276
01:17:29,200 --> 01:17:33,160
Speaker 1: family members inadvertently, but that was always a concern. Yeah,

1277
01:17:33,200 --> 01:17:35,960
Speaker 1: I think that that almost certainly was a big part

1278
01:17:35,960 --> 01:17:38,280
Speaker 1: of what happened in New York back in the spring. Now,

1279
01:17:38,280 --> 01:17:40,479
Speaker 1: the good thing you've got going for you now in

1280
01:17:40,600 --> 01:17:43,639
Speaker 1: New York is, you know, so many people have already

1281
01:17:43,640 --> 01:17:46,160
Speaker 1: had it. You have a very high level of community immunity,

1282
01:17:46,200 --> 01:17:48,439
Speaker 1: probably higher than anywhere else in the United States. And

1283
01:17:48,479 --> 01:17:50,960
Speaker 1: so if you look at the New York state numbers,

1284
01:17:51,200 --> 01:17:53,679
Speaker 1: it's now mostly outside of the New York City area

1285
01:17:53,680 --> 01:17:55,160
Speaker 1: and sort of the rest of the state is kind

1286
01:17:55,160 --> 01:17:58,760
Speaker 1: of catching up New York City. If you look at

1287
01:17:58,800 --> 01:18:02,519
Speaker 1: the hospital utilization in the emergency room data, you've actually

1288
01:18:02,600 --> 01:18:07,400
Speaker 1: got lower emergency room visits for respiratory illnesses and influenza

1289
01:18:07,439 --> 01:18:10,960
Speaker 1: like illness now than you know, any of the previous

1290
01:18:10,960 --> 01:18:13,759
Speaker 1: five years this time of year. So you're actually lower

1291
01:18:13,800 --> 01:18:17,280
Speaker 1: than normal in New York City. I think because you've

1292
01:18:17,280 --> 01:18:19,960
Speaker 1: got a lot of community immunity to COVID, and because

1293
01:18:20,000 --> 01:18:22,360
Speaker 1: the other factor, which is happening everywhere in the world

1294
01:18:22,439 --> 01:18:26,320
Speaker 1: right now with very little attention paid to it, there's

1295
01:18:26,360 --> 01:18:28,960
Speaker 1: almost no flu activity this year. And we don't know

1296
01:18:29,000 --> 01:18:32,400
Speaker 1: if that's because you know, the policy measures like the

1297
01:18:32,439 --> 01:18:35,519
Speaker 1: masks and the distancing and school closures are somehow more

1298
01:18:35,560 --> 01:18:38,080
Speaker 1: effective for flu than they are for COVID, or if

1299
01:18:38,120 --> 01:18:41,040
Speaker 1: the virus itself has somehow disrupted. We don't really know

1300
01:18:41,120 --> 01:18:44,160
Speaker 1: why it's the case, but it's a remarkable story because

1301
01:18:44,280 --> 01:18:46,280
Speaker 1: remember the experts that we're gonna have this twindemic flu

1302
01:18:46,360 --> 01:18:47,880
Speaker 1: is going to hit at the same time as COVID,

1303
01:18:48,080 --> 01:18:51,320
Speaker 1: all the hospital's gonna be overwhelmed. Instead, we've got, you know,

1304
01:18:51,360 --> 01:18:54,240
Speaker 1: the mildest flu season since at least twenty fifteen, and

1305
01:18:54,320 --> 01:18:56,320
Speaker 1: maybe you know, we'll see if it doesn't take off

1306
01:18:56,320 --> 01:18:59,439
Speaker 1: at all, maybe the mildest flu season on records. So

1307
01:18:59,479 --> 01:19:03,559
Speaker 1: you've got really under utilization of hospitals in a place

1308
01:19:03,600 --> 01:19:06,320
Speaker 1: like New York City that has relatively little COVID activity

1309
01:19:06,400 --> 01:19:09,280
Speaker 1: because we're not seeing any fluid. I pulled some numbers

1310
01:19:09,360 --> 01:19:11,880
Speaker 1: last week. I'm glad you brought that up. Phil I'm

1311
01:19:11,920 --> 01:19:16,200
Speaker 1: speaking of Phil Kirpin, syndicated columnist, journalist, and at Phil

1312
01:19:16,680 --> 01:19:19,800
Speaker 1: I looked at the initial Now, now I had someone, right,

1313
01:19:19,840 --> 01:19:22,760
Speaker 1: I've had people right into me since to say we're

1314
01:19:22,800 --> 01:19:26,160
Speaker 1: not really testing for flu the way that we normally do.

1315
01:19:26,240 --> 01:19:28,360
Speaker 1: And to that, I say, okay, because I am asking.

1316
01:19:28,360 --> 01:19:30,040
Speaker 1: You know, so sometimes people are asking a question and

1317
01:19:30,080 --> 01:19:32,759
Speaker 1: they're really trying to push a conclusion. I'm actually asking

1318
01:19:32,760 --> 01:19:36,400
Speaker 1: the question. But I pose to the audience. I said,

1319
01:19:37,120 --> 01:19:39,840
Speaker 1: you know, the initial data on the CDC website for

1320
01:19:39,880 --> 01:19:43,080
Speaker 1: the first week of December, and and I think it

1321
01:19:43,120 --> 01:19:45,080
Speaker 1: was it was low for what they actually had for COVID.

1322
01:19:45,120 --> 01:19:47,120
Speaker 1: So this was initial data. So the numbers are clearly

1323
01:19:47,120 --> 01:19:49,080
Speaker 1: going to go up, and you know, maybe it went

1324
01:19:49,160 --> 01:19:51,320
Speaker 1: from you know, maybe I might even go up by

1325
01:19:51,320 --> 01:19:53,040
Speaker 1: a factor of ten let's say, right, I mean, it

1326
01:19:53,040 --> 01:19:55,479
Speaker 1: could go up substantially. But the initial data said that

1327
01:19:55,600 --> 01:20:00,680
Speaker 1: they had something like two thousand plus COVID debts in

1328
01:20:00,720 --> 01:20:03,519
Speaker 1: the first week of December that we're officially COVID, you know,

1329
01:20:03,560 --> 01:20:07,759
Speaker 1: meaning that this is the way they had three three

1330
01:20:07,880 --> 01:20:12,040
Speaker 1: from the flu. Now I can understand more COVID I

1331
01:20:12,040 --> 01:20:15,400
Speaker 1: got under but there's clearly something going on here. I

1332
01:20:15,439 --> 01:20:19,000
Speaker 1: mean you mentioned some of the possibilities. There's no way

1333
01:20:19,040 --> 01:20:22,040
Speaker 1: that you have almost a factor of a thousand more

1334
01:20:22,240 --> 01:20:24,880
Speaker 1: COVID debts than you do flu debts, given what we

1335
01:20:24,920 --> 01:20:28,439
Speaker 1: would see in a normal flu season. That's not possible. Well,

1336
01:20:29,400 --> 01:20:33,120
Speaker 1: you know, flue peaks are more often in January and

1337
01:20:33,120 --> 01:20:35,679
Speaker 1: February than they are in November and December time, sometimes

1338
01:20:35,680 --> 01:20:38,479
Speaker 1: you have in earlier flu seasons. So you know a

1339
01:20:38,560 --> 01:20:40,439
Speaker 1: lot of people say, well, you know, flu's not here yet,

1340
01:20:40,479 --> 01:20:43,400
Speaker 1: it's still coming. That might be true, but we've never

1341
01:20:43,439 --> 01:20:46,120
Speaker 1: seen levels this low. We've never seen levels this low.

1342
01:20:46,160 --> 01:20:48,800
Speaker 1: And if you look at the CDC flu testing data,

1343
01:20:49,360 --> 01:20:54,840
Speaker 1: it's down about ninety five almost one hundred percent some weeks,

1344
01:20:54,840 --> 01:20:56,920
Speaker 1: and we've had like ninety eight percent reduction from the

1345
01:20:56,960 --> 01:20:59,960
Speaker 1: five year average. And it's not that we're not testing.

1346
01:21:00,120 --> 01:21:04,080
Speaker 1: The flu tests are actually higher than the five year average,

1347
01:21:04,080 --> 01:21:06,719
Speaker 1: and they're actually at a record high. At the number

1348
01:21:06,720 --> 01:21:08,960
Speaker 1: of flu tests at the CDC tracks, and the CDC

1349
01:21:09,080 --> 01:21:11,880
Speaker 1: only tracks clinical labs and public health labs, so they

1350
01:21:11,880 --> 01:21:14,000
Speaker 1: don't track, you know, like the rapid tests in the

1351
01:21:14,080 --> 01:21:16,360
Speaker 1: doctor's office. That's not in the stats, So they only

1352
01:21:16,400 --> 01:21:18,360
Speaker 1: have thousands of tests. They don't have millions of tests,

1353
01:21:19,000 --> 01:21:22,320
Speaker 1: but it's still it indicates that I think one of

1354
01:21:22,400 --> 01:21:27,360
Speaker 1: three things is going on buck Either we've got the

1355
01:21:27,479 --> 01:21:30,320
Speaker 1: public health measures that are being implemented for some reason,

1356
01:21:30,439 --> 01:21:32,680
Speaker 1: or very effective at stopping flu, even though they don't

1357
01:21:32,720 --> 01:21:36,160
Speaker 1: seem to be. They're not effective at stopping covid right right,

1358
01:21:36,240 --> 01:21:37,920
Speaker 1: So that's a little hard to believe, although a lot

1359
01:21:37,920 --> 01:21:40,679
Speaker 1: of people have been saying that or somehow the covid

1360
01:21:40,800 --> 01:21:44,200
Speaker 1: virus itself disrupts the flu virus, which is possible. There's

1361
01:21:44,200 --> 01:21:47,599
Speaker 1: a phenomenon called viral interference, and this was actually how

1362
01:21:47,640 --> 01:21:49,760
Speaker 1: swine flu ended back in two thousand and nine. The

1363
01:21:49,840 --> 01:21:52,559
Speaker 1: rhinovirus came in and it sort of just knocked it out,

1364
01:21:52,640 --> 01:21:55,040
Speaker 1: you know, people got that instead, and it sort of

1365
01:21:55,120 --> 01:21:56,760
Speaker 1: knocked it out, and there was some hope. There was

1366
01:21:56,760 --> 01:21:59,240
Speaker 1: actually an article, you know, months ago, hoping that flu

1367
01:21:59,320 --> 01:22:02,120
Speaker 1: season would come in and sort of disrupt COVID. That

1368
01:22:02,240 --> 01:22:04,920
Speaker 1: definitely didn't happen, but maybe the opposite happened. Maybe COVID

1369
01:22:04,920 --> 01:22:07,720
Speaker 1: disrupted flu, and you know, once you get COVID, your

1370
01:22:08,120 --> 01:22:11,439
Speaker 1: mucus build up blocks flu, or some mechanism causes viral

1371
01:22:11,520 --> 01:22:14,640
Speaker 1: interference or the third possibility is that we've got some

1372
01:22:14,680 --> 01:22:17,880
Speaker 1: sort of a data artifact where maybe you know, we're

1373
01:22:17,960 --> 01:22:20,599
Speaker 1: get so many false positives for COVID that people get flu,

1374
01:22:20,680 --> 01:22:23,240
Speaker 1: they test false positive, it gets into the stats as

1375
01:22:23,240 --> 01:22:27,559
Speaker 1: of COVID case instead of a flu case. Maybe there's

1376
01:22:27,560 --> 01:22:29,600
Speaker 1: a timing issue where even though we have lots of

1377
01:22:29,600 --> 01:22:32,400
Speaker 1: flu tests, people are only taking the flu test after

1378
01:22:32,439 --> 01:22:34,559
Speaker 1: they get a negative COVID test back, and by then

1379
01:22:34,680 --> 01:22:37,840
Speaker 1: flu is not detectable anymore. Some people have suggested that,

1380
01:22:37,920 --> 01:22:41,320
Speaker 1: so they're basically there are three possibilities, in my judgment,

1381
01:22:41,360 --> 01:22:46,160
Speaker 1: Either the policies are actually stopping flu somehow there's actual

1382
01:22:46,360 --> 01:22:48,639
Speaker 1: viral interference, or we've got some sort of a data

1383
01:22:48,720 --> 01:22:51,000
Speaker 1: artifact based on the sequence and the way that we're

1384
01:22:51,000 --> 01:22:53,960
Speaker 1: doing the testing that's causing the flu cases to be

1385
01:22:54,080 --> 01:22:56,479
Speaker 1: mischaracterized as COVID. So it's got to be one of

1386
01:22:56,479 --> 01:22:58,960
Speaker 1: those three things. I'm not sure which it is, or

1387
01:22:59,000 --> 01:23:02,439
Speaker 1: if it's a combination, but I wish there were a

1388
01:23:02,439 --> 01:23:05,599
Speaker 1: lot more curiosity about this, you know, among the media

1389
01:23:05,640 --> 01:23:08,280
Speaker 1: and among the public health officials, because it's a pretty

1390
01:23:08,280 --> 01:23:11,519
Speaker 1: remarkable phenomenon. Talk to me about this, and we're speaking

1391
01:23:11,520 --> 01:23:14,919
Speaker 1: of Phil Kirpin. He is the president of American Commitment,

1392
01:23:14,920 --> 01:23:18,680
Speaker 1: and he's a syndicated columnist. Phil I see all these

1393
01:23:18,760 --> 01:23:20,479
Speaker 1: charts and I've I've looked at some of the data myself,

1394
01:23:20,520 --> 01:23:24,920
Speaker 1: and they show mask mandates going into place on a timeline.

1395
01:23:25,560 --> 01:23:29,200
Speaker 1: And you know, for a state, right whether it's California

1396
01:23:29,360 --> 01:23:32,360
Speaker 1: or Hawaii or New York or wherever mask mandate goes

1397
01:23:32,400 --> 01:23:36,040
Speaker 1: into effect, and then you have countless charts where you

1398
01:23:36,080 --> 01:23:38,960
Speaker 1: just give it time and the case is just skyrocket

1399
01:23:39,160 --> 01:23:42,400
Speaker 1: after the mandate goes into effect. What can we just

1400
01:23:42,439 --> 01:23:46,200
Speaker 1: tell from the numbers about this as a policy? Can

1401
01:23:46,280 --> 01:23:49,320
Speaker 1: can we draw any conclusions or you can you draw

1402
01:23:49,360 --> 01:23:53,320
Speaker 1: any conclusions from what we're seeing. I don't think masks

1403
01:23:53,360 --> 01:23:57,600
Speaker 1: have any effect mask mandates. You know, we should we

1404
01:23:57,640 --> 01:24:00,559
Speaker 1: should differentiate the two masked mandates and masks are not

1405
01:24:00,640 --> 01:24:03,960
Speaker 1: necessarily synonymous, because just because the mandates in an area

1406
01:24:03,960 --> 01:24:06,519
Speaker 1: doesn't mean everyone's wearing them, or wearing them properly, or

1407
01:24:06,520 --> 01:24:09,280
Speaker 1: handling them properly and so forth. You know, the reason

1408
01:24:09,439 --> 01:24:14,160
Speaker 1: historically we've never recommended masks outside of medical settings is

1409
01:24:14,240 --> 01:24:17,439
Speaker 1: it's actually really hard to use a mask properly, to

1410
01:24:17,479 --> 01:24:19,680
Speaker 1: make sure you never touch the outside to remove it.

1411
01:24:20,320 --> 01:24:22,599
Speaker 1: Carefully and throw it out or wash it without ever

1412
01:24:22,640 --> 01:24:25,360
Speaker 1: touching the outside. And you know, that's why we've never

1413
01:24:25,400 --> 01:24:28,160
Speaker 1: recommended them in non medical settings, because even if they

1414
01:24:28,200 --> 01:24:31,040
Speaker 1: work sort of conceptually in sort of a lab test,

1415
01:24:31,400 --> 01:24:34,200
Speaker 1: we never had confidence that people would use them correctly

1416
01:24:34,240 --> 01:24:37,439
Speaker 1: in a way that actually could be beneficial. And I

1417
01:24:37,479 --> 01:24:39,680
Speaker 1: think that based on the data that I'm seeing, you know,

1418
01:24:39,800 --> 01:24:42,479
Speaker 1: it's sort of you could go either way on whether

1419
01:24:42,520 --> 01:24:44,559
Speaker 1: they work in an idealized setting. There is a lot

1420
01:24:44,600 --> 01:24:46,839
Speaker 1: of lab data showing that they probably would be beneficial

1421
01:24:46,880 --> 01:24:50,240
Speaker 1: if they were used sort of perfectly, but in practice,

1422
01:24:50,640 --> 01:24:53,240
Speaker 1: I don't see any evidence that they've been beneficial at all.

1423
01:24:53,320 --> 01:24:56,360
Speaker 1: And you know, there there cherry picking that goes on,

1424
01:24:56,640 --> 01:24:58,799
Speaker 1: And the CDC had a couple of very low quality

1425
01:24:58,800 --> 01:25:02,240
Speaker 1: studies looking at Arizona in Kansas, where they essentially just

1426
01:25:02,320 --> 01:25:06,360
Speaker 1: cherry picked their end dates and their comparators and said, look,

1427
01:25:06,640 --> 01:25:10,280
Speaker 1: masks to the reason we saw a decline. And you know,

1428
01:25:10,320 --> 01:25:14,280
Speaker 1: if you look at kind of what's happened seasonally, you

1429
01:25:14,400 --> 01:25:18,040
Speaker 1: have essentially identical patterns in places with and without mask mandates,

1430
01:25:18,080 --> 01:25:21,080
Speaker 1: if they've got the same geography in the same sort

1431
01:25:21,120 --> 01:25:23,479
Speaker 1: of time of year. And so I don't think that

1432
01:25:23,600 --> 01:25:25,760
Speaker 1: they make a difference one way or the other. You

1433
01:25:25,800 --> 01:25:29,240
Speaker 1: could argue some have suggested they may actually be harmful.

1434
01:25:29,320 --> 01:25:31,960
Speaker 1: The reason that the normatic states have all avoided the

1435
01:25:32,040 --> 01:25:35,599
Speaker 1: mask mandates, you know, Sweden, Denmark, Norway and so forth,

1436
01:25:35,600 --> 01:25:38,280
Speaker 1: as they say, look, you know, the mask doesn't really

1437
01:25:38,280 --> 01:25:41,080
Speaker 1: do that much, especially the way a typical person handles it,

1438
01:25:41,200 --> 01:25:43,000
Speaker 1: is not well trained, the way as a surgeon would be,

1439
01:25:43,000 --> 01:25:45,320
Speaker 1: and so forth. But if you tell people that the

1440
01:25:45,360 --> 01:25:48,479
Speaker 1: mask protects you, then suddenly they're going to stand right

1441
01:25:48,479 --> 01:25:50,920
Speaker 1: next to each other for prolonged periods of time with

1442
01:25:51,160 --> 01:25:52,880
Speaker 1: masks on, and they're going to think they don't need

1443
01:25:52,960 --> 01:25:55,120
Speaker 1: to keep their distance. And oh and I'm sure people

1444
01:25:55,120 --> 01:25:56,880
Speaker 1: that have mild code they might go out of the

1445
01:25:56,960 --> 01:25:59,680
Speaker 1: house even if they're feeling sick because mask on and

1446
01:25:59,760 --> 01:26:01,760
Speaker 1: so the you know, a false belief that a mask

1447
01:26:01,800 --> 01:26:03,840
Speaker 1: will protect you might actually put you at more risk.

1448
01:26:03,920 --> 01:26:05,360
Speaker 1: This is what I've been saying, that you're gonna have

1449
01:26:05,360 --> 01:26:07,200
Speaker 1: people and say, well, maybe I got COVID, but my

1450
01:26:07,200 --> 01:26:09,360
Speaker 1: symptoms aren't that bad and I'm wearing a mask, so

1451
01:26:09,400 --> 01:26:11,360
Speaker 1: I'm good to go. It's like, no, this is a

1452
01:26:11,360 --> 01:26:14,240
Speaker 1: bad idea. There's a bad idea, but I'm I could

1453
01:26:14,240 --> 01:26:16,519
Speaker 1: guarantee that's been happening all over the country, all over

1454
01:26:16,560 --> 01:26:19,559
Speaker 1: the world. Phil, Look, I appreciate that you're willing to

1455
01:26:19,560 --> 01:26:21,400
Speaker 1: take take a look at the data here on the

1456
01:26:21,479 --> 01:26:24,360
Speaker 1: numbers and come to conclusions that you know aren't right

1457
01:26:24,400 --> 01:26:26,479
Speaker 1: in line with the consensus. I feel like this is

1458
01:26:27,240 --> 01:26:29,479
Speaker 1: the brainwashing that has gone on on this issue is

1459
01:26:29,640 --> 01:26:31,439
Speaker 1: unlike anything else I've ever seen in my life. I

1460
01:26:31,439 --> 01:26:33,439
Speaker 1: just want to give you the last word. Yeah, I mean,

1461
01:26:33,479 --> 01:26:35,479
Speaker 1: probably the most frightening thing of the past year, Buck

1462
01:26:35,520 --> 01:26:39,080
Speaker 1: has been the extent to which people not only accepted

1463
01:26:39,360 --> 01:26:42,840
Speaker 1: all of these various arbitrary government decrees, but demanded them

1464
01:26:42,840 --> 01:26:45,920
Speaker 1: and welcomed them and cheered them on. And I think

1465
01:26:45,960 --> 01:26:48,639
Speaker 1: the extent to which a large portion of the public

1466
01:26:49,800 --> 01:26:54,439
Speaker 1: supports the heavy handed government policy response is probably the

1467
01:26:54,439 --> 01:26:57,800
Speaker 1: most frightening takeaway of this whole thing. And you know,

1468
01:26:57,840 --> 01:26:59,760
Speaker 1: it means we could we could see this again every

1469
01:26:59,800 --> 01:27:02,960
Speaker 1: time there's a disease. So I am concerned about that,

1470
01:27:03,040 --> 01:27:06,639
Speaker 1: and I share your you know, I share your sentiments

1471
01:27:06,640 --> 01:27:10,040
Speaker 1: on that. Bill Kirpin, President of American Commitment. Phil really

1472
01:27:10,080 --> 01:27:21,920
Speaker 1: appreciate it. Talk to you soon, all right, Come on, liberty, truth,

1473
01:27:22,360 --> 01:27:26,240
Speaker 1: and great hair. You're listening to the best of the

1474
01:27:26,280 --> 01:27:32,280
Speaker 1: Butt Sexton show. Well, I think the party is uncertain

1475
01:27:32,280 --> 01:27:34,120
Speaker 1: of the course that we're going to take going forward.

1476
01:27:34,520 --> 01:27:37,439
Speaker 1: The principles that have long been the hallmark of my

1477
01:27:37,520 --> 01:27:40,040
Speaker 1: party are very much in question, which is, do we

1478
01:27:40,080 --> 01:27:42,920
Speaker 1: believe in balancing the budget? Do we believe in standing

1479
01:27:43,000 --> 01:27:46,080
Speaker 1: up to people like Kim Jong gun and Vladimir Putin?

1480
01:27:46,360 --> 01:27:49,599
Speaker 1: Are we committed to the principle that character counts? These

1481
01:27:49,640 --> 01:27:51,040
Speaker 1: are all things that I think we're going to have

1482
01:27:51,080 --> 01:27:53,000
Speaker 1: to decide over the coming years. I can tell you

1483
01:27:53,040 --> 01:27:55,080
Speaker 1: this much. Mid Romney's not going to be the leader

1484
01:27:55,080 --> 01:27:57,080
Speaker 1: of the Republican Party. That's for damn sure. Mid Romney

1485
01:27:57,120 --> 01:27:58,920
Speaker 1: is a Democrat now, I'm not going to forget that

1486
01:27:58,960 --> 01:28:02,519
Speaker 1: one anytime soon. He should be ashamed of his vote

1487
01:28:03,080 --> 01:28:06,920
Speaker 1: for the president to be removed during that sham impeachment.

1488
01:28:07,200 --> 01:28:11,040
Speaker 1: An impeachment about a president having a phone call where

1489
01:28:11,080 --> 01:28:14,160
Speaker 1: he asked about what we know is an entirely legitimate

1490
01:28:14,160 --> 01:28:19,120
Speaker 1: issue Biden family corruption, which is quite real. There's a

1491
01:28:19,160 --> 01:28:23,080
Speaker 1: federal investigation going on around it. You know, they may

1492
01:28:23,120 --> 01:28:25,799
Speaker 1: not like that the Trumpster was using some bare knockle

1493
01:28:25,840 --> 01:28:28,960
Speaker 1: politics here, but he was within his rights to do it.

1494
01:28:28,960 --> 01:28:31,559
Speaker 1: It was a fair ask. No action was taken on

1495
01:28:31,600 --> 01:28:34,799
Speaker 1: it anyway, and mid Romney voted to have the president

1496
01:28:34,880 --> 01:28:38,360
Speaker 1: removed from office based on that. Now, let's not ever

1497
01:28:38,400 --> 01:28:42,240
Speaker 1: forget this. There are a lot of these never trumpers.

1498
01:28:42,280 --> 01:28:45,479
Speaker 1: There are a lot of these stealth Democrats running around

1499
01:28:45,960 --> 01:28:47,280
Speaker 1: who were now all of a sudden going to be

1500
01:28:47,320 --> 01:28:51,640
Speaker 1: talking about how much they care about protecting life and

1501
01:28:51,680 --> 01:28:53,240
Speaker 1: the pro life movement. They're gonna be talking about the

1502
01:28:53,280 --> 01:28:56,840
Speaker 1: constitution and limited government and a strong national defense and

1503
01:28:56,920 --> 01:28:59,040
Speaker 1: all these things. They think they were going to turn

1504
01:28:59,080 --> 01:29:01,559
Speaker 1: the clock back to, you know, two thousand and six

1505
01:29:01,640 --> 01:29:06,160
Speaker 1: or something, and the Romneyite McCain, you know, mccinnian view

1506
01:29:07,120 --> 01:29:09,720
Speaker 1: of the Republican Party is going to be what we

1507
01:29:09,800 --> 01:29:12,120
Speaker 1: go back to. And I think that they're in for

1508
01:29:12,320 --> 01:29:15,920
Speaker 1: a brute awakening. It's not going to happen, and it

1509
01:29:15,960 --> 01:29:19,360
Speaker 1: should not happen. Buck took the day off, but don't worry.

1510
01:29:19,520 --> 01:29:22,640
Speaker 1: We've still got your Coverard. This is the best of

1511
01:29:22,640 --> 01:29:29,240
Speaker 1: the Buck Sexton Show right now for some good news,

1512
01:29:29,280 --> 01:29:33,160
Speaker 1: although in a way it's also troubling that it came

1513
01:29:33,160 --> 01:29:39,160
Speaker 1: to this. I told you that General Flynn was pardoned

1514
01:29:39,240 --> 01:29:41,240
Speaker 1: by the president. You'd no doubt I've seen or heard

1515
01:29:41,280 --> 01:29:43,559
Speaker 1: that a lot of places. It was pretty big news

1516
01:29:43,560 --> 01:29:48,400
Speaker 1: when it happened. And in response to that, you had

1517
01:29:48,560 --> 01:29:55,720
Speaker 1: Judge Emmett Sullivan produce a thirty four page opinion from

1518
01:29:55,760 --> 01:29:59,799
Speaker 1: the from the Federal Bench that shows you what finals

1519
01:30:00,000 --> 01:30:04,840
Speaker 1: stage Trump't derangement syndrome. Looks like. General Flynn is an

1520
01:30:04,840 --> 01:30:08,320
Speaker 1: innocent man. They ruined this guy, and they used the

1521
01:30:08,479 --> 01:30:11,760
Speaker 1: law to settle political scores against him. They ruined this guy,

1522
01:30:12,200 --> 01:30:17,920
Speaker 1: or have tried to based on lies, deception, the destruction

1523
01:30:18,240 --> 01:30:23,519
Speaker 1: of his constitutional rights. It was all politicized. It was

1524
01:30:23,560 --> 01:30:26,960
Speaker 1: a partisan hit. That's what they did to General Flynn.

1525
01:30:27,000 --> 01:30:32,559
Speaker 1: We all know it. This is very clear. But it

1526
01:30:32,600 --> 01:30:35,120
Speaker 1: took a pardon from the President of the United States

1527
01:30:35,360 --> 01:30:39,400
Speaker 1: to get a federal judge to stop going after him.

1528
01:30:40,200 --> 01:30:43,760
Speaker 1: And then he wrote a thirty four page thirty four

1529
01:30:43,840 --> 01:30:45,920
Speaker 1: page opinion from the bench where he talked about how

1530
01:30:45,960 --> 01:30:48,200
Speaker 1: Flynn is guilty and the administration shouldn't have done this,

1531
01:30:48,240 --> 01:30:50,120
Speaker 1: and this is you know, yes, they have the power,

1532
01:30:50,160 --> 01:30:52,479
Speaker 1: but this is a miscarriage of justice. Like a lunatic,

1533
01:30:52,960 --> 01:30:59,960
Speaker 1: he continued a prosecution by judge after the Department of Justice,

1534
01:31:00,439 --> 01:31:04,320
Speaker 1: which is the prosecutorial arm of the federal government, dropped

1535
01:31:04,360 --> 01:31:07,280
Speaker 1: the case and told him we never should have brought

1536
01:31:07,320 --> 01:31:10,760
Speaker 1: this case. But he thinks he's respecting the system by

1537
01:31:10,840 --> 01:31:13,840
Speaker 1: trashing it because he doesn't like a decision that they made.

1538
01:31:13,880 --> 01:31:17,040
Speaker 1: It was their decision. What is this guy doing? Yes,

1539
01:31:17,720 --> 01:31:20,479
Speaker 1: General Flynn is no longer in criminal jeopardy and he

1540
01:31:20,520 --> 01:31:24,720
Speaker 1: has been officially pardoned. But we also need to know

1541
01:31:24,760 --> 01:31:28,000
Speaker 1: that Judge Emmett Sullivan is a Trump deranged lunatic and

1542
01:31:28,080 --> 01:31:30,600
Speaker 1: he should be and I mean this removed from the

1543
01:31:30,640 --> 01:31:37,280
Speaker 1: federal bench and disbarred forthwith right away. That's what should happen.

1544
01:31:37,600 --> 01:31:40,599
Speaker 1: This guy is scary. Do you think if you're a

1545
01:31:40,640 --> 01:31:43,680
Speaker 1: person known in public life as a conservative, as a

1546
01:31:43,680 --> 01:31:45,160
Speaker 1: Trump supporter, do you think that you could get a

1547
01:31:45,160 --> 01:31:50,160
Speaker 1: fair trial and Judge Emmett Sullivan's courtroom. This guy's a

1548
01:31:50,160 --> 01:31:52,479
Speaker 1: federal circuit judge in DC. It's a pretty big deal.

1549
01:31:52,840 --> 01:31:55,040
Speaker 1: You think you get a fair trial? Absolutely not. This

1550
01:31:55,040 --> 01:31:58,559
Speaker 1: guy's a disgrace, a disgrace to the judiciary. But he

1551
01:31:58,600 --> 01:32:03,640
Speaker 1: shows you what we're up against. This was unheard of

1552
01:32:04,520 --> 01:32:07,640
Speaker 1: when the when the DJ says the judge doesn't get

1553
01:32:07,680 --> 01:32:09,400
Speaker 1: to pick somebody. Does a judge get to say, you

1554
01:32:09,439 --> 01:32:11,200
Speaker 1: know what, I don't like this guy. I'm gonna bring

1555
01:32:11,240 --> 01:32:13,920
Speaker 1: him into my courtroom and prosecute him. It's basically what

1556
01:32:13,960 --> 01:32:16,719
Speaker 1: they did to Judge Sullivan, I mean, to General Flynn,

1557
01:32:18,840 --> 01:32:24,040
Speaker 1: completely insane, but I'm very so so it's good that

1558
01:32:24,240 --> 01:32:26,479
Speaker 1: General Flynn is no longer in criminal jeopardy, but they

1559
01:32:27,200 --> 01:32:32,839
Speaker 1: dragged him through four years of this madness, four years

1560
01:32:33,160 --> 01:32:39,840
Speaker 1: of this insanity for what, for what? To make an

1561
01:32:39,840 --> 01:32:45,519
Speaker 1: example of him? And unfortunately that still stands. Do you

1562
01:32:45,560 --> 01:32:50,160
Speaker 1: think that now people might have second thoughts, especially to

1563
01:32:50,240 --> 01:32:55,360
Speaker 1: support Trump if he's leaving that Oval office in January,

1564
01:32:55,479 --> 01:32:59,200
Speaker 1: which I'll leave it to you. I'll leave the percentages

1565
01:32:59,240 --> 01:33:04,320
Speaker 1: to you, but certainly is a possibility. I think we

1566
01:33:04,320 --> 01:33:06,120
Speaker 1: could say it's a probability. I've been saying that for

1567
01:33:06,160 --> 01:33:09,960
Speaker 1: weeks if that happens. Do you think that people are

1568
01:33:09,960 --> 01:33:12,479
Speaker 1: going to be a little bit concerned about what could

1569
01:33:12,520 --> 01:33:16,559
Speaker 1: happen to them if they go forward and support Donald J. Trump?

1570
01:33:16,800 --> 01:33:19,720
Speaker 1: You think that may be something to consider her? As

1571
01:33:19,760 --> 01:33:22,600
Speaker 1: I do? As I do, I think there are going

1572
01:33:22,640 --> 01:33:25,679
Speaker 1: to be a lot of people who say, oh, what

1573
01:33:26,160 --> 01:33:30,760
Speaker 1: are my risks here? What's going to happen. Here is

1574
01:33:30,800 --> 01:33:36,040
Speaker 1: the Attorney General for New York State, Leticia James, who

1575
01:33:36,080 --> 01:33:43,600
Speaker 1: is straight up threatening like a mob boss, threatening prosecution

1576
01:33:44,400 --> 01:33:48,559
Speaker 1: of Donald Trump by her state when he leaves office.

1577
01:33:49,479 --> 01:33:57,240
Speaker 1: Play seven. It's important to understand he's pardoned from federal crimes,

1578
01:33:57,560 --> 01:34:00,960
Speaker 1: but he's not pardoned from state crimes. Year I introduced

1579
01:34:00,960 --> 01:34:03,800
Speaker 1: a bill in the state legislature which would close the

1580
01:34:03,840 --> 01:34:07,080
Speaker 1: pardon loophole so that individual such as the President of

1581
01:34:07,120 --> 01:34:10,720
Speaker 1: the United States would not evade justice. It's important that

1582
01:34:10,760 --> 01:34:14,400
Speaker 1: we have this check on presidential powers, and in the legislature,

1583
01:34:14,479 --> 01:34:17,320
Speaker 1: the state legislature. I'm so happy they passed that bill

1584
01:34:17,520 --> 01:34:19,040
Speaker 1: and it is now the law in the state of

1585
01:34:19,120 --> 01:34:23,360
Speaker 1: New York. President Trump cannot avoid justice in the great

1586
01:34:23,360 --> 01:34:25,760
Speaker 1: state of New York. People who asked me, should the

1587
01:34:25,800 --> 01:34:31,519
Speaker 1: president pardon himself? The answer is yes. What's what happens

1588
01:34:31,560 --> 01:34:33,760
Speaker 1: if he pardons, If he writes a preemptive pardon for

1589
01:34:33,840 --> 01:34:38,360
Speaker 1: himself and his family members, think about this? What what?

1590
01:34:38,360 --> 01:34:41,519
Speaker 1: What's the downside? Oh, everyone's gonna scream, Oh, look what

1591
01:34:41,560 --> 01:34:44,559
Speaker 1: he did, He's a criminal. They're saying that. Anyway, there's

1592
01:34:44,560 --> 01:34:46,680
Speaker 1: no fair minded person who looks at Trump and look

1593
01:34:46,840 --> 01:34:49,559
Speaker 1: looks at what's going on right now and says, yeah,

1594
01:34:49,640 --> 01:34:53,519
Speaker 1: he'll he'll be left alone in private life. They'll they'll

1595
01:34:53,520 --> 01:34:57,120
Speaker 1: back all. Don't let him go, you know, go lead

1596
01:34:57,400 --> 01:35:03,479
Speaker 1: a quiet family life with his kids and grandkids. And nope, no,

1597
01:35:03,880 --> 01:35:06,879
Speaker 1: we chanted lock her up. And then Hillary evaded justice

1598
01:35:06,960 --> 01:35:10,240
Speaker 1: even though she did break the law. They will go

1599
01:35:10,320 --> 01:35:13,320
Speaker 1: after Trump and they'll fabricate crimes. That's how they play

1600
01:35:13,360 --> 01:35:17,800
Speaker 1: the game. We play, you know, two hand touch. We're

1601
01:35:17,840 --> 01:35:22,920
Speaker 1: playing flag football here in politics, they are putting on

1602
01:35:23,080 --> 01:35:25,400
Speaker 1: brass knuckles and hitting us in the back of the

1603
01:35:25,439 --> 01:35:28,120
Speaker 1: head when the ref is not looking. That's how they

1604
01:35:28,160 --> 01:35:31,360
Speaker 1: play the game. Unfortunately, I think we're going to get

1605
01:35:31,400 --> 01:35:36,719
Speaker 1: another another lesson than that here very soon. They're gonna

1606
01:35:36,760 --> 01:35:40,479
Speaker 1: they're gonna go after people with prosecutions. They're gonna go

1607
01:35:40,520 --> 01:35:43,839
Speaker 1: after people with the irs. Oh but they talk of unity,

1608
01:35:44,200 --> 01:35:48,920
Speaker 1: remember that in their little self congratulatory delusion. We just

1609
01:35:48,960 --> 01:35:54,960
Speaker 1: want the American people to unify. But remember New York

1610
01:35:55,000 --> 01:35:57,639
Speaker 1: state charges. It is true, you can only pardon yourself

1611
01:35:57,640 --> 01:36:01,240
Speaker 1: from federal charges you got. You cannot clear yourself, even

1612
01:36:01,280 --> 01:36:06,040
Speaker 1: as president, from state charges. And nor could he clear

1613
01:36:06,040 --> 01:36:09,040
Speaker 1: his family members from that. And They've been talking about

1614
01:36:09,040 --> 01:36:11,080
Speaker 1: this for a long time now, you might say, buck,

1615
01:36:11,160 --> 01:36:15,200
Speaker 1: but can they really get him? I don't know. Can

1616
01:36:15,200 --> 01:36:18,960
Speaker 1: they fabricate a crime they fabricated Russia collusion. But even

1617
01:36:19,000 --> 01:36:22,040
Speaker 1: if they can't convict Trump or any of his family members,

1618
01:36:22,600 --> 01:36:26,439
Speaker 1: they can certainly investigate them, hound them, go after them,

1619
01:36:27,360 --> 01:36:31,160
Speaker 1: harass them. I think Ivanka Trump just what was it

1620
01:36:31,200 --> 01:36:35,200
Speaker 1: a week ago? Was was deposed having to do with

1621
01:36:35,640 --> 01:36:41,200
Speaker 1: inauguration spending? What? Yeah, do you think there'll be any?

1622
01:36:41,400 --> 01:36:42,760
Speaker 1: They ask is, do you think they'll actually be any

1623
01:36:42,800 --> 01:36:47,639
Speaker 1: federal criminal charges about the inauguration spending? No? No, not

1624
01:36:47,640 --> 01:36:49,680
Speaker 1: not against Ivanka, not against any of the drums. Not

1625
01:36:49,720 --> 01:36:53,120
Speaker 1: gonna happen. But why well, they've got somebody, the DJ

1626
01:36:53,720 --> 01:36:57,080
Speaker 1: wants to harass them. It's like it's auditioning for a bigger,

1627
01:36:57,120 --> 01:36:59,479
Speaker 1: better role on a Biden administration. This is what they do.

1628
01:37:01,160 --> 01:37:03,720
Speaker 1: It's it's appalling. Look Trump is and I want to

1629
01:37:03,720 --> 01:37:05,679
Speaker 1: be very clear, Trump is not giving up the fight.

1630
01:37:07,120 --> 01:37:09,479
Speaker 1: He's He's staying in this to the absolute very enemy.

1631
01:37:09,520 --> 01:37:13,120
Speaker 1: I think he's gonna fight this until the day that

1632
01:37:13,360 --> 01:37:17,439
Speaker 1: the moving trucks arrive. And God bless him. Why not?

1633
01:37:18,760 --> 01:37:22,639
Speaker 1: Why why pretend that everything is fine here, And why

1634
01:37:22,720 --> 01:37:26,000
Speaker 1: pretend that the Biden administration in any way that these

1635
01:37:26,040 --> 01:37:29,720
Speaker 1: Democrats have acted in good faith. They put forward this

1636
01:37:30,400 --> 01:37:34,880
Speaker 1: quasi senile clown, and we're all supposed to say, yeah,

1637
01:37:34,960 --> 01:37:37,599
Speaker 1: you guys have the best interests of the nation at heart. Sure,

1638
01:37:38,520 --> 01:37:41,120
Speaker 1: I don't think so. Not gonna happen with me. I mean,

1639
01:37:41,160 --> 01:37:45,080
Speaker 1: I can't speak for anybody else. Here's the president though,

1640
01:37:45,160 --> 01:37:47,439
Speaker 1: just just letting everybody know I'm doing a little bit

1641
01:37:47,439 --> 01:37:50,360
Speaker 1: of trolling Play eleven. The next administration will be the

1642
01:37:50,400 --> 01:37:52,880
Speaker 1: one ultimately that implements a lot of the distribution of

1643
01:37:52,880 --> 01:37:55,320
Speaker 1: this vaccine and will oversee much of the future of

1644
01:37:55,400 --> 01:37:58,840
Speaker 1: the way operation goes forward. Why not include members of

1645
01:37:58,840 --> 01:38:02,080
Speaker 1: the Bible Transition as part of this summit that you're

1646
01:38:02,080 --> 01:38:03,880
Speaker 1: hosting today. Well, we're gonna have to see who the

1647
01:38:03,920 --> 01:38:08,519
Speaker 1: next administration is because we won in those swing states

1648
01:38:08,600 --> 01:38:11,880
Speaker 1: and there was terrible things that went on. So we're

1649
01:38:11,880 --> 01:38:14,000
Speaker 1: gonna have to see who the next administration is. But

1650
01:38:14,360 --> 01:38:18,880
Speaker 1: whichever the next administration is will really benefit by what

1651
01:38:18,920 --> 01:38:22,879
Speaker 1: we've been able to do with this incredible science. The doctors,

1652
01:38:23,120 --> 01:38:26,280
Speaker 1: all of the people that came up, the lab technicians,

1653
01:38:25,760 --> 01:38:28,960
Speaker 1: the work that's been done is incredible and it will

1654
01:38:29,000 --> 01:38:32,320
Speaker 1: be incredible for the next administration, and hopefully the next

1655
01:38:32,360 --> 01:38:38,360
Speaker 1: administration will be the Trump administration. We'll see. But I

1656
01:38:38,479 --> 01:38:42,320
Speaker 1: like that he still goads them and he's showing them

1657
01:38:42,360 --> 01:38:45,400
Speaker 1: he's not backing down one bit. They think they can

1658
01:38:45,479 --> 01:38:50,400
Speaker 1: tame Trump as he's in these weeks of December before

1659
01:38:50,439 --> 01:38:54,599
Speaker 1: what could be a presidential transition, and they're wrong. He's

1660
01:38:54,640 --> 01:38:56,519
Speaker 1: not going to back down. He's not going to give up.

1661
01:38:57,439 --> 01:39:00,240
Speaker 1: And what you see now is more and more reason

1662
01:39:00,320 --> 01:39:02,680
Speaker 1: to continue on with that fight. Even even if we

1663
01:39:02,720 --> 01:39:07,000
Speaker 1: don't win. We stay unified and we show the other

1664
01:39:07,040 --> 01:39:12,880
Speaker 1: side that we got we got some backbone, we can

1665
01:39:12,920 --> 01:39:16,760
Speaker 1: dig in. We're willing to take this all the way,

1666
01:39:16,800 --> 01:39:24,120
Speaker 1: to take this to the map, Bucks off spreading freedom

1667
01:39:24,320 --> 01:39:27,599
Speaker 1: coast to coast. This is the best of the Buck

1668
01:39:27,680 --> 01:39:35,720
Speaker 1: Sexton show. You know, what the President isn't doing is

1669
01:39:35,760 --> 01:39:38,479
Speaker 1: telling anybody telling America's what they should do in the meantime,

1670
01:39:38,520 --> 01:39:42,080
Speaker 1: while we're waiting for this vaccine he distributed to general population,

1671
01:39:42,160 --> 01:39:45,320
Speaker 1: He's not communicating the message about what they should do

1672
01:39:45,439 --> 01:39:47,640
Speaker 1: to curve the spread of this. That's what Biden is

1673
01:39:47,680 --> 01:39:50,880
Speaker 1: talking about. Biden is talking you know, obviously darker terms,

1674
01:39:51,600 --> 01:39:54,719
Speaker 1: obviously not putting nearly as much emphasis on the vaccine,

1675
01:39:54,720 --> 01:39:57,599
Speaker 1: but talking about the near term, the next few hundred days,

1676
01:39:57,600 --> 01:39:59,599
Speaker 1: in which basically Americans still have to do a lot

1677
01:39:59,640 --> 01:40:04,040
Speaker 1: to pretend themselves until we can get that inoculation. That's right.

1678
01:40:04,120 --> 01:40:06,280
Speaker 1: This is what you're going to be told every day

1679
01:40:06,320 --> 01:40:11,240
Speaker 1: from now until the end of January. We haven't been

1680
01:40:11,320 --> 01:40:14,800
Speaker 1: told enough? Did do you feel like that we haven't

1681
01:40:14,840 --> 01:40:20,240
Speaker 1: been told enough about social distancing? Where a mask wash

1682
01:40:20,320 --> 01:40:25,160
Speaker 1: your hands? Here here's a question that I asked yesterday

1683
01:40:25,240 --> 01:40:30,200
Speaker 1: on Twitter, you know, before they banned me. But here's

1684
01:40:30,200 --> 01:40:33,519
Speaker 1: a question that they ask on Twitter, and that I

1685
01:40:33,560 --> 01:40:38,120
Speaker 1: asked on Twitter rather and I gotta tell you, as

1686
01:40:38,120 --> 01:40:41,679
Speaker 1: I look at it, it's amazing to me how unself

1687
01:40:41,680 --> 01:40:46,559
Speaker 1: aware of so many people are. I said about this

1688
01:40:47,640 --> 01:40:51,439
Speaker 1: COVID stuff that we're being told all the time, I

1689
01:40:51,479 --> 01:40:53,639
Speaker 1: asked the very real question, does anyone have an explanation

1690
01:40:53,680 --> 01:40:57,440
Speaker 1: of how it's possible? Mass compliance is the most widespread

1691
01:40:57,479 --> 01:40:59,920
Speaker 1: it has been all year in this country, But we

1692
01:41:00,080 --> 01:41:04,519
Speaker 1: now have more COVID cases than we did in March

1693
01:41:05,200 --> 01:41:10,000
Speaker 1: of twenty twenty and April, after months a viral spread

1694
01:41:10,600 --> 01:41:14,920
Speaker 1: with no mask mandates and almost no public masking at all,

1695
01:41:15,160 --> 01:41:18,439
Speaker 1: And I said, please answer me before Twitter bands this question,

1696
01:41:18,479 --> 01:41:20,439
Speaker 1: because as we know, social media companies are run by

1697
01:41:20,479 --> 01:41:25,800
Speaker 1: idiot libs and they can't think for themselves. Okay, so

1698
01:41:26,439 --> 01:41:28,760
Speaker 1: what is the answer to this. What's amazing to me,

1699
01:41:29,200 --> 01:41:31,800
Speaker 1: and this tells you so much, is how many people

1700
01:41:31,880 --> 01:41:35,919
Speaker 1: respond to this with because it's blah blah blah, you idiot,

1701
01:41:36,479 --> 01:41:40,200
Speaker 1: And there's a hundred different people with a hundred different

1702
01:41:40,520 --> 01:41:44,719
Speaker 1: reasons why I'm an idiot for not knowing what they're

1703
01:41:44,960 --> 01:41:50,160
Speaker 1: approved consensus left wing Fauci seal of approval answer is

1704
01:41:50,840 --> 01:41:55,680
Speaker 1: it's because people aren't masking up enough, really, so they

1705
01:41:55,680 --> 01:41:57,840
Speaker 1: didn't really think about the question very much, did they.

1706
01:41:58,120 --> 01:42:02,240
Speaker 1: We went from basically clean no masking in March and April,

1707
01:42:02,360 --> 01:42:05,320
Speaker 1: very very little, very intermittent here and there, and certainly

1708
01:42:05,320 --> 01:42:09,320
Speaker 1: no mandates. We went from that to eighty percent ninety

1709
01:42:09,320 --> 01:42:14,439
Speaker 1: percent mass compliance. And somehow cases and cases are higher.

1710
01:42:14,760 --> 01:42:17,720
Speaker 1: Some of them were saying because cases are not hospitalizations

1711
01:42:17,720 --> 01:42:22,360
Speaker 1: and death uitiot, Really, hospitalizations and deaths are also higher.

1712
01:42:23,520 --> 01:42:26,040
Speaker 1: But you just go, you go down this list because

1713
01:42:26,080 --> 01:42:29,040
Speaker 1: Europe figured it out and we didn't really Germany just said,

1714
01:42:29,080 --> 01:42:33,320
Speaker 1: it's all time one day death record from COVID Germany

1715
01:42:33,439 --> 01:42:36,200
Speaker 1: is a sixth the size of the United States. They

1716
01:42:36,200 --> 01:42:39,360
Speaker 1: had almost what was it, five hundred five hundred plus

1717
01:42:39,400 --> 01:42:41,400
Speaker 1: dead in one day, So it's you know, two or

1718
01:42:41,439 --> 01:42:44,360
Speaker 1: three thousand dead in one day in Germany if you

1719
01:42:44,400 --> 01:42:47,559
Speaker 1: made it a comparable to the US population. Oh, and

1720
01:42:47,600 --> 01:42:49,439
Speaker 1: I thought the Germans figured out the whole thing. I

1721
01:42:49,520 --> 01:42:51,679
Speaker 1: thought the Germans had the answer. It was those dumb

1722
01:42:51,720 --> 01:42:57,679
Speaker 1: Trump supporters. It is so dangerous and so wrong for

1723
01:42:57,760 --> 01:43:03,720
Speaker 1: people to think it's okay to blame disfavored political groups

1724
01:43:03,760 --> 01:43:07,160
Speaker 1: in the United States and group in this case half

1725
01:43:07,160 --> 01:43:10,680
Speaker 1: the country that supported Donald Trump. They're the reason for

1726
01:43:10,720 --> 01:43:14,320
Speaker 1: this virus. This is idiocy. There's no basis for this,

1727
01:43:14,560 --> 01:43:17,400
Speaker 1: and they can't answer these questions when you bring them up.

1728
01:43:18,400 --> 01:43:20,559
Speaker 1: And my favor, of course, as I've said, is it's

1729
01:43:20,600 --> 01:43:23,920
Speaker 1: so obvious, idiot. And then they tell me something and

1730
01:43:23,920 --> 01:43:26,800
Speaker 1: I say, well, your other liberal blue check friend over here,

1731
01:43:27,000 --> 01:43:30,559
Speaker 1: who believes in the science, has a different answer. So

1732
01:43:30,680 --> 01:43:32,400
Speaker 1: which one of you is correct? And if it's a

1733
01:43:32,520 --> 01:43:36,320
Speaker 1: hundred different things, maybe it's not obvious, is it. All

1734
01:43:36,360 --> 01:43:38,920
Speaker 1: you have to do is ask the questions. You don't

1735
01:43:38,960 --> 01:43:41,600
Speaker 1: even have to take stands right now, just ask the

1736
01:43:41,680 --> 01:43:44,680
Speaker 1: questions you're not supposed to. And when you get unsatisfactory

1737
01:43:44,720 --> 01:43:47,960
Speaker 1: answers and you're told shut up, peasant, do what you're told.

1738
01:43:48,240 --> 01:43:52,479
Speaker 1: You know exactly what you're up against. Anyone can observe

1739
01:43:52,880 --> 01:43:56,200
Speaker 1: that what the media, the left, the Libs have been

1740
01:43:56,240 --> 01:43:59,040
Speaker 1: saying was going to save us. We can control this,

1741
01:43:59,320 --> 01:44:04,080
Speaker 1: we can flat in the curve. Clearly that is not true.

1742
01:44:05,200 --> 01:44:10,120
Speaker 1: Clearly it is called an observation of reality all around us.

1743
01:44:10,800 --> 01:44:13,000
Speaker 1: I know people here in New York who are getting COVID.

1744
01:44:13,200 --> 01:44:15,360
Speaker 1: I have friends in LA who have just gotten COVID.

1745
01:44:15,560 --> 01:44:18,880
Speaker 1: I know people all across the country are seeing cases

1746
01:44:19,320 --> 01:44:25,360
Speaker 1: and hospitalizations spiking even more than they did the last

1747
01:44:25,800 --> 01:44:27,439
Speaker 1: at the beginning of the pandemic. So this is now

1748
01:44:27,960 --> 01:44:31,280
Speaker 1: called second wave that we're seeing, right, this is the

1749
01:44:31,320 --> 01:44:34,599
Speaker 1: second wave. But if we have gotten so much better

1750
01:44:34,600 --> 01:44:36,800
Speaker 1: with our ppe, we remember we have better treatments for

1751
01:44:36,840 --> 01:44:40,040
Speaker 1: this now. So somehow the virus has spread more and

1752
01:44:40,080 --> 01:44:43,160
Speaker 1: it's spread more efficiently. Okay, maybe there's a mutation that's

1753
01:44:43,560 --> 01:44:45,519
Speaker 1: led to the increased spread. We don't know. That's a

1754
01:44:45,600 --> 01:44:48,600
Speaker 1: real answer. I could handle that as an answer. But

1755
01:44:48,760 --> 01:44:51,679
Speaker 1: where a mask, like what Cuomo says all the time.

1756
01:44:52,040 --> 01:44:55,720
Speaker 1: That's not a real answer. That's not me saying that

1757
01:44:55,760 --> 01:44:58,200
Speaker 1: it doesn't work at all. I'm just saying the reason

1758
01:44:58,240 --> 01:45:00,400
Speaker 1: that we have this huge spike in cases is not

1759
01:45:00,520 --> 01:45:04,559
Speaker 1: lack of mass compliance. That is madness. People are masking

1760
01:45:04,640 --> 01:45:06,840
Speaker 1: up all over the place. I know people who are

1761
01:45:07,800 --> 01:45:13,639
Speaker 1: very mask conscientious. They're sick or they've gotten sick. So

1762
01:45:14,040 --> 01:45:16,360
Speaker 1: what are they Is it their fault? Oh no, it's

1763
01:45:16,360 --> 01:45:20,800
Speaker 1: only a Republicans. When a Republican gets COVID, it's his fault. Right,

1764
01:45:20,880 --> 01:45:24,200
Speaker 1: So when Rudy Giuliani gets COVID nineteen, the media says, see,

1765
01:45:24,280 --> 01:45:27,560
Speaker 1: he's reckless. But when Jared Polis, the governor of Colorado,

1766
01:45:27,760 --> 01:45:30,120
Speaker 1: big mask maniac, when he gets it and his wife

1767
01:45:30,160 --> 01:45:32,639
Speaker 1: gets it, it's oh, gosh, it's a virus. I guess

1768
01:45:32,640 --> 01:45:36,040
Speaker 1: it can really spread. Gosh, this is real contagious. Is

1769
01:45:36,080 --> 01:45:39,040
Speaker 1: this is tearing us apart? We should be unified against this,

1770
01:45:39,720 --> 01:45:41,920
Speaker 1: We should be united as a country. This isn't This

1771
01:45:42,000 --> 01:45:46,720
Speaker 1: is an external enemy that is mixing in in all

1772
01:45:46,760 --> 01:45:51,080
Speaker 1: over our society, this virus. And instead people have used

1773
01:45:51,080 --> 01:45:53,719
Speaker 1: this as a wedge. They've used this for further division

1774
01:45:54,400 --> 01:45:57,839
Speaker 1: and they refuse to deal with what we can all

1775
01:45:57,880 --> 01:46:03,479
Speaker 1: see and observe they are lying to you, and just

1776
01:46:03,680 --> 01:46:07,200
Speaker 1: asking them to explain themselves results in them saying that

1777
01:46:07,479 --> 01:46:08,960
Speaker 1: you are a liar.