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Speaker 1: I've been watching this case out of Moscow, Idaho, home

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Speaker 1: of Idaho State where four students were stabbed and murdered.

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Speaker 1: We maybe even in their sleep. Back in November. We

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Speaker 1: didn't know a whole lot about what was going on

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Speaker 1: with the case, but the police and the FBI were

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Speaker 1: on it and they were making breakthroughs along the way.

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Speaker 1: Joining us to tell us about those breakthroughs and how

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Speaker 1: they did it is our ABCNIS correspondent Alex Stone. Alex

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Speaker 1: always going to talk to you, my friend in Happy

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Speaker 1: New Years. What's the latest here out of this case

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Speaker 1: that went from Idaho to Pennsylvania.

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Speaker 2: Yeah, hey, Chris, Happy New Year to you as well.

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Speaker 2: And you remember for so many weeks now, and we've

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Speaker 2: talked about it with John and Ken and Nay. Yeah,

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Speaker 2: it was what is going on that it didn't seem

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Speaker 2: like police really were going anywhere in this and family

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Speaker 2: members of the victims they were worried that it was

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Speaker 2: going cold, and by many accounts it was somewhat that

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Speaker 2: they didn't have a lot of leads, but they got

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Speaker 2: a DNA match and they were able to work that.

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Speaker 2: The last week all of this broke open and then

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Speaker 2: they were able to make the arrest on Friday, and

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Speaker 2: what we know and a couple of things that we've

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Speaker 2: been learning today. So not only was it DNA, but

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Speaker 2: they used public genealogy databases to find him. So this

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Speaker 2: is one of those where it seems at the moment,

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Speaker 2: according to law enforcement sources, that they had a piece

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Speaker 2: of DNA that maybe a week two weeks ago they

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Speaker 2: got to hit back on from the lab, but they

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Speaker 2: didn't know who had belonged to that there was somebody

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Speaker 2: unknown there, and they went to those public genealogy databases

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Speaker 2: that we know more and more about that investigators have

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Speaker 2: been using and either found Brian Coberger, the twenty eight

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Speaker 2: year old accused killer now, or a family member, and

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Speaker 2: then they worked it from the family member they knew

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Speaker 2: somebody was related and then said, well, this somebody lives

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Speaker 2: very nearby, and then worked it from there and this

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Speaker 2: somebody he has a white Lantra that they had been

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Speaker 2: looking for for many weeks, and then they were able

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Speaker 2: to make the arrest, and the police chief in Moscow,

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Speaker 2: Idaho telling our team this right now, saying this is

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Speaker 2: their only guy. They think he acted alone, that he

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Speaker 2: is their only killer, and they believe they have the

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Speaker 2: right person, saying.

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Speaker 3: We believe we have our guy, the one that committed

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Speaker 3: these murders.

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Speaker 2: So we know that the FBI, we learned today as well,

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Speaker 2: surveiled the Coburger family home for four days last week

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Speaker 2: before they moved in and made the arrest on Friday,

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Speaker 2: and that they had been watching him. Did he go anywhere,

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Speaker 2: did he try to hide anything? And the white Lantro

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Speaker 2: was parked out front. The chief telling us during that

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Speaker 2: time when he knew an arrest was coming, but had

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Speaker 2: to act like nothing was going on during that time,

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Speaker 2: he says.

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Speaker 3: It's stressful. You knew that this individual was out there somewhere,

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Speaker 3: We knew that there was going to be interest made

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Speaker 3: in Pennsylvania. That still, even though we're here, stressful here.

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Speaker 2: Yeah, he says, I can't believe that they got there. So, Chris,

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Speaker 2: you know, now we're hearing a lot about this guy.

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Speaker 2: That criminology was what he was going for in his PhD.

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Speaker 2: Friends going back to high school say he had been

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Speaker 2: super into crime and the mind of a killer and

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Speaker 2: serial killers and all that kind of stuff. Was that

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Speaker 2: the motive in this Police don't seem to know yet,

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Speaker 2: they say just based on the circumstances that they still

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Speaker 2: believe it was targeted. But did he target the victims

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Speaker 2: because you know, he was interested in somebody. Was it

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Speaker 2: that they were targeted based on, you know, blonde haired women.

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Speaker 2: They don't know. Was this something that was personal or

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Speaker 2: was it more the mind of a serial killer and

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Speaker 2: criminology that he was going through. They don't know.

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Speaker 1: Yeah, those are the questions I suppose, Alex Downer, this

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Speaker 1: correspondent that that we're looking for answers to because it seemed,

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Speaker 1: at least early on in the investigation, the police thought

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Speaker 1: that the killer knew these people and was targeting somebody.

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Speaker 1: They said it was a targeted attack. So you know

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Speaker 1: what is the relationship is going to be tough. Can

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Speaker 1: we let's talk about that white Lantra because we did

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Speaker 1: hear a bit about that white Alantra for a while.

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Speaker 1: Was it it was a gas station clerk? Is my

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Speaker 1: understanding that was that was reviewing some security cam footage,

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Speaker 1: just bored and decided to review security cam footage and

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Speaker 1: brought that to the attention of the police.

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Speaker 2: Yeah, many weeks ago they had already they were on

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Speaker 2: the case of that they were looking for potentially a

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Speaker 2: wide Lantra in the area. And then they got, for

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Speaker 2: whatever reason, a little bit more firm on that they

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Speaker 2: wanted to track down whoever was in there because they

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Speaker 2: thought that they had some information. Not saying it was

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Speaker 2: a killer, but they knew something. And then that gas

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Speaker 2: station about a mile away from the crime scene about

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Speaker 2: two three weeks ago go saw the a white Lantra

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Speaker 2: that they thought was an Alantra driving by on the street.

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Speaker 2: But again he was all very circumstantial, very general of

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Speaker 2: he was in the area. You know, maybe it had

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Speaker 2: been a newspaper delivery person, you know, driving by, could

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Speaker 2: have been an uber. Police though they had something to

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Speaker 2: make them believe that there was more to it than that.

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Speaker 2: That is the vehicle that they found in Pennsylvania. That

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Speaker 2: is a vehicle. We now know that that Coburger and

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Speaker 2: his father drove cross country and drove to Pennsylvania in

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Speaker 2: mid December on a pre planned road trip to go

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Speaker 2: home for a Christmas break. That his dad apparently had

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Speaker 2: no idea that his son was allegedly involved in this.

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Speaker 2: And here is the public defender, Coburger's public defender telling

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Speaker 2: us this today.

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Speaker 3: Driving across country approximately too and a half, Dade and

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Speaker 3: it recovered. I was acting normal back.

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Speaker 2: Yeah, acting totally normal during it. And we found out

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Speaker 2: to confirm through him about five minutes ago that they

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Speaker 2: were pulled over twice in Indiana, once for tailgating and

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Speaker 2: once for speeding. They were pulled over about an hour

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Speaker 2: apart from two different state troopers, and at that time

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Speaker 2: he was not a suspect. On December thirteenth, they did

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Speaker 2: not yet know that they had somebody, and they had

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Speaker 2: not tracked him down. Those troopers pulled him over had

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Speaker 2: no idea that this guy was suspected of killing four

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Speaker 2: college students. They warned him, they ticketed them, and then

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Speaker 2: then they went.

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Speaker 1: On, Yeah, nobody likes getting pulled over twice in one day.

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Speaker 1: That's a bit bizarre, especially when we find out that

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Speaker 1: it may be somebody who was involved in these murders

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Speaker 1: after the fact.

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Speaker 2: Obviously it was totally just by chance. I mean, can

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Speaker 2: you imagine you would assume, I mean, I don't know

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Speaker 2: the mindset of Coburger, but you would imagine that you'd

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Speaker 2: be sweating that out. Maybe he wasn't, but you'd be

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Speaker 2: thinking that they're on me. But but they apparently were

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Speaker 2: not so.

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Speaker 1: Alex Jones our ABC News correspondent when we find out

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Speaker 1: the FBI had been keeping tabs on him for about

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Speaker 1: four days. As as you mentioned, Alex, do we know

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Speaker 1: if the FBI was trying to collect any trash or

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Speaker 1: other evidence that might have DNA. I'm thinking back to

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Speaker 1: that Golden State killer case. That was really the first

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Speaker 1: one I know of where they were able to use

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Speaker 1: familial DNA to crack the case open, and they, as

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Speaker 1: I recall, I think they waited around for him to

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Speaker 1: leave a Starbucks cup or something behind. Do we know

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Speaker 1: if the FBI had collected any other evidence like that.

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Speaker 2: You know, it wouldn't be surprising. We don't know the

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Speaker 2: details of the surveillance that they did, the detail that

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Speaker 2: they were doing on them. They probably did if they

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Speaker 2: were able to, But as it was described to us

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Speaker 2: that they were watching him, Yeah, they wanted to see

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Speaker 2: did he try to hide that Alantra, Did he go

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Speaker 2: out and do anything? They want to know more about

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Speaker 2: this guy, and police admit they don't know much about him.

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Speaker 2: They're looking into his criminology group back at the University

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Speaker 2: of Washington, just over the border from Idaho, where he's

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Speaker 2: a PhD student. Has he done anything else. Does he

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Speaker 2: have a history of anything else? You know, is this

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Speaker 2: the latest in in other crimes that that he had

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Speaker 2: committed friends? You know, again, they say he'd been really

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Speaker 2: into this stuff where he had been a TA students

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Speaker 2: say he was a really hard greater, would not make

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Speaker 2: eye contact with him very much, but had loosened up

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Speaker 2: in recent weeks since the murders and become much looser

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Speaker 2: in class and an easier greater. So whatever all that means,

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Speaker 2: and then you're hearing it, yeah, all the yeah, all

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Speaker 2: the the friends who I mean, like this woman, she's

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Speaker 2: known him for a long time and it was just.

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Speaker 3: A shock because there's seven billion people.

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Speaker 2: In this world and it just happened to be him.

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Speaker 3: He was always nice to.

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Speaker 2: Maybe not for other people. Other people say he had

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Speaker 2: been aggressive towards them. Jack Bayliss has known him forever,

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Speaker 2: but they grew up in Pennsylvania together, so he's.

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Speaker 3: Been curious to how the human mind works, to guess

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Speaker 3: and so just as relates to crimes to coloninels.

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Speaker 2: But he says he was an overall a nice guy.

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Speaker 3: He's pently fromly nice, fear around talk, you know, grandtelligent person.

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Speaker 2: So they're trying to piece all of it together and who, why,

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Speaker 2: how they still don't have the murder weapon, We don't

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Speaker 2: know of a motive. Now he's going to be in

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Speaker 2: court tomorrow afternoon in Pennsylvania. His attorney says he is

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Speaker 2: not going to fight extradition, So we'll go right back

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Speaker 2: to Idaho. Once he is in court. In Idaho, under

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Speaker 2: state law, they will unseal all of the court documents

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Speaker 2: describing what police know the probable cause to make the arrest,

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Speaker 2: something that we don't typically see in California, but in

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Speaker 2: some states we do, Arizona, we do Idaho, we do.

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Speaker 2: Then that unseals everything and we'll know a lot more

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Speaker 2: about exactly how they what led them to the way

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Speaker 2: to Lantra and to him, and what they think he

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Speaker 2: was doing, and maybe motive all of that. So maybe

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Speaker 2: as early as tomorrow, maybe Wednesday, maybe Thursday, we should

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Speaker 2: know a lot more.

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Speaker 1: Yeah. I'm the only thing that that I get hung

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Speaker 1: up on here is the people saying, well, he was

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Speaker 1: always interested in serial killers, and I thought, well, the

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Speaker 1: biggest streaming show on Netflix last year was the Damer

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Speaker 1: Show and investigation Discovery makes a whole lot of money

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Speaker 1: talking about true crime. So there's an awful lot of people

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Speaker 1: that are interested in true crime. But then where's that

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Speaker 1: line right from a passing interest too? I guess you know,

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Speaker 1: maybe this guy was studying how to get away with.

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Speaker 2: It and that ically, Yeah, I mean, you know, was

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Speaker 2: it the you know, dexter kind of stuff going on,

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Speaker 2: and it was it? You know, it was he Jeff

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Speaker 2: kind of interested, you know, the date line effect or

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Speaker 2: true crime podcast that sort of thing. Or was it

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Speaker 2: where he was enamored by it and wanted to carry

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Speaker 2: out something we don't know? And then you would seem

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Speaker 2: police don't know either, but friends want after another saying

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Speaker 2: that even going back to not just college but high

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Speaker 2: school as well, that he was really really into it.

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Speaker 1: All right, Alex Stone is there. Abscenis correspondent. Alex, thank

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Speaker 1: you so much for studying this case and updating us.

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Speaker 1: Always a pleasure talking to you. Happen here.

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Speaker 2: You're my friend, you too, sounds good?

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Speaker 1: Thanks for all right, buddy. You know, Alex was talking

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Speaker 1: about this technique that we saw that they used, this

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Speaker 1: this genealogical or forensic DNA that they were using. A

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Speaker 1: lot of people don't really understand how this works. I

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Speaker 1: want to dive into this in just a few moments

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Speaker 1: and also tell you how some companies are starting to

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Speaker 1: make Boku bucks on it. That's next. Chris Merrill in

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Speaker 1: for John and Ken KF. I am six forty. We're

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Speaker 1: live everywhere in your iHeart ready. W APP just talked

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Speaker 1: with Alex stone or Absinos correspondent about the students, the

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Speaker 1: Idaho State University students that were slain back in early November.

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Speaker 1: The arrest of the suspect, Brian Coberger. They think that

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Speaker 1: might be the guy, and how they came to that

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Speaker 1: arrest seems to be reliant on some evidence regarding this

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Speaker 1: white Hondai lantra that they think he drove across the

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Speaker 1: country that may have been in the area that they

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Speaker 1: were saying, Hey, you know, keep your eyes peeled for

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Speaker 1: this white lantra. Maybe it has something to do with it.

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Speaker 1: We're not sure. But then we find out that it

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Speaker 1: was forensic DNA, specifically forensic genealogical DNA that may have

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Speaker 1: brought them to this suspect. Just a little bit on this,

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Speaker 1: I want to give you the report first on News

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Speaker 1: Nation has been covering this like mad Chris Cuomo was

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Speaker 1: talking with an expert about family DNA, but as I'm

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Speaker 1: listening to this interview, I don't think Chris Cuomo really

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Speaker 1: understands it. Go ahead and play this guy, the Idaho

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Speaker 1: suspect DNA.

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Speaker 4: How do they find your DNA if you are not

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Speaker 4: in the system through this and ancestral DNA thing?

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Speaker 1: How does that work?

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Speaker 4: What needs to be available to find me through these

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Speaker 4: other people?

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Speaker 5: That's a great question, and so it's very rare that

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Speaker 5: we will find a close family member and certainly not

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Speaker 5: the suspect in our genetic genealogy databases. So what we're

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Speaker 5: looking for are people who share what we consider significant

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Speaker 5: amounts of DNA, but it can be less than one

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Speaker 5: percent of their DNA. If you share only one percent

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Speaker 5: of your DNA, then you're likely third cousins with someone,

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Speaker 5: which means you share your great great grandparents. And so

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Speaker 5: we get a whole list of people that share segments

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Speaker 5: of DNA with this unknown person we're trying to identify,

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Speaker 5: and we can reverse engineer their family tree by who

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Speaker 5: they're related to. So the only reason two people would

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Speaker 5: share these significant stretches of DNA across their genome is

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Speaker 5: if they have a common ancestor in their family tree.

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Speaker 5: They have to have inherited that DNA from someone back

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Speaker 5: in that tree, and so hopefully you'll get matches to

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Speaker 5: different lines, their mother's side, theirs, father's side. In some

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Speaker 5: cases you get all four grandparents' lines, and there's we

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Speaker 5: all have unique family trees except for our full siblings.

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Speaker 5: And so if you're able to put enough of those

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Speaker 5: ancestors back in that tree and piece it together, that's

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Speaker 5: going to narrow it down to just one immediate family.

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Speaker 5: Sometimes you can't get quite that far, so you might

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Speaker 5: have to look at first cousins if you can only

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Speaker 5: get to grandparents.

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Speaker 3: But that's how we do it.

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Speaker 5: We're not using close relatives. In most of these cases.

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Speaker 5: It's usually people who won't even know the suspect.

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Speaker 4: Okay, understood, You still need a name though, you need

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Speaker 4: somewhere to start. So they have to have something that

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Speaker 4: helped them develop an understanding.

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Speaker 1: Right, So we wouldn't. So that is our last question,

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Speaker 1: which is all right, So Chris Cuomo gets confused. He says, right,

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Speaker 1: but you have to have a name, right, you have

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Speaker 1: to have a name. Chris Cuomo not understand when she's

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Speaker 1: trying to explain how this works. And he says, gotcha, gotcha,

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Speaker 1: I get it, I get it, But you have to

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Speaker 1: have a name. Chris Cuomo is still thinking in the

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Speaker 1: old fashioned like fingerprint stuff. So if you're on a

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Speaker 1: crime scene and you collect a fingerprint, you have to

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Speaker 1: have that fingerprint in a database somewhere to match the

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Speaker 1: fingerprint to somebody. Cuomo seems to believe that's how this works.

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Speaker 1: It doesn't the way the genealogy works. And I took

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Speaker 1: for granted that people understood this. But when you've got

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Speaker 1: somebody like Cuomo, who I mean, guys, no dummy, he's

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Speaker 1: been around, he's been following stories for decades. The way

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Speaker 1: this works, and she put it. The expert there put

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Speaker 1: it this way is that you may only have a

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Speaker 1: connection with say a third cousin, so you're only sharing

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Speaker 1: one percent of DNA. If you have a DNA sample

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Speaker 1: at a crime scene and you run that through your

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Speaker 1: database and you find a sample in your database that

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Speaker 1: has a fifty percent match, I know that you're dealing

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Speaker 1: with a parent or a child of that of that suspect.

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Speaker 1: If it's say a quarter percent or twenty five percent match,

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Speaker 1: you're probably dealing with a grandparent. Now, these numbers can fluctuate,

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Speaker 1: and without getting into the various strains and the chromosomes

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Speaker 1: and the scent of morgans that they use to identify

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Speaker 1: all of these things, just basically, if you think about it,

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Speaker 1: you have fifty percent of your father's DNA, fifty percent

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Speaker 1: of your mother's DNA, all right, and then you would

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Speaker 1: have twenty five percent of your of each grandparent's DNA

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Speaker 1: that then gets passed down and passed down the higher

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Speaker 1: up you get. And you probably remember this from from

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Speaker 1: when you're younger, and somebody will say, well, I'm a quarter,

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Speaker 1: I'm a quarter Irish, or somebody will say I have

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Speaker 1: five percent Cherokee in me or something like that, right,

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Speaker 1: or I'm one sixteenth Cherokee. They'll say, that's kind of

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Speaker 1: how this works. But when you start getting out to

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Speaker 1: the cousins and you go, well, my second cousin has

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Speaker 1: got fifteen percent match, my third cousin might only have

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Speaker 1: a one percent match, meaning we have shared great grandparents.

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Speaker 1: So what they do is they go, okay, we found

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Speaker 1: our database, which might be whether they called jed match

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Speaker 1: or family tree or one of these others not ancestry

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Speaker 1: or my heritage. Those they don't share with the police,

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Speaker 1: but some of these others do for a cost. Every

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Speaker 1: time police want to run one of these tests, it's

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Speaker 1: about seven hundred bucks just for the police. You might

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Speaker 1: not have to pay that if you're just doing a

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Speaker 1: family tree match, right like you did your little sample,

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Speaker 1: and then you're gonna go check it out online. Yeah,

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Speaker 1: it doesn't cost you that much. Cost a police about

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Speaker 1: seven hundred bucks every time they want to do this.

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Speaker 1: So what they do is they go, Okay, well we

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Speaker 1: ran it through and here's what we had for a

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Speaker 1: database match. Of our sixty million people that are in

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Speaker 1: the database, we are able to find this one that

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Speaker 1: looks like it might be a third cousin. We found

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Speaker 1: this one that might be a second cousin, and we

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Speaker 1: found this one that might be an uncle. So what

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Speaker 1: they do then is triangulate, all right, who out there

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Speaker 1: would have this person as their third cousin, this person

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Speaker 1: is their second cousin, and that person is their uncle.

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Speaker 1: So by doing that they're able to then narrow it

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Speaker 1: down to a pair of siblings or if it's an

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Speaker 1: only child, you get it right, or maybe it's somebody

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Speaker 1: over you know, this cousin happens to fit that same formula,

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Speaker 1: but they're able to narrow it down so tightly based

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Speaker 1: on the information they have. Chris Cuomo seems to think

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Speaker 1: that they have to have somebody in a database that

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Speaker 1: they go looking for to see if it matches. That's

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Speaker 1: not how it works. Imagine if you had a fingerprint

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Speaker 1: from a crime scene and you ran that through a database,

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Speaker 1: and the database we're able to tell you, well, this

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Speaker 1: fingerprint is not a match for anybody, but it's a

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Speaker 1: ten percent match for this person, and it's a four

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Speaker 1: percent match for this person. And then you're able to

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Speaker 1: piece that together. You might find somebody else who potentially

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Speaker 1: could have that fingerprint, and then you go find that

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Speaker 1: person and get their fingerprints and see if it's a match.

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Speaker 1: This is where the genealogical DNA, the forensic genealogical DNA,

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Speaker 1: is revolutionary. It's a breakthrough, but it's also early on,

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Speaker 1: which means you're gonna have a lot of defense attorneys

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Speaker 1: that are looking for ways to poke holes in the science.

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Speaker 1: So far, they haven't been very successful in poking holes

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Speaker 1: because science doesn't care what they believe, all right, speaking

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Speaker 1: of law, gonna be some new ones here in twenty three.

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Speaker 1: Are you prepared? It's next Chris Maryland for John and

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Speaker 1: KENKF I am six forty, were live everywhere and your

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Speaker 1: heart ready to app Somebody send me a message about

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Speaker 1: the DNA, the genealogical DNA, and how they could be

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Speaker 1: screwed up. And they're right, it can be screwed up.

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Speaker 1: And I appreciate that. We were talking about the genealogical

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Speaker 1: DNA that has been used by forensic detectives. In the

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Speaker 1: case of the stabbing in Idaho. We first saw this used.

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Speaker 1: I believe it was the first time that it was

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Speaker 1: used when they caught the Golden State killer, remember that,

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Speaker 1: And they basically narrowed it down to two people, and

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Speaker 1: then they grabbed DNA from those two people. One guy

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Speaker 1: lived in Seattle and then one guy lived actually the

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Speaker 1: killer I believe was in Seattle. This was the guy

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Speaker 1: that had done stabbings and rapes and murders back in

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Speaker 1: the seventies and eighties, mostly in the secon Or mental

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Speaker 1: but I think he had a couple down here too.

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Speaker 1: They were able to basically use some of that old DNA,

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Speaker 1: run it through a genealogical database, find some ancillary matches,

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Speaker 1: and narrow it down basically triangulate who that might be.

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Speaker 1: And I made mention that defense attorneys are going to

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Speaker 1: question the science, and somebody asked, what you know, what

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Speaker 1: questions are there? It seems pretty obvious it's DNA. DNA

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Speaker 1: doesn't lie. You're right, and I appreciate the message. There

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Speaker 1: are some hang ups on this, and one of the

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Speaker 1: hang ups that genealogists are facing, not just forensic genealogists,

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Speaker 1: but there are a lot of questions. And you may

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Speaker 1: have heard stories of people that are finding out things

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Speaker 1: about their family that they otherwise didn't know. And sometimes

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Speaker 1: the DNA is coming back, and sometimes it's showing that

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Speaker 1: Grandpa isn't actually Grandpa, like the person you knew is

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Speaker 1: Grandpa isn't actually Grandpa. And then we find out, well,

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Speaker 1: Grandma may have had an affair at some point. This

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Speaker 1: sort of thing is coming out, right, So there are

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Speaker 1: some of those challenges. So suppose you start matching people

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Speaker 1: in this DNA sequence, but you don't have a direct match.

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Speaker 1: So in the case of our suspect in the Idaho killings,

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Speaker 1: let's suppose that they find like a second cousin, and

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Speaker 1: they find an aunt, and they find a first cousin somewhere,

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Speaker 1: and they start they start saying, well, this first cousin

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Speaker 1: and this aunt, all right, well those are close. Well

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Speaker 1: they're together, so they're related to this guy and this

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Speaker 1: guy him and his wife, they have a child, and

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Speaker 1: so that might be our killer, unless, of course, this

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Speaker 1: guy fathered a child outside of wedlock, right, and that

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Speaker 1: doesn't necessarily show up on doesn't show up where you

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Speaker 1: might think you know where, Uh oh, he had a

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Speaker 1: child out of wedlock. The girlfriend never listed the father

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Speaker 1: on the birth certificate or something of that nature. Right Now,

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Speaker 1: all of a sudden, you run into some dead end.

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Speaker 1: So that's some of the challenges. The other challenge that

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Speaker 1: you can run into is what they call endogamy, and

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Speaker 1: that's incest. So that'll throw your stats off too, Yeah,

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Speaker 1: mess everything up, Like, hmm, that's strange. We've got a

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Speaker 1: connection here and this should be this should be the grandparent,

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Speaker 1: but it also matches the same as the parent. How

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Speaker 1: does that happen? Well, you get it happens. And actually,

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Speaker 1: what genealogists are finding is two things. First, it happens

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Speaker 1: more often than people ever imagined. And second, a lot

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Speaker 1: in the South, yeah, but not all in the South,

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Speaker 1: believe it or not, Remote and cold climates are places

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Speaker 1: where they have a lot of that going on, especially historically,

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Speaker 1: especially when you were still in horse and buggy times.

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Speaker 1: You might have a village and there might be you know,

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Speaker 1: six or ten families living in the small village. Say

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Speaker 1: the pickens are a little slim. Might not be your

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Speaker 1: cousin or excuse me, might not be your sister, but

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Speaker 1: it might be a cousin that you end up with.

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Speaker 1: Happened a lot, happens a lot. So yeah, those are

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Speaker 1: some of the challenges that investigators are facing right now.

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Speaker 1: Has our all genealogists who are studying DNA and trying

434
00:23:20,480 --> 00:23:22,840
Speaker 1: to figure out how to use that as they create

435
00:23:22,880 --> 00:23:27,000
Speaker 1: family trees. But you know, the same challenges genealogists are

436
00:23:27,000 --> 00:23:31,400
Speaker 1: having can also be a challenge for those investigators. New

437
00:23:31,480 --> 00:23:34,800
Speaker 1: laws happening starting now, and there are a few that

438
00:23:34,840 --> 00:23:40,679
Speaker 1: really caught my eye. One of those and we debated

439
00:23:40,720 --> 00:23:42,000
Speaker 1: this a little bit. I was in for Tim Conway

440
00:23:42,040 --> 00:23:43,800
Speaker 1: Junior last week. We debated this a little bit on

441
00:23:43,840 --> 00:23:51,400
Speaker 1: the air, and that is the Equality and Pricing cal

442
00:23:51,440 --> 00:23:54,240
Speaker 1: Matters reports this Shoppers may have noticed that shampoos and

443
00:23:54,280 --> 00:23:57,720
Speaker 1: other personal care products marketed to women sometimes cost more

444
00:23:57,760 --> 00:24:02,760
Speaker 1: than very similar versions for men. I believe this to

445
00:24:02,760 --> 00:24:07,520
Speaker 1: be true, and I also buy women's shampoo and conditioner,

446
00:24:09,520 --> 00:24:13,640
Speaker 1: and I'm not ashamed. I don't know if it works

447
00:24:13,680 --> 00:24:15,800
Speaker 1: any better, but I do know that I believe it

448
00:24:15,840 --> 00:24:20,320
Speaker 1: works better. How does that look? If there's something that

449
00:24:20,520 --> 00:24:24,320
Speaker 1: it's kind of this running gag about men's soap, which

450
00:24:24,359 --> 00:24:26,440
Speaker 1: is like a five and one soap. It's like it's

451
00:24:26,440 --> 00:24:29,160
Speaker 1: a shampoo, a conditioner, a body wash, and a toothpaste

452
00:24:29,200 --> 00:24:32,159
Speaker 1: all in one. It's kind of a running gag just

453
00:24:32,160 --> 00:24:34,119
Speaker 1: how many things they can throw into that, you know,

454
00:24:34,160 --> 00:24:36,920
Speaker 1: that bottle. But there is this piece of me that goes,

455
00:24:37,400 --> 00:24:39,040
Speaker 1: is that really all that effective? Or is that just

456
00:24:39,119 --> 00:24:40,760
Speaker 1: gonna dry my hair out? So then I go and

457
00:24:40,760 --> 00:24:43,240
Speaker 1: I buy women's stuff, or I figure if my wife

458
00:24:43,320 --> 00:24:44,800
Speaker 1: is going to use my razor, I can use her

459
00:24:44,840 --> 00:24:47,520
Speaker 1: shampoo and conditioner. Then I find out that as much

460
00:24:47,560 --> 00:24:50,360
Speaker 1: as I thought my razors were incredibly expensive, her shampoo

461
00:24:50,359 --> 00:24:52,840
Speaker 1: and conditioner is about ten times more than my razors are.

462
00:24:53,080 --> 00:24:58,080
Speaker 1: So I do it discreetly. The new law in California

463
00:24:58,119 --> 00:25:00,000
Speaker 1: says that stores are going to be banned from charge

464
00:25:00,240 --> 00:25:05,040
Speaker 1: a different price based on gender. So what does that mean. Well,

465
00:25:05,080 --> 00:25:07,399
Speaker 1: they call it the pink tax. So let's suppose that

466
00:25:07,440 --> 00:25:12,000
Speaker 1: you have a panteen men's shampoo. I don't even know

467
00:25:12,000 --> 00:25:15,119
Speaker 1: if there was a panting men's shampoo, so it's just

468
00:25:15,200 --> 00:25:18,280
Speaker 1: my wild example here. But then you have a panting

469
00:25:18,320 --> 00:25:22,080
Speaker 1: women's shampoo. Well, if the women's shampoo is priced higher

470
00:25:22,119 --> 00:25:25,560
Speaker 1: than the men's shampoo, that would be a pink tax.

471
00:25:26,760 --> 00:25:29,639
Speaker 1: So you can't do that anymore. So the goal of

472
00:25:29,680 --> 00:25:32,320
Speaker 1: the law is to lower the prices of the women's

473
00:25:32,359 --> 00:25:35,240
Speaker 1: products so that they're not more expensive than the men's products.

474
00:25:36,520 --> 00:25:38,320
Speaker 1: In the end, I think what's going to happen is

475
00:25:38,359 --> 00:25:41,000
Speaker 1: the manufacturers are simply going to raise the price of

476
00:25:41,040 --> 00:25:44,040
Speaker 1: the men's products so that they match the women's products.

477
00:25:44,160 --> 00:25:46,280
Speaker 1: I don't think anybody's going to spend less money. They're

478
00:25:46,320 --> 00:25:47,800
Speaker 1: going to raise the price of the men's products. And

479
00:25:47,840 --> 00:25:50,760
Speaker 1: then I said, well inflation, Yeah, the prices had to come,

480
00:25:50,840 --> 00:25:55,800
Speaker 1: you know, inflation. That's how I see this playing out. Yeah,

481
00:25:55,840 --> 00:25:59,200
Speaker 1: you got rid of the pink tax. Now just everybody

482
00:25:59,200 --> 00:26:02,120
Speaker 1: pays it, not only on a few other things too,

483
00:26:02,720 --> 00:26:13,120
Speaker 1: including this law that allows you to sue anybody that

484
00:26:13,280 --> 00:26:16,280
Speaker 1: makes or sells illegal ghost guns or assault style weapons.

485
00:26:16,920 --> 00:26:20,000
Speaker 1: This is the law that California did almost as a

486
00:26:20,040 --> 00:26:24,320
Speaker 1: performative law in response to Texas abortion law. California was

487
00:26:24,320 --> 00:26:26,639
Speaker 1: trying to show how dumb the Texas abortion law that

488
00:26:26,720 --> 00:26:28,720
Speaker 1: SB eight was, that was the one that basically allowed

489
00:26:28,720 --> 00:26:32,159
Speaker 1: anybody to sue anybody for an abortion. So California said, well,

490
00:26:32,200 --> 00:26:33,800
Speaker 1: this is ridiculous. What if we were to do it

491
00:26:33,840 --> 00:26:37,640
Speaker 1: with guns, and so then they did, Well, that's going

492
00:26:37,640 --> 00:26:41,440
Speaker 1: into effect now with some caveats, it's not quite as

493
00:26:42,720 --> 00:26:48,520
Speaker 1: unconstitutionally as the Texas law, but still close. Also, you're

494
00:26:48,520 --> 00:26:51,639
Speaker 1: not supposed to in California now, you're not supposed to

495
00:26:53,280 --> 00:26:57,960
Speaker 1: spread misinformation, and the state Medical Board is supposed to

496
00:26:58,000 --> 00:27:01,720
Speaker 1: be able to punish physicians easier who deliberately spread misinformation.

497
00:27:01,840 --> 00:27:04,200
Speaker 1: Some doctors are assuing that to stop that law, calling

498
00:27:04,200 --> 00:27:06,159
Speaker 1: it a violation of their free speech rights. This came

499
00:27:06,200 --> 00:27:10,000
Speaker 1: to light, of course, during the era of COVID and

500
00:27:10,359 --> 00:27:12,199
Speaker 1: so many doctors that decided they were going to be

501
00:27:12,920 --> 00:27:17,120
Speaker 1: either have alternate viewpoints or alternate facts. Just a few

502
00:27:17,160 --> 00:27:18,760
Speaker 1: of these laws that we're going to have to start

503
00:27:18,760 --> 00:27:22,000
Speaker 1: facing as we ring in the new year. Well, it

504
00:27:22,000 --> 00:27:23,840
Speaker 1: wouldn't be a new year if we didn't have the

505
00:27:23,840 --> 00:27:26,560
Speaker 1: big rose Parade and the Rose Ball going on right now.

506
00:27:27,640 --> 00:27:30,679
Speaker 1: But the Rose Ball will never be the same again.

507
00:27:31,800 --> 00:27:33,560
Speaker 1: You're gonna find out why. And just to set Chris

508
00:27:33,600 --> 00:27:35,560
Speaker 1: merrill In for John and KMKA if I am six

509
00:27:35,680 --> 00:27:37,879
Speaker 1: forty live everywhere in your Heart radio at Chris merrill

510
00:27:37,920 --> 00:27:40,399
Speaker 1: In for the boys, we'll be back tomorrow. Mark, you

511
00:27:40,480 --> 00:27:44,200
Speaker 1: were talking about the parade and did you say celebrities

512
00:27:44,200 --> 00:27:45,080
Speaker 1: had to get out and walk.

513
00:27:45,440 --> 00:27:48,000
Speaker 6: Yeah, apparently one of the vintage cars broke down and

514
00:27:48,080 --> 00:27:49,800
Speaker 6: Denny trey Hoe and the mayor had to get out

515
00:27:49,800 --> 00:27:50,160
Speaker 6: and walk.

516
00:27:55,560 --> 00:27:58,680
Speaker 1: I shouldn't laugh, but and it's kind of funny, especially

517
00:27:58,680 --> 00:28:00,640
Speaker 1: because we've heard of them. I mean how many times

518
00:28:00,680 --> 00:28:02,399
Speaker 1: you know oftentimes there's people in the prey and you're like,

519
00:28:02,400 --> 00:28:05,040
Speaker 1: I don't know who that is, but no, I know

520
00:28:05,119 --> 00:28:10,320
Speaker 1: the mayor and Danny Trejoll. That's great. Just imagine people

521
00:28:10,359 --> 00:28:11,800
Speaker 1: like you and me standing by the side of the

522
00:28:11,840 --> 00:28:14,200
Speaker 1: road and be like, I think Machet Day's walking down

523
00:28:14,200 --> 00:28:15,920
Speaker 1: the street there he is.

524
00:28:16,359 --> 00:28:17,960
Speaker 6: Well, it would have been a lot funnier if it

525
00:28:17,960 --> 00:28:22,000
Speaker 6: had been a float, a big float that wire, because

526
00:28:22,040 --> 00:28:23,600
Speaker 6: who doesn't love animal house.

527
00:28:24,280 --> 00:28:29,439
Speaker 1: Yes, totally, So what do they do with the old vehicle?

528
00:28:29,480 --> 00:28:31,760
Speaker 1: Because if it stops, nobody can get around it. The

529
00:28:31,800 --> 00:28:34,280
Speaker 1: marching band isn't gonna walk over it, right, So they

530
00:28:34,320 --> 00:28:37,080
Speaker 1: got to like, do they have to just call people

531
00:28:37,119 --> 00:28:38,480
Speaker 1: in from the crowd to help push it off?

532
00:28:38,560 --> 00:28:38,760
Speaker 2: Yeah?

533
00:28:38,760 --> 00:28:39,760
Speaker 6: I just set it on fire.

534
00:28:40,680 --> 00:28:43,480
Speaker 1: Oh no, No, this is in Pasadena Market. You can't

535
00:28:43,480 --> 00:28:45,640
Speaker 1: get away with it there. Oh I could be wrong.

536
00:28:45,680 --> 00:28:48,360
Speaker 1: I was just guessing other parts of the other parts.

537
00:28:48,360 --> 00:28:50,200
Speaker 1: You can, uh, you can just set it on fire.

538
00:28:50,240 --> 00:28:52,600
Speaker 1: Nobody would notice the difference. But no, Pasadena, they would

539
00:28:52,600 --> 00:28:55,840
Speaker 1: notice that that would happen. I was fascinated. The OC

540
00:28:56,000 --> 00:28:58,440
Speaker 1: Register ran a story and you know why, why are

541
00:28:58,440 --> 00:29:03,560
Speaker 1: they running a story about the the Rose Pard. I

542
00:29:03,720 --> 00:29:05,720
Speaker 1: really don't know why, but they did, and I'm glad

543
00:29:05,760 --> 00:29:09,920
Speaker 1: they did because they talked about Peggy O'Leary. You may

544
00:29:09,960 --> 00:29:13,600
Speaker 1: not know who Peggy O'Leary is, but Peggy O'Leary is

545
00:29:13,680 --> 00:29:17,840
Speaker 1: this eighty year old woman who cares very deeply about

546
00:29:17,920 --> 00:29:22,840
Speaker 1: her community and keeping it clean. She is the queen

547
00:29:23,000 --> 00:29:28,920
Speaker 1: of Parade Pooper Scoopers. She is the longest serving volunteered

548
00:29:29,120 --> 00:29:32,400
Speaker 1: Pooper scooper. She said, I started on a whim one

549
00:29:32,480 --> 00:29:34,680
Speaker 1: year I watched the parade from the grandstands that observed

550
00:29:34,680 --> 00:29:37,680
Speaker 1: a small contingent of volunteers picking up after the horses,

551
00:29:37,680 --> 00:29:41,440
Speaker 1: and it looked like fun. Now this is what makes

552
00:29:41,440 --> 00:29:44,600
Speaker 1: her special. She sees people picking up scot and goes

553
00:29:44,880 --> 00:29:49,680
Speaker 1: that looks like fun. So indeed, she then volunteered. She

554
00:29:49,800 --> 00:29:52,200
Speaker 1: is not a member of the Tournament of Roses. She

555
00:29:52,440 --> 00:29:54,320
Speaker 1: signed that. She's a excuse me, not a member of

556
00:29:54,320 --> 00:29:56,560
Speaker 1: the Tournament of Roses White sup Brigade. But she still

557
00:29:56,600 --> 00:30:00,720
Speaker 1: wears like a white jumpsuit of some sort. She signed

558
00:30:00,760 --> 00:30:03,520
Speaker 1: up to volunteer in nineteen ninety and hasn't missed a

559
00:30:03,520 --> 00:30:07,720
Speaker 1: parade since. She just cleans up the poop at some point.

560
00:30:07,960 --> 00:30:12,600
Speaker 1: Don't you think you'd want a promotion? Nope, not Peggy.

561
00:30:12,760 --> 00:30:14,920
Speaker 1: She shows up the parade route at six am joins

562
00:30:14,920 --> 00:30:17,120
Speaker 1: her two person team, one wielding a push brew and

563
00:30:17,120 --> 00:30:20,080
Speaker 1: the other with a snow shovel. The station, excuse me.

564
00:30:20,120 --> 00:30:22,840
Speaker 1: Their station is the famed TV corner on Orange Grove Boulevard,

565
00:30:22,920 --> 00:30:25,360
Speaker 1: starting at Green Street and on Colorado Boulevard until the

566
00:30:25,360 --> 00:30:29,000
Speaker 1: Elks Lodge and then others, of course follow the horses

567
00:30:29,000 --> 00:30:32,160
Speaker 1: throughout the rest of the parade route, and she kind of.

568
00:30:32,720 --> 00:30:37,320
Speaker 1: She made herself a little crown of flowers, little floral

569
00:30:37,360 --> 00:30:41,040
Speaker 1: crown there, and then she's got matching gloves, and she says,

570
00:30:41,040 --> 00:30:42,560
Speaker 1: we just try to stay out of the way of horses,

571
00:30:42,560 --> 00:30:45,120
Speaker 1: the floats and the bands, and then have fun. I

572
00:30:45,160 --> 00:30:46,880
Speaker 1: don't know how much fun you have picking up poop,

573
00:30:46,920 --> 00:30:50,200
Speaker 1: but I'm so glad somebody is able to find some

574
00:30:50,280 --> 00:30:54,000
Speaker 1: enjoyment there. And I gotta tell you, she's eighty. She

575
00:30:54,080 --> 00:30:57,080
Speaker 1: looks like a very spry eighty year old. This lady,

576
00:30:58,240 --> 00:31:03,200
Speaker 1: quite frankly looks awesome. She taught at Belvedere Junior High

577
00:31:03,240 --> 00:31:07,080
Speaker 1: in East Los Angeles and South Pad South Pasadena Junior High.

578
00:31:07,160 --> 00:31:09,560
Speaker 1: Easy for me to say. Then she got her master's

579
00:31:09,600 --> 00:31:11,640
Speaker 1: degree and retired from the University of San Francisco as

580
00:31:11,680 --> 00:31:14,760
Speaker 1: a Senior Associate director of the Sports Management Masters Program.

581
00:31:15,680 --> 00:31:19,680
Speaker 1: Her husband is a fellow longtime South Pasadeen Pasadenan Passid

582
00:31:19,880 --> 00:31:24,080
Speaker 1: pasaden Ninan. Her son and her two granddaughters say they

583
00:31:24,080 --> 00:31:25,880
Speaker 1: get a kick out of all the New Year's activities

584
00:31:26,080 --> 00:31:32,320
Speaker 1: that pooper scooping included. I love it. Take that beach, boys,

585
00:31:32,320 --> 00:31:34,400
Speaker 1: there's your little old lady from Pasadena. She's out there

586
00:31:34,440 --> 00:31:38,920
Speaker 1: cleaning up horse crap. It's perfect. I kind of want

587
00:31:38,960 --> 00:31:42,840
Speaker 1: to adopt her to be my grandmother because you know,

588
00:31:42,880 --> 00:31:44,520
Speaker 1: I lost my grandmother a few years ago and I

589
00:31:44,560 --> 00:31:46,440
Speaker 1: need somebody cool and fun, and she would be a

590
00:31:46,480 --> 00:31:51,400
Speaker 1: perfect fit for that. The Rose Bowl game is going on. Incidentally,

591
00:31:51,960 --> 00:31:55,640
Speaker 1: it's Penn State Utah. It's tied at the half in

592
00:31:56,200 --> 00:32:00,720
Speaker 1: fourteen fourteen. Have you seen the crowd shots? No, no,

593
00:32:01,040 --> 00:32:02,880
Speaker 1: I just have it up. I don't have the full

594
00:32:02,920 --> 00:32:05,320
Speaker 1: game up here. I've just got the like the score.

595
00:32:05,680 --> 00:32:07,560
Speaker 1: So one of the crowd shots is it fulls and empty?

596
00:32:07,640 --> 00:32:08,400
Speaker 1: Was it's going on? Well?

597
00:32:08,440 --> 00:32:10,400
Speaker 6: The Rose bull is packed to the brim, but it

598
00:32:10,520 --> 00:32:14,600
Speaker 6: is seventy Utah fans twenty Penn State fans.

599
00:32:14,640 --> 00:32:16,520
Speaker 1: There's just a spattery of white.

600
00:32:18,200 --> 00:32:18,440
Speaker 2: Wow.

601
00:32:19,440 --> 00:32:22,520
Speaker 1: Say where they're all white? Yeah, it's a sea of red. Wow.

602
00:32:23,840 --> 00:32:26,440
Speaker 1: That's impressive. Good for Utah. Utah doesn't make it to

603
00:32:26,440 --> 00:32:28,640
Speaker 1: the Rose bul very often, do they. I think they've

604
00:32:28,640 --> 00:32:32,280
Speaker 1: only had just a couple of appearances. No, well, yeah,

605
00:32:32,320 --> 00:32:34,960
Speaker 1: because they they haven't always been Yeah, in the conference.

606
00:32:35,040 --> 00:32:37,040
Speaker 1: So the Pack, the Pac twelve, and the Big Ten

607
00:32:37,160 --> 00:32:38,600
Speaker 1: have always been the teams that have played in the

608
00:32:38,680 --> 00:32:42,760
Speaker 1: Rose Bowl. That has changed a few times, in recent years,

609
00:32:42,920 --> 00:32:45,240
Speaker 1: and Eric, feel free to correct me on this, but

610
00:32:45,280 --> 00:32:47,479
Speaker 1: I believe that's changed a few times in recent years

611
00:32:48,240 --> 00:32:53,320
Speaker 1: because of the playoffs. Yeah, yeah, just the way. So

612
00:32:53,400 --> 00:32:56,800
Speaker 1: if it's structured, if the if the if the Rose

613
00:32:56,800 --> 00:32:59,840
Speaker 1: Bowl is one of the playoff bowls, which it was

614
00:32:59,840 --> 00:33:02,600
Speaker 1: not this year. Correct, If it's one of the playoff bowls,

615
00:33:02,800 --> 00:33:05,920
Speaker 1: then it may be whoever is that that one in four,

616
00:33:06,000 --> 00:33:06,880
Speaker 1: two and three seed?

617
00:33:07,120 --> 00:33:10,080
Speaker 6: Right, it wouldn't be the traditional Big ten Pac twelve matchup.

618
00:33:11,120 --> 00:33:16,120
Speaker 1: Okay, that's what I thought. But now, well, by the way,

619
00:33:16,160 --> 00:33:18,080
Speaker 1: the first first Rose bul do you know who played

620
00:33:18,080 --> 00:33:22,480
Speaker 1: the first Rose Bull Michigan was my University of Michigan.

621
00:33:22,520 --> 00:33:26,760
Speaker 1: Wolverines go to the University of Michigan. No, my grandmother

622
00:33:26,840 --> 00:33:30,000
Speaker 1: went there back in nineteen forty nine for one semester.

623
00:33:30,320 --> 00:33:33,400
Speaker 1: That's the closest I ever got. But they beat the

624
00:33:33,440 --> 00:33:36,840
Speaker 1: hell out of Stanford really bad. In nineteen o two.

625
00:33:37,000 --> 00:33:41,240
Speaker 1: They beat the snot out of Stanford. It was something

626
00:33:41,320 --> 00:33:44,760
Speaker 1: ridiculous like fifty one to ten or something like that.

627
00:33:45,280 --> 00:33:56,560
Speaker 1: Oh yeah, here it is score forty nine nothing, yeah,

628
00:33:56,880 --> 00:34:01,320
Speaker 1: forty nine nothing. Yeah, Stanford quit the third quarter. They

629
00:34:01,360 --> 00:34:04,320
Speaker 1: just said that's it, We're out. So that's a fun fact.

630
00:34:04,440 --> 00:34:07,080
Speaker 1: The first game, first Rose Bowl, one of the teams

631
00:34:07,160 --> 00:34:11,359
Speaker 1: quit because they were getting slobberknocked. So then it went

632
00:34:11,360 --> 00:34:13,640
Speaker 1: on hiatus for another ten or twelve years or something,

633
00:34:13,640 --> 00:34:16,399
Speaker 1: and then they came back. But now I guess they're

634
00:34:16,480 --> 00:34:18,399
Speaker 1: changing it. So it's no longer going to be Big

635
00:34:18,440 --> 00:34:21,080
Speaker 1: ten versus Pac twelve. They're calling it the end of

636
00:34:21,080 --> 00:34:24,600
Speaker 1: an era. This is the last showdown between the traditional

637
00:34:25,160 --> 00:34:26,840
Speaker 1: Big Ten and Pac twelve. And it used to be

638
00:34:26,840 --> 00:34:29,239
Speaker 1: you had to be the conference champions. But then as

639
00:34:29,280 --> 00:34:33,000
Speaker 1: they start bringing in these different New York state bowls,

640
00:34:33,120 --> 00:34:36,799
Speaker 1: especially the College Football Playoffs, oftentimes you'll get the Big

641
00:34:36,880 --> 00:34:39,960
Speaker 1: Ten or the Pac twelve conference champion that will be

642
00:34:40,040 --> 00:34:42,640
Speaker 1: playing in a different bowl game rather than the Rose

643
00:34:42,680 --> 00:34:45,279
Speaker 1: Bowl as part of the College Football Playoffs. And with

644
00:34:45,320 --> 00:34:48,160
Speaker 1: the College Football Playoffs expanding, it looks like this is

645
00:34:48,200 --> 00:34:50,800
Speaker 1: going to be it as far as the Big twelve

646
00:34:51,440 --> 00:34:54,600
Speaker 1: Pac ten showdown, So don't expect to see those two

647
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Speaker 1: teams getting deferential treatment for the Rose Bowl in the future.

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Speaker 1: So there you go. All right, We'll give you an

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Speaker 1: update on the deputy that was shot in Riverside County

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Speaker 1: last week as the sheriff has sort of stirred up

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Speaker 1: the Hornets Nest and frankly, I think it needed to

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Speaker 1: be stirred. We'll talk about that here. And just to

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Speaker 1: set Chris Merril in for John and Ken k if

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Speaker 1: I AM six forty were live everywhere on your iHeartRadio

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Speaker 1: app