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Speaker 1: You're listening to John and Ken on demand from KFI

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Speaker 1: AM six forty John and Ken Show, John Cobelt and

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Speaker 1: Ken Champeau KFI AM six forty Live everywhere on the

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Speaker 1: iHeartRadio app.

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Speaker 2: We start this hour by bringing Steve Bolloyd back to

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Speaker 2: the show, a senior legal fellow at the Energy and

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Speaker 2: Environment Legal Institute, and he wrote an editorial that appeared

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Speaker 2: in the Wall Streetjourtle about this story that July third

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Speaker 2: and July fourth with the two hottest days on Earth

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Speaker 2: on record. As he says, it comes from the global

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Speaker 2: warming industry, and of course they got a lot and

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Speaker 2: I mean a lot of media play those.

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Speaker 1: Two days supposedly the hottest in one hundred and twenty

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Speaker 1: five thousand years. Say that out loud, July fourth was

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Speaker 1: the hottest in one hundred and twenty five thousand years.

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Speaker 1: Somebody check how long humans have been around, because I

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Speaker 1: think we evolved into our current form about one hundred

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Speaker 1: thousand years ago.

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Speaker 3: Let's get Steve on the line here, Steve Maloy.

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Speaker 4: Hey, John, how are you doing all right?

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Speaker 1: So Steve you can explain this to us. How would

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Speaker 1: they know what the temperature was globally one hundred and

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Speaker 1: twenty five thousand years ago.

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Speaker 4: Well they don't. I think that's the joke. I mean,

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Speaker 4: they're making these claims which get parroted through the lamestream media.

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Speaker 4: You know, the claim is based on satellite gathered data

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Speaker 4: to start with. Now, what satellites did they have one

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Speaker 4: hundred and twenty five thousand years ago? Absolutely none. And

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Speaker 4: if you look into it just a little bit deeper,

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Speaker 4: you see that, you know, most of the world where

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Speaker 4: people live wasn't really warmer. There was this incredible heat

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Speaker 4: wave over the Antarctic, you know, went from like normally

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Speaker 4: it's winter down there right now, and normally it's like,

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Speaker 4: you know, seventy below, but it went made it up

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Speaker 4: to thirty below, right, still pretty cold. But you know that,

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Speaker 4: you know, forty degree difference over a large area, Well,

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Speaker 4: obviously that's going to affect this, you know, bogus notion

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Speaker 4: of a global average global temperature, which of course nobody

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Speaker 4: lives at. Where do you measure it? You know, Al

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Speaker 4: Gore says the Earth has a fever war Do you

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Speaker 4: put the thermometer?

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Speaker 2: We didn't.

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Speaker 3: We didn't even have thermometers till what the eighteen.

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Speaker 4: Hundreds, Uh yeah, basically around that, but we have you know,

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Speaker 4: we haven't had reliable measurements of We still don't have

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Speaker 4: reliable measurements of global temperatures. Much of the Earth's surface

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Speaker 4: is still not covered. Even where we measure temperatures, they're

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Speaker 4: not accurate to within one degree centigrade. And course, that

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Speaker 4: is the amount of global warming the alarmists claim we've

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Speaker 4: had since industrial las right, so you can really measure it.

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Speaker 1: We barely had people around one hundred and twenty five

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Speaker 1: thousand years ago. We certainly didn't have thermometers. We didn't

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Speaker 1: have satellites. We didn't have thermometers till the eighteen hundreds.

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Speaker 1: I can remember that weather satellites came around the late

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Speaker 1: nineteen seventies or in nineteen seventy eight, seventy nine. I

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Speaker 1: think Sony anything pre all those demarcations is just total nonsense.

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Speaker 4: Well, yeah, for sure. And I mean the reason I

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Speaker 4: brought up the Antarctic heat wave is because that's probably

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Speaker 4: been happening a lot over the course of time. And

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Speaker 4: if we're going to say, well, this is the hottest

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Speaker 4: day based on that, well we have we've never been

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Speaker 4: really been able to measure that until recently, until we've

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Speaker 4: had satellites. There's there aren't very many temperature stations down there.

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Speaker 4: None of them are really reliable. The whole thing is

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Speaker 4: just made up, like all of climate. You know, I

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Speaker 4: pointed out in my article that if you looked at

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Speaker 4: where there were where people actually live and you know,

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Speaker 4: measured actually measuring actual temperatures where people live, the Earth

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Speaker 4: is about fifty seven and a half degrees has been

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Speaker 4: that way for a very long time. You know, nothing

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Speaker 4: has changed recently. This is not the hottest June, This

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Speaker 4: is not the hottest July, this is not the hottest year.

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Speaker 4: This is just another year, another month, another day, another week.

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Speaker 3: So where where do they get the extra your heat from?

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Speaker 1: Because you're right that the temperatures probably averages around fifty seven,

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Speaker 1: not sixty two.

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Speaker 4: They got they got it from this Antarctic heat wave,

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Speaker 4: which just that Yeah, we've only you know, been measuring recently.

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Speaker 1: So that that threw off the whole world's temperature average.

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Speaker 4: Yeah, the Arctic is an exactly average right now. It

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Speaker 4: has been for months now. There is an unusual going anywhere.

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Speaker 4: This is just you know, summer and weather. You know,

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Speaker 4: it's been hot before. In California, it's been hot before

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Speaker 4: in Arizona. It's been hot before in Texas. You know,

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Speaker 4: in nineteen eighty, Texas had a heat wave that went

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Speaker 4: on for about you know, ten weeks or so. Two

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Speaker 4: thousand people died. Back then, it was just the heat

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Speaker 4: wave and bad weather and and you know, it wasn't

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Speaker 4: climate change or global warming. Now we've completely weaponized all

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Speaker 4: these terms.

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Speaker 1: Are you ware of any explanation as to why we

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Speaker 1: had ice ages and why they ended?

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Speaker 4: Well, you know, there are you know, the Earth goes

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Speaker 4: around the sun and there's a little bit of a wobble.

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Speaker 4: There's this, you know, Malankovitch cycle. It's called also there

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Speaker 4: are you know, all sorts of changes that go on,

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Speaker 4: and the earth of the Earth is the core of

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Speaker 4: the earth is very hot, and that is changing, you know,

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Speaker 4: I mean the Earth is constantly changing. And this notion

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Speaker 4: that you know, climate alarmist wants you to believe that, well,

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Speaker 4: you know, if everyone has we just have windmills and

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Speaker 4: solar panels, we're going to go back to the climate

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Speaker 4: of yesteryear. No, we're not. Well, I don't even know

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Speaker 4: what that means.

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Speaker 1: But this is a lot of money for a lot

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Speaker 1: of people, isn't it.

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Speaker 4: Yeah, this is trillions and trillions of dollars. As a

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Speaker 4: matter of fact, you know, the alarmist community, they want

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Speaker 4: to spend two hundred and seventy trillion dollars over the

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Speaker 4: next thirty years getting to net zero, John Kerry, once

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Speaker 4: we get to this is really funny. Once we get

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Speaker 4: to net zero, John Carey wants to spend another one

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Speaker 4: point six quadrillion dollars sucking carbon dioxide out of the atmosphere.

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Speaker 3: Quadrillion.

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Speaker 4: Yeah, quadrillion. He was asked about that last week at

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Speaker 4: the house here. Yeah, he wants to. He wants to

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Speaker 4: suck out of the air one point six trillion tons

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Speaker 4: of carbon dioxide and each you know, doing that costs

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Speaker 4: one thousand dollars a ton, so that works out to

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Speaker 4: one point six quadrillion. Do guys crazy? They're all crazy.

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Speaker 3: Do you know what?

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Speaker 1: You're the first person I've ever heard you use the

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Speaker 1: phrase quadrillion to describe to describe any spending plan. This

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Speaker 1: this temperature.

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Speaker 2: Claim, Steve, came from the University of Maine's Climate reanalyzer,

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Speaker 2: which you right, relies on a mix of satellite temperature

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Speaker 2: data and computer model guestimation. This story got so much

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Speaker 2: play in the media everywhere. It comes from just this

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Speaker 2: University of Maine's climate reanalyzer.

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Speaker 4: Uh yeah, it's exactly yeah, And and they're the ones

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Speaker 4: that they use some satellite day. It has some computer models,

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Speaker 4: and of course none of these computer models work. It's

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Speaker 4: just making stuff up. And because it got this really

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Speaker 4: shocking answer, you know, the dirty secret is that this

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Speaker 4: year has been cool. And not only has this year

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Speaker 4: been cool, there's been no global warming in the past

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Speaker 4: almost nine years, despite emissions of five hundred billion times.

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Speaker 4: You know, we're taught that every emission warms the planet,

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Speaker 4: will the last five hundred billion have warmed nothing. So

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Speaker 4: that's why the media is going just absolutely bonkers this

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Speaker 4: year with every heat wave and everything they can make up.

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Speaker 4: They're just throwing everything and anything against the wall hoping

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Speaker 4: it's sticked.

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Speaker 2: We were talking about this last hour that media, especially

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Speaker 2: the media here in California. It was pretty quiet the

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Speaker 2: first six months because it was a pretty cool beginning

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Speaker 2: to the year. As soon as this heat wave hit

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Speaker 2: last week, Holy mackerel, the story's just multiplied. In fact,

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Speaker 2: what was why did that happen?

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Speaker 1: We had one of the coolest six month stretches that

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Speaker 1: anybody could remember.

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Speaker 4: Okay, so what's really what really is controlling our climate

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Speaker 4: and has for at least the last forty years, has

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Speaker 4: been these El Nino's that come out of the Pacific,

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Speaker 4: and the last El Nino, the last time we had

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Speaker 4: global warming was in twenty fifteen, and then we went

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Speaker 4: into this the negative phase of that, the La Ninia

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Speaker 4: phase where there's some cooling and then you know, now

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Speaker 4: we're going and we had a like a three years

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Speaker 4: of La Ninia, So that made it pretty cool, and

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Speaker 4: that's why you got all that rain in the in

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Speaker 4: the winter and spring, and why it's been cloudy and cool.

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Speaker 4: And so now we're going into an al Nina phase

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Speaker 4: and the al Nino is once again going to drive

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Speaker 4: temperatures up a little if it's if it's strong enough,

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Speaker 4: and so that that's really what's going on. It's these

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Speaker 4: El Ninos that emissions have nothing to do with.

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Speaker 2: I like the way you also wrote ninety six percent

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Speaker 2: of US temperature stations produce corrupted data.

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Speaker 4: Why is that, Well, it's just it's it's very hard

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Speaker 4: to get a real, real measurement. You know, a lot

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Speaker 4: of these temperature stations tend to be in urban heat islands.

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Speaker 4: You know, the urban heat island effect is where like

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Speaker 4: you know, if you look at your local weather app

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Speaker 4: in the evening, you see urban areas. You know, cities

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Speaker 4: are warmer than the countryside. That's because of all the

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Speaker 4: asphalt and concrete waste heat.

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Speaker 1: Oh yeah, my driveway is ten degrees hotter than right

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Speaker 1: then after I pull the car out down the block.

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Speaker 4: So if you have a temperature station at an airport

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Speaker 4: which is nothing but concreted asphalt and hot air coming

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Speaker 4: out of jet engines, well you're gonna get a biased result.

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Speaker 4: So there is there's a lot of that, and there's

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Speaker 4: a lot of other things that can corrupt temperature readings,

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Speaker 4: and uh, you know people have done research and found

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Speaker 4: that you know, ninety six percent of these stations are corrupted.

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Speaker 4: They're not accurate to within one degree center grade, which is,

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Speaker 4: you know, exactly the amount of global warming they claim

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Speaker 4: we've had. So we really don't know what's going on

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Speaker 4: at all. You know, you throw in this, you know,

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Speaker 4: the Antarctic heat waves, who knows, who knows what global

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Speaker 4: temperatures really done. But they you know, the alarmists want

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Speaker 4: us to give up fossil fuels destroy our standard of living.

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Speaker 4: They want to tell us how to live, where to live,

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Speaker 4: what kind of electricity we can have, what kind of

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Speaker 4: food we can eat. It's all crazy, all right.

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Speaker 2: Steve, always a pleasure to talk to you. Thanks for

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Speaker 2: coming on.

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Speaker 4: Thank you, y bye.

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Speaker 2: Steve malloy, Senior legal fellow at the Energy and Environment

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Speaker 2: Legal Institute, and also writes about what he calls chunk science.

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Speaker 2: And this was about the report that Earth's had its

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Speaker 2: hottest temperature, you know, twenty five our average temperature on

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Speaker 2: twenty five thousand years. Johnny Ken KFI AM six forty

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Speaker 2: Live Everywhere iHeartRadio app Johnny.

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Speaker 1: Kent Show, John Cobel ken Champell KFI AM six forty

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Speaker 1: Live Everywhere on the iHeartRadio app. Live on the radio

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Speaker 1: for one until four, and then after four o'clock it's

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Speaker 1: Johnny Ken on demand the podcast, so you can catch

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Speaker 1: up on what you missed.

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Speaker 2: And we have spent a lot of time since the

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Speaker 2: pandemic talking about the ramp and fraud that affected the

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Speaker 2: Employment Development Department, that's California's unemployment office. Thirty billion plus

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Speaker 2: dollars ripped off from our unemployment system by all sorts

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Speaker 2: of fraudsters, including prisoners and prisoners friends. We've mentioned this

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Speaker 2: story many times, but now we're going to move to

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Speaker 2: another one that's kind of under the radar, and it

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Speaker 2: comes from a term that has really gotten popular in

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Speaker 2: the last few years. It is the term ghosting. John,

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Speaker 2: you've heard the term ghosting. People say this a lot

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Speaker 2: when with dates or people they know. I got ghosted.

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Speaker 1: I've heard it with a couple of guys you run

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Speaker 1: restaurants have told me they get ghosted by job applicants.

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Speaker 3: They're hired, but they never show you know.

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Speaker 2: What's the loss there, except you feel like you've got

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Speaker 2: the position filled and then you don't.

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Speaker 1: But you're not paying anything.

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Speaker 3: They've been ghosted.

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Speaker 1: It's like, yeah, you start Monday, Monday comes no sign

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Speaker 1: of them.

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Speaker 2: Well, this is about the California community college system and

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Speaker 2: ghost students. You see, colleges are very aggressive and trying

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Speaker 2: to recruit students, and one of the things that's become

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Speaker 2: very popular.

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Speaker 1: In the last I don't know, ten years.

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Speaker 2: You see all the commercials you can get your degree online.

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Speaker 1: That's right.

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Speaker 2: You don't have to actually physically come to a classroom,

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Speaker 2: study online, take your tests online, get your diploma online.

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Speaker 1: We have a fake school. We're offering a fake degree online.

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Speaker 2: Well, in this case, they aren't fake schools, they're real

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Speaker 2: community colleges, but the students are fake. And it's because

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Speaker 2: the fraudsters are looking for financial aid. The story starts

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Speaker 2: out with a great one manned by the name of

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Speaker 2: Richard Valacenti. He got a check in the mail for

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Speaker 2: fourteen hundred dollars last summer. The US Department of Education

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Speaker 2: notified him the money was a mistake. It was an

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Speaker 2: overpayment of a three thousand dollars PEL grant. He used

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Speaker 2: to attend Saddleback College in Orange County. Well, Valacenti is

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Speaker 2: sixty four years old and he never applied for any pelgrants.

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Speaker 2: He's actually a radiation on collegist that you see, Davis.

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Speaker 2: He's never even heard of Saddleback College. So they used

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Speaker 2: to personal information to make him a student, a ghost student,

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Speaker 2: to apply for money grant money. That's what the fraudsters

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Speaker 2: are up to. And when you read this story in

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Speaker 2: the San Francisco Chronicle that they get away with this at.

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Speaker 1: An alarmingly high rate.

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Speaker 2: More than four hundred and sixty thousand of the two

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Speaker 2: point three million requests to the California Community College online

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Speaker 2: application system since July alone, it's about twenty percent or

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Speaker 2: probably scammers think about that.

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Speaker 1: Those numbers can pile up, what's four hundred and sixty

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Speaker 1: thousand times how many dollars?

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Speaker 3: Yeah, yeah, that's a.

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Speaker 2: Community Colleges are required to accept any student in the

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Speaker 2: state with a high school diploma, and a social security

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Speaker 2: number is not required to apply for them.

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Speaker 1: And there you go, because you let in so many

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Speaker 1: illegal aliens, and these stupid progressives say, well, we can't

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Speaker 1: require social security numbers, not everyone, as it's a social

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Speaker 1: security number.

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Speaker 3: That's just not fair.

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Speaker 1: Well, this is what happens, and then they close the

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Speaker 1: schools because of their stupid COVID banck. Look at all

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Speaker 1: the layers of stupid here. Okay, there's no social Security number.

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Speaker 1: COVID shuts down the schools forever.

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Speaker 3: And then you're allowed to take.

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Speaker 1: Your course online. Nobody ever has to see your face.

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Speaker 1: You can take your online course. You don't have to

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Speaker 1: have your screen on.

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Speaker 2: Yeah, if the fraudsters are human, but they use bots

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Speaker 2: software algorithms to mimic enrolled students. They talk to Kim Rich,

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Speaker 2: a criminal justice instructor at Pierce College, near La, who

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Speaker 2: says that she's got to ferret out these fake students.

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Speaker 2: She looks for consecutive ID numbers, similar email patterns that

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Speaker 2: don't match student names and birth dates from the sixties

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Speaker 2: and seventies and indicate that these people are too old

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Speaker 2: for community college.

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Speaker 3: Well why didn't you make them come in to get

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Speaker 3: their loan?

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Speaker 1: Well, eventually they do. That is that often happens?

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Speaker 4: Yes?

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Speaker 3: Do you think banks do this?

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Speaker 1: You think Bank of America does it for people who

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Speaker 1: want to get a mortgage.

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Speaker 2: The Chancellor's office now requires colleges to send monthly reports

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Speaker 2: of their fake students and administrators. Apparently, in one case

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Speaker 2: at City College in San Francisco, twenty nine bogus students

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Speaker 2: received over twenty two thousand dollars in pelgrants. Administrators just

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Speaker 2: blocked five hundred and five ghost students from this summer's classes,

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Speaker 2: and more than forty three hundred suspicious enrollments more than

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Speaker 2: ten percent were probably a fake students.

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Speaker 3: And how many got through.

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Speaker 1: They're only talking about the ones that they that they caught, right,

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Speaker 1: but there's probably hundreds and thousands that blew through.

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Speaker 2: So this Pierce College story, this woman had two eight

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Speaker 2: week classes that were supposed to begin on April tenth

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Speaker 2: each were filled with forty students by early March, so

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Speaker 2: she was asked to teach another It filled up in

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Speaker 2: a week. She was kind of shocked after she analyzed

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Speaker 2: her three rosters. Enrollment in one class dropped from forty

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Speaker 2: to two twenty nine, and another down to twenty two,

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Speaker 2: and the last to just two students. Just started at

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Speaker 2: the face.

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Speaker 1: It was the same bots right, Well, one department eliminated

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Speaker 1: eighty ghost students and another eighty showed up within an hour.

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Speaker 3: Eighty ghosts an hour.

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Speaker 2: Total enrollment appears was at seventy seven hundred before the

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Speaker 2: college's eight week classes began this spring. By the time

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Speaker 2: instructors cleared the ghosts, enrollment was down to just under

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Speaker 2: five thousand.

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Speaker 1: Just like that, So like a third of the enrollment

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Speaker 1: was fake and they were looking for money.

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Speaker 2: Well, you can see how easy this is to do

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Speaker 2: this because you're just doing this all by remote.

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Speaker 3: Yeah, exaplication. So why didn't you end all that?

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Speaker 1: How about you want to enroll and you want money,

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Speaker 1: then you have to show up, and you show up

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Speaker 1: and we want to see ID and we want your fingerprint.

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Speaker 2: Yes, some have rules you have to show up at

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Speaker 2: least once to the class, because that would defeat the

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Speaker 2: point of recruiting more students who can't get to the

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Speaker 2: college because they have jobs or whatever, so they want

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Speaker 2: to work on their own time.

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Speaker 1: Were stealing the idea of people who are sixty five

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Speaker 1: years old, right.

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Speaker 2: Yeah, that's what he did, right, He took this guy's identity.

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Speaker 1: Right, So when you have to show up, then okay,

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Speaker 1: that scam is toast. There's no way around it once

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Speaker 1: you need real bodies to show up in class. God,

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Speaker 1: the whole bureaucracy in California, from top to bottom, is

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Speaker 1: stupid and lazy, and they don't care about all this

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Speaker 1: money that gets blown out. It's nobody cares start stupid

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Speaker 1: tax money.

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Speaker 2: Well, apparently some of the college people interviewed here, the

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Speaker 2: stressles are trying to define the mess.

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Speaker 1: Yes, the professor cares because she has a class scheduled

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Speaker 1: for eighty kids and now there's two, right or something

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Speaker 1: like that, So yeah, she cares.

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Speaker 3: But the people who set up the system, they don't.

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Speaker 1: Think for five minutes, like, well, what's going to happen

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Speaker 1: if we never require a human being to engage with us? Personally,

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Speaker 1: what's gonna happen? You're giving away free money. I mean,

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Speaker 1: it's obvious, especially after the Edd scandal where they blew

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Speaker 1: thirty billion dollars on all the worldwide fraudsters. Of course,

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Speaker 1: this goes on constantly, all day, all night. There are thousands,

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Speaker 1: hundreds of thousands of people around the planet. We're scamming

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Speaker 1: one program or another. All right, we got more coming up.

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Speaker 1: John and Ken KFI A M six forty. We're live

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Speaker 1: everywhere the iHeartRadio app. More the Johnny Kent Show, John

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Speaker 1: Cobelt and Ken Shampeau. It's k F I AM six

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Speaker 1: forty live everywhere on the iHeartRadio app. And the iHeart

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00:18:42,640 --> 00:18:45,440
Speaker 1: app is where you can hear the John and kennon

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Speaker 1: demand podcast. And you know, this is kind of a

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Speaker 1: two parter.

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Speaker 2: We did a story that was running the San Francisco

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Speaker 2: Chronicle entitled how ghost students are applying to colleges to

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Speaker 2: steal financial aid. We talked a lot that during the pandemic,

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Speaker 2: people were stealing unemployment money, but what also started and

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Speaker 2: got bigger during the pandemic was stealing community college aid

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Speaker 2: money by what they call using ghost students. That is,

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Speaker 2: they would probably collect the name and some identifying information

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Speaker 2: of real people, but stick them in there as prospective

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Speaker 2: community college students and then apply for financial aid, which

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Speaker 2: would get diverted to the fraudster.

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Speaker 1: It says here.

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Speaker 2: Although the state software has caught more than half of

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Speaker 2: fraudulent mission applications in July, it's still left about two

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Speaker 2: hundred thousand sham applications. The pelgrant is the most common.

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Speaker 2: It's a federal college subsidy for needy students, and fraudsters

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Speaker 2: love to try to steal that money. We're going to

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Speaker 2: talk to somebody reached out to us because she's mentioned

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Speaker 2: in the article. Kim Rich is a criminal justice instructor

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Speaker 2: at Pierce College to Community College in Woodland Hills, and

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Speaker 2: she apparently is an expert at identifying these fake students

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Speaker 2: in her online classes. And of course that's the other

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Speaker 2: part of this. If the student is online, they don't

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Speaker 2: necessarily show up in front of you in the classroom.

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Speaker 2: It would be easier for them to be a ghost.

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Speaker 2: Let's get Kim on the show and talk more about this.

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Speaker 1: Kim, how are you great? How are you good?

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Speaker 4: Thanks?

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Speaker 3: Thanks for coming on.

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Speaker 1: All right, explain what you've seen from your post at

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Speaker 1: Pierce College.

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Speaker 5: Well, this release started basically a couple of years ago,

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Speaker 5: and the pandemic is really the catalyst for allowing this

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Speaker 5: to happen. Obviously, financial aid fraud has been around forever,

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Speaker 5: but you know, being online really enabled them to take

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Speaker 5: advantage of the situation. And also the free flowing money

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Speaker 5: that our government has been handing out also didn't, you know,

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Speaker 5: really help this cause. And in California you can apply

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Speaker 5: to one or one hundred and sixteen of our California

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Speaker 5: community colleges all through one portal, and so this made

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Speaker 5: it even easier for these criminals to access all of

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Speaker 5: our colleges community colleges and to be able to apply

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Speaker 5: to them and roll in them and then be able

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Speaker 5: to apply for and obtain financial aid.

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Speaker 1: So you could use dozens of names and apply to

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Speaker 1: dozens of colleges and get dozens of grant checks.

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Speaker 5: Yes you can.

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Speaker 2: What does it mean in terms of paying tuition or

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Speaker 2: anything else that they have to do? I mean, does

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Speaker 2: the money come that quickly to them?

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Speaker 5: It says, And basically they've been able to use some

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Speaker 5: kind of algorithm. I am not tech savvy in that sense,

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Speaker 5: but they've been able to basically have these spots, you know,

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Speaker 5: just constantly applying and are enrolling in these courses. And

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Speaker 5: for instance, in my one class you know, has a

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Speaker 5: cap enrollment of forty, thirty eight of them ended up

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Speaker 5: being fake students. So thirty eight enrolled in this class,

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Speaker 5: and so they were able to if they who knows

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Speaker 5: if they actually ended up getting financial aid or not.

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Speaker 5: I don't have access to that data, but they could have.

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Speaker 5: Otherwise there's no point of them being enrolled in a class.

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Speaker 5: They're not there to get an education. They don't even exist.

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Speaker 5: They're not real people. So they have the opportunity to

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Speaker 5: receive financial aid if they, you know, have that timeframe

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Speaker 5: where they can capture that financial aid and basically get

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Speaker 5: away with it.

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Speaker 1: What are they using.

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Speaker 2: They're using real people's names and some sort of identifying data.

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Speaker 1: Is that what they use?

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Speaker 5: Yeah, they're obviously using real people's information. Back when I

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Speaker 5: first detected this in summer of twenty twenty one, there

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Speaker 5: were in my course then I had found several instances

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Speaker 5: of identity staff where they had been using people's information

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Speaker 5: from throughout the country, even using people who were deceased.

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Speaker 5: They were using their images and all of their data

440
00:23:18,720 --> 00:23:21,520
Speaker 5: that I was able to find on the internet.

441
00:23:22,359 --> 00:23:25,440
Speaker 2: Is this because you're a criminal justice instructor you really

442
00:23:25,440 --> 00:23:27,399
Speaker 2: made a point to try to track these down.

443
00:23:29,359 --> 00:23:33,760
Speaker 5: No, I just wanted to basically see how they were

444
00:23:33,880 --> 00:23:38,760
Speaker 5: coming upon using these images that were in the online class.

445
00:23:39,040 --> 00:23:41,600
Speaker 5: The images were kind of one of the reasons that

446
00:23:42,160 --> 00:23:45,960
Speaker 5: I want these do not look like normal students images

447
00:23:46,040 --> 00:23:48,800
Speaker 5: that they would use as an avatar in their class.

448
00:23:48,800 --> 00:23:52,200
Speaker 5: They definitely looked like they were something from the internet.

449
00:23:54,000 --> 00:23:55,760
Speaker 2: I was going to ask for your techniques and trying

450
00:23:55,800 --> 00:23:59,080
Speaker 2: to ferret out these these fake students. Is that what

451
00:23:59,119 --> 00:24:00,600
Speaker 2: do you usually do what looking for?

452
00:24:01,960 --> 00:24:05,600
Speaker 5: It's not really necessarily a technique, not something that I

453
00:24:05,640 --> 00:24:07,960
Speaker 5: would say, hey, you know, this is what you should

454
00:24:08,000 --> 00:24:11,639
Speaker 5: do look for ABCD. It's just a lot of times

455
00:24:12,600 --> 00:24:15,280
Speaker 5: something that jumps out to me, things that I see

456
00:24:15,440 --> 00:24:22,000
Speaker 5: in common that are not normal or things that are irregular.

457
00:24:22,359 --> 00:24:25,480
Speaker 5: Now there's kind of becoming more of a system. You'll

458
00:24:25,520 --> 00:24:30,479
Speaker 5: see obviously strange things in the names. You'll see you know,

459
00:24:30,560 --> 00:24:34,280
Speaker 5: the first name the last name are similar, or they're

460
00:24:34,359 --> 00:24:38,480
Speaker 5: the same identical first name and last name on the rosters.

461
00:24:38,520 --> 00:24:44,480
Speaker 5: Oftentimes you'll see them using characters or even numbers in

462
00:24:44,560 --> 00:24:52,560
Speaker 5: their name. Sometimes their names are actually very interesting. They'll

463
00:24:52,920 --> 00:24:55,960
Speaker 5: actually have like a little sentence is actually part of

464
00:24:56,000 --> 00:25:01,360
Speaker 5: the name. They come up with all unique things just

465
00:25:01,400 --> 00:25:04,719
Speaker 5: to get into class, hoping that people won't catch it.

466
00:25:04,880 --> 00:25:08,000
Speaker 5: And if they get on the roster and the class begins,

467
00:25:08,320 --> 00:25:12,919
Speaker 5: that means many people before it gets to the instructor

468
00:25:13,160 --> 00:25:16,879
Speaker 5: have not caught that because they have been on the

469
00:25:17,000 --> 00:25:20,560
Speaker 5: roster enrolled in class for quite some time, that somebody

470
00:25:20,600 --> 00:25:22,320
Speaker 5: should have caught it and has them.

471
00:25:22,840 --> 00:25:26,600
Speaker 1: Going back to that class where you had forty people enrolled,

472
00:25:26,840 --> 00:25:30,040
Speaker 1: thirty eight of them were fake. How did you figure

473
00:25:30,080 --> 00:25:33,240
Speaker 1: this out? Did you have thirty eight bots on the

474
00:25:33,280 --> 00:25:36,040
Speaker 1: first day of class staring at you from the screen.

475
00:25:38,560 --> 00:25:43,159
Speaker 5: My class is not a live class, so they have

476
00:25:43,400 --> 00:25:47,240
Speaker 5: basically a week to complete the work that I assigned

477
00:25:47,320 --> 00:25:52,040
Speaker 5: to them, but there's built in assignments where I can

478
00:25:52,160 --> 00:25:57,160
Speaker 5: basically read out if a person is real or not. However,

479
00:25:58,080 --> 00:26:03,120
Speaker 5: there are some tail tells lines where I basically determined

480
00:26:03,200 --> 00:26:08,320
Speaker 5: that the majority of them were fake, Like nobody except

481
00:26:08,320 --> 00:26:13,120
Speaker 5: for a handful of them, actually logged into the class.

482
00:26:13,480 --> 00:26:18,399
Speaker 1: So that's kind of there's a tip off right there.

483
00:26:19,240 --> 00:26:25,640
Speaker 5: Yeah, exactly, And you know I was not the only

484
00:26:25,760 --> 00:26:29,399
Speaker 5: professor at the college that this happened to. I believe

485
00:26:29,560 --> 00:26:36,200
Speaker 5: mine was the lowest enrollment, but there were other faculty

486
00:26:36,320 --> 00:26:41,920
Speaker 5: who had numbers below ten, even below five where these

487
00:26:42,160 --> 00:26:46,200
Speaker 5: classes were full at one point in time up too

488
00:26:46,240 --> 00:26:51,680
Speaker 5: close to a month before the classes began, and this

489
00:26:51,800 --> 00:26:56,159
Speaker 5: should have been caught way before the semester began, and

490
00:26:56,200 --> 00:27:01,480
Speaker 5: they weren't. And the enrollment at the call for specifically

491
00:27:01,520 --> 00:27:07,840
Speaker 5: these late start classes dropped close to three thousand students

492
00:27:08,040 --> 00:27:12,240
Speaker 5: just for these late start online classes. And that's a

493
00:27:12,280 --> 00:27:15,359
Speaker 5: big drop and enrollment just for that time period.

494
00:27:15,920 --> 00:27:19,320
Speaker 2: Where do they is the money paid, if you know,

495
00:27:19,359 --> 00:27:21,040
Speaker 2: the grant money. Is it paid by check or direct

496
00:27:21,040 --> 00:27:23,560
Speaker 2: deposit or how do these scammers get it sent to them?

497
00:27:23,760 --> 00:27:25,359
Speaker 2: They figure out some sort of scheme there.

498
00:27:26,960 --> 00:27:29,000
Speaker 5: So in the I guess you would call it the

499
00:27:29,040 --> 00:27:34,359
Speaker 5: old days actually really just only pre pandemic. Most of

500
00:27:34,359 --> 00:27:36,280
Speaker 5: the time you would go to the business office, show

501
00:27:36,320 --> 00:27:40,119
Speaker 5: your ID, you would get a check, pay for you know,

502
00:27:40,280 --> 00:27:44,800
Speaker 5: obviously your tuition books, and then obviously some of the

503
00:27:44,880 --> 00:27:48,840
Speaker 5: money is used for expenses, living expenses. Now it goes

504
00:27:49,000 --> 00:27:53,520
Speaker 5: through basically what you mentioned, a direct deposit system, and

505
00:27:53,840 --> 00:27:56,840
Speaker 5: there is I guess you could call it maybe a

506
00:27:58,160 --> 00:28:04,600
Speaker 5: intermediate program platform. It's called bank Mobile and the contract

507
00:28:04,600 --> 00:28:08,119
Speaker 5: where I believe approximately one third of the colleges throughout

508
00:28:08,119 --> 00:28:12,480
Speaker 5: the United States. And so once the college receives the

509
00:28:12,560 --> 00:28:16,840
Speaker 5: money and takes their portion from what I have researched

510
00:28:16,880 --> 00:28:22,240
Speaker 5: and read, it goes into this bank Mobile account and

511
00:28:22,280 --> 00:28:29,359
Speaker 5: then the real student or the criminals can access bank

512
00:28:29,520 --> 00:28:33,520
Speaker 5: Mobile and request that money be sent to their own

513
00:28:33,560 --> 00:28:37,240
Speaker 5: personal account, and then they have access to the funds.

514
00:28:37,960 --> 00:28:40,680
Speaker 2: Well, Kim, thank you so much for coming on. We're

515
00:28:40,720 --> 00:28:42,920
Speaker 2: glad you heard we were talking about this story and

516
00:28:43,240 --> 00:28:44,280
Speaker 2: we enjoyed talking to you.

517
00:28:44,360 --> 00:28:45,040
Speaker 1: Appreciate it.

518
00:28:45,440 --> 00:28:47,040
Speaker 5: Thank you very much, Appreciate your time.

519
00:28:47,240 --> 00:28:49,600
Speaker 2: All right, It's Kim Rich, a criminal justice instructor at

520
00:28:49,600 --> 00:28:53,680
Speaker 2: Los Angeles is Pierce College. It's in Woodland Hills, and she,

521
00:28:54,720 --> 00:28:57,760
Speaker 2: among many other community college instructors, they have to spend

522
00:28:57,800 --> 00:29:00,800
Speaker 2: some of their time looking for ghost students, fake student

523
00:29:01,000 --> 00:29:03,560
Speaker 2: bots who will apply for financial aid.

524
00:29:03,600 --> 00:29:05,320
Speaker 1: Didn't want to rip off the system.

525
00:29:05,480 --> 00:29:09,520
Speaker 2: Johnny KENKFIAM six forty Live Everywhere, the iHeartRadio app.

526
00:29:10,160 --> 00:29:12,920
Speaker 1: Johnny Kent Show, John Cobelt, and Ken Champeau cat Fox

527
00:29:13,240 --> 00:29:18,480
Speaker 1: AM six forty Live Everywhere on the iHeartRadio app I can't.

528
00:29:18,200 --> 00:29:23,080
Speaker 2: Stell all right, So the voters of Los Angeles, now

529
00:29:23,080 --> 00:29:27,280
Speaker 2: it's more clear, got fooled the endless well that is

530
00:29:27,320 --> 00:29:30,840
Speaker 2: spending on the homeless homeless industrial complex.

531
00:29:30,880 --> 00:29:34,560
Speaker 1: We call it. Billions and billions of dollars spent. Not enough.

532
00:29:35,080 --> 00:29:37,040
Speaker 2: So they looked for a new way in the city

533
00:29:37,040 --> 00:29:40,840
Speaker 2: of Los Angeles to drain even more money from taxpayers,

534
00:29:41,360 --> 00:29:44,240
Speaker 2: and they put on the ballot measure ULA. I think

535
00:29:44,240 --> 00:29:47,040
Speaker 2: that stands for you to night LA. But it's a

536
00:29:47,120 --> 00:29:52,600
Speaker 2: property transfer tax. And when they sold it to the voters,

537
00:29:52,760 --> 00:29:55,320
Speaker 2: they basically said, this is just going to soak the wealthy.

538
00:29:55,400 --> 00:29:58,280
Speaker 2: This is only going to affect people who have very

539
00:29:58,440 --> 00:30:01,680
Speaker 2: very expensive homes for sale. If you have a property

540
00:30:01,720 --> 00:30:05,240
Speaker 2: costing between five million and ten million, the transfer tax

541
00:30:05,360 --> 00:30:08,240
Speaker 2: is four point four to five percent. When it gets

542
00:30:08,240 --> 00:30:12,320
Speaker 2: above ten million, it jumps to five point nine five percent.

543
00:30:12,600 --> 00:30:14,480
Speaker 2: Now this is above and beyond anything else you're going

544
00:30:14,520 --> 00:30:16,880
Speaker 2: to pay to transfer the property.

545
00:30:17,360 --> 00:30:19,080
Speaker 1: They got it passed.

546
00:30:19,760 --> 00:30:22,400
Speaker 2: And now what we learned, And we learned this because

547
00:30:22,960 --> 00:30:27,320
Speaker 2: Chicago is thinking about putting the same measure on its

548
00:30:27,360 --> 00:30:30,520
Speaker 2: ballot to try to get out of there. They're calling

549
00:30:30,560 --> 00:30:35,200
Speaker 2: it bring Chicago Home. Transfer tax. It goes before a

550
00:30:35,280 --> 00:30:39,160
Speaker 2: vote in that city in March. But we learned from

551
00:30:39,200 --> 00:30:44,800
Speaker 2: Los Angeles Councilwoman Nitia Rahman that quote, Well, we marketed

552
00:30:44,840 --> 00:30:47,200
Speaker 2: it as a mansion tax, and that's what made it

553
00:30:47,240 --> 00:30:50,959
Speaker 2: easy for voters to get behind. But now what we've learned,

554
00:30:51,440 --> 00:30:55,720
Speaker 2: it goes after commercial properties too, office buildings, shopping centers,

555
00:30:56,000 --> 00:31:00,400
Speaker 2: industrial warehouses, apartment buildings where renters could get hit with

556
00:31:00,440 --> 00:31:02,880
Speaker 2: these increases when the apartment changed his hands.

557
00:31:02,920 --> 00:31:04,600
Speaker 3: It wasn't just soaking the wealthy.

558
00:31:05,240 --> 00:31:11,240
Speaker 1: It ends up soaking renters because if the taxes are

559
00:31:11,320 --> 00:31:14,280
Speaker 1: heavy on a rental building, renters are going to have

560
00:31:14,360 --> 00:31:19,720
Speaker 1: to pay higher rents. And if you're soaking business owners,

561
00:31:20,200 --> 00:31:22,560
Speaker 1: they're going to have to charge you more for their

562
00:31:22,560 --> 00:31:26,640
Speaker 1: goods and services. So the Chicago Tribune did a story

563
00:31:26,720 --> 00:31:30,040
Speaker 1: on what plan they were trying to pass in Chicago,

564
00:31:30,120 --> 00:31:33,880
Speaker 1: and they went to Nitthea Rahman and she explained how

565
00:31:34,000 --> 00:31:39,640
Speaker 1: she and the others in her progressive circle fulled the public.

566
00:31:40,600 --> 00:31:45,080
Speaker 1: It was marketed as a mentioned tax, marketed not that

567
00:31:45,160 --> 00:31:46,440
Speaker 1: it was a mansion tax.

568
00:31:46,480 --> 00:31:48,880
Speaker 3: It was in bart I don't.

569
00:31:48,720 --> 00:31:51,800
Speaker 2: Think we even focused on the commercial aspects of this

570
00:31:51,840 --> 00:31:54,120
Speaker 2: as much as just the private real estate sales.

571
00:31:54,400 --> 00:31:57,880
Speaker 1: I don't remember. Maybe even we were fooled because we.

572
00:31:57,920 --> 00:32:00,520
Speaker 2: Said, well, it's all going to affect millionaires and billionaire

573
00:32:00,840 --> 00:32:03,120
Speaker 2: how many people sell properties for more than five million?

574
00:32:03,160 --> 00:32:05,959
Speaker 1: Because who covered this other than the El Segundo propaganda

575
00:32:06,000 --> 00:32:08,160
Speaker 1: times And I bet you if we go back and

576
00:32:08,200 --> 00:32:13,040
Speaker 1: look at their coverage, that part was not prominent. And

577
00:32:13,080 --> 00:32:16,040
Speaker 1: they did not dissect exactly that if you go after

578
00:32:16,080 --> 00:32:18,760
Speaker 1: commercial buildings and you go after rental buildings, that it

579
00:32:18,760 --> 00:32:22,000
Speaker 1: would jack up prices for consumers and it would jack

580
00:32:22,120 --> 00:32:26,360
Speaker 1: up rents for renters. Because what you need when you

581
00:32:26,400 --> 00:32:31,520
Speaker 1: promote propaganda is you need media outlets to amplify the propaganda,

582
00:32:31,560 --> 00:32:32,800
Speaker 1: and that's what we have here. And I bet you

583
00:32:32,880 --> 00:32:35,440
Speaker 1: the TV stations barely covered this because it would be

584
00:32:35,480 --> 00:32:36,240
Speaker 1: too complicated.

585
00:32:37,120 --> 00:32:39,760
Speaker 2: So they talked to a guy with the California Business

586
00:32:39,760 --> 00:32:43,360
Speaker 2: Properties Association of Matthew Hargrove, he's the CEO, and he said,

587
00:32:43,880 --> 00:32:45,720
Speaker 2: without doing a lot of digging, you're going to find

588
00:32:45,760 --> 00:32:48,160
Speaker 2: out this was a disaster for LA real estate. It's

589
00:32:48,200 --> 00:32:51,840
Speaker 2: a market. Markets react to taxes. They're not coming anywhere

590
00:32:51,880 --> 00:32:55,160
Speaker 2: near their promise numbers. That's the problem with doing policy

591
00:32:55,440 --> 00:32:58,720
Speaker 2: at the ballot box LA officials had predicted the first

592
00:32:58,880 --> 00:33:02,840
Speaker 2: year of this new city, higher transfer attacks would rake

593
00:33:02,880 --> 00:33:05,840
Speaker 2: in six hundred and seventy two million for homeless services,

594
00:33:06,320 --> 00:33:09,280
Speaker 2: and proponents those really pushing this on the ballot and said,

595
00:33:09,280 --> 00:33:12,680
Speaker 2: oh no, we're going to rake in nine hundred million. Well,

596
00:33:12,800 --> 00:33:16,200
Speaker 2: how's of October one hundred million for six months, so

597
00:33:16,360 --> 00:33:18,520
Speaker 2: you doubled that two hundred million. That's well short of

598
00:33:18,520 --> 00:33:19,440
Speaker 2: those two predictions.

599
00:33:19,680 --> 00:33:26,000
Speaker 1: Well, after the uh tax went into effect the month

600
00:33:26,000 --> 00:33:30,320
Speaker 1: of April, only two mansions worth five million or more

601
00:33:30,360 --> 00:33:32,680
Speaker 1: were sold. In March it was one hundred and twenty

602
00:33:32,680 --> 00:33:37,400
Speaker 1: six people sold to beat the deadline, and then after

603
00:33:37,440 --> 00:33:41,200
Speaker 1: the deadline the market dried up almost entirely, from one

604
00:33:41,280 --> 00:33:42,640
Speaker 1: hundred and twenty six to two.

605
00:33:43,520 --> 00:33:47,000
Speaker 3: And that's house. See, most people who.

606
00:33:46,840 --> 00:33:49,760
Speaker 1: Have made a lot of money and they have expensive

607
00:33:49,760 --> 00:33:53,680
Speaker 1: homes or condos are smart people, or they hire smart people,

608
00:33:53,800 --> 00:33:57,200
Speaker 1: and for them it's not hard to do math. For

609
00:33:57,280 --> 00:33:59,840
Speaker 1: political hacks, it's very hard to do math. They're not

610
00:34:00,160 --> 00:34:04,680
Speaker 1: at numbers. Nithia Rahman is really bottom line of communist,

611
00:34:05,160 --> 00:34:08,799
Speaker 1: so it's not surprising she wants to soak the rich

612
00:34:09,040 --> 00:34:11,920
Speaker 1: and soak property owners. You remember, communists don't believe that

613
00:34:12,000 --> 00:34:17,440
Speaker 1: you should own private property, and most of the people

614
00:34:17,480 --> 00:34:21,040
Speaker 1: behind this measure are basically communists. Communist is having a

615
00:34:21,080 --> 00:34:24,160
Speaker 1: resurgence in this country, just like anti Semitism is.

616
00:34:25,440 --> 00:34:27,440
Speaker 3: It's starting to look like that.

617
00:34:27,520 --> 00:34:31,440
Speaker 1: You know, the nineteen thirties again, nineteen thirties, nineteen forties,

618
00:34:31,520 --> 00:34:33,520
Speaker 1: nineteen fifties, there was a lot of this stuff. I

619
00:34:33,520 --> 00:34:36,240
Speaker 1: guess the old generation died out and there's no public

620
00:34:36,320 --> 00:34:39,760
Speaker 1: memory of what life was like under communism, what life

621
00:34:39,960 --> 00:34:44,399
Speaker 1: was like when Jews were being slaughtered, and so that's

622
00:34:44,440 --> 00:34:47,759
Speaker 1: why you have rebounds, because a new generation doesn't know.

623
00:34:48,440 --> 00:34:52,000
Speaker 2: And there you have a ten million dollar property and

624
00:34:52,040 --> 00:34:54,920
Speaker 2: you get hit with this five point ninety five percent

625
00:34:55,280 --> 00:34:59,880
Speaker 2: transfer tex that is six hundred thousand dollars. Now the

626
00:35:00,120 --> 00:35:03,080
Speaker 2: to say, well, that's just pennies to a billionaire, but

627
00:35:03,120 --> 00:35:05,880
Speaker 2: you know, if you're involved in commercial real estate, where

628
00:35:05,920 --> 00:35:08,600
Speaker 2: you know margins can be tough, particularly feeling an apartment

629
00:35:08,680 --> 00:35:11,359
Speaker 2: building or a shopping center or something like that, six

630
00:35:11,480 --> 00:35:13,440
Speaker 2: hundred thousand dollars is a lot of money that's going

631
00:35:13,480 --> 00:35:15,799
Speaker 2: to affect your decisions and your timing offends me.

632
00:35:16,239 --> 00:35:21,000
Speaker 1: It's not not Nithia Rahman's business just because she doesn't

633
00:35:21,040 --> 00:35:24,280
Speaker 1: have the talents and intelligence to make millions or billions

634
00:35:24,280 --> 00:35:28,879
Speaker 1: of dollars. She promotes law that denies other people from

635
00:35:28,960 --> 00:35:32,920
Speaker 1: enjoying the profits that they that they make. Who the

636
00:35:32,960 --> 00:35:36,680
Speaker 1: hell is she? She's like a little little gnat on

637
00:35:36,719 --> 00:35:40,600
Speaker 1: your rear end, buzzing around, trying, trying, trying to take

638
00:35:40,880 --> 00:35:44,440
Speaker 1: from you what she herself cannot create. She doesn't create wealth.

639
00:35:45,280 --> 00:35:47,760
Speaker 1: She's never created a dime of wealth in her life.

640
00:35:49,120 --> 00:35:52,640
Speaker 1: So what is this her wacky theory? Well, I just

641
00:35:52,920 --> 00:35:55,120
Speaker 1: I don't think it's fair. It's not up to you.

642
00:35:55,680 --> 00:35:57,880
Speaker 1: Who are you? Who are these people?

643
00:35:58,600 --> 00:36:01,520
Speaker 2: It's thinking that some people are just putting off selling,

644
00:36:01,760 --> 00:36:04,359
Speaker 2: or they're hoping maybe a court case overturns the tax

645
00:36:04,400 --> 00:36:07,279
Speaker 2: hike or and I think a recent one was not

646
00:36:07,360 --> 00:36:10,319
Speaker 2: good news. I think it was upheld, or they just

647
00:36:10,400 --> 00:36:12,600
Speaker 2: price it if they're in that range at just under

648
00:36:12,600 --> 00:36:14,920
Speaker 2: five million, so there's no transfer a tax a like

649
00:36:14,960 --> 00:36:17,399
Speaker 2: four point nine ninety nine million, right, just to give

650
00:36:17,440 --> 00:36:17,960
Speaker 2: them the finger.

651
00:36:18,760 --> 00:36:21,120
Speaker 1: Yeah, and that's and that's that's the tricks you have

652
00:36:21,200 --> 00:36:23,920
Speaker 1: to pull. But you know it should get it should

653
00:36:23,920 --> 00:36:26,200
Speaker 1: get repealed. It's not producing the money, and the money

654
00:36:26,239 --> 00:36:30,440
Speaker 1: is going for what to pay more criminally crooked nonprofits.

655
00:36:31,680 --> 00:36:32,839
Speaker 3: I mean, that's the thing.

656
00:36:32,960 --> 00:36:36,160
Speaker 1: The money just goes into a black hole and enrichest

657
00:36:36,200 --> 00:36:40,040
Speaker 1: people who are in the in the fraud industry, nonprofit

658
00:36:40,160 --> 00:36:46,480
Speaker 1: homeless organizations, oxters are hucksters. It's a scam. Seister is

659
00:36:46,480 --> 00:36:50,080
Speaker 1: an huckster. Sist, Yes, it's sister and huckster. That's the

660
00:36:50,120 --> 00:36:55,880
Speaker 1: leading to the law firm that represents them exactly clearly.

661
00:36:56,120 --> 00:36:57,919
Speaker 2: But I just love the way she said. And we've

662
00:36:57,960 --> 00:36:59,840
Speaker 2: known this for as long as we've done this show

663
00:37:00,360 --> 00:37:02,880
Speaker 2: that people will vote for a tax that does not

664
00:37:03,200 --> 00:37:06,799
Speaker 2: affect them, a statewide sales tax, gas tax they're not

665
00:37:06,840 --> 00:37:09,359
Speaker 2: too happy with. But you know, I remember the tax

666
00:37:09,400 --> 00:37:12,759
Speaker 2: on millionaires for mental health services. Yeah, Darryl Steinberg twenty

667
00:37:12,840 --> 00:37:15,279
Speaker 2: years ago worked. You don't see me mentally ill peep

668
00:37:15,360 --> 00:37:15,800
Speaker 2: on the streets.

669
00:37:15,920 --> 00:37:17,320
Speaker 3: No, it's been a miracle.

670
00:37:17,520 --> 00:37:20,839
Speaker 1: Hasn't that done the job? It's all crime, is what

671
00:37:20,840 --> 00:37:23,279
Speaker 1: they're committing. The mental health tax is a crime. This

672
00:37:23,400 --> 00:37:26,760
Speaker 1: mansion tax is a crime. It's just taking money because

673
00:37:26,880 --> 00:37:30,440
Speaker 1: you don't like successful people. I mean, that is a bitter,

674
00:37:30,600 --> 00:37:32,840
Speaker 1: sad potion. And just one quick story about that.

675
00:37:32,920 --> 00:37:35,160
Speaker 2: Mental health taxes came up A couple of months ago,

676
00:37:35,560 --> 00:37:37,640
Speaker 2: they were trying to move some of that money out

677
00:37:37,680 --> 00:37:41,080
Speaker 2: of there into housing, and I'm thinking, Wow, don't we

678
00:37:41,080 --> 00:37:43,120
Speaker 2: hear every day we have a mental health crisis. We

679
00:37:43,160 --> 00:37:46,120
Speaker 2: don't have enough mental health workers and psych facilities, and

680
00:37:46,200 --> 00:37:48,600
Speaker 2: yet they wanted to take money from the millionaires tax

681
00:37:48,640 --> 00:37:52,040
Speaker 2: and move it over to more of their crazy housing ideas.

682
00:37:52,560 --> 00:37:54,520
Speaker 2: That tells you all you need to know about how

683
00:37:54,560 --> 00:37:58,560
Speaker 2: hopeless and useless that they are. We've got more coming up.

684
00:37:58,600 --> 00:38:01,719
Speaker 2: Johnny NKFI AM six four already live everywhere. iHeartRadio app