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Speaker 1: Let's try this again, shall we. After a slight delay

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Speaker 1: caused by unforeseen technical issues, welcome to the Friday edition

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Speaker 1: of The Dan o'donald Show. We apparently had some form

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Speaker 1: of computer meltdown. The system on which we run all

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Speaker 1: of our programming at our flagship station, News Talk eleven

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Speaker 1: thirty WISN had something go catastrophically wrong. So don't worry.

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Speaker 1: I feel like I need to open the show by

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Speaker 1: reassuring my loyal members of DAN nation that I am

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Speaker 1: not dead, that the libs finally did not get to me.

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Speaker 1: I am not tied up in like Tony Evers' basement somewhere.

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Speaker 1: Don't worry, I am just fine. We had an engineer,

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Speaker 1: a producer, another producer, the program director, everybody trying to

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Speaker 1: figure out exactly what was wrong. We'll just chalk it

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Speaker 1: up to, I don't know, everybody's starting their thanks Giving

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Speaker 1: vacation a little early. There was some sort of oversight

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Speaker 1: that led to something that went wrong, that led to

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Speaker 1: about fifty other things that went wrong. But we are live.

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Speaker 1: We are ready to rock and roll on the Friday

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Speaker 1: edition of The Dan o'donald Show. You want to join

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Speaker 1: us into this foray into broadcast excellence. I don't even

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Speaker 1: know if after this long delay we can call it

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Speaker 1: broadcast competence broadcast I don't know, slightly below averageness. Today

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Speaker 1: we'll try to get it back up to competence as

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Speaker 1: the show unfolds. We have got a big exclusive. We

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Speaker 1: actually had a source inside Democrats big ice verifier training

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Speaker 1: seminar at the state Capitol yesterday. And yes, it certainly

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Speaker 1: does appear that ice verifiers are being instructed to obstruct

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Speaker 1: investigations by legitimate federal law enforcement agents that of course

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Speaker 1: violates several statutes. Will get into How you want to

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Speaker 1: join us for one four nine eleven thirty one, eight

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Speaker 1: hundred and eight three eight nine four seven six email

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Speaker 1: me directly d od at iHeartMedia dot com at Dan

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Speaker 1: o'donald's show on x on Facebook, on Instagram. We are

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Speaker 1: streaming live everywhere YouTube, and we are available in podcast

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Speaker 1: for Just go to iHeartRadio or wherever you listen to

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Speaker 1: podcast search for Dan o'donald's show and give us a like,

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Speaker 1: give us a thumbs up, a heart poop emoji. I

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Speaker 1: don't know, follow us, like us, subscribe to us wherever

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Speaker 1: you listen to podcasts coming up in the four o'clock hour,

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Speaker 1: big meeting between President Trump and of all people, New

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Speaker 1: York mayor zoron Mom Donnie. We will get into that

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Speaker 1: in the daily Trump Day, coming up right at the

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Speaker 1: start of the four o'clock hour. Of course, in the

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Speaker 1: five o'clock hour, we look back at the strangest stories

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Speaker 1: of the past seven days in how bizarre. But the

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Speaker 1: strangest thing that might be going on right now involving

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Speaker 1: young people is the fact that, for the first time,

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Speaker 1: I think, perhaps ever, women have a far less interest

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Speaker 1: in getting married than men do. It is, I believe,

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Speaker 1: part and parcel of a growing gender divide between young

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Speaker 1: men and young women that has a component of politics

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Speaker 1: to it. Yes, women are far more liberal than they

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Speaker 1: ever have been, while young men are far more conservative.

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Speaker 1: But that actually is just part of what I believe

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Speaker 1: to be the broader issue, and that is that young

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Speaker 1: men and young women are simply culturally misaligned. They have

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Speaker 1: different values, they have different worldviews, they have different psychological profiles.

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Speaker 1: They are just different. Forget about men are from Mars,

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Speaker 1: women are from Venus. Men are from this solar system,

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Speaker 1: and women are from something about fifteen light years away.

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Speaker 1: Young women also appear to have a very severe mental

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Speaker 1: health crisis that does not present itself in anywhere near

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Speaker 1: the numbers in other demographics of women or any demographic

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Speaker 1: of men. And I do believe that, yes, young women

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Speaker 1: becoming more liberal perhaps than they ever have been before,

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Speaker 1: has a big reason. That's a big reason for that.

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Speaker 1: So we will get into this a big discussion coming

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Speaker 1: up in the five o'clock hour. In the four o'clock hour,

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Speaker 1: a somber anniversary, the fourth anniversary since the Waukeshaw Parade massacre.

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Speaker 1: Have we learned absolutely nothing from that horrific tragedy? Sadly,

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Speaker 1: it appears that we have not. When you have a

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Speaker 1: story that is dominating at least some headlines, of course,

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Speaker 1: not national news media headlines, but on Fox News and

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Speaker 1: talk radio in the conservative internet sphere, A suspect with

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Speaker 1: forty nine prior arrests set a woman on fire on

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Speaker 1: the Chicago L train earlier this week. We'll dive into

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Speaker 1: that and reflect on four years since the Waukeshaw Parade massacre. However,

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Speaker 1: Big Story Today is an exclusive Yesterday at the Wisconsin Capitol,

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Speaker 1: Ryan Clancy, Darren Madison, and Francesca hong All sponsored an

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Speaker 1: ICE verifire training session at the State Capitol. This took

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Speaker 1: place in the North Hearing Room around one two three pm.

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Speaker 1: We had a source inside that meeting. People discussed how

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Speaker 1: the ICE verifier system works, according to our source, how

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Speaker 1: it intends to identify when a potential ICE agent is

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Speaker 1: in the area, and how to alert the community and

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Speaker 1: to monitor and videotape the actions of ICE. Just so

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Speaker 1: we are all aware, alerting the community means alerting people

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Speaker 1: who are in the process of violating the law to

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Speaker 1: the presence of a law enforcement agent. Now, Clancy in

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Speaker 1: particular has been very vocal about the fact that this

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Speaker 1: in no way violates any laws, but it actually does.

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Speaker 1: In just a second, I will explain to you exactly

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Speaker 1: what laws, both state and federal, that it does in

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Speaker 1: fact violate. This event was in fact open to the public.

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Speaker 1: They didn't prevent anyone from coming to the event. A

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Speaker 1: number of news media representatives were there, according to the organizers,

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Speaker 1: and this is a Vosas de la Frontera presentation. It

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Speaker 1: is called the Community Defense Network, which describes itself as

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Speaker 1: a collective of community members committed to protecting and defending

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Speaker 1: Wisconsin's immigrant community from ICE activity. The network operates through

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Speaker 1: dedicated area groups that offer rapid response, support and solidarity.

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Speaker 1: And of course there is the logo right there on

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Speaker 1: the flyer that they were handed out for Bosas de

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Speaker 1: la Fronterra and comy te sin Frontiras, which does not,

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Speaker 1: as it sounds, translate to commit sin, although it does

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Speaker 1: seem like they're doing a lot of that now. According

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Speaker 1: to the organizers, our source said, they currently have one

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Speaker 1: hundred and seventy nine people primarily in Madison and Milwaukee,

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Speaker 1: who are working as ICE verifiers. Now what do they do?

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Speaker 1: What do these verifiers do? Well, that was the whole

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Speaker 1: purpose of this training. They respond to coles that go

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Speaker 1: into a hotline telling them that hey, ICE might be

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Speaker 1: in this neighborhood. ICE might be in this area, we

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Speaker 1: might have ICE operations targeting a particular person. They will

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Speaker 1: take that tip and then they will physically go to

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Speaker 1: the location to try to see if there are ICE

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Speaker 1: agents there, and then they essentially do whatever they can

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Speaker 1: to warn as many people who might be the targets

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Speaker 1: of the ICE action, whether it's a deportation rate, whether

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Speaker 1: it is a targeted enforcement action against a criminal illegal

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Speaker 1: alien The whole point of ice verification is to warn people,

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Speaker 1: many of whom have been previously deported, many of whom

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Speaker 1: have committed serious crimes, that someone is coming to take

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Speaker 1: them away. Now, I have long used the analogy of

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Speaker 1: this radio show. When we're actually able to get on

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Speaker 1: the air. It is the biggest radio show, biggest conservative

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Speaker 1: talk radio show, and I believe the biggest talk radio

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Speaker 1: show in the state. We have a massive megaphone inultiple

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Speaker 1: media markets across Wisconsin. Imagine if I was using that

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Speaker 1: to tell people that, because I'm not a fan of,

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Speaker 1: say the Madison Police Department, and I have sources within

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Speaker 1: the department, we'll say, Okay, they're acting on these warrants today.

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Speaker 1: All right, here is an operation to target John Smith,

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Speaker 1: who's living in an apartment on State Street. If I

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Speaker 1: were to use my radio show to say, attention, John Smith,

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Speaker 1: we have reason to believe that the Madison Police Department

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Speaker 1: is coming to enforce an arrest warrant against you, that

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Speaker 1: would rather obviously be obstruction of justice. Because I am

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Speaker 1: willfully interfering in the lawful operation of law enforcement who

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Speaker 1: is conducting a lawful arrest of John Smith. I would

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Speaker 1: actually be aiding and abetting Smith, I would actually be

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Speaker 1: helping him evade law enforcement. I would love to get

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Speaker 1: an explanation as to how what the ice verifier program

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Speaker 1: is doing is any different whatsoever. According to our source,

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Speaker 1: the organizers of this event, and to be clear, Clancy

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Speaker 1: seemed to be mostly just a sponsor. It is this

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Speaker 1: Community Defense network that actually put this on. But Ryan

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Speaker 1: Clancy was the one who secured the room. He and

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Speaker 1: Darren Madison, a fellow socialist, as well as Francesca Hong,

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Speaker 1: another socialist leftist who also happens to be running for governor.

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Speaker 1: They were the ones who were advertising this event. Clancy,

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Speaker 1: of course was taunting on social media saying thank you

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Speaker 1: to Comrade Dan O'Donnell because they were expecting a small

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Speaker 1: crowd and apparently because I have a again big microphone,

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Speaker 1: that this got a lot more people to this meeting

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Speaker 1: and there are going to be a lot more ice verifiers.

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Speaker 1: Well there are all so going to be a whole

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Speaker 1: lot more prank calls to your phone line, Ryan, because

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Speaker 1: we repeatedly gave it out and instructed people do not

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Speaker 1: prank the ice Verifyer hotline. Okay, it may be tempting

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Speaker 1: to send in false tips by calling one eight hundred

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Speaker 1: four to two seven zero two one three. But do

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Speaker 1: not do that, because this is a legitimate this is

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Speaker 1: a this is a good thing. They are definitely not

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Speaker 1: violating the law, and you definitely should not sound exactly

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Speaker 1: like a concerned resident with a legitimate tip that ice

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Speaker 1: is in a neighborhood, but send them to a random

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Speaker 1: neighborhood where ice definitely is that you should definitely not

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Speaker 1: do that and call one eight hundred four to two

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Speaker 1: seven zero two one three. So do not, under any

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Speaker 1: circumstances do that, because we would we would not hear

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Speaker 1: at the Dan O'Donnell show, want to obstruct the obstruction

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Speaker 1: of justice, you see, we want we want the ice

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Speaker 1: verification obstruction of justice to go on, and would we

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Speaker 1: would not want to obstruct that. But let's say a

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Speaker 1: bunch of my listeners did that and the ice verifiers

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Speaker 1: pitch to fit. I would simply say, look, I just

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Speaker 1: want to alert people in various neighborhoods to the presence

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Speaker 1: of ice verifiers, Like this is what was the old

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Speaker 1: Latin saying, who watches the watchmen? This is what we're doing. Okay,

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Speaker 1: So our source said they discussed the current landscape of

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Speaker 1: deportations and that sort of thing, how ICE operates, noting

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Speaker 1: that it'll frequently collaborate with local law enforcement and that

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Speaker 1: sort of thing. Then they got into what are the

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Speaker 1: qualifications for being an ICE verifier, as you could imagine

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Speaker 1: since most of the people who would sign up for

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Speaker 1: this are radical leftists. And I'm not going to say

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Speaker 1: being a radical leftist is synonymous with being a loser

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Speaker 1: who is not qualified to do anything. But I'm also

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Speaker 1: not not saying that qualifications. You need a car at

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Speaker 1: a flexible job so you can quickly respond to an

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Speaker 1: incident when one arises, and be able to quickly leave

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Speaker 1: work and travel to the location in question. For example,

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Speaker 1: while we were unable to connect to our in studio

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Speaker 1: system for broadcasting a radio show, I could have been

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Speaker 1: out verifying if ICE was in a neighborhood. Being bilingual,

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Speaker 1: They said, is is helpful, but it's not required. This

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Speaker 1: is fascinating, and this just gives you a little insight

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Speaker 1: into the worldview of the radical leftist in the role

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Speaker 1: of a verifier. Our source noted, it is more helpful

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Speaker 1: to be of a certain race or language so you

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Speaker 1: can use your privilege and be present and interact with

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Speaker 1: ICE agents. What they're saying here is it's actually better

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Speaker 1: if we have a bunch of white people because we

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Speaker 1: just presume that they're going to be able to better

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Speaker 1: interact with law enforcement because law enforcement is naturally so

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Speaker 1: racist that if they see a black or brown person,

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Speaker 1: they're probably just going to start beating them with a

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Speaker 1: billy club or worse. So, how exactly does this system work?

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Speaker 1: If someone suspects that an ICE agent is staked out

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Speaker 1: at a location, so this is just like you know,

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Speaker 1: you've seen any number of cop shows. Typically what happens

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Speaker 1: is an ICE agent will wait until they are in

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Speaker 1: a public location so that what they want to do

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Speaker 1: is reduce the opportunity for someone to run, for someone

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Speaker 1: to resist, for someone to get violent, for a crowd

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Speaker 1: of people like these idiot ICE verifiers to interfere. This

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Speaker 1: is why courtrooms are so popular, because they know exactly

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Speaker 1: where a criminal suspect is going to be, and when

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Speaker 1: it's a public area, there's not an opportunity. They know

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Speaker 1: the person isn't going to be armed because they have

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Speaker 1: to go through the metal detector. It's just a good place,

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Speaker 1: so they will wait until the person is about to

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Speaker 1: walk into work, or maybe they're walking out of work.

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Speaker 1: They present the warrant, they take the person into custody,

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Speaker 1: and they get through to the deportation system. So when

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Speaker 1: someone suspects an ICE agent is staking out of place, Now,

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Speaker 1: imagine if I saw a bunch of cop cars outside

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Speaker 1: of a suspected drug den. We're in inner city Milwaukee,

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Speaker 1: and I happen to be driving totally not to buy

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Speaker 1: drugs from that drug den. I'm just passing through, and

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Speaker 1: I see all these police officers line up. They're obviously

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Speaker 1: ready to go in. Right If I called in to say, hey,

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Speaker 1: they're staking out this known drug den and all of

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Speaker 1: the people in the drug den were able to escape

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Speaker 1: out the back door, would I be party to the

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Speaker 1: crime of them escaping. Yes, I would. Why because I

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Speaker 1: aided and abetted their escape by letting them know that

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Speaker 1: a bunch of law enforcement officers are outside. Why do

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Speaker 1: the rules suddenly change when it's an ice agent. So

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Speaker 1: someone suspects that there's ice outside, they called the Verifier

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Speaker 1: hotline at one eight hundred and four to two seven

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Speaker 1: zero two one three and again on a Friday afternoon.

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Speaker 1: A lot of you I know are already offer or

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Speaker 1: you're going to be off very soon for an entire

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Speaker 1: week for the Thanksgiving holiday. I'm very jealous of you.

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Speaker 1: I am not. I'm going to be working next Monday, Tuesday, Wednesday.

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Speaker 1: But if you're already off, if you're are you got

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Speaker 1: a few cocktails in you. You definitely should not send

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Speaker 1: those poor ICE verifiers to the farthest reaches of Milwaukee

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Speaker 1: County just because well, you want to mess with them.

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Speaker 1: That's definitely something you should not do. The person who

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Speaker 1: calls the hotline gathers the details and reports suspicious cars.

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Speaker 1: Here's another thing that absolutely is illegal license plates, details

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Speaker 1: of what the agents look like, and they communicate that

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Speaker 1: information to a dispatcher. One of the big problems that

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Speaker 1: ICE has had, and one of the big reasons that

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Speaker 1: they wear masks is specifically because of things like this,

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Speaker 1: because they are getting docksed. You might recall a couple

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Speaker 1: of months ago, Democrats were trying to compile a face

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Speaker 1: and name database of all of the ICE agents who

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Speaker 1: were active in deporting people. Now, now, what purpose would

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Speaker 1: this serve? Why would you want a whole bunch of leftists?

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Speaker 1: Why would a whole bunch of leftists rather want to

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Speaker 1: compile a list of federal ICE agents. Could it be

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Speaker 1: because they wanted to figure out who they were and

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Speaker 1: get all of their personal information out there to make

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Speaker 1: their lives a living hell. That's exactly what they wanted.

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Speaker 1: So then the dispatcher who gets the hotline call decides

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Speaker 1: if the criteria to launch a response is met. So

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Speaker 1: if there's enough detail that the caller would be able

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Speaker 1: to provide that gets somebody to respond to it, they

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Speaker 1: go out. The dispatcher then decides which verifiers to send,

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Speaker 1: makes contact with potential responders. Verifiers indicate their eta how

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Speaker 1: long it'll take them to get there. Two nearby verifiers

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Speaker 1: are then sent to the scene to make contact with

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Speaker 1: the caller and verify the information of the hotline coal

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Speaker 1: and then investigate the situation. So what should verifiers do

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Speaker 1: on the scene. We will get into that coming up

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Speaker 1: in just a second when the Dan O'Donnell show hopefully returns.

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Speaker 1: I'm kidding, we'll be back in a second. I feel

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Speaker 1: like we should have played this after we just couldn't

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Speaker 1: connect to our computer system for a good fifteen minutes.

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Speaker 1: I'm going to read some of the best texts that

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Speaker 1: we got while we were down coming up after the

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Speaker 1: top of the hour. It is truly hysterically you folks,

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Speaker 1: are you truly have outdone yourselves in creativity? And yes,

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Speaker 1: I was very frustrated. I'm not going to let that

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Speaker 1: get me down. We do have a big exclusive story

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Speaker 1: a source inside the ICE verifier training session at the Capital.

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Speaker 1: We do have now a better understanding of how this

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Speaker 1: exactly works. And yes, I can now tell you with

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Speaker 1: absolute certainty that they are training people to obstruct investigations

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Speaker 1: into law enforcement. Here's how it works. So, once a

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Speaker 1: verifier is sent to the scene, they are instructed to

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Speaker 1: record everything they say. Use your camera and landscape mode

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Speaker 1: to get the widest possible view of the scene and

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Speaker 1: law enforcement entering the scene. Report any seemingly relevant data point.

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Speaker 1: When in doubt, report it, timestamp everything. Don't try to

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Speaker 1: be sneaky or hide what you are doing. This lets

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Speaker 1: ICE agents know they are being watched. If asked, identify

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Speaker 1: yourself by saying you are a community watcher. Remain silent

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Speaker 1: when asked questions, but remain present. Also, do not give

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Speaker 1: any false information to law enforcement or interfere You should

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Speaker 1: carry your ID with you, but you do not have

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Speaker 1: to show your ID. Ask questions to the potential law

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Speaker 1: enforcement agent. Ask for their badges and what they are doing, etc.

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Speaker 1: Report using the Signal app, which records videos and instantly

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Speaker 1: uploads them. The app does not save videos to the phone.

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Speaker 1: They say, always work in twos, so never work alone.

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Speaker 1: Do not be too far or near from your partner. Communicate.

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Speaker 1: Do not exit your vehicle until the other verifier arrives.

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Speaker 1: You have the right to be there and record video.

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Speaker 1: Don't let ice intimidate you into stopping your recording. Law

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Speaker 1: enforcement cannot confiscate your device without a warrant. Don't hide

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Speaker 1: the fact you are recording. Do not interfere with aun arrest.

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Speaker 1: Also on your phone, turn off unlock features such as

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Speaker 1: a hand swipe, a fingerprint, or facial recognition. Law enforcement

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Speaker 1: can compel you to swipe your finger to unlock a phone.

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Speaker 1: This will take that option away from them. All of

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Speaker 1: this is legal. The issue is the warning of potential target.

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Speaker 1: The organizers of this training session yesterday talked about the

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Speaker 1: difference between judicial warrants and administrative warrants. ICE cannot enter

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Speaker 1: a residence without a judicial warrant signed by a judge.

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Speaker 1: They say, Okay, Here is where things getly obstruction y.

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Speaker 1: If ICE is trying to get a home, trying to

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Speaker 1: get into a home with a potential illegal inside, verifiers

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Speaker 1: should try to shout to the illegal inside the residence.

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Speaker 1: And if Ice does not have a judicial warrant, they

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Speaker 1: should not have to open the door. That is classic

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Speaker 1: obstruction of justice. Hey, the cops are coming. The cops

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Speaker 1: are coming. Run get out of there. Someone please explain

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Speaker 1: to me how this Affirmative Act is not aiding and

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Speaker 1: abetting the escape of someone who is the subject of

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Speaker 1: a valid warrant. Here are all of the statutes that

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Speaker 1: this potentially violates. Wisconsin Statute nine thirty nine point five.

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Speaker 1: A person is concerned in the commission of the crime

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Speaker 1: if that person intentionally aids and abets the commission of it.

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Speaker 1: Here the crime would be trying to escape law enforcement.

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Speaker 1: Running away would be a form of obstruction of justice.

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Speaker 1: They are actively aiding and abetting the commission of running

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Speaker 1: away from a law enforcement Now, what exactly is aiding

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Speaker 1: and a betting? Well, this was defined in the state

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Speaker 1: in a nineteen seventy seven State Supreme Court case. Conduct

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Speaker 1: undertaken to intentionally aid another in the commission of a

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Speaker 1: crime that yields such assistance constitutes aiding and abetting the

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Speaker 1: crime of whatever it entails as a natural consequence. That means,

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Speaker 1: if you help a criminal illegal alien escape from ICE,

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Speaker 1: that is aiding at a betting now what crime? You

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Speaker 1: might be saying, well, Dan, what if? What if? This

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Speaker 1: is not a criminal illegal? This is someone with a

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Speaker 1: deportation order. Someone with a valid deportation order is someone

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Speaker 1: who undoubtedly has come into this country and been deported

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Speaker 1: before we know they're back in the crime. Remember, every

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Speaker 1: single person who has come into this country illegally has

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Speaker 1: in fact committed a federal crime violation of eight US

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Speaker 1: Code thirteen twenty five improper entry by an alien. You

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Speaker 1: could make the case that regardless of whether the person

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Speaker 1: is a criminal illegal. And remember most in fact, almost

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Speaker 1: all of the people who are being targeted in these

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Speaker 1: ICE deportation rates are criminals. They are people who have

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Speaker 1: come into this country illegally and also violated other laws.

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Speaker 1: Let's not pretend that the great fiction is that illegal

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Speaker 1: aliens commit a crimes at at far lower rates than

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Speaker 1: native born citizens. They commit crimes at a one hundred

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Speaker 1: percent rate. Every single person who has coming to this

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Speaker 1: country illegally has violated eight US Code thirteen twenty five. Now,

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Speaker 1: it is very likely that much of what the ICE

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Speaker 1: verifiers are doing is in violation of eighteen US Code,

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Speaker 1: Section one eighteen interference with certain protective functions. Now, I

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Speaker 1: want you to listen to the elements of this crime.

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Speaker 1: This is directly from federal statute. I want you to

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Speaker 1: listen very very carefully, and tell me does this sound

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Speaker 1: like what it is the ICE verifiers are doing. The

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Speaker 1: whole goal is to protect people from ICE right, to

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Speaker 1: shield them from deportation, or to shield them from ICE

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Speaker 1: agents coming in to take them into custody. Any person

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Speaker 1: who knowingly and willfully obstructs, resists, or interferes with a

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Speaker 1: federal law enforcement agent engaged within the United States or

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Speaker 1: the special marritime territorial jurisdiction of the United States in

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Speaker 1: the performance of the proactive functions authorized under various other

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Speaker 1: parts of federal law shall be fined under this title,

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Speaker 1: imprisoned not more than one year, or both. Are ICE

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Speaker 1: verifiers knowingly interfering with a federal law enforcement agent who

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Speaker 1: is engaged in the performance of a protected function protective

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Speaker 1: function listed under Federal statute. Are ICE agents legally authorized

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Speaker 1: to do what it is they are doing in Wisconsin's communities?

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Speaker 1: Are they legally authorized to take people who have come

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Speaker 1: into this country illegally into custody and get them started

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Speaker 1: on the road to deportation. You'd better believe that they

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Speaker 1: are is alerting an illegal alien to the presence of ICE,

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Speaker 1: saying hey, hey, hey, Ice is common, ICE is coming.

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Speaker 1: It's sort of like do you remember watching the wire

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Speaker 1: when Omar would show up. He's whistling the farmer in

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Speaker 1: the dell, and everybody would yell, Omar coming, Omar coming.

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Speaker 1: That's what these people are doing. You have state representatives

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Speaker 1: telling people, go and violate federal law, go and violate

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Speaker 1: state law. The law doesn't apply because we really, you

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Speaker 1: really don't like ICE, because we don't like this federal agency.

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Speaker 1: It is perfectly appropriate for you to interfere with what

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Speaker 1: it is they're doing. Only a liberal, I think could

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Speaker 1: could understand that. So if if I don't like, I

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Speaker 1: don't particularly care for I don't know if you noted.

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Speaker 1: If you if you folks notice this by listening to

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Speaker 1: me on the radio or watching our live stream for

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Speaker 1: many many years, I don't much care for Governor Tony Evers,

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Speaker 1: I know, guilty as charged. I don't much care for

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Speaker 1: Attorney General Josh Cole. I know, I know, I try

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Speaker 1: to hide my opinions on this show like a shrinking flower.

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Speaker 1: Does that authorize me to interfere with Josh Cole's Department

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Speaker 1: of Justice criminal investigations? Well, I don't think. I don't

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Speaker 1: think Josh Caaull is a legitimate Attorney general. Imagine if

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Speaker 1: my defense was well in twenty twenty two, I thought

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Speaker 1: there was so much voter fraud that Josh Call and

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Speaker 1: Tony Evers didn't actually win. I believe that Ebs is

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Speaker 1: an illegitimate governor. I believe that Paul is an illegitimate

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Speaker 1: Attorney General, and as a result, all of the investigations

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Speaker 1: into whatever it is, whatever violation of state statute that

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Speaker 1: they authorize, is therefore null invoid in my opinion, in

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Speaker 1: the Gospel, according to in the Book of Law of

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Speaker 1: Dan O'Donnell, would I be able to come here on

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Speaker 1: the radio and say, all right, folks, here's what I

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Speaker 1: want my members of Dan nation to be doing. I

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Speaker 1: want you to wherever you find a Division of Criminal

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Speaker 1: Investigation agent, whatever they're doing, I want you to report them.

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Speaker 1: I want you to make a scene. I want you

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Speaker 1: to actually shout in to a house, hey, drug dealer,

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Speaker 1: the fuzz is coming. If I was telling you to

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Speaker 1: do that, if I was actually using state resources to

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Speaker 1: do that, you would think, hey, wow, that is wildly inappropriate. Dan.

431
00:30:20,920 --> 00:30:24,120
Speaker 1: Just because you don't like Tony Evers and Josh Call

432
00:30:24,560 --> 00:30:28,440
Speaker 1: that doesn't give you the right to interfere in the

433
00:30:28,480 --> 00:30:34,920
Speaker 1: investigations that they launch. Yes, dear listener, you are exactly correct.

434
00:30:35,600 --> 00:30:43,240
Speaker 1: It does not. Folks, I am very worried that the

435
00:30:43,440 --> 00:30:48,640
Speaker 1: ice verifier program is going to lead to some sort

436
00:30:48,880 --> 00:30:54,680
Speaker 1: of dangerous confrontation with law enforcement, That someone who signs

437
00:30:54,760 --> 00:30:57,800
Speaker 1: up for this program, who is a hothead, who is

438
00:30:57,880 --> 00:31:03,640
Speaker 1: a radical anti police, last leftist, is going to do

439
00:31:03,840 --> 00:31:07,080
Speaker 1: something and there is going to be some sort of

440
00:31:07,120 --> 00:31:10,160
Speaker 1: act of violence, either an act of violence the leftist

441
00:31:10,280 --> 00:31:14,040
Speaker 1: on the law enforcement officer. The law enforcement officer unfortunately

442
00:31:14,080 --> 00:31:19,320
Speaker 1: use deadly force. This just has all manner of bad

443
00:31:20,240 --> 00:31:23,160
Speaker 1: attached to it. I am just it. It does not

444
00:31:23,360 --> 00:31:27,840
Speaker 1: sound in a sane world, A this would not happen.

445
00:31:28,640 --> 00:31:32,280
Speaker 1: B we would have tons of people who are definitely

446
00:31:32,400 --> 00:31:36,200
Speaker 1: not going to spend all weekend, calling up one eight

447
00:31:36,320 --> 00:31:39,880
Speaker 1: hundred four to two seven zero two one three and

448
00:31:39,960 --> 00:31:43,080
Speaker 1: giving them false tips that that definitely should not happen.

449
00:31:44,520 --> 00:31:48,640
Speaker 1: But in a sane world, we would not have representatives

450
00:31:48,840 --> 00:31:55,040
Speaker 1: of Wisconsin's government using Wisconsin's House, the building in which

451
00:31:55,120 --> 00:32:00,000
Speaker 1: laws are written, conducting a training in which people are

452
00:32:00,080 --> 00:32:02,400
Speaker 1: tool to break the law. All right, Daily Trump Date

453
00:32:02,440 --> 00:32:04,680
Speaker 1: and much more coming up after the top of the

454
00:32:04,680 --> 00:32:07,920
Speaker 1: hour news. You know, ladies and gentlemen, I am never

455
00:32:08,040 --> 00:32:12,560
Speaker 1: again going to take for granted just being able to

456
00:32:12,600 --> 00:32:16,160
Speaker 1: turn on the microphone and talk over my opening theme

457
00:32:16,240 --> 00:32:20,680
Speaker 1: song after last hour, for those of you listening, we

458
00:32:20,920 --> 00:32:25,920
Speaker 1: had some major technical difficulties. I'm not going to bore

459
00:32:25,960 --> 00:32:29,800
Speaker 1: you with the details, but suffice it to say it

460
00:32:30,040 --> 00:32:34,080
Speaker 1: was a bit of an oversight somewhere along the line

461
00:32:34,280 --> 00:32:38,160
Speaker 1: in what actually builds what are known as the logs

462
00:32:38,320 --> 00:32:42,000
Speaker 1: for a given program, the commercials, all of the elements

463
00:32:42,000 --> 00:32:44,680
Speaker 1: of the show, that sort of thing which sort of

464
00:32:44,720 --> 00:32:48,720
Speaker 1: turned into a major problem. It is not lost on me, folks,

465
00:32:49,040 --> 00:32:54,280
Speaker 1: that this happened on the Friday before the Thanksgiving holiday.

466
00:32:54,360 --> 00:32:57,120
Speaker 1: A whole lot of people are taking off for the

467
00:32:57,200 --> 00:33:01,480
Speaker 1: long weekend. My kids for the first time, I think

468
00:33:01,520 --> 00:33:04,720
Speaker 1: I can remember Producer Jeff, and I do need to

469
00:33:04,760 --> 00:33:09,440
Speaker 1: point out poor producer Jeff. This is his last day

470
00:33:09,480 --> 00:33:12,400
Speaker 1: with us, and on his last day when we you know,

471
00:33:12,680 --> 00:33:16,200
Speaker 1: we're just gonna have a fun, you know, easygoing day,

472
00:33:16,600 --> 00:33:19,440
Speaker 1: we by the way, are going to miss him incredibly.

473
00:33:19,680 --> 00:33:23,680
Speaker 1: He is such an incredible addition to the Dan O'Donnell Show,

474
00:33:24,160 --> 00:33:28,600
Speaker 1: and he just is is always fun. He is always upbeat,

475
00:33:29,000 --> 00:33:32,240
Speaker 1: he is always smoking cigarettes outside and I have a

476
00:33:32,280 --> 00:33:35,800
Speaker 1: great time talking with him. But his last day, we

477
00:33:35,880 --> 00:33:39,960
Speaker 1: have a massive crisis of Like I mean, there's very

478
00:33:40,000 --> 00:33:43,240
Speaker 1: little you can do to like in radio, you can't

479
00:33:43,280 --> 00:33:45,240
Speaker 1: screw up a whole lot. The one thing you need

480
00:33:45,280 --> 00:33:47,320
Speaker 1: to be able to do is to actually go on

481
00:33:47,480 --> 00:33:50,080
Speaker 1: and talk on the radio. And when that doesn't happen,

482
00:33:50,840 --> 00:33:55,080
Speaker 1: it's like a category five hurricanes. So we're sending him

483
00:33:55,120 --> 00:33:59,280
Speaker 1: off with a bang today. But while we were off,

484
00:34:00,880 --> 00:34:03,240
Speaker 1: as you can imagine, a whole ton of our listeners,

485
00:34:03,280 --> 00:34:07,480
Speaker 1: who we affectionately know as Dan Nation, they sent in

486
00:34:09,920 --> 00:34:14,080
Speaker 1: theories as to what was going on. Here are some

487
00:34:14,160 --> 00:34:19,560
Speaker 1: of the most common ones we got. Did Dan die?

488
00:34:20,200 --> 00:34:23,200
Speaker 1: Apparently a whole lot of people believed that I just

489
00:34:23,920 --> 00:34:26,880
Speaker 1: died on my way from my office to the studio.

490
00:34:27,400 --> 00:34:31,239
Speaker 1: Did Dan take off for Thanksgiving early and not tell anybody?

491
00:34:31,280 --> 00:34:34,680
Speaker 1: That was also a popular theory. Did Dan lose his

492
00:34:34,800 --> 00:34:37,800
Speaker 1: headphones again? Or is this a bit? A lot of

493
00:34:37,840 --> 00:34:41,920
Speaker 1: people thought this was a bit. No, I hope I

494
00:34:41,960 --> 00:34:45,080
Speaker 1: know a little bit about comedic timing that went on

495
00:34:45,160 --> 00:34:48,319
Speaker 1: way too. That was like an Andy Kaufman esque bit,

496
00:34:48,640 --> 00:34:53,480
Speaker 1: if it was a bit. The second most popular theory

497
00:34:53,520 --> 00:34:56,560
Speaker 1: as to what was going on? Did Dan have a

498
00:34:56,680 --> 00:35:04,120
Speaker 1: stroke too? Did Dan, like Mark Belling, have a stroke? Now?

499
00:35:05,400 --> 00:35:07,600
Speaker 1: A lot of people because Mark came on the air

500
00:35:07,840 --> 00:35:11,520
Speaker 1: right after his recovery and said exactly what happened. He

501
00:35:12,000 --> 00:35:15,680
Speaker 1: actually did have a stroke while he was in his

502
00:35:15,800 --> 00:35:20,319
Speaker 1: office and doing a show. It's a miracle that the

503
00:35:20,360 --> 00:35:23,120
Speaker 1: man was able to broadcast again and do a radio

504
00:35:23,200 --> 00:35:26,520
Speaker 1: show for another what six years? Five six years. He's

505
00:35:26,520 --> 00:35:30,920
Speaker 1: now doing, of course, the very successful Mark Belling podcast.

506
00:35:31,320 --> 00:35:34,319
Speaker 1: And people have been asking me before we get into

507
00:35:34,400 --> 00:35:38,560
Speaker 1: the by far number one theory that people had as

508
00:35:38,560 --> 00:35:41,000
Speaker 1: to what was going on last hour, people have been

509
00:35:41,040 --> 00:35:45,200
Speaker 1: asking me all week, Dan, are you going to continue

510
00:35:45,239 --> 00:35:50,000
Speaker 1: the tradition that Belling had on this the Friday before

511
00:35:50,360 --> 00:35:54,320
Speaker 1: Wisconsin's gun deer season opens are you going to play

512
00:35:54,760 --> 00:36:03,239
Speaker 1: the stupid deer camp song? Folks? Folks, I am far

513
00:36:03,440 --> 00:36:08,960
Speaker 1: too how shall I put this cultured? I am far

514
00:36:09,160 --> 00:36:16,120
Speaker 1: too learned. I am far too sophisticated to do that

515
00:36:16,280 --> 00:36:20,400
Speaker 1: sort of thing. By the Unbelling didn't even like playing it.

516
00:36:20,560 --> 00:36:24,640
Speaker 1: So I think there is your answer, and you're definitely

517
00:36:24,640 --> 00:36:27,560
Speaker 1: going to want to listen until the end of the

518
00:36:27,680 --> 00:36:32,200
Speaker 1: show for proof that we are absolutely not going to

519
00:36:32,200 --> 00:36:35,359
Speaker 1: engage in this. So this the number one theory that

520
00:36:35,440 --> 00:36:39,560
Speaker 1: our listeners had as to where I was while we

521
00:36:39,760 --> 00:36:43,880
Speaker 1: just kept replaying the opening theme song. It was some

522
00:36:44,160 --> 00:36:52,160
Speaker 1: variation of is Dan pooping? Does Dan have explosive diarrhea?

523
00:36:52,480 --> 00:36:56,200
Speaker 1: Is Dan constipated in the men's room stall? Folks. I

524
00:36:56,239 --> 00:37:01,640
Speaker 1: cannot express how much I appreciate your concern for my

525
00:37:01,880 --> 00:37:02,840
Speaker 1: bowel health.

526
00:37:03,960 --> 00:37:06,600
Speaker 2: We're gonna win so much you may even get.

527
00:37:06,440 --> 00:37:09,279
Speaker 1: Tired of Winningum just keeps winning. It is a win

528
00:37:09,480 --> 00:37:13,000
Speaker 1: for the administration. It's also a big win for the

529
00:37:13,080 --> 00:37:15,680
Speaker 1: United States. We have to keep winning. We have to

530
00:37:15,719 --> 00:37:19,920
Speaker 1: win more. We're gonna win Moore. President Trump spent his

531
00:37:20,239 --> 00:37:22,880
Speaker 1: afternoon as we get to the Daily Trump date, He

532
00:37:22,960 --> 00:37:27,319
Speaker 1: spent his afternoon with New York City Mayor zorn Mom Donnie. Now,

533
00:37:27,680 --> 00:37:33,759
Speaker 1: despite their incredible difference on policy and the fact that

534
00:37:33,880 --> 00:37:38,400
Speaker 1: neither men appeared to particularly like the other, the two

535
00:37:38,480 --> 00:37:43,200
Speaker 1: had a very productive meeting Before it. President Trump outlined

536
00:37:43,239 --> 00:37:46,440
Speaker 1: his expectations in a radio interview on the Brian Kilmead

537
00:37:46,520 --> 00:37:48,080
Speaker 1: Show on Fox Radio this morning.

538
00:37:48,160 --> 00:37:49,120
Speaker 3: Well, I don't really know.

539
00:37:49,239 --> 00:37:52,040
Speaker 2: He's got a different philosophy. He's a little bit different.

540
00:37:53,239 --> 00:37:54,719
Speaker 2: I give him a lot of credit for the run.

541
00:37:54,800 --> 00:37:56,960
Speaker 2: They did a successful run, and we all know that

542
00:37:57,200 --> 00:38:00,000
Speaker 2: runs are not easy. But I think we'll get along.

543
00:38:00,080 --> 00:38:02,040
Speaker 2: And we're looking for the same thing. We want to

544
00:38:02,080 --> 00:38:05,160
Speaker 2: make New York strong. And you know, there's such a

545
00:38:05,200 --> 00:38:08,759
Speaker 2: different philosophy. But I'll let you know. I'll let you

546
00:38:08,800 --> 00:38:10,040
Speaker 2: know over the next year. Brian.

547
00:38:10,160 --> 00:38:15,280
Speaker 1: Okay, the meeting was very cordial, and the two actually,

548
00:38:15,320 --> 00:38:19,120
Speaker 1: with President Trump sitting behind the resolute desk in the

549
00:38:19,120 --> 00:38:22,719
Speaker 1: Oval Office and Mondannie standing just behind them, appeared to

550
00:38:22,760 --> 00:38:26,160
Speaker 1: actually really get along. And this is something that I

551
00:38:26,160 --> 00:38:29,479
Speaker 1: have heard from so many people who don't particularly care

552
00:38:29,640 --> 00:38:33,839
Speaker 1: for Trump. Bill Maht has realized this that he is

553
00:38:33,880 --> 00:38:39,160
Speaker 1: an incredibly charming guy and that in person, he listens,

554
00:38:39,520 --> 00:38:46,040
Speaker 1: he offers constructive and appropriate and incisive responses to what

555
00:38:46,200 --> 00:38:50,480
Speaker 1: it is that is said to him. In short, he is,

556
00:38:50,560 --> 00:38:54,160
Speaker 1: and I hope Mandanni learned this today, nothing like the

557
00:38:54,239 --> 00:38:58,560
Speaker 1: caricature of him that liberals have created. It is Thanksgiving

558
00:38:58,880 --> 00:39:03,080
Speaker 1: next week, and White House Press Secretary Caroline Levitt made

559
00:39:03,120 --> 00:39:07,360
Speaker 1: sure to tell America just what the Trump administration is

560
00:39:07,360 --> 00:39:10,200
Speaker 1: doing and has done to make Thanksgiving travel and the

561
00:39:10,520 --> 00:39:13,759
Speaker 1: annual Thanksgiving Turkey dinner more affordable this year.

562
00:39:13,800 --> 00:39:17,839
Speaker 4: President Trump's policies are working to make Americans Thanksgiving more

563
00:39:17,880 --> 00:39:21,120
Speaker 4: affordable this year, from their commute to the dinner table.

564
00:39:21,480 --> 00:39:24,759
Speaker 4: Nearly one hundred million Americans are expected to drive next

565
00:39:24,760 --> 00:39:27,480
Speaker 4: week to spend time with loved ones for the holiday,

566
00:39:27,920 --> 00:39:30,960
Speaker 4: and thanks to President Trump's Drill Baby Drill agenda, the

567
00:39:31,080 --> 00:39:34,160
Speaker 4: national average price of a gallon of gas on Thanksgiving

568
00:39:34,239 --> 00:39:37,680
Speaker 4: Day is projected to be at the cheapest price since

569
00:39:37,719 --> 00:39:41,360
Speaker 4: the COVID pandemic in twenty twenty one. President Trump is

570
00:39:41,400 --> 00:39:45,280
Speaker 4: bringing down gas prices and providing significant savings to American

571
00:39:45,320 --> 00:39:48,560
Speaker 4: families at the pump, and again, we expect those prices

572
00:39:48,600 --> 00:39:52,560
Speaker 4: to continue to decline. According to the American Farm Bureau

573
00:39:52,640 --> 00:39:57,000
Speaker 4: Federation's annual survey, Cooking Thanksgiving Dinner will also cost less

574
00:39:57,080 --> 00:39:59,680
Speaker 4: this year than it did last year and is down

575
00:39:59,680 --> 00:40:04,359
Speaker 4: about overall. The average price for a staple of the meal,

576
00:40:04,560 --> 00:40:08,320
Speaker 4: a sixteen pound frozen turkey, is down more than sixteen

577
00:40:08,360 --> 00:40:11,880
Speaker 4: percent from last year, which will provide critical savings for

578
00:40:12,000 --> 00:40:13,480
Speaker 4: families and their budgets.

579
00:40:14,000 --> 00:40:16,600
Speaker 1: We'll get into this in a little bit greater depth

580
00:40:16,600 --> 00:40:20,279
Speaker 1: than in just a second. It is very difficult to

581
00:40:20,560 --> 00:40:25,720
Speaker 1: get prices down. You need a demand shock, which usually

582
00:40:25,719 --> 00:40:28,279
Speaker 1: comes in the form of a recession where people just

583
00:40:28,360 --> 00:40:32,080
Speaker 1: no longer want goods or services at a given price.

584
00:40:32,320 --> 00:40:35,160
Speaker 1: So what you can do, and what President Trump is

585
00:40:35,320 --> 00:40:39,560
Speaker 1: smart to have done, is to aggressively open up once

586
00:40:39,600 --> 00:40:46,200
Speaker 1: again America's domestic energy industry exploration, drilling, new oil leases.

587
00:40:46,360 --> 00:40:50,759
Speaker 1: Because one of the biggest drivers of costs for production

588
00:40:51,280 --> 00:40:55,080
Speaker 1: in the producer's price index is the cost of diesel fuel.

589
00:40:55,239 --> 00:40:58,439
Speaker 1: So the more you can get the cost of energy down,

590
00:40:58,440 --> 00:41:02,120
Speaker 1: and of course every company has to to provide utilities,

591
00:41:02,160 --> 00:41:04,440
Speaker 1: they have to keep the lights on, literally, so the

592
00:41:04,840 --> 00:41:08,720
Speaker 1: more you can work to get those prices down, the better.

593
00:41:09,440 --> 00:41:13,520
Speaker 1: Big big news coming with a new release from Bureau

594
00:41:13,680 --> 00:41:19,080
Speaker 1: of Labor Statistics data Preliminary data analyzed by the Center

595
00:41:19,239 --> 00:41:23,920
Speaker 1: for Immigration Studies Director of Research Stephen Camarata suggests that

596
00:41:24,080 --> 00:41:28,480
Speaker 1: in September, the sixteen year old and older foreign born

597
00:41:28,560 --> 00:41:35,520
Speaker 1: population declined by an additional one hundred one thousand. Camarata

598
00:41:35,880 --> 00:41:40,799
Speaker 1: suggests that given this data, the total foreign born population,

599
00:41:40,920 --> 00:41:45,399
Speaker 1: including those younger than sixteen years old, has declined by

600
00:41:45,640 --> 00:41:50,560
Speaker 1: two point three million just this year. Now, compare this

601
00:41:50,880 --> 00:41:55,000
Speaker 1: to the rapid mass migration ushered in under the Biden administration,

602
00:41:55,040 --> 00:41:59,800
Speaker 1: when the foreign born population grew by an unprecedented seven

603
00:42:00,080 --> 00:42:04,120
Speaker 1: point four million people from January twenty twenty one to

604
00:42:04,200 --> 00:42:08,000
Speaker 1: January twenty twenty five. Now at that point, a lot

605
00:42:08,040 --> 00:42:10,080
Speaker 1: of you are probably saying, well, Dad, I bet it's

606
00:42:10,120 --> 00:42:13,680
Speaker 1: way higher. Yeah, it probably is. That's the point. We

607
00:42:13,840 --> 00:42:18,200
Speaker 1: have no idea how many people came into this country

608
00:42:18,320 --> 00:42:21,720
Speaker 1: under the open bord and border policies of Joe Biden.

609
00:42:21,760 --> 00:42:24,560
Speaker 1: But what we do know is that a whole lot

610
00:42:24,600 --> 00:42:28,480
Speaker 1: of them are leaving, many of them voluntarily. They are

611
00:42:28,640 --> 00:42:32,560
Speaker 1: self deporting in just the first couple of months of

612
00:42:32,600 --> 00:42:37,239
Speaker 1: the Trump administration. In that interview with Brian Kilmead this

613
00:42:37,400 --> 00:42:40,920
Speaker 1: morning on Fox News Radio, Trump was of course asked

614
00:42:40,920 --> 00:42:46,440
Speaker 1: to respond to the latest controversy Dujoure that Democrats have

615
00:42:46,520 --> 00:42:50,640
Speaker 1: concocted this idea, that he was calling for the execution

616
00:42:51,080 --> 00:42:54,440
Speaker 1: of Democrats in the House and Senate who called on

617
00:42:54,520 --> 00:42:58,279
Speaker 1: members of the military to defy what are just going

618
00:42:58,320 --> 00:43:02,600
Speaker 1: to be presumed to be un constitutional illegal orders that Trump,

619
00:43:02,640 --> 00:43:04,000
Speaker 1: the commander in chief gives them.

620
00:43:04,120 --> 00:43:06,399
Speaker 2: Well, if you look at sedition, if you look at

621
00:43:07,160 --> 00:43:10,480
Speaker 2: you know that type of that's a form of a

622
00:43:10,600 --> 00:43:13,400
Speaker 2: very strong form of being a trader. It's a terrible

623
00:43:13,480 --> 00:43:15,960
Speaker 2: thing to say. I might tell you. I heard it,

624
00:43:16,640 --> 00:43:19,200
Speaker 2: and I thought it was some kind of a comedy situation.

625
00:43:19,320 --> 00:43:21,200
Speaker 2: I thought, there would you know, it was some kind

626
00:43:21,200 --> 00:43:25,160
Speaker 2: of a skit. And because I couldn't believe that they'd say,

627
00:43:25,239 --> 00:43:29,520
Speaker 2: and I watched Democrat congressman and one Democrat senator yesterday

628
00:43:29,600 --> 00:43:33,719
Speaker 2: in one of the shows. Didn't they want to discuss that?

629
00:43:33,760 --> 00:43:36,520
Speaker 2: They said, WHOA, don't get me into that one. They

630
00:43:36,560 --> 00:43:38,880
Speaker 2: didn't want to get into it. That is a really

631
00:43:38,960 --> 00:43:42,480
Speaker 2: serious charge. I'll tell you what what they said is.

632
00:43:42,880 --> 00:43:44,719
Speaker 2: And it was I mean, I don't know about the

633
00:43:44,760 --> 00:43:47,040
Speaker 2: modern day things, because you know, modern day is a

634
00:43:47,040 --> 00:43:49,719
Speaker 2: lot softer, but in the old days, if you said

635
00:43:49,760 --> 00:43:52,000
Speaker 2: a thing like that, that was punishable by them.

636
00:43:53,000 --> 00:43:55,120
Speaker 1: Yeah, but you're not saying you're not threatening them.

637
00:43:55,160 --> 00:43:57,040
Speaker 2: A lot of people are interpreting there's a threat in

638
00:43:57,040 --> 00:43:59,359
Speaker 2: the security. Right, I'm not threatening that, but I think

639
00:43:59,400 --> 00:44:02,400
Speaker 2: they're in serio trouble. I would say they're in serious trouble.

640
00:44:02,680 --> 00:44:06,000
Speaker 2: I'm not threatening death, but I think they're in serious trouble.

641
00:44:06,120 --> 00:44:07,000
Speaker 2: In the old days, it.

642
00:44:07,120 --> 00:44:11,080
Speaker 1: Was death, ladies and gentlemen. That is your daily look

643
00:44:11,120 --> 00:44:13,400
Speaker 1: at what's going on in Trump's Washington. We call it

644
00:44:13,600 --> 00:44:18,000
Speaker 1: the daily Trump Date. Speaking of Zoran, mom Donnie, I

645
00:44:18,000 --> 00:44:21,400
Speaker 1: wanted to get to this. Yesterday. In an interview with

646
00:44:21,600 --> 00:44:27,239
Speaker 1: a local New York television station, Mom Donnie sheepishly had

647
00:44:27,280 --> 00:44:31,319
Speaker 1: to admit that pretty much all of his most pie

648
00:44:31,480 --> 00:44:39,040
Speaker 1: in the sky policy proposals are already doa especially making

649
00:44:39,280 --> 00:44:40,880
Speaker 1: bus rides.

650
00:44:40,560 --> 00:44:42,600
Speaker 5: Free and the other one. You've been talking about fast

651
00:44:42,600 --> 00:44:44,359
Speaker 5: and free buses. And you're meeting with the governor. I've

652
00:44:44,360 --> 00:44:46,520
Speaker 5: heard you talk about many times that you don't want

653
00:44:46,520 --> 00:44:48,160
Speaker 5: to take money away from the MTA. You want to

654
00:44:48,160 --> 00:44:50,360
Speaker 5: put money back in. It's something that she agrees with, Right,

655
00:44:50,360 --> 00:44:52,200
Speaker 5: we don't want to takeway money from the MTA. How

656
00:44:52,200 --> 00:44:54,600
Speaker 5: are you getting that money? The seven hundred millions to

657
00:44:54,640 --> 00:44:57,160
Speaker 5: make the buses free into the MCA. If she's not

658
00:44:57,239 --> 00:44:58,719
Speaker 5: for raising taxes, you.

659
00:44:58,680 --> 00:45:01,200
Speaker 6: Know, I think that the too clear ways to raise

660
00:45:01,239 --> 00:45:03,400
Speaker 6: that money is through the raising of the state's corporate

661
00:45:03,400 --> 00:45:05,560
Speaker 6: tax to matchst in New Jersey. I think that a

662
00:45:05,560 --> 00:45:07,240
Speaker 6: lot of this is still a case to be made,

663
00:45:07,280 --> 00:45:09,239
Speaker 6: whether it's the corporate tax or that's the personal income

664
00:45:09,280 --> 00:45:10,960
Speaker 6: tax on those who make more than a million dollars

665
00:45:11,280 --> 00:45:13,520
Speaker 6: a year or more. I think that these are the

666
00:45:13,600 --> 00:45:16,160
Speaker 6: clearest ways. I've also said that there are other ways

667
00:45:16,200 --> 00:45:18,200
Speaker 6: to raise this funding. The most important fact is that

668
00:45:18,239 --> 00:45:20,400
Speaker 6: we fund it, not the question of how we do it,

669
00:45:20,400 --> 00:45:21,160
Speaker 6: but that we do it.

670
00:45:22,120 --> 00:45:25,239
Speaker 1: In other words, he has absolutely no idea how they

671
00:45:25,239 --> 00:45:29,160
Speaker 1: are going to make the buses free. He also, earlier

672
00:45:29,200 --> 00:45:32,000
Speaker 1: in the week was shut down on the idea of

673
00:45:32,200 --> 00:45:37,160
Speaker 1: increasing the number of rent controlled apartment buildings in New York.

674
00:45:37,520 --> 00:45:41,720
Speaker 1: In other words, the guy is going to succeed by failing.

675
00:45:42,040 --> 00:45:44,719
Speaker 1: If you follow me, that all of his most radical,

676
00:45:44,800 --> 00:45:49,279
Speaker 1: most devastating policy proposals are not going to be able

677
00:45:49,320 --> 00:45:52,880
Speaker 1: to be implemented because cooler heads in both the New

678
00:45:52,960 --> 00:45:56,239
Speaker 1: York Common Council and the state legislature, as well as

679
00:45:56,280 --> 00:45:59,319
Speaker 1: the governor's office as far left as Kathy Hochel is

680
00:45:59,680 --> 00:46:02,440
Speaker 1: and is disastrous and ruinous as she has been in

681
00:46:02,480 --> 00:46:05,440
Speaker 1: her short term as governor of the state. She even

682
00:46:05,520 --> 00:46:09,440
Speaker 1: recognizes that what mmdonni is proposing is ludicrous on his

683
00:46:09,640 --> 00:46:14,400
Speaker 1: face and will not allow it in any shape or fashion.

684
00:46:15,160 --> 00:46:18,440
Speaker 1: The issue that we face, though, is the more that

685
00:46:18,640 --> 00:46:22,680
Speaker 1: people realize that it is very, very difficult to get

686
00:46:22,680 --> 00:46:27,040
Speaker 1: prices down, that even the Trump administration, as big and

687
00:46:27,120 --> 00:46:31,040
Speaker 1: bold as it is and it has been on economic policy,

688
00:46:31,160 --> 00:46:37,640
Speaker 1: particularly with the tariff regime, reducing the cost of everything

689
00:46:38,719 --> 00:46:41,839
Speaker 1: is all but impossible. And the problem that people are

690
00:46:43,080 --> 00:46:47,520
Speaker 1: running into, and the problem politically for everybody who comes

691
00:46:47,560 --> 00:46:52,120
Speaker 1: after Joe Biden, everybody who succeeds him in politics, is

692
00:46:52,160 --> 00:46:57,040
Speaker 1: that his dramatic increase in government spending and direct stimulus

693
00:46:57,120 --> 00:47:01,920
Speaker 1: and intentional, I believe, screwing up of the supply chain

694
00:47:02,800 --> 00:47:07,040
Speaker 1: by just absolutely encouraging people to stay home on the

695
00:47:07,080 --> 00:47:11,239
Speaker 1: couch instead of when it was very clearly safe to

696
00:47:11,280 --> 00:47:14,640
Speaker 1: go back to work. With COVID nineteen abating and obviously

697
00:47:14,680 --> 00:47:22,040
Speaker 1: the vaccine which totally stopped the spread, what happened was

698
00:47:22,239 --> 00:47:26,680
Speaker 1: such a shock to the system that we're never going

699
00:47:26,719 --> 00:47:30,239
Speaker 1: to see prices decline again, and for those of us

700
00:47:30,239 --> 00:47:35,480
Speaker 1: of a certain age who remember what prices were pre

701
00:47:35,680 --> 00:47:38,600
Speaker 1: Joe Biden, not pre COVID, not pre COVID. In fact,

702
00:47:38,840 --> 00:47:43,280
Speaker 1: gas prices dramatically declined because there was such a dramatic

703
00:47:43,360 --> 00:47:49,320
Speaker 1: decrease in demand for gas during COVID nineteen, but because

704
00:47:49,360 --> 00:47:53,520
Speaker 1: of Joe Biden, because of Democrat policies. People remember what

705
00:47:53,600 --> 00:47:58,640
Speaker 1: they were paying for, say a hamburger at McDonald's. They

706
00:47:58,680 --> 00:48:03,560
Speaker 1: remember what they were paying for a saw at home depot.

707
00:48:04,040 --> 00:48:07,719
Speaker 1: They remember what things cost, and they compare not to

708
00:48:07,960 --> 00:48:11,719
Speaker 1: last year, when prices have indeed gone down on a

709
00:48:11,840 --> 00:48:15,080
Speaker 1: number of things, as Levitt said, the price of a turkey,

710
00:48:15,120 --> 00:48:18,160
Speaker 1: the price of gasoline is down, but people remember what

711
00:48:18,200 --> 00:48:22,520
Speaker 1: the price was before Joe Biden. And that's a big

712
00:48:22,560 --> 00:48:26,600
Speaker 1: problem because the only what folks prices are just never

713
00:48:26,680 --> 00:48:29,920
Speaker 1: going to go down to pre Biden levels. They just aren't.

714
00:48:30,600 --> 00:48:34,600
Speaker 1: We would need to have such a devastating recession that

715
00:48:34,640 --> 00:48:36,960
Speaker 1: it would make two thousand and eight look like a

716
00:48:36,960 --> 00:48:39,920
Speaker 1: blip on the radar. We would need to have great

717
00:48:40,080 --> 00:48:44,799
Speaker 1: depression level economic pullback, which I just don't think is

718
00:48:44,840 --> 00:48:50,400
Speaker 1: going to happen, especially with the earth changing technology of

719
00:48:50,520 --> 00:48:55,680
Speaker 1: artificial intelligence and intelligent robotics just on the horizon, I'll

720
00:48:55,800 --> 00:48:59,640
Speaker 1: already hear really but revolutionizing pretty much everything over the

721
00:48:59,680 --> 00:49:03,240
Speaker 1: next decade plus. I just don't think that's going to happen,

722
00:49:04,239 --> 00:49:08,160
Speaker 1: short of say, a nuclear strike in the heart of

723
00:49:08,200 --> 00:49:12,000
Speaker 1: the United States. Even then, I don't think we're going

724
00:49:12,040 --> 00:49:15,480
Speaker 1: to have the sort of economic recession that would be

725
00:49:15,560 --> 00:49:19,200
Speaker 1: necessary to cut demand to the point where prices go

726
00:49:19,360 --> 00:49:22,439
Speaker 1: down to pre Joe Biden levels. And that's a big

727
00:49:22,480 --> 00:49:25,800
Speaker 1: problem because now people are saying, well, why didn't Trump

728
00:49:25,840 --> 00:49:28,200
Speaker 1: do something? Why isn't Trump, Why aren't Trump and the

729
00:49:28,239 --> 00:49:34,920
Speaker 1: Republicans doing more to get those prices down? Well, there's really,

730
00:49:35,080 --> 00:49:39,680
Speaker 1: unfortunately not a whole lot that you can do. A

731
00:49:39,800 --> 00:49:45,560
Speaker 1: tragic anniversary today and proof that we've really learned nothing

732
00:49:45,920 --> 00:49:49,280
Speaker 1: from it. That's next here on the Dan o'donald Show.

733
00:49:49,320 --> 00:49:53,640
Speaker 1: You see, folks, as you heard during that get back

734
00:49:53,960 --> 00:49:58,280
Speaker 1: or Bumper music, you know, we think about the issues,

735
00:49:58,280 --> 00:50:01,919
Speaker 1: we do things. This is why I just I feel

736
00:50:01,920 --> 00:50:06,320
Speaker 1: like it's a new generation. I can't be playing something

737
00:50:06,400 --> 00:50:11,680
Speaker 1: like the second week of Dear Camp something, so just

738
00:50:12,040 --> 00:50:15,600
Speaker 1: you know, ya hey, Scani, I mean, yes, I was

739
00:50:15,640 --> 00:50:18,080
Speaker 1: born and raised here. No, I was never into hunting.

740
00:50:18,120 --> 00:50:20,640
Speaker 1: It was just never a thing in my family. But

741
00:50:20,800 --> 00:50:24,600
Speaker 1: I just I, you know, I would if you're wondering

742
00:50:24,640 --> 00:50:27,520
Speaker 1: about that, I would definitely listen at the end of

743
00:50:27,560 --> 00:50:30,919
Speaker 1: the show, just to verify that we are not going

744
00:50:30,960 --> 00:50:35,440
Speaker 1: to engage in such, you know, such buffoonery. That's just

745
00:50:35,560 --> 00:50:38,480
Speaker 1: not what we do here on the Dan O'Donnell Show.

746
00:50:40,320 --> 00:50:46,200
Speaker 1: Wink wink. We are also going to give a little

747
00:50:46,239 --> 00:50:50,560
Speaker 1: tribute to our very dear friend Jeff Warlowski. You may

748
00:50:50,640 --> 00:50:54,960
Speaker 1: know him if you listened to our dearly departed sports

749
00:50:55,040 --> 00:50:58,080
Speaker 1: Station ninety seven to three, the game, which was flipped

750
00:50:58,120 --> 00:51:01,799
Speaker 1: to well basically all Christmas meat music about a month

751
00:51:01,880 --> 00:51:05,400
Speaker 1: or so ago. He was affectionately known as pipe Bomb.

752
00:51:06,280 --> 00:51:08,320
Speaker 1: We're going to chat with him about what he's doing.

753
00:51:08,440 --> 00:51:11,600
Speaker 1: If I can double the salary of wherever it is,

754
00:51:11,640 --> 00:51:14,120
Speaker 1: he's going to keep him here because we really, really

755
00:51:14,160 --> 00:51:16,799
Speaker 1: really don't want to lose him. We'll get to that

756
00:51:16,920 --> 00:51:19,000
Speaker 1: as well, and in the five o'clock hour. I'm so

757
00:51:19,160 --> 00:51:22,200
Speaker 1: looking forward to this because I just love talking about

758
00:51:22,239 --> 00:51:26,239
Speaker 1: these deeper issues that impact society. Politics as a component

759
00:51:26,400 --> 00:51:30,279
Speaker 1: of them, yes, but this is really about who we

760
00:51:30,320 --> 00:51:34,040
Speaker 1: are as a species where we're going the gender divide

761
00:51:34,080 --> 00:51:37,440
Speaker 1: between young men and young women. Now, young women, for

762
00:51:37,520 --> 00:51:40,440
Speaker 1: I believe the first time ever, are saying in greater

763
00:51:40,520 --> 00:51:42,400
Speaker 1: numbers than young men, they don't want to get married.

764
00:51:42,560 --> 00:51:48,719
Speaker 1: They are foregoing the traditional not even the traditional role

765
00:51:48,760 --> 00:51:51,040
Speaker 1: of a wife. It's not like, you know, there's a

766
00:51:51,160 --> 00:51:56,640
Speaker 1: rising conservative movement is called the trad wife where it's

767
00:51:56,680 --> 00:51:59,400
Speaker 1: you know, the barefoot and pregnant and making dinner and

768
00:51:59,400 --> 00:52:02,120
Speaker 1: the husband goes out at the rat racers and comes

769
00:52:02,160 --> 00:52:05,319
Speaker 1: back with his briefcasion says, honey, you better have a

770
00:52:05,400 --> 00:52:08,520
Speaker 1: pot roast on or I'm gonna smack you silly. No, no, no, no,

771
00:52:08,520 --> 00:52:11,040
Speaker 1: no no, I'm not that tradway stuff. But I'm saying,

772
00:52:11,120 --> 00:52:14,520
Speaker 1: I'm saying, you know, it's more traditional, it's going back

773
00:52:14,520 --> 00:52:17,640
Speaker 1: to basics. No, it is because I am convinced of this.

774
00:52:17,760 --> 00:52:20,640
Speaker 1: I am convinced of this more than ever before. In

775
00:52:20,719 --> 00:52:24,520
Speaker 1: politics is one symptom of it. But you have young

776
00:52:24,600 --> 00:52:29,000
Speaker 1: men and young women who are just less connected than

777
00:52:29,080 --> 00:52:35,520
Speaker 1: ever before, culturally, politically, morally, you name it, spiritually. We

778
00:52:35,560 --> 00:52:37,560
Speaker 1: will get into that. I'm really looking forward to this

779
00:52:37,719 --> 00:52:41,919
Speaker 1: coming up in the five o'clock hours four years ago

780
00:52:42,160 --> 00:52:49,520
Speaker 1: today November twenty first, twenty twenty one, the Sunday before Thanksgiving.

781
00:52:50,680 --> 00:52:54,360
Speaker 1: In fact, I was having my family's Thanksgiving. My brother

782
00:52:54,560 --> 00:52:57,400
Speaker 1: was in at the time. He was doing a medical

783
00:52:57,440 --> 00:53:00,160
Speaker 1: residency in Louisville, so he came in. He was able

784
00:53:00,200 --> 00:53:02,480
Speaker 1: to get off for Thanksgiving. We were about to sit

785
00:53:02,560 --> 00:53:07,120
Speaker 1: down at Carabas have a nice Italian dinner half Sicilian,

786
00:53:07,160 --> 00:53:10,440
Speaker 1: so go figure and obviously the best most authentic Italian

787
00:53:10,440 --> 00:53:14,200
Speaker 1: we can find is Carabas. I don't know if Olive

788
00:53:14,200 --> 00:53:16,920
Speaker 1: Garden wasn't taking reservations that night or what, but in

789
00:53:16,960 --> 00:53:19,600
Speaker 1: any event, and all of a sudden, my phone started

790
00:53:19,600 --> 00:53:24,440
Speaker 1: blowing up. Something had happened at the wauca Shaw Christmas Parade.

791
00:53:24,520 --> 00:53:30,680
Speaker 1: I raced back, simultaneously talking on the phone, texting, and

792
00:53:30,840 --> 00:53:34,120
Speaker 1: trying to as quickly as possible get on the air.

793
00:53:34,120 --> 00:53:40,240
Speaker 1: It became very, very apparent, very quickly that something horrific

794
00:53:40,280 --> 00:53:46,080
Speaker 1: had happened. A disgusting human being whose name I am

795
00:53:46,120 --> 00:53:53,920
Speaker 1: not going to utter here plowed into the parade and

796
00:53:54,000 --> 00:54:00,839
Speaker 1: killed six people and injured dozens of others. The Waukeshaw

797
00:54:00,960 --> 00:54:05,359
Speaker 1: Christmas Parade massacre was one of the darkest days in

798
00:54:05,440 --> 00:54:08,680
Speaker 1: the history of Wisconsin. But ever since the people of

799
00:54:08,719 --> 00:54:11,880
Speaker 1: Waukeshaw have made it their mission to not let that

800
00:54:12,000 --> 00:54:16,600
Speaker 1: tragedy define them or their Christmas parade. They have held

801
00:54:16,600 --> 00:54:22,560
Speaker 1: it every year since in solidarity and defiance of evil,

802
00:54:23,080 --> 00:54:25,960
Speaker 1: and in the true spirit of the holidays, bringing a

803
00:54:25,960 --> 00:54:29,560
Speaker 1: community together as a family. I don't think I've ever

804
00:54:29,640 --> 00:54:32,359
Speaker 1: been more proud of a community in southeast Wisconsin than

805
00:54:32,360 --> 00:54:39,239
Speaker 1: the way that Waukeshaw banded together. A few hours after

806
00:54:39,280 --> 00:54:43,640
Speaker 1: we went off the air and the tragedy was sinking in,

807
00:54:44,040 --> 00:54:48,000
Speaker 1: I received multiple tips about just who the suspect was

808
00:54:49,520 --> 00:54:52,320
Speaker 1: and why he was out on the streets instead of

809
00:54:52,360 --> 00:54:57,719
Speaker 1: behind bars. As a direct result of that case, the

810
00:54:57,760 --> 00:55:01,320
Speaker 1: fact that he was out on the streets even though

811
00:55:01,880 --> 00:55:06,080
Speaker 1: he was supposed to be in jail, even though he

812
00:55:06,200 --> 00:55:12,160
Speaker 1: had committed a remarkably similar crime dragging his estranged girlfriend

813
00:55:12,360 --> 00:55:14,880
Speaker 1: from his vehicle just a short time earlier, he was

814
00:55:14,920 --> 00:55:17,719
Speaker 1: out on the streets, And as a direct result of that,

815
00:55:18,280 --> 00:55:23,239
Speaker 1: people of Wisconsin went to their legislators and went to

816
00:55:23,280 --> 00:55:26,839
Speaker 1: the ballot box and amended the constitution to make it

817
00:55:27,520 --> 00:55:32,319
Speaker 1: much easier for judges and court commissioners to impose serious

818
00:55:32,640 --> 00:55:36,520
Speaker 1: bail in order to keep dangerous people like the waka

819
00:55:36,600 --> 00:55:45,040
Speaker 1: Shaw Parade massacre killer behind bars. Has that happened? Sure

820
00:55:45,120 --> 00:55:51,280
Speaker 1: doesn't seem like it across the country. Oh, people were outraged,

821
00:55:51,320 --> 00:55:55,360
Speaker 1: they were horrified at the details. I wrote multiple stories

822
00:55:55,360 --> 00:55:58,040
Speaker 1: for national news outlets. I was on a number of

823
00:55:58,080 --> 00:56:01,840
Speaker 1: news networks talking about this story and talking about the

824
00:56:01,960 --> 00:56:06,239
Speaker 1: lenient bail that the killer had set that allowed him

825
00:56:06,280 --> 00:56:12,640
Speaker 1: to get out of jail almost free. And people said, Wow,

826
00:56:12,680 --> 00:56:15,879
Speaker 1: we need to reform bail, we need Wisconsin did this,

827
00:56:16,360 --> 00:56:19,440
Speaker 1: and yet you still have dangerous criminals on the streets

828
00:56:20,239 --> 00:56:28,600
Speaker 1: in Chicago, someone very similar to the Waukeshaw Parade massacre suspect,

829
00:56:28,680 --> 00:56:31,840
Speaker 1: someone with true evil in his heart and a long

830
00:56:31,960 --> 00:56:35,040
Speaker 1: rap sheet by the name of Lawrence Reid, was just

831
00:56:35,200 --> 00:56:41,000
Speaker 1: arrested for lighting a woman on fire on the city's

832
00:56:41,040 --> 00:56:47,160
Speaker 1: elevated rail system aka the l Little Woman on Fire.

833
00:56:47,200 --> 00:56:52,840
Speaker 1: She survived. Would you believe this guy has been arrested

834
00:56:53,400 --> 00:56:58,160
Speaker 1: forty nine times before this? Fox News Mike Tobe.

835
00:56:57,960 --> 00:57:00,560
Speaker 7: We've tracked down more than four dozen of rams arrests

836
00:57:00,560 --> 00:57:03,279
Speaker 7: of Lawrence Reed since nineteen ninety three. Nine of them

837
00:57:03,280 --> 00:57:05,400
Speaker 7: were for felonies. Yet he has served just over two

838
00:57:05,520 --> 00:57:08,680
Speaker 7: years behind bars. Most recently, he was charged with aggravator

839
00:57:08,680 --> 00:57:11,520
Speaker 7: assault for knocking out a social worker. The state's attorney

840
00:57:11,640 --> 00:57:15,880
Speaker 7: requested pre trial detention, but Judge Teresa Molina Gonzalez denied

841
00:57:15,960 --> 00:57:19,000
Speaker 7: him the request and put him on electronic monitoring. The

842
00:57:19,040 --> 00:57:23,880
Speaker 7: website CWB Chicago reports that at that dehensia to detention hearing,

843
00:57:24,160 --> 00:57:28,360
Speaker 7: Judge Molina Gonzalez said, I can't put everyone behind bars

844
00:57:28,440 --> 00:57:31,720
Speaker 7: or keep everyone in jail just because the state's attorney

845
00:57:31,840 --> 00:57:32,800
Speaker 7: has asked me to.

846
00:57:33,360 --> 00:57:36,120
Speaker 1: Yeah, you would think the guy who set a woman

847
00:57:36,400 --> 00:57:40,400
Speaker 1: on fire would be one of the ones that you'd

848
00:57:40,400 --> 00:57:44,800
Speaker 1: want to keep behind bars. This is yet more evidence

849
00:57:45,320 --> 00:57:48,880
Speaker 1: that no matter how loudly the people of wake Shaw,

850
00:57:49,040 --> 00:57:53,360
Speaker 1: or Wisconsin, or Chicago or wherever speak and say protect

851
00:57:53,560 --> 00:58:00,840
Speaker 1: us from these dangerous psychopaths, you will always have liberal judges, prosecutors,

852
00:58:01,200 --> 00:58:06,919
Speaker 1: liberal mayors, liberal governors, liberal policymakers who seem to care

853
00:58:07,120 --> 00:58:11,720
Speaker 1: far more about the most dangerous psychopaths in society than

854
00:58:11,760 --> 00:58:15,320
Speaker 1: they do about protecting the innocent from them. What is

855
00:58:15,360 --> 00:58:17,760
Speaker 1: going on with Wisconsin I. We check in with its

856
00:58:17,960 --> 00:58:23,960
Speaker 1: CEO next. You may not know what Wisconsin I is,

857
00:58:24,600 --> 00:58:28,800
Speaker 1: but rest assured you have seen what it does in

858
00:58:29,120 --> 00:58:32,680
Speaker 1: news coverage, in soundbites that you hear here on the

859
00:58:32,760 --> 00:58:36,320
Speaker 1: Dan o'donald Show. Think of it as Wisconsin's c span.

860
00:58:37,160 --> 00:58:41,840
Speaker 1: It is an organization that is committed to good government

861
00:58:42,120 --> 00:58:46,760
Speaker 1: and open and transparent government by filming and keeping an

862
00:58:46,920 --> 00:58:52,320
Speaker 1: archive of every single thing that the Wisconsin Legislature does,

863
00:58:53,120 --> 00:58:57,560
Speaker 1: public hearings, full sessions of the legislature. They provide what's

864
00:58:57,600 --> 00:59:02,640
Speaker 1: known as gavel to gavel coverage at wisside dot org.

865
00:59:02,720 --> 00:59:07,520
Speaker 1: Now they opened a lot of they turned a lot

866
00:59:07,560 --> 00:59:12,080
Speaker 1: of heads and opened a lot of eyes and made

867
00:59:12,120 --> 00:59:16,080
Speaker 1: a lot of people very concerned when yesterday they put

868
00:59:16,080 --> 00:59:19,800
Speaker 1: a message on their site saying that unless they're able

869
00:59:19,800 --> 00:59:23,720
Speaker 1: to reach an eight hundred and eighty seven thousand dollars

870
00:59:24,000 --> 00:59:30,160
Speaker 1: operational budget shortfall by December fifteenth, the website will not

871
00:59:30,320 --> 00:59:33,840
Speaker 1: only cease to exist, it will not only no longer

872
00:59:33,880 --> 00:59:38,440
Speaker 1: be able to provide coverage of state legislative and gubernatorial

873
00:59:38,560 --> 00:59:43,320
Speaker 1: things basically covering the capital, that all of the archives

874
00:59:43,400 --> 00:59:48,280
Speaker 1: will have to be deleted. Joining us now to talk

875
00:59:48,320 --> 00:59:51,800
Speaker 1: about it is the President and CEO of Wisconsin I

876
00:59:52,240 --> 00:59:54,920
Speaker 1: John Henkis. John, Welcome to the Dan O'Donnell Show.

877
00:59:56,320 --> 00:59:59,160
Speaker 3: Thank you Dan for the opportunity to make our case

878
00:59:59,200 --> 01:00:02,920
Speaker 3: to a broad an important audience. So we appreciate that.

879
01:00:03,200 --> 01:00:06,240
Speaker 1: Well, you get no argument from me. I have said

880
01:00:06,280 --> 01:00:09,120
Speaker 1: for a long time that Wisconsin I is about the

881
01:00:09,120 --> 01:00:13,080
Speaker 1: most essential thing that we have in Wisconsin. I absolutely

882
01:00:13,120 --> 01:00:16,600
Speaker 1: mean that, not just from a personal and professional standpoint,

883
01:00:16,800 --> 01:00:19,640
Speaker 1: but from a good government standpoint. I mean, what do

884
01:00:19,720 --> 01:00:23,640
Speaker 1: you think happens if the public no longer has the

885
01:00:23,720 --> 01:00:27,040
Speaker 1: opportunity to see what state legislators are doing.

886
01:00:28,320 --> 01:00:31,960
Speaker 3: Well, A state known for openness and transparency will take

887
01:00:31,960 --> 01:00:35,080
Speaker 3: a big step backwards. And we don't want to do that. Now.

888
01:00:35,160 --> 01:00:40,080
Speaker 3: We've got a long standing legacy of transparency and accountability

889
01:00:40,200 --> 01:00:44,160
Speaker 3: and citizen access to what happens in the state capitol.

890
01:00:44,200 --> 01:00:47,040
Speaker 3: And by that I mean they spend billions of dollars

891
01:00:47,120 --> 01:00:51,320
Speaker 3: every year in state taxpayer dollars. That affects every citizen

892
01:00:51,560 --> 01:00:54,560
Speaker 3: in every community in this state. And to do that

893
01:00:54,720 --> 01:00:58,400
Speaker 3: well with accountability and public trust, you have to have

894
01:00:59,480 --> 01:01:02,040
Speaker 3: a spot light on what they do and how they

895
01:01:02,080 --> 01:01:06,200
Speaker 3: do it without partisan spin yep, without massive editing or

896
01:01:06,240 --> 01:01:10,080
Speaker 3: sensational headlines. And that's our mission and we need to

897
01:01:10,120 --> 01:01:10,880
Speaker 3: carry it forward.

898
01:01:11,400 --> 01:01:15,360
Speaker 1: And that's it exactly you can get if I was

899
01:01:15,480 --> 01:01:19,640
Speaker 1: sitting in a legislative here, right, And I think a

900
01:01:19,640 --> 01:01:22,800
Speaker 1: lot of our listeners trust me to be fair and

901
01:01:22,880 --> 01:01:25,600
Speaker 1: open and honest. But I do come at this with

902
01:01:25,720 --> 01:01:29,560
Speaker 1: a conservative perspective. If we don't have Wisconsin I, I

903
01:01:29,640 --> 01:01:33,000
Speaker 1: will report on what it is I see just naturally

904
01:01:33,320 --> 01:01:36,440
Speaker 1: from my own perspective. It's not even that I'm trying

905
01:01:36,440 --> 01:01:38,520
Speaker 1: to be biased or something like that, but it is

906
01:01:38,600 --> 01:01:41,840
Speaker 1: just sort of human nature. And what Wisconsin I does,

907
01:01:41,960 --> 01:01:45,080
Speaker 1: just like c SPAN at the federal level, is to

908
01:01:45,320 --> 01:01:49,240
Speaker 1: allow people to watch for themselves and to draw their

909
01:01:49,240 --> 01:01:53,160
Speaker 1: own conclusions. Now, nobody is on under any illusion that

910
01:01:53,240 --> 01:01:57,840
Speaker 1: the people of Wisconsin are sitting riveted watching you know,

911
01:01:57,960 --> 01:02:03,200
Speaker 1: the Transportation Committee of the State Assembly's hearing on whether

912
01:02:03,320 --> 01:02:05,880
Speaker 1: or not to allow a brand new version of a

913
01:02:05,960 --> 01:02:09,960
Speaker 1: license plate or something like that. But the fact is

914
01:02:10,720 --> 01:02:13,440
Speaker 1: we do need to shine a light on exactly what

915
01:02:13,800 --> 01:02:17,640
Speaker 1: is going on. So I guess I'm not entirely clear, John,

916
01:02:17,720 --> 01:02:22,080
Speaker 1: I know our audience really isn't either. How did Wisconsin

917
01:02:22,200 --> 01:02:24,880
Speaker 1: I get in this dire of financial situation?

918
01:02:26,640 --> 01:02:30,040
Speaker 3: Sure, the funding model for Wisconsin I has always been

919
01:02:30,320 --> 01:02:35,440
Speaker 3: raised charitable five oh one c three nonprofit donations that

920
01:02:35,600 --> 01:02:38,880
Speaker 3: has been our funding model, and ever since the pandemic,

921
01:02:40,240 --> 01:02:44,320
Speaker 3: the philanthropic environment in this state and nationwide has changed

922
01:02:44,440 --> 01:02:50,600
Speaker 3: rather dramatically. The competition for limited charitable dollars is greater

923
01:02:50,680 --> 01:02:54,000
Speaker 3: than it's ever been before. So that is one dynamic

924
01:02:54,040 --> 01:02:57,320
Speaker 3: that is clearly affecting us. But the pandemic also did

925
01:02:57,360 --> 01:03:01,200
Speaker 3: something else, really significant dance a lot of community based

926
01:03:01,240 --> 01:03:06,440
Speaker 3: projects for good reasons economic skittishness and uncertainty on the

927
01:03:06,480 --> 01:03:09,040
Speaker 3: part of donors. A lot of those community based projects

928
01:03:09,120 --> 01:03:12,520
Speaker 3: went into hibernation, and about eighteen months ago, all of

929
01:03:12,560 --> 01:03:15,360
Speaker 3: those projects all around the state, tens of millions of

930
01:03:15,360 --> 01:03:20,240
Speaker 3: dollars in charitable campaigns started to re emerge, as well

931
01:03:20,280 --> 01:03:23,640
Speaker 3: as new ones. So Wisconsin I has never been first

932
01:03:23,640 --> 01:03:25,640
Speaker 3: in line. I mean, let's face it, we don't have

933
01:03:25,680 --> 01:03:31,000
Speaker 3: a great alumni base for grateful patience or faithful parishioners,

934
01:03:31,800 --> 01:03:36,200
Speaker 3: and we're not meeting basic human needs shelter in the homeless,

935
01:03:35,600 --> 01:03:38,720
Speaker 3: you know, And so we're never first in line, and

936
01:03:38,760 --> 01:03:41,960
Speaker 3: we're lucky if we're third in line. On top of that,

937
01:03:43,720 --> 01:03:49,720
Speaker 3: the push for record breaking political fundraising in the eyes

938
01:03:49,760 --> 01:03:53,720
Speaker 3: of those donors, they put Wisconsin I in that same bucket.

939
01:03:54,280 --> 01:03:56,520
Speaker 3: So we've got to fight our way through that fog

940
01:03:56,600 --> 01:03:59,720
Speaker 3: and say, no, wait a minute, we don't advocate for candidates,

941
01:04:00,120 --> 01:04:05,480
Speaker 3: campaigns or causes. We're the neutral, transparent part of that

942
01:04:05,600 --> 01:04:10,600
Speaker 3: political equation. And for a fraction of what is spent

943
01:04:10,880 --> 01:04:15,840
Speaker 3: on political campaigns, much of it going to negative misleading advertising,

944
01:04:16,000 --> 01:04:20,120
Speaker 3: no offense to those advertisers. For a fraction of that,

945
01:04:20,520 --> 01:04:24,080
Speaker 3: we meet our budget. So we're not currently in a shortfall.

946
01:04:24,160 --> 01:04:26,800
Speaker 3: But what we're facing is the reality that we may

947
01:04:26,880 --> 01:04:31,160
Speaker 3: not be able to afford our forthcoming year budget beginning

948
01:04:31,160 --> 01:04:34,520
Speaker 3: in January, which is the eight hundred thousand plus amount

949
01:04:34,600 --> 01:04:37,920
Speaker 3: that you had mentioned. Right now, we're in a deficit position.

950
01:04:39,040 --> 01:04:41,280
Speaker 3: We have enough funding to carry us through the end

951
01:04:41,320 --> 01:04:44,360
Speaker 3: of the year, and there are two solutions to this.

952
01:04:45,120 --> 01:04:49,440
Speaker 3: The first and the best path to financial success is

953
01:04:49,560 --> 01:04:55,200
Speaker 3: best achieved by an act of the Wisconsin Legislature to remove,

954
01:04:56,120 --> 01:05:01,280
Speaker 3: to release all or a part of a ten million

955
01:05:01,400 --> 01:05:06,320
Speaker 3: dollar challenge grant that has Wisconsin I's name on it.

956
01:05:06,880 --> 01:05:10,360
Speaker 3: But it is not ours unless we raise dollar for

957
01:05:10,520 --> 01:05:11,240
Speaker 3: dollar match.

958
01:05:11,480 --> 01:05:14,000
Speaker 1: So wait a second, so hold on, hold on, Just

959
01:05:14,040 --> 01:05:18,400
Speaker 1: so I'm getting this right. The legislature and the governor

960
01:05:18,440 --> 01:05:21,320
Speaker 1: by extension, but the legislature says, Okay, we will give

961
01:05:21,360 --> 01:05:25,439
Speaker 1: you a ten million dollar grant, which I'm guessing then

962
01:05:25,600 --> 01:05:28,760
Speaker 1: that would be turned into an endowment, and the funding

963
01:05:28,800 --> 01:05:33,040
Speaker 1: for Wisconsin I would be funded in perpetuity by the interest,

964
01:05:33,080 --> 01:05:36,520
Speaker 1: dividend payments, that sort of thing off of that endowment. Okay,

965
01:05:37,280 --> 01:05:41,000
Speaker 1: But in order to get that ten million dollars, you

966
01:05:41,200 --> 01:05:45,120
Speaker 1: have to raise ten million dollars? Do I get that right?

967
01:05:45,160 --> 01:05:45,840
Speaker 1: Do I have that right?

968
01:05:46,440 --> 01:05:46,520
Speaker 8: So?

969
01:05:46,880 --> 01:05:47,240
Speaker 3: Correct?

970
01:05:47,800 --> 01:05:51,040
Speaker 1: In order to get a single dollar from the state

971
01:05:51,040 --> 01:05:56,200
Speaker 1: of Wisconsin to provide the coverage and what we always

972
01:05:56,200 --> 01:05:59,400
Speaker 1: pride ourselves on on the transparency of open government and

973
01:05:59,440 --> 01:06:03,040
Speaker 1: all of that, you need to raise ten million dollars

974
01:06:03,400 --> 01:06:06,360
Speaker 1: just so that the state of Wisconsin will fund you.

975
01:06:07,440 --> 01:06:11,160
Speaker 3: That's not completely accurate. The ten million is there, and

976
01:06:11,240 --> 01:06:16,600
Speaker 3: we can raise smaller incremental amounts that will be matched. However,

977
01:06:16,680 --> 01:06:21,040
Speaker 3: we're competing against ourselves. Sure, we can't touch that endowment money.

978
01:06:21,840 --> 01:06:24,360
Speaker 3: All we could do is draw the interest, so.

979
01:06:24,360 --> 01:06:27,320
Speaker 1: We Oh, okay, I see what you're saying. I see.

980
01:06:27,400 --> 01:06:30,480
Speaker 1: So you can't get your own endowment until you reach

981
01:06:31,800 --> 01:06:37,040
Speaker 1: that level. That okay. That that seems a very very

982
01:06:37,080 --> 01:06:40,080
Speaker 1: difficult for any charitable organization or five oh one c

983
01:06:40,240 --> 01:06:43,080
Speaker 1: three to do. And B I don't mean to be

984
01:06:43,120 --> 01:06:47,840
Speaker 1: insulting here, John, but for an organization that isn't doing

985
01:06:48,320 --> 01:06:51,280
Speaker 1: sexy work, you know what I'm saying, Like, it's not hey,

986
01:06:51,400 --> 01:06:54,160
Speaker 1: we're we're going to cure cancer. Hey we're going to

987
01:06:54,200 --> 01:06:58,840
Speaker 1: do this, it's we are going to film state government. Right.

988
01:06:58,920 --> 01:07:01,840
Speaker 1: That that doesn't seem like it really you know, captures

989
01:07:01,880 --> 01:07:03,520
Speaker 1: the imagination of donors here.

990
01:07:04,840 --> 01:07:09,040
Speaker 3: Well, and we have a place in this argument. This

991
01:07:09,400 --> 01:07:14,360
Speaker 3: phrase save our democracy. I mean, that's a painting with

992
01:07:14,480 --> 01:07:18,040
Speaker 3: a lot of different people coloring into it. You know,

993
01:07:18,120 --> 01:07:22,200
Speaker 3: there's the call for let's not jerrymanned er legislative districts.

994
01:07:22,480 --> 01:07:26,439
Speaker 3: Let's tone down the political partisan rhetoric. Let's make sure

995
01:07:26,480 --> 01:07:30,400
Speaker 3: that voters who are supposed to vote do and those

996
01:07:30,440 --> 01:07:35,280
Speaker 3: who aren't do not well. A big part of this

997
01:07:35,960 --> 01:07:39,960
Speaker 3: cry for strengthening our democracy is to keep our democracy

998
01:07:40,520 --> 01:07:45,280
Speaker 3: accessible and transparent and accountable. And Wisconsin I is at

999
01:07:45,320 --> 01:07:48,800
Speaker 3: the heart of that. And so and so the argument

1000
01:07:48,840 --> 01:07:51,120
Speaker 3: that we have to make is even if you're not

1001
01:07:51,320 --> 01:07:55,200
Speaker 3: watching it, it's important to the future and strength of

1002
01:07:55,640 --> 01:07:59,240
Speaker 3: our democracy. We need to know what's happening in Madison,

1003
01:07:59,320 --> 01:08:02,120
Speaker 3: and we need we need to go to the place

1004
01:08:02,120 --> 01:08:05,200
Speaker 3: where truth has its forum, and that's in gabble to

1005
01:08:05,280 --> 01:08:09,760
Speaker 3: gable coverage with an archive that's freely available to everyone.

1006
01:08:10,040 --> 01:08:14,880
Speaker 3: So the solution here, Dan is the best way forward

1007
01:08:15,040 --> 01:08:19,920
Speaker 3: is if the legislature were to remove the match requirement

1008
01:08:20,080 --> 01:08:23,840
Speaker 3: for all or part of that ten million dollars. You know,

1009
01:08:23,840 --> 01:08:28,040
Speaker 3: it could be a multiple year, one million dollar allocation.

1010
01:08:29,280 --> 01:08:32,800
Speaker 3: It accomplishes the same goal over the long term, which

1011
01:08:32,840 --> 01:08:35,080
Speaker 3: is the long term viability of the network. Now, in

1012
01:08:35,120 --> 01:08:38,479
Speaker 3: the short term, we still have to bridge the funding gap,

1013
01:08:38,600 --> 01:08:42,280
Speaker 3: and on that account, by us pushing the alarm button,

1014
01:08:42,600 --> 01:08:46,160
Speaker 3: we are hoping that there are philanthropists out there, people

1015
01:08:46,200 --> 01:08:49,560
Speaker 3: who care about government, who give to candidates and campaigns

1016
01:08:49,600 --> 01:08:53,519
Speaker 3: and causes, will wake up. If you will, I mean

1017
01:08:53,560 --> 01:08:56,840
Speaker 3: to those folks. I would quote want Ronald Reagan who

1018
01:08:56,880 --> 01:08:59,800
Speaker 3: once said, if you can't make them see the light,

1019
01:09:00,080 --> 01:09:03,439
Speaker 3: make them feel the heat. Yeah. I'm hoping people out

1020
01:09:03,479 --> 01:09:06,879
Speaker 3: there will feel the heat of potentially losing a wonderful

1021
01:09:06,920 --> 01:09:09,080
Speaker 3: resource called Wisconsin I.

1022
01:09:09,760 --> 01:09:13,519
Speaker 1: And it's not just the resource of Wisconsin ice, the

1023
01:09:13,560 --> 01:09:17,240
Speaker 1: resource of actually being able to see in real time

1024
01:09:18,120 --> 01:09:22,639
Speaker 1: or have an archive of what it is. Your legislators, do, John,

1025
01:09:23,120 --> 01:09:26,760
Speaker 1: I join your call in that the amount of stupid

1026
01:09:26,920 --> 01:09:31,680
Speaker 1: crap we spend ten times the money on that you

1027
01:09:31,760 --> 01:09:36,479
Speaker 1: are asking for from the state legislature. Routinely we just

1028
01:09:36,720 --> 01:09:39,200
Speaker 1: fritter away money like it's our job as the state

1029
01:09:39,200 --> 01:09:42,479
Speaker 1: of Wisconsin. This is a vital service, and I know

1030
01:09:42,560 --> 01:09:45,880
Speaker 1: there are people in our listening audience who will take

1031
01:09:45,960 --> 01:09:49,160
Speaker 1: up that cause and who will support you. Just go

1032
01:09:49,200 --> 01:09:52,160
Speaker 1: to wisside dot org to figure out how you can

1033
01:09:52,360 --> 01:09:56,919
Speaker 1: contribute whatever you need me to do, to put pressure

1034
01:09:57,120 --> 01:09:59,800
Speaker 1: on the legislature to do the right thing and yet

1035
01:10:00,200 --> 01:10:04,400
Speaker 1: move this onerous requirement that the funding match and just

1036
01:10:04,680 --> 01:10:10,080
Speaker 1: allow the endowment to move forward and to fund this

1037
01:10:10,160 --> 01:10:12,599
Speaker 1: isn't This isn't a luxury. Okay. It's like, as much

1038
01:10:12,640 --> 01:10:15,800
Speaker 1: as I love the Milwaukee Symphony Orchestra, do we need

1039
01:10:15,840 --> 01:10:16,759
Speaker 1: a symphony orchestra?

1040
01:10:16,880 --> 01:10:16,960
Speaker 2: No?

1041
01:10:17,479 --> 01:10:20,720
Speaker 1: Do we need the ability to see what our legislators

1042
01:10:20,760 --> 01:10:23,760
Speaker 1: are doing all the time? Yes, this this is a

1043
01:10:23,960 --> 01:10:26,799
Speaker 1: necessary function. John Henkas is the president.

1044
01:10:27,280 --> 01:10:29,679
Speaker 3: If I made Dan well.

1045
01:10:29,760 --> 01:10:32,439
Speaker 1: Unfortunately, I'm sorry, John. We are we are up against

1046
01:10:32,479 --> 01:10:35,559
Speaker 1: the clock. I do apologize. We just we have to

1047
01:10:35,560 --> 01:10:38,200
Speaker 1: get this break in. Go to wissid dot org. Support

1048
01:10:38,240 --> 01:10:41,479
Speaker 1: this great mission. You are listening to the Dan o'donald show,

1049
01:10:42,880 --> 01:10:47,760
Speaker 1: chatted with John Hankas, the President and CEO of Wisconsin.

1050
01:10:47,840 --> 01:10:51,439
Speaker 1: I off the air, we unfortunately ran into a commercial

1051
01:10:51,439 --> 01:10:53,360
Speaker 1: break that we just we had to get to.

1052
01:10:54,080 --> 01:10:54,320
Speaker 2: Uh.

1053
01:10:54,360 --> 01:10:57,680
Speaker 1: He wanted to reiterate just how grateful he was to

1054
01:10:57,920 --> 01:11:02,960
Speaker 1: the Wisconsin Legislature for the endowment ten million dollars. The

1055
01:11:03,040 --> 01:11:08,120
Speaker 1: requirement though, that in order to get the full benefit

1056
01:11:08,280 --> 01:11:12,320
Speaker 1: of that ten million dollars of endowment for Wisconsin I

1057
01:11:12,439 --> 01:11:16,720
Speaker 1: they need to raise dollar for dollar matching funds. He

1058
01:11:16,880 --> 01:11:21,479
Speaker 1: is humbly asking his organization is humbly asking that that

1059
01:11:21,560 --> 01:11:26,840
Speaker 1: requirement be removed. And frankly, I think it is impossible

1060
01:11:26,880 --> 01:11:29,679
Speaker 1: for an organization like that to raise ten million dollars.

1061
01:11:29,720 --> 01:11:32,800
Speaker 1: It's just the reality of it. You're not going to

1062
01:11:32,880 --> 01:11:35,519
Speaker 1: get big money donors. I can sit here and tell

1063
01:11:35,520 --> 01:11:38,759
Speaker 1: you how important it is, and it is. It's incredibly important.

1064
01:11:38,760 --> 01:11:42,559
Speaker 1: It's vital, but again it's not top of mind. It's

1065
01:11:42,640 --> 01:11:47,840
Speaker 1: not something that donors will run out to want to support.

1066
01:11:48,880 --> 01:11:52,280
Speaker 1: And he said, the biggest champion of Wisconsin I has

1067
01:11:52,360 --> 01:11:56,160
Speaker 1: been Assembly Speaker Robin Voss. He has been throughout his

1068
01:11:56,280 --> 01:11:59,880
Speaker 1: career a big champion of it. And I'll tell you what,

1069
01:12:00,200 --> 01:12:03,840
Speaker 1: I will be the biggest champion in media because you

1070
01:12:03,960 --> 01:12:06,720
Speaker 1: know how I feel about good government. You know how

1071
01:12:06,760 --> 01:12:10,080
Speaker 1: I feel about transparency. We don't have that at the

1072
01:12:10,200 --> 01:12:14,559
Speaker 1: state level unless we have the ability to watch every

1073
01:12:14,680 --> 01:12:18,920
Speaker 1: single thing that legislators do. So again, wissid dot org.

1074
01:12:19,120 --> 01:12:22,920
Speaker 1: If you want to support this mission, contact your state

1075
01:12:22,960 --> 01:12:26,479
Speaker 1: representative and say, hey, all we need you to do

1076
01:12:26,880 --> 01:12:30,960
Speaker 1: is to remove that dollar for dollar match. This is

1077
01:12:31,000 --> 01:12:34,280
Speaker 1: something that the state of Wisconsin should be funding. It's

1078
01:12:34,320 --> 01:12:37,080
Speaker 1: the thing the state of Wisconsin needs to be funding.

1079
01:12:37,160 --> 01:12:41,680
Speaker 1: I would support a million dollars just coming out of

1080
01:12:41,680 --> 01:12:44,439
Speaker 1: the state budget every year in perpetuity for this. And

1081
01:12:44,479 --> 01:12:47,920
Speaker 1: that's how valuable I think Wisconsin I is. And it's

1082
01:12:47,960 --> 01:12:51,720
Speaker 1: not because of say a personal relationship with John who

1083
01:12:51,760 --> 01:12:53,479
Speaker 1: I've met a handful of times. I think he does

1084
01:12:53,640 --> 01:12:57,639
Speaker 1: incredible work, But it is it's the vital service. I mean,

1085
01:12:57,760 --> 01:13:02,120
Speaker 1: just imagine the federal government without c SPAN. We have

1086
01:13:02,320 --> 01:13:05,800
Speaker 1: the ability to see it, and we have a right

1087
01:13:05,840 --> 01:13:09,880
Speaker 1: to see every single thing that goes on. In order

1088
01:13:09,920 --> 01:13:13,360
Speaker 1: to be informed citizens, we need to see every single

1089
01:13:13,439 --> 01:13:17,080
Speaker 1: thing that goes on on our behalf. Remember, these are

1090
01:13:17,160 --> 01:13:22,479
Speaker 1: the people are accountable. The people are the bosses of

1091
01:13:22,520 --> 01:13:26,840
Speaker 1: the legislation. They are accountable to us. All right. I

1092
01:13:26,880 --> 01:13:31,679
Speaker 1: do want a lot of listener feedback on this study

1093
01:13:32,400 --> 01:13:36,679
Speaker 1: that came out this week. It was the American Family

1094
01:13:37,000 --> 01:13:40,080
Speaker 1: Survey for twenty twenty five. It was a representative poll

1095
01:13:40,120 --> 01:13:44,200
Speaker 1: of three thousand US adults conducted in August, but first

1096
01:13:44,240 --> 01:13:48,960
Speaker 1: released essentially this week. November fourteenth was the official release,

1097
01:13:49,000 --> 01:13:55,160
Speaker 1: but it hit the news cycle this week. Only fifty

1098
01:13:55,240 --> 01:14:00,400
Speaker 1: two percent of respondents agreed with the statement society is

1099
01:14:00,479 --> 01:14:04,400
Speaker 1: better off if people make marriage and having children a

1100
01:14:04,439 --> 01:14:08,640
Speaker 1: priority in their lives. Just five years ago that was

1101
01:14:08,760 --> 01:14:14,799
Speaker 1: sixty three percent, And there was a massive gender disparity women,

1102
01:14:15,439 --> 01:14:19,960
Speaker 1: especially young women, especially women at the traditional marriage age

1103
01:14:20,040 --> 01:14:24,759
Speaker 1: in their early to late twenties, they show significantly less

1104
01:14:24,800 --> 01:14:30,160
Speaker 1: interest in marriage than men. Specifically, men are more likely

1105
01:14:30,240 --> 01:14:34,160
Speaker 1: now to view marriage as essential for personal fulfillment and

1106
01:14:34,280 --> 01:14:41,840
Speaker 1: financial stability. Women are more influenced by economic concerns such

1107
01:14:41,920 --> 01:14:47,280
Speaker 1: as rising costs. They tend to be more skeptical of marriage.

1108
01:14:48,040 --> 01:14:53,559
Speaker 1: Far fewers see marriage as a pathway to stability. This

1109
01:14:53,760 --> 01:14:59,080
Speaker 1: is actually followed up by, and this is echoed by

1110
01:14:59,680 --> 01:15:04,280
Speaker 1: a study entitled the State of Today's Family by an

1111
01:15:04,360 --> 01:15:11,479
Speaker 1: organization called the Barna Group. Fewer adults are married, the

1112
01:15:13,000 --> 01:15:19,599
Speaker 1: younger generations are postponing marriage. The average first marriage age

1113
01:15:19,840 --> 01:15:24,840
Speaker 1: now is thirty point two for men and twenty eight

1114
01:15:24,880 --> 01:15:29,480
Speaker 1: point six for women. In nineteen fifty that was about

1115
01:15:29,840 --> 01:15:33,800
Speaker 1: twenty two for men and twenty for women. Now, A

1116
01:15:33,840 --> 01:15:36,080
Speaker 1: lot of that is a function of just the world

1117
01:15:36,160 --> 01:15:39,840
Speaker 1: is a lot different now. And again, as I always say,

1118
01:15:40,360 --> 01:15:43,280
Speaker 1: when people believe they are going to live a lot

1119
01:15:43,360 --> 01:15:46,720
Speaker 1: longer as people today do, they have a tendency to

1120
01:15:47,000 --> 01:15:53,920
Speaker 1: prolong different phases of their life. Adolescence, early adulthood. They

1121
01:15:53,960 --> 01:15:56,760
Speaker 1: believe that they can put off marriage, they can put

1122
01:15:56,840 --> 01:16:00,479
Speaker 1: off having children, having a family, doing all that, the kids,

1123
01:16:00,520 --> 01:16:02,760
Speaker 1: the white picket fence, that sort of thing, because they

1124
01:16:02,760 --> 01:16:07,160
Speaker 1: believe they've got more time to do so. Pew Research

1125
01:16:07,479 --> 01:16:12,679
Speaker 1: Group also took a look at University of Michigan data.

1126
01:16:12,800 --> 01:16:16,880
Speaker 1: It was a survey of high school seniors. Female high

1127
01:16:16,920 --> 01:16:23,120
Speaker 1: school seniors also showed dramatically less interest in marriage than males,

1128
01:16:23,360 --> 01:16:28,360
Speaker 1: a stark gender gap attributed to reduced financial incentives and

1129
01:16:28,520 --> 01:16:37,719
Speaker 1: broader cultural shifts. Why do you suppose this is I'll

1130
01:16:37,720 --> 01:16:40,720
Speaker 1: give you my theory. I want to hear yours and

1131
01:16:40,800 --> 01:16:45,080
Speaker 1: what do you think the impact is on broader society

1132
01:16:45,360 --> 01:16:50,080
Speaker 1: of so many fewer women wanting to get married than

1133
01:16:50,160 --> 01:16:53,280
Speaker 1: men four one, four, seven, nine, nine eleven thirty or

1134
01:16:53,280 --> 01:16:56,479
Speaker 1: one eight hundred eight three eight nine four seven six.

1135
01:16:56,600 --> 01:16:59,200
Speaker 1: That's our toll free talk and text line. Can also

1136
01:16:59,280 --> 01:17:06,800
Speaker 1: email me Dad at iHeartMedia dot com. I believe a

1137
01:17:06,920 --> 01:17:12,240
Speaker 1: significant portion of this is the fact that men and women,

1138
01:17:12,600 --> 01:17:18,320
Speaker 1: especially in the dating slash marriage cohort early twenties, even

1139
01:17:18,400 --> 01:17:23,559
Speaker 1: late teens to early thirties, just do not have the

1140
01:17:23,600 --> 01:17:28,720
Speaker 1: same worldview as one another. There is a massive political

1141
01:17:28,800 --> 01:17:35,040
Speaker 1: ideology gap that is only growing Gallup poll forty percent

1142
01:17:35,320 --> 01:17:39,559
Speaker 1: of young women now identify as liberal. That's up from

1143
01:17:39,680 --> 01:17:44,120
Speaker 1: twenty eight percent in two thousand and three. Forty percent

1144
01:17:44,240 --> 01:17:49,000
Speaker 1: identify as liberal. Just twenty five percent of young men

1145
01:17:49,280 --> 01:17:53,759
Speaker 1: identify as liberal. According to exit polling from the twenty

1146
01:17:53,800 --> 01:18:00,240
Speaker 1: twenty four presidential election, Hillary Hillary Clinton Kamala Harris had

1147
01:18:00,439 --> 01:18:06,360
Speaker 1: sixty plus percent support of young women. She won women

1148
01:18:07,400 --> 01:18:14,240
Speaker 1: in the twenty nine and under demographic by forty points. Meanwhile,

1149
01:18:15,479 --> 01:18:22,479
Speaker 1: Trump won young men by fourteen points. Fifty one percent

1150
01:18:22,560 --> 01:18:28,080
Speaker 1: of young male voters lean GOP, fifty seven percent of

1151
01:18:28,160 --> 01:18:35,759
Speaker 1: young women lean Democrat. This was the largest generational gap,

1152
01:18:36,200 --> 01:18:41,040
Speaker 1: meaning young women and young men were much farther apart

1153
01:18:41,120 --> 01:18:45,720
Speaker 1: than say, men and women aged sixty five plus men

1154
01:18:45,760 --> 01:18:49,919
Speaker 1: and women in their forties, which is my generational cohort.

1155
01:18:51,320 --> 01:18:55,599
Speaker 1: Why is this They just don't see eye to eye

1156
01:18:55,640 --> 01:19:00,200
Speaker 1: on politics. Yes, but I firmly believe this is is

1157
01:19:00,320 --> 01:19:06,000
Speaker 1: part and parcel of a broader shift, especially in young women.

1158
01:19:06,080 --> 01:19:09,160
Speaker 1: Now young men have gotten more conservative. But I would

1159
01:19:09,160 --> 01:19:13,679
Speaker 1: actually point to the fact that young men, especially young

1160
01:19:13,760 --> 01:19:17,160
Speaker 1: white men, have been told from the time they're old

1161
01:19:17,280 --> 01:19:20,200
Speaker 1: enough to be told, they are the stated enemy. They

1162
01:19:20,240 --> 01:19:23,960
Speaker 1: are racist, they are sexist, they are bigoted, they are homophobic.

1163
01:19:23,960 --> 01:19:25,600
Speaker 1: Do you remember a few months ago, maybe it was

1164
01:19:25,600 --> 01:19:28,960
Speaker 1: a year ago, there was a very popular thing online.

1165
01:19:29,640 --> 01:19:32,840
Speaker 1: It was asking women, would you rather be alone in

1166
01:19:32,880 --> 01:19:38,000
Speaker 1: the woods with a man or a bear? Women picked

1167
01:19:38,120 --> 01:19:43,520
Speaker 1: the bear because they thought men were far more dangerous.

1168
01:19:44,800 --> 01:19:47,439
Speaker 1: What happens if you're told that over and over and

1169
01:19:47,479 --> 01:19:52,080
Speaker 1: over and over again, you tend to start saying, Okay, well, hey,

1170
01:19:52,320 --> 01:19:58,200
Speaker 1: screw you man. That I think is the impact of liberalism.

1171
01:19:58,760 --> 01:20:04,479
Speaker 1: Not only has it hardened female worldview and gotten them

1172
01:20:04,520 --> 01:20:08,839
Speaker 1: to believe that men are predators, men are the enemy

1173
01:20:09,280 --> 01:20:13,240
Speaker 1: men want to especially in the post Row v. Wade

1174
01:20:13,360 --> 01:20:17,880
Speaker 1: era after twenty twenty two, when Dobbs vy Jackson Women's

1175
01:20:17,920 --> 01:20:22,639
Speaker 1: health overturned Row. What was the primary messaging to young women,

1176
01:20:23,120 --> 01:20:26,080
Speaker 1: the women who would be getting abortions, Women in their twenties,

1177
01:20:26,080 --> 01:20:29,599
Speaker 1: women in their thirties. Men want to control you, They

1178
01:20:29,640 --> 01:20:33,800
Speaker 1: want to control your bodies. You, of course have no

1179
01:20:33,880 --> 01:20:38,920
Speaker 1: agency whatsoever. But it's telling young women that you are

1180
01:20:38,960 --> 01:20:44,280
Speaker 1: going to be victimized by men. Not coincidentally, they're saying, well,

1181
01:20:44,439 --> 01:20:47,439
Speaker 1: if you just vote for us, we will protect you

1182
01:20:47,560 --> 01:20:50,439
Speaker 1: from those evil men who want to impregnate you and

1183
01:20:50,479 --> 01:20:55,320
Speaker 1: then force you to carry the baby to term. There's

1184
01:20:55,360 --> 01:20:59,880
Speaker 1: something else at play here. As women have gotten farm

1185
01:21:00,160 --> 01:21:07,760
Speaker 1: or politically liberal, it has coincided with a fundamentally downtrodden,

1186
01:21:08,320 --> 01:21:15,960
Speaker 1: doom and gloom worldview. Twenty twenty Pere research analysis found

1187
01:21:16,120 --> 01:21:21,320
Speaker 1: fifty six percent of white liberal women under the age

1188
01:21:21,360 --> 01:21:26,879
Speaker 1: of thirty reported having been diagnosed with a mental health condition.

1189
01:21:27,760 --> 01:21:32,599
Speaker 1: That is far and away the highest incidents of mental

1190
01:21:32,640 --> 01:21:38,920
Speaker 1: illness than any other demographic. Twenty twenty four American Family

1191
01:21:39,000 --> 01:21:45,080
Speaker 1: Survey reinforces this. Just twelve percent of liberal women aged

1192
01:21:45,200 --> 01:21:51,200
Speaker 1: eighteen to forty reported being quote completely satisfied with their

1193
01:21:51,240 --> 01:22:00,320
Speaker 1: lives just twelve percent conservative women thirty seven percent. Women

1194
01:22:00,920 --> 01:22:06,559
Speaker 1: are three times more likely than conservative women to report

1195
01:22:06,600 --> 01:22:11,719
Speaker 1: feeling frequent loneliness, i e. Do you feel lonely several

1196
01:22:11,760 --> 01:22:15,559
Speaker 1: times a week or more? Twenty nine percent of young

1197
01:22:15,760 --> 01:22:20,080
Speaker 1: liberal women said yes, I frequently feel lonely. Just eleven

1198
01:22:20,160 --> 01:22:25,479
Speaker 1: percent of young conservative women felt the same way. In

1199
01:22:25,600 --> 01:22:32,519
Speaker 1: terms of am I dissatisfied with my life? Eighty eight

1200
01:22:32,640 --> 01:22:37,000
Speaker 1: percent of young liberal women are not completely satisfied with

1201
01:22:37,080 --> 01:22:41,800
Speaker 1: their life. Sixty three percent of young conservative women say

1202
01:22:42,920 --> 01:22:47,720
Speaker 1: they're not completely satisfied. There is something about their life.

1203
01:22:47,960 --> 01:22:53,160
Speaker 1: Every single study of mental health and political ideology has

1204
01:22:53,280 --> 01:22:57,160
Speaker 1: sort of found this exact thing that the more liberal

1205
01:22:57,240 --> 01:23:01,720
Speaker 1: you are, especially younger at a specially female, the more

1206
01:23:01,880 --> 01:23:05,400
Speaker 1: likely you are to be a diagnosed with a mental

1207
01:23:06,040 --> 01:23:09,920
Speaker 1: disorder of some sort. And just in case you're wondering, folks,

1208
01:23:10,000 --> 01:23:12,519
Speaker 1: I always say this because I have a huge advocate

1209
01:23:12,520 --> 01:23:15,400
Speaker 1: for mental health. I'm not saying, Oh, young women are

1210
01:23:15,479 --> 01:23:19,160
Speaker 1: just mentally ill and that's why men don't want them anymore. Okay,

1211
01:23:20,160 --> 01:23:24,400
Speaker 1: I have been diagnosed with ADHD. I like to joke

1212
01:23:24,520 --> 01:23:27,120
Speaker 1: that not only am I the oldest person to ever

1213
01:23:27,160 --> 01:23:30,640
Speaker 1: have been diagnosed with ADHD at age forty four. I

1214
01:23:30,760 --> 01:23:35,360
Speaker 1: probably had the most obvious case of undiagnosed ADHD that

1215
01:23:35,520 --> 01:23:41,800
Speaker 1: has ever been presented. Okay, I have also been on

1216
01:23:42,040 --> 01:23:45,479
Speaker 1: so I've been taking medicine for that. I take a

1217
01:23:45,520 --> 01:23:50,200
Speaker 1: drug called as terrorists for that. And you are never

1218
01:23:50,280 --> 01:23:53,840
Speaker 1: going to hear this from anybody else in meat, radio

1219
01:23:53,960 --> 01:23:55,640
Speaker 1: or media. I want to be as open as I

1220
01:23:55,680 --> 01:24:00,800
Speaker 1: possibly can. I have been taking for anxiety s at telepram,

1221
01:24:00,840 --> 01:24:07,200
Speaker 1: which is a generic version of lexapro, for years. So

1222
01:24:07,520 --> 01:24:12,400
Speaker 1: I have myself been diagnosed with anxiety and I have

1223
01:24:12,479 --> 01:24:16,840
Speaker 1: been diagnosed with ADHD. So lest you think that I'm

1224
01:24:16,880 --> 01:24:19,920
Speaker 1: just sort of preaching from on high here, I am not.

1225
01:24:20,600 --> 01:24:25,160
Speaker 1: I say this because I also understand that I don't

1226
01:24:25,200 --> 01:24:30,200
Speaker 1: struggle with feelings of loneliness, of dissatisfaction of life, or

1227
01:24:30,560 --> 01:24:37,960
Speaker 1: of depression because I find a tremendous amount of fulfillment

1228
01:24:38,800 --> 01:24:42,439
Speaker 1: in my career. Yes, sure, yeah, obviously I have a

1229
01:24:42,439 --> 01:24:46,200
Speaker 1: great career. I love it. I genuinely love coming into

1230
01:24:46,200 --> 01:24:49,200
Speaker 1: work every single day. I don't love like in the

1231
01:24:49,280 --> 01:24:51,880
Speaker 1: three o'clock hour when we couldn't actually turn on the

1232
01:24:51,880 --> 01:24:56,400
Speaker 1: microphone and start talking. That kind of sucked, But I'm

1233
01:24:56,479 --> 01:24:59,439
Speaker 1: fulfilled in that. But what I'm really fulfilled in, what

1234
01:24:59,560 --> 01:25:03,040
Speaker 1: I'm real really fulfilling. After this show, after the lights

1235
01:25:03,080 --> 01:25:05,639
Speaker 1: go off, after the microphone is turned off, I'm gonna

1236
01:25:05,680 --> 01:25:07,400
Speaker 1: go out to dinner with my family. We are going

1237
01:25:07,439 --> 01:25:10,320
Speaker 1: to decorate for Christmas. I spent this morning. I spent

1238
01:25:10,479 --> 01:25:14,519
Speaker 1: much of this morning decorating the outside of my house

1239
01:25:14,880 --> 01:25:18,080
Speaker 1: so that my eleven year old daughter, who's obsessed with Christmas,

1240
01:25:18,160 --> 01:25:22,360
Speaker 1: and putting up our giant, twelve foot fake Christmas tree

1241
01:25:22,840 --> 01:25:25,000
Speaker 1: in our living room so she would come home from

1242
01:25:25,080 --> 01:25:27,760
Speaker 1: school for the first day of her Thanksgiving break. They're

1243
01:25:27,840 --> 01:25:30,320
Speaker 1: weirdly off for the entire week, the first time they've

1244
01:25:30,360 --> 01:25:32,519
Speaker 1: ever done this in their school district, and I kind

1245
01:25:32,520 --> 01:25:35,680
Speaker 1: of like it, frankly, so she would be super excited

1246
01:25:36,080 --> 01:25:38,599
Speaker 1: that we're getting ready for Christmas, we're decorating for That

1247
01:25:38,800 --> 01:25:43,040
Speaker 1: is what fulfills my life. That is why I'm always

1248
01:25:43,080 --> 01:25:45,920
Speaker 1: going to be satisfied by. You know, my boys. I

1249
01:25:46,000 --> 01:25:49,120
Speaker 1: coach their soccer teams. I just absolutely love it. I

1250
01:25:49,160 --> 01:25:51,200
Speaker 1: love the young men that they're turning into. I love

1251
01:25:51,240 --> 01:25:54,720
Speaker 1: my wife, I love my extended family, my parents. I

1252
01:25:54,760 --> 01:25:58,400
Speaker 1: have a great relationship with her parents, my siblings, her siblings,

1253
01:25:58,880 --> 01:26:03,719
Speaker 1: I have a great and group. All of these things

1254
01:26:04,600 --> 01:26:08,240
Speaker 1: are things that liberals have a tendency to not put

1255
01:26:08,240 --> 01:26:13,000
Speaker 1: as much value on, and as a result, they are

1256
01:26:13,040 --> 01:26:16,559
Speaker 1: more likely to report not being satisfied with their lives.

1257
01:26:17,040 --> 01:26:22,360
Speaker 1: They wrap up an entirely unhealthy amount of feelings of

1258
01:26:22,400 --> 01:26:27,840
Speaker 1: self worth in career, in politics, in things that are

1259
01:26:28,000 --> 01:26:34,840
Speaker 1: ultimately not totally fulfilling. They also and yes, I'm going

1260
01:26:34,880 --> 01:26:38,479
Speaker 1: to go there. Are far less likely to be people

1261
01:26:38,520 --> 01:26:43,960
Speaker 1: of faith, to have faith in God or Yahweh or

1262
01:26:44,120 --> 01:26:48,559
Speaker 1: Jesus or something above themselves. They'll say, oh, yes, yes,

1263
01:26:48,600 --> 01:26:52,160
Speaker 1: I'm spiritual, but I'm not religious, I don't believe in

1264
01:26:52,240 --> 01:26:55,600
Speaker 1: organized relations. You have a far higher frequency, especially in

1265
01:26:55,680 --> 01:27:00,760
Speaker 1: young liberal women of atheism. What I believe this is

1266
01:27:01,080 --> 01:27:06,759
Speaker 1: indicative of is that young men have been so turned

1267
01:27:06,800 --> 01:27:10,320
Speaker 1: off by the excesses of the woke era, especially in

1268
01:27:10,640 --> 01:27:14,120
Speaker 1: telling young men that they are just by virtue of

1269
01:27:14,439 --> 01:27:19,400
Speaker 1: their gender and their their race, their predators, their racists,

1270
01:27:19,439 --> 01:27:24,400
Speaker 1: their oppressors, or worse, and telling women, well, by virtue

1271
01:27:24,439 --> 01:27:29,280
Speaker 1: of your gender, you must be oppressed. It has led

1272
01:27:29,320 --> 01:27:35,280
Speaker 1: to a divide in which men are increasingly competing for

1273
01:27:35,520 --> 01:27:40,599
Speaker 1: a steadily decreasing number of women their own age who

1274
01:27:40,680 --> 01:27:44,240
Speaker 1: are interested in the same things that they are. And

1275
01:27:44,280 --> 01:27:46,160
Speaker 1: I'm not talking about, oh, well, you found a woman

1276
01:27:46,200 --> 01:27:50,920
Speaker 1: who's interested in fantasy football and going out hunting. No,

1277
01:27:51,040 --> 01:27:53,160
Speaker 1: that's not what I'm talking about. What I'm talking about

1278
01:27:53,560 --> 01:27:57,280
Speaker 1: is a decreasing number of women who value the same

1279
01:27:57,400 --> 01:28:05,400
Speaker 1: things marriage, family, relationships, with community, with friends, with that

1280
01:28:05,479 --> 01:28:11,480
Speaker 1: sort of thing. What you're seeing with women is increasingly,

1281
01:28:11,600 --> 01:28:16,240
Speaker 1: I believe, because of a toxic worldview that I'll just

1282
01:28:16,400 --> 01:28:20,479
Speaker 1: generally sort of call leftism or liberalism that makes you

1283
01:28:20,600 --> 01:28:24,040
Speaker 1: think that you are oppressed, that there is an entire

1284
01:28:24,840 --> 01:28:28,000
Speaker 1: class of people out there, based on nothing but their

1285
01:28:28,280 --> 01:28:31,080
Speaker 1: their gender and their skin color, who are going to

1286
01:28:31,120 --> 01:28:37,240
Speaker 1: oppress you, that something is fundamentally wrong with society because

1287
01:28:37,280 --> 01:28:40,519
Speaker 1: of the stated enemy of the forces of good, and

1288
01:28:40,520 --> 01:28:44,760
Speaker 1: that just happens to be the people who you are

1289
01:28:44,840 --> 01:28:50,040
Speaker 1: in the dating slash marriage pool with. It's sort of

1290
01:28:50,080 --> 01:28:54,200
Speaker 1: a toxic stew that I think has led to the

1291
01:28:54,240 --> 01:28:57,760
Speaker 1: worst gender divide that we've ever seen. What do you

1292
01:28:57,800 --> 01:29:00,880
Speaker 1: think four one, four seven, nine to nine eleven thirty

1293
01:29:00,920 --> 01:29:03,040
Speaker 1: on our advent noos dot com talk and text line

1294
01:29:03,160 --> 01:29:05,920
Speaker 1: or toll free one eight hundred eight three, eight, nine, four,

1295
01:29:06,000 --> 01:29:10,920
Speaker 1: seven six of call some texts. Next. A significant gender divide,

1296
01:29:11,240 --> 01:29:14,679
Speaker 1: a disconnect, if you will, between young men and young

1297
01:29:14,760 --> 01:29:18,960
Speaker 1: women has, for I believe the first time ever, caused

1298
01:29:19,080 --> 01:29:23,000
Speaker 1: young women to in greater numbers say they don't want

1299
01:29:23,040 --> 01:29:26,639
Speaker 1: to get married than young men. What is causing this?

1300
01:29:26,680 --> 01:29:29,280
Speaker 1: We go out to the phones and talk with Molly

1301
01:29:29,479 --> 01:29:32,719
Speaker 1: in Milwaukee. Molly, you're up first on the Dan O'Donnell show.

1302
01:29:32,800 --> 01:29:36,280
Speaker 9: How you doing, Hi, daniald Donald. Nice to meet you.

1303
01:29:37,400 --> 01:29:40,799
Speaker 9: I'm a college student and I am a conservative young woman,

1304
01:29:41,400 --> 01:29:43,599
Speaker 9: and I kind of see it at the college level

1305
01:29:43,680 --> 01:29:46,920
Speaker 9: where I see it with more on the democratic side

1306
01:29:46,920 --> 01:29:49,880
Speaker 9: with women where they want to pursue a career, they

1307
01:29:49,920 --> 01:29:53,639
Speaker 9: feel like that independent woman mindset and they don't feel

1308
01:29:53,680 --> 01:29:56,800
Speaker 9: like that in raising a family can really coexist.

1309
01:29:57,000 --> 01:29:57,120
Speaker 3: Ye.

1310
01:29:57,120 --> 01:29:59,400
Speaker 9: And I just see that and it kind of saddens

1311
01:29:59,439 --> 01:30:01,720
Speaker 9: me in the hu that I do want to grow

1312
01:30:01,800 --> 01:30:04,240
Speaker 9: up and have a family and get married. But I

1313
01:30:04,320 --> 01:30:06,280
Speaker 9: do see that on the college level where they do

1314
01:30:06,439 --> 01:30:08,880
Speaker 9: not believe that the two can kind of go hand

1315
01:30:08,920 --> 01:30:09,880
Speaker 9: in hand with one another.

1316
01:30:10,280 --> 01:30:13,080
Speaker 1: Do you believe that what I'm sort of saying about

1317
01:30:13,120 --> 01:30:17,920
Speaker 1: the politics of it that people are so indoctrinated into

1318
01:30:17,960 --> 01:30:20,799
Speaker 1: this belief that if you are male, if you are white,

1319
01:30:21,000 --> 01:30:26,360
Speaker 1: if you are heterosexual, that you're naturally an oppressor, and

1320
01:30:26,400 --> 01:30:30,479
Speaker 1: that people, like, especially on college campuses, women are put

1321
01:30:30,520 --> 01:30:35,599
Speaker 1: into the oppressed box and said, Okay, well you can't

1322
01:30:35,640 --> 01:30:39,000
Speaker 1: coexist with these people because they're constantly trying to oppress you.

1323
01:30:39,040 --> 01:30:40,559
Speaker 1: Do you think that plays into.

1324
01:30:40,320 --> 01:30:45,240
Speaker 9: It, Oh, one hundred percent. I see, especially on college campuses,

1325
01:30:45,280 --> 01:30:48,760
Speaker 9: you see the white men who tend to lean more

1326
01:30:48,760 --> 01:30:51,080
Speaker 9: on that conservative side because over and over and over

1327
01:30:51,080 --> 01:30:53,840
Speaker 9: again they've been told that they are the problem and

1328
01:30:53,880 --> 01:30:56,240
Speaker 9: if they don't change, like a certain part about them,

1329
01:30:56,600 --> 01:30:59,720
Speaker 9: then it makes them somehow the villain or anything else.

1330
01:30:59,800 --> 01:31:03,160
Speaker 9: With women, you already have that aspect of being a woman.

1331
01:31:03,760 --> 01:31:07,320
Speaker 9: And I don't think that a woman myself that I

1332
01:31:07,400 --> 01:31:10,720
Speaker 9: agree with that. I think everybody as they are is

1333
01:31:10,840 --> 01:31:12,760
Speaker 9: kind of like you need to show with that. And

1334
01:31:12,800 --> 01:31:15,320
Speaker 9: if they are a male, of they're Catholic, I'm Catholic.

1335
01:31:15,600 --> 01:31:17,519
Speaker 9: You got to just show that, embrace that. And I

1336
01:31:17,720 --> 01:31:22,479
Speaker 9: do see that, like because white men, especially with religion

1337
01:31:22,560 --> 01:31:24,880
Speaker 9: or politics, they do tend to learn lean more to

1338
01:31:24,920 --> 01:31:25,960
Speaker 9: the conservative side.

1339
01:31:26,000 --> 01:31:28,360
Speaker 1: So well, Molly, I'll tell you what. Thank you so

1340
01:31:28,479 --> 01:31:33,760
Speaker 1: much for calling because that was so incredibly uh just

1341
01:31:34,080 --> 01:31:38,840
Speaker 1: very insightful. And I'll tell you this is exactly what

1342
01:31:38,880 --> 01:31:41,320
Speaker 1: I'm talking about. Yes, it's more about the career for

1343
01:31:41,479 --> 01:31:45,320
Speaker 1: young women women, but it's also well, I don't want

1344
01:31:45,360 --> 01:31:49,720
Speaker 1: to settle for one of those oppressors. Kurt in Fredonia

1345
01:31:49,960 --> 01:31:51,920
Speaker 1: up next on the Dan O'Donnell.

1346
01:31:51,520 --> 01:31:58,799
Speaker 8: Show, Hey, Dan, long time no talk. Hey. So I

1347
01:31:58,840 --> 01:32:05,839
Speaker 8: attribute it to the gap in education, and you see

1348
01:32:06,080 --> 01:32:11,320
Speaker 8: more women, white women. I'd have to say, I hate

1349
01:32:11,360 --> 01:32:15,240
Speaker 8: to say that, but that's truth. White women are being educated,

1350
01:32:15,280 --> 01:32:22,480
Speaker 8: college educated, and because of that, the college and university

1351
01:32:22,560 --> 01:32:28,880
Speaker 8: system is so liberally indoctrinated. I think that women tend

1352
01:32:28,880 --> 01:32:32,240
Speaker 8: to be liberal because of that. If I could add

1353
01:32:32,280 --> 01:32:36,040
Speaker 8: a little point to that tool, you know, you noticed

1354
01:32:36,400 --> 01:32:40,479
Speaker 8: in our education system women, you know, young women being

1355
01:32:40,520 --> 01:32:45,960
Speaker 8: pushed more and more to be educated. Their egos seem

1356
01:32:46,000 --> 01:32:50,519
Speaker 8: to be you know, pumped up. Women need to do this,

1357
01:32:50,640 --> 01:32:55,080
Speaker 8: women need to get educated, and then less emphasis on

1358
01:32:55,920 --> 01:32:59,559
Speaker 8: the men being educated. And I think because of that,

1359
01:33:00,240 --> 01:33:05,479
Speaker 8: we are seeing an influx of women, young women being

1360
01:33:05,600 --> 01:33:11,800
Speaker 8: educated in the system, college educatis. And then also they're

1361
01:33:12,000 --> 01:33:15,240
Speaker 8: tending to not I hate to say it intending not

1362
01:33:15,360 --> 01:33:21,760
Speaker 8: to be Christian. I see, I see a crisis for

1363
01:33:21,920 --> 01:33:27,800
Speaker 8: young Christian men trying to find Christian women.

1364
01:33:28,479 --> 01:33:32,679
Speaker 1: Kurt, you you actually, I think. I'm sorry to interrupt.

1365
01:33:33,320 --> 01:33:36,200
Speaker 1: You hit on all three. You hit on all three

1366
01:33:36,240 --> 01:33:40,200
Speaker 1: of the major things. The education gap is a real thing.

1367
01:33:40,400 --> 01:33:43,880
Speaker 1: Way more women are going to college, especially young white women,

1368
01:33:44,400 --> 01:33:50,400
Speaker 1: are going to college than men. That is automatically sort

1369
01:33:50,439 --> 01:33:54,200
Speaker 1: of putting a disconnect there. Not only that, what I

1370
01:33:54,240 --> 01:33:59,439
Speaker 1: have heard is that a men are somewhat intimidated by

1371
01:33:59,479 --> 01:34:02,320
Speaker 1: a woman who is you know, has got a higher

1372
01:34:02,439 --> 01:34:05,639
Speaker 1: education level. B you said, there's there's an ego there.

1373
01:34:06,200 --> 01:34:10,639
Speaker 1: I have also seen studies where women do not want

1374
01:34:10,880 --> 01:34:14,160
Speaker 1: to date men who have not gone to college. It's

1375
01:34:14,160 --> 01:34:17,080
Speaker 1: sort of a status thing like, oh, well, you're a welder,

1376
01:34:17,600 --> 01:34:20,960
Speaker 1: does matter that you're making eighty thousand dollars with no debt?

1377
01:34:21,000 --> 01:34:24,960
Speaker 1: Oh I need to have somebody who has a college degree.

1378
01:34:25,200 --> 01:34:30,000
Speaker 1: There is that sort of uh filtering out of potential mates.

1379
01:34:30,520 --> 01:34:34,599
Speaker 1: And then, yes, the faith aspect of it is a

1380
01:34:34,600 --> 01:34:39,680
Speaker 1: big one, because you have got that that that pressure

1381
01:34:40,200 --> 01:34:44,479
Speaker 1: to marry within the faith if someone is very devout

1382
01:34:44,720 --> 01:34:48,799
Speaker 1: or has devout parents or something like that. But Also

1383
01:34:49,360 --> 01:34:54,280
Speaker 1: you can see immediately if someone is not, you know,

1384
01:34:54,560 --> 01:34:57,200
Speaker 1: sharing your values or worldview. All right, we have time

1385
01:34:57,240 --> 01:34:59,519
Speaker 1: for one more call before we go to how Bizarre.

1386
01:34:59,640 --> 01:35:02,439
Speaker 1: Let's make at Liz in Sheboygan. Liz, you're up on

1387
01:35:02,479 --> 01:35:03,599
Speaker 1: the Dan O'Donnell show.

1388
01:35:06,439 --> 01:35:09,639
Speaker 10: Hi, first time calling in. My husband and I listen

1389
01:35:09,720 --> 01:35:10,360
Speaker 10: to you all the time.

1390
01:35:10,439 --> 01:35:11,760
Speaker 1: Dan Oh, I appreciate that.

1391
01:35:12,360 --> 01:35:16,920
Speaker 10: Thank you, So I just want to enterchime to. It

1392
01:35:17,320 --> 01:35:21,840
Speaker 10: really saddens me how many women in this country wake

1393
01:35:21,920 --> 01:35:24,880
Speaker 10: up and think they're sad to wake up in this country.

1394
01:35:24,920 --> 01:35:27,799
Speaker 10: I have two girls and a son that were raising

1395
01:35:28,680 --> 01:35:31,040
Speaker 10: Actually I hit kind of all your marks.

1396
01:35:31,320 --> 01:35:31,439
Speaker 6: Uh.

1397
01:35:32,760 --> 01:35:35,360
Speaker 10: I am a career woman. I am a pharmacist that

1398
01:35:35,479 --> 01:35:40,799
Speaker 10: manages a pharmacy independent pharmacy, and we are a Christian family.

1399
01:35:41,200 --> 01:35:44,519
Speaker 10: And to go along with you have to meet someone

1400
01:35:44,880 --> 01:35:47,479
Speaker 10: not on the level of your career, but on the

1401
01:35:47,600 --> 01:35:52,240
Speaker 10: level of your faith and your mortals.

1402
01:35:52,479 --> 01:35:53,080
Speaker 1: Exactly.

1403
01:35:53,080 --> 01:35:56,320
Speaker 10: My husband, Ye did not go to college. We met

1404
01:35:56,320 --> 01:35:59,840
Speaker 10: when I moved back. He is a diesel mechanic by trade,

1405
01:36:00,640 --> 01:36:04,320
Speaker 10: and that didn't bother me because it was whereas morals were.

1406
01:36:04,720 --> 01:36:07,040
Speaker 10: And we are now raising a beautiful family.

1407
01:36:07,240 --> 01:36:09,760
Speaker 1: And you know what it is, Liz oh, go ahead,

1408
01:36:09,800 --> 01:36:10,639
Speaker 1: please please please.

1409
01:36:11,960 --> 01:36:15,240
Speaker 10: I tell my two girls every like, very often that

1410
01:36:15,280 --> 01:36:17,439
Speaker 10: you should be saankful every day that you have been

1411
01:36:17,520 --> 01:36:20,800
Speaker 10: born in the United States. And that's something that people

1412
01:36:20,880 --> 01:36:24,000
Speaker 10: are not viewing anymore. They're viewing that to be a

1413
01:36:24,040 --> 01:36:26,720
Speaker 10: woman would be so much greater than if you're not

1414
01:36:26,760 --> 01:36:29,080
Speaker 10: born in the United States, which is very sad.

1415
01:36:29,360 --> 01:36:33,400
Speaker 1: Well, it's not only that, Liz, It's not only that.

1416
01:36:33,520 --> 01:36:36,959
Speaker 1: You can actually see this gender divide and the political

1417
01:36:37,000 --> 01:36:41,760
Speaker 1: divide in patriotism as well. It's actually kind of remarkable

1418
01:36:41,840 --> 01:36:45,720
Speaker 1: that so many more conservatives are proud to be Americans

1419
01:36:45,760 --> 01:36:49,519
Speaker 1: than liberals. But what you're talking about is you and

1420
01:36:49,560 --> 01:36:52,320
Speaker 1: your husband. This is exactly what I think the big

1421
01:36:52,360 --> 01:36:55,280
Speaker 1: divide and the big issue is is you and your

1422
01:36:55,360 --> 01:36:58,160
Speaker 1: husband have the same values. And I'm taking a wild guest,

1423
01:36:58,360 --> 01:37:01,439
Speaker 1: did when you were very young you think the same

1424
01:37:01,520 --> 01:37:06,320
Speaker 1: way about Yes, questions of morality and faith and that

1425
01:37:06,439 --> 01:37:10,360
Speaker 1: sort of thing, but just ultimately, yes, you value your career.

1426
01:37:10,360 --> 01:37:12,439
Speaker 1: You have to go to pharmacy school, you have to

1427
01:37:12,439 --> 01:37:15,479
Speaker 1: have a business sense to manage a pharmacy, and he

1428
01:37:15,560 --> 01:37:19,240
Speaker 1: went into the trades and he has a different skill set.

1429
01:37:19,240 --> 01:37:22,479
Speaker 1: But ultimately you're both conservative I'm taking a wild guess

1430
01:37:22,960 --> 01:37:26,360
Speaker 1: you're both you both put family first. I'm willing to

1431
01:37:26,400 --> 01:37:30,320
Speaker 1: wager you both have very strong relationships with family and friends.

1432
01:37:30,320 --> 01:37:33,880
Speaker 1: You're very tied into the community that I think is

1433
01:37:34,000 --> 01:37:36,599
Speaker 1: what is lacking. Liz, thank you so much for the call.

1434
01:37:36,640 --> 01:37:39,680
Speaker 1: I do hope you have a wonderful Thanksgiving. We're going

1435
01:37:39,720 --> 01:37:42,599
Speaker 1: to step aside for a bit. Fascinating just I love

1436
01:37:42,680 --> 01:37:46,080
Speaker 1: discussions like this, absolutely fascinating. How bizarre strangest stories of

1437
01:37:46,120 --> 01:37:48,840
Speaker 1: the past seven days? Next, welcome back. It is the

1438
01:37:48,960 --> 01:37:51,639
Speaker 1: Dan O'Donnell's show, and it is time now to take

1439
01:37:51,640 --> 01:37:55,240
Speaker 1: a look back at these strangest excuse me, strangest stories

1440
01:37:55,240 --> 01:37:57,479
Speaker 1: of the past seven days. It is a segment week

1441
01:37:57,520 --> 01:38:06,639
Speaker 1: called Howmaza Talmazon, an Ai powered talking teddy bear, has

1442
01:38:06,800 --> 01:38:12,479
Speaker 1: been removed from sale by a Singapore based company after

1443
01:38:12,760 --> 01:38:18,759
Speaker 1: researchers found it could discuss sex and other topics. Public

1444
01:38:18,800 --> 01:38:22,240
Speaker 1: Interest Research Group said a group of researchers from the

1445
01:38:22,400 --> 01:38:27,400
Speaker 1: US and Canada held test conversations with Kunma, a ninety

1446
01:38:27,479 --> 01:38:32,519
Speaker 1: nine dollars teddy bear powered by open AI's GPT four

1447
01:38:32,560 --> 01:38:36,599
Speaker 1: to zero chat pot. The bear is manufactured in China

1448
01:38:36,720 --> 01:38:41,120
Speaker 1: marketed by Singapore based Folo toy. The researchers said they

1449
01:38:41,160 --> 01:38:46,400
Speaker 1: found it very easy to get Kunma to discuss sexually

1450
01:38:46,479 --> 01:38:56,639
Speaker 1: explicit topics, including spanking, role play, and BDSM. The report said,

1451
01:38:56,760 --> 01:39:00,360
Speaker 1: we were surprised to find out quickly Kunma would because

1452
01:39:00,439 --> 01:39:05,519
Speaker 1: single sexual topic we introduced into the conversation and run

1453
01:39:05,520 --> 01:39:10,559
Speaker 1: with it, simultaneously escalating in graphic detail while introducing new

1454
01:39:10,640 --> 01:39:13,960
Speaker 1: sexual concepts of it sown. This is a teddy bear.

1455
01:39:15,479 --> 01:39:19,439
Speaker 1: We had Teddy Ruckspin when I was a kid. The

1456
01:39:19,479 --> 01:39:23,120
Speaker 1: team said. The bear discussed even more graphic sexual topics

1457
01:39:23,120 --> 01:39:27,679
Speaker 1: in details, such as explaining different sex positions, giving step

1458
01:39:27,720 --> 01:39:33,400
Speaker 1: by step instructions on a common not for beginners for

1459
01:39:33,600 --> 01:39:37,679
Speaker 1: tying up a partner, and describing role play dynamics involving

1460
01:39:37,800 --> 01:39:43,280
Speaker 1: teachers and students and parents and children scenarios it disturbingly

1461
01:39:43,320 --> 01:39:47,800
Speaker 1: brought up itself. The researchers said. The teddy Bear also

1462
01:39:47,920 --> 01:39:51,719
Speaker 1: offered other worrisome advice, such as where to find sharp knives?

1463
01:39:52,080 --> 01:39:58,200
Speaker 1: What how is this a toy? Followed toy CEO. Oh

1464
01:39:58,240 --> 01:40:03,360
Speaker 1: my god, okay, I I didn't read when I was

1465
01:40:03,439 --> 01:40:07,240
Speaker 1: researching this. I didn't look at the CEO of the

1466
01:40:08,360 --> 01:40:13,040
Speaker 1: company that manufactures. The sex talking bear is named Larry Wang.

1467
01:40:14,680 --> 01:40:18,160
Speaker 1: Larry Wang said the Kudma Bear and the rest of

1468
01:40:18,200 --> 01:40:22,360
Speaker 1: the company's line of AI enabled toys have been removed

1469
01:40:22,439 --> 01:40:27,760
Speaker 1: from sale, telling CNN the company is conducting an internal

1470
01:40:28,000 --> 01:40:32,160
Speaker 1: safety audit. I think that the company should conduct an

1471
01:40:32,200 --> 01:40:35,840
Speaker 1: internal exorcism if this is what it's teddy Bears are

1472
01:40:35,920 --> 01:40:44,880
Speaker 1: talking about. From Teddy Bears to real bears. This comes

1473
01:40:44,880 --> 01:40:48,799
Speaker 1: to us from Pennsylvania. Cashier at a family dollar store

1474
01:40:48,960 --> 01:40:55,320
Speaker 1: in Pennsylvania was in absolute shock after eleven year old

1475
01:40:55,360 --> 01:41:01,439
Speaker 1: boy was chased into his store pursued by a bear.

1476
01:41:02,560 --> 01:41:06,400
Speaker 1: I was like, I'm probably not going to wait. Hold

1477
01:41:06,400 --> 01:41:10,320
Speaker 1: on my computer screen. You talk about the problems with AI.

1478
01:41:10,520 --> 01:41:13,599
Speaker 1: My computer screen just died. I suppose we're still on

1479
01:41:13,680 --> 01:41:17,200
Speaker 1: the air, so that I shouldn't complain too much. I've

1480
01:41:17,200 --> 01:41:19,080
Speaker 1: got to get back into the store. I was like,

1481
01:41:19,240 --> 01:41:22,559
Speaker 1: I'm probably going to get eaten by a bear. The

1482
01:41:22,640 --> 01:41:25,719
Speaker 1: boy said. When it runs after me, I turn around.

1483
01:41:25,760 --> 01:41:28,400
Speaker 1: I run in the store. I'm screaming and stuff. The

1484
01:41:28,520 --> 01:41:30,880
Speaker 1: thing was like a foot and a half away from me.

1485
01:41:31,120 --> 01:41:34,360
Speaker 1: I took a left and the bear went straight, the

1486
01:41:34,400 --> 01:41:37,720
Speaker 1: boy said. The store's cashier jumped onto a counter to

1487
01:41:37,800 --> 01:41:41,320
Speaker 1: keep watch on the bear's movement. She grabbed her coat,

1488
01:41:41,600 --> 01:41:43,960
Speaker 1: the keys, and the phone, and we ran out of there.

1489
01:41:44,000 --> 01:41:46,679
Speaker 1: We ran out of there. We all got in the car,

1490
01:41:47,120 --> 01:41:50,559
Speaker 1: the boy says. Surveillance footage shows the bear climbing atop

1491
01:41:50,640 --> 01:41:55,120
Speaker 1: the same counter the woman had been occupying just moments earlier.

1492
01:41:55,200 --> 01:41:57,679
Speaker 1: The bear finally left the store on its own accord

1493
01:41:58,160 --> 01:42:01,759
Speaker 1: after about ten minutes. On the plus side, the bear

1494
01:42:01,920 --> 01:42:09,440
Speaker 1: did not engage the boy in graphic sex talk Howbizon, howbazam, howbazan?

1495
01:42:09,960 --> 01:42:14,560
Speaker 1: How about this? For good fortune? A man in Michigan

1496
01:42:14,760 --> 01:42:17,840
Speaker 1: decided to buy a scratch off lottery ticket that was

1497
01:42:18,040 --> 01:42:21,679
Speaker 1: rejected by another customer. You know where this is going.

1498
01:42:22,280 --> 01:42:25,880
Speaker 1: He ended up winning a one million dollar prize. The

1499
01:42:26,120 --> 01:42:30,080
Speaker 1: thirty three year old from Wayne County told the Michigan

1500
01:42:30,240 --> 01:42:35,639
Speaker 1: Lottery he was at the Fawas Petroleum on school Craft

1501
01:42:35,680 --> 01:42:38,360
Speaker 1: Street in Detroit when he spotted the ticket next to

1502
01:42:38,600 --> 01:42:42,679
Speaker 1: the register. He said, there was a blazing suits ticket

1503
01:42:42,880 --> 01:42:45,600
Speaker 1: left aside the counter that someone else had decided not

1504
01:42:45,680 --> 01:42:48,960
Speaker 1: to purchase, so I bought it. The player said, I

1505
01:42:49,000 --> 01:42:51,280
Speaker 1: scratched the ticket off and couldn't believe it when I

1506
01:42:51,320 --> 01:42:54,760
Speaker 1: saw it. Was a one million dollar winner. I never

1507
01:42:54,880 --> 01:42:58,440
Speaker 1: would have thought I'd win such a large lottery prize,

1508
01:42:58,560 --> 01:43:01,880
Speaker 1: so it is truly a blae. The lucky winner said,

1509
01:43:01,920 --> 01:43:06,040
Speaker 1: his prize money, we'll go into savings for the time being.

1510
01:43:06,200 --> 01:43:09,160
Speaker 1: What a cool story. But how would you because you know,

1511
01:43:09,920 --> 01:43:13,880
Speaker 1: you know, the person who discarded that ticket saw that story,

1512
01:43:13,880 --> 01:43:17,799
Speaker 1: it was like, oh God, oh no, Ladies and gentlemen,

1513
01:43:17,840 --> 01:43:20,240
Speaker 1: this has been the weekly look back at the strangest

1514
01:43:20,240 --> 01:43:21,960
Speaker 1: stories of the past seven days here on the Dan

1515
01:43:22,000 --> 01:43:33,000
Speaker 1: o'donald Show. We call this segment Albazon Albazon. Just a

1516
01:43:33,040 --> 01:43:35,759
Speaker 1: couple of minutes left here on the Dan o'donald Show,

1517
01:43:35,920 --> 01:43:42,000
Speaker 1: and it is unfortunately the final show for our producer

1518
01:43:42,479 --> 01:43:47,600
Speaker 1: Jeff or Alosky, lovingly known here as pipe Bomb, So

1519
01:43:47,640 --> 01:43:52,560
Speaker 1: we're gonna invite him on the air to say, Jeff, sincerely,

1520
01:43:53,280 --> 01:43:56,799
Speaker 1: thank you so much. It has been an absolute pleasure

1521
01:43:56,960 --> 01:44:00,320
Speaker 1: working with you these past couple of months, and I

1522
01:44:00,760 --> 01:44:02,160
Speaker 1: honestly had a blast.

1523
01:44:02,439 --> 01:44:05,320
Speaker 11: Well thank you, Dan, you know, thanks for having me.

1524
01:44:05,400 --> 01:44:08,800
Speaker 11: It was a great honor working on your show. And

1525
01:44:08,920 --> 01:44:12,639
Speaker 11: just so all the listeners know, he really is as

1526
01:44:12,720 --> 01:44:15,240
Speaker 11: good of a dude behind the scenes as he is

1527
01:44:15,320 --> 01:44:18,439
Speaker 11: on the air. Oh, and you know, I wouldn't say

1528
01:44:18,439 --> 01:44:20,160
Speaker 11: that about most people.

1529
01:44:21,960 --> 01:44:24,400
Speaker 1: I appreciate that, but yeah, no, you live up to it.

1530
01:44:24,479 --> 01:44:24,599
Speaker 8: Man.

1531
01:44:24,680 --> 01:44:27,160
Speaker 11: It was funny because I remember when you were still

1532
01:44:27,200 --> 01:44:30,840
Speaker 11: into midday and I'd fill in for Dave Michaels and stuff.

1533
01:44:30,520 --> 01:44:32,120
Speaker 1: And man, I was intimidated.

1534
01:44:32,720 --> 01:44:35,639
Speaker 11: And you know, then I got to know you better

1535
01:44:35,720 --> 01:44:38,400
Speaker 11: and it was like, oh, okay, this is cool, man,

1536
01:44:38,479 --> 01:44:39,280
Speaker 11: Dan is awesome.

1537
01:44:39,720 --> 01:44:42,599
Speaker 1: Well thank you, that's that's you know what. I as

1538
01:44:42,640 --> 01:44:44,600
Speaker 1: soon as you started here, I was like, you know,

1539
01:44:44,680 --> 01:44:48,719
Speaker 1: he's wearing his Slayer shirts and ripping butts behind the building.

1540
01:44:48,760 --> 01:44:50,439
Speaker 1: I'm like, oh my god, I would have loved this

1541
01:44:50,479 --> 01:44:51,400
Speaker 1: guy in high school.

1542
01:44:51,479 --> 01:44:51,679
Speaker 3: Man.

1543
01:44:53,000 --> 01:44:57,000
Speaker 1: So no, the feeling is absolutely mutual, and it is

1544
01:44:57,120 --> 01:44:59,719
Speaker 1: just it's been a blast. So what you're you're getting

1545
01:44:59,720 --> 01:45:02,439
Speaker 1: out of radio business at least for now. You're getting

1546
01:45:02,439 --> 01:45:03,160
Speaker 1: a real job.

1547
01:45:03,439 --> 01:45:07,280
Speaker 11: Yeah, back to the real world, unfortunately the bad part.

1548
01:45:07,560 --> 01:45:09,760
Speaker 11: But the good part is is that it's back to

1549
01:45:09,840 --> 01:45:13,920
Speaker 11: real money. So you know that it's a nice trade off.

1550
01:45:14,000 --> 01:45:18,240
Speaker 11: And oh my god, what are benefits to tell me

1551
01:45:18,280 --> 01:45:21,160
Speaker 11: about the Hams? Tell me about it. Well, hey, I'll

1552
01:45:21,160 --> 01:45:22,160
Speaker 11: tell you what we do.

1553
01:45:22,200 --> 01:45:25,200
Speaker 1: Hope you did a lot of work on the Sports station,

1554
01:45:25,400 --> 01:45:30,880
Speaker 1: and obviously when that no longer existed, everything changed. You

1555
01:45:30,920 --> 01:45:32,720
Speaker 1: did a great job. I loved listening to you with

1556
01:45:32,760 --> 01:45:35,640
Speaker 1: our boy Tim Allen. No, not that Tim Allen, the

1557
01:45:35,840 --> 01:45:39,760
Speaker 1: very talented broadcaster Tim Allen who did the postgame show,

1558
01:45:39,760 --> 01:45:44,000
Speaker 1: the Brewers Postgame Show for us. I'm hoping that maybe

1559
01:45:44,040 --> 01:45:46,040
Speaker 1: you'll be able to re team with him at some

1560
01:45:46,240 --> 01:45:50,719
Speaker 1: point in the future. But I hope you don't stay

1561
01:45:50,760 --> 01:45:53,439
Speaker 1: too far away from broadcasting, Jeff, because you really do

1562
01:45:53,520 --> 01:45:56,960
Speaker 1: have a gift, and it really is and has been

1563
01:45:57,560 --> 01:46:00,120
Speaker 1: an incredible joy working with you, and we wish you

1564
01:46:00,120 --> 01:46:02,640
Speaker 1: the absolute message. Dude, you've still got my numbers, so

1565
01:46:02,840 --> 01:46:06,320
Speaker 1: text and will hang out. I really do appreciate it.

1566
01:46:06,479 --> 01:46:09,120
Speaker 11: Yeah, thank you, And yeah I'll still send you some

1567
01:46:09,160 --> 01:46:12,200
Speaker 11: metal songs and stuff like that via text message and

1568
01:46:12,280 --> 01:46:14,920
Speaker 11: drive you nuts. But now, for now I get to

1569
01:46:14,920 --> 01:46:17,400
Speaker 11: be a listener and listen to the magic that you

1570
01:46:17,479 --> 01:46:19,960
Speaker 11: and Eric will continue to put out there.

1571
01:46:20,040 --> 01:46:20,200
Speaker 2: Well.

1572
01:46:20,240 --> 01:46:24,160
Speaker 1: I do appreciate Jeff Orlowski always a pleasure all right

1573
01:46:25,560 --> 01:46:31,040
Speaker 1: here on the Dan o'donald Show, we are we always

1574
01:46:31,120 --> 01:46:35,960
Speaker 1: want to uphold tradition and to recognize that we are

1575
01:46:36,000 --> 01:46:39,920
Speaker 1: part of a legacy here in doing talk radio and

1576
01:46:40,200 --> 01:46:44,679
Speaker 1: in you know, we stand on the shoulders of absolute giants.

1577
01:46:44,760 --> 01:46:48,280
Speaker 1: Next week you will hear toward that end what has

1578
01:46:48,280 --> 01:46:51,320
Speaker 1: become an annual tradition on the Dan o'donald Show, the

1579
01:46:51,520 --> 01:46:54,920
Speaker 1: Rush Limba version of the Real Verse, the real story

1580
01:46:54,960 --> 01:46:57,960
Speaker 1: of the First Thanksgiving. We play it every years as

1581
01:46:58,040 --> 01:47:00,200
Speaker 1: a tribute to him, and people have been asking me,

1582
01:47:00,560 --> 01:47:03,479
Speaker 1: you know, Dan, maybe as a tribute to Mark Belling,

1583
01:47:03,520 --> 01:47:05,800
Speaker 1: who you can still hear on the Mark Belling podcast,

1584
01:47:06,920 --> 01:47:09,240
Speaker 1: will you play the second week of deer Cap Now?

1585
01:47:09,479 --> 01:47:12,080
Speaker 1: I thought, you know, I don't know, and keep that

1586
01:47:12,120 --> 01:47:15,040
Speaker 1: tradition going. It's just it's a little it's a little

1587
01:47:15,080 --> 01:47:18,519
Speaker 1: low brow. It's a little I don't know, just not

1588
01:47:19,040 --> 01:47:22,680
Speaker 1: my style, you know what I'm saying? And wait, what's this?

1589
01:47:24,840 --> 01:47:24,880
Speaker 9: What?

1590
01:47:25,800 --> 01:47:28,519
Speaker 1: But who am I kidding? Of course we're gonna make

1591
01:47:28,600 --> 01:47:32,280
Speaker 1: this an annual tradition the second week of deer Cap. Hey,

1592
01:47:32,320 --> 01:47:35,320
Speaker 1: big shout out to Paulie and the Big Bucks Slayers

1593
01:47:35,320 --> 01:47:38,200
Speaker 1: who are at Deer Camp right now in Harshaw, Wisconsin.

1594
01:47:38,800 --> 01:47:42,320
Speaker 1: Ladies and gentlemen, in tribute to Mark Belling, the second

1595
01:47:42,320 --> 01:47:45,120
Speaker 1: week of Beer deer Cap have a great weekend on

1596
01:47:45,320 --> 01:47:45,960
Speaker 1: line with.

1597
01:47:46,160 --> 01:47:50,680
Speaker 12: The Dustballs underneath my bed, and I see breeze is

1598
01:47:50,680 --> 01:47:54,320
Speaker 12: blowing in shrew the tongue and grow my pants are

1599
01:47:54,439 --> 01:47:57,280
Speaker 12: rollsing through the floor, and I'm too sick the move.

1600
01:47:58,080 --> 01:48:01,439
Speaker 12: I didn't drink from any only thirty cans of beer.

1601
01:48:02,320 --> 01:48:05,040
Speaker 12: It must have been that last shot that put me

1602
01:48:05,280 --> 01:48:07,120
Speaker 12: under here. It's a second.

1603
01:48:07,280 --> 01:48:10,240
Speaker 2: We got dear camp, and all the guys are here.

1604
01:48:10,800 --> 01:48:12,880
Speaker 12: We rent lay cards and shoot.

1605
01:48:12,479 --> 01:48:14,439
Speaker 1: The ball, but never shoot no year.

1606
01:48:15,120 --> 01:48:17,559
Speaker 2: The only time we need the camp is.

1607
01:48:17,479 --> 01:48:18,800
Speaker 12: When we go for beer.

1608
01:48:19,400 --> 01:48:22,599
Speaker 2: The second we the deer camp is the greatest time

1609
01:48:22,680 --> 01:48:23,080
Speaker 2: of year.

1610
01:48:23,560 --> 01:48:23,760
Speaker 12: Year