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Speaker 1: Well, joining me now is one of the most I

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Speaker 1: think interesting people in American politics today. It's the head

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Speaker 1: of the Teamsters Union and Sean O'Brien. Before we get

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Speaker 1: started with sort of your life in the literally in

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Speaker 1: the center lane of American politics these days, the Teamsters

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Speaker 1: in general have a reputation, you know, my lifetime, of

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Speaker 1: being the less partisan of the major unions that you know,

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Speaker 1: while you know, when I was growing up, most of

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Speaker 1: the labor movement was Democratic. But if there was a

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Speaker 1: labor union that would be open to supporting Republicans, it

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Speaker 1: was the Teamsters. Walk me through that. What is that relationship?

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Speaker 1: Why is that What would you say explains that history?

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Speaker 2: Well, I think what explains the histories. We are one

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Speaker 2: of the lodgest We always have been one of the largest,

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Speaker 2: I believe, most influential unions in the country. You know,

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Speaker 2: we've been around since nineteen oh three. But we're very diverse.

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Speaker 2: We're a very diverse union. We always have been and

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Speaker 2: I think we always will be. And you know there's

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Speaker 2: no secret that you know, we have endorsed Republican candidates prior,

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Speaker 2: but historically we've always went with Democrats, and I think

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Speaker 2: you know that I'm a lifelong Democrat, so I was

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Speaker 2: brought up in a Democratic state, so you know, you

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Speaker 2: always pulled that party line. But you know the history,

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Speaker 2: if you look back in history, it wasn't always that

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Speaker 2: way with the teams As union, you know, I think

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Speaker 2: the philosophy has always been, let's try and work with

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Speaker 2: the people that are going to work on behalf of

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Speaker 2: the best interests of our members. And that's why we're

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Speaker 2: a little bit different than most because we're a lot,

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Speaker 2: we're transparent, we're inclusive, and we want to support people

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Speaker 2: that are going to support our issues regardless of what

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Speaker 2: their political affiliation has. And that's always been the case

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Speaker 2: pretty much.

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Speaker 1: Uh. The if I were to paint a picture of

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Speaker 1: the average Teamsters member of a Teamsters union, it's a

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Speaker 1: it's a truck driver. But that is I think being

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Speaker 1: very myopic. Tell me, you're actually a very diverse set

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Speaker 1: of workers, uh that are that are members of the

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Speaker 1: Teamsters Union. Walk my listeners through that.

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Speaker 3: All right?

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Speaker 2: The easiest way to describe it, because it is a

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Speaker 2: very complicated, uh description if you try to you know,

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Speaker 2: sector bisector, so building trades or a company or electrician. Uh,

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Speaker 2: you're a plumber, right. Everybody knows that's what you are.

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Speaker 2: The teamster is the best way to say it, and

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Speaker 2: I say it all the time. We represent everybody from

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Speaker 2: airline pilots to zoom keepers and everybody in between.

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Speaker 1: I remember, like you guys have been helping to organize

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Speaker 1: Amazon worker we have.

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Speaker 2: Yeah, we we've uh, we've actually taken that fight on.

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Speaker 2: We joined forces with Amazon Labor Union, which success organized

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Speaker 2: in New York. And you know, there's no secret that

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Speaker 2: we have a longstanding relationship bargaining relationship with UPS, which

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Speaker 2: is one of the was the largest UH package delivery companies,

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Speaker 2: and so it was a natural fit for us to

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Speaker 2: uh joined forces and women organizing uh the direct employees

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Speaker 2: and also organizing the third party leasing arrangement, which is

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Speaker 2: a scam and a shell game, which we all know about.

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Speaker 2: So that's been our biggest focus. Amazon not just to

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Speaker 2: the teams is Union, not just to you know, germane

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Speaker 2: to us. But they're probably going to be the biggest

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Speaker 2: threat to organize labor UH because they have their fingers

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Speaker 2: in so many different industries and so many different uh

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Speaker 2: you know, technologies that could affect us.

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Speaker 1: So you know, let's talk about automated robotic. Look, Amazon

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Speaker 1: is going hard at replacing the human being. They want

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Speaker 1: to replace the human being as fast as possible. Amazon's

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Speaker 1: not alone, They're just the largest entity with the resources

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Speaker 1: to do it. You're try to protect human labor.

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Speaker 2: Well, we have to protect human labor, because you know,

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Speaker 2: without human labor, where are these folks gonna go. And

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Speaker 2: that didn't get the opportunity to go to college, that

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Speaker 2: didn't get the opportunity that that some people got, and look,

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Speaker 2: you know, AI is probably the biggest threat to the

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Speaker 2: human population. And I think, you know, and I've been

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Speaker 2: focused on this meeting with people that I normally wouldn't

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Speaker 2: even talk to because my concern is, like, what is

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Speaker 2: what effect is AI? Because it's so it's so complicated.

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Speaker 2: But I think what we're going to see with AI

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Speaker 2: and this automation and all these corporations that are falling

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Speaker 2: in love with it, you're going to see the the

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Speaker 2: upper management of a lot of these corporations be affected

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Speaker 2: by AI because they're not gonna need all these analysts,

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Speaker 2: they're not gonna need all these white collar jobs. So

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Speaker 2: you're going to see a further disparity once that middle

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Speaker 2: layer management is you know, basically affected and they lose

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Speaker 2: their jobs, You're going to see CEOs pay continue to

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Speaker 2: grow because all the savings. My mission is to make

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Speaker 2: sure that we capture capture that money for the folks

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Speaker 2: that are still working these blue collar jobs and create

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Speaker 2: hopefully opportunity for retraining in new jobs as a result

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Speaker 2: of the implementation of technology. And Amazon, to your point,

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Speaker 2: doesn't care about the humans. They care about they care

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Speaker 2: about their brand, and they care about their profits, and

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Speaker 2: that's it.

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Speaker 1: You know, I'm pretty convinced that the issue of twenty

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Speaker 1: twenty eight is going to be like, if you're a

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Speaker 1: presidential candidate and you don't have a policy on AI

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Speaker 1: job displacement, you shouldn't be running for president. No, it's

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Speaker 1: probably going to be the table stakes, right, I.

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Speaker 2: Mean, twenty twenty eight is going to be like, so,

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Speaker 2: I just did some little bit of research on you

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Speaker 2: because I'm a huge fan, but I'm a little bit

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Speaker 2: more mature because I'm six days older than you. I

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Speaker 2: was born Actril second, nineteen seventy two.

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Speaker 1: No, kiddy, look at that, all right.

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Speaker 2: But it's gonna be like twenty twenty eight has the

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Speaker 2: potential to be like, do you remember WWF what was

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Speaker 2: that big event they used to have every a summer.

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Speaker 1: Slam, Summer Wrestlemanians, WrestleMania.

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Speaker 2: Yeah, like WrestleMania, but ye you.

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Speaker 1: Put the rumble at the end where there's a million

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Speaker 1: people in the ring.

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Speaker 2: But now, yeah, it's happening right now across the street

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Speaker 2: from where I'm at. But no, I mean, look, this

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Speaker 2: is a huge threat to the American workforce, and whether

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Speaker 2: you're a Republican or Democrat, you have to have a

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Speaker 2: solution in support network to support workers whose jobs are

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Speaker 2: going to be at risk. Maybe even you know extinct

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Speaker 2: and you're spawn on. I mean, everybody falls in love

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Speaker 2: with convenience and technology. We're all guilty of it. You know,

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Speaker 2: we own something online, we hit that button, we want

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Speaker 2: it yesterday. But what cost does that come at? Right?

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Speaker 2: Does it comes at a cost of someone's job?

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Speaker 1: What is your leverage? So let's take UPS UPS a

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Speaker 1: big you know the UPS drivers, and UPS says hey man,

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Speaker 1: we love these robot trucks and we're going to have

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Speaker 1: these robot drivers. What's your leverage to protect your human.

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Speaker 2: My leverage is the collective Bogging agreement we negotiated where

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Speaker 2: we negotiated language that any technological change needs to be

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Speaker 2: agreed upon. If there's a disagreement, it's subject to arbitration.

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Speaker 2: But we also know we also negotiate provisions that UPS

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Speaker 2: has to maintain a certain level of full time jobs

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Speaker 2: and create full time jobs as a result of it.

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Speaker 2: So you know, we're already in stages and it's been

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Speaker 2: going off a ten of twelve years where UPS in

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Speaker 2: the warehouses, where we have fifty four percent of our

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Speaker 2: membership out of three hundred and forty thousand apart time

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Speaker 2: is to get full time benefits, health and welfare, pension.

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Speaker 2: So we're very, very sensitive to any type of job elimination.

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Speaker 2: But we we're convinced and we have committees where because

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Speaker 2: of our collective bogging agreement, we can identify opportunities to

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Speaker 2: create new jobs as a result of technology being implemented.

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Speaker 2: So that's the difference right now between an unionized company

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Speaker 2: like UPS versus non union FedEx and or Amazon. We

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Speaker 2: have the ability because we negotiated those terms and conditions.

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Speaker 2: But you know, if you're a non union Amazon employee

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Speaker 2: inside the warehouse, you know chances are at some point

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Speaker 2: in time, if Amazon has the opportunity to replace you

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Speaker 2: with a robot. They are going to do their best

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Speaker 2: to do that. And I got to tell you, I

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Speaker 2: think we all know technology it's not full growth and

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Speaker 2: the best I always tell people, like when we're fighting

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Speaker 2: about these autonomous vehicles, which is disturbing to me, you know,

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Speaker 2: and I'm a Democrat. It's disturbing to me when you

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Speaker 2: have governors in California, in Illinois and Colorado who say, hey,

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Speaker 2: I want to support working people. I want to support

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Speaker 2: you know, the creation of jobs. And when you work

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Speaker 2: bipartisan on a state level and you have agreed to

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Speaker 2: legislation that's going to mandate human operators and commercial vehicles

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Speaker 2: and it gets to the governor's desk and they veto it,

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Speaker 2: what does that signal this just happened.

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Speaker 1: So you brought this up? You look you it's like

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Speaker 1: you read my research on you, and but I was

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Speaker 1: about this was very recent legislation. And these are three

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Speaker 1: Democratic governors who all are all want labor support. I

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Speaker 1: probably all believe, you know, would say they're very supportive

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Speaker 1: of collective party. But Jared Poulos, Dab Pritzker, Gavin Newsom,

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Speaker 1: what's their explanation for why they vetoed these bills.

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Speaker 2: That is a great question. So what do they tell

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Speaker 2: you? You're probably going to find this how to believe Newsom

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Speaker 2: is not a big fan of Sean O'Brien. Have been

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Speaker 2: critical of him because he's in love with big tech.

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Speaker 2: I mean, that's the bottom line, right.

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Speaker 1: You see tech as adversarial.

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Speaker 2: I see tech as adversarial because the script has been

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Speaker 2: flipped right from where the report publicans were fifteen years ago.

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Speaker 2: Now the Democrats seem to be holding their seats and

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Speaker 2: falling in love. I call it like Stockholm syndrome. You know,

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Speaker 2: some of these governors have fallen in love or some

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Speaker 2: of the Democrats have fallen in love with their captor, right,

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Speaker 2: and they don't know the result, the catastrophic result. I

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Speaker 2: talked to the governor from Colorado, right, called him up

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Speaker 2: before because we were getting word that. You know, he

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Speaker 2: was on the fence whether he was going to veto

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Speaker 2: it or sign it into legislation. No, I forget. I

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Speaker 2: was in Times Square, I was at another event, and

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Speaker 2: I called him. I said, look, this is going to

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Speaker 2: be detrimental to working people. It's going to be detrimental

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Speaker 2: to CBL license holders. It's not just a union issue.

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Speaker 2: I go, there could be like two hundred and fifty

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Speaker 2: thousand people affected by this. He's like, I love the team,

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Speaker 2: says I go, okay, this is where I've always supported

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Speaker 2: you and everything you've done. I don't know whether that's

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Speaker 2: true or not. I'm saying to myself, he says, but

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Speaker 2: I just can't be with you on this one. I said, really,

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Speaker 2: this is the one that really matters. This is the

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Speaker 2: only one that matter is. I said, where are you

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Speaker 2: going to put those two hundred and fifty thousand well

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Speaker 2: to why I'm going to set two hundred thousand, two

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Speaker 2: unre fifty thousand people that lose their job? Where are

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Speaker 2: they gonna go? I said? And furthermore, I drove a

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Speaker 2: truck my whole life. I said, you know, the best

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Speaker 2: technology and the best information is a human hot instinct

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Speaker 2: in their brain. They can react quicker than any computer.

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Speaker 2: What are you going to do when you're platooning a

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Speaker 2: vehicle wearing two hundred forty thousand pounds and a malfunction

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Speaker 2: kills a family of four? Are you gonna be okay

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Speaker 2: with that? Because I certainly am not going to be

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Speaker 2: okay with it? And he says, oh, you know what,

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Speaker 2: don't worry about that stuff. It's ten to fifteen years

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Speaker 2: down the road. I said, no, it's ten to fifteen

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Speaker 2: minutes down the road. But that's the perplexing stuff for us.

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Speaker 2: And that's where you know, I get criticized sometimes because

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Speaker 2: they'll say, well, you're a labor leader and you're criticizing

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Speaker 2: the Democrats. Well, I'm a label leader that criticizes the Republicans.

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Speaker 2: I'm a labor leader criticizes the independence as well when

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Speaker 2: you're not making reasonable decisions on how it's going to

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Speaker 2: affect working people. More so, your constituents who if they

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Speaker 2: don't have a job, where do they go? They want,

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Speaker 2: they go, They go on the they go on the

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Speaker 2: they go on the done.

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Speaker 1: Look, I look at your job is to you have

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Speaker 1: one job, right, You're there to protect your workers. You're

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Speaker 1: there to do that. I get that. What is you

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Speaker 1: also have to be responsive to technological change? What's your recipe?

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Speaker 1: If you could go back to Polus, you could go

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Speaker 1: back to pritzkerg and say, look, I get that. You

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Speaker 1: want to you want to be able to innovate. You

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Speaker 1: want to be able to to to allow automation to

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Speaker 1: have a chance in some areas, where maybe automation will

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Speaker 1: be better in certain in certain things. You know, you

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Speaker 1: see things with microsurgeries, right that maybe having a robot

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Speaker 1: do it is better than the human hand. I think

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Speaker 1: we all accept that. Where's your line on this and

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Speaker 1: where do you feel where do you feel like you

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Speaker 1: have to show some flexibility?

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Speaker 2: That's a great question. I don't think. I think people

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Speaker 2: there's a perception out there when you speak against anything

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Speaker 2: that has an effect on jobs, you have viewed as

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Speaker 2: an impediment, right, and that impediment is what That impediment

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Speaker 2: is the bottom line of a balance sheet and the

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Speaker 2: profits of that company, int or technology. We do not

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Speaker 2: want to be an impediment that is going to potentially

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Speaker 2: maybe improve our members' jobs, improve productivity, improve work as safety.

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Speaker 2: We are going to embrace technology because we have for

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Speaker 2: since nineteen oh three. I mean, think about think about

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Speaker 2: what's behind me two horse heads and carriages. Right. What

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Speaker 2: technology that we had to deal with was a combustible

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Speaker 2: engine that came and created vehicles that we got off

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Speaker 2: of horses and got behind staring wilds and trucks. Right,

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Speaker 2: So we're not trying to be an impediment. We know

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Speaker 2: what's coming the problem is it's a difference between implementation

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Speaker 2: versus conversation and input. So, in other words, there seems

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Speaker 2: to be a disconnect where hey, we're just going to

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Speaker 2: implement this technology without any consideration of having a conversation

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Speaker 2: to say, hey, look this is what we're thinking of doing.

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Speaker 2: This potential could be the effect. What do you think

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Speaker 2: about this technology? It would say, great, However, where can

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Speaker 2: we create jobs? How is this going to affect workers?

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Speaker 2: Those conversations aren't happening. It's you know, we don't want

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Speaker 2: to be an impediment, but we want to be part

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Speaker 2: of the solution to a potential problem. As a result

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Speaker 2: of it, we know it's coming. Just give us a

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Speaker 2: seat at the table and hair our point of view.

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Speaker 2: And like we're seeing the grocery warehouse industry, you know,

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Speaker 2: there was a big push and there is a big

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Speaker 2: push in these big grocery warehouses where we represent you know,

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Speaker 2: thousands upon thousands of workers nationwide, the big grocery chains

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Speaker 2: where they did implement robots to select orders that did jobs. However,

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Speaker 2: we created jobs as a result of it. Who's going

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Speaker 2: to program these robots, who's going to maintain these robots,

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Speaker 2: who's going to do quality control. So we were able

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Speaker 2: to create jobs because we had those conversations, and we

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Speaker 2: maintain the workforce. We do not want to be impediment

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Speaker 2: to anything that's going to potentially make life easier. But

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Speaker 2: we can't embrace something where we don't have the knowledge

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Speaker 2: and or a solution to the bigger problem, which where

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Speaker 2: do you put these people to work.

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Speaker 1: Let's go back to the nineties and NAFTA and what

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Speaker 1: was in anticipation of what was going to be huge displacement,

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Speaker 1: massive job shifting, outsourcing overseas. Some of it was just

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Speaker 1: outsourcing from the north to the south, right to work

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Speaker 1: states versus so called white to work states, et cetera.

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Speaker 1: What were the mistakes that your predecessors in the labor

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Speaker 1: leadership world made then that you don't want to repeat, Well,

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Speaker 1: as we bring AI on board here.

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Speaker 2: Yeah, so again we took people for their word. I

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Speaker 2: think back then, you know, think about it when when

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Speaker 2: NAFTA came into effect, you know, Clinton introduced that. We

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Speaker 2: were very supportive of Clinton in the ninety two election.

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Speaker 2: All this isn't going to hurt, it's going to help.

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Speaker 2: You know, There'll be a residual value as a result.

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Speaker 2: Of these trade agreements, I think we trust Agay, you

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Speaker 2: guys were the least.

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Speaker 1: If I remember, the Teamsters were the most supportive of

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Speaker 1: NAFTA compared to the other unions, right.

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Speaker 2: Because it was well initially, yeah, initially we were very

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Speaker 2: very well. After that, we were anything that was introduced.

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Speaker 2: I think it was p and tr after that, Yeah,

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Speaker 2: trying to trade Dale and I think KAFTA was after that.

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Speaker 2: After getting burnt on NAFTA, you know, the skepticism was

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Speaker 2: at an all time high. So I think to your question,

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Speaker 2: what mistakes were made that I don't want to make

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Speaker 2: that my predecess made. They trusted the people that we

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Speaker 2: supported at that point in time, where I'm not suggest

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Speaker 2: you shouldn't trust people. But just because someone has a

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Speaker 2: d the name doesn't mean that making good policy behalf

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Speaker 2: of American workers. And I don't think it was well

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Speaker 2: thought out, uh and or explained. Well, maybe it wasn't

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Speaker 2: explained to to with all the facts associated with it.

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Speaker 2: So that's why we're being different. We're different nowadays under

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Speaker 2: our leadership because I'm having those conversations with both sides.

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Speaker 2: If the Republicans introduce something that it's good for us

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Speaker 2: I'm gonna go to the Democrats and say, all right,

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Speaker 2: the Republicans are telling us that this this is good

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Speaker 2: for our members. Is it good in your opinion?

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Speaker 3: Is it good?

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Speaker 2: And if it is, why is it? If it's not,

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Speaker 2: why is it not? So I don't think any of

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Speaker 2: those discussions happened, and I think people just back then, uh,

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Speaker 2: you know, took people for their word. I mean, I

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Speaker 2: just I'm not gonna do that, you know. I want

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Speaker 2: to know exactly what the effects are going to be.

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Speaker 2: And look, hopefully they're going to be honest and open

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Speaker 2: with us. If look, if I'm gonna if I'm gonna

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Speaker 2: take a hit, tell me I'm gonna take a hit.

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Speaker 2: That way, I can be prepared to defend it, you know.

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Speaker 2: But if you're going to be, you know, less than

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Speaker 2: honorable in telling us the effects and or your intentions,

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Speaker 2: then that's a problem for the people that tell us.

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Speaker 1: That there's a reason results matter more than promises, just

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Speaker 1: like there's a reason. Morgan and Morgan is America's largest

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Speaker 1: injury law firm. For the last thirty five years, they've

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Speaker 1: recovered twenty five billion dollars for more than half a

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Speaker 1: million clients. It includes cases where insurance companies offered next

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Speaker 1: to nothing, just hoping to get away with paying as

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Speaker 1: little as possible. Morgan and Morgan fought back ended up

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Speaker 1: winning millions. In fact, in Pennsylvania, one client was awarded

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Speaker 1: twenty six million dollars, which was a staggering forty times

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Speaker 1: the amount that the insurance company originally offered. That original

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Speaker 1: offer six hundred and fifty thousand dollars twenty six million,

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Speaker 1: six hundred and fifty thousand dollars. So with more than

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Speaker 1: one thousand lawyers across the country, they know how to

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Speaker 1: deliver for everyday people. If you're injured, you need a lawyer.

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Speaker 1: You need somebody to get your back. Check out for

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Speaker 1: the People dot com, Slash podcast, Ordal Pound Law, Pound

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Speaker 1: five two nine law on your cell phone. And remember

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Speaker 1: all law firms are not the same. So check out

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Speaker 1: Morgan and Morgan. Their fee is free unless they win.

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Speaker 1: When we look at you, know you've pointed out how

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Speaker 1: close an age we are. And in some ways, when

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Speaker 1: you and I were growing up, Democrats were the party

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Speaker 1: of labor. Republicans were to party of business. As you

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Speaker 1: and I became adults, the Democrats started to become basically

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Speaker 1: the Clinton wing of the party became the party of

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Speaker 1: business also, So then all of a sudden and there

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Speaker 1: was this moment where it looked like labor was shrinking

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Speaker 1: and shrinking and shrinking. Then then I think that the

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Speaker 1: Great Recession sort of awoken to people, right, and suddenly

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Speaker 1: there was people realized, oh, job protections, Maybe I can't

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Speaker 1: trust these entities. Where would you see? Was was the

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Speaker 1: setup a mistake back when we were kids that labor

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Speaker 1: shouldn't have been tied to one party and frankly business

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Speaker 1: shouldn't have been tied to one party.

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Speaker 2: Yeah, I mean I think if we all had a

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Speaker 2: duel of us, so to speak, no, we know now,

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Speaker 2: I think most of us would adopt the philosophy that

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Speaker 2: we're trying to adopt now. From my union, I can

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Speaker 2: only speak for my union.

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Speaker 1: Being Teamster's transactional rather than D and R.

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Speaker 2: Right, yeah, right, It's just what's who is going to bet?

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Speaker 2: Who is going to you know, make decisions that are

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Speaker 2: going to support working people. I mean, that's it's It's

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Speaker 2: not hard, it's pretty simple, and I think oftentimes we

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Speaker 2: complicate too many things. But I think if we had

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Speaker 2: a do over, it wouldn't be just you know, embracing

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Speaker 2: one party versus the other. And conversely, you know, one

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Speaker 2: party shouldn't embrace big business versus working people either. I mean,

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Speaker 2: I think both sides are guilty of that, right and

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Speaker 2: who's paying the consequence as far right now, I mean,

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Speaker 2: you think about these trade deals, these trade deals right now,

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Speaker 2: if you go back and you look at footage of

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Speaker 2: you know, and again I don't want to seem like

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Speaker 2: I'm picking on the guy Chuck Schumer. In nineteen ninety six,

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Speaker 2: he's given a speech on the Senate floor, I believe,

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Speaker 2: or maybe the House floor saying how bad the Chinadale

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Speaker 2: is and how we need to these tariffs and all

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Speaker 2: this other stuff. And then two thousand and seven, two

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Speaker 2: thousand and eight, Hillary Clinton's you know, explaining to her

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Speaker 2: policy and immigration. Now fast forward, you know, the same

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Speaker 2: positions that these folks were taking, you know, fifteen twenty

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Speaker 2: years ago, is the same policy is basically implemented under

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Speaker 2: this administration, although the immigration policy has been a little

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Speaker 2: bit more aggressive than probably people thought, which you know,

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Speaker 2: again that's another debate for another conversation, but it's like

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Speaker 2: contradicting it best. So for me and you, we've been

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Speaker 2: fortunate enough to look at what the the argument was

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Speaker 2: from the Dems then to what it is now, what

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Speaker 2: the arguments from the Republicans were then, and where we

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Speaker 2: are now. It's like it's so contradicting, Like who do

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Speaker 2: you believe?

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Speaker 1: Well, that's quite curious, you know, I've watched Marco Rubio

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Speaker 1: as a senator started to do this transition, right, the

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Speaker 1: guy who ran in twenty ten, in twenty sixteen versus

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Speaker 1: the guy you saw run for reelection in twenty twenty two.

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Speaker 1: Do you believe him?

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Speaker 3: So?

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Speaker 2: I don't know him that well, okay, but if you.

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Speaker 1: Don't want to pay I'm not picking on him. He's

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Speaker 1: an example of somebody that has shifted to being a

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Speaker 1: bit more friendly to your positions. But the question is

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Speaker 1: whether how do you get trusted? Is it just rhetorical?

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Speaker 1: Is he only there for the voters? You know?

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Speaker 2: No, So I agree with you he has he has

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Speaker 2: gotten a lot more sympathetic to our issues. I had

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Speaker 2: a conversation with him, and again I met a lot

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Speaker 2: of these folks at the r n c H when

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Speaker 2: I went there, But I had a conversation about a

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Speaker 2: month ago at the White House, and he probably didn't

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Speaker 2: know me from a hole in the wall prior to

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Speaker 2: the r n C. But he came right up to

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Speaker 2: me and he gave me his whole history of his

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Speaker 2: dad being a hotel worker, losing his job, they went

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Speaker 2: on strike, and he said all the right things, and

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Speaker 2: he's like, look, I like I embraced unions. It helped

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Speaker 2: me through my whole you know, childhood. We led a

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Speaker 2: good middle class life. So he's saying all the right things,

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Speaker 2: and the dealings that we've had to deal with them

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Speaker 2: on he's been fair, you know. Now, whether that's you know,

431
00:23:38,040 --> 00:23:43,240
Speaker 2: sincerity or politically motivated, the truth always comes out. I mean,

432
00:23:43,359 --> 00:23:46,040
Speaker 2: so if you had to ask me out, how's Macromobile?

433
00:23:46,400 --> 00:23:49,679
Speaker 2: Nice guy, great conversations with him, says all the right things.

434
00:23:51,400 --> 00:23:55,200
Speaker 1: When you what do you make of of of this

435
00:23:55,760 --> 00:23:59,199
Speaker 1: shift in the Republican Party over the last ten years?

436
00:23:59,359 --> 00:24:02,840
Speaker 1: Is it how much of it's been just rhetorical and

437
00:24:02,840 --> 00:24:04,840
Speaker 1: how much of it have you actually seen in policy?

438
00:24:05,040 --> 00:24:08,320
Speaker 2: So I'll tell you I can probably go a little

439
00:24:08,359 --> 00:24:11,600
Speaker 2: bit more. I can probably give a better better description

440
00:24:12,480 --> 00:24:14,080
Speaker 2: over the last three and a half years and ten

441
00:24:14,160 --> 00:24:20,160
Speaker 2: years because I come from Massachusetts, right and in Massachusetts,

442
00:24:20,200 --> 00:24:23,600
Speaker 2: as you know, especially Boston, That's where I'm from.

443
00:24:24,600 --> 00:24:29,480
Speaker 1: You know, I never would I never would have guessed yeah, yeah,

444
00:24:29,520 --> 00:24:31,160
Speaker 1: this southern accent.

445
00:24:30,840 --> 00:24:36,240
Speaker 2: And cowboy boots on two. But uh, you know, we

446
00:24:36,320 --> 00:24:40,200
Speaker 2: never looked at it as Dems are Republicans because how

447
00:24:40,240 --> 00:24:43,080
Speaker 2: I looked at it, and this philosophy is unqualified opinion.

448
00:24:43,560 --> 00:24:46,639
Speaker 2: I always looked at people are only a certain party

449
00:24:46,680 --> 00:24:51,720
Speaker 2: affiliation because of the zip code where they lived. Right,

450
00:24:52,359 --> 00:24:56,679
Speaker 2: nine out of ten times. There was bipartisanship on many

451
00:24:56,920 --> 00:25:00,240
Speaker 2: and most issues. So when I came to the SEE

452
00:25:00,240 --> 00:25:02,840
Speaker 2: three and a half years ago, and we had a

453
00:25:02,880 --> 00:25:05,119
Speaker 2: lot of success working with the legislation. I did twenty

454
00:25:05,200 --> 00:25:07,560
Speaker 2: years as a head of a local twenty five in Boston,

455
00:25:07,600 --> 00:25:10,200
Speaker 2: the one of the biggest locals, and I had a

456
00:25:10,200 --> 00:25:12,760
Speaker 2: great relationships with both Democrats and Republicans. We got a

457
00:25:12,800 --> 00:25:13,479
Speaker 2: lot of good work down.

458
00:25:13,520 --> 00:25:19,880
Speaker 4: We've got autism autism legislation past mandating private insurance companies

459
00:25:19,920 --> 00:25:23,680
Speaker 4: to provide services for families with autism.

460
00:25:23,920 --> 00:25:26,560
Speaker 2: We passed movie tax and centers into perpetuity. That's going

461
00:25:26,600 --> 00:25:29,439
Speaker 2: to support an industry, and that was all bipartisan did

462
00:25:29,440 --> 00:25:32,679
Speaker 2: a lot of great work, brought casinos to Boston. So

463
00:25:33,080 --> 00:25:35,600
Speaker 2: when I came here. I'm like, you know, I'll take

464
00:25:35,640 --> 00:25:38,200
Speaker 2: the JV and I don't mean that disrespectful, the junior

465
00:25:38,280 --> 00:25:41,920
Speaker 2: varsity template, and we're going to bring into the varsity game.

466
00:25:42,560 --> 00:25:46,320
Speaker 2: And we started reaching out across the aisle, talking new

467
00:25:46,760 --> 00:25:52,119
Speaker 2: people like our age demographic, jade, like Josh Hawley, jd Vance,

468
00:25:52,320 --> 00:25:56,520
Speaker 2: Roger Marshall, a lot of folks that we had a

469
00:25:56,520 --> 00:25:59,840
Speaker 2: lot in common with, may not agreed on everything. And

470
00:26:00,520 --> 00:26:03,080
Speaker 2: that's how last three and a half years, I think

471
00:26:03,200 --> 00:26:06,760
Speaker 2: the one thing that we've we've done well, which is

472
00:26:06,800 --> 00:26:10,679
Speaker 2: always room for employment, is reached across the island. Had conversations. So,

473
00:26:10,760 --> 00:26:13,400
Speaker 2: for instance, Josh Howley, when I first met with him,

474
00:26:14,119 --> 00:26:16,239
Speaker 2: we talked about a lot of issues, told him how

475
00:26:16,240 --> 00:26:19,160
Speaker 2: many members we had in the state, and we said,

476
00:26:19,200 --> 00:26:21,440
Speaker 2: you know, we don't support national right to work. We

477
00:26:21,480 --> 00:26:23,080
Speaker 2: don't support right to work, and he said why I

478
00:26:23,520 --> 00:26:25,440
Speaker 2: support right to work. I'm like, well, tell me why.

479
00:26:26,320 --> 00:26:28,960
Speaker 2: And we had this conversation. I told him why we didn't,

480
00:26:29,080 --> 00:26:31,360
Speaker 2: and we put out some you know, facts and figures.

481
00:26:31,880 --> 00:26:36,040
Speaker 2: Do you know he flipped his narrative right away and said,

482
00:26:36,480 --> 00:26:38,560
Speaker 2: you know, I no longer support right to work. This

483
00:26:38,640 --> 00:26:41,440
Speaker 2: is not getting my constituents. So think about if we

484
00:26:41,960 --> 00:26:44,920
Speaker 2: didn't have those conversations, and look, not all of them

485
00:26:44,920 --> 00:26:47,919
Speaker 2: in the success story that you know, look.

486
00:26:47,800 --> 00:26:50,520
Speaker 1: I look holly to me, you know, I look I

487
00:26:50,560 --> 00:26:53,240
Speaker 1: am not. I am more and more convinced that it

488
00:26:53,240 --> 00:26:56,280
Speaker 1: doesn't matter who you elected, It matters what your incentives are.

489
00:26:56,520 --> 00:26:57,240
Speaker 2: Right, right.

490
00:26:58,400 --> 00:27:01,400
Speaker 1: He lives in a state. You just it's a union state.

491
00:27:01,520 --> 00:27:05,000
Speaker 1: It's a conservative state culturally, right, but it's a union state,

492
00:27:05,240 --> 00:27:09,000
Speaker 1: always has been, and which is why I think that

493
00:27:09,080 --> 00:27:14,160
Speaker 1: whole you know, Missouri, the Democrats hung on longer there

494
00:27:14,200 --> 00:27:16,120
Speaker 1: than because of the fight over right to work.

495
00:27:16,359 --> 00:27:17,600
Speaker 2: Now you look at you look at do you look

496
00:27:17,600 --> 00:27:18,760
Speaker 2: at Ohio for instance?

497
00:27:18,840 --> 00:27:18,919
Speaker 3: Right?

498
00:27:19,320 --> 00:27:23,479
Speaker 2: That used to be completely blue, right right? Pretty much

499
00:27:23,520 --> 00:27:26,640
Speaker 2: a lot of industry Ohio was crushed with these bad

500
00:27:26,720 --> 00:27:29,000
Speaker 2: trade deals. I mean when you really think about it.

501
00:27:29,320 --> 00:27:31,119
Speaker 2: So what we've focused on is and then this is

502
00:27:31,160 --> 00:27:34,680
Speaker 2: the example of you know, my unqualified opinion in the

503
00:27:34,760 --> 00:27:37,520
Speaker 2: last three and a half years is you get Senator

504
00:27:37,560 --> 00:27:42,680
Speaker 2: Bernie Marino, Republican. I mean, he's embracing, he's embracing, uh,

505
00:27:43,119 --> 00:27:45,360
Speaker 2: you know, a lot of policies, pushing forward a lot

506
00:27:45,359 --> 00:27:48,240
Speaker 2: of our agenda because he represents those people that were

507
00:27:48,240 --> 00:27:51,400
Speaker 2: affected in Ohio and as a result, I mean he

508
00:27:51,480 --> 00:27:55,320
Speaker 2: first hand witnessed, you know, the demonization of industry in

509
00:27:55,359 --> 00:27:58,160
Speaker 2: Ohio as a result of these bad trade deals. He's

510
00:27:58,160 --> 00:28:00,479
Speaker 2: been another breath of fresh air. There were working with

511
00:28:01,600 --> 00:28:04,480
Speaker 2: Senator Eustead as well, who came in, you know, filling

512
00:28:04,960 --> 00:28:09,600
Speaker 2: Vice President Vance's seat, has also started to come to

513
00:28:09,640 --> 00:28:12,959
Speaker 2: that philosophy. Plus it's an election, yeah.

514
00:28:12,359 --> 00:28:15,239
Speaker 1: Right, any space and a guy like Shared Brown, who

515
00:28:15,280 --> 00:28:17,040
Speaker 1: I'm sure you do have a relationship with.

516
00:28:17,320 --> 00:28:20,480
Speaker 2: We do. And Sharon Brown wasn't happy that I went

517
00:28:20,480 --> 00:28:23,840
Speaker 2: and spoke at the r n c R and I said, look,

518
00:28:23,840 --> 00:28:25,680
Speaker 2: I would have gave that same speech had I been

519
00:28:25,680 --> 00:28:30,000
Speaker 2: invited to the DNC. And you know, it's funny in politics.

520
00:28:30,280 --> 00:28:32,200
Speaker 2: And you know, still.

521
00:28:31,480 --> 00:28:33,680
Speaker 1: Trying to understand why you weren't invited to the dancing.

522
00:28:34,200 --> 00:28:35,600
Speaker 1: I don't know you have a good explanation.

523
00:28:36,000 --> 00:28:37,760
Speaker 2: I no, I wish I did. I wish I did.

524
00:28:37,800 --> 00:28:40,800
Speaker 2: But you know, I listen, I tell people all the

525
00:28:40,840 --> 00:28:43,840
Speaker 2: time when I at my age, when I don't get

526
00:28:43,840 --> 00:28:47,320
Speaker 2: invited to weddings, I'm okay because I'll just send a check.

527
00:28:47,360 --> 00:28:48,040
Speaker 2: I don't need to go.

528
00:28:48,400 --> 00:28:51,520
Speaker 1: But it's so funny, you say that right. You know,

529
00:28:51,560 --> 00:28:53,080
Speaker 1: my wife and I joke about this all the time.

530
00:28:53,120 --> 00:28:55,360
Speaker 1: You hit a certain age. First, you're younger, you're like,

531
00:28:55,400 --> 00:28:57,440
Speaker 1: how come I didn't get invited to this? You're older,

532
00:28:57,440 --> 00:28:59,280
Speaker 1: You're like, God, why did I get invited to this?

533
00:28:59,360 --> 00:29:01,240
Speaker 2: So I tell people all the time, Look, don't invite me.

534
00:29:01,280 --> 00:29:04,360
Speaker 2: I'm gonna send a check anyways, it's a fundraiser. Just

535
00:29:04,400 --> 00:29:07,040
Speaker 2: don't invite me. Know that I'm thinking of you. I'll

536
00:29:07,080 --> 00:29:11,880
Speaker 2: send the donation, right, But no, I mean it's our

537
00:29:12,000 --> 00:29:15,440
Speaker 2: I mean, it's it's there. There's some good Republicans coming

538
00:29:15,480 --> 00:29:18,120
Speaker 2: along that way having dialogue with now there's something that

539
00:29:18,560 --> 00:29:22,400
Speaker 2: no matter what dialogue we have and or case we make,

540
00:29:22,600 --> 00:29:24,800
Speaker 2: they're just rigid. They're rigid and not going to move.

541
00:29:25,120 --> 00:29:29,320
Speaker 2: And that's okay too. But you know, I think the

542
00:29:29,400 --> 00:29:33,280
Speaker 2: last three and a half years, the conversations UH have

543
00:29:33,400 --> 00:29:38,080
Speaker 2: been have been very positive. UH in continuing even if

544
00:29:38,080 --> 00:29:42,160
Speaker 2: we agree to disagree on issues, my goal, and I

545
00:29:42,200 --> 00:29:45,360
Speaker 2: think I think I would love it to be everybody's goal,

546
00:29:45,440 --> 00:29:48,760
Speaker 2: especially now. I mean, this is such an awful, hostile,

547
00:29:49,200 --> 00:29:53,560
Speaker 2: gross time in the United States when you fail to

548
00:29:53,640 --> 00:29:56,600
Speaker 2: keep communicating regardlessl of talks are going good or bad.

549
00:29:57,920 --> 00:29:59,959
Speaker 2: You're failing your job, You're failing your constituents.

550
00:30:00,720 --> 00:30:04,920
Speaker 1: What could Kamala Harris have done differently to earn a

551
00:30:05,080 --> 00:30:06,320
Speaker 1: even co endorsement from you?

552
00:30:06,760 --> 00:30:11,600
Speaker 2: Not run for president? No, it was just never gonna Yeah,

553
00:30:11,600 --> 00:30:13,800
Speaker 2: it's just it wasn't gonna happen for us. I'm members

554
00:30:13,800 --> 00:30:16,600
Speaker 2: we we did some significant pulling. I'm not suggest I'm

555
00:30:16,600 --> 00:30:21,200
Speaker 2: not getting personal, but uh, let me let me back

556
00:30:21,280 --> 00:30:24,120
Speaker 2: up for a second. Joe Biden was was was great

557
00:30:24,160 --> 00:30:26,160
Speaker 2: to unions as a president. I'm never going to take

558
00:30:26,160 --> 00:30:27,040
Speaker 2: that away from him.

559
00:30:27,560 --> 00:30:29,840
Speaker 1: When he came, he was probably the most pro union

560
00:30:29,920 --> 00:30:33,440
Speaker 1: president he was you have ever had, We've had since FDR.

561
00:30:33,840 --> 00:30:38,400
Speaker 2: There's no doubt. There was no doubt. And again, uh,

562
00:30:38,760 --> 00:30:41,680
Speaker 2: you know, people always remind you of what they've done

563
00:30:41,800 --> 00:30:43,480
Speaker 2: for you in the past, not what they're going to

564
00:30:43,560 --> 00:30:46,400
Speaker 2: do for you in the future. And Joe Biden came

565
00:30:46,480 --> 00:30:48,400
Speaker 2: and met with us, and I got to tell you, like,

566
00:30:48,440 --> 00:30:51,000
Speaker 2: I felt bad. I really did, because you know, I

567
00:30:51,080 --> 00:30:54,280
Speaker 2: was brought up to be always respectful of people that

568
00:30:54,320 --> 00:30:56,720
Speaker 2: are older than your be just always respect the position,

569
00:30:56,920 --> 00:31:00,000
Speaker 2: respect the person. And you know, he lost his fastball

570
00:31:00,920 --> 00:31:04,120
Speaker 2: and it was like, you know, part of it for

571
00:31:04,240 --> 00:31:07,960
Speaker 2: me personally, was like, it just looks like someone's being

572
00:31:08,000 --> 00:31:10,800
Speaker 2: propped up and then not looking out for his best interest,

573
00:31:10,840 --> 00:31:13,200
Speaker 2: in looking out for their own personal interest. And then

574
00:31:13,240 --> 00:31:15,320
Speaker 2: when you know, he dropped out of the race and

575
00:31:16,000 --> 00:31:19,840
Speaker 2: Kamala came in, it kind of gave the sense of

576
00:31:21,400 --> 00:31:25,040
Speaker 2: it was like a birthright for her to be the candidate.

577
00:31:25,720 --> 00:31:28,280
Speaker 2: And you know, that was a big, big mistake I

578
00:31:28,320 --> 00:31:31,400
Speaker 2: think on the Democratic Party. This should have been a

579
00:31:31,400 --> 00:31:35,560
Speaker 2: continguency plan two years prior to the election, and that

580
00:31:35,680 --> 00:31:38,000
Speaker 2: wasn't there. And you know, you hear all these stories

581
00:31:38,040 --> 00:31:40,840
Speaker 2: living in DC. You know that he was going to

582
00:31:40,880 --> 00:31:44,120
Speaker 2: be a transitional president. There was a meeting and you know,

583
00:31:44,200 --> 00:31:46,280
Speaker 2: he got pushed back from a lot of staff people

584
00:31:46,280 --> 00:31:48,760
Speaker 2: that whose jobs could have been in jeopardy, all this

585
00:31:48,800 --> 00:31:51,400
Speaker 2: other stuff. I mean, I think, you know, hey, she

586
00:31:51,560 --> 00:31:56,320
Speaker 2: ran for the president. She lost. You can't recreate history.

587
00:31:56,680 --> 00:31:58,840
Speaker 2: But I don't think she was the best candidate. You know,

588
00:31:59,080 --> 00:32:01,360
Speaker 2: if I really had to think about, there were a

589
00:32:01,440 --> 00:32:03,400
Speaker 2: lot more candidates out there and it probably would have

590
00:32:03,400 --> 00:32:05,640
Speaker 2: gave Trump a run for his money.

591
00:32:05,840 --> 00:32:08,960
Speaker 1: Would you describe your membership as pretty fifty to fifty.

592
00:32:09,000 --> 00:32:11,920
Speaker 2: No, sixty, It was sixty five thirty five when we

593
00:32:11,920 --> 00:32:14,320
Speaker 2: did a polling, we did significant polling. We actually rump

594
00:32:14,600 --> 00:32:19,239
Speaker 2: sixty five for Trump Republican. Yes, so we did so,

595
00:32:19,560 --> 00:32:22,120
Speaker 2: I'll tell you it was interesting. We've never done this

596
00:32:22,160 --> 00:32:24,800
Speaker 2: before as an organization. But you know, we're out in

597
00:32:24,800 --> 00:32:26,680
Speaker 2: the field every single day and we're talking to our

598
00:32:26,680 --> 00:32:31,080
Speaker 2: members social media. There's so much communication and some of

599
00:32:31,120 --> 00:32:35,719
Speaker 2: it's not credible, but you could just see members gravitating

600
00:32:35,720 --> 00:32:37,560
Speaker 2: towards the Republicans. And I don't think it was just

601
00:32:37,600 --> 00:32:39,800
Speaker 2: because it was Trump. I think it's just, you know,

602
00:32:39,800 --> 00:32:43,800
Speaker 2: the Democrats weren't controlled the last sixteen out of twenty years,

603
00:32:44,200 --> 00:32:47,040
Speaker 2: and what really have we got done? What really Democrats

604
00:32:47,040 --> 00:32:51,120
Speaker 2: do for us? Under Obama we had a Democratic House, Senate,

605
00:32:52,200 --> 00:32:54,800
Speaker 2: and president. And our biggest issue back then was the

606
00:32:54,800 --> 00:32:58,240
Speaker 2: Employee Free Choice Act should have been a layout right,

607
00:32:58,240 --> 00:33:01,520
Speaker 2: which was basically the pro Act right that didn't happen.

608
00:33:02,040 --> 00:33:04,400
Speaker 2: And then under Biden this was.

609
00:33:04,360 --> 00:33:09,160
Speaker 1: The basically the ability to ask for collective bargaining right.

610
00:33:09,000 --> 00:33:12,239
Speaker 2: The ability of an employer to once there was a

611
00:33:12,240 --> 00:33:16,560
Speaker 2: majority status, to recognize and sit down and bargain and

612
00:33:16,720 --> 00:33:19,120
Speaker 2: you know, come to a collective bargain agreement. And it

613
00:33:19,160 --> 00:33:21,960
Speaker 2: should have been a layup. But it again, that's part

614
00:33:21,960 --> 00:33:24,360
Speaker 2: of the reason why our members started defecting. They was

615
00:33:24,400 --> 00:33:27,560
Speaker 2: seeing time and time again that you know, the working

616
00:33:27,600 --> 00:33:30,400
Speaker 2: people's agendas weren't being put forward. I mean, you think

617
00:33:30,440 --> 00:33:35,400
Speaker 2: about bankruptcy. Bankruptcy laws in this country are antiquated, and

618
00:33:35,440 --> 00:33:38,200
Speaker 2: we deal with it all the time when companies go bankrupt.

619
00:33:38,280 --> 00:33:40,880
Speaker 1: This is an Elizabeth Warren obsession, right to the bankruptcy

620
00:33:40,960 --> 00:33:41,680
Speaker 1: legislation right.

621
00:33:41,920 --> 00:33:44,680
Speaker 2: When companies go bankrupt, and we've seen it, you know,

622
00:33:44,760 --> 00:33:49,440
Speaker 2: everybody gets this, right. We had a last line of creditors.

623
00:33:50,120 --> 00:33:54,560
Speaker 2: Uh in the line they're not even treated as creditors. No,

624
00:33:54,600 --> 00:33:59,080
Speaker 2: we're treated as qumodity commodity right, like we'll throw them

625
00:33:59,280 --> 00:34:01,640
Speaker 2: three cents on the dollar and tell them that's not

626
00:34:01,720 --> 00:34:04,000
Speaker 2: we can do. So, you know, the whole system has

627
00:34:04,000 --> 00:34:07,000
Speaker 2: failed us. And even when there were times like under

628
00:34:07,360 --> 00:34:12,439
Speaker 2: strong democratic leadership, you know, our issues weren't taken in consideration. Now,

629
00:34:13,840 --> 00:34:19,120
Speaker 2: one thing that Biden did unbelievable for us on is

630
00:34:19,480 --> 00:34:22,280
Speaker 2: you know, funding these pension funds so that they didn't collapse.

631
00:34:22,719 --> 00:34:25,279
Speaker 2: And I say that all the time, and that got

632
00:34:25,280 --> 00:34:27,720
Speaker 2: thrown in my face when I spoke at the RNC

633
00:34:27,960 --> 00:34:30,960
Speaker 2: right after it. You know a lot of Democrats, like

634
00:34:31,000 --> 00:34:33,360
Speaker 2: Sherrid Brown was not happy that I spoke there. He

635
00:34:33,400 --> 00:34:35,880
Speaker 2: came to my office and he said, you know, I

636
00:34:36,440 --> 00:34:40,160
Speaker 2: help with that legislation. Butch lewis no doubt you helped

637
00:34:40,239 --> 00:34:43,480
Speaker 2: us with that legislation. We are grateful we got pensions.

638
00:34:43,480 --> 00:34:46,760
Speaker 2: They're going to be solving till twenty fifty one. People

639
00:34:46,760 --> 00:34:48,359
Speaker 2: aren't going to have to worry about. That was the

640
00:34:48,440 --> 00:34:53,239
Speaker 2: right thing to do. However, who broke them? Who broke

641
00:34:53,280 --> 00:34:55,719
Speaker 2: these pensions? What do you mean? And I had the

642
00:34:55,719 --> 00:34:59,239
Speaker 2: same conversation with a lot of other Democratic senators. I said,

643
00:34:59,239 --> 00:35:03,640
Speaker 2: in nineteen eighty, Ted Kennery from Massachusetts pass legislation deregulation

644
00:35:03,719 --> 00:35:06,520
Speaker 2: the trucking industry. The Teams to union lost four hundred

645
00:35:06,520 --> 00:35:10,920
Speaker 2: thousand trucking jobs, and that deregulation started filtering into other industries.

646
00:35:11,120 --> 00:35:13,880
Speaker 2: If you lose four hundred thousand jobs, that's four hundred

647
00:35:13,920 --> 00:35:17,960
Speaker 2: thousand contributions times forty hours a week, times you know,

648
00:35:18,040 --> 00:35:21,719
Speaker 2: fifty two weeks a year. That is a significant drain

649
00:35:21,800 --> 00:35:25,239
Speaker 2: on these funds. You know, each year it goes on.

650
00:35:25,520 --> 00:35:28,080
Speaker 2: And then take into consideration a lot of these companies,

651
00:35:28,640 --> 00:35:32,160
Speaker 2: good companies were forced into bankruptcy where none of these

652
00:35:32,200 --> 00:35:35,360
Speaker 2: monies were captured because the bankruptcy laws did pax. And

653
00:35:35,400 --> 00:35:39,080
Speaker 2: I said, look, I'm very grateful you fixed the problem

654
00:35:39,120 --> 00:35:42,640
Speaker 2: that you helped create. And I use this analogy. I'm

655
00:35:42,640 --> 00:35:46,719
Speaker 2: playing street arc in my neighborhood nineteen eighty' you know,

656
00:35:46,960 --> 00:35:52,520
Speaker 2: eight years old, right, I break my mother's window. Forty

657
00:35:52,600 --> 00:35:54,880
Speaker 2: years later, I say, I'm going to fix that window.

658
00:35:55,200 --> 00:35:58,480
Speaker 2: Should I look for accolades from my mother for fixing

659
00:35:58,520 --> 00:36:01,520
Speaker 2: a problem that I helped create? And Joe Biden was

660
00:36:01,520 --> 00:36:03,839
Speaker 2: the center. He signed off on the legislation of deregulation,

661
00:36:04,160 --> 00:36:06,000
Speaker 2: and that was when Reagan was a president, who by

662
00:36:06,000 --> 00:36:09,319
Speaker 2: the way, we endorsed Reagan as well. So it's you know.

663
00:36:09,600 --> 00:36:10,840
Speaker 1: Everybody lets you down on that one.

664
00:36:11,160 --> 00:36:13,840
Speaker 2: Yeah, yeah, But my point is, you know, once you

665
00:36:13,880 --> 00:36:16,200
Speaker 2: took a position like we did, because the polling we did,

666
00:36:16,280 --> 00:36:18,879
Speaker 2: and we did three intense poems, we did a straw

667
00:36:18,920 --> 00:36:22,520
Speaker 2: pole in the Union Halls where we could have tipped

668
00:36:22,560 --> 00:36:25,720
Speaker 2: it should have been tipped like eighty twenty to Biden,

669
00:36:26,280 --> 00:36:29,120
Speaker 2: and it was like, you know, thirty five percent Biden,

670
00:36:29,520 --> 00:36:34,600
Speaker 2: thirty percent Trump, and then independent factored in as well.

671
00:36:34,719 --> 00:36:36,719
Speaker 2: We're like, all right, this isn't a good gauge. So

672
00:36:36,760 --> 00:36:39,560
Speaker 2: then we do a publication every month, every quarter, I

673
00:36:39,600 --> 00:36:42,360
Speaker 2: believe every month it's one. It goes to one point

674
00:36:42,400 --> 00:36:48,000
Speaker 2: six million people. And we got record participation with a

675
00:36:48,120 --> 00:36:50,920
Speaker 2: with a code, a QR code, and Harris was in

676
00:36:50,960 --> 00:36:52,840
Speaker 2: the race with Waltz at this point in time, and

677
00:36:52,880 --> 00:36:57,839
Speaker 2: it went sixty five thirty five Republican, and like, all right,

678
00:36:57,920 --> 00:37:00,560
Speaker 2: let's do one more poll. So we utilize the impolster

679
00:37:01,320 --> 00:37:05,239
Speaker 2: that the Harris Waltz campaign utilized and it was the

680
00:37:05,280 --> 00:37:07,840
Speaker 2: same result as we got from the QR code of

681
00:37:07,840 --> 00:37:10,319
Speaker 2: our members. So we were like, all right, we've got

682
00:37:10,360 --> 00:37:13,280
Speaker 2: to represent sixty five percent of our members. We also

683
00:37:13,280 --> 00:37:15,799
Speaker 2: have to represent the thirty five percent. You know, this

684
00:37:15,920 --> 00:37:19,000
Speaker 2: is too close. We're gonna we're going to take a pass.

685
00:37:19,000 --> 00:37:23,120
Speaker 2: We're going to not make an endorsement. Local unions, joint consuls,

686
00:37:23,400 --> 00:37:25,719
Speaker 2: they're autonomous. You do what you want to do in

687
00:37:25,760 --> 00:37:26,240
Speaker 2: this one.

688
00:37:26,320 --> 00:37:28,440
Speaker 1: And they kind of did, if I'm not mistakes, they did.

689
00:37:28,400 --> 00:37:30,839
Speaker 2: But you know, the majority of them, I mean, California

690
00:37:30,960 --> 00:37:35,440
Speaker 2: was probably the most outgoing for Harris and Wallas, and

691
00:37:35,440 --> 00:37:39,920
Speaker 2: there were some other uh maybe maybe Illinois, but most people,

692
00:37:40,080 --> 00:37:42,120
Speaker 2: you know, chose to take a step back as well,

693
00:37:42,120 --> 00:37:44,600
Speaker 2: because again, now members of their constituents.

694
00:37:44,960 --> 00:37:47,560
Speaker 1: What's your relationship these days with the rest of the

695
00:37:47,640 --> 00:37:51,640
Speaker 1: labor movement, right, it's it's sometimes with the collective of

696
00:37:51,640 --> 00:37:54,080
Speaker 1: the afl CIO and all of that. And they've been

697
00:37:54,440 --> 00:37:56,880
Speaker 1: they've been back and forth overtime, and you know, to me,

698
00:37:57,960 --> 00:38:01,000
Speaker 1: there's the Teamsters, then there's the afl CIO. Is that

699
00:38:01,000 --> 00:38:03,680
Speaker 1: that's still that's still the pecking order in your in

700
00:38:03,719 --> 00:38:04,080
Speaker 1: your mind.

701
00:38:04,080 --> 00:38:06,239
Speaker 2: You're not a member of yeah c IO, right, yeah,

702
00:38:06,239 --> 00:38:07,799
Speaker 2: well not a member of the fl CIO. I mean,

703
00:38:07,840 --> 00:38:10,640
Speaker 2: they do good work, there's no doubt about it. We

704
00:38:10,800 --> 00:38:15,239
Speaker 2: definitely represent different interests with our members versus you know there.

705
00:38:15,440 --> 00:38:17,640
Speaker 1: Why aren't you a part of a fl CIA.

706
00:38:17,920 --> 00:38:21,040
Speaker 2: You know what happened when probably about I think twenty

707
00:38:21,120 --> 00:38:23,640
Speaker 2: years ago when you know, there was there was a

708
00:38:23,719 --> 00:38:26,480
Speaker 2: riff between I think President trumpker at that point in

709
00:38:26,480 --> 00:38:29,080
Speaker 2: time and some of the other labor unions I think

710
00:38:29,120 --> 00:38:33,160
Speaker 2: the Laborers, the Compenters, the Teamsters, uh, and there are

711
00:38:33,160 --> 00:38:35,440
Speaker 2: a couple other affiliates. I think s c IU formed

712
00:38:35,480 --> 00:38:37,040
Speaker 2: their own change to Win coalition.

713
00:38:37,120 --> 00:38:39,879
Speaker 1: Well I remember that that really blew things up and with.

714
00:38:39,840 --> 00:38:44,200
Speaker 2: Drew withdrew UH the international unions, but you know, a

715
00:38:44,200 --> 00:38:45,799
Speaker 2: lot of the affiliates and that was one of them.

716
00:38:45,840 --> 00:38:48,920
Speaker 2: In Boston, we stayed. We stayed with the fl CIO

717
00:38:49,040 --> 00:38:52,360
Speaker 2: locally for some time and that's still that's still the practice.

718
00:38:52,400 --> 00:38:54,680
Speaker 2: That's the encouragement from us. We just you know, we

719
00:38:54,719 --> 00:38:57,120
Speaker 2: do our own thing. We've got our own staff, we've

720
00:38:57,120 --> 00:38:59,520
Speaker 2: got our owner ability to lobby, We've got our own ability.

721
00:38:59,600 --> 00:39:01,800
Speaker 2: I mean there are times we work on projects together.

722
00:39:02,680 --> 00:39:05,480
Speaker 2: I think, to your question, I'm gonna answer it honestly.

723
00:39:06,280 --> 00:39:09,439
Speaker 2: I think, Uh, you know this this some ill will

724
00:39:10,160 --> 00:39:15,680
Speaker 2: from other unions on us non endorsing UH Vice President Harris.

725
00:39:16,600 --> 00:39:18,320
Speaker 2: But you know, at the end of the day, Chuck,

726
00:39:19,239 --> 00:39:22,960
Speaker 2: I will help any union. I will help any affiliate,

727
00:39:23,640 --> 00:39:25,600
Speaker 2: even if we do have a difference of opinions. But

728
00:39:26,080 --> 00:39:28,840
Speaker 2: you know, there is I've heard some chatter now again

729
00:39:29,360 --> 00:39:32,080
Speaker 2: when you see them, everybody is your best friend, right,

730
00:39:32,520 --> 00:39:34,760
Speaker 2: but you know, you go online and you see everything.

731
00:39:34,880 --> 00:39:37,560
Speaker 2: I don't take it personally, I get it. My whole

732
00:39:37,680 --> 00:39:39,840
Speaker 2: focus and goal is I've got to serve the people

733
00:39:39,840 --> 00:39:42,000
Speaker 2: that I'm elected to serve, and I got to make

734
00:39:42,040 --> 00:39:45,360
Speaker 2: decisions and recommend decisions. H and the best interests in

735
00:39:45,560 --> 00:39:47,319
Speaker 2: And you know, I believed at the time, and I

736
00:39:47,320 --> 00:39:51,200
Speaker 2: still believe that we made the best decision possible. And look,

737
00:39:51,360 --> 00:39:53,400
Speaker 2: we're in a good spot. I mean, some of these

738
00:39:53,480 --> 00:39:57,960
Speaker 2: unions that criticized me, uh with help broker meetings with

739
00:39:57,960 --> 00:40:01,560
Speaker 2: with with the White House, you know, to you know,

740
00:40:01,719 --> 00:40:05,719
Speaker 2: stop any kind of attack on a certain industry, or

741
00:40:05,960 --> 00:40:10,600
Speaker 2: to help facilitate a relationship. So look, I'm sure there's

742
00:40:10,680 --> 00:40:14,000
Speaker 2: some hurt feelings, but even if we did endorse in

743
00:40:14,000 --> 00:40:16,360
Speaker 2: the selection, it wouldn't have moved the needle. You know,

744
00:40:16,400 --> 00:40:18,520
Speaker 2: we did what was the best interesting. Look, we pulled

745
00:40:18,520 --> 00:40:21,200
Speaker 2: our members, and you know, I think we made the

746
00:40:21,280 --> 00:40:21,840
Speaker 2: right decision.

747
00:40:22,360 --> 00:40:27,879
Speaker 1: So if Andy Basheer, Wes Moore, I'll throw I'll throw

748
00:40:27,920 --> 00:40:28,720
Speaker 1: a Gretchen Whitmer.

749
00:40:29,480 --> 00:40:32,360
Speaker 2: We forget, don't forget Josh Shapiro.

750
00:40:32,320 --> 00:40:34,919
Speaker 1: Josh Shapiro, the four of them come to you and say,

751
00:40:35,600 --> 00:40:37,560
Speaker 1: what do I do to make sure I'm not at

752
00:40:37,560 --> 00:40:40,160
Speaker 1: the thirty five of a sixty five thirty five split

753
00:40:40,200 --> 00:40:41,160
Speaker 1: in twenty twenty eight.

754
00:40:41,400 --> 00:40:43,920
Speaker 2: I want to tell them, what do you tell them?

755
00:40:44,320 --> 00:40:48,720
Speaker 2: Go out talk to your constituents, our members. Remember to member,

756
00:40:48,760 --> 00:40:53,440
Speaker 2: have face to face conversations. Ask their opinions, don't dictate

757
00:40:54,360 --> 00:40:55,359
Speaker 2: what they should.

758
00:40:55,080 --> 00:40:56,520
Speaker 3: Be doing for you.

759
00:40:56,520 --> 00:40:58,960
Speaker 2: You work for them. You need to win the trust

760
00:40:59,000 --> 00:40:59,520
Speaker 2: back over.

761
00:41:00,000 --> 00:41:13,360
Speaker 3: I was part of the problem.

762
00:41:13,640 --> 00:41:15,720
Speaker 1: Give me an example of something. I mean, I've heard

763
00:41:15,880 --> 00:41:18,600
Speaker 1: a similar look. You know, there's sort of this stereotype

764
00:41:18,640 --> 00:41:21,440
Speaker 1: of that I joke these days of Democrats and Republicans.

765
00:41:21,440 --> 00:41:23,359
Speaker 1: Republicans go out of their way to agree with the voter.

766
00:41:23,760 --> 00:41:25,680
Speaker 1: Democrats go out of their way to convince the voter

767
00:41:25,760 --> 00:41:29,400
Speaker 1: that they're right, and it's it's sort of a you

768
00:41:29,440 --> 00:41:31,880
Speaker 1: know which, which is actually a much harder thing to do.

769
00:41:32,120 --> 00:41:33,640
Speaker 2: I'm going to get your true testimonial.

770
00:41:33,960 --> 00:41:34,160
Speaker 1: Yeah.

771
00:41:34,239 --> 00:41:38,320
Speaker 2: I was speaking at an International Union's convention, uh probably

772
00:41:38,320 --> 00:41:42,400
Speaker 2: about a month ago in Hawaii, and I was explaining

773
00:41:42,600 --> 00:41:44,440
Speaker 2: just what I explained to you, the polling and everything

774
00:41:44,440 --> 00:41:49,360
Speaker 2: else and after the whole and it was like in

775
00:41:49,400 --> 00:41:54,319
Speaker 2: front of about five thousand people walking out, and a

776
00:41:54,400 --> 00:41:56,640
Speaker 2: lady approaches me, and I can see it coming and

777
00:41:56,719 --> 00:42:00,600
Speaker 2: you just see the body language. And she walked right

778
00:42:00,680 --> 00:42:04,480
Speaker 2: up to me and pointed her finger and said, what

779
00:42:04,520 --> 00:42:07,719
Speaker 2: are you doing to educate those sixty five percent of

780
00:42:07,719 --> 00:42:10,919
Speaker 2: the numbers? I said, I'm not doing anything to educate them.

781
00:42:11,360 --> 00:42:16,280
Speaker 2: I said, what are the Democrats doing to find out

782
00:42:16,719 --> 00:42:21,399
Speaker 2: why sixty sixty five percent of our members didn't support them.

783
00:42:21,719 --> 00:42:23,960
Speaker 2: That's not up to me, that's up to the members.

784
00:42:23,960 --> 00:42:27,680
Speaker 2: I said, that's the problem here. It's my job to

785
00:42:27,840 --> 00:42:31,160
Speaker 2: educate someone who made a choice based upon you know,

786
00:42:32,200 --> 00:42:36,719
Speaker 2: personal and or maybe validated concerns with the party. What

787
00:42:36,760 --> 00:42:39,200
Speaker 2: do you want me to do? Is educating me telling

788
00:42:39,280 --> 00:42:41,160
Speaker 2: what to do? Because that's not what we're going to do.

789
00:42:41,960 --> 00:42:44,480
Speaker 1: You know, it's interesting, It's a dilemma. I know some

790
00:42:44,719 --> 00:42:49,799
Speaker 1: unions have a similar split, particularly the Trades, where a

791
00:42:49,880 --> 00:42:53,160
Speaker 1: majority of their members are Trump, but the leadership all

792
00:42:53,200 --> 00:42:58,279
Speaker 1: went to the Democrats, right, and they do try to

793
00:42:58,400 --> 00:43:00,719
Speaker 1: quote educate their members. Look, we know you may not

794
00:43:01,000 --> 00:43:05,120
Speaker 1: like these issues, but do you know Speaker Pelosi is

795
00:43:05,120 --> 00:43:07,759
Speaker 1: what got this done and you may not like her,

796
00:43:07,800 --> 00:43:12,560
Speaker 1: but here's why we're siding with her. Is that on

797
00:43:12,640 --> 00:43:14,200
Speaker 1: a labor leader to explain or not?

798
00:43:15,160 --> 00:43:17,799
Speaker 2: Oh, you have to. I think you have to in

799
00:43:17,800 --> 00:43:21,480
Speaker 2: that scenario. Like I've been critical of both Republican and Democrats,

800
00:43:22,040 --> 00:43:24,759
Speaker 2: However I always acknowledge what they've done for us or

801
00:43:24,800 --> 00:43:28,799
Speaker 2: haven't done for us. So you know, Chuck Schumer, you

802
00:43:28,840 --> 00:43:31,719
Speaker 2: know reminds me every time he sees me that you know,

803
00:43:31,800 --> 00:43:36,000
Speaker 2: he fixed our pensions. Well he didn't do it alone, right,

804
00:43:37,360 --> 00:43:40,000
Speaker 2: And I'll tell people, Look, Joe Biden was the most

805
00:43:40,000 --> 00:43:43,759
Speaker 2: pro union president. He actually signed the legislation I fixed

806
00:43:43,760 --> 00:43:46,560
Speaker 2: out pensions, and then I'll give the story on why

807
00:43:46,600 --> 00:43:50,040
Speaker 2: these pensions were broke. Like I said to you, So, yeah,

808
00:43:50,120 --> 00:43:51,880
Speaker 2: it is up to us to give the tale of

809
00:43:51,920 --> 00:43:54,560
Speaker 2: the table on both sides as far as yeah, they

810
00:43:54,600 --> 00:43:57,880
Speaker 2: did this over here, but I could also point to

811
00:43:58,160 --> 00:44:00,520
Speaker 2: three or four different things that they haven't done either,

812
00:44:00,880 --> 00:44:04,080
Speaker 2: Like I've had situations where saying, hey, you know, Josh

813
00:44:04,120 --> 00:44:07,040
Speaker 2: Hally isn't for working people, or Roger Marshall's for working people.

814
00:44:07,040 --> 00:44:10,160
Speaker 2: Oh really, I said, they signed on to support letters

815
00:44:10,160 --> 00:44:12,560
Speaker 2: for our members, though we're potentially going to strike at ups.

816
00:44:12,880 --> 00:44:17,680
Speaker 2: They signed on to help our rail workers who didn't

817
00:44:17,680 --> 00:44:21,680
Speaker 2: have a contract for four years. Yeah, although so and

818
00:44:21,719 --> 00:44:25,160
Speaker 2: so a Democrat might have, you know, said, taken credit

819
00:44:25,239 --> 00:44:28,000
Speaker 2: for something, they didn't sign onto this legislation, as signed

820
00:44:28,000 --> 00:44:30,439
Speaker 2: on to the support of this legislation. They didn't sign

821
00:44:30,440 --> 00:44:33,440
Speaker 2: on to support Amazon workers. So we can always point

822
00:44:33,480 --> 00:44:35,400
Speaker 2: and I think to your point, Yeah, we're going to

823
00:44:35,400 --> 00:44:37,440
Speaker 2: point out what people have done for us, but we're

824
00:44:37,480 --> 00:44:39,520
Speaker 2: also going to point out what they haven't done for us.

825
00:44:42,080 --> 00:44:44,840
Speaker 1: We've spent a lot of time noting where Democrats have

826
00:44:44,960 --> 00:44:48,319
Speaker 1: let you down. Why do you trust the these? Uh,

827
00:44:49,560 --> 00:44:52,600
Speaker 1: the the your new allies, some of your new allies.

828
00:44:52,920 --> 00:44:55,200
Speaker 2: Listen, I'm a Democrat, always going to be a Democrat.

829
00:44:55,239 --> 00:44:59,239
Speaker 2: I don't trust anybody. Okay, I want to see when

830
00:44:59,280 --> 00:45:02,359
Speaker 2: people say something looking And I was brought up and

831
00:45:02,960 --> 00:45:04,759
Speaker 2: you know, I was brought up by a very very

832
00:45:04,760 --> 00:45:09,200
Speaker 2: strong Irish woman and my very strong Irish father who's

833
00:45:09,200 --> 00:45:10,960
Speaker 2: no longer with us. But the one thing they always said,

834
00:45:10,960 --> 00:45:13,239
Speaker 2: with all you have left in your life is your

835
00:45:13,280 --> 00:45:17,520
Speaker 2: reputation and your work. And the Republicans have a great

836
00:45:17,520 --> 00:45:22,719
Speaker 2: opportunity right now because the Democratic parties fraction. They're portraying

837
00:45:22,760 --> 00:45:26,160
Speaker 2: themselves as wanting to be the party of working people,

838
00:45:26,600 --> 00:45:30,360
Speaker 2: and the Democrats have to win the trust and support

839
00:45:30,400 --> 00:45:35,959
Speaker 2: back of working people. And I'm leveraging both of those narratives. Hey,

840
00:45:36,239 --> 00:45:38,279
Speaker 2: you said when you were running, you want to you

841
00:45:38,280 --> 00:45:40,359
Speaker 2: want to you want to be the party working people. Well,

842
00:45:40,360 --> 00:45:42,880
Speaker 2: why aren't you jumping on board support? And you know,

843
00:45:42,920 --> 00:45:47,359
Speaker 2: the Faster Labor Contracts Act as Republicans. Because we've got

844
00:45:47,480 --> 00:45:51,799
Speaker 2: bipartisans support and growing in that, that's an opportunity for

845
00:45:51,840 --> 00:45:55,400
Speaker 2: Republicans to actually say well or to demonstrate, hey, we

846
00:45:55,440 --> 00:45:58,719
Speaker 2: do support we do support working people. And also if

847
00:45:58,760 --> 00:46:01,120
Speaker 2: they do that, the Democrats going to come home and

848
00:46:01,120 --> 00:46:05,279
Speaker 2: criticize that. No, they can't. But but if the Republicans

849
00:46:05,320 --> 00:46:07,840
Speaker 2: say I'm not supporting it or we don't get Republican support,

850
00:46:08,160 --> 00:46:11,560
Speaker 2: they're just allowing the Democrats to weaponize that issue. And

851
00:46:11,640 --> 00:46:15,319
Speaker 2: maybe that's the Maybe that's the UH strategy. I don't know.

852
00:46:15,680 --> 00:46:17,320
Speaker 1: Let me get you out of here. In two things

853
00:46:17,360 --> 00:46:22,560
Speaker 1: one twenty twenty six is is this a low I

854
00:46:22,840 --> 00:46:27,480
Speaker 1: saw for instance, in Michigan, various teamsters, you know, the

855
00:46:27,960 --> 00:46:30,440
Speaker 1: state went one way, a couple of locals went another.

856
00:46:31,120 --> 00:46:34,719
Speaker 1: Is that mostly how teamsters endorsements work into in a

857
00:46:34,800 --> 00:46:38,279
Speaker 1: midterm year or will the National Will year office sort

858
00:46:38,320 --> 00:46:41,359
Speaker 1: of way in uncertain Senate races, certain House races.

859
00:46:41,400 --> 00:46:42,839
Speaker 2: Yeah, we're going to We're going to weigh in on

860
00:46:42,960 --> 00:46:46,960
Speaker 2: certain Senate races, especially the senators and House members that

861
00:46:47,040 --> 00:46:49,240
Speaker 2: support us, whether you have a D n R or nine.

862
00:46:49,560 --> 00:46:51,160
Speaker 2: You know, the beauty of the teams to's union. We

863
00:46:51,160 --> 00:46:55,000
Speaker 2: have three hundred and nineteen local unions in thirty I

864
00:46:55,000 --> 00:46:59,200
Speaker 2: believe thirty something, joint councils, regional councils. You know, everybody's

865
00:47:00,200 --> 00:47:03,560
Speaker 2: they like their pride of autonomy, and we give them that. However,

866
00:47:03,640 --> 00:47:07,319
Speaker 2: if we are working on legislation like fastera Labor Contracts

867
00:47:07,360 --> 00:47:11,520
Speaker 2: Act or warehouse protection, and we're getting support from from

868
00:47:11,680 --> 00:47:13,440
Speaker 2: people that are currently in office that might have a

869
00:47:13,520 --> 00:47:15,680
Speaker 2: dn R, we're gonna we're going to weigh in and say, look,

870
00:47:15,960 --> 00:47:19,600
Speaker 2: this is what these people have done for us. But

871
00:47:19,800 --> 00:47:21,520
Speaker 2: at the end of the day, it's usually left up

872
00:47:21,520 --> 00:47:23,840
Speaker 2: to the local unions and the joint consuls.

873
00:47:26,520 --> 00:47:31,080
Speaker 1: I'm gonna paint a scenario for you. Uh, the athletes

874
00:47:31,120 --> 00:47:34,600
Speaker 1: of the Big ten decide they're going to organize. I

875
00:47:34,640 --> 00:47:37,759
Speaker 1: think it's coming, frankly, collective bargaining in college sports. There's

876
00:47:37,800 --> 00:47:41,839
Speaker 1: a lot of money at state. There's frankly no protections

877
00:47:41,840 --> 00:47:49,680
Speaker 1: for these athletes right now in various ways. Is do

878
00:47:48,480 --> 00:47:54,840
Speaker 1: you do the teamsters want? You know, would would athletes

879
00:47:54,880 --> 00:47:57,959
Speaker 1: who got a collective you know, we're able to sort

880
00:47:58,000 --> 00:48:02,960
Speaker 1: of get a collective be recognized as a union. Would

881
00:48:03,000 --> 00:48:05,359
Speaker 1: you want them as Teamsters members? Or is that too far.

882
00:48:05,800 --> 00:48:11,400
Speaker 1: Is that too far? There's no there's no union out there. Okay,

883
00:48:10,960 --> 00:48:14,520
Speaker 1: well explain why, explain why teamsters, we'll be able to

884
00:48:14,560 --> 00:48:16,360
Speaker 1: help the big ten football players.

885
00:48:16,400 --> 00:48:19,719
Speaker 2: I play college football one semester. Right. It's a full

886
00:48:19,719 --> 00:48:23,879
Speaker 2: time job, a lot of demands. Uh, and there's no guarantees.

887
00:48:24,600 --> 00:48:24,799
Speaker 3: Right.

888
00:48:25,160 --> 00:48:27,080
Speaker 2: Do you want to go put sports aside? Do you

889
00:48:27,120 --> 00:48:30,080
Speaker 2: want to go work for an employer whether there's a

890
00:48:30,120 --> 00:48:34,080
Speaker 2: lot of demand and no return. No, you don't, so

891
00:48:34,360 --> 00:48:37,160
Speaker 2: that that's right in our whalehouse. As far as repers,

892
00:48:37,200 --> 00:48:39,120
Speaker 2: I will represent anybody you know we were accused of.

893
00:48:39,560 --> 00:48:42,080
Speaker 2: If a fire hydrant wanted to negotiate a contract, the

894
00:48:42,080 --> 00:48:45,279
Speaker 2: teams would represent them. Right, No, we would love to

895
00:48:45,360 --> 00:48:47,759
Speaker 2: because you don't think about it. You are don't you

896
00:48:47,800 --> 00:48:50,080
Speaker 2: believe that's coming? I think it's coming. Look a good

897
00:48:50,080 --> 00:48:51,839
Speaker 2: friend of mine, I know you're a you're a huge

898
00:48:51,920 --> 00:48:55,480
Speaker 2: University of Miami. Gino Torrett is a very good friend

899
00:48:55,520 --> 00:48:58,680
Speaker 2: of mine. Oh you know he and our Yeah, way

900
00:48:58,719 --> 00:49:00,480
Speaker 2: back when I mean he was saying, you know, this

901
00:49:00,560 --> 00:49:03,680
Speaker 2: is a full time job, like it was forty plus

902
00:49:03,719 --> 00:49:06,520
Speaker 2: hours per week, and the demands that are put on you,

903
00:49:06,560 --> 00:49:08,480
Speaker 2: like you don't have you don't have the ability to

904
00:49:08,520 --> 00:49:12,399
Speaker 2: say no to these college coaches or these even the administration.

905
00:49:12,640 --> 00:49:15,359
Speaker 2: So it's like, you know, there's no rights of these

906
00:49:15,360 --> 00:49:17,920
Speaker 2: call they owned you, and no one should be owned.

907
00:49:17,960 --> 00:49:20,560
Speaker 2: No one should be mandated what to say and what

908
00:49:20,640 --> 00:49:24,040
Speaker 2: to do. And let's let's face it, I mean college sports,

909
00:49:24,040 --> 00:49:28,759
Speaker 2: the NCAA, you know this nil money. I mean, I

910
00:49:28,800 --> 00:49:30,959
Speaker 2: think you're one hundred percent right, it's coming and.

911
00:49:31,040 --> 00:49:34,000
Speaker 1: No, I mean, yeah, we just.

912
00:49:34,000 --> 00:49:36,040
Speaker 2: Don't want to be the union that represents them. You know,

913
00:49:36,280 --> 00:49:40,520
Speaker 2: my son plays college hockey and you know, he's forty

914
00:49:40,560 --> 00:49:43,800
Speaker 2: hours a week, you know, up in the morning training practice,

915
00:49:43,840 --> 00:49:46,839
Speaker 2: and then classes are like you know, eight seven, eight

916
00:49:46,880 --> 00:49:49,319
Speaker 2: o'clock at night. There's twelve thirteen hour days. But the

917
00:49:49,360 --> 00:49:51,640
Speaker 2: majority of the time during the season is focused on

918
00:49:51,960 --> 00:49:52,520
Speaker 2: the season.

919
00:49:53,480 --> 00:49:55,440
Speaker 1: Now, and with all this, I mean when you're talking

920
00:49:55,600 --> 00:49:58,560
Speaker 1: multi billion dollar TV contracts now for these conferences. So

921
00:49:59,080 --> 00:50:01,520
Speaker 1: I think the only way this works is if it's

922
00:50:01,560 --> 00:50:06,879
Speaker 1: a players union by conference, but who knows, I mean yeah,

923
00:50:07,120 --> 00:50:09,759
Speaker 1: or maybe it's by region or something like that. Yeah,

924
00:50:10,080 --> 00:50:12,239
Speaker 1: it'd be nice if our conferences were by region, but

925
00:50:12,360 --> 00:50:12,680
Speaker 1: you know.

926
00:50:12,800 --> 00:50:17,440
Speaker 2: Wouldn't it. Yeah, we got that maybe BC would be

927
00:50:17,480 --> 00:50:19,160
Speaker 2: a competitor.

928
00:50:18,719 --> 00:50:20,319
Speaker 1: Were you a BC player? Where'd you play?

929
00:50:20,800 --> 00:50:25,840
Speaker 2: I went to the University of Mass Mass You Mass, Yeah, yeah.

930
00:50:25,680 --> 00:50:27,800
Speaker 1: Trying hard to be an FBS I love.

931
00:50:27,680 --> 00:50:29,960
Speaker 2: Oh yeah yeah. So I went to the U Mass

932
00:50:29,960 --> 00:50:32,919
Speaker 2: Boston campus. I went to University of New Haven first

933
00:50:32,920 --> 00:50:35,040
Speaker 2: and then went to you Mass. No.

934
00:50:36,000 --> 00:50:40,440
Speaker 1: Well, by the time this airs will know whether the

935
00:50:40,480 --> 00:50:42,239
Speaker 1: Red Sox have beaten the Yankees or not.

936
00:50:42,360 --> 00:50:44,839
Speaker 2: But it's gonna be a tough one. Huh yeah, it's

937
00:50:44,880 --> 00:50:45,200
Speaker 2: gonna be.

938
00:50:45,360 --> 00:50:48,920
Speaker 1: How great two of three between old rivals like this.

939
00:50:49,000 --> 00:50:50,720
Speaker 2: I mean, no matter what, we hate to see someone

940
00:50:50,760 --> 00:50:52,879
Speaker 2: losing that in that situation, you know.

941
00:50:53,520 --> 00:50:55,480
Speaker 1: Get out of here. I got a Red Sox fan.

942
00:50:55,640 --> 00:50:57,319
Speaker 1: What do you mean you hate to see someone lose?

943
00:50:57,360 --> 00:50:59,759
Speaker 2: Well, you do because I mean, look, they're playing that

944
00:50:59,840 --> 00:51:02,080
Speaker 2: high n right. They hate each other.

945
00:51:02,760 --> 00:51:06,520
Speaker 1: Your your empathy, You're filled with empathy. Where's the where's

946
00:51:06,560 --> 00:51:07,799
Speaker 1: the Boston hate? Man?

947
00:51:08,080 --> 00:51:12,040
Speaker 2: Listen, Let's talk hockey. Let's talk football like there's no

948
00:51:12,080 --> 00:51:15,240
Speaker 2: other team than Boston Bruins and the New England Patriots.

949
00:51:15,280 --> 00:51:17,960
Speaker 1: You know, So that's where you that's that's where they

950
00:51:17,960 --> 00:51:18,359
Speaker 1: come at.

951
00:51:18,680 --> 00:51:22,480
Speaker 2: Yeah. Baseball's baseball, you know, Baseball great American sport. We

952
00:51:22,560 --> 00:51:24,120
Speaker 2: used to say my neighbor. But yeah, the kids that

953
00:51:24,800 --> 00:51:27,960
Speaker 2: can't skate end up playing baseball. Oh wow, I know

954
00:51:28,120 --> 00:51:29,600
Speaker 2: exactly where you grew up.

955
00:51:30,600 --> 00:51:33,200
Speaker 1: Hey, shot up bright. This is great man. I appreciate you.

956
00:51:33,480 --> 00:51:35,319
Speaker 2: Appreciate you, my friend. This is all right,