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Speaker 1: Hey, Brian, Hi Katie, Brian, that song is for you

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Speaker 1: because it's a wonderful day here at the pod because

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Speaker 1: the mid term elections are right around the corner on Tuesday,

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Speaker 1: November six and it's all about the mid terms today

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Speaker 1: on our podcast. Brian and I couldn't be more excited.

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Speaker 1: I'm like a kidna candy store, Katie. Most polls, as

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Speaker 1: you know, are favoring Democrats to take control of the

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Speaker 1: House and the Republicans will likely keep control of the Senate.

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Speaker 1: But then again, after two thousand sixteen, who really knows,

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Speaker 1: right nobody, Well, if that does happen, Katie, if the

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Speaker 1: projections are right, it would really change the balance of

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Speaker 1: power in this country. And on the off chance that

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Speaker 1: the Democrats take the House and the Senate, well things

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Speaker 1: will look a lot different for President Trump and for

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Speaker 1: American politics. We've been hearing so much about the mid

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Speaker 1: terms in the news the days, it's sometimes hard to

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Speaker 1: cut through the opinions and memes and downright vitriol to

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Speaker 1: actually understand what's happening in all these races. So today

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Speaker 1: we've invited Claire Malone, a senior political writer at five

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Speaker 1: thirty eight, to give us a picture of where all

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Speaker 1: these races stand and which ones we should pay attention

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Speaker 1: to on Tuesday, and also to give us her view

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Speaker 1: on the big picture, Brian kind of what are the

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Speaker 1: stakes of this election? And then we're going to talk

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Speaker 1: to a wonderful author, Michael Lewis. He has a new

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Speaker 1: book out called The Fifth Risk, which is actually very

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Speaker 1: relevant to the election next week. Michael Lewis, of course

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Speaker 1: wrote The Big Short, he wrote Moneyball, and now for

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Speaker 1: The Fifth Risk, he spent months talking to former and

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Speaker 1: current employees of the federal government and he believes that

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Speaker 1: the Trump administration is wreaking havoc from within. In his view,

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Speaker 1: either political hacks are in charge or appointees more concerned

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Speaker 1: about self interests than the public interests. We've got a

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Speaker 1: lot to cover today. So oh wait a second, Brian,

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Speaker 1: are you hearing that or is it just in my head?

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Speaker 1: It's just in your head. No, I'm actually hearing that.

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Speaker 1: That's right, it's our new theme music. We've given our

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Speaker 1: show sound a bit of a facelift. No funny remarks here,

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Speaker 1: by the way, you should say to the tabloid reporters,

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Speaker 1: that's the only facelift that's happened around here. But I'm

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Speaker 1: pumpch and we want to say a big thank you

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Speaker 1: to Jared Arnold, who composed the new music for us. Yeah.

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Speaker 1: I really like it. It's it's sounding, it's sounding kind

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Speaker 1: of groovy. What do you think? Well, I try to

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Speaker 1: avoid using the word groovy. I haven't used that since,

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Speaker 1: but I would give it a ninety eight for dancing. Anyway,

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Speaker 1: enough about our new music, Let's get to our conversation

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Speaker 1: with Claire Malone from five thirty eight. We began by

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Speaker 1: asking her what's really at stake in next week selections

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Speaker 1: for people who aren't like us, who haven't been glued

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Speaker 1: to their seats paying attention to every healthy people, Yeah,

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Speaker 1: normal people. In other words, what is its stake for

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Speaker 1: these elections? Well, uh, midterm elections are pretty much always

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Speaker 1: a reaction to the party who's in power, and the

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Speaker 1: Republicans have a lot of control over the government. So

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Speaker 1: they have the White House, they have the House of Representatives,

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Speaker 1: and they have the Senate. And I think is is

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Speaker 1: probably no surprise to anyone in America. Um, we're in

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Speaker 1: a highly polarized partisan period of American life, and we

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Speaker 1: have a president who has played into that quite a bit.

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Speaker 1: And so, UM, I think when we talk about the

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Speaker 1: stakes of this election, we are talking about, for getting

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Speaker 1: nitty gritty, you know, the possibility that, you know, if

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Speaker 1: Democrats theoretically retained control of both houses of Congress, they

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Speaker 1: could potentially impeach the president or you know, try to

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Speaker 1: remove him from office. So that's I think the if

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Speaker 1: you're going for the thirty thousand foot up view of things,

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Speaker 1: that's what's at stake. We're talking about all House seats,

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Speaker 1: thirty three Senate seats, thirty six governorships, state legislatures, basically

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Speaker 1: a lot of a lot of bots. Yes, I'm glad

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Speaker 1: you brought up state legislatures, and there's also attorney general's racist.

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Speaker 1: There's a lot of state level seats that are at

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Speaker 1: play here that we don't talk as much about. Um.

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Speaker 1: But right now, it's looking like the Democrats have a

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Speaker 1: pretty good chance of taking back back the House of Representatives.

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Speaker 1: So we have a forecasting model and we give them about,

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Speaker 1: let's say, an eight percent shot of taking back the

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Speaker 1: House of Representatives. The Senate is kind of flipped where

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Speaker 1: the Democrats have about only chance of taking the Senate.

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Speaker 1: And I think you can kind of if you want

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Speaker 1: to look back two years to the split that we

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Speaker 1: saw in the popular vote and the electoral college, they're

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Speaker 1: sort of mirror in the patterns that we're seeing in

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Speaker 1: the House of Representatives in the Senate. So the House

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Speaker 1: of Representatives that's parallel is the popular vote, which the

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Speaker 1: Democrat Hillary Clinton one by three million, and then you've

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Speaker 1: got the Senate, which we can compare to the electoral college.

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Speaker 1: And and it's interesting because the Senate sort of plays

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Speaker 1: to Republicans advantages in these rural states where votes are

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Speaker 1: I guess more effectively economically distributed. We talk a about

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Speaker 1: that where people aren't clustering in certain places. Yeah, we will.

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Speaker 1: You just explain that a little bit for people. Give

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Speaker 1: us a quick civics lesson if you could clear on

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Speaker 1: on Gerrymanderin and sort of why the Senate is so

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Speaker 1: different than House races. Yeah, well, I think we always

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Speaker 1: want to start and talk about the way that Americans

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Speaker 1: have self sorted. Um, so Democrats have tended to in

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Speaker 1: the past few election cycles, past couple of decades, be

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Speaker 1: in big cities or in suburban areas surrounding big cities.

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Speaker 1: And the reason why that why Republicans have um an

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Speaker 1: advantage in the electoral College and in the Senate map

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Speaker 1: is that their votes are in there all over, even

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Speaker 1: in small states. So, uh, they might win a bunch

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Speaker 1: of small counties in North Dakota and that counts for

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Speaker 1: a lot. A Senate seat in North Dakota is worth

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Speaker 1: just as much as a Senate seat in California. And

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Speaker 1: the appeal right now of Republicans seems to be being

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Speaker 1: received better by people in these x urban or you know,

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Speaker 1: rural rural places, and that's a problem obviously the Democrats

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Speaker 1: are trying to kind of claw their way back on.

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Speaker 1: So if you want to think about it in terms

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Speaker 1: of waves, people have talked about this election potentially being

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Speaker 1: a wave election for the Democrats. There are a couple

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Speaker 1: of sea walls that the Republicans have built up to

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Speaker 1: protect themselves from these waves. One is just because of

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Speaker 1: the way the House seats are drawn and in some

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Speaker 1: cases jerrymander to benefit one party. The Democrats have to

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Speaker 1: win the House popular vote by about six points, which

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Speaker 1: is like a near landslide margin in order to win

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Speaker 1: control of the House. And in the Senate, it's not

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Speaker 1: jerrymandered because the state borders are what they've always been,

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Speaker 1: But North Dakota has two Senate seats, Wyoming has two

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Speaker 1: Senate seats, etcetera. And California has two Senate seats, and

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Speaker 1: so there's a there's a bit of a bias there

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Speaker 1: as well. But didn't things start to change a bit

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Speaker 1: even just a couple of weeks ago for the Democrats?

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Speaker 1: And why well, things have sort of as the as

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Speaker 1: the last month of a campaign kind of comes in,

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Speaker 1: you start to see basically partisanship kick in um so

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Speaker 1: on the House side of things that that got kind

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Speaker 1: of a little bit better for for Democrats, and it

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Speaker 1: got a little bit worse for them in the Senate,

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Speaker 1: where you saw states like Nevada, states like Tennessee where

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Speaker 1: you have a pretty centrist Democrat, Phil Brettison, who's the

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Speaker 1: former governor of Tennessee, running for a Senate seat, and

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Speaker 1: he was a pretty popular guy and that race was

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Speaker 1: pretty close. But you're starting to see voters sort of

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Speaker 1: kick in and say, well, I kind of like the

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Speaker 1: guy from the opposite party, but I'm gonna put on

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Speaker 1: my team jersey and wear it and vote for that

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Speaker 1: person in election day. And that's sort of what's showing

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Speaker 1: up in polls. So you are seeing a little bit

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Speaker 1: of a return to what we generally expect. If it's

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Speaker 1: a red state, you're probably going to think that, Well,

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Speaker 1: a lot of those undecided voters that were getting pulled

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Speaker 1: in late September, they might be returning home and saying, well,

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Speaker 1: I'm gonna vote for my party, even if I'm not

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Speaker 1: loving what the president is doing. And I wanted to

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Speaker 1: ask you about early voting because someone told me over

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Speaker 1: the weekend that early voting wasn't looking great in terms

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Speaker 1: of turnout for Latino voters and millennials. Is somebody just

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Speaker 1: saying that to me without any any real knowledge helped

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Speaker 1: me out here. So we have kind of a five

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Speaker 1: thirty eight line where we say early voting there isn't

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Speaker 1: actually any real proof that it gives us a lot

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Speaker 1: of information about, you know, who's going to win an election, Democratic, Republican,

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Speaker 1: because it doesn't. You know, all you know is the

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Speaker 1: early voters. You can tell what their party registration is,

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Speaker 1: we don't know who they voted for, and a lot

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Speaker 1: of times, as we saw in where a lot of

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Speaker 1: Democrats voted for Trump, people cross party lines. But I

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Speaker 1: do think that we are probably going to see. I mean, unfortunately,

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Speaker 1: certain demographics in this country haven't been reached by the

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Speaker 1: political community. The outreach community. Latinos, I think, are one

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Speaker 1: that Democrats had hoped in to really turn out and

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Speaker 1: say the Southwest, and even with Trump's inflammatory rhetoric, they

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Speaker 1: really didn't turn out. And I think that's sort of

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Speaker 1: what people are thinking might happen this year. Although I

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Speaker 1: will say in general it is predicted to be a

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Speaker 1: high turnout election on both sides, Democrat and Republican. What

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Speaker 1: about millennials. It seems to me that young people are

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Speaker 1: so energized, at least from everything I see in my

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Speaker 1: social media feed, which maybe I'm not getting a completely

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Speaker 1: clear perspective. But what about those numbers. I don't think

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Speaker 1: we really know um and I think we kind of

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Speaker 1: have to rely this is the five eight thing. We

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Speaker 1: kind of have to rely on historical trends, and generally

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Speaker 1: younger voters aren't a constituency that you can necessarily count

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Speaker 1: on to turn out in elections. I will say, going

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Speaker 1: back again, I'm not going to make any predictions because

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Speaker 1: it is going to be a high turnout election. That's

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Speaker 1: what's being sort of forecasted from these polls where they

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Speaker 1: you sort of posters ask about your enthusiasm to vote,

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Speaker 1: and the enthusiasm to vote is extremely high, so perhaps

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Speaker 1: we will see higher numbers of millennials voting. Are you

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Speaker 1: a little gunshy because of two thousand sixteen over there

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Speaker 1: at eight? No, I think, I mean, I think, I

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Speaker 1: will say I think. The one thing that is annoying

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Speaker 1: to interview people from the site is that we always

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Speaker 1: kind of do this thing well where we'll say, well,

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Speaker 1: we can't predict it, because but I will say that

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Speaker 1: we did rethink some of the ways that we present

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Speaker 1: our probabilities for people. Is kind of a big with Claire.

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Speaker 1: Well we are we will say that we were the

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Speaker 1: least wrong of anyone congratulation. We should fact check that,

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Speaker 1: and we should actually also explain to our listeners what

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Speaker 1: these forecasts really means. So two years ago, five thirty

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Speaker 1: eight said Hillary Clinton had a seventy one percent chance

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Speaker 1: to win the presidency. Now that was notably lower than

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Speaker 1: some of the others. The New York Times said, Huffington

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Speaker 1: Post really went out there and said, but how do

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Speaker 1: these models work and how do they differ? Yeah? Sure, so, um,

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Speaker 1: the way that the five thirty model works is that

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Speaker 1: we take all of the public polling that's available and

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Speaker 1: we put it together, and we waited based on how

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Speaker 1: good we think the polster is, so better posters get

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Speaker 1: a heavier weight in the model. So we take polls

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Speaker 1: and so that's that's the poll component. Well, also add

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Speaker 1: in whether or not their incumbent. That helps a person

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Speaker 1: if they're an incumbent and they're running. We take into

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Speaker 1: account how partisan a state is. We take into account fundraising,

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Speaker 1: how much a candidate has raised. We smush all those

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Speaker 1: things together in a model. And Um, what I always

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Speaker 1: like to point out is was a really interesting election. Yes,

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Speaker 1: we were, and all of the other models were off.

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Speaker 1: And what was the reason why polls were so off

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Speaker 1: in the election is that, if you'll remember, Donald Trump

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Speaker 1: had huge media reach, he had name recognition, and he

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Speaker 1: motivated a lot of people who had fallen off the

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Speaker 1: voter rolls to come out and vote, and so polls

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Speaker 1: missed a lot of those people. And so we did

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Speaker 1: have a polling problem in And um, yeah, I think

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Speaker 1: there's a lot of you know, a lot of us

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Speaker 1: ineen who are trying to make people basically more I

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Speaker 1: guess literate readers of polls and to know we're not

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Speaker 1: pulling us out of nowhere. And we also want you

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Speaker 1: to know that there is a possibility that this is wrong.

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Speaker 1: This is how probabilities work. So but it is I

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Speaker 1: think it's a learning process for for all of us

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Speaker 1: to make people better news consumers more. Literally, what you

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Speaker 1: meant two years ago was if you were to run

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Speaker 1: this election with all the information and data we have

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Speaker 1: ten times, seven out of ten times Hillary Clinton would

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Speaker 1: win and three out of ten times Donald Trump would win.

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Speaker 1: And so it's not like your quote wrong when you

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Speaker 1: say seventy one percent chance to win and she loses.

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Speaker 1: It's that this was one of those events where it

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Speaker 1: was more likely than not that she would win, but

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Speaker 1: she actually didn't. Yeah, And that's and so this year

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Speaker 1: in our model, we've tried to switch it from making

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Speaker 1: the big bold number instead of it having b oh,

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Speaker 1: it's an eight percent chance, you know, we'll try to say, oh,

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Speaker 1: it's a two and six chance, or it's a three

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Speaker 1: and ten chance that this person will win, just to

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Speaker 1: give people because I think that when we talk about

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Speaker 1: gambling odds, that's kind of the vernacular that we use

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Speaker 1: and so we want to try to make it clearer

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Speaker 1: to people what we're saying. When we do that, Let's

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Speaker 1: talk about recent events layer, because it has been a

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Speaker 1: insane news cycle. As you know, we had the Brett

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Speaker 1: Kavanaugh hearings. We have the pipe bombs that were sent

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Speaker 1: to a number of Democratic officials, philanthropist George Soros CNN,

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Speaker 1: and now most recently, the massacre at that synagogue in Pittsburgh.

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Speaker 1: How do you measure the impact those events have on voters? Yeah,

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Speaker 1: I guess I'll start with Kavanaugh, since it's a bit

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Speaker 1: easier to parse the Kavanaugh hearing. Certainly senators who are

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Speaker 1: voting on the Kavanaugh hearing, some of them in red states.

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Speaker 1: Those red state Democrats had to make tough choices that

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Speaker 1: I think probably for some of them, let's say Heidi

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Speaker 1: hide Camp in North Dakota, probably endangered their their chances

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Speaker 1: on the on the Senate map um and she's someone

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Speaker 1: who's a pretty moderate Democrat. You know, she's from a

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Speaker 1: state that really likes Trump, and she's one of those

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Speaker 1: people that's really been trying to sort of say, run

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Speaker 1: a campaign that says, listen, I'm first and foremost in

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Speaker 1: North Dakotin. I'm not here for Pelosian schumers, a da

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Speaker 1: right as a kind of a response to a lot

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Speaker 1: of Republican tack ads that try to tie red state

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Speaker 1: Democrats to unpopular figures um. And so Heidi hide Camp

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Speaker 1: was sort of chugging along in a re election effort

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Speaker 1: that was, you know, it's a hard state to win.

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Speaker 1: And when the Kavanaugh vote came up, I think she

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Speaker 1: would be open and saying it was a sort of

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Speaker 1: a wrenching decision for her to have to make, because

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Speaker 1: on the one hand, I think she's a woman who

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Speaker 1: was not in favor of this guy who had been

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Speaker 1: accused of um of sexual assault. And on the other hand,

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Speaker 1: I think she knew it was a little bit of

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Speaker 1: a you know, it was gonna it was gonna really

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Speaker 1: diminished the chances that she would be able to win

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Speaker 1: her race in that state, and she made the choice.

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Speaker 1: She voted against Kavanaugh, and it has unleashed, you know,

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Speaker 1: a string of basically attacks against her that says, listen,

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Speaker 1: this this person is not who you are North Dakota.

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Speaker 1: So do you all measure For example, you know, I

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Speaker 1: I spent the weekend in Virginia with my daughter and

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Speaker 1: we spent the night with a friend of mine from

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Speaker 1: high school and we were talking about the Kavanaugh hearings

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Speaker 1: and she was troubled by the way he was treated

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Speaker 1: and felt, you know, sympathetic to his outrage when he testified.

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Speaker 1: And I said, hey, you're one of those white suburban

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Speaker 1: women growing up, you know, in Arlington, Virginia, and that's

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Speaker 1: where we were. Who is you know, supporting perhaps Republican

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Speaker 1: candidates because of what happened to Brett Kavanaugh? Do you

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Speaker 1: are you able to to get that specific in terms

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Speaker 1: of how you're looking at at segments of the electorate,

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Speaker 1: so that doesn't go into the model per se, but

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Speaker 1: you you've hit that nail on the head when you

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Speaker 1: when you bring up demographics that we watch as ones

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Speaker 1: that are shifting post So if we take I'm gonna

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Speaker 1: I'm gonna make a wild guest that your your friend

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Speaker 1: might be college educated, she might be white, and those people,

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Speaker 1: white college educated women are kind of the new swing voters.

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Speaker 1: They used to vote Republican pretty steadily, and now I

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Speaker 1: think post Trump, there maybe in the middle like true

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Speaker 1: into Pennant voters or their trending Democratic. So we I

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Speaker 1: think we'll be watching for women in general and how

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Speaker 1: they vote on election day, but college educated white women

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Speaker 1: in particular, because their constituency that was traditional Republican that

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Speaker 1: more and more seemed to moving over to the Democratic

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Speaker 1: side of things. Well, this was a reality check for me, though,

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Speaker 1: because I think that there are a lot of women

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Speaker 1: who sympathized with him and Brian. I'm curious in Los Angeles,

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Speaker 1: you know that hotbed of conservativism, if you've run against

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Speaker 1: run up against um women who share my friend's point

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Speaker 1: of view. I actually had a conversation with one woman

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Speaker 1: I know who wouldn't tell me what her personal views are,

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Speaker 1: but said that she was convinced that other women would

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Speaker 1: sympathize with Kavanaugh because we've all seen women who make

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Speaker 1: false allegations to get something, and it was hard for

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Speaker 1: me to imagine what Dr Ford would get in this situation.

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Speaker 1: And I mean, last time I checked, she wasn't even

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Speaker 1: allowed to or able to go back to her own home.

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Speaker 1: But I think we've seen in the data that the

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Speaker 1: Kavanaugh hearings energized a lot of Republican voters who might

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Speaker 1: not have voted or and motivated some right leaning independent

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Speaker 1: voters to stick with the Republicans. Yeah, I think that's

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Speaker 1: fair because women, these these you know, college educated white

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Speaker 1: women were probably already a more activated constituency to begin with.

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Speaker 1: So the perceived mistreatment of Kavanaugh, I think, yeah, that

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Speaker 1: certainly has played a factor. Now we kind of have

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Speaker 1: the X factor of these really terrible events of the

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Speaker 1: past week basically, and I we're not quite sure how

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Speaker 1: these are going to affect things. I mean, you know,

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Speaker 1: potentially they could have an effect on Trump's approval rating,

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Speaker 1: and that is often a sign of how people might

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Speaker 1: vote in their congressional races. But it's just you know,

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Speaker 1: I don't mean this is sound flip, but model does

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Speaker 1: not take into account I hate crimes. You know how

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Speaker 1: that factors into American elections, And unfortunately that's something that's

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Speaker 1: happening right now. And doesn't that also, Claire, take a

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Speaker 1: while to seep into the public consciousness and to be

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Speaker 1: reflected in polling data. It does take a little while

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Speaker 1: to seep in. So we're recording this the week before

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Speaker 1: the election. I'm guessing that pollsters will be putting out

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Speaker 1: polls into the field. They probably started last week after

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Speaker 1: the bombings, and so we might see some some data

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Speaker 1: on how people are perceiving those events visa VI the election.

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Speaker 1: Trump's comments in the wake of the synagogue shooting were

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Speaker 1: I found them totally odd, um, And I'm not sure

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Speaker 1: how how people will react to that. But you're right,

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Speaker 1: it does take a little bit of time for these

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Speaker 1: things to seep in, and um, you know, the election

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Speaker 1: is a week away, so we might end up seeing

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Speaker 1: some of those results. Frankly, the day of aren't politics local?

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Speaker 1: I mean, do they really? Is it really a direct

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Speaker 1: reaction to the presidency? In other words, if I live

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Speaker 1: in a state, couldn't I say, I don't really like

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Speaker 1: Donald Trump, but I do like that, you know, my senator.

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Speaker 1: That happens less and less. We call it ticket splitting, um,

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Speaker 1: And because Americans are so much more partisan, we see

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Speaker 1: a lot more people just voting straight down the ticket,

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Speaker 1: Republican or Democratic. There is the old truism, right that

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Speaker 1: all politics is local, but I think more and more

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Speaker 1: it's become nationalized, in part because this was happening pre Trump.

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Speaker 1: But I do think Trump is a He has a

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Speaker 1: talent for driving new cycles, and I think that that

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Speaker 1: is something that that propelled him into office and continues

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Speaker 1: to dominate our politics new cycle. Overwhelmingly, we've become much

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Speaker 1: more like a parliamentary system where people aren't paying attention

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Speaker 1: as they used to a generation ago, to local factors,

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Speaker 1: local candidates. They're really just voting for what team they

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Speaker 1: want and charge in Washington, particularly in these House and

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Speaker 1: Senate races, I want to ask you about one candidate

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Speaker 1: in particular who's been perhaps the star of this cycle,

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Speaker 1: better or Rourke. In Texas, he has just a one

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Speaker 1: in five chance to win. I haven't seen a single

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Speaker 1: poll with him in the lead. He's usually mid to

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Speaker 1: high single digits behind. Have journalists given voters a false

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Speaker 1: sense of his chances, and especially donors who poured more

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Speaker 1: than seventy million dollars into his campaign. Yeah, So I

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Speaker 1: wrote a piece about Beatto about a month ago that

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Speaker 1: was a little bit premised off this Brian and in

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Speaker 1: my lead was basically the number of times he's been

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Speaker 1: compared to a Kennedy And I think it was a

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Speaker 1: hilarious piece. Everybody should read it, by the way, But

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Speaker 1: I think that there's something real there, which is the

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Speaker 1: midterm elections are I guess, distinctly unsexy as far as

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Speaker 1: there's tons of races, there's not one, one or two

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Speaker 1: candidates that you could follow along with. And O'Rourke is young,

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Speaker 1: He's a Democrat making a play in Texas, so there's

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Speaker 1: sort of a substantive political story there. But I do

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Speaker 1: think he is a telegenic person running against Ted Cruz,

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Speaker 1: the Republican incumbent, who is not a particularly beloved figure

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Speaker 1: even by Republicans. Lindsay Graham had a great line that

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Speaker 1: you know, you could you could shoot him on the

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Speaker 1: floor of the Senate and none of his colleagues would

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Speaker 1: would convict the person who shot him. So he's it's

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Speaker 1: it's a he's not a popular guy, let's say. But

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Speaker 1: I think that the media has a little bit hyped

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Speaker 1: up his chances, perhaps to the to the regular reader

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Speaker 1: or media consumer, because of these attractive telligen he's kind

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Speaker 1: of the it guy of the campaign. Yeah, and I

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Speaker 1: think what I do think is really real and something

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Speaker 1: to be taken seriously about Beata o rourke. Listen, I

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Speaker 1: think that he probably won't win the Senate election, but

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Speaker 1: he's raised huge, huge amounts of money Barack Obama two

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Speaker 1: thousand seven financial quarter kind of money, and the comparison

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Speaker 1: to a former president is on purpose because I think

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Speaker 1: a lot of people say, listen, Donald Trump is a celebrity.

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Speaker 1: He was a celebrity before he was the president. Maybe

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Speaker 1: you need someone who has that kind of ineffable our

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Speaker 1: power if you want to beat Trump. I mean, you know,

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Speaker 1: as much as people want to say that voters care

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Speaker 1: more about policy than they do about politics and the

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Speaker 1: things that seem superficial, it's not true. I think people

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Speaker 1: I think politics is a lot more fairmonic, and more

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Speaker 1: like like dating or tribalism than it is referring to

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Speaker 1: pair mony. I am, I am Katie. But but what

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Speaker 1: I mean by that is people vote for the person

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Speaker 1: that they like, the person that they think is kind

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Speaker 1: of like, you know, the person they have a beer with, right, yeah, exactly.

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Speaker 1: And I think that the person I think they want

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Speaker 1: to watch on on a screen, or the person or

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Speaker 1: the person for Democrats who they find inspiring. And I

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Speaker 1: think that the one thing about a Rourks campaign is

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Speaker 1: it has been a positive campaign. You know, he's a

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Speaker 1: demographically a person who could perhaps be more appealing to

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Speaker 1: people outside of Texas. He's a young white man with

430
00:22:49,280 --> 00:22:53,399
Speaker 1: progressive values, which which might be more palatable to you

431
00:22:53,440 --> 00:22:56,199
Speaker 1: know Obama Trump voters, which is what we refer to,

432
00:22:56,400 --> 00:22:58,720
Speaker 1: you know, voters who voted for President Obama but then

433
00:22:58,760 --> 00:23:01,920
Speaker 1: switched voted for Trump. So there's a lot of a

434
00:23:01,960 --> 00:23:03,720
Speaker 1: lot of things to think through with bouto Rourke, and

435
00:23:03,760 --> 00:23:06,920
Speaker 1: I think he represents more than just his Senate campaign

436
00:23:06,920 --> 00:23:10,480
Speaker 1: in Texas. Let's just run through a few more campaigns.

437
00:23:10,560 --> 00:23:13,040
Speaker 1: O'Brien is going to be so excited. I'm excited about

438
00:23:13,080 --> 00:23:15,240
Speaker 1: the first one. And this is the Senate race in

439
00:23:15,520 --> 00:23:20,440
Speaker 1: in Tennessee, and Marcia Blackburn may have to shake it off.

440
00:23:21,280 --> 00:23:23,120
Speaker 1: Do you like that? You guys? That was very clever.

441
00:23:23,760 --> 00:23:28,160
Speaker 1: I just pulled that out him. Well. Taylor Swift made

442
00:23:28,160 --> 00:23:30,720
Speaker 1: a big difference when she finally came out of her

443
00:23:31,160 --> 00:23:35,760
Speaker 1: a political cocoon and spoke very candidly about her feelings

444
00:23:35,800 --> 00:23:39,840
Speaker 1: on Instagram, my favorite social media platform. Tennessee. Yes she

445
00:23:39,920 --> 00:23:42,960
Speaker 1: lives in Tennessee. And then all these people yes, and

446
00:23:43,000 --> 00:23:45,520
Speaker 1: all these people came out and registered to vote. So

447
00:23:45,600 --> 00:23:49,400
Speaker 1: what's happening there? Claire. I mentioned Phil Brettison, the Democratic

448
00:23:49,440 --> 00:23:52,480
Speaker 1: candidate running against Marcia Blackburn a little earlier. That's a

449
00:23:52,480 --> 00:23:55,399
Speaker 1: really interesting race because Tennessee is a super red state.

450
00:23:55,400 --> 00:23:59,520
Speaker 1: It's very Republican. Marcia Blackburn has been a longtime congresswoman

451
00:23:59,520 --> 00:24:03,360
Speaker 1: and she really well she actually goes by Congressman Marsha Blackburn.

452
00:24:03,400 --> 00:24:06,160
Speaker 1: That's her official title. UM, and she sort of took

453
00:24:06,160 --> 00:24:08,200
Speaker 1: on the Tea Party mantle. So she's a very sort

454
00:24:08,200 --> 00:24:12,520
Speaker 1: of popular, super conservative candidate. UM. And Phil Bretta is

455
00:24:12,600 --> 00:24:13,880
Speaker 1: in is you know, he used to be the mayor

456
00:24:13,920 --> 00:24:17,760
Speaker 1: of Nashville. He brought the Tennessee Titans in into the state.

457
00:24:18,119 --> 00:24:20,480
Speaker 1: He was governor, and he was a sort of popular

458
00:24:20,640 --> 00:24:24,320
Speaker 1: moderate governor Bill Clinton we're running in the mid terms,

459
00:24:24,440 --> 00:24:26,280
Speaker 1: he'd probably be something like Phil Breda is in, like

460
00:24:26,359 --> 00:24:29,480
Speaker 1: a southern moderate Democrat. You know, we've we've got it

461
00:24:29,520 --> 00:24:31,720
Speaker 1: as a pretty close race for a red state and

462
00:24:31,800 --> 00:24:35,000
Speaker 1: part because of Bret is is basically an incumbent. He's

463
00:24:35,000 --> 00:24:37,320
Speaker 1: really well known to the state. UM and he's a

464
00:24:37,359 --> 00:24:40,080
Speaker 1: popular guy. And so we're basically it's almost like the

465
00:24:40,080 --> 00:24:44,920
Speaker 1: forces of partisanship, super red, super Republican versus the forces

466
00:24:44,960 --> 00:24:48,800
Speaker 1: of I guess personality and all politics is local? Can

467
00:24:48,840 --> 00:24:52,760
Speaker 1: bretas in win on all politics is local platform in

468
00:24:52,760 --> 00:24:55,600
Speaker 1: a state that is very very partisan. Well, and another

469
00:24:55,680 --> 00:24:59,119
Speaker 1: interesting little wrinkle in Tennessee. As red as the state is,

470
00:24:59,720 --> 00:25:03,600
Speaker 1: it is never elected before a right wing Republican to

471
00:25:03,720 --> 00:25:06,440
Speaker 1: statewide office, to the Senate, or for good. I think

472
00:25:06,440 --> 00:25:09,320
Speaker 1: it's a good point. Yeah, let's talk about Missouri Claire

473
00:25:09,359 --> 00:25:13,640
Speaker 1: McCaskill versus Josh Holly. Claire McCaskill is the incumbent Democrat

474
00:25:13,640 --> 00:25:16,800
Speaker 1: and Josh Holly is the the attorney general in that state.

475
00:25:16,920 --> 00:25:20,160
Speaker 1: It's an interesting one. I mean, Claire McCaskill has had

476
00:25:20,200 --> 00:25:23,080
Speaker 1: some luck that's come her way. Uh. The last time

477
00:25:23,160 --> 00:25:26,240
Speaker 1: she ran, she ran against Todd Aiken And if you

478
00:25:26,240 --> 00:25:29,320
Speaker 1: remember Todd Aikin's name, it's because you remember he talked

479
00:25:29,320 --> 00:25:34,040
Speaker 1: about legitimate rape, which did not play well. Uh. And

480
00:25:34,119 --> 00:25:38,240
Speaker 1: she won that election against the ultimate oxy moron, Yes exactly. Um.

481
00:25:38,280 --> 00:25:40,680
Speaker 1: And then she had a little bit of quote unquote

482
00:25:40,760 --> 00:25:45,520
Speaker 1: luck this year because Missouri had a governor scandal. Eric

483
00:25:45,560 --> 00:25:47,879
Speaker 1: Grayten's who was the governor, had to resign because of

484
00:25:47,920 --> 00:25:50,800
Speaker 1: a potential sexual assault that he was accused of. So

485
00:25:51,000 --> 00:25:54,000
Speaker 1: Missouri has had a weird political year. Um. And so

486
00:25:54,080 --> 00:25:56,119
Speaker 1: I think Claire McCaskill was doing pretty well because the

487
00:25:56,119 --> 00:25:59,359
Speaker 1: Republicans in the state, frankly weren't looking good. They weren't

488
00:25:59,400 --> 00:26:01,639
Speaker 1: a good light, but it has. It's a red state.

489
00:26:01,640 --> 00:26:05,320
Speaker 1: Trump won that state and Josh Holly and Clara McCaskill

490
00:26:05,359 --> 00:26:08,400
Speaker 1: have basically been battling it out over healthcare. We did

491
00:26:08,400 --> 00:26:11,160
Speaker 1: a podcast in five last week where we talked about,

492
00:26:11,240 --> 00:26:14,560
Speaker 1: you know, the number one campaign ad topic is healthcare,

493
00:26:14,880 --> 00:26:17,320
Speaker 1: and that's what Claire McCaskill is running on in that state.

494
00:26:17,359 --> 00:26:20,080
Speaker 1: And Josh Holly is one of the attorneys general who

495
00:26:20,160 --> 00:26:23,080
Speaker 1: is signed on to this make Obamacare illegal, and so

496
00:26:23,160 --> 00:26:26,560
Speaker 1: he is in a bit of a tight spot in

497
00:26:26,560 --> 00:26:29,040
Speaker 1: a state where where healthcare is a big issue. But

498
00:26:29,080 --> 00:26:31,800
Speaker 1: a lot of Republicans O'Brien, right, I mean, I've been

499
00:26:31,800 --> 00:26:37,000
Speaker 1: reading increasingly that Republicans have co opted the healthcare conversation

500
00:26:37,040 --> 00:26:41,960
Speaker 1: are basically, uh, presenting themselves as the candidates who are

501
00:26:42,000 --> 00:26:46,480
Speaker 1: going to preserve and save healthcare and pre existing coverage

502
00:26:46,480 --> 00:26:49,920
Speaker 1: for pre existing conditions, etcetera. And on the other hand,

503
00:26:50,000 --> 00:26:54,520
Speaker 1: they want to dismantle Obamacare. So frankly, I'm confused, Well,

504
00:26:54,640 --> 00:26:58,480
Speaker 1: they're attempting to do that because healthcare has turned from

505
00:26:58,480 --> 00:27:00,680
Speaker 1: a good issue for them in all ast mid term

506
00:27:00,680 --> 00:27:03,560
Speaker 1: four years ago to a really bad issue for them

507
00:27:03,640 --> 00:27:05,720
Speaker 1: this time. Under the category of you don't know what

508
00:27:05,720 --> 00:27:08,800
Speaker 1: you've got until it's gone. A lot of voters are

509
00:27:10,240 --> 00:27:17,520
Speaker 1: Mitchell just pandering the always seemed to go Brian UM.

510
00:27:17,600 --> 00:27:20,440
Speaker 1: So a lot of voters are concerned about the protections

511
00:27:20,520 --> 00:27:23,360
Speaker 1: that they've come to enjoy under the Affordable Care Act

512
00:27:23,400 --> 00:27:26,080
Speaker 1: going away, and so the Republicans are making a big

513
00:27:26,119 --> 00:27:29,080
Speaker 1: effort to say no, no, no no, we're for preserving UH

514
00:27:29,119 --> 00:27:32,760
Speaker 1: protections for people with pre existing conditions. If Claire mccaskell

515
00:27:32,800 --> 00:27:36,240
Speaker 1: can't win in Missouri, probably no Democrat can win for

516
00:27:36,320 --> 00:27:39,840
Speaker 1: federal office, at least in this environment in Missouri. Because

517
00:27:40,560 --> 00:27:44,560
Speaker 1: she's run a really effective campaign. Um. She's a very

518
00:27:44,600 --> 00:27:46,960
Speaker 1: good senator, and I think if she were to lose,

519
00:27:47,000 --> 00:27:49,920
Speaker 1: it would be basically just that they want a supporter

520
00:27:50,000 --> 00:27:52,320
Speaker 1: of Donald Trump's in the Senate. Claire. Let's talk about

521
00:27:52,320 --> 00:27:55,080
Speaker 1: the governor's race in Florida between Andrew Gillam and ron

522
00:27:55,200 --> 00:27:58,160
Speaker 1: De Santis. Andrew Gillam is doing pretty well, so so

523
00:27:58,359 --> 00:28:02,080
Speaker 1: the background. Andrew Gillam is the is the Democrat, he

524
00:28:02,200 --> 00:28:06,440
Speaker 1: is the black mayor of Tallahassee. UM, and Rhonda Santis

525
00:28:06,560 --> 00:28:10,000
Speaker 1: is a pretty right wing Republican and they are locked

526
00:28:10,000 --> 00:28:13,200
Speaker 1: in a race that is looking increasingly bad for De Santists,

527
00:28:13,200 --> 00:28:15,760
Speaker 1: I think in part because of his his pretty far

528
00:28:15,880 --> 00:28:19,960
Speaker 1: right policies. Florida is a purple state. Gil Him and

529
00:28:20,000 --> 00:28:23,400
Speaker 1: De Santis were both kind of surprises in their primaries.

530
00:28:23,760 --> 00:28:25,359
Speaker 1: Then the Democratic side there were a lot, you know,

531
00:28:25,359 --> 00:28:27,199
Speaker 1: a lot of centrists that people thought would win. And

532
00:28:27,240 --> 00:28:29,200
Speaker 1: gil Him is kind of trying to run as an outsider.

533
00:28:29,240 --> 00:28:30,920
Speaker 1: So I think that's appealing to a lot of people.

534
00:28:31,040 --> 00:28:35,840
Speaker 1: And actually the governor's race might have cascading effects on

535
00:28:35,880 --> 00:28:39,040
Speaker 1: the Senate race because Bill Nelson is the Democratic and

536
00:28:39,080 --> 00:28:41,680
Speaker 1: coming in the Senate and he's running against Republican Governor

537
00:28:41,760 --> 00:28:44,360
Speaker 1: Rick Scott for the seat. And some people are saying

538
00:28:44,400 --> 00:28:46,640
Speaker 1: these are both older white men. Some people are saying

539
00:28:46,640 --> 00:28:50,200
Speaker 1: that gill Him might actually turn out certain constituencies that

540
00:28:50,240 --> 00:28:53,680
Speaker 1: wouldn't that Bill Nelson, the white older man, wouldn't necessarily

541
00:28:53,680 --> 00:28:56,400
Speaker 1: be able to get on his own. What's interesting, immediately

542
00:28:56,440 --> 00:28:59,120
Speaker 1: out of the gate, as the general election began, De

543
00:28:59,240 --> 00:29:06,200
Speaker 1: Santis mixed up um in racial politics um and arguably

544
00:29:06,240 --> 00:29:09,280
Speaker 1: it was his own fault because he used the phrase,

545
00:29:09,520 --> 00:29:12,080
Speaker 1: let's not monkey up the progress that we've made in

546
00:29:12,120 --> 00:29:15,080
Speaker 1: Florida with a liberal governor and a lot of people

547
00:29:15,120 --> 00:29:17,400
Speaker 1: took that to be a racial attack on Andrew Gilham,

548
00:29:17,440 --> 00:29:21,560
Speaker 1: and it's basically not gone very smoothly for de Santis

549
00:29:21,600 --> 00:29:24,640
Speaker 1: since then. Well, Andrew Gillham was so effective I think

550
00:29:24,680 --> 00:29:27,520
Speaker 1: in the debate and that sound bite got played over

551
00:29:27,560 --> 00:29:29,480
Speaker 1: and over again where he said, I'm not saying you're

552
00:29:29,480 --> 00:29:33,320
Speaker 1: a racist, I'm saying racist, think you're a racist. Good line.

553
00:29:34,240 --> 00:29:39,000
Speaker 1: Let's talk about Georgia, the race between Stacy Abrahams, who

554
00:29:39,000 --> 00:29:42,920
Speaker 1: would be the first black female governor in history, and

555
00:29:42,960 --> 00:29:46,240
Speaker 1: Brian Kemp. There's been so much debate. I saw that

556
00:29:46,320 --> 00:29:49,800
Speaker 1: President Carter spoke out about this and said that Brian Kemp,

557
00:29:49,840 --> 00:29:54,400
Speaker 1: who is the Secretary of State for the State of Georgia,

558
00:29:54,760 --> 00:29:57,760
Speaker 1: should step down from that role during the campaign because

559
00:29:57,800 --> 00:30:01,080
Speaker 1: he controls a lot of the vote. Dean and how

560
00:30:01,080 --> 00:30:04,760
Speaker 1: it's carried out. Um, so help us understand that, Claire. Yeah,

561
00:30:04,800 --> 00:30:07,520
Speaker 1: So that the controversy in Georgia is that it has

562
00:30:07,560 --> 00:30:11,720
Speaker 1: a pretty restrictive voting law and a lot of African

563
00:30:11,760 --> 00:30:15,400
Speaker 1: American voters that their registrations now have problems and they

564
00:30:15,480 --> 00:30:18,040
Speaker 1: might not be able to vote in the election. And

565
00:30:18,400 --> 00:30:21,760
Speaker 1: what President Carter was saying is basically that Brian Kemp

566
00:30:21,760 --> 00:30:24,120
Speaker 1: is not an impartial administrator of this election and that

567
00:30:24,200 --> 00:30:26,840
Speaker 1: he shouldn't be able to administer it. Now, what's interesting

568
00:30:26,840 --> 00:30:30,120
Speaker 1: about Georgia is one it's got these racial dynamics, both

569
00:30:30,120 --> 00:30:32,320
Speaker 1: in the voting stuff but also in the in the

570
00:30:32,360 --> 00:30:35,640
Speaker 1: candidates themselves, with Stacy being black and Brian Kemp being

571
00:30:35,920 --> 00:30:38,680
Speaker 1: a pretty far right Republican. He's also white, white guy.

572
00:30:39,000 --> 00:30:41,760
Speaker 1: What I think is interesting about this campaign is she

573
00:30:42,040 --> 00:30:44,560
Speaker 1: is trying to win a southern state as a black

574
00:30:44,600 --> 00:30:47,720
Speaker 1: woman with a kind of new proposition, which is she's saying,

575
00:30:47,840 --> 00:30:50,880
Speaker 1: I am going to register and turn out a whole

576
00:30:50,880 --> 00:30:54,760
Speaker 1: bunch of minorities in addition to winning the moderate swing voters.

577
00:30:54,920 --> 00:30:59,360
Speaker 1: Those white college educated women said my friend like your friend, um,

578
00:30:59,440 --> 00:31:02,040
Speaker 1: And that's that's kind of a new proposition for the

579
00:31:02,080 --> 00:31:03,760
Speaker 1: South a little bit. I mean, you saw a little

580
00:31:03,760 --> 00:31:07,200
Speaker 1: bit with Doug Jones in in Alabama and that special election,

581
00:31:07,280 --> 00:31:08,680
Speaker 1: and I went and hung out with him in the

582
00:31:08,720 --> 00:31:11,600
Speaker 1: spring and for a profile I did, and Jones is,

583
00:31:11,800 --> 00:31:14,520
Speaker 1: you know, he's really trying to maintain ties to the

584
00:31:14,560 --> 00:31:18,680
Speaker 1: black community because they turned out in huge Obama level

585
00:31:18,720 --> 00:31:21,840
Speaker 1: numbers for him. Black women, Yes, exactly, And in order

586
00:31:21,880 --> 00:31:23,520
Speaker 1: for him to, you know, when he's when he's up

587
00:31:23,520 --> 00:31:25,800
Speaker 1: for re election again in he's going to need to

588
00:31:25,840 --> 00:31:28,560
Speaker 1: have that huge turnout of those black voters. So the

589
00:31:28,600 --> 00:31:32,080
Speaker 1: South we're seeing, you know, potentially with Abram's a bit

590
00:31:32,120 --> 00:31:34,360
Speaker 1: of a new dynamic of the kind of candidate that

591
00:31:34,400 --> 00:31:37,120
Speaker 1: Democrats see as winnable. Because I think that's what's different

592
00:31:37,160 --> 00:31:40,200
Speaker 1: with Southern Democrats in those Deep South states is often

593
00:31:40,560 --> 00:31:42,640
Speaker 1: I think black populations have felt like they don't have

594
00:31:42,680 --> 00:31:45,120
Speaker 1: a viable candidate on a state level that they want

595
00:31:45,120 --> 00:31:47,320
Speaker 1: to turn out for and vote for um And so

596
00:31:47,360 --> 00:31:49,000
Speaker 1: I think that's what those are the that's the different

597
00:31:49,040 --> 00:31:51,280
Speaker 1: dynamic that you're seeing with Stacy Abrams. When you say

598
00:31:51,360 --> 00:31:56,160
Speaker 1: problems with their registration or with something associated with their

599
00:31:56,280 --> 00:31:59,120
Speaker 1: ability to vote, what do you mean by that? So

600
00:31:59,200 --> 00:32:02,800
Speaker 1: Georgia's law has it that if anything on your registration

601
00:32:03,200 --> 00:32:05,720
Speaker 1: card doesn't match your I D. So it could be

602
00:32:05,760 --> 00:32:08,640
Speaker 1: a typo in your name or a number is off

603
00:32:08,640 --> 00:32:12,880
Speaker 1: on your address, then it invalidates the voter registration. So

604
00:32:13,480 --> 00:32:16,200
Speaker 1: if you're thinking that that has echoes to old Southern

605
00:32:16,880 --> 00:32:19,640
Speaker 1: poll laws, you are you are right. It's an incredibly

606
00:32:19,680 --> 00:32:23,720
Speaker 1: restrictive law, and I believe Kemp was, you know, basically

607
00:32:23,720 --> 00:32:26,840
Speaker 1: caught on tape at a fundraiser saying I'm gonna lose

608
00:32:26,920 --> 00:32:29,680
Speaker 1: if if all these people vote, which I think is

609
00:32:29,680 --> 00:32:32,760
Speaker 1: probably where President Carter's comments come from. A bit that's

610
00:32:32,800 --> 00:32:35,080
Speaker 1: quite a quite a skewed thing for a Secretary of

611
00:32:35,120 --> 00:32:38,720
Speaker 1: State to say. So. So, Georgia certainly has a long

612
00:32:38,840 --> 00:32:43,600
Speaker 1: history of restrictive voting laws and it continues in well,

613
00:32:43,640 --> 00:32:46,480
Speaker 1: and restrictive voting laws could be to go back to

614
00:32:46,560 --> 00:32:48,600
Speaker 1: my metaphor from the beginning, that the kind of the

615
00:32:48,640 --> 00:32:51,920
Speaker 1: third Sea wall against a democratic wave that Republicans have

616
00:32:52,000 --> 00:32:54,880
Speaker 1: put up that particularly in states that they've controlled for

617
00:32:55,000 --> 00:32:58,720
Speaker 1: some period of time, they can shape the electorate based

618
00:32:58,720 --> 00:33:02,200
Speaker 1: on who's allowed to vote and who isn't um. But

619
00:33:02,320 --> 00:33:06,720
Speaker 1: you know, those two governors races are really interesting because

620
00:33:06,720 --> 00:33:09,160
Speaker 1: they go to a larger debate that's happening within the

621
00:33:09,200 --> 00:33:13,160
Speaker 1: Democratic Party about where the party should go. Particularly in

622
00:33:13,200 --> 00:33:18,800
Speaker 1: advance of Gilham and Abrams are both considered sort of

623
00:33:18,880 --> 00:33:23,480
Speaker 1: mobilization candidates. That is, they're more about exciting the base,

624
00:33:24,280 --> 00:33:28,840
Speaker 1: getting large numbers of millennials African Americans to turn out,

625
00:33:28,920 --> 00:33:32,360
Speaker 1: with a more explicitly progressive agenda and that's been kind

626
00:33:32,360 --> 00:33:34,120
Speaker 1: of the way they've been covered by the media. But

627
00:33:34,120 --> 00:33:36,080
Speaker 1: I would say I think there's a piece that's missing,

628
00:33:36,480 --> 00:33:39,920
Speaker 1: which is that Gilham and Abrams have both also spent

629
00:33:40,000 --> 00:33:43,640
Speaker 1: a lot of time and effort trying to win over white,

630
00:33:43,760 --> 00:33:46,720
Speaker 1: moderate swing voters because they both have to do that

631
00:33:46,760 --> 00:33:49,240
Speaker 1: because the Democratic base alone is not big enough to

632
00:33:49,280 --> 00:33:51,120
Speaker 1: win in either of these states. And so I think

633
00:33:51,120 --> 00:33:53,240
Speaker 1: it's a little bit of a kind of a misperception

634
00:33:53,600 --> 00:33:56,080
Speaker 1: that they're just doing one and not the other. But anyway,

635
00:33:56,080 --> 00:34:00,400
Speaker 1: I'll get off my soapbox now. Finally, Claire, if Amocrats

636
00:34:00,440 --> 00:34:04,640
Speaker 1: win the House, which it looks fairly likely, is that

637
00:34:04,680 --> 00:34:09,239
Speaker 1: a yes, How will it change Washington? I mean, you know,

638
00:34:09,280 --> 00:34:14,080
Speaker 1: Washington has had basically one party rule during the Trump administration,

639
00:34:14,120 --> 00:34:17,200
Speaker 1: which means Republicans have controlled the House, the Senate, in

640
00:34:17,239 --> 00:34:19,640
Speaker 1: the White House. So I think if Democrats win the House,

641
00:34:20,080 --> 00:34:24,759
Speaker 1: they will be going gung ho on oversight, so you know,

642
00:34:24,800 --> 00:34:29,640
Speaker 1: looking into Trump's taxes, looking into abuse at certain agencies.

643
00:34:29,680 --> 00:34:32,279
Speaker 1: The e p A jumps to mind with Scott Pruitt's

644
00:34:32,400 --> 00:34:36,080
Speaker 1: uh sort of financial mismanagement. I think there's going to

645
00:34:36,160 --> 00:34:39,880
Speaker 1: be a lot more vocal oversight of what the Trump

646
00:34:39,920 --> 00:34:45,320
Speaker 1: administration is doing, and perhaps you know, investigations will be open.

647
00:34:45,400 --> 00:34:47,919
Speaker 1: So I think that's one thing. I mean, I think

648
00:34:47,960 --> 00:34:50,440
Speaker 1: that Nancy Pelosi, if she were sitting here at this table,

649
00:34:50,440 --> 00:34:52,720
Speaker 1: would say, we do not want to impeach the president.

650
00:34:53,280 --> 00:34:58,880
Speaker 1: And this goes to, you know, Brian's point about alienating voters.

651
00:34:58,920 --> 00:35:04,400
Speaker 1: I think people remember or how divisive the impeachment proceedings

652
00:35:04,440 --> 00:35:08,640
Speaker 1: against Bill Clinton were. I think people feel impeachment would

653
00:35:08,680 --> 00:35:11,319
Speaker 1: almost be a bridge too far. There will certainly be

654
00:35:11,400 --> 00:35:15,719
Speaker 1: Democrats who will be calling to bring articles impeachment against

655
00:35:15,760 --> 00:35:19,600
Speaker 1: President Trump, but I'm not sure that the Democratic leadership

656
00:35:19,640 --> 00:35:22,440
Speaker 1: wants to go that far and alienate a bunch of

657
00:35:22,440 --> 00:35:24,200
Speaker 1: people that they need to win over in twice. So

658
00:35:24,320 --> 00:35:27,480
Speaker 1: the Senate has to convict, right, convict. I mean, so

659
00:35:28,040 --> 00:35:36,040
Speaker 1: isn't it sort of just um kind of a pr stunt. Yeah,

660
00:35:35,600 --> 00:35:38,480
Speaker 1: it's a base it's a base rally. I think it's

661
00:35:38,480 --> 00:35:42,160
Speaker 1: a base rallying effort. Pre that would be the argument

662
00:35:42,200 --> 00:35:45,520
Speaker 1: for for bringing up impeachment, and I think the counter argument,

663
00:35:46,120 --> 00:35:49,719
Speaker 1: which again Pelosi vouches for, is listen, we can't do

664
00:35:49,800 --> 00:35:51,880
Speaker 1: this right now. We need to win. Yes, we need

665
00:35:51,920 --> 00:35:53,399
Speaker 1: to win the base, but we also need to win

666
00:35:53,960 --> 00:36:00,440
Speaker 1: Obama Trump voters in the Midwest. Claire Malone from Claire,

667
00:36:00,480 --> 00:36:02,879
Speaker 1: thanks so much. This was so much fun. I haven't

668
00:36:02,880 --> 00:36:07,760
Speaker 1: seen Brian this happy in months, honestly, Oh my god,

669
00:36:07,960 --> 00:36:09,880
Speaker 1: it was. This was very big for me. Thank you

670
00:36:09,960 --> 00:36:11,719
Speaker 1: very much. Thank you so much for having me. It

671
00:36:11,760 --> 00:36:19,800
Speaker 1: was very fun. From my into. Before we take a break,

672
00:36:19,880 --> 00:36:23,160
Speaker 1: a quick announcement. This week is our pre mid terms show,

673
00:36:23,560 --> 00:36:27,800
Speaker 1: so naturally next week will be our post mid term show. Gosh, Brian,

674
00:36:27,840 --> 00:36:30,080
Speaker 1: I don't know what you're gonna do with yourself as

675
00:36:30,120 --> 00:36:32,439
Speaker 1: part of that show. By the way, we want you,

676
00:36:32,520 --> 00:36:35,000
Speaker 1: our listeners, to call in and tell us what you think.

677
00:36:35,320 --> 00:36:37,040
Speaker 1: We really want to know what's on your mind, what

678
00:36:37,200 --> 00:36:40,359
Speaker 1: questions you have about what it all means. So if

679
00:36:40,360 --> 00:36:43,319
Speaker 1: you'd like to talk with Katie or me, which is

680
00:36:43,320 --> 00:36:45,239
Speaker 1: hard to believe, but mostly if you'd like to talk

681
00:36:45,239 --> 00:36:48,160
Speaker 1: to Katie, call nine to nine to two four four

682
00:36:48,280 --> 00:36:52,279
Speaker 1: six three seven, leave a voicemail anytime between now and

683
00:36:52,400 --> 00:36:55,120
Speaker 1: Wednesday morning, and we'll select a few of you to

684
00:36:55,200 --> 00:36:58,359
Speaker 1: be on next week's show. In your voicemail, make sure

685
00:36:58,360 --> 00:37:00,480
Speaker 1: to tell us where you're from, why you're hauling, and

686
00:37:00,560 --> 00:37:02,879
Speaker 1: your phone number. So that we can call you back.

687
00:37:03,080 --> 00:37:05,200
Speaker 1: We can't wait to hear from you again. That number

688
00:37:05,280 --> 00:37:09,120
Speaker 1: is nine to nine, two to four, four, six, three seven,

689
00:37:09,280 --> 00:37:11,760
Speaker 1: and we'll be back with Michael Lewis to talk about

690
00:37:11,800 --> 00:37:15,120
Speaker 1: the decay of the federal government. Yep, b that's right

691
00:37:15,120 --> 00:37:22,520
Speaker 1: after this. Now, before we talk with Michael Lewis, we

692
00:37:22,560 --> 00:37:25,600
Speaker 1: have an important message for you, and that message is

693
00:37:26,360 --> 00:37:31,880
Speaker 1: it's fun when everybody v O T S. That's my

694
00:37:32,000 --> 00:37:35,719
Speaker 1: new voting song. Brian, Yeah, Katie, I think what you're

695
00:37:35,719 --> 00:37:38,560
Speaker 1: saying is it's really important that everybody votes and that

696
00:37:38,640 --> 00:37:41,840
Speaker 1: they sing along with me. Research shows that the majority

697
00:37:41,880 --> 00:37:44,560
Speaker 1: of young people still are not sure whether they'll vote.

698
00:37:44,640 --> 00:37:48,000
Speaker 1: Can you believe that? What is wrong with you people? Brian?

699
00:37:48,040 --> 00:37:50,879
Speaker 1: Does that mean you're not sure yet? Well, I don't

700
00:37:50,880 --> 00:37:54,600
Speaker 1: think I'm still considered a young person anymore. Sadly, anyway,

701
00:37:54,640 --> 00:37:56,520
Speaker 1: if I am, I'm in the minority because I am

702
00:37:56,560 --> 00:37:59,319
Speaker 1: already a positive that I'm going to vote, and I

703
00:37:59,400 --> 00:38:02,160
Speaker 1: even have a plan to do so. And how self

704
00:38:02,360 --> 00:38:05,480
Speaker 1: confident do I sound? You sound very confident and I

705
00:38:05,520 --> 00:38:08,359
Speaker 1: am as well. I plan to vote. But I get

706
00:38:08,360 --> 00:38:10,800
Speaker 1: it some of you young people don't know where to vote.

707
00:38:11,080 --> 00:38:13,120
Speaker 1: You're not sure what's on the ballot. You don't want

708
00:38:13,120 --> 00:38:14,799
Speaker 1: to vote the wrong way, or maybe you just think

709
00:38:14,840 --> 00:38:17,880
Speaker 1: your vote doesn't matter. Well, surprise, surprise, We're here to

710
00:38:17,880 --> 00:38:20,520
Speaker 1: tell you it does matter. Look at two thousand, look

711
00:38:20,520 --> 00:38:24,120
Speaker 1: at one vote per precinct can make all the difference.

712
00:38:24,400 --> 00:38:26,880
Speaker 1: And lucky for all of us, our friends at Crooked

713
00:38:26,880 --> 00:38:30,440
Speaker 1: Media have launched votes save America, a step by step

714
00:38:30,480 --> 00:38:33,239
Speaker 1: guide to answer all of your questions. On votes save

715
00:38:33,320 --> 00:38:35,840
Speaker 1: America dot com, you can check if you're registered and

716
00:38:35,960 --> 00:38:38,840
Speaker 1: register if you're not. You can see what the rules

717
00:38:38,840 --> 00:38:42,080
Speaker 1: are in your state about registration deadlines and voter i D.

718
00:38:42,560 --> 00:38:45,640
Speaker 1: You can learn more about candidates and close races, and

719
00:38:45,760 --> 00:38:48,400
Speaker 1: you can look at a ballot guide that explains what

720
00:38:48,600 --> 00:38:52,359
Speaker 1: is on your specific ballot in plain English. So visit

721
00:38:52,480 --> 00:38:55,560
Speaker 1: votes save America dot com and remember to vote. On

722
00:38:55,640 --> 00:38:58,960
Speaker 1: November six, we turned out to Michael Lewis. He's written

723
00:38:59,000 --> 00:39:02,560
Speaker 1: bestsellers like The Blindside, The Big Short, and Moneyball, all

724
00:39:02,560 --> 00:39:05,040
Speaker 1: of which were adapted for the big screen. By the way,

725
00:39:05,200 --> 00:39:07,840
Speaker 1: Michael has a knack for taking a topic that seems

726
00:39:07,840 --> 00:39:11,360
Speaker 1: boring or complicated, like statistics in baseball, for example, and

727
00:39:11,400 --> 00:39:14,759
Speaker 1: making it very exciting and relevant and that's exactly what

728
00:39:14,800 --> 00:39:17,239
Speaker 1: he's done in his latest book, which is called The

729
00:39:17,239 --> 00:39:19,920
Speaker 1: Fifth Risk. The new book tackles the decay of the

730
00:39:19,960 --> 00:39:23,160
Speaker 1: federal government under the Trump administration. So we'll talk with

731
00:39:23,239 --> 00:39:26,880
Speaker 1: Michael about why this could be really, really dangerous for

732
00:39:26,920 --> 00:39:30,120
Speaker 1: the world, for our country, and how it could be stopped.

733
00:39:34,400 --> 00:39:36,759
Speaker 1: Michael Lewis, Welcome to the podcast. We're thrilled to have

734
00:39:36,880 --> 00:39:38,920
Speaker 1: you here. Pleasure to be here. I know that your

735
00:39:38,960 --> 00:39:41,960
Speaker 1: book tries to pull back the curtain and really show

736
00:39:42,000 --> 00:39:44,600
Speaker 1: people with the impact of two years of the Trump

737
00:39:44,640 --> 00:39:49,120
Speaker 1: administration has had on the federal government. And you really

738
00:39:49,160 --> 00:39:53,080
Speaker 1: talk about the importance of the transition from the very

739
00:39:53,120 --> 00:39:57,440
Speaker 1: beginning as there's a transition from one administration to another.

740
00:39:58,120 --> 00:40:01,400
Speaker 1: So tell us why the this period of time is

741
00:40:01,480 --> 00:40:07,080
Speaker 1: so critical. Well, the United States government, unlike most governments

742
00:40:07,080 --> 00:40:10,360
Speaker 1: in the world, has a layer of leadership. It's politically

743
00:40:10,360 --> 00:40:13,320
Speaker 1: import appointed four thousand or so people who are actually

744
00:40:13,400 --> 00:40:17,960
Speaker 1: run the place are appointed by the president. And what

745
00:40:18,080 --> 00:40:22,000
Speaker 1: you have after a presidential election, assuming that the incumbent

746
00:40:22,040 --> 00:40:25,799
Speaker 1: doesn't win, is someone's leaving with their four thousand people

747
00:40:25,840 --> 00:40:28,840
Speaker 1: who have been running the place for a while, and

748
00:40:28,880 --> 00:40:31,440
Speaker 1: someone's coming in with their four thousand people, many of

749
00:40:31,480 --> 00:40:34,360
Speaker 1: whom have never been there before. There's this transfer of

750
00:40:34,440 --> 00:40:37,920
Speaker 1: knowledge that is absolutely critical, and it is has nothing

751
00:40:37,960 --> 00:40:40,640
Speaker 1: to do with political ideology. It's so sort of how

752
00:40:40,760 --> 00:40:43,319
Speaker 1: to So you go into the Department of Energy and

753
00:40:43,320 --> 00:40:46,600
Speaker 1: they say, we managed the nuclear arsenal. Here's how you

754
00:40:46,719 --> 00:40:52,440
Speaker 1: test stomic weapons without actually blowing one up. Important. In fact,

755
00:40:52,640 --> 00:40:54,880
Speaker 1: you can think of the federal government as like this

756
00:40:55,000 --> 00:40:58,719
Speaker 1: huge portfolio of risks that are being managed, and many

757
00:40:58,760 --> 00:41:02,240
Speaker 1: of which we don't even think about. And the idea

758
00:41:02,480 --> 00:41:05,240
Speaker 1: is that you know, before the election, well before the election,

759
00:41:05,440 --> 00:41:09,480
Speaker 1: the candidates of both major parties have hundreds of people

760
00:41:09,680 --> 00:41:12,239
Speaker 1: waiting to rush in the day after the election, because

761
00:41:12,239 --> 00:41:16,160
Speaker 1: you really only have from from that day until the inauguration.

762
00:41:16,320 --> 00:41:19,160
Speaker 1: And then by a law, the people who have left

763
00:41:19,239 --> 00:41:20,959
Speaker 1: are not allowed to get in touch with the people

764
00:41:20,960 --> 00:41:25,120
Speaker 1: who are there. They can be solicited. And the thing

765
00:41:25,160 --> 00:41:26,799
Speaker 1: that interested me in the story in the first place,

766
00:41:26,840 --> 00:41:28,840
Speaker 1: because I did not have a native interest in the

767
00:41:28,840 --> 00:41:31,320
Speaker 1: Department of Agriculture, you know, I mean, they didn't occur

768
00:41:31,360 --> 00:41:35,359
Speaker 1: to me that would be material, was that the Obama administration,

769
00:41:36,120 --> 00:41:38,120
Speaker 1: partly because there was a law requiring them to do it,

770
00:41:38,719 --> 00:41:41,040
Speaker 1: but partly because Bush at handed the government off so

771
00:41:41,120 --> 00:41:44,520
Speaker 1: well to Obama had to go on to great links

772
00:41:44,600 --> 00:41:47,759
Speaker 1: to create essentially the best course ever created in how

773
00:41:47,800 --> 00:41:51,040
Speaker 1: the government works. Thousand people across the government for the

774
00:41:51,040 --> 00:41:53,719
Speaker 1: better part of the year putting together briefings. So if

775
00:41:53,760 --> 00:41:57,200
Speaker 1: you got made secretary of the Interior, you would be

776
00:41:57,239 --> 00:42:00,360
Speaker 1: briefed by people who really understood how the Interior Department worked,

777
00:42:00,400 --> 00:42:03,279
Speaker 1: and you would be hit the ground running. They were

778
00:42:03,280 --> 00:42:07,000
Speaker 1: expecting the day after the election for hundreds of people

779
00:42:07,000 --> 00:42:09,640
Speaker 1: to come in. So let's let's back up one day

780
00:42:09,680 --> 00:42:13,520
Speaker 1: before that, those meetings uh to election night, and you

781
00:42:13,600 --> 00:42:18,000
Speaker 1: tell this really incredible story about Mike Pence and his wife,

782
00:42:18,040 --> 00:42:22,040
Speaker 1: which is really indicative of how the Trump people felt

783
00:42:22,160 --> 00:42:25,640
Speaker 1: about their chances of winning and may explain the chaos

784
00:42:25,680 --> 00:42:27,960
Speaker 1: of the transition. So this is actually right. The key

785
00:42:27,960 --> 00:42:30,000
Speaker 1: to the whole thing is that they weren't running to win.

786
00:42:30,040 --> 00:42:32,200
Speaker 1: They didn't think they were going to win. Bannon would

787
00:42:32,200 --> 00:42:35,040
Speaker 1: take exception to this. Bannon may have actually, in his

788
00:42:35,120 --> 00:42:37,360
Speaker 1: heart of hearts, believed it, but most everybody involved with

789
00:42:37,440 --> 00:42:41,160
Speaker 1: it thought, including Trump, was not prepared to win. So

790
00:42:41,200 --> 00:42:44,040
Speaker 1: they had not written an acceptance speech. They had written

791
00:42:44,080 --> 00:42:48,359
Speaker 1: a concession speech. That explains why a lot of people

792
00:42:48,360 --> 00:42:50,520
Speaker 1: are willing to go along for the ride, and how

793
00:42:50,560 --> 00:42:53,280
Speaker 1: they go along for the ride because they aren't thinking

794
00:42:53,280 --> 00:42:55,520
Speaker 1: this man is going to actually run the federal government.

795
00:42:55,520 --> 00:42:58,400
Speaker 1: They're thinking he's building a brand. I think it's what

796
00:42:58,480 --> 00:43:02,040
Speaker 1: they were thinking. And I'm I'm building my brand being

797
00:43:02,040 --> 00:43:04,719
Speaker 1: associated with it for some period of time. I'm not

798
00:43:04,760 --> 00:43:08,760
Speaker 1: actually preparing to govern in the country. The Mike Pence

799
00:43:08,800 --> 00:43:13,680
Speaker 1: story was I mean Karen Pence, Mike's wife. Mike apparently

800
00:43:13,760 --> 00:43:16,759
Speaker 1: leaned over to kiss her when Pennsylvania was called for

801
00:43:16,800 --> 00:43:19,080
Speaker 1: Trump and it was clear Trump's could be president, and

802
00:43:19,080 --> 00:43:22,520
Speaker 1: and and she says, pushed him away and says, you

803
00:43:22,640 --> 00:43:26,360
Speaker 1: got what you wanted, Mike, leave me alone. And yeah, no,

804
00:43:26,440 --> 00:43:29,839
Speaker 1: I don't. She was the people in the room. It's

805
00:43:30,000 --> 00:43:34,520
Speaker 1: something that really makes feelings about winning. And Trump himself

806
00:43:34,680 --> 00:43:37,960
Speaker 1: had been playing the game. It's like he really is

807
00:43:38,000 --> 00:43:40,440
Speaker 1: a guy whose bluff is called. He had not taken

808
00:43:40,480 --> 00:43:42,759
Speaker 1: seriously the idea he had to take over this operation.

809
00:43:42,800 --> 00:43:45,960
Speaker 1: But Chris Christie had been appointed head of the transition,

810
00:43:46,600 --> 00:43:50,000
Speaker 1: and what happened right after election night to him. So

811
00:43:50,200 --> 00:43:52,320
Speaker 1: we really need to know is what happened before because

812
00:43:52,600 --> 00:43:55,719
Speaker 1: Christie had seen in the newspaper that they were required

813
00:43:55,760 --> 00:43:58,960
Speaker 1: to prepare for the transition and that there were federal

814
00:43:59,080 --> 00:44:02,040
Speaker 1: resources of ail able to do it. And he called

815
00:44:02,080 --> 00:44:03,839
Speaker 1: Trump and said, let me do it, because he said,

816
00:44:03,920 --> 00:44:05,279
Speaker 1: I'm not gonna be president, but the next of us

817
00:44:05,280 --> 00:44:08,560
Speaker 1: thing that's kind of planned to be president. And this

818
00:44:08,600 --> 00:44:10,640
Speaker 1: isn't my view, this is a view of just independent

819
00:44:10,719 --> 00:44:14,399
Speaker 1: referees like that. Christie did a superb job. He got

820
00:44:14,520 --> 00:44:18,239
Speaker 1: lots of really qualified people ready to go into the agencies,

821
00:44:18,640 --> 00:44:21,000
Speaker 1: and had also vetted a lot of the people who

822
00:44:21,160 --> 00:44:24,480
Speaker 1: might have be plausible candidates for the top jobs in

823
00:44:24,480 --> 00:44:27,280
Speaker 1: the government. So they vetted out Mike Flynn, for example.

824
00:44:27,800 --> 00:44:30,360
Speaker 1: And it's all ready to go in spite of Donald

825
00:44:30,400 --> 00:44:33,200
Speaker 1: Trump's actual hostility to the whole operation because they were

826
00:44:33,280 --> 00:44:36,279
Speaker 1: he thought they were spending his money and then and

827
00:44:36,360 --> 00:44:38,520
Speaker 1: that he wasn't gonna win, and he wasn't gonna win, right,

828
00:44:38,560 --> 00:44:41,680
Speaker 1: so why bother right? And Bannon said to Trump, well,

829
00:44:41,719 --> 00:44:43,759
Speaker 1: if you fire the transition, how's that gonna look on

830
00:44:43,800 --> 00:44:45,840
Speaker 1: Morning Joe. It's gonna look like you're given up already.

831
00:44:46,120 --> 00:44:47,720
Speaker 1: And so he said, all right, I just don't spend

832
00:44:47,800 --> 00:44:50,640
Speaker 1: very much money. But ultimately he did fire Chris Christmas,

833
00:44:50,640 --> 00:44:52,840
Speaker 1: So the day after the election they fired him. So

834
00:44:53,200 --> 00:44:56,440
Speaker 1: it was only for show. They built this great operation.

835
00:44:56,840 --> 00:44:59,080
Speaker 1: It turns out only for show that the minute they said, oh,

836
00:44:59,120 --> 00:45:01,400
Speaker 1: we're gonna do this, Trump got rid of him. And

837
00:45:02,000 --> 00:45:06,479
Speaker 1: the natural next question is why, uh and Christie would

838
00:45:06,480 --> 00:45:09,080
Speaker 1: tell you that it's because he put Jared Kushner's father

839
00:45:09,120 --> 00:45:12,880
Speaker 1: in jail back when he was a prosecutor for I

840
00:45:12,880 --> 00:45:16,640
Speaker 1: think that didn't help. Jared clearly wanted Christy gone, but

841
00:45:17,080 --> 00:45:20,120
Speaker 1: you had to have Trump's approval of that. And why

842
00:45:20,320 --> 00:45:23,839
Speaker 1: would Trump? If I were Donald Trump, I would have

843
00:45:23,920 --> 00:45:26,120
Speaker 1: somewhere deep in my soul a sense that I don't

844
00:45:26,160 --> 00:45:28,120
Speaker 1: really know how this thing works, that I'm gonna be

845
00:45:28,120 --> 00:45:30,400
Speaker 1: taking over and it would be nice to have all

846
00:45:30,440 --> 00:45:32,839
Speaker 1: these people who kind of know the thing, and they

847
00:45:32,840 --> 00:45:34,759
Speaker 1: can I don't have to pay attention to it then right,

848
00:45:34,800 --> 00:45:38,200
Speaker 1: and it'll all just kind of run. I think he

849
00:45:38,280 --> 00:45:41,279
Speaker 1: had positive reasons for one in chaos. I think that

850
00:45:41,400 --> 00:45:44,640
Speaker 1: they were friends of his people who were and people

851
00:45:44,680 --> 00:45:47,960
Speaker 1: have connections to Russia, like Mike Flynn, who he wanted

852
00:45:48,000 --> 00:45:51,200
Speaker 1: to be able to put in important positions. I think

853
00:45:51,200 --> 00:45:53,919
Speaker 1: he functions better. I think he thinks he functioned better

854
00:45:54,000 --> 00:45:56,759
Speaker 1: if it's not things are not orderly. So I think

855
00:45:56,800 --> 00:45:59,080
Speaker 1: he was just kind of attracted to, like, let let

856
00:45:59,080 --> 00:46:01,799
Speaker 1: the chips fall or they may. I'll take care of

857
00:46:01,840 --> 00:46:03,880
Speaker 1: all this. I'll decide who's going to be in the

858
00:46:03,920 --> 00:46:08,480
Speaker 1: cabinet mainly by casting them by appearance. And it wasn't

859
00:46:08,520 --> 00:46:12,520
Speaker 1: sufficient that Jared Kushner wanted Christie out. Trump also had

860
00:46:12,560 --> 00:46:14,919
Speaker 1: to say, I'm I want this whole thing gone. You're

861
00:46:14,960 --> 00:46:18,160
Speaker 1: saying that he wanted Mike Flynn in there because of

862
00:46:18,239 --> 00:46:21,640
Speaker 1: his connections with Russia. I can't imagine why else? Like

863
00:46:21,680 --> 00:46:24,839
Speaker 1: why else? Go to that trouble? Christie's operation had said

864
00:46:24,880 --> 00:46:27,440
Speaker 1: Mike Flinch did not be national security advisor. He's got

865
00:46:27,840 --> 00:46:30,319
Speaker 1: shadowy problems you don't want to know about, but just

866
00:46:30,320 --> 00:46:33,839
Speaker 1: don't put him in any important position. The Trump's are

867
00:46:33,880 --> 00:46:37,520
Speaker 1: insistent that Mike Flynn be in, and to the point

868
00:46:37,520 --> 00:46:41,319
Speaker 1: where they want to get rid of the entire transition operation,

869
00:46:41,800 --> 00:46:45,439
Speaker 1: which would prevent it from happening. Why else, I mean,

870
00:46:46,560 --> 00:46:49,239
Speaker 1: it's it's hard to it just it seems I don't

871
00:46:49,280 --> 00:46:51,960
Speaker 1: know this for a fact, but it seems a plausible explanation.

872
00:46:52,040 --> 00:46:55,160
Speaker 1: And to what end, you know? I wonder about this

873
00:46:55,640 --> 00:46:57,799
Speaker 1: that I think that we will find out eventually when

874
00:46:57,800 --> 00:47:01,600
Speaker 1: we untangled Donald Trump's finances and his relationships to the Russians.

875
00:47:02,120 --> 00:47:04,680
Speaker 1: What he's thinking in the back of his lizard brain

876
00:47:05,040 --> 00:47:10,120
Speaker 1: is if this proceeds normally, and the State Department is

877
00:47:10,200 --> 00:47:14,120
Speaker 1: run normally, for example, it could be harder to cloud

878
00:47:14,520 --> 00:47:16,919
Speaker 1: my relations with these people. People are gonna know things,

879
00:47:17,040 --> 00:47:20,760
Speaker 1: find out things people who aren't allies. Um, I want allies.

880
00:47:20,800 --> 00:47:24,719
Speaker 1: I want loyalists around this issue, because loyalists will keep

881
00:47:24,760 --> 00:47:27,439
Speaker 1: the trap shut that if I had to bet, But again,

882
00:47:27,480 --> 00:47:30,120
Speaker 1: I don't know that. But never mind the motive for

883
00:47:30,160 --> 00:47:33,799
Speaker 1: a second. Just the fact of it is astonishing. You know,

884
00:47:34,000 --> 00:47:36,560
Speaker 1: in a normal society that understood the value of its

885
00:47:36,600 --> 00:47:38,840
Speaker 1: government that had been a revolt, we're not going to

886
00:47:38,960 --> 00:47:41,640
Speaker 1: show up for the briefings. It's crazy. I mean three

887
00:47:41,680 --> 00:47:44,080
Speaker 1: months ago when I was finishing, I was still getting

888
00:47:44,120 --> 00:47:48,719
Speaker 1: briefings from very important people in the government that had

889
00:47:48,800 --> 00:47:51,480
Speaker 1: never been given because no one had ever showed up

890
00:47:51,800 --> 00:47:54,760
Speaker 1: to hear it. And it's just a loss of knowledge.

891
00:47:54,760 --> 00:47:57,520
Speaker 1: Who run anything that way? It's just there's no decent

892
00:47:57,640 --> 00:48:00,799
Speaker 1: argument for not learning about the thing you need to run,

893
00:48:01,480 --> 00:48:03,680
Speaker 1: which leads perfectly to the title of the book, the

894
00:48:03,719 --> 00:48:06,080
Speaker 1: fifth risk. Can you go through the first four risks

895
00:48:06,120 --> 00:48:09,040
Speaker 1: and then we'll talk about the fifth one. Well, there's

896
00:48:09,080 --> 00:48:12,320
Speaker 1: something that's not in the book that informed the title.

897
00:48:12,920 --> 00:48:14,880
Speaker 1: When I first started, I was talking to people in

898
00:48:14,880 --> 00:48:20,160
Speaker 1: the White House and they had planned a exercise which

899
00:48:20,200 --> 00:48:23,759
Speaker 1: was going to happen between the outgoing Obama cabinet and

900
00:48:23,760 --> 00:48:27,360
Speaker 1: the incoming Trump cabinet. They would scheme out what happens

901
00:48:27,400 --> 00:48:30,360
Speaker 1: is several terrible things happened. One was a pandemic, another

902
00:48:30,520 --> 00:48:33,040
Speaker 1: was a terrorist attack inside the United States with a

903
00:48:33,120 --> 00:48:36,879
Speaker 1: nuclear weapon. Another was a hurricane that surprised some part

904
00:48:36,880 --> 00:48:40,040
Speaker 1: of the country. The fourth was an earthquake in the

905
00:48:40,040 --> 00:48:42,600
Speaker 1: Pacific Northwest. And I said, what's the fifth and said,

906
00:48:42,600 --> 00:48:45,359
Speaker 1: we hadn't thought about the fifth. And I realized that

907
00:48:45,440 --> 00:48:47,680
Speaker 1: what I was writing about at that moment was the

908
00:48:47,719 --> 00:48:50,520
Speaker 1: stuff that nobody's thinking about because there's so much of

909
00:48:50,520 --> 00:48:52,480
Speaker 1: it within the federal government. It's sort of like the

910
00:48:52,960 --> 00:48:57,000
Speaker 1: risk we're not attending to sufficiently. This then happens again

911
00:48:57,080 --> 00:48:59,680
Speaker 1: when I go into the Energy Department and I'm sitting

912
00:48:59,719 --> 00:49:02,360
Speaker 1: down with a guy who had never given his briefing,

913
00:49:02,640 --> 00:49:05,560
Speaker 1: the chief risk officer, and he worked in the Obama ministry.

914
00:49:05,560 --> 00:49:07,520
Speaker 1: He worked in the Obama administration. He was brought in

915
00:49:07,560 --> 00:49:11,080
Speaker 1: by Ernie Monies, m I T physicist who had run

916
00:49:11,120 --> 00:49:15,640
Speaker 1: the Energy Department. His name is John McWilliams, and John said,

917
00:49:15,960 --> 00:49:17,480
Speaker 1: he said, actually, I came up with a list of

918
00:49:17,560 --> 00:49:20,560
Speaker 1: hundred and forty two basically existential risks. I said, I

919
00:49:20,640 --> 00:49:23,080
Speaker 1: don't have time pretend I'm like a Trump guy who's bored.

920
00:49:23,080 --> 00:49:25,920
Speaker 1: Give me five. And he says, I think in no

921
00:49:26,000 --> 00:49:29,440
Speaker 1: particular order, but he says one, Uh, that a nuclear

922
00:49:29,440 --> 00:49:31,640
Speaker 1: weapon will go off when it's not supposed to think.

923
00:49:31,680 --> 00:49:34,839
Speaker 1: He said then the Iran, that the Iran deal would

924
00:49:34,880 --> 00:49:38,360
Speaker 1: come unraveled, that the next administration would not appreciate how

925
00:49:38,400 --> 00:49:40,680
Speaker 1: important it was and how good a deal it was,

926
00:49:40,800 --> 00:49:43,040
Speaker 1: because they wouldn't bother to listen to the physicists who

927
00:49:43,080 --> 00:49:45,960
Speaker 1: would explain to them that now Iran cannot build a

928
00:49:46,040 --> 00:49:50,160
Speaker 1: nuclear bomb. And that's exactly what happened. Uh. North Korea

929
00:49:50,440 --> 00:49:53,399
Speaker 1: was I think the third. The failure of the nation

930
00:49:53,480 --> 00:49:55,920
Speaker 1: is in the electrical grid, which is a monitor. And

931
00:49:55,960 --> 00:49:57,640
Speaker 1: you think, oh, well, that's just the lights go out,

932
00:49:58,000 --> 00:50:00,560
Speaker 1: that's a disaster. People die, And then we get the

933
00:50:00,560 --> 00:50:02,880
Speaker 1: fifth and actually he said, let me think a little bit,

934
00:50:02,920 --> 00:50:04,520
Speaker 1: and I thought, well, we have a pattern. When we

935
00:50:04,560 --> 00:50:06,000
Speaker 1: get to five, we've got to think a little bit.

936
00:50:06,160 --> 00:50:10,080
Speaker 1: And then he finally said, very kind of innocuously program management.

937
00:50:10,520 --> 00:50:12,920
Speaker 1: And when he meant by that, which sounds incredibly tedious,

938
00:50:13,040 --> 00:50:15,160
Speaker 1: and in some ways it is incredibly tedious, but what

939
00:50:15,280 --> 00:50:18,920
Speaker 1: he means by that is that the government is managing

940
00:50:19,160 --> 00:50:24,400
Speaker 1: really dangerous situations that are very long term situations. And

941
00:50:24,440 --> 00:50:27,759
Speaker 1: the example I plucked out of the Department Energy to

942
00:50:27,880 --> 00:50:31,080
Speaker 1: use to illustrate the point in the book was, Uh,

943
00:50:31,120 --> 00:50:34,440
Speaker 1: the nuclear waste clean up in hand for Washington. Eastern

944
00:50:34,480 --> 00:50:38,920
Speaker 1: Washington is where the plutonium was created for the Adam

945
00:50:38,960 --> 00:50:42,839
Speaker 1: bombs that were dropped on Japan. In the course of

946
00:50:42,840 --> 00:50:45,040
Speaker 1: creating it, they were in such a rush they didn't

947
00:50:45,040 --> 00:50:47,960
Speaker 1: pay attention what they were doing. The waste materials hundreds

948
00:50:47,960 --> 00:50:51,040
Speaker 1: of millions of gallons filled with with stuff you don't

949
00:50:51,040 --> 00:50:55,960
Speaker 1: want to touch. Uh. Beer anywhere near I mean anybody.

950
00:50:56,080 --> 00:50:57,479
Speaker 1: A lot of people who have worked at this side

951
00:50:57,480 --> 00:51:00,440
Speaker 1: of die of cancer. Uh. But just poured into the

952
00:51:00,560 --> 00:51:04,799
Speaker 1: into the soil, and there's this plume of it moving

953
00:51:04,840 --> 00:51:07,359
Speaker 1: through the earth to the wards the Columbia River and

954
00:51:07,360 --> 00:51:10,120
Speaker 1: it's being managed by the Department of Energy. They're spending

955
00:51:10,160 --> 00:51:13,640
Speaker 1: three billion dollars a year to clean this up. If

956
00:51:13,680 --> 00:51:17,080
Speaker 1: we just don't do that right and the stuff gets

957
00:51:17,120 --> 00:51:20,600
Speaker 1: to the Columbia River, it's catastrophic for the Pacific Northwest.

958
00:51:21,080 --> 00:51:25,839
Speaker 1: He said that was just one example. That's professional technical management.

959
00:51:25,960 --> 00:51:28,760
Speaker 1: That's got to be there. People who know about things,

960
00:51:29,120 --> 00:51:31,080
Speaker 1: and that's what the Trump people didn't bring in. They

961
00:51:31,080 --> 00:51:33,920
Speaker 1: didn't bring anybody who knew about anything. It sounds like

962
00:51:34,000 --> 00:51:37,120
Speaker 1: you really outline a lot of disasters waiting to happen,

963
00:51:37,120 --> 00:51:40,080
Speaker 1: and not just at the Department of Energy, but in

964
00:51:40,200 --> 00:51:44,879
Speaker 1: other very frankly unsexy agencies like the Department of Agriculture

965
00:51:44,880 --> 00:51:47,759
Speaker 1: and the Department of Commerce. The whole point was to

966
00:51:47,800 --> 00:51:50,120
Speaker 1: take things that nobody's paying attention to, which is kind

967
00:51:50,120 --> 00:51:52,800
Speaker 1: of your area of expertise. I feel like you always

968
00:51:52,800 --> 00:51:55,879
Speaker 1: take these sort of arcane, dry subjects and you kind

969
00:51:55,880 --> 00:51:58,359
Speaker 1: of make them fun and entertaining. You have to hear

970
00:51:58,400 --> 00:52:00,239
Speaker 1: three or four times that you should read the book

971
00:52:00,239 --> 00:52:02,360
Speaker 1: before you actually think I better read the book, because

972
00:52:02,360 --> 00:52:03,799
Speaker 1: it really do I want to read a book about

973
00:52:03,840 --> 00:52:07,000
Speaker 1: the Department Agriculture, but talk about the Department of agriculture

974
00:52:07,040 --> 00:52:10,280
Speaker 1: and Commerce, and I think a lot of listeners Michael

975
00:52:10,320 --> 00:52:13,319
Speaker 1: will be surprised to hear what they have per view

976
00:52:13,560 --> 00:52:17,840
Speaker 1: over and how important they are. They're all misnamed, these departments.

977
00:52:18,160 --> 00:52:21,919
Speaker 1: I mean, we've gotten so detached from our government. That's

978
00:52:21,920 --> 00:52:24,279
Speaker 1: so the reason I picked the ones I picked was

979
00:52:24,400 --> 00:52:27,719
Speaker 1: I just wanted to dramatize how little we all know

980
00:52:27,920 --> 00:52:31,680
Speaker 1: about what our government does. But the Department Agriculture, it

981
00:52:31,760 --> 00:52:37,239
Speaker 1: does subsidize farming. It was created by Lincoln during the

982
00:52:37,280 --> 00:52:41,480
Speaker 1: middle of the Civil War UH with the explicit mission

983
00:52:42,120 --> 00:52:46,719
Speaker 1: to turn agriculture into a science so farming could be

984
00:52:46,800 --> 00:52:49,920
Speaker 1: very more efficient, so we need fewer farmers, so those

985
00:52:49,960 --> 00:52:52,000
Speaker 1: people could go then go do other things, and the

986
00:52:52,040 --> 00:52:57,720
Speaker 1: economy would grow. The enterprise has been spectacularly successful. Farmers

987
00:52:57,800 --> 00:52:59,279
Speaker 1: used to feed a few people, and now they feed

988
00:52:59,440 --> 00:53:01,680
Speaker 1: each heeds a few hundred people who we need many

989
00:53:01,719 --> 00:53:06,120
Speaker 1: fewer farmers. It is now expanded into a science project

990
00:53:06,239 --> 00:53:09,880
Speaker 1: that UH that just distributes about three billion dollars a

991
00:53:09,960 --> 00:53:13,480
Speaker 1: year in grants to researchers, almost all of them one

992
00:53:13,520 --> 00:53:17,240
Speaker 1: way or another related to how we secure the food

993
00:53:17,239 --> 00:53:20,440
Speaker 1: supply UH in the face of climate change, UM and

994
00:53:20,520 --> 00:53:24,440
Speaker 1: food safety by the way, I just want to interject food. Yeah,

995
00:53:24,680 --> 00:53:27,200
Speaker 1: you know, how do we make sure that our chicken

996
00:53:27,320 --> 00:53:30,879
Speaker 1: doesn't poison us? Among other things, the Department of Agriculture

997
00:53:31,440 --> 00:53:35,359
Speaker 1: inspects the nine billion birds a year that are killed

998
00:53:35,360 --> 00:53:37,640
Speaker 1: in America so we can eat them, not to mention

999
00:53:37,760 --> 00:53:41,440
Speaker 1: cows and all kinds of others, all kinds of other things. Now,

1000
00:53:41,480 --> 00:53:44,960
Speaker 1: if you're hiring someone to pass out three billion dollars

1001
00:53:45,000 --> 00:53:46,680
Speaker 1: a year in grants, too, you would want to probably

1002
00:53:46,680 --> 00:53:49,160
Speaker 1: want to hire someone who knew about agricultural research. And

1003
00:53:49,160 --> 00:53:51,479
Speaker 1: that's usually who occupies the job of scientists, someone who's

1004
00:53:51,520 --> 00:53:54,160
Speaker 1: done their own research, is respected in the field. Uh.

1005
00:53:54,200 --> 00:53:56,600
Speaker 1: And that's who was there when Trump came in and

1006
00:53:56,640 --> 00:54:01,120
Speaker 1: Trump nominated to replace her, uh, a right wing talk

1007
00:54:01,160 --> 00:54:03,839
Speaker 1: show radio host from Iowa who supported him, who has

1008
00:54:03,840 --> 00:54:08,240
Speaker 1: no science background whatsoever. I mean, just this kind of stuff.

1009
00:54:08,560 --> 00:54:11,320
Speaker 1: It's like like I don't know about agricultural science, but

1010
00:54:11,360 --> 00:54:13,880
Speaker 1: I stayed it in a holiday in express. It is

1011
00:54:14,000 --> 00:54:17,480
Speaker 1: like happened across the government. Uh So that's three billion

1012
00:54:17,480 --> 00:54:20,040
Speaker 1: dollars a year. I think the Agriculture Department budget is

1013
00:54:20,080 --> 00:54:23,120
Speaker 1: close to two hundred billion, and much of that if

1014
00:54:23,120 --> 00:54:26,480
Speaker 1: you follow just the money, it's feeding people. It's feeding

1015
00:54:26,800 --> 00:54:29,440
Speaker 1: poor kids, it's feeding old people. It's food stamps, and

1016
00:54:29,440 --> 00:54:31,920
Speaker 1: it's school nutrition programs. That's where the bulk of the

1017
00:54:32,000 --> 00:54:35,000
Speaker 1: money goes. And those programs, when you actually dig into

1018
00:54:35,000 --> 00:54:37,279
Speaker 1: them and talk to the people who administer them, the

1019
00:54:37,280 --> 00:54:39,319
Speaker 1: Trump people would love to cut them. But you're what

1020
00:54:39,400 --> 00:54:41,919
Speaker 1: you're doing is you're you're leaving kids hungry and old

1021
00:54:42,000 --> 00:54:45,680
Speaker 1: people hungry. I describe how ignorance is actually a tool

1022
00:54:45,719 --> 00:54:48,400
Speaker 1: for Trump that if you do remain ignorant of the

1023
00:54:48,760 --> 00:54:50,959
Speaker 1: of the thing, you can you can do all sorts

1024
00:54:51,000 --> 00:54:55,120
Speaker 1: of brutal stuff and positiblemility you can put if as

1025
00:54:55,160 --> 00:54:57,240
Speaker 1: long as you don't meet a kid who's going hungry

1026
00:54:57,400 --> 00:55:00,320
Speaker 1: and as a result can't concentrate at school as a result,

1027
00:55:00,360 --> 00:55:02,640
Speaker 1: one thing leads to another and the life ends and tragedy.

1028
00:55:03,400 --> 00:55:05,000
Speaker 1: You can say, oh yea Alice has cut the school

1029
00:55:05,080 --> 00:55:08,040
Speaker 1: lunch program. In fact, when you get into it, you

1030
00:55:08,080 --> 00:55:12,839
Speaker 1: find these dedicated public servants who really understand the programs

1031
00:55:13,000 --> 00:55:16,680
Speaker 1: and understand that, like the problem with the programs isn't fraud,

1032
00:55:16,880 --> 00:55:19,239
Speaker 1: which is what some people have you believe, they're very

1033
00:55:19,239 --> 00:55:22,160
Speaker 1: little fraud and and they work very hard to eliminate it.

1034
00:55:22,360 --> 00:55:25,480
Speaker 1: The problem is if they're not as heavily used as

1035
00:55:25,480 --> 00:55:27,880
Speaker 1: they should be, that the people who need them don't

1036
00:55:28,360 --> 00:55:31,120
Speaker 1: have too much trouble getting access to them, and the

1037
00:55:31,120 --> 00:55:34,319
Speaker 1: people who really care about them solve those problems so

1038
00:55:34,360 --> 00:55:37,239
Speaker 1: on a state by state basis, When you don't we

1039
00:55:37,280 --> 00:55:39,120
Speaker 1: don't acknowledge any of that. When you say, oh, just

1040
00:55:39,120 --> 00:55:41,239
Speaker 1: get rid of the government is too big, what you're

1041
00:55:41,280 --> 00:55:44,840
Speaker 1: doing is just ignoring the problem altogether. And when you

1042
00:55:44,880 --> 00:55:49,480
Speaker 1: say that government workers are these incompetent bureaucrats who don't

1043
00:55:49,520 --> 00:55:52,520
Speaker 1: know what they're doing, you sort of support the idea

1044
00:55:52,600 --> 00:55:54,960
Speaker 1: of just cutting off all these programs, no matter how

1045
00:55:55,000 --> 00:55:57,680
Speaker 1: valuable they are. I think that's absolutely right. And what

1046
00:55:57,840 --> 00:56:02,520
Speaker 1: I found in talking to these people, bureaucrats, civil servants,

1047
00:56:02,680 --> 00:56:09,320
Speaker 1: public servants, was that they were, as a rule, extraordinarily dedicated,

1048
00:56:09,360 --> 00:56:14,239
Speaker 1: hard working, mission driven people operating in a hugely dysfunctional system.

1049
00:56:14,320 --> 00:56:18,280
Speaker 1: And the fact that system is dysfunctional is our fault,

1050
00:56:18,440 --> 00:56:22,040
Speaker 1: not theirs. It's because we've resisted any kind of decent

1051
00:56:22,080 --> 00:56:25,400
Speaker 1: reforms of government. If you want to make the argument

1052
00:56:25,800 --> 00:56:29,480
Speaker 1: that our society is disintegrating and in decay, you might

1053
00:56:29,640 --> 00:56:32,120
Speaker 1: start by looking at what we've done with the government

1054
00:56:32,239 --> 00:56:35,200
Speaker 1: five times as many people in the federal workforce over

1055
00:56:35,239 --> 00:56:37,640
Speaker 1: the age of sixty then under the age of thirty,

1056
00:56:38,040 --> 00:56:41,440
Speaker 1: ninety billion dollars spent on i T in the federal government.

1057
00:56:41,719 --> 00:56:45,440
Speaker 1: Seventy billion is spent just on these ancients just maintaining

1058
00:56:45,480 --> 00:56:48,719
Speaker 1: these ancient, decrepit systems from the sixties. It's it's a

1059
00:56:48,760 --> 00:56:52,799
Speaker 1: system that's almost built at this point to fail. And

1060
00:56:52,880 --> 00:56:55,440
Speaker 1: in spite of that, people want to come in and

1061
00:56:55,480 --> 00:56:58,560
Speaker 1: do stuff and sometimes do. Did President Obama when he

1062
00:56:58,640 --> 00:57:01,759
Speaker 1: was in charge, do anything to try to fix these

1063
00:57:01,760 --> 00:57:05,959
Speaker 1: problems you've identified? Not enough. The Bush administration had been

1064
00:57:06,800 --> 00:57:09,880
Speaker 1: beginning to engage with how you reform the government, and

1065
00:57:09,920 --> 00:57:13,320
Speaker 1: the Obama administration has kind of started over. The world's

1066
00:57:13,320 --> 00:57:15,960
Speaker 1: authority on this is Max Styre, who runs something called

1067
00:57:15,960 --> 00:57:19,800
Speaker 1: a Partnership for Public Service, which is this extraordinary nonprofit

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00:57:20,080 --> 00:57:22,800
Speaker 1: started by one guy who basically said, I'm going to

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00:57:22,880 --> 00:57:25,439
Speaker 1: try to fix the government. I'm gonna start by trying

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00:57:25,440 --> 00:57:28,560
Speaker 1: to get young, talented people into the government. The only

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00:57:28,600 --> 00:57:30,280
Speaker 1: way I can do that is if I fixed this thing.

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00:57:30,560 --> 00:57:33,160
Speaker 1: He's managed to get the laws passed that require people

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00:57:33,160 --> 00:57:35,400
Speaker 1: to prepare for the transition, and he's got a lot

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00:57:35,400 --> 00:57:38,520
Speaker 1: of ideas about ways you might reform the place so

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00:57:38,640 --> 00:57:44,280
Speaker 1: it is more agile, responsible, responsive, and and just works better. Uh.

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00:57:44,280 --> 00:57:47,320
Speaker 1: And he would tell you that Obama was disappointing to

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00:57:47,400 --> 00:57:50,240
Speaker 1: him this way, but nothing like Trump, I mean really

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00:57:50,280 --> 00:57:52,280
Speaker 1: responsible and the kind of people he put into the

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00:57:52,320 --> 00:57:55,640
Speaker 1: government for example, that that he said, you never seen

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00:57:55,680 --> 00:57:59,160
Speaker 1: anything like Trump. We're two years into the Trump administration.

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00:57:59,600 --> 00:58:02,840
Speaker 1: Do you see it getting any better? At if the

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00:58:02,880 --> 00:58:07,520
Speaker 1: Democrats Michael take the House, will they have any control

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00:58:07,720 --> 00:58:12,880
Speaker 1: over the current state of disarray? So the answer is no,

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00:58:13,040 --> 00:58:16,280
Speaker 1: and no. Trump is symptom, not just cause here we

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00:58:16,360 --> 00:58:21,440
Speaker 1: don't elect someone who is so ignorant and negligent unless

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00:58:21,480 --> 00:58:25,280
Speaker 1: we have got to the point where were so misvalue

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00:58:25,360 --> 00:58:28,600
Speaker 1: and misunderstand the thing he's running. If the society understood

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00:58:28,600 --> 00:58:30,560
Speaker 1: the government, we all had a good civics lesson, we'd

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00:58:30,600 --> 00:58:32,960
Speaker 1: all say that person shouldn't be running that because that's

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00:58:32,960 --> 00:58:35,080
Speaker 1: going to be a catastrophe, because that that enterprise the

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00:58:35,120 --> 00:58:38,640
Speaker 1: government is really important. The narrative needs to change first.

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00:58:38,880 --> 00:58:40,240
Speaker 1: I mean, that's why I wrote the book. I mean,

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00:58:40,280 --> 00:58:42,520
Speaker 1: if they just try to start to change the narrative

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00:58:42,600 --> 00:58:45,960
Speaker 1: so people stop seeing the government as the problem and

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00:58:46,000 --> 00:58:49,840
Speaker 1: start seeing it as a tool as a solution. But

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00:58:50,400 --> 00:58:53,080
Speaker 1: you know, it's if this society is gonna survive, that's

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00:58:53,080 --> 00:58:55,000
Speaker 1: got to happen. So it's a big deal. I think

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00:58:55,040 --> 00:58:58,640
Speaker 1: it actually could happen. But you can change narratives. You

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00:58:58,640 --> 00:59:01,320
Speaker 1: know this, You've told stories. But yeah, we have to

1100
00:59:01,320 --> 00:59:05,880
Speaker 1: stop undermining this institution and starts trying to be constructive

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00:59:05,880 --> 00:59:08,560
Speaker 1: about it and understanding it. And meanwhile, if the Democrats

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00:59:08,600 --> 00:59:10,640
Speaker 1: take the House, they don't really have any power to

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00:59:10,680 --> 00:59:14,200
Speaker 1: do this, do they. If Trump is removed, that would help,

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00:59:14,720 --> 00:59:18,919
Speaker 1: but uh, it wouldn't solve the core problems. What's really

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00:59:18,960 --> 00:59:21,880
Speaker 1: needed is a political leader, probably will come out of

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00:59:21,880 --> 00:59:23,680
Speaker 1: the Democratic Party, but could easily come out of the

1107
00:59:23,720 --> 00:59:27,160
Speaker 1: Republican Party who can make the positive case for government,

1108
00:59:27,480 --> 00:59:30,160
Speaker 1: which is with caveats, which we need to change this thing.

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00:59:30,440 --> 00:59:33,880
Speaker 1: We have a nineteen forties automobile on a twenty one

1110
00:59:33,960 --> 00:59:38,320
Speaker 1: century highway. Someone who can sell that case. I think

1111
00:59:38,360 --> 00:59:40,040
Speaker 1: you can get elected selling that case. They just have

1112
00:59:40,080 --> 00:59:42,760
Speaker 1: to be good at it. And this is something that Obama.

1113
00:59:42,840 --> 00:59:45,640
Speaker 1: President Obama may try to sell because he's optioned the

1114
00:59:45,680 --> 00:59:49,800
Speaker 1: book to come up with the series for Netflix to

1115
00:59:49,920 --> 00:59:52,960
Speaker 1: help people better understand the government. Yes, it's just as

1116
00:59:52,880 --> 00:59:56,280
Speaker 1: a civics lesson, that's right. And I did three departments

1117
00:59:56,400 --> 00:59:58,880
Speaker 1: because it would be the work of many lifetimes to

1118
00:59:58,920 --> 01:00:01,560
Speaker 1: do the whole government. But you could do this in

1119
01:00:01,600 --> 01:00:05,640
Speaker 1: a fun way across the entire government. Well, Michael Lewis.

1120
01:00:05,680 --> 01:00:08,160
Speaker 1: The book is called The Fifth Risk. Thank you so

1121
01:00:08,280 --> 01:00:10,560
Speaker 1: much for coming into and talking to us about It's

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01:00:10,560 --> 01:00:16,680
Speaker 1: always great to see you. Thanks for having me. So

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01:00:16,720 --> 01:00:19,240
Speaker 1: that's all for today, and a reminder one more time,

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01:00:19,320 --> 01:00:23,320
Speaker 1: please vote on Tuesday, November six in the midterm elections.

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01:00:23,440 --> 01:00:26,439
Speaker 1: It is really important and on next week's show we'll

1126
01:00:26,480 --> 01:00:29,520
Speaker 1: be taking your calls and making sense of all the

1127
01:00:29,560 --> 01:00:33,200
Speaker 1: election results, or at least trying to. Emma Morgan Stern

1128
01:00:33,280 --> 01:00:36,680
Speaker 1: is our producer, Nora Richie is the associate producer, and

1129
01:00:36,760 --> 01:00:40,120
Speaker 1: Jared O'Connell is our audio engineer who makes every show

1130
01:00:40,560 --> 01:00:44,320
Speaker 1: sound like a dream. Ryan Connor is our audio engineer

1131
01:00:44,400 --> 01:00:46,640
Speaker 1: here in l A. I'd also like to shout from

1132
01:00:46,640 --> 01:00:50,240
Speaker 1: the rooftops about my team at Katie Kirk Media, my

1133
01:00:50,320 --> 01:00:54,160
Speaker 1: assistant Beth Dems and Julia Lewis my social media mix

1134
01:00:55,280 --> 01:00:58,120
Speaker 1: and a saucy one at that. Jared Arnold wrote our

1135
01:00:58,160 --> 01:01:00,560
Speaker 1: new theme music you can find me on Twitter I'm

1136
01:01:00,560 --> 01:01:03,800
Speaker 1: at Goldsmith b and you can follow Katie on Twitter, Facebook,

1137
01:01:03,800 --> 01:01:09,080
Speaker 1: at especially Instagram under Katie Kurk. Those Instagram stories are

1138
01:01:09,200 --> 01:01:12,840
Speaker 1: really something to follow. I notice you do, Brian, because

1139
01:01:12,840 --> 01:01:14,919
Speaker 1: I see your name all the time, so don't mock

1140
01:01:15,040 --> 01:01:18,440
Speaker 1: me too much. One more reminder. If you want to

1141
01:01:18,480 --> 01:01:20,680
Speaker 1: call in to ask us a question or share your

1142
01:01:20,720 --> 01:01:23,440
Speaker 1: thoughts about the mid terms, you can reach us at

1143
01:01:24,720 --> 01:01:27,520
Speaker 1: four four six three seven. Just leave a voicemail with

1144
01:01:27,560 --> 01:01:29,720
Speaker 1: your name, where you're calling from, and what you'd like

1145
01:01:29,800 --> 01:01:32,440
Speaker 1: to tell us, or leave us a message about something

1146
01:01:32,560 --> 01:01:35,040
Speaker 1: other than the mid terms, or you can always email

1147
01:01:35,200 --> 01:01:39,360
Speaker 1: us at comments at current podcast dot com. Thank you,

1148
01:01:39,480 --> 01:01:43,360
Speaker 1: as always for listening. We really appreciate your support and

1149
01:01:43,440 --> 01:01:45,240
Speaker 1: we'll talk to you next week.