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Speaker 1: All here on the Big One.

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Speaker 2: Gary jeff on a snowed in Tuesday night, got a

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Speaker 2: good show if we can pack it all in half

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Speaker 2: an hour less, So if there's time, we will have

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Speaker 2: Yanya Kelleck on tonight. He is a senior editor at

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Speaker 2: something called the Epoch Times. If you're not familiar with

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Speaker 2: the Epoch Times or the Epic Times, and they joke

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Speaker 2: about how to pronounce it within that organization. It is

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Speaker 2: probably the most balanced news source you could possibly find,

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Speaker 2: and no aspersions on anyone else. But it's really straight

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Speaker 2: down the middle news, and it's news that a lot

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Speaker 2: of the mainstream media is not covering, like, for example,

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Speaker 2: Communist China's organ harvesting program, which is a live and

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Speaker 2: well which is something you can't say for the people

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Speaker 2: that it targets. There's a new book called Killed to Order.

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Speaker 2: If we go to it, great, Yanya Kellek Here tonight

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Speaker 2: we have a repeat of Saturday's Rock and Roll Archaeology

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Speaker 2: Waiting in the wings should be right around ten o'clock

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Speaker 2: and again everything may or may not get moved back.

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Speaker 2: A guy named Jonathan Butcher who says, through a lot

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Speaker 2: of research and study that we are simply not as

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Speaker 2: divided as the media tells us. We are good discussions

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Speaker 2: ahead there. Dave Hatter with some tech talk before we're done.

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Speaker 2: Thomas Haviland, who has been a guest on the program

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Speaker 2: many times, will join us again tonight to talk about

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Speaker 2: the latest research into the white fibrous blood clots that

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Speaker 2: have been found in corpses ever since the rollout of

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Speaker 2: the COVID vaccine. And there is more disturbing news tonight

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Speaker 2: with the latest and also the fur Ball Andy Furman

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Speaker 2: with half an hour or so of good conversation. We

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Speaker 2: always have a lot of fun. We're glad that you're

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Speaker 2: in and you're safe, and you're ready for some action

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Speaker 2: on the Nightcap and it all begins in just a

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Speaker 2: few here on seven hundred WLW. Here on seven hundred

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Speaker 2: WLW and joining us tonight is Yanya Kellik, who is

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Speaker 2: a senior editor at the Epoch Times or Epic Times.

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Speaker 2: I know that there's kind of a joke around the

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Speaker 2: office that they both call it the Epoch and the

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Speaker 2: Epic Times, but it's one of the most down the

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Speaker 2: middle news sources and they cover stories that no one

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Speaker 2: else is covering. And so Yan is doing the same

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Speaker 2: thing with his brand new book called Killed to Order

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Speaker 2: about forced Chinese organ harvesting. As ghoulish as it sounds,

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Speaker 2: it is going on. It's been going on, and it's

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Speaker 2: something that we all ought to know about. And Yan

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Speaker 2: has written this wonderful book, particularly about the organ harvesting

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Speaker 2: that the Communist Chinese Party is involved in. And he's

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Speaker 2: going to talk with us for a few minutes tonight

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Speaker 2: on that. John, Welcome to the show. How are you.

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Speaker 3: I'm deeply honored to be on your show, and I'm

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Speaker 3: so glad that you're eager to cover this. You know,

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Speaker 3: terrible atrocity that's happening in China right now, has been

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Speaker 3: for the last twenty to twenty five years.

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Speaker 2: Right But if it can happen there, we know for

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Speaker 2: a fact that we have Communist Chinese agents in this country.

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Speaker 2: What's to stop them from doing it here in the

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Speaker 2: United States?

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Speaker 1: I mean, not that it's any.

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Speaker 2: Less grisly, because it's not, as far as we know,

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Speaker 2: going on here. But there are all kinds of Chinese

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Speaker 2: nationals still in our country, and the Communist Chinese government

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Speaker 2: believes that they are are possessions of theirs, and so

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Speaker 2: you know, what's what's to stop them from taking their

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Speaker 2: own people off the streets in this country.

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Speaker 4: Huh.

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Speaker 3: Well, so let me lay out for you what makes

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Speaker 3: this particular situation in China kind of you and more

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Speaker 3: horrifying than most people are ready to accept, at least

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Speaker 3: for the last twenty years or so. So you kind

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Speaker 3: of need what you would call a state actor. Okay,

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Speaker 3: you need someone who has total control over a society,

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Speaker 3: or a lot of control over society. You need to

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Speaker 3: have the ability to push heavy propaganda into a population,

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Speaker 3: to be able to dehumanize a group of people, something

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Speaker 3: like what existed in the nineteen thirties, for example in Germany,

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Speaker 3: right when the Germans dehumanize the Jews. You also have

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Speaker 3: to have the ability to incarcerate a large number of people,

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Speaker 3: and that's typically only a state actor can do that.

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Speaker 3: And this is what the Chinese Communist Party has done

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Speaker 3: repeatedly with different groups over the years. You know, in

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Speaker 3: nineteen eighty nine, after them and Square Masker and so forth,

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Speaker 3: there was a lot of incarceration of students and so forth.

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Speaker 3: But in nineteen ninety nine, ten years after that, there

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Speaker 3: was a very popular spiritual discipline. It was called Fallongong.

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Speaker 3: It was truthfulness, compassion, tolerance. These are the principles people

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Speaker 3: were practicing in very grassroots, very bottom up. There a

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Speaker 3: lot of individual agency. The regime did not like this,

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Speaker 3: so they made it illegal, and then they said, we're

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Speaker 3: going to re educate people. They're going to have to

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Speaker 3: renounce their belief in this. But these people would not

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Speaker 3: basically be brainwashed easily, and so they started incarcerating them

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Speaker 3: at the same time. Remember they're dehumanizing them through propaganda.

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Speaker 3: These people were kind of like on way moral pillars

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Speaker 3: in society before that. They had to convince society that

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Speaker 3: they should be suspicious of them or even hate them.

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Speaker 3: And then they incarcerated say a million, it's not clear

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Speaker 3: how many. Of course this is all a state secret,

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Speaker 3: but a lot. Now they started blood typing, tissue typing,

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Speaker 3: organ scanning, all of this kind of stuff. That population

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Speaker 3: that was across the labor camps, prisons, and other sort

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Speaker 3: of incarceratory operations in China. So now if I'm an

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Speaker 3: American or in South Korea or somewhere else, I'm reading

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Speaker 3: an ad online and I'm kind of desperate because i

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Speaker 3: need a new heart, and I've been waiting for a

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Speaker 3: couple of years and they haven't found a match for me,

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Speaker 3: and I might die any moment, and they say, well,

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Speaker 3: for two hundred grand, I'm going to get you a

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Speaker 3: new heart in two weeks. And that's extremely tempting because

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Speaker 3: and the reason they can do that and they can

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Speaker 3: schedule it, and it means that they know and someone's

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Speaker 3: going to be dead is because that's so called donor

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Speaker 3: is incarcerated in prison, the prisoner of conscience. It started

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Speaker 3: with the fell and gone okay, and they're already blood

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Speaker 3: typed in type, already matched and ready to be killed

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Speaker 3: to order. And that's why the book is called killed

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Speaker 3: to order because and so this is something you know,

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Speaker 3: this is not your garden variety black market organ operation.

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Speaker 3: This is a whole nother level.

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Speaker 1: Wow. And and it is going on as we speak

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Speaker 1: and as we speak.

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Speaker 2: And people from you mentioned Americans, Koreans, others.

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Speaker 3: Who have people from all over the world have gone

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Speaker 3: from what we know, and there was even a Korean

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Speaker 3: film crew that went kind of posing as people looking

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Speaker 3: for transplants. We just found shocking things a few years back.

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Speaker 2: Yeah, Well, I mean we know that the communist Chinese

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Speaker 2: government does not value the individual, especially an individual like

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Speaker 2: you mentioned the Felon Gong, so people exhibiting as you well,

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Speaker 2: put it on that individual element away from the collective.

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Speaker 2: And we've heard the horror stories about what they've done

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Speaker 2: imprisoning Wiger Muslims for example. In addition and the slave

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Speaker 2: labor that's being used to produce these cheap goods.

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Speaker 3: You know, you raise a massive point here, by the way,

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Speaker 3: this is so they started, they built their whole transplant

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Speaker 3: industry on the backs of the Felon Gong. Basically over

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Speaker 3: between two thousand and two thousand and five, the data

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Speaker 3: shows that there was this exponential growth. Thousands of transplant

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Speaker 3: hospitals are being built and are active. Okay, and then

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Speaker 3: we get to twenty fourteen, and you know, basically, no

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Speaker 3: one's really done anything about this. No one has really

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Speaker 3: challenged the regime meaningfully. There's been a little bit few

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Speaker 3: laws passed in a few countries. And then they think

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Speaker 3: to themselves, hey, look, no one has really cared. We

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Speaker 3: have this other population that we're kind of interested in

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Speaker 3: getting rid of. So and these are the Wigers, like

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Speaker 3: you pointed out up in northwest, very vulnerable population under

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Speaker 3: military control in northwestern China, and she and John province

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Speaker 3: and then they dehumanize them even further as a as

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Speaker 3: a nethnic minority. And then they put them million of

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Speaker 3: them in the camps and they started working on them

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Speaker 3: as a second group. Right, And this is my biggest

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Speaker 3: concern is you're kind of alluded to this, right. When

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Speaker 3: you don't deal with things like this, they spread, right.

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Speaker 3: And I've even written op eds and when in the

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Speaker 3: Baltimore Sun recently about our own complicitly our own how

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Speaker 3: how we're being changed by China and the way they

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Speaker 3: operate there. But I'm worried, you know, right now over Christmas,

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Speaker 3: you saw this massive ramp up in the persecution of

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Speaker 3: Christians right in China, and back in October, right there's

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Speaker 3: the Zion Church got all rolled up and there's still

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Speaker 3: all incarcerated now over there. So I'm worried that since

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Speaker 3: there's still has been in action. This is part of

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Speaker 3: the reason for this book Killed to Order, by the way,

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Speaker 3: it's Killed to Order dot com if you're looking interested

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Speaker 3: in checking it out, that it will that it will

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Speaker 3: shift to the next group, to house Christians, to positive Tibatans,

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Speaker 3: to other very vulnerable groups that the regime would be

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Speaker 3: very happy to see not around.

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Speaker 2: Well, you talk about us being many of us being

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Speaker 2: complicit or just ignoring the fact that it's going on,

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Speaker 2: which is a dangerous thing to do, and you pointed

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Speaker 2: out the reasons why. Uh, but how how do you

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Speaker 2: get inside? And how did you get your information in

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Speaker 2: such a closed society? I mean it it was months

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Speaker 2: before we found out how many people had been incinerated

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Speaker 2: during the COVID outbreak that came out of communist China,

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Speaker 2: and people were being you know, welded into their apartments

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Speaker 2: to die, basically to keep them separate from the rest

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Speaker 2: of the population.

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Speaker 1: How do you get how does somebody like.

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Speaker 2: Jan you kind get inside and get the information that

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Speaker 2: you have in this.

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Speaker 3: Book, So by standing on the shoulders of giants. So

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Speaker 3: there's there's probably been less than ten people who have

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Speaker 3: been I think the real hero researchers of this issue.

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Speaker 3: It started with a guy named Yakob Leavie who was

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Speaker 3: a professor of transplant surgery at Tel Aviv University and

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Speaker 3: he actually had a patient that had had done got

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Speaker 3: a new heart transplant in two weeks, which got him involved.

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Speaker 3: Then there was two Canadian human rights lawyers. One was

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Speaker 3: a former Secretary of State David Kilgore, and another one

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Speaker 3: was involved in hunting down the last Nazi war criminals

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Speaker 3: in Canada. David made us so they actually and then

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Speaker 3: there was a whole team of Chinese on this group

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Speaker 3: called the World Organization Investigate the Persecution of Fell and

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Speaker 3: Gong that actually did a lot of both had contacts

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Speaker 3: inside China, you know, doing groundwork, but also did a

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Speaker 3: lot of phone in stuff from outside, like even talking

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Speaker 3: things like I mean, crazy stuff like they would call

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Speaker 3: hospitals and the hospitals would admit that they're doing transplants

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Speaker 3: into weeks that they're found they're using Fell and Gong.

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Speaker 3: These things that these conversations have been verified as real too.

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Speaker 3: You know, it wasn't just the why by night and

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Speaker 3: this has work done over twenty five years. And then

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Speaker 3: you know there's been I mean, there's even been a

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Speaker 3: crazy book written back in the mid two thousands called

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Speaker 3: Larry's Kidney where a guy you know charts his cousins

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Speaker 3: or brothers visit to China to get one of these

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Speaker 3: illicit organs and it's all kind of it's a lot

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Speaker 3: of this kind of odd information or another example, while

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Speaker 3: I won't I won't go sort of delabor the point.

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Speaker 3: But there's been I would say in probably about ten.

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Speaker 3: Most recently a guy named Matthew Robertson who wrote a

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Speaker 3: whole PhD. Pisis on this and a paper in the

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Speaker 3: American Journal of Transplantation titled Execution by Organ Procurement. He

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Speaker 3: worked with the act Obiliviy on this, and what they

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Speaker 3: showed was in that in the published US, not US,

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Speaker 3: but published transplant literature wherever it was public. Right, there's

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Speaker 3: at these seventy papers in which Chinese scientists, researchers, doctors,

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Speaker 3: surgeons have violated the dead donor rule. What that means

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Speaker 3: is is the person was killed by their organs being removed.

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Speaker 3: And the way I read that is that it's just

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Speaker 3: normal over there, that's just how it's done. So they've

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Speaker 3: forgotten that. They can't write you this murder into their

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Speaker 3: scientific methods.

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Speaker 1: It's Frankenstein.

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Speaker 2: But they're using live people to do it, who would

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Speaker 2: be live other than having their heart plugged out of

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Speaker 2: their chest.

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Speaker 1: While I we're still that's crazy. I believe it's really extreme.

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Speaker 3: It's really extreme, and this is for years it's been

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Speaker 3: really hard to even you know, most people, most rational

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Speaker 3: people and thoughtful people, empathetic people just don't want to

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Speaker 3: deal with something that's extreme. It just sounds so macabre

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Speaker 3: and out there. I kind of it's sort of shifted.

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Speaker 3: And that's part of the reason why I've written Killed

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Speaker 3: to Order is I feel like most people I talk

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Speaker 3: to these days are just like, oh my god, that's horrible,

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Speaker 3: but they're not checking out in the middle of the conversation,

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Speaker 3: which is what would happen ten even ten years ago.

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Speaker 3: So no, I'm grateful that we're ready to accept that

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Speaker 3: this is real because I think we need that in

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Speaker 3: order to actually stop it well, and.

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Speaker 2: We need to know exactly what we're facing in the

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Speaker 2: enemy that is not only communists China, but communism in general,

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Speaker 2: because this is what happens every time there is this

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Speaker 2: one party authoritarian rule. Yeahn they they treat they.

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Speaker 1: Treat people like their possessions.

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Speaker 2: Like I said, they're not people, they're they belong to

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Speaker 2: them to do whatever they want.

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Speaker 3: You know, this is such an important point and I

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Speaker 3: wish more people frankly understood this reality. But so a big,

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Speaker 3: a big part of the book is helping, you know,

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Speaker 3: explain how that system actually works using this organ harvesting as.

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Speaker 1: A lens and one of the topics I cover.

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Speaker 3: And there is something we call, even in the West,

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Speaker 3: utilitarian bioethics, okay, And so utilitarian bioethics is an approach

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Speaker 3: it's like the greatest good for the greatest number, or

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Speaker 3: the greatest happiness for the greatest numbers, another way to

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Speaker 3: describe it. And this is sort of deeply embedded in

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Speaker 3: every communist society because and what happened. The crazy part

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Speaker 3: is in communist societies, the greatest good for the society,

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Speaker 3: part of the communist party, is the survival of the

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Speaker 3: communist party. Right, so the greatest good any number of

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Speaker 3: people can be sacrific for the greatest good of the

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Speaker 3: communist party, of course, right, what could be more important?

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Speaker 3: And that's why this is this I figured this out,

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Speaker 3: you know, basically writing the book. And it's just that

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Speaker 3: this is why you get mass atrocities every single time,

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Speaker 3: as you rightly pointed out, in these communist societies.

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Speaker 2: Janya kelik Uh, and I hope I didn't butcher your

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Speaker 2: last name.

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Speaker 3: Young you are I would say you're the top one

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Speaker 3: percent tyler pronouncing the correctly for bank.

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Speaker 2: You John Ya kelik Senior editor at the Epoch Times

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Speaker 2: and the author of Killed to Order. Go to killto

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Speaker 2: Order dot com if you would like to order killed

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Speaker 2: to Order and thank you so much for your time tonight, John.

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Speaker 3: Yeah, thanks so much. It's coming out March seventeen.

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Speaker 1: March seventy. You can pre order now. Okay, one hundred percent.

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Speaker 3: Thank you so much, sir.

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Speaker 1: This is great, fantastic.

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Speaker 2: I wish you very very much success with that and

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Speaker 2: getting the word out of what's actually going on. And

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Speaker 2: this goes on, as he mentioned, in every communist society.

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Speaker 2: Eventually they own you, they control you, and decide whether

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Speaker 2: you get to live or not at a whim or

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Speaker 2: maybe at the cost of a rich tourist who needs

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Speaker 2: a kidney or a heart. Rock and Roll Archaeology the

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Speaker 2: replay coming up in minutes on seven hundred w l W.

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Speaker 2: Uncle Milestones with another edition of Rock and Roll Archaeology

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Speaker 2: on seven hundred W l W.

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Speaker 1: Without a warning.

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Speaker 5: You took, you said you.

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Speaker 4: Die, come ever in pain?

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Speaker 6: Maybe please and maybe you feel let me bleed show you.

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Speaker 7: Let it shine on me, Let it shine on me,

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Speaker 7: Let us shine, shine, shine and shine. I'll get a

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Speaker 7: little lonely in the middle even night I need you

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Speaker 7: die to.

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Speaker 1: Make things all day.

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Speaker 6: Come on, pain, come on, please come on, say there,

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Speaker 6: come on, please.

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Speaker 5: Show all your right Let it shine on me.

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Speaker 8: Just a little bit hardh a little bit higher, just

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Speaker 8: a little bit the incredible Bobby Blue Bland and turn

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Speaker 8: on your love light.

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Speaker 2: Kicking things off rock and roll archaeology. We bring in

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Speaker 2: the prof the music professor, Jim Lebarbar tell me about

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Speaker 2: Bobby Blue Bland, but.

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Speaker 9: To celebrated the birthday on January twenty seventh. Dropped out

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Speaker 9: of school in the third grade to work in the

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Speaker 9: cotton fields and never graduated from high school. Developed that sound,

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Speaker 9: mixing gospel with the blues and R and B. Great

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Speaker 9: storyteller inspiration behind that unique style. A preacher, a Detroit

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Speaker 9: preacher by they was C. L. Franklin. He studied his

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Speaker 9: sermons that was a reefer's daddy and sometimes referred to

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Speaker 9: as the Lion of the blues or the Sinatra of

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Speaker 9: the blues. And with that song turn on Your Love life,

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Speaker 9: that expanded his fan base. He said it crossed over

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Speaker 9: from the Chipman circuit. It got if I can say

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Speaker 9: the white people to listen Bobby Blue Bland and turn

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Speaker 9: on your love.

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Speaker 2: Light another posthumous birthday that we'll celebrate on this rock

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Speaker 2: and roll archaeology. Tragically, he died the way he died,

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Speaker 2: But Terry Katt of Chicago we remember, Yeah.

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Speaker 9: Of January thirty, first birthday, founding member of Chicago, played

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Speaker 9: the guitar, lead guitar, saying vocals on the love of

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Speaker 9: the early records and the guys in the band and

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Speaker 9: other musicians really called out his guitar skills and is

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Speaker 9: Ray Charles influenced vocal style. Jimmy Hendricks said Terry Kat

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Speaker 9: the best guitar player in the universe from Jimmy Hendricks Well.

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Speaker 9: In nineteen seventy eight, after a party at the home

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Speaker 9: of a roadie Don Johnson in La Terry Knt again

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Speaker 9: played with his guns. He spun his downloaded thirty eight

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Speaker 9: Revolve on his finger, put it to his temple, pulled

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Speaker 9: the trigger and the guy said, hey, you can't heiny.

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Speaker 9: We'll be careful, and he basically said, John said, don't

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Speaker 9: worry about Lloyd. Look, the cliff is not even in it.

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Speaker 9: His last words were, what do you think I'm going

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Speaker 9: to do? Blow my brains out, and then showed Terry

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Speaker 9: Kat showed him the empty magazine. Cat then replaced the

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Speaker 9: magazine in the gun, put the gun in his temple,

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Speaker 9: pulled the trigger, and apparently didn't remember that the gun

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Speaker 9: had around in the chamber. He died instantly from the gunshot.

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Speaker 9: And this was one of his giant records that he

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Speaker 9: sang lead on.

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Speaker 10: Uh.

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Speaker 9: Trombone player James Pancott wrote this song was part of

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Speaker 9: a thirteen minute suite called Ballet for a Girl in

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Speaker 9: Buchanan and record executives, without the band's permission, edited the

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Speaker 9: song and released it turned but it turned into their

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Speaker 9: first top ten hits. Terry Kat singing the lead vocals,

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Speaker 9: bringing a gritty, soulful feel to the rock track make

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Speaker 9: Me Smile.

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Speaker 4: In the fuck They don't know.

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Speaker 5: I'm a loud in the.

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Speaker 11: Time time on see your best inside Me tell me.

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Speaker 1: Make me smile? Well, you're right.

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Speaker 2: That Uh that Ray Charles influences all over that forgot

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Speaker 2: How much I love that record? Another posthumous birthday celebration,

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Speaker 2: gone but not forgotten.

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Speaker 1: Leslie Gore.

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Speaker 9: Yeah, let's say go ahead this week, this week in

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Speaker 9: nineteen sixty four, now in Cincinnati, not in the national charts,

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Speaker 9: but in Cincinnati. Lesley Gore preceeding the Beatles, because next

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Speaker 9: week the Beatles take over all the charts forever, and

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Speaker 9: they were never but this week was the number one

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Speaker 9: record in Cincinnati. A seventeen year old girl from Telefly,

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Speaker 9: New Jersey, hits number one with a landmark feminist anthem

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Speaker 9: written by John Madera and Dave White. Now, she told

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Speaker 9: me she was in the Catskills sitting by this moom

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Speaker 9: pool relaxing before doing the record.

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Speaker 1: Hup for a guy.

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Speaker 9: She said, it was a freebee, was Timmy, it was

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Speaker 9: a freebee, was doing him a favorite. Well, these two

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Speaker 9: guys come by. They have a guitar and they said,

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Speaker 9: you gotta hear this song. And then they take her

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Speaker 9: into a cabana and played the song and she liked it.

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Speaker 9: She said, you know, I really like this. Meet me

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Speaker 9: in New York with Princy Jones.

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Speaker 1: On Monday, and they did.

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Speaker 9: And then a week later she got in the studio,

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Speaker 9: cut this song and loud, they're going more freedom vocally

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Speaker 9: and it predated the Women's liberation movement and Helen readies

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Speaker 9: I am woman by a good year.

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Speaker 1: I could seven.

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Speaker 9: Years and this this was a giant record, never hit

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Speaker 9: number one. It was the number two, but number one

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Speaker 9: in Cincinnati. Heard Handsome to the Women Leslie Gort and

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Speaker 9: you don't own me, You don't.

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Speaker 1: All I'm not just one of your to alreadies.

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Speaker 4: You doing all me.

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Speaker 5: Don't say I can't go.

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Speaker 11: With what to do? Tell me what to say?

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Speaker 4: You don't know. Don't try to change me.

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Speaker 12: You don't know me.

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Speaker 4: Don't tell me. Don't beside you what to say? You

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00:24:22,480 --> 00:24:25,320
Speaker 4: what to do? So change.

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Speaker 1: Oh.

401
00:24:36,560 --> 00:24:40,040
Speaker 4: Yeah.

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Speaker 2: This week in rock and roll history, number one in

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Speaker 2: Cincinnati and born in Cincinnati on January thirtieth, is our

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00:24:49,080 --> 00:24:53,600
Speaker 2: next artist who again this is gone but certainly not forgotten.

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Speaker 1: Artist who was Marty Bennett Ballen.

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Speaker 9: Yeah, Martin Buckwald buck Bald. But he didn't graduate from

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00:25:02,280 --> 00:25:05,520
Speaker 9: school here. He was graduate in high school from San Francisco.

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00:25:05,600 --> 00:25:09,080
Speaker 9: Born in Cincinnati, and in nineteen sixty two, Buckwald changed

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Speaker 9: his name the Mardy Balen and had a club turned

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00:25:13,160 --> 00:25:17,200
Speaker 9: a little nightclub and San Francisco launched the restaurant turn

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Speaker 9: club that he created named the Matrix, And that's where

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00:25:19,600 --> 00:25:21,760
Speaker 9: the group was born. And he was one of the

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Speaker 9: lead singers and songwriters from nineteen sixty five and nineteen

414
00:25:24,800 --> 00:25:27,720
Speaker 9: seventy one with Jefferson Airplane quit the band in seventy one,

415
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Speaker 9: fed up at the antiics to Paul Kantner and Greistie Slick,

416
00:25:31,440 --> 00:25:34,800
Speaker 9: and then in nineteen seventy five got back and then

417
00:25:34,800 --> 00:25:38,960
Speaker 9: became Jefferson Starship and he became a great lead singer

418
00:25:38,960 --> 00:25:42,119
Speaker 9: with him, had several hits for three years, one after another,

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Speaker 9: and he.

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Speaker 1: A lead on this record.

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Speaker 9: It was the song he wrote about his girlfriend Barbara

422
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Speaker 9: at the time, and also about the miraculous powers, and

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00:25:50,640 --> 00:25:54,200
Speaker 9: inspired by an Indian gurrouse singing and his readings of

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00:25:54,720 --> 00:25:59,479
Speaker 9: Persian poetry reading regarding love and God poetry that quated

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Speaker 9: making love to a woman as a metaphor for making

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00:26:02,160 --> 00:26:04,399
Speaker 9: love to God. And he wrote this song picked at

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Speaker 9: number three. He sold a million copies. And here it

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00:26:07,359 --> 00:26:41,440
Speaker 9: is Marty BAlN Jefferson Starship and miracles.

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Speaker 4: We get, we get.

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00:27:00,920 --> 00:27:12,440
Speaker 13: Water deep, so we're making love this pi.

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00:27:14,080 --> 00:27:20,359
Speaker 14: It's reading nothing we can you know if we'll put it,

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00:27:21,320 --> 00:27:25,639
Speaker 14: you know, but it's just stops.

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00:27:26,320 --> 00:27:26,880
Speaker 4: It was so.

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Speaker 13: We get by.

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00:27:54,119 --> 00:28:30,040
Speaker 2: So I definitely believe in miracles. The Starship Jefferson Starship

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00:28:30,080 --> 00:28:33,560
Speaker 2: on Rock and Roll Archaeology on seven hutter WLW and

437
00:28:33,960 --> 00:28:37,760
Speaker 2: on January thirtieth. Another birthday, baby, and he's still with us.

438
00:28:37,960 --> 00:28:40,280
Speaker 2: Phil Collins just turned seventy five.

439
00:28:40,960 --> 00:28:43,760
Speaker 9: Oh what a great talent. Phil Collins, born and raised

440
00:28:43,760 --> 00:28:46,240
Speaker 9: in West London, started playing the drums at the age

441
00:28:46,240 --> 00:28:48,440
Speaker 9: of five. At seven seven years old, the other's a

442
00:28:48,480 --> 00:28:51,280
Speaker 9: talent contest. He's singing a ballad of Davy Crockett seven

443
00:28:51,320 --> 00:28:54,240
Speaker 9: years old. Stops the orchestra halfway through to tell them

444
00:28:54,440 --> 00:28:58,360
Speaker 9: you're in the wrong key. A very accomplished professional actor.

445
00:28:58,400 --> 00:29:00,360
Speaker 9: A lot of people don't know this early on when

446
00:29:00,360 --> 00:29:02,920
Speaker 9: he was a teenager, and then he put it into

447
00:29:03,040 --> 00:29:05,760
Speaker 9: the musical career. Became the drummer of course for Genesis

448
00:29:05,760 --> 00:29:08,600
Speaker 9: in nineteen seventy took over the lead role in nineteen

449
00:29:08,680 --> 00:29:11,680
Speaker 9: seventy five when Peter Gabriel left, and then became a

450
00:29:11,680 --> 00:29:14,760
Speaker 9: solo performer. And this was his first single as a

451
00:29:14,800 --> 00:29:18,560
Speaker 9: solo artist. Song that the bandmates or Genesis rejected it

452
00:29:18,680 --> 00:29:21,080
Speaker 9: and Collins wrote this song about the anger he felt

453
00:29:21,080 --> 00:29:26,720
Speaker 9: after divorcing his first wife, Andrea Virturelli. Devastated that he

454
00:29:26,800 --> 00:29:27,960
Speaker 9: left Genesis.

455
00:29:27,480 --> 00:29:27,920
Speaker 15: For a time.

456
00:29:27,960 --> 00:29:31,080
Speaker 9: He was really and thist some lingering tension caused by

457
00:29:31,160 --> 00:29:34,560
Speaker 9: the divorce. It led Collins to the title, negative feelings

458
00:29:34,600 --> 00:29:36,600
Speaker 9: were in the air, and in fact that not just

459
00:29:36,680 --> 00:29:39,600
Speaker 9: the couple getting divorced, but the entire family. And he

460
00:29:39,640 --> 00:29:42,760
Speaker 9: explained that the drowning is a symbolic representing the pain

461
00:29:42,840 --> 00:29:45,200
Speaker 9: and anger he was feeling. The line really was saying

462
00:29:45,240 --> 00:29:47,400
Speaker 9: something like that, I wouldn't give you the time of day,

463
00:29:47,440 --> 00:29:49,560
Speaker 9: and you know not if you were the last person

464
00:29:49,600 --> 00:29:51,520
Speaker 9: on earth. And with that in mind, give a listen

465
00:29:51,720 --> 00:29:54,680
Speaker 9: Phil Collins his first solo hits in the air Tonight,

466
00:29:56,960 --> 00:29:57,920
Speaker 9: Thanks problem.

467
00:30:05,640 --> 00:30:16,120
Speaker 6: I can feel come the night, Bollo. I'm not in

468
00:30:16,240 --> 00:30:28,840
Speaker 6: a way for the Oman roll my Bollo, kenn feel coming.

469
00:30:30,040 --> 00:30:51,200
Speaker 4: Night bulla Bulo told me you were drowning out loved

470
00:30:52,200 --> 00:31:00,880
Speaker 4: the land. I'm seeing your face before my dread no

471
00:31:01,000 --> 00:31:02,680
Speaker 4: week you know who.

472
00:31:02,640 --> 00:31:03,120
Speaker 11: I am.

473
00:31:05,800 --> 00:31:09,280
Speaker 4: Love so much.

474
00:31:10,920 --> 00:31:18,920
Speaker 16: So in mind twice speak quite a game no way

475
00:31:19,320 --> 00:31:21,360
Speaker 16: then saw me.

476
00:31:21,400 --> 00:31:23,120
Speaker 4: In about lies.

477
00:31:26,680 --> 00:31:29,600
Speaker 11: Light coming.

478
00:31:30,840 --> 00:31:31,000
Speaker 4: Night.

479
00:31:33,000 --> 00:31:47,560
Speaker 17: Hello when I'm waiting for Somon. No oh, no, I'm

480
00:31:47,560 --> 00:31:49,719
Speaker 17: being coming.

481
00:31:51,080 --> 00:31:51,240
Speaker 13: Night.

482
00:31:53,200 --> 00:31:58,360
Speaker 4: Hello when I'm waiting for.

483
00:31:58,840 --> 00:32:21,120
Speaker 11: Somon brool, I'm gonna lost Larry.

484
00:32:23,280 --> 00:32:37,760
Speaker 4: Howe guess the person the last time we ever was

485
00:32:37,920 --> 00:32:40,400
Speaker 4: the reason why you can't the.

486
00:32:40,600 --> 00:32:41,320
Speaker 11: Silence of.

487
00:32:43,440 --> 00:32:45,360
Speaker 4: The lousing clean.

488
00:32:46,600 --> 00:32:52,280
Speaker 12: Who he doesn't show but as to lose so strange

489
00:32:52,360 --> 00:33:01,920
Speaker 12: as you men.

490
00:33:04,320 --> 00:33:51,560
Speaker 18: No Black, the Small Rown, no the st Ronny, no Snow.

491
00:34:00,080 --> 00:34:26,759
Speaker 2: The Rock and Roll Archaeologist is a production of the

492
00:34:26,920 --> 00:34:34,400
Speaker 2: Saturday Morning Edition on seven hundred w l W. He

493
00:34:34,520 --> 00:34:37,239
Speaker 2: has been the guy who has been kind of like

494
00:34:37,320 --> 00:34:41,800
Speaker 2: the Paul Revere of the dangers the aftermath of the

495
00:34:41,920 --> 00:34:47,520
Speaker 2: COVID vaccines after the fact, you know, and of course

496
00:34:48,040 --> 00:34:52,000
Speaker 2: he was. He was put upon by the Air Force

497
00:34:52,080 --> 00:34:54,279
Speaker 2: and by the government at the time of the mandates

498
00:34:54,440 --> 00:34:56,680
Speaker 2: to get the jab which of course he never did

499
00:34:56,800 --> 00:34:59,759
Speaker 2: and I never did either. And we have that in

500
00:35:00,320 --> 00:35:03,000
Speaker 2: but we also have in common a need to know

501
00:35:03,880 --> 00:35:08,040
Speaker 2: how much more that we haven't known up to this

502
00:35:08,239 --> 00:35:11,360
Speaker 2: point about the effects of the spike protein and the

503
00:35:11,560 --> 00:35:16,440
Speaker 2: mRNA inside a whole lot of us in this country particularly,

504
00:35:17,160 --> 00:35:21,640
Speaker 2: and around the world. Thomas Hablin, welcome again to the Nightcap.

505
00:35:21,840 --> 00:35:24,840
Speaker 2: You first brought to our attention the white fibrous clots

506
00:35:25,040 --> 00:35:28,080
Speaker 2: that in Balmer's corners have been seeing all over the

507
00:35:28,160 --> 00:35:32,640
Speaker 2: country since the rollout of the COVID nineteen vaccine, and

508
00:35:32,760 --> 00:35:35,960
Speaker 2: we've talked about that in depth, but there's a new

509
00:35:36,000 --> 00:35:36,560
Speaker 2: study out.

510
00:35:36,719 --> 00:35:38,160
Speaker 1: But anyway, welcome to the show.

511
00:35:39,320 --> 00:35:41,680
Speaker 19: Well, Gary Jeff, Yeah, thanks for having me on again.

512
00:35:42,080 --> 00:35:44,880
Speaker 19: In fact, I just completed my fourth annual worldwide and

513
00:35:44,920 --> 00:35:46,960
Speaker 19: Bomber blood clots survey here at the end of twenty

514
00:35:47,000 --> 00:35:50,920
Speaker 19: twenty five, and the results matched the previous year's Gary Jeffy,

515
00:35:51,080 --> 00:35:53,919
Speaker 19: and bombers are seeing the white fibrous clots in about

516
00:35:53,960 --> 00:35:58,960
Speaker 19: seventy percent of their corpses, and actually they're seeing seventy

517
00:35:58,960 --> 00:36:00,439
Speaker 19: percent of them. We are seeing the clot and they're

518
00:36:00,440 --> 00:36:02,680
Speaker 19: seeing them in about twenty percent of their corpses. Okay,

519
00:36:02,840 --> 00:36:06,000
Speaker 19: so that matches my previous years. And one of the

520
00:36:06,000 --> 00:36:09,480
Speaker 19: strange things, Gary Jeff is I had way less respondents

521
00:36:09,520 --> 00:36:11,680
Speaker 19: to this year's survey, and went down from three hundred

522
00:36:11,680 --> 00:36:14,040
Speaker 19: and one in my twenty twenty four survey to only

523
00:36:14,160 --> 00:36:17,120
Speaker 19: fifty nine respondents in this year's survey. I think it's

524
00:36:17,160 --> 00:36:19,680
Speaker 19: because the bambers are in a pickle now. They were

525
00:36:19,719 --> 00:36:21,880
Speaker 19: hoping that these white fireber's clocks would go away, but

526
00:36:21,960 --> 00:36:24,920
Speaker 19: they still know that they're happening. But now they're afraid

527
00:36:24,960 --> 00:36:26,880
Speaker 19: to come out and say that they're seeing them and

528
00:36:26,960 --> 00:36:29,839
Speaker 19: admit that because people the first question they'll ask him is, well,

529
00:36:29,880 --> 00:36:31,960
Speaker 19: where were you four or five years ago when you

530
00:36:32,040 --> 00:36:34,640
Speaker 19: first started seeing these things. So now they're in a

531
00:36:34,719 --> 00:36:37,160
Speaker 19: dilemma where they don't want to talk about it, but

532
00:36:37,320 --> 00:36:38,560
Speaker 19: it's definitely still.

533
00:36:38,360 --> 00:36:44,000
Speaker 2: Happening, all right, and in primarily people who were vaccinated

534
00:36:44,160 --> 00:36:46,279
Speaker 2: correct against COVID nineteen.

535
00:36:46,640 --> 00:36:49,000
Speaker 19: Correct from what we've been able to gather by because

536
00:36:49,040 --> 00:36:51,960
Speaker 19: a lot of the funeral directors and the bambers they

537
00:36:52,080 --> 00:36:53,800
Speaker 19: do dual duty. They're both in the ball ran and

538
00:36:53,840 --> 00:36:56,560
Speaker 19: the funeral directors, and several of them, including a mister

539
00:36:56,680 --> 00:37:00,279
Speaker 19: Dana Goodell who I recently ran into, who's the current

540
00:37:00,320 --> 00:37:04,200
Speaker 19: board member on the Iowa Funeral Director's Association, Dana does both.

541
00:37:04,200 --> 00:37:06,839
Speaker 19: He's a funeral director Annon Balmer, and he says he's

542
00:37:06,840 --> 00:37:09,080
Speaker 19: been getting He says, I've gotten the nasty habit of

543
00:37:09,280 --> 00:37:11,480
Speaker 19: asking the people. When I find the White Fiber's class.

544
00:37:11,880 --> 00:37:13,879
Speaker 19: My first thing I asked him is was your loved

545
00:37:13,920 --> 00:37:16,640
Speaker 19: one did they have COVID? And I say no. Now,

546
00:37:16,840 --> 00:37:19,120
Speaker 19: then I asked him the critical question, did your loved

547
00:37:19,120 --> 00:37:21,880
Speaker 19: one take the COVID vaccine? He said, oh, yeah, But

548
00:37:21,960 --> 00:37:23,719
Speaker 19: then he says he drops it. After that, he doesn't

549
00:37:23,760 --> 00:37:27,080
Speaker 19: go any further because he doesn't want to, you know,

550
00:37:27,640 --> 00:37:30,400
Speaker 19: excite a grieving family basically that their loved one may

551
00:37:30,400 --> 00:37:33,520
Speaker 19: have been killed by the vaccine with these white fibrous clots.

552
00:37:33,640 --> 00:37:36,640
Speaker 2: Well, some people after all this time, Thomas might ask,

553
00:37:37,120 --> 00:37:39,399
Speaker 2: And it looks like it's been all this time. It's

554
00:37:39,440 --> 00:37:42,680
Speaker 2: just been a couple of years. But might ask, oh, well,

555
00:37:42,760 --> 00:37:45,800
Speaker 2: these people are dead already. What does it matter and

556
00:37:45,920 --> 00:37:48,080
Speaker 2: what do these white fibrous clots mean.

557
00:37:49,680 --> 00:37:52,719
Speaker 19: Well, it matters because the white fiber's cloths are probably

558
00:37:52,760 --> 00:37:55,960
Speaker 19: what killed them, right, They're blocking veins and arteries, causing

559
00:37:56,000 --> 00:37:58,800
Speaker 19: strokes and heart attacks. And we've seen a tremendous increase

560
00:37:58,840 --> 00:38:02,680
Speaker 19: in fact younger people as well. And that gets into

561
00:38:02,840 --> 00:38:04,560
Speaker 19: a topic I think we want to talk about a

562
00:38:04,560 --> 00:38:07,759
Speaker 19: little bit as excess mortality, and a lot of people

563
00:38:07,800 --> 00:38:10,879
Speaker 19: don't realize that in a highly vaccinated countries that took

564
00:38:10,920 --> 00:38:14,200
Speaker 19: the COVID vaccine there still appears to be ten percent

565
00:38:14,320 --> 00:38:17,480
Speaker 19: plus excess mortality even in the years twenty twenty two

566
00:38:17,600 --> 00:38:20,640
Speaker 19: through twenty twenty four. People they can actually go on

567
00:38:20,680 --> 00:38:24,080
Speaker 19: a website it's called Our World and Data. Our World

568
00:38:24,160 --> 00:38:26,600
Speaker 19: and Data, and if you look up excess mortality, you

569
00:38:26,640 --> 00:38:29,400
Speaker 19: can find these graphs for all the different countries and

570
00:38:29,440 --> 00:38:33,000
Speaker 19: you can play around with it and select different countries,

571
00:38:33,320 --> 00:38:36,240
Speaker 19: and if you look at countries like the United States, Germany,

572
00:38:38,239 --> 00:38:41,160
Speaker 19: you know, countries that had high uptake of the vaccine.

573
00:38:41,560 --> 00:38:44,520
Speaker 19: You'll see, for example, the United States, and there were

574
00:38:44,640 --> 00:38:46,920
Speaker 19: large spikes in twenty twenty and twenty twenty one in

575
00:38:47,000 --> 00:38:49,720
Speaker 19: excess mortality, which makes sense, right, because the COVID virus

576
00:38:50,000 --> 00:38:52,800
Speaker 19: had just struck twenty twenty year. We did not have

577
00:38:52,920 --> 00:38:56,120
Speaker 19: the vaccines yet, so people were dying of COVID. Twenty

578
00:38:56,200 --> 00:38:59,680
Speaker 19: twenty one, we had the nasty delta variant of COVID,

579
00:39:00,160 --> 00:39:03,400
Speaker 19: large spikes in that year as well, But then the

580
00:39:04,320 --> 00:39:07,239
Speaker 19: excess mortality still stays up at ten percent in twenty

581
00:39:07,320 --> 00:39:09,680
Speaker 19: twenty two, twenty twenty three, and all the way through

582
00:39:09,719 --> 00:39:13,759
Speaker 19: twenty twenty four, which is even after we have much

583
00:39:13,800 --> 00:39:15,920
Speaker 19: milder omicron variant of COVID.

584
00:39:16,000 --> 00:39:19,800
Speaker 2: Yeah, were less people were dying of the virus itself

585
00:39:19,920 --> 00:39:22,480
Speaker 2: in those years, correct.

586
00:39:22,280 --> 00:39:25,120
Speaker 19: Yet the excess mortality is still staying up at ten

587
00:39:25,120 --> 00:39:28,760
Speaker 19: percent plus for highly vaccinated countries. For countries like South

588
00:39:28,800 --> 00:39:31,200
Speaker 19: Africa that had very low uptake of the COVID jabs,

589
00:39:31,920 --> 00:39:35,040
Speaker 19: starting in twenty twenty two, their excess mortality goes back

590
00:39:35,120 --> 00:39:37,360
Speaker 19: down to zero percent, so they're not having any problems

591
00:39:37,360 --> 00:39:40,120
Speaker 19: at all with exces mortality. They had large spikes just

592
00:39:40,200 --> 00:39:42,239
Speaker 19: like the rest of the world in the year twenty

593
00:39:42,320 --> 00:39:45,040
Speaker 19: twenty and twenty twenty one because of the virus, but

594
00:39:45,200 --> 00:39:48,640
Speaker 19: then their excess mortality went to zero starting in twenty

595
00:39:48,680 --> 00:39:52,239
Speaker 19: twenty two because they had less uptake of the COVID vaccines.

596
00:39:52,880 --> 00:39:55,400
Speaker 19: So it's quite damning, you know. And here in the

597
00:39:55,440 --> 00:39:58,719
Speaker 19: United States, for example, that ten percent excess mortality means

598
00:39:58,760 --> 00:40:02,560
Speaker 19: that before the pandemic came around, about three million Americans

599
00:40:03,040 --> 00:40:05,520
Speaker 19: were dying every year. So ten percent of that is

600
00:40:05,560 --> 00:40:09,839
Speaker 19: three hundred thousand. So since twenty one, we've had three

601
00:40:09,920 --> 00:40:14,319
Speaker 19: hundred thousand extra Americans dying every year. Gary Jeff. Three

602
00:40:14,440 --> 00:40:18,160
Speaker 19: hundred thousand extra Americans dying every year. Now, people may

603
00:40:18,560 --> 00:40:20,279
Speaker 19: say to themselves, well, I've not seen that in my

604
00:40:20,960 --> 00:40:23,919
Speaker 19: daily life. That's because it's subtle at the individual level.

605
00:40:24,360 --> 00:40:27,040
Speaker 19: If you think about it, ten percent excess mortality means

606
00:40:27,080 --> 00:40:29,520
Speaker 19: that you may see eleven people die this year versus

607
00:40:29,640 --> 00:40:32,120
Speaker 19: ten last year. Are you really going to notice eleven

608
00:40:32,239 --> 00:40:35,200
Speaker 19: versus ten dying? Probably not right. But when you aggregate

609
00:40:35,239 --> 00:40:39,000
Speaker 19: that up to mass populations, you see three hundred thousand

610
00:40:39,080 --> 00:40:41,719
Speaker 19: extra Americans dying every year, and that's what's been going on.

611
00:40:42,520 --> 00:40:43,480
Speaker 1: I wonder.

612
00:40:46,000 --> 00:40:48,760
Speaker 2: If anyone and I already know the answer to this, Thomas,

613
00:40:48,840 --> 00:40:51,560
Speaker 2: and we've talked about it several times. I wonder if

614
00:40:51,600 --> 00:40:55,880
Speaker 2: anybody is ever going to admit that the cure or

615
00:40:56,000 --> 00:40:59,960
Speaker 2: the prevention was worse than the actual disease.

616
00:41:01,520 --> 00:41:02,719
Speaker 20: There is good news there.

617
00:41:02,760 --> 00:41:06,279
Speaker 19: I mean, for example, very few people have actually taken

618
00:41:06,320 --> 00:41:08,799
Speaker 19: the COVID jabs these days if had. The study came

619
00:41:08,840 --> 00:41:12,279
Speaker 19: out on this last December, seventeenth of December. It was

620
00:41:12,320 --> 00:41:14,800
Speaker 19: a study from the University of New York and University

621
00:41:14,840 --> 00:41:17,680
Speaker 19: of North Carolina at Chapel Hill, and they were surveying

622
00:41:18,239 --> 00:41:22,640
Speaker 19: women of reproductive age, and they saw that only thirteen

623
00:41:22,680 --> 00:41:25,960
Speaker 19: percent of pregnant women actually took the twenty twenty four

624
00:41:26,080 --> 00:41:29,680
Speaker 19: twenty twenty five COVID booster that year. Being interested to

625
00:41:29,680 --> 00:41:32,879
Speaker 19: see how many took this twenty twenty five twenty twenty

626
00:41:32,920 --> 00:41:35,520
Speaker 19: sixth season, my guess is probably even a lower percentage.

627
00:41:35,800 --> 00:41:38,320
Speaker 19: But they asked those women, and there were sixteen hundred

628
00:41:38,320 --> 00:41:42,640
Speaker 19: and eleven women of reproductive age in that study. They

629
00:41:42,680 --> 00:41:45,560
Speaker 19: asked him this question, They said, the COVID vaccine is

630
00:41:46,040 --> 00:41:48,480
Speaker 19: do you agree with this statement, the COVID vaccine is

631
00:41:48,520 --> 00:41:52,640
Speaker 19: safe to receive during pregnancy, Gary Jeff. Only one hundred

632
00:41:52,640 --> 00:41:55,320
Speaker 19: and ninety nine of the sixteen hundred and eleven said

633
00:41:55,480 --> 00:41:58,240
Speaker 19: agreed with that statement. Only twelve percent agree with that statement.

634
00:41:58,760 --> 00:42:02,319
Speaker 19: Others are either uncertain or disagreed with it. Another question

635
00:42:02,360 --> 00:42:05,320
Speaker 19: they asked him was, do you agree with this statement,

636
00:42:05,880 --> 00:42:09,359
Speaker 19: the COVID vaccine reduces the risk of severe disease from

637
00:42:09,440 --> 00:42:13,160
Speaker 19: COVID nineteen during pregnancy Garry Jeff. Only one hundred and

638
00:42:13,200 --> 00:42:17,920
Speaker 19: fifty two of the sixteen nine percent agreed with that statement.

639
00:42:18,520 --> 00:42:22,360
Speaker 19: The other ninety one percent either were uncertain or disagreed

640
00:42:22,400 --> 00:42:24,640
Speaker 19: with it. And these were women, by the way, that

641
00:42:24,680 --> 00:42:27,080
Speaker 19: they actually taken most of them, about ninety seven percent

642
00:42:27,080 --> 00:42:30,919
Speaker 19: of them actually taken the first couple jabs. So people

643
00:42:30,960 --> 00:42:33,279
Speaker 19: are catching on to it now. They're realizing that it

644
00:42:33,360 --> 00:42:36,600
Speaker 19: made a mistake. They may not be telling you publicly

645
00:42:36,640 --> 00:42:39,479
Speaker 19: about it, but privately they're deciding not to get the shot.

646
00:42:39,719 --> 00:42:42,520
Speaker 1: Be hindsight, that's a good sign. Yeah, hindsight's twenty twenty.

647
00:42:42,600 --> 00:42:45,279
Speaker 2: And as they kind of look in the rear view mirror,

648
00:42:45,360 --> 00:42:49,120
Speaker 2: they're seeing all these adverse effects that they told weren't

649
00:42:49,120 --> 00:42:51,440
Speaker 2: going to be a part of their future if they

650
00:42:51,560 --> 00:42:54,719
Speaker 2: protected themselves from COVID nineteen with the JAB.

651
00:42:55,360 --> 00:43:00,080
Speaker 1: And you know that the information that you have held.

652
00:43:01,480 --> 00:43:04,879
Speaker 2: Get out there, and the information that we're finding out

653
00:43:04,920 --> 00:43:11,239
Speaker 2: from a lot of different sources is that THEIRS wasn't reporting.

654
00:43:12,239 --> 00:43:14,840
Speaker 1: All of the adversus side effects.

655
00:43:14,840 --> 00:43:19,520
Speaker 2: Of the JAB, of the mRNA, that not enough was

656
00:43:19,680 --> 00:43:22,920
Speaker 2: known about it when they rolled it out in a

657
00:43:23,040 --> 00:43:26,800
Speaker 2: mad rush, in a mad hurry. And then, you know,

658
00:43:27,040 --> 00:43:30,200
Speaker 2: to compound things, they mandated it for people in the

659
00:43:30,280 --> 00:43:34,960
Speaker 2: military such as yourself, and you were threatened with losing

660
00:43:35,560 --> 00:43:38,640
Speaker 2: everything because you wouldn't accept the job.

661
00:43:39,320 --> 00:43:39,960
Speaker 1: Is that correct?

662
00:43:40,800 --> 00:43:41,000
Speaker 19: Yeah?

663
00:43:41,320 --> 00:43:41,440
Speaker 15: You know.

664
00:43:41,520 --> 00:43:44,600
Speaker 19: The good thing though, governments are turning around. For here, example,

665
00:43:44,600 --> 00:43:47,319
Speaker 19: in the United States, you know Pete Hexas said, hey,

666
00:43:47,360 --> 00:43:49,040
Speaker 19: we're going to let you back the military folks they

667
00:43:49,120 --> 00:43:51,600
Speaker 19: kicked out. You can come back in those that you

668
00:43:51,680 --> 00:43:54,359
Speaker 19: know didn't want to take the job. Canada, by the way,

669
00:43:54,480 --> 00:43:57,080
Speaker 19: is starting to make a turnaround as well. They recently

670
00:43:57,480 --> 00:44:00,760
Speaker 19: their government is now taking direct control for their vaccine

671
00:44:00,840 --> 00:44:03,840
Speaker 19: injury support program that they had Actually they kind of

672
00:44:03,920 --> 00:44:06,520
Speaker 19: shelled it out to a company to administer for them.

673
00:44:06,800 --> 00:44:10,120
Speaker 19: The company was called Auxxero, and the government gave them

674
00:44:10,160 --> 00:44:13,560
Speaker 19: fifty million dollars to distribute to vaccine injured people in Canada.

675
00:44:14,080 --> 00:44:17,319
Speaker 19: They only distributed eighteen million, or the fifty million Gary Jeff.

676
00:44:17,560 --> 00:44:19,759
Speaker 19: They actually had thirty three million of that went to

677
00:44:19,840 --> 00:44:21,600
Speaker 19: administrative cost to the company.

678
00:44:22,600 --> 00:44:23,840
Speaker 20: So Canada said.

679
00:44:23,800 --> 00:44:26,800
Speaker 19: Another of that, they realized they have over ten thousand

680
00:44:26,880 --> 00:44:31,080
Speaker 19: people in Canada have actually filed serious claims of injury

681
00:44:31,160 --> 00:44:32,960
Speaker 19: vaccine injury due to the COVID vaccine.

682
00:44:33,480 --> 00:44:35,160
Speaker 20: So good on them.

683
00:44:35,280 --> 00:44:38,080
Speaker 19: Canada's finally recognizing, Hey, you know a lot of people

684
00:44:38,160 --> 00:44:40,960
Speaker 19: were injured by this this injection, and we need to

685
00:44:42,000 --> 00:44:42,919
Speaker 19: make those people whole.

686
00:44:43,120 --> 00:44:45,560
Speaker 2: Do you believe that there was Do you believe and

687
00:44:45,680 --> 00:44:48,360
Speaker 2: this is without any evidence on your part. You're a

688
00:44:48,920 --> 00:44:51,440
Speaker 2: you're not a researcher. Well you are a researcher, but

689
00:44:51,560 --> 00:44:52,600
Speaker 2: you're not you know.

690
00:44:52,960 --> 00:44:53,720
Speaker 19: I'm not a doctor.

691
00:44:54,200 --> 00:44:57,600
Speaker 2: You're not a doctor, you're not a virologist. But do

692
00:44:57,719 --> 00:45:01,120
Speaker 2: you believe that the an shall roll out of the

693
00:45:01,239 --> 00:45:04,640
Speaker 2: vaccine saved millions of lives? We're told that all the

694
00:45:04,760 --> 00:45:07,480
Speaker 2: time and way, and there's.

695
00:45:07,320 --> 00:45:09,600
Speaker 19: No there are no studies to prove that. That's just

696
00:45:09,680 --> 00:45:11,560
Speaker 19: a statement. They may like like said when they ask

697
00:45:11,640 --> 00:45:14,239
Speaker 19: those pregnant women, do you believe the vaccine reduces the

698
00:45:14,320 --> 00:45:18,359
Speaker 19: risk of severe disease from COVID nineteen during pregnancy? Only

699
00:45:18,480 --> 00:45:21,440
Speaker 19: nine percent agreed with that statement. And there's a good

700
00:45:21,480 --> 00:45:24,000
Speaker 19: reason only nine percent agreed because there has been no proof.

701
00:45:24,400 --> 00:45:27,960
Speaker 19: They people see otherwise, right, they see that you take

702
00:45:28,000 --> 00:45:30,960
Speaker 19: the shot, you're catching the virus anyways, you're transmitting it

703
00:45:31,000 --> 00:45:34,919
Speaker 19: to others. They've heard stories or actually no family members

704
00:45:35,040 --> 00:45:37,560
Speaker 19: or friends who have been injured by the vaccines, you know,

705
00:45:37,920 --> 00:45:39,320
Speaker 19: And this is part of the bad news that we have.

706
00:45:39,480 --> 00:45:42,479
Speaker 19: Right these shots are still available on the market, Gry Jeff.

707
00:45:43,080 --> 00:45:45,279
Speaker 19: We talked about the access mortality being in up ten

708
00:45:45,320 --> 00:45:49,200
Speaker 19: percent plus in countries that have high vaccination rates. We

709
00:45:49,320 --> 00:45:52,400
Speaker 19: know the Big farm is still still planning on retooling

710
00:45:52,480 --> 00:45:55,800
Speaker 19: their other drugs in the future to be mRNA, you know,

711
00:45:55,920 --> 00:45:59,160
Speaker 19: use that same platform with the lip and antoparticle delivery system.

712
00:45:59,800 --> 00:46:02,239
Speaker 19: And then we also have a problem of biolabs out

713
00:46:02,280 --> 00:46:04,920
Speaker 19: there all around the world. There still exists they're working

714
00:46:05,000 --> 00:46:08,400
Speaker 19: on gain of function research on other deadly viruses.

715
00:46:08,320 --> 00:46:09,520
Speaker 20: You know, COVID nineteen.

716
00:46:09,560 --> 00:46:13,719
Speaker 19: The one blessing there is the COVID nineteen virus only

717
00:46:13,800 --> 00:46:17,720
Speaker 19: had a case fatality rate of about zero point three percent.

718
00:46:17,920 --> 00:46:20,160
Speaker 19: In other words, about three out of every one thousand

719
00:46:20,200 --> 00:46:24,560
Speaker 19: people that caught COVID died of it. There's other viruses

720
00:46:24,600 --> 00:46:27,560
Speaker 19: out there, Darry Jeff, like NIPPA virus that have the

721
00:46:27,640 --> 00:46:31,680
Speaker 19: case fatality rate of between forty to seventy percent. Oh yes,

722
00:46:32,520 --> 00:46:36,160
Speaker 19: and there's and we have some good information that appears

723
00:46:36,200 --> 00:46:41,520
Speaker 19: that these biolabs, these are working on, you know, gain

724
00:46:41,560 --> 00:46:44,040
Speaker 19: of function with things like nippa to make it easier

725
00:46:44,080 --> 00:46:46,440
Speaker 19: to catch and make it easier to evade the immune system.

726
00:46:46,520 --> 00:46:48,120
Speaker 19: They don't have to make it any dead layer because

727
00:46:48,120 --> 00:46:53,120
Speaker 19: it's already extremely deadly. There's fifty one bio labs that

728
00:46:53,160 --> 00:46:56,360
Speaker 19: are what's called a BS four lab that where they

729
00:46:56,400 --> 00:46:58,680
Speaker 19: actually you have to use their dress and suits and

730
00:46:58,719 --> 00:47:01,319
Speaker 19: stuff because they's so danger to handle. There's fifty one

731
00:47:01,360 --> 00:47:03,800
Speaker 19: of those labs all around the world, Gary Jeff. And

732
00:47:03,880 --> 00:47:06,680
Speaker 19: then there are thousands of labs that are at thes

733
00:47:07,640 --> 00:47:10,759
Speaker 19: BSL one to BSL three level. So we've got a

734
00:47:10,880 --> 00:47:13,799
Speaker 19: serious problem on our hands. You know, with these all

735
00:47:13,880 --> 00:47:17,360
Speaker 19: these biolabs, we're continuing to work on even more dangerous

736
00:47:17,440 --> 00:47:20,760
Speaker 19: viruses that could potentially be accidentally at least to the public.

737
00:47:21,400 --> 00:47:24,320
Speaker 1: Well, you know what the thing is, Thomas.

738
00:47:24,800 --> 00:47:27,759
Speaker 2: If another country is doing this, another state actor is

739
00:47:27,840 --> 00:47:31,560
Speaker 2: doing this, then the United States obviously thinks, well, we've

740
00:47:31,600 --> 00:47:34,759
Speaker 2: got to be involved because we're going to have to

741
00:47:34,960 --> 00:47:37,719
Speaker 2: come up with a cure if it's going to be

742
00:47:37,800 --> 00:47:41,840
Speaker 2: introduced from one of these other biolabs around the world.

743
00:47:42,520 --> 00:47:45,160
Speaker 2: And there are a lot of people that really don't

744
00:47:45,320 --> 00:47:51,759
Speaker 2: like America and and don't want the West to survive. So,

745
00:47:51,920 --> 00:47:55,480
Speaker 2: I mean, there's so many aspects of this that are frightening.

746
00:47:55,920 --> 00:47:59,759
Speaker 2: But what is most egregious to most of us who

747
00:48:00,040 --> 00:48:02,160
Speaker 2: who don't believe this should be done, this gain of

748
00:48:02,200 --> 00:48:07,080
Speaker 2: function research in the name of making viruses more deadly,

749
00:48:08,480 --> 00:48:10,680
Speaker 2: is that our tax dollars go to that.

750
00:48:11,880 --> 00:48:15,520
Speaker 19: From US funding, our tax dollars go to it. You're

751
00:48:15,520 --> 00:48:19,520
Speaker 19: absolutely right, Gary, Jeff. But the frightening part is is,

752
00:48:19,640 --> 00:48:22,640
Speaker 19: like I say, in trying to work on the defense

753
00:48:23,480 --> 00:48:29,399
Speaker 19: from potential attackers, you also risk the What happened in Wuhan, right,

754
00:48:29,480 --> 00:48:32,960
Speaker 19: what happened, Juan, is the virus got accidentally released and

755
00:48:33,080 --> 00:48:37,120
Speaker 19: then spread quickly around the world. And we saw what happened,

756
00:48:37,800 --> 00:48:40,279
Speaker 19: and like I said, thank goodness, the case fatality rate

757
00:48:40,400 --> 00:48:45,800
Speaker 19: was so small for COVID nineteen virus. But if pathogens

758
00:48:45,840 --> 00:48:49,319
Speaker 19: that have at forty to seventy percent case fatality rate

759
00:48:49,680 --> 00:48:52,840
Speaker 19: get unleashed upon the world, we are in serious trouble,

760
00:48:53,360 --> 00:48:54,000
Speaker 19: you think.

761
00:48:54,520 --> 00:48:55,160
Speaker 1: My goodness.

762
00:48:55,800 --> 00:49:01,360
Speaker 2: Yeah, so our world in data is one of your references, Thomas,

763
00:49:01,440 --> 00:49:02,040
Speaker 2: that you mentioned.

764
00:49:02,239 --> 00:49:04,120
Speaker 19: Yeah, people can go to there. It's on the web,

765
00:49:04,200 --> 00:49:07,000
Speaker 19: and then they can search for excess mortality and they'll

766
00:49:07,000 --> 00:49:10,480
Speaker 19: be able to find graphs and all the countries out there,

767
00:49:11,080 --> 00:49:16,160
Speaker 19: and they can select those and see what the excess bortality. Basically,

768
00:49:16,200 --> 00:49:19,319
Speaker 19: what excess bortality means is they compared the years twenty

769
00:49:19,400 --> 00:49:22,160
Speaker 19: twenty through twenty twenty four to a baseline set of

770
00:49:22,280 --> 00:49:23,960
Speaker 19: years from twenty fifteen through twenty.

771
00:49:23,880 --> 00:49:27,280
Speaker 4: Nineteen BC before COVID exactly.

772
00:49:27,400 --> 00:49:29,080
Speaker 19: So here in the United State, for example, about three

773
00:49:29,160 --> 00:49:32,440
Speaker 19: million Americans died every year in the years twenty fifteen

774
00:49:32,480 --> 00:49:34,719
Speaker 19: to twenty nineteen, but then it started to be three

775
00:49:34,760 --> 00:49:37,640
Speaker 19: point three million dying year, three hundred thousand extra people

776
00:49:37,760 --> 00:49:40,759
Speaker 19: dying a year starting in twenty twenty going forward to

777
00:49:40,840 --> 00:49:41,280
Speaker 19: the present.

778
00:49:41,560 --> 00:49:44,799
Speaker 2: Thomas Ablin, I appreciate your work, and I appreciate your time.

779
00:49:44,840 --> 00:49:48,640
Speaker 2: We're all out of it right now. But let's make

780
00:49:48,680 --> 00:49:51,200
Speaker 2: a plan to do this again soon.

781
00:49:51,320 --> 00:49:53,800
Speaker 4: Okay, thanks Garry Jeff, appreciate it.

782
00:49:53,920 --> 00:49:58,439
Speaker 2: You've bet Thomas Ablin and excess mortality in the era

783
00:49:58,640 --> 00:50:03,920
Speaker 2: of the COVID nineteen vaccine. The Nightcap continues seven out

784
00:50:03,920 --> 00:50:04,760
Speaker 2: of w LW.

785
00:50:06,760 --> 00:50:07,840
Speaker 1: It's the Nightcap.

786
00:50:08,160 --> 00:50:10,680
Speaker 2: And as we get into this hour, always love to

787
00:50:10,800 --> 00:50:11,759
Speaker 2: have the next guest on.

788
00:50:12,480 --> 00:50:14,440
Speaker 1: And he's nice enough to make time for.

789
00:50:14,520 --> 00:50:17,920
Speaker 2: Me when he's a very very busy man not only

790
00:50:18,000 --> 00:50:20,279
Speaker 2: at intrust It but also is the mirror of Fort

791
00:50:20,360 --> 00:50:22,839
Speaker 2: Wright and then he's all over the radio and TV

792
00:50:23,360 --> 00:50:25,759
Speaker 2: other places, but he takes time to talk to little

793
00:50:25,840 --> 00:50:27,720
Speaker 2: ol Me and he's doing so this evening.

794
00:50:28,760 --> 00:50:30,480
Speaker 1: Dave Hatter, how are you.

795
00:50:31,960 --> 00:50:34,280
Speaker 10: I'm good, Garrett Jeff, thanks for having me on as always.

796
00:50:34,320 --> 00:50:34,640
Speaker 10: How are you?

797
00:50:34,880 --> 00:50:35,040
Speaker 15: Yeah?

798
00:50:35,360 --> 00:50:39,560
Speaker 2: I forgot about in listing all of your duties, your responsibilities.

799
00:50:40,000 --> 00:50:44,759
Speaker 2: Of course, your boss dictates all of your activities at

800
00:50:44,840 --> 00:50:46,440
Speaker 2: home and then you.

801
00:50:48,600 --> 00:50:52,160
Speaker 10: And then you have this gives Private Hatter his orders

802
00:50:52,200 --> 00:50:54,000
Speaker 10: and he follows them faithfully, and.

803
00:50:54,040 --> 00:50:56,480
Speaker 1: Then you have you have kids and all the other stuff.

804
00:50:57,520 --> 00:51:00,319
Speaker 2: So first off, with just our few minutes, I wanted

805
00:51:00,360 --> 00:51:06,440
Speaker 2: to talk about this AI license plate reader technology and

806
00:51:07,040 --> 00:51:09,640
Speaker 2: you call it an Orwelliam nightmare, and I would guess,

807
00:51:09,719 --> 00:51:10,759
Speaker 2: so what's going on?

808
00:51:11,480 --> 00:51:14,480
Speaker 10: Yeah, so I think flock cameras and things like that.

809
00:51:14,719 --> 00:51:17,840
Speaker 10: These things have created a lot of controversy. Some cities

810
00:51:17,880 --> 00:51:20,600
Speaker 10: that have deployed them have started pulling them back. And

811
00:51:20,680 --> 00:51:23,759
Speaker 10: I mean, you know you're under conference Surveilanus Carrey, Jeff.

812
00:51:23,760 --> 00:51:26,120
Speaker 10: I don't think anyone is under any illusions. That's not

813
00:51:26,239 --> 00:51:28,000
Speaker 10: the case at this point. You know, there are cameras

814
00:51:28,040 --> 00:51:30,400
Speaker 10: everywhere out there. The big difference with some of this

815
00:51:30,520 --> 00:51:33,160
Speaker 10: new technology is it's not merely just taking a picture

816
00:51:33,200 --> 00:51:35,839
Speaker 10: of your license plate or something like that. These things

817
00:51:35,880 --> 00:51:39,240
Speaker 10: can have facial recognition. We all know facial recognition has issues.

818
00:51:40,120 --> 00:51:42,680
Speaker 10: There's biasing, the AI algorithms. You know, we talked about

819
00:51:42,719 --> 00:51:44,160
Speaker 10: this stuff off and off for the years. But this

820
00:51:44,280 --> 00:51:46,360
Speaker 10: particular article, and I encourage everyone to get read it

821
00:51:46,400 --> 00:51:49,840
Speaker 10: for themselves. AI license plate reader is an Orwellian nightmare.

822
00:51:49,920 --> 00:51:53,040
Speaker 10: This is from Proton. Proton one of my favorite companies

823
00:51:53,080 --> 00:51:55,360
Speaker 10: out there. I use them for my personal email, I

824
00:51:55,480 --> 00:51:58,839
Speaker 10: use their personal VPN. They've got a bunch of other

825
00:51:58,920 --> 00:52:02,239
Speaker 10: products there. Or you know, can you is any trun

826
00:52:02,360 --> 00:52:06,080
Speaker 10: company one hundred percent trustworthy? Probably not but they're known

827
00:52:06,120 --> 00:52:08,520
Speaker 10: in this privacy space. I encourage you to check them out.

828
00:52:08,560 --> 00:52:10,920
Speaker 10: But they did this expose on this which I think

829
00:52:11,040 --> 00:52:13,680
Speaker 10: is really well done, and they don't focus on a

830
00:52:13,719 --> 00:52:16,360
Speaker 10: specific tech as much as just the general idea. And

831
00:52:16,400 --> 00:52:18,880
Speaker 10: they say automated license plate systems have become a routine

832
00:52:18,960 --> 00:52:22,000
Speaker 10: site on the roads, they can perform valuable functions, blah

833
00:52:22,040 --> 00:52:24,080
Speaker 10: blah blah. But then they go on to say, you know,

834
00:52:24,120 --> 00:52:26,879
Speaker 10: instead of police searching for license plate flenks to specific crimes,

835
00:52:26,920 --> 00:52:29,640
Speaker 10: the dehydriven systems can examine millions of license plates to

836
00:52:29,680 --> 00:52:32,640
Speaker 10: analyze the behavior of every car call on camera. When

837
00:52:32,680 --> 00:52:35,720
Speaker 10: it's information, they can identify quote a suspicious table patterns

838
00:52:35,760 --> 00:52:37,960
Speaker 10: such as driving patterns that may be associated with drug

839
00:52:38,000 --> 00:52:42,040
Speaker 10: trafficking activity. Now I understand why people think this all

840
00:52:42,160 --> 00:52:44,920
Speaker 10: makes sense, but my issue is we are slowly but

841
00:52:45,040 --> 00:52:47,200
Speaker 10: surely building a pan opticon. I don't know if your

842
00:52:47,239 --> 00:52:49,279
Speaker 10: listeners are familiar with that term. I encouraged them to

843
00:52:49,280 --> 00:52:51,680
Speaker 10: go look it up. It's an eighteenth century idea from

844
00:52:51,680 --> 00:52:53,680
Speaker 10: a guy who wanted to treat a prison where it

845
00:52:53,680 --> 00:52:55,400
Speaker 10: was circular and the guards were in the middle, so

846
00:52:55,440 --> 00:52:57,080
Speaker 10: you would never know if you're being watched or not.

847
00:52:57,880 --> 00:53:00,279
Speaker 10: And that's what these kinds of systems are building, because again,

848
00:53:00,640 --> 00:53:03,640
Speaker 10: the facial recognition stuff is not perfect. You're being tracked

849
00:53:03,680 --> 00:53:06,839
Speaker 10: all the time. And they explain it in a lot

850
00:53:06,880 --> 00:53:08,600
Speaker 10: more detail than we have time for here. But like

851
00:53:08,680 --> 00:53:12,480
Speaker 10: they say, FLOCK alone, forty thousand license plate reading cameras

852
00:53:12,600 --> 00:53:15,160
Speaker 10: used by five thousand law enforcement agencies and over four

853
00:53:15,239 --> 00:53:19,600
Speaker 10: thousand cities across forty nited states, no oversight or accountability.

854
00:53:19,600 --> 00:53:22,960
Speaker 10: There was a recent story about Flock where someone some

855
00:53:23,200 --> 00:53:25,319
Speaker 10: guy who was concerned about this showed how these things

856
00:53:25,360 --> 00:53:26,960
Speaker 10: were exposed to the Internet and he was able to

857
00:53:27,000 --> 00:53:29,160
Speaker 10: go stand in front of a FLOCK camera and watch

858
00:53:29,239 --> 00:53:32,480
Speaker 10: himself on his own phone. Look it up, folks. So yeah,

859
00:53:32,520 --> 00:53:35,640
Speaker 10: I'm one hundred percent against this stuff. I understand the convenience,

860
00:53:35,680 --> 00:53:38,399
Speaker 10: I understand the security argument. But I'll just go back

861
00:53:38,400 --> 00:53:40,759
Speaker 10: to what Benjamin Franklin said, He who deserves gives up

862
00:53:40,840 --> 00:53:43,839
Speaker 10: liberty in the name of security deserves neither. And that's

863
00:53:43,960 --> 00:53:46,840
Speaker 10: my take on this. We need less of this, not more.

864
00:53:47,920 --> 00:53:51,839
Speaker 2: Agreed, And that's the thing that they're trying to find

865
00:53:51,880 --> 00:53:54,520
Speaker 2: out everywhere you go. You know, during COVID they wanted

866
00:53:54,520 --> 00:53:57,719
Speaker 2: to restrict our travel and this would make something like

867
00:53:57,840 --> 00:54:01,040
Speaker 2: that all easier for them.

868
00:54:02,320 --> 00:54:03,960
Speaker 10: And for what it's worked there, yeah, I agree for

869
00:54:04,080 --> 00:54:05,840
Speaker 10: what it's worth. I mean, you know, folks, if you

870
00:54:05,920 --> 00:54:08,840
Speaker 10: follow me on x, Facebook, LinkedIn, whatever makes sense of you,

871
00:54:08,960 --> 00:54:10,879
Speaker 10: I'm sharing this kind of stuff all the time. I've

872
00:54:10,920 --> 00:54:14,200
Speaker 10: posted this specific article. You know, read it for yourself,

873
00:54:14,239 --> 00:54:15,799
Speaker 10: make up your own mind. I can tell you I'm

874
00:54:15,800 --> 00:54:16,680
Speaker 10: one hundred percent.

875
00:54:16,480 --> 00:54:21,520
Speaker 2: Against uh, Google and AI chat botch can strip women

876
00:54:21,680 --> 00:54:22,600
Speaker 2: down to bikinis.

877
00:54:23,280 --> 00:54:24,239
Speaker 1: What's going on there?

878
00:54:25,440 --> 00:54:25,640
Speaker 19: Yeah?

879
00:54:25,800 --> 00:54:28,200
Speaker 10: So, I mean this this speaks to a couple of

880
00:54:28,280 --> 00:54:30,440
Speaker 10: different problems with AI. I mean, there are lots of them.

881
00:54:31,280 --> 00:54:34,239
Speaker 10: But you know, Groc has come under fire for this

882
00:54:35,000 --> 00:54:37,640
Speaker 10: and it's gotten a lot of press recently. But this,

883
00:54:37,880 --> 00:54:41,440
Speaker 10: this article I sent you, speaks to that. You know,

884
00:54:41,600 --> 00:54:46,080
Speaker 10: all of these generative AI tools chats ept, Google's Gemini,

885
00:54:46,239 --> 00:54:49,279
Speaker 10: Grock have the capability for people to try to do

886
00:54:49,400 --> 00:54:51,120
Speaker 10: what's known as jail breaking, to give them to do

887
00:54:51,280 --> 00:54:55,000
Speaker 10: things they're not supposed to do, to create prompts that

888
00:54:55,160 --> 00:54:57,759
Speaker 10: eventually convince it to do something that's not supposed to do.

889
00:54:58,480 --> 00:55:01,120
Speaker 10: And while again GROC has recently come under fire for

890
00:55:01,200 --> 00:55:04,120
Speaker 10: this because not problem is not exclusive to groc It's

891
00:55:04,160 --> 00:55:06,600
Speaker 10: a problem with just the way these things work, and frankly,

892
00:55:06,680 --> 00:55:10,080
Speaker 10: the difficulty of ensuring that they won't do things that

893
00:55:10,160 --> 00:55:12,080
Speaker 10: they're not designed to do. I tell you how to

894
00:55:12,160 --> 00:55:15,239
Speaker 10: make a bomb or something like that, right, and you know,

895
00:55:15,800 --> 00:55:20,080
Speaker 10: unfortunately that I think this is a sad feature that

896
00:55:20,239 --> 00:55:21,800
Speaker 10: you can go and do something like this, because it

897
00:55:21,880 --> 00:55:23,840
Speaker 10: surely becomes a form of deep fake generation.

898
00:55:24,000 --> 00:55:24,120
Speaker 20: Right.

899
00:55:24,200 --> 00:55:26,160
Speaker 10: You and I have been talking about deep fakes for years.

900
00:55:27,000 --> 00:55:28,520
Speaker 10: But you know, if you have a photo of someone

901
00:55:29,000 --> 00:55:30,800
Speaker 10: and you know how they do the prompting, right, you

902
00:55:30,880 --> 00:55:33,000
Speaker 10: can post it in there and then you know, either

903
00:55:33,080 --> 00:55:35,879
Speaker 10: A put them into bikini or b you potentially trade

904
00:55:35,880 --> 00:55:38,520
Speaker 10: a new photo where they're completely nude and then do

905
00:55:38,640 --> 00:55:43,759
Speaker 10: whatever you want with that. So my personal opinion is,

906
00:55:44,560 --> 00:55:46,359
Speaker 10: and I know they're all working on ways to try

907
00:55:46,400 --> 00:55:48,360
Speaker 10: to stop this, just based on the nature of the

908
00:55:48,440 --> 00:55:50,960
Speaker 10: way these things work, I'm not sure it can be

909
00:55:51,120 --> 00:55:53,600
Speaker 10: done because if you are creative enough in your prompting

910
00:55:54,239 --> 00:55:57,359
Speaker 10: and or you chain enough prompts together, I'm not sure

911
00:55:57,480 --> 00:56:02,120
Speaker 10: how it wouldn't lose the context and not give you

912
00:56:02,200 --> 00:56:03,839
Speaker 10: what you want eventually. And that's one of the ways

913
00:56:03,880 --> 00:56:06,080
Speaker 10: these things are jail broken. Is you work it through

914
00:56:06,160 --> 00:56:09,080
Speaker 10: multiple steps. You don't ask the immediate question of something

915
00:56:09,160 --> 00:56:10,759
Speaker 10: that you know it will tell you it can't do.

916
00:56:11,360 --> 00:56:15,719
Speaker 10: You work your way into it. So it's unfortunate. I

917
00:56:15,800 --> 00:56:18,839
Speaker 10: think it's kind of pathetic really that this is a thing.

918
00:56:19,400 --> 00:56:21,560
Speaker 10: But frankly, about the only thing you can do at

919
00:56:21,600 --> 00:56:24,040
Speaker 10: the moment, if you're somewhat concerned about this, is don't

920
00:56:24,120 --> 00:56:27,400
Speaker 10: post photos of yourself online where then someone else can

921
00:56:27,440 --> 00:56:29,959
Speaker 10: take them and use them. And you know that's getting

922
00:56:30,000 --> 00:56:31,800
Speaker 10: harder and hard to do every day. Gary Jeff and

923
00:56:33,080 --> 00:56:35,400
Speaker 10: the flock camera might be posting photos as you're out there.

924
00:56:35,440 --> 00:56:35,759
Speaker 9: Who knows?

925
00:56:35,800 --> 00:56:38,440
Speaker 10: Are that Ruba sleeper you have that posted the photo

926
00:56:38,480 --> 00:56:39,240
Speaker 10: of you on the toilet?

927
00:56:39,719 --> 00:56:41,040
Speaker 1: Look that up. It's the real thing.

928
00:56:41,120 --> 00:56:43,960
Speaker 10: It's why I despise the Internet of things. You know,

929
00:56:44,120 --> 00:56:47,000
Speaker 10: you're The more you can reduce your digital footprint, the

930
00:56:47,120 --> 00:56:47,840
Speaker 10: better off you'll be.

931
00:56:48,719 --> 00:56:53,320
Speaker 2: You're absolutely correct, because I look absolutely awful in a speedo, Dave.

932
00:56:54,400 --> 00:56:56,120
Speaker 10: And so do wh I Gary jamb that's the last

933
00:56:56,120 --> 00:56:58,600
Speaker 10: thing you want to see, No, because.

934
00:56:58,360 --> 00:56:59,160
Speaker 1: You can't unsee it.

935
00:57:00,440 --> 00:57:02,320
Speaker 10: No, your eyes might bleed.

936
00:57:04,160 --> 00:57:06,279
Speaker 1: Dave Patter, thank you so much and we'll talk to

937
00:57:06,320 --> 00:57:06,680
Speaker 1: you soon.

938
00:57:06,760 --> 00:57:10,160
Speaker 10: My friend I hope, oh, always my pleasure to right.

939
00:57:10,560 --> 00:57:13,759
Speaker 2: Coming up next Jonathan Butcher, who has written a new

940
00:57:13,800 --> 00:57:15,279
Speaker 2: book called The.

941
00:57:18,520 --> 00:57:18,720
Speaker 1: Well.

942
00:57:19,280 --> 00:57:20,960
Speaker 2: You'll hear about it in just a moment, but it

943
00:57:21,080 --> 00:57:25,680
Speaker 2: basically says, through research and study that we're not as

944
00:57:25,760 --> 00:57:29,400
Speaker 2: divided as a nation as we're told by the politicians

945
00:57:29,440 --> 00:57:30,000
Speaker 2: in the media.

946
00:57:31,360 --> 00:57:32,800
Speaker 1: Coming up next on the Nightcap.

947
00:57:34,280 --> 00:57:37,960
Speaker 2: As we continue on this Nightcap, our next guest is

948
00:57:38,240 --> 00:57:41,360
Speaker 2: the Will Skillman, Fellow of Education at the Heritage Foundation,

949
00:57:41,960 --> 00:57:45,360
Speaker 2: author of Splintered, Critical Race Theory and the Progressive War

950
00:57:45,440 --> 00:57:48,080
Speaker 2: on Truth, and he's been involved in editing and writing

951
00:57:48,200 --> 00:57:51,800
Speaker 2: chapters in many other great tomes put out by the

952
00:57:51,840 --> 00:57:56,880
Speaker 2: Heritage Foundation. The newest one is The Polarization Myth America's

953
00:57:56,960 --> 00:58:04,400
Speaker 2: surprising consensus on race, schools, and sex, even though Lord

954
00:58:04,480 --> 00:58:08,560
Speaker 2: knows it's being portrayed as we're just so divided on everything.

955
00:58:10,280 --> 00:58:14,080
Speaker 2: Jonathan Butcher joins us for a few minutes tonight. Jonathan,

956
00:58:14,160 --> 00:58:14,760
Speaker 2: how are you, sir?

957
00:58:16,320 --> 00:58:17,440
Speaker 15: I'm great, Thank you for having me.

958
00:58:18,200 --> 00:58:21,840
Speaker 2: So this is something that I have been kind of

959
00:58:22,040 --> 00:58:25,920
Speaker 2: thinking about and have talked about on the air without

960
00:58:25,960 --> 00:58:29,280
Speaker 2: any kind of proof to back it up, that I

961
00:58:29,440 --> 00:58:35,160
Speaker 2: think that most Americans agree on the most important things

962
00:58:35,280 --> 00:58:39,640
Speaker 2: that matter in our lives, and that the division that's

963
00:58:39,720 --> 00:58:44,920
Speaker 2: being sown, I believe on purpose, the seeming chaos around

964
00:58:45,040 --> 00:58:49,960
Speaker 2: us and the vehement disagreements on things like race and

965
00:58:50,160 --> 00:58:52,160
Speaker 2: gender just aren't so.

966
00:58:52,560 --> 00:58:53,560
Speaker 1: When you get out in.

967
00:58:55,400 --> 00:58:58,840
Speaker 2: A public setting almost anywhere, I mean, just living your

968
00:58:58,920 --> 00:59:02,919
Speaker 2: everyday life, I find that most people have the same

969
00:59:03,840 --> 00:59:07,560
Speaker 2: core values when it comes to these things and are

970
00:59:07,680 --> 00:59:10,240
Speaker 2: not deeply divided.

971
00:59:10,800 --> 00:59:12,960
Speaker 1: So what did you find in writing this book?

972
00:59:14,840 --> 00:59:17,600
Speaker 15: So in my book, I did a nationally representative survey

973
00:59:17,840 --> 00:59:20,280
Speaker 15: of the general public of the US, as well as

974
00:59:20,880 --> 00:59:24,000
Speaker 15: a nationally representative survey of parents. And I mean, look,

975
00:59:24,040 --> 00:59:25,800
Speaker 15: you really only need about a little more than a

976
00:59:25,880 --> 00:59:28,840
Speaker 15: thousand perhaps to get a nationally representative survey, but I

977
00:59:28,920 --> 00:59:31,120
Speaker 15: wanted more, so I had a double the side. I

978
00:59:31,200 --> 00:59:33,000
Speaker 15: had about two thousand people that we were able to

979
00:59:33,080 --> 00:59:35,960
Speaker 15: survey from all over the US to make it representative.

980
00:59:35,960 --> 00:59:37,800
Speaker 15: And I contracted with the company.

981
00:59:37,560 --> 00:59:37,880
Speaker 20: To do it.

982
00:59:38,400 --> 00:59:40,680
Speaker 15: And I asked the hot button questions of the topics

983
00:59:40,720 --> 00:59:44,040
Speaker 15: that you listed right there, including gender, including the idea

984
00:59:44,080 --> 00:59:47,280
Speaker 15: of using racial preferences and college admissions, for example, And

985
00:59:47,640 --> 00:59:52,240
Speaker 15: I found that there was a clear pluralities, if not majorities,

986
00:59:52,280 --> 00:59:55,160
Speaker 15: of my respondents said, we shouldn't be judging people based

987
00:59:55,200 --> 00:59:59,439
Speaker 15: on skin color for job promotion or for admission into

988
01:00:00,200 --> 01:00:03,840
Speaker 15: college or two schools. They also don't want explit books

989
01:00:03,880 --> 01:00:07,800
Speaker 15: with explicit sex acts on shelves in school libraries. They

990
01:00:07,840 --> 01:00:11,160
Speaker 15: want parents to be involved in choosing what books to

991
01:00:11,240 --> 01:00:14,400
Speaker 15: put on school shelves. They want character and virtue taught

992
01:00:14,440 --> 01:00:17,120
Speaker 15: in schools. On all these issues and more, I found

993
01:00:17,120 --> 01:00:21,360
Speaker 15: that there's some very common sense positions that Americans share,

994
01:00:21,480 --> 01:00:23,960
Speaker 15: and that's that's something that we can build an identity

995
01:00:24,000 --> 01:00:26,600
Speaker 15: on and can help lawmakers as they take very strong

996
01:00:26,680 --> 01:00:30,000
Speaker 15: positions against these so called experts who are telling us

997
01:00:30,040 --> 01:00:30,560
Speaker 15: something different.

998
01:00:31,000 --> 01:00:35,040
Speaker 2: So did on the question of gender, did most people

999
01:00:35,560 --> 01:00:38,200
Speaker 2: in the survey come down on the side that there

1000
01:00:38,280 --> 01:00:41,680
Speaker 2: are two sexes and there's not, you know, an unlimited

1001
01:00:41,720 --> 01:00:43,080
Speaker 2: amount of genders.

1002
01:00:45,480 --> 01:00:45,680
Speaker 20: Yes.

1003
01:00:45,760 --> 01:00:48,000
Speaker 15: And it wasn't just my survey. I mean there are

1004
01:00:48,120 --> 01:00:53,080
Speaker 15: surveys from the Gallop and elsewhere that show that people,

1005
01:00:53,360 --> 01:00:56,640
Speaker 15: you know, there are either pluralities or majorities who believe

1006
01:00:56,840 --> 01:01:00,280
Speaker 15: that there are just only two sexes, which of course

1007
01:01:00,760 --> 01:01:03,440
Speaker 15: the biological truth, but even more than that, right, they

1008
01:01:03,480 --> 01:01:06,280
Speaker 15: don't want boys playing on girls' sports team. They don't

1009
01:01:06,280 --> 01:01:08,600
Speaker 15: want boys to have access to girls private spaces like

1010
01:01:08,720 --> 01:01:13,240
Speaker 15: locker rooms and bathrooms. And you know, crucially, they don't

1011
01:01:13,280 --> 01:01:17,120
Speaker 15: want young people taught the concept of gender right or

1012
01:01:17,160 --> 01:01:20,280
Speaker 15: that they can be they can be born in the

1013
01:01:20,320 --> 01:01:23,200
Speaker 15: wrong body. And we have a policy that we've worked

1014
01:01:23,240 --> 01:01:25,600
Speaker 15: on at the Heritage Foundation. It's been passed in states

1015
01:01:25,600 --> 01:01:29,120
Speaker 15: around the country that says that if you have a

1016
01:01:29,240 --> 01:01:32,040
Speaker 15: child who says they were confused about their sex, you

1017
01:01:32,160 --> 01:01:34,840
Speaker 15: have to address them by the name and pronoun that

1018
01:01:34,880 --> 01:01:38,520
Speaker 15: corresponds with their birth certificate unless you get express permission

1019
01:01:38,600 --> 01:01:40,720
Speaker 15: from the parents. And the key here is that you

1020
01:01:40,840 --> 01:01:43,680
Speaker 15: are keeping parents up a part of this very crucial

1021
01:01:43,800 --> 01:01:44,880
Speaker 15: health related decision.

1022
01:01:46,200 --> 01:01:50,800
Speaker 2: So a lot of people, particularly on the left, Jonathan,

1023
01:01:52,720 --> 01:01:56,520
Speaker 2: tend to be on the wrong side of these issues

1024
01:01:57,240 --> 01:02:04,680
Speaker 2: almost exclusively as far as race critical, race theory, gender dysphoria.

1025
01:02:05,280 --> 01:02:09,360
Speaker 2: And we see this over and over again. Why would

1026
01:02:09,440 --> 01:02:15,360
Speaker 2: they want to be on the twenty or thirty percent

1027
01:02:15,520 --> 01:02:18,520
Speaker 2: side as opposed to the eighty or seventy percent side

1028
01:02:18,520 --> 01:02:20,160
Speaker 2: where most of Americans are at.

1029
01:02:21,200 --> 01:02:22,440
Speaker 1: Why would they want to do that.

1030
01:02:23,000 --> 01:02:28,000
Speaker 2: Unless they're purposely trying to sew division into our society.

1031
01:02:28,160 --> 01:02:31,280
Speaker 2: For another reason, I.

1032
01:02:31,280 --> 01:02:33,600
Speaker 15: Don't think that they even represent most of those on

1033
01:02:33,720 --> 01:02:36,440
Speaker 15: the left. I think that they are extremists, and frankly,

1034
01:02:36,840 --> 01:02:39,240
Speaker 15: they are the fringe right, those that are pushing these

1035
01:02:39,320 --> 01:02:42,880
Speaker 15: radical ideas, even though they call everyone else the fringe right.

1036
01:02:43,400 --> 01:02:46,479
Speaker 15: And I think that Look people I interviewed for my book,

1037
01:02:46,600 --> 01:02:49,680
Speaker 15: I interviewed a woman named Aaron Friday, who look. She

1038
01:02:49,760 --> 01:02:51,840
Speaker 15: told me she's a lifelong Democrat. She's voted on the

1039
01:02:51,920 --> 01:02:54,640
Speaker 15: left for her whole life. But when this whole transgender

1040
01:02:54,720 --> 01:02:57,840
Speaker 15: idea came for her daughter, she became active and she

1041
01:02:58,160 --> 01:03:00,520
Speaker 15: had to work for more than a year to rescue

1042
01:03:00,560 --> 01:03:03,280
Speaker 15: her daughter from these ideas that she was born in

1043
01:03:03,320 --> 01:03:07,480
Speaker 15: the wrong body. She challenged her child's school about what

1044
01:03:07,520 --> 01:03:11,000
Speaker 15: they were teaching on this idea of gender. So look,

1045
01:03:11,360 --> 01:03:14,680
Speaker 15: right or left, there are people who, you know, take

1046
01:03:14,720 --> 01:03:18,480
Speaker 15: a very I think, common sense approach to understanding that

1047
01:03:18,560 --> 01:03:21,280
Speaker 15: we need to protect young people from radical ideas that

1048
01:03:21,360 --> 01:03:24,720
Speaker 15: will have irreversible consequences. Right, they will have consequences that

1049
01:03:24,720 --> 01:03:26,720
Speaker 15: will change someone, change them for their whole life.

1050
01:03:27,000 --> 01:03:30,840
Speaker 2: Yeah, previously you were authoring a splintered critical race theory

1051
01:03:30,880 --> 01:03:33,480
Speaker 2: and the progressive War on the truth, and I think

1052
01:03:33,560 --> 01:03:37,480
Speaker 2: that's what you're talking about. The fringe this war on

1053
01:03:37,640 --> 01:03:43,760
Speaker 2: the truth has ulterior motives in at least my estimation,

1054
01:03:44,480 --> 01:03:47,160
Speaker 2: and that is to take down our complete society.

1055
01:03:48,520 --> 01:03:50,080
Speaker 1: What other reason could they have?

1056
01:03:51,840 --> 01:03:54,320
Speaker 15: Yeah, and that's at the root of critical race theory, right.

1057
01:03:54,520 --> 01:03:57,440
Speaker 15: Critical race theory is built on something called critical theory,

1058
01:03:57,720 --> 01:04:01,080
Speaker 15: which is an extension of Marxism from the nine and

1059
01:04:01,240 --> 01:04:05,640
Speaker 15: it's a gad fly of what is known as traditional theory,

1060
01:04:05,720 --> 01:04:10,560
Speaker 15: the idea of Enlightenment, rationalism, individual liberty, representative government. And

1061
01:04:10,640 --> 01:04:13,520
Speaker 15: it does as you explain, It is trying to take

1062
01:04:13,560 --> 01:04:16,440
Speaker 15: apart this rule of law in this representative system that

1063
01:04:16,520 --> 01:04:18,320
Speaker 15: we have. But they have no plans to replace it

1064
01:04:19,040 --> 01:04:21,240
Speaker 15: with anything. I mean they don't. They don't have a

1065
01:04:21,280 --> 01:04:23,760
Speaker 15: plan for the future. All they have is a revolution and.

1066
01:04:23,840 --> 01:04:29,560
Speaker 2: Critical race theory basically, and critical theory, which it sprang from,

1067
01:04:30,440 --> 01:04:34,120
Speaker 2: has very little to do with critical thinking, which is

1068
01:04:34,160 --> 01:04:36,360
Speaker 2: what we need a lot more in the field of

1069
01:04:36,560 --> 01:04:42,080
Speaker 2: education and encouraging the next generation to do just that.

1070
01:04:42,280 --> 01:04:47,560
Speaker 2: The book is The Polarization Myth America's surprising consensus on race, schools,

1071
01:04:47,720 --> 01:04:50,160
Speaker 2: and sex. And if you think we're really a divided

1072
01:04:50,280 --> 01:04:53,880
Speaker 2: nation on these issues, maybe you should crack this open

1073
01:04:54,240 --> 01:04:58,440
Speaker 2: and become educated Jonathan, thank you so much for your

1074
01:04:58,480 --> 01:04:59,880
Speaker 2: time tonight, and I wish we had more.

1075
01:05:00,080 --> 01:05:03,560
Speaker 1: Maybe we'll do it again. Okay, thank you, you bet.

1076
01:05:04,360 --> 01:05:10,200
Speaker 2: It's Jonathan Butcher the polarization myth coming up next, No myth.

1077
01:05:10,960 --> 01:05:14,240
Speaker 2: He is a man and one of these days someone

1078
01:05:14,280 --> 01:05:17,959
Speaker 2: will call him a legend. Andy Furman closes out the show.

1079
01:05:18,160 --> 01:05:20,640
Speaker 2: Now on the Bend and many people's a guest. I

1080
01:05:20,720 --> 01:05:24,680
Speaker 2: went around the Bend many many years ago. On this nightcap,

1081
01:05:25,680 --> 01:05:30,080
Speaker 2: we bring back in our friendly fan. No, I don't

1082
01:05:30,080 --> 01:05:32,280
Speaker 2: know if he's a fan or not anymore. Been covering

1083
01:05:32,320 --> 01:05:35,640
Speaker 2: sports for so long, I guess you kind of lose

1084
01:05:35,760 --> 01:05:38,440
Speaker 2: your luster sometimes to be a fan. I'll ask him

1085
01:05:38,480 --> 01:05:42,160
Speaker 2: about that. But he's actually not in his car tonight,

1086
01:05:42,360 --> 01:05:46,520
Speaker 2: which is unusual. Are you pulling a segment, Dennison because

1087
01:05:46,520 --> 01:05:47,000
Speaker 2: of the snow?

1088
01:05:47,080 --> 01:05:47,400
Speaker 1: Andy?

1089
01:05:48,480 --> 01:05:50,480
Speaker 20: No, actually I'm not in the car. This is a

1090
01:05:50,520 --> 01:05:51,200
Speaker 20: little too cold.

1091
01:05:52,160 --> 01:05:54,520
Speaker 1: But I thought maybe it was because it's so much.

1092
01:05:55,120 --> 01:05:59,440
Speaker 20: Undisclosed situation, undisclosed location right now. But I started to

1093
01:05:59,520 --> 01:06:02,080
Speaker 20: rock and roll. I'm glad you brought up the term fan. Okay,

1094
01:06:02,480 --> 01:06:04,640
Speaker 20: I think it's a it's a it's it's a poor

1095
01:06:05,080 --> 01:06:08,200
Speaker 20: choice of words to say that someone who's behind the

1096
01:06:08,320 --> 01:06:10,840
Speaker 20: microphone as a sports talk coast is a fan. I

1097
01:06:10,920 --> 01:06:12,800
Speaker 20: really believe that. I just I don't think you can.

1098
01:06:12,920 --> 01:06:14,760
Speaker 20: I tell you what. I've been listening to a lot

1099
01:06:14,800 --> 01:06:18,880
Speaker 20: of sports talk radio for years. I still do nationwide, locally,

1100
01:06:18,920 --> 01:06:21,800
Speaker 20: whatever it may be, and most of them, I say, really,

1101
01:06:21,840 --> 01:06:23,760
Speaker 20: it's truly most of them. And this is not a

1102
01:06:23,880 --> 01:06:26,320
Speaker 20: slap of them. It's true. Most of them, you know,

1103
01:06:26,640 --> 01:06:29,160
Speaker 20: love the NFL because it is the most popular sport

1104
01:06:29,200 --> 01:06:32,000
Speaker 20: and number two is college football. But when it's over,

1105
01:06:32,400 --> 01:06:34,160
Speaker 20: they think that the world has come to an end

1106
01:06:34,240 --> 01:06:36,600
Speaker 20: because they have to start working. The football is great

1107
01:06:36,640 --> 01:06:38,760
Speaker 20: because eight there's a lot of storylines, b it's quite

1108
01:06:38,760 --> 01:06:41,160
Speaker 20: easy because it's once a week. You make predictions. You

1109
01:06:42,000 --> 01:06:43,920
Speaker 20: just decide who's going to win, who's not going to win.

1110
01:06:44,120 --> 01:06:47,439
Speaker 20: And it's laziness basically, And now you really have to work.

1111
01:06:47,680 --> 01:06:49,959
Speaker 20: You got to work between now and maybe the draft.

1112
01:06:50,040 --> 01:06:53,400
Speaker 20: I'm hearing shows now talking about the draft. Are you kidding?

1113
01:06:53,760 --> 01:06:57,880
Speaker 20: The draft is, say April. There's several things going on

1114
01:06:58,040 --> 01:06:59,840
Speaker 20: right now. But that's that's not for me to judge.

1115
01:06:59,840 --> 01:07:02,400
Speaker 20: I'm a program director. I'm just a fan. I'm a

1116
01:07:02,480 --> 01:07:04,400
Speaker 20: fan of talk radio. I'm a fan of sports, and

1117
01:07:04,480 --> 01:07:06,400
Speaker 20: I think that there's a lot of issues out there,

1118
01:07:06,440 --> 01:07:08,680
Speaker 20: and one of the issues I think is Bill Belichick

1119
01:07:08,760 --> 01:07:10,760
Speaker 20: not getting into the Hall of Fame on the first ballot.

1120
01:07:10,920 --> 01:07:13,600
Speaker 20: All right, Pete Rose told me this years ago. He

1121
01:07:13,680 --> 01:07:16,080
Speaker 20: said in baseball, if you don't getting in the first ballot,

1122
01:07:16,120 --> 01:07:18,000
Speaker 20: you shouldn't get in at all. You know why, you

1123
01:07:18,040 --> 01:07:20,480
Speaker 20: don't get better with age. You didn't deserve to get in.

1124
01:07:20,560 --> 01:07:22,960
Speaker 20: You're not getting in. That's not the case with Bill Belichick.

1125
01:07:23,280 --> 01:07:25,840
Speaker 20: He basically was railroaded there. And one of the guys

1126
01:07:25,880 --> 01:07:28,680
Speaker 20: who railroaded them, I believe was Bill Pollion. Bill Pollion

1127
01:07:28,720 --> 01:07:32,160
Speaker 20: a big craft of Robert Kraft, supporter, general former general

1128
01:07:32,200 --> 01:07:34,320
Speaker 20: manager of the Buffalo Bills, and I think that he

1129
01:07:34,480 --> 01:07:37,920
Speaker 20: did not vote for Bill Belichick. However, he came back

1130
01:07:37,960 --> 01:07:39,680
Speaker 20: in the New York Times and he said that he did.

1131
01:07:40,160 --> 01:07:43,400
Speaker 20: But the point is that he says, I'm pretty sure,

1132
01:07:43,760 --> 01:07:46,440
Speaker 20: about ninety five percent sure that I did vote for him.

1133
01:07:46,560 --> 01:07:49,080
Speaker 20: Wait a minute, ninety five percent sure. If you have

1134
01:07:49,240 --> 01:07:52,560
Speaker 20: no freaking clue who you voted for, you know what, Bill,

1135
01:07:52,720 --> 01:07:55,240
Speaker 20: you shouldn't be voting. You shouldn't be voting. Really, you

1136
01:07:55,280 --> 01:07:58,120
Speaker 20: don't know who you voted for. Are you one last thing?

1137
01:07:58,400 --> 01:08:01,680
Speaker 20: Two things about Bill Poleon right now. Either he's lying

1138
01:08:02,080 --> 01:08:04,600
Speaker 20: and he did a campaign against Bill Belichick and now

1139
01:08:04,680 --> 01:08:07,680
Speaker 20: maybe he's covering his rear end and his role. Or

1140
01:08:07,800 --> 01:08:10,920
Speaker 20: maybe he really can't remember and he's got dementia and

1141
01:08:11,000 --> 01:08:13,000
Speaker 20: he shouldn't be voting. It's one of the two, right,

1142
01:08:13,120 --> 01:08:13,640
Speaker 20: That's what it is.

1143
01:08:14,280 --> 01:08:17,439
Speaker 1: Ask him what he had for breakfast? I mean, jeezus,

1144
01:08:17,720 --> 01:08:20,160
Speaker 1: but that's what. Yeah, no doubt.

1145
01:08:20,840 --> 01:08:24,000
Speaker 2: I think I would remember if I had the responsibility

1146
01:08:24,640 --> 01:08:29,840
Speaker 2: of deciding whether to enshrine the greatest coach that is

1147
01:08:29,920 --> 01:08:34,240
Speaker 2: ever as far as results go and championships in the NFL,

1148
01:08:35,120 --> 01:08:37,920
Speaker 2: and I decided not to do that, I think I

1149
01:08:38,000 --> 01:08:40,800
Speaker 2: would recall that Andy. I don't believe it would be

1150
01:08:40,840 --> 01:08:42,880
Speaker 2: a matter of a gray area.

1151
01:08:43,080 --> 01:08:44,840
Speaker 1: Was well, I don't know, maybe I did.

1152
01:08:46,160 --> 01:08:48,080
Speaker 20: I would have to say that pettiness had won out

1153
01:08:48,160 --> 01:08:50,800
Speaker 20: in this situation because they snubbed him. Look, he was

1154
01:08:50,840 --> 01:08:52,640
Speaker 20: a butt ale at times to media people, but so

1155
01:08:52,760 --> 01:08:54,800
Speaker 20: what who cares? He was the greatest coach who won

1156
01:08:54,920 --> 01:08:56,680
Speaker 20: eight Super Bowl rings, six as a head coach and

1157
01:08:56,720 --> 01:08:58,920
Speaker 20: two as an assistant. And I think the fact that

1158
01:08:59,000 --> 01:09:01,960
Speaker 20: he has a young as a as a. I guess

1159
01:09:02,200 --> 01:09:04,320
Speaker 20: a lover, a companion, whoever you may want to call

1160
01:09:04,360 --> 01:09:08,040
Speaker 20: a girlfriend. I think girlfriend. I think there's some jealousies

1161
01:09:08,080 --> 01:09:09,840
Speaker 20: over there. They don't like it. Maybe it's a bad

1162
01:09:09,880 --> 01:09:12,040
Speaker 20: image in their mind. So they voted against and they

1163
01:09:12,120 --> 01:09:14,600
Speaker 20: voted against this guy. That's what they did. It was

1164
01:09:14,680 --> 01:09:17,439
Speaker 20: pettiness and jealousy and envy, whatever it may be. And

1165
01:09:17,600 --> 01:09:18,960
Speaker 20: he didn't get into the Hall of Fame, and he

1166
01:09:19,000 --> 01:09:21,400
Speaker 20: will get in next year, for sure. But you know,

1167
01:09:22,000 --> 01:09:24,360
Speaker 20: it's just it wasn't right. It's not a good look.

1168
01:09:24,800 --> 01:09:26,280
Speaker 20: It's not a good look for the Hall of Fame.

1169
01:09:26,640 --> 01:09:27,840
Speaker 20: It really isn't andy.

1170
01:09:27,880 --> 01:09:30,559
Speaker 1: I don't like it when people use the term lover.

1171
01:09:31,200 --> 01:09:34,240
Speaker 2: It just connotates something you know that may or may

1172
01:09:34,320 --> 01:09:37,439
Speaker 2: not be going on, and it's kind of suggestive. So

1173
01:09:37,840 --> 01:09:40,880
Speaker 2: let's just go with girlfriend, the one that's like fifty

1174
01:09:41,000 --> 01:09:41,920
Speaker 2: years younger than him.

1175
01:09:42,680 --> 01:09:47,280
Speaker 20: That's fine. No, no, no, I'll ask you this question.

1176
01:09:47,360 --> 01:09:49,479
Speaker 20: If you fact that if you had a vote yeah

1177
01:09:49,520 --> 01:09:51,160
Speaker 20: for the Hall of Fame, would you have voted to him?

1178
01:09:51,280 --> 01:09:51,400
Speaker 4: Oh?

1179
01:09:51,479 --> 01:09:54,360
Speaker 1: Absolutely? How do you not vote for Bill Belichick?

1180
01:09:55,200 --> 01:09:59,600
Speaker 2: I mean, part of eight Super Bowls two is in

1181
01:09:59,640 --> 01:10:03,080
Speaker 2: assay six as the head man. You can take out

1182
01:10:03,200 --> 01:10:06,600
Speaker 2: the flight date, which was a nothing deal, or you

1183
01:10:06,680 --> 01:10:09,800
Speaker 2: can take out the video charges which they got, you know,

1184
01:10:09,960 --> 01:10:13,639
Speaker 2: suspended for that's still He's still won four more Super

1185
01:10:13,680 --> 01:10:17,400
Speaker 2: Bowls as a head coach. I mean, there has been

1186
01:10:17,560 --> 01:10:23,000
Speaker 2: no dynasty perhaps as enduring as the one that Bill

1187
01:10:23,160 --> 01:10:27,760
Speaker 2: Belichick was orchestrating in New England. And to not have

1188
01:10:28,000 --> 01:10:31,880
Speaker 2: him in the National Football Hall of Fame, it's just

1189
01:10:32,600 --> 01:10:34,559
Speaker 2: it's a travesty beyond words.

1190
01:10:34,640 --> 01:10:34,840
Speaker 15: To me.

1191
01:10:35,200 --> 01:10:37,040
Speaker 20: I'm with you on that, I really am. You know,

1192
01:10:37,360 --> 01:10:39,160
Speaker 20: I want to talk about the super Bowl for a second,

1193
01:10:39,200 --> 01:10:42,479
Speaker 20: and I'm surprised the conversation hasn't come up as usually

1194
01:10:42,600 --> 01:10:44,840
Speaker 20: does every year. How come the Super Bowl is not

1195
01:10:45,000 --> 01:10:49,400
Speaker 20: on Saturday rather than Sunday. You know, Look, I didn't

1196
01:10:49,400 --> 01:10:51,040
Speaker 20: want to go down that road, but I'm waiting for

1197
01:10:51,080 --> 01:10:53,519
Speaker 20: it to happen. Well, when these people behind microphones get

1198
01:10:53,560 --> 01:10:55,360
Speaker 20: a little lazy and they're going to bring that up. Look,

1199
01:10:55,439 --> 01:10:57,519
Speaker 20: it's a weekend event. They make it the whole weekend.

1200
01:10:57,520 --> 01:11:00,040
Speaker 20: That's what they do. And I think it's great. And

1201
01:11:00,080 --> 01:11:01,720
Speaker 20: they say, why is it six o'clock with Hey, why

1202
01:11:01,720 --> 01:11:04,000
Speaker 20: it's six o'clock because it's primetime. They want to go

1203
01:11:04,080 --> 01:11:06,280
Speaker 20: with the primetime. It's three o'clock on the West coast

1204
01:11:06,320 --> 01:11:08,559
Speaker 20: at six o'clock east, and it goes right into maybe

1205
01:11:08,640 --> 01:11:11,800
Speaker 20: ten thirty eleven o'clock with postgame activity so that they

1206
01:11:11,880 --> 01:11:13,800
Speaker 20: have the primetime activity on TV.

1207
01:11:13,960 --> 01:11:16,640
Speaker 2: So that's basically it ain not that it matters, but

1208
01:11:16,800 --> 01:11:19,760
Speaker 2: you are Jewish. So Saturday is the Sabbath, that's the day,

1209
01:11:19,880 --> 01:11:21,040
Speaker 2: that's the day of rest.

1210
01:11:20,960 --> 01:11:23,400
Speaker 20: Saturday sundown, Saturday sundown, it's over.

1211
01:11:23,840 --> 01:11:27,160
Speaker 2: Right exactly, so they'd have to start the game after

1212
01:11:27,320 --> 01:11:31,760
Speaker 2: the sun went down so you could participate and actively

1213
01:11:31,960 --> 01:11:35,799
Speaker 2: watch the game instead of praying and reading your torah

1214
01:11:35,920 --> 01:11:39,000
Speaker 2: like you usually do all day every day on the Sabbath.

1215
01:11:39,240 --> 01:11:42,280
Speaker 20: Right, Andy, Yeah, I'm one last note. If I man,

1216
01:11:42,360 --> 01:11:44,400
Speaker 20: the super Bowl will move on to something else. Obviously

1217
01:11:44,439 --> 01:11:47,519
Speaker 20: people are really upset now, but it's the two teams

1218
01:11:47,520 --> 01:11:49,720
Speaker 20: that you know, the Patriots basically in Seattle, which I

1219
01:11:49,720 --> 01:11:52,120
Speaker 20: think is unbelievable how these two teams were not even

1220
01:11:52,160 --> 01:11:53,840
Speaker 20: in the playoffs last year and they came back out

1221
01:11:53,840 --> 01:11:56,320
Speaker 20: of nowhere, which shows that it can be done. But

1222
01:11:56,439 --> 01:11:59,479
Speaker 20: the biggest loser, the biggest loser of football right now,

1223
01:12:00,080 --> 01:12:01,840
Speaker 20: have to be the New York Jets. Okay, they have

1224
01:12:01,960 --> 01:12:04,360
Speaker 20: not reached the postseason as twenty ten, which is the

1225
01:12:04,400 --> 01:12:07,400
Speaker 20: longest playoff draft of any team in major American sports.

1226
01:12:07,760 --> 01:12:10,040
Speaker 20: And it hurts even more this year for the Jests

1227
01:12:10,120 --> 01:12:13,720
Speaker 20: lt Why their savior, the guy they draft is their

1228
01:12:13,800 --> 01:12:16,760
Speaker 20: savior and they dumped them. Sam Donald's the quarterback for

1229
01:12:16,800 --> 01:12:19,839
Speaker 20: one of the teams and the co leader in sacks

1230
01:12:19,920 --> 01:12:23,120
Speaker 20: on one on Seattle Leonard Williams, who was the Jets

1231
01:12:23,200 --> 01:12:25,559
Speaker 20: first round pick of twenty fifteen. So these two guys

1232
01:12:25,640 --> 01:12:27,200
Speaker 20: are playing in the Super Bowl. Dreaded them by the

1233
01:12:27,280 --> 01:12:29,000
Speaker 20: Jests to get them out of the doldrums, and they

1234
01:12:29,080 --> 01:12:31,640
Speaker 20: never did so. Obviously, it's haunting the Jets right now.

1235
01:12:31,680 --> 01:12:32,920
Speaker 20: I think it's funny. I really do.

1236
01:12:33,800 --> 01:12:36,479
Speaker 2: Anything that happens to the New York Jets is funny

1237
01:12:36,520 --> 01:12:39,400
Speaker 2: to me. You talked about these teams weren't even in

1238
01:12:39,439 --> 01:12:42,679
Speaker 2: the playoffs last year. The two participants in Super Bowl

1239
01:12:42,760 --> 01:12:43,799
Speaker 2: sixty on Sunday?

1240
01:12:44,640 --> 01:12:46,000
Speaker 1: Right what that?

1241
01:12:46,240 --> 01:12:50,679
Speaker 2: Even that brings us back to Bill Belichick and those

1242
01:12:50,840 --> 01:12:53,679
Speaker 2: New England Patriots teams that he coached the Super Bowls.

1243
01:12:55,200 --> 01:12:59,560
Speaker 2: It'll shows because the NFL is the most socialist professional

1244
01:12:59,640 --> 01:13:02,920
Speaker 2: sport franchise with their revenue sharing and everything there's so

1245
01:13:03,120 --> 01:13:07,240
Speaker 2: much parody and so many availabilities to rise up from

1246
01:13:07,280 --> 01:13:10,400
Speaker 2: the ashes from year to year in the NFL, and

1247
01:13:10,520 --> 01:13:15,880
Speaker 2: yet Bill Belichick's Patriots got there almost every year Andy

1248
01:13:16,200 --> 01:13:16,960
Speaker 2: during their heyday.

1249
01:13:17,400 --> 01:13:17,880
Speaker 20: That's funny.

1250
01:13:17,880 --> 01:13:19,160
Speaker 1: It shows how excellent that.

1251
01:13:20,040 --> 01:13:22,040
Speaker 20: It's about the Jets being like, you know, the soul

1252
01:13:22,120 --> 01:13:25,160
Speaker 20: loses in this situation. Let's remember this, the Patriots had

1253
01:13:25,200 --> 01:13:28,000
Speaker 20: Bill Belichick as a coach, and then Belichick resigned on

1254
01:13:28,120 --> 01:13:30,360
Speaker 20: a napkin as the Jets coach and he went to

1255
01:13:30,439 --> 01:13:32,960
Speaker 20: New England. Yes, there's another situation for the Jets.

1256
01:13:33,439 --> 01:13:36,040
Speaker 1: Well, well, what's happened to that franchise? How have they

1257
01:13:36,120 --> 01:13:37,200
Speaker 1: become like the.

1258
01:13:37,280 --> 01:13:41,439
Speaker 20: Laughing Now to the top. I think that Woodie Johnson

1259
01:13:41,560 --> 01:13:44,120
Speaker 20: is a terrible owner, and I think he meddles too much.

1260
01:13:44,120 --> 01:13:46,400
Speaker 20: I think owners should be seen and I've heard and

1261
01:13:46,800 --> 01:13:48,720
Speaker 20: to some extent, I think Mike Brown is that way.

1262
01:13:48,760 --> 01:13:50,160
Speaker 20: I think he does a decent job. They had a

1263
01:13:50,200 --> 01:13:52,800
Speaker 20: lot of bad luck with the Cincinnati Bengals. I mean,

1264
01:13:53,120 --> 01:13:55,559
Speaker 20: everybody's on Duke Tobin's back. I mean, come on, really,

1265
01:13:55,920 --> 01:13:58,240
Speaker 20: get off the guy's back. It's a crap shoot. That's

1266
01:13:58,280 --> 01:14:01,200
Speaker 20: what the draft is. Last year, one of the moves

1267
01:14:01,200 --> 01:14:03,160
Speaker 20: I made. I didn't like when they got rid of

1268
01:14:03,240 --> 01:14:07,479
Speaker 20: Louisan Romo, the defensive coordinator. He was a scapegoat. And certainly,

1269
01:14:07,720 --> 01:14:09,040
Speaker 20: you know, it didn't make much of a difference this

1270
01:14:09,160 --> 01:14:11,719
Speaker 20: year with the defense. But still in all that's basically

1271
01:14:11,800 --> 01:14:13,439
Speaker 20: what happens. There are other teams right now in the

1272
01:14:13,520 --> 01:14:16,960
Speaker 20: same funk, if you will, as the Cincinnati Bengals, the

1273
01:14:17,120 --> 01:14:21,080
Speaker 20: Arizona Cardinals, New Orleans Saints. It happens, it happens, okay,

1274
01:14:21,400 --> 01:14:23,000
Speaker 20: And I think they'll be back. I think if Joe

1275
01:14:23,040 --> 01:14:25,880
Speaker 20: Burrow was healthy next year, they'll be back. And it's

1276
01:14:25,880 --> 01:14:28,120
Speaker 20: funny when you look at the Pro Bowl, not these

1277
01:14:28,160 --> 01:14:30,840
Speaker 20: Bengal players of the Pro Bowl. I mean, really sure

1278
01:14:30,920 --> 01:14:33,000
Speaker 20: Joe Flacco on the Pro Bowl? Are you kidding? I

1279
01:14:33,080 --> 01:14:35,160
Speaker 20: mean what team did he play for? I mean he

1280
01:14:35,280 --> 01:14:37,680
Speaker 20: played for the same team, but should Door Sanders was

1281
01:14:37,760 --> 01:14:40,080
Speaker 20: in his Pro Bowl as well. It's crazy, it really is.

1282
01:14:40,320 --> 01:14:43,840
Speaker 2: Maybe in flag football he has a chance to really

1283
01:14:43,960 --> 01:14:46,920
Speaker 2: shine finally at this stage of his career.

1284
01:14:47,200 --> 01:14:49,200
Speaker 20: I don't think many people are interested in the Pro Bowl.

1285
01:14:49,400 --> 01:14:52,040
Speaker 1: No, no, but nobody's caring about it for years.

1286
01:14:52,680 --> 01:14:54,439
Speaker 20: If someone went to ask me, I say what I

1287
01:14:54,479 --> 01:14:56,800
Speaker 20: would have I would have a bowl called the toilet Bowl.

1288
01:14:57,680 --> 01:15:01,160
Speaker 20: Major sponsors in Santa Flash, some diaper companies where it

1289
01:15:01,200 --> 01:15:03,599
Speaker 20: may be the two worst teams in the league players

1290
01:15:03,640 --> 01:15:06,200
Speaker 20: as a toilet Bowl and the winner is the first

1291
01:15:06,280 --> 01:15:08,960
Speaker 20: draft pick in the draft the toilet Bowl. There's interest

1292
01:15:09,040 --> 01:15:11,240
Speaker 20: in it, and people would play and people would watch it,

1293
01:15:11,439 --> 01:15:13,960
Speaker 20: and it wouldn't be flat football, be regular football. That's

1294
01:15:14,040 --> 01:15:15,599
Speaker 20: just my take. The toilet Bowl.

1295
01:15:15,640 --> 01:15:18,680
Speaker 2: Well, I mean what the Jets and the Cardinals have been,

1296
01:15:20,040 --> 01:15:22,360
Speaker 2: they've been on the beach for a while. I mean,

1297
01:15:22,600 --> 01:15:25,280
Speaker 2: to bring him back out now would be an even

1298
01:15:25,479 --> 01:15:27,840
Speaker 2: bigger laughing stock at.

1299
01:15:27,760 --> 01:15:30,400
Speaker 20: This people would go because of his setting involved and

1300
01:15:30,439 --> 01:15:32,920
Speaker 20: there's something to be one and or a loss for

1301
01:15:33,000 --> 01:15:35,840
Speaker 20: that game for the draft pick. And speaking of you,

1302
01:15:35,960 --> 01:15:37,479
Speaker 20: I mentioned should do a singer. Just talk about his

1303
01:15:37,560 --> 01:15:40,519
Speaker 20: dad for a second. Okay, Colorado football coach, they went

1304
01:15:40,600 --> 01:15:42,840
Speaker 20: three to nine last year in football. Did you see

1305
01:15:42,880 --> 01:15:45,200
Speaker 20: what he did just the other day? No, he levied

1306
01:15:45,400 --> 01:15:49,200
Speaker 20: fines on his players for violations. Okay, can I read

1307
01:15:49,200 --> 01:15:51,479
Speaker 20: you some of these fines that he's listed for sure?

1308
01:15:51,640 --> 01:15:54,240
Speaker 2: Well, they've got money now, you know it's the nil.

1309
01:15:54,439 --> 01:15:56,320
Speaker 2: So you know we're going to treat him just like pros,

1310
01:15:56,360 --> 01:15:59,240
Speaker 2: and they're going to be fine if they're not adhering

1311
01:15:59,320 --> 01:16:01,080
Speaker 2: to his high standards.

1312
01:16:01,160 --> 01:16:02,840
Speaker 1: Anyway, give me some of the funds.

1313
01:16:03,240 --> 01:16:06,000
Speaker 20: He's got fifty two new incoming players coming in from

1314
01:16:06,040 --> 01:16:08,679
Speaker 20: the transfer portal this year. My question is this, why

1315
01:16:08,920 --> 01:16:09,879
Speaker 20: do why the fines?

1316
01:16:10,000 --> 01:16:10,200
Speaker 9: Now?

1317
01:16:10,720 --> 01:16:12,479
Speaker 20: Does that mean that you want to tighten the ship

1318
01:16:12,520 --> 01:16:15,120
Speaker 20: because it was rather loose before? I don't know. Here's

1319
01:16:15,160 --> 01:16:17,320
Speaker 20: some of the finds he's issuing for his plays. If

1320
01:16:17,360 --> 01:16:19,280
Speaker 20: you're late to a meeting or a film session four

1321
01:16:19,360 --> 01:16:23,479
Speaker 20: hundred bucks late to practice, five hundred late to strength

1322
01:16:23,560 --> 01:16:27,519
Speaker 20: and conditioning workout, one thousand late to treatment, one thousand

1323
01:16:28,080 --> 01:16:33,320
Speaker 20: absent from treatment, fifteen hundred absent from strength to conditioning workout,

1324
01:16:33,400 --> 01:16:36,599
Speaker 20: fifteen hundred absent from a meeting or a film session

1325
01:16:37,160 --> 01:16:39,959
Speaker 20: get this two thousand dollars and the absent from practice

1326
01:16:40,640 --> 01:16:43,680
Speaker 20: twenty five hundred dollars. Violation of team rooms twenty five

1327
01:16:43,760 --> 01:16:47,559
Speaker 20: hundred dollars, and a public or social media misconduct up

1328
01:16:47,600 --> 01:16:50,400
Speaker 20: to five thousand dollars based on the severity. Okay, I

1329
01:16:50,520 --> 01:16:53,320
Speaker 20: get it, I understand it. It's pretty nice. But I

1330
01:16:53,400 --> 01:16:55,920
Speaker 20: would think that players will see this and read this

1331
01:16:56,479 --> 01:16:58,400
Speaker 20: would say, you know what, I ain't going that school.

1332
01:16:58,960 --> 01:17:01,479
Speaker 1: Well, you know, could absolutely happen. Andy.

1333
01:17:01,560 --> 01:17:05,439
Speaker 2: But on the other side, the real logic in this

1334
01:17:05,920 --> 01:17:10,080
Speaker 2: is the job of a student athlete used to include

1335
01:17:10,160 --> 01:17:11,040
Speaker 2: the student part.

1336
01:17:11,600 --> 01:17:12,639
Speaker 1: Now their only job.

1337
01:17:12,720 --> 01:17:16,479
Speaker 2: If they're playing at a Division one college football program

1338
01:17:16,640 --> 01:17:19,320
Speaker 2: and they have the chance to get paid sometimes millions

1339
01:17:19,360 --> 01:17:22,600
Speaker 2: of dollars in a season. Football is their job. And

1340
01:17:22,720 --> 01:17:26,160
Speaker 2: if you're not doing your job, sometimes you get your

1341
01:17:26,200 --> 01:17:27,799
Speaker 2: pay doct It's it's.

1342
01:17:27,720 --> 01:17:28,400
Speaker 16: The same thing.

1343
01:17:28,880 --> 01:17:31,040
Speaker 1: So, I mean, if they were.

1344
01:17:31,000 --> 01:17:33,240
Speaker 20: Athlete, that that's a miss nomore.

1345
01:17:33,520 --> 01:17:33,560
Speaker 14: No.

1346
01:17:33,720 --> 01:17:36,680
Speaker 2: No, If they were still student athletes, I might have

1347
01:17:37,040 --> 01:17:40,839
Speaker 2: a problem with it. But since they are basically semi

1348
01:17:40,920 --> 01:17:43,920
Speaker 2: pro or professional football players at the college level, I

1349
01:17:44,000 --> 01:17:45,920
Speaker 2: got no issues with that at all.

1350
01:17:46,600 --> 01:17:48,800
Speaker 20: I got a linebacker going to University of Miami and

1351
01:17:48,880 --> 01:17:50,200
Speaker 20: Florida's gonna be his eighth year.

1352
01:17:52,000 --> 01:17:52,400
Speaker 1: That's nut.

1353
01:17:53,120 --> 01:17:56,519
Speaker 20: I mean, I look at this. Doesn't anybody scratch ahead

1354
01:17:56,520 --> 01:17:59,000
Speaker 20: and does this happen? Why is this happening? I mean,

1355
01:17:59,360 --> 01:18:02,800
Speaker 20: there's no list, there's nothing gone. I mean, I don't

1356
01:18:02,800 --> 01:18:05,760
Speaker 20: get it. The school presidents. I guess they sucked up

1357
01:18:05,800 --> 01:18:08,639
Speaker 20: realizing there's big money coming in which has increases enrollment.

1358
01:18:08,720 --> 01:18:11,600
Speaker 20: Maybe I don't know. They're on TV. They're exposed, so

1359
01:18:11,760 --> 01:18:13,840
Speaker 20: they shut them out, They take the money and walk away.

1360
01:18:13,920 --> 01:18:16,960
Speaker 20: But you know, this is an academic institution. And I

1361
01:18:17,040 --> 01:18:20,160
Speaker 20: think that you look, you're a Vanderbilt fan. You saw

1362
01:18:20,240 --> 01:18:22,360
Speaker 20: that quarterback list, You're at Vanderbilt. The way he acted

1363
01:18:22,400 --> 01:18:25,320
Speaker 20: at the Heisman Trophy, the guy was a lunatic. Really,

1364
01:18:25,680 --> 01:18:32,120
Speaker 20: I mean five years ago, he couldn't have gotten into Vanderbilt, right, No, no, no, no, he.

1365
01:18:32,320 --> 01:18:36,880
Speaker 1: Had obviously enough of a grade point standard to get into.

1366
01:18:37,439 --> 01:18:42,639
Speaker 20: That Harvard two semesters together. Maybe I don't know, right,

1367
01:18:42,720 --> 01:18:43,040
Speaker 20: but but.

1368
01:18:43,120 --> 01:18:44,839
Speaker 1: Again, the game changed.

1369
01:18:45,680 --> 01:18:48,880
Speaker 2: So that does allow for a Diego Pavia to be

1370
01:18:49,280 --> 01:18:53,040
Speaker 2: at the Harvard of the South and they're in beautiful Nashville,

1371
01:18:53,120 --> 01:18:59,080
Speaker 2: Tennessee and play for the Vanderbilt Commodols. And I talked

1372
01:18:59,120 --> 01:19:01,720
Speaker 2: to Scott Drought, who played basketball at Vanderbilt as a

1373
01:19:01,720 --> 01:19:04,720
Speaker 2: good friend of mine, and he said, it's just a

1374
01:19:04,800 --> 01:19:08,840
Speaker 2: totally different game. I mean when he played, if you

1375
01:19:09,000 --> 01:19:13,479
Speaker 2: missed practice, but more to the point, Andy, if you

1376
01:19:13,760 --> 01:19:18,160
Speaker 2: missed class. C. M. Newton would sit you on the bench,

1377
01:19:19,040 --> 01:19:21,519
Speaker 2: and it was all about it was still a student

1378
01:19:21,600 --> 01:19:22,960
Speaker 2: athlete game at that point.

1379
01:19:23,280 --> 01:19:27,400
Speaker 1: It's not anymore. It's it's an athlete game. It's a professional.

1380
01:19:28,360 --> 01:19:30,000
Speaker 20: Yeah. Back in the day, you would watch games on

1381
01:19:30,120 --> 01:19:34,200
Speaker 20: TV and they'd flash on the screen the player's name

1382
01:19:34,479 --> 01:19:36,879
Speaker 20: and what he's majoring in. You don't see that anymore.

1383
01:19:37,240 --> 01:19:39,040
Speaker 20: They don't put the majors on there anymore. You know why.

1384
01:19:39,040 --> 01:19:40,639
Speaker 20: I don't think they even have any I don't think

1385
01:19:40,640 --> 01:19:42,280
Speaker 20: they stay in school long enough to get a major,

1386
01:19:42,439 --> 01:19:45,800
Speaker 20: to declare a major. I'm not down on that. I

1387
01:19:45,880 --> 01:19:48,680
Speaker 20: still love college sports. I watched college sports. I root

1388
01:19:48,760 --> 01:19:51,000
Speaker 20: for various teams, and you know, i'd be just exciting.

1389
01:19:51,080 --> 01:19:53,599
Speaker 20: I love it. But I think that the whole aspect,

1390
01:19:54,240 --> 01:19:57,519
Speaker 20: the whole situation of college sports is asked backwards.

1391
01:19:57,720 --> 01:20:02,120
Speaker 2: These divisions, These Division one athletes, these Division one athletes,

1392
01:20:02,400 --> 01:20:04,880
Speaker 2: their majors, Andy are betting co eds.

1393
01:20:05,479 --> 01:20:06,400
Speaker 1: That's their major.

1394
01:20:07,240 --> 01:20:10,040
Speaker 20: Well it always was, I think, yeah, yeah, But.

1395
01:20:10,120 --> 01:20:12,280
Speaker 2: Now that's the only thing they have to think about.

1396
01:20:12,280 --> 01:20:14,880
Speaker 2: They don't have to think about the science lab or

1397
01:20:15,080 --> 01:20:20,320
Speaker 2: the astrophysics exam. All they're thinking about is how do

1398
01:20:20,479 --> 01:20:23,960
Speaker 2: I get more money for playing football or basketball?

1399
01:20:24,520 --> 01:20:28,320
Speaker 1: And which which co ed am I going to bed tonight?

1400
01:20:28,680 --> 01:20:28,800
Speaker 12: Right?

1401
01:20:28,840 --> 01:20:30,559
Speaker 20: But I'm just confused. I mean, how come no one

1402
01:20:30,680 --> 01:20:33,320
Speaker 20: asked the question when you want to transfer from school

1403
01:20:33,360 --> 01:20:35,200
Speaker 20: A to school B. A you don't sit out a

1404
01:20:35,320 --> 01:20:37,599
Speaker 20: year and B how many credit hours do you lose?

1405
01:20:37,720 --> 01:20:40,960
Speaker 20: I don't get that there's no questions like that. Hollis professors.

1406
01:20:41,000 --> 01:20:43,360
Speaker 20: I mean, the presidents, they don't care. I don't I

1407
01:20:43,360 --> 01:20:47,120
Speaker 20: don't understand how it happened. They kind of change this, Garry.

1408
01:20:47,160 --> 01:20:50,360
Speaker 20: I mean, don't you think they have to change the caller.

1409
01:20:50,479 --> 01:20:52,479
Speaker 20: Perry wrote an obed the other day, I think for

1410
01:20:52,600 --> 01:20:55,600
Speaker 20: the Washington Post, and he said, you know, it's got

1411
01:20:55,720 --> 01:20:58,360
Speaker 20: to change, and maybe you could only transfer one time.

1412
01:20:58,920 --> 01:21:01,240
Speaker 20: You know what he said, spot on, It really was

1413
01:21:01,920 --> 01:21:05,280
Speaker 20: this bouncing around from school to school. It hurts the athlete.

1414
01:21:05,320 --> 01:21:07,400
Speaker 20: I don't say why it hurts the athlete, because I

1415
01:21:07,520 --> 01:21:09,760
Speaker 20: think that if you're transferring from school A to school B,

1416
01:21:10,120 --> 01:21:12,719
Speaker 20: there's a damn good reason why you're sulking. You're not happy,

1417
01:21:13,040 --> 01:21:15,320
Speaker 20: You could be somewhat of a troublemaker. You don't get

1418
01:21:15,320 --> 01:21:17,360
Speaker 20: along with the coach. And if I'm a personnel guy

1419
01:21:17,400 --> 01:21:18,840
Speaker 20: in the NFL, I don't know if I want to

1420
01:21:18,880 --> 01:21:21,600
Speaker 20: draft this guy. You know, really, if he doesn't like it,

1421
01:21:21,880 --> 01:21:24,640
Speaker 20: he leads he can't suck it up and weed it

1422
01:21:24,720 --> 01:21:27,920
Speaker 20: out right. I don't think the athletes realize it's not

1423
01:21:28,040 --> 01:21:30,559
Speaker 20: a good, healthy thing to jump around from school to school.

1424
01:21:30,800 --> 01:21:32,599
Speaker 20: It will hurt you in the long run if you've

1425
01:21:32,600 --> 01:21:34,760
Speaker 20: got the talent to play at the next level. It

1426
01:21:34,880 --> 01:21:35,280
Speaker 20: really did.

1427
01:21:35,720 --> 01:21:36,600
Speaker 4: It's not good, you know.

1428
01:21:36,720 --> 01:21:41,439
Speaker 2: And that's the other thing about this is that nothing

1429
01:21:41,520 --> 01:21:44,879
Speaker 2: has changed about the percentage of players that will transition

1430
01:21:45,000 --> 01:21:47,599
Speaker 2: from college to the NFL. It's still a very very

1431
01:21:47,720 --> 01:21:52,120
Speaker 2: small percentage whoever play at the next level. So I

1432
01:21:52,200 --> 01:21:56,280
Speaker 2: mean there's probably a feeling of, well, I'm probably not

1433
01:21:56,439 --> 01:21:58,400
Speaker 2: going to be making this money for the rest of

1434
01:21:58,479 --> 01:22:00,680
Speaker 2: my life or for the next ten years because I'm

1435
01:22:00,720 --> 01:22:03,160
Speaker 2: not gonna cut it in the NFL, so I better

1436
01:22:03,240 --> 01:22:07,040
Speaker 2: get everything I can right now. And that transferring from

1437
01:22:07,720 --> 01:22:11,479
Speaker 2: from school to school affects that well.

1438
01:22:11,680 --> 01:22:14,919
Speaker 20: And more than that, you're a guy from Vanderbilt, your quarterback,

1439
01:22:15,240 --> 01:22:17,439
Speaker 20: you know. I don't think a is gonna make it

1440
01:22:17,479 --> 01:22:19,680
Speaker 20: in the NFL because of his attitude, no doubt about that,

1441
01:22:20,000 --> 01:22:22,120
Speaker 20: but be he'd be more suited to be a jockey

1442
01:22:22,160 --> 01:22:22,839
Speaker 20: than a quarterback.

1443
01:22:22,880 --> 01:22:24,880
Speaker 2: I don't think he's gonna make it in the NFL

1444
01:22:24,880 --> 01:22:26,639
Speaker 2: because he's five nine andy.

1445
01:22:26,920 --> 01:22:28,080
Speaker 20: So what I'm saying he should be a jockey.

1446
01:22:28,360 --> 01:22:30,240
Speaker 1: I mean he might play in the CFL.

1447
01:22:31,040 --> 01:22:36,320
Speaker 2: He's Johnny Manziel though with more bravado, and I love

1448
01:22:36,400 --> 01:22:39,719
Speaker 2: to watch him play. So hopefully he'll he'll land somewhere

1449
01:22:39,760 --> 01:22:42,040
Speaker 2: where I can watch him, because I just I don't

1450
01:22:42,080 --> 01:22:43,120
Speaker 2: care if he's a jerk or not.

1451
01:22:43,360 --> 01:22:44,400
Speaker 1: I like to watch.

1452
01:22:45,000 --> 01:22:45,120
Speaker 9: Well.

1453
01:22:45,160 --> 01:22:48,400
Speaker 20: I think most most owners and personnel guys could care.

1454
01:22:48,560 --> 01:22:51,519
Speaker 20: Couldn't kill less either, really, I mean they don't. They

1455
01:22:51,560 --> 01:22:53,320
Speaker 20: say they have these meetings. He's one on ones. I

1456
01:22:53,360 --> 01:22:56,040
Speaker 20: don't think they mean anything. They don't mean squad. Maybe

1457
01:22:56,080 --> 01:22:58,880
Speaker 20: that's just for the public consumption. I mean, if you

1458
01:22:59,000 --> 01:23:01,759
Speaker 20: get a play who's a bad apple but a great player,

1459
01:23:01,760 --> 01:23:04,800
Speaker 20: you're gonna draft them. You can help you win, You're

1460
01:23:04,840 --> 01:23:05,519
Speaker 20: gonna draft them.

1461
01:23:05,640 --> 01:23:07,160
Speaker 1: It's all about public consumption.

1462
01:23:08,080 --> 01:23:11,479
Speaker 2: The bottom the bottom line is the bottom line, Andy,

1463
01:23:12,040 --> 01:23:14,120
Speaker 2: plain and simple, and our time is up.

1464
01:23:14,920 --> 01:23:16,439
Speaker 20: Oh my goodness, that's the bottom line.

1465
01:23:16,479 --> 01:23:16,760
Speaker 10: I guess.

1466
01:23:16,840 --> 01:23:19,400
Speaker 1: Huh, we we have reached the bottom line.

1467
01:23:20,720 --> 01:23:21,080
Speaker 20: All right.

1468
01:23:21,400 --> 01:23:24,160
Speaker 2: Uh, thank you so much, fur Ball. Take care of yourself,

1469
01:23:24,360 --> 01:23:26,760
Speaker 2: and if you if you get back in your car,

1470
01:23:27,280 --> 01:23:29,040
Speaker 2: be very very careful.

1471
01:23:29,280 --> 01:23:30,559
Speaker 1: I heard it slick out there.

1472
01:23:31,000 --> 01:23:32,320
Speaker 20: Oh my goodness, you're scaring me.

1473
01:23:32,400 --> 01:23:36,120
Speaker 2: Now, all right, bye the fur ball on the nightcap.

1474
01:23:36,720 --> 01:23:39,360
Speaker 2: You're on seven hundred w l W back to rapid

1475
01:23:39,520 --> 01:23:40,040
Speaker 2: just a moment.

1476
01:23:41,479 --> 01:23:42,080
Speaker 14: Well, that's it.

1477
01:23:42,479 --> 01:23:45,160
Speaker 2: Hey, thanks for tuning in tonight, and in my admonission

1478
01:23:45,240 --> 01:23:47,840
Speaker 2: against you, be very very careful if you've got to

1479
01:23:47,920 --> 01:23:50,960
Speaker 2: drive and get out. We're going back down into the

1480
01:23:51,080 --> 01:23:55,360
Speaker 2: teens and maybe single digits by tomorrow morning. Our two

1481
01:23:55,439 --> 01:23:58,760
Speaker 2: day heat wave is over and there's been some fresh snow,

1482
01:23:58,840 --> 01:24:02,320
Speaker 2: as you will know. We end tonight's program the way

1483
01:24:02,560 --> 01:24:05,439
Speaker 2: I like to do, with the Star Spangled banner, our

1484
01:24:05,560 --> 01:24:09,760
Speaker 2: national anthem to honor America on seven hundred WLW