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Speaker 1: You're listening to The Buck Sexton Show podcast, make sure

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Speaker 1: you subscribe to the podcast on the iHeartRadio app or

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Speaker 1: wherever you get your podcasts. Hey, everybody, welcome to another

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Speaker 1: episode of The Buck Sexton Show. I have Tutor Dixon

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Speaker 1: with me now. Not only does she have the coolest

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Speaker 1: name that I've heard in a long time, and my

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Speaker 1: name is Buck Sexton, so I feel like I know

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Speaker 1: something about at least unusual names. Her name is just

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Speaker 1: straight up cool. She ran for governor of Michigan came

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Speaker 1: really close to defeating the wicked Witch of Michigan, Gretchen Whitmer,

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Speaker 1: which would have been amazing. I is a mom, is

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Speaker 1: an American patriot, wife, commentator, soon to be podcaster, Michigander.

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Speaker 1: Tutor Dixon. Great to have you on. Thank you. I'm

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Speaker 1: happy to be here. So how do you decide it?

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Speaker 1: I always like to start with the origin story, you know,

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Speaker 1: it's almost like a comic book. How do you decide

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Speaker 1: to get to get into this game? I mean, you know,

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Speaker 1: I was rooting for you so much because I was

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Speaker 1: a New Yorker during the pandemic and Michigan was one

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Speaker 1: of the only places where I didn't expect the lockdowns

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Speaker 1: to get as crazy as it got, if that makes

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Speaker 1: sense New York, LA, DC. Sure, Michigan, is that what happened? Right? Yes,

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Speaker 1: So we were watching this happen and the origin story

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Speaker 1: kind of goes back far because my origin story in

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Speaker 1: Michigan starts in a steel foundry. So I spent most

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Speaker 1: of my career in the steel foundry on the shop floor,

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Speaker 1: working the product through, helping make sure we get it

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Speaker 1: on time to our customers. And then in twenty seventeen,

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Speaker 1: I had a friend come to me and say, I

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Speaker 1: don't know if you know what's happening in our schools,

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Speaker 1: but it's really kind of this anti American message, and

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Speaker 1: I want to provide a news service for middle and

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Speaker 1: high school students that would be pro America but also

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Speaker 1: talk about jobs. And that was near and dear to

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Speaker 1: my heart because it was really hard for us to

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Speaker 1: find people to come and work in the shop. And

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Speaker 1: I thought, this is great. This is an opportunity to

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Speaker 1: introduce young people to manufacturing, and I think that's lost

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Speaker 1: on a lot of young people these days. But then

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Speaker 1: as we expanded that, we grew into conservative media, into

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Speaker 1: the political world, and then twenty came and I saw

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Speaker 1: factory shut down. I saw people out of work. I

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Speaker 1: saw our communities really falling apart, and I saw my

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Speaker 1: own kids, my own kids at home, they're not at school.

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Speaker 1: My ten year old at one point looked at me

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Speaker 1: and she goes, mom, I was putting in her bed

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Speaker 1: and she started crying, and I said, why are you crying, honey?

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Speaker 1: And I think as adults, we started to forget that

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Speaker 1: our kids were home for so long without ever leaving

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Speaker 1: the house. They weren't even allowed to go to the

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Speaker 1: grocery store with us. And she looked at me and

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Speaker 1: she said, I think this is what it feels like

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Speaker 1: to be depressed. And that was sort of that crowning

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Speaker 1: blow where I said, we've got to do something and

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Speaker 1: talked to some friends and we thought who's going to run?

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Speaker 1: Who is going to run for governor in Michigan? And

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Speaker 1: we talked to folks in Lancing. There wasn't that traditional

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Speaker 1: politician type person stepping up to do it. And I

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Speaker 1: had this crazy moment where it's like, how how surely

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Speaker 1: hard can it be to run for governor? And it

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Speaker 1: turns out it's kind of hard. Tell me, actually, I

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Speaker 1: want to get back to the running for governor thing

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Speaker 1: in a second. I'm just curious about that again, as

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Speaker 1: somebody who wasn't in politics, you just decided to run

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Speaker 1: for governor in a serious, a serious state. You know,

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Speaker 1: It's not like the governor of Rhode Island. Let's be honest,

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Speaker 1: you know what I mean. I mean, you know, no

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Speaker 1: offense or Rhode Island. But come on, but but you know,

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Speaker 1: you know, I'm just saying, Michigan's got a lot of people. So, uh,

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Speaker 1: the steel foundry. You when someone sees you, I don't

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Speaker 1: think they're thinking, this is somebody who was on this

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Speaker 1: on the floor of the steel foundry. Um, what is that? Like?

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Speaker 1: How is the American steel industry doing. I'm always curious

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Speaker 1: about about that. I wonder, you know, we were the

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Speaker 1: best in the world. Are we still the best in

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Speaker 1: the world? And tell me about the steel Well, I

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Speaker 1: think this is a really interesting because the steel industry, well,

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Speaker 1: I come from the foundry industry. So what we're doing

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Speaker 1: is we're pouring molten metal into a sand mold in

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Speaker 1: making a product for someone like a Caterpillar or a

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Speaker 1: John Deer. So we did a lot of mining, military,

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Speaker 1: heavy equipment, farm equipment things like that, but you're making

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Speaker 1: pieces for someone else. And this was something that over

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Speaker 1: the Obama years really saw a lot going to China,

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Speaker 1: and China was really taking over that space and they

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Speaker 1: really have. There's not that many steel foundries left in

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Speaker 1: the United States. And it's such a crucial part of

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Speaker 1: what we do because, as I said, it's in all

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Speaker 1: of your farm equipment. I mean, this is what your

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Speaker 1: vehicles are made out of. This is what your military

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Speaker 1: vehicles were made up. We made quite a few parts

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Speaker 1: for the MRAP vehicles at that time, and you just

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Speaker 1: think about the idea of these things coming over from China. Now,

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Speaker 1: a lot of our military equipment has a ninety percent

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Speaker 1: or eighty percent by America clause, but you still have

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Speaker 1: a portion of that that can come from another country.

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Speaker 1: And so I know you hear people on our our

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Speaker 1: side of the aisle talking about America First quite a bit.

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Speaker 1: So I think America First is something that we have

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Speaker 1: to break into a few different categories when we look

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Speaker 1: at America First. Because coming from the steel industry, I

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Speaker 1: knew what it was like. I watched our patterns, our

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Speaker 1: parts go overseas bit by bit by bit until our

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Speaker 1: foundry closed, and many other foundries closed. So I think

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Speaker 1: when we think about America, first we really need to

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Speaker 1: think about how much do we feel comfortable having in China?

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Speaker 1: And then how much of that do we need to

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Speaker 1: bring back to the United States. But that question real quick, tutor,

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Speaker 1: how do we bring it back? Is it just because

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Speaker 1: the labor in China is obviously a lot cheaper? Do

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Speaker 1: we have advantages either technologically or just do we just

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Speaker 1: make a better product here? How do we bring it

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Speaker 1: back here? Is a tariff something that's That's what I

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Speaker 1: was going to say. A lot of people don't understand

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Speaker 1: that it's some of these parts. Once you close the factories,

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Speaker 1: these factories don't start up again, and there aren't a

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Speaker 1: lot of people out there that are saying, what should

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Speaker 1: I do? I don't I start up a steel foundry.

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Speaker 1: They're very hard to start up and it's very hard

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Speaker 1: to operate. There's not a whole lot of knowledge of

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Speaker 1: how to do it yet left in the United States.

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Speaker 1: So certain trades are really being lost completely to the

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Speaker 1: United States. So in that case, I would say, well,

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Speaker 1: how do we find a friendly country to make sure

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Speaker 1: we're outsourcing to a friendly country? And then if we can,

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Speaker 1: over time bring that back. I would love to see

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Speaker 1: those jobs come back. But I want to be realistic

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Speaker 1: too and say, there are certain technologies that we do

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Speaker 1: really well, and there are certain technologies that are a

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Speaker 1: lost art in the United States that we need to

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Speaker 1: find an allied country rather than an adversarial country to

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Speaker 1: do business in. And I know that's an unpopular view,

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Speaker 1: but I'm coming from a place of really having seen

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Speaker 1: it been on the shop floor, and I know we

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Speaker 1: have great steel foundries here. As much business as we

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Speaker 1: can put on them, we should, But in the cases

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Speaker 1: where you just can't find a source, you need to

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Speaker 1: go to an allied country. That's so important that we

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Speaker 1: start talking about that relationship with our allies and making

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Speaker 1: sure that's secure. If you say the United States sent

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Speaker 1: one hundred and fifty billion dollars worth of product to

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Speaker 1: China last year, China sent five hundred and sixty billion

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Speaker 1: dollars worth of product to the United States. So although

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Speaker 1: they are very reliant on us to be their biggest buyer,

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Speaker 1: we are also very reliant on them for our pharmaceuticals,

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Speaker 1: for our steel, for almost every product there's a piece

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Speaker 1: of it in China. When you think about five hundred

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Speaker 1: and sixty billion dollars worth of imports. I was just

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Speaker 1: talking to General Mattis over the weekend and I said, so,

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Speaker 1: don't you think that that seems like, well, China doesn't

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Speaker 1: really want to attack us if we are their biggest customer.

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Speaker 1: And he said, but you're thinking from a logical standpoint.

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Speaker 1: You're thinking from a logical point of view, and that's

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Speaker 1: not necessarily how you have to think when you're talking

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Speaker 1: about countries like that, which I think is something we

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Speaker 1: have to remember, and that's something that goes beyond government,

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Speaker 1: that goes to the private sector, because you know, and

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Speaker 1: I know that the majority of these companies our private sector.

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Speaker 1: This isn't our military equipment, this isn't all government, this

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Speaker 1: is private sector. So when you think about not having pharmaceuticals,

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Speaker 1: we really need to be pushing those companies to use

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Speaker 1: friendly countries or come back to the United States. I

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Speaker 1: want to ask you about running for a governor in

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Speaker 1: a second. But a word from our sponsor here, tunnelth

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Speaker 1: So tutor running for governor, you're hanging out with some friends,

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Speaker 1: you're in Michigan. You're like no one else is running.

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Speaker 1: Gretchen Whitmer's horrible, like truly horrible. I don't really care.

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Speaker 1: I'm gonna say this. You know, I'm in Florida now.

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Speaker 1: I was in New York for almost forty years of

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Speaker 1: my life, give or take the college years and some

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Speaker 1: CIA years thrown in there. But I don't really care

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Speaker 1: about other states governors very much. Right if someone asked

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Speaker 1: me what do I think of the governor of Wyoming?

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Speaker 1: I don't even know the governor of Wyoming is off

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Speaker 1: the top of my head. Am I gonna lie? Your governor, though,

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Speaker 1: was like Fauci in a wig? Like your governor was

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Speaker 1: the absolute worst? So you step up to stop the madness?

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Speaker 1: What's that process? Like? I mean, what learn from doing it?

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Speaker 1: And would you do it again? I've said to people,

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Speaker 1: maybe it's like pregnancy and you forget and then you

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Speaker 1: do it again. Maybe there's that chance because it really

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Speaker 1: is very, very hard. It's interesting because I think what

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Speaker 1: people don't understand, and this is one of the questions

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Speaker 1: we got over and over again. It was like, why

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Speaker 1: don't you come out and say these things are lies?

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Speaker 1: Or why do they Why are they allowed to lie

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Speaker 1: about you? When you're a public figure you know this

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Speaker 1: buck they can say things about you and there's no

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Speaker 1: defamation clause. You can't go after them, so they can

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Speaker 1: make up anything they want. And I think that was

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Speaker 1: the hardest part was seeing them make things about my family,

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Speaker 1: seeing them make splice up my words and create commercials

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Speaker 1: out of things that I didn't really say to make

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Speaker 1: it look like I said something that I hadn't said.

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Speaker 1: That was really challenging. But also, I mean, the whole

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Speaker 1: process is incredibly brutal because you go through this battle

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Speaker 1: with your own side first. You're fighting your own side first,

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Speaker 1: and it gets really ugly, and people that you have

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Speaker 1: trusted for years do things in turn against you, and

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Speaker 1: you think, wow, this is really harsh. I mean, you

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Speaker 1: remember Donald Trump a lot of times, Donald Trump Junior

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Speaker 1: has come out and said, you know, my dad when

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Speaker 1: he went down that escalator, said now we find out

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Speaker 1: who our friends are. And that's really exactly right. You

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Speaker 1: find out who's going to call you and say did

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Speaker 1: you say this? You find out who's going to come

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Speaker 1: out and say something about you behind your back, and

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Speaker 1: it was that was pretty shocking. But I think that,

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Speaker 1: you know, going around the state, the thing that was

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Speaker 1: the most surprising to me that was nothing to do

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Speaker 1: with me at all. Going around the state. If you

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Speaker 1: go to other states, you see things thriving. I mean,

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Speaker 1: we've gone to Dallas, We've gone to Nashville and seeing

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Speaker 1: folks down that you know down in Nashville, and those

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Speaker 1: cities are just booming. They have cars everywhere, people are

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Speaker 1: driving around, all the restaurants are open. I think people

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Speaker 1: don't realize in Michigan we lost full communities. So as

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Speaker 1: I was campaigning, I had people really literally falling into

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Speaker 1: my arms and crying and saying, bring back our communities.

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Speaker 1: We used to have a whole row of restaurants down

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Speaker 1: the street, and out of the six restaurants that we're here,

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Speaker 1: there's one left our community. And that was really the

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Speaker 1: sense of community totally lost. And so that was the

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Speaker 1: most surprising thing to me. As I started leaving the

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Speaker 1: state to travel to some other cities and talk to

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Speaker 1: folks about investing in Michigan. I saw, Wow, the rest

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Speaker 1: of the country is really bounced back and Michigan really hasn't.

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Speaker 1: But the overwhelming joy of people too, the resilience of

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Speaker 1: the human spirit going out and talking to these people

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Speaker 1: and even through tears, they're just holding my hands and saying,

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Speaker 1: we're going to pray for you. We want to see

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Speaker 1: this happen. And it was such an amazing experience for

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Speaker 1: people who are concerned about running for office because it's

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Speaker 1: brutal and you get attacked in the media, and the

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Speaker 1: media is not your friend, especially if you are on

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Speaker 1: the right side of the aisle. The media is not

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Speaker 1: your friend. I have to tell you it is the

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Speaker 1: most boarding thing you can do to go out and

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Speaker 1: talk to people and give them hope. That was just

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Speaker 1: amazing and I really encourage other people to go out

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Speaker 1: and attempt to serve if you can. Yeah. Well, on

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Speaker 1: the on the media side is you'll be seeing more

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Speaker 1: and more going forward. Tutor. For every fifty people on

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Speaker 1: Twitter who tell you that you know, meaning me in

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Speaker 1: this case, you know, tell me that I'm I'm horrible, dumb,

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Speaker 1: ugly and should you know, go jump off a bridge,

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Speaker 1: there'll be one person who comes up to me in

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Speaker 1: an airport or while I'm in line at the grocery store,

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Speaker 1: who's like, I love your show, and all I ever

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Speaker 1: remember is that person. We do it for that person,

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Speaker 1: right the other with their blue hair and their cat food.

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Speaker 1: You know, they're sad. They're sad, and those are not

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Speaker 1: real people. And that's what I try to explain to

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Speaker 1: people that the Twitter verse is not the average person.

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Speaker 1: The average person isn't on Twitter. They're not They're not

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Speaker 1: looking at what you're doing on Twitter. Twitter may set

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Speaker 1: a media narrative, but the people are totally different. Tonight,

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Speaker 1: I was at my daughter's basketball game. I'm just watching

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Speaker 1: the basketball game and this woman kind of comes down

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Speaker 1: the bleachers and sits next to me, and she said,

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Speaker 1: I just want to tell you that we watched your

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Speaker 1: entire race and we were so proud to be supporting you.

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Speaker 1: And it really is so humbling because you feel like, Wow,

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Speaker 1: I didn't even know that these people were out there,

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Speaker 1: that they felt that way about me, And what can

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Speaker 1: I do to keep that promise in other ways? And

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Speaker 1: that's something that's been important to me in this If

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Speaker 1: I can't be serving them in that way, then I

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Speaker 1: believe that God put me on this journey for some reason,

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Speaker 1: that there's still a path to helping folks and making

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Speaker 1: sure that we bring those communities back whatever way I

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Speaker 1: can do that, and so that's why I'm still in

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Speaker 1: the game and I'm still focused on serving people however

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Speaker 1: I can. Did your daughter's team win, by the way, No,

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Speaker 1: it was terrible. I think I've blown out. Oh man,

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Speaker 1: that could be a rough one. What was it? I

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Speaker 1: mean it was the other team, the other team just

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Speaker 1: usually at that level. I coached high school soccer at

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Speaker 1: one point, and if you have one or two players

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Speaker 1: who are going to go you know, you can always

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Speaker 1: tell to one or two players on a team that

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Speaker 1: are going to go college, especially if they're gonna go

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Speaker 1: play D one, that's the team that wins. Usually there's

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Speaker 1: not happening. It wasn't happening. Now. Well it's sixth grade though,

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Speaker 1: so sixth grade everybody is still kind of you know,

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Speaker 1: learning their own body too. So I mean you go

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Speaker 1: in and you never know. But the funny thing is,

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Speaker 1: so my sixth grader plays basketball, and then my fourth

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Speaker 1: graders play with their twins and they play basketball, and

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Speaker 1: we are truly the shortest people here. So we live

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Speaker 1: in an area of Michigan that is very Dutch, and

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Speaker 1: Dutch people are all extraordinarily tall. Like, we walked into

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Speaker 1: school the first day and people were like, oh, look

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Speaker 1: at those tiny little children. But they were actually in

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Speaker 1: the class with the other kids. They just thought that

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Speaker 1: they were tiny little children. So no one expects my

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Speaker 1: one daughter, she's the smallest one of my twins, to

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Speaker 1: be anything on the basketball court, and she is like

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Speaker 1: so awesome. She goes out there and she made four

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Speaker 1: baskets on Saturday, and she's just like this little ringer.

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Speaker 1: No one expects it, which is kind of cool to

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Speaker 1: watch when I mean there was a great this guy

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Speaker 1: was amazing. Did you watch I used to watch the

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Speaker 1: Clay makes fun of me and says that I don't

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Speaker 1: like sports. That's actually as I've gotten older, Um, I

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Speaker 1: don't really watch munch professional sports. I do like playing

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Speaker 1: sports and certainly hope to, uh you know, coach my

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Speaker 1: own kids one day. But way back in the day,

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Speaker 1: I did watch NBA. Do you remember there was a guy,

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Speaker 1: Mugsy Bogues who was in the NBA. I think he

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Speaker 1: was five foot five. There was a there was a

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Speaker 1: player in the NBA. He's a famous player. And then

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Speaker 1: there was a guy named spud web This is back

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Speaker 1: in the early nineties, and spud Webb actually won the

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Speaker 1: Slam Dunk Contest and he was five foot nine. So

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Speaker 1: I'm just saying, tell your girls, there's a chance she

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Speaker 1: will defy genetics and still be able to play basketball.

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Speaker 1: But she's really I mean, I never you know, it's

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Speaker 1: funny because as a parent, there are things that your

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Speaker 1: kids do and you never thought that could be possible.

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Speaker 1: You know, you're like, that's not part of us. Didn't

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Speaker 1: come from me, it didn't come from my husband. So

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Speaker 1: then they do something and it totally blows your mind.

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Speaker 1: My one, my oldest daughter, is extraordinarily shy, and she

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Speaker 1: went to school and she went to this school's new three.

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Speaker 1: When COVID hit, we moved them to this school. And

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Speaker 1: she's tried out for the play, never done anything like

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Speaker 1: this before. And the girl at the front desk said

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Speaker 1: to me, well, Larkin's amazing. She's going to Hollywood. And

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Speaker 1: I will confess that as a mom, I thought she

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Speaker 1: must have the wrong child because Larkin is shy. She's

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Speaker 1: not that's not her. And then she comes out on

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Speaker 1: stage at the play and she's singing, and she's like amazing.

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Speaker 1: And I turned to my husband and I'm like, did

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Speaker 1: you know how she could sing? It's like, how do

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Speaker 1: we not about our own kid? You know? But I

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Speaker 1: think that's the coolest part about parenting. Sometimes your child

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Speaker 1: does and then you're like, where does that come from?

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Speaker 1: But it's amazing, And there are things that are not

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Speaker 1: amazing that they do too. I've heard stories about that,

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Speaker 1: you know. I'm actually I've got to ask you a

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Speaker 1: few questions here. I gotta ask you for some advice

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Speaker 1: in a second, because Tooter, I'm getting married in just

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Speaker 1: a matter of days, so I want the woman, thank you. Yeah,

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Speaker 1: I want the woman's perspective on how to make everything

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Speaker 1: go as smoothly as possible for me for the next

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Speaker 1: forty years or so. So we'll get to that in

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Speaker 1: just a second. Yeah, I'm sure you've got some thoughts.

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Speaker 1: Heads up, if you're a T Mobile subscriber, they're investigating

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Speaker 1: thirty seven million customers right after the New year. Cyber

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Speaker 1: your credit that's happened to me before. It's why I

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Speaker 1: And all right, tutor, Now this is the part of

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Speaker 1: the podcast that everyone's gonna have to take notes on.

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Speaker 1: So you're how many kids you have? Three? You have

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Speaker 1: three kids or four kids? Okay, so you are a

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Speaker 1: happily married wife and mom with four kids. How do

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Speaker 1: I follow in the footsteps here? I mean, obviously I

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Speaker 1: can't personally have the four kids, but I'd like to

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Speaker 1: have two or three getting married? How do I have

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00:20:07,617 --> 00:20:12,177
Speaker 1: happy wife, happy life? You know? I mean if I

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Speaker 1: had the answer to that, then I would not be podcasting.

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00:20:15,617 --> 00:20:18,697
Speaker 1: I would just be laying back when my private jet

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00:20:18,697 --> 00:20:21,337
Speaker 1: going wherever I wanted. Right, because everybody wants to know

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Speaker 1: what the answers. We are complicated people. Women were complicated.

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Speaker 1: It's very special. Yeah, yes so, and we like to

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Speaker 1: make sure it's specialized to each one of us so

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Speaker 1: that you are always confused. That's the goal. Wow, it's

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Speaker 1: working right now. I'm confused right now. I want an

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Speaker 1: advice and I feel like I know even less than

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Speaker 1: two minutes ago. But I think, so you know that

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Speaker 1: they say there's a love language, and I don't know

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Speaker 1: if I really haven't read that book, but I will

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Speaker 1: tell you that for me, if my husband empties the

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Speaker 1: dishwasher or does the laundry, I am like, that is

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Speaker 1: so amazing. And I think that At one point on

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Speaker 1: the campaign trail, someone said to me, so, what are

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Speaker 1: your hobbies? And I thought, the only thing coming to

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Speaker 1: mind right now is laundry, because when you have four kids,

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Speaker 1: it's all you do. So when those chores are picked

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Speaker 1: up by him, it's just such a relief and it

428
00:21:17,177 --> 00:21:20,297
Speaker 1: makes me feel so happy inside. But I think everybody's different,

429
00:21:20,377 --> 00:21:22,977
Speaker 1: So you know, what my love language is is obviously

430
00:21:23,057 --> 00:21:25,297
Speaker 1: different than how someone else feels like they're cared for

431
00:21:25,377 --> 00:21:27,697
Speaker 1: and taken care of. But that I think is the

432
00:21:27,737 --> 00:21:31,217
Speaker 1: most important thing really in a relationship is communicating what

433
00:21:31,377 --> 00:21:34,137
Speaker 1: makes you feel like I'm there for you, that I'm

434
00:21:34,177 --> 00:21:37,497
Speaker 1: a partner. And that's where I think we so oftentimes

435
00:21:37,697 --> 00:21:41,137
Speaker 1: split in cases where we feel like we're doing it alone,

436
00:21:41,177 --> 00:21:43,937
Speaker 1: we're doing life alone, and it might not be that

437
00:21:43,977 --> 00:21:46,297
Speaker 1: you're doing life alone, but it might just be that

438
00:21:46,337 --> 00:21:48,497
Speaker 1: you don't know what the other person needs to feel

439
00:21:48,497 --> 00:21:51,137
Speaker 1: like they have a partner, a teammate alongside them. And

440
00:21:51,177 --> 00:21:54,457
Speaker 1: when you have four kids, it is We're at the

441
00:21:54,457 --> 00:21:56,937
Speaker 1: point where my girls are, my twins are nine, and

442
00:21:56,977 --> 00:22:01,497
Speaker 1: then I have eleven and thirteen, and it is a battle.

443
00:22:01,657 --> 00:22:03,697
Speaker 1: You know. I thought, I kept thinking, once they can

444
00:22:03,697 --> 00:22:06,417
Speaker 1: tie their shoes, life won't be so much easier. Then

445
00:22:06,457 --> 00:22:08,777
Speaker 1: you have these moments where you think, well, once they

446
00:22:08,777 --> 00:22:11,617
Speaker 1: can read, life will be so much easier. And it

447
00:22:12,377 --> 00:22:15,137
Speaker 1: really is just a different level of heart. That's why

448
00:22:15,177 --> 00:22:19,657
Speaker 1: that partnership with your spouse is so key, that partnership

449
00:22:19,657 --> 00:22:22,217
Speaker 1: where you just feel like I'm safe with this person

450
00:22:22,817 --> 00:22:26,817
Speaker 1: because life is hard, and I think people expect life

451
00:22:26,817 --> 00:22:29,337
Speaker 1: to be so easy. You know, I look at some

452
00:22:29,377 --> 00:22:31,977
Speaker 1: of the things that we fight about in campaigns and

453
00:22:32,017 --> 00:22:34,817
Speaker 1: I think life is not easy. You know, when my

454
00:22:34,897 --> 00:22:37,577
Speaker 1: girls were when my twins were two, I had two,

455
00:22:37,657 --> 00:22:40,577
Speaker 1: four and six when I was diagnosed with cancer, and

456
00:22:41,617 --> 00:22:44,497
Speaker 1: that was one of those moments where I thought, gosh,

457
00:22:44,537 --> 00:22:48,137
Speaker 1: if something, if this goes south, the twins probably won't

458
00:22:48,177 --> 00:22:52,377
Speaker 1: remember me. My middle daughter won't likely remember much, and

459
00:22:52,417 --> 00:22:54,977
Speaker 1: my six year old will have very faint memories of me.

460
00:22:55,417 --> 00:22:58,577
Speaker 1: And if you don't have that person that support next

461
00:22:58,577 --> 00:23:01,217
Speaker 1: to you saying we're going to power through this, it's

462
00:23:01,217 --> 00:23:03,497
Speaker 1: really hard. I mean, I just think it's a matter

463
00:23:03,577 --> 00:23:06,057
Speaker 1: of finding where you prop up the person when they

464
00:23:06,097 --> 00:23:10,577
Speaker 1: are falling over and making sure you're doing that masked.

465
00:23:10,617 --> 00:23:14,137
Speaker 1: What was the what kind of cancer were you battling

466
00:23:14,137 --> 00:23:17,137
Speaker 1: At the time, I had breast cancer, So that was

467
00:23:17,577 --> 00:23:20,337
Speaker 1: really a shocking moment. It was interesting because I mean,

468
00:23:20,377 --> 00:23:23,257
Speaker 1: maybe this is too much information, but you all know

469
00:23:23,337 --> 00:23:27,537
Speaker 1: this now. So when I went in, I was nursing

470
00:23:27,697 --> 00:23:30,817
Speaker 1: at the time, and I would have never thought that

471
00:23:30,897 --> 00:23:32,737
Speaker 1: this is what cancer felt like. I went into the

472
00:23:32,777 --> 00:23:36,457
Speaker 1: doctor and the physician's assistant was like, how long have

473
00:23:36,497 --> 00:23:39,977
Speaker 1: you had this lump here? And I didn't think anything

474
00:23:39,977 --> 00:23:42,657
Speaker 1: of it. So she sent me for a mammogram and

475
00:23:42,737 --> 00:23:45,297
Speaker 1: an ultrasound. And I went in for the mammogram and

476
00:23:45,337 --> 00:23:48,577
Speaker 1: the girl said, you know what, the mammogram is totally clean,

477
00:23:48,657 --> 00:23:51,457
Speaker 1: there's nothing there. They did send you for an ultrasound,

478
00:23:51,497 --> 00:23:54,097
Speaker 1: so we'll do one just to be safe, but you're

479
00:23:54,097 --> 00:23:56,097
Speaker 1: going to be fine. And I went in for the

480
00:23:56,177 --> 00:23:57,897
Speaker 1: ultrasound and you know, you go in and they're like,

481
00:23:57,937 --> 00:24:00,377
Speaker 1: how many children do you have? Oh? Four? Hold are

482
00:24:00,377 --> 00:24:03,297
Speaker 1: their names? And then they do the ultrasound and their

483
00:24:03,337 --> 00:24:07,217
Speaker 1: faces all changed and there it's like how many children

484
00:24:07,297 --> 00:24:10,057
Speaker 1: did you say you have? And I remember thinking, oh,

485
00:24:10,297 --> 00:24:12,617
Speaker 1: this is really not this is not a good reaction.

486
00:24:12,657 --> 00:24:16,857
Speaker 1: They said, would you mind staying for a biopsy? And

487
00:24:16,977 --> 00:24:20,497
Speaker 1: so I stayed for the biopsy, and then it was

488
00:24:20,537 --> 00:24:25,777
Speaker 1: like a miscommunication between the biopsy doctor and my doctor.

489
00:24:25,817 --> 00:24:28,017
Speaker 1: My doctor thought that I knew, so that she called

490
00:24:28,057 --> 00:24:29,777
Speaker 1: me into her office a few days later and I

491
00:24:29,817 --> 00:24:32,377
Speaker 1: walked in and she just immediately started handing me cancer

492
00:24:32,377 --> 00:24:37,337
Speaker 1: brochures and I said, do I have cancer? And she said,

493
00:24:37,377 --> 00:24:40,617
Speaker 1: I thought they already told you. So. Then was the

494
00:24:40,737 --> 00:24:44,217
Speaker 1: journey of what's next. And it's funny because when you

495
00:24:44,337 --> 00:24:47,097
Speaker 1: end up with a diagnosis like this, everyone around you

496
00:24:47,457 --> 00:24:50,377
Speaker 1: wants you immediately to go straight to the doctor and

497
00:24:50,497 --> 00:24:52,897
Speaker 1: get it fixed, get it fixed. And I was sort

498
00:24:52,937 --> 00:24:54,777
Speaker 1: of one of those people that wanted to talk to

499
00:24:54,817 --> 00:24:57,577
Speaker 1: a few different doctors to find out and I recommend that.

500
00:24:57,817 --> 00:25:01,737
Speaker 1: I really, I think it's so often as people we

501
00:25:01,857 --> 00:25:04,977
Speaker 1: think whatever the first doctor says, we have to listen.

502
00:25:05,137 --> 00:25:07,217
Speaker 1: The doctor is the person of authority. We just have

503
00:25:07,377 --> 00:25:09,817
Speaker 1: to go with that person. And the first doctor I

504
00:25:09,817 --> 00:25:12,417
Speaker 1: talked too was just not the person I ended up

505
00:25:12,417 --> 00:25:15,577
Speaker 1: going to Johns Hopkins. And this is how cool this

506
00:25:15,657 --> 00:25:19,777
Speaker 1: story is. After my surgery. Three years after my surgery,

507
00:25:20,137 --> 00:25:23,137
Speaker 1: my breast surgeon called me and he said, and you

508
00:25:23,177 --> 00:25:26,257
Speaker 1: think about this after all of these other people have

509
00:25:26,337 --> 00:25:29,257
Speaker 1: gone in, because if you're in Johns Hopkins Cancer Center,

510
00:25:29,417 --> 00:25:32,337
Speaker 1: you have somebody coming in every five minutes with breast cancer.

511
00:25:32,577 --> 00:25:35,017
Speaker 1: But three years later, the surgeon called me and he said,

512
00:25:35,377 --> 00:25:38,097
Speaker 1: I've a young woman, she's thirty five. She has the

513
00:25:38,217 --> 00:25:41,137
Speaker 1: same cancer you have, and she's really scared. Would you

514
00:25:41,177 --> 00:25:46,217
Speaker 1: call her and talk her through it? How amazing is that? Yeah? Yeah,

515
00:25:46,257 --> 00:25:48,497
Speaker 1: I mean I also I think that's so important whenever

516
00:25:48,617 --> 00:25:52,577
Speaker 1: someone has a really serious health issue, that there's that

517
00:25:52,697 --> 00:25:55,177
Speaker 1: first thing. The first step is the feeling of alone.

518
00:25:55,657 --> 00:25:57,457
Speaker 1: And you know, when you're dealing with the health system,

519
00:25:57,497 --> 00:25:59,337
Speaker 1: and I've had to deal with this with family members

520
00:25:59,337 --> 00:26:03,417
Speaker 1: and who have had to go through you realize one

521
00:26:03,417 --> 00:26:05,097
Speaker 1: of the things that I think you're you have to

522
00:26:05,097 --> 00:26:08,337
Speaker 1: fight along the way is the recognition that it feels

523
00:26:08,377 --> 00:26:10,457
Speaker 1: sometimes like nobody cares about what you're going through but

524
00:26:10,577 --> 00:26:13,657
Speaker 1: you know, when you're making your way through the hospital corridors,

525
00:26:14,097 --> 00:26:17,217
Speaker 1: waiting in the waiting rooms and waiting for the meetings

526
00:26:17,217 --> 00:26:19,857
Speaker 1: and the scans, and you know, my grandmother had had

527
00:26:19,937 --> 00:26:22,977
Speaker 1: cancer and just she had multiple cancers at the same time.

528
00:26:23,537 --> 00:26:26,097
Speaker 1: And being able to talk to somebody who's gone through

529
00:26:26,217 --> 00:26:28,097
Speaker 1: it and come out on the other side as you

530
00:26:28,137 --> 00:26:32,297
Speaker 1: have in particular, as you know, health healthy, and you know,

531
00:26:32,617 --> 00:26:34,737
Speaker 1: prosperous as you've been, I think that would be a

532
00:26:34,857 --> 00:26:36,297
Speaker 1: very powerful I didn't know by the way that you

533
00:26:36,297 --> 00:26:37,897
Speaker 1: would you would have been through that, that you are

534
00:26:37,937 --> 00:26:41,377
Speaker 1: a cancer survivor. So, um, I'm glad that you've got

535
00:26:41,377 --> 00:26:45,817
Speaker 1: great car at Johns Hopkins University. So you're a mom.

536
00:26:46,017 --> 00:26:49,177
Speaker 1: You have fought lots of battles already come out of

537
00:26:49,177 --> 00:26:55,097
Speaker 1: it successfully. What do you particularly energized about these days?

538
00:26:55,217 --> 00:26:57,457
Speaker 1: What do you see and you're like, this is the issue,

539
00:26:57,537 --> 00:27:01,057
Speaker 1: this is the thing. I'm trying to transition to someone.

540
00:27:01,217 --> 00:27:02,977
Speaker 1: I do a lot of work on the border, and

541
00:27:03,057 --> 00:27:06,337
Speaker 1: I think that immigration is a fascinating and really important

542
00:27:06,377 --> 00:27:09,297
Speaker 1: illegal immigration specifically, What for you right now is the

543
00:27:09,297 --> 00:27:12,217
Speaker 1: thing that you are the most we need to fix

544
00:27:12,297 --> 00:27:16,017
Speaker 1: this in this country. Well, It's funny that you bring

545
00:27:16,097 --> 00:27:20,737
Speaker 1: up immigration because I probably have a slightly different view

546
00:27:20,777 --> 00:27:24,857
Speaker 1: on it than maybe other people, but maybe not. Maybe

547
00:27:25,657 --> 00:27:27,937
Speaker 1: other people just haven't really talked about it this way.

548
00:27:27,977 --> 00:27:31,217
Speaker 1: But as I told you, it's difficult to start a

549
00:27:31,297 --> 00:27:34,497
Speaker 1: steel foundry in the United States because that's not the

550
00:27:34,577 --> 00:27:37,857
Speaker 1: skill set that we have anymore. But my dad recently

551
00:27:37,937 --> 00:27:41,097
Speaker 1: helped someone start a new foundry up in Indiana, and

552
00:27:41,737 --> 00:27:44,737
Speaker 1: he wanted to bring in folks from the Czech Republic

553
00:27:44,777 --> 00:27:48,017
Speaker 1: in Ukraine that we're specialists in their field. But according

554
00:27:48,057 --> 00:27:51,817
Speaker 1: to these immigration documents, to be considered a specialist in

555
00:27:51,857 --> 00:27:55,457
Speaker 1: your field, you had to have a degree in that field. Well,

556
00:27:55,857 --> 00:27:58,737
Speaker 1: we need laborers, and these are people that are truly

557
00:27:58,817 --> 00:28:02,217
Speaker 1: specialists in pouring molten metal. And that may seem like

558
00:28:02,257 --> 00:28:04,097
Speaker 1: you can just pour it any which way, but it

559
00:28:04,177 --> 00:28:06,337
Speaker 1: really is something that you have to be skilled to know.

560
00:28:06,697 --> 00:28:09,137
Speaker 1: And so when you talk about immigration, I think about

561
00:28:09,137 --> 00:28:12,977
Speaker 1: immigration warm Michigan is dying for workers right now. We

562
00:28:13,017 --> 00:28:15,897
Speaker 1: need workers in hotels, we need workers and restaurants, we

563
00:28:15,937 --> 00:28:19,737
Speaker 1: need workers in factories. These are in many cases skilled

564
00:28:19,817 --> 00:28:23,057
Speaker 1: laborers that want to come into this country that can't.

565
00:28:23,097 --> 00:28:25,897
Speaker 1: So when we keep hearing from everybody. Oh, there's just

566
00:28:25,937 --> 00:28:27,497
Speaker 1: people that want to come in. There's people that want

567
00:28:27,497 --> 00:28:30,257
Speaker 1: to come in. You cannot tell me that the United

568
00:28:30,297 --> 00:28:33,257
Speaker 1: States of America, with the intelligent people that we have

569
00:28:33,337 --> 00:28:37,817
Speaker 1: and the data that we have and the technology that

570
00:28:37,857 --> 00:28:40,297
Speaker 1: we have, that we would not be able to create

571
00:28:40,337 --> 00:28:43,337
Speaker 1: an immigration system that would be able to match people

572
00:28:43,417 --> 00:28:46,657
Speaker 1: to the open positions that we have. And say, if

573
00:28:46,697 --> 00:28:49,097
Speaker 1: you are able to do this job, and you want

574
00:28:49,097 --> 00:28:51,977
Speaker 1: to stay in this job for however long, you can

575
00:28:52,097 --> 00:28:55,457
Speaker 1: earn your green card or you can you can earn

576
00:28:55,457 --> 00:28:58,817
Speaker 1: your citizenship over time by filling a position that we

577
00:28:58,937 --> 00:29:02,297
Speaker 1: simply cannot fill. And this is the time. I mean,

578
00:29:02,337 --> 00:29:07,217
Speaker 1: you're hearing about the lack of workers, right, aren't you. Oh? Yeah, absolutely, Well,

579
00:29:07,257 --> 00:29:08,977
Speaker 1: one thing that I'm hearing a lot. We actually just

580
00:29:09,057 --> 00:29:14,257
Speaker 1: talk to chef Andrew Gruel, who runs a restaurant out

581
00:29:14,257 --> 00:29:16,297
Speaker 1: in Los Angeles about this, and I think it's really

582
00:29:16,337 --> 00:29:18,457
Speaker 1: important that we can't get people to show up to

583
00:29:18,497 --> 00:29:21,777
Speaker 1: work because we keep thinking, you pay them more than

584
00:29:21,817 --> 00:29:24,897
Speaker 1: what they can get from the system and they'll show up. Right,

585
00:29:24,897 --> 00:29:27,737
Speaker 1: So it's twenty If minimum wage in Los Angeles is

586
00:29:27,777 --> 00:29:30,137
Speaker 1: fifteen dollars, which I think it is, it's something like that.

587
00:29:31,057 --> 00:29:34,417
Speaker 1: But if somebody can make the equivalent of ten dollars

588
00:29:34,537 --> 00:29:37,097
Speaker 1: or twelve dollars an hour staying home with welfare and

589
00:29:37,177 --> 00:29:40,297
Speaker 1: various benefits that they have unemployment for however long they

590
00:29:40,297 --> 00:29:42,337
Speaker 1: can get at things like that, you have to pay

591
00:29:42,377 --> 00:29:44,777
Speaker 1: them a lot more than a little more than that

592
00:29:44,937 --> 00:29:46,777
Speaker 1: to make them show up to a job and actually

593
00:29:46,817 --> 00:29:49,457
Speaker 1: give you eight hours of their day. And that's where

594
00:29:49,657 --> 00:29:51,337
Speaker 1: he says, there's a golf right now. There are a

595
00:29:51,377 --> 00:29:53,137
Speaker 1: lot of people that are in kind of the gray

596
00:29:53,137 --> 00:29:56,897
Speaker 1: economy side hustles, get money from the state, have their

597
00:29:56,897 --> 00:29:59,577
Speaker 1: hands in different things. And when you say, okay, well

598
00:29:59,617 --> 00:30:01,297
Speaker 1: I'm paying a good wage, they say, yeah, but I

599
00:30:01,377 --> 00:30:03,817
Speaker 1: have to show up to get that wage. This other stuff.

600
00:30:03,857 --> 00:30:05,897
Speaker 1: I do whatever I want, which I mean it was

601
00:30:05,977 --> 00:30:07,697
Speaker 1: it was eye opening to hear it from somebody who's

602
00:30:07,897 --> 00:30:11,177
Speaker 1: trying to run a business and keep it alan sheet healthy.

603
00:30:12,177 --> 00:30:14,937
Speaker 1: But that's what we keep saying in Michigan. Where did

604
00:30:14,977 --> 00:30:17,937
Speaker 1: everyone go? And there are so many, as you put inside,

605
00:30:18,017 --> 00:30:21,537
Speaker 1: hustles right now, and even young people, even my own kids,

606
00:30:21,657 --> 00:30:24,017
Speaker 1: talk about, well, if I were to grow up and

607
00:30:24,617 --> 00:30:27,577
Speaker 1: work on Instagram or work on and I keep saying

608
00:30:28,217 --> 00:30:31,737
Speaker 1: that's those are not really real jobs. I mean for

609
00:30:31,777 --> 00:30:34,257
Speaker 1: some people it really it's a real job. She's on

610
00:30:34,297 --> 00:30:36,137
Speaker 1: a podcast and she's like, it's not a real job. No,

611
00:30:36,257 --> 00:30:39,777
Speaker 1: I like that, that's fine, that's good, it's okay. I mean,

612
00:30:39,777 --> 00:30:41,337
Speaker 1: Claydon I joke around of this all the time. We're like,

613
00:30:41,377 --> 00:30:43,177
Speaker 1: how can we get paid to do this? It's crazy?

614
00:30:43,257 --> 00:30:45,337
Speaker 1: But go ahead. And it's not that I would say

615
00:30:45,377 --> 00:30:47,937
Speaker 1: to my kids, you know, only a few people actually

616
00:30:47,937 --> 00:30:50,337
Speaker 1: get to be football stars. But it is kind of

617
00:30:50,417 --> 00:30:53,177
Speaker 1: like that, you know, this is not you that this

618
00:30:53,257 --> 00:30:56,257
Speaker 1: is a really hard career to make money, and it

619
00:30:56,337 --> 00:30:58,417
Speaker 1: is not like you're going to go to a restaurant

620
00:30:58,417 --> 00:31:01,377
Speaker 1: and get hired and be able to work right away.

621
00:31:01,417 --> 00:31:04,737
Speaker 1: But there are so many young people that believe, well,

622
00:31:04,897 --> 00:31:07,257
Speaker 1: so and so can just travel around the country and

623
00:31:07,297 --> 00:31:10,537
Speaker 1: take pictures and become very wealthy and so is that

624
00:31:11,257 --> 00:31:14,217
Speaker 1: causing a lack of work ethic? Is it just because

625
00:31:14,257 --> 00:31:16,737
Speaker 1: it's easy to make a few dollars here and then

626
00:31:16,737 --> 00:31:19,457
Speaker 1: take a few days off. We do seem to have

627
00:31:19,577 --> 00:31:22,177
Speaker 1: a work ethic problem in the United States, and I

628
00:31:22,217 --> 00:31:25,417
Speaker 1: don't know that we've really identified where it's coming from.

629
00:31:25,457 --> 00:31:28,577
Speaker 1: In Michigan, I've had people come up with all kinds

630
00:31:28,577 --> 00:31:31,697
Speaker 1: of theories. Oh, the marijuana industry, it pays under the table.

631
00:31:31,817 --> 00:31:33,937
Speaker 1: Maybe they all went there, But how could all of

632
00:31:33,937 --> 00:31:37,217
Speaker 1: these people go? Now, Michigan's unique. We have people leaving

633
00:31:37,257 --> 00:31:41,097
Speaker 1: the state as well, so we're losing population. That always hurts.

634
00:31:41,137 --> 00:31:44,577
Speaker 1: But where are all the workers? And yet you have

635
00:31:44,657 --> 00:31:46,977
Speaker 1: all these people that would love to come into the

636
00:31:46,977 --> 00:31:51,137
Speaker 1: country and fill those jobs and not necessarily have a

637
00:31:51,137 --> 00:31:54,457
Speaker 1: minimum wage that puts the restaurant out of business. We

638
00:31:54,577 --> 00:31:57,577
Speaker 1: have some interesting things going on in Michigan where you

639
00:31:57,657 --> 00:32:02,657
Speaker 1: might get rid of tipping, have all servers make a

640
00:32:02,697 --> 00:32:05,817
Speaker 1: certain minimum wage. Some servers don't like that because if

641
00:32:05,857 --> 00:32:08,377
Speaker 1: they get tipped at a restaurant, they can make way

642
00:32:08,417 --> 00:32:14,217
Speaker 1: more than minimum wage. So it's a tough situation because people,

643
00:32:14,417 --> 00:32:16,337
Speaker 1: I don't know. People don't seem to want You're right,

644
00:32:16,377 --> 00:32:18,057
Speaker 1: they don't want to work the full day. You have

645
00:32:18,217 --> 00:32:20,777
Speaker 1: made people so jealous of you. They just want your job.

646
00:32:21,097 --> 00:32:24,137
Speaker 1: Well to see they have to recall though that. For example,

647
00:32:24,177 --> 00:32:25,737
Speaker 1: there was a time when I had to show up

648
00:32:26,097 --> 00:32:30,337
Speaker 1: to the NYPD and clock into the minute, and if

649
00:32:30,377 --> 00:32:33,137
Speaker 1: I was one minute late, I had to literally one

650
00:32:33,177 --> 00:32:36,097
Speaker 1: minute late for my tour. I would have to fill

651
00:32:36,097 --> 00:32:39,617
Speaker 1: out forms explaining why I was late, I would have

652
00:32:39,657 --> 00:32:42,857
Speaker 1: to add time onto the back. So when you've done

653
00:32:42,897 --> 00:32:44,497
Speaker 1: those kinds of jobs, where they want I mean the

654
00:32:44,537 --> 00:32:46,777
Speaker 1: same thing the CIA. I mean it's the CIA. They

655
00:32:46,777 --> 00:32:48,697
Speaker 1: know where you are, right, So I would come in.

656
00:32:49,057 --> 00:32:51,697
Speaker 1: You're expected to be there the certain hours you're there,

657
00:32:51,977 --> 00:32:54,857
Speaker 1: and they're also people talk about overtime and stuff, but

658
00:32:54,897 --> 00:32:57,537
Speaker 1: we would just you would work way more hours than

659
00:32:57,537 --> 00:32:59,417
Speaker 1: what was expected. I mean we were in a war

660
00:32:59,497 --> 00:33:02,777
Speaker 1: office effectively the Rock office, and so there wasn't a

661
00:33:02,817 --> 00:33:04,617
Speaker 1: lot of like, oh it's five o'clock, time to go,

662
00:33:04,697 --> 00:33:06,377
Speaker 1: you know, if there was work to be done, people

663
00:33:06,417 --> 00:33:09,257
Speaker 1: just stayed and did it. But yeah, no, absolutely, I

664
00:33:09,257 --> 00:33:12,017
Speaker 1: mean coming into media, I joke about this with people

665
00:33:12,017 --> 00:33:13,577
Speaker 1: all the time in the business, I'm like, this is

666
00:33:13,897 --> 00:33:15,937
Speaker 1: it is a gift. I feel like everybody who gets

667
00:33:15,977 --> 00:33:19,737
Speaker 1: to make content and inform people for a living is

668
00:33:19,937 --> 00:33:22,497
Speaker 1: incredibly lucky. And if you've done other jobs as I

669
00:33:22,537 --> 00:33:25,377
Speaker 1: have before this, and I was doing intel work for

670
00:33:25,417 --> 00:33:28,537
Speaker 1: about seven years, then when you get to do this,

671
00:33:28,617 --> 00:33:30,777
Speaker 1: you say to yourself, well, this is really this is

672
00:33:30,777 --> 00:33:33,177
Speaker 1: really a special thing. I mean I could be sitting

673
00:33:33,177 --> 00:33:34,657
Speaker 1: here people don't even know I could be sitting here

674
00:33:34,657 --> 00:33:36,777
Speaker 1: in my pajamas right now doing this podcast. They don't

675
00:33:36,777 --> 00:33:40,457
Speaker 1: even know that would not have flown in the Iraq office.

676
00:33:40,537 --> 00:33:42,017
Speaker 1: Let me tell you that it was jacket and tie

677
00:33:42,057 --> 00:33:45,137
Speaker 1: every day there. So I think if I were the

678
00:33:45,257 --> 00:33:48,017
Speaker 1: king of New York that I could fix New York

679
00:33:48,057 --> 00:33:50,617
Speaker 1: City pretty quickly because I know the city super well

680
00:33:50,657 --> 00:33:53,777
Speaker 1: and I understand the deficiencies. I firmly believe that, like,

681
00:33:53,777 --> 00:33:56,337
Speaker 1: if New York would just bring me in and let

682
00:33:56,337 --> 00:33:58,337
Speaker 1: me be more than the mayor, I have to be

683
00:33:58,417 --> 00:34:00,297
Speaker 1: kind of the dictator of New York, Like I couldn't

684
00:34:00,297 --> 00:34:02,297
Speaker 1: have like the city council chirping in my ear about

685
00:34:02,377 --> 00:34:04,697
Speaker 1: some nonsense. If they has empowered me, I could fix it.

686
00:34:05,337 --> 00:34:07,257
Speaker 1: Detroit used to be one of the greatest cities, one

687
00:34:07,297 --> 00:34:10,377
Speaker 1: of the greatest cities in America. Now Detroit on rtually

688
00:34:10,417 --> 00:34:12,777
Speaker 1: mean I grew up, I watched the RoboCop movies, you know,

689
00:34:12,897 --> 00:34:15,417
Speaker 1: Beverly Hills Cop. I mean, Detroit has a reputation as

690
00:34:15,417 --> 00:34:19,817
Speaker 1: a city and it's not a particularly pleasant one for

691
00:34:19,857 --> 00:34:23,577
Speaker 1: the last twenty thirty years or so? Could it be fixed?

692
00:34:24,537 --> 00:34:27,497
Speaker 1: Do you think you could bring Detroit back? Well, I

693
00:34:27,537 --> 00:34:30,137
Speaker 1: will tell you one of the You asked earlier, what's

694
00:34:30,337 --> 00:34:32,537
Speaker 1: some of the most shocking stuff you discovered on the

695
00:34:32,617 --> 00:34:37,337
Speaker 1: campaign trail. There is a significant amount of corruption in

696
00:34:37,377 --> 00:34:39,817
Speaker 1: the state of Michigan, so that is part of the

697
00:34:39,857 --> 00:34:42,457
Speaker 1: big problem in Detroit. But of course, yes, it can

698
00:34:42,497 --> 00:34:45,417
Speaker 1: be fixed, it can be brought back. Detroit should be

699
00:34:45,537 --> 00:34:48,617
Speaker 1: I mean, Detroit really should overtake Chicago and be the

700
00:34:48,657 --> 00:34:52,057
Speaker 1: big city of the Midwest because it's beautiful. We have

701
00:34:52,137 --> 00:34:55,457
Speaker 1: an incredible landscape. You can just go up, just go

702
00:34:55,617 --> 00:34:59,177
Speaker 1: north of Detroit. You'd be at right on an island.

703
00:34:59,297 --> 00:35:01,897
Speaker 1: You can be vacationing. You can go up to mackinaw

704
00:35:02,137 --> 00:35:04,177
Speaker 1: you can vacation. You can come over to my side

705
00:35:04,177 --> 00:35:06,657
Speaker 1: of the state, be at the beach. Michigan is an

706
00:35:06,697 --> 00:35:10,937
Speaker 1: absolutely stunning state. You can go skiing, you can snow

707
00:35:11,017 --> 00:35:13,177
Speaker 1: skiing in the winter, you can go water skiing in

708
00:35:13,217 --> 00:35:17,217
Speaker 1: the summer. And you have this beautiful city right on

709
00:35:17,257 --> 00:35:20,177
Speaker 1: the edge of the state. And you can go back

710
00:35:20,177 --> 00:35:23,377
Speaker 1: and forth to Canada. You can go over there and

711
00:35:23,457 --> 00:35:25,657
Speaker 1: gamble if you want, you can come right back. You

712
00:35:25,657 --> 00:35:27,977
Speaker 1: can do all kinds of fun things from the state

713
00:35:28,017 --> 00:35:31,177
Speaker 1: of Michigan and from the city of Detroit. But we

714
00:35:31,297 --> 00:35:34,497
Speaker 1: have and it has built back quite a bit. Detroit

715
00:35:34,617 --> 00:35:37,537
Speaker 1: is much better than what you think of Detroit from

716
00:35:37,617 --> 00:35:41,417
Speaker 1: the past. The reputation of Detroit has kind of stuck

717
00:35:41,457 --> 00:35:43,617
Speaker 1: with it. But if you go into Detroit now, there's

718
00:35:43,657 --> 00:35:47,257
Speaker 1: so many communities that have been built up, really beautiful communities,

719
00:35:47,417 --> 00:35:49,457
Speaker 1: and it does have a ways to go, but it's

720
00:35:49,537 --> 00:35:56,297
Speaker 1: certainly not from the standpoint of you see the murders

721
00:35:56,337 --> 00:36:00,537
Speaker 1: in Chicago and Saint Louis solid time, Detroit is very dangerous,

722
00:36:00,657 --> 00:36:03,937
Speaker 1: but we don't have that kind of level of crime.

723
00:36:04,057 --> 00:36:06,937
Speaker 1: So I do believe that that's been worked on. There's

724
00:36:06,977 --> 00:36:11,337
Speaker 1: the opportunity to increase community police seen to make sure

725
00:36:11,377 --> 00:36:14,217
Speaker 1: that we are building back that city and get investors.

726
00:36:14,217 --> 00:36:17,617
Speaker 1: But to get investors into Detroit, you really have to

727
00:36:17,657 --> 00:36:20,897
Speaker 1: make Michigan as a state more appealing. And that's one

728
00:36:20,897 --> 00:36:23,017
Speaker 1: of the things that we talked about quite a bit

729
00:36:23,057 --> 00:36:26,417
Speaker 1: on the campaign trails. How do we make Michigan more

730
00:36:26,457 --> 00:36:30,257
Speaker 1: appealing to businesses. I think in the last ten years,

731
00:36:30,377 --> 00:36:34,817
Speaker 1: Dallas has increased by two hundred headquarters. The state of

732
00:36:34,897 --> 00:36:37,577
Speaker 1: Michigan doesn't have that. So if we can make the

733
00:36:37,617 --> 00:36:40,817
Speaker 1: state of Michigan look better and build the roads that

734
00:36:40,857 --> 00:36:43,657
Speaker 1: we need, for new businesses, make sure that we get

735
00:36:43,697 --> 00:36:47,457
Speaker 1: our energy costs down, bring more businesses here. Then we

736
00:36:47,497 --> 00:36:51,097
Speaker 1: can build up Detroit. We can have investors come and

737
00:36:51,137 --> 00:36:54,617
Speaker 1: build up Detroit. But really Detroit gets a bad rap.

738
00:36:54,697 --> 00:36:57,097
Speaker 1: It has cleaned it up quite a bit. There has

739
00:36:57,137 --> 00:36:59,737
Speaker 1: been a lot of good work in policing done there

740
00:36:59,817 --> 00:37:02,417
Speaker 1: to bring the city back and make it safer. Needs

741
00:37:02,457 --> 00:37:06,257
Speaker 1: to be more done in the city of Detroit, but

742
00:37:06,417 --> 00:37:08,697
Speaker 1: I would love to see if be the shining star

743
00:37:08,737 --> 00:37:11,577
Speaker 1: in the Midwest. Yeah. I do think at one point

744
00:37:11,577 --> 00:37:14,097
Speaker 1: it was the highest back in the fifties, the era

745
00:37:14,177 --> 00:37:17,897
Speaker 1: of forward. Obviously, it was the highest per capita concentration

746
00:37:18,017 --> 00:37:21,377
Speaker 1: of millionaires of any city in the United States, which

747
00:37:21,377 --> 00:37:24,097
Speaker 1: I think is as an interesting statistic. And also there's

748
00:37:24,137 --> 00:37:28,057
Speaker 1: all these you've probably seen it, these urban tours or

749
00:37:28,217 --> 00:37:32,897
Speaker 1: or urbanum kind of photography landscape things where the'll go

750
00:37:32,937 --> 00:37:36,537
Speaker 1: and they'll show these beautiful old buildings in Detroit that

751
00:37:36,577 --> 00:37:39,497
Speaker 1: have been abandoned. You know, these these things that were

752
00:37:39,537 --> 00:37:43,297
Speaker 1: built that looked like cathedrals practically, I mean, they're they're

753
00:37:43,297 --> 00:37:46,817
Speaker 1: amazing structures have just been you know, left left to

754
00:37:47,457 --> 00:37:51,177
Speaker 1: grow with vines and trash and everything. So clearly there's

755
00:37:51,337 --> 00:37:53,577
Speaker 1: a great history. I have heard the downtown has gotten

756
00:37:53,577 --> 00:37:56,017
Speaker 1: a lot better. I've actually I've never been to Detroit,

757
00:37:56,097 --> 00:37:58,417
Speaker 1: so maybe this is an opportunity for me to put

758
00:37:58,417 --> 00:38:01,297
Speaker 1: it on the wall, come spend some money in the

759
00:38:01,337 --> 00:38:04,697
Speaker 1: state of Michigan. But I will say that if we're

760
00:38:04,737 --> 00:38:07,897
Speaker 1: being really honest about Michigan, you brought up forward. What

761
00:38:08,017 --> 00:38:10,137
Speaker 1: a perfect time to talk about the fact that the

762
00:38:10,177 --> 00:38:13,257
Speaker 1: automotive industry is leaving the state of Michigan. And Gretchen

763
00:38:13,297 --> 00:38:15,457
Speaker 1: Whitmer will go out every day and tell you all

764
00:38:15,457 --> 00:38:17,897
Speaker 1: of the auto jobs that she's brought back. We lost

765
00:38:17,977 --> 00:38:21,417
Speaker 1: thirty two thousand auto jobs I think thirty four thousand,

766
00:38:21,617 --> 00:38:24,017
Speaker 1: eighty two thousand jobs total in the state of Michigan

767
00:38:24,057 --> 00:38:27,137
Speaker 1: while she was governor. But our auto jobs have really

768
00:38:27,337 --> 00:38:32,777
Speaker 1: really declined over the past four years. And the autocompany

769
00:38:32,897 --> 00:38:35,177
Speaker 1: she'll tell you that the autocompanies are coming here, that

770
00:38:35,177 --> 00:38:38,177
Speaker 1: we're getting these battery plants. But you're seeing the battery plants.

771
00:38:38,377 --> 00:38:42,337
Speaker 1: Go into Ohio, go into Tennessee, go into North Carolina,

772
00:38:42,377 --> 00:38:44,657
Speaker 1: and where the battery plants are, you will see the

773
00:38:44,697 --> 00:38:48,217
Speaker 1: assembly plants. Because that battery is the same size as

774
00:38:48,257 --> 00:38:51,897
Speaker 1: the vehicle so right now, I had a donor say

775
00:38:51,897 --> 00:38:55,177
Speaker 1: to me, well, we didn't want to support you in

776
00:38:55,217 --> 00:38:58,337
Speaker 1: the race because we weren't sure what would happen. So

777
00:38:58,377 --> 00:39:01,137
Speaker 1: we cut a deal with Whitmer, and she said that

778
00:39:01,457 --> 00:39:05,097
Speaker 1: she would do all these things if we donated to her.

779
00:39:05,457 --> 00:39:07,777
Speaker 1: And then, can you believe one of the first things

780
00:39:07,817 --> 00:39:10,257
Speaker 1: they decided to do was go after right to work

781
00:39:10,297 --> 00:39:16,977
Speaker 1: in the state of Michigan. Yeah, yeah, yeah, how did

782
00:39:16,977 --> 00:39:20,017
Speaker 1: you not? And you know, I know that you're you're

783
00:39:20,097 --> 00:39:21,857
Speaker 1: in the in the commentary role now you're not an

784
00:39:21,897 --> 00:39:25,017
Speaker 1: active race. Is Gretchen Whittner a bad person? Because what

785
00:39:25,137 --> 00:39:27,017
Speaker 1: she did during the pandemic makes me think she's a

786
00:39:27,057 --> 00:39:29,537
Speaker 1: bad person. I'm just going to ask you. I will

787
00:39:29,577 --> 00:39:33,137
Speaker 1: just say that my interactions with her were always very pleasant. So, um,

788
00:39:33,417 --> 00:39:35,457
Speaker 1: you are such a nice person. I have to say,

789
00:39:35,497 --> 00:39:39,657
Speaker 1: you're a very nice lady. I'm impressed. I haven't even

790
00:39:39,657 --> 00:39:41,217
Speaker 1: met her, and I want to treasure I'm like, I

791
00:39:41,257 --> 00:39:44,177
Speaker 1: cannot believe with you to keep going. I'm sorry, Well,

792
00:39:45,097 --> 00:39:47,057
Speaker 1: she was always very nice to me. I don't like

793
00:39:47,097 --> 00:39:50,017
Speaker 1: her policies, I mean, and I will never like her

794
00:39:50,057 --> 00:39:53,577
Speaker 1: policies because her policies are very progressive. She is a

795
00:39:53,697 --> 00:39:56,777
Speaker 1: very far leftist, So this is not somebody who is

796
00:39:57,057 --> 00:39:59,217
Speaker 1: I mean, she's talking about shutting down our pipeline and

797
00:39:59,377 --> 00:40:03,537
Speaker 1: that's something that nobody really addresses. A few people address,

798
00:40:03,657 --> 00:40:06,297
Speaker 1: but this is something that she's been pushing for four years,

799
00:40:06,297 --> 00:40:09,057
Speaker 1: shutting down our pipeline in the state of Michigan. She's

800
00:40:09,177 --> 00:40:12,097
Speaker 1: very progressive. With hunting. They came out with this new

801
00:40:12,217 --> 00:40:15,057
Speaker 1: hunting rule where if you shoot a deer, you have

802
00:40:15,137 --> 00:40:18,217
Speaker 1: to report it on this website now within forty or

803
00:40:18,337 --> 00:40:21,377
Speaker 1: seventy two hours. And our hunters are like, you know

804
00:40:21,577 --> 00:40:23,377
Speaker 1: a lot of times we're out, you know, a week

805
00:40:23,537 --> 00:40:26,137
Speaker 1: where we don't have any service and we can't do this.

806
00:40:26,177 --> 00:40:28,897
Speaker 1: How it doesn't matter if you get a misdemeanor. Why

807
00:40:29,097 --> 00:40:31,257
Speaker 1: do you have to report shooting a deer? I don't

808
00:40:31,297 --> 00:40:35,337
Speaker 1: know what's the point of that. The Department of Natural

809
00:40:35,377 --> 00:40:38,577
Speaker 1: Resources has to know if every time there is a

810
00:40:38,617 --> 00:40:41,217
Speaker 1: deer that is taken out of the herd, and they

811
00:40:41,337 --> 00:40:43,537
Speaker 1: keep track of exactly how many deer are shot of

812
00:40:43,577 --> 00:40:46,177
Speaker 1: a year, which I understand, but it's the amount of

813
00:40:46,217 --> 00:40:47,777
Speaker 1: time that you have to have it done it and

814
00:40:47,817 --> 00:40:50,137
Speaker 1: you have to do it online. This is something that

815
00:40:50,457 --> 00:40:53,177
Speaker 1: is not easy for our hunters. But then they're coming

816
00:40:53,177 --> 00:40:57,057
Speaker 1: out with these rules. Agencies that are not legislators are

817
00:40:57,097 --> 00:41:00,497
Speaker 1: coming out with rules that end up with misdemeanors if

818
00:41:00,537 --> 00:41:02,017
Speaker 1: you don't do them. And guess what if you get

819
00:41:02,017 --> 00:41:04,937
Speaker 1: a misdemeanor, then you lose your CPL. So you can

820
00:41:05,017 --> 00:41:07,697
Speaker 1: have your guns taken away, you can have your rights

821
00:41:07,737 --> 00:41:11,377
Speaker 1: taken away because someone who's not a lawmaker made a

822
00:41:11,497 --> 00:41:15,097
Speaker 1: law that results in you getting a misdemeanor that results

823
00:41:15,137 --> 00:41:16,937
Speaker 1: in no CPR. Are you Are you a hunter? By

824
00:41:16,937 --> 00:41:19,857
Speaker 1: the way, I am not a hunter, but I spent

825
00:41:19,977 --> 00:41:21,937
Speaker 1: a lot of time, so I spent a lot of

826
00:41:21,977 --> 00:41:25,137
Speaker 1: time with hunters while I was campaigning and learning. You know,

827
00:41:25,337 --> 00:41:27,017
Speaker 1: I'm one of those people that I feel like I

828
00:41:27,097 --> 00:41:29,337
Speaker 1: have to do it so I can totally understand it.

829
00:41:29,537 --> 00:41:30,937
Speaker 1: So one day they said, do you want to go

830
00:41:30,977 --> 00:41:35,417
Speaker 1: bear hunting? And I'm like, of course, But inside I thought,

831
00:41:36,977 --> 00:41:39,017
Speaker 1: I'm gonna tell you. I'm gonna tell you right now

832
00:41:39,057 --> 00:41:41,777
Speaker 1: toooter just you, me and the many many people who

833
00:41:41,817 --> 00:41:43,377
Speaker 1: will hear this. So this is like we're in a

834
00:41:43,457 --> 00:41:47,497
Speaker 1: friend zone here, um the trust tree. I think bears

835
00:41:47,497 --> 00:41:49,977
Speaker 1: are so cute. I could never shoot a bear. I'm

836
00:41:50,017 --> 00:41:54,097
Speaker 1: just I don't know. This is my fear. I'm like,

837
00:41:54,257 --> 00:41:56,857
Speaker 1: we're gonna I'm gonna be really strong. I'm gonna I'm

838
00:41:56,857 --> 00:41:59,097
Speaker 1: gonna watch this happen, and I'm gonna be And I

839
00:41:59,137 --> 00:42:01,657
Speaker 1: worried about it for two weeks beforehand, and I'm like,

840
00:42:01,977 --> 00:42:04,857
Speaker 1: what's it like? You know, in my mind, we are

841
00:42:04,897 --> 00:42:08,657
Speaker 1: out all day going through the woods, you know, in

842
00:42:08,657 --> 00:42:12,137
Speaker 1: in all camo and trying to find these deer and

843
00:42:12,177 --> 00:42:14,857
Speaker 1: we get there and like, no, you ride in a car,

844
00:42:15,017 --> 00:42:16,777
Speaker 1: you would look for the tracks and then you chase

845
00:42:16,817 --> 00:42:19,537
Speaker 1: the steer down. But fortunately we were a week before

846
00:42:19,697 --> 00:42:21,897
Speaker 1: you could actually shoot the deer. So this was just

847
00:42:22,097 --> 00:42:26,937
Speaker 1: like practice deer or bear chasing. Bear bear chasing. Yes,

848
00:42:27,257 --> 00:42:30,417
Speaker 1: so we couldn't shoot any bears while we were out there,

849
00:42:30,457 --> 00:42:32,817
Speaker 1: but we could track them down and chase it. And

850
00:42:32,857 --> 00:42:37,577
Speaker 1: then they send these dogs. The dogs are really chase. Yeah,

851
00:42:37,617 --> 00:42:40,777
Speaker 1: So it was it was a rough I just want

852
00:42:40,777 --> 00:42:42,777
Speaker 1: to be friends with the bear and let them get

853
00:42:43,057 --> 00:42:45,137
Speaker 1: a picnic basket. I think they want to be friends

854
00:42:45,137 --> 00:42:46,897
Speaker 1: with you, though, so you should be careful. That is

855
00:42:46,937 --> 00:42:49,857
Speaker 1: probably true. Actually they're probably you know, they're they're they

856
00:42:49,897 --> 00:42:51,977
Speaker 1: look cute. From Afar. I remember I saw grizzlies up

857
00:42:52,017 --> 00:42:55,217
Speaker 1: in Alaska, and from far away you're like, they're majestic

858
00:42:55,297 --> 00:42:57,777
Speaker 1: and beautiful. And then it got within about fifty yards

859
00:42:57,777 --> 00:43:00,217
Speaker 1: of us, and I was like, um, we all have

860
00:43:00,297 --> 00:43:03,657
Speaker 1: fifty cowhandguns. Right, like you start to your your whole

861
00:43:03,937 --> 00:43:07,897
Speaker 1: sensibility goes from these things are amazing. I feel like

862
00:43:07,897 --> 00:43:10,617
Speaker 1: I'm you know, watching Wild Kingdom and Richard and Burrows

863
00:43:10,697 --> 00:43:13,577
Speaker 1: narrating to We're not gonna like get eaten right, you know,

864
00:43:13,697 --> 00:43:15,777
Speaker 1: it's it shifts very quickly when they get much known.

865
00:43:15,857 --> 00:43:20,977
Speaker 1: The grizzlies aren't there. Well they are. They're a little

866
00:43:20,977 --> 00:43:23,737
Speaker 1: bit more cuddling, but I don't like giant trash pandas

867
00:43:23,777 --> 00:43:26,577
Speaker 1: They're like they're like overgrown raccoons. Most most black bears

868
00:43:26,577 --> 00:43:29,977
Speaker 1: aren't really that big. Um. Before before we close, actually

869
00:43:30,017 --> 00:43:33,257
Speaker 1: I have I have kind of a serious question, political

870
00:43:33,257 --> 00:43:35,337
Speaker 1: analysis question. I want to ask you more about about

871
00:43:35,417 --> 00:43:38,337
Speaker 1: hunting and well, actually a quick one. What is the

872
00:43:38,337 --> 00:43:44,697
Speaker 1: most underrated place in Michigan in your mind? You know,

873
00:43:44,857 --> 00:43:46,977
Speaker 1: whether it's a city or a place to go, Like,

874
00:43:47,057 --> 00:43:50,257
Speaker 1: what's the place that you know you would say, um,

875
00:43:50,337 --> 00:43:53,097
Speaker 1: you know, like I don't know if I were talking

876
00:43:53,137 --> 00:43:55,777
Speaker 1: about New York, which I know super well, I would

877
00:43:55,817 --> 00:43:59,617
Speaker 1: say underrated, although everyone knows everything in New York, but

878
00:43:59,897 --> 00:44:03,177
Speaker 1: the north shore of rather the north Fork of Long Island,

879
00:44:03,337 --> 00:44:05,297
Speaker 1: is really amazing and you get a lot of the

880
00:44:05,417 --> 00:44:09,857
Speaker 1: advantage of the very famous Hampton's Beaches without the price

881
00:44:10,097 --> 00:44:13,697
Speaker 1: the craziness, for example. Right, So, well, we've spent a

882
00:44:13,697 --> 00:44:16,617
Speaker 1: lot of time in the Upper Peninsula of Michigan, and

883
00:44:16,897 --> 00:44:18,857
Speaker 1: I think that if you haven't been there, I mean,

884
00:44:18,897 --> 00:44:21,737
Speaker 1: it is truly God's country. It is the summertime, it

885
00:44:21,817 --> 00:44:23,897
Speaker 1: is so beautiful. We went in the summer, and we

886
00:44:23,937 --> 00:44:27,617
Speaker 1: went in February. February. You have to be a harder

887
00:44:27,697 --> 00:44:30,577
Speaker 1: core to go in February, because I thought I live

888
00:44:30,577 --> 00:44:32,817
Speaker 1: on the west side of Michigan. We get Lake Effect snows,

889
00:44:32,857 --> 00:44:35,777
Speaker 1: so in my mind I'm thinking I've seen a white out.

890
00:44:35,817 --> 00:44:38,577
Speaker 1: I know how bad snow is. No, it was nothing

891
00:44:38,657 --> 00:44:40,657
Speaker 1: compared a white out. I mean, I couldn't even see

892
00:44:40,657 --> 00:44:43,377
Speaker 1: my fingers in front of my face. This was so snowy.

893
00:44:43,417 --> 00:44:46,017
Speaker 1: But we got to see the dog sled race. If

894
00:44:46,097 --> 00:44:49,737
Speaker 1: you have never done that, that's what I think is underrated.

895
00:44:49,777 --> 00:44:51,617
Speaker 1: You've got to go stand out in the cold with

896
00:44:51,697 --> 00:44:55,177
Speaker 1: your hot cocoa and watch these people, these mushers, get

897
00:44:55,217 --> 00:44:57,817
Speaker 1: on their sleds and take off and just know that

898
00:44:57,857 --> 00:45:00,537
Speaker 1: they're going to be outside in this frigid cold night

899
00:45:00,617 --> 00:45:03,337
Speaker 1: after night, snuggled up with their dogs. And it is

900
00:45:03,497 --> 00:45:05,577
Speaker 1: pretty majestic to see that happened. I mean, this might

901
00:45:05,617 --> 00:45:08,817
Speaker 1: tell you. I'm the guy at the ski lodge who

902
00:45:08,937 --> 00:45:11,297
Speaker 1: is all about rooms service and like the hot tub

903
00:45:11,337 --> 00:45:17,257
Speaker 1: situation for everyone. You know, Yeah, I have no shame.

904
00:45:17,297 --> 00:45:19,377
Speaker 1: I'm like this, I'm taking a spat to whatever else

905
00:45:19,457 --> 00:45:23,617
Speaker 1: is snowshoeing or mushing or whatever. Um. One one last

906
00:45:23,657 --> 00:45:25,697
Speaker 1: thing for you, just how do we how do we

907
00:45:25,737 --> 00:45:28,857
Speaker 1: get a Republican to win? This was the serious question

908
00:45:28,897 --> 00:45:30,457
Speaker 1: that I was going to ask you, How do we

909
00:45:30,497 --> 00:45:33,777
Speaker 1: get a Republican to win in Michigan in twenty twenty four,

910
00:45:33,817 --> 00:45:38,777
Speaker 1: because that's obviously really important. Well that is okay, So

911
00:45:38,857 --> 00:45:42,057
Speaker 1: this is the major question in the state of Michigan

912
00:45:42,097 --> 00:45:45,257
Speaker 1: because you know that Michigan not only did we lose

913
00:45:45,257 --> 00:45:48,977
Speaker 1: the governor seat, but we lost the state and the

914
00:45:49,017 --> 00:45:51,417
Speaker 1: State House and State Senate. So we always we'd had

915
00:45:51,417 --> 00:45:55,577
Speaker 1: a majority for forty years, lost everything. So for Michigan,

916
00:45:55,617 --> 00:45:57,977
Speaker 1: I think it's really important to look to Florida and

917
00:45:58,017 --> 00:46:00,257
Speaker 1: I say that because I think so many people say

918
00:46:00,297 --> 00:46:03,057
Speaker 1: to me regularly, Oh, Rhonda Santis has been able to

919
00:46:03,137 --> 00:46:06,537
Speaker 1: do great things in Florida. But Rhonda Santis has only

920
00:46:06,537 --> 00:46:09,537
Speaker 1: been able to do great things in Florida because so

921
00:46:09,657 --> 00:46:12,657
Speaker 1: much the procedure on the ground was set up in

922
00:46:12,697 --> 00:46:16,897
Speaker 1: the past for him. And I mean that by Rick Scott,

923
00:46:16,897 --> 00:46:19,977
Speaker 1: by Jeb Bush. The ground game that we've talked about

924
00:46:20,057 --> 00:46:22,817
Speaker 1: so much about mail in ballots. You know, Florida was

925
00:46:22,857 --> 00:46:25,737
Speaker 1: never complaining about this. They knew that a lot of

926
00:46:25,737 --> 00:46:28,497
Speaker 1: their population is using mail in ballots, so they had

927
00:46:28,537 --> 00:46:32,057
Speaker 1: that ground game of chasing ballots. We as Republicans have

928
00:46:32,097 --> 00:46:34,857
Speaker 1: a habit of chasing voters. We have rallies, we talk

929
00:46:34,937 --> 00:46:36,897
Speaker 1: to people, we want to get people together, and we

930
00:46:36,977 --> 00:46:41,057
Speaker 1: think we've got all these voters. But for Democrats that

931
00:46:41,257 --> 00:46:44,577
Speaker 1: this is a machine we want. If you're a Democrat,

932
00:46:44,777 --> 00:46:47,617
Speaker 1: we want ballots in our bag. We know we have them,

933
00:46:47,697 --> 00:46:52,097
Speaker 1: they are packed away, those votes are we already have them,

934
00:46:52,137 --> 00:46:54,897
Speaker 1: We've already counted them. So that's what we have to

935
00:46:54,977 --> 00:46:57,937
Speaker 1: change our mindset as Republicans and say we've got to play.

936
00:46:58,217 --> 00:46:59,937
Speaker 1: We've got to play on the same level. We have

937
00:47:00,057 --> 00:47:01,777
Speaker 1: got to make sure that we're doing that, that we

938
00:47:01,897 --> 00:47:05,217
Speaker 1: are identifying new voters, we find out who they are.

939
00:47:05,217 --> 00:47:08,777
Speaker 1: And Florida has done this. Florida has registered more Republicans

940
00:47:08,817 --> 00:47:11,737
Speaker 1: every single year. Ground game like you would not believe,

941
00:47:11,817 --> 00:47:14,457
Speaker 1: going out using data checking to see how many people

942
00:47:14,457 --> 00:47:17,137
Speaker 1: are in this neighborhood, how many are Republicans? The rest

943
00:47:17,137 --> 00:47:20,057
Speaker 1: who aren't registered are probably Republicans. Will go do that

944
00:47:20,337 --> 00:47:23,457
Speaker 1: and they go and they register them, then they hunt

945
00:47:23,497 --> 00:47:27,137
Speaker 1: the mail in ballots. They've got this down. So I'm

946
00:47:27,177 --> 00:47:30,057
Speaker 1: saying for all states. If you're looking at all state,

947
00:47:30,417 --> 00:47:32,617
Speaker 1: all states that are saying, wow, how are we going

948
00:47:32,657 --> 00:47:35,777
Speaker 1: to get back in the game as Republicans win. Let's

949
00:47:35,777 --> 00:47:38,617
Speaker 1: take a look at what the successful states have done,

950
00:47:38,817 --> 00:47:41,737
Speaker 1: what their motto or what their method has been to

951
00:47:41,817 --> 00:47:45,137
Speaker 1: get those ballots and bring that to our other purple

952
00:47:45,217 --> 00:47:48,377
Speaker 1: states and turn them red. But it's hard, it's work.

953
00:47:48,737 --> 00:47:50,977
Speaker 1: It's got to be a lot of raising money, it's

954
00:47:50,977 --> 00:47:52,857
Speaker 1: got to be a lot of people on the ground.

955
00:47:52,897 --> 00:47:55,657
Speaker 1: This is a business. This is not this is not

956
00:47:55,737 --> 00:47:58,377
Speaker 1: just a feeling. It's got to be a business mindset

957
00:47:58,377 --> 00:48:01,137
Speaker 1: of we have a job to do and we've got

958
00:48:01,137 --> 00:48:04,417
Speaker 1: to get it done. Tutor, thanks so much. For being

959
00:48:04,497 --> 00:48:06,497
Speaker 1: with us here today on the Buck Sex and Show.

960
00:48:06,577 --> 00:48:10,417
Speaker 1: Where can everyone go to follow your work, your projects ahead,

961
00:48:10,817 --> 00:48:13,337
Speaker 1: help you save Michigan, make Michigan great again, all of

962
00:48:13,337 --> 00:48:17,737
Speaker 1: it well we are. I'm at on Twitter at tutor Dixon,

963
00:48:17,777 --> 00:48:21,137
Speaker 1: on Facebook at tutor Dixon, and the tutor dixon dot

964
00:48:21,177 --> 00:48:24,697
Speaker 1: com website is under construction. We will be unveiling something

965
00:48:24,737 --> 00:48:27,617
Speaker 1: new soon, so stay tuned for that and check back in.

966
00:48:28,457 --> 00:48:30,417
Speaker 1: Tutor Dixon, thanks so much for being with us. Good

967
00:48:30,417 --> 00:48:32,417
Speaker 1: to see you. Thank you so much