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Speaker 1: Welcome to Worst Year Ever, a production of I Heart Radio.

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Speaker 1: Welcome Together Everything, So don't don't don hey, and welcome

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Speaker 1: back to Worst Year Ever. My name is Katie Stole.

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Speaker 1: Obviously mine's not, but it is Cody Johnston. And I

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Speaker 1: also am a person who has been named legally in

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Speaker 1: birth certificates and similar documents. And what was that name

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Speaker 1: that are on your birth certificate and similar documents. That's

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Speaker 1: a great question, Katie. Should we start the show absolutely?

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Speaker 1: Robert um uh this week, guys, I think we're all

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Speaker 1: pretty pumped to be talking about Kamala Harris is pumped

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Speaker 1: the right word. Yeah, thrilled, um, ecstatic, I'm just over

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Speaker 1: the moon. Yeah, as the British would say, I'm jim

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Speaker 1: Chim Cheru about it. I'm really chuffed about it, chuffed

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Speaker 1: that used to use chuff, right, Walgard about it. Yeah,

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Speaker 1: I'm I'm pufful the tough old about it. I'm stunned

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Speaker 1: by our linguistic skills. Yeah, I know the world. Yeah,

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Speaker 1: you're right Walgard about it in it. I know if

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Speaker 1: you're aware of this, Katie, but we are the world.

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Speaker 1: We know all of it's all of its slang. Yeah.

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Speaker 1: So this was originally just going to be my episode,

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Speaker 1: but it's a big one, so we kind of divat

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Speaker 1: it up. But I'm gonna get it started right. We're

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Speaker 1: we're kind of revising this as we go along and

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Speaker 1: how we we do this show, and I think we

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Speaker 1: might we might wind up doing future episodes like this

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Speaker 1: where we all take chunks of a candidate's history. Who knows,

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Speaker 1: we're learning how to do our jobs in real time

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Speaker 1: and let us know what you guys think, much like

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Speaker 1: a bridge builder. Yeah, you know, just if if this

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Speaker 1: is a more interesting way to present the information, or

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Speaker 1: if you just want one person monologuing for an hour.

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Speaker 1: You know, we're people for the people, so learning together.

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Speaker 1: We value your feedback. Um, but let's just let's just

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Speaker 1: dig in on Kamala, all right, Harris Harris, because there's

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Speaker 1: a lot to get through. Kamala was born in Oakland, California,

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Speaker 1: six four. I just want to real quick, make controversial statement.

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Speaker 1: I am pro candidates who have been born Okay, putting

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Speaker 1: that out there, bold take. Why don't you put a

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Speaker 1: pin that. Listen to the rest of the episode and

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Speaker 1: see if you still have that. Okay, so far, I'm

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Speaker 1: I'm I'm pro pro birth Okay Great born in Oakland, California.

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Speaker 1: Her mother is Shiamola Goppolin, who immigrated from Indian nineteen sixty.

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Speaker 1: She got her doctor and into chronology at UC Berkeley

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Speaker 1: and conducted breast cancer research. Her father, Donald Harris, immigrated

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Speaker 1: from Jamaica to go to grad school at UC Berkeley.

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Speaker 1: He's now an econ professor at Stanford. Her younger sister,

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Speaker 1: Maya Harris, is a political analyst for MSNBC, worked on

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Speaker 1: Hillary Clinton's campaign, and is now campaign chairwoman for Kamala. Uh.

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Speaker 1: This is quite the impressive family. Uh. Kamala attended Howard University.

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Speaker 1: That's interesting because I was under the impression that people

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Speaker 1: usually picked to run their campaign members of the weird

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Speaker 1: beach cult that they grew up in. Is that not

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Speaker 1: the standard? Apparently it's not the standard. After Artoli episode,

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Speaker 1: I also thought that but no family members close family

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Speaker 1: members who have also worked for Hillary Clinton? Is maybe

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Speaker 1: more learning a lot Anyway. She attended Howard University, studied

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Speaker 1: economics and political science, was on the debate team. She

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Speaker 1: also was I guess is a member of Alpha Kappa Alpha,

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Speaker 1: which is the nation's oldest black sorority and actually an

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Speaker 1: incredibly powerful, influential group of women, a lot of very

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Speaker 1: cool people in at Groom community. While at Howard, Harris

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Speaker 1: decided that she wanted to become a prosecutor. Uh. And

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Speaker 1: this was confusing for a lot of people, especially her parents,

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Speaker 1: you know, being an African American woman from Oakland. Uh,

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Speaker 1: it didn't seem like the logical step for her. But

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Speaker 1: this is a quote from The Atlantic, which is actually

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Speaker 1: quoting Harris's book, Uh Yet growing up a protests, Harris writes,

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Speaker 1: she'd seen the mechanics of fighting for justice from the outside.

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Speaker 1: That dynamic did not appeal to her. She wanted insider power,

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Speaker 1: establishment power. When activists came marching and banging on doors,

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Speaker 1: Harris writes, I wanted to be on the other side

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Speaker 1: to let them in. Okay, Okay, she wanted them And

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Speaker 1: that's a really I think that's a really Like I'm

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Speaker 1: in contact with a lot of activists just as a

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Speaker 1: part of my job, because I cover protests and activism

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Speaker 1: a shipload and a number of people who have been

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Speaker 1: like talking with over the years and over like you know,

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Speaker 1: successive sort of things they've been involved with, have started,

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Speaker 1: you know, expressing that exact same interest, where like, I'm

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Speaker 1: tired of feeling like I'm just shouting at a wall,

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Speaker 1: and maybe if I get into office, I can do

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Speaker 1: something like I do think that is like a pretty

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Speaker 1: common sentiment to be absolutely I get that, if only

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Speaker 1: we could be bricks in that wall, just another brick

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Speaker 1: in the wall, you know, Cody, I think you're onto

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Speaker 1: something here. You should cut a fucking album based around

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Speaker 1: that sentiment. I would love to. That would be amazing.

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Speaker 1: The edifice, yeah, the blockage, the obstacle, the tall, thin obstacle,

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Speaker 1: between the obstacle between inside and outside. That's good, right,

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Speaker 1: pretty good. I think I think this album could be

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Speaker 1: hugely successful and also wildly misinterpreted by generation listeners. That's

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Speaker 1: the best kind of art, all right. She got her

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Speaker 1: j d from the University of California at Hastings College

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Speaker 1: of Law UH and she then became an Assistant d

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Speaker 1: A for Alameda County UH and she specialized in prosecuting

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Speaker 1: child sex abuse cases. Harris UH in that position saw

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Speaker 1: how much power prosecutors have, and apparently sometimes she kind

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Speaker 1: of relished it. Quote. When I was prosecuting child molestations cases,

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Speaker 1: I will tell you I was as close to a

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Speaker 1: vigilante as you can get. It was also during this

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Speaker 1: time that she began a relationship with an attorney, California

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Speaker 1: Assembly speaker and future mayor, Willie Brown. At this time,

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Speaker 1: Brown was sixty and Kamala was thirty. Brown was married

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Speaker 1: but had been separated for a long time. Um, and

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Speaker 1: they were together for a few years. From everything I've read,

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Speaker 1: her relationship with Brown elevated her profile and standing in

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Speaker 1: San Francisco social circles, which would end up being helpful

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Speaker 1: for her as she entered into politics. UM, that's that

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Speaker 1: seems fine to me, to be honest, Like, people can

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Speaker 1: say what they want, Like, thirty years is a huge

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Speaker 1: age gap, but if you're thirty, you know what you're doing,

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Speaker 1: you know what you're Yeah, it's not the problem. I

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Speaker 1: mean it's a big age gap, but you know she's

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Speaker 1: an adult woman. Um, this is the next This next

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Speaker 1: part is what people take issue with, which is that

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Speaker 1: Brown appointed her to to patronage positions the Unemployment Insurance

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Speaker 1: and the California Medical Assistance Commission, which earned her over

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Speaker 1: four hundred thousand dollars over five years. Willie Brown became

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Speaker 1: mayor of San Francisco and Kamala broke up with him

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Speaker 1: shortly after his inauguration UM, but she has received a

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Speaker 1: significant amount of criticism for relationship with Willie Brown over

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Speaker 1: the years. Tommy Lauren even accused her of sleeping her

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Speaker 1: way to the top. There's one thing we know about

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Speaker 1: Tommy Lauren, It's that she is of moral consistency. That's

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Speaker 1: very funny coming from u UM. And you know, look,

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Speaker 1: sure it's not great that he gave his girlfriend very

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Speaker 1: lucrative jobs. I'll admit that he certainly gave her a

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Speaker 1: boost both professionally and socially again in the Unity, avating

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Speaker 1: her status. But ultimately that criticism from our perspective now

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Speaker 1: isn't quite fair and it's also a bit sixist, you know,

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Speaker 1: it's something that you wouldn't necessarily say about a man.

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Speaker 1: Commal is clearly a driven woman and a politician, and

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Speaker 1: Willie Brown can't take credit for where she is right now,

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Speaker 1: but he certainly helped her, you know, get her career started. Now,

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Speaker 1: let's talk about her as a d A. Uh In

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Speaker 1: Kamala became the assistant d A to Terence Hallinan, who

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Speaker 1: is known as one of the most progressive, if not

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Speaker 1: the most progressive days at the time. Uh. This is

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Speaker 1: from The Atlantic about Helenan, a legendary civil rights activists,

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Speaker 1: defense attorney, former city supervisor, and an outspoken advocate for

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Speaker 1: marijuana legislation. He swiftly fired senior prosecutors in order to

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Speaker 1: hire more minorities and reformists. He instructed his deputies to

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Speaker 1: avoid the practice of objecting to a proposed juror for

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Speaker 1: criminal trial, an unusual stance that weakened the hand of

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Speaker 1: the d a's office to avoid and paneling all white juries.

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Speaker 1: So he's kind of a cool guy, right, sounds pretty cool.

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Speaker 1: I'm I'm pro that pro that. I'll talk a bit

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Speaker 1: more about him in a second. But Harris and Helena

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Speaker 1: had a bit of a contentious time while she worked

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Speaker 1: under him. Uh. There was this proposition Prop. Twenty one

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Speaker 1: that would allow prosecutors to try juvenile defendants in superior

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Speaker 1: court rather than juvenile court, and both Helenan and Kamala

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Speaker 1: opposed it. Um and Kamala actively campaigned against the measure. However,

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Speaker 1: she got a lot of interviews and attention as opposed

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Speaker 1: to him. Uh. And that's something that the District attorney's

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Speaker 1: public information officer allowed to happen, and that didn't sit

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Speaker 1: well with Terrence, who accused Harris and the public Information

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Speaker 1: officer of conspiring to make Harris into a star so

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Speaker 1: she could run against him in the two thousand three election.

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Speaker 1: Harris claimed that she wasn't going to run against him

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Speaker 1: because that would be unprofessional. But then there was all

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Speaker 1: this drama. He demoted Harris, uh and like set up

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Speaker 1: a canary trap to see if she would link information.

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Speaker 1: She didn't. But ultimately, what is it? What a So?

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Speaker 1: What is a What is a canary trip? Because the

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Speaker 1: only one I'm familiar with is when you put one

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Speaker 1: in a mind to see if it dies. I think

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Speaker 1: it was that poison. No, I don't know exactly what

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Speaker 1: it was. It was it was referenced in this article.

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Speaker 1: You know, it's like a little a trap for her

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Speaker 1: to set into, like something to see if she would

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Speaker 1: leak information something that's not necessarily true. Probably like I

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Speaker 1: know who did that because it's the only person I Okay, Okay,

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Speaker 1: so that makes sense. I don't understand calling it a

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Speaker 1: canary trap. Okay. Anyway, she didn't leak it, but she

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Speaker 1: did end up running against him in two thousand three.

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Speaker 1: Maybe it was because she was angry at their situation,

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Speaker 1: or maybe she'd always planned to run um. But let's

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Speaker 1: talk about that a bit. At the time, the early

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Speaker 1: two thousand's, we'd just come through this whole tough on

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Speaker 1: crime period of the nineties, well in the eighties, and

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Speaker 1: a lot of people in San Francisco didn't trust helen

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Speaker 1: An's progressive policies, and that is exactly what Harris ran on.

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Speaker 1: She literally used the line quote it's not progressive to

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Speaker 1: be soft on crime for her campaign quote. She carefully

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Speaker 1: cultivated a base of support among police officers, domestic violence advocates,

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Speaker 1: wealthy donors, and a diverse range of local officials and

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Speaker 1: community leaders who had bristled at helen AND's leftist politics

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Speaker 1: and abrasive styles. Throughout much of the campaign, Harris attacked

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Speaker 1: helen And is too weak and ineffective to keep community

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Speaker 1: safe from dangerous criminals. In contrast, Harris promised to get

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Speaker 1: tough and I want to talk a little bit about Helenan,

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Speaker 1: uh to contrast with Kamala spared with me here a bit.

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Speaker 1: Helenan's office had a low felony conviction rate, far lower

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Speaker 1: than the rest of the state because Helenan was pushing

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Speaker 1: a lot of resources into rehabilitation programs instead of convictions,

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Speaker 1: which on paper looks like just a dismissal. Also, San

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Speaker 1: San Francisco is a really liberal city, so juries were

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Speaker 1: more lenient. But the thing is that despite that, overall

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Speaker 1: crime rates were plummeting. Violent crime had gone down close

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Speaker 1: to sixty in San Francisco since he took office, but

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Speaker 1: that did not matter. Lown fiction rate became the headline

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Speaker 1: that the media latched onto and the talking point that

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Speaker 1: Harris pushed her campaign argued that Helen and had failed

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Speaker 1: to keep communities safe from surgeon gang violence and with

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Speaker 1: you know, points pointed was low conviction rate. They you know,

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Speaker 1: they'd flyer the city's you know talking about this, uh

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Speaker 1: and it just got really ugly. And again they really

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Speaker 1: tapped into that whole tough on crime narrative. You know,

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Speaker 1: it doesn't sound like she's opening the door to the activists,

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Speaker 1: yet I know it sure doesn't. So yeah, that's why

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Speaker 1: it's important. She's like leaning out the window throwing waded

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Speaker 1: up garbage. Yet does the bricks in the wall and

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Speaker 1: like yeah, try just try, yeah and have good I

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Speaker 1: built this wall, keep that in mind as we talked

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Speaker 1: more about this. Uh. During during his time in office,

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Speaker 1: Helen and had also really tried to crack down on

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Speaker 1: police misconduct, bringing cases against cops to trial, introducing a

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Speaker 1: ballot measure to increase police oversight. Um. So, the tensions

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Speaker 1: between him and the police department were very strained, and

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Speaker 1: ultimately they ended up endorsing Kamala Accountable. No. I know

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Speaker 1: it's wild, but they endorsed Kamala citing her as the

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Speaker 1: law and order candidate. So like, if you were to

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Speaker 1: say the phrase like Kamala Harris is a cop, that

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Speaker 1: wouldn't be necessarily the most inaccurate. It wouldn't be. And

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Speaker 1: we're gonna talk so much more about that. She's got

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Speaker 1: it a little bit of an interesting relationship with the cops.

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Speaker 1: Definitely will explore that. Also, outgoing mayor her ex boyfriend

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Speaker 1: Willie Brown also endorsed her. Obviously, UH again got her

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Speaker 1: the support of elite, wealthy San Francisco people like the Getties,

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Speaker 1: but real quick Worth noting Willie Brown had issues with

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Speaker 1: Helen An like how he was investigating city corruption cases

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Speaker 1: and speaking of activists, encouraged handing out soup to homeless people.

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Speaker 1: Even going so far as showing up to Ladle soup

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Speaker 1: along with volunteer organizations, which is a problem because it

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Speaker 1: was illegal in the city at the time, and that

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Speaker 1: piste off a lot of people because he was blatantly ignored,

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Speaker 1: ignoring a latently dumb So anyway, I wonder why really

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Speaker 1: endorsed his ex girlfriend. Anyway, spoiler alert, Kamala one she won,

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Speaker 1: Helenan was out once in office. Kamala did keep some

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Speaker 1: of his legacy, uh, you know, like focusing on drug

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Speaker 1: diversion programs and providing rehabilitation resources. She also had this

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Speaker 1: re entry program from minor offenders, the Back on Track Program,

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Speaker 1: and it received a lot of praised, although many criticized

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Speaker 1: it because it only affected miners that had no previous

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Speaker 1: criminal record. Um so they felt like that felt short.

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Speaker 1: But she felt the pressure to live up to her

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Speaker 1: campaign promises you know, tough on crime, and according to

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Speaker 1: former prosecutors, Harris adopted inflexible charging procedures you know, to

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Speaker 1: look tough on crime, most likely in preparation for running

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Speaker 1: for state wide office someday. Another key issue in Harris's

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Speaker 1: tenure as d A, which many of you have probably

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Speaker 1: heard about, was truancy, which she saw as a crisis.

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Speaker 1: Harris believed that students who have high truancy rates at

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Speaker 1: every level of schooling or more likely to be the

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Speaker 1: perpetrators or victims of crimes. So she attempted to solve

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Speaker 1: this issue by criminalizing truancy for the parents of truant children.

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Speaker 1: Quote from Kamala, the crisis is not only crippling our economy,

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Speaker 1: it is a basic threat to public safety. Um that

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Speaker 1: seems like something with no unanticipated downsides. No, you know,

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Speaker 1: not criminalizing parents for their kids being absent, uh, not

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Speaker 1: capitalizing on people's fears, and like creating a bad guy

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Speaker 1: that doesn't necessarily need to be considered the bad guy.

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Speaker 1: Maybe they need other kinds of resources than being put

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Speaker 1: in jail, I don't know. And not not unfairly criminalizing

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Speaker 1: the poor, because the poor are the ones who are

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Speaker 1: most poor. Working parents are the ones who are most

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Speaker 1: likely to not have as much time to watch their

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Speaker 1: kids and you know, be worked, both working full time

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Speaker 1: and thus unable to police them as much as they

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Speaker 1: need to. It certainly is a problematic position that she held.

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Speaker 1: I like it. I think peri justice is the best

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Speaker 1: kind of justice. It goes back to the roots of

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Speaker 1: like people were surprised coming from where she came from,

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Speaker 1: where she was surrounded, grew up in a community of

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Speaker 1: people that you would think she would be able to

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Speaker 1: empathize with. You know. Well, I was against all this

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Speaker 1: until Cody framed it as putitive justice because that makes

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Speaker 1: me think of like how laser guns sound, And now

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Speaker 1: I'm on board jailing poor parents. In recent years, Harris

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Speaker 1: has said that her goal was not to arrest parents,

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Speaker 1: but rather to you know, provide a stick to the

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Speaker 1: school district's carrot. Whatever that means that this is the stick,

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Speaker 1: is the stick arresting parents? Like what you just I know,

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Speaker 1: I shot at you to make you dig faster. The

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Speaker 1: goal was not to hit you with the bullets. The

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Speaker 1: goal was to provide a stick that was the bullets

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Speaker 1: heading towards called motivation. Um, it's just a hang in

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Speaker 1: their baby poster. Yeah, well, you know doesn't It doesn't

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Speaker 1: matter what she was going for. Parents of truant kids

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Speaker 1: were criminalized, and Harris has since apologized and tried to

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Speaker 1: distance herself from the issue. But that's why we're here, baby,

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Speaker 1: your past is coming back. Um. There was also this

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Speaker 1: story about how Deborah Madden, a police crime lab technician

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Speaker 1: who routinely testified as a witness for the prosecution, got

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Speaker 1: caught stealing the cocaine that she was supposed to analyze

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Speaker 1: as evidence. Um. And after that, it was then realized

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Speaker 1: that she had had this previous felony conviction for domestic violence.

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Speaker 1: And I guess a big part of the responsibility lay

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Speaker 1: with the police department for not disclosing all the information

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Speaker 1: to Commla's office, or at least that's what they say,

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Speaker 1: But Kamala had been informed multiple times that Deborah was

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Speaker 1: an unreliable witness, and ultimately Kamla's office got in trouble

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Speaker 1: for not disclosing that information to defense attorneys or the

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Speaker 1: defendants who should have that information. And it was older

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Speaker 1: in like sises being dismissed. You're you're you're missing some

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Speaker 1: really important data, Katie, And yeah, was it? Was it

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Speaker 1: good blow? Was it some primo ship or was she

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Speaker 1: like was it some of that like garbage that gets cut.

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Speaker 1: I dug around and I couldn't find it. Um. And

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Speaker 1: I've got, you know, a search on on Deborah Madden's

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Speaker 1: and I'm systematically hunting them down to see if it's

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Speaker 1: that Debora Madden and as soon as I find the answer,

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Speaker 1: I will report back to you guys on the quality

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Speaker 1: of listeners. If you did cocaine with Deborah Man and

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Speaker 1: him in, let us know if it was the good ship,

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Speaker 1: because I really don't think we can have a solid

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Speaker 1: take on this until we know the quality of thee

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Speaker 1: and I apologize for my feelings. Please send any information

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Speaker 1: you have to Tips at Worst Tips at worst pod

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Speaker 1: dot cocaine. That's it, that's the address. That's that's for

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Speaker 1: just cocaine related tips. Any that you have UM as

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Speaker 1: d A. She also set about repairing relations with the

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Speaker 1: police department that had weakened under Helenan, but ultimately she

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Speaker 1: faced backlash from law enforcement pretty quickly into her time

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Speaker 1: there when she didn't seek the death penalty for a

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Speaker 1: gang member who was convicted of murdering an SF police officer,

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Speaker 1: Isaac Espinoza in two thousand four. Kamalos staunch against the

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Speaker 1: death penalty, and it's one of the reasons people describe

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Speaker 1: her as progressive. Um but that moved distanc from the

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Speaker 1: law enforcement community. Quote our members never forgave Harris that

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Speaker 1: was then president of the police Union Gary de Langness.

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Speaker 1: I wonder if she'll ever prove to be not totally

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Speaker 1: consistent about the death penalty. I wonder wonder that anyway

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Speaker 1: she felt that lack of support from them when she

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Speaker 1: ran for California Attorney General in two thousand and ten.

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Speaker 1: At that time, only one law enforcement group endorsed her,

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Speaker 1: and she she barely won, So she spent her first

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Speaker 1: term as a g actively courting their approval. I guess,

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Speaker 1: and I think that this is when she really earned

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Speaker 1: her reputation as a cop um, which I am assuming

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Speaker 1: Robert will be digging into it in a minute. Um. Anyway,

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Speaker 1: by the time she was up for re election, Uh,

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Speaker 1: once she had completed her first term, she then had

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Speaker 1: the endorsement of a dozen law enforcement groups. So that's

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Speaker 1: a big swing in the support. Out of the park,

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Speaker 1: out of the park. I wonder if someone wrote six

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Speaker 1: pages about why that might be. I wonder if someone did.

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Speaker 1: I also wonder if it's time for us to break

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Speaker 1: for an ad real quick sylph. He's nodding, yes, everything,

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Speaker 1: we're back, We're back. Oh my god, those services I

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Speaker 1: am uh exploding with capitalism is how I would just

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Speaker 1: grabbed myself right Now much like I don't know one

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Speaker 1: of Raytheon's fine guided thermobaric missiles um, which you can

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Speaker 1: all buy if you sign an arms contract with the

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Speaker 1: United States government. Anyway, let's talk about Kamala Harris is yeah.

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Speaker 1: Kamala Harris's career as a California's Attorney general. She was

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Speaker 1: elected in two thousand eleven, as Katie stated, in making

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Speaker 1: her the top cop in the state. She held the

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Speaker 1: job until two thousand seventeen, when she was elected senator,

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Speaker 1: replacing longtime incumbent Barbara Boxer. Now. One of the more

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Speaker 1: controversial decisions by A. G. Harris during this period was

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Speaker 1: her attitude towards the treatment of transgender people in state custody.

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Speaker 1: In two thousan fifteen, she fold legal brief which argued

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Speaker 1: against providing gender confirmation surgery for a prisoner mickel Lyle Norsworthy.

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Speaker 1: The prisoner in this case argued that being forced to

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Speaker 1: go without the surgery counted as cruel and unusual punishment.

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Speaker 1: The advocate describes this as quote what some see as

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Speaker 1: the only blot on her l g B t Q

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Speaker 1: rights record. Now, I should note that the advocate, which

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Speaker 1: is a fairly mainstream Queer Focus news site is generally

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Speaker 1: positive about Kamala Do in large part to her pioneering

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Speaker 1: history fighting against the trans panic defense. Is a defense attorney,

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Speaker 1: this is something she can bean like a big, like

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Speaker 1: nationwide like conference of of lawyers and das and ship

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Speaker 1: in San Francisco when she was um the d A

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Speaker 1: to try to deal with and like basically provide arguments

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Speaker 1: against the trans panic defense in case out of where, Like,

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Speaker 1: the trans panic defense is this thing people would use

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Speaker 1: to claim like people when they murdered transgender particularly transgender women,

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Speaker 1: would defend themselves by saying that, like, they were so

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Speaker 1: freaked out by the fact that a transgender woman was

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Speaker 1: flirting with them that they just went crazy and murdered

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Speaker 1: her and can't be held accountable for their actions. That

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Speaker 1: there's something about transgender women that so upsets men that

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Speaker 1: they can't be considered in their right mind when they

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Speaker 1: murder them. People got off as from murdering people as

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Speaker 1: a result the gay panic defense. I have a friend's

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Speaker 1: brother a while back was murdered, and uh, the guy

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Speaker 1: got off on a gay panic defense even than the guy.

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Speaker 1: It's a thing. It's a and Kamala did a lot

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Speaker 1: to fight against it and provide, um, like lawyers and

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Speaker 1: stuff who were who were arguing against people who had

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Speaker 1: committed that crime, prosecutors, um, with ways around that defense,

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Speaker 1: with like ways to argue against it in court and stuff.

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Speaker 1: So she does get she has to get a lot

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Speaker 1: of credit for that. That That was a that was a

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Speaker 1: big deal, and she did it at a time when

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Speaker 1: she was, you know, one of the relatively few voices

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Speaker 1: in law enforcement really making that an issue. So there

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Speaker 1: there's a reason why, um, someone like the advocate would

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Speaker 1: give her, you know, would describe her what she did,

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Speaker 1: you know, arguing against Michel Leonore's worth these gender confirmation

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Speaker 1: surgery is the only blot on her record. Um. Now

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Speaker 1: it's interesting to me how the advocate describes Kamala's defense

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Speaker 1: of her stance on mckel lyle nor's Worthy's case. Um.

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Speaker 1: She pointed out that when she was attorney General, the

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Speaker 1: state's Department of Corrections was a client of hers and

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Speaker 1: she had to represent its interests, but she worked behind

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Speaker 1: the scenes to get the policy changed so that any

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Speaker 1: inmate requiring such procedures could receive them. Now, I I'd

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Speaker 1: have not found any hard evidence that she did in

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Speaker 1: fact work behind the scenes, nor have I found any

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Speaker 1: evidence that she did not, nor's worthy one her case.

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Speaker 1: So I'm not really sure how much fighting behind the

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Speaker 1: scenes was even necessary UM. And in fact, like at

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Speaker 1: the time at which like Kamala was arguing against this

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Speaker 1: woman's right to transition UM, the state courts in California

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Speaker 1: had confirmed that she had a right to do it. Now,

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Speaker 1: the fact of the matter is that Harris wrote more

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Speaker 1: than one brief opposing incarcerating trans women's rights UH to

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Speaker 1: get quartered ordered surgeries. So this is not a one off.

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Speaker 1: This is something that happening number of times while she

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Speaker 1: was the Attorney general. Now, in January of two thousand nineteen,

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Speaker 1: Kamala Harris was questioned about all this by The Washington Blade,

426
00:24:57,720 --> 00:25:01,320
Speaker 1: which is another queer focused UM sort of a new site,

427
00:25:01,480 --> 00:25:03,800
Speaker 1: and I believe a responses here are rather telling. So

428
00:25:03,840 --> 00:25:06,520
Speaker 1: the Blade asks, how would you address concerns about seeking

429
00:25:06,560 --> 00:25:09,359
Speaker 1: to deny surgery for trans inmates as California A g.

430
00:25:09,800 --> 00:25:12,600
Speaker 1: Kamala Harris. So, I was, as you are rightly pointing out,

431
00:25:12,600 --> 00:25:14,679
Speaker 1: the Attorney general of California for two terms, and I

432
00:25:14,680 --> 00:25:16,639
Speaker 1: had a host of clients that I was obligated to

433
00:25:16,680 --> 00:25:19,480
Speaker 1: defend and represent, and I couldn't fire my clients. And

434
00:25:19,520 --> 00:25:22,280
Speaker 1: there are unfortunately situations that occurred when my clients took

435
00:25:22,280 --> 00:25:24,639
Speaker 1: positions that were contrary to my beliefs. And it was

436
00:25:24,680 --> 00:25:26,119
Speaker 1: in office with a lot of people who would do

437
00:25:26,119 --> 00:25:27,840
Speaker 1: the work on a daily basis, and I do wish

438
00:25:27,920 --> 00:25:30,560
Speaker 1: that sometimes they would have personally consulted me before they

439
00:25:30,640 --> 00:25:33,080
Speaker 1: wrote the things that they wrote. Yes, I do, but

440
00:25:33,119 --> 00:25:34,960
Speaker 1: the bottom line is the buck stops with me, and

441
00:25:34,960 --> 00:25:37,679
Speaker 1: I take full responsibility for what my office did. But

442
00:25:37,760 --> 00:25:39,960
Speaker 1: on that issue, I will tell you I vehemently disagree

443
00:25:40,000 --> 00:25:41,720
Speaker 1: and in fact work behind the scenes to ensure that

444
00:25:41,720 --> 00:25:44,120
Speaker 1: the Department of Corrections but allow transitioning inmates to receive

445
00:25:44,160 --> 00:25:46,760
Speaker 1: the medical attention that they required, they needed and deserved.

446
00:25:47,200 --> 00:25:50,440
Speaker 1: Then the BLADE asks to be clear, should transitmates throughout

447
00:25:50,440 --> 00:25:55,159
Speaker 1: the country have access to gender uh reconstructive surgery and

448
00:25:55,240 --> 00:25:57,800
Speaker 1: Kamala Harris responds, I believe we are at a point

449
00:25:57,840 --> 00:25:59,840
Speaker 1: where we have got to stop vilifying people based on

450
00:26:00,000 --> 00:26:02,640
Speaker 1: actual orientation and gender identity, and we've got to understand

451
00:26:02,680 --> 00:26:05,240
Speaker 1: that when we are talking about a particular transgender community,

452
00:26:05,240 --> 00:26:06,959
Speaker 1: for too long, they have been the subject of bias

453
00:26:06,960 --> 00:26:09,760
Speaker 1: and frankly, a lack of understanding about their circumstances and

454
00:26:09,800 --> 00:26:11,919
Speaker 1: their physical needs in addition to any other needs they have,

455
00:26:12,000 --> 00:26:13,680
Speaker 1: and it's about time that we have a better understanding

456
00:26:13,720 --> 00:26:17,040
Speaker 1: of that. You will notice she was asked a yes

457
00:26:17,160 --> 00:26:19,920
Speaker 1: or no question and did not respond with yes or no.

458
00:26:21,040 --> 00:26:28,040
Speaker 1: That yes, right, yeah, yeah, which is like, that's not

459
00:26:28,080 --> 00:26:33,399
Speaker 1: what you're being asked. She from what I under the

460
00:26:33,400 --> 00:26:35,560
Speaker 1: bit that you so you dug into this more she

461
00:26:35,760 --> 00:26:39,040
Speaker 1: was like in the Norseworthy situation, specifically as she was

462
00:26:39,160 --> 00:26:42,480
Speaker 1: for her receiving hormone therapy but not for having any

463
00:26:42,520 --> 00:26:46,800
Speaker 1: sort of reconstructive surgery, correct saying that Northworthy was not

464
00:26:46,880 --> 00:26:51,040
Speaker 1: in mediate physical danger, but Norseworthy received. Didn't she get

465
00:26:52,040 --> 00:26:56,359
Speaker 1: attacked in prison? I believe so. Yeah. I mean it's

466
00:26:56,520 --> 00:26:58,960
Speaker 1: I'm not sure about Norseworthy specific case. I should have

467
00:26:59,000 --> 00:27:01,959
Speaker 1: looked into it more. There was a lot to look into. Um.

468
00:27:01,760 --> 00:27:06,119
Speaker 1: I will tell you that transgender people, particularly transgender people

469
00:27:06,160 --> 00:27:09,480
Speaker 1: who have not had gender reconstructive surgery and so um

470
00:27:09,680 --> 00:27:12,720
Speaker 1: cannot do not like physically present um as their as

471
00:27:12,720 --> 00:27:16,720
Speaker 1: their gender, are attacked and murdered in prisons at a

472
00:27:17,320 --> 00:27:21,040
Speaker 1: rate wildly higher than the general population, which is part

473
00:27:21,040 --> 00:27:23,360
Speaker 1: of the judge. This is not just a matter of

474
00:27:23,440 --> 00:27:24,920
Speaker 1: like people in the right will be like, oh, what

475
00:27:25,000 --> 00:27:27,119
Speaker 1: their prisoners, Why should care about their feelings? It's not

476
00:27:27,520 --> 00:27:30,919
Speaker 1: a feelings thing. It's a people get murdered, um and

477
00:27:31,000 --> 00:27:34,359
Speaker 1: like yeah, it's uh. And and also one of the

478
00:27:34,520 --> 00:27:37,240
Speaker 1: horrible things that prisons often do to like oh, because

479
00:27:37,240 --> 00:27:39,920
Speaker 1: they'll get murdered otherwise, it's put these people in solitary confinement,

480
00:27:39,920 --> 00:27:43,000
Speaker 1: which is essentially torture. So it's this is very a

481
00:27:43,080 --> 00:27:45,399
Speaker 1: lot of fucked up things are going on around this,

482
00:27:45,480 --> 00:27:48,200
Speaker 1: and I don't want to like we're focusing on commalit

483
00:27:48,240 --> 00:27:50,679
Speaker 1: today because we have to. Please don't take this as

484
00:27:50,800 --> 00:27:54,040
Speaker 1: like my comprehensive take on the treatment of transgender people

485
00:27:54,080 --> 00:27:57,840
Speaker 1: within the prison system. There's a lot to cover. Um,

486
00:27:57,880 --> 00:28:00,240
Speaker 1: this is a very fucked up and dark top pick.

487
00:28:00,800 --> 00:28:03,320
Speaker 1: So you'll note a few things about that response she

488
00:28:03,359 --> 00:28:05,480
Speaker 1: gave to the blade Um, which is that she obliquely

489
00:28:05,520 --> 00:28:08,119
Speaker 1: blamed other people in her office before she stated that

490
00:28:08,160 --> 00:28:10,679
Speaker 1: the buck stops with me, and that she didn't actually

491
00:28:10,720 --> 00:28:15,720
Speaker 1: answer the question about gender reassignment surgery. Now Dot Triple

492
00:28:15,760 --> 00:28:18,600
Speaker 1: threat um out dot Com takes a more critical look

493
00:28:18,600 --> 00:28:21,439
Speaker 1: at Kamala's record than the advocate um, and they noted

494
00:28:21,480 --> 00:28:23,719
Speaker 1: in this response to her non answer. They noted this

495
00:28:23,800 --> 00:28:27,200
Speaker 1: in response to her non answer, uh quote. Senator Elizabeth

496
00:28:27,200 --> 00:28:30,080
Speaker 1: Warren to Massachusetts, who was also seeking the Democratic Party's

497
00:28:30,080 --> 00:28:32,840
Speaker 1: presidential nomination, very recently came out in full support of

498
00:28:32,840 --> 00:28:36,200
Speaker 1: state funded gender affirming surgeries for incarcerated trans people, though

499
00:28:36,200 --> 00:28:38,400
Speaker 1: it should be noted that she vocally opposed the manner

500
00:28:38,400 --> 00:28:40,960
Speaker 1: while running for senator in two thousand twelve. I don't

501
00:28:40,960 --> 00:28:43,280
Speaker 1: think it's a good use of taxpayer dollars, she said

502
00:28:43,280 --> 00:28:45,680
Speaker 1: at the time. Now, I think it's really important to

503
00:28:45,720 --> 00:28:47,920
Speaker 1: be fair here um, when we talk about the attitudes

504
00:28:47,960 --> 00:28:50,800
Speaker 1: of elected leaders towards trans rights and towards gay rights.

505
00:28:51,040 --> 00:28:54,600
Speaker 1: President Obama didn't officially back gay marriage until a year

506
00:28:54,640 --> 00:28:58,000
Speaker 1: after Kamala was elected Attorney General, and support for trans

507
00:28:58,080 --> 00:29:01,080
Speaker 1: rights lagged well behind that. As we see with Senator Warren,

508
00:29:01,160 --> 00:29:03,240
Speaker 1: it was not at all uncommon for Democrats to be

509
00:29:03,320 --> 00:29:06,960
Speaker 1: non supportive of gender afform affirming surgery for incarcerated trans

510
00:29:07,040 --> 00:29:09,720
Speaker 1: people the time that Kamala was arguing against it for

511
00:29:09,720 --> 00:29:12,720
Speaker 1: the state of California. That doesn't excuse being wrong, but

512
00:29:12,800 --> 00:29:15,200
Speaker 1: we can't focus on only Kamala in this and blame

513
00:29:15,240 --> 00:29:18,520
Speaker 1: her for something that all Democrats were wrong on. That said,

514
00:29:18,520 --> 00:29:21,480
Speaker 1: I do believe her behavior in particularly her answers in

515
00:29:21,520 --> 00:29:24,440
Speaker 1: the modern day, are very troubling. Um And I believe

516
00:29:24,480 --> 00:29:26,560
Speaker 1: that the pattern of behavior you see with her that

517
00:29:26,640 --> 00:29:28,640
Speaker 1: you saw in this case is troubling if you look

518
00:29:28,640 --> 00:29:31,440
Speaker 1: at it in the greater context of other morally questionable

519
00:29:31,440 --> 00:29:34,720
Speaker 1: decisions she made as the attorney General. Um Like. For

520
00:29:34,760 --> 00:29:37,000
Speaker 1: one thing, you'll notice, like Elizabeth Warren also wrong on

521
00:29:37,040 --> 00:29:39,840
Speaker 1: this issue in two thousand twelve, just like Kamala now

522
00:29:40,000 --> 00:29:42,280
Speaker 1: was willing to take an affirmative stance on it, where

523
00:29:42,320 --> 00:29:44,560
Speaker 1: Kamala is still not really willing to answer that question.

524
00:29:45,120 --> 00:29:48,440
Speaker 1: Um So. In two thousand four, as d A in

525
00:29:48,480 --> 00:29:51,720
Speaker 1: San Francisco, as you noted, Katie, she refused to seek

526
00:29:51,720 --> 00:29:53,400
Speaker 1: the death penalty for a man who shot a cop.

527
00:29:53,880 --> 00:29:58,160
Speaker 1: Um Now, this hurt her support with uh like police

528
00:29:58,160 --> 00:30:00,320
Speaker 1: officers and like, really made it more difficult for her

529
00:30:00,320 --> 00:30:02,880
Speaker 1: to get elected. Um and so that that is a

530
00:30:02,920 --> 00:30:05,240
Speaker 1: brave and unpopular stance. You have to give her credit

531
00:30:05,280 --> 00:30:07,480
Speaker 1: for that. That's fucking hard to do, is the d A.

532
00:30:08,200 --> 00:30:11,880
Speaker 1: Um So, you would think that that's just something that

533
00:30:12,000 --> 00:30:14,400
Speaker 1: sort of runs through her whole career. This like kind

534
00:30:14,400 --> 00:30:17,240
Speaker 1: of vehement opposition to the death penalty. But in two

535
00:30:17,280 --> 00:30:19,720
Speaker 1: thousand fourteen, well into her time and office as a

536
00:30:19,800 --> 00:30:23,440
Speaker 1: g she appealed to judge's decision that called California's death

537
00:30:23,480 --> 00:30:27,560
Speaker 1: penalty system unconstitutional. Now, Harris justified this in a lot

538
00:30:27,600 --> 00:30:30,000
Speaker 1: of the same way she justified her opposition to gender

539
00:30:30,040 --> 00:30:33,280
Speaker 1: reassignment surgery for inmates. She said she was just advocating

540
00:30:33,320 --> 00:30:35,920
Speaker 1: for her client client. This is what she says now.

541
00:30:36,160 --> 00:30:38,520
Speaker 1: She also, at the time, though, made the peculiar claim

542
00:30:38,560 --> 00:30:41,640
Speaker 1: that this band undermines important protections that are courts provide

543
00:30:41,680 --> 00:30:46,800
Speaker 1: the defendants, the people who might get executed. Um. Now,

544
00:30:46,960 --> 00:30:51,040
Speaker 1: it's worth noting that while she she she argued essentially

545
00:30:51,080 --> 00:30:53,240
Speaker 1: in favor of the death penalty because she says she

546
00:30:53,320 --> 00:30:56,160
Speaker 1: had to because she was advocating for her client, she

547
00:30:56,320 --> 00:30:59,920
Speaker 1: did not, as Attorney general, always choose to reflectively refle

548
00:31:00,000 --> 00:31:03,400
Speaker 1: acxibly represent a client when that client's stances were counter

549
00:31:03,480 --> 00:31:06,880
Speaker 1: to her own beliefs. As Attorney General, she declined to

550
00:31:06,920 --> 00:31:10,880
Speaker 1: defend Proposition eight, which banns same sex marriage, so clearly

551
00:31:10,920 --> 00:31:15,600
Speaker 1: she was able to use her own discretion on other issues. Um. Interesting.

552
00:31:15,640 --> 00:31:19,040
Speaker 1: So yeah, that's that's really interesting to me. So this

553
00:31:19,120 --> 00:31:22,880
Speaker 1: is not a situation where she just had no alternatives,

554
00:31:23,160 --> 00:31:29,000
Speaker 1: could have made the choice trying to be easily moved

555
00:31:29,040 --> 00:31:32,880
Speaker 1: brick in the wall and deciding when to actually do

556
00:31:32,920 --> 00:31:34,800
Speaker 1: that and when to not do that. Well, it's also

557
00:31:34,880 --> 00:31:39,720
Speaker 1: like whose approval is she courting with this specific decision.

558
00:31:40,120 --> 00:31:43,120
Speaker 1: I would say that Prop eight that is a more

559
00:31:43,200 --> 00:31:49,320
Speaker 1: popular across the board in progressive circles to be opposed to, versus,

560
00:31:49,440 --> 00:31:51,680
Speaker 1: you know, the maybe the groups of people that she's

561
00:31:51,720 --> 00:31:56,640
Speaker 1: been trying to win back over that she you know, relationships.

562
00:31:57,680 --> 00:31:59,920
Speaker 1: I think you absolutely if you want to look at

563
00:31:59,920 --> 00:32:03,240
Speaker 1: it as just sort of like a cross political move,

564
00:32:03,960 --> 00:32:07,400
Speaker 1: it makes sense that way, because yeah, Okay, if I

565
00:32:07,480 --> 00:32:09,920
Speaker 1: don't back this death penalty thing, um, that's going to

566
00:32:10,000 --> 00:32:12,479
Speaker 1: piss off more cops, and I need more police groups

567
00:32:12,480 --> 00:32:16,640
Speaker 1: to back me in my re election campaign. But cops

568
00:32:16,680 --> 00:32:18,640
Speaker 1: on the whole in California don't really care all that

569
00:32:18,720 --> 00:32:21,640
Speaker 1: much about gay rights. They're not there. They don't support

570
00:32:21,920 --> 00:32:24,000
Speaker 1: Prop eight more than the rest of the population does.

571
00:32:24,240 --> 00:32:27,320
Speaker 1: And if I if I support Prop eight, uh, that

572
00:32:27,360 --> 00:32:29,480
Speaker 1: will cost me more net votes. So I'm going to

573
00:32:29,520 --> 00:32:32,360
Speaker 1: oppose prop eight like that makes sense to me. And

574
00:32:32,480 --> 00:32:34,720
Speaker 1: I don't think she took a stand for trans people

575
00:32:35,160 --> 00:32:38,920
Speaker 1: because she and I guess she was correct in this. Um,

576
00:32:39,280 --> 00:32:42,000
Speaker 1: she didn't think that there were enough of them to

577
00:32:42,040 --> 00:32:45,280
Speaker 1: matter electorally exactly wasn't worth the fight. Political climate was

578
00:32:45,320 --> 00:32:49,600
Speaker 1: such that people barely even understood what trans meant, and

579
00:32:50,000 --> 00:32:53,440
Speaker 1: it wasn't something that it was. It's an issue that

580
00:32:53,480 --> 00:32:56,800
Speaker 1: could have been potentially harmful for her at the time. Um,

581
00:32:56,840 --> 00:32:59,360
Speaker 1: she just really seems to have been positioning herself straddling

582
00:32:59,360 --> 00:33:06,000
Speaker 1: that line between progressive policies and also catering to you know,

583
00:33:06,040 --> 00:33:10,400
Speaker 1: this tough on crime. Yeah, it's trying to be trying

584
00:33:10,400 --> 00:33:12,960
Speaker 1: to be a progressive cop. Yeah, it's trying to be

585
00:33:13,000 --> 00:33:15,040
Speaker 1: a progressive cop. But it's also it's not trying to

586
00:33:15,080 --> 00:33:17,240
Speaker 1: be a progressive cop. Or at least one way you

587
00:33:17,240 --> 00:33:21,160
Speaker 1: could look at this is she's not like it looks

588
00:33:21,200 --> 00:33:23,720
Speaker 1: this looks to me less like she's she's an actual

589
00:33:23,720 --> 00:33:26,720
Speaker 1: progressive cop and more she understands where the winds are blowing.

590
00:33:26,760 --> 00:33:29,880
Speaker 1: She's in California. You want to seem like a progressive cop,

591
00:33:29,960 --> 00:33:33,360
Speaker 1: but you also the most important thing is to get reelected.

592
00:33:33,760 --> 00:33:36,680
Speaker 1: So when being progressive means pissing off a bunch of

593
00:33:36,680 --> 00:33:39,200
Speaker 1: cops in favor of a tiny number of transgender people.

594
00:33:39,560 --> 00:33:43,240
Speaker 1: You're gonna you're gonna throw the trans people under the bus. Um, Like,

595
00:33:43,400 --> 00:33:48,120
Speaker 1: that's that's what I see here. Um Now, I I

596
00:33:48,240 --> 00:33:50,160
Speaker 1: do have to say, like stating all that, Um, I

597
00:33:50,160 --> 00:33:52,000
Speaker 1: wouldn't be doing my due diligence if I didn't point

598
00:33:52,040 --> 00:33:54,360
Speaker 1: out some very significant ways that she did earn like

599
00:33:54,440 --> 00:33:56,920
Speaker 1: the title of progressive, that she really pushed some very

600
00:33:56,960 --> 00:33:59,720
Speaker 1: progressive program. So I'm gonna quote from a really good

601
00:33:59,760 --> 00:34:02,960
Speaker 1: vo article on her background here. She expanded her back

602
00:34:03,000 --> 00:34:05,240
Speaker 1: on Track program to other parts of the state after

603
00:34:05,280 --> 00:34:07,680
Speaker 1: Black Lives Matter took off. She introduced and expanded what

604
00:34:07,720 --> 00:34:10,040
Speaker 1: her office described as first of its kind training to

605
00:34:10,080 --> 00:34:13,280
Speaker 1: address racial bias as well as procedural justice, earning praise

606
00:34:13,280 --> 00:34:16,200
Speaker 1: from local newspapers. She made the California Department of Justice

607
00:34:16,239 --> 00:34:19,040
Speaker 1: the first statewide agency to require body cameras, and she

608
00:34:19,120 --> 00:34:22,160
Speaker 1: launched open Justice, a platform that, among other data, allows

609
00:34:22,200 --> 00:34:25,359
Speaker 1: the public to track reported killings by police officers. That's

610
00:34:25,360 --> 00:34:33,040
Speaker 1: all great, but yeah, there's there's this is a butt

611
00:34:33,120 --> 00:34:36,920
Speaker 1: full article. Um So. Her office also sought to release

612
00:34:36,960 --> 00:34:39,319
Speaker 1: fewer prisoners. When the U. S. Supreme Court found that

613
00:34:39,360 --> 00:34:42,040
Speaker 1: California's prisons were so overcrowded that it counted as cruel

614
00:34:42,080 --> 00:34:45,120
Speaker 1: and unusual punishment to keep that many people incarcerated, she

615
00:34:45,280 --> 00:34:50,200
Speaker 1: argued against releasing people because, and this is cartoonishly marged,

616
00:34:50,680 --> 00:34:53,920
Speaker 1: releasing too many prisoners would deplete the prison labor pool.

617
00:34:54,880 --> 00:34:57,520
Speaker 1: It's unbelievable. It made me gasp when I was reading

618
00:34:57,520 --> 00:35:02,680
Speaker 1: about that, Like that's like Garga levels of evil, because, yeah,

619
00:35:02,719 --> 00:35:06,480
Speaker 1: I would negatively impact cheap prison laborer because I guess

620
00:35:06,520 --> 00:35:10,279
Speaker 1: they could having them go out to fight wildfires only

621
00:35:10,280 --> 00:35:12,880
Speaker 1: cost them two dollars a day. Yeah, yeah, should that

622
00:35:12,960 --> 00:35:15,520
Speaker 1: That was specifically part of the justifications that we wanted

623
00:35:15,520 --> 00:35:18,640
Speaker 1: as many of the incarcerated people that we pay under

624
00:35:18,719 --> 00:35:22,399
Speaker 1: a legal minimum wage to fight our fires, fighting our fires,

625
00:35:22,640 --> 00:35:24,799
Speaker 1: some of them, all of them not being able to

626
00:35:24,840 --> 00:35:28,080
Speaker 1: have that job when they leave prison. Um, maybe there's

627
00:35:28,080 --> 00:35:30,279
Speaker 1: other ways to deal with this problem of not enough

628
00:35:30,320 --> 00:35:33,839
Speaker 1: wild firefighters. Maybe let them take that job after doing

629
00:35:33,920 --> 00:35:41,600
Speaker 1: it in prisons rehabilitation programs. Um, do you have this

630
00:35:41,719 --> 00:35:44,479
Speaker 1: extending to for one credits quote from her lawyers, because

631
00:35:44,520 --> 00:35:47,520
Speaker 1: if not, I want to share this at the time

632
00:35:47,840 --> 00:35:50,799
Speaker 1: Harris's lawyers argued that extending to for one credits to

633
00:35:50,840 --> 00:35:53,880
Speaker 1: all minimum custody inmates at this time would severely impact

634
00:35:53,920 --> 00:35:57,480
Speaker 1: the fire can't participation a dangerous outcome while California is

635
00:35:57,520 --> 00:35:59,920
Speaker 1: the middle of a difficult fire season in a severe drought.

636
00:36:00,360 --> 00:36:04,560
Speaker 1: And then later on, Harris claimed that the arguments uh

637
00:36:04,840 --> 00:36:06,960
Speaker 1: that she was shocked by those arguments that were made,

638
00:36:07,239 --> 00:36:12,000
Speaker 1: and she said she wasn't aware of her you don't

639
00:36:12,040 --> 00:36:15,279
Speaker 1: know specifically claimed she didn't realize they were using that

640
00:36:15,400 --> 00:36:19,080
Speaker 1: argument until she saw negative news that full quote, if

641
00:36:19,080 --> 00:36:21,279
Speaker 1: you want to, I want, oh beautiful, hit me up.

642
00:36:21,320 --> 00:36:24,839
Speaker 1: It's really it's it's really such a everything that we've

643
00:36:24,840 --> 00:36:28,120
Speaker 1: been talking about, because it's literally just I will be

644
00:36:28,200 --> 00:36:31,279
Speaker 1: very candid with you, very candid. Yeah, because I saw

645
00:36:31,320 --> 00:36:34,000
Speaker 1: that article this morning and I was shocked, and I'm

646
00:36:34,040 --> 00:36:36,040
Speaker 1: looking into it to see if the way it was

647
00:36:36,120 --> 00:36:39,200
Speaker 1: characterized in the paper is actually how it occurred in court.

648
00:36:39,560 --> 00:36:41,920
Speaker 1: I was very troubled by what I read. I just

649
00:36:42,000 --> 00:36:44,680
Speaker 1: need to find out what did we actually say in court.

650
00:36:45,400 --> 00:36:48,520
Speaker 1: It's baffling to me. It's not baffling, you're lying, you

651
00:36:48,560 --> 00:36:53,760
Speaker 1: know what. I'm looking into it. It's all just that anyway,

652
00:36:53,840 --> 00:36:56,640
Speaker 1: buck stops with me. But also I didn't know they

653
00:36:56,640 --> 00:37:00,120
Speaker 1: were doing this. Again, that's ship I'm gonna take. I'm

654
00:37:00,120 --> 00:37:02,520
Speaker 1: gonna take some responsibility, and I'm gonna get to the

655
00:37:02,520 --> 00:37:05,600
Speaker 1: bottom of why who did this. We're very we're very

656
00:37:05,600 --> 00:37:10,120
Speaker 1: strongly looking into it. Quick question, has literally anyone who's

657
00:37:10,120 --> 00:37:13,200
Speaker 1: ever said the buck stops with me actually been arguing

658
00:37:13,200 --> 00:37:15,600
Speaker 1: that the buck stops with them when they use that statement?

659
00:37:15,680 --> 00:37:17,520
Speaker 1: Or is it always used to be like, the buck

660
00:37:17,560 --> 00:37:21,040
Speaker 1: stops with me? But here's who's faulted about. I mean,

661
00:37:21,120 --> 00:37:26,120
Speaker 1: every case that I've seen in the last never, never, never,

662
00:37:26,239 --> 00:37:29,040
Speaker 1: ever has anyone said the buck stops with me and

663
00:37:29,160 --> 00:37:36,040
Speaker 1: I resign. Yeah, never followed up with that, Yeah, amazing. Um. Yeah,

664
00:37:36,080 --> 00:37:39,919
Speaker 1: so there's a bit of a pattern, you can say. Uh, Now,

665
00:37:40,000 --> 00:37:42,160
Speaker 1: it's fair to note that the AG's office of the

666
00:37:42,239 --> 00:37:45,160
Speaker 1: largest state in the Union handles way too many cases

667
00:37:45,200 --> 00:37:47,239
Speaker 1: for any one person to keep up with. That is

668
00:37:47,360 --> 00:37:50,400
Speaker 1: absolutely a reality, and maybe there should be some structural

669
00:37:50,480 --> 00:37:52,640
Speaker 1: changes to a number of things in order to address that.

670
00:37:53,239 --> 00:37:57,960
Speaker 1: UM But in you know, Justice Department UM policy did

671
00:37:58,000 --> 00:38:01,000
Speaker 1: not require state lawyers to seek approve from the A A. G.

672
00:38:01,200 --> 00:38:03,760
Speaker 1: So it is true that the people making this argument

673
00:38:03,800 --> 00:38:07,000
Speaker 1: did not have to clear it with Kamala Harris. But

674
00:38:07,800 --> 00:38:11,080
Speaker 1: it would have been completely within Kamala Harris's prerogative as

675
00:38:11,120 --> 00:38:14,600
Speaker 1: Attorney General to change that policy to institute a more

676
00:38:14,680 --> 00:38:16,719
Speaker 1: hands on approach that would have given her in her

677
00:38:16,760 --> 00:38:20,200
Speaker 1: office more approval and allowed her to catch things like this.

678
00:38:20,640 --> 00:38:24,040
Speaker 1: She did not institute this. It is suggested by some

679
00:38:24,200 --> 00:38:26,040
Speaker 1: that the reason she didn't is because it would have

680
00:38:26,080 --> 00:38:32,160
Speaker 1: antagonized her employees and law enforcement. We're seeing that same. Yeah.

681
00:38:32,239 --> 00:38:34,120
Speaker 1: Now this is where I should note that people today,

682
00:38:34,160 --> 00:38:37,319
Speaker 1: including myself, have taken to calling miss Kamala Harris a cop,

683
00:38:37,560 --> 00:38:39,919
Speaker 1: which some people say is unfair and reductive. I want

684
00:38:39,960 --> 00:38:42,279
Speaker 1: to note that during this time, she described herself as

685
00:38:42,360 --> 00:38:46,600
Speaker 1: California's top cop. So if you're calling Kamala Harris a cop,

686
00:38:46,640 --> 00:38:49,520
Speaker 1: you are calling her what she called herself. And it's fine. Well,

687
00:38:49,560 --> 00:38:51,279
Speaker 1: if you're gonna if we're gonna be more accurate, don't

688
00:38:51,280 --> 00:38:53,759
Speaker 1: say is a top as a cop, Say Kamala Harris

689
00:38:53,840 --> 00:39:00,319
Speaker 1: is the top cop. She was the top cope. And maybe,

690
00:39:00,360 --> 00:39:02,680
Speaker 1: if you want to be whimsical, suggest that Kamala Harris

691
00:39:02,719 --> 00:39:04,640
Speaker 1: was the time cop so that we can imagine her

692
00:39:04,719 --> 00:39:07,800
Speaker 1: in Jean Claude Van Damn kick fighting their way through history,

693
00:39:07,920 --> 00:39:12,080
Speaker 1: which I do enjoy. Let's all do that. I've just

694
00:39:12,120 --> 00:39:15,000
Speaker 1: take a moment to imagine it's a cod which would

695
00:39:15,000 --> 00:39:22,839
Speaker 1: you mind giving us a time machine? Noise? Oh god, Now,

696
00:39:22,920 --> 00:39:25,560
Speaker 1: just as you listen to this, I just imagine Kamala

697
00:39:25,600 --> 00:39:28,520
Speaker 1: Harris looping back in time to stop Hitler with the

698
00:39:28,560 --> 00:39:34,080
Speaker 1: support of is this adult Hitler Hitler? I think both.

699
00:39:34,160 --> 00:39:39,360
Speaker 1: I think she's really I'd rather take that She's gonna

700
00:39:39,440 --> 00:39:42,799
Speaker 1: throw baby Hitler at adult Hitler like Ahab throwing his

701
00:39:42,840 --> 00:39:45,120
Speaker 1: harpoon at the white whale. That's just going to destroy

702
00:39:45,160 --> 00:39:48,560
Speaker 1: the entire universe. It might, it might, and that would

703
00:39:48,640 --> 00:39:55,880
Speaker 1: really hurt her chances of elections. So she's yeah, we

704
00:39:55,880 --> 00:39:58,440
Speaker 1: would be calling certain people Nazis, and everyone be like,

705
00:39:58,600 --> 00:40:02,400
Speaker 1: you mean that obscure group in Germany that like, for

706
00:40:02,440 --> 00:40:05,279
Speaker 1: a year and a half are concerned about that? What

707
00:40:05,320 --> 00:40:09,720
Speaker 1: are you talking about now? Because of her progressive past

708
00:40:10,000 --> 00:40:12,239
Speaker 1: and decisions like declining to seek the death penalty for

709
00:40:12,280 --> 00:40:15,040
Speaker 1: that cop killer, Harris, like you said, was initially elected

710
00:40:15,080 --> 00:40:16,799
Speaker 1: a g with very little support. In her two thousand

711
00:40:16,880 --> 00:40:20,240
Speaker 1: ten victory was narrow enough, it was less than one percent.

712
00:40:20,400 --> 00:40:24,120
Speaker 1: She won by so incredibly narrow um and you know,

713
00:40:24,239 --> 00:40:27,200
Speaker 1: as you noted, uh, once she was in she seems

714
00:40:27,239 --> 00:40:28,880
Speaker 1: to have felt the need to throw red meat to

715
00:40:28,920 --> 00:40:31,160
Speaker 1: law enforcement in order to secure re election. So I'm

716
00:40:31,200 --> 00:40:32,800
Speaker 1: gonna quote again from that box right up from the

717
00:40:32,800 --> 00:40:36,319
Speaker 1: two sketchies cases that resulted from this trend. Harris also

718
00:40:36,360 --> 00:40:39,239
Speaker 1: overlooked and defended law enforcement officials accused of misconduct, and

719
00:40:39,280 --> 00:40:42,080
Speaker 1: one such case, state prosecutor Robert Murray falsified a confession,

720
00:40:42,160 --> 00:40:44,200
Speaker 1: using it to threaten the defendant with life in prison.

721
00:40:44,280 --> 00:40:46,920
Speaker 1: After a court throughout the indictment, Harris's office appealed it,

722
00:40:47,040 --> 00:40:49,920
Speaker 1: dismissing them misconduct because it did not involve physical violence.

723
00:40:50,200 --> 00:40:53,640
Speaker 1: Harris also resisted some attempts to hold police accountable for shootings,

724
00:40:53,680 --> 00:40:55,880
Speaker 1: including a bill that would have required the Attorney General's

725
00:40:55,880 --> 00:40:58,600
Speaker 1: office to investigate killings by police, and efforts to create

726
00:40:58,640 --> 00:41:01,880
Speaker 1: statewide standards for police own body cameras. She also defied

727
00:41:01,920 --> 00:41:04,680
Speaker 1: calls to have her office quickly investigate certain police shootings

728
00:41:04,680 --> 00:41:10,440
Speaker 1: in California. So that's good. Now. The darkest, maybe the

729
00:41:10,520 --> 00:41:13,279
Speaker 1: darkest chapter of Kamala's history as a g is the

730
00:41:13,320 --> 00:41:17,840
Speaker 1: story of George Gauge. Have you guys heard this? It's

731
00:41:18,480 --> 00:41:20,839
Speaker 1: fucked now. I'm gonna quote next from a New York

732
00:41:20,840 --> 00:41:23,759
Speaker 1: Times article, an opinion column titled Kamala Harris was not

733
00:41:23,920 --> 00:41:27,560
Speaker 1: a progressive prosecutors by someone at the Innocence Project. Quote

734
00:41:28,680 --> 00:41:31,359
Speaker 1: consider George Gauge, an electrician with no criminal record who

735
00:41:31,400 --> 00:41:34,520
Speaker 1: was charged in nine with sexually abusing his stepdaughter, who

736
00:41:34,520 --> 00:41:37,840
Speaker 1: reported the allegations years later. The case largely hinged on

737
00:41:37,840 --> 00:41:41,279
Speaker 1: the stepdaughter's testimony, and Mr Gage was convicted. Afterward, the

738
00:41:41,320 --> 00:41:44,600
Speaker 1: judge discovered that the prosecutor had unlawfully held back potentially

739
00:41:44,640 --> 00:41:48,400
Speaker 1: exculpatory evidence, including medical reports, indicating that the stepdaughter had

740
00:41:48,400 --> 00:41:51,760
Speaker 1: been repeatedly untruthful with law enforcement. Her mother even described

741
00:41:51,760 --> 00:41:55,040
Speaker 1: her as a pathological liar who lives her lies. And

742
00:41:55,080 --> 00:41:57,760
Speaker 1: two thousand fifteen, when the case reached the United States

743
00:41:57,800 --> 00:41:59,920
Speaker 1: Court of Appeals for the Ninth Circuit in San Francisco,

744
00:42:00,280 --> 00:42:03,600
Speaker 1: Miss Harris's prosecutors defended the conviction. They pointed out that

745
00:42:03,680 --> 00:42:06,080
Speaker 1: Mr Gauge, while forced to act as his own lawyer,

746
00:42:06,280 --> 00:42:08,800
Speaker 1: had not properly raised the legal issue in the lower

747
00:42:08,840 --> 00:42:12,440
Speaker 1: court as the law required. The appellate judges acknowledged this

748
00:42:12,480 --> 00:42:15,320
Speaker 1: impediment and sent the case to mediation, a clear signal

749
00:42:15,320 --> 00:42:17,960
Speaker 1: for Miss Harris to dismiss the case. When she refused

750
00:42:17,960 --> 00:42:20,840
Speaker 1: to budge, the court upheld the conviction on that technicality.

751
00:42:21,239 --> 00:42:24,280
Speaker 1: Mr Gauge is still in prison serving a seventy year sentence.

752
00:42:25,480 --> 00:42:28,359
Speaker 1: That is fun, is fun, and it makes sense. There's

753
00:42:28,440 --> 00:42:31,440
Speaker 1: other stories like that, but it also makes sense. You know,

754
00:42:31,520 --> 00:42:38,440
Speaker 1: she started off prosecuting uh child sexual abuse cases, and

755
00:42:38,520 --> 00:42:42,320
Speaker 1: so that's something that you know, is her calling card

756
00:42:42,480 --> 00:42:45,920
Speaker 1: is such and so I guess that makes sense now, Katie,

757
00:42:46,040 --> 00:42:53,800
Speaker 1: speaking of calling cards, Yes, this product and our service

758
00:42:53,920 --> 00:42:57,239
Speaker 1: you could call our calling card, much like Kamala's is

759
00:42:58,560 --> 00:43:02,480
Speaker 1: unfairly imprisoning a man for crime. He didn't you did it?

760
00:43:02,680 --> 00:43:13,360
Speaker 1: You really got through that, Robert. We'll be right together everything.

761
00:43:15,160 --> 00:43:18,240
Speaker 1: So we're back. We're back. Um, we're back, and we're

762
00:43:18,280 --> 00:43:28,200
Speaker 1: talking about about kahar Malla Harris's Carress Carress. Yeah. Yeah. Now,

763
00:43:29,160 --> 00:43:30,719
Speaker 1: so when we talk about the case of George Gates,

764
00:43:30,760 --> 00:43:32,120
Speaker 1: there's a couple of things going on. One of them

765
00:43:32,160 --> 00:43:34,200
Speaker 1: is that like there's kind of this war between believing

766
00:43:34,200 --> 00:43:36,600
Speaker 1: the victim and also the fact that like there are

767
00:43:36,600 --> 00:43:40,120
Speaker 1: false accusations and this is particularly when we look at

768
00:43:40,160 --> 00:43:45,759
Speaker 1: false accusations cases of children and step children claiming years

769
00:43:45,800 --> 00:43:49,520
Speaker 1: later they were sexually abused. There's a dark history with that.

770
00:43:49,600 --> 00:43:52,319
Speaker 1: Obviously it happens, but also there was during the Satanic Panic,

771
00:43:52,320 --> 00:43:53,960
Speaker 1: there were a huge number of kids who had like

772
00:43:54,040 --> 00:43:58,040
Speaker 1: false memories essentially like pushed onto them by hypnotherapists and

773
00:43:58,080 --> 00:44:01,960
Speaker 1: ship and a ton of completely innocent people got charged

774
00:44:02,080 --> 00:44:04,080
Speaker 1: and like people who like worked at daycares. There's a

775
00:44:04,120 --> 00:44:06,719
Speaker 1: lot of this happened in California. So like there's a long,

776
00:44:06,840 --> 00:44:11,879
Speaker 1: fucked up history in California of this exact thing happening. Um.

777
00:44:11,920 --> 00:44:14,279
Speaker 1: And all of the cases, even outside of Kamala's are

778
00:44:14,400 --> 00:44:17,880
Speaker 1: are are that dark. Um. So it's like this is

779
00:44:17,920 --> 00:44:21,720
Speaker 1: like really messy and ugly, and it seems like Gauges

780
00:44:21,800 --> 00:44:24,680
Speaker 1: is a case where an innocent guy was was accused

781
00:44:24,680 --> 00:44:27,879
Speaker 1: of something he didn't do. Um, And it's fucked It's

782
00:44:27,920 --> 00:44:30,080
Speaker 1: just fucked um. And I'm sure if you were to

783
00:44:30,200 --> 00:44:32,600
Speaker 1: question Kamala about this, she would say again that she

784
00:44:32,680 --> 00:44:34,160
Speaker 1: was just doing her job as an advocate for the

785
00:44:34,160 --> 00:44:37,200
Speaker 1: state of California. Whether you find that defense compelling or not,

786
00:44:37,280 --> 00:44:39,959
Speaker 1: as a matter of your own personal morality, in terms

787
00:44:39,960 --> 00:44:42,640
Speaker 1: of my personal morality. I think the best article I

788
00:44:42,680 --> 00:44:45,040
Speaker 1: found on this subject was a column on The Intercept

789
00:44:45,160 --> 00:44:48,120
Speaker 1: titled can a prosecutor Become a President in the Age

790
00:44:48,160 --> 00:44:50,520
Speaker 1: of Black Lives Matter? And I'd like to quote from

791
00:44:50,520 --> 00:44:54,440
Speaker 1: that last. To become a prosecutor is a is to

792
00:44:54,560 --> 00:44:57,400
Speaker 1: make a choice to align oneself with a powerful and

793
00:44:57,480 --> 00:45:01,760
Speaker 1: fundamentally biased system. As Paul Butler, former prosecutor and author

794
00:45:01,800 --> 00:45:05,040
Speaker 1: of Chokehold Policing Black Men, told The Guardian, as a

795
00:45:05,120 --> 00:45:06,799
Speaker 1: lawyer who went to law school with a goal of

796
00:45:06,840 --> 00:45:09,160
Speaker 1: helping black people and using my legal skills to make

797
00:45:09,160 --> 00:45:12,200
Speaker 1: things better, the realization that the law itself was a

798
00:45:12,239 --> 00:45:16,160
Speaker 1: mechanism to keep African American people down was frightening. He added,

799
00:45:16,400 --> 00:45:19,640
Speaker 1: Lawyers are competitive and ambitious, and the way that manifests

800
00:45:19,680 --> 00:45:22,080
Speaker 1: itself in a prosecutor's office is you want to get

801
00:45:22,120 --> 00:45:25,239
Speaker 1: tough sentences. I got caught up in that world. You

802
00:45:25,280 --> 00:45:27,760
Speaker 1: feel like you're doing the lord's work. You tell yourselves

803
00:45:27,800 --> 00:45:30,960
Speaker 1: that you're helping the community, but he vividly recalls, the

804
00:45:31,080 --> 00:45:35,319
Speaker 1: expectation is far from reality. Compare his self reflection with

805
00:45:35,360 --> 00:45:38,640
Speaker 1: Harris's reply when asked about her decision to become a prosecutor.

806
00:45:39,200 --> 00:45:41,200
Speaker 1: There is a duty and a responsibility to be a

807
00:45:41,280 --> 00:45:43,279
Speaker 1: voice for the most voiceless and vulnerable and to do

808
00:45:43,320 --> 00:45:45,720
Speaker 1: the work of justice. And that's the work I wanted

809
00:45:45,760 --> 00:45:48,880
Speaker 1: to do. Harris revealed that her own parents questioned her

810
00:45:48,920 --> 00:45:51,800
Speaker 1: choice to become a prosecutor. My family and extended family

811
00:45:51,840 --> 00:45:53,920
Speaker 1: thought at best it was a curious decision, she recalled,

812
00:45:53,960 --> 00:45:56,080
Speaker 1: saying that she had to defend it like one would

813
00:45:56,080 --> 00:45:59,000
Speaker 1: a thesis. They asked, in Harris's words, why would you

814
00:45:59,040 --> 00:46:00,840
Speaker 1: go and be part of an institution that is not

815
00:46:00,920 --> 00:46:05,480
Speaker 1: always fair and does not always pursue justice? Now. That

816
00:46:05,600 --> 00:46:08,160
Speaker 1: column went on to compare Kamala's history as a district

817
00:46:08,160 --> 00:46:11,560
Speaker 1: attorney and an a g very unfavorably to Larry Krassner,

818
00:46:11,840 --> 00:46:15,400
Speaker 1: the recently elected district attorney in Philadelphia. In his first

819
00:46:15,400 --> 00:46:18,480
Speaker 1: weekend office, Krastner showed a distinct lack of fox for

820
00:46:18,520 --> 00:46:20,920
Speaker 1: how his actions would affect the likelihood of law enforcement

821
00:46:20,960 --> 00:46:24,319
Speaker 1: supporting him for re election. He fired thirty one prosecutors

822
00:46:24,360 --> 00:46:28,360
Speaker 1: who were not on board with his reforms immediately. Under Krastner,

823
00:46:28,440 --> 00:46:31,359
Speaker 1: the Philadelphia d A no longer charges sex workers who

824
00:46:31,400 --> 00:46:34,440
Speaker 1: have less than three prior convictions. It does not prosecute

825
00:46:34,440 --> 00:46:37,960
Speaker 1: marijuana possession plea bargaining no longer starts with the highest

826
00:46:38,000 --> 00:46:42,000
Speaker 1: possible sentences, and prosecutors are required to add up the

827
00:46:42,040 --> 00:46:45,759
Speaker 1: cost of incarcerating a prisoner and justify why the expense

828
00:46:45,840 --> 00:46:48,799
Speaker 1: is worthwhile to the city based on their crimes. Um,

829
00:46:48,840 --> 00:46:52,440
Speaker 1: that's not like. That's to show like you can go

830
00:46:52,600 --> 00:46:56,600
Speaker 1: in as a prosecutor with a very progressive mindset and

831
00:46:56,680 --> 00:46:59,840
Speaker 1: make changes like that. Um, it would be unfair to

832
00:46:59,840 --> 00:47:02,879
Speaker 1: say that Kamala Harris did not do anything progressive, either

833
00:47:02,920 --> 00:47:06,080
Speaker 1: as a d A or as a as an attorney general.

834
00:47:06,080 --> 00:47:08,319
Speaker 1: She did a number of very progressive things, but I

835
00:47:08,360 --> 00:47:10,640
Speaker 1: do not think it's fair to call her a progressive prosecutor.

836
00:47:10,719 --> 00:47:13,239
Speaker 1: She is a prosecutor who wanted to get reelected, and

837
00:47:13,280 --> 00:47:16,400
Speaker 1: she took progressive stances when they were popular and increased

838
00:47:16,400 --> 00:47:18,759
Speaker 1: her odds of getting elected. That's not a hundred percent

839
00:47:18,800 --> 00:47:20,879
Speaker 1: of the time. She did take some bold cases, but

840
00:47:20,960 --> 00:47:23,360
Speaker 1: that was not the norm for her career, right. I

841
00:47:23,400 --> 00:47:25,600
Speaker 1: think that's where I land on this calculated it's a

842
00:47:25,640 --> 00:47:29,840
Speaker 1: calculator prosecutor. She called herself a tough progressive prosecutor. I

843
00:47:29,840 --> 00:47:33,319
Speaker 1: believe I saw that quote somewhere and you know, yeah again, yeah,

844
00:47:33,520 --> 00:47:36,839
Speaker 1: it's it's not as progressive as you think she would like. Yeah,

845
00:47:36,920 --> 00:47:41,719
Speaker 1: not quite. Um, yeah, yeah, it's all very interesting. One

846
00:47:42,080 --> 00:47:45,040
Speaker 1: quick thing about her time is a g I guess

847
00:47:45,360 --> 00:47:52,080
Speaker 1: in she did not prosecute Steve Manuchen's bank One West Bank,

848
00:47:52,640 --> 00:47:57,600
Speaker 1: despite their being evidence of misconduct, and later Manuchin donated

849
00:47:57,640 --> 00:48:01,480
Speaker 1: two thousand dollars to her campaign. Uh how about that?

850
00:48:01,520 --> 00:48:03,880
Speaker 1: Why do you think he did that? Well, you know,

851
00:48:04,120 --> 00:48:06,879
Speaker 1: why do you think one? Why does one and why

852
00:48:06,920 --> 00:48:10,319
Speaker 1: does one not? But Comma, it's important. Though she did

853
00:48:10,360 --> 00:48:13,520
Speaker 1: not vote. She voted against his confirmation as as Secretary

854
00:48:13,560 --> 00:48:16,239
Speaker 1: of the Treachery. So yeah, the buck stopped there. The

855
00:48:16,280 --> 00:48:20,080
Speaker 1: buck did stopped there. Sometimes the buck does stop where

856
00:48:20,120 --> 00:48:22,480
Speaker 1: where it should stop. Cody, do you want to talk

857
00:48:22,520 --> 00:48:25,480
Speaker 1: to us a bit about her platform and how that

858
00:48:25,560 --> 00:48:28,919
Speaker 1: is changed? Um? And I think honestly we've covered We've

859
00:48:28,920 --> 00:48:31,040
Speaker 1: covered a lot of it just sort of by talking

860
00:48:31,080 --> 00:48:34,480
Speaker 1: about these events, because, like we said, like she is

861
00:48:34,520 --> 00:48:36,600
Speaker 1: against the death penalty. Now that that is part of

862
00:48:36,600 --> 00:48:39,640
Speaker 1: her platform, her history, and that is a little shaky.

863
00:48:40,480 --> 00:48:45,640
Speaker 1: Um Yeah, clearly clearly choosing to to be that sometimes

864
00:48:45,680 --> 00:48:48,480
Speaker 1: and not be that other times. Um. She wants to

865
00:48:48,960 --> 00:48:54,800
Speaker 1: uh does issue with cash bail. She wants to reform, slash,

866
00:48:54,840 --> 00:48:59,960
Speaker 1: reduce cash bail. Um. But as her time as his attorney.

867
00:49:00,000 --> 00:49:01,360
Speaker 1: Don't know if you read about this. Here's just a

868
00:49:01,440 --> 00:49:03,600
Speaker 1: quote from her. People come to San Francisco to commit

869
00:49:03,680 --> 00:49:06,560
Speaker 1: crimes because it's cheaper to do it. So she wanted

870
00:49:06,600 --> 00:49:11,279
Speaker 1: to San Francisco lately, but she so she wanted to

871
00:49:11,360 --> 00:49:14,960
Speaker 1: raise cash bail during that time. I I love the

872
00:49:15,000 --> 00:49:18,719
Speaker 1: picture that paints of criminals. Hey, Chuck, you know what

873
00:49:18,880 --> 00:49:20,320
Speaker 1: this fucking I don't want to I don't want to

874
00:49:20,360 --> 00:49:23,239
Speaker 1: be criming in Milwaukee. This Let's go to San Francisco,

875
00:49:23,320 --> 00:49:27,759
Speaker 1: will any where the crimes are paved with gold. It's

876
00:49:27,760 --> 00:49:31,480
Speaker 1: warm enough to sleep on the street. Yeah, so like

877
00:49:31,520 --> 00:49:33,520
Speaker 1: the lots. Fine, that is a little a little, a

878
00:49:33,560 --> 00:49:37,279
Speaker 1: little much. It's a little still but also inconsistent with

879
00:49:37,520 --> 00:49:41,200
Speaker 1: how she's framing it now. Um. And also I think

880
00:49:41,200 --> 00:49:45,120
Speaker 1: it's telling that she's saying that she wants to reform

881
00:49:45,239 --> 00:49:48,600
Speaker 1: cash bail and reduce cash bail as opposed to just

882
00:49:48,719 --> 00:49:53,879
Speaker 1: abolish cash bail um. Because that, I mean, that's what

883
00:49:53,960 --> 00:49:56,759
Speaker 1: you would if you were like, like really progressive and

884
00:49:56,760 --> 00:49:59,040
Speaker 1: wanting to like reduce this, you would say, well, we

885
00:49:59,040 --> 00:50:03,760
Speaker 1: shouldn't have cash bail. It's easily too easily manipulated and benefits.

886
00:50:04,000 --> 00:50:06,520
Speaker 1: She just wants to want to reduce it. And because

887
00:50:06,520 --> 00:50:08,680
Speaker 1: nothing too extreme here. Yeah, it's this sort of the

888
00:50:08,719 --> 00:50:11,520
Speaker 1: middle ground, sort of calculating how how much you can go,

889
00:50:11,560 --> 00:50:14,080
Speaker 1: how much you can't. Yeah, it's like, oh, you get

890
00:50:14,160 --> 00:50:16,600
Speaker 1: impaled by an iron bar, Well, let's replace that with

891
00:50:16,640 --> 00:50:19,439
Speaker 1: a slightly smaller iron bar. Don't you feel better now?

892
00:50:19,520 --> 00:50:24,040
Speaker 1: It looks far smaller. It does look smaller, it feels smaller. UM.

893
00:50:24,080 --> 00:50:26,080
Speaker 1: So the cash bail is interesting. UM. She does she

894
00:50:26,120 --> 00:50:29,319
Speaker 1: wants to get rid of mandatory minimum sentencing. So that's

895
00:50:29,360 --> 00:50:31,680
Speaker 1: something where it's like, no, we should get rid of this. UM.

896
00:50:31,719 --> 00:50:35,320
Speaker 1: So I want to give her a little credit where UM.

897
00:50:35,440 --> 00:50:38,680
Speaker 1: One thing she does want to end is private prisons now,

898
00:50:39,360 --> 00:50:42,759
Speaker 1: although as we sort of talk about UM, it does

899
00:50:42,800 --> 00:50:45,520
Speaker 1: seem like she doesn't necessarily want to do that because

900
00:50:45,560 --> 00:50:50,760
Speaker 1: of all the free labor that you can get from prisons. UM.

901
00:50:50,840 --> 00:50:53,920
Speaker 1: And she's been criticized in the past UM for not

902
00:50:54,040 --> 00:50:57,399
Speaker 1: using her position as a g to oppose Governor Jerry

903
00:50:57,440 --> 00:51:00,360
Speaker 1: Brown UM in response to a prison over crowding he

904
00:51:00,400 --> 00:51:03,960
Speaker 1: wanted to move inmates to private prisons, and she did

905
00:51:03,960 --> 00:51:08,000
Speaker 1: not fight back on that. Um. So again little inconsistency

906
00:51:08,040 --> 00:51:12,520
Speaker 1: seems to be sort of calculated. Um and uh, I

907
00:51:12,560 --> 00:51:15,719
Speaker 1: just wanted to bring up this thing with the firefighting

908
00:51:16,400 --> 00:51:22,080
Speaker 1: because when you have that and that happened and you're

909
00:51:22,120 --> 00:51:25,120
Speaker 1: talking about things like, you know, she's supportive of things

910
00:51:25,120 --> 00:51:27,560
Speaker 1: like the Green New Deal vaguely not like not specifically

911
00:51:27,560 --> 00:51:29,480
Speaker 1: the Green New Deal, but we're talking about that and

912
00:51:29,520 --> 00:51:31,560
Speaker 1: all the sort of work that needs to be done,

913
00:51:31,880 --> 00:51:34,319
Speaker 1: it sort of makes you wonder, like where where is

914
00:51:34,320 --> 00:51:37,640
Speaker 1: that labor going to come from from? Somebody who has

915
00:51:37,760 --> 00:51:42,560
Speaker 1: uh supported keeping people in prison because of the free

916
00:51:42,640 --> 00:51:48,319
Speaker 1: labor that it offers us. Um. Yeah, yeah, It's one

917
00:51:48,360 --> 00:51:50,680
Speaker 1: of those things when you when I look at like

918
00:51:50,760 --> 00:51:54,080
Speaker 1: okay if um, you know again its new secret. Like

919
00:51:54,120 --> 00:51:56,440
Speaker 1: my my my top pick would be Bernie Sanders. I

920
00:51:56,440 --> 00:51:58,840
Speaker 1: think my two would be Warren. If I think about

921
00:51:59,200 --> 00:52:02,560
Speaker 1: who I would prefer outside of those, I'm not saying

922
00:52:02,680 --> 00:52:06,600
Speaker 1: Kamala's top of that list. She's someone who I don't

923
00:52:06,640 --> 00:52:09,600
Speaker 1: trust to make principle moral stances, and I don't trust

924
00:52:09,680 --> 00:52:12,759
Speaker 1: to take on her own serious action for things that

925
00:52:12,800 --> 00:52:16,480
Speaker 1: are are immediately necessary. Like massive sweeping criminal justice reform,

926
00:52:16,520 --> 00:52:22,000
Speaker 1: like climate change legislation. Um. I do trust that she's

927
00:52:22,040 --> 00:52:24,239
Speaker 1: someone who wants to be elected enough that is there,

928
00:52:24,280 --> 00:52:28,239
Speaker 1: if there is a sustained and large scale campaign to

929
00:52:28,360 --> 00:52:31,440
Speaker 1: push those things, she will do what she thinks is popular.

930
00:52:31,520 --> 00:52:34,600
Speaker 1: And and that that's not a negative when you compared

931
00:52:34,680 --> 00:52:36,799
Speaker 1: to where we are right now, where no action will

932
00:52:36,800 --> 00:52:42,680
Speaker 1: ever be to politician, a liberal politician. Yeah, yeah, exactly exactly. Um,

933
00:52:42,719 --> 00:52:47,120
Speaker 1: but like, yeah, also, it's it's a bummer to be

934
00:52:47,280 --> 00:52:48,839
Speaker 1: like to be at that point where it's like, well,

935
00:52:49,520 --> 00:52:51,480
Speaker 1: at least this person will stand up for what's right

936
00:52:51,560 --> 00:52:55,120
Speaker 1: if millions of people protest in favor of it. Yeah,

937
00:52:55,200 --> 00:52:59,240
Speaker 1: if we shame her into action, she will take action. Yeah,

938
00:52:59,760 --> 00:53:04,040
Speaker 1: which is not the worst case scenario. No, it's not. There.

939
00:53:04,120 --> 00:53:10,640
Speaker 1: Certainly have been presidents that you can't say the same before. Um. Yes,

940
00:53:10,800 --> 00:53:12,719
Speaker 1: you know, I've heard a lot of people when they

941
00:53:12,719 --> 00:53:15,360
Speaker 1: talk about why they want Kamala or at least before,

942
00:53:15,680 --> 00:53:18,760
Speaker 1: is that they want to see her on a debate

943
00:53:18,880 --> 00:53:22,960
Speaker 1: stage with Donald Trump. And I get the appeal of that,

944
00:53:23,080 --> 00:53:24,799
Speaker 1: but well, first of all, I don't know if Donald

945
00:53:24,800 --> 00:53:27,200
Speaker 1: Trump would show up for a debate with Kamala Harris,

946
00:53:27,560 --> 00:53:29,920
Speaker 1: but also that Donald Trump would show up for a

947
00:53:29,960 --> 00:53:33,800
Speaker 1: debate with any one. Why would Yeah, what would he

948
00:53:33,840 --> 00:53:35,880
Speaker 1: have to gain from it? Yeah, maybe he had nothing

949
00:53:35,880 --> 00:53:38,040
Speaker 1: to lose, nothing to gain, he would just not do it,

950
00:53:38,080 --> 00:53:42,480
Speaker 1: would be exactly as he is. But I know my

951
00:53:42,600 --> 00:53:45,160
Speaker 1: college shot here is that he will say something along

952
00:53:45,200 --> 00:53:47,560
Speaker 1: the lines of I think my record for president speaks

953
00:53:47,560 --> 00:53:49,399
Speaker 1: for itself, and I have no need to debate an

954
00:53:49,400 --> 00:53:53,439
Speaker 1: opponents ever had a story. Maybe I'll be wrong. I'm

955
00:53:53,480 --> 00:53:55,680
Speaker 1: just I am excited to see her question him in

956
00:53:55,719 --> 00:54:00,080
Speaker 1: an appeachment hearing or something that actually she's great in

957
00:54:00,719 --> 00:54:04,239
Speaker 1: prositutor exactly. Um. I look forward to a bunch of

958
00:54:04,320 --> 00:54:08,680
Speaker 1: lawyers who are now senators doing that in the court. Um.

959
00:54:08,719 --> 00:54:12,080
Speaker 1: I think that desiring that, aside from whether or not

960
00:54:12,280 --> 00:54:14,600
Speaker 1: he's going to show up, is a silly reason to

961
00:54:14,680 --> 00:54:18,239
Speaker 1: want somebody to be the president. Yes, I guess what's

962
00:54:18,239 --> 00:54:20,759
Speaker 1: going to happen when those debates are over in the

963
00:54:20,840 --> 00:54:27,759
Speaker 1: elections over us? Yeah, And I kind of think debating

964
00:54:27,920 --> 00:54:31,240
Speaker 1: is a lot like actually running for for public office.

965
00:54:31,320 --> 00:54:33,520
Speaker 1: And I think this is something I did debate, um

966
00:54:33,560 --> 00:54:36,000
Speaker 1: for basically all of high school, and I was uh

967
00:54:36,080 --> 00:54:37,319
Speaker 1: not the best at it, but I made it to

968
00:54:37,400 --> 00:54:39,480
Speaker 1: nationals one year and I was I was like very

969
00:54:39,520 --> 00:54:41,440
Speaker 1: highly ranked within my state. I was good at it.

970
00:54:41,920 --> 00:54:45,560
Speaker 1: And Um. One of the things, the good thing that

971
00:54:45,640 --> 00:54:47,799
Speaker 1: you do that speech and debate teaches you is how

972
00:54:47,800 --> 00:54:49,920
Speaker 1: to make an affirmative in a negative argument. But I

973
00:54:49,920 --> 00:54:51,960
Speaker 1: think it is always a helpful thing whenever you're trying

974
00:54:52,000 --> 00:54:54,120
Speaker 1: to understand an issue is to figure out the best

975
00:54:54,120 --> 00:54:55,960
Speaker 1: case for and against it and then sort of like

976
00:54:56,000 --> 00:54:58,040
Speaker 1: you can. That is one way you can arrive at truth.

977
00:54:58,480 --> 00:55:01,279
Speaker 1: The downside is that UM, and this is something you'll

978
00:55:01,320 --> 00:55:03,600
Speaker 1: see with allse like Ben Shapiro, one of the real

979
00:55:03,680 --> 00:55:05,960
Speaker 1: easy ways to win is to just lie or twist

980
00:55:06,000 --> 00:55:07,840
Speaker 1: the facts in a way that you know your opponent

981
00:55:07,840 --> 00:55:10,400
Speaker 1: won't be ready to counter, because all that matters is

982
00:55:10,440 --> 00:55:13,839
Speaker 1: actually scoring points in the moment. An objective truth has

983
00:55:13,920 --> 00:55:17,120
Speaker 1: nothing to do with winning a debate, And it's sort

984
00:55:17,120 --> 00:55:20,640
Speaker 1: of similar to running for office, where taking a stance

985
00:55:20,680 --> 00:55:23,799
Speaker 1: that wins the argument is often better than taking a

986
00:55:23,840 --> 00:55:26,279
Speaker 1: stance that is the right thing, Which is why I

987
00:55:26,800 --> 00:55:29,759
Speaker 1: get I don't, I don't. I don't like um did

988
00:55:30,280 --> 00:55:35,000
Speaker 1: bates per Se? I like, yeah, it's not value And

989
00:55:35,080 --> 00:55:37,919
Speaker 1: having all the candidates talk and argue their points, but

990
00:55:38,280 --> 00:55:43,000
Speaker 1: especially debates between politicians who are seasoned doing that specifically,

991
00:55:43,120 --> 00:55:44,880
Speaker 1: it's like, well, what do you actually believe? Oh, I

992
00:55:44,920 --> 00:55:47,319
Speaker 1: can actually look at your record of That's why so

993
00:55:47,400 --> 00:55:50,320
Speaker 1: many people are more drawn to Bernie and to Warren.

994
00:55:51,160 --> 00:55:56,399
Speaker 1: H yeah, if not many, if we're looking, but why Yeah,

995
00:55:57,760 --> 00:56:00,000
Speaker 1: but that that is the appeal of those two candidates.

996
00:56:00,000 --> 00:56:05,440
Speaker 1: It's why an elderly, wild haired socialist has become one

997
00:56:05,480 --> 00:56:09,120
Speaker 1: of those popular politicians in the country for basically shouting

998
00:56:09,200 --> 00:56:17,239
Speaker 1: numbers at people for the last six years. Yeah, yeah, yeah, yeah,

999
00:56:17,280 --> 00:56:22,280
Speaker 1: he's Um, it's why you can It's why after six years, Uh,

1000
00:56:22,560 --> 00:56:26,919
Speaker 1: everybody is saying healthcare is a human right. Yes, yes,

1001
00:56:26,920 --> 00:56:28,520
Speaker 1: because you say it over and over because you believe it,

1002
00:56:28,560 --> 00:56:31,000
Speaker 1: then everyone else will yeah catch on the history books

1003
00:56:31,000 --> 00:56:34,640
Speaker 1: will love it no matter what happens. That is true. Um,

1004
00:56:34,640 --> 00:56:37,520
Speaker 1: he's a lovable man. Um. Happy birthday whenever your birthday

1005
00:56:37,560 --> 00:56:41,239
Speaker 1: is Bernie. Uh. Speak of healthcare, we talk about this

1006
00:56:41,320 --> 00:56:43,760
Speaker 1: a lot. We talk about Medicare for all on this show.

1007
00:56:43,840 --> 00:56:46,160
Speaker 1: And because that's I think gonna be a large part

1008
00:56:46,160 --> 00:56:50,200
Speaker 1: of the alleged debate UM going forward, and it's definitely

1009
00:56:50,440 --> 00:56:56,000
Speaker 1: UH debate topic amongst the candidates for the Democratic primary. UM,

1010
00:56:56,120 --> 00:57:00,160
Speaker 1: and I think just sort of to color uh, what

1011
00:57:00,280 --> 00:57:03,640
Speaker 1: we've been talking about in this history. Kamala was one

1012
00:57:03,640 --> 00:57:06,800
Speaker 1: of the first people, UH to come out in favor

1013
00:57:07,040 --> 00:57:11,160
Speaker 1: of Bernie Sanders Medicare for all plans. She ran an

1014
00:57:11,200 --> 00:57:14,320
Speaker 1: ad in August. I was proud to be the first

1015
00:57:14,360 --> 00:57:16,560
Speaker 1: Senate Democrat to come out and support of Bernie Sanders

1016
00:57:16,600 --> 00:57:19,080
Speaker 1: Medicare for all. Bill. UM. It is absurd that we

1017
00:57:19,120 --> 00:57:21,440
Speaker 1: are the only major industrialized nation in the world not

1018
00:57:21,480 --> 00:57:24,000
Speaker 1: to guarantee health care to all people. At your name

1019
00:57:24,000 --> 00:57:26,520
Speaker 1: if you agree it's not for Medicare for all, UM,

1020
00:57:26,560 --> 00:57:28,920
Speaker 1: and UH, that is true. She came out, there was

1021
00:57:28,960 --> 00:57:31,040
Speaker 1: a big press conference, you can see all the different

1022
00:57:31,080 --> 00:57:35,000
Speaker 1: senators who support that UM. And since then she has

1023
00:57:35,560 --> 00:57:40,520
Speaker 1: slowly drifted away from that. UM. At a large donor

1024
00:57:42,280 --> 00:57:46,400
Speaker 1: fundraiser UM in the Hampton's of all places, UM, she

1025
00:57:46,480 --> 00:57:50,000
Speaker 1: was heard to UH have said, uh she had not

1026
00:57:50,120 --> 00:57:55,640
Speaker 1: been comfortable with Bernie's plan. And so that sort of

1027
00:57:56,200 --> 00:58:00,000
Speaker 1: UH has driven us to where she is now, UM,

1028
00:58:00,040 --> 00:58:02,240
Speaker 1: which is calling it medicare for all. UM. I will

1029
00:58:02,280 --> 00:58:04,760
Speaker 1: I will say it's it is better than like a

1030
00:58:04,760 --> 00:58:07,600
Speaker 1: Pete Buddha Jedge, who was like medicare for all who wanted,

1031
00:58:07,720 --> 00:58:11,600
Speaker 1: or medicare if you sign you know, that kind of thing. Um,

1032
00:58:11,960 --> 00:58:15,800
Speaker 1: So she's not that far from it, but it is

1033
00:58:16,120 --> 00:58:18,240
Speaker 1: a she. I think she would call it a middle

1034
00:58:18,280 --> 00:58:23,440
Speaker 1: ground attempt at a medicare plan um that includes private insurance.

1035
00:58:23,600 --> 00:58:28,400
Speaker 1: Still um, which, I'm surprised that she changed your opinion.

1036
00:58:28,440 --> 00:58:31,040
Speaker 1: Surprised she changed your opinion. I wonder if it's from

1037
00:58:31,440 --> 00:58:34,600
Speaker 1: uh maybe donors from like the farming industry and things

1038
00:58:34,640 --> 00:58:38,960
Speaker 1: like that, and just sort of sort of that calculation. Cody,

1039
00:58:39,360 --> 00:58:43,400
Speaker 1: this is not a conspiracy theory podcast, and your crackpot

1040
00:58:43,520 --> 00:58:50,120
Speaker 1: theories about money influencing politics are not welcome here. Okay, okay, okay,

1041
00:58:50,240 --> 00:58:56,880
Speaker 1: I good luck with the podcast everybody. Now we're bringing

1042
00:58:56,920 --> 00:58:59,200
Speaker 1: in the dog from Frasier. We are bringing in the

1043
00:58:59,240 --> 00:59:02,240
Speaker 1: dog from Fraser. This is the Fraser Castle. Can please,

1044
00:59:02,400 --> 00:59:12,520
Speaker 1: Oh Robert, that dogs dead? Oh God out the dog

1045
00:59:12,560 --> 00:59:14,320
Speaker 1: that they got to play the dog after the first

1046
00:59:14,320 --> 00:59:16,840
Speaker 1: dog died is probably dead. Well, I mean, I I

1047
00:59:17,000 --> 00:59:19,840
Speaker 1: heart does keep a witch doctor on staff? Um. Oh,

1048
00:59:19,880 --> 00:59:23,200
Speaker 1: I'm back on the pod. Make I desperately need a

1049
00:59:23,200 --> 00:59:27,880
Speaker 1: witch doctor. Why don't we finish this episode? You're back

1050
00:59:27,920 --> 00:59:29,640
Speaker 1: on the pod. Yeah, and we don't have to get

1051
00:59:29,640 --> 00:59:33,280
Speaker 1: into it too much. It's just that the uh, the

1052
00:59:33,320 --> 00:59:36,200
Speaker 1: comparison of now too earlier. It does seem like she

1053
00:59:36,280 --> 00:59:38,640
Speaker 1: sort of jumped on the bandwagon as it was very,

1054
00:59:38,760 --> 00:59:41,040
Speaker 1: very popular, and she wanted to be the first on

1055
00:59:41,120 --> 00:59:43,439
Speaker 1: there to sort of get those ads out early on

1056
00:59:43,840 --> 00:59:46,439
Speaker 1: and maybe get like an email like a donor list

1057
00:59:46,440 --> 00:59:48,600
Speaker 1: and get get sort of her name and get the

1058
00:59:48,640 --> 00:59:51,960
Speaker 1: access and sort of build her brand up and then

1059
00:59:52,240 --> 00:59:54,120
Speaker 1: distance herself and be like, well, also, prevent sure is

1060
00:59:54,120 --> 00:59:59,400
Speaker 1: really good. We don't lose that. Um So, uh, that's

1061
00:59:59,440 --> 01:00:02,040
Speaker 1: just something to think about, thinking about it, just something

1062
01:00:02,200 --> 01:00:05,640
Speaker 1: to think about. I love thinking. I'm tired of it.

1063
01:00:06,360 --> 01:00:12,840
Speaker 1: I'm middle ground. I'm feeling Kamala about it. Well, that

1064
01:00:12,920 --> 01:00:16,800
Speaker 1: was pretty interesting. We learned a lot today. Yeah. I

1065
01:00:16,840 --> 01:00:18,760
Speaker 1: went through like sort of an arc as I was

1066
01:00:18,840 --> 01:00:21,840
Speaker 1: reading about Kamala's time as a g where like I

1067
01:00:22,160 --> 01:00:25,120
Speaker 1: started reading like some of those Advocate articles more positive

1068
01:00:25,160 --> 01:00:26,560
Speaker 1: pointed out you know, she did a lot of really

1069
01:00:26,560 --> 01:00:29,320
Speaker 1: good stuff for LGBT people that like was not common

1070
01:00:29,320 --> 01:00:31,800
Speaker 1: in that period for someone in your position to do.

1071
01:00:32,080 --> 01:00:33,919
Speaker 1: And I was like, maybe maybe I got this ship wrong,

1072
01:00:34,120 --> 01:00:36,760
Speaker 1: Like maybe being unfair to her and then like it's

1073
01:00:36,800 --> 01:00:39,040
Speaker 1: it's like this parabola of like hitting a certain point

1074
01:00:39,120 --> 01:00:42,320
Speaker 1: and then hitting like the right articles be like oh no, no,

1075
01:00:43,520 --> 01:00:47,960
Speaker 1: it was a real whirlwind, a roller coaster ride. Is

1076
01:00:48,040 --> 01:00:51,640
Speaker 1: digging through it, you're like okay, oh okay. Well, I

1077
01:00:51,680 --> 01:00:55,880
Speaker 1: think that's also like if you're calculated and you're trying

1078
01:00:55,880 --> 01:00:57,480
Speaker 1: to do the middle ground, you're trying to please these

1079
01:00:57,480 --> 01:00:59,240
Speaker 1: people at the time is right and these people and

1080
01:00:59,280 --> 01:01:01,720
Speaker 1: the other times, then you're going to have that journey.

1081
01:01:01,920 --> 01:01:04,000
Speaker 1: And I guess that's also why going back to what

1082
01:01:04,040 --> 01:01:07,120
Speaker 1: I said at the beginning about her relationship with Willie

1083
01:01:07,160 --> 01:01:12,439
Speaker 1: Brown and the criticism she's received, is like, yeah, again,

1084
01:01:12,480 --> 01:01:14,440
Speaker 1: she had to start this one was a politician and

1085
01:01:14,480 --> 01:01:18,040
Speaker 1: she's smart. She's maneuvered her way through this, and you

1086
01:01:18,160 --> 01:01:20,800
Speaker 1: can't you can't take a give you can't give credit

1087
01:01:20,840 --> 01:01:23,360
Speaker 1: to him for this career that she's I mean, listen

1088
01:01:23,400 --> 01:01:28,880
Speaker 1: to her answer about the transgender prison stuff. No, that's

1089
01:01:28,880 --> 01:01:34,320
Speaker 1: a politician answering, Oh my god, yeah, yeah, yeah, sir.

1090
01:01:34,400 --> 01:01:37,600
Speaker 1: Were you were you drunk driving when you ran into

1091
01:01:37,640 --> 01:01:40,840
Speaker 1: that family of elderly people walking down the street. Well,

1092
01:01:40,880 --> 01:01:42,960
Speaker 1: you know, I think drunk driving is a real problem,

1093
01:01:43,000 --> 01:01:44,960
Speaker 1: and I think we need to look seriously both the

1094
01:01:45,040 --> 01:01:48,480
Speaker 1: societal and the personal emotional causes of such things. And

1095
01:01:48,640 --> 01:01:50,600
Speaker 1: I really think we we have to treat it like

1096
01:01:50,640 --> 01:01:52,840
Speaker 1: the problem that it is. Now, Will you help me

1097
01:01:52,880 --> 01:01:55,080
Speaker 1: pull this corpse out of the grill on my fift

1098
01:01:55,240 --> 01:01:58,000
Speaker 1: before I roll right along? I've got more tequila to drink.

1099
01:01:58,080 --> 01:02:01,600
Speaker 1: Thunderous applause. We need to take a serious look at

1100
01:02:01,600 --> 01:02:08,520
Speaker 1: the safety of cars. Yeah, not wrong. If I didn't

1101
01:02:08,560 --> 01:02:11,160
Speaker 1: hear the question, I'd be like, yeah, I guess so

1102
01:02:12,040 --> 01:02:15,840
Speaker 1: if that was just a random state, Okay, we got

1103
01:02:15,920 --> 01:02:22,320
Speaker 1: to worry about cars, you're right, Yeah, yeah, Kamala Harris

1104
01:02:22,400 --> 01:02:31,800
Speaker 1: pro drunk driving. Yeah, and you're thinking of Betto Betto

1105
01:02:32,080 --> 01:02:38,560
Speaker 1: as he drunkenly skateboards in Calibunga. That's a real problem

1106
01:02:38,560 --> 01:02:41,600
Speaker 1: in America. And I really if if he changed his

1107
01:02:41,960 --> 01:02:46,520
Speaker 1: slogan to just Calibunga, I'd be all in. Although he

1108
01:02:46,520 --> 01:02:50,120
Speaker 1: would Trump Trump would have resigned. Congress would have voted

1109
01:02:50,240 --> 01:02:53,880
Speaker 1: unanimously to make him the president, like Mitch McConnell, like

1110
01:02:53,960 --> 01:02:57,800
Speaker 1: sits back, you know what, yes, yes, everything you want.

1111
01:02:57,960 --> 01:02:59,720
Speaker 1: Trump would have taken off his tie and put it

1112
01:03:00,000 --> 01:03:03,920
Speaker 1: for better I'm sad that before we could do an

1113
01:03:03,920 --> 01:03:11,480
Speaker 1: episode on him my family. I want to ask, in

1114
01:03:11,520 --> 01:03:14,479
Speaker 1: a serious note, if Betto had thought drinking a beer

1115
01:03:14,480 --> 01:03:17,959
Speaker 1: on stage would have won him votes, what what sort

1116
01:03:18,000 --> 01:03:20,200
Speaker 1: of six back with? Because I I go back and

1117
01:03:20,240 --> 01:03:21,880
Speaker 1: forth between what kind of beer he'd have brought out.

1118
01:03:22,120 --> 01:03:23,920
Speaker 1: One end is he would have picked like a super

1119
01:03:24,000 --> 01:03:26,480
Speaker 1: hipstory like I P A or something like like like

1120
01:03:26,560 --> 01:03:28,640
Speaker 1: really niche that he could have been a beer guy about.

1121
01:03:29,000 --> 01:03:30,640
Speaker 1: The other is he would have gone with like the

1122
01:03:30,640 --> 01:03:33,800
Speaker 1: most stereotypically blue collar beer, possibly led out with a

1123
01:03:33,840 --> 01:03:38,400
Speaker 1: Miller like or something like that, one of the water beers. Yeah,

1124
01:03:39,200 --> 01:03:40,520
Speaker 1: part of me thinks he might have gone out with

1125
01:03:40,520 --> 01:03:42,960
Speaker 1: a Texas beer. And if he did, like this is

1126
01:03:42,960 --> 01:03:45,520
Speaker 1: only gonna make sense to Texas people. There's the right

1127
01:03:45,560 --> 01:03:47,320
Speaker 1: answer and the wrong answer. If you roll out on

1128
01:03:47,360 --> 01:03:49,320
Speaker 1: stage with the Texas beer, the right answer is shiner

1129
01:03:49,360 --> 01:03:51,400
Speaker 1: back and the wrong answer is lone Star. And I'm

1130
01:03:51,480 --> 01:03:54,440
Speaker 1: certain he would have done a Lone Star. I'm not

1131
01:03:54,480 --> 01:03:57,720
Speaker 1: from Texas, and I agree with you. Also, Yeah, certain,

1132
01:03:57,920 --> 01:04:00,280
Speaker 1: as someone who has vomited up his body way in

1133
01:04:00,440 --> 01:04:02,880
Speaker 1: both of those beers he would have he would have

1134
01:04:02,960 --> 01:04:04,320
Speaker 1: he would have rolled out with a lone star and

1135
01:04:04,320 --> 01:04:05,480
Speaker 1: he would have been wrong to do it. And this

1136
01:04:05,560 --> 01:04:08,240
Speaker 1: is my stance for the fourteen people from Texas listening

1137
01:04:08,240 --> 01:04:12,600
Speaker 1: to righted It open and been like Kara Berna, I

1138
01:04:12,640 --> 01:04:17,280
Speaker 1: didn't even say it right. You can't even do that, right, yeah, right,

1139
01:04:18,760 --> 01:04:22,439
Speaker 1: all right, guys, this has gone off the rails, real real,

1140
01:04:22,480 --> 01:04:27,200
Speaker 1: well it's this is the worst year ever. But we

1141
01:04:27,240 --> 01:04:30,360
Speaker 1: can make it more tolerable by occasionally laughing about beatos

1142
01:04:30,920 --> 01:04:34,720
Speaker 1: like strange fan fiction. The man is going to bring

1143
01:04:34,800 --> 01:04:37,400
Speaker 1: us all together in He's not going to do anything

1144
01:04:37,480 --> 01:04:41,160
Speaker 1: else from now on. All right, you guys can find

1145
01:04:41,240 --> 01:04:46,160
Speaker 1: us online on Instagram and on Twitter at worst steer Pod,

1146
01:04:47,000 --> 01:04:52,280
Speaker 1: I'm Gatti's stole. Uh say my name, say my name?

1147
01:04:51,760 --> 01:04:55,880
Speaker 1: No name? Thank you, samon name Say that's a song.

1148
01:04:55,920 --> 01:04:58,840
Speaker 1: I know that Destiny's Child. I got it, I got

1149
01:04:58,960 --> 01:05:01,080
Speaker 1: a pop cultures. What is your name that you didn't

1150
01:05:01,080 --> 01:05:05,680
Speaker 1: introduce at the beginning? Beyonce? No wait, no, that's another

1151
01:05:05,760 --> 01:05:08,880
Speaker 1: person from Destiny's Child. I have forgotten that one pop

1152
01:05:08,880 --> 01:05:12,320
Speaker 1: culture piece has erased my identity. Well, I'm so sorry.

1153
01:05:12,320 --> 01:05:14,200
Speaker 1: We'll leave it at that, then, Katie and Cody and

1154
01:05:14,320 --> 01:05:20,200
Speaker 1: co host, Thanks, guys, we'll see you next time. Sign it? Wait? Wait?

1155
01:05:20,240 --> 01:05:21,920
Speaker 1: Should we? Should we tell them where to find us

1156
01:05:21,960 --> 01:05:25,200
Speaker 1: on the internet dot com? I did? Oh, I forgot

1157
01:05:25,240 --> 01:05:32,840
Speaker 1: that because I remember to see well, look forward to

1158
01:05:32,880 --> 01:05:34,760
Speaker 1: the rest of this year. Well I where I really

1159
01:05:34,840 --> 01:05:41,400
Speaker 1: learned how to walk? Who's the president right now? Beyond

1160
01:05:42,360 --> 01:05:56,320
Speaker 1: nailed it? Yes, I tried. Worst Year Ever is a

1161
01:05:56,320 --> 01:05:59,000
Speaker 1: production of I Heart Radio. For more podcasts from my

1162
01:05:59,080 --> 01:06:02,120
Speaker 1: heart Radio, visit the I heart Radio app, Apple Podcasts,

1163
01:06:02,200 --> 01:06:04,080
Speaker 1: or wherever you listen to your favorite shows.