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Speaker 1: You are entering the freedom hunch. That much anticipated and

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Speaker 1: long delayed study out of Denmark on masks is out

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Speaker 1: with some surprising results at least to some more votes

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Speaker 1: turning up for Trump in Georgia, Michigan. What's going on here?

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Speaker 1: Plus the tech tyrants exposed once again and more insane

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Speaker 1: Turkey Day Guideline buck Sexton decoding the news and disseminating

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Speaker 1: information with actionable intelligence, Make no mistake a great American again.

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Speaker 1: This is the buck Sexton Show. Plus CIA analysts can

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Speaker 1: speak to three hours without a phone call. Try doing

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Speaker 1: that sometimes. No Welcome friends to the buck Sexton Show.

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Speaker 1: Great to have you here with me. As always, I

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Speaker 1: know we're going to dive together into the latest over

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Speaker 1: these election results that continue to make their way through

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Speaker 1: the courts. We're going to spend time all that, but

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Speaker 1: I'm sorry, I gotta start with something else today. A

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Speaker 1: study that has been waited, waited for by a lot

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Speaker 1: of folks. It's been talked about, delayed for a few months,

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Speaker 1: about whether or not wearing a mask wear a mask.

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Speaker 1: Cuomo says about whether or not wearing a mask is

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Speaker 1: effective protection for the wearer. Now, we have to be

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Speaker 1: very specific and how we talk about this and how

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Speaker 1: we discussed this, because what they're going to do is

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Speaker 1: look for any lack of precision. What the mask mandate

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Speaker 1: maniacs will do is say, oh, but did you see

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Speaker 1: the the point two fives that that's not what it says.

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Speaker 1: You said that it doesn't protect, and it does protect,

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Speaker 1: it protects by Okay. So I'm gonna try to be

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Speaker 1: as precise as possible because I read every word of

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Speaker 1: this Danish study and there's much broader themes here, friends,

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Speaker 1: than even just whether or not these mask mandates are

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Speaker 1: good public health policy. And I understand that there are

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Speaker 1: a lot of people all over the world, but particularly

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Speaker 1: here in the United States, a lot of people who

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Speaker 1: think they are really, really smart, and everybody else who

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Speaker 1: questions them is so so dumb, not even that they're wrong,

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Speaker 1: but that they're too stupid. They're contemptible in their ignorance,

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Speaker 1: So they're not even worth engaging on these issues. That's

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Speaker 1: the attitude. And they're going to have a heck of

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Speaker 1: a time explaining what's going on here, because now we

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Speaker 1: actually have some data masks prevent people from transmitting the

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Speaker 1: coronavirus to others. According to scientists in this New York

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Speaker 1: Times right up of the piece. But a new trial

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Speaker 1: failed to document protection from the virus among the wearers.

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Speaker 1: Now let's look at this exactly Like I said, this

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Speaker 1: is important and this goes to much even bigger themes

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Speaker 1: than coronavirus restrictions. So that's why I find this so important.

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Speaker 1: This is such a lesson, such a cautionary tale. But

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Speaker 1: you have researchers in Denmark that they reported it in

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Speaker 1: Annals of Science I believe is the journal that it

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Speaker 1: was published in. So this is peer review. I'm sorry,

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Speaker 1: Annals of Internal Medicine, pardon me, Annals of Internal Medicine.

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Speaker 1: And this is peer reviewed. And this is involving three

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Speaker 1: thousand and thirty participants randomly assigned to wear masks two

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Speaker 1: nine ninety four assigned to the control group. This is

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Speaker 1: act schuel science. Look at results based upon with a

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Speaker 1: control group, based upon an experiment, show the data and

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Speaker 1: use the scientific method, and then come to a conclusion.

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Speaker 1: And then understand that this can be tried again and

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Speaker 1: again and replicated. See if we get the same results.

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Speaker 1: Try to control for all variables. This is science, the

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Speaker 1: same way the vaccine. The amazing vaccines that are just

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Speaker 1: on the precipice of approval, and that we're pushed along, yes,

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Speaker 1: by absolutely brilliant scientists, people that can do stuff that

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Speaker 1: you and I would not be able to do with

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Speaker 1: you all the money in the world. Right, these guys

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Speaker 1: have real and gals have real expertise and knowledge. They've

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Speaker 1: made these vaccines and they hopefully will bring about this.

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Speaker 1: It's not just a pandemic from COVID, but there's also

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Speaker 1: on top of that, a pandemic of fear, anxiety, government overreach.

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Speaker 1: So much has come along with this, as I've been

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Speaker 1: saying would be the case. But they did this the

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Speaker 1: right way. They did a real experiment. Why haven't we

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Speaker 1: seen more of these? By the way, didn't you ask

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Speaker 1: that question? We're making enormously consequential public policy decisions. We're

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Speaker 1: inflicting upon people the constant psychological and physical irritation and

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Speaker 1: trauma of wearing a mask outside, wearing a mask on

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Speaker 1: the treadwill wearing a mask indoors now in your own

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Speaker 1: a home. That's the latest guidance in Pennsylvania. Cases going

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Speaker 1: up all over the country. Mask wearing higher rates of

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Speaker 1: adoption than ever before in this country. You're not supposed

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Speaker 1: to ask any questions about this, do it or else?

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Speaker 1: Is now the attitude? Okay, well, let's look at what

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Speaker 1: the actual science tells us. Listen to the scientists. They say, Okay, well,

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Speaker 1: I read this entire study. Doesn't really take all that long.

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Speaker 1: Actually it's pretty easy read. And you can see it

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Speaker 1: online and if you will, post a link to it

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Speaker 1: at bucksexton dot com and it's linked in some of

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Speaker 1: my tweets which are also posted there. So go to

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Speaker 1: Bucksexton dot com and here's what it tells you. And

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Speaker 1: I think it's very important that mask wearing. According to

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Speaker 1: the data. Here's how the New York Times quotes it.

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Speaker 1: The study did not contradict growing evidence at mask can

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Speaker 1: prevent transmission of the virus from wear to others. But

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Speaker 1: the conclusion is at odds with the view that masks

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Speaker 1: also protect the wearers, which was a position just endorsed

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Speaker 1: last week by the Centers for Disease Control and Prevention. Okay,

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Speaker 1: they're trying to be very gentle with their audience. Oh no,

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Speaker 1: it's still true that a mask protects you, as in

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Speaker 1: from me. But my wearing of a mask, if I'd

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Speaker 1: go into a room with a mask on. Okay, according

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Speaker 1: to this study, and there is a person who is

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Speaker 1: COVID infectious in that room, they can prove no benefit

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Speaker 1: whatsoever for my wearing of the mask as a protection

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Speaker 1: for me. None. And the way that they did this study,

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Speaker 1: so that everybody's very clear, is they had, like I said,

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Speaker 1: a few thousand participants on each side, and the people

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Speaker 1: that were told to wear a mask, the participants wearing

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Speaker 1: a mask, forty two participants recommended mask wearing got COVID,

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Speaker 1: fifty three without mask wearing got COVID. So it's one

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Speaker 1: point eight percent versus two point one percent difference, which

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Speaker 1: is statistically for the purposes of this experiment completely insignificant,

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Speaker 1: means nothing effectively, you can tell no difference whatsoever. So

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Speaker 1: you have thousands of people told wear a mask every day.

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Speaker 1: Now I know what they're going to say, Buck, but

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Speaker 1: their mask usage wasn't perfect, right, or some of them

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Speaker 1: did it all the time. That it's sometimes okay, But

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Speaker 1: if masks were really effective, with about three thousand people

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Speaker 1: who are at least sometimes wearing masks, and you've got

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Speaker 1: about three thousand or so people who are never ever

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Speaker 1: wearing masks, right, Like they're like, not, they're in the

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Speaker 1: non mask group. Don't you think the difference should be

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Speaker 1: more than Oh? What is it? Point three percent? Is

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Speaker 1: that really what we're going for here? And keep in mind,

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Speaker 1: no one even thinks that that's a hard and fast number.

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Speaker 1: It's effectively zero. But even if if there was a

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Speaker 1: point three percent reduction in COVID nineteen for a mask wearing,

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Speaker 1: do you think it's worth it? Are you going to

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Speaker 1: continue to wear a mask point three percent? What have

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Speaker 1: I've been saying to you, Maybe it's five percent, maybe

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Speaker 1: it's ten percent. I've been saying I think it might

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Speaker 1: maybe does something. This says it does even less. Ah.

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Speaker 1: Now we get to the chorus of people, I'm so smart.

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Speaker 1: I read the study. You haven't read it. No, I've

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Speaker 1: read it. I've read it several times. It's not hard

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Speaker 1: to read. What they'll say is, ah, but this tells

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Speaker 1: us you need even more mask wearing because it's not

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Speaker 1: about you, it's about protecting people from you. And this

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Speaker 1: is what the scientists all still agree on. That's what

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Speaker 1: they'll tell you a little problem with that, though, First problem,

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Speaker 1: where is the study that proves that? Where is the

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Speaker 1: study that shows that I asked the question. I wanted it.

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Speaker 1: I don't want to hear but ah, but dadah blah

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Speaker 1: blah blah. You know, people just mumbling about all the

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Speaker 1: smart people that say no, no, where is the show

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Speaker 1: me the data, show me the evidence to prove that.

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Speaker 1: Even bigger problem for that argument here, remember people, ultimately,

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Speaker 1: at this point, you have people that have their reputations

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Speaker 1: on the line for being super smart experts, and you

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Speaker 1: also people who don't want to believe that they're sheep

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Speaker 1: and been doing You know, look, I've been wearing a

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Speaker 1: mask when I go into stores and stuff because I

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Speaker 1: have no choice, right they make you otherwise, I can't

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Speaker 1: buy groceries, I can't go anywhere in New York City.

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Speaker 1: So you know this is a mandate, it's not a

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Speaker 1: But there are people that are firm believers, and they

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Speaker 1: really look down on other people even who question this.

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Speaker 1: They look down on them that they think they are

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Speaker 1: less than that they're dumb, they're reckless, And this was

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Speaker 1: a huge part of the Trump is responsible for all

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Speaker 1: the COVID Don't forget that too, because Trump wasn't a

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Speaker 1: mask worshiper from day one, which not even fouc you was.

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Speaker 1: We can get into that. But because people that support Trump,

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Speaker 1: just generally, I think, have a more individualistic view of

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Speaker 1: life and of what's important as an American and individual liberty,

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Speaker 1: and they don't like being told by the government where

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Speaker 1: this uncomfortable, annoying restriction on your face all the time,

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Speaker 1: and forget about the separation and really the dehumanizing aspects

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Speaker 1: of this. And you know, I've hated this all along.

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Speaker 1: I've hated masks, all right, and now they tell us, oh,

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Speaker 1: but it's about protecting other people from you, which is

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Speaker 1: so interesting because, as even the New York Times had

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Speaker 1: to point out, they had to beat us too it

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Speaker 1: because otherwise it looks like they're trying to hide it.

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Speaker 1: The CDC recently said masks are very effective at protecting

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Speaker 1: you when you wear it, you wear a mask, it

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Speaker 1: blocks the aerosols, it blocks the particles. That was what

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Speaker 1: the CDC was saying a week ago. The Centers for

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Speaker 1: Disease Control, now we have a study out that says

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Speaker 1: that there's no way to prove that at all, and

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Speaker 1: if anything, it looks like it is just a complete waste.

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Speaker 1: People are going to point to and say, no, but

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Speaker 1: that's not true. It says they could. And this is

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Speaker 1: when they do the deep dive statistical analysis of what

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Speaker 1: all the data means. It could reduce transmission buy up

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Speaker 1: to forty percent. Yeah, the same study says it could

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Speaker 1: also increase transmission to wear a mask because if people

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Speaker 1: touching it sself up to twenty percent, so you got

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Speaker 1: to maybe up to forty maybe up to twenty. That

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Speaker 1: means they don't know. But well, let's focus on what

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Speaker 1: we do know. Let's use our common sense. Let's not

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Speaker 1: be shouted down and condescended to by the mask wearing

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Speaker 1: chorus all the time. Here you had about three thousand

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Speaker 1: people told to wear masks, given masks and they knew

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Speaker 1: they were a part of a study about mask wearing,

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Speaker 1: and three thousand other people who I'm sure, we're happy

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Speaker 1: to sign up for this, and now we're not wearing

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Speaker 1: a mask. About the same number of people got infected

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Speaker 1: in both groups. Okay, Now they also will say, oh buck,

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Speaker 1: but at that time in Denmark there wasn't a lot

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Speaker 1: of mask you know, adopt mask wearing wasn't really that widespread.

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Speaker 1: They can look at all the flaws and they can

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Speaker 1: try to keep justifying their public policy as much as

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Speaker 1: they want. The point here is that the evidence for

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Speaker 1: a mask protecting you from the inhalation of Arasoli's COVID

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Speaker 1: nineteen virus, the best study we have this year, shows

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Speaker 1: that there is no benefit to you of wearing that mask.

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Speaker 1: Now we have to move to the secondary question, or

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Speaker 1: the next question, which is is there a benefit to

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Speaker 1: other people if you wear a mask. We are told

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Speaker 1: to take that on the advice. We're told to take

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Speaker 1: that based on the expertise of the scientific consensus. And

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Speaker 1: if you question it, you're a bad person, You're a moron.

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Speaker 1: There's no there's no reflection, there's no humility in this

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Speaker 1: conversation whatsoever from that art from that group. They pretend

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Speaker 1: that this never have doesn't matter what the evidence has

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Speaker 1: showed in this one. We're still right. We're just right

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Speaker 1: in a different way. Sure. Why was the CDC wrong

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Speaker 1: about masks as a protective mechanism for you from infection

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Speaker 1: a week ago? And why was the CDC's initial guidance

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Speaker 1: now nine months months ago? Why was their initial guidance

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Speaker 1: that mask wearing is not a good policy and it

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Speaker 1: is not effective at all? What has changed between now

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Speaker 1: and then? Use your own common sense. Look at what

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Speaker 1: is being proofd What have I said that it's not true?

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Speaker 1: Find one thing. Everything I am telling you is a

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Speaker 1: matter of either historical record or of the data, and

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Speaker 1: of fact. But people don't want to believe that they

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Speaker 1: have been fooled, that they are easily led by the consensus,

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Speaker 1: and on this one, on this story, that masks are

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Speaker 1: a protective shield for you from the virus in the

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Speaker 1: air around you, from people using the people that have

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Speaker 1: been saying that based on the science are wrong. They

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Speaker 1: are wrong. Now they they can do a lot of

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Speaker 1: dancing around. Oh but maybe it's inconclusive, and there's other things.

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Speaker 1: Why do we think this Danish study was delayed for months?

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Speaker 1: You don't think that there was a lot of wrangling

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Speaker 1: around this to try to avoid releasing it. People don't

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Speaker 1: like looking dumb, even if it's just And maybe they

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Speaker 1: are right. Maybe that does protect from aerosolis virus that

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Speaker 1: goes to somebody else, or if you wear the mask right,

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Speaker 1: maybe it contains more of your very That's possible. I

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Speaker 1: don't know, But I do know that the other thing

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Speaker 1: they were telling us until last week, and that they

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Speaker 1: would have made fun of you for bringing up in public.

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Speaker 1: They were wrong about that based on what we know now.

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Speaker 1: And here's the other part of it. We learn more

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Speaker 1: in time. Science is about testing and re testing assumptions,

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Speaker 1: data fact These are about what is true, and sometimes

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Speaker 1: we think something's true, we find out that it's not.

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Speaker 1: That's a part of being an intellectually honest and worthwhile entity.

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Speaker 1: But you think the control freaks out there or even

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Speaker 1: are are going to give that a moment's attention. Of

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Speaker 1: course not. They were just wrong on this one, and

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Speaker 1: you know what they're moving on to. We're right about

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Speaker 1: the other thing. Shut up, wear your mask. Keep that

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Speaker 1: one going until we see what the studies tell us

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Speaker 1: about that. You're in the freedom This is the Buck

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Speaker 1: Sexton Show podcast. Well, I say I can't enforce the

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Speaker 1: order because I think it's unconstitutional. And in order to

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Speaker 1: explain why it's unconstitutional, I just have to take a

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Speaker 1: second brand and explain what he can do constitution That

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Speaker 1: Bill of Rights allows a balancing act for the safety

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Speaker 1: of the society and limiting individual's liberty. So let me

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Speaker 1: give it the easiest example. You can't yell fire in

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Speaker 1: a crowded movie theater if there's not a fire and

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Speaker 1: so the government can limit your First Amendment freedom of

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Speaker 1: speech rights. But we under the case law and under

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Speaker 1: the Constitution, the governor absolutely has a right to limit

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Speaker 1: how many people can go to a bar or a restaurant.

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Speaker 1: We're in face masks in public buildings and private businesses.

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Speaker 1: He can also limit what time them must close. But

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Speaker 1: under the Constitution the order is very vague and it's

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Speaker 1: ten or less people is the most you can have

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Speaker 1: in your private residence. Well, I don't think that the

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Speaker 1: Constitution allows for the infringement of your own the number

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Speaker 1: of people have in your own home. So I started

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Speaker 1: that position. So he has authority to do a lot,

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Speaker 1: but not to tell us as law enforcement, to go

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Speaker 1: into people's house and count who's there. That's New York.

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Speaker 1: New York's Fulton County Sheriff Richard Giardino on the just

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Speaker 1: monstrously tyrannical and stupid Cuomo mandate about how many people

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Speaker 1: are allowed in your home over Thanksgiving. You know, we

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Speaker 1: can fight back about their pseudoscience, We can fight back

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Speaker 1: about the lack of honesty around all these issues. And

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Speaker 1: remember it was all part of getting everybody freaked out.

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Speaker 1: And oh my god, Trump didn't do enough. We have

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Speaker 1: to get rid of Trump and all this stuff. We

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Speaker 1: can fight back against these things, or we can continue

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Speaker 1: to be told how many people are in our homes

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Speaker 1: for Thanksgiving. And don't think it just ends when the

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Speaker 1: vaccine comes out. We're gonna have to have months and

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Speaker 1: months and months of basically no new cases. If you

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Speaker 1: allow the Democrats and the Biden, the Biden apparatus, and

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Speaker 1: the people in the media to determine when it's safe

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Speaker 1: for you to be, maybe maybe by next Christmas they'll

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Speaker 1: stop telling you what to do. You want to waste

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Speaker 1: all that time? Do you think that's very you think

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Speaker 1: that's smart? This whole thing is out. It's outrageous telling

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Speaker 1: you how many people are allowed on your private home

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Speaker 1: because of an aerosolized virus. What do we think tyranny

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Speaker 1: in America would look like if not this? Thanks for

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Speaker 1: listening to the buses and show podcasts. Remember to subscribe

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Speaker 1: on Apple podcasts, the iHeartRadio app, or wherever you get

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Speaker 1: your podcasts. Do you think there will be any humility

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Speaker 1: from the various public health experts who have been going

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Speaker 1: on TV and have been claiming that anyone who even

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Speaker 1: questions the constantly shifting medical consensus about how to do

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Speaker 1: with COVID nineteen, and that's a fact. It has been

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Speaker 1: constantly shifting. And they say, oh, it's because we have

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Speaker 1: new data. And usually the new data is we can

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Speaker 1: see that what they were telling us to do didn't work,

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Speaker 1: so they tell us to do something else based on

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Speaker 1: the data. But it's never an admission that the previous

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Speaker 1: declarations they made were incorrect. Now that part of it

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Speaker 1: does not get any attention whatsoever, that part of it

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Speaker 1: doesn't really matter. No, it's all still about bashing Trump.

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Speaker 1: It's Trump supporters fault. You see that COVID is still spreading.

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Speaker 1: That's what the left wants you to believe. It's Trump

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Speaker 1: supporters fault. That there have been huge spikes in European

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Speaker 1: countries that have mass compliance numbers that are very high,

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Speaker 1: that have gone through a series of different lockdowns. You see,

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Speaker 1: it's just those evil Trumpsters that are behind this whole thing.

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Speaker 1: It's really the Trump virus, that's what they want you

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Speaker 1: to believe. It's not the China virus, the Trump virus.

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Speaker 1: These people are insane. But they also believe that the

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Speaker 1: president worked with the Russians distinal election from Hillary Clinton.

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Speaker 1: They also think that that's true. So what can you

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Speaker 1: say about that? But here's an example of the kind

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Speaker 1: of derangement, derangement that you will see on television. This

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Speaker 1: guy wanders into he's an emergency room physician. He's wandering

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Speaker 1: into terrorism analysis, all kinds of stuff, all kinds of stuff.

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Speaker 1: All would who's find uh you know a guy with

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Speaker 1: an MD who's a huge lib and all of a sudden,

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Speaker 1: the person's on TV telling everybody about who, who you

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Speaker 1: should listen to, who you shouldn't do, the whole the

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Speaker 1: whole thing. It's it's it's outrageous. Um. This guy's a leftist.

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Speaker 1: By the way, this guy's an You go online, you

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Speaker 1: check him out. He's a leftist. But this is what

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Speaker 1: you get on CNN as a medical expert. Play whatever

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Speaker 1: that is? Fourteen. No, they need to can him. Um.

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Speaker 1: I mean, one of the things I can't wait for

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Speaker 1: when when the inauguration happens, is that he'll be gone.

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Speaker 1: He's a radiologists, which is great, has nothing to do

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Speaker 1: with public health. He probably hasn't taken care of a

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Speaker 1: patient in thirty some years. You know, he's a right

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Speaker 1: wing ideologue who is going after my governor who's doing

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Speaker 1: everything she can despite a hostile state legislature and Supreme

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Speaker 1: Court and our state who has taken away powers. They're

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Speaker 1: doing everything they can. We know, when the President tweeted

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Speaker 1: liberate Michigan after that, we had a plot to kidnappin,

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Speaker 1: murder Governor Whitmer and basically take down the whole state government.

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Speaker 1: You know. So now he's tweeting rise up. I mean,

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Speaker 1: there's not much difference between liberate and rise up and

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Speaker 1: whatever he claims to say. These are these are called

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Speaker 1: to arms for people in our state, one of the

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Speaker 1: worst states for domestic terrorism. So you know, I'm grateful

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Speaker 1: that Governor Whitmer has said, listen, she's not going to

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Speaker 1: worry about her political fortunes, about reelection or about you know,

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Speaker 1: any kind of attempts against her. She's going to do

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Speaker 1: what's right and try to protect us. And she is

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Speaker 1: so much here that is misleading, dumb, wrong. But you know,

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Speaker 1: this guy just find a doctor somewhere. This guy's a

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Speaker 1: doctor in Michigan. And so now we all have to

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Speaker 1: believe everything that he says about everything, including terrorism. I've

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Speaker 1: actually worked professionally in terrorism. This guy doesn't know what

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Speaker 1: the hell he's talking about. But he's allowed to have

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Speaker 1: his opinion, right now, that's fine. The whole thing about

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Speaker 1: the terrorist plot against Governor Whitman, you know what they

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Speaker 1: always leave out of that. Now, the same right wing

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Speaker 1: pro Trump terrorists that they've they've rounded up and said,

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Speaker 1: we're plotting all the stuff. First of all, their plots

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Speaker 1: were absurd. They were never going to come to fruition.

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Speaker 1: Nothing was ever really going to happen. This was what

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Speaker 1: often this is what often occurs when you've got an informant,

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Speaker 1: an FBI informant, placed among people who gets them talking,

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Speaker 1: a lot of talking, a lot of idiocy, and yeah,

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Speaker 1: they're bad people and I don't care if they're gonna

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Speaker 1: end up getting in trouble here. But the point is

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Speaker 1: that they weren't really, you know, at the actionable phase

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Speaker 1: of any of this at all. And they also wanted

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Speaker 1: to want One of them wanted to, as this is

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Speaker 1: based on the FBI affidavit in the court, FBI scorn

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Speaker 1: statement in the court, one of the plotters wanted to

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Speaker 1: assassinate President Trump. So these are the pro Trump people

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Speaker 1: that are also planning a lethal plot against the president.

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Speaker 1: That's that's what they leave out of this because that

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Speaker 1: didn't get out into the court record for about a week.

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Speaker 1: But it was good for Governor Whitmer, who's a moron,

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Speaker 1: to go around saying, oh, gosh, you know that President's

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Speaker 1: mean people were all plotting all the mean stuff against me.

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Speaker 1: Oh yeah, so we heard all that. But they leave

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Speaker 1: that out. That these people were psychopaths and they hated

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Speaker 1: the president too, and the stuff they were talking about was,

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Speaker 1: while violent and evil, also nowhere near actually ever happening.

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Speaker 1: But nonetheless Sky's waxing philosophal But that and trying to

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Speaker 1: tie Scott Atlas is inciting terrorism, which is what happens

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Speaker 1: when you are opposed to lockdowns. If people were having

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Speaker 1: a real conversation about this, if people were willing to

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Speaker 1: look at what's true and what we've seen and what's real,

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Speaker 1: they wouldn't have to resort to such disgraceful smears. Also,

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Speaker 1: I mean putting down doctor Atlas for having a background

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Speaker 1: in radiology. Radiology. Radiologists are mds. They die nos disease,

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Speaker 1: including through using X rays and MRIs, and they are

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Speaker 1: part of the medical profession. And he was a head

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Speaker 1: of I think it was neuro radiology at Stanford Medical

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Speaker 1: School for many years. So yeah, no, he doesn't know

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Speaker 1: anything about public health though they guy doesn't know anything

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Speaker 1: about the medical system at all. No, he's not on

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Speaker 1: a par with a guy who's in er doc in

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Speaker 1: some hospital in Michigan. Yeah, no, it has no idea.

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Speaker 1: I mean, really, we're going to get into a credential battle.

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Speaker 1: Let's be honest about what we're talking about. But even

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Speaker 1: beyond that, they hate they hate doctor Atlas. And yet

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Speaker 1: what is he saying that the ten person mandates on Thanksgiving?

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Speaker 1: Or absurd? And people need to stop with this. It

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Speaker 1: is absurd. And if you don't think it's absurd, you're

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Speaker 1: a weak willed, weak minded person. And if you don't

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Speaker 1: think it's absurd, you should just look at what's going

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Speaker 1: on with the people who put these policies in place

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Speaker 1: and then break them and know that they'll get away

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Speaker 1: with it, I hope. But they're so concerned about public health.

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Speaker 1: Somebody who tells you do what I say, or else

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Speaker 1: people will die, and then does the thing that they

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Speaker 1: tell you not to do or else people will die

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Speaker 1: is an unserious hypocrite who clearly does not really believe

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Speaker 1: that things they are telling you or they're actually a monster,

427
00:25:19,200 --> 00:25:22,240
Speaker 1: but they don't really think you're going to kill people anymore.

428
00:25:22,320 --> 00:25:24,960
Speaker 1: So that if you are out living your life and

429
00:25:25,359 --> 00:25:27,440
Speaker 1: you know you could pass any number of diseases to

430
00:25:27,520 --> 00:25:31,160
Speaker 1: somebody without knowing it. I mean, we can talk about

431
00:25:31,160 --> 00:25:33,440
Speaker 1: the flu, but that I know that sets everybody off,

432
00:25:33,440 --> 00:25:38,439
Speaker 1: That gets them all upset. But this is where we are, friends.

433
00:25:39,200 --> 00:25:41,199
Speaker 1: The more information we have, the more we realize that

434
00:25:41,200 --> 00:25:45,119
Speaker 1: the public health authorities in this country have just dramatically

435
00:25:45,119 --> 00:25:52,200
Speaker 1: failed us. They have completely collapsed on us here. And

436
00:25:52,400 --> 00:25:54,680
Speaker 1: I mean public health authorities. I'm not talking about doctors

437
00:25:54,680 --> 00:25:56,720
Speaker 1: who are doing a job. I'm not talking about nurses

438
00:25:56,760 --> 00:25:59,080
Speaker 1: who are doing a job, who are trying to provide

439
00:25:59,119 --> 00:26:03,480
Speaker 1: care to people. That's great. I'm talking about those mds

440
00:26:03,480 --> 00:26:07,800
Speaker 1: in our midst who are making national policy, who are

441
00:26:07,880 --> 00:26:10,439
Speaker 1: harnessing the force of the federal, of the state, of

442
00:26:10,480 --> 00:26:14,200
Speaker 1: local government, which ultimately means a willingness to take your

443
00:26:14,240 --> 00:26:16,240
Speaker 1: stuff and lock you up if you don't agree. That's

444
00:26:16,280 --> 00:26:20,800
Speaker 1: what government force is. The mds who have been pushing

445
00:26:20,800 --> 00:26:26,320
Speaker 1: those decisions have been catastrophically wrong. We have not gotten

446
00:26:26,320 --> 00:26:28,560
Speaker 1: the benefits that they have promised we would have and

447
00:26:28,640 --> 00:26:33,800
Speaker 1: we have certainly had all of the downside. Plasz. Joy

448
00:26:33,920 --> 00:26:36,720
Speaker 1: behar out there who says, you know, you know, doctor

449
00:26:37,440 --> 00:26:41,800
Speaker 1: doctor Atlas, he's you know what he is, he's embarrassing

450
00:26:41,880 --> 00:26:47,600
Speaker 1: play eleven well as the unofficial spokesperson for the social

451
00:26:47,600 --> 00:26:51,280
Speaker 1: security crowd. Let me say to doctor Atlas, this is

452
00:26:51,359 --> 00:27:00,639
Speaker 1: not my last thanksgiving, you embarrassing quack. He's a neuro

453
00:27:01,080 --> 00:27:05,080
Speaker 1: He's a neuro radiologist. Joy, what does it happened to first?

454
00:27:05,320 --> 00:27:09,280
Speaker 1: Do no harm? This guy is. He is a menace

455
00:27:09,359 --> 00:27:12,879
Speaker 1: to society, this man. Of course, Trump picks him because

456
00:27:12,880 --> 00:27:15,800
Speaker 1: he only picks the best people. But I mean, come on,

457
00:27:16,600 --> 00:27:18,840
Speaker 1: you know, don't don't listen to a radiologist when it

458
00:27:18,880 --> 00:27:21,520
Speaker 1: comes to a virus. Please, ladies and gentlemen out there,

459
00:27:21,760 --> 00:27:24,320
Speaker 1: do not listen to this quack. He's a quack. He's

460
00:27:24,320 --> 00:27:31,120
Speaker 1: a quack. Quack quack. Neuro radiologists you google it. They

461
00:27:31,160 --> 00:27:34,560
Speaker 1: have further certification than just radiologists, and that they also

462
00:27:34,640 --> 00:27:38,800
Speaker 1: treat abnormalities in the nervous system, spine, head and neck,

463
00:27:39,640 --> 00:27:43,680
Speaker 1: and they can treat diseases by means of image guided surgery.

464
00:27:43,920 --> 00:27:46,600
Speaker 1: So yeah, no, not really, not really a doctor, just

465
00:27:46,640 --> 00:27:52,560
Speaker 1: a doctor who diagnoses neck, brain spine injuries and can

466
00:27:52,600 --> 00:27:56,320
Speaker 1: do surgery to help fix that. Well, other than that,

467
00:27:56,400 --> 00:27:58,720
Speaker 1: not really. I mean it's not like you know, this

468
00:27:58,840 --> 00:28:01,719
Speaker 1: guy's like lower than a prediatrist on the medical food chain. Right,

469
00:28:01,760 --> 00:28:03,600
Speaker 1: no offensive a dietris out there. I'm just saying, I

470
00:28:03,600 --> 00:28:06,000
Speaker 1: know they get a lot of heat. This is nonsense.

471
00:28:06,920 --> 00:28:09,760
Speaker 1: But listen to joy Biha. She knows it's not my

472
00:28:09,920 --> 00:28:12,280
Speaker 1: last ex Giving. What he's saying is, if you're eighty

473
00:28:12,320 --> 00:28:15,240
Speaker 1: six years old, are you not going to see your grandkids?

474
00:28:15,240 --> 00:28:16,920
Speaker 1: Are you're not going to see your family this Thanksgiving

475
00:28:16,960 --> 00:28:20,840
Speaker 1: because you're afraid of a virus that you probably won't

476
00:28:20,880 --> 00:28:24,600
Speaker 1: catch by the numbers, and you might, But you also,

477
00:28:24,640 --> 00:28:26,480
Speaker 1: in any given a year, could die from any number

478
00:28:26,520 --> 00:28:28,920
Speaker 1: of things that you could catch from just living your life.

479
00:28:29,480 --> 00:28:32,320
Speaker 1: Do you this is a question for people to answer themselves.

480
00:28:32,480 --> 00:28:34,720
Speaker 1: Do you want to live your life or do you

481
00:28:34,760 --> 00:28:36,800
Speaker 1: want to hide in fear? If you want to hide,

482
00:28:36,800 --> 00:28:40,320
Speaker 1: that's fine, that's your right right that you have a

483
00:28:40,400 --> 00:28:42,960
Speaker 1: right to do that. I there is no notice how

484
00:28:43,000 --> 00:28:45,800
Speaker 1: there's no coercion from our side to force people to

485
00:28:45,880 --> 00:28:49,800
Speaker 1: leave their homes, force people to go out into crowded places. No,

486
00:28:49,960 --> 00:28:51,840
Speaker 1: But in the other direction. Of course, they have no

487
00:28:51,920 --> 00:28:55,320
Speaker 1: problem with the utilization of state force to make you

488
00:28:55,360 --> 00:28:57,880
Speaker 1: stay in your home, to make you avoid other people.

489
00:28:59,480 --> 00:29:03,480
Speaker 1: This does get down to very basic philosophy about about

490
00:29:03,480 --> 00:29:09,120
Speaker 1: the government and noticed that there's so little, so little

491
00:29:10,720 --> 00:29:14,000
Speaker 1: emphasis put on the pain that they're causing people. Here.

492
00:29:15,360 --> 00:29:17,280
Speaker 1: Oh you know, I know, she's supposed to be so

493
00:29:17,400 --> 00:29:20,520
Speaker 1: nice and yah gosh, yeah, it's a lovely lady. Governor

494
00:29:20,560 --> 00:29:23,880
Speaker 1: Wheatmer up in Michigan. Yo. Yeah, here she is talking

495
00:29:23,920 --> 00:29:26,840
Speaker 1: about that small business. I'm just crushing the small businesses

496
00:29:26,880 --> 00:29:29,240
Speaker 1: like a little bug under my boot. But you know,

497
00:29:29,720 --> 00:29:32,960
Speaker 1: I feel bad for them. Play sixteen. The restaurant industry

498
00:29:33,000 --> 00:29:36,200
Speaker 1: has really had a tough year because of COVID, because

499
00:29:36,240 --> 00:29:38,640
Speaker 1: there's not been a national strategy, and we've seen COVID

500
00:29:38,720 --> 00:29:42,560
Speaker 1: just explode across the country in waves. This is really

501
00:29:42,680 --> 00:29:46,680
Speaker 1: driven by our epidemialogists and our public health experts that

502
00:29:46,840 --> 00:29:50,000
Speaker 1: tell us it's inherently dangerous. With a kind of a

503
00:29:50,120 --> 00:29:52,520
Speaker 1: community spread that we have all across Michigan and all

504
00:29:52,560 --> 00:29:55,080
Speaker 1: across the Midwest and frankly all across the country. The

505
00:29:55,120 --> 00:29:58,600
Speaker 1: inherently dangerous situations are when you are inside with people

506
00:29:58,640 --> 00:30:01,720
Speaker 1: from a different household are many different households for a

507
00:30:01,760 --> 00:30:04,560
Speaker 1: prolonged period of time with masks off. That's what happens

508
00:30:04,560 --> 00:30:06,960
Speaker 1: in restaurants, and that's why it's really going to be

509
00:30:06,960 --> 00:30:09,400
Speaker 1: critical that the Feds get their act together and give

510
00:30:09,480 --> 00:30:12,840
Speaker 1: us some stimulus support for these small businesses, for these

511
00:30:12,880 --> 00:30:17,320
Speaker 1: restaurant workers. I have incredible empathy for what they're struggling with,

512
00:30:17,320 --> 00:30:21,280
Speaker 1: and yet we have to follow the epidemiology the public

513
00:30:21,320 --> 00:30:24,960
Speaker 1: health experts and make decisions that combat the spread before

514
00:30:24,960 --> 00:30:27,560
Speaker 1: our hospitals get overwhelmed and before we hit a thousand

515
00:30:27,640 --> 00:30:30,080
Speaker 1: deaths a week in Michigan, because that's what the modeling

516
00:30:30,200 --> 00:30:32,720
Speaker 1: is telling us where we're headed right now. But we're

517
00:30:32,720 --> 00:30:36,280
Speaker 1: we're in masks and we've been social distancing. So why

518
00:30:36,280 --> 00:30:38,280
Speaker 1: are the models telling them? You mean, the models that

519
00:30:38,280 --> 00:30:41,080
Speaker 1: have been wrong always during this whole thing, the models

520
00:30:41,080 --> 00:30:43,120
Speaker 1: that keep being wrong. We have to listen more about this.

521
00:30:43,800 --> 00:30:47,320
Speaker 1: The government cannot protect you from an aerosolized virus that

522
00:30:47,480 --> 00:30:51,200
Speaker 1: is at pandemic stage, that is already in you know,

523
00:30:51,680 --> 00:30:54,200
Speaker 1: it's all over the place. You know, they do they

524
00:30:54,520 --> 00:30:57,120
Speaker 1: write these news reports about how the Chinese government says

525
00:30:57,160 --> 00:31:00,800
Speaker 1: they've found coronavirus on beefs and from halfway across the

526
00:31:00,800 --> 00:31:03,040
Speaker 1: world that arrives in China. I mean, this is what

527
00:31:03,080 --> 00:31:06,959
Speaker 1: we're dealing with. But the government says, just listen to us,

528
00:31:07,000 --> 00:31:10,280
Speaker 1: just let us take away your constitutional rights and will

529
00:31:10,320 --> 00:31:14,560
Speaker 1: protect you. It's a lie. They can't they can't do it,

530
00:31:15,120 --> 00:31:17,640
Speaker 1: but they won't admit that. They won't admit that. I

531
00:31:17,720 --> 00:31:20,280
Speaker 1: if people started to believe that there were limitations on

532
00:31:20,360 --> 00:31:23,640
Speaker 1: what government could do to protect them, that would start

533
00:31:23,640 --> 00:31:26,320
Speaker 1: to change their underlying political philosophy in ways that would

534
00:31:26,360 --> 00:31:29,040
Speaker 1: not be helpful for Democrats, for status, for the left.

535
00:31:30,720 --> 00:31:34,760
Speaker 1: But it's it's never. It's never that they were wrong.

536
00:31:35,000 --> 00:31:37,160
Speaker 1: It's just that we didn't do it well enough. Oh,

537
00:31:37,200 --> 00:31:40,160
Speaker 1: get ready for you know, I've been saying this, N

538
00:31:40,280 --> 00:31:43,760
Speaker 1: ninety five masks. That's where it's really at. Okay, maybe

539
00:31:43,800 --> 00:31:45,560
Speaker 1: the cloth masks weren't a good as good, but it's

540
00:31:45,600 --> 00:31:47,240
Speaker 1: N ninety five masks. Or you gotta double up on

541
00:31:47,280 --> 00:31:50,080
Speaker 1: the cloth masks, or do what they're doing in Pennsylvania now,

542
00:31:50,160 --> 00:31:51,360
Speaker 1: or they have a state mandate that you have to

543
00:31:51,400 --> 00:31:55,040
Speaker 1: wear a mask inside your own home, inside your own home,

544
00:31:55,880 --> 00:31:59,360
Speaker 1: that's right. You know, you have one hundreds of thousands

545
00:31:59,360 --> 00:32:01,480
Speaker 1: of people to die from heart disease. We could also

546
00:32:01,520 --> 00:32:04,800
Speaker 1: have a mandate that you can only eat two thousand

547
00:32:04,800 --> 00:32:06,600
Speaker 1: calories a day and have to do one hundred push

548
00:32:06,680 --> 00:32:09,600
Speaker 1: ups before before you shower every morning. That would make

549
00:32:09,600 --> 00:32:11,880
Speaker 1: people probably healthier in the aggregate, would save a lot

550
00:32:11,920 --> 00:32:16,040
Speaker 1: of lives. Is that constitutional too? Under emergency health powers?

551
00:32:18,680 --> 00:32:21,640
Speaker 1: You're in the freedom hud. This is the Buck Sexton

552
00:32:21,720 --> 00:32:28,200
Speaker 1: Show podcast. Well, there's no further visits come before the Senate,

553
00:32:28,440 --> 00:32:32,160
Speaker 1: Astana Jorn under the previous order, following the remarks of

554
00:32:32,320 --> 00:32:37,960
Speaker 1: Senator Brown, without objection President Center from Ohio, I'd start

555
00:32:38,000 --> 00:32:40,400
Speaker 1: by asking the presiding officer to please wear a mask

556
00:32:40,840 --> 00:32:43,680
Speaker 1: as he speaks and people below him or I can't

557
00:32:43,680 --> 00:32:46,480
Speaker 1: tell you what to do, but I know that the behavior.

558
00:32:46,520 --> 00:32:49,200
Speaker 1: I don't wear a mask when I'm speaking, like most senators,

559
00:32:49,640 --> 00:32:53,840
Speaker 1: I'm most SATs. I don't need your instruction from I

560
00:32:53,880 --> 00:32:56,400
Speaker 1: know you don't need my instruction, but I there clearly

561
00:32:56,480 --> 00:32:59,240
Speaker 1: isn't much interest in this body in public health. We

562
00:32:59,320 --> 00:33:02,240
Speaker 1: have a president who hasn't shown up at the Coronavirus

563
00:33:02,320 --> 00:33:05,440
Speaker 1: Task Force meeting in months. We have a majority leader

564
00:33:05,480 --> 00:33:08,520
Speaker 1: that calls us back here to vote on an unqualified

565
00:33:08,600 --> 00:33:12,240
Speaker 1: nominee and at the same time to vote for judge

566
00:33:12,280 --> 00:33:15,360
Speaker 1: after judge after judge, exposing all the people who can't

567
00:33:15,360 --> 00:33:18,120
Speaker 1: say anything. I understand, the people in front of you

568
00:33:18,200 --> 00:33:21,280
Speaker 1: and the presiding officer, and expose all the staff here,

569
00:33:21,760 --> 00:33:25,560
Speaker 1: and the majority leader just doesn't seem to care. That's

570
00:33:25,600 --> 00:33:29,840
Speaker 1: what mask shaming is really for making long political statements. Afterwards.

571
00:33:30,560 --> 00:33:35,680
Speaker 1: That was Sharad Brown in the Senate. Someone's getting up

572
00:33:35,680 --> 00:33:37,280
Speaker 1: to speak, No one's around them, no one's near them.

573
00:33:37,280 --> 00:33:38,600
Speaker 1: But you know, can you wear a matt? Why aren't

574
00:33:38,600 --> 00:33:42,800
Speaker 1: you wearing a mask? Ah? Yes? You notice how it

575
00:33:43,080 --> 00:33:46,840
Speaker 1: turns people against each other so quickly too. It creates

576
00:33:46,880 --> 00:33:50,000
Speaker 1: this immediate attention on the people that want this as

577
00:33:50,000 --> 00:33:51,480
Speaker 1: a policy. They want ever to do it all you

578
00:33:51,520 --> 00:33:54,680
Speaker 1: got to do it to protected. They forget that the

579
00:33:54,760 --> 00:33:57,120
Speaker 1: chance of the person that they're mask shaming actually having

580
00:33:57,160 --> 00:33:59,240
Speaker 1: COVID nineteen, just based on the numbers is less than

581
00:33:59,240 --> 00:34:02,280
Speaker 1: one percent. So ninety nine out of one hundred people

582
00:34:02,280 --> 00:34:05,320
Speaker 1: that you go around in you mask shame, You're you're

583
00:34:05,360 --> 00:34:08,520
Speaker 1: actually telling a healthy person, why aren't you wearing a mask?

584
00:34:08,920 --> 00:34:11,080
Speaker 1: And I understand this, this is why they want the policy.

585
00:34:11,160 --> 00:34:13,080
Speaker 1: But if we're really just getting down to it in

586
00:34:13,120 --> 00:34:15,560
Speaker 1: each individual incident. It's a little bit like walking around

587
00:34:15,560 --> 00:34:18,719
Speaker 1: to somebody who you know is littering and acting like,

588
00:34:19,000 --> 00:34:21,359
Speaker 1: you know, the world is going to run out of

589
00:34:22,400 --> 00:34:24,640
Speaker 1: clean water and our oceans, all the sea life is

590
00:34:24,640 --> 00:34:26,560
Speaker 1: going to die because you just dropped a gum wrapper

591
00:34:26,600 --> 00:34:29,600
Speaker 1: on the street. Right, That's like, okay, well, i'll get

592
00:34:29,640 --> 00:34:32,040
Speaker 1: I'll get it next time, but you know, maybe don't

593
00:34:32,040 --> 00:34:34,760
Speaker 1: put this all on my shoulders. And at that time,

594
00:34:34,960 --> 00:34:36,960
Speaker 1: not even really the case. You're saying it to somebody

595
00:34:36,960 --> 00:34:39,440
Speaker 1: who didn't even necessarily literally you don't know, right, because

596
00:34:39,600 --> 00:34:43,320
Speaker 1: if they're innocent, if they're healthy, it doesn't make any difference.

597
00:34:43,840 --> 00:34:47,160
Speaker 1: This whole thing has gotten so absurd. But remember the

598
00:34:47,280 --> 00:34:51,360
Speaker 1: moment that this became a Trump thing, then this became

599
00:34:51,400 --> 00:34:56,360
Speaker 1: a Trump versus non Trump thing. All fair arguments and

600
00:34:56,440 --> 00:35:00,839
Speaker 1: all data and everything else got pushed aside because this

601
00:35:00,920 --> 00:35:05,640
Speaker 1: was this whole the response, the COVID pandemic, all weaponized

602
00:35:06,000 --> 00:35:08,560
Speaker 1: to try and defeat Donald Trump in this election. And look,

603
00:35:08,560 --> 00:35:12,640
Speaker 1: it may have ended up being successful. Friends, we have

604
00:35:12,760 --> 00:35:15,520
Speaker 1: to deal with that reality. They may have been able

605
00:35:15,560 --> 00:35:17,200
Speaker 1: to do it. And I know people say, oh buck,

606
00:35:17,239 --> 00:35:20,240
Speaker 1: they didn't really vote on COVID. Now, the country's mood

607
00:35:21,040 --> 00:35:24,240
Speaker 1: was changed, that the feeling of this place was changed,

608
00:35:25,000 --> 00:35:27,759
Speaker 1: no question about it, as a result of COVID. And

609
00:35:27,920 --> 00:35:30,759
Speaker 1: a huge amount of resources and time had to be

610
00:35:30,800 --> 00:35:34,040
Speaker 1: spent by the Trump campaign trying to explain to people

611
00:35:34,120 --> 00:35:37,080
Speaker 1: that they were doing everything that Joe Biden says he

612
00:35:37,080 --> 00:35:40,120
Speaker 1: would do. They just don't go around making a big

613
00:35:40,160 --> 00:35:43,640
Speaker 1: thing of how it's all democrats fault that we have COVID,

614
00:35:43,680 --> 00:35:46,680
Speaker 1: which is what they say about Republicans. Thanks for listening

615
00:35:46,680 --> 00:35:50,120
Speaker 1: to the buses and show podcasts. Remember to subscribe on

616
00:35:50,200 --> 00:35:55,799
Speaker 1: Apple podcasts, the iHeartRadio app, or wherever you get your podcasts. Well,

617
00:35:55,800 --> 00:36:00,240
Speaker 1: would you look at that? More ballots in the last

618
00:36:00,320 --> 00:36:05,080
Speaker 1: forty eight hours, found ballots that had not been counted,

619
00:36:05,160 --> 00:36:08,000
Speaker 1: No particularly good reason for that, just didn't get counted.

620
00:36:09,000 --> 00:36:12,319
Speaker 1: More ballots that were not counted. And who wants to

621
00:36:12,360 --> 00:36:15,520
Speaker 1: guess whether they go majority for Trump or by it

622
00:36:15,560 --> 00:36:18,319
Speaker 1: an You want to take a guess? Ah, Yes, it

623
00:36:18,360 --> 00:36:23,000
Speaker 1: turns out that they have found not one, but two

624
00:36:23,160 --> 00:36:29,440
Speaker 1: batches of ballots in Fayette County and also in Floyd County, Georgia. Now,

625
00:36:29,480 --> 00:36:32,400
Speaker 1: Georgia is a state where you've got about a what

626
00:36:32,560 --> 00:36:36,759
Speaker 1: is it a fifteen thousand vote margin, something like that.

627
00:36:36,840 --> 00:36:41,280
Speaker 1: So on Monday we found twenty six hundred new votes

628
00:36:41,719 --> 00:36:46,000
Speaker 1: in Floyd County. And now they've also announced that there

629
00:36:46,000 --> 00:36:49,040
Speaker 1: were two thousand, seven hundred and fifty five uncounted votes

630
00:36:49,120 --> 00:36:53,440
Speaker 1: on a memory card in Fayette County. So over the

631
00:36:53,440 --> 00:36:59,880
Speaker 1: course of two days, you got about five thousand uncounted

632
00:37:00,160 --> 00:37:05,120
Speaker 1: ballots that just show up. In Georgia. Now, remember we're

633
00:37:05,160 --> 00:37:10,440
Speaker 1: told it's over, be quiet, go home, nothing to see here.

634
00:37:11,120 --> 00:37:16,040
Speaker 1: Trump lost. That's where we're told. But if you find,

635
00:37:16,120 --> 00:37:19,319
Speaker 1: ever the course of two days, five thousand ballots that

636
00:37:19,400 --> 00:37:22,640
Speaker 1: were just not included in the tallly at all, and

637
00:37:22,760 --> 00:37:24,640
Speaker 1: at least in one of those two batches, they went

638
00:37:24,680 --> 00:37:28,799
Speaker 1: two for one Trump. Okay, so two for one going

639
00:37:28,840 --> 00:37:32,879
Speaker 1: to Trump. They've cut down the Biden lead to under

640
00:37:33,040 --> 00:37:37,719
Speaker 1: thirteen thousand votes. Now in that state, I just want

641
00:37:37,719 --> 00:37:40,400
Speaker 1: to know, at what point do we get to say, wow,

642
00:37:40,440 --> 00:37:43,280
Speaker 1: we really do need to make sure that we cross

643
00:37:43,320 --> 00:37:45,120
Speaker 1: all the t's and done all the eyes here. At

644
00:37:45,120 --> 00:37:48,640
Speaker 1: what point is it obvious to anybody who's being honest

645
00:37:49,719 --> 00:37:51,560
Speaker 1: that the only way forward here is to make sure

646
00:37:51,560 --> 00:37:56,239
Speaker 1: that we do check for every legal ballot that we

647
00:37:56,320 --> 00:37:59,920
Speaker 1: make sure that illegal ballots are not counted, and yet

648
00:38:00,239 --> 00:38:06,640
Speaker 1: that we find and rectify irregularities, fraud, all of these things.

649
00:38:07,080 --> 00:38:09,759
Speaker 1: We're talking about five thousand new votes found in a

650
00:38:09,840 --> 00:38:12,920
Speaker 1: state with less than fifteen thousand for the marginal victory.

651
00:38:13,040 --> 00:38:17,120
Speaker 1: Shouldn't that matter to everybody? Isn't that important? Is it

652
00:38:17,200 --> 00:38:19,239
Speaker 1: surprising to anyone? I'm gonna ask you this, Is it

653
00:38:19,320 --> 00:38:24,640
Speaker 1: surprising to anyone that we have a circumstance that we

654
00:38:24,680 --> 00:38:30,120
Speaker 1: have a situation where we're finding okay, where we're finding ballots,

655
00:38:30,920 --> 00:38:33,920
Speaker 1: and there are all these changes that were made this

656
00:38:34,040 --> 00:38:36,879
Speaker 1: year to the way the election was going to be done.

657
00:38:37,800 --> 00:38:39,600
Speaker 1: Of course, this is what's going to happen when you

658
00:38:39,640 --> 00:38:43,240
Speaker 1: have last been a changes, all this additional mail in balloting,

659
00:38:43,400 --> 00:38:46,919
Speaker 1: all these let's be real, let's be honest, all these

660
00:38:46,960 --> 00:38:49,640
Speaker 1: games that Democrats were playing to try to shift the

661
00:38:49,680 --> 00:38:54,680
Speaker 1: election playing field in their favor. Yes, there are going

662
00:38:54,760 --> 00:38:57,799
Speaker 1: to be ballots that are found that don't count or

663
00:38:57,840 --> 00:39:00,480
Speaker 1: that haven't been counted rather and that shouldn't count if

664
00:39:00,480 --> 00:39:04,760
Speaker 1: they're illegally cast. So isn't this exactly what we should

665
00:39:04,800 --> 00:39:08,680
Speaker 1: be expecting? But remember, if you have any questions about

666
00:39:08,680 --> 00:39:11,480
Speaker 1: this election, at this point, if you just want the

667
00:39:11,520 --> 00:39:14,960
Speaker 1: process to continue so that we make sure that we

668
00:39:15,040 --> 00:39:19,800
Speaker 1: have certainty. You are a conspiracy theorist, You're a bad person,

669
00:39:20,160 --> 00:39:24,719
Speaker 1: you're a trumper, and you're awful. That's what the dominant theme,

670
00:39:24,760 --> 00:39:27,840
Speaker 1: the dominant narrative, certainly from the media and from the

671
00:39:27,840 --> 00:39:32,799
Speaker 1: Democrat Party is. And to this, I just ask, well,

672
00:39:32,840 --> 00:39:36,279
Speaker 1: how do they explain this in Georgia? How do they

673
00:39:36,320 --> 00:39:38,600
Speaker 1: explain the five thousand votes that they had to fix

674
00:39:38,680 --> 00:39:44,200
Speaker 1: with a glitch in Michigan? If every vote counts, then

675
00:39:44,200 --> 00:39:47,040
Speaker 1: doesn't that mean we'd want to try to get every

676
00:39:47,120 --> 00:39:50,880
Speaker 1: vote to be correct here, so illegal ballots not counted

677
00:39:50,880 --> 00:39:54,680
Speaker 1: because that cancels out legal ones. I think this should

678
00:39:54,680 --> 00:39:58,160
Speaker 1: be very straightforward, but we got a lot of challenges here. Friends.

679
00:39:59,040 --> 00:40:02,000
Speaker 1: There's what we know and what we can prove. There's

680
00:40:02,080 --> 00:40:05,640
Speaker 1: what looks fishy and what we'll be able to definitively

681
00:40:05,840 --> 00:40:08,440
Speaker 1: show in a court of law and get a judge

682
00:40:08,440 --> 00:40:11,799
Speaker 1: to take action on. There are many steps here, many

683
00:40:11,840 --> 00:40:15,239
Speaker 1: phases that have to go a certain way for this

684
00:40:15,320 --> 00:40:18,920
Speaker 1: election to be overturned in Trump's favor. And I've been

685
00:40:18,960 --> 00:40:22,720
Speaker 1: telling you it's a long shot. It's a long shot.

686
00:40:22,800 --> 00:40:25,040
Speaker 1: People who were saying otherwise. I don't think they're being

687
00:40:25,040 --> 00:40:29,719
Speaker 1: honest with you. I think that there's a lot of Oh,

688
00:40:29,840 --> 00:40:32,840
Speaker 1: I'm going to be the most magarific, I'm going to

689
00:40:32,920 --> 00:40:36,839
Speaker 1: be the most pro Trump, even in these last weeks here,

690
00:40:37,320 --> 00:40:40,959
Speaker 1: just to show everybody my devotion to the cause, even

691
00:40:40,960 --> 00:40:43,960
Speaker 1: though I believe that this is going to go for

692
00:40:44,040 --> 00:40:45,840
Speaker 1: Joe Biden. But I'm not going to tell anybody that.

693
00:40:45,920 --> 00:40:48,279
Speaker 1: I'm here telling you I think Trump's chances are not

694
00:40:48,360 --> 00:40:51,080
Speaker 1: good at this point. But that doesn't mean we don't fight.

695
00:40:52,239 --> 00:40:55,839
Speaker 1: That doesn't mean we don't figure out exactly what happened here.

696
00:40:55,840 --> 00:40:57,680
Speaker 1: To the best of our ability. It's about this election

697
00:40:57,760 --> 00:41:03,200
Speaker 1: and the next election. This is mean you also have

698
00:41:03,480 --> 00:41:10,120
Speaker 1: in Nevada this allegation which came from Adam Laxalt. I

699
00:41:10,120 --> 00:41:15,520
Speaker 1: think he's the GOP chief there play for what we

700
00:41:15,560 --> 00:41:20,719
Speaker 1: are providing today in this lawsuit is that many of

701
00:41:20,760 --> 00:41:27,520
Speaker 1: these votes were improperly cast. We are presenting today in

702
00:41:27,640 --> 00:41:33,040
Speaker 1: our formal contest that there are north of fifteen thousand

703
00:41:33,120 --> 00:41:40,000
Speaker 1: people who voted in Nevada and another state. We are

704
00:41:40,080 --> 00:41:46,160
Speaker 1: presenting that people voted in people that had already done

705
00:41:46,160 --> 00:41:49,920
Speaker 1: a change of address and left the state outside of

706
00:41:50,000 --> 00:41:54,360
Speaker 1: thirty the thirty day requirement, their ballots were still cast.

707
00:41:55,239 --> 00:42:03,160
Speaker 1: We are also presenting dead voters. Those are all verifiable

708
00:42:03,360 --> 00:42:08,480
Speaker 1: allegations one way or the other. Shouldn't we know? Shouldn't

709
00:42:08,480 --> 00:42:11,520
Speaker 1: we have a real understanding of what's true here and

710
00:42:11,640 --> 00:42:15,560
Speaker 1: what's not. What's the argument against this? Oh, that Trump

711
00:42:15,640 --> 00:42:20,360
Speaker 1: hasn't conceded soon enough, that Trump is a risk to

712
00:42:20,400 --> 00:42:25,239
Speaker 1: our democracy. No, what we do know is that the

713
00:42:25,360 --> 00:42:29,200
Speaker 1: left's answers, whenever we try to pose these questions, always

714
00:42:29,239 --> 00:42:34,560
Speaker 1: revolve around a version of orange man bad. Trump is

715
00:42:34,600 --> 00:42:38,879
Speaker 1: a unique threat. Trump is uniquely awful, and because of that,

716
00:42:38,920 --> 00:42:41,799
Speaker 1: the Democrats say, he doesn't even really get to have

717
00:42:41,960 --> 00:42:46,440
Speaker 1: his process. We don't get to have the president waits

718
00:42:48,160 --> 00:42:50,439
Speaker 1: to see what actually happened. He's supposed to get ahead

719
00:42:50,480 --> 00:42:52,719
Speaker 1: of it and say, you know what, you're right, I'm

720
00:42:52,719 --> 00:42:57,759
Speaker 1: sorry I lost this election. He's not even allowed to

721
00:42:57,800 --> 00:42:59,880
Speaker 1: get his due process. That's what they want you to

722
00:43:00,200 --> 00:43:04,279
Speaker 1: that's their their position on all of this. Because he's

723
00:43:04,320 --> 00:43:07,400
Speaker 1: the worst. That's why Don Lemon's out there, Don Lemon,

724
00:43:08,239 --> 00:43:14,279
Speaker 1: monsieur Don Lemon. He is out there telling people that

725
00:43:14,360 --> 00:43:17,279
Speaker 1: this is this is about what your grandkids think. Play

726
00:43:17,360 --> 00:43:21,160
Speaker 1: ten it is all local, but imagine those local folks

727
00:43:21,360 --> 00:43:23,480
Speaker 1: having the influence they had. They could have had a

728
00:43:23,560 --> 00:43:26,640
Speaker 1: very big influence on a national election on who was

729
00:43:26,840 --> 00:43:30,480
Speaker 1: president of the United States. I think that, you know,

730
00:43:30,520 --> 00:43:33,319
Speaker 1: I heard some folks on your air talking about how

731
00:43:34,040 --> 00:43:36,279
Speaker 1: how history is going to look back on this, and

732
00:43:36,320 --> 00:43:37,600
Speaker 1: I think a lot of people are going to be

733
00:43:37,680 --> 00:43:40,799
Speaker 1: embarrassed over time when they look back and say, how

734
00:43:40,800 --> 00:43:42,640
Speaker 1: did I do that? How did I fall for that?

735
00:43:43,000 --> 00:43:46,160
Speaker 1: What happened to me? What was I thinking in that time? Wrong?

736
00:43:46,560 --> 00:43:48,759
Speaker 1: You may want to win, You may want to you know,

737
00:43:48,800 --> 00:43:50,440
Speaker 1: whatever it is you have what do they call it

738
00:43:50,719 --> 00:43:53,680
Speaker 1: liberal tears? You may want all of that, But your

739
00:43:53,719 --> 00:43:55,920
Speaker 1: grandchildren and your kids will look back and say, oh,

740
00:43:56,000 --> 00:43:58,880
Speaker 1: what did grandpa did? What dude? What did dadd what

741
00:43:58,920 --> 00:44:02,560
Speaker 1: did bomb do in this moment, and realize that you

742
00:44:02,600 --> 00:44:04,360
Speaker 1: were on the wrong side of history and that you

743
00:44:04,440 --> 00:44:08,960
Speaker 1: possibly were teaching them the wrong thing. It'sn't that all.

744
00:44:09,000 --> 00:44:12,359
Speaker 1: It's that ridiculous thinking about that. Yeah, your grandkids are

745
00:44:12,360 --> 00:44:15,520
Speaker 1: really going to say, excuse me, granddaddy, where were you

746
00:44:16,080 --> 00:44:19,960
Speaker 1: during the great recount fight of twenty twenty in those weeks?

747
00:44:20,000 --> 00:44:24,120
Speaker 1: What side of the issue where you on? No that's

748
00:44:24,360 --> 00:44:29,000
Speaker 1: not going to happen. Your grandkids will not care. Nobody

749
00:44:29,280 --> 00:44:33,520
Speaker 1: will even remember this. In six months, we will remember

750
00:44:33,560 --> 00:44:36,680
Speaker 1: who the president is and we may suffer the consequences

751
00:44:36,680 --> 00:44:39,600
Speaker 1: if he's the if it's the wrong one, But no

752
00:44:39,640 --> 00:44:41,319
Speaker 1: one's going to remember that. You said, yeah, can we

753
00:44:41,320 --> 00:44:44,799
Speaker 1: just make sure every legal vot vote is counted. That's

754
00:44:45,000 --> 00:44:48,840
Speaker 1: that's a very standard, very defensible. In fact, it's the

755
00:44:48,880 --> 00:44:52,200
Speaker 1: only really defensible position here. But this is what they do.

756
00:44:52,239 --> 00:44:55,320
Speaker 1: They create these narratives. It's a version of the journals

757
00:44:55,320 --> 00:44:57,400
Speaker 1: always saying, you know, my five year old came to

758
00:44:57,440 --> 00:45:01,600
Speaker 1: me and said, you know, dad, why you that Republicans

759
00:45:01,640 --> 00:45:05,160
Speaker 1: don't understand the unique threat to our democracy posed by

760
00:45:05,239 --> 00:45:09,640
Speaker 1: Donald Trump's erosion of norms. Now, you're five year old.

761
00:45:09,640 --> 00:45:11,840
Speaker 1: Didn't say that, journal, but nice try right. They do

762
00:45:11,920 --> 00:45:13,840
Speaker 1: that all the time. This was a thing that was

763
00:45:13,880 --> 00:45:16,920
Speaker 1: really popular a couple of years ago. Blue check journals

764
00:45:16,920 --> 00:45:21,600
Speaker 1: would lie about how their toddler was waxing philosophical about

765
00:45:21,600 --> 00:45:24,720
Speaker 1: the unique threat to the Constitution posed by President Trump

766
00:45:24,920 --> 00:45:27,839
Speaker 1: because Libs, for some reason, think that what comes out

767
00:45:27,840 --> 00:45:30,080
Speaker 1: of the mouths of children when it comes to politics

768
00:45:30,200 --> 00:45:34,439
Speaker 1: is really important and powerful. You know, if a kid

769
00:45:34,560 --> 00:45:37,200
Speaker 1: says it, Well, then we really got to pay attention.

770
00:45:38,239 --> 00:45:41,799
Speaker 1: Of course, this is absurd, but that's what they do.

771
00:45:41,920 --> 00:45:43,719
Speaker 1: This is also why they made such a big thing

772
00:45:43,719 --> 00:45:46,719
Speaker 1: of Greta Thunberg, who, at age sixteen was traveling the

773
00:45:46,760 --> 00:45:49,840
Speaker 1: world lecturing people on climate change. Yes, that's right, I

774
00:45:50,160 --> 00:45:57,400
Speaker 1: take advice about complicated multinational climate change treaties from a

775
00:45:57,480 --> 00:46:00,719
Speaker 1: sixteen year old. Yes, that's an intel eligent move for

776
00:46:00,760 --> 00:46:03,560
Speaker 1: an adult. Sure, that's that's really smart. But no, the libs,

777
00:46:04,080 --> 00:46:07,360
Speaker 1: it's all about the emotions, the feelings that theatrics around

778
00:46:07,360 --> 00:46:10,000
Speaker 1: all this, and that's what Don Lemon is appealing to here. Well,

779
00:46:10,040 --> 00:46:13,799
Speaker 1: will your grandchildren say about this moment? Other grandchildren are

780
00:46:13,880 --> 00:46:16,200
Speaker 1: gonna say, did you get me, you know, the latest

781
00:46:16,280 --> 00:46:18,040
Speaker 1: video game that I want for Christmas? They're they're not

782
00:46:18,080 --> 00:46:21,240
Speaker 1: gonna care about what you said. Here's and it's laughable.

783
00:46:21,280 --> 00:46:25,680
Speaker 1: I mean, it's absurd to believe otherwise. But that's one

784
00:46:25,719 --> 00:46:28,520
Speaker 1: way that they do this, and that's one way they

785
00:46:28,520 --> 00:46:30,759
Speaker 1: try to convince you that you have no ground here

786
00:46:30,800 --> 00:46:34,200
Speaker 1: whatsoever to stand and say that you want every vote

787
00:46:34,200 --> 00:46:36,360
Speaker 1: to be counted. And if we're going to talk about

788
00:46:36,360 --> 00:46:40,200
Speaker 1: embarrassment and people that have gone down the rabbit hole

789
00:46:40,360 --> 00:46:43,920
Speaker 1: people that have believed things that are foolish. Has anyone

790
00:46:43,960 --> 00:46:46,520
Speaker 1: at CNN have any of these journals apologized for their

791
00:46:46,600 --> 00:46:50,640
Speaker 1: role in the Russia collusion hoax. Not one, None of

792
00:46:50,640 --> 00:46:53,839
Speaker 1: them have. None of them have apologized. None of them

793
00:46:53,880 --> 00:46:59,400
Speaker 1: feel any any sheepishness or any shame for running around

794
00:46:59,760 --> 00:47:04,400
Speaker 1: for years with the ridiculous story that the President of

795
00:47:04,520 --> 00:47:09,839
Speaker 1: the United States was a Russian asset who worked to

796
00:47:09,920 --> 00:47:12,799
Speaker 1: steal the election from Hillary Clinton in twenty sixteen, many

797
00:47:12,840 --> 00:47:15,799
Speaker 1: of them still believe that. Many of them still think

798
00:47:15,800 --> 00:47:20,279
Speaker 1: there was Russian collusion, and that's how they avoid the embarrassment.

799
00:47:20,280 --> 00:47:22,759
Speaker 1: I mean, what should be the deep intellectual embarrassment of

800
00:47:23,000 --> 00:47:27,760
Speaker 1: falling for that. But now they're telling us, Oh, if

801
00:47:27,840 --> 00:47:31,200
Speaker 1: you stand and fight now and want the final counts

802
00:47:31,239 --> 00:47:34,759
Speaker 1: to be accurate, you're going to be embarrassed one day. No,

803
00:47:34,920 --> 00:47:37,480
Speaker 1: I don't think I'll take advice from them on this.

804
00:47:37,920 --> 00:47:40,160
Speaker 1: I also don't think I'll take advice from them on embarrassment,

805
00:47:40,160 --> 00:47:45,600
Speaker 1: considering how often they accuse Trump and Republicans of more

806
00:47:45,680 --> 00:47:51,879
Speaker 1: or less being Nazis. Here's CNN's Christian Mampu with them.

807
00:47:52,160 --> 00:47:56,680
Speaker 1: Fanciest accent, you've ever heard on television in your life.

808
00:47:57,760 --> 00:48:02,960
Speaker 1: Listen to me, because I'm so sophisticated, an international because

809
00:48:02,960 --> 00:48:08,759
Speaker 1: of my accent that obviously comes from a very expensive

810
00:48:09,160 --> 00:48:13,279
Speaker 1: boarding school in England. But I'm even more international than that.

811
00:48:15,000 --> 00:48:17,920
Speaker 1: But here she is telling everybody, Yeah, you know, maybe

812
00:48:17,920 --> 00:48:19,920
Speaker 1: I shouldn't have said that Trump is just just like

813
00:48:20,000 --> 00:48:22,799
Speaker 1: the Nazis. At the top of my show, unci an

814
00:48:22,840 --> 00:48:27,160
Speaker 1: International play nine and finally, tonight, a comment on my program.

815
00:48:27,200 --> 00:48:30,120
Speaker 1: At the end of last week, I observed the eighty

816
00:48:30,160 --> 00:48:33,279
Speaker 1: second anniversary of Crystal Nacht, as I often do. It

817
00:48:33,440 --> 00:48:35,960
Speaker 1: is the event that began the horrors of the Holocaust.

818
00:48:36,239 --> 00:48:40,640
Speaker 1: I also noted President Trump's attacks on history, facts, knowledge,

819
00:48:40,680 --> 00:48:44,600
Speaker 1: and truth. I shouldn't have juxtaposed the two thoughts Hitler

820
00:48:44,640 --> 00:48:47,440
Speaker 1: and his evil stand alone of course in history. I

821
00:48:47,560 --> 00:48:50,440
Speaker 1: regret any pain my statement may have caused. My point

822
00:48:50,640 --> 00:48:54,120
Speaker 1: was to say how democracy can potentially slip away, and

823
00:48:54,200 --> 00:48:58,960
Speaker 1: how we must always zealously guard our democratic values. Yeah,

824
00:48:59,000 --> 00:49:02,480
Speaker 1: so I compared Trump to Hitler, and I realize that

825
00:49:02,480 --> 00:49:05,880
Speaker 1: that's deeply offensive to some people because it's the dumbest,

826
00:49:05,960 --> 00:49:12,319
Speaker 1: most ridiculous comparison imaginable, and it undermines and underplays the

827
00:49:12,320 --> 00:49:16,040
Speaker 1: true evil of the Holocaust. So let's just move on.

828
00:49:17,000 --> 00:49:24,759
Speaker 1: There you go, CNN's perhaps best known globally anchor total imbecile.

829
00:49:25,120 --> 00:49:28,120
Speaker 1: But doesn't matter. No one's even gonna remember it a week.

830
00:49:28,440 --> 00:49:30,960
Speaker 1: But they want to lecture you and me and tell

831
00:49:31,040 --> 00:49:34,560
Speaker 1: us to be worried about what our grandchildren will think.

832
00:49:35,719 --> 00:49:38,560
Speaker 1: I don't care what the Libs think, that's for sure.

833
00:49:41,040 --> 00:49:43,919
Speaker 1: You're in the freedom mine. This is the Buck Sex

834
00:49:44,000 --> 00:49:53,399
Speaker 1: and Show podcast. Mister Dorsey, does voter fraud exist? All right?

835
00:49:53,600 --> 00:49:56,279
Speaker 1: I don't know for certain. Are you an expert in

836
00:49:56,360 --> 00:50:01,360
Speaker 1: voter fraud? No, I'm not. Well, why then, is Twitter

837
00:50:01,480 --> 00:50:07,120
Speaker 1: right now putting purported warnings on virtually any statement about

838
00:50:07,239 --> 00:50:12,200
Speaker 1: voter fraud. We're simply linking to a product conversation so

839
00:50:12,160 --> 00:50:14,560
Speaker 1: that people have more information. No, no, you're not. You

840
00:50:14,680 --> 00:50:17,160
Speaker 1: put up a page that says, quote, voter fraud of

841
00:50:17,239 --> 00:50:20,439
Speaker 1: any kind is exceedingly rare in the United States. That's

842
00:50:20,440 --> 00:50:23,920
Speaker 1: not linking to a broader conversation. That's taking a disputed

843
00:50:23,960 --> 00:50:26,799
Speaker 1: policy position. And you're a publisher when you're doing that,

844
00:50:26,880 --> 00:50:29,239
Speaker 1: you're entitled to take a policy position, but you don't

845
00:50:29,239 --> 00:50:31,520
Speaker 1: get to pretend you're not a publisher. And get a

846
00:50:31,560 --> 00:50:36,160
Speaker 1: special benefit under Section two thirty. As a result, Link

847
00:50:36,280 --> 00:50:40,520
Speaker 1: is pointing to a product conversation with tweets from publishers

848
00:50:40,719 --> 00:50:44,440
Speaker 1: and people all around the country. No, it's taking a position.

849
00:50:45,600 --> 00:50:48,279
Speaker 1: You know, Ted Cruze understands what's going on here, and

850
00:50:48,360 --> 00:50:51,000
Speaker 1: he's got them and they know this. I am big

851
00:50:51,040 --> 00:50:53,279
Speaker 1: tech in this election, because you remember, it was really

852
00:50:53,320 --> 00:50:56,000
Speaker 1: social pressure from their peers, from their friends and the

853
00:50:56,000 --> 00:50:59,840
Speaker 1: people that they want to like them. At Facebook, at Twitter,

854
00:51:00,000 --> 00:51:06,440
Speaker 1: at these organizations, they were insufficiently devoted to getting a

855
00:51:06,480 --> 00:51:10,840
Speaker 1: Hillary elected by suppressing information and by stacking the deck

856
00:51:11,360 --> 00:51:14,239
Speaker 1: in favor of Hillary against Donald Trump. So this time

857
00:51:14,280 --> 00:51:18,400
Speaker 1: around they tried to find ways to rectify that, and

858
00:51:18,480 --> 00:51:21,880
Speaker 1: the way they choose to rectify it is by challenging

859
00:51:21,920 --> 00:51:26,439
Speaker 1: certain statements by showing that what the president says, even

860
00:51:26,480 --> 00:51:30,400
Speaker 1: the president of the United States, this is disputed. They

861
00:51:30,440 --> 00:51:32,960
Speaker 1: didn't do that for the Russia collusion hoax for four years.

862
00:51:34,080 --> 00:51:36,080
Speaker 1: They haven't done it on any number of things. They

863
00:51:36,080 --> 00:51:39,480
Speaker 1: definitely don't do it for you know, Faucian company. I

864
00:51:39,520 --> 00:51:43,640
Speaker 1: wonder now are they going to censor people who say

865
00:51:43,680 --> 00:51:46,920
Speaker 1: that the biggest study yet done tells you that mask

866
00:51:47,000 --> 00:51:49,920
Speaker 1: wearing does not protect you from virus. That's what the

867
00:51:49,960 --> 00:51:53,680
Speaker 1: study did say. It could not prove that, and that

868
00:51:53,760 --> 00:51:57,080
Speaker 1: was what it's set out to prove as a study.

869
00:51:57,120 --> 00:51:58,920
Speaker 1: Are they going to make Are they gonna mark that

870
00:51:59,040 --> 00:52:02,640
Speaker 1: as sense of content that you know could lead people

871
00:52:02,680 --> 00:52:06,000
Speaker 1: in the wrong direction? Friends, we've seen this now we

872
00:52:06,120 --> 00:52:10,080
Speaker 1: understand what they're really doing. We understand what the game

873
00:52:10,239 --> 00:52:15,200
Speaker 1: is that's being played, and we also see that the

874
00:52:15,920 --> 00:52:22,440
Speaker 1: tech totalitarians don't even recognize what they're doing when it's exposed.

875
00:52:22,440 --> 00:52:25,000
Speaker 1: When we see it, they don't really recognize it as wrong.

876
00:52:25,120 --> 00:52:28,000
Speaker 1: It's just, oh, we'll have to figure out another way

877
00:52:28,000 --> 00:52:32,080
Speaker 1: to do this suppression. Remember the Hunter Biden stories that

878
00:52:32,200 --> 00:52:36,080
Speaker 1: the New York New York Post broke and then were

879
00:52:36,400 --> 00:52:39,560
Speaker 1: blocked by Twitter and Facebook right before an election. I mean,

880
00:52:39,560 --> 00:52:42,839
Speaker 1: this is an kind contribution. It was to the Joe

881
00:52:42,880 --> 00:52:46,400
Speaker 1: Biden campaign by journalists so called, or by tech platform

882
00:52:46,400 --> 00:52:49,960
Speaker 1: in this case. And here's what Dorsey says about the

883
00:52:49,960 --> 00:52:54,240
Speaker 1: New York Post account being suspended Play six. When Twitter

884
00:52:54,520 --> 00:52:58,479
Speaker 1: is editing and censoring and silencing the New York Post.

885
00:52:58,560 --> 00:53:02,480
Speaker 1: The newspaper was a fourth highest circulation in the country

886
00:53:02,640 --> 00:53:05,440
Speaker 1: and Politico one of the leading newspapers in the country.

887
00:53:05,719 --> 00:53:08,080
Speaker 1: Is Twitter behaving as a publisher when it's deciding what

888
00:53:08,239 --> 00:53:11,120
Speaker 1: stories reporters are allowed to write and publish and what

889
00:53:11,200 --> 00:53:14,759
Speaker 1: stories they're not. No, and that account is not suspended

890
00:53:15,280 --> 00:53:18,120
Speaker 1: if I allow follow up the hacked materials policy. Um,

891
00:53:18,320 --> 00:53:20,640
Speaker 1: we realized that there was an error in that policy.

892
00:53:20,719 --> 00:53:24,800
Speaker 1: And hold on. I'm literally looking at the tweet from

893
00:53:24,840 --> 00:53:27,719
Speaker 1: Twitter that says your account has been locked. You're you're

894
00:53:27,760 --> 00:53:31,960
Speaker 1: telling me that this is not us. That's a lock

895
00:53:32,080 --> 00:53:35,279
Speaker 1: and can be unlocked when you to lead, I understand

896
00:53:35,320 --> 00:53:41,160
Speaker 1: that you lock your account for posting true information. That's

897
00:53:41,160 --> 00:53:43,080
Speaker 1: where we are with the tech gives. I remember when

898
00:53:43,120 --> 00:53:44,879
Speaker 1: the libs said that this was a conspiracy a few

899
00:53:44,920 --> 00:53:47,640
Speaker 1: years ago, there was any bias in big tech. They

900
00:53:47,640 --> 00:53:50,960
Speaker 1: were all liars and idiots. Now it's all proven. But

901
00:53:51,080 --> 00:53:54,720
Speaker 1: guess what Big tech doesn't want to change. Friends. Thanks

902
00:53:54,719 --> 00:53:58,000
Speaker 1: for listening to The Bus Sesson Show podcasts. Remember to

903
00:53:58,040 --> 00:54:01,880
Speaker 1: subscribe on Apple podcasts, the iHeartRadio app, or wherever you

904
00:54:01,960 --> 00:54:07,000
Speaker 1: get your podcasts. Some fiery moments yesterday on Capitol Hill

905
00:54:07,280 --> 00:54:12,440
Speaker 1: as Mark Zuckerberg of Facebook was once again facing lawmakers,

906
00:54:12,480 --> 00:54:17,160
Speaker 1: including a Senator Marsha Blackburne, who is with us now

907
00:54:17,280 --> 00:54:20,200
Speaker 1: from the great state of Tennessee. Senator Blackburn, thanks so

908
00:54:20,239 --> 00:54:23,560
Speaker 1: much for joining. I am thrilled to join you. Thank

909
00:54:23,600 --> 00:54:28,160
Speaker 1: you so much. So, what was the single biggest moment

910
00:54:28,280 --> 00:54:30,960
Speaker 1: that you saw that people should be aware of yesterday?

911
00:54:31,000 --> 00:54:33,960
Speaker 1: During those those hearings, you know, they went on for

912
00:54:34,040 --> 00:54:36,280
Speaker 1: quite some time. Most people didn't have time to watch

913
00:54:36,320 --> 00:54:39,239
Speaker 1: at all. Are we at a point now where big

914
00:54:39,280 --> 00:54:43,360
Speaker 1: Tech realizes, Senator, that some of their practices have to change.

915
00:54:43,719 --> 00:54:47,880
Speaker 1: I think the biggest moment from yesterday was one that

916
00:54:48,040 --> 00:54:53,240
Speaker 1: came through the collective of looking at this hearing book.

917
00:54:53,680 --> 00:54:58,719
Speaker 1: You saw them pretty much admit that, yes, they are

918
00:54:58,800 --> 00:55:03,520
Speaker 1: doing some blocking and throttling and censoring, but they think

919
00:55:03,520 --> 00:55:10,080
Speaker 1: it's okay because they are getting into the business of publishing,

920
00:55:10,760 --> 00:55:14,800
Speaker 1: which through their statements they admit that they are doing

921
00:55:15,719 --> 00:55:23,000
Speaker 1: this because they're editorializing. Well, editorializing is creating content, and

922
00:55:23,080 --> 00:55:26,719
Speaker 1: that is not where they are supposed to be. They

923
00:55:26,719 --> 00:55:31,280
Speaker 1: are information services. They are to be the new town square.

924
00:55:31,960 --> 00:55:35,560
Speaker 1: Town squares need a cop on the beat to make

925
00:55:35,680 --> 00:55:38,680
Speaker 1: certain that you have the point the counterpoint, and it's

926
00:55:38,800 --> 00:55:42,080
Speaker 1: done in the civil manner. And Senator, what would you

927
00:55:42,120 --> 00:55:44,759
Speaker 1: like to see happen now, because one of the questions

928
00:55:44,800 --> 00:55:48,640
Speaker 1: that keeps coming up after these hearings is what now

929
00:55:48,880 --> 00:55:53,680
Speaker 1: we've seen, whether it's Jack Dorsey of Twitter, Mark Zuckerberg

930
00:55:53,760 --> 00:55:57,720
Speaker 1: of Facebook, we see these tech CEOs now the CEO

931
00:55:57,760 --> 00:56:01,920
Speaker 1: of Google. They'll go on Capitol Hill and they have

932
00:56:02,040 --> 00:56:04,279
Speaker 1: these moments where we see exactly what you're saying, that

933
00:56:04,280 --> 00:56:08,759
Speaker 1: they're blurring a line between platform and publisher. There's clear bias.

934
00:56:08,800 --> 00:56:11,239
Speaker 1: They used to say there wasn't bias, it was just algorithms.

935
00:56:11,239 --> 00:56:13,839
Speaker 1: Now we know that's not true. But it feels like

936
00:56:13,960 --> 00:56:17,279
Speaker 1: not a lot changes. How can things change? Center? How

937
00:56:17,320 --> 00:56:19,319
Speaker 1: would you like to see them change? When it comes

938
00:56:19,360 --> 00:56:23,640
Speaker 1: to big tech. There are two pieces of legislation that

939
00:56:23,800 --> 00:56:28,520
Speaker 1: I have authored that are moving through the process right now.

940
00:56:29,080 --> 00:56:33,160
Speaker 1: One is in Commerce Committee and it is a privacy bill,

941
00:56:33,560 --> 00:56:37,680
Speaker 1: and it is pretty much centered around legislation I started

942
00:56:37,680 --> 00:56:41,440
Speaker 1: working on eight years ago. It's called the Browser Act.

943
00:56:42,000 --> 00:56:46,279
Speaker 1: And what the Privacy Bill will do is to have

944
00:56:46,520 --> 00:56:51,160
Speaker 1: one set of privacy standards and federal preemption that's for

945
00:56:51,320 --> 00:56:56,560
Speaker 1: the entire Internet ecosystem. Then it's going to have one regulator,

946
00:56:56,800 --> 00:57:01,120
Speaker 1: the FTC. It is going to put in the consumers

947
00:57:01,120 --> 00:57:07,200
Speaker 1: hand the online user's hand the ability to opt in

948
00:57:07,680 --> 00:57:12,040
Speaker 1: if they want to share data and information, and then

949
00:57:12,080 --> 00:57:17,840
Speaker 1: to opt out on nonsensitive information things like tracking and

950
00:57:17,920 --> 00:57:23,320
Speaker 1: so that way, it will change Big texts approach. It

951
00:57:23,440 --> 00:57:27,080
Speaker 1: is going to change their business model, but it's a

952
00:57:27,160 --> 00:57:31,680
Speaker 1: good change. It is in favor of the consumer. Now.

953
00:57:31,760 --> 00:57:35,800
Speaker 1: The second bill moving through is one that does reform

954
00:57:35,960 --> 00:57:40,600
Speaker 1: section to thirty. It is a good piece of legislation.

955
00:57:40,800 --> 00:57:44,840
Speaker 1: It is called the Online Freedom and Viewpoint Diversity Bill,

956
00:57:45,360 --> 00:57:50,360
Speaker 1: and Senator Lindsay Graham and Senator Roger Wicker, the Chairman

957
00:57:50,400 --> 00:57:53,880
Speaker 1: of Commerce and the Chairman of Judiciary, have joined me

958
00:57:53,960 --> 00:57:58,400
Speaker 1: on that bill. It would be very specificous to who

959
00:57:58,480 --> 00:58:02,360
Speaker 1: can use the libe ability protection in section to thirty.

960
00:58:02,400 --> 00:58:05,880
Speaker 1: In flind they can use it. It would also eliminate

961
00:58:05,960 --> 00:58:10,120
Speaker 1: this subjectiveness that big tech hides behind and says, well

962
00:58:10,160 --> 00:58:15,240
Speaker 1: we have community standards, well, we have terms of service.

963
00:58:15,960 --> 00:58:21,160
Speaker 1: And it would be very specific and the reasons that

964
00:58:21,320 --> 00:58:25,920
Speaker 1: you have to exercise some kind of censorship, because it

965
00:58:25,920 --> 00:58:29,400
Speaker 1: would spell out it has to be unlawful conduct, it

966
00:58:29,480 --> 00:58:35,640
Speaker 1: has to cause incentivized terrorism, or lead to personal harm.

967
00:58:36,200 --> 00:58:39,960
Speaker 1: Those would be the reasons for being able to censor something.

968
00:58:40,400 --> 00:58:44,800
Speaker 1: That bill is scheduled for a markup in Judiciary Committee tomorrow.

969
00:58:45,120 --> 00:58:50,000
Speaker 1: We're speaking of Senator Marsha Blackburne of Tennessee. Senator, what

970
00:58:50,280 --> 00:58:53,520
Speaker 1: is the Democrat response? I mean, from your colleagues in

971
00:58:53,560 --> 00:58:57,080
Speaker 1: the Senate, for example, with what you're talking about? Here

972
00:58:56,800 --> 00:58:59,600
Speaker 1: are some of them on board? And for the ones

973
00:58:59,640 --> 00:59:02,600
Speaker 1: who aren't, why would they object to what seemed like

974
00:59:02,720 --> 00:59:05,800
Speaker 1: very common sense ways to address big tech censorship that

975
00:59:05,840 --> 00:59:09,560
Speaker 1: we all know? Is there? Well? Money, money, money is

976
00:59:09,600 --> 00:59:14,360
Speaker 1: the reason. And the majority of contributions that have been

977
00:59:14,400 --> 00:59:19,240
Speaker 1: given by big tech employees and their CEOs have all

978
00:59:19,280 --> 00:59:23,240
Speaker 1: gone to Democrats, and so the Democratic Party has been

979
00:59:23,360 --> 00:59:27,800
Speaker 1: very hesitant to tackle these issues that consumers want to

980
00:59:27,800 --> 00:59:31,920
Speaker 1: see addressed. So they're just looking to keep things exactly

981
00:59:31,960 --> 00:59:34,560
Speaker 1: as they are. That's discouraging, but I think we are

982
00:59:35,000 --> 00:59:37,880
Speaker 1: que serves them well, right, Well, we saw that obviously

983
00:59:37,920 --> 00:59:40,080
Speaker 1: with the suppression efforts in the run up to the

984
00:59:40,080 --> 00:59:44,600
Speaker 1: election and Twitter removing that or suppressing that story about

985
00:59:44,640 --> 00:59:46,720
Speaker 1: a hunter Biden, and so it's all out there for

986
00:59:46,760 --> 00:59:49,800
Speaker 1: everybody to see. Hopefully we'll be able to advance the

987
00:59:49,920 --> 00:59:52,800
Speaker 1: legislation and the changes that you're talking about. But big

988
00:59:52,800 --> 00:59:54,840
Speaker 1: tech is very powerful and they have a lot of sway,

989
00:59:54,920 --> 00:59:58,080
Speaker 1: not just with money, but obviously also with perception and

990
00:59:58,160 --> 01:00:02,040
Speaker 1: moving the national conversation in days that really the mainstream

991
01:00:02,040 --> 01:00:04,120
Speaker 1: media I think is jealous of These days, Facebook and

992
01:00:04,160 --> 01:00:06,400
Speaker 1: Twitter much more powerful. But Senator, I also want to

993
01:00:06,400 --> 01:00:09,320
Speaker 1: ask you about the other big issue this week in

994
01:00:09,360 --> 01:00:11,360
Speaker 1: the news going on now for a couple of weeks,

995
01:00:11,760 --> 01:00:17,880
Speaker 1: these recounts lawsuits that continued battle over who really won

996
01:00:18,320 --> 01:00:22,840
Speaker 1: based on legal ballots this last presidential election. You have

997
01:00:22,880 --> 01:00:26,040
Speaker 1: some experience, not just running for US Senate and being

998
01:00:26,080 --> 01:00:30,120
Speaker 1: in office, you have experienced working on election commissions. How

999
01:00:30,160 --> 01:00:32,600
Speaker 1: concerned are you based on what you've heard so far

1000
01:00:32,800 --> 01:00:35,880
Speaker 1: about the legitimacy of the vote counts in some of

1001
01:00:35,920 --> 01:00:39,640
Speaker 1: these states that are contested still well, and I have

1002
01:00:39,720 --> 01:00:43,920
Speaker 1: no doubt if every legal vote was counted in every

1003
01:00:44,040 --> 01:00:49,120
Speaker 1: illegally cast ballot was thrown out, President Donald Trump would

1004
01:00:49,160 --> 01:00:53,080
Speaker 1: have four more years. What we have seen happen is

1005
01:00:53,160 --> 01:00:57,400
Speaker 1: some of these communities were not careful in mailing out

1006
01:00:57,440 --> 01:01:02,000
Speaker 1: the ballots. Basically, what they did was to mail one

1007
01:01:02,080 --> 01:01:06,400
Speaker 1: to everybody. It was like a publisher's clearing house, sweep

1008
01:01:06,480 --> 01:01:09,560
Speaker 1: steak's notice. Fill it out, send it in if you

1009
01:01:09,640 --> 01:01:13,080
Speaker 1: want to participate and that is not what is intended

1010
01:01:13,080 --> 01:01:16,880
Speaker 1: for our right to vote. And everybody got one. You

1011
01:01:16,920 --> 01:01:19,240
Speaker 1: know what. I have talked to people that got three

1012
01:01:19,280 --> 01:01:24,080
Speaker 1: and four at their home because they went to former residences.

1013
01:01:24,120 --> 01:01:26,400
Speaker 1: I talked to someone who lives in one of these

1014
01:01:26,480 --> 01:01:32,320
Speaker 1: Blue cities and they had been in their house eleven years.

1015
01:01:32,480 --> 01:01:35,760
Speaker 1: The previous owner, the only other person that had ever

1016
01:01:35,880 --> 01:01:41,600
Speaker 1: owned their home, died twelve years ago. That deceased individual

1017
01:01:41,680 --> 01:01:47,040
Speaker 1: who's been deceased twelve years received about in the mail.

1018
01:01:47,720 --> 01:01:52,480
Speaker 1: What you're going to see happen. This issue will pivot

1019
01:01:52,600 --> 01:01:56,280
Speaker 1: to the states, and these state legislatures are going to

1020
01:01:56,320 --> 01:01:59,520
Speaker 1: have to put some things in place that require these

1021
01:01:59,720 --> 01:02:03,440
Speaker 1: local election commissions to clean up their roles and to

1022
01:02:03,520 --> 01:02:07,800
Speaker 1: make certain that only individuals who are allowed to vote

1023
01:02:07,840 --> 01:02:11,480
Speaker 1: are getting about to vote. Now, that would be for

1024
01:02:11,600 --> 01:02:14,040
Speaker 1: the future, which is obviously very important. We all want

1025
01:02:14,040 --> 01:02:16,720
Speaker 1: to have faith in our future elections. But Senator, for

1026
01:02:16,880 --> 01:02:20,680
Speaker 1: this most recent election, just based on what you've seen

1027
01:02:20,920 --> 01:02:23,640
Speaker 1: and what you believe, some of the let's call them

1028
01:02:23,640 --> 01:02:27,480
Speaker 1: proven irregularities already have been and the possible fraud that

1029
01:02:27,560 --> 01:02:33,720
Speaker 1: still remains to be conclusively proven, is it too late?

1030
01:02:34,480 --> 01:02:37,800
Speaker 1: Did we essentially did the Democrats with these changes because

1031
01:02:37,840 --> 01:02:40,880
Speaker 1: of COVID in the way that we did voting will

1032
01:02:40,960 --> 01:02:43,640
Speaker 1: it be almost impossible to prove the kind of things

1033
01:02:43,680 --> 01:02:47,360
Speaker 1: you're talking about. The lawsuits are filed. There are some

1034
01:02:47,440 --> 01:02:50,840
Speaker 1: by the Trump campaign, there are some by individuals who

1035
01:02:50,880 --> 01:02:56,480
Speaker 1: witnessed irregularities, and they are gathering their information. They have

1036
01:02:56,680 --> 01:03:00,520
Speaker 1: from now until the time the Electoral College will meet,

1037
01:03:00,800 --> 01:03:03,560
Speaker 1: and prior to that, your states are going to be

1038
01:03:03,600 --> 01:03:08,040
Speaker 1: certifying these elections. I mean, look at the fact that

1039
01:03:08,120 --> 01:03:13,040
Speaker 1: Georgia found six thousand ballots that had not been counted,

1040
01:03:13,600 --> 01:03:17,200
Speaker 1: and out of that the majority of those ballots went

1041
01:03:17,280 --> 01:03:20,880
Speaker 1: to Donald Trump. It certainly seems like if they could

1042
01:03:20,880 --> 01:03:23,720
Speaker 1: find six thousand here and six thousand there, there's a

1043
01:03:23,720 --> 01:03:26,200
Speaker 1: lot more reason to dig into this and make sure

1044
01:03:26,240 --> 01:03:27,880
Speaker 1: that we got the right vote count in the end.

1045
01:03:28,160 --> 01:03:31,360
Speaker 1: Senator Marsha Blackburn, everybody of Tennessee. Senator, we really appreciate

1046
01:03:31,360 --> 01:03:33,560
Speaker 1: your time. Thanks for joining us today. Good to be

1047
01:03:33,640 --> 01:03:38,200
Speaker 1: with you. Thank you, bye bye. Now you're in the

1048
01:03:38,320 --> 01:03:45,440
Speaker 1: Freedom Mind. This is the Buck Sexton Show podcast. What

1049
01:03:45,560 --> 01:03:50,080
Speaker 1: do the Democrats think of the usage of big tech?

1050
01:03:50,120 --> 01:03:52,560
Speaker 1: We were just speaking about this before we had Senator

1051
01:03:52,600 --> 01:03:55,440
Speaker 1: Blackburn on let's talk about this. What do the Democrats

1052
01:03:55,480 --> 01:03:58,680
Speaker 1: think of it? They like it. You have to remember

1053
01:03:58,800 --> 01:04:02,640
Speaker 1: this isn't something that we've identified that both sides can

1054
01:04:02,680 --> 01:04:06,479
Speaker 1: agree is a problem. The problem is that now people

1055
01:04:06,640 --> 01:04:10,040
Speaker 1: understand what's going on because they much preferred the old way.

1056
01:04:10,320 --> 01:04:14,480
Speaker 1: The Democrats liked it when their news stories and their

1057
01:04:14,520 --> 01:04:18,919
Speaker 1: information would be shared freely all over the internet, and

1058
01:04:19,000 --> 01:04:24,680
Speaker 1: somehow Twitter and Facebook would decide that they wouldn't share

1059
01:04:25,040 --> 01:04:27,080
Speaker 1: conservative stuff where that they would throttle it or they

1060
01:04:27,080 --> 01:04:30,480
Speaker 1: would shadow bandit, and people didn't really know exactly what's

1061
01:04:30,520 --> 01:04:34,000
Speaker 1: going on. I can't even tell you how much on Parlor,

1062
01:04:34,040 --> 01:04:36,560
Speaker 1: for example, the Parlor app. And I've thought this was

1063
01:04:36,560 --> 01:04:38,840
Speaker 1: true for a long time. I mean, there are blue

1064
01:04:38,920 --> 01:04:43,439
Speaker 1: check journals that have pretty big followings on Twitter and

1065
01:04:43,600 --> 01:04:46,000
Speaker 1: nobody knows who the heck these people are, and nobody cares.

1066
01:04:46,640 --> 01:04:50,680
Speaker 1: But they've got hundreds of thousands of followers, and they've

1067
01:04:50,680 --> 01:04:52,640
Speaker 1: had them for a long time. And I remember I've

1068
01:04:52,640 --> 01:04:55,680
Speaker 1: been on Twitter now for what going on nine years,

1069
01:04:56,600 --> 01:04:58,640
Speaker 1: and it took a long time to build up the

1070
01:04:58,640 --> 01:05:03,040
Speaker 1: following that I have right now. On Parlor, I've been

1071
01:05:03,040 --> 01:05:04,440
Speaker 1: in Parlor for a matter of months. I've already got

1072
01:05:04,440 --> 01:05:07,200
Speaker 1: two hundred thousand followers more than that, I mean, and

1073
01:05:07,240 --> 01:05:08,720
Speaker 1: it just keeps going up and up and up, and

1074
01:05:08,800 --> 01:05:11,880
Speaker 1: everything I post on parlor just goes off like a

1075
01:05:11,960 --> 01:05:14,760
Speaker 1: rocket ship because people are, Oh, they're interacting with it,

1076
01:05:14,800 --> 01:05:17,000
Speaker 1: they want to share it, they want to I've had

1077
01:05:17,040 --> 01:05:18,960
Speaker 1: so many things on Twitter. I go, wait a second,

1078
01:05:19,200 --> 01:05:22,520
Speaker 1: this is not How is this not having more of

1079
01:05:22,520 --> 01:05:26,160
Speaker 1: a reach considering how it's reacted to by the people

1080
01:05:26,160 --> 01:05:30,760
Speaker 1: who do see it. The algorithms have been skewed against us.

1081
01:05:30,840 --> 01:05:35,919
Speaker 1: It's obvious. That's another reason why they hate the competitors

1082
01:05:35,920 --> 01:05:39,400
Speaker 1: that are popping up. Now, what way could you prove

1083
01:05:39,480 --> 01:05:43,200
Speaker 1: before that conservative content was being throught older shadow band?

1084
01:05:43,560 --> 01:05:45,760
Speaker 1: How would you be in a position to show that

1085
01:05:46,360 --> 01:05:50,800
Speaker 1: if the only platforms you could go to were controlled

1086
01:05:51,160 --> 01:05:57,280
Speaker 1: completely dominated by Libs, How, oh you couldn't. Now that's

1087
01:05:57,280 --> 01:06:00,320
Speaker 1: starting to change a little bit, and the Democrats are

1088
01:06:00,360 --> 01:06:03,600
Speaker 1: realizing that this was the sneaky advantage that they had had.

1089
01:06:03,640 --> 01:06:05,320
Speaker 1: We figured out after a while. It took us a

1090
01:06:05,360 --> 01:06:10,520
Speaker 1: long time. At the mainstream media is effectively a Democrat superpack.

1091
01:06:11,880 --> 01:06:15,720
Speaker 1: We know that people maybe fought that idea in the nineties,

1092
01:06:16,040 --> 01:06:18,040
Speaker 1: in the early two thousands. They would say, oh no,

1093
01:06:18,160 --> 01:06:21,640
Speaker 1: come on, journalism. Journalism, it's a real thing now. I mean,

1094
01:06:21,680 --> 01:06:24,160
Speaker 1: if you think that journos are unbiased, you just don't

1095
01:06:24,200 --> 01:06:27,400
Speaker 1: know what you're talking about. It's not a defensable position.

1096
01:06:27,440 --> 01:06:31,560
Speaker 1: It's laughable, it's silly. But big tech started to fill

1097
01:06:31,600 --> 01:06:35,360
Speaker 1: in that void for them. Big tech became the advantage

1098
01:06:35,400 --> 01:06:40,560
Speaker 1: that they had that they pretended they did not have. Right,

1099
01:06:40,680 --> 01:06:42,560
Speaker 1: Big tech became this thing that they would point to

1100
01:06:42,600 --> 01:06:46,320
Speaker 1: and they'd say, oh, well, this is just algorithms. It's

1101
01:06:46,360 --> 01:06:51,000
Speaker 1: not people making these decisions. It's not that there's something

1102
01:06:51,040 --> 01:06:54,440
Speaker 1: that we've done or we've decided, being the CEOs and

1103
01:06:54,480 --> 01:06:57,560
Speaker 1: the people behind the scenes at these tech companies. It's

1104
01:06:57,600 --> 01:07:00,480
Speaker 1: just the way it is. It's the computers doing it, basically,

1105
01:07:01,600 --> 01:07:04,080
Speaker 1: That's what they were saying. And think about how much

1106
01:07:04,120 --> 01:07:07,800
Speaker 1: that's helped things like grow, Like I mean, the Huffington

1107
01:07:07,840 --> 01:07:09,360
Speaker 1: Post is a trash heap. I mean, this is a

1108
01:07:09,400 --> 01:07:14,920
Speaker 1: garbage website, always has been, but had an enormous assistance

1109
01:07:15,040 --> 01:07:18,760
Speaker 1: from Facebook. You've seen some of these these liberal news

1110
01:07:18,800 --> 01:07:23,040
Speaker 1: outlets that have grown tremendously in their reach over time

1111
01:07:23,080 --> 01:07:26,560
Speaker 1: and become prominent and you know, brought in a lot

1112
01:07:26,600 --> 01:07:28,520
Speaker 1: of revenue, although they usually spend a lot of revenue

1113
01:07:28,520 --> 01:07:30,960
Speaker 1: off and more than they break in. And it's because

1114
01:07:31,080 --> 01:07:34,200
Speaker 1: they have free reign on Facebook. You know, somehow we've

1115
01:07:34,200 --> 01:07:36,840
Speaker 1: created a media ecosystem in this country, and it's not

1116
01:07:36,880 --> 01:07:40,080
Speaker 1: just news media, but a media ecosystem where the left

1117
01:07:40,520 --> 01:07:43,880
Speaker 1: can do whatever it wants, say whatever it wants, no consequences,

1118
01:07:44,240 --> 01:07:50,480
Speaker 1: gets maximum exposure on both the new and the established platforms,

1119
01:07:50,520 --> 01:07:55,240
Speaker 1: and can count on blue chip advertisers from large from

1120
01:07:55,240 --> 01:07:58,439
Speaker 1: major corporations, major companies to advertise with them, to stick

1121
01:07:58,520 --> 01:08:01,080
Speaker 1: by them. On the right, we have to worry about

1122
01:08:01,120 --> 01:08:04,840
Speaker 1: boycotts and there's the brand damage. Meanwhile, we represent half

1123
01:08:04,840 --> 01:08:08,000
Speaker 1: the country, but we have to deal with all these

1124
01:08:08,000 --> 01:08:10,840
Speaker 1: additional challenges and all this other bullcrap that's going on,

1125
01:08:11,520 --> 01:08:14,520
Speaker 1: and we still in the marketplace of ideas, crush those

1126
01:08:14,560 --> 01:08:18,960
Speaker 1: fools on a whole range of issues. But they have

1127
01:08:19,040 --> 01:08:21,760
Speaker 1: far more places to make the argument, and they have

1128
01:08:21,840 --> 01:08:26,040
Speaker 1: far more people who are wildly overpaid to do things

1129
01:08:26,080 --> 01:08:28,360
Speaker 1: that they're not even that good at. But they just

1130
01:08:28,479 --> 01:08:32,400
Speaker 1: have more slots. They have more places that are more

1131
01:08:32,439 --> 01:08:37,080
Speaker 1: easily monetized because of these built in advantages for the left.

1132
01:08:37,120 --> 01:08:39,200
Speaker 1: I mean this stuff. I understand some of this might

1133
01:08:39,240 --> 01:08:41,400
Speaker 1: sound a little bit like inside baseball to somebody works

1134
01:08:41,400 --> 01:08:44,360
Speaker 1: in media, but this stuff really matters. This is how

1135
01:08:44,479 --> 01:08:48,800
Speaker 1: Joe Biden, that clown, can even think about winning an

1136
01:08:48,800 --> 01:08:53,120
Speaker 1: election against Donald Trump because of these advantages that I'm

1137
01:08:53,120 --> 01:08:56,479
Speaker 1: telling you about. And it extends to other issues as well.

1138
01:08:56,520 --> 01:09:00,479
Speaker 1: It's not just on the presidential election. Here Senator Coons

1139
01:09:01,360 --> 01:09:05,680
Speaker 1: talking to Jack Dorsey about how there are other areas

1140
01:09:05,960 --> 01:09:08,840
Speaker 1: where he wants I mean, the Democrats want censorship in

1141
01:09:08,880 --> 01:09:13,439
Speaker 1: their favor. They think that Facebook and these other places

1142
01:09:13,520 --> 01:09:17,479
Speaker 1: there's a home court advantage that's supposed to that they're

1143
01:09:17,479 --> 01:09:19,760
Speaker 1: supposed to have all the time, and Senator Coons of

1144
01:09:19,800 --> 01:09:22,320
Speaker 1: Delaware is one of them. Play five. I just I

1145
01:09:22,400 --> 01:09:28,160
Speaker 1: cannot think of a greater harm than climate change, which

1146
01:09:28,240 --> 01:09:31,000
Speaker 1: is transforming literally our planet and causing harm to our

1147
01:09:31,120 --> 01:09:34,920
Speaker 1: entire world. I think we're experiencing significant harm as we speak.

1148
01:09:34,960 --> 01:09:39,960
Speaker 1: I recognize the pandemic and misinformation about COVID nineteen manipulated

1149
01:09:40,000 --> 01:09:43,240
Speaker 1: media also cause harm, but I'd urge you to reconsider

1150
01:09:43,280 --> 01:09:47,960
Speaker 1: that because helping to disseminate climate denialism, in my view,

1151
01:09:48,960 --> 01:09:52,599
Speaker 1: further facilitates and accelerates one of the greatest existential threats

1152
01:09:52,600 --> 01:09:58,479
Speaker 1: to our world. So sensor climate change questions, climate change

1153
01:09:58,520 --> 01:10:02,400
Speaker 1: opinions on your platform or because it's an existential threat.

1154
01:10:02,560 --> 01:10:08,040
Speaker 1: There is only one acceptable opinion on climate change, and

1155
01:10:08,040 --> 01:10:10,920
Speaker 1: it's whatever the heck they say it is, whatever the

1156
01:10:10,960 --> 01:10:14,400
Speaker 1: Democrat Party could census. Is on any issue, whatever the

1157
01:10:14,479 --> 01:10:17,680
Speaker 1: left and the statists decide. You'd say, well, hold on,

1158
01:10:17,720 --> 01:10:22,320
Speaker 1: what about if somebody says that climate emissions have to

1159
01:10:22,400 --> 01:10:25,720
Speaker 1: be reduced fifty percent in the next thirty years, but

1160
01:10:25,880 --> 01:10:28,160
Speaker 1: I say, no, we can get there to the same

1161
01:10:28,200 --> 01:10:30,880
Speaker 1: place and we reduce at twenty five percent because of

1162
01:10:30,920 --> 01:10:33,320
Speaker 1: the following technologies that are already getting cleaner. Are they

1163
01:10:33,360 --> 01:10:35,280
Speaker 1: going to censor that? The answers, yes. Under their logic,

1164
01:10:35,360 --> 01:10:38,840
Speaker 1: they have to censor that one approved opinion, just like

1165
01:10:38,880 --> 01:10:43,360
Speaker 1: we're in communist China. One approved opinion allowed, that's it.

1166
01:10:44,160 --> 01:10:49,120
Speaker 1: Other opinions shut down because they're an existential threat. Listen

1167
01:10:49,160 --> 01:10:51,400
Speaker 1: to these little totalitarians. Listen to the way they talk

1168
01:10:51,400 --> 01:10:55,240
Speaker 1: about these things. The free exchange of ideas, intellectual discourse,

1169
01:10:55,680 --> 01:11:02,480
Speaker 1: free inquiry. These are under assault by the Democrat establishment

1170
01:11:02,560 --> 01:11:08,680
Speaker 1: in America every single day, openly. Now, this is a

1171
01:11:08,720 --> 01:11:12,680
Speaker 1: fight for the most basic intellectual freedom and if we

1172
01:11:12,840 --> 01:11:16,920
Speaker 1: don't take up our side, we will lose. Thanks for

1173
01:11:17,000 --> 01:11:20,800
Speaker 1: listening to The Busson Show podcast. Remember to subscribe on

1174
01:11:20,880 --> 01:11:25,160
Speaker 1: Apple podcasts, the iHeartRadio app, or wherever you get your podcasts.

1175
01:11:26,360 --> 01:11:31,200
Speaker 1: Were the machines not tabulating the votes correctly? Was there

1176
01:11:31,240 --> 01:11:33,560
Speaker 1: a problem here with the vote count that has to

1177
01:11:33,600 --> 01:11:37,000
Speaker 1: do with the software, the company's involved, and other allegations

1178
01:11:37,040 --> 01:11:40,040
Speaker 1: out there? Who better to ask about this than somebody

1179
01:11:40,040 --> 01:11:42,280
Speaker 1: who gets to the bottom of things and has for

1180
01:11:42,320 --> 01:11:45,519
Speaker 1: a very long time. Sarah Carter, my friend joins us now.

1181
01:11:45,560 --> 01:11:48,400
Speaker 1: She's the host of the Sarah Carter Show. Sarah a

1182
01:11:48,680 --> 01:11:52,599
Speaker 1: Carter dot com for her latest investigative journalism. Sarah, thanks

1183
01:11:52,600 --> 01:11:55,200
Speaker 1: so much. Oh, thanks so much for having me on

1184
01:11:55,240 --> 01:11:57,559
Speaker 1: the Showbuck. It's so great talking to you, even though

1185
01:11:57,840 --> 01:12:00,639
Speaker 1: these are really trying times for a lot of AMA. Yeah,

1186
01:12:00,680 --> 01:12:03,280
Speaker 1: they are so, Sarah, What, from what you're seeing in

1187
01:12:03,280 --> 01:12:06,000
Speaker 1: your sources and what you've been able to on cover

1188
01:12:06,160 --> 01:12:11,479
Speaker 1: so far, what are the biggest concerns right now in

1189
01:12:12,880 --> 01:12:16,400
Speaker 1: you know, with regard to these vote counts. Well, I

1190
01:12:16,400 --> 01:12:19,800
Speaker 1: think there's a number of concerns. One, we've heard that

1191
01:12:19,920 --> 01:12:25,040
Speaker 1: there have been serious issues with allegedly with the software

1192
01:12:25,520 --> 01:12:27,920
Speaker 1: and the voting machines that were used in this election.

1193
01:12:28,080 --> 01:12:32,520
Speaker 1: That would be Dominion Voting Systems and Smart Madic. Smartmadock

1194
01:12:32,760 --> 01:12:35,519
Speaker 1: was the company that developed the software for everybody out

1195
01:12:35,520 --> 01:12:37,679
Speaker 1: there who's trying to figure out all of these new

1196
01:12:38,080 --> 01:12:43,480
Speaker 1: companies and words. So Smartmadic allegedly developed the original software

1197
01:12:43,920 --> 01:12:48,720
Speaker 1: that Dominion Voting Systems is connected to. Dominion Voting Systems

1198
01:12:49,000 --> 01:12:52,720
Speaker 1: is used in because forty percent of the American electorate

1199
01:12:53,400 --> 01:12:57,839
Speaker 1: used Dominion Voting Systems in this general election. That's twenty

1200
01:12:57,880 --> 01:13:01,320
Speaker 1: eight states, So that's a lot of right, that's a

1201
01:13:01,360 --> 01:13:04,479
Speaker 1: lot of people that we're using this system. Now we

1202
01:13:04,560 --> 01:13:09,200
Speaker 1: have Sidney Powell, awesome attorney, probably one of the best

1203
01:13:09,240 --> 01:13:14,000
Speaker 1: litigators in the country right now, obviously a big champion

1204
01:13:14,080 --> 01:13:18,719
Speaker 1: of President Donald Trump. Also defending Lieutenant General Michael Flynn.

1205
01:13:18,840 --> 01:13:24,519
Speaker 1: She has been in his case against the former Obama

1206
01:13:24,560 --> 01:13:29,559
Speaker 1: administration DJ Robert Muller trial. Now she's on this now

1207
01:13:29,640 --> 01:13:34,480
Speaker 1: she's focused on helping the president and helping the administration

1208
01:13:34,800 --> 01:13:38,320
Speaker 1: of what they believe and what they are alleging systemic

1209
01:13:38,360 --> 01:13:42,280
Speaker 1: fraud in the general election. Now that's Sydney Powell's argument.

1210
01:13:42,600 --> 01:13:45,559
Speaker 1: Jenna Ellis is on the team with her. Former mayor

1211
01:13:45,640 --> 01:13:49,040
Speaker 1: Rudy Giuliani is heading that team. He's also a very

1212
01:13:49,080 --> 01:13:52,439
Speaker 1: good friend of President Trump. Now, what they are saying

1213
01:13:52,880 --> 01:13:56,240
Speaker 1: is that this system is rigged in such a way

1214
01:13:57,320 --> 01:14:01,679
Speaker 1: that it is almost impossible to proof. Although they say

1215
01:14:01,720 --> 01:14:05,080
Speaker 1: they have proof and affidavits, it is almost impossible to

1216
01:14:05,120 --> 01:14:09,600
Speaker 1: prove fraud. Now. They are saying this because they have

1217
01:14:09,640 --> 01:14:12,640
Speaker 1: been speaking to sources. Some of these sources I have

1218
01:14:12,760 --> 01:14:16,680
Speaker 1: spoken to as well. I have seen and read the affidavits,

1219
01:14:16,720 --> 01:14:19,880
Speaker 1: And now those affidavits are public, and anybody could go

1220
01:14:19,880 --> 01:14:22,200
Speaker 1: out there and read the book and go to my

1221
01:14:22,240 --> 01:14:25,080
Speaker 1: website Seracarter dot com. You can see the story and

1222
01:14:25,160 --> 01:14:28,120
Speaker 1: what Sidney Pale and Jenna Ellis are saying. Look, we

1223
01:14:28,160 --> 01:14:33,160
Speaker 1: are battling for every legitimate vote, every legitimate vote. This

1224
01:14:33,280 --> 01:14:36,880
Speaker 1: is a huge problem. They say, we need to investigate this.

1225
01:14:37,040 --> 01:14:40,960
Speaker 1: I agree with them. There is one affidavit of an

1226
01:14:41,840 --> 01:14:45,000
Speaker 1: the name is actually removed for the protection of this person,

1227
01:14:45,400 --> 01:14:48,759
Speaker 1: somebody that was actually very close to former Venezuelan dictator

1228
01:14:48,840 --> 01:14:51,639
Speaker 1: Hugo Chavez. And you're probably thinking, like, what what does

1229
01:14:51,640 --> 01:14:54,720
Speaker 1: that have to do with us? You know, well, according

1230
01:14:54,840 --> 01:15:00,360
Speaker 1: to this affidavit. The Smartmatic software was developed in the

1231
01:15:00,439 --> 01:15:04,439
Speaker 1: early two thousands at the direction of Hugo Chavez in

1232
01:15:04,520 --> 01:15:07,560
Speaker 1: his election. He wanted to be able to develop software

1233
01:15:07,880 --> 01:15:10,919
Speaker 1: that would allow him to steal the election without anybody

1234
01:15:10,960 --> 01:15:13,840
Speaker 1: being the wiser. The person in this affidavit, and I

1235
01:15:13,840 --> 01:15:18,160
Speaker 1: have spoken to people directly connected to this person, and

1236
01:15:18,240 --> 01:15:20,640
Speaker 1: I've known about this for a little bit more than

1237
01:15:20,680 --> 01:15:24,400
Speaker 1: a week now. This person was directly connected to Hugo

1238
01:15:24,479 --> 01:15:27,720
Speaker 1: Chavis and in the room when Hugo Chavis asked for

1239
01:15:27,720 --> 01:15:31,840
Speaker 1: this software to be developed with those developers. According to him,

1240
01:15:31,920 --> 01:15:35,760
Speaker 1: it is the same software. There's an underlying, like mirroring

1241
01:15:35,800 --> 01:15:40,320
Speaker 1: image of this software that actually allows the opposing political

1242
01:15:40,360 --> 01:15:43,519
Speaker 1: party or the party that is aware of what's going on,

1243
01:15:43,680 --> 01:15:45,760
Speaker 1: to kind of watch the votes. At least that's what

1244
01:15:45,840 --> 01:15:49,280
Speaker 1: happened in Venezuela. There have been issues with this software

1245
01:15:49,280 --> 01:15:52,599
Speaker 1: with dominion voting software. Texas would not use it because

1246
01:15:52,880 --> 01:15:54,800
Speaker 1: they felt that there were too many problems with the

1247
01:15:54,840 --> 01:15:58,000
Speaker 1: software and they felt that it was hackable. Now we

1248
01:15:58,080 --> 01:16:02,439
Speaker 1: know there's a Princeton professor. It's out there on YouTube.

1249
01:16:02,479 --> 01:16:05,600
Speaker 1: He was on Fox News. He's an IT expert. He

1250
01:16:05,720 --> 01:16:09,360
Speaker 1: showed how he could hack Dominion software within seven minutes

1251
01:16:10,320 --> 01:16:12,960
Speaker 1: if he had access to the actual machine and he

1252
01:16:13,120 --> 01:16:17,680
Speaker 1: showed how to do it. Dominion is claiming that that

1253
01:16:18,320 --> 01:16:22,519
Speaker 1: these allegations are completely false and that their software is valid.

1254
01:16:22,680 --> 01:16:24,960
Speaker 1: So now there's a big battle in the courts, and

1255
01:16:25,000 --> 01:16:27,639
Speaker 1: that's going to be Sydney's another side of this election problem.

1256
01:16:27,680 --> 01:16:29,559
Speaker 1: And I'll, you know, I'll try to make it quick,

1257
01:16:29,600 --> 01:16:32,679
Speaker 1: but is what's happening in Georgia and what's happening in Michigan.

1258
01:16:33,439 --> 01:16:36,160
Speaker 1: In Michigan, there are a lot of claims right now,

1259
01:16:36,200 --> 01:16:38,559
Speaker 1: and the numbers are showing it that there were way

1260
01:16:38,560 --> 01:16:41,840
Speaker 1: more voters than people registered. How did they explain that?

1261
01:16:42,360 --> 01:16:46,280
Speaker 1: You can't? That's a big problem. In Georgia, what we're

1262
01:16:46,280 --> 01:16:49,280
Speaker 1: seeing is and I just actually got off the phone

1263
01:16:49,280 --> 01:16:52,720
Speaker 1: with some people in Georgia that were marching actually to

1264
01:16:52,840 --> 01:16:57,280
Speaker 1: the state capitol. They are chanting stop the steal. They're

1265
01:16:57,280 --> 01:17:00,840
Speaker 1: actually out there with Democratic congressman and Jones, who's a

1266
01:17:00,840 --> 01:17:03,480
Speaker 1: big Trump supporter, to the chagrin of all the Democrats,

1267
01:17:03,760 --> 01:17:07,280
Speaker 1: and they're heading to the Secretary of State to his office,

1268
01:17:07,320 --> 01:17:11,160
Speaker 1: demanding to speak with him because right now in Georgia,

1269
01:17:11,320 --> 01:17:15,600
Speaker 1: there have been thousands of votes certainly over three thousand

1270
01:17:16,200 --> 01:17:20,920
Speaker 1: votes that have been discovered that were never processed. So

1271
01:17:20,960 --> 01:17:25,880
Speaker 1: basically they found memory cards, you know, that were never

1272
01:17:26,000 --> 01:17:31,360
Speaker 1: uploaded to these machines dominion voting systems that were just

1273
01:17:31,439 --> 01:17:34,360
Speaker 1: sitting there. One of them had thousands of votes, like

1274
01:17:34,439 --> 01:17:37,080
Speaker 1: twenty seven hundred votes, so those would have been twenty

1275
01:17:37,080 --> 01:17:42,080
Speaker 1: seven hundred voters that were disenfranchised. And then they found

1276
01:17:42,160 --> 01:17:45,120
Speaker 1: it in another county, and then they founded in Walton County,

1277
01:17:45,120 --> 01:17:47,400
Speaker 1: And I could tell you I was talking to Marcy McCarthy.

1278
01:17:47,760 --> 01:17:52,839
Speaker 1: She was an observer actually in a Dacab County, Georgia.

1279
01:17:53,000 --> 01:17:56,040
Speaker 1: She was on the floor calling me all the time,

1280
01:17:56,400 --> 01:17:58,799
Speaker 1: telling me what was going on whenever she had a break,

1281
01:17:59,160 --> 01:18:01,920
Speaker 1: and it was very frustrating for her. She couldn't even

1282
01:18:01,960 --> 01:18:06,320
Speaker 1: see what they were doing. Those were the counters tabulating

1283
01:18:06,360 --> 01:18:08,320
Speaker 1: the votes. She felt like it was a big mess.

1284
01:18:09,160 --> 01:18:11,200
Speaker 1: She had told me. She's in a story that I

1285
01:18:11,320 --> 01:18:13,840
Speaker 1: posted on Sarah carter dot com tool meeting. Look, I've

1286
01:18:13,880 --> 01:18:17,519
Speaker 1: never been more frustrated in my life with an election

1287
01:18:17,520 --> 01:18:20,280
Speaker 1: than I've been with this one. It is so disheartening.

1288
01:18:20,560 --> 01:18:23,080
Speaker 1: So I think what we're seeing across the board, we

1289
01:18:23,120 --> 01:18:25,600
Speaker 1: saw what happened in Nevada. There's issues in Nevada. We

1290
01:18:25,600 --> 01:18:31,360
Speaker 1: saw what's happening now in Arizona, where Maricopa County Congressman

1291
01:18:31,439 --> 01:18:33,920
Speaker 1: Andy Biggs is kind of like, I don't know how

1292
01:18:33,960 --> 01:18:36,760
Speaker 1: this happened, but we want to recount in Maricopa County

1293
01:18:36,840 --> 01:18:41,200
Speaker 1: because everybody, everybody and their mother basically thought that Maricopa

1294
01:18:41,200 --> 01:18:43,519
Speaker 1: County would go to President Trump. Now that's not to

1295
01:18:43,600 --> 01:18:46,320
Speaker 1: see there was any vote a front at all. Maybe

1296
01:18:46,320 --> 01:18:49,200
Speaker 1: it did go to Joe Biden, we don't know of.

1297
01:18:49,360 --> 01:18:52,599
Speaker 1: Allegedly the first count it shows going to Biden by

1298
01:18:52,640 --> 01:18:56,240
Speaker 1: a small margin. But Congressman Biggs is calling, and he's

1299
01:18:56,240 --> 01:18:58,679
Speaker 1: head of the Freedom Caucus. He's calling for a recount there.

1300
01:18:58,720 --> 01:19:01,280
Speaker 1: He may not get that. So there's a lot of

1301
01:19:01,320 --> 01:19:03,720
Speaker 1: issues across the country book that people are looking at.

1302
01:19:04,280 --> 01:19:08,000
Speaker 1: It's very complicated because whether or not these end up

1303
01:19:08,000 --> 01:19:11,080
Speaker 1: in the courts, whether or not it's all provable, whether

1304
01:19:11,200 --> 01:19:15,080
Speaker 1: or not the state legislatures, you know, Republican state legislatures

1305
01:19:15,080 --> 01:19:17,559
Speaker 1: should be able to do something if they really believe

1306
01:19:18,080 --> 01:19:20,760
Speaker 1: that there was election fraud or that there were so

1307
01:19:20,800 --> 01:19:24,160
Speaker 1: many irregularities. It's up to the states too. They can

1308
01:19:24,240 --> 01:19:27,160
Speaker 1: stop this, whether they have the courage to do that

1309
01:19:27,280 --> 01:19:31,719
Speaker 1: or not. Who knows before they certify the votes. But

1310
01:19:32,000 --> 01:19:35,880
Speaker 1: that's the issue now, and that's kind of where everything stands.

1311
01:19:36,280 --> 01:19:39,519
Speaker 1: Speaking to Sarah Carter, investigative journalist, host of The Sarah

1312
01:19:39,600 --> 01:19:44,000
Speaker 1: Carter Show podcast, Sarah, just explain this part to me,

1313
01:19:44,040 --> 01:19:47,840
Speaker 1: if you would, the Sydney Powell allegation. I mean, I'm

1314
01:19:47,880 --> 01:19:52,280
Speaker 1: hearing about all this shady background for Smartmadoc and okay,

1315
01:19:52,640 --> 01:19:56,960
Speaker 1: but do we have any that a software is hackable

1316
01:19:57,040 --> 01:19:59,679
Speaker 1: is not the same thing as saying it was hacked.

1317
01:20:00,479 --> 01:20:06,160
Speaker 1: What is Powell alleging exactly that someone broke into the

1318
01:20:06,240 --> 01:20:10,400
Speaker 1: software or that someone had access to the tabulation and

1319
01:20:10,439 --> 01:20:12,599
Speaker 1: then new to call a halt and then to add

1320
01:20:12,680 --> 01:20:14,800
Speaker 1: votes in later. And this is where I think we

1321
01:20:14,840 --> 01:20:18,559
Speaker 1: need to have greater clarity. Oh, I totally agree with you.

1322
01:20:18,680 --> 01:20:22,320
Speaker 1: I think there absolutely needs to be greater clarity with this.

1323
01:20:23,360 --> 01:20:26,840
Speaker 1: There are allegations, and Sydney's brought this up and I

1324
01:20:26,880 --> 01:20:29,200
Speaker 1: have not seen proof of this, so I'm just laying

1325
01:20:29,200 --> 01:20:32,160
Speaker 1: it out there. But Sydney has been talking to sources,

1326
01:20:32,200 --> 01:20:36,320
Speaker 1: and there are a number of sources out there that have,

1327
01:20:36,760 --> 01:20:42,479
Speaker 1: I guess, expressed that there was fraud in connection with

1328
01:20:42,520 --> 01:20:46,880
Speaker 1: these voting machines. But as you have said, proving it

1329
01:20:46,920 --> 01:20:50,200
Speaker 1: is quite different than just making allegations. You and I

1330
01:20:50,240 --> 01:20:54,120
Speaker 1: both know you're an intelligence expert book, I've covered the

1331
01:20:54,160 --> 01:20:57,920
Speaker 1: intelligence community for some time. We understand that, you know,

1332
01:20:58,040 --> 01:21:01,960
Speaker 1: none of these machines are safe. That we are constantly

1333
01:21:02,000 --> 01:21:05,519
Speaker 1: in a battle with either enemy states or even within

1334
01:21:05,560 --> 01:21:11,000
Speaker 1: our own country to ensure the sanctity of I guess

1335
01:21:11,040 --> 01:21:15,280
Speaker 1: and integrity of our servers and our computer systems, and

1336
01:21:15,400 --> 01:21:18,360
Speaker 1: even our own privacy, you know, because we could get

1337
01:21:18,360 --> 01:21:21,960
Speaker 1: hacked by anyone. But I think like it's very difficult.

1338
01:21:22,040 --> 01:21:25,760
Speaker 1: On the other hand, these are huge companies, These are

1339
01:21:25,800 --> 01:21:29,800
Speaker 1: global companies. They have had issues in the in the past. Look,

1340
01:21:29,840 --> 01:21:35,400
Speaker 1: Smart Maddock in twenty eighteen was called out in the Philippines. Uh.

1341
01:21:35,880 --> 01:21:38,639
Speaker 1: They were not happy with the way the elections were

1342
01:21:38,680 --> 01:21:43,000
Speaker 1: handled in the Philippines. They didn't feel that dominion voting

1343
01:21:43,000 --> 01:21:46,599
Speaker 1: systems they that came out, which was connected to Smart Madock,

1344
01:21:46,800 --> 01:21:49,960
Speaker 1: was trustworthy. They felt that there was something wrong with

1345
01:21:50,000 --> 01:21:52,439
Speaker 1: the with the elections in the Philippines. Even in twenty

1346
01:21:52,680 --> 01:21:56,720
Speaker 1: ten before um and there were a lot of reporters

1347
01:21:56,760 --> 01:22:01,280
Speaker 1: actually calling people out on Smart about Smart matter. But

1348
01:22:01,439 --> 01:22:05,639
Speaker 1: remember this is a time where people are are so upset,

1349
01:22:05,760 --> 01:22:10,000
Speaker 1: where the nation is so divided, and I think the

1350
01:22:10,600 --> 01:22:13,400
Speaker 1: worst part of all of this is that, I mean, well,

1351
01:22:13,439 --> 01:22:17,759
Speaker 1: thankfully we have a peaceful, usually peaceful transitions of power,

1352
01:22:18,600 --> 01:22:21,280
Speaker 1: and that's what we hope for in a democracy and

1353
01:22:21,320 --> 01:22:24,920
Speaker 1: in our republic. But people are so divided now and

1354
01:22:25,040 --> 01:22:28,040
Speaker 1: so angry that I feel like when I talk to

1355
01:22:28,080 --> 01:22:31,400
Speaker 1: people about the election, especially Republicans, because remember, there were

1356
01:22:31,400 --> 01:22:34,439
Speaker 1: over seventy three million people that voted for President Trump,

1357
01:22:34,920 --> 01:22:38,960
Speaker 1: and that's a huge number of people. That's more than

1358
01:22:39,240 --> 01:22:42,080
Speaker 1: any Republican president has ever had in the past. Right,

1359
01:22:42,560 --> 01:22:45,479
Speaker 1: So there are people that are very frustrated and angry.

1360
01:22:45,960 --> 01:22:48,720
Speaker 1: They feel there was just no way in their minds, like,

1361
01:22:48,800 --> 01:22:52,040
Speaker 1: how could Joe Biden have won this election? No one

1362
01:22:52,080 --> 01:22:55,479
Speaker 1: even showed up to his rallies. We were out there

1363
01:22:55,520 --> 01:22:59,080
Speaker 1: in full force. How could there possibly be more voters

1364
01:22:59,120 --> 01:23:03,560
Speaker 1: in Michigan than are registered? And that needs to be investigated.

1365
01:23:04,000 --> 01:23:07,160
Speaker 1: What happened in Nevada? Why did they see more people

1366
01:23:08,280 --> 01:23:11,200
Speaker 1: that they're allegedly there? I mean, and Rick Cornell has

1367
01:23:11,240 --> 01:23:14,120
Speaker 1: brought this up, the former ambassador to Germany as well

1368
01:23:14,160 --> 01:23:16,920
Speaker 1: as DNI that in Nevada, they saw a number of

1369
01:23:17,000 --> 01:23:21,000
Speaker 1: votes where people were from out of state had voted

1370
01:23:21,000 --> 01:23:25,840
Speaker 1: in Nevada or had voted twice. So I think everybody's

1371
01:23:25,880 --> 01:23:29,679
Speaker 1: fighting for that, for that vote, for that legitimate vote.

1372
01:23:30,080 --> 01:23:34,639
Speaker 1: And you know, the American public, I think, and has

1373
01:23:34,800 --> 01:23:39,040
Speaker 1: faith in the system overall in general. But I think

1374
01:23:39,120 --> 01:23:42,040
Speaker 1: with what we've seen over the last four years, especially

1375
01:23:42,040 --> 01:23:46,160
Speaker 1: what we've seen with the weaponization of our intelligence agencies,

1376
01:23:46,160 --> 01:23:50,600
Speaker 1: with the weaponization of the FBI against this president and

1377
01:23:50,800 --> 01:23:54,240
Speaker 1: the Lincoln Project and all of these Republicans that hate

1378
01:23:54,280 --> 01:23:58,400
Speaker 1: President Trump. Right, a lot of people are doubting even

1379
01:23:58,479 --> 01:24:02,680
Speaker 1: this election. They're saying, you know what, this president was

1380
01:24:02,760 --> 01:24:07,720
Speaker 1: so hated by the establishment that it's absolutely possible that

1381
01:24:07,880 --> 01:24:12,200
Speaker 1: anything could have happened. And I really believe that because

1382
01:24:12,240 --> 01:24:15,719
Speaker 1: of that, because of the actions, and because of the

1383
01:24:15,840 --> 01:24:19,639
Speaker 1: lack of trust in our government institutions. Now that has

1384
01:24:19,680 --> 01:24:23,120
Speaker 1: just spilled over into the US election, and now you're

1385
01:24:23,160 --> 01:24:27,080
Speaker 1: just seeing the ramifications of that. People marching in the streets,

1386
01:24:27,360 --> 01:24:30,400
Speaker 1: people not believing in this election. And in a way,

1387
01:24:30,760 --> 01:24:32,559
Speaker 1: I'm a little bit afraid of where it's all going

1388
01:24:32,640 --> 01:24:34,880
Speaker 1: to go. Sarah. Before we let you get back to

1389
01:24:35,200 --> 01:24:37,880
Speaker 1: uncovering the truth, and we're speaking to Sarah Carter. Go

1390
01:24:38,000 --> 01:24:43,240
Speaker 1: to Sarah Acarter dot com for her latest investigative journalism. Sarah,

1391
01:24:43,280 --> 01:24:45,880
Speaker 1: how much faith can we put in Sydney Powell's allegations

1392
01:24:45,920 --> 01:24:47,799
Speaker 1: just based on what you know of her as a lawyer,

1393
01:24:47,840 --> 01:24:51,360
Speaker 1: and just wait, can we take this to the bank

1394
01:24:51,760 --> 01:24:56,880
Speaker 1: on her credibility? Yeah? Absolutely, Look, I've known Sidney Powell

1395
01:24:56,920 --> 01:25:01,840
Speaker 1: for years. She's brilliant, she's smart, she's a fighter, and

1396
01:25:02,000 --> 01:25:06,160
Speaker 1: I have never in my life ever spoken to Sydney

1397
01:25:06,800 --> 01:25:10,639
Speaker 1: or seen her work on something as vigorously or even

1398
01:25:11,160 --> 01:25:13,680
Speaker 1: with only a small bit of intent, you know, and

1399
01:25:14,200 --> 01:25:17,639
Speaker 1: not be telling the full truth about it. Sydney has

1400
01:25:17,680 --> 01:25:21,760
Speaker 1: the sources. Sydney knows what's going on here. Now she

1401
01:25:21,880 --> 01:25:26,320
Speaker 1: has to prove it right. And I know, based on

1402
01:25:26,360 --> 01:25:30,680
Speaker 1: the affidavits that she's already obtained, based on the information

1403
01:25:30,800 --> 01:25:34,000
Speaker 1: that she still hasn't made public, that I can take

1404
01:25:34,080 --> 01:25:37,320
Speaker 1: this to the bank. But remember, Buck, we've been writing

1405
01:25:37,400 --> 01:25:42,320
Speaker 1: around for how long now, since the election in twenty sixteen,

1406
01:25:42,600 --> 01:25:47,120
Speaker 1: for the Department of Justice to do anything about the

1407
01:25:47,160 --> 01:25:52,400
Speaker 1: weaponization of these bureaucracies, agencies that we put our trust

1408
01:25:52,479 --> 01:25:58,920
Speaker 1: in and that abused the system abused, the American voter abused.

1409
01:25:59,120 --> 01:26:02,439
Speaker 1: The president of the United States of America and his

1410
01:26:02,600 --> 01:26:06,240
Speaker 1: family and his friends and anyone that was around him

1411
01:26:06,880 --> 01:26:10,400
Speaker 1: did whatever they wanted, and no one has yet to

1412
01:26:10,439 --> 01:26:14,040
Speaker 1: pay the price. No one. So I think the issue

1413
01:26:14,080 --> 01:26:17,360
Speaker 1: for us as Americans is like we're waking up now,

1414
01:26:17,840 --> 01:26:20,599
Speaker 1: you know, the beast is rising, and people are saying,

1415
01:26:20,640 --> 01:26:23,879
Speaker 1: wait a minute, is there a two tiered system of justice?

1416
01:26:24,200 --> 01:26:27,120
Speaker 1: Does it even matter if we bring the proof? Would

1417
01:26:27,120 --> 01:26:30,240
Speaker 1: it even matter if we showed up with all of

1418
01:26:30,280 --> 01:26:33,960
Speaker 1: the ballots that we're not fed into the system? Would

1419
01:26:34,000 --> 01:26:37,320
Speaker 1: anyone even care? Because this is the problem that I have.

1420
01:26:38,120 --> 01:26:41,840
Speaker 1: There are people that hate President Trump so much, people

1421
01:26:41,880 --> 01:26:45,120
Speaker 1: that may have had integrity in the past, that if

1422
01:26:45,120 --> 01:26:48,160
Speaker 1: they had the chance to remove him, I think they

1423
01:26:48,160 --> 01:26:50,920
Speaker 1: would do anything and everything they could to do that,

1424
01:26:51,439 --> 01:26:54,639
Speaker 1: including breaking the law. I believe that we heard about that,

1425
01:26:55,040 --> 01:26:59,000
Speaker 1: they saw that happen, you know. So for me, I

1426
01:26:59,200 --> 01:27:01,560
Speaker 1: you know, I hope that she can prove it. I

1427
01:27:02,000 --> 01:27:03,600
Speaker 1: believe in her. I have faith in her. I know

1428
01:27:03,640 --> 01:27:05,160
Speaker 1: it's a little bit longer of an answer than you

1429
01:27:05,200 --> 01:27:07,479
Speaker 1: expect it, but but I wanted to make it clear.

1430
01:27:07,960 --> 01:27:10,640
Speaker 1: Sarah Carter, everybody, Sarah a Carter dot Com for her

1431
01:27:10,680 --> 01:27:14,240
Speaker 1: latest Follow her also on Twitter, and listen to her show,

1432
01:27:14,240 --> 01:27:16,800
Speaker 1: The Sarah Carter Show. Sarah, my friend. Always great to

1433
01:27:16,800 --> 01:27:19,200
Speaker 1: talk to you. Thanks so much. Oh, thanks so much

1434
01:27:19,200 --> 01:27:24,519
Speaker 1: for having me on Buck. You're in the Freedom. This

1435
01:27:24,600 --> 01:27:30,880
Speaker 1: is the Buck Sex and Show Podcast. Yeah. I think

1436
01:27:31,080 --> 01:27:34,320
Speaker 1: a lot of the guidelines you're seeing are Orwellian. Let

1437
01:27:34,360 --> 01:27:37,120
Speaker 1: me start by saying, the CDC has put out considerations

1438
01:27:37,439 --> 01:27:41,400
Speaker 1: as we prepare to go about Thanksgiving about socially distancing,

1439
01:27:41,439 --> 01:27:44,160
Speaker 1: wearing masks, doing what you can, and there's a whole list,

1440
01:27:44,160 --> 01:27:46,320
Speaker 1: a page of very good considerations, And in that they

1441
01:27:46,360 --> 01:27:48,760
Speaker 1: say we're not recommending a certain number of people, but

1442
01:27:48,800 --> 01:27:51,360
Speaker 1: we are giving considerations that you should put in place.

1443
01:27:51,360 --> 01:27:53,400
Speaker 1: And I think that's the American way. The American people

1444
01:27:53,479 --> 01:27:55,880
Speaker 1: know how to protect their health. We've dealt with COVID

1445
01:27:55,920 --> 01:27:58,320
Speaker 1: for many months. But it's Orwellian in a place like

1446
01:27:58,479 --> 01:28:01,840
Speaker 1: organ to say if you in numbers more than six,

1447
01:28:02,200 --> 01:28:04,320
Speaker 1: we might come to your house and arrest you when

1448
01:28:04,320 --> 01:28:06,439
Speaker 1: you get thirty days of jail time. That's not the

1449
01:28:06,479 --> 01:28:08,960
Speaker 1: American way. We don't lose our freedom in this country.

1450
01:28:09,000 --> 01:28:12,679
Speaker 1: We make responsible health decisions as individuals. Amen to that,

1451
01:28:12,960 --> 01:28:16,120
Speaker 1: going to arrest you, they say in Oregon, they're gonna

1452
01:28:16,160 --> 01:28:19,400
Speaker 1: arrest you, or at least they can, and I hope

1453
01:28:19,439 --> 01:28:22,000
Speaker 1: they don't do what they say they have the power

1454
01:28:22,080 --> 01:28:24,920
Speaker 1: to do. Is not the way we function in a

1455
01:28:24,960 --> 01:28:30,080
Speaker 1: free society. That's not what the constitutionally guarantee liberty is

1456
01:28:30,760 --> 01:28:33,639
Speaker 1: by being an American. And yet that's where we are.

1457
01:28:34,680 --> 01:28:38,800
Speaker 1: People are okay with this. There's police power now that's

1458
01:28:38,800 --> 01:28:40,320
Speaker 1: going to be used to prevent you from gathering with

1459
01:28:40,360 --> 01:28:43,519
Speaker 1: your family because of the very small possibility that you

1460
01:28:43,600 --> 01:28:46,320
Speaker 1: may transmit a virus for which there is a very

1461
01:28:46,360 --> 01:28:51,960
Speaker 1: small possibility that you will die. Oh okay. Explain to

1462
01:28:52,000 --> 01:28:54,120
Speaker 1: me again how this won't be abused in the future.

1463
01:28:54,400 --> 01:28:57,080
Speaker 1: Explain to me again, how we aren't a society that's

1464
01:28:57,080 --> 01:29:00,799
Speaker 1: increasingly being conditioned to just shut up. Do we're told

1465
01:29:00,880 --> 01:29:05,120
Speaker 1: by the experts and the elites, no matter how often

1466
01:29:05,120 --> 01:29:08,479
Speaker 1: they're wrong, no matter how much they violate the Bill

1467
01:29:08,520 --> 01:29:11,280
Speaker 1: of Rights, doesn't matter. Right, do what you're told, peasant?

1468
01:29:11,840 --> 01:29:14,400
Speaker 1: When do we say it's enough? When have we all

1469
01:29:14,439 --> 01:29:19,000
Speaker 1: had enough? I'm already there. Who's with me? Who wants

1470
01:29:19,040 --> 01:29:21,799
Speaker 1: to start something else? Who wants to push a movement

1471
01:29:21,880 --> 01:29:29,760
Speaker 1: here to nullify these unconstitutional insanities. Thanks for listening to

1472
01:29:29,800 --> 01:29:34,040
Speaker 1: The Busson Show podcasts. Remember to subscribe on Apple podcast,

1473
01:29:34,160 --> 01:29:42,360
Speaker 1: at the iHeartRadio app, or wherever you get your podcasts.

1474
01:29:42,800 --> 01:29:56,200
Speaker 1: Team Buck, it's time for roll. Call Facebook dot com,

1475
01:29:56,240 --> 01:29:59,639
Speaker 1: slashbuck sexon or Team Buck at iHeartMedia dot com. Don't

1476
01:29:59,640 --> 01:30:03,639
Speaker 1: forget it. Check in at buck Sexton dot com for

1477
01:30:03,800 --> 01:30:07,439
Speaker 1: all of the latest and greatest on our site there

1478
01:30:07,920 --> 01:30:11,439
Speaker 1: and please bookmark it. Check in on it. It's a

1479
01:30:11,479 --> 01:30:13,759
Speaker 1: place you can listen to the podcast of the show.

1480
01:30:13,840 --> 01:30:16,280
Speaker 1: It's also a place where we're posting new stories. I'll

1481
01:30:16,320 --> 01:30:18,880
Speaker 1: be posting editorials I have been, I won't be posting more.

1482
01:30:19,640 --> 01:30:23,360
Speaker 1: So please do make that a part of your daily routine.

1483
01:30:24,200 --> 01:30:25,280
Speaker 1: So we want to check it in on our buddy

1484
01:30:25,280 --> 01:30:28,400
Speaker 1: producer Mark. Hey, producer, Mark, How you doing good? How

1485
01:30:28,400 --> 01:30:30,960
Speaker 1: are you Buck? I don't like that it's thirty something

1486
01:30:31,000 --> 01:30:32,920
Speaker 1: agrees in New York. I didn't sign up for this.

1487
01:30:33,000 --> 01:30:36,200
Speaker 1: That's why I just stay indoors. Temperature is always the

1488
01:30:36,240 --> 01:30:37,600
Speaker 1: same in here. Probably a good move, but you know,

1489
01:30:37,640 --> 01:30:39,559
Speaker 1: if you move to Pennsylvania, I know you're in New Jersey.

1490
01:30:39,880 --> 01:30:42,080
Speaker 1: Move to Pennsylvania. You got a mask up indoors now too,

1491
01:30:42,760 --> 01:30:45,720
Speaker 1: in my own apartment. Yeah, if anyone else is there,

1492
01:30:45,840 --> 01:30:49,679
Speaker 1: that's the rule. No, thank you. Yeah, that's not happening.

1493
01:30:49,800 --> 01:30:52,360
Speaker 1: That's right, that's not happening. See, they're just gonna keep

1494
01:30:52,360 --> 01:30:55,760
Speaker 1: pushing until we say blank off. We should get one

1495
01:30:55,720 --> 01:30:57,160
Speaker 1: of those little beet buttons so I can just go

1496
01:30:57,280 --> 01:30:59,120
Speaker 1: beep whatever I want to say, something that I'm allowed

1497
01:30:59,160 --> 01:31:01,479
Speaker 1: to say, we bleep it. I can always just edit

1498
01:31:01,520 --> 01:31:04,439
Speaker 1: it in. That's true too. But I'm just saying we go,

1499
01:31:04,720 --> 01:31:07,040
Speaker 1: we got we got bleeps, we got things I gotta say.

1500
01:31:07,120 --> 01:31:09,960
Speaker 1: I'm just hoping New Jersey doesn't mess up indoor dining

1501
01:31:09,960 --> 01:31:15,280
Speaker 1: before my anniversary. Oh you going Italian? No, we're going

1502
01:31:15,280 --> 01:31:18,360
Speaker 1: to like a some trendy place. My wife wanted to go. Hey,

1503
01:31:18,400 --> 01:31:23,080
Speaker 1: you know, she's the wife. She wants to romance romantic, Fine,

1504
01:31:23,120 --> 01:31:25,439
Speaker 1: whatever you want. Yeah. I mean you don't really strike

1505
01:31:25,439 --> 01:31:27,439
Speaker 1: me as generally a scented candles guy, but you gotta

1506
01:31:27,439 --> 01:31:30,759
Speaker 1: make the lady happy. I actually do like scented candles. Really,

1507
01:31:30,960 --> 01:31:34,160
Speaker 1: what's wrong with them? I don't know, nothing wrong with

1508
01:31:34,160 --> 01:31:37,600
Speaker 1: your house spelling? Nice? Hey okay, hey, hey, you know

1509
01:31:37,720 --> 01:31:40,439
Speaker 1: producer Mark full of surprises for everybody good to know.

1510
01:31:41,439 --> 01:31:44,559
Speaker 1: So all right, now, let's see what the folks think

1511
01:31:44,600 --> 01:31:46,360
Speaker 1: of and the roll call here, let's get into some

1512
01:31:46,400 --> 01:31:49,960
Speaker 1: of this. Ralph Hey Bugger producer Mark input on the

1513
01:31:50,000 --> 01:31:53,400
Speaker 1: student loan section of the November sixteenth show. I have

1514
01:31:53,520 --> 01:31:56,880
Speaker 1: a teaching degree through student loans. I've made three hundred

1515
01:31:56,880 --> 01:32:00,439
Speaker 1: dollars a month plus in monthly payments for fifteen years

1516
01:32:01,120 --> 01:32:04,839
Speaker 1: and have only paid ten thousand dollars toward the principle,

1517
01:32:04,880 --> 01:32:08,120
Speaker 1: which is forty nine thousand, five hundred dollars. I had

1518
01:32:08,160 --> 01:32:11,120
Speaker 1: to go to college to get a sufficient job to

1519
01:32:11,200 --> 01:32:14,639
Speaker 1: raise my family. The current interest rate is five point

1520
01:32:14,720 --> 01:32:17,960
Speaker 1: seven five percent, which ensures the loan will never be

1521
01:32:17,960 --> 01:32:21,240
Speaker 1: paid off of my lifetime. I'm sixty five now, I'm

1522
01:32:21,240 --> 01:32:23,280
Speaker 1: not a liberal and feel I have a worthwhile degree

1523
01:32:23,280 --> 01:32:25,839
Speaker 1: in a field that pays very little. The loan structure

1524
01:32:25,880 --> 01:32:28,880
Speaker 1: needs to change to a bank loan format so loans

1525
01:32:28,880 --> 01:32:31,720
Speaker 1: can be paid off in a timely manner. Otherwise, the

1526
01:32:31,760 --> 01:32:35,000
Speaker 1: student loan system is another unlimited income source for the FEDS.

1527
01:32:35,000 --> 01:32:39,719
Speaker 1: Shield tie, I signed not a privilege eighteen year old kid, Ralph. Look,

1528
01:32:39,760 --> 01:32:43,719
Speaker 1: I sympathize which with your situation, my friend, and these

1529
01:32:43,800 --> 01:32:47,560
Speaker 1: loans they are. They're non dischargeable, so that I have

1530
01:32:47,600 --> 01:32:50,920
Speaker 1: to remember they're non dischargeable and anyone can get them

1531
01:32:50,920 --> 01:32:54,479
Speaker 1: regardless of credit history or ability to pay. So in

1532
01:32:54,520 --> 01:32:57,280
Speaker 1: that sense, they're not normal loans. I mean when you

1533
01:32:57,320 --> 01:32:59,360
Speaker 1: go to get a loan for a house, they want

1534
01:32:59,360 --> 01:33:01,559
Speaker 1: to see income, they want to see bank statements, they

1535
01:33:01,600 --> 01:33:03,960
Speaker 1: want to see you know, your job, they want to

1536
01:33:03,960 --> 01:33:08,320
Speaker 1: see all these things because they're taking a risk. You

1537
01:33:08,360 --> 01:33:10,760
Speaker 1: don't want to do this. But if you take out

1538
01:33:10,760 --> 01:33:14,200
Speaker 1: a mortgage for a home and then you can't pay it,

1539
01:33:14,360 --> 01:33:17,200
Speaker 1: you can walk away from that. You know, you could

1540
01:33:17,640 --> 01:33:19,439
Speaker 1: mail in the keys to the bank and say here

1541
01:33:19,520 --> 01:33:22,200
Speaker 1: you go. Now that'll ruin your credit for at least

1542
01:33:22,240 --> 01:33:24,880
Speaker 1: ten years and it's not a good thing, and they'll

1543
01:33:24,880 --> 01:33:28,600
Speaker 1: send collections after you and ever. But you can discharge

1544
01:33:28,600 --> 01:33:30,640
Speaker 1: it in bankruptcy usually. I mean, I don't know that

1545
01:33:30,720 --> 01:33:33,439
Speaker 1: much about this, but I do know that it is

1546
01:33:33,479 --> 01:33:36,160
Speaker 1: possible to walk away from a house and then the

1547
01:33:36,200 --> 01:33:38,080
Speaker 1: bank is stuck with a home that they have to sell.

1548
01:33:38,160 --> 01:33:40,400
Speaker 1: And you know that that's how this goes. But there's

1549
01:33:40,400 --> 01:33:43,439
Speaker 1: a risk factor into this for you and for the bank.

1550
01:33:43,840 --> 01:33:46,200
Speaker 1: With student loans, it's okay, we're gonna give this to you.

1551
01:33:46,240 --> 01:33:48,000
Speaker 1: We're gonna give you this this amount of money for

1552
01:33:48,040 --> 01:33:50,439
Speaker 1: your loans, and this is the rate you're gonna pay

1553
01:33:50,439 --> 01:33:52,160
Speaker 1: it back, and you can never get out of this.

1554
01:33:52,640 --> 01:33:55,080
Speaker 1: It's really it's effectively impossible. I mean, I've heard of

1555
01:33:55,120 --> 01:33:58,759
Speaker 1: some stories of getting out of it, but it's basically impossible. Well,

1556
01:33:58,800 --> 01:34:00,760
Speaker 1: that's not the way that the mark it's supposed, that's

1557
01:34:00,760 --> 01:34:03,960
Speaker 1: not the market working. This is this is government policy

1558
01:34:04,120 --> 01:34:09,160
Speaker 1: enacted through a loan program. So, Ralph, I I sympathize

1559
01:34:09,200 --> 01:34:12,880
Speaker 1: with you getting a you know, a teaching degree through

1560
01:34:12,880 --> 01:34:14,680
Speaker 1: student loans. I mean, if the government really is going

1561
01:34:14,760 --> 01:34:16,439
Speaker 1: to do what it's doing right now, what they should

1562
01:34:16,479 --> 01:34:19,640
Speaker 1: say is if you go into certain public sector or

1563
01:34:19,720 --> 01:34:22,639
Speaker 1: public interest work, there'll be a government forgiveness of your loans.

1564
01:34:22,880 --> 01:34:25,920
Speaker 1: But then what you have is effectively the taxpayer subsidizing

1565
01:34:26,000 --> 01:34:29,519
Speaker 1: certain degrees. And Ralph, I'd be very curious, maybe you

1566
01:34:29,520 --> 01:34:31,040
Speaker 1: want to write and tell us. And I asked this

1567
01:34:31,120 --> 01:34:34,280
Speaker 1: question all honesty, could you have done your teaching job

1568
01:34:34,520 --> 01:34:39,639
Speaker 1: without getting an advanced degree? You know, I'm just I'm

1569
01:34:39,680 --> 01:34:45,080
Speaker 1: just wondering, could you have done your teaching job that

1570
01:34:45,840 --> 01:34:48,280
Speaker 1: I'm assuming you've got a master's here although I'm trying

1571
01:34:48,320 --> 01:34:51,960
Speaker 1: to most public schools do require a master's at least eventually,

1572
01:34:52,439 --> 01:34:55,680
Speaker 1: right right, That's okay, so exactly my point here. So

1573
01:34:55,760 --> 01:34:58,040
Speaker 1: if you need a master's to teach, do you really

1574
01:34:58,479 --> 01:35:02,240
Speaker 1: that's a a certific cation requirement. But I'm asking you, Ralph,

1575
01:35:02,320 --> 01:35:03,559
Speaker 1: do you think that you could have been a great

1576
01:35:03,560 --> 01:35:05,920
Speaker 1: teacher without that masters? Because that's the way to really

1577
01:35:05,920 --> 01:35:07,760
Speaker 1: rethink it. And I'm not saying this is on you.

1578
01:35:07,840 --> 01:35:11,200
Speaker 1: I'm just saying the system. Why do public schools require this?

1579
01:35:12,040 --> 01:35:14,479
Speaker 1: Isn't a bachelor's degree enough to teach kids, especially if

1580
01:35:14,479 --> 01:35:16,600
Speaker 1: you're gonna if you're gonna specialize in a subject. And

1581
01:35:16,920 --> 01:35:19,240
Speaker 1: so that's what I mean. I think there's a lot there.

1582
01:35:20,680 --> 01:35:23,439
Speaker 1: Brian Rights just on an article saying that regular and

1583
01:35:23,680 --> 01:35:27,639
Speaker 1: double stuff oreos that are gluten free will be here

1584
01:35:27,640 --> 01:35:32,639
Speaker 1: come January. Thoughts, great show is always gentlemen shields high Well, Brian,

1585
01:35:32,840 --> 01:35:35,800
Speaker 1: that's good news and bad news. Good news in that

1586
01:35:36,680 --> 01:35:40,439
Speaker 1: oreos are delicious, bad news in that I'm trying to

1587
01:35:40,479 --> 01:35:45,439
Speaker 1: fit into my suits again and it's coming along slowly

1588
01:35:45,520 --> 01:35:48,360
Speaker 1: here and double stuff oreos are not going to help

1589
01:35:48,400 --> 01:35:55,719
Speaker 1: in that process. Pucer Mark Favorite Cookies M Favorite package chookie.

1590
01:35:55,760 --> 01:36:00,479
Speaker 1: Absolutely out of the chocolate cream. Oreos the best. Yeah,

1591
01:36:00,560 --> 01:36:03,040
Speaker 1: what are the uh do you remember a cookie's called

1592
01:36:03,080 --> 01:36:05,040
Speaker 1: the hydros or something like that. Do you remember that

1593
01:36:05,080 --> 01:36:07,280
Speaker 1: from a long no idea? What that is? They're like

1594
01:36:07,320 --> 01:36:11,000
Speaker 1: the rip off oreos, you know, they're like the fakey oreos,

1595
01:36:11,040 --> 01:36:15,599
Speaker 1: you know, the newman zones. Oreos like the healthy It's

1596
01:36:15,720 --> 01:36:18,280
Speaker 1: it's like an off brand. It's like the off brand Oreos.

1597
01:36:18,360 --> 01:36:21,600
Speaker 1: They're not as good. Yeah, and oreos. I used to

1598
01:36:21,600 --> 01:36:23,120
Speaker 1: eat them because I used to be a gluten eater

1599
01:36:23,240 --> 01:36:27,240
Speaker 1: for first thirty years of my life. And oreos are delicious,

1600
01:36:27,280 --> 01:36:29,160
Speaker 1: I will say that. And if you the problem is

1601
01:36:29,160 --> 01:36:32,160
Speaker 1: if you dunk them in milk. They're so easy to

1602
01:36:32,240 --> 01:36:35,120
Speaker 1: consume that you can knock off a whole sleeve oreos

1603
01:36:35,160 --> 01:36:36,800
Speaker 1: and you're just like, oh, that wasn't that wasn't hard.

1604
01:36:36,800 --> 01:36:38,400
Speaker 1: I don't even want to know how many calories are

1605
01:36:38,439 --> 01:36:40,160
Speaker 1: gonna sleeve of oreos. I don't even need to need

1606
01:36:40,200 --> 01:36:42,120
Speaker 1: the milk. I can just knock off a sleeve of orios.

1607
01:36:42,120 --> 01:36:44,000
Speaker 1: That's why I don't keep them in the house. Yeah No,

1608
01:36:44,280 --> 01:36:46,360
Speaker 1: And they'd be dangerous for me to have around. Oreos.

1609
01:36:46,479 --> 01:36:49,120
Speaker 1: I'll just I'll just h it's very the gluten free

1610
01:36:49,120 --> 01:36:50,840
Speaker 1: orios that are coming out. I gotta there has to

1611
01:36:50,840 --> 01:36:52,560
Speaker 1: be a treat that I see at people's houses for

1612
01:36:52,640 --> 01:36:54,760
Speaker 1: parties or something, and then I'll have one or two

1613
01:36:54,800 --> 01:36:57,200
Speaker 1: and that's it, all right, But who's buying gluten free

1614
01:36:57,200 --> 01:37:00,800
Speaker 1: oreos for a party? People that that Buck is coming

1615
01:37:00,840 --> 01:37:02,679
Speaker 1: to their house Producer Mark, Yeah, but then they're gonna

1616
01:37:02,680 --> 01:37:04,360
Speaker 1: be like, hey, Buck, take the rest of this because

1617
01:37:04,600 --> 01:37:06,559
Speaker 1: we're not going to eat them. That is true. I

1618
01:37:06,560 --> 01:37:09,240
Speaker 1: do end up getting sent home with the gluten free

1619
01:37:09,240 --> 01:37:11,080
Speaker 1: products that people buy to be kind to me when

1620
01:37:11,120 --> 01:37:13,280
Speaker 1: they know him coming to their house, and then I

1621
01:37:13,320 --> 01:37:16,360
Speaker 1: eat them and you know, crackers and all that stuff. Yeah,

1622
01:37:16,720 --> 01:37:19,599
Speaker 1: it's the life. What can I tell you? Friends, Don

1623
01:37:19,920 --> 01:37:23,120
Speaker 1: bucking Mark, regular listener of your program since March. Mark,

1624
01:37:23,160 --> 01:37:25,519
Speaker 1: you do a great job. I have read Gates of

1625
01:37:25,600 --> 01:37:28,320
Speaker 1: fire Buck upon your recommendation, and found it a very

1626
01:37:28,360 --> 01:37:31,479
Speaker 1: inspiring story. I think that US freedom lovers of today

1627
01:37:31,520 --> 01:37:34,479
Speaker 1: should adopt the Spartan's attitude to fight the rampant corruption

1628
01:37:34,520 --> 01:37:37,600
Speaker 1: in our federal government. Now. I appreciate every time I

1629
01:37:37,640 --> 01:37:41,600
Speaker 1: hear you say shields high, Don. I am not a

1630
01:37:41,600 --> 01:37:45,559
Speaker 1: big novel readery. Really. I'm a history guy and a

1631
01:37:45,640 --> 01:37:50,120
Speaker 1: nonfiction guy for books, but I just I thought Gates

1632
01:37:50,120 --> 01:37:54,719
Speaker 1: of Fire was fantastic. It's a Stephen Pressman novel, historical fiction,

1633
01:37:55,479 --> 01:37:58,240
Speaker 1: and it's amazing. It's just really well written. It's just

1634
01:37:58,600 --> 01:38:00,680
Speaker 1: it's great and there's so much in and it's so

1635
01:38:00,840 --> 01:38:03,760
Speaker 1: rich the way he does it. So I'm glad you

1636
01:38:03,840 --> 01:38:06,880
Speaker 1: enjoyed Gates of Fire. Highly highly recommended. I think you'll

1637
01:38:06,960 --> 01:38:09,400
Speaker 1: Anyone else who hasn't read it, I will really enjoy it.

1638
01:38:10,479 --> 01:38:12,040
Speaker 1: And thank you for listening. Great to have a new,

1639
01:38:12,360 --> 01:38:17,639
Speaker 1: relatively new listener to the show. Joseph buck Obama says,

1640
01:38:17,680 --> 01:38:21,080
Speaker 1: we would not expect the kind of behavior from children

1641
01:38:21,080 --> 01:38:24,519
Speaker 1: if they lost that Trump is displaying. No, the behavior

1642
01:38:24,520 --> 01:38:27,559
Speaker 1: we wouldn't expect is the kind of crying, kicking, and

1643
01:38:27,640 --> 01:38:30,920
Speaker 1: screaming that the Democrats displayed when they lost the twenty

1644
01:38:30,920 --> 01:38:34,080
Speaker 1: sixteen elections. It bothers me how much they ignore their

1645
01:38:34,160 --> 01:38:36,439
Speaker 1: own actions and they act high and mighty as they

1646
01:38:36,479 --> 01:38:39,639
Speaker 1: condemn people who have behaved far more maturely than they

1647
01:38:39,680 --> 01:38:43,000
Speaker 1: ever did or have. Yeah, Joseph, I mean that's a

1648
01:38:43,040 --> 01:38:45,160
Speaker 1: big part of I think the mentality right now that

1649
01:38:45,200 --> 01:38:48,880
Speaker 1: conservatives have around all of this is that we're being

1650
01:38:48,960 --> 01:38:51,600
Speaker 1: kind of lectured by the other side about decorum and

1651
01:38:51,640 --> 01:38:55,960
Speaker 1: how to act when they are the ones. They are

1652
01:38:55,960 --> 01:38:59,759
Speaker 1: the ones that we're marching out in the streets screaming

1653
01:39:00,120 --> 01:39:04,160
Speaker 1: my president and acting like lunatics and screaming at the sky.

1654
01:39:04,640 --> 01:39:07,599
Speaker 1: When Hillary lost in twenty sixteen and took it those

1655
01:39:07,640 --> 01:39:11,960
Speaker 1: many steps further into the Russia collusion hoax, took it

1656
01:39:12,000 --> 01:39:14,960
Speaker 1: those many steps further into pretending something happened that didn't

1657
01:39:15,000 --> 01:39:18,640
Speaker 1: just to make themselves feel better. The whole thing is

1658
01:39:18,680 --> 01:39:26,280
Speaker 1: honestly an outrage, but no accountability, no accountability in this whatsoever.

1659
01:39:26,439 --> 01:39:28,800
Speaker 1: They just they've gotten away. Look, they've gotten away with it.

1660
01:39:29,479 --> 01:39:32,960
Speaker 1: I wish I could say otherwise, but this is what

1661
01:39:33,000 --> 01:39:35,479
Speaker 1: they're doing. This is what they're up to. Pete. Is

1662
01:39:35,479 --> 01:39:38,120
Speaker 1: there a place to see a compilation of all these

1663
01:39:38,200 --> 01:39:42,680
Speaker 1: races across the country. How many mayors, governors, representative centers, etc.

1664
01:39:42,960 --> 01:39:45,240
Speaker 1: For the local the federal level won their Republican races,

1665
01:39:45,280 --> 01:39:48,600
Speaker 1: Democrat or other. Pete. I'm sure there is, but I

1666
01:39:48,600 --> 01:39:52,400
Speaker 1: don't know of one off hand. But there's lots of

1667
01:39:52,439 --> 01:39:55,000
Speaker 1: maps and data crunching, and you know, this is all

1668
01:39:55,040 --> 01:39:58,840
Speaker 1: over the all over the interwebs now, so you should

1669
01:39:58,880 --> 01:40:00,519
Speaker 1: be able to find it if you google it up.

1670
01:40:00,520 --> 01:40:02,200
Speaker 1: But if you find it great one, please send it

1671
01:40:02,240 --> 01:40:05,360
Speaker 1: into us and maybe we can share it here on

1672
01:40:05,400 --> 01:40:09,000
Speaker 1: the show, share it on bucksexon dot com. But yeah,

1673
01:40:09,000 --> 01:40:12,479
Speaker 1: that is one of the big outstanding questions here. How

1674
01:40:12,680 --> 01:40:15,000
Speaker 1: is it that Republicans did so well in the House.

1675
01:40:15,080 --> 01:40:18,280
Speaker 1: How is it the Republicans had such a strong showing

1676
01:40:18,280 --> 01:40:21,679
Speaker 1: in other ways but Joe Biden managed to beat Trump. Anyway,

1677
01:40:22,560 --> 01:40:26,200
Speaker 1: It's not that it's impossible, but it does raise some questions.

1678
01:40:26,520 --> 01:40:32,120
Speaker 1: It doesn't it doesn't prove fraud, but it does indicate

1679
01:40:32,240 --> 01:40:34,840
Speaker 1: that there's something funky. As I like to say, what

1680
01:40:35,040 --> 01:40:37,400
Speaker 1: is that funky smell? We don't know. Why don't we

1681
01:40:37,439 --> 01:40:39,599
Speaker 1: find out? Let's find out what the funky smell is? Right,

1682
01:40:39,640 --> 01:40:43,519
Speaker 1: Producer Mark, Yeah, you use a candle. Discussed this before,

1683
01:40:43,560 --> 01:40:45,920
Speaker 1: exactly cover up the funky smell with a scented candle.

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01:40:45,960 --> 01:40:48,839
Speaker 1: Do you have a favorite? Are you like a sage

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01:40:49,120 --> 01:40:52,519
Speaker 1: and and you know ce salt guy or something? What

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01:40:52,560 --> 01:40:53,840
Speaker 1: do you what do you go for? I mean, I

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01:40:54,160 --> 01:40:58,000
Speaker 1: was like a nice vanilla candle something like that. Now

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01:40:58,040 --> 01:41:00,680
Speaker 1: I'm just picturing Producer Mark and missus Mark's house in

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01:41:00,720 --> 01:41:03,759
Speaker 1: New Jersey, like Enya is always playing in the background,

1690
01:41:03,760 --> 01:41:05,960
Speaker 1: and you guys have you know, dim dim lights and

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01:41:06,200 --> 01:41:09,160
Speaker 1: uh and candles go. First of all, I don't own

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01:41:09,160 --> 01:41:11,920
Speaker 1: a house yet. Second of all, look, I mean what

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01:41:12,040 --> 01:41:15,679
Speaker 1: I didn't really candles were abnormal? No. I like candles.

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01:41:15,720 --> 01:41:17,720
Speaker 1: I like you will even talk about lighting candles in

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01:41:17,760 --> 01:41:19,720
Speaker 1: your own I'm a big fan. I'm a big fell

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01:41:19,800 --> 01:41:21,360
Speaker 1: I don't like the scented ones in much. I just

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01:41:21,400 --> 01:41:23,759
Speaker 1: like candles in general. I think that they're they're soothing.

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01:41:24,320 --> 01:41:26,120
Speaker 1: But you know, I'm just trying to get a sense

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01:41:26,120 --> 01:41:28,920
Speaker 1: of what it's like over at the Casa cosa day

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01:41:28,920 --> 01:41:31,280
Speaker 1: producer Mark. I forgot the one we had recently, but

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01:41:31,320 --> 01:41:33,640
Speaker 1: it smelled amazing. It wasn't vanilla. It was like some

1702
01:41:33,680 --> 01:41:38,320
Speaker 1: sort of pumpkin spiced cheesecake thing, like something like like

1703
01:41:38,400 --> 01:41:41,200
Speaker 1: dessert flavored. I mean, I would say we should start

1704
01:41:41,200 --> 01:41:43,680
Speaker 1: a candle called like Essence or Freedom Hut, but it

1705
01:41:43,680 --> 01:41:47,040
Speaker 1: would be this smell left over after you char grill

1706
01:41:47,560 --> 01:41:50,720
Speaker 1: a riby, after you've cooked bacon on the same pan

1707
01:41:50,880 --> 01:41:55,400
Speaker 1: that morning, mixed with a lot of coffee mugs that

1708
01:41:55,479 --> 01:41:57,360
Speaker 1: still have like a coffee ring around them because you

1709
01:41:57,360 --> 01:41:59,400
Speaker 1: haven't cleaned them yet. I don't know. I don't know

1710
01:41:59,400 --> 01:42:01,679
Speaker 1: if that's really what people need. You know, I can't

1711
01:42:01,680 --> 01:42:03,679
Speaker 1: imagine a lot of cleaning goes on in the freedom

1712
01:42:03,720 --> 01:42:07,400
Speaker 1: mund No, it's I need help sometimes. The good thing

1713
01:42:07,439 --> 01:42:09,920
Speaker 1: is when the snow Princess comes over for visits. I

1714
01:42:10,439 --> 01:42:14,400
Speaker 1: need this to not be like a hazmat suit only environment.

1715
01:42:14,960 --> 01:42:19,320
Speaker 1: So I basically termed my entire domicile into some form

1716
01:42:19,640 --> 01:42:23,559
Speaker 1: of of you know, content creation. Now. I mean I've

1717
01:42:23,560 --> 01:42:26,120
Speaker 1: got wires everywhere and cameras and lights and everything else.

1718
01:42:26,520 --> 01:42:28,880
Speaker 1: So I try to create little areas of calm. So

1719
01:42:28,920 --> 01:42:30,519
Speaker 1: that's where that's where the candles come in, you know,

1720
01:42:30,520 --> 01:42:33,080
Speaker 1: I create the little little corner. I do have a

1721
01:42:33,120 --> 01:42:36,760
Speaker 1: giant couch that we call old Gray, and it's way

1722
01:42:36,760 --> 01:42:38,880
Speaker 1: too big for the space, but I don't care because

1723
01:42:39,439 --> 01:42:44,800
Speaker 1: two people can comfortably not uncomfortably comfortably sleep on this

1724
01:42:44,840 --> 01:42:48,040
Speaker 1: thing at one time. It's an l shape, and I

1725
01:42:48,080 --> 01:42:50,120
Speaker 1: gotta say that thing is my salvation man. You know,

1726
01:42:50,160 --> 01:42:52,000
Speaker 1: at the end of the day, it'll just you just

1727
01:42:52,080 --> 01:42:56,759
Speaker 1: fall into it. It's this big, fluffy gray hug. It's amazing.

1728
01:42:57,040 --> 01:42:59,719
Speaker 1: It's like me and my recliner. Yeah, oh, you gotta

1729
01:42:59,800 --> 01:43:02,280
Speaker 1: is it lazy boy? I know something from like Raymond

1730
01:43:02,320 --> 01:43:05,320
Speaker 1: Flanningen or something. Yeah, it's nice. You gotta have your chair.

1731
01:43:05,400 --> 01:43:07,320
Speaker 1: Every every man's got to have that comfy chair. I

1732
01:43:07,400 --> 01:43:09,639
Speaker 1: do the show, you know. I do radio. For anybody

1733
01:43:09,640 --> 01:43:12,960
Speaker 1: who watches our videocast, if it, they'll see it. I

1734
01:43:13,080 --> 01:43:15,479
Speaker 1: do radio in a chair. This chair that I do

1735
01:43:15,520 --> 01:43:17,920
Speaker 1: it in is falling apart. I've had to tape parts

1736
01:43:17,920 --> 01:43:20,599
Speaker 1: of it back together and everything else. But something about

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01:43:20,640 --> 01:43:22,559
Speaker 1: this chair is so comfy, you know. And when you

1738
01:43:22,600 --> 01:43:25,479
Speaker 1: find that comfy chair, it's like that comfortable sweatshirt you've

1739
01:43:25,479 --> 01:43:27,880
Speaker 1: had for ten years that just feels better than all

1740
01:43:27,880 --> 01:43:33,519
Speaker 1: the other sweatshirts. You're in the Freedom Hunt. This is

1741
01:43:33,520 --> 01:43:41,040
Speaker 1: the Buck Sexton Show podcast, rolling on with Roll Call Brandy,

1742
01:43:41,280 --> 01:43:43,519
Speaker 1: because there are enough time for these lawsuits brought on

1743
01:43:43,560 --> 01:43:45,760
Speaker 1: by the Trump campaign to play out. What happens if

1744
01:43:45,800 --> 01:43:48,439
Speaker 1: December comes, the states have to make this election official

1745
01:43:48,479 --> 01:43:52,760
Speaker 1: and there's still litigation happening, Brandy. There are deadlines. There

1746
01:43:52,760 --> 01:43:56,679
Speaker 1: are deadlines for state certification, deadlines for electoral college. And

1747
01:43:57,000 --> 01:44:00,640
Speaker 1: we will have a president by We will have a

1748
01:44:00,680 --> 01:44:03,839
Speaker 1: president by an auguration day, that's for sure. The system

1749
01:44:03,880 --> 01:44:06,439
Speaker 1: is set up in that way, and if they can

1750
01:44:06,479 --> 01:44:08,680
Speaker 1: still be having they can still have lawsuits pending. But

1751
01:44:08,720 --> 01:44:11,040
Speaker 1: if the process continues, unless the judge is going to

1752
01:44:11,120 --> 01:44:16,240
Speaker 1: shut down things like the certification, we're gonna it moves along,

1753
01:44:16,800 --> 01:44:19,840
Speaker 1: I think, is the answer here. So we will have

1754
01:44:19,920 --> 01:44:24,040
Speaker 1: a president as of January twentieth. And there's a lot

1755
01:44:24,040 --> 01:44:28,160
Speaker 1: of ways this could go. But as I've been saying,

1756
01:44:28,160 --> 01:44:31,080
Speaker 1: do you prepare yourselves, friends, prepare yourselves for the very

1757
01:44:31,640 --> 01:44:35,639
Speaker 1: serious possibility that it is it is Biden who ends

1758
01:44:35,720 --> 01:44:38,080
Speaker 1: up as the president here. I'm not saying give up,

1759
01:44:38,080 --> 01:44:40,920
Speaker 1: and I'm just saying, psychologically, get ready for that. I

1760
01:44:40,920 --> 01:44:44,080
Speaker 1: don't want you to be, you know, caught unaware or

1761
01:44:44,200 --> 01:44:45,400
Speaker 1: not not that you really could be. At this point,

1762
01:44:45,400 --> 01:44:47,120
Speaker 1: we all know he's ahead in the electrocompet I mean,

1763
01:44:47,160 --> 01:44:50,880
Speaker 1: you know, prepare yourself for that psychologically, because we might

1764
01:44:51,040 --> 01:44:53,040
Speaker 1: we might be making that switch at some point and

1765
01:44:53,080 --> 01:44:56,760
Speaker 1: it's disappointing, but that's where we are. We operate here

1766
01:44:56,760 --> 01:44:59,000
Speaker 1: in the real world, right one of the one of

1767
01:44:59,040 --> 01:45:01,400
Speaker 1: the principle of this show. We operate in the world

1768
01:45:01,400 --> 01:45:03,200
Speaker 1: as it is, not as we wish it would be.

1769
01:45:03,840 --> 01:45:07,280
Speaker 1: Chris Hey buck Love, the show listen every day. Great job,

1770
01:45:07,320 --> 01:45:09,920
Speaker 1: thanks for keeping us posted with the news. Love the

1771
01:45:10,000 --> 01:45:12,439
Speaker 1: Hillary impersonation. You had to be rolling with the Hillary

1772
01:45:12,520 --> 01:45:15,640
Speaker 1: Halloween trick or treat. I hear you talking about the

1773
01:45:15,680 --> 01:45:18,439
Speaker 1: Democrat governors and mayors and how terrible they're handling the

1774
01:45:18,439 --> 01:45:21,160
Speaker 1: COVID deal, calling them out. Don't forget to rip on

1775
01:45:21,280 --> 01:45:25,760
Speaker 1: King Polis, our tyrannical governor in Colorado and his sidekick

1776
01:45:26,520 --> 01:45:29,960
Speaker 1: Michael Hancock, the terrible mayor of Denver who has ten

1777
01:45:30,040 --> 01:45:33,560
Speaker 1: cities all over and together they let the peaceful protesters

1778
01:45:33,960 --> 01:45:36,840
Speaker 1: spray paint the capitol. It's sad and disgusting. So give

1779
01:45:36,880 --> 01:45:41,599
Speaker 1: them hell, well, Chris, I'm giving them hell right now. Absolutely. Polis,

1780
01:45:41,680 --> 01:45:46,280
Speaker 1: the governor of California, California, the governor of California as

1781
01:45:46,320 --> 01:45:50,559
Speaker 1: a different governor. The governor of Colorado is doing a

1782
01:45:50,640 --> 01:45:52,960
Speaker 1: terrible job and we all know that. And it's a

1783
01:45:53,000 --> 01:45:56,439
Speaker 1: shame the Colorado has become this state that's blue, such

1784
01:45:56,439 --> 01:45:59,839
Speaker 1: a beautiful place, so much going for it. But that's

1785
01:45:59,880 --> 01:46:03,760
Speaker 1: the issue. Democrats. They leave the places they've ruined, as

1786
01:46:03,760 --> 01:46:06,280
Speaker 1: we know, and then they want to ruin other places

1787
01:46:06,280 --> 01:46:10,160
Speaker 1: with the same failed policies, the same bad ideas. So

1788
01:46:10,920 --> 01:46:13,800
Speaker 1: that's that's something that we have to find an antidote too.

1789
01:46:13,840 --> 01:46:15,479
Speaker 1: We have to find a way to push back against that.

1790
01:46:15,520 --> 01:46:19,160
Speaker 1: Otherwise we're gonna keep on running into the same problems,

1791
01:46:19,200 --> 01:46:23,240
Speaker 1: the same same nonsense. Friends, that's the show for today.

1792
01:46:23,280 --> 01:46:26,360
Speaker 1: Please pass the buck. Share the podcast with someone in

1793
01:46:26,400 --> 01:46:28,040
Speaker 1: your life. Be like, Hey, check out this guy Buck,

1794
01:46:28,040 --> 01:46:29,559
Speaker 1: and then just text it to him, email it to

1795
01:46:29,640 --> 01:46:31,960
Speaker 1: him until tomorrow. Shields hig